Development and uncertainty analysis of a high-resolution NH3 emissions inventory and its implications with precipitation over the Pearl River Delta region, China

被引:68
|
作者
Zheng, J. Y. [1 ,2 ]
Yin, S. S. [1 ,2 ]
Kang, D. W. [3 ]
Che, W. W. [1 ,2 ]
Zhong, L. J. [4 ]
机构
[1] S China Univ Technol, Sch Environm Sci & Engn, Guangzhou 510006, Guangdong, Peoples R China
[2] Pearl River Delta Atmospher Environm Res Joint La, Guangzhou 510006, Guangdong, Peoples R China
[3] Comp Sci Corp, Res Triangle Pk, NC 27709 USA
[4] Guangdong Prov Environm Monitoring Ctr, Guangzhou 510045, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
AGRICULTURAL AMMONIA EMISSIONS; EASTERN UNITED-STATES; SPATIAL-DISTRIBUTION; ATMOSPHERIC TRANSPORT; SOUTHERN CHINA; HONG-KONG; AIR; DEPOSITION; POLLUTION; AEROSOLS;
D O I
10.5194/acp-12-7041-2012
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Detailed NH3 emission inventories are important to understand various atmospheric processes, air quality modeling studies, air pollution management, and related environmental and ecological issues. A high-resolution NH3 emission inventory was developed based on state-of-the-science techniques, up-to-date information, and advanced expert knowledge for the Pearl River Delta region, China. To provide model-ready emissions input, this NH3 emissions inventory was spatially allocated to 3 km x 3 km grid cells using source-based spatial surrogates with geographical information system (GIS) technology. For NH3 emissions, 9 source categories and 45 subcategories were identified in this region, and detailed spatial and temporal characteristics were investigated. Results show that livestock is by far the most important NH3 emission source by contributing about 61.7% of the total NH3 emissions in this region, followed by nitrogen fertilizer applications (similar to 23.7%) and non-agricultural sources (similar to 14.6%). Uncertainty analysis reveals that the uncertainties associated with different sources vary from source to source and the magnitude of the uncertainty associated with a specific source mainly depends on the degree of accuracy of the emission factors and activity data as well as the technique used to perform the estimate. Further studies should give priority to the hog, broiler, goose subsectors of the livestock source and N fertilizer application source in order to reduce uncertainties of ammonia emission estimates in this region. The validity of the NH3 emissions inventory is justified by the trend analysis of local precipitation compositions, such as pH values, the Ca2++NH4+/SO42- + NO3- ratios, and NH4+ concentrations which are directly or indirectly related to NH3 emissions.
引用
收藏
页码:7041 / 7058
页数:18
相关论文
共 17 条
  • [1] An AIS-based high-resolution ship emission inventory and its uncertainty in Pearl River Delta region, China
    Li, Cheng
    Yuan, Zibing
    Ou, Jiamin
    Fan, Xiaoli
    Ye, Siqi
    Xiao, Teng
    Shi, Yuqi
    Huang, Zhijiong
    Ng, Simon K. W.
    Zhong, Zhuangmin
    Zheng, Junyu
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 573 : 1 - 10
  • [2] High resolution of black carbon and organic carbon emissions in the Pearl River Delta region, China
    Zheng, Junyu
    He, Min
    Shen, Xingling
    Yin, Shasha
    Yuan, Zibing
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2012, 438 : 189 - 200
  • [3] High-resolution measurement of ammonia emissions from fertilization of vegetable and rice crops in the Pearl River Delta Region, China
    Gong, Weiwei
    Zhang, Yisheng
    Huang, Xiaofeng
    Luan, Shengji
    [J]. ATMOSPHERIC ENVIRONMENT, 2013, 65 : 1 - 10
  • [4] High-resolution sampling and analysis of ambient particulate matter in the Pearl River Delta region of southern China: source apportionment and health risk implications
    Zhou, Shengzhen
    Davy, Perry K.
    Huang, Minjuan
    Duan, Jingbo
    Wang, Xuemei
    Fan, Qi
    Chang, Ming
    Liu, Yiming
    Chen, Weihua
    Xie, Shanju
    Ancelet, Travis
    Trompetter, William J.
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2018, 18 (03) : 2049 - 2064
  • [5] Use of high-resolution precipitation observations in quantifying the effect of urban extent on precipitation characteristics for different climate conditions over the Pearl River Delta, China
    Wang, Dashan
    Wang, Dagang
    Qi, Xiangyan
    Liu, Lin
    Wang, Xianwei
    [J]. ATMOSPHERIC SCIENCE LETTERS, 2018, 19 (06):
  • [6] A highly resolved temporal and spatial air pollutant emission inventory for the Pearl River Delta region, China and its uncertainty assessment
    Zheng, Junyu
    Zhang, Lijun
    Che, Wenwei
    Zheng, Zhuoyun
    Yin, Shasha
    [J]. ATMOSPHERIC ENVIRONMENT, 2009, 43 (32) : 5112 - 5122
  • [7] Spatiotemporal variability of biogenic terpenoid emissions in Pearl River Delta, China, with high-resolution land-cover and meteorological data
    Wang, Xuemei
    Situ, Shuping
    Guenther, Alex
    Chen, Fei
    Wu, Zhiyong
    Xia, Beicheng
    Wang, Tijian
    [J]. TELLUS SERIES B-CHEMICAL AND PHYSICAL METEOROLOGY, 2011, 63 (02): : 241 - 254
  • [8] Development of a high-resolution emission inventory of agricultural machinery with a novel methodology: A case study for Yangtze River Delta region
    Zhang, Jie
    Liu, Lu
    Zhao, Yu
    Li, Huipeng
    Lian, Yijia
    Zhang, Zongyi
    Huang, Cheng
    Du, Xin
    [J]. ENVIRONMENTAL POLLUTION, 2020, 266
  • [9] High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies
    Wen, Li
    Kang, Ning
    Wang, Lijie
    Wei, Qiannan
    Zhang, Hedi
    Shen, Jianling
    Yue, Dingli
    Zhai, Yuhong
    Lin, Weiwei
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2024, 58 (25) : 10920 - 10931
  • [10] High-resolution modeling of gaseous methylamines over a polluted region in China: source-dependent emissions and implications of spatial variations
    Mao, Jingbo
    Yu, Fangqun
    Zhang, Yan
    An, Jingyu
    Wang, Lin
    Zheng, Jun
    Yao, Lei
    Luo, Gan
    Ma, Weichun
    Yu, Qi
    Huang, Cheng
    Li, Li
    Chen, Limin
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2018, 18 (11) : 7933 - 7950