Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

Effects of Scale and Logging on Landscape Structure in a Forest Mosaic

Landscape structure in a forest mosaic changes with spatial scale (i.e. spatial extent) and thresholds may occur where structure changes markedly. Forest management alters landscapestructure and may affect the intensity and location of thresholds. Our purpose was to examine landscape structure at different scales to determine thresholds where landscape structure changes markedly in managed forest mosaics of the Appalachian Mountains in the eastern United States. We also investigated how logging influences landscape structure and whether these management activities change threshold values. Using threshold and autocorrelation analyses, we found that thresholds in landscape indices exist at 400, 500, and 800 m intervals from the outer edge of management units in our studyregion. For landscape indices that consider all landcovercategories, such as dominance and contagion, landscape structureand thresholds did not change after logging occurred. Measurements for these overall landscape indices were stronglyinfluenced by midsuccessional deciduous forest, the most commonlandcover category in the landscape. When restricting analysesfor mean patch size and percent cover to individual forest types,thresholds for early-successional forests changed after logging. However, logging changed the landscape structure at small spatialscale, but did not alter the structure of the entire forestmosaic. Previous forest management may already have increasedthe heterogeneity of the landscape beyond the point whereadditional small cuts alter the overall structure of the forest. Because measurements for landscape indices yield very differentresults at different spatial scales, it is important first toidentify thresholds in order to determine the appropriate scalesfor landscape ecological studies. We found that threshold andautocorrelation analyses were simple but powerful tools for thedetection of appropriate scales in the managed forest mosaicunder study.     

Methane oxidation and abundance of methane oxidizers in tropical agricultural soil (vertisol) in response to CuO and ZnO nanoparticles contamination

There is worldwide concern over the increase use of nanoparticles (NPs) and their ecotoxicological effect. It is not known if the annual production of tons of industrial nanoparticles (NPs) has the potential to impact terrestrial microbial communities, which are so necessary for ecosystem functioning. Here, we have examined the consequences of adding the NPs particularly the metal oxide (CuO, ZnO) on CH₄ oxidation activity in vertisol and the abundance of heterotrophs, methane oxidizers, and ammonium oxidizers. Soil samples collected from the agricultural field located at Madhya Pradesh, India, were incubated with either CuO and ZnO NPs or ionic heavy metals (CuCl₂, ZnCl₂) separately at 0, 10, and 20 μg g^?1 soil. CH₄ oxidation activity in the soil samples was estimated at 60 and 100 % moisture holding capacity (MHC) in order to link soil moisture regime with impact of NPs. NPs amended to soil were highly toxic for the microbial-mediated CH₄ oxidation, compared with the ionic form. The trend of inhibition was Zn 20?>?Zn 10?>?Cu 20?>?Cu 10. NPs delayed the lag phase of CH₄ oxidation to a maximum of 4-fold and also decreased the apparent rate constant k up to 50 % over control. ANOVA and Pearson correlation analysis (α?=?0.01) revealed significant impact of NPs on the CH₄ oxidation activity and microbial abundance (p?<?0.0001, and high F statistics). Principal component analysis (PCA) revealed that PC1 (metal concentration) rendered 76.06 % of the total variance, while 18.17 % of variance accounted by second component (MHC). Biplot indicated negative impact of NPs on CH₄ oxidation and microbial abundance. Our result also confirmed that higher soil moisture regime alleviates toxicity of NPs and opens new avenues of research to manage ecotoxicity and environmental hazard of NPs.     

An Evaluation of Selenium Concentrations in Water, Sediment, Invertebrates, and Fish from the Republican River Basin: 1997–1999

The Republican River Basin of Colorado,Nebraska, and Kansas lies in a valley which contains PierreShale as part of its geological substrata. Selenium is anindigenous constituent in the shale and is readily leached intosurrounding groundwater. The Basin is heavily irrigated throughthe pumping of groundwater, some of which is selenium-contaminated, onto fields in agricultural production. Water,sediment, benthic invertebrates, and/or fish were collected from46 sites in the Basin and were analyzed for selenium to determinethe potential for food-chain bioaccumulation, dietary toxicity,and reproductive effects of selenium in biota. Resultingselenium concentrations were compared to published guidelines orbiological effects thresholds. Water from 38% of the sites (n = 18) contained selenium concentrations exceeding 5 g L^-1, which is reported to be a high hazard for selenium accumulation into the planktonic food chain. An additional 12 sites (26% of the sites) contained selenium in water between 3–5 g L^-1, constituting a moderate hazard. Selenium concentrations in sedimentindicated little to no hazard for selenium accumulation fromsediments into the benthic food chain. Ninety-five percent ofbenthic invertebrates collected exhibited selenium concentrationsexceeding 3 g g^-1, a level reported as potentially lethal to fish and birds that consume them. Seventy-five percent of fish collected in 1997, 90% in 1998, and 64% in 1999 exceeded 4 g g^-1selenium, indicating a high potential for toxicity andreproductive effects. However, examination of weight profilesof various species of collected individual fish suggestedsuccessful recruitment in spite of selenium concentrations thatexceeded published biological effects thresholds for health andreproductive success. This finding suggested that universalapplication of published guidelines for selenium may beinappropriate or at least may need refinement for systems similarto the Republican River Basin. Additional research is needed todetermine the true impact of selenium on fish and wildliferesources in the Basin.     

Characterizing ecological risk for polycyclic aromatic hydrocarbons in water from Lake Taihu, China

Lake Taihu provides vital ecological services for humans in China; it receives a great deal of attention regarding its ecological and environmental conditions. In this study, the ecological risks of eight individual polycyclic aromatic hydrocarbons (PAHs) in water were assessed using probabilistic distributions of the hazard quotient based on Monte Carlo simulation. The results show that the 95th percentile of the hazard quotients ranged from 0.00074 to 2.831, and the ecological risk of Flua was highest, followed by, in descending order of risk, B[a]P?>?Pyr?>?Ant?>?Phe?>?Flu?>?Ace?>?Chr. The probabilities of hazard quotients exceeding a decision criteria of 0.3 were 18.09%, 6.51%, 3.76%, and 2.85% for Flua, B[a]P, Pyr, and Ant, respectively, indicating their potential ecological risks to aquatic organisms. The spatial distribution of hazard quotients for these four individual PAHs with potential ecological risk were obtained using Geographic Information System (GIS), and similar spatial distribution patterns were also observed in the lake. The highest ecological risks of these four individual PAHs to aquatic organisms were found in Meiliang Bay, followed by Gonghu Bay and Xukou Bay. The uncertainty within the ecological risk assessment was also discussed.     

The ecological impact assessment of a proposed road development (the Slovak approach)

The construction of roads is one of the most widespread forms of natural landscape modification. Over the last 20 years, dozens of road constructions have been assessed in Slovakia, which makes it possible to talk about methodological positives and negatives. A special feature of Slovakia is that many planned or renovated roads are located in protected areas or are in contact with them (including Natura 2000 sites). Therefore, it is important to understand the scope of the roads' ecological impacts and find ways for their appropriate evaluation and incorporation into the Environmental Impact Assessment process. For this reason, the Ecological Impact Assessment methodology can be used as a basis for our research, which consists of three stages. In the first stage (scoping), a buffer circumventing the proposed road is created to determine the area for impact prediction and evaluation. Subsequently, the landscape structure and baseline landscape conditions are discussed, a map of current landscape structure is created and the current ecological status of the affected area is calculated. In the second stage (the evaluation of ecological resources), important ecological parts of the landscape are delineated. This step is based on the importance of previous information and its vulnerability, and leads to the mapping of the road ecological impact zone. In the third stage (impact assessment), important ecological parts are spatially correlated with the proposed road construction. Finally, the significance of ecological impacts of the activity is evaluated by applying specific criteria (duration, reversibility, magnitude, size and road ecological impact zone significance). A scale is proposed for each criterion to evaluate the total significance of impacts. In this way, detailed significant ecological impacts can be found which will help lead to proposed correct mitigation measures and a post-project analysis.     

Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region

Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E?~?1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.     

Decision support model for assessing aquifer pollution hazard and prioritizing groundwater resources management in the wet Pampa plain, Argentina

This paper gives an account of the implementation of a decision support system for assessing aquifer pollution hazard and prioritizing subwatersheds for groundwater resources management in the southeastern Pampa plain of Argentina. The use of this system is demonstrated with an example from Dulce Stream Basin (1,000 km² encompassing 27 subwatersheds), which has high level of agricultural activities and extensive available data regarding aquifer geology. In the logic model, aquifer pollution hazard is assessed as a function of two primary topics: groundwater and soil conditions. This logic model shows the state of each evaluated landscape with respect to aquifer pollution hazard based mainly on the parameters of the DRASTIC and GOD models. The decision model allows prioritizing subwatersheds for groundwater resources management according to three main criteria including farming activities, agrochemical application, and irrigation use. Stakeholder participation, through interviews, in combination with expert judgment was used to select and weight each criterion. The resulting subwatershed priority map, by combining the logic and decision models, allowed identifying five subwatersheds in the upper and middle basin as the main aquifer protection areas. The results reasonably fit the natural conditions of the basin, identifying those subwatersheds with shallow water depth, loam–loam silt texture soil media and pasture land cover in the middle basin, and others with intensive agricultural activity, coinciding with the natural recharge area to the aquifer system. Major difficulties and some recommendations of applying this methodology in real-world situations are discussed.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.     

Designing a graph-based approach to landscape ecological assessment of linear infrastructures

The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures.     

Solar photovoltaics in airport: Risk assessment and mitigation strategies

Solar PV systems are being installed in airports across the globe. It is a relatively new application of solar PV technology with a potential impact on aviation safety. The main objective of this paper is to assess the risk of solar photovoltaics at the airport. At first, potential risk/ hazard to aviation safety from solar photovoltaics in airport premises is identified, and then the severity and probability level for each risk is assessed. A risk assessment matrix is developed using Hazard Identification and Risk Assessment method. It is observed that there are seven types of possible hazards from airport-based solar PV systems. The risk index is highest for glare occurrence from PV modules (4B), strike from birds in PV site (4B), and interference to communication systems (3B). It is concluded that most of the risks need implementation of mitigation measures such as prior glare assessment in the feasible sites, periodic monitoring of bird's activity in the PV array and follow safety distance between PV array and communication aids. Researchers and engineers must work along with aviation and airport officials to mitigate possible risks from solar PV installation in the airports.     

A Regional Survey of the Microbiological Water Quality along the Shoreline of the Southern California Bight

A regional survey of the microbiological water quality along the shoreline of the Southern California Bight (SCB), from Point Conception south to Ensenada, Mexico, was conducted during August, 1998, by 36 agencies under the coordination of the Southern California Coastal Water Research Project (SCCWRP). Microbiological water quality was assessed by calculating the percentage of shoreline-mile-days that exceeded bacterial indicator thresholds for total and fecal coliforms, total/fecal ratios, and enterococci. Sample sites were selected using a stratified random sampling approach, with the SCB recreational shoreline divided into six strata: high- and low-use sandy beaches, high- and low-use rocky shoreline, and perennial and ephemeral freshwater outlets. Samples were collected on a weekly basis at a total of 253 sites, beginning on August 2^nd, 1998 and continuing for five weeks. Samples were analyzed by 22 participating labs using their normal methods (multiple tube fermentation, membrane filtration, Colilert® and/or Enterolert®). All labs met testing criteria established through intercalibration exercises and quality control check samples distributed during the sampling period. Nearly 95% of the shoreline-mile days did not exceed daily and monthly bacterial indicator thresholds, demonstrating good bacteriological water quality along the SCB shoreline. Freshwater outlets, comprised mainly of storm drains, had the poorest water quality with 60% and 40% of the shoreline-miles exceeding monthly and daily thresholds, respectively. Freshwater outlets were also more likely to demonstrate exceedances by multiple indicators at a single site, and repeat exceedances at sites over the five-week period. Compared with the southern California beaches, Mexican beaches had nearly 5 times the number of exceedances for total and fecal coliforms, and nearly 8 times the number of exceedances for total/fecal ratios.     

Forest ecological classification and mapping: Their application for ecosystem management in Newfoundland

A prerequisite to sustaining ecosystems is the inventory and classification of landscape structure and composition. Ecological classification and mapping involves the delineation of landscapes into easily recognizable units. Topography, soils, vegetation, physical landscape form, and successional pathways are delineation criteria commonly used.Damman (1967) developed a forest type classification system for Newfoundland using vegetation, soil and landforms as the defining criteria. Damman's forest types were used in combination with mensurational data to assign forest types to timber volume productivity classes. Since each of the Damman forest types is associated with characteristic soils, parent materials, moisture regime and topographic position, the mapping units are similar to Canada Land Inventory (CLI) mapping units. Field work to confirm the correlation between Damman forest types and CLI capability classes was initiated in 1993. CLI maps were recoded in 1994 and Damman forest types were determined; resulting ecosystem-based maps provide a common framework to assess forestry/wildlife interactions in an ecosystem planning process.     

Multi-scale landscape factors influencing stream water quality in the state of Oregon

Enterococci bacteria are used to indicate the presence of human and/or animal fecal materials in surface water. In addition to human influences on the quality of surface water, a cattle grazing is a widespread and persistent ecological stressor in the Western United States. Cattle may affect surface water quality directly by depositing nutrients and bacteria, and indirectly by damaging stream banks or removing vegetation cover, which may lead to increased sediment loads. This study used the State of Oregon surface water data to determine the likelihood of animal pathogen presence using enterococci and analyzed the spatial distribution and relationship of biotic (enterococci) and abiotic (nitrogen and phosphorous) surface water constituents to landscape metrics and others (e.g. human use, percent riparian cover, natural covers, grazing, etc.). We used a grazing potential index (GPI) based on proximity to water, land ownership and forage availability. Mean and variability of GPI, forage availability, stream density and length, and landscape metrics were related to enterococci and many forms of nitrogen and phosphorous in standard and logistic regression models. The GPI did not have a significant role in the models, but forage related variables had significant contribution. Urban land use within stream reach was the main driving factor when exceeding the threshold (> or =35 cfu/100 ml), agriculture was the driving force in elevating enterococci in sites where enterococci concentration was <35 cfu/100 ml. Landscape metrics related to amount of agriculture, wetlands and urban all contributed to increasing nutrients in surface water but at different scales. The probability of having sites with concentrations of enterococci above the threshold was much lower in areas of natural land cover and much higher in areas with higher urban land use within 60 m of stream. A 1% increase in natural land cover was associated with a 12% decrease in the predicted odds of having a site exceeding the threshold. Opposite to natural land cover, a one unit change in each of manmade barren and urban land use led to an increase of the likelihood of exceeding the threshold by 73%, and 11%, respectively. Change in urban land use had a higher influence on the likelihood of a site exceeding the threshold than that of natural land cover.     

Monitoring an ecosystem at risk: What is the degree of grassland fragmentation in the Canadian Prairies?

Increasing fragmentation of grassland habitats by human activities is a major threat to biodiversity and landscape quality. Monitoring their degree of fragmentation has been identified as an urgent need. This study quantifies for the first time the current degree of grassland fragmentation in the Canadian Prairies using four fragmentation geometries (FGs) of increasing specificity (i.e. more restrictive grassland classification) and five types of reporting units (7 ecoregions, 50 census divisions, 1,166 municipalities, 17 sub-basins, and 108 watersheds). We evaluated the suitability of 11 datasets based on 8 suitability criteria and applied the effective mesh size (m _eff) method to quantify fragmentation. We recommend the combination of the Crop Inventory Mapping of the Prairies and the CanVec datasets as the most suitable for monitoring grassland fragmentation. The grassland area remaining amounts to 87,570.45 km² in FG4 (strict grassland definition) and 183,242.042 km² in FG1 (broad grassland definition), out of 461,503.97 km² (entire Prairie Ecozone area). The very low values of m _eff of 14.23 km² in FG4 and 25.44 km² in FG1 indicate an extremely high level of grassland fragmentation. The m _eff method is supported in this study as highly suitable and recommended for long-term monitoring of grasslands in the Canadian Prairies; it can help set measurable targets and/or limits for regions to guide management efforts and as a tool for performance review of protection efforts, for increasing awareness, and for guiding efforts to minimize grassland fragmentation. This approach can also be applied in other parts of the world and to other ecosystems.     

Applying a Large,Statewide Database to the Assessment,Stressor Diagnosis,and Restoration of Stream Fish Communities

In this report, predictions of the species that were expected to occur at stream sites were generated and probable stressors to fish species that were predicted to occur but were absent were diagnosed. Predictions were generated based on the hierarchical screening method of Smith and Powell (1971, Am. Mus. Novit. 2458, 1–30), using fish abundance in conjunction with 25 environmental variables at 895 sites. The sites were sampled throughout Maryland and represent the entire range of environmental quality from severely degraded to minimally degraded. Stressor variable values that exceeded tolerance thresholds for species that were expected to occur, but were absent, were considered to be probable stressors. This method was tested for efficacy in stream site assessments and stressor diagnosis using an independent data set. Sites that were classified as degraded according to the IBI and to non-biological criteria had fewer predicted species present compared to minimally influenced sites, indicating that the proportion of predicted species present accurately represents the biological integrity of a stream site. The nine stressors that were applied to the test data set accounted for species absences in 43.7% of degraded sites. Impervious land cover was the most common stressor identified. In addition to assessing stream biological integrity and identifying stressors to fish species, this approach also provides tolerance thresholds for predicted fish species that are useful endpoints necessary to plan effective restoration of fish species in Maryland.     

An approach to analyzing the intensity of the daytime surface urban heat island effect at a local scale

A landscape index LI is proposed to evaluate the intensity of the daytime surface urban heat island (SUHI) effect at a local scale. Three aspects of this landscape index are crucial: the source landscape, the sink landscape, and the contribution of source and sink landscapes to the intensity of the SUHI. Source and sink landscape types are identified using the thermo-band of Landsat 7 with a spatial resolution of 60 m, along with appropriate threshold values for the Normalized Difference Vegetation Index, Modified Normalized Difference Water Index, and Normalized Difference Built-up Index. The landscape index was defined as the ratio of the contributions of the source and sink landscapes to the intensity of the SUHI. The intensity of the daytime SUHI is assessed with the help of the landscape index. Our analysis indicates the landscape index can be used to evaluate and compare the intensity of the daytime SUHI for different areas.     

Greenhouse gas emissions from two hydroelectric reservoirs in Mediterranean region

Water reservoirs are used for many purposes, such as water supply, irrigation, flood mitigation, and hydroelectric energy generation. Although hydroelectric energy is considered “green,” many studies show that the construction of a reservoir enhances greenhouse gas (GHG) emissions at the transformed area. These emissions, mainly of CO₂, CH₄, and N₂O gases, depend on the age of the reservoir, landscape and soil composition, fauna and flora remnants of the impounded area, climatic conditions, and basin runoffs. Consequently, GHG emissions significantly vary between reservoirs and depending on local specificities. Several studies have investigated GHG emissions from reservoirs around the world, focusing mainly on reservoirs located in cold regions, temperate regions, and tropical regions. Research is lacking for reservoirs in Mediterranean countries, like Greece, and similar regions. This work initially assesses the net GHG emissions of a newly created reservoir (Ilarion est. 2012) in Western Macedonia, Greece. The methodology for net GHG emission calculation was based on the use of literature data concerning pre-impoundment emission factors and local specificities of the reservoir (terrain type, canopy cover), as well as on the 2-year measurement data that were collected using a “static floating chamber.” Furthermore, in this work, the gross GHG emissions of an older, in-line reservoir (Polyfytos est. 1974) were also calculated, based on 2-year measurement data. The results show that the global warming potential (GWP) of the reservoirs is dictated by methane emissions; it minimizes during winter and spring and maximizes during summer and autumn. Hydroelectric energy production at Ilarion Reservoir results in 32 to 97 times less total CO₂ equivalent emissions in comparison to fossil fuels, while at Polyfytos Reservoir only 8 to 24 times less (based on gross emissions). It appears that the impact of a reservoir’s morphology on GHG emissions is more significant than that of a reservoir’s age.     

Arsenic concentration variability, health risk assessment, and source identification using multivariate analysis in selected villages of public water system, Lahore, Pakistan

This paper reports high levels and variability in arsenic (As) levels at locations identified as one of the highest As-contaminated locations in Pakistan. Groundwater pollution related to arsenic has been reported since many years in the areas lying in outskirts of District Lahore, Pakistan. A comparative study is done to determine temporal variations of As from three villages, i.e., Kalalanwala (KLW), Manga Mandi (MM), and Shamki Bhattian (SKB). Seventy-three percent of the 30 investigated samples ranging in depth from 20 to 200 m, show an increasing trend in variations of As concentration over a time span of 4 years and 87 % of samples exceeded the WHO standard of 10 μg/L for As while 77 % of samples have As concentration >50 μg/L (national standard). Further results indicate that high levels of As is accompanied with increase pH (r?=?0.8) favoring desorption of As from minerals at higher pH under oxidizing conditions. For health risk assessment of arsenic, the average daily dose, hazard quotient (HQ), and cancer risk were calculated. The residents of the studied areas had toxic risk index in the order of SKB>KLW>MM, with 87 % of samples exceeding the typical toxic risk index 1.00 (ranging from 2.3–48.6) which was 83 % (ranging from 0.3–41) 4 years before. The results of the present study therefore indicate that arsenic concentrations are increasing in the area, which needs an immediate attention to provide alternate sources of water to save people at risk.     

Lead forms in urban turfgrass and forest soils as related to organic matter content and pH

Identification of reference streams and human disturbance gradients are crucial steps in assessing the effects of human disturbances on stream health. We describe a process for identifying reference stream reaches and assessing disturbance gradients using readily available, geo-referenced stream and human disturbance databases. We demonstrate the utility of this process by applying it to wadeable streams in Michigan, USA, and use it to identify which human disturbances have the greatest impact on streams. Approximately 38% of cold-water and 16% of warm-water streams in Michigan were identified as being in least-disturbed condition. Conversely, approximately 3% of cold-water and 4% of warm-water streams were moderately to severely disturbed by landscape human disturbances. Anthropogenic disturbances that had the greatest impact on moderately to severely disturbed streams were nutrient loading and percent urban land use within network watersheds. Our process for assessing stream health represents a significant advantage over other routinely used methods. It uses inter-confluence stream reaches as an assessment unit, permits the evaluation of stream health across large regions, and yields an overall disturbance index that is a weighted sum of multiple disturbance factors. The robustness of our approach is linked to the scale of disturbances that affect a stream; it will be less robust for identifying less degraded or reference streams with localized human disturbances. With improved availability of high-resolution disturbance datasets, this approach will provide a more complete picture of reference stream reaches and factors contributing to degradation of stream health.