National Renewable Energy Laboratory 

Data and Analysis on Energy in Cities

Megan Day, AICP

Colorado College Economics and Business Department Seminar Series

September 3, 2018

NREL/PR-7A40-72323
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable 

Energy, operated by the Alliance for Sustainable Energy, LLC. 

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for 

Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. 

Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy, 

Strategic Priorities and Impact Analysis. The views expressed in the presentation do not necessarily 

represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by 

accepting the presentation for publication, acknowledges that the U.S. Government retains a nonexclusive, 

paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow 

others to do so, for U.S. Government purposes.

This document was prepared as an account of work sponsored by an agency of the United States 

government. Neither the United States government nor any agency thereof, nor any of their employees, 

makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, 

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imply its endorsement, recommendation, or favoring by the United States government or any agency 

thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the 

United States government or any agency thereof.
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Cities-LEAP

Cities Leading through Energy Analysis and Planning

DELIVERS

standardized, localized 

energy data and 

analysis

ENABLES

Cities to lead clean 

energy innovation

INTEGRATE

strategic energy 

analysis into decision 

making

that and
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WHY

CITIES?

SUPPORTS THE WIDESPREAD 

IMPLEMENTATION

of city-sponsored, data-driven energy 

policies, programs, and projects that 

have the potential

DRIVE A SEA 

CHANGE

in the national 

energy landscape.

to

Cities-LEAP
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Cities-LEAP – Cities Leading through Energy Analysis and Planning

FOUNDATIONAL 

RESEARCH

City-Level Energy 

Decision Making: Data 

Use in Energy Planning, 

Implementation, and 

Evaluation in U.S. Cities

CITY ENERGY 

FUTURES

Aggregate, national 

economic and GHG 

impact of suites of city 

energy actions

FUNDING 

OPPORTUNITY 

ANNOUNCEMENT

Three awardees pursuing 

innovative approaches to 

incorporating

energy data in city 

decision making

DATA TO DECISIONS

Pathways to apply data

CITY ENERGY 

PROFILES

Developed new, 

replicable methodology 

and generated a publicly 

available city energy 

profile for every U.S. city
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City-Level Energy Decision Making: Data Use in Energy 

Planning, Implementation, and Evaluation in U.S. Cities

The most common actions fall in 

the Transportation & Land Use and 

Buildings & Efficiency sectors. 

Aznar, A., M. Day, E. Doris, S. Mathur, P. Donohoo-Vallett. 2015. City-Level Energy Decision Making: Data 

Use in Energy Planning, Implementation, and Evaluation in U.S. Cities. Golden, CO: National Renewable 

Energy Laboratory. NREL/TP-7A40-64128. http://www.nrel.gov/docs/fy15osti/64128.pdf. 
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• A city’s level of influence in each sector 

• Political priorities

• Timing and opportunities 

• Staff capacity 

• Data availability and granularity, data management 

and monitoring systems

• Cost considerations 

Factors that Impact City Energy Decision Making

Aznar, A., M. Day, E. Doris, S. Mathur, P. Donohoo-Vallett. 2015. City-Level Energy Decision Making: Data 

Use in Energy Planning, Implementation, and Evaluation in U.S. Cities. Golden, CO: National Renewable 

Energy Laboratory. NREL/TP-7A40-64128. http://www.nrel.gov/docs/fy15osti/64128.pdf. 
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Cities-LEAP

Energy Data for Every 

U.S. City:

Developed new, replicable 

methodology, estimated:

• Electricity, natural gas,

vehicle fuel consumption, expenditures

• Vehicle miles traveled

• Rooftop PV potential

• Building stock by area, number, use

• Commercial and industrial energy 

consumption by NAICS code

• Building energy disclosure potential impact

• Housing types by income

• GHG emissions

Actual data on:

Registered vehicles

• Vehicle fuel types

• Average fuel economy

23,400+ U.S. Cities

https://apps1.eere.energy.gov/sled/
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City Energy Profiles: Electricity, Natural Gas

Learning about 

the energy 

market in your 

city and similar 

cities can lead to 

more strategic 

energy decisions 

toward a clean 

energy future.

https://apps1.eere

.energy.gov/sled
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Electricity and Natural Gas Consumption and Expenditures 

Methodology

Integrated Public Use Microdata Series (IPUMS-USA)

National Historic Geographic

Information System

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Transportation – Fuel Types

Light-Duty Alternative Fuel and Conventional Vehicle, Oakland, CA

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Transportation – Fuel Use, VMT

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Buildings & Industry – Rooftop PV

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Building Stock Characterization

http://apps1.eere.energy.gov/sled/#/. 
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City Energy Profiles: Commercial & Industrial Activity

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Commercial Building Energy Benchmarking

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Greenhouse Gas Emissions Summary

https://apps1.eere.energy.gov/sled
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City Energy Profiles: Income and Housing Data

https://apps1.eere.energy.gov/sled
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Commonly 

implemented city 

actions have the 

potential to achieve 

35% of the 

remaining US COP21 

target.

Estimating the National Carbon Abatement Potential of City 

Policies: A Data-Driven Approach

O’Shaughnessy, E., et al. (2016). Estimating the 

National Carbon Abatement Potential of City Policies: A 

Data-Driven Approach. NREL: 

http://www.nrel.gov/docs/fy17osti/67101.pdf.
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Estimating the National Carbon Abatement Potential of City 

Policies: A Data-Driven Approach

https://www.energy.gov/eere/analysis/downloads/estimating-national-carbon-abatement-potential-city-policies-data-driven
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Estimated national 

employment impacts 

during implementation 

of actions in three 

policy areas

Using an IMPLAN input–output 

(I-O) model to estimate direct, 

indirect, and induced impacts, 

we find city actions across three 

of the policy areas considered 

could support between 52,000 

net jobs nationally (moderate 

abatement scenario) and 

269,000 net jobs (high 

abatement scenario) while 

being implemented and an 

average of 6,000 jobs 

(moderate) to 96,000 jobs (high) 

annually thereafter. 

Analysis suggests the net 

economic impacts of city carbon 

abatement actions are minimal 

and generally slightly positive. 

Estimating the National Carbon Abatement Potential of City 

Policies: A Data-Driven Approach

O’Shaughnessy, E., et al. (2016). Estimating the National Carbon 

Abatement Potential of City Policies: A Data-Driven Approach. NREL: 

http://www.nrel.gov/docs/fy17osti/67101.pdf.
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City Emissions – Drivers of Change Analysis

Drivers of change in emissions in the City of Bellevue, Washington

*After accounting for weather. This change is the net effect of factors that may include occupant behavior, changes to building types and uses, federal 

appliance standards, utility programs and new electronic devices.

Drivers of Change Analysis for Local GHG Emissions: Data for Better Decisions. U.S. Department of Energy Office of Energy Efficiency & 

Renewable Energy. 2018. https://www.energy.gov/eere/analysis/drivers-change-local-greenhouse-gas-emissions-toolkit
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City Energy – From Data to Decisions

Cities-LEAP Partnered with ten cities to demonstrate pathways to apply CitiesLEAP and SLED data and analysis to inform energy planning and decision making

• Asheville, NC Building energy efficiency

• Boise, ID Reducing vehicle fuel consumption

• Carrboro, NC Targeting efficiency for low income households

• Columbia, MO GHG reduction, efficiency for low income households

• Denton, TX Reducing vehicle miles traveled and fuel consumption

• Lafayette, CO Planning for EV infrastructure

• Moab, UT Building energy efficiency

• New Haven, CT Targeting efficiency for low income households

• San Jose, CA Rooftop PV market potential

• South Lake Tahoe, CA EE for buildings and local industries 

https://energy.gov/eere/analysis/downloads/city-energy-data-decisions
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City Energy: 

From Data to Decisions 

https://energy.gov/eere/analysis/dow

nloads/city-energy-data-decisions
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Low-Income Energy 

Affordability Analysis

City Energy – From Data to Decisions

Identifying geographic 

concentrations of 

households with a high 

energy burden can inform 

more strategic policy 

decisions and targeted 

energy efficiency 

interventions. 

https://www.energy.gov/eere/analys

is/downloads/city-energy-datadecisions
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Low-Income Energy Affordability Data

Energy Burden Estimates, Carrboro, NC (2015)

(Preliminary, unpublished analysis. Do not circulate.) Low-Income Energy Affordability Data (LEAD) Tool

https://openei.org/datasets/dataset/celica-data
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Low-Income Energy Affordability Data

Average monthly expenditures by heating fuel type in New Haven, CT (2015)

Avg. monthly household expenditures ($)

https://openei.org/datasets/dataset/celica-data
ACCESS CITY ENERGY PROFILES, TOOL BOX

apps1.eere.energy.gov/sled

ACCESS THE REPORTS

City Energy: From Data to Decisions

https://www.energy.gov/eere/analysis/downloads/city-energydata-decisions

City-Level Energy Decision Making: Data Use in Energy Planning, 

Implementation, and Evaluation in U.S. Cities

http://www.nrel.gov/docs/fy15osti/64128.pdf

Estimating the National Carbon Abatement Potential of City 

Policies:

A Data Driven Approach

http://www.nrel.gov/docs/fy17osti/67101.pdf

STAY INFORMED

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CONTACT

Megan.day@nrel.gov