Mass Human Migration and the Urban Heat Island during the Chinese New Year Holiday: A Case Study in Harbin City, Northeast China

WU Ling-Yun, ZHANG Jing-Yong, and SHI Chun-Xiang

1State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

2Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

3National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China

Mass Human Migration and the Urban Heat Island during the Chinese New Year Holiday: A Case Study in Harbin City, Northeast China

WU Ling-Yun1, ZHANG Jing-Yong2*, and SHI Chun-Xiang3

1State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

2Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

3National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China

Many Chinese people leave big cities for family reunions during the Chinese New Year (CNY), which is the most important public holiday in China. However, how modern mass human migration during the CNY holiday affects the urban heat island (UHI) is still unknown. Here, the authors investigate the role of modern human migration for the UHI effects during the CNY holiday for the period of 1992-2006 in Harbin City, Northeast China. The results show that during the CNY week, the UHI effects expressed as daily mean, maximum, and minimum temperature differences between urban and rural stations averaged over the period of 1992-2006 are 0.65°C (43%), 0.31°C (48%), and 1.14°C (71%) lower than during the background period (four weeks before and four weeks after the CNY week), respectively. Our findings identify previously unknown impacts of modern mass human migration on the UHI effects based on a case study in Harbin City.

urban heat island, Chinese New Year holiday, mass human migration, surface air temperature, Harbin City Citation: Wu, L.-Y., J.-Y. Zhang, and C.-X. Shi, 2015: Mass human migration and the Urban Heat Island during the Chinese New Year holiday: A case study in Harbin City, Northeast China, Atmos. Oceanic Sci. Lett., 8, 63-66,

10.3878/AOSL20140087.

1　Introduction

The altered land surface and anthropogenic heat release increase the sensible heat flux from the land surface to the atmosphere in city areas, leading to higher temperatures than in surrounding rural areas—a phenomenon known as the urban heat island (UHI) (Howard, 1820; Balchin and Pye, 1947; Oke, 1982; Gordon, 1994; Kalnay and Cai, 2003; Li et al., 2004; Zhang et al., 2005; Liu et al., 2007; Ren et al., 2007; Miao et al., 2009; Oleson et al., 2010; Yang et al., 2013; Georgescu et al., 2014). The UHI can not only produce detrimental impacts, such as degradation in air quality and water quality, amplification in heat waves and storms, and increases in energy demands for air conditioning in summer (e.g., Weaver et al., 2009; Milojevic et al., 2011; Myhre et al., 2013), but also beneficial effects, such as less demands for heating in winter (e.g., Taha, 1997; Stewart and Oke, 2012). Therefore, it is im-portant to understand the nature and causes of the UHI, to develop mitigation or adaptation strategies in the future.

The Chinese New Year (CNY), the beginning of the lunar New Year, is traditionally China's most important public holiday, officially lasting for one week. Since Reform and Opning-up, many people from rural or underdeveloped areas have migrated to big cities. During the CNY holiday, many people in big cities return to their native places for traditional family gatherings.

The reduction of the urban population during the CNY holiday decreases human activities in urban areas, thus leading to reductions in anthropogenic heat emissions from such as vehicles, heating, industrial energy consumption, and human metabolism. The effects of anthropogenic heat on the UHI are relatively large in mid- and high-latitude cities in winter due to weaker solar radiation input, shallower boundary layer, and greater energy use for heating (K?ysik, 1996; Ichinose et al., 1999; Fan and Sailor, 2005; Bohnenstengel et al., 2014). Less human activities can also directly and indirectly affect other processes and thus change the UHI (Bonan, 2008). However, how the mass human migration affects the UHI during the CNY holiday is still unknown.

Harbin City is the capital of Heilongjiang Province, Northeast China, and covers the area from 44°04'N to 46°40'N and from 125°42' E to 130°10'E. The city is known for its coldest climate and longest winter among the major cities of China. Harbin City is a key cultural, political, economic, and scientific center in Northeast China. It has experienced a rapid growth in population from 4.22 million in 1990 to 9.80 million in 2006. Migrant workers and college students usually leave the city for family reunions before the CNY holiday. Also, some local residents leave the city for visiting their relatives and friends, or other purposes. This study investigates the role of modern human migration for the UHI during the CNY holiday in Harbin City for the period of 1992-2006.

2　Data and method

The homogenized daily mean (Tmean), maximum (Tmax) and minimum (Tmin) temperatures used in this study are obtained from the China Meteorological Administration. The UHI effect is defined as the temperature differences between urban (Harbin) and rural (Fangzheng) stations (ΔT = Turban-Trural). The description of the two stations isprovided in Table 1.

The CNY day is determined according to the lunar calendar, therefore, the date of the CNY day changes with year. Table 2 shows that the date of the CNY day varies between 22 January and 19 February during the period of 1992-2006. In this study, the CNY day is denoted as day +1, and the day before as day -1. The CNY week is from day +1 to day +7. Our study period includes nine weeks from 28 days before to 34 days after the CNY day. The dates of the CNY day, the CNY week, and the start (day -28) and end (day +35) days of the study period are listed in Table 2.

3　Results

Figure 1 shows daily mean (ΔTmean), maximum (ΔTmax), and minimum (ΔTmin) temperature differences between urban and rural stations from 28 days before the CNY day (day -28) to 34 days after the CNY day (day +35) averaged over the period of 1992-2006 in Harbin City. ΔTmean, ΔTmax, and ΔTminfrom day -28 to day +35 show a similar feature. All three temperature variables have relatively lower values during the CNY week. Meanwhile, some differences exist. ΔTmeanranges between 0.37°C and 3.11°C, and the mean value is 1.43°C for day -28 to day +35. During the CNY week (day +1 to day +7), ΔTmeanis lower than the mean value. ΔTmaxvalues during day -28 to day +35exhibit smaller magnitudes than ΔTmeanwith a mean value of 0.62°C, and during the CNY week, they are lower than the mean value except on day +1. Comparatively, ΔTminhas the larger magnitude than ΔTmean, varying from -0.26°C to 3.36°C during day -28 to day +35. ΔTminduring the CNY week is much lower than the mean value of 1.49°C.

Table 1 The description of urban and rural stations.

Table 2 Dates of the Chinese New Year (CNY), CNY week, 28 days before the CNY day (day -28), and 34 days after the CNY day (day +35) from 1992 to 2006.

Since the CNY holiday officially lasts for one week, we further examine the weekly means of ΔTmean, ΔTmax, and ΔTminduring day -28 to day +35 averaged over the period of 1992-2006 (Fig. 2). Here, we define the CNY week as week +1, one week before as week -1, one week after as week +2, and so on. ΔTmeanhas the lowest value of 0.86°C in the CNY week, and the weekly mean ΔTmeanvalues fluctuate between 1.25°C and 1.71°C in non-holiday weeks. ΔTminis much stronger than ΔTmaxin non-holiday weeks. However, during the CNY week, ΔTmaxand ΔTminonly have small differences with magnitudes of 0.48°C and 0.34°C, respectively. Therefore, the reduction of ΔTminis much larger than that of ΔTmaxduring the CNY week, compared to non-holiday weeks.

To further compare the UHI differences between the CNY holiday and non-holiday times, we define four weeks before and four weeks after the CNY week as the background period. Table 3 lists the values of the UHI during the CNY week and the background period, the differences between them, and the relative changes of the UHI during the CNY week to the background period averaged over the period of 1992-2006. ΔTmean, ΔTmax, and ΔTminduring the CNY week are consistently much lower than during the background period. The differences between them are 0.65°C, 0.31°C, and 1.14°C, respectively. The relative changes of ΔTmeanand ΔTmaxduring the CNY to the background period have the similar value of 43% and 48%. Comparatively, the change of ΔTmincan reach 71%. The differences in ΔTmeanand ΔTminare significant at the 99% confidence level by Student's t-test, and the ΔTmaxdifference is significant at the 98% confidence level.

4　Conclusions

Harbin City, located at the highest latitude, has the coldest climate among major cities in China. The city has undergone rapid urbanization in the last decades. During the CNY holiday, many people in the city return to their native places or leave for other purposes for celebrating the most important Chinese holiday. This provides us an unique opportunity to explore how mass human migration affects the UHI. In this study, we investigate the role of mass human migration for the UHI during the CNY holiday in Harbin City for the period of 1992-2006 usingobservational data.

Table 3 Statistics of the UHI effects expressed as daily mean (ΔTmean), maximum (ΔTmax), and minimum (ΔTmin) temperature differences between urban and rural stations averaged over the period of 1992-2006. The background period is defined as week -4 to week -1 and week +2 to week +5.

Our results indicate that the UHI effects during the CNY week are much lower than during the background period (four weeks before and four weeks after the CNY week). The reduction of ΔTmeanduring the CNY week is 0.65°C, with respect to the background period. The reductions of ΔTmax, and ΔTminare asymmetric, with magnitudes of 0.31°C and 1.14°C, respectively. The relative changes of ΔTmean, ΔTmax, and ΔTminto those during the background period are 43%, 48%, and 71%, respectively. These changes in ΔTmeanand ΔTminare significant at the 99% confidence level by Student's t-test, and the ΔTmaxchange is significant at the 98% confidence level. The reduced population during the CNY holiday in the urban area of Harbin City leads to less human activities, which results in less anthropogenic heat emissions and also affects other processes, thus significantly reducing the UHI effects. Our findings provide observational evidence that mass human migration can significantly affect the UHI.

Acknowledgements. This work was supported by the National Natural Science Foundation of China (Grant Nos. 41275089 and 41305071) and the National Basic Research Program of China (Grant No. 2012CB955604). Jingyong ZHANG was supported by the Jiangsu Collaborative Innovation Center for Climate Change.

References

Balchin, W. G. V., and N. Pye, 1947: A micro-climatological investigation of bath and the surrounding district, Quart. J. Roy. Meteor. Soc., 73, 297-323.

Bohnenstengel, S. I., I. Hamilton, M. Davies, et al., 2014: Impact of anthropogenic heat emissions on London's temperatures, Quart. J. Roy. Meteor. Soc., 140, 687-698.

Bonan, G. B., 2008: Ecological Climatology (2nd ed.), Cambridge University Press, Cambridge and New York, 550pp.

Fan, H., and D. J. Sailor, 2005: Modeling the impacts of anthropogenic heating on the urban climate of Philadelphia: A comparison of implementations in two PBL schemes, Atmos. Environ., 39, 73-84.

Georgescu, M., P. E. Morefield, B. G. Bierwagen, et al., 2014: Urban adaptation can roll back warming of emerging megapolitan regions, PNAS, doi:10.1073/pnas.1322280111.

Gordon, A. H., 1994: Weekdays warmer than weekends? Nature, 367, 325-326.

Howard, L., 1820: The Climate of London, Deduced from Meteoro

logical Observations, Made at Different Places in theNeighbourhood of the Metropolis, Vol. Ⅱ, Cambridge University Press, London, 384pp.

Ichinose, T., K. Shimodozono, and K. Hanaki, 1999: Impact of anthropogenic heat on urban climate in Tokyo, Atmos. Environ., 33, 3897-3909.

Kalnay, E., and M. Cai, 2003: Impact of urbanization and land-use change on climate, Nature, 423, 528-531.

K?ysik, K., 1996: Spatial and seasonal distribution of anthropogenic heat emissions in Loda, Poland, Atmos. Environ., 20, 3397-3404.

Li, Q., H. Zhang, X. Liu, et al., 2004: Urban heat island effect on annual mean temperature during the last 50 years in China, Theor. Appl. Climatol., 79, 165-174.

Liu, W., C. Ji, J. Zhong, et al., 2007: Temporal characteristics of the Beijing urban heat island, Theor. Appl. Climatol., 87, 213-221.

Miao, S., F. Chen, M. A. LeMone, et al., 2009: An observational and modeling study of characteristics of urban heat island and boundary layer structures in Beijing, J. Appl. Meteor. Climatol., 48, 484-501.

Milojevic, A., P. Wilkinson, B. Armstrong, et al., 2011: Impact of London's urban heat island on heat-related mortality, Epidemiology, 22, 182-183.

Myhre, G., D. Shindell, F.-M. Bréon, et al., 2013: Anthropogenic and Natural Radiative Forcing, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al. (Eds.), Cambridge University Press, Cambridge and New York, 659-740, doi:10.1017/ CBO9781107415324.018.

Oke, T. R., 1982: The energetic basis of the urban heat island, Quart. J. Roy. Meteor. Soc., 108, 1-24.

Oleson, K. W., G. B. Bonan, and J. Feddema, 2010: Effects of white roofs on urban temperature in a global climate model, Geophys. Res. Lett., 37, L03701, doi:10.1029/2009GL042194.

Ren, G., Z. Chu, Z. Chen, et al., 2007: Implications of temporal change in urban heat island intensity observed at Beijing and Wuhan stations, Geophys. Res. Lett., 34, L05711, doi:10.1029/2006GL027927.

Stewart, I. D., and T. R. Oke, 2012: Local climate zones for urban temperatures studies, Bull. Amer. Meteor. Soc., 93, 1879-1900.

Taha, H., 1997: Urban climates and heat islands: Albedo, evapotranspiration, and anthropogenic heat, Energy Build., 25, 99-103.

Weaver, C. P., X. Z. Liang, J. Zhu, et al., 2009: A preliminary synthesis of modeled climate change impacts on U. S. regional ozone concentrations, Bull. Amer. Meteor. Soc., 90, 1843-1863.

Yang, P., G. Ren, and W. Liu, 2013: Spatial and temporal characteristics of Beijing urban heat island intensity, J. Appl. Meteor., 52, 1803-1816.

Zhang, J., W. Dong, L. Wu, et al., 2005: Impact of land use changes on surface warming in China, Adv. Atmos. Sci., 22, 343-348.

5 November 2014; revised 3 December 2014; accepted 4 December 2014; published 16 March 2015

ZHANG Jing-Yong, zjy@mail.iap.ac.cn