晉城市大氣VOCs污染特征及來源解析

張鵬輝,胡冬梅*,彭 林,牛偉利,龔興曉,閆雨龍,牛月圓,董佳奇

晉城市大氣VOCs污染特征及來源解析

張鵬輝1,胡冬梅1*,彭 林2,牛偉利3,龔興曉4,閆雨龍2,牛月圓1,董佳奇1

(1.華北電力大學環境科學與工程學院,資源環境系統優化教育部重點實驗室,北京 102206；2.北京交通大學環境學院,北京 100044；3.晉城市生態環境局,山西 晉城 048000；4.山西省晉城生態環境監測中心,山西 晉城 048000)

采集晉城市環境空氣揮發性有機物(VOCs)樣品,分析不同風向下VOCs組分特征,運用特征比值法和正定矩陣因子分析模型(PMF)解析VOCs來源,采用混合單顆粒拉格朗日積分軌跡(HYSPLIT)追蹤夏季典型污染過程區域VOCs傳輸貢獻.結果表明,偏南風和偏北風主導風向下晉城市大氣VOCs濃度分別為(19.4±7.1)和(33.3±17.3)μg/m3,偏北風時濃度約比偏南風時高近70%,北部工業園區對市區VOCs影響較大;各組分按濃度大小排序為烷烴>芳香烴>烯烴>炔烴,偏北風時烷烴和芳香烴濃度顯著高于偏南風時,炔烴濃度相仿.偏南風和偏北風時臭氧生成潛勢(OFP)分別為(50.5±17.1)和(84.30±44.0)μg/m3;不同風向下各組分貢獻均為烯烴>烷烴>芳香烴>炔烴;北風風向下各VOCs組分及OFP小時變化幅度明顯高于南風時,尤其早晚間和交通流高峰時段較為顯著,北部工業園區和機動車排放源對市區影響突出.偏北風和偏南風時大氣VOCs均受老化氣團控制,不同風向下OFP及實際O3小時濃度變化呈相反趨勢,河南北部接壤區域存在強潛在源區,其對晉城市夏季VOCs貢獻率約為25.3%.本地燃燒源、機動車排放源和工業源是晉城市VOCs管控的重點源,尤其要重點加強北部工業企業和機動車排放源管控.

揮發性有機物(VOCs)；污染特征；臭氧生成潛勢(OFP)；來源解析

大氣臭氧(O3)已經成為夏季影響我國城市環境空氣質量的首要污染物[1-4],其主要前體物為揮發性有機物(VOCs)和氮氧化物(NO)[5].北京、天津、長治等多城市O3敏感性分析指示城區O3多為VOCs主控區[6-9],準確識別VOCs來源對于大氣O3污染防控至關重要.

VOCs組分眾多、來源復雜,控制難度較大[10].研究表明,汽車尾氣、煤炭燃燒和液化石油氣/天然氣(LPG/NG)是北京市VOCs重要源,且其貢獻隨環保管控政策的實施呈明顯時間變化,隨著燃煤管控實施,燃煤源對VOCs貢獻從2014年26.3%～45.1%,下降到2016年22.3%,同時汽車尾氣貢獻呈上升趨勢,從44.1%上升至50.0%[11-13].此外,城市產業布局也對VOCs有重要影響.雄安市拉鏈加工、油墨印刷、聚乙烯吹膜行業排放的苯系物OFP貢獻率分別為80.87%、89.63%、85.97%[14].除本地排放外,VOCs還受到區域傳輸的影響.上海市VOCs區域傳輸貢獻為22.1%～41.9%,且呈現上升趨勢[15]. VOCs及O3污染區域聯防聯控的需求愈加強烈和迫切.

晉城市位于山西省東南部,主要產業為煤炭、鋼鐵、煤化工、焦化、水泥等,是典型的重工業型城市. 2019～2022年晉城市O3濃度分別為201μg/m3, 176μg/m3,180μg/m3,181μg/m3,近年來夏季O3污染形勢嚴峻,且常與河北南部、河南北部、山東西南部城市構成區域性O3污染.本研究以晉城市O3污染較重的夏季(2022年6月)為研究時段,采集大氣VOCs樣品,解析不同主導風向下晉城市VOCs污染特征、主要來源及O3生成潛勢,為晉城市大氣VOCs及O3污染防控提供科學依據.

1 材料與方法

1.1 樣品采集

晉城市是山西省東南部重要的重工業城市,與河南、山東等區域接壤,其地理位置及大氣VOCs采樣點位如圖1所示.大氣VOCs樣品采集點位為國家空氣質量監測站點(E112.863539,N35.493759),該采樣點位于晉城市區人群密集處,能夠較好反映晉城市區VOCs污染特征及人群健康影響.

采樣時間為2022年6月1日～31日,其中5d為O3清潔天,26d為O3污染天,采集設備為國家VOCs組分站在線監測設備,采樣時間分辨率為1h,每天24個樣品.采樣期間,同步記錄當日的溫度、風速、風向等氣象條件.

圖1 晉城市地理位置及大氣VOCs采樣點分布

1.2 數據預處理

將VOCs組分數據按濃度從小到大排序,當VOCs組分數據濃度大于MAX或者小于MIN時,認定其為離群值[16],MAX及MIN計算如式(2)和(3).除去離群值后共得到有效VOCs數據589組,將小時VOCs數據與氣象數據對應共同用于污染特征分析.

式中:為第25百分位數;為第75百分位數;為第25百分位數與第75百分位數差值的絕對值; MAX為最大范圍;MIN為最小范圍.

1.3 研究方法

1.3.1 臭氧生成潛勢 VOCs作為O3前體物,其O3生成潛勢受VOCs濃度、反應活性和氣象條件等因素共同影響.Carter[17]提出最大增量反應活性(MIR)概念來評估理想條件下VOCs物種通過化學反應產生O3的能力,計算公式為:

式中:OFP指第個VOCs物種的臭氧生成潛勢,μg/m3;MIR指第個VOCs物種的最大增量反應系數,以O3/VOCs計,g/g,不同組分的MIR值見文獻[17].

1.3.2 PMF模型 正定矩陣因子分析模型(PMF)是一種多變量因子分析模型,?；诖髿釼OCs組分觀測數據用于VOCs來源解析[18].PMF模型計算原理由式(5)給出,樣本數據的不確定度由式(6)計算.

式中:E為次觀測的污染物的濃度;為因子;A和B分別表示源成分譜和源貢獻;ε為殘差;為樣本的不確定度;為誤差比例;為VOCs種類的實測濃度;為VOCs種類的檢出限.在PMF模型的源分配中,目標函數采用迭代最小化算法求解,且值必須盡可能小.目標函數定義在式(7)中.

式中:σ表示樣本的不確定偏差.

1.3.3 HYSPLIT4模式 除本地排放外,VOCs污染也會受到區域污染物傳輸的影響.本研究針對晉城市夏季典型O3污染過程,采用混合單顆粒拉格朗日積分軌跡(HYSPLIT)計算氣團軌跡,追蹤VOCs區域污染來源[19-21].采用Meteoinfo軟件中的HYSPLIT模型,模擬了觀測內500m高度到達采樣點的48h后軌,聚類分析了不同觀測周期下氣團軌跡的來源方向[22].

CWT方法基于污染物濃度對軌跡進行加權,定量反映軌跡的濃度貢獻.本研究采用CWT法對晉城市VOCs潛在源區進行劃分,將研究區域劃分為0.2°× 0.2°網格單元陣列.CWT由以下式確定:

式中:C為單元中后向軌跡的平均權重濃度;C是軌跡對應的VOCs濃度;t是軌跡在單元中停留的時間;權重函數(n)用于減少不確定性;n代表單元中端點的數量,ave為每個網格的平均軌跡端點數.

2 結果與討論

2.1 晉城市夏季VOCs及組分特征

共分析56種VOCs組分,其中烷烴29種、芳香烴16種、烯烴10種、炔烴1種.將風向角度為90°～270°的風定義為偏南風,風向角度為0°～90°和270°～360°的風定義為偏北風.觀測期間,偏南風出現的頻數為402,頻率為55.8%;偏北風出現的頻數為318,頻率為44.2%.如圖2所示,晉城市夏季偏北風向下總VOCs平均質量濃度為(33.3±17.3)μg/m3,其中烷烴和芳香烴含量最高,分別為(21.1±12.4)和(7.4±4.5)μg/m3,占比為63.4%和22.1%;烯烴和炔烴含量偏低,分別為(2.9±1.4)和(1.9±1.6)μg/m3,占比為8.7%和5.8%.其中,濃度較高的VOCs化合物主要有異戊烷、乙烷、丙烷、正丁烷、苯、甲苯、乙炔、正戊烷、乙烯、異丁烷等,以異戊烷和乙烷濃度最高,分別為(4.0±3.6)和(3.9±1.4)μg/m3.偏南風作用時晉城市總VOCs平均質量濃度(19.4±7.1)μg/m3,約比偏北風作用下低41.7%,其中烷烴和芳香烴含量依然最高(占比60.9%和18.0%,烯烴和炔烴含量偏低(占比11.7%和9.4%),濃度最高的VOCs化合物為乙烷和丙烷.南風和北風作用下晉城市VOCs組分占比表明,偏北風向下工業源、燃燒源和溶劑使用源對晉城市區VOCs的影響更大.

晉城市夏季VOCs濃度組成與國內其他城市比較見表１.晉城市VOCs濃度顯著低于鄭州、成都、陽泉等地,與北京、天津、太原接近,VOCs濃度水平較低.從組分看,天津、鄭州和太原等城市與晉城市烷烴占比相當.相關研究表明,烷烴主要來自機動車尾氣排放、油氣揮發以及燃燒[23].晉城市烯烴占比與北京、鄭州接近,其中乙烯濃度貢獻較高,乙烯等烯烴類物質主要來自機動車排放、燃燒和溶劑使用[24].炔烴所包括的物質主要為乙炔,乙炔是燃燒源的指示物種[25],晉城市炔烴的占比明顯高于其他城市,表明燃燒源對晉城市VOCs的貢獻較大.晉城市芳香烴占比相對較低,與天津、太原和陽泉相當,芳香烴主要來自溶劑使用源[26],其揮發性會隨著溫度上升增強.

圖2 偏北風和偏南風下晉城大氣VOCs排名前10物種

表1 晉城市夏季VOCs濃度組成與國內其他城市比較

圖3 晉城市夏季大氣VOCs各組分OFP及貢獻率

臭氧生成潛勢(OFP)可定量反映VOCs組分對O3生成的貢獻,南風和北風風向下OFP值分別為(50.5±17.1)和(84.30±44.0)μg/m3,各組分貢獻均為烯烴>烷烴>芳香烴>炔烴,且北風風向下烷烴、芳香烴和烯烴OFP值均高于南風,炔烴相差不大(見圖3).

偏北風向下晉城市TVOC、烷烴、烯烴、芳香烴、OFP生成濃度及NO小時濃度高于偏南風向,尤其早晚間和交通流高峰時段較為顯著(見圖4(a)、4(b)和4(h)),而南風風向下各VOCs組分及OFP變化較小,一定程度指示了北部工業園區和機動車排放源對市區影響較為突出.

值得注意的是,不同風向下的O3濃度則呈相反趨勢,偏南風作用下晉城市O3小時濃度均高于偏北風作用下(圖4(c)),表明除本地生成的O3外,南部可能存在較多的區域污染物傳輸貢獻.

圖4 偏北風和南風下晉城市大氣主要污染物小時濃度變化特征

2.2 VOCs來源解析

2.2.1 比值分析 苯和甲苯比值(B/T)常用來分析大氣中VOCs的主要來源,當B/T值<0.2、0.2～1、1～1.5、1.5～2.2和>2.5時,分別指示大氣中VOCs受溶劑使用源、機動車排放源、燃燒源、燃煤和生物質燃燒的影響較大[33-35].雖然苯、乙苯和間對二甲苯具有一定的同源性,但在大氣中的老化速度有明顯差異,二甲苯與自由基的反應速度約為乙苯的3倍,因此可用乙苯與間/對-二甲苯的比值(E/X)或苯與間/對-二甲苯比值(B/X)來判斷氣團的壽命[36].當E/X>0.33或B/X>1.7時,初步判斷該區域氣團老化程度較大[31,37].異戊烷與正戊烷在大氣中的存活時間相似,通過其比值(I/N)可初步分析VOCs的可能來源.我國隧道實驗和汽油揮發I/N值分別為2.9和3.8,而燃煤源I/N值介于0.56～0.8[38-39],當I/N值在3.1左右時VOCs主要來源于汽車和工業共同排放,通常是由工業油氣的逸散揮發、機動車尾氣和蒸發損失等原因引起[40].

2022年夏季南風風向下晉城市B/T在0.4～3.3之間,平均值為(1.0±0.5);北風風向下為0.2～6.2,平均值為(1.4±0.9),初步判斷南風風向下VOCs排放受機動車排放和燃燒源的影響較大,北風風向下受燃燒源的影響較大,且燃燒源中燃煤源的影響較大.南風和北風風向下E/X分別在0.3～1.2和0.2～0.8,均值分別為(0.5±0.1)和(0.4±0.1);B/X分別在0.3～13.0和0.2～15.6,均值分別為(3.0±2.3)和(2.8±2.2),采樣期間位于夏季且晴天居多,VOCs反應較快,加之區域傳輸的作用,因而初步判斷晉城市環境空氣中VOCs受老化氣團控制.南風風向下I/N在1.6～6.5之間,北風風向下在1.3～5.5之間,平均值分別為(2.5±0.4)和(2.5±0.5),判斷晉城市VOCs受汽油揮發的影響較大.綜上,不同風向下B/T、E/X、B/X和I/N值結果較為接近,初步研判為VOCs排放主要受汽油揮發、機動車排放及燃燒源影響.

2.2.2 PMF分析 采用PMF5.0模型對晉城市區環境空氣VOCs進行定量來源解析,最終選取源指示性較強和較穩定的34種VOCs參與模型運算.因子1中載荷貢獻最大的物種是異戊二烯,認作植物排放源[41].因子2中載荷較大的物種有乙烷、丙烷、異戊烷、正丁烷、甲苯、苯、乙苯、間對二甲苯等,認作機動車排放源[42-43].因子3中,鄰、間、對二甲苯、1,2,4-三甲基苯、1,2,4-三甲基苯等物種載荷貢獻較高,認作溶劑使用源[44-45].乙烷、丙烷除天然氣和液化石油氣揮發外,燃燒源中也有排放,丙烯等C2～C4烯烴也來自于燃煤,乙炔和乙烯是燃煤源示蹤劑,故因子4是主要來自于工業燃煤的燃燒源[43].因子5中載荷貢獻較大的物種除C2～C6等短鏈烴外,還有甲苯、乙苯和間/對-二甲苯等芳香烴,這些物種通常是鋼鐵、焦化、煤化工等行業在產品生產中的排放,故因子5認作工業源[46].

經計算(圖6),南風風向下晉城市夏季VOCs排放主要來源為燃燒源(28.7%)、機動車排放源(26.1%)和工業源(23.2%),北風風向下主要為工業源(31.4%)、機動車排放源(31.1%)和燃燒源(22.5%).因此,燃燒源、機動車排放源和工業源是晉城市VOCs管控的重點源,北風時尤其要重點加強北部工業企業排放和北部機動車排放源管控.

圖6 不同風向下晉城大氣VOCs來源貢獻

2.3 區域傳輸對晉城市VOCs影響分析

對2022年晉城市夏季典型O3污染過程進行6h后向軌跡模擬分析,共589條氣團軌跡.氣團聚類獲得4條典型污染路徑(圖7(a)).路徑1為西北路徑,經內蒙古、陜西北部南下進入晉城,包含276條氣團軌跡,占所有軌跡的46.9%;路徑2為正南路徑,氣團由河南沿正北向上,占26.1%;路徑3為東南路徑,從安徽北部進入河南,占11.4%;路徑4為偏東路徑,起源于京津冀地區由偏南回流引起,比例為15.6%.路徑1～4平均VOCs濃度分別為30.0,24.4,29.0和19.6μg/m3,表明西北方向氣團和東南路徑氣團對城市VOCs影響最大,其次為正南路徑.

CWT定量解析結果表明,晉城市大氣VOCs強潛在源區集中在晉城本地北部區域和東南部與焦作接壤區域(圖7(b)),一方面印證了北部工業企業及機動車排放源是晉城市VOCs主要來源,另一方面也定量展示了河南北部區域存在強潛在源區,其對晉城市夏季VOCs貢獻率約為25.3%.

3 結論

3.1 偏南風和偏北風主導時晉城市VOCs濃度分別為(19.4±7.1)和(33.3±17.3)μg/m3,后者較前者高近70%;不同風向下各組分貢獻均為烷烴>芳香烴>烯烴>炔烴,偏北風時烷烴和芳香烴濃度顯著高于偏南風時,炔烴濃度相仿.

3.2 偏南風和偏北風時晉城市OFP值分別為(50.5±17.1)和(84.3±44.0)μg/m3;不同風向下各組分貢獻均為烯烴>烷烴>芳香烴>炔烴;北風風向下各VOCs組分及OFP變化較大,尤其早晚間和交通流高峰時段較為顯著,南風時變幅較小,北部工業園區和北部機動車排放源對市區影響較為突出.

3.3 偏北風和偏南風時晉城大氣VOCs均受老化氣團控制;不同風向下OFP及實際O3小時濃度變化呈相反趨勢,除晉城本地排放外,河南北部接壤區域存在強潛在源區,其對晉城市夏季VOCs貢獻率約為25.3%.

3.4 燃燒源、機動車排放源和工業源是晉城市VOCs管控的重點源,尤其要重點加強北部工業企業排放和北部機動車排放源管控.

[1] Li K, Jacob D J, Liao H, et al. Anthropogenic drivers of 2013～2017 trends in summer surface ozone in China [J]. Proceedings of the National Academy of Sciences of the United States of America, 2019, 116(2):422-427.

[2] Lu X, Zhang L, Wang X, et al. Rapid Increases in warm-season surface ozone and resulting health impact in China since 2013 [J]. Environmental Science & Technology Letters, 2020,7(4):240-247.

[3] 楊 俊,布 多,劉 君,等.我國城市臭氧污染防治現狀研究綜述[J]. 環境與可持續發展, 2022,47(4):86-90.Yang J, Bu D, Liu J, et al.Research review on urban ozone pollution control in China [J]. Environment and sustainable development, 2020,7(4):240-247.

[4] 陳多宏,沈 勁,陳瑤瑤,等.2020年珠三角區域臭氧污染特征及主要成因分析[J/OL]. 中國環境科學, 2022,DOI:10.19674/ j.cnki.issn1000-6923.20220616.007. Chen D H, Shen J, Chen Y Y, et al. Characteristics and main causes of ozone pollution in the pearl river delta in 2020 [J/OL]. China Environmental Science, 2022,DOI:10.19674/j.cnki.issn1000-6923. 20220616.007.

[5] 崔虎雄,吳迓名,高 松,等.上海城區典型污染過程VOCs特征及臭氧潛勢分析[J]. 環境科學, 2011,32(12):3537-3542. Cui H X, Wu Y M, Gao S, et al. Characteristics of ambient VOCs and their role in O3formation: a typical air pollution episode in Shanghai urban area [J]. Environmental Science, 2011,32(12):3537-3542.

[6] Zhang X, Li H, Wang X Z, et al. Heavy ozone pollution episodes in urban Beijing during the early summertime from 2014 to 2017: Implications for control strategy [J]. Environmental Pollution, 2021, DOI:10.1016/j.envpol.2021.117162.

[7] 張 蕊,孫雪松,王 裕,等.北京市城區夏季大氣VOCs變化特征及臭氧生成潛勢[J]. 環境科學, 2023,44(4):1954-1961. Zhang R, Sun X S, Wang Y, et al. Variation characteristics and ozone formation potential of ambient VOCs in urban Beijing in summer [J]. Environmental Science, 2023,44(4):1954-1961.

[8] 陳澤鑫,古金霞,霍光耀,等.天津市揮發性有機物污染特征與來源及其O3生成潛勢[J]. 環境污染與防治, 2022,44(2):201-205. Chen Z X, Gu J X, Huo G Y, et al.Pollution characteristics and sources of volatile organic compounds and their O3formation potential in Tianjin [J]. Environmental Pollution & Control, 2022,44(2):201- 205.

[9] 張翔宇.長治市環境空氣中揮發性有機物來源解析及環境影響研究[D]. 北京:華北電力大學, 2022. Zhang X Y. Source analysis and environmental impact study of volatile organic compounds in Changzhi [D]. Beijing: North China Electric Power University, 2022.

[10] Atkinson R, Arey J. Atmospheric degradation of volatile organic compounds [J]. Chemical Reviews, 2003,103(12):4605-4638.

[11] Li J, Xie S D, Zeng L M, et alCharacterization of ambient volatile organic compounds and their sources in Beijing, before, during, and after Asia-Pacific Economic Cooperation China 2014 [J]. Atmospheric Chemistry and Physics, 2015,15(14):7945-7959.

[12] Shi Y Q, Xi Z Y, Simayi M, et al. Scattered coal is the largest source of ambient volatile organic compounds during the heating season in Beijing [J]. Atmospheric Chemistry and Physics, 2020,20(15):9351- 9369.

[13] Yang W Q, Zhang Y L, Wang X M, et al. Volatile organic compounds at a rural site in Beijing: influence of temporary emission control and wintertime heating [J]. Atmospheric Chemistry and Physics, 2018, 18(17):12663-12682.

[14] 王學臣,王 帥,劉大喜,等.典型工業源揮發性有機物排放特征及臭氧生成潛勢分析[J]. 環境污染與防治, 2020,42(11):1387-1391. Wang X C, Wang S, Liu D X, et al. VOCs emission characteristics and ozone formation potential analysis of typical industrial sources [J]. Environmental Pollution & Control, 2020,42(11):1387-1391.

[15] Liu Y H, Wang H L, Jing S G, et al. Strong regional transport of volatile organic compounds (VOCs) during wintertime in Shanghai megacity of China [J]. Atmospheric Environment, 2021,244,117940.

[16] Frigge M, Hoaglin D C, Iglewicz B. Some Implementa- tions of the Boxplot [J]. The American Statistician, 1989,43:50-54.

[17] Carter W P L. Development of ozone reactivity scales for volatile organic compounds [J]. Air & Waste, 1994,44(7):881-899.

[18] Norris G, Duvall R, Brown S, et al． EPA positive matrix factorization (PMF) 5.0 fundamentals and user guide [R]. Washington, DC, USA: EPA, 2014.

[19] 徐祥德,周 麗,周秀驥,等.城市環境大氣重污染過程周邊源影響域[J]. 中國科學:地球科學, 2004,34(10):958-966. Xu X D, Zhou L, Zhou X J, et al. The influence domain of the surrounding sources in the process of heavy atmospheric pollution in urban environment [J]. Scientia Sinica(Terrae), 2004,34(10):958-966.

[20] 王 茜.利用軌跡模式研究上海大氣污染的輸送來源[J]. 環境科學研究, 2013,26(4):357-363. Wang Q. Study of air pollution transportation source in shanghai using trajectory model [J]. Research of Environmental Sciences, 2013,26(4): 357-363.

[21] Wang Y. Q, Zhang X Y, Draxler R R. TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data [J]. Environmental Modelling & Software, 2009,24(8):938-939.

[22] Davis R E, Normile C P, Sitka L, et al. A comparison of trajectory and air mass approaches to examine ozone variability [J]. Atmospheric Environment, 2010,44(1):64-74.

[23] 陸嘉暉,吳 影,劉慧琳,等.南寧市冬季揮發性有機物特征及其來源分析[J]. 中國環境科學, 2022,42(8):3616-3625. Lu J H, Wu Y, Liu H L, et, al.Characteristics and sources of volatile organic compounds (VOCs) in winter over Nanning of China [J]. China Environmental Science, 2022,42(8):3616-3625.

[24] 鄧思欣,劉永林,司徒淑娉,等.珠三角產業重鎮大氣VOCs污染特征及來源解析[J]. 中國環境科學, 2022,41(7):2993-3003. Deng S X, Liu Y L, Situ S P, et, al.Characteristics and source apportionment of volatile organic compounds in an industrial town of Pearl River Delta. [J]. China Environmental Science, 2022,41(7): 2993-3003.

[25] 馬 靜,燕瑩瑩,孔少飛,等.武漢軍運會前后臭氧及其前體物的特征和來源[J]. 中國環境科學, 2022,42(7):3023-3032. Ma J, Yan Y Y, Kong S F, et, al.Characteristics and sources of ozone and its precursors around the Wuhan Military Games [J]. China Environmental Science, 2022,42(7):3023-3032

[26] 張浩然,劉 敏,王小嫚,等.南昌市2021年春季大氣VOCs污染特征和來源分析[J]. 中國環境科學, 2022,42(3):1040-1047. Zhang H R, Liu M, Wang X M, et, al.Characteristics and sources of atmospheric VOCs during spring of 2021in Nanchang [J]. China Environmental Science, 2022,42(3):1040-1047.

[27] Zhang L H, Li H, Wu Z H, et al. Characteristics of atmospheric volatile organic compounds in urban area of Beijing: Variations, photochemical reactivity and source apportionment[J]. Journal of Environmental Sciences (China), 2020,95:190-200.

[28] 王文美,高璟赟,肖致美,等.天津市夏季不同臭氧濃度級別VOCs特征及來源[J]. 環境科學, 2021,42(8):3585-3594. Wang W M, Gao J Y, Xiao Z M, et al. Characteristics and sources of VOCs at different ozone concentration levels in Tianjin [J]. Environmental Science, 2021,42(8):3585-3594.

[29] 齊一謹,王玲玲,倪經緯,等.鄭州市夏季大氣VOCs污染特征及來源解析[J]. 環境科學, 2021,43(12):5429-5441. Qi Y J, Wang L L, Ni J W, et al.Characteristics and source apportionment of ambient summer volatile organic compounds in Zhengzhou, China [J]. Environmental Science, 2021,43(12):5429- 5441.

[30] 司雷霆,王 浩,李 洋,等.太原市夏季大氣VOCs污染特征及臭氧生成潛勢[J]. 中國環境科學, 2019,39(9):3655-3662. Si L T, Wang H, Li Y, et al. Pollution characteristics and ozone formation potential of ambient VOCs in summer in Taiyuan [J]. China Environmental Science, 2019,39(9):3655-3662.

[31] 牛月圓,劉倬誠,李如梅,等.陽泉市區夏季揮發性有機物污染特征、來源解析及其環境影響 [J]. 環境科學, 2020,41(7):3066-3075. Niu Y Y, Liu Z C, Li R M, et al. Characteristics, source apportionment, and environmental lmpact of volatile organic compounds in summer in Yangquan [J]. Environmental Science, 2020,41(7):3066-3075.

[32] 徐晨曦,陳軍輝,韓 麗,等.成都市2017年夏季大氣VOCs污染特征、臭氧生成潛勢及來源分析 [J]. 環境科學研究, 2019,32(4):619- 626. Xu C X, Chen J H, Han L, et al. Analyses of pollution characteristics, ozone formation potential and sources of VOCs atmosphere in Chengdu city in summer 2017[J]. Research of Environmental Science, 2019,32(4):619-626.

[33] 張翼翔,尹沙沙,袁明浩,等.鄭州市春季大氣揮發性有機物污染特征及源解析[J]. 環境科學, 2019,40(10):4372-4381. Zhang Y X, Yin S S, Yuan M H, et al.Characteristics and source apportionment of ambient VOCs in spring in Zhengzhou [J]. Environmental Science, 2019,40(10):4372-4381.

[34] 張 棟,于世杰,王 楠,等.鄭州市冬季VOCs污染特征、來源及健康風險評估[J]. 環境科學學報, 2020,40(8):2935-2943. Zhang D, Yu S J, Wang N, et al. Characteristics, sources and health risk assessment of ambient VOCs in winter of Zhengzhou [J]. Acta Scientiae Circumstantiae, 2020,40(8):2935-2943.

[35] Liu Y F, Kong L W, Liu X G, et al. Characteristics, secondary transformation, and health risk assessment of ambient volatile organic compounds (VOCs) in urban Beijing, China [J]. Atmospheric Pollution Research, 2021,12(3):33-46.

[36] Hui L R, Liu X G, Tan Q W, et al. VOC characteristics, sources and contributions to SOA formation during haze events in Wuhan, Central China [J]. Science of The Total Environment, 2019,650(2):2624-2639.

[37] Yurdakul S, Civan M, Kuntasal ?, et al. Temporal variations of VOC concentrations in Bursa atmosphere [J]. Atmospheric Pollution Research, 2018,9(2):189-206.

[38] 聶 燁,彭 瑾,王祖武,等.黃石市大氣揮發性有機物污染特征及源解析[J]. 環境科學與技術, 2021,44(S1):183-190. Nie Y, Peng J, Wang Z W, et al. Pollution characteristics, ozone formation potential, and sources of atmospheric volatile organic compounds in huangshi [J]. Environmental Science & Technology, 2021,44(S1):183-190.

[39] Zheng H, Kong S F, Xing X L, et al. Monitoring of volatile organic compounds (VOCs) from an oil and gas station in Northwest China for 1year [J]. Atmospheric Chemistry and Physics, 2018,18(7):4567- 4595.

[40] Bari M A, Kindzierski W B. Ambient volatile organic compounds (VOCs) in Calgary, Alberta: Sources and screening health risk assessment [J]. Science of The Total Environment, 2018,631-632: 627-640.

[41] Hui L R, Liu X G, Tan Q W, et al. Characteristics, source apportionment and contribution of VOCs to ozone formation in Wuhan, Central China [J]. 2018,192:55-71.

[42] Mo Z W, Shao M, Lu S H. Compilation of a source profile database for hydrocarbon and OVOC emissions in China [J]. Atmospheric Environment, 2016,143:209-217.

[43] Song Y, Shao M, liu Y, et al. Source apportionment of ambient volatile organic compounds in Beijing [J]. Environmental Science & Technology, 2007,41(12):4348-4353.

[44] Zhong Z M, Sha Q E, Zheng J Y, et al. Sector-based VOCs emission factors and source profiles for the surface coating industry in the Pearl River Delta region of China [J]. Science of The Total Environment, 2017,583:19-28.

[45] Cai C J, Geng F H, Tie X X, et al. Characteristics and source apportionment of VOCs measured in Shanghai, China [J]. Atmospheric Environment, 2010,44(38):5005-5014.

[46] 王鐵宇,李奇鋒,呂永龍.我國VOCs的排放特征及控制對策研究[J]. 環境科學, 2013,34(12):4756-4763. Wang T Y, Li Q F, LV Y L. Characteristics and countermeasures of volatile organic compounds (VOCs) emission in China [J]. Environmental Science, 2013,34(12):4756-4763.

Characteristics and sources of atmospheric VOCs pollution in Jincheng.

ZHANG Peng-hui1, HU Dong-mei1*, PENG Lin2, NIU Wei-li3, GONG Xing-xiao4, YAN Yu-long2, NIU Yue-yuan1, DONG Jia-qi1

(1.Key Laboratory of Resources and Environmental System Optimization, Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China；2.School of the Environment, Beijing Jiaotong University, Beijing 100044, China；3.Jincheng Municipal Bureau of Ecology and Environment, Jincheng 048000, China；4.Jincheng Ecological Environment Monitoring Center of Shanxi Province, Jincheng 048000, China)., 2023,43(9)：4525～4533

Volatile organic compounds (VOCs) samples were collected at environmental sampling sites in Jincheng, and the characteristics of VOCs components under different wind direction were analyzed. The VOC sources were identified by diagnostic ratios and positive matrix factorization (PMF), the hybrid single-particle lagrangian integrated trajectory (HYSPLIT) was used to trace the contribute of typical contaminated areas in summer. The results showed that the average VOC concentration was (19.4 ±7.1) μg/m3under southerly wind, and (33.3±17.3) μg/m3under northerly wind.VOCs concentration in northerly wind was nearly 70% higher than that in southerly wind, and northern industrial park had a great impact on VOCs concentration in urban areas. The components concentration showed the characteristics ofalkane > aromatic > alkene >alkyne. The concentration of alkane and aromatic was significantly higher in the northerly wind than that in the southerly wind, and the concentration of alkyne was similar in different wind directions.The average concentration of ozone formation potential (OFP) was (50.5±17.1) μg/m3under southerly wind, and (84.30±44.0) μg/m3under northerly wind.Under different wind direction, the contribution of components showed the characteristics of alkene > alkanes > aromatics > alkynes. The hourly variation range of VOCs components and OFP under the north wind direction was significantly higher than that under the south wind direction,especially in the morning and evening and during the rush hour.The northern industrial park and the vehicular emissions had a prominent impact on the urban area.Atmospheric VOCs were controlled by aging air mass under northerly and southerly winds, and the changes of OFP and O3concentration showed the opposite trends under different wind directions.There was a strong potential source area in the northern border region of Henan, and its percentage contribution to Jincheng summer VOCs was about 25.3%.Local combustion, vehicular emissions and industrial process were the key sources of VOCs control in Jincheng, especially to strengthen the control of industrial and vehicular emissions in the northern region of Jincheng City.

volatile organic compounds (VOCs)；pollution characteristics；ozone formation potential (OFP)；source apportionment

X511

A

1000-6923(2023)09-4525-09

張鵬輝(1997-),男,山西晉城人,碩士研究生,主要從事大氣污染防治研究.發表論文1篇.2445757400@qq.com.

張鵬輝1,胡冬梅1*,彭 林,等.晉城市大氣VOCs污染特征及來源解析 [J]. 中國環境科學, 2023,43(9):4525-4533.

Zhang P H, Hu D M, Peng L, et al. Characteristics and sources of atmospheric VOCs pollution in Jincheng [J]. China Environmental Science, 2023,43(9):4525-4533.

2023-02-17

大氣重污染成因與治理攻關項目(DQGG202109);國家重點研發計劃項目(2019YFC0214203,2019YFC0214202);國家自然科學基金資助項目(21976053)

* 責任作者, 副教授, huhu3057@163.com