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Grantee Research Project Results

2007 Progress Report: Impacts of Global Climate and Emissions Changes on U.S. Air Quality (Ozone, Particulate Matter, Mercury) and Projection Uncertainty

EPA Grant Number: R833373
Title: Impacts of Global Climate and Emissions Changes on U.S. Air Quality (Ozone, Particulate Matter, Mercury) and Projection Uncertainty
Investigators: Liang, Xin-Zhong , Wuebbles, Donald J. , Williams, Allen , Liu, Feng , Lei, Hang , Huang, Ho-Chun , Zhu, Jinhong , Lin, Jintai , Hayhoe, Katharine , Patten, Ken , Kunkel, Kenneth , Caughey, Michael , Wang, Xueyuan , Tao, Zhining
Current Investigators: Liang, Xin-Zhong , Wuebbles, Donald J. , Williams, Allen , Lei, Hang , He, Hao , Kunkel, Kenneth , Caughey, Michael , Su, Senjian
Institution: University of Illinois Urbana-Champaign
Current Institution: University of Maryland - College Park
EPA Project Officer: Chung, Serena
Project Period: April 15, 2007 through April 14, 2011 (Extended to April 14, 2013)
Project Period Covered by this Report: March 1, 2007 through February 29,2008
Project Amount: $900,000
RFA: Consequences of Global Change For Air Quality (2006) RFA Text |  Recipients Lists
Research Category: Climate Change , Air

Objective:

The objective of this study is to quantify and understand the impacts and uncertainties of global climate and emission changes, from the present to 2050 and 2100, on USA air quality, focusing on ozone, particulate matter and mercury. The original contribution of this research will derive from the application of a unique, state-of-the-art, well-established ensemble modeling system that couples a global climate-chemical transport component with a mesoscale regional climate-air quality component over North America. Both components incorporate multiple alternative models representing the likely range of climate sensitivity and chemistry response under the conceivable emissions scenarios to rigorously assess the result uncertainty. Each will be enhanced to contain a fully coupled model to study climate-aerosol interactions, focusing on how they affect USA air quality at the present and in the future.
 
We propose to conduct 3 primary sets of experiments by the ensemble modeling system to achieve the proposed objective. Historical simulations of climate and air quality for the recent past will first be conducted for system validation and bias identification, and also used as the baseline reference for future projections. Future projections for 2050 and 2100 will then be made to quantify the individual and combined impacts of global climate and emissions changes on USA air quality. Finally, sensitivity experiments will refine understanding of relationships with major contributing source regions and types, and uncertainties associated with key conclusions. All experiments will focus on April-October when most air quality episodes occur (except for sensitivity studies on the PM and mercury annual cycle), and integrate for a period of 5-10 years to obtain reasonably robust statistics. Subsequent diagnostic studies will identify possible future changes, and their climate and emissions causes, in the frequency, duration, and extreme pollutant concentrations of adverse air quality episodes over the USA.
 
Through the proposed application of this unique ensemble modeling system, we will make a major contribution to a key goal of the EPA Global Change Research Program to quantify the effect and uncertainty of global changes on USA air quality. The advanced state of the system components will result in a more complete scientific understanding of complex interactions among global climate and emissions and USA air quality across a full range of spatial and temporal scales. We will build on recent achievements of our ozone study, including a developed modeling system, viable experiment design, effective modeling strategy and objective diagnostic approach, for ozone consolidation, aerosol elaboration and mercury exploration studies for use in designing future effective emission control strategies to meet the national standards.

Approach:

The Approach is to conduct 3 primary sets of experiments by the ensemble modeling system to achieve the proposed objective. Historical simulations of climate and air quality for the recent past will first be conducted for system validation and bias identification, and also used as the baseline reference for future projections. Future projections for 2050 and 2100 will then be made to quantify the individual and combined impacts of global climate and emissions changes on U.S. air quality. Finally, sensitivity experiments will refine understanding of relationships with major contributing source regions and types, and uncertainties associated with key conclusions. All experiments will focus on April-October when most air quality episodes occur (except for sensitivity studies on the PM and mercury annual cycle), and integrate for a period of 5-10 years to obtain reasonably robust statistics. Subsequent diagnostic studies will identify possible future changes, and their climate and emissions causes, in the frequency, duration, and extreme pollutant concentrations of adverse air quality episodes over the U.S.

Progress Summary:

·                     We have demonstrated that the RCMs’ downscaling reduces significantly driving GCMs’ present-climate biases and narrows inter-model differences in representing climate sensitivity and hence in simulating the present and future climates. Very high spatial pattern correlations of the RCM minus GCM differences in precipitation and surface temperature between the present and future climates indicate that major model resent climate biases are systematically propagated into future climate projections at regional scales. The total impacts of the biases on trend projections also depend strongly on regions and cannot be linearly removed. The result suggests that the nested RCM-GCM approach that offers skill enhancement in representing the present climate also likely provides higher credibility in downscaling the future climate projection.
 
·                     We have found that changes in intercontinental transport (ICT) of pollutants can have substantial consequences on future U.S. air quality. The projected ICT changes are primarily affected by changes in anthropogenic emissions over Europe and Asia, which may cause 3–8 ppb more (0-2 ppb less) ozone under the A1Fi (B1) scenario in 2049 and 2099 over the western U.S. The nested regional air quality model simulations show that the net increase due to the long range transport in 2095-2099 ranges from +4% to +11% in daily maximum 8-hr average ozone concentrations. Therefore global, especially Asian, emission control is important for future U.S. pollution mitigation.
 
·                     We have quantified the uncertainty in projecting future U.S. ozone changes by using the ensemble approach based on the nested regional modeling system. This ensemble consists of six combinations of two GCMs each with two emissions scenarios and two downscaling RCMs with different cumulus parameterizations. The result indicates a large range of uncertainties due to various model configurations and emissions scenarios. The projected daily maximum 8-hr average ozone changes range from -31% to +51%. In general, the A1Fi scenario projects a substantial increase in both surface ozone concentrations and exceedance days, while the B1 scenario results in a significant decrease. Thus future U.S. pollution control must consider the large uncertainty in model projected trends and their sensitivities to global climate and emissions changes.
 
·                     We have investigated the model factors that affect the simulation of summertime U.S. surface ozone diurnal cycle in the global chemistry transport model MOZART. We have identified that the dominant factor is the representation of the planetary boundary layer (PBL) mixing, while the influence of horizontal resolutions and precursor emissions is relatively small but non-negligible. With the non-local mixing PBL scheme, a relatively high horizontal resolution (~1.1°) and updated emissions data, the MOZART is able to simulate the key characteristics of the observed ozone diurnal cycle.
 
·                     We have demonstrated that the Bermuda high over the North Atlantic plays a major role in U.S. climate variations. In particular, when the Bermuda high is strong, abnormally warmer (colder) air prevails over the eastern (western) U.S. We anticipate that interannual variations and future changes of the Bermuda high have significant impacts on the patterns of surface air temperature, precipitation, wind circulation, and consequently pollutant transport and air quality in the U.S. Unfortunately all existing GCMs poorly simulate the Bermuda high interannual correlation patterns, imposing a serious problem for U.S. air quality modeling.
 
·                     We have incorporated the NCAR CCSM3 and the GFDL CM2.1, with the respective low and high climate sensitivity, in addition to the PCM and HadCM3 used in our previous STAR project, to improve the representation of the uncertainty range in GCM simulations of the present climate and future projections. Taken together, the simulations from the four GCMs under 4 IPCC SRES emissions scenarios form the largest ensemble for U.S. regional climate and air quality downscaling studies.
 
·                     We have now acquired the NCAR CCSM3 6-hourly outputs for the present climate and the future projection of the IPCC SRES A1Fi (high) scenario in window periods: 1990-1999, 2045-2055 and 2090-2099. We also have acquired GFDL CM2.1 6-hourly output for the present climate and the future projection of the IPCC SRES A2 (medium high) scenario in window periods: 1990-1999 and 2045-2055. We are acquiring the CCSM3 6-hourly outputs for the future projections of the SRES A2 B2 and B1 scenarios in window periods 2045-2055 and 2090-2099. These CCM3 and CM2.1 future projections will bridge the gap between the PCM and HadCM3 for a direct comparison.
 
·                     We have completed the RCM integration driven by the CCSM3 for 1990-1999. The result indicates that the present-day climate simulated by the CCSM3 is more realistic than the previous PCM, so does the corresponding RCM downscaling result. We anticipate that the global chemical transport and regional air quality simulations as driven by the CCSM3 and its RCM downscaling climates will be more credible than those based on the PCM.
 
·                     We have completed the CAM-Chem global chemistry transport integration driven by the CCSM3 climate during 1995-1999. As compared with the MOZART used in our previous STAR project, the CAM-Chem produces systematically greater positive ozone biases except for California. The only difference between the two simulations is that dry deposition is represented online in the CAM-Chem while prescribed in the MOZART. The result indicates the necessity to improve dry deposition representation. In addition, the CAM-Chem captures the main characteristics of the annual mean PM10 and PM2.5 geographic distributions. The PM10 biases are generally in the range of -8 to +16µg/m3 as compared with the sparse EPA AQS measurements. They may result from the dust transport that is currently not incorporated in the model. For PM2.5, the CAM-Chem simulates 9-12 µg/m3 over the eastern U.S., approximately 3µg/m3 higher than observations, and 3-12 µg/m3 in the western U.S., close to observations.
 
·                     We have implemented the latest emission processor SMOKE v2.4 and incorporated the best available anthropogenic emissions inventories as well as biogenic emissions using BELD3 for the U.S., Mexico and Canada. By integrating the RCM downscaling meteorology driven by the CCSM3 simulation in 1995, we have processed the emissions on the regional modeling grids for the entire year and analyzed their diurnal cycles and seasonal variations.
 
·                     We have improved the CMAQ representation of lateral boundary conditions. In particular, we have incorporated the dynamic relaxation procedure to integrate large-scale forcings from the CAM-Chem global simulations across the buffer zones of a specified width. Such a procedure is fully consistent with that used in the RCM climate downscaling. Wider buffer zones have been found necessary to ensure realistic RCM climate downscaling over the continental U.S. domain. So is expected to ensure realistic CMAQ air quality downscaling from the CAM-Chem. This expands, for the first time, the CMAQ ability from the long-standing method of representing the long-range chemical transport using a single cell around the domain edges. More importantly, we can now integrate the external forcings as time tendencies rather than full fields of chemical species and thus reduce the impact from the existing CAM-Chem systematic errors.
 
·                     We have completed a full year integration of the CMAQ regional modeling system that integrates the SMOKE processed emissions, the RCM downscaling meteorology, and the long range chemistry transport from the CAM-Chem, all driven by the CCSM3 climate simulation in 1995. The system simulates the observed PM10 seasonal variations over the Northeast reasonably well except for some overestimation in November. In the Midwest, the model largely underestimates PM10 during summer, likely resulting from the lack of local emissions and regional transport of dust particles. On the other hand, the CMAQ realistically simulates the spatial patterns and magnitudes of the annual mean ammonium, nitrate and sulfate concentrations, as well as their wet depositions. Such agreement with observations lends certain confidence for the use of the regional modeling system to simulate PM2.5 over the U.S. The CMAQ also captures the observed patterns of wet deposition of mercury over the Northeast and Midwest, but fails to reproduce the high depositions over the Southeast. This failure may be identified with poor estimations of mercury emissions, currently lack of those from Mexico, Canada and oceans.
 
·                     Progress in completing project tasks is in line with our original proposal and in some cases we have accomplished more than originally proposed. With the support of this EPA STAR project, we have so far published 2 articles, submitted 3 articles and almost completed 1 manuscript for publication in peer-reviewed journals. We have also made 5 presentations in meetings and seminars.

Expected Results:

Through the proposed application of this unique ensemble modeling system, we will make a major contribution to quantify the effect and uncertainty of global changes on U.S. air quality. The advanced state of the system components will result in a more complete scientific understanding of complex interactions among global climate and emissions and U.S. air quality across a full range of spatial and temporal scales. We will build on recent achievements of our ozone study, including a developed modeling system, viable experiment design, effective modeling strategy and objective diagnostic approach, for ozone consolidation, aerosol elaboration and mercury exploration studies for use in designing future effective emission control strategies to meet the national standards.

Future Activities:

  • Prepare consistent regional and global emission projections for 2050 and 2100
  • Conduct sensitivity experiments to study uncertainty due to emissions projection
  • Conduct sensitivity experiments to study uncertainty due to climate change projection
  • Conduct projection experiments to study impacts of global climate and emission changes
  • Diagnose outputs to quantify relative roles of global climate and emission changes
  • Conduct sensitivity experiments to study present effects of climate-aerosol interactions
  • Publish the results in peer-reviewed journal articles

Journal Articles:

No journal articles submitted with this report: View all 21 publications for this project

Supplemental Keywords:

ambient air, acid deposition, mobile sources, tropospheric, precipitation, VOC, metals, solvents, oxidants, nitrogen oxides, sulfates, organics, acid rain, effluent, discharge, environmental chemistry, hydrology, mathematics, climate models, climate change, emission, uncertainty, pollutant transport, ozone, particulate matter, mercury, aerosol, cloud, radiation, regional climate model, air quality model, RFA, Air, climate change, Air Pollution Effects, Atmosphere, air quality modeling, environmental monitoring, particulate matter

Relevant Websites:

http://www.sws.uiuc.edu/atmos/modeling/caqims/

Progress and Final Reports:

Original Abstract
  • 2008 Progress Report
  • 2009 Progress Report
  • 2010 Progress Report
  • 2011 Progress Report
  • Final Report
  • Top of Page

    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

    • Final Report
    • 2011 Progress Report
    • 2010 Progress Report
    • 2009 Progress Report
    • 2008 Progress Report
    • Original Abstract
    21 publications for this project
    21 journal articles for this project

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