基于过程的可解释机器学习方法预测的碳中和未来气候变化对中国臭氧污染的影响

IF 4.6 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geophysical Research Letters Pub Date : 2024-07-06 DOI:10.1029/2024GL109520
Huimin Li, Yang Yang, Hang Su, Hailong Wang, Pinya Wang, Hong Liao
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引用次数: 0

摘要

臭氧(O3)污染是中国严重的空气质量问题,对人类健康和生态系统构成威胁。气候变化将直接改变臭氧的物理和化学过程,并间接改变臭氧前体物的自然排放,从而影响臭氧浓度。本研究采用基于过程的可解释极端梯度提升(XGBoost)模型,并结合多源数据,预测了 2030 年和 2060 年中国的近地表臭氧浓度。结果表明,与高排放情景(SSP5-8.5)相比,在碳中和情景(SSP1-1.9)下,预计 2060 年中国东部上空由气候驱动的臭氧浓度将下降 0.4 ppb 以上。在这一降幅中,80%归因于与气候变冷有关的臭氧物理和化学过程的变化,其余 20%归因于生物源异戊二烯排放量的减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Ozone Pollution in China Affected by Climate Change in a Carbon Neutral Future as Predicted by a Process-Based Interpretable Machine Learning Method

Ozone (O3) pollution is a severe air quality issue in China, posing a threat to human health and ecosystems. The climate change will affect O3 levels by directly changing physical and chemical processes of O3 and indirectly changing natural emissions of O3 precursors. In this study, near-surface O3 concentrations in China in 2030 and 2060 are predicted using the process-based interpretable Extreme Gradient Boosting (XGBoost) model integrated with multi-source data. The results show that the climate-driven O3 levels over eastern China are projected to decrease by more than 0.4 ppb in 2060 under the carbon neutral scenario (SSP1-1.9) compared with the high emission scenario (SSP5-8.5). Among this reduction, 80% is attributed to the changes in physical and chemical processes of O3 related to a cooler climate, while the remaining 20% is attributed to the reduced biogenic isoprene emissions.

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来源期刊
Geophysical Research Letters
Geophysical Research Letters 地学-地球科学综合
CiteScore
9.00
自引率
9.60%
发文量
1588
审稿时长
2.2 months
期刊介绍: Geophysical Research Letters (GRL) publishes high-impact, innovative, and timely research on major scientific advances in all the major geoscience disciplines. Papers are communications-length articles and should have broad and immediate implications in their discipline or across the geosciences. GRLmaintains the fastest turn-around of all high-impact publications in the geosciences and works closely with authors to ensure broad visibility of top papers.
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