Impact of distillery effluent application to land on soil microflora

A pot culture experiment was conducted to evaluate the effect of different treatments of distillery wastewater, i.e. raw, treated, diluted and raw distillery wastewater mixed with domestic waste stabilization pond effluent (1:1) on populations of bacteria, fungi, actinomycetes and nitrogen fixing bacteria. The results indicated that raw wastewater decreased the population of bacteria, fungi and actinomycetes. The growth rates of Rhizobium and Azotobacter were also reduced after raw wastewater application. The toxic effect of raw wastewater was minimized when it was mixed with stabilization pond effluent (1:1), this was demonstrated by an increase in the populations of all the microorganisms studied. When a groundnut plant was irrigated with raw distillery wastewater, no fruits were produced and there was also less nodulation. This study indicates that raw distillery wastewater is very toxic to the soil microorganisms which are important in the soil ecosystem.     

Development of an ombrotrophic peat bog (low ash) reference material for the determination of elemental concentrations

Given the increasing interest in using peat bogs as archives of atmospheric metal deposition, the lack of validated sample preparation methods and suitable certified reference materials has hindered not only the quality assurance of the generated analytical data but also the interpretation and comparison of peat core metal profiles from different laboratories in the international community. Reference materials play an important role in the evaluation of the accuracy of analytical results and are essential parts of good laboratory practice. An ombrotrophic peat bog reference material has been developed by 14 laboratories from nine countries in an inter-laboratory comparison between February and October 2002. The material has been characterised for both acid-extractable and total concentrations of a range of elements, including Al, As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Mn, Na, Ni, P, Pb, Ti, V and Zn. The steps involved in the production of the reference material (i.e. collection and preparation, homogeneity and stability studies, and certification) are described in detail.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Benchmarking for best practice environmental management

Benchmarking of environmental performance to demonstrate theachievement of best practice environmental management is acomponent of a new form of licensing of industrialdischarges in Western Australia. The paper describes theapproaches to benchmarking for the critical environmentalissues for an alumina refinery and wastewater treatmentplant. It also describes the lessons learnt from thebenchmarking process on appropriate methods, the benefitsand difficulties in the benchmarking process, and changesthat would assist benchmarking for best practiceenvironmental management.     

Monitoring of Butter and Ghee (Clarified Butter Fat) for Pesticidal Contamination from Cotton Belt of Haryana, India

Butter (45) and ghee (55) samples were collected from rural and urban areas of cotton growing belt of Haryana and analysed for detecting the residues of organochlorine, synthetic pyrethroid and organophosphate insecticides. The estimation was carried out by using multi residue analytical technique employing GC-ECD and GC-NPD systems equipped with capillary columns. Butter samples were comparatively more contaminated (97%) than ghee (94%), showing more contamination with organochlorine insecticides from urban samples. About 11% samples of butter showed endosulfan residues above MRL value and 2% samples had residues of synthetic pyrethroids and organophosphates each above their respective MRL values. In ghee, residues of HCH & DDT both and of endosulfan exceeded the MRL values in 5 and 20% samples, respectively. Among organophosphates, only chlorpyriphos was detected with 9% samples showing its residue above MRL value. Irrespective of contamination levels, residues above the MRL values were more in ghee. More extensive study covering other agricultural regions/zones of Haryana has been suggested to know the overall scenario of contamination of milk products.     

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.     

Examples of the role of analytical chemistry in environmental risk management research

Analytical chemistry is an important tier of environmental protection and has been traditionally linked to compliance and/or exposure monitoring activities for environmental contaminants. The adoption of the risk management paradigm has led to special challenges for analytical chemistry applied to environmental risk analysis. Namely, methods developed for regulated contaminants may not be appropriate and/or applicable to risk management scenarios. This paper contains examples of analytical chemistry applied to risk management challenges broken down by the analytical approach and analyte for some selected work in our laboratory. Specific techniques discussed include stable association complex electrospray mass spectrometry (cESI-MS), gas chromatography-mass spectrometry (GC-MS), split-flow thin cell (SPLITT) fractionation and matrix-assisted laser desorption time of flight mass spectrometry (MALDI-ToF-MS). Specific analytes include haloacetic acids (HAA9), perchlorate, bromate, triazine degradation products, metal-contaminated colloids and Cryptosporidium parvum oocysts.     

Response of the Ascorbate-Peroxidase of Selenastrum capricornutum to Copper and Lead in Stormwaters

The green alga Selenastrum capricornutum expresses a uniqueascorbate peroxidase, that responds to copper and lead. Attemptswere made to test if this peroxidase could be used to monitor thelevels of copper and lead in natural waters. When S.capricornutum was exposed to a stormwater sample, the specificactivity of the peroxidase in the cell extract was commensuratewith the combined copper and lead contents in the sample. Theperoxidase responses were also correlated with the 96 hr biomasstoxicity assay of S. capricornutum. However, unlike thebiomass toxicity assay, the peroxidase activity was not affectedby the anions in the samples. The use of this peroxidase can beused as a marker for testing heavy metal toxicity in the water.     

Luminescence spectroscopy as a screening tool for the potential carcinogenicity of asphalt fumes

A subset of polycyclic aromatic compounds (PACs), which contain 4-6 annulated rings, has been documented as the source of carcinogenicity in animal skin painting studies of petroleum products and asphalt fumes (M. L. Machado, P. W. Beatty, J. C. Fetzer, A. H. Glickman and E. L. McGinnis, Fundam. Appl. Toxicol., 1993, 21, 492; T. A. Roy, S. W. Johnson, G. R. Blackburn and C. R. Mackerer, Fundam. Appl. Toxicol., 1988, 10, 466). Because of the chemical complexity of these materials, it has been difficult to identify the specific compounds within this broad range of PACs responsible for their carcinogenicity. An alternative approach using luminescence spectroscopy was taken in this study to quantify, without identification, a subset of these compounds that appears to cause cancer. The fluorescence response at a specific wavelength pair was obtained for 39 laboratory asphalt fume condensates from animal skin painting studies, yielding a linear correlation coefficient of R2 = 0.96 between the fluorescence response in these materials and the carcinogenicity found in animal studies. In the absence of other asphalt fume condensates from animal studies, 17 petroleum oils were also evaluated using this method and compared with the available animal skin painting data. The details of the method include a clean-up step that removes the highly polar compounds and spectral subtraction of two- and three-ring PAC interference, both of which add to the fluorescence response, yet were not found to contribute to a carcinogenic response from skin painting studies. Full scan fluorescence plots also produce a fingerprint which can be used to assess contamination, such as coal tar products or mixtures of materials, that are not defined as asphalt, yet may be present in the working environment.