华北区域点冬季二次有机气溶胶特征与影响因素

为探明二次有机气溶胶(SOA)的污染特征和影响因素,本研究于2018年11月—2019年1月对华北区域点(德州市郊区点)细颗粒物(PM_(2.5))的化学组成进行了在线测量,并分析了PM_(2.5)中有机碳(OC)、元素碳(EC)和水溶性离子组分的污染特征及PM_(2.5)与气象要素之间的相关性.结果表明,观测期间德州PM_(2.5)污染严重,平均质量浓度为(115.6±24.6)μg·m~(-3);其中,有机碳和元素碳是PM_(2.5)的主要成分,平均质量浓度分别为(8.2±5.8)μg·m~(-3)和(2.6±2.2)μg·m~(-3),占PM_(2.5)总质量的7.1%和2.2%;PM_(2.5)与风速呈负相关,与相对湿度呈正相关,与气温的相关性较差,偏北风对PM_(2.5)浓度影响较大.同时,本研究利用EC示踪OC/EC比值法对PM_(2.5)中的二次有机碳(SOC)进行了估算,通过估算得到的SOC结果表明,华北区域点冬季SOC是OC的重要组成部分,平均浓度为(4.0±2.9)μg·m~(-3),占OC的45.7%,SOC在白天占比较高(62.7%),早晚由于有局地生物质燃烧影响,SOC占比降低,约占OC的42.7%.本研究还分析了SOC生成的影响因素,分析了德州市冬季O_3、含水量、酸度与SOC的相关性.结果表明,SOC受臭氧浓度影响,但在白天和夜晚表现出不同的相关关系,可能存在不同的生成机制.最后,利用ISORROPIA模型估算了颗粒物的含水量和酸度,发现SOC在高含水量和低含水量下存在不同的关系,高含水量更能促进SOC生成;在高含水量下SOC与H~+具有显著相关性,但在低含水量下则不相关,表明颗粒物含水量较高、H~+浓度较高情况下液相酸催化反应可能对SOC具有重要贡献.     

烟花爆竹燃放对大气污染物及PM2.5组分影响

为了解烟花爆竹燃放对保定市大气污染物和PM_2.5中水溶性离子及有机碳（OC）、元素碳（EC）浓度的影响,对保定市春节期间大气污染物和颗粒物组分的浓度特征进行了分析,并评估了烟花爆竹的贡献.结果表明： 2019年春节期间烟花爆竹集中燃放期PM_2.5、PM₁₀、SO₂、NO₂、CO平均浓度比非集中燃放期分别增加了1.3、1.0、1.1、0.4、0.02倍;保定市春节期间禁燃措施施行后,除夕、初一2d污染物平均浓度、最高浓度和高浓度持续时间均明显下降,集中燃放期烟花爆竹燃放对PM_2.5、PM₁₀和SO₂浓度贡献量从50%左右（2018年、2017年）下降至30%左右（2019年）,其中SO₂贡献量下降幅度超过PM_2.5和PM₁₀;组分分析表明,接待中心站点（主城区）、涿州站点（区县建成区）烟花爆竹燃放期K⁺、Mg²⁺、Cl^-浓度在水溶性离子中的总占比分别为39.3%、51.1%,比非燃放期的占比显著上升;烟花爆竹燃放对PM_2.5中K⁺、Mg²⁺、Cl^-浓度贡献率在50%以上,其中对K⁺贡献占比高达89.0%,涿州站点SO₄^2-、K⁺、Mg²⁺、Cl^-的贡献量分别是接待中心站点的2.2、2.1、1.9、1.8倍,燃放期硫氧化率（SOR）、氮氧化率（NOR）相比于非燃放期均有一定程度的升高;集中燃放期OC、EC浓度较非集中燃放期分别升高了2.5、2.1倍,烟花爆竹燃放对OC影响大于EC.     

两种喹诺酮类抗生素对亚心形扁藻的毒性效应研究

研究了恩诺沙星和盐酸环丙沙星两种喹诺酮类抗生素对亚心形扁藻的毒理学效应。经多组不同浓度的两种抗生素处理后,分别对扁藻的96EC50、叶绿素和胞外聚合物（EPS）进行分析。结果表明,两种抗生素在低浓度时对扁藻生长具有促进作用,而在高浓度时体现抑制毒性作用。高浓度时,抗生素浓度越高对扁藻的生长、叶绿素和胞外聚合物抑制效果越明显,但当浓度达到一定高度后,抑制会达到其阈值。恩诺沙星和盐酸环丙沙星对扁藻的半生长抑制率分别为19.8 mg/L和28.7 mg/L。     

微生物燃料电池恒电流预培养阳极生物膜分析表征

阳极性能是影响微生物燃料电池(Microbial Fuel Cells,MFCs)性能的关键因素之一,同时阳极的接种挂膜过程是影响微生物燃料电池启动效率的关键因素.因此,本课题组提出了预培养阳极作为微生物燃料电池的一种新型阳极的概念,在三电极体系下,通过外加恒定电流预培养阳极,在不同条件下对阳极表面进行电化学选择和生物膜驯化以丰富生物膜结构和厚度.结果表明,阳极的性能与预培养电流大小密切相关,预培养阳极CF-4i(外加4 A·m-2电流密度)通过循环伏安法、塔菲尔曲线、电化学阻抗谱测试,性能好于其他测试组及对照组,装配阳极CF-4i的微生物燃料电池能实现最大功率密度968.20 m W·m-2,是对照组的2.53倍.同时,通过共聚焦显微镜观察发现,生物膜大体分两层,外层的活细胞及内层的死细胞,外层活细胞长在内层死细胞之上.这种结构分布表明,阳极生物膜中的活细胞部分绝大多数都分布于生物膜的外侧,而不是均布于整个阳极生物膜中;同时这也表明不是整个阳极生物膜都具有新陈代谢活性,但死亡的细胞可以继续积累在电极表面附近,活的外层膜负责电流的产生,而内层的死细胞作为一种导电基质.     

Characteristics of Carbonaceous Aerosol at Taichung Harbor, Taiwan during Summer and Autumn Period of 2005

In recent years, suspended particle pollution has become a serious problem in Taiwan. The carbonaceous materials EC and OC are play important roles in various atmospheric processes. The primary OC/EC ratio approach is applied to assess the contribution of secondary organic aerosol (SOA) to the PM_2.5 and PM₁₀ mass at the Taichung harbor sampling site. The results indicated that the average EC and OC concentration were 1.06 and 6.50 μg m⁻³, respectively, in fine particulate. And the average EC and OC concentration were 4.04 and 40.32 μg m⁻³, respectively, in coarse particulate at Taichung Harbor sampling site. In addition, and the average EC/OC rations was 8.72 in fine particle, respectively, at Taichung Harbor, Taiwan during summer and autumn period of 2005. The fine particle exhibited high particulate concentrations in October, and lower concentration particulate occurred in August. And in this study OC and EC concentrations in this study are compared with those in other cities. The results of EC and OC concentration in this study are also compare with those other cities.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

Regulation (EC) No. 1107/2009 and upcoming challenges for exposure assessment of plant protection products--Harmonisation or national modelling approaches?

In the new European Pesticide Regulation (EC) No. 1107/2009, the harmonisation of approaches for estimation of the environmental exposure of pesticides is considered a major goal. Several member states currently require their own models for the calculation of predicted environmental concentrations (PEC) in surface water. The variety of methods makes risk evaluations rather time-consuming for both notifiers and evaluating authorities. In the present study we compare surface water concentrations of 19 compounds using EU and country-specific models and risk assessment approaches to evaluate to which extent the resulting estimated exposure concentrations differ. Our results show that EU and country specific approaches and the resulting surface water concentrations differ considerably regarding basic model assumptions and assessment methods. The results indicate that the aimed harmonisation of risk assessment approaches within the EU will be difficult based on current models. New scenarios may help to achieve a harmonisation taking country-specific features into account.     

A new direct thermal desorption-GC/MS method: Organic speciation of ambient particulate matter collected in Golden, BC

Particulate matter having an aerodynamic diameter less than 2.5 μm (PM2.5) is thought to be implicated in a number of medical conditions, including cancer, rheumatoid arthritis, heart attack, and aging. However, very little chemical speciation data is available for the organic fraction of ambient aerosols. A new direct thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) method was developed for the analysis of the organic fraction of PM2.5. Samples were collected in Golden, British Columbia, over a 15-month period. n-Alkanes constituted 33–98% by mass of the organic compounds identified. PAHs accounted for 1–65% and biomarkers (hopanes and steranes) 1–8% of the organic mass. Annual mean concentrations were: n-alkanes (0.07–1.55 ng m⁻³), 16 PAHs (0.02–1.83 ng m⁻³), and biomarkers (0.02–0.18 ng m⁻³). Daily levels of these organics were 4.89–74.38 ng m⁻³, 0.27–100.24 ng m⁻³, 0.14–4.39 ng m⁻³, respectively. Ratios of organic carbon to elemental carbon (OC/EC) and trends over time were similar to those observed for PM2.5. There was no clear seasonal variation in the distribution of petroleum biomarkers, but elevated levels of other organic species were observed during the winter. Strong correlations between PAHs and EC, and between petroleum biomarkers and EC, suggest a common emission source – most likely motor vehicles and space heating.