人为热排放对不同类型建成区温度影响的模拟研究

doi:10.18306/dlkxjz.2018.04.007

Abstract

Abstract:

Along with the rapid urbanization process, large amounts of anthropogenic heat are released into the atmosphere, which are becoming a key issue for regional weather condition. To understand what role anthropogenic heat release plays in regional temperature warming, Weather Research & Forecasting (WRF) model was applied to simulate temperature during 2-6 July 2010 with different configuration of anthropogenic heat release. The results indicate that the simulated temperature is consistent with the meteorological station observation data, with the correlation coefficient of 0.89 and the root-mean-square error of 2.96. High density residential area had the highest daily average temperature followed by industrial or commercial zone and low density residential area. On the other hand, low density residential area had the highest daily diurnal temperature range followed by high density residential area and industrial or commercial zone. Anthropogenic heat release caused a notable warming in the whole downtown area of Guangzhou City, which was more significant in high density residential area and commercial zone than low density residential area. The spatial association between temperature rise caused by anthropogenic heat release and building density is 0.17 (high density residential area), 0.14 (low density residential area), and 0.16 (industrial or commercial zone), respectively. Conversely, anthropogenic heat release decreased diurnal temperature range (the difference between daily maximum temperature and daily minimum temperature), which was more significant in high density residential area and commercial zone than low density residential area. The spatial association between daily temperature range decrease caused by anthropogenic heat release and building density is 0.14 (high density residential area), 0.15 (low density residential area), and 0.19 (industrial or commercial zone). Furthermore, when doubling the anthropogenic heat release, the spatial association between building density and simulated temperature rise and daily temperature range decrease was enhanced.

Key words: anthropogenic heat release, different types of built-up land, heat waves, numerical simulation, WRF model, geographical detector

Zheng CAO, Zhifeng WU, Wenjun MA. Effect of anthropogenic heat release on temperature in different types of built-up land in Guangzhou, China[J].PROGRESS IN GEOGRAPHY, 2018, 37(4): 515-524.

Figures/Tables 12

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References 43

[1]	车汶蔚. 2010. 珠江三角洲高时空分辨率机动车污染排放清单开发及控制对策研究[D]. 广州: 华南理工大学.
	[Che W W.2010. A highly resolved mobile source emission inventory in the Pearl River Delta and assessment of motor vehicle pollution control strategies[D]. Guangzhou, China: South China University of Technology.]
[2]	崔耀平, 刘纪远, 张学珍, 等. 2015. 京津唐城市群土地利用变化的区域增温效应模拟[J]. 生态学报, 35(4): 993-1003. doi: 10.5846/stxb201305191114
	[Cui Y P, Liu J Y, Zhang X Z, et al.2015. Modeling urban sprawl effects on regional warming in Beijing-Tianjing-Tangshan urban agglomeration[J]. Acta Ecologica Sinica, 35(4): 993-1003.] doi: 10.5846/stxb201305191114
[3]	方迎波, 占文凤, 黄帆, 等. 2017. 长三角城市群表面城市热岛日内逐时变化规律[J]. 地球科学进展, 32(2): 187-198. doi: 10.11867/j.issn.1001-8166.2017.02.0187
	[Fang Y B, Zhan W F, Huang F, et al.2017. Hourly variation of surface urban heat island over the Yangtze River Delta urban agglomeration[J]. Advances in Earth Science, 32(2): 187-198.] doi: 10.11867/j.issn.1001-8166.2017.02.0187
[4]	李炟, 束炯, 谈建国, 等. 2015. 基于土地利用和人为热修正的城市夏季高温数值试验[J]. 热带气象学报, 31(3): 364-373.
	[Li D, Shu J, Tan J G, et al.2015. A numerical simulation experiment of an urban summer heat wave based on modified data of land-use and anthropogenic heat[J]. Journal of Tropical Meteorology, 31(3): 364-373.]
[5]	李元征, 尹科, 周宏轩, 等. 2016. 基于遥感监测的城市热岛研究进展[J]. 地理科学进展, 35(9): 1062-1074. doi: 10.18306/dlkxjz.2016.09.002
	[Li Y Z, Yin K, Zhou H X, et al.2016. Progress in urban heat island monitoring by remote sensing[J]. Progress in Geography, 35(9): 1062-1074.] doi: 10.18306/dlkxjz.2016.09.002
[6]	陆燕, 王勤耕, 翟一然, 等. 2014. 长江三角洲城市群人为热排放特征研究[J]. 中国环境科学, 34(2): 295-301. doi: 10.3969/j.issn.1000-6923.2014.02.004
	[Lu Y, Wang Q G, Zhai Y R, et al.2014. Anthropogenic heat emissions in the Yangtze River Delta region[J]. China Environmental Science, 34(2): 295-301.] doi: 10.3969/j.issn.1000-6923.2014.02.004
[7]	麦健华, 罗乃兴, 赖文锋, 等. 2011. 城市化对珠江三角洲热岛效应影响的模拟[J]. 热带地理, 31(2): 187-192. doi: 10.3969/j.issn.1001-5221.2011.02.012
	[Mai J H, Luo N X, Lai W F, et al.2011. A simulation about the impact of urbanization on the urban heat island in the Pearl River Delta region[J]. Tropical Geography, 31(2): 187-192.] doi: 10.3969/j.issn.1001-5221.2011.02.012
[8]	蒙伟光, 张艳霞, 李江南, 等. 2010. WRF/UCM在广州高温天气及城市热岛模拟研究中的应用[J]. 热带气象学报, 26(3): 273-282. doi: 10.3969/j.issn.1004-4965.2010.03.003
	[Meng W G, Zhang Y X, Li J N, et al.2010. Application of WRF/UCM in the simulation of a heat wave event and urban heat island around Guangzhou City[J]. Journal of Tropical Meteorology, 26(3): 273-282.] doi: 10.3969/j.issn.1004-4965.2010.03.003
[9]	曲建升, 孙成权, 张志强, 等. 2003. 全球变化科学中的碳循环研究进展与趋向[J]. 地球科学进展, 18(6): 980-987. doi: 10.3321/j.issn:1001-8166.2003.06.021
	[Qu J S, Sun C Q, Zhang Z Q, et al.2003. Trends and advances of the global change studies on carbon cycle[J]. Advance in Earthe Sciences, 18(6): 980-987.] doi: 10.3321/j.issn:1001-8166.2003.06.021
[10]	陶玮, 刘峻峰, 陶澍. 2014. 城市化过程中下垫面改变对大气环境的影响[J]. 热带地理, 34(3): 283-292.
	[Tao W, Liu J F, Tao S.2014. Effects of urban underlying surface change on ambient atmospheric environment[J]. Tropical Gegraphy, 34(3): 283-292.]
[11]	王建鹏, 薛春芳, 黄少妮, 等. 2015. 城市化及人为热对西安市气象要素影响差异敏感性分析[J]. 干旱气象, 33(3): 434-443. doi: 10.11755/j.issn.1006-7639(2015)-03-0434
	[Wang J P, Xue C F, Huang S N, et al.2015. Sensitivity test of impact of urbanization and anthropogenic heat on meteorological elements in Xi'an[J]. Journal of Arid Meteorology, 33(3): 434-443.] doi: 10.11755/j.issn.1006-7639(2015)-03-0434
[12]	王劲峰, 徐成东. 2017. 地理探测器: 原理与展望[J]. 地理学报, 72(1): 116-134.
	[Wang J F, Xu C D.2017. Geodetector: Principle and prospective[J]. Acta Gegraphical Sinica, 72(1): 116-134.]
[13]	王志铭, 王雪梅. 2011. 广州人为热初步估算及敏感性分析[J]. 气象科学, 31(4): 422-430. doi: 10.3969/j.issn.1009-0827.2011.04.009
	[Wang Z M, Wang X M.2011. Estimation and sensitivity test of anthropogenic heat flux in Guangzhou[J]. Journal the Meteorological Sciences, 31(4): 422-430.] doi: 10.3969/j.issn.1009-0827.2011.04.009
[14]	吴风波,汤剑平. 2015. 城市化对长江三角洲地区夏季降水、气温的影响[J]. 热带气象学报, 31(2): 255-263.
	[Wu F B, Tang J P.2015. The impact of urbanization on summer precipitation and temperature in the Yangtze River Delta[J]. Journal of Tropical Meteorology, 31(2): 255-263.]
[15]	张弛,束炯,陈珊珊. 2011. 城市人为热排放分类研究及其对气温的影响[J]. 长江流域资源与环境,20(2): 232-238.
	[Zhang C, Shu J, Chen S S.2011. Urban anthropogenic heat release categoriziing and its effects on urban temperature[J]. Resource and Environment in the Yangtze Basin, 20(2): 232-238.]
[16]	郑玉兰, 苗世光, 包云轩, 等. 2017. 建筑物制冷系统人为热排放与气象环境的相互作用[J]. 高原气象, 36(2): 562-574. doi: 10.7522/j.issn.1000-0534.2016.00005
	[Zheng Y L, Miao S G, Bao Y X, et al.2017. Interaction of anthropogenic heat emission from building cooling system and meteorological environment[J]. Plateau Meteorology, 36(2): 562-574.] doi: 10.7522/j.issn.1000-0534.2016.00005
[17]	Block A, Keuler K, Schaller E.2004. Impacts of anthropogenic heat on regional climate patterns[J]. Geophysical Research Letters, 31(12): L12211. doi: 10.1029/2004GL019852
[18]	Chen Y, Jiang W M, Zhang N, et al.2009. Numerical simulation of the anthropogenic heat effect on urban boundary layer structure[J]. Theoretical and Applied Climatology, 97(1-2): 123-134. doi: 10.1007/s00704-008-0054-0
[19]	Correa E, Ruiz M A, Canton A, et al.2012. Thermal comfort in forested urban canyons of low building density: An assessment for the city of Mendoza, Argentina[J]. Building and Environment, 58(58): 219-230. doi: 10.1016/j.buildenv.2012.06.007
[20]	Fan H L, Sailor D J.2005. Modeling the impacts of anthropogenic heating on the urban climate of Philadelphia: A comparison of implementations in two pbl schemes[J]. Atmospheric Environment, 39(1): 73-84. doi: 10.1016/j.atmosenv.2004.09.031
[21]	Feng J M, Wang Y L, Ma Z G, et al.2012. Simulating the regional impacts of urbanization and anthropogenic heat release on climate across China[J]. Journal of Climate, 25(20): 7187-7203. doi: 10.1175/JCLI-D-11-00333.1
[22]	Giridharan R, Lau S S, Ganesan S, et al.2008. Lowering the outdoor temperature in high-rise high-density residential developments of coastal Hong Kong: The vegetation influence[J]. Building and Environment, 43(10): 1583-1595. doi: 10.1016/j.buildenv.2007.10.003
[23]	Guo G H, Wu Z F, Xiao R B, et al.2015. Impacts of urban biophysical composition on land surface temperature in urban heat island clusters[J]. Landscape and Urban Planning, 135: 1-10. doi: 10.1016/j.landurbplan.2014.11.007
[24]	Heaviside C, Vardoulakis S, Cai X M.2016. Attribution of mortality to the urban heat island during heatwaves in the West Midlands, UK[J]. Environmental health, 15(S1): S27. doi: 10.1186/s12940-016-0100-9 pmid: 26961286
[25]	Hinkel K M, Nelson F E, Klene A E, et al.2003. The urban heat island in winter at Barrow, Alaska[J]. International Journal of Climatology, 23(15): 1889-1905. doi: 10.1002/joc.971
[26]	Huang L H, Long E S, Ouyang J L.2015. Measurement of the thermal environment in temporary settlements with high building density after 2008 Wenchuan earthquake in China[J]. Procedia Engineering, 121: 95-100. doi: 10.1016/j.proeng.2015.08.1027
[27]	Intergovernmental Panel on Climate Change. 2014. Climate change 2014: Synthesis report[M]. Cambridge, UK: Cambridge University Press.
[28]	Kato S, Yamaguchi Y.2005. Analysis of urban heat-island effect using ASTER and ETM+ data: Separation of anthropogenic heat discharge and natural heat radiation from sensible heat flux[J]. Remote Sensing of Environment, 99(1-2): 44-54. doi: 10.1016/j.rse.2005.04.026
[29]	Kimura F, Takahashi S.1991. The effects of land-use and anthropogenic heating on the surface temperature in the Tokyo metropolitan area: A numerical experiment[J]. Atmospheric Environment.:Part B: Urban Atmosphere, 25(2): 155-164. doi: 10.1016/0957-1272(91)90050-O
[30]	Koralegedara S B, Lin C Y, Sheng Y F, et al.2016. Estimation of anthropogenic heat emissions in urban Taiwan and their spatial patterns[J]. Environmental Pollution, 215: 84-95. doi: 10.1016/j.envpol.2016.04.055 pmid: 27179327
[31]	Kusaka H, Chen F, Tewari M, et al.2012. Numerical simulation of urban heat island effect by the WRF model with 4-km grid increment: An inter-comparison study between the urban canopy model and slab model[J]. Journal of the Meteorological Society of Japan Series I, 90B: 33-45. doi: 10.2151/jmsj.2012-B03
[32]	Lee S H, McKeen S A, Sailor D J.2014. A regression approach for estimation of anthropogenic heat flux based on a bottom-up air pollutant emission database[J]. Atmospheric Environment, 95: 629-633. doi: 10.1016/j.atmosenv.2014.07.009
[33]	Lee S H, Song C K, Baik J J, et al.2009. Estimation of anthropogenic heat emission in the Gyeong-In region of Korea[J]. Theoretical and Applied Climatology, 96(3-4): 291-303. doi: 10.1007/s00704-008-0040-6
[34]	Li Y, Zhu L J, Zhao X Y, et al.2013. Urbanization impact on temperature change in China with emphasis on land cover change and human activity[J]. Journal of Climate, 26(22): 8765-8780. doi: 10.1175/JCLI-D-12-00698.1
[35]	Narumi D, Kondo A, Shimoda Y.2009. Effects of anthropogenic heat release upon the urban climate in a Japanese megacity[J]. Environmental Research, 109(4): 421-431. doi: 10.1016/j.envres.2009.02.013 pmid: 19349044
[36]	Peng J, Xie P, Liu Y X, et al.2016. Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region[J]. Remote Sensing of Environment, 173: 145-155. doi: 10.1016/j.rse.2015.11.027
[37]	Pigeon G, Legain D, Durand P, et al.2007. Anthropogenic heat release in an old European agglomeration (Toulouse, France)[J]. International Journal of Climatology, 27(14): 1969-1981. doi: 10.1002/joc.1530
[38]	Strømann-Andersen J, Sattrup P A.2011. The urban canyon and building energy use: Urban density versus daylight and passive solar gains[J]. Energy and Buildings, 43(8): 2011-2020. doi: 10.1016/j.enbuild.2011.04.007
[39]	Oke T R.1988. The urban energy balance[J]. Progress in Physical Geograpgy, 12(4): 471-508. doi: 10.1177/030913338801200401
[40]	Wang X M, Sun X G, Tang J P, et al.2015. Urbanization-induced regional warming in Yangtze River Delta: Potential role of anthropogenic heat release[J]. International Journal of Climatology, 35(15): 4417-4430. doi: 10.1002/joc.4296
[41]	Weng Q H, Liu H, Lu D S.2007. Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States[J]. Urban Ecosystems, 10(2): 203-219. doi: 10.1007/s11252-007-0020-0
[42]	Wu K, Yang X Q.2013. Urbanization and heterogeneous surface warming in eastern China[J]. Chinese Science Bulletin, 58(12): 1363-1373. doi: 10.1007/s11434-012-5627-8
[43]	Yang X Y, Li Y G.2015. The impact of building density and building height heterogeneity on average urban albedo and street surface temperature[J]. Building and Environment, 90: 146-156. doi: 10.1016/j.buildenv.2015.03.037

数据名称	数据分类		分辨率/m
数据名称	一级类		二级类
Globaland30	耕地	水田、旱地、菜地、雨养旱地、牧草种植地等	30
	森林	落叶阔叶林、常绿阔叶林、落叶针叶林、常绿针叶林、混交林
	草地	草原、草甸、稀树草原、荒漠草原、人工草地
	灌木地	山地灌丛、落叶灌丛、常绿灌丛、荒漠灌丛
	湿地	内陆沼泽、湖泊沼泽、河流洪泛湿地、森林/灌木湿地、泥潭沼泽、红树林
	水体	江河、湖泊、水库、坑塘
	苔原	灌丛苔原、禾本苔原、湿苔原、高寒苔原、裸地苔原
	人造地表	居民地、工矿、交通设施
	裸地	荒漠、沙地、砾石地、裸岩、盐碱地
	冰川/永久积雪	永久积雪、冰川、极地冰盖
广州市中心城区建筑密度数据	居住地	高密度住宅区、低密度住宅区	500
广州市中心城区建筑密度数据	商业用地		500

	Bias/℃	R	RMSE
7月2日	-0.36	0.81	2.22
7月3日	-0.25	0.85	2.20
7月4日	-0.29	0.82	2.27
7月5日	-0.22	0.88	2.16
7月6日	-0.15	0.89	2.13
高密度住宅区(7月2-6日)	-0.17	0.91	2.01
低密度住宅区(7月2-6日)	-0.20	0.87	2.10
商业区(7月2-6日)	-0.26	0.80	2.25

建成区类型	高密度住宅区	低密度住宅区	商业区
1倍人为热增温效应q值	0.17^**	0.13^**	0.16^**
2倍人为热增温效应q值	0.21^**	0.15^**	0.19^**
q值增幅	0.04	0.02	0.03

建成区类型	高密度住宅区	低密度住宅区	商业区
1倍人为热增温效应q值	0.14^**	0.15^**	0.19^**
2倍人为热增温效应q值	0.16^**	0.16^**	0.23^**
q值增幅	0.02	0.01	0.04

Effect of anthropogenic heat release on temperature in different types of built-up land in Guangzhou, China

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