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.     

Migratory crustaceans as biomonitors of metal pollution in their nursery areas. The Lesina lagoon (SE Italy) as a case study

Lichens collected in an unpolluted forest (background) in November 2004, transplanted at 41 sampling sites along the Madina-Tetteh Quarshie road, retrieved in February 2005 and analysed were found to contain higher concentrations of Manganese (Mn), Vanadium (V), lead, Cadmium (Cd), Chromium (Cr) and Nickel (Ni) than in the background area. Observations showed that of all the heavy metals studied, Manganese concentrations were highest at all sampling points with maximum values around a traffic light, an intersection and car fitting/mechanic workshops. Significant correlations were found between Ni and Mn, Mn and Cr and Mn and V. Statistical analysis also revealed a relatively even dispersion of the studied elements on the eastern side of the road than on the western side.     

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.     

Dioxin uptake by Indian plant species

Dioxins like various gaseous pollutants and aerosols can be scavenged by appropriate vegetative greenbelts. Based on their stomatal properties and the models for contaminant uptake, uptake of dioxin (2,3,7,8-TCDD) by three important Indian plant species, viz. Eugenia jambolana (Jamun), Azadirachta indica (Neem) and Ficus religiosa (Peepal), has been estimated. 2,3,7,8-TCDD is a contaminant with severe harmful ecological ramifications. Computations show that Ficus religiosa has highest uptake capacity. The present exercise has its utility in designing appropriate green-belts for mitigating adverse environmental and human health impacts due to dioxins. This can be an effective management option for mitigating the damages caused by dioxins.     

An evaluation of selenium concentrations in water, sediment, invertebrates, and fish from the Solomon River Basin

The Solomon River Basin is located in north-central Kansas in an area underlain by marine geologic shales. Selenium is an indigenous constituent of these shales and is readily leached into the surrounding groundwater. Portions of the Basin are irrigated primarily through the pumping of selenium-contaminated groundwater from wells onto fields in agricultural production. Water, sediment, macroinvertebrates, and fish were collected from various sites in the Basin in 1998 and analyzed for selenium. Selenium concentrations were analyzed spatially and temporally and compared to reported selenium toxic effect thresholds for specific ecosystem components: water, sediments, food-chain organisms, and wholebody fish. A selenium aquatic hazard assessment for the Basin was determined based on protocol established by Lemly. Throughout the Basin, water, macroinvertebrate, and whole fish samples exceeded levels suspected of causing reproductive impairment in fish. Population structures of several fish species implied that successful reproduction was occurring; however, the influence of immigration of fish from low-selenium habitats could not be discounted. Site-specific fish reproduction studies are needed to determine the true impact of selenium on fishery resources in the Basin. The U.S. Government’s right to retain a non-exclusive, royalty free license in and to any copyright is acknowledged.     

Application of GIS in the study of mass transport of pollutants by Adyar and Cooum Rivers in Chennai, Tamilnadu

Residential, industrial, commercial, institutional and recreational activities discharge degradable and non-degradable wastes that reach the coastal water through rivers and cause coastal pollution. In the present study, mass transport of pollutants by Adyar and Cooum Rivers to the coastal water as a result of land-based discharges was estimated during low tide. The lowest and the highest flow recorded in Adyar varied from 514.59 to 2,585.08×10⁶ litres/day. Similarly, the flow in Cooum River fluctuated between 266.45 and 709.34×10⁶ litres/day. The present study revealed that the Adyar River transported 53.89–454.11 t/d of suspended solids, 0.06–19.64 t/d of ammonia, 15.95–123.24 t/d of nitrate and 0.4–17.86 t/d of phosphate, 0.004–0.09 kg/d of cadmium, 0.15–1.29 kg/d of lead and 3.03–17.58 kg/d of zinc to the coastal water owing to its high discharge. Similarly, the Cooum River transported 11.87–120.06 t/d of suspended solids, 0.08–58.7 t/d of ammonia, 6.11–29.25 t/d of nitrate and 0.66–10.73 t/d of phosphate, 0.003–0.021 kg/d of cadmium, 0.02–0.44 kg/d of lead and 1.36–3.87 kg/d of zinc. A higher concentration of suspended solids was noticed in post monsoon and summer months. An increase in the mass transport of ammonia, nitrate, phosphate in summer months (April and May) and an increase in the mass transport of cadmium, lead and zinc were observed in monsoon months (October–December) in both the rivers. Thus mass transport of pollutants study reveal that Cooum and Adyar Rivers in Chennai contribute to coastal pollution by transporting inorganic and trace metals significantly through land drainage.     

Development of an integrated sensor to measure odors

Odorous air samples collected from several sources were presented to an olfactometer, an electronic nose, a hydrogen sulfide (H(2)S) detector and an ammonia (NH(3)) detector. The olfactometry measurements were used as the expected values while measurements from the other instrumentation values became input variables. Five hypotheses were established to relate the input variables and the expected values. Both linear regression and artificial neural network analyses were used to test the hypotheses. Principal component analysis was utilized to reduce the dimensionality of the electronic nose measurements from 33 to 3 without significant loss of information. The electronic nose or the H(2)S detector can individually predict odor concentration measurements with similar accuracy (R (2) = 0.46 and 0.50, respectively). Although the NH(3) detector alone has a very poor relationship with odor concentration measurements, combining the H(2)S and NH(3) detectors can predict odor concentrations more accurately (R (2) = 0.58) than either individual instrument. Data from the integration of the electronic nose, H(2)S, and NH(3) detectors produce the best prediction of odor concentrations (R (2) = 0.75). With this accuracy, odor concentration measurements can be confidently represented by integrating an electronic nose, and H(2)S and NH(3) detectors.     

Coupling upland watershed and downstream waterbody hydrodynamic and water quality models (SWAT and CE-QUAL-W2) for better water resources management in complex river basins

Effective water resources management programs have always incorporated detailed analyses of hydrological and water quality processes in the upland watershed and downstream waterbody. We have integrated two powerful hydrological and water quality models (SWAT and CE-QUAL-W2) to simulate the combined processes of water quantity and quality both in the upland watershed and downstream waterbody. Whereas the SWAT model outputs water quality variables in its entirety, the CE-QUAL-W2 model requires inputs in various pools of organic matter contents. An intermediate program was developed to extract outputs from SWAT at required subbasin and reach outlets and converts them into acceptable CE-QUAL-W2 inputs. The CE-QUAL-W2 model was later calibrated for various hydrodynamic and water quality simulations in the Cedar Creek Reservoir, TX, USA. The results indicate that the two models are compatible and can be used to assess and manage water resources in complex watersheds comprised of upland watershed and downstream waterbodies.     

Quantitative arsenic speciation in two species of earthworms from a former mine site

The relationship between the total arsenic concentration and the chemical speciation of arsenic in two species of earthworm (Lumbricus rubellus and Dendrodrilus rubidus) in relation to the host soil, was investigated for 13 sites of varying arsenic content, including a background level garden soil and a former mine site at the Devon Great Consols, UK. Earthworms were collected with the host soil (As soil concentration range 16-12, 466 mg kg(-1) dry weight) and measured for their total arsenic (concentration range 7-595 mg kg(-1) dry weight) using inductively coupled plasma mass spectrometry (ICP-MS). A methanol-water mixture was used to extract arsenic species from the earthworms prior to determination of the individual arsenic species by a combination of anion and cation exchange high performance liquid chromatography coupled to inductively coupled plasma mass spectrometry (HPLC-ICP-MS). A gradient elution anion exchange method is presented whereby nine arsenic species could be measured in one sample injection. Arsenic species were identified by comparison of retention times and sample spiking with known standards and a fully characterised seaweed extract. Arsenic was generally present in the earthworm as arsenate (As(V)) or arsenite (As(III)) and arsenobetaine (AB). Methylarsonate (MA), dimethylarsinate (DMA) and three arsenosugars (glycerol, phosphate, sulfate) were present as minor constituents. These results are discussed in relation to the mechanisms for coping with exposure to soil bound arsenic.