Printer Friendly

An assessment of life cycle greenhouse gas emissions associated with the use of water, sand, and chemicals in shale gas production of the Pennsylvania Marcellus Shale.

Editor's Note: Two supplemental documents that were submitted along with this peer-reviewed article have been posted online due to publication space limitations. These documents were not peer reviewed or copy edited by the Journal. They are provided as extra resources should the reader want more information. The supplemental text and table can be accessed at www.neha.org/jeh/supplemental.

Introduction

In recent years, the widespread use of hydraulic fracturing (HF) has enabled the rapid expansion of unconventional natural gas, tight gas, and tight oil production in the U.S. (Clark et al., 2013; Verrastro, 2012). As a result, the U.S. has been the world's leading natural gas and oil producer since 2010 and 2013, respectively (Smith, 2014; U.S. Energy Information Administration [U.S. EIA], 2015a; International Energy Agency, 2014). In 2012, over 60% of the natural gas produced in the U.S. came from unconventional sources; this number is projected to increase to 75% by 2040 (U.S. EIA, 2014). By 2040, it is projected that natural gas and coal will account for 31% and 34%, respectively, of U.S. electricity generation (U.S. EIA, 2015b).

In 2013, electricity production generated the largest share (31%) of U.S. greenhouse gas (GHG) emissions (U.S. Environmental Protection Agency [U.S. EPA], 2015). A reduction in GHG emissions over the next few decades can reduce risks to environmental and human health due to increasingly frequent, intense, and longer-lasting extreme heat; worsening droughts, wildfires, and air pollution risks; increasingly frequent extreme precipitation, intense storms, and changes in precipitation patterns that lead to drought and ecosystem changes; and rising sea levels that intensify coastal flooding and storm surge (Intergovernmental Panel on Climate Change, 2014; Luber et al., 2014).

The growth of U.S. shale gas production is said to be a pathway to a more energy-sustainable future; however, questions remain concerning its life cycle impacts on climate change. There have been numerous life cycle assessments (LCAs) that evaluate the life cycle greenhouse gas (LC-GHG) emissions of shale gas compared with conventional gas and/or coal. The primary focus of most studies is on the release of methane into the atmosphere during production, processing, transmission, storage, and distribution of natural gas (Burnham et al., 2012; Cathles, Brown, Taam, & Hunter, 2012; Clark, Han, Burnham, Dunn, & Wang, 2011; Fulton, Mellquist, Kitasei, & Bluestein, 2011; Howarth, Santoro, & Ingraffea, 2011; Howarth, Santoro, & Ingraffea, 2012; Hultman, Rebois, Scholten, & Ramig, 2011; Jiang et al., 2011; Skone, Littlefield, & Marriott, 2011).

Although recent LCAs have captured many stages of shale gas production, most studies have not considered the GHG emissions associated with the production and transportation of silica sand or chemical additives mixed in the HF fluid, nor the transportation of water to and from well sites. For example, Jiang and co-authors' study (2011) was among the most complete LCAs of HF, but broad approximations of sand, water, and chemical quantities used in HF and broad transportation assumptions for flowback water were used.

Our study complements Jiang and coauthors' work (2011) by using real-world field data of injected fluid to estimate sand, water, and chemical quantities used in HF wells. Our study also uses real-world field data of waste fluid to more accurately estimate transportation relevant to the various fates of flowback water. Using real-world quantities of sand, water, and chemicals in the HF fluid would allow for more accurate health and climate assessments as they relate to the life cycle production, transportation, and disposal of these materials. In addition, computing GHG emissions from real-world data will supplement the existing LCAs that either do not include chemicals, sand, or water, or rely on broad assumptions with respect to their usage.

Methods

Chemical Inventory

The chemical inventory for this study was created from real-world, well-specific chemical data from FracFocus Hydraulic Fracturing Fluid Product Component Information Disclosure Forms for Pennsylvania wells, which were extracted and compiled into a dataset by SkyTruth. A quality assurance analysis was conducted to assess both the accuracy of the SkyTruth data extraction from the FracFocus disclosure forms and the validity of the FracFocus data. The dataset was screened for duplicate, missing, or erroneous data, as well as extreme outliers. To assess suspected duplicate or erroneous data, disclosure forms from fracfocusdata.org were downloaded and compared with the SkyTruth extracted dataset.

After the removal of duplicate wells (n = 16), wells with insufficient information (n = 5), and wells with suspected erroneous data (n = 3), the dataset included 1,921 HF wells with fracture dates from January 1, 2011, to August 31, 2012. The usage of sand, water, and chemicals detailed in the dataset pertains to these 1,921 wells.

The dataset included 181 chemicals with Chemical Abstracts Services (CAS) numbers for which frequency of use was computed. Of the 181 chemicals with CAS numbers, some lack any type of chemical quantity used (n = 18), so only the remaining 163 chemicals were included in calculating the chemical usage statistics. Frequency of use and chemical usage statistics were only computed for chemicals with CAS numbers and can be found in the chemical inventory (see supplemental table).

Approximately 150 additional chemicals without CAS numbers appeared in the dataset listed as proprietary or under a generic name (e.g., surfactants). These 150 chemical names do not appear in the chemical inventory. Of the 150 chemicals without CAS numbers, 17 lacked any type of chemical quantity. The chemical quantities of the remaining 133 chemicals without CAS numbers were included in our GHG assessment of chemical production and transportation, but are not listed in the chemical inventory.

Concentration values were reported in FracFocus as a percent by mass, which were converted to volumes using chemical density (see supplemental text for calculation details and concentration values). Table 1 provides summary information for the sample of Pennsylvania wells. Figure 1 shows the frequency and quantities for all chemicals used in at least 10% of the wells (see supplemental table for the full chemical inventory).

Assessment of Greenhouse Gas Emissions

Production and Transportation of Chemicals The Economic Input-Output Life Cycle Assessment (EIO-LCA), developed by the Green Design Institute of Carnegie Mellon University, is an online tool we used to calculate the LC-GHG emissions associated with the production and transportation of chemicals used per well. The EIO-LCA U.S. National 2002 Purchaser Price Model was the most recent model published, which incorporates GHG emissions associated with all direct and indirect activities involved with the production of a product from the extraction of raw materials to the transportation to the final consumer (i.e., a cradle to consumer model). The estimation of GHG emissions from the production and transportation of HF chemicals was based on the average chemical quantities used per well from the dataset and the price to purchase the chemicals (see supplemental text for details).

Production of Sand

The EIO-LCA U.S. National 2002 Producer Price Model, which incorporates GHG emissions associated with all direct and indirect activities considered in the Purchaser Price Model minus transportation to the final consumer (i.e., a cradle to gate of factory model), was used to calculate the LC-GHG emissions associated with the production of sand used in the HF fluid per well. The estimation of GHG emissions from the production of HF sand was based on the quantity of sand per well from the dataset and the price to purchase sand (see supplemental text).

Transportation of Sand and Water

In order to assess GHG emissions associated with the transportation of sand and water used in HF, the number of ton-miles were calculated for a base case scenario using quantities of sand and water per well from the well dataset, and estimated distances traveled relative to the Pennsylvania Marcellus Shale gas development. The following transportation sections detail the methodology used to estimate average distances traveled for sand and water.

A) Transportation of Sand

In the base case scenario, sand is trucked from the mine to a processing plant (both in Wisconsin, mean distance 18.8 miles). Then the sand travels by rail to a transload station in Pennsylvania (mean distance 929 miles), and finally trucked to the HF well site (mean distance 32 miles) (see supplemental text for details on sand transport assumptions).

Two different rail routes from Wisconsin to Pennsylvania were assessed (supplemental text, figure 3). According to Google Maps, the rail route through parts of Canada is 1,027 miles and the entirely U.S. route is 830. The average of the two routes (929 miles) was used as the average rail distance traveled.

B) Transportation of Water: Freshwater to HF Well

In the Marcellus Shale, approximately two thirds of freshwater injected into a new hydraulically fractured well comes from surface water withdrawal sources (e.g., rivers, ponds, lakes, etc.) (Paugh, 2008; Penn State Cooperative Extension, 2011; Penn State Public Broadcasting, 2011; Seydor, Clements, Pantelemonitis, & Deshpande, 2012; Yoxtheimer, 2011). The geographic locations of 354 water withdrawal sources registered with the Pennsylvania Department of Environmental Protection (PA DEP) from January 2007 through October 2013 were compared with the geographic locations of registered HF wells in Pennsylvania using FracFocus maps in order to estimate the average distance water travels by truck from withdrawal source to HF well (estimated average distance: 8 miles) (see supplemental text, figure 6, for further information supporting water assumptions).

C) Transportation of Water: Flowback Water Approximately 35% to 40% of the injected water in Marcellus Shale wells returns to the surface as flowback water over the lifetime of the well (Jiang et al., 2011; Johnson, 2013; National Association of Development Organizations Research Foundation, 2010; Olawoyin et al., 2011; Paugh, 2008). Depending on the fate of flowback water, the distance traveled can vary greatly. According to PA DEP, of the waste fluid data from July 2012 through June 2013, 68.7% of HF fluid waste was reused without being brought to a recycling facility, 18.0% was reused after being brought to a centralized treatment plant for recycling, and 12.4% was brought to an injection disposal well. Travel associated with the disposal methods for the less than 1% of remaining waste fluid (e.g., brought to a landfill, used for road spreading, or brought to a centralized treatment plant and discharged) was not assessed in this study.

The July 2012 through June 2013 PA DEP fluid waste data were used to estimate the average distance waste fluid travels to centralized treatment plants for recycling and injection disposal wells. Google Maps driving routes were used to calculate the driving distance between the GPS coordinates of the HF wells and the addresses of the respective disposal facilities for a 5% random sample of reports of waste fluid to recycling facilities (n = 390) and reports of waste fluid to injection disposal wells (n = 411). The average distance waste fluid traveled to a recycling facility was 55 miles, and because recycling is typically round trip, 110 miles was used in this analysis. The average one-way distance traveled to an injection disposal well was 162 miles. This was not assumed to be round trip, and therefore 162 miles was assumed for injection well disposal.

Travel associated with water that was reused without being brought to a recycling facility was also considered in this study. We assumed that 15% of reused water is reused at the same well pad, and 85% is trucked to a different well 1.5 miles away (see supplemental text for details).

Quantities of Water Traveled

The quantities of water traveled that were used in the base case calculation were based on a range of assumptions and scenarios regarding water used in HF, as well as the dataset mean quantity of water injected per well (4.3 million gallons). Based on our literature review (supplemental text, figure 6), we assumed in the base case scenario that 80% of the 4.3 million gallons injected per well came from a freshwater source and 20% was reused from a previous well. A 70/30% and 90/10% split was used in the low-end and high-end scenarios, respectively. Of the water withdrawn from a freshwater source, it was assumed that 90% traveled to HF wells by truck (average estimate: 3.1 million gallons) and 10% traveled by temporary pipeline (Figure 2).

The quantities of initially injected water that return to the surface as flowback water were based on the dataset mean total HF fluid per well (4.3 million gallons of water and 18,958 gallons of chemicals). Three scenarios regarding the percentage of initially injected water that returns to the surface as flowback water were analyzed (10%, 30%, and 50%). According to our literature review (supplemental text, figure 6) and our assessment of PA DEP waste fluid data, 30% (1.3 million gallons) was used in the average estimate calculation. From the PA DEP waste fluid data, 12.4% (average estimate: 160,000 gallons) of flowback water was brought to an injection disposal well, 18.0% (average estimate: 232,000 gallons) was reused after being brought to a centralized treatment plant for recycling, and 68.7% (average estimate: 885,000 gallons) was reused without being brought to a recycling facility. Of the water reused without being brought to a recycling facility, it was assumed that 85% (average estimate: 752,000 gallons) traveled to a different well pad.

Vehicle Carrying-Capacity Assumptions

The calculation of truck-trips was based on quantities of sand and water used in the estimates, as well as various assumptions regarding train and truck carrying capacities (see supplemental text, table 7, for the carrying capacities used in the base case scenario, as well as the range of carrying capacities used in the low-end and high-end scenarios).

Life Cycle Transportation GHG Emissions Factors

Life cycle transportation GHG emission factors of 984 grams of C[O.SUB.2] equivalence (C[O.sub.2]e) per ton-mile for class 8b trucks and 269 grams of C[O.sub.2]e per ton-mile for intermodal rail were obtained from Facanha and Horvath (2007). The emission factors incorporate all life cycle phases of vehicles, transportation infrastructure, and fuels--including the production, use, maintenance, and end of life of vehicles and infrastructure--as well as the life cycle of diesel fuel (i.e., petroleum extraction and refining, fuel distribution) (Facanha & Horvath, 2007) (see supplemental text for a breakout of grams/ton-mile for C[O.SUB.2] and NOx).

Final results of GHG emissions are presented in grams of C[O.sub.2]e per megajoule (MJ) of natural gas extracted from the well (i.e., in units of GHG emissions per natural gas energy). Consistent with Jiang and coauthors (2011), the conversion of tons (t) of C[O.sub.2]e/well to grams C[O.sub.2]e/MJ of natural gas is based on an assumed average natural gas production per well of 2.7 billion cubic feet or 2.89 x [10.sup.9] MJ.

GHG Emissions From Deep Well Injection and Water Treatment

GHG emissions associated with deep-well injection of waste fluid were assessed using the EIO-LCA tool. GHG emissions from treatment of fluid waste were based on an emission factor of 3.4 grams of C[O.sub.2]e emissions per gallon of water treated (Stokes & Horvath, 2006). This emissions factor was applied to the quantity of fluid waste brought to recycling facilities.

Results

The transportation of sand, freshwater, and flowback water associated with HF results in 1,235 one-way truck-trips on average per well in the Marcellus Shale. The truck-trips do not include vehicle travel from drill pad workers; delivering equipment such as drill rig components, trailers, and forklifts; ancillary activities such as servicing portable restrooms; or transportation for chemical delivery.

The highest proportions of truck-trips are from the transportation of water from withdrawal sources to HF wells (56.0%; average = 692), the transportation of flowback water to another well pad to be reused (13.7%; average = 169), and the transportation of sand from transload facilities to HF wells (10.1%; average = 125).

The transportation of sand, freshwater, and flowback water associated with HF results in 2,718,089 ton-miles on average per HF well. The highest proportions of ton-miles are from the transportation of sand from Wisconsin to Pennsylvania via rail (83.6%; average = 2,272,789 ton-miles) (supplemental text, table 9).

Figure 3 shows GHG emissions per well calculated in this study. The ranges shown for sand transportation, water transportation, and water treatment represent low-end and high-end estimates based on varying assumptions. The ranges for sand transportation and water transportation pertain to the total column, not just the top section of the column. Of the GHG emissions per HF well assessed in this study (average: 1,374 t C[O.sub.2]e), the production and transportation of sand account for the highest proportion (66.9%; average = 920 t C[O.sub.2]e), followed by the transportation and treatment of water (29.7%; average = 408 t C[O.sub.2]e), and the production and transportation of chemicals (3.4%; average = 46 t C[O.sub.2]e).

Discussion

Using real-world data, the average GHG emission estimate for combined sand and chemicals in this study is 4.8 times higher than those estimated by Jiang and co-authors (2011). The average estimate for water consumption (including transportation and treatment) in this study is 10% higher than Jiang and coauthors with low- and high-end range estimates bracketing their average estimate (Figure 4). GHG emissions from sand, water, and chemicals estimated in this study, however, account for only 0.63% of all other upstream and downstream processes estimated by Jiang and co-authors (Figure 5).

The results for natural gas production, processing, transmission, and storage from Jiang and co-authors (2011) displayed in Figure 5 are based on estimates of methane leakage/venting. According to Howarth and co-authors (2012), unconventional gas upstream and downstream methane emissions used by Jiang and co-authors are roughly one half and one third of those from U.S. EPA (2011), respectively, and are lower than those from any other paper or report that has examined the GHG emissions of shale gas production (Howarth et al., 2012; U.S. EPA, 2011).

As methane leakage, venting, and flaring activities do not influence water consumption or sand and chemical production, if Jiang and co-authors' estimates of upstream and downstream GHG emissions are too low, then the proportion of total GHG emissions attributable to sand, water, and chemicals estimated in this study would be even lower.

Strengths and Limitations

Certain limitations are associated with the FracFocus/SkyTruth data. Most of the Pennsylvania FracFocus data (78%) have been disclosed voluntarily (i.e., fracture date before April 14, 2012), and therefore might not be representative of all wells in Pennsylvania during this time. Duplicated data, missing information, and suspected erroneous entries were discovered, some of which were attributable to entry errors to FracFocus, and some issues were due to SkyTruth's data extraction. Several quality assurance steps were taken to correct misinformation such as duplications, typos, and erroneous data, but all types of errors might not have been corrected. Extreme outliers were also removed (see supplemental table).

The large sample size of 1,921 wells helps to minimize the impact of potential errors in the dataset. Ultimately the use of reported chemical data to assess GHG emissions allows for a more accurate assessment than previously reported.

The use of the EIO-LCA model has limitations due to the lack of specificity and relativity to Pennsylvania Marcellus Shale production. The use of real-world field data from over 1,900 HF and 30 natural gas operators to estimate sand, water, and chemical quantities per well, however, allowed for a more accurate estimation of GHG emissions than previous LCAs using the EIO-LCA model. Compared with Jiang and co-authors' assessment (2011), whose sand and chemical volumes were based on a fact sheet by one natural gas operator, Chesapeake Energy, our assessment assumed a 6.5 times higher mass of sand (2.2 million kg versus 0.34 million kg), twice the mass of acids (23,649 kg versus 12,000 kg), a third the mass of surfactants (1,015 kg versus 3,000 kg), and nearly twice the mass of chemicals overall (44,982 kg versus 24,930 kg).

The use of real-world, field waste fluid data to determine the proportions of flowback water associated with different disposal methods, and to determine the average distance traveled per disposal method, allowed for a more accurate assessment of the HF water cycle. For example, Jiang and co-authors (2011) used injection disposal well as the base case disposal method with a distance traveled of 80 miles. Twelve months of recent PA DEP waste fluid data show that only 12% of flowback water traveled to deep injection wells, with an average distance traveled of 162 miles.

Conclusion

The truck-trips calculated in this study provide insight into the traffic-related impacts and the associated diesel emissions associated with HF in the Pennsylvania Marcellus Shale. To transport sand and water, the average estimate in this study results in 1,235 truck-trips per well and 7,410-9,880 truck-trips for a multiwell drill pad with six to eight wells, respectively. This does not include empty return truck-trips or the 150-200 rail cars of sand needed for six to eight wells on a pad, respectively.

The chemical inventory developed from FracFocus data provides more transparency to the HF process, especially regarding the quantities and frequencies of chemicals used. Of note, only 16 chemicals on average were used per well despite 181 chemicals identified across 1,921 wells. This suggests a high degree of variability with each company's choice in chemical usage. Other than hydrochloric acid (98% of wells; mean = 6,458 gallons), most other chemicals were used far less frequently and in lower volumes. With respect to local communities, this underscores the importance of knowing which HF chemicals are actually used in a localized geographical area when conducting an environmental assessment and considering risks to public health, as opposed to considering all HF chemicals that are known to be used in HF This information can help narrow the scope of environmental health risk assessments and can offer opportunities to substitute less toxic or less volatile compounds where applicable.

The GHG emissions from the upstream processes assessed in this study (i.e., sand, water, and chemicals) are relatively small compared with natural gas combustion, methane leakage, venting, and flaring from the other downstream phases of the HF process. Comparing the upstream GHG emissions against the large magnitude of the downstream emissions suggests that long-term reliance on unconventional natural gas emits a substantial amount of overall GHG emissions, which will exacerbate climate change. These findings focus attention on large GHG emission sources that historically have had a high degree of uncertainty, such as the magnitude of methane leakage from unconventional natural gas extraction. Further study is needed to better understand the implications of LC-GHG emissions from shale gas production, especially with regards to methane emissions.

Christopher Sibrizzi, MPH

Peter LaPuma, PhD, PE, CIH

The George Washington University Milken Institute School of Public Health Department of Environmental and Occupational Health

Corresponding Author: Christopher Sibrizzi, The George Washington University, Milken Institute School of Public Health, Department of Environmental and Occupational Health, 950 New Hampshire Avenue NW, 7th Floor, Washington, DC 20052.

E-mail: csibriz@gwu.edu.

References

Burnham, A., Han, J., Clark, C.E., Wang, M., Dunn, J.B., & Palou-Rivera, I. (2012). Life-cycle greenhouse gas emissions of shale gas, natural gas, coal, and petroleum. Environmental Science and Technology, 46(2), 619-627.

Cathles, L.M., III, Brown, L., Taam, M., & Hunter, A. (2012). A commentary on "The greenhouse-gas footprint of natural gas in shale formations" by R.W. Howarth, R. Santoro, and A. Ingraffea. Climatic Change, 113(2), 525-535.

Clark, C.E., Burnham, A., Harto, C., & Horner, R. (2013). Hydraulic fracturing and shale gas production: Technology, impacts, and policy. Chicago, IL: Argonne National Laboratory. Retrieved from http:// www.afdc.energy.gov/uploads/publication/anl_hydraulic_fracturing.pdf

Clark, C.E., Han, J., Burnham, A., Dunn, J.B., & Wang, M.Q. (2011). Life-cycle analysis of shale gas and natural gas (No. ANL/ ESD/11-11). Chicago, IL: Argonne National Laboratory, U.S. Department of Energy. Retrieved from https://greet.es.anl.gov/ publication-shale_gas

Facanha, C., & Horvath, A. (2007). Evaluation of life-cycle air emission factors of freight transportation. Environmental Science and Technology, 41(20), 7138-7144.

Fulton, M., Mellquist, N., Kitasei, S., & Bluestein, J. (2011). Comparing greenhouse gas emissions from natural gas and coal. Washington, DC: Worldwatch Institute/Deutsche Bank. Retrieved from http://www.worldwatch.org/system/files/pdf/Natural_Gas_LCA_ Update_082511.pdf

Howarth, R.W., Santoro, R., & Ingraffea, A. (2011). Methane and the greenhouse-gas footprint of natural gas from shale formations. Climatic Change, 106(4), 679-690.

Howarth, R.W., Santoro, R., & Ingraffea, A. (2012). Venting and leaking of methane from shale gas development: Response to Cathles et al. Climatic Change, 113(2), 537-549.

Hultman, N., Rebois, D., Scholten, M., & Ramig, C. (2011). The greenhouse impact of unconventional gas for electricity generation. Environmental Research Letters, 6(4).

Intergovernmental Panel on Climate Change (2014). Climate change 2014: Synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp.

International Energy Agency. (2014). Key world energy statistics. Paris, France: International Energy Agency Publications.

Jiang, M., Griffin, W.M., Hendrickson, C., Jaramillo, P, VanBriesen, J., & Venkatesh, A. (2011). Life cycle greenhouse gas emissions of Marcellus shale gas. Environmental Research Letters, 6(3).

Johnson, K. (2013, May). Operators turn to reuse, recycling. The American Oil & Gas Reporter. Retrieved from http://www.aogr. com/magazine/editors-choice/operators-turn-to-reuse-recycling

Luber, G., Knowlton, K., Balbus, J., Frumkin, H., Hayden, M., Hess, J., ... Ziska, L. (2014). Human health. In J.M. Melillo, T.C. Richmond, & G.W Yohe (Eds.), Climate change impacts in the United States: The third national climate assessment (pp. 220256). Washington, DC: U.S. Global Change Research Program. Retrieved from http://www.globalchange.gov/browse/reports/ climate-change-impacts-united-states-third-national-climateassessment-0

National Association of Development Organizations Research Foundation. (2010). Natural gas drilling in the Marcellus shale: Regional economic opportunities and infrastructure challenges. Washington, DC: Author.

Olawoyin, R., York, J., Madu, C., Li, H., Ahn, C.H., & Enab, K. (2011) . Optimization of well stimulation fluids in the Marcellus shale gas development using integrated technologies. Pennsylvania State University.

Paugh, L.O. (2008, January). Marcellus shale water management challenges in Pennsylvania (No. SPE 119898). Society of Petroleum Engineers Shale Gas Production Conference, Ft. Worth, TX. Retrieved from https://www.onepetro.org/conference-paper/ SPE-119898-MS

Penn State Cooperative Extension. (2011). Water's journey through the shale gas drilling and production processes in the mid-Atlantic region. University Park, PA: Pennsylvania State University. Retrieved from http://extension.psu.edu/natural-resources/water/ marcellus-shale/regulations/waters-journey-through-the-shalegas-drilling-and-production-processes-in-the-mid-atlantic-region

Penn State Public Broadcasting. (2011). Explore shale: An exploration of natural gas drilling and development in the Marcellus shale. Retrieved from http://exploreshale.org

Seydor, S.M., Clements, E., Pantelemonitis, S., & Deshpande, V (2012). Understanding the Marcellus shale supply chain working paper. Pittsburgh, PA: University of Pittsburgh Katz Graduate School of Business.

Skone, TJ., Littlefield, J., & Marriott, J. (2011). Life cycle greenhouse gas inventory of natural gas extraction, delivery and electricity production (No. NETL/DOE-2011/1522). U.S. Department of Energy, National Energy Technology Laboratory.

Smith, G. (2014, July 4). U.S. seen as biggest oil producer after overtaking Saudi Arabia. Bloomberg. Retrieved from http://www. bloomberg.com/news/articles/2014-07-04/u-s-seen-as-biggestoil-producer-after-overtaking-saudi

Stokes, J., & Horvath, A. (2006). Life cycle energy assessment of alternative water supply systems. International Journal of Life Cycle Assessment, 11(5), 335-343.

U.S. Energy Information Administration. (2014). Annual energy outlook 2014 with projections to 2040 (No. DOE/EIA-0383(2014). Washington, DC: Author. Retrieved from http://www.eia.gov/ forecasts/archive/aeo14/

U.S. Energy Information Administration. (2015a). International energy statistics. Retrieved from http://www.eia.gov/cfapps/ipdbproject/ IEDIndex3.cfm?tid=5&pid=53&aid=1

U.S. Energy Information Administration. (2015b). Annual energy outlook 2015 with projections to 2040 (No. DOE/EIA-0383(2015). Washington, DC: Author. Retrieved from www.eia.gov/forecasts/ aeo/pdf/0383%282015%29.pdf

U.S. Environmental Protection Agency. (2011). Inventory of U.S. greenhouse gas emissions and sinks: 1990-2009 (No. EPA 430-R-11005). Washington, DC: Author. Retrieved from https://www.epa. gov/ghgemissions/us-greenhouse-gas-inventory-report-archive

U.S. Environmental Protection Agency. (2015). Inventory of U.S. greenhouse gas emissions and sinks: 1990-2013 (No. EPA 430-R-15004). Washington, DC: Author. Retrieved from https://www.epa. gov/ghgemissions/us-greenhouse-gas-inventory-report-archive

Verrastro, F.A. (2012). The role of unconventional oil and gas: A new paradigm for energy. Washington, DC: Center for Strategic and International Studies. Retrieved from https://www.csis.org/ analysis/role-unconventional-oil-and-gas-new-paradigm-energy

Yoxtheimer, D. (2011). Water management options for Marcellus natural gas development. Penn State Cooperative Extension.

TABLE 1

Summary Information for Dataset

Data Summary Information         Quantity         Unit

Number of wells                   1,921          wells
  Fracture date (before           1,495          wells
    4/14/2012)
  Fracture date (on or after       426           wells
    4/14/2012)
Mean well vertical depth          6,942     feet (1.3 miles)
Mean water quantity per well       4.27     million gallons
Mean quantity silica               4.89      million pounds
  sand per well
Mean quantity chemicals           18,958        gallons
  per well
Mean number of chemicals            16         chemicals
  used per well
Chemicals in dataset               181         chemicals
  with CAS numbers.

FIGURE 5

Greenhouse Gas Emissions Resulting From Upstream and
Downstream Processes in Hydraulic Fracturing (in Grams of
C[O.sub.2]e/MJ of Natural Gas)

Natural Gas Production,                  9.7
Natural Gas Distribution,                0.8
Natural Gas Transmission and Storage,    1.4
Other Upstream,                          1.64
Natural Gas Processing,                  4.3
Natural Gas Combustion,                 50

Upstream Inputs to Hydraulic Fracturing Well

Chemicals,                               0.014
Sand,                                    0.29
Water,                                   0.129

Note: Table made from pie chart.


----------

Please note: Some tables or figures were omitted from this article.
COPYRIGHT 2016 National Environmental Health Association
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:ADVANCEMENT OF THE SCIENCE
Author:Sibrizzi, Christopher; LaPuma, Peter
Publication:Journal of Environmental Health
Geographic Code:1U2PA
Date:Nov 1, 2016
Words:4963
Previous Article:Water and environmental equity.
Next Article:Assessed food safety risks associated with grocery stores.
Topics:

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters