Screening and identification of early warning algal species for metal contamination in fresh water bodies polluted from point and non-point sources

The water bodies of Lucknow, Unnao and Kanpur (U.P.), India polluted through various point and non point sources were found to be either eutrophic or oligotrophic in nature. These water bodies supported a great number of algal diversity, which varied seasonally depending upon the physico-chemical properties of water. Further, the water bodies polluted through non point sources supports diverse algal species, while the water bodies polluted through point sources supports growth of tolerant blue green algae. High biomass producing algal species growing in these water bodies have accumulated significant amount of metals in their tissues. Maximum amount of Fe was found accumulated by species of Oedogonium sp. II (20,523.00 mug g(-1) dw) and Spirogyra sp. I (4,520.00 mug g(-1) dw), while maximum Chromium (Cr) was found accumulated in Phormedium bohneri (2,109.00 mug g(-1) dw) followed by Oscillatoria nigra (1,957.88 mug g(-1) dw) and Oedogonium sp. I (156.00 mug g(-1) dw) and Ni in Ulothrix sp. (495.00 mug g(-1) dw). Results showed that some of these forms growing in polluted environment and accumulating high amounts of toxic metals may be used as bioindicator species, however, their performance in metal contaminated water under different ecological niche is to be ascertained.     

Emission of isoprene from common Indian plant species and its implications for regional air quality

Isoprene is most dominant volatile organic compounds (VOC) emitted by many plants. In this study 40 common Indian plant species were examined for isoprene emission using dynamic flow through enclosure chamber technique. Isoprene emission rates of plants species were found to vary from undetectable to 69.5 microg g(-1) h(-1) (Madhuca latifolia). Besides, an attempt has been made to evaluate suitability of 80 common Indian plant species for planting programmes. Out of 80 species, 29 species were moderate to high emitters (10 to < or =25 microg g(-1) h(-1)), 12 species were low emitter emitters (1 to < or =10 microg g(-1) h(-1)) and remaining 39 species were found to be negligible or non emitters (<1 microg g(-1) h(-1)) of isoprene. About 50% plant species selected for planting programmes in India were found to be moderate to high emitters of isoprene.     

Assessing the Impacts of Forests on Human Welfare: Preliminary Results from the Mid-Atlantic Integrated Assessment

This paper presents results from the first phase of the socio-economic assessment of forest ecosystems in the Mid-Atlantic Integrated Assessment (MAIA). First, we present results of the analysis of changes in the distribution of human population and forest land use in the region. Then, trends in wood products employment and income between 1975–95 are used to examine the economic contributions of forest-based industries in the Mid-Atlantic region. Between 1970–90 the population of the MAIA region increased by 14% (4.3 million people) resulting in the average population density increasing by 25 people per square mile from 179 to 204 people per square mile. Nevertheless, population density was lower in large parts of the region in 1990 than in 1950. Although forests dominate the MAIA landscape, the trend is toward more people owning smaller forest land holdings, with developed lands increasing by 21% and rural lands decreasing by 2.64% between 1982–94. All of this suggests increasing forest fragmentation in all states of the region except New York, Pennsylvania, and West Virginia. Forest industry has been an important contributor to the economy of the MAIA region, producing an average of a quarter million jobs (2.03% of all wage employment) and generating $4.5 billion in wages and salaries each year between 1975–95. If recent trends continue, forest industry will continue to be an important source of employment and income for parts of some states in the MAIA region; however, the forest industry's importance relative to the entire mid-Atlantic economy will likely continue to decline in the 21^st century.     

Step-up multiple regression model to compute Chlorophyll a in the coastal waters off Cochin, southwest coast of India

The interaction effects of abiotic processes in the production of phytoplankton in a coastal marine region off Cochin are evaluated using multiple regression models. The study shows that chlorophyll production is not limited by nutrients, but their physiological regulations (responses to nutrients, pH, temperature and salinity) are mainly responsible for the increased biological production. The model explaining 77% of variability for chlorophyll a production is indicative of preconditioning of the coastal waters. The phytoplankton production is found to be sensitive to the environment, which varies seasonally. Further, the study suggests that supply of organic matter and grazing of zooplankton (not included) would improve the model efficiency. Despite this, the good agreement in the computed and measured chlorophyll a values shows that step-up multiple regression model is a useful tool to understand the influence of environmental variables on the production of phytoplankton in these coastal waters.     

The Need for Scale Sensitive Approaches in Spatially Explicit Land Use Change Modeling

This paper introduces some of the issues that are relevant to the spatially explicit modeling of land use systems. A short overview is given of the ways and means in which a number of different land use change models describe the land use system. Specific attention is given to the empirical modeling approach used in the CLUE (Conversion of Land Use and its Effects) modeling framework. This approach is demonstrated for three case studies in China, Ecuador and the Atlantic Zone of Costa Rica. These case-studies illustrate the methodology for multi-scale analysis of land use driving factors and their application in spatially explicit modeling exercises. Model functioning, performance and limitations are discussed. The presented case-studies indicate that empirical modeling results can contribute to a better theoretic imbedding of land use change research in scale sensitive and integrated theories.     

Biomonitoring of heavy metals by pollen in urban environment

Abstract Industrial development and consumption of petroleum products leads to increase air pollution levels especially in urban and industrial areas. Heavy metal components associated with air pollutants have far reaching effects with respect to economic and ecological importance of pollens. The pollens are male reproductive organs of the plant and travel through air from flower to flower for pollination purpose. During this period they are exposed to air pollutants. Present investigation thus pertains to study of effect of air pollutants on pollens especially biosorption and bioaccumulation of heavy metals. The pollens of three commonly occurring plants namely Cassia siamea, Cyperus rotundus, Kigelia pinnata have been studied from the NH-6 of Nagpur city, India. The pollens exposed to polluted air showed the presence of higher concentrations of Ca, Al and Fe as compared to unexposed pollens. Higher concentration of these metals was observed in Cyperus rotundus followed by Cassia siamea and Kigelia pinnata. These results indicate that pollens act as good indicator of air pollution giving results in short time of exposure of 5–10 h. Apart from this, it is also reported that some of these metals play crucial role in the metabolic activity in pollens for example Calcium is necessary for growth of pollen tube and other metabolic activities in pollens. The presence of these metals in pollens may also enhance the allergenicity of the pollens. Similarly accumulation of heavy metals may also deteriorate the quality of pollen for their economical use. The viability of pollen is also affected by these pollutants in sensitive species leading to impairment of their fertility.     

Whole body vibration exposure in heavy earth moving machinery operators of metalliferrous mines

As mining operations get mechanized, the rate of profit generation increases and so do the rate of occupational hazards. This study deals with one such hazard - occupational vibration. The present study was carried out to determine the whole body vibration (WBV) exposure of the heavy earth moving machinery (HEMM) operators in two types of metalliferous mines in India, when they were engaged in the mining activity. Cross-comparison was done of the vibration dose value (VDV) for HEMM operators as well as each type of mine. The VDV for the shovel operator in bauxite mine was observed to be 13.53 +/- 5.63 m/s(7/4) with 25% of the readings higher than the prescribed limit whereas in iron ore mine VDV for dumper operator was 10.81 +/- 3.44 m/s(7/4) with 14.62% readings on the higher side. Cross-comparison of the VDV values for bauxite and iron ore mines revealed that it was 9.57 +/- 4.93 and 8.21 +/- 5.12 m/s(7/4) with 21.28 and 14.95% of the readings on the higher side respectively. The Student's t test level was found to be insignificant for both type of mines, indicating that the WBV exposure is not dependent on the type of mine but is dependent on the working condition and type of HEMM in operation.     

Impact of intensive agricultural practices on drinking water quality in the EVROS Region (NE GREECE) by GIS analysis

Chemical fertilizers are used extensively in modern agriculture, in order to improve yield and productivity of agricultural products. However, nutrient leaching from agricultural soil into groundwater resources poses a major environmental and public health concern. The Evros region is one of the largest agricultural areas in Northern Greece, extending over 1.5 million acres of cultivated land. Many of its drinking water resources are of groundwater origin and lie within agricultural areas. In order to assess the impact of agricultural fertilizers on drinking water quality in this region, tap-water samples from 64 different locations were collected and analyzed for the presence of nitrates [Formula: see text], nitrites [Formula: see text], ammonium [Formula: see text], sulfate [Formula: see text] and phosphate [Formula: see text]. These chemicals were selected based on the information that ammonium nitrate, ammonium sulfate and inorganic phosphate were the primary fertilizers used in local crop production. [Formula: see text], [Formula: see text] and [Formula: see text] levels exceeding accepted values were recorded in 6.25, 4.70 and 9.38% of all sampling points, respectively. [Formula: see text] and [Formula: see text] concentrations, on the other hand, were inside the permitted range. The data generated were introduced into a geographic information system (GIS) program for computer analysis and projection maps representing afflicted areas were created. Our results indicate a profound geographic correlation in the surface distribution of primary contaminants in areas of intensified agricultural production. Thus, drinking water pollution in these areas can be attributed to excessive fertilizer use from agricultural sources.     

Heavy metal concentration in fish tissues inhabiting waters of “Buško Blato” reservoar (Bosnia and Herzegovina)

Heavy metals concentration (mercury, lead, cadmium, arsenic, copper, zinc and chromium) in tissues (muscles, liver, kidney and gonads) of Dalmatian barbelgudgeon, the nase, the souffie and brown trout, inhabiting waters of Busko Blato reservoir in Bosnia and Herzegovina, has been determined by atomic absorption spectrophotometry. The meat of the tested fish sorts does not contain elevated concentration of most analyzed heavy metals with exception of lead (higher than MAC in Italy, Germany and Denmark) and mercury (in muscles of brown trout higher than MAC in most countries). The lowest level of all heavy metals is always detected in gonads, with higher values in fry compared to milt for copper, zinc, chromium and arsenic. The highest copper concentration is observed in the liver from the souffie which is suggested as a suitable biomonitor for copper intoxication. In muscles of all fish sorts, lead was always present in much higher concentration than cadmium, while in kidneys of most fish sorts, lead and cadmium concentrations were similar. We showed that bioaccumulation of some heavy metals in the fish sorts analyzed is tissue and sex dependent. Also, we concluded that the small water exchange in reversible shallow reservoir does not induce elevated concentration of heavy metals in fish tissues inhabiting Busko Blato.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).