云南荞麦地流域地下水水化学特征及物质来源分析

为研究荞麦地流域地下水的水化学特征及物质来源,2017年7月在研究区共采集地下水的水样32个,综合运用聚类分析、因子分析和路径模型分析等方法,分析了荞麦地流域地下水水化学特征,并定性和定量探讨了荞麦地流域地下水水化学的物质来源.结果表明,研究区内水体整体呈弱碱性,Ca~(2+)、Mg~(2+)、SO_4~(2-)、HCO_3~-和N_3O~-等主要阴阳离子具有较高的空间变异性.通过聚类分析可知,研究区内地下水可分为两大类:A类和B类,分别具有两个子集:A_1、A_2、B_1和B_2,并且从A类地下水到B类地下水化学类型开始变得复杂,A类地下水水化学类型均为HCO_3-Ca型,B_1类地下水和B_2类地下水分别有HCO_3-Ca型、HCO_3-Na·Ca型、HCO_3-Na·Ca·Mg型和HCO_3-Ca型、HCO_3-Ca·Mg型、HCO_3-Na·Ca型各3类.为进一步探讨地下水水化学的影响因素,通过因子分析和路径模型分析可确定碳酸盐岩、人类活动、蒸发岩和硅酸盐岩是地下水的主要物质来源.其中人类活动的作用和MgSO_4型蒸发岩的溶解,是形成以碳酸盐岩为地下水化学组分的主要来源,同时具有多元地下水水化学特征的重要原因.     

曹妃甸地区地下水水化学特征及影响因素的R型因子分析

通过对2008年12月份在曹妃甸地区采集测试的25组水化学资料进行分析,探讨了该区地下水的水化学特征,并利用R型因子分析法对影响该区地下水化学组分的4个主要因素进行了研究,结果表明:区内浅层地下水基本都为高矿化的Cl-Na型,深层地下水水化学类型具有一定的水平分带性;高矿化的地表水和潜水主要是蒸发浓缩作用和沿海土壤易溶盐含量高共同影响的结果,深层地下水水化学组分主要受含水介质中易溶盐分组成和补给水高碳酸含量的影响;地下水中NH4+、NO3-和NO2-的广泛检出反映了农业生产和人们生活排污等人类活动对地下水化学组分的影响。     

不同水分管理方式下水稻生长季N_2O排放量估算:模型应用

基于田间原位测定结果,作者建立了不同水分管理方式下稻田N2O排放估算的统计模型.在模型验证和输入参数检验的基础上,本研究应用模型估算了20世纪50～90年代我国稻田水稻生长季N2O直接排放量.结果表明,由于水稻种植面积和氮输入量的增加、以及水分管理方式的变化,稻田N2O-N季节排放量从20世纪50年代平均每年9.55 Gg增加到了90年代每年32.26 Gg,同期伴随着水稻单产的增加.在20世纪50～90年代间,我国水稻生产的N2O-N排放量以平均每10 a 6.74 Gg的速度递增.20世纪50年代和90年代稻田N2O-N季节排放通量平均分别为0.32 kg·hm-2和1.00 kg·hm-2,相当于季节氮输入总量的0.37%和0.46%.本研究模型估算50～90年代间稻田N2O季节排放量的不确定性为59.8%～37.5%.就全国稻田的不同种植区域而言,长江中下游地区稻田水稻生长季N2O排放量占全国稻田N2O排放总量的51%～56%.20世纪90年代水稻生长季N2O排放量约占我国农田N2O年总排放量的8%～11%.相对于旱地作物而言,过去几十年水稻生产的发展在很大程度上减缓了我国农业生产的N2O排放.然而,随着水稻生产中节水灌溉的推广和氮肥施用量的增加,我国稻田N2O季节排放量预计将相应增加.     

梭鱼草净化黑臭河水的日变化试验研究

测定了曝气和非曝气的2个植物净化槽在1 d中7个不同时间点的出水水质理化指标(pH、DO、COD、NH_4~+-N、TP)及植物叶片的叶绿素(Chla)、可溶性蛋白(SP)含量及过氧化物酶(POD)活性,另设空白槽为对照;试验目的是研究各指标的日变化情况及相互关系,为提高梭鱼草净化黑臭河水的处理效率及其植物净化槽的合理优化运行提供科学依据.结果表明,各水槽内所测指标的变化均在一定程度上与光强变化相关,对非曝气植物槽的分析发现,在出水理化指标中TP浓度与光强的相关性最好(r=0.93,p<0.01),而在植物生理指标中SP含量与光强相关性最好(r=0.91,p<0.01);植物处理使出水的DO日均值增加了0.13 mg/L,而曝气植物处理则使其增加了1.8 mg/L,曝气是对城市黑臭河水进行植物净化修复的必要辅助手段;曝气植物槽对黑臭河水中COD和NH_4~+-N的去除率日均值比植物槽升高了7.1%和6.3%(p<0.01),TP去除率却相应下降了38%(p<0.01);与非曝气槽植物相比,曝气槽植物体内Chla、SP日平均含量显著降低(p<0.05)而POD活性显著升高(p<0.05);光强和曝气的变化能迅速而显著地影响梭鱼草的生理特性从而改善其净化槽出水水质,是构建和优化黑臭河水植物净化槽时值得考虑的重要调控因素.     

地下环境中Fe2+对硝基苯的还原衰减作用模拟研究

研究了地下环境中的Fe2+对硝基苯(NB)的还原衰减作用,模拟了Fe2+还原硝基苯的过程及不同硬度、CO32-、SO42-、NO3-、Cl-等地下水化学组成对反应的影响,目的是阐明Fe2+还原硝基苯的机制及水化学组成对反应影响的原因.结果表明,在温度为10℃、pH为6.8的条件下,Fe2+和硝基苯浓度皆对其还原衰减有影...     

Multivariate analysis of surface water quality in the Three Gorges area of China and implications for water management

Multivariate statistical techniques, cluster analysis, non-parametric tests, and factor analysis were applied to analyze a water quality dataset including 13 parameters at 37 sites of the Three Gorges area, China, from 2003–2008 to investigate spatio-temporal variations and identify potential pollution sources. Using cluster analysis, the twelve months of the year were classified into three periods of lowflow (LF), normal-flow (NF), and high-flow (HF); and the 37 monitoring sites were divided into low pollution (LP), moderate pollution (MP), and high pollution (HP). Dissolved oxygen (DO), potassium permanganate index (CODMn), and ammonia-nitrogen (NH4 +-N) were identified as significant variables affecting temporal and spatial variations by non-parametric tests. Factor analysis identified that the major pollutants in the HP region were organic matters and nutrients during NF, heavy metals during LF, and petroleum during HF. In the MP region, the identified pollutants primarily included organic matter and heavy metals year-around, while in the LP region, organic pollution was significant during both NF and HF, and nutrient and heavy metal levels were high during both LF and HF. The main sources of pollution came from domestic wastewater and agricultural activities and runoff; however, they contributed differently to each region in regards to pollution levels. For the HP region, inputs from wastewater treatment plants were significant; but for MP and LP regions, water pollution was more likely from the combined effects of agriculture, domestic wastewater, and chemical industry. These results provide fundamental information for developing better water pollution control strategies for the Three Gorges area.     

粤闽交界中强地震前水化学异常特征分析

研究了粤闽交界90年以来ML≥4.5地震前水化学前兆资料,结果表明:(1)水化学前兆异常形态复杂多样,以短期和短临变化为主;(2)同一台站震前所观测的异常变化具有多测项同步异常的特征;(3)震前异常持续时间、异常形态与震中距有关。同时研究表明,统计水化学异常出现的集中程度无法判定未来震中位置。     

WATCH

Abstract

The characteristics of fine particulate pollution (PM₁₀ and PM_2.5) were measured at urban and suburban sites in Jinan during the 2008–2009 heating and non-heating seasons. The results showed that PM₁₀ and PM_2.5 pollution was quite serious, and PM mass concentration was higher during the heating season than the non-heating season. PM was the highest in the chemical factory and lowest in the development zone. The mass concentrations of PM₁₀ and PM_2.5 were linearly related, and the mass concentration ratio of PM_2.5/PM₁₀ was up to 0.59 in urban areas. PM pollution in Jinan was related to local meteorological factors: PM_2.5 mass concentration and humidity were positively correlated, and PM_2.5 mass concentration was negatively correlated with both click on the temperature and wind speed, although wind speed varied more.     

Variations in the elemental compositions of plants,and computer‐aided sampling in ecosystems∗

To obtain comparable results of multi‐element analysis of plant materials by different laboratories, a harmonized sampling procedure for terrestrial and marine ecosystems is essential. The heterogeneous distribution of chemical elements in living organisms is influenced by different biological parameters. These parameters are mainly characterized by genetic predetermination, seasonal changes, edaphic and climatic conditions, and delocalization processes of chemical substances by metabolic activities.

The biological variations of the element content in plants were divided into 5 systematic levels, which are: 1. the plant species; 2. the population; 3. the stand (within an ecosystem); 4. the individual; and 5. the plant compartment. Each of these systematic levels can be related to: 1. genetic variabilities; 2. different climatic, edaphic and anthropogenic influences; 3. microclimatic or microedaphic conditions; 4. age of plants (stage of development), exposure to environmental influences (light, wind, pollution etc.), seasonal changes; and 5. transport and deposition of substances within the different plant compartments (organs, tissues, cells, organelles).

An expert system for random and systematic sampling for multi‐element analysis of environmental materials, such as plants, soils and precipitation is presented. After statistical division of the research area, the program provides advice for contamination‐free collection of environmental samples.     

Trend,seasonal variation and sources of suspended particulated matter (SPM) in Spain

In this study we analyze the temporal evolution of the suspended particulated matter (SPM) in the air of the six Spanish remote stations belonging to the European Monitoring and Evaluation Programme network. A negative trend is observed in three of them and a positive trend in one. Another objective of this work was to know the geographical sources of SPM in Spain. To do this we used the conditional probability functions (cf. Ashbaugh et al. (1985), Atmos. Environ., 19, 1263–1270) and information about air masses trajectories. The North of Africa and regions inside Spain are the main sources while Continental Europe and the British Islands are less important.