Emission,speciation, and evaluation of impacts of non-methane volatile organic compounds from open dump site

Surface emission from Dhapa, the only garbage disposal ground in Kolkata, is a matter of concern to the local environment and also fuels the issues of occupational and environmental health. Surface emission of the Dhapa landfill site was studied using a flux chamber measurement for nonmethane volatile organic compounds (NMVOCs). Eighteen noncarbonyl volatile organic compounds (VOCs) and 14 carbonyl VOCs, including suspected and known carcinogens, were found in appreciable concentrations. The concentrations of the target species in the flux chamber were found to be significantly higher for most of the species in summer than winter. Surface emission rate of landfill gas was estimated by using two different approaches to assess the applicability for an open landfill site. It was found that the emissions predicted using the model Land GEM version 3.02 is one to two orders less than the emission rate calculated from flux chamber measurement for the target species. Tropospheric ozone formation has a serious impact for NMVOC emission. The total ozone-forming potential (OFP) of the Dhapa dumping ground considering all target NMVOCs was estimated to be 4.9E+04 and 1.2E+05 g/day in winter and summer, respectively. Also, it was found that carbonyl VOCs play a more important role than noncarbonyl VOCs for tropospheric ozone formation. Cumulative cancer risk estimated for all the carcinogenic species was found to be 2792 for 1 million population, while the total noncancer hazard index (HI) was estimated to be 246 for the occupational exposure to different compounds from surface emission to the dump-site workers at Dhapa.

Implications:This paper describes the real-time surface emission of NMVOCs from an open municipal solid waste (MSW) dump site studied using a flux chamber. Our study findings indicate that while planning for new landfill site in tropical meteorology, real-time emission data must be considered, rather than relying on modeled data. The formation of tropospheric ozone from emitted NMVOC has also been studied. Our result shows how an open landfill site acts as a source and adds to the tropospheric ozone for the airshed of a metropolitan city.     

Major ionic compositions of fine particulate matter in an animal feeding operation facility and its vicinity

Animal feeding operations (AFOs) produce particulate matter (PM) and gaseous pollutants. Investigation of the chemical composition of PM_2.5 inside and in the local vicinity of AFOs can help to understand the impact of the AFO emissions on ambient secondary PM formation. This study was conducted on a commercial egg production farm in North Carolina. Samples of PM_2.5 were collected from five stations, with one located in an egg production house and the other four located in the vicinity of the farm along four wind directions. The major ions of NH₄⁺, Na⁺, K⁺, SO₄^2?, Cl^?, and NO₃^? were analyzed using ion chromatography (IC). In the house, the mostly abundant ions were SO₄^2?, Cl^?, and K⁺. At ambient stations, SO₄^2?, and NH₄⁺ were the two most abundant ions. In the house, NH₄⁺, SO₄^2?, and NO₃^? accounted for only 10% of the PM_2.5 mass; at ambient locations, NH₄⁺, SO₄^2?, and NO₃^? accounted for 36–41% of the PM_2.5 mass. In the house, NH₄⁺ had small seasonal variations indicating that gas-phase NH₃ was not the only major force driving its gas–particle partitioning. At the ambient stations, NH₄⁺ had the highest concentrations in summer. In the house, K⁺, Na⁺, and Cl^? were highly correlated with each other. In ambient locations, SO₄^2? and NH₄⁺ had a strong correlation, whereas in the house, SO₄^2? and NH₄⁺ had a very weak correlation. Ambient temperature and solar radiation were positively correlated with NH₄⁺ and SO₄^2?. This study suggests that secondary PM formation inside the animal house was not an important source of PM_2.5. In the vicinity, NH₃ emissions had greater impact on PM_2.5 formation.

ImplicationsThe chemical composition of PM_2.5 inside and in the local vicinity of AFOs showed the impact of the AFO emissions on ambient secondary PM_2.5 formation, and the fate and transport of air pollutants associated with AFOs. The results may help to manage in-house animal facility air quality, and to develop regional air quality control strategies and policies, especially in animal agriculture-concentrated areas.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

NAPL migration and ecotoxicity of conventional and renewable fuels in accidental spill scenarios

Fuels derived from non-petroleum renewable resources have raised interest due to their potential in replacing petroleum-based fuels, but information on their fate and effects in the terrestrial and aquatic environments in accidental spill scenario is limited. In this study, migration of four fuels (conventional diesel, conventional gasoline, renewable diesel NExBTL, and ethanol-blended gasoline RE85 containing maximum 85 % ethanol) as non-aqueous phase liquids (NAPL) in soil was demonstrated in a laboratory-scale experiment. Ecotoxicity data was produced for the same fuels. There was no significant difference in migration of conventional and renewable diesel, but gasoline migrated 1.5 times deeper and 7–9 times faster in sand than diesel. RE85 spread horizontally wider but not as deep (p?Eisenia fetida followed by ethanol-blended gasoline (LC50 1,643 mg/kg THC) and conventional diesel (LC50 2,432 mg/kg THC), although gasoline evaporated fast from soil. For comparison, the toxicity of the water-accommodated fractions (WAF) of the fuels was tested with water flea Daphnia magna and Vibrio fischeri, also demonstrating groundwater toxicity. The WAF of conventional gasoline and RE85 showed almost similar toxicity to both the aquatic test species. EC50 values of 1:10 (by volume) WAF were 9.9 %WAF (gasoline) and 9.3 %WAF (RE85) to D. magna and 9.3 %WAF (gasoline) and 12.3 %WAF (RE85) to V. fischeri. Low solubility decreased toxicity potential of conventional diesel in aquatic environment, but direct physical effects of oil phase pose a threat to organisms in nature. Renewable diesel NExBTL did not show clear toxicity to any test species.     

Estimated crop yield losses due to surface ozone exposure and economic damage in India

In this study, we estimate yield losses and economic damage of two major crops (winter wheat and rabi rice) due to surface ozone (O₃) exposure using hourly O₃ concentrations for the period 2002–2007 in India. This study estimates crop yield losses according to two indices of O₃ exposure: 7-h seasonal daytime (0900–1600 hours) mean measured O₃ concentration (M7) and AOT40 (accumulation exposure of O₃ concentration over a threshold of 40 parts per billion by volume during daylight hours (0700–1800 hours), established by field studies. Our results indicate that relative yield loss from 5 to 11 % (6–30 %) for winter wheat and 3–6 % (9–16 %) for rabi rice using M7 (AOT40) index of the mean total winter wheat 81 million metric tons (Mt) and rabi rice 12 Mt production per year for the period 2002–2007. The estimated mean crop production loss (CPL) for winter wheat are from 9 to 29 Mt, account for economic cost loss was from 1,222 to 4,091 million US$ annually. Similarly, the mean CPL for rabi rice are from 0.64 to 2.1 Mt, worth 86–276 million US$. Our calculated winter wheat and rabi rice losses agree well with previous results, providing the further evidence that large crop yield losses occurring in India due to current O₃ concentration and further elevated O₃ concentration in future may pose threat to food security.     

The effect of aerosol optical depth on rainfall with reference to meteorology over metro cities in India

Rainfall is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment’s impact on rainfall will be increasingly important in ongoing climate diagnostics and prediction. Aerosol optical depth (AOD) measurements on the monsoon seasons of the years 2008 to 2010 were made over four metro regional hotspots in India. The highest average of AOD was in the months of June and July for the four cities during 3 years and lowest was in September. Comparing the four regions, Kolkata was in the peak of aerosol contamination and Chennai was in least. Pearson correlation was made between AOD with climatic parameters. Some changes in the parameters were found during drought year. Temperature, cloud parameters, and humidity play an important role for the drought conditions. The role of aerosols, meteorological parameters, and their impacts towards the precipitation during the monsoon was studied.     

Potential use of Caulerpa fastigiata biomass for removal of lead: kinetics, isotherms, thermodynamic, and characterization studies

The present study attempts to analyze the biosorption trend of biosorbent Caulerpa fastigiata (macroalgae) biomass for removal of toxic heavy metal ion Pb (II) from solution as a function of initial metal ion concentration, pH, temperature, sorbent dosage, and biomass particle size. The sorption data fitted with various isotherm models and Freundlich model was the best one with correlation coefficient of 0.999. Kinetic study results revealed that the sorption data on Pb (II) with correlation coefficient of 0.999 can best be represented by pseudo-second-order. The biosorption capacity (q _e ) of Pb (II) is 16.11?±?0.32 mg g^?1 on C. fastigiata biomass. Thermodynamic studies showed that the process is exothermic (ΔH° negative). Free energy change (ΔG°) with negative sign reflected the feasibility and spontaneous nature of the process. The SEM studies showed Pb (II) biosorption on selective grains of the biosorbent. The FTIR spectra indicated bands corresponding to –OH, COO^?, –CH, C?=?C, C?=?S, and –C–C– groups were involved in the biosorption process. The XRD pattern of the C. fastigiata was found to be mostly amorphous in nature.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

Nutrient baselines of Cerrado low-order streams: comparing natural and impacted sites in Central Brazil

The aquatic systems responsible for water supply in the Brazilian Federal District (FD) have been threatened by anthropogenic pressures, especially considering the expressive demographic increase in the region during the last decades. The purposes of this research were: (a) to assess the water quality in streams located in the FD by monitoring physical–chemical variables; (b) to define baselines for these variables among different ecological status categories. The 14 investigated streams were sampled between 2006 and 2009, in the dry (August–September, 2006, 2008, 2009) and rainy (March–April, 2008, 2009) seasons. All sampling sites were classified in four categories (“very impacted”, “impacted”, “in transition” and “natural”) using an adaptation of a rapid habitat assessment protocol. Differences in water quality among sites were generally well predicted in the four ecological status categories defined by the protocol, which showed a gradient in nutrient concentrations from reference sites classified as “natural” (medians: electrical conductivity?=?7.3 μS cm^?1; nitrate?=?0.040 mg L^?1; ammonium?=?0.039 mg L^?1; soluble reactive phosphorus (SRP)?=?<0.001 mg L^?1; total phosphorus (TP)?=?0.006 mg L^?1; ) to those classified as “very impacted” (medians: electrical conductivity?=?87.7 μS cm^?1; nitrate?=?0.247 mg L^?1; ammonium?=?0.219 mg L^?1; SRP?=?0.010 mg L^?1; TP?=?0.035 mg L^?1). Point sources inputs were the main factor for water quality deterioration. The nutrient baselines reported were relatively low when compared to data collected from reference areas in Brazil (e.g., São Paulo State) or temperate regions, especially for TP.     

Spatial and temporal variability of metals in inter-tidal beach sediment of Mumbai, India

Nine metals were monitored in the beach sediment in Mumbai from May 2011 to March 2012 to evaluate the spatial and temporal distributions. The average heavy metal concentrations exhibited the following order: Fe > Mn > Cr > Co > Ni > Pb > Zn > Cu > Cd for the four sampling sites. The mean concentrations (± SD) of Fe, Mn, Cr, Co, Ni, Pb, Zn, Cu and Cd were estimated to be 31.15?±?10.02 g kg^?1, 535.04?±?76.42, 151.98?±?97.90, 92.76?±?14.18, 67.52?±?11.32, 59.57?±?15.19, 54.65?±?15.01, 32.24?±?8.07 and 18.75?±?1.76 mg kg^?1, respectively. The results indicated that the sediments were polluted with Cd, Cr, Co and Pb due to high anthropogenic influences. Spatial variation of metals revealed that most of the metals were high in Dadar beach and low in Aksa beach. Cd was the highest contaminant metal studied with a mean contamination factor of 93.75. The pollution load indices of the studied beaches ranged from 1.63 (Aksa) to 1.91 (Dadar) and indicated that the beach sediments were polluted with heavy metals. The heavy metal contents increased in relation to monsoon, and most of the heavy metals showed significantly high concentrations in November during the post-monsoon. The statistical analysis revealed significant effect of study site on all the metals studied. Further, there was a significant difference on metal accumulation on bimonthly basis in relation to weather pattern in Mumbai beaches.