MODIS气溶胶光学深度与克罗地亚PM10的关系

Sanja R. Grguric, J. Krizan, Goran Gašparac, O. Antonić, Z. Špirić, Rodelise E. Mamouri, A. Christodoulou, A. Nisantzi, A. Agapiou, K. Themistocleous, K. Fedra, C. Panayiotou, D. Hadjimitsis
{"title":"MODIS气溶胶光学深度与克罗地亚PM10的关系","authors":"Sanja R. Grguric, J. Krizan, Goran Gašparac, O. Antonić, Z. Špirić, Rodelise E. Mamouri, A. Christodoulou, A. Nisantzi, A. Agapiou, K. Themistocleous, K. Fedra, C. Panayiotou, D. Hadjimitsis","doi":"10.2478/s13533-012-0135-6","DOIUrl":null,"url":null,"abstract":"This study analyzes the relationship between Aerosol Optical Depth (AOD) obtained from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based PM10 mass concentration distribution over a period of 5 years (2008–2012), and investigates the applicability of satellite AOD data for ground PM10 mapping for the Croatian territory. Many studies have shown that satellite AOD data are correlated to ground-based PM mass concentration. However, the relationship between AOD and PM is not explicit and there are unknowns that cause uncertainties in this relationship.The relationship between MODIS AOD and ground-based PM10 has been studied on the basis of a large data set where daily averaged PM10 data from the 12 air quality stations across Croatia over the 5 year period are correlated with AODs retrieved from MODIS Terra and Aqua. A database was developed to associate coincident MODIS AOD (independent) and PM10 data (dependent variable). Additional tested independent variables (predictors, estimators) included season, cloud fraction, and meteorological parameters — including temperature, air pressure, relative humidity, wind speed, wind direction, as well as planetary boundary layer height — using meteorological data from WRF (Weather Research and Forecast) model.It has been found that 1) a univariate linear regression model fails at explaining the data variability well which suggests nonlinearity of the AOD-PM10 relationship, and 2) explanation of data variability can be improved with multivariate linear modeling and a neural network approach, using additional independent variables.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Relationship between MODIS based Aerosol Optical Depth and PM10 over Croatia\",\"authors\":\"Sanja R. Grguric, J. Krizan, Goran Gašparac, O. Antonić, Z. Špirić, Rodelise E. Mamouri, A. Christodoulou, A. Nisantzi, A. Agapiou, K. Themistocleous, K. Fedra, C. Panayiotou, D. Hadjimitsis\",\"doi\":\"10.2478/s13533-012-0135-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study analyzes the relationship between Aerosol Optical Depth (AOD) obtained from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based PM10 mass concentration distribution over a period of 5 years (2008–2012), and investigates the applicability of satellite AOD data for ground PM10 mapping for the Croatian territory. Many studies have shown that satellite AOD data are correlated to ground-based PM mass concentration. However, the relationship between AOD and PM is not explicit and there are unknowns that cause uncertainties in this relationship.The relationship between MODIS AOD and ground-based PM10 has been studied on the basis of a large data set where daily averaged PM10 data from the 12 air quality stations across Croatia over the 5 year period are correlated with AODs retrieved from MODIS Terra and Aqua. A database was developed to associate coincident MODIS AOD (independent) and PM10 data (dependent variable). Additional tested independent variables (predictors, estimators) included season, cloud fraction, and meteorological parameters — including temperature, air pressure, relative humidity, wind speed, wind direction, as well as planetary boundary layer height — using meteorological data from WRF (Weather Research and Forecast) model.It has been found that 1) a univariate linear regression model fails at explaining the data variability well which suggests nonlinearity of the AOD-PM10 relationship, and 2) explanation of data variability can be improved with multivariate linear modeling and a neural network approach, using additional independent variables.\",\"PeriodicalId\":49092,\"journal\":{\"name\":\"Central European Journal of Geosciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Central European Journal of Geosciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/s13533-012-0135-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Central European Journal of Geosciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/s13533-012-0135-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

本文分析了5年(2008-2012年)Terra和Aqua中分辨率成像光谱仪(MODIS)获得的气溶胶光学深度(AOD)与地面PM10质量浓度分布的关系,并探讨了卫星AOD数据在克罗地亚境内地面PM10制图中的适用性。许多研究表明,卫星AOD数据与地面PM质量浓度相关。然而,AOD与PM之间的关系并不明确,存在导致这种关系不确定性的未知因素。MODIS AOD和地面PM10之间的关系已经在一个大型数据集的基础上进行了研究,其中克罗地亚12个空气质量站5年期间的每日平均PM10数据与MODIS Terra和Aqua检索的AOD相关。建立了一个数据库来关联一致的MODIS AOD(独立)和PM10数据(因变量)。其他测试的独立变量(预测器、估计器)包括季节、云分数和气象参数——包括温度、气压、相对湿度、风速、风向以及行星边界层高度——使用WRF(天气研究与预报)模式的气象数据。结果表明:1)单变量线性回归模型不能很好地解释数据变异性,表明AOD-PM10关系具有非线性;2)使用额外的自变量,可以通过多元线性建模和神经网络方法来改善数据变异性的解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relationship between MODIS based Aerosol Optical Depth and PM10 over Croatia
This study analyzes the relationship between Aerosol Optical Depth (AOD) obtained from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based PM10 mass concentration distribution over a period of 5 years (2008–2012), and investigates the applicability of satellite AOD data for ground PM10 mapping for the Croatian territory. Many studies have shown that satellite AOD data are correlated to ground-based PM mass concentration. However, the relationship between AOD and PM is not explicit and there are unknowns that cause uncertainties in this relationship.The relationship between MODIS AOD and ground-based PM10 has been studied on the basis of a large data set where daily averaged PM10 data from the 12 air quality stations across Croatia over the 5 year period are correlated with AODs retrieved from MODIS Terra and Aqua. A database was developed to associate coincident MODIS AOD (independent) and PM10 data (dependent variable). Additional tested independent variables (predictors, estimators) included season, cloud fraction, and meteorological parameters — including temperature, air pressure, relative humidity, wind speed, wind direction, as well as planetary boundary layer height — using meteorological data from WRF (Weather Research and Forecast) model.It has been found that 1) a univariate linear regression model fails at explaining the data variability well which suggests nonlinearity of the AOD-PM10 relationship, and 2) explanation of data variability can be improved with multivariate linear modeling and a neural network approach, using additional independent variables.
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
Central European Journal of Geosciences
Central European Journal of Geosciences GEOSCIENCES, MULTIDISCIPLINARY-
自引率
0.00%
发文量
0
审稿时长
>12 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信