“…In addition, tourism accommodations and tourism catering are important components of the tourism footprint, accounting for 3-21% and 2-16% of the total TCF, respectively. Furthermore, traveling by air is a dominant and increasing factor in the energy consumption and CO 2 emissions of tourism transportation [17,20,22,74], especially for isolated or island-based destinations, where tourists overwhelmingly arrive by air [18,20,48]. …”
Section: Measurement Resultsmentioning
confidence: 99%
“…Combining the two methods can effectively provide more comprehensive and accurate results, as observed in tourism footprint calculations that have been performed in New Zealand [18], Australia [20] and Switzerland [52] (Table 1). In addition, Cadarso et al [22], Zhong et al [25], and Zhou et al [58] combined IO analysis with an LCA to build the IO-LCA joint model, which reduces truncation errors and superpositions and simplifies the calculation process. Overall, comprehensive methods will make tourism footprint results more dependable and less contestable.…”
Section: Methodsmentioning
confidence: 99%
“…Against this background, TCF analysis focuses on environmental issues caused by large-scale tourism, particularly its energy consumption and CO 2 emissions (defined as the amount of CO 2-eq emissions caused directly and indirectly by tourism activity), which have been widely researched at various scales, such as analyses for the countries of New Zealand [18], Sweden [19], Australia [20], Spain [21,22], Iceland [23], and China [24][25][26]; the regions of Taiwan [27][28][29], Wales [30], and Poole [31]; and even the scenic locations of the Penghu Islands [32] and Huangshan National Park [33]. TCF analysis excels at assessing the impact of tourism greenhouse gas emissions on climate change and identifying the contribution of tourism carbon emissions to climate change at the global scale, which has become a key research field.…”
Section: Rootsmentioning
confidence: 99%
“…Few longitudinal studies have examined the tourism footprint based on different regions and time series analyses, although the analyses by Cadarso et al [22], Sharp et al [23], Sun [29] and Tang et al [47] are based on a time series. This deficit means that we cannot effectively understand the dynamic change trend in the tourism footprint and the impact of tourism activities on the environment across time dimensions.…”
Section: Performing Space-time Calculations Of the Tourism Footprintmentioning
Abstract:The tourism footprint family comprises the tourism ecological footprint (TEF), the tourism carbon footprint (TCF) and the tourism water footprint (TWF). The tourism footprint represents an important tool for quantitatively assessing the impact of tourism activities on the ecosystem of a tourist destination. This paper systematically reviews the relevant literature on TEF, TCF and TWF, analyses and summarizes the main progress and failures in the analytical frameworks, research methods, measurement results, environmental impacts and reductions in the tourism footprint. This paper also proposes areas for further developing the tourism footprint research, including unifying the analytical frameworks and boundaries of the tourism footprint, distinguishing the geographical scope of the tourism footprint effectively, improving the process of analyzing the environmental impact of the tourism footprint, measuring the tourism footprint scientifically and roundly, performing space-time calculations of the tourism footprint, and expanding the tourism footprint family by introducing new members. Accordingly, this paper is devoted to the continued study of the tourism footprint.
“…In addition, tourism accommodations and tourism catering are important components of the tourism footprint, accounting for 3-21% and 2-16% of the total TCF, respectively. Furthermore, traveling by air is a dominant and increasing factor in the energy consumption and CO 2 emissions of tourism transportation [17,20,22,74], especially for isolated or island-based destinations, where tourists overwhelmingly arrive by air [18,20,48]. …”
Section: Measurement Resultsmentioning
confidence: 99%
“…Combining the two methods can effectively provide more comprehensive and accurate results, as observed in tourism footprint calculations that have been performed in New Zealand [18], Australia [20] and Switzerland [52] (Table 1). In addition, Cadarso et al [22], Zhong et al [25], and Zhou et al [58] combined IO analysis with an LCA to build the IO-LCA joint model, which reduces truncation errors and superpositions and simplifies the calculation process. Overall, comprehensive methods will make tourism footprint results more dependable and less contestable.…”
Section: Methodsmentioning
confidence: 99%
“…Against this background, TCF analysis focuses on environmental issues caused by large-scale tourism, particularly its energy consumption and CO 2 emissions (defined as the amount of CO 2-eq emissions caused directly and indirectly by tourism activity), which have been widely researched at various scales, such as analyses for the countries of New Zealand [18], Sweden [19], Australia [20], Spain [21,22], Iceland [23], and China [24][25][26]; the regions of Taiwan [27][28][29], Wales [30], and Poole [31]; and even the scenic locations of the Penghu Islands [32] and Huangshan National Park [33]. TCF analysis excels at assessing the impact of tourism greenhouse gas emissions on climate change and identifying the contribution of tourism carbon emissions to climate change at the global scale, which has become a key research field.…”
Section: Rootsmentioning
confidence: 99%
“…Few longitudinal studies have examined the tourism footprint based on different regions and time series analyses, although the analyses by Cadarso et al [22], Sharp et al [23], Sun [29] and Tang et al [47] are based on a time series. This deficit means that we cannot effectively understand the dynamic change trend in the tourism footprint and the impact of tourism activities on the environment across time dimensions.…”
Section: Performing Space-time Calculations Of the Tourism Footprintmentioning
Abstract:The tourism footprint family comprises the tourism ecological footprint (TEF), the tourism carbon footprint (TCF) and the tourism water footprint (TWF). The tourism footprint represents an important tool for quantitatively assessing the impact of tourism activities on the ecosystem of a tourist destination. This paper systematically reviews the relevant literature on TEF, TCF and TWF, analyses and summarizes the main progress and failures in the analytical frameworks, research methods, measurement results, environmental impacts and reductions in the tourism footprint. This paper also proposes areas for further developing the tourism footprint research, including unifying the analytical frameworks and boundaries of the tourism footprint, distinguishing the geographical scope of the tourism footprint effectively, improving the process of analyzing the environmental impact of the tourism footprint, measuring the tourism footprint scientifically and roundly, performing space-time calculations of the tourism footprint, and expanding the tourism footprint family by introducing new members. Accordingly, this paper is devoted to the continued study of the tourism footprint.
“…However, the carbon footprint embodied in the tourism industry includes infrastructure construction, hotel building construction, catering services, transportation etc., which leads to an underestimation of the tourism sector's environmental responsibility [2][3][4]. There is obvious economic growth for those countries that have endeavored in tourism development [5][6][7][8].…”
This research is the first attempt of a carbon emission investigation of tourism-based farms. A total of 36 cases were investigated. The result reveals that each tourist returns an average revenue of 28.6 USD and generates an average 10.9 kg-CO2eq per visit of carbon emissions. The average carbon emission density for each land area is 8.2 t/ha·year and is 245 kg/m²·year for each floor area. It is estimated that the overall carbon emissions reach 321,751 tons annually. The tourism-based farms were clustered into five categories, based on their business characteristics. It was found that high-end vacation leisure farms produce 2.46 times the carbon emissions than natural eco-conservation farms. Carbon emissions were 42% higher than the annual average in July and August. A secondary high season is in February, but it is merely higher than the annual average by 8% because of the mild climate. Two significant models for predicting carbon emissions were constructed by stepwise regression. As agriculture administrative authorities in Taiwan gradually have begun admitting the cultivated lands for multi-purpose usage, tourism-based farms have been increasing drastically. This study provides references for both public authorities and farm managers in exploring the issues with regard to carbon emissions and farm sustainability.
Achieving carbon neutrality targets requires substantial financial support. Effective utilization of renewable energy is an essential means of promoting energy‐saving and emission reduction to realize a green and circular economy. This paper combines carbon trading mechanisms with the operational mode of Chinese micro‐grid enterprises. This method uses the real options theory to construct an investment decision model for photovoltaic (PV) micro‐grid enterprises. The study aims to analyze the impact of carbon trading revenue on a numerical simulation of PV micro‐grid enterprise investment decisions. The findings demonstrate that when projected growth rates, volatility standard deviations, and risk‐free interest rates rise in the carbon trading market, the carbon price threshold rises, causing businesses to seek out investment opportunities with higher future carbon prices. The increase of micro‐grid generation technology acceptance probability, the availability of resources to meet generation investment requirements, and the generation project cycle will decrease the carbon price threshold and accelerate enterprise investment. Studying the influence of carbon trading prices on micro‐grid investment has specific guidance and practical significance for future government subsidy policies and the investment strategies of grid enterprises.
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