Capturing the complexity of economic, environmental, and social interactions to analyze impacts of climate change

Analyzing the impacts of climate change can require a model or suite of models capable of capturing the full complexity of economic, environmental, and societal interactions and the adaptive nature of producer, consumer, and government stakeholders to engage within a coherent structure.

Our team’s subject matter expertise in emissions, cross-sector climate impacts, and climate solutions contributes to our ability to provide comprehensive, robust model simulations of how individual sectors and the broader economy will respond to mitigation efforts.  Drawing on our extensive experience, we develop and apply our economic models to help our clients:

  • Project reference levels of emissions decades into the future
  • Simulate responses of emissions sources to policy and market conditions 
  • Account for variables and conditions that might change in the future and what scenarios are possible or probabl
  • Evaluate implications, risk, and consequences of different scenarios for the environment, economy, health, and well-being.

Our modeling teams develop and apply state-of-the-science models in several key areas:

Land use

We use a diverse array of models to address land use competition and the implications of policy and environmental changes on land use change, land management intensity, and greenhouse gas (GHG) emissions. We also draw on partial equilibrium models such as the Forest and Agricultural Sector Optimization Model with Greenhouse Gases (FASOM-GHG), the Global Timber Model (GTM), the Global Forestry and Agriculture Model (GFAM), and Global Biosphere Management Model (GLOBIOM), and the Land Use and Resource Allocation (LURA) model.


Our electricity modeling capabilities include spatially explicit levelized cost of electricity (LCOE) model developed by RTI and applications of the National Renewable Energy Laboratory’s open-access ReEDS model, including a linkage to our general equilibrium model of the United States, ARTIMAS®. 


RTI’s water resources team has developed models, data systems, and frameworks to increase understanding of flood and water supply risks and support decision making for clients facing a range of water-related challenges.  Our systems include RTI’s WaterFALL®, HydroBID, HydroRAM, and WaterALLOC to evaluate impacts of climate change on water availability and infrastructure and our Amanzi systems and Rapid Dam Risk Suite for flood-related analyses. 


RTI’s economists support a wide range of economy-wide analyses, from local input-output analyses to global general equilibrium analyses. Our intertemporal dynamic ARTIMAS model of the U.S. economy covers 9 census regions with state-level breakouts and detailed sectoral coverage including a technologically rich, integrated electricity sector or optional dynamic linkage with NREL’s open-source ReEDS model. Our recursive dynamic RTI ADAGE® model of the global economy covers 8 regions with detailed treatment of land use, biofuel, and transportation sectors. 


Our economists specialize in developing non-market valuation models of differential environmental attributes (e.g., temperature) to estimate impacts on human health and well-being.  RTI’s work on assessing heat-related health impacts can be applied to inform adaptation and mitigation strategies in urban locations and our econometric models can be applied to estimate the value of milder seasonal temperatures and examine the impact of counterfactual climate scenarios on migration patterns. 


Indicators can provide a useful way to track and communicate impacts of climate change and help assess vulnerabilities and resilience of communities.  We have supported the development and application of a variety of ecosystem indicators including forestry and agricultural productivity and aquatic ecosystem health, and vulnerability indicators representing historical and projected extreme events, characteristics of waste facilities, wind and hydrological patterns, and sensitivity (e.g., socioeconomic, demographic) characteristics. We apply spatial mapping techniques to these indicators to identify vulnerable communities and support an indicator-based assessment approach that enables assessment of community resilience and supports planning.