南京地区一次臭氧污染过程的行业排放贡献研究
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摘要
采用WRF-CHEM模式对南京地区春季一次臭氧(O_3)污染过程进行了模拟及行业排放贡献分析.此次O_3污染过程发生在2015年5月22—26日,南京地区一直处于地面高压控制的晴好天气之下,并于25日达到O_3污染的峰值.模拟与观测的一致性指数IOA达到0.89,表征本次O_3污染过程的模拟与观测结果的一致性较高.通过5类排放源(工业源、农业源、居住源、交通源、生物源)的敏感性试验,探究各行业排放源中O_3前体物对近地面O_3浓度的相对贡献.结果表明工业源在白天为持续正贡献,且在午后16:00时达到峰值,而交通源、居住源和农业源的贡献随气温的升高在白天由负贡献转为正贡献,并在18:00时左右达到峰值.在夜晚,O_3则主要通过交通源排放的大量NO进行滴定消耗.在高O_3浓度(≥200μg·m~(-3))时,各人为排放源均为正贡献,工业源的贡献最大,达到50μg·m~(-3),在低O_3浓度(<200μg·m~(-3))时,交通源、居住源和农业源呈负贡献.生物源在人为排放源主导的南京城区O_3污染过程中的贡献几乎为零.考虑到O_3生成机制的复杂性,对于南京地区,减少工业源排放是控制O_3污染的关键.
Rapid growth of industrialization, transportation, and urbanization has caused increasing emissions of ozone(O_3) precursors, enhancing the O_3 formation and increasing the frequencies of O_3 pollution events. A widespread and severe O_3 pollution episode from 22 to 26 May 2015 under fine weather controlled by surface high pressure in Nanjing has been examined using the Weather Research and Forecasting model coupled to chemistry(WRF-CHEM) to evaluate contribution of various anthropogenic and biogenic sources to O_3 pollution. The consistency index IOA of simulation and observation reached 0.89, indicating well model simulation in the temporal variations and spatial distributions of near-surface O_3 concentrations. Using the factor separation approach, sensitivity studies have demonstrated the synergistic contribution of O_3 precursors to the near-surface O_3 in various industry emission sources in forming this episode. The results show that industrial sources contribute continuously and positively during the day, and peaked at 16:00 in the afternoon, playing the most important role in the O_3 formation for the severe O_3 pollution in Nanjing. While transportation sources, residential sources and agricultural sources changed from negative contribution to positive contribution with the increase of temperature during the day and peaked around 18:00. At night, ozone is consumed by titration primarily through a large amount of NO emitted from transportation sources. When the ozone concentration is higher than 200 μg·m~(-3), the contribution of each industry emission is positive, and the contribution of industrial source is the most, reaching 50 μg·m~(-3). When the ozone concentration is lower than 200 μg·m~(-3), sources of transportation, residential and agriculture contribute negatively. Besides, the contribution of biological sources to the O_3 pollution process in the urban area of Nanjing is almost zero.
Rapid growth of industrialization, transportation, and urbanization has caused increasing emissions of ozone(O_3) precursors, enhancing the O_3 formation and increasing the frequencies of O_3 pollution events. A widespread and severe O_3 pollution episode from 22 to 26 May 2015 under fine weather controlled by surface high pressure in Nanjing has been examined using the Weather Research and Forecasting model coupled to chemistry(WRF-CHEM) to evaluate contribution of various anthropogenic and biogenic sources to O_3 pollution. The consistency index IOA of simulation and observation reached 0.89, indicating well model simulation in the temporal variations and spatial distributions of near-surface O_3 concentrations. Using the factor separation approach, sensitivity studies have demonstrated the synergistic contribution of O_3 precursors to the near-surface O_3 in various industry emission sources in forming this episode. The results show that industrial sources contribute continuously and positively during the day, and peaked at 16:00 in the afternoon, playing the most important role in the O_3 formation for the severe O_3 pollution in Nanjing. While transportation sources, residential sources and agricultural sources changed from negative contribution to positive contribution with the increase of temperature during the day and peaked around 18:00. At night, ozone is consumed by titration primarily through a large amount of NO emitted from transportation sources. When the ozone concentration is higher than 200 μg·m~(-3), the contribution of each industry emission is positive, and the contribution of industrial source is the most, reaching 50 μg·m~(-3). When the ozone concentration is lower than 200 μg·m~(-3), sources of transportation, residential and agriculture contribute negatively. Besides, the contribution of biological sources to the O_3 pollution process in the urban area of Nanjing is almost zero.
引文
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杨笑笑, 汤莉莉, 张运江, 等. 2016. 南京夏季市区 VOCs 特征及 O3生成潜势的相关性分析[J]. 环境科学,37(2): 443-451
Yang X, Liu H, Man H, et al. 2015. Characterization of road freight transportation and its impact on the national emission inventory in China[J]. Atmospheric Chemistry and Physics, 15: 2105
Zhang Q, Streets D G, Carmichael G R, et al. 2009. Asian emissions in 2006 for the NASA INTEX-B mission [J]. Atmospheric Chemistry and Physics, 9: 5131-5153
Bei N, Lei W, Zavala M, et al. 2010. Ozone predictabilities due to meteorological uncertainties in the Mexico City basin using ensemble forecasts[J]. Atmospheric Chemistry & Physics Discussions, 10: 6295-6309
Brune W H. 2001. Introduction to Atmospheric Chemistry: Daniel J. Jacob; Princeton University Press, Princeton, NJ, 1999, 266pp., ISBN 0-691-00185-5 [J]. Atmospheric Environment, 35(9): 1715
Chen X, Zhang L W, Huang J J, et al. 2016. Long-term exposure to urban air pollution and lung cancer mortality: A 12-year cohort study in Northern China[J]. Science of the Total Environment, 571: 855-861
Chou M-D, Suarez M J. 1999. A solar radiation parameterization for atmospheric studies[J]. NASA Tech. Memo, 104606: 40
Geng F, Tie X, Xu J, et al. 2008. Characterizations of ozone, NOx, and VOCs measured in Shanghai, China[J]. Atmospheric Environment, 42: 6873-6883
Geng F, Zhang Q, Tie X, et al. 2009. Aircraft measurements of O3, NOx, CO, VOCs, and SO2 in the Yangtze River Delta region [J]. Atmospheric Environment, 43: 584-593
Guenther C. 2006. Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature) [J]. Atmospheric Chemistry and Physics, 6(11):3181-3210
Hong S Y, Noh Y, Dudhia J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. Monthly Weather Review, 134: 2318-2341
Horowitz L W, Walters S, Mauzerall D L, et al. 2003. A global simulation of tropospheric ozone and related tracers: Description and evaluation of MOZART, version 2[J]. Journal of Geophysical Research Atmospheres, 108: ACH 16-11
Hu X M, Doughty D C, Sanchez K J, et al. 2012. Ozone variability in the atmospheric boundary layer in Maryland and its implications for vertical transport model[J]. Atmospheric Environment, 46: 354-364
Kurokawa J, Ohara T, Morikawa T, et al. 2013. Emissions of air pollutants and greenhouse gases over Asian regions during 2000—2008: Regional Emission inventory in ASia (REAS) version 2 [J]. Atmospheric Chemistry and Physics, 13: 11019-11058
Li G, Bei N, Cao J, Et al. 2017. Widespread and persistent ozone pollution in eastern China during the non-winter season of 2015: observations and source attributions[J]. Atmos Chem Phys, 17: 2759-2774
Li L, Chen C H, Fu J S, et al. 2011. Air quality and emissions in the Yangtze River Delta, China[J]. Atmospheric Chemistry & Physics, 10: 1621-1639
Lin J T, Mcelroy M B. 2010. Impacts of boundary layer mixing on pollutant vertical profiles in the lower troposphere: Implications to satellite remote sensing[J]. Atmospheric Environment, 44: 1726-1739
Mlawer E J, Taubman S J, Brown P D, et al. 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated‐k model for the longwave[J]. Journal of Geophysical Research: Atmospheres, 102: 16663-16682
Oikawa P, Ge C, Wang J, et al. 2015. Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region [J]. Nature Communications, 6:8753
Pusede S E, Steiner A L, Cohen R C. 2015. Temperature and recent trends in the chemistry of continental surface ozone[J]. Chemical Reviews, 115: 650-659
Seinfeld J H, Pandis S N. 2006. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change[M]. New Jersey
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Wang S, Zhang Q, Streets D, et al. 2012a. Growth in NOx emissions from power plants in China: bottom-up estimates and satellite observations [J]. Atmospheric Chemistry and Physics, 12: 4429-4447
Wang Y, Zhang Q, He K, et al. 2013. Sulfate-nitrate-ammonium aerosols over China: response to 2000—2015 emission changes of sulfur dioxide, nitrogen oxides, and ammonia[J]. Atmospheric Chemistry and Physics, 13: 2635-2652
Wang Z H, Zeng H L, Wei Y M, et al. 2012b. Regional total factor energy efficiency: an empirical analysis of industrial sector in China[J]. Applied Energy, 97: 115-123
Weinhold B. 2008. Ozone nation: EPA standard panned by the people[J]. Environmental Health Perspectives, 116(7): A302
Xing J, Wang S, Chatani S, et al. 2011. Projections of air pollutant emissions and its impacts on regional air quality in China in 2020 [J]. Atmospheric Chemistry and Physics, 11: 3119-3136
Xue L K, Wang T, Gao J, et al. 2013. Ozone production in four major cities of China: sensitivity to ozone precursors and heterogeneous processes[J]. Atmospheric Chemistry & Physics, 13: 27243-27285
夏思佳, 刘倩, 赵秋月, 2018. 江苏省人为源VOCs排放清单及其对臭氧生成贡献[J]. 环境科学,(2): 592-599
杨笑笑, 汤莉莉, 张运江, 等. 2016. 南京夏季市区 VOCs 特征及 O3生成潜势的相关性分析[J]. 环境科学,37(2): 443-451
Yang X, Liu H, Man H, et al. 2015. Characterization of road freight transportation and its impact on the national emission inventory in China[J]. Atmospheric Chemistry and Physics, 15: 2105
Zhang Q, Streets D G, Carmichael G R, et al. 2009. Asian emissions in 2006 for the NASA INTEX-B mission [J]. Atmospheric Chemistry and Physics, 9: 5131-5153