{"title":"1981 - 2017年湘西雾霾日变化特征及影响因素","authors":"W. Zhou, Benzhi Wang, Chao Chen, Yuzhen Yang","doi":"10.1109/ICSGEA.2019.00103","DOIUrl":null,"url":null,"abstract":"In order to reveal the evolution, spatial and temporal distribution characteristics and influencing factors of haze weather in Xiangxi under the background of climate change, daily meteorological data of eight national meteorological observatories in Xiangxi were revised and analyzed. The results showed that the haze days in Xiangxi from 1981 to 2017 showed a significant increase trend; the number of haze days in autumn and winter was more than that in spring and summer; the regional distribution was more in the south, north and less in the middle; the proportion of light haze was the largest in the central urban area of Xiangxi, accounting for 66.81%, and the proportion of severe haze was the smallest, accounting for 4.17%. Except for light haze, the number of light, medium and heavy haze days increased. The main meteorological factors are annual average temperature, maximum temperature, high temperature day, precipitation≥ 0.1mm days), f ≥ 5.0m/s days, average wind speed and so on. The average temperature, maximum temperature and average wind speed are significantly positively correlated with haze day; the number of days with precipitation ≥ 0.1mm decreases, relative humidity ≤80% increases, and PM2.5 and SO2 are negatively correlated with visibility and relative humidity, and the frequency of haze occurrence. There was a significant correlation between the rates.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Daily Variation Characteristics and Influencing Factors of the Haze in Xiangxi From 1981 to 2017\",\"authors\":\"W. Zhou, Benzhi Wang, Chao Chen, Yuzhen Yang\",\"doi\":\"10.1109/ICSGEA.2019.00103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to reveal the evolution, spatial and temporal distribution characteristics and influencing factors of haze weather in Xiangxi under the background of climate change, daily meteorological data of eight national meteorological observatories in Xiangxi were revised and analyzed. The results showed that the haze days in Xiangxi from 1981 to 2017 showed a significant increase trend; the number of haze days in autumn and winter was more than that in spring and summer; the regional distribution was more in the south, north and less in the middle; the proportion of light haze was the largest in the central urban area of Xiangxi, accounting for 66.81%, and the proportion of severe haze was the smallest, accounting for 4.17%. Except for light haze, the number of light, medium and heavy haze days increased. The main meteorological factors are annual average temperature, maximum temperature, high temperature day, precipitation≥ 0.1mm days), f ≥ 5.0m/s days, average wind speed and so on. The average temperature, maximum temperature and average wind speed are significantly positively correlated with haze day; the number of days with precipitation ≥ 0.1mm decreases, relative humidity ≤80% increases, and PM2.5 and SO2 are negatively correlated with visibility and relative humidity, and the frequency of haze occurrence. There was a significant correlation between the rates.\",\"PeriodicalId\":201721,\"journal\":{\"name\":\"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSGEA.2019.00103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSGEA.2019.00103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Daily Variation Characteristics and Influencing Factors of the Haze in Xiangxi From 1981 to 2017
In order to reveal the evolution, spatial and temporal distribution characteristics and influencing factors of haze weather in Xiangxi under the background of climate change, daily meteorological data of eight national meteorological observatories in Xiangxi were revised and analyzed. The results showed that the haze days in Xiangxi from 1981 to 2017 showed a significant increase trend; the number of haze days in autumn and winter was more than that in spring and summer; the regional distribution was more in the south, north and less in the middle; the proportion of light haze was the largest in the central urban area of Xiangxi, accounting for 66.81%, and the proportion of severe haze was the smallest, accounting for 4.17%. Except for light haze, the number of light, medium and heavy haze days increased. The main meteorological factors are annual average temperature, maximum temperature, high temperature day, precipitation≥ 0.1mm days), f ≥ 5.0m/s days, average wind speed and so on. The average temperature, maximum temperature and average wind speed are significantly positively correlated with haze day; the number of days with precipitation ≥ 0.1mm decreases, relative humidity ≤80% increases, and PM2.5 and SO2 are negatively correlated with visibility and relative humidity, and the frequency of haze occurrence. There was a significant correlation between the rates.