Climate Change Impact on Air Quality inCaliforniaREPORT TO THECALIFORNIA AIR RESOURCES BOARDProject # 04-349Prepared by:Dr. Michael J. Kleeman1Dr. Shu-Hua Chen2Dr. Robert A. Harley31Department of Civil and Environmental Engineering2Department of Land, Air, and Water ResourcesUniversity of California, DavisOne Shields Avenue, Davis, CA, 956163Department of Civil and Environmental EngineeringUniversity of California, BerkeleyBerkeley, California 94720June 20101
DISCLAIMERThe statements and conclusions in this report are those of the contractor and notnecessarily those of the California Air Resources Board. The mention of commercialproducts, their source, or their use in connection with material reported herein is not to beconstrued as actual or implied endorsement of such products.This report was prepared by the University of California at Davis as an account of workpartially sponsored by the United States Environmental Protection Agency (USEPA).This research has not been subject to the Agency’s required peer and policy review andtherefore does not necessarily reflect the reviews of the Agency and no officialendorsement should be inferred.2
ACKNOWLEDGEMENTSWe thank Nehzat Motallebi (CARB) for project management support and for helpobtaining datasets used for statistical downscaling of ozone concentrations. We thankDan Cayan, Mary Tyree, Martha Coakley and Josh Shiffrin (UCSD) for data processingand analyses related to the downscaling of meteorological variables.We gratefully acknowledge the U.S. Department of Energy’s (DOE) Office of Science(BER) Accelerated Climate Prediction Initiative (ACPI) project for supplying globalclimate model simulations. We thank Stephen Zelinka (CARB, Sonoma Technology Inc.)for providing observation data to evaluate WRF results. Thanks also go to the NationalTyphoon and Flood Research Institute and National Central University, Taiwan, whichprovided computer clusters for part of the WRF simulations. We thank KemalGurer(CARB) and Dr. Jian-Wen Bao (NOAA) for help in the early stage of the WRFdownscaling.The work described in this report was primarily accomplished by UC Davis graduatestudents Abdullah Mahmud, Mark Hixson, and Zhan Zhao and UC Berkeley graduatestudent Dev Millstein. Additional help was provided by UC Davis graduate studentJianlin Hu and UC Davis postdoctoral scholar James Chen.3
TABLE OF CONTENTSACKNOWLEDGEMENTS. 3LIST OF TABLES. 7LIST OF FIGURES . 9LIST OF ACRONYMS . 18ABSTRACT. 21EXECUTIVE SUMMARY . 221.0 INTRODUCTION . 291.1 Motivation. 291.2 Previous Analysis for Climate Effects on Air Quality in California . 291.3 Research Objectives. 311.4 Scope of the Current Study. 332.0 A PRELIMINARY ASSESSMENT OF THE SENSITVITY OF AIR QUALITY INCALIFORNIA TO GLOBAL CHANGE . 352.1 Introduction. 352.2 Background. 352.3 Model Description . 362.4 Model Application . 372.5 Results. 392.6 Discussion. 542.7 Conclusions. 563.0 IMPACT OF CLIMATE CHANGE ON PHOTOCHEMICAL AIR POLLUTION INSOUTHERN CALIFORNIA . 573.1 Introduction. 573.2 Methods . 583.3 Results and Discussion . 623.3.1 Base Case Model Evaluation . 623.3.2 Effects of Climate Change . 643.3.3 Effects of Emission and Inflow Boundary Condition Changes . 663.3.4 Combined Effects . 673.3.5 Temporal Patterns of Ozone Change. 693.3.6 Future Temperature Change. 713.4 Summary and Recommendations . 744.0 STATISTICAL DOWNSCALING OF CLIMATE CHANGE IMPACTS ONOZONE CONCENTRATIONS IN CALIFORNIA . 754.1 Introduction. 754.2 Data and Methods . 764.3 Results. 774.4 Conclusion . 955.0 THE IMPACT OF CLIMATE CHANGE ON AIR QUALITY RELATEDMETEOROLOGICAL CONDITIONS IN CALIFORNIA – PART I: PRESENT TIMESIMULATION ANALYSIS. 965.1 Introduction. 965.2 Methodology and Model Description . 985.2.1 Methodology . 985.2.2 PCM model . 994
5.2.3 WRF model and the interface between WPS and PCM . 995.2.4 WRF basic configuration . 1005.3 Tests of different physics schemes in WRF. 1015.3.1 Numerical experiments design . 1015.3.2 Results analysis . 1025.4 Downscaling Results Analysis. 1045.4.1 Downscaling results driven by PCM vs. GFS data. 1045.4.2 Surface comparison between simulation results and observation data. 1105.4.3. Low PBLH during summer . 1165.5 Conclusions. 1216.0 THE IMPACT OF CLIMATE CHANGE ON AIR QUALITY RELATEDMETEOROLOGICAL CONDITIONS IN CALIFORNIA – PART II: PRESENTVERSUS FUTURE TIME SIMULATION ANALYSIS . 1236.1 Introduction. 1236.2 Model configurations and methodology . 1246.3 Results. 1256.3.1. Stagnation Event Analysis. 1256.3.2. Future changes of air quality related meteorological fields . 1276.3.3 Climate change impacts on land-sea breeze . 1346.3.4 Significance Test . 1386.4 Conclusions. 1407.0 CLIMATE IMPACT ON AIRBORNE PARTICULATE MATTERCONCENTRATIONS IN CALIFORNIA USING SEVEN YEAR ANALYSISPERIODS. 1417.1 Introduction. 1417.2 Methods . 1427.3 Results. 1487.4 Summary and Conclusions . 1628.0 CLIMATE IMPACT ON POPULATION-WEIGHTED AIRBORNEPARTICULATE MATTER CONCENTRATIONS IN CALIFORNIA DURING SHORTAND LONG TIME PERIODS . 1648.1 Introduction. 1648.2 Methods . 1658.3 Results and discussion . 1678.3.1 Annual Average PM Concentrations . 1678.3.2 Extreme Events. 1738.4 Conclusions. 1799.0 CLIMATE IMPACT ON PARTICULATE MATTER (PM) IN CALIFORNIA FOREMISSIONS PROJECTED IN 2050 . 1809.1 Introduction. 1809.2 Emissions Projections . 1809.3 Results. 1829.4 Conclusions. 19810.0 COMBINED IMPACT OF CLIMATE CHANGE AND EMISSIONS CONTROLSON PARTICULATE MATTER (PM) IN CALIFORNIA . 19910.1 Introduction. 1995
10.2 Methods . 19910.3 Results. 20010.4 Conclusions. 20911.0 SUMMARY AND CONCLUSIONS . 21011.1 A Preliminary Assessment of the Sensitivity of Air Quality in California toGlobal Change . 21011.2 Impact of Climate Change on Photochemical Air Pollution in Southern California. 21011.3 Statistical Downscaling of Climate Change Impacts on Ozone Concentrations inCalifornia . 21111.4 The Impact of Climate Change on Air Quality Related Meteorological Conditionsin California – Part I: Present Time Simulation Analysis . 21211.5 The Impact of Climate Change on Air Quality Related Meteorological Conditionsin California – Part II: Present versus Future Time Simulation Analysis . 21211.6 Climate Impact on Airborne Particulate Matter Concentrations in CaliforniaUsing Seven Year Analysis Periods . 21311.7 Climate Impact on Population-Weighted Airborne Particulate MatterConcentrations in California during Short and Long Time Periods . 21311.8 Climate Impact on Particulate Matter (PM) in California for Emissions Projectedin 2050 . 21411.9 Combined Impact of Climate Change and Emissions Controls on ParticulateMatter in California . 21511.10 Future research. 215Reference . 2176
LIST OF TABLESTable 2-1: Lateral boundary conditions used during model simulations. 37Table 2-2: Air quality episodes to be studied with sensitivity analysis. 38Table 2-3: Emissions summary for the air quality episodes described in Table 2-2. . 38Table 2-4: Relative change in composition for O3, hydroxyl radical (OH), totalreactive nitrogen (RN), and various forms of reactive nitrogen at 1500 PST onSeptember 9, 1993 caused by a 5 K temperature perturbation. PN is particulatenitrate. . 41Table 2-5: Relative change in composition for O3, hydroxyl radical (OH), totalreactive nitrogen (RN), and various forms of reactive nitrogen at 1500 PST onSeptember 25, 1996 caused by a 5K temperature perturbation. PN is particulatenitrate. . 41Table 2-6: Relative change in composition for O3, hydroxyl radical (OH), totalreactive nitrogen (RN), and various forms of reactive nitrogen at 1500 PST onJanuary 6, 1996 caused by a 5K temperature perturbation. PN is particulate nitrate. 41Table 3-1: Domain-wide emission totals (tons/day) . 59Table 3-2: AVOC, BVOC and NOx, base case and future emissions by county.Emissions are reported in tons/day for Thursday July 14th. . 61Table 3-3: Average weekday ozone (ppb) at 1500 h LT (local time): base case levelsand differences between specified run and base case . 68Table 3-4: Average weekday 8-h ozone (ppb) at 1000 h – 1800 h LT (local time):base case levels and differences between specified run and base case. . 68Table 4-1: Variables that were perturbed during the Monte Carlo simulations of ozoneformation. . 82Table 4-2: Temperature (T850) increase (oC) in 2070-2099 relative to 1961-1990projected for the SoCAB and SJAB by various climate models under the IPCC A2and B1 emissions scenario. . 90Table 4-3: Summary of predicted decadal median daily 1-hr maximum ozoneconcentrations under IPCC A2 and B1 global emissions scenarios at Upland(SoCAB) and Parlier (SJVAB). Note that the underlying assumption for thisprediction is that the emissions in CA remain at the 1990-2004 level. . 94Table 5-1: Simulation cases for normal and leap years. . 99Table 5-2. Six suites of physics schemes for WRF simulations . 101Table 7-1: Domain-averaged initial concentrations of major model gas and particlespecies at the surface. 145Table 7-2: Average boundary concentrations of various model gas and particlespecies concentrations along the western boundary of the modeling domain. . 1467
Table 9-1: County-specific growth factors between 2029/2030 and 2050 based onDepartment of Finance population projections. . 1828
LIST OF FIGURESFigure 1: Average weekday ozone (ppb) at 1500 h LT (local time) for a SoCABepisode in 2005: base case levels and differences between specified run and basecase. . 23Figure 3: The number of days per year conducive to forming 1-hr maximum ozone of90 ppb or more at Upland, CA under the Intergovernmental Panel on Climate Change(IPCC) emissions scenarios: A2 (top panel) and B1 (bottom panel). Note that theunderlying assumption for this prediction is that the criteria emissions in CA remainat the 1990-2004 level. Uncertainty bars represent the third and the first quartiles ofthe predicted number of days. . 25Figure 4: Changes in annual average PM2.5 mass concentrations and corresponding pvalues in CA likely to occur in the future (2047-53) due to climate change from thepresent-day (2000-06). The p-value quantifies the likelihood that average futureconcentrations are equal to present day concentrations. . 26Figure 5: Future (2047-53) minus present (2000-06) change in population-weightedPM2.5 total mass, components, and primary source categories for (a) annual averagesand (b) 99th percentile extreme pollution events. Results are averaged across theentire state of California. The error bars represent the 95% confidence interval. . 27Figure 2-1: Basecase O3 concentration at 1500 PST on September 9, 1993 (panel a)and sensitivity of O3 concentration to (b) 5 K temper
Climate Change Impact on Air Quality in California REPORT TO THE CALIFORNIA AIR RESOURCES BOARD . Project # 04-349 . Prepared by: Dr. Michael J. Kleeman1 . Dr. Shu-Hua Chen. 2 . Dr. Robert A. Harley. 3 1. Department of Civil and Environmental Engineering . 2. Department of Land, Air, and Water Resources University of California, Davis
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