基于IASI的京津冀及周边NH<sub>3</sub>分布特征及影响因素分析

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Abstract Monitoring and obtaining observation data of atmospheric anomia is of great significance for further reducing fine particles pollution. The study uses satellite remotely sensed Infrared Atmospheric Sounding Interferometer (IASI) data to conduct research on the accounting method of atmospheric ammonia emission intensity and total ammonia in the Beijing-Tianjin-Hebei and surrounding areas, providing support for the remote sensing monitoring application of atmospheric ammonia and ammonia reduction. Spatial interpolation was performed on spatially discontinuous data to calculate the annual average emission intensity (YNH₃), seasonal average emission intensity (QNH₃), and monthly average emission intensity (MNH₃) of atmospheric ammonia, and to estimate the total amount of atmospheric ammonia (TNH₃). By doing so, the spatial distribution characteristics and temporal variation patterns of atmospheric ammonia in the study area were analyzed, and finally, the influencing factors of atmospheric ammonia emissions were further examined. The results showed that from 2014 to 2022, the daily average emission intensity of atmospheric ammonia in the study area was 7.99kg/km². The central part of the region was a high value area for YNH₃, and the five cities with low column concentrations and low increasing rates were mainly distributed in northern Hebei and southern Henan. The eight cities with low column concentrations but high increasing rates were distributed in southwestern Henan, central Hebei, and Jiaodong Peninsula. The nineteen cities with high column concentrations but low increasing rates and sixteen cities with high column concentrations and high increasing rates were distributed in the central region and the surrounding of the Bohai Sea. Over the past 9 years, both YNH₃ and TNH₃ have shown an increasing trend, with YNH₃ in the study area growing from 5.89kg/km² to 9.20kg/km², with a compound annual growth rate of 5.73%; TNH₃ increased from 1169kt to 1825kt. In terms of temporal distribution, QNH₃ exhibited periodic changes, with summer being the peak season for QNH₃ and July being the peak month for MNH₃. TNH₃ had a high correlation with arable land and population, and their spatial distributions were highly consistent with each other, indicating that farming and population are important influencing factors of ammonia emissions in the study area. Random Forest analysis showed that agricultural and living sources were the most significant reduction factors of ammonia emission. This study demonstrated that remote sensing monitoring of atmospheric ammonia can offer data support for air quality monitoring operations.

Key words： Atmospheric ammonia IASI spatio-temporal characteristics influencing factors

Received: 18 June 2024

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X511

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	SONG Xiao-ke
	JIANG Lei
	LU Hai-feng
	SHEN Xiu-e
	WANG Xin-hui
	SUN Shuang
	LI Lei
	LI Jin-xiang

Cite this article:

SONG Xiao-ke,JIANG Lei,LU Hai-feng等. Spatio-temporal distribution and influencing factors of atmospheric ammonia in Beijing-Tianjin-Hebei and its surrounding areas based on IASI observation data[J]. CHINA ENVIRONMENTAL SCIENCECE, 2025, 45(1): 30-39.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2025/V45/I1/30

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