Final Database 2023-06 (1).xlsx

	B	C	D	E	F	G
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2	Database Methodology and Detailed Sources
3	This sheet contains detailed descriptions of the methodology used to populate datasets for the iron and steel, cement, metallurgical coke, and aluminum industries.
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5	Acronyms
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7	Acronym	Meaning		Link
8	EPA	Environmental Protection Agency		https://www.epa.gov/
9	USGS	United States Geological Survey		https://www.usgs.gov/
10	EIA	United States Energy Information Agency		https://www.eia.gov/
11	MECS	Manufacturing Energy Consumption Survey		https://www.eia.gov/consumption/manufacturing/
12	NAICS	North American Industry Code System		https://www.naics.com/search/
13	BGA	BlueGreen Alliance		https://www.bluegreenalliance.org/
14	FLIGHT	EPA's Facility Level Greenhouse Gas Tool		https://ghgdata.epa.gov/ghgp/main.do?site_preference=normal
15	GHGRP	EPA's Greenhouse Gas Reporting Program		https://www.epa.gov/ghgreporting
16	GSPT	Global Steel Plant Tracker		https://globalenergymonitor.org/projects/global-steel-plant-tracker/
17	BLS	Bureau of Labor Statistics		https://www.bls.gov/
18	IMPLAN	Impact Analysis for Planning		https://implan.com/
19	NEI	National Emissions Inventory		https://www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei
20	ECHO	EPA Enforcement and Compliance History Online		https://echo.epa.gov/
21	BOF	Basic oxygen furnace		https://www.britannica.com/technology/steel/Basic-oxygen-steelmaking
22	EAF	Electric arc furnace		https://www.britannica.com/technology/steel/Electric-arc-steelmaking
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24
25	Total Facilities in the United States, 2020
26	Sources	Links
27	EPA Envirofacts Search	https://enviro.epa.gov
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29	Description
30	Iron and steel	Synapse queried EPA's Envirofacts for all iron and steel facilities, yielding 122 unique GHGRP IDs. Of these, Synapse identified and removed 22 ore pellet, metallurgical coke, or mining facilities, leaving 100 iron and steel production facilities.
31	Metallurgical coke	Synapse queried EPA's Envirofacts database for NAICS code 324199, "All Other Petroleum and Coal Products Manufacturing," yielding 12 merchant metallurgical coke facilities.
32	Cement	Synapse queried EPA's Envirofacts database for all cement facilities, yielding 92 unique GHGRP IDs.
33	Aluminum	Synapse queried EPA's Envirofacts database for all primary aluminum facilities, yielding 7 unique GHGRP IDs.
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35	Industrial Process
36	Sources	Links
37	Global Steel Plant Tracker	https://globalenergymonitor.org/projects/global-steel-plant-tracker/
38	EPA FLIGHT	https://ghgdata.epa.gov/ghgp/main.do
39	BlueGreen Alliance industrial databases	https://www.bluegreenalliance.org/
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41	Description
42	Synapse utilized data from BGA describing facility-level iron and steel production technologies (e.g., basic oxygen furnace, electric arc furncace, direct reduced iron). Synapse combined this data with data provided by the Global Steel Plant Tracker database, giving the BGA data precedence where the two overlapped. For aluminum, Synapse used EPA's FLIGHT to determine which industrial process aluminum facilities use. Synapse researched metallurgical coke facilities individually to determine if they were recovering byproducts. Synpase did not identify facility-specific process information for cement production.
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44	Estimated Production, 2020
45	Sources	Links
46	USGS Mineral Commodity Survey, 2021	https://pubs.usgs.gov/periodicals/mcs2021/mcs2021.pdf
47	Global Steel Plant Tracker	https://globalenergymonitor.org/projects/global-steel-plant-tracker/
48	BlueGreen Alliance industrial databases	https://www.bluegreenalliance.org/
49
50	Summary
51	This table summarizes a comparison of our calculated production estimates versus the known production value according to USGS annual mineral commodity summaries. Note that because our methodology for metcoke and aluminum is designed to allocate the known production, the values are the same, whereas the methodologies for iron and steel and cement determine facility-level production based on an emissions factor. These methodologies yield an estimate that is close to actual production in 2020.
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55			Iron and steel	Metcoke	Aluminum	Cement
56		Total known production (metric tons)	72,700,000	11,412,215	1,012,000	89,000,000
57		Total calculated production (metic tons)	76,745,894	11,412,215	1,012,000	85,540,748
58		% difference	5.3%	0.0%	0.0%	-4.0%
59
60	Description
61	Iron and Steel	Synapse estimated production data using historical data from BGA and GSPT then adjusted to 2020 based on industry-wide data from USGS. BGA developed production estimates for each facility based on facility-specific research. The BGA data included a raw production value for each facility that was either reported production in a specific historical year or the estimated production capacity of the facility. Global Steel Plant Tracker, an initiative of Global Energy Monitor, also publishes a dataset that includes estimated production capacity per facility. Synapse used these two sources to establish a raw value for every facility. Where the two sources overlapped, Synapse used BGA's number. Synapse then adjusted historical production values to 2020 estimates, where applicable, and adjusted capacity values to 2020 production. The former step was accomplished by adjusting historical production according to the comparative difference between industry-wide production in 2020 and the historical year. Synapse adjsuted capacity values by multiplying the industry-wide average capacity factor published by USGS in its mineral commodity summary. Synapse totaled final values and compared to industry-wide production data for 2020 available from the USGS's annual mineral commodity summaries.
62	Metallurgical Coke	Synapse obtained total metallurgical coke production from USGS's annual mineral commodity summaries and developed a methodology to allocate the total to individual facilities. Synapse optained all capacity and production data for facilities owned by Suncoke from Suncoke's SEC Form 10-k filing for 2020. For the remaining facilities, Synapse researched individual capacities online. Synapse totaled all facility capacities and compared that value to the total industry production in 2020 to develop an industry-wide capacity factor, which was then applied to each non-Suncoke facility to estimate those facilities' production in 2020.
63	Cement	Synapse estimated production data using historical data compiled by BGA and a capacity factor adjustment from USGS's annual mineral commodity summaries. BGA used three types of sources to develop initial production estimates: data directly from each company, data from the media or other third parties, and data from the Industry About database. Most plants started with two values (one from Indsutry About and one from either the company or media). For each production value, Synapse performed a series of adjustments. When a source provided production capacity rather than actual production, Synapse adjusted downward based on the average 2019 capacity utilization (the most recent year available), given by the 2021 USGS Mineral Commodity Survey, to estimate actual production. For plants where a source gave a value in short tons, Synapse converted the value to metric tons. For plants where a source gave a production value for clinker rather than cement, BGA adjusted upwards using an adjustment factor based on the annual production of clinker versus cement in the United States as found in the USGS commodity summaries. Synapse preserved this calculation. In many cases sources were ambiguous about units, capacity vs. actual production, and clinker vs. cement, so these adjustments may have been misapplied to some facilities and should be seen as potentially increasing uncertainty at the facility level. For each facility, BGA chose what staff believed to be the best production value. BGA generally preferred values from the company over its internal database and the media. When no company value was available, BGA generally averaged IA and the media where possible. However, there were several exceptions to these rules based on staff assessment of source quality. Synapse reviewed BGA's judgements and preserved them. Final estimates for facility-level production were totaled and compared to industry-wide production data for 2020 available from the USGS's annual mineral commodity summaries.
64	Aluminum	Synapse researched production capacity for each individual facility. Total primary aluminum production in 2020, available via USGS's 2021 Mineral Commodity Summary, was allocated to each facility according to the facility's share of total capacity.
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66	Estimated Electricity Usage and Emissions, 2020
67	Sources	Links
68	EIA manufacturing Energy (MECS) survey	https://www.eia.gov/consumption/manufacturing/data/2018/
69	USGS Mineral Commodity Summary	https://www.usgs.gov/centers/national-minerals-information-center/mineral-commodity-summaries
70	eGrid Power Profiler by Zip Code, Version 11.1	https://www.epa.gov/egrid/power-profiler#/
71	Comparative Carbon Footprints of Metallurgical Coke and Anthracite for Blast Furnace and Electric Arc Furnace Use (2015), pg. 70	https://www.blaschakanthracite.com/wp-content/uploads/Carbon-Footprint-Archival-Report-v-4-September-20151.pdf
72	Hasanbeigi and Springer (2019), "How clean is the U.S. steel industry?"	https://www.belfercenter.org/sites/default/files/files/publication/how-clean-is-the-us-steel-industry-nv.pdf
73	Stubbles (2000), "Energy use in the U.S. steel industry: an historical pers[ective and future opportunities	https://www.energy.gov/sites/prod/files/2013/11/f4/steel_energy_use.pdf
74	Schobert and Schobert (2015), "Comparative carbon footprints of metallurgical coke and anthracite for blast furnace and electric arc furncae use."	https://www.blaschakanthracite.com/wp-content/uploads/Carbon-Footprint-Archival-Report-v-4-September-20151.pdf
75	International Aluminum (2017), "Life cycle inventory data and environmental metrics."	https://international-aluminium.org/resource/life-cycle-inventory-data-and-environmental-metrics/
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77	Description
78	EIA collects manufacturing end-use energy data through the MECS survey, which provides total energy use by industry NAICS code. The MECS data breaks out electricity usage and the most recent data year is 2018. USGS meanwhile gives us total annual production of iron and steel, cement, and aluminum via its annual mineral commodity surveys. This data, plus other industry-specific data, was used to develop an industry-specific electricity usage factor per ton of production. In all three industries, the zip codes of each facility was then used to identify the grid transmission zone with an associated generation resource mix and an electric grid emissions factor on a lbs CO₂ equivalent per MWh basis. This factor was used to estimate total electricity-related emissions for the iron and steel and cement industries. For aluminum, each of the seven facilities was researched individually to find facility-specific electricity consumption data. In many cases, aluminum facilities contracted for renewable electricity supply in sufficient quantity to meet all or a large portion of the facility's electricity demand. The remaining energy consumption was assumed to be generated by fossil energy. To determine the amount of emissions attributable to that fossil energy, split between coal generation and natural gas generation according to the proportion described in eGRID 2020 for the facility's state. Each megawatt-hour (MWh) of electricity from coal was assumed to emit 1.0 ton CO₂e, and each MWh of electricity from natural gas was assumed to emit 0.5 tons CO₂e.
79	Industry	Methodology
80	Iron and Steel	Synapse retrieved data on ferroalloy and iron and steel energy consumption from EIA MECS, which are bundled into one category. From Hasanbeigi and Springer (2019) Synapse retrieved the actual energy intensity per ton of steel for BOFs and EAFs in 2018. Synpase retrieved production in tons from BOFs and EAFs in 2018 from USGS. Synapse used an iterative process to figure out a reasonable energy intensity for ferroalloys, subtract that out from the MECS industry total, then get an estimate of total energy in gigajoules (GJ) for iron and steel. Synapse then allocated that to BOFs and EAFs using their respective tonnages of production from USGS and their respective energy intensities. Synapse then determined the proportion of the energy at each type of furnace that is provided by electricity using Stubbles (2000).
81	Metallurgical Coke	Synapse used the electrical intensity per ton of metallurgical coal found in Schobert and Schobert (2015).
82	Aluminum	First, Synapse subtracted the electricity usage used to produce alumina, given by Aluminum international (2017), from the NAICS code total given by MECS, then Synapse divided total remaining industry electricity usage by tonnage of aluminum produced.
83	Cement	Synapse divided the total electricity usage of cement facilities as given in EIA MECS 2018 divided by the total tonnage cement given in USGS's mineral commodity summary for 2018.
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85	Greenhouse Gas Emissions Data, 2020
86	Sources	Links
87	EPA Envirofacts, System Data Search	https://enviro.epa.gov
88	2020 Summary Data collected by EPA GHG Reporting Program	https://www.epa.gov/system/files/other-files/2021-10/2020_data_summary_spreadsheets.zip
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90	Description
91	GHG emissions by gas (CO₂, N₂O, CH₄, or BioCO₂ if applicable) and by process (stationary production, material production, or other) were downloaded in units of CO₂ equivalent and matched to each facility according to GHGRP ID.
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93	Risk-Screening Environmental Indicators (RSEI) Scores, 2020
94	Sources	Links
95	EPA EasyRSEI Dashboard Version 2.3.10	https://edap.epa.gov/public/extensions/EasyRSEI/EasyRSEI.html
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97	Description
98	Synapse exported facility-level RSEI score results from EasyRSEI using unique facility identifiers for each facility. RSEI scores are unitless values that account for the size of the chemical release, the fate and transport of the chemical through the environment, the size and location of the exposed population, and the chemical's toxicity. A RSEI Score is calculated as toxicity weight multiplied by the exposed population multiplied by the estimated dose. Higher RSEI scores indicate higher impact and have lower ranks, signaling their place in the order of impact (i.e., the first place facility has the greatest impact)
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100	Non-GHG Pollutant Data