| Title: | Environmental Probabilistic Risk Assessment Tools |
|---|---|
| Description: | It contains functions for dose calculation for different routes, fitting data to probability distributions, random number generation (Monte Carlo simulation) and calculation of systemic and carcinogenic risks. For more information see the publication: Barrio-Parra et al. (2019) "Human-health probabilistic risk assessment: the role of exposure factors in an urban garden scenario" <doi:10.1016/j.landurbplan.2019.02.005>. |
| Authors: | Fernando Barrio-Parra [aut, cre, cph]
|
| Maintainer: | Fernando Barrio-Parra <[email protected]> |
| License: | GPL |
| Version: | 1.0.1 |
| Built: | 2024-11-26 06:23:57 UTC |
| Source: | CRAN |
A collection of functions employed in environmental risk assessment to model exposure to a toxicant and predicting health effects, allowing to characterize variability and uncertainty in risk estimations
A set of tools to perform a deterministic and probabilistic risk assessment.
F.Barrio-Parra
Maintainer: [email protected]
#### Performs Deterministic Environmental Risk Assessment ##### # Example of dermal contact with a chemical in swiming water # Estimate the dermal absorbed dose during swiming in waters with a carcinogenic chemical # (water concentration of 250 mg/m^3) DWIR ( CW = 250) # For a systemic effect: DWIR ( CW= 250, AT=24*365) # Specifying all the parameters for the carcinogenic case I = DWIR ( CW=250, IR=1.5, EF = 300, ED = 24, BW = 85) # Chemical Slope factor SFAs = 1.5 # Dermal Absorption Factor ABSAs = 3e-02 # Gastrointestinal Absorption Factor GIAs = 1 # Risk Estimation RISKdermal (AD = I, SF = SFAs, GI = GIAs) #### Perform a test to assess the fitness of a theorical distribution to empirical data #### set.seed(123) a <- rnorm(n=100, mean =1.5, sd = 0.25) b <- rnorm(n = 15, mean = 300, sd = 15) fit_dist_test(a) fit_dist_test(b) # Graphical representation of data fitting to a distribution plot_fit_dist(a, "norm") plot_fit_dist(b, "norm") #### Perform a Probabilistic Environmental Risk Assessment #### Fita <- Fit_dist_parameter(a) Fitb <- Fit_dist_parameter(b) IRr <-random_number_generator(n = 10000, Fited = Fita, dist = "norm", a =0.8, b = 2.1) EFr <-random_number_generator(n = 10000, Fited = Fitb, dist = "norm", a =250, b = 330) I = DWIR ( CW=250, IR=IRr, EF = EFr, ED = 24, BW = 85) # Risk Estimation Risk <- RISKdermal (AD = I, SF = SFAs, GI = GIAs) hist (Risk) quantile (Risk, c (0.05, 0.25, 0.5, 0.75, 0.95))#### Performs Deterministic Environmental Risk Assessment ##### # Example of dermal contact with a chemical in swiming water # Estimate the dermal absorbed dose during swiming in waters with a carcinogenic chemical # (water concentration of 250 mg/m^3) DWIR ( CW = 250) # For a systemic effect: DWIR ( CW= 250, AT=24*365) # Specifying all the parameters for the carcinogenic case I = DWIR ( CW=250, IR=1.5, EF = 300, ED = 24, BW = 85) # Chemical Slope factor SFAs = 1.5 # Dermal Absorption Factor ABSAs = 3e-02 # Gastrointestinal Absorption Factor GIAs = 1 # Risk Estimation RISKdermal (AD = I, SF = SFAs, GI = GIAs) #### Perform a test to assess the fitness of a theorical distribution to empirical data #### set.seed(123) a <- rnorm(n=100, mean =1.5, sd = 0.25) b <- rnorm(n = 15, mean = 300, sd = 15) fit_dist_test(a) fit_dist_test(b) # Graphical representation of data fitting to a distribution plot_fit_dist(a, "norm") plot_fit_dist(b, "norm") #### Perform a Probabilistic Environmental Risk Assessment #### Fita <- Fit_dist_parameter(a) Fitb <- Fit_dist_parameter(b) IRr <-random_number_generator(n = 10000, Fited = Fita, dist = "norm", a =0.8, b = 2.1) EFr <-random_number_generator(n = 10000, Fited = Fitb, dist = "norm", a =250, b = 330) I = DWIR ( CW=250, IR=IRr, EF = EFr, ED = 24, BW = 85) # Risk Estimation Risk <- RISKdermal (AD = I, SF = SFAs, GI = GIAs) hist (Risk) quantile (Risk, c (0.05, 0.25, 0.5, 0.75, 0.95))
Estimates the Absorbed dose [mg/Kg*day] of chemicals through dermal contact with a soil
AD(CS = 1, SA = 2800, AF = 0.2, ABS = 0.001, EF = 350, ED = 24, BW = 70, AT = 365 * 70)AD(CS = 1, SA = 2800, AF = 0.2, ABS = 0.001, EF = 350, ED = 24, BW = 70, AT = 365 * 70)
CS |
Chemical concentration in soil [mg/Kg] |
SA |
Skin surface area available for contact [cm^2] |
AF |
Skin adherence factor [mg/cm^2] |
ABS |
Absorption factor (Chemical specific) [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical Absorbed dose [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
## Estimated absorbed dose for the estimation of carcinogenic effects using # the default variables (EPA 2011) for a chemical soil concentration of # 0.2 mg/Kg AD( CS=0.2) # For a systemic effect: AD( CS=0.2, AT=24*365) # Specifying all the parameters for the carcinogenic case AD( CS=0.2, SA=2300, AF=0.25, ABS=0.01, EF=150, ED=10, BW=80)## Estimated absorbed dose for the estimation of carcinogenic effects using # the default variables (EPA 2011) for a chemical soil concentration of # 0.2 mg/Kg AD( CS=0.2) # For a systemic effect: AD( CS=0.2, AT=24*365) # Specifying all the parameters for the carcinogenic case AD( CS=0.2, SA=2300, AF=0.25, ABS=0.01, EF=150, ED=10, BW=80)
Dermal conctact with chemicals in soil by bootstrap
ADboot(n, CS, SA, AF, ABS, EF, ED, BW, AT)ADboot(n, CS, SA, AF, ABS, EF, ED, BW, AT)
n |
Output vector length |
CS |
Chemical concentrtion in soil [mg/Kg] |
SA |
Skin surface area available for contact [cm^2] |
AF |
Skin adherence factor [mg/cm^2] |
ABS |
Absorption factor (Chemical specific) [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical Absorbed dose [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
# Carcinogenic effects c <- rnorm( n= 10, mean = 0.2, sd = 0.05 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) ADboot (n = 1000, SA=2300, AF=0.25, ABS=0.01,CS = c, BW = b, ED = 10, EF = 250)# Carcinogenic effects c <- rnorm( n= 10, mean = 0.2, sd = 0.05 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) ADboot (n = 1000, SA=2300, AF=0.25, ABS=0.01,CS = c, BW = b, ED = 10, EF = 250)
Estimates the Intake rate by inhalation of airborne chemicals (vapor phase) [mg/Kg*day]
AIR(CA = 1, IR = 20, ET = 24, EF = 350, ED = 24, BW = 70, AT = 365 * 70)AIR(CA = 1, IR = 20, ET = 24, EF = 350, ED = 24, BW = 70, AT = 365 * 70)
CA |
Chemical concentrtion in air [mg/m^3] |
IR |
Inhalation Rate [m^3/hour] |
ET |
Exposure time [hours/day] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Intake rate by inhalation of airborne chemicals (vapor phase) I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
## Estimated absorbed dose for the estimation of carcinogenic effects using # the default variables (EPA 2011) for a chemical air concentration # of 0.2 mg/m^3 AIR ( CA=0.2) # For a systemic effect: AIR ( CA=0.2, AT=24*365) # Specifying all the parameters for the carcinogenic case AIR ( CA=0.2, IR=25, ET = 24, EF = 300, ED = 24, BW = 85)## Estimated absorbed dose for the estimation of carcinogenic effects using # the default variables (EPA 2011) for a chemical air concentration # of 0.2 mg/m^3 AIR ( CA=0.2) # For a systemic effect: AIR ( CA=0.2, AT=24*365) # Specifying all the parameters for the carcinogenic case AIR ( CA=0.2, IR=25, ET = 24, EF = 300, ED = 24, BW = 85)
Estimates the Intake rate by inhalation of airborne chemicals (vapor phase) [mg/Kg*day]
AIRboot(n, CA, IR, ET, EF, ED, BW, AT)AIRboot(n, CA, IR, ET, EF, ED, BW, AT)
n |
Output vector length |
CA |
Chemical concentrtion in air [mg/m^3] |
IR |
Inhalation Rate [m^3/hour] |
ET |
Exposure time [hours/day] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Intake rate by inhalation of airborne chemicals (vapor phase) I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
# Carcinogenic effects c <- rnorm( n= 10, mean = 0.2, sd = 0.05 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) AIRboot (n = 1000, CA=c, IR=25, ET = 24, EF = 300, ED = 24, BW = b)# Carcinogenic effects c <- rnorm( n= 10, mean = 0.2, sd = 0.05 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) AIRboot (n = 1000, CA=c, IR=25, ET = 24, EF = 300, ED = 24, BW = b)
Auxiliar function to check p-value significance (Function created for internal use of the model).
condition(n)condition(n)
n |
p-value |
Return "Significant" or "Not-significant" - Object class "character"
condition ( 0.001) condition (0.1)condition ( 0.001) condition (0.1)
Estimates the chemical Intake rate by Drinking Water [mg/Kg*day]
DWIR(CW = 1, IRW = 2, EF = 350, ED = 24, BW = 80, AT = 365 * 70)DWIR(CW = 1, IRW = 2, EF = 350, ED = 24, BW = 80, AT = 365 * 70)
CW |
Chemical concentrtion in water [mg/L] |
IRW |
Water Ingestion Rate [L/Day] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical intake rate by drinking water I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
# Estimate the dermal absorbed dose during swiming in waters with a carcinogenic chemical # (water concentration of 250 mg/m^3) DWIR ( CW = 250) # For a systemic effect: DWIR ( CW= 250, AT=24*365) # Specifying all the parameters for the carcinogenic case DWIR ( CW=250, IR=1.5, EF = 300, ED = 24, BW = 85)# Estimate the dermal absorbed dose during swiming in waters with a carcinogenic chemical # (water concentration of 250 mg/m^3) DWIR ( CW = 250) # For a systemic effect: DWIR ( CW= 250, AT=24*365) # Specifying all the parameters for the carcinogenic case DWIR ( CW=250, IR=1.5, EF = 300, ED = 24, BW = 85)
Estimates the chemical Intake rate by Drinking Water [mg/Kg*day]
DWIRboot(n, CW, IRW, EF, BW, ED, AT)DWIRboot(n, CW, IRW, EF, BW, ED, AT)
n |
Output vector length |
CW |
Chemical concentrtion in water [mg/L] |
IRW |
Water Ingestion Rate [L/Day] |
EF |
Exposure frequency [day/yr] |
BW |
Body weight [Kg] |
ED |
Exposure duration [yr] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical intake rate by drinking water I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
# Carcinogenic effects c <- rnorm( n= 10, mean = 250, sd = 15 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) DWIRboot (n = 1000, CW=c, IR=1.5, EF = 300, ED = 24, BW = b)# Carcinogenic effects c <- rnorm( n= 10, mean = 250, sd = 15 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) DWIRboot (n = 1000, CW=c, IR=1.5, EF = 300, ED = 24, BW = b)
Auxiliar function for internal use only
extr_par(x, dist)extr_par(x, dist)
x |
List of parameters obtained by the aplication of the Fit_dist_parameter function |
dist |
Name of the distribution we would like to stract the parameters ("norm", "lnorm", "geom", "exp", "pois", "gamma", "cauchy", "logis", "weibull", "nbinom", "beta", "chisq", "t", "f") |
A list of fitted parameters.
F. Barrio-Parra
a <- rnorm(n=100, mean =10, sd = 1) b <- Fit_dist_parameter(a) extr_par(x = b, dist ="norm")a <- rnorm(n=100, mean =10, sd = 1) b <- Fit_dist_parameter(a) extr_par(x = b, dist ="norm")
Returns the distribution parameters adjusted for by maximum likelihood (mle) for the following distributions: "normal","log-normal","geometric","exponential","Poisson", "cauchy" , "logistic" and "weibull"
Fit_dist_parameter(x)Fit_dist_parameter(x)
x |
A numeric vector of length at least one containing only finite values (non-censored data) |
normal |
Fitted Mean and sd for a normal distribution |
`log-normal` |
Fitted Meanlog and sdlog for a log-normal distribution |
geometric |
Fitted prob for a geometric distribution |
exponential |
Fitted rate for a exponential distribution |
Poisson |
Fitted lambda for a exponential distribution |
cauchy |
Fitted location and scale for a Cauchy distribution |
logistic |
Fitted location and scale for a Logistic distribution |
weibull |
Fitted shape and scale for a weibull distribution |
F. Barrio-Parra
Function fitdistr in Library (MASS)
a <- rnorm(n=100, mean =10, sd = 1) b <- Fit_dist_parameter(a) # Examples of result extraction b$normal b$weibulla <- rnorm(n=100, mean =10, sd = 1) b <- Fit_dist_parameter(a) # Examples of result extraction b$normal b$weibull
Returns a data frame with the summary of Fiting distribution tests for the following distributions: "normal","log-normal","geometric","exponential","Poisson", "cauchy" , "logistic" and "weibull".
The considered Godness-of-fit tests are: Bayesian Information Criterium (BIC), Akaike Information Criterium (AIC), Kolmogorov-Smirnov test and Anderson-Darling test.
fit_dist_test(x)fit_dist_test(x)
x |
A numeric vector of length at least one containing only finite values |
Distribution |
Name of the tested distribution |
BayesianIC |
Bayesian Information Criterium (BIC) |
AkaikeIC |
Akaike Information Criterium (AIC) |
Kol-SmirD |
The value of the Kolmogorov-Smirnov test statistic |
Kol-SmirPvalue |
The value of the Kolmogorov-Smirnov test p-value |
Signigicance KS |
A column to check the significance of the Kolmogorov-Smirnov test |
And-Darl |
The value of the nderson-Darling test statistic |
And-DarlPvalue |
The value of the Anderson-Darling test p-value |
Signigicance AD |
A column to check the significance of the Anderson-Darling test |
F. Barrio-Parra
ad.test library(kSamples), AIC library(stats), BIC library(stats), ks.test library(stats),
set.seed(123) a <- rnorm(n=100, mean =10, sd = 1) fit_dist_test(a) b<- rexp(n = 100,rate = 1) fit_dist_test(b)set.seed(123) a <- rnorm(n=100, mean =10, sd = 1) fit_dist_test(a) b<- rexp(n = 100,rate = 1) fit_dist_test(b)
Returns the Hazard Index (non carcinogenic effects)
HI(I, RFD)HI(I, RFD)
I |
Intake Rate [mg/Kg*day] |
RFD |
Reference dose [mg/Kg*day] |
Hazard Index [-] - Object class "numeric"
F. Barrio-Parra
# Assessing if there is systemic risk for an adult receptor that drinks water with 1000 ug/L # of hexaclorobence (Reference Dose (IRIS data base) = 8e-04 [mg/Kg*day]) in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) HI (I = DWIR( CW=1, AT=24*365), RFD = 8e-04)# Assessing if there is systemic risk for an adult receptor that drinks water with 1000 ug/L # of hexaclorobence (Reference Dose (IRIS data base) = 8e-04 [mg/Kg*day]) in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) HI (I = DWIR( CW=1, AT=24*365), RFD = 8e-04)
Returns the Hazard Index for dermal exposure with chemicals (non carcinogenic effects)
HIdermal(AD, RFD, GI)HIdermal(AD, RFD, GI)
AD |
Absorbed dose [mg/Kg*day] |
RFD |
Reference dose [mg/Kg*day] |
GI |
Gastrointestinal Absorption factor (chemical specific) [-] |
Hazard Index [-] - Object class "numeric"
F. Barrio-Parra
# Assess if there is non-carcinogenic risk for an dadult thorug dermal # contact exposed to a soil that contains 45 mg/Kg of As in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) RfDAs = 3e-04 # Dermal Absorption Factor ABSAs = 3e-02 # Gastrointestinal Absorption Factor GIAs = 1 I = AD (CS = 45,ABS = ABSAs, AT= 24*365) HIdermal (AD = I, RFD = RfDAs, GI = GIAs)# Assess if there is non-carcinogenic risk for an dadult thorug dermal # contact exposed to a soil that contains 45 mg/Kg of As in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) RfDAs = 3e-04 # Dermal Absorption Factor ABSAs = 3e-02 # Gastrointestinal Absorption Factor GIAs = 1 I = AD (CS = 45,ABS = ABSAs, AT= 24*365) HIdermal (AD = I, RFD = RfDAs, GI = GIAs)
Returns the Hazard Index (systemic effects) for inhalation of vapors
HIinhal(INH, RFC)HIinhal(INH, RFC)
INH |
Inhalated dose (mg/m^3) |
RFC |
Reference concentration (mg/m^3) |
Hazard Index (non carcinogenic effects) [-] - Object class "numeric"
F. Barrio-Parra
# Assess if there is systemic risk for the exposure of an adult # (Reasonable Maximum Exposure) to a Toluene air concentration of 2 mg/ m^3 HIinhal (INH = AIR (CA = 2, AT = 365*24), RFC = 5)# Assess if there is systemic risk for the exposure of an adult # (Reasonable Maximum Exposure) to a Toluene air concentration of 2 mg/ m^3 HIinhal (INH = AIR (CA = 2, AT = 365*24), RFC = 5)
Estimates the Intake rate of chemicals by inhalation of resuspended soil particles [mg/Kg*day]
INH(C = 10, EF = 350, ED = 24, PEF = 1.36^9, AT = 365 * ED)INH(C = 10, EF = 350, ED = 24, PEF = 1.36^9, AT = 365 * ED)
C |
Concentration of chemicals in soil(mg/kg) |
EF |
Exposure frequency (day/year) |
ED |
Exposure duration (years) |
PEF |
Particle emision factor meaning resuspended particles(m^3/kg) |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical intake rate by inhalation of soil particles I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
# Estimated dose for the estimation of carcinogenic effects due to the # inhalation of soil particles that contains 45 mg/Kg of As in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) INH(C= 45, AT = 365*70) # For non-carcinogenic effects: INH(C= 45)# Estimated dose for the estimation of carcinogenic effects due to the # inhalation of soil particles that contains 45 mg/Kg of As in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) INH(C= 45, AT = 365*70) # For non-carcinogenic effects: INH(C= 45)
A function to help assessing the distribution that best fit a data vector
plot_fit_dist(x, dist)plot_fit_dist(x, dist)
x |
A numeric vector of length at least one containing only finite values (values must be >= 0) |
dist |
Character vector indicating the distribution to be ploted:"norm", "lnorm", "geom", "exp", "pois", "cauchy", "logis", "weibull" |
Returns: Empirical and theoretical density plots, Empirical and theoretical CDFs, Q-Q plot, P-P plot
F. Barrio-Parra
plotdist from Library (fitdstrplus)
set.seed(123) a <- rnorm(n = 100, mean = 10, sd = 1) plot_fit_dist(a, "norm")set.seed(123) a <- rnorm(n = 100, mean = 10, sd = 1) plot_fit_dist(a, "norm")
Return a vector of n random numbers following a truncated distribution (dist) in agreement with a fitted parameters "Fited"
random_number_generator(n, Fited, dist, a, b)random_number_generator(n, Fited, dist, a, b)
n |
The number of desired generated numbers |
Fited |
A list contaning the parameters obtained by application of Fit_dist_parameter |
dist |
Character vector indicating the distribution to be applied:"norm", "lnorm", "geom", "exp", "pois", "cauchy", "logis", "weibull" |
a |
Truncation Lower limit |
b |
Truncation Upper limit |
A vector of n random numbers - Object class "numeric"
F. Barrio-Parra
Fit_dist_parameter
set.seed(123) a <- rnorm(n = 100, mean = 10, sd = 1) Fit <- Fit_dist_parameter(a) b <-random_number_generator(n = 10000, Fited = Fit, dist = "norm", a =8, b = 12) hist(a,xlim= c(7,14)) hist(b,xlim= c(7,14))set.seed(123) a <- rnorm(n = 100, mean = 10, sd = 1) Fit <- Fit_dist_parameter(a) b <-random_number_generator(n = 10000, Fited = Fit, dist = "norm", a =8, b = 12) hist(a,xlim= c(7,14)) hist(b,xlim= c(7,14))
Returns the Risk estimation (carcinogenic effects)
RISK(I, SF)RISK(I, SF)
I |
Intake Rate [mg/Kg*day] |
SF |
Slope Factor [(mg/Kg*day)^-1] (chemical specific) |
Risk [-] - Object class "numeric"
F. Barrio-Parra
# Assessing if there is carcinogenic risk for an adult receptor that drinks water with 1000 ug/L # of hexaclorobence (Oral Slope Factor (IRIS data base) = 1.6 [mg/Kg*day]^-1) in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) RISK (I = DWIR( CW=1), SF = 1.6)# Assessing if there is carcinogenic risk for an adult receptor that drinks water with 1000 ug/L # of hexaclorobence (Oral Slope Factor (IRIS data base) = 1.6 [mg/Kg*day]^-1) in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) RISK (I = DWIR( CW=1), SF = 1.6)
Returns the Risk for dermal exposure with chemicals (carcinogenic effects)
RISKdermal(AD, SF, GI)RISKdermal(AD, SF, GI)
AD |
Absorbed dose [mg/Kg*day] |
SF |
Slope Factor [(mg/Kg*day)^-1] (chemical specific) |
GI |
Gastrointestinal Absorption factor (chemical specific) [-] |
Risk [-] - Object class "numeric"
F. Barrio-Parra
AD
# Assess if there is carcinogenic risk for an dadult thorug dermal # contact exposed to a soil that contains 45 mg/Kg of As in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) SFAs = 1.5 # Dermal Absorption Factor ABSAs = 3e-02 # Gastrointestinal Absorption Factor GIAs = 1 I = AD (CS = 45,ABS = ABSAs) RISKdermal (AD = I, SF = SFAs, GI = GIAs)# Assess if there is carcinogenic risk for an dadult thorug dermal # contact exposed to a soil that contains 45 mg/Kg of As in a residencial # scenario (default EPA Maximum Reasonable Exposure parameters) SFAs = 1.5 # Dermal Absorption Factor ABSAs = 3e-02 # Gastrointestinal Absorption Factor GIAs = 1 I = AD (CS = 45,ABS = ABSAs) RISKdermal (AD = I, SF = SFAs, GI = GIAs)
Returns the risk (carcinogenic effects) for inhalation of vapors
RISKInhal(URi, I)RISKInhal(URi, I)
URi |
Inhalation Unit risk [(ug/m^3)^-1] |
I |
Inhalated dose (mg/m^3) |
Risk [-] - Object class "numeric"
# Assess if there is cancer risk for the exposure of an adult # (Reasonable Maximum Exposure) to a benzene air concentration of 2 mg/ m^3 RISKInhal ( I = AIR (CA = 2), URi = 7.8e-06)# Assess if there is cancer risk for the exposure of an adult # (Reasonable Maximum Exposure) to a benzene air concentration of 2 mg/ m^3 RISKInhal ( I = AIR (CA = 2), URi = 7.8e-06)
Auxiliar function (employed only for internal use)
sampler(n, a)sampler(n, a)
n |
Number of sampling iterations |
a |
data vector |
Resampled vector of length n - Object class "numeric"
F. Barrio-Parra
a <- rnorm (n = 20, mean = 0, sd = 1) b <- sampler (n = 100, a = a)a <- rnorm (n = 20, mean = 0, sd = 1) b <- sampler (n = 100, a = a)
Function that return if the p-value allows to accept H0 in a Kolmogorov Smirnov or Anderson Darling test
sig(n)sig(n)
n |
p-value |
Text string ("Significant"" / "Not Significant"") - Object class "character"
sig ( 0.001 ) sig ( 0.1 )sig ( 0.001 ) sig ( 0.1 )
Estimates the chemical Intake rate by accidental soil ingestion [mg/Kg*day]
SIR(CS = 1, IR = 100, FI = 1, EF = 350, ED = 24, BW = 80, AT = 365 * 70)SIR(CS = 1, IR = 100, FI = 1, EF = 350, ED = 24, BW = 80, AT = 365 * 70)
CS |
Chemical concentrtion in soil [mg/Kg] |
IR |
Soil Ingestion Rate [mg/Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical intake rate by soil ingestion I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
# Ingestion rate for a children weighing 20 Kg who ingest 200 mg # of soil every day, 250 days per year during 10 years. 95-UCL of # Arsenic in soil is 25 mg/Kg # Carcinogenic effects SIR ( CS = 25, BW = 20, IR = 200, ED = 10, EF = 250) # Systemic effects SIR ( CS = 25, BW = 20, IR = 200, ED = 10, EF = 250, AT = 365*10)# Ingestion rate for a children weighing 20 Kg who ingest 200 mg # of soil every day, 250 days per year during 10 years. 95-UCL of # Arsenic in soil is 25 mg/Kg # Carcinogenic effects SIR ( CS = 25, BW = 20, IR = 200, ED = 10, EF = 250) # Systemic effects SIR ( CS = 25, BW = 20, IR = 200, ED = 10, EF = 250, AT = 365*10)
Estimates the chemical Intake rate by accidental soil ingestion [mg/Kg*day]
SIRboot(n, CS, IR, FI, EF, ED, BW, AT)SIRboot(n, CS, IR, FI, EF, ED, BW, AT)
n |
Output vector length |
CS |
Chemical concentrtion in soil [mg/Kg] |
IR |
Soil Ingestion Rate [mg/Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Chemical intake rate by soil ingestion I [mg/Kg*day] - Object class "numeric"
# Carcinogenic effects c <- rnorm( n= 10, mean = 22, sd = 2 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) SIRboot (n = 1000, CS = c, BW = b, IR = 200, ED = 10, EF = 250)# Carcinogenic effects c <- rnorm( n= 10, mean = 22, sd = 2 ) b <- rnorm( n= 100, mean = 20, sd = 5 ) SIRboot (n = 1000, CS = c, BW = b, IR = 200, ED = 10, EF = 250)
Estimates the chemical Intake rate by ingestion of contaminated fruits and vegetables [mg/Kg*day]
VI(CF = 1, IR = 210, FI = 1, EF = 350, ED = 24, BW = 80, AT = 365 * 70)VI(CF = 1, IR = 210, FI = 1, EF = 350, ED = 24, BW = 80, AT = 365 * 70)
CF |
Chemical concentration in food [mg/Kg] |
IR |
Vegetables Ingestion Rate [g / Kg * Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight (kg) |
AT |
Averaging time [day] (For No carcinogenic effects AT = 365*ED) |
Chemical intake rate by vegetable ingestion I [mg/Kg*day] - Object class "numeric"
F. Barrio-Parra
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
# Assess the chemical intake by an adult that eats lettuce with a concentration of 2 mg/ Kg # in a maximum reasonable exposure scenario for non- carcinogenic effects VI (CF = 2, AT = 365*24)# Assess the chemical intake by an adult that eats lettuce with a concentration of 2 mg/ Kg # in a maximum reasonable exposure scenario for non- carcinogenic effects VI (CF = 2, AT = 365*24)
Estimates the chemical Intake rate by ingestion of contaminated fruits and vegetables [mg/Kg*day]
VIboot( n, CF, IR, FI, EF, ED, BW, AT)VIboot( n, CF, IR, FI, EF, ED, BW, AT)
n |
Output vector length |
CF |
Chemical concentrtion in food [mg/Kg] |
IR |
Vegetables Ingestion Rate [g / Kg * Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body Weight [Kg] |
AT |
Averaging time [day] (For No carcinogenic effects AT = 365*ED) |
A vector of Chemical intake rate by vegetable ingestion I [mg/Kg*day] - Object class "numeric"
# Assess the chemical intake by an adult that eats lettuce with a concentration of 2 mg/ Kg of a # chemical with non- carcinogenic effects in a maximum reasonable exposure scenario # Figure out 10 data of Chemical concentration following a normal distribution (mean = 2, sd= 2) # and 100 Body weight data that follow a normal distribution (mean = 70, sd = 15) c <- rnorm( n= 10, mean = 2, sd = 2 ) b <- rnorm( n= 100, mean = 70, sd = 5 ) VIboot (n = 1000, CF = c, BW = b, AT = 365*24)# Assess the chemical intake by an adult that eats lettuce with a concentration of 2 mg/ Kg of a # chemical with non- carcinogenic effects in a maximum reasonable exposure scenario # Figure out 10 data of Chemical concentration following a normal distribution (mean = 2, sd= 2) # and 100 Body weight data that follow a normal distribution (mean = 70, sd = 15) c <- rnorm( n= 10, mean = 2, sd = 2 ) b <- rnorm( n= 100, mean = 70, sd = 5 ) VIboot (n = 1000, CF = c, BW = b, AT = 365*24)