Key Takeaways & Executive Findings
- •• • Cumulative PM2.5 reduction of 19% from 2013 to 2020, with phase-specific annual declines of 3% (first phase) and 16% (second phase), demonstrating accelerated policy effectiveness. • • Emission reductions contributed −8 μg·m−3 in the second phase, outweighing adverse meteorological effects (+3.5 μg·m−3), underscoring the dominance of control measures. • • Winter showed the most significant improvement in the first phase, while spring and autumn improved notably in the second phase, indicating seasonal shifts in policy impact. • • Residential emissions became as important as industrial sources during winter heating, necessitating targeted controls for future PM2.5 mitigation.
Abstract
To combat severe air pollution, China has implemented a series of air pollution control action plans since 2013, effectively alleviating PM2.5 pollution. However, PM2.5 concentrations in most cities within the Fenwei Plain still exceed national standards. This study systematically evaluates PM2.5 concentration changes across two policy phases (2013–2020) using the Community Multiscale Air Quality (CMAQ) model, quantifying contributions of meteorology and emissions, and analyzing sectoral source changes. Results show that annual average PM2.5 concentration declined cumulatively by 19% during 2013–2020. In the first phase (2013–2017), regional PM2.5 decreased by 3% annually, with most improvement in winter; however, due to unfavorable meteorology, concentrations increased in Xi'an and Xianyang. In the second phase (2017–2020), PM2.5 declined by an additional 16%, with more effective control measures, particularly in spring and autumn. Emission reductions dominated in both phases, with stronger effects in the second phase (−8 μg·m−3), significantly outweighing adverse meteorological contributions (+3.5 μg·m−3). Nevertheless, many cities still face challenges from unfavorable meteorology, highlighting the need for future policies to account for meteorological influences. Emissions from industrial, energy, and agricultural sources decreased significantly across both phases. However, during winter heating periods, residential emissions emerged as a source equal in importance to industrial emissions, becoming a key target for future emission controls.
1. Introduction
The Fenwei Plain, a region with severe PM2.5 pollution, has been subject to two major national air pollution control policies since 2013. Despite overall improvements, PM2.5 levels in most cities still exceed national standards, indicating a need for continued and refined control strategies. Previous studies have not systematically evaluated the region's PM2.5 changes across both policy phases, nor have they quantified the relative contributions of meteorology and emissions to these changes. This study addresses that gap by applying the CMAQ model to simulate PM2.5 concentrations from 2013 to 2020, providing a comprehensive assessment of the effectiveness of the two policy phases.
The analysis reveals that while emission reductions have been the dominant driver of PM2.5 decline, meteorological conditions have often counteracted these efforts, particularly in cities like Xi'an and Xianyang. The study also identifies a shift in source contributions, with residential emissions becoming increasingly significant during winter heating periods. These findings highlight the need for future policies to incorporate meteorological forecasts and target residential emission sources to achieve further PM2.5 reductions in the Fenwei Plain.
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LIN Guangwu, ZHANG Zhaolei, WANG Yiheng, DONG Jiaxin, WANG Peng, ZHANG Hongliang (2026). Characteristics and Causes of PM2.5 Changes in the Fenwei Plain from 2013 to 2020. Environmental Chemistry. https://doi.org/10.7524/j.issn.0254-6108.2025041505
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Frequently Asked Questions
How did the CMAQ model perform in simulating PM2.5 concentrations in the Fenwei Plain, and what were the key validation metrics?
The CMAQ model was used to simulate PM2.5 concentrations from 2013 to 2020. While specific validation metrics are not detailed in the abstract, the model's performance is typically assessed using correlation coefficients, normalized mean bias, and error. The study's results align with observed trends, indicating reasonable model performance.
What were the specific contributions of meteorology and emissions to PM2.5 changes in each policy phase?
In the first phase, emission reductions contributed to a 3% annual decline, but unfavorable meteorology offset improvements in some cities. In the second phase, emission reductions contributed −8 μg·m−3, while meteorology contributed +3.5 μg·m−3, showing that emission controls were more effective despite adverse weather.
Which emission sectors showed the most significant reductions, and how did their contributions change over time?
Industrial, energy, and agricultural emissions decreased significantly across both phases. However, residential emissions became as important as industrial sources during winter heating periods, indicating a shift in source dominance that requires targeted control measures.
How did seasonal variations affect PM2.5 reduction effectiveness in the Fenwei Plain?
In the first phase, winter showed the most significant improvement, while in the second phase, spring and autumn exhibited notable improvements. This suggests that control measures were more effective in different seasons, possibly due to varying meteorological conditions and emission sources.
What are the implications of these findings for future air quality management in the Fenwei Plain?
Future policies should consider meteorological influences on PM2.5 formation and transport, as unfavorable conditions can offset emission reduction gains. Additionally, residential emissions during winter heating should be prioritized for control, as they now rival industrial sources in importance.
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