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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.

Purpose This study aims to investigate the interrelationships and elasticities between the production of renewable energy (RE) and three key variables: oil prices, gross domestic product (GDP) and carbon dioxide (CO2) emissions. Design/methodology/approach The research uses panel data and time-series analyses for 10 developed and 16 emerging countries for the period 1976–2018, to identify panel and country-specific elasticity of RE production and dynamic causal relationships between these variables. The study uses an autoregressive distributed lag model to determine the long- and short-run dynamics between RE production and the three variables in each country. Findings Results show a long-run elasticity between RE and GDP, and short-run dynamics between RE and oil prices and CO2 emissions in the developed countries. Whereas in the emerging countries category, there were long-run relationships between RE and GDP, CO2 emissions and oil prices. Practical implications Results of this study are in fact crucial and can be applied in the drafting of resilience policies to tackle energy vulnerability as well as sustainable growth. The study results will inform and guide governments on the right policies to stimulate RE production in their own countries in the interests of both their national security and sustainable development globally. Originality/value This paper attempts to contribute to the literature in at least two ways. First, research on identifying common determining factors, including socioeconomic factors, in both emerging and advanced economies is considerably scarce. Most of the previous research in this field has focused only on the absolute value of RE production in a particular geographical area. Second, many studies have focused on RE consumption. This research differs from them by focusing on the production of RE. Thus, the main contribution of this study is to fill these gaps. The study also presents novel empirical evidence to determine RE production elasticity from 26 countries.

AbstractClimate change impacts are being felt across sectors in all regions of the world, and adaptation projects are being implemented to reduce climate risks and existing vulnerabilities. Climate adaptation actions also have significant synergies and tradeoffs with the Sustainable Development Goals (SDGs), including SDG 5 on gender equality. Questions are increasingly being raised about the gendered and climate justice implications of different adaptation options. This paper investigates if reported climate change adaptation actions are contributing to advancing the goal of gender equality (SDG 5) or not. It focuses on linkages between individual targets of SDG 5 and climate change adaptation actions for nine major sectors where transformative climate actions are envisaged. The assessment is based on evidence of adaptation actions documented in 319 relevant research publications published during 2014–2020. Positive links to nine targets under SDG 5 are found in adaptation actions that are consciously designed to advance gender equality. However, in four sectors—ocean and coastal ecosystems; mountain ecosystems; poverty, livelihood, sustainable development; and industrial system transitions, we find more negative links than positive links. For adaptation actions to have positive impacts on gender equality, gender-focused targets must be intentionally brought in at the prioritisation, designing, planning, and implementation stages. An SDG 5+ approach, which takes into consideration intersectionality and gender aspects beyond women alone, can help adaptation actions move towards meeting gender equality and other climate justice goals. This reflexive approach is especially critical now, as we approach the mid-point in the timeline for achieving the SDGs.

Machine learning (ML) has seen a substantial increase in its role in improving operations for staff and customers in different industries. However, there appears to be a somewhat limited adoption of ML by farm businesses, highlighted by a review of the literature investigating innovative behaviors by rural businesses. A review of the literature identified a dearth of studies investigating ML adoption by farm businesses in rural regions of the United Arab Emirates (UAE), especially in the context of family-owned farms. Therefore, this paper aims to investigate the drivers and barriers to ML adoption by family/non-family-owned farms in rural UAE. The key research questions are (1) what are the drivers and barriers for rural UAE farms adopting ML? As well as (2) is there a difference in the drivers and barriers between family and non-family-owned farms? Twenty semi-structured interviews were conducted with farm businesses across several rural regions in the UAE. Then, through a Template Analysis (TA), drivers and barriers for rural UAE-based farm owners adopting ML were identified. Interview findings highlighted that farms could benefit from adopting ML in daily operations to save costs and improve efficiency. However, 16 of 20 farms were unaware of the benefits related to ML due to access issues (highlighted by 12 farms) in incorporating ML operations, where they felt that incorporating ML into their operations was costly (identified by 8 farms). It was also identified that non-family-owned farms were more likely to take up ML, which was attributed to local culture influencing family farms (11 farms identified culture as a barrier). This study makes a theoretical contribution by proposing the Machine Learning Adoption Framework (MLAF). In terms of practical implications, this study proposes an ML program specifically targeting the needs of farm owners in rural UAE. Policy-based implications are addressed by the findings aligning with the United Nations’ Sustainability Development Goals 9 (Industry, Innovation, and Infrastructure) and 11 (Sustainable Cities and Communities).

AbstractGlobal CO2emissions from different industries have been increasing at an alarming rate. This growth is outpacing the efforts, nations are putting in place to reduce their carbon footprints. In this topical review, we critically analyze the level of CO2emissions on a global scale and across various industries and activities within them and the dominant anthropogenic forcing instability. The global CO2emission from various economic sectors such as industries, transportation and variety of waste sources were traced globally and regionally. To contextualize our review, the sector wise CO2emission trends data for a period more than a decade is reviewed which highlighted the main sources of emissions. The data shows the overall reduction of carbon footprints and its progress across various sectors is very limited. The governing factors for this continued global pattern can be ascribed to two main factors: high consumer demands, and poor efforts towards shifting low and zero carbon services across all sectors. Some efforts have been witnessed to shift towards clean fuels and renewables, particularly in Europe and North America. However, rapid growth in industrialization limits the shifting of fossil-based energy systems towards less harmful systems. In Asia, particularly in eastern, southern, and south-eastern regions, the carbon footprints were found to increased owing to a huge demand for materials production, travelling and energy services. Therefore, it is of utmost importance to identify, understand and tackle the most persistent and climate-harmful factors across all industries and drive such policies to substitute the fossil fuels with renewables.

This research measured the welfare impacts of food trade liberalization in India, Egypt, Pakistan, Saudi Arabia, and the United Arab Emirates (UAE) using the partial equilibrium model—World Integrated Trade Solution (WITS). Macroeconomic settings, domestic policy objectives, and food security indicator data are used to assess the implications of the simulations on food availability and stability. Simulation results for India, Egypt, and Pakistan indicate annual welfare gains (consumer surplus) of 2571, 340, and 25 million USD, respectively, while Saudi Arabia and the UAE have gains of 14 and 17 million USD. Results show that tariff elimination would have wide-ranging welfare impacts across food commodities within these countries. Moreover, reductions for specific commodities directly relevant to food energy and protein availability would have a greater direct impact on the poor. Lowering the highest tariffs on those commodities might raise the real incomes of more than 350 million persons by 7.5% or more and could create shifts in consumption towards more diversified and nutritionally sound diets.

Household air pollution (HAP), primarily from biomass fuels used for cooking, is associated with adverse health outcomes and premature mortality. It affects almost half of the world’s population, especially in low-income and low-resourced communities. However, many of the ’improved’ biomass cookstoves (ICS) aimed at reducing HAP lack empirical evidence of pollutant reduction and reliability in the field. A scoping review guided by the Joanna Briggs Institute framework was systematically conducted to explore and analyse the characteristics of cookstoves to assess the ICS available to meet the socio-economic and health needs of households in sub-Sahara Africa (sSA). The review searched Scopus, PubMed, Web of Science, EMBASE, Global Health Database on OVID, BASE, and conducted a grey literature search from 2014 to 2022 for all field-based ICS studies. In addition, user perspectives were explored for cookstoves analysed as available, affordable, and effective in reducing harmful biomass emissions. The search returned 1984 records. Thirty-three references containing 23 ICS brands were included. The cookstoves were analysed into seven categories: (1) efficiency in HAP reduction, (2) availability, (3) affordability, (4) sustainability, (5) safety, (6) health outcomes, and (7) user experience. Most (86.9%) of the improved cookstoves showed a reduction in harmful emission levels compared to the traditional three-stone fire. However, the levels were higher than the WHO-recommended safe levels. Only nine were priced below 40 USD. Users placed emphasis on cookstoves’ suitability for cooking, fuel and time savings, safety, and price. Equality in cooking-related gender roles and psychosocial benefits were also reported. The review demonstrated limited field testing, a lack of evidence of ICS emissions in real-life settings in sSA, heterogeneity in emission measurements, and incomplete descriptions of ICS and kitchen features. Gender differences in exposure and psychosocial benefits were also reported. The review recommends improved cookstove promotion alongside additional measures to reduce HAP at a cost affordable to low-resource households. Future research should focus on detailed reporting of study parameters to facilitate effective comparison of ICS performance in different social settings with different local foods and fuel types. Finally, a more community-based approach is needed to assess and ensure user voices are represented in HAP intervention studies, including designing the cookstoves.