Hg Vapor Emission from Broken Compact Fluorescent Lamps (CFLs) in an Acrylic Chamber

The United States Environmental Protection Agency/Environmental Response Team (US EPA/ERT), in collaboration with St. John's College, Dr. B. R. Ambedkar University, Agra, India, is conducting a study to determine Hg vapor emission rates resulting from broken compact fluorescent lamps (CFLs) in a residential setting. The overall objectives of the study are to determine Hg vapor emission data and provide homeowners with cleanup procedures and disposal options for broken CFLs. Most of the currently available CFLs in the US market are manufactured in China for US companies. Several different types of CFLs were purchased from local stores and their Hg content was determined. Based on previous studies, such as the 2011 study by Singhvi and colleagues, five popular spiral CFLs were selected for emission studies in an acrylic chamber. This study found that Hg vapor emissions from CFLs may be significantly greater than those from beads of liquid Hg with weights comparable to the Hg content of the CFLs. The average 24-hour Hg loss into the atmosphere from CFLs broken on a plastic surface ranged from 0.6% to 22% of the bulb content, while that for CFLs broken on carpet ranged from 2.6% to 28%. Projections for a 12 foot × 9.33 foot × 8 foot (25.4 m³) room based on the chamber measurements in this study indicate that CFL breakage in some household settings may produce 24-hour Hg concentrations above the 2000 Agency for Toxic Substances and Disease Registry (ATSDR) minimum risk level (MRL) of 0.2 μg/m³, for typical air exchange rates. This study also indicates that Hg emission may not be proportional to exposed surface area based on experiments using liquid Hg with different surface areas.     

Urban soil quality of Raipur,Chhattisgarh, India

Soil quality in urban areas in India is degraded due to multiple anthropogenic activities. The objectives of this work are to determine the concentration variations, toxicity, and sources of carbons, metals, and ions in the surface soil of Raipur, the industrialized capital city of Chhattisgarh state, India. High concentrations of Al, K, Ca, Ti, Fe, and elemental carbon (EC) were registered. Relatively lower concentrations of V, Cr, Mn, Ni, Cu, Zn, Sr, Ba, Pb, organic carbon (OC), and carbonate carbon (CC), as well as ions (viz. F^–, Cl^–, NO₃^–, SO₄^2–, Na⁺, K⁺, Mg²⁺, and Ca²⁺), were also recorded. EC was found to be one of the major pollutants, although enrichment factors pointed to high contamination with SO₄^2–, K⁺, Mg²⁺_, Cr, Mn, and Pb; and extreme contamination with NO₃^– and Ca²⁺. The spatial and temporal variations, enrichment factors, toxicity, and sources of the chemical species detected in the soil are discussed.     

Indoor air quality modeling for PM10, PM2.5, and PM1.0 in naturally ventilated classrooms of an urban Indian school building

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student??s health and performance as they spend a substantial amount of their time (6?C7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants?? health. The objectives of the present study are twofold, one, to measure the concentrations of PM₁₀ (<10  $\upmu $ m), PM_2.5 (<2.5  $\upmu $ m), and PM_1.0 (<1.0  $\upmu $ m) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM₁₀ (NVIAQM_pm10), PM_2.5 (NVIAQM_pm2.5), and PM_1.0 (NVIAQM_pm1.0) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO₂ concentrations have also been monitored during school hours. Predicted indoor PM₁₀ concentrations show poor correlations with observed indoor PM₁₀ concentrations (R ² = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM_pm2.5 and NVIAQM_pm1.0 results show good correlations with observed concentrations of PM_2.5 (R ² = 0.87 for weekdays and 0.9 for weekends) and PM_1.0 (R ² = 0.86 for weekdays and 0.87 for weekends). NVIAQM_pm10 shows the tendency to underpredict indoor PM₁₀ concentrations during weekdays as it does not take into account the occupant??s activities and its effects on the indoor concentrations during the class hours. Intense occupant??s activities cause resuspension or delayed deposition of PM₁₀. The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant??s activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R _c. The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R _c (0.001 to 0.500) significantly affects the model performance.     

Nutraceuticals and mitochondrial oxidative stress: bridging the gap in the management of bronchial asthma

Environmental Science and Pollution Research - Asthma is a chronic inflammatory disease primarily characterized by inflammation and reversible bronchoconstriction. It is currently one of the...     

Distribution and correlation of radon and uranium and associated hydrogeochemical processes in alluvial aquifers of northwest India

Environmental Science and Pollution Research - The spatial and vertical distributions of radon and uranium are evaluated in relation to the hydrogeology, geomorphology, and hydrochemistry of...     

Synthesis of highly fluorescent and water soluble graphene quantum dots for detection of heavy metal ions in aqueous media

Environmental Science and Pollution Research - Fluorescent graphene quantum dots (GQDs) are nanomaterials which possess unique properties that show great potential in different applications. In...     

Soil carbon and nitrogen in 28-year-old land uses in reclaimed coal mine soils of Ohio

Carbon (C) and nitrogen (N) play an important role in the restoration of ecosystem functions of reclaimed mine soils (RMSs). Postreclamation land use in RMSs affects soil C and N pools and fluxes. We compared the effects of 28-yr-old postreclamation land uses (forest, hay, and pasture) on selected chemical properties of soil, and C and N pools in reference to undisturbed forest and moderately disturbed agricultural land use in southeastern Ohio. The electrical conductivity was higher in RMSs under hay than that in pasture and forest land uses. The RMSs under pasture, hay, and forest had moderately acidic, neutral to slightly alkaline, and slightly alkaline pH, respectively. In the 0- to 5-cm soil depth, soil organic C (SOC) was higher in RMSs under pasture by 99% and under hay by 52% over that under forest. Similarly, total nitrogen (TN) was higher in RMSs under pasture by 98% and under hay by 43% over that under forest. Aggregate-associated SOC concentration in the 0- to 5-cm depth decreased in the order of RMSs under hay > RMSs under pasture > RMSs under forest. The SOC pools in the 0- to 30-cm depth decreased in the order of RMSs under hay = RMSs under pasture > RMSs under forest = undisturbed forest = agriculture land use. Nitrogen pools followed a similar trend. Hay land use has a better potential for improving soil quality in RMSs by enhancing chemical properties and SOC and TN pools than forest or pasture land uses.     

Supply responses in tropical forestry: A Malaysian case study

The rapid exhaustion of Malaysia's commercial primaeval forest base has raised questions regarding the management and economic responses in the sector. The article assesses the institutional and management structure of Malaysian forestry which, together with the social and political barriers at work, prevent an orderly programme of harvesting and reforestation. The supply is then set out in terms of an econometric model, formulated both in static and dynamic terms to measure, among other things, the responses of output to price changes. The model, which is the first of its kind to be tested for the Malaysian forestry sector, is applied on three wood-based commodities — sawlogs, sawnwood and plywood. To learn of possible regional variations, the model is also applied to data of the country's three principal components — Peninsular Malaysia, Sarawak and Sabah. The results indicate that short-run price elasticities of supply are low, and in some cases, even contrary to expectations based on economic theory. Allowing for data inconsistencies, the slow responses of output to changes in price may be attributed to the method of wood disposal, its timing as well as the social and political barriers to entry at work in the sector.     

GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

ABSTRACT: Genetic Programming (GP) is a domain‐independent evolutionary programming technique that evolves computer programs to solve, or approximately solve, problems. To verify GP's capability, a simple example with known relation in the area of symbolic regression, is considered first. GP is then utilized as a flow forecasting tool. A catchment in Singapore with a drainage area of about 6 km² is considered in this study. Six storms of different intensities and durations are used to train GP and then verify the trained GP. Analysis of the GP induced rainfall and runoff relationship shows that the cause and effect relationship between rainfall and runoff is consistent with the hydrologic process. The result shows that the runoff prediction accuracy of symbolic regression based models, measured in terms of root mean square error and correlation coefficient, is reasonably high. Thus, GP induced rainfall runoff relationships can be a viable alternative to traditional rainfall runoff models.