Global-Health-Engineering/bcsa

The bcsa package provide datasets for source apportionment of light absorbing carbon (LAC) in Blantyre, Malawi. The package contains data on Absorption Angstrom Exponent experiments determination of local pollution sources. The package also contains data on spatial distribution and ambient concentrations of LAC concentrations. # bcsa The goal of `bcsa` is to provide datasets for source apportionment of light absorbing carbon (LAC) in Blantyre, Malawi. This package combines datasets collected as part of two projects. The first project is on determining Absorption Angstrom Exponent (AAE) values of local pollution sources in Blantyre, Malawi. AAE values can be used to differentiate the LAC from fossil fuel and biomass based sources. The second project is to determine the light absorbing carbon concentrations by mobile, personal and stationary monitoring in Blantyre. The package includes the following seven datasets: 1. `df_aae`: Data of experiments to determine AAE values 2. `df_mm`: Mobile monitoring data in eight settlements 3. `df_mm_road_type`: Mobile monitoring data classified by highways (main_road) and non-highways (non_main_roads) in eight settlements 4. `df_pm`: Personal monitoring data in four settlements 5. `df_pm_trips`: Data on times when open waste burning was observed during the personal monitoring 6. `df_sm`: Raw data from stationary monitoring in two settlements 7. `df_collocation`: Data when the two LAC monitors are placed and run next to each other to check data quality This study used the MA200 micro-aethalometer to measure the light absorbing carbon (LAC) concentrations. The MA200 measures the LAC concentrations in real-time at five different wavelengths, that allows for source apportionment. ## Installation You can install the development version of bcsa from GitHub with: ``` r # install.packages("devtools") devtools::install_github("Global-Health-Engineering/bcsa") ``` Alternatively, you can download the individual datasets as a CSV or XLSX file from the table below. | dataset | CSV | XLSX | |:----------------|:---------------------- …