Maria Dimitrova, Plamen Trenchev, Daniela Avetisyan
{"title":"基于开放获取GAMS数据的保加利亚上空大气污染物成分的时空行为","authors":"Maria Dimitrova, Plamen Trenchev, Daniela Avetisyan","doi":"10.1117/12.2684037","DOIUrl":null,"url":null,"abstract":"In recent years a steady trend of increasing concentrations of major air pollutants is observed. The nature and dynamics of this trend vary according to the type of pollutant, source of emissions, and location. Because of these differences, it is important to comprehensively analyze the spatial and temporal behavior of the most important air pollutants using satellite and ground-based measurement data. An important step in this process is locating, tracking, and quantifying the emissions. This paper presents the results of air pollution monitoring based on the analysis of data obtained from 32 Ground-based Automatic Measuring Stations (GAMS) located throughout Bulgaria. The spatial and temporal behavior of major air pollutants such as NO, NO2, SO2, CO, and benzene for the period 2015 - 2022 was investigated. However, not all GAMS have data for all types of pollutants. The largest amount of information is available for SO2 and NO2, while small numbers of GAMS provide data for CO. For pollutants such as NO2, SO2, and CO an analysis with satellite data from the European Sentinel-5P satellite was performed. Due to the uneven distribution of the available information from ground measurements, the spatial behavior of the pollutants studied is presented using a unified methodology for selected regions. Monthly and annual average data were also analyzed in our study.","PeriodicalId":117988,"journal":{"name":"Remote Sensing of Clouds and the Atmosphere XXVIII","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal behavior of atmospheric pollutant ingredients over Bulgaria, based on open access GAMS data\",\"authors\":\"Maria Dimitrova, Plamen Trenchev, Daniela Avetisyan\",\"doi\":\"10.1117/12.2684037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years a steady trend of increasing concentrations of major air pollutants is observed. The nature and dynamics of this trend vary according to the type of pollutant, source of emissions, and location. Because of these differences, it is important to comprehensively analyze the spatial and temporal behavior of the most important air pollutants using satellite and ground-based measurement data. An important step in this process is locating, tracking, and quantifying the emissions. This paper presents the results of air pollution monitoring based on the analysis of data obtained from 32 Ground-based Automatic Measuring Stations (GAMS) located throughout Bulgaria. The spatial and temporal behavior of major air pollutants such as NO, NO2, SO2, CO, and benzene for the period 2015 - 2022 was investigated. However, not all GAMS have data for all types of pollutants. The largest amount of information is available for SO2 and NO2, while small numbers of GAMS provide data for CO. For pollutants such as NO2, SO2, and CO an analysis with satellite data from the European Sentinel-5P satellite was performed. Due to the uneven distribution of the available information from ground measurements, the spatial behavior of the pollutants studied is presented using a unified methodology for selected regions. Monthly and annual average data were also analyzed in our study.\",\"PeriodicalId\":117988,\"journal\":{\"name\":\"Remote Sensing of Clouds and the Atmosphere XXVIII\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Clouds and the Atmosphere XXVIII\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2684037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Clouds and the Atmosphere XXVIII","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2684037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatiotemporal behavior of atmospheric pollutant ingredients over Bulgaria, based on open access GAMS data
In recent years a steady trend of increasing concentrations of major air pollutants is observed. The nature and dynamics of this trend vary according to the type of pollutant, source of emissions, and location. Because of these differences, it is important to comprehensively analyze the spatial and temporal behavior of the most important air pollutants using satellite and ground-based measurement data. An important step in this process is locating, tracking, and quantifying the emissions. This paper presents the results of air pollution monitoring based on the analysis of data obtained from 32 Ground-based Automatic Measuring Stations (GAMS) located throughout Bulgaria. The spatial and temporal behavior of major air pollutants such as NO, NO2, SO2, CO, and benzene for the period 2015 - 2022 was investigated. However, not all GAMS have data for all types of pollutants. The largest amount of information is available for SO2 and NO2, while small numbers of GAMS provide data for CO. For pollutants such as NO2, SO2, and CO an analysis with satellite data from the European Sentinel-5P satellite was performed. Due to the uneven distribution of the available information from ground measurements, the spatial behavior of the pollutants studied is presented using a unified methodology for selected regions. Monthly and annual average data were also analyzed in our study.