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

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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.

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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

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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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Authors and Affiliations

  1. Department of Environmental Science and Engineering, Fudan University, Shanghai, China

    Wenjing Zhan, Yan Zhang, Weichun Ma, Qi Yu & Limin Chen

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  1. Wenjing Zhan
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  2. Yan Zhang
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  3. Weichun Ma
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  4. Qi Yu
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  5. Limin Chen
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Correspondence to Yan Zhang.

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Zhan, W., Zhang, Y., Ma, W. et al. Estimating influences of urbanizations on meteorology and air quality of a Central Business District in Shanghai, China. Stoch Environ Res Risk Assess 27, 353–365 (2013). https://doi.org/10.1007/s00477-012-0603-z

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