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贵阳市气候康养资源评价
Evaluation of Climate Health Resources in Guiyang City

DOI: 10.12677/JLCE.2023.122007, PP. 50-57

Keywords: 气候康养,极端气候,马尔可夫状态转移,贵阳市
Climate Health
, Extreme Climate, Markov State Transition, Guiyang City

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Abstract:

有效的气候康养资源评价能够为我国养老产业提供科学依据,有利于高效利用气候资源以及带动当地经济发展,兼具生态效益、社会效益及经济效益。由于人体机能对长期气候的适应性和极端气温的季节性和区域性差异,不同地区人群对当地的气候条件适应特征不同,不利于人群健康的极端气温指标也不同。基于此,本研究以贵阳市为研究区域,从极端天气气候事件的概念出发,运用保证法计算得到符合贵阳市气候特征的极端气温指标,并通过马尔可夫状态转移模型展开贵阳市气候康养资源的评价。研究结果表明:贵阳温度时空分布特征有明显的差异;贵阳市各辖区极端温度转移风险表明,各状态主要向正常转移,正常状态向极端状态转移的风险因月份有所差异,在温暖月份和寒冷月份,正常状态向高温、低温转移的风险大致相等;季节过渡月份表现出较大的极端状态转移风险。研究结论可为气候康养资源的有效利用提供依据。
Effective evaluation of climatotherapy resources can provide scientific basis for Chinese pension industry, which has ecological benefit, social results and economic benefits and uses climate resources efficiently. Due to the adaptability of human body function to long-term climate and the seasonal and regional differences of extreme temperature, people from different regions adapt different climate characteristic and the indicators of extreme temperature that are adverse to people’s health are also different. So, this study takes Guiyang city as the study area, starts from the concept of extreme weather and using guarantee rate method to count extreme climate indicators which accord with climate resources of Guiyang city, and through the Markov state transfer model to apprise climate resources of Guiyang city. The results show that there are obvious differences in the temporal and spatial distribution characteristics of Guiyang; The risk of extreme temperature transfer shows that the risk of transition from normal state to extreme state are different due to month; and the risk of transition from normal state to high temperature and low temperature is roughly equal in warm and cold months; the seasonal transition month shows a higher risk of extreme state transfer. The research conclusion can provide the effective basis of climate health resources.

References

[1]  林锦屏, 郭来喜. 中国南方十一座旅游名城避寒疗养气候旅游资源评估[J]. 人文地理, 2003(6): 26-30.
[2]  Bra-ga, A.L.F., Zanobetti, A. and Schwartz, J. (2020) The Effect of Weather on Respiratory and Cardiovascular Deaths in 12 U.S. Cities. Environmental Health Perspectives, 11, 859-863.
[3]  Knowlton, K., Rotkin-Ellman, M., King, G., Margo-lis, H.G., Smith, D., Solomon, G., Trent, R. and English, P. (2009) The 2006 California Heat Wave: Impacts on Hospi-talizations and Emergency Department Visits. Environmental Health Perspectives, 117, 61-67.
https://doi.org/10.1289/ehp.11594
[4]  王玲, 白原, 刘小云, 何涛, 梁戎, 张元, 李雪梅. 高血压与气象因素的关系[J]. 医学综述, 2007(3): 239-241.
[5]  Basu, R. and Ostro, B.D. (2008) A Multicounty Analysis Identifying the Populations Vulnerable to Mortality Associated with High Ambient Temperature in California. American Journal of Epi-demiology, 168, 632-637.
https://doi.org/10.1093/aje/kwn170
[6]  Vida, S., Durocher, M., Ouarda, T.B.M.J. and Gosselin, P. (2012) Rela-tionship between Ambient Temperature and Humidity and Visits to Mental Health Emergency Departments in Quebec. Psychiatric Services, 63, 1150-1153.
https://doi.org/10.1176/appi.ps.201100485
[7]  衣晓峰. 候鸟式养生并不适合所有老年人[N]. 中国中医药报, 2017-11-06(007).
[8]  贾忠义. 湿度对健康的影响[J]. 医药与保健, 2006(5): 64.
[9]  Yang, Q., Yuan, Q., Li, T., Shen, H. and Zhang, L. (2017) The Relationships between PM2.5 and Meteorological Factors in China: Seasonal and Regional Variations. International Journal of Environmental Research and Public Health, 14, Article 1510.
https://doi.org/10.3390/ijerph14121510
[10]  Gerber, Y., Jacobsen, S.J., Killian, J.M., Weston, S.A. and Roger, V.L. (2006) Seasonality and Daily Weather Conditions in Relation to Myocardial Infarction and Sudden Cardiac Death in Olmsted County, Minnesota, 1979 to 2002. Journal of the American College of Cardiology, 48, 287-292.
https://doi.org/10.1016/j.jacc.2006.02.065
[11]  毕鹏, 施小明, 刘起勇. 过去十年中国气候变化与人群健康研究进展及未来展望[J]. 气候变化研究进展, 2020, 16(6): 763-769.
[12]  屈芳, 肖子牛. 气候变化对人体健康影响评估[J]. 气象科技进展, 2019, 9(4):14.
[13]  张灵玲, 陈燕. 气候变化对江苏人体健康的影响[C]//中国气象学会年会. 第33届中国气象学会S16气候环境变化与人体健康. 2016: 249-256.
[14]  李想, 赵冬艳. 大连市雷暴气候统计特征及趋势分析[J]. 现代农业科技, 2012(9): 21-22.
[15]  罗党, 林培源, 李钰雯. 基于灰色残差马尔可夫模型的郑州市旱涝灾害预测[J]. 华北水利水电学院学报, 2015, 36(5): 1-4, 9.

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