Global Change and Climate Research
OverviewThe Energy and Climate Assessment (ECA) Team is a multi-disciplinary group that is based in National RisK Management Research Laboratory’s (NRMRL's) Air Pollution Prevention and Control Division (APPCD) in Research Triangle Park, N.C. ECA supports EPA’s global change and climate research by providing “bottom-up” analyses that consider the drivers of technology change and the implications on emissions and air quality. This is done via a systems perspective that moves beyond traditional lifecycle assessment to consider important economic, social, and technological interactions.
Team Members | Motivations | Capabilities | Tools | Methodologies | Projects | Contact Information |
Core EPA Team Members | ||
Name | Roles | Contact Information |
---|---|---|
Rebecca Dodder | Biomass and biofuels, agricultural sector | dodder.rebecca@epa.gov |
Cynthia Gage | Transportation, refrigeration, energy efficiency and conservation, end-use demands | gage.cynthia@epa.gov |
Tim Johnson | Co-team lead, regional assessments, geographic and systems modeling, electric sector | johnson.tim@epa.gov |
Dan Loughlin | Light-duty transportation, emissions, sensitivity & uncertainty analysis, and team liaison to EPA's Office of Air and Radiation | loughlin.dan@epa.gov |
Carol Shay Lenox | Co-team lead, database management, model calibration, energy efficiency and conservation | shay.carol@epa.gov |
Post-doctoral Fellows | ||
Name | Roles | Contact Information |
Ozge Kaplan | Electric sector, biomass, landfills, waste-to-energy | kaplan.ozge@epa.gov |
Samudra Vijay | Industrial sector, electric sector | vijay.samudra@epa.gov |
In the past century, factors such as population growth and migration, economic expansion, land use change, climate change, technology change, and resource constraints have had considerable effects on the environment and human health. With populations expected to continue to grow and additional countries joining the ranks of the developed, the potential for humans to impact critical Earth systems is increasing. In this context, it is important that decision makers have the information necessary to identify future risks to the environment and to act proactively and effectively to moderate or adapt to those risks.
Two potential area of concern in the future are climate change and air quality. Current demands for transportation and energy are met largely through the combustion of fossil fuels. Combustion is a major source of greenhouse gases as well as the man-made emissions that contribute to air pollution, such as tropospheric ozone (O3), coarse and fine particular matter (PM), and mercury (Hg). Thus, there is the potential for increasing energy demands to result in exacerbated climate change and degraded air quality.
Energy generation and demand technologies are not expected to remain static,
however. Potentially cleaner technologies that may play a role in meeting
future energy demands include: advanced nuclear reactors, wind and solar
power, biomass, coal gasification, and hydrogen fuel cell vehicles. The
extent to which these and other technologies penetrate the energy system
may have important implications on our ability to adapt to future global
changes while protecting the environment.
The EPA ECA team is using the MARKet ALlocation (MARKAL) energy system model to estimate future-year technology penetrations and the associated greenhouse gas and criteria pollutant emissions. A wide range of scenarios can be investigated with MARKAL, including different assumptions about future technology characteristics, fuel costs, energy policies, and air quality regulations. The MARKAL framework also allows assessments related to specific technologies, such as the cost or efficiency needed for a new technology to be competitive with conventional technologies. For example, wind turbines could be evaluated and compared to conventional coal for meeting peak and baseload electricity demands.
An advantage of using MARKAL over single-sector models is that it characterizes both intra- and cross-sector impacts of technologies. For example, if hydrogen fuel cell vehicles were to penetrate the transportation market, MARKAL suggests that the least cost method for producing hydrogen would be via steam methane reform of natural gas. Increased demand for natural gas could drive up natural gas prices, potentially leading to fuel switching from natural gas to other fuels in electricity generation and other sectors. MARKAL allows us to identify these interactions and characterize the potential effects on sectoral and system-wide emissions.
The ECA team, along with other EPA partners in the Agency, is using a suite of tools that work with the MARKAL model to provide additional insights into the U.S. energy system. For example, we have integrated MARKAL into a modeling framework that facilitates Monte Carlo simulations. By analyzing the Monte Carlo results using data-mining algorithms, we are able to identify and rank the key factors that lead to particular outcomes, such as the penetration of a particular technology or high levels of air pollutant emissions. We are also using mathematical modeling techniques collectively called Modeling to Generate Alternatives. These techniques allow us to identify a small number of very different, cost-effective technology pathways to achieve emissions reduction goals. The similarities and differences among these solutions provide valuable information regarding the flexibility available.
Tools- EPA National MARKAL (MARKet ALocation) Database and Model (EPANMD) – MARKAL is a model that represents an energy system from the extraction or import of fuels, through their conversion to useful forms, to their use to meet commercial, industrial, residential, and transportation demands. The U.S. EPA has developed a national MARKAL database that extends to 2035. EPA is working to regionalize the database into nine census regions and to extend the modeling horizon to 2055. For more information about MARKAL...
- Regulatory Models: MOBILE, SMOKE, & CMAQ – These models are the U.S. EPA’s regulatory models for many emissions and air quality applications. The MOBILE model is used to calculate vehicle emissions factors given characteristics of the vehicle fleet, roadways, and driving speeds. SMOKE is an emissions processing model that takes emissions and activity factors as input. Emissions are then temporalized, speciated, and gridded such that they can be input into an air quality model. The CMAQ model is EPA’s air quality model that is used to estimate air quality. CMAQ outputs hourly ambient concentrations of pollutants such as tropospheric ozone and fine particulate matter. Spatial resolution typically ranges from urban-scale (4km by 4km grid cells) to regional or national scale (80km by 80 km grid cells). The ECA team is partnering with other EPA groups to link MARKAL-generated emissions with these modeling tools.
- PM2.5 and Ozone Response Surface Models – Execution of models such as SMOKE and CMAQ can be very computationally intensive, limiting their use in applications in sensitivity analyses and that require more than a few scenarios to be evaluated. An alternative is to capture the relationship between emissions and air pollutant concentrations using a statistical response surface application, and then to use this representation as a surrogate for the full-scale model. OAQPS has developed response surface models for ozone and fine particulate matter. The ECA Team, in conjunction with OAQPS, is exploring linking these models to MARKAL to provide estimates of the air quality impacts associated with different future-year technology scenarios.
- MIMS – The Multimedia Integrated Modeling System (MIMS) is a modeling framework developed by EPA’s National Exposure Research Laboratory (NERL). MIMS is used by the ECA team to carry out sensitivity and uncertainty analyses with MARKAL and other models, visualize and analyze results, and link MARKAL to other models to form integrated modeling systems.
Other models and tools being used by the EPA ECA Team for various purposes include: GREET, a life cycle model for light duty vehicle technologies; MAGICC, a simple climate change model; CUECost, a model for estimating costs and efficiencies of emissions controls on coal-fired electricity generation plants; and WEKA, data-mining software.
The tools mentioned in the previous section are being used within a variety of systems analysis methodologies. These include:
- Prescriptive modeling – Identifying the technological pathways that meet specific demands and performance constraints (e.g., criteria emissions limits) at least cost
- Scenario analysis – Imposing the penetration of a technology, technology pathway, or state of the world (e.g., future fuel availability scenarios, synchronization with alternative IPM scenarios), and examining the in- and cross-sector implications on technologies, fuel use, emissions, and other key outputs
- Modeling to Generate Alternatives (MGA) – Identifying very different alternative pathways to meet modeled goals, potentially with very different environmental implications (e.g., different pathways for meeting future emissions limits might have very different impacts on air quality, reliance on imports)
- Sensitivity analysis – Identifying the input parameters that have the greatest impact on the magnitude or variance of key model outputs. Parametric sensitivity analysis is used to examine the model response to incremental changes, while global sensitivity analysis examines sensitivities over a large number of input realizations
- Multi-objective analysis - Examining the tradeoffs between competing objectives, such as minimizing cost and reducing emissions
- Uncertainty analysis – Estimating the range, percentiles, and distributions of key model outputs
- Reliability analysis – Examining the likelihood that a specific performance target is or is not met
- Risk assessment – Identifying potentially undesirable outcomes that may occur and characterizing the common elements of pathways that lead to or avoid these outcomes
- Risk management – Identifying technological pathways for reducing risks related to air pollutant and greenhouse gas emissions
- Hedging analysis – Identifying optimal short-term strategies that account for assumptions about the likelihood of various prospective technologies being available (e.g., advanced nuclear, carbon capture and sequestration), policies (e.g., tightened criteria pollutant limits) being in place, or demand scenarios being realized (e.g., high, medium, low) in a specific future year
- Model Integration - Linkage to OAQPS’s Response Surface Model (RSM) and benefits assessment model (BenMAP) to evaluate air quality and health benefit implications. Further, these and other tools are being linked to develop decision-support systems to assist decision-makers in evaluating the energy system and emissions responses to various state, regional, and national actions.
Projects
Selected projects that were recently completed or that are currently being
carried out by ECA Team are described below.
- Global Change Air Quality Assessment – The Global Change Air Quality Assessment is a project being carried out by the EPA’s Office of Research and Development as part of the Federal government’s Climate Change Science Program. The goal of the assessment is to characterize the impacts of global change (e.g., population growth and migration, economic growth, technology change, land use change, and policy) on future-year U.S. air quality, with a focus on the year 2050. US EPA's ECA team's primary role in this project is to generate emissions scenarios that take into account technology change. For more information about the assessment...
- Adaptation - The models and methodologies described above provide decision makers with tools and analyses to act proactively and effectively to moderate or adapt to environmental risks associated with global change. For example, one approach by which populations adapt to climate change is through modifying energy service demands for heating and air conditioning. By analyzing these demand shifts, the ECA team can aid decision makers in anticipating the resultant impacts on technology choices, fuel use, and thus environmental releases. One of the early projects which will support adaptation responses is a workshop which is planned for FY 2008. This workshop will bring a representative set of decision makers together with EPA researchers to discuss needs and options for dealing with the vulnerabilities and opportunities climate change presents for their natural and social environments.
- Geographic Allocation of Emissions – With MARKAL, the ECA team can generate future year emissions growth factors associated with meeting various demands (e.g., electricity generation, home heating, and commercial cooling). One potential approach for using these factors in emissions modeling is to apply them to current sources. This, however, does not take into account factors such as the expansion of urban and suburban areas and the introduction of new energy capacity to meet the demands of these areas. To more accurately predict future year air quality, we are exploring methods to take these and other factors into account when geographically allocating future-year emissions.
- Aerosols and Regional Climate and Air Quality Impacts – Emissions of aerosols and aerosol pre-cursors from anthropogenic sources can have regional impacts both on air quality and climate. Air quality impacts are a concern since aerosols (e.g., fine particulate matter) have been linked to human respiratory problems. Regional climate impacts are related to the positive and negative warming forcings associated with different chemical species of aerosols. We are exploring how direct aerosol emissions associated with different energy technology scenarios can be characterized with MARKAL.
- NE-MARKAL – The ECA team has completed a cooperative agreement with the Northeast States for Coordinated Air Use Management (NESCAUM). The outcome of the project was NESCAUM’s development of a six-state version of the MARKAL model. The New England MARKAL model (NE-MARKAL) is being used by NESCAUM to evaluate the implications of a variety of state and regional actions on pollutant emissions. NESCAUM is currently expanding the model to include all 12 Northeast states.
For more information, please contact Carol Lenox (919-541-0590) or Tim Johnson (919-541-0575).