About the Explorer

The Clean Energy Futures Data Explorer provides interactive access to data from the Clean Energy Futures (CEF) project, an ongoing multi-institutional research initiative that quantifes the carbon emissions, costs, and air quality outcomes of contrasting electricity sector policies to address climate change. The project is a collaboration among researchers at Syracuse University; the Center for Climate, Health and the Global Environment at the Harvard T.H. Chan School of Public Health; Resources for the Futures; and the Georgia Institute of Technology. For more information about the CEF project please see the main project web site and the policy brief from July 2021.

The Explorer provides access to results for thirteen scenarios: a baseline and twelve policy cases. Please see the July 2021 policy brief for a detailed description of the scenarios. The table below provides a quick reference showing a few key details. The "code" column shows a short code used to refer to the scenario in the Explorer; the "crediting" column refers to partial crediting for natural gas; the "banking" column indicates whether credits or allowances can be banked in early years for use later; and the "notes" column indicates any limitations on the data available in the Explorer. Finally, ACP is an abbreviation for "alternative compliance payment," a fee that a utility can pay in lieu of fully complying with a policy.

The Explorer provides national and state-level results for the variables discussed below. Results for some variables are available at the county level, as noted.

Electricity Generation:

Shown as annual terawatt hours (TWh). Some visualizations break generation sources down into four broad categories: fossil, renewable, nuclear, and other. Other visualizations provide more detail and break generation down into more than a dozen categories.

Emissions:

Annual electricity-sector emissions are provided for all scenarios for carbon dioxide (CO₂), nitrogen oxides (NO_x), and sulfur dioxide (SO₂). Most scenarios also provide results for mercury (Hg) emissions. CO₂, NO_x and SO₂ are shown in thousands of short tons, and mercury is shown in pounds.

Air Quality:

Changes in ambient air quality from baseline are provided for two pollutants, fine particulate matter (PM2.5) and ozone (O₃), The estimates are provided at the county level. Changes in PM2.5 are shown in micrograms per cubic meter and changes in ozone are shown as parts per billion.

Premature Deaths Averted:

The impact of changes in PM2.5 and ozone on annual premature mortality is provided at the national, state, and county level. At the national and state level it is shown as premature deaths averted, both in total and by pollutant. At the county level it is shown as the number of premature deaths averted per 100,000 people (the change in the risk of death) associated with each pollutant.

Generating Capacity:

Shown as gigawatts (GW). As with generation, some visualizations break generation sources down into four broad categories: fossil, renewable, nuclear, and other. Other visualizations provide more detail and break generation down into more than a dozen categories.

System Costs:

Shown in billions of 2019 dollars. Total annual costs are provided, as well as the following components: levelized capital costs, fixed operating and maintenance costs, variable operating and maintenance costs, fuel costs, and costs associated with carbon capture and sequestration (CCS).

The Explorer is fairly straightforward to use but here are a few notes that may be useful.

Years available:

Most of the visualizations provide results for six years: 2020, 2025, 2030, 2035, 2040, and 2050. However, those providing ambient air quality or human health impacts only have data for three years: 2030, 2040, and 2050. Those are the years for which the project has carried out air quality modeling using the CMAQ model.

Tooltips:

Each visualization has a small message, or tooltip, that appears when the cursor hovers over a map or graph element. The tooltip provides the numeric value, and the corresponding unit, of the variable being visualized for the state or graph element under the cursor.

Changes vs. levels:

All of the visualizations provide data on changes from the baseline, and therefore exclude the baseline itself from the list of available scenarios. However, three of the visualizations also provide the levels (actual values, rather than changes from baseline) of the corresponding variable via a "show as level" button.

Selecting states or counties:

It is possible to select states or counties by choosing them via the drop-down selectors in the center of each visualization, or by clicking on them in the corresponding map. However, the two methods differ in how one returns to the larger map: if the drop-down selector was used, use it again and select "All"; if the state or county was clicked on, click on the state or county again.

Map tools:

A small menu of tools will appear when hovering over a map. The plus and minus icons change the map's zoom level; the home button returns the map to its original zoom level; and the arrow submenu provides some advanced tools for panning and selecting.

This interactive visualization tool was constructed by Jonnel Acoba, Kyle Downey, Andrew Etheridge, Austin Scheibmeir, and Katie Smith, a team of graduate students at Syracuse University's Maxwell School. The Clean Energy Futures Project is grateful for their superb work.