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基于多源数据的像元尺度东北三省夜间PM_(2.5)估算

Estimation of Nighttime PM_(2.5) in the Three Northeast Provinces at Pixel Scale Based on Multi-source Data
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摘要 气候变化与森林植被影响着PM_(2.5)质量浓度的分布,而PM_(2.5)作为空气的重要污染物也可直接或间接影响森林植被生长。目前,基于光学气溶胶厚度(AOD)反演日间PM2.5的技术已经较为成熟,夜间PM_(2.5)作为日间PM_(2.5)的补充,对于PM_(2.5)的全天监测具有重要意义。基于辐射传输理论,以夜间灯光亮度、增强型植被指数和7个气象因素(2 m露点温度、2 m温度、U风速分量、V风速分量、大气表面压力、蒸发量、降雨量)作为输入变量,夜间PM_(2.5)质量浓度作为响应变量,建立机器学习估算模型,以期为东北三省夜间PM_(2.5)质量浓度监测提供参考。结果表明,基于集成树构建的模型具有较高的估算精度,其拟合优度(R2)为0.68,平均绝对误差(MAE)为7.05μg/m^(3),均方根误差(RMSE)为11.62μg/m^(3)。此外,通过分析东北三省各监测站PM_(2.5)估算值与真实值的误差,发现模型具有一定的时空敏感性。通过及时准确地掌控夜间PM_(2.5)质量浓度的分布状况,可以为森林植被保护工作的开展提供参考。 Climate change and forest vegetation affect the distribution of PM_(2.5) concentrations,and PM_(2.5) as an important air pollutant can also affect forest vegetation growth directly or indirectly.Currently,the technique of inverting daytime PM_(2.5) based on optical aerosol thickness(AOD)data is relatively mature,and as a complement to daytime PM_(2.5),nighttime PM_(2.5) is of great significance for the all-day PM_(2.5) monitoring.Based on the radiation transmission theory,the machine learning estimation model of nighttime PM_(2.5) concentration in the three northeastern provinces was established with nighttime light brightness,enhanced vegetation index and seven meteorological factors(2 m dewpoint temperature,2 m temperature,u component of wind speed,v component of wind speed,atmospheric surface pressure,evaporation,precipitation)as input variables,and nighttime PM_(2.5) concentration as response variable,aiming to provide a reference for monitoring nighttime PM_(2.5) concentration in the three northeastern provinces.The results show that the model constructed based on the integration tree has high estimation accuracy,with a goodness of fit(R2)of 0.68,a mean absolute error(MAE)of 7.05μg/m^(3),and a root mean square error(RMSE)of 11.62μg/m^(3).In addition,the model is found to have certain spatial and temporal sensitivity by analyzing the errors between the estimated and true PM_(2.5) values at each monitoring station in the three northeastern provinces.It can provide a reference for the forest vegetation conservation work by timely and accurately controlling the distribution of nighttime PM_(2.5) concentration.
作者 李海洋 叶俊 LI Haiyang;YE Jun(School of Mining Engineering,Heilongjiang University of Science and Technology,Harbin 150022,China)
出处 《森林工程》 北大核心 2024年第4期11-18,共8页 Forest Engineering
基金 黑龙江科技大学引进高层次人才科研启动基金项目(7021000009020403)。
关键词 夜间PM_(2.5)质量浓度 机器学习 辐射传输 东北三省 森林植被保护 Nighttime PM_(2.5) concentration machine learning radiation transmission the three northeastern provinces forest vegetation conservation
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