AAAR 36th Annual Conference October 16 - October 20, 2017 Raleigh Convention Center Raleigh, North Carolina, USA
Abstract View
Viewing Satellite-Based PM2.5 Data through an Urban Lens
SARAH SERAJ, Sarah Chambliss, Joshua Apte, University of Texas at Austin
Abstract Number: 504 Working Group: Regional and Global Air Quality and Climate Modeling
Abstract Fine particulate matter (PM2.5) is associated with a range of adverse health effects and is a growing concern in cities worldwide. The scarcity of in situ monitors historically limited the tracking of global air quality trends, particularly in developing countries. Recently, high-resolution global maps of PM2.5 (0.01° × 0.01° grid) have been developed that combine satellite retrievals, geophysical models, and ground measurements from 1998-2015. Linking these remotely-sensed data with a map of urban areas to produce time-resolved PM2.5 concentration estimates for 4,231 major cities reveals that the global population-weighted average urban PM2.5 concentration has increased from 25 μg/m3 to 33 μg/m3 from 2000-2015. Of the 2.5 billion urban residents considered, 75% live in cities where PM2.5 concentrations have risen. While 1072 cities (25%) showed improvement in PM2.5, the majority of them are in high-income countries. Moreover, 3,665 of the 4,231 cities (87%) have average concentrations above the WHO guideline of 10 μg/m3, corresponding to 89% of the population in those cities. Trends in both absolute urban concentrations and intra-urban variability are most strongly influenced by the region of the world in which a city is located, and show a secondary association with economic variables. Cities in predominantly high-income regions show lower mean concentrations and lower intraurban variability, while GDP provides little predictive power for concentration in cities in middle- and low-income countries. Cities in Asia, with the exception of those in Southeast Asia and Japan, tend to have the highest concentrations regardless of income level. Remotely-sensed urban PM2.5 levels tend to agree more closely with ground-based monitors in high-income regions than low-income regions, which may be indicative of sub-1km scale heterogeneity in pollution from local sources in developing world cities.