Post‐earthquake rehabilitation of the rural water systems in Kashmir's Jehlum Valley

After the devastating earthquake of 8 October 2005 in Kashmir, international organizations provided the Pakistani government with relief and reconstruction assistance. Under the oft‐cited motto ‘rebuild better’, many of these efforts targeted the rural areas. The emergency period was followed by a development phase, during which all actors sought to ensure that their reconstruction projects would have long‐term, sustainable impacts. Based on the authors’ experience during that phase, this paper offers specific guidelines for rehabilitation work on Kashmir's rural water supply system, stressing the need for analysis of the social context to guarantee sustainability of the completed projects.     

Calculating Air Quality and Its Control

Air quality is shown as a function of averaging times of five minutes to one year for carbon monoxide, hydrocarbons, nitric oxide, nitrogen dioxide, nitrogen oxides, oxidant, and sulfur dioxide in Chicago, Cincinnati, Los Angeles, New Orleans, Philadelphia, San Francisco, and Washington, D. C. Concentrations are approximately lognormally distributed for all pollutants in all cities for all averaging times. Maximum concentration is inversely proportional to averaging time to an exponent. The exponent is a function of the standard geometric deviation. General air quality and control parameters are derived and shown for one example, nitrogen oxides in Washington, D. C. These values are compared to one air quality standard.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 6. Calculating Concentration Reductions Needed to Achieve the New National Ozone Standard

The new ozone National Ambient Air Quality Standard specifies that the expected number of days per calendar year that the 1 hour average ozone concentration can exceed 0.12 ppm must be equal to or less than 1. This paper describes a method to calculate design frequency, design concentration, and the percentage concentration reduction necessary to achieve this standard. The design frequency is once per year (1/365) if daily maximum hour ozone concentrations are available at a particular site for an equal number of days in summer (April through September) and winter (October through March). An equation is used to adjust design frequency as a function of the number of summer and winter samples available. The design concentration (the ambient concentration measured at the design frequency) needs to be reduced to 0.12 ppm. Graphical and digital methods for determining the design concentration are presented. Percentage concentration reductions needed to achieve the standard are calculated for each site which has ozone concentration data available in the National Aerometric Data Bank for at least half of the days in one summer of years 1975 through 1977. The degree of reduction calculated for the site with the highest concentrations in each county is indicated by shading on a map of the United States.     

Fe and As geochemical self-removal dynamics in mineral waters: evidence from the Ferrarelle groundwater system (Riardo Plain,Southern Italy)

Environmental Geochemistry and Health - A theoretical pattern for Fe and As co-precipitation was tested directly in a groundwater natural system. Several monitoring wells were sampled to identify...     

Gathering new knowledge from existing monitoring dataset of Campania marine coastal area (Southern Italy)

Environmental Science and Pollution Research - In this study we propose, a multi-step strategy of selection and characterization of long-term dataset of contaminant concentrations in different...     

Solid state dehalogenation of PCBs in contaminated soil using NaBH4

In this work we present the results of an experimental study on the abatement of polychlorinated biphenyl (PCBs) in contaminated soil using a high energy milling technique, that promotes a reaction only by impact between milling bodies. A sample of soil from a controlled landfill was treated with powdered NaBH(4) using two different hydride/soil ratios (5 and 2.5% w/w). The efficiency of the dehalogenation/hydrogenation reaction was studied as a function of the milling time (3.5 up to 30 h). After each run, the total PCBs content and the production of inorganic chloride were measured. The complete abatement was obtained with a starting PCBs concentration of about 2600 mg/kg. The residual PCBs concentration resulted to be <0.2 mg/kg. The final products of the treatment were biphenyl and NaCl. Other toxic or hazardous organic by-products were not generated. Boron was found as boric acid.     

ASSESSING RELATIVE RISKS TO AQUATIC ECOSYSTEMS: A MID-APPALACHIAN CASE STUDY1

ABSTRACT: Aquatic monitoring aims to assess the condition of aquatic habitats and biota. To make statements about condition, the range of human activities and the risks they pose to aquatic ecosystems must be identified. Assessing relative risk and placing sample sites on a human disturbance gradient is necessary for interpreting biological response and distinguishing human disturbance from natural controls in aquatic systems. We describe a process that uses readily available sources, such as topographic maps, aerial photographs, and field information, to identify and prioritize stream reach and watershed stressors for 102 streams in the mid-Appalachian region of the United States. All perceptible human alterations to riparian and upland areas along with their number, type, intensity, and extent of impact were recorded and ranked; a relative risk index was developed to assign scores to the watersheds. The resulting risk index scores were consistent with measures of stream condition based on water chemistry and benthic macroinvertebrates. The risk index gives a cost-effective, regional picture of the relative risk of impairment to aquatic ecosystems in the mid-Appalachian region of the USA and could be modified for other regions or ecosystem types.     

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: The case study of Denmark

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME = 29.5%; N = 54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME = 31.5%; N = 14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME = 30%; N = 39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas.