Spatio-Temporal Evolution and Prediction of Tourism Comprehensive Climate Comfort in Henan Province, China

Jun, Zhao; Wang, Shengjie

doi:10.3390/atmos12070823

Cited by 16 publications

(13 citation statements)

References 57 publications

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“…The CCI evaluation model recommended by China's "Climate Suitability Evaluation on Human Settlement Environment" (GB/T27963-2011) mainly covers THI, WEI, and other indicators. Based on previous CCI evaluation models, ICL was combined with THI and WEI to build a integrated CCI evaluation index system (Zhang et al, 2018;Zhao and Wang, 2021). The weights of indicators were determined by classification and assignment, analytic hierarchy, and other methods.…”

Section: Research Methods and Evaluation Indicatorsmentioning

confidence: 99%

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Temporal and Spatial Evolution of Climate Comfort and Population Exposure in Guangdong Province in the Last Half Century

Ye¹,

Song²,

Zhong³

2022

Preprint

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Regional Climatic Comfort Index (CCI) deteriorated significantly due to the climate change and anthropogenic interference. Knowledge regarding the long-term temporal dynamics of CCI in typical regions should be strengthened. In this study, we analyze the temporal and spatial evolution of CCI from 1969 to 2018 in Guangdong Province, based on meteorological indicators, including heat, humidity, wind and cloth loading etc.. Additionally, the population exposure to climate unconformity was examined since 1990 with the help of population data. Our study found that: (1) the warming and humidifying of the summer climate served as the main driving force for the continuous deterioration of CCI, with the comfortable days decreased by 1.06d/10a and the extremely muggy days increased by 2.83d/10a; (2) spatially, the lowest climate comfortability concentrated in southwestern Guangdong with more than 50 uncomfortable days each year, while the climate comfortability in northeastern Guangdong tends to deteriorated whit higher rate, which can reach as high as 6d/10a; (3) in summer, the population exposure to uncomfortable climate highly centralized in the Pearl River Delta, Shantou, Jieyang, and the surrounding areas, and both area and population exposure showed increasing trends. Particularly, Shenzhen held the highest growth rate of population exposure with an increase rate of 2.94 million/10a; (4) although the discomfort distribution and deterioration rate vary across the province, the spatial heterogeneity of comfortability is diminishing in Guangdong Province. This study will provide scientific reference for regional urban planning, thermal environment improvement, local resident health risk analysis, and key strategy implementation, etc.

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Section: Research Methods and Evaluation Indicatorsmentioning

confidence: 99%

“…(3) ICL: Cloth loading recommendations are based on many factors, including temperature, solar radiation, human metabolism, and wind speed. Different choices of cloth loading can effectively improve or exacerbate climate discomfort (Zhao and Wang, 2021).…”

Section: Research Methods and Evaluation Indicatorsmentioning

confidence: 99%

Temporal and Spatial Evolution of Climate Comfort and Population Exposure in Guangdong Province in the Last Half Century

Ye¹,

Song²,

Zhong³

2022

Preprint

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“…The ICL is a model that reflects how people change their clothes according to the external environment. This model considers human activity level parameters from the perspective of the thermal balance of the human body surface and has been widely used in climate comfort evaluation studies Zhao and Wang, 2021). In 1955, Burton and Edholm.…”

Section: Introductionmentioning

confidence: 99%

The index of clothing for assessing tourism climate comfort: Development and application

Liu²,

Deng³

et al. 2023

Front. Environ. Sci.

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Climate comfort is a significant factor in analyzing the effects of climate change on tourism, and considerable research has used multidimensional climate indices to evaluate climate comfort. In particular, the index of clothing (ICL) is recognized as one of the most popular climate indices and has been widely applied in many studies. While few studies focused on the calculation method of the index of clothing model’s surface solar radiation (Ract), the computed value was greater than that observed at ground stations. Thus, this study tried to improve solar radiation energy calculation on the Earth’s surface in the index of clothing model with the method recommended by the International Food and Agriculture Organization (FAO), and then validated the new model based on the meteorological data of 31 provincial capitals in mainland China during 1980–2019. Results showed that: 1) The value of Ract calculated by the International Food and Agriculture Organization (FAO) method was close to the site observations (Pbais < 15%), and was suggested to be used in enhancing the estimate approach for Ract in the index of clothing; 2) Different from the original index of clothing, ICL-new is significantly more effective in evaluating climate comfort in middle and low latitude regions; 3) Climate change had a considerable influence on the climate comfort of cities in mainland China. Since 1980, the climate comfort of cities in eastern China had increased in spring, while that of cities in western China had declined, and most cities had a decreasing trend in summer. Finally, our findings revealed that ICL-new can realistically and precisely depicts the actual scenario than the original index of clothing, and it is more suitable to provide scientific impact assessment and tourism management for government agencies and destination management.

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“…Efficiency, which refers to the efficient allocation of resources, is an economic conception [2] . Tourism efficiency is an important basis for measuring whether the utilization of regional tourism resources is reasonable and the level of tourism development [3] . The research on tourism efficiency began earlier abroad, mostly focusing on core tourism departments such as hotels [4] , travel agencies [5] , scenic spots [6] , tourism transportation [7], etc.in China…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Influencing Factors Analysis of Urban Tourism Efficiency in Taihang Mountain Region

2023

tmte

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The level of tourism efficiency directly affects the level of tourism industry quality, to improve tourism efficiency is an important measure to achieve quality upgrading of tourism. With the Taihang Mountain region as the research object and 18 cities within the region as the decision-making unit, the tourism efficiency of the region during 2016-2020 was comprehensively measured based on the DEA-Malmquist index model, and the influencing factors were analyzed. The results show that: (1) From 2016 to 2020, the comprehensive tourism efficiency of Taihang Mountain region shows a general trend of fluctuation, and the development level of tourism development of each city is uneven. (2) The total factor production efficiency of regional tourism showed an obvious downward trend from 2016 to 2020, mainly due to limited investment scale and no obvious progress in technology; The index of regional total factor production efficiency ranked East Taihang > West Taihang > South Taihang. (3) Industrial structure, transportation convenience and government intervention in tourism economy have significant influences on improving tourism efficiency, while economic development level and scientific and technological innovation level have weak influences.

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Spatio-Temporal Evolution and Prediction of Tourism Comprehensive Climate Comfort in Henan Province, China

Cited by 16 publications

References 57 publications

Temporal and Spatial Evolution of Climate Comfort and Population Exposure in Guangdong Province in the Last Half Century

Temporal and Spatial Evolution of Climate Comfort and Population Exposure in Guangdong Province in the Last Half Century

The index of clothing for assessing tourism climate comfort: Development and application

Evaluation and Influencing Factors Analysis of Urban Tourism Efficiency in Taihang Mountain Region

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