,1, 肖舜,1, 董治宝1, 曹军骥2, 张宁宁2, 刘随心2, 沈振兴3, 徐红梅3, 陶燕4, 李星敏5, 王鑫1, 王雨萌1Characteristics and health risk of polycyclic aromatic hydrocarbons in PM2.5 in the typical urban and rural areas of the Fenwei Plain
CAI Ruiting,1, XIAO Shun,1, DONG Zhibao1, CAO Junji2, ZHANG Ningning2, LIU Suixin2, SHEN Zhenxing3, XU Hongmei3, TAO Yan4, LI Xingmin5, WANG Xin1, WANG Yumeng1通讯作者:
收稿日期:2020-01-3修回日期:2020-12-20网络出版日期:2021-03-25
| 基金资助: |
Received:2020-01-3Revised:2020-12-20Online:2021-03-25
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作者简介 About authors
蔡瑞婷(1994-), 女, 陕西宝鸡人, 硕士, 研究方向为大气污染与环境健康。E-mail:
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蔡瑞婷, 肖舜, 董治宝, 曹军骥, 张宁宁, 刘随心, 沈振兴, 徐红梅, 陶燕, 李星敏, 王鑫, 王雨萌. 汾渭平原典型城乡PM2.5中多环芳烃特征与健康风险. 地理学报[J], 2021, 76(3): 740-752 doi:10.11821/dlxb202103017
CAI Ruiting, XIAO Shun, DONG Zhibao, CAO Junji, ZHANG Ningning, LIU Suixin, SHEN Zhenxing, XU Hongmei, TAO Yan, LI Xingmin, WANG Xin, WANG Yumeng.
1 引言
大气污染对人体健康与气候变化的影响已经成为不争的事实[1,2]。世界卫生组织（WHO）将“室外大气污染”列入1类致癌物清单,并视其为普遍和主要的环境致癌物。据2019年联合国国家规划署（UNEP）最新报道,全世界每年约700万人因空气污染过早死亡,其中有60万儿童死于由污染空气诱发的急性下呼吸道感染,1/3的脑卒中、慢性阻塞性肺病和心脏病由大气污染引起[3,4,5]。众所周知,PM2.5是大气霾污染的主要成分,其空气动力学等效粒径≤ 2.5 μm,颗粒表面形态结构复杂且比表面积大[6],利于富集环境空气中毒害组分进而穿透肺部参与全身血液循环引发一系列心脑血管疾病。有研究表明高浓度PM2.5暴露会引发人体血压上升、心律失常,产生中风、急性心梗、动脉粥样硬化等症状,且暴露时间越长,心血管疾病患者死亡率越高[7,8,9]。多环芳烃（PAHs）是富集于PM2.5中一类由两个或两个以上苯环连接而成的持久性有机污染物,半衰期较长,可随颗粒物在大气环境中长距离迁移扩散造成大范围持续性污染[10]。有****发现南北极和青藏高原等偏远清洁地区颗粒态气溶胶污染与大气环流形势密切相关[11,12,13],Wang等[14]通过对鲁朗高原观测站点持续监测发现受印度季风系统及南支西风带影响,南亚地区大气粉尘跨境传输是造成青藏高原东南缘大气PAHs浓度水平呈现夏季低冬季高的主要原因。此外PAHs对人体健康影响也不容忽视,国内外大量的流行病学统计研究显示[15,16,17],PAHs吸入性暴露是大气污染诱发肺癌的主要因素,长期接触PAHs还会导致免疫力低下、DNA和肝脏损伤及白内障等症状,孕妇接触PAHs可能造成早产、胎儿畸形及发育迟缓等严重后果。迄今为止发现的PAHs有200多种,其中以苯并芘（BaP）为首的16种PAHs因具有致畸、致癌、致突变性的“三致效应”而被美国环保署（US EPA）列入优控名单[18]。有关空气污染及其具有显著致癌作用的大气有机化学成分研究目前已经成为国内外大气污染与环境健康领域关注的热点问题,针对大气环境中PAHs的研究主要集中在污染物形态、迁移转化及归趋、人群环境健康暴露风险等多个方面[19,20,21]。研究表明全球PAHs三大主要来源为住宅区生物质燃烧、野外生物质燃烧及机动车尾气排放,其中亚洲地区年均贡献量最大,占据全球PAHs总排放量50%以上[22]。通过对欧洲与亚洲地区学校环境暴露研究发现亚洲儿童学校环境PAHs暴露程度高于欧洲儿童,且居住于工业区的儿童其体内PAHs代谢产物含量远高于郊区等其他功能区生活的儿童[23]。中国城市与农村大气污染问题由来已久,受到了政府和公众的广泛关注,数据显示[24,25],96%的中国人口PM2.5暴露程度超过世界卫生组织规定的年均浓度限值（35 μg/m3）,每年约120万人因大气污染过早死亡。随着城市化步入快速发展阶段,中国大气污染已由单纯煤烟型污染转化为复合型污染[26],国内****针对大气PAHs不同区域、季节差异及人群健康等特征开展了卓有成效的研究工作。有****对北京雾霾期不同功能区大气PAHs研究表明农村及郊区人群PAHs暴露水平高于市区,且城郊两区人群均存在BaP致癌风险[27];而通过对上海地区PM2.5中PAHs污染特征研究发现机动车尾气排放及煤燃烧是上海市大气环境中PAHs主要来源,且冬季PAHs浓度与温度、相对湿度呈负相关而在其他季节则无明显相关性[28];对成都地区2009—2016年连续7年PM10中PAHs污染状况分析表明工业源是丰水期PAHs呈现高浓度的主要因素,而燃烧源对干旱期PAHs有较大贡献,且控制汽车尾气尤其是柴油车尾气排放对降低PAHs致癌风险有显著作用[29]。
汾渭平原地处黄土高原东南缘,大气细颗粒黄土背景粉尘浓度偏高,由于受到东亚冬季风和西风环流的共同影响,该区域霾污染天气的产生与大气环流背景密切相关[30]。近年来全国大气污染水平总体减缓,但由于汾渭平原是中国焦炭及原煤主产区,重工业、焦化等高耗能高污染行业占主要地位,煤炭在能源消费中占比近90%,结合不利于污染物扩散的盆地地形配置,导致汾渭平原大气污染居高不下。2018年汾渭平原平均大气质量优良天数仅占全年54.6%,远低于79.3%的全国平均优良天数占比,汾渭平原11个城市在全国空气质量排名末位20城市中所占数量由2015年的0个增至6个,成为仅次于京津冀的第二大污染区,同年被列入国家大气污染防治三大重点区域之一[31]。目前国内大气PAHs研究报道较多集中在京津翼、长三角、珠三角等东部经济发达地区,对新增重污染区汾渭平原的研究报道较少,故本文以汾渭平原典型城乡地区为研究区分析PM2.5中多环芳烃污染特征及人体健康风险,以期为该地区大气污染治理提供科学依据。
2 材料与方法
2.1 研究区域及样品采集
西安作为汾渭平原的核心城市,是唯一布局在中国西北地区的国际化大都市和国家中心城市,截至2018年年底西安市常住人口达到1000.37万,机动车保有量达330万[32],随着城市化及工业化的快速发展,大气污染已成为西安市首要环境问题,故本文选取西安作为汾渭平原城市研究区域。农村采样点位于汾渭平原最西部的宝鸡市陇县,该地区冬季采暖方式主要以燃煤及生物质秸秆燃烧为主,是中国典型的以固体燃料为主要能源结构的北方农村,可有效代表汾渭平原农村地区大气现状。城市采样点位于陕西师范大学长安校区格物楼6层楼顶（距地面高度为20 m）,农村采样点位于陕西省宝鸡市陇县某村（距地面高度为5 m）（图1）。为分析重污染天气PM2.5中PAHs污染特征及其健康风险,本文按照中国《环境空气质量指数（AQI）技术规定（试行）》（HJ633-2012）规定[33],当200 ≤ AQI ≤ 300,视为重度污染天气,选取典型重污染时段共采集大气样品14份,其中西安样品10份,采样日期为2018年12月20日、2019年1月4—5日、11—14日、24日,2月18日、20日;陇县样品4份,采样日期为2019年2月11—13日、19日。
图1
新窗口打开|下载原图ZIP|生成PPT图1采样点位置图
Fig. 1Location of the sampling sites
西安与陇县PM2.5样品均使用美国Airmetrics MiniVol便携式空气采样器采集,额定流速为5 L/min,采样时长控制在23~24 h范围内。选用Whatman 47 mm石英纤维滤膜,滤膜在采样前需在马弗炉内450 ℃下烧灼5 h,经恒温恒湿方可称重,采样后样品用铝箔纸密封保存,保存温度低于4 ℃。同时为确保周边视野开阔且无污染物排放源干扰,将仪器架高至距楼顶地面1.5 m以上。
2.2 实验方法
本文使用中国科学院地球环境研究所气溶胶化学与物理重点实验室Sartorius百万分之一分析天平,使用国际通用的重量法计算PM2.5质量浓度。采用超声萃取法进行预处理,具体步骤为：将1/4滤膜置于装有20 mL二氯甲烷—正己烷混合液（体积比为1∶1）的样品瓶进行常温超声萃取30 min,共萃取3次;待萃取完成后,将萃取液转移到梨形瓶中使用旋转蒸发仪浓缩至0.5 mL左右;将浓缩后的少量样品提取液转移至经混合液洗脱后的Silica固相柱进行净化;最后将样品氮吹浓缩转至进样瓶,定容至1 mL,放于冰箱4 ℃以下冷藏保存待测。预处理后的样品采用气相色谱—质谱联用仪（GC-MS,Agilent）进行测样,色谱柱为DB-5MS（30 m×0.25 mm×0.25 μm）,以高纯度氦气作为载气（≥ 99.999%）,不分流进样1 μL,恒流流速为1 mL/min,质谱为全扫描模式。仪器运行条件为进样口温度为280 ℃,传输线温度为280 ℃,离子源温度为230 ℃。色谱柱升温程序为：进样口初始温度为70 ℃,保持3 min后以25 ℃/min的速度立即升温至150 ℃,再以3 ℃/min的速度升温至280 ℃保持5 min,最后升温至300 ℃保持10 min。16种优控PAHs分别为：萘（NaP）、苊烯（Acy）、苊（Ace）、芴（Fl）、菲（Phe）、蒽（Ant）、荧蒽（Flu）、芘（Pyr）、苯并[a]蒽（BaA）、屈（Chr）、苯并[b]荧蒽（BbF）、苯并[k]荧蒽（BkF）、苯并[a]芘（BaP）、二苯并[a, h]蒽（DBA）、苯并[g, h, i]苝（BghiP）、茚并[1, 2, 3-c, d]芘（IcdP）。
通过色谱保留时间与特征离子进行PAHs定性分析,使用外标法对目标化合物进行定量分析：将16种PAHs标准混合液配制浓度梯度为10 μg/mL、20 μg/mL、50 μg/mL、80 μg/mL、100 μg/mL的标准系列溶液,各取1 mL转移至进样瓶上机测样并绘制目标化合物标准曲线,其相关系数均大于0.99。
2.3 质量控制和质量保证
样品采集与分析过程中,所使用到的玻璃器皿均用无水乙醇冲洗3次;采样前后滤膜恒温恒湿称量至误差小于0.015 mg;5%的样品进行平行样测定分析,确保误差小于20%;每5个样品做一个空白加标,除NaP以外15种PAHs回收率均在75%~125%之间。故本文对NaP值不予讨论,15种PAHs方法检出限（MDL）为0.01~0.74 ng/m3。2.4 健康风险评价
健康风险评价将污染物与人体健康相联系,以风险度作为评价指标定量描述人群长期暴露在不利环境中所造成的健康危害[34]。人体暴露主要有饮食摄入、皮肤吸收、呼吸3个途径,本文核心为PM2.5中PAHs,故只考虑呼吸途径产生的健康风险。采用EPA推荐的BaP毒性当量法及终生致癌风险模型（ILCR）来评估西安与陇县PM2.5中PAHs对人体造成的健康危害。其中,毒性当量法是以BaP浓度作为参考值来表征其他PAHs组分的毒性,通过致癌等效系数计算出混合物的BaP等效毒性质量浓度（TEQ）,计算公式为[35]：式中：Ci为各单体PAHs浓度（ng/m3）;TEFi为各组分毒性等效因子;TEQ为毒性等效浓度（ng/m3）。
污染物通过呼吸途径引起的致癌风险采用ILCR模型来计算,公式为[36]：
式中：R为人群终身致癌超额危险度（无量纲）;Ci为毒性等效浓度（ng/m3）;IR为呼吸速率（m3/h）;EF为暴露频率（d/a）;ET为暴露时间（h/d）;ED为暴露持续时长（a）;CSF为吸入BaP致癌强度系数（mg/(kg d)）;BW为体重（kg）;AT为平均暴露时间（d）。
3 结果与讨论
3.1 污染特征
3.1.1 PM2.5与PAHs污染水平 采样期间以西安为代表的城市地区及以陇县为代表的西部农村地区PM2.5日均质量浓度如图2a所示,平均质量浓度为235.72 μg/m3,质量浓度变化范围为123.89~362.87 μg/m3,且采样期日均浓度均超出《环境空气质量标准》（GB3095-2012）二级浓度限值（75 μg/m3）[37],超标率为100%。重污染天气下西安PM2.5平均质量浓度为214.67 μg/m3,是标准限值的2.9倍,与国内其他城市相比较,该值高于北京市[38]重污染天气PM2.5质量浓度（141.3 μg/m3）,略低于济南城区[39]重污染天气PM2.5平均浓度（260 μg/m3）。而陇县在重污染天气下PM2.5平均质量浓度达到288.34 μg/m3,稍高于西安样品浓度,超出标准限值近4倍。图2
新窗口打开|下载原图ZIP|生成PPT图2重污染期间PM2.5、PAHs质量浓度及不同环数PAHs占比
Fig. 2Concentrations of PM2.5, PAHs and percentage of different rings PAHs during heavy polluted weather
城市与农村地区重污染天气PM2.5中PAHs平均质量浓度为348.24 ng/m3,范围在162.92~926.06 ng/m3之间。其中西安PAHs质量浓度平均值为243.78 ng/m3,该值高于广州市区[40]重污染期PM2.5中PAHs平均浓度（59.82 ng/m3）,但低于北京市（423.9 ng/m3）及南京市[41]（307.79 ng/m3）重霾期研究结果。陇县PAHs在重污染期均处于较高污染水平,平均质量浓度为609.39 ng/m3,是西安PAHs浓度含量的2.5倍。
由图2a可见采样期间西安2019年1月11—14日为研究时段持续时间较长的典型连续重污染过程,该时间段及2019年1月4—5日的重污染过程中PM2.5浓度表现出与PAHs基本一致的变化趋势（R2 = 0.68）。在持续时间较短的2018年12月20日、2019年1月24日、2月18日、20日等非连续重污染时段,PM2.5与PAHs浓度相关性水平则较低,这可能是由于城市地区污染源相对复杂,在不同时间段污染源类型及排放强度会发生变化,且在连续发生的重污染过程中污染物浓度较多受制于气象条件影响[42]。而陇县冬季污染物以供暖燃烧固体燃料排放为主,来源相对稳定[43],因此在2019年2月11—13日、19日重污染期PM2.5与PAHs浓度变化趋势一致,两者相关性系数高达0.92。此外,西安在2019年1月13日达到重污染期PM2.5和PAHs最高值,是由于当天为周末,市区人群活动量与机动车出行量均高于工作日;而陇县PM2.5与PAHs质量浓度最高值出现在2月11日,该日为阴历正月初七,处于当地春节社火民俗活动高峰期,大量烟花爆竹在当天燃放,人群活动丰富频繁。以上日期最高值也表明人为活动对于大气污染影响显著,是造成当地空气污染的主要因素。
3.1.2 PAHs组成特征 重污染天气下西安与陇县PM2.5中的低环（LMW,2~3环）、中环（MMW,4环）、高环（HMW,5~6环）PAHs分别为占总PAHs质量浓度的11%、34%、55%及4%、55%、41%（图2b）。其中西安PAHs以5~6环为主,4环次之,3环含量最低;而陇县则以4环为主,5~6环次之,同样3环占比最低。但西安3环及6环PAHs含量明显高于陇县,而4环PAHs低于陇县。环数占比的差异性除了与城乡地区污染源的不同有关外,也是由于随着PAHs苯环数及结构式复杂程度的增加,其化学性质愈加稳定,在大气中固—气相分配系数增大,使得中高环PAHs较多富集于细颗粒物上;另外,受冬季环境气温低,大气层稳定等多种气象因素影响,强挥发性的低环PAHs固相富集量降低,从而导致中高环PAHs含量在两地区均高于低环PAHs[44]。
西安各单体PAHs中含量最高的是BkF,平均质量浓度为35.20 ng/m3,Flu、BbF、Chr次之,而Ant含量最低,平均质量浓度为1.87 ng/m3（图3）。Flu为陇县重污染天气含量最高的PAHs单体,平均质量浓度为92.93 ng/m3,该值超出西安市重污染期Flu均值3倍多,有研究表明,高Flu值是煤炭燃烧源的象征[45],说明陇县煤炭使用率高是影响PM2.5中PAHs含量的重要因素。除Flu外,陇县Chr、Pyr、BbF含量也相对较高,分别占总PAHs的15%、14%、13%、13%,Acy和Ant含量较低,均仅占2%,而Acy、Ant是石油源及自然成岩的标志物,表明采样区石油源及自然源排放的PAHs极少。
图3
新窗口打开|下载原图ZIP|生成PPT图3重污染天气下PM2.5中各单体PAHs平均浓度水平
Fig. 3Concentrations of single- PAHs in PM2.5 during heavy polluted weather
重污染期间西安与陇县PM2.5中PAHs各单体含量比较发现（图3）,低环PAHs中,除Ant、Fl的城市平均含量略低于农村地区外,Acy、Ace、Phe质量浓度均表现为陇县高于西安。而中高环PAHs中,除BkF、DBA外,其余单体PAHs则表现为陇县平均质量浓度远高于西安,其中BaA含量差异最为显著。特别需要说明的是,BaP是唯一列入中国环境空气质量标准的PAHs,日均限值为2.5 ng/m3,而重污染天气下西安和陇县PM2.5中BaP日均浓度分别为18.39 ng/m3、40.32 ng/m3,各超出标准限值的7.3倍和16.1倍,远高于人群可接受水平。
3.2 PAHs与气象要素相关性分析
大气污染除了受区域特殊地形配置条件、社会经济发展水平以及能源结构等因素影响外,还与污染天气过程期间气象条件变化密切相关[46]。图4为采样期间西安及陇县PAHs浓度与气象参数之间的关系图,为进一步探究PAHs污染与气象条件之间的相关性,对重污染期PM2.5中PAHs质量浓度与气象要素（气温、气压、相对湿度、风速）进行相关性分析（表1）。采样期间PM2.5中PAHs与气温、气压及风速均呈显著负相关性,其Pearson相关系数分别为-0.624、-0.760、-0.690,以上相关系数均通过α = 0.01双尾显著性水平检验,同时结果表明,采样期间PAHs浓度与相对湿度无明显相关。以上结果与Zhang[47]研究武汉地区冬季PAHs污染与气象要素相关性的结果基本一致。图4
新窗口打开|下载原图ZIP|生成PPT图4重污染期间PM2.5中PAHs浓度与气象要素变化特征
Fig. 4Variation characteristics of PAHs and meteorology parameters during heavy polluted weather
Tab. 1
表1
表1重污染期间PM2.5中PAHs与气象要素Pearson相关性
Tab. 1
| 各参数 | PAHs | 气温 | 气压 | 风速 | 相对湿度 |
|---|---|---|---|---|---|
| PAHs | 1 | ||||
| 气温 | -0.624** | 1 | |||
| 气压 | -0.760** | 0.197 | 1 | ||
| 风速 | -0.690** | 0.306 | 0.620** | 1 | |
| 相对湿度 | 0.227 | -0.193 | -0.172 | -0.278 | 1 |
新窗口打开|下载CSV
重污染期间研究区域气温波动范围为-5.1~2.5 ℃,平均温度为-0.9 ℃,平均气压为955 hPa,平均风速为2.7 m/s,且东北风为主导风向,温度及风速值均整体偏小。相关性分析结果表明重污染期间PM2.5中PAHs质量浓度与气温、气压及风速呈显著负相关,即当该气象因子值较低时,PAHs浓度呈升高趋势,尤其是农村地区,气温、气压及风速值远小于城市地区,而PAHs浓度却呈现较高水平。西安与陇县均地处汾渭平原西部,三面环山且山区气温偏低,复杂的地形条件结合不利的气象因素,不利于低环PAHs的挥发与富集,也抑制了中环PAHs的半挥发性。另外当冬季近地面温度及气压较低且风速较小时,易形成近地面稳定大气层结,出现逆温层而减缓空气对流,不利于大气污染物的水平和垂直扩散,造成汾渭平原西部近地面大气细颗粒物的累积及PAHs的富集。
3.3 PAHs源解析
3.3.1 特征比值法 特征比值法是PAHs源解析最经典方法之一,主要依据相同分子量PAHs的同分异构体化合物浓度比值来判断其环境来源[48]。通常利用Ant/(Ant+Phe)、Flu/(Flu+Pyr)、BaA/(BaA+Chr)、IcdP/(IcdP+BghiP)等的特征比值作为源解析判断依据[49],当Ant/(Ant+Phe)小于0.1时,PAHs判断为石油源排放,大于0.1时则是燃烧源;当Flu/(Flu+Pyr)大于0.5时,则认为是煤炭及生物质的燃烧,该值介于0.4~0.5时,则视为化石燃料燃烧排放;当BaA/(BaA+Chr)大于0.35,可能是煤炭及生物质燃烧源,介于0.2~0.35时,则是石油、燃烧的混合源;当IcdP/(IcdP+BghiP)<0.2时,为石油源,介于0.2~0.5之间,表示PAHs为化石燃料燃烧源,大于0.5则为煤炭或生物质燃烧源。重污染期间西安与陇县特征比值结果如图5所示,Ant/(Ant+Phe)比值均介于0.1~0.2,表明西安与陇县PAHs均以燃烧源为主;西安Flu/(Flu+Pyr)值介于0.4~0.8,表明可能来源有油类燃烧、煤炭及生物质燃烧,陇县Flu/(Flu+Pyr)值介于0.5~0.6,表明煤炭及生物质燃烧是该农村地区PAHs主要来源。西安BaA/(BaA+Chr)范围为0.2~0.5,IcdP/(IcdP+BghiP)范围为0.3~0.72,表明PAHs由交通源及燃烧源共同作用产生,陇县两比值范围分别为0.4~0.5、0.5~0.8,表明生物质及煤炭燃烧为主要排放源。
图5
新窗口打开|下载原图ZIP|生成PPT图5重污染期间PAHs特征比值法源解析
Fig. 5Source of PAHs in PM2.5 by diagnostic ratios during heavy polluted weather
故特征比值法分析结果表明,煤炭、生物质的燃烧及机动车尾气混合排放的混合源是西安PM2.5中高浓度PAHs的主要因素;而煤炭和生物质燃烧是陇县PM2.5中PAHs的主要来源。
3.3.2 主成分分析法（PCA） 除特征比值法法外,主成分分析法也是解析PAHs来源的重要手段。对西安与陇县重污染天气PM2.5中PAHs单体进行主成分分析,最大方差法旋转后的因子荷载结果如图6所示。从解析结果看,共提取出3个特征值大于1的因子,累计贡献率为82.23%。其中因子1解释了52.7%的来源,负载系数较大的单体为BaA、Chr、Pyr、Flu,研究表明Pyr及Chr是生物质燃烧的标志物成分,而BaA、Flu代表燃煤排放[50],因此因子1可归因为煤炭及生物质燃烧源。因子2共解释了15.89%的来源,在Phe及BkF上荷载较高,Phe被视为重油及柴油燃烧产生的PAHs,而BkF是柴油燃烧标志物[51],因此因子2可判断为是柴油车尾气排放源。因子3解释了13.68%的来源,在BghiP上有较大的荷载,而BghiP是汽油车排放物的标志物[52],表明因子3代表汽油类机动车尾气排放源。以上结果表明汾渭平原西部地区重污染天气下PM2.5中PAHs最主要来源为煤炭及生物质燃烧,机动车尾气排放源次之,这也说明中国城市及农村地区冬季取暖方式对大气PAHs污染的影响至关重要。
图6
新窗口打开|下载原图ZIP|生成PPT图6重污染期间PAHs主成分分析法源解析结果
Fig. 6Source of PAHs in PM2.5 by PCA method during heavy polluted weather
3.4 健康风险分析
BaP是16种优控PAHs中致癌致畸性最强,且唯一列入中国环境质量标准的PAHs。EPA推荐以BaP浓度为背景值,由式（1）计算基于BaP的等效毒性浓度TEQ（表2）。中国《环境空气质量标准》（GB3095-2012）规定二类区BaP日均浓度限值为2.5 ng/m3,重污染期间西安PM2.5中PAHs的TEQ平均质量浓度为44.37 ng/m3,陇县为79.72 ng/m3,分别超出规定限值的17.7倍和31.9倍,表明在重污染天气下汾渭平原西部地区大气PAHs污染已远超人群可接受水平,对人体健康造成威胁。Tab. 2
表2
表2重污染天气下PM2.5中PAHs的TEQ均值(μg/m3)
Tab. 2
| 单体PAHs | TEFi | 西安TEQ | 陇县TEQ | 单体PAHs | TEFi | 西安TEQ | 陇县TEQ |
|---|---|---|---|---|---|---|---|
| Acy | 0.001 | 0.00383 | 0.00123 | Chr | 0.01 | 0.23066 | 0.89568 |
| Ace | 0.001 | 0.00818 | 0.00178 | BbF | 0.10 | 2.45329 | 7.87647 |
| Fl | 0.001 | 0.00157 | 0.00365 | BkF | 0.10 | 3.51998 | 3.05048 |
| Phe | 0.001 | 0.01240 | 0.00909 | BaP | 1.00 | 18.39103 | 40.82083 |
| Ant | 0.010 | 0.01870 | 0.01310 | IcdP | 0.10 | 1.86381 | 5.06751 |
| Flu | 0.001 | 0.02908 | 0.09293 | DBA | 1.00 | 16.31994 | 13.74001 |
| Pyr | 0.001 | 0.01833 | 0.08488 | BghiP | 0.01 | 0.19340 | 0.30031 |
| BaA | 0.100 | 1.30446 | 7.76588 | ||||
| ∑TEQ | 44.36863 | 79.72385 |
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EPA将ILCR值分为3类,最低风险阈值为10-6,当风险计算值小于10-6时,表明无风险;当计算值高于10-6且低于10-4,有潜在致癌风险;当该值大于10-4时,有较高致癌风险,且值越大,风险程度越高,此时应当引起高度重视[53]。本文参考EPA《暴露参数手册》[54]《中国人群暴露参数手册（成人卷）》[55]及《中国人群暴露参数手册（儿童卷）概要》[56]确定相关参数,根据式（2）计算出西安与陇县在重污染天气条件下通过呼吸暴露的儿童及成人致癌风险值（表3）。西安男性、女性的成人及儿童ILCR值分别为3.552×10-6、3.874×10-6、0.468×10-6、0.493×10-6,陇县该值分别为0.88×10-6、0.921×10-6、9.895×10-6、10.405×10-6。
Tab. 3
表3
表3不同年龄段人群各项暴露参数取值及ILCR值
Tab. 3
| 参数 | 西安 | 陇县 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 儿童 | 成人 | 儿童 | 成人 | ||||||||
| 男 | 女 | 男 | 女 | 男 | 女 | 男 | 女 | ||||
| IR(m3/h) | 0.36 | 0.36 | 0.75 | 0.75 | 0.34 | 0.34 | 0.73 | 0.73 | |||
| ET(h/d) | 2.2 | 2.2 | 3.08 | 2.87 | 2.4 | 2.2 | 4.60 | 4.30 | |||
| ED(a) | 6 | 6 | 52 | 52 | 6 | 6 | 52 | 52 | |||
| EF(d/a) | 365 | 365 | 365 | 365 | 365 | 365 | 365 | 365 | |||
| CSF(mg/(kg d)) | 3.1 | 3.1 | 3.1 | 3.1 | 3.1 | 3.1 | 3.1 | 3.1 | |||
| BW(kg) | 20.2 | 19.2 | 67.3 | 57.5 | 19.9 | 19.0 | 63.1 | 56.1 | |||
| AT(d) | 25500 | 25500 | 25500 | 25500 | 25500 | 25500 | 25500 | 25500 | |||
| ILCR(×10-6) | 0.468 | 0.493 | 3.552 | 3.874 | 0.880 | 0.921 | 9.895 | 10.405 | |||
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两地区PAHs暴露风险均以成人女性值为最高,成人男性次之、儿童风险值较低。陇县不同人群ILCR值普遍要高于西安,其中成人与儿童致癌风险分别是西安的近3倍和2倍。另外,不同年龄组、不同性别致癌风险也有所不同,主要表现为成人致癌风险普遍高于儿童、女性高于男性的特征,与中国深圳及武汉地区[57]的研究结果基本一致,这是由于不同性别及年龄段的人群呼吸速率、体重及室外暴露时间具有差异性,如相对于成人,儿童具有较短的室外暴露时间及较低的呼吸速率,而相对于男性,女性则体重较轻。与国内其他地区相比较,本文城市与农村成人致癌风险值均高于天津[58]市区（2.18×10-6）及郊区（6.67×10-6）重污染天气下研究结果,但西安市成人致癌风险值低于南京市重霾期研究结果（6.7×10-6）,儿童风险值低于北京市[59]儿童大气PAHs呼吸暴露风险值（1.3×10-6）。整体而言,西安与陇县在重污染天气下成人致癌风险值均超过10-6,存在潜在致癌风险;儿童致癌风险值均低于10-6,无明显致癌风险。
4 结论
（1）重度污染天气下汾渭平原典型城市与农村地区PM2.5及PM2.5中PAHs平均质量浓度分别为214.67 μg/m3、288.34 μg/m3、243.78 ng/m3、609.39 ng/m3,PM2.5及PM2.5中PAHs均表现为陇县污染水平高于西安,PAHs组成中西安以5~6环为主,而陇县以4环为主,3环PAHs占比均为最低;（2）PM2.5中PAHs与气象因素相关性分析结果表明：重污染期间PAHs质量浓度与气温、气压及风速呈负相关,且相关性显著,与相对湿度则无明显相关性;
（3）使用特征比值法及主成分分析法解析西安与陇县重污染期间PM2.5中PAHs来源,结果表明煤炭及生物质燃烧源是陇县PAHs的主要来源,而燃烧排放与机动车尾气排放的混合源是西安市呈现高浓度PAHs的主要因素;
（4）健康风险评价结果表明汾渭平原以陇县为代表的西部农村地区在重污染天气下PAHs人群致癌风险远高于以西安为代表的城市地区。不同人群呈现出成人致癌风险高于儿童,女性致癌风险高于男性的特征,总体表现为两地区成人致癌风险均超过风险阈值,存在潜在致癌风险,儿童则无明显致癌风险。
参考文献 原文顺序
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被引期刊影响因子
DOI:10.1038/nature01675URLPMID:12774119 [本文引用: 1]
The most important anthropogenic influences on climate are the emission of greenhouse gases and changes in land use, such as urbanization and agriculture. But it has been difficult to separate these two influences because both tend to increase the daily mean surface temperature. The impact of urbanization has been estimated by comparing observations in cities with those in surrounding rural areas, but the results differ significantly depending on whether population data or satellite measurements of night light are used to classify urban and rural areas. Here we use the difference between trends in observed surface temperatures in the continental United States and the corresponding trends in a reconstruction of surface temperatures determined from a reanalysis of global weather over the past 50 years, which is insensitive to surface observations, to estimate the impact of land-use changes on surface warming. Our results suggest that half of the observed decrease in diurnal temperature range is due to urban and other land-use changes. Moreover, our estimate of 0.27 degrees C mean surface warming per century due to land-use changes is at least twice as high as previous estimates based on urbanization alone.
DOI:10.1016/j.envint.2011.03.003URL [本文引用: 1]
As the largest developing country. China has been changing rapidly over the last three decades and its economic expansion is largely driven by the use of fossil fuels, which leads to a dramatic increase in emissions of both ambient air pollutants and greenhouse gases (GHGs). China is now facing the worst air pollution problem in the world, and is also the largest emitter of carbon dioxide. A number of epidemiological studies on air pollution and population health have been conducted in China, using time-series, case-crossover, cross-sectional, cohort, panel or intervention designs. The increased health risks observed among Chinese population are somewhat lower in magnitude, per amount of pollution, than the risks found in developed countries. However, the importance of these increased health risks is greater than that in North America or Europe, because the levels of air pollution in China are very high in general and Chinese population accounts for more than one fourth of the world's totals. Meanwhile, evidence is mounting that climate change has already affected human health directly and indirectly in China, including mortality from extreme weather events; changes in air and water quality; and changes in the ecology of infectious diseases. If China acts to reduce the combustion of fossil fuels and the resultant air pollution, it will reap not only the health benefits associated with improvement of air quality but also the reduced GHG emissions. Consideration of the health impact of air pollution and climate change can help the Chinese government move forward towards sustainable development with appropriate urgency. (C) 2011 Elsevier Ltd.
DOI:10.1016/s1470-2045(13)70487-xURLPMID:25035875 [本文引用: 1]
DOI:10.1016/S0140-6736(16)31679-8URL [本文引用: 1]
[本文引用: 1]
DOI:10.1016/S1352-2310(01)00301-6URL [本文引用: 1]
AbstractWeekly PM2.5 samples were simultaneously collected at a residential (Tsinghua University) and a downtown (Chegongzhuang) site in Beijing from July 1999 through September 2000. The ambient mass concentration and chemical composition of the PM2.5 were determined. Analyses included elemental composition, water-soluble ions, and organic and elemental carbon. Weekly PM2.5 mass concentrations ranged from 37 to 357 μg/m3, with little difference found between the two sites. Seasonal variation of PM2.5 concentrations was significant, with the highest concentration in the winter and the lowest in the summer. Spring dust storms had a strong impact on the PM2.5. Overall, organic carbon was the most abundant species, constituting no less than 30% of the total PM2.5 mass at both sites. Concentrations of organic and elemental carbon were 35% and 16% higher at Tsinghua University than at Chegongzhuang. Ammonium, nitrate and sulfate were comparable at the sites, accounting for 25–30% of the PM2.5 mass.]]>
DOI:10.11821/dlxb201711012URL [本文引用: 1]
2.5 has been universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM2.5 concentration for the purpose of regional air quality control and management. Using PM2.5 data from 2000 to 2011 that is inversed from NASA atmospheric remote sensing images, and employing the methods in geo-statistics, geographic detectors and geo-spatial analysis, this paper reveals the spatio-temporal evolution patterns and driving factors of PM2.5 concentration in China. The main findings are as follows: (1) In general, the average concentration of PM2.5 in China has increased quickly and reached its peak value in the year of 2006; after that, it has been maintained at around 22.47-28.26 μg/m3. (2) PM2.5 is strikingly uneven in China, with a higher concentration in North and East than in South and West, respectively. In particular, the areas with a relatively high concentration of PM2.5 are mainly the four regions including the Huang-Huai-Hai Plain, the Lower Yangtze River Delta Plain, the Sichuan Basin, and the Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM2.5. (3) The center of gravity of PM2.5 has shown an overall eastward movement trend, which indicates an increasingly serious haze in eastern China. Particularly, the center of gravity of high-value PM2.5 is kept on moving eastward, while that of the low-value PM2.5 moves westward. (4) The spatial autocorrelation analysis indicates a significantly positive spatial correlation. The "High-High" PM2.5 agglomeration areas include the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan plain regions. The "Low-Low" PM2.5 agglomeration areas include Inner Mongolia and Heilongjiang to the north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan and Fujian and other southeast coastal and island areas. (5) Geographic detection analysis indicates that both natural and human factors account for the spatial variations of PM2.5 concentration. In particular, factors such as natural geographical location, population density, automobile quantity, industrial discharge and straw burning are the main driving forces of PM2.5 concentration in China.]]>
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DOI:10.1111/j.1539-6924.2011.01630.xURL [本文引用: 1]
Ground-level ozone (O3) and fine particulate matter (PM2.5) are associated with increased risk of mortality. We quantify the burden of modeled 2005 concentrations of O3 and PM2.5 on health in the United States. We use the photochemical Community Multiscale Air Quality (CMAQ) model in conjunction with ambient monitored data to create fused surfaces of summer season average 8-hour ozone and annual mean PM2.5 levels at a 12 km grid resolution across the continental United States. Employing spatially resolved demographic and concentration data, we assess the spatial and age distribution of air-pollution-related mortality and morbidity. For both PM2.5 and O3 we also estimate: the percentage of total deaths due to each pollutant; the reduction in life years and life expectancy; and the deaths avoided according to hypothetical air quality improvements. Using PM2.5 and O3 mortality risk coefficients drawn from the long-term American Cancer Society (ACS) cohort study and National Mortality and Morbidity Air Pollution Study (NMMAPS), respectively, we estimate 130,000 PM2.5-related deaths and 4,700 ozone-related deaths to result from 2005 air quality levels. Among populations aged 6599, we estimate nearly 1.1 million life years lost from PM2.5 exposure and approximately 36,000 life years lost from ozone exposure. Among the 10 most populous counties, the percentage of deaths attributable to PM2.5 and ozone ranges from 3.5% in San Jose to 10% in Los Angeles. These results show that despite significant improvements in air quality in recent decades, recent levels of PM2.5 and ozone still pose a nontrivial risk to public health.
DOI:10.1016/j.partic.2013.11.001URL [本文引用: 1]
Concern over the health effects of fine particles in the ambient environment led the U.S. Environmental Protection Agency to develop the first standard for PM2.5 (particulate matter less than 2.5 mu m) in 1997. The Particle Technology Laboratory at the University of Minnesota has helped to establish the PM2.5 standard by developing many instruments and samplers to perform atmospheric measurements. In this paper, we review various aspects of PM2.5, including its measurement, source apportionment, visibility and health effects, and mitigation. We focus on PM2.5 studies in China and where appropriate, compare them with those obtained in the U.S. Based on accurate PM2.5 sampling, chemical analysis, and source apportionment models, the major PM2.5 sources in China have been identified to be coal combustion, motor vehicle emissions, and industrial sources. Atmospheric visibility has been found to correlate well with PM2.5 concentration. Sulfate, ammonium, and nitrate carried by PM2.5, commonly found in coal burning and vehicle emissions, are the dominant contributors to regional haze in China. Short-term exposure to PM2.5 is strongly associated with the increased risk of morbidity and mortality from cardiovascular and respiratory diseases in China. The strategy for PM2.5 mitigation must be based on reducing the pollutants from the two primary sources of coal-fired power plants and vehicle emissions. Although conventional Particulate Emission Control Devices (PECD) such as electrostatic precipitators in Chinese coal-fired power plants are generally effective for large particles, most of them may not have high collection efficiency of PM2.5. Baghouse filtration is gradually incorporated into the PECD to increase the PM2.5 collection efficiency. By adopting stringent vehicle emissions standard such as Euro 5 and 6, the emissions from vehicles can be gradually reduced over the years. An integrative approach, from collaboration among academia, government, and industries, can effectively manage and mitigate the PM2.5 pollution in China. (C) 2013 Published by Elsevier B.V. on behalf of Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences.
DOI:10.1016/j.atmosenv.2007.12.010URL [本文引用: 1]
AbstractThere is an increasing concern about the occurrence of polycyclic aromatic hydrocarbons (PAHs) in the environment as they are ubiquitous in ambient air and some of them are among the strongest known carcinogens. PAHs and their derivatives are produced by the incomplete combustion of organic material arising, partly, from natural combustion such as forest and volcanic eruption, but with the majority due to anthropogenic emissions. The PAH concentration varies significantly in various rural and urban environments and is mainly influenced by vehicular and domestic emissions. The review serves as a database to identify and characterize the emission sources of PAHs and hence various approaches including diagnostic ratio (DR) and principal component analysis (PCA) are discussed in detail. These approaches allow individual PAHs to be associated with their origin sources. The factors that effect PAH emission and estimated emission rate are also discussed in this paper. Although the levels of low molecular weight PAHs are high in vapor phase, most of the probable human carcinogenic PAHs are found to be associated with particulate matter, especially in fine mode particles in ambient air. Many countries have proposed a non-mandatory concentration limit for PAHs, whereas the health risk studies conducted in relation to PAH exposure, urge that these pollutants should be given a high priority when considering air quality management and reduction of impacts.]]>
DOI:10.1021/es052346lURLPMID:16749684 [本文引用: 1]
Polycyclic aromatic hydrocarbon (PAH) air concentrations measured over the period 1992-2000 at the Canadian High Arctic station of Alert were subject to time-series analysis using dynamic harmonic regression (DHR). For most of the PAHs, the DHR model fit to the observed data was good, with DHR capable of interpolating over missing data points during periods when air concentrations were below detection limits. As expected, DHR identified seasonal increases in PAH air concentrations. However, it has also identified additional, subtler
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DOI:10.1016/j.atmosenv.2006.11.002URL [本文引用: 1]
AbstractDuring the 2003 Chinese Arctic Research Expedition from the Bohai Sea to the high Arctic (37–80°N) aboard the icebreaker Xuelong (Snow Dragon), air samples were collected using a modified high-volume sampler that pulls air through a quartz filter and a polyurethane foam plug (PUF). These filters and PUFs were analyzed for particulate phase and gas phase polycyclic aromatic hydrocarbons (PAHs), respectively, in the North Pacific Ocean and adjacent Arctic region. The ∑PAHs (where ∑=15 compounds) ranged from undetectable level to 4380 pg m−3 in the particulate phase and 928–92 600 pg m−3 in the gas phase, respectively. A decreasing latitudinal trend was observed for gas-phase PAHs, probably resulting from temperature effects, dilution and decomposition processes; particulate-phase PAHs, however, showed poor latitudinal trends, because the effects of temperature, dilution and photochemistry played different roles in different regions from middle-latitude source areas to the high latitudes. The ratios of PAH isomer pairs, either conservative or sensitive to degradation during long-range transport, were employed to interpret sources and chemical aging of PAHs in ocean air. In this present study the fluoranthene/pyrene and indeno[123-cd]pyrene/benzo[ghi]pyrene isomer pairs, whose ratios are conservative to photo-degradation, implies that biomass or coal burning might be the major sources of PAHs observed over the North Pacific Ocean and the Arctic region in the summer. The isomer ratios of 1,7/(1,7+2,6)-DMP (dimethylphenanthrene) and anthracene/phenanthrene, which are sensitive to aging of air masses, not only imply chemical evolving of PAHs over the North Pacific Ocean were different from those over the Arctic, but reveal that PAHs over the Arctic were mainly related to coal burning, and biomass burning might have a larger contribution to the PAHs over the North pacific ocean.]]>
DOI:10.1016/j.atmosenv.2015.04.050URL [本文引用: 1]
DOI:10.1016/j.envint.2013.07.019URL [本文引用: 1]
Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds comprised of two or more fused benzene rings arranged in various configurations. PAHs are widespread environmental contaminants formed as a result of incomplete combustion of organic materials such as fossil fuels. The occurrence of PAHs in ambient air is an increasing concem because of their carcinogenicity and mutagenicity. Although emissions and allowable concentrations of PAHs in air are now regulated, the health risk posed by PAH exposure suggests a continuing need for their control through air quality management. In light of the environmental significance of PAH exposure, this review offers an overview of PAH properties, fates, transformations, human exposure, and health effects (acute and chronic) associated with their emission to the atmosphere. Biomarkers of PAH exposure and their significance are also discussed. (C) 2013 Elsevier Ltd.
DOI:10.1016/0045-6535(95)00348-7URLPMID:8867146 [本文引用: 1]
The health risk associated with inhalatory exposure to PAHs either in the occupational atmosphere or in outdoor air is commonly assessed on the basis of benzo(a)pyrene (BaP) concentrations in air. The PAH-related health risk is calculated with the help of epidemiological data from coke oven workers. The proportion of individual carcinogenic PAHs to BaP has been shown to vary in different environments by one to two orders of magnitude. Despite this, the unit risk value for BaP derived from epidemiological studies of coke oven workers is used for risk estimation of these environments. Toxic equivalency factors (TEFs) for individual PAHs were used to estimate human health risk associated with inhalatory exposure to PAHs. Given the uncertainties involved in risk assessment in general, a variability of risk estimation for PAH mixtures based on the toxic equivalency factor concept by a factor 2.6 is low and rather unreasonably precise. This underlines the importance of BaP as a surrogate compound of a PAH mixture.
DOI:10.1016/j.reprotox.2017.07.012URLPMID:28739294 [本文引用: 1]
Polycyclic aromatic hydrocarbons (PAHs) are a class of common persistent environmental pollutants found in water, air, soil, and plants and can be released by natural sources. However, the majority of atmospheric PAHs are from vehicular emissions, coal-burning plants, and the production and use of petroleum-derived substances. Exposure to PAHs has been implicated in cancer and other diseases, including reproductive disorders. This scoping review is a preliminary step that explores the utility and feasibility of completing a systematic review evaluating the effect of PAHs on female reproduction. We performed literature searches in PubMed, Web of Science, and Scopus, then screened, identified, and categorized relevant studies. Our results identified fertility and pregnancy/fetal viability as outcomes with sufficient research for systematic review. In addition to presenting the relevant studies, the review identifies data gaps, and provides the groundwork to develop the most appropriate research questions for systematic review.
DOI:10.1007/s10311-007-0095-0URL [本文引用: 1]
Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds with two or more fused aromatic rings. They have a relatively low solubility in water, but are highly lipophilic. Most of the PAHs with low vapour pressure in the air are adsorbed on particles. When dissolved in water or adsorbed on particulate matter, PAHs can undergo photodecomposition when exposed to ultraviolet light from solar radiation. In the atmosphere, PAHs can react with pollutants such as ozone, nitrogen oxides and sulfur dioxide, yielding diones, nitro- and dinitro-PAHs, and sulfonic acids, respectively. PAHs may also be degraded by some microorganisms in the soil. PAHs are widespread environmental contaminants resulting from incomplete combustion of organic materials. The occurrence is largely a result of anthropogenic emissions such as fossil fuel-burning, motor vehicle, waste incinerator, oil refining, coke and asphalt production, and aluminum production, etc. PAHs have received increased attention in recent years in air pollution studies because some of these compounds are highly carcinogenic or mutagenic. Eight PAHs (Car-PAHs) typically considered as possible carcinogens are: benzo(a)anthracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene (B(a)P), dibenzo(a,h)anthracene, indeno(1,2,3-cd)pyrene and benzo(g,h,i)perylene. In particular, benzo(a)pyrene has been identified as being highly carcinogenic. The US Environmental Protection Agency (EPA) has promulgated 16 unsubstituted PAHs (EPA-PAH) as priority pollutants. Thus, exposure assessments of PAHs in the developing world are important. The scope of this review will be to give an overview of PAH concentrations in various environmental samples and to discuss the advantages and limitations of applying these parameters in the assessment of environmental risks in ecosystems and human health. As it well known, there is an increasing trend to use the behavior of pollutants (i.e. bioaccumulation) as well as pollution-induced biological and biochemical effects on human organisms to evaluate or predict the impact of chemicals on ecosystems. Emphasis in this review will, therefore, be placed on the use of bioaccumulation and biomarker responses in air, soil, water and food, as monitoring tools for the assessment of the risks and hazards of PAH concentrations for the ecosystem, as well as on its limitations.]]>
DOI:10.1016/j.envpol.2019.02.068URLPMID:30851590 [本文引用: 1]
Polycyclic aromatic hydrocarbons (PAHs) are organic compounds composed of at least two benzene rings. This paper reviews the characteristics, sources and health risk of airborne particulate PAHs in Chinese cities. The airborne particulate PAH concentrations varied from 3.35 to 910ngm(-3), with an average of 75.0ngm(-3), and the pollution level of PAHs in northern cities was generally higher than that in southern cities. The PAH concentrations in different cities underwent similar seasonal variations, with high concentrations in the winter and relatively low concentrations in the summer. Many factors, such as meteorological conditions and source emissions, influenced the spatiotemporal pattern of PAHs. High temperatures, frequent flow exchanges, abundant rainfall and strong solar radiation reduced the level of particulate PAHs in the atmosphere. The historical changes in the level of airborne particulate PAHs in four cities were analyzed. The PAH concentrations in Beijing and Taiyuan presented a trend of first increasing and then decreasing, while the level of particulate PAHs in Nanjing and Guangzhou had a decreasing tendency from year 2000-2015. The airborne particulate PAHs in cities were derived from several sources, including coal combustion, vehicle emissions, coking industries, biomass burning and petroleum volatilization. The results of a health risk assessment indicated that the incremental lifetime cancer risk (ILCR) for people in the northern cities was higher than that for people in the other regions, especially during the cold season. Moreover, adults were at greater risk than people in other age groups, and the health risk to females was slightly higher than that to males. The potential risk of airborne particulate PAH exposure was relatively high in some cities, and controlling PAH emissions at the source should be required to prevent pollution.
DOI:10.1016/j.ejpe.2015.03.011URL [本文引用: 1]
DOI:10.1016/j.chemosphere.2018.04.054URLPMID:29665530 [本文引用: 1]
Exposure to PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) can elicit several types of cancer and non-cancer effects. Previous studies reported substantial burdens of PAH-induced lung cancer, but the burdens of other cancer types and non-cancer effects remain unknown. Thus, we estimate the cancer and non-cancer burden of disease, in disability-adjusted life years (DALYs), attributable to ambient PM2.5-bound PAHs exposure in Nagpur district, India, using risk-based approach. We measured thirteen PAHs in airborne PM2.5 sampled from nine sites covering urban, peri-urban and rural areas, from February 2013 to June 2014. We converted PAHs concentrations to benzo[a]pyrene equivalence (B[a]Peq) for cancer and non-cancer effects using relative potency factors, and relative toxicity factors derived from quantitative structure-activity relationships, respectively. We calculated time-weighted exposure to B[a]Peq, averaged over 30 years, and adjusted for early-life susceptibility to cancer. We estimated the DALYs/year using B[a]Peq exposure levels, published toxicity data, and severity of the diseases from Global Burden of Disease 2016 database. The annual average concentration of total PM2.5-bound PAHs was 458+/-246ng/m(3) and resulted in 49,500 DALYs/year (0.011 DALYs/person/year). The PAH-related DALYs followed this order: developmental (mostly cardiovascular) impairments (55.1%)>cancer (26.5%) or lung cancer (23.1%)>immunological impairments (18.0%)>reproductive abnormalities (0.4%).
DOI:10.1016/j.emcon.2019.04.002URL [本文引用: 1]
DOI:10.1016/j.envint.2018.12.052URLPMID:30654326 [本文引用: 1]
Children, an important vulnerable group, spend most of their time at schools (up to 10h per day, mostly indoors) and the respective air quality may significantly impact on children health. Thus, this work reviews the published studies on children biomonitoring and environmental exposure to particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) at school microenvironments (indoors and outdoors), major sources and potential health risks. A total of 28, 35, and 31% of the studies reported levels that exceeded the international outdoor ambient air guidelines for PM10, PM2.5, and benzo(a)pyrene, respectively. Indoor and outdoor concentrations of PM10 at European schools, the most characterized continent, ranged between 7.5 and 229mug/m(3) and 21-166mug/m(3), respectively; levels of PM2.5 varied between 4 and 100mug/m(3) indoors and 6.1-115mug/m(3) outdoors. Despite scarce information in some geographical regions (America, Oceania and Africa), the collected data clearly show that Asian children are exposed to the highest concentrations of PM and PAHs at school environments, which were associated with increased carcinogenic risks and with the highest values of urinary total monohydroxyl PAH metabolites (PAH biomarkers of exposure). Additionally, children attending schools in polluted urban and industrial areas are exposed to higher levels of PM and PAHs with increased concentrations of urinary PAH metabolites in comparison with children from rural areas. Strong evidences demonstrated associations between environmental exposure to PM and PAHs with several health outcomes, including increased risk of asthma, pulmonary infections, skin diseases, and allergies. Nevertheless, there is a scientific gap on studies that include the characterization of PM fine fraction and the levels of PAHs in the total air (particulate and gas phases) of indoor and outdoor air of school environments and the associated risks for the health of children. There is a clear need to improve indoor air quality in schools and to establish international guidelines for exposure limits in these environments.
DOI:10.1016/j.envpol.2017.01.060URLPMID:28169071 [本文引用: 1]
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DOI:10.1016/j.scitotenv.2018.07.049URL [本文引用: 1]
DOI:10.1016/j.ecoenv.2019.109740URLPMID:31655327 [本文引用: 1]
To comparatively analyze source-specific risks of atmospheric particulate matter (PM), PM10-bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) were synchronously detected in a megacity (Chengdu, China) from 2009 to 2016. Non-cancer risk (assessed by hazard quotient, HQ) of PAHs and HMs was within the acceptable level, while cancer risk (assessed by incremental life cancer risk (ILCR), R) of PAHs and HMs were 1.01x10(-4) and 9.40x10(-5) in DP and WP, which showed low risk. HMs dominated cancer (92.12%) and non-cancer (99.99%) risks. An advanced method named as joint source-specific risk assessment of HMs and PAHs (HP-SRA model) was developed to assess comprehensive source-specific risks. Gasoline combustion (contributed 9.6% of PM10, 0.3% of HQ and 10.0% of R), diesel combustion (6.2% of PM10, 0.2% of HQ and 10.7% of R), coal combustion (17.5% of PM10, 1.8% of HQ and 13.4% of R), industrial source (9.1% of PM10, 80.7% of HQ and 35.0% of R), crustal dust (28.1% of PM10, 9.0% of HQ and 1.6% of R), nitrate (7.5% of PM10, 1.1% of HQ and 6.2% of R) and sulphate & secondary organic carbon & adsorption (SSA, 19.6% of PM10, 6.9% of HQ and 23.1% of R) were identified as main sources. For cancer risk, industrial sources and SSA posed the highest proportion. Higher levels of Co and Ni generated from industrial sources and Cr (), Cd and Ni absorbed in the SSA can result in high-risk contributions. Thus, controlling HMs levels in industrial emissions is essential to protecting human health.
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http://www.geog.com.cn/article/2021/0375-5444/www.tjj.xa.gov.cn/,
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http://www.geog.com.cn/article/2021/0375-5444/www.tjj.xa.gov.cn/,
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DOI:10.1037//0278-6133.4.3.219URLPMID:4029106 [本文引用: 1]
This article describes a scale measuring dispositional optimism, defined in terms of generalized outcome expectancies. Two preliminary studies assessed the scale's psychometric properties and its relationships with several other instruments. The scale was then used in a longitudinal study of symptom reporting among a group of undergraduates. Specifically, respondents were asked to complete three questionnaires 4 weeks before the end of a semester. Included in the questionnaire battery was the measure of optimism, a measure of private self-consciousness, and a 39-item physical symptom checklist. Subjects completed the same set of questionnaires again on the last day of class. Consistent with predictions, subjects who initially reported being highly optimistic were subsequently less likely to report being bothered by symptoms (even after correcting for initial symptom-report levels) than were subjects who initially reported being less optimistic. This effect tended to be stronger among persons high in private self-consciousness than among those lower in private self-consciousness. Discussion centers on other health related applications of the optimism scale, and the relationships between our theoretical orientation and several related theories.
DOI:10.3390/ijerph7051889URLPMID:20622999 [本文引用: 1]
or= 228) and individual PAH and compared across heating versus nonheating seasons. Results show that heating compared to nonheating season was associated significantly with higher (BaP-TEQ)(Sigma8PAH) and (BaP-MEQ)(Sigma8PAH) both indoors and outdoors (p
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DOI:10.1016/j.scitotenv.2019.01.078URL [本文引用: 1]
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DOI:10.1016/j.marpolbul.2015.09.014URLPMID:26392374 [本文引用: 1]
The polycyclic aromatic hydrocarbons (PAHs) in PM2.5 contribute significantly to health risk. The objectives of this study were to assess the occurrence and variation in the concentrations and sources of PM2.5-bound PAHs sampled from the atmosphere of a typical southeastern Chinese city (Guangzhou) from June 2012 to May 2013, with the potential risks being investigated. The annual average concentration of PM2.5 was 64.88mugm(-3). The annual average concentration of PAHs in PM2.5 was 33.89ngm(-3). Benzo(a)pyrene (BaP) was found to be the predominant PAH in all PM2.5 samples throughout the year, constituting approximately 8.78% of the total PAH content. The significant meteorological parameters for most of the PAHs were sunshine time, air pressure, and humidity, together representing 10.7-52.4% of the variance in atmospheric PAH concentrations. Motor-vehicle exhaust and coal combustion were probably the main sources of PAHs in PM2.5 in Guangzhou. The average inhalation cancer risk (ICR) for a lifetime of 70years was 5.98x10(-4) (ranging from 8.39x10(-5) to 1.95x10(-3)).
DOI:10.1016/j.partic.2014.03.010URL [本文引用: 1]
DOI:10.1016/j.envpol.2017.08.025URLPMID:28810202 [本文引用: 1]
Based on the 12-hour PM2.5 samples collected in an urban site of Beijing, sixteen PM2.5-bound Polycyclic Aromatic Hydrocarbons (PAHs) were measured to investigate the characteristics and potential source regions of particulate PAHs in Beijing. The study period included the summer period in July-August 2014, the APEC source control period during the Asia-Pacific Economic Cooperation (APEC) meeting in the first half of November 2014, and the heating period in the second half of November 2014. Compared to PM2.5, sum of 16 PM2.5-bound PAHs exhibited more significant seasonal variation with the winter concentration largely exceeding the summer concentration. Temperature appeared to be the most crucial meteorological factor during the summer and heating periods, while PM2.5-bound PAHs showed stronger correlation with relative humidity and wind speed during the APEC source control period. Residential heating significantly increased the concentrations of higher-ring-number (>/=4) PAHs measured in PM2.5 fraction. Potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analysis as well as the (3 + 4) ring/(5 + 6) ring PAH ratio analysis revealed the seasonal difference in the potential source area of PM2.5-bound PAHs in Beijing. Southern Hebei was the most likely potential source area in the cold season. Using black carbon (BC) and carbon monoxide (CO) as the PAH tracers, regional residential, transportation and industry emissions all contributed to the PAH pollution in Beijing.
DOI:10.1016/j.biombioe.2013.01.031URLPMID:25678760 [本文引用: 1]
Emissions and size distributions of 28 particle-bound polycyclic aromatic hydrocarbons (PAHs) from residential combustion of 19 fuels in a domestic cooking stove in rural China were studied. Measured emission factors of total PAHs were 1.79+/-1.55, 12.1+/-9.1, and 5.36+/-4.46 mg/kg for fuel wood, brushwood, and bamboo, respectively. Approximate 86.7, 65.0, and 79.7% of the PAHs were associated with fine particulate matter with size less than 2.1 microm for these three types of fuels. Statistically significant difference in emission factors and size distributions of particle-bound PAHs between fuel wood and brushwood was observed, with the former had lower emission factors but more PAHs in finer PM. Mass fraction of the fine particles associated PAHs was found to be positively correlated with fuel density and moisture, and negatively correlated with combustion efficiency. Low and high molecular weight PAHs segregated into the coarse and fine PM, respectively. The high accumulation tendency of the PAHs from residential wood combustion in fine particles implies strong adverse health impact.
DOI:10.1016/j.atmosenv.2012.03.007URL [本文引用: 1]
Six unique OH-reaction products of naphthalene and phenanthrene were detected and quantified in ambient PM2.5 collected in Seoul, Korea between 2006 and 2007. The range of annual average concentrations of six reaction products, 2-formylcinnamaldehyde, phthalic acid, phthalide, dibenzopyranone, 9-fluorenone, and 1,2-naphthalic anhydride extended from 2.45 to 49.9 ng M-3 and all of these values were higher than the average concentration of single particulate PAH compounds in Seoul, Korea. The seasonal pattern of six reaction products generally showed higher concentrations in winter months than in summer months. This indicates that the formation of these compounds by atmospheric photochemical reactions is significant both in winter and summer and that enhanced primary sources and higher particle to gas partitioning activity due to lower ambient temperature may contribute to the high concentrations of these compounds in the winter months in Seoul, Korea. The high correlation of the formation of 2-formylcinnamladehyde and dibenzopyranone with the estimated SOC concentration, suggests that the formation of SOA from gas phase PAH reactions in the real atmospheres is significant. Also, we suggest that (E)-2-formylcinnamaldehyde and dibenzopyranone could be used as unique indicators for the atmospheric oxidative reactions of naphthalene and phenanthrene, respectively. (C) 2012 Elsevier Ltd.
DOI:10.1016/S1352-2310(99)00521-XURL [本文引用: 1]
DOI:10.1016/S1352-2310(02)00295-9URL [本文引用: 1]
AbstractTwenty-four hour samples of air particulate matter with aerodynamic diameters from 2 to 10 μm (PM10) and <2.5 μm (PM2.5) were collected in Hanoi throughout 1 year since August 1998. The air sampler was located in a meteorological garden where routine surface observations and upper air radiosoundings were conducted. Very high PM2.5 and PM2.5−10 concentrations were observed in conjunction with the occurrence of nocturnal radiation inversions from October to December and subsidence temperature inversions (STI) from January to March. In the first case, the PM2.5−10 fraction was much enhanced and particulate pollution was significantly higher at night than in daytime. During the occurence of STIs particulate mass was almost evenly distributed among the two fractions and no significant diurnal variations in concentrations were observed. In summer (May–September) particulate pollution was much lower than in winter.The multiple regression of 24-h particulate concentrations against meteorological parameters for both the winter and summer monsoon periods shows that the most important determinants of PM2.5 are wind speed and air temperature, while rainfall and relative humidity largely control the daily variations of PM2.5−10, indicating the high abundance of soil dust in this fraction. As to turbulence parameters, among the determinants of 24-h particulate concentrations are the vertical gradients of potential temperature and wind speed recorded at 06.30 and 18.30, respectively. Meteorological parameters could explain from 60% to 74% of the day-to-day variations of particulate concentrations.]]>
DOI:10.1016/j.envpol.2018.11.111URLPMID:30557806 [本文引用: 1]
Levels, compositions, sources, and cancer risks of fine particle (PM2.5)-bound PAHs were investigated at an urban site of Wuhan, Central China. Totally 115 PM2.5 samples collected during four seasons from 2014 to 2015 were analyzed for 16 USEPA priority PAHs. The annual average of PM2.5 and total PAHs were 106+/-41.7mugm(-3) and 25.1+/-19.4ngm(-3), respectively. The seasonal levels of PM2.5 and PAHs varied in a similar trend, with the highest concentrations in winter and the lowest in summer. PM2.5-bound PAHs under different pollution level was discussed and the highest average PAH levels were found at a moderate (115-150mugm(-3)) air quality level. Three sources including coal combustion and biomass burning, petrogenic source, and vehicle emissions were extracted and quantified by the positive matrix factorization (PMF) model, accounting for 22.7+/-21.3%, 34.4+/-29.0% and 42.9+/-31.3% of the total PAHs, respectively. The potential source contribution function (PSCF) and the concentration-weighted trajectory (CWT) were combined to explore the geographic origins of PAHs. The spatial distributions of coal combustion and biomass burning, petrogenic source, and vehicle emissions were well correlated with medium molecular weight (MMW), low molecular weight (LMW) and high molecular weight (HMW) PAHs, respectively. Results of PSCF and CWT indicated that the long-distance transport form north of Wuhan as far as northern and eastern of China was higher than that from the southern China while the contribution of local areas was higher than those from the long-range transport. The overall lifetime lung cancer risk (LLCR) via inhalation exposure to PM2.5-bound PAHs was estimated as 3.03x10(-4), with vehicle emissions contributed 57.1% (1.6x10(-4)) to the total risk on average, followed by coal combustion and biomass burning (31.0%, 9.6x10(-5)), and petrogenic source (11.9%, 3.6x10(-5)).
DOI:10.1016/j.atmosenv.2008.07.025URL [本文引用: 1]
AbstractPolycyclic aromatic hydrocarbons (PAHs) are emitted to the atmosphere from a variety of sources. Though classified as persistent organic pollutants (POPs), their levels are affected by atmospheric removal and transformation processes. Efforts have been made to conduct receptor modelling of PAHs for over 25 years, whereby ambient measurement data are manipulated to compare relative amounts of compounds to those expected in relevant sources. These relative amounts, which can be based on particle or total (gas + particle) concentrations, are typically presented as diagnostic ratios of two isomeric species or as profiles representing several species at once.This review examines two of the assumptions necessary for conventional ratio- or profile-based source apportionment methods to be valid. The term “conventional” refers to the direct comparison of source and ambient data without accounting for alterations that occur in the atmosphere. These assumptions, namely source specificity and species conservation, do not generally hold for PAHs as a class. Though concerns over conventional source apportionment have been expressed for some time, studies continue to appear in the literature that do not account for its limitations. In an effort to contribute to the reversal of this trend, a set of conditions under which conventional source apportionment may be valid is presented herein. Research relating to emissions' measurement analysis, numerical modelling and atmospheric processing is also suggested.]]>
DOI:10.1016/S0146-6380(02)00002-5URL [本文引用: 1]
DOI:10.1016/S1352-2310(99)00233-2URL [本文引用: 1]
DOI:10.1016/j.atmosenv.2015.01.077URL [本文引用: 1]
DOI:10.1021/es001540zURLPMID:11414034 [本文引用: 1]
Samples of organic aerosol were collected in Santiago de Chile. An activated-charcoal diffusion denuder was used to strip out organic vapors prior to particle collection. Both polynuclear aromatic hydrocarbons (PAHs) and aliphatic hydrocarbons were determined using gas chromatography/mass spectrometry (GC/MS). Organic particle sources were resolved using both concentration diagnostic ratios and multivariate methods such as hierarchical cluster analysis (HCA) and factor analysis (FA). Four factors were identified based on the loadings of PAHs and n-alkanes and were attributed to the following sources: (1) high-temperature combustion of fuels; (2) fugitive emissions from oil residues; (3) biogenic sources; and (4) unburned fuels. Multilinear regression (MLR) analysis was used to determine emission profiles and contributions of the sources. The reconstructed concentrations of particle phase aliphatic and polynuclear aromatic hydrocarbons were in good agreement (R2 > 0.70) with those measured in Santiago de Chile.
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DOI:10.1016/j.scitotenv.2019.135840URL [本文引用: 1]
