[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2873":3,"related-2873":65},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":9,"secondary_topics":21,"classification":22,"search_phrases":38,"slug":39,"view_count":40,"doi":41,"paper":42,"created_at":64},2873,"Dynamics of the spatiotemporal correlation between Aerosol Optical Depth satellite data and PM2.5 surface monitoring: An exploratory approach","https:\u002F\u002Fdoi.org\u002F10.35208\u002Fert.1740066","PM2.5 is a major air pollutant with diverse natural and anthropogenic sources, which significantly impacts human health and the environment. Remote sensing serves as a complementary resource for air-monitoring networks, providing valuable information on the spatiotemporal patterns of air pollutants at a global scale This study analyzes the feasibility of the use of MODIS MAIAC Aerosol Optical Depth (AOD) remote sensing for the estimation of surface PM2.5 and explores the dynamic relationship between AOD and PM2.5 in conjunction with regional factors such as heterogeneity of emissions sources, topography and meteorological variables in the Toluca Valley Metropolitan Area (TVMA), identified as the most polluted metropolitan area in Mexico. The five-year (2018-2023) temporal analysis during the dry seasons (Nov – May) revealed similar patterns between monthly average PM2.5 and AOD, with higher values observed during the Hot-Dry season. Spatially, 90% of the monitoring sites exhibited a moderate linear correlation (0.4 \u003C R \u003C 0.69) between AOD and PM2.5, while one site showed a weaker correlation (0.33); associated with a heterogeneity of local emission sources and the presence of coarse-mode aerosols. Regarding meteorological factors, higher Boundary Layer Height (BLH) and lower Relative Humidity (RH), during the Hot-Dry season corresponded to stronger correlations, as increased convection facilitates the vertical mixing of particles, in contrast, higher RH during the Cold-Dry impacts aerosol optical properties. This study highlights the complex influence of emission sources and meteorological conditions on the relationship between AOD and PM2.5, underscoring the importance of considering these factors when resorting to satellite data for air quality assessment.","PM2.5是一种主要空气污染物，来源涵盖多种自然和人为因素，对人类健康和环境具有显著影响。遥感作为空气监测网络的补充资源，可在全球尺度上提供空气污染物时空分布的有价值信息。本研究分析了利用MODIS MAIAC气溶胶光学厚度（AOD）遥感估算地表PM2.5的可行性，并结合排放源异质性、地形和气象变量等区域因素，探讨了托卢卡谷都市区（TVMA）——被认定为墨西哥污染最严重的大都市区——AOD与PM2.5之间的动态关系。五年（2018—2023年）旱季（11月至次年5月）的时间分析显示，月均PM2.5与AOD呈现相似的变化模式，且在热旱季观测到较高值。在空间上，90%的监测站点AOD与PM2.5之间呈中等线性相关（0.4 \u003C R \u003C 0.69），而一个站点相关性较弱（0.33），这与当地排放源异质性及粗模态气溶胶的存在有关。就气象因素而言，热旱季较高的边界层高度（BLH）和较低的相对湿度（RH）对应更强的相关性，因为对流增强促进了颗粒物的垂直混合；相反，冷旱季较高的相对湿度则影响气溶胶光学特性。本研究凸显了排放源和气象条件对AOD与PM2.5关系的复杂影响，强调了在利用卫星数据进行空气质量评估时考虑这些因素的重要性。",null,"Environmental Research and Technology","2026-09-16T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该论文研究墨西哥托卢卡谷地AOD卫星数据与地面PM2.5的时空相关性，属大气环境遥感领域，与三农、农业信息化、智慧农业、数字乡村等主题无关，不建议进入每日精选。",[19],{"name":10,"url":6},[12],[],{"status":23,"locked":14,"version":24,"method":25,"evidence":26},"needs_review","2026-10-22.2","rules",{"candidates":27,"agricultural_evidence":14,"reason":37},[28],{"code":29,"score":30,"supported":31,"title":32,"abstract":33,"tags":36},"I3",6,true,[],[34,35],"遥感","remote sensing",[],"农业相关性需要复核",[],"Dynamicsofthespatiotemporalcorrelationbe-2873",1,"10.35208\u002Fert.1740066",{"doi":41,"openalex_id":43,"authors":44,"venue":10,"cited_by_count":15,"oa_url":56,"card":57,"direction":61,"ingested_from":63},"W7213470726",[45,47,50,53],{"name":46,"orcid":9},"Angélica Neria-Hernández",{"name":48,"orcid":49},"Xanat Antonio Némiga","https:\u002F\u002Forcid.org\u002F0000-0002-8827-6575",{"name":51,"orcid":52},"Francisco Zepeda Mondragón","https:\u002F\u002Forcid.org\u002F0000-0003-3297-7580",{"name":54,"orcid":55},"Violeta Múgica-Álvarez","https:\u002F\u002Forcid.org\u002F0000-0003-2394-041X","https:\u002F\u002Fertjournal.org\u002Findex.php\u002Fpub\u002Farticle\u002Fdownload\u002F661\u002F445",{"tldr":58,"method":59,"finding":60,"direction":61,"opportunity":62},"分析墨西哥托卢卡谷MODIS AOD与地面PM2.5的时空相关性及气象影响。","用2018-2023旱季MODIS MAIAC AOD与地面PM2.5监测数据做","90%站点AOD与PM2.5中度相关，边界层高度和相对湿度显著影响相关性。","农业遥感与作物表型","可借鉴AOD-PM2.5动态关系思路，研究卫星气溶胶数据估算农业区颗粒物对作物影响。","openalex","2026-09-18T23:30:31.827838Z",{"total":15,"page":40,"page_size":40,"items":66},[]]