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Chemical composition and spatio-temporal variability of pollutant aerosols over the Himalayas using AERONET data
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Ao-nan ZHANG1, Zhi-wen DONG1, *, Fang-zhou LI2, Xiao-yu JIAO1, Cong JIANG3
China Environmental Science | 2026, 46(2) : 618 - 626
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China Environmental Science | 2026, 46(2): 618-626
• Air Pollution Control •
Chemical composition and spatio-temporal variability of pollutant aerosols over the Himalayas using AERONET data
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Ao-nan ZHANG1, Zhi-wen DONG1, *, Fang-zhou LI2, Xiao-yu JIAO1, Cong JIANG3
Affiliations
  • 1.School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430078, China
  • 2.College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
  • 3.Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Department of Ecohydrology and Biogeochemistry, Berlin 12587, Germany
Published: 2026-02-20
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This study established a five-component aerosol model (including Black Carbon (BC), Brown Carbon (BrC), Ammonium Sulfate (AS), Dust (DU), and Water (AW)) utilizing AERONET data, to perform inversion calculations on the aerosol components variability in the Himalayas and surrounding regions. The results indicated that, on a multi-year average, the proportion of the mass concentration of each component at various monitoring sites was similar, with AS, DU, AW, BrC, and AW accounting for 53.49%, 29.33%, 10.63%, 5.27%, and 1.28%, respectively. The aerosol mass concentration in the southern slope of the Himalayas (annual average of 390mg/m2) was significantly higher than that in the northern slope (annual average of 49mg/m2), primarily due to the substantial obstruction of South Asian pollutant aerosols by the high-altitude mountains during transboundary transport crossed the Himalayas (with only about 13% transported over the Himalayas). Generally, the aerosol mass concentration in the Himalayan region was highest in spring (multi-year average), while it saw significant reductions in summer, autumn, and winter. This variation was mainly attributed to the cumulative effect of atmospheric pollutant emissions prior to the South Asian Monsoon (SAM) and the substantial transport of dust aerosols from South Asian deserts, which were greatly diminished during the summer monsoon period due to heavy precipitation. Interannually, the average aerosol mass concentration from 2015 to 2024 (with southern slope average of 370.83mg/m2) was slightly lower than that during the earlier period from 2006 to 2015 (with southern slope average of 453.26mg/m2), reflecting an improvement in recent pollution levels in South Asia. However, the overall atmospheric pollution remained extremely serious. Given that the absorbing aerosols like black carbon and brown carbon can significantly accelerate the melting of glacial snow, the persistent high emissions of polluted aerosols in the South Asian region may continue affecting the accelerated glacial changes in the Himalayas in the future.

AERONET  /  aerosol component  /  Himalayas  /  pollutants emission  /  spatiotemporal variability
张傲楠, 董志文, 李芳洲, 焦晓瑜, 江聪. 基于AERONET的喜马拉雅地区污染物气溶胶组成及时空变化研究. 中国环境科学, 2026 , 46 (2) : 618 -626 .
Ao-nan ZHANG, Zhi-wen DONG, Fang-zhou LI, Xiao-yu JIAO, Cong JIANG. Chemical composition and spatio-temporal variability of pollutant aerosols over the Himalayas using AERONET data[J]. China Environmental Science, 2026 , 46 (2) : 618 -626 .
Year 2026 volume 46 Issue 2
94
14
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Article Info
  • Receive Date:2025-07-02
  • Online Date:2026-10-08
  • Published:2026-02-20
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  • Received:2025-07-02
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Affiliations
    1.School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430078, China
    2.College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
    3.Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Department of Ecohydrology and Biogeochemistry, Berlin 12587, Germany
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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