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基于TROPOMI的淮河流域大气NO2干沉降估算

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基于Sentinel-5P卫星TROPOMI数据,利用随机森林方法反演2018~2020年淮河流域地面NO2浓度,采用推算法获得淮河流域2018~2020年NO2干沉降通量,并通过划分不同集水区(水域、农田、城区和植被覆盖区)估算大气NO2干沉降对淮河流域水体氮素的贡献。结果显示,卫星反演地面NO2浓度与地面站点实测资料一致性较高,相关系数(R)为 0。94,平均绝对误差(MAE)为2。7,均方根误差(RSME)为4。1。淮河流域地面NO2浓度和NO2 干沉降通量均有明显的季节变化,春夏秋冬4个季节地面NO2平均浓度分别为13。7,12。2,17。6,23。1μg/m3;NO2平均干沉降通量分别为1。25,1。13,1。61,2。13kg N/(hm2·a)。淮河流域地面NO2浓度和干沉降通量均表现为南北部高,东西部低。农田区域NO2干沉降对流域水体氮素的贡献最大,占比83。47%。2019年淮河流域大气NO2干沉降总量为1。34×105t,对水体氮素的贡献为1。36×104tN;2020年大气NO2干沉降总量为1。25×105t,对水体氮素的贡献为1。18×104tN。
Estimation of atmospheric NO2dry deposition in Huaihe River Basin based on TROPOMI
Based on Sentinel-5P TROPOMI,we retrieved the surface NO2 concentration in the Huaihe River Basin(HRB)during 2018~2020 by using random forest(RF),and the estimation method was used to obtain the dry deposition flux of NO2.We then divided the HRB into four areas(water,agriculture,urban,and vegetation)to estimate the nitrogen contribution of atmospheric NO2 dry deposition to the HRB water.The results show that the model simulation result is in good agreement with the measured data,achieving a correlation coefficient(R)of 0.94,a mean absolute error(MAE)of 2.7,and a root mean square error(RSME)of 4.1 in surface NO2 estimation.There is a clear seasonal variation in the NO2 dry deposition flux and surface NO2 concentration in the HRB.The average surface NO2 concentration in spring,summer,autumn,and winter was 13.7,12.2,17.6,23.1μg/m3;the average dry deposition flux of NO2 was 1.25,1.13,1.61,2.13kg N/(hm2·a).The surface NO2 concentration and dry deposition flux in HRB are higher in the north and south,and lower in the east and west.NO2 dry deposition in agriculture was a major contributor with 83.47%.In 2019,the overall atmospheric NO2 dry deposition in HRB was 1.34× 105t,and its contribution to water nitrogen was 1.36× 104t N;In 2020,the overall atmospheric NO2 dry deposition was 1.25× 105t,and the contribution of NO2 to water nitrogen is 1.18× 104t N.

NO2 dry depositionTROPOMIrandom forestHuaihe River Basinnitrogen contribution

刘佳瑜、王钰、丘仲锋、赵冬至、田野、武燕、张渊智

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南京信息工程大学海洋科学学院,江苏南京 210044

自然资源部空间海洋遥感与应用重点实验室,北京 100081

NO2干沉降 TROPOMI 随机森林模型 淮河流域 氮素贡献

国家自然科学基金

41976165

2024

中国环境科学
中国环境科学学会

中国环境科学

CSTPCDCHSSCD北大核心
影响因子:2.174
ISSN:1000-6923
年,卷(期):2024.44(4)
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