Emission and influences of non-road mobile sources on air quality in China, 2000–2019

氮氧化物 空气质量指数 环境科学 空气污染 大气科学 污染 排放清单 气象学 中国 化学 地理 燃烧 考古 有机化学 地质学 生物 生态学
作者
Chaoyu Wen,Jianlei Lang,Ying Zhou,Xiaohan Fan,Zejun Bian,Dongsheng Chen,Jingjing Tian,Peiruo Wang
出处
期刊:Environmental Pollution [Elsevier]
卷期号:324: 121404-121404 被引量:11
标识
DOI:10.1016/j.envpol.2023.121404
摘要

Non-road mobile sources (NRMS) are potential important contributors to air pollution in China. However, their extreme impact on air quality had been seldom studied. In this study, the emission inventory of NRMS in mainland China during 2000–2019 was established. Then, the validated WRF-CAMx-PSAT model was applied to simulate the contribution to the atmospheric PM2.5, NO3−, and NOx. Results showed that emissions increased rapidly since 2000 and reached a peak in 2014–2015, with an annual average change rate (AACR) of 8.7–10.0%; after then, the emissions were relatively stable (AACR, −1.4–1.5%). The modeling results indicated that NRMS has become a crucial contributor to the air quality in China: from 2000 to 2019, the contribution to PM2.5, NOx, and NO3− significantly increased by 131.1%, 43.9%, and 61.7%; and for NOx, the contribution ratio in 2019 reached 24.1%. Further analysis showed that the reduction (−0.8% and −0.5%) of the NOx and NO3− contribution ratios was much lower than that (−4.8%) of NOx emissions from 2015 to 2019, implying that the control of NRMS lagged behind the national overall pollution control level. The contribution ratio of agricultural machinery (AM) and construction machinery (CM) to PM2.5, NOx, NO3− in 2019 was 2.6%, 11.3%, 8.3% and 2.5%, 12.6%, 6.8%, respectively. Although the contribution was much lower, the contribution ratio of civil aircraft had the fastest growth (202–447%). Moreover, an interesting phenomenon was that AM and CM had opposite contribution sensitivity characteristics for air pollutants: CM had a higher Contribution Sensitivity Index (CSI) for primary pollutants (e.g., NOx), ∼1.1 times that of AM; while AM had a higher CSI for secondary pollutants (e.g., NO3−), ∼1.5 times that of CM. This work can provide a deeper understanding for the environmental impact of NRMS emissions and for the control strategy formulation of NRMS.
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