Exposures in Finland

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Question

What are typical exposure levels of common pollutants in Finland?

Answer

+ Show code- Hide code library(OpasnetUtils) # A package with Opasnet functionalities library(xtable) # A package with table formats library(ggplot2) # A package with fancy graph formats objects.get("q5z9YayubD5KjRPt") # objects.latest("Op_en5918", "calculations") # Get the latest ovariables from code calculations on page Op_en5918. Exposure <- EvalOutput(Exposure) Exposed.Fraction <- EvalOutput(Exposed.Fraction) Background.Exposure <- EvalOutput(Background.Exposure) print(xtable(Exposure@output[Exposure@output$Iter == 1, ]), type = 'html') # Show a result table print(xtable(Background.Exposure@output[Background.Exposure@output$Iter == 1, ]), type = 'html') print(xtable(Exposed.Fraction@output), type = 'html') ggplot(exposureFinland@output, # Show a bar chart aes(x = Exposure, y = exposureFinlandResult)) + geom_bar(position="dodge") + theme_grey(base_size = 24) + theme(axis.text.x = element_text(angle = 90, hjust = 1))

Default run

Rationale

Calculations

Huom! Päivitin tätä koodia sen jälkeen kun raportoin virheestä ei lipsu vaan särkyi. Senhetkinen koodi löytyy [1]

Note! The ovariables are NOT updated by updating the data table. You have to also re-run this initiation code.

[http://en.opasnet.org/en-opwiki/index.php/Special:R-tools?id=SXD46CcsFO9WaKs5 Default run}

+ Show code- Hide code library(OpasnetUtils) library(xtable) data <- tidy(opbase.data("Op_en5918")) data <- data[ , !colnames(data) %in% c("Obs", "Exposure.metric", "Age", "Description")] # Remove redundant columns. colnames(data)[colnames(data) == "Exposed.fraction"] <- "Exposed.fractionResult" colnames(data)[colnames(data) == "Exposure"] <- "ExposureResult" colnames(data)[colnames(data) == "Background.exposure"] <- "Background.ExposureResult" Exposure <- Ovariable( "Exposure", data = data[ , !colnames(data) %in% c( "Exposed.fractionResult", "Background.ExposureResult" )], save = FALSE ) Exposed.Fraction <- Ovariable( "Exposed.Fraction", data = data[ , !colnames(data) %in% c( "ExposureResult", "Background.ExposureResult" )], save = FALSE ) Background.Exposure <- Ovariable( "Background.Exposure", data = data[ , !colnames(data) %in% c( "Exposed.fractionResult", "ExposureResult" )], save = FALSE ) objects.put(Exposure, Exposed.Fraction, Background.Exposure) cat("Ovariables Exposure, Exposed.Fraction, and Background.Exposure saved. Save the key.\n") # page_indent = Op_en5918, code_name = calculations\n") print(xtable(EvalOutput(Exposure, N = 1)@output), type = 'html') print(xtable(EvalOutput(Exposed.Fraction, N = 1)@output), type = 'html') print(xtable(EvalOutput(Background.Exposure, N = 1)@output), type = 'html')

Data

Part of data from op_fi:Seturi/altistus

Exposures in Finland: Difference between revisions(-)

Obs	Pollutant	Exposure.route	Unit	Exposure.metric	Population	Age	Exposed.fraction	Exposure	Background.exposure	Description
1	Indoor radon	Inhalation	Bq /m3		Whole population		1	100 (95 - 105)	5 (4 - 9)
2	PM2.5	Inhalation	µg /m3		Whole population		1	7 (6 - 8)	3
3	Chlorination byproducts	Ingestion	µg /L		Users of chlorinated surface water		0.44	611 (488.8 - 733.2)	0

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