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Journal of Resources and Ecology >

2024 , Vol. 15 >Issue 5: 1324 - 1334

DOI: https://doi.org/10.5814/j.issn.1674-764x.2024.05.019

Impact of Human Activities on Ecosystem

Evaluation of the Green Development Status in Mountainous Scenic Area based on the Tourism Ecological Footprint Model

  • LIU Zhongxiu , 1, 2, * ,
  • Nor Kalsum MOHD ISA 1
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  • 1. Department of Geography and Environment, Faculty of Human Sciences, Education University of Sultan Idriss, Tanjong Malim, Perak 35900, Malaysia
  • 2. School of Civil Engineering and Architecture, Linyi University, Linyi, Shandong 276005, China
* LIU Zhongxiu, E-mail:

Received date: 2023-11-13

  Accepted date: 2024-05-12

  Online published: 2024-10-09

Supported by

The Key Research and Development Program of Shandong Province (Soft Science Project)(2023RZB01001)

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Abstract

This study employs the Tourism Ecological Footprint Model to meticulously evaluate the green development status of mountainous scenic areas, specifically focusing on the Wenfeng Mountain Scenic Area. The overarching aim is to conduct a comprehensive analysis of the ecological impact stemming from tourism activities. The evaluation encompasses complex calculations and analyses of the ecological footprint, ecological carrying capacity, and ecological surplus. In the case study of Wenfeng Mountain Scenic Area, the findings indicate a notable state of ecological surplus in the current stage of tourism development. The specific quantitative results reveal a surplus, indicating that the ecological impact of tourism activities is well within the sustainable carrying capacity of the region. This implies that despite substantial tourism activities, the ecological environment of the Wenfeng Mountain Scenic Area remains effectively protected and maintained. The ecological surplus signifies a balance between tourism development and the preservation of the local ecosystem, which is crucial for the sustainable development of the region. Moreover, this study delves into the nuances of the ecological components, providing detailed breakdowns of the ecological footprints attributed to various tourism-related activities, including accommodation, transportation, dining, sightseeing, and shopping. These specifics offer a nuanced understanding of the ecological dynamics associated with diverse tourism-related factors. The meticulous assessment of Wenfeng Mountain Scenic Area's green development status has several significant implications. Decision-makers can draw insights into the delicate balance that is required between tourism promotion and environmental conservation. The ecological surplus suggests that current practices align with sustainable development goals andprovide a positive model for similar regions. However, this study also draws attention to some critical limitations in the Tourism Ecological Footprint Model. The detailed results highlight challenges related to model applicability, data collection, and calculation methods, stressing the need for further refinement and validation. Acknowledging these limitations is crucial for refining the model and ensuring its robust application in diverse geographical contexts. In conclusion, this study delivers a granular understanding of the green development status of mountainous scenic areas, specifically the Wenfeng Mountain Scenic Area. The detailed results serve as a rich reference for decision-makers and researchers, offering new insights into specific aspects of tourism-related ecological impacts. As avenues for future research, refining the evaluation indicators and improving the data collection and analysis methodologies will be pivotal for advancing the precision and reliability of green development assessments.

Key words： green development; tourism ecological footprint; Wenfeng Mountain Scenic Area

Cite this article

LIU Zhongxiu , Nor Kalsum MOHD ISA . Evaluation of the Green Development Status in Mountainous Scenic Area based on the Tourism Ecological Footprint Model[J]. Journal of Resources and Ecology, 2024 , 15(5) : 1324 -1334 . DOI: 10.5814/j.issn.1674-764x.2024.05.019

1 Introduction

In the realm of sustainable development, the trajectory toward an ecological economy and environmental harmony is delineated by the concept of green development. For tourism destinations, green development is rooted in the principles of ecological civilization, which emphasizes the indispensable role of the tourism industry in realizing the ecological dividends inherent in sustainable practices. This importance is particularly pronounced in mountainous scenic areas, where the path to green development assumes paramount significance.
Within the framework of green development theory, the symbiotic relationship between economic prosperity and ecological preservation is emphasized, especially in regions characterized by rugged terrain and distinctive natural landscapes. In such places, the demand for sound tourism practices is accentuated, with the ecological backdrop serving not merely as a backdrop but also as a vital component shaping the attractiveness and sustainability of tourism destinations.
As the veritable lifeblood sustaining the tourism industry, any perturbation in the delicate ecological equilibrium of mountainous scenic areas poses a formidable constraint, potentially stymying the industry’s trajectory toward green development. Consequently, a judicious assessment of the green development status in these regions emerges as both a foundational prerequisite for translating theoretical constructs of sustainable development into tangible practices and a pivotal compass for steering developmental trajectories that are consistent with the principles of green development.
Recognizing the ecological environment as the linchpin for the existence and advancement of the tourism sector, disruptions to this fragile equilibrium pose consequential threats to the harmonization of economic advancement and ecological vitality in mountainous scenic areas. Thus, a meticulous inquiry into the green development status becomes imperative, and serves not only as an evaluative metric but also as a guiding beacon for delineating sustainable tourism practices consistent with the principles of ecological civilization. In this context, this study employs the Tourism Ecological Footprint Model for a nuanced evaluation of the green development status within mountainous scenic areas, with a specific focus on a case study of Wenfeng Mountain Scenic Area.

2 Literature review

The tourism ecological footprint model is an important tool for assessing the environmental impact of tourism activities, and it has received widespread attention and research application in recent years. This model aims toevaluate the sustainability and green development level of tourism by measuring the resources consumed and the environmental impacts generated by tourism activities (Sultan et al., 2020). It decomposes tourism activities into indicators, such as energy consumption, water resource utilization, and waste emissions, which quantify the consumption of natural resources and the environmental impact of tourism (Wang et al., 2017). The tourism ecological footprint model can provide a scientific basis for tourism management and decision-making, thereby promoting the sustainable development of the tourism industry (El Archi et al., 2023). In-depth research and application of the tourism ecological footprint model can provide valuable insights and experiences for achieving harmonious development between tourism and the environment (Li et al., 2021).
Research on the tourism ecological footprint model has made significant progress in recent years, which mainly focuses on five aspects. First, there have been methodological improvements. Researchers have made improvements to the methods of the tourism ecological footprint model (Sharp et al., 2016; Collins and Cooper, 2017; Dong et al., 2019; Sun et al., 2020; Du et al., 2022) that enhance its accuracy and applicability. These refinements include improving data collection methods, developing more refined indicators and measurement methods, and incorporating spatial and temporal dimensions to better reflect the environmental impact of tourism activities. Second, the scope of application has been expanded. The application of the tourism ecological footprint model has been expanding to different regions, types of tourist destinations and scales of tourism activities. Researchers have conducted ecological footprint assessments for different types of tourist destinations, such as urban tourist destinations (Katircioglu et al., 2018; Lenzen et al., 2018; Kongbuamai et al., 2020; Nathaniel et al., 2021), coastal resorts (Puig et al., 2017; Gallucci and Dimitrova, 2020; Wu et al., 2020; Toshima et al., 2021) and mountainous scenic areas (Luo et al., 2020; Yang et al., 2020; Liu et al., 2022), to reveal the environmental impacts and sustainability of tourism activities. Third, the research results have been applied in policymaking. The results of research using the tourism ecological footprint model have gained attention and application from policymakers and the tourism industry (Guan et al., 2022). By assessing the environmental impacts of tourism activities (Canteiro et al., 2018), governments and tourism management departments can formulate corresponding policies and management measures to promote the sustainable development of the tourism industry and ecological conservation (Tien et al., 2019). Fourth, integration with other indicators has been explored. Researchers have begun to integrate the tourism ecological footprint model with other environmental and sustainable development indicators to provide more comprehensive assessments and decision-making support (He et al., 2016). For example, combining the tourism ecological footprint with indicators such as the carbon footprint and the water footprint can better reveal the impacts of tourism activities on multiple environmental factors (Li, 2018; Zhu et al., 2019; Wang and Ge, 2020; Chen et al., 2021). Fifth, regional differences and comparative studies have received attention. Researchers have begun to focus on the regional differences in tourism ecological footprints and conduct comparative studies (Katircioglu et al., 2018). By comparing the tourism ecological footprints of different regions (Shi et al., 2020), the characteristics and issues of tourism development in different regions can be revealed (Dunets et al., 2019), which provides guidance and experience for local governments and tourism managers. In conclusion, research on the tourism ecological footprint model has provided important theoretical and practical support for assessing the environmental impact of tourism activities, promoting sustainable tourism development, and realizing ecological conservation.
The existing research on the tourism ecological footprint model is undeniably commendable, and has shed light on critical aspects of environmental impact assessment in the tourism sector. However, some areas still warrant attention to further enhance the depth and applicability of future studies. While the research thus far details the progress made in various dimensions, an explicit identification of the initial research gaps or the specific problems is lacking, which this study aims to address based on the existing literature. Clearly articulating these gaps and problems can provide a stronger foundation for understanding the significance of the research. Various studies mention methodological improvements but lack clarity in presenting the sources of data used, such as references or links to official databases. A more transparent presentation of data sources would enhance the credibility and replicability of a given study. While the model quantifies the consumption of natural resources and environmental impacts, a more detailed discussion on the quantification methods employed would add rigor. This could involve a thorough exploration of the metrics used and their implications for accuracy. Studies could benefit from more extensive discussions on the temporal aspects of the ecological footprint to better understand the dynamic nature of tourism activities. Incorporating longitudinal studies could reveal the temporal variations in ecological impact and contribute to a more nuanced understanding of sustainability over time. The application of research results in policymaking is highlighted in some studies, but a more in-depth discussion on the actual impacts of these policies and their effectiveness in promoting sustainability would enhance the practical implications.

3 Measurement model and estimation method

The concept of ecological footprint refers to the ecological productive land area (including land and water) required to sustainably meet the consumption of natural resources and absorb the waste generated by a specific population in a given area (Wackernagel and Rees, 1998). The tourism ecological footprint specifically pertains to the various resource consumption and waste absorption levels associated with tourism activities within a certain temporal and spatial scope (Gössling, 2002). It represents the area of biologically productive land required to accommodate the resource consumption and waste generation by tourists during their travel experiences (Gössling et al., 2002). This area is globally standardized, devoid of regional characteristics, and possesses direct comparability (Hunter and Shaw, 2007).
In the accounting system of the tourism ecological footprint, the biologically productive land can be categorized into six basic types: fossil energy land, arable land, pastureland, forestland, built-up land, and water area, based on differences in productivity (Chen and Hsieh, 2011). Considering the characteristics of tourism ecological consumption, the tourism ecological footprint calculation primarily consists of components such as tourism transportation, sightseeing, accommodation, dining, shopping, and entertainment (Table 1) (Li and Yang, 2007).
Table 1 Calculation accounts of the tourism ecological footprint
Ecological footprint Accounting components
Transportation Energy consumption of transportation vehicles and the built-up land area for transportation facilities
Sightseeing Energy and material consumption during sightseeing activities and the built-up land area for tourist attractions
Accommodation Energy consumption, consumption of hotel facilities and room supplies, and the built-up land area for accommodation facilities
Food Consumption of food, energy, and the built-up land area for dining facilities
Shopping Material and energy consumption in the production of tourism goods and the built-up land area for shopping venues
Entertainment Energy and material consumption during entertainment activities and the built-up land area for entertainment facilities

3.1 Calculation of the tourism ecological footprint

The formula for calculating the tourism ecological footprint is:
T E F = N × t e f = N × ∑ i = 1 n ( a a i ) = N × ∑ i = 1 n ( c i / p i )
where TEF represents the total tourism ecological footprint; N is the number of tourists; tef denotes the per capita tourism ecological footprint; i represents the type of goods and inputs consumed in tourism activities; aai represents the biologically productive area per capita equivalent for the i-th type of tourism consumption goods; pi is the average productivity of the i-th type of tourism consumption goods; and ci denotes the per capita consumption of the i-th type of tourism goods.

3.2 Calculation of the tourism ecological carrying capacity

Tourism ecological carrying capacity, also known as the tourism ecological capacity, refers to the sustainable maximum sum of ecologically productive land area that can be provided to humans without impairing the productivity and functional integrity of the relevant ecosystems. Unlike the traditional ecological carrying capacity, which is measured in terms of population, the ecological carrying capacity in this study is measured in terms of area. It can be understood as the maximum value of the ecological footprint under certain natural and social conditions. The formula for the tourism ecological carrying capacity is:
T E C = ∑ i = 1 n S i × y i × e i
where TEC represents the tourism ecological capacity; i denotes the six basic types of land; Si represents the area of the i-th land type; yi represents the yield factor of the i-th land type; and ei denotes the equilibrium factor of the i-th land type.

3.3 Calculation of the green development level in mountainous scenic areas

Based on the internal system of tourism, the monitoring indicator EI is constructed to measure the green development level in mountainous scenic areas. The calculation formula for EI is:
E I = T E F / T E C
Based on the above model, a smaller value of EI indicates a higher level of green development in mountainous scenic areas.
If EI<1, then the tourism ecological footprint is smaller than the tourism ecological capacity. In this case, the area managers should focus on protecting the ecological environment while considering how to tap into and develop the tourist market, improve infrastructure, enhance the tourism image, and maximize the utilization of their resource advantages.
If EI>1, then the tourism ecological footprint has exceeded the tourism ecological capacity, indicating certain pressure on the ecological environment. The larger the EI value, the greater the pressure. In such cases, the focus should be on planning and managing the tourism area, with an emphasis on protecting the ecological environment and taking measures to reduce the negative impacts of tourist activities. These measures should aim to minimize the ecological footprint without compromising tourist satisfaction and the economic benefits of the scenic area. Raising tourists’ awareness of their positive or negative impacts on the ecological environment and providing environmental education during their travel experiences are also important to foster a conscious commitment to environmental protection and help the tourists to reduce their personal ecological footprint.

3.4 Models for tourism ecological footprint subsystems

3.4.1 Tourism transportation ecological footprint model

The calculation of the tourism transportation ecological footprint mainly involves two aspects: the built-up land area of tourism transportation facilities and the energy consumption associated with tourism activities, such as round trips from the place of origin to the tourist destination and the energy consumption of transportation within the tourist destination. The calculation of the built-up land area occupied by tourism transportation facilities includes airports, train stations, bus terminals, ship terminals, railways, highways, parking lots, cable car stations in scenic areas, bridges, tunnels, etc., which are required by tourists. Note that the built-up land area occupied by tourism transportation facilities should be the sum of the areas of various transportation facilities in the region, excluding areas not used by tourists. The calculation model for the tourism transportation ecological footprint is:
T E F transport = ∑ i = 1 n S i × R i + ∑ j = 1 n ( N j × D j × C j / r )
where Si represents the area of the i-th type of transportation facility; Ri represents the utilization rate of the i-th type of transportation facility; Nj represents the number of tourists choosing the j-th type of transportation; Dj represents the average travel distance of tourists choosing the j-th type of transportation; Cj represents the energy consumption per unit distance per capita of the j-th type of transportation; and r represents the average heat value of fossil fuel production land area in the world.

3.4.2 Tourism sightseeing ecological footprint model

The calculation of the sightseeing ecological footprint mainly includes the built-up land areas of tourist trails, roads, scenic viewpoints, etc., within various scenic areas, as well as the conversion of fossil energy land area consumed by sightseeing vehicles during activities within the scenic areas. The energy consumption during sightseeing activities is relatively small and can be neglected. The formula for the sightseeing ecological footprint model is:
T E F visiting = ∑ i = 1 n P i + ∑ i = 1 n H i + ∑ i = 1 n V i
where Pi represents the built-up land area of tourist trails in the $i$-th scenic area; Hi represents the built-up land area of roads in the i-th scenic area; and Vi represents the built-up land area of scenic viewpoints in the i-th scenic area.

3.4.3 Tourism accommodation ecological footprint model

The calculation of the tourism accommodation ecological footprint includes the areas of hotels, resorts, guesthouses, and other types of accommodations providing beds, as well as the energy consumption for heating, cooling, air conditioning, lighting, cleaning, television, internet, and other related services for guests. Considering the different requirements for built-up land areas and the energy consumption for different types and grades of accommodations, tourism accommodations can be classified into eight basic types: one-star hotels, two-star hotels, three-star hotels, four-star hotels, five-star hotels, public inns, private inns, and cruise ships.
Generally, the built-up land area per bed is 100 m² for one to two-star hotels, 300 m² for three to four-star hotels, 2000 m² for five-star hotels, 100 m² for public inns, 50 m² for private inns, and 15 m² for cruise ships. The energy consumption per bed is 40 MJ for one to two-star hotels, 70 MJ for three to four-star hotels, 110 MJ for five-star hotels, 40 MJ for public inns, 30 MJ for private inns, and 40 MJ for cruise ships. The calculation model for the tourism accommodation ecological footprint is:
T E F accommodation = ∑ i = 1 n ( N i × S i ) + ∑ i = 1 n ( 365 × N i × K i × C i / r )
where Ni represents the number of beds in the i-th type of accommodation facility; Si represents the built-up land area per bed in the i-th type of accommodation facility; Ki represents the average room rental rate per year in the i-th type of accommodation facility; Ci represents the energy consumption per bed in the i-th type of accommodation facility; and r represents the average heat value of fossil fuel production land area in the world.

3.4.4 Tourism dining ecological footprint model

The calculation of the tourism dining ecological footprint includes the built-up land area of catering facilities providing services such as meals, local cuisine tasting, banquets, buffets, snacks, and beverages to tourists, as well as the biologically productive land area consumed for food consumption by tourists (including arable land, forest land, grassland, and water area), and the fossil energy land area consumed for providing catering services. The built-up land area of catering facilities only includes the areas of various social restaurants (excluding those within accommodation facilities) and does not include catering services provided within tourism accommodation facilities. To overcome the difficulty in obtaining data on food and energy consumption by tourists, the food and energy consumption by tourists at the tourist destination is assumed to be the same as that of local residents. The per capita daily food and energy consumption of local residents can be obtained from local statistical yearbooks. The calculation model for the tourism dining ecological footprint is:
T E F food = ∑ i = 1 n S i + ∑ i = 1 n ( N × D × C i / P i ) + ∑ i = 1 n ( N × D × E i / r i )
where Si represents the built-up land area of various social catering facilities; N represents the number of tourists; D represents the average number of days of a tourist stay; Ci represents the per capita daily consumption of the i-th type of food by tourists; Pi represents the average productivity of the biologically productive land corresponding to the i-th type of food; Ei represents the per capita daily consumption of the i-th type of energy by tourists; and ri represents the average heat value of fossil fuel production land area for the i-th type of energy in the world.

3.4.5 Tourism shopping ecological footprint model

The tourism shopping ecological footprint refers to the built-up land area, biologically productive land area, and fossil energy land area required during the production, processing, transportation, and sale of tourism products purchased by tourists. The energy consumption during tourism product production and sale is relatively small and can be neglected. The formula for the tourism shopping ecological footprint model is:
T E F shopping = ∑ i = 1 n S i + ∑ j = 1 n R j / P j g j
where Si represents the built-up land area of the i-th tourism product production and sale facility; Rj represents the consumption expenditure of tourists purchasing the j-th type of tourism product; Pj represents the average selling price of the j-th type of tourism product; and gj represents the average productivity of the biologically productive land corresponding to one unit of the j-th type of tourism product.

3.4.6 Tourism entertainment ecological footprint model

The calculation of the leisure and entertainment ecological footprint includes the built-up land area and energy consumption of recreational facilities provided for tourists. It is calculated as:
T E F entertainmernt = ∑ i = 1 n S i
where Si represents the built-up land area of the i-th category of outdoor recreational facilities for tourists.

3.5 Research area and data sources

3.5.1 Overview of Wenfeng Mountain Scenic Area

Wenfeng Mountain Scenic Area is located in Shangyan Town, 15 km east of Lanling County, Shandong Province. The area is crossed by National Highway 206, making it easily accessible for tourism. With an area of 4.5 km², the main peak has an elevation of 212 m and is composed of limestone and metamorphic rocks. The average annual temperature is 13.6 °C, and the average annual precipitation is 886.6 mm. Wenfeng Mountain Scenic Area is known for its beautiful scenery and rich cultural heritage. The development of tourism in Wenfeng Mountain Scenic Area started around 2003, and with the support of the local government, the tourism industry has been rapidly growing in recent years. Despite the measures taken to protect the ecological environment from the early stages of tourism development, the increasing number of tourists and the construction of a large amount of tourism infrastructure to accommodate the rapid growth of the industry have intensified the pressure on the local ecological environment.

3.5.2 Data and sources

According to the tourism ecological footprint model, this study collected data necessary for calculating the tourism ecological footprint of Wenfeng Mountain Scenic Area for 2021. The data used in this study can be categorized into three types: basic data, survey data, and standard data.
(1) Basic Data includes the total quantity and composition of tourism-related transportation, accommodation, dining, entertainment, sightseeing, and shopping facilities, as well as total energy consumption and its composition, and total tourist expenditure. These data are classified as secondary data, sourced from the Lanling County Statistical Yearbook and reports from the Culture and Tourism Bureau of Lanling County.
(2) Survey Data includes the area and utilization rates of various tourism-related facilities, demographic composition of tourists, composition of tourist expenditures, average travel distance within the tourist area, transportation choices, and average length of stay. These are categorized as primary data, gathered through a detailed survey conducted from April 2023 to June 2023, to supplement and validate the data from 2021.
(3) Standard Data includes information on energy consumption per unit distance for different transportation modes, average heat value of fossil fuel production land area, and equilibrium factors. These data are also classified as secondary data, obtained from transportation statistical yearbooks and relevant research literature.
Due to limitations in the availability of comprehensive data for 2021, the study used primary data from 2023 to fill gaps and verify assumptions about resource consumption patterns during the calculation of the 2021 ecological footprint. This approach ensures that the calculations reflect the most accurate and complete data available.

4 Results and analysis

4.1 Data Sources

This study evaluated the green development status of Wenfeng Mountain Scenic Area, a representative mountainous scenic area, using a combination of primary and secondary data.

4.1.1 Primary Data

The primary data were acquired through a structured survey conducted over a two-month period from April 2023 to June 2023. The survey covered Wenfeng Mountain Scenic Area, the Culture and Tourism Bureau of Lanling County, and other tourism-related enterprises and institutions. A total of 1000 questionnaires were distributed to visitors of the scenic area using purposive sampling, with careful consideration given to demographic factors such as age, gender, and geographic origin.
The survey instrument, developed based on methodologies from renowned studies on tourism impact and ecological footprint evaluation, collected data on visitor behavior, ecological impact, and perceptions of ecological balance. Although collected in 2023, these primary data were used to supplement and validate certain assumptions made about 2021, given the limitations of available data from that period.

4.1.2 Secondary Data

The secondary data used in this study were drawn from various official sources, including the Lanling County Statistical Yearbook, reports from the Culture and Tourism Bureau, the Natural Resources Bureau, and the Forestry Bureau, as well as policy documents relevant to Wenfeng Mountain Scenic Area. These data provided critical background on the area's ecological profile, biodiversity indices, land use patterns, environmental quality indicators, and tourism trends.
Secondary data for 2021 were used as the core basis for calculating the tourism ecological footprint, and the primary data from 2023 were integrated to ensure a more accurate reflection of conditions, where 2021 data were incomplete or unavailable. This comprehensive approach allowed for a robust analysis of the green development status of the Wenfeng Mountain Scenic Area, contextualizing the current state within historical trends and existing policy frameworks.
The survey instrument drew inspiration from established research frameworks (Hunter, 2002; Hunter and Shaw, 2007; Wang et al., 2017; Lee and Chen, 2021; Miralles et al., 2023) and was carefully tailored to the context of the Wenfeng Mountain Scenic Area. Adjustments were made to align with the specificities of the scenic area and the objectives of the green development assessment. While purposive sampling facilitated diversity, we recognize some limitations in achieving absolute representativity. Mitigating measures included thorough demographic consideration during respondent selection and robust statistical adjustments during data analysis. In essence, the synthesis of meticulously collected primary and secondary data, coupled with a nuanced sampling approach, substantiates the depth, reliability, and applicability of our assessment of Wenfeng Mountain Scenic Area’s green development status.

4.2 Calculation of tourism ecological footprint

The calculation of the tourism ecological footprint was carried out sequentially for six subsystems: tourism transportation, tourism sightseeing, tourism accommodation, tourism dining, tourism shopping, and tourism entertainment.

4.2.1 Tourism transportation ecological footprint

The calculation of the tourism transportation ecological footprint includes the energy consumption required for tourists to travel from their place of residence to the tourism destination and within the various tourism destinations, as well as the occupation of tourism transportation facilities. The footprint of building land occupied by transportation facilities includes the total area occupied by various transportation facilities used by tourists. The energy consumption is the product of the travel distance of tourists and the per capita energy consumption per unit distance for the transportation mode chosen. The energy footprint is the conversion of energy consumption into the land area for fossil fuel production, with the conversion factor based on the average heat value of fossil fuel production land area worldwide (Milano et al., 2016). The data on the tourists' place of residence and choice of transportation mode were obtained from culture and tourism bureau statistics, and the per unit energy consumption values for various transportation modes were compiled from transportation statistical yearbooks and relevant research literature.

4.2.2 Tourism sightseeing ecological footprint

According to the information from the culture and tourism bureau of Lanling County, tourists mainly concentrate their sightseeing activities in two key scenic spots: the Inspirational Education Base and the Patriotic Education Base. The energy consumption and material consumption during the sightseeing processes at other scenic spots are negligible and can be ignored. Therefore, the ecological footprint of tourists’ sightseeing activities can be approximated by the footprint of the building spaces occupied by the sightseeing facilities.

4.2.3 Tourism accommodation ecological footprint

The calculation of the accommodation ecological footprint is based on the corresponding building area per bed and the daily energy consumption standard for different levels of hotels and inns, taking into account the duration of a tourist’s stay. The general standards for building area and energy consumption per bed used in the tourism area design were applied.

4.2.4 Tourism dining ecological footprint

The dining subsystem calculates the consumption of biological resources such as grains, meat, vegetables, and fruits by tourists during their stay in the tourism area. The corresponding biological production land includes arable land, grassland, water bodies, and forests. Due to the lack of specific statistical data for the dining subsystem, the tourists were assumed to consume the same amount of food as the local residents, considering the tendency of tourists to embrace local customs and choose characteristic foods of the tourism area. The ecological footprint of tourism dining in Wenfeng Mountain Scenic Area was calculated based on this assumption.

4.2.5 Tourism shopping ecological footprint

The tourism products in Lanling County mainly include Lanling wine, chestnuts, garlic, and burdock, which involve the consumption of both food and industrial products. In addition, the processing of tourism products also consumes corresponding energy, such as electricity. Therefore, tourism shopping entails comprehensive resource consumption. Due to the diverse types of tourism products, comprehensively gathering detailed statistics was not feasible. Therefore, the majority of tourists’ tourism shopping expenditures in Lanling County were assumed to be used to purchase Lanling wine and burdock for calculating the corresponding biological production land area.

4.2.6 Tourism entertainment ecological footprint

Since large independent leisure and entertainment facilities are currently lacking in Lanling County, the ecological footprint of tourism entertainment was not calculated.
Based on the statistical data and the calculation methods described above, the ecological footprints of tourism dining, tourism accommodation, tourism transportation, tourism sightseeing, and tourism shopping in the Wenfeng Mountain Scenic Area were calculated and summarized (Table 2). From Table 2, the per capita tourism ecological footprint in the Wenfeng Mountain Scenic Area in 2021 was 0.016354 ha per person, with the transportation footprint being the largest, accounting for 57.84%, followed by the dining footprint, accounting for 34.30%. Therefore, transportation and dining are the key factors influencing the tourism ecological footprint. Currently, the average duration of a tourist’s stay in Wenfeng Mountain is relatively short, around 1 day. Moreover, the energy consumption in the Wenfeng Mountain Scenic Area is mainly attributed to the inter-regional transportation energy consumption of domestic tourists.
Table 2 Tourism ecological footprints of the Wenfeng Mountain Scenic Area in 2021
Tourism ecological
footprint type		 Ecological footprint
(ha per person)		 Percentage occupied (%)
Tourism transportation 0.009460 57.84
Tourism sightseeing 0.000101 0.74
Tourism accommodation 0.001030 6.29
Tourism dining 0.005610 34.30
Tourism shopping 0.000153 0.93
Total 0.016354 100

4.3 Calculation of tourism ecological carrying capacity

In the calculation of ecological carrying capacity, there are variations in resource availability among different countries or regions. Not only are there significant differences in ecological productivity between different land types per unit area, but there is also variation in ecological productivity within any given land type. Therefore, direct comparisons of actual areas of the same land type between different countries or regions are not feasible, and standardization of the different land types is required. The difference in local yield represented by a certain land type in a country or region compared to the world average yield can be expressed as a “yield factor”. The yield factor for a specific land type in a country or region is the ratio of its average productivity to the average productivity of the same land type worldwide (Kitzes et al., 2007). To make the calculated results comparable, equilibrium factors are used for adjustments, and the selection of equilibrium factors in this study was based on the Global Footprint Network Report (Austin, 2014).
Currently, the tourism-oriented land in the Wenfeng Mountain Scenic Area mainly consists of cropland, grassland, woodland, and built-up land. The built-up land includes land for scenic areas, shopping, transportation, and accommodation. Based on statistical data from the Lanling County Tourism Bureau and other relevant sources, the per capita tourism ecological carrying capacity of the Wenfeng Mountain Scenic Area in 2021 was calculated to be 0.036508 ha per person. After deducting 12% for biodiversity protection, the per capita tourism ecological carrying capacity was calculated to be 0.032127 ha per person.

4.4 Analysis of green development status in the Wenfeng Mountain Scenic Area

In 2021, the per capita tourism ecological footprint in the Wenfeng Mountain Scenic Area was 0.016354 ha per person, while the per capita ecological carrying capacity for local tourists was 0.032127 ha per person, which is higher than the per capita tourism ecological footprint. Thus, the ecological surplus was 0.015773 ha per person, with a tourism ecological occupancy rate of 50.90% and an ecological surplus rate of 49.10%. This indicates that the tourism development in the Wenfeng Mountain Scenic Area is still in a state of ecological surplus, and the impact of tourism development on the local ecology has not exceeded the carrying capacity of tourism. The tourism development is in a good state of green development, the pressure of tourism activities on the tourism environment is within the carrying capacity range, and the ecological environment is maintained in a good state. Thus, the ecological environment on which the tourism development in the Wenfeng Mountain Scenic Area depends is secure.

5 Discussion and policy implications

5.1 Discussion

In this section, we delve into a detailed analysis of the primary findings of this study and discuss them within the existing literature to comprehensively understand the key issues in green development assessment.

5.1.1 In-depth reflection on model applicability

The Tourism Ecological Footprint Model employed in this study serves as a robust tool for evaluating green development. However, a nuanced consideration of the model’s applicability is imperative. This model assumes the constancy of population, technology, and material consumption levels during computation. In regions with nascent economies or relative poverty, this assumption might lead to erroneously small ecological footprint values, falsely suggesting sustainability. Future research should rigorously validate the model’s applicability across diverse regions and developmental stages.

5.1.2 Challenges related to data reliability

While this study imposed high data requirements on the Tourism Ecological Footprint Model, real-world data collection may encounter challenges. In particular, various aspects involving consumption data, conversion factors (equilibrium factors), and energy/biological resource data can directly impact the accuracy of model calculations. Future research needs to diligently address these challenges to enhance data reliability.

5.1.3 Limitations in the overall calculations of the model

The Tourism Ecological Footprint Model is often confined to calculating the overall ecological footprint of a specific region, while temporal and spatial dimensions are neglected. For instance, during peak tourism seasons, the ecological footprints might surpass ecological carrying capacity while the overall assessments might still be deemed sustainable during off-peak seasons. Future research should explore methods with greater spatiotemporal flexibility to accurately capture the fluctuations in ecological footprints.

5.1.4 Prospects for green development strategies

While this study provides practical green development recommendations for the Wenfeng Mountain Scenic Area, it underscores the need for region-specific green development strategies in diverse mountainous terrains. Subsequent research endeavors should explore a myriad of green development schemes tailored to distinct regional characteristics and demands.
In conclusion, through an in-depth discussion of the study’s findings, we provide a comprehensive understanding of green development in mountainous scenic areas, and offer valuable insights for future research and decision-making endeavors.

5.2 Policy implications

In this section, we combine the key findings of our study to propose pertinent policy recommendations, with the aim of guiding future decision-making and management practices.

5.2.1 Reinforcement of ecological conservation measures

Considering that the Wenfeng Mountain Scenic Area’s tourism development still resides in an ecological surplus state, one recommendation is that the government should continue to propel the rapid growth of the tourism industry while intensifying efforts in ecological environment protection and management. This will entail ensuring that the impact of tourism activities consistently remains within the ecological carrying capacity. Achieving sustainability in ecological balance can be facilitated through the formulation of more stringent environmental protection policies and standards, augmented law enforcement, and a steadfast commitment to ecological preservation.

5.2.2 Optimization of tourism resource allocation and management

To realize a dual win-win situation of sustainable tourism development and ecological preservation, the government can enhance the planning and management of tourism resources. Scientifically orchestrating the tourism resources within the scenic area, optimizing the structure of tourism products, and improving resource utilization efficiency can collectively mitigate adverse impacts on the ecological environment.

5.2.3 Integration of technological means for enhanced management

Leveraging advanced technological tools such as intelligent monitoring systems and big data analytics can elevate the oversight of tourism activities. This advancement will facilitate a more timely and comprehensive understanding of the impact of tourism activities on the ecological environment, and provide decision-makers with a scientific basis for informed decision-making.
Promotion of tourist education and behavioral guidance: Strengthening education for tourists to heighten their awareness regarding the environmental impacts of their behavior is crucial. This can be achieved through initiatives such as awareness campaigns and informative signage to guide tourists toward more environmentally conscious travel behavior. The government's role is pivotal in fostering responsible tourism practices.

5.2.4 Increasing investment to foster ecological sustainability

Governments can augment their investments in ecological sustainability, in support of relevant research projects, to propel continual innovation in ecological environment monitoring and assessment technologies. This will aid in enhancing the accuracy and scientific validity of green development assessments.
In summary, through clear policy implications, we can offer beneficial recommendations for the management and decision-making processes of Wenfeng Mountain Scenic Area and similar mountainous terrains. Following these recommendations can propel them toward achieving green and sustainable goals within the realm of tourism development.

6 Conclusions

Based on the tourism ecological footprint model, this study assessed the green development status of the Wenfeng Mountain Scenic Area. Through the calculation and analysis of the tourism ecological footprint, ecological carrying capacity, and ecological surplus, the tourism development in the Wenfeng Mountain Scenic Area is still in a state of ecological surplus. Therefore, the impact of tourism activities on the local ecological environment has not exceeded the carrying capacity, and the ecological environment has been well maintained and protected.
This conclusion is of great significance for the sustainable development and promotion of green tourism in the Wenfeng Mountain Scenic Area. While continuing to promote rapid tourism industry development, ecological protection and management must be further strengthened to ensure the coordinated development of tourism activities and the ecological environment. By properly planning and managing tourism resources, optimizing the structure of tourism products, and improving resource utilization efficiency, sustainable tourism development and ecological conservation can be achieved in a win-win situation.
Through the assessment and analysis conducted here, this study provides valuable references and guidance for the green development of the Wenfeng Mountain Scenic Area, as well as insights for similar mountainous scenic areas. With continuous efforts and improvements, the sustainable development of the tourism industry and the ecological environment can be achieved, providing people with better tourism experiences and environmental quality.

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