北京市典型重污染过程中PM2.5载带水溶性无机离子污染特征分析

为研究北京地区冬季PM_(2.5)载带的水溶性无机离子组分污染特征,2013年1月在中国环境科学研究院内采用在线离子色谱(URG-9000B,AIM-IC)对PM_(2.5)中水溶性无机离子(SO_4~(2-)、NO_3~-、Cl~-、NH_4~+、Na~+、K~+、Mg~(2+)、Ca~(2+))进行监测与分析。结果表明,采样期间总水溶性无机离子(TWSI)浓度为61.0μg/m~3,其中二次无机离子SO_4~(2-)、NO_3~-、NH_4~+(SNA)占比达72.3%,在PM_(2.5)中占比为40.29%,表明北京市PM_(2.5)二次污染严重。重污染天[NO_3~-]/[SO_4~(2-)]表明,固定源污染较移动源更为显著。三元相图表明,在空气质量为优的情况下,NH_4~+(在SNA中占比为30.3%~65.5%,下同)主要以NH_4NO_3的形式存在,较少比例以(NH_4)_2SO_4存在;严重污染时,NH_4~+(47.3%~77.9%)主要以(NH_4)_2SO_4形式存在,其次以NH_4NO_3的形式存在,其余的NH_4~+以NH_4Cl的形式存在。[NO_3~-]/[SO_4~(2-)]日变化表明,早、晚机动车高峰影响北京重污染发生。     

蚌埠市夏季大气细颗粒物在线源解析

为了解蚌埠市环境空气中PM_(2.5)的来源,于2017年8月18日—9月18日,在百货大楼和高新区站点,利用单颗粒物气溶胶飞行时间质谱仪开展PM_(2.5)在线源解析。结果表明,百货大楼点位ρ(PM_(2.5))高于高新区点位,轻度污染比例(4.2%)明显高于高新区点位(0.8%),出现了中度污染(0.3%);SPAMS的PM_(2.5)质谱图显示百货大楼点位PM_(2.5)中K~+、Na~+特征明显,高新区点位HSO_4~-、NO_3~-、NO_2~-等无机信号较为明显;2个点位NO_3~-、NO_2~-、NH_4~+离子颗粒数占总颗粒数的百分比明显较高,且高新区点位NO_3~-、HSO_4~-离子数占比要明显高于百货大楼点位,燃料燃烧、工业工艺源、农田氮肥施用是其主要的人为污染源;2个点位PM_(2.5)成分主要为元素碳,分别占比42.4%,40.6%;污染时段,ρ(PM_(2.5))快速上升,除受本地机动车尾气源和燃煤源累积影响外,百货大楼点位扬尘源排放增加,高新区点位扬尘源和工业工艺排放源增加;2个点位机动车尾气源均为首要污染源,分别占比29.5%和30.9%,其次为燃煤源(24.3%和24.7%),扬尘源占比分别为22.9%和20.8%。     

大同市大气颗粒物浓度与水溶性离子季度分布特征

为研究大同市大气颗粒物质量浓度与水溶性离子组成特征,于2013年2、7、9、12月,分别对大同市及其对照点庞泉沟国家大气背景点进行了PM2.5及PM10的采样,通过超声萃取-IC法测定了样品中的9种水溶性离子,结果表明,大同市大气颗粒物污染1、4季度重于2、3季度,PM2.5季度均值全年均未超标,PM10仅第1季度超标1.4倍,污染状况总体良好,PM2.5与PM10相关系数R为0.75,说明大同市颗粒物污染有较为相近的来源,且不同季节均以粗颗粒物为主;大同市PM2.5中水溶性离子浓度分布为SO2-4、NO-3、NH+4Cl-、Ca2+K+、Na+F-、Mg2+,PM10中Ca2+浓度仅次于SO2-4、NO-3,控制扬尘将有效降低PM10的浓度;PM2.5及PM10中的9种水溶性离子在不同季度的浓度与颗粒物浓度分布规律类似,1、4季度较高,2、3季度较低;由阴阳离子平衡计算结果可知,相关性方程的斜率K为1.045,表明大同市大气颗粒物中阳离子相对亏损,大气细粒子组分偏酸性。NO-3与SO2-4浓度比值均小于1,大同市以硫酸型污染为主,大气中的SO2-4主要来源于人类活动排放。     

重庆市主城区大气水溶性离子在线观测分析

2015年12月—2016年3月期间,利用在线气体与气溶胶成分监测仪(IGAC)在重庆市大气超级站开展连续观测分析,并捕捉到2次持续时间较长的空气重污染过程。对PM_(2.5)中9种水溶性离子及5种气态前体物的观测结果分析表明:NO_3~-、NH_4~+和SO_4~(2-)是重庆市主城区PM_(2.5)中主要的水溶性离子成分,其浓度均表现出明显的日变化特征,主要以(NH4)_2SO_4和NH_4NO_3的形式存在。NH_3和SO_2是最主要的气态污染物。2次重污染过程的水溶性离子组分有明显差异,细颗粒物累积型污染的NH_4~+、SO_4~(2-)、NO_3~-浓度高,二次转化十分明显;春节期间烟花爆竹集中燃放,Cl~-、K~+浓度高,主要属于一次排放;污染期间主要离子组分的同源性特征显著。     

徐州市不同类型颗粒物重污染过程特征及组分差异性分析

经过多年的大气污染防治,我国空气质量有了大幅改善,但重污染过程仍有发生。对2018—2021年徐州市3种不同类型颗粒物重污染过程的污染特征、演变趋势、PM_2.5组分特征和相关性及污染成因分析结果表明:在不同类型的重污染过程中,二次无机离子NO₃^-、SO₄^2-、NH₄⁺在PM_2.5中的占比均是最高。在累积型重污染期间,NO₃^-、SO₄^2-、NH₄⁺分别增长144%、142%、183%,二次无机离子对PM_2.5的增长贡献较大。结合相关性分析及SOR、NOR值发现,硝酸盐和硫酸盐的二次生成作用显著。在沙尘型重污染期间,结合雷达监测结果及后向轨迹图可以看出,沙尘沉降至高空与近地面污染物叠加造成颗粒物高值。化学组分中Ca²⁺、Mg²⁺浓度对PM_2.5浓度的影响最大,二次生成和转化对其影响较小。在烟花燃放型重污染期间,和烟花爆竹有关的K⁺、Mg²⁺、Cl^-离子较污染前分别上升1 112%、2 058%、和239%,对污染过程影响显著。     

上海青浦地区大气降水的化学特征

利用上海青浦地区2003—2014年观测的大气降水监测资料,分析该区域12 a以来大气降水的酸化程度、化学组成特征,探讨降水中化学成分的不同来源及相对贡献。结果表明:降水pH年均值为4.43~6.33,酸雨频率为2.6%~86.8%,降水酸化程度大致经历了明显恶化和波动变化2个阶段。降水电导率年均值为1.77~4.01 m S/m,呈下降趋势。降水中各离子雨量加权平均当量浓度顺序为SO_4~(2-)NH_4~+Ca~(2+)NO_3~-Cl~-Na~+Mg~(2+)F-K~+,SO_4~(2-)、NH+4、Ca~(2+)和NO_3~-是降水中的主要离子,占离子总量的83.0%;降水类型由硫酸型向硫酸和硝酸混合型转变。降水离子中的二次组分SO_4~(2-)、NO_3~-和NH_4~+绝大部分来源于人为源,Ca~(2+)、Mg~(2+)和K+主要来自于土壤源和人为源的贡献,Cl~-主要来自海洋源,同时人为源的影响也不可忽视。     

重庆市黔江区降水地球化学特征

为了解生态旅游城市重庆市黔江区大气污染状况,2015年采集了91个降水样品,分析了降水中离子组分分布特征,运用富集因子法、海盐示踪法、相关性分析、主成分分析、聚类分析和HYSPLIT模型分析了降水化学组分来源。研究结果表明:黔江区域降水p H为5.66~6.96,加权平均值为6.34,降水离子组分浓度大小次序为SO_4~(2-)Ca~(2+)NH_4~+Mg~(2+)NO_3~-Cl~-Na~+K~+F~-,SO_4~(2-)、Ca~(2+)之和占总离子的63.95%;除Mg~(2+)和K+外,其余组分离子浓度与总离子浓度随季节变化(冬季春季秋季夏季)呈同样的变化特征。Ca~(2+)、Mg~(2+)和K+大部分均来源于陆源贡献,Na~+可能受到了海洋源的影响,SO_4~(2-)和NO_3~-主要来源于人为输入源的贡献,Cl~-是受土壤物质和海洋的双重影响。轨迹水汽运输结果表明:黔江区域的降水主要受到西北气团、西南季风、西风环流和极地气候共同作用输入。降水中各个离子组分均表现出显著性或极显著性关系,主成分分析结果表明,第一主成分上研究的降水离子组分中都具有相对较大正载荷,第二组分pH、降水量和气温为一类。     

Factor analysis and linear regression model (LRM) of metal speciation and physico-chemical characters of groundwater samples

An approach is described for viewing the interrelationship between different variables and also tracing the sources of pollution of groundwater of north Chennai (India). The data set of 43 variables which include major ions, minor ions and trace metal speciation (Cu, Pb, Cd and Zn) collected during the pre-monsoon and post-monsoon seasons of the year 2000–2001, was subjected to R-mode factor analysis to comprehend the distribution pattern of the said variables. It was found that first factor measures salinity and hardness which explained 19.12% of the total variance (comprised of variables EC, TDS, Na⁺, K⁺, Ca²⁺, Mg²⁺, total hardness, Cl⁻ and SO₄ ²⁻) during pre-monsoon, while it was 25.08% during post-monsoon. The second and third factors were attributed to speciation of zinc and copper ions during both pre-monsoon and post-monsoon. Although there were two more factors, loaded with speciation parameters of lead and cadmium, the variance of them were less than 10%. From this study it is seen that sea water intrusion, municipal solid waste disposal are the identified sources of component of pollution. The importance of metal ions is taking a secondary role and the anthropogenic origin-industrial activity, is the reason in the evaluation of pollution status as they come in the second, third, fourth and fifth factors. As the trace metal speciation was grouped in separate factors, linear regression model (LRM) with correlation analysis was applied to check its validity for prediction of speciation and to apply LRM for rapid monitoring of water pollution.     

Assessment of the sources of suspended particulate matter aerosol using US EPA PMF 3.0

The main purpose of this paper was to carry out a source apportionment of suspended particulate matter (SPM) samples using positive matrix factorization procedure. The central and local Government of Japan introduced strict emission regulations in 2002/10 and 2003/10, respectively, in curbing SPM pollution from major metropolitans. This paper also highlighted the impact of the measures taken by the central and local Government of Japan on the reduction of SPM and the contributions of sources. SPM samples were collected for 6 years starting from 1999 to 2005 at two sites, i.e., site A (urban) and site B (suburban) of Yokohama, Japan. Microwave digestion and inductively coupled plasma-mass spectroscopy (ICP-MS) were employed to measure Mg, Al, Ca, V, Cr, Mn, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ag, Cd, Cs, Ba, Pb and Bi, while water soluble ions (Na⁺, NH₄  ⁺_{4}^{\ \,+}, K⁺, Ca^2 +, Mg^2 +, Cl⁻, NO₃  ^-_{3}^{\ \,-} and SO₄  ^2-)_{4}^{\ \,2-}) as well as carbonaceous mass (EC and OC) were analyzed using ion chromatograph and CHN analyzer, respectively. The sources identified at two sites were automobile, soil dust, marine aerosol, mixed sources, and secondarily formed aerosol. Also, source quantification was performed. Automobile and soil dust were striking contributors at site A. Automobile and soil dust of SPM aerosol might be produced from local origin at current study areas. Besides, Asian dust had an impact on high concentrations of SPM aerosol in some certain period of the year due to the outflows of East Asian emission. In contrast, secondary aerosol in the form of sulfate and ammonium as well as mixed sources (coal, long-transported Cs, and other unknown sources) were remarkable at site B. Stationary/industrial combustion has apparently more impact on the release of SPM components at site B than A. Automobile regulations in 2002 and 2003, respectively, resulted in reduction of SPM by 28% for site A and 16% for site B. There was also net reduction of automobile contribution at both sites due to the above measures being implemented.     

1997—2010年北京市大气降水离子特征变化趋势研究

依据北京市环境保护监测中心1997—2010年降水监测资料,分析北京地区降水中离子特征及变化趋势,阐明北京市降水污染现状及变化特征。结合北京市特有的气象条件、地形地貌和工业分布情况,分析污染物来源及污染变化趋势。研究表明:年度降水电导率呈现波动变化,降水污染严重程度依次为南部郊区>市区>北部背景点。北京地区大气降水中的主要阳离子成分是Ca²⁺和NH₄⁺,主要阴离子成分是SO₄^2-和NO₃^-。近年来[SO₄^2-]/[NO₃^-]比值逐步下降,污染类型由典型硫酸型发展为硫酸+硝酸混合型。阳离子[Ca²⁺]/[NH₄⁺]比值下降,碱性离子缓冲能力降低。9种离子各季节浓度变化趋势基本一致,由高到低依次是春季>秋季>冬季>夏季,这种季节变化特征与气象因素密切相关。相关性及聚类分析表明:NO₃^-与SO₄^2-存在很强相关性,说明其前体物SO₂和NO_X在大气中经常一同排放且进入降水途径相同;H⁺浓度不是由某个离子决定,是所有致酸离子和中和离子相互作用的结果,而NH₄⁺来源不同于其它离子,北京地区的氨存在其单独排放源。     

黄河流域甘肃段面源污染估算与空间分析

采用遥感分布式面源污染评估模型（DPeRS）,对2018年黄河流域(甘肃段)面源污染空间分布特征进行分析,具体包括多类型污染量产排特征解析和流域优先管控单元识别。结果表明,污染量上,2018年黄河流域（甘肃段）总氮(TN)、总磷(TP)、氨氮(NH₃^-N)、化学需氧量(COD_Cr)的面源污染排放负荷分别为65.6,11.8,19.1和77.2 kg/km²,入河量分别为836.7,33.3,220.2和1 353.3 t;空间分布上,氮型(TN和NH₃^-N)排放负荷高值区主要分布在流域中部和东部局部地区,流域大部分地区TP排放负荷均较高,COD_Cr面源污染排放负荷高值区分布较为零散。与排放负荷相比,黄河流域（甘肃段）面源污染入河负荷并不突出,这与该地区水资源量少有密切关系。筛选出黄河流域（甘肃段）面源污染优先控制单元15个,面积占比为85.2%,I类优控单元主要分布在庆阳市、天水市、兰州市和白银市等地区,II类优控单元主要分布在甘南藏族自治州,且TN、TP、NH₃^-N和COD_Cr面源污染优控单元识别结果的平均精度达到80%。     

Evaluation of groundwater suitability for domestic,irrigational, and industrial purposes: a case study from Thirumanimuttar river basin,Tamilnadu, India

The Thirumanimuttar sub-basin forms an important groundwater province in south India, facing serious deficiency in both quality and quantity of groundwater due to increased demand associated with rapid population explosion, agricultural growth and industrial activities. A total of 194 groundwater samples were collected and 15 water quality parameters were analyzed using standard procedures. Na⁺, Cl⁻, Ca^2 +, HCO₃^-_{3}^{-}, Mg^2 + and SO₄^2-_{4}^{2-} concentration ions are more dominant in both seasons. The total dissolved solids and electrical conductivity was observed good correlation with Na⁺, Cl⁻, HCO₃^-_{3}^{-}, Ca^2 +, Mg^2 +, Cl⁻, PO₄^3-_{4}^{3-} and NO₃^- _{3}^{- } ions indicating dominance of plagioclase feldspar weathering, anthropogenic input and over drafting of groundwater irrespective of seasons. The Hill–Piper diagram indicates alkaline earths exceed the alkalis, an increase of weak acids was noted during both the seasons. For assessing the groundwater for irrigation suitability parameters like total hardness, sodium adsorption ratio, residual sodium carbonate (RSC), permeability index, and sodium percentage are also calculated. Permanent hardness was noted in higher during both the seasons due to discharge of untreated effluents and ion exchange process. The RSC indicates 56% of the samples are not suitable for irrigation purposes in both seasons, if continuously used will affect the crop yield. From the results, nearly 72% of the samples are not suitable for irrigation.     

Five-year monitoring study of chemical characteristics of Wet atmospheric precipitation in the southern region of Jordan

Wet atmospheric samples were collected from different locations in the southern region of Jordan during a 5-year period (October 2006 to May 2011). All samples were analyzed for pH, EC, major ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃ ^?, Cl^?, NO₃ ^?, and SO₄ ^2?), and trace metals (Fe²⁺, Al³⁺,Cu²⁺, Pb²⁺, and Zn²⁺). The highest ion concentrations were observed during the beginning of the rainfall events because large amounts of dust accumulated in the atmosphere during dry periods and were scavenged by rain. The rainwater in the study area is characterized by low salinity and neutral pH. The major ions found in rainwater followed the order of HCO₃?>?Cl^??>?SO₄ ^2? and Ca²⁺?>?Na⁺ > Mg²⁺ > NH₄ ⁺ > K⁺. Trace metals were identified to be of anthropogenic origin resulting from cement and phosphate mining activities located within the investigated area and from heating activities during the cold period of the year (January to April). The wet precipitation chemistry was analyzed using factor component analysis for possible sources of the measured species. Factor analysis (principal component analysis) was used to assess the relationships between the concentrations of the studied ions and their sources. Factor 1 represents the contribution of ions from local anthropogenic activities, factor 2 represents the contribution of ions from natural sources, and factor 3 suggests biomass burning and anthropogenic source. Overall, the results revealed that rainwater chemistry is strongly influenced by local anthropogenic sources rather than natural and marine sources, which is in a good agreement with the results obtained by other studies conducted in similar sites around the world.     

Major ion chemistry of shallow groundwater of a fast growing city of Central India

Nagpur City located in semiarid area of central India is a fast-growing industrial centre. In recent years, rapid development has created an increased demand for drinking water, which is increasingly being fulfilled by groundwater abstraction. The present study was undertaken to assess major ion chemistry of shallow groundwater to understand geochemical evolution of groundwater and water quality for promoting sustainable development and effective management of groundwater resources. A total of 47 water samples were collected from shallow aquifer of selected parts of the city and the water chemistry of various ions viz. Ca^2 +, Mg^2 +, Na⁺, K⁺, CO₃  ^2-_{3}^{\ \, 2-}, HCO₃  ^-_{3}^{\ \, -}, Cl⁻, SO₄  ^2-_{4}^{\ \,2-} and NO₃  ^-_{3}^{\ \,-} are carried out. The chemical relationships in Piper diagram identify Ca–HCO₃–Cl and mixed Ca–Na–HCO₃–Cl as most prevalent water types. Alkaline earth exceeds alkalis and weak acids exceed strong acids. Ionic ratios and Gibb’s diagram suggest that silicate rock weathering and anthropogenic activities are the main processes that determine the ionic composition in the study area. The nitrate appeared as a major problem of safe drinking water in this region. We recorded highest nitrate concentration, i.e., 411 mg/l in one of the dug well. A comparison of groundwater quality in relation to drinking water quality standards revealed that about half of the shallow aquifer samples are not suitable for drinking.     

Impact of water quality on bacterioplankton assemblage along Cértima River Basin (central western Portugal) assessed by PCR–DGGE and multivariate analysis

The information on bacterial community composition (BCC) in Portuguese water bodies is very scarce. Cértima River (central western Portugal) is known to have high levels of pollution, namely organic. In the present work, the BCC from a set of 16 water samples collected from Cértima River Basin and its main tributaries was characterized using 16S rDNA–denaturing gradient gel electrophoresis, a culture-independent molecular approach. Molecular data were related to environmental parameters through multivariate analysis to investigate potential impact of water pollution along the river. Principal component analysis using environmental data showed a water quality gradient from more pristine waters (at the mountain tributaries) to waters with increasingly eutrophic potential (such as Fermentelos Lake). This gradient was mainly defined by factors such as organic and inorganic nutrient sources, electrical conductivity, hydrogen carbonate concentration, and pH. Molecular results showed variations in BCC along Cértima River Basin but in the main river section, a Bacteroidetes phylotype (Flavobacterium sp.) proved to be dominant throughout the river course. Multivariate analysis suggests that spatial variation of BCC along the Cértima River Basin depended mainly on parameters such as Chl a, total suspended solid (TSS), total organic carbon, electrical conductivity, and HCO _boxclose^-_{3}^{-} levels. Bacteroidetes phylotypes were all related to higher electrical conductivity and HCO₃^-_{3}^{-} levels although some of these were also correlated with high SO₄^2-_{4}^{2-} and others with high soluble reactive phosphorus, nitrate, TN, and Kjeld-N levels. The Gammaproteobacteria occurrence was correlated with high SO₄^2-_{4}^{2-} levels. One of the Betaproteobacteria phylotypes showed to correlate with low redox potential (E_h) and high temperature, pH, TSS, and Chl a levels while another one showed a negative correlation with Chl a values.     

2021年青岛市一次PM_(2.5)和沙尘混合空气污染过程分析

以2021年3月青岛市空气自动站监测数据为依据,借助环境气象激光雷达、气溶胶激光雷达、在线离子色谱仪等技术手段,并利用后向轨迹模式(HYSPLIT)对青岛市一次PM_(2.5)和沙尘混合空气污染过程、气象条件、颗粒物组成以及传输路径等进行了综合分析。结果表明:静小风、湿度大、垂直方向逆温以及高空多次向近地面的污染物输送是第1阶段PM_(2.5)污染的主要原因,NO^(-)_(3)、SO^(2-)_(4)、NH^(+)_(4)浓度分别占水溶性离子浓度总和的51.7%,24.8%,22.4%,三者之和占ρ(PM_(2.5))的52.3%,机动车源、工业源和燃烧源贡献较大,其中尤以机动车源影响最显著;第2阶段各子站颗粒物浓度变化呈现明显的传输特征,PM_(2.5)中Ca^(2+)浓度升至第1阶段的6倍,沙尘源影响显著,污染气团主要来自蒙古国和我国内蒙古,前期由西北地区直接到达青岛,后期是经渤海湾、烟台到达青岛东南海域,最后回流至青岛;冷高压强度较弱导致近地面水平扩散条件不利,ρ(PM_(10))长时间维持在较高水平。     

杭州秋冬季PM2.5污染特征分析

为研究杭州PM_2.5污染来源特征,利用2013—2019年杭州市PM_2.5监测数据和气象观测数据,分析了杭州市2013—2019年PM_2.5浓度变化,选取本地积累型和输入型2种PM_2.5污染过程,结合单颗粒气溶胶飞行时间质谱仪（SPAMS）和在线离子色谱数据,探讨杭州市PM_2.5化学组分和污染来源。结果表明：每年秋冬季（11月至次年3月）杭州以东北风、西北风及偏南风为主,风速低于4 m/s时,大气扩散条件差,受本地污染物积累影响,PM_2.5浓度容易出现超标;风速较大且为东北风和西北风时,受上游污染输入影响,易出现PM_2.5重度污染。本地积累型和输入型案例中,PM_2.5化学组分中占比最大的为NO₃^-、SO₄^2-和NH₄⁺;PM_2.5浓度上升过程中,二次NO₃^-和SO₄^2-转换率明显上升,其中NO₃^-上升更为显著,二次气溶胶污染严重。2次案例中,PM_2.5来源贡献占比前3位均为机动车尾气源、燃煤源和工业工艺源,其中本地积累型PM_2.5浓度上升阶段,机动车尾气源占比会明显上升;输入型案例中,输入阶段机动车尾气源占比显著上升,燃煤源贡献也小幅上升。     

基于DPeRS模型的渭河典型断面汇水区面源污染评估及污染成因分析

近年来甘肃渭河桦林断面月度水质不稳定达标的问题引起了管理部门的广泛关注,掌握桦林断面汇水范围面源污染现状,对控制流域面源污染和促进水质稳定达标具有重要意义。采用遥感分布式污染估算（DPeRS）面源污染评估模型,对2018年黄河流域甘肃桦林断面汇水区面源污染空间分布特征进行分析,开展多类型污染量产排特征解析。结果表明：农业面源污染量方面,2018年甘肃桦林断面汇水区总氮（TN）、总磷（TP）、氨氮（NH⁺₄-N）、重铬酸盐指数（COD_Cr）面源污染排放量分别为11 591,2 697,7 141和1 458 t,入河量分别为2 184,512,1347,263 t;空间分布上,氮型（TN和NH⁺₄-N）排放负荷高值区主要分布在陇西县、武山县县段和岷县县段;武山县县段TP排放负荷较为突出;COD_Cr型面源污染高负荷区主要分布在陇西县、渭源县县段和武山县县段。农业面源污染物入河排放负荷空间分布差异明显,氮磷型（TN、NH⁺₄-N和TP）入河高负荷区主要分布在武山县县段、陇西县、临洮县县段;COD_Cr型面源污染入河高负荷区呈分散分布。漳县西部地区水土流失量较高,漳县西部、陇西县和渭源县县段北部局部地区泥沙负荷量较高。枯水期污染治理仍是保障水质稳定达标的关键期,农田径流是渭河桦林断面所在汇水区氮磷型面源污染的首要污染类型,畜禽养殖是COD_Cr型面源污染的首要污染类型。     

2020年泰州市细颗粒物质量浓度高值区污染来源解析

2020年在位于泰州市主城区大气细颗粒物(PM_(2.5))质量浓度高值区的莲花国控空气站点进行手工采样,分析了大气PM_(2.5)的质量浓度和元素组成,以及离子、有机碳和元素碳的质量浓度。根据监测结果,采用正定矩阵因子分解(PMF)受体模型对其来源进行解析。结果显示,莲花站点大气PM_(2.5)中主要组分包括有机物、硝酸盐、硫酸盐、铵盐、地壳物质、氯盐、钾盐、黑炭、微量元素和钠盐,占比分别为35.7%,25.6%,13.9%,11.9%,6.1%,2.3%,1.5%,1.5%,0.8%和0.7%,有机物、硝酸盐、硫酸盐、铵盐为首要污染组分,这4类物质对PM_(2.5)的累计贡献为87.1%。根据解析结果与实际污染特征,提出应优化城市路网结构,强化工地扬尘管控,全面取缔燃煤炉和严抓秸秆禁烧工作等控制对策。     

Assessment of geospatial and hydrochemical interactions of groundwater quality,southwestern Nigeria

Groundwater pollution resulting from anthropogenic activities and poor effluent management is on the rise in Nigeria. Hence, groundwater used for domestic purposes is questionable and therefore calls for scientific scrutiny. Investigation of hydrochemical interactions and quality of groundwater resource is essential in order to monitor and identify sources of water pollutants. As a result, groundwater samples were collected from 21 locations in Abeokuta South, Nigeria and analyzed for physicochemical parameters using standard methods. Results obtained were subjected to hydrochemical and geospatial analyses. Water quality parameters investigated exhibited wide variations from location to location. Fe²⁺, Mg²⁺, SO₄^2?, Cl^?, total hardness (TH), Mn, Na⁺, NO₃^?, SiO₂, and alkalinity exhibited the highest levels of variation with coefficients of variation of 131.3, 92.8, 83.9, 76.7, 65.9, 64.3, 57.6, 57.2, 57.0, and 52.5, respectively. The average pH value was 6.76 with 71% of the water samples being slightly acidic. Na²⁺, Mg²⁺, Fe²⁺, and EC contents exhibited the most violation of drinking water standards with percent violations of 100, 52.4, 47.6, and 47.6%, respectively. Parameters, such as Mn, Ca²⁺, NO₃^?, and CO₃^2?, were within the WHO guideline values for drinking water in all the samples. The highest level of significant correlation was found to exist between Na⁺ and Cl^? (r?=?0.84, α?=?0.01). Six principal components, which explained 83.5% of the variation in water quality, were extracted with the first (34.1%) and second components (15.7%) representing the influence of mineral dissolution and anthropogenic practices, respectively, on the hydrochemistry of the area. Four hydrochemical clusters were identified with distinctly partitioned water quality. Further analysis revealed that 38, 29, 24, and 9% of the samples were the Na-K-HCO₃, Na-K-Cl-SO₄, Ca-Mg-HCO₃, and Ca-Mg-Cl-SO₄ types, respectively. Anthropogenic activities are increasing threat to groundwater quality in the study location and therefore call for urgent attention. There is also a need for routine monitoring of groundwater in Abeokuta.