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 probability model for evaluating building contamination from an environmental event

Asbestos dust and bioaerosol sampling data from suspected contaminated zones in buildings allowed development of an environmental data evaluation protocol based on the differences in frequency of detection of a target contaminant between zones of comparison. Under the assumption that the two test zones of comparison are similar, application of population proportion probability calculates the significance of observed differences in contaminant levels. This was used to determine whether levels of asbestos dust contamination detected after a fire were likely the result of smoke-borne contamination, or were caused by pre-existing/background conditions. Bioaerosol sampling from several sites was also used to develop the population proportion probability protocol. In this case, significant differences in indoor air contamination relative to the ambient conditions were identified that were consistent with the visual observations of contamination. Implicit in this type of probability analysis is a definition of "contamination" based on significant differences in contaminant levels relative to a control zone. Detection of a suspect contaminant can be assessed as to possible sources(s) as well as the contribution made by pre-existing (i.e., background) conditions, provided the test and control zones are subjected to the same sampling and analytical methods.     

APCA Honors Six Individuals and Three Sections In 1987 Awards Program

Abstract

A growing interest in security and occupant exposure to contaminants revealed a need for fast and reliable identification of contaminant sources during incidental situations. To determine potential contaminant source positions in outdoor environments, current state-of-the-art modeling methods use computational ?uid dynamic simulations on parallel processors. In indoor environments, current tools match accidental contaminant distributions with cases from precomputed databases of possible concentration distributions. These methods require intensive computations in pre- and postprocessing. On the other hand, neural networks emerged as a tool for rapid concentration forecasting of outdoor environmental contaminants such as nitrogen oxides or sulfur dioxide. All of these modeling methods depend on the type of sensors used for real-time measurements of contaminant concentrations. A review of the existing sensor technologies revealed that no perfect sensor exists, but intensity of work in this area provides promising results in the near future. The main goal of the presented research study was to extend neural network modeling from the outdoor to the indoor identification of source positions, making this technology applicable to building indoor environments. The developed neural network Locator of Contaminant Sources was also used to optimize number and allocation of contaminant concentration sensors for real-time prediction of indoor contaminant source positions. Such prediction should take place within seconds after receiving real-time contaminant concentration sensor data. For the purpose of neural network training, a multizone program provided distributions of contaminant concentrations for known source positions throughout a test building. Trained networks had an output indicating contaminant source positions based on measured concentrations in different building zones. A validation case based on a real building layout and experimental data demonstrated the ability of this method to identify contaminant source positions. Future research intentions are focused on integration with real sensor networks and model improvements for much more complicated contamination scenarios.     

A Probability Model for Evaluating Building Contamination from an Environmental Event

ABSTRACT

Asbestos dust and bioaerosol sampling data from suspected contaminated zones in buildings allowed development of an environmental data evaluation protocol based on the differences in frequency of detection of a target contaminant between zones of comparison. Under the assumption that the two test zones of comparison are similar, application of population proportion probability calculates the significance of observed differences in contaminant levels. This was used to determine whether levels of asbestos dust contamination detected after a fire were likely the result of smoke-borne contamination, or were caused by pre-existing/background conditions.

Bioaerosol sampling from several sites was also used to develop the population proportion probability protocol. In this case, significant differences in indoor air contamination relative to the ambient conditions were identified that were consistent with the visual observations of contamination. Implicit in this type of probability analysis is a definition of “contamination” based on significant differences in contaminant levels relative to a control zone. Detection of a suspect contaminant can be assessed as to possible sources(s) as well as the contribution made by pre-existing (i.e., background) conditions, provided the test and control zones are subjected to the same sampling and analytical methods.     

Metal stress consequences on frost hardiness of plants at northern high latitudes: a review and hypothesis

Since sewage discharges can significantly contribute to the contaminant loadings in coastal areas, it is important to identify sources, pathways and environmental sinks. Sterol and fatty alcohol biomarkers were quantified in source materials, suspended sediments and settling matter from the Ria Formosa Lagoon. Simple ratios between key biomarkers including 5beta-coprostanol, cholesterol and epi-coprostanol were able to identify the sewage sources and effected deposition sites. Multivariate methods (PCA) were used to identify co-varying sites. PLS analysis using the sewage discharge as the signature indicated approximately 25% of the variance in the sites could be predicted by the sewage signature. A new source of sewage derived organic matter was found with a high sewage predictable signature. The suspended sediments had relatively low sewage signatures as the material was diluted with other organic matter from in situ production. From a management viewpoint, PLS provides a useful tool in identifying the pathways and accumulation sites for such contaminants.     

Use of principal component analysis to profile temporal and spatial variations of chlorinated solvent concentration in groundwater

This work aims at evaluating spatial distribution patterns of concentration variations for chlorinated solvents in groundwater, based on principal component analysis and geographic information system (GIS) tools. The study investigates long-time series of chlorinated solvent concentrations in groundwater measured for 18 contaminated industrial sites. The characterization of contaminant plumes and delineation of pollutant sources are essential for choosing appropriate monitoring and remediation strategies, as contaminated groundwaters are characterized by complex patterns of spatial and temporal concentration variability, with wide unpredictable fluctuations over time. The present work describes the results of a new exploratory statistical method called the Variability Index Method (VIM) applied to environmental data to assess the performance of using concentration variations as molecular tracers to reveal aquifer dynamics, industrial impacts, and point sources for contamination plumes. The application of this method provides a useful assessment of controls over contaminant concentration variations as well as support for remediation techniques.     

Assessing the impact of source-zone remediation efforts at the contaminant-plume scale through analysis of contaminant mass discharge

The long-term impact of source-zone remediation efforts was assessed for a large site contaminated by trichloroethene. The impact of the remediation efforts (soil vapor extraction and in-situ chemical oxidation) was assessed through analysis of plume-scale contaminant mass discharge, which was measured using a high-resolution data set obtained from 23 years of operation of a large pump-and-treat system. The initial contaminant mass discharge peaked at approximately 7kg/d, and then declined to approximately 2kg/d. This latter value was sustained for several years prior to the initiation of source-zone remediation efforts. The contaminant mass discharge in 2010, measured several years after completion of the two source-zone remediation actions, was approximately 0.2kg/d, which is ten times lower than the value prior to source-zone remediation. The time-continuous contaminant mass discharge data can be used to evaluate the impact of the source-zone remediation efforts on reducing the time required to operate the pump-and-treat system, and to estimate the cost savings associated with the decreased operational period. While significant reductions have been achieved, it is evident that the remediation efforts have not completely eliminated contaminant mass discharge and associated risk. Remaining contaminant mass contributing to the current mass discharge is hypothesized to comprise poorly accessible mass in the source zones, as well as aqueous (and sorbed) mass present in the extensive lower-permeability units located within and adjacent to the contaminant plume. The fate of these sources is an issue of critical import to the remediation of chlorinated-solvent contaminated sites, and development of methods to address these sources will be required to achieve successful long-term management of such sites and to ultimately transition them to closure.     

Trends in spatial and temporal levels of persistent organic pollutants in Lake Erie sediments

A Lake Erie sediment survey was conducted in 1997 to characterize spatial trends in contamination, and for comparison with a 1971 survey to assess any changes in environmental quality since the advent of measures to reduce contaminant sources. Contaminant data for some contaminant classes in 1971 was based on analysis of frozen archived samples, thereby allowing a direct comparison between surficial sediment contamination in 1971 and 1997 based on modern analytical methods. Lake-wide contaminant concentrations of polychlorinated biphenyls (PCBs) and organochlorine compounds including hexachlorobenzene and the DDT compounds in 1997 were substantially lower, compared to levels in samples collected in 1971. Lake-wide average sediment PCB levels were found to have decreased roughly 70% from 136 ng/g in 1971 to 43 ng/g in 1997. Similarly, reductions in other compound classes ranged from 40% to 80%. In 1997, some individual contaminants classes including PCBs exhibited a spatial trend toward increasing sediment contamination from the eastern basin to the western basin, and from the north-central basin to the south-central basin. Levels of organic contaminants in sediments in some areas of Lake Erie still exceeded the strictest Canadian Federal and Ontario Provincial guidelines. However, exceedances of guidelines describing contaminated environments in 1997 were predominantly restricted to the western basin and near-shore sites in the southern part of the central basin.     

A dynamic contaminant transport computational architecture (DCTCA) for radiological assessment of ecological systems

A novel methodology called dynamic contaminant transport computational architecture (DCTCA) is developed to help flexibility of constructing process structure for radiological assessment of ecological systems. The method tracks radionuclide movements in ecological systems by doing calculations on vectors and matrices. All environmental components in an ecosystem are both sources and receptors as they are media that pass radionuclides. The transport factor matrix is the transformation matrix from sources to receptors. The cubic transport model base (CTMB) in the architecture allows a number of transport models to be selected and applied to a single source-receptor transport process. CTMB stores those models in a cubic structure and has them available to be selected and form a combined model set to be used in scenarios.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Application of Forensic Techniques for Age Dating and Source Identification in Environmental Litigation

A multitude of forensic techniques are available for age dating and source identification, including corrosion models for underground storage tanks, the commercial availability of a compound, chemical associations with discrete types of manufacturing processes, chemical profiling, proprietary additives, stable isotope analysis, degradation models, biomarkers and contaminant transport models. The selection and use of these techniques in environmental litigation must be thoroughly understood and applied to be effective as forensic evidence. When introduced as scientific evidence, the governing assumptions and quality of the data are critically evaluated and frequently successfully challenged. The purpose of this paper is to present an overview of commonly used environmental forensic techniques and their possible applications so that a user can decide which technique or combination of methods is most appropriate for their case.     

An inverse Gaussian plume approach for estimating atmospheric pollutant emissions from multiple point sources

A method is developed for estimating the emission rates of contaminants into the atmosphere from multiple point sources using measurements of particulate material deposited at ground level. The approach is based on a Gaussian plume type solution for the advection–diffusion equation with ground-level deposition and given emission sources. This solution to the forward problem is incorporated into an inverse algorithm for estimating the emission rates by means of a linear least squares approach. The results are validated using measured deposition and meteorological data from a large lead–zinc smelting operation in Trail, British Columbia. The algorithm is demonstrated to be robust and capable of generating reasonably accurate estimates of total contaminant emissions over the relatively short distances of interest in this study.     

Investigation,Remediation and Cost Allocation of Contaminants from the Britannia Mine in British Columbia: A Case Study

This case study, from the province of British Columbia, is described to illustrate the use of environmental forensic techniques. The study involves acid rock drainage (ARD) from the Britannia Mine, a mine located in southwestern British Columbia, that has been closed for approximately 25 years and discharges between 4 and 40 million litres of ARD, depending on the time of year into nearby Howe Sound every day. The ARD occurs as an oxidation of sulphide mineralization exposed to air and water. The sources of ARD contamination from this site are copper, aluminium, iron, zinc and manganese. Current copper concentrations discharging from the 4100 Portal Level range from 40 to 100 mg/L. Environmental forensic techniques are applied to describe the origin of the contaminant release, the timing of the release, the distribution of the contamination, finding the responsible parties and allocating remediation costs for cleanup. Other forensic techniques described include the use of geochemistry to determine contaminant degradation.     

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.     

Large-scale spatial variation in mercury concentrations in cattle in NW Spain

Mercury (Hg) is a highly toxic environmental contaminant and man-made emissions account for between a quarter and a third of total atmospheric levels. Point discharges, particularly coal-burning power stations, are major sources of atmospheric Hg and can result in marked spatial variation in mercury deposition and subsequent uptake by biota. The aims of this study were to quantify the extent to which major point and diffuse sources of atmospheric Hg emissions affected accumulation of Hg by biota throughout Galicia and Asturias, two of the major regions in northwest Spain. We did this by relating renal Hg concentrations in locally reared cattle (n=284) to the proximity of animals to point and diffuse sources of Hg emissions. Mercury residues in calf kidneys ranged between non-detected and 89.4 g/kg wet weight. Point discharges from coal-fired power plants in Galicia had the most dominant impact on Hg accumulation by calves in Galicia, affecting animals throughout the region and explaining some two-thirds of the variation in renal residues between animals located directly downwind from the plants. The effects of more diffuse emission sources on Hg accumulation in calves were not distinguishable in Galicia but were detected in cattle from neighbouring Asturias. The impact of both point and diffuse sources in elevating environmental levels of bioavailable Hg and subsequent accumulation by cattle extended to approximately 140-200 km downwind from source.     

A regional flux-based risk assessment approach for multiple contaminated sites on groundwater bodies

In the context of the Water Framework Directive (EP and CEU, 2000), management plans have to be set up to monitor and to maintain water quality in groundwater bodies in the EU. In heavily industrialized and urbanized areas, the cumulative effect of multiple contaminant sources is likely and has to be evaluated. In order to propose adequate measures, the calculated risk should be based on criteria reflecting the risk of groundwater quality deterioration, in a cumulative manner and at the scale of the entire groundwater body. An integrated GIS- and flux-based risk assessment approach for groundwater bodies is described, with a regional scale indicator for evaluating the quality status of the groundwater body. It is based on the SEQ-ESO currently used in the Walloon Region of Belgium which defines, for different water uses and for a detailed list of groundwater contaminants, a set of threshold values reflecting the levels of water quality and degradation with respect to each contaminant. The methodology is illustrated with first results at a regional scale on a groundwater body-scale application to a contaminated alluvial aquifer which has been classified to be at risk of not reaching a good quality status by 2015. These first results show that contaminants resulting from old industrial activities in that area are likely to contribute significantly to the degradation of groundwater quality. However, further investigations are required on the evaluation of the actual polluting pressures before any definitive conclusion be established.     

MTBE Transport Screening Analysis in Vadose Zone Risk and Liability Apportionment Assessment

The problem of allocating liability cleanup costs is an arduous task when more than one potentially responsible party has contributed to the groundwater plume. This problem is most likely to be encountered when dealing with methyl-tert -butyl-ether (MTBE) contamination, as MTBE is seen to travel large distances in underlying aquifers. There has been a significant effort in the recent past to develop liability allocation methodologies that incorporate fate and transport behavior and toxicological characteristics of the contaminants. The application of such methods often requires estimation of contaminant input from the vadose zone into the underlying aquifer. A screening level analysis is presented here to develop preliminary insights on relative mass contributions arising from different source types. The analysis illustrates how different vadose zone conceptualizations lead to vastly different contaminant loadings. Parametric studies indicate that the contaminant flux into the aquifer is very sensitive to changes in water infiltration rates. Hence, a reliable estimate of this parameter is critical for equitable allocation of remedial costs. Conceptual model formulation, should focus on identifying whether the fuel present in the aquifer can flow as a separate phase. It is also important to obtain reliable estimates for fluid saturations at the site.