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Spatiotemporal Evolution of Anthropogenic Emissions and Their Impact on Air Pollution in Guangdong Province from 2006 to 2020

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Listed:
  • Jingjie Li

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Keyu Zhu

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Cheng Chen

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Zhijiong Huang

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Yinyan Huang

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Qinge Sha

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Manni Zhu

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Haoqi Chen

    (College of Environment and Climate, Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China)

  • Junyu Zheng

    (Sustainable Energy and Environmental Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511458, China)

Abstract

Air quality in Guangdong Province has improved in recent years, but progress varies across different provincial sub-regions, particularly between Pearl River Delta (PRD) and non-PRD (NPRD) regions. To unveil possible causes of this, this study established a high-resolution gridded emission inventory for Guangdong (2006–2020) by integrating multi-year Point of Interest (POI) data and road network information. The spatiotemporal evolutions of anthropogenic sulfur dioxide (SO 2 ), nitrous oxide (NO X ), and particulate matter (PM 10 and PM 2.5 ) emissions were analyzed, with a focus on their impacts on PM 2.5 pollution using the CMAQ model. Spatial shifts in emission sources were quantified using spatial statistical methods, including the average nearest neighbor index (ANNI), kernel density analysis (KDA), standard deviational ellipse (SDE), and mean center (MC). From 2006 to 2020, emissions decreased significantly for SO 2 (88%), NO X (26%), PM 10 (64%), and PM 2.5 (68%). Emission hotspots shifted toward NPRD regions, driven by stricter environmental policies and industrial restructuring, lowering PRD-to-NPRD emission ratios for SO 2 (from 1.25 to 0.87), NO X (1.67–1.51), and PM 10 (0.94–0.89). The spatial evolution of emissions varied across sources. For example, the emission share of industrial sources in the PRD declined despite an increase in enterprises, whereas vehicle emissions remained concentrated in the PRD. CMAQ modeling results revealed that overall emission reductions from 2012 to 2020 lowered provincial PM 2.5 concentrations by 9.2–10.5 μg/m 3 . Accounting for spatial evolution further enhanced PM 2.5 reductions in the PRD by 1.4 μg/m 3 (April) and 1.1 μg/m 3 (October). Conversely, PM 2.5 improvements in NPRD regions weakened, with reductions declining by 0.2–3.2 μg/m 3 (April) and 0.1–1.4 μg/m 3 (October). These findings provide guidance for formulating region-specific strategies, aiming for more equitable air quality improvements across Guangdong.

Suggested Citation

  • Jingjie Li & Keyu Zhu & Cheng Chen & Zhijiong Huang & Yinyan Huang & Qinge Sha & Manni Zhu & Haoqi Chen & Junyu Zheng, 2025. "Spatiotemporal Evolution of Anthropogenic Emissions and Their Impact on Air Pollution in Guangdong Province from 2006 to 2020," Sustainability, MDPI, vol. 17(11), pages 1-23, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:4844-:d:1663981
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    References listed on IDEAS

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    1. Ran Wang & Hui Ci & Ting Zhang & Yuxin Tang & Jinyuan Wei & Hui Yang & Gefei Feng & Zhaojin Yan, 2023. "Spatial-Temporal Evolution Characteristics of Industrial Carbon Emissions in China’s Most Developed Provinces from 1998–2013: The Case of Guangdong," Energies, MDPI, vol. 16(5), pages 1-21, February.
    2. Zhou, Ya & Shan, Yuli & Liu, Guosheng & Guan, Dabo, 2018. "Emissions and low-carbon development in Guangdong-Hong Kong-Macao Greater Bay Area cities and their surroundings," Applied Energy, Elsevier, vol. 228(C), pages 1683-1692.
    3. Jiang Zhu & Xiang Li & Huiming Huang & Xiangdong Yin & Jiangchun Yao & Tao Liu & Jiexuan Wu & Zhangcheng Chen, 2023. "Spatiotemporal Evolution of Carbon Emissions According to Major Function-Oriented Zones: A Case Study of Guangdong Province, China," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    4. Liya Yang & Honghui Zhang & Xinqi Liao & Haiqi Wang & Yong Bian & Geng Liu & Weiling Luo, 2023. "The Relationship between Spatial Characteristics of Urban-Rural Settlements and Carbon Emissions in Guangdong Province," IJERPH, MDPI, vol. 20(3), pages 1-22, February.
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