基于高光谱分形分析的水稻镉污染动态监测

水稻中过量镉会影响叶绿素含量和细胞结构,进而改变水稻在光谱维上的特征表现.利用长春郊区实测大田水稻高光谱数据和同步测量的土壤、水稻生化参数,系统分析水稻冠层光谱曲线的分形特征及不同镉污染胁迫程度下光谱分维与两类光谱指数的变化情况,构建光谱分维、光谱指数与水稻叶片镉浓度的空间分布图,探讨光谱分维与光谱指数在提取镉污染胁迫等级信息中的相互关系及物理机制.研究表明,光谱分维相对于光谱指数能够更好地综合反映镉污染胁迫下水稻生理特征参数的变化,因而为有效地大范围动态监测水稻镉污染提供诊断依据.     

基于自动监测监控技术的环境安全防控系统的设计与应用

采用先进的物联网、云计算和模型仿真等技术,陈述了基于自动监测监控技术的环境安全防控系统的设计和应用。该系统利用物联网、GIS等先进技术,将重点源企业、河流断面、放射源等纳入到统一的环境监控网络中,全方位构建区域内环境安全防控大格局。根据城市环境应急现状,建立三级环境安全防控体系,实现对环境安全事故的有效预防、控制和处置。     

Nutrient mitigation in a temporary river basin

We estimate the nutrient budget in a temporary Mediterranean river basin. We use field monitoring and modelling tools to estimate nutrient sources and transfer in both high and low flow conditions. Inverse modelling by the help of PHREEQC model validated the hypothesis of a losing stream during the dry period. Soil and Water Assessment Tool model captured the water quality of the basin. The ‘total daily maximum load’ approach is used to estimate the nutrient flux status by flow class, indicating that almost 60 % of the river network fails to meet nitrogen criteria and 50 % phosphate criteria. We recommend that existing well-documented remediation measures such as reforestation of the riparian area or composting of food process biosolids should be implemented to achieve load reduction in close conjunction with social needs.     

Fucus spiralis as monitoring tool of metal contamination in the northwest coast of Portugal under the European Water Framework Directives

Metals (Cd, Cr, Cu, Fe, Mn and Zn) in coastal seawaters and soft tissues of macroalga Fucus spiralis from the northwest coast of Portugal were determined to assess spatial variations of metal bioavailabilities and bioaccumulation factors to compare different ecological quality classifications. Both coastal seawaters and soft tissues of F. spiralis showed significant spatial variations in their metal concentrations along the coast. The macroalgae F. spiralis accumulated more efficiently Cd, Mn and Zn and showed low bioaccumulation factors to Cr, Cu and Fe. Regarding the metal guidelines of the Norwegian Pollution Control Authority, the entire northwest (NW) coast of Portugal in April 2013 should be classified as ‘class I—unpolluted’ for all metals, except in Ave for Cu (‘class II—moderately polluted’) and Cavado for Cd and Cu (‘class II—moderately polluted’), revealing the low metal bioavailabilities of these seawaters. As there were always significant positive correlations between all metals in seawaters and F. spiralis, this macroalga species was considered a suitable monitoring tool of metal contamination in the NW coast of Portugal and a useful aquatic organism to be included in the European Environmental Specimen Banks in order to establish a real-time environmental monitoring network under the European Water Framework Directives.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

核电厂放射性流出物监测工作探讨

简述了放射性流出物监测的重要性,分析了我国核电厂放射性流出物监测中存在问题,探讨了借鉴国际原子能机构安全及相关标准开展我国核电厂放射性流出物监测的管理机制、监测方案、监测报告和质量保证等具体要求与方法,并提出提升技术基础能力、完善法规标准、加强监管力度的建议.     

Avoiding climate change uncertainties in Strategic Environmental Assessment

This article is concerned with how Strategic Environmental Assessment (SEA) practice handles climate change uncertainties within the Danish planning system. First, a hypothetical model is set up for how uncertainty is handled and not handled in decision-making. The model incorporates the strategies ‘reduction’ and ‘resilience’, ‘denying’, ‘ignoring’ and ‘postponing’. Second, 151 Danish SEAs are analysed with a focus on the extent to which climate change uncertainties are acknowledged and presented, and the empirical findings are discussed in relation to the model. The findings indicate that despite incentives to do so, climate change uncertainties were systematically avoided or downplayed in all but 5 of the 151 SEAs that were reviewed. Finally, two possible explanatory mechanisms are proposed to explain this: conflict avoidance and a need to quantify uncertainty.     

太湖流域稀土企业放射性废水污染调查

为治理太湖流域稀土加工过程中产生的放射性废水环境污染,对比分析了太湖流域2家典型稀土企业2005年-2009年的废水和底泥的总α、总β和238U、232Th、226Ra、40K,评价放射性污染对环境的影响程度,为消除放射性废水环境污染危害提供客观依据和方法建议.     

甘家湖湿地边缘带土地荒漠化演变中土壤颗粒分形特征

采用分形理论,研究了甘家湖湿地边缘带不同景观变化类型土壤颗粒体积分形维数的特征。结果表明,（1）从芦苇湿地边缘、胡杨林土、梭梭灌木林土、芦苇湿地、耕地周边、耕地到盐化草甸土的土壤粒径变化可以看出：湿地边缘带土壤荒漠化演变中砂粒含量在逐渐上升,粉粒、粘粒含量逐渐下降。这表明湿地边缘带人为的放牧、开垦、牛羊践踏对土壤产生了...     

面向智慧城市的分布式噪声管理系统设计

针对城市噪声污染多头管理、监测方法单一、治理效率低等问题,基于Android 4G技术城市环境噪声分布式监测设计思想,介绍智慧城市噪声分布式监测的应用方法。以移动终端作为传感器节点替代传统集中式噪声监测的分布式监测方法,依托云计算数据处理平台,解决了监测网络数据管理分散、定点检测站和一些手持检测设备收集数据引起的信息滞后的问题,有益于实现城市环境噪声污染数据分析、处理和融合等复杂功能,使各种质控任务和标准传递等复杂任务得到自动化执行与反馈,将对城市噪声污染联防联控起到积极推动作用。     

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O<Subscript>3</Subscript> Air Quality Monitoring Network in Vojvodina Province,Serbia

A monitoring network of ground-level ozone (O₃) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O₃ monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O₃ monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.     

Temporal-spatial variability and fractal characteristics of soil nitrogen and phosphorus in Xinji District, Hebei Province, China

Traditional statistics, geostatistics, fractal dimensions, and geographic information systems (GIS) were employed to study the temporal?Cspatial variability of soil total nitrogen (TN) and total phosphorus (TP) levels in Xinji District, Hebei Province area of the North China Plain from 1980 to 2007. The results indicate that nutrient levels follow normal or lognormal distributions. The TN content was 0.59 ±0.155 g kg^???1 in 2007, an increase of 0.44 g kg^???1 compared with that of 1980. In 2007, the TP content was 1.21 ±0.227 g kg^???1, an increase of 0.01 g kg^???1 from 1980. The geostatistical analysis showed that the distribution of these soil nutrients in the study area exhibits a trend and anisotropy. The range and [C ₀/(C ₀?+?C)] of TN and TP in 1980 were all less than in 2007. The ordinary kriging interpolation method was used to analyze the nutrient contents differences between 1980 and 2007. The results indicate that soil TN levels have increased over the 27-year period, and the area where the TN level had increased by at least 0.4 g kg^???1 was about 61.7% of the district. The area where the TP content increased covered about 58.4% of the district. The variance analysis indicated that land-use type had a clear influence on the distribution and change in TN and TP content. Using the 3-D box-counting dimension method combined with GIS, the fractal dimension of soil nutrient spatial distribution over the two periods showed that in 27 years, the fractal dimension of TN increased from 1.95 to 2.02, and the fractal dimension of TP increased from 1.89 to 2.01, indicating that the complexity of the spatial distribution of all nutrient contents had increased. This study can provide a basis for accurate fertilizing and to enhance the conversion of soil characteristics under different spatial scales.     

基于分形求和模型的克拉玛依市空气质量评价

以克拉玛依市4个区2012年的大气自动监测数据为样本,基于分形求和模型,分析大气污染物的分布特征,利用分维数确定污染物浓度分布的随机程度,计算 SO2、NO2、PM10的大气环境背景值与标准值,确定适合于评价区域的ORAQI指数计算公式,并与 API指数作对比。ORAQI指数计算结果显示,克拉玛依市全年环境空气质量基本呈现“U”字形变化,春夏季大气质量好于秋冬季,全年空气质量有明显的季节变化,4个区中克拉玛依区空气质量相对较差,乌尔禾区空气质量最好。相对于 API指数的均匀分布结果,ORAQI指数具有更好的次要污染物体现能力,可以综合体现所评价的各项污染因子的贡献。     

Quantification of reef benthos communities and variability inherent to the monitoring using video transect method

Long-term monitoring program of organisms is the most recommended for understanding changing processes on reefs. The video transect method presents advantages for that. Specialists state that it is important to make sure that the recorded coverage is always the same between campaigns, so that differences in results may be entirely attributed to environmental changes. This study aimed to test the capability of implementing this requirement through tracking simulation and its validity for monitoring the benthic communities of reefs using the video transect method. Ten transects 20 m long were established in Todos os Santos Bay coral reefs. Subsequent to the first transect capture, a second diver repeated the same track, simulating two different monitoring campaigns. Data were transformed and a matrix of similarity was generated using Bray–Curtis’ Index. ANOSIM analysis was performed to test the similarity of the ten transects and its repetitions. The result, R = 0.08 (P = 0.928), shows that reef monitoring using video transect, the way it is described in the literature, is appropriate, but it is important to consider some premises discussed in this work.     

Improving Estimation of Specific Surface Area by Artificial Neural Network Ensembles Using Fractal and Particle Size Distribution Curve Parameters as Predictors

Specific surface area (SSA) is one of the principal soil properties used in modeling soil processes. In this study, artificial neural network (ANN) ensembles were evaluated to predict SSA. Complete soil particle-size distribution was estimated from sand, silt, and clay fractions using the model by Skaggs et al. and then the particle-size distribution curve parameters (PSDCPs) and fractal parameters were calculated. The PSDCPs were used to predict 20 particle-size classes for a soil sample’s particle size distribution. Fractal parameters were calculated by the model of Bird et al. In addition, total soil-specific surface area (TSS) was calculated using the above 20 size classes. Pedotransfer functions were developed for SSA and TSS using ANN ensembles from 63 pieces of SSA data taken from the literature. Fractal parameters, PSDCPs, and some other soil properties were used to predict SSA and TSS. Introducing fractal parameters and PSDCPs improved the SSA estimations by 12.5 and 11.1 %, respectively. The improvements were even better for TSS estimations (27.7 and 27.0 %, respectively). The use of fractal parameters as estimators described 44 and 92.8 % of the variation in SSA and TSS, respectively, while PSDCPs explained 42 and 6.6 % of the variation in SSA and TSS, respectively. The results suggested that fractal parameters and PSDCPs could be successfully used as predictors in ANN ensembles to predict SSA and TSS.     

河流重油泄漏事故的应急监测

介绍了河流重油泄漏事故的应急监测,包括监测方案制定、监测点位设置、分析对象确定、跟踪监测、数据分析等。重油污染可通过监测水体中的石油类进行。监测结果表明,重油泄漏事故在短期内对水环境造成了严重影响,清除完全后,水体可逐步恢复正常。重油污染具有一定的持久性,在事发后需要对水体进行长期的跟踪监测。     

Cumulative effects of developed road network on woodland—a landscape approach

Population growth, during the twentieth century, has increased demand for new farmlands. Accordingly, road networks have rapidly been developed to facilitate and accelerate human access to the essential resources resulted in extensive land use changes. The present study aims at assessing cumulative effects of developed road network on tree cover of Golestan Province in northern Iran. In order to detect changes over the study period of 1987–2002, the LULC map of the study area was initially prepared from the satellite images of Landsat TM (1987) and ETM+ (2002) using maximum likelihood supervised classification method. Afterwards, a total number of seven landscape matrices were selected to detect cumulative effects of the developed road network on woodland cover. The obtained results indicated that the fragile patches are mainly located at a distance of 171–342 m from the roadside. Furthermore, the majority of the patches affected by cumulative effects of development activities are situated at a distance of 342–684 m from the roadside, over an approximate area of 55 ha. The analysis of landscape metrics revealed that the developed road network has increased the landscape metrics of “the number of patches” and “patches perimeter-area ratio”. It has also followed by a decrease in metrics such as “patches area”, “Euclidean nearest neighbor distance”, “patches proximity”, “shape index”, “contiguity”, and “mean patches fractal dimension”. The road network has also increased the “number of patches” and decreased the “mean patches area” representing further fragmentation of the landscape. With identification of highly affected wooldland cover patches, it would be possible to apply adaptive environmental management strategies to preserve and rehabilitate high-priority patches.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Assessing the impact of multiple drivers of land sensitivity to desertification in a Mediterranean country

Experiencing climate changes and increased human pressure, Mediterranean regions are considered representative hotspots of desertification. However, relatively few studies have been devoted to quantify the individual impact of different factors shaping land sensitivity to desertification in these contexts. Our study contributes to this deserving (positive and normative) issue with a diachronic analysis of the impact of multiple drivers of desertification risk on six indicators of land sensitivity based on the Environmentally Sensitive Area (ESA) approach. Indicators (average and maximum ESA score, coefficient of variation and normalized range in the ESA scores, share of ‘fragile’ and ‘critical’ areas in total landscape) were calculated in 777 rural districts of Italy at three time points (early-1960s, early-1990s, and early-2010s). Multivariate models were used to determine the impact of 12 predictors (climate, soil, vegetation, and land management quality) on each indicator of land sensitivity. Results of the analysis identified two non-redundant dimensions respectively associated with the average level of land sensitivity and its intrinsic variability across space. Impacts of climate and vegetation qualities on the level of land sensitivity were high, decreasing over time, and more intense respectively in Northern and Southern Italy. Impacts of soil and land management qualities were moderate, increasing over time, and involving almost all the country's area. Our study emphasizes the role of context-based measures promoting sustainable land management. The ‘local’ dimension proved to be crucial in any strategy of risk mitigation undertaken at disaggregated spatial scales.