气候变化领域集成服务门户(CCPortal): Modeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamics

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DOI	10.5194/acp-20-16055-2020
	Modeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamics
	Ge X.; Schaap M.; Kranenburg R.; Segers A.; Jan Reinds G.; Kros H.; De Vries W.
发表日期	2020
ISSN	1680-7316
起始页码	16055
结束页码	16087
卷号	20 期号:24
英文摘要	Ammonia emissions into the atmosphere have increased substantially in Europe since 1960, primarily due to the intensification of agriculture, as illustrated by enhanced livestock and the use of fertilizers. These associated emissions of reactive nitrogen, particulate matter, and acid deposition have contributed to negative societal impacts on human health and terrestrial ecosystems. Due to the limited availability of reliable measurements, emission inventories are used to assess large-scale ammonia emissions from agriculture by creating gridded annual emission maps and emission time profiles globally and regionally. The modeled emissions are subsequently utilized in chemistry transport models to obtain ammonia concentrations and depositions. However, current emission inventories usually have relatively low spatial resolutions and coarse categorizations that do not distinguish between fertilization on various crops, grazing, animal housing, and manure storage in its spatial allocation. Furthermore, in assessing the seasonal variation of ammonia emissions, they do not consider local climatology and agricultural management, which limits the capability to reproduce observed spatial and seasonal variations in the ammonia concentrations. This paper describes a novel ammonia emission model that quantifies agricultural emissions with improved spatial details and temporal dynamics in 2010 in Germany and Benelux. The spatial allocation was achieved by embedding the agricultural emission model Integrated Nitrogen Tool across Europe for Greenhouse gases and Ammonia Targeted to Operational Responses (INTEGRATOR) into the air pollution inventory Monitoring Atmospheric Composition and Climate-III (MACC-III), thus accounting for differentiation in ammonia emissions from manure and fertilizer application, grazing, animal houses and manure storage systems. The more detailed temporal distribution came from the integration of TIMELINES, which provided predictions of the timing of key agricultural operations, including the day of fertilization across Europe. The emission maps and time profiles were imported into LOTOS-EUROS to obtain surface concentrations and total columns for validation. The comparison of surface concentration between modeled output and in situ measurements illustrated that the updated model had been improved significantly with respect to the temporal variation of ammonia emission, and its performance was more stable and robust. The comparison of total columns between remote sensing observations and model simulations showed that some spatial characteristics were smoothened. Also, there was an overestimation in southern Germany and underestimation in northern Germany. The results suggested that updating ammonia emission fractions and accounting for manure transport are the direction for further improvement, and detailed land use is needed to increase the spatial resolution of spatial allocation in ammonia emission modeling. © 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
英文关键词	agricultural emission; agricultural intensification; ammonia; atmospheric chemistry; concentration (composition); livestock farming; seasonal variation; spatiotemporal analysis; Germany
语种	英语
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/168860
作者单位	Environmental Systems Analysis Group, Wageningen University, Wageningen, the Netherlands, Netherlands; Department of Climate, Air and Sustainability, TNO, Utrecht, the Netherlands, Netherlands; Wageningen Environmental Research, Wageningen, the Netherlands, Netherlands
推荐引用方式 GB/T 7714	Ge X.,Schaap M.,Kranenburg R.,et al. Modeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamics[J],2020,20(24).
APA	Ge X..,Schaap M..,Kranenburg R..,Segers A..,Jan Reinds G..,...&De Vries W..(2020).Modeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamics.Atmospheric Chemistry and Physics,20(24).
MLA	Ge X.,et al."Modeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamics".Atmospheric Chemistry and Physics 20.24(2020).