healthiar (version 0.2.1)

prepare_exposure: Prepare exposure data

Description

This function prepares tabular population exposure data compatible with the attribute() and compare() functions, based on gridded pollution concentration data and vector data representing geographic units. The function calculates an average concentration value in each geographic unit, weighted by the fraction of the population in each sub-unit.

Usage

prepare_exposure(poll_grid, geo_units, population, geo_id_macro)

Value

This function returns a list containing:

1) main (tibble) containing the main results as vectors;

• geo_id_macro (string column) containing the (higher-level) geographic IDs of the assessment

• exp_value (numeric column) containing the (population-weighted) mean exposure

• exp_type (string column) specifying the exposure type

2) detailed (list) containing detailed (and interim) results.

Arguments

poll_grid

SpatRaster of the pollution concentration data.

geo_units

sf of the geographic sub-units.

population

Numeric vector containing the total population number in each geographic sub-unit.

geo_id_macro

Numeric or string vector containing the higher-level IDs of the geographic units the sub-unit belong to and will be aggregated at.

Author

Arno Pauwels

Examples

# Goal: determine population-weighted mean PM2.5 exposure for several
# neighborhoods of Brussels (Belgium)

exdat_pwm_1 <- terra::rast(system.file("extdata", "exdat_pwm_1.tif", package = "healthiar"))
exdat_pwm_2 <- sf::st_read(
    system.file("extdata", "exdat_pwm_2.gpkg", package = "healthiar"),
    quiet = TRUE
)

pwm <- prepare_exposure(
  poll_grid = exdat_pwm_1, # Formal class SpatRaster
  geo_units = exdat_pwm_2, # sf of the geographic sub-units
  population = sf::st_drop_geometry(exdat_pwm_2$population), # population per geographic sub-unit
  geo_id_macro = sf::st_drop_geometry(exdat_pwm_2$region) # higher-level IDs to aggregate at
)

pwm$main # population-weighted mean exposures for the (higher-level) geographic units