摘要
Long-term and synchronous monitoring of PMIo and PM2.s was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models （PMF2, ME2-2way and ME2-3way）, Consistent results were found： the primary source categories contributed 63.4% （PMF2）, 64.8% （ME2-2way） and 66.8% （ME2-Bway） to PMIo, and contributed 60.9% （PMF2）, 65.5% （ME2-2way） and 61.0% （ME2-3way） to PM2.s. Secondary sources contributed 31.8% （PMF2）, 32.9% （ME2-2way） and 31.7% （ME2-3way） to PMIo, and 35.0% （PMF2）, 33.8% （ME2-2way） and 36.0% （ME2-3way） to PM2.s. The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment （SDA） was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east （ENE） contributed the highest to both PM^o （12.7%） and PMzs （9.7%） in Chengdu, followed by the crustal dust from south-east （SE） for PMao （9.8%） and secondary nitrate ＆ secondary organic carbon from ENE for PMzs （9.6%）. Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and tn dovolon offoctive nolhltion control gtrateMeg.
Long-term and synchronous monitoring of PMIo and PM2.s was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models （PMF2, ME2-2way and ME2-3way）, Consistent results were found： the primary source categories contributed 63.4% （PMF2）, 64.8% （ME2-2way） and 66.8% （ME2-Bway） to PMIo, and contributed 60.9% （PMF2）, 65.5% （ME2-2way） and 61.0% （ME2-3way） to PM2.s. Secondary sources contributed 31.8% （PMF2）, 32.9% （ME2-2way） and 31.7% （ME2-3way） to PMIo, and 35.0% （PMF2）, 33.8% （ME2-2way） and 36.0% （ME2-3way） to PM2.s. The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment （SDA） was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east （ENE） contributed the highest to both PM^o （12.7%） and PMzs （9.7%） in Chengdu, followed by the crustal dust from south-east （SE） for PMao （9.8%） and secondary nitrate ＆ secondary organic carbon from ENE for PMzs （9.6%）. Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and tn dovolon offoctive nolhltion control gtrateMeg.
基金
supported by the Tianjin Natural Science Foundation(No.16JCQNJC08700)
the Fundamental Research Funds for the Central Universities
National Key Research and Development Program of China(No.2016YFC0208500)
the National Natural Science Foundation of China(No.21407174)
the Tianjin Research Program of Application Foundation(No.14JCQNJC08100)
the Tianjin Science and Technology Project(Nos.16YFZCSF00260,14ZCDGSF00027,14ZCDGSF00029)
the Special Funds for Research on Public Welfares of the Ministry of Environmental Protection of China(201309072)
