Boundary-Layer Meteorology

, Volume 127, Issue 2, pp 219–239 | Cite as

Urban Surface Modification as a Potential Ozone Air-quality Improvement Strategy in California: A Mesoscale Modelling Study

Original Paper

Abstract

Two of several surface modification (heat-island reduction) strategies, increased surface albedo and urban reforestation, are evaluated via mesoscale meteorological and photochemical modelling of regulatory episodes in central and southern California. The simulations suggest that these strategies can have beneficial impacts on air quality, with increased albedo being relatively more effective than urban reforestation. The simulations also show that air quality indices, such as regional 1-h peaks, area peaks, 8-h relative reduction factors, 24-h averages, etc., improve for both central and southern California and that for the range of strategies evaluated here, the improvements in air quality can be significant. The simulations of southern California suggest that there may be a threshold beyond which further surface modifications tend to produce smaller net improvements in ozone air quality.

Keywords

Air quality Meteorological modelling Photochemical modelling Surface modifications Urban heat islands 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arya SP (1998) Introduction to micrometeorology. International Geophysics Series, vol 42. Academic Press, San Diego, 307 ppGoogle Scholar
  2. Bloch L, Winer A (1994) Estimation of hydrocarbon emission from trees using phylogenetic relationships. In: Taha H et al. (eds) Ch. 9 in Analysis of Energy Efficiency and Air Quality in the SoCAB – Phase II. Lawrence Berkeley National Laboratory Report No. 35728, Berkeley, CaliforniaGoogle Scholar
  3. Benjamin MT, Sudol M, Bloch L, Winer AM (1996) Low-emitting urban forest: a taxonomic methodology for assigning isoprene and monoterpene emission rates. Atmos Environ 30: 1437–1452CrossRefGoogle Scholar
  4. Dudhia J (1993) A non-hydrostatic version of the Penn State/NCAR mesoscale model: validation tests and simulation of an Atlantic cyclone and cold front. Mon Wea Rev 121: 1493–1513CrossRefGoogle Scholar
  5. Emery C, Tai E, Yarwood G (2001) Enhanced meteorological modelling and performance evaluation for two Texas ozone episodes. Report prepared for the Texas Natural Resources Conservation Commission by Environ International Corp., Novato, CaliforniaGoogle Scholar
  6. Environ Corp (2004) Comprehensive Air Quality Model with Extensions Version 4. Environ Corp., Novato, CaliforniaGoogle Scholar
  7. EPA (1991) Guidelines for regulatory application of the Urban Airshed Model. U.S. Environmental Protection Agency Report EPA-450/4-91-013. Office of Air Quality Planning and Standards, RTP, North CarolinaGoogle Scholar
  8. EPA (1996) Air quality criteria for ozone and related photochemical oxidants. Report EPA-600-P93-004aF, US EPA ORD. National Center for Environmental Assessment, Washington, DCGoogle Scholar
  9. Gery MW, Whitten GZ, Killus JP (1988) Development and testing of the CBM-IV for urban and regional modelling. Report EPA-600/3-88-012. U.S. EPA, Research Triangle Park, North CarolinaGoogle Scholar
  10. Grell GA, Dudhia J, Stauffer DR (1994) A description of the fifth generation PSU/NCAR mesoscale modelling system (MM5). Technical Note NCAR/TN—379+STR, National Center for Atmospheric Research, Boulder, ColoradoGoogle Scholar
  11. Guenther A, Baugh B, Brasseur G et al (1999) Isoprene emission estimates and uncertainties for the Central African EXPRESSO study domain. J Geophys Res 104: 30625–30639CrossRefGoogle Scholar
  12. Guenther AB, Fall R, Zimmerman PR et al (1993) Isoprene and monoterpene emission rate variability: model evaluations and sensitivity analyses. J Geophys Res 98: 12609–12617CrossRefGoogle Scholar
  13. Hong SH, Pan HL (1996) Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon Wea Rev 124: 2322–2339CrossRefGoogle Scholar
  14. Kistler R, Kalnay E, Collins W et al (2001) The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation. Bull Am Meteorol Soc 82: 247–267CrossRefGoogle Scholar
  15. Lehrman D, Knuth B, Fairley D (2001) Characterization of the CCOS 2000 measurement period. Interim Report (Contract 01-2CCOS) available from the California Air Resources Board, Sacramento, CaliforniaGoogle Scholar
  16. Levinson R, Berdahl PH, Akbari H (2005) Spectral solar optical properties of pigments, Part I: model for deriving scattering and absorption coefficients from transmittance and reflectance measurements. Solar Energy Mater Solar Cells. doi: 10.1016/j.solmat.2004.11.012 Google Scholar
  17. Mao Q, Gautney LL, Cook TM et al (2006) Numerical experiments on MM5-CMAQ sensitivity to various PBL schemes. Atmos Environ 40: 3092–3110CrossRefGoogle Scholar
  18. O’Brien JJ (1970) A note on the vertical structure of the eddy exchange coefficient in the planetary boundary layer. J Atmos Sci 27: 1213–1215CrossRefGoogle Scholar
  19. Pielke RA (1984) A three-dimensional numerical model of the sea breeze over South Florida. Mon Wea Rev 102: 115–139CrossRefGoogle Scholar
  20. Pielke RA (2002) Mesoscale Meteorological Modelling, International Geophysics Series, vol 78. Academic Press, San Diego, 676 ppGoogle Scholar
  21. SCAQMD (2003) Air Quality Management Plan 2003. South Coast Air Quality Management District, Diamond Bar, CaliforniaGoogle Scholar
  22. Seaman NL, Stauffer DR (1996) SARMAP meteorological model. Final Report prepared for the San Joaquin Valleywide Air Pollution Study Agency, Department of Meteorology, Pennsylvania State University, University Park, PAGoogle Scholar
  23. Seaman NL, Stauffer DR, Lario-Gibbs AM (1995) A multi-scale four dimensional data assimilation system applied in the San Joaquin Valley during SARMAP: Part I: modelling design and basic performance characteristics. J Appl Meteorol 34: 1739–1761CrossRefGoogle Scholar
  24. Steiner A, Tonse S, Cohen R, Goldstein A, Harley R (2006) Influence of future climate and emissions on regional air quality in California. J Geophys Res (Atmospheres) 111: D18303. doi: 10.1029/2005JD006935 CrossRefGoogle Scholar
  25. Taha H (1996) Modelling the impacts of increased urban vegetation on the ozone air quality in the south coast air basin. Atmos Environ 30: 3423–3430CrossRefGoogle Scholar
  26. Taha H (1997) Modelling the impacts of large-scale albedo changes on ozone air quality in the south coast air basin. Atmos Environ 31: 1667–1676CrossRefGoogle Scholar
  27. Taha H (1999) Modifying a mesoscale meteorological model to better incorporate urban heat storage: a bulk-parameterization approach. J Appl Meteorol 38: 466–473CrossRefGoogle Scholar
  28. Taha H (2005) Surface modifications as a potential ozone air-quality improvement strategy in California: Part I: mesoscale modelling. Final report prepared for the California Energy Commission, Altostratus Inc. Available from the Energy’ Commission’s website at: http://www.energy.ca.gov/2005publications/CEC-500-2005-128/CEC-500-2005-128.PDF
  29. Taha H (2007) Urban heat islands and their mitigation vs. local impacts of climate change. Presented at the 4th California Climate Change Conference, September 10–13 2007, Sacramento, California (available from author and from the California Energy Commission’s web site)Google Scholar
  30. Taha H (2008) Episodic performance and sensitivity of the urbanized MM5 (uMM5) to perturbations in surface properties in Houston TX. Boundary-Layer Meteorol. doi: 10.1007/s10546-007-9258-6 Google Scholar
  31. Taha H, Chang SC, Akbari H (2000) Meteorological and air-quality impacts of heat island mitigation in three U.S. cities. Lawrence Berkeley National Laboratory Report No. 44222, Berkeley, CaliforniaGoogle Scholar
  32. Tesche TW, McNAlly DE, Emery CA et al (2001) Evaluation of the MM5 model over the Midwestern U.S. for three 8-hour oxidant episodes. Prepared for the Kansas City Ozone Technical Workgroup by Alpine Geophysics LLC and Environ International CorpGoogle Scholar
  33. United States Geological Survey (1990) Cartographic projection procedures for the Unix Environment. USGS Report 90–284Google Scholar
  34. Zhou L, Dickinson RE, Tian Y et al (2003) Comparison of seasonal and spatial variations of albedos from moderate-resolution imaging spectroradiometer (MODIS) and Common Land Model. J Geophys Res 108:D15 4488. doi: 10.1029/2002JD003326

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Altostratus Inc.MartinezUSA

Personalised recommendations