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Increases in Anthropogenic Heat Release from Energy Consumption Lead to More Frequent Extreme Heat Events in Urban Cities

Abstract

With economic development and rapid urbanization, increases in Gross Domestic Product and population in fast-growing cities since the turn of the 21st Century have led to increases in energy consumption. Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events. To investigate the effects of energy consumption on urban extreme temperature events, including extreme heat and cold events, a dynamic representation scheme of anthropogenic heat release (AHR) was implemented in the Advanced Research version of the Weather Research and Forecasting (WRF) model, and AHR data were developed based on energy consumption and population density in a case study of Beijing, China. Two simulations during 1999–2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme. It was shown that the mean temperature increased with the increase in AHR, and more frequent extreme heat events were produced, with an annual increase of 0.02–0.19 days, as well as less frequent extreme cold events, with an annual decrease of 0.26–0.56 days, based on seven extreme temperature indices in the city center. AHR increased the sensible heat flux and led to surface energy budget changes, strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter. In addition, it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.

摘 要

21世纪以来,快速发展的经济和城市化增加了人口与GDP,能源消耗快速增加。由此产生的人为热释放到近地表大气,引发城市热环境的改变及极端温度事件的频发。为探究能源消耗对城市极端温度事件(包括极端高温和低温事件)的影响,本文以北京市为例,构建了基于能源消耗和人口密度的人为热数据集,并在WRF模式中实现了人为热参数化方案的动态表达。基于改进后的模式,本文分别开展了有人为热影响和没有人为热影响的两组模拟试验,模拟时间为1999年至2017年,空间分辨率为3km。结果表明:人为热排放的增加导致平均气温升高;基于7个极端温度指标,极端热事件发生频率增加,年增加量为0.02~0.19天;极端低温事件降低,年减少量为0.26~0.56天。这主要因为人为热通过感热通量引起地表能量收支变化,增强了边界层的动力过程,使夏季人为热的加热效率低于冬季。同时还表明,适当的能源管控可能有助于缓解不同季节极端温度事件的影响。

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References

  1. Alexander, L. V., and Coauthors, 2006: Global observed changes in daily climate extremes of temperature and precipitation. J. Geophys. Res., 111, D05109, https://doi.org/10.1029/2005JD006290.

    Google Scholar 

  2. Basara, J. B., H. G. Basara, B. G. Illston, and K. C. Crawford, 2010: The impact of the urban heat island during an intense heat wave in Oklahoma City. Advances in Meteorology, 230365, https://doi.org/10.1155/2010/230365.

  3. Block, A., K. Keuler, and E. Schaller, 2004: Impacts of anthropogenic heat on regional climate patterns. Geophys. Res. Lett., 31, L12211, https://doi.org/10.1029/2004GL019852.

    Article  Google Scholar 

  4. Chen, B., G. Y. Shi, B. Wang, J. Q. Zhao, and S. C. Tan, 2012: Estimation of the anthropogenic heat release distribution in China from 1992 to 2009. Acta Meteorologica Sinica, 26, 507–515, https://doi.org/10.1007/s13351-012-0409-y.

    Article  Google Scholar 

  5. Chen, B., L. Dong, G. Y. Shi, L. J. Li, and L. F. Chen, 2014a: Anthropogenic heat release: Estimation of global distribution and possible climate effect. J. Meteor. Soc. Japan, 92A, 157–165, https://doi.org/10.2151/jmsj.2014-A10.

    Article  Google Scholar 

  6. Chen, M. X., H. Zhang, W. D. Liu, and W. Z. Zhang, 2014b: The global pattern of urbanization and economic growth: Evidence from the last three decades. PLoS One, 9, e103799, https://doi.org/10.1371/journal.pone.0103799.

    Article  Google Scholar 

  7. Dong, Y., A. C. G. Varquez, and M. Kanda, 2017: Global anthropogenic heat flux database with high spatial resolution. Atmos. Environ., 150, 276–294, https://doi.org/10.1016/j.atmosenv.2016.11.040.

    Article  Google Scholar 

  8. Du, H. Y., D. D. Wang, Y. Y. Wang, X. L. Zhao, F. Qin, H. Jiang, and Y. L. Cai, 2016: Influences of land cover types, meteorological conditions, anthropogenic heat and urban area on surface urban heat island in the Yangtze River Delta Urban Agglomeration. Science of the Total Environment, 571, 461–470, https://doi.org/10.1016/j.scitotenv.2016.07.012.

    Article  Google Scholar 

  9. Enerdata, 2018: Global Energy Trends, 2018 Edition. [Available from https://yearbook.enerdata.net/total-energy/world-consumption-statistics.html]

  10. Feng, J. M., Y. L. Wang, Z. G. Ma, and Y. H. Liu, 2012: Simulating the regional impacts of urbanization and anthropogenic heat release on climate across China. J. Climate, 25, 7187–7203, https://doi.org/10.1175/JCLI-D-11-00333.1.

    Article  Google Scholar 

  11. Feng, J. M., J. Wang, and Z. W. Yan, 2014: Impact of anthropogenic heat release on regional climate in three vast urban agglomerations in China. Adv. Atmos. Sci., 31, 363–373, https://doi.org/10.1007/s00376-013-3041-z.

    Article  Google Scholar 

  12. Founda, D., and M. Santamouris, 2017: Synergies between Urban Heat Island and Heat Waves in Athens (Greece), during an extremely hot summer (2012). Scientific Reports, 7, 10973, https://doi.org/10.1038/s41598-017-11407-6.

    Article  Google Scholar 

  13. Freychet, N., S. Tett, J. Wang, and G. Hegerl, 2017: Summer heat waves over Eastern China: Dynamical processes and trend attribution. Environmental Research Letters, 1, 024015, https://doi.org/10.1088/1748-9326/aa5ba3.

    Article  Google Scholar 

  14. Grimmond, C. S. B, 1992: The suburban energy balance: Methodological considerations and results for a mid-latitude west coast city under winter and spring conditions. International Journal of Climatology, 12, 481–497, https://doi.org/10.1002/joc.3370120506.

    Article  Google Scholar 

  15. Huang, D. Q., Y. F. Qian, and J. A. Zhu, 2010: Trends of temperature extremes in China and their relationship with global temperature anomalies. Adv. Atmos. Sci., 27, 937–946, https://doi.org/10.1007/s00376-009-9085-4.

    Article  Google Scholar 

  16. Iamarino, M., S. Beevers, and C. S. B. Grimmond, 2012: High-resolution (space, time) anthropogenic heat emissions: London 1970–2025. International Journal of Climatology, 22, 1754–1767, https://doi.org/10.1002/joc.2390.

    Article  Google Scholar 

  17. Ichinose, T., K. Shimodozono, and K. Hanaki, 1999: Impact of anthropogenic heat on urban climate in Tokyo. Atmos. Environ., 33, 3897–3909, https://doi.org/10.1016/S1352-2310(99)00132-6.

    Article  Google Scholar 

  18. Jenerette, G. D., S. L. Harlan, W. L. Stefanov, and C. A. Martin, 2011: Ecosystem services and urban heat riskscape moderation: Water, green spaces, and social inequality in Phoenix, USA. Ecological Applications, 21, 2637–2651, https://doi.org/10.1890/10-1493.1.

    Article  Google Scholar 

  19. Li, D., and E. Bou-Zeid, 2013: Synergistic interactions between urban heat islands and heat waves: The impact in cities is larger than the sum of its parts. J. Appl. Meteorol. Climatol., 52, 2051–2064, https://doi.org/10.1175/JAMC-D-13-02.1.

    Article  Google Scholar 

  20. Mohan, M., Y. Kikegawa, B. R. Gurjar, S. Bhati, A. Kandya, and K. Ogawa, 2012: Urban heat island assessment for a tropical urban airshed in India. Atmospheric and Climate Sciences, 2, 127–138, https://doi.org/10.4236/acs.2012.22014.

    Article  Google Scholar 

  21. Narumi, D., A. Kondo, and Y. Shimoda, 2009: Effects of anthropogenic heat release upon the urban climate in a Japanese megacity. Environ. Res., 109, 421–431, https://doi.org/10.1016/j.envres.2009.02.013.

    Article  Google Scholar 

  22. Norton, B. A., A. M. Coutts, S. J. Livesley, R. J. Harris, A. M. Hunter, and N. S. G. Williams, 2015: Planning for cooler cities: A framework to prioritise green infrastructure to mitigate high temperatures in urban landscapes. Landscape and Urban Planning, 134, 127–138, https://doi.org/10.1016/j.landurbplan.2014.10.018.

    Article  Google Scholar 

  23. Rizvi, S. H., K. Alam, and M. J. Iqbal, 2019: Spatio -temporal variations in urban heat island and its interaction with heat wave. Journal of Atmospheric and Solar-Terrestrial Physics, 185, 50–57, https://doi.org/10.1016/j.jastp.2019.02.001.

    Article  Google Scholar 

  24. Ryu, Y. H., and J. J. Baik, 2012: Quantitative analysis of factors contributing to urban heat island intensity. J. Appl. Meteorol. Climatol., 51, 842–854, https://doi.org/10.1175/JAMC-D-11-098.1.

    Article  Google Scholar 

  25. Sailor, D. J., 2011: A review of methods for estimating anthropogenic heat and moisture emissions in the urban environment. International Journal of Climatology, 31(2), 189–199, https://doi.org/10.1002/joc.2106.

    Article  Google Scholar 

  26. Sailor, D. J., and L. Lu, 2004: A top-down methodology for developing diurnal and seasonal anthropogenic heating profiles for urban areas. Atmos. Environ., 38, 2737–2748, https://doi.org/10.1016/j.atmosenv.2004.01.034.

    Article  Google Scholar 

  27. Salamanca, F., M. Georgescu, A. Mahalov, M. Moustaoui, and M. Wang, 2014: Anthropogenic heating of the urban environment due to air conditioning. J. Geophys. Res., 119, 5949–5965, https://doi.org/10.1002/2013JD021225.

    Article  Google Scholar 

  28. Schrijvers, P. J. C., H. J. J. Jonker, S. Kenjereš, and S. R. de Roode, 2015: Breakdown of the night time urban heat island energy budget. Building and Environment, 83, 50–64, https://doi.org/10.1016/j.buildenv.2014.08.012.

    Article  Google Scholar 

  29. Schröter, D., and Coauthors, 2005: Ecosystem service supply and vulnerability to global change in Europe. Science, 310, 1333–1337, https://doi.org/10.1126/science.1115233.

    Article  Google Scholar 

  30. Sillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013: Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J. Geophys. Res., 118(6), 2473–2493, https://doi.org/10.1002/jgrd.50188.

    Article  Google Scholar 

  31. Sina, 2018: Extreme heat is wreaking havoc around the globe, with temperatures as high as 30 degrees North Pole! Beijing will be hot for another four days. [Available online from https://tech.sina.com.cn/d/n/2018-08-03/doc-ihhehtqh1857157.shtml] (in Chinese)

  32. Skamarock, W. C., and Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Technical Note NCAR/TN-475+STR.

  33. Tewari, M., F. Chen, H. Kusaka, and S. G. Miao, 2007: Coupled WRF/Unified Noah/urban-canopy modeling system. NCAR, Boulder, 1–22.

    Google Scholar 

  34. Tian, Z. X., S. S. Li, J. L. Zhang, J. J. K. Jaakkola, and Y. M. Guo, 2012: Ambient temperature and coronary heart disease mortality in Beijing, China: A time series study. Environmental Health, 11, 56, https://doi.org/10.1186/1476-069X-11-56.

    Article  Google Scholar 

  35. United Nations, 2018: 2018 revision of world urbanization prospects. [Available online from https://www.un.org/development/desa/publications/2018-revision-of-world-urbanization-prospects.html]

  36. Wang, M. N., X. D. Yan, J. Y. Liu, and X. Z. Zhang, 2013: The contribution of urbanization to recent extreme heat events and a potential mitigation strategy in the Beijing-Tianjin-Hebei metropolitan area. Theor. Appl. Climatol., 114, 407–416, https://doi.org/10.1007/s00704-013-0852-x.

    Article  Google Scholar 

  37. Wang, X. M., X. G. Sun, J. P. Tang, and X. Q. Yang, 2015: Urbanization — induced regional warming in Yangtze River Delta: Potential role of anthropogenic heat release. International Journal of Climatology, 35, 4417–4430, https://doi.org/10.1002/joc.4296.

    Article  Google Scholar 

  38. Washington, W. M., 1972: Numerical climatic-change experiments: The effect of man’s production of thermal energy. J. Appl. Meteorol. Climatol., 11, 768–772, https://doi.org/10.1175/1520-0450(1972)011<0768:NCCETE>2.0.CO;2.

    Article  Google Scholar 

  39. Wen, Q. H., X. B. Zhang, Y. Xu, and B. Wang, 2013: Detecting human influence on extreme temperatures in China. Geophys. Res. Lett., 40, 1171–1176, https://doi.org/10.1002/grl.50285.

    Article  Google Scholar 

  40. Wilby, R. L., 2003: Past and projected trends in London’s urban heat island. Weather, 58, 251–260, https://doi.org/10.1256/wea.183.02.

    Article  Google Scholar 

  41. WMO, 2013: The global climate 2001–2010: A decade of climate extremes-summary report. WMO-No.1119, 1–15.

  42. Yaghoobian, N., and J. Kleissl, 2012: Effect of reflective pavements on building energy use. Urban Climate, 2, 25–42, https://doi.org/10.1016/j.uclim.2012.09.002.

    Article  Google Scholar 

  43. Yu, M., G. R. Carmichael, T. Zhu, and Y. F. Cheng, 2014: Sensitivity of predicted pollutant levels to anthropogenic heat emissions in Beijing. Atmos. Environ., 89, 169–178, https://doi.org/10.1016/j.atmosenv.2014.01.034.

    Article  Google Scholar 

  44. Zhang, J., T. T. Li, J. G. Tan, C. R. Huang, and H. D. Kan, 2014: Impact of temperature on mortality in three major Chinese cities. Biomedical and Environmental Sciences, 27, 485–494, https://doi.org/10.3967/bes2014.080.

    Google Scholar 

  45. Zhao, L., M. Oppenheimer, Q. Zhu, J. W. Baldwin, K. L. Ebi, E. Bou-Zeid, K. Y. Guan, and X. Liu, 2018: Interactions between urban heat islands and heat waves. Environmental Research Letters, 13, 034003, https://doi.org/10.1088/1748-9326/aa9f73.

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA23090102), the National Natural Science Foundation of China (Grant No. 41830967), the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (Grant No. QYZDY-SSW-DQC012), and the National Key Research and Development Program of China (Grant Nos. 2018YFC1506602 and 2020YFA0608203). We also thank the National Meteorological Information Center, China Meteorological Administration, for data support.

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Correspondence to Zhenghui Xie.

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Article Highlights

• A dynamic representation scheme of AHR was implemented in the WRF model.

• AHR datasets were developed based on local energy consumption and population density via a case study in the city of Beijing, China.

• With the heating effect in the near-surface atmosphere, AHR from energy consumption is expected to increase the frequency of extreme heat events and decrease that of extreme cold events.

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Liu, B., Xie, Z., Qin, P. et al. Increases in Anthropogenic Heat Release from Energy Consumption Lead to More Frequent Extreme Heat Events in Urban Cities. Adv. Atmos. Sci. 38, 430–445 (2021). https://doi.org/10.1007/s00376-020-0139-y

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Key words

  • anthropogenic heat release
  • extreme temperature event
  • Weather Research and Forecasting model
  • Beijing

关键词

  • 人为热
  • 极端温度事件
  • WRF模式
  • 北京