Fine Particles (PM2.5) in Residential Areas of Lucknow City and Factors Influencing the Concentration

Urban populations are exposed to a high level of fine and ultrafine particles from motor vehicle emissions which affect human health. To assess the hourly variation of fine particle (PM_2.5) concentration and the influence of temperature and relative humidity (RH) on the ambient air of Lucknow city, monitoring of PM_2.5 along with temperature and RH was carried out at two residential locations, namely Vikas Nagar and Alambagh, during November 2005. The 24 h mean PM_2.5 concentration at Alambagh was 131.74 μg/m³ and showed an increase of 13.74%, which was significantly higher (p < 0.05) than the Vikas Nagar level. The 24 h mean PM_2.5 on weekdays for both locations was found to be 142.74 μg/m³ (an increase of 66.23%) which was significantly higher (p < 0.01) than the weekend value, indicating that vehicular pollution is one of the important sources of PM_2.5. The mean PM_2.5 at night for all the monitoring days was 157.69 μg/m³ and was significantly higher (p < 0.01) than the daytime concentration (89.87 μg/m³). Correlation and multiple regressions showed that the independent variables, i. e., time, temperature, and RH together accounted for 54%, whereas RH alone accounted for 53% of total variations of PM_2.5, suggesting that RH is the best influencing variable to predict the PM_2.5 concentration in the urban area of Lucknow city. The 24 h mean PM_2.5 for all the monitoring days was found to be higher than the NAAQS recommended by the US‐EPA (65 μg/m³) and can be considered to be an alarming indicator of adverse health effects for city dwellers.     

Atmospheric Particulate Concentration Measured in an Urban Area Bandung

— Atmospheric particulate concentration for total suspended particles (TSP) and for PM₁₀ (particulate matter under 10 micron) was measured in Jalan Braga and ITB campus, Bandung. Six samples were collected over one- or two-day time periods using High Volume Sampler (HVS) for TSP and Low Volume Sampler (LVS) or Anderson Cascade Impactor for PM₁₀. Samples were further analyzed to determine concentrations of metals, sulfate and nitrate. Concentration of NO_x (NO and NO₂) was also measured hourly and simultaneously during the sampling period. The results from this study show that the atmospheric particulate concentration in Jalan Braga for TSP ranged from 304.04 to 363.17, and for PM₁₀ concentration ranged from 277.02 to 336.44 μg/m³. The lead concentrations were 1.42–2.37 μg/m³ in the TSP and 0.81–1.57 μg/m³ in the PM₁₀. The nitrate concentrations were 5.89–6.51 μg/m³ and 2.27–3.45 μg/m³ for the TSP and PM₁₀, respectively. The hourly NO_x concentration varied between 0.14–0.35 ppm. The total elements (metals, sulfate and nitrate) found in the samples contribute from 20 to 25% of the total particulate concentration.     

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi-Natural Experiment

In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM₁₀ (27%), PM_2.5 (19%), NO₂ (74%), SO₂ (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m⁻³ in PM₁₀, 23 µg m⁻³ in PM_2.5, 14 µg m⁻³ in NO₂, 2 µg m⁻³ in SO₂, and 0.7 mg m⁻³ in CO can be achieved.     

Source apportionment and secondary organic aerosol estimation of PM2.5 in an urban atmosphere in China

PM2.5 is the key pollutant in atmospheric pollution in China.With new national air quality standards taking effect,PM2.5 has become a major issue for future pollution control.To effectively prevent and control PM2.5,its emission sources must be precisely and thoroughly understood.However,there are few publications reporting comprehensive and systematic results of PM2.5 source apportionment in the country.Based on PM2.5 sampling during 2009 in Shenzhen and follow-up investigation,positive matrix factorization(PMF)analysis has been carried out to understand the major sources and their temporal and spatial variations.The results show that in urban Shenzhen(University Town site),annual mean PM2.5 concentration was 42.2μg m?3,with secondary sulfate,vehicular emission,biomass burning and secondary nitrate as major sources;these contributed30.0%,26.9%,9.8%and 9.3%to total PM2.5,respectively.Other sources included high chloride,heavy oil combustion,sea salt,dust and the metallurgical industry,with contributions between 2%–4%.Spatiotemporal variations of various sources show that vehicular emission was mainly a local source,whereas secondary sulfate and biomass burning were mostly regional.Secondary nitrate had both local and regional sources.Identification of secondary organic aerosol(SOA)has always been difficult in aerosol source apportionment.In this study,the PMF model and organic carbon/elemental carbon(OC/EC)ratio method were combined to estimate SOA in PM2.5.The results show that in urban Shenzhen,annual SOA mass concentration was 7.5μg m?3,accounting for 57%of total organic matter,with precursors emitted from vehicles as the major source.This work can serve as a case study for further in-depth research on PM2.5 pollution and source apportionment in China.     

Black carbon aerosols and their radiative properties in the Pearl River Delta region

The climatic and environmental effects of atmospheric aerosols are a hot topic in global science community, and radiative properties of the aerosols are one of the important parameters in assessing climatic change. Here we studied the black carbon concentration and absorption coefficient measured with aethalometers, scattering coefficient measured with nephelometers, and single scattering albedo derived at an atmospheric composition watch station in Guangzhou from 2004 to 2007. Our main results are as follows. The data of black carbon concentration and absorption coefficients measured with instruments cannot be directly used until they are measured in parallel with internationally accepted instruments for comparison, calibration, and reduction. After evaluation of the data, the result shows that the monthly mean of BC concentration varies 3.1–14.8 μg·m⁻³ and the concentration decreases by about 1 μg·m⁻³ in average over the four years; It is higher in the dry season with a multi-year mean of 8.9 μg/m³ and lower in the rainy season with a multi-year mean of 8.0 μg·m⁻³; The extreme maximum of monthly mean concentration occurred in December 2004 and extreme minimum in July 2007, and a 4-year mean is 8.4 μg·m⁻³. It is also shown that monthly mean scattering coefficient derived varies 129 −565 Mm⁻¹, monthly mean absorption coefficient 32–139 Mm⁻¹, and monthly mean single scattering albedo 0.71–0.91, with annual mean values of 0.80, 0.82, 0.79 and 0.84 for 2004, 2005, 2006 and 2007, respectively. Three instruments were used to take simultaneous measurements of BC in PM₁₀, PM_2.5, and PM₁ and the results showed that PM_2.5 took up about 90% of PM₁₀ and PM₁ accounted for about 68% of PM_2.5, and BC aerosols are mainly present in fine particulates. The variability of BC concentrations is quite consistent between the Nancun station (141 m above sea level) and the Panyu station (13 m above sea level), which are 8 km apart from each other. The concentration in higher altitude station (Panyu) is consistently lower than the lower altitude station (Nancun), and the difference of annual mean is about 4 μg·m⁻³. Supported by Natural Science Foundation of China (Grant Nos. U0733004, 40375002, 40418008, 40775011), National High Technology R & D Program of China (Grant Nos. 2006AA06A306 and 2006AA06A308) and National Basic Research Program of China (Grant No. 2005CB422207)     

Predicting spatio-temporal concentrations of PM<Subscript>2.5</Subscript> using land use and meteorological data in Yangtze River Delta,China

The prediction of PM_2.5 concentrations with high spatiotemporal resolution has been suggested as a potential method for data collection to assess the health effects of exposure. This work predicted the weekly average PM_2.5 concentrations in the Yangtze River Delta, China, by using a spatio-temporal model. Integrating land use data, including the areas of cultivated land, construction land, and forest land, and meteorological data, including precipitation, air pressure, relative humidity, temperature, and wind speed, we used the model to estimate the weekly average PM_2.5 concentrations. We validated the estimated effects by using the cross-validated R² and Root mean square error (RMSE); the results showed that the model performed well in capturing the spatiotemporal variability of PM_2.5 concentration, with a reasonably large R² of 0.86 and a small RMSE of 8.15 (μg/m³). In addition, the predicted values covered 94% of the observed data at the 95% confidence interval. This work provided a dataset of PM_2.5 concentration predictions with a spatiotemporal resolution of 3 km × week, which would contribute to accurately assessing the potential health effects of air pollution.     

Lead concentrations and isotopes in aerosols from Xiamen, China

To investigate the magnitude and origin of lead (Pb) pollution in the atmosphere of Xiamen, China, 40 aerosol samples were collected from the coast of Xiamen from January to December 2003. All these samples were measured for Pb isotopic compositions (²⁰⁸Pb/²⁰⁶Pb = 2.10897 ± 0.00297, ²⁰⁷Pb/²⁰⁶Pb = 0.85767 ± 0.00159, n = 40) using a Multi-collector-Inductively Coupled Plasma Mass Spectrometer (MC-ICPMS). Thirty-five out of forty samples were also measured for Pb concentrations (79.1 ± 38.3 ng/m³, n = 35) by Atomic Absorption Spectroscopy (AAS). The results indicate that the Pb concentrations display significant seasonal variations while Pb isotopic ratios remain relatively constant. The Pb concentrations were high in January and February, abruptly decreased in March, remained relatively constant (but low) from April to August, and then gradually increased from September to December. This corresponds to the rainless climate in winter and rain scavenging in summer. The higher Pb concentration of Xiamen aerosols in winter and spring may be also caused by long-range transferred anthropogenic Pb during the northeastern monsoon seasons. Although the use of leaded gasoline in Xiamen was banned in 2000, our new data indicate that the Pb annual concentrations of aerosols in Xiamen increased about 12% when compared to the data measured between 1991 and 1993. Thus, Pb pollution in the atmosphere of Xiamen has not receded even after the phase-out of leaded gasoline. Our results further confirm the previous studies’ conclusion that the primary source of atmospheric Pb in China, especially in South China, is the vast combustion of lead-containing coal, not leaded gasoline.     

Estimation of the PM2.5 effective hygroscopic parameter and water content based on particle chemical composition: Methodology and case study

Particle hygroscopicity plays a key role in understanding the mechanisms of haze formation and particle optical properties. The present study developed a method for predicting the effective hygroscopic parameter k and the water content of PM_(2.5) on the basis of the k-K?hler theory and bulk chemical components of PM_(2.5). Our study demonstrated that the effective hygroscopic parameter can be estimated using the PM_(2.5) mass concentration, water-soluble ions, and total water-soluble carbon. By combining the estimated k and ambient relative humidity, the water content of PM_(2.5) can be further estimated. As an example, the k and water content of PM_(2.5) in Beijing were estimated utilizing the method proposed in this study. The annual average value of k of PM_(2.5) in Beijing was 0.25±0.09, the maximum k value 0.26±0.08 appeared in summer, and the seasonal variation is insignificant. The PM_(2.5) water content was determined by both the PM_(2.5) hygroscopicity and the ambient relative humidity(RH). The annual average mass ratio of water content and PM_(2.5) was 0.18±0.20, and the maximum value 0.31±0.25 appeared in summer. Based on the estimated water content of PM_(2.5) in Beijing, the relationship between the PM_(2.5) water content and RH was parameterized as: m(%)=0.03+(5.73×10~(-8)) ×RH~(3.72).This parametric formula helps to characterize the relationship between the PM_(2.5) mass concentration and atmospheric visibility.     

Three-dimensional analysis of ozone and PM<Subscript>2.5</Subscript> distributions obtained by observations of tethered balloon and unmanned aerial vehicle in Shanghai,China

A lightweight unmanned aerial vehicle (UAV) and a tethered balloon platform were jointly used to investigate three-dimensional distributions of ozone and PM_2.5 concentrations within the lower troposphere (1000 m) at a localized coastal area in Shanghai, China. Eight tethered balloon soundings and three UAV flights were conducted on May 25, 2016. Generalized additive models (GAMs) were used to quantitatively describe the relationships between air pollutants and other obtained parameters. Field observations showed that large variations were captured both in the vertical and horizontal distributions of ozone and PM_2.5 concentrations. Significant stratified layers of ozone and PM_2.5 concentrations as well as wind directions were observed throughout the day. Estimated bulk Richardson numbers indicate that the vertical mixing of air masses within the lower troposphere were heavily suppressed throughout the day, leading to much higher concentrations of ozone and PM_2.5 in the planetary boundary layer (PBL). The NO and NO₂ concentrations in the experimental field were much lower than that in the urban area of Shanghai and demonstrated totally different vertical distribution patterns from that of ozone and PM_2.5. This indicates that aged air masses of different sources were transported to the experimental field at different heights. Results derived from the GAMs showed that the aggregate impact of the selected variables for the vertical variations can explain 94.3% of the variance in ozone and 94.5% in PM_2.5. Air temperature, relative humidity and atmospheric pressure had the strongest effects on the variations of ozone and PM_2.5. As for the horizontal variations, the GAMs can explain 56.3% of the variance in ozone and 57.6% in PM_2.5. The strongest effect on ozone was related to air temperature, while PM_2.5 was related to relative humidity. The output of GAMs also implied that fine aerosol particles were in the stage of growth in the experimental field, which is different from ozone (aged air parcels of ozone). Geographical parameters influenced the horizontal variations of ozone and PM_2.5 concentrations by changing underlying surface types. The differences of thermodynamic properties between land and sea resulted in quick changes of PBL height, air temperature and dew point over the coastal area, which was linked to the extent of vertical mixing at different locations. The results of GAMs can be used to analyze the sources and formation mechanisms of ozone and PM_2.5 pollutions at a localized area.     

Krypton and Xenon Radionuclides Monitoring in the Northwest Region of Russia

Monitoring of Xe and Kr radionuclides was conducted from August 2006 to 30 July 2008 within the framework of ISTC Project #2133. Cherepovets City in Vologda Province and St. Petersburg were chosen as monitoring locations. Kr–Xe concentrate samples were obtained as a result of processing of several thousand m³ of atmospheric air. New results of ⁸⁵Kr monitoring show, that for last 15 years, the ⁸⁵Kr volumetric activity in the atmospheric air of the northwest region of Russia has increased approximately 50% and has achieved a level of 1.5 Bq/m³. This value correlates well with similar data for Western Europe and Japan. The xenon fraction (80–160 cm³ under STP) is adsorbed on charcoal in the ampoule, which is measured in the well of HPGe gamma detector. Minimum detectable concentration (MDC) of ¹³³Xe for this technique is 0.008 mBq/m³, and it is the most sensitive method used today. The ¹³³Xe concentration in the atmospheric air of Cherepovets City varied in the monitoring period ranging from 0.09 to 2.5 mBq/m³. During the period of March 2007–30 July 2008, ¹³³Xe activity concentration in the atmospheric air of St. Petersburg changed from background values (0.2–0.3 mBq/m³) to 185 mBq/m³ and for approximately 20% of the samples ¹³⁵Xe was also measured with the ¹³⁵Xe/¹³³Xe activity ratio varied within the range of 0.03–3.5.     

Mass fraction spatiotemporal geostatistics and its application to map atmospheric polycyclic aromatic hydrocarbons after 9/11

This work proposes a space/time estimation method for atmospheric PM_2.5 components by modelling the mass fraction at a selection of space/time locations where the component is measured and applying the model to the extensive PM_2.5 monitoring network. The method we developed utilizes the nonlinear Bayesian maximum entropy framework to perform the geostatistical estimation. We implemented this approach using data from nine carcinogenic, particle-bound polycyclic aromatic hydrocarbons (PAHs) measured from archived PM_2.5 samples collected at four locations around the World Trade Center (WTC) from September 22, 2001 to March 27, 2002. The mass fraction model developed at these four sites was used to estimate PAH concentrations at additional PM_2.5 monitors. Even with limited PAH data, a spatial validation showed the application of the mass fraction model reduced the mean squared error (MSE) by 7–22%, while in the temporal validation there was an exponential improvement in MSE positively associated with the number of days of PAH data removed. Our results include space/time maps of atmospheric PAH concentrations in the New York area after 9/11.     

Spatial Distribution of SO2, NO2, and O3 Concentrations in an Industrial City of Turkey Using a Passive Sampling Method

Ambient concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) were measured at 51 sampling points by passive sampling technique in Kocaeli, an important industrial city in Turkey. Samples were analyzed by UV‐spectrophotometry for NO₂ and O₃ and by ion chromatography for SO₂, respectively. Concentrations of SO₂, NO₂, and O₃ were determined to investigate their spatial distribution and source characterization. The sampling campaigns revealed an average concentration of 8 µg/m³ (max. 82 µg/m³) for SO₂, and 14 µg/m³ (max. 40 µg/m³) for NO₂, in summer; while average winter concentrations were 25 µg/m³ (max. 61 µg/m³) for SO₂, and 50 µg/m³ (max. 100 µg/m³) for NO₂. The maximum ozone concentrations were determined to be 86 µg/m³ in summer and 61 µg/m³ in winter downwind of the source areas of the precursor pollutant emissions. The results showed that NO₂ and SO₂ concentrations in industrial and urban areas were two to four times higher compared with rural areas in the summer and winter. In the light of the information obtained from the spatial interpolation of the pollutant concentrations, a selection of appropriate locations for continuous monitoring was suggested according to the European Community (EU) directives.     

Artificial Neural Network Prediction of Tropospheric Ozone Concentrations in Istanbul,Turkey

Tropospheric (ground‐level) ozone has adverse effects on human health and environment. In this study, next day's maximum 1‐h average ozone concentrations in Istanbul were predicted using multi‐layer perceptron (MLP) type artificial neural networks (ANNs). Nine meteorological parameters and nine air pollutant concentrations were utilized as inputs. The total 578 datasets were divided into three groups: training, cross‐validation, and testing. When all the 18 inputs were used, the best performance was obtained with a network containing one hidden layer with 24 neurons. The transfer function was hyperbolic tangent. The correlation coefficient (R), mean absolute error (MAE), root mean squared error (RMSE), and index of agreement or Willmott's Index (d₂) for the testing data were 0.90, 8.78 µg/m³, 11.15 µg/m³, and 0.95, respectively. Sensitivity analysis has indicated that the persistence information (current day's maximum and average ozone concentrations), NO concentration, average temperature, PM₁₀, maximum temperature, sunshine time, wind direction, and solar radiation were the most important input parameters. The values of R, MAE, RMSE, and d₂ did not change considerably for the MLP model using only these nine inputs. The performances of the MLP models were compared with those of regression models (i.e., multiple linear regression and multiple non‐linear regression). It has been found that there was no significant difference between the ANN and regression modeling techniques for the forecasting of ozone concentrations in Istanbul.     

Average mass concentrations of TSP, PM10 and PM2.5 in Erzurum urban atmosphere, Turkey

In this study, particulate matters (TSP, PM₁₀, PM_2.5 and PM_10–2.5) which are hazardous for environment and human health were investigated in Erzurum urban atmosphere at a sampling point from February 2005 to February 2006. During sampling, two low volume samplers were used and each sampling period lasted approximately 24 h. In order for detection of representative sampling region and point of Erzurum, Kriging method was applied to the black smoke concentration data for winter seasons. Mass concentrations of TSP, PM₁₀ and PM_2.5 of Erzurum urban atmosphere were measured on average, as 129, 31 and 13 μg/m³, respectively, in the sampling period. Meteorological factors, such as temperature, wind speed, wind direction and rainfall were typically found to be affecting PMs, especially PM_2.5. Air temperature did not seem to be significantly affecting TSP and PM₁₀ mass concentrations, but had a considerably negative induction on PM_2.5 mass concentrations. However, combustion sourced PM_2.5 was usually diluted from the urban atmosphere by the speed of wind, soil sourced coarse mode particle concentrations (TSP, PM₁₀) were slightly affected by the speed of wind. Rainfall was found to be decreasing concentrations to 48% in all fractions (TSP, PM₁₀, PM_10–2.5, PM_2.5) and played an important role on dilution of the atmosphere. Fine mode fraction of PM (PM_2.5) showed significant daily and seasonal variations on mass concentrations. On the other hand, coarse mode fractions (TSP, PM₁₀ and PM_10–2.5) revealed more steady variations. It was observed that fine mode fraction variations were affected by the heating in residences during winter seasons.     

The Airshed for Ozone and Fine Particulate Pollution in the Eastern United States

— To examine the spatial scales associated with atmospheric pollutants such as ozone (O₃) and fine particulate matter (PM_2.5), we employ the following five techniques: (1) Analysis of the persistence of high O₃ concentrations aloft; (2) spatial and lag correlations between the short-term components (i.e., weather-induced variations) in the time series of O₃ and PM_2.5 throughout the eastern United States; (3) analysis of mixed-layer forward trajectories compiled at different locations on a climatological basis to identify the potential region covered in 1-day of atmospheric transport; (4) analysis of three-dimensional Lagrangian trajectories of tracer particles for three high-O₃ episode events in the summer of 1995; and (5) analysis of the spatial extent over which emissions have an impact through photochemical model simulations. Regardless of the method chosen, the results demonstrate that pollutants such as O₃ and PM_2.5 have the potential to affect regions having spatial scales of several hundred kilometers. This finding has implications to regulatory policies for addressing the pollution problem, and for optimally designing monitoring networks for such pollutants.     

The performance of grass filter strips in controlling high‐concentration suspended sediment from overland flow under rainfall/non‐rainfall conditions

There is little information on the performance of vegetative filter strips (VFS) in filtering high‐concentration sediment from subcritical overland flow. Flume experiments on simulated grass strips were conducted using combinations of three slope gradients (3°, 9° and 15°), five 1‐m‐wide slope positions (from upslope to downslope), two flow rates (60 and 20 L min^‐1 m^‐1) and sediment concentrations of 100–300 kg m^‐3 under simulated rainfall and non‐rainfall conditions. The results showed that sediment deposition efficiency increased with VFS width as a power function. Rainfall significantly reduced sediment deposited within VFS. Higher sediment concentration corresponded to a larger sediment deposition load but reduced deposition efficiency. Flow rate had a negative effect on deposition efficiency but no effect on deposition load. Sediments were more easily deposited at the upper slope position than downslope, and the upper slope position had a higher percentage of coarse sediments. The deposited sediment had significantly greater median diameters (D₅₀) than the inflow sediment. A greater proportion of coarse sediments larger than 25 µm in diameter were deposited, and particles smaller than 1 µm and of 10–25 µm had a better deposition performance than particles of 1–10 µm. Rainfall reduced the deposited sediment D₅₀ at a slope gradient of 3° and had no significant influence on it at 9° or 15°. A higher sediment concentration led to a smaller D₅₀ of the deposited sediment. Rainfall had no significant effect on overland flow velocity. Both the deposited sediment load and D₅₀ decreased with increasing flow velocity, and flow velocity was the most sensitive factor impacting sediment deposition. The results from this study should be useful to control sediment flowing into rivers in areas with serious soil erosion. Copyright © 2013 John Wiley & Sons, Ltd.     

Role of Nitrogen Oxides,Black Carbon,and Meteorological Parameters on the Variation of Surface Ozone Levels at a Tropical Urban Site – Hyderabad,India

In this study, temporal variations of surface ozone (O₃) were investigated at tropical urban site of Hyderabad during the year 2009. O₃, oxides of nitrogen (NO_x = NO + NO₂), black carbon (BC), and meteorological parameters were continuously monitored at the established air monitoring station. Results revealed the production of surface O₃ from NO₂ through photochemical oxidation. Averaged datasets illustrated the variations in ground‐level concentrations of these air pollutants along different time scales. Maximum mean concentrations of O₃ (56.75 ppbv) and NO_x (8.9 ppbv) were observed in summer. Diurnal‐seasonal changes in surface O₃ and NO_x concentrations were explicated with complex atmospheric chemistry, boundary layer dynamics, and local meteorology. In addition, nocturnal chemistry of NO_x played a decisive role in the formation of O₃ during day time. Mean BC mass concentration in winter (10.92 µg m^?3) was high during morning hours. Heterogeneous chemistry of BC on O₃ destruction and NO_x formation was elucidated. Apart from these local observations, long‐range transport of trace gases and BC aerosols were evidenced from air mass back trajectories. Further, statistical modeling was performed to predict O₃ using multi‐linear regression method, which resulted in 91% of the overall variance.     

Field Study of Vertical Screening Distance Criteria for Vapor Intrusion of Ethylene Dibromide

Several regulatory agencies recommend screening petroleum vapor intrusion (PVI) sites based on vertical screening distance between a petroleum hydrocarbon source in soil or groundwater and a building foundation. U.S. Environmental Protection Agency (U.S. EPA) indicate the risk of PVI is minimal at buildings that are separated by more than 6 feet (1.8 m) from a dissolved-phase source and 15 feet (4.6 m) from a light nonaqueous phase liquid (LNAPL) source. This vertical screening distance method is not, however, recommended at sites with leaded gasoline sources containing ethylene dibromide (EDB) because of a lack of field data to document EDB attenuation in the vadose zone. To help address this gap, depth-discrete soil-gas samples were collected at a leaded gasoline release site in Sobieski, Minnesota (USA). The maximum concentration of EDB in groundwater (175 μg/L) at the site was high relative to those observed at other leaded gasoline release sites. Soil gas was analyzed for EDB using a modification of U.S. EPA Method TO-14A that achieved analytical detection limits below the U.S. EPA Vapor Intrusion Screening Level (VISL) for EDB based on a 10⁻⁶ cancer risk (<0.16 μg/m³). Concentrations of EDB in soil gas above LNAPL reached as high as 960 μg/m³ and decreased below the VISL within a source-separation distance of 7 feet. This result coupled with BioVapor model predictions of EDB concentrations indicate that vertical screening distances recommended by regulatory agencies at PVI sites are generally applicable for EDB over the range of anticipated source concentrations and soil types at most sites.     

Environmental Factors Associated With Natural Methane Occurrence in the Appalachian Basin

The recent boom in shale gas development in the Marcellus Shale has increased interest in the methods to distinguish between naturally occurring methane in groundwater and stray methane associated with drilling and production operations. This study evaluates the relationship between natural methane occurrence and three principal environmental factors (groundwater redox state, water type, and topography) using two pre‐drill datasets of 132 samples from western Pennsylvania, Ohio, and West Virginia and 1417 samples from northeastern Pennsylvania. Higher natural methane concentrations in residential wells are strongly associated with reducing conditions characterized by low nitrate and low sulfate ([NO₃^?] < 0.5 mg/L; [SO₄^2?] < 2.5 mg/L). However, no significant relationship exists between methane and iron [Fe(II)], which is traditionally considered an indicator of conditions that have progressed through iron reduction. As shown in previous studies, water type is significantly correlated with natural methane concentrations, where sodium (Na) ‐rich waters exhibit significantly higher (p<0.001) natural methane concentrations than calcium (Ca)‐rich waters. For water wells exhibiting Na‐rich waters and/or low nitrate and low sulfate conditions, valley locations are associated with higher methane concentrations than upland topography. Consequently, we identify three factors (“Low NO₃^? & SO₄^2?” redox condition, Na‐rich water type, and valley location), which, in combination, offer strong predictive power regarding the natural occurrence of high methane concentrations. Samples exhibiting these three factors have a median methane concentration of 10,000 µg/L. These heuristic relationships may facilitate the design of pre‐drill monitoring programs and the subsequent evaluation of post‐drill monitoring results to help distinguish between naturally occurring methane and methane originating from anthropogenic sources or migration pathways.