贵阳市冬季大气PM_(2.5)和PM_(10)浓度空间插值及分布研究
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摘要
为了解贵阳市冬季大气污染现状,以贵阳市污染相对严重的白云区为研究对象,连续采集PM_(2.5)、PM_(10)浓度数据,利用普通克里金法进行空间插值获取PM_(2.5)、PM_(10)分布特征。通过留一法交叉验证,比较6种半变异函数模型(三角函数、高斯函数、球面函数、指数函数、J-Bessel函数和K-Bessel函数)的空间插值精度,选出最适的函数模型;采用分区统计和格网统计的方法,对不同土地利用类型、植被覆盖度下的PM_(2.5)、PM_(10)平均浓度进行比较分析。结果表明,三角函数是PM_(2.5)空间插值的最适模型,指数函数是PM_(10)空间插值的最适模型;贵阳市白云区冬季大气PM_(2.5)、PM_(10)浓度总体表现出城区浓度高,郊区浓度低的分布特征;土地利用类型和植被覆盖度对PM_(2.5)和PM_(10)浓度有着较强的影响。
In order to understand the current atmospheric pollution situation of Guiyang during winter,the Baiyun District was selected as the research area to collect PM_(2.5)and PM_(10)concentration data continuously,and ordinary Kriging method was used for spatial interpolation to analyze characteristics of PM_(2.5)and PM_(10)distribution.Through the"leave-one-out"cross validation method,the spatial interpolation accuracy of different semi-variable function,such as the trigonometric function,Gaussian function,spherical functions,exponential functions,J-Bessel function and K-Bessel function was compared,and the most suitable function model was selected.The average PM_(2.5),PM_(10)concentration of different land use type and vegetation coverage was analyzed respectively by means of zoning statistics and grid statistics.The results showed that the triangular function model was the most suitable for the spatial interpolation of PM_(2.5)and the exponential function model was the most suitable for the spatial interpolation of PM_(10).In the Baiyun District,the concentration of PM_(2.5)and PM_(10)presented the distribution characteristics as higher in urban areas and lower in suburban areas.Land use type and vegetation coverage had a strong impact on PM_(2.5)and PM_(10)concentrations.
In order to understand the current atmospheric pollution situation of Guiyang during winter,the Baiyun District was selected as the research area to collect PM_(2.5)and PM_(10)concentration data continuously,and ordinary Kriging method was used for spatial interpolation to analyze characteristics of PM_(2.5)and PM_(10)distribution.Through the"leave-one-out"cross validation method,the spatial interpolation accuracy of different semi-variable function,such as the trigonometric function,Gaussian function,spherical functions,exponential functions,J-Bessel function and K-Bessel function was compared,and the most suitable function model was selected.The average PM_(2.5),PM_(10)concentration of different land use type and vegetation coverage was analyzed respectively by means of zoning statistics and grid statistics.The results showed that the triangular function model was the most suitable for the spatial interpolation of PM_(2.5)and the exponential function model was the most suitable for the spatial interpolation of PM_(10).In the Baiyun District,the concentration of PM_(2.5)and PM_(10)presented the distribution characteristics as higher in urban areas and lower in suburban areas.Land use type and vegetation coverage had a strong impact on PM_(2.5)and PM_(10)concentrations.
引文
[1]李红,曾凡刚,邵龙义,等.可吸入颗粒物对人体健康危害的研究进展[J].环境与健康杂志,2002,19(1):85-87.
[2]HOEK G,MELIEFSTE K,CYRYS J,et al.Spatial variability of fine particle concentrations in three European areas[J].Atmospheric Environment,2002,36(25):4077-4088.
[3]MARTUZEVICIUS D,GRINSHPUN S A,REPONEN T,et al.Spatial and temporal variations of PM2.5concentration and composition throughout an urban area with high freeway density-the Greater Cincinnati study[J].Atmospheric Environment,2004,38(8):1091-1105.
[4]袁杨森,刘大锰,车瑞俊,等.北京市秋季大气颗粒物的污染特征研究[J].生态环境,2007,16(1):18-25.
[5]唐昀凯,刘胜华.城市土地利用类型与PM2.5浓度相关性研究——以武汉市为例[J].长江流域资源与环境,2015,24(9).
[6]姜北.河北省麻山药主产区土壤适宜性评价[D].保定:河北农业大学,2013.
[7]王兴,刘莹,王春晖,等.海洋盐度分布的插值方法应用与对比研究[J].海洋通报,2016,35(3):324-330.
[8]汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程[M].2版.北京:科学出版社,2012.
[9]宋超.面向城市消防站选址规划的时空动态火灾风险建模分析[D].合肥:中国科学技术大学,2017.
[10]程朋,张珺,张茹,等.山西高原降水量空间插值分析[J].人民黄河,2016,38(2):24-27.
[11]王嫣然,张学霞,赵静瑶,等.2013-2014年北京地区PM2.5时空分布规律及其与植被覆盖度关系研究[J].生态环境学报,2016,25(1):103-111.
[12]DZIERZANOWSKI K,POPEK R,GAWROASKA H,et al.Deposition of particulate matter of different size fractions on leaf surfaces and in waxes of urban forest species[J].International Journal of Phytoremediation,2011,13(10):1037-1046.
[13]赵松婷,李新宇,李延明.园林植物滞留不同粒径大气颗粒物的特征及规律[J].生态环境学报,2014,23(2):271-276.
[2]HOEK G,MELIEFSTE K,CYRYS J,et al.Spatial variability of fine particle concentrations in three European areas[J].Atmospheric Environment,2002,36(25):4077-4088.
[3]MARTUZEVICIUS D,GRINSHPUN S A,REPONEN T,et al.Spatial and temporal variations of PM2.5concentration and composition throughout an urban area with high freeway density-the Greater Cincinnati study[J].Atmospheric Environment,2004,38(8):1091-1105.
[4]袁杨森,刘大锰,车瑞俊,等.北京市秋季大气颗粒物的污染特征研究[J].生态环境,2007,16(1):18-25.
[5]唐昀凯,刘胜华.城市土地利用类型与PM2.5浓度相关性研究——以武汉市为例[J].长江流域资源与环境,2015,24(9).
[6]姜北.河北省麻山药主产区土壤适宜性评价[D].保定:河北农业大学,2013.
[7]王兴,刘莹,王春晖,等.海洋盐度分布的插值方法应用与对比研究[J].海洋通报,2016,35(3):324-330.
[8]汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程[M].2版.北京:科学出版社,2012.
[9]宋超.面向城市消防站选址规划的时空动态火灾风险建模分析[D].合肥:中国科学技术大学,2017.
[10]程朋,张珺,张茹,等.山西高原降水量空间插值分析[J].人民黄河,2016,38(2):24-27.
[11]王嫣然,张学霞,赵静瑶,等.2013-2014年北京地区PM2.5时空分布规律及其与植被覆盖度关系研究[J].生态环境学报,2016,25(1):103-111.
[12]DZIERZANOWSKI K,POPEK R,GAWROASKA H,et al.Deposition of particulate matter of different size fractions on leaf surfaces and in waxes of urban forest species[J].International Journal of Phytoremediation,2011,13(10):1037-1046.
[13]赵松婷,李新宇,李延明.园林植物滞留不同粒径大气颗粒物的特征及规律[J].生态环境学报,2014,23(2):271-276.
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