基于PMF模型的土壤重金属源解析中变量敏感性研究
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摘要
为探究应用受体模型对土壤污染物进行源解析,输入变量对模型运行及其结果的影响,以乐安河中上游地区土壤重金属调查数据作为典型受体模型(PMF模型)的输入数据集,并在PMF模型基础方案运行结果的基础上,采用局部敏感性分析法来探讨输入变量变化对模型诊断及源识别结果的影响.结果表明:6因子数情景是研究区土壤重金属源解析PMF模型最佳运行结果;土壤中Cu、Mo、Na2O、As、Mn和Cd等参数属于敏感变量,这些变量均为每个因子中的主要载荷元素,即每个源的特征污染物;不同变量的敏感性有较大差异,Cu、Mo的总敏感性最大,分别为12.1,8.2,大于其他输入变量的敏感性.因此,在应用PMF模型进行源解析时,特征污染物是敏感性较强的变量,其数据质量的优劣是影响源解析结果可靠性的重要因素.
To explore the impacts of variables on receptor model results in source apportionment for soil pollutants, the sampling data set of soil heavy metals in the middle and upper reaches of Le'an River was used as the input data set for the typical receptor model(PMF model). After obtaining the results of basic scenarios by PMF model, local sensitivity analysis method was introduced to study the sensitivity of variables on PMF diagnosis and source identification. The six-factor scenario was the best result for the simulation of PMF base model, Cu、Mo、Na2 O、As、Mn and Cd in the soil were the sensitive variables and also the main loading elements in each factor profile(i.e. the typical pollutants of each source). There was a significant difference on the sensitivity for these variables: the total sensitivity of Cu and Mo are much higher than that of the other variables, reaching 12.1 and 8.2 respectively. Therefore, it revealed that the sensitive variables should be the specific pollutants when applying the receptor model for source apportionment, and the data quality was an important factors affecting of the reliability of source apportionment.
To explore the impacts of variables on receptor model results in source apportionment for soil pollutants, the sampling data set of soil heavy metals in the middle and upper reaches of Le'an River was used as the input data set for the typical receptor model(PMF model). After obtaining the results of basic scenarios by PMF model, local sensitivity analysis method was introduced to study the sensitivity of variables on PMF diagnosis and source identification. The six-factor scenario was the best result for the simulation of PMF base model, Cu、Mo、Na2 O、As、Mn and Cd in the soil were the sensitive variables and also the main loading elements in each factor profile(i.e. the typical pollutants of each source). There was a significant difference on the sensitivity for these variables: the total sensitivity of Cu and Mo are much higher than that of the other variables, reaching 12.1 and 8.2 respectively. Therefore, it revealed that the sensitive variables should be the specific pollutants when applying the receptor model for source apportionment, and the data quality was an important factors affecting of the reliability of source apportionment.
引文
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[23]Pianosi F,Beven K,Freer J,et al.Sensitivity analysis of environmental models:A systematic review with practical workflow[J].Environmental Modelling&Software,2016,79:214-232.
[24]Norris G,Duvall R,Brown S,et al.EPA positive matrix factorization(PMF)5.0 fundamentals and user guide[Z].2014.
[25]邢可霞,郭怀成.环境模型不确定性分析方法综述[J].环境科学与技术,2006,29(5):112-114.Xing K X,Guo H C.Review on uncertainty analysis methods in environment model[J].Environmental Science&Technology,2006,29(5):112-114.
[26]李娇,滕彦国,吴劲,等.基于PMF模型及地统计法的乐安河中上游地区土壤重金属来源解析[J/OL].环境科学研究:1-12[2019-02-13].https://doi.org/10.13198/j.issn.1001-6929.2018.07.14.Li J,Teng Y G,Wu J,Jiang J Y,Huang Y.Source apportionment of soil heavy metal in the middle and upper reaches of Le’an river based on PMF model and geostatistic[J/OL].Research of Environmental Sciences:1-12[2019-02-13].https://doi.org/10.13198/j.issn.1001-6929.2018.07.14.
[27]Paatero P,Eberly S,Brown S G,et al.Methods for estimating uncertainty in factor analytic solutions[J].Atmospheric Measurement Techniques,2014,7(3):781-797.
[2]Chen H Y,Teng Y G,Lu S J,et al.Contamination features and health risk of soil heavy metals in China[J].Science of the Total Environment,2015,512:143-153.
[3]陈卫平,杨阳,谢天,等.中国农田土壤重金属污染防治挑战与对策[J].土壤学报,2018,55(2):261-272.Chen W P,Yang Y,Xie T,et al.Challenges and countermeasures for heavy metal pollution control in farmlands of China[J].Acta Pedologica Sinica,2018,55(2):261-272.
[4]骆永明.污染土壤修复技术研究现状与趋势[J].化学进展,2009,21(2/3):558-565.Luo Y M.Current research and development in soil remediation technologies[J].Progress in Chemistry,2009,21(2/3):558-565.
[5]董騄睿,胡文友,黄标,等.基于正定矩阵因子分析模型的城郊农田土壤重金属源解析[J].中国环境科学,2015,35(7):2103-2111.Dong L R,Hu W Y,Huang B,et al.Source appointment of heavy metals in suburban farmland soils based on positive matrix factorization[J].China Environmental Science,2015,35(7):2103-2111.
[6]李娇,吴劲,蒋进元,等.近十年土壤污染物源解析研究综述[J].土壤通报,2018,49(1):232-242.Li J,Wu J,Jiang J Y,et al.Review on source apportionment of soil pollutants in recent ten years[J].Chinese Journal of Soil Science,2018,49(1):232-242.
[7]Wang G Q,A Y L,Jang H,et al.Modeling the source contribution of heavy metals in surficial sediment and analysis of their historical changes in the vertical sediments of a drinking water reservoir[J].Journal of Hydrology,2015,520:37-51.
[8]瞿明凯,李卫东,张传荣,等.基于受体模型和地统计学相结合的土壤镉污染源解析[J].中国环境科学,2013,33(5):854-860.Qu M K,Li W D,Zhang C R,et al.Source apportionment of soil heavy metal Cd based on the combination of receptor model and geostatistics[J].China Environmental Science,2013,33(5):854-860.
[9]张慧,郑志志,马鑫鹏,等.哈尔滨市土壤表层重金属污染特征及来源辨析[J].环境科学研究,2017,30(10):1597-1606.Zhang H,Zheng Z Z,Ma X P,et al.Sources and pollution characteristics of heavy metals in surface soils of Harbin city[J].Research of Environmental Sciences,2017,30(10):1597-1606.
[10]Jiang Y X,Chao S H,Liu J W,et al.Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province,China[J].Chemosphere,2017,168:1658-1668.
[11]Luo X S,Xue Y,Wang Y L,et al.Source identification and apportionment of heavy metals in urban soil profiles[J].Chemosphere,2015,127:152-157.
[12]艾建超,王宁,杨净.基于UNMIX模型的夹皮沟金矿区土壤重金属源解析[J].环境科学,2014,35(9):3530-3536.Ai J C,Wang N,Yang J.Source apportionment of soil heavy metals in Jiapigou goldmine based on the UNMIX model[J].Environmental Science,2014,35(9):3530-3536.
[13]李娇,陈海洋,滕彦国,等.拉林河流域土壤重金属污染特征及来源解析[J].农业工程学报,2016,32(19):226-233.Li J,Chen H Y,Teng Y G,et al.Contamination characteristics and source apportionment of soil heavy metals in Lalin River basin[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(19):226-233.
[14]韩培培,谢俭,王剑,等.丹江口水库新增淹没区农田土壤重金属源解析[J].中国环境科学,2016,36(8):2437-2443.Han P P,Xie J,Wang J,et al.Source apportionment of heavy metals in farmland soil from new submerged area in Danjiangkou Reservoir[J].China Environmental Science,2016,36(8):2437-2443.
[15]Hu W Y,Wang H F,Dong L R,et al.Source identification of heavy metals in peri-urban agricultural soils of southeast China:An integrated approach[J].Environmental Pollution,2018,237:650-661.
[16]Zhang X W,Wei S,Sun Q Q,et al.Source identification and spatial distribution of arsenic and heavy metals in agricultural soil around Hunan industrial estate by positive matrix factorization model,principle components analysis and geo statistical analysis[J].Ecotoxicology and Environmental Safety,2018,159:354-362.
[17]Liang J,Feng C T,Zeng G M,et al.Spatial distribution and source identification of heavy metals in surface soils in a typical coal mine city,Lianyuan,China[J].Environmental Pollution,2017,225.681-690.
[18]Saltelli A,Tarantola S,Campolongo F.Sensitivity analysis as an ingredient of modeling[J].Statistical Science,2000,15(4):377-395.
[19]陈卫平,涂宏志,彭驰,等.环境模型中敏感性分析方法评述[J].环境科学,2017,38(11):4889-4896.Chen W P,Xu H Z,Peng C,et al.Comment on sensitivity analysis methods for environmental models[J].Environmental Science,2017,38(11):4889-4896.
[20]何亮,赵刚,靳宁,等.不同气候区和不同产量水平下APSIM-Wheat模型的参数全局敏感性分析[J].农业工程学报,2015,31(14):148-157.He L,Zhao G,Jin N,et al.Global sensitivity analysis of APSIM-Wheat parameters in different climate zones and yield levels[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(14):148-157.
[21]Cho E,Arhonditsis G B,Khim J,et al.Modeling metal-sediment interaction processes:parameter sensitivity assessment and uncertainty analysis[J].Environmental Modelling&Software,2016,80:159-174.
[22]Huan H,Wang J S,Teng Y G,et al.Assessment and validation of groundwater vulnerability to nitrate based on a modified DRASTICmodel:a case study in Jilin City of northeast China[J].Science of the Total Environment,2012,440:14-23.
[23]Pianosi F,Beven K,Freer J,et al.Sensitivity analysis of environmental models:A systematic review with practical workflow[J].Environmental Modelling&Software,2016,79:214-232.
[24]Norris G,Duvall R,Brown S,et al.EPA positive matrix factorization(PMF)5.0 fundamentals and user guide[Z].2014.
[25]邢可霞,郭怀成.环境模型不确定性分析方法综述[J].环境科学与技术,2006,29(5):112-114.Xing K X,Guo H C.Review on uncertainty analysis methods in environment model[J].Environmental Science&Technology,2006,29(5):112-114.
[26]李娇,滕彦国,吴劲,等.基于PMF模型及地统计法的乐安河中上游地区土壤重金属来源解析[J/OL].环境科学研究:1-12[2019-02-13].https://doi.org/10.13198/j.issn.1001-6929.2018.07.14.Li J,Teng Y G,Wu J,Jiang J Y,Huang Y.Source apportionment of soil heavy metal in the middle and upper reaches of Le’an river based on PMF model and geostatistic[J/OL].Research of Environmental Sciences:1-12[2019-02-13].https://doi.org/10.13198/j.issn.1001-6929.2018.07.14.
[27]Paatero P,Eberly S,Brown S G,et al.Methods for estimating uncertainty in factor analytic solutions[J].Atmospheric Measurement Techniques,2014,7(3):781-797.
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