Search results

The purpose of this paper is to focus on tracing GHG emissions across the supply chain industries associated with the US residential, commercial and industrial building stock and provides optimized GHG reduction policy plans for sustainable development.

A two-step hierarchical approach is developed. First, Economic Input-Output-based Life Cycle Assessment (EIO-LCA) is utilized to quantify the GHG emissions associated with the US residential, commercial and industrial building stock. Second, a mixed integer linear programming (MILP) based optimization framework is developed to identify the optimal GHG emissions’ reduction (percent) for each industry across the supply chain network of the US economy.

The results indicated that “ready-mix concrete manufacturing”, “electric power generation, transmission and distribution” and “lighting fixture manufacturing” sectors were found to be the main culprits in the GHG emissions’ stock. Additionally, the majorly responsible industries in the supply chains of each building construction categories were also highlighted as the hot-spots in the supply chains with respect to the GHG emission reduction (percent) requirements.

The decision making in terms of construction-related expenses and energy use options have considerable impacts across the supply chains. Therefore, regulations and actions should be re-organized around the systematic understanding considering the principles of “circular economy” within the context of sustainable development.

Although the literature is abundant with works that address quantifying environmental impacts of building structures, environmental life cycle impact-based optimization methods are scarce. This paper successfully fills this gap by integrating EIO-LCA and MILP frameworks to identify the most pollutant industries in the supply chains of building structures.

Carbon footprint assessment requires a holistic approach, where all possible lifecycle stages of products from raw material extraction to the end of life are considered. The purpose of this paper is to develop an analytical sustainability assessment framework to assess the carbon footprint of US economic supply chains from two perspectives: supply chain layers (tiers) and carbon footprint sources.

The methodology consists of two phases. In the first phase, the data were collected from EORA input output and environmental impact assessment database. In the second phase, 48 input-output-based lifecycle assessment models were developed (seven CO₂ sources and total CO₂ impact, and six supply chain tiers). In the third phase, the results are analyzed by using data visualization, data analytics, and statistical approaches in order to identify the heavy carbon emitter industries and their percentage shares in the supply chains by each layer and the CO₂ source.

Vast majority of carbon footprint was found to be attributed to the power generation, petroleum refineries, used and secondhand goods, natural gas distribution, scrap, and truck transportation. These industries dominated the entire supply chain structure and found to be the top drivers in all six layers.

This study decomposes the sources of the total carbon footprint of US economic supply chains into six layers and assesses the percentage contribution of each sector in each layer. Thus, it paves the way for quantifying the carbon footprint of each layer in today’s complex supply chain structure and highlights the importance of handling CO₂ source in each layer separately while maintaining a holistic focus on the overall carbon footprint impacts in the big picture. In practice, one size fits all type of policy making may not be as effective as it could be expected.

This paper provides a two-dimensional viewpoint for tracing/analyzing carbon footprint across a national economy. In the first dimension, the national economic system is divided into six layers. In the second dimension, carbon footprint analysis is performed considering specific CO₂ sources, including energy production, solvent, cement and minerals, agricultural burning, natural decay, and waste. Thus, this paper contributes to the state-of-art sustainability assessment by providing a comprehensive overview of CO₂ sources in the US economic supply chains.

Water heating is one of the major energy‐consuming operations in the lodging sector. The purpose of the current study is to estimate the energy consumed and emission associated with hot water usage, to predict the energy cost required under different hot water systems in hotels; and to create a model for the decision‐making criteria in selecting hot water systems.

A total of 24 hotels, which use heat pumps as their main water heating systems, were investigated. A tailor‐made model for estimating the energy requirement of the water heating system was employed. Comparative studies on the energy consumption and energy costs of various types of water heating systems, including heat pumps, diesel boilers, gas boilers, and electric boilers, were conducted. Moreover, an analytic hierarchy process was used to analyze hoteliers' and lenders' selection criteria for water heating facilities.

The energy output for water heating by heat pumps was estimated at 15 GW in the lodging sector. The use of heat pumps can achieve substantial energy savings and reduction of air pollutants when compared with the energy requirements under conventional boilers. The latter accounts for 13 percent of the hoteliers' total decision weight on choosing water‐heating systems. Whereas the air pollutants generated by gas‐fired boilers are remarkably lower than those emitted in the power plants due to the use of heat pumps. Both bankers and hoteliers consider seriously the energy saving potential of hot water supply by trucks.

Due to the small number of decision‐makers in hotels participating in the analytic hierarchy process, the result can only provide an indication of the overall picture of the selection criteria adopted by hoteliers.

The analysis provides hotel owners and managers with an objective and scientific investigation of the emission prediction and energy cost estimation based on the use of different hot water systems. Hotel operators and owners can use the analytical results as reference for making green purchasing decisions.

The current study, which is based on the operational experiences of existing hotels, is a collaborative work between hospitality industry practitioners and educators. It is also the first of its kind to indicate the emission impact of various types of hotel water heating systems and the perspectives of hoteliers and bankers on these systems.

Although extensive studies have examined the link between tourism and carbon emissions, the impact of tourism on carbon emissions remains controversial. In contrast to prior studies, this study aims to investigate the effects of tourism on carbon emissions at the city level and the underlying moderating mechanism.

This study designs an econometric model drawing on panel data for 313 city-level regions in China from 2001 to 2019. This study also performs rigorous robustness tests to support the regression results. In addition, the temporal and spatial heterogeneity is analyzed based on which this study discusses the moderators of the effects of tourism on carbon emissions.

The results show that both tourist arrivals and tourism revenue significantly impact carbon emissions. Also, there exists a significant temporal and spatial heterogeneity of these effects. Economic development significantly enhances while green technology and tertiary industry development suppress the positive relationship between tourism and carbon emissions. Moreover, regarding the impact on carbon emissions, an explicit substitution exists between tourism and tertiary industry development.

For the first time, this study quantitatively estimates the moderators of tourism’s impact on carbon emissions and concludes the moderating effects of economic growth, technological progress and industrial structure, thus furthering the theoretical understanding of the heterogeneity of tourism’s association with carbon emissions. The study also fills a technical gap in previous studies by demonstrating the reliability of the findings through various robustness tests. This is also the first empirical study to systematically examine the relationship between tourism and carbon emissions in China.

尽管已经有大量的研究考察了旅游和碳排放之间的联系, 但旅游对碳排放的影响仍有争议。与之前的研究相比, 本研究旨在研究城市层面上旅游业对碳排放的影响以及潜在的调节机制。

本研究基于2001-2019年中国313个城市层面的面板数据, 设计了一个计量经济学模型。本研究还进行了各种严格的稳健性检验以支持基准回归结果。本研究还分析了时空异质性, 并在此基础上讨论了旅游对碳排放影响的调节因素。

研究结果显示, 旅游者人次和旅游收入都对碳排放有明显影响。同时, 这些影响存在明显的时间和空间异质性。经济发展明显增强但是绿色技术和第三产业发展抑制了旅游业与碳排放之间的正向关系。此外, 旅游业和第三产业发展在对碳排放的影响方面存在显著的替代关系。

本研究首次定量估计了旅游业对碳排放影响的调节因素, 并总结出经济增长、技术进步和产业结构的调节作用, 从而进一步推动了对旅游业与碳排放关联的异质性的理论认识。文章还填补了以往研究的技术空白, 通过各种稳健性检验证明了研究结果的可靠性。本研究还是第一个系统地研究中国旅游业与碳排放关系的实证研究。

Este estudio diseña un modelo econométrico basado en datos de panel para 313 regiones a nivel de ciudad en China desde 2001 hasta 2019. Este estudio también aplica rigurosas pruebas de robustez para apoyar los resultados de la regresión. Además, se analiza la heterogeneidad temporal y espacial en base a la cual este estudio discute los moderadores efectos del turismo en las emisiones de carbono.

Aunque numerosos estudios han examinado la relación entre el turismo y las emisiones de carbono, su impacto sigue siendo controvertido. A diferencia de los estudios anteriores, este estudio pretende investigar los efectos del turismo en las emisiones de carbono a nivel de ciudad y el mecanismo moderador subyacente.

Los resultados muestran que tanto las llegadas de turistas como los ingresos por turismo influyen significativamente en las emisiones de carbono. Además, existe una importante heterogeneidad temporal y espacial de estos efectos. El desarrollo económico aumenta significativamente, mientras que la tecnología verde y el desarrollo de la industria terciaria suprimen la relación positiva entre el turismo y las emisiones de carbono. Además, en lo que respecta al impacto sobre las emisiones de carbono, existe una sustitución explícita entre el turismo y el desarrollo de la industria terciaria.

Por primera vez, este estudio estima cuantitativamente los moderadores del impacto del turismo en las emisiones de carbono y concluye los efectos moderadores del crecimiento económico, el progreso tecnológico y la estructura industrial, lo que permite avanzar en la comprensión teórica de la heterogeneidad de la asociación del turismo con las emisiones de carbono. El artículo también resuelve una carencia técnica de los estudios anteriores al demostrar la fiabilidad de las conclusiones mediante diversas pruebas de solidez. Este es también el primer estudio empírico que examina sistemáticamente la relación entre el turismo y las emisiones de carbono en China.

The purpose of this paper is to address the question of how a developing country, like Mexico, can reform its electricity industry at the same time as addressing climate change issues.

The objective is to provide a tool that policy makers could use to make better and more informed decisions if they decide to liberalise the power sector in Mexico. The problems they would face are difficult to address in an analytically tractable way using conventional economic models. Also, these problems are too idiosyncratic to solve by translating empirical experience from other markets. In response, a system dynamics model has been developed in order to test the impact of a range of different environmental and energy policies.

The paper finds that a reform setting where competition is allowed in fossil fuel technologies; while the public company (CFE) keeps control of hydro and nuclear capacity produce the most well rounded scores in terms of efficiency, CO2 emission reductions and political feasibility. The results could improve the policy implementation process by shedding light on the circumstances and policy choices that can exacerbate or minimise effects.

A simulation of this kind would increase the understanding of these kinds of policies by providing structured insights into key uncertainties. They can also foster new ideas – in the energy sector have underpinned major policy initiatives. But results should be taken with caution, as complete validation of models is impossible.

These results add to the policy implementation literature. For the case of Mexico that has not engaged in a specific model of deregulation, the use of simulation model would be very useful to predict flaws in the design of the new regulation and to prevent unwanted scenarios to happen.

A judicious implementation of an electricity reform can help achieve lower carbon emissions reductions which would be beneficial against the climate change problem.

To the author's knowledge, the approach of analysing ex ante the environmental outcome of electricity reform using a simulation model in a developing country has not been treated in literature.

This study aims to create the causal relationship between transportation behavior to Karimunjawa, the number of tourists and the amount of CO2 produced; calculate the reduction of CO2 emissions from the transportation to Karimunjawa based on several proposed policy scenarios; and formulate the managerial implication and recommendation to support the implementation of several proposed policy scenarios.

This study develops a system dynamics‐based model by using three sub-systems, i.e. “the number of tourist sub-system,” “the switching behavior of tourist travel sub-system” and “the CO2 emission sub-system.”

The simulation results have shown that, under the current situation, tourist travel behavior should be changed to maximum condition to get the minimum CO2 emission. Improvement of the behavior of tourist in selecting the mode of transportation and the departure point of mini-tour bus and ferry are an effective way to reduce the CO2 emission.

This study only considers limited variables as the driver of the level of change of the capacity of Karimunjawa and the road as well as the variables as the driver of tourism growth. This study only focuses on CO2 emission from the direct impacts of tourist travel; this study does not consider the indirect impact of tourism activity on CO2 emissions. International air travel is not included in the present study.

From a managerial perspective, this study demonstrates that change in the tourist travel behavior is generally not effective in triggering CO2 emission reduction, unless it is accompanied by the strict restriction policy related to the tourist route.

This study has the potential to raise societal awareness that the causality of tourist growth and CO2 emissions should be seen as the impact of tourist travel behavior. In this case, to modify the travel behavior, tourist needs to change their mode of transportation to more sustainable transportation.

This paper intends to fill the literature gap of the effect of tourism growth from two perspectives, namely, tourist travel behavior and environmental. The modeling of tourist transport and CO2 emission will provide an overview of the selection of the problem-solving mode for tourist transport that can give a significant contribution to the greenhouse gas emissions reduction to the environmental.

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.

This paper aims to quantify the loss (or leakage) of organic cattle to conventional value chains in Ireland and assess its economic and environmental impacts.

The paper adopts a Bio-economy Input-Output (BIO) model, a quantitative economic model representing the interdependencies between different sectors of the economy, to assess the economic and environmental impacts of organic leakage in the Irish beef sector.

The study reveals that 17% of organic cattle aged under 1 year old leave the organic value chain, leaking to the conventional market as a result of imbalances in the development of the beef value chain. The economic cost of this organic leakage is 5.66 million euros. Leakage also has environmental effects because of changes in lifecycle methane and nitrogen emissions based on longer finishing times on organic farms and chemical fertilisers applied on conventional farms. The organic leakage results in a reduction of 82 tons of methane emission and 52 additional tons of nitrogen emission, which leads to 11,484 tons of net global warming potential (GWP) for a 100-year time horizon.

Because of data availability, the research focussed on the baseline year 2015, which had national data available for disaggregation in Ireland. Therefore, researchers are encouraged to assess the economic and environmental impacts when more recent data are available and to analyse the change in the impacts over the years.

This study contributes to the discussion on organic conversion and provides valuable insights for stakeholders, especially policymakers, for the design of future organic schemes.

This is the first paper to assess organic leakage in the beef sector.

The purpose of this paper is to provide an input-output life cycle assessment model to estimate the carbon footprint of US manufacturing sectors. To achieve this, the paper sets out the following objectives: develop a time series carbon footprint estimation model for US manufacturing sectors; analyze the annual and cumulative carbon footprint; analyze and identify the most carbon emitting and carbon intensive manufacturing industries in the last four decades; and analyze the supply chains of US manufacturing industries to help identify the most critical carbon emitting industries.

Initially, the economic input-output tables of US economy and carbon footprint multipliers were collected from EORA database (Lenzen et al., 2012). Then, economic input-output life cycle assessment models were developed to quantify the carbon footprint extents of the US manufacturing sectors between 1970 and 2011. The carbon footprint is assessed in metric tons of CO₂-equivalent, whereas the economic outputs were measured in million dollar economic activity.

The salient finding of this paper is that the carbon footprint stock has been increasing substantially over the last four decades. The steep growth in economic output unfortunately over-shadowed the potential benefits that were obtained from lower CO₂ intensities. Analysis of specific industry results indicate that the top five manufacturing sectors based on total carbon footprint share are “petroleum refineries,” “Animal (except poultry) slaughtering, rendering, and processing,” “Other basic organic chemical manufacturing,” “Motor vehicle parts manufacturing,” and “Iron and steel mills and ferroalloy manufacturing.”

This paper proposes a state-of-art time series input-output-based carbon footprint assessment for the US manufacturing industries considering direct (onsite) and indirect (supply chain) impacts. In addition, the paper provides carbon intensity and carbon stock variables that are assessed over time for each of the US manufacturing industries from a supply chain footprint perspective.

This paper aims to minimize the total carbon emissions and costs and also maximize the total social benefits.

The present study develops a mathematical model for a closed-loop supply chain network of perishable products so that considers the vital aspects of sustainability across the life cycle of the supply chain network. To evaluate carbon emissions, two different regulating policies are studied.

According to the obtained results, increasing the lifetime of the perishable products improves the incorporated objective function (IOF) in both the carbon cap-and-trade model and the model with a strict cap on carbon emission while the solving time increases in both models. Moreover, the computational efficiency of the carbon cap-and-trade model is higher than that of the model with a strict cap, but its value of the IOF is worse. Results indicate that efficient policies for carbon management will support planners to achieve sustainability in a cost-effectively manner.

This research proposes a mathematical model for the sustainable closed-loop supply chain of perishable products that applies the significant aspects of sustainability across the life cycle of the supply chain network. Regional economic value, regional development, unemployment rate and the number of job opportunities created in the regions are considered as the social dimension.