An empirical model to estimate ammonia emission from cropland fertilization in China

文献类型： 外文期刊

第一作者： Wang, Chen

作者： Wang, Chen;Xu, Jianming;Gu, Baojing;Cheng, Kun;Sun, Jianfei;Cheng, Kun;Sun, Jianfei;Ren, Chenchen;Liu, Hongbin;Reis, Stefan;Reis, Stefan;Yin, Shasha

作者机构：

关键词： Ammonia; Regression model; Spatio-temporal; Management practices; High resolution

期刊名称：ENVIRONMENTAL POLLUTION （ 影响因子：8.071； 五年影响因子：8.35 ）

ISSN： 0269-7491

年卷期： 2021 年 288 卷

页码：

收录情况： SCI

摘要： Ammonia (NH3) volatilization is one of the main pathways of nitrogen loss from cropland, resulting not only in economic losses, but also environmental and human health impacts. The magnitude and timing of NH3 emissions from cropland fertilizer application highly depends on agricultural practices, climate and soil factors, which previous studies have typically only considered at coarse spatio-temporal resolution. In this paper, we describe a first highly detailed empirical regression model for ammonia (ERMA) emissions based on 1443 field observations across China. This model is applied at county level by integrating data with unprecedented high spatio-temporal resolution of agricultural practices and climate and soil factors. Results showed that total NH3 emissions from cropland fertilizer application amount to 4.3 Tg NH3 yr(-1) in 2017 with an overall NH3 emission factor of 12%. Agricultural production for vegetables, maize and rice are the three largest emitters. Compared to previous studies, more emission hotspots were found in South China and temporally, emission peaks are estimated to occur three months earlier in the year, while the total amount of emissions is estimated to be close to that calculated by previous studies. A second emission peak is identified in October, most likely related to the fertilization of the second crop in autumn. Incorporating these new findings on NH3 emission patterns will enable a better parametrization of models and hence improve the modelling of air quality and subsequent impacts on ecosystems through reactive N deposition.

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