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夏季北京市城区氨排放可能被严重低估。

Summertime Urban Ammonia Emissions May Be Substantially Underestimated in Beijing, China.

机构信息

Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.

Department of Ecology and Environment of Shanxi Province, Taiyuan 030024, China.

出版信息

Environ Sci Technol. 2023 Sep 5;57(35):13124-13135. doi: 10.1021/acs.est.3c05266. Epub 2023 Aug 24.

DOI:10.1021/acs.est.3c05266
PMID:37616592
Abstract

Ammonia (NH) is critical to the nitrogen cycle and PM formation, yet a great deal of uncertainty exists in its urban emission quantifications. Model-underestimated NH concentrations have been reported for cities, yet few studies have provided an explanation. Here, we explore reasons for severe WRF-Chem model underestimations of NH concentrations in Beijing in August 2018, including simulated gas-particle partitioning, meteorology, regional transport, and emissions, using spatially refined (3 km resolution) NH emission estimates in the agricultural sector for Beijing-Tianjin-Hebei and in the traffic sector for Beijing. We find that simulated NH concentrations are significantly lower than ground-based and satellite observations during August in Beijing, while wintertime underestimations are much more moderate. Further analyses and sensitivity experiments show that such discrepancies cannot be attributed to factors other than biases in NH emissions. Using site measurements as constraints, we estimate that both agricultural and non-agricultural NH emission totals in Beijing shall increase by ∼5 times to match the observations. Future research should be performed to allocate underestimations to urban fertilizer, power, traffic, or residential sources. Dense and regular urban NH observations are necessary to constrain and validate bottom-up inventories and NH simulation.

摘要

氨(NH)对氮循环和 PM 形成至关重要,但城市排放量化存在很大的不确定性。据报道,城市的模型低估了 NH 浓度,但很少有研究对此提供解释。在这里,我们利用京津冀地区农业部门和北京市交通部门精细化(3 公里分辨率)的 NH 排放估算,探讨了 2018 年 8 月北京 WRF-Chem 模型严重低估 NH 浓度的原因,包括模拟的气粒分配、气象条件、区域传输和排放情况。结果表明,在 8 月北京,模拟的 NH 浓度明显低于地面观测和卫星观测,而冬季的低估程度要温和得多。进一步的分析和敏感性实验表明,这些差异不能归因于 NH 排放以外的因素。利用站点测量值作为约束条件,我们估计北京的农业和非农业 NH 排放总量需要增加约 5 倍,才能与观测结果相匹配。未来的研究应该针对城市肥料、电力、交通或住宅来源的排放进行分配,以减少低估。密集和定期的城市 NH 观测对于约束和验证自上而下的清单和 NH 模拟是必要的。

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