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吴凌云, 张井勇, 远芳. 春节人口迁移的气候效应:以郑州为例[J]. 气候与环境研究, 2016, 21(1): 41-46. DOI: 10.3878/j.issn.1006-9585.2015.15056
引用本文: 吴凌云, 张井勇, 远芳. 春节人口迁移的气候效应:以郑州为例[J]. 气候与环境研究, 2016, 21(1): 41-46. DOI: 10.3878/j.issn.1006-9585.2015.15056
WU Lingyun, ZHANG Jingyong, YUAN Fang. Climatic Effects of Mass Human Migration during the Chinese New Year Holiday:A Case Study in Zhengzhou City[J]. Climatic and Environmental Research, 2016, 21(1): 41-46. DOI: 10.3878/j.issn.1006-9585.2015.15056
Citation: WU Lingyun, ZHANG Jingyong, YUAN Fang. Climatic Effects of Mass Human Migration during the Chinese New Year Holiday:A Case Study in Zhengzhou City[J]. Climatic and Environmental Research, 2016, 21(1): 41-46. DOI: 10.3878/j.issn.1006-9585.2015.15056

春节人口迁移的气候效应:以郑州为例

Climatic Effects of Mass Human Migration during the Chinese New Year Holiday:A Case Study in Zhengzhou City

  • 摘要: 目前,我们对人类活动通过温室气体、气溶胶和土地利用对气候产生重要影响已经获得了很多认识。但是,人口迁移流动在多大程度上能够影响气候尚不清楚。中国春节期间的人口大迁移是世界上每年最大规模的人类迁徙。利用城市站和参考站的气温差表示城市热岛强度,以一个典型中国中部大城市-郑州为例,研究了春节人口大迁移对城市热岛效应的影响。结果表明,2005~2013年平均的春节周日平均、日最高和日最低温度郑州站与中牟站的差分别为0.16℃、0.29℃和-0.03℃,比春节周前2~4周和春节周后2~4周的平均值低了0.50℃、0.06℃和0.66℃。相对变化而言,日平均、日最高和日最低温度的差分别降低了76%、16%和105%。春节周日平均和日最低温度的差的变化都通过了99%的信度检验。

     

    Abstract: The human impacts on the climate through emissions of greenhouse gases and aerosols, as well as land use changes, are widely recognized. However, to what extent mass human migration can affect the climate remains largely unknown. The population movements around the Chinese New Year (CNY) represent the world's largest annual human migration. In the present study, we investigate the role of mass human migration in influencing the urban heat island (UHI) during the CNY holiday for the period 2005-2013 in Zhengzhou city, a typical large city in central China. It is found that the UHI effects expressed as daily mean (ΔTmean), maximum (ΔTmax), and minimum (ΔTmin) surface air temperature differences between the stations of Zhengzhou and Zhongmou, averaged over the period 2005-2013 during the CNY week, are 0.16℃, 0.29℃ and -0.03℃, respectively; and these values are 0.50℃ (76%), 0.06℃ (16%) and 0.66℃ (105%) lower than those during the background period (2-4 weeks before the CNY week and after the CNY week), respectively. Changes in ΔTmean and ΔTmin are both significant at the 99% confidence level by the Student's t-test.

     

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