Comparative analysis of methods for seasonal particulate organic nitrate estimation in urban areas

IF 8.5 1区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

npj Climate and Atmospheric Science Pub Date : 2025-01-17 DOI:10.1038/s41612-025-00904-5

Wenfei Zhu, Jialin Shi, Song Guo, Qinghong Wang, Jun Chen, Shengrong Lou, Min Hu

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引用次数: 0

Abstract

Accurately estimating particulate organic nitrate under high NO_x and oxidizing conditions is critical. This study compared the NO_x⁺ ratio, unconstrained Positive Matrix Factorization (PMF), and Multilinear Engine-2 (ME2) methods to estimate particulate organic nitrate in Shanghai across different seasons. The factors associated with organic nitrate, as identified through two receptor methods, exhibited consistent daily patterns in spring, summer, and autumn, although source contributions varied. The NO_x⁺ ratio method reported higher organic nitrate levels than the PMF and ME2 methods, likely due to the fixed R_ON/R_AN parameter. Seasonal R_ON/R_AN parameters were optimized based on precursor emissions in Shanghai, achieving values of 3.13 in spring, 2.25 in summer, and 1.88 in autumn. This optimization reduced discrepancies in organic nitrate using the NO_x⁺ ratio to 3.2–7.4%. The optimized parameters in this study support the rapid and accurate estimation of organic nitrate during different seasons in urban areas.

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来源期刊

npj Climate and Atmospheric Science Earth and Planetary Sciences-Atmospheric Science

CiteScore

8.80

自引率

3.30%

发文量

审稿时长

21 weeks

期刊介绍： npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols. The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.