Air Pollution knowledge Assessments (APnA) City Program in Asia and Africa

Representative emissions and pollution data is a critical requirement for supporting clean air action plans for cities. The data can be used for both long-term policy assessments and short-term pollution alert systems via modeling at various scales. In a data sparse environment, several assumptions are made, and several data resources are accessed to construct a reliable emissions and pollution modeling framework to support public and policy dialogue. These assumptions include interpolation of observations from one zone to another, extrapolation of operational conditions from one country to another, and utilization all available source and emissions data, complemented with open satellite retrievals and global databases with information on population, topography, land use, urbanization level, road network, locations of commercial and other points of interest, to compile a city’s spatially and temporally representative dynamic emissions map. The urban airshed inventory is maintained at a spatial resolution of 0.01 degrees (~1km) and with monthly and hourly temporal modulation suitable for chemical transport modeling. Here, we will present examples from the Air Pollution knowledge Assessments (APnA) program implemented for 60 Indian cities and expansion of the program to Balkan, Central Asian, and African cities, while addressing data gaps using emerging technology and big data feeds, combined with traditional meteorological and chemical transport modeling (WRF-CAMx) systems. Where available validation of the model results against available monitoring data from reference-grade and sensor networks is also included in the study. All the methodologies and data resources are accessible @ https://www.urbanemissions.info