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Temporal-spatial distributions of road silt loadings and fugitive road dust emissions in Beijing from 2019 to 2020 被引量:1
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作者 Haibin Wang Lihui Han +6 位作者 Tingting Li Song Qu Yuncheng Zhao shoubin fan Tong Chen Haoran Cui Junfang Liu 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2023年第10期56-70,共15页
Road silt loading(sL)is an important parameter in the fugitive road dust(FRD)emissions.In this study,the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads(TRAKER)combined with the AP-42 method was fir... Road silt loading(sL)is an important parameter in the fugitive road dust(FRD)emissions.In this study,the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads(TRAKER)combined with the AP-42 method was firstly developed to quickly measure and estimate the sLs of paved roads in Beijing,China.The annual average sLs in Beijing was 0.59±0.31 g/m^(2)in 2020,and decreased by 22.4%compared with that in 2019.The seasonal variations of sLs followed the order of spring>winter>summer>autumn in the two years.The seasonal mean road sLs on the same type road in the four seasons presented a decline trend from^(2)019 to 2020,especially on the Expressway,decreasing 47.4%-72.7%.The road sLs on the different type roads in the same season followed the order of Major arterial∼Minor arterial∼Branch road>Express road,and Township road∼Country highway>Provincial highway∼National highway.The emission intensities of PM10 and PM_(2.5)from FRD in Beijing in 2020 were lower than those in 2019.The PM10 and PM_(2.5)emission intensities at the four planning areas in the two years all presented the order of the capital functional core area>the urban functional expansion area>the urban development new area>the ecological conservation and development area.The annual emissions of PM10 and PM_(2.5)from FRD in Beijing in 2020 were 74,886 ton and 18,118 ton,respectively,decreasing by∼33.3%compared with those in 2019. 展开更多
关键词 Road silt loading Temporal-spatial distribution Emission factor Emission inventory
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Exploring the heavy air pollution in Beijing in the fourth quarter of 2015: assessment of environmental benefits for red alerts 被引量:2
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作者 Teng NIE Lei NIE +6 位作者 Zhen ZHOU Zhanshan WANG Yifeng XUE Jiajia GAO Xiaoqing WU shoubin fan Linglong CHENG 《Frontiers of Earth Science》 SCIE CAS CSCD 2018年第2期361-372,共12页
In recent years, Beijing has experienced severeair pollution which has caused widespread public concern.Compared to the same period in 2014, the first threequarters of 2015 exhibited significantly improved airquality.... In recent years, Beijing has experienced severeair pollution which has caused widespread public concern.Compared to the same period in 2014, the first threequarters of 2015 exhibited significantly improved airquality. However, the air quality sharply declined in thefourth quarter of 2015, especially in November andDecember. During that time, Beijing issued the first redalert for severe air pollution in history. In total, 2 red alerts,3 orange alerts, 3 yellow alerts, and 3 blue alerts wereissued based on the adoption of relatively temporaryemergency control measures to mitigate air pollution. Thisstudy explored the reasons for these variations in airquality and assessed the effectiveness of emergency alertsin addressing severe air pollution. A synthetic analysis ofemission variations and meteorological conditions wasperformed to better understand these extreme air pollutionepisodes in the fourth quarter of 2015. The results showedthat compared to those in the same period in 2014, thedaily average emissions of air pollutants decreased in thefourth quarter of 2015. However, the emission levels ofprimary pollutants were still relatively high, which was themain intrinsic cause of haze episodes, and unfavorablemeteorological conditions represented important externalfactors. Emergency control measures for heavy airpollution were implemented during this red alert period,decreasing the emissions of primary air pollutants byapproximately 36% and the PMa.5 concentration by 11%-21%. 展开更多
关键词 heavy air pollution red alert emissions
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Air pollutant emissions from the asphalt industry in Beijing,China 被引量:1
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作者 Song Qu shoubin fan +7 位作者 Gang Wang Wanqing He Kangli Xu Lei Nie Yuncheng Zhao Qingchun Zhu Tingting Li Guohao Li 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2021年第11期57-65,共9页
Improving our understanding of air pollutant emissions fromthe asphalt industry is critical for the development and implementation of pollution control policies.In this study,the spatial distribution of potential maxi... Improving our understanding of air pollutant emissions fromthe asphalt industry is critical for the development and implementation of pollution control policies.In this study,the spatial distribution of potential maximum emissions of volatile organic compounds(VOCs)in the complete life cycle of asphaltmixtures,as well as the particulate matter(PM),asphalt fume,nonmethane hydrocarbons(NMHCs),VOCs,and benzoapyrene(BaP)emissions from typical processes(e.g.,asphalt and concrete mixing stations,asphalt heating boilers,and asphalt storage tanks)in asphalt mixing plants,were determined in Beijing in 2017.The results indicated that the potential maximum emissions of VOCs in the complete life cycle of asphalt mixtures were 18,001 ton,with a large contribution from the districts of Daxing,Changping,and Tongzhou.The total emissions of PM,asphalt fume,NMHC,VOCs,and BaP from asphalt mixing plants were 3.1,12.6,3.1,23.5,and 1.9×10^(−3)ton,respectively.The emissions of PMfromasphalt and concretemixing stations contributed themost to the total emissions.The asphalt storage tankwas the dominant emission source of VOCs,accounting for 96.1%of the total VOCs emissions in asphalt mixing plants,followed by asphalt heating boilers.The districts of Daxing,Changping,and Shunyi were the dominant regions for the emissions of PM,asphalt fume,NMHC,and BaP,while the districts of Shunyi,Tongzhou,and Changping contributed the most emissions of VOCs. 展开更多
关键词 Asphalt mixing plant Particulate matter Asphalt fume Nonmethane hydrocarbon Volatile organic compounds Benzoapyrene
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