GNSS反演数据与PM2.5质量浓度相关性研究
|
摘要
针对目前雾霾中PM2.5的测定方法存在局限性的问题,提出一种利用全球导航卫星系统(global navigation satellite system,GNSS)反演技术探测大气颗粒物PM2.5浓度的新思路。通过观察分析,发现雾霾天气的变化具有季节性,为此选取4个不同时期的数据进行GNSS反演,获得大气对流层中的一些延迟量,进而获得大气可降水量。通过分析大气可降水量与同时期的PM2.5浓度之间的相关性,验证GNSS反演技术探测PM2.5浓度思路的可行性。实验结果表明,GNSS反演数据与PM2.5浓度存在一定的关系,在监测PM2.5浓度方面存在潜在的应用价值,并为完善当前的雾霾预警机制的研究提供参考。
In view of the limitations of the current determination methods of PM2.5 in haze, a new idea of using GNSS inversion technique to detect PM2.5 concentration of atmospheric particles is proposed in this paper. Data of four different periods is selected to perform GNSS inversion to obtain some troposphere delay and atmospheric precipitation. By analyzing the correlation between atmospheric pre-cipitable water and the concentration of PM2.5 in the same period, the feasibility of GNSS inversion technique to detect PM2.5 concentration is verified. Experimental results show that there is a certain relationship between GNSS inversion data and PM2.5 concentration, which has potential application value in monitoring PM2.5 concentration, and provides a reference for improving the current research of haze warning mechanism.
In view of the limitations of the current determination methods of PM2.5 in haze, a new idea of using GNSS inversion technique to detect PM2.5 concentration of atmospheric particles is proposed in this paper. Data of four different periods is selected to perform GNSS inversion to obtain some troposphere delay and atmospheric precipitation. By analyzing the correlation between atmospheric pre-cipitable water and the concentration of PM2.5 in the same period, the feasibility of GNSS inversion technique to detect PM2.5 concentration is verified. Experimental results show that there is a certain relationship between GNSS inversion data and PM2.5 concentration, which has potential application value in monitoring PM2.5 concentration, and provides a reference for improving the current research of haze warning mechanism.
引文
[1] 孙峰,张大伟,孙瑞雯,等.北京地区冬季典型PM2.5重污染案例分析[J].中国环境监测,2014,30(6):1-12
[2] 杨新兴,尉鹏,冯丽华.大气颗粒物PM2.5及其源解析[J].前沿科学,2013,7(2):12-19
[3] 杨洪斌,邹旭东,汪宏宇,等.大气环境中PM-(2.5)的研究进展与展望[J].气象与环境学报,2012,28(3):77-82
[4] 郭新彪,魏红英.大气PM2.5对健康影响的研究进展[J].科学通报,2013,58(13):1 171-1 177
[5] 魏玉香,银燕,杨卫芬,等.南京地区PM2.5污染特征及其影响因素分析[J].环境科学与管理,2009,34(9):29-34
[6] 郭洁,李国平,黄文诗.GPS可降水量与大雾天气关系的初步分析[J].自然灾害学报,2011,20(4):142-146
[7] 王勇,闻德保,刘严萍,等.雾霾天气对GPS天顶对流层延迟与可降水量影响研究[J].大地测量与地球动力学,2014,34(2):120-123
[8] 李同文,孙越乔,杨晨雪,等.融合卫星遥感与地面测站的区域PM2.5反演[J].测绘地理信息,2015,40(3):6-9
[9] 蒋光伟.基于地基GPS的实时遥感水汽的理论与应用[D].陕西:长安大学,2010
[10] Businger T.The Promise of GPS in Atmospheric Monitoring [J].Bulletin of the American Meteorological Society,1996,77(1):5-18
[11] 王勇,刘严萍.地基GPS气象学原理与应用研究[M].北京:测绘出版社,2012
[12] 江琪,王飞,张恒德,等.北京市PM2.5和反应性气体浓度的变化特征及其与气象条件的关系[J].中国环境科学,2017,37(3):829-837
[13] 周一敏,赵昕奕.北京地区PM2.5浓度与气象要素的相关分析[J].北京大学学报(自然科学版),2017,53(1):111-124
[14] 王勇,刘严萍,李江波,等.水汽和风速对雾霾中PM2.5/PM10变化的影响[J].灾害学,2015,30(1):5-7
[15] 张双成,赵迎辉,戴凯阳,等.西安地区雾霾与GPS水汽的相关性分析[J].工程勘察,2016,44(3):47-50
[2] 杨新兴,尉鹏,冯丽华.大气颗粒物PM2.5及其源解析[J].前沿科学,2013,7(2):12-19
[3] 杨洪斌,邹旭东,汪宏宇,等.大气环境中PM-(2.5)的研究进展与展望[J].气象与环境学报,2012,28(3):77-82
[4] 郭新彪,魏红英.大气PM2.5对健康影响的研究进展[J].科学通报,2013,58(13):1 171-1 177
[5] 魏玉香,银燕,杨卫芬,等.南京地区PM2.5污染特征及其影响因素分析[J].环境科学与管理,2009,34(9):29-34
[6] 郭洁,李国平,黄文诗.GPS可降水量与大雾天气关系的初步分析[J].自然灾害学报,2011,20(4):142-146
[7] 王勇,闻德保,刘严萍,等.雾霾天气对GPS天顶对流层延迟与可降水量影响研究[J].大地测量与地球动力学,2014,34(2):120-123
[8] 李同文,孙越乔,杨晨雪,等.融合卫星遥感与地面测站的区域PM2.5反演[J].测绘地理信息,2015,40(3):6-9
[9] 蒋光伟.基于地基GPS的实时遥感水汽的理论与应用[D].陕西:长安大学,2010
[10] Businger T.The Promise of GPS in Atmospheric Monitoring [J].Bulletin of the American Meteorological Society,1996,77(1):5-18
[11] 王勇,刘严萍.地基GPS气象学原理与应用研究[M].北京:测绘出版社,2012
[12] 江琪,王飞,张恒德,等.北京市PM2.5和反应性气体浓度的变化特征及其与气象条件的关系[J].中国环境科学,2017,37(3):829-837
[13] 周一敏,赵昕奕.北京地区PM2.5浓度与气象要素的相关分析[J].北京大学学报(自然科学版),2017,53(1):111-124
[14] 王勇,刘严萍,李江波,等.水汽和风速对雾霾中PM2.5/PM10变化的影响[J].灾害学,2015,30(1):5-7
[15] 张双成,赵迎辉,戴凯阳,等.西安地区雾霾与GPS水汽的相关性分析[J].工程勘察,2016,44(3):47-50