黄、渤海滨海带大气颗粒物时空分布与来源特征

PM10作为大气污染物监测的主要指标之一,探究大气PM10浓度对大气环境质量和人体健康评价具有重要意义。黄、渤海滨海带包括京、津和辽、冀、鲁、苏等工、农业大省,区域大气PM10污染的时空分布和来源特征具有复杂性和典型性。在锦州、北京、天津、烟台、青岛、连云港和盐城7个城市布设10个采样点,含7个城市点和3个农村点,开展为期一年的大气颗粒物的采样;同时,于冬季1月和夏季7月在锦州、天津和烟台进行合计60 d的加密采样,藉以确定研究区域大气PM10的时空分布和来源特征。结果表明,黄、渤海滨海带大气年均PM10总浓度为(129’18)"g·m~(-3),单月最低值出现在2015年7月盐城农村样点15"g·m~(-3),最高值为2015年3月北京城市点307"g·m~(-3)。盐城大气PM10浓度(城市点(85’27)"g·m~(-3)和农村点(66’35)"g·m~(-3))显著低于其他样点大气PM10浓度。渤海滨海带中西部的京(140’68"g·m~(-3))、津(169’60"g·m~(-3))两市大气PM10年均浓度显著高于东部的锦州(125’41"g·m~(-3))和烟台(109’31"g·m~(-3));而且黄海滨海带大气PM10年均浓度(114"g·m~(-3))显著低于渤海滨海带年均浓度(136"g·m~(-3)),总体上表现出西高东低、北高南低的特征。黄、渤海滨海带城市点和农村点年均浓度分别为(129’18)"g·m~(-3)和(112’30)"g·m~(-3);农村点春冬季大气PM10浓度和城市点浓度相当,无显著差异,夏秋季大气PM10浓度略低于城市浓度,表明农村地区大气颗粒物污染情况也较为严重,需受到关注。区域内PM10浓度季节变化整体表现为春冬高、夏秋低。利用多元回归分析初步判断黄、渤海滨海带PM10属于复合来源,大气PM10浓度约30%的变化与降水、人均能耗和沙尘天气相关。黄、渤海滨海带大气PM10浓度的昼夜变化不大,大气PM10浓度与气温呈现正相关,与风速和降水呈现负相关,表现为受各种气象因素综合作用的影响。

Spatial and Temporal Distribution of Atmospheric Particle Matter and Source Characteristics in the Littoral Areas of Bohai Sea and Yellow Sea

Since PM10 is one of the major indicators to assess atmospheric pollution,it is significant to explore the tempo-spatial changes in PM10 for the air quality and human health.In the littoral zones of Bohai Sea and Yellow Sea,there are two municipalities and some industrial and agricultural provinces,therefore the spatiotemporal distribution and source characteristics of PM10 are characterized by complexity and representativeness.In this study,the PM10 samples were collected in 7 urban sites (i.e.,Jinzhou,Beijing,Tianjin,Yantai,Qingdao,Lianyungang and Yancheng) and 3 corresponding rural sites for a period of 1 year.Meanwhile,the intensive sampling activities were conducted in January and July lasted for a total of 60 days in the sites at Jinzhou,Tianjin and Yantai.The results showed that the annual average of PM10 concentrations in the whole littoral zone was (129 ±18) μg· m-3.The minimum concentration of PM10 in a single month was 15 μg·m-3 at the rural site of Yancheng in July 2015;while the maximum concentration of PM10 in a single month was 307 μg·m-3 at the urban site of Beijing in March 2015.The concentrations of PM10 in Yancheng (85 ±27 μg·m-3 and 66 ±35 μg·m-3 at urban and rural sites,respectively) were obviously lower than those at the other sampling sites.The concentrations of PM10 in Beijing (140 ±68 μg· m-3)and in Tianjin (169 ±60 μg·m-3) situated in the mid-west part of Bohai littoral zone,were evidently greater than those in Jinzhou (125 ±41 μg·m-3) and in Yantai (109 ±31 μg·m-3) located in the east part of Bohai littoral zone.Moreover,the annual average concentration of PM10 in the coastal zone of Yellow Sea (114 μg·m-3) was apparently lower than that in the coastal areas of Bohai Sea (136 μg·m3).Therefore,the spatial distribution of PM10 concentration exhibited the decreasing trend from the west to the east and from the north to the south.In addition,the annual averages of PM10 concentrations in the urban and rural sites were (129 ±18) μg·m-3 and (112 ±30) μg·m-3,respectively.The levels of PM10 in the rural sites during winter and spring were close to those in the urban sites with no significant differences,indicating that the air pollution in the local rural areas was considerably severe and thus more attention should be paid.The levels of PM10 in the rural sites during summer and autumn were slightly lower than those in the urban sites.In view of two coastal zones,the seasonal feature of PM10 concentration was higher in spring and winter,and lower in summer and autumn.Based on a multivariate regression model,the emission source of PM10 in the littoral areas of Bohai Sea and Yellow Sea was multiple.About 30％ of the total variations in the concentration of PM10 could be attributed to the local wet precipitation,energy consumption per capita and sandstorm.The diurnal changes in concentration of PM10 were not significant in the two zones.The concentration PM10 showed positive correlation with air temperature,and negative correlations with wind velocity and wet precipitation.In other words,PM2.5 concentration was affected by the combined meteorological factors.