Heavy metal contamination in the Delhi segment of Yamuna basin

Concentration of heavy metals (Cd, Ni, Zn, Fe, Cu, Mn, Pb, Cr, Hg and As) in the waters of River Yamuna and in the soil of agricultural fields along its course in Delhi are reported from 13 sites, spread through the Delhi stretch of Yamuna, starting from the Wazirabad barrage till the Okhla barrage. Varying concentration of heavy metals was found. Peaks were observed in samples collected downstream of Wazirabad and Okhla barrage, indicating the anthropogenic nature of the contamination. The Wazirabad section of the river receives wastewater from Najafgarh and its supplementary drains, whereas the Shahdara drain releases its pollution load upstream of the Okhla barrage. Average heavy metal concentration at different locations in the river water varied in the order of Fe>Cr>Mn>Zn>Pb>Cu>Ni>Hg>As>Cd. The river basin soil shows higher level of contamination with lesser variation than the water samples among sampling locations, thereby suggesting deposition over long periods of time through the processes of adsorption and absorption. The average heavy metal concentration at different locations in soil varied in the order of Fe>Mn>Zn>Cr>Pb>Ni>Hg>Cu>As>Cd.     

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.     

Changing environment and urban identity following open-cast mining and thermic power plant in Turkey: case of Soma

This paper is a summary of a project changed into a book named by “Changing Environment, City and Identity in Soma with the Geographical Evaluations” issued on May 2005. In this research, Soma, which is one of the most remarkable districts in Manisa in the West Anatolia from the point of economical figures, is assessed with its physical environment potential, improving economical activities and changing socio-economical structure. Owing to the open coal basins in the northeast and southwest of the district where lignite is produced and the impact of the thermic power plant near the city centre, Soma has changed on a large scale. This change has introduced some environmental problems into the district such as the devastation of the forestry land; the infertility of farming land; and soil, water and air pollution. Even though the change under discussion has led to many problems to deal with, it has also influenced its socio-economical structure to a large extent and revealed new type of inhabitants having different life expectations and aims. In conclusion, in this article, changing environment and city structure after lignite processing and thermic station establishment in Soma are discussed through the effective geographical factors. The new city profile formed by the local dynamics in question is evaluated according to the data obtained by the studies made in the neighbourhood.     

Chemical forms and ecological risk of arsenic in the sediment of the Daliao River System in China

The chemical forms and ecological risk of As were characterized in the sediment of the Daliao River System (DRS), which has been affected by long-term intensive industrial, urban, and agricultural activities. Twenty-seven samples of surface sediment were collected and analyzed for total As content and that of its chemical forms. The results indicated that the average total As content in the sediment was 9.83 mg kg^− 1 but that the levels ranged from 1.57 to 83.09 mg kg^− 1. At the sites near cities, mining sites, and the estuary of the DRS, it is likely that adverse effects on aquatic organisms occur, due to As levels in the sediment that are often higher than the threshold effect level and occasionally higher than the probable effect level. A selectively sequential extraction indicated that the majority of As in the sediment was bound to Fe oxides (62.1%), with moderate proportions of residual As (19.8%), specifically adsorbed As (17.9%), and a low proportion of non-specifically adsorbed As (1.1%). In addition, the content of Fe in the sediment was positively and significantly correlated with the contents of amorphous and crystalline Fe oxide-bound As, confirming the crucial role of Fe oxides in immobilizing high amounts of As in superficial environments. The average molar ratio of As to Fe was 1.18 × 10^− 4 in the surface sediment of the DRS, similar to that of natural Fe oxides, but much lower than that of synthesized Schwertmannite. Therefore, the release of As under reduced and low pH conditions can cause serious problems for water resources and for living organisms.     

Seagrass resource assessment using remote sensing methods in St. Joseph Sound and Clearwater Harbor,Florida, USA

In the event of a natural or anthropogenic disturbance, environmental resource managers require a reliable tool to quickly assess the spatial extent of potential damage to the seagrass resource. The temporal availability of the Landsat 5 Thematic Mapper (TM) imagery provided a suitable option to detect and assess damage of the submerged aquatic vegetation (SAV). This study examined Landsat TM imagery classification techniques to create two-class (SAV presence/absence) and three-class (SAV estimated coverage) SAV maps of the seagrass resource. The Mahalanobis Distance method achieved the highest overall accuracy (86%) and validation accuracy (68%) for delineating the seagrass resource (two-class SAV map). The Maximum Likelihood method achieved the highest overall accuracy (74%) and validation accuracy (70%) for delineating the seagrass resource three-class SAV map. The Landsat 5 TM imagery classification provided a seagrass resource map product with similar accuracy to the aerial photointerpretation maps (validation accuracy 71%). The results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource.     

Assessment of sediment quality in the Mediterranean Sea–Boughrara lagoon exchange areas (southeastern Tunisia): GIS approach-based chemometric methods

Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea–Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I _geo) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments.     

Socio-economic features of commercial fishery in the bordering upper Danube River area of Serbia

The multidisciplinary socio-economic study of fisheries in the bordering part of the Danube River between Serbia and Croatia (at the following sites: Apatin, Ba?ka Palanka, Ba?ko Novo Selo, Bezdan, and Sombor) that was performed in order to investigate various aspects of fish resource utilization (management, policy of protection and exploitation of freshwater fishery resources, present fisheries legislation, catch statistics), was realized during 2004 and 2005. Data were collected via survey with a structured interview. Socio-economic circumstances, together with ecological factors, have had an influence on the fish stock and number of commercial fishermen. Awareness of the occurring problems, both economic and ecological ones, is apparent, regardless of whether it is assessed in the field of commercial or recreational fishing. Fishery sector in Serbia is in a prolonged process of transition, with the enforcement of fishing regulations, but also the lack of control that leaves space for illegal commercial fishing. The statements, consciousness, experience and behavior of commercial fishermen represent a good basis for planning the sustainable development of fishing in this section of the Danube River.     

Occurrence and characterization of selected organochlorine contaminants in outdoor dust collected from Xinxiang,a fast developing city in North China

As facile “environmental media”, the outdoor dust may reflect the changes of contaminants in environment more promptly. In the present study, selected organochlorine contaminants (OCs) include hexachlorocyclohexanes (HCHs), dichlorodiphenyltrichloroethanes (DDTs), hexachlorobenzene (HCB), and pentachlorobenzene (PeCB) were detected in 20 outdoor dust samples collected from Xinxiang City. The concentrations of ΣHCHs, ΣDDTs, HCB, and PeCB in dust were in the range of 0.18–5.05 ng/g dry weight, 0.44–13.50 ng/g dry weight, 0.13–51.61 ng/g dry weight and ND-0.74 ng/g dry weight, respectively. Long-range transport, historical use, and recent impact of impure pesticides might be the main sources of OCs in the outdoor dust. The results of this study indicated that impure pesticide application maybe an important source of DDTs and HCB in the environment.     

Determination of ametryn in sugarcane and ametryn–atrazine herbicide formulations using spectrophotometric method

A sensitive spectrophotometric method has been developed for determination of ametryn in agricultural samples. The proposed method was based on reaction with pyridine and further coupling with sulfanilic acid to form a colored product. The absorbance was measured at 400 nm with a molar absorptivity of 2.1 × 10⁵ L mol⁻¹ cm⁻¹. The method shows a linear range from 0.2–20 μg mL⁻¹ with limit of detection and limit of quantification 0.16 and 0.54 μg mL⁻¹, respectively. The method has been successfully applied to the determination of ametryn in sugarcane juice and commercial formulations after separation of ametryn from triazine herbicides based on solvent extraction. Recovery values were found to be in the range of 96.0 ± 0.2% to 98.4 ± 0.1%.     

The role of environmental and socio-demographic indicators in the analysis of land use changes in a protected area of the Natura 2000 Network: the case study of Lake Trasimeno,Umbria, Central Italy

This article sets out to analyse how and to what degree land use is linked to the physical characteristics of the territory itself, and the way in which changes in land use are determined by agricultural and socio-demographic dynamics. The study was conducted within the territorial boundaries of five municipalities surrounding Lake Trasimeno and refers to the periods 1977–2000 for land use and 1971–2001 for socio-demography data. The use of environmental, social, economic and agricultural indicators demonstrates how a mix of various indicators are useful for monitoring the changes which took place. It also shows the powerful influence that socio-demographic factors exert upon land use and landscape change.