Grantee Research Project Results
2017 Progress Report: Project 1: Modeling Emissions from Energy Transitions
EPA Grant Number: R835871C001Subproject: this is subproject number 001 , established and managed by the Center Director under grant R835871
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Center for the Study of Childhood Asthma in the Urban Environment
Center Director: Hansel, Nadia
Title: Project 1: Modeling Emissions from Energy Transitions
Investigators: Zimmerman, Julie B. , Hobbs, Benjamin F. , Eckelman, Matthew J. , Weyant, John P. , Wara, Michael W. , Ellis, J. Hugh , Gillingham, Kenneth
Institution: Yale University , The Johns Hopkins University , Stanford University
Current Institution: Yale University , Stanford University , The Johns Hopkins University
EPA Project Officer: Callan, Richard
Project Period: October 1, 2015 through September 30, 2020 (Extended to September 30, 2022)
Project Period Covered by this Report: October 1, 2016 through September 30,2017
RFA: Air, Climate And Energy (ACE) Centers: Science Supporting Solutions (2014) RFA Text | Recipients Lists
Research Category: Climate Change , Airborne Particulate Matter Health Effects , Air , Social Science , Environmental Justice , Particulate Matter
Objective:
In Project 1, researchers are collaborating with the Solutions for Energy, AiR, Climate and Health Center (SEARCH) Center Policy and Decision Making Support Unit and state air regulatory agencies to develop a suite of energy transition scenarios representing many drivers and shifts in the energy sector that could impact regional emissions and air quality. These transitions are being modeled using the National Energy Modeling System (NEMS). NEMS results will be downscaled, and combined with emissions from indirect energy use determined through lifecycle cost assessment (LCA), for input into air quality simulation models, run in Project 3 by researchers at North Carolina State University.
Progress Summary:
Development of transition scenarios: The Project 1 and Policy and Decision Making Support Unit teams have actively coordinated plans to implement transition scenarios in NEMS. In particular, we have focused on two scenarios so far: one to study electric vehicle penetration and market implications and the other to examine the impacts of increasing U.S. natural gas supply on energy markets, regional emissions and air quality. We also are preparing a third scenario, which focuses on increased distributed generation and demand response changing the electricity system.
Participants in this effort include project staff from Yale, Johns Hopkins University (JHU) and Stanford, the latter having also participated in the Policy and Decision Making Unit through the efforts of Michael Wara.The Policy Unit has provided advice on the development of the scenarios, given feedback on our surveys with policymakers and facilitated discussions with policymakers.
Modeling transition scenarios in NEMS: In Year 1, we focused on developing a working version of NEMS. In Year 2, we set up a working version of NEMS running at Yale, with runs replicating both the Annual Energy Outlook (AEO) 2016 and AEO 2017. The original version of the model acquired from Energy Information Agency (EIA) required additional work to adapt to our purposes. We have addressed compilation issues and successfully made several model runs, using expertise at both Yale and JHU and assistance from contacts at EIA. The steps of changes implemented to make the model run on the Yale workstation have been documented. As later versions of NEMS become available in the future, those changes can be implemented to the newer models and reduce the time to solve compatibility issues. In addition, we have adopted a version control platform, "Git," to document every change applied to the model. We can switch easily to previous working versions and various scenarios to replicate model results without adding storage burdens.
The working version of NEMS in our team has thus far been used to run two transition scenarios, and a third scenario is under development by the Stanford part of the team. For the electric vehicle (EV) scenario, we have run several subscenarios, in which preference for EVs increased over time. We are in the process of developing alternative battery cost trajectories to compare the level of EV penetration and modifying the way NEMS allocates emissions associated with electric vehicles across regions to improve its accuracy.
For the abundant natural gas scenario, we have modified the total availability of natural gas resources within NEMS according to Potential Gas Committee's latest report on U.S. natural gas resources and reserves estimates, which is assumed to be 3,100 Tcf compared to the 2,355 Tcf assumed by AEO 2017. We also have made several runs with or without the Clean Power Plan or hypothetical carbon taxes. One important addition to our study is that we also have developed a simple approach to compute the economic welfare outcome changes from our modeled transition scenarios when compared to the AEO 2017 reference case.
The Stanford team members have been focusing on the specification and incorporation into NEMS of the "increased distributed generation and demand response" energy transition scenario. The work stream involves a comprehensive literature review of similar modeling work to make sure that the scenarios are developed based on the best evidence available.
Downscaling: The output data from NEMS are used for downscaling. For outputs that are already available by NEMS region by default, we use the standard NEMS output files. For those that are not reported in the regional level but instead at the national level, the Yale team first modified the model code to extract all relevant raw data from NEMS running in text files and then processed and transformed them to the same regional format as the standard NEMS output for use in the downscaling procedures.
The Johns Hopkins team continued building tools to downscale NEMS results, using data produced by the Yale-NEMS model. The downscaling method we have implemented thus far produces a set of spatially and sectorally differentiated emission growth rates, which will be used by Project 3 for processing and air quality simulation for most economic sectors. Some of this work relies on growth factors available from the U.S. Environmental Protection Agency (EPA) that they have used when creating downscaled scenarios based in part upon MARKAL results. We also have made progress on downscaling electric generating unit point sources and transportation. In particular, we began implementing innovative techniques for downscaling new point sources that includes a GIS screening step and generation placement based on capacity expansion modeling, to improve on current technique of "grow-in-place." The modeling method considers within-region transmission constraints; site availability; and the distribution of electricity demand, existing generators and renewable resources. We also have a version of SMOKE transportation emissions model running, which we will use to develop the transportation sector downscaling technique.
Lifecycle Assessment: During the reporting year, the Project 1, LCA teams have:
- Supported doctoral students, as well as three undergraduate under-represented minority students in preliminary project research, with one-on-one mentoring and integration into the research team.
- Installed, tested and calibrated a multiregion input-output model (EXIOBASE) that focuses on trade, together with a domestic national model (USEEIO) that focuses on domestic manufacturing, with pilot scenarios for increases in electric vehicle production.
- Recreated and identified several errors in a well-known comparative life cycle assessment of passenger vehicles.
- Compared model operation and emissions coverage between EPA's 2011 NATA study and the NEMS model used for the SEARCH project, in preparation for adding additional pollutant outputs to NEMS.
In addition to progress on the proposed tasks, the LCA team also has conducted exploratory analysis in using advanced machine learning algorithms to predict local ambient air quality based on upwind monitoring and meteorological data, for possible testing within the SEARCH project.
Future Activities:
Development of transition scenarios: Final transition scenarios will be developed with input from internal teams and external stakeholders.
Modeling transition scenarios in NEMS: Our next steps include continuing to fine-tune our scenario implementations within NEMS and analyzing modeling results for the EV and abundant natural gas scenarios. We will then continue the process of writing papers and submitting them to academic journals. We expect to have our first working paper ready around the end of the calendar year. Meanwhile, we will begin implementing runs of additional energy transition scenarios, including a shift to an electricity grid focused on distributed generation and demand response, and another scenario representing a shift to a carbon-constrained economy, as mentioned above. Modeling the scenarios will involve a combination of utilizing existing levers in the model and making changes to the underlying input data and code.
Upon completion of its transitions literature review, the Stanford team will work with the Yale Project 1 modeling team on the implementation of the energy transition scenarios in NEMS. This has been greatly facilitated by having NEMS working with AEO 2017 on a workstation that has secure VPN capabilities. The Stanford team will be implementing the scenario on the Yale NEMS workstation and in coordination with the Yale team; the results will be passed on to the Johns Hopkins team for downscaling to eventual use by Project 2 and Project 4.
Downscaling: We will continue to refine and streamline the basic growth factor calculation methodology and continue to coordinate with Project 3 on procedures for sharing downscaled growth rates. We also will implement the point source and transportation downscaling techniques and ensure that the new downscaling methods can be implemented by the air quality simulation team. The point source work is under review at the premier energy engineering systems annual conference held in the summer, and additional conference and journal papers will be submitted.
Anticipating that we will have more NEMS transition runs than will ultimately be analyzed for air quality impacts, our team will develop a method to prioritize which transitions are most significant from a public health perspective. These likely will be scenarios that show relatively larger growth or more significant changes in spatial distribution for ozone precursors and particulate matter.
Lifecycle Assessment: In the coming year, the SEARCH LCA team will attempt to add background lifecycle inventory (LCI) data to the NEMS model Industrial Demand module code, in close collaboration with the Yale-NEMS modeling team. LCI data will be derived from two different models for alternate testing: one that reflects solely domestic manufacturing and one that reflects the international supply chains that support electric vehicle and component manufacturing worldwide. Based on initial work, the LCA team also will propose a list of additional pollutants to include in the Electricity and Fuels modules of NEMS and will continue exploratory work in applying machine learning methods for air quality prediction.
Journal Articles:
No journal articles submitted with this report: View all 3 publications for this subprojectSupplemental Keywords:
Emissions downscaling, energy-economic modeling, energy transitions, lifecycle assessment, LCA, National Energy Modeling System, NEMS, pollution prevention, social science, systems analysisRelevant Websites:
The SEARCH Center: Solutions for Energy, AiR, Climate, and Health
Progress and Final Reports:
Original AbstractMain Center Abstract and Reports:
R835871 Center for the Study of Childhood Asthma in the Urban Environment Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R835871C001 Project 1: Modeling Emissions from Energy Transitions
R835871C002 Project 2: Assessment of Energy-Related Sources, Factors and Transitions Using Novel High-Resolution Ambient Air Monitoring Networks and Personal Monitors
R835871C003 Project 3: Air Quality and Climate Change Modeling: Improving Projections of the Spatial and Temporal Changes of Multipollutants to Enhance Assessment of Public Health in a Changing World
R835871C004 Project 4: Human Health Impacts of Energy Transitions: Today and Under a Changing World
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
Main Center: R835871
118 publications for this center
73 journal articles for this center