Probing air pollution in the Taichung metropolitan area, Taiwan.Part 1: Comprehensive model evaluation and the spatial-temporal evolution of a PM2.5 pollution event

Chuang, Ming-Tung; Chou, Charles C.‐K.; Lin, Chuan-Yao; Lee, Ja-Huai; Lin, Wei-Che; Chen, Wei-Nai; Liu, Chian‐Yi; Chang, Chih-Chung

doi:10.1016/j.atmosres.2023.106713

Cited by 6 publications

(2 citation statements)

References 32 publications

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“…Ammonia emissions used are from the MIX emission inventory (Li et al., 2017), a widely‐used state of the art emission inventory for Asia (Ding et al., 2022; Hammer et al., 2020; P. Wang et al., 2020). Evaluation studies (Chuang et al., 2023; Wu et al., 2021), show simulated ammonium underestimation of 16%–30% on seasonal scales in East Asia. Sea salt and dust emissions (Ginoux et al., 2001) are parameterized in WRF‐Chem.…”

Section: Methodsmentioning

confidence: 99%

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Drivers of PM_2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Venkataraman,

Anand,

Maji

et al. 2024

JGR Atmospheres

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Emission sources influencing high particulate air pollution levels and related mortality in India have been studied earlier on country‐wide and sub‐national scales. Here, we use novel data sets of emissions (for 2019) and observations created under the Carbonaceous Aerosol Emissions, Source Apportionment, and Climate Impacts network in India (Venkataraman et al., 2020, https://doi.org/10.1175/bams‐d‐19‐0030.1) in WRF‐Chem simulations to evaluate drivers of high PM2.5 levels during episodes and in airsheds with different pollution levels. We identify airsheds in “extreme” (110–140 μg/m3), “severe” (80–110 μg/m3) and “significant” (40–80 μg/m3) exceedance of the Indian annual ambient air quality standard (National Ambient Air Quality Standards [NAAQS]) of 40 μg/m3 for PM2.5. We find that primary organic matter and anthropogenic mineral matter (largely coal fly‐ash) drive high PM2.5 levels, both annually and during high PM2.5 episodes. PM2.5 episodes are driven by organic aerosol in north India (Mohali) in wintertime but are additionally influenced by mineral matter and secondary inorganics in central (Bhopal), south India (Mysuru) and eastern India (Shyamnagar). Across airsheds in exceedance of the NAAQS and during high PM2.5 episodes, primary PM2.5 emissions arise largely from the residential sector (50%–75%). Formal sector emissions (industry, thermal power and transport; 40%–55%) drive airshed and episode scale PM2.5 exceedance in northern and eastern India. Agricultural residue burning emissions predominate (50%–75%) on episode scales, both in northern and central India, but not on annual scales. Interestingly, residential sector emissions strongly influence (60%–90%) airsheds in compliance with the NAAQS (annual mean PM2.5 < 40 μg/m3), implying the need for modern residential energy transitions for the reduction of ambient air pollution across India.

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Section: Methodsmentioning

confidence: 99%

“…Wang et al, 2020). Evaluation studies (Chuang et al, 2023;Wu et al, 2021), show simulated ammonium underestimation of 16%-30% on seasonal scales in East Asia. Sea salt and dust emissions (Ginoux et al, 2001) are parameterized in WRF-Chem.…”

Section: Emissionsmentioning

confidence: 99%

Drivers of PM_2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Venkataraman,

Anand,

Maji

et al. 2024

JGR Atmospheres

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Spatial-temporal evaluation of PM2.5 concentration for health risk reduction strategy development in a basin with different weather patterns

Chen

Chang

et al. 2023

Atmospheric Pollution Research

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Characteristics and impacts of fine particulates from the largest power plant plume in Taiwan

Chuang,

Chou,

Lee

et al. 2024

Atmospheric Pollution Research

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Probing air pollution in the Taichung metropolitan area, Taiwan.Part 1: Comprehensive model evaluation and the spatial-temporal evolution of a PM2.5 pollution event

Cited by 6 publications

References 32 publications

Drivers of PM_2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Drivers of PM_2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Spatial-temporal evaluation of PM2.5 concentration for health risk reduction strategy development in a basin with different weather patterns

Characteristics and impacts of fine particulates from the largest power plant plume in Taiwan

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Probing air pollution in the Taichung metropolitan area, Taiwan.Part 1: Comprehensive model evaluation and the spatial-temporal evolution of a PM2.5 pollution event

Cited by 6 publications

References 32 publications

Drivers of PM2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Drivers of PM2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Spatial-temporal evaluation of PM2.5 concentration for health risk reduction strategy development in a basin with different weather patterns

Characteristics and impacts of fine particulates from the largest power plant plume in Taiwan

Contact Info

Product

Resources

About

Drivers of PM_2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network

Drivers of PM_2.5 Episodes and Exceedance in India: A Synthesis From the COALESCE Network