Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong‐Hong Kong‐Macau Greater Bay Area of China Using a Regional‐To‐Local Coupling Model. (11th March 2022)
- Record Type:
- Journal Article
- Title:
- Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong‐Hong Kong‐Macau Greater Bay Area of China Using a Regional‐To‐Local Coupling Model. (11th March 2022)
- Main Title:
- Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong‐Hong Kong‐Macau Greater Bay Area of China Using a Regional‐To‐Local Coupling Model
- Authors:
- Zhang, Xuguo
Stocker, Jenny
Johnson, Kate
Fung, Yik Him
Yao, Teng
Hood, Christina
Carruthers, David
Fung, Jimmy C. H. - Abstract:
- Abstract: Ultrahigh‐resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM2.5 ) concentrations over the past decade has triggered ozone (O3 ) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh‐resolution perspective. We propose a regional‐to‐local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NOx ) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NOx, PM2.5, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO2 and PM2.5 but increased O3 concentrations in urban areas. Guangzhou is located in a VOC‐limited O3 formation regime, and traffic is a key factor in controlling NOx and O3 . The reduced industrial VOC scenario leads to reduced O3 concentrations throughout the mitigation domain. The maximum decrease in median hourly NO2 is >11 μg/m³, and the maximum increase in the median daily maximum 8‐hr rolling O3 is >10 μg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O3 increase reduces to <7 μg/m³. The daily averaged PM2.5 decreases by <2 μg/m³ for the reduced traffic scenario and varies little forAbstract: Ultrahigh‐resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM2.5 ) concentrations over the past decade has triggered ozone (O3 ) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh‐resolution perspective. We propose a regional‐to‐local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NOx ) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NOx, PM2.5, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO2 and PM2.5 but increased O3 concentrations in urban areas. Guangzhou is located in a VOC‐limited O3 formation regime, and traffic is a key factor in controlling NOx and O3 . The reduced industrial VOC scenario leads to reduced O3 concentrations throughout the mitigation domain. The maximum decrease in median hourly NO2 is >11 μg/m³, and the maximum increase in the median daily maximum 8‐hr rolling O3 is >10 μg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O3 increase reduces to <7 μg/m³. The daily averaged PM2.5 decreases by <2 μg/m³ for the reduced traffic scenario and varies little for the reduced industrial VOC scenario. An O3 episode analysis of the dual‐control scenario leads to O3 decreases of up to 15 μg/m³ (8‐hr metric) and 25 μg/m³ (1‐hr metric) in rural areas. Plain Language Summary: Spatial concentration maps of air pollutants showing variations over small distances are useful for assessing human health in metropolitan regions. The combined control of fine particulate matter and ozone is not yet fully understood at a high resolution. This study implements a regional‐to‐local urban modeling system for quantitatively assessing opportunities for pollution reduction. Typical air pollutants are explored, focusing on emissions from the traffic and industrial sectors. We find that implementing combined controls in both sectors leads to considerable reductions in emissions. The scenario analysis reveals the most substantial contributors to ozone pollution in various locations. The contributions of air pollution from both sectors are assessed. The research findings will improve the awareness of air quality management strategies and benefit multilevel governments by facilitating joint control of regional air pollution issues. Key Points: A regional‐to‐local coupled model is constructed to explore the likely impact of emissions reductions and pollution mitigation pathways The O3 formation regime in Guangzhou is VOC‐limited and the traffic sector is of paramount importance for controlling NOx and O3 Investigation of frequent summer O3 episodes emphasizes the value of more stringent VOC controls, particularly for the industrial sector … (more)
- Is Part Of:
- GeoHealth. Volume 6:Number 3(2022)
- Journal:
- GeoHealth
- Issue:
- Volume 6:Number 3(2022)
- Issue Display:
- Volume 6, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 6
- Issue:
- 3
- Issue Sort Value:
- 2022-0006-0003-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-03-11
- Subjects:
- street‐scale -- air dispersion model -- CMAQ–ADMS‐urban -- sensitivity analysis -- ozone -- Greater Bay Area
Environmental health -- Periodicals
Electronic journals
Periodicals
616.98 - Journal URLs:
- http://agupubs.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)2471-1403/issues/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2021GH000506 ↗
- Languages:
- English
- ISSNs:
- 2471-1403
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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