{ From user ktluser, Model Claih at 4-kesä-2012 23:17:24 }
SoftwareVersion 4.3.3


{ System Variables with non-default values: }
Time := Sequence( -1, 110, 1 )
Description Time: Dynamic simulation periods are specified in Time's definition. This is usually a list of numbers or labels, typically in some unit of time (days, weeks, months, etc.).  Use the ÒDynamic()Ó function in your variables to perform dynamic simulation.
SampleSize := 6
SampleType := 1
UseTable := 0
{!40000|Att_PrevIndexValue Run: [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]}
TypeChecking := 1
Checking := 1
GraphWindows := 10
ShowHier := 1
SaveOptions := 2
SaveValues := 0
ProbIndex := [0.025,0.05,0.25,0.5,0.75,0.95,0.975]
DistSteps := 1
Naming := 0
AllWarnings := 0
DisplayOutputs Null: ,
{!40000|Att_CatLineStyle Graph_Primary_Valdim: 9}
{!40000|Att_CatLineStyle Graph_Stats_Valdim: 9}
{!40000|Att_GraphValueRange Graph_Pdf_Valdim: 1,0,0,1,,,,0,1}
{!40000|Att_ContLineStyle Graph_Pdf_Valdim: 6}
{!40000|Att_ContLineStyle Graph_Cdf_Valdim: 1}
{!40300|Sys_DomainSelfIndex := 1}

{!40300|ProactivelyEvaluate Index: 1}

Attribute Reference
Attribute Log

AskAttribute Recursive,Function,Yes
AskAttribute Reference,Function,Yes
AskAttribute Log,Function,Yes
AskAttribute Reference,Module,Yes
AskAttribute Log,Module,Yes
AskAttribute Value,Variable,Yes
AskAttribute Check,Variable,Yes
AskAttribute BalloonHelp,Variable,Yes
AskAttribute Reference,Variable,Yes
AskAttribute Log,Variable,Yes

Model Claih
Author: vkoe
Date: 28. Novta 2008 10:15
SaveAuthor: ktluser
SaveDate: 4. Junta 2012 23:17
DefaultSize: 48,24
DiagState: 2,41,6,446,422,17
FontStyle: Arial, 13
FileInfo: 0,Model Claih,2,2,0,0,C:\temp\Claih_model-1.ANA

Module Costs
Title: Costs
Author: vkoe
Date: 25. Janta 2011 13:39
DefaultSize: 48,24
NodeLocation: 272,256,1
NodeSize: 52,28
DiagState: 2,-3,0,864,558,17
NodeColor: 52427,63897,65535

Chance Energy_cost
Title: Energy cost
Units: e / 5 year period
Definition: var a:=Heat_cost_input[Cost='Energy'];~
a:=if House_area_type='All' then a else a[House_area_type=House_area_type];~
var b:=Energy_cost_change;~
b:=  if Energy_price_scen='All' then b else b[ ENergy_price_scen=Energy_price_scen];~
a:=a*b;~
~
var c:=Area_heat_purc;~
c:=if Bioher_sec_heat_scen = 'All' then c else c[Bioher_sec_heat_scen = Bioher_sec_heat_scen];~
~
a:=a*c*5/100;~
~
a:= if Decision_maker='Citizen' then a else a*((100-Energy_tax)/100);~
~
sum(a,heat_system);
NodeLocation: 296,248,1
NodeSize: 48,21
WindState: 2,212,353,476,449
DefnState: 2,154,293,416,303,0,MIDM
ValueState: 2,138,94,609,281,0,MIDM
NodeColor: 19661,48336,65535
ReformDef: [Fu_period,Bioher_pri_heat_scen]
ReformVal: [Fu_period,Bioher_pri_heat_scen,2]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [Heat_system,2,Bioher_pri_heat_scen,3,Fu_period,1]}

Chance Invest_cost
Title: Heat investment cost
Units: e
Description: Lähde: Motiva 2009~
~
Oletukset:~
~
Uudessa rakennuksessa pääasiallinen lämmityslaite sisältyy rakennuslainaan ja kuoletusaika on 30 v. Lämpöpumppu ostetaan kuitenkin kertaostoksena rakennuksen valmistumisen jälkeen.~
~
Vanhassa rakennuksessa otetaan remonttilaina ja kuoletusaika on 10 v. Ilmalämpöpumppu ostetaan kuitenkin kertaostoksena remontin jälkeen.~
~
Kaukolämmön osalta sisältää liittymismaksun
Definition: Var a:=Heat_cost_input[Cost='Investment'];~
a:=sum(a*Prim_heat_sys[Const_year=Const_year],heat_system);~
a:=a[Fu_period=2012];~
~
var b:=a/(30/5);~
b:=if Fu_period < Start_year+30 then b else 0;~
~
var c:=a/(10/5);~
c:=if Fu_period < Start_year+10 then c else 0;~
~
a:= if House_area_type='New' then b[House_area_type='New'] else c[House_area_type='Old'];~
~
b:=Heat_cost_input[Cost='Investment', Heat_system='Air heat pump'];~
b:= if House_area_type='All' then b else b[House_area_type=House_area_type];~
b:= b*Sec_hs;~
b:=b[Bioher_sec_heat_scen='Air heat pump'];~
~
c:=Heat_cost_input[Cost='Investment', Heat_system='Secondary wood'];~
c:= if House_area_type='All' then c else c[House_area_type=House_area_type];~
c:= c*Sec_hs;~
c:=c[Bioher_sec_heat_scen='Wood'];~
~
a:= if Bioher_sec_heat_scen = 'Air heat pump' then a+b else a;~
a:= if Bioher_sec_heat_scen = 'Wood' then a+c else a;~
~
a:=a*Houses_per_area;~
~
if Decision_maker='Citizen' then a else a*((100-Vat)/100)~

NodeLocation: 296,48,1
NodeSize: 48,28
WindState: 2,86,36,553,737
DefnState: 2,151,215,416,303,0,MIDM
ValueState: 2,173,80,619,287,0,MIDM
NodeColor: 19661,48336,65535
ReformDef: [Bioher_sec_heat_scen,Heat_system]
ReformVal: [Fu_period,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [House_area_type,2,Bioher_sec_heat_scen,2,Bioher_pri_heat_scen,1,Fu_period,5]}

Chance Maint_cost
Title: Maintenance cost
Units: e/5 year period
Description: Lähde: rakentaja.fi lämmitysjärjestelmälaskuri
Definition: var a:=Heat_cost_input[Cost='Maintenance'];~
a:= if House_area_type='All' then a else a[House_area_type=House_area_type];~
a:=Triangular(a*0.9, a, a*1.1);~
a:=sum(a*Prim_heat_sys[Const_year=Const_year],heat_system);~
~
var b:=Heat_cost_input[Cost='Maintenance', Heat_system='Air heat pump'];~
b:= if House_area_type='All' then b else b[House_area_type=House_area_type];~
b:= b*Sec_hs;~
b:=b[Bioher_sec_heat_scen='Air heat pump'];~
~
var c:=Heat_cost_input[Cost='Maintenance', Heat_system='Secondary wood'];~
c:= if House_area_type='All' then c else c[House_area_type=House_area_type];~
c:= c*Sec_hs;~
c:=c[Bioher_sec_heat_scen='Wood'];~
~
a:= if Bioher_sec_heat_scen = 'Air heat pump' then a+b else a;~
a:= if Bioher_sec_heat_scen = 'Wood' then a+c else a;~
~
a:=a*5*Houses_per_area;~
~
if Decision_maker='Citizen' then a else a*((100-Vat)/100)
NodeLocation: 296,192,1
NodeSize: 48,24
WindState: 2,918,173,709,701
DefnState: 2,154,213,416,303,0,MIDM
ValueState: 2,629,96,635,303,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Fu_period,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [House_area_type,2,Bioher_pri_heat_scen,1,Fu_period,1]}

Variable Heating_cost
Title: Total heating cost
Units: € / fu period
Definition: var a:= sum((Invest_cost+Investment_interest+Maint_cost+Energy_cost)*Present_value,fu_period);~
~
if Bioher_pri_heat_scen='All' then a else a[Bioher_pri_heat_scen=Bioher_pri_heat_scen]
NodeLocation: 296,352,1
NodeSize: 48,24
WindState: 2,88,115,527,584
ValueState: 2,99,199,463,298,0,MIDM
ReformVal: [Undefined,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [Bioher_pri_heat_scen,3,Sys_LocalIndex('Probability'),1]}

Chance Life_year_unit_cost
Title: Value of a life year
Units: e/life year
Description: Lähde: Desaigues et al. 2011: Economic evaluation of air pollution mortality: a 9-country contingent valuation survey of value of a life year (VOLY). Ecological indicators 11, 902-910)
Definition: Triangular( 25000, 40000, 100000 )
NodeLocation: 416,248,1
NodeSize: 48,24
ValueState: 2,119,134,397,263,0,CONF
NodeColor: 65535,52427,61166

Variable Investment_interest
Title: Investment interest cost
Units: e / 5 year period
Description: Investointilainan kuoletusajaksi oletettu uudella talolla 30 vuotta ja remontoitavalla talolla 10 vuotta, vuosikorko 3,5%.~
~
HUOM! Ei huomioi verotuksen korkovähennystä.
Definition: Var a:=Heat_cost_input[Cost='Investment'];~
a:= if House_area_type='All' then a else a[House_area_type=House_area_type];~
a:=sum(a*Prim_heat_sys[Const_year=Const_year],heat_system);~
~
var b:=Heat_cost_input[Cost='Investment', Heat_system='Air heat pump'];~
b:= if House_area_type='All' then b else b[House_area_type=House_area_type];~
b:= b*Sec_hs;~
b:=b[Bioher_sec_heat_scen='Air heat pump'];~
~
var c:=Heat_cost_input[Cost='Investment', Heat_system='Secondary wood'];~
c:= if House_area_type='All' then c else c[House_area_type=House_area_type];~
c:= c*Sec_hs;~
c:=c[Bioher_sec_heat_scen='Wood'];~
~
a:= if Bioher_sec_heat_scen = 'Air heat pump' then a+b else a;~
a:= if Bioher_sec_heat_scen = 'Wood' then a+c else a;~
~
a:=(a*Houses_per_area)[Fu_period=2012];~
~
if House_area_type='New' then~
~
(b:=a/30;~
a:=a-b*(Fu_year-Start_year);~
a:=if a>0 then a else 0;~
a:=a*(Interest/100);~
sum(if floor((Fu_year-Start_year)/5)+1 = @Fu_period then a else 0 , Fu_year))~
~
else~
~
(b:=a/10;~
a:=a-b*(Fu_year-Start_year);~
a:=if a>0 then a else 0;~
a:=a*(Interest/100);~
sum(if floor((Fu_year-Start_year)/5)+1 = @Fu_period then a else 0 , Fu_year))
NodeLocation: 296,112,1
NodeSize: 48,20
WindState: 2,132,217,718,529
ValueState: 2,105,126,677,303,0,MIDM
ReformVal: [Fu_period,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Fu_period, Index Fu_year
{!40000|Att_ResultSliceState: [Bioher_sec_heat_scen,1,Bioher_pri_heat_scen,1,Fu_period,1]}

Variable Yll_cost
Title: Total cost of lost life years
Units: € / fu period
Definition: var a:= yll_tot;~
a:= sum(a[@sex=1, exposure = 'Alternative'], mort_endpoint_bioher);~
~
sum(a*Life_year_unit_cost*Present_value, fu_period)
NodeLocation: 416,352,1
NodeSize: 48,24
WindState: 2,351,50,476,224
ValueState: 2,441,190,702,593,0,SAMP
ReformVal: [Bioher_pri_heat_scen,Run,1,Undefined,Undefined,2]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [Fu_period,3,Bioher_pri_heat_scen,1,Bioher_sec_heat_scen,1]}

Chance Co2_market_prize
Title: CO2 market price
Units: e/t
Description: Hinnat perustuvat DECC 2009-raporttiin.~
~
Tulevaisuuden hinnat perustuen Covec 2010 -raporttiin:~
~
Table(Fu_period)(~
Fractiles[10,12.5,15,32.5,50],Fractiles[10,15,20,57.5,95],Fractiles[10,17.5,25,100,175],Fractiles[10,23.75,37,124.75,212.5],Fractiles[10,30,50,150,250],Fractiles[10,30,50,150,250])
Definition: Table(Fu_period,Heat_system)(~
Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(12,15,18),Triangular(12,15,18),Triangular(12,15,18),Triangular(37,75,112),Triangular(12,15,18),~
Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(15,23,29),Triangular(15,23,29),Triangular(15,23,29),Triangular(37,75,112),Triangular(15,23,29),~
Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(37,75,112),Triangular(17,31,39),Triangular(17,31,39),Triangular(17,31,39),Triangular(37,75,112),Triangular(17,31,39),~
Triangular(41,81,122),Triangular(41,81,122),Triangular(41,81,122),Triangular(41,81,122),Triangular(41,81,122),Triangular(31,59,85),Triangular(31,59,85),Triangular(31,59,85),Triangular(41,81,122),Triangular(31,59,85),~
Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),Triangular(44,87,131),~
Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192),Triangular(71,128,192)~
)
NodeLocation: 544,248,1
NodeSize: 48,24
DefnState: 2,88,305,901,303,0,MIDM
ValueState: 2,116,143,604,281,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heat_system,Fu_period]
ReformVal: [Fu_period,Heat_system,2]
{!40000|Att_ResultSliceState: [Heat_system,10,Sys_LocalIndex('PROBABILITY'),1,Fu_period,2]}

Variable Co2_cost
Title: CO2 emission cost
Units: € / fu period
Definition: var a:=sum(sum(Co2_emission*Co2_market_prize,heat_system)*Present_value,Fu_period);~
a:=if Bioher_pri_heat_scen='All' then a else a[Bioher_pri_heat_scen=Bioher_pri_heat_scen];~
a:= if Bioher_sec_heat_scen = 'All' then a else a[Bioher_sec_heat_scen = Bioher_sec_heat_scen];~
a~

NodeLocation: 544,352,1
NodeSize: 48,24
WindState: 2,298,354,476,359
ValueState: 2,676,209,526,304,0,MIDM
ReformVal: [Tot_heat_con,Bioher_pri_heat_scen,2]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [Bioher_pri_heat_scen,2,Sys_LocalIndex('Probability'),1]}

Objective Total_cost
Title: total cost
Units: € / fu period
Definition: Heating_cost+yll_cost+Co2_cost
NodeLocation: 672,352,1
NodeSize: 48,24
WindState: 2,98,90,476,224
ValueState: 2,36,43,416,303,0,SAMP
ReformVal: [Bioher_pri_heat_scen,Run,2,Undefined,Undefined,2]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [House_type,1,Sys_LocalIndex('PROBABILITY'),1,Bioher_pri_heat_scen,1]}

Objective Co2
Title: CO2 emiss change
Units: %
Description: Change in CO2 emission compared to BAU scenario
Definition: var a:=sum(sum(Co2_emission,Heat_system),fu_period);~
var b:=a-a[Bioher_pri_heat_scen='BAU'];~
b/a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None']*100~
~

NodeLocation: 544,448,1
NodeSize: 48,23
ValueState: 2,126,350,1138,437,1,MIDM
ReformVal: [Tot_heat_con,Bioher_pri_heat_scen]
{!40000|Att_ResultSliceState: [Heat_system,10,Bioher_pri_heat_scen,1,Tot_heat_con,1]}

Objective Change_heating_cost
Title: Change heating cost
Units: %
Definition: var a:=sum(Heating_cost,fu_period);~
var b:=a-a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None'];~
b/a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None']*100
NodeLocation: 296,448,1
NodeSize: 48,24
ValueState: 2,774,109,693,414,1,MIDM
ReformVal: [Undefined,Bioher_pri_heat_scen]

Objective Change_yll_cost
Title: Change YLL cost
Units: %
Definition: var a:=sum(yll_cost,fu_period);~
var b:=a-a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None'];~
b/a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None']*100
NodeLocation: 416,448,1
NodeSize: 48,24
ValueState: 2,112,154,680,379,1,MIDM
ReformVal: [Bioher_sec_heat_scen,Bioher_pri_heat_scen]

Objective Heating_cost_per_red
Title: Heating cost per reduced CO2 t
Units: e/tCO2
Definition: var a:=sum(Heating_cost,fu_period);~
a:=a-a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None'];~
var b:=sum(Co2_emission[Const_year='2010'],fu_period);~
b:=b[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None']-b;~
a:=a/b;~
if b>0 then a else NAN;~

NodeLocation: 296,536,1
NodeSize: 48,29
WindState: 2,100,382,476,261
ValueState: 2,94,152,799,365,1,MIDM
ReformVal: [Bioher_sec_heat_scen,Bioher_pri_heat_scen]
{!40000|Att_ResultSliceState: [Const_year,7,Bioher_pri_heat_scen,1,Bioher_sec_heat_scen,1]}

Objective Tot_cost_per_reduced
Title: Tot cost per reduced ~
CO2 t
Units: e/CO2
Definition: var a:=sum(Heating_cost+yll_cost,fu_period);~
a:=a-a[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None'];~
var b:=sum(Co2_emission[Const_year='2010'],fu_period);~
b:=b[Bioher_pri_heat_scen='BAU',Bioher_sec_heat_scen='None']-b;~
b:= if b>0 then b else 0;~
a:=a/b;~
if b>0 then a else NAN;
NodeLocation: 416,536,1
NodeSize: 48,29
WindState: 2,253,367,476,224
ValueState: 2,103,155,771,484,1,MIDM
ReformVal: [Bioher_sec_heat_scen,Bioher_pri_heat_scen]

Index Cost
Title: Cost
Definition: ['Investment','Maintenance','Energy']
NodeLocation: 424,80,1
NodeSize: 48,12
WindState: 2,1005,439,476,224
{!40000|Att_PrevIndexValue: ['Investment','Maintenance','Energy']}

Index Uncertain_var
{!40000|Att_PrevIndexValue: ['Investment','Interest','Life year cost','Energy cost change','CO2 price','House size','Unit heat consumption','Blank']}
Title: Uncertain var
Description: A list of uncertain variables used in the model.
Definition: ['Investment','Interest','Life year cost','Energy cost change','CO2 price','House size','Unit heat consumption','Blank']
NodeLocation: 880,448,1
NodeSize: 48,12
NodeInfo: 1,1,1,1,1,1,0,0,0,0
WindState: 2,102,90,476,469
DefnState: 2,351,356,688,342,0,MIDM
ValueState: 2,168,178,582,361,0,MIDM
ReformVal: [Self,Self]

Chance Uncertain_inputs
Title: Uncertain inputs
Description: A list of uncertain variables used in the model. This list is used to analyse the role of each variable by e.g. value-of-information analysis or importance analysis. The variables with 'V:' are not uncertain but describe variability within the population. Note that the last variable 'Blank' is NOT included in the model and therefore whatever significance is attached to this variable, is just a random effect.
Definition: Table(Uncertain_var)(~
0,0,Life_year_unit_cost,Energy_cost,Co2_market_prize,House_size,Unit_heat_con,0)
IndexVals: ['Pollutant levels in fish feed after lower limits (S+P)','Salmon consumption after feed limits (S+P)','Does omega-3 help CHD patients or everyone? (S)','Dose-response of health benefit (S)','Highest omega-3 dose with health benefit (S)','Current average consumption of salmon (S)','Fraction of farmed from total salmon use (S)','Omega3 content in salmon (S)','Consider pollutant or net health effect? (P)','Dieldrin concentration in farmed salmon (S)','Toxaphene concentration in farmed salmon (S)','PCB concentration in farmed salmon (S)','Farmed salmon use after recommendation (S)','Lower limits for pollutants in fish feed? (P)','Recommend restricted farmed salmon consumption? (P)']
NodeLocation: 880,416,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,0,0,0
WindState: 2,198,209,476,275
DefnState: 2,791,420,396,377,0,MIDM
ValueState: 2,148,242,582,361,1,PDFP
NodeColor: 52425,39321,65535
GraphSetup: Graphtool:0~
Distresol:10~
Diststeps:0~
Cdfresol:5~
Cdfsteps:1~
Symbolsize:6~
Baroverlap:0~
Linestyle:1~
Frame:1~
Grid:1~
Ticks:1~
Mesh:1~
Scales:1~
Rotation:45~
Tilt:0~
Depth:70~
Frameauto:1~
Showkey:1~
Xminimum:-20K~
Xmaximum:140K~
Yminimum:0~
Ymaximum:30u~
Zminimum:1~
Zmaximum:1~
Xintervals:0~
Yintervals:0~
Includexzero:0~
Includeyzero:0~
Includezzero:0~
Statsselect:[1,1,1,1,1,0,0,0]~
Probindex:[0.05,0.25,0.5,0.75,0.95]~

ReformVal: [Undefined,Uncertain_var,Undefined,Undefined,1]

Function Voi1(out:prob;deci:indextype;input:prob;input_ind:indextype;classes)
Title: VOI
Description: Value of information (VOI) Version 2.~
~
This function calculates the total VOI (expected value of perfect information, EVPI) for a given decision, and VOI (expected value of partial perfect information, EVPPI) for certain variables. The outcome to be optimised is out; the decision to be made must be indexed by deci; the variables for EVPPI calculation must be listed in input, which is indexed by input_ind. The solution is numerical, and for this purpose, the outcome is classified into a number of bins (the number is defined by classes, which may be a number or an array of numbers). The VOI function assumes that costs are calculated and that the correct optimising function is MIN.~
~
Procedure~
~
First, a new index is generated. It contains 'Total VOI' in the first row and the EVPPI variables in the subsequent rows. Then, net cost under uncertainty (ncuu) and evpi are calculated. ~
~
The rest of the procedure is calculated separetely for each value of classes.~
Varia is a temporary index that has classes number of bins.~
Each iteration is located in one of the bins depending on the value of input. After this classification, the value of out is located into the bin for that iteration. When the mean is taken, the result is the average of outcome multiplied by the probability that the true value of input is in the same bin. The best decision is made given the bin, and then the expected outcomes of each bin are summed up. When ncuu is subtracted from this value, we get EVPPI. Finally, the EVPI and EVPPI are concatenated into a single index.~
~
It may be a good idea to include a row 'Blank' in the input_ind and use it for a random variable that is NOT part of the model. This gives a rough estimate on how much random noise may produce VOI in the system. It might also be good to use different values for Classes, because there may be numerical instability with low iteration numbers, and it is not obvious what low is in each case.~
~
Developed by Jouni Tuomisto and Marko Tainio, National Public Health Institute (KTL), Finland, 2005.
Definition: index a:= ['Total VOI'];~
index variable:= concat(a,input_ind);~
var ncuu:= min(mean(sample(out)),deci);~
var evpi:= (if a='Total VOI' then mean(min(sample(out),deci))-ncuu else 0);~
~
for x[]:= classes do (~
index varia:= sequence(1/x,1,1/x);~
var evppi:= ceil(rank(input,run)*x/samplesize)/x;~
evppi:= if evppi=Varia then out else 0;~
evppi:= sum(min(mean(evppi),deci),varia)-ncuu;~
concat(evpi,evppi,a,input_ind,variable) )
NodeLocation: 880,248,1
NodeSize: 48,24
WindState: 2,264,146,637,814
Log: ?.?Ennen maaliskuuta.2005 Jouni Tuomisto~
~
Keksin juuri uuden konseptin: Value of consensus (VOC) joka lasketaan niistŠ muuttujista, jotka eivŠt ole epŠvarmuutta vaan vaihtelua vŠestšssŠ. Se lasketaan siis samalla tavalla kuin VOI mutta tulkinta on eri: mikŠ on arvo sille, jos saataisiin kaikki konsensukseen jonkin muuttujan arvon taakse (eri arvoja painotetaan sen suhteessa, paljonko niiden alkuperŠinen kannatus on).~
~
11.7.2005 Jouni Tuomisto~
PŠivitettiin VOI versio 1 versioksi 2. Laskentaa ei muutettu muuta kuin rivijŠrjestystŠ siistimŠllŠ. LisŠksi kirjoitettiin ensimmŠinen kunnon (?) Description-osa.

Variable Classes
Title: Classes
Description: The number of classes in the value-of-information analysis. This is a technical parametre only, and it should be large enough. However, the samplesize should be at least 100 times larger than this to avoid random noise.
Definition: [11]
NodeLocation: 880,296,1
NodeSize: 48,12
WindState: 2,102,90,476,405
NodeColor: 52425,39321,65535
Log: Huom! Kaikki alajuoksun solmut eivŠt toimi, jos tŠmŠ on indeksi. Kuitenkin uusi VOI-solmu toimii.

Objective Total_cost_voi
Title: Total cost VOI
Units: euro
Description: Value of information analysis for the input variables with the passenger decision between composite and car traffic. The analysis calculates the expected benefit for the passenger when the uncertainty of a variable is resolved.
Definition: Voi1(Total_cost,Bioher_pri_heat_scen,uncertain_inputs,uncertain_var,Classes)
NodeLocation: 880,352,1
NodeSize: 48,24
WindState: 2,130,343,655,412
ValueState: 2,87,276,935,386,0,MIDM
GraphSetup: Graphtool:0~
Distresol:10~
Diststeps:1~
Cdfresol:5~
Cdfsteps:1~
Symbolsize:6~
Baroverlap:0~
Linestyle:1~
Frame:1~
Grid:1~
Ticks:1~
Mesh:1~
Scales:1~
Rotation:45~
Tilt:0~
Depth:70~
Frameauto:1~
Showkey:1~
Xminimum:0~
Xmaximum:1~
Yminimum:0~
Ymaximum:1~
Zminimum:0~
Zmaximum:1~
Xintervals:0~
Yintervals:0~
Includexzero:0~
Includeyzero:0~
Includezzero:0~
Statsselect:[1,1,1,1,1,0,0,0]~
Probindex:[0.05,0.25,0.5,0.75,0.95]~

ReformVal: [Sys_LocalIndex('VARIABLE'),Heat_system]
NumberFormat: 1,D,4,3,0,0
{!40000|Att_ResultSliceState: [Classes,1,Fu_period,5,Bioher_sec_heat_scen,1,House_area_type,1,Heat_system,7,Sys_LocalIndex('variable'),1]}
Log: 10.5.2005 Jouni Tuomisto~
~
Vanha syntaksi siltŠ ajalta, kun cost__variation laskettiin Costista:~
~
var a:= array(Mode1,[sample(Cost__variation),0]);~
a:= sum(a[stakeholder='Passenger']*sum(trip_fraction,mode1),length);~
Voi(a,Mode1,uncertain_inputs,uncertain_var,Classes)

Chance Interest
Title: Interest
Definition: Uniform(3,4)
NodeLocation: 184,112,1
NodeSize: 48,24
ValueState: 2,132,146,416,303,0,CONF

Chance Energy_cost_change
Title: Energy cost change
Units: kerroin
Description: Source specific increase:~
~
Öljyn hintakehitys perustuu Englannin hallinnon Energia ja ilmaston muutos osaston (DECC) arvioon öljyn hintakehityksestä 2010-2030.~
~
Sähkön ja kaukolämmön hintakehitys perustuu ARA:n raporttiin energiaskenaarioiden järjestelmävaikutuksista rakennuskantaan (Pesola ym. 2009)~
~
Pelletin hintakehitys on oma arvio~
~
Similar increase:~
~
Kaikkien energialähteiden hinta nousee 30 vuodessa 50%.~
~
--------------------------------------~
var a:=Heat_cost_input[Cost='Energy cost increase',House_type='New'];~
a:=Triangular(a*0.5, a, a*1.5);~
var b:= Fu_period-Start_year+2.5;~
a*b
Definition: Table(Fu_period,Heat_system,Energy_price_scen)(~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,1,1,~
1,Triangular(1.24,1.39,1.47),1.0833,~
1,Triangular(1.05,1.1,1.15),1.0833,~
1,Triangular(1.05,1.1,1.15),1.0833,~
1,Triangular(1.23,1.33,1.43),1.0833,~
1,Triangular(1.23,1.33,1.43),1.0833,~
1,Triangular(1,1.12,1.34),1.0833,~
1,Triangular(1,1.12,1.34),1.0833,~
1,Triangular(1.18,1.23,1.28),1.0833,~
1,Triangular(1.05,1.1,1.15),1.0833,~
1,Triangular(1,1.12,1.34),1.0833,~
1,Triangular(1.12,1.45,1.65),1.167,~
1,Triangular(1.1,1.15,1.20),1.167,~
1,Triangular(1.1,1.15,1.20),1.167,~
1,Triangular(1.46,1.66,1.86),1.167,~
1,Triangular(1.46,1.66,1.86),1.167,~
1,Triangular(1,1.24,1.34),1.167,~
1,Triangular(1,1.24,1.34),1.167,~
1,Triangular(1.41,1.46,1.51),1.167,~
1,Triangular(1.1,1.15,1.20),1.167,~
1,Triangular(1,1.24,1.34),1.167,~
1,Triangular(1.01,1.52,1.85),1.25,~
1,Triangular(1.15,1.2,1.25),1.25,~
1,Triangular(1.15,1.2,1.25),1.25,~
1,Triangular(1.63,1.92,2.21),1.25,~
1,Triangular(1.63,1.92,2.21),1.25,~
1,Triangular(1.09,1.36,1.64),1.25,~
1,Triangular(1.09,1.36,1.64),1.25,~
1,Triangular(1.53,1.63,1.73),1.25,~
1,Triangular(1.15,1.2,1.25),1.25,~
1,Triangular(1.09,1.36,1.64),1.25,~
1,Triangular(0.91,1.59,2.07),1.333,~
1,Triangular(1.2,1.25,1.3),1.333,~
1,Triangular(1.2,1.25,1.3),1.333,~
1,Triangular(1.80,2.18,2.56),1.333,~
1,Triangular(1.80,2.18,2.56),1.333,~
1,Triangular(1.19,1.49,1.79),1.333,~
1,Triangular(1.19,1.49,1.79),1.333,~
1,Triangular(1.70,1.80,1.90),1.333,~
1,Triangular(1.2,1.25,1.3),1.333,~
1,Triangular(1.19,1.49,1.79),1.333,~
1,Triangular(0.91,1.59,2.07),1.417,~
1,Triangular(1.2,1.25,1.3),1.417,~
1,Triangular(1.2,1.25,1.3),1.417,~
1,Triangular(1.90,2.37,2.83),1.417,~
1,Triangular(1.90,2.37,2.83),1.417,~
1,Triangular(1.21,1.51,1.81),1.417,~
1,Triangular(1.21,1.51,1.81),1.417,~
1,Triangular(1.70,1.90,2.10),1.417,~
1,Triangular(1.2,1.25,1.3),1.417,~
1,Triangular(1.21,1.51,1.81),1.417~
)
NodeLocation: 184,248,1
NodeSize: 48,24
WindState: 2,39,84,476,319
DefnState: 2,74,468,944,303,0,MIDM
ValueState: 2,121,245,659,337,0,MIDM
ReformDef: [Energy_price_scen,Heat_system]
ReformVal: [Fu_period,Heat_system]
{!40000|Att_ResultSliceState: [Heat_system,8,Sys_LocalIndex('Probability'),1,Fu_period,1]}
{!40000|Att_EditSliceState: [Fu_period,2,Heat_system,1,Energy_price_scen,3]}

Index Cost_factor
Title: Cost factor
Definition: ['Investment','Invest interest','Maintenance','Energy','YLL','CO2']
NodeLocation: 672,480,1
NodeSize: 48,12

Variable Cost_share
Title: Cost share
Definition: var a:=sum(Invest_cost, fu_period);~
var b:=sum(Investment_interest, fu_period);~
var c:=sum(Maint_cost, fu_period);~
var d:=sum(Energy_cost, fu_period);~
var e:=YLL_cost;~
var f:= Co2_cost;~
~
a:=Table(Cost_factor)(~
a, b, c, d, e, f);~
a/Total_cost
NodeLocation: 672,448,1
NodeSize: 48,24
WindState: 2,174,475,476,335
DefnState: 2,1085,443,416,303,0,MIDM
ValueState: 2,130,154,1330,584,1,MIDM
ReformVal: [Cost_factor,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Cost_factor
{!40000|Att_ResultSliceState: [Fu_period,3,Bioher_pri_heat_scen,1,Cost_factor,1]}

Chance Heat_cost_input
Title: Heat cost input
Description: Investointikustannus: lähteenä Motiva, vanhoissa rakennuksissa vesikiertoisen lämmönjakojärjestlmän hinnaksi arvioitu 5000 e joka poistettu investointihinnaksi. Lämpöpumpun hinta on oma arvio. Takalle ei investointikustannusta, koska oletetaan että se laitetaan uuteen taloon joka tapauksessa ja että vanhassa talossa se jo on. Sähkötaloissa investointivaihtoehtoina vain suora sähkö ja lämpöpumppu.~
~
Ylläpitokustannus: Lähteenä rakentaja.fi lämmitystapalaskuri (syksy 2011)~
~
Energian hinta (snt/kWh): sis. verot ja muut kuluttajille koituvat maksut, perustuu tilastokeskuksen vuoden 2011 keskimääräisiin hintoihin. Kaukolämmön hinta kaukolämpötilastosta 2011 (uusi pientalo, kulutus 18000 kWh). Other wood boiler ja secondary wood lähteenä halkoliiteri.fi (Metsäkeskus).~
~
Sähkölämmityksen osalta oletettu, että sähköliittymä on yleissähkö, ei aikasähkö. Sähkölämmitys oletetaan ei-varaavaksi, jolloin sähkölämmittäjä ei maksa korkeampaa vuosimaksua kuin ei-sähkölämmittäjä saadakseen halvempaa yösähköä. Eli sähkölämmittäjälle ei koidu ylimääräistä vuosimaksua.
Definition: Table(Cost,Fu_period,Heat_system,House_area_type)(~
Uniform(10000,14000),Uniform(5000,9000),~
Uniform(12000,18000),Uniform(7000,13000),~
Uniform(10000,14000),Uniform(5000,9000),~
Uniform(10000,14000),Uniform(5000,9000),~
Uniform(10000,14000),Uniform(5000,9000),~
Uniform(4000,6000),Uniform(4000,6000),~
Uniform(16000,20000),Uniform(9000,15000),~
Uniform(10000,14000),Uniform(5000,9000),~
0,0,~
Uniform(1500,2300),Uniform(1500,2300),~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
Uniform(1500,2300),Uniform(1500,2300),~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
122,122,~
170,170,~
170,170,~
57,57,~
57,57,~
48,48,~
112,112,~
57,57,~
100,100,~
50,50,~
122,122,~
170,170,~
170,170,~
57,57,~
57,57,~
48,48,~
112,112,~
57,57,~
100,100,~
50,50,~
122,122,~
170,170,~
170,170,~
57,57,~
57,57,~
48,48,~
112,112,~
57,57,~
100,100,~
50,50,~
122,122,~
170,170,~
170,170,~
57,57,~
57,57,~
48,48,~
112,112,~
57,57,~
100,100,~
50,50,~
122,122,~
170,170,~
170,170,~
57,57,~
57,57,~
48,48,~
112,112,~
57,57,~
100,100,~
50,50,~
122,122,~
170,170,~
170,170,~
57,57,~
57,57,~
48,48,~
112,112,~
57,57,~
100,100,~
50,50,~
10.7,10.7,~
5.3,5.3,~
4,4,~
7.2,7.2,~
7.2,7.2,~
12.7,12.7,~
12.7,12.7,~
7.2,7.2,~
4,4,~
12.7,12.7,~
10.7,10.7,~
5.3,5.3,~
4,4,~
7.2,7.2,~
7.2,7.2,~
12.7,12.7,~
12.7,12.7,~
7.2,7.2,~
4,4,~
12.7,12.7,~
10.7,10.7,~
5.3,5.3,~
4,4,~
7.2,7.2,~
7.2,7.2,~
12.7,12.7,~
12.7,12.7,~
7.2,7.2,~
4,4,~
12.7,12.7,~
10.7,10.7,~
5.3,5.3,~
4,4,~
7.2,7.2,~
7.2,7.2,~
12.7,12.7,~
12.7,12.7,~
7.2,7.2,~
4,4,~
12.7,12.7,~
10.7,10.7,~
5.3,5.3,~
4,4,~
7.2,7.2,~
7.2,7.2,~
12.7,12.7,~
12.7,12.7,~
7.2,7.2,~
4,4,~
12.7,12.7,~
10.7,10.7,~
5.3,5.3,~
4,4,~
7.2,7.2,~
7.2,7.2,~
12.7,12.7,~
12.7,12.7,~
7.2,7.2,~
4,4,~
12.7,12.7~
)
NodeLocation: 424,48,1
NodeSize: 48,24
WindState: 2,268,288,476,259
DefnState: 2,146,127,525,383,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [House_area_type,Heat_system]
ReformVal: [House_area_type,Heat_system]
{!40000|Att_ResultSliceState: [Cost,2,Heat_system,1,House_area_type,1]}
{!40000|Att_EditSliceState: [Cost,2,Fu_period,3,Heat_system,1,House_area_type,1]}

Decision Energy_price_scen
Title: Energy price scenario
Definition: Choice(Self,3)
NodeLocation: 72,248,1
NodeSize: 48,24
WindState: 2,83,64,481,290
Domain: ['Current level','Source specific increase','Similar increase']
{!40300|DomainExpr: Discrete('Current level','Source specific increase','Similar increase',type:'Text')}
{!40200|Att_ChoiceIndexes: Keyword Self}
{!40000|Att_PrevIndexValue: ['Current level','Source specific increase','Similar increase']}

Variable Present_value
Title: Present value
Definition: var a:=Fu_period-Start_year+2.5;~
var b:= Disc_rate/100;~
(1+b)^-a
NodeLocation: 176,352,1
NodeSize: 48,16
ValueState: 2,1063,62,415,303,0,MIDM

Variable Disc_rate
Title: Discount rate
Units: %
Description: Annual discount rate for monetary value
Definition: 3
NodeLocation: 64,352,1
NodeSize: 48,16
WindState: 2,546,7,476,224
NodeColor: 65535,52427,61166

Variable Energy_tax
Title: Energy taxation
Description: VAT + Fuel tax
Definition: Table(Heat_system)(~
33.6,23,23,33.6,23,28.4,28.4,29.4,23,28.4)
NodeLocation: 184,192,1
NodeSize: 48,16
DefnState: 2,597,447,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Vat
Title: VAT
Units: %
Description: Value added tax
Definition: 23
NodeLocation: 184,48,1
NodeSize: 48,16
NodeColor: 65535,52427,61166

Decision Decision_maker
Title: Decision maker
Definition: Choice(Self,2)
NodeLocation: 72,48,1
NodeSize: 48,24
Domain: ['Citizen','Society']
{!40300|DomainExpr: Discrete('Citizen','Society',type:'Text')}
{!40200|Att_ChoiceIndexes: Keyword Self}

Variable Sec_hs
Title: Sec hs
Definition: Table(Bioher_pri_heat_scen,Bioher_sec_heat_scen)(~
0,0,0,~
0,1,1,~
0,0,1,~
0,0,1,~
0,0,1,~
0,1,1,~
0,0,1,~
0,0,1~
)
NodeLocation: 536,48,1
NodeSize: 48,24
ReformDef: [Bioher_sec_heat_scen,Bioher_pri_heat_scen]

Variable Va2
Definition: index runn:= 1..(rounds*10);~
var x:= 1;~
var a:= 0;~
var c:= 0;~
while x<= rounds do (~
a:= whatif(Total_cost[Run = Ru], Run, 1..10);~
c:= if runn = 10*(x-1)+Ru then a else c;~
x:= x+1);~
sum(c, Ru)
NodeLocation: 680,216,1
NodeSize: 48,24
WindState: 2,415,181,476,440
ValueState: 2,487,41,675,303,0,MIDM
ReformVal: [Sys_LocalIndex('runn'),Bioher_pri_heat_scen]
{!40000|Att_ResultSliceState: [Sys_LocalIndex('runn'),11,Bioher_pri_heat_scen,1,Ru,1]}

Index Ru
Title: Ru
Definition: 1..10
NodeLocation: 680,248,1
NodeSize: 48,12

Variable Rounds
Title: Rounds
Description: How many rounds are calculated? There will be 10 times more iterations.
Definition: 200
NodeLocation: 680,104,1
NodeSize: 48,24

Close Costs

Module Model2
Title: Health impacts
Description: Model to calculate DALYs for environmental exposures. Node 'Exposure scenarios' contains three scenarios (Business-as-usual, Increasing exposure, and decreasing exposure). Calculation is divided to mortality and morbidity. Morbidity calculation utilizes DALY weights and duration of disease to yield YLD (Years of Life lost due to Disease), and mortality calculation yields YLL (Years of Life Lost). In the end, these two values are added and the results are DALYs in scenarios.~
~
Pink nodes are source data nodes inputted by a user.
Author: ktluser
Date: Fri, Apr 11, 2008 9:48 AM
DefaultSize: 48,24
NodeLocation: 128,256,1
NodeSize: 52,28
NodeInfo: 1,1,1,1,1,1,0,,0,
DiagState: 2,80,-16,865,765,17
NodeColor: 52427,63897,65535
FontStyle: Arial, 12

Variable Start_year
Title: Assessment start year
Description: Start year of the assessment.
Definition: 2012
NodeLocation: 80,424,1
NodeSize: 48,24
NodeColor: 65535,52427,57888

Variable Followup_time
Title: Follow-up period
Units: Years
Description: Number of follow-up years
Definition: 30
NodeLocation: 80,512,1
NodeSize: 48,24
ValueState: 2,120,130,416,303,0,MIDM
NodeColor: 65535,52427,57888

Variable Input_mort_risk
Title: Input mortality risk
Units: -
Description: Annual mortality rate in BAU scenario.
Definition: var a:=Mort_data/Pop_data;~
~
a:=if isnan(a)=1 then 0 else a;~
~
if a = inf then 0 else a
NodeLocation: 264,208,1
NodeSize: 48,24
WindState: 2,176,259,494,409
ValueState: 2,176,116,467,818,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Mort_endpoint_bioher,Age]
Att__TotalsIndex: Index Mort_endpoint_bioher
{!40000|Att_ResultSliceState: [Age1,2,Sex,1,Age_cat,1,Cause_of_death,1]}

Variable Pop_data
Title: Population data
Description: Annual total population
Definition: Table(Age,Sex)(~
56.6834K,~
56.6834K,~
56.6834K,~
56.6834K,~
56.6834K,~
60.615K,~
60.615K,~
60.615K,~
60.615K,~
60.615K,~
66.1678K,~
66.1678K,~
66.1678K,~
66.1678K,~
66.1678K,~
63.786K,~
63.786K,~
63.786K,~
63.786K,~
63.786K,~
66.42360000000001K,~
66.42360000000001K,~
66.42360000000001K,~
66.42360000000001K,~
66.42360000000001K,~
65.8828K,~
65.8828K,~
65.8828K,~
65.8828K,~
65.8828K,~
61.4958K,~
61.4958K,~
61.4958K,~
61.4958K,~
61.4958K,~
72.47440000000001K,~
72.47440000000001K,~
72.47440000000001K,~
72.47440000000001K,~
72.47440000000001K,~
75.9178K,~
75.9178K,~
75.9178K,~
75.9178K,~
75.9178K,~
76.9778K,~
76.9778K,~
76.9778K,~
76.9778K,~
76.9778K,~
80.20660000000001K,~
80.20660000000001K,~
80.20660000000001K,~
80.20660000000001K,~
80.20660000000001K,~
80.29120000000001K,~
80.29120000000001K,~
80.29120000000001K,~
80.29120000000001K,~
80.29120000000001K,~
54.3002K,~
54.3002K,~
54.3002K,~
54.3002K,~
54.3002K,~
48.0772K,~
48.0772K,~
48.0772K,~
48.0772K,~
48.0772K,~
41.4752K,~
41.4752K,~
41.4752K,~
41.4752K,~
41.4752K,~
34.9876K,~
34.9876K,~
34.9876K,~
34.9876K,~
34.9876K,~
23.3004K,~
23.3004K,~
23.3004K,~
23.3004K,~
23.3004K,~
11.2926K,~
11.2926K,~
11.2926K,~
11.2926K,~
11.2926K,~
4394.400000000001,~
4394.400000000001,~
4394.400000000001,~
4394.400000000001,~
4394.400000000001,~
886.6,~
886.6,~
886.6,~
886.6,~
886.6~
)
NodeLocation: 416,208,1
NodeSize: 48,24
WindState: 2,106,219,484,386
DefnState: 2,261,166,356,524,0,MIDM
ValueState: 2,164,80,273,772,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Sex,Age]
ReformVal: [Sex,Age]
Att__TotalsIndex: Index Age, Index Age_cat

Index Age
Title: Age
Description: List of age in 1 year year intervals.
Definition: Sequence( 0, 99, 1 )
NodeLocation: 416,240,1
NodeSize: 48,12
{!40000|Att_PrevIndexValue: [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]}

Variable Morb_data
Title: Morbidity data
Units: cases/a
Description: Annual number of morbidity cases due to a given cause-of-morbidity.~

Definition: Table(Age,Morb_endpoint,Sex)(~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0,~
0~
)
NodeLocation: 576,112,1
NodeSize: 48,24
WindState: 2,107,127,476,264
DefnState: 2,163,191,514,530,0,MIDM
ValueState: 2,177,164,456,499,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Morb_endpoint,Age]
ReformVal: [Morb_endpoint,Age]
Att__TotalsIndex: Index Age_cat
{!40000|Att_ResultSliceState: [Gender,1,Age_cat,1,Morbidity,1]}
{!40000|Att_EditSliceState: [Gender,1,Age_cat,1,Morbidity,2]}

Variable Input_morb_risk
Title: Input morbidity risk
Description: Annual morbidity rate in BAU scenario.
Definition: var a:=Morb_data/Pop_data;~
~
a:=if isnan(a)=1 then 0 else a;~
~
if a = inf then 0 else a
NodeLocation: 576,208,1
NodeSize: 48,24
WindState: 2,66,175,506,335
ValueState: 2,208,78,499,796,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Morb_endpoint,Age]
Att__TotalsIndex: Index Morb_endpoint
{!40000|Att_ResultSliceState: [Sex,1,Age1,1,Morbidity,1]}

Variable Morb_risk_scenarios
Title: Morbidity risk scenarios
Units: -
Description: Annual morbidity risk in different exposure scenarios. Calculated only for those morbidity endpoints for which baseline morbidity data is provided.
Definition: var a:= Exposures;~
var b:= Morbidity_erf;~
var c:= Morb_erf_unit;~
c:= if c = 0 then 1 else c;~
var d:=Pop_frac;~
~
var e:= exp(ln(b[Erf_type='Relative Risk'])/c*a[@Fu_period=1]);~
Var f:=((e*d)+(1-d))[Exposure='Reference'];~
var g:=((e*d)+(f*(1-d)))[Exposure='BAU'];~
g:=((g-1)/g);~
g:= Input_morb_risk*(1-g);~
~
f:=Table(Exposure)(f, f, 1);~
e:= exp(ln(b[Erf_type='Relative Risk'])/c*a);~
f:=(e*d)+(f*(1-d));~
f*g~

NodeLocation: 576,280,1
NodeSize: 48,24
WindState: 2,140,145,643,472
DefnState: 2,603,496,559,303,0,MIDM
ValueState: 2,166,156,519,497,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Exposure,Age]
{!40000|Att_ResultSliceState: [Sex,1,Morb_endpoint,1,Fu_period,1,Age,1,Exposure,1]}

Variable Age_weight
Title: Age weight
Description: What are the most valuable ages in human life?
Definition: If Age_weighting= 'Yes' then~
~
var a:=0.1658*Age*exp(-0.04*Age);~
sum(if floor(Age/5)+1 = @age_cat then a else 0 , Age)/5~
~
else 1~

NodeLocation: 744,376,1
NodeSize: 48,12
WindState: 2,185,183,476,341
DefnState: 2,168,7,416,585,0,MIDM
ValueState: 2,189,167,362,363,0,MIDM
NodeColor: 19661,48336,65535

Variable Birth_rate
Title: Birth rate
Units: births/year
Description: Annual number of births
Definition: Table(Sex,Fu_year)(~
57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,57K,0,0~
)
NodeLocation: 80,368,1
NodeSize: 48,24
WindState: 2,174,211,476,224
DefnState: 2,264,245,388,472,0,MIDM
ValueState: 2,292,307,416,482,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Sex,Fu_year]
ReformVal: [Sex,Fu_year]

Variable Discount
Title: Annual discount rate
Units: %
Description: Annual time discount rate for future loss of life
Definition: 0
NodeLocation: 744,416,1
NodeSize: 48,16
ValueState: 2,234,206,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Mort_data
Title: Mortality data
Units: deaths/a
Description: Annual number of deaths due to a given cause-of-death~
~
Note! All causes of death must be included in the node dataset because the life table modelling is based on total mortality.~

Definition: Table(Age,Sex,Mort_endpoint_bioher)(~
40.8,9,~
40.8,9,~
40.8,9,~
40.8,9,~
40.8,9,~
3.8,6.4,~
3.8,6.4,~
3.8,6.4,~
3.8,6.4,~
3.8,6.4,~
4.6,6,~
4.6,6,~
4.6,6,~
4.6,6,~
4.6,6,~
7,23.6,~
7,23.6,~
7,23.6,~
7,23.6,~
7,23.6,~
10.2,39.8,~
10.2,39.8,~
10.2,39.8,~
10.2,39.8,~
10.2,39.8,~
12.4,34.6,~
12.4,34.6,~
12.4,34.6,~
12.4,34.6,~
12.4,34.6,~
17.8,30.8,~
17.8,30.8,~
17.8,30.8,~
17.8,30.8,~
17.8,30.8,~
48.6,50.8,~
48.6,50.8,~
48.6,50.8,~
48.6,50.8,~
48.6,50.8,~
92.2,64.40000000000001,~
92.2,64.40000000000001,~
92.2,64.40000000000001,~
92.2,64.40000000000001,~
92.2,64.40000000000001,~
166.4,81.2,~
166.4,81.2,~
166.4,81.2,~
166.4,81.2,~
166.4,81.2,~
302.6,93.2,~
302.6,93.2,~
302.6,93.2,~
302.6,93.2,~
302.6,93.2,~
457.8,97.2,~
457.8,97.2,~
457.8,97.2,~
457.8,97.2,~
457.8,97.2,~
475.2,58.8,~
475.2,58.8,~
475.2,58.8,~
475.2,58.8,~
475.2,58.8,~
643,59.4,~
643,59.4,~
643,59.4,~
643,59.4,~
643,59.4,~
919.4,55.6,~
919.4,55.6,~
919.4,55.6,~
919.4,55.6,~
919.4,55.6,~
1312,60.4,~
1312,60.4,~
1312,60.4,~
1312,60.4,~
1312,60.4,~
1560,59.6,~
1560,59.6,~
1560,59.6,~
1560,59.6,~
1560,59.6,~
1355.4,44.4,~
1355.4,44.4,~
1355.4,44.4,~
1355.4,44.4,~
1355.4,44.4,~
895.6,38.4,~
895.6,38.4,~
895.6,38.4,~
895.6,38.4,~
895.6,38.4,~
301.2,11.8,~
301.2,11.8,~
301.2,11.8,~
301.2,11.8,~
301.2,11.8~
)
NodeLocation: 264,120,1
NodeSize: 48,24
WindState: 2,164,118,514,452
DefnState: 2,231,183,389,673,0,MIDM
ValueState: 2,235,136,472,503,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Mort_endpoint_bioher,Age]
ReformVal: [Mort_endpoint_bioher,Age]
Att__TotalsIndex: Index Age, Index Age_cat, Index Mort_endpoint_bioher
{!40000|Att_ResultSliceState: [Sex,1,Age_cat,1,Cause_of_death,1]}
{!40000|Att_EditSliceState: [Sex,2,Age1,1,Mort_endpoint,1]}

Variable Mort_risk_scenarios
Title: Mortality risk scenarios
Units: -
Description: Annual mortality risk in different exposure scenarios.~

Definition: var a:= Exposures;~
var b:= Mortality_erf;~
var c:= Mort_erf_unit;~
c:= if c = 0 then 1 else c;~
var d:=Pop_frac;~
~
var e:= exp(ln(b[Erf_type='Relative Risk'])/c*a[@Fu_period=1]);~
Var f:=((e*d)+(1-d))[Exposure='Reference'];~
var g:=((e*d)+(f*(1-d)))[Exposure='BAU'];~
g:=(g-1)/g;~
g:= Input_mort_risk*(1-g);~
~
f:=Table(Exposure)(f, f, 1);~
e:= exp(ln(b[Erf_type='Relative Risk'])/c*a);~
f:=(e*d)+(f*(1-d));~
g:=f*g;~
~
Var h:= a-a[Exposure='BAU', @Fu_period=1];~
h:= b[Erf_type='Absolute Risk']/c*h*d;~
~
sum(Table(Erf_type)(g,h),Erf_type)~

NodeLocation: 264,280,1
NodeSize: 48,24
WindState: 2,348,172,630,827
DefnState: 2,131,524,556,303,0,MIDM
ValueState: 2,96,60,614,775,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Exposure,Age]
Att__TotalsIndex: Index Mort_endpoint_bioher
{!40000|Att_ResultSliceState: [Fu_period,2,Sex,1,Mort_endpoint_bioher,2,Bioher_pri_heat_scen,1,Age,1,Exposure,3]}

Objective Le_cohort
Title: Life expectancy in birth cohort
Units: Years
Description: Life-expectancy for a birth cohort exposed to the given level throughout the entire life.
Definition: var a:= sum(Mort_risk_scenarios,Mort_endpoint_bioher);~
~
a:= if Mort_effect = 'Acute' then a[Exposure='BAU'] else a;~
~
a:=a[Fu_period=period_lt];~
a:= if a = null then a[Exposure='Reference',Period_lt=max(Fu_period)] else a;~
a:= Si_pi(a, 5, Period_lt, Year_lt, Year_help)*5;~
~
a:=if a < 0 then 0 else a;~
a:=if a>1 then 1 else a;~
~
a:= 1-a;~
~
var b:=1;~
var c:=0;~
var d:=0;~
var x:= 0;~
while x<=99 do (~
c:=b*a[Age=x, @Year_lt=x+1];~
d:=d+c+(b-c)/2;~
b:=c;~
x:= x+1); ~
~
d~
~
~
~

NodeLocation: 368,400,1
NodeSize: 48,24
WindState: 2,91,93,539,715
ValueState: 2,177,439,429,195,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Exposure,Sex,Undefined,2]
Att__TotalsIndex: Index Age, Index Mort_endpoint_bioher
{!40000|Att_ResultSliceState: [Sex,1,Period_lt,4,Age,1,Exposure,1]}
Reference: ~


Objective Ab_morbidity_spec
Title: Morbidity, specified
Units: cases
Description: Morbidity cases attributable to the exposure in different scenarios.
Definition: var a:= Exposures;~
var b:= Morbidity_erf;~
var c:= Morb_erf_unit;~
c:= if c = 0 then 1 else c;~
var d:= Pop_frac;~
var e:= Morb_risk_scenarios;~
~
var f:= b[Erf_type='Absolute Risk']/c*a*d;~
~
var g:=sum(Table(Erf_type)(e,f),erf_type);~
g:=if g<0 then 0 else g;~
g:= sum(if floor(Age/5)+1 = @age_cat then g else 0, Age)/5;~
g:=g-g[Exposure='Reference'];~
~
g:=g*Pop_in_time_ave;~
var h:=Table(Time_unit)(g, g*5);~
h:= if Followup_time <2 then g else h;~
~
if Outcome= 'Change in EBD' then h[Exposure='Alternative']-h[Exposure='BAU'] else h~
~
~

NodeLocation: 576,424,1
NodeSize: 48,20
WindState: 2,251,183,531,758
ValueState: 2,179,198,564,526,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Fu_period,Age_cat]
Att__TotalsIndex: Index Age, Index Age_cat
{!40000|Att_ResultSliceState: [Sex,1,Morb_endpoint,2,Exposure,1,Time_unit,1,Age_cat,1,Fu_period,1]}

Objective Yll_spec
Title: YLL, specified
Units: years
Description: Years of life lost due to mortality attributable to the exposure of interest
Definition: if Mort_effect = 'Acute' then ~
~
Ab_mortality_spec*Life_lost*Pv_life_year[period_lt=Fu_period]*Age_weight~
~
else if App_yll = 'Direct' then~
~
var a:=Life_years;~
a:= (a[Exposure='Reference']-a);~
if Outcome= 'Change in EBD' then a[Exposure='Alternative']-a[Exposure='BAU'] else a~
~
else~
~
Ab_mortality_spec*Ad_le[Exposure='Reference']*Pv_life_year[Period_lt=Fu_period]~

NodeLocation: 264,576,1
NodeSize: 48,12
WindState: 2,78,94,550,810
ValueState: 2,98,64,639,568,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Fu_period,Age_cat,Undefined,Undefined,1]
Att__TotalsIndex: Index Age, Index Fu_period, Index Age_cat, Index Period_lt, Index Mort_endpoint_bioher
{!40000|Att_ResultSliceState: [Sex,1,Exposure,2,Time_unit,2,Mort_endpoint_bioher,0,Age_cat,0,Fu_period,1]}

Objective Yld_spec
Title: YLD, specified
Units: years
Description: Years of life lost due to morbidity attributable to the exposure of interest.
Definition: ~
var a:= Ab_morbidity_spec*Duration*Daly_weight*Pv_life_year[period_lt=Fu_period];~
~
if isnan(a)=1 then 0 else a~
~

NodeLocation: 576,576,1
NodeSize: 48,12
WindState: 2,106,126,565,408
ValueState: 2,124,295,654,548,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Fu_period,Age_cat]
Att__TotalsIndex: Index Age, Index Fu_period, Index Age_cat, Index Morb_endpoint
{!40000|Att_ResultSliceState: [Sex,1,Time_unit,2,Exposure,1,Morb_endpoint,2,Age_cat,1,Fu_period,1]}

Objective Daly_spec
Title: DALY, specified
Units: years
Description: Annual loss of disability adjusted life years attributable to the exposure in different scenarios.~

Definition: if App_yll = 'Direct' then~
~
Yll_spec+sum(Yld_spec[Fu_period=period_lt, time_unit='5-year period'],morb_endpoint)~
~
else~
~
sum(Yll_spec,Mort_endpoint_bioher)+sum(Yld_spec,Morb_endpoint)
NodeLocation: 416,576,1
NodeSize: 48,20
WindState: 2,107,95,476,419
DefnState: 2,191,289,416,303,0,MIDM
ValueState: 2,225,149,436,533,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Period_lt,Age_cat,Undefined,Undefined,1]
Att__TotalsIndex: Index Age, Index Age_cat, Index Period_lt
{!40000|Att_ResultSliceState: [Sex,1,Exposure,1,Age_cat,0,Period_lt,1]}

Alias Cause_of_death2
Title: Cause of death
Definition: 1
NodeLocation: 264,152,1
NodeSize: 52,12
Original: Mort_endpoint_bioher

Alias Morbidity2
Title: Morbidity
Definition: 1
NodeLocation: 576,144,1
NodeSize: 52,12
Original: Morb_endpoint

Module Help_nodes
Title: Technical nodes
Author: vkoe
Date: 21. Janta 2009 9:47
DefaultSize: 48,24
NodeLocation: 744,64,1
NodeSize: 48,24
NodeInfo: 1,0,0,1,1,1,0,,0,
DiagState: 2,-3,0,448,245,17

Index Fu_period
Title: Follow-up period
Definition: sequence(Start_year,Start_year+(Followup_time-1),5)
NodeLocation: 448,176,1
NodeSize: 48,16
WindState: 2,90,70,476,224
ValueState: 2,116,494,416,303,0,MIDM
ReformVal: [Undefined,Self]
{!40300|Att_SlicerPopupSize: 227,98}
{!40000|Att_PrevIndexValue: [2012,2017,2022,2027,2032,2037]}

Index Age_cat
{!40000|Att_PrevIndexValue: ['0-4','5-9','10-14','15-19','20-24','25-29','30-34','35-39','40-44','45-49','50-54','55-59','60-64','65-69','70-74','75-79','80-84','85-89','90-94','95+']}
Title: Age cat
Description: Age categories used in morbidity datasets.
Definition: ['0-4','5-9','10-14','15-19','20-24','25-29','30-34','35-39','40-44','45-49','50-54','55-59','60-64','65-69','70-74','75-79','80-84','85-89','90-94','95+']
NodeLocation: 96,224,1
NodeSize: 48,12
WindState: 2,25,12,335,453
ValueState: 2,754,375,416,462,0,MIDM

Index Sex
Title: Sex
Definition: If Sex_class='Yes' then Copyindex(Sex_yes) else Copyindex(Sex_no)
NodeLocation: 96,88,1
NodeSize: 48,12
WindState: 2,102,90,476,224
{!40000|Att_PrevIndexValue: ['Male/female']}

Function Si_pi(data, kerroin;karkea,tarkka:indextype;indtieto)
Title: Si_pi
Description: Data = data to be divided into more detailed parts~
Kerroin = relative weight inside a cluster~
Karkea = index for the clustered data~
Tarkka = index for the detailed data~
Indtieto = Data about which detailed item belongs to which cluster~
~
esim: Si_pi1(Base_mortality, 5, Age_cat, age1, Age_help) (baseline mortality from 5-year age categories to 1-year age categories)
Definition: var a:=sum((if indtieto=karkea then kerroin else 0), tarkka);~
a:= sum((if indtieto=karkea then a else 0), karkea);~
a:= kerroin/a;~
sum((if indtieto=karkea then data*a else 0), karkea)
NodeLocation: 208,48,1
NodeSize: 48,24
WindState: 2,372,218,476,494

Variable Age_help
Title: Age help
Description: A help node to group age index~
~
This node is used in transforming morbidity and mortality datasets in 5 year intervals into 1 year interval datasets.
Definition: Table(Age)(~
'0-4','0-4','0-4','0-4','0-4','5-9','5-9','5-9','5-9','5-9','10-14','10-14','10-14','10-14','10-14','15-19','15-19','15-19','15-19','15-19','20-24','20-24','20-24','20-24','20-24','25-29','25-29','25-29','25-29','25-29','30-34','30-34','30-34','30-34','30-34','35-39','35-39','35-39','35-39','35-39','40-44','40-44','40-44','40-44','40-44','45-49','45-49','45-49','45-49','45-49','50-54','50-54','50-54','50-54','50-54','55-59','55-59','55-59','55-59','55-59','60-64','60-64','60-64','60-64','60-64','65-69','65-69','65-69','65-69','65-69','70-74','70-74','70-74','70-74','70-74','75-79','75-79','75-79','75-79','75-79','80-84','80-84','80-84','80-84','80-84','85-89','85-89','85-89','85-89','85-89','90-94','90-94','90-94','90-94','90-94','95+','95+','95+','95+','95+')
NodeLocation: 208,120,1
NodeSize: 48,24
NodeInfo: 1,1,0,1,1,1,0,,0,
DefnState: 2,85,271,416,571,0,MIDM
NodeColor: 65535,65531,1

Index Sex_yes
Title: Sex yes
Definition: ['Male','Female']
NodeLocation: 96,40,1
NodeSize: 48,12

Index Sex_no
Title: Sex no
Definition: ['Male/female']
NodeLocation: 96,64,1
NodeSize: 48,12

Variable Outcome_scen_help
Title: Outcome scen help
Definition: Table(Age_cat)(~
'All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages','All ages')
NodeLocation: 208,176,1
NodeSize: 48,24
NodeInfo: 1,0,0,1,1,1,0,,0,
DefnState: 2,198,274,416,303,0,MIDM
NodeColor: 65535,65531,1

Decision Mort_effect
Title: Type of mortality effect
Definition: Choice(Self,1)
NodeLocation: 328,48,1
NodeSize: 48,24
WindState: 2,169,50,476,224
ValueState: 2,301,363,416,303,0,MIDM
Domain: ['Chronic','Acute']
{!40300|DomainExpr: Discrete('Chronic','Acute',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Index Erf_type
Title: ERF type
Definition: ['Relative Risk','Absolute Risk']
NodeLocation: 96,128,1
NodeSize: 48,12
{!40000|Att_PrevIndexValue: ['Relative Risk','Absolute Risk']}

Decision App_yll
Title: Approach for YLL calculation
Definition: Choice(Self,2)
NodeLocation: 328,176,1
NodeSize: 48,29
WindState: 2,265,286,476,224
ValueState: 2,284,345,416,303,0,MIDM
Aliases: FormNode Approach_for_yll_cal
Domain: ['Direct','Indirect']
{!40300|DomainExpr: Discrete('Direct','Indirect',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Variable Year_help
Title: Year help
Definition: var a:= if year_lt >= period_lt and year_lt< period_lt+5 then period_lt else 0;~
sum(a,period_lt)
NodeLocation: 208,232,1
NodeSize: 48,24
WindState: 2,102,90,476,224
DefnState: 2,120,130,424,513,0,MIDM
ValueState: 2,458,169,416,679,0,MIDM
NodeColor: 65535,65532,19661

Decision Outcome
Title: Outcome of interest
Definition: Choice(Self,1)
NodeLocation: 328,112,1
NodeSize: 48,24
Aliases: FormNode Outcome_of_interest
Domain: ['EBD','Change in EBD']
{!40300|DomainExpr: Discrete('EBD','Change in EBD',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Index Pop_unit
Title: Population unit
Definition: ['Total population','100000 population']
NodeLocation: 96,160,1
NodeSize: 48,16

Index Time_unit
Title: Time unit
Definition: ['Average annual','5-year period']
NodeLocation: 96,192,1
NodeSize: 48,12
WindState: 2,275,208,476,224

Variable Period_vs_year
Title: Period vs year
Definition: var a:= if Year_lt = Period_lt then Period_lt else 0;~
sum(a,Year_lt)~

NodeLocation: 448,56,1
NodeSize: 48,24
ValueState: 2,360,165,501,494,0,MIDM
ReformVal: [Fu_year,Fu_period]

Index Year_lt
Title: Year LT
Definition: if App_yll = 'Direct' then sequence(Start_year,Start_year+Followup_time+99,1) ~
else~
sequence(Start_year,Start_year+104,1)
NodeLocation: 448,108,1
NodeSize: 48,12
ValueState: 2,537,377,416,303,0,MIDM

Index Period_lt
Title: Period LT
Definition: if App_yll = 'Direct' then sequence(Start_year,Start_year+Followup_time+99,5)~
else~
sequence(Start_year,Start_year+104,5)
NodeLocation: 448,136,1
NodeSize: 48,12
WindState: 2,258,313,476,224
ValueState: 2,415,203,450,537,0,MIDM

Index Fu_year
Title: Follow-up year
Definition: sequence(Start_year,Start_year+(Followup_time-1),1)
NodeLocation: 448,208,1
NodeSize: 48,16
ValueState: 2,447,277,436,438,0,MIDM
{!40000|Att_PrevIndexValue: [2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025,2026,2027,2028,2029,2030,2031,2032,2033,2034,2035,2036,2037,2038,2039,2040,2041]}

Variable Year_spec
Title: Year specific input data
Description: Is the input data for exposure/health outcome follow up -year specific?
Definition: if Assessment_type='Exposure scenarios' then Exp_year_class else Ys_change_mort
NodeLocation: 96,272,1
NodeSize: 48,24
WindState: 2,200,186,476,224

Index Morb_endpoint
{!40000|Att_PrevIndexValue: ['Chronic bronchitis','RAD']}
Title: Morb endpoints
Description: Morbidity endpoints included in the assessment.~
~
Type in the list into the definition field. Press 'Enter' to add new rows and 'Back' to remove rows. When the list is complete press 'Alt' + 'Enter'.
Definition: ['Chronic bronchitis','RAD']
NodeLocation: 200,424,1
NodeSize: 52,21
WindState: 2,151,56,476,275
ValueState: 2,612,556,416,303,0,MIDM
Aliases: Alias Morbidity2

Index Mort_endpoint_bioher
Title: Mort endpoints
Description: Causes of death -classification used in the assessment.~
~
Type in the list into the definition field. Press 'Enter' to add new rows and 'Back' to remove rows. When the list is complete press 'Alt' + 'Enter'.
Definition: ['Non-accidental','Accidental']
NodeLocation: 104,424,1
NodeSize: 52,21
WindState: 2,107,90,476,266
Aliases: Alias Cause_of_death2
{!40000|Att_PrevIndexValue: ['Non-accidental','Accidental']}

Decision Sex_class
Title: Sex specified impact assessment
Definition: Choice(Self,1)
NodeLocation: 96,360,1
NodeSize: 48,32
NodeInfo: 1,1,0,1,1,1,0,,0,
Domain: ['No','Yes']
{!40300|DomainExpr: Discrete('No','Yes',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Decision Assessment_type
Title: Starting point for the assessment
Definition: Choice(Self,1)
NodeLocation: 208,360,1
NodeSize: 48,32
NodeInfo: 1,1,0,1,1,1,0,,0,
WindState: 2,102,90,476,224
Domain: ['Exposure scenarios','Health outcome scenarios','Total burden of disease']
{!40300|DomainExpr: Discrete('Exposure scenarios','Health outcome scenarios','Total burden of disease',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Module Nodes3
Title: BoD
Author: jtue
Date: 17. huhta 2009 14:34
DefaultSize: 48,24
NodeLocation: 448,272,1
NodeSize: 48,24
DiagState: 2,-3,0,448,245,17

Variable As_total_yll
Title: Age-specific total YLL
Definition: Table(Age,Sex,Mort_endpoint_bioher)(~
0,0,~
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0,0,~
0,0,~
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0,0,~
0,0,~
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0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0~
)
NodeLocation: 96,48,1
NodeSize: 48,24
DefnState: 2,179,125,483,580,0,MIDM
ValueState: 2,235,231,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Mort_endpoint_bioher,Age]
ReformVal: [Mort_endpoint_bioher,Age]
{!40000|Att_EditSliceState: [Gender,1,Age_cat,1,Cause_of_death,1]}

Variable As_total_yld
Title: Age-specific total YLD
Definition: Table(Age,Sex,Morb_endpoint)(~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
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0,0,~
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0,0,~
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0,0,~
0,0,~
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0,0,~
0,0,~
0,0,~
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0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0~
)
NodeLocation: 96,104,1
NodeSize: 48,24
DefnState: 2,117,131,416,483,0,MIDM
ValueState: 2,230,251,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Morb_endpoint,Age]
ReformVal: [Morb_endpoint,Age]

Close Nodes3

Module Nodes1
Title: Mortality outcome scenarios
Author: vkoe
Date: 22. Janta 2009 14:46
DefaultSize: 48,24
NodeLocation: 448,400,1
NodeSize: 48,28
DiagState: 2,-3,0,448,245,17
NodeColor: 65535,52427,61166

Variable Input_mort_abfrac
Title: Attributable fraction in mortality data
Units: Fraction
Description: Fraction of mortality in mortallity input data attributable to the exposure of interest
Definition: Table(Age,Sex,Mort_endpoint_bioher)(~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
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0,0,~
0,0,~
0,0,~
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0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0~
)
NodeLocation: 88,72,1
NodeSize: 48,32
WindState: 2,302,266,476,224
DefnState: 2,282,226,453,412,0,MIDM
ValueState: 2,475,502,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Mort_endpoint_bioher,Age]
ReformVal: [Mort_endpoint_bioher,Age]
Domain: ['item 1']
{!40300|DomainExpr: Discrete('item 1',type:['text'])}

Variable Change_mort
Title: Year-specific change in attributable mortality risk
Units: %
Description: Precentage change in the mortality risk attributable to the exposure of interest.~
~
Note! Change refers to the change in risk in comparison to the mortality risk in the start of the assessment, NOT in comparison to the previous 5-year follow-up step.
Definition: Table(Age,Fu_period,Sex,Mort_endpoint_bioher,Scenario)(~
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)
NodeLocation: 88,232,1
NodeSize: 48,36
WindState: 2,232,283,476,224
DefnState: 2,119,191,619,449,0,MIDM
ValueState: 2,340,384,508,469,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Fu_period,Age]
ReformVal: [Fu_period,Age]
{!40000|Att_ResultSliceState: [Sex,1,Scenario,1,Mort_endpoint,2,Age,1,Fu_period,1]}
{!40000|Att_EditSliceState: [Sex,1,Mort_endpoint,2,Scenario,1,Age,1,Fu_period,1]}

Decision Ys_change_mort
Title: Year-specific input for mortality outcome
Definition: Choice(Self,1)
NodeLocation: 88,144,1
NodeSize: 48,32
ValueState: 2,294,402,416,303,0,MIDM
Domain: ['Yes','No']
{!40300|DomainExpr: Discrete('Yes','No',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Index Scenario
{!40000|Att_PrevIndexValue: ['BAU','Alternative']}
Title: Scenario
Definition: ['BAU','Alternative']
NodeLocation: 88,280,1
NodeSize: 48,12

Close Nodes1

Module Technical_nodes
Title: Morbidity outcome scenarios
Author: vkoe
Date: 12. Mayta 2009 15:35
DefaultSize: 48,24
NodeLocation: 448,336,1
NodeSize: 48,28
DiagState: 2,-3,0,448,245,17
NodeColor: 65535,52427,61166

Decision Input_morb_outcome
Title: Input for morbidity outcome calculation
Definition: Choice(Self,1)
NodeLocation: 104,48,1
NodeSize: 48,36
WindState: 2,366,308,476,224
ValueState: 2,464,402,416,303,0,MIDM
Domain: ['Percentage change','No. of cases']
{!40300|DomainExpr: Discrete('Percentage change','No. of cases',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Variable Input_morb_abfrac
Title: Attributable fraction in morbidity data
Description: Fraction of morbidity in morbidity input data attributable to the exposure of interest
Definition: Table(Age,Sex,Morb_endpoint)(~
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)
NodeLocation: 104,128,1
NodeSize: 48,36
WindState: 2,257,286,476,224
DefnState: 2,197,238,416,424,0,MIDM
ValueState: 2,336,352,418,410,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Morb_endpoint,Age]
ReformVal: [Morb_endpoint,Age]

Variable Outcome_morb
Title: Year-specific morbidity outcome
Units: % change or no. of cases
Description: Precentage change in the total morbidity risk attributáble to the expoure/risk factor or number of attributable morbidity cases~
~
Note! Change refers to the change in risk in comparison to the morbidity risk in the start of the assessment, NOT in comparison to the previous 5-year follow-up step.
Definition: Table(Age,Fu_period,Sex,Morb_endpoint,Scenario)(~
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)
NodeLocation: 104,224,1
NodeSize: 48,28
WindState: 2,221,256,476,224
DefnState: 2,132,163,612,436,0,MIDM
ValueState: 2,314,401,654,415,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Fu_period,Age]
ReformVal: [Fu_period,Age]
Att__TotalsIndex: Index Age
{!40000|Att_ResultSliceState: [Sex,1,Morb_endpoint,1,Scenario,2,Age,1,Fu_period,1]}
{!40000|Att_EditSliceState: [Sex,1,Morb_endpoint,1,Scenario,1,Age,1,Fu_period,1]}

Close Technical_nodes

Variable Secondary_wood_emf
Title: Secondary wood EMF BAU
Description: Average PM emission factor for wood heating devices used as secondary heat sources based on:~
*PM emission factor for different types of secondary heaters~
*fraction of these heaters in secondary wood heating in Finland~
~
Data: Kavosenoja, Piltti-malli~
~
Assumption: secondary wood heaters are:~
*iron stoves~
*Other stove or oven~
*Open fireplace
Definition: var a:=Wh_frac[wood_heater='Iron stove']+Wh_frac[wood_heater='Masonry heater']+Wh_frac[wood_heater='Open fireplace'];~
a:=1/a;~
a:=Wh_frac*a*Wh_pm_emf;~
a[wood_heater='Iron stove']+a[wood_heater='Masonry heater']+a[wood_heater='Open fireplace']
NodeLocation: 328,288,1
NodeSize: 48,24
WindState: 2,130,122,496,508
ValueState: 2,96,314,416,303,0,CONF
ReformVal: [Self,Wood_heater]
Att__TotalsIndex: Index Wood_heater

Close Help_nodes

Objective Ab_mortality_spec
Title: Mortality, specified
Units: deaths
Description: Deaths attributable to the exposure in different scenarios.~

Definition: var a:= Mort_risk_scenarios;~
a:=if a<0 then 0 else a;~
a:=if a>1 then 1 else a;~
a:= sum(if floor(Age/5)+1 = @age_cat then a else 0 , Age)/5;~
a:=a-a[Exposure='Reference'];~
~
a:= a*Pop_in_time_ave;~
var b:=Table(Time_unit)(a, a*5);~
a:= if Followup_time <2 then a else b;~
~
if Outcome= 'Change in EBD' then a[Exposure='Alternative']-a[Exposure='BAU'] else a~

NodeLocation: 472,424,1
NodeSize: 48,20
WindState: 2,215,208,462,640
ValueState: 2,187,205,672,550,0,MIDM
NodeColor: 65535,19661,38773
GraphSetup: {!40000|Att_graphvaluerange Ab_mortality_spec:|1:1,,0,,,,,8000,14K}~
{!40000|Att_graphvaluerange Graph_cdf_valdim:1,,1,1}~
{!40000|Att_graphvaluerange Graph_pdf_valdim:1,0,0,1,,,,0,200}
ReformVal: [Fu_period,Age_cat,2,2,1]
Att__TotalsIndex: Index Age, Index Fu_period, Index Age_cat
{!40000|Att_ResultSliceState: [Sex,1,Time_unit,2,Mort_endpoint_bioher,1,Exposure,2,Bioher_pri_heat_scen,3,Age_cat,0,Fu_period,1]}
{!40200|Att_GraphSetupSlices: [3,1,DensityIndex,1]}

Objective Ad_le
Title: Age-adjusted life expectancy
Units: Years
Description: Age-adjusted life expectancy~

Definition: Var a:=Life_years;~
~
var b:= 0;~
var x:= 1;~
while x<= min([size(Age_cat),size(Period_lt)]) do (~
b:= b + a;~
a:= a[@Age_cat=@Age_cat+1, @Period_lt=@Period_lt+1];~
a:= if a=null then 0 else a;~
x:= x+1);~
~
b:=b[@Period_lt=1]/Pop_in_time_beg[@Period_lt=1];~
if isnan(b)=1 then 0 else b
NodeLocation: 264,392,1
NodeSize: 48,24
WindState: 2,104,73,476,599
ValueState: 2,298,156,419,505,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Exposure,Age_cat]
{!40000|Att_ResultSliceState: [Sex,2,Age_cat,1,Exposure,3]}

Variable Pop_frac
Title: Fraction of exposed population
Definition: Table(Exposure)(~
1,1,1)
NodeLocation: 416,120,1
NodeSize: 48,24
WindState: 2,88,119,476,224
DefnState: 2,179,207,411,195,0,MIDM
ValueState: 2,254,283,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Life_lost
Title: Loss of life at death
Units: Years/death
Definition: Table(Age_cat,Sex,Mort_endpoint_bioher)(~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0~
)
NodeLocation: 80,576,1
NodeSize: 48,24
WindState: 2,134,115,476,224
DefnState: 2,143,110,414,526,0,MIDM
ValueState: 2,187,304,416,387,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Mort_endpoint_bioher,Age_cat]
ReformVal: [Sex,Age_cat]
{!40000|Att_ResultSliceState: [Mort_endpoint,1,Age_cat,1,Sex,1]}

Variable Pv_life_year
Title: PV of a life year
Description: Present value of one life year~

Definition: var a:=Period_lt-Start_year+2.5;~
var b:= Discount/100;~
(1+b)^-a~
~

NodeLocation: 744,456,1
NodeSize: 48,20
WindState: 2,111,148,476,291
ValueState: 2,201,137,345,447,0,MIDM
NodeColor: 19661,48336,65535

Module Technical_nodes1
Title: Mortality ERF
Author: vkoe
Date: 1. Junta 2009 8:35
DefaultSize: 48,24
NodeLocation: 80,280,1
NodeSize: 48,24
DiagState: 2,171,164,365,344,17
NodeColor: 65535,52427,61166

Module Erf_pm2_5
Title: ERF PM2.5 and natural mortality
Author: ktluser
Date: 6. Mayta 2008 9:06
DefaultSize: 48,24
NodeLocation: 80,40,1
NodeSize: 48,28
DiagState: 1,51,83,1067,576,17
NodeColor: 52427,63897,65535

Variable Ambient_pdm
Title: ambient.PDM
Description: PDM = performance-based decision maker~
~
Numbers from table 4, page 742.~
~
Ref: Jouni T. Tuomisto, Andrew Wilsonb, John S. Evans, Marko Tainio. Uncertainty in mortality response to airborne fine particulate matter:~
Combining European air pollution experts. Reliability Engineering and System Safety 93 (2008) 732–744
Definition: Table(Percentile1)(~
0.029,0.14,0.62,1.1,3.9)
NodeLocation: 208,64,1
NodeSize: 48,24
WindState: 2,180,151,517,324
DefnState: 2,330,631,416,303,0,MIDM
ValueState: 2,26,8,416,303,0,MIDM
NodeColor: 65535,52427,57888

Index Percentile1
Title: Percentile
Definition: [0.05,0.25,0.5,0.75,0.95]
NodeLocation: 208,96,1
NodeSize: 48,13
{!40000|Att_PrevIndexValue: [0.05,0.25,0.5,0.75,0.95]}

Variable Ambient_edm
Title: ambient.EDM
Description: EDM = equal-weight decision maker~
~
Numbers from table 4, page 742.~
~
Ref: Jouni T. Tuomisto, Andrew Wilsonb, John S. Evans, Marko Tainio. Uncertainty in mortality response to airborne fine particulate matter:~
Combining European air pollution experts. Reliability Engineering and System Safety 93 (2008) 732–744
Definition: Table(Percentile1)(~
0.034,0.41,0.98,1.6,4.6)
NodeLocation: 368,64,1
NodeSize: 48,24
WindState: 2,98,90,476,395
DefnState: 2,428,392,416,303,0,MIDM
ValueState: 2,264,274,416,303,0,MIDM
NodeColor: 65535,52427,57888

Chance Edm_cumdist
Title: EDM-cumdist
Definition: var a:=cumdist(Percentile1,Ambient_edm, , false );~
a
NodeLocation: 368,160,1
NodeSize: 48,24
ValueState: 2,516,25,416,579,0,CONF

Chance Pdm_cumdist
Title: PDM-cumdist
Definition: var a:=cumdist(Percentile1,Ambient_pdm, , false );~
a
NodeLocation: 208,160,1
NodeSize: 48,24
ValueState: 2,44,17,274,456,0,CONF
GraphSetup: Probindex:[0.05, 0.25, 0.5, 0.75, 0.95 ]

Variable Combined_c_r_functio
Title: Combined c-r function
Definition: var a:=if Pdm_vs__edm=1 then Pdm_cumdist else Edm_cumdist;~
a
NodeLocation: 288,232,1
NodeSize: 48,24
ValueState: 2,300,63,237,252,0,CONF

Chance Pdm_vs__edm
Title: PDM vs. EDM
Definition: Bernoulli(.5)
NodeLocation: 448,232,1
NodeSize: 48,24
WindState: 2,102,90,476,224
ValueState: 2,328,338,416,303,0,CONF
DisplayOutputs: Variable Clipboard_input_vari,

Variable Cr_plausibility
Title: cr.plausibility
Definition: Combined_c_r_functio
NodeLocation: 288,304,1
NodeSize: 48,24
ValueState: 2,84,60,399,269,0,CONF

Variable Hitox_pdm
Title: hitox.PDM
Description: PDM = performance-based decision maker~
~
Numbers from table 4, page 742.~
~
The high/low constituents are presented in article Cooke et al. High relates in general to combustion partilces. Low relates to secondary particles (4 experts) and for crustal particles (2 experts).~
~
Ref: Jouni T. Tuomisto, Andrew Wilsonb, John S. Evans, Marko Tainio. Uncertainty in mortality response to airborne fine particulate matter:~
Combining European air pollution experts. Reliability Engineering and System Safety 93 (2008) 732–744~
~
ref: Cooke RM, Wilson AM, Tuomisto JT, Morales O, Tainio M, Evans JS. A Probabilistic characterization of the relationship between fine particulate matter and mortality: Elicitation of European experts. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 41 (18)
Definition: Table(Percentile1)(~
0.062,0.6800000000000001,1.1,2.4,8)
NodeLocation: 528,64,1
NodeSize: 48,24
WindState: 2,83,85,476,414
DefnState: 2,461,446,416,303,0,MIDM
NodeColor: 65535,52427,57888

Variable Hitox_edm
Title: hitox.EDM
Description: EDM = equal-weight decision maker~
~
Numbers from table 4, page 742.~
~
The high/low constituents are presented in article Cooke et al. High relates in general to combustion partilces. Low relates to secondary particles (4 experts) and for crustal particles (2 experts).~
~
Ref: Jouni T. Tuomisto, Andrew Wilsonb, John S. Evans, Marko Tainio. Uncertainty in mortality response to airborne fine particulate matter:~
Combining European air pollution experts. Reliability Engineering and System Safety 93 (2008) 732–744~
~
ref: Cooke RM, Wilson AM, Tuomisto JT, Morales O, Tainio M, Evans JS. A Probabilistic characterization of the relationship between fine particulate matter and mortality: Elicitation of European experts. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 41 (18)
Definition: Table(Percentile1)(~
0.08699999999999999,0.87,1.9,3.7,10)
NodeLocation: 688,64,1
NodeSize: 48,24
DefnState: 2,10,15,416,303,0,MIDM
NodeColor: 65535,52427,57888

Variable Lotox_edm
Title: lotox.EDM
Description: EDM = equal-weight decision maker~
~
Numbers from table 4, page 742.~
~
The high/low constituents are presented in article Cooke et al. High relates in general to combustion partilces. Low relates to secondary particles (4 experts) and for crustal particles (2 experts).~
~
Ref: Jouni T. Tuomisto, Andrew Wilsonb, John S. Evans, Marko Tainio. Uncertainty in mortality response to airborne fine particulate matter:~
Combining European air pollution experts. Reliability Engineering and System Safety 93 (2008) 732–744~
~
ref: Cooke RM, Wilson AM, Tuomisto JT, Morales O, Tainio M, Evans JS. A Probabilistic characterization of the relationship between fine particulate matter and mortality: Elicitation of European experts. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 41 (18)
Definition: Table(Percentile1)(~
0,0,0.11,0.43,2)
NodeLocation: 960,64,1
NodeSize: 48,24
DefnState: 2,11,18,416,303,0,MIDM
NodeColor: 65535,52427,57888

Variable Lotox_pdm
Title: lotox.PDM
Description: PDM = performance-based decision maker~
~
Numbers from table 4, page 742.~
~
The high/low constituents are presented in article Cooke et al. High relates in general to combustion partilces. Low relates to secondary particles (4 experts) and for crustal particles (2 experts).~
~
Ref: Jouni T. Tuomisto, Andrew Wilsonb, John S. Evans, Marko Tainio. Uncertainty in mortality response to airborne fine particulate matter:~
Combining European air pollution experts. Reliability Engineering and System Safety 93 (2008) 732–744~
~
ref: Cooke RM, Wilson AM, Tuomisto JT, Morales O, Tainio M, Evans JS. A Probabilistic characterization of the relationship between fine particulate matter and mortality: Elicitation of European experts. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 41 (18)
Definition: Table(Percentile1)(~
0,0.018,0.25,0.36,1)
NodeLocation: 800,64,1
NodeSize: 48,24
DefnState: 2,20,19,416,303,0,MIDM
NodeColor: 65535,52427,57888

Variable Combined_c_r_functi3
Title: Combined c-r function.high
Definition: var a:=if Pdm_vs__edm=1 then Pdm_cumdist_high else Edm_cumdist_high;~
a
NodeLocation: 608,232,1
NodeSize: 56,24
ValueState: 2,75,105,237,252,0,CONF

Variable Cr_plausibility_high
Title: cr.plausibility.high
Definition: Combined_c_r_functi3
NodeLocation: 608,304,1
NodeSize: 48,24
ValueState: 2,500,64,416,303,0,CONF

Chance Edm_cumdist_high
Title: EDM-cumdist.high
Definition: var a:=cumdist(Percentile1,Hitox_edm, , false );~
a
NodeLocation: 688,160,1
NodeSize: 48,24
ValueState: 2,549,74,416,303,0,CONF
DisplayOutputs: Variable Clipboard_input_vari,

Chance Pdm_cumdist_high
Title: PDM-cumdist.high
Definition: var a:=cumdist(Percentile1,Hitox_pdm, , false );~
a
NodeLocation: 528,160,1
NodeSize: 48,24
ValueState: 2,951,63,274,408,0,CONF
GraphSetup: Probindex:[0.05, 0.25, 0.5, 0.75, 0.95 ]
DisplayOutputs: Variable Clipboard_input_vari,

Variable Combined_c_r_functi1
Title: Combined c-r function.low
Definition: var a:=if Pdm_vs__edm=1 then Pdm_cumdist_low else Edm_cumdist_low;~
a
NodeLocation: 880,232,1
NodeSize: 56,24
ValueState: 2,300,63,237,252,0,CONF

Variable Cr_plausibility_low
Title: cr.plausibility.low
Definition: Combined_c_r_functi1
NodeLocation: 880,304,1
NodeSize: 48,24
ValueState: 2,744,304,416,303,0,CONF

Chance Edm_cumdist_low
Title: EDM-cumdist.low
Definition: var a:=cumdist(Percentile1,Lotox_edm, , false );~
a
NodeLocation: 960,160,1
NodeSize: 48,24
ValueState: 2,870,239,416,303,0,CONF
DisplayOutputs: Variable Clipboard_input_vari,

Chance Pdm_cumdist_low
Title: PDM-cumdist.low
Definition: var a:=cumdist(Percentile1,Lotox_pdm, , false );~
a
NodeLocation: 800,160,1
NodeSize: 48,24
ValueState: 2,951,63,274,408,0,CONF
GraphSetup: Probindex:[0.05, 0.25, 0.5, 0.75, 0.95 ]
DisplayOutputs: Variable Clipboard_input_vari,

Index Cr_choice
{!40000|Att_PrevIndexValue: ['Equal toxicity','Differential toxicity']}
Title: cr.choice
Definition: ['Equal toxicity','Differential toxicity']
NodeLocation: 608,440,1
NodeSize: 48,12

Variable Cr_function
Title: cr.function
Definition: Table(Cr_choice)(~
Cr_plausibility,Cr_plausibility_high)
NodeLocation: 608,408,1
NodeSize: 48,24
DefnState: 2,22,33,685,446,0,MIDM
ValueState: 2,106,83,421,240,0,MIDM
ReformDef: [Cr_choice]
ReformVal: [Cr_choice,Undefined,1]
{!40000|Att_ResultSliceState: [Run,1,Cr_choice,1]}

Constant Higher_toxicity_was_
Title: Higher toxicity was applied for traffic emissions and lower for agricultural dust emissions
Definition: Cr_function
NodeLocation: 792,408,1
NodeSize: 72,58

Chance Ambient_pdm_low_unc
Title: ambient.PDM.low.unc
Definition: Triangular( 0.14, 0.62, 1.1 )
NodeLocation: 64,64,1
NodeSize: 48,24
ValueState: 2,284,165,509,294,1,MIDM

Chance Ambient_edm_low_unc
Title: ambient.EDM.low.unc
Definition: Triangular( 0.41, 0.98, 1.6 )
NodeLocation: 64,112,1
NodeSize: 48,24
ValueState: 2,284,165,509,294,1,MIDM

Close Erf_pm2_5

Variable Mortality_erf
Title: Mortality ERF
Description: Exposure-response function for mortality endpoint
Definition: Table(Age,Sex,Mort_endpoint_bioher,Erf_type)(~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0,~
Pm_erf,0,~
1,0~
)
NodeLocation: 192,120,1
NodeSize: 48,24
DefnState: 2,348,191,416,629,0,MIDM
ValueState: 2,193,10,601,655,0,MIDM
ReformDef: [Mort_endpoint_bioher,Age]
ReformVal: [Mort_endpoint_bioher,Age]
{!40000|Att_ResultSliceState: [Sex,1,Erf_type,1,Age,1,Mort_endpoint_bioher,1]}
{!40000|Att_EditSliceState: [Sex,1,Mort_endpoint_bioher,2,Age,1,Erf_type,1]}

Variable Mort_erf_unit
Title: Mortality ERF unit
Description: Number of exposure units the relative risk for mortality refers to.
Definition: Table(Mort_endpoint_bioher)(~
1,0)
NodeLocation: 80,184,1
NodeSize: 48,24
DefnState: 2,115,212,416,303,0,MIDM
ValueState: 2,197,343,416,303,0,MIDM
NodeColor: 65535,52427,57888

Chance Pm_erf
Title: PM ERF
Definition: var a:=Cr_plausibility;~
1+a/100
NodeLocation: 80,120,1
NodeSize: 48,24
WindState: 2,39,132,476,224
ValueState: 2,62,24,416,679,0,CONF

Close Technical_nodes1

Module Technical_nodes2
Title: Morbidity ERF
Author: vkoe
Date: 1. Junta 2009 8:35
DefaultSize: 48,24
NodeLocation: 744,280,1
NodeSize: 48,24
DiagState: 2,145,159,315,324,17
NodeColor: 65535,52427,61166

Variable Morb_erf_claih
Title: Morbidity ERF Claih
Description: Exposure-response functions for morbidity, defined as relative risk (RR)~
~
This node is used if the ERF differs between age groups~
~
*Age classification: 1 year intervals. ~
*Sex classification: can be used if necessary~
*RR=1 is used if If there is no known dependence between the studied exposure and a particular morbidity
Definition: Table(Pollutant)(~
1,1,1)
NodeLocation: 80,48,1
NodeSize: 48,24
WindState: 2,183,44,488,475
DefnState: 2,165,77,532,889,0,MIDM
ValueState: 2,397,1,451,895,0,MIDM
NodeColor: 65535,52427,57888
ReformDef: []
ReformVal: []
{!40000|Att_ResultSliceState: [Pollutant,1]}
{!40000|Att_EditSliceState: [Sex,1,Erf_type,2,Pollutant,1,Age,1,Morb_endpoint,1]}
Reference: Cafe raport

Variable Morbidity_erf
Title: Morbidity ERF
Units: -
Description: Exposure-response function for morbidity endpoint
Definition: if Assessment = 'Bioher' then Morb_erf_bioher else Morb_erf_claih
NodeLocation: 200,112,1
NodeSize: 48,24
WindState: 2,595,61,534,370
ValueState: 2,234,224,422,470,0,MIDM
ReformVal: [Morb_endpoint,Age]
{!40000|Att_ResultSliceState: [Sex,1,Erf_type,2,Age,1,Morb_endpoint,1]}

Variable Morb_erf_bioher
Title: Morbidity ERF bioher
Description: Exposure-response functions for morbidity, defined as relative risk (RR)~
~
This node is used if the ERF differs between age groups~
~
*Age classification: 1 year intervals. ~
*Sex classification: can be used if necessary~
*RR=1 is used if If there is no known dependence between the studied exposure and a particular morbidity
Definition: Table(Age,Sex,Erf_type,Morb_endpoint)(~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
0,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0.902,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0,~
1,1,~
53.3u,0~
)
NodeLocation: 80,112,1
NodeSize: 48,24
WindState: 2,183,216,488,475
DefnState: 2,81,63,532,755,0,MIDM
ValueState: 2,246,106,451,895,0,MIDM
NodeColor: 65535,52427,57888
ReformDef: [Morb_endpoint,Age]
ReformVal: [Morb_endpoint,Age]
{!40000|Att_ResultSliceState: [Sex,1,Erf_type,2,Age,1,Morb_endpoint,1]}
{!40000|Att_EditSliceState: [Sex,1,Erf_type,2,Age,1,Morb_endpoint,1]}
Reference: Cafe raport

Variable Morb_erf_unit
Title: Morbidity ERF unit
Description: Number of exposure units the relative risk for morbidity refers to.
Definition: Table(Morb_endpoint)(~
1,10)
NodeLocation: 80,168,1
NodeSize: 48,24
WindState: 2,141,188,476,224
DefnState: 2,184,217,416,303,0,MIDM
ValueState: 2,261,321,416,303,0,MIDM
NodeColor: 65535,52427,57888

Close Technical_nodes2

Module Technical_nodes3
Title: Duration of morbidity
Author: vkoe
Date: 1. Junta 2009 8:35
DefaultSize: 48,24
NodeLocation: 744,520,1
NodeSize: 48,24
DiagState: 2,143,103,359,300,17
NodeColor: 65535,52427,61166

Variable Duration
Title: Duration of morbidity
Units: Years
Definition: if Duration_age_class = 'No' then Duration_gen else Duration_as
NodeLocation: 224,144,1
NodeSize: 48,24
ValueState: 2,187,170,416,303,0,MIDM
ReformVal: [Sex,Morb_endpoint]

Variable Duration_as
Title: Age-specific duration of morbidity
Units: Years
Description: Incidence endpoint: duration of the disease in years~
Prevalence endpoint: duration = 1 year
Definition: Table(Age_cat,Sex,Morb_endpoint)(~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0~
)
NodeLocation: 96,192,1
NodeSize: 48,24
WindState: 2,93,99,482,362
DefnState: 2,255,263,392,451,0,MIDM
ValueState: 2,257,310,416,303,0,MIDM
NodeColor: 65535,52427,57888
ReformDef: [Morb_endpoint,Age_cat]
ReformVal: [Morb_endpoint,Age_cat]

Variable Duration_gen
Title: General duration of morbidity
Units: Years
Description: Incidence endpoint: duration of the disease in years~
Prevalence endpoint: duration = 1 year
Definition: Table(Sex,Morb_endpoint)(~
8,1/365~
)
NodeLocation: 96,136,1
NodeSize: 48,24
DefnState: 2,250,285,416,303,0,MIDM
ValueState: 2,268,374,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Sex,Morb_endpoint]
ReformVal: [Sex,Morb_endpoint]

Decision Duration_age_class
Title: Age-specific duration of morbidity
Definition: Choice(Self,1)
NodeLocation: 96,72,1
NodeSize: 48,29
ValueState: 2,223,352,416,303,0,MIDM
Domain: ['No','Yes']
{!40300|DomainExpr: Discrete('No','Yes',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Close Technical_nodes3

Module Technical_nodes4
Title: Disability severity weight
Author: vkoe
Date: 1. Junta 2009 8:35
DefaultSize: 48,24
NodeLocation: 744,576,1
NodeSize: 48,24
DiagState: 2,146,132,330,303,17
NodeColor: 65535,52427,61166

Variable Daly_weight
Title: Severity weight
Definition: If Severity_age_class = 'No' then DALY_weight_gen else DALY_weight_as
NodeLocation: 208,112,1
NodeSize: 48,24
ValueState: 2,328,410,416,303,0,MIDM
ReformVal: [Sex,Morb_endpoint]
Att__TotalsIndex: Index Morb_endpoint

Variable Daly_weight_as
Title: Age-specific severity weight
Description: Daly weights for morbidity~
~
Current data:~
Arbitrary weights
Definition: Table(Age_cat,Sex,Morb_endpoint)(~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0~
)
NodeLocation: 88,168,1
NodeSize: 48,24
WindState: 2,102,90,476,224
DefnState: 2,278,279,425,515,0,MIDM
ValueState: 2,235,272,364,461,0,MIDM
NodeColor: 65535,52427,57888
ReformDef: [Morb_endpoint,Age_cat]
ReformVal: [Morb_endpoint,Age_cat]
Reference: WHO

Variable Daly_weight_gen
Title: General severity weight
Definition: Table(Sex,Morb_endpoint)(~
0.15,0.09900000000000001~
)
NodeLocation: 88,112,1
NodeSize: 48,24
DefnState: 2,288,293,416,303,0,MIDM
ValueState: 2,288,390,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Sex,Morb_endpoint]

Decision Severity_age_class
Title: Age-specific severity weight
Definition: Choice(Self,2)
NodeLocation: 88,48,1
NodeSize: 48,29
ValueState: 2,232,352,416,303,0,MIDM
Domain: ['Yes','No']
{!40300|DomainExpr: Discrete('Yes','No',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Close Technical_nodes4

Module Exposure1
Title: Exposure
Author: vkoe
Date: 5. Novta 2009 13:17
DefaultSize: 48,24
NodeLocation: 416,64,1
NodeSize: 48,24
DiagState: 2,627,177,513,306,17
NodeColor: 65535,52427,61166

Variable Exposures
Title: Exposure
Units: ug/m3
Description: Table(Exposure)(~
Pm_exposure[Bioher_pri_heat_scen='BAU', Bioher_sec_heat_scen='None', Const_year=Const_year,Fu_period=2010], Alternative_scenarios, 0 )~
~
Pm_exposure[Bioher_pri_heat_scen='BAU', Bioher_sec_heat_scen='None', Const_year=Const_year, Fu_period=2012]
Definition: Table(Exposure)(~
Pm_exposure[Bioher_pri_heat_scen='BAU', Bioher_sec_heat_scen='None', Const_year=Const_year, Fu_period=2012],Alternative_scenario,0)
NodeLocation: 240,192,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
WindState: 2,106,59,490,416
DefnState: 2,190,479,740,278,0,MIDM
ValueState: 2,277,438,580,360,0,MIDM
NodeColor: 19661,48336,65535
GraphSetup: {!40000|Att_graphvaluerange Graph_pdf_valdim:1,0,1,1,,,,0,1}~
{!40000|Att_graphvaluerange Exposures:1,,1,,,,,0,1}~
{!40000|Att_contlinestyle Run:0}
ReformDef: [Exposure,Sex]
ReformVal: [Fu_period,Exposure]
{!40000|Att_ResultSliceState: [Bioher_pri_heat_scen,2,Exposure,2,Fu_period,1]}
Reference: Cafe raport

Index Exposure
Title: Exposure
Description: Jouni 14.6.2009: I changed the name from Scen to Exposure because this is not just a list of scenarios, it is specifically the list of counterfactual exposure scenarios.~
~
Row 'Impacted' is changed to 'Alternative scenario' because a) also people in BAU are impacted and b) we don't know a priori whether the alternative scenario is a higher or lower exposure.~
______________________~
~
Exposure scenarios.
Definition: ['BAU','Alternative','Reference']
NodeLocation: 240,224,1
NodeSize: 52,12
NodeInfo: 1,1,1,1,1,1,0,0,0,0
WindState: 2,614,154,476,262
{!40000|Att_PrevIndexValue: ['BAU','Alternative','Reference']}

Decision Exp_age_class
Title: Age-specific exposure
Definition: Choice(Self,2)
NodeLocation: 120,40,1
NodeSize: 48,24
Domain: ['Yes','No']
{!40300|DomainExpr: Discrete('Yes','No',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Decision Exp_year_class
Title: Year-specific exposure
Definition: Choice(Self,1)
NodeLocation: 240,40,1
NodeSize: 48,24
Domain: ['Yes','No']
{!40300|DomainExpr: Discrete('Yes','No',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

Variable Alternative_scenario
Title: Alternative scenarios
Definition: if Bioher_pri_heat_scen = 'All' then Pm_exposure else Pm_exposure[Bioher_pri_heat_scen = Bioher_pri_heat_scen]
NodeLocation: 120,192,1
NodeSize: 48,24
WindState: 2,351,282,476,403
ValueState: 2,384,380,570,303,0,MIDM
ReformVal: [Fu_period,Bioher_pri_heat_scen]
{!40000|Att_ResultSliceState: [Bioher_sec_heat_scen,3,Bioher_pri_heat_scen,1,Fu_period,1]}

Alias BIOHER_primary_heat1
Title: BIOHER primary heat scenarios
Definition: 1
NodeLocation: 120,120,1
NodeSize: 52,32
Original: Bioher_pri_heat_scen

Close Exposure1

Objective Ad_le_loss
Title: Loss of age-adjusted life expectancy
Units: Years
Definition: var a:=Ad_le;~
a[Exposure='Reference']-a
NodeLocation: 264,448,1
NodeSize: 48,24
ValueState: 2,185,146,416,460,0,MIDM
ReformVal: [Exposure,Age_cat]
{!40000|Att_ResultSliceState: [Age1,1,Sex,1,Sys_localindex('PROBABILITY'),1,Exposure,1]}

Objective Le_loss
Title: Loss of life expectancy in birth cohort
Units: Years
Definition: var a:=Le_cohort;~
a[Exposure='Reference']-a
NodeLocation: 368,448,1
NodeSize: 48,24
WindState: 2,109,95,476,276
ValueState: 2,227,154,458,200,0,MIDM
ReformVal: [Sex,Exposure,Undefined,2]

Text Te2
NodeLocation: 180,168,-1
NodeSize: 164,144
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te3
NodeLocation: 416,168,-1
NodeSize: 64,144
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te4
NodeLocation: 652,168,-1
NodeSize: 164,144
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te5
NodeLocation: 104,544,-1
NodeSize: 88,80
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te6
NodeLocation: 104,392,-1
NodeSize: 88,72
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te8
NodeLocation: 732,556,-1
NodeSize: 84,68
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te15
NodeLocation: 732,404,-1
NodeSize: 84,84
NodeInfo: 1,0,0,1,0,1,0,,0,

Text Te125
NodeLocation: 420,472,-1
NodeSize: 220,152
NodeInfo: 1,0,0,1,0,1,0,,0,

Module Population_in_time1
Title: Population in time
Author: vkoe
Date: 9. Febta 2010 10:56
DefaultSize: 48,24
NodeLocation: 416,280,1
NodeSize: 48,24
DiagState: 2,60,368,408,249,17
NodeColor: 19661,48336,65535

Index Age_child
{!40000|Att_PrevIndexValue: [0,1,2,3,4]}
Title: Age child
Definition: 0..4
NodeLocation: 80,96,1
NodeSize: 48,12

Variable Pop_in_time_child
Title: Population in time child
Definition: var k: Birth_rate[Fu_year=Year_lt];~
k:= if k = null then {k[@Year_lt=Followup_time]} 0 else k;~
var a:= if @Year_lt = 1 then Pop_data else (if @Age=1 then k else 0);~
a:= a[Age=age_child];~
~
var j:= sum(Mort_risk_scenarios,Mort_endpoint_bioher)[Age=age_child];~
j:=if Mort_effect = 'Acute' then j[Exposure='BAU'] else j;~
~
j:=j[Fu_period=Period_lt];~
j:= if j = null then j[Exposure='Reference',Period_lt=max(Fu_period)] else j;~
j:= Si_pi(j, 5, Period_lt, Year_lt, Year_help)*5;~
~
j:= if j < 0 then 0 else j;~
j:= if j > 1 then 1 else j;~
~
j:= 1-j;~
~
var x:= 1;~
while x<= min([size(age_child),size(Year_lt)]) do (~
var b:= a*j;~
b:= b[@age_child=@age_child-1, @Year_lt=@Year_lt-1];~
a:= if b=null then a else b;~
x:= x+1);~
~
sum(if Year_lt = period_vs_year then a else 0,Year_lt)~

NodeLocation: 80,64,1
NodeSize: 48,24
WindState: 2,188,97,553,652
ValueState: 2,92,317,688,319,0,MIDM
ReformVal: [Period_lt,Age_child]
Att__TotalsIndex: Index Age, Index Age_child
{!40000|Att_ResultSliceState: [Sex,1,Exposure,1,Age_child,3,Period_lt,3]}

Variable Pop_in_time_beg
Title: Population in time, beginning of time step
Description: Population projection for 100 years in different exposure scenarios. Population is modeled for the start year of each 5-year time step~
~
.j:= if Year_spec = 'Yes' then~
(j:=j[Fu_period=Period_lt];~
j:= if j = null then j[Exposure='Reference',Period_lt=max(Fu_period)] else j)~
else j;~

Definition: var a:= sum(if floor(Age/5)+1 = @Age_cat then Pop_data else 0 , Age);~
a:= if @Age_cat=1 then sum(Pop_in_time_child, Age_child) else (if @period_lt = 1 then a else  0);~
~
var j:= sum(Mort_risk_scenarios,Mort_endpoint_bioher);~
j:=if Mort_effect = 'Acute' then j[Exposure='BAU'] else j;~
j:=j[Fu_period=Period_lt];~
j:= if j = null then j[Exposure='Reference',Period_lt=max(Fu_period)] else j;~
~
j:= if j < 0 then 0 else j;~
j:= if j > 1 then 1 else j;~
~
j:= 1-j;~
~
j:= sum(if floor(Age/5)+1 = @Age_cat then j else 0 , Age)/5;~
var m:=j[@Age_cat=@Age_cat+1];~
m:= if m=null then 0 else m;~
var n:=((j^5)+(j^4*m)+(j^3*m^2)+(j^2*m^3)+(j*m^4))/5;~
~
var x:= 1;~
while x<= min([size(Age_cat),size(Period_lt)]) do (~
var b:= a*n;~
b:= b[@Age_cat=@Age_cat-1, @Period_lt=@Period_lt-1];~
a:= if b=null then a else b;~
x:= x+1);~
a~
~

NodeLocation: 192,64,1
NodeSize: 48,32
WindState: 2,89,106,569,714
ValueState: 2,599,34,750,535,0,MIDM
ReformVal: [Period_lt,Age_cat]
Att__TotalsIndex: Index Age_cat, Index Period_lt
{!40000|Att_ResultSliceState: [Sex,1,Exposure,3,Age_cat,1,Period_lt,1]}

Variable Pop_in_time_ave
Title: Population in time, average for time step
Description: Average annual population number for each 5-year time step during the follow-up period.~

Definition: var a:=Pop_in_time_beg[Period_lt=Fu_period];~
var b:=(Pop_in_time_beg[@Period_lt=@Period_lt+1])[Period_lt=Fu_period];~
b:= if b = null then a[Fu_period=max(Fu_period)] else b;~
b:=(a+b)/2;~
if Followup_time <2 then a else b
NodeLocation: 304,64,1
NodeSize: 48,32
WindState: 2,72,90,537,592
ValueState: 2,173,249,661,491,0,MIDM
ReformVal: [Fu_period,Age_cat]
Att__TotalsIndex: Index Age_cat
{!40000|Att_ResultSliceState: [Sex,1,Exposure,1,Age_cat,1,Fu_period,1]}

Variable Life_years
Title: Life years in time
Units: years
Description: Calculates the number of life years lived by a given 5-year age group in a given 5-year time step 100 years onwards from the beginning of the assessment.~

Definition: var a:= Pop_in_time_beg;~
~
var b:=sum(Mort_risk_scenarios,Mort_endpoint_bioher);~
b:= if Mort_effect = 'Acute' then b[Exposure='BAU'] else b; ~
b:=b[Fu_period=period_lt];~
b:= if b = null then b[Exposure='Reference',Period_lt=max(Fu_period)] else b;~
~
b:= if b < 0 then 0 else b;~
b:= if b>1 then 1 else b;~
~
b:= 1-b;~
~
b:= sum(if floor(Age/5)+1 = @Age_cat then b else 0 , Age)/5;~
var c:=b[@Age_cat=@Age_cat+1];~
c:= if c=null then c[Age_cat='90-94'] else c;~
var d:=((b^5)+(b^4*c)+(b^3*c^2)+(b^2*c^3)+(b*c^4))/5;~
~
var e:= a-(a*d);~
((a*d*5)+e*2.5)*Age_weight*Pv_life_year~

NodeLocation: 192,128,1
NodeSize: 48,24
WindState: 2,164,94,476,635
ValueState: 2,86,186,620,582,0,MIDM
ReformVal: [Period_lt,Age_cat]
Att__TotalsIndex: Index Age_cat, Index Period_lt
{!40000|Att_ResultSliceState: [Sex,1,Exposure,2,Age_cat,0,Period_lt,0]}

Close Population_in_time1

Objective Ab_mortality_tot
Title: Mortality, total
Units: deaths/follow-up period
Definition: sum(Ab_mortality_spec,age_cat,Fu_period)[Time_unit='5-year period']
NodeLocation: 472,456,1
NodeSize: 48,12
WindState: 2,119,145,476,224
ValueState: 2,174,163,682,327,0,MIDM
GraphSetup: {!40000|Att_graphvaluerange Graph_pdf_valdim:1,0,0,1,,,,0,1m}
ReformVal: [Undefined,Bioher_pri_heat_scen,Undefined,2]
{!40000|Att_ResultSliceState: [Sex,1,Mort_endpoint_bioher,1,Exposure,2,Bioher_pri_heat_scen,1]}

Objective Ab_morbidity_tot
Title: Morbidity, total
Units: cases/follow-up period
Definition: sum(sum(Ab_morbidity_spec,age_cat),Fu_period)[Time_unit='5-year period']
NodeLocation: 576,456,1
NodeSize: 48,12
ValueState: 2,154,150,413,208,0,MIDM
ReformVal: [Exposure,Morb_endpoint]
{!40000|Att_ResultSliceState: [Sex,1,Pop_unit,1,Exposure,1,Morb_endpoint,1]}

Objective Yll_tot
Title: YLL, total
Units: years/follow-up period
Description: if App_yll = 'Direct' then~
~
sum(Yll_spec,age_cat,Period_lt)[Time_unit='5-year period']~
~
else~
~
sum(Yll_spec,age_cat,Fu_period)[Time_unit='5-year period']
Definition: if App_yll = 'Direct' then~
~
sum(Yll_spec,age_cat)[Time_unit='5-year period']~
~
else~
~
sum(Yll_spec,age_cat)[Time_unit='5-year period']
NodeLocation: 264,600,1
NodeSize: 48,12
WindState: 2,110,129,476,317
ValueState: 2,250,254,522,306,0,MIDM
ReformVal: [Fu_period,Bioher_pri_heat_scen,2]
Att__TotalsIndex: Index Fu_period, Index Period_lt, Index Mort_endpoint_bioher
{!40000|Att_ResultSliceState: [Exposure,2,Fu_period,0,Mort_endpoint_bioher,0,Bioher_pri_heat_scen,7,Sex,1]}

Objective Daly_tot
Title: DALY, total
Units: years/follow-up period
Definition: if App_yll = 'Direct' then~
~
sum(Daly_spec,Age_cat,Period_lt)[Time_unit='5-year period']~
~
else~
~
sum(Daly_spec,age_cat,Fu_period)[Time_unit='5-year period']
NodeLocation: 416,608,1
NodeSize: 48,12
WindState: 2,102,90,476,406
ValueState: 2,230,467,325,245,0,MIDM
ReformVal: [Sex,Exposure]
{!40000|Att_ResultSliceState: [Exposure,1,Sex,1,Pop_unit,1]}

Objective Yld_tot
Title: YLD, total
Units: years/follow-up period
Definition: sum(Yld_spec,age_cat,Fu_period)[Time_unit='5-year period']
NodeLocation: 576,600,1
NodeSize: 48,12
WindState: 2,153,140,476,400
ValueState: 2,225,270,478,247,0,MIDM
ReformVal: [Morb_endpoint,Exposure]
Att__TotalsIndex: Index Morb_endpoint
{!40000|Att_ResultSliceState: [Sex,1,Age_cat,10,Exposure,1,Morb_endpoint,1]}

Decision Age_weighting
Title: Age weighting
Definition: Choice(Self,2)
NodeLocation: 744,344,1
NodeSize: 48,12
Domain: ['Yes','No']
{!40300|DomainExpr: Discrete('Yes','No',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}

FormNode Approach_for_yll_cal
Title: Approach for YLL calculation
Definition: 0
NodeLocation: 172,652,1
NodeSize: 140,12
NodeInfo: 1,0,0,1,0,0,0,72,0,1
Original: App_yll

FormNode Outcome_of_interest
Title: Outcome of interest
Definition: 0
NodeLocation: 148,684,1
NodeSize: 116,12
NodeInfo: 1,0,0,1,0,0,0,72,0,1
Original: Outcome

Function Ict(exp: prob)
Title: ICT YLL total
Description: var a:= for i := Run do (Whatif( Yll_tot, exposures, exp[Run = i])); sum(a[@sex=1, exposure = 'Alternative'], mort_endpoint_bioher)~
~
var a:= Whatif( Yll_tot, exposures, exp);~
sum(a[@sex=1, exposure = 'Alternative'], mort_endpoint_bioher)~

Definition: var a:= for i := Run do (Whatif( Yll_tot, exposures, exp[Run = i])); sum(a[@sex=1, exposure = 'Alternative'], mort_endpoint_bioher)~

NodeLocation: 416,664,1
NodeSize: 48,24
WindState: 2,108,146,476,386

Close Model2

Module Pm2_5_emissions___ex
Title: PM2.5
Author: vkoe
Date: 25. Octta 2011 11:15
DefaultSize: 48,24
NodeLocation: 128,176,1
NodeSize: 52,28
DiagState: 2,17,397,470,510,17
NodeColor: 52427,63897,65535

Chance If_source_categories
Title: PM2.5 intake fraction
Description: Domestic from Piltti~
Others from Kopra~

Definition: Table(Power_capacity)(~
Triangular(0.00000018,0.00000028,0.00000037),Triangular(0.00000027,0.00000034,0.00000044),Triangular(0.00000027,0.00000034,0.00000044),Triangular(0.0000024,0.0000034,0.0000044))
NodeLocation: 112,392,1
NodeSize: 48,24
WindState: 2,329,205,476,224
DefnState: 2,227,328,416,303,0,MIDM
ValueState: 2,555,505,323,303,0,MIDM
NodeColor: 65535,52427,61166

Index Wood_heater
Title: Wood heater
Definition: ['Manual with accumulator','Manual without accumulator','Auto feed wood chip boiler','Auto feed pellet boiler','Iron stove','Masonry heater','Open fireplace']
NodeLocation: 112,88,1
NodeSize: 48,12
WindState: 2,464,250,476,224
{!40000|Att_PrevIndexValue: ['Manual with accumulator','Manual without accumulator','Auto feed wood chip boiler','Auto feed pellet boiler','Iron stove','Masonry heater','Open fireplace']}

Variable Wh_frac
Title: Wood heater fraction BAU
Description: Lähde: Karvosenoja 2008
Definition: Table(Wood_heater)(~
0.27,0.13,0.07000000000000001,5m,7m,0.507,8m)
NodeLocation: 112,56,1
NodeSize: 48,24
WindState: 2,179,150,476,382
DefnState: 2,147,361,416,303,0,MIDM
ValueState: 2,260,276,416,303,0,MIDM
NodeColor: 65535,52427,61166

Chance Wh_pm_emf
Title: Wood heater PM2.5 EMF
Units: mg/MJ
Description: Lähde: Karvosenoja 2008~
~
Vanhojen ja uusien takkojen päästöjakauman moodi perustuu Niko Karvosenojan arvioihin. Epävarmuusrajat on määritetty omaan veikkaukseen perustuen (+- 30%). Niko käyttää 2008 julkaisussa ilmoitettuja epävarmuusrajoja. Ne sisältävät kuitenkin myös saunakiukaat jne., joten ei sovellu kovin hyvin sellaisenaan tähän (?).
Definition: Table(Wood_heater,House_area_type)(~
Triangular(37.6,80,150),Triangular(37.6,80,150),~
Triangular(329,700,1310),Triangular(329,700,1310),~
Triangular(23.5,50, 93.9),Triangular(23.5,50, 93.9),~
Triangular(14.1,30,56.3),Triangular(14.1,30,56.3),~
Triangular(329,700,1310),Triangular(329,700,1310),~
Triangular(56,80,104),Uniform(91,130,170),~
Triangular(376,800,1500),Triangular(376,800,1500)~
)
NodeLocation: 112,136,1
NodeSize: 48,24
WindState: 2,146,152,476,224
DefnState: 2,200,470,521,303,0,MIDM
ValueState: 2,139,176,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [House_area_type,Wood_heater]
ReformVal: [House_area_type,Wood_heater]

Variable Pm_source_type
Title: PM2.5 source type
Definition: Table(Heat_system,Power_capacity)(~
0,0,0,1,~
0,0,0,1,~
0,0,0,1,~
0,0,1,0,~
0,0,1,0,~
1,1,1,0,~
1,1,1,0,~
1,1,1,0,~
0,0,0,1,~
1,1,1,0~
)
NodeLocation: 112,296,1
NodeSize: 48,24
DefnState: 2,256,209,416,303,0,MIDM
ValueState: 2,223,284,416,303,0,MIDM
ReformDef: [Power_capacity,Heat_system]
ReformVal: [Power_capacity,Heat_system]

Variable Pm_exposure
Title: PM2.5 exposure
Units: ug/m3
Description: Average annual exposure
Definition: var a:=sum((Pm_emission*If_source_categories)/(sum(pop_data,age,sex)*20*365)*1000, Power_capacity);~
a
NodeLocation: 256,392,1
NodeSize: 48,24
WindState: 2,171,206,557,343
ValueState: 2,125,306,574,339,0,MIDM
ReformVal: [Fu_period,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Heat_system
{!40000|Att_ResultSliceState: [Tot_heat_con,2,Bioher_pri_heat_scen,6,Fu_period,4]}

Variable Dom_pm_emf
Title: Domestic heat production PM2.5 EMF
Units: mg/MJ
Description: Emission factors for domestic and local district heating systems~
~
Assumption: fraction of devices in 'other wood boiler' and 'secondary wood' category stay the same in the future~
~
Note: average PM emission factors for electricity and current district heat production are calculated in the node 'PM emission' (identifier: pm_emission)
Definition: Table(Heat_system,House_area_type)(~
2,2,~
Wh_pm_emf[Wood_heater='Auto feed pellet boiler'],Wh_pm_emf[Wood_heater='Auto feed pellet boiler'],~
Wh_pm_emf[Wood_heater='Auto feed wood chip boiler'],Oth_wood_boil_emf,~
0,0,~
0,0,~
0,0,~
0,0,~
0,0,~
Wh_pm_emf[Wood_heater='Masonry heater'],Wh_pm_emf[Wood_heater='Masonry heater'],~
0,0~
)
NodeLocation: 256,136,1
NodeSize: 48,32
WindState: 2,107,303,476,340
DefnState: 2,674,511,753,303,0,MIDM
ValueState: 2,125,150,378,308,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [House_area_type,Heat_system]
ReformVal: [House_area_type,Heat_system]

Chance Pp_pm_emf
Title: Power plant PM2.5 EMF
Units: mg/MJ
Description: Yli 20 MW laitosten päästökertoimet ovat VTT:n raportista (Ohlström ym. 2005)~
~
Alle 20 MW laitosten päästökertoimet ovat SYKE:n raportista (Jalovaara ym. 2003)~
~
Vuodesta 2017 eteenpäin päästöjakauman yläraja asetettu IE-direktiivin (>50 MW laitokset) sekä PINO-asetuksen (<50 MW laitokset) TSP päästörajan mukaan. IE-direktiivi tulee voimaan olemassa olevilla laitoksilla 1.1.2016 ja PINO-asetus olemassa olevilla laitoksilla 1.1.2018. Uusilla tätä aikaisemmin. TSP raja varmaan yliarvioi PM2.5 päästöjen ylärajaa, mutta toisaalta paremmat suodattimet varmaan tehostavat erityisesti suurimpien hiukkasten poistoa. Suurissa (>50 MW) voimalaitoksissa PM2.5 osuus TSP:stä on jotain väliltä 10-60% (tieto Niko Karvosenojalta).~

Definition: Table(Fu_period,Pp_fuel,Power_capacity)(~
uniform(4,13),uniform(2,24),uniform(10,90),0,~
0,0,0,0,~
uniform(2,20),uniform(4,23),uniform(10,150),0,~
uniform(3,15),uniform(5,15),uniform(5,50),0,~
uniform(1,15),uniform(2,20),uniform(10,150),0,~
10,10,40,0,~
10,10,40,0,~
uniform(4,8.7),uniform(2,14.5),uniform(10,40.6),0,~
0,0,0,0,~
uniform(2,12),uniform(4,20),uniform(10,60),0,~
uniform(3,10.8),uniform(5,18),uniform(5,18),0,~
uniform(1,11.4),uniform(2,19),uniform(10,57),0,~
10,10,40,0,~
10,10,40,0,~
uniform(4,8.7),uniform(2,14.5),uniform(10,40.6),0,~
0,0,0,0,~
uniform(2,12),uniform(4,20),uniform(10,60),0,~
uniform(3,10.8),uniform(5,18),uniform(5,18),0,~
uniform(1,11.4),uniform(2,19),uniform(10,57),0,~
10,10,40,0,~
10,10,40,0,~
uniform(4,8.7),uniform(2,14.5),uniform(10,40.6),0,~
0,0,0,0,~
uniform(2,12),uniform(4,20),uniform(10,60),0,~
uniform(3,10.8),uniform(5,18),uniform(5,18),0,~
uniform(1,11.4),uniform(2,19),uniform(10,57),0,~
10,10,40,0,~
10,10,40,0,~
uniform(4,8.7),uniform(2,14.5),uniform(10,40.6),0,~
0,0,0,0,~
uniform(2,12),uniform(4,20),uniform(10,60),0,~
uniform(3,10.8),uniform(5,18),uniform(5,18),0,~
uniform(1,11.4),uniform(2,19),uniform(10,57),0,~
10,10,40,0,~
10,10,40,0,~
uniform(4,8.7),uniform(2,14.5),uniform(10,40.6),0,~
0,0,0,0,~
uniform(2,12),uniform(4,20),uniform(10,60),0,~
uniform(3,10.8),uniform(5,18),uniform(5,18),0,~
uniform(1,11.4),uniform(2,19),uniform(10,57),0,~
10,10,40,0,~
10,10,40,0~
)
NodeLocation: 112,208,1
NodeSize: 48,32
WindState: 2,205,88,476,451
DefnState: 2,180,269,607,303,0,MIDM
ValueState: 2,91,283,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Power_capacity,Pp_fuel]
ReformVal: [Power_capacity,Pp_fuel]
{!40000|Att_ResultSliceState: [Fu_period,6,Pp_fuel,1,Power_capacity,1]}
{!40000|Att_EditSliceState: [Fu_period,1,Pp_fuel,1,Power_capacity,1]}

Chance Pm_emission
Title: PM2.5 emission
Units: mg/a
Description: Emissions for current district heat and electricity production are calculated based on: ~
~
*Heat/electricity produced (kWh/a) in different types of power plants and the efficiency of the plants~
*Average PM2.5 emission factor (mg/MJ) for different types of heat/electricity power plants based on~
**Fuels used in different types of power plants~
**Filtering capacity/emission standards for different types of plants~
~
*Local district, wood sekä Local district, oil: PM2.5 päästökerroin määritetty Niko Karvosenojalta ja Mikko Savolahdelta saatujen tietojen perusteella. Päästökerroin on pienille 1-5 MW:n laitoksille joissa savukaasut puhdistetaan ainoastaan syklonin avulla. Jakauman alaraja määräytyy sen mukaan, että sen on päästökattona 5-10 MW:n laitoksissa PINO-asetuksessa ja sen alle pääsemiseen vaaditaan kuulemma jo syklonia tehokkaampi hiukkaserotin. Alaraja voi  siis myös aliarvioida kaikkein pienimpien, vain syklonia käyttävien laitosten päästöjakaumaa.~
~
var f:=sum(k*Pm_source_type{, heat_system});~
f:=f[Heat_system='Pellet boiler']+f[Heat_system='Other wood boiler'];~
sum(f, heat_system)~
~
var f:=(k*Pm_source_type)[Bioher_pri_heat_scen='BAU'];~
f:= f[Heat_system='Pellet boiler']+f[Heat_system='Other wood boiler'];~
f[const_year='1990']
Definition: var t:= if Bioher_sec_heat_scen = 'All' then Area_heat_purc else Area_heat_purc[Bioher_sec_heat_scen = Bioher_sec_heat_scen];~
~
var k:=If heat_system = 'Current district' then ~
~
var a:=t*dh_pp_frac/dh_pp_effic*Dh_pp_capacity;~
var b:=sum(Dist_heat_fuel*Pp_pm_emf, pp_fuel);~
sum(a*3.6*b, dh_pp)~
~
else ~
~
if heat_system = 'Geothermal' or heat_system = 'Electricity' or heat_system = 'Air heat pump' then~
~
var a:=t*elect_pp_frac/elect_pp_effic*elect_pp_capacity;~
var b:=sum(Elect_fuel*Pp_pm_emf, pp_fuel);~
sum(a*3.6*b, elect_pp)~
~
else~
~
if heat_system = 'Local district, oil' then~
t/0.9*uniform(2,30)*3.6~
~
else~
~
if heat_system = 'Local district, wood' then~
t/0.9*uniform(60,150)*3.6~
~
else~
~
t*Dom_pm_emf[House_area_type=House_area_type]*3.6;~
~
sum(k*Pm_source_type, heat_system)~
~
~
~

NodeLocation: 256,296,1
NodeSize: 48,24
WindState: 2,198,75,474,778
ValueState: 2,102,216,529,333,0,MIDM
ReformVal: [Power_capacity,Bioher_pri_heat_scen]
{!40000|Att_ResultSliceState: [Fu_period,2,Tot_heat_con,1,Bioher_pri_heat_scen,7,Power_capacity,1]}

Variable Oth_wood_boil_emf
Title: Other wood boiler EMF BAU
Description: Average PM emission factor for non-pellet wood boilers based on:~
*PM emission factor for different types of boilers~
*fraction of these boilers in wood heating in Finland~
~
Data: Kavosenoja, Piltti-malli~
~
Assumption: other wood boilers are:~
*Manual with accumulator~
*Manual without accumulator~
*Auto feed wood chip boiler
Definition: var a:=Wh_frac[wood_heater='Manual with accumulator']+Wh_frac[wood_heater='Manual without accumulator']+Wh_frac[wood_heater='Auto feed pellet boiler']+Wh_frac[wood_heater='Auto feed wood chip boiler'];~
a:=1/a;~
a:=Wh_frac*a*Wh_pm_emf[House_area_type='Old'];~
a[wood_heater='Manual with accumulator']+a[wood_heater='Manual without accumulator']+a[wood_heater='Auto feed wood chip boiler']
NodeLocation: 256,56,1
NodeSize: 48,24
WindState: 2,126,106,552,518
ValueState: 2,117,178,416,303,0,MIDM
Att__TotalsIndex: Index Wood_heater

Close Pm2_5_emissions___ex

Module Claih1
Title: CLAIH
Author: vkoe
Date: 25. Octta 2011 11:15
DefaultSize: 48,24
NodeLocation: 552,88,1
NodeSize: 48,24
NodeInfo: 1,0,0,1,1,1,0,,0,
DiagState: 2,283,22,956,606,17

Index Pollutant
{!40000|Att_PrevIndexValue: ['PM','Radon','Mold']}
Title: Pollutant
Definition: ['PM','Radon','Mold']
NodeLocation: 100,36,1
NodeSize: 52,12

Variable Mort_erf_claih
Title: Mortality ERF Claih
Description: Exposure-response functions for mortality, defined as relative risk (RR)~
~
This node is used if the ERF differs between age groups~
~
*Relative risk =1 if there is no known dependence between the studied exposure and a particular cause of death~
*Absolute risk = 0 If there is no known dependence between the studied exposure and a particular cause of death
Definition: Table(Age,Sex,Erf_type,Mort_endpoint_bioher,Pollutant)(~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0~
)
NodeLocation: 104,88,1
NodeSize: 48,24
WindState: 2,125,89,476,532
DefnState: 2,365,144,498,534,0,MIDM
ValueState: 2,152,162,511,641,0,MIDM
NodeColor: 65535,52427,57888
ReformDef: [Mort_endpoint_bioher,Age]
ReformVal: []
{!40000|Att_ResultSliceState: [Sex,1,Erf_type,1,Run,21,Pollutant,1,Age,1,Mort_endpoint,1]}
{!40000|Att_EditSliceState: [Sex,1,Erf_type,2,Pollutant,3,Age,1,Mort_endpoint_bioher,1]}

Index Pm_source
Title: PM source
Description: Small power plants: <50 MW thermal capacity~
Large power plants: >50 MW thermal capacity)
Definition: ['Domestic','Small power plant','Large power plant']
NodeLocation: 96,36,1
NodeSize: 48,12
WindState: 2,98,90,476,326
DisplayOutputs: Variable Domwood_pm_emis

Module Building_stock
Title: Building stock
Author: vkoe
Date: 15. Janta 2009 6:55
DefaultSize: 48,24
NodeLocation: 120,168,1
NodeSize: 48,24
DiagState: 2,85,92,796,571,17
NodeColor: 52427,63897,65535

Index Building_type
{!40000|Att_PrevIndexValue: ['Detached house','Row house','Apartment building']}
Title: Building type
Definition: ['Detached house','Row house','Apartment building']
NodeLocation: 320,192,1
NodeSize: 48,12
DisplayOutputs: Variable Domwood_pm_emis

Variable Bs_current
Title: Current building stock
Description: ~
~
Cbs_heat_sys*House_energy_efficie
Definition: var a:=Cbs_age*Heat_system_by_year;~
a:=a/sum(a,const_year);~
a:=a*Cbs_heat_sys;~
a/sum(a,const_year);~
a*Bs_energy_effic_cur
NodeLocation: 320,152,1
NodeSize: 48,28
WindState: 2,147,104,590,431
ValueState: 2,152,250,643,292,1,MIDM
ReformVal: [Const_year,Heat_sys_prim]
Att__TotalsIndex: Index Building_type, Index Energy_class, Index Heat_sys_prim, Decision Const_year
{!40000|Att_ResultSliceState: [Energy_class,1,Building_type,1,Heat_sys_prim_orig,2,Const_year,6]}

Variable Cbs_heat_sys
Title: Current heat systems
Units: m2
Description: Current building stock by heating type, floor area
Definition: Table(Building_type,Heat_sys_prim)(~
9.75642M,37.696145M,29.872312M,67.265322M,3.603349M,2.730025M,~
15.113361M,7.525292M,200.314K,9.247771M,47.74K,146.664K,~
77.47528M,9.553845M,347.294K,1.318741M,19.602K,549.336K~
)
NodeLocation: 200,96,1
NodeSize: 48,24
WindState: 2,916,530,476,224
DefnState: 2,468,482,692,303,0,MIDM
ValueState: 2,287,185,719,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Building_type,Heat_sys_prim]
ReformVal: [Heat_sys_prim,Building_type]
Att__TotalsIndex: Index Building_type, Index Heat_sys_prim
{!40000|Att_ResultSliceState: [Building_type,2,Heat_system,1]}
{!40000|Att_EditSliceState: [Heat_system,4,Area1,1,Building_type,1]}

Index Energy_class
{!40000|Att_PrevIndexValue: ['Traditional','Current standard','Low-energy','Passive house']}
Title: Energy class
Definition: ['Traditional','Current standard','Low-energy','Passive house']
NodeLocation: 320,88,1
NodeSize: 48,12

Variable Bs_energy_effic_cur
Title: Current building stock energy efficiency
Description: Fraction of current building stock in different energy efficiency classes by building heating type
Definition: Table(Building_type,Energy_class,Const_year)(~
1,1,1,1,1,1,0,0,0,~
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,~
1,1,1,1,1,1,0,0,0,~
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,~
1,1,1,1,1,1,0,0,0,~
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~
)
NodeLocation: 320,48,1
NodeSize: 48,32
DefnState: 2,372,116,661,303,0,MIDM
ValueState: 2,328,338,702,260,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Energy_class]
{!40000|Att_ResultSliceState: [Building_type,1,Heating_system,2,Energy_class,1,Subsidies_for_energy,1]}
{!40000|Att_EditSliceState: [Building_type,1,Const_year,1,Energy_class,1]}

Variable Cbs_age
Title: Current building stock age
Units: m2
Description: Current building stock by age, floor area
Definition: Table(Building_type,Const_year)(~
40.802288M,14.074485M,21.999879M,29.136341M,18.950781M,21.619076M,0,0,0,~
971.421K,1.911846M,7.63526M,11.476249M,5.729734M,4.282367M,0,0,0,~
16.235186M,15.83794M,23.525259M,12.025787M,10.825779M,9.934372M,0,0,0~
)
NodeLocation: 200,152,1
NodeSize: 48,24
DefnState: 2,340,354,787,302,0,MIDM
ValueState: 2,900,302,787,324,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Const_year,Building_type]
ReformVal: [Const_year,Building_type]
Att__TotalsIndex: Index Building_type, Decision Const_year

Variable Heat_system_by_year
Title: Heat system by year
Units: -
Description: Fraction of heat systems in new detached houses constructed in different decades (heat system selected when constructed)~
~
Ei kovin hyvä lähestymistapa sellaisenaan, koska yliarvioi öljylämmityksen osuutta ja aliarvioi erityisesti puulämmityksen osuutta (ei huomioi siirtymistä öljylämmityksestä muihin vaihtoehtoihin, aliarvioi puulämmityksen osuutta vanhassa rakennuskannassa (?)).
Definition: Table(Building_type,Heat_sys_prim,Const_year)(~
0.04,0.04,0.06,0.08,0.08,0.13,0.16,0.16,0.16,~
0.67,0.67,0.57,0.2,0.15,0.12,0.09,0.09,0.09,~
0.04,0.04,0.14,0.16,0.07000000000000001,0.05,0.05,0.05,0.05,~
0.25,0.25,0.23,0.53,0.66,0.59,0.54,0.54,0.54,~
100u,100u,100u,0.01,0.01,0.09,0.14,0.14,0.14,~
100u,100u,100u,0.02,0.03,0.02,0.02,0.02,0.02,~
0.28,0.31,0.33,0.46,0.5600000000000001,0.59,0.59,0.59,0.59,~
0.6,0.59,0.58,0.16,0.19,0.09,0.09,0.09,0.09,~
0,0,0,0.01,0,0,0,0,0,~
0.13,0.11,0.09,0.37,0.25,0.31,0.31,0.31,0.31,~
100u,100u,100u,100u,100u,0.01,0.01,0.01,0.01,~
100u,100u,100u,100u,100u,100u,100u,100u,100u,~
0.72,0.72,0.72,0.91,0.96,0.98,0.98,0.98,0.98,~
0.28,0.28,0.28,0.06,0.03,0.02,0.02,0.02,0.02,~
1m,1m,1m,1m,1m,1m,1m,1m,1m,~
0,0,0,0.03,0.01,0,0,0,0,~
100u,100u,100u,100u,100u,100u,100u,100u,100u,~
100u,100u,100u,0.02,0.03,0.02,0.02,0.02,0.02~
)
NodeLocation: 200,40,1
NodeSize: 48,24
WindState: 2,98,90,476,430
DefnState: 2,275,25,676,268,0,MIDM
ValueState: 2,473,161,767,263,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heat_sys_prim,Const_year]
ReformVal: [Const_year,Heat_sys_prim]
Att__TotalsIndex: Index Heat_sys_prim, Decision Const_year
{!40000|Att_ResultSliceState: [Building_type,1,Heat_system,1,Const_year,1]}
{!40000|Att_EditSliceState: [Building_type,1,Const_year,1,Heat_sys_prim,1]}

Module Mo2
Author: vkoe
Date: 8. Febta 2011 9:41
DefaultSize: 48,24
NodeLocation: 88,592,1
NodeSize: 48,24
NodeInfo: 1,0,1,1,1,1,0,,0,
DiagState: 1,384,175,550,300,17

Index Efficiency_renovatio
{!40000|Att_PrevIndexValue: ['Traditional','Current standard','Low-energy','Passive house']}
Title: Efficiency renovation
Definition: copyindex(Energy_class)
NodeLocation: 96,88,1
NodeSize: 48,16

Variable Efficiency_renovati1
Title: Efficiency renovations
Description: m2 renovated annually from one energy class to another
Definition: Table(Energy_class,Efficiency_renovatio)(~
0,50,0,0,~
0,0,50,0,~
0,0,0,50,~
0,0,0,0~
)
NodeLocation: 96,48,1
NodeSize: 48,24
DefnState: 2,344,354,595,319,0,MIDM
ValueState: 2,594,132,551,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Efficiency_renovatio,Energy_class]
ReformVal: [Efficiency_renovatio,Energy_class]
{!40000|Att_ResultSliceState: [Subsidies_for_energy,1,Efficiency_renovatio,1,Energy_class,1]}
{!40000|Att_EditSliceState: [Subsidies_for_energy,1,Efficiency_renovatio,1,Energy_class,1]}

Variable Energy_fractions_of_
Title: Energy fractions of new buildings
Definition: Table(Building_type,Energy_class,Heat_sys_prim)(~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0~
)
NodeLocation: 336,112,1
NodeSize: 48,29
DefnState: 2,345,404,648,303,0,MIDM
ValueState: 2,504,514,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Energy_class,Heat_sys_prim]
ReformVal: [Energy_class,Heat_sys_prim]

Variable Future_building_stoc
Title: Future building stock
Definition: var a:= Bs_current;~
var b:= sum(Efficiency_renovati1,Energy_class)[Efficiency_renovatio=Energy_class];~
a:= a +b*a/sum(a,Heat_sys_prim);~
b:= sum(Efficiency_renovati1,Efficiency_renovatio);~
a:= a -b*a/sum(a,Heat_sys_prim);~
~
b:= sum(Heating_renovations,Heat_sys_prim)[Heating_renovation=Heat_sys_prim];~
a:= a +b*a/sum(a,Energy_class);~
b:= sum(Heating_renovations,Heating_renovation);~
a:= a -b*a/sum(a,Energy_class);~
~
a +New_buildings*Energy_fractions_of_
NodeLocation: 224,48,1
NodeSize: 48,24
WindState: 2,117,88,574,521
ValueState: 2,141,350,758,303,0,MIDM
ReformVal: [Heat_sys_prim,Energy_class]
Att__TotalsIndex: Index Energy_class, Index Heat_sys_prim
{!40000|Att_ResultSliceState: [Building_type,2,Const_year,3,Energy_class,1,Heat_system,1]}

Variable Heating_renovations
Title: Heating renovations
Description: m2 renovated annually from one heating system to another
Definition: Table(Heat_sys_prim,Heating_renovation)(~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0~
)
NodeLocation: 96,136,1
NodeSize: 48,24
DefnState: 2,88,98,646,303,0,MIDM
ValueState: 2,648,67,505,318,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heating_renovation,Heat_sys_prim]
ReformVal: [Heating_renovation,Heat_sys_prim]
{!40000|Att_EditSliceState: [Decision_on_heat_pro,2,Building_type,1,Heating_renovation,1,Heating_system,1]}

Index Heating_renovation
{!40000|Att_PrevIndexValue: ['District','Light oil','Wood','Electricity','Geothermal','Other']}
Title: Heating renovation
Definition: Copyindex(Heat_sys_prim)
NodeLocation: 96,176,1
NodeSize: 48,16

Variable New_buildings
Title: New buildings
Units: m2
Definition: Table(Building_type,Heat_sys_prim)(~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0~
)
NodeLocation: 336,48,1
NodeSize: 48,24
DefnState: 2,248,258,607,303,0,MIDM
ValueState: 2,488,498,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heat_sys_prim,Building_type]
ReformVal: [Building_type]
{!40000|Att_EditSliceState: [Building_type,1,Decision_on_heat_pro,2,Area1,1,Heating_system,1]}

Close Mo2

Objective Bs_devel
Title: Building stock development
Definition: Bs_current-Bs_loss+Bs_new
NodeLocation: 320,288,1
NodeSize: 48,28
DefnState: 2,716,306,416,303,0,MIDM
ValueState: 2,118,366,785,303,0,MIDM
ReformVal: [Const_year,Heat_sys_prim]
DisplayOutputs: Variable Domwood_pm_emis
Att__TotalsIndex: Index Building_type, Index Energy_class, Index Heat_sys_prim, Decision Const_year
{!40000|Att_ResultSliceState: [Building_type,0,Energy_class,0,Fu_period_claih,2,Heat_system,1,Const_year,1]}

Variable New_build
Title: Annual new buildings
Units: m2/a
Description: Uudisrakentaminen korvaa poistuman. Lisäksi asumisväljyys kasvaa nykyisestä 39 m2/hlö ollen vuonna 2050 n. 50 m2/hlö. Oletus on, että asumisväljyys kasvaa lineaarisesti, eli n. 0.275 m2/hlö vuosittain. Asukasmäärän muutoksia ei oteta tässä nyt huomioon.~

Definition: Building_stock_loss+sum(Bs_current, const_year, energy_class, Heat_sys_prim)*0.007
NodeLocation: 552,288,1
NodeSize: 48,24
WindState: 2,61,86,476,224
ValueState: 2,413,177,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Building_stock_loss
Title: Annual building stock loss
Units: m2/year
Description: Vuosittainen poistuma on n. 0.3% koko rakennuskannasta vuosien 2010-2019 välillä. Poistuman voidaan olettaa kohdistuvan yli 50 vuotta vanhoihin rakennuksiin.
Definition: sum(Bs_current, const_year, energy_class, Heat_sys_prim)*0.003
NodeLocation: 88,288,1
NodeSize: 48,24
WindState: 2,422,466,476,224
ValueState: 2,247,191,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformVal: [Heat_sys_prim,Building_type]
Att__TotalsIndex: Index Building_type

Variable Building_stock_loss1
Title: Building stock loss fraction
Definition: Table(Energy_class,Const_year,Fu_period)(~
1,2,2.5,3,3+(1/3),3+(1/3)+(1/4),~
0,0,0.5,1,1+(1/3),1+(1/3)+(1/4),~
0,0,0,0,(1/3),(1/3)+(1/4),~
0,0,0,0,0,1/4,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0~
)
NodeLocation: 88,352,1
NodeSize: 48,24
DefnState: 2,244,57,648,303,0,MIDM
ValueState: 2,409,120,732,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Fu_period,Const_year]
ReformVal: [Const_year]
Att__TotalsIndex: Decision Const_year
{!40000|Att_EditSliceState: [Energy_class,1,Const_year,1]}

Variable Bs_loss
Title: Building stock loss
Definition: var a:=Bs_current;~
var b:=sum(a, Heat_sys_prim);~
b:= if b = 0 then 1 else b;~
b:=a/b;~
~
Building_stock_loss1*b*Building_stock_loss*5
NodeLocation: 200,288,1
NodeSize: 48,24
ValueState: 2,117,223,589,334,0,MIDM
ReformVal: [Heat_sys_prim,Const_year]
Att__TotalsIndex: Index Heat_sys_prim, Decision Const_year
{!40000|Att_ResultSliceState: [Building_type,1,Energy_class,1,Fu_period,6,Const_year,1,Heat_system,1]}

Variable New_building_energy
Title: New building heat fraction
Definition: (Bs_current[Const_year='2000',energy_class='Traditional'])/sum((Bs_current[Const_year='2000',energy_class='Traditional']),Heat_sys_prim)
NodeLocation: 552,352,1
NodeSize: 48,24
WindState: 2,305,250,476,224
DefnState: 2,40,100,1062,303,0,MIDM
ValueState: 2,88,98,706,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Const_year]
ReformVal: [Heat_sys_prim,Building_type]
{!40000|Att_EditSliceState: [Const_year,7,Building_type,2,Energy_class,1,Heat_system,1]}

Variable New_building_energy_
Title: New building energy fraction
Definition: Table(Energy_class,Const_year)(~
0,0,0,0,0,0,0,0,0,~
0,0,0,0,0,0,1,1,1,~
0,0,0,0,0,0,0,0,0,~
0,0,0,0,0,0,0,0,0~
)
NodeLocation: 552,408,1
NodeSize: 48,24
DefnState: 2,120,130,765,303,0,MIDM
ValueState: 2,120,130,789,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Energy_class,Const_year]
ReformVal: [Energy_class,Const_year]

Variable Bs_new
Title: Building stock new
Definition: New_build*5*New_building_energy*New_building_energy_*Help1
NodeLocation: 440,288,1
NodeSize: 48,24
ValueState: 2,138,244,809,303,0,MIDM
ReformVal: [Const_year,Heat_sys_prim]
Att__TotalsIndex: Index Heat_sys_prim
{!40000|Att_ResultSliceState: [Building_type,1,Energy_class,2,Fu_period,7,Heat_system,1,Const_year,1]}

Variable Help1
Title: help
Definition: Table(Const_year,Fu_period)(~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
1,2,2,2,2,2,~
0,0,1,2,2,2,~
0,0,0,0,1,2~
)
NodeLocation: 656,288,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
DefnState: 2,217,227,692,303,0,MIDM
ReformDef: [Fu_period,Const_year]

Variable Heat_system_renovati
Title: Heat system renovations
Definition: 0
NodeLocation: 320,352,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Energy_efficiency_re
Title: Energy efficiency renovations
Definition: 0
NodeLocation: 320,408,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Va1
Definition: var a:=Cbs_heat_sys[building_type='Detached house'];~
a/sum(a, heat_sys_prim)
NodeLocation: 80,96,1
NodeSize: 48,24
ValueState: 2,328,724,416,303,0,MIDM

Close Building_stock

Index Heat_sys_prim
{!40000|Att_PrevIndexValue: ['District','Light oil','Wood','Electricity','Geothermal','Other']}
Title: Prim heat sys
Definition: ['District','Light oil','Wood','Electricity','Geothermal','Other']
NodeLocation: 208,352,1
NodeSize: 56,12
WindState: 2,98,90,476,256
DisplayOutputs: Variable Domwood_pm_emis

Decision Dec_build_heat
Title: Building heating system
Definition: ['BAU']
NodeLocation: 272,56,1
NodeSize: 48,28

Decision Dec_dh_prod
Title: District heat production
Definition: ['BAU']
NodeLocation: 496,56,1
NodeSize: 48,28

Decision Dec_build_ef
Title: Building energy efficiency
Definition: ['BAU']
NodeLocation: 384,56,1
NodeSize: 48,28
WindState: 2,102,90,476,224

Module Household_heating_co
Title: Cost from household heating
Author: vkoe
Date: 15. Janta 2009 6:55
DefaultSize: 48,24
NodeLocation: 392,312,1
NodeSize: 48,29
NodeInfo: 1,1,1,1,1,1,0,,0,
DiagState: 1,153,62,646,476,17

Variable Costs_from_energy_pr
Title: Cost from district heating infrastructure
Definition: 0
NodeLocation: 456,96,1
NodeSize: 48,32

Variable Cost_heat_renov
Title: Cost of heating renovation
Units: e
Definition: Cost_of_new_heat__s+Value_of_old_heat__s
NodeLocation: 320,296,1
NodeSize: 48,24
DefnState: 2,129,535,669,303,0,MIDM
ValueState: 2,88,98,665,303,0,MIDM
NodeColor: 19661,48336,65535
ReformDef: [Heat_sys_prim,Heating_renovation]
ReformVal: [Heat_sys_prim,Heating_renovation]
{!40000|Att_ResultSliceState: [Building_type,2,Heating_renovation,1,Heating_system,1]}

Variable Costs_from_energy_co
Title: Cost from household heating
Units: e/m2
Definition: {Operating cost:}~
var a:= Q_heat_purchase*Energy_price*Fu_time;~
~
{Investment cost:}~
var b:= (Cost_heat_renov+Cost_effic_renov)/Size_single_family_h/Fu_time;~
~
a+b
NodeLocation: 456,296,1
NodeSize: 48,24
WindState: 2,430,168,476,313
ValueState: 2,450,197,582,378,0,MIDM
ReformVal: [Efficiency_renovatio,Heat_sys_prim]
{!40000|Att_ResultSliceState: [Building_type,1,Energy_class,2,Citizen__household_h,2,Heating_system,2,Efficiency_renovatio,2]}

Variable Energy_price
Title: Energy price
Units: e/kWh
Definition: Table(Heat_sys_prim)(~
0.04670000000000001,0.06800000000000001,0.023,0,0.077,0)
NodeLocation: 456,224,1
NodeSize: 48,24
WindState: 2,102,90,476,224
DefnState: 2,344,354,416,303,0,MIDM
ValueState: 2,472,482,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Cost_effic_renov
Title: Cost of energy effic. renovation
Units: e
Definition: Table(Efficiency_renovatio,Energy_class)(~
0,0,0,0,~
100,0,0,0,~
200,100,0,0,~
300,200,100,0~
)
NodeLocation: 320,352,1
NodeSize: 48,23
DefnState: 2,440,450,591,204,0,MIDM
ValueState: 2,408,418,562,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Energy_class,Efficiency_renovatio]
ReformVal: [Efficiency_renovatio,Energy_class]

Variable Size_single_family_h
Title: Building size
Units: m2
Definition: 120
NodeLocation: 320,240,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Value_of_old_heat__s
Title: Value of old heat. system
Units: e
Definition: var a:= Original_value-(Original_value/Life_scale*Age_heat_syst);~
~
if isnan(a)=1 then 0 else a~

NodeLocation: 208,320,1
NodeSize: 48,24
WindState: 2,554,110,476,224
ValueState: 2,152,162,416,303,0,MIDM

Variable Cost_of_new_heat__s
Title: Cost of new heat. system
Definition: Table(Heating_renovation,Heat_sys_prim)(~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
0,0,0,0,0,0,~
1000,1000,1000,1000,1000,1000,~
0,0,0,0,0,0~
)
NodeLocation: 208,264,1
NodeSize: 48,24
DefnState: 2,152,162,673,303,0,MIDM
ValueState: 2,208,522,774,244,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heating_renovation,Heat_sys_prim]
ReformVal: [Heating_renovation,Heat_sys_prim]

Variable Age_heat_syst
Title: Heat. system age
Units: a
Definition: Table(Heat_sys_prim)(~
0,10,0,0,0,0)
NodeLocation: 96,320,1
NodeSize: 48,24
ValueState: 2,56,66,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Life_scale
Title: Heat system life cycle
Units: a
Definition: Table(Heat_sys_prim)(~
0,20,0,0,0,0)
NodeLocation: 96,376,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Original_value
Title: Heat. system original value
Units: e
Definition: Table(Heat_sys_prim)(~
0,1000,0,0,0,0)
NodeLocation: 96,264,1
NodeSize: 48,24
ValueState: 2,584,594,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Co2_price
Title: CO2 market price
Units: e/t
Definition: 13.8
NodeLocation: 568,88,1
NodeSize: 48,24

Variable Fu_time
Title: Followup time
Definition: 10
NodeLocation: 456,368,1
NodeSize: 48,24

Close Household_heating_co

Objective Total_heat_purchase
Title: Total heat purchase by heating type
Units: kWh/a
Definition: sum(Bs_devel*Q_heat_purchase, Const_year, Building_type, Energy_class)
NodeLocation: 256,144,1
NodeSize: 52,28
WindState: 2,258,192,476,224
ValueState: 2,114,195,627,306,0,MIDM
ReformVal: [Heat_sys_prim]
{!40000|Att_ResultSliceState: [Building_type,2,Const_year,1,Heat_system,1]}

Variable Exposure_mold
Title: Exposure to mold and dampness
Description: Fraction of exposed population
Definition: 15/100
NodeLocation: 208,240,1
NodeSize: 48,24

Variable Erf_mold
Title: ERF mold and asthma
Description: OR= 1.56 ~
~
RR=OR/(1-CR+(CR*OR))~
~
Asthma prevalence in Finland: 8%
Definition: 1.56/(1-0.08+(0.08*1.56))
NodeLocation: 96,240,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Exposure_radon
Title: Exposure to radon
Units: Bq/m3
Definition: 120
NodeLocation: 208,296,1
NodeSize: 48,24

Variable Erf_radon_lc
Title: ERF radon and lung cancer
Units: RR per Bq/m3
Definition: exp(ln(1.16)/100)
NodeLocation: 96,352,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Erf_pm_rad
Title: ERF PM2.5 and RAD
Units: / 10 ug3
Description: AR, 15-64 years old
Definition: 0.902
NodeLocation: 96,296,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Erf_pm_cb
Title: ERF PM2.5 and chronic bronchitis
Units: / 1 ug3
Description: AR, >27 years old
Definition: 5.33E-05
NodeLocation: 96,408,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Module Personal_exposure_pm
Title: Exposure to indoor PM2.5
Author: vkoe
Date: 8. Febta 2011 9:41
DefaultSize: 48,24
NodeLocation: 392,144,1
NodeSize: 48,28
DiagState: 2,32,26,700,485,17
NodeColor: 52427,63897,65535

Variable Combustion_time
Title: Combustion time
Units: h
Description: NEEDS: The combustion time. Thus, how long the wood is burned. One hour was used in scenario 4b, Table 5.5 (pages 154-155).~
~
LAMA: combustion time is 24h/day because source strenght is averaged assuming a given burn time
Definition: 24
NodeLocation: 432,112,1
NodeSize: 48,24
WindState: 2,345,106,476,224
NodeColor: 65535,52427,57888

Variable Emission_factor_
Title: Emission factor (R)
Units: ug/h
Description: NEEDS: Total PM10 emission (outdoor+indoor) is 7118750 ug/h for each hour of burning~
~
LAMA model: an average daily emission rate of PM2.5 to indoors is 2690 ug/h assuming a given burn time in a day
Definition: 2690
NodeLocation: 432,56,1
NodeSize: 48,24
NodeColor: 65535,52427,57888

Variable Removal_factor_1
Title: Removal factor (R)
Units: -
Description: Removal factor describes the amount of pollutant that is removed through chimney. Value 0 means that all the emissions are emitted to indoor and 1 means that all the emissions emitted outdoor. The NEEDS report desctibes in page 157 that R is probably more than 0.99, possibly even 0.999.~
~
The value 0.99 was used in Scenrio 4b.~
~
0.999 is used here, because it results in concentrations comparable to the LAMA model approach
Definition: .999
NodeLocation: 432,168,1
NodeSize: 48,24
NodeColor: 65535,52427,57888

Variable Pm_decay_rate
Title: PM2.5 decay rate
Units: /h
Description: Removal rate(deposition rate) describes the removal of PM from indoor air. The value used here (0.5) is from the NEEDS report (page 154, Table 5.4).~
~
LAMA model PM2.5 decay rate = normal(0.39, 0.09)
Definition: 0.39
NodeLocation: 200,176,1
NodeSize: 48,24
NodeColor: 65535,52427,57888

Variable Aeration_rate
Title: Building aeration rate
Units: 1/h
Description: Aeration rate is air exchange rate. Thus, how fast the air exchange. The value 1 id from NEEDS report.~
~
Aeration rate is assumed to be the sum of air exchange and air leak rate. AIr exchange should be 0.5/h~
~
Air_leak_factor+0.5
Definition: Air_leak_factor+0.5
NodeLocation: 312,176,1
NodeSize: 48,24
WindState: 2,785,103,476,224
ValueState: 2,282,233,615,303,0,MIDM
NodeColor: 65535,52427,57888
ReformVal: [Energy_class,Const_year]

Variable Pm_emis_indoor
Title: PM2.5 indoor emission
Units: ug
Description: Primary PM2.5 emissions to indoor air from domestic wood combustion.~
~
Emission_factor_*Combustion_time*(1-Removal_factor_1)~
~
Emission_factor_*Combustion_time*365~
~

Definition: Domwood_pm_emis*(1-Removal_factor_1)*1000
NodeLocation: 432,256,1
NodeSize: 48,24
WindState: 2,311,104,476,339
DefnState: 2,47,32,416,303,0,MIDM
ValueState: 2,182,99,619,303,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Energy_class,Const_year]
Att__TotalsIndex: Index Energy_class, Decision Const_year
{!40000|Att_ResultSliceState: [Fu_period,3,Const_year,1,Energy_class,1]}

Variable Volume_finland
Title: Wood heated building volume
Units: m3
Description: Total volume of wood heated houses in Finland. Average height assumed to be 2.5 m.~
~
sum(Build_stock_current[Heat_system='Wood'], building_type)*2.5
Definition: sum(Bs_devel[Heat_sys_prim='Wood'], building_type)*2.5
NodeLocation: 80,256,1
NodeSize: 48,24
WindState: 2,533,48,476,224
ValueState: 2,280,290,596,303,0,MIDM
ReformVal: [Energy_class,Const_year]

Variable Volume_indoor1
Title: Volume indoor
Units: m3
Description: This node applies to lower part of NEEDS report equation 1 from page 84.
Definition: (Aeration_rate+Pm_decay_rate)*24*365*Volume_finland
NodeLocation: 200,256,1
NodeSize: 48,24
WindState: 2,180,757,476,224
ValueState: 2,538,219,499,303,0,MIDM
ReformVal: [Energy_class,Const_year]

Variable Average_concentratio
Title: PM2.5 indoor concentration
Units: ug/m3
Description: Average indoor concentration of PM2.5 in year 2000 due to domestic wood combustion in different houses.
Definition: var a:=Pm_emis_indoor/Volume_indoor1;~
a:=if Volume_indoor1=0 then 0 else a;~
a~

NodeLocation: 312,256,1
NodeSize: 48,24
WindState: 2,439,71,476,283
ValueState: 2,146,62,521,303,0,MIDM
NodeColor: 65535,19661,38773
ReformVal: [Energy_class,Const_year]
{!40000|Att_ResultSliceState: [Fu_period,1,Const_year,1,Energy_class,1]}

Variable Pop_frac_indoor_pm
Title: Fraction of exposed population
Description: The fraction of population exposed to wood smoke PM2.5 in different housing conditions.~
~
Based on the fraction of wood heated building stock  from the whole building stock.
Definition: var a:=sum(Bs_devel,building_type);~
a[Heat_sys_prim='Wood']/sum(a,Heat_sys_prim,const_year,energy_class)~

NodeLocation: 432,376,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
WindState: 2,128,50,762,314
ValueState: 2,403,200,545,303,0,MIDM
NodeColor: 65535,52427,57888
ReformVal: [Energy_class,Const_year]
Att__TotalsIndex: Index Energy_class, Decision Const_year
{!40000|Att_ResultSliceState: [Fu_period,1,Const_year,1,Energy_class,1]}

Variable Population_average_e
Title: Pop average indoor conc
Units: ug/m3
Description: This node estimates population average exposure for domestic wood combustion generated PM2.5 emiddions through indoor. Thus, if only 14% of people are exposed to PM2.5in recreational building, then population average exposure is 14% of total exposure.
Definition: sum(Average_concentratio*Pop_frac_indoor_pm,energy_class, const_year)
NodeLocation: 312,376,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
WindState: 2,129,81,476,224
ValueState: 2,451,126,416,303,0,MIDM
ReformVal: [Energy_class,Const_year]

Variable Domwood_pm_emis
Title: Dom wood comb PM2.5 emission
Definition: ({Pm_emf}*((sum(Bs_devel*Q_heat_purchase, Building_type))*3.6))[Heat_sys_prim='Wood', Pm_source='DOM']
NodeLocation: 552,256,1
NodeSize: 48,24
WindState: 2,310,661,476,224
DisplayInputs: Index Pm_source, Index Building_type, Objective Bs_devel, Index Heat_sys_prim, Variable Q_heat_purchase

Close Personal_exposure_pm

Module Personal_exposure_to
Title: Personal exposure to PM2.5
Author: vkoe
Date: 10. Febta 2011 12:43
DefaultSize: 48,24
NodeLocation: 392,216,1
NodeSize: 48,29
DiagState: 2,138,258,715,459,17
NodeColor: 52427,63897,65535

Index Microenv
{!40000|Att_PrevIndexValue: ['Outdoor','Home','Work','Other indoor','Traffic']}
Title: Microenv
Definition: ['Outdoor','Home','Work','Other indoor','Traffic']
NodeLocation: 488,80,1
NodeSize: 48,12
WindState: 2,98,90,476,227

Variable Time_use
Title: Pop average time use
Definition: Table(Microenv)(~
2/24,12/24,8/24,1/24,1/24)
NodeLocation: 488,48,-3
NodeSize: 48,24
WindState: 2,98,90,476,224
DefnState: 2,734,677,357,204,0,MIDM

Variable Pm_home
Title: PM2.5 home
Description: Outdoor air infiltration + average from indoor air sources
Definition: var a:=Pm_outdoor*Pm_infiltration;~
~
if Heat_sys_prim = 'Wood' then a+Average_concentratio else a
NodeLocation: 328,160,1
NodeSize: 48,24
WindState: 2,907,709,489,224
ValueState: 2,216,582,637,303,0,MIDM
ReformVal: [Energy_class,Const_year]
{!40000|Att_ResultSliceState: [Heat_system,3,Fu_period,1,Const_year,1,Energy_class,1]}

Variable Pm_outdoor
Title: Pop average PM2.5 outdoor exp
Units: ug/m3
Description: Pop average exposure from all outdoor sources~
~
Traffic~
Domestic wood combustion~
Power plants~
Industry~
Agriculture~
Long range transport~
Other
Definition: 10
NodeLocation: 328,56,1
NodeSize: 48,29

Variable Pm_work
Title: PM2.5 Work
Definition: Pm_outdoor*Pm_infiltration
NodeLocation: 328,216,1
NodeSize: 48,24

Variable Traffic_pm_ef
Title: Traffic enrich factor
Definition: 2.5
NodeLocation: 328,272,1
NodeSize: 48,24

Variable Building_pm_penet
Title: Building PM2.5 penetration
Description: Building penetration factor for PM2.5~
~
LAMA: normal(1, 0.06)
Definition: 1
NodeLocation: 96,160,1
NodeSize: 48,24

Variable Pm_infiltration
Title: PM2.5 infiltration
Definition: (Building_pm_penet*Aeration_rate)/(Aeration_rate+Pm_decay_rate)
NodeLocation: 208,160,1
NodeSize: 48,24

Index Pm_outdoor_source
Title: PM outdoor source
Definition: ['Traffic','Domestic combustion','Power plants','Industry','Long range tran']
NodeLocation: 328,96,1
NodeSize: 48,16
WindState: 2,1075,100,476,224

Variable Pm2_5_concentration
Title: PM2.5 conc microenv
Units: ug/m3
Definition: Table(Microenv)(~
Pm_outdoor,Pm_home,Pm_work,Pm_work,Pm_outdoor*Traffic_pm_ef)
NodeLocation: 488,152,1
NodeSize: 48,24
DefnState: 2,1154,634,416,303,0,MIDM
ValueState: 2,654,463,505,361,0,MIDM
ReformVal: [Const_year]
{!40000|Att_ResultSliceState: [Energy_class,1,Heat_system,1,Microenv,2,Const_year,1,Fu_period,1]}

Variable Pers_pm
Title: Personal PM2.5 exposure
Definition: sum(Pm2_5_concentration*Time_use, microenv)
NodeLocation: 488,216,1
NodeSize: 48,24
ValueState: 2,925,650,627,303,0,MIDM
ReformVal: [Const_year]
{!40000|Att_ResultSliceState: [Energy_class,3,Heat_system,3,Const_year,1,Fu_period,1]}

Variable Building_type_pop_fr
Title: Building type pop Frac
Definition: var a:=Bs_devel;~
a/sum(a,const_year,energy_class,Heat_sys_prim,building_type)
NodeLocation: 608,272,1
NodeSize: 48,24
ValueState: 2,157,656,652,303,0,MIDM
ReformVal: [Building_type]

Variable Pop_aver_personal_pm
Title: Pop aver pers PM2.5 exposure
Definition: sum(Pers_pm*Building_type_pop_fr, Const_year, building_type, Heat_sys_prim,energy_class)
NodeLocation: 488,272,1
NodeSize: 48,24
ValueState: 2,273,287,416,303,0,MIDM

Close Personal_exposure_to

Variable Q_heat_purchase
Title: Unit energy purchase
Units: kWh/m2/a
Description: Heat purchased for a building
Definition: var a:=sum(Q_space_heating+Q_water_heating,month);~
~
a:=if Heat_sys_prim = 'Electricity' then a[heat_dist='Electric radiator'] else a[heat_dist='Water radiator'];~
~
a/Hs_efficiency~

NodeLocation: 296,408,1
NodeSize: 48,24
WindState: 2,120,235,476,260
ValueState: 2,369,248,516,488,0,MIDM
NodeColor: 65535,19661,50247
ReformVal: [Building_type,Const_year]
DisplayOutputs: Variable Domwood_pm_emis
{!40000|Att_ResultSliceState: [Energy_class,3,Fu_period,1,Heat_sys_prim,1,Heat_source,1,Const_year,7,Building_type,1]}

Close Claih1

Module Total_heat_consumpti
Title: Heat purchase
Author: vkoe
Date: 25. Octta 2011 11:15
DefaultSize: 48,24
NodeLocation: 128,96,1
NodeSize: 52,28
DiagState: 2,25,408,493,462,17
NodeColor: 52427,65535,65535

Module Building_heat_consum
Title: Building ~
unit heat consumption
Author: vkoe
Date: 1. Febta 2011 9:55
DefaultSize: 48,24
NodeLocation: 568,72,1
NodeSize: 52,28
NodeInfo: 1,0,1,1,1,1,0,,0,
DiagState: 2,22,120,1089,664,17
NodeColor: 52427,63897,65535

Variable Q_space_heating
Title: Unit SH energy consumption
Units: kWh/m2/month
Description: Tästä pitää vielä vähentää poistoilmalämpöpumpun varaajan siirtämä ja tilojen lämmityksessä hyödynnetty energia (Q_lp_tilat)
Definition: (Q_conduction+Q_air_leak+Q_air_exchange-Q_internal_heat+Q_sh_system)/(Ground_floor_area*No_of_floors)
NodeLocation: 464,496,1
NodeSize: 48,29
WindState: 2,174,165,491,260
ValueState: 2,158,167,610,411,0,MIDM
NodeColor: 65535,19661,50247
ReformVal: [Fu_period,Month]
Att__TotalsIndex: Index Month
{!40000|Att_ResultSliceState: [Heat_dist,1,Const_year,7,Month,0,Fu_period,1]}

Variable Q_water_heating
Title: Unit WH energy consumption
Units: kWh/m2/month
Description: a: lämpimän veden kulutus vuodessa per rakennus~
b: veden lämmitykseen kuluva netto energia~
~
Tästä pitää vielä vähentää poistoilmalämpöpumpun varaajan siirtämä ja veden lämmityksessä hyödynnetty energia
Definition: var a:= Hot_water_use/1000;~
var b:=1000*4.2*a*50/3600;~
~
(b+Q_wh_system)/(Ground_floor_area*No_of_floors)
NodeLocation: 464,560,1
NodeSize: 48,29
WindState: 2,168,260,476,265
ValueState: 2,151,182,708,381,0,MIDM
NodeColor: 65535,19661,50247
ReformVal: [Const_year,Month]
Att__TotalsIndex: Index Month

Variable Q_conduction
Title: Conduction heat loss
Units: kWh/month
Description: Rakenteiden läpi johtuva lämpöenergia~
~
a: Rakennusosien yhteenlaskettu ominaislämpöhäviö (H_joht, W/K)
Definition: var a:=(A_outside_wall*U_outside_wall)+(A_roof*U_roof)+(Ground_floor_area*U_floor)+(A_window*U_window)+(A_outer_door*U_outer_door);~
~
a:=a*(Ts-Tu)*Time_period/1000;~
a
NodeLocation: 352,384,1
NodeSize: 48,24
WindState: 2,71,69,510,307
ValueState: 2,124,182,737,418,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Const_year,Month]
Att__TotalsIndex: Index Month
{!40000|Att_ResultSliceState: [Fu_period,1,Month,1,Const_year,2]}

Variable Q_air_leak
Title: Air leak heat loss
Units: kWh/month
Description: a: air leak, vuotoilmavirta (m3/s), lasketaan:~
~
rakennuksen vuotoilmakerroin (1/h) * rakennuksen ilmatilavuus (m3) / 3600 (laatumuunnos m3/h > m3/s)~
~
b: air leak unit heat loss (W/K), lasketaan:~
~
(ilman tiheys (kg/m3) * ilman ominaislämpökapasiteetti (Ws/(kgK) * vuotoilmavirta (m3/s)
Definition: var a:= Air_leak_factor*(Ground_floor_area*Building_height)/3600; ~
var b:= 1.2*1000*a;~
~
b:=b*(Ts-Tu)*Time_period/1000;~
b
NodeLocation: 576,384,1
NodeSize: 48,24
WindState: 2,53,96,476,355
ValueState: 2,209,178,529,381,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Fu_period,Month]
Att__TotalsIndex: Index Month
{!40000|Att_ResultSliceState: [Const_year,5,Month,1,Fu_period,1]}

Variable Q_air_exchange
Title: Air exchange heat loss
Units: kWh/month
Description: ~
~
a: rakennuksen poistoilmavirta (m3/s), lasketaan:~
~
ominaispoistoilmavirran mukaan, tai vaihtoehtoisesti poistoilmakertoimeen perustuen:~
~
poistoilmakerroin (1/h) * rakennuksen ilmatilavuus (m3) / 3600 (laatumuunnos m3/h > m3/s)~
~
Keskimääränen poistoilmavirta lasketaan ilmanvaihtolaitteiston tehon ja käyntiajan pohjalta.~
~
b: ilmanvaihdon ominaislämpöhäviö (W/K)~
~
Building_input_data[Building_input='Floor area']
Definition: var a:=(Air_exchange*(Ground_floor_area*No_of_floors))/1000;~
~
var b:= 1.2*1000*a*(1-Eta_a);~
~
b:=(b*(Ts-Tu)*Time_period)/1000;~
~
b
NodeLocation: 464,384,1
NodeSize: 48,24
WindState: 2,595,89,476,506
ValueState: 2,124,341,674,382,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Const_year,Month]
Att__TotalsIndex: Index Month
{!40000|Att_ResultSliceState: [Const_year,7,Month,1,Fu_period,1]}

Chance Ts
Title: Indoor air temp
Units: Celsius
Description: Indoor air temperature~
~

Definition: Triangular(20, 21, 23)
NodeLocation: 352,320,1
NodeSize: 48,24
NodeColor: 1,65535,32766

Variable Tu
Title: Outdoor air temp
Units: Celsius
Description: Rakennusalan sijainnilla painotettu keskimääräinen kuukausittainen ulkolämpötila Suomessa. Perustuu keskimääräisiin mitattuihin lämpötiloihin eri alueilla 1971-2000 sekä ilmaston lämpenemisarvioon kaudelle 2010-2039. Lämpenemisarviot ovat vuodenaikakohtaisia, mutta keskimääräisiä koko Suomelle.~

Definition: var a:=Oa_temp_change/55;~
var b:=Fu_period-Start_year+25+2.5;~
a:=Oa_temp_loc+(a*b);~
sum(a*Building_loc, loc)
NodeLocation: 352,184,1
NodeSize: 48,24
WindState: 2,98,90,476,424
DefnState: 2,117,159,656,303,0,MIDM
ValueState: 2,165,510,817,374,0,MIDM
NodeColor: 19661,48336,65535
ReformDef: [Fu_period,Month]
ReformVal: [Fu_period,Month]
{!40000|Att_ResultSliceState: [Const_year,8,Month,1,Fu_period,1]}

Variable Time_period
Title: Time period
Units: h
Definition: Table(Month)(~
31*24,28*24,31*24,30*24,31*24,30*24,31*24,31*24,30*24,31*24,30*24,31*24)
NodeLocation: 352,240,1
NodeSize: 48,24

Chance A_outside_wall
Title: Outside wall area
Units: m2
Description: Assumptions: ~
~
Detached house width/lenght ratio = 1/1.5~
Row house width/lenght ratio = 1/6~
Appartment building width/lenght ratio = 1/3~
~
Table(Building_type)(~
(sqrt(Ground_floor_area/1.5)*5*Building_height)-A_window-A_outer_door,sqrt(Ground_floor_area/6)*14*Building_height-A_window-A_outer_door,sqrt(Ground_floor_area/3)*8*Building_height-A_window-A_outer_door)~
~

Definition: (sqrt(Ground_floor_area/1.5)*5*Building_height)-A_window-A_outer_door
NodeLocation: 240,320,1
NodeSize: 48,24
WindState: 2,181,184,616,496
DefnState: 2,375,713,416,303,0,MIDM
ValueState: 2,210,60,416,303,0,SAMP
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Const_year,Undefined,Undefined,Undefined,2]

Chance U_outside_wall
Title: Outside wall heat cond
Units: W/(m2K)
Definition: var a:=Building_input_data[Building_input='U wall'];~
Triangular(a*0.8, a, a*1.2)
NodeLocation: 128,320,1
NodeSize: 48,24
DefnState: 2,168,178,737,303,0,MIDM
ValueState: 2,300,118,416,303,0,MIDM
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Const_year,2]

Chance A_roof
Title: Roof area
Units: m2
Definition: Ground_floor_area
NodeLocation: 240,264,1
NodeSize: 48,24
ValueState: 2,495,39,581,303,0,SAMP
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Const_year,Undefined,Undefined,Undefined,2]

Chance U_roof
Title: Roof heat cond
Units: W/(m2K)
Definition: var a:=Building_input_data[Building_input='U roof'];~
Triangular(a*0.8, a, a*1.2)
NodeLocation: 128,264,1
NodeSize: 48,24
DefnState: 2,136,146,906,303,0,MIDM
ValueState: 2,322,214,416,303,0,MIDM
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Const_year,2]

Chance U_floor
Title: Floor heat cond
Units: W/(m2K)
Definition: var a:=Building_input_data[Building_input='U floor'];~
Triangular(a*0.8, a, a*1.2)
NodeLocation: 128,384,1
NodeSize: 48,24
DefnState: 2,200,210,947,303,0,MIDM
ValueState: 2,147,351,640,411,0,CONF
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Const_year,2]

Chance A_window
Title: Window area
Units: m2
Description: Assumption: Window area is 15% from the floor area.~
~

Definition: var a:=Building_input_data[Building_input='Window area'];~
a:=Triangular(a*0.9, a, a*1.1);~
a*Ground_floor_area*No_of_floors
NodeLocation: 240,200,1
NodeSize: 48,24
DefnState: 2,558,475,416,303,0,MIDM
ValueState: 2,212,226,480,303,0,CONF
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Undefined,2]

Chance U_window
Title: Window heat cond
Units: W/(m2K)
Definition: var a:=Building_input_data[Building_input='U window'];~
Triangular(a*0.8, a, a*1.2)
NodeLocation: 128,200,1
NodeSize: 48,24
DefnState: 2,162,84,624,303,0,MIDM
ValueState: 2,202,336,569,303,0,CONF
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Const_year,2]

Chance A_outer_door
Title: Outer door area
Units: m2
Description: Assumptions: ~
*average door: width 85 cm, height 2 m~
*Detached houses: 2 doors~
*Row houses: 2 doors per apartment, 4 apartments per house~
*Apartment building: 3 doors (double front door and single back door)~
~
Table(Building_type)(~
0.85*2*2,0.85*2*4,0.85*2*3)~

Definition: var a:=Building_input_data[Building_input='Door area'];~
Triangular(a*0.9, a, a*1.1)
NodeLocation: 240,144,1
NodeSize: 48,24
WindState: 2,98,90,476,328
DefnState: 2,465,133,416,303,0,MIDM
NodeColor: 65535,52427,61166

Chance U_outer_door
Title: Outer door heat cond
Units: W/(m2K)
Definition: var a:=Building_input_data[Building_input='U door'];~
Triangular(a*0.8, a, a*1.2)
NodeLocation: 128,144,1
NodeSize: 48,24
WindState: 2,231,334,476,224
DefnState: 2,72,82,592,303,0,MIDM
ValueState: 2,169,287,526,303,0,MIDM
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Const_year,2]

Chance Building_height
Title: Building height
Description: One floor height is 3 m. Apartment buildings have in average 4 floors~
~

Definition: var a:=Building_input_data[Building_input='Floor height'];~
a:= Triangular(a,a*1.1,a*1.2);~
a*No_of_floors
NodeLocation: 128,448,1
NodeSize: 48,24
WindState: 2,184,302,476,379
ValueState: 2,236,48,291,524,0,SAMP
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Undefined,2,Undefined,Undefined,2]

Chance Ground_floor_area
Title: Ground floor area
Units: m2
Definition: var a:=Building_input_data[Building_input='Floor area'];~
a:=Triangular(a*0.75, a, a*1.25);~
a/No_of_floors
NodeLocation: 240,384,1
NodeSize: 48,24
WindState: 2,206,159,476,340
DefnState: 2,265,188,416,303,0,MIDM
ValueState: 2,474,4,612,521,0,SAMP
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Undefined,2,Undefined,Undefined,2]

Index Month
{!40000|Att_PrevIndexValue: [1,2,3,4,5,6,7,8,9,10,11,12]}
Title: Month
Definition: [1,2,3,4,5,6,7,8,9,10,11,12]
NodeLocation: 352,272,1
NodeSize: 48,12

Chance No_of_floors
Title: No. of floors
Description: if Floor_area < 150 then 1 else (1*Bernoulli_floors +2*(1-Bernoulli_floors))~
~

Definition: var a:=Building_input_data[Building_input='Floors'];~
a:=Bernoulli(a);~
1*a+2*(1-a)
NodeLocation: 240,448,1
NodeSize: 48,24
WindState: 2,105,179,476,305
DefnState: 2,272,326,416,303,0,MIDM
ValueState: 2,297,125,416,303,0,SAMP
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Const_year,Undefined,Undefined,Undefined,2]

Chance Air_leak_factor
Title: Air leak factor
Units: 1/h
Description: vuotoilmavirta~
~
rakennuksen vuotoilmakerroin voidaan laskea ilmanvaihtoluvun n50 perusteella:~
~
vuotoilmakerroin (1/h) = n50 / 25~
~
var a:=Building_input_data[Building_input='Heat recovery efficiency'];~
a:=Triangular(a*0.9, a, a*1.1);
Definition: var a:=Building_input_data[Building_input='Air leak factor'];~
Triangular(a*0.9, a, a*1.1)
NodeLocation: 576,320,1
NodeSize: 48,24
WindState: 2,526,51,476,435
DefnState: 2,282,519,549,303,0,MIDM
ValueState: 2,650,204,520,303,0,SAMP
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Energy_class,Const_year]

Chance Air_exchange
Title: Air exchange
Units: dm3/s/m2
Description: Ominaispoistoilmavirta~
~
tavallisesti asuinrakennuksissa 0.35-0.5 dm3/s/m2~
~
Rakennusmääräyskokoelman osan D2 suosituksen mukaan poistoilmakertoimen tulisi olla 0.5/h, jota vastaa arvo 0.35 m2/s~
~

Definition: var a:=Building_input_data[Building_input='Air exchange rate'];~
Triangular(a*0.9, a, a*1.1)~

NodeLocation: 464,320,1
NodeSize: 48,24
WindState: 2,73,107,476,350
ValueState: 2,165,204,673,303,0,CONF
NodeColor: 65535,52427,61166
ReformVal: [Const_year,Undefined,2]

Chance Eta_a
Title: Heat recovery air exchange
Units: -
Description: Ilmanvaihdon poistoilman lämmöntalteenoton (LTO) vuosihyötysuhde.~
~
Jos lämmöntalteenottoa ei ole, eta_a = 0.~
~
Vuosihyötysuhde voidaan laskea kaavalla eta_a = 0.6 * eta_t~
jossa eta_t = ilmanvaihdon lämmöntalteenoton tuloilman lämpötilasuhde, kun tulo- ja poistoilmavirta ovat yhtä suuret.
Definition: var a:=Building_input_data[Building_input='Heat recovery efficiency'];~
a:=Triangular(a*0.9, a, a*1.1);~
var b:=Building_input_data[Building_input='Heat recovery probability'];~
b:=Bernoulli(b);~
a*b+(1-b)*0~

NodeLocation: 464,264,1
NodeSize: 48,24
WindState: 2,98,90,476,324
DefnState: 2,218,142,625,303,0,MIDM
ValueState: 2,129,158,636,389,0,SAMP
NodeColor: 1,65535,32766
ReformDef: [Energy_class,Const_year]
ReformVal: [Const_year,Const_year,Undefined,Undefined,Undefined,2]

Variable Sh_unit_rel_wr
Title: Space heat unit release wr
Units: kWh/brm2/kk
Description: vesiradiaattorien kuukausittaiset lämmitysjärjestelmähaviöt lämmityskaudella~
~
a: kehityshäviöt~
b: jakeluhäviöt~
c: luovutushäviöt~
d: säätöhaviöt~
e: varaajahäviöt
Definition: var a:= 2*Ground_floor_area*No_of_floors;~
var k:= 2000/(Ground_floor_area*No_of_floors);~
a:= if a<2000 then k else 2;~
var b:=10;~
var c:= 4;~
var d:=2;~
var e:= 10;~
(a+b+c+d+e)/sum(heating_season,month)
NodeLocation: 688,208,1
NodeSize: 48,24
WindState: 2,227,560,476,384
NodeColor: 65535,52427,61166

Variable Sh_unit_rel_er
Title: Space heat unit release er
Units: kWh/brm2/month
Description: Sähkölämmityspattereiden ominaislämpöhäviö~
~
a: kehityshäviöt~
b: jakeluhäviöt~
c: luovutushäviöt~
d: säätöhäviöt~
e: varaajahäviöt
Definition: var a:= 0;~
var b:= 0;~
var c:= 4;~
var d:= 4;~
var e:= 0;~
~
(a+b+c+d+e)/sum(heating_season,month)
NodeLocation: 688,264,1
NodeSize: 48,24
WindState: 2,386,119,570,373
NodeColor: 65535,52427,61166

Variable Heating_season
Title: Heating season
Description: Lämmityskausi alkaa kun T ~ 12-15 C
Definition: Table(Month)(~
1,1,1,1,1,0,0,0,1,1,1,1)
NodeLocation: 688,320,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Q_sh_system
Title: SH system heat loss
Units: kWh/month
Description: Lämmitysjärjestelmän lämpöhaviöenergia. Kehityshäviöt, jakeluhäviöt, luovutushäviöt, säätöhaviöt, varaajahäviöt. Häviöita ainoastaan lämmityskaudella.
Definition: var a:= if Heat_dist = 'Water radiator' then Sh_unit_rel_wr else Sh_unit_rel_er;~
~
a:=a*Ground_floor_area*No_of_floors*heating_season;~
~
a
NodeLocation: 688,384,1
NodeSize: 48,24
WindState: 2,439,144,531,349
ValueState: 2,418,141,603,379,0,MIDM
NodeColor: 19661,48336,65535
ReformVal: [Const_year,Month]
{!40000|Att_ResultSliceState: [Heat_dist,2,Month,1,Building_type,1]}

Variable Q_wh_system
Title: WH system heat loss
Units: kWh/month
Description: Käyttäveden lämmitysjärjestelmän lämpöhaviöenergia~
~
muodostuu kehitys-, kierto- ja varaajahäviöistä. Kehityshäviöt, sisältyvät yleensä tilojen lämmityksen kehityshäviöihin, joten ei tarvitse sisällyttää tähän.~
~
kiertohäviöt: ominaishäviön oletusarvona 15 kWh/brm2/a~
varaajahäviöt ominaishäviön oletusarvona 3/kWh/brm2/a (aliarvioi pienetn varaajien ja yliarvioi suurten varaajien häviöitä, vaihteluväli n. 1-5 kWh/brm2/a)
Definition: var a:=(15+3)*Ground_floor_area*No_of_floors;~
a/12
NodeLocation: 240,560,1
NodeSize: 48,24
WindState: 2,380,87,476,333
ValueState: 2,1228,127,416,303,0,MIDM

Chance Hot_water_use
Title: Hot water use
Units: dm3/a/building
Description: Rakennusmääräyskokoelman oletusarvo: lämpimän veden ominaiskulutus asuinrakennuksessa = 600 dm3/brm2/a~
~
Motiva: Lämpimän veden käyttö on keskimäärin 40-50 l/vrk/hlö~
~
Oletus: Pientalossa asuu Suomessa keskimäärin 2.4 hlöä (Tilastokeskus)
Definition: Triangular(40, 45, 50)*(Time_period/24)*Triangular(2,2.4,5)
NodeLocation: 128,560,1
NodeSize: 48,24
WindState: 2,98,90,476,306
ValueState: 2,240,287,416,303,0,MIDM
NodeColor: 1,65535,32766

Module Internal_heat
Title: Internal heat
Author: vkoe
Date: 4. Febta 2011 9:49
DefaultSize: 48,24
NodeLocation: 592,496,1
NodeSize: 48,24
NodeInfo: 1,0,1,1,1,1,0,,0,
DiagState: 2,461,28,758,375,17

Variable Q_internal_heat
Title: Internal heat
Units: kWh/month
Definition: (Q_electricity_heat_r+Q_persons+Q_sun+Q_sh_release+Q_wh_release)*Eta_internal_heat
NodeLocation: 408,248,1
NodeSize: 48,24
WindState: 2,98,90,602,224
ValueState: 2,82,74,1033,405,0,SAMP
NodeColor: 65535,19661,50247
ReformVal: [Const_year,Month]
Att__TotalsIndex: Index Month
{!40000|Att_ResultSliceState: [Fu_period,1,Heat_dist,2,Month,1,Const_year,1]}

Variable Q_persons
Title: Person heat release
Units: kWh/month
Description: Voidaan myös laskea tarkemmin henkilöiden määrän ja oleskeluajan perusteella~
~
Q_persons = yhden henkilön keskimäärin luovuttama lämpöteho (70 W) * henkilöiden määrä * oleskeluaika (h) / 1000~
~
Jos rakennus on käytössä koko ajan, oleskeluaika = laskentajakson pituus tunneissa * 0.6
Definition: Q_pers_unit_rel*Ground_floor_area*No_of_floors/12
NodeLocation: 304,176,1
NodeSize: 48,24
WindState: 2,98,90,476,291
ValueState: 2,161,390,416,303,0,MIDM

Variable Q_sh_release
Title: SH heat release
Units: kWh/month
Definition: Q_sh_system*0.7~

NodeLocation: 520,176,1
NodeSize: 48,24
WindState: 2,98,90,476,224
ValueState: 2,414,271,820,453,0,MIDM
ReformVal: [Const_year,Month]
{!40000|Att_ResultSliceState: [Heat_sys_prim,4,Month,1,Building_type,1]}

Variable Q_wh_release
Title: WH heat release
Units: kWh/month
Definition: var a:= 600*Ground_floor_area*No_of_floors/1000;~
var b:=1000*4.2*a*50/3600;~
~
(b*0.3+Q_wh_system*0.5)/12
NodeLocation: 624,176,1
NodeSize: 48,24

Variable Q_electricity_heat_r
Title: Electricity heat release
Units: kWh/month
Definition: Electricity_heat_uni*Ground_floor_area*No_of_floors/12
NodeLocation: 408,176,1
NodeSize: 48,24
ReformVal: [Building_type,Const_year]

Variable Q_sun
Title: Sun heat absorption
Units: kWh/month
Definition: G_sun_horizontal*F_direction*F_permeability*A_window*g
NodeLocation: 200,176,1
NodeSize: 48,24
ValueState: 2,487,235,416,303,0,MIDM
ReformVal: [Const_year,Month]
DisplayInputs: Variable G_sun_vertical

Variable Eta_internal_heat
Title: Internal heat use efficiency
Units: -
Description: How much of the internal heat can be exploited on a monthly basis~
~
a: rakennuksen sisäinen lämpökuorma (kWh)~
b: rakennuksen lämpöhäviö (kWh)~
c: rakennuksen ominaislämpöhäviö (W/K)~
d: rakennuksen aikavakio (h)~
e: numeerinen parametri, joka riippuu aikavakiosta
Definition: var a:= Q_sh_release+Q_wh_release+Q_persons+Q_electricity_heat_r+Q_sun;~
var b:= (Q_conduction+Q_air_leak+Q_air_exchange);~
var c:=(b/((Ts-Tu)*Time_period))*1000;~
var d:=C_rak_unit/c;~
var e:=1+(d/15);~
~
(1-(a/b)^e)/(1-(a/b)^(e+1))~

NodeLocation: 200,248,1
NodeSize: 48,24
WindState: 2,335,120,727,448
ValueState: 2,486,311,469,375,0,MIDM
ReformVal: [Fu_period,Month]
{!40000|Att_ResultSliceState: [Fu_period,1,Energy_class,1,Heat_sys_prim,2,Const_year,7,Month,1,Building_type,1]}

Variable C_rak_unit
Title: C_rak_unit
Units: Wh/(brm2 K)
Description: Rakennuksen sisäpuolinen tehollinen lämpökapasiteetti, riippuu rakennusmateriaalista~
~
Table(Building_type)(~
150, 150, 190 )~

Definition: 150
NodeLocation: 96,248,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Q_pers_unit_rel
Title: Q persons unit release
Units: kWh/brm2/a
Description: Table(Building_type)(~
8,11,17)
Definition: 8
NodeLocation: 304,112,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable Electricity_heat_uni
Title: Electricity heat unit release
Units: kWh/brm2
Definition: 32
NodeLocation: 408,112,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable G_sun_horizontal
Title: Sun radiation horizontal
Units: kWh/m2
Description: Oletusarvot: Jyväskylän seutu
Definition: Table(Month)(~
5.7,23.3,47.3,93.40000000000001,147.1,171.4,138.4,116.4,61.4,26.6,5.5,2.8)
NodeLocation: 200,56,1
NodeSize: 48,24
DefnState: 2,659,339,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable G_sun_vertical
Title: Sun radiation vertical
Units: kWh/m2
Description: Oletusarvot: Jyväskylän seutu, ikkunat lounaaseen
Definition: Table(Month)(~
7.6,41.8,58.5,92.3,101.1,107.7,84.8,93.09999999999999,58.8,34.6,6.2,2.8)
NodeLocation: 200,112,1
NodeSize: 48,24
DefnState: 2,731,315,416,303,0,MIDM
NodeColor: 65535,52427,61166
DisplayOutputs: Variable Q_sun

Variable F_direction
Title: Direction conversion factor
Units: -
Description: Muuntokerroin, jolla vaakatasolle tuleva auringon kokonaissäteilyenergia muunnetaan ilmansuunnittain pystypinnalle tulevaksi kokonaissäteilyenergiaksi~
~
oletusarvot: Jyväskylän seutu, ikkunat lounaaseen
Definition: Table(Month)(~
1.333,1.794,1.237,0.987,0.6870000000000001,0.628,0.613,0.8,0.958,1.301,1.127,1)
NodeLocation: 96,112,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable G
Title: Window permeability factor
Units: -
Description: ikkunan valoaukon auringon kokonaissäteilyn läpäisykerroin~
~
Voidaan laskea: g = 0.9 * ikkunan valoaukon kohtisuoran auringonsäteilyn kokonaisläpäisykerron~
~
käytetty oletusarvo: yksipuitteinen, kolmilasinen ikkuna
Definition: 0.9*0.7
NodeLocation: 96,56,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Variable F_permeability
Title: Radiation permeability factor
Units: -
Description: Auringon säteilyn läpäisyn kokonaiskorjauskerroin~
~
Voidaan laskea: F_läpäisy = F_kehä * F_verho * F_ varjostus~
~
Jos varjostuksia ja pysyviä verhoja ei ole, F_läpäisy oletusarvona voidaan käyttää 0.75~
~
F_kehä = ikkunan valoaukko (m2) / ikkunan koko kehysrakenteineen (m2). Voidaan käyttää oletusarvoa 0.75~
~
F_verho: tyypilliset arvot eri verho/sälekaihdin tyypeille vaihtelevat välillä 0.3-0.8. Oletusarvonana 0.5, joka vastaa vaaleita tekstiiliverhoja sisäpuolella. Valkoiset sälekaihtimet ikkunan välissä = 0.3.~
~
F_varjostus lasketaan ikkunan horisontaalisten, yläpuolisten vaakasuorien rakenteiden ja sivuilla olevien pystysuorien rakenteiden varjostuksen tulona. Oletusarvona on, että näitä varjostuksia ei ole.
Definition: 0.75*0.5
NodeLocation: 96,176,1
NodeSize: 48,24
WindState: 2,98,90,476,295
NodeColor: 65535,52427,61166

Close Internal_heat

Index Heat_loss
{!40000|Att_PrevIndexValue: ['Conduction','Air exchange','Air leak','SH system','Water heating','WH system']}
Title: Heat loss source
Definition: ['Conduction','Air exchange','Air leak','SH system','Water heating','WH system']
NodeLocation: 920,424,1
NodeSize: 48,16

Variable Heat_loss_fraction
Title: Heat loss
Definition: Table(Heat_loss)(~
sum(Q_conduction,month),sum(Q_air_exchange,month),sum(Q_air_leak,month),sum(Q_sh_system,month),sum(Q_water_heating,month)*Ground_floor_area*No_of_floors-Q_wh_system*12,Q_wh_system*12)
NodeLocation: 920,384,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
DefnState: 2,120,187,575,303,0,MIDM
ValueState: 2,169,62,669,362,0,MIDM
ReformVal: [Heat_loss,Const_year]
{!40000|Att_ResultSliceState: [Fu_period,1,Heat_dist,2,Const_year,1,Heat_loss,1]}

Variable Heat_loss_fraction1
Title: Heat loss fraction
Definition: var a:=Heat_loss_fraction;~
a/sum(a,heat_loss)
NodeLocation: 1024,384,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
ValueState: 2,87,68,680,567,1,MIDM
ReformVal: [Heat_loss,Const_year]
{!40000|Att_ResultSliceState: [Fu_period,3,Heat_dist,2,Const_year,1,Heat_loss,1]}

Variable Internal_heat_source
Title: Internal heat source
Definition: Table(Internal_heat1)(~
sum(Q_sun,month),sum(Q_persons,month),sum(Q_electricity_heat_r,month),sum(Q_sh_release,month),sum(Q_wh_release,month))
NodeLocation: 920,496,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
DefnState: 2,198,406,416,303,0,MIDM
ValueState: 2,236,330,416,303,0,MIDM
ReformVal: [Internal_heat1,Heat_sys_prim]
{!40000|Att_ResultSliceState: [Building_type,1,Heat_sys_prim,1,Internal_heat1,1]}

Index Internal_heat1
{!40000|Att_PrevIndexValue: ['Sun','Person','Electricity','SH release','WH release']}
Title: Internal heat
Definition: ['Sun','Person','Electricity','SH release','WH release']
NodeLocation: 920,528,1
NodeSize: 48,12
WindState: 2,109,378,476,224

Variable Internal_heat_fracti
Title: Internal heat fraction
Definition: var a:=Internal_heat_source;~
a/sum(a,internal_heat1)
NodeLocation: 1024,496,1
NodeSize: 48,24
NodeInfo: 1,1,1,1,1,1,0,,0,
ValueState: 2,116,138,761,303,1,MIDM
ReformVal: [Internal_heat1,Const_year]
{!40000|Att_ResultSliceState: [Heat_dist,2,Building_type,1,Internal_heat1,1]}

Index Heat_dist
Title: Heat distribution
Definition: ['Water radiator','Electric radiator']
NodeLocation: 688,424,1
NodeSize: 48,16
WindState: 2,96,113,476,224

Index Building_input
{!40000|Att_PrevIndexValue: ['Floor height','Floors','Floor area','Window area','Door area','U wall','U roof','U floor','U window','U door','Air exchange rate','Heat recovery probability','Heat recovery efficiency','Air leak factor']}
Title: Building input
Definition: ['Floor height','Floors','Floor area','Window area','Door area','U wall','U roof','U floor','U window','U door','Air exchange rate','Heat recovery probability','Heat recovery efficiency','Air leak factor']
NodeLocation: 128,72,1
NodeSize: 48,12
WindState: 2,1191,59,548,384

Variable Building_input_data
Title: Building input data
Definition: Table(Const_year,Building_input)(~
2.5,0.7,109,0.15,0.85*2*2,0.48,0.3,0.3,2.1,1.4,0.4,0,0.3,0.48,~
2.5,0.7,124,0.15,0.85*2*2,0.4,0.28,0.3,2.1,1.4,0.4,0,0.3,0.4,~
2.5,0.7,144,0.15,0.85*2*2,0.3,0.25,0.3,1.6,1.4,0.4,0,0.3,0.28,~
2.5,0.7,158,0.15,0.85*2*2,0.28,0.25,0.3,1.4,1.4,0.4,0,0.3,0.24,~
2.5,0.7,166,0.15,0.85*2*2,0.28,0.16,0.3,1.4,1.4,0.4,0,0.3,0.24,~
2.5,0.7,176,0.15,0.85*2*2,0.25,0.16,0.25,1.4,1.4,0.4,0.7,0.3,0.16,~
2.5,0.7,176,0.15,0.85*2*2,0.17,0.09,0.16,1,1,0.4,1,0.45,0.08,~
2.5,0.7,176,0.15,0.85*2*2,0.17,0.09,0.16,1,1,0.4,1,0.45,0.08,~
2.5,0.7,176,0.15,0.85*2*2,0.17,0.09,0.16,1,1,0.4,1,0.45,0.08~
)
NodeLocation: 128,40,1
NodeSize: 48,24
WindState: 2,125,144,476,224
DefnState: 2,93,221,870,369,0,MIDM
ValueState: 2,165,190,882,464,0,MIDM
NodeColor: 1,65535,32766
ReformDef: [Building_input,Const_year]
ReformVal: [Const_year,Building_input]

Variable Oa_temp_loc
Title: Outdoor temp, location
Description: Alueet perustuvat Tilastokeskuksen nykyiseen suuraluejakoon.~
~
Suuralueiden keskimääräiset lämpötilat on laskettu IL:n kuukausitilastoista. Lämpötila tietyllä alueella on keskiarvo seuraavien havaintoasemien tiedoista:~
~
*Etelä-Suomi: Kaarina, Helsinki-Vantaan lentokenttä, Lahti, Lappeenranta~
*Länsi-Suomi: Tampere-Pirkkalan lentokenttä, Jyväskylän lentokenttä, Seinäjoki~
*Itä-Suomi: Tohmajärvi, Valtimo, Siikajoki~
*Pohjois-Suomi: Rovaniemiemen lentoasema
Definition: Table(Month,Loc)(~
-6.2,-7.4,-10.2,-11.7,~
-6.7,-7.7,-9.9,-11,~
-2.6,-3.3,-4.6,-6.1,~
2.9,2.2,1,-1,~
9.9,9,8.1,5.8,~
14.6,14.1,13.6,12.2,~
16.9,16,15.9,14.9,~
15,14,13.3,12.1,~
9.800000000000001,8.800000000000001,8,6.6,~
4.8,3.9,2.7,0.2,~
-0.3,-1.5,-3.2,-6.1,~
-4,-5.4,-7.8,-10~
)
NodeLocation: 352,48,1
NodeSize: 48,24
WindState: 2,98,90,476,339
DefnState: 2,138,183,414,335,0,MIDM
ValueState: 2,1432,108,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Loc,Month]
ReformVal: [Loc,Month]

Index Loc
{!40000|Att_PrevIndexValue: ['South','West','East','North']}
Title: Location
Definition: ['South','West','East','North']
NodeLocation: 352,80,1
NodeSize: 48,12

Variable Building_loc
Title: Residential building location
Description: Alueet perustuvat Tilastokeskuksen suuraluejakoon.~
~
Rakennusten osuus eri alueilla perustuu Tilastokeskuksen aluekohtaiseen rakennusten kerrosalatilastoon.
Definition: Table(Const_year,Loc)(~
0.42,0.32,0.15,0.1,~
0.39,0.3,0.15,0.16,~
0.37,0.31,0.15,0.17,~
0.38,0.28,0.16,0.18,~
0.43,0.27,0.14,0.16,~
0.47,0.27,0.11,0.15,~
0.42,0.29,0.13,0.16,~
0.42,0.29,0.13,0.16,~
0.42,0.29,0.13,0.16~
)
NodeLocation: 352,120,1
NodeSize: 48,24
DefnState: 2,147,378,676,303,0,MIDM
ValueState: 2,559,698,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Const_year,Loc]
ReformVal: [Loc,Const_year]

Chance Oa_temp_change
Title: Outdoor air temp change
Description: Lämpötilan muutos kaudella 2010-2039 verrattuna kauteen 1971-2000~
~
Jylhä et al. 2009. IL:n raportti.
Definition: Table(Month)(~
Fractiles[0.95, 1.8, 2.2, 2.7, 3.45],Fractiles[0.95, 1.8, 2.2, 2.7, 3.45],Fractiles[0.3, 1, 1.4, 1.9, 2.7],Fractiles[0.3, 1, 1.4, 1.9, 2.7],Fractiles[0.3, 1, 1.4, 1.9, 2.7],Fractiles[0, 0.6, 1.1, 1.5, 2.3],Fractiles[0, 0.6, 1.1, 1.5, 2.3],Fractiles[0, 0.6, 1.1, 1.5, 2.3],Fractiles[0.45, 1.1, 1.4, 1.7, 2.35],Fractiles[0.45, 1.1, 1.4, 1.7, 2.35],Fractiles[0.45, 1.1, 1.4, 1.7, 2.35],Fractiles[0.95, 1.8, 2.2, 2.7, 3.45])
NodeLocation: 456,48,1
NodeSize: 48,24
WindState: 2,185,245,476,224
DefnState: 2,388,250,416,303,0,MIDM
ValueState: 2,687,228,375,331,0,MIDM
NodeColor: 65535,52427,61166
ReformVal: [Undefined,Month,2]

Close Building_heat_consum

Variable Hs_efficiency
Title: Heat production efficiency
Units: -
Description: Efficiency of the heat production device~
~
Note! ~
*For local district heat production, the efficiency of the power plant is accounted for in this node.~
*For district heat and electricity production, efficiencies of different types of power plants are accounted for in the nodes ~
**'Heat production CO2 EMF (identifier: Heat_co2_emf)~
**'PM emission' (identifier: pm_emission)
Definition: Table(Heat_system)(~
0.9300000000000001,0.8,0.75,1,1,1,2.5,1,0.7,2)
NodeLocation: 408,280,1
NodeSize: 48,24
WindState: 2,98,90,608,392
DefnState: 2,138,384,363,303,0,MIDM
ValueState: 2,320,143,416,303,0,MIDM
ReformDef: [Bioher_sec_heat_scen,Heat_system]
ReformVal: [Bioher_sec_heat_scen,Heat_system]
{!40000|Att_EditSliceState: [Bioher_pri_heat_scen,3,Heat_system,1,Bioher_sec_heat_scen,1]}

Decision Const_year
Title: Area construction year
Description: Construction year of a building
Definition: Choice(Self,7)
NodeLocation: 136,80,1
NodeSize: 56,32
WindState: 2,101,85,476,358
Domain: ['<1960','1960','1970','1980','1990','2000','2010','2020','2030']
{!40300|DomainExpr: Discrete('<1960','1960','1970','1980','1990','2000','2010','2020','2030',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}
{!40000|Att_PrevIndexValue: ['<1960','1960','1970','1980','1990','2000','2010','2020','2030']}

Decision Bioher_pri_heat_scen
Title: BIOHER primary heat scenarios
Definition: Choice(Self,0)
NodeLocation: 272,80,1
NodeSize: 52,32
WindState: 2,144,132,494,353
ValueState: 2,211,252,416,303,0,MIDM
Aliases: Alias BIOHER_primary_heat1
Domain: ['BAU','Oil','Pellet','Local district, oil','Local district, wood','Electricity','Geothermal','Current district']
{!40300|DomainExpr: Discrete('BAU','Oil','Pellet','Local district, oil','Local district, wood','Electricity','Geothermal','Current district',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}
{!40000|Att_PrevIndexValue: ['BAU','Oil','Pellet','Local district, oil','Local district, wood','Electricity','Geothermal','Current district']}

Variable Area_unit_heat_con
Title: Area unit heat consumption
Units: kWh/m2/a
Definition: var a:= sum(Q_space_heating+Q_water_heating, month);~
~
if Heat_system = 'Electricity' or Heat_system = 'Secondary wood' or Heat_system = 'Air heat pump' then a[heat_dist='Electric radiator'] else a[heat_dist='Water radiator']
NodeLocation: 568,152,4
NodeSize: 48,29
WindState: 2,153,144,476,370
DefnState: 2,526,451,447,303,0,MIDM
ValueState: 2,90,188,777,303,0,MIDM
ReformDef: [Heat_system]
ReformVal: [Const_year,Heat_system]
{!40000|Att_ResultSliceState: [Fu_period,2,Heat_system,1,Const_year,1]}

Variable Area_prim_sec_heat
Title: Area primary & secondary heat consumption
Units: kWh/a
Description: Total heat consumption covered with different primary and secondary heating systems within an area
Definition: {var a:= Prim_heat_sys*House_size*Area_unit_heat_con*Houses_per_area;}~
~
var x:=Prim_heat_sys*Tot_heat_con*Houses_per_area;~
x:= if House_area_type = 'All' then x else x[House_area_type = House_area_type];~
x:=if Const_year = 'All' then x else x[Const_year = Const_year];~
~
var y:=Prim_heat_sys*Unit_heat_con*House_size*Houses_per_area;~
y:= if House_area_type = 'All' then y else y[House_area_type = House_area_type];~
y:= if Const_year = 'All' then y else y[Const_year = Const_year];~
~
var a:= if House_or_area='Single house' then x else y;~
~
var b:=sum(a*Sec_heat_sys,Heat_system);~
~
var c:=b[Bioher_sec_heat_scen='Air heat pump'];~
var d:=b[Bioher_sec_heat_scen='Wood'];~
~
var e:=if Bioher_sec_heat_scen = 'Air heat pump' and Heat_system='Air heat pump' then c else 0;~
~
e:=if Bioher_sec_heat_scen = 'Wood' and Heat_system='Secondary wood' then d else e;~
~
e:=a*(1-Sec_heat_sys)+e;~
~
if Bioher_sec_heat_scen = 'All' then e else e[Bioher_sec_heat_scen = Bioher_sec_heat_scen]~
~
~
~
~

NodeLocation: 272,360,3
NodeSize: 56,28
WindState: 2,207,249,637,534
ValueState: 2,154,354,829,320,0,MIDM
ReformVal: [Bioher_pri_heat_scen,Heat_system]
Att__TotalsIndex: Index Heat_system
{!40000|Att_ResultSliceState: [Tot_heat_con,4,Heat_system,0,Bioher_pri_heat_scen,1]}

Index Heat_system
Title: Heating system
Definition: ['Oil','Pellet boiler','Wood boiler','Local district, oil','Local district, wood','Electricity','Geothermal','Current district','Secondary wood','Air heat pump']
NodeLocation: 272,400,1
NodeSize: 56,12
WindState: 2,121,138,476,291
{!40000|Att_PrevIndexValue: ['Oil','Pellet boiler','Wood boiler','Local district, oil','Local district, wood','Electricity','Geothermal','Current district','Secondary wood','Air heat pump']}

Decision Bioher_sec_heat_scen
Title: BIOHER secondary heat scenarios
Definition: Choice(Self,2)
NodeLocation: 408,80,1
NodeSize: 52,32
WindState: 2,17,65,476,224
ValueState: 2,247,276,416,303,0,MIDM
Domain: ['None','Air heat pump','Wood']
{!40300|DomainExpr: Discrete('None','Air heat pump','Wood',type:['text'])}
{!40200|Att_ChoiceIndexes: Keyword Self}
{!40000|Att_PrevIndexValue: ['None','Air heat pump','Wood']}

Chance Sec_heat_sys
Title: Secondary heat system
Description: Fraction of heat consumption produced with a secondary heat system
Definition: Table(Bioher_pri_heat_scen,Heat_system,Bioher_sec_heat_scen)(~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0,~
0,Triangular(0.1,0.3,0.5),Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0.15,0.3,0.5),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,Triangular(0.2,0.4,0.7),Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,Triangular(0, 0.15, 0.3),~
0,0,0,~
0,0,0~
)
NodeLocation: 408,160,1
NodeSize: 48,24
DefnState: 2,100,314,840,303,0,MIDM
ValueState: 2,140,295,957,373,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heat_system,Bioher_pri_heat_scen]
ReformVal: [Bioher_sec_heat_scen,Bioher_pri_heat_scen,Undefined,Undefined,1]
{!40000|Att_ResultSliceState: [Heat_system,6,Bioher_pri_heat_scen,8,Bioher_sec_heat_scen,2]}
{!40000|Att_EditSliceState: [Bioher_sec_heat_scen,3,Bioher_pri_heat_scen,2,Heat_system,1]}

Variable Area_heat_purc
Title: Area heat purchase
Units: kWh/a
Description: Heat energy purchase by different primary and secondary heating systems within an area
Definition: Area_prim_sec_heat/Hs_efficiency
NodeLocation: 408,360,1
NodeSize: 52,28
ValueState: 2,757,94,840,333,0,MIDM
ReformVal: [Bioher_pri_heat_scen,Heat_system,2]
Att__TotalsIndex: Index Heat_system
{!40000|Att_ResultSliceState: [Heat_system,0,House_area_type,2,Sys_LocalIndex('Probability'),1,Bioher_pri_heat_scen,6]}

Variable Prim_heat_sys
Title: Primary heat system
Description: Fraction of primary heat systems within an area
Definition: Table(Const_year,Bioher_pri_heat_scen,Heat_system)(~
0.67,0,0.04,0,0,0.25,100u,0.04,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.67,0,0.04,0,0,0.25,100u,0.04,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.57,0,0.14,0,0,0.23,100u,0.06,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.2,0,0.16,0,0,0.55,0.01,0.08,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.15,0,0.07000000000000001,0,0,0.69,0.01,0.08,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.12,0.01,0.05,0,0,0.6,0.09,0.13,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.09,0.01,0.04,0,0,0.5600000000000001,0.14,0.16,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.09,0.01,0.04,0,0,0.5600000000000001,0.14,0.16,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0,~
0.09,0.01,0.04,0,0,0.5600000000000001,0.14,0.16,0,0,~
1,0,0,0,0,0,0,0,0,0,~
0,1,0,0,0,0,0,0,0,0,~
0,0,0,1,0,0,0,0,0,0,~
0,0,0,0,1,0,0,0,0,0,~
0,0,0,0,0,1,0,0,0,0,~
0,0,0,0,0,0,1,0,0,0,~
0,0,0,0,0,0,0,1,0,0~
)
NodeLocation: 272,160,1
NodeSize: 48,24
WindState: 2,98,90,476,300
DefnState: 2,51,233,1087,321,0,MIDM
ValueState: 2,138,100,865,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Heat_system,Const_year]
ReformVal: [Bioher_pri_heat_scen,Heat_system]
Att__TotalsIndex: Index Heat_system
{!40000|Att_ResultSliceState: [Const_year,7,Heat_system,1,Bioher_pri_heat_scen,1]}
{!40000|Att_EditSliceState: [Bioher_pri_heat_scen,1,Const_year,1,Heat_system,1]}

Chance House_size
Title: House size
Units: m2
Description: v. 2010 rakennettujen omakotitalojen koko (ka, tilastokeskuksen datoista laskettu)~
~
var a:=Building_input_data[Building_input='Floor area'];~
Triangular(a*0.75, a, a*1.25)
Definition: Table(House_area_type)(~
Triangular(176*0.8,176,176*1.2),Triangular(135*0.8,135,135*1.2))
NodeLocation: 272,288,1
NodeSize: 48,24
DefnState: 2,265,371,416,303,0,MIDM
ValueState: 2,220,364,385,202,0,MIDM
NodeColor: 65535,52427,61166

Variable Houses_per_area
Title: Houses per area
Definition: 1
NodeLocation: 272,216,1
NodeSize: 48,24
NodeColor: 65535,52427,61166

Decision Tot_heat_con
Title: Total heat consumption
Definition: Choice(Self,0)
NodeLocation: 128,224,1
NodeSize: 48,24
WindState: 2,102,83,476,277
Domain: [5000,10K,20K,30K,40K]
{!40300|DomainExpr: Discrete(5000,10K,20K,30K,40K,type:'number')}
{!40200|Att_ChoiceIndexes: Keyword Self}

Decision House_area_type
Title: House/area type
Definition: Choice(Self,1)
NodeLocation: 128,288,1
NodeSize: 48,24
WindState: 2,91,57,476,252
ValueState: 2,275,393,416,303,0,MIDM
Domain: ['New','Old']
{!40300|DomainExpr: Discrete('New','Old',type:'Text')}
{!40200|Att_ChoiceIndexes: Keyword Self}
{!40000|Att_PrevIndexValue: ['New','Old']}

Chance Unit_heat_con
Title: Unit heat consumption
Description: Low energy: 40-60 kWh/m2 tai 60% standarditasosta
Definition: Table(House_area_type)(~
Uniform(70,100),Uniform(120,260))
NodeLocation: 128,360,1
NodeSize: 48,24
ValueState: 2,72,75,416,303,0,CONF
ReformVal: [House_area_type,Undefined,2]

Decision House_or_area
Title: House / area POV
Definition: Choice(Self,2)
NodeLocation: 128,168,1
NodeSize: 48,24
Domain: ['Single house','Average area']
{!40300|DomainExpr: Discrete('Single house','Average area',type:'Text')}
{!40200|Att_ChoiceIndexes: Keyword Self}

Close Total_heat_consumpti

Module Co1
Title: CO2
Author: vkoe
Date: 25. Octta 2011 11:15
DefaultSize: 48,24
NodeLocation: 272,176,1
NodeSize: 52,28
DiagState: 2,261,108,344,317,17
NodeColor: 52427,65535,65535

Variable Heat_co2_emf
Title: Heat production CO2 EMF
Units: CO2-ekv g/kWh
Definition: Table(Heat_system)(~
Fuel_co2_emf[pp_fuel='Oil'],0,Fuel_co2_emf[pp_fuel='Wood'],Fuel_co2_emf[pp_fuel='Oil']/0.9,Fuel_co2_emf[pp_fuel='Wood']/0.9,sum(Elect_fuel*Fuel_co2_emf/Elect_pp_effic*Elect_pp_frac, pp_fuel, elect_pp),sum(Elect_fuel*Fuel_co2_emf/Elect_pp_effic*Elect_pp_frac, pp_fuel, elect_pp),sum(Dist_heat_fuel*Fuel_co2_emf/DH_PP_EFFIC*DH_PP_FRAC, pp_fuel, dh_pp),Fuel_co2_emf[pp_fuel='Wood'],sum(Elect_fuel*Fuel_co2_emf/Elect_pp_effic*Elect_pp_frac, pp_fuel, elect_pp))
NodeLocation: 96,152,1
NodeSize: 48,27
WindState: 2,117,153,476,224
DefnState: 2,96,234,745,303,0,MIDM
ValueState: 2,376,446,540,303,0,MIDM
NodeColor: 65535,52427,61166
ReformVal: [Fu_period,Heat_system]

Variable Co2_emission
Title: CO2 emission
Units: t / 5 year period
Description: CO2 emission during 5-year period~
~
sum(Area_heat_purc*Heat_co2_emf*5/1000000, Heat_system, Fu_period, const_year)~

Definition: (Area_heat_purc*Heat_co2_emf*5)/1000000
NodeLocation: 208,152,1
NodeSize: 48,24
WindState: 2,736,366,476,331
ValueState: 2,385,189,678,296,0,MIDM
ReformVal: [Fu_period,Bioher_pri_heat_scen]
Att__TotalsIndex: Index Fu_period
{!40000|Att_ResultSliceState: [Heat_system,1,Tot_heat_con,1,Bioher_pri_heat_scen,1,Fu_period,1]}

Variable Fuel_co2_emf
Title: Fuel CO2 EMF
Units: g/kWh
Description: Motiva 2004
Definition: Table(Pp_fuel)(~
279,202,382,341,0,0,301)
NodeLocation: 96,72,1
NodeSize: 48,24
WindState: 2,98,90,476,224
DefnState: 2,114,248,416,303,0,MIDM
ValueState: 2,159,186,416,303,0,MIDM
NodeColor: 65535,52427,61166

Close Co1

Module District_heat_produc
Title: District heat & electricity production
Author: vkoe
Date: 8. Febta 2011 9:41
DefaultSize: 48,24
NodeLocation: 272,96,1
NodeSize: 52,28
DiagState: 1,92,129,541,339,17
NodeColor: 52427,63897,65535

Index Pp_fuel
Title: PP fuel
Definition: ['Oil','Natural gas','Peat','Coal','Wood','Bio','Other']
NodeLocation: 208,88,1
NodeSize: 48,12
WindState: 2,813,483,476,253
{!40000|Att_PrevIndexValue: ['Oil','Natural gas','Peat','Coal','Wood','Bio','Other']}

Variable Dist_heat_fuel
Title: Current district heat fuels
Description: Tilastokeskus, kaikki vuosina 2005-2010 tuotettu kaukolämpö~
~
Other: mm. muovipolttoaineet, muut jätepolttoaineet, sekapolttoaineiden fossiilinen osuus, vety, sähkö, teollisuuden reaktio- ja sekundaarilämpö~
~
Yhteistuotannossa ja erillistuotannossa puun käytön oletettu lisääntyvän v.2008 energiastrategian mukaisesti (karkea arvioi). Tämän on oletettu vähentävän hiilen osuutta yhteistuotannossa ja öljyn osuutta erillistuotannossa.~
~

Definition: Table(Fu_period,Pp_fuel,Dh_pp)(~
0.01,0.24,~
0.31,0.29,~
0.21,0.11,~
0.29,0.06,~
0.15,0.15,~
0.01,0.03,~
0.02,0.12,~
0.01,0.235,~
0.31,0.29,~
0.21,0.11,~
0.285,0.06,~
0.155,0.155,~
0.01,0.03,~
0.02,0.12,~
0.01,0.23,~
0.31,0.29,~
0.21,0.11,~
0.28,0.06,~
0.16,0.16,~
0.01,0.03,~
0.02,0.12,~
0.01,0.2,~
0.31,0.29,~
0.21,0.11,~
0.25,0.06,~
0.19,0.19,~
0.01,0.03,~
0.02,0.12,~
0.01,0.17,~
0.31,0.29,~
0.21,0.11,~
0.22,0.06,~
0.22,0.22,~
0.01,0.03,~
0.02,0.12,~
0.01,0.17,~
0.31,0.29,~
0.21,0.11,~
0.22,0.06,~
0.22,0.22,~
0.01,0.03,~
0.02,0.12~
)
NodeLocation: 208,56,1
NodeSize: 48,24
WindState: 2,130,118,476,425
DefnState: 2,106,275,554,303,0,MIDM
ValueState: 2,178,141,583,303,0,MIDM
NodeColor: 19664,65535,19661
ReformDef: [Fu_period,Pp_fuel]
ReformVal: [Fu_period,Pp_fuel]
{!40000|Att_ResultSliceState: [Dh_pp,1,Pp_fuel,1,Fu_period,1]}
{!40000|Att_EditSliceState: [Dh_pp,2,Pp_fuel,1,Fu_period,1]}

Index Dh_pp
Title: DH PP
Definition: ['CHP','Heat']
NodeLocation: 96,88,1
NodeSize: 48,12
{!40000|Att_PrevIndexValue: ['CHP','Heat']}

Variable Dh_pp_frac
Title: Current district heat production
Description: Tilastokeskus, kaikki vuosina 2005-2010 tuotettu kaukolämpö
Definition: Table(Dh_pp)(~
0.76,0.24)
NodeLocation: 96,56,1
NodeSize: 48,24
WindState: 2,102,90,476,224
DefnState: 2,155,252,416,303,0,MIDM
ValueState: 2,156,176,416,303,0,MIDM
NodeColor: 19664,65535,19661

Index Elect_pp
Title: Elect PP
Description: CHP: combined power and heat generation~
Thermal non-CHP: thermal, non-nuclear power plants which only generate electricity
Definition: ['CHP','Thermal non-CHP']
NodeLocation: 96,192,1
NodeSize: 48,12
{!40000|Att_PrevIndexValue: ['CHP','Thermal non-CHP']}

Variable Elect_pp_frac
Title: Electricity production
Description: Lauhdevoimaloissa ja yhteistuotantovoimaloissa tuotetun sähkön osuus~
~
Tilastokeskus, osuus kaikesta 2005-2010 kulutetusta sähköstä~
~
Muut tuotantotavat 2010:~
Ydinvoima 26%~
Vesivoima 16%~
Tuulivoima 0.3%~
Tuonti 13%~
~
Tulevaisuuden muutos perustuu v. 2008 energiastrategiaan ja sen 2009 päivitykseen (TEM). Sähkön kulutus ja yhteistuotanto vähenevät tulevaisuudessa metsäteollisuuden rakannemuutoksesta johtuen. Lauhdevoiman osuuden arvioidaan pysyvän suurinpiirtein nykytasolla.~
~

Definition: Table(Fu_period,Elect_pp)(~
0.31,0.14,~
0.285,0.14,~
0.26,0.14,~
0.245,0.14,~
0.23,0.14,~
0.23,0.14~
)
NodeLocation: 96,160,1
NodeSize: 48,24
WindState: 2,109,312,476,374
DefnState: 2,141,346,639,303,0,MIDM
ValueState: 2,93,275,607,249,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Fu_period,Elect_pp]
ReformVal: [Fu_period,Elect_pp]
Att__TotalsIndex: Index Elect_pp

Variable Elect_fuel
Title: Electricity fuels
Description: Tilastokeskus, vuosina 2005-2010 tuotettu sähkö, lauhdevoimaloissa ja yhteistuotantovoimaloissa sähköntuotantoon käytettyjen polttoaineiden osuus~
~
Other: mm. muovipolttoaineet, muut jätepolttoaineet, sekapolttoaineiden fossiilinen osuus, vety, sähkö~
~
Tulevaisuuden kehitys perustuu v. 2008 energiastrategian linjauksiin. Siinä uusiutuvien osuutta ei kasvateta lauhdevoiman tuotannossa. Yhteistuotannossa v. 2020 mennessä uusiutuvien määrä kasvaa kaukolämmön tuotannossa, mutta sitä kompensoi teollisuuden yhteistuotannossa uusuituvien osuuden määrän lasku. Kokonaisuudessaan uusuiutuvien osuus pysyy nykytasolla.~
~
Muiden polttoaineiden osuuksien muuttumisesta ei ole tietoa, joten niiden on arvioitu pysyvän nykytasolla.~

Definition: Table(Fu_period,Pp_fuel,Elect_pp)(~
0.01,0.01,~
0.38,0.05,~
0.12,0.18,~
0.16,0.64,~
0.3,0.1,~
0.01,0.01,~
0.01,0.02,~
0.01,0.01,~
0.38,0.05,~
0.12,0.18,~
0.16,0.64,~
0.3,0.1,~
0.01,0.01,~
0.01,0.02,~
0.01,0.01,~
0.38,0.05,~
0.12,0.18,~
0.16,0.64,~
0.3,0.1,~
0.01,0.01,~
0.01,0.02,~
0.01,0.01,~
0.38,0.05,~
0.12,0.18,~
0.16,0.64,~
0.3,0.1,~
0.01,0.01,~
0.01,0.02,~
0.01,0.01,~
0.38,0.05,~
0.12,0.18,~
0.16,0.64,~
0.3,0.1,~
0.01,0.01,~
0.01,0.02,~
0.01,0.01,~
0.38,0.05,~
0.12,0.18,~
0.16,0.64,~
0.3,0.1,~
0.01,0.01,~
0.01,0.02~
)
NodeLocation: 208,160,1
NodeSize: 48,24
WindState: 2,152,254,476,450
DefnState: 2,167,212,577,303,0,MIDM
ValueState: 2,190,386,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Fu_period,Pp_fuel]
ReformVal: [Elect_pp,Pp_fuel]
{!40000|Att_ResultSliceState: [Fu_period,1,Pp_fuel,1,Elect_pp,1]}
{!40000|Att_EditSliceState: [Elect_pp,2,Pp_fuel,1,Fu_period,1]}

Variable Dh_pp_effic
Title: Distric heat power plant efficiency
Definition: Table(Dh_pp)(~
0.9,0.9)
NodeLocation: 320,56,1
NodeSize: 48,24
WindState: 2,164,321,476,224
DefnState: 2,149,523,416,303,0,MIDM
ValueState: 2,153,243,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Dh_pp,Pp_fuel]

Variable Elect_pp_effic
Title: Electricity power plant efficiency
Definition: Table(Elect_pp)(~
0.9,0.44)
NodeLocation: 320,160,1
NodeSize: 48,24
DefnState: 2,199,233,416,303,0,MIDM
ValueState: 2,195,381,416,303,0,MIDM
NodeColor: 65535,52427,61166

Variable Elect_pp_capacity
Title: Electricity power plant capacity
Definition: Table(Elect_pp,Power_capacity)(~
0.8100000000000001,0.04,0.15,0,~
0.8,0.2,0,0~
)
NodeLocation: 440,160,1
NodeSize: 48,24
WindState: 2,125,124,476,224
DefnState: 2,206,333,416,303,0,MIDM
ValueState: 2,193,369,381,229,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Elect_pp,Power_capacity]
ReformVal: [Elect_pp,Power_capacity]

Index Power_capacity
Title: Power capacity
Definition: ['>50 MW','20-50 MW','<20 MW','Domestic']
NodeLocation: 440,96,1
NodeSize: 48,16
{!40000|Att_PrevIndexValue: ['>50 MW','20-50 MW','<20 MW','Domestic']}

Variable Dh_pp_capacity
Title: District heat power plant capacity
Description: Lämmöntuotanto eri kokoluokan voimaloissa, laskettu Energiateolliisuuden kaukolämpötilastosta vuodelle 2010.~
~
Perustuu lämpökapasiteetin jakaumaan eri kokoisissa voimaloissa (CHP latoksissa kokoluokan määrittää kokonaiskapasiteetti, sähkö+lämpö)
Definition: Table(Dh_pp,Power_capacity)(~
0.83,0.07000000000000001,0.1,0,~
0.47,0.29,0.24,0~
)
NodeLocation: 440,56,1
NodeSize: 48,24
WindState: 2,137,200,476,280
DefnState: 2,100,395,528,303,0,MIDM
ValueState: 2,195,273,416,303,0,MIDM
NodeColor: 65535,52427,61166
ReformDef: [Dh_pp,Power_capacity]
ReformVal: [Dh_pp,Power_capacity]
{!40000|Att_EditSliceState: [Dh_pp,2,Power_capacity,1,Fu_period,1]}

Close District_heat_produc

Library Performance_profiler
Title: Performance Profiler
Description: Use this library to see which variables and functions are taking most of the computation time or memory when running your model. You need Analytica Enterprise, Power Player, or ADE - it will not work for lesser editions of Analytica.  Here's how to use it:~
~
1. First run your model, i.e. show (and therefore compute) results for the outputs you are interested in timing.~
~
2. Click the "Performance profiles" button to display the Bytes (memory used) and CPU msecs (milliseconds of computation time by the computers "Central Processing Unit") for each object (variable or function).  ~
~
NOTES:~
A. Select option from "Sort objects by" to control how results are sorted.~
~
B. It omits objects with negligible CPU time (less than 1 millisecond) AND less than 25 Bytes memory.~
~
C. "msecs w. ancestors" means the CPU time to compute the object PLUS all its ancestors or predecessors.~
~
D. "Bytes" shows the memory usage after computing the variable. Some objects with complex expressions may use much more memory during the computation.~
~
E. In Performance Profiles, double-click on an Object title (in Object_ID index or its Module title to open its Object window.~
~
If you want to add in the time for further calculations:~
~
3. Make those calculations by showing results for those variables.~
~
4. Click button "Update Profiles"~
~
5. Click the "Performance profiles" button again.~
~
If you want to time some different calculations:~
~
6. Click "Zero out times"~
~
7. Change relevant inputs to cause their dependents to need to be recomputed.~
~
8. Show results for outputs of interest.~
~
9. Click button "Update Profiles"~
~
10. Click the "Performance profiles" button to see the new timings and memory usage.~
~
Copyright 2007 Lumina Decision Systems, Inc
Author: Lonnie Chrisman & Alex Graham
Date: Sun, Jul 13, 2003 12:18 PM
SaveAuthor: Lonnie
SaveDate: Thu, Oct 07, 2010 1:40 PM
DefaultSize: 48,24
NodeLocation: 136,328,1
NodeSize: 60,28
NodeInfo: 1,1,1,1,1,1,0,0,0,0
DiagState: 2,14,393,448,245,21
WindState: 2,372,189,507,744
FontStyle: Arial, 15

Button Zero_out_times
Title: Zero out times
Description: Zeros all computation times, so that only the times of subsequent computations will be shown.
NodeLocation: 248,40,1
NodeSize: 48,24
Script: ResetEvalTimes~
Reset_profiler := 1~


Button Update_profiles
Title: Update profiles
Description: Sets the profiles to recompute, adding in any further computation time since profiles were last generated.
NodeLocation: 64,40,1
NodeSize: 48,24
WindState: 2,39,304,476,224
Script: (Reset_profiler := Reset_profiler+1)

FormNode Sort_profiled_objec1
Title: Sort profiled objects by
Definition: 0
NodeLocation: 168,83,1
NodeSize: 154,13
NodeInfo: 0,0,0,0,0,0,0,170
Original: Sort_objects_by

FormNode Ordered_profiles1
Title: Ordered profiles
Definition: 1
NodeLocation: 168,112,1
NodeSize: 154,14
NodeInfo: 1,0,0,1,0,0,0,72,0,1
Original: Performance_profiles

Text Te7
NodeLocation: 168,68,-1
NodeSize: 160,60
NodeInfo: 1,0,0,0,1,1,0,,0,

Module Profiler_details
Title: Profiler details
Author: Max Henrion
Date: Wed 03-Oct-07 8:20 AM
DefaultSize: 48,24
NodeLocation: 168,168,1
NodeSize: 48,24
DiagState: 2,377,221,454,301,21

Function Profiler_descendants(m: Object)
Title: Profiler_Descendants(m)
Description: Returns a list including module m and all its descendants, i.e. objects (variables, functions, and modules)  contained in m - and in any modules it contains, recursively -- excluding this Profiling module.
Definition: VAR res := [Handle(m)];~
VAR c := contains OF  m ;~
IFONLY (c) = NULL OR  Identifier m  = Id_of_this_library THEN res~
ELSE BEGIN ~
  FOR v := c Do BEGIN~
     VAR d := Profiler_descendants(v);~
     res := Concat(res, d);~
     0~
  END; ~
  res~
END
NodeLocation: 184,182,1
NodeSize: 68,24
WindState: 2,75,242,580,585
Recursive: 1

Decision Sort_objects_by
Title: Sort objects by
Description: Select field to sort profiled objects. "CPU secs" or "KBytes" are most useful. "Class" doesn't work.
Definition: Choice(Profiler_fields,3,0)
NodeLocation: 336,248,1
NodeSize: 48,24
WindState: 2,102,90,523,465
Aliases: FormNode Sort_profiled_objec1
{!40200|Att_ChoiceIndexes: Index Profiler_fields}

Index Profiler_fields
Title: Profiler fields
Definition: ['Class','Module','Bytes','CPU msecs','msecs w ancestors']
NodeLocation: 96,54,1
NodeSize: 48,24
{!40000|Att_PrevIndexValue: ['Class','Module','Bytes','CPU msecs','msecs w ancestors']}

Variable Attrib_name_by_profi
Title: Attrib name by profile field
Definition: Table(Profiler_fields)(~
'Class',0,'Memory','EvaluationTime','EvaluationTimeAll')
NodeLocation: 208,55,1
NodeSize: 48,31
DefnState: 2,352,26,430,218,0,MIDM

Function Profileobj(o: atomic handle)
Title: ProfileObj(o)
Description: Returns a profile (with Class, Bytes, Memory, CPU seconds, CPU seconds w ancestors) for  the object with identifier o.
Definition: FOR field := Profiler_fields DO~
     IFONLY field = 'Module' THEN (Isin OF o)~
     ELSE IF field = 'Bytes' THEN MemoryInUseBy(Handle(o))~
     ELSE (VAR attrib := Attrib_name_by_profi[Profiler_fields=field]; ~
              IF attrib ='Class' THEN  (attrib OF o) ELSE (attrib OF o)*1000)
NodeLocation: 336,54,1
NodeSize: 56,24
WindState: 2,432,9,541,583

Function Profileall()
Title: ProfileAll()
Description: Returns a profile (with Class, Bytes, CPU msecs, msecs w ancestors) for all the variables in this model whose CPU msecs>0 or Bytes > 24, excluding those in the Profiler.
Definition: var top := topmodel_id;~
MetaIndex allobjs := Profiler_descendants(top);~
VAR allProfiles := Profileobj(allobjs);~
MetaIndex Objs := Subset(allProfiles[Profiler_fields='CPU msecs'] > 0 OR~
                                           allProfiles[Profiler_fields='Bytes'] > 24 OR~
                                           allProfiles[Profiler_fields='msecs w ancestors']);~
allProfiles[allobjs = Objs]
NodeLocation: 336,120,1
NodeSize: 56,24
WindState: 2,438,69,525,397

Variable Topmodel_id
Title: TopModel ID
Definition: Reset_profiler; VAR m := Isin OF Self;~
WHILE (NOT IsUndef(Isin OF  m )) DO m := Isin OF  m
NodeLocation: 208,118,1
NodeSize: 48,24

Variable Performance_profiles
Title: Performance profiles
Description: Shows the Class, Kbytes (memory used), CPU secs (to compute this object), CPU secs w. ancestors (time to compute this variable and all its predecessors) for all objects (variables and functions) with non-zero computation time, sorted as requested.
Definition: VAR Profiles := Profileall();~
var sortField := Profiles[Profiler_fields=Sort_objects_by];~
if Sort_objects_by<>"Class" then sortField := -sortField;~
MetaIndex object_id := SortIndex(sortField, Profiles.Objs);~
Profiles[.Objs = object_id]
NodeLocation: 336,182,1
NodeSize: 52,24
WindState: 2,102,90,497,494
ValueState: 2,74,28,844,548,0,MIDM
Aliases: FormNode Ordered_profiles1
GraphSetup: {!40000|Att_graphvaluerange Performance_profiles:1,,,,,,10}~
{!40000|Att_graphindexrange Profiler_fields:1,,,,,,10}~
{!40000|Flip:8}~
{!40000|Att_catlinestyle Graph_primary_valdim:9}
ReformVal: [Profiler_fields,Sys_LocalIndex('OBJECT_ID')]
NumberFormat: 1,I,6,3,1,0
{!40000|Att_ResultSliceState: [Profiler_fields,2,Sys_LocalIndex('OBJECTS_IDS'),1]}

Variable Reset_profiler
Title: Reset Profiler
Description: Used to reset the computations for profiling.
Definition: 1
NodeLocation: 96,118,1
NodeSize: 48,24

Variable Id_of_this_library
Title: ID of this library
Definition: Identifier(Isin OF (Isin OF Self))
NodeLocation: 184,248,1
NodeSize: 48,24

Close Profiler_details

Close Performance_profiler

Close Claih