北京蔬菜地土壤中抗生素抗性基因与可移动元件的分布特征

为揭示北京地区蔬菜土壤中抗生素抗性基因与可移动元件的分布特征应用高通量荧光定量PCR方法(HT-qPCR),选取北京3个区5个蔬菜基地进行调查研究.在蔬菜基地土壤中共检测到92～121种抗生素抗性基因,4～6种可移动元件,抗生素抗性基因及可移动元件按区分开.各蔬菜基地中共有且丰度较高的抗生素抗性基因型为:多重耐药类oprD、acrA-04和acrA-05,大环内酯类-林肯酰胺类-链阳性菌素B类抗生素抗性基因(MLSB)酰胺酶类fox5,万古霉素类vanC-03;共有可移动元件为intI1.蔬菜基地土壤中共检测到7种抗生素,含量较高的抗生素种类为恩诺沙星(ENR)、诺氟沙星(NOR)、土霉素(OTC)、磺胺甲噁唑(SMX).顺义区S1与S2蔬菜基地土壤中抗生素的种类与丰度均最高,依次是通州区T蔬菜基地、昌平区C2与C1蔬菜基地.相关性分析表明,蔬菜基地土壤中抗生素抗性基因丰度与抗生素丰度存在显著正相关(P 0.05).研究结果可为后续控制抗生素抗性基因的传播提供基础理论数据.     

基于PMF模型的PM2.5中金属元素污染及来源的区域特征分析

金属元素是大气PM_2.5的重要组成成分,对人群危害性极强且兼具源特异性,分析不同经济模式地区大气细颗粒物中金属污染状况及来源差异,可以为科学规划城市产业布局和保护大气环境提供参考.通过霾/非霾期大气PM_2.5采样,使用电感耦合等离子体发射光谱仪（ICP-OES）测定成都市及仁寿县样品中18种金属元素质量浓度,分析其污染水平,并基于正定矩阵因子分解模型（PMF）解析两地大气PM_2.5中金属元素的来源.结果表明,成都市扬尘源、移动源和燃煤源特征元素占元素总和的比值大于仁寿县,而仁寿县生物质燃烧源、工业源以及燃油源特征元素占比则较高.两地Cr、Cd和As元素浓度均超标,表明PM_2.5中重金属污染严重.随着霾污染加剧,两地PM_2.5中金属元素总量上升,但增幅远低于PM_2.5浓度增长.此外,不同元素在霾期和非霾期浓度比值存在差异,成都市变化范围为0.7（Al）~2.8（Ba）,仁寿县介于0.8（Al）~3.1（Mn）之间,但总的来说两地大致呈现出燃煤和工业活动排放元素增幅较大,机动车污染源次之,扬尘源增幅较缓的状况.受地区产业布局、经济规模和发展模式的影响,大气PM_2.5中金属元素污染水平及来源呈现出不同的区域特征.在重点发展第三产业的大型城市,如成都,更易遭受交通运输和城市建设等带来的大气污染,而在仁寿等第二产业占比不断增加的郊县,其污染主要受化石燃料燃烧和工业过程排放的影响.     

内蒙古白云鄂博矿区土壤稀土元素污染特征及评价

白云鄂博矿床是世界上最大的轻稀土矿床,在长期开采过程中向周围环境中释放了大量的稀土元素.为了制定有效地修复方案,必须对稀土元素的浓度、空间分布、分布模式、污染水平和生态风险进行分析和评价.结果表明,土壤样品总稀土含量平均值为6064.95 mg·kg^-1,高于对照点（207.44 mg·kg^-1）、内蒙古（150.95 mg·kg^-1）和中国（184.72 mg·kg^-1）土壤背景值,说明周边土壤出现稀土富集现象.轻稀土元素占到稀土总量的83%~99%,Ce是最主要的轻稀土元素.总稀土的高值区域主要集中于矿源附近,分布极不均匀,受外界干扰较大.各个功能区稀土球粒陨石标准化模式相似,归一化曲线向右倾斜,轻重稀土分馏明显.δCe和δEu的计算显示土壤具有明显的Ce正异常和Eu负异常.La/Yb、La/Sm和Gd/Yb的比值表明,土壤中稀土元素的分布模式是轻稀土元素富集,而且轻稀土元素较重稀土元素具有更为显著的分馏作用.采用4种方法对研究区土壤中稀土元素污染状况和生态风险进行评价.地累积指数计算表明Ce、Nd、Pr和La的均值达到了重污染程度.校正污染程度评价结果显示,不同功能区稀土元素的平均mC_d值范围为7.14~31.38,尾矿库属于高污染水平,居民区和工业区属于非常高污染水平,而采矿区和排土场则达到极高污染水平.污染负荷指数评价显示尾矿库属于中度污染水平,其余功能区则达到重度污染水平.白云鄂博矿区土壤中稀土元素的潜在生态风险指数范围为120.99~6376.46,33%的样点呈现出极强生态风险,16%的样点呈现很强的生态风险,12%的样点呈现较强的生态风险,30%的样点呈现中等风险,只有9%的样点呈现较低的生态风险.因此,亟待采取有效地措施来控制白云鄂博矿区土壤中稀土元素的污染和潜在生态风险.     

北京地区秋冬季大气污染特征及成因分析

为了研究近两年北京地区PM2. 5污染特征及成因变化,利用常规观测资料和改进的后向轨迹模型(Traj Stat)对2016～2017年秋冬季大气重污染时段的颗粒物浓度、气象要素和气团传输路径进行了综合分析.结果表明,研究期间北京地区共发生13次持续2 d以上的重污染事件,冬季过程约占61. 5%,且污染程度和持续时间均高于秋季.地面受弱气压场控制、高湿度、静小风以及较低的混合层高度,加之北京三面环山的特殊地势是导致秋冬季静稳型污染频发的重要因素,重污染期间PM2. 5/PM10的平均比值高达0. 86.累积阶段气团主要来自于西北、偏西、西南和东南方向,其中西南和东南路径为典型污染传输通道,轨迹频率为21. 6%.此外,采用WRF-CAMx模型定量估算了2016年12月16～22日典型过程中本地和外来污染源对北京PM2. 5的贡献,结果发现不同气团输送条件下,二者的贡献差异较大.当南部气团输入时,本地贡献会显著下降,以外部区域输送为主导;若气流来自西北方向情况则相反.污染过程期间,本地贡献为16. 5%～69. 3%.     

北京大气PM2.5载带金属浓度、来源及健康风险的城郊差异

为探究北京地区大气PM_2.5载带金属在城区和郊区污染特征、来源及其健康风险的差异,于2017年6~11月采集海淀和大兴两地的PM_2.5日样本,分析PM_2.5及其载带的13种金属浓度.利用PMF源解析方法对13种金属元素来源进行分析,并采用健康风险评价方法对其中9种金属的健康危害进行评估.结果表明,城区PM_2.5及Cr、Co、Mn和Ni等10种金属浓度与郊区均有显著差异（P<0.05）.源解析结果发现,城区和郊区均可解释为4个源,但来源略有不同,占比亦有差异.城区的为机动车源（51.2%）、燃煤来源（19.1%）、扬尘来源（19.3%）和燃油来源（10.4%）;郊区的为机动车源（47.9%）、燃煤来源（22.6%）、扬尘来源（20.2%）和电镀来源（9.3%）.健康风险评价结果表明,城郊各金属HQ值均小于1,均不存在非致癌风险.城区中Ni和Pb,郊区中Cd、Co、Ni和Pb可忽略致癌风险,而城区的As（2.77×10^-5）、Cd（2×10^-6）、Co（1.76×10^-6）和Cr（Ⅵ）（7.88×10^-6）,郊区的As（8.34×10^-6）和Cr（Ⅵ）（4.94×10^-6）的R值介于10^-6与10^-4之间,具有一定的致癌风险.     

The concentration and probabilistic risk assessment of potentially toxic elements in fillets of silver pomfret (Pampus argenteus): A global systematic review and meta-analysis

The contamination of fish type products such as silver pomfret fish fillets by potentially toxic elements (PTEs) has raised global health concerns. Related studies regarding the concentration of PTEs in fillets of silver pomfret fish were retrieved among some international databases such as Scopus, PubMed and Embase between 1 January 1983 and 10 March 2020. The pooled (mean) concentration of PTEs in fillets of silver pomfret fish was meta-analyzed with the aid of a random-effect model (REM). Also, the non-carcinogenic risk was estimated via calculating the 95th percentile of the total target hazard quotient (TTHQ). The meta-analysis of 21 articles (containing 25 studies or data reports) indicated that the ranking of PTEs in fillets of silver pomfret fish was Fe (11,414.81 µg/kg wet weight, ww) > Zn (6055.72 µg/kg ww) > Cr (1825.79 µg/kg ww) > Pb (1486.44 µg/kg ww) > Se (1053.47 µg/kg ww) > Cd (992.50 µg/kg ww) > Ni (745.23 µg/kg ww) > Cu (669.71 µg/kg ww) > total As (408.24 µg/kg ww) > Co (87.03 µg/kg ww) > methyl Hg (46.58 µg/kg ww). The rank order of health risk assessment by country based on the TTHQ for adult consumers was Malaysia (2.500) > Bangladesh (0.886) > Iran (0.144) > China (0.045) > Pakistan (0.020) > India (0.015), while the corresponding values for child consumers was Malaysia (11.790) > Bangladesh (4.146) > Iran (0.675) > China (0.206) > Pakistan (0.096) > India (0.077). The adult consumers in Malaysia and children in Malaysia and Bangladesh were at considerable non-carcinogenic risk. Therefore, following the recommended control plans in order to reduce the health risk associated with the ingestion of PTEs via consumption of silver pomfret fish fillets is crucial.     

郑州市典型污染过程PM1中重金属浓度、来源及健康风险评估

颗粒物中重金属元素可对人体健康造成不利影响,粒径越小危害越大.利用在线重金属观测仪于2021年1月7～25日在郑州市连续测定PM₁中Al、 Si、 K、 Ca、 V、 Cr、 Mn、 Fe、 Ni、 Cu、 Zn、 As、 Se、 Ba、 Pb和Cd共16种重金属元素.结果表明,观测期间ρ（K）的浓度最高(0.62μg·m^-3).根据污染物浓度和气象特征,将观测期间划分为清洁日、沙尘日和霾日.大气PM₁中重金属污染特征和健康风险评价在不同污染过程下的贡献不同.利用美国EPA健康风险评价法评估重金属的健康风险,采用富集因子法和正定矩阵因子模型（PMF）解析重金属来源,并利用浓度权重轨迹分析法（CWT）和后向轨迹法对传输的影响进行评估.结果表明在不同污染过程下Zn、 As、 Se、 Pb和Cd的富集因子超过100,均受人类活动影响较大.在观测期间重金属主要来源为工业源、燃煤/生物质源、机动车源和扬尘源.将健康风险结果代入PMF分析发现,在清洁日、沙尘日和霾日期间工业源是致癌与非致癌健康风险的主要贡献源,且本地区PM_...     

WDXRF法测定污染土壤和沉积物中金属元素

采用土壤稀释〖CD*2〗波长色散X射线荧光光谱法（WDXRF）测定污染土壤和沉积物样品中的重金属和As,解决了由于元素含量高超出工作曲线测定范围产生较大误差的问题,确保测定结果的有效性。通过标准物质、实际样品的方法比对评估方法的准确度和精密度,该方法测定标准样品中多个无机元素的分析结果均满足国标准确度要求,与常规ICP OES法测定值一致,相对偏差均＜4.5%。     

Chemical and colloidal analyses of natural seep water collected from the exploratory studies facility inside Yucca Mountain,Nevada, USA

Yucca Mountain is being considered as a geological repository for the USA’s spent nuclear fuel and high-level nuclear waste. Numerous groundwater seeps appeared during March 2005 within the exploratory studies facility (ESF), a tunnel excavated in the mountain. Because of the relevance to radionuclide transport and unsaturated zone-modeling studies, we analyzed the seep samples for major anions and cations, rare earth elements, and colloids. Major ion species and elemental concentrations in seep samples reflect interaction of the water with the volcanic rock and secondary calcites. Elemental fractograms from flow-injection field-flow fractionation ICP–MS scans detected Br, Ca, Cl, Cu, Fe, I, Mg, Si, Sr, W, and U at void fractions, suggesting they may be present in the form of dissolved anions. Colloids approximately 10 nm in hydrodynamic diameter, possibly calcite, were also present in the seepage samples. Geochemical calculations indicate, however, these may be an artifact (not present in the groundwater) which arose because of loss of CO₂ during sample collection and storage.     

Medical geochemistry research in Spišsko-Gemerské rudohorie Mts., Slovakia

This study presents an assessment of the potential impact of geological contamination of the environment on the health of the population in Spišsko-Gemerské rudohorie Mts. (SGR Mts.). The concentration levels of potentially toxic elements (mainly As, Cd, Cu, Hg, Pb, Sb, and Zn) were determined in soils, groundwater, surface water, and stream sediments as well as in the food chain (locally grown vegetables). A medical study included some 30 health indicators for all 98 municipalities of the study area. The As and Sb contents in human fluids and tissues were analyzed in one municipality identified to be at the highest risk. Based on element content, environmental and health risks were calculated for respective municipalities. Out of 98 municipalities 14 were characterized with extremely high environmental risk and 10 were characterized with very high carcinogenic risk from arsenic (groundwater). Extensive statistical analysis of geochemical data (element contents in soils, groundwater, surface water, and stream sediments) and health indicators was performed. Significant correlations between element contents in the geological environment and health indicators, mainly cancer and cardiovascular diseases, were identified. Biological monitoring has confirmed the transfer of elements from the geological environment to human fluids and tissues as well as to the local food chain.