Grantee Research Project Results
Final Report: Study the Impact of Global Change on Air Quality Using the Global-Through-Urban Weather Research and Forecast Model with Chemistry
EPA Grant Number: R833376Title: Study the Impact of Global Change on Air Quality Using the Global-Through-Urban Weather Research and Forecast Model with Chemistry
Investigators: Zhang, Yang , Streets, David G. , Karamchandani, Prakash
Institution: North Carolina State University , Atmospheric and Environmental Research, Inc. , Argonne National Laboratory
Current Institution: North Carolina State University , Argonne National Laboratory , Atmospheric and Environmental Research, Inc.
EPA Project Officer: Chung, Serena
Project Period: May 7, 2007 through May 6, 2011 (Extended to May 6, 2012)
Project Amount: $900,000
RFA: Consequences of Global Change For Air Quality (2006) RFA Text | Recipients Lists
Research Category: Climate Change , Air
Objective:
The objectives of this project were to estimate the long-term impacts of global changes on urban and regional air quality over the next 50 years and provide a realistic assessment of those impacts and associated uncertainties using an advanced 3-D model and available observational datasets. We hypothesized that the two-way feedbacks between climate changes and air quality are important in quantifying the impact of global changes on air quality.
Summary/Accomplishments (Outputs/Outcomes):
During this project period, we accomplished major tasks in model development, applications, and evaluations that were critical to achieve our goals. We compiled global emissions based on existing global emission inventories and the latest regional emission inventories in the United States, Canada, and East Asia. We improved mesoscale Weather Research and Forecasting (WRF)/Chem model and developed GU-WRF/Chem based on the National Center for Atmospheric Research's (NCAR) GWRF (gLite-based WRF) and improved mesoscale WRF/Chem. We applied GU-WRF/Chem to various regional domains in North America, Europe, and Asia and global-through-urban nested domains for comprehensive model evaluation using both satellite and ground-base measurements provided from our collaborators in the United States, Europe, and Asia as well as those available from public web sites. We applied GU-WRF/Chem for two current years (2001 and 2010) and four future-year simulations (2020, 2030, 2040, and 2050) to characterize the variation trends in climate, air quality, and their interactions under future emission/climate scenarios and examined aerosol direct/semi-direct and indirect effects. We also conducted several sensitivity simulations to study the variation trends of the intercontinental transport of Asian pollutants in a changing climate and the relative importance of aerosol direct/semi-direct and indirect effects. These results are presented in 10 journal publications, 3 papers that are in review, and 8 papers that are in preparation. Our major findings and their significances are summarized below.
Conclusions:
Our major findings and their scientific significances and policy implications in this project are:
- Mesoscale WRF/Chem has been further developed and improved in terms of gas-phase chemistry, aerosol treatments, and aerosol-cloud interactions. GU-WRF/Chem has been developed based on GWRF and improved mesoscale WRF/Chem for global-through-urban applications.
- Application and evaluation of mesoscale WRF/Chem on various regional testbeds including CONUS and subdomains, Mexico City, East Asia, and Europe demonstrate the capability of WRF/Chem in reproducing observations and forecasting air quality. Application of evaluation of GU-WRF/Chem over global and nested regional and urban domains for current year emissions and climate scenarios show better or comparable performance than various versions of mesoscale WRF/Chem due mainly to improved model treatments and configurations. Large biases in mesoscale and GU-WRF/Chem model predictions of some species or variables can be explained by uncertainties in emissions and model treatments. Although GU-WRF/Chem is not a climate model, the intercomparison of the meteorological and chemical predictions of GU-WRF/Chem under future year emission/climate scenarios are comparable to those projected by NCAR’s Community Climate System Model (CCSM).
- Sensitivity simulations using mesoscale WRF/Chem and GU-WRF/Chem show moderate to high sensitivity of model predictions to model treatments including different gas-phase mechanisms, different aerosol modules, different nucleation parameterizations, and different aerosol-cloud interaction schemes. Such sensitivity can contribute to uncertainties in the model estimate of aerosol number concentrations, aerosol optical depth (AOD), cloud optical depths (COT), cloud condensation nuclei (CCN), cloud drooplet number concentration (CDNC), precipitation and other meteorological variables through aerosol direct, semi-direct, and indirect effects.
- Applications of GU-WRF/Chem under current and future year emission/climate scenarios show warmer and drier weather in the future. The changes in future O3 and PM2.5 concentrations depend on changed climate conditions and subsequent changes in biogenic volatile organic compound (BVOC) emissions, as well as projected anthropogenic emissions of their precursors. In response to changes in climate and emissions, the surface-level concentrations of O3 are predicted to increase over most of regions in all seasons and those of PM2.5 are predicted to either decrease or increase, depending on regions and seasons. Those changes lead to an increase in AOD, CCN, and CDNC in most areas.
- East Asian anthropogenic emissions (EAAEs) contribute to 1.2 and ~2 ppb of the surface maximum 8-hr average O3 mixing ratio on a global average under the current and future emission/climate scenarios, respectively. The increase in their contributions to surface O3 mixing ratios in 2050 results from the projected increases in the emissions of O3 precursors and temperatures at 2-m, as well as changed flow patterns. The impact on PM2.5 especially in the PBL is not homogenous as the removal of EAAEs alters the wind speed and PBL height through cloud and radiative feedbacks, but EAAEs contribute 0.3-0.4 μ m-3 to the global average PM2.5 concentration under both scenarios. In addition, EAAEs of aerosol and greenhouse gases affect climate, particularly over East Asia and the North Pacific, where they have a strong impact on CDNC, AOD, COT, and thus the amount of incoming solar radiation reaching the surface. These results show that EAAEs have a large impact on global air quality and climate, especially on downwind regions, demonstrating a need to synergize global emissions control efforts.
- Aerosol indirect effects dominate over aerosol direct and semi-direct effects in influencing the changes in the mixing ratios of gaseous pollutants such as max 8-h O3 mixing ratios and meteorological variables such as incoming shortwave radiation, AOD, COT, CCN, CDNC, and precipitation under both current and future emission/climate scenarios. This indicates the importance of reducing uncertainties in estimating aerosol indirect effects.
Journal Articles on this Report : 20 Displayed | Download in RIS Format
Other project views: | All 124 publications | 22 publications in selected types | All 20 journal articles |
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Chuang M-T, Zhang Y, Kang D. Application of WRF/Chem-MADRID for real-time air quality forecasting over the Southeastern United States. Atmospheric Environment 2011;45(34):6241-6250. |
R833376 (2010) R833376 (Final) |
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Glotfelty T, Zhang Y, Karamchandani P, Streets DG. Will the role of intercontinental transport change in a changing climate? Atmospheric Chemistry and Physics 2014;14(17):9379-9402. |
R833376 (Final) |
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Karamchandani P, Zhang Y, Chen S-Y. Development and initial application of a sub-grid scale plume treatment in a state-of-the-art online Multi-scale Air Quality and Weather Prediction Model. Atmospheric Environment 2012;63:125-134. |
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Karamchandani P, Zhang Y, Chen S-Y, Balmori-Bronson R. Development of an extended chemical mechanism for global-through-urban applications. Atmospheric Pollution Research 2012;3(1):1-24. |
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Li M, Zhang Q, Streets DG, He KB, Cheng YF, Emmons LK, Huo H, Kang SC, Lu Z, Shao M, Su H, Yu X, Zhang Y. Mapping Asian anthropogenic emissions of non-methane volatile organic compounds to multiple chemical mechanisms. Atmospheric Chemistry and Physics 2014;14(11):5617-5638. |
R833376 (Final) |
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Misenis C, Zhang Y. An examination of sensitivity of WRF/Chem predictions to physical parameterizations, horizontal grid spacing, and nesting options. Atmospheric Research 2010;97(3):315-334. |
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Wang K, Zhang Y, Nenes A, Fountoukis C. Implementation of dust emission and chemistry into the Community Multiscale Air Quality modeling system and initial application to an Asian dust storm episode. Atmospheric Chemistry and Physics 2012;12(21):10209-10237. |
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Wang K, Zhang Y, Yahya K, Wu S-Y, Grell G. Implementation and initial application of new chemistry-aerosol options in WRF/Chem for simulating secondary organic aerosols and aerosol indirect effects for regional air quality. Atmospheric Environment 2015;115:716-732. |
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Yahya K, Zhang Y, Vukovich JM. Real-time air quality forecasting over the southeastern United States using WRF/Chem-MADRID:Multiple-year assessment and sensitivity studies. Atmospheric Environment 2014;92:318-338. |
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Zhang Y. Online-coupled meteorology and chemistry models: history, current status, and outlook. Atmospheric Chemistry and Physics 2008;8(11):2895-2932. |
R833376 (2007) R833376 (Final) |
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Zhang Y, Pan Y, Wang K, Fast JD, Grell GA. WRF/Chem-MADRID: incorporation of an aerosol module into WRF/Chem and its initial application to the TexAQS2000 episode. Journal of Geophysical Research 2010;115(D18):D18202 (32 pp.) |
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Zhang Y, Wen X-Y, Jang CJ. Simulating chemistry–aerosol–cloud–radiation–climate feedbacks over the continental U.S. using the online-coupled Weather Research Forecasting Model with Chemistry (WRF/Chem). Atmospheric Environment 2010;44(29):3568-3582. |
R833376 (2009) R833376 (2010) R833376 (Final) |
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Zhang Y, Bocquet M, Mallet V, Seigneur C, Baklanov A. Real-time air quality forecasting, Part I: History, techniques, and current status. Atmospheric Environment 2012;60:632-655. |
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Zhang Y, Bocquet M, Mallet V, Seigneur C, Baklanov A. Real-time air quality forecasting, Part II: State of the science, current research needs, and future prospects. Atmospheric Environment 2012;60:656-676. |
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Zhang Y, Chen Y, Sarwar G, Schere K. Impact of gas-phase mechanisms on Weather Research Forecasting Model with Chemistry (WRF/Chem) predictions: mechanism implementation and comparative evaluation. Journal of Geophysical Research-Atmospheres 2012;117(D1):D01301 (31 pp.) |
R833376 (2010) R833376 (Final) |
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Zhang Y, Hemperly J, Meskhidze N, Skamarock WC. The Global Weather Research and Forecasting (GWRF) model:model evaluation, sensitivity study, and future year simulation. Atmospheric and Climate Sciences 2012;2(3):231-253. |
R833376 (Final) |
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Zhang Y, Karamchandani P, Glotfelty T, Streets DG, Grell G, Nenes A, Yu F, Bennartz R. Development and initial application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem). Journal of Geophysical Research-Atmospheres 2012;117(D20):D20206 (33 pp.). |
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Zhang Y, Sartelet K, Wu S-Y, Seigneur C. Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description, evaluation of meteorological predictions, and aerosol-meteorology interactions. Atmospheric Chemistry and Physics 2013;13(14):6807-6843. |
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Zhang Y, Sartelet K, Zhu S, Wang W, Wu S-Y, Zhang X, Wang K, Tran P, Seigneur C, Wang Z-F. Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 2: Evaluation of chemical concentrations and sensitivity simulations. Atmospheric Chemistry and Physics 2013;13(14):6845-6875. |
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Zhang Y, He J, Zhu S, Gantt B. Sensitivity of simulated chemical concentrations and aerosol-meteorology interactions to aerosol treatments and biogenic organic emissions in WRF/Chem. Journal of Geophysical Research-Atmospheres 2016;121(10):6014-6048. |
R833376 (Final) |
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Supplemental Keywords:
global-through-urban WRF/Chem, air quality modeling, climate modeling, coupled meteorology and air quality, aerosols, air quality-climate change feedbacks, RFA, Air, climate change, Air Pollution Effects, Atmosphere, air quality modelingRelevant Websites:
http://www.meas.ncsu.edu/aqforecasting/ (research and resulted publications are disseminated via the web site of Zhang’s group)Progress and Final Reports:
Original AbstractThe 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
- 2010 Progress Report
- 2009 Progress Report
- 2008 Progress Report
- 2007 Progress Report
- Original Abstract
20 journal articles for this project