New paper published in Atmospheric Research by Alifa et al.

Author: Paola Crippa

Key predictor variables for PM10.

The influence of meteorology and emissions on the spatio-temporal variability of PM10 in Malaysia


Equatorial Asia experiences frequent degraded air quality conditions, as a result of the complex interaction between the abundant air pollution sources and the local/regional meteorological patterns, which ultimately impact densely populated cities. Due to the scarcity of extensive observational datasets, both observational and modeling studies have been rather limited in their spatio-temporal extent and/or the certainty of their estimates. This study presents a country-wide, multi-decadal analysis of PM10 observations (i.e. particulate matter with aerodynamic diameter < 10 μm) from a network in Malaysia comprising 52 monitoring sites, which allows a novel and comprehensive assessment of the spatio-temporal variability of the country's air quality. Through statistical analyses and adoption of a parsimonious statistical model, we investigate the influence of urban and wildfire emissions, as well as of key meteorological variables on the observed PM10 patterns, at a variety of temporal scales. Our results suggest a strong influence of wildfire pollution from neighboring countries on the seasonal increase of both monthly average PM10 and number of days exceeding Malaysia's air quality standards. Regional differences in median PM10 during the non-fire season suggest the contribution of urban emissions in deteriorating air quality. The influence of meteorology varies by region and season, with an indication of wet deposition mechanisms reducing PM10 concentrations during the boreal winter and spring, while the summer and fall present temperatures and winds enhancing fire ignition conditions and long-range transport of transboundary pollution. The Klang Valley area remains the region with the most challenging pollution dynamics, showing both high persistent PM10 levels and yearly fire-season extreme pollution episodes. This study provides a baseline of model performance for future studies focusing on investigating regional scale transport and urban-level pollution, as well as on future projections of air quality conditions resulting from pollution mitigation strategies and climate change.