Impact of Parameterization on the Estimation of Ammonia Emissions: A Case Study over the Yangtze River Delta

被引：0

作者：

Zhang Q. ^{[1
]}

Huang L. ^{[2
]}

Yin S.-J. ^{[2
]}

Wang Q. ^{[2
]}

Li H.-L. ^{[2
]}

Wang Y.-J. ^{[2
]}

Wang J. ^{[1
]}

Chen Y.-H. ^{[1
]}

Li L. ^{[2
]}

机构：

[1] College of Environmental Science and Engineering, Donghua University, Shanghai

[2] School of Environmental and Chemical Engineering, Shanghai University, Shanghai

来源：

Huanjing Kexue/Environmental Science | 2020年 / 41卷 / 03期

关键词：

Ammonia; Emission factor; Livestock feeding; Scenario analysis; Yangtze River Delta;

D O I：

10.13227/j.hjkx.201908131

中图分类号：

学科分类号：

摘要：

Atmospheric ammonia plays an important role in the formation of secondary inorganic composition of PM2.5, which has attracted a high level of attention from researchers both in China and abroad. Quantifying ammonia emissions is of great scientific significance regarding research on the formation of secondary aerosol, realizing better model performance, and control of ammonia emissions. Previous studies have shown that agricultural activities are the dominant source of atmospheric ammonia, of which livestock and poultry farming contribute the most. Existing studies on estimating ammonia emissions from livestock and poultry farming activities are mostly based on emission factors and activities. However, the choice of different emission activities could lead to large differences in estimated ammonia emissions. This study makes a variety of assumptions from the selection of activity levels (volume vs. inventory) and emission coefficients (monthly vs. annual average temperature), and establishes eight scenarios from which to calculate atmospheric ammonia emissions from livestock and poultry farming in the Yangtze River Delta region in 2017. The results show that selection of different activity levels has the greatest impact on estimated ammonia emissions; estimation based on volume is higher than that based on inventory by 27.6%-34.1%. Calculation based on a more detailed monthly average temperature is higher than using average annual temperature by 3 000 to 4 000 tons per year. In addition, the spatial and temporal distributions of the ammonia emissions are also closely related to the choice of volume vs. inventory and the choice of monthly average temperature vs. annual average temperature. When using inventory as the emission activity, Zhoushan (Zhejiang Province) has the lowest ammonia emissions, while Huainan (Anhui Province) has the highest. In contrast, when volume is used, Lishui (Zhejiang Province) has the lowest ammonia emissions and Nanjing (Jiangsu Province) has the highest. Emissions calculations based on monthly average temperature are supposed to be more representative than those based on annual average temperature, with the highest emissions from May to September and the lowest in the winter (December, January, and February). © 2020, Science Press. All right reserved.

引用

页码：1158 / 1166

页数：8

共 25 条

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