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Abstract This paper describes a new tool to assess the medium- and long-term economic and environmental impacts of large-scale policies. The approach – macro life cycle assessment (M-LCA) – is based on life cycle assessment methodology and includes additional elements to model economic externalities and the temporal evolution of background parameters. The general equilibrium model GTAP was therefore used to simulate the economic consequences of policies in a dynamic framework representing the temporal evolution of macroeconomic and technological parameters. Environmental impacts, expressed via four indicators (human health, ecosystems, global warming and natural resources), are computed according to policy life cycle and its indirect economic consequences. In order to illustrate the approach, two 2005–2025 European Union (EU) energy policies were compared using M-LCA. The first policy, the bioenergy policy, aims to significantly increase energy generation from biomass and reduce EU energy demand for coal. The second policy, the baseline policy, is a business as usual policy where year 2000 energy policies are extended to 2025. Results show that, compared to the baseline policy, the bioenergy policy generates fewer impacts on three of the four environmental indicators (human health, global warming and natural resources) at the world and EU scales, though the results may differ significantly at a regional level. The results also highlight the key contribution of economic growth to the total environmental impacts computed for the 2005–2025 period. A comparison of the results with a more conventional consequential LCA approach illustrates the benefits of M-LCA when modeling the indirect environmental impacts of large-scale policies. The sensitivity and uncertainty analysis indicates that the method is quite robust. However, its robustness must still be evaluated based on the sensitivity and uncertainty of additional parameters, including the evolution of economic growth.

This study investigates the nexus between renewable energy consumption and economic growth in Italy in the 1970-2007 years. The unit root tests results point out that our four variables are integrated of order one. Cointegration analysis reach contradictory results. However, the long-run estimations reveal that, if renewable energy consumption increases by 1%, real GDP decreases by 0.23%. The Toda and Yamamoto approach shows that exists a unidirectional causal flow, running from renewable energy consumption to aggregate income, in line with the "growth hypothesis". Moreover, these results are confirmed by Granger causality tests. While forecasts applications set out that VAR forecasts represent an improvement on simpler forecasts in more than half the comparisons, for each variable. In fact, VAR gives more accurate forecasts, over-performing the mean, RW, and AR methods.

We derived a promising approach to reducing the energy consumption necessary in manufacturing processes from the combination of management methodologies and Industry 4.0 technologies. Based on a literature review and experts’ opinions, this work contributes to the efficient use of energy in batch production processes combining the analysis of the overall equipment effectiveness with the study of variables managed by cyber-physical production systems. Starting from the analysis of loss cause identification, we propose a method that obtains quantitative data about energy losses during the execution of batch processes. The contributions of this research include the acquisition of precise information about energy losses and the improvement of value co-creation practices so that energy consumption can be reduced in manufacturing processes. Decision-makers can use the findings to start a virtuous process aiming at carbon footprint and energy costs reductions while ensuring production goals are met.

The measurement of sustainability is complex due to its multiple dimensions of different relative importance and different natures. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism, and sustainable impact tourism. In the context of multiple-criteria decision analysis, this paper presents a flexible method for assess and rank decision alternatives based on their sustainability. The proposal does not require the relative importance of each criterion to be precisely assigned beforehand, which reduces the subjectivity of the decision making and yields results that can be of interest for decision makers. To show the difference between these three sustainability options in tourism and the benefits of the method, the proposal is applied to public and private tourism management in Spain—in particular, to hotel booking and the evaluation and management of sustainability in the autonomous regions.

The present age is characterized by a very complex economic relationship among finance, technology, social needs, etc., which can be summarized in the word “sustainability.” The sustainable consumption and production policies represent the keys to realize sustainable development. But, the analysis of the carbon footprint data points out that the present economies are still carbon-consumption production. The reduction of greenhouse gasses emissions is based on a shift from fossil to renewable and bio-based industrial raw materials, with a related reorganization of the chains of the energy and manufacturing sectors. But, this requirement implies technological choices based on a sustainable measurement of their impacts on the ecological and economical contexts. So, social and economic requirements must also be taken into account by the decision-makers. Bioeconomy can represent a possible approach to deal with the requirements of the present time. But, new needs emerge in relation to sustainability. So, sustainable policies require new indicators, in order to consider the link among economics, technologies, and social well-being. In this paper, an irreversible thermodynamic approach is developed, in order to introduce a thermoeconomic indicator, based on thermodynamic optimization methods, but also on socioeconomic and ecological evaluations. The entropy production rate is introduced in relation to the CO2emission flows from human activities, and it is related to the income index, in order to consider the economic and social equity. This approach is of interest of the researchers in the field of econophysics, thermoeconomy, economics, and bioeconomy.

The Human Mobility Transition model describes shifts in mobility dynamics and transport systems. The aspirational stage, ‘human urbanism’, is characterised by high active travel, universal public transport, low private vehicle use and equitable access to transport. We explored factors associated with travel behaviour in Africa and the Caribbean, investigating the potential to realise ‘human urbanism’ in this context. We conducted a mixed-methods systematic review of ten databases and grey literature for articles published between January 2008 and February 2019. We appraised study quality using Critical Appraisal Skills Programme checklists. We narratively synthesized qualitative and quantitative data, using meta-study principles to integrate the findings. We identified 39,404 studies through database searching, mining reviews, reference screening, and topic experts’ consultation. We included 129 studies (78 quantitative, 28 mixed-methods, 23 qualitative) and 33 grey literature documents. In marginalised groups, including the poor, people living rurally or peripheral to cities, women and girls, and the elderly, transport was poorly accessible, travel was characterised by high levels of walking and paratransit (informal public transport) use, and low private vehicle use. Poorly controlled urban growth (density) and sprawl (expansion), with associated informality, was a salient aspect of this context, resulting in long travel distances and the necessity of motorised transportation. There were existing population-level assets in relation to ‘human urbanism’ (high levels of active travel, good paratransit coverage, low private vehicle use) as well as core challenges (urban sprawl and informality, socioeconomic and gendered barriers to travel, poor transport accessibility). Ineffective mobility systems were a product of uncoordinated urban planning, unregulated land use and subsequent land use conflict. To realise ‘human urbanism’, integrated planning policies recognising the linkages between health, transport and equity are needed. A shift in priority from economic growth to a focus on broader population needs and the rights and wellbeing of ordinary people is required. Policymakers should focus attention on transport accessibility for the most vulnerable.

Using the economic complexity methodology on data for disease prevalence in 195 countries during the period of 1990-2016, we propose two new metrics for quantifying the disease space of countries. With these metrics, we analyze the geography of diseases and empirically investigate the effect of economic development on the health complexity of countries. We show that a higher income per capita increases the complexity of countries’ diseases. We also show that complex diseases tend to be non-ubiquitous diseases that are prevalent in disease-diversified (complex) countries, while non-complex diseases tend to be non-ubiquitous diseases that are prevalent in non-diversified (non-complex) countries. Furthermore, we build a disease-level index that links a disease to the average level of GDP per capita of the countries in which the disease is prevalent. With this index, we highlight the link between economic development and the complexity of diseases and illustrate how increases in income per capita are associated with more complex diseases.