Improve Compliance with Limited Resources by a Three-Group Inspection Regime

Frequent monitoring and relatively high fines are usually necessary to bring about improvements in environmental quality, but more challenging for many countries with limited human, material, and financial resources is to put them into practice. This paper developed a three-group model of a state-dependent enforcement in a repeated game to improve the policy implementation under limited inspection capacities. A certain number of firms are grouped (group 1, group 2, group 3) for different supervision intensity (e.g., the order of inspection probability corresponding to each group is p ₁?<?p ₂?<?p ₃) based on their environmental performance. The optimal policy parameters, such as inspection probability of each group and the probability that a firm found in compliance is moved to a better reputation group, were obtained as the basis for regulator’s policy making. Numerical simulations indicated that the three-group inspection regime can significantly increase compliance rate as compared with static enforcement with the same monitoring probability. Among the number of firms in each group under steady state conditions, group 2 had the most, group 1 was the second, and group 3 had the smallest. Analysis and prediction of a three-group reputation example provided a good experiment for the model. The results give a practical reference for the policy makers with inspection capacity constraints to achieve higher compliance rate.     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

Regional status assessment of stony corals in the US Virgin Islands

States may protect coral reefs using biological water quality standards outlined by the Clean Water Act. This requires biological assessments with indicators sensitive to human disturbance and regional, probability-based survey designs. Stony coral condition was characterized on a regional scale for the first time in the nearshore waters of the US Virgin Islands (USVI). Coral composition, abundance, size, and health were assessed at 66 stations in the St. Croix region in fall 2007 and at 63 stations in the St. Thomas and St. John region in winter 2009. Indicators were chosen for their sensitivity to human disturbance. Both surveys were probability-based (random) designs with station locations preselected from areas covered by hardbottom and coral reef substrate. Taxa richness was as high as 21 species but more than half the area of both regions exhibited taxa richness of <10 species in the 25 m² transect area. Coral density was as high as 5 colonies m^?2 but more than half the area of both regions had <2 colonies m^?2. Both regions showed similar dominant species based on frequency of occurrence and relative abundance. Because of large colony sizes, Montastrea annularis provided more total surface area and live surface area than more abundant species. The surveys establish baseline regional conditions and provide a foundation for long-term regional monitoring envisioned by the USVI Department of Planning and Natural Resources. The probabilistic sampling design assures the data can be used in Clean Water Act reporting.     

Biomonitoring of polychlorinated biphenyls (PCBs) in heavily polluted aquatic environment in different fish species

The distribution and concentrations of polychlorinated biphenyls (PCBs) were determined in fish species (European perch Perca fluviatilis, northern pike Esox lucius, pike perch Sander lucioperca, wels catfish Silirus glanus, common carp Cyprinus carpio, European eel Anguilla anguilla, freshwater bream Abramis brama, goldfish Carassius auratus, and roach Rutilus rutilus) in a heavily polluted water reservoir Zemplínska ?írava (Slovakia). The study performed at two different time points 5?years apart (2004 and 2009) revealed serious PCB contamination of fish muscle tissue and significant interspecies as well as tissue-specific differences in PCB uptake by fish. Total PCBs broadly correlated with the trophic position of individual fish species within a food chain (P??0.05). The study has shown that the kind of fish, its feeding habit, and specific conditions of the habitat are mutually interrelated factors that are responsible for significant variations in fish body burdens. A tendency to PCB biomagnification was also proved in some fish species of this water reservoir.     

Multivariate analysis of mixed contaminants (PAHs and heavy metals) at manufactured gas plant site soils

Principal component analysis (PCA) was used to provide an overview of the distribution pattern of polycyclic aromatic hydrocarbons (PAHs) and heavy metals in former manufactured gas plant (MGP) site soils. PCA is the powerful multivariate method to identify the patterns in data and expressing their similarities and differences. Ten PAHs (naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]pyrene) and four toxic heavy metals — lead (Pb), cadmium (Cd), chromium (Cr) and zinc (Zn) — were detected in the site soils. PAH contamination was contributed equally by both low and high molecular weight PAHs. PCA was performed using the varimax rotation method in SPSS, 17.0. Two principal components accounting for 91.7% of the total variance was retained using scree test. Principle component 1 (PC1) substantially explained the dominance of PAH contamination in the MGP site soils. All PAHs, except anthracene, were positively correlated in PC1. There was a common thread in high molecular weight PAHs loadings, where the loadings were inversely proportional to the hydrophobicity and molecular weight of individual PAHs. Anthracene, which was less correlated with other individual PAHs, deviated well from the origin which can be ascribed to its lower toxicity and different origin than its isomer phenanthrene. Among the four major heavy metals studied in MGP sites, Pb, Cd and Cr were negatively correlated in PC1 but showed strong positive correlation in principle component 2 (PC2). Although metals may not have originated directly from gaswork processes, the correlation between PAHs and metals suggests that the materials used in these sites may have contributed to high concentrations of Pb, Cd, Cr and Zn. Thus, multivariate analysis helped to identify the sources of PAHs, heavy metals and their association in MGP site, and thereby better characterise the site risk, which would not be possible if one uses chemical analysis alone.     

Heavy metal pattern and solute concentration in soils along the oldest highway of the world – the AVUS Autobahn

Highways and main roads are a potential source of contamination for the surrounding environment. High traffic rates result in elevated heavy metal concentrations in road runoff, soil and water seepage, which has attracted much attention in the recent past. Nonetheless, investigations of pollutants in roadside soils are still a subject of major interest due to the rapid development of traffic systems and increasing traffic all over the world. The accumulation of the heavy metals Pb, Cd, Cu and Zn in soils along the oldest federal highway of the world has been studied by sampling a roadside transect of 125 by 10?m. In addition, heavy metal concentrations of Pb, Cd, Zn, Cu, Ni and Cr in soil solutions from different distances (2.5, 5 and 10?m) from the hard shoulder of the highway and from three soil depths (10, 30, and 50?cm) were investigated. The results show that heavy metal concentrations are up to 20 times increased compared to the geochemical background levels and a reference site of 800-m distance from the roadside. Soil matrix concentrations in the topsoil (0-10?cm) mostly exceeded the precautionary values of the German Federal Soil Protection and Contamination Ordinance (BBodSchV). The concentrations of Cd, Pb and Zn in the soil matrix tended to decrease with distance from the roadside edge, whereas the concentrations in the soil solution increased at a distance of 10?m onwards due to a lower soil pH. Because of both high pH values and a high sorption capacity of the soils, soil solution concentrations seldom exceeded the trigger values of the German Federal Soil Protection and Contamination Ordinance (BBodSchV) for transferring soil solution to groundwater.