2012 Progress Report: Regional Infrastructure and Air Quality Planning in Light of Global ChangeEPA Grant Number: R834283
Title: Regional Infrastructure and Air Quality Planning in Light of Global Change
Investigators: Hess, Peter , Donaghy, Kieran P. , Mahowald, Natalie M. , Zhang, Ke Max
Institution: Cornell University
EPA Project Officer: Callan, Richard
Project Period: October 1, 2009 through September 30, 2012 (Extended to September 30, 2015)
Project Period Covered by this Report: October 1, 2011 through September 30,2012
Project Amount: $591,683
RFA: Adaptation for Future Air Quality Analysis and Decision Support Tools in Light of Global Change Impacts and Mitigation (2008) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Global Climate Change , Climate Change , Air
The purpose of the research is to: 1) determine how changes exogeneous to the United States, including changes in climate, changes in emissions and changes in the global economy, will impact U.S. air quality over the Northeastern region of the United States in the future; 2) determine how long-term changes in transportation infrastructure, technology and power generation in response to future economic and regulatory changes (including those induced by climate change) will induce communities within the Northeastern United States to make regional scale changes in land use, transportation and spatial interaction to reduce greenhouse gas emissions, and thus modify regional air quality.
In the past year, we have operationalized a dynamic commodity-flow model. This model characterizes the evolution over space and time of the interdependent behaviors of producers (shippers) and carriers and their associated emissions. It also provides the capability, heretofore missing, to forecast the evolution of emissions patterns resulting from structural changes in the economic geography of a set of regions, from which regional air quality forecasts can then be made.
The model solution was able to satisfactorily reproduce differences between the imputed historical data in commodity flows over the 31 years for which we have data when compared for five states in the Midwestern region and the rest of the United States. The model was able to reproduce, on the basis of economic reasoning:
- increased geographic concentration or clustering of sectoral activities,
- increased demand for intermediate inputs and intrasectoral trade, hence
- economies of scale and scope in production,
- increased transport intensity of production, hence
- an increase in transport’s share of emissions (non-point source) even as point source emissions decrease on a per-unit of production basis.
We have run a number of control simulations diagnosing the ability of the CESM 1.0 (Community Earth System Model 1.0) to simulate the regional climate and chemistry over the Northeastern United States. The two simulations run to date use different configurations of the same modeling framework: (1) an offline simulation using reanalyzed MERRA meteorology, and (2) an online simulation with observed SSTs, where the meteorology is internally generated but observed sea surface temperatures (SSTs) are used. Both simulations reproduce much of the interannual variability of summertime temperature and ozone as measured at CASTNET stations over the Eastern United States. This suggests that SST is an important component in forcing the summer-time interannual ozone variability over the Eastern United States. It also raises the question of whether models with internally generated SST will be able to simulate the observed ozone climatology of the Eastern region.
The climate penalty factor is better simulated in the offline configuration (3.0 ± 0.3 ppbv/K) than the online configuration (4.2 ± 0.32 ppbv/K) when compared with CASTNET data (2.5 ± 0.1 ppbv/K) using monthly averaged ozone and temperature evaluated at the CASTNET sites. We are re-evaluating this factor when measured using reference temperature and 2m ozone.
Future activities include (1) evaluation of simulations of the Community Earth System Model (CESM) in a fully coupled mode in which the model internally generates both the meteorology and the SSTs; (2) employing the dynamic commodity flow model to continue to refine future emission scenarios on regional and local scales over the Northeast United States; and (3) running the CESM in future and present day configurations using emissions generated from the dynamic commodity flow model.
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Journal Articles:No journal articles submitted with this report: View all 16 publications for this project
Supplemental Keywords:RFA, Scientific Discipline, Air, POLLUTION PREVENTION, Energy, climate change, Air Pollution Effects, Environmental Monitoring, Atmospheric Sciences, Atmosphere, atmospheric nitrogen, particulate matter, decision making, energy efficiency, environmental policy, forests, deforestation, ecosystem sustainability, air quality, Global Climate Change, land use