1 Stationary Energy
1.1 Introduction
1.2 Electricity
1.2.1 Introduction
Emissions from the electricity generation sector have declined by 54% in Minnesota since 2005, largely as a result of transitions in the grid towards energy sources such as wind and solar (MPCA 2023). In 2023, Minnesota Governor Walz signed a bill mandating a statewide carbon-free electricity standard by 2040. The law “establishes a standard for utilities to supply Minnesota customers with electricity generated or procured from carbon-free resources, beginning at an amount equal to 80% of retail sales for public utility customers in Minnesota in 2030 and increasing every 5 years to reach 100% for all electric utilities by 2040. The bill also requires that, by 2035, an amount equal to at least 55% of an electric utility’s total retail electric sales to customers in Minnesota must be generated or procured from eligible energy technologies.” Wisconsin has not adopted a similar carbon-free electricity standard, but a Wisconsin DNR report noted both the economic gains from such to the renewable energy economy in the state, as well as the opportunities for decarbonization (Holt 2019).
1.2.2 Methods
The general workflow for quantifying electricity emissions is to identify all of the electric utilities that operate within our study area, collect any reporting they provide to the states of Minnesota and Wisconsin about the amount of energy delivered to all their customers (with reference to federal reporting sources where state-level reporting gaps exist), and apply EPA-provided emissions factors to the reported activity/energy deliveries to calculate estimated emissions. Methodologies for allocating utility activity reports to counties varies across MN and WI and are further described in the following section. Most inputs we use in the construction of our electricity emissions data set are of the highest quality rank (Table B.2), as they are either direct government-created data (e.g., emissions factors) or data reported to state/federal authorities (e.g., regulatory filings). However, for two Minnesota electric utilities – Elk River Municipal Utilities (Elk River Municipal Utilities 2022) and New Prague Utilities Commission (New Prague Utilities Commission 2022) – where regulatory filing data could not be sourced to quantify electricity deliveries, we referred to financial reporting documents published by the utilities.
Total regional emissions (Emissionsr) represents the sum of all recorded energy deliveries by utility i within county j, where i refers to each of the electric utilities operating across our region, and j refers to the eleven counties included in this inventory. Our regional total therefore represents an aggregation of electricity deliveries for all distinct utility-county records.
\[Emissions_r = \Sigma (mWhDelivered_iCounty_j \times {Emissions Factor}) \]
Our inventory takes a “demand-side” approach to emissions quantification and seeks to aggregate all reported delivery of energy to ALL customers served by utilities (meaning all customer types, inclusive of residential, commercial, industrial, and government accounts). This means that energy loss and use experienced by utilities in the process of energy generation and transmission, and delivery and resale to utilities operating outside of our study area, are not directly reflected in the numbers attributed to counties. The U.S. Energy Information Administration (EIA) estimates that annual electricity transmission and distribution (T&D) losses averaged about 5% of the electricity transmitted and distributed in the United States in 2018 through 2022. (Administration 2023)
While our primary data collection does not include a breakout of electricity deliveries by sector, we do leverage year 2021 NREL SLOPE forecasts of electricity consumption (built from a base year of 2016 observed data) by sector (residential, commercial, industrial) at the county level to calculate modeled proportions of consumption by sector, which we then apply to our aggregate numbers to calculate estimated emissions by sector NREL (2017).
1.2.2.1 Identifying utilities in scope
To identify the electric utilities that operate within our 11-county study area, we referred to maps and geospatial datasets capturing utility service areas in Minnesota and Wisconsin. To identify Wisconsin electric utilities, we downloaded the Electric Service Territory map maintained by the Wisconsin Public Service Commission (Wisconsin Public Service Commission and Tomaszewski 2024). To identify Minnesota electric utilities, we downloaded the Electric Service Territory map maintained by the Minnesota Public Utilities Commission and the Minnesota IT Geospatial Information Office(Office 2023).
1.2.2.2 Collecting and aggregating activity data from utilities
After identifying which utilities operate within our study area within each state, we collect reporting submitted by these utilities to the relevant state and federal authorities and use a variety of approaches, depending on data availability, to allocate utility activity/energy deliveries to specific counties.
1.2.2.2.1 Minnesota
All electric utilities authorized to do business in Minnesota are required to file an annual data report pursuant to MN Rules Chapter 7610. The Minnesota Public Utilities Commission makes these reports searchable through an eFiling Site, and downloadable as Excel workbooks (Commerce 2005). For each utility identified in distinct_electricity_util_type_MN.RDS (a data product of minnesota_electricUtilities.R, a script that looks for intersections between electric utility service areas and our Minnesota counties), we downloaded the relevant 2021 annual reports from this site (see note about Great River Energy in the previous section for caveats), except for North Branch Municipal Water and Light, which did not submit a 2021 report (we used their 2022 report as a substitution). Elk River Municipal Utilities and New Prague Utilities Commission did not file reports for 2021 or 2022, and so we used financial reports to identify their total electricity delivered; both utilities operated within only one county in our study area, which meant no estimation/allocation was necessary.
We wrote code to extract the county-level data reported in the report section titled “ITS DELIVERIES TO ULTIMATE CONSUMERS BY COUNTY FOR THE LAST CALENDAR YEAR” on the relevant annual data report Excel workbooks compiled into a folder directory, and created a table with three columns: county, utility, and mWh_delivered (megawatt-hours). By compiling this data for all utilities found to operate within our study area, aggregating all electricity deliveries at the county level becomes possible.
1.2.2.2.2 Wisconsin
All municipal and investor-owned utilities authorized to do business in Wisconsin are required to file an annual report with financial and operational information pursuant to Wis. Stat. § 196.07. The Public Services Commission of Wisconsin makes these reports searchable through an E-Services Portal, and downloadable as either PDFs or Excel workbooks, with options to export only specific portions of the reports as spreadsheets (Public Service Commission of Wisconsin 2022). For each utility identified in distinct_electricity_util_type_WI.RDS (a data product of wisconsin_electricUtilities.R, a script that looks for intersections between electric utility service areas and our Wisconsin counties), we downloaded the relevant 2021 annual reports from this site.
A similar process was followed for the four Wisconsin cooperative utilities for which we referenced federal regulatory filings data to populate our dataset of electricity deliveries.
Because of the small amount of data, and the different data structures of the reports for municipally-, cooperatively-, and investor-owned utilities in Wisconsin, we hard-coded observed information into data frames rather than extracting data through a web scraper or document analyzer (see processed_wi_electricUtil_activityData.R).
1.2.2.3 Emissions factors
To transform electricity deliveries (recorded in mWh) into emissions in metric tons CO2e, we referenced 2021 Emissions & Generation Resource Integrated Database (eGRID) summary data for the MROW subregion (Midwest Reliability Organization - West) (USEPA 2021a).
This dataset provides estimates in lbs/mWh for CO2, CH4, N2O, and CO2e emissions based on MROW’s sub-regional electricity generation grid mix; converting this factor to metric tons per mWh and multiplying the county-level mWh estimates yields an estimate for CO2e. To generate this sub-regional estimate, eGRID first calculates estimated emissions at the plant level, and assigns plants to regions. By using an emissions factor that is localized, our inventory accounts for the specific grid mix in our study area (see the grid mix linked to the eGRID MROW emissions factor used in this inventory below). Per the eGRID technical guide, “the subregions were defined to limit the import and export of electricity in order to establish an aggregated area where the determined emission rates most accurately matched the generation and emissions from the plants within that subregion.”
| Energy.Source | Percentage |
|---|---|
1.2.3 Results
1.2.3.2 Comparison with federal inventories
1.2.3.2.1 Energy Information Administration (EIA)
We compared our county-level emissions figures to emissions estimates derived from the EIA’s State Electricity Profiles, which were generated by down-scaling EIA’s Minnesota and Wisconsin state-level numbers for total electricity retail sales. We achieved this by applying the proportions of each state’s population residing in each of our study area counties to generate county-level emissions estimates. Our inventory quantified 15,937,600 metric tons of electricity in our study area relative to 20,214,537 metric tons based on the aforementioned downscaled statewide retail numbers.
1.2.3.2.2 NREL SLOPE
The NREL SLOPE (State and Local Planning for Energy) Platform provides yearly forecasted emissions tied to the user of electricity up to 2050 based on 2016 reported data at the county level. In comparing these figures to our own inventory, we observed that, where we estimated 15,937,600 metric tons of emissions linked to electricity deliveries in our study area in the year 2021, NREL SLOPE forecasted 19,284,150metrics tons in our study area.
1.3 Natural Gas
1.3.1 Introduction
Greenhouse gas emissions from Minnesota homes and apartment buildings have increased 14% over the past 15 years, and natural gas use is the largest source of these emissions (MPCA 2023). Many local and state governments are evaluating policies to reduce natural gas usage, such as building electrification (when paired with decarbonization of the electric grid) and banning natural gas hookups in new construction.
1.3.2 Methods
The general workflow for quantifying natural gas emissions is to identify all of the natural gas utilities that operate within our study area, collect any reporting they provide to the states of Minnesota and Wisconsin about the amount of energy delivered to all their customers, reference federal reporting sources where state-level reporting gaps exist, and apply EPA-provided emissions factors to the reported energy deliveries to calculate emissions. Methodologies for allocating utility activity reports to counties varies across MN and WI and are further described in the following section. All inputs we use in the construction of our natural gas emissions data set are of the highest quality rank (Table B.2), as they are either direct government-created data (e.g., emissions factors) or data reported to state or federal authorities (e.g., regulatory filings).
Total regional emissions (Emissionsr) represents the sum of all recorded energy deliveries by utility i within county j, where i refers to each of the electric utilities operating across our region, and j refers to the eleven counties included in this inventory. Our regional total therefore represents an aggregation of electricity deliveries for all distinct utility-county records within our 11 counties. Our inventory takes a “demand-side” approach to emissions quantification and seeks to aggregate all reported delivery of energy to all customers served by utilities (meaning residential, commercial, industrial, and government accounts).
\[Emissions_r = \Sigma (mcfDelivered_iCounty_j \times {Emissions Factor}) \]
While our primary data collection does not include a breakout of natural gas deliveries by sector, and represents only total natural gas deliveries, we do leverage year 2021 NREL SLOPE forecasts of natural gas consumption (built from a base year of 2016 observed data) by sector (residential, commercial, industrial) at the county level to calculate modeled proportions of consumption by sector, which we then apply to our aggregate numbers to calculate estimated emissions by sector. (Ma et al. 2019) (NREL 2017)
1.3.2.1 Identifying utilities in scope
To identify the natural gas utilities that operate within our 11-county study area, we first referred to maps and geospatial datasets capturing utility service areas in Minnesota and Wisconsin. Where possible, state-maintained data sources were used, with federal sources referenced where state sources could not be accessed. To identify Wisconsin gas utilities, we downloaded the Natural Gas Service Territory map maintained by the Wisconsin Public Utilities Commission (Public Service Commission of Wisconsin 2021). Since Minnesota does not publish a state-maintained data set of natural gas service areas (Minnesota IT Services 2021), we used the Department of Homeland Security’s Natural Gas Service Territories map from its Homeland Infrastructure Foundation-Level Data (HIFLD) portal to identify in-scope Minnesota gas utilities (Homeland Security 2017).
1.3.2.2 Collecting and aggregating activity data from utilities
After identifying which utilities operate within our study area within each state, we collected the reporting submitted by these utilities to the relevant state and federal authorities, and followed a distinct process for each state to accumulate data and then allocate energy deliveries to specific counties therein.
1.3.2.2.1 Minnesota
All natural gas utilities authorized to do business in Minnesota are required to file an annual data report pursuant to MN Rules Chapter 7610 (Commerce 2005). The Minnesota Public Utilities Commission makes these reports searchable through an eFiling Site (Minnesota Department of Commerce 2022). For each utility identified in distinct_natGas_util_MN.RDS (a data product of minnesota_natGasUtilities.R, a script that looks for intersections between electric utility service areas and our Minnesota counties), we downloaded the relevant annual reports from this site in their Excel workbook form.
We wrote code to extract the county-level data reported in report section “ANNUAL GAS DELIVERED TO ULTIMATE CONSUMERS BY COUNTY IN 2021” from these reports (which were compiled into a distinct folder directory for file processing), and created a table with three columns county, utility, and mcf_delivered (thousand cubic feet of natural gas delivered). By compiling this data for all utilities found to operate within our study area, aggregating all natural gas deliveries at the county level becomes possible.
1.3.2.2.2 Wisconsin
All municipal and investor-owned natural gas utilities authorized to do business in Wisconsin are required to file an annual report with financial and operational information pursuant to Wis. Stat. § 196.07. The Public Services Commission of Wisconsin makes these reports searchable through an E-Services Portal, and downloadable as either PDFs or Excel workbooks, with options to export only specific portions of the reports as spreadsheets (Wisconsin State Legislature 2024). For each utility identified in distinct_natGas_util_WI.RDS (a data product of wisconsin_natGasUtilities.R, a script that looks for intersections between electric utility service areas and our Wisconsin counties), we downloaded the relevant 2021 annual reports from this site.
Because of the small amount of data, we hard-coded observed information into data frames rather than extracting data through a web scraper or document analyzer as we did in Minnesota (see processed_wi_electricUtil_activityData.R.
1.3.2.3 Emissions factors
Natural gas energy deliveries were reported in standard cubic feet and converted into emissions in metric tons CO2e, referencing the 2021 EPA GHG Emissions Factor Hub (USEPA 2021b).
1.3.3 Results
1.3.3.2 Comparison with other inventories
1.3.3.2.1 NREL SLOPE
The NREL SLOPE (State and Local Planning for Energy) Platform provides yearly forecasted emissions from natural gas through 2050 based on 2016 observed/reported data at the county level. In comparing these figures to our own inventory, we observed that, where we estimated 12,349,748 metric tons of emissions linked to natural gas use in our study area in the year 2021, NREL SLOPE forecasted 13,910,111 metric tons in our study area.