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- Hindawi Publishing Corporation
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- Copyright © 2020 Lei Hua et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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- 10.1155/2020/4256164
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Abstract
Hindawi Advances in Meteorology Volume 2020, Article ID 4256164, 8 pages https://doi.org/10.1155/2020/4256164 Research Article Climate Comfort Evaluation of National 5A Tourist Attractions in the Mainland of China Based on Universal Thermal Climate Index 1 1,2 1 1 1 1,2 Lei Hua , Hailin Zhang , Xiuyun Liu, Xiufeng Yang, He Duan, and Tieniu Wu College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China Key Laboratory for Geographical Process Analysis & Simulation, Wuhan, Hubei Province, China Correspondence should be addressed to Hailin Zhang; hailzhang@mail.ccnu.edu.cn Received 11 February 2020; Revised 20 August 2020; Accepted 16 September 2020; Published 28 September 2020 Academic Editor: Panagiotis Nastos Copyright © 2020 Lei Hua et al. )is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Based on the daily climate data from 839 meteorological stations covering the 2014–2017 period in the mainland of China, the Universal )ermal Climate Indices (UTCI) were calculated and the UTCI of 247 national 5A tourist attractions in the mainland of China are obtained with ordinary kriging interpolation method. )en, a spatial analysis of all the attractions was carried out based on UTCI. )e results showed that the mainland of China’s annual average UTCI is generally distributed as strip-belts along a latitudinal direction and the climate comfort level gradually decreases from south to north. Significant regional differences in climate comfort results are obtained between the southeast coastal areas and the northwest inland. It was found that the number of attractions with the best climate comfort level is relatively high in spring and autumn while it is less in summer and winter. Considering the climate comfort levels, the attractions are grouped into five categories of “comfortable during spring and autumn,” “comfortable during winter,” “comfortable during spring, autumn, and winter,” “comfortable during spring, summer, and autumn,” and “uncomfortable during the four seasons” to carry out the study for determining the most convenient period of the year in terms of climate comfort. Research on climate comfort has been around for nearly 1. Introduction a hundred years. As early as the 1920s, some scholars began Climate comfort, also known as thermal comfort, usually to pay attention to climate comfort research and not only refers to the meteorological conditions that humans can proposed but also established a variety of assessment con- ensure their normal physiological metabolism to feel cepts and models. Early research was based on statistical comfortable while not needing any adjustment for heat empirical indicators. Houhton FC proposed an equal prevention and/or cold protection [1]. )e climate comfort line including the variables of temperature and comfort research is based on the heat exchange between humidity, which also pioneered the use of empirical models for the comfort evaluation [9]. Early empirical indicators the human physiological sense and the atmosphere [2]. From the perspective of meteorology, it analyzes the mainly included Effective Temperature (ET) [10], Wet Bulb comfort index of human physiological touch under dif- Globe Temper (WBGT) [11], Temperature-Humidity Index ferent climatic conditions [3, 4]. Climate comfort is a key (THI) [12], and Wind Chill Index (WCI) [13, 14]. )e factor affecting the population’s mobility in the natural empirical indices are easy to calculate and be understood by environment so that it is also an important factor affecting the public. However, they contain unreasonable calculations tourism development. )e climate comfort conditions are to reduce the accuracy of the results so that they cannot meet an important determinant of tourists’ choice for desti- the basic requirements of the good correspondence between nations [5–8]. the assessment values and the human thermophysiological 2 Advances in Meteorology thermal conditions in China at both annual and seasonal scales state. )e empirical indices are also limited in terms of time and space scales [15]. For this reason, a reasonable human by using UTCI. It was also an important attempt to implement an application on climate comfort assessment on a larger scale comfort model is required to be based on the human body heat exchanger system by taking the influence of various [22]. )e mainland of China is experiencing a transfor- issues, such as environmental factors, human metabolic heat mation from traditional sightseeing to resort tourism so dissipation, and clothing thermal resistance into account that national 5A tourist attractions are the most popular [16]. With the development of biometeorology and com- destinations from this perspective. )is study emphasizes puter technology after the 1960s, a variety of indices in- a special evaluation of the comfort conditions for at- cluding Predicted Mean Vote (PMV) [17], Predicted tractions in the mainland of China based on UTCI by using an ordinary kriging interpolation method. )e re- Percentage of Dissatisfied (PPD) [14], Standard Effective Temperature (SET) [18], and Physiological Equivalent sults of this study are expected to be helpful for the op- timization of the tourism industry and the development of Temperature (PET) [19] were proposed for the study of climate comfort. However, the abovementioned indices are high-quality tourism destinations. replaced gradually due to the lack of precise calculation of the heat exchange between the human body and the envi- 2. Data and Methods ronment. With the development of multidisciplinary inte- gration, climate comfort research became increasingly 2.1. Data. )e meteorological data from 839 meteoro- rigorous and convenient. Under the umbrella of the WMO logical stations in the mainland of China is provided by Commission on Climatology, 45 scientists from 23 countries China Meteorological Science Data Sharing Network in the fields of thermal physiology, mathematical modeling, (Figure 1). )e data covers the 2014–2017 period and occupational medicine, meteorological data handling, and includes daily average temperature, water vapor pres- application development are organized to work together. sure, and wind speed parameters. )e dataset of national With the help of multidisciplinary research and taking the 5A tourist attractions (hereafter referred to as “attrac- responding factors, such as heat conduction, long- and tions”) is obtained from the China Tourism Yearbook short-wave radiation, and skin moisture evaporation, into published by the China National Tourism Administra- consideration, a Universal )ermal Climate Index is pro- tion in 2017. posed based on multinode model (Universal )ermal Cli- mate Index, UTCI) [15]. Compared with the existing 2.2. Methods models, the operational procedure of UTCI shows plausible responses to humidity and radiative loads from the envi- 2.2.1. Universal .ermal Climate Index and Climate Comfort ronment with higher temperatures as well as the wind in Grading. )is study uses a simplified UTCI calculation colder conditions [15]. Moreover, UTCI is the most com- method, which refers to the temperature that enables the prehensive and universal indicator of human thermal and human body to produce the same physiological response cold stress at present. Compared with other indicators, as the actual environment in the standard reference UTCI has the advantage of applying a variety of climate conditions. )e standard reference conditions for the types, being sensitive to changes in climate factors, and model include 0.5 m/s wind speed at 10 m, 50% relative better describing the process of change in the thermal ° humidity, temperature less than 29 C at 2 m, and 20 hPa environment. vapor pressure for temperature higher than 29 C at 2 m as Over the past 20 years, the tourism industry has developed well as the walking speed of 4 km/h for an adult which is rapidly in China, especially in the mainland of China. Many equivalent to a metabolic rate of 135 W/m . )e climate new tourism resources and tourism destinations are being comfort level is categorized according to UTCI as pro- established due to the great potential for tourism development vided in Table 1. )e calculation formula is defined by by keeping in mind that many tourism activities are climate- Accent et al. [29] as sensitive or climate-dependent [20]. Moreover, China’s climate has a high seasonal variability especially heat stress during UTCI � f T , T , V ,RH, (1) a mrt a summer and cold stress during winter [21]. On the other hand, most regions have favorable climate conditions for relatively a where T is the temperature ( C), T is the radiation mrt short period and it makes a significant impact on tourism [22]. temperature ( C), V is the wind speed (m/s), and RH is the In addition, China covers a wide area with a complex topog- relative humidity (%). raphy and diverse climate zones that lead to substantial regional )e calculation of UTCI is implemented by the software disparities in climate [21]. )ese factors highlight the necessity BioKlima 2.6. )e average radiant instead of temperature, of an assessment nationwide considering the climate condition which is required by the calculation of UTCI, is not directly in terms of tourism. Numerous studies are conducted to observed so that cloud data, air pressure, and solar elevation evaluate climate comfort conditions and their implications for angle are used as surrogate variables. Except for the solar tourism in China [20, 22–31]. However, most of these studies elevation angle, other factors are derived by using site ob- were carried out on a local scale, such as a province, city, or servation data. )e solar elevation angle, for instance, is resort. Ge et al. [22] provided a nationwide assessment of obtained by Advances in Meteorology 3 ° ° sin H � sin φ × sin δ + cos φ × cos δ × cos t, −90 ≤ H≤90 , t � 15(n − 12), (2) 1 − N δ � 23.45 × sin(N − 80.25) × , cos t � −tgφ × tgδ, where H is the solar elevation angle; t is the solar hour angle; Changbai Mountains as well as Inner Mongolia, Xinjiang, δ is the declination angle; n is the obtained observation data; Gansu in the northeast of China by accounting for 17.8%. N is the number of observations for days; and φ is the Only two attractions, the Aershan-Chaihe attraction in the latitude; the negative value is the sunrise angle, while the Inner Mongolia Autonomous Region and the Mohe Arctic positive value is the sunset angle. Village attraction in the northeastern of China, are located in the strip-belt with the annual climate comfort level of 4 since they are strongly affected by the Daxinganling and the 2.2.2. Kriging Interpolation Method. Ordinary kriging is an Xiaoxing’anling Mountains. )e strip-belt area has mod- estimation technique known as the best linear unbiased erate cold stress which causes to feel coolish. In addition, 6 estimator which uses the semivariogram method. Its in- attractions with a comfort level of 7 indicate that annual terpolation through variography provides an interpola- climate conditions have strong thermal stress during the tion estimate using the observed values and their spatial year because of being located in the Hainan Island, on the relationships. Ordinary kriging interpolation, which is northern edge of the tropics with high temperature, hu- detailed in the literature [33], is used in this study. midity, and average radiation all year round. )e UTCI for all 839 meteorological stations is calcu- lated as the first step. )en, spatial interpolation is per- formed for each cell with 10km∗10km grid points over the 3.2. Seasonal Variability. Figure 3 shows the spatial distri- study area by the ordinary kriging method using ArcGIS software. According to the criteria listed in Table 1, climate bution of the climate comfort level with respect to seasons. )e climate comfort distribution is similar during spring and comfort level is assigned for each attraction based on the UTCI value. Finally, the spatial distribution of climate autumn. )e attractions have significant regional differences in different seasons with strip-like spatial distribution comfort level for 247 national 5A tourist attractions is analyzed. characteristics. As shown in Table 2 and Figure 3, the overall number of attractions with good climate comfort is obtained relatively higher in spring and autumn while it is less in 3. Results summer and winter. )e spatial distribution of the comfortable attractions 3.1. Annual Variability. As shown in Figure 2, the annual average climate comfort level in the mainland of China is during spring and autumn is similar. )ey are mainly concentrated in the areas along the rivers and oceans in- generally distributed in a strip-like spatial pattern along a latitudinal direction. )e climate comfort level also gradually cluding Jiangsu, Anhui, Hunan, Hubei, Guizhou, Zhejiang, and Fujian. Due to the influence of monsoon climate and decreases from southeast to northwest. Due to the influence of topographic factors, the Qinghai-Tibet Plateau and the aerosol changes and the significant thermal inertia of oceans Tarim Basin have an island-like spatial pattern. )e central and rivers [34, 35], the temperature in the vicinity of these part of the Qinghai-Tibet Plateau represents a climate areas regulates these areas, making these areas cooler in comfort level of 4 due to its high altitude on the plateau and summer, warmer in winter, and more comfortable in spring and autumn. Under the influence of subtropical high, the mountains. )e Tarim Basin has an island-like spatial pat- tern with a climate comfort level of 5 due to its higher spatial distribution of the attractions in the summer season is the most noticeable one because the most comfortable areas surrounding. )e annual average climate comfort evaluation results are moved northward. )e best climate comfort levels are located mostly in high-latitude and high-altitude regions, showed that there are 195 attractions with a climate comfort level of 6, which is the optimal level for a human, indicating mainly in Xinjiang, Inner Mongolia, northern Qinghai, that the climate is comfortable. )is group accounts for 80% Gansu, northwestern Shanxi, Heilongjiang, Hebei, Liaoning, of all tourism locations (Table 2). )ese tourist attractions and Beijing. are mainly located in the southeast where Yanshan, Taihang, )e number of attractions with the best climate comfort Qinling, Wushan, and Hengduan Mountains are found level of 6 during autumn is the highest and it accounts for including Shandong, Henan, Hubei, Chongqing, Guizhou, 83%. In winter, the number of areas that experience “no thermal stress” in the same category is only 64 and located in Yunnan, Anhui, Jiangsu, and Zhejiang in the central and eastern regions of China. Forty-four attractions with the the south of the middle and lower reaches of the Yangtze River because of the Siberian high-pressure influence. On comfort level of 5 and slight cold stress mainly occurred in the areas of Tianshan, Kunlun, Qilian, Helan, Yanshan, and the other hand, the number of attractions with the climate 4 Advances in Meteorology N N 250 500 1,500 0 1,000 km 0 250 500 1,000 1,500 Weather station km National boundary National 5A tourist attraction Provincial administrative region National boundary Thermal perception 4 6 Figure 1: Distribution of meteorological stations in the mainland 5 7 of China. Figure 2: Spatial distribution of annual average climate comfort in the mainland of China. Table 1: UTCI equivalent temperatures in terms of thermal stress and climate comfort level [32]. Table 2: )e number of national 5A tourist attractions with respect Climate comfort level UTCI ( C) Stress category to climate comfort levels in the mainland of China (the total Freezing (1) <−40 Extreme cold stress number of scenic spots is 247). Chilly (2) −40∼−27 Very strong cold stress Cold (3) −27∼−13 Strong cold stress Level 3 Level 4 Level 5 Level 6 Level 7 Coolish (4) −13∼0 Moderate cold stress Annual — 2 44 195 6 Cool (5) 0∼9 Slight cold stress Spring — 6 48 185 7 Comfortable (6) 9∼26 No thermal stress Summer — — 2 113 132 Warm (7) 26∼32 Moderate heat stress Autumn — 1 27 206 13 Hot (8) 32∼38 Strong heat stress Winter 13 64 105 61 4 Hottish (9) 38∼46 Very strong heat stress Note: “—” indicates that there is no national 5A tourist attraction for the Torrid (10) >46 Extreme heat stress corresponding level. comfort level of 5 is the highest (namely, 108) where the below 1000 meters. )e numbers of comfortable attractions climate conditions with moderate cold stress are not suitable during “spring, autumn, and winter” (category II) and for travel. “comfortable during winter” (category V) are 51 and 64, For an extended study, the seasonal comfort charac- respectively. )ey are mainly distributed in the lower-lati- teristic is classified into five categories of “comfortable tude areas of the south of the middle and lower reaches of the during spring and autumn,” “comfortable during winter,” Yangtze River, including Yunnan, Guizhou, Hunan, Jiangxi, “comfortable during spring, autumn, and winter,” Zhejiang, Fujian, Guangdong, and Guangxi. )ere are 61 “comfortable during spring, summer, and autumn,” and comfortable attractions during “spring, summer, and au- “uncomfortable during the four seasons (Figure 4).” tumn” (category III), distributed in the central part of China, )e majority (72%) of the attractions with the best near the Taihang and Qinling Mountains including Beijing, climate comfort level of 6 are located in category I (com- Hebei, Shanxi, Shaanxi, southern Sichuan, Yunnan, and fortable during spring and autumn) according to Figure 4. Guizhou. )ese tourist attractions are characterized by )ese tourist attractions are located along the southeast of having relatively longer comfortable days for tourists. Only 7 the line formed by Taihang, Qinling, and Wushan Moun- attractions in the south of Hainan Island are obtained to be tains including north of Hainan Island with an elevation “uncomfortable during the four seasons” (category V) where Advances in Meteorology 5 Spring Summer Autumn Winter 0 825 1,650 2,475 km National 5A tourist attraction National boundary Thermal perception Figure 3: Spatial distribution of climate comfort levels of national 5A tourist attractions with respect to seasons. high temperature and humidity is observed throughout the 4. Discussion year because of the low latitudes of the tropical region. )e )is study is based on daily climate data of meteorological best climate comfort level of 6 occurs only in January and stations in the mainland of China. )e density of December. 6 Advances in Meteorology climate change [38–41]. Aerosol cooling of the surface and reduction of local water evaporation and water vapor content in the atmosphere by reducing thermal differ- ences between land and sea and increasing atmospheric stability and decreasing incident solar radiation have resulted in a weakening of monsoon circulation and a decrease in monsoon precipitation [42, 43]. Atmospheric aerosol particles and precipitation are more complex: on the one hand, the increase of aerosol concentration in dry areas or seasons may lead to the decrease of cloud droplet effective radius, which may delay or even inhibit pre- cipitation [44, 45]. On the other hand, precipitation is the I II III IV V main way of wet removal of aerosol particles [46, 47]. Figure 4: )e number of national 5A tourist attractions with )ese will affect the climate comfort between regions different comfort categories. I: “comfortable during spring and [44–51]. In the future, the study of climate comfort autumn”; II: “comfortable during spring, autumn, and winter”; III: should consider the influence of these factors and im- “comfortable during spring, summer, and autumn”; IV: “un- prove the study of climate comfort. comfortable during the four seasons”; and V: “comfortable during )e findings in this study are expected to help to op- winter.” timize the tourism industry and facilitate the development of national 5A tourist attractions in the mainland of China. )ere are fewer attractions in the northern and southwest of meteorological stations is gradually decreasing from the China although these regions have the best climate comfort level during summer. )us, more high-quality resorts in southeast coastal areas to the northwest inland areas due to the uneven geographical distribution of the site. For this these regions should be developed to attract tourists. In the southern parts of Hainan Island, for instance, winter resorts reason, the accuracy of the climate comfort evaluation re- sults is inevitably affected to some extent. Quite a fair should be promoted to attract tourists who pursue com- fortable climate conditions during winter. number of national 5A tourist attractions are located in the mountainous and water areas so the impact of altitude and water thermal inertia on climate comfort are represented. 5. Conclusions On the other hand, it is also necessary to integrate the Digital Elevation Model (DEM) data to improve the accuracy of the )is research aims to carry out climate comfort evaluation of climate comfort evaluation [36]. Based on the seasonal and national 5A tourist attractions in the mainland of China. annual scale analysis, the impact of extreme and severe Our results show that the annual average climate comfort weather conditions are smoothed and concealed. In order to level in the study area is generally distributed in a strip-like observe the actual fluctuations of climate comfort levels, the spatial pattern along the latitudinal direction while the research should be carried out on smaller time scales [34]. climate comfort level gradually decreases from south to Although the UTCI model is currently a state-of-the-art tool north. And there are significant regional differences in terms for climate comfort assessment, the standard scale can be of climate comfort between the southeast coastal areas and adjusted considering the people’s perception of the thermal the northwest inland. environment, their physiological processes change, and A similar spatial distribution of climate comfort is ob- adoption for the study area [36]. )e assumption of standard tained for spring and autumn. )e overall number of na- personal characteristics such as age, gender, physical fitness, tional 5A tourist attractions located in the comfortable metabolic rate, and clothing behavior in this study is also climate zone with the climate comfort level of 6 is higher in another factor that brings some uncertainty to the results spring and autumn while it is less in summer and winter. To [32, 34, 36]. By taking the abovementioned factors into extend the study, seasonal climate comfort levels are clas- account, the results of this study would be more practical sified into five categories of “comfortable during spring and and accurate. autumn,” “comfortable during winter,” “comfortable during In addition, climate comfort is not fixed, and there are spring, autumn, and winter,” “comfortable during spring, many influencing factors in the change of climate factors. summer, and autumn,” and “uncomfortable during the four Not all of the above research can be fully summarized seasons.” )e best climate comfort level is obtained to be [35, 37]. )e climate is affected by the change of solar during “spring and autumn” where the associated attractions radiation, the change of aerosol, and the change of at- are located between the southeast of the line formed by mospheric circulation, which leads to the constant Taihang, Qinling, and Wushan Mountains as well as north of change of climate. 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Journal
Advances in Meteorology – Hindawi Publishing Corporation
Published: Sep 28, 2020