标准加入法测定特质土壤中微量SO_4~(2-)

介绍了用电导滴定标准加入法测定特质土壤中微量 SO2 - 4的方法 ,本法克服了其他方法在测定特质土壤中微量 SO2 - 4时存在的不足 ,具有简便快速、精密度好、检出限低的优点。     

2015~2019年南京北郊碳质气溶胶组成变化

碳质气溶胶是大气细颗粒物的重要组成,对空气质量、人体健康和气候变化有着重要影响.为了探究碳质气溶胶在减排背景下的长期变化,本研究测定了南京北郊5 a（2014年12月17日至2020年1月5日） PM_2.5样品的有机碳（OC）和元素碳（EC）浓度.结果表明,ρ（OC）和ρ（EC）5a平均值分别为（10.2±5.3）μg·m^-3和（1.6±1.1）μg·m^-3,其中OC占PM_2.5的31.1%,EC占PM_2.5的5.2%.OC和EC均呈现出冬高夏低的季节特征.通过非参数的Mann-Kendall检验和Sen’s斜率发现,OC和PM_2.5的浓度整体呈显著下降趋势[OC:P<0.000 1,-0.79μg·（m³·a）^-1,-0.29%·a^-1; PM_2.5:P<0.000 1,-4.59μg·（m³·a）^-1,-1.5...     

Spatiotemporal dynamics of cell abundance, colony size and intracellular toxin concentrations of pelagic and benthic Microcystis in Lake Caohai, China

Lake Caohai has experienced extensive Microcystis blooms in recent years,and to improve its water quality,the local government carried out a series of water control measures.To better understand the dynamics of both pelagic and benthic Microcystis and their characteristics in Lake Caohai,we conducted a 1-year investigation from December 2015to December 2016 to gain a seasonal outlook on the distribution and dynamics of cell abundance,colony size and intracellular microcystins(MCs)of Microcystis.The results indicated that the Microcystis bloom occupied primarily the northeastern region and then moved gradually from lakeshore to lake center.The perennial southwesterly winds and the water inflow from northeast to southwest in Lake Caohai determined the spatiotemporal distribution of pelagic Microcystis.Benthic Microcystis was mainly distributed in the northeastern region in summer,occupied the lake center in autumn and then occupied the southeastern region in winter,determined by the sedimentation of pelagic Microcystis and the death of benthic Microcystis.Small colonies(20-60μm)overwintered more easily in both water column and sediment.The concentrations of intracellular toxin of benthic Microcystis were observed to be significantly higher than those of pelagic Microcystis.This might be because Microcystis synthesized large amount of MCs to acclimate to an unfavorable benthic environment.This knowledge on the dynamics of Microcystis expands our understanding of mechanisms underpinning the formation of Microcystis blooms.     

Enhanced adsorption of arsenate by spinel zinc ferrite nano particles: Effect of zinc content and site occupation

In this work, zinc ferrite spinel with different zinc contents (Zn_xFe_3-xO₄) was synthesized by a hydrothermal method and used for removing As(V) in aqueous solution. X-ray diffraction (XRD) results indicated that in the crystal structure of Zn_xFe_3-xO₄, the zinc atoms tended to occupy the octahedral sites for x?<?0.6 and diffused into the tetrahedral sites gradually with x?>?0.6. The size of Zn_xFe_3-xO₄ crystallites increased with the increasing zinc content. Batch adsorption experiments showed that the adsorption isotherms could be well described by the Langmuir model, while the adsorption kinetics followed the pseudo-second-order kinetic model. Zinc ferrite exhibited the highest adsorption capacity towards As(V) when x?=?0.6. Study of the mechanism indicated that doping with zinc increased the number of surface hydroxyl groups on ferrite spinel, and thus enhanced the adsorption capacity when x?=?0.6. This work revealed the effects of doping site and content of metal atoms on the adsorption ability of ferrite spinel towards As(V).     

Potential factors and mechanism of particulate matters explosive increase induced by free radicals oxidation

Atmospheric particulate pollution in China has attracted much public attention. Occasionally, the particle number concentration increases sharply in a short time period, which is defined as a “particulate matter explosive increase”. Heavy particulate matter pollution not only reduces visibility but also has an adverse effect on human health. Hence, there is an urgent need to discover the causes of particulate matter explosive increase. During this campaign, the particle number concentration and free radicals were measured at a tall building on the campus of Lanzhou University of Technology. Additionally, we examined a series of chemicals to reproduce the observed particulate matter explosive increase in a smog chamber to determine its potential factors. Then, we analyzed the mechanism of particulate matter explosive increase in the presence of free radicals. We found that, among the potential inorganic and organic sources analyzed, a mixture of organic and SO₂ in the research region had a major effect on particulate matter explosive increase. Moreover, free radical oxidation has a large effect, especially in the formation of organic particulates.     

山东省自然保护区管理状况调查与分析

基于自然保护区管理机构、人员配置、固定资产、事业经费、基建与生态工程投入、旅游收入等17项调查指标,系统调查了山东省自然保护区管理机构、人员配置和资金投入状况,定量分析了山东省自然保护区管理状况,论述了自然保护区管理存在的主要问题与对策。结果表明:山东省56%的自然保护区建立了专门的管理机构,63%的自然保护区现有人员数量低于25人,33%的自然保护区事业经费低于45万元。自然保护区管理存在的主要问题是管理机构不健全、人员配置不合理和资金投入不足。因此,山东省自然保护区管理应进一步完善管理机构,合理配置人员,增加资金投入。     

长三角背景大气PM2.5中非极性有机化合物组成特征及来源

为了探究长三角区域大气细颗粒物中非极性有机化合物的组成及来源特征,于2019年12月至2020年11月在临安区域大气本底站采集了129个PM_2.5样品,对其有机碳(OC)、元素碳(EC)和非极性有机化合物(NPOCs,包括多环芳烃、正构烷烃和藿烷类)进行了分析,并用分子示踪物、特征比值和正定矩阵因子分析模型等方法探究了有机气溶胶的主要来源.结果表明,临安ρ(PM_2.5)的年平均值约为(32.36±20.44)μg·m^-3,ρ(NPOCs)年平均值约为(59.05±40.39)ng·m^-3,呈现出冬高夏低的季节变化特征.正构烷烃主要源于化石燃料和生物质(草和木材等)燃烧等人为源,其次为高等植物角质层蜡排放;多环芳烃主要源于燃煤燃烧、机动车排放和生物质燃烧等非化石源的混合贡献;藿烷类物质主要源于机动车排放,其中冬季还受到燃煤源的影响.后向轨迹聚类分析和潜在源区分析表明临安主要受到外来气团输送的影响.结合正定矩阵因子分析模型对采样期间观测到的NPOCs进行源解析,得到了燃煤燃烧源、交通排放源和生物质燃烧等...     

中国主要背景区域冬季大气PM2.5中非极性有机化合物组成及来源解析

本研究于2019年12月至2020年1月在5个区域大气本底站：临安、金沙、龙凤山、上甸子和瓦里关,同步采集了PM_2.5样品,分析了其中的非极性有机物：多环芳烃、正构烷烃和藿烷类化合物。结果表明,上甸子和龙凤山的多环芳烃平均浓度显著高于其他站点,分别为35.2±25.6 ng/m³和27.5±16.8 ng/m³;藿烷类物质的浓度在上甸子和临安出现高值,分别为2.72±1.78 ng/m³和2.47±0.990 ng/m³;正构烷烃浓度以临安最高,为86.7±40.6 ng/m³。对各站点多环芳烃和藿烷类化合物采用比值法,正构烷烃采用主峰碳数（C_max）、碳优势指数（carbon preference index,CPI）和植物蜡贡献率（% Wax C_n）,结合主成分分析-多元线性回归模型（PCA/MLR）综合进行源解析。结果显示采样期间除瓦里关外,其余站点燃烧源均以化石燃料源为主,贡献率分别为临安（94.9%） > 金沙（75.3%） > 龙凤山（74.7%） > 上甸子（62.5%） > 瓦里关（35.6%）。后向轨迹聚类分析（HYSPLIT）和潜在源贡献因子分析法（PSCF）表明各站点主要受到外来传输气团的影响,并查明了各站点的潜在污染源区。对背景站点的研究表明,东北地区和京津冀地区PM_2.5中非极性有机物来源相似,京津冀地区的生物质燃烧源贡献率高于东北地区;长江中下游地区化石燃料贡献率显著高于生物质燃烧;华中地区燃煤和交通排放源排放贡献率均低于长江三角洲地区;青藏高原地区生物质燃烧贡献率远高于其他地区。     

Cross-boundary transport and source apportionment for PM2.5 in a typical industrial city in the Hebei Province, China: A modeling study

Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain. In this study, an industrial district (Shahe City) with a large glass manufacturing sector was investigated to clarify the relative contribution of fine particulate matter (PM_2.5) to the city's high levels of pollution. The Nest Air Quality Prediction Model System (NAQPMS), paired with Weather Research and Forecasting (WRF), was adopted and applied with a spatial resolution of 5 km. During the study period, the mean mass concentrations of PM_2.5, SO₂, and NO₂ were observed to be 132.0, 76.1, and 55.5 μg/m³, respectively. The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level. The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4% of the city's total PM_2.5 concentration. This contribution increased to 73.9±21.2% when unfavorable meteorological conditions (high relative humidity, weak wind, and low planetary boundary layer height) were present; such conditions are more frequently associated with severe pollution (PM_2.5 ≥ 250 μg/m³). The contribution from Shahe was 52.3±21.6%. The source apportionment results showed that industry (47%), transportation (10%), power (17%), and residential (26%) sectors were the most important sources of PM_2.5 in Shahe. The glass factories (where chimney stack heights were normally < 70 m) in Shahe contributed 32.1% of the total PM_2.5 concentration in Shahe. With an increase in PM_2.5 concentration, the emissions from glass factories accumulated vertically and narrowed horizontally. At times when pollution levels were severe, the horizontally influenced area mainly covered Shahe. Furthermore, sensitivity tests indicated that reducing emissions by 20%, 40%, and 60% could lead to a decrease in the mass concentration of PM_2.5 of of 12.0%, 23.8%, and 35.5%, respectively.