10 0 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662,663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687,688,689,690,691,692,693,694,695,696,697,698,699,700,701,702,703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721,722,723,724,725,726,727,728,729,730,731,732,733,734,735,736,737,738,739,740,741,742,743,744,745,746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774,775,776,777,778,779,780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800,801,802,803,804,805,806,807,808,809,810,811,812,813,814,815,816,817,818,819,820,821,822,823,824,825,826,827,828,829,830,831,832,833,834,835,836,837,838,839,840,841,842,843,844,845,846,847,848,849,850,851,852,853,854,855,856,857,858,859,860,861,862,863,864,865,866,867,868,869,870,871,872,873,874,875,876,877,878,879,880,881,882,883,884,885,886,887,888,889,890,891,892,893,894,895,896,897,898,899,900,901,902,903,904,905,906,907,908,909,910,911,912,913,914,915,916,917,918,919,920,921,922,923,924,925,926,927,928,929,930,931,932,933,934,935,936,937,938,939,940,941,942,943,944,945,946,947,948,949,950,951,952,953,954,955,956,957,958,959,960,961,962,963,964,965,966,967,968,969,970,971,972,973,974,975,976,977,978,979,980,981,982,983,984,985,986,987,988,989,990,991,992,993,994,995,996,997,998,999,1000] 1 1 1 2 0 0 1 <a href="http://en.opasnet.org/w/Image:Opasnet_base_connection.ANA">Wiki description</a> HP_Omistaja 9. maata 2008 10:42 jtue 15. jouta 2008 16:45 48,24 1,0,0,1,1,1,0,0,0,0 1,17,27,572,442,17 2,102,90,476,224 Arial, 15 0,Model Op_en2676,2,2,0,1,C:\DOCUME~1\jtue\LOCALS~1\Temp\Opasnet_base_connection.ANA 100,1,1,1,1,9,2970,2100,1,0 jtue 1. jouta 2008 10:57 48,24 112,112,1 48,24 1,139,81,509,560,17 jtue 18. heita 2008 10:14 48,24 392,448,1 48,24 1,539,22,650,613,17 This library contains functions to make various instances of concatenation more convenient. Concat3 thru Concat10 are generalizations of the built-in Concat function which concatenate from 3 to 10 arrays in a single call (while the built-in Concat concatenates two arrays). ConcatRows concatenates all the rows of a single array. David Kendall & Lonnie Chrisman Mon, Jan 26, 2004 8:49 AM Lonnie Wed, Sep 05, 2007 3:23 PM 48,24 72,424,1 68,20 1,0,0,1,1,1,0,0,0,0 1,39,36,798,452,23 (A1, A2, A3: ArrayType; I1, I2, I3, J: IndexType ) Concatenates three arrays, A1, A2, and A3. I1, I2, and I3 are the indexes that are joined; J is the index of the new array; J usually is the concatenation of I1, I2, and I3 Index I12 := Concat(I1,I2); Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, J ) 88,64,1 48,26 2,56,56,986,596 A1,A2,A3,I1,I2,I3,J (A1, A2, A3, A4: ArrayType; I1, I2, I3, I4, J: IndexType ) Concatenates four arrays, A1, A2, A3, and A4. I1, I2, I3, and I4 are the indexes that are joined; J is the index of the new array; J usually is the concatenation of I1, I2, I3, and I4. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, J); 192,64,1 48,24 2,30,30,986,596 A1,A2,A3,A4,I1,I2,I3,I4,J 0 (A1, A2, A3, A4, A5, A6, A7, A8, A9: ArrayType; I1, I2, I3, I4, I5, I6, I7, I8, I9, J: IndexType) Concatenates nine arrays, A1, ..., A9. I1, ..., I9 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I9. Index I12 := Concat(I1,I2); Index I123 := Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Index I1234567 := Concat(I123456, I7); Index I12345678 := Concat(I1234567, I8); Concat( Concat( Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, I1234567), A8, I1234567, I8, I12345678), A9, I12345678, I9, J); 88,232,1 48,24 2,27,120,469,638 A1,A2,A3,A4,A5,A6,A7,A8,A9,I1,I2,I3,I4,I5,I6,I7,I8,I9,J 0 (A1, A2, A3, A4, A5: ArrayType; I1, I2, I3, I4, I5, J: IndexType ) Concatenates five arrays, A1, ..., A5. I1, ..., I5 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I5. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, J); 88,120,1 48,24 2,160,160,986,596 A1,A2,A3,A4,A5,I1,I2,I3,I4,I5,J (A1, A2, A3, A4, A5, A6: ArrayType; I1, I2, I3, I4, I5, I6, J: IndexType ) Concatenates six arrays, A1, ..., A6. I1, ..., I6 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I6. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, J); 192,120,1 48,24 2,644,94,602,712 A1,A2,A3,A4,A5,A6,I1,I2,I3,I4,I5,I6,J 0 (A1, A2, A3, A4, A5, A6, A7: ArrayType; I1, I2, I3, I4, I5, I6, I7, J: IndexType ) Concatenates seven arrays, A1, ..., A7. I1, ..., I7 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I7. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, J); 88,176,1 48,24 2,580,98,551,565 A1,A2,A3,A4,A5,A6,A7,I1,I2,I3,I4,I5,I6,I7,J (A1, A2, A3, A4, A5, A6, A7, A8: ArrayType; I1, I2, I3, I4, I5, I6, I7, I8, J: IndexType ) Concatenates eight arrays, A1, ..., A8. I1, ..., I8 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I8. Index I12 := Concat(I1,I2); Index I123:= Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Index I1234567 := Concat(I123456, I7); Concat( Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, I1234567), A8, I1234567, I8, J); 192,176,1 48,24 2,12,98,561,737 A1,A2,A3,A4,A5,A6,A7,A8,I1,I2,I3,I4,I5,I6,I7,I8,J 0 (A1, A2, A3, A4, A5, A6, A7, A8, A9, A10: ArrayType; I1, I2, I3, I4, I5, I6, I7, I8, I9, I10, J: IndexType) Concatenates ten arrays, A1, ..., A10. I1, ..., I10 are the indexes joined; J is the index of the new array; J usually is the concatenation of I1, ..., I10. Index I12 := Concat(I1,I2); Index I123 := Concat(I12, I3); Index I1234 := Concat(I123, I4); Index I12345 := Concat(I1234, I5); Index I123456 := Concat(I12345, I6); Index I1234567 := Concat(I123456, I7); Index I12345678 := Concat(I1234567, I8); Index I123456789 := Concat(I12345678, I9); Concat( Concat( Concat( Concat( Concat( Concat( Concat( Concat( Concat( A1,A2,I1,I2,I12 ), A3, I12, I3, I123), A4, I123, I4, I1234), A5, I1234, I5, I12345), A6, I12345, I6, I123456), A7, I123456, I7, I1234567), A8, I1234567, I8, I12345678), A9, I12345678, I9, I123456789), A10, I123456789, I10, J); 192,232,1 48,24 2,542,93,632,744 A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,I1,I2,I3,I4,I5,I6,I7,I8,I9,I10,J 0 (A : ArrayType ; RowIndex,ColIndex,ResultIndex : IndexType) Takes an array, A indexed by RowIndex & ColIndex, and concatenates each row, henceforth flattening the array by one dimension. The result is indexed by ResultIndex, which must be an index with size(RowIndex) * size(ColIndex) elements. index L := [ identifier of RowIndex, identifier of ColIndex, "val"]; slice(Mdarraytotable(A,ResultIndex,L),L,3) 320,64,1 64,24 2,30,320,478,348 A,RowIndex,ColIndex,ResultIndex Lonnie Thu, Sep 11, 1997 2:15 PM Lonnie Tue, Feb 05, 2008 10:03 AM 48,24 64,376,1 52,20 1,1,1,1,1,1,0,0,0,0 1,20,272,499,497,17 Arial, 13 (A:ArrayType;I:IndexType;L:IndexType;row;dbTableName) Generates the SQL "INSERT INTO" statement for one line of table A. A is a 2-D table indexed by rows I and columns L. L's domain serves as the column names in the database table. dbTableName is the name of the table in the database. The result begins with two semi-colons, since it will be used with an SQL statement preceeding it. 29.8.2008 Jouni Tuomisto I added the parameter IGNORE because it ignores rows that would cause duplicate-key violations. This way, there is no need to check for e.g. existing locations of new indices. (';;INSERT IGNORE INTO ' & dbTableName & '(' & JoinText(L,L,',') & ') VALUES (' & Vallist(A[I=row],L)) & ')' 184,32,1 52,24 2,41,136,487,469 A,I,L,row,dbTableName (V:ArrayType;I:IndexType) Takes a list of values, and returns a string which the concatenation of each value, separated by commas, and with each value quoted. JoinText( '''' & V & '''', I, ',') 72,32,0 52,24 V,I 1,F,4,14,0,0 (Tabl:ArrayType;RowIndex:IndexType;LabelIndex:IndexType;dbTableName) Returns the SQL that will write the table to the database table. This can be used as the second argument to DBWrite. This SQL statement replaces the entire contents of an existing table with the new data. 'DELETE FROM '& Dbtablename & JoinText(Insertrecsql(Tabl, Rowindex, Labelindex, Rowindex, Dbtablename),RowIndex) 328,32,1 88,24 2,728,341,510,476 Tabl,RowIndex,LabelIndex,dbTableName (Tabl:ArrayType;RowIndex:IndexType;LabelIndex:IndexType;dbTableName) Returns the SQL that will write the table to the database table. This can be used as the second argument to DBWrite. This SQL statement replaces the entire contents of an existing table with the new data. JoinText(Insertrecsql(Tabl, Rowindex, Labelindex, Rowindex, Dbtablename),RowIndex) 328,88,1 88,24 2,559,127,510,476 Tabl,RowIndex,LabelIndex,dbTableName index j:= ['id','Obj_id_d','Location','Description']; array(j,[ cardinals[table1='Loc']+@locations.i, Locations[.j='Dim_id'], Locations[.j='Location'], Locations[.j='Description']]) 320,160,1 48,16 2,810,147,476,224 2,40,50,649,245,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] 1) Takes the first index and calculates the parameters for it. 2) Does the same for all other indices and concatenates the parameter results. 3) All parameters are lumped into a single array. 4) A complicated way to take into account whether there are any new indices. This is done because if then else cannot be used for these arrays in a straightforward way (the condition cannot have critical dimensions). If-then-else is replaced with conditional slice. 5) Finally, extra rows are removed. 9.10.2008 Jouni Tuomisto It seems that this part 4) could be simpler in the same way as e.g. Variables_missing. However, I don't want to put time on this issue, because this seems to work. Today I also added local variable f to make it possible to add descriptions about locations into the Result database. The database has been changed accordingly a few days ago. Note that this node only seems to work when there is only one new index at a time. Therefore, if you want to use the module, create the indices one by one, add the structure to the database, and only then define your actual variables of interest. var a:= if objects[.j='Typ_id']= 6 then 1 else 0; index k:= subset(a); a:= objects[object3=k]; var b:= [0]; var c:= [0]; var e:= [0]; var f:= [0]; var x:= 1; while x<=size(k) do ( var d:= evaluate(slice(k,x)); b:= concat(b,d); c:= concat(c,(if d=0 then slice(k,x) else slice(k,x))); e:= concat(e,1..size(d)); var g:= evaluate(a[@k=x, .j='Description node']); g:= if size(g) = size(d) then g else (if d=0 then g else g); f:= concat(f, g); x:= x+1); index i:= 1..size(b); b:= slice(b,i)&''; c:= slice(c,i); e:= slice(e,i); f:= slice(f,i); var d:= if ind[.j='Iident'] = c then ind[.j='Dident'] else ''; d:= jointext(d,d.i); index j:= ['Dim_ident','Dim_id','Location','Loc_id','Ind_ident','Ind_id','Row_number', 'Description']; array(j,[d, findid(d,obj,'Ident'), b, cardinals[table1='Loc']+i, c, findid(c,Obj,'Ident'), e, f]) 200,192,1 48,16 2,730,35,521,557 2,189,535,886,232,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] ['','','','','','','','','',''] [Inp_ind,1,Indices_missing,1,Self,1] ICD-10 ['Cardiopulmonary','Lung cancer','All others','All causes'] 304,432,1 48,22 ['Cardiopulmonary','Lung cancer','All others','All causes'] ['Harjavalta'] 296,464,1 64,12 2,192,588,476,224 kg <a href="http://en.opasnet.org/w/index.php?title=rdb&curid=2693">Wiki description</a> array(Op_en2665,uniform(100,110)) 304,384,1 48,24 2,93,226,539,360,0,MIDM [] [0,1,0,1] (a:prob) index statistics:= ['Mean','SD','0.01','0.025','0.05','0.25','0.5 (Median)','0.75','0.95','0.975','0.99']; a:= array(statistics,[mean(a), sdeviation(a), getfract(a,0.01), getfract(a,0.025), getfract(a,0.05), getfract(a,0.25), getfract(a,0.5), getfract(a,0.75), getfract(a,0.95), getfract(a,0.975), getfract(a,0.99)]); round(a*10)/10&'' 440,384,1 48,12 a (table:texttype) Brings the largest id number from the table defined in the parameter. index i:= DBquery(odbc,' SELECT MAX(id) AS id FROM '&table&' '); index j:= dblabels(i); max(max(DBTable(i, j ),i),j) 440,448,1 48,12 2,102,90,476,331 39325,65535,39321 table ['Obj','Res','Loc','Locres','Roww','Sett','Item','Sam'] 200,64,1 48,13 2,15,594,158,227,0,MIDM ['Obj','Res','Loc','Locres','Roww','Sett','Item','Sam'] Table(Table1)( 113,1475,671,1072,659,34,34,736.942K ) 200,32,1 48,24 2,193,270,416,303,0,MIDM 2,472,313,416,303,0,MIDM 39325,65535,39321 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 1) Finds information for other parameters. 2) Adjusts the information about the Run. There is no need to search for existing objects, because the name is unique. Thus, all additions just are ignored. var a:= object3; var b:= findintext(wikis,Identifier of a); b:= if b=0 then 0 else b+textlength(Wikis); var c:= sum(if b=0 then 0 else @wikis,wikis); b:= sum(b,wikis); b:= if b = 0 then 0 else selecttext(a,b); var d:= findintext(Object_types,Class of a); d:= sum(if d=0 then 0 else indexvalue(object_types),object_types); Index iobj:= ['id','Ident','Name','Unit','Typ_id','Page','Wik_id']; a:= array(iobj,[ Cardinals[table1='Obj']+@object3, Identifier of a, Title of a, Units of a, d, b, c]); Index j:= concat(iobj,add_info); a:= concat(a, Object_info, iobj, add_info, j); var e:= Object3; e:= Description of e; e:= if findintext('Describe the run in this node.',e)=1 then 1 else 0; a:= if j = 'Name' and e=1 then a & ' Edition: Analytica '&Analyticaedition&', Platform: '&Analyticaplatform&', Version: '&Analyticaversion else a; a:= if j = 'Typ_id' and e=1 then 9 else a; a:= if j = 'Begin' and e=1 then datepart(today(),'Y')&'-'&datepart(today(),'M')&'-'&datepart(today(),'D') else a; a:= if j = 'Who' and e=1 then Who_ran_the_model else a 200,104,1 48,16 2,41,46,581,571 2,22,596,1214,178,0,MIDM [Sys_localindex('J'),Object3] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [0,1,1,0] [Object_types,3,Object1,1,Iobj,1] 'Jouni' 56,104,1 48,24 [Formnode Who_ran_the_model1] 52425,39321,65535 Add the Dimension id for each index. Table(Add_info,Object3)( 0,0,0,34, 1,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,'Descr_op_en2665' ) 56,152,1 48,20 2,140,217,476,224 2,437,196,664,303,0,MIDM [Formnode Object_info1] 52425,39321,65535 [Add_info,Object3] [Add_info,Object3] ['Dim #','Probabilistic?','Who','Begin','Url','Description node'] 56,184,1 48,12 ['Dim #','Probabilistic?','Who','Begin','Url','Description node'] getfract forces the effect of sample() away, while mid doesn't 1) Does the process for each variable one at a time. Only the deterministic information about variables are considered (therefore getfract). 2) Gets the samplesize (0 if deterministic) for the variable. 3) Gets the Var_id for the variable. 4) Flattens the array. The value is discarded and only the location info is kept. Location is changed into text because that is the format in the RDB. 5) Gets the Dimension (Dim_id) for each index of h. 6) Gets the Location (Loc_id) for each cell in a, given the dimension and location. 7) Gets the Ind_id for each Index listed in h. 8) Flattens the array a. 9) Concatenates the results of all variables. 10) Makes Row the index of the implicit index. var output=0; var e:= Cardinals[table1='Res']; var f:= Cardinals[table1='Locres']; index j:= ['Locres_id','Location','Res_id','Roww_id','Vident','Obj_id_v','Obj_id_r','Mean','N']; var o:= if Objects [.j='Typ_id'] = 1 then 1 else 0; index k:= subset(o); o:= objects[object3=k]; var x:= 1; while x<= size(k) do ( var c:= slice(o,k,x); var a:= mean(sample(evaluate(c[.j='Ident']))); index h:= indexnames(a); index L:= concat(h,['Value']); index res_id:= (1..size(a))+e; index locres_id= (1..size(a)*size(h))+f; e:= e+size(res_id); f:= f+size(locres); a:= mdarraytotable(a,res_id,L); var mean1:= a[L='Value']; a:= a[L=h]&''; var g:= findid(h, ind, 'Iident')&'+'&findid(a, Loc, 'Location'); var m:= if Roww.j='Obj_id_i' then Roww&'+'&Roww[.j='Loc_id'] else Roww; var n:= if objects[.j='Typ_id']= 9 then objects[.j='Ident'] else ''; n:= jointext(n,object3); a:= array(j,[ locres_id, a, res_id, findid(g, m, 'Obj_id_i'), c[.j='Ident'], findid(c[.j='Ident'], Obj, 'Ident'), findid(n, Obj, 'Ident'), mean1, if c[.j='Probabilistic?']=0 then 0 else samplesize]); a:= concatrows(a,h,res_id,locres_id); output:= if x= 1 then a else for y:= j do ( concat(output[j=y],a[j=y]) ); x:= x+1); index i:= 1..size(output)/size(j); for y:= j do (slice(output[j=y],i)) 200,240,1 48,16 2,731,14,518,798 2,15,251,554,328,0,MIDM [Sys_localindex('I'),Sys_localindex('J')] [] [Sys_localindex('H'),3,Sys_localindex('I'),1,Sys_localindex('ENDSCEN'),1] (in, table; cond:texttype) This function gets an id from an Opasnet Base table. in: the variable for which the id is needed. table: the Opasnet Base table from where the id is brought. The table must be indexed by j (field) and i (row). comp: the name of the field that is compared with in. Comp must be text. var id:= if in = table[.j=cond] then table[.j='id'] else 0; sum(id, table.i) 440,416,1 48,12 2,589,70,476,224 in,table,cond index j:= ['id','Res_id','Roww_id']; inp_locres[.j=j] 320,240,1 52,16 2,790,83,476,224 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] [] index j:= ['id','Obj_id_v','Obj_id_r','Mean','N']; var a:= inp_locres[.j=j]; index i:= unique(a,a.i); a[.i=i] 320,272,1 48,16 2,807,62,476,224 2,28,38,416,303,0,MIDM 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] [] Table(Self)( 'Op_en','Op_fi','Heande','En','Fi','Erac','Beneris','Intarese','Piltti','Kantiva','Bioher','Heimtsa') [1,2,3,4,5,8,9,10,11,13,14,15] 56,64,1 48,12 65535,52427,65534 [Object2,Self] Table(Self)( 'Variable','Dimension','Method','Model','Class','Index','Nugget','Encyclopedia article','Run','Chance','Decision','Objective','Constant','Determ') [1,2,3,4,5,6,7,8,9,1,1,1,1,1] 56,32,1 48,20 2,674,337,416,303,0,MIDM 2,0,262,416,303,0,MIDM 65535,52427,65534 This makes a list of all indices that are used by the variables in Object1. var a:= indexnames(evaluate(Objects_excl_indices)); a:= concat(Objects_excl_indices,a); index i:= a; a:= slice(a,@i); a:= if a='Object1' or a='Objects_excl_indices' then 0 else 1; subset(a) 200,128,1 48,13 2,102,90,476,464 2,32,349,416,303,0,MIDM [Op_en2665,Objects_excl_indices] ['Op_en2693','Op_en2676','Op_en2694','Op_en2665'] index j:= ['id','Obj_id_i','Roww','Loc_id']; array(j,[ cardinals[table1='Roww']+@locations.i, Locations[.j='Ind_id'], Locations[.j='Row_number'], Locations[.j='Loc_id']]) ['item 1'] 320,192,1 48,16 2,791,59,475,327 2,250,441,416,303,0,MIDM 2,782,442,448,347,0,MIDM 65535,45873,39321 [Self] [Sys_localindex('J'),Sys_localindex('I')] ['item 1'] ktluser 10. Decta 2008 13:16 48,24 536,288,1 48,24 1,0,1,1,1,1,0,,0, 1,669,462,550,300,17 273 96,36,1 48,12 1,1,0,1,1,1,0,0,0,0 samplesize 96,40,1 48,16 [Formnode Size_of_sample1] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 (table; label:texttype) var a:= dimensions[.j='Dim_name']; a:= ','&jointext(a,a.i,',')&','; var e:= new_index_info[iind='Dim_name']&'' ; index k:= concat(['All dimensions have been defined already'],e); a:= if findintext(','&k&',',a)>0 then 0 else 1; a:= if sum(a,a.k)>1 and @k=1 then 0 else a; subset(a) 96,36,1 48,12 2,102,90,492,374 table,label 1) The process is done for each variable one at a time (this is indexed by x). 2) The variable is given index runn which is equal to run if probabilistic and 0 if not. 3) The array is flattened first to 2-D, the value only is kept, added with sample and result_id. 4) Variables are concatenated to each other. 5) Index i is made the index of the implicit index. var output=0; var e:= Cardinals[table1='Res']; var f:= Cardinals[table1='Sam']; index j:= ['id','Res_id','Descr_id','Sample','Result']; var o:= if Objects [.j='Typ_id'] = 1 then 1 else 0; index k:= subset(o); o:= objects[object3=k]; var x:= 1; var temp:= 0; while x<= size(k) do ( var c:= slice(o,k,x); var a:= sample(evaluate(c[.j='Ident'])); index h:= indexnames(a); index L:= concat(h,['Value']); index runn:= if c[.j='Probabilistic?']=1 then copyindex(run) else [0]; index res_id:= (1..size(a))+e; index sam_id:= (1..size(res_id)*size(runn))+f; e:= e+size(res_id); f:= f+size(sam_id); a:= mdarraytotable(a,res_id,L)[.L='Value']; a:= if c[.j='Probabilistic?']=1 then a[run=runn] else (if runn=0 then mean(a) else mean(a)); a:= array(j,[0, res_id, 0, runn, a]); a:= concatrows(a,res_id,runn,sam_id); a:= if a.j='id' then sam_id else a; output:= if x= 1 then a else for y:= j do ( concat(output[j=y],a[j=y]) ); x:= x+1); index i:= 1..size(output)/size(j); for y:= j do (slice(output[j=y],i)) 456,128,1 48,16 2,713,0,528,795 2,12,249,625,356,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 [0,0,0,0] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24] [Sys_localindex('RUNN'),4,Sys_localindex('RES_ID'),1,Sys_localindex('J'),1] Table(Self,Vari)( 'H2556',0 ) ['item 1'] 96,121,1 48,22 1,1,1,1,1,1,0,0,0,0 2,102,90,476,481 2,219,290,416,482,0,MIDM 2,663,308,420,375,0,MIDM 52425,39321,65535 [Vari,Self] [Vari,Self] [1,1,1,0] [Sys_localindex('I'), 1, Sys_localindex('F'), 1, Sys_localindex('G'), 1 ] ['Dim_name','Description node'] 96,78,1 48,13 ['Dim_name','Description node'] 1) a defines the dim_id. 2) b defines the loc_id. If the location exists already, this loc_id is used; otherwise, a sequence of numbers is used. 3) information is written into the right table format. var a:= if Locations[.j='Dim_name'] = Dim[.j='Dim_name'] then Dim[.j='Dim_id'] else 0; a:= max(a,Dim.i); var b:= if Locations[.j='Dim_name'] = loc[.j='Dim_name'] and Locations[.j='Location'] = loc[.j='Location'] then loc[.j='Loc_id'] else 0; b:= max(b,loc.i); b:= if b>0 then b else cardinals[table1='Loc']+@Locations.i; index j:= ['Loc_id','Dim_id','Location','Description']; a:= array(j,[b, a, Locations[.j='Location'], Locations[.j='Description']]); ['item 1','item 2','item 3','item 4','item 5','item 6','item 7','item 8','item 9','item 10','item 11','item 12','item 13','item 14','item 15','item 16','item 17','item 18','item 19','item 20','item 21'] 440,80,1 48,16 2,779,65,476,551 2,319,169,421,433,0,MIDM 2,18,51,780,757,0,MIDM 19661,48336,65535 [Self] [Sys_localindex('J'),Sys_localindex('I')] ['item 1','item 2','item 3','item 4','item 5','item 6','item 7','item 8','item 9','item 10','item 11','item 12','item 13','item 14','item 15','item 16','item 17','item 18','item 19','item 20','item 21'] [Sys_localindex('J'),3,Sys_localindex('K'),1] ['Var_name','Probabilistic?'] 96,152,1 48,12 ['Var_name','Probabilistic?'] This node checks the indices listed in variables in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. For syntax help, see Variables_missing. var a:= if Objects[.j='Typ_id']=6 then 1 else 0; a:= subset(a); object3[object3=a] 96,110,1 48,22 1,1,1,1,1,1,0,0,0,0 2,531,26,493,499 2,505,449,490,264,0,MIDM 39321,39325,65535 [Self,Vari] ['All indices have been defined already'] Table(Iind,Self)( 0, 0 ) ['item 1'] 432,32,1 48,22 2,337,297,476,224 2,34,74,606,204,0,MIDM 2,490,553,520,238,0,MIDM 52425,39321,65535 [Iind,Self] [Iind,Self] This lists all indices that are used by all of the variables that are to be inserted into the result database. This is based on an assumption that the index Ind_var is always the outermost index and therefore last. Then it is sliced away. reset; var a:= Variables_to_be_save[vari='Var_name']; a:= indexnames(evaluate(a)); index i:= 1..size(a); a:= slice(a,i); a:= if a= 'Variables_to_be_save' then 0 else a; a[i=subset(a)] 336,144,1 48,16 2,32,156,476,566 2,533,234,416,303,0,MIDM [Sys_localindex('J'),Self] ['Age1','Municipality_fin1','Inp_var'] [Inp_ind,1,Indices_missing,1,Self,1] 1) Takes the first index and calculates the parameters for it. 2) Does the same for all other indices and concatenates the parameter results. 3) All parameters are lumped into a single array. 4) A complicated way to take into account whether there are any new indices. This is done because if then else cannot be used for these arrays in a straightforward way (the condition cannot have critical dimensions). If-then-else is replaced with conditional slice. 5) Finally, extra rows are removed. 9.10.2008 Jouni Tuomisto It seems that this part 4) could be simpler in the same way as e.g. Variables_missing. However, I don't want to put time on this issue, because this seems to work. Today I also added local variable f to make it possible to add descriptions about locations into the Result database. The database has been changed accordingly a few days ago. Note that this node only seems to work when there is only one new index at a time. Therefore, if you want to use the module, create the indices one by one, add the structure to the database, and only then define your actual variables of interest. var a:= indices_used; var b:= evaluate(a[@.indices_used=1]); var c:= if b=0 then a[@.indices_used=1] else a[@.indices_used=1]; var e:= 1..size(b); var f:= new_index_info[indices_missing=a[@.indices_used=1]]; f:= evaluate(f[iind='Description node']); f:= if size(f) = size(b) then f else (if b=0 then f else f); var x:= 2; while x<=size(a) do ( var d:= evaluate(a[@.indices_used=x]); b:= concat(b,d); c:= concat(c,(if d=0 then a[@.indices_used=x] else a[@.indices_used=x])); e:= concat(e,1..size(d)); var g:= new_index_info[indices_missing=a[@.indices_used=1]]; g:= evaluate(g[iind='Description node']); g:= if size(g) = size(b) then g else (if b=0 then g else g); f:= concat(f, g); x:= x+1); index k:= 1..size(b); b:= slice(b,k); c:= slice(c,k); e:= slice(e,k); f:= slice(f,k); var d:= New_index_info[iind='Dim_name',indices_missing=c]; d:= if d=null then 0 else d; index j:= ['Dim_name','Location','Ind_name','Row_number', 'Description']; a:= array(j,[d,b&'',c,e,f]); index L:= 1..size(k)+1; index m:= ['All locations have been defined already']; a:= concat(a,m,k,m,L); index g:= if slice(indices_missing,1) = 'All indices have been defined already' then size(k)+1..size(k)+1 else k; a:= slice(a,L,g); a:= a[g=subset(a[.j='Dim_name'])]; index i:= 1..(size(a)/size(j)); for h:= j do slice(a[j=h],i) 328,104,1 48,16 2,60,14,521,658 2,413,120,778,708,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] ['','','','','','','','','',''] [Inp_ind,1,Indices_missing,1,Self,1] var a:= findid(Objects[.j='Dim_name'], Dim, 'Dim_name'); index j:= ['Ind_id','Ind_name','Dim_id']; array(j,[ Card_obj+@Indices_missing, indices_missing, a]) ['item 1'] 216,56,1 48,16 2,79,239,502,318 2,197,430,416,303,0,MIDM 2,616,387,416,303,0,MIDM 19661,48336,65535 [Iind,Self] [Indices_missing,Sys_localindex('J')] ['item 1'] [Indices_missing,1,Sys_localindex('CO'),1,Sys_localindex('I'),1] Reset; index a:= DBquery(odbc,' SELECT id FROM Obj '); index b:= dblabels(a); max(max(DBTable(a, b ),a),b) 328,64,1 48,16 39325,65535,39321 [] Reset; index a:= DBquery('DSN=resultdatabase','SELECT Loc_id FROM `Location` '); index b:= ['Loc_id']; max(max(DBTable(a, b ),a),b) 328,24,1 48,16 39325,65535,39321 This makes a list of all indices that are used by the variables in Object1. var a:= indexnames(evaluate(Objects_excl_indices)); a:= if a='Objects_excl_indices' then 0 else 1; a:= subset(a); a:= concat(Objects_excl_indices,a); index i:= 1..size(a); a:= slice(a,i); a:= if a='Object1' then 0 else a; a[i=subset(a)] 216,16,1 48,12 2,302,365,416,303,0,MIDM [Op_en2665,Objects_excl_indices] ['Testvariable','Op_fi2345','Op_en2676','Run_info1','Age1'] 1) Takes the first index and calculates the parameters for it. 2) Does the same for all other indices and concatenates the parameter results. 3) All parameters are lumped into a single array. 4) A complicated way to take into account whether there are any new indices. This is done because if then else cannot be used for these arrays in a straightforward way (the condition cannot have critical dimensions). If-then-else is replaced with conditional slice. 5) Finally, extra rows are removed. 9.10.2008 Jouni Tuomisto It seems that this part 4) could be simpler in the same way as e.g. Variables_missing. However, I don't want to put time on this issue, because this seems to work. Today I also added local variable f to make it possible to add descriptions about locations into the Result database. The database has been changed accordingly a few days ago. Note that this node only seems to work when there is only one new index at a time. Therefore, if you want to use the module, create the indices one by one, add the structure to the database, and only then define your actual variables of interest. var a:= indices_used; var b:= evaluate(a[@.indices_used=1]); var c:= if b=0 then a[@.indices_used=1] else a[@.indices_used=1]; var e:= 1..size(b); var f:= new_index_info[indices_missing=a[@.indices_used=1]]; f:= evaluate(f[iind='Description node']); f:= if size(f) = size(b) then f else (if b=0 then f else f); var x:= 2; while x<=size(a) do ( var d:= evaluate(a[@.indices_used=x]); b:= concat(b,d); c:= concat(c,(if d=0 then a[@.indices_used=x] else a[@.indices_used=x])); e:= concat(e,1..size(d)); var g:= new_index_info[indices_missing=a[@.indices_used=1]]; g:= evaluate(g[iind='Description node']); g:= if size(g) = size(b) then g else (if b=0 then g else g); f:= concat(f, g); x:= x+1); index k:= 1..size(b); b:= slice(b,k); c:= slice(c,k); e:= slice(e,k); f:= slice(f,k); var d:= New_index_info[iind='Dim_name',indices_missing=c]; d:= if d=null then 0 else d; index j:= ['Dim_name','Location','Ind_name','Row_number', 'Description']; a:= array(j,[d,b&'',c,e,f]); index L:= 1..size(k)+1; index m:= ['All locations have been defined already']; a:= concat(a,m,k,m,L); index g:= if slice(indices_missing,1) = 'All indices have been defined already' then size(k)+1..size(k)+1 else k; a:= slice(a,L,g); a:= a[g=subset(a[.j='Dim_name'])]; index i:= 1..(size(a)/size(j)); for h:= j do slice(a[j=h],i) 216,104,1 48,16 2,728,38,521,557 2,413,120,778,708,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] ['','','','','','','','','',''] [Inp_ind,1,Indices_missing,1,Self,1] Ei toimi: new locs locs 96,53,-1 48,29 96,48,1 48,24 2,102,90,476,378 getfract forces the effect of sample() away, while mid doesn't 1) Does the process for each variable one at a time. Only the deterministic information about variables are considered (therefore getfract). 2) Gets the samplesize (0 if deterministic) for the variable. 3) Gets the Var_id for the variable. 4) Flattens the array. The value is discarded and only the location info is kept. Location is changed into text because that is the format in the RDB. 5) Gets the Dimension (Dim_id) for each index of h. 6) Gets the Location (Loc_id) for each cell in a, given the dimension and location. 7) Gets the Ind_id for each Index listed in h. 8) Flattens the array a. 9) Concatenates the results of all variables. 10) Makes Row the index of the implicit index. var output=0; var e:= Cardinals[table1='Res']; var f:= Cardinals[table1='Locres']; index j:= ['id','Res_id','Roww_id','Obj_id_v','Obj_id_r','Mean','N']; var o:= if Objects [.j='Typ_id'] = 1 then 1 else 0; index k:= subset(o); o:= objects[object3=k]; var x:= 1; var temp:= 0; var c:= slice(o,k,x); var a:= mean(sample(evaluate(c[.j='Ident']))); index h:= indexnames(a); index L:= concat(h,['Value']); index res_id:= (1..size(a))+e; index locres_id= (1..size(a)*size(h))+f; e:= e+size(res_id); f:= f+size(locres); temp:= a; a:= mdarraytotable(a,res_id,L); output:= if x= 1 then a else for y:= j do ( concat(output[j=y],a[j=y]) ); index i:= 1..size(output)/size(L); for y:= L do (slice(output[L=y],i)); 216,160,1 48,16 2,745,15,518,798 2,281,16,434,814,0,MIDM [Sys_localindex('L'),Sys_localindex('I')] [] [Sys_localindex('H'),3,Sys_localindex('I'),1,Sys_localindex('ENDSCEN'),1] var a:= Objects[.j='Typ_id']; a:= if a= 4 or a=9 then 1 else 0; index i:= subset(a); a:= Objects[object3=i]; var b:= a[.j='Typ_id']; b:= if b=4 then 3 else if b=9 then 9 else 0; index j:= ['id','Obj_id','Typ_id','Fail']; a:= array(j,[ Cardinals[table1='Sett']+@i, a[.j='id'], b, 0]) 320,64,1 48,16 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] index j:= ['id','Ident','Name','Units','Typ_id','Page','Wik_id']; index i:= 1..size(object3); Objects[.j=j, @object3=@i] 320,32,1 48,16 2,248,258,673,303,0,MIDM 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] var a:= if Objects[.j='Typ_id']=1 then 1 else 0; a:= Objects[object3=subset(a),.j='id']; index i:= 1..size(a); a:= slice(a,i); var b:= if Objects[.j='Typ_id']=9 then Objects[.j='id'] else 0; b:= sum(b,object3); index j:= ['id','Sett_id','Obj_id','Fail']; array(j,[ cardinals[table1='Item']+@i, b, a, 0]) 320,96,1 48,16 2,40,160,476,224 2,619,157,416,303,0,MIDM 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] If the result is not a number, then the actual result text can be written into the Description field of the Descr table. This is not coded yet, because there has not been a need for text results. index j:= ['id','Description']; j 320,336,1 48,16 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] index j:= ['id','Begin','End','Who','Url']; var a:= Objects[.j=j]; a:= if a = null or j='id' then 0 else a; a:= if sum(a,j) = 0 then 0 else 1; index i:= subset(a); a:= Objects[object3=i, .j=j] 320,128,1 48,16 65535,45873,39321 [Sys_localindex('I'),Sys_localindex('J')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] The usage of local variables: a: the temporary variable that is being edited. e: cardinal of the Res table. f: cardinal of the Sam table. j: output column headings. i: output row numbers. 1) Several local variables are initiated. 2) The process is done for each variable one at a time (this is indexed by x). 3) The variable is given index runn which is equal to run if probabilistic and 0 if not. 4) The array is flattened first to 2-D, the value only is kept. 5) Variables are concatenated to each other. 6) Index i is made the index of the implicit index. var output=0; var e:= Cardinals[table1='Res']; var f:= Cardinals[table1='Sam']; index j:= ['id','Res_id','Descr_id','Sample','Result']; var o:= if Objects [.j='Typ_id'] = 1 then 1 else 0; index k:= subset(o); o:= objects[object3=k]; var x:= 1; while x<= size(k) do ( var c:= slice(o,k,x); var a:= sample(evaluate(c[.j='Ident'])); index h:= indexnames(a); index L:= concat(h,['Value']); index runn:= if c[.j='Probabilistic?']=1 then copyindex(run) else [0]; index res_id:= (1..size(a))+e; index sam_id:= (1..size(res_id)*size(runn))+f; e:= e+size(res_id); f:= f+size(sam_id); a:= mdarraytotable(a,res_id,L)[.L='Value']; a:= if c[.j='Probabilistic?']=1 then a[run=runn] else (if runn=0 then mean(a) else mean(a)); a:= array(j,[0, res_id, 0, runn, a]); a:= concatrows(a,res_id,runn,sam_id); a:= if a.j='id' then sam_id else a; output:= if x= 1 then a else for y:= j do ( concat(output[j=y],a[j=y]) ); x:= x+1); index i:= 1..size(output)/size(j); for y:= j do (slice(output[j=y],i)) 320,304,1 48,16 2,102,90,476,701 2,761,364,416,303,0,MIDM 65535,45873,39321 [Sys_localindex('J'),Sys_localindex('I')] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [] Table(Op_en2665)( 'Cardiopulmonary deaths, ICD-10 ## ','Lung cancer deaths, ICD-10 ## ','All other non-accidental deaths, ICD-10 ## ','All non-accidental deaths, ICD-10## ') 208,432,1 48,24 52425,39321,65535 232,288,1 48,20 2,781,100,476,601 This module saves model results into the Result Database. You need a password for that. Note that the necessary variable, index, dimension, and run information will be asked. You must add all tables before the process is completed. 240,48,-1 236,40 Note! You can insert several variables at the same time. Each variable MUST have at least one index. 416,160,-1 76,64 Fill in the data below if needed (in this order). 168,288,-5 160,192 1,0,0,1,0,1,0,,0, 228,324,1 52,12 2,272,482,476,337 0 156,132,1 140,12 1,0,0,1,0,0,0,110,0,1 52425,39321,65535 Username 0 156,156,1 140,12 1,0,0,1,0,0,0,110,0,1 52425,39321,65535 Password 1 156,396,1 140,12 1,0,0,1,0,0,0,72,0,1 Size_of_sample 228,348,1 52,12 2,615,38,625,307 0 156,180,1 140,12 1,0,0,1,0,0,0,110,0,1 52425,39321,65535 Who_ran_the_model Describe the run in this node. The same general instructions apply for Run info as for other objects. In addition, do the following: * DO change the Identifier and the Title. * Do NOT change this Description. * Title should contain the main description of the run WITHOUT the following (which will be added automatically to the Opasnet Base): ** User ** Date ** Analytica version and platform 0 232,256,1 48,12 2,576,173,476,224 52425,39321,65535 0 156,204,1 140,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Objects_excl_indices 0 156,229,1 140,13 1,0,0,1,0,0,0,72,0,1 52425,39321,65535 Object_info ktluser 3. Augta 2008 18:31 jtue 9. lokta 2008 14:01 48,24 112,64,1 48,24 1,1,1,1,1,1,0,0,0,0 1,15,17,593,327,17 Arial, 15 0 272,24,1 160,16 1,0,0,1,0,0,0,214,0,1 Var_info 0 272,56,1 160,16 1,0,0,1,0,0,0,214,0,1 Var_result 1 272,88,1 160,16 1,0,0,1,0,0,0,72,0,1 Var_result (vident:text, run:optional) Reads the data about the var_name variable from the result database. Uses the run_id run if specified; otherwise uses the newest run of that variable. PARAMETERS: * Var_name: the name of the variable in the result database. * Run_id: the identifier of the run from which the results will be brought. If omitted, the newest result will be brought. if isnotspecified(run) then run:= newestrun(vident); index i:= DBquery(Odbc,' SELECT Var.Ident as Vident, Var.Name as Vname, Var.Unit as Vunit, Res.id, Ind.Ident as Iident, Loct, Mean, N, Run.Name as Rname FROM Obj as Var, Res, Locres, Loc, Obj as Ind, Obj as Run, Roww WHERE Res.Obj_id_r = Run.id AND Res.Obj_id_v = Var.id AND Locres.Res_id = Res.id AND Locres.Roww_id = Roww.id AND Roww.Obj_id_i = Ind.id AND Roww.Loc_id = Loc.id '); index j:= dblabels(i); dbtable(i,j) 56,88,1 48,16 2,7,60,516,428 39325,65535,39321 vident,run (vident:text) This function checks for the newest result (according to run_id) of the variable. The function is used if the user does not define the run_id as an optional parameter in functions Do_first and Readdata. PARAMETERS: * Var_name: the name of the variable in the result database. * Run_id: the identifier of the run from which the results will be brought. If omitted, the newest result will be brought. index i:= DBquery(Odbc,' SELECT Obj_id_r FROM Res, Obj as Var WHERE Var.id = Res.Obj_id_v AND Var.Ident = "'&vident&'" GROUP BY Var.id, Obj_id_r '); index j:= dblabels(i); max(max(dbtable(i,j),i),j) 56,120,1 48,16 2,401,51,476,566 39325,65535,39321 vident (vident:text; run, textornot:optional) Brings the data from the result database and transforms it into variables of the correct form. NOTE! All necessary indices must be created before running this function. The necessary indices can be viewed by calling the function Do_first with the same parameters as this function. PARAMETERS: * Vident: the Ident of the variable in the result database. * Run: the identifier of the run from which the results will be brought. If omitted, the newest result will be brought. * Textornot: Tells whether the result is numerical or text. If parameter is omitted or false, numerical is assumed, otherwise text. 1) Brings the data and makes indices for index list, locations, and result_id's. 2) Makes an array containing result_id, indexed by all indices and all locations. 3) Makes an array containing result_id, indexed by the indices of the variable itself. 4) Brings the results into the structure created in 3). Makes the sample fo along the index Run. var data:= Read_sample(vident, run); var a:= data[.j='Iident']; index ind_name:= a[.i=unique(a,a.i)]; a:= data[.j='Loct']; index location:= a[.i=unique(a,a.i)]; a:= data[.j='Res.id']; index result_id:= a[.i=unique(a,a.i)]; var x:= 1; a:= null; while x<= size(data.i) do ( var b:= data[@.i=x]; a:= if location = b[.j='Loct'] and ind_name = b[.j='Iident'] and result_id = b[.j='Res.id'] then b[.j='Res.id'] else a; x:= x+1); var c:= result_id; x:= 1; while x<=size(ind_name) do ( c:= if c= a[location=evaluate(ind_name[@ind_name=x]), @ind_name=x] then result_id else 0; x:=x+1); c:= sum(c,result_id); a:= data[.j='sample']; index sample:= a[.i=unique(a,a.i)]; x:= 1; a:= null; while x<= size(data.i) do ( var b:= data[@.i=x]; a:= if c = b[.j='result_id'] and sample = b[.j='sample'] then b[.j='result'] else a; x:= x+1); a:= if max(sample)>0 then a[sample=run] else a[@sample=1]; if isnotspecified(textornot) or textornot=false then evaluate(a) else a 56,56,1 48,16 2,415,23,476,475 vident,run,textornot (vident:text; run:optional) This function brings the variable from the Result Database and analyses its structure. Each index used will be shown as a column along '.Ind_name', and each location of that index will be shown along '.K'. The last row of '.K' shows the samplesize of the variable. Use this information to create the necessary indices for your model and to adjust the samplesize of the model. If the samplesize of the model is smaller than in the result database, the remaining samples are omitted; if larger, the cells with no results in the database are replaced with null. NOTE! The indices created should be lists of labels (not lists of numbers). PARAMETERS: * Var_name: the name of the variable in the result database. * Run_id: the identifier of the run from which the results will be brought. If omitted, the newest result will be brought. if isnotspecified(run) then run:= newestrun(vident); var data:= Read_mean(vident, run); index j:= ['Iident','Loct']; var a:= data[.j=j]; index i:= unique(a,a.i); a:= a[.i=i]; index ind_name:= a[i=unique(a[j='Iident'], i), j='Iident']; a:= if ind_name=a[j='Iident'] then a[j='Loct']; index b:= ['Sample size']; var d:= array(b,[max(data[.j='Sample'])]); concat(a,d,i,b) 56,24,1 48,16 2,335,61,476,436 vident,run do_first('Op_en2406') 168,128,1 48,12 2,680,114,476,224 2,653,32,569,698,0,MIDM [Formnode Var_info1] [Sys_localindex('IND_NAME'),Sys_localindex('K')] Var_sample('H2556') 168,152,1 48,12 2,612,23,639,490,0,MIDM [Formnode Var_result1, Formnode Var_result2] [] (index1:texttype) This node brings descriptions (if any) of each location of an index from the result database. The only parameter for function Descr is the name of an index (as text). var a:= sum((if indices[.j='Iident'] = index1 then indices[.j='Dim.id'] else 0), indices.i); a:= if locations[.j='Dim.id'] = a and locations[.j='Loct'] = evaluate(index1) then locations[.j='Description'] else ''; jointext(a,a.i) 56,152,1 48,16 2,281,63,476,313 index1 This node brings descriptions (if any) of each location of an index from the result database. The only parameter for function Descr is the name of an index (as text). Descr('Condb_agent2') 168,176,1 52,12 2,287,122,476,224 2,610,365,331,391,0,MIDM [Sys_localindex('I')] ['ang','bou','brw','caw','cho','dcc','eas','ess','fol','har','mik','nor','nww','por','sea','sev','sos','sou','sww','teh','tha','thr','wes','wrx','yor'] 456,152,1 48,24 ['item 1','item 2','item 3','item 4','item 5','item 6','item 7','item 8','item 9','item 10','item 11','item 12','item 13','item 14','item 15','item 16','item 17','item 18','item 19','item 20','item 21','item 22','item 23','item 24','item 25'] newestrun('Op_en2406') 312,152,1 48,24 Read_mean('Op_en2406') 384,200,1 48,24 2,56,66,1002,303,0,MIDM [Sys_localindex('J'),Sys_localindex('I')] (vident:text; run, textornot:optional) Brings the data from the result database and transforms it into variables of the correct form. NOTE! All necessary indices must be created before running this function. The necessary indices can be viewed by calling the function Do_first with the same parameters as this function. PARAMETERS: * Vident: the Ident of the variable in the result database. * Run: the identifier of the run from which the results will be brought. If omitted, the newest result will be brought. * Textornot: Tells whether the result is numerical or text. If parameter is omitted or false, numerical is assumed, otherwise text. 1) Brings the data and makes indices for index list, locations, and result_id's. 2) Makes an array containing result_id, indexed by all indices and all locations. 3) Makes an array containing result_id, indexed by the indices of the variable itself. 4) Brings the results into the structure created in 3). Makes the sample fo along the index Run. var data:= Read_mean(vident, run); var a:= data[.j='Iident']; index ind_name:= a[.i=unique(a,a.i)]; a:= data[.j='Loct']; index location:= a[.i=unique(a,a.i)]; a:= data[.j='Res.id']; index result_id:= a[.i=unique(a,a.i)]; var x:= 1; a:= null; while x<= size(data.i) do ( var b:= data[@.i=x]; a:= if location = b[.j='Loct'] and ind_name = b[.j='Iident'] and result_id = b[.j='Res.id'] then b[.j='Res.id'] else a; x:= x+1); var c:= result_id; x:= 1; while x<=size(ind_name) do ( c:= if c= a[location=evaluate(ind_name[@ind_name=x]), @ind_name=x] then result_id else 0; x:=x+1); c:= sum(c,result_id); a:= data[.j='sample']; index sample:= a[.i=unique(a,a.i)]; x:= 1; a:= null; while x<= size(data.i) do ( var b:= data[@.i=x]; a:= if c = b[.j='result_id'] and sample = b[.j='sample'] then b[.j='result'] else a; x:= x+1); a:= if max(sample)>0 then a[sample=run] else a[@sample=1]; if isnotspecified(textornot) or textornot=false then evaluate(a) else a 56,184,1 48,16 2,431,23,476,475 vident,run,textornot (vident:text, run:optional) Reads the data about the var_name variable from the result database. Uses the run_id run if specified; otherwise uses the newest run of that variable. PARAMETERS: * Var_name: the name of the variable in the result database. * Run_id: the identifier of the run from which the results will be brought. If omitted, the newest result will be brought. if isnotspecified(run) then run:= newestrun(vident); index i:= DBquery(Odbc,' SELECT Res.id, Sample, Result FROM Res, Sam WHERE Res.Obj_id_v = "'&vident&'" AND Res.Obj_id_r ='&Run&' AND Sam.Res_id = Res.id '); index j:= dblabels(i); dbtable(i,j) 56,224,1 48,22 2,7,60,516,428 39325,65535,39321 vident,run Brings the same information from Opasnet Base as Object info. Brings the same information from Opasnet Base as Object info. 488,351,1 48,31 2,745,90,476,224 Instructions for uploading results to the Opasnet Base: * Make sure that you have created an object page in the Opasnet wiki for each object you want to upload. (This applies also to assessments and runs!) * Use the wiki identifier as the Identifier for the object in Analytica. * Use the wiki page name as the Title for the object. * Make sure that you have defined the Units. * If an object with the same Ident (Analytica identifier) already exists, metadata about that object will NOT be updated. However, the actual results will be uploaded normally. 208,360,-1 196,192 ktluser 8. Decta 2008 3:01 48,24 256,64,1 48,24 1,15,51,556,497,17 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102;Database=resultdb;User='&username&'; Password='&password&';Option=3' 184,248,1 48,12 1,1,0,1,1,1,0,,0, 'Add username' 184,200,0 48,12 1,1,1,1,1,1,0,0,0,0 [Formnode Username1] 52425,39321,65535 'Add password' 184,224,0 48,12 1,1,1,1,1,1,0,0,0,0 [Formnode Password1] 52425,39321,65535 ['Op_en2693','Op_en2676','Op_en2694'] 80,248,1 48,24 [Formnode Object2] 52425,39321,65535 Contains the parameters for the open database connectivity (ODBC). 'Driver={MySQL ODBC 5.1 Driver};Server=10.66.10.102;Database=resultdb;User=result_reader; Password=ora4ever;Option=3' 184,176,1 48,12 1,1,0,1,1,1,0,,0, 2,102,90,476,224 index i:= copyindex(D_i); index j:= copyindex(D_j); Dim1[d_i=i, d_j=j] 424,64,1 48,13 1,1,0,1,1,1,0,0,0,0 2,89,98,476,224 2,635,328,556,489,0,MIDM 19661,54073,65535 [D_i,D_j] [Sys_localindex('J'),Sys_localindex('I')] index i:= copyindex(I_i); index j:= copyindex(I_j); Ind1[I_i=i, I_j=j] 424,88,1 48,13 1,1,0,1,1,1,0,0,0,0 2,380,47,476,296 2,15,147,876,493,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] index i:= copyindex(L_i); index j:= copyindex(L_j); Loc1[L_i=i, L_j=j] 424,112,1 48,13 1,1,0,1,1,1,0,0,0,0 2,370,45,476,445 2,43,42,667,516,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(O_i); index j:= copyindex(O_j); Obj2[O_i=i, O_j=j] 424,136,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,55,147,846,421,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] Standard versions 424,128,-1 72,100 1,0,0,1,0,1,0,,0, [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22] 80,32,1 48,12 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22] ['id','Ident','Name'] 80,53,1 48,12 ['id','Ident','Name'] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] 80,80,1 48,12 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] ['id','Iident','Iname','Did','Dident','Dname'] 80,101,1 48,12 ['id','Iident','Iname','Did','Dident','Dname'] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453] 80,125,1 48,12 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453] ['id','Obj_id_d','Location','Locn','Num','Description','id','Ident','Name','Unit','Typ_id','Page','Wik_id'] 80,149,1 48,12 ['id','Obj_id_d','Location','Locn','Num','Description','id','Ident','Name','Unit','Typ_id','Page','Wik_id'] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107] 80,173,1 48,13 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107] ['id','Ident','Name','Unit','Typ_id','Page','Wik_id'] 80,197,1 48,13 ['id','Ident','Name','Unit','Typ_id','Page','Wik_id'] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(S_i); index j:= copyindex(S_j); Sett1[S_i=i, S_j=j] 424,208,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,319,421,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(R_i); index j:= copyindex(R_j); Roww1[R_i=i, R_j=j] 424,184,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,66,340,399,421,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. index i:= copyindex(It_i); index j:= copyindex(It_j); Item1[it_i=i, it_j=j] 424,160,1 48,13 1,1,0,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 19661,54073,65535 [Sys_localindex('J'),Sys_localindex('I')] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] 184,29,1 48,13 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] ['id','Sett_id','Obj_id','Fail'] 184,53,1 48,13 ['id','Sett_id','Obj_id','Fail'] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659] 184,80,1 48,13 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598,599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634,635,636,637,638,639,640,641,642,643,644,645,646,647,648,649,650,651,652,653,654,655,656,657,658,659] ['id','Obj_id_i','Roww','Loc_id'] 184,101,1 48,13 ['id','Obj_id_i','Roww','Loc_id'] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] 184,125,1 48,13 [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34] ['id','Obj_id','Sty_id'] 184,149,1 48,13 ['id','Obj_id','Sty_id'] Table(D_i,D_j)( 43,'Vehicle_type','Vehicle type', 45,'Transport_mode','Transport mode', 46,'Cost_type','Cost type', 47,'Composite_fraction','Composite fraction', 51,'Food_source','The method for food production', 52,'Feed_pollutant','Decision about fish feed', 53,'Salmon_recomm','Decision about samon consumption recommendation', 32,'0','No dimension has been identified', 54,'Parameter','Statistical and other parameters of a variable', 42,'Environ_compartment','Environmental compartment', 41,'Emission_source','Emission source', 36,'Pollutant','Pollutant', 34,'Health_impact','Health impact', 33,'Decision','Possible range of decisions for a single decision-maker', 35,'Time','Time', 40,'Period','Period', 48,'Age','Age', 37,'Spatial_location','Spatial location', 38,'Length','Length', 49,'Municipality_fin','Municipalities in Finland', 44,'Person_or_group','Person or group', 39,'Non_health_impact','Non-health impact' ) 304,64,1 48,13 1,1,1,1,1,1,0,0,0,0 2,89,98,476,224 2,604,56,556,489,0,MIDM 39325,65535,39321 [D_i,D_j] [D_j,D_i] Table(I_i,I_j)( 55,'Salmon_decision','',33,'Decision','Possible range of decisions for a single decision-maker', 80,'Reg_poll','',33,'Decision','Possible range of decisions for a single decision-maker', 81,'Recommendation1','',33,'Decision','Possible range of decisions for a single decision-maker', 83,'H1899','',33,'Decision','Possible range of decisions for a single decision-maker', 84,'H1898','',33,'Decision','Possible range of decisions for a single decision-maker', 56,'Hma_area','',37,'Spatial_location','Spatial location', 57,'Hma_region','',37,'Spatial_location','Spatial location', 58,'Hma_zone','',37,'Spatial_location','Spatial location', 88,'Condb_location1','',37,'Spatial_location','Spatial location', 93,'Op_en2672','',37,'Spatial_location','Spatial location', 59,'Year_1','',35,'Time','Time', 61,'Year_2','',35,'Time','Time', 82,'Year3','',35,'Time','Time', 60,'Op_en2665','Cause of death 1',34,'Health_impact','Health impact', 62,'Cause_of_death_2','',34,'Health_impact','Health impact', 85,'Cause_of_death3','',34,'Health_impact','Health impact', 63,'Length_1','',38,'Length','Length', 70,'Output_1','',39,'Non_health_impact','Non-health impact', 65,'Period_1','',40,'Period','Period', 86,'Run','',32,'0','No dimension has been identified', 71,'Vehicle_noch','',43,'Vehicle_type','Vehicle type', 92,'Vehicle_1','',43,'Vehicle_type','Vehicle type', 72,'Stakeholder_1','',44,'Person_or_group','Person or group', 73,'Mode1','',45,'Transport_mode','Transport mode', 74,'Cost_structure_1','',46,'Cost_type','Cost type', 75,'Comp_fr_1','',47,'Composite_fraction','Composite fraction', 76,'Age1','',48,'Age','Age', 77,'Municipality_fin1','',49,'Municipality_fin','Municipalities in Finland', 79,'Salmon1','',51,'Food_source','The method for food production', 78,'Pollutant1','',36,'Pollutant','Pollutant', 89,'Condb_agent1','',36,'Pollutant','Pollutant', 91,'Condb_agent2','',36,'Pollutant','Pollutant', 87,'Condb_compartment1','',42,'Environ_compartment','Environmental compartment', 90,'Condb_param1','',54,'Parameter','Statistical and other parameters of a variable' ) 304,88,1 48,13 1,1,1,1,1,1,0,0,0,0 2,380,47,476,296 2,232,242,874,303,0,MIDM 2,209,67,876,493,0,MIDM 39325,65535,39321 [I_j,I_i] [I_j,I_i] Table(L_i,L_j)( 1,1,'Business as usual',0,0,'',1,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 2,1,'Recommend restrictions to salmon consumption',0,0,'',2,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 3,1,'Stricter limits for fish feed pollutants',0,0,'',3,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 4,1,'Restrictions to salmon consumption AND stricter fish feed limits',0,0,'',4,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 26,2,'All causes',0,0,'',26,'Op_en2693','Testvariable','kg',1,2693,1, 197,6,'>= 5 km',0,0,'',197,'Ppmconc_bustraffic','PM2.5 concentration from bus traffic in Helsinki in 2020','ug/m3',1,0,0, 196,6,'< 5 km',0,0,'',196,'Ppmconc_bustraffic','PM2.5 concentration from bus traffic in Helsinki in 2020','ug/m3',1,0,0, 8,3,'2020',0,0,'',8,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 7,3,'1997',0,0,'',7,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 10,2,'Cardiopulmonary',0,0,'',10,'Op_en2693','Testvariable','kg',1,2693,1, 11,2,'Lung ca',0,0,'',11,'Op_en2693','Testvariable','kg',1,2693,1, 12,2,'All others',0,0,'',12,'Op_en2693','Testvariable','kg',1,2693,1, 27,5,'Downtown',0,0,'',27,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 28,5,'Centre',0,0,'',28,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 29,5,'Suburb',0,0,'',29,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 30,5,'Länsi-Espoo',0,0,'',30,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 31,5,'Pohjois-Espoo',0,0,'',31,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 32,5,'Etelä-Espoo',0,0,'',32,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 33,5,'Keski-Espoo',0,0,'',33,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 34,5,'Länsi-Vantaa',0,0,'',34,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 35,5,'Keski-Vantaa',0,0,'',35,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 36,5,'Pohjois-Vantaa',0,0,'',36,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 37,5,'Itä-Vantaa',0,0,'',37,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 38,5,'Kanta-Helsinki',0,0,'',38,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 39,5,'Länsi-Helsinki',0,0,'',39,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 40,5,'Vanha-Helsinki',0,0,'',40,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 41,5,'Konalanseutu',0,0,'',41,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 42,5,'Pakilanseutu',0,0,'',42,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 43,5,'Malminseutu',0,0,'',43,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 44,5,'Itä-Helsinki',0,0,'',44,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 45,5,'1001',0,0,'',45,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 46,5,'1002',0,0,'',46,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 47,5,'1003',0,0,'',47,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 48,5,'1004',0,0,'',48,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 49,5,'1005',0,0,'',49,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 50,5,'1006',0,0,'',50,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 51,5,'1007',0,0,'',51,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 52,5,'1008',0,0,'',52,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 53,5,'1009',0,0,'',53,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 54,5,'1010',0,0,'',54,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 55,5,'1011',0,0,'',55,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 56,5,'1012',0,0,'',56,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 57,5,'1013',0,0,'',57,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 58,5,'1014',0,0,'',58,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 59,5,'1015',0,0,'',59,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 60,5,'1016',0,0,'',60,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 61,5,'1017',0,0,'',61,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 62,5,'1018',0,0,'',62,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 63,5,'1019',0,0,'',63,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 64,5,'1020',0,0,'',64,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 65,5,'1021',0,0,'',65,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 66,5,'1022',0,0,'',66,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 67,5,'1023',0,0,'',67,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 68,5,'1024',0,0,'',68,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 69,5,'1025',0,0,'',69,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 70,5,'1026',0,0,'',70,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 71,5,'1027',0,0,'',71,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 72,5,'1028',0,0,'',72,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 73,5,'1029',0,0,'',73,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 74,5,'1030',0,0,'',74,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 75,5,'1031',0,0,'',75,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 76,5,'1032',0,0,'',76,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 77,5,'1033',0,0,'',77,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 78,5,'1034',0,0,'',78,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 79,5,'1035',0,0,'',79,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 80,5,'1036',0,0,'',80,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 81,5,'1037',0,0,'',81,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 82,5,'1038',0,0,'',82,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 83,5,'1039',0,0,'',83,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 84,5,'1040',0,0,'',84,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 85,5,'1041',0,0,'',85,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 86,5,'1042',0,0,'',86,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 87,5,'1043',0,0,'',87,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 88,5,'1044',0,0,'',88,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 89,5,'1045',0,0,'',89,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 90,5,'1046',0,0,'',90,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 91,5,'1047',0,0,'',91,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 92,5,'1048',0,0,'',92,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 93,5,'1049',0,0,'',93,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 94,5,'1050',0,0,'',94,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 95,5,'1051',0,0,'',95,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 96,5,'1052',0,0,'',96,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 97,5,'1053',0,0,'',97,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 98,5,'1054',0,0,'',98,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 99,5,'1055',0,0,'',99,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 100,5,'1056',0,0,'',100,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 101,5,'1057',0,0,'',101,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 102,5,'1058',0,0,'',102,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 103,5,'1059',0,0,'',103,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 104,5,'1060',0,0,'',104,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 105,5,'1061',0,0,'',105,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 106,5,'1062',0,0,'',106,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 107,5,'1063',0,0,'',107,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 108,5,'1064',0,0,'',108,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 109,5,'1065',0,0,'',109,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 110,5,'1066',0,0,'',110,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 111,5,'1067',0,0,'',111,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 112,5,'1068',0,0,'',112,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 113,5,'1069',0,0,'',113,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 114,5,'1070',0,0,'',114,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 115,5,'1071',0,0,'',115,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 116,5,'1072',0,0,'',116,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 117,5,'1073',0,0,'',117,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 118,5,'1074',0,0,'',118,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 119,5,'1075',0,0,'',119,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 120,5,'1076',0,0,'',120,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 121,5,'1077',0,0,'',121,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 122,5,'1078',0,0,'',122,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 123,5,'1079',0,0,'',123,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 124,5,'1080',0,0,'',124,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 125,5,'1081',0,0,'',125,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 126,5,'1082',0,0,'',126,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 127,5,'1083',0,0,'',127,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 128,5,'1084',0,0,'',128,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 129,5,'1085',0,0,'',129,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 130,5,'1086',0,0,'',130,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 131,5,'1087',0,0,'',131,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 132,5,'1088',0,0,'',132,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 133,5,'1089',0,0,'',133,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 134,5,'1090',0,0,'',134,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 135,5,'1091',0,0,'',135,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 136,5,'1092',0,0,'',136,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 137,5,'1093',0,0,'',137,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 138,5,'1094',0,0,'',138,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 139,5,'1095',0,0,'',139,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 140,5,'1096',0,0,'',140,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 141,5,'1097',0,0,'',141,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 142,5,'1098',0,0,'',142,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 143,5,'1099',0,0,'',143,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 144,5,'1100',0,0,'',144,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 145,5,'1101',0,0,'',145,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 146,5,'1102',0,0,'',146,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 147,5,'1103',0,0,'',147,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 148,5,'1104',0,0,'',148,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 149,5,'1105',0,0,'',149,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 150,5,'1106',0,0,'',150,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 151,5,'1107',0,0,'',151,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 152,5,'1108',0,0,'',152,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 153,5,'1109',0,0,'',153,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 154,5,'1110',0,0,'',154,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 155,5,'1111',0,0,'',155,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 156,5,'1112',0,0,'',156,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 157,5,'1113',0,0,'',157,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 158,5,'1114',0,0,'',158,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 159,5,'1115',0,0,'',159,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 160,5,'1116',0,0,'',160,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 161,5,'1117',0,0,'',161,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 162,5,'1118',0,0,'',162,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 163,5,'1119',0,0,'',163,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 164,5,'1120',0,0,'',164,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 165,5,'1121',0,0,'',165,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 166,5,'1122',0,0,'',166,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 167,5,'1123',0,0,'',167,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 168,5,'1124',0,0,'',168,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 169,5,'1125',0,0,'',169,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 170,5,'1126',0,0,'',170,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 171,5,'1127',0,0,'',171,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 172,5,'1128',0,0,'',172,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 173,5,'1129',0,0,'',173,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 174,5,'1130',0,0,'',174,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 175,3,'2000',0,0,'',175,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 176,3,'2001',0,0,'',176,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 177,3,'2002',0,0,'',177,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 178,3,'2003',0,0,'',178,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 179,3,'2004',0,0,'',179,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 180,3,'2005',0,0,'',180,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 181,3,'2006',0,0,'',181,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 182,3,'2007',0,0,'',182,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 183,3,'2008',0,0,'',183,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 184,3,'2009',0,0,'',184,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 185,3,'2010',0,0,'',185,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 186,3,'2011',0,0,'',186,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 187,3,'2012',0,0,'',187,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 188,3,'2013',0,0,'',188,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 189,3,'2014',0,0,'',189,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 190,3,'2015',0,0,'',190,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 191,3,'2016',0,0,'',191,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 192,3,'2017',0,0,'',192,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 193,3,'2018',0,0,'',193,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 194,3,'2019',0,0,'',194,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 418,1,'BAU',0,0,'',418,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 198,8,' 6.00-20.00',0,0,'',198,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 199,8,'20.00-24.00',0,0,'',199,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 200,8,' 0.00- 6.00',0,0,'',200,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 364,7,'Trips',0,0,'',364,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 365,7,'Trips by vehicle',0,0,'',365,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 366,7,'Vehicle km',0,0,'',366,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 367,7,'Parking lot',0,0,'',367,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 368,7,'Link intensity',0,0,'',368,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 369,7,'Vehicles',0,0,'',369,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 370,7,'Waiting',0,0,'',370,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 371,11,'Bus no change',0,0,'',371,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 372,11,'Bus one change',0,0,'',372,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 373,11,'Cab no change',0,0,'',373,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 374,11,'Cab one change',0,0,'',374,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 375,11,'Cab non-full',0,0,'',375,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 376,11,'Car',0,0,'',376,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 377,11,'No-change',0,0,'',377,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 378,12,'Passenger',0,0,'',378,'Fig_5c_expanding','Societal costs at different levels of guarantee','e/day',1,0,0, 379,12,'Society',0,0,'',379,'Fig_5c_expanding','Societal costs at different levels of guarantee','e/day',1,0,0, 380,13,'Car',0,0,'',380,'Bw1','Human body weight in Harjavalta','kg',1,2475,1, 381,13,'Composite',0,0,'',381,'Bw1','Human body weight in Harjavalta','kg',1,2475,1, 382,14,'Vehicle',0,0,'',382,'Testvariable2','Another variable for testing','kg',1,0,0, 383,14,'Driver',0,0,'',383,'Testvariable2','Another variable for testing','kg',1,0,0, 384,14,'Driving',0,0,'',384,'Testvariable2','Another variable for testing','kg',1,0,0, 385,14,'Parking',0,0,'',385,'Testvariable2','Another variable for testing','kg',1,0,0, 386,14,'Parking land',0,0,'',386,'Testvariable2','Another variable for testing','kg',1,0,0, 387,14,'Emissions',0,0,'',387,'Testvariable2','Another variable for testing','kg',1,0,0, 388,14,'Time',0,0,'',388,'Testvariable2','Another variable for testing','kg',1,0,0, 389,14,'Accidents',0,0,'',389,'Testvariable2','Another variable for testing','kg',1,0,0, 390,14,'Ticket',0,0,'',390,'Testvariable2','Another variable for testing','kg',1,0,0, 391,15,'0',0,0,'',391,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 392,15,'0.02',0,0,'',392,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 393,15,'0.05',0,0,'',393,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 394,15,'0.1',0,0,'',394,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 395,15,'0.25',0,0,'',395,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 396,15,'0.4',0,0,'',396,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 397,15,'0.45',0,0,'',397,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 398,15,'0.5',0,0,'',398,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 399,15,'0.55',0,0,'',399,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 400,15,'0.65',0,0,'',400,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 401,15,'0.75',0,0,'',401,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 402,15,'0.9',0,0,'',402,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 403,15,'1',0,0,'',403,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 404,16,'18-65',0,0,'',404,'Op_en1900','Pollutant health risk due to the consumption of salmon','avoided cases/a',1,1900,1, 405,16,'3',0,0,'',405,'Op_en1900','Pollutant health risk due to the consumption of salmon','avoided cases/a',1,1900,1, 406,17,'Harjavalta',0,0,'',406,'Op_en1903','Persistent pollutant concentrations in salmon','µg/kg',1,1903,1, 407,4,'Dieldrin',0,0,'',407,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 408,4,'Toxaphene',0,0,'',408,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 409,4,'Dioxin',0,0,'',409,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 410,4,'PCB',0,0,'',410,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 411,19,'Farmed salmon',0,0,'',411,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 412,19,'Wild salmon',0,0,'',412,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 413,19,'Market salmon',0,0,'',413,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 414,20,'BAU',0,0,'',414,'Op_en1907','Omega-3 content in salmon','g/g',1,1907,1, 415,20,'More actions',0,0,'',415,'Op_en1907','Omega-3 content in salmon','g/g',1,1907,1, 416,21,'BAU',0,0,'',416,'Op_en1908','Omega-3 intake due to salmon in the population of the Western Europe','g/d',1,1908,1, 417,21,'Restrict farmed salmon use',0,0,'',417,'Op_en1908','Omega-3 intake due to salmon in the population of the Western Europe','g/d',1,1908,1, 419,1,'More actions',0,0,'',419,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 421,1,'Restrict farmed salmon use',0,0,'',421,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 422,2,'Cardiovascular',0,0,'',422,'Op_en2693','Testvariable','kg',1,2693,1, 423,10,'Home indoor',0,0,'Abbreviation in the Concentration database: I',423,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 424,10,'(Home) outdoor',0,0,'Abbreviation in the Concentration database: O',424,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 425,10,'(Personal) Work',0,0,'Abbreviation in the Concentration database: W',425,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 426,10,'Personal',0,0,'Abbreviation in the Concentration database: P',426,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 427,10,'Drinking water',0,0,'Abbreviation in the Concentration database: DW',427,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 428,10,'Indoor dust',0,0,'Abbreviation in the Concentration database: ID',428,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 429,10,'Human',0,0,'Abbreviation in the Concentration database: H',429,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 430,10,'Soil',0,0,'Abbreviation in the Concentration database: S',430,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 431,10,'Beverage',0,0,'Abbreviation in the Concentration database: B',431,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 432,10,'Food',0,0,'Abbreviation in the Concentration database: F',432,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 433,10,'In-Vehicle',0,0,'Abbreviation in the Concentration database: IV',433,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 434,10,'School',0,0,'Abbreviation in the Concentration database: SC',434,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 435,5,'Athens',0,0,'Country: Greece. Abbreviation in the Concentration Database: A',435,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 436,5,'Antwerp',0,0,'Country: Belgium. Abbreviation in the Concentration Database: ANT',436,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 437,5,'Antioch-Pittsburg',0,0,'Country: USA. Abbreviation in the Concentration Database: AP',437,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 438,5,'Antioch-Pittsburg A-P',0,0,'Country: USA. Abbreviation in the Concentration Database: A-P',438,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 439,5,'Arizona',0,0,'Country: USA. Abbreviation in the Concentration Database: AZ',439,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 440,5,'Basel',0,0,'Country: Germany. Abbreviation in the Concentration Database: B',440,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 441,5,'Baltimore',0,0,'Country: USA. Abbreviation in the Concentration Database: BAL',441,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 442,5,'Bayonne',0,0,'Country: USA. Abbreviation in the Concentration Database: BAY',442,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 443,5,'Bayonne-Ellizabeth',0,0,'Country: USA. Abbreviation in the Concentration Database: BE',443,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 444,5,'Copenhagen',0,0,'Country: Denmark. Abbreviation in the Concentration Database: C',444,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 445,5,'California',0,0,'Country: USA. Abbreviation in the Concentration Database: CA',445,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 446,5,'Columbus',0,0,'Country: USA. Abbreviation in the Concentration Database: CO',446,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 447,5,'Daegu',0,0,'Country: South Korea. Abbreviation in the Concentration Database: D',447,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 448,5,'Devils Lake',0,0,'Country: USA. Abbreviation in the Concentration Database: DLA',448,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 449,5,'Dublin',0,0,'Country: Ireland. Abbreviation in the Concentration Database: DU',449,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 450,5,'Elizabeth',0,0,'Country: USA. Abbreviation in the Concentration Database: ELI',450,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 451,5,'EPA Region 5.',0,0,'Country: USA. Abbreviation in the Concentration Database: EPA5',451,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 452,5,'Flanders',0,0,'Country: Belgium. Abbreviation in the Concentration Database: FLA',452,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 453,5,'Florence',0,0,'Country: Italy. Abbreviation in the Concentration Database: FL',453,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 454,5,'Grenoble',0,0,'Country: France. Abbreviation in the Concentration Database: G',454,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 455,5,'Germany',0,0,'Country: Germany. Abbreviation in the Concentration Database: GE',455,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 456,5,'Genoa',0,0,'Country: Italy. Abbreviation in the Concentration Database: GEN',456,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 457,5,'Greensboro GNC',0,0,'Country: USA. Abbreviation in the Concentration Database: GNC',457,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 458,5,'Greensboro',0,0,'Country: USA. Abbreviation in the Concentration Database: GRB',458,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 460,5,'Helsinki',0,0,'Country: Finland. Abbreviation in the Concentration Database: H',460,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 461,5,'Hannover',0,0,'Country: Germany. Abbreviation in the Concentration Database: HA',461,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 462,5,'Ile de France',0,0,'Country: France. Abbreviation in the Concentration Database: IDF',462,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 463,5,'Los Angeles',0,0,'Country: USA. Abbreviation in the Concentration Database: LA',463,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 464,5,'Milan',0,0,'Country: Italy. Abbreviation in the Concentration Database: M',464,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 465,5,'Minneapolis',0,0,'Country: USA. Abbreviation in the Concentration Database: MP',465,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 466,5,'Minnesota',0,0,'Country: USA. Abbreviation in the Concentration Database: MS',466,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 467,5,'Murcia',0,0,'Country: Spain. Abbreviation in the Concentration Database: MU',467,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 468,5,'Mexico City',0,0,'Country: Mexico. Abbreviation in the Concentration Database: MXC',468,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 469,5,'Oxford',0,0,'Country: England. Abbreviation in the Concentration Database: O',469,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 470,5,'Prague',0,0,'Country: Czech. Abbreviation in the Concentration Database: P',470,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 471,5,'Padua',0,0,'Country: Italy. Abbreviation in the Concentration Database: PA',471,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 472,5,'Puebla',0,0,'Country: Mexico. Abbreviation in the Concentration Database: PB',472,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 473,5,'Rouen',0,0,'Country: France. Abbreviation in the Concentration Database: R',473,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 475,5,'Strasbourg',0,0,'Country: France. Abbreviation in the Concentration Database: STR',475,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 476,5,'Umbria region',0,0,'Country: Italy. Abbreviation in the Concentration Database: UMB',476,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 477,5,'United States',0,0,'Country: USA. Abbreviation in the Concentration Database: USA',477,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 478,5,'Valdez',0,0,'Country: USA. Abbreviation in the Concentration Database: VAL',478,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 479,5,'Woodland',0,0,'Country: USA. Abbreviation in the Concentration Database: WDL',479,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 480,4,'66-25-1',0,0,'hexanal',480,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 481,4,'71-36-3',0,0,'1-butanol',481,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 482,4,'71-43-2',0,0,'benzene',482,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 483,4,'78-83-1',0,0,'2-methyl-1-propanol',483,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 484,4,'79-00-5',0,0,'1,1,2-trichloroethane',484,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 485,4,'79-01-6',0,0,'trichloroethene',485,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 486,4,'80-56-8',0,0,'alfa-pinene',486,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 487,4,'91-20-3',0,0,'naphtalene',487,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 488,4,'95-47-6',0,0,'o-xylene',488,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 489,4,'95-63-6',0,0,'trimethylbenzenes',489,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 490,4,'100-41-4',0,0,'ethylbenzene',490,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 491,4,'100-42-5',0,0,'styrene',491,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 492,4,'100-52-7',0,0,'benzaldehyde',492,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 493,4,'103-65-1',0,0,'propylbenzene',493,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 494,4,'104-76-7',0,0,'2-ethylhexanol',494,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 495,4,'108-38-3',0,0,'m(&p)-xylene',495,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 496,4,'108-88-3',0,0,'toluene',496,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 497,4,'108-95-2',0,0,'phenol',497,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 498,4,'110-54-3',0,0,'hexane',498,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 499,4,'110-82-7',0,0,'cyclohexane',499,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 500,4,'111-76-2',0,0,'ethanol, 2-butoxy-',500,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 501,4,'111-84-2',0,0,'nonane',501,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 502,4,'111-87-5',0,0,'1-octanol',502,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 503,4,'124-13-0',0,0,'octanal',503,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 504,4,'124-18-5',0,0,'decane',504,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 505,4,'127-18-4',0,0,'tetrachloroethene',505,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 506,4,'138-86-3',0,0,'d-limonene',506,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 507,4,'872-50-4',0,0,'2-pyrrolidinone, 1-methyl-',507,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 508,4,'1120-21-4',0,0,'undecane',508,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 509,4,'13466-78-9',0,0,'3-caren',509,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 510,4,'TVOC',0,0,'Toluene based total VOC',510,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 511,4,'67-66-3',0,0,'chloroform',511,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 512,4,'106-46-7',0,0,'1,4-dichlorobenzene',512,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 514,4,'56-23-5',0,0,'carbon tetrachloride',514,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 515,4,'75-09-2',0,0,'methylene chloride',515,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 517,4,'127-91-3',0,0,'b-pinene',517,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 520,4,'142-82-5',0,0,'n-heptane',520,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 521,4,'111-65-9',0,0,'n-octane',521,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 525,4,'112-40-3',0,0,'n-dodecane',525,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 526,4,'629-50-5',0,0,'n-tridecane',526,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 527,4,'629-59-4',0,0,'n-tetradecane',527,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 528,4,'629-62-9',0,0,'n-pentadecane',528,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 529,4,'107-83-5',0,0,'2-methylpentane',529,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 530,4,'96-14-0',0,0,'3-methylpentane',530,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 531,4,'565-59-3',0,0,'2,3-dimethylpentane',531,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 532,4,'591-76-4',0,0,'2-methylhexane',532,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 533,4,'589-34-4',0,0,'3-methylhexane',533,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 534,4,'592-27-8',0,0,'2-methylheptane',534,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 535,4,'589-81-1',0,0,'3-methylheptane',535,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 536,4,'96-37-7',0,0,'methylcyclopentane',536,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 537,4,'108-87-2',0,0,'methylcyclohexane',537,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 538,4,'526-73-8',0,0,'1,2,3-trimethylbenzene',538,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 540,4,'108-67-8',0,0,'1,3,5 trimethylbenzene',540,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 541,4,'4994-16-5',0,0,'4-phenylcyclohexene',541,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 542,4,'1,1,1-trichloroethane',0,0,'1,1,1-trichloroethane',542,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 545,4,'141-78-6',0,0,'ethylacetate',545,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 546,4,'123-86-4',0,0,'n-butylacetate',546,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 547,4,'78-93-3',0,0,'methyl ethyl ketone',547,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 548,4,'106-35-4',0,0,'3-heptatone',548,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 549,4,'93-58-3',0,0,'methyl benzoate',549,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 552,4,'123-51-3',0,0,'iso-amyl alcohol^a',552,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 554,4,'67-63-0',0,0,'2-propanol^a',554,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 555,4,'1634-04-4',0,0,'t-butyl methylether',555,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 556,4,'7439-92-1',0,0,'lead',556,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 557,4,'7440-38-2',0,0,'arsenic',557,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 558,4,'7440-43-9',0,0,'cadmium',558,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 559,4,'7440-39-3',0,0,'barium',559,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 560,4,'7440-47-3',0,0,'chrome',560,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 561,4,'7440-50-8',0,0,'copper',561,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 562,4,'7439-96-5',0,0,'manganese',562,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 563,4,'7440-02-0',0,0,'nickel',563,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 564,4,'7782-49-2',0,0,'selenium',564,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 565,4,'7440-62-2',0,0,'vanadium',565,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 566,4,'7440-66-6',0,0,'zinc',566,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 567,4,'71-55-6',0,0,'1,1,1-trichloroethane',567,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 568,4,'7439-97-6',0,0,'mercury',568,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 570,4,'60-27-5',0,0,'creatinine',570,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 571,4,'7429-90-5',0,0,'aluminium',571,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 572,4,'7440-70-2',0,0,'calcium',572,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 573,4,'7439-95-4',0,0,'magnesium',573,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 574,4,'7723-14-0',0,0,'phosphorus',574,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 575,4,'7440-24-6',0,0,'strontium',575,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 576,4,'7439-89-6',0,0,'iron',576,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 577,4,'7440-09-7',0,0,'potassium',577,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 578,4,'7440-23-5',0,0,'sodium',578,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 579,4,'58-89-9',0,0,'lindane',579,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 580,4,'52645-53-1',0,0,'permenthrine',580,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 581,4,'107-13-1',0,0,'acrylonitrile',581,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 582,4,'79-06-1',0,0,'acrylamide',582,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 589,4,'611-14-3',0,0,'1-ethyl 2methyl benzene',589,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 592,4,'109-66-0',0,0,'n-pentane',592,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 593,4,'7785-26-4',0,0,'alpha-pinene',593,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 594,4,'5989-27-5',0,0,'d-limonene',594,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 596,4,'106-99-0',0,0,'butadiene',596,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 597,4,'74-84-0',0,0,'ethane',597,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 598,4,'74-85-1',0,0,'ethylene',598,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 599,4,'74-86-2',0,0,'acetylene',599,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 600,4,'107-06-2',0,0,'1,2-dichloroethane',600,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 601,4,'106-42-3',0,0,'p-xylene',601,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 603,4,'98-82-8',0,0,'isopropylbenzene',603,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 604,4,'110-86-1',0,0,'pyridine',604,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 606,4,'109-06-8',0,0,'2-picoline',606,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 608,4,'108-99-6',0,0,'3-picoline',608,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 609,4,'108-89-4',0,0,'4-picoline',609,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 610,4,'104-51-8',0,0,'n-butylbenzene',610,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 611,4,'536-78-7',0,0,'3-ethylpyridine',611,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 613,4,'25551-13-7',0,0,'trimethylbenzene',613,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 618,4,'1336-36-3',0,0,'PCBs',618,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 619,4,'3547-04-4',0,0,'DDE',619,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 620,4,'118-74-1',0,0,'HCB',620,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 621,4,'5315-79-7',0,0,'1-hydroxypyrene',621,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 623,4,'1330-20-7',0,0,'xylenes',623,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 624,4,'37210-16-5',0,0,'CO2',624,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 625,4,'630-08-0',0,0,'CO',625,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 626,4,'54-11-5',0,0,'nicotine',626,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 628,4,'3588-17-8',0,0,'trans,trans-Muconic acid',628,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 629,4,'50-32-8',0,0,'benzo(a)pyrene',629,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 631,4,'590-86-3',0,0,'isovaleraldehyde',631,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 632,4,'123-38-6',0,0,'propionaldehyde',632,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 633,4,'123-72-8',0,0,'n-butyraldehyde',633,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 634,4,'75-07-0',0,0,'acetaldehyde',634,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 636,4,'50-00-0',0,0,'formaldehyde',636,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 637,4,'110-62-3',0,0,'valeraldehyde',637,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 638,4,'4170-30-3',0,0,'crotonaldehyde',638,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 639,22,'n',0,0,'Number of observations',639,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 640,22,'n_lt_LOQ',0,0,'Number of observations below level of quantitation',640,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 641,22,'F0.10',0,0,'Fractile 0.1',641,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 642,22,'F0.50',0,0,'Fractile 0.5',642,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 643,22,'F0.90',0,0,'Fractile 0.9',643,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 644,22,'F0.95',0,0,'Fractile 0.95',644,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 645,22,'Mean',0,0,'Arithmetic mean',645,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 646,22,'GeoMean',0,0,'Geometric mean',646,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 647,5,'ang',0,0,'Anglian Water ',647,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 648,5,'bou',0,0,'Bristol Water ',648,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 649,5,'brw',0,0,'Bournemouth & West hants ',649,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 650,5,'caw',0,0,'Cambridge Water ',650,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 651,5,'cho',0,0,'Cholderton Water ',651,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 652,5,'dcc',0,0,'Dee Valley Water ',652,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 653,5,'eas',0,0,'Welsh Water ',653,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 654,5,'ess',0,0,'Essex and Suffolk Water ',654,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 655,5,'fol',0,0,'Folkestone & Dover Water ',655,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 656,5,'har',0,0,'Hartlepool Water ',656,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 657,5,'mik',0,0,'Mid Kent Water ',657,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 658,5,'nor',0,0,'Northumbrian Water ',658,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 659,5,'nww',0,0,'Portsmouth Water ',659,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 660,5,'por',0,0,'Sutton & East Surrey Water ',660,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 661,5,'sea',0,0,'South East Water ',661,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 662,5,'sev',0,0,'Southern Water ',662,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 663,5,'sos',0,0,'South Staffordshire Water ',663,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 664,5,'sou',0,0,'Severn Trent Water ',664,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 665,5,'sww',0,0,'South West Water ',665,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 666,5,'teh',0,0,'Tendring Hundred Water ',666,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 667,5,'tha',0,0,'Thames Water ',667,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 668,5,'thr',0,0,'Three Valleys Water ',668,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 669,5,'wes',0,0,'United Utilties (North West Water) ',669,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 670,5,'wrx',0,0,'Wessex Water ',670,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 671,5,'yor',0,0,'Yorkshire Water',671,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1 ) 304,112,1 48,13 1,1,1,1,1,1,0,0,0,0 2,370,45,476,445 2,518,523,725,303,0,MIDM 2,404,34,750,516,0,MIDM 39325,65535,39321 [L_j,L_i] [L_j,L_i] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(O_i,O_j)( 1,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 2,'Op_en2693','Testvariable','kg',1,2693,1, 3,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 4,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 5,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 6,'Ppmconc_bustraffic','PM2.5 concentration from bus traffic in Helsinki in 2020','ug/m3',1,0,0, 7,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 8,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 9,'Fig_3_cost_by_source','Cost by source','e/trip',1,0,0, 10,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 11,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 12,'Fig_5c_expanding','Societal costs at different levels of guarantee','e/day',1,0,0, 13,'Bw1','Human body weight in Harjavalta','kg',1,2475,1, 14,'Testvariable2','Another variable for testing','kg',1,0,0, 15,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 16,'Op_en1900','Pollutant health risk due to the consumption of salmon','avoided cases/a',1,1900,1, 17,'Op_en1903','Persistent pollutant concentrations in salmon','µg/kg',1,1903,1, 18,'Op_en1905','Exposure to persistent pollutants due to salmon in the population of the Western Europe','µg/kg/d',1,1905,1, 19,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 20,'Op_en1907','Omega-3 content in salmon','g/g',1,1907,1, 21,'Op_en1908','Omega-3 intake due to salmon in the population of the Western Europe','g/d',1,1908,1, 22,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 23,'Op_en1911','Cardiovascular mortality in the Western Europe','cases/a',1,1911,1, 24,'Op_en1912','Cardiovascular effects of omega-3 in salmon in teh Western Europe','avoided cases/a',1,1912,1, 25,'Op_en1898','Recommendation for consumption of farmed salmon','-',1,1898,1, 26,'Op_en1899','Pollutant concentration limits for fish feed','-',1,1899,1, 27,'Op_en1902','Persistent pollutant concentrations in fish feed','fraction',1,1902,1, 28,'Op_en1904','Salmon intake in the population of the Western Europe','g/d',1,1904,1, 29,'Op_en1909','ERF of omega-3 fatty acids on cardiovascular effects','1/(g/d)',1,1909,1, 30,'Op_en2556','Personal exposures to volatile organic compounds in Germany','ug/m^3',1,2556,1, 31,'Op_en2406','Excess cases of iMetHb in England and Wales','number',1,2406,1, 33,'Decision','Possible range of decisions for a single decision-maker','-',2,2496,1, 34,'Health_impact','Health impact','',2,2495,1, 35,'Time','Time','s or date',2,2497,1, 36,'Pollutant','Pollutant','-',2,2493,1, 37,'Spatial_location','Spatial location',' km or °',2,2498,1, 38,'Length','Length','km',2,2498,1, 39,'Non_health_impact','Non-health impact','-',2,2500,1, 40,'Period','Period','s',2,2497,1, 41,'Emission_source','Emission source','-',2,2492,1, 42,'Environ_compartment','Environmental compartment','-',2,2490,1, 43,'Vehicle_type','Vehicle type','-',2,0,0, 44,'Person_or_group','Person or group','-',2,2499,1, 45,'Transport_mode','Transport mode','-',2,0,0, 46,'Cost_type','Cost type','-',2,0,0, 47,'Composite_fraction','Composite fraction','fraction',2,0,0, 48,'Age','Age','a',2,2497,1, 49,'Municipality_fin','Municipalities in Finland','-',2,2498,1, 51,'Food_source','The method for food production','-',2,0,0, 52,'Feed_pollutant','Decision about fish feed','-',2,0,0, 53,'Salmon_recomm','Decision about samon consumption recommendation','-',2,0,0, 32,'0','No dimension has been identified','-',2,0,0, 54,'Parameter','Statistical and other parameters of a variable','-',2,0,0, 55,'Salmon_decision','','',6,0,0, 56,'Hma_area','','',6,0,0, 57,'Hma_region','','',6,0,0, 58,'Hma_zone','','',6,0,0, 59,'Year_1','','',6,0,0, 60,'Op_en2665','Cause of death 1','ICD-10',6,2665,1, 61,'Year_2','','',6,0,0, 62,'Cause_of_death_2','','',6,0,0, 63,'Length_1','','',6,0,0, 70,'Output_1','','',6,0,0, 65,'Period_1','','',6,0,0, 86,'Run','','',6,0,0, 71,'Vehicle_noch','','',6,0,0, 72,'Stakeholder_1','','',6,0,0, 73,'Mode1','','',6,0,0, 74,'Cost_structure_1','','',6,0,0, 75,'Comp_fr_1','','',6,0,0, 76,'Age1','','',6,0,0, 77,'Municipality_fin1','','',6,0,0, 82,'Year3','','',6,0,0, 81,'Recommendation1','','',6,0,0, 80,'Reg_poll','','',6,0,0, 79,'Salmon1','','',6,0,0, 78,'Pollutant1','','',6,0,0, 83,'H1899','','',6,0,0, 84,'H1898','','',6,0,0, 85,'Cause_of_death3','','',6,0,0, 87,'Condb_compartment1','','',6,0,0, 88,'Condb_location1','','',6,0,0, 89,'Condb_agent1','','',6,0,0, 90,'Condb_param1','','',6,0,0, 91,'Condb_agent2','','',6,0,0, 92,'Vehicle_1','','',6,0,0, 93,'Op_en2672','','',6,0,0, 94,'94','Analytica','',9,0,0, 95,'95','Analytica 4.1.0.9','',9,0,0, 97,'97','Analytica 4.1.0.9, CompositeTraffic_1_0_6.ana v. 11:47, 1000 iterations','',9,0,0, 99,'99','Analytica 4.1.0.9, RDB connection.ANA, 100 iterations','',9,0,0, 100,'100','RDB connection.ANA v. 1.9.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 100','',9,0,0, 101,'101','RDB connection.ANA v. 2.9.2008. Test data only., Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 100','',9,0,0, 102,'102','RDB connection.ANA v. 3.9.2008 b. Test data only., Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 100','',9,0,0, 103,'103','Farmed salmon.ANA 10:36, 31 December 2007, RDB connection.ANA 13:58, 3 September 2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 1000','',9,0,0, 104,'104','Farmed salmon.ANA 10:36, 31 December 2007, RDB connection.ANA 13:58, 3 September 2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 1000','',9,0,0, 105,'105','Farmed salmon.ANA 10:36, 31 December 2007, RDB connection.ANA 13:58, 3 September 2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 1000','',9,0,0, 106,'106','Farmed salmon.ANA 10:36, 31 December 2007, RDB connection.ANA 13:58, 3 September 2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 10','',9,0,0, 107,'107','Farmed salmon.ANA 8.9.2008, RDB connection.ANA 8.9.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 10','',9,0,0, 108,'108','Farmed salmon.ANA 8.9.2008, RDB connection.ANA 8.9.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 1000','',9,0,0, 98,'98','Test','',9,0,0, 109,'109',' CompositeTraffic_1_0_6.ANA 16.9.2008, RDB connection.ANA 16.9.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 10','',9,0,0, 110,'110',' CompositeTraffic_1_0_6.ANA 16.9.2008, RDB connection.ANA 16.9.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 1000','',9,0,0, 111,'111','RDB connection.ANA 16.9.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 100','',9,0,0, 112,'112','RDB connection.ANA 9.10.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 100','',9,0,0, 113,'113','RDB connection.ANA 9.10.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 10','',9,0,0, 114,'Op_en2694','RDB connection.ANA 9.10.2008, Edition: Enterprise, Platform: Windows, Version: 40100, Samplesize: 10',0,9,0,0 ) 304,136,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,152,162,1057,343,0,MIDM 2,573,21,700,421,0,MIDM 39325,65535,39321 [O_j,O_i] [O_j,O_i] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(S_i,S_j)( 1,33,1, 2,37,1, 3,37,1, 4,37,1, 5,35,1, 6,34,1, 7,35,1, 8,34,1, 9,38,1, 10,39,1, 11,40,1, 12,32,1, 13,43,1, 14,44,1, 15,45,1, 16,46,1, 17,47,1, 18,48,1, 19,49,1, 20,35,1, 21,33,1, 22,33,1, 23,51,1, 24,36,1, 25,33,1, 26,33,1, 27,34,1, 28,42,1, 29,37,1, 30,36,1, 31,54,1, 32,36,1, 33,43,1, 34,37,1 ) 304,208,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [S_j,S_i] [S_i,S_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(R_i,R_j)( 1,58,1,27, 2,58,2,28, 3,58,3,29, 4,57,1,30, 5,57,2,31, 6,57,3,32, 7,57,4,33, 8,57,5,34, 9,57,6,35, 10,57,7,36, 11,57,8,37, 12,57,9,38, 13,57,10,39, 14,57,11,40, 15,57,12,41, 16,57,13,42, 17,57,14,43, 18,57,15,44, 19,56,1,45, 20,56,2,46, 21,56,3,47, 22,56,4,48, 23,56,5,49, 24,56,6,50, 25,56,7,51, 26,56,8,52, 27,56,9,53, 28,56,10,54, 29,56,11,55, 30,56,12,56, 31,56,13,57, 32,56,14,58, 33,56,15,59, 34,56,16,60, 35,56,17,61, 36,56,18,62, 37,56,19,63, 38,56,20,64, 39,56,21,65, 40,56,22,66, 41,56,23,67, 42,56,24,68, 43,56,25,69, 44,56,26,70, 45,56,27,71, 46,56,28,72, 47,56,29,73, 48,56,30,74, 49,56,31,75, 50,56,32,76, 51,56,33,77, 52,56,34,78, 53,56,35,79, 54,56,36,80, 55,56,37,81, 56,56,38,82, 57,56,39,83, 58,56,40,84, 59,56,41,85, 60,56,42,86, 61,56,43,87, 62,56,44,88, 63,56,45,89, 64,56,46,90, 65,56,47,91, 66,56,48,92, 67,56,49,93, 68,56,50,94, 69,56,51,95, 70,56,52,96, 71,56,53,97, 72,56,54,98, 73,56,55,99, 74,56,56,100, 75,56,57,101, 76,56,58,102, 77,56,59,103, 78,56,60,104, 79,56,61,105, 80,56,62,106, 81,56,63,107, 82,56,64,108, 83,56,65,109, 84,56,66,110, 85,56,67,111, 86,56,68,112, 87,56,69,113, 88,56,70,114, 89,56,71,115, 90,56,72,116, 91,56,73,117, 92,56,74,118, 93,56,75,119, 94,56,76,120, 95,56,77,121, 96,56,78,122, 97,56,79,123, 98,56,80,124, 99,56,81,125, 100,56,82,126, 101,56,83,127, 102,56,84,128, 103,56,85,129, 104,56,86,130, 105,56,87,131, 106,56,88,132, 107,56,89,133, 108,56,90,134, 109,56,91,135, 110,56,92,136, 111,56,93,137, 112,56,94,138, 113,56,95,139, 114,56,96,140, 115,56,97,141, 116,56,98,142, 117,56,99,143, 118,56,100,144, 119,56,101,145, 120,56,102,146, 121,56,103,147, 122,56,104,148, 123,56,105,149, 124,56,106,150, 125,56,107,151, 126,56,108,152, 127,56,109,153, 128,56,110,154, 129,56,111,155, 130,56,112,156, 131,56,113,157, 132,56,114,158, 133,56,115,159, 134,56,116,160, 135,56,117,161, 136,56,118,162, 137,56,119,163, 138,56,120,164, 139,56,121,165, 140,56,122,166, 141,56,123,167, 142,56,124,168, 143,56,125,169, 144,56,126,170, 145,56,127,171, 146,56,128,172, 147,56,129,173, 148,56,130,174, 149,55,1,1, 150,55,2,2, 151,55,3,3, 152,55,4,4, 153,59,1,7, 154,59,2,8, 155,60,1,10, 156,60,2,11, 157,60,3,12, 158,61,1,175, 159,61,2,176, 160,61,3,177, 161,61,4,178, 162,61,5,179, 163,61,6,180, 164,61,7,181, 165,61,8,182, 166,61,9,183, 167,61,10,184, 168,61,11,185, 169,61,12,186, 170,61,13,187, 171,61,14,188, 172,61,15,189, 173,61,16,190, 174,61,17,191, 175,61,18,192, 176,61,19,193, 177,61,20,194, 178,61,21,8, 179,62,1,10, 180,62,2,11, 181,62,3,12, 182,62,4,26, 183,63,1,196, 184,63,2,197, 185,65,1,198, 186,65,3,200, 187,66,85,285, 188,66,84,284, 189,66,83,283, 190,66,82,282, 191,66,81,281, 192,65,2,199, 193,66,80,280, 194,66,79,279, 195,66,78,278, 196,66,77,277, 197,66,76,276, 198,66,75,275, 199,66,74,274, 200,66,73,273, 201,66,72,272, 202,66,71,271, 203,66,70,270, 204,66,69,269, 205,66,68,268, 206,66,67,267, 207,66,66,266, 208,66,65,265, 209,66,64,264, 210,66,63,263, 211,66,62,262, 212,66,61,261, 213,66,60,260, 214,66,59,259, 215,66,58,258, 216,66,57,257, 217,66,56,256, 218,66,55,255, 219,66,54,254, 220,66,53,253, 221,66,52,252, 222,66,51,251, 223,66,50,250, 224,66,49,249, 225,66,48,248, 226,66,47,247, 227,66,46,246, 228,66,45,245, 229,66,44,244, 230,66,43,243, 231,66,42,242, 232,66,41,241, 233,66,40,240, 234,66,39,239, 235,66,38,238, 236,66,37,237, 237,66,36,236, 238,66,35,235, 239,66,34,234, 240,66,33,233, 241,66,32,232, 242,66,31,231, 243,66,30,230, 244,66,29,229, 245,66,28,228, 246,66,27,227, 247,66,26,226, 248,66,25,225, 249,66,24,224, 250,66,23,223, 251,66,22,222, 252,66,21,221, 253,66,20,220, 254,66,19,219, 255,66,18,218, 256,66,17,217, 257,66,16,216, 258,66,15,215, 259,66,14,214, 260,66,13,213, 261,66,12,212, 262,66,11,211, 263,66,10,210, 264,66,9,209, 265,66,8,208, 266,66,7,207, 267,66,6,206, 268,66,5,205, 269,66,4,204, 270,66,3,203, 271,66,2,202, 272,66,1,201, 273,71,7,377, 274,71,6,376, 275,71,5,375, 276,71,4,374, 277,71,3,373, 278,71,2,372, 279,71,1,371, 280,66,163,363, 281,66,162,362, 282,66,161,361, 283,66,160,360, 284,66,159,359, 285,66,158,358, 286,66,157,357, 287,66,156,356, 288,66,155,355, 289,66,154,354, 290,66,153,353, 291,66,152,352, 292,66,151,351, 293,66,150,350, 294,66,149,349, 295,66,148,348, 296,66,147,347, 297,66,146,346, 298,66,145,345, 299,66,144,344, 300,66,143,343, 301,66,142,342, 302,66,141,341, 303,66,140,340, 304,66,139,339, 305,66,138,338, 306,66,137,337, 307,66,136,336, 308,66,135,335, 309,66,134,334, 310,66,133,333, 311,66,132,332, 312,66,131,331, 313,66,130,330, 314,66,129,329, 315,66,128,328, 316,66,127,327, 317,66,126,326, 318,66,125,325, 319,66,124,324, 320,66,123,323, 321,66,122,322, 322,66,121,321, 323,66,120,320, 324,66,119,319, 325,66,118,318, 326,66,117,317, 327,66,116,316, 328,66,115,315, 329,66,114,314, 330,66,113,313, 331,66,112,312, 332,66,111,311, 333,66,110,310, 334,66,109,309, 335,66,108,308, 336,66,107,307, 337,66,106,306, 338,66,105,305, 339,66,104,304, 340,66,103,303, 341,66,102,302, 342,66,101,301, 343,66,100,300, 344,66,99,299, 345,66,98,298, 346,66,97,297, 347,66,96,296, 348,66,95,295, 349,66,94,294, 350,66,93,293, 351,66,92,292, 352,66,91,291, 353,66,90,290, 354,66,89,289, 355,66,88,288, 356,66,87,287, 357,66,86,286, 358,73,1,380, 359,72,2,379, 360,72,1,378, 361,74,3,384, 362,74,2,383, 363,74,1,382, 364,73,2,381, 365,70,7,370, 366,70,6,369, 367,70,5,368, 368,70,4,367, 369,70,3,366, 370,70,2,365, 371,70,1,364, 372,74,4,385, 373,74,5,386, 374,74,6,387, 375,74,7,388, 376,74,8,389, 377,74,9,390, 378,75,1,391, 379,75,2,392, 380,75,3,393, 381,75,4,394, 382,75,5,395, 383,75,6,396, 384,75,7,397, 385,75,8,398, 386,75,9,399, 387,75,10,400, 388,75,11,401, 389,75,12,402, 390,75,13,403, 391,76,1,404, 392,76,2,405, 393,77,1,406, 394,78,1,407, 395,78,2,408, 396,78,3,409, 397,78,4,410, 398,79,1,411, 399,79,2,412, 400,79,3,413, 401,80,1,414, 402,80,2,415, 403,81,1,416, 404,81,2,417, 405,82,1,175, 406,83,1,418, 407,83,2,419, 408,84,1,418, 409,84,2,421, 410,85,1,422, 411,87,1,423, 412,87,2,424, 413,87,3,425, 414,87,4,426, 415,87,5,427, 416,87,6,428, 417,87,7,429, 418,87,8,430, 419,87,9,431, 420,87,10,432, 421,87,11,433, 422,87,12,434, 423,88,1,435, 424,88,2,436, 425,88,3,437, 426,88,4,438, 427,88,5,439, 428,88,6,440, 429,88,7,441, 430,88,8,442, 431,88,9,443, 432,88,10,444, 433,88,11,445, 434,88,12,446, 435,88,13,447, 436,88,14,448, 437,88,15,449, 438,88,16,450, 439,88,17,451, 440,88,18,452, 441,88,19,453, 442,88,20,454, 443,88,21,455, 444,88,22,456, 445,88,23,457, 446,88,24,458, 447,88,25,459, 448,88,26,460, 449,88,27,461, 450,88,28,462, 451,88,29,463, 452,88,30,464, 453,88,31,465, 454,88,32,466, 455,88,33,467, 456,88,34,468, 457,88,35,469, 458,88,36,470, 459,88,37,471, 460,88,38,472, 461,88,39,473, 462,88,40,474, 463,88,41,475, 464,88,42,476, 465,88,43,477, 466,88,44,478, 467,88,45,479, 468,89,1,480, 469,89,2,481, 470,89,3,482, 471,89,4,483, 472,89,5,484, 473,89,6,485, 474,89,7,486, 475,89,8,487, 476,89,9,488, 477,89,10,489, 478,89,11,490, 479,89,12,491, 480,89,13,492, 481,89,14,493, 482,89,15,494, 483,89,16,495, 484,89,17,496, 485,89,18,497, 486,89,19,498, 487,89,20,499, 488,89,21,500, 489,89,22,501, 490,89,23,502, 491,89,24,503, 492,89,25,504, 493,89,26,505, 494,89,27,506, 495,89,28,507, 496,89,29,508, 497,89,30,509, 498,89,31,510, 499,89,32,511, 500,89,33,512, 501,89,34,513, 502,89,35,514, 503,89,36,515, 504,89,37,516, 505,89,38,517, 506,89,39,518, 507,89,40,519, 508,89,41,520, 509,89,42,521, 510,89,43,522, 511,89,44,523, 512,89,45,524, 513,89,46,525, 514,89,47,526, 515,89,48,527, 516,89,49,528, 517,89,50,529, 518,89,51,530, 519,89,52,531, 520,89,53,532, 521,89,54,533, 522,89,55,534, 523,89,56,535, 524,89,57,536, 525,89,58,537, 526,89,59,538, 527,89,60,539, 528,89,61,540, 529,89,62,541, 530,89,63,542, 531,89,64,543, 532,89,65,544, 533,89,66,545, 534,89,67,546, 535,89,68,547, 536,89,69,548, 537,89,70,549, 538,89,71,550, 539,89,72,551, 540,89,73,552, 541,89,74,553, 542,89,75,554, 543,89,76,555, 544,89,77,556, 545,89,78,557, 546,89,79,558, 547,89,80,559, 548,89,81,560, 549,89,82,561, 550,89,83,562, 551,89,84,563, 552,89,85,564, 553,89,86,565, 554,89,87,566, 555,89,88,567, 556,89,89,568, 557,89,90,569, 558,89,91,570, 559,89,92,571, 560,89,93,572, 561,89,94,573, 562,89,95,574, 563,89,96,575, 564,89,97,576, 565,89,98,577, 566,89,99,578, 567,89,100,579, 568,89,101,580, 569,89,102,581, 570,89,103,582, 571,89,104,583, 572,89,105,584, 573,89,106,585, 574,89,107,586, 575,89,108,587, 576,89,109,588, 577,89,110,589, 578,89,111,590, 579,89,112,591, 580,89,113,592, 581,89,114,593, 582,89,115,594, 583,89,116,595, 584,89,117,596, 585,89,118,597, 586,89,119,598, 587,89,120,599, 588,89,121,600, 589,89,122,601, 590,89,123,602, 591,89,124,603, 592,89,125,604, 593,89,126,605, 594,89,127,606, 595,89,128,607, 596,89,129,608, 597,89,130,609, 598,89,131,610, 599,89,132,611, 600,89,133,612, 601,89,134,613, 602,89,135,614, 603,89,136,615, 604,89,137,616, 605,89,138,617, 606,89,139,618, 607,89,140,619, 608,89,141,620, 609,89,142,621, 610,89,143,622, 611,89,144,623, 612,89,145,624, 613,89,146,625, 614,89,147,626, 615,89,148,627, 616,89,149,628, 617,89,150,629, 618,89,151,630, 619,89,152,631, 620,89,153,632, 621,89,154,633, 622,89,155,634, 623,89,156,635, 624,89,157,636, 625,89,158,637, 626,89,159,638, 627,94,6,652, 628,94,5,651, 629,94,4,650, 630,94,3,649, 631,94,2,648, 632,94,1,647, 633,90,1,639, 634,90,2,640, 635,90,3,641, 636,90,4,642, 637,90,5,643, 638,90,6,644, 639,90,7,645, 640,90,8,646, 641,94,7,653, 642,94,8,654, 643,94,9,655, 644,94,10,656, 645,94,11,657, 646,94,12,658, 647,94,13,659, 648,94,14,660, 649,94,15,661, 650,94,16,662, 651,94,17,663, 652,94,18,664, 653,94,19,665, 654,94,20,666, 655,94,21,667, 656,94,22,668, 657,94,23,669, 658,94,24,670, 659,94,25,671 ) 304,184,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [R_j,R_i] [R_i,R_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(It_i,It_j)( 1,1,55,0, 2,2,56,0, 3,2,57,0, 4,2,58,0, 5,5,59,0, 6,6,60,0, 7,5,61,0, 8,6,62,0, 9,9,63,0, 10,11,65,0, 11,10,70,0, 12,13,71,0, 13,14,72,0, 14,15,73,0, 15,16,74,0, 16,17,75,0, 17,18,76,0, 18,19,77,0, 19,24,78,0, 20,23,79,0, 21,1,80,0, 22,1,81,0, 23,5,82,0, 24,1,83,0, 25,1,84,0, 26,6,85,0, 27,12,86,0, 28,28,87,0, 29,2,88,0, 30,24,89,0, 31,31,90,0, 32,24,91,0, 33,13,92,0, 34,2,93,0 ) 304,160,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [It_j,It_i] [It_i,It_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] Table(D_i,D_j)( 43,'Vehicle_type','Vehicle type', 45,'Transport_mode','Transport mode', 46,'Cost_type','Cost type', 47,'Composite_fraction','Composite fraction', 51,'Food_source','The method for food production', 52,'Feed_pollutant','Decision about fish feed', 53,'Salmon_recomm','Decision about samon consumption recommendation', 32,'0','No dimension has been identified', 54,'Parameter','Statistical and other parameters of a variable', 42,'Environ_compartment','Environmental compartment', 41,'Emission_source','Emission source', 36,'Pollutant','Pollutant', 34,'Health_impact','Health impact', 33,'Decision','Possible range of decisions for a single decision-maker', 35,'Time','Time', 40,'Period','Period', 48,'Age','Age', 37,'Spatial_location','Spatial location', 38,'Length','Length', 49,'Municipality_fin','Municipalities in Finland', 44,'Person_or_group','Person or group', 39,'Non_health_impact','Non-health impact' ) 304,240,1 48,13 1,1,1,1,1,1,0,0,0,0 2,89,98,476,224 2,604,56,556,489,0,MIDM 39325,65535,39321 [D_i,D_j] [D_j,D_i] Table(I_i,I_j)( 55,'Salmon_decision','',33,'Decision','Possible range of decisions for a single decision-maker', 80,'Reg_poll','',33,'Decision','Possible range of decisions for a single decision-maker', 81,'Recommendation1','',33,'Decision','Possible range of decisions for a single decision-maker', 83,'H1899','',33,'Decision','Possible range of decisions for a single decision-maker', 84,'H1898','',33,'Decision','Possible range of decisions for a single decision-maker', 56,'Hma_area','',37,'Spatial_location','Spatial location', 57,'Hma_region','',37,'Spatial_location','Spatial location', 58,'Hma_zone','',37,'Spatial_location','Spatial location', 88,'Condb_location1','',37,'Spatial_location','Spatial location', 93,'Op_en2672','',37,'Spatial_location','Spatial location', 59,'Year_1','',35,'Time','Time', 61,'Year_2','',35,'Time','Time', 82,'Year3','',35,'Time','Time', 60,'Cause_of_death_1','',34,'Health_impact','Health impact', 62,'Cause_of_death_2','',34,'Health_impact','Health impact', 85,'Cause_of_death3','',34,'Health_impact','Health impact', 63,'Length_1','',38,'Length','Length', 70,'Output_1','',39,'Non_health_impact','Non-health impact', 65,'Period_1','',40,'Period','Period', 86,'Run','',32,'0','No dimension has been identified', 71,'Vehicle_noch','',43,'Vehicle_type','Vehicle type', 92,'Vehicle_1','',43,'Vehicle_type','Vehicle type', 72,'Stakeholder_1','',44,'Person_or_group','Person or group', 73,'Mode1','',45,'Transport_mode','Transport mode', 74,'Cost_structure_1','',46,'Cost_type','Cost type', 75,'Comp_fr_1','',47,'Composite_fraction','Composite fraction', 76,'Age1','',48,'Age','Age', 77,'Municipality_fin1','',49,'Municipality_fin','Municipalities in Finland', 79,'Salmon1','',51,'Food_source','The method for food production', 78,'Pollutant1','',36,'Pollutant','Pollutant', 89,'Condb_agent1','',36,'Pollutant','Pollutant', 91,'Condb_agent2','',36,'Pollutant','Pollutant', 87,'Condb_compartment1','',42,'Environ_compartment','Environmental compartment', 90,'Condb_param1','',54,'Parameter','Statistical and other parameters of a variable' ) 304,264,1 48,13 1,1,1,1,1,1,0,0,0,0 2,380,47,476,296 2,232,242,874,303,0,MIDM 2,209,67,876,493,0,MIDM 39325,65535,39321 [I_j,I_i] [I_j,I_i] Table(L_i,L_j)( 1,1,'Business as usual',0,0,'',1,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 2,1,'Recommend restrictions to salmon consumption',0,0,'',2,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 3,1,'Stricter limits for fish feed pollutants',0,0,'',3,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 4,1,'Restrictions to salmon consumption AND stricter fish feed limits',0,0,'',4,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 26,2,'All causes',0,0,'',26,'Testvariable','Variable used for testing','kmh',1,0,0, 197,6,'>= 5 km',0,0,'',197,'Ppmconc_bustraffic','PM2.5 concentration from bus traffic in Helsinki in 2020','ug/m3',1,0,0, 196,6,'< 5 km',0,0,'',196,'Ppmconc_bustraffic','PM2.5 concentration from bus traffic in Helsinki in 2020','ug/m3',1,0,0, 8,3,'2020',0,0,'',8,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 7,3,'1997',0,0,'',7,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 10,2,'Cardiopulmonary',0,0,'',10,'Testvariable','Variable used for testing','kmh',1,0,0, 11,2,'Lung ca',0,0,'',11,'Testvariable','Variable used for testing','kmh',1,0,0, 12,2,'All others',0,0,'',12,'Testvariable','Variable used for testing','kmh',1,0,0, 27,5,'Downtown',0,0,'',27,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 28,5,'Centre',0,0,'',28,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 29,5,'Suburb',0,0,'',29,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 30,5,'Länsi-Espoo',0,0,'',30,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 31,5,'Pohjois-Espoo',0,0,'',31,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 32,5,'Etelä-Espoo',0,0,'',32,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 33,5,'Keski-Espoo',0,0,'',33,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 34,5,'Länsi-Vantaa',0,0,'',34,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 35,5,'Keski-Vantaa',0,0,'',35,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 36,5,'Pohjois-Vantaa',0,0,'',36,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 37,5,'Itä-Vantaa',0,0,'',37,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 38,5,'Kanta-Helsinki',0,0,'',38,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 39,5,'Länsi-Helsinki',0,0,'',39,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 40,5,'Vanha-Helsinki',0,0,'',40,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 41,5,'Konalanseutu',0,0,'',41,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 42,5,'Pakilanseutu',0,0,'',42,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 43,5,'Malminseutu',0,0,'',43,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 44,5,'Itä-Helsinki',0,0,'',44,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 45,5,'1001',0,0,'',45,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 46,5,'1002',0,0,'',46,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 47,5,'1003',0,0,'',47,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 48,5,'1004',0,0,'',48,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 49,5,'1005',0,0,'',49,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 50,5,'1006',0,0,'',50,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 51,5,'1007',0,0,'',51,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 52,5,'1008',0,0,'',52,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 53,5,'1009',0,0,'',53,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 54,5,'1010',0,0,'',54,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 55,5,'1011',0,0,'',55,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 56,5,'1012',0,0,'',56,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 57,5,'1013',0,0,'',57,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 58,5,'1014',0,0,'',58,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 59,5,'1015',0,0,'',59,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 60,5,'1016',0,0,'',60,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 61,5,'1017',0,0,'',61,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 62,5,'1018',0,0,'',62,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 63,5,'1019',0,0,'',63,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 64,5,'1020',0,0,'',64,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 65,5,'1021',0,0,'',65,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 66,5,'1022',0,0,'',66,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 67,5,'1023',0,0,'',67,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 68,5,'1024',0,0,'',68,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 69,5,'1025',0,0,'',69,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 70,5,'1026',0,0,'',70,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 71,5,'1027',0,0,'',71,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 72,5,'1028',0,0,'',72,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 73,5,'1029',0,0,'',73,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 74,5,'1030',0,0,'',74,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 75,5,'1031',0,0,'',75,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 76,5,'1032',0,0,'',76,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 77,5,'1033',0,0,'',77,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 78,5,'1034',0,0,'',78,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 79,5,'1035',0,0,'',79,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 80,5,'1036',0,0,'',80,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 81,5,'1037',0,0,'',81,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 82,5,'1038',0,0,'',82,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 83,5,'1039',0,0,'',83,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 84,5,'1040',0,0,'',84,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 85,5,'1041',0,0,'',85,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 86,5,'1042',0,0,'',86,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 87,5,'1043',0,0,'',87,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 88,5,'1044',0,0,'',88,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 89,5,'1045',0,0,'',89,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 90,5,'1046',0,0,'',90,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 91,5,'1047',0,0,'',91,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 92,5,'1048',0,0,'',92,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 93,5,'1049',0,0,'',93,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 94,5,'1050',0,0,'',94,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 95,5,'1051',0,0,'',95,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 96,5,'1052',0,0,'',96,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 97,5,'1053',0,0,'',97,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 98,5,'1054',0,0,'',98,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 99,5,'1055',0,0,'',99,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 100,5,'1056',0,0,'',100,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 101,5,'1057',0,0,'',101,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 102,5,'1058',0,0,'',102,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 103,5,'1059',0,0,'',103,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 104,5,'1060',0,0,'',104,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 105,5,'1061',0,0,'',105,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 106,5,'1062',0,0,'',106,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 107,5,'1063',0,0,'',107,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 108,5,'1064',0,0,'',108,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 109,5,'1065',0,0,'',109,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 110,5,'1066',0,0,'',110,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 111,5,'1067',0,0,'',111,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 112,5,'1068',0,0,'',112,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 113,5,'1069',0,0,'',113,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 114,5,'1070',0,0,'',114,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 115,5,'1071',0,0,'',115,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 116,5,'1072',0,0,'',116,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 117,5,'1073',0,0,'',117,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 118,5,'1074',0,0,'',118,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 119,5,'1075',0,0,'',119,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 120,5,'1076',0,0,'',120,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 121,5,'1077',0,0,'',121,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 122,5,'1078',0,0,'',122,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 123,5,'1079',0,0,'',123,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 124,5,'1080',0,0,'',124,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 125,5,'1081',0,0,'',125,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 126,5,'1082',0,0,'',126,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 127,5,'1083',0,0,'',127,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 128,5,'1084',0,0,'',128,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 129,5,'1085',0,0,'',129,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 130,5,'1086',0,0,'',130,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 131,5,'1087',0,0,'',131,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 132,5,'1088',0,0,'',132,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 133,5,'1089',0,0,'',133,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 134,5,'1090',0,0,'',134,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 135,5,'1091',0,0,'',135,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 136,5,'1092',0,0,'',136,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 137,5,'1093',0,0,'',137,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 138,5,'1094',0,0,'',138,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 139,5,'1095',0,0,'',139,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 140,5,'1096',0,0,'',140,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 141,5,'1097',0,0,'',141,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 142,5,'1098',0,0,'',142,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 143,5,'1099',0,0,'',143,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 144,5,'1100',0,0,'',144,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 145,5,'1101',0,0,'',145,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 146,5,'1102',0,0,'',146,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 147,5,'1103',0,0,'',147,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 148,5,'1104',0,0,'',148,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 149,5,'1105',0,0,'',149,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 150,5,'1106',0,0,'',150,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 151,5,'1107',0,0,'',151,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 152,5,'1108',0,0,'',152,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 153,5,'1109',0,0,'',153,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 154,5,'1110',0,0,'',154,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 155,5,'1111',0,0,'',155,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 156,5,'1112',0,0,'',156,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 157,5,'1113',0,0,'',157,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 158,5,'1114',0,0,'',158,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 159,5,'1115',0,0,'',159,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 160,5,'1116',0,0,'',160,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 161,5,'1117',0,0,'',161,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 162,5,'1118',0,0,'',162,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 163,5,'1119',0,0,'',163,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 164,5,'1120',0,0,'',164,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 165,5,'1121',0,0,'',165,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 166,5,'1122',0,0,'',166,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 167,5,'1123',0,0,'',167,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 168,5,'1124',0,0,'',168,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 169,5,'1125',0,0,'',169,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 170,5,'1126',0,0,'',170,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 171,5,'1127',0,0,'',171,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 172,5,'1128',0,0,'',172,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 173,5,'1129',0,0,'',173,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 174,5,'1130',0,0,'',174,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 175,3,'2000',0,0,'',175,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 176,3,'2001',0,0,'',176,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 177,3,'2002',0,0,'',177,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 178,3,'2003',0,0,'',178,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 179,3,'2004',0,0,'',179,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 180,3,'2005',0,0,'',180,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 181,3,'2006',0,0,'',181,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 182,3,'2007',0,0,'',182,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 183,3,'2008',0,0,'',183,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 184,3,'2009',0,0,'',184,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 185,3,'2010',0,0,'',185,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 186,3,'2011',0,0,'',186,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 187,3,'2012',0,0,'',187,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 188,3,'2013',0,0,'',188,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 189,3,'2014',0,0,'',189,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 190,3,'2015',0,0,'',190,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 191,3,'2016',0,0,'',191,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 192,3,'2017',0,0,'',192,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 193,3,'2018',0,0,'',193,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 194,3,'2019',0,0,'',194,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 418,1,'BAU',0,0,'',418,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 198,8,' 6.00-20.00',0,0,'',198,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 199,8,'20.00-24.00',0,0,'',199,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 200,8,' 0.00- 6.00',0,0,'',200,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 364,7,'Trips',0,0,'',364,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 365,7,'Trips by vehicle',0,0,'',365,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 366,7,'Vehicle km',0,0,'',366,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 367,7,'Parking lot',0,0,'',367,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 368,7,'Link intensity',0,0,'',368,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 369,7,'Vehicles',0,0,'',369,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 370,7,'Waiting',0,0,'',370,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 371,11,'Bus no change',0,0,'',371,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 372,11,'Bus one change',0,0,'',372,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 373,11,'Cab no change',0,0,'',373,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 374,11,'Cab one change',0,0,'',374,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 375,11,'Cab non-full',0,0,'',375,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 376,11,'Car',0,0,'',376,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 377,11,'No-change',0,0,'',377,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 378,12,'Passenger',0,0,'',378,'Fig_5c_expanding','Societal costs at different levels of guarantee','e/day',1,0,0, 379,12,'Society',0,0,'',379,'Fig_5c_expanding','Societal costs at different levels of guarantee','e/day',1,0,0, 380,13,'Car',0,0,'',380,'Bw1','Human body weight in Harjavalta','kg',1,2475,1, 381,13,'Composite',0,0,'',381,'Bw1','Human body weight in Harjavalta','kg',1,2475,1, 382,14,'Vehicle',0,0,'',382,'Testvariable2','Another variable for testing','kg',1,0,0, 383,14,'Driver',0,0,'',383,'Testvariable2','Another variable for testing','kg',1,0,0, 384,14,'Driving',0,0,'',384,'Testvariable2','Another variable for testing','kg',1,0,0, 385,14,'Parking',0,0,'',385,'Testvariable2','Another variable for testing','kg',1,0,0, 386,14,'Parking land',0,0,'',386,'Testvariable2','Another variable for testing','kg',1,0,0, 387,14,'Emissions',0,0,'',387,'Testvariable2','Another variable for testing','kg',1,0,0, 388,14,'Time',0,0,'',388,'Testvariable2','Another variable for testing','kg',1,0,0, 389,14,'Accidents',0,0,'',389,'Testvariable2','Another variable for testing','kg',1,0,0, 390,14,'Ticket',0,0,'',390,'Testvariable2','Another variable for testing','kg',1,0,0, 391,15,'0',0,0,'',391,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 392,15,'0.02',0,0,'',392,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 393,15,'0.05',0,0,'',393,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 394,15,'0.1',0,0,'',394,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 395,15,'0.25',0,0,'',395,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 396,15,'0.4',0,0,'',396,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 397,15,'0.45',0,0,'',397,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 398,15,'0.5',0,0,'',398,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 399,15,'0.55',0,0,'',399,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 400,15,'0.65',0,0,'',400,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 401,15,'0.75',0,0,'',401,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 402,15,'0.9',0,0,'',402,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 403,15,'1',0,0,'',403,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 404,16,'18-65',0,0,'',404,'Op_en1900','Pollutant health risk due to the consumption of salmon','avoided cases/a',1,1900,1, 405,16,'3',0,0,'',405,'Op_en1900','Pollutant health risk due to the consumption of salmon','avoided cases/a',1,1900,1, 406,17,'Harjavalta',0,0,'',406,'Op_en1903','Persistent pollutant concentrations in salmon','µg/kg',1,1903,1, 407,4,'Dieldrin',0,0,'',407,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 408,4,'Toxaphene',0,0,'',408,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 409,4,'Dioxin',0,0,'',409,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 410,4,'PCB',0,0,'',410,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 411,19,'Farmed salmon',0,0,'',411,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 412,19,'Wild salmon',0,0,'',412,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 413,19,'Market salmon',0,0,'',413,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 414,20,'BAU',0,0,'',414,'Op_en1907','Omega-3 content in salmon','g/g',1,1907,1, 415,20,'More actions',0,0,'',415,'Op_en1907','Omega-3 content in salmon','g/g',1,1907,1, 416,21,'BAU',0,0,'',416,'Op_en1908','Omega-3 intake due to salmon in the population of the Western Europe','g/d',1,1908,1, 417,21,'Restrict farmed salmon use',0,0,'',417,'Op_en1908','Omega-3 intake due to salmon in the population of the Western Europe','g/d',1,1908,1, 419,1,'More actions',0,0,'',419,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 421,1,'Restrict farmed salmon use',0,0,'',421,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 422,2,'Cardiovascular',0,0,'',422,'Testvariable','Variable used for testing','kmh',1,0,0, 423,10,'Home indoor',0,0,'Abbreviation in the Concentration database: I',423,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 424,10,'(Home) outdoor',0,0,'Abbreviation in the Concentration database: O',424,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 425,10,'(Personal) Work',0,0,'Abbreviation in the Concentration database: W',425,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 426,10,'Personal',0,0,'Abbreviation in the Concentration database: P',426,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 427,10,'Drinking water',0,0,'Abbreviation in the Concentration database: DW',427,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 428,10,'Indoor dust',0,0,'Abbreviation in the Concentration database: ID',428,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 429,10,'Human',0,0,'Abbreviation in the Concentration database: H',429,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 430,10,'Soil',0,0,'Abbreviation in the Concentration database: S',430,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 431,10,'Beverage',0,0,'Abbreviation in the Concentration database: B',431,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 432,10,'Food',0,0,'Abbreviation in the Concentration database: F',432,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 433,10,'In-Vehicle',0,0,'Abbreviation in the Concentration database: IV',433,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 434,10,'School',0,0,'Abbreviation in the Concentration database: SC',434,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 435,5,'Athens',0,0,'Country: Greece. Abbreviation in the Concentration Database: A',435,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 436,5,'Antwerp',0,0,'Country: Belgium. Abbreviation in the Concentration Database: ANT',436,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 437,5,'Antioch-Pittsburg',0,0,'Country: USA. Abbreviation in the Concentration Database: AP',437,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 438,5,'Antioch-Pittsburg A-P',0,0,'Country: USA. Abbreviation in the Concentration Database: A-P',438,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 439,5,'Arizona',0,0,'Country: USA. Abbreviation in the Concentration Database: AZ',439,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 440,5,'Basel',0,0,'Country: Germany. Abbreviation in the Concentration Database: B',440,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 441,5,'Baltimore',0,0,'Country: USA. Abbreviation in the Concentration Database: BAL',441,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 442,5,'Bayonne',0,0,'Country: USA. Abbreviation in the Concentration Database: BAY',442,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 443,5,'Bayonne-Ellizabeth',0,0,'Country: USA. Abbreviation in the Concentration Database: BE',443,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 444,5,'Copenhagen',0,0,'Country: Denmark. Abbreviation in the Concentration Database: C',444,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 445,5,'California',0,0,'Country: USA. Abbreviation in the Concentration Database: CA',445,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 446,5,'Columbus',0,0,'Country: USA. Abbreviation in the Concentration Database: CO',446,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 447,5,'Daegu',0,0,'Country: South Korea. Abbreviation in the Concentration Database: D',447,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 448,5,'Devils Lake',0,0,'Country: USA. Abbreviation in the Concentration Database: DLA',448,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 449,5,'Dublin',0,0,'Country: Ireland. Abbreviation in the Concentration Database: DU',449,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 450,5,'Elizabeth',0,0,'Country: USA. Abbreviation in the Concentration Database: ELI',450,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 451,5,'EPA Region 5.',0,0,'Country: USA. Abbreviation in the Concentration Database: EPA5',451,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 452,5,'Flanders',0,0,'Country: Belgium. Abbreviation in the Concentration Database: FLA',452,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 453,5,'Florence',0,0,'Country: Italy. Abbreviation in the Concentration Database: FL',453,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 454,5,'Grenoble',0,0,'Country: France. Abbreviation in the Concentration Database: G',454,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 455,5,'Germany',0,0,'Country: Germany. Abbreviation in the Concentration Database: GE',455,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 456,5,'Genoa',0,0,'Country: Italy. Abbreviation in the Concentration Database: GEN',456,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 457,5,'Greensboro GNC',0,0,'Country: USA. Abbreviation in the Concentration Database: GNC',457,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 458,5,'Greensboro',0,0,'Country: USA. Abbreviation in the Concentration Database: GRB',458,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 460,5,'Helsinki',0,0,'Country: Finland. Abbreviation in the Concentration Database: H',460,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 461,5,'Hannover',0,0,'Country: Germany. Abbreviation in the Concentration Database: HA',461,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 462,5,'Ile de France',0,0,'Country: France. Abbreviation in the Concentration Database: IDF',462,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 463,5,'Los Angeles',0,0,'Country: USA. Abbreviation in the Concentration Database: LA',463,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 464,5,'Milan',0,0,'Country: Italy. Abbreviation in the Concentration Database: M',464,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 465,5,'Minneapolis',0,0,'Country: USA. Abbreviation in the Concentration Database: MP',465,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 466,5,'Minnesota',0,0,'Country: USA. Abbreviation in the Concentration Database: MS',466,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 467,5,'Murcia',0,0,'Country: Spain. Abbreviation in the Concentration Database: MU',467,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 468,5,'Mexico City',0,0,'Country: Mexico. Abbreviation in the Concentration Database: MXC',468,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 469,5,'Oxford',0,0,'Country: England. Abbreviation in the Concentration Database: O',469,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 470,5,'Prague',0,0,'Country: Czech. Abbreviation in the Concentration Database: P',470,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 471,5,'Padua',0,0,'Country: Italy. Abbreviation in the Concentration Database: PA',471,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 472,5,'Puebla',0,0,'Country: Mexico. Abbreviation in the Concentration Database: PB',472,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 473,5,'Rouen',0,0,'Country: France. Abbreviation in the Concentration Database: R',473,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 475,5,'Strasbourg',0,0,'Country: France. Abbreviation in the Concentration Database: STR',475,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 476,5,'Umbria region',0,0,'Country: Italy. Abbreviation in the Concentration Database: UMB',476,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 477,5,'United States',0,0,'Country: USA. Abbreviation in the Concentration Database: USA',477,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 478,5,'Valdez',0,0,'Country: USA. Abbreviation in the Concentration Database: VAL',478,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 479,5,'Woodland',0,0,'Country: USA. Abbreviation in the Concentration Database: WDL',479,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 480,4,'66-25-1',0,0,'hexanal',480,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 481,4,'71-36-3',0,0,'1-butanol',481,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 482,4,'71-43-2',0,0,'benzene',482,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 483,4,'78-83-1',0,0,'2-methyl-1-propanol',483,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 484,4,'79-00-5',0,0,'1,1,2-trichloroethane',484,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 485,4,'79-01-6',0,0,'trichloroethene',485,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 486,4,'80-56-8',0,0,'alfa-pinene',486,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 487,4,'91-20-3',0,0,'naphtalene',487,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 488,4,'95-47-6',0,0,'o-xylene',488,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 489,4,'95-63-6',0,0,'trimethylbenzenes',489,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 490,4,'100-41-4',0,0,'ethylbenzene',490,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 491,4,'100-42-5',0,0,'styrene',491,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 492,4,'100-52-7',0,0,'benzaldehyde',492,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 493,4,'103-65-1',0,0,'propylbenzene',493,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 494,4,'104-76-7',0,0,'2-ethylhexanol',494,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 495,4,'108-38-3',0,0,'m(&p)-xylene',495,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 496,4,'108-88-3',0,0,'toluene',496,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 497,4,'108-95-2',0,0,'phenol',497,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 498,4,'110-54-3',0,0,'hexane',498,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 499,4,'110-82-7',0,0,'cyclohexane',499,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 500,4,'111-76-2',0,0,'ethanol, 2-butoxy-',500,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 501,4,'111-84-2',0,0,'nonane',501,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 502,4,'111-87-5',0,0,'1-octanol',502,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 503,4,'124-13-0',0,0,'octanal',503,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 504,4,'124-18-5',0,0,'decane',504,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 505,4,'127-18-4',0,0,'tetrachloroethene',505,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 506,4,'138-86-3',0,0,'d-limonene',506,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 507,4,'872-50-4',0,0,'2-pyrrolidinone, 1-methyl-',507,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 508,4,'1120-21-4',0,0,'undecane',508,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 509,4,'13466-78-9',0,0,'3-caren',509,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 510,4,'TVOC',0,0,'Toluene based total VOC',510,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 511,4,'67-66-3',0,0,'chloroform',511,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 512,4,'106-46-7',0,0,'1,4-dichlorobenzene',512,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 514,4,'56-23-5',0,0,'carbon tetrachloride',514,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 515,4,'75-09-2',0,0,'methylene chloride',515,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 517,4,'127-91-3',0,0,'b-pinene',517,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 520,4,'142-82-5',0,0,'n-heptane',520,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 521,4,'111-65-9',0,0,'n-octane',521,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 525,4,'112-40-3',0,0,'n-dodecane',525,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 526,4,'629-50-5',0,0,'n-tridecane',526,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 527,4,'629-59-4',0,0,'n-tetradecane',527,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 528,4,'629-62-9',0,0,'n-pentadecane',528,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 529,4,'107-83-5',0,0,'2-methylpentane',529,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 530,4,'96-14-0',0,0,'3-methylpentane',530,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 531,4,'565-59-3',0,0,'2,3-dimethylpentane',531,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 532,4,'591-76-4',0,0,'2-methylhexane',532,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 533,4,'589-34-4',0,0,'3-methylhexane',533,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 534,4,'592-27-8',0,0,'2-methylheptane',534,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 535,4,'589-81-1',0,0,'3-methylheptane',535,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 536,4,'96-37-7',0,0,'methylcyclopentane',536,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 537,4,'108-87-2',0,0,'methylcyclohexane',537,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 538,4,'526-73-8',0,0,'1,2,3-trimethylbenzene',538,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 540,4,'108-67-8',0,0,'1,3,5 trimethylbenzene',540,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 541,4,'4994-16-5',0,0,'4-phenylcyclohexene',541,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 542,4,'1,1,1-trichloroethane',0,0,'1,1,1-trichloroethane',542,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 545,4,'141-78-6',0,0,'ethylacetate',545,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 546,4,'123-86-4',0,0,'n-butylacetate',546,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 547,4,'78-93-3',0,0,'methyl ethyl ketone',547,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 548,4,'106-35-4',0,0,'3-heptatone',548,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 549,4,'93-58-3',0,0,'methyl benzoate',549,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 552,4,'123-51-3',0,0,'iso-amyl alcohol^a',552,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 554,4,'67-63-0',0,0,'2-propanol^a',554,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 555,4,'1634-04-4',0,0,'t-butyl methylether',555,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 556,4,'7439-92-1',0,0,'lead',556,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 557,4,'7440-38-2',0,0,'arsenic',557,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 558,4,'7440-43-9',0,0,'cadmium',558,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 559,4,'7440-39-3',0,0,'barium',559,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 560,4,'7440-47-3',0,0,'chrome',560,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 561,4,'7440-50-8',0,0,'copper',561,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 562,4,'7439-96-5',0,0,'manganese',562,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 563,4,'7440-02-0',0,0,'nickel',563,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 564,4,'7782-49-2',0,0,'selenium',564,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 565,4,'7440-62-2',0,0,'vanadium',565,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 566,4,'7440-66-6',0,0,'zinc',566,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 567,4,'71-55-6',0,0,'1,1,1-trichloroethane',567,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 568,4,'7439-97-6',0,0,'mercury',568,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 570,4,'60-27-5',0,0,'creatinine',570,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 571,4,'7429-90-5',0,0,'aluminium',571,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 572,4,'7440-70-2',0,0,'calcium',572,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 573,4,'7439-95-4',0,0,'magnesium',573,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 574,4,'7723-14-0',0,0,'phosphorus',574,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 575,4,'7440-24-6',0,0,'strontium',575,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 576,4,'7439-89-6',0,0,'iron',576,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 577,4,'7440-09-7',0,0,'potassium',577,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 578,4,'7440-23-5',0,0,'sodium',578,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 579,4,'58-89-9',0,0,'lindane',579,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 580,4,'52645-53-1',0,0,'permenthrine',580,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 581,4,'107-13-1',0,0,'acrylonitrile',581,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 582,4,'79-06-1',0,0,'acrylamide',582,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 589,4,'611-14-3',0,0,'1-ethyl 2methyl benzene',589,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 592,4,'109-66-0',0,0,'n-pentane',592,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 593,4,'7785-26-4',0,0,'alpha-pinene',593,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 594,4,'5989-27-5',0,0,'d-limonene',594,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 596,4,'106-99-0',0,0,'butadiene',596,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 597,4,'74-84-0',0,0,'ethane',597,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 598,4,'74-85-1',0,0,'ethylene',598,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 599,4,'74-86-2',0,0,'acetylene',599,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 600,4,'107-06-2',0,0,'1,2-dichloroethane',600,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 601,4,'106-42-3',0,0,'p-xylene',601,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 603,4,'98-82-8',0,0,'isopropylbenzene',603,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 604,4,'110-86-1',0,0,'pyridine',604,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 606,4,'109-06-8',0,0,'2-picoline',606,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 608,4,'108-99-6',0,0,'3-picoline',608,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 609,4,'108-89-4',0,0,'4-picoline',609,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 610,4,'104-51-8',0,0,'n-butylbenzene',610,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 611,4,'536-78-7',0,0,'3-ethylpyridine',611,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 613,4,'25551-13-7',0,0,'trimethylbenzene',613,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 618,4,'1336-36-3',0,0,'PCBs',618,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 619,4,'3547-04-4',0,0,'DDE',619,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 620,4,'118-74-1',0,0,'HCB',620,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 621,4,'5315-79-7',0,0,'1-hydroxypyrene',621,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 623,4,'1330-20-7',0,0,'xylenes',623,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 624,4,'37210-16-5',0,0,'CO2',624,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 625,4,'630-08-0',0,0,'CO',625,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 626,4,'54-11-5',0,0,'nicotine',626,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 628,4,'3588-17-8',0,0,'trans,trans-Muconic acid',628,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 629,4,'50-32-8',0,0,'benzo(a)pyrene',629,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 631,4,'590-86-3',0,0,'isovaleraldehyde',631,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 632,4,'123-38-6',0,0,'propionaldehyde',632,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 633,4,'123-72-8',0,0,'n-butyraldehyde',633,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 634,4,'75-07-0',0,0,'acetaldehyde',634,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 636,4,'50-00-0',0,0,'formaldehyde',636,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 637,4,'110-62-3',0,0,'valeraldehyde',637,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 638,4,'4170-30-3',0,0,'crotonaldehyde',638,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 639,22,'n',0,0,'Number of observations',639,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 640,22,'n_lt_LOQ',0,0,'Number of observations below level of quantitation',640,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 641,22,'F0.10',0,0,'Fractile 0.1',641,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 642,22,'F0.50',0,0,'Fractile 0.5',642,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 643,22,'F0.90',0,0,'Fractile 0.9',643,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 644,22,'F0.95',0,0,'Fractile 0.95',644,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 645,22,'Mean',0,0,'Arithmetic mean',645,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 646,22,'GeoMean',0,0,'Geometric mean',646,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 647,5,'ang',0,0,'Anglian Water ',647,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 648,5,'bou',0,0,'Bristol Water ',648,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 649,5,'brw',0,0,'Bournemouth & West hants ',649,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 650,5,'caw',0,0,'Cambridge Water ',650,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 651,5,'cho',0,0,'Cholderton Water ',651,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 652,5,'dcc',0,0,'Dee Valley Water ',652,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 653,5,'eas',0,0,'Welsh Water ',653,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 654,5,'ess',0,0,'Essex and Suffolk Water ',654,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 655,5,'fol',0,0,'Folkestone & Dover Water ',655,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 656,5,'har',0,0,'Hartlepool Water ',656,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 657,5,'mik',0,0,'Mid Kent Water ',657,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 658,5,'nor',0,0,'Northumbrian Water ',658,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 659,5,'nww',0,0,'Portsmouth Water ',659,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 660,5,'por',0,0,'Sutton & East Surrey Water ',660,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 661,5,'sea',0,0,'South East Water ',661,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 662,5,'sev',0,0,'Southern Water ',662,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 663,5,'sos',0,0,'South Staffordshire Water ',663,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 664,5,'sou',0,0,'Severn Trent Water ',664,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 665,5,'sww',0,0,'South West Water ',665,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 666,5,'teh',0,0,'Tendring Hundred Water ',666,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 667,5,'tha',0,0,'Thames Water ',667,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 668,5,'thr',0,0,'Three Valleys Water ',668,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 669,5,'wes',0,0,'United Utilties (North West Water) ',669,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 670,5,'wrx',0,0,'Wessex Water ',670,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 671,5,'yor',0,0,'Yorkshire Water',671,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1 ) 304,288,1 48,13 1,1,1,1,1,1,0,0,0,0 2,370,45,476,445 2,404,34,750,516,0,MIDM 39325,65535,39321 [L_j,L_i] [L_j,L_i] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(O_i,O_j)( 2,'Testvariable','Variable used for testing','kmh',1,0,0, 6,'Ppmconc_bustraffic','PM2.5 concentration from bus traffic in Helsinki in 2020','ug/m3',1,0,0, 8,'Comptraf_scenoutput','Composite traffic v.1 scenario outputs','various',1,0,0, 9,'Fig_3_cost_by_source','Cost by source','e/trip',1,0,0, 10,'Fig_5a_societal_cost','Societal cost','e/day',1,0,0, 11,'Fig_5b_subsidies','Subsidies needed to obtain the composite fraction objective','e/day',1,0,0, 12,'Fig_5c_expanding','Societal costs at different levels of guarantee','e/day',1,0,0, 14,'Testvariable2','Another variable for testing','kg',1,0,0, 15,'Testvariable3','Testvariable 3: Another variable for testing','kg',1,0,0, 25,'Op_en1898','Recommendation for consumption of farmed salmon','-',1,1898,1, 26,'Op_en1899','Pollutant concentration limits for fish feed','-',1,1899,1, 16,'Op_en1900','Pollutant health risk due to the consumption of salmon','avoided cases/a',1,1900,1, 1,'Op_en1901','Net health effects due to the consumption of salmon','avoided cases/a',1,1901,1, 27,'Op_en1902','Persistent pollutant concentrations in fish feed','fraction',1,1902,1, 17,'Op_en1903','Persistent pollutant concentrations in salmon','µg/kg',1,1903,1, 28,'Op_en1904','Salmon intake in the population of the Western Europe','g/d',1,1904,1, 18,'Op_en1905','Exposure to persistent pollutants due to salmon in the population of the Western Europe','µg/kg/d',1,1905,1, 19,'Op_en1906','Dose-response function of persistent pollutants','(mg/kg/d)-1',1,1906,1, 20,'Op_en1907','Omega-3 content in salmon','g/g',1,1907,1, 21,'Op_en1908','Omega-3 intake due to salmon in the population of the Western Europe','g/d',1,1908,1, 29,'Op_en1909','ERF of omega-3 fatty acids on cardiovascular effects','1/(g/d)',1,1909,1, 22,'Op_en1910','Total mortality in the Western Europe','cases/a',1,1910,1, 23,'Op_en1911','Cardiovascular mortality in the Western Europe','cases/a',1,1911,1, 24,'Op_en1912','Cardiovascular effects of omega-3 in salmon in teh Western Europe','avoided cases/a',1,1912,1, 3,'Op_en2201','The mortality due to PM 2.5 from buses','premature deaths',1,2201,1, 7,'Op_en2202','Concentration-response to PM2.5','m3/ug',1,2202,1, 5,'Op_en2204','Primary PM2.5 emissions from bus traffic in Helsinki Metropolitan Area','kg/a',1,2204,1, 4,'Op_en2205','Bus engine technology','see wiki page',1,2205,1, 31,'Op_en2406','Excess cases of iMetHb in England and Wales','number',1,2406,1, 13,'Bw1','Human body weight in Harjavalta','kg',1,2475,1, 30,'Op_en2556','Personal exposures to volatile organic compounds in Germany','ug/m^3',1,2556,1, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0, 0,0,0,0,0,0,0 ) 304,312,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,152,162,1057,343,0,MIDM 2,529,143,700,421,0,MIDM 39325,65535,39321 [O_j,O_i] [O_j,O_i] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(S_i,S_j)( 1,33,1, 2,37,1, 3,37,1, 4,37,1, 5,35,1, 6,34,1, 7,35,1, 8,34,1, 9,38,1, 10,39,1, 11,40,1, 12,32,1, 13,43,1, 14,44,1, 15,45,1, 16,46,1, 17,47,1, 18,48,1, 19,49,1, 20,35,1, 21,33,1, 22,33,1, 23,51,1, 24,36,1, 25,33,1, 26,33,1, 27,34,1, 28,42,1, 29,37,1, 30,36,1, 31,54,1, 32,36,1, 33,43,1, 34,37,1 ) 304,384,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [S_j,S_i] [S_i,S_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(R_i,R_j)( 1,58,1,27, 2,58,2,28, 3,58,3,29, 4,57,1,30, 5,57,2,31, 6,57,3,32, 7,57,4,33, 8,57,5,34, 9,57,6,35, 10,57,7,36, 11,57,8,37, 12,57,9,38, 13,57,10,39, 14,57,11,40, 15,57,12,41, 16,57,13,42, 17,57,14,43, 18,57,15,44, 19,56,1,45, 20,56,2,46, 21,56,3,47, 22,56,4,48, 23,56,5,49, 24,56,6,50, 25,56,7,51, 26,56,8,52, 27,56,9,53, 28,56,10,54, 29,56,11,55, 30,56,12,56, 31,56,13,57, 32,56,14,58, 33,56,15,59, 34,56,16,60, 35,56,17,61, 36,56,18,62, 37,56,19,63, 38,56,20,64, 39,56,21,65, 40,56,22,66, 41,56,23,67, 42,56,24,68, 43,56,25,69, 44,56,26,70, 45,56,27,71, 46,56,28,72, 47,56,29,73, 48,56,30,74, 49,56,31,75, 50,56,32,76, 51,56,33,77, 52,56,34,78, 53,56,35,79, 54,56,36,80, 55,56,37,81, 56,56,38,82, 57,56,39,83, 58,56,40,84, 59,56,41,85, 60,56,42,86, 61,56,43,87, 62,56,44,88, 63,56,45,89, 64,56,46,90, 65,56,47,91, 66,56,48,92, 67,56,49,93, 68,56,50,94, 69,56,51,95, 70,56,52,96, 71,56,53,97, 72,56,54,98, 73,56,55,99, 74,56,56,100, 75,56,57,101, 76,56,58,102, 77,56,59,103, 78,56,60,104, 79,56,61,105, 80,56,62,106, 81,56,63,107, 82,56,64,108, 83,56,65,109, 84,56,66,110, 85,56,67,111, 86,56,68,112, 87,56,69,113, 88,56,70,114, 89,56,71,115, 90,56,72,116, 91,56,73,117, 92,56,74,118, 93,56,75,119, 94,56,76,120, 95,56,77,121, 96,56,78,122, 97,56,79,123, 98,56,80,124, 99,56,81,125, 100,56,82,126, 101,56,83,127, 102,56,84,128, 103,56,85,129, 104,56,86,130, 105,56,87,131, 106,56,88,132, 107,56,89,133, 108,56,90,134, 109,56,91,135, 110,56,92,136, 111,56,93,137, 112,56,94,138, 113,56,95,139, 114,56,96,140, 115,56,97,141, 116,56,98,142, 117,56,99,143, 118,56,100,144, 119,56,101,145, 120,56,102,146, 121,56,103,147, 122,56,104,148, 123,56,105,149, 124,56,106,150, 125,56,107,151, 126,56,108,152, 127,56,109,153, 128,56,110,154, 129,56,111,155, 130,56,112,156, 131,56,113,157, 132,56,114,158, 133,56,115,159, 134,56,116,160, 135,56,117,161, 136,56,118,162, 137,56,119,163, 138,56,120,164, 139,56,121,165, 140,56,122,166, 141,56,123,167, 142,56,124,168, 143,56,125,169, 144,56,126,170, 145,56,127,171, 146,56,128,172, 147,56,129,173, 148,56,130,174, 149,55,1,1, 150,55,2,2, 151,55,3,3, 152,55,4,4, 153,59,1,7, 154,59,2,8, 155,60,1,10, 156,60,2,11, 157,60,3,12, 158,61,1,175, 159,61,2,176, 160,61,3,177, 161,61,4,178, 162,61,5,179, 163,61,6,180, 164,61,7,181, 165,61,8,182, 166,61,9,183, 167,61,10,184, 168,61,11,185, 169,61,12,186, 170,61,13,187, 171,61,14,188, 172,61,15,189, 173,61,16,190, 174,61,17,191, 175,61,18,192, 176,61,19,193, 177,61,20,194, 178,61,21,8, 179,62,1,10, 180,62,2,11, 181,62,3,12, 182,62,4,26, 183,63,1,196, 184,63,2,197, 185,65,1,198, 186,65,3,200, 187,66,85,285, 188,66,84,284, 189,66,83,283, 190,66,82,282, 191,66,81,281, 192,65,2,199, 193,66,80,280, 194,66,79,279, 195,66,78,278, 196,66,77,277, 197,66,76,276, 198,66,75,275, 199,66,74,274, 200,66,73,273, 201,66,72,272, 202,66,71,271, 203,66,70,270, 204,66,69,269, 205,66,68,268, 206,66,67,267, 207,66,66,266, 208,66,65,265, 209,66,64,264, 210,66,63,263, 211,66,62,262, 212,66,61,261, 213,66,60,260, 214,66,59,259, 215,66,58,258, 216,66,57,257, 217,66,56,256, 218,66,55,255, 219,66,54,254, 220,66,53,253, 221,66,52,252, 222,66,51,251, 223,66,50,250, 224,66,49,249, 225,66,48,248, 226,66,47,247, 227,66,46,246, 228,66,45,245, 229,66,44,244, 230,66,43,243, 231,66,42,242, 232,66,41,241, 233,66,40,240, 234,66,39,239, 235,66,38,238, 236,66,37,237, 237,66,36,236, 238,66,35,235, 239,66,34,234, 240,66,33,233, 241,66,32,232, 242,66,31,231, 243,66,30,230, 244,66,29,229, 245,66,28,228, 246,66,27,227, 247,66,26,226, 248,66,25,225, 249,66,24,224, 250,66,23,223, 251,66,22,222, 252,66,21,221, 253,66,20,220, 254,66,19,219, 255,66,18,218, 256,66,17,217, 257,66,16,216, 258,66,15,215, 259,66,14,214, 260,66,13,213, 261,66,12,212, 262,66,11,211, 263,66,10,210, 264,66,9,209, 265,66,8,208, 266,66,7,207, 267,66,6,206, 268,66,5,205, 269,66,4,204, 270,66,3,203, 271,66,2,202, 272,66,1,201, 273,71,7,377, 274,71,6,376, 275,71,5,375, 276,71,4,374, 277,71,3,373, 278,71,2,372, 279,71,1,371, 280,66,163,363, 281,66,162,362, 282,66,161,361, 283,66,160,360, 284,66,159,359, 285,66,158,358, 286,66,157,357, 287,66,156,356, 288,66,155,355, 289,66,154,354, 290,66,153,353, 291,66,152,352, 292,66,151,351, 293,66,150,350, 294,66,149,349, 295,66,148,348, 296,66,147,347, 297,66,146,346, 298,66,145,345, 299,66,144,344, 300,66,143,343, 301,66,142,342, 302,66,141,341, 303,66,140,340, 304,66,139,339, 305,66,138,338, 306,66,137,337, 307,66,136,336, 308,66,135,335, 309,66,134,334, 310,66,133,333, 311,66,132,332, 312,66,131,331, 313,66,130,330, 314,66,129,329, 315,66,128,328, 316,66,127,327, 317,66,126,326, 318,66,125,325, 319,66,124,324, 320,66,123,323, 321,66,122,322, 322,66,121,321, 323,66,120,320, 324,66,119,319, 325,66,118,318, 326,66,117,317, 327,66,116,316, 328,66,115,315, 329,66,114,314, 330,66,113,313, 331,66,112,312, 332,66,111,311, 333,66,110,310, 334,66,109,309, 335,66,108,308, 336,66,107,307, 337,66,106,306, 338,66,105,305, 339,66,104,304, 340,66,103,303, 341,66,102,302, 342,66,101,301, 343,66,100,300, 344,66,99,299, 345,66,98,298, 346,66,97,297, 347,66,96,296, 348,66,95,295, 349,66,94,294, 350,66,93,293, 351,66,92,292, 352,66,91,291, 353,66,90,290, 354,66,89,289, 355,66,88,288, 356,66,87,287, 357,66,86,286, 358,73,1,380, 359,72,2,379, 360,72,1,378, 361,74,3,384, 362,74,2,383, 363,74,1,382, 364,73,2,381, 365,70,7,370, 366,70,6,369, 367,70,5,368, 368,70,4,367, 369,70,3,366, 370,70,2,365, 371,70,1,364, 372,74,4,385, 373,74,5,386, 374,74,6,387, 375,74,7,388, 376,74,8,389, 377,74,9,390, 378,75,1,391, 379,75,2,392, 380,75,3,393, 381,75,4,394, 382,75,5,395, 383,75,6,396, 384,75,7,397, 385,75,8,398, 386,75,9,399, 387,75,10,400, 388,75,11,401, 389,75,12,402, 390,75,13,403, 391,76,1,404, 392,76,2,405, 393,77,1,406, 394,78,1,407, 395,78,2,408, 396,78,3,409, 397,78,4,410, 398,79,1,411, 399,79,2,412, 400,79,3,413, 401,80,1,414, 402,80,2,415, 403,81,1,416, 404,81,2,417, 405,82,1,175, 406,83,1,418, 407,83,2,419, 408,84,1,418, 409,84,2,421, 410,85,1,422, 411,87,1,423, 412,87,2,424, 413,87,3,425, 414,87,4,426, 415,87,5,427, 416,87,6,428, 417,87,7,429, 418,87,8,430, 419,87,9,431, 420,87,10,432, 421,87,11,433, 422,87,12,434, 423,88,1,435, 424,88,2,436, 425,88,3,437, 426,88,4,438, 427,88,5,439, 428,88,6,440, 429,88,7,441, 430,88,8,442, 431,88,9,443, 432,88,10,444, 433,88,11,445, 434,88,12,446, 435,88,13,447, 436,88,14,448, 437,88,15,449, 438,88,16,450, 439,88,17,451, 440,88,18,452, 441,88,19,453, 442,88,20,454, 443,88,21,455, 444,88,22,456, 445,88,23,457, 446,88,24,458, 447,88,25,459, 448,88,26,460, 449,88,27,461, 450,88,28,462, 451,88,29,463, 452,88,30,464, 453,88,31,465, 454,88,32,466, 455,88,33,467, 456,88,34,468, 457,88,35,469, 458,88,36,470, 459,88,37,471, 460,88,38,472, 461,88,39,473, 462,88,40,474, 463,88,41,475, 464,88,42,476, 465,88,43,477, 466,88,44,478, 467,88,45,479, 468,89,1,480, 469,89,2,481, 470,89,3,482, 471,89,4,483, 472,89,5,484, 473,89,6,485, 474,89,7,486, 475,89,8,487, 476,89,9,488, 477,89,10,489, 478,89,11,490, 479,89,12,491, 480,89,13,492, 481,89,14,493, 482,89,15,494, 483,89,16,495, 484,89,17,496, 485,89,18,497, 486,89,19,498, 487,89,20,499, 488,89,21,500, 489,89,22,501, 490,89,23,502, 491,89,24,503, 492,89,25,504, 493,89,26,505, 494,89,27,506, 495,89,28,507, 496,89,29,508, 497,89,30,509, 498,89,31,510, 499,89,32,511, 500,89,33,512, 501,89,34,513, 502,89,35,514, 503,89,36,515, 504,89,37,516, 505,89,38,517, 506,89,39,518, 507,89,40,519, 508,89,41,520, 509,89,42,521, 510,89,43,522, 511,89,44,523, 512,89,45,524, 513,89,46,525, 514,89,47,526, 515,89,48,527, 516,89,49,528, 517,89,50,529, 518,89,51,530, 519,89,52,531, 520,89,53,532, 521,89,54,533, 522,89,55,534, 523,89,56,535, 524,89,57,536, 525,89,58,537, 526,89,59,538, 527,89,60,539, 528,89,61,540, 529,89,62,541, 530,89,63,542, 531,89,64,543, 532,89,65,544, 533,89,66,545, 534,89,67,546, 535,89,68,547, 536,89,69,548, 537,89,70,549, 538,89,71,550, 539,89,72,551, 540,89,73,552, 541,89,74,553, 542,89,75,554, 543,89,76,555, 544,89,77,556, 545,89,78,557, 546,89,79,558, 547,89,80,559, 548,89,81,560, 549,89,82,561, 550,89,83,562, 551,89,84,563, 552,89,85,564, 553,89,86,565, 554,89,87,566, 555,89,88,567, 556,89,89,568, 557,89,90,569, 558,89,91,570, 559,89,92,571, 560,89,93,572, 561,89,94,573, 562,89,95,574, 563,89,96,575, 564,89,97,576, 565,89,98,577, 566,89,99,578, 567,89,100,579, 568,89,101,580, 569,89,102,581, 570,89,103,582, 571,89,104,583, 572,89,105,584, 573,89,106,585, 574,89,107,586, 575,89,108,587, 576,89,109,588, 577,89,110,589, 578,89,111,590, 579,89,112,591, 580,89,113,592, 581,89,114,593, 582,89,115,594, 583,89,116,595, 584,89,117,596, 585,89,118,597, 586,89,119,598, 587,89,120,599, 588,89,121,600, 589,89,122,601, 590,89,123,602, 591,89,124,603, 592,89,125,604, 593,89,126,605, 594,89,127,606, 595,89,128,607, 596,89,129,608, 597,89,130,609, 598,89,131,610, 599,89,132,611, 600,89,133,612, 601,89,134,613, 602,89,135,614, 603,89,136,615, 604,89,137,616, 605,89,138,617, 606,89,139,618, 607,89,140,619, 608,89,141,620, 609,89,142,621, 610,89,143,622, 611,89,144,623, 612,89,145,624, 613,89,146,625, 614,89,147,626, 615,89,148,627, 616,89,149,628, 617,89,150,629, 618,89,151,630, 619,89,152,631, 620,89,153,632, 621,89,154,633, 622,89,155,634, 623,89,156,635, 624,89,157,636, 625,89,158,637, 626,89,159,638, 627,94,6,652, 628,94,5,651, 629,94,4,650, 630,94,3,649, 631,94,2,648, 632,94,1,647, 633,90,1,639, 634,90,2,640, 635,90,3,641, 636,90,4,642, 637,90,5,643, 638,90,6,644, 639,90,7,645, 640,90,8,646, 641,94,7,653, 642,94,8,654, 643,94,9,655, 644,94,10,656, 645,94,11,657, 646,94,12,658, 647,94,13,659, 648,94,14,660, 649,94,15,661, 650,94,16,662, 651,94,17,663, 652,94,18,664, 653,94,19,665, 654,94,20,666, 655,94,21,667, 656,94,22,668, 657,94,23,669, 658,94,24,670, 659,94,25,671 ) 304,360,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [R_j,R_i] [R_i,R_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(It_i,It_j)( 1,1,55,0, 2,2,56,0, 3,2,57,0, 4,2,58,0, 5,5,59,0, 6,6,60,0, 7,5,61,0, 8,6,62,0, 9,9,63,0, 10,11,65,0, 11,10,70,0, 12,13,71,0, 13,14,72,0, 14,15,73,0, 15,16,74,0, 16,17,75,0, 17,18,76,0, 18,19,77,0, 19,24,78,0, 20,23,79,0, 21,1,80,0, 22,1,81,0, 23,5,82,0, 24,1,83,0, 25,1,84,0, 26,6,85,0, 27,12,86,0, 28,28,87,0, 29,2,88,0, 30,24,89,0, 31,31,90,0, 32,24,91,0, 33,13,92,0, 34,2,93,0 ) 304,336,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [It_j,It_i] [It_i,It_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] This node checks the variables listed in Var_for_rdb and makes an index of those that are NOT found in the result database. This is then used as an index in Inp_var for adding variable information. Table(S_i,S_j)( 1,33,1, 2,37,1, 3,37,1, 4,37,1, 5,35,1, 6,34,1, 7,35,1, 8,34,1, 9,38,1, 10,39,1, 11,40,1, 12,32,1, 13,43,1, 14,44,1, 15,45,1, 16,46,1, 17,47,1, 18,48,1, 19,49,1, 20,35,1, 21,33,1, 22,33,1, 23,51,1, 24,36,1, 25,33,1, 26,33,1, 27,34,1, 28,42,1, 29,37,1, 30,36,1, 31,54,1, 32,36,1, 33,43,1, 34,37,1 ) 304,408,1 48,13 1,1,1,1,1,1,0,0,0,0 2,378,21,493,501 2,529,143,700,421,0,MIDM 39325,65535,39321 [S_j,S_i] [S_i,S_j] ['H1991'] [Self,1,Sys_localindex('I'),1,Sys_localindex('J'),1] 72,296,1 48,12 2,65,110,476,224