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Sustainability performance of the global trade as well as of the traded products are affected by the trade policies and trade tariffs. Trade tariffs and policies can either encourage or discourage trade among the countries affecting feasibility of trade. In other words, the scope and amount of these trade tariffs have impact on the trade globally. Based on an in-depth literature review, this chapter aims to examine impacts of the trade policies and trade tariffs on the environmental footprint of the global trade. With this aim, recent trade policies and trade tariffs as well as roles of the trade policies, trade tariffs in reducing environmental footprint of the global trade are examined. It arrives at the conclusion that trade tariffs can affect environmental footprint of the global trade as well as of the traded products. They can have impact on the feasibility of the trading activities influencing their profit margins and costs. Based on these findings, recommendations for trade policies and trade tariffs are thereby provided to enhance sustainability performance of the global trade.

Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018.

After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches.

The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance.

The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

This study investigates the relationship among economic growth, energy usage, urbanization, trade openness, carbon emission, ecological footprint, and ecological carbon footprint with the sample of G-7 countries over the period 1991–2017. The Continuously-Updated and Fully-Modified (CUP-FM) estimator method applied to the panel series is utilized. As a result of empirical analysis, an increase in the real per capita GDP increases the ecological footprint by 0.844%. Also, there are positive impacts that are detrimental to the environment among the environmental quality and explanatory variables for each established model. The findings indicate that a relationship exists among the variables in the long run, and at the same time, carbon emission as an indicator of pollution should be noticed as well as the ecological footprint and ecological carbon footprint. It is observed that a positive relationship exists among the variables such as economic growth, energy usage, and environmental pollution indicator. In this context, G-7 countries indicate that, upon taking their developed economic structures and global pollution levels into account, the Environment Kuznets curve (EKC) hypothesis becomes valid, and that the U-shaped behavior is valid for the total ecological footprint. It is been seen that, besides economic growth and energy usage, other explanatory variables contribute to environmental degradation in trade openness. In compliance with these results, in terms of the sustainability of economic development, G-7 countries should pay attention to economic activities that would impair the environmental quality and control them with regulations.

The purpose of this paper is to reduce the carbon footprint of food by adjusting the international trade and planting structure and to provide possible ideas for the improvement of the world's food green production and green trade.

Using the literature analysis method to collect carbon footprint data calculated based on the life cycle assessment (LCA) method, and establishing an optimization model and an ARIMA prediction model for empirical analysis, this paper explores the possibility to reduce carbon emissions by adjusting import structure and self-production structure.

The results show that only through the adjustment of the import structure, carbon emissions can be reduced by 3.29 million tons at the source of imports. When domestic self-production is included, a total of 4.51 million tons of carbon emissions can be reduced, this provides ideas for low-carbon emission reduction in agriculture and animal husbandry.

This article is the first to use the carbon footprint data obtained by other scholars using LCA to optimize and analyze the grain trade structure and planting structure from a low-carbon perspective, and obtain specific emission reductions.

In the new global economy, environmental degradation is still among the crucial struggles braving policymakers. The intention of the current analysis, therefore, is to investigate the asymmetric impact of energy use, trade openness, population changes and urbanization, on the ecological footprint (EF) in four ASEAN countries by using time span data extending from 1972 to 2018.

The stationarity of the variables was first demonstrated by using a quantile autoregression unit root test. Then the cointegration relationship among quantiles was verified. In the third step, this study investigated the pattern of causality in quantiles which allowed them to model any locational asymmetry in such a relationship. In the final part of the paper, the asymmetric quantile approaches the methods adopted to address the ways in which the considered variables impacted on the EF.

The outcomes demonstrated that the estimated coefficient of the variables was generally found significant and in line with the expected impact sign. Likewise, locational asymmetry was detected from the fact that the considered variables at the upper tails did not operate in the same way as those in the lower ones. In this case, the results suggest that a rise in energy consumption, as well as a negative shock to economic growth and/or trade openness, all diminish environmental quality. In contrast, promoting economic growth, a positive shock to trade openness, and human capital reduce environmental degradation.

As far as is known, the current study among the early attempt to explore the asymmetric impact of trade openness, energy use, population changes and urbanization, on the EF in the ASEAN countries.

In situation of uncertainty, many companies refuse today to bind their destiny to the fate of a specific territory. Nevertheless territories are engaged in trajectories that result from their industrial history and legacies. Companies are significant actors in structuring a given territory. Their territorial footprint is plural: industrial, organisational, psycho-cultural, environmental and political. It creates trajectories, hysteresis effects and irreversibility. We will mobilise cognitive approaches and more singularly the evolutionary approach to appreciate the territorial print of a given company. We focus on the Defence industry in Brest region (Brittany, France), a singular territory formatted by the naval shipyard industry. This latter has been involved in deep reorganisations since the beginning of the 1990s. This leads to many questions about possible industrial diversification and how to rebuild a cognitive trajectory of such territory by involving local authorities and the civil society.

This study attempts to come in help for Morocco by investigating rigorously the linkage between environmental degradation, measured by ecological footprint (EF), and the gross domestic product growth (EG), the human capital (HC) index and the natural resources (NR) depletion over the period of 1980:Q1 to 2021:Q1. The paper examines the validity of environmental Kuznets curve (EKC) hypothesis in the Moroccan context.

Unlike previous studies, which are based only on the autoregressif dynamic linear (ARDL) model, this paper investigates two recent models: the novel DYNARDL simulation approach and the Kernel-based regularized least squares (KRLS) technics and uses in addition the frequency domain causality (FDC) test.

Models output say a significant and negative association between HC and the EF and a significant and positive interplay between economic growth and environmental quality in the long term. In the short term, findings reveal a significant and negative association between NR and the EF. Based on the FDC test, results conclude about a unidirectional causality from NR to the EF in short-, medium-, and long-term. Moreover, results validate the EKC hypothesis for the Moroccan environment sustainability.

In this study, the researchers use the “ecological footprint” as dependent variable to obtain more accurate and comprehensive assessment of environmental deterioration. Based on time series data investigations, this study is the first paper, which validates the EKC hypothesis and develops important policy implications for Morocco context to achieve sustainable development targets.

The purpose of this paper is to study reducing the variation of environmental footprint estimates based on multiregional input–output (MRIO) databases. Footprint estimates from various MRIO databases sometimes vary significantly. As a result, conclusions about the absolute levels or trends of a footprint may be inconsistent. The sources of these variations are attributable to three phases in the footprint calculations: differences in data preparation, MRIO database construction and footprint calculation.

This paper provides a literature overview and a breakdown of the computation of footprints based on MRIO database. Based on these insights, strategies that lead to lower variation in footprint estimates are formulated.

Convergence of footprint estimates require enhanced cooperation amongst academics, among statisticians and between academics and statisticians.

Reducing the variation in footprint estimates is a major challenge. This paper aims to contribute to this convergence in three ways. First, this paper provides the first overview of footprint work at statistical offices, government agencies and international organisations. These are the front-runners that may play a role in cooperating with academics (and other statistical offices) to resolve some of the issues. Second, a detailed analysis of the sources of the variation in estimates is provided. These problems are illustrated using examples from the various MRIO databases and the data of Statistics Netherlands. Third, strategies are discussed that might help reduce variation between footprint estimates.

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.

In a globalized economic system, the role of agrifood production is to ensure at the same time both the population's livelihood and environmental resource conservation. The present study aims at expanding the debate on the potentials of the fair-trade in terms of environmental sustainability.

The research presents a methodology divided into three phases: (1) the identification of the water footprint values associated with the production of bananas, cocoa and coffee imported from developing countries to Italy; (2) the calculation of the virtual water volumes used to produce the crops imported from developing countries to Italy through fair-trade; (3) the analysis of the economic water productivity, obtained by the fair-trade premium, for bananas, cocoa and coffee.

The results of this study identified and measured the amount of virtual water flows and water savings or losses deriving from the fair-trade of bananas, cocoa and coffee. The average virtual water flow related to the fair-trade imports in Italy amounts to 7.27 million m³ for bananas, 22,275 m³ for cocoa and 14,334 m³ for coffee. The research findings also highlight that fair-trade and the related premium ensures at the same time the achievement of social and institutional purposes but also the remuneration of virtual water used within the life cycle of the imported crops.

Previous scientific literature showed that fair-trade premium has commonly been used to finance environmental protection. No study has evaluated the environmental impacts associated with fair-trade, nor the monetary value associated with the natural resources exploited to produce crops to be exported. This empirical paper fills a literature gap in terms of identification, measurement and evaluation of virtual water flows along the supply chain processes of some fair-traded crops, also providing, through the economic water productivity approach, a useful tool for decision-makers.