The Distribution of Climate Comfort Duration for Forest Therapy Has Temporal and Regional Heterogeneity in Xinjiang

Abstract

Climatic comfortability serves as a crucial factor in tourism decision making; however, there remains a gap in evaluating the climate comfort conditions specifically for forest therapy. We developed a new index—Forest Therapy Climate Comfort Index (FTCCI)—to evaluate the climate comfort conditions for forest therapy by integrating the Temperature (T), Temperature and Humidity Index (THI), and Wind Efficiency Index (WEI). A total of 26 potential forest therapy bases were selected from the protected areas in Xinjiang and divided into five clusters: Aksu cluster, Hami cluster, Altai cluster, Ili and its surrounding cluster, and Urumqi and its surrounding cluster. Based on the monthly observation data from 25 surface meteorological stations in Xinjiang, spanning from 1994 to 2023, employing the Co-Kriging interpolation method, we explored the spatial–temporal variation in FTCCI from June to September and made clear the climate comfort duration across 26 bases in Xinjiang. The results indicated that (1) The variation in T, THI, and WEI in 26 bases demonstrated a consistent pattern of temporal variation. July emerged as the optimal month, followed closely by August, with most indices in both months falling within the comfort level. Conversely, September proved to be the least favorable month due to frigid conditions and discomfort for the human body, whereas June’s sensation was slightly more tolerable. (2) The distribution of T, THI, and WEI showed regional heterogeneity. The Urumqi and its surrounding cluster displayed the most favorable conditions for forest therapy, whereas the Aksu cluster showed the poorest performance. (3) There were differences in both FTCCI and climate comfort duration among various clusters in Xinjiang. Overall, excluding Tomur Peak and Nalati (July and August), the remaining 24 bases offered ideal climate comfort conditions for forest therapy from mid to late June through August. Notably, the bases in Urumqi and its surrounding cluster had the longest climate comfort duration, ranging from 3.5 to 4 months. Therefore, reliance on the unique climate, resource, and geographical condition of each base is crucial in creating special forest therapy products that cater to the diverse health needs of tourists.

1. Introduction

Urbanization is often paralleled with a rise in population health issues [1]. Individuals in urban environments frequently experience psychological and physiological stress, resulting in a prolonged sub-health state [2], forcing people to seek stress reduction and healthy lifestyles. Research has demonstrated that engaging with nature can effectively alleviate both physical and mental stress [3], while simultaneously enhancing health, well-being, and cognitive capabilities [1]. Since the early 21st century, numerous East Asian and European countries have embarked on utilizing urban forests, peri-urban forests, and protected areas as avenues to ameliorate public health and well-being [4,5]. In this context, forest therapy has emerged as a novel approach to forest tourism, aimed at alleviating stress and fostering health [3,6]. Furthermore, in the process of forest therapy tourism, the pursuit of comfort is the basic need of tourists. The comfort within the natural environment is profoundly influenced by climatic conditions, typically assessed through climate comfort [7]. Climate comfort not only affects the length of the local tourist season [8], but also plays a decisive role in enhancing the attractiveness of tourist destinations [9,10]. However, the vast amount of information pertaining to the local climate can often be overwhelming for visitors, making it challenging to extract valuable references from it. Hence, there is an urgent need for a more concise way to directly display the climate comfort conditions of a region to measure whether it is suitable for forest therapy tourism.

Globally, research on using climate comfort to evaluate the suitability of climate conditions for tourism activities in a specific region has attracted much attention and become a trending topic. In Southeast Asia, Europe, North America, and other countries with prosperous tourism, scholars have determined the optimal months for tourism by analyzing the temporal and spatial trends of climate comfort [11,12,13,14,15]. Concurrently, they examined how climate comfort impacts tourists’ behavioral decisions and the potential implications these have on local tourism development [12,15,16,17]. This includes analyzing the linear correlation between tourist arrivals and climate comfort [14,18], investigating how tourists select their travel itineraries based on climate conditions [9,11], and evaluating in detail the specific impacts of climate conditions on tourist behavior [19]. In China, most scholars generally take provinces, regions, or national tourist attractions as research objects, and have found that China’s climate comfort reveals obvious spatial heterogeneity and differences between distinct climate zone types [20,21]. Apart from certain regions in Xinjiang, Qinghai, Tibet, and the Northeast, the spatial distribution of annual and seasonal climate comfort levels tends to shift from comfortable to cold with increasing latitude [21,22,23]. Additionally, a pronounced regional disparity in climate comfort exists between the southeastern coastal area and the northwestern inland region [21]. Furthermore, some scholars have delved into the underlying factors driving the temporal and spatial variations in climate comfort, considering various perspectives such as urban green space exposure [24], population density [25], and global warming [26]. In Xinjiang, several researchers have studied the spatial and temporal pattern and evolution trend of the tourism climate comfort period, ultimately yielding insights into the regional and seasonal distributions that are optimal for tourism activities [8,27,28]. These studies offer invaluable references for us to have a more comprehensive understanding of tourism climate comfort.

In the above research on tourism climate comfort, numerous scholars achieve their research goals by constructing multiple assessment models, which are usually developed based on linear equations of factors such as temperature, relative humidity, wind speed, and sunshine hours [28]. Prominent examples include the Temperature and Humidity Index (THI) [7,8,18], Wind Efficiency Index (WEI) [7,8,29], Wind Chill Index (WCI) [27,30,31], Clothing Index (ICL) [8,25,30], Universal Thermal Climate Index (UTCI) [21,28,32], Tourism Climate Index (TCI) [18,33], and Holiday Climate Index (HCI) [10,18,33]. These indicators are easily calculable and predictable making them widely utilized. However, these indices primarily cater to traditional tourism, and there is a gap in research on the evaluation of climate comfort specifically for forest therapy tourism. In the similar realm of forest therapy tourism, there is only one Iranian scholar who has conducted an in-depth exploration of the climate comfort on people’s health tourism, utilizing four indicators: Baker’s Index, THI, Minard Index, and Wet-Dry Temperature Index [34]. However, it is unfortunate that this scholar’s research primarily focuses on the individual impact of each index on people’s health tourism, falling short of developing a comprehensive index capable of systematically assessing the overall effect of climate comfort.

As the principal natural forest region in northwest China, Xinjiang has a vast distribution of mountainous natural forests in the Tianshan and Altai Mountains [35]. It not only contains diverse forest landscapes, but also has numerous healthcare resources such as grasslands, lakes, hot springs, sand therapy, and Chinese herbal medicine. These features have laid a solid foundation for the forest therapy tourism development in Xinjiang. Moreover, the tourism climate comfort period in northern Xinjiang is primarily concentrated from May to September [30], while mountainous regions at higher altitudes have a shorter duration of climate comfort days [27]. Therefore, considering the climate comfort for forest therapy, this study specifically focuses on the timeframe from June to September. On this basis, targeting 26 potential forest therapy bases in Xinjiang, this study develops a new Forest Therapy Climate Comfort Index (FTCCI) to evaluate the climate comfort conditions for forest therapy by combining temperature, THI, and WEI. The application scope of FTCCI is exclusively confined to evaluating climate comfort conditions for forest therapy, omitting other multifaceted and comprehensive requirements involved in such activities. Subsequently, the spatial and temporal patterns of FTCCI in 26 potential forest therapy bases in Xinjiang from June to September are quantitatively evaluated, and the climate comfort duration of each base is defined.

It is of great theoretical and practical importance for this research. On the one hand, this study imparts academic support for the quantitative evaluation of climate comfort conditions for forest therapy, assisting tourists in selecting the most climatically suitable time and location for forest therapy tourism. On the other hand, it provides a valuable reference for the planning of layout planning, facility configuration, and activity arrangements within forest therapy bases, thereby enabling the local government to optimize economic and social benefits. The scientific questions of this study are as follows: (1) How do researchers quantitatively evaluate the suitability of carrying out forest therapy activities from the perspective of climate comfort? (2) What are the spatial and temporal patterns of climate comfort conditions for forest therapy in Xinjiang? (3) What are the differences of climate comfort duration for forest therapy across diverse regions in Xinjiang?

2. Material and Methods

2.1. Study Area

The Xinjiang Uygur Autonomous Region is situated at China’s northwest border, covering an area of 1,664,900 km², accounting for one-sixth of China’s total land area [28]. The topography of Xinjiang is renowned as “two basins sandwiched by three mountains”. Located in the hinterland of the Eurasian continent, Xinjiang features a typical temperate continental arid climate, characterized by extreme temperature fluctuations, scant precipitation, and dry weather [36]. With its vast territory and abundant resources, Xinjiang has an integration of healthcare resources from forests, grasslands, wetlands, deserts, and hot springs, thereby laying a solid foundation for the development of forest therapy tourism.

2.2. Study Object

Xinjiang is abundant in natural forest resources, primarily concentrated in the mid-mountain belts of the Tianshan and Altai Mountains at altitudes ranging from 1400 to 2800 m [37]. The development of forest therapy tourism in Xinjiang is intricately linked to the support of numerous healthcare resources, with forest resources serving as the core resource base for such tourism. However, forest therapy tourism, as a form of high-consumption tourism, relies not solely on the abundance of forest resources but also necessitates the backing of comprehensive tourism infrastructure. Furthermore, distinctive healthcare resources play a vital role in enriching the essence of forest therapy tourism and elevating the sense of experience and satisfaction among tourists. Therefore, the selection principle for potential forest therapy bases in Xinjiang is principally determined by three key considerations: the distribution of forest resources, the foundation of tourism facilities, and the availability of distinctive healthcare resources. Drawing upon the protected areas of forest ecosystems in Xinjiang, this study prioritized tourist attractions rated 4A or higher, as well as existing forest therapy pilot bases. Subsequently, protected areas with distinctive healthcare resources were considered, ultimately resulting in a total of 26 potential forest therapy bases (Table S1 and Figure 1a).

Altitude significantly impacts both human physiological functions and mental states [38]. Research indicates that altitudes ranging from 500 to 3000 m are considered optimal for human health and well-being [39,40]. Regions below 500 m, due to their relatively low terrain, often experience a humid and hot climate, which can impose a certain physiological burden on individuals. Conversely, altitudes exceeding 3000 m, with lower atmospheric pressure and oxygen partial pressure, are prone to hypoxia, which can easily lead to altitude sickness [38,41]. The above 26 potential forest therapy bases span a diverse range of altitudes, ranging from 370 to 7346 m. Nevertheless, not all altitude regions encompassed within these bases are amenable to forest therapy activities. Therefore, the altitude range favorable for forest therapy activities was narrowed down to 500–3000 m. Subsequently, the forest therapy optimized areas within each base were delineated (Figure 1a), serving as focal point of this study.

Based on a thorough consideration of the tourism development layout in Xinjiang, formulated by the Xinjiang Department of Culture and Tourism [42], we prioritized the proximity and transportation convenience of potential forest therapy bases and the alignment of forest therapy tourism development directions. Incorporating the principle of administrative region coordination and referencing the existing plan for Xinjiang’s tourism climate regionalization [43], we have categorized the 26 potential forest therapy bases in Xinjiang into five distinct clusters (Table S1 and Figure 1b): Aksu cluster (Tomur Peak), Hami cluster (Hami Tianshan), Altai cluster (comprising Kanas, Baihaba, Jiadengyu, Shenzhongshan, Altai Hot Spring, and White Birch), Ili and its surrounding cluster (including Nalati, Kunes, West Tianshan, Kalajun, Kesang Cave, Xiata, Sayram Lake, Daxigou, Tangbula, and Qiaxi), as well as Urumqi and its surrounding cluster (encompassing Wusu Foshan, Lujiao Bay, Tianshan Grand Canyon, Jiangbulak, Urumqi Tianshan, Tianshan Tianchi Lake, Tianchi Forest, and Cheshi).

2.3. Data

The meteorological data and stations utilized in this paper are sourced from the historical dataset of monthly surface meteorological observations provided by the China Meteorological Data Network (http://data.cma.cn/ 10 February 2024) spanning the past 30 years (1994–2023). Twenty-five meteorological stations in Xinjiang are carefully chosen, situated in proximity to the potential forest therapy bases. The data cover the monthly average temperature, average relative humidity, average wind speed, average sunshine hours from June to September. The DEM data are based on the 12.5 m DEM data in Xinjiang, which are derived from the Third Xinjiang Scientific Expedition Program, “Scientific Research Data Platform and Standard System Construction (2021xjkk1300)”. The vector data of 26 potential forest therapy bases in Xinjiang protected areas are obtained from the Third Xinjiang Scientific Expedition Program, “Investigation of Xinjiang Protected Areas and Scientific Expedition of National Park Potential Areas (2021xjkk1200)”.

2.4. Methods

2.4.1. Assessment of Climate Comfort Conditions for Forest Therapy

Owing to the scarcity of methods for evaluating climate comfort conditions in forest therapy at present, this study aims to develop a new index—Forest Therapy Climate Comfort Index (FTCCI)—that accurately reflects the suitability for forest therapy activities within a certain period or region. Climate comfort primarily considers the adaptability of healthy individuals to climatic factors, including temperature, humidity, wind speed, and sunshine without the aid of any cooling or heating equipment or facilities [7,26]. Among various climatic factors, temperature not only plays an important role in maintaining human health [34], but also greatly affects the healthcare resources generated by forest environment [44]. In domestic practice, models like THI and WEI have become widely utilized indicators in meteorological and geographical circles for evaluating climate comfort [45]. Furthermore, both indices have been officially codified as the national standard for climatic suitability evaluating human settlements and have gained widespread recognition nationwide [46]. Consequently, the T, THI, and WEI should be considered when assessing the climate comfort conditions for forest therapy.

• Temperature (T)

The most comfortable temperature is slightly different in the four seasons. In terms of annual temperature, the ideal range for forest therapy activities is between 18 °C and 26 °C [38,39]. The classification of temperature is shown in

Table 1. The classification of climatic indicators.

Rank	Feeling	T	THI	WEI	Description of Feeling of Healthy People	Score
1	Frigid	<15 °C	<14.0	<−400	Extremely cold, uncomfortable	1
2	Cold	15~18 °C	14.0~16.9	−400~−300	Relative cold, a little uncomfortable	3
3	Comfortable	18~26 °C	17.0~25.4	−299~−100	Comfortable	5
4	Hot	26~30 °C	25.5~27.5	−99~−10	Relative hot, a little uncomfortable	3
5	Sweltering	>30 °C	>27.5	>−10	Extremely hot, uncomfortable	1

.

2.

Temperature and Humidity Index (THI)

The THI comprehensively captures the human body’s perception of ambient temperature and humidity, calculated by Equation (1) [46]:

$$THI=T-0.55\left(1-RH\right)\left(T-14.4\right)$$

(1)

where $THI$ is the Temperature and Humidity Index; $T$ is the average temperature (°C); $RH$ is the average relative humidity (%).

3.

Wind Efficiency Index (WEI)

The WEI comprehensively characterizes the human body’s perception of wind, temperature, and sunshine, which is calculated by Equation (2) [46]:

$$WEI=-\left(10\sqrt{WS}+10.45-WS\right)\left(33-T\right)+8.55S$$

(2)

where $WEI$ is the Wind Efficiency Index; $WS$ is the average wind speed (m/s); $T$ is the average temperature (°C); $S$ is the average sunshine duration (h/d).

Drawing from previous research findings [39,40,46], this study categorizes T, THI, and WEI into five distinct levels, as outlined in Table 1. In this classification, a score of 5 is assigned when the human body feels comfortable, while a score of 3 is given when the body experiences either cold or hot, and a score of 1 is awarded when the body feels both frigid and sweltering.

4.

Forest Therapy Climate Comfort Index (FTCCI)

To develop the FTCCI, this study adopted the expert consultation method to assign weights for three key indicators: T, THI, and WEI. For this purpose, this study invited 24 well-known industry experts with extensive theoretical research or rich practical experience in forest therapy, tourism meteorology, and other related fields to participate. We sent score sheets to these experts and received them all in return. During the scoring process, the experts are required to make independent judgments on the importance of the FTCCI based on T, THI, and WEI. The scoring criteria are as follows: a full score of 10 means that the index is of the highest importance to FTCCI; a score of 0 signifies that the index is not important to FTCCI; the other levels of importance score range between 0 and 10 points (with non-integer score values allowed), and the sum of the importance scores of the three indicators must equal 10 points. Drawing from their collective insights and expertise, we derive the following weighting model and classification (

Table 2. The classification of FTCCI and score of climate comfort duration.

Grade	Forest Therapy Climate Comfort Index	Forest Therapy Suitability	Climate Comfort Duration Score/Month
Level I	4 <$FTCCI$≤ 5	the most optimal for forest therapy	1
Level II	3 <$FTCCI$≤ 4	greater suitable for forest therapy	1
Level III	2 <$FTCCI$≤ 3	generally suitable for forest therapy	0.5
Level IV	1 <$FTCCI$≤ 2	unsuitable for forest therapy	0
Level V	0 <$FTCCI$≤ 1	extremely unsuitable for forest therapy	0

), and the calculation equation is outlined below:

$$FTCCI=0.4X_T+0.35X_{THI}+0.25X_{WEI}$$

(3)

where $FTCCI$ is the forest therapy climate comfort index; $X_T$, $X_{THI}$, and $X_{WEI}$ are graded scores of Temperature, Temperature and Humidity Index, and Wind Efficiency Index, respectively. The values 0.4, 0.35, and 0.25 are the weight coefficients of each index. A score of 1 is awarded to Level I and Level II, signifying that the entire month is optimal for forest therapy. Conversely, a score of 0.5 is given to Level III, indicating that the middle to early or middle to late parts of the month are more conducive for such activities. Lastly, a score of 0 is assigned to Level IV and Level V, meaning that the entire month is not suitable for forest therapy.

2.4.2. Co-Kriging Spatial Interpolation Method

The Co-Kriging method is a multivariate statistical interpolation method, which integrates data from both target and auxiliary variables to map the spatial distribution of the target variables [47]. Among the diverse spatial interpolation methods, Co-Kriging interpolation stands out for its ability to comprehensively consider both the spatial autocorrelation of target variables and their intricate relationships with other auxiliary variables [48]. Therefore, the Co-Kriging method is implemented to interpolate meteorological data for the forest therapy optimized areas of 26 bases in Xinjiang. The interpolation process specifically focuses on target variables such as T, THI, and WEI, while elevation serves as an auxiliary variable to enhance the accuracy of the interpolation.

2.5. Data Processing

The ArcGIS 10.8 software was used for spatial interpolation, and the average values of T, THI, and WEI were calculated by grids. Meanwhile, ANOVA variance analysis was performed using SPSS 27.0 software.

3. Results

3.1. The Spatial—Temporal Variation in Temperature

In June, the Temperature (T) primarily ranged from 15 °C to 22 °C, among which Tomur Peak, Nalati, and Kunes were lower than 15 °C (Table S2 and Figure 2a). Moreover, the T in the Urumqi and its surrounding cluster ranged from 18 °C to 26 °C, which was conducive for forest therapy activities (Figure 2b). In July, the T principally fell within the range of 18 °C to 25 °C, creating an ideal climate environment for forest therapy (Figure 2c,d). Excluding the low altitudes of Urumqi Tianshan and Tianshan Tianchi Lake, the T was predominantly maintained at 26 °C~28 °C. In August, the T was mainly 17 °C~24 °C, among which Tomur Peak was the lowest, followed by Nalati and Kunes (Figure 2e). Meanwhile, aside from Tomur Peak and Nalati, the T in the remaining 24 bases was at a comfortable level (Figure 2f). In September, the T chiefly ranged from 8 °C~20 °C, among which, Tomur Peak and Nalati held the lowest temperatures, averaging between 7 °C~8 °C, while Urumqi Tianshan and Tianshan Tianchi Lake recorded the highest temperatures, peaking at 20 °C~21 °C (Figure 2g). It was observed that only a few bases, including Urumqi Tianshan, Tianshan Tianchi Lake, Tianchi Forest, and the low altitudes of Cheshi, showed a comfortable level (Figure 2h).

Overall, the T in 26 potential forest therapy bases manifested significant temporal and spatial differences from June to September (

Table 3. Variance analysis of T in different potential forest therapy base clusters.

Potential Forest Therapy Base Clusters	June	July	August	September
Aksu cluster	13.1 Cc	19.1 Ca	17.2 Db	7.4 Cd
Hami cluster	15.7 Bc	21.3 Ba	19.4 Cb	10.5 Bd
Altai cluster	16.6 Bc	23.0 Aa	21.0 Bb	9.9 BCd
Ili and its surrounding cluster	15.8 Bc	21.3 Ba	19.5 Cb	9.7 BCd
Urumqi and its surrounding cluster	21.7 Ab	23.9 Aa	22.6 Aab	18.1 Ac

Note: capital letters indicate that the T in the same month varies significantly in different potential forest therapy base clusters; lowercase letters indicate that the T in the same potential forest therapy base clusters varies significantly in different months.

). The T across the five diverse clusters proved a consistent variation pattern: July was the highest, followed by August, June, and September. In different months, the T was the highest in the Urumqi and its surrounding cluster and the lowest in the Aksu cluster. In July and August, the T in the Altai cluster surpassed that of the Hami cluster and the Ili and its surrounding cluster, while the T in these three clusters was similar in June and September.

3.2. The Spatial—Temporal Variation in Temperature and Humidity Index

In June, the Temperature and Humidity Index (THI) mainly fell within the range of 13.0 to 20.9 (Table S2 and Figure 3a). Apparently, the Urumqi and its surrounding cluster and the lower altitudes of Qiaxi showed a THI ranging from 17.0 to 25.4, making them suitable for forest therapy (Figure 3b). In July and August, the THI primarily converged within the range of 17.0 to 22.9, which was at a comfortable level (Figure 3d–f). In September, the THI generally varied between 8.0 and 18.9 (Figure 3g), and only Urumqi Tianshan, Tianshan Tianchi Lake, and Tianchi Forest fell within the comfortable level (Figure 3h).

In general, the temporal and spatial variation in THI in 26 potential forest therapy bases had significant differences from June to September (

Table 4. Variance analysis of THI in different potential forest therapy base clusters.

Potential Forest Therapy Base Clusters	June	July	August	September
Aksu cluster	13.7 Cc	18.7 Da	17.1 Db	8.9 Cd
Hami cluster	15.2 Bc	19.6 CDa	18.2 Cb	11.4 Bd
Altai cluster	15.9 Bc	20.9 Aa	19.4 ABb	10.7 BCd
Ili and its surrounding cluster	15.5 Bc	19.9 BCa	18.5 BCb	10.5 BCd
Urumqi and its surrounding cluster	18.9 Ab	20.8 ABa	19.7 Ab	16.6 Ac

Note: capital letters indicate that the THI in the same month varies significantly in different potential forest therapy base clusters; lowercase letters indicate that the THI in the same potential forest therapy base clusters varies significantly in different months.

). In the five different clusters, July had the highest THI, followed by August, June, and September. Except for July, the THI in Urumqi and its surrounding cluster was slightly lower than that in the Altai cluster, and the other three months were the highest. The THI in Aksu cluster was at its lowest from June to September. From June to August, the THI in the Altai cluster was higher than that in Ili and its surrounding cluster, as well as the Hami cluster.

3.3. The Spatial—Temporal Variation in Wind Efficiency Index

In June, the Wind Efficiency Index (WEI) generally varied from −350 to −140. The WEI in the Urumqi and its surrounding cluster was within the range of −299 to −100, resulting in support for forest therapy. Furthermore, most areas in Tangbula, Kunes, Qiaxi, Kalajun, and Kesang Cave were at the comfortable level (Table S2 and Figure 4a,b). In July, the WEI basically ranged from −270 to −70 (Figure 4c). Apart from the WEI in most areas of Urumqi and its surrounding cluster which held a relatively hot feeling, the remaining bases were at a comfortable level (Figure 4d). In August, the WEI broadly varied between −320 and −100 (Figure 4e). Despite the THI in the low altitudes of Tianshan Tianchi Lake which were at a hot level, the high altitudes of Tomur Peak, Nalati, and Kunes were at a cold level, and most areas within the 26 forest therapy optimized areas kept a comfortable level (Figure 4f). In September, the WEI mainly concentrated in the range of −260 to −520 (Figure 4g), and only Urumqi Tianshan, Tianshan Tianchi Lake, and Tianchi Forest were at a comfortable level (Figure 4h).

In general, WEI showed significant differences in different time and space scales (

Table 5. Variance analysis of WEI in different potential forest therapy base clusters.

Potential Forest Therapy Base Clusters	June	July	August	September
Aksu cluster	−372 Cc	−272 Ca	−311 Cb	−511 Bd
Hami cluster	−327 Bc	−204 Ba	−256 Bb	−465 Bd
Altai cluster	−323 Bc	−192 Ba	−234 Bb	−498 Bd
Ili and its surrounding cluster	−313 Bc	−213 Ba	−251 Bb	−465 Bd
Urumqi and its surrounding cluster	−187 Ab	−111 Aa	−150 Ab	−314 Ac

Note: capital letters indicate that the WEI in the same month varies significantly in different potential forest therapy base clusters; lowercase letters indicate that the WEI in the same potential forest therapy base clusters varies significantly in different months.

). In the five clusters, the WEI indicated the same time change rule: July > August > June > September. From June to September, the WEI in Urumqi and its surrounding cluster was the highest, whereas the Aksu cluster had the lowest values. Moreover, the difference in WEI between the Altai cluster, Hami cluster, and Ili and its surrounding cluster was not significant.

3.4. The Spatial—Temporal Variation in FTCCI and Climate Comfort Duration

In June, the Forest Therapy Climate Comfort Index (FTCCI) in eight bases of Urumqi and its surrounding cluster was at Level I; Tangbula and Qiaxi were at Level II; Nalati and Tomur Peak were at Level IV, and the remaining 14 bases were at Level III (Figure 5a,

Table 6. The grade of FTCCI and climate comfort duration in different potential forest therapy base clusters.

Potential Forest Therapy Base Clusters	Forest Therapy Optimized Areas	The Grade of FTCCI				Climate Comfort Duration/Month
		June /Level	July /Level	August /Level	September /Level
Aksu cluster	Tomur Peak	IV	I	II	V	2 (July and August)
Hami cluster	Hami Tianshan	III	I	I	V	2.5 (mid to late June, July, and August)
Altai cluster	Kanas	III	I	I	V	2.5 (mid to late June, July, and August)
	Baihaba	III	I	I	V	2.5 (mid to late June, July, and August)
	Jiadengyu	III	I	I	V	2.5 (mid to late June, July, and August)
	Shenzhongshan	III	I	I	V	2.5 (mid to late June, July, and August)
	Altai Hot Spring	III	I	I	V	2.5 (mid to late June, July, and August)
	White Birch	III	I	I	V	2.5 (mid to late June, July, and August)
Ili and its surrounding cluster	Nalati	IV	I	II	V	2 (July and August)
	Kunes	III	I	I	V	2.5 (mid to late June, July, and August)
	West Tianshan	III	I	I	V	2.5 (mid to late June, July, and August)
	Kalajun	III	I	I	V	2.5 (mid to late June, July, and August)
	Kesang Cave	III	I	I	V	2.5 (mid to late June, July, and August)
	Xiata	III	I	I	V	2.5 (mid to late June, July, and August)
	Sayram Lake	III	I	I	V	2.5 (mid to late June, July, and August)
	Daxigou	III	I	I	V	2.5 (mid to late June, July, and August)
	Tangbula	II	I	I	V	3 (June, July, and August)
	Qiaxi	II	I	I	V	3 (June, July, and August)
Urumqi and its surrounding cluster	Wusu Foshan	I	I	I	III	3.5 (June, July, August, and mid to early September)
	Lujiao Bay	I	I	I	III	3.5 (June, July, August, and mid to early September)
	Tianshan Grand Canyon	I	I	I	III	3.5 (June, July, August, and mid to early September)
	Jiangbulak	I	I	I	III	3.5 (June, July, August, and mid to early September)
	Urumqi Tianshan	I	I	I	I	4 (June, July, August, and September)
	Tianshan Tianchi Lake	I	I	I	I	4 (June, July, August, and September)
	Tianchi Forest	I	I	I	I	4 (June, July, August, and September)
	Cheshi	I	I	I	II	4 (June, July, August, and September)

, and Table S2). In July, the FTCCI in 26 bases reached Level I (Figure 5b and Table 6). In August, the FTCCI in Nalati and Tomur Peak was at Level II, whereas the remaining 24 bases were at Level I (Figure 5c and Table 6). In September, the FTCCI in Urumqi Tianshan, Tianshan Tianchi Lake, and Tianchi Forest was at Level I, while Cheshi fell into Level II. Additionally, Wusu Foshan, Lujiao Bay, Tianshan Grand Canyon, and Jiangbulak were at Level III, whereas the remaining 18 bases were at Level V (Figure 5d and Table 6).

Based on Table 2, the climate comfort duration for forest therapy in different clusters was summarized in Table 6. The bases in Urumqi and its surrounding cluster were conducive to forest therapy activities from June to September, up to 3.5 to 4 months. Among them, Wusu Foshan, Lujiao Bay, Tianshan Grand Canyon, and Jiangbulak were merely suitable for such activities during the middle to early part of September. Moreover, the bases located in the Altai cluster and Hami cluster were optimal for forest therapy during mid to late June, July, and August. Most of the bases in Ili and its surrounding cluster also offered prime climate conditions for forest therapy activities during the same period. However, Nalati had a more limited suitable period for forest therapy, specifically from July to August, which coincided with the situation in Aksu cluster. Conversely, Tangbula and Qiaxi had a prolonged period of forest therapy, spanning from June to August, totaling three months.

In summary, the FTCCI had significant temporal and spatial differences (

Table 7. Variance analysis of FTCCI in different potential forest therapy base clusters.

Potential Forest Therapy Base Clusters	June	July	August	September
Aksu cluster	1.5 Cc	5.0 Aa	3.7 Bb	1.0 Bcd
Hami cluster	3.0 Bb	5.0 Aa	5.0 Aa	1.0 Bc
Altai cluster	3.0 Bb	5.0 Aa	5.0 Aa	1.0 Bc
Ili and its surrounding cluster	2.9 Bb	5.0 Aa	4.9 Aa	1.0 Bc
Urumqi and its surrounding cluster	5.0 Aa	4.8 Aa	5.0 Aa	3.9 Ab

Note: capital letters indicate that the FTCCI in the same month varies significantly in different potential forest therapy base clusters; lowercase letters indicate that the FTCCI in the same potential forest therapy base clusters varies significantly in different months.

). In terms of time, July and August were the most favorable months for forest therapy across all 26 bases, followed by June. However, in September, only Urumqi and its surrounding cluster was suitable for forest therapy. From the perspective of space, Urumqi and its surrounding cluster had the longest climate comfort duration for forest therapy, whereas the Aksu cluster held the shortest duration. Meanwhile, the climate comfort duration for the Altai cluster, Hami cluster, and Ili and its surrounding cluster were remarkably similar, with minimal significant differences.

4. Discussion

4.1. Index Selection and Weight Assignment of Forest Therapy Climate Comfort Index (FTCCI)

The intricate nature of the human heat exchange mechanism necessitates a comprehensive consideration of various climate factors when developing a forest therapy climate comfort index. Among the numerous climatic factors that influence human perception, temperature, humidity, wind speed, and sunshine stand out as the most crucial ones [29]. These factors are intricately linked to the exchange of heat and water between the human body and its external environment, subsequently exerting a profound influence on individuals’ physiological and psychological states [31]. The level of temperature directly dictates the perception of cold and warmth within the body, while humidity impacts the body’s capacity to sweat and dissipate heat. Wind speed modulates the body’s perceived temperature by regulating airflow, and sunshine holds a close correlation with emotional states. Nonetheless, relying solely on a specific meteorological index alone is insufficient to fully capture the nuances of climate comfort. Therefore, it is imperative to incorporate multiple meteorological variables into the construction of an evaluation model.

By incorporating additional meteorological variables and expanding classification standards, the Temperature and Humidity Index (THI) and Wind Efficiency Index (WEI) effectively overcome the limitations of previous climate comfort evaluation models that solely focused on specific sensations of cold, heat, and wind efficiency. Furthermore, the THI offers valuable insights into the heat exchange occurring between the human body and its surrounding environment, considering both temperature and humidity [8]. This index aids forest therapy participants in selecting the most suitable time and location for their activities. Additionally, the WEI integrates factors like wind speed, temperature, and sunshine [7], allowing participants to comprehend the perceived temperature under varying wind and sun conditions, and enabling them to plan their forest therapy activities in a reasonable manner. Hence, the THI, along with the WEI, occupy a pivotal role in the establishment of the forest therapy climate comfort index, serving as an indispensable and crucial component.

Additionally, this study underscores the significance of incorporating the critical indicator of temperature exclusively when developing climate comfort evaluation models, marking the first instance of such an emphasis. Temperature, being a primary meteorological factor, holds significant geographical and ecological importance, particularly in the context of forest therapy activities. Previous studies have firmly established that temperature serves as the primary determinant in the evolution of the tourism climate comfort period [27]. Furthermore, temperature exerts the greatest influence on the notable changes in the number of suitable days for tourism, accounting for over 50% of the total impact [49]. Temperature has a notable positive influence on tourism behavior [19], with a rise of 2.5 °C in temperature and a 7% increase in precipitation correlating to a 3.1% surge in tourist days [50]. Crucially, temperature holds a pivotal role in maintaining health and attracting tourists [34]. Most of the forest therapy factors originating from “natural healthcare resources”, including negative air ion concentration, air oxygen content, and phytoncide, are influenced by temperature. Temperature is also the common cause for the spatial and temporal variability of “natural healthcare resources” [44]. Therefore, when selecting the appropriate time and location for forest therapy activities, the temperature factor must be thoroughly considered. In this study, temperature holds the largest proportion in FTCCI, followed by the THI, with the WEI ranking the lowest. This aligns with the findings of Zhu et al. [51] who concluded that temperature comprises the largest proportion in the healthcare index. It is found that temperature has the most significant impact on climate comfort, exhibiting a positive correlation [28]. Furthermore, the proportion of the THI surpasses that of the WEI, concurring with numerous research findings [7,8,30].

It is undeniable that the suitability of the forest environment holds paramount significance for the successful execution of forest therapy activities, as its suitability is directly tied to enhancing both the efficacy and quality of the healthcare benefits. When evaluating the suitable conditions for forest therapy activities, it is imperative to undertake a comprehensive assessment encompassing a multitude of pivotal factors. These encompass, but are not exhaustive to, the size of the forest area, forest coverage, terrain characteristics, climatic conditions, landscape resources, and healthcare environmental elements. However, the FTCCI introduced in this study specifically aims to evaluate the comfort level of climatic conditions conducive to forest therapy activities, and it does not cover other multidimensional and comprehensive requirements and standards pertaining to the forest environment. This signifies that when employing the FTCCI to guide practice for forest therapy activities, other vital factors such as the natural landscape of the forest environment, the quality of the healthcare environment, the scale of the forest land, and the structure of the stand should be comprehensively considered.

4.2. The Spatial—Temporal Variation in Various Indicators of FTCCI

Climate comfort varies from season and region [52], thus impacting human health and activities which are influenced by seasonal and regional variations in climate comfort [53]. The Temperature (T), Thermal Humidity Index (THI), and Wind Effect Index (WEI) in 26 potential forest therapy bases present a consistent temporal variation pattern: July > August > June > September. Studies have shown that the change in temperature will consequently affect the human thermal bioclimate [52], and the evaluation of climate comfort is most influenced by temperature [8]. Consequently, as models for assessing climate comfort, the THI and WEI exhibit similar temporal variation to temperature. Moreover, all indices pertaining to the FTCCI reveal notable spatial heterogeneity. Overall, the T, THI, and WEI in Urumqi and its surrounding cluster are significantly higher than other clusters, followed by the Altai cluster, Hami cluster (Hami Tianshan), and most of the bases in Ili and its surrounding cluster. On the contrary, the Aksu cluster (Tomur Peak) stands as the lowest, followed by the Ili and its surrounding cluster of Nalati and Kunes. This could be closely associated with the disparities in latitude, geographical location, and altitude [53,54]. The bases in Urumqi and its surrounding cluster are situated adjacent to the southern edge of Gurbantonggut Desert, exhibiting typical arid climate features [55]. This desert holds a pivotal position in influencing temperature variations within the surrounding region [56]. Owing to the combined effects of local circulation and the urban heat island effect [57], heat continuously flows from the desert towards the cities surrounding Urumqi. Concurrently, the T, THI, and WEI of the Altai cluster situated at a higher latitude, as well as the Ili and its surrounding cluster influenced by the Atlantic moist current, and the Hami Tianshan located at a higher altitude, are all comparatively lower than those of the Urumqi and its surrounding clusters. Due to its altitude, Tomur Peak experiences a chilly climate accompanied by an increase in wind speed. Consequently, it shows relatively low temperature, THI, and WEI. Analogously, Nalati and Kunes are primarily influenced by the “cold pole” effect prevalent in the Bayanbulak alpine region [54].

Since 1960, the annual average temperature in China has witnessed a marked elevation, especially in northern China, and it is anticipated that this upward trend will persist and intensify in the years to come under simulated scenarios with different emission concentrations [58]. Amidst the prevailing trend of global warming, the climate comfort conditions and the corresponding durations in diverse regions are bound to undergo alterations. For Xinjiang, this phenomenon could potentially present a great opportunity for bolstering its tourism sector. It has been reported that under the background of global warming, the significant reduction in cold discomfort days and the moderate increase in comfort days will collectively contribute to an improvement of the overall climate comfort condition in the frigid regions of middle and high latitudes in China [26]. As temperature escalates in northwest China, the decline in relative humidity and wind speed has a pronounced influence on both THI and WEI [8]. Furthermore, the climate comfort period in the northern half of China, predominantly distributed in summer, and the northwest region is one of the key areas where the number of comfortable days increases significantly [26]. Our results clearly suggest that the climate comfort duration of forest therapy in Xinjiang is overwhelmingly concentrated in July and August. Therefore, as a typical representative of northwest China, the temperature rise in Xinjiang, coupled with the deceleration of wind speed, will facilitate the enhancement of FTCCI, thereby extending the climate comfort duration of forest therapy tourism.

4.3. The FTCCI and Its Enlightenment to Forest Therapy Tourism Development

We found that there are obvious disparities in FTCCI and climate comfort duration across different clusters. In general, the bases in Urumqi and its surrounding cluster enjoy the longest climate comfort duration, whereas the climate conditions in Tomur Peak and Nalati are comparatively unfavorable for healthcare. Regarding the bases in other clusters, their climate comfort duration remains at a normal level, primarily spanning from mid to late June through August. This result is generally consistent with the conclusion of most scholars on the tourism climate comfort in Xinjiang [27,43,54,55], who widely agree that the period from May to October is the optimal time for tourism in Xinjiang. However, these studies predominantly concentrate on mass tourism, with few in-depth studies conducted from the unique perspective of forest therapy tourism. Among the 26 potential forest therapy bases selected by this study, the vast majority have established a relatively complete tourism infrastructure system. Of these, 11 potential bases are situated within 5A tourist attractions, 10 are in 4A tourist attractions, 3 reside in 3A tourist attractions, and the remaining 2 potential bases are found in unrated tourist attractions (Table S1). Although the tourism infrastructure conditions in unrated and 3A tourist attractions are still insufficient, the remaining 21 potential forest therapy bases possess exceptional tourism infrastructure conditions, laying a solid foundation for the development of forest therapy tourism.

Climate comfort is not only vital for ensuring individuals’ comfort and well-being [23], but it also serves as a significant factor affecting people’s tourism activities [10,21]. Based on the varying climate comfort duration for forest therapy across diverse clusters, the forest therapy activity’s themes appropriate for development in each cluster vary and possess unique characteristics. Forest therapy activity, also known as forest therapy product, refers to a series of health care services and activities that rely on high-quality forest therapy resources to achieve a specific health management goal, including but not limited to forest bathing, forest yoga, forest meditation, forest catharsis, forest music, and hot spring bathing [5]. Given this, it is imperative to develop the forest therapy products accurately based on the respective climate comfort conditions, healthcare resources, and geographical location. For instance, the bases in Urumqi and its surrounding cluster allow the in-depth development of distinctive forest therapy products, encompassing forest bathing, hot spring soaking, hiking, and farming experiences. For tourists visiting from outside Xinjiang, these bases closed to Urumqi offer excellent accessibility, enabling them to easily enjoy the unique forest therapy resources without enduring long journeys. The bases in the Altai cluster could closely focus on the health theme of “Kanas, a pure land on Earth”. With Kanas at its heart, these bases leverage their vast forest resources, highlighting the traditional Tuva tribal dwellings in Baihaba Village, Kanas Village, and Hemu Village as distinctive wellness accommodations. By integrating the rejuvenating hot spring resources of Shenzhongshan and Altai Hot Spring, it offers tourists an idyllic sanctuary where they can unwind and reconnect with nature. The bases in Ili and its surrounding cluster are endowed with forest therapy resources, including magnificent Picea schrenkiana forests, breezy grasslands, majestic glacier landscapes, and serene lake vistas; combined with the local Kazakh national culture, we can develop a unique Ili’s forest therapy tourism loop. Hami Tianshan primarily caters to tourists in eastern Xinjiang, whereas the Tomur Peak specializes in serving tourists from southern Xinjiang and around Aksu, and is committed to becoming a leading forest therapy base in southern Xinjiang.

Certainly, the above content outlines the theme positioning and target customer of forest therapy for each distinct cluster. Considering the different environmental conditions, the positive influence on individuals’ physical and mental well-being yields outstanding variations. When embarking on the further planning of specialized forest therapy products, it is necessary to integrate the unique features of each potential forest therapy base, including stand characteristics, topography, climatic conditions, natural landscapes, and healthcare environmental quality. This integration will facilitate precise development and comprehensive expansion, ensuring tailored offerings that cater to the specific needs and potential of each base.

4.4. Limitations

Admittedly, some limitations exist in this study. Firstly, this study relies on monthly average climate data from 25 meteorological stations in Xinjiang. Nevertheless, the uneven geographical distribution of these stations inevitably impacts the precision of the Forest Therapy Climate Comfort Index (FTCCI) to a certain degree. Secondly, the application scope of FTCCI is confined exclusively to evaluating the climate comfort conditions within forest environments, with the objective of ascertaining their suitability for conducting forest therapy activities. Hence, when implementing forest therapy activities, it is imperative to not only refer to the FTCCI but also consider various aspects of the forest environment, encompassing forest area size, forest coverage, terrain characteristics, climatic conditions, landscape resources, and healthcare environmental factors, to ensure the comprehensiveness and accuracy of comprehensive assessment.

5. Conclusions

The Forest Therapy Climate Comfort Index (FTCCI) serves as a metric to assess the impact of forest climate on human health and comfort, and analyze whether the climate comfort conditions in different regions and periods are suitable for forest therapy. In this study, the FTCCI is developed for the first time to quantitatively evaluate the spatial–temporal pattern of climate comfort conditions for forest therapy in Xinjiang. It is found that the climate comfort for forest therapy has temporal and regional heterogeneity in Xinjiang. The bases in Urumqi and its surrounding cluster enjoy the longest duration of healthcare and comfort, up to 3.5~4 months, making them particularly suitable for forest therapy pursuits. Excluding Tomur Peak and Nalati (July and August), the remaining 24 bases all possess ideal climate comfort conditions for forest therapy from mid to late June through August. It is further elucidated that the climate comfort duration varies among potential forest therapy bases in different clusters. Therefore, the future development direction of forest therapy tourism in distinct clusters should capitalize on their unique climate, resource, and geographical condition to create specialized forest therapy products. The results enhance our comprehension of the climatic conditions conducive to forest therapy in Xinjiang, enabling tourists to identify the most optimal region and period for such endeavors. Moreover, it furnishes the local government with a robust scientific foundation for site selection and product planning of forest therapy bases in the future, thereby contributing to the prosperous development of forest therapy in Xinjiang.