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This work analyzes gendered processes by a methodology based on clustering factors with influence in the decision-making process of women as users or employees of the transport system. Considering gender as a social construction which changes over time and space, this study is based on the concept of a woman as a person who adopts this role in society. This paper performs a deep analysis of those factors women consider as needs and barriers to use or work in the transport system in four scenarios: railway public transport infrastructures, automated vehicles, bicycle sharing, and jobholders. A literature review and focus group discussions were performed under the consideration that the definition of woman includes the addition of several personal characteristics (age, sexual orientation, family responsibilities, and culture). The data analysis allowed the identification of fairness characteristics (FCs) that affect the interaction of women with the transport system for each scenario. A methodology for clustering the fairness characteristics identified the main areas of action to improve the inclusion of women within each use case. Further studies will be focused on the quantification and prioritization of the FCs through mathematical methods and the suggestion of inclusive measures by an interdisciplinary panel.

The optimal response to a potential productivity shock which becomes more imminent with global warming is to have carbon taxes to curb the risk of a calamity and to accumulate precautionary capital to facilitate smoothing of consumption. This paper investigates how differences between regions in terms of their vulnerability to climate change and their stage of development affect the cooperative and non-cooperative responses to this aspect of climate change. It is shown that the cooperative response to these stochastic tipping points requires converging carbon taxes for developing and developed regions. The non-cooperative response leads to a bit more precautionary saving and diverging carbon taxes. We illustrate the various outcomes with a simple stylized North–South model of the global economy.

Abstract Background Car driving is a form of passive transportation associated with higher sedentary behaviour, which is associated with morbidity. The decision to drive a car is likely to be influenced by the ‘drivability’ of the built environment, but there is lack of scientific evidence regarding the relative contribution of environmental characteristics of car driving in Europe, compared to individual characteristics. This study aimed to determine which neighbourhood- and individual-level characteristics were associated with car driving in adults of five urban areas across Europe. Second, the study aimed to determine the percentage of variance in car driving explained by individual- and neighbourhood-level characteristics. Methods Neighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n = 4258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model. Results Higher residential density (β:-2.61, 95%CI: − 4.99; -0.22) and higher land-use mix (β:-3.73, 95%CI: − 5.61; -1.86) were significantly associated with fewer weekly minutes of car driving. At the individual level, higher age (β: 1.47, 95%CI: 0.60; 2.33), male sex (β: 43.2, 95%CI:24.7; 61.7), being employed (β:80.1, 95%CI: 53.6; 106.5) and ≥ 3 person household composition (β: 47.4, 95%CI: 20.6; 74.2) were associated with higher weekly minutes of car driving. Individual and neighbourhood characteristics contributed about equally to explained variance in minutes of weekly car driving, with 2 and 3% respectively, but total explained variance remained low. Conclusions Residential density and land-use mix were neighbourhood characteristics consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual- and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas. This study suggests that more, higher quality, and longitudinal data are needed to increase our understanding of car use and its effects on determinants of health.

The relatively new and still amorphous concept of 'green growth' can be understood as a call for balancing longer-term investments in sustaining environmental wealth with nearer-term income growth to reduce poverty. We draw on a large body of economic theory available for providing insights on such balancing of income growth and environmental sustainability. We show that there is no a priori assurance of substantial positive spillovers from environmental policies to income growth, or for a monotonic transition to a 'green steady state' along an optimal path. The greenness of an optimal growth path can depend heavily on initial conditions, with a variety of different adjustments occurring concurrently along an optimal path. Factor-augmenting technical-change targeting at offsetting resource depletion is critical to sustaining long-term growth within natural limits on the availability of natural resources and environmental services.

Abstract This paper analyzes a game in which countries repeatedly make emission and technology investment decisions. We derive the best equilibrium, that is, the Pareto-optimal subgame-perfect equilibrium, when countries are insufficiently patient for folk theorems to be relevant. Relative to the first best, the best equilibrium requires countries to overinvest in technologies that are green, that is, strategic substitutes for polluting, but to underinvest in adaptation and brown technologies, that is, strategic complements to polluting. Technological transfers and spillovers might discourage investments but can be necessary to motivate compliance with emissions when countries are heterogeneous.

This study reviews the scientific literature for business models contributing to sustainable plastic management and suggests avenues for future research. We define sustainable plastic management (SPM) as any technique along the waste hierarchy seeking to minimize the environmental damage of plastic material. Limited cases were found during the literature review, whereas many more SPM business models exist in practice, signaling a research gap. Forty-four scientifically documented business models were identified and analyzed on the basis of business model component, sustainability, level of waste hierarchy and sustainable business model archetype. Our results suggest that business models focus on recycling and creating value from waste, as well as the development of bioplastic. Few cases qualified as triple bottom line businesses, as many reported environmental and economic, but not social, benefits. Circular economy business models were found in a quarter of all cases. Finally, we present a synthesis of the barriers and opportunities for sustainable plastic management by the private sector. Drivers include maintaining competitive advantage, accessing green customers, collaboration with stakeholders, and achieving efficiency improvements. Barriers frequently mentioned were high costs, complexity of new systems, supply chain lock-in and low customer buy-in. Further research should expand the scale of SPM research, identify the enabling conditions for sustainable plastic management, and determine environmental impact.