Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

Metal Pollution Assessment of Sediment and Water in the River Hindon, India

The metal pollution in water and sediment of the River Hindon in western Uttar Pradesh (India) was assessed for Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn. The metal concentrations in water showed wide temporal variation compared with bed sediment because of variability in water discharge and variations in suspended solid loadings. Metal concentrations in bed sediments provided a better evaluation of the degree and the extent of contamination in the aquatic environment, Santagarh and Atali being the most polluted sites of the river. The ratio of heavy metals to conservative elements (Fe, Al, etc.) may reveal the geochemical imbalances due to the elevated metal concentrations normally attributed to anthropogenic sources. Metal/Al ratios for the bed sediments of the river Hindon were used to determine the relative mobility and general trend of relative mobility occurred Fe > Mn > Zn > Cr > Ni > Pb > Cu > Cd.     

Application of a systemic approach to the study of pollution of the Tinto and Odiel rivers (Spain)

The province of Huelva in the SW of Spain presents high environmental contrasts: together with the great abundance of natural spaces, it shows the impacts of historical natural resources exploitation processes. In the Ria of Huelva, the effluents of the chemical industries must be added to the contaminating inputs of the Tinto and Odiel rivers, coming from the acid drainage of the mines located in the Iberian Pyrite Belt. This forced the Environmental Agency (AMA) to elaborate in 1987 an Effluent Remediation Plan in order to negate unacceptable environmental impacts. The application of a grey box systemic analysis to the AMD pollution, undergone by the Tinto and Odiel rivers has allowed to set a conclusive explanation of the sampling results observed for a period of 11 years, thus making available an overall view of the polluting process and, above all, an explanation of its partial aspects.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Air Pollution and Heat Exposure Study in the Workplace in a Glass Manufacturing Unit in India

Air pollution in the workplace environment due to industrial operation have been found to cause serious occupational health hazard. Similarly, heat stress is still most neglected occupational hazard in the tropical and subtropical countries like India. The hot climate augments the heat exposure close to sources like furnaces. In this study an attempt is made to assess air pollution and heat exposure levels to workers in the workplace environment in glass manufacturing unit located in the State of Gujarat, India. Samples for workplace air quality were collected for SPM, SO₂, NO₂ and CO₂ at eight locations. Results of workplace air quality showed 8-hourly average concentrations of SPM: 165–9118 μg/m³, SO₂: 6–9 μg/m³ and NO₂: 5–42 μg/m³, which were below the threshold limit values of workplace environment. The level of CO₂ in workplace air of the plant was found to be in the range 827–2886 μg/m³, which was below TLV but much higher than the normal concentration for CO₂ in the air (585 mg/m³). Indoor heat exposure was studied near the furnace and at various locations in an industrial complex for glass manufacturing. The heat exposure parameters including the air temperature, the wet bulb temperature, and the globe parameters were measured. The Wet Bulb Globe Temperature (WBGT), an indicator of heat, exceeded ACGIH TLVs limits most of the time at all the locations in workplace areas. The recommended duration of work and rest have also been estimated.     

Flow-injection analysis with fluorescence detection for the determination of trace levels of ammonium in seawater

A method using flow-injection, gas-diffusion, derivatisation and then fluorescent detection has been established for ammonium ion determination in seawater. The fluorescent derivative formed by reacting ortho-phthaldialdehyde (OPA) and sulfite with ammonia gives high sensitivity while removing potential interferences. This is required to measure the low concentrations of ammonium often seen in the open ocean. The experimental conditions (flow-rate, reagent concentrations, membrane configurations, etc.) were manipulated to improve performance. For a sample throughput of 30 samples h(-1), the limit of detection was 7 nM, the coefficient of variation was 5.7% at 800 nM, and the calibration curve was linear to at least 4 micromol L(-1). Interferences were minimised by a gaseous diffusion step. Volatile small molecular-weight amines as interferents were discriminated against by this method. They neither passed through the membrane as efficiently as ammonia, nor reacted as readily with OPA when sulfite was the reductant. Contamination by ammonia from laboratory and shipboard sources complicates application of the method to natural waters, especially measurement of low concentrations (<100 nM) in open-ocean waters. Steps to overcome contamination are described in detail. Some results are presented for ammonium determination in Southern Ocean and Huon Estuary (Tasmania) waters.     

Microbial population dynamics at effluent treatment plants

The requirements for treated wastewater are becoming increasingly more stringent, and therefore the improved efficiency of biological treatment processes is indispensable at industrial effluent treatment plants (ETPs). Microorganisms such as bacteria play an important role in the natural cycling of materials and particularly in the decomposition of organic wastes. The knowledge of the interactions among these microbial populations needs to be harnessed for optimum evaluation and functioning of effluent treatment plants. Modern molecular techniques have revolutionized the methods of assessing these microbial populations. The combination of the results of these microbial assessments along with the on-site parameters at ETPs would favor an efficient treatment. In this review, the various approaches and importance of correlating the microbial population dynamics and treatment of wastewater at industrial ETPs has been elaborated.