期刊文献+

Characteristics of ventilation coefficient and its impact on urban air pollution 被引量:1

Characteristics of ventilation coefficient and its impact on urban air pollution
下载PDF
导出
摘要 The temporal variation of ventilation coefficient was estimated and a simple model for the prediction of urban ventilation coefficient in Changsha was developed. Firstly, Pearson correlation analysis was used to investigate the relationship between meteorological parameters and mixing layer height during 2005-2009 in Changsha, China. Secondly, the multi-linear regression model between daytime and nighttime was adopted to predict the temporal ventilation coefficient. Thirdly, the validation of the model between the predicted and observed ventilation coefficient in 2010 was conducted. The results showed that ventilation coefficient significantly varied and remained high during daytime, while it stayed relatively constant and low during nighttime. In addition, the diurnal ventilation coefficient was distinctly negatively correlated with PM10 (particle with the diameter less than 10 μm) concentration in Changsha, China. The predicted ventilation coefficient agreed well with the observed values based on the multi-linear regression models during daytime and nighttime. The urban temporal ventilation coefficient could be accurately predicted by some simple meteorological parameters during daytime and nighttime. The ventilation coefficient played an important role in the PM10 concentration level. The temporal variation of ventilation coefficient was estimated and a simple model for the prediction of urban ventilation coefficient in Changsha was developed. Firstly, Pearson correlation analysis was used to investigate the relationship between meteorological parameters and mixing layer height during 2005-2009 in Changsha, China. Secondly, the multi-linear regression model between daytime and nighttime was adopted to predict the temporal ventilation coefficient. Thirdly, the validation of the model between the predicted and observed ventilation coefficient in 2010 was conducted. The results showed that ventilation coefficient significantly varied and remained high during daytime, while it stayed relatively constant and low during nighttime. In addition, the diurnal ventilation coefficient was distinctly negatively correlated with PM10 (particle with the diameter less than 10 ~m) concentration in Changsha, China. The predicted ventilation coefficient agreed well with the observed values based on the multi-linear regression models during daytime and nighttime. The urban temporal ventilation coefficient could be accurately predicted by some simple meteorological parameters during daytime and nighttime. The ventilation coefficient played an important role in the PM10 concentration level.
出处 《Journal of Central South University》 SCIE EI CAS 2012年第3期615-622,共8页 中南大学学报(英文版)
基金 Project(51178466) supported by the National Natural Science Foundation of China Project(FANEDD200545) supported by Foundation for the Author of National Excellent Doctoral Dissertation of China Project(2011JQ006) supported by Fundamental Research Funds of the Central Universities of China
关键词 ventilation coefficient mixing layer height particulate matter multi-linear regression 城市空气污染 通风系数 多元线性回归模型 可吸入颗粒物 模型预测 特征 气象参数 浓度水平
  • 相关文献

参考文献20

  • 1SUN Ye-le, ZHUANG Guo-shun, TANG Ao-han, WANG Ying, AN Zhi-sheng. Chemical characteristics of PM2.s and PMl0 in Haze-Fog episodes in Beijing [J]. Environmental Science and Technology, 2006, 40(10): 3148-3155.
  • 2AKPINAR S, HAKAN F O, AKPINAR E K. Evaluation of relationship between meteorological parameters and air pollutant concentrations during winter season in Elazlg, Turkey [J]. Environmental Monitoring and Assessment, 2007, 146(1/2/3): 211-224.
  • 3EMEIS S, SCHAFER K, MUNKEL C. Surface-based remote sensing of the mixing-layer height-A review [J]. Meteorologische Zeitschrift, 2008, 17(5): 621-630.
  • 4SCHAFER K, EMERIS S, HOFFMANN H, JAHN C. Influence of mixing layer height upon air pollution in urban and sub-urban areas [J]. Meteorologische Zeitschrift, 2006, 15(6): 647-658.
  • 5GHIAUS C, ALLARD F, SANTAMOURIS M, GEORGAKIS C, NICO E Urban environment influence on natural ventilation potential [J]. Building and Environment, 2006, 41(4): 395-406.
  • 6MOTESADDI Z S, KHAJEVANDI M, DAMEZ F D, ARDESTANI M. Determination of air pollution monitoring stations [J]. International Journal of Environmental Research, 2008, 2(3): 313-318.
  • 7GOYAL S K, CHALAPATI R C V. Assessment of atmospheric assimilation potential for industrial development in an urban environment: Kochi (India) [J]. Science of the Total Environment, 2007, 376 (1/2/3): 27-39.
  • 8MARIA I C~ NICOLAS A M. Air pollution potential: Regional study in Argentina [J]. Environmental Management, 2000, 25(4): 375-382.
  • 9RIGBY M, TIMMIS R, TOUMI R. Similarities of boundary layer ventilation and particulate matter roses [J]. Atmospheric Environment, 2006, 40(27): 5112-5124.
  • 10HOLZWORTH G C. Mixing depths, wind speed and air pollution potential for selected locations in the United States [J]. Journal of Applied Meteorology, 1967, 6(6): 1039-1044.

同被引文献14

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部