珠三角地区不同季节颗粒物数谱分布特性

基于珠三角大气超级站不同季节3 nm~10μm颗粒物数谱分布在线监测数据,系统分析不同季节颗粒物数浓度、表面积浓度与体积浓度的水平与构成及数谱分布日变化规律,揭示了珠三角地区颗粒物数谱分布特征。结果表明,冬季、春季和秋季珠三角大气超级站总颗粒物数浓度分别为2.17×104、1.97×104、2.24×104个/立方厘米,总颗粒物表面积浓度分别为2.98×103、2.28×103、2.78×103μm2/cm3,总颗粒物体积浓度分别为1.33×102、1.04×102、1.40×102μm3/cm3。颗粒物总数浓度中,爱根核模和积聚模态颗粒物是主要贡献者,在总数浓度的比例均达到40%以上;总颗粒物表面积浓度中,积聚模态颗粒物是主要贡献者,月平均比例高达88%以上;总颗粒物体积浓度中,积聚模态颗粒物也是主要贡献者,月平均贡献为65%~80%,其次为粗粒子模贡献较大,比例为20%~30%。积聚模态颗粒物的重要贡献较好地体现了超级站的区域性。冬季、春季和秋季颗粒物数浓度平均日变化趋势均为7:00~9:00和18:00~20:00存在较高的爱根核模态颗粒物数浓度,意味着机动车排放对细颗粒物污染的影响较显著。10月颗粒物数谱分布平均日变化中存在明显的颗粒物增长过程,体现了新粒子生成事件的重要影响。     

交通限行对大气颗粒物及PM_(2.5)中二■英的影响

为了研究北京大气颗粒物和二■英(PCDD/Fs)的污染状况以及评估交通限行对大气颗粒物和PCDD/Fs的影响。利用同位素稀释高分辨率气相色谱/高分辨率质谱(HRGC/HRMS)联用法和USEPA 1613B标准方法,以中国地质大学(北京)东门为采样点,采集大气PM_(2.5)、PM_(10)、TSP样品,对北京市交通限行期间以及交通限行前后等不同交通状况下颗粒物浓度及大气PM_(2.5)中17种2,3,7,8-PCDD/Fs污染特征进行了监测。结果表明,PM_(2.5)、PM_(10)、TSP的日均质量浓度在交通限行前分别为126、202、304μg/m~3,限行期间分别为39、78、93μg/m~3,限行结束后分别为79、126μg/m~3。PM_(2.5)中17种PCDD/Fs的质量浓度(毒性浓度) 3个时段分别为1 804 fg/m~3(70 fg I-TEQ/m~3)、252 fg/m~3(9 fg I-TEQ/m~3)和1 196 fg/m~3(48 fg I-TEQ/m~3)。北京市交通限行期间颗粒物浓度和二■英浓度显著低于交通限行前后,交通源减排措施的实施是大气颗粒物和二■英污染水平降低的主要原因,从减排效果看,交通源减排措施对大气细颗粒物(PM_(2.5))的控制效果明显好于大气粗颗粒物。     

一次连续在线观测分析天津市细颗粒物污染特征

根据2005年的5月17日—5月23日GR IMM(1.109#)谱分析仪在线观测结果考察天津市细颗粒物浓度和质量浓度特征。观测期间,天津市颗粒物数浓度平均值为1 124 cm-3,粒径分布为0.25μm~0.60μm,98.5%粒子的粒径0.65μm。同期PM10日均质量浓度值为204μg/m3,ρ(PM2.5)为104μg/m3,ρ(PM1.0)为82.9μg/m3。ρ(PM1.0)/ρ(PM2.5)超过80%,粒径1μm超细颗粒物为天津城市大气颗粒物的主要成分。     

上海市浦东城区冬季颗粒物数浓度及其谱分布特征

采用APS-3321空气动力学粒径谱仪对上海市浦东城区2012年12月至2013年2月0.5~20μm大气颗粒物浓度及其谱分布进行了实时监测。结果发现,上海市浦东城区冬季大气颗粒物数浓度为360个/cm3,其中0.5~1.0μm颗粒物数为345个/cm3,占总颗粒物的95.7%;1.0~2.5μm颗粒物数为15个/cm3,占颗粒物总数的4.1%;2.5~20.0μm颗粒物数为0.6个/cm3,占颗粒物总数的0.2%。当空气质量为AQI≤50、50AQI≤100、100AQI≤200、AQI200时,颗粒物数浓度分别为77.5、243.2、522.6、868.5个/m3。随着空气污染的加重,小于PM2.5颗粒物数浓度增加显著且对总的颗粒物数浓度的贡献也有所增加,且AQI200时,PM2.5中1.0~2.5μm颗粒物数浓度贡献增幅最大;此外,不同空气质量条件下,颗粒物数浓度的日变化存在一定差异,这对于空气污染防治具有重要意义。     

冬季南京城区气溶胶化学组分和吸湿性观测

大气气溶胶的吸湿特性改变了颗粒物的粒径、光学性质、云凝结核活性,进而对大气能见度、地面辐射强迫和人体健康产生重要影响。针对长三角腹地城市南京重污染天气频发现象,笔者使用吸湿串联电迁移差分分析仪(H-TDMA)结合在线气体组分及气溶胶监测系统(MARGA)和相关气象数据对冬季南京城区气溶胶吸湿增长特性进行外场观测研究。结果表明:灰霾期间SO_4~(2-)、NO_3~-、NH_4~+的质量浓度分别为(17.57±9.07)(26.16±11.39)(13.61±6.68)μg/m~3,非灰霾期间为(9.62±3.58)(12.12±7.51)(5.78±3.59)μg/m~3,前者是后者的2倍。水溶性组分质量浓度大小依次为NO_3~-SO_4~(2-)NH_4~+Cl~-K~+Ca~(2+)Na~+Mg~(2+)。其中NO_3~-的贡献最大,占PM_(2.5)的29%,其次是SO_4~(2-)占14%,NH_4~+占8%。其他水溶性组分(Cl~-、K~+、Ca~(2+)、Na~+、Mg~(2+))约占PM_(2.5)的5.9%。SO_4~(2-)、NO_3~-、NH_4~+的质量浓度没有明显日变化且保持在较高水平。观测期间气溶胶的不同粒径段粒子吸湿增长因子概率密度分布(GF-PDF)均呈双峰,随粒径增大,强吸湿组粒子的吸湿性增大,而弱吸湿组的吸湿性减弱。其中,40 nm粒径段粒子强、弱吸湿增长因子分别为1.335±0.03和1.054±0.008,80 nm粒径段为1.348±0.03和1.053±0.011,40 nm较80 nm粒径段的粒子弱吸湿峰更为明显。灰霾期间粒子的吸湿增长因子分别为1.307±0.08和1.413±0.07,非灰霾期间为1.230±0.03和1.300±0.03。冷锋过境时气溶胶弱吸湿组谱分布没有明显的变化,强吸湿组谱分布明显向弱吸湿方向偏移,吸湿性减弱。灰霾期间和整个观测期间PM_(2.5)的平均质量浓度分别为(87.56±25.87)(69.31±28.75)μg/m~3,灰霾期间主要的二次气溶胶质量浓度占PM_(2.5)的66%,而粒子的平均吸湿增长因子从1.325±0.03降低到1.301±0.07。特殊时段春节期间弱吸湿组粒子的吸湿性增大,而强吸湿组粒子的吸湿性减弱。其中110 nm粒径段粒子强吸湿组吸湿增长因子明显下降,SO_4~(2-)、NO_3~-、NH_4~+的质量浓度也发生明显下降,吸湿增长因子和水溶性化学组分的变化呈良好一致性。     

石化基地大气VOCs大气化学反应活性分析

为了识别独山子石化基地大气VOCs大气化学反应活性和关键活性组份,2013年在研究区内高约25 m的楼顶采用在线的气相色谱仪进行了VOCs观测。结果表明,独山子石化基地大气VOCs的冬季OH消耗速率常数(L~(OH))为29.6×10~(-12)cm~3/分子·s,平均VOCs最大O3增量反应活性(MIR)为248.3 g/g,比乙烯的OH消耗速率常数(0.21×10~(-12)cm~3/分子·s)和最大O3增量反应活性(5.48 g/g)高出149倍和45倍,说明冬季独山子石化基地区域大气中VOCs的大气化学反应活性极强。大气VOCs的OH消耗速率常数(L~(OH))月变化呈现"L"型分布,其中烯烃的OH消耗速率常数(L~(OH))占比最大,占压倒性优势,1月和7月高达90%,其他月份也在70%~85%。冬季大气VOCs最大O_3增量反应活性(MIR)是夏季35倍,只因冬季寒冷且光照弱,使得O_3浓度不高,但导致PM_(2.5)浓度居高不下。     

百色市PM10和PM2.5中有机碳和元素碳污染特征及来源解析

2015—2016年在百色市布设3个采样点采集PM_(10)和PM_(2.5)样品,分析其中有机碳(OC)和元素碳(EC)的含量。结果表明,PM_(10)和PM_(2.5)中OC、EC四季均值分别为15.0μg/m~3、5.55μg/m~3和11.7μg/m~3、4.72μg/m~3;OC与EC相关性不显著,存在不同的污染来源;OC/EC值多数2,存在二次污染,主要来源于柴油、汽油车尾气和燃煤的排放。由总碳质气溶胶(TCA)和8个碳组分丰度分析可知,百色市碳气溶胶(CA)来源于汽车尾气、道路扬尘、燃煤的排放。二次有机碳(SOC)在OC中的占比均75%,表明百色市大气颗粒物中OC以SOC为主,夜间污染重于昼间。     

因子分析法解析北京市大气颗粒物PM10的来源

2004年10月份在北京市6个采样点采集了大气PM10样品,分析了大气颗粒物的质量浓度、元素组成、离子、有机碳(OC)和元素碳(EC)的浓度,并用因子分析模型对颗粒物的来源进行了研究。结果显示,北京市大气颗粒物的来源主要有6类:建筑水泥尘/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘、生物质燃烧尘和燃油尘。用模型计算得到的各源对PM10的贡献率分别为建筑水泥尘/机动车尾气尘/燃煤尘占36.57%、土壤风沙尘占16.07%、二次粒子尘占12.33%、工业粉尘占10.29%、生物质燃烧尘占6.07%、燃油尘占3.84%、其它占14.84%。其中建筑水泥/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘是大气颗粒物PM10的主要来源。实验表明,在缺少源成分谱时可以用因子分析模型来分析大气颗粒物的来源及其相对贡献。     

徐州市区春季大气中VOCs污染特征分析

2017年3月-5月采用大气挥发性有机物在线连续自动监测系统对徐州市新城区大气中102种VOCs进行观测,分析徐州市春季大气中VOCs的体积和组成特征。结果发现:观测期间,徐州市大气中VOCs的小时体积分数为(3.81~221.85)×10~(-9),平均体积分数为27.97×10~(-9);各物种体积占比依次为烷烃、含氧有机物、卤代烃、芳香烃和烯(炔)烃;占比最高的5种污染物是乙烷、丙酮、乙烯、乙炔和丙烷。徐州市臭氧处在VOCs控制区,对臭氧生成潜势(OFP)贡献率最大的是含氧有机物(33.99%)和芳香烃(32.21%);关键活性组分是乙烯、正己醛、甲苯、间/对-二甲苯和丁烯酮。     

上海室内外降尘磁学空间变化特征

采用磁学方法分析上海市室内外降尘样品的磁学参数在不同功能区和不同行政区的变化特征,探讨影响室内外降尘磁学性质的影响因素。研究结果表明:上海市大气降尘污染有自然和人为2种影响因素;室内外降尘样品的磁性特征均受磁铁矿控制,主要以假单畴和多畴颗粒为主;低频磁化率在功能区上呈现出工业区(553.464×10~(-8)m~3/kg)交通区(484.302×10~(-8) m~3/kg)商业区(443.216×10~(-8) m~3/kg)居住区(320.849×10~(-8) m~3/kg)清洁区(269×10~(-8) m~3/kg)的空间变化趋势在行政区上整体呈现出宝山区(558.104×10~(-8) m~3/kg)、杨浦区(464.263×10~(-8) m~3/kg)的磁化率偏高,崇明区(218.673×10~(-8) m~3/kg)、奉贤区(218.868×10~(-8) m~3/kg)、松江区(218.689×10~(-8) m~3/kg)磁化率较低。室内外降尘的低频磁化率(χ_(if))、饱和等温剩磁(SIRM)和非磁滞剩磁磁化率(χ_(ARM))的相关系数分别为0.777、0.504、0.547,有较好的正相关关系表明室内外降尘来源很可能存在一定的趋同性。对比分析不同磁学参数,可以更好地反映降尘污染状况。研究发现χ_(lf)、SIRM和χ_(ARM)可以作为上海市大气降尘磁性特征的有效参考指标。在不同行政区大气降尘磁化率和PM_(10)浓度表现出相似的空间变化趋势。降尘样品的磁学参数测量速度快,方便用于监测城市空气污染的状况,在一定程度上可以对空气污染指数有一定的指代作用。     

Biogeochemical patterns in a river network along a land use gradient

The Bode catchment (Germany) shows strong land use gradients from forested parts of the National Park (23 % of total land cover) to agricultural (70 %) and urbanised areas (7 %). It is part of the Terrestrial Environmental Observatories of the German Helmholtz association. We performed a biogeochemical analysis of the entire river network. Surface water was sampled at 21 headwaters and at ten downstream sites, before (in early spring) and during the growing season (in late summer). Many parameters showed lower concentrations in headwaters than in downstream reaches, among them nutrients (ammonium, nitrate and phosphorus), dissolved copper and seston dry mass. Nitrate and phosphorus concentrations were positively related to the proportion of agricultural area within the catchment. Punctual anthropogenic loads affected some parameters such as chloride and arsenic. Chlorophyll a concentration and total phosphorus in surface waters were positively related. The concentration of dissolved organic carbon (DOC) was higher in summer than in spring, whereas the molecular size of DOC was lower in summer. The specific UV absorption at 254 nm, indicating the content of humic substances, was higher in headwaters than in downstream reaches and was positively related to the proportion of forest within the catchment. CO₂ oversaturation of the water was higher downstream compared with headwaters and was higher in summer than in spring. It was correlated negatively with oxygen saturation and positively with DOC concentration but negatively with DOC quality (molecular size and humic content). A principle component analysis clearly separated the effects of site (44 %) and season (15 %), demonstrating the strong effect of land use on biogeochemical parameters.     

Estimating Air Quality in a Traffic Tunnel Using a Forecasting Combination Model

This study performs a field analysis of the diffusion collection rate coefficients of radial geometry passive samplers to measure NO₂ in a Mediterranean coastal area. The study shows that the collection rate coefficients are not constant and depend on certain environmental parameters as well as on the levels of some co-pollutants. A mathematical model, which explains the variation of the collection rate coefficient, has been established.     

Benthic Biological Processes and EH as a Basis for a Benthic Index

It is proposed that the common measures of benthic community condition can be augmented with a vertical EH profile taken through the benthic bioturbation zone. Sediment EH, an electrochemical measure of oxidized and reduced compounds in sediment porewater, measures the integrative consequences of all metabolic and transport processes of the benthic community. Biota, especially microbiota, metabolize carbon using a variety of electron acceptors, including O2, SO4 and some nitrogen and metal compounds. Motile benthic macrofauna ingest and transport particles, ventilate deep burrows and anoxic sediment with overlying seawater while sedentary suspension-feeding fauna deposit suspended organic matter onto the sediment surface. Collectively, these metabolic and behavioral processes advect particles and seawater between bottom water and deep sediment and define the overall structure of porewater chemistry. That structure creates a full spectrum of biogeochemical conditions of solubility, reactivity, and microbial metabolism which remineralizes excess organic carbon and most organic contaminants, defines solubility of trace metals, and pushes the vertical EH profile toward oxidizing conditions. It is proposed that a standard EH probe inserted downward through the bioturbation zone will provide a general measure of this resulting porewater chemistry and thus the impact of feeding, irrigation, and metabolism of the total macro, meio, and microbenthic community. If such a measure can be validated it will permit extended measurement of community function and reduced efforts in measuring community structure.     

Using statistical power analysis as a tool when designing a monitoring program: experience from a large-scale Swedish landscape monitoring program

The National Inventory of Landscapes in Sweden (NILS) is a large-scale, sample-based monitoring program that combines aerial photointerpretation with field inventory to follow landscape-scale biophysical conditions and changes. A statistical power analysis was conducted before the NILS program began in 2003 with the aim to determine an appropriate sampling effort and compare some design alternatives. The chosen sampling effort was then evaluated in a second power analysis conducted just before the first 5-year re-inventory rotation started. The latter power analysis revealed which magnitude of actual change might be detected within the future for different central monitoring variables. This article reports results from these power analyses and discusses our experiences in using power analysis as a tool for designing large-scale monitoring programs. The results showed that even quite small changes in the more common variables, such as land cover types and more common plant species, can be detected on the national scale. However, on the regional scale, or for less common variables, changes will be more difficult to detect. The power analyses have revealed the size level of changes that will be possible to detect. The results have also generated incentives for further improvements of NILS, e.g., input to the modification and revision of the variable content, flow and hierarchy, and incentives for launching other complementary monitoring programs connected to NILS. They have also created a basis for a better and more user-oriented communication of results from NILS to different stakeholders.     

The Composition of PM10 as collected by a Conventional TEOM, a Modified TEOM and a Partisol Gravimetric Monitor at a Kerbside Site in the North East of England

The composition of airborne particulate matter sampled by a conventional TEOM^®, an experimental modified TEOM, operated at a lower temperature but fitted with a drier to remove moisture and a Partisol^®, installed at a kerbside site in the North East of England, has been investigated. The results indicate that there is a seasonal variation in the composition of PM₁₀ as sampled by the three monitors, with chloride concentration being significantly higher in the winter. The Partisol was found to sample a higher mass of chloride and nitrate, however the differences between the monitors was only significant for chloride. Both TEOM's were found to sample a greater mass of sulphate, although the variability in the data collected meant that significance of the results was not proven statistically. The range of artifacts associated with PM₁₀ monitors is reviewed. Difficulties in the interpretation of results due to the variable nature of airborne particulate matter and the ability of filter based systems to accurately represent the composition of atmospheric particles are considered.     

The composition of PM10 as collected by a conventional TEOM, a modified TEOM and a Partisol gravimetric monitor at a kerbside site in the North East of England

The composition of airborne particulate matter sampled by a conventional TEOM, an experimental modified TEOM, operated at a lower temperature but fitted with a drier to remove moisture and a Partisol, installed at a kerbside site in the North East of England, has been investigated. The results indicate that there is a seasonal variation in the composition of PM(10) as sampled by the three monitors, with chloride concentration being significantly higher in the winter. The Partisol was found to sample a higher mass of chloride and nitrate, however the differences between the monitors was only significant for chloride. Both TEOM's were found to sample a greater mass of sulphate, although the variability in the data collected meant that significance of the results was not proven statistically. The range of artifacts associated with PM(10) monitors is reviewed. Difficulties in the interpretation of results due to the variable nature of airborne particulate matter and the ability of filter based systems to accurately represent the composition of atmospheric particles are considered.     

Characterizing ozone pollution in a petrochemical industrial area in Beijing,China: a case study using a chemical reaction model

This study selected a petrochemical industrial complex in Beijing, China, to understand the characteristics of surface ozone (O₃) in this industrial area through the on-site measurement campaign during the July–August of 2010 and 2011, and to reveal the response of local O₃ to its precursors’ emissions through the NCAR-Master Mechanism model (NCAR-MM) simulation. Measurement results showed that the O₃ concentration in this industrial area was significantly higher, with the mean daily average of 124.6 μg/m³ and mean daily maximum of 236.8 μg/m³, which are, respectively, 90.9 and 50.6 % higher than those in Beijing urban area. Moreover, the diurnal O₃ peak generally started up early in 11:00–12:00 and usually remained for 5–6 h, greatly different with the normal diurnal pattern of urban O₃. Then, we used NCAR-MM to simulate the average diurnal variation of photochemical O₃ in sunny days of August 2010 in both industrial and urban areas. A good agreement in O₃ diurnal variation pattern and in O₃ relative level was obtained for both areas. For example of O₃ daily maximum, the calculated value in the industrial area was about 51 % higher than in the urban area, while measured value in the industrial area was approximately 60 % higher than in the urban area. Finally, the sensitivity analysis of photochemical O₃ to its precursors was conducted based on a set of VOCs/NOx emissions cases. Simulation results implied that in the industrial area, the response of O₃ to VOCs was negative and to NOx was positive under the current conditions, with the sensitivity coefficients of ?0.16~?0.43 and +0.04~+0.06, respectively. By contrast, the urban area was within the VOCs-limitation regime, where ozone enhancement in response to increasing VOCs emissions and to decreasing NOx emission. So, we think that the VOCs emissions control for this petrochemical industrial complex will increase the potential risk of local ozone pollution aggravation, but will be helpful to inhibit the ozone formation in Beijing urban area through reducing the VOCs transport from the industrial area to the urban area.