Center for Industrial Ecology, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China.
Center for Industrial Ecology, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Baiyunshan Pharmaceutical Factory, Guangzhou Baiyunshan Pharmaceutical Holdings Co., Guangzhou 510515, China.
Sci Total Environ. 2020 Aug 20;731:138897. doi: 10.1016/j.scitotenv.2020.138897. Epub 2020 Apr 24.
Excessive anthropogenic activities have led to high-level ammonia loss and volatilization, which is regarded as a key factor in Chinese haze formation. In this study, a comprehensive analysis of ammonia emission estimations is accomplished at both temporal (1980-2016) and spatial (provincial) scales using a mass-balanced model, and emission projections through 2030 are also studied in different development scenarios. The results show that the ammonia emissions increased from 4.7 Tg N yr in 1980 to 11 Tg N yr in 2016, which is an approximately 2.4-fold increase. The cropland and livestock emissions are the largest contributors, as most reports show approximately 80% contributions; however, nonagriculture sources of fuel combustion, waste treatment and ammonia escape have grown rapidly in recent years, accounting for 14% in 2016. The spatial differences also reveal the complex heterogeneity in Chinese provinces. In addition, the emission intensities of major agriculture and non-agriculture sources are 0-80 kg N ha yr and over 100 kg N ha yr, respectively, indicating a higher degree of ammonia concentration from non-agriculture emissions, which should attract wide concern. In terms of scenario analysis, emissions would reach 12.8 Tg N yr in 2030 under the currently developed model and 7.3 Tg N yr under a series of reduction policies; the spatial analysis also shows that the North China Plain has a 2.1 Tg N yr reduction potential. The results of this study provide new insights into ammonia emission estimations and a better understanding of the environmental impacts of ammonia emitted from different sources.
人为活动的过度发展导致了高水平的氨损失和挥发，这被认为是中国雾霾形成的关键因素。在本研究中，利用质量平衡模型在时间（1980-2016 年）和空间（省级）尺度上对氨排放估算进行了综合分析，并在不同发展情景下研究了到 2030 年的排放预测。结果表明，氨排放量从 1980 年的 4.7Tg N yr 增加到 2016 年的 11Tg N yr，增长了约 2.4 倍。农田和畜牧业排放是最大的贡献者，因为大多数报告显示约 80%的贡献；然而，近年来，燃料燃烧、废物处理和氨逸出等非农业源的排放量增长迅速，占 2016 年的 14%。空间差异也揭示了中国各省的复杂异质性。此外，主要农业和非农业源的排放强度分别为 0-80kgNha yr 和超过 100kgNha yr，表明非农业排放的氨浓度更高，这应引起广泛关注。就情景分析而言，在目前的发展模式下，2030 年排放量将达到 12.8TgNyr，在一系列减排政策下，排放量将达到 7.3TgNyr；空间分析还表明，华北平原具有 2.1TgNyr 的减排潜力。本研究的结果为氨排放估算提供了新的见解，并更好地了解了不同来源排放的氨对环境的影响。
