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Estimating influences of urbanizations on meteorology and air quality of a Central Business District in Shanghai, China

  • Wenjing Zhan
  • Yan ZhangEmail author
  • Weichun Ma
  • Qi Yu
  • Limin Chen
Original Paper

Abstract

Two sensitivity simulations were performed and compared by model in order to understand how high-rise buildings influence meteorology and air quality in the Lujiazui Central Business District (CBD) of Shanghai, China. The coupled meteorological-photochemical model, Metphomod, was used, with a 500-m horizontal resolution and the observations and the simulated results generally agreed well. The scheme considering buildings within roughness could reduce uncertainties in the simulated meteorological conditions and concentrations of air pollutants. The high-rise buildings decreased wind speeds by 0.5–4 m/s, increased temperatures by up to 1 °C and turbulent kinetic energy by 1–2 J/m3 in the Lujiazui CBD. The changes in meteorological conditions also increased NO by about 2–5 %. However, the complex meteorological changes of higher temperatures and stronger turbulent kinetic energy, coupled with changes of precursors’ concentrations in the Lujiazui CBD, decreased O3 concentrations by up to 6 % somewhere, while increasing O3 formation by up to 2 % in downwind areas. The results suggested that it was necessary to include high-rise building parameters in models when estimating the meteorology and diagnosing air pollution of highly urbanized regions.

Keywords

High-rise buildings Uncertainty in modeling Meteorology Air quality Urban 

Abbreviations

API

Air Pollution Index

BEIS

Biogenic Emissions Inventory System

CBD

Central Business District

COPERT III

COmputer Programme to calculate Emissions from Road Transport III

GIS

Geographic Information System

GMT

Greenwich Mean Time

Metphomod

METeorological PHOtochemical coupled MODel

MM5

Fifth-Generation Penn State/NCAR Mesoscale Model

NCEP

National Center for Environmental Prediction

NMVOC

Non-Methane Volatile Organic Compounds

PAR

Photosynthetically Active Radiation

ppm

Parts Per Billion

RMSE

Root Mean Square Error

TKE

Turbulent Kinetic Energy

VOC

Volatile Organic Compounds

WRF

Weather Research and Forecasting model

Notes

Acknowledgments

This work was supported by the Foundation for new teacher by Ministry of Education (Grant Nos. 2008024610) and National Natural Science Foundation of China (Grant Nos. 41005076). Thanks for helps of Professor Rahn from University of Rohde Island in English language and grammar.

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Wenjing Zhan
    • 1
  • Yan Zhang
    • 1
    Email author
  • Weichun Ma
    • 1
  • Qi Yu
    • 1
  • Limin Chen
    • 1
  1. 1.Department of Environmental Science and EngineeringFudan UniversityShanghaiChina

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