南京北郊冬春季大气能见度影响因子贡献研究

为研究南京北郊气象要素以及气溶胶对大气能见度的影响,利用2014年1~5月的能见度、相对湿度、温度、颗粒物浓度及其化学成分等观测数据,探讨了气溶胶不同化学组分对消光系数的贡献,提出了该地区能见度基于不同参数的拟合方案.结果表明,观测期间平均能见度为(5.78±3.64)km,能见度与相对湿度、PM_(2.5)存在明显的负相关,相关系数分别为-0.66、-0.48.冬季平均消光系数为(398.72±219.88)Mm~(-1),Organic、NH_4NO_3、(NH_4)_2SO_4和EC对消光的贡献率分别为38.81%、27.81%、23.95%和7.15%;春季平均消光系数为(248.36±78.42)Mm~(-1),Orgamic、NH_4NO_3、(NH_4)_2SO_4和EC对消光的贡献率分别为31.59%、24.36%、32.63%和8.64%.对比不同的能见度拟合方案时,基于颗粒物成分的能见度拟合方案优于基于散射系数的.不同相对湿度区间内PM_(2.5)对能见度的影响程度不同,基于PM_(2.5)、相对湿度和温度的能见度拟合方案说明:低相对湿度的条件下,PM_(2.5)对能见度的影响较大;随相对湿度增大,相对湿度成为更为重要的影响因子.     

北京地区大气消光特征及参数化研究

为了研究大气消光系数的特征及规律,从2013~2014年在北京地区对大气能见度、气溶胶质量浓度、气溶胶散射系数、黑碳质量浓度、反应性气体以及气象要素开展了系统加强观测,并对已发表的气溶胶光散射吸湿增长因子[f(RH)]拟合方案进行了对比,系统分析了大气消光特征和影响大气消光能力的关键因子,最终建立了大气消光系数参数化模型,探讨不同季节、不同污染条件下参数化方案的特征.结果表明,气溶胶散射作用占环境总消光作用的94%以上,在夏秋季,相对湿度可以使气溶胶的散射能力提升70%~80%.包含气溶胶质量浓度和相对湿度两个因子的参数化模型,可以较好地体现出气溶胶和相对湿度对大气消光系数的影响机制,以及消光能力的季节差异.     

Role of secondary aerosols in haze formation in summer in the Megacity Beijing

A field experiment from 18 August to 8 September 2006 in Beijing, China, was carried out. A hazy day was defined as visibility < l0 km and RH (relative humidity) < 90%. Four haze episodes, which accounted for ~ 60% of the time during the whole campaign, were characterized by increases of SNA (sulfate, nitrate, and ammonium) and SOA (secondary organic aerosol) concentrations. The average values with standard deviation of SO₄^2 −, NO₃⁻, NH₄⁺ and SOA were 49.8 (± 31.6), 31.4 (± 22.3), 25.8 (± 16.6) and 8.9 (± 4.1) μg/m³, respectively, during the haze episodes, which were 4.3, 3.4, 4.1, and 1.7 times those in the non-haze days. The SO₄^2 −, NO₃⁻, NH₄⁺, and SOA accounted for 15.8%, 8.8%, 7.3%, and 6.0% of the total mass concentration of PM₁₀ during the non-haze days. The respective contributions of SNA species to PM₁₀ rose to about 27.2%, 15.9%, and 13.9% during the haze days, while the contributions of SOA maintained the same level with a slight decrease to about 4.9%. The observed mass concentrations of SNA and SOA increased with the increase of PM₁₀ mass concentration, however, the rate of increase of SNA was much faster than that of the SOA. The SOR (sulfur oxidation ratio) and NOR (nitrogen oxidation ratio) increased from non-haze days to hazy days, and increased with the increase of RH. High concentrations of aerosols and water vapor favored the conversion of SO₂ to SO₄^2 − and NO₂ to NO₃⁻, which accelerated the accumulation of the aerosols and resulted in the formation of haze in Beijing.     

Local PM10 and PM2.5 emission inventories from agricultural tillage and harvest in northeastern China

Mineral particles or particulate matters(PMs) emitted during agricultural activities are major recurring sources of atmospheric aerosol loading.However,precise PM inventory from agricultural tillage and harvest in agricultural regions is challenged by infrequent local emission factor(EF) measurements.To understand PM emissions from these practices in northeastern China,we measured EFs of PM_(10) and PM_(2.5) from three field operations(i.e.,tilling,planting and harvesting) in major crop production(i.e.,corn and soybean),using portable real-time PM analyzers and weather station data.County-level PM_(10) and PM_(2.5) emissions from agricultural tillage and harvest were estimated,based on local EFs,crop areas and crop calendars.The EFs averaged(107 ± 27),(17 ± 5) and 26 mg/m~2 for field tilling,planting and harvesting under relatively dry conditions(i.e.,soil moisture 15%),respectively.The EFs of PM from field tillage and planting operations were negatively affected by topsoil moisture.The magnitude of PM_(10) and PM_(2.5) emissions from these three activities were estimated to be 35.1 and 9.8 kilotons/yr in northeastern China,respectively,of which Heilongjiang Province accounted for approximately45%.Spatiotemporal distribution showed that most PM_(10) emission occurred in April,May and October and were concentrated in the central regions of the northeastern plain,which is dominated by dryland crops.Further work is needed to estimate the contribution of agricultural dust emissions to regional air quality in northeastern China.     

成都市冬季相对湿度对颗粒物浓度和大气能见度的影响

利用成都市城区2015年12月的连续在线观测数据,如相对湿度（RH）、能见度、颗粒物（PM₁₀、PM_2.5和PM₁）浓度、气态污染物（SO₂和NO₂）浓度以及PM_2.5中SO₄^2-和NO₃^-浓度,探讨RH对颗粒物浓度和大气能见度的影响.结果表明,高颗粒物浓度和高RH协同作用导致低能见度事件.观测阶段,PM_2.5在PM₁₀中的平均比重为64%,表明成都市冬季细颗粒物污染严重;随着RH增加,PM_2.5/PM₁₀显著增加,表明高RH会加重细颗粒物污染.随着PM_2.5浓度增加,能见度呈幂指数下降;在相同PM_2.5浓度下,RH越高,能见度越低.当颗粒物浓度较低时,RH对能见度的影响作用较强;当颗粒物浓度较高时,大气消光主要由PM_2.5浓度控制,RH对能见度的影响减弱.当RH大于70%时,硫氧化率（SOR）和氮氧化率（NOR）的均值分别从0.27和0.11（RH小于40%）增长至0.40和0.19,表明较高RH对二次硫酸盐和硝酸盐的生成有显著的促进作用,二次硫酸盐和硝酸盐单独或协同影响空气质量.     

能见度与PM2.5浓度关系及其分布特征

利用相对湿度、能见度和PM_(2.5)质量浓度观测数据,针对不同相对湿度下,建立了消光系数与PM_(2.5)质量浓度之间线性关系,并分析了相关关系的全国分布特征.结果表明,我国中东部大部分地区在一定相对湿度区间内均可建立线性相关关系,而且相关性较好,相对湿度40%～90%区间内的平均相关系数高于0. 75,其中北京相关系数高达0. 9.北京、长三角和四川等地的PM_(2.5)单位质量消光效率在同等相对湿度下明显大于其他地区.不同地区湿度对能见度影响程度不同,北京等地在相对湿度大于90%时相对湿度对能见度作用大于PM_(2.5),而广州在相对湿度大于80%时相对湿度的作用明显增强.利用能见度反算北京地区PM_(2.5)浓度可知,1980～1996年,PM_(2.5)浓度年际变化不大,受采暖方式影响冬季PM_(2.5)浓度显著较高; 1997～2009年呈现缓慢下降趋势; 2010～2012年呈现上升趋势. 1980年以来,全国的PM_(2.5)浓度整体呈上升的趋势,尤其是华北地区,PM_(2.5)浓度始终高于全国其他地区.     

成都地区气溶胶散射吸湿增长因子双变量模型

基于成都市2017年10～12月逐时的“干”气溶胶散射系数和吸收系数观测数据,结合该时段同时次的能见度（V）、相对湿度（RH）以及二氧化氮（NO₂）监测资料,利用“光学综合法”计算气溶胶散射吸湿增长因子,并探究了气溶胶散射吸湿增长因子单变量f（RH）模型的适用性及其改进方案.结果表明：幂函数、二次多项式、幂指函数形式的f（RH）模型在低RH条件下（RH<85%）均能很好地模拟气溶胶散射吸湿增长因子随RH的变化特征,但在高RH条件下（RH>85%）的模拟值会出现较大的偏差.黑碳质量浓度（C_BC）是影响气溶胶散射吸湿增长因子的另一关键变量,二者之间满足非线性关系.以RH和C_BC为自变量构建了气溶胶散射吸湿增长因子双变量f（RH,C_BC）模型,模型计算值和实测值之间的决定系数R²为0.763,平均相对误差MRE为14.28%.双变量模型f（RH,C_BC）的应用显著改善了气溶胶散射消光系数的模拟效果.     

Chemical characterization of size-resolved aerosols in four seasons and hazy days in the megacity Beijing of China

Size-resolved aerosol samples were collected by MOUDI in four seasons in 2007 in Beijing. The PM₁₀ and PM_1.8 mass concentrations were 166.0 ± 120.5 and 91.6 ± 69.7 μg/m³, respectively, throughout the measurement, with seasonal variation: nearly two times higher in autumn than in summer and spring. Serious fine particle pollution occurred in winter with the PM_1.8/PM₁₀ ratio of 0.63, which was higher than other seasons. The size distribution of PM showed obvious seasonal and diurnal variation, with a smaller fine mode peak in spring and in the daytime. OM (organic matter = 1.6 × OC (organic carbon)) and SIA (secondary inorganic aerosol) were major components of fine particles, while OM, SIA and Ca^2 + were major components in coarse particles. Moreover, secondary components, mainly SOA (secondary organic aerosol) and SIA, accounted for 46%–96% of each size bin in fine particles, which meant that secondary pollution existed all year. Sulfates and nitrates, primarily in the form of (NH₄)₂SO₄, NH₄NO₃, CaSO₄, Na₂SO₄ and K₂SO₄, calculated by the model ISORROPIA II, were major components of the solid phase in fine particles. The PM concentration and size distribution were similar in the four seasons on non-haze days, while large differences occurred on haze days, which indicated seasonal variation of PM concentration and size distribution were dominated by haze days. The SIA concentrations and fractions of nearly all size bins were higher on haze days than on non-haze days, which was attributed to heterogeneous aqueous reactions on haze days in the four seasons.     

高分辨率气溶胶光学厚度在珠三角及香港地区区域颗粒物监测中的应用研究

利用最新的MODlS(中分辨率成像光谱仪)气溶胶光学厚度(AOD)反演算法,反演珠江三角洲及香港地区2008年高分辨率(1 km x1 km)AOD分布,并与AERONET观测数据进行了验证(r=0.917).分析了2008年珠江三角洲及香港地区5个站点地面监测PM10质量浓度与反演的AOD数据相关性.结果表明:两者直...     

Source apportionment of PM2.5 light extinction in an urban atmosphere in China

Haze in China is primarily caused by high pollution of atmospheric fine particulates (PM_2.5). However, the detailed source structures of PM_2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor (PMF) analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit (R² = 0.953). The results show that the contribution rates of ammonium sulphate, ammonium nitrate, biomass burning organic aerosol (BBOA), secondary organic aerosol (SOA) and black carbon (BC) were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols (79.4% versus 20.6%) and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected.     

中山市旱季霾特征及数值模拟分析

利用观测数据、Hysplit后向轨迹模式以及WRF-CMAQ模式对中山市旱季霾特征进行模拟分析.中山市霾污染的天气形势以大陆高压型为主.当相对湿度在71%~90%时,气溶胶浓度和能见度的负相关性最显著,且当能见度减小到5 km以下时,PM_(2.5)浓度的大幅减小才能使能见度略有好转.最有可能引起中山发生霾天气的两条污染带,一条是沿中山至湖南南部,另一条是沿中山到粤东地区.WRF-CMAQ模式能较好地模拟出2014年1月份中山PM_(2.5)浓度、能见度的变化趋势以及广东省区域内灰霾的污染过程.在气溶胶质量权重及消光贡献中,硫酸盐的比重最高,在高相对湿度下,二次气溶胶的消光权重超过80%.通过中山PM_(2.5)过程分析发现,在霾过程,无冷空气时PM_(2.5)主要来自气溶胶反应、排放源和水平平流,贡献率分别为35%、15%和10%,有冷空气时水平平流的贡献最大,达37%;在清洁过程,无冷空气时气溶胶主要靠水平平流和干沉降清除,贡献率分别为-39%和-14%,有冷空气时清除以水平平流和垂直对流、扩散为主,贡献率分别为-29%和-25%,说明不同天气条件下霾的污染和清洁机制有着明显差别.     

Emissions from the combustion of eucalypt and pine chips in a fluidized bed reactor

Interest in renewable energy sources has increased in recent years due to environmental concerns about global warming and air pollution,reduced costs and improved efficiency of technologies.Under the European Union(EU)energy directive,biomass is a suitable renewable source.The aim of this study was to experimentally quantify and characterize the emission of particulate matter(PM_(2.5))resulting from the combustion of two biomass fuels(chipped residual biomass from pine and eucalypt),in a pilot-scale bubbling fluidized bed(BFB)combustor under distinct operating conditions.The variables evaluated were the stoichiometry and,in the case of eucalypt,the leaching of the fuel.The CO and PM_(2.5)emission factors were lower when the stoichiometry used in the experiments was higher(0.33±0.1 g CO/kg and 16.8±1.0 mg PM_(2.5)/kg,dry gases).The treatment of the fuel by leaching before its combustion has shown to promote higher PM_(2.5)emissions(55.2±2.5 mg/kg,as burned).Organic and elemental carbon represented 3.1 to 30 wt.% of the particle mass,while carbonate(CO_3~(2-))accounted for between 2.3 and 8.5 wt.%.The particulate mass was mainly composed of inorganic matter(71% to 86% of the PM_(2.5)mass).Compared to residential stoves,BFB combustion generated very high mass fractions of inorganic elements.Chloride was the water soluble ion in higher concentration in the PM_(2.5)emitted by the combustion of eucalypt,while calcium was the dominant water soluble ion in the case of pine.     

成都市PM10中碳质气溶胶长期来源特点

大气颗粒物中包含多种组分的气溶胶,其中碳质气溶胶由于对人体健康、能见度有较大影响,已受到越来越多的关注.为研究碳质气溶胶的长期变化规律,采集了成都市2009—2013年的PM₁₀样品,对其中所含的无机元素、水溶性离子及碳组分分别进行测定,并使用“PMF（正定矩阵因子分解法）-比值”模型分别对PM₁₀和所含的碳质气溶胶的来源进行分析.结果表明,1月、2月、5月和12月的碳质气溶胶浓度较高,其中1月、2月和12月的OC/EC（有机碳与元素碳质量浓度之比）较高,并且PMF-比值模型计算结果也显示冬季SOC增多,表明冬季可能有更多的二次有机碳（SOC）生成;5月的char-EC/soot-EC（二者质量浓度之比,其中char-EC=EC1-OP,soot-EC=EC2+EC3,它们可更好地区分源类）较高,K含量也较高,表明可能有更多的生物质燃烧排放.PM₁₀解析共发现6类源,依次为地壳扬尘（26.5%）、二次硫酸盐（25.1%）、燃煤&生物质燃烧混合源（17.3%）、二次硝酸盐&二次有机碳混合源（12.3%）、机动车源（11.8%）和水泥尘源（7.0%）;碳质气溶胶解析发现,OC主要来源依次为机动车源（38.2%）、燃煤&生物质燃烧混合源（33.1%）和二次有机碳（25.3%）,char-EC的主要来源是燃煤&生物质燃烧混合源和机动车源,分别占50.5%和45.4%,soot-EC则主要受机动车影响（达73.2%）.研究显示,成都市PM₁₀主要来自于地壳扬尘、二次生成和燃煤&生物质燃烧,而碳质气溶胶主要来自于机动车、燃煤&生物质燃烧.      

Chemical characteristics of fine particles and their impact on visibility impairment in Shanghai based on a 1-year period observation

In this work, a one-year observation focusing on high time resolution characteristics of components in fine particles was conducted at an urban site in Shanghai. Contributions of different components on visibility impairment were also studied. Our research indicates that the major components of PM_2.5 in Shanghai are water-soluble inorganic ions and carbonaceous aerosol, accounting for about 60% and 30% respectively. Higher concentrations of sulfate (SO₄²⁻) and organic carbon (OC) in PM_2.5 occurred in fall and summer, while higher concentrations of nitrate (NO₃⁻) were observed in winter and spring. The mass concentrations of Cl⁻ and K⁺ were higher in winter. Moreover, NO₃⁻ increased significantly during PM_2.5 pollution episodes. The high values observed for the sulfate oxidizing rate (SOR), nitrate oxidizing rate (NOR) and secondary organic carbon (SOC) in OC indicate that photochemical reactions were quite active in Shanghai. The IMPROVE (Interagency Monitoring of Protected Visual Environments) formula was used in this study to investigate the contributions of individual PM_2.5 chemical components to the light extinction efficient in Shanghai. Both NH₄NO₃ and (NH₄)₂SO₄ had close relationships with visibility impairment in Shanghai. Our results show that the reduction of anthropogenic SO₂, NO_x and NH₃ would have a significant effect on the improvement of air quality and visibility in Shanghai.     

天津冬季相对湿度对气溶胶浓度谱分布和大气能见度的影响

于2013年1月连续在线观测天津城区气溶胶数浓度谱分布和大气能见度,并结合相关气象资料,探讨相对湿度(RH)对气溶胶浓度谱分布和大气能见度的影响.结果表明,观测期间发生了4次连续雾霾天气过程, 4次雾霾天气过程对应着气溶胶粒子数浓度的连续高值,低能见度天气系高浓度气溶胶粒子和高相对湿度协同所致;随着RH增大,PN1和PN2.5-10呈增长趋势, RH>90%后,PN1和PN2.5-10有所降低,PN1-2.5则持续增长,高RH对气粒转化和气溶胶粒子的碰并聚合作用明显;气溶胶吸湿增长因子计算表明,高RH下水汽对能见度影响很大,尤其是大雾天气下其影响甚至可能超过气溶胶粒子浓度对其的影响.     

Aerosol scattering coefficients and major chemical compositions of fine particles observed at a rural site in the central Pearl River Delta, South China

During November-December 2010 aerosol scattering coefficients were monitored using a single-waved (525 nm) Nephelometer at a regional monitoring station in the central Pearl River Delta region and 24-hr fine particle (PM_2.5) samples were also collected during the period using quartz filters for the analysis of major chemical components including organic carbon (OC), elemental carbon (EC), sulfate, nitrate and ammonium. In average, these five components accounted for about 85% of PM_2.5 mass and contributed 42% (OC), 19% (SO₄^2-), 12% (NO₃^-), 8.4% (NH₄⁺) and 3.7% (EC), to PM_2.5 mass. A relatively higher mass scattering efficiency of 5.3 m²/g was obtained for fine particles based on the linear regression between scattering coefficients and PM_2.5 mass concentrations. Chemical extinction budget based on IMPROVE approach revealed that ammonium sulfate, particulate organic matter, ammonium nitrate and EC in average contributed about 32%, 28%, 20% and 6% to the light extinction coefficients, respectively.     

Evolutionary processes and sources of high-nitrate haze episodes over Beijing, Spring

Rare and consecutive high-nitrate haze pollution episodes were observed in Beijing in spring2012. We present detailed characterization of the sources and evolutionary mechanisms of this haze pollution, and focus on an episode that occurred between 15 and 26 April. Submicron aerosol species were found to be substantially elevated during haze episodes, and nitrates showed the largest increase and occupation(average: 32.2%) in non-refractory submicron particles(NR-PM_1), which did not occur in other seasons as previously reported. The haze episode(HE) was divided into three sub-episodes, HEa, HEb, and HEc. During HEa and HEc, a shallow boundary layer, stagnant meteorological conditions, and high humidity favored the formation of high-nitrate concentrations, which were mainly produced by three different processes —daytime photochemical production, gas-particle partitioning, and nighttime heterogeneous reactions — and the decline in visibility was mainly induced by NR-PM_1.However, unlike HEa and HEc, during HEb, the contribution of high nitrates was partly from the transport of haze from the southeast of Beijing — the transport pathway was observed at ~800–1000 m by aerosol Lidar —and the decline in visibility during HEb was primarily caused by PM_(2.5). Our results provide useful information for air quality improvement strategies in Beijing during Spring.     

浙江金华秋季干气溶胶中主要化学组分的消光贡献解析

造成雾霾事件的主要原因是高浓度的大气细颗粒物污染.为了深入研究大气细颗粒物的消光来源,本研究采用高时间分辨率气溶胶观测仪器获得了浙江金华秋季PM1主要化学组分浓度及干气溶胶吸收系数和散射系数演变情况.结合有机气溶胶正矩阵因子解析模型(PMF)和多元线性回归方法,建立了拟合优度很高(R2=0.977)的细颗粒物中主要化学组分与干气溶胶消光系数间的定量关系模型.结果表明,观测期间消光贡献最大的是硫酸铵,贡献率为35.1%;其次是硝酸铵,贡献率为26.7%;二次有机气溶胶(SOA)、生物质燃烧有机气溶胶(BBOA)、黑碳(BC)及氯化铵的消光贡献率分别为14.3%、11.2%、8.7%、4.0%.在一些特定污染时段,BBOA具有最大的消光贡献,是导致此时大气能见度大幅度衰减的首要因子.     

Particulate matter assessment of a wetland in Beijing

To increase the knowledge on the particulate matter of a wetland in Beijing, an experimental study on the concentration and composition of PM₁₀ and PM_2.5 was implemented in Beijing Olympic Forest Park from 2013 to 2014. This study analyzed the meteorological factors and deposition fluxes at different heights and in different periods in the wetlands. The results showed that the mean mass concentrations of PM₁₀ and PM_2.5 were the highest at 06:00–09:00 and the lowest at 15:00–18:00. And the annual concentration of PM₁₀ and PM_2.5 in the wetland followed the order of dry period (winter) > normal water period (spring and autumn) > wet period (summer), with the concentration in the dry period significantly higher than that in the normal water and wet periods. The chemical composition of PM_2.5 in the wetlands included NH₄⁺, K⁺, Na⁺, Mg^2 +, SO₄^2 −, NO₃⁻, and Cl⁻, which respectively accounted for 12.7%, 1.0%, 0.8%, 0.7%, 46.6%, 33.2%, and 5.1% of the average annual composition. The concentration of PM₁₀ and PM_2.5 in the wetlands had a significant positive correlation with relative humidity, a negative correlation with wind speed, and an insignificant negative correlation with temperature and radiation. The daily average dry deposition amount of PM₁₀ in the different periods followed the order of dry period > normal water period > wet period, and the daily average dry deposition amount of PM_2.5 in the different periods was dry period > wet period > normal water period.     

Chemical and optical properties of aerosols and their interrelationship in winter in the megacity Shanghai of China

A field campaign on air quality was carried out in Shanghai in winter of 2012. The concentrations of NO, NO₂, NO_x, SO₂, CO, and PM_2.5 increased during haze formation. The average masses of SO₄^2-, NO₃^- and NH₄⁺ were 10.3, 11.7 and 6.7 μg/m³ during the haze episodes, which exceeded the average (9.2, 7.9, and 3.4 μg/m³) of these components in the non-haze days. The mean values for the aerosol scattering coefficient (b_sp), aerosol absorption coefficient (b_ap) and single scattering albedo (SSA) were 288.7, 27.7 and 0.91 Mm^-1, respectively. A bi-peak distribution was observed for the mass concentrations of CO, NO, NO₂, and NO_x. More sulfate was produced during daytime than that in the evening due to photochemical reactions. The mass concentration of NH₄⁺ achieved a small peak at noontime. NO₃^- showed lower concentrations in the afternoon and higher concentrations in the early morning. There were obvious bi-peak diurnal patterns for bsp and bap as well as SSA. bsp and bap showed a positive correlation with PM_2.5 mass concentration. (NH₄)₂SO₄, NH₄NO₃, organic mass, elemental carbon and coarse mass accounted for 21.7%, 19.3%, 31.0%, 9.3% and 12.3% of the total extinction coefficient during non-haze days, and 25.6%, 24.3%, 30.1%, 8.1% and 8.2% during hazy days. Organic matter was the largest contributor to light extinction. The contribution proportions of ammonium sulfate and ammonium nitrate to light extinction were significantly higher during the hazy time than during the non-haze days.