天津市采暖季PM2.5组分消光特性及来源分析

为了解天津市采暖季细颗粒物组分对能见度的影响、明确消光组分来源,对天津市2017年采暖季大气PM_2.5样品进行了为期一月的连续采集,并测定水溶性离子、有机碳和元素碳的含量,通过修正IMPROVE方程研究了细颗粒物消光特性,并采用主成分分析—多元线性回归模型(PCA-MLR)对其来源进行解析,同时应用潜在源贡献因子(PSCF)和浓度权重轨迹(CWT)明确PM_2.5质量浓度的潜在污染源区域。结果表明,OC、EC以及SNA(NO3^?、NH₄⁺、SO₄^2?)的生成和积累对于能见度的下降具有重要影响,且能见度随SOR和NOR二次转化程度的升高而下降;2017年天津市采暖季日均消光系数为(294.56±262.89)Mm^?1,其中OM(34.86%)、硝酸盐(22.84%)、硫酸盐(11.59%)和EC(11.54%)为主要消光组分,硝酸盐和硫酸盐的增加对于能见度的下降起主要影响作用;根据PCA分析结果可知,天津市采暖季PM_2.5中的碳组分和水溶性离子主要来源于燃煤、生物质燃烧(68%),受扬尘(22%)和海盐(8%)的影响较小;区域传输分析结果表明天津市采暖季PM_2.5污染源潜在区域主要分布在河北中西部、河南北部、山西北部和内蒙古中部、西部。     

Assessment of groundwater contamination using geographic information systems

In this study two sites were selected in order to investigate groundwater contamination and spatial relationships among groundwater quality, topography, geology, landuse and pollution sources. One site is the Asan area, an agricultural district where pollution sources are scattered and which is mainly underlain by granite of Cretaceous age. The other site is the Gurogu area of Seoul city, an industrial district where an industrial complex and residential areas are located and which is mainly underlain by gneiss of Precambrian age. Groundwater samples collected from these districts were analysed for chemical constituents. An attribute value files of chemical constituents of groundwater and the spatial data layers were constructed and pollution properties were investigated to establish out spatial relationships between the groundwater constituents and pollution sources using geographic information systems (GIS).Relatively high contents of Si and HCO₃ ^– in the groundwater from the Asan area reflect the effect of water–rock interaction whereas high contents of Cl^–, NO₃ ^– and Ca²⁺ in the groundwater from the Gurogu area are due to the pollution of various sources. The significant seasonal variation of SiO₂, HCO₂ ^– and Ca²⁺ contents, and that of Ca²⁺ content were observed in the Asan and the Gurogu areas, respectively. Seasonal variation of pollutants such as Cl^–, NO₃ ^– and SO₄ ^2– was not observed in either area. Pollution over the critical level of the Korean drinking water standard has been investigated from 15 sampling sites out of 40 in the Asan area, and 33 sampling sites out of 51 in the Gurogu area. Pollution by NO₃ ^–, Cl^–, Fe²⁺, Mn²⁺, SO₄ ^2– and Zn²⁺ in the groundwater from the industrial district (Gurogu area) and that of NO₃ , SO₄ ^2– and Zn²⁺ in the groundwater from the agricultural district (Asan area) were observed. The principal pollutant in both areas is NO₃ ^–. Deep groundwater from the Asan area is not yet contaminated with NO₃ ^– except for one site, but most of the shallow groundwater site occurring near the potential point sources is seriously contaminated. From the result of buffering analysis, it seems clear that factories and stock farms are the principal pollution sources in the Asan area. The groundwater from the Gurogu area has already been seriously polluted considering the fact of NO₃ ^– contamination of deep groundwater. Chlorine pollution of shallow groundwater in the Gurogu area was also observed. Spatial relationship between pollution level and its source was clarified in this study by using GIS, which will be applicable to the effective management of groundwater quality.     

黄河源区生态破坏现状及保护对策

黄河源区自然条件严酷,生态环境脆弱。随着黄河源区资源开发力度逐步加大,草场和灌丛植被遭到不同程度的破坏,生态环境日趋恶化。具体表现为草原退化严重,水土流失加剧,土地荒漠化扩大,水源涵养能力大为降低。因此,保护黄河源区生态环境,建立黄河源头特殊生态功能保护区已刻不容缓。     

不同碳源对两株真菌纤维素酶合成的诱导和调控

定时测定B-6(Aspergillus sp.)、AS3.3711(Trichoderma sp.)在各类碳源中的纤维素酶活力，结果发现，酶的合成受培养基中碳源性质的调节控制。结构相对完整的纤维类物质（α-纤维素粉、微晶纤维素）诱导活性较高，电泳结果表明，纤维素酶系是协同表达的，但酶系各组分的百分比在不同的诱导条件下却各不相同。在测定糖耗与酶活力的关系中发现纤维二糖直接诱导B-6纤维素酶的合成，对AS3.3711则起了间接诱导作用，其经菌体代谢后的某种转化产物才是AS3.3711纤维素酶合成的真正诱导源。图6表1参14     

基于受体模型和控制单元分区的流域污染源解析——以永定河张家口段为例

为识别永定河张家口段水体污染的主要来源并确定流域重点管控行业和优控单元,将受体模型与控制单元分区相结合,建立流域污染源解析方法。结合研究区水系分布、行政区划和数字高程模型(DEM)数据进行控制单元划分,利用聚类分析进行水质和污染源空间特征分析,通过因子分析和绝对主成分-多元线性回归(APCS-MLR)受体模型进行分区污染源识别与贡献率计算。结果表明:永定河张家口段按水质污染程度可分为污染较重的A区(洋河、清水河中下游)和污染较轻的B区(洋河、清水河上游及桑干河);A区受工业点源与面源混合影响,其中工业点源、农业种植贡献率分别为43%、44%;B区主要受面源影响,其中农村生活及旅游、农业种植、畜禽养殖贡献率分别为30%、18%、17%;由污染源空间特征,提出A区的重点管控行业为冶金和食品制造业,B区则为采矿业和食品制造业,确定覆盖阳原县的2、3号,覆盖涿鹿县北部和蔚县北部的5号,覆盖万全区的14号控制单元为面源污染优先防控单元。源解析与控制单元分区相结合的方法可较好地反映水质空间分异特征,提高源解析能力。     

基于随机森林算法与农户视角的村落级农业面源污染风险分析

当前农业面源污染问题依然严峻,村落级尺度下各地块的污染风险状态精细识别有待进一步研究.本文针对三峡库区典型村落重庆市涪陵区南沱镇睦和村进行研究,结合无人机多光谱技术、农户行为调研、随机森林算法等进行地物识别及泛地块网格划分,通过测算总氮(total nitrogen,TN)、总磷(total phosphorus,TP...     

放射源使用中潜在照射危险的评价与控制浅述

文章介绍了潜在照射的主要来源及危害。结合实际应用中的具体情况,对其使用实践中可能导致的潜在危害作了简单的分析,并根据ICPLP的相关建议和国家相关的具体要求,提出在放射源应用领域潜在照射控制的主要原则和措施。     

巢湖水及沉积物中总磷的分布变化特征

磷是导致巢湖水体富营养化的主要营养物质。采集大量巢湖表层水和沉积物样品,通过检测上覆水和沉积物中总磷含量,分析巢湖水体中磷的时空变化及赋存特征。结果显示:巢湖南淝河和裕溪河河口的上覆水中总磷含量值时间变化特征为8月5月3月12月;且南淝河口总磷含量年均值超过地表水Ⅴ类水质标准,明显高于裕溪河口值;表层水和沉积物中总磷含量在空间分布上呈西高东低趋势,最高值均出现在靠近合肥市河口处。巢湖周边土壤及湖区磷的等值线分布表明:杭埠河流域农业污染、东巢湖东南部水土流失可能是巢湖磷面源污染的主要来源。巢湖上覆水和沉积物中总磷的相关系数为0.515,蓝藻爆发期全湖表层沉积物中总磷含量显著减少,揭示目前内源磷释放已是巢湖富营养化的主要因素。结果将对巢湖流域的污染综合防治及蓝藻治理工作提供科学依据。     

农田面源污染团队式治理方法初探

我国农田面源污染的环境经济治理方式还不健全,急需适应我国农业特征的面源污染治理手段。现阶段环境税费政策通过对农业投入的控制,容易影响农户农业生产的积极性,而且还存在一定的技术难度和设备成本约束。团队式治理方法是一种更直接的面源污染监管手段,通过将农户组成团队,比管理单个农户节约成本;通过一定的奖惩措施激励农户主动调整污染排放水平;给定的合约条件约束了农户在重复博弈下的"搭便车"行为,保证了团队的存续。     

武汉集中式饮用水源地土壤重金属的时空分布特征及生态风险评价

研究了武汉市19个集中式饮用水源地土壤重金属Cd、Hg、As、Pb、Cr、Cu、Ni和Zn的时空分布特征,采用单因子污染指数和综合污染指数分析重金属污染程度,利用潜在生态风险指数评价重金属生态风险,通过相关性和聚类分析重金属的来源.结果表明,武汉市中心城区水源地土壤重金属的含量普遍高于远城区,同时长江干流附近的水源地土...