Characteristics of particulate matter (PM10) and its relationship with meteorological factors during 2001–2012 in Beijing
Atmospheric pollution has become a significant challenge in Beijing metropolitan region, China. In this study, wavelet analysis and gray analysis were proposed to explore the temporal characteristics of particulate matter (PM10) and its relationships with meteorological factors during 2001–2012. The...
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Published in | Environmental pollution (1987) Vol. 192; pp. 266 - 274 |
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Format | Journal Article Conference Proceeding |
Language | English |
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01.09.2014
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Abstract | Atmospheric pollution has become a significant challenge in Beijing metropolitan region, China. In this study, wavelet analysis and gray analysis were proposed to explore the temporal characteristics of particulate matter (PM10) and its relationships with meteorological factors during 2001–2012. The analysis indicated that air quality had got better significantly over the last decade. It was clearly interannual, seasonal, and monthly variation of atmospheric pollution, which represented that the air quality was the worst in spring, and got better in summer, subsequently tended to be more serious in autumn and winter. Generally atmospheric pressure was the most important meteorological feature influencing on PM10, followed by relative humidity and wind speed. However, the dominant meteorological factors influencing the atmospheric pollution were different in the four seasons. The results suggest that urban design and effective measures based on the relationship between meteorological factors and PM10 would be effective for improving atmospheric pollution.
[Display omitted]
•Wavelet analysis was proposed to explore the temporal characteristics of PM10.•The relationship of PM10 with meteorological factors was studied using gray analysis.•The seasonal order of air quality is: summer > autumn > winter > spring.•Atmospheric pressure was the most important meteorological feature affecting PM10.•The results suggest the potential meteorological measures to control air pollution.
The study investigates the temporal variation of API and its relationship with meteorological factors to further explore the mechanism of air pollution in Beijing. |
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AbstractList | Atmospheric pollution has become a significant challenge in Beijing metropolitan region, China. In this study, wavelet analysis and gray analysis were proposed to explore the temporal characteristics of particulate matter (PM sub(10)) and its relationships with meteorological factors during 2001-2012. The analysis indicated that air quality had got better significantly over the last decade. It was clearly interannual, seasonal, and monthly variation of atmospheric pollution, which represented that the air quality was the worst in spring, and got better in summer, subsequently tended to be more serious in autumn and winter. Generally atmospheric pressure was the most important meteorological feature influencing on PM sub(10), followed by relative humidity and wind speed. However, the dominant meteorological factors influencing the atmospheric pollution were different in the four seasons. The results suggest that urban design and effective measures based on the relationship between meteorological factors and PM sub(10) would be effective for improving atmospheric pollution. Atmospheric pollution has become a significant challenge in Beijing metropolitan region, China. In this study, wavelet analysis and gray analysis were proposed to explore the temporal characteristics of particulate matter (PM10) and its relationships with meteorological factors during 2001-2012. The analysis indicated that air quality had got better significantly over the last decade. It was clearly interannual, seasonal, and monthly variation of atmospheric pollution, which represented that the air quality was the worst in spring, and got better in summer, subsequently tended to be more serious in autumn and winter. Generally atmospheric pressure was the most important meteorological feature influencing on PM10, followed by relative humidity and wind speed. However, the dominant meteorological factors influencing the atmospheric pollution were different in the four seasons. The results suggest that urban design and effective measures based on the relationship between meteorological factors and PM10 would be effective for improving atmospheric pollution. Atmospheric pollution has become a significant challenge in Beijing metropolitan region, China. In this study, wavelet analysis and gray analysis were proposed to explore the temporal characteristics of particulate matter (PM10) and its relationships with meteorological factors during 2001–2012. The analysis indicated that air quality had got better significantly over the last decade. It was clearly interannual, seasonal, and monthly variation of atmospheric pollution, which represented that the air quality was the worst in spring, and got better in summer, subsequently tended to be more serious in autumn and winter. Generally atmospheric pressure was the most important meteorological feature influencing on PM10, followed by relative humidity and wind speed. However, the dominant meteorological factors influencing the atmospheric pollution were different in the four seasons. The results suggest that urban design and effective measures based on the relationship between meteorological factors and PM10 would be effective for improving atmospheric pollution. [Display omitted] •Wavelet analysis was proposed to explore the temporal characteristics of PM10.•The relationship of PM10 with meteorological factors was studied using gray analysis.•The seasonal order of air quality is: summer > autumn > winter > spring.•Atmospheric pressure was the most important meteorological feature affecting PM10.•The results suggest the potential meteorological measures to control air pollution. The study investigates the temporal variation of API and its relationship with meteorological factors to further explore the mechanism of air pollution in Beijing. |
Author | Xu, Xinliang Qiao, Zhi Tian, Guangjin |
Author_xml | – sequence: 1 givenname: Guangjin orcidid: 0000-0003-3610-6627 surname: Tian fullname: Tian, Guangjin email: tianguangjin@bnu.edu.cn, 122333236@qq.com organization: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinwai Street, Beijing 100875, PR China – sequence: 2 givenname: Zhi surname: Qiao fullname: Qiao, Zhi organization: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinwai Street, Beijing 100875, PR China – sequence: 3 givenname: Xinliang surname: Xu fullname: Xu, Xinliang organization: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, No. A11, Datun Road, ChaoYang District, Beijing 100101, PR China |
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Keywords | Beijing Temporal characteristics PM10 Meteorological factors Atmospheric condition Megacity Air quality Urban area Coarse particle 2000-2010 Trend analysis Aerosols Air pollution Time-series analysis PM Concentration distribution |
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Snippet | Atmospheric pollution has become a significant challenge in Beijing metropolitan region, China. In this study, wavelet analysis and gray analysis were proposed... |
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SubjectTerms | Air Pollutants - analysis Air pollution Air Pollution - statistics & numerical data Air quality Applied sciences Atmospheric pollution Autumn Beijing China Environmental Monitoring - methods Exact sciences and technology Humans Meteorological Concepts Meteorological factors Meteorology Particulate emissions Particulate Matter - analysis PM10 Pollutants physicochemistry study: properties, effects, reactions, transport and distribution Pollution Pollution abatement Seasons Springs Temporal characteristics Urban planning Wind Winter |
Title | Characteristics of particulate matter (PM10) and its relationship with meteorological factors during 2001–2012 in Beijing |
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