Risk assessment and prioritisation of contaminated sites on the catchment scale

Contaminated sites pose a significant threat to groundwater resources worldwide. Due to limited available resources a risk-based prioritisation of the remediation efforts is essential. Existing risk assessment tools are unsuitable for this purpose, because they consider each contaminated site separately and on a local scale, which makes it difficult to compare the impact from different sites. Hence a modelling tool for risk assessment of contaminated sites on the catchment scale has been developed. The CatchRisk screening tool evaluates the risk associated with each site in terms of its ability to contaminate abstracted groundwater in the catchment. The tool considers both the local scale and the catchment scale. At the local scale, a flexible, site specific leaching model that can be adjusted to the actual data availability is used to estimate the mass flux over time from identified sites. At the catchment scale, a transport model that utilises the source flux and a groundwater model covering the catchment is used to estimate the transient impact on the supply well. The CatchRisk model was tested on a groundwater catchment for a waterworks north of Copenhagen, Denmark. Even though data scarcity limited the application of the model, the sites that most likely caused the observed contamination at the waterworks were identified. The method was found to be valuable as a basis for prioritising point sources according to their impact on groundwater quality. The tool can also be used as a framework for testing hypotheses on the origin of contamination in the catchment and for identification of unknown contaminant sources.     

Seasonal Variation of Toxic Benzene Emissions in Petroleum Refinery

Petroleum refineries are largest chemical industries that are responsible for the emission of several pollutants into the atmosphere. Benzene is among the most important air pollutants that are emitted by petroleum refineries, since they are involved in almost every refinery process. Volatile organic compounds (VOCs) are a major group of air pollutants, which play a critical role in atmospheric chemistry. These contribute to toxic oxidants, which are harmful to ecosystem, human health and atmosphere. The variability of pollutants is an important factor in determining human exposure to these chemicals. The ambient air concentrations of benzene were measured in several sites around the Digboi petroleum refinery, near the city of Gowahati in northeast India, during winter and summer 2004. The seasonal and spatial variations of the ambient air concentrations of this benzene were investigated and analyzed. An estimation of the contribution of the refinery to the measured atmospheric levels of benzene was also performed. The ambient air mixing ratios of benzene in a large area outside the refinery was generally low, in ppbv range, much lower than the ambient air quality standards. This article presents the temporal and spatial variation of air pollution in and around petroleum refinery and showed that no health risk due to benzene is present in the areas adjacent to the refinery.     

Factors affecting river health and its assessment over broad geographic ranges: the Western Australian experience

AusRivAS is an Australia-wide program that measures river condition using predictive models to compare the macroinvertebrate families occurring at a river site with those expected if the site were in natural condition. Results of assessment of 685 sites across all major rivers in Western Australia are presented. Most rivers were in relatively natural condition in the northern half of the state where the human population is low and pastoralism is the major land use. In the south, where the human population is higher and agriculture is more intensive, rivers were mostly more disturbed. AusRivAS assessment produced some erroneous results in rivers of the south-west cropping zone because of the lack of appropriate reference site groups and biased distribution of sampling sites. Collecting low numbers of animals from many forested streams, because of low stream productivity and samples that were difficult to sort, also affected assessments. Overall, however, AusRivAs assessment identified catchment processes that were inimical to river health. These processes included salinisation, high nutrient and organic loads, erosion and loss of riparian vegetation. River regulation, channel modification and fire were also associated with river degradation. As is the case with other assessment methods, one-off sampling at individual sites using AusRivAS may be misleading. Seasonal drought, in particular, may make it difficult to relate conditions at the time of sampling to longer-term river health. AusRivAS has shown river condition in Western Australia is not markedly different from other parts of Australia which, as a whole, lacks the substantial segments of severely degraded river systems reported in England.     

Serial Correlation and Inter-annual Variability in Relation to the Statistical Power of Monitoring Schemes to Detect Trends in Fish Populations

We studied the effects of inter-annual variability and serial correlation on the statistical power of monitoring schemes to detect trends in biomass of bream (Abramis brama) in Lake Veluwemeer (The Netherlands). In order to distinguish between 'true' system variability and sampling variability we simulated the development of the bream population, using estimates for population structure and growth, and compared the resulting inter-annual variabilities and serial correlations with those from field data. In all cases the inter-annual variability in the field data was larger than in simulated data (e.g. for total biomass of all assessed bream sigma = 0.45 in field data, and sigma = 0.03-0.14 in simulated data) indicating that sampling variability decreased statistical power for detecting trends. Moreover, sampling variability obscured the inter-annual dependency (and thus the serial correlation) of biomass, which was expected because in this long-lived population biomass changes are buffered by the many year classes present. We did find the expected serial correlation in our simulation results and concluded that good survey data of long-lived fish populations should show low sampling variability and considerable inter-annual serial correlation. Since serial correlation decreases the power for detecting trends, this means that even when sampling variability would be greatly reduced, the number of sampling years to detect a change of 15%.year(-1) in bream populations (corresponding to a halving or doubling in a six-year period) would in most cases be more than six. This would imply that the six-year reporting periods that are required by the Water Framework Directive of the European Union are too short for the existing fish monitoring schemes.     

Distribution of PAHs in Surface Soils from Petroleum Handling Facilities in Calabar

The level of concentrations of polycyclic aromatic hydrocarbons (PAHs) in surface soils from petroleum handling facilities (kerosene tank, generating plant, petrol stations, mechanic workshops, leaking pipeline and air port fuel dump) from Calabar metropolis southeastern Nigeria was determined by gas chromatography/ mass spectrometry. The results show that total polycyclic aromatic hydrocarbons (PAHs) varied from 1.80 to 334.43 mg/kg with a mean of 50.31 mg/kg. The lowest value of 1.80 mg/kg was obtained from petrol station while the highest value of 334.43 mg/kg was obtained from facility characterised by petrol stations and mechanic workshops. The ratio of phenanthrene/anthracene and fluoranthene/pyrene, varied from 0.43 to 27.72 and from 0.14 to 17.76 respectively. These ratios indicate various sources for the PAH. The two to three ring PAHs are the most abundant. Based on the PAH ratios and content alone it is not possible to distinguish between contribution from motor vehicle exhaust, gasoline spillage, used engine oil or petroleum production. However, considering the area of the study, it is very likely that the major source of soil contamination is originating from petroleum product.     

Fugitive emissions opacity determination using the digital opacity compliance system (DOCS)

Maintenance of Department of Defense (DoD) weapon systems, conducting battlefield training exercises as well as meeting military construction and/or demolition schedules, invariably generate fugitive air emissions, many of which are visible. Although there is no codified federal method for quantifying fugitive emissions opacity, many state and local air regulatory agencies have instituted enforceable fugitive emission opacity standards at DoD facilities. The current study focused on comparing the performance of the digital opacity compliance system (DOCS) with U.S. Environment Protection Agency Method 9 (Method 9) certified human observers in quantifying the visible opacity associated with fugitive emissions produced using a commercial fog generator. By systematically repositioning both DOCS cameras and Method 9-certified observers during field testing, differences in method performance as a function of observational locations were documented. At both the 30- and 300-ft off-set distances, opacity levels reported by the DOCS technology and Method 9-certified smoke readers were found to be statistically different at the 99% confidence level. Alternatively, at the 90- and 150-ft off-set distances, results suggested that there was an insignificant difference at the 99% confidence level between the two methods. Comparing the magnitude of the each method's standard deviation suggested that, at the 30-ft off-set distance, the DOCS technology was consistently more precise than Method 9-certified readers regardless of the observer's downwind distance. However, at the 90, 150, and 300-ft off-set distances, method precision seemed to vary as a function of both off-set and downwind distance. The primary factor affecting the consistency in opacity measurements appeared to be the impact of ground-level air turbulence on fog plume dispersion and transport. Field observations demonstrated that localized wind shear played a critical and decisive role in how and to what extent fugitive emissions opacity could be determined, regardless of the method selected.     

Refinery evaluation of optical imaging to locate fugitive emissions

Fugitive emissions account for approximately 50% of total hydrocarbon emissions from process plants. Federal and state regulations aiming at controlling these emissions require refineries and petrochemical plants in the United States to implement a Leak Detection and Repair Program (LDAR). The current regulatory work practice, U.S. Environment Protection Agency Method 21, requires designated components to be monitored individually at regular intervals. The annual costs of these LDAR programs in a typical refinery can exceed US$1,000,000. Previous studies have shown that a majority of controllable fugitive emissions come from a very small fraction of components. The Smart LDAR program aims to find cost-effective methods to monitor and reduce emissions from these large leakers. Optical gas imaging has been identified as one such technology that can help achieve this objective. This paper discusses a refinery evaluation of an instrument based on backscatter absorption gas imaging technology. This portable camera allows an operator to scan components more quickly and image gas leaks in real time. During the evaluation, the instrument was able to identify leaking components that were the source of 97% of the total mass emissions from leaks detected. More than 27,000 components were monitored. This was achieved in far less time than it would have taken using Method 21. In addition, the instrument was able to find leaks from components that are not required to be monitored by the current LDAR regulations. The technology principles and the parameters that affect instrument performance are also discussed in the paper.     

Pesticide Residues in Bovine Milk from a Predominantly Agricultural State of Haryana, India

One hundred forty seven samples of bovine milk were collected from 14 districts of Haryana, India during December 1998–February 1999 and analysed for the presence of organochlorine pesticide (OCPs) residues. ∑HCH, ∑DDT, ∑endosulfan and aldrin were detected in 100%, 97%, 43% and 12% samples and with mean values of 0.0292, 0.0367, 0.0022 and 0.0036 μg/ml, respectively. Eight percent samples exceeded the maximum residue limit (MRL) of 0.10 mg/kg as recommended by WHO for ∑HCH, 4% samples of 0.05 mg/kg for α-HCH, 5% samples of 0.01 mg/kg for γ-HCH, 26% samples of 0.02 mg/kg for β-HCH as recommended by PFAA and 24% samples of 0.05 mg/kg as recommended by FAO for ∑DDT. Concentrations of β-HCH and p,p′-DDE were more as compared to other isomers and metabolites of HCH and DDT.     

Relation of waste generation and composition to socio-economic factors: a case study

To develop an effective waste management strategy for a given region, it is important to know the amount of waste generated and the composition of the waste stream. Past research has shown that the amount of waste generated is proportional to the population and the average mean living standards or the average income of the people. In addition, other factors may affect the amount and composition of waste. These are climate, living habits, level of education, religious and cultural beliefs, and social and public attitudes. This paper presents the findings of a study carried out in a suburban municipal area in Sri Lanka to determine the solid waste generation rate and waste composition based on field surveys and to determine the related socio-economic factors. A database was developed that included information on the quantity and composition of waste generated in a sample of households in the study area over a time period. The collected data was analysed to relate waste generation and composition data to various socio-economic factors. Over 400 sample households were selected for the study using a stratified random sampling methodology based on municipal wards and property values. A technique that considers both the number of households in a particular income group (property value range) and the standard deviation of property values within a given income group was used to determine the appropriate sample size for each municipal ward. Through category and regression analyses, the quantities of waste and waste composition were related to several socio-economic factors. The paper describes the basis for the sample selection, the methodology adopted for data collection, the socio-economic parameters used for the analysis, and the relationships developed from the analysis.