广州大气中异戊二烯浓度变化特征、化学活性和来源分析

在广州番禺大气成分站(GPACS)应用在线监测仪器对异戊二烯进行长达1年的观测,获得异戊二烯浓度变化特征、大气化学活性和来源规律.结果表明:广州地区异戊二烯日均浓度为1.12 ppbv,由于受光照和温度影响较大,各月日均浓度在0.07~2.72 ppbv范围内波动.异戊二烯在冬季的日变化规律与其他季节不同,呈现双峰值变化,较大峰值出现在下午14:00,主要受光照和温度影响;较小峰值出现在晚上22:00左右,主要受机动车排放影响.采用最大增量活性(Maximum Incremental Reactivity,MIR)因子加权法和等效丙烯浓度法均发现异戊二烯的大气化学活性在监测的VOCs物种中最强,分别占总活性的15.45%和36.74%.通过异戊二烯与机动车标志性物质3-甲基戊烷、顺-2-丁烯的比值发现,广州地区异戊二烯在冬季夜晚主要来源于机动车排放,在秋季和春季夜晚也受到机动车排放影响,而夏季夜晚受机动车排放最不明显.这主要是由于在冬季、秋季和春季,监测点主要受到来自广州城区污染物输送的影响,而在夏季污染物从广州郊区输送使监测点受机动车排放的影响很小.异戊二烯与3-甲基戊烷、顺-2-丁烯在各季节的白天都没有线性关系,表明白天异戊二烯的排放受机动车的影响不大.     

北京及周边地区大气羰基化合物的时空分布特征初探

利用2,4-二硝基苯肼（DNPH）/HPLC方法,于2010年6月24日、7月22日、8月24日、9月14日（夏季）和2011年1月13日（冬季）,在北京及周边地区38个采样点组织5次同步观测,测定了大气中23种羰基化合物的浓度水平.观测结果表明,北京市各类站点夏季和冬季的总羰基化合物体积分数分别为（16.38±6.03）×10-9,（8.50±5.27）×10-9;周边城市夏季和冬季的体积分数分别为（13.19±5.71）×10-9,（13.05±2.44）×10-9.区域大气中最主要的羰基化合物是甲醛、乙醛和丙酮,三者约占总羰基化合物浓度的78%～91%.夏季羰基化合物的浓度水平明显高于冬季,并且上午09：00～12：00时段的浓度高于下午13：00～16：00时段的浓度.在空间分布上,北京市夏季羰基化合物的高值区主要集中在交通密集的主城区,而冬季受西北风影响呈现由西北向东南递增的趋势.夏季,机动车尾气对大气羰基化合物有显著的一次和二次贡献,同时在不利的气象条件影响下,造成城市地区羰基化合物的污染现象.冬季,大气羰基化合物以一次排放为主,燃煤和机动车可能是主要的污染源.     

Characteristics of ozone and ozone precursors (VOCs and NOx) around a petroleum refinery in Beijing, China

A field measurement campaign for ozone and ozone precursors(VOCs and NOx) was conducted in summer 2011 around a petroleum refinery in the Beijing rural region. Three observation sites were arranged, one at southwest of the refinery as the background, and two at northeast of the refinery as the downwind receptors. Monitoring data revealed the presence of serious surface O3 pollution with the characteristics of high average daily mean and maximum concentrations(64.0 and 145.4 ppbV in no-rain days, respectively) and multi-peak diurnal variation. For NOx, the average hourly concentrations of NO2 and NO were in the range of 20.5–46.1 and 1.8–6.4 ppbV, respectively. For VOC measurement, a total of 51 compounds were detected. Normally, TVOCs at the background site was only dozens of ppbC, while TVOCs at the downwind sites reached several hundreds of ppbC. By subtracting the VOC concentrations at background, chemical profiles of VOC emission from the refinery were obtained, mainly including alkanes(60.0% ± 4.3%), alkenes(21.1% ± 5.5%) and aromatics(18.9% ± 3.9%). Moreover, some differences in chemical profiles for the same measurement hours were observed between the downwind sites; the volume ratios of alkanes with low reactivity and those of alkenes with high reactivity respectively showed an increasing trend and a decreasing trend. Finally, based on temporal and spatial variations of VOC mixing ratios, their photochemical degradations and dispersion degradations were estimated to be 0.15–0.27 and 0.42–0.62, respectively, by the photochemical age calculation method, indicating stronger photochemical reactions around the refinery.     

Primary and secondary organic aerosol in an urban/industrial site: Sources, health implications and the role of plastic enriched waste burning

PM10 samples were collected from an urban/industrial site nearby Athens, where uncontrolled burning activities occur. PAHs, monocarboxylic, dicarboxylic, hydroxycarboxylic and aromatic acids, tracers from BVOC oxidation, biomass burning tracers and bisphenol A were determined. PAH, monocarboxylic acids, biomass burning tracers and bisphenol A were increased during autumn/winter, while BSOA tracers, dicarboxylic- and hydroxycarboxylic acids during summer. Regarding aromatic acids, different sources and formation mechanisms were indicated as benzoic, phthalic and trimellitic acids were peaked during summer whereas p-toluic, isophthalic and terephthalic were more abundant during autumn/winter. The Benzo[a]pyrene-equivalent carcinogenic power, carcinogenic and mutagenic activities were calculated showing significant (p < 0.05) increases during the colder months. Palmitic, succinic and malic acids were the most abundant monocarboxylic, dicarboxylic and hydrocarboxylic acids during the entire sampling period. Isoprene oxidation was the most significant contributor to BSOA as the isoprene-SOA compounds were two times more abundant than the pinene-SOA (13.4 ± 12.3 and 6.1 ± 2.9 ng/m³, respectively). Ozone has significant impact on the formation of many studied compounds showing significant correlations with: isoprene-SOA (r = 0.77), hydrocarboxylic acids (r = 0.69), pinene-SOA (r = 0.63),dicarboxylic acids (r = 0.58), and the sum of phthalic, benzoic and trimellitic acids (r = 0.44). PCA demonstrated five factors that could explain sources including plastic enriched waste burning (30.8%), oxidation of unsaturated fatty acids (23.0%), vehicle missions and cooking (9.2%), biomass burning (7.7%) and oxidation of VOCs (5.8%). The results highlight the significant contribution of plastic waste uncontrolled burning to the overall air quality degradation.     

南京北郊大气VOCs体积分数变化特征

利用2011-03-01~2012-02-29南京北郊大气VOCs观测资料,对大气VOCs体积分数的时间序列变化特征、光化学活性差异和来源特征进行了研究.结果表明,VOCs体积分数平均为43.52×10-9,并呈现夏季高,冬季低的季节变化.VOCs体积分数呈现夜间高,白天低的日变化特征.VOCs体积分数夜间呈现夏季>秋季>春季>冬季,白天呈现冬季>夏季>春季>秋季.VOCs日变化幅度秋季最大,冬季最小.烷烃和烯烃日变化幅度最大值出现在秋季,芳香烃和炔烃日变幅最大值出现在春季.采用丙烯等量体积分数方法表示,VOCs物种中烯烃含量最高,芳香烃次之,烷烃最小.T/B、E/B和X/B比值平均值分别是1.23、0.95和0.81,反映出影响观测点的气团呈现一定老化程度.以3-甲基戊烷作为机动车排放典型示踪物,估算得到乙烯、甲苯和间,对-二甲苯分别有85%、71%和82%来自非机动车源.     

我国植物VOCs排放速率的研究

1992～2000年,使用流动式、封闭式采样法,气相色谱-火焰离子化检测器,测定了我国4 种气候类型(温带-寒温带,温带,温带-亚热带,热带-亚热带),7 个地区(黑龙江,北京,福建,广东,四川,湖南,云南),共 58 种当地优势树种、庄稼和草地异戊二烯和单萜烯的排放速率.使用G93 算法,换算出相应异戊二烯和单萜烯的标准排放因子,并划分了这些排放因子的等级.同种树种在不同的气候带和季节的排放有明显的差异,通常,VOCs 排放速率南方高于北方,夏季高于冬季;阔叶树主要排放异戊二烯,针叶树主要排放单萜烯,但是我国南方相当数量的阔叶林的排放特征不符合上述规律.     

广州地区不同粒径段大气颗粒物中水溶性有机碳的吸光贡献

对广州地区春季（2015年3~4月）、夏季（2015年6~7月）、秋季（2015年9~10月）、冬季（2015年12月~2016年1月）四个季节6个粒径段（<0.49、0.49~0.95、0.95~1.5、1.5~3.0、3.0~7.2以及7.2~10.0μm）的大气颗粒物样品中水溶性有机碳（WSOC）的浓度和光学性质等变化特征进行了研究.结果表明,WSOC的浓度水平呈现冬季[（5.07±2.80）μg/m³]>秋季[（3.87±1.51）μg/m³]>春季[（3.60±1.16）μg/m³]>夏季[（2.42±0.51）μg/m³]的季节变化特征;WSOC的质量平均直径（MMD）为0.57μm （春）、0.42μm （夏）、0.49μm （秋）和0.56μm （冬）.WSOC的质量吸收效率MAE₃₆₅差异较大,分布在0.18~1.42m²/g之间,冬季最高;吸收波长指数AAE值分布在3.6~9.8之间.细颗粒物（<3μm）中WSOC对PM₁₀WSOC总吸光的贡献达到了90%以上,其中<0.49μm颗粒物的贡献超过50%.在300~500nm之间,春季、夏季、秋季和冬季WSOC对颗粒物总吸光比例平均值分别为5.23%、2.95%、3.04%和6.92%;其中<0.49μm粒径段的贡献最高,分别为3.11%、1.79%、1.65%和3.45%.进一步通过特征紫外吸光度SUVA值的分析表明芳香性和分子量可能是影响WSOC吸光能力的重要因素.粒径越小颗粒物含有越多的不饱和键,使得MAE₃₆₅值较高.     

Characterization, reactivity, source apportionment, and potential source areas of ambient volatile organic compounds in a typical tropical city

Based on one-year observation, the concentration, sources, and potential source areas of volatile organic compounds (VOCs) were comprehensively analyzed to investigate the pollution characteristics of ambient VOCs in Haikou, China. The results showed that the annual average concentration of total VOCs (TVOCs) was 11.4 ppbV, and the composition was dominated by alkanes (8.2 ppbV, 71.4%) and alkenes (1.3 ppbV, 20.5%). The diurnal variation in the concentration of dominant VOC species showed a distinct bimodal distribution with peaks in the morning and evening. The greatest contribution to ozone formation potential (OFP) was made by alkenes (51.6%), followed by alkanes (27.2%). The concentrations of VOCs and nitrogen dioxide (NO₂) in spring and summer were low, and it was difficult to generate high ozone (O₃) concentrations through photochemical reactions. The significant increase in O₃ concentrations in autumn and winter was mainly related to the transmission of pollutants from the northeast. Traffic sources (40.1%), industrial sources (19.4%), combustion sources (18.6%), solvent usage sources (15.5%) and plant sources (6.4%) were identified as major sources of VOCs through the positive matrix factorization (PMF) model. The southeastern coastal areas of China were identified as major potential source areas of VOCs through the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. Overall, the concentration of ambient VOCs in Haikou was strongly influenced by traffic sources and long-distance transport, and the control of VOCs emitted from vehicles should be strengthened to reduce the active species of ambient VOCs in Haikou, thereby reducing the generation of O₃.     

Vertical distribution of volatile organic compounds conducted by tethered balloon in the Beijing-Tianjin-Hebei region of China

Volatile organic compounds (VOCs) as precursors of ozone and secondary organic aerosols can cause adverse effects on the environment and human health. However, knowledge of the VOC vertical profile in the lower troposphere of major Chinese cities is poorly understood. In this study, tethered balloon flights were conducted over the juncture of Beijing-Tianjin-Hebei in China during the winter of 2016. Thirty-six vertical air samples were collected on selected heavy and light pollution days at altitudes of 50-1000 meters above ground level. On average, the concentration of total VOCs (TVOCs) at 50-100 m was 4.9 times higher than at 900-1000 m (46.9 ppbV vs. 8.0 ppbV). TVOC concentrations changed rapidly from altitudes of 50-100 to 401-500 m, with an average decrease of 72%. With further altitude increase, the TVOC concentration gradually decreased. The xylene/benzene ratios of 34/36 air samples were lower than 1.1, and the benzene/toluene ratios of 34/36 samples were higher than 0.4, indicating the occurrence of aged air mass during the sampling period. Alkenes contributed most in terms of both OH loss rate (39%-71%) and ozone formation potential (40%-72%), followed by aromatics (6%-38%). Finally, the main factors affecting the vertical distributions of VOCs were local source emission and negative dispersion conditions on polluted days. These data could advance our scientific understanding of VOC vertical distribution.     

广州城区近地面层大气污染物垂直分布特征

为更好地了解广州城区近地面层大气污染物的扩散与输送过程,利用广州塔4层大气污染物垂直梯度观测平台(高度分别为地面、118、168和488 m)于2014年1月—2015年12月对多种大气污染物进行连续观测,分析了广州城区近地面层大气污染物的垂直分布特征.结果表明:①ρ(PM₁₀)、ρ(PM_2.5)、ρ(PM₁)、ρ(NO₂)和ρ(NO)随高度的上升而降低,其中ρ(PM₁₀)、ρ(PM_2.5)和ρ(PM₁)在低层(地面点位)—高层(488 m点位)的递减率分别为35%、30%和26%,ρ(NO₂)和ρ(NO)分别为75%和84%;ρ(O₃)随高度上升而增加,其低层—高层的增长率为135%;ρ(SO₂)和ρ(CO)则随高度上升先增后减.②除ρ(O₃)外,其余污染物浓度均符合“冬强夏弱”的季节特征,ρ(O₃)则在夏秋季较高,春冬季较低.冬季ρ(PM₁₀)、ρ(PM_2.5)、ρ(NO₂)和ρ(NO)高、低层间差异为全年各季最大,分别为38.6、18.5、49.4和31.9 μg/m3.③各污染物小时浓度日变化特征均不同程度地受混合层发展过程的影响,各高度污染物浓度在一天中混合层高度最高的时段(12:00—17:00)最接近,而在其余时段分层较明显.除O₃外,其余污染物质量浓度在中、低层大致呈早晚双峰分布,而在高层大致呈单峰分布.ρ(O₃)则在各层均保持单峰分布,峰值一致出现在14:00.④对一次典型污染过程分析发现,不同高度的ρ(PM_2.5)和ρ(NO₂)最大差值分别可达183.0和148.0 μg/m3,ρ(PM_2.5)显著地受到本地近地面污染源的影响,污染物高浓度区域主要集中在488 m以下.      

北京上甸子区域大气本底站四氯化碳(CCl_4)在线观测

利用自组装GC-ECD系统在北京上甸子区域大气本底站开展大气四氯化碳(CCl4)摩尔分数在线观测.2007年4月～2008年3月期间,该站CCl4本底摩尔分数(89.4±0.7)×10-12,与北半球同纬度带Mace Head和Trinidad Head本底站观测结果基本一致;非本底摩尔分数(94.7±5.1)×10-12,出现频率63.6%,表明该站也能捕捉到高摩尔分数CCl4空气团输送信息;CCl4本底摩尔分数变化较小,且没有明显的季节变化;非本底摩尔分数呈现夏高冬低的特点,平均非本底摩尔分数最高月份(6月)比最低月份(1月)高7.6×10-12.应用CO比值相关法初步估算2007年4月～2008年3月我国CCl4排放量约4.7kt·a-1,与文献报道Bottom-up方法估算我国同期CCl4排放量接近;CO比值相关法估算CCl4排放量的不确定性主要来自同源假设及观测站代表性.     

春季黄、渤海中异戊二烯的浓度空间分布与海-气通量

利用吹扫捕集-气质联用方法测定了2014年5月黄海、渤海所取海水样品中异戊二烯的含量,探讨了其分布特征、海-气通量及影响因素.研究结果表明：春季黄海、渤海海域表层海水中异戊二烯的浓度范围为6.02~32.91pmol/L,（平均值±标准偏差）为（15.39±4.98）pmol/L,在黄海中部海域出现浓度高值;表层海水中异戊二烯与叶绿素a（Chl-a）浓度有一定的正相关性（R²=0.2529,n=49,P < 0.001）,说明浮游植物生物量在异戊二烯生产和分布中发挥重要作用;春季黄海、渤海异戊二烯海-气通量的变化范围为0.78~192.43nmol/（m²·d）,（平均值±标准偏差）为（24.08±30.11）nmol/（m²·d）,表明我国陆架海区是大气异戊二烯重要的源.     

内蒙古草原挥发性有机物排放通量的研究

2002年夏季,利用静态箱方法,对我国内蒙古草原生态系统挥发性有机物的排放进行了首次测量,同时观测了太阳辐射、温湿度等参数.结果表明,异戊二烯是草地挥发性有机物排放中的主要成分.异戊二烯的排放有明显的日变化、逐日变化和季节变化规律.因子分析表明,可见光辐射、温度、水汽含量是影响异戊二烯排放的主要因子,而且可见光辐射是控制其排放过程的最主要因子.根据相关分析,在考虑影响异戊二烯的排放因子时,不仅要考虑通常的影响因子--可见光辐射、温度,还要考虑水汽的作用.箱方法的使用不可避免地造成箱内外太阳辐射、温湿度等的差别,因此,必须考虑修正采样箱对挥发性有机物排放通量带来的影响.2002年夏季,异戊二烯排放通量(C)的最大值为1649.3μg/(m²·h).6、8、9月采样期间异戊二烯排放通量的日平均值分别为886.6、707.0、427.2μg/(m²·h).     

珠江三角洲天然源VOCs排放量估算及时空分布特征

利用实际观测的气象数据和基于遥感图像解译的土地利用现状和植被资料,运用GloBEIS模型,对珠江三角洲2006年度天然源VOCs排放总量进行了估算.结果表明,该区天然源VOCs的年度排放总量达29.6万t,其中异戊二烯7.30万t,占24.7%,单萜10.2万t,占34.4%.其排放量具有夏季高冬季低的典型特征,夏季占全年排放量的40.5%,冬季占11.1%.其空间特征与土地利用和植被分布密切相关,天然源VOCs排放主要集中在城镇化程度较低和林区较密集的区域.此外,对天然源VOCs排放估算过程中可能的不确定性来源进行了讨论.     

内蒙古河套灌区春小麦挥发性有机物排放特征

于2021年5月下旬至6月中旬,采用动态箱采样法对内蒙古河套灌区17种春小麦排放生物源挥发性有机物(BVOC)进行了研究,同时记录了温度、湿度和光合有效辐射(PAR)等参数.结果表明:内蒙古河套灌区春小麦主要排放异戊二烯、α-蒎烯和甲苯,生长期其排放率分别为(0.85~39.31),(2.60~14.32)和(6.41~35.39)ng/(g·h),成熟期其排放率分别为(1.75~7.99),(1.11~5.81)和(1.91~25.61)ng/(g·h);生长期异戊二烯、单萜烯类和BTEX标准状态(T=303K,PAR=1000µmol/(m²·s))下排放率分别为(12.92±5.14),(11.98±7.13)和(23.13±7.32)ng/(g·h),成熟期分别为(2.47±0.64),(5.73±1.19)和(14.23±5.27)ng/(g·h),生长期的排放率明显大于成熟期;一定环境温度和PAR范围内,河套灌区春小麦BVOC排放率与环境温度和PAR均呈指数相关,具有明显的日变化特征,但环境温度超过45℃时会抑制其BVOC排放率.     

天津近岸海域大气颗粒物无机组分季节变化及源析

2006~2007年在天津近岸海域分4个季节走航采集了不同粒径大气颗粒物样品,分析了其质量浓度以及元素、离子和碳等化学组成,并应用富集因子以及特征化合物比值对其来源进行了探讨.结果表明,天津近岸海域TSP,PM10和PM2.5的质量浓度分别为(294.98±3.95),(279.87±17.53),(205.50±38.13)μg/m3,且呈现出明显的季节变化,秋季颗粒物浓度最高,冬季次之,夏季最低. TSP、PM10和PM2.5中总元素浓度分别为48.76, 47.94,32.08 μg/m3. TSP中含量最高的离子是Na+, PM10和PM2.5中含量最高的离子是Cl-. 3种不同粒径中OC浓度秋、冬两季均明显高于春夏两季. Al/Fe的比值分析结果表明,春季TSP的主要来源为土壤尘,秋、冬季PM10和PM2.5主要受燃煤的影响. Cu、Zn和Pb的富集系数较高,其中Pb在冬季PM10中富集达到最高为741.3. NO3-/SO42-的变化范围为0.28~0.85,春夏季该比值较高于秋冬季,反映了该海域同时受燃煤与机动车污染的影响.OC/EC变化范围为2.13~5.58,表明该海域气溶胶中存在着大量二次有机碳.     

北京大气颗粒物中一元羧酸的季节变化和来源分析

通过膜采样溶剂提取、衍生化GC/MS分析,对2006年9月~2007年8月间北京大气PM10和PM2.5中的一元羧酸进行了观测研究.结果表明,可检出C10~C30的烷酸以及油酸、亚油酸和桐油酸3种烯酸,其中含量最高的是C16和C18 2种烷酸.PM10中,一元羧酸总浓度为61.7~1652.3ng/m3,年平均为426.2ng/m3;PM2.5中,一元羧酸总浓度为34.5~992.1ng/m3,年平均为319.6ng/m3.75%的一元羧酸分布在细粒子中,且冬、春季浓度明显高于夏、秋季.春、夏、秋、冬4个季节PM10中一元羧酸浓度分别为(625.1±403.8), (200.0±95.3), (263.0±201.1), (659.9±433.5)ng/m3; PM2.5中一元羧酸浓度为(431.7±211.0), (194.4±95.8), (207.9±160.8), (463.6±262.1)ng/m3.源解析显示,燃煤排放是冬季最主要的人为污染源;机动车排放则在其他季节贡献最大.     

西南典型区域夏季大气含氧挥发性有机化合物来源解析

含氧挥发性有机物（OVOCs）是大气光化学过程中的重要中间产物,是臭氧的重要来源之一.利用质子转移反应飞行时间质谱仪（PTR-TOF-MS）在成都平原对OVOCs进行观测,探讨其日变化特征、光化学反应活性、臭氧生成潜势和来源.结果表明,10个VOCs［乙醛、丙酮、异戊二烯、甲基乙基酮（methyl ethyl ketone,MEK）、甲基乙烯基甲酮（methyl vinyl ketone,MVK）、甲基丙烯醛（methacrolein,MACR）、苯、甲苯、苯乙烯、C8芳香烃和C9芳香烃］总浓度（体积分数）为（10.97±4.69）×10^-9,OVOCs为（8.54±3.44）×10^-9,芳香烃为（1.53±0.93）×10^-9,生物源VOCs为（0.90±0.32）×10^-9;光化学活性和臭氧生成潜势均排名前三的物种为：异戊二烯、乙醛和C8芳香烃;3个OVOCs物种（乙醛、丙酮和MEK）主要来源于本地生物源和人为二次源,且丙酮有较强的区域背景值,说明该地区的污染受到较为显著的区域传输的影响.本研究可加深对西南地区臭氧的区域形成机制的认识,为科学管控臭氧污染提供依据.     

Seasonal variation and sources of derivatized phenols in atmospheric fine particulate matter in North China Plain

Qualitative and quantitative analyses of derivatized phenols in Beijing and in Xinglong were performed from 2016 to 2017 using gas chromatography-mass spectrometry.The results showed substantially more severe pollution in Beijing.Of the 14 compounds detected,the total average concentration was 100 ng/m~3 in Beijing,compared with 11.6 ng/m~3 in Xinglong.More specifically,concentration of nitro-aromatic compounds(NACs)(81.9 ng/m~3 in Beijing and 8.49 ng/m3 in Xinglong) was the highest,followed by aromatic acids(14.6 ng/m~3 in Beijing and 2.42 ng/m~3 in Xinglong) and aromatic aldehydes(3.62 ng/m~3 in Beijing and 0.681 ng/m~3 in Xinglong).In terms of seasonal variation,the highest concentrations were found for 4-nitrocatechol in winter in Beijing(79.1±63.9 ng/m~3) and 4-nitrophenol in winter in Xinglong(9.72±8.94 ng/m~3).The analysis also revealed diurnal variations across different seasons.Most compounds presented higher concentrations at night in winter because of the decreased boundary layer height and increased heating intensity.While some presented higher levels during the day,which attributed to the photo-oxidation process for summer and more biomass burning activities for autumn.Higher concentrations appeared in winter and autumn than in spring and summer,which resulted from more coal combustions and adverse meteorological conditions.The significant correlations among NACs indicated similar sources of pollution.Higher correlations presented within each subgroup than those between the subgroups.Good correlations between levoglucosan and nitrophenols,nitrocatechols,nitro salicylic acids,with correlation coefficients(r) of 0.66,0.69 and 0.69,respectively,indicating an important role of biomass burning among primary sources.     

Seasonal and diurnal variations of atmospheric peroxyacetyl nitrate, peroxypropionyl nitrate, and carbon tetrachloride in Beijing

Atmospheric peroxyacetyl nitrate(PAN), peroxypropionyl nitrate(PPN), and carbon tetrachloride(CCl4) were measured from September 2010 to August 2011 in Beijing. PAN exhibited low values from mid-autumn to early spring(October to March) with monthly average concentrations ranging from 0.28 to 0.73 ppbV, and increased from early spring to summer(March to August), ranging from 1.37–3.79 ppbV. The monthly variation of PPN was similar to PAN, with low values(below detection limit to 0.18 ppbV) from mid-autumn to early spring, and a monthly maximum in September(1.14 ppbV). The monthly variation of CCl4was tightly related to the variation of temperature, exhibiting a minimum in winter(69.3 pptV) and a maximum of 180.6 pptV in summer. Due to weak solar intensity and short duration, PAN and O3showed no distinct diurnal patterns from morning to night during winter, whereas for other seasons, they both exhibited maximal values in the late afternoon(ca. 15:00 to 16:00 local time) and minimal values during early morning and midnight. Good linear correlations between PAN and PPN were found in autumn(R = 0.91), spring(R = 0.94), and summer(R = 0.81), with slopes of 0.130, 0.222, and 0.133, respectively, suggesting that anthropogenic hydrocarbons dominated the photochemical formation of PANs in Beijing. Positive correlation between PAN and O3 in summer with the low slopes( O3 / PAN) ranging from 9.92 to 18.0 indicated serious air pollution in Beijing, and strong negative correlation in winter reflected strong O3consumption by NO titration and less thermal decompositin of PAN.