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Under the global climate change, carbon footprint has become a hot issue at home and abroad. However, there is no consensus on the concept, measurement and application of carbon footprint.

In this paper, first, the concept and connotation of carbon footprint are reviewed; then, different methods of carbon footprint measurement are compared, and it is found that “bottom-up” life cycle assessment and “top-down” input–output analysis are applicable to different research scales.

Finally, the problems in the process of carbon footprint assessment in textile industry are analyzed and further research directions are proposed.

Analyzed and further research directions are proposed.

This study aims to conduct a critical analysis of online carbon calculators, assesing their accuracy and ability to provide holistic carbon impact appraisals of different elements of holiday travel. It seeks to identify the major data sources for estimates and establish the interrelatedness between them. The determinant factors for the variance in the magnitude of the carbon footprint appraisals between calculators are critically reviewed.

The paper reviews the key online carbon calculators to better understand how estimates of carbon footprint are made, what background information is available to tool users and which factors affect the accuracy and comprehensiveness of appraisals.

The study concludes that the applicability of existing carbon calculators to carbon impact assessment in tourism is limited. Moreover, poor accesibility of the background data, inconsistencies in the multiplying factors used and inhomogeneity in the appraisal methods employed question the accuracy, credibility and transparency of carbon calculators. Suggestions are made on how to improve the overall quality and reliability of carbon calculators in order to enhance their consistency, transparency and applicability in the tourism domain.

The paper contributes to a better understanding of assessment approaches available in the tourism domain to produce reliable estimates of the carbon impacts from holiday travel.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

This paper investigates the (a)symmetric effects of financial development in the presence of economic growth, energy consumption, urbanization and foreign direct investment on environmental quality of South Africa between 1980 and 2017.

A robust measure of financial development is generated using banking institutions and non-banking institutions market-based financial development indicators, while environmental quality is measured using carbon footprint, non-carbon footprint and ecological footprint. The objectives of the study are captured using linear and non-linear autoregressive distributed lag.

The result from the symmetric analysis suggests that financial development stimulates carbon footprint and ecological footprint in the short run; however, financial development abates non-carbon footprint. In the long run, financial development has a significant negative effect on carbon footprint and ecological footprint. However, the asymmetric analysis established strong asymmetric effect in the short run, while no asymmetric effect is found in the long run. The short run asymmetric analysis reveals that positive shock in financial development increases carbon footprint and ecological footprint; however, positive changes in financial development reduce non-carbon footprint. Negative shocks in financial development, on the other hand, have a positive impact carbon footprint, non-carbon footprint and ecological footprint.

The study's outcome implies that the concept of “more finance, more growth” could also be applied to “more finance, better environment” in South Africa. The study offers vital policy suggestions for the realization of sustainable development in South Africa.

This empiric adds to the body of knowledge on the influence of financial development on various components of environmental quality (carbon footprint, non-carbon footprint and ecological footprint) in South Africa.

The purpose of this paper is to present a comprehensive analysis of the carbon footprint of the Delft University of Technology (TU Delft), including direct and indirect emissions from utilities, logistics and purchases, as well as a discussion about the commonly used method. Emissions are presented in three scopes (scope 1 reports direct process emissions, scope 2 reports emissions from purchased energy and scope 3 reports indirect emissions from the value chain) to identify carbon emission hotspots within the university’s operations.

The carbon footprint was calculated using physical and monetary activity data, applying a process and economic input-output analysis.

TU Delft’s total carbon footprint in 2018 is calculated at 106 ktCO₂eq. About 80% are indirect (scope 3) emissions, which is in line with other studies. Emissions from Real estate and construction, Natural gas, Equipment, ICT and Facility services accounted for about 64% of the total footprint, whereas Electricity, Water and waste-related carbon emissions were negligible. These findings highlight the need to reduce universities’ supply chain emissions.

A better understanding of carbon footprint hotspots can facilitate strategies to reduce emissions and finally achieve carbon neutrality. In contrast to other work, it is argued that using economic input-output models to calculate universities’ carbon footprints is a questionable practice, as they can provide only an initial estimation. Therefore, the development of better-suited methods is called for.

As net-zero pledges gain momentum globally, more and more accommodation businesses seek to quantify their carbon emissions. Building on Chan (2021), this study aims to explore what drives Australian accommodation providers to measure the carbon footprint of their businesses and what barriers hinder them from doing so.

Empirical data were collected by conducting ten semi-structured interviews with owners, senior executives, consultants, certification bodies and hotel management companies. The set of interviews represented different segments of the hotel industry and various accommodation types. Data were analysed with thematic analysis.

The major drivers for adopting carbon footprint analysis are as follows: the analysis being perceived as an important contribution to a company's corporate responsibility, the owner or manager's environmental concern, the assessment being a requirement for obtaining an eco-certification and the business benefits associated with implementing the initiative. The major barriers hindering adoption include the following: difficulties with data gathering, the lack of a standard methodology, a lengthy decision-making process and a lack of resources.

Based on the empirical findings and three theories on ecological responsiveness, this study develops a conceptual framework for implementing carbon footprint analysis in the accommodation context and recommends strategies to increase the adoption of carbon footprint analysis.

This study responds to Chan and Hsu's (2016) call for further research on carbon footprint in the hotel context and represents the first attempt to explore the drivers and barriers specifically associated with implementing carbon footprint analysis in the accommodation sector.

The term “carbon footprint” emerged during the early 2000s, but many hotels remain unaware of what they should do to implement a comprehensive programme to reduce carbon footprint despite having some environmental measures. This study aims to investigate the barriers to reducing hotel carbon footprint and to explore why many hotel managers remain bystanders.

In-depth semi-structured interviews were conducted with hotel executives to understand what hinders hotels’ implementation of comprehensive programmes to reduce their carbon footprint. The NVivo 11 software package was used to organise data and code the transcribed interviews to identify patterns and themes.

The findings identified several main barriers. They were (1) a lack of understanding, (2) a lack of owner initiative, (3) difficulty with measurements, (4) a lack of stakeholder coordination and support, (5) a lack of a strong mediator, (6) balancing interests and (7) risky investment. The findings of this study suggest some specific strategies for overcoming these barriers.

The study sample was restricted to the Hong Kong hotel executives interviewed; therefore, the findings will not reflect the full picture of managerial perceptions. Drawing on the foundations laid by this study, researchers could collect quantitative data from hotels in other countries to conduct a cross-cultural study.

Very few studies have investigated barriers to carbon-footprint reduction programmes. Specifically, none have been published in the hotel environmental management literature. This study represents a preliminary step towards understanding the barriers that prevent hotels from implementing the programmes.

The paper investigates the effects of climate change along with ecological and carbon footprint on rice crop production in India during 1982–2016.

The autoregressive distributed lag (ARDL), canonical cointegration regression (CCR) and fully modified ordinary least square (FMOLS) models are used in the paper.

A long-run relationship is found between climate change and rice production in India. Results report that ecological footprint and carbon footprint spur long-term rice production. While rainfall boosts rice crop productivity in the short term, it has a negative long-term impact. Further, the findings of ARDL models are validated by other cointegration models, i.e., the FMOLS and CCR models.

This study provides insights into the role of ecological footprint and carbon footprint along with climate variables in relation to rice production.

In the literature, the effects of ecological and carbon footprint on rice production are missing. Therefore, this is the first study to empirically examine the impact of climate change along with ecological footprint and carbon footprint on rice production in India.

The purpose of this study is to model a vehicle routing problem with integrated picking and delivery under carbon cap and trade policy. This study also provides sensitivity analyses of carbon cap and price to the total cost.

A mixed integer linear programming (MILP) model is formulated to model the vehicle routing with integrated order picking and delivery constraints. The model is then solved by using the CPLEX solver. Carbon footprint is estimated by a fuel consumption function that is dependent on two factors, distance and vehicle speed. The model is analyzed by considering 10 suppliers and 20 customers. The distance and vehicle speed data are generated using simulation with random numbers.

Significant amount of carbon footprint can be reduced through the adoption of eco-efficient vehicle routing with a marginal increase in total transportation cost. Sensitivity analysis indicates that compared to carbon cap, carbon price has more influence on the total cost.

The model considers mid-sized problem instances. To analyze large size problems, heuristics and meta-heuristics may be used.

This study provides an analysis of carbon cap and price model that would assist practitioners and policymakers in formulating their policy in the context of carbon emissions.

This study provides two significant contributions to low carbon supply chain management. First, it provides a vehicle routing model under carbon cap and trade policy. Second, it provides a sensitivity analysis of carbon cap and price in the model.

The purpose is to analyse the nutritional adequacy and carbon footprint of intermediated meals provided to preschool children and primary-level students in a Portuguese municipality.

An observational cross-sectional study was conducted with a convenience sampling consisting of school snacks from a Portuguese municipality. The nutritional assessment used food labels and a Portuguese food composition table. The literature review for carbon footprint assessment was conducted by searching for the products under analysis or similar ones.

The results showed that 80% of snacks have a higher energy value than recommended. The majority of options are below recommendations for protein and fat and above recommendations for carbohydrates. The intermediated meals with more dairy products in composition have the highest carbon footprint. The carbon footprint included the packaging of the products, and it wasn't possible to determine the influence of non-food products.

This study has limitations in the fact that we do not know the carbon footprint of Portuguese products and we had to compare them with others, from different countries, with possibly different types of production.

Intermediate meals are inadequate, and the carbon footprint is higher when the intermediated meals include products of animal origin – the reason why the composition of intermediated meals should be redesigned considering the achievement of these targets.

The promotion of intermediated meals that promote the Mediterranean eating pattern contributes to health and well-being and is a vehicle for nutrition education and healthy food consumption in schools.

Many studies have been conducted to analyse the carbon footprint and environmental impact of school meals, but commonly lunch is the meal evaluated and the assessment of intermediated meals' impact is an open field.