State of the Art Report on Mathematical Methods for Groundwater Pollution Source Identification

The reliable assessment of hazards or risks arising from groundwater contamination problems and the design of efficient and effective techniques to mitigate these problems require the capability to predict the behavior of chemical contaminants in flowing water. Most attempts at quantifying contaminant transport have relied on a solution of some form of a well-known governing equation referred to as advection-dispersion-reaction equation. To choose an appropriate remediation strategy, knowledge of the contaminant release source and time release history becomes pertinent. As additional contaminated sites are being detected, it is almost impossible to perform exhaustive drilling, testing, and chemical fingerprint analysis every time. Moreover, chemical fingerprinting and site records are not sufficient to allow a unique solution for the timing of source releases. The purpose of this paper is to present and review mathematical methods that have been developed during the past 15 years to identify the contaminant source location and recover the time release history.     

Mathematical Model for Pollution Source Identification in Rivers

Release of pollution into rivers is required to be handled with special consideration to environmental standards. For this purpose, it is essential to specify the contribution of each pollution source in contamination of water resources. In this study, a mathematical model is proposed for determining locations and concentration release histories of polluting point sources using measured downstream river concentrations via an inverse problem framework. The inverse solution is based on the integral equation obtained from applying the Green's function method on the one-dimensional advection-dispersion contaminant transport equation. Discretization of this integral equation results in a linear, over-determined and ill-posed system of algebraic equations that are solved by using the Tikhonov regularization method. Several examples and some real field data are investigated to illustrate the abilities of the proposed model. Results imply that the proposed method is effective and can identify the pollution sources in rivers with acceptable accuracy.     

A Monitoring Network Design Procedure for Three-Dimensional (3D) Groundwater Contaminant Source Identification

Finding the location and concentration of contaminant sources is an important step in groundwater remediation and management. This discovery typically requires the solution of an inverse problem. This inverse problem can be formulated as an optimization problem where the objective function is the sum of the square of the errors between the observed and predicted values of contaminant concentration at the observation wells. Studies show that the source identification accuracy is dependent on the observation locations (i.e., network geometry) and frequency of sampling; thus, finding a set of optimal monitoring well locations is very important for characterizing the source. The objective of this study is to propose a sensitivity-based method for optimal placement of monitoring wells by incorporating two uncertainties: the source location and hydraulic conductivity. An optimality metric called D-optimality in combination with a distance metric, which tends to make monitoring locations as far apart from each other as possible, is developed for finding optimal monitoring well locations for source identification. To address uncertainty in hydraulic conductivity, an integration method of multiple well designs is proposed based on multiple hydraulic conductivity realizations. Genetic algorithm is used as a search technique for this discrete combinatorial optimization problem. This procedure was applied to a hypothetical problem based on the well-known Borden Site data in Canada. The results show that the criterion-based selection proposed in this paper provides improved source identification performance when compared to uniformly distributed placement of wells.     

State of the Art Report on Multivariate Chemometric Methods in Environmental Forensics

Environmental forensic analysis has evolved significantly from the early days of qualitative chemical fingerprint evaluations. The need for quantitative rigor has made the use of numerical methods critical in identifying and mapping contaminant sources in complex environmental systems. Given multiple contaminant sources, the environmental scientist is faced with the challenge of unraveling the contributions of multiple plumes with overlapping spatial and temporal distributions. The problem may be addressed through a multivariate statistical approach, but there is a mind-boggling array of the available “chemometric” methods. This paper provides an overview of these methods, along with a review of their advantages, disadvantages, and pitfalls. Methods discussed include principal component analysis and several receptor-modeling techniques.     

A hybrid method for inverse characterization of subsurface contaminant flux

The methods presented in this work provide a potential tool for characterizing contaminant source zones in terms of mass flux. The problem was conceptualized by considering contaminant transport through a vertical "flux plane" located between a source zone and a downgradient region where contaminant concentrations were measured. The goal was to develop a robust method capable of providing a statement of the magnitude and uncertainty associated with estimated contaminant mass flux values. In order to estimate the magnitude and transverse spatial distribution of mass flux through a plane, the problem was considered in an optimization framework. Two numerical optimization techniques were applied, simulated annealing (SA) and minimum relative entropy (MRE). The capabilities of the flux plane model and the numerical solution techniques were evaluated using data from a numerically generated test problem and a nonreactive tracer experiment performed in a three-dimensional aquifer model. Results demonstrate that SA is more robust and converges more quickly than MRE. However, SA is not capable of providing an estimate of the uncertainty associated with the simulated flux values. In contrast, MRE is not as robust as SA, but once in the neighborhood of the optimal solution, it is quite effective as a tool for inferring mass flux probability density functions, expected flux values, and confidence limits. A hybrid (SA-MRE) solution technique was developed in order to take advantage of the robust solution capabilities of SA and the uncertainty estimation capabilities of MRE. The coupled technique provided probability density functions and confidence intervals that would not have been available from an independent SA algorithm and they were obtained more efficiently than if provided by an independent MRE algorithm.     

A State of the Art Report on Industrial Precipitator Control Equipment

Informative report No. 3 has been prepared to provide background information on the origin, purpose, and general theory of operation of automatic power controls for industrial electrostatic precipitators. A comprehensive body of literature describing the process and mechanisms of dust collection in precipitators is readily available to those interested, but information on the control equipment used with the process is widely scattered. This report is intended to provide assistance toward the understanding of manufacturers’ literature describing specific control apparatus, and it may be used as a starting point for more intensive investigation of the subject. To the latter end, a history of the development of these controls and a bibliography of pertinent literature and patents has been included. It is expected that this report will be of particular interest to technical and supervisory personnel concerned with the selection, evaluation, and operation of precipitation equipment.     

Azinphos Methyl Residues in Shallow Groundwater from the Fruit Production Region of Northern Patagonia,Argentina

Groundwater samples were collected from monitoring wells along an area of intensive fruit production. Different types of correlations were investigated between soil physicochemical characteristics, depths and agricultural practices with pesticide detection frequency. In the three analyzed periods azinphos methyl, S-(3,4-diydro-4-oxobenzo[d]-[1,2,3]-triazin-3-ylmethyl)-O,O-dimethyl phosphorodithioate, showed a definite seasonal behavior related to the application pattern, increasing its concentration in the aquifer from October to November-December and then decreasing towards March. Samples obtained during the non-spraying season showed that azinphos methyl residues were lower than detection limit (LOD).

An inverse correlation was observed between azinphos methyl concentration and the time elapsed since the last pesticide application. Seasonal events such as rain and irrigation influence the chemical concentration in the well, while no correlation was obtained between soil characteristics and azinphos methyl concentration. The soil attenuation capacity was not enough to prevent the presence of azinphos methyl in the aquifer during the application season.     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.     

A PCE groundwater plume discharging to a river: influence of the streambed and near-river zone on contaminant distributions

An investigation of a tetrachloroethene (PCE) groundwater plume originating at a dry cleaning facility on a sand aquifer and discharging to a river showed that the near-river zone strongly modified the distribution, concentration, and composition of the plume prior to discharging into the surface water. The plume, streambed concentration, and hydrogeology were extensively characterized using the Waterloo profiler, mini-profiler, conventional and driveable multilevel samplers (MLS), Ground Penetrating Radar (GPR) surveys, streambed temperature mapping (to identify discharge zones), drivepoint piezometers, and soil coring and testing. The plume observed in the shallow streambed deposits was significantly different from what would have been predicted based on the characteristics of the upgradient plume. Spatial and temporal variations in the plume entering the near-river zone contributed to the complex contaminant distribution observed in the streambed where concentrations varied by factors of 100 to 5000 over lateral distances of less than 1 to 3.5 m. Low hydraulic conductivity semi-confining deposits and geological heterogeneities at depth below the streambed controlled the pattern of groundwater discharge through the streambed and influenced where the plume discharged into the river (even causing the plume to spread out over the full width of the streambed at some locations). The most important effect of the near-river zone on the plume was the extensive anaerobic biodegradation that occurred in the top 2.5 m of the streambed, even though essentially no biodegradation of the PCE plume was observed in the upgradient aquifer. Approximately 54% of the area of the plume in the streambed consisted solely of PCE transformation products, primarily cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC). High concentrations in the interstitial water of the streambed did not correspond to high groundwater-discharge zones, but instead occurred in low discharge zones and are likely sorbed or retarded remnants of past high-concentration plume discharges. The high-concentration areas (up to 5529 microg/l of total volatile organics) in the streambed are of ecological concern and represent potential adverse exposure locations for benthic and hyporheic zone aquatic life, but the effect of these exposures on the overall health of the river has yet to be determined. Even if the upgradient source of PCE is remediated and additional PCE is prevented from reaching the streambed, the high-concentration deposits in the streambed will likely take decades to hundreds of years to flush completely clean under natural conditions because these areas have low vertical groundwater flow velocities and high retardation factors. Despite high concentrations of contaminants in the streambed, PCE was detected in the surface water only rarely due to rapid dilution in the river and no cDCE or VC was detected. Neither the sampling of surface water nor the sampling of the groundwater from the aquifer immediately adjacent to the river gave an accurate indication of the high concentrations of PCE biodegradation products present in the streambed. Sampling of the interstitial water of the shallow streambed deposits is necessary to accurately characterize the nature of plumes discharging to rivers.     

Influence of indoor transport and mixing time scales on the performance of sensor systems for characterizing contaminant releases

Optimizing real-time sensor systems to detect and identify relevant characteristics of an indoor contaminant event is a challenging task. The interpretation of incoming sensor data is confounded by uncertainties in building operation, in the forces driving contaminant transport, and in the physical parameters governing transport. In addition, simulation tools used by the sensor interpretation algorithm introduce modeling uncertainties. This paper explores how the time scales inherent in contaminant transport influence the information that can be extracted from real-time sensor data. In particular, we identify three time scales (within room mixing, room-to-room transport, and removal from the building) and study how they affect the ability of a Bayesian Monte Carlo (BMC) sensor interpretation algorithm to identify the release location and release mass from a set of experimental data, recorded in a multi-floor building. The research shows that some limitations in the BMC approach do not depend on details of the models or the algorithmic implementation, but rather on the physics of contaminant transport. These inherent constraints have implications for the design of sensor systems.     

南京市污染源普查的质控工作探讨

对南京市在污染源普查过程中采取的质控措施进行了探讨,分析出普查质控工作的不足,并提出了几点建议。为提高以后普查的质量拓宽思路。     

天目湖流域农业面源污染控制研究

天目湖是溧阳市饮用水源地,近年的水质下降,与流域农业面源污染和旅游产业发展不无关系。因此,通过对农田、林地、居民居住地地表径流污染以及畜禽、水产养殖、农村生活及旅游等氮、磷污染物排放量的估算,提出农业化肥减施、种植业结构调整、农田基础设施生态改造、农村环境综合整治等控制措施。     

Comment on “Analysis of groundwater contamination using concentration-time series recorded during an integral pumping test: Bias introduced by strong concentration gradients within the plume” by Allelign Zeru and Gerhard Schäfer

We consider the results of a recent paper in this journal [Zeru, A. and Schäfer, G., 2005. Analysis of groundwater contamination using concentration–time series recorded during an integral pumping test: Bias introduced by strong concentration gradients within the plume. Journal of Contaminant Hydrology 81 (2005) 106–124], which addresses the field-scale characterisation of contaminant plumes in groundwater. There, it is concluded that contaminant concentration gradients can bias Integral Pumping Test (IPT) interpretations considerably, in particular if IPTs are conducted in advective fronts of contaminant plumes. We discuss implications of this setting and also argue that the longitudinal and transverse dispersivities used in the examples of Zeru and Schäfer (2005) of up to 30 m and 3 m, respectively, are generally very high for the here relevant capture zone scale (< 20 m). However, regardless of both longitudinal and transverse concentration gradients, we further show through a counter-example that IPT results are unbiased as long as the concentration attenuation along the flow direction is linear over the capture zone extent.     

Hydraulic constraints on the performance of a groundwater denitrification wall for nitrate removal from shallow groundwater

Denitrification walls are a practical approach for decreasing non-point source pollution of surface waters. They are constructed by digging a trench perpendicular to groundwater flow and mixing the aquifer material with organic matter, such as sawdust, which acts as a carbon source to stimulate denitrification. For efficient functioning, walls need to be permeable to groundwater flow. We examined the functioning of a denitrification wall constructed in an aquifer consisting of coarse sands. Wells were monitored for changes in nitrate concentration as groundwater passed through the wall and soil samples were taken to measure microbial parameters inside the wall. Nitrate concentrations upstream of the wall ranged from 21 to 39 g N m(-3), in the wall from 0 to 2 g N m(-3) and downstream from 19 to 44 g N m(-3). An initial groundwater flow investigation using a salt tracer dilution technique showed that the flow through the wall was less than 4% of the flow occurring in the aquifer. Natural gradient tracer tests using bromide and Rhodamine-WT confirmed groundwater bypass under the wall. Hydraulic conductivity of 0.48 m day(-1) was measured inside the wall, whereas the surrounding aquifer had a hydraulic conductivity of 65.4 m day(-1). This indicated that during construction of the wall, hydraulic conductivity of the aquifer had been greatly reduced, so that most of the groundwater flowed under rather than through the wall. Denitrification rates measured in the center of the wall ranged from 0.020 to 0.13 g N m(-3) day(-1), which did not account for the rates of nitrate removal (0.16-0.29 g N m(-3) day(-1)) calculated from monitoring of groundwater nitrate concentrations. This suggested that the rate of denitrification was greater at the upstream face of the wall than in its center where it was limited by low nitrate concentrations. While denitrification walls can be an inexpensive tool for removing nitrate from groundwater, they may not be suitable in aquifers with coarse textured subsoils where simple inexpensive construction techniques result in major decreases in hydraulic conductivity.     

规划环境影响评价指标体系及评价方法浅析

对规划环境影响评价的内容作出了概述性的介绍，并根据规划环境影响评价的特点，得出规划环境影响评价的指标体系应包括自然环境指标、生态环境指标、资源利用指标、能源利用指标和社会经济指标5大体系。列举了当前适用于规划环境影响评价的技术方法，并对其进行简单的对比分析。     

A study on the carrying capacity of the available habitat for the Rhinopithecus bieti population at Mt. Laojun in Yunnan, China

Background, aim, and scope  The Yunnan snub-nosed monkey is one of the most endangered primates in the world. It is experiencing a range of ongoing threats and the persisting effects of past disturbances. The prospects for this species are not very optimistic because habitat corridors are severely damaged by logging, grazing, and mining. Each group of the monkeys in different areas is facing a unique variety of threats. Based on genetic analysis, Rhinopithecus bieti should be separated into three management units for conservation, of which the Mt. Laojun management unit involves the most endangered primates. Despite the fact that the vegetation on Mt. Laojun is in a relatively pristine state, only two groups of monkeys, of a total of fewer than 300, survive in the area. With this paper, we aimed to address the capacity of the monkeys’ habitat at the study site and the possible reasons for the small populations. Materials and methods  Rapid ecological assessment based on a SPOT 5 image and field survey was used to simulate the vegetation of the whole area based on reference ecological factors of the GIS system. The vegetation map of the site was thus derived from this simulation. Based on the previous studies, the three vegetation types were identified as the suitable habitat of the monkeys. The confusion matrix-based field GPS points were applied to analyze the precision of the habitat map. Based on the map of suitable habitat of the monkeys, the utilization of the habitat and the carrying capacity were analyzed in the GIS. Results  The confusion matrix-based field GPS points were applied to the habitat analysis process, and it was found that the habitat map was 81.3% precise. Then, with the current habitat map, we found that the mixed forest currently used by the monkeys is only a very small fraction (2.65%) of the overall potential habitat of the population, while the dark conifer forest is 4.09%. Discussion  Poaching is the greatest short-term threat to this species, particularly in the southern range where local residents have a strong tradition of hunting. Quite a few individual monkeys are still trapped accidentally due to the high density of traps. These problems are hard to mitigate because it is difficult to enforce laws due to the extremely rugged terrain. Conclusions  The results show that there is a great ecological capacity of the area for the monkey’s survival and a great potential for an expansion of the monkey population at the site. Based on the current population and its geographical range, it can be estimated that the suitable habitat area defined by this study can support more monkeys, about many times the current population. Thus, at least in the Mt. Laojun Area, poaching pressure is the main factor to be responsible for the low density of Yunnan snub-nosed monkeys instead of habitat alteration. Recommendations and perspectives  Based on these results, some suggestions relating to conservation can be made: Focus conservation efforts on the current distribution area of the monkeys and create a 20 km buffer zone; design a long-term plan for the suitable habitat outside the buffer zone to set up a wildlife corridor in the long run; establish an association for the local hunters exploiting, their knowledge on the animals to promote monkey conservation and stop poaching. Also, the map derived from the study helps managers to allocate conservation resources more efficiently and enhances the overall outcomes of conservation measures.