Spatiotemporal Characteristics of Atmospheric NO2 Concentration in Southeast Asia using Satellite Observations

Abstract

Southeast Asia has long experienced severe air pollution, posing significant risks to public health. Contrary to global trends of declining emissions, the region’s rapid industrialization may exacerbate air quality problems. This study investigates the spatiotemporal characteristics of atmospheric nitrogen dioxide (NO2) concentrations across Southeast Asia using satellite-based observations. Two analytical approaches are employed: an analysis of tropospheric NO2 concentration fields and a flux-divergence-based assessment of NO2 emissions. First, regional and local patterns of NO2 concentrations are examined using tropospheric column density data from the Ozone Monitoring Instrument (OMI) for the period 2005–2022. The results indicate that elevated NO2 concentrations are primarily concentrated in major urban centers, likely associated with vehicular emissions and industrial activities. Notably, enhanced NO2 levels are also observed in several forested regions. These anomalies are hypothesized to be associated with biomass burning, a relationship further supported through integration with MODIS burned area products. Detailed analyses are then conducted for 12 hotspot regions using time series decomposition to isolate long-term trends, seasonal variability, and residual components. To account for the potential influence of the COVID‑19 pandemic, the analysis period for each hotspot is divided into pre‑ and post‑pandemic phases, revealing distinct concentration trends for individual regions. Second, NO₂ emission patterns are investigated using flux divergence calculations derived from TROPOspheric Monitoring Instrument (TROPOMI) observations in combination with wind fields from the ECMWF ERA5 reanalysis. Regional-scale emission maps are first produced for Southeast Asia, followed by focused analyses for three selected areas: the Bangkok Metropolitan Region, the Northern Vietnam Industrial Corridor, and the Singapore–Kuala Lumpur Region. Independent auxiliary datasets are used to reference the accuracy of the inferred emission patterns. The results demonstrate that the flux divergence approach effectively identifies major emission sources, especially in complex areas like Bangkok's urban region.