Using the calculated health impacts, economiccosts can be associated with these lives lost or impacted. BenMAP-CE includes the Cost of Illness metric, which represents the cost of hospital admissions, emergency room visits, work loss days, and medical bills related to poor air quality (OAR US EPA 2016b). Furthermore, BenMAP-CE estimates economic values from pollution with a Willingness to Pay metric, which incorporates the Cost of Illness metrics as well as the economic value of pain and dissatisfaction (OAR US EPA 2016b). A Value of Statistical Life (VSL) can also be used to calculate the cost of avoided premature loss of life. VSL is the dollar value associated with the amount a population is willing to pay to slightly decrease the risk of death (OAR US EPA 2016b). From these values, future policy can be assessed relative to this issue or a benefit cost analysis can be derived from this study related to the cost of natural gas to better incorporate the cost environmental externalities.
GIFT2008, and 5d. PA2007). The Health Impact Functions (HIF) are displayed across the top of each table. The HIFs are Krewski: adult mortality low range, Lepeule: adult mortality high range, Infant: infant mortality, Cardio.: hospital admissions for cardiovascular diseases except heart attack, and Resp.: hospital admissions for respiratory diseases including asthma. In parentheses behind each HIF is the age range of that HIF. The top row of values for each HIF represents the middle best estimate. The bottom row of values for each HIF represents a range from the lower 2.5 percentile to the upper 97.5 percentile. The tables are split into two sections. The top section shows the number of health impact incidences per 1 million people in the age range of the respective HIF, rounded to the nearest integer. The bottom section shows the valuation of the respective health impacts in 2010 US dollars, in thousands of dollars. Each section has five sets of values: Min (the CMAQ cell with the lowest value in the HIF), Max (the CMAQ cell with the highest value), Total (the sum of the values of all CMAQ cells), Avg (the average value of the CMAQ cells), and StDev (the standard deviation of values of CMAQ cells).
methane leakage, natural gas as a bridge fuel to a cleaner energy future, the potential for a U.S. manufacturing renaissance based on expanded natural gas production, the potential economic impacts should the U.S. expand natural gas exports, and methodological approaches to understanding and managing human health risks. While not exhaustive, these issues are central to the national debate and discourse regarding the challenges and opportunities of expanded shale gas production. For many of the topics, the results presented in the literature are mixed or uncertain due to the application of different methodological approaches, datasets, scenario assumptions, and other factors. In other areas, there are clearer indications of outcomes such as existing opportunities to reduce GHG emissions through existing technology and best practices, the influence of federal renewable mandates for transitioning to low- or zero-carbon technologies, economic benefits for gas-intensive industries from lower gas prices, and the price effects of expanding natural gas exports.
transportation sector is a large source of these emissions and is expected to continue growing as globalization persists. Within the US, the expanding development of the natural gas industry is helping to support many industries and leading to increased transportation. The process of HighVolumeHydraulicFracturing (HVHF) is one of the newer advanced extraction techniques that is increasing natural gas and oil reserves dramatically within the US, however the technique is very resource intensive. HVHF requires large volumes of water and sand per well, which is primarily transported by trucks in rural areas. Trucks are also used to transport waste away from HVHF well sites. This study focused on the emissions generated from the transportation of HVHF materials to remote well sites, dispersion, and subsequent health impacts. The Geospatial Intermodal Freight Transport (GIFT) model was used in this analysis within ArcGIS to identify roadways with highvolume traffic and emissions. High traffic road segments were used as emissions sources to determine the atmospheric dispersion of particulatematter using
Exponent’s Atmospheric Sciences staff has experience serving a wide range of industrial and government clients around the world. Team members have been influential in the evolution of air quality modeling. Exponent scientists have participated in the original development of, or contributed to, five of the seven U.S. EPA models recommended in the Guideline on Air Quality Models. Most notable of these is the CALPUFF model, an advanced non-steady-state meteorological and air quality modeling system recommended by the EPA as the preferred model for assessing long-range transport of pollutants and their impacts on Federal Class I areas or for near-field applications involving complex
of the microorganisms 86 or growth medium leaching from the mats to the test medium. Our approach was to treat the first cycle as a wash and adaption step and exclude it from further rate evaluation. After several successive loadings, the biodegradation performance decreased with a steeper decrease at higher TDS concentrations. This behavior could be a result of a reduction in mat activity due to nutrient limitation, salinity stresses, or starvation between cycles. The highest biodegradation rates were observed at 0 and 50,000 mg/L TDS conditions for both acetate and guar gum. The 100,000 mg/L TDS condition exhibited a decreased rate, and no biological substrate removal was observed in the 200,000 mg/L TDS condition. Tests in real produced water reflected trends observed in synthetic produced water. A similar trend was seen in real produced water experiments, where the performance of mats decreased in Sample A 1/2 (91,351 mg/L TDS) and no biodegradation occurred in Sample A (182,702 mg/L TDS), similar to the test conditions with salt concentrations of 100,000 and 200,000 mg/L TDS, respectively. Improved COD removal in real produced water is likely due to constituents in the produced water, such as trace minerals, organics, nutrients, or salts. Additionally, it has been shown that trace minerals (e.g. Mg, Fe) have a significant effect on cell viability during starvation conditions. 87 As demonstrated by biofilms treating synthetic produced water, salinity had a strong role in driving the performance of the mats. In real produced water, uncharacterized compounds, including biocides, may have influenced the performance; however, these results demonstrate the ability of biofilms to perform in actual produced water samples.
Studies concerning 236 water wells in Pavil- lion, Wyoming in the USA indicated elevated pH in two wells, high content of potassium and chlo- rides; however, no raised barium on chromium content was observed in any of the considered wells [Di Giulio 2011]. On the other hand, the studies on groundwater in north-east Pennsylva- nia indicated elevated content of chlorides, cal- cium, sodium, and strontium, which is not nec- essarily connected with the shale gas extraction, but mainly stems from the composition of brine in shale formations [Warner 2012].
Before the supplementation with vitamins E and C, TBARS and PC levels were significantly increased, levels of GSH and vitamin E were decreased, while the activities of SOD and CAT were increased in workers and GST was increased in all groups compared to controls . SOD activity was augmented in blood of mining workers with subsequent progression of pneumoconiosis compared with those without progression in a five years of follow-up study , as well as in rat lungs exposed for one week to coal mining ambience . After the antioxidant intervention essentially all these OS biomarkers were normalized to control levels  (see details below). Thus the antioxidant intervention was able to confer a protective effect against the oxidative insult associated with airborne contamination derived fromemissions of an electric power plant, in a way very similar to the results obtained in other projects carried out by our research group involving other chronic diseases, such as chronic cardiopathy associated with Chaga’s disease  and also patients with chronic hepatitis C , using the same protocol for antioxidant intervention.
Future expansion of this work could include modeling each aircraft individually using a plume-in-grid technique, or other alternate approaches to include sub-grid variability, to track the formation of aerosols due to aircraft emissions near the aircraft engine as well as downstream. Specifically, this would include obtaining additional information from previous and ongoing field campaigns that include measurement of volatile components of PM from aircraft engines (Kinsey, 2009) and ongoing projects funded by the Transportation Research Board’s Airport Cooperative Research Program (ACRP) and the U.S. Department of Defense Strategic Environmental Research and Development Program (SERDP), and using this new information to enhance the modeling approaches discussed here. A second expansion would involve including aircraft emissions at cruise altitude as opposed to only up to 10,000 feet. However, modeling at higher altitudes presents a new set of limitations and uncertainties as regional scale models such as the one used here are typically designed to predict surface level concentrations. A final consideration would be to include climate change as part of the future year scenario to access how changes in climate and meteorology would impact the contributions of aviation emissions on future air quality.
We model the decision to ban fracking as an irreversible decision in a context of uncertainty and learning for three reasons. First, in practice, fracking is a relatively new technology and little is known about it 11 . This uncertainty becomes resolved over time as the industry learns best practices, as municipalities learn how to regulate, as the public becomes familiar with the technology, and as the body of scientific analysis grows. Second, the decision to frack for most policymakers today is irreversible. Many of the potential damages associated with fracking (e.g., groundwater contamination) can have irreversible consequences and once fracking is allowed, the industry will resist rule changes after investing in a jurisdiction 12 . Irreversibility aligns our finite horizon dynamic model with the QOV literature, though uncertainty is never completely resolved. Third, fracking moratoria have been successfully enacted or adopted in the US, at both the state and local levels, as well as internationally. These temporary bans represent a delay in an irreversible action and allow the decision to be revisited in the future. The QOV approach to environmental problems says that uncertainty that resolves over time, potentially irreversible environmental damage, and the ability to postpone the decision lead to an additional benefit of delaying a project. In this case, even when the expected net present value of undertaking a project is positive, it may be economically optimal to delay the project and revisit the decision with better information. This model allows us to quantify the value of learning in the context of local fracking decisions and to present a positive economic analysis of its effects on local policy.
major problems in rock fill dams, since it plays a significant role in the initiation and extension of cracks in the clay core. There have been a number of well-studied cases in which dams have failed or been damaged by concentrated leaks for no apparent cause. In some of experiences, investigators concluded that differential settlement cracks were the probable causes, even though no cracks were seen on the surface. Hydraulicfracturing is generally considered as a key cause which may induce the leakage of the dam during first filling. The likelihood of the occurrence of hydraulicfracturing increases with increasing the water level or the crack depth. The lower part of the dam core is the zone in which the phenomenon of hydraulicfracturing may be induced easily. Hence it is necessary that every precaution be taken against leakage to ensure safety of the dam. The investigations of results indicate that hydraulicfracturing in earth and rockfill dams can be controlled and is helpful to reduce the likelihood of the occurrence of hydraulicfracturing by increasing any of Young’s Modulus, increasing the Poisson’s Ratio and increasing the density of core soil
The upper air wind-speed profiles (Figure 4(c)) were accurately captured, but WRF/Chem had some difficul- ties below 2500 m. The overall wind-speed correlation was r = 0.69. The highest correlations occurred above 3000 m where the magnitudes of shear and windspeed variability were least. Simulated and observed regions of wind shear matched well (Figure 4(d)). WRF/Chem overestimated wind speeds by 0.2 - 1.2 m ∙s −1 from the sur- face to about 1100 m, and marginally underestimated the wind speeds above this level to the tropopause. Gener- ally, wind-speed biases (simulated minus observed) remained less than 0.7 m ∙s −1 in levels close to the surface. The overall mean simulated and observed wind speeds were exactly 10.1 m ∙s −1 , resulting in a mean bias of nearly zero due to compensation of positive and negative differences. WRF/Chem also simulated the wind-speed variance well (5.80 m 2 ∙s −2 vs. 5.67 m 2 ∙s −2 ). When we assume that the temporal standard deviation is representa- tive for the daily variability, WRF/Chem and the observations also show the same vertical mean variability of about 2.4 m ∙s −1 .
Through a research-based partnership of University of Michigan (U-M) institutes, centers, and faculty, we are holistically evaluating the impacts of hydraulicfracturing in Michigan. Hydraulic fractur- ing has the potential to touch issues that all Michigan residents care about - drinking water, air quality, Great Lakes health, water supply, local land use, energy security, economic growth, tourism, and natural resource protection. This project’s technical analysis, stakeholder engagement, and proposed approaches to minimize negative impacts will be important outcomes that guide future decision making on this issue and hopefully help state decision makers avoid some of the pitfalls encountered in other states. The project is based on the premise that natural gas extraction
It is again emphasized that there are many problems with the basic data for individual power stations used in this exercise and the volume of data is such that extensive checking is too time consuming for the scope of the project. Plainly, improvements to these data are an essential prerequisite for accurate and detailed analysis and plant-by- plant policy recommendations. It is, however, anticipated that the general conclusions reached are likely to be more robust as a result of errors for individual power stations canceling each other out when results are brought together.
The acidic gas samples and fine particulatematter samples were collected using a URG Dual Sequential Fine Particle Sampler (URG-2000-01K) on loan from the North Carolina Division of Air Quality. (A picture of the instrument is seen in Figure 2.7) As a sample is collected, air is pulled through the instrument by the two external attached pumps. The air is pulled in through the inlet, and immediately passes through a cyclone, which removes all particles with a diameter larger than 2.5 micrometers. (µm) After traveling through a channel splitter, the air traveled through a 30 mm-diameter, 150 mm-length sodium carbonate coated annular denuder to collect the acidic gases, and then through a filter pack containing one Teflon filter and one nylon filter in series to collect the inorganic particulates. The air is then pulled all the way into the pumps, and is released out of the back of the
ports are also used to increase the storage capacity of the combustion residues (e.g. ashes) incurred during the course of the filter’s service life. Materials such as silicon carbide, aluminum titanate, and cordierite are used here in series production [32-39]. The filter efficiency depends on the pore size of the ceramics and the particle compos- ition. Hydrocarbons with a high boiling point that are still present in gaseous form at filtering temperature and only adhere to the particles when they cool down and mix with the ambient air cannot be filtered out. Figure 6 shows the filtering mechanisms. Due to the overlapping filtration mechanisms, both large as well as small particles can be held back reliably, thus achieving a filtering efficiency of nearly 100% across the entire spectrum of sizes . Since almost all emitted particles are smaller than the pores of the filter substrate, they are not caught in the filter due to their size but mostly by means of diffusion. Since the dif- fusion speed increases with decreasing particle size, smaller particles are actually separated the most effect- ively. With rising soot loads, there is a transition from deep filtration in the filter wall down to surface filtration. Both the soot layer stored in the pores as well as the soot cake on the filter wall itself act as a highly effective filter- ing medium. Due to the low deep filtering capacity of the ceramic honeycomb filter, the range of surface filtration is already being reached after a short load time. This is why a significant particle breakthrough in an intact filter can only be detected after the completion of an entire regener- ation process in the startup phase of the load . Particle catalysts can also reach particle filtration levels of consid- erately more than 50% , but these levels remain below those of wall-flow filters. For new systems, it is also pos- sible to reach filtration efficiencies of more than 90% in combination with the filtration of nano-particles by means of electrostatic forces .
station, but this was driven by fine PM mass concentra- tion, whereas coarse PM underground was higher than the overground station but similar to ambient concen- trations. In terms of composition, the most notable dif- ference was enrichment of Fe in the underground samples compared to overground and ambient samples along with enrichment of non-crustal species such as Mn, Cr, Co, Ni, Cu, Ba, Mo, Cd, and Eu, with the en- richment more pronounced in the fine fraction than the coarse fraction on both PM mass/mass and mass/vol- ume concentration measures. This concentration enrich- ment was attributed to the specific sources of these elements underground and the enclosed environment of the underground, respectively. Secondary ions and or- ganic carbon species underground were suggested to have derived from outdoor sources. Crustal species con- centrations were similar in coarse PM underground and above ground, but there was suggested to be an add- itional source of Al and Ca in fine PM underground. Correlation analyses suggested that Al and Ca, along with the aforementioned non-crustal species, likely de- rived from a single railway-specific source present above and below ground, as there was a generally high correl- ation between these elements. However, the authors also suggest additional other sources for Ba (brake wear), Cu (sources not suggested, although may be electrical con- tact components), and Zn (may originate from above-ground vehicular emissions). As noted in other studies earlier, these elements generally exhibited lower water solubility in underground PM than in overground or ambient PM, across both coarse and fine PM. When taking airborne PM mass concentration into account, Fe and Ba were the only water-soluble components enriched in underground PM compared to the other two sites. Across all sites, ROS generation in DCF-loaded PM-exposed macrophages was strongly correlated with
Figure 2 shows the percentage change in the total root mean square deviation (TRMSD) with decreasing number of clusters, which consist of back trajectories for the YRK (Yorkville, GA) site. The x-axis represents the number of clusters, while y-axis refers to the percentage change in RMSD when the number of cluster increases from x-1 to x. Figure 2 indicates when the number of clusters increases from 1 to 20, large changes in the TRMSD occur at 4, 7, and 18 clusters. As in any other clustering methodology, some decisions have to be made by the user [Romesburg, 1984]. The user can define a percentage change in RMSD which, when exceeded at some stage in the reduction of the number of clusters, signifies an optimum number of clusters to be retained in the analysis. Hence Figure 2 indicates a “break” or significant percentage change in reducing the distinct number of clusters from 8 to 7. 7 clusters were therefore retained as best describing significantly different forms of air flow to YRK site in the period considering both the number of clusters and the change of RMSD. Once these distinct (optimum number of) clusters of trajectories have been identified, the average back-trajectories for the 7 clusters at YRK (Yorkville, GA) site will be plotted. For further reference, clusters are named according to their general direction: N, NE, S, etc. The cluster that stays relatively closer to the reception site is named C (close) because speed of air parcel has influence on the level of pollutant as discussed in proceeding part.
The box model (i.e., 0-D CMAQ-MADRID 2) is used to study SOA formation and explore various methods to improve the computational efficiency of the SOA module. Two processes have been identified as the most computationally-expensive processes in the SOA module in MADRID 2: (1) solving the partitioning equations for condensable organic compounds; and (2) estimating their activity coefficients and partitioning coefficients in the multicomponent mixtures using the Universal Function Activity Coefficient (UNIFAC) method (Fredenslund et al., 1975; 1977). The two processes can be speeded up by relaxing the error tolerance levels and reducing the maximum number of numerical solver iterations for the partitioning equations for organic species; turning on organic-inorganic interactions only when the water content associated with organic compounds is significant; and parameterizing the calculation of activity coefficients for organic mixtures in the hydrophilic module. The improved CMAQ-MADRID 2 is applied to the SOS episode, 1999. The model results are compared with those from the original CMAQ-MADRID 2, to assess the improvements in terms of computational efficiency and numerical accuracy. The results are compared against the observations available by routine monitoring networks and special studies, and predictions from CMAQ and CMAQ-MADRID 1 as well. The process analysis embedded in CMAQ, including the Integrated Process Rate analysis (IPR) and the Integrated Reaction Rate analysis (IRR), is also conducted to identify the physical processes for O 3 and
Hydraulicfracturing, often referred to as fracturing, is generically the fracturing of rocks around a wellbore in order to increase the permeability of the rock and therefore the flow of gas from it. Many wells are drilled in close proximity on a well pad and after reaching the depth of the target formation, such as the Marcellus Shale, the drill pivots to go horizontally into the formation. This multitude of wells creates a wheel-spoke pattern in the gas bearing shale formation, and dramatically increases the yield of hydrocarbons from shale compared to what was available through conventional means (Arthur and Layne, 2008). Approximately 4.25 million gallons of water per well are used to hydraulically fracture the Marcellus Shale with other formations varying (Kondash and Vengosh, 2015). The water is mixed with a variety of chemicals to create fractures and maintain the well. In order to prop open these fractures, silica granules called proppant are injected along with gelling agents to help push the proppant into place (PA DEP). This is followed by breaker chemicals, such as persulfates, which break down the gelled water in order to pull it back out following a shut-in period of several days to weeks (Marcon et al., 2017). After this shut in period, a portion of this water and the natural brine in the formation, totaling to 1.37 million gallons per well in the Marcellus Shale (Kondash and