Estimation of the Spatio-Temporal Characteristics of Anthropogenic Heat Emission in the Qinhuai District of Nanjing Using the Inventory Survey Method

Abstract

Taking the Qinhuai District of Nanjing, China, as the study area, this research adopted the bottom-up energy inventory method to estimate the anthropogenic heat emission at the spatial resolution of 100 m during the daytime and nighttime. Land use data derived by the visual interpretation from high resolution imagery was combined with the field investigation as well as statistical population data to estimate the spatial distribution of the population, which was then used to calculate the human metabolism. The traffic heat emission estimation was mainly based on the interpretation of different levels of roads and the statistical vehicle volume from field video recordings. The spatialized population, the collected energy consumption statistical data, the corresponding function and the number of floors in the buildings were combined to compute the industrial and the building heat emissions, respectively. The results illustrate the detailed spatio-temporal distribution variances of each type of anthropogenic heat emission during the daytime and the nighttime, which show a higher reasonability and precision. During the daytime, the high intensity of anthropogenic heat emissions is mainly distributed in the southwest of the study area, while the heat intensity is uniformly distributed during the nighttime. The average anthropogenic heat flux densities are 33.45 W/m2 and 15.34 W/m2 in the daytime and the nighttime, respectively. The highest heat flux density with the value of 14.93 W/m2 is released by commercial buildings during the daytime, while the traffic heat is the highest with the average value of 5.17 W/m2 during the nighttime.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  1. Afshari, A., Schuch, F., Marpu, P.: Estimation of the traffic related anthropogenic heat release using BTEX measurements - a case study in Abu Dhabi. Urban Clim. 24, 311–325 (2018)

    Article  Google Scholar 

  2. Allen, L., Lindberg, F., Grimmond, C.S.B.: Global to city scale urban anthropogenic heat flux: model and variability. Int. J. Climatol. 31, 1990–2005 (2011)

    Article  Google Scholar 

  3. Assimakopoulos, M.N., Mihalakakou, G., Flocas, H.A.: Simulating the thermal behavior of a building during summer period in the urban environment. Renew Energy. 32(11), 1805–1816 (2007)

    Article  Google Scholar 

  4. Chen, B., Shi, G.Y., Wang, B., Zhao, J.Q., Tan, S.C.: Estimation of the anthropogenic heat release distribution in China from 1992 to 2009. Acta Meteor Sin. 26, 507–515 (2012)

    Article  Google Scholar 

  5. Chow, W.T.L., Salamanca, F., Georgescu, M., Alex, M., Milne, J.M., Ruddell, B.L.: A multi-method and multi-scale approach for estimating city-wide anthropogenic heat fluxes. Atmos. Environ. 99, 64–76 (2014)

    Article  Google Scholar 

  6. Davies, M., Steadman, P., Oreszczyn, T.: Strategies for the modification of the urban climate and the consequent impact on building energy use. Energ Policy. 36(12), 4548–4551 (2008)

    Article  Google Scholar 

  7. Flanner, M.G.: Integrating anthropogenic heat flux with global climate models. Geophys. Res. Lett. 4(2), 270–271 (2009)

    Google Scholar 

  8. Gallego, F.J.: A population density grid of the European union. Popul Environ. 31(6), 460–473 (2010)

    Article  Google Scholar 

  9. Hamilton, I.G., Davies, M., Steadman, P., Stone, A., Ridley, L., Evans, S.: The significance of the anthropogenic heat emissions of London's buildings: a comparison against captured shortwave solar radiation. Build. Environ. 44(4), 807–817 (2009)

    Article  Google Scholar 

  10. Hsieh, C.M., Aramaki, T., Hanaki, K.: Estimation of heat rejection based on the air conditioner use time and its mitigation from buildings in Taipei City. Build. Environ. 42(9), 3125–3137 (2007)

    Article  Google Scholar 

  11. Ichinose, T., Shimodozono, K., Hanaki, K.: Impact of anthropogenic heat on urban climate in Tokyo. Atmos. Environ. 33(24), 3897–3909 (1999)

    Article  Google Scholar 

  12. Kłysik, K.: Spatial and seasonal distribution of anthropogenic heat emissions in Lodz, Poland. Atmos Environ. 30(20), 3397–3404 (1996)

    Article  Google Scholar 

  13. Koralegedara, S.B., Lin, C.Y., Sheng, Y.F., Kuo, C.H.: Estimation of anthropogenic heat emissions in urban TaiWan and their spatial patterns. Environ. Pollut. 215, 84–95 (2016)

    Article  Google Scholar 

  14. Lai, L.W.: The influence of urban heat island phenomenon on PM concentration: an observation study during the summer half-year in metropolitan Taipei, Taiwan. Theor Appl Climatol. 131, 227–243 (2018)

    Article  Google Scholar 

  15. Li, H.D., Meier, F., Lee, X.H., Chakraborty, T., Liu, J.F., Schaap, M., Sodoudi, S.: Interaction between urban heat island and urban pollution island during summer in Berlin. Sci. Total Environ. 636, 818–828 (2018)

    Article  Google Scholar 

  16. Liu, R.T., Han, Z.W.: The effects of anthropogenic heat release on urban meteorology and implication for haze pollution in the Beijing-Tianjin-Hebei region. Adv Meteorol 6178308 (2016)

  17. Lu, Y., Wang, Q.G., Zhang, Y.Y., Sun, P., Qian, Y.: Anthropogenic heat emissions in the Yangtze River Delta region. Int. J. Climatol. 36, 1134–1142 (2016)

    Article  Google Scholar 

  18. Makar, P.A., Gravel, S., Chirkov, V., Strawbridge, K.B., Froude, F., Arnold, J., Brook, J.: Heat flux, urban properties, and regional weather. Atmos. Environ. 40(15), 2750–2766 (2006)

    Article  Google Scholar 

  19. Mirzaei, P.A., Haghighat, F.: Approaches to study urban Heat Island–abilities and limitations. Build. Environ. 45(10), 2192–2201 (2010)

    Article  Google Scholar 

  20. Nie, W.S., Sun, T., Ni, G.H.: Spatiotemporal characteristics of anthropogenic heat in an urban environment: a case study of Tsinghua campus. Build. Environ. 82, 675–686 (2014)

    Article  Google Scholar 

  21. Offerle, B., Grimmond, C.S.B., Fortuniak, K.: Heat storage and anthropogenic heat flux in relation to the energy balance of a central European city Centre. Int. J. Climatol. 25, 1405–1419 (2005)

    Article  Google Scholar 

  22. Pigeon, G., Legain, D., Durand, P., Masson, V.: Anthropogenic heat release in an old European agglomeration (Toulouse, France). Int. J. Climatol. 27(14), 1969–1981 (2007)

    Article  Google Scholar 

  23. Qi, W., Liu, S.H., Gao, X.L., Zhou, M.: Modeling the spatial distribution of urban population during the daytime and at night based on land use: a case study in Beijing, China. J Geogr Sci. 6, 756–768 (2015)

    Article  Google Scholar 

  24. Quah, A.K.L., Roth, M.: Diurnal and weekly variation of anthropogenic heat emissions in a tropical city, Singapore. Atmos Environ. 46(1), 92–103 (2012)

    Article  Google Scholar 

  25. Sailor, D.J.: A review of methods for estimating anthropogenic heat and moisture emissions in the urban environment. Int. J. Climatol. 31, 189–199 (2009)

    Article  Google Scholar 

  26. Sailor, D.J., Lu, L.: A top–down methodology for developing diurnal and seasonal anthropogenic heating profiles for urban areas. Atmos. Environ. 38(17), 2737–2748 (2004)

    Article  Google Scholar 

  27. Sun, R.H., Wang, Y.N., Chen, L.D.: A distributed model for quantifying temporal-spatial patterns of anthropogenic heat based on energy consumption. J. Clean. Prod. 170, 601–609 (2018)

    Article  Google Scholar 

  28. Taha, H.: Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat. Energ Buildings. 25(2), 99–103 (1997)

    Article  Google Scholar 

  29. Torrance, K.E., Shun, J.S.W.: Time-varying energy consumption as a factor in urban climate. Atmos. Environ. 10(4), 329–337 (1976)

    Article  Google Scholar 

  30. Wang, Y.N., Sun, R.H., Chen, L.D.: A review of anthropogenic heat calculation methods. J. Appl. Ecol. 27(6), 2024–2030 (2016)

    Google Scholar 

  31. Wang, Y.Y., Du, H.Y., Xu, Y.Q., Lu, D.B., Wang, X.Y., Guo, Z.Y.: Temporal and spatial variation relationship and influence factors on surface urban heat island and ozone pollution in the Yangtze River Delta, China. Sci Total Environ. 631-632, 921–933 (2018)

    Article  Google Scholar 

  32. Xie, M., Zhu, K.G., Wang, T.J., Wen, F., Li, M.M., Li, S., Zhuang, B.L., Han, Y., Chen, P.L., Liao, J.B.: Changes of regional meteorology induced by anthropogenic heat and their impacts on air quality in South China. Atmos. Chem. Phys. 16(23), 1–29 (2016)

    Article  Google Scholar 

  33. Yang, W.M., Chen, B., Cui, X.F.: High-resolution mapping of anthropogenic heat in China from 1992 to 2010. Int J Environ Res Public Health. 11, 4066–4077 (2014)

    Article  Google Scholar 

  34. Zheng, Z.F., Ren, G.Y., Wang, H., Dou, J.X., Gao, Z.Q., Duan, C.F., Li, Y.B., Ngarukiyimana, J.P., Zhao, C., Cao, C., Jiang, M., Yang, Y.J.: Relationship between fine-particle pollution and the urban heat island in Beijing, China: observational evidence. Bound-Layer Meteorol. 169, 93–113 (2018)

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Key R&D Program of China (No. 2018YFC1506801), the Natural Science Foundation of China (No. 41571418, 41871028), the Qing Lan Project of Jiangsu Province, and the Priority Academic Program Development of Jiangsu Higher Education Institutions.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Shanyou Zhu.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Responsible Editor: Yunsoo Choi.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhang, G., Luo, Y. & Zhu, S. Estimation of the Spatio-Temporal Characteristics of Anthropogenic Heat Emission in the Qinhuai District of Nanjing Using the Inventory Survey Method. Asia-Pacific J Atmos Sci 56, 367–380 (2020). https://doi.org/10.1007/s13143-019-00142-9

Download citation

Keywords

  • Anthropogenic heat emission
  • Bottom-up energy inventory method
  • Remote sensing
  • Spatio-temporal distribution