Impact of overland traffic on heavy metal levels in highway dust and soils of Istanbul, Turkey

The purpose of this study was to investigate the impact of overland traffic on the spatial distribution of heavy metals in urban soils (Istanbul, Turkey). Road dust, surface, and subsurface soil samples were collected from a total of 41 locations along highways with dense traffic and secondary roads with lower traffic and analyzed for lead (Pb), zinc (Zn), and copper (Cu) concentrations. Statistical evaluation of the heavy metal concentrations observed along highways and along the secondary roads showed that the data were bimodally distributed. The maximum observed Pb, Zn, and Cu concentrations were 1,573, 522 and 136 mg/kg, respectively, in surface soils along highways and 99.3, 156, and 38.1 mg/kg along secondary roads. Correlation analysis of the metal concentrations in road dust, surface and 20-cm depth soils suggests the presence of a common pollution source. However, metal concentrations in the deeper soils were substantially lower than those observed at the surface, indicating low mobility of heavy metals, especially for Pb and Zn. A modified kriging approach that honors the bimodality of the data was used to estimate the spatial distribution of the surface concentrations of metals, and to identify hotspots. Results indicate that despite the presence of some industrial zones within the study area, traffic is the main heavy metal pollution source.     

Characterizing the forest fragmentation of Canada’s national parks

Characterizing the amount and configuration of forests can provide insights into habitat quality, biodiversity, and land use. The establishment of protected areas can be a mechanism for maintaining large, contiguous areas of forests, and the loss and fragmentation of forest habitat is a potential threat to Canada’s national park system. Using the Earth Observation for Sustainable Development of Forests (EOSD) land cover product (EOSD LC 2000), we characterize the circa 2000 forest patterns in 26 of Canada’s national parks and compare these to forest patterns in the ecological units surrounding these parks, referred to as the greater park ecosystem (GPE). Five landscape pattern metrics were analyzed: number of forest patches, mean forest patch size (hectare), standard deviation of forest patch size (hectare), mean forest patch perimeter-to-area ratio (meters per hectare), and edge density of forest patches (meters per hectare). An assumption is often made that forests within park boundaries are less fragmented than the surrounding GPE, as indicated by fewer forest patches, a larger mean forest patch size, less variability in forest patch size, a lower perimeter-to-area ratio, and lower forest edge density. Of the 26 national parks we analyzed, 58% had significantly fewer patches, 46% had a significantly larger mean forest patch size (23% were not significantly different), and 46% had a significantly smaller standard deviation of forest patch size (31% were not significantly different), relative to their GPEs. For forest patch perimeter-to-area ratio and forest edge density, equal proportions of parks had values that were significantly larger or smaller than their respective GPEs and no clear trend emerged. In summary, all the national parks we analyzed, with the exception of the Georgian Bay Islands, were found to be significantly different from their corresponding GPE for at least one of the five metrics assessed, and 50% of the 26 parks were significantly different from their respective GPEs for all of the metrics assessed. The EOSD LC 2000 provides a heretofore unavailable dataset for characterizing broad trends in forest fragmentation in Canada’s national parks and in their surrounding GPEs. The interpretation of forest fragmentation metrics must be guided by the underlying land cover context, as many forested ecosystems in Canada are naturally fragmented due to wetlands and topography. Furthermore, interpretation must also consider the management context, as some parks are designed to preserve fragmented habitats. An analysis of forest pattern such as that described herein provides a baseline, from which changes in fragmentation patterns over time could be monitored, enabled by earth observation data.     

Fire risk evaluation using multicriteria analysis—a case study

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential “hotspots” of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing “where and when” forest fires will most likely occur.     

Monsoon-induced changes in the size-fractionated phytoplankton biomass and production rate in the estuarine and coastal waters of southwest coast of India

Changes in the autotrophic pico- (0.2–2 μm), nano- (2–20 μm), and microplankton (>20 μm) biomass (chlorophyll a) and primary production were measured in the estuarine and coastal waters off Cochin, southwest coast of India during the onset and establishment of a monsoon. During this period, the estuary was dominated by nutrient-rich freshwater, whereas the coastal waters were characterized with higher salinity values (>30 psu) and less nutrients. The average surface chlorophyll a concentrations and primary production rates were higher in the estuary (average 13.7 mg m^???3 and 432 mgC m^???3 day^???1) as compared to the coastal waters (5.3 mg m^???3 and 224 mgC m^???3 day^???1). The nanoplankton community formed the major fraction of chlorophyll a and primary production, both in the estuary (average 85 ± SD 8.3% and 81.2 ± SD 3.2%) and the coastal waters (average 73.2 ± SD 17.2% and 81.9 ± 15.7%). Nanoplankton had the maximum photosynthetic efficiency in the coastal waters (average 4.8 ± SD 3.9 mgC mgChl a m^???3 h^???1), whereas in the estuary, the microplankton had higher photosynthetic efficiency (average 7.4 ± 7 mgC mgChl a m^???3 h^???1). The heavy cloud cover and increased water column turbidity not only limit the growth of large-sized phytoplankton in the Cochin estuary and coastal waters but also support the proliferation of nanoplankton community during the monsoon season, even though large variation in nanoplankton chlorophyll a and production exists between these two areas.     

Assessing the water quality index of water treatment plant and bore wells, in Delhi, India

Water quality monitoring exercise was carried out with water quality index (WQI) method by using water characteristics data for bore wells and a water treatment plant in Delhi city from December 2006 to August 2007. The water treatment plant received surface water as raw water, and product water is supplied after treatment. The WQI is used to classify water quality as excellent, good, medium, bad, and very bad. The National Sanitation Foundation WQI procedure was used to calculate the WQI. The index ranges from 0 to 100, where 100 represents an excellent water quality condition. Water samples were collected monthly from a bore well in Nehru Camp (site 1), a bore well in Sanjay Gandhi pumping station (site 2), and water treatment plant in Haiderpur (site 3). Five parameters were analyzed, namely, nitrate, pH, total dissolved solids, turbidity, and temperature. We found that the WQI was around 73–80 in site 3, which corresponds to “good,” and it decreased to 54.32–60.19 and 59.93–70.63 in site 1 and site 2, respectively, indicating that these bore wells were classified as “medium” quality.     

Metal fractionation study on bed sediments of Hussainsagar Lake, Hyderabad, India

Hussainsagar Lake in the heart of Hyderabad City (India) receives toxic substances through five streams draining from a catchment area of 245 km². Of particular interest are heavy metals received from urban runoff as well as municipal sewage and industrial effluents. Heavy metals entering the lake get adsorbed onto the suspended sediments, which eventually settle down in the bottom of the lake. In this study, fractionation of metal ions has been studied on the bed sediments of Hussainsagar Lake in order to determine the ecotoxic potential of metal ions. Comparison of sediments with average shale values indicated anthropogenic enrichment with copper, nickel, lead, cadmium, and zinc. The risk assessment code as applied to the present study reveals that 10–17% of manganese, 10–18% of nickel, 14–24% of chromium, 10–19% of lead, 21–30% of cadmium, and 18–28% of zinc exist in exchangeable fraction and, therefore, comes under medium risk category and may enter into food chain. The association of these metals with the exchangeable fraction may cause deleterious effects to aquatic life. The present database will help in formulating guidelines for carrying out dredging operations under restoration programs in the Hussainsagar Lake.     

Hydrogeochemical characterization of fluoride rich groundwater of Wailpalli watershed, Nalgonda District, Andhra Pradesh, India

The groundwater of Nalgonda district is well known for its very high fluoride content for the past five decades. Many researchers have contributed their scientific knowledge to unravel causes for fluoride enrichment of groundwater. In the present paper, an attempt has been made to relate the high fluoride content in the groundwater to hydrogeochemical characterization of the water in a fracture hard rock terrain—the Wailpally watershed. Groundwater samples collected from all the major geomorphic units in pre- and post-monsoon seasons were analyzed for its major ion constituents such as Ca^2?+?, Mg^2?+?, Na^?+?, K^?+?, CO $_{3}^{-}$ , HCO $_{3}^{-}$ , Cl^???, SO $_{4}^{-2}$ , NO $_{3}^{-}$ , and F^???. The groundwaters in the watershed have the average fluoride content of 2.79 mg/l in pre-monsoon and 2.83 mg/l in post-monsoon. Fluoride concentration in groundwater does not show perceptible change neither with time nor in space. The ionic dominance pattern is in the order of Na^?+? > Ca^2?+??> Mg^2?+??> K^??? among cations and HCO $_{3}^{-}\:\,>$ Cl^????> SO $_{4}^{-2} >$ NO $_{3}^{-} >$ F^??? among anions in pre-monsoon. In post-monsoon, Mg replaces Ca^2?+? and NO $_{3}^{-}$ takes the place of SO $_{4}^{-2}$ . The Modified Piper diagram reflect that the water belong to Ca^?+?2–Mg^?+?2–HCO $_{3}^{-}$ to Na^?+?–HCO $_{3}^{-}$ facies. Negative chloralkali indices in both the seasons prove that ion exchange between Na^?+? and K^?+? in aquatic solution took place with Ca^?+?2 and Mg^?+?2 of host rock. The interpretation of plots for different major ions and molar ratios suggest that weathering of silicate rocks and water–rock interaction is responsible for major ion chemistry of groundwater in Wailpally watershed. Chemical characteristics and evolution of this fluoride-contaminated groundwater is akin to normal waters of other hard rock terrain; hence, it can be concluded that aquifer material play an important role in the contribution of fluoride in to the accompanying water. High fluoride content in groundwater can be attributed to the continuous water–rock interaction during the process of percolation with fluorite-bearing country rocks under arid, low precipitation, and high evapotranspiration conditions.     

Emissions of SO2, NO x and particulates from a pipe manufacturing plant and prediction of impact on air quality

Integrated pipe manufacturing industry is operation intensive and has significant air pollution potential especially when it is equipped with a captive power production facility. Emissions of SO₂, NO _x , and particulate matter (PM) were estimated from the stationary sources in a state-of-the-art pipe manufacturing plant in India. Major air polluting units like blast furnace, ductile iron spun pipe facility, and captive power production facility were selected for stack gas monitoring. Subsequently, ambient air quality modeling was undertaken to predict ground-level concentrations of the selected air pollutants using Industrial Source Complex (ISC 3) model. Emissions of SO₂, NO _x , and particulate matter from the stationary sources in selected facilities ranged from 0.02 to 16.5, 0.03 to 93.3, and 0.09 to 48.3 kg h^???1, respectively. Concentration of SO₂ and NO _x in stack gas of 1,180-kVA (1 KW = 1.25 kVA) diesel generator exceeded the upper safe limits prescribed by the State Pollution Control Board, while concentrations of the same from all other units were within the prescribed limits. Particulate emission was highest from the barrel grinding operation, where grinding of the manufactured pipes is undertaken for giving the final shape. Particulate emission was also high from dedusting operation where coal dust is handled. Air quality modeling indicated that maximum possible ground-level concentration of PM, SO₂, and NO _x were to the tune of 13, 3, and 18 μg/m³, respectively, which are within the prescribed limits for ambient air given by the Central Pollution Control Board.     

Multiscale satellite and spatial information and analysis framework in support of a large-area forest monitoring and inventory update

Many countries undertake a national forest inventory to enable statistically valid monitoring in support of national and international reporting of forest conditions and change. Canada’s National Forest Inventory (NFI) program is designed to operate on a 10-year remeasurement cycle, with an interim report produced at the 5-year mid-point. The NFI is a sample-based inventory, with approximately 18,850 2 ×2-km photo plots across the country, distributed on a 20×20-km grid of sample points; these photo plots are the primary data source for the NFI. Capacity to provide annual monitoring information is required to keep policy and decision makers apprised of current forest conditions. In this study, we implemented a multistage monitoring framework and used a Moderate Resolution Imaging Spectroradiometer (MODIS) change product to successfully identify 78% of the changes in forest cover area that were captured with a Landsat change detection approach. Of the NFI photo plots that were identified by both the Landsat and MODIS approaches as having changes in forest cover, the proportion of change area within the plots was similar (R ²?=?0.78). Approximately 70% of the Landsat-derived change events occupied less than 40% of a single MODIS pixel, and more than 90% of the change events of this size were successfully detected with the MODIS product. Finally, MODIS estimates of the proportion of forest cover change at the NFI photo plot level were comparable to change estimates for the ecoregions as a whole (R ²?=?0.95). High-temporal, low-spatial resolution imagery such as MODIS, in combination with other remotely sensed data sources, can provide information on disturbance events within a national forest inventory remeasurement cycle, thereby satisfying the interim information needs of policy and decision makers as well as the requirements of national and international reporting commitments.     

Evaluation of geochemical associations as a screening tool for identifying anthropogenic trace metal contamination

Geochemical association plots are used as a screening tool for environmental site assessments and use empirical log–log relationships between total trace metal concentrations and concentrations of a major (i.e., reference) soil metal constituent, such as iron (Fe), to discern sites with naturally elevated trace metal levels from sites with anthropogenic contamination. Log–log relationships have been consistently observed between trace metal and reference metal concentrations and are often considered constant. Consequently, we used a regional geochemistry data set to evaluate background trace metal/Fe log–log associations across soils with highly diverse composition. Our results indicate that, although geochemical associations may be proportional, they significantly differ across predominant United States Department of Agriculture (USDA) soil orders. This suggests that highly complex interactions between soil-forming factors and variable secondary clay mineral composition affect the ratio of trace metals to Fe concentrations in soils. Also, intra-order variability in trace metal/Fe ratios generally ranged multiple orders of magnitude which suggest that the order level of the USDA soil taxonomic system is insufficient to reasonably classify background trace metal concentrations. Consequently, geochemical association plots are a useful screening tool for environmental site assessments, but ubiquitous application of generic background metal data sets could result in erroneous conclusions. Because significantly different ratios were observed across predominant USDA soil orders, an agglomerative clustering technique was used to elucidate hierarchical patterns of association. We present these results as a mechanism to aid environmental assessors in screening candidate background metal data sets for their applicability to site-specific soil composition; although site-specific background metal data should be utilized if ample pristine reference sites with similar (i.e., sub-order) soil composition can be identified and sampled.