基于Catboost模型的广东省近地表NO2浓度估算[j]。

Q2 Environmental Science 环境科学 Pub Date : 2024-11-08 DOI:10.13227/j.hjkx.202312044
Hong-Fei Zhang, Ning Du, Li Wang, Xian-Yun Zhang, De-Cai Gong, Long Li
{"title":"基于Catboost模型的广东省近地表NO2浓度估算[j]。","authors":"Hong-Fei Zhang, Ning Du, Li Wang, Xian-Yun Zhang, De-Cai Gong, Long Li","doi":"10.13227/j.hjkx.202312044","DOIUrl":null,"url":null,"abstract":"<p><p>Nitrogen oxide (NO<i><sub>x</sub></i>) is an important air pollutant in the atmosphere, and nitrogen dioxide (NO<sub>2</sub>) is one of its main components. The monitoring and estimation of NO<sub>2</sub> concentration is very important for environmental protection and public health. The near-real-time nitrogen dioxide concentration data (NRTI NO<sub>2</sub>), ERA5 meteorological reanalysis data, and DEM data provided by Sentinel-5P atmospheric pollution monitoring satellite were used as estimation variables to estimate the near-surface NO<sub>2</sub> concentration in Guangdong Province based on the Catboost model. The results showed that: ① The Catboost model estimated the near-surface NO<sub>2</sub> concentration with the highest accuracy, with the coefficient of determination (<i>R</i><sup>2</sup>), root mean square error (RMSE), and mean absolute error (MAE) of the model fit reaching 0.91, 4.89 μg·m<sup>-3</sup>, and 3.45 μg·m<sup>-3</sup> and the cross-validated <i>R</i><sup>2</sup>, RMSE, and MAE reaching 0.90, 4.91 μg·m<sup>-3</sup>, and 3.43 μg·m<sup>-3</sup>, with good stability on the monthly and quarterly scales. ② The monthly average NO<sub>2</sub> concentration near the surface of Guangdong Province showed a U-shaped trend, with the highest value of 43.8 μg·m<sup>-3</sup> in January and the lowest value of 14.37 μg·m<sup>-3</sup> in July. The seasonal distribution of the near-surface NO<sub>2</sub> concentration was characterized by \"high during winter and low during summer and transitional during spring and autumn,\" and the NO<sub>2</sub> concentration in each season was in the following order: winter (27.53 μg·m<sup>-3</sup>) &gt; spring (20.77 μg·m<sup>-3</sup>) &gt; autumn (18.77 μg·m<sup>-3</sup>) &gt; summer (14.85 μg·m<sup>-3</sup>). ③ From a spatial distribution perspective, areas with high near-surface NO<sub>2</sub> values in Guangdong Province were mainly located in rapidly developing and densely populated areas, while areas with low values were mainly distributed in areas focusing on port economy, agriculture, and new energy sources.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"45 11","pages":"6276-6285"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Estimation of Near-surface NO<sub>2</sub> Concentration in Guangdong Province Based on Catboost Model].\",\"authors\":\"Hong-Fei Zhang, Ning Du, Li Wang, Xian-Yun Zhang, De-Cai Gong, Long Li\",\"doi\":\"10.13227/j.hjkx.202312044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Nitrogen oxide (NO<i><sub>x</sub></i>) is an important air pollutant in the atmosphere, and nitrogen dioxide (NO<sub>2</sub>) is one of its main components. The monitoring and estimation of NO<sub>2</sub> concentration is very important for environmental protection and public health. The near-real-time nitrogen dioxide concentration data (NRTI NO<sub>2</sub>), ERA5 meteorological reanalysis data, and DEM data provided by Sentinel-5P atmospheric pollution monitoring satellite were used as estimation variables to estimate the near-surface NO<sub>2</sub> concentration in Guangdong Province based on the Catboost model. The results showed that: ① The Catboost model estimated the near-surface NO<sub>2</sub> concentration with the highest accuracy, with the coefficient of determination (<i>R</i><sup>2</sup>), root mean square error (RMSE), and mean absolute error (MAE) of the model fit reaching 0.91, 4.89 μg·m<sup>-3</sup>, and 3.45 μg·m<sup>-3</sup> and the cross-validated <i>R</i><sup>2</sup>, RMSE, and MAE reaching 0.90, 4.91 μg·m<sup>-3</sup>, and 3.43 μg·m<sup>-3</sup>, with good stability on the monthly and quarterly scales. ② The monthly average NO<sub>2</sub> concentration near the surface of Guangdong Province showed a U-shaped trend, with the highest value of 43.8 μg·m<sup>-3</sup> in January and the lowest value of 14.37 μg·m<sup>-3</sup> in July. The seasonal distribution of the near-surface NO<sub>2</sub> concentration was characterized by \\\"high during winter and low during summer and transitional during spring and autumn,\\\" and the NO<sub>2</sub> concentration in each season was in the following order: winter (27.53 μg·m<sup>-3</sup>) &gt; spring (20.77 μg·m<sup>-3</sup>) &gt; autumn (18.77 μg·m<sup>-3</sup>) &gt; summer (14.85 μg·m<sup>-3</sup>). ③ From a spatial distribution perspective, areas with high near-surface NO<sub>2</sub> values in Guangdong Province were mainly located in rapidly developing and densely populated areas, while areas with low values were mainly distributed in areas focusing on port economy, agriculture, and new energy sources.</p>\",\"PeriodicalId\":35937,\"journal\":{\"name\":\"环境科学\",\"volume\":\"45 11\",\"pages\":\"6276-6285\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"环境科学\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.13227/j.hjkx.202312044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"环境科学","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.13227/j.hjkx.202312044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0

摘要

氮氧化物(NOx)是大气中重要的大气污染物,二氧化氮(NO2)是其主要成分之一。二氧化氮浓度的监测与评价对环境保护和公众健康具有重要意义。利用近实时二氧化氮浓度数据(NRTI NO2)、ERA5气象再分析数据和Sentinel-5P大气污染监测卫星DEM数据作为估算变量,基于Catboost模型估算广东省近地表NO2浓度。结果表明:①Catboost模型对近地表NO2浓度的预测精度最高,模型拟合的决定系数(R2)、均方根误差(RMSE)和平均绝对误差(MAE)分别达到0.91、4.89和3.45 μg·m-3,交叉验证的R2、RMSE和MAE分别达到0.90、4.91和3.43 μg·m-3,在月和季度尺度上具有较好的稳定性。②广东省近地表NO2月平均浓度呈u型变化趋势,1月最高为43.8 μg·m-3, 7月最低为14.37 μg·m-3。近地表NO2浓度的季节分布表现为“冬高夏低,春秋过渡性”,各季节NO2浓度的变化顺序为:冬季(27.53 μg·m-3);春季(20.77 μg·m-3) >;秋季(18.77 μg·m-3) >;夏季14.85 μg·m-3。③从空间分布上看,广东省近地表NO2值高的地区主要分布在经济快速发展和人口密集的地区,低值地区主要分布在以港口经济、农业和新能源为主的地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
[Estimation of Near-surface NO2 Concentration in Guangdong Province Based on Catboost Model].

Nitrogen oxide (NOx) is an important air pollutant in the atmosphere, and nitrogen dioxide (NO2) is one of its main components. The monitoring and estimation of NO2 concentration is very important for environmental protection and public health. The near-real-time nitrogen dioxide concentration data (NRTI NO2), ERA5 meteorological reanalysis data, and DEM data provided by Sentinel-5P atmospheric pollution monitoring satellite were used as estimation variables to estimate the near-surface NO2 concentration in Guangdong Province based on the Catboost model. The results showed that: ① The Catboost model estimated the near-surface NO2 concentration with the highest accuracy, with the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE) of the model fit reaching 0.91, 4.89 μg·m-3, and 3.45 μg·m-3 and the cross-validated R2, RMSE, and MAE reaching 0.90, 4.91 μg·m-3, and 3.43 μg·m-3, with good stability on the monthly and quarterly scales. ② The monthly average NO2 concentration near the surface of Guangdong Province showed a U-shaped trend, with the highest value of 43.8 μg·m-3 in January and the lowest value of 14.37 μg·m-3 in July. The seasonal distribution of the near-surface NO2 concentration was characterized by "high during winter and low during summer and transitional during spring and autumn," and the NO2 concentration in each season was in the following order: winter (27.53 μg·m-3) > spring (20.77 μg·m-3) > autumn (18.77 μg·m-3) > summer (14.85 μg·m-3). ③ From a spatial distribution perspective, areas with high near-surface NO2 values in Guangdong Province were mainly located in rapidly developing and densely populated areas, while areas with low values were mainly distributed in areas focusing on port economy, agriculture, and new energy sources.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
期刊介绍:
期刊最新文献
[Key Problems and Strategies for Greenhouse Gas Reduction in China's Wastewater Treatment Industry]. [Legacy Effects of Long-term Straw Returning on Straw Degradation and Microbial Communities of the Aftercrop]. [Mechanisms of Rhizosphere Microorganisms in Regulating Plant Root System Architecture in Acidic Soils]. [Meta-analysis of the Occurrence Characteristics and Influencing Factors of Microplastics in Agricultural Soil in China]. [Meta-analysis on the Effects of Organic Fertilizer Application on Global Greenhouse Gas Emissions from Agricultural Soils].
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1