LCA.6132.185s.2019 Life Cycle Associates, LLC Michael ... · Life Cycle Associates, LLC Michael...

LCA.6132.185s.2019

1 | KMMEF GHG Analysis

Supplemental Technical Analysis for Response to DSEIS Comments Prepared by Stefan Unnasch, Life Cycle Associates, LLC Michael Lawrence, Jack Faucett Associates. August, 2019

Section Page Introduction .................................................................................................................................... 5

Global Warming Potential ........................................................................................................... 7

1.1. 20‐ versus 100‐Year Time Horizon .............................................................................. 10

Natural Gas Supply for KMMEF ................................................................................................ 14

Upstream Natural Gas Emissions and Methane Leakage Rates ............................................... 15

3.1. British Columbia Methane Emissions ......................................................................... 16

3.2. Range of CH4 Emission Rates ...................................................................................... 17

3.3. Conversion of Leak Rates to LCA Model Inputs .......................................................... 21

Power Generation Emissions .................................................................................................... 24

Alternative Supply Scenarios .................................................................................................... 25

Project Alternatives .................................................................................................................. 30

6.1. KMMEF with Combined Reforming Technology ........................................................ 30

6.2. KMMEF with Biogas Technology ................................................................................ 33

6.3. Biomass Material and Other Technologies ................................................................ 35

Other Sources of Olefins ........................................................................................................... 35

7.1. Emissions from Crude Oil to Naphtha to Olefins........................................................ 36

7.2. Upstream Emissions from Crude Oil and Oil Refining ................................................ 38

7.3. Total Emissions Associated with Crude to Naphtha to Olefins .................................. 40

7.4. Comparison of KMMEF MTO with Other Olefin Options ........................................... 44

Market Displacement Effects of MTO and Naphtha ................................................................. 46

8.1. Effect of Oil Prices ....................................................................................................... 47

Methanol as Fuel ...................................................................................................................... 50

References ......................................................................................................................... 51

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Figures Figure 1. Development of AGWP‐CO2, AGWP‐CH4, and GWP‐CH4 with Time Horizon .............. 11 Figure 2. Methanol Production and Imports in China (million tonnes/year) ............................... 27 Figure 3: Source of Global Methanol Exports (2017) (Simoes 2019) ........................................... 28 Figure 4. Global Methanol Imports to China (2017) (Simoes 2019) ............................................. 28 Figure 5. Effect of Additional Natural Gas‐Based Methanol on Supply Curve ............................. 29 Figure 6. Carbon Balance for Combined Reforming Technology.................................................. 30 Figure 7. Landfill Gas Projects ....................................................................................................... 34 Figure 8. Petroleum Products Produced in PADD3 Refineries ..................................................... 36 Figure 9. Life Cycle GHG Emissions for Crude Oil‐to‐Naphtha‐to‐Olefins .................................... 38 Figure 10. Carbon Intensity of Crude Oil Resources for China ..................................................... 39 Figure 11. System Boundary Diagram for Naphtha‐Centric Oil Refining ...................................... 41 Figure 12. Petroleum Products Produced in PADD3 Refineries and Associated GHG Emissions adjusted to produce sufficient Naphtha to produce 1.37 MTPA Olefins. The olefins route is based on the naphtha stream (Green line) .................................................................................. 42 Figure 13. Total GHG Emissions for Natural Gas and Crude Oil Routes to Olefins before Allocation to Products. .................................................................................................................. 44 Figure 14. Oil and Co‐Produced Natural Gas in Eagle Ford Region .............................................. 45 Figure 15. GHG Emissions for Olefin Production for Same Output as KMMEF ............................ 46 Figure 16. 2014 Global Ethylene Supply Curve ............................................................................. 48 Figure 17. 2016 Global Ethylene Supply Curve ............................................................................. 48 Figure 18. Crude Oil Price History ................................................................................................. 49 Tables Table 1. Principal Categories of Comments and Organization of Responses ................................. 6 Table 2. Annual GHG Emissions from KMMEF Methanol – AR4‐100 ............................................. 9 Table 3. Annual GHG Emissions from KMMEF Methanol – AR5‐100 ........................................... 10 Table 4. Annual GHG Emissions from KMMEF Methanol – AR4‐20 ............................................. 13 Table 5. Annual GHG Emissions from KMMEF Methanol – AR5‐20 ............................................. 14 Table 6. Summary of Recent Upstream Natural Gas Leakage Estimates (as a % of gas delivered)....................................................................................................................................................... 20 Table 7. GREET1_2018 Inputs for Natural Gas Production ........................................................... 23 Table 8. Effect of Higher CH4 Emissions on Net GHG Emissions (million tonnes/year) for the Baseline Scenario .......................................................................................................................... 24 Table 9. Effect of NPCC Power Mixon KMMEF Methanol – AR4‐100 GWP .................................. 25 Table 10. Direct Emissions from Combined Reforming Technology at KMMEF – AR4‐100 ......... 31 Table 11. Lifecycle GHG Emissions with Combined Reforming Technology at KMMEF ............... 33 Table 12. Life Cycle GHG Emissions with Anaerobic Digestion (AD) Biogas ................................. 35 Table 13. Annual GHG Emissions for Olefin Production ............................................................... 44 Table 14: Comparison of Methanol as Splash Blend and Octane Enhancer (360,000 metric tonnes) ............................................................................................. Error! Bookmark not defined.

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Terms and Abbreviations ANL Argonne National Laboratory ARB California Air Resources Board Btu British Thermal Unit CH4 Methane CI Carbon intensity CO Carbon monoxide CO2 Carbon dioxide CO2e Carbon dioxide equivalent DOE U.S. Department of Energy DSEIS Draft Supplemental Environmental Impact Statement EIA US Energy Information Agency EPA U.S. Environmental Protection Agency FEIS Final Environmental Impact Statement g CO2e Grams of carbon dioxide equivalent GBtu Giga Btu, 109 Btus GHG Greenhouse Gas GHGenius LCA model based on UC Davis Life Cycle Emission Model (LEM) that was

developed for Natural Resources Canada GREET The Greenhouse gas, Regulated Emissions, and Energy use in

Transportation model GWh Gigawatt Hours GWP Global Warming Potential HHV Higher Heating Value IPCC Intergovernmental Panel on Climate Change KMMEF Kalama Manufacturing and Marine Export Facility LCA Life Cycle Analysis or Life Cycle Assessment LCFS Low Carbon Fuel Standard LHV Lower Heating Value mmBtu Million Btu MTO Methanol to Olefin MTPA Million Metric Tonnes per Annum N2O Nitrous oxide NG Natural gas NOx Oxides of nitrogen NWIW Northwest Innovation Works, LLC –Kalama NWP Northwest Pipeline SCF Standard Cubic Foot SEPA (Washington) State Environmental Policy Act ULE Ultra Low Emission UN United Nations UNFCC United Nations Framework Convention on Climate Change

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Introduction

Various agencies, tribes, stakeholder groups, and interested citizens provided a range of comments on the Washington State Environmental Policy Act (SEPA) Draft Supplemental Environmental Impact Statement (DSEIS) for the Kalama Manufacturing & Marine Export Facility (KMMEF). Numerous comments were specific to the Kalama Manufacturing and Marine Export Facility Supplement GHG Analysis included as Appendix A to the DSEIS (LCA report) (Unnasch 2018). To help in considering and responding to these comments in the Final Supplemental Environmental Impact Statement, the SEPA Responsible Officials (SROs) requested additional information in the following categories:

1. Global warming potential (GWP)

2. Source of natural gas and effect of potential natural gas supply shifts on Greenhouse

Gas (GHG) emissions

3. Upstream natural gas emissions and methane leakage rates

4. Power generation emissions

5. Alternative scenarios

6. Project alternatives

7. Other sources of olefins

8. Market displacement effects

a. Price of oil

b. Different methanol sources

The sections of the LCA report that discuss these categories are listed in Table 1. The table also lists the sections of this report that address the above categories.

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Table 1. Principal Categories of Comments and Organization of Responses

Category Comment Section of LCA Report

Section of Supplemental Memorandum

Global Warming Potential (GWP)

Consider 20‐year GWP. Consider AR5 GWP values.

App A.6 1. Global Warming Potential

Sources of Natural Gas KMMEF will affect NG supplies.

App B.1 2. Potential for Supply shifts in Natural Gas Supply due to KMMEF

Methane emissions/leakage rates

Review latest data sources on fugitive methane emissions.

App B.1.2 3. Upstream Natural Gas Emissions and Methane Leakage Rates

Marginal Power Consider emissions for power generation.

App B.2 4. Power Generation Emissions

Other supply Scenarios

Examine more scenarios that represent range of effects.

Sections 4 and 5

5. Alternative Supply scenarios 7. Other Sources of Olefins

Other production scenarios

Examine more scenarios that represent range of effects. Examine alternatives to KMMEF technology (CR), Dairy biogas.

Section 4 6. Production Alternatives

Other Sources of Olefins

Compare KMMEF methanol to other olefin routes.

Sections 4.3.4 and 5.4

7. Other Sources of Olefins

Market Displacement Effects

Examine other scenarios for methanol displacement effects. Consider effect of oil prices.

Section 4.5 8. Market Displacement Effects of MTO and Naphtha

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Global Warming Potential

Issue: Use of 20‐year vs 100‐year Global Warming Potential; use of Fourth Assessment Report vs. Fifth Assessment report values Comments were received about the use of the 20‐year Global Warming Potential (GWP) values rather than the 100‐year GWP values to report GHG emissions for KMMEF. Related comments indicated that the most recent GWP values from the Intergovernmental Panel on Climate Change (IPCC) should be the basis of the analysis. This section supplements the discussion in the Draft Supplement EIS with a discussion of GWP in general and how it relates to the expected emissions from the proposed project. Section A.6 of the LCA report examines the factors affecting GWP. Figure 6.2 and Table 6.3 examine the effect of GWP on net GHG emissions according to GWP values established by the IPCC in its assessment report. The information indicates that if a 20‐year GWP were considered, the net result of the project, in consideration of the displacement effects would be even greater GHG reductions due to the higher methane emissions from displaced methanol production from coal.1 Numerous greenhouse gases contribute to global warming and climate change, and each gas has different heat trapping effects. Some greenhouse gases are more effective at trapping heat than carbon dioxide (CO2) while others are less. The duration of different gases in the atmosphere is also a factor. For example, CO2 stays in the atmosphere for longer periods while methane (CH4) lasts for a shorter time so its impact is shorter‐lived. While a gas may initially have a large effect, over a longer period as it is removed from the atmosphere, its effect on global warming is reduced as compared to the effect of CO2. The IPCC developed the GWP to allow the comparison of these different heat trapping effects relative to CO2. The GWP compares the amount of heat trapped by a certain mass of a gas to the amount of heat trapped by the same mass of CO2. The result is expressed as a factor of the GWP of CO2. GWPs are used as the common unit of measure, known as CO2 equivalents (CO2e), which allows the comparison of emissions across gases. The GWP is calculated over a specific time horizon, commonly 20 or 100 years. The GWP allows the comparison of greenhouse gases with different heat trapping effects and lifetimes in the atmosphere. Methane traps more heat than CO2 per kg of each gas. However,

1Methane releases from coal and surrounding rock strata occur during coal mining operations. It represents approximately 50 percent of the emissions from coal mining operations. A change in the GWP that increases the CO2e of methane results in increased calculated CO2e from coal mining operations. Page 129 of the LCA report discussed coal mine methane emissions. These emissions are quantified on page 84 and 85 of the LCA and show that methane emission make up the majority of upstream life cycle emissions of coal extraction. For example, under the Baseline AR4‐100 year GWP upstream emissions for coal based methanol are calculated as 1.81 million tonnes CO2e /year (Table 2 below) and for the AR4‐20 year GWP they are calculated as 3.77 million tonnes CO2e /annum (Table 4 below).

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because of photooxidation, CH4 breaks down in the atmosphere to CO2 within 20 years and the resulting CO2 persists in the atmosphere for centuries. 2The time dependence is taken into account with the GWP. This supplemental memorandum compares the GWP effect in the IPCC’s fifth assessment report (AR5) with the GWP in fourth assessment report (AR4), and discusses the 20 versus 100‐year time horizon. The primary difference between the AR4 and AR5 values is that the AR5 takes into account the latest data and analysis, including atmospheric concentrations of pollutants as well as the fate of secondary pollutants when CH4 and Nitrogen Dioxide (N2O) decompose in the atmosphere. For an example of this would change emission values, CH4 has a CO2e of 30 when considered over 100 years but a CO2e value of 85 over 20 years based on the IPCC AR5 GWPs as shown in Table 1.1 of the LCA report. To put this into context this means that 1 kg of CH4 released into the atmosphere today would have the same heat trapping impact as releasing 85 kg of CO2 if impacts are considered over 20 years and the same impact as 30 kg of CO2 over if the impact is considered over a period of 100 years. The DSEIS used GWP factors because the project would result in GHG emissions of three different gases over three different periods: CO2, CH4, and N2O and considered under both AR4‐100 and AR5‐100 as well as AR5‐20 GWP factors. Ultimately, the EIS focused its analysis and conclusions on emissions using the IPCC’s AR4‐100 GWP values. The AR4‐100 GWP factors are consistent with international, U.S., and Washington reporting requirements (EPA, 2014; Ministry of Energy Mines and Petroleum Resources, 2017; United Nations/Framework Convention on Climate Change, 2015; WA Dept of Ecology, 2011, 2016, Washington Administrative Code (WAC) 173‐441‐040 Table A.1). The AR4 values are used for reporting because the AR5 values have not been adopted for GHG reporting by Washington (Ecology, 2011, 2016). To understand the differences between the two sets of values for KMMEF, Tables 2 and 3 compare the emissions and displacement impact of the KMMEF for both AR4 and AR5 basis using 100‐year GWP values and the same baseline, lower, upper and market mediated scenarios used in the DSEIS (see Table 3‐7). The net GHG reductions are greater with the AR5 basis due to higher methane leaks associated with displaced methanol.

2 Methane reacts to produce water vapor and CO2 in the presence of sunlight, oxygen and ozone in the atmosphere.

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Table 2. Annual GHG Emissions from KMMEF Methanol – AR4‐100

Average Annual GHG Emissions (million tonne CO2e /annum)

Scenario Baseline Lower Upper Market

Mediated Baseline in WA

Construction Emissions Direct 0.0004 0.0004 0.0004a 0.0004a 0.0002

Upstream 0.015 0.015 0.015 0.015 0.0008

Operational Emissions Upstream Natural Gas 1.04 1.025 1.225 1.041 0.052

Upstream Power 0.19 0.00 0.28 0.22 0.17

Direct Emissions 0.73 0.73 0.73 0.73 0.73

Downstream Emissions 0.17 0.17 0.30 0.17 0.00009

Petroleum Fuel Production 0.03 0.03 0.06 0.03 0.0048

KMMEF Total 2.17 1.96 2.62 2.20 0.96

Displaced Emissions Upstream Feedstock ‐1.81 ‐1.90 ‐0.91 ‐1.61 Upstream Power ‐0.66 ‐0.94 ‐0.66 ‐0.66 Direct Emissions ‐10.92 ‐11.47 ‐10.40 ‐10.92 Downstream Emissions ‐0.24 ‐0.24 ‐0.24 ‐0.24 Petroleum Fuel Production ‐0.06 ‐0.06 ‐0.06 ‐0.06

Displaced Total ‐13.69 ‐14.61 ‐12.27 ‐13.49

Net Emissions ‐11.5 ‐12.6 ‐9.6 ‐11.3

Same as Table 6.1 from LCA report. Note: the direct construction emissions included a typographical error in the DSEIS which has been corrected here.

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Mediated Baseline in

WA

Construction Emissions Direct 0.0004 0.0004 0.0004 0.0004 0.0002

Upstream 0.0146 0.0146 0.0146 0.0146 0.0008


Upstream Power 0.1869 0.0000 0.2827 0.2249 0.17




Subtotal 2.24 2.0374 2.7223 2.2807 0.96


Displaced Subtotal ‐13.91 ‐14.83 ‐12.40 ‐13.71

Net Emissions ‐11.67 ‐12.79 ‐9.68 ‐11.43 It should also be noted that this project would be subject to Washington state regulations on GHG emission reporting. Ongoing tracking of the GHG emissions from the KMMEF project would be based on the GHG factors that are required by the state at the time of reporting. The AR‐4 values are currently required per WAC 173‐441‐040, Table A.1

1.1. 20‐ versus 100‐Year Time Horizon

The GWP of CH4 represents the ratio of the heat trapping effect of CH4 divided by the heat trapping effect of CO2 over a specific time horizon. As described in Appendix A.6 of the LCA report, the absolute global warming potential (AGWP) represents the cumulative warming effect of each gas in terms of warming energy over time (see units in Figure 1). The time horizon affects the GWP of CH4 and N2O emissions. The GWP of CO2 is always 1.0. Most of the cumulative warming effect of CH4 takes place within 20 years.3 The AGWP CH4 curve levels off while the cumulative AGWP effect of CO2 continues for several hundred years. Therefore, the

3 The AGWP of CH4 is 22 on the right‐hand scale after 20 years and 26 after 500 years and beyond, or 77 percent of the total warming effect from CH4 occurs within the first 20 years. The AGWP of CO2 is 0.27 after 20 years and 3.2 after 500 years, or 8.4 percent of the warming effect over 500 years occurs within the first 20 years. Note that the ratio of 22/0.27 = 82 which is the 20‐year GWP of CH4.

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100‐year GWP provides a representation of GHG emissions that takes into account more of the warming effect of the pollutants. The 100‐year GWP takes into account all of the warming effect of methane4 (and 28 percent of the warming effect of CO2 over a 500‐year period.

Figure 1. Development of AGWP‐CO2, AGWP‐CH4, and GWP‐CH4 with Time Horizon Source: Myhre, 2013

Given the significant global warming effect of CO2 and the long‐term need to stabilize climate change, the use of the 20‐year time horizon does not accurately represent the impact of emission sources with a mix of CO2 and CH4 emissions for assessing the global warming impacts of this project.

4 The oxidation of CH4 to CO2 is not shown in this chart as the AGWP curve tapers off to horizontal.

77% of the warming effect of CH4 occurs within 20 years

Only 8.4% of the warming effect of CO2 occurs within 20 years

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Table 4 and Table 5 compare the emissions and displacement impact of KMMEF on the basis of AR4 and AR5 using 20‐year GWP values. The net GHG reductions are greater with both the AR4 and AR5 20‐year factors due to higher methane leaks associated with displaced methanol.

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Average Annual GHG Emissions (million tonne CO2e/annum)

Scenario Baseline,

AR4 Lower Upper Market


WA


Upstream 0.016 0.016 0.016 0.016 0.0009


Upstream Power 0.20 0.00 0.30 0.38 0.17




Total 2.89 2.66 3.66 3.07 0.96



Net Emissions ‐12.9 ‐14.1 ‐9.9 ‐12.5

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Scenario Baseline, AR4 Lower Upper Market

Mediated Baseline in WA


Upstream 0.016 0.016 0.016 0.016 0.0009


Upstream Power 0.21 0.00 0.310 0.39 0.17




Subtotal 3.09 2.86 3.95 3.28 0.96



Net Emissions ‐13.2 ‐14.5 ‐9.9 ‐12.9

In comparing the effect of using different GWPs, the emissions in CO2e alone are greater using a 20‐year GWP compared to 100‐year GWP and are greater using that from AR5 than using AR4; when you compare KMMEF life cycle emissions with market displacement alternative sources of methanol, using the 100‐year, AR 4 GWP results in the least amount of displacement, and thus is the most conservative figure for disclosure (reflecting higher emissions) comparison of net displacement.

Potential for Supply shifts in Natural Gas Supply due to KMMEF

Issue: Effect of possible supply shifts on emissions. Using natural gas at KMMEF will represent new demands or changes in demand for natural gas in the Western U.S. Several comments questioned the potential effect on GHG emissions if existing natural gas users in Washington shifted supply from Canada to U.S. sources due to a lack of available gas from Canada or changes in prices associated with the use of additional natural gas by the KMMEF. Section 2.4.2 of the LCA report examined the gas flows in the region based on data from the Energy Information Administration (EIA). As indicated in Table B.6 and Figure 2.8 of the LCA report, almost all of the gas entering Washington comes from Canada, while Rocky Mountain gas primarily moves to Nevada and California. Moreover, at full methanol output, the gas used by the KMMEF over its 40‐year lifetime is less than 1 percent of the gas reserves in British Columbia (Province of British Columbia 2019) and on a yearly basis

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represents approximately 5 percent of the available marketable gas in British Columbia.5 This fraction of gas usage is not expected to have a significant effect on the price of natural gas in the Western U.S., and should not cause a significant shift of gas supply for the other users in the Western U.S.

Upstream Natural Gas Emissions and Methane Leakage Rates

Issue: GHG emissions from methane from upstream natural gas. Some comments noted the range of methane emissions and upstream emission data from natural gas production used in the LCA report and DSEIS was under estimating expected emissions from these sources. As described in Section 3.2 of the LCA, a wide range of studies and emission rates were reviewed in developing upstream emissions from natural gas. Figure 6.2 of the LCA report presented the ranges of emissions used in the LCA to develop the sensitivity analysis. The sensitivity analysis allows decision makers to evaluate the potential impacts of the project under a variety of modelling assumptions. The Baseline Scenario in the LCA report used the upstream emissions for natural gas production based on the GHGenius model. GHGenius is used for many policy initiatives to estimate emissions from industrial and fuel production facilities ((S&T) Squared 2019, Ministry of Energy Mines and Petroleum Resources 2017, Navius 2017). The GHGenius model was used for the Baseline Scenario because it has regionally specific detail on natural gas upstream emissions for Canadian provinces, including British Columbia. Differences in emission rates for gas production depend, in part, on regulations and production practices. Other LCA models such as GREET also examine the upstream life cycle emissions from natural gas production. These models and studies are summarized in Appendix B of the LCA report and further clarification is provided here. As shown on Table 3.7 of the LCA report fugitive methane emissions (or leaks) result in an approximately 35% of the upstream CO2e emissions due to the GWP of methane (see GWP discussion above). Leaks can occur at the gas well, at the processing plant and along the transmission route. The following section gives more detail on the GHG emissions of likely sources of natural gas as well as the estimates of methane emissions in LCA models. The role of methane in the upstream emissions of natural gas were described in Appendix B.1 of the LCA report. Taking this data and the other sources identified here into account, the GHGenius estimates are in the mid‐range of estimates. Emission estimates in the GHGenius model that were used in the LCA study are consistent with the inventory for emission from British Columbia. Regulations in British Columbia also support a lower estimate in methane leakage than those estimated for the United States. Data on leak rates that were presented in the LCA report and additional studies are then discussed here. Many leak studies identify total methane emissions but do not address the allocation between natural gas and oil production. The relationship between leak rates and LCA model inputs are

5 Based on 2018 values as reported by the Province of British Columbia. https://www2.gov.bc.ca/gov/content/industry/natural‐gas‐oil/statistics

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also examined. Finally, the effect of the various leak rates are compared to the sensitivity analysis previously presented in Section 6.1 of the LCA report.

3.1. British Columbia Methane Emissions

Additional consideration of the province’s existing emission regulations factored into the decision to use the regionally specific GHG data for British Columbia in the LCA’s Baseline Scenario. The GHG emissions are regulated by a combination of existing and new legislation at both provincial and federal levels; some of these encompass methane fugitive emissions. At the federal level, the government has committed to reducing methane emissions by 40 to 45 percent below 2012 levels by 2025 (Lee‐Anderson 2017). In conjunction with Canada’s commitment to the Paris climate agreement, on May 27, 2017, the government proposed regulations to reduce the release of methane and certain volatile organic compounds (VOCs). The regulations target three primary sources of methane emissions and will go into effect starting in 2020 or 2023 depending on applicability. The regulations concern these topics:

1. Conservation (capture) or destruction of methane gas released by hydraulic fracturing

wells

2. Ceiling on and restrictions of emissions from compressors

3. Additional requirements on conservation and destruction equipment

a. Equipment must capture and conserve at least 95 percent of the methane

emissions

b. Hard limits on methane venting rate

c. Leak detection and repair (LDAR) system

d. Emissions from pneumatic controllers and other equipment

These federal regulations recognize that British Columbia already has “conserve or destroy”6 restrictions in place under provincial regulations and thus will only enforce the restrictions that are not already in place. On January 16, 2019, the BC Oil and Gas Commission announced new regulations aiming to reduce methane emissions from upstream oil and gas operations (BC Oil and Gas Commission 2019b). The new regulation amends the existing drilling and production regulation by incorporating methane emission controls (BC Oil and Gas Commission 2018). The new regulation aims to meet or exceed the Canadian methane reduction targets. This British Columbia provincial regulation, similar to the Canadian federal regulation, enforces a system of leak detection and repair requirements that will begin January 1, 2020. The regulation enforces periodic “screening survey” and “comprehensive survey” of methane leaks followed by corrective action or repairs. The regulation includes restrictions on emissions from the following sources (BC Oil and Gas Commission, 2019a):

6 This term is used in regulations that require either the capture of methane for productive use or reinjection into storage (conserve) or the destruction through combustion to produce CO2.

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1. Pneumatic devices

2. Equipment leaks

3. Compressor seals

4. Glycol dehydrators

5. Storage tanks

6. Surface casing vents

The Commission estimates that the regulation will reduce methane emissions by 10.9 million tonnes of CO2e over a period of 10 years or 1.09 million tonnes of CO2e per year, which represents an approximately 25 percent reduction in the fugitive methane inventory. Historical reductions in the British Columbia inventory are shown in Figure B.3 of the LCA report. Any reductions in GHG emissions due to the implementation of future regulations are not reflected in the analysis here. There is a potential for a small percentage of the gas to come from Alberta in addition to British Columbia because of the interconnected nature of the pipeline network and the fact that the Montney field spans both provinces. Upstream life cycle GHG emissions are analyzed for all Canadian Provinces in GHGenius. The total upstream life cycle emissions are lower for Alberta than for British Columbia though the model does not take into account movement from Alberta through British Columbia. The gas leaks and flare component is slightly lower for Alberta. The total upstream emissions for gas from Alberta if transported to Washington would be the same as that of British Columbia gas based on GHGenius.

3.2. Range of CH4 Emission Rates

Comments were received regarding the potential for methane emissions in the life cycle as well as GHG emissions from natural gas production by hydraulic fracturing. Recent data on methane leaks have been published in the scientific literature. Appendix B of the LCA report documented these data sets. Leak rates based on studies performed in collaboration with the Environmental Defense Fund (EDF) study (Alvarez, et. al. 2018) were evaluated and shown in the sensitivity analysis in Figure 6.2 of the LCA report. The following section discusses the range of leak rate estimates and how the data are incorporated in the upstream life cycle analysis. Appendix B of the LCA report examined a range of methane emission rates from upstream natural gas sources. The emission rate from the baseline case GHGenius and the Upper estimate utilizing GREET resulted in upstream GHG emissions of 1.04 and 1.23 million tonnes of CO2e per year respectively (See Table 6.1 of the LCA). Figure 6.2 of the LCA showed the effect of using higher leak rates including those reported in the EDF study. Information on methane emission rates have been published from other sources. The Argonne National Laboratory (ANL) recently updated the GREET model from version 2017 to version 2018. The ANL values reflect U.S. natural gas production and upstream emission rates. While U.S. derived gas is not proposed nor available for use at the KMMEF, these values provide a high estimate of the upstream emissions from natural gas production and transport to establish an upper range. ANL’s assessment shows a small increase in the methane leak rate from the

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2017 GREET model to the 2018 GREET model for the upstream emissions for U.S. natural gas production. However, the overall upstream emissions for U.S. natural gas production are lower in the 2018 analysis because of lower estimates of CO2 from flaring. Fugitive emissions from natural gas production in British Columbia are addressed in multiple estimates, including estimates completed by the provincial government and others based on peer‐reviewed studies. To independently assess the validity of the leak rates in the GHGenius model, emissions from various sources will be considered to determine how it could affect emissions. British Columbia quantified its 2015 methane leakage as 4.65 billion cubic feet or 98,500 tonnes of CH4 from all oil and gas operations (British Columbia, 2018). Dividing this estimate by the total natural gas production in the province of 1,801 billion cubic feet yields a methane leak rate of approximately 0.26 percent and provides a comparison of the nominal leak rates from different LCA studies shown in Appendix B.1 of the LCA report. This leak rate does not take into account allocation to co‐produced crude oil and natural gas liquids which would result in lower CH4 emissions than assigning all of the emissions to natural gas production. A recently published study of atmospheric methane concentrations estimated 111,800 tonnes CH4 compared to the bottom‐up inventory of 78,000 tonne CH4 for the year analyzed (Atherton, 2017). These emissions are consistent with the controls required in British Columbia and with the inventory values from Appendix B.1 of the LCA report. The methane emissions from the GHGenius model are consistent with the current GHG inventory for British Columbia, and the inventory has been declining over time (see Appendix B of the LCA report). GHGenius version 5a, which is newer than GHGenius version 4.03 ((S&T) Squared, 2013) as used in the LCA report is also available. However, the upstream emissions for natural gas in GHGenius version 5a are grouped differently than those in GHGenius version 4.03 with no increase in emissions. Thus, the update in GHGenius does not affect the analysis of KMMEF emissions in the LCA. Many of the comments regarding natural gas leak rates reflected scientific papers that address specific aspects of oil and gas operations or examine total leak rates using different measurement techniques. The 2018 EDF study completed by Alvarez previously mentioned provided an assessment of estimated underreporting of the inventory of leak rates. The leak rate is reported as 2.3 percent of natural gas production. However, methane leaks occur in both oil and natural gas operations and the reported leak rate is for combined operations. To obtain an accurate estimate based on the component attributable to natural gas production the total leak rate needs to be converted to an LCA model inputs, which was done by Argonne National Laboratory in the 2018 update to GREET. The GREET model includes an EDF assumption option for natural gas losses (but not for crude oil production). The increased leak rate used in ANL’s GREET model is 60 percent greater than the EPA inventory which is also consistent with the reported increase over EPA inventory estimates in the Alvarez paper.

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Several studies show extraordinarily high leak rates from oil and gas operations with high range estimates of 9 to 17% (Howarth et al. 2015; Caulton et al. 2014; Schneising et al., 2014; Karion et a. 2013). All of the studies cite the high variability in emissions. These emission rates have not been incorporated into statewide emission inventories due to the evolving science and uncertainty in the estimates. A study by Stanford University, the University of Calgary, and others (Brandt, 2017) shows that independent emission measurements can be greater than the official emission inventory or emission factor. Analysis of the key graphic in the study indicates that leak rates may be two times the inventory values. The Alvarez study of U.S. oil and natural gas supply chain indicates that high emitting gas fields may emit 15 times the methane that is expected in the U.S. national GHG inventory and that 20 percent of the sites emit 60 percent of the methane from oil and gas production. Many of the emissions are associated with so called “super emitters”. Therefore the estimates are difficult to translate to leak rates to cover the industry as a whole, as they represent only a small number of sources. Since the Alvarez study provides an overall assessment of the high estimate of CH4 emissions and these estimates are incorporated as a GREET option, the GREET EDF option provides the high range of emissions from natural gas production. Other papers cited in the comments mention individual components as a source of GHG emissions but the GREET EDF case provides the best estimate of the high range based on peer reviewed literature. Table 6 identifies various estimates of methane leakage rates from natural gas production which were previously presented in Appendix B of the LCA report. The data are grouped according to LCA model inputs, emission inventories, and leak rate studies. Data that were not presented in the LCA report are shaded.

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Table 6. Summary of Recent Upstream Natural Gas Leakage Estimates (as a % of gas delivered)

Activity Type Gas Field Leaks

Processing Leaks

Transmission Leaks

Distribution Leaks

Total Leaks

Model Inputs

GHGenius (S&T) Squared, 2013

BC 0.18% 0.003% 0.014% 0.13% 0.32%

GREET1_2015 Shale 0.34%

0.13% 0.41% 0.43% 1.30%

Conv. 0.30% 1.26%

GREET1_2016 Shale 0.77%

0.13% 0.36% 0.14% 1.38%

Conv. 0.70% 1.32%

GREET1_2017a Shale 0.67%

0.03% 0.22% 0.08% 1.00%

Conv. 0.66% 0.99%

GREET1_2018a Shale 0.681%

0.03% 0.21% 0.09% 1.02%

Conv 0.664% 1.00%

Inventories of Annual Emissions

BC Inventory (British Columbia, 2018)

BC 0.26% 0.1% 0.03% 0.01% 0.4%

EPA GHGI 2013 datab U.S. 0.31% 0.15% 0.36% 0.22% 1.04%

EPA GHGI 2014 datab U.S. 0.68% 0.15% 0.20% 0.07% 1.11%

Methane Leak Rate Studies

EDF Studies 2015d U.S. 0.58% 0.09% 0.25% 0.07% 0.99%

NG Vehicle LCA (Tong, 2015) e

U.S. 0.49% 0.04% 0.46% 0.31% 1.30%

Direct Source Measurements (Allen, 2013)c

U.S. 0.38% n/a n/a n/a

BC Mobile Measurement (Atherton, 2017)

BC 0.3% ‐‐ ‐‐ ‐‐ ‐‐

G7 Study (Brandt, 2017) BC 0.18% n/a n/a n/a n/a

EDF (Alvarez, 2018)

Allocated to oil and NGf U.S. 1.08% 0.24% 0.32% 0.11% 1.78%

All assigned to NGg U.S. 1.8% 0.13% 0.32% 0.08% 2.3% a The extraction, processing, and transmission fugitives are 135.5, 6.8, and 44.7 g CH4/mmBtu respectively. The GREET model identifies the distribution but does not use it since industrial and commercial NG users are upstream of the local distribution; see Table 7 for GREET1_2018 inputs. b Reported in EPA 2015 and EPA 2016. c Taken from ANL “Updates to CH4 Emissions with Natural Gas Pathways in GREET1_2015,” Table 5 – ANL divided reported methane emission values by U.S. Energy Information Administration (EIA) gross withdrawals. d The gas field value uses EPA’s value for gas field emissions (0.31 percent) and Marchese’s value for gathering (0.27 percent). The processing value is a combination of EPA’s value for routine maintenance and the Marchese, 2015 processing value. Transmission is from Zimmerle, 2015.Distribution is from Lamb, 2015. e The gas field estimate also includes road construction, well drilling, and fracking emissions. f EPA 2014 values x 1.6 based on 60 percent increase from the EPA emission inventory estimates based on the Alvarez study.

g Emissions are not allocated between crude oil and natural gas production but instead assigned only to natural gas.

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3.3. Conversion of Leak Rates to LCA Model Inputs

The GREET model is parameterized with CH4 emissions from the EDF studies. It provides a basis for further examining comments encouraging the use of EDF studies on methane emissions. The EDF data are represented in both the GREET1_2017 and GREET1_2018 models. Both leakage and flaring rates vary in these models and the effect of using these different rates is examined below. Total fugitive emissions reported in the EDF studies correspond to oil and gas production and therefore it is necessary to allocate total fugitive emissions between the crude oil and the natural gas produced by the same well. The allocation depends upon the amount of associated gas produced with crude oil. It is also important to note that these figures are an average, and emission rates vary broadly over regions. For example, measurements in the Bakken shale in North Dakota account for a significant source of U.S. GHG emissions from natural gas production (Kort, 2016). All of these studies highlight the need for improved monitoring of natural gas production operations. Translating these emissions to LCA inputs is challenging because the atmospheric measurements are site‐specific and do not represent an overall inventory. The estimate of 60 percent greater than the EPA inventory in Alvarez 2018 is consistent with the sensitivity analysis included in Figure 6.2 of the LCA report (reproduced below). Figure 6.2 of the LCA report examined these higher leak rates and the emission rates identified in the EDF study is represent by the solid blue square. The higher leak rates were not added to the cumulative sensitivity analysis since all of the uncertainties in emissions would be additive. A sensitivity analysis is used to examine issues relating to uncertainties in model structure, or in input or parameter values. The objective of sensitivity analysis is to estimate the uncertainty in the model's predictions caused by uncertainty in the values of inputs and to determine the degree to which inaccuracies in their assumed values could lead to changes in predictions. It would be inappropriate to consider and calculate emissions based on all the variabilities presented by the sensitivity analysis.

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Table 7 shows the GREET inputs for methane leaks as well as flaring in the GREET1_2018 model based on the EPA and EDF scenarios as explained below. Methane leaks are represented in g CH4/mmBtu, LHV of natural gas delivered to the pipeline system.7 The GREET model leakage factors take into account the allocation of emissions between oil and gas production as well as the co‐produced natural gas liquids. Therefore, the frequently cited 2.3 percent of U.S. natural gas production does not translate directly to GREET inputs. The EDF 2018 value in GREET is corresponds to the 60 percent increase in methane emissions over EPA inventory estimates cited in Alvarez 2018. Note that ANL translated of emission estimates from various studies into the GREET input factor (ANL 2017).8 The GREET input for the 2017 and 2018 models has a scenario option (labeled EDF) that if selected takes into account the higher range of CH4

emissions.

7 The lower heating value (LHV) is used as the denominator for emission rates in many LCA models. The net GHG emission results are the same as long as the conversion units are tracked properly. The upstream life cycle data in the LCA report were shown in on a higher heating value (HHV) basis since natural gas is purchased on an HHV basis. The LHV based emission rates can be converted to HHV‐based rates by multiplying by 0.903. 8 The density of natural gas (19,600 g natural gas to produce a mmBtu of natural gas) allows the comparison of the GREET input of 137 g leak/mmBtu CH4 to a percentage leak rate of 0.7%.

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Table 7. GREET1_2018 Inputs for Natural Gas Production

a GREET1_2017 Recovery‐Flaring input is 9,789 Btu NG/mmBtu NG. On a higher heating value basis, upstream life cycle GHG emissions based on AR5 factors for natural gas are 11,485 g/mmBtu in version 2017 and 10,944 g CO2e/mmBtu in the 2018 version, which reflects the increase in CH4 and reduction in flaring.

137 g CH4/mmBtu × 160% from Alvarez 2018 = 219 g/mmBtu, which is consistent with the representation of the EDF value above.

The upstream life cycle GHG emission results from GREET1_2018 (based on inputs from Table 7) with the EDF parameters are 14,694 g CO2e/mmBtu, Higher Heating Value (HHV)9 of natural gas with the AR5 100 year GWP. The upstream natural gas emissions with the EDF leakage rates value from GREET1_2018 with AR5 100 year GWP values results in upstream natural gas emissions of 1.57 million tonnes per year (MTPA) of CO2e, which is 0.53 million tonnes of CO2e higher than the baseline case using GHGenius and AR4 values. This is higher than the Upper scenario examined in the LCA but is consistent with the “Alvarez, 2018” scenario presented in the sensitivity analysis on Page 98 and 99 of the LCA report. The net GHG emissions for this scenario result in a net GHG reduction of 0.31 MTPA, since the AR5 GWP also affects the emissions displaced by the shift from coal based methanol. The comparison of the baseline result with the EDF/AR5 values is shown in Table 8.

9 Higher Heating Value is a measure of heat content based on the gross energy content of a combustible fuel. Heat content of combustible energy forms can be expressed in terms of either gross heat content (higher heating value) or net heat content (lower heating value), depending upon whether or not the available heat energy includes or excludes the energy used to vaporize water (contained in the original energy form or created during the combustion process).

Unit

Conventional

NG Shale gas

Conventional

NG Shale gas

Recovery ‐ CH4 Leakage and Venting g CH4/mmBtu NG 137.1 140.6 214.3 214.3

Recovery - Completion CH4 Venting g CH4/mmBtu NG 0.5 3.3 N/A N/ARecovery - Workover CH4 Venting g CH4/mmBtu NG 0.0 0.7 N/A N/A

Recovery - Liquid Unloading CH4 Venting g CH4/mmBtu NG 4.4 4.4 N/A N/AWell Equipment - CH4 Venting and Leakage g CH4/mmBtu NG 132.2 132.2 N/A N/A

Processing - CH4 Venting and Leakage g CH4/mmBtu NG 5.9 5.9 9.5 9.5

Transmission and Storage - CH4 Venting and Leakage g CH4/mmBtu NG/68 43.6 43.6 60.4 60.4

Distribution - CH4 Venting and Leakage g CH4/mmBtu NG 19.4 19.4 19.4 19.4

2 emission rate for recovery and processing in conventional NG and shale gas pathways

Unit Conventional NG Shale gas nventional NG Shale gas

Recovery ‐ Flaring Btu NG/mmBtu NG 1,749 1,484 1,749 1,484

Recovery ‐ Venting g CO2/mmBtu NG 19 19 19 19

Processing ‐ Flaring Btu NG/mmBtu NG 3,018 3,018 3,018 3,018

Processing ‐ Venting g CO2/mmBtu NG 547 547 547 547

Used in calculation: EPA 2018 EDF 2018

EPA 2018 EDF 2018

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Table 8. Effect of Higher CH4 Emissions on Net GHG Emissions (million tonnes/year) for the Baseline Scenario

As shown, using a higher leak rate would increase the emissions from Upstream Natural Gas and Petroleum Fuel Production sources. Note that the Baseline scenario does not represent the lowest GHG emissions of the different scenarios (baseline, upper, lower and market mediated) considered in the DSEIS. Use of higher leak rate assumptions would also affect the upstream emissions associated with other olefin production routes. Natural gas is a small fraction of the coal‐to‐methanol‐to‐olefin route. However, methane leak rates from oil production are as significant in the crude oil‐to‐ naphtha‐to‐olefins pathway as they are in the KMMEF natural gas to methanol to olefin (MTO) route. These effects are examined in Section 7.

Power Generation Emissions

Issue: Emissions from upstream purchased power. Some comments concerned the greenhouse gas intensity of purchased power at KMMEF and suggested that the resource mix described by the Northwest Power and Conservation Council (NPCC 2018) marginal generation mix be used in calculating project related GHG emissions from purchased power. Table 9 shows the effect of the NPCC mix if that electricity mix were to be applied to purchased power for the KMMEF. The emission factor used here represents the high range of potential emissions from power generation.

Upstream Data Source for NG GHGenius

4.03 GREET1_2018

GWP Factor AR4‐100 AR4‐100 AR5‐100 AR5‐20 AR4‐20

Process parameters/ electricity mix Baseline

Baseline Adjusted with GREET Natural Gas and EDF Leakage Rate


Upstream 0.015 0.015 0.015 0.016 0.016


Upstream Power 0.19 0.19 0.19 0.21 0.20




KMMEF Total 2.17 2.54 2.70 4.46 4.04

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Table 9. Effect of NPCC Power Mix on KMMEF Methanol – AR4‐100 GWP

Average Annual GHG Emissions (million tonnes/year)

Scenario Baseline Baseline NPCC

Baseline in WA NW Power Council

Construction Emissions

Direct 0.0004 0.0004 0.0002

Upstream 0.015 0.015 0.0008

Operational Emissions

Upstream Natural Gas 1.04 1.04 0.052

Upstream Power 0.19 0.37 0.37

Direct Emissions 0.73 0.73 0.73

Downstream Emissions 0.17 0.17 0.00009

Petroleum Fuel Production 0.03 0.03 0.005

KMMEF Total 2.17 2.36 1.16

Source: Northwest Power Council power generation mix

The market‐mediated scenario in the LCA report examined a marginal power mix (see Section 2.4.4) as described in Appendix B.2. The marginal analysis in the LCA report takes into account Washington’s expected low growth and change in resource mix, including a 15 percent renewable portfolio standard, which is the best estimate possible of marginal power generation mix that supports a permanent and sustainable load growth. This estimate was included in the LCA report as the Upper scenario. The issue of determining and selecting the life cycle GHG intensity for purchased power is not unique to the KMMEF. For example, new demands for electric power have been considered in fuel policy development by California and Washington. Electric power is used for charging electric vehicles, converting water to hydrogen, or as an input for fuel production facilities. These technologies have been examined in fuel policies such as the California Low Carbon Fuel Standard and the state of Washington Clean Fuel Standard (examined in 2014 and currently under development). The permanent and sustainable load growth for these fuel production technologies is comparable to that of the KMMEF. For example, 400,000 electric cars (80 percent of California’s population), 20 miles/day, 0.3 kWh/mile/24 hours requires 100 megawatts of new power, which is the same as the import power for the KMMEF. As discussed below, the treatment of electric power under these fuel policies has evolved over the decades and the treatment of new loads in the Baseline scenario is the same as that for other new loads considered in developing state‐level environmental policy.

Alternative Supply Scenarios

Issue: Potential for other sources of methanol and olefins to affect analysis.

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Several comments questioned that KMMEF methanol had not been compared with other natural gas‐based methanol plants and asked what would happen if more natural gas‐based methanol plants were constructed. Methanol could be supplied to the market from other projects built in different locations. Market research publications cite growth from 130 to 240 million tonnes per year from 2017 to 2026 (GlobalData 2018; Spilker 2018). Recent announcements of several methanol projects in North America include (NOTE – specific references to be added in final version):

Sabic/SL South Louisiana methanol plant (Chemical Week 2019)

Celanese Clear Lake Texas (Chemical and Engineering News 2019)

Primus Green Energy New Martinsville, West Virginia10 (Cision PR Newswire 2018)

IGP Methanol, Myrtle Grove Louisiana (IGP Methanol 2019)

“YCI Methanol St. James Parish Methanol Project (Business Wire 2018)

Methanex Geismar, Louisiana (Methanex 2019)

Natgasoline, Beumont, Texas (Enterprise 2018)

While these projects have been announced, projects that advance to construction and operations are typically much fewer than those announced. Thus, it is not possible to predict actual future supply based on these project announcements. The growth in the demand for methanol is the underlying driver for the projections of new capacity. The Methanol Institute identifies current global capacity as 110 MTPA with demand of 75 MTPA (Methanol Institute 2018), with much of the underutilized capacity in China as indicated in Section 4 of the LCA report. However, with future global methanol demand growing to over 110 million tonnes per year (refer to references in Section 4.5.2 of LCA report, Alvarado, 2017) meeting this demand will require new production capacity. Natural gas‐based methanol projects and additional natural gas‐based capacity will compete with less cost‐effective plants in China. As described in the LCA report methanol capacity in China exceeds demand while lower cost natural gas‐based methanol is still imported and outcompeting coal‐based production in China. The potential completion of the projects that have been announced could affect the global supply of methanol. The analysis presented in Section 4 of the LCA report identified global methanol producers and the facilities that could ship to China. The available current capacity was based on historical imports to China. Figure 2 shows the history of methanol production and consumption in China. China has been a net importer of methanol while having excess production capacity, presumably because the imported methanol is produced at a lower cost than the domestic product, even with a planned economy in China. Therefore, new natural gas‐based capacity is expected to continue to displace Chinese production. While factors of production are determined by the Chinese state in a planned economy in the short term, in the

10 This project would not have access to Chinese markets but would increase global production

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long run, economics would eventually prevail because the cash cost of KMMEF‐produced methanol is under $150 per tonne. The KMMEF plant will be competitive compared to the current plants in China (see natural gas prices and yield in the LCA report Section 4.4).

Figure 2. Methanol Production and Imports in China (million tonnes/year) Source: Methanol Institute, 2019

Several developers are planning new methanol production projects globally. Likely locations for new facilities include the U.S. Gulf Coast, Australia, and Iran. The capacity of these projects ranges from small scale to 5 MTPA. In addition to China, these facilities will provide methanol to a chemical market that is growing globally. In order to assess the effect of additional natural gas‐based methanol, the supply and demand analysis was modified to include the following capacity additions in the Gulf Coast, Australia, and Iran. These projects would take time to develop but, when completed, would affect the supply curve shown in Figure 4.17 of the LCA report. This analysis assumes three new natural gas to methanol plant locations with the following capacities to evaluate the market impacts from additional natural gas to methanol facilities.

1. U.S. Gulf Coast and Trinidad– 3.6 MTPA

2. Iran – 5 MTPA

3. Australia – 1.8 MTPA

These plants were selected because they could hypothetically access the China market and they address the question about the potential effect of more natural gas‐based capacity becoming available. Historically, China has imported methanol from the Middle East, Southeast Asia, and the Gulf Coast of the U.S (Simoes 2019). All of these projects are consistent with earlier imports of methanol to China and with the global export capacity shown in

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Figure 3: Source of Global Methanol Exports (2017) (Simoes 2019)

Figure 4. Global Methanol Imports to China (2017) (Simoes 2019)

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The development of Gulf Coast projects is described above and the construction of new Iranian projects is described in an industry trade article (ICIS 2019). The Iranian capacity tends to be as large as projects in the United States. Since Southeast Asia has also historically shipped methanol to China, a hypothetical Australian plant was examined as the basis for gas prices and transport distance.

Certainly, global natural gas‐based methanol capacity will grow apace; however, the new capacity will affect new demand both in China and globally. The capacity expansion discussed above illustrates an aggressive case of new supply within the context of the supply and demand scenarios considered in the LCA report as shown in Figure 5.

With the additional capacity shown above, the supply curve shifts to the right as shown in Figure 5. The 10,400 k tonnes per year of capacity displaces the capacity of China‐based methanol production. Note that new capacity without the opportunity to reach China could be introduced elsewhere in the world. Regional trading of methanol would result in a similar effect. Note that the size of the yellow circles is proportional to the methanol plant capacity identified above.

Figure 5. Effect of Additional Natural Gas‐Based Methanol on Supply Curve Source: LCA report, Figure 4.17

With the additional capacity, the marginal GHG emissions from the KMMEF are essentially the same as those shown in Section 5 of the LCA report. The key factor affecting GHG emissions from displaced methanol is the coal‐to‐methanol use rate and the transport distance. All of the displaced methanol plants in Figure 5 are coal‐based and, using the method described in Section 4.5.2 of the LCA report, the coal‐to‐methanol conversion rate is essentially the same.

KMMEF

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Therefore, as more natural gas‐based methanol plants are built, more coal‐based methanol plants will be displaced with the same net effect on emissions as shown in Table 1.

Production Scenarios

Issue: Could other technology for gas to methanol/olefins be used and result in lower emissions. Commenters requested the consideration of different methods of methanol production than the natural gas to methanol process that is used for the proposed project. These includes different production technologies as well as different feedstocks. A different natural gas to methanol processing referred to as combined reforming (CR) was a project alternative analyzed in the FEIS. Biogas and biomass are also potential gas feedstocks, albeit in limited current supply. The availability and impacts of these three methods are discussed here.

6.1. KMMEF with Combined Reforming Technology

The CR alternative was analyzed in the DEIS and discussed in the DSEIS but a full analysis was not included of the GHG emissions from this alternative. The CR technology employs a combination of a steam‐methane reformer (SMR) and an autothermal reformer to produce syngas for methanol production. CR technology has been identified as “best available control technology (“BACT”) for gas to methanol processing by in other permit actions (EPA 2013). The CR technology uses a gas‐fired SMR and therefore consumes more natural gas than the ultra‐low emission (ULE) technology that was selected for the KMMEF, where the energy required for the SMR process is supplied by heat recycled within the process. The CR technology generates steam from the waste heat and the steam provides power to the plant so the electrical demand for CR is lower than the electrical demand for ULE technology. The overall carbon balance is shown in Figure 6. Natural gas is fed into the process as reformer feedstock with additional gas burned in a boiler. The electric power requirement for the CR technology would be supplied by existing grid electricity, rather than additional onsite generation, as is required for ULE technology.

Figure 6. Carbon Balance for Combined Reforming Technology

Natural Gas 3295.3 tonne CO2

320 G Btu 36 GBtu 899.6 tonne C

4648 tonne C

0.018 tonne CH4

284 GBtu

10,000 tonne Methanol

3748.5 tonne C

216.9 GBtu, HHV

Methanol Plant

Reformer Heaters &

Boiler

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The process using CR technology results in direct emissions from continuous operation as shown in Table 10, following the same approach used in Section 3.3.2 of the LCA report. Annual direct emissions for continuous operation are 1.1 million tonnes GHG per year compared with 0.72 million tonnes GHG per year for the ULE technology. Consistent the analysis shown in the DSEIS for the ULE Alternative, the emission estimates in Table 10 reflect continuous operation rather than maximum equipment operating levels. Table 10. Direct Emissions from Combined Reforming Technology at KMMEF – AR4‐100

Emission Unit CO2 CH4 N2O CO2e

GHG Emissions (tonne CO2e/yr)

Reformer Heatersa 1,072,322 5.9 0.6 1,072,645

Boilers 114,000 1 0.1 114,048

Cooling Tower 0 0 0 0

Flare Pilot 154.7 0.003 0 155

Flare 0 0 0 0

Tank Vent Scrubber 5.6 0 0 5.6

Ship Vent Scrubber 0 0 0 3.4

Tanks 0.06 0 0 0.06

Emergency Generators 271.9 0.01 0.002 273

Emergency Fire Pump 44.8 0.0 0.0 45.0

Component Leaks 0.1 0.4 0 12.53

Power Generation Turbine 0 0 0 0

Total Direct Emissions 1,186,799 6.9 0.7 1,187,182

kg/tonne methanol 329.7 0.0019 0.0002 329.8 a Feed gas to boiler and reformer furnace would be integrated, so emissions from boilers are included with reformer heaters here. Combustion CH4 and N2O are estimated at the same values as the ULE system.

Table 11 shows the life cycle GHG emissions for the CR technology for the scenarios considered in the LCA report. Note that the direct and upstream natural gas emissions are higher than those of the ULE technology shown in Table 2 while the emissions from power are lower because of the smaller demand for purchased power. Overall, the net life cycle GHG emissions are lower for the proposed ULE technology compared with the CR technology (Table 3.13 in the LCA report shows 270.8 kg CO2e per tonne methanol for the ULE technology). Similarly, the direct emissions within Washington are lower for the ULE technology (0.96 million tonnes per year from

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Table 2) compared to the CR technology (1.29 million tonnes per year from Table 11).

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Table 11. Lifecycle GHG Emissions with Combined Reforming Technology at KMMEF

Average Annual GHG Emissions (million tonnes/year)



WA


Upstream 0.015 0.015 0.015 0.015 0.0008


Upstream Power 0.044 0.000 0.066 0.052 0.040




KMMEF with CR Total 2.66 2.51 3.58 2.58 1.29


Displaced Total ‐13.69 ‐14.61 ‐12.68 ‐13.49

Net Emissions ‐11.1 ‐12.1 ‐9.10 ‐10.9

6.2. KMMEF with Biogas Technology

Many commenters requested that the SEIS consider the life cycle effects of supplying the KMMEF with biogas. While biogas is a potential feedstock for the KMMEF via injection into the pipeline system, current biogas projects and the infrastructure necessary to get the biogas into the pipeline system are limited. Thus, it may not be reasonable at this time to assume any significant portion of the KMMEF natural gas supply from biogas. Pipeline injection of biogas is a strategy for GHG reductions under programs such as the renewable fuel standard (EPA 2016) and the California Low Carbon Fuel Standard (ARB 2015b). Biogas injected into a pipeline receives GHG reduction credits under these programs. Biogas from landfills or anaerobic digesters could also provide a direct or indirect source of natural gas for the KMMEF (American Biogas Council 2015). The use of biogas reduces GHG emissions since the alternative fate of the biogas is either flaring landfill gas (LFG), disposing of manure in a lagoon, or landfilling food waste. The EPA estimates that about 565 municipal waste landfills in the United States provide LFG to one or more LFG energy projects currently in operation, for a total of 623 projects with those in the west shown on Figure 7. EPA estimates that approximately 470 additional “candidate” landfills could cost‐effectively have their methane turned into an energy resource. There are

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four LFG sites in Washington. The KMMEF could incentivize additional landfill projects that feed the pipeline that runs to the project, further reducing the CO2 intensity of the project relative to displaced methanol from coal. Landfills can typically produce 2000 million Btu of biogas per day.

Figure 7. Landfill Gas Projects Source: U.S. EPA, 2019

Biogas from the anaerobic digestion of animal manure can reduce GHG emissions even further since the alternative fate of the manure is disposal in a lagoon. The GHG intensity of the biogas is about ‐220 g CO2e/MJ due to the avoided methane. California’s ARB recently published a temporary look‐up table of values for dairy gas to compressed natural gas with a GHG intensity of ‐150 g/MJ, which includes compression to CNG and combustion in a vehicle (ARB 2019). While projects using dairy manure are also limited, such biogas sources could reduce the GHG emissions from the KMMEF. A typical facility may produce 200 to 1000 MMBtu per day of biogas. Aggregating such facilities would take time and require the installation of additional equipment off site. This analysis examines the effect of assuming the contribution of 2,960 MMBtu per day of biogas, or 1 percent of the KMMEF gas supply. The GHG savings from biogas accrue to the upstream emissions.11 The results with 2 percent biogas are also shown in Table 12. Procuring biogas from landfills would not result in the same level of GHG reductions but landfill gas may be more readily available. Landfill gas operations do not result in the same level of emission reductions as dairy biogas because much of the methane is currently controlled through flaring. Most cattle manure is not controlled and diverting it to biogas production avoids the methane production from manure management.

11 For 1 percent biogas with a GHG intensity of – 200 g/MJ, the upstream emissions are reduced in proportion to the GHG intensity of the biogas. 0.99 x 12 g/MJ + 0.01 x ‐200 g/MJ = 9.9 g/MJ or 9.9/12 = 82.5 percent of the baseline value.

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Table 12. Life Cycle GHG Emissions with Anaerobic Digestion (AD) Biogas

Scenario Baseline Baseline in WA

1% AD Biogas

2% AD Biogas

Construction Emissions Direct 0.0004 0.0002 0.0004 0.0004

Upstream 0.0145 0.0008 0.015 0.015

Operational Emissions Upstream Natural Gas 1.04 0.0519 0.82 0.60

Upstream Power 0.19 0.17 0.19 0.19

Direct Emissions 0.73 0.73 0.73 0.73

Downstream Emissions 0.1659 0.0001 0.166 0.166

Petroleum Fuel Production 0.031 0.0048 0.031 0.031

KMMEF Total 2.17 0.96 1.95 1.73

6.3. Biomass Material and Other Technologies

Research on the gasification of biomass for the synthesis gas route to methanol is extensive (Meerman 2011). While these technologies are emerging, they are not options for the KMMEF. Studies estimate an efficiency rate of 54 to 58 percent from wood to methanol or an approximate yield of 180 gallons of methanol per tonne of dry biomass (Hamelinck 2001, ANL 2018). Large quantities of biomass would be required (from 19,000 to 26,000 tonnes per day). Several projects have been proposed at less than 1 percent of the size of the KMMEF but there are no commercially available technologies at the size of the KMMEF (Biofuelsdigest, 2018). Similarly, the synthesis of methanol from waste carbon dioxide or carbon dioxide from air capture is being considered (Mignard, 2003; Schemme, 2017). These technologies could potentially use carbon dioxide from corn ethanol plants or even from the KMMEF as a feedstock source. However, such technologies are not commercially ready. They would also require an on‐site steam reformer to produce hydrogen generating GHG emissions negating any emission benefits or from water hydrolysis, which is not economic unless large quantities of very low‐cost, low carbon power are available.

Other Sources of Olefins12

Issue: Could other methods for the creation of olefins be used. Comments were provided that indicate other methods of creating olefins should be considered with the assertion that they would result in less GHG emissions than the proposed project. The question of petrochemical feedstocks is complex. China has developed a coal to chemicals infrastructure because of the lack of other feedstocks. If a sufficient supply of naphtha were available in China, then the growth in coal‐based methanol and chemicals would have been much slower (China’s reliance on energy imports is illustrated in the MIT analysis of trade flows

12 Note that this section evaluates an alternative olefin feedstock, not a project alternative under SEPA, solely for the purposes of responding to comments raised on this issue.

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(Simoes, 2019b)). The following sections describe the details of crude oil‐to‐naphtha‐to‐olefins, examine the role of naphtha in the life cycle of crude oil production, and compare the emissions from KMMEF MTO with other options for olefin production that may be available.

7.1. Emissions from Crude Oil to Naphtha to Olefins

Various hydrocarbons are a potential feedstock for olefin production. These feedstocks include ethane and propane extracted from natural gas and naphtha from crude oil refinery production. Comments on the DSEIS stated that the use of the crude oil‐derived naphtha route would result in lower GHG emissions per tonne of olefin than the proposed project. Section 5.4 and Appendix E of the LCA report examined the GHG emissions associated with olefin production. As indicated in Figure 5.3 of the LCA report, the GHG emissions for petroleum olefin production were calculated as being higher than those from MTO produced with KMMEF methanol. Crude oil refineries primarily process naphtha into gasoline. West Coast refineries do not produce naphtha as a product (EIA, 2019b). In the Houston area, which is part of PADD 313, naphtha is sold as a chemical feedstock. Figure 8 shows the fraction of product from PADD3 for 2017 where only 1.3 percent of the refinery output is naphtha. This demonstrates that naphtha is not the primary product of oil refineries, and is not readily available in sufficient quantities for methanol production

Figure 8. Petroleum Products Produced in PADD3 Refineries Source: EIA, 2019b

The analysis of crude oil to naphtha‐based olefins is complex due to the need for consistent upstream data for crude oil, process fuel, and power for the steam cracker (the method in

13 Petroleum Administration for Defense Districts (PADDs) are geographic aggregations of the U.S. into five districts intended to help in the assessment of regional petroleum product supplies.

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which olefins are produced from crude oil). The life cycle GHG emissions from MTO production in the LCA report include crude oil production, refining to naphtha, transport to steam cracker, and then olefin production. Each step also includes the production of additional co‐products. Crude oil production results in associated natural gas. Oil refineries produce gasoline, diesel, jet fuel, and petroleum coke as well as naphtha. Steam crackers produce pyrolysis gasoline and heavy fuel oil. Thus, total GHG emissions for these steps must be allocated among these products. The emissions associated with crude oil production and refining are allocated to these different co‐products in the LCA report. The analysis of GHG emissions from olefins in the LCA is consistent with the analysis in the GREET model. A number of publications (see Appendix E of the LCA Report) show the GHG intensity of olefins in the range of 1.5 to 2.3 kg CO2e/kg olefin. These estimates include a range of olefin types. For example, ethylene from ethane cracking will have lower GHG emissions than mixed olefins from naphtha steam cracking. Figure 9 compares estimates of the GHG intensity of crude oil‐to‐naphtha‐to‐olefins from this study to the value cited in the comments to the draft SEIS (SEI, 2018). Based on the results shown below, the full scope of GHG emissions may be missing from many literature values due to the complexity of steam cracking as well as the emissions from crude oil‐ to‐naphtha, which may be the case for the 2008 values in the SEI report14. Another study indicated that the direct emissions from a steam cracker range from 1.8 to 2 kg CO2/kg of olefin (Haribal, 2018). The study shows that 8 to 12 MJ of energy are required as process energy inputs for the steam cracker with a total energy input of 67 to 100 MJ per kg of olefin15. These energy inputs, plus the life upstream emissions from naphtha feed and electric power, are consistent with the results presented here.

14 The olefin studies cited by Ren were completed before a more complete understanding of the life cycle emissions from crude oil were widely published. 15 A rough calculation confirms the 1900 g/kg from Haribal. 10 MJ of process fuel x 75 g CO2 /MJ process fuel = 750 g CO2/kg of olefin. 70 MJ of feed – 43 MJ/kg of olefin results in 27 MJ of material that is converted to coke, fuel gas, or co‐products. The paper refers to upstream and downstream components, which do not include crude oil production but instead are operating units such as demethanizer and compressor.

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Figure 9. Life Cycle GHG Emissions for Crude Oil‐to‐Naphtha‐to‐Olefins As indicated in Figure 9, earlier literature in olefin production either omits portions of the life cycle of olefin production when comparing to olefin production from the KMMEF or uses outdated upstream emission factors. Note that the steam cracker emissions calculated in the LCA report are in close agreement with the emissions from the Xiang study referenced in comments to the DSEIS by the Stockholm Institute. The upstream emissions associated with naphtha production are not analyzed in detail in the Xiang study and refers to older studies (Ren 2009) that were published before a greater understanding of the upstream emissions from crude oil production had been developed (Keesom 2012, Brandt 2014). As illustrated in Figure 9, the upstream emissions from naphtha production include crude oil production, methane leakage from crude oil production, a share of refining emissions based on the allocation system in GREET, and naphtha transport. While some of these emissions are likely in the crude oil step identified in the SEI paper, some appear to have been omitted.

7.2. Upstream Emissions from Crude Oil and Oil Refining

As indicated above, the upstream emissions from crude oil‐to‐naphtha‐to‐olefins include the emissions associated with crude oil production. Many researchers have examined the emissions associated with crude oil production and oil refining (Bergerson 2006, COWI Consortium 2015, Keesom 2012). All of these studies examine the inputs for crude oil production, venting and flaring of methane, and the distribution of emissions within the oil refinery. The GHG analysis results are consistent with the GREET model results used in the LCA report. Note that crude oil production results in fugitive methane emissions that are about the same as those for natural gas production (135 g CH4/mmBtu crude oil in GREET1_2018; ANL, 2018).

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Producing more naphtha would require additional crude oil production since most of the naphtha intermediate product in oil refineries is converted to gasoline. As more and more crude oil is extracted, more energy‐intense production methods are employed and the GHG intensity of crude oils are expected to increase based on the mix of global petroleum production resources and the requirement to use more energy intense production methods to extract the incremental barrel of oil (Gordon, 2015). The details of crude oil production for supply to China were recently analyzed in a paper published in Nature Energy (Masnadi, 2018). The analysis confirms that increasing volumes of crude oil shown on the right‐hand side of the x‐axis in Figure 10 will result in higher GHG emissions.

Figure 10. Carbon Intensity of Crude Oil Resources for China Source: Masnadi, 2018

Lighter crude oils, such as those produced in the Bakken, contain higher fractions of naphtha and light hydrocarbon components (de Place 2014). These sources of crude oil could increase naphtha production but the material is not located close to China and would need to be moved by rail to oil refineries, processed into refined products and naphtha, and shipped to China, with associated GHG emissions for each step. An analysis of GHG emissions of crude oil from the Bakken conducted by Stanford University in collaboration with ANL details the emissions associated with the production of light crude oil from shale (Brandt 2015). The life cycle GHG emissions for the crude oil refining to finished fuel production are examined here. The life cycle GHG emissions for the crude oil portion correspond to 10.3 g CO2/MJ of crude oil, which is consistent with the values used for crude oil to Washington refineries in the LCA report.

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7.3. Total Emissions Associated with Crude to Naphtha to Olefins

Since naphtha is co‐produced with other petroleum productions, its role in the life cycle emissions of crude oil products provides an essential element of the environmental footprint of naphtha to steam cracking for olefin production. The life cycle analysis of naphtha presented in the LCA report as well as the values shown in Figure 9 allocated products in the crude oil‐to‐naphtha‐to‐olefin route to multiple co‐products, including associated gas produced during oil production as well as refinery products. Naphtha is a low value co‐product from oil refining. If more naphtha resources are required for olefin production, either more crude oil would need to be refined or naphtha would be produced instead of other refined products. Shifting oil refinery output from gasoline to naphtha production was presented as an option for olefin production (Stockholm Environment Institute, 2018). While oil refineries are not configured for such a shift, a move to expand naphtha production would require the diversion of naphtha from gasoline production or the use of high‐naphtha crude oil and rail transport from regions like the Bakken. Figure 11 illustrates how the pathway for naphtha production results in many other co‐products. The production of residual oil and petroleum coke would continue with naphtha production. The overall emissions from crude oil production and refining are examined here. Full life cycle emissions include upstream emissions for crude oil and other inputs, emissions from naphtha refining (portion of total); emissions from transporting naphtha, and emissions from steam cracking naphtha to olefins. The extraction of crude oil incudes the emission sources shown in Figures 11 and 12. Crude oil is transported to an oil refinery and is followed by the conversion of naphtha to olefins. The emissions from crude oil production include the operation of drilling equipment, flaring and venting, separation of associated gas, and venting CO2, fugitive methane, and other substances. Upstream GHG emissions in the LCA report (Section 2.4.7) are based on the OPGEE model (Brandt 2014), which examines a mix of crude oil production types and locations. The emissions from OPGEE are aligned with crude oil production in the GREET model. ARB takes the same approach (ARB 2018). Emissions downstream of the oil refinery include transport to a steam cracker and conversion to olefins. As discussed in Appendix E of the LCA report, naphtha steam crackers process feed into olefins. The conversion process involves the combustion of fuel gas and coke as well as the co‐production of heavy hydrocarbons and pyrolysis gasoline. The emissions from the steam cracker are assigned to the products and co‐products. Similarly, emissions from crude oil production and refining to naphtha are also assigned to products and co‐products from the steam cracker, which result in the emissions described in Section 5.4 of the LCA report. The naphtha‐to‐olefin route is currently commercially viable because naphtha is a low value co‐product of oil refining. If the use of naphtha were expanded for more olefin production, then naphtha feed would need to be diverted from gasoline production, or more sources of crude oil high in naphtha would need to be identified and refined. This could change the relative value of naphtha as a feedstock compared to other feedstocks, such as natural gas.

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Figure 11. System Boundary Diagram for Naphtha‐Centric Oil Refining The distribution of upstream emissions from crude oil production to refined products and steam cracking for olefin production are illustrated in

Figure 12Figure 12 for a 250,000 barrels per day oil refinery that diverts 55,000 barrels per day of naphtha to steam cracker feed. The flows represent GHG emissions on a CO2 equivalent basis. Note that the crude oil and natural gas inputs are also shown as CO2 to represent inputs and outputs to the refinery. This quantity of naphtha would be required to produce 1.37 MTPA of olefins. For the analysis presented here, 40 percent of the naphtha feed to gasoline is diverted to steam cracking. Figure 12 shows all of the flows of crude oil and associated gas production and refining to produce the same quantity of olefins as the KMMEF. In the example here, naphtha is diverted from gasoline to olefin production. The olefins route is based on the naphtha stream (Green line). The analysis here allocates the emissions from oil and gas production and refining to naphtha and other products. Several components of the crude oil life cycle will still result in emissions regardless of the mix of products. These include the production, fugitive methane,

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and refining emission as well as the emissions associated with petroleum coke or heavy residual oil production. The distribution of emissions from crude oil production and refining to refined products in the analysis presented here is based on the energy intensity method used in the GREET model. Since gasoline and diesel production are more energy‐intense than naphtha production, a larger share of the crude oil emissions per tonne of product is assigned to these fuels. If more refined product were diverted to naphtha, a larger share of the crude oil production and fugitive CH4 would be assigned to each tonne of naphtha.

Figure 12. Petroleum Products Produced in PADD3 Refineries and Associated GHG Emissions adjusted to produce sufficient Naphtha to produce 1.37 MTPA Olefins. Source: EIA, 2019b, GREET

Naphtha

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Both steam crackers and oil refineries produce fuel products that are subsequently burned. While these emissions are not treated as part of the life cycle of naphtha to olefins, the fact that much higher emissions are associated with the other products in the crude oil pathway is of interest. Note that the emissions from petroleum coke and non‐olefin by ‐ products from the steam cracker are equal to the 3.26 MTPA of GHG emissions for olefin production but are not included in the allocated emissions calculation presented in Section 5.4 and Appendix E of the LCA report. If these emissions from petroleum coke combustion and other parts of the crude oil supply chain were included in the naphtha to olefins analysis, the emissions would be even higher. Therefore, producing 1.37 MTPA of naphtha carries with it the associated co‐production of over 10 times as much petroleum products. These petroleum products result in over 70 MTPA of GHG emissions. While the use of naphtha as chemical feed does not cause these emissions to be produced, the use of naphtha from the petroleum system cannot be viewed in isolation. The naphtha is transported to a steam cracker where it produces olefins, pyrolysis gasoline, and heavy fuel oil. Oil refinery emissions are also allocated to naphtha and other refined products based on the energy intensity of processing the products in the oil refinery. Note that the total emissions associated with the throughput in Figure 12 are over 70 million tonnes of CO2e per year. 1.3 tonnes of CO2e per year are allocated to naphtha feed for steam cracking to olefins, and 1.05 MTPA are allocated to the naphtha steam cracker. A total of 3.26 million tonnes of CO2e per year of life cycle emissions are associated with the production of 1.37 tonnes of CO2e per year of olefins, while the balance of emissions associated with refined products and co‐produced natural gas.

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Figure 13. Total GHG Emissions for Natural Gas and Crude Oil Routes to Olefins before Allocation to Products. Source: EIA, 2019 combined with GREET

7.4. Comparison of KMMEF MTO with Other Olefin Options

The total emissions associated with naphtha‐to‐olefins are compared with the natural gas to MTO route in Figure 13. These emissions include all of the products and co‐products before allocation. The crude oil pathway includes petroleum fuels and coke. Note that these total emissions are allocated to other products in a life cycle analysis which are discussed in the following section. The natural gas route also includes the co‐production of natural gas liquids. Note that the crude oil route involves total emissions that are six times higher than those from the natural gas route, even when an oil refinery is heavily configured for naphtha production. Key factors that affect the life cycle emissions of the crude oil‐to‐naphtha‐to‐olefin route include:

Crude oil production emissions

Methane leaks during crude oil production (about the same as those for natural gas)

Crude oil transport

Crude oil refining to products including naphtha

Naphtha transport

Steam cracking of naphtha to olefins, pyrolysis gasoline, and heavy fuel oil

Table 13 shows the annual GHG emissions for feedstock production plus olefin production for different routes using different feedstocks and the effect of the EDF methane emission rates from Table 7. Note that the emissions for the KMMEF correspond to Table 5.12 in the LCA report. Similarly, the methanol production emissions for the CR technology are shown below from Table 10 combined with the same MTO emissions. Finally, the emissions for crude oil‐to‐ naphtha‐based steam cracking are shown from Table 5.12 in the LCA report. The KMMEF ULE technology results in a net GHG reduction compared with all of these options, and all options result in lower emissions than coal‐based MTO. Table 13. Annual GHG Emissions for Olefin Production

GHG M tonne/year

Olefin Route Feedstock Olefin AR4‐100

KMMEF ULE, MTO 2.17 0.41 2.58 KMMEF ULE, MTO, EDF CH4 2.84 0.41 3.26 KMMEF CR, MTO 2.55 0.41 2.97 Naphtha, Steam Cracking 1.80 1.47 3.26 Naphtha, Steam Cracking EDF CH4

a 1.92 1.47 3.39 Coal to Methanol, MTO 13.69 0.41 14.10

a EDF scenario assumed to add 50 g CH4/mmBtu to crude oil production.

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GWP factors have little effect on the relative comparison of KMMEF to MTO compared with crude oil‐to‐naphtha‐to‐olefins since both pathways include methane leaks. The baseline life cycle GHG emissions in the GREET model are 135 g CH4/mmBtu natural gas and 129 g CH4/mmBtu crude oil.16 These emissions propagate throughout the life cycle. The higher leak rates from the EDF studies also apply to crude oil production (Alvarez, 2018; Schneising, 2014). For the purposes of this analysis, CH4 venting emissions in the EDF scenario for naphtha steam cracking were assumed to result in an additional 50 g CH4/mmBtu based on the EDF study which identified a 60 percent increase in methane emissions above EPA inventory levels. Furthermore, oil fields that are high naphtha producers (e.g., Eagle Ford, Texas) co‐produce natural gas (EIA, 2019). In 2019, this region produced 7,000 million standard cubic foot (scf) of natural gas for every 1450 thousand barrels per day as shown in Figure 144, or about 0.8 Btu of natural gas for every Btu of crude oil produced.

Figure 14. Oil and Co‐Produced Natural Gas in Eagle Ford Region Source: EIA, 2019a

Estimates of higher methane leak rates affect both the natural gas‐to‐methanol and the crude oil‐to‐naphtha pathways for olefin production. This point is especially significant for high naphtha crude oils which are co‐produced with high levels of natural gas. Applying the EDF parameters for the KMMEF to MTO route results in a comparable increase in emissions for the crude oil‐to‐naphtha‐to‐olefin route. As shown in Appendix E of the LCA report, naphtha steam cracking involves many sources of emissions, including fired fuel gas, burned coke, power to operate the process, and the effect of unconverted naphtha. The sensitivity analysis in Section 6 examined the effect of GWP and methane leak rate on KMMEF methanol. These same factors also affect the life cycle emissions of crude oil‐to‐naphtha‐to‐olefins. Figure 15 shows the emission results from Table 11 with a range of GWP factors as well as different assumptions on methane leak rates. The GWP factors and leak rates have a similar effect on all of the routes as methane leaks are part of the feedstock production step for natural gas, crude oil, and coal.

16 Emission rates are on an LHV basis. The emission rate is 60 g/mmBtu for BC gas in the Baseline case based on GHGenius.

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Figure 15. GHG Emissions for Olefin Production for Same Output as KMMEF

Market Displacement Effects of MTO and Naphtha

Issue: Comments questioned the assumptions around displacement including the effects of price of crude oil and whether the project would result in the displacement of other methods of olefin production such as naphtha. Section 4 of the LCA report discussed, in considerable detail, how the worldwide methanol market is structured. It is a complex market, with producers located around the world who manufacture methanol to satisfy demands that range from fuel use to intermediate chemical inputs. Multiple potential feedstocks for methanol further complicate the supply profile. The projections for growth in the methanol market were documented in the LCA report. In particular, studies by AsiaChem, IHS Markit, and DOE (AsiaChem 2018, Alvarado 2016 & 2017, Gross 2017). These projects are consistent with a recently completed study by the International Energy Agency (Fernandez Pales 2018). Add to this the high growth in methanol demand over the past two decades and the expectation of continued high growth in the next decade, and the picture emerges of a complex market in transition The world demand for plastics, highlighted by demand from the Chinese industrial sector, is a key driver of expanding methanol production (Simoes 2019). Couple this with the stated commitment of the Chinese government to reduce coal processing and its GHG emissions, and the high cost, high emissions from coal‐to‐methanol plants are the methanol supply sector most vulnerable to reduced production (AsiaChem 2018). These coal‐based plants already operate at rates of capacity considerably less than modern non‐coal production facilities, and competing with new, cleaner, more efficient non‐coal plants will be difficult (citation). Section 5 above addressed what could occur if additional methanol production is developed and how the supply curve for methanol changes when new, low cost plants offering substantial

AR5 results with EDF CH4 leak rate are cross hatched for to illustrate comparison

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capacity to the market become available. Marginal production from high cost inefficient plants is displaced. This is how markets function. Indeed, the initial market adjustments are expected to be reductions in production at the marginal facilities. However, since these marginal facilities are smaller, higher cost coal‐to‐methanol and coal‐to‐olefin facilities, it is likely that market prices that fall below their marginal cost will lead to their eventual closure as new, lower cost capacity meets growing demand (Mas‐Colell 1995).

8.1. Effect of Oil Prices

At high oil prices, the long‐run economics of MTO would likely result in the reduction of coal‐based methanol production. Even if other new methanol capacity goes to MTO, the cost competitiveness of KMMEF methanol would likely result in displacement effects of coal‐based methanol. As discussed in the LCA Report, coal‐to‐methanol is the marginal method of producing methanol that would be replaced over time by KMMEF and other non‐coal based methanol production. The economics of the more recent methanol and olefin production technologies will reduce reliance on coal‐based production. However, when oil prices are low, MTO and all other uses of methanol are less economical. At low oil prices, the use of methanol for MTO has a higher value than its use as fuel. Thus, even in a low oil price period, MTO will not be impacted substantially. Because methanol in China is a fungible commodity and MTO facilities face paying the market price for methanol, imported methanol will still continue to displace domestic methanol as long as MTO facilities continue to operate, given the comparative price of domestic methanol production compared to imported methanol production. Figure 16 and Figure 17 show the relative ranking of MTO on a supply curve of ethylene production. Ethylene prices track olefin prices with the price of ethylene about 80 percent of other olefins (ICIS, 2018, Lippe, 2017). Olefin production from the KMMEF will cost less than $500 to $600/tonne (feedstock methanol is less than $150/tonne of methane × 2.6 tonne methanol/tonne olefin). With 2016 energy prices, MTO from coal was less competitive than at higher oil prices today and in 2014 but KMMEF MTO would remain economical. The conclusion is that MTO remains cost competitive at moderate to high oil prices, which is the outlook for the future. As shown in Figure 18 crude oil prices have remained above $40 per barrel in recent history except for a reaction to price collapses. With prevailing crude oil prices, MTO will remain competitive to naphtha.

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Figure 16. 2014 Global Ethylene Supply Curve Source: Zinger, 2016. Note values are in short tons.

Figure 17. 2016 Global Ethylene Supply Curve Source: Zinger, 2016. Note costs are in short tons.

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Figure 18. Crude Oil Price History Source: EIA, 2019a

The fact that China remains a leader in manufacturing indicates that demand for olefins will continue to grow. Based on historical trends and existing capacity, MTO will provide about 10 percent of China’s olefin market. At higher oil prices, MTO will become more economically

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attractive (as compared to naphtha to olefins) and facilities should operate at greater capacity. The capacity of the KMMEF is about 18 percent of the MTO market and about 2 percent of the total China olefins demand. Any displacement effects will likely be driven by energy prices rather than by the new volume of available methanol. Absent the capacity from KMMEF, other sources of methanol would be needed. The competition between sources of olefins will depend more on energy prices than on the availability of methanol from KMMEF because the methanol volume represents a relatively small fraction of the methanol used in China MTO.

Methanol as Fuel

Issue: Comments were submitted that suggested that the methanol from the KMMEF would be used as fuel and GHG emissions needed to be considered for this use. The LCA report examined the potential use of methanol as a fuel blending component in Section 5.5 and in Appendix D. Table D.4 calculated the emissions resulting from the use of 100 million gallons of methanol in an M15 blend. The emissions attributable to combustion of methanol as a fuel are approximately 0.41 million tonnes CO2e. Table 14 shows the results of using the entire annual production in the same manner. Emissions attributable to methanol combustion would be approximately 4.94 million tonnes CO2e. Table 14: Comparison of Methanol as Splash Blend and Octane Enhancer

M15 Splash Blending M15 Octane Blending

Passenger Car Fuel Baseline Gasoline

KMMEF M15

China Coal M15

Baseline Gasoline

KMMEF M15

China Coal M15

Fuel Economy (mi/gal) 33.9 31.6 31.6 33.9 31.3 31.3

(Btu/mi), LHV 3,429 3,395 3,395 3,429 3,429 3,429

Methanol (M gal) 0 1,198 1,198 0 1,198 1,198

(tonne) 0 3,600,000 3,600,000 0 3,600,000 3,600,000

Fuel (M gal) 7,450.8 7,984.0 7,984.0 7,377.0 7,984.0 7,984.0

(GBtu) 864,963 856,399 856,399 856,399 856,399 856,399

Emissions (g CO2e/mmBtu), LHV Vehicle 76,768 76,397 76,397 76,768 76,397 76,397

Upstream M100 Component 31,594 199,713 31,594 199,713

Reduction for Octane Contribution ‐595 Upstream Finished Fuel 19,833 20,775 34,234 19,833 20,228 33,687

Annual Emissions (M tonne CO2e/y) Vehicle 66.40 65.43 65.43 65.74 65.43 65.43

Methanol Component 0 4.94 4.94 0 4.94 4.94

Gasoline Component 66.40 60.48 60.48 65.74 60.48 60.48

Upstream 17.16 17.792 29.318 16.985 17.323 28.850

Total 83.56 83.22 94.74 82.73 82.75 94.28

Difference from Baseline 0 ‐0.339 11.19 0 0.020 11.55

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