Search

This paper discusses the relationship between morality and engagement focused on the narratives about climate change. The goal of our research is to understand whether moral grounds identified in individuals and in narratives can influence youth's engagement in environmental debate and news consumption on climate change. Recognizing that people's perceptions of climate change are related to several factors, such as ideas, cultures, and values, we sought to understand whether there is a "green morality" or a prevalence of more responsive moral attributes in individuals when they are exposed to thinking about the environment. We use the Moral Foundations Theory to analyze comments on the environmental news on Twitter and a questionnaire adapted to the environment on moral grounds. The data were collected from Brazil and Portugal between 2021 and 2022. The overall results showed a high incidence of responses with Care/Harm and Fairness/Cheating, and an average incidence of responses related to Loyalty/Betrayal and Authority/Subversion. The results indicate that youngsters show a more prominent moral to care and environmental harm, as well as justice and responsibility, which may influence their interest in the consumption of environmental news and future engagement. In addition, there are factors, such as political issues, that can influence moral values and engagement. [ABSTRACT FROM AUTHOR]

• Out-of-sample prediction of extreme precipitation using nonstationary models. • Significant trends in data of extreme precipitation are insufficient to warrant the selection of a nonstationary model. • Large prediction uncertainty reduces the support for nonstationary models of extreme precipitation. • (Non)stationary model selection should explicitly account for model complexity. Knowledge of the recurrence intervals of precipitation extremes is vital for infrastructure design, risk assessment, and insurance planning. However, trends and shifts in rainfall patterns globally pose challenges to the application of extreme value analysis (EVA) which relies critically on the assumption of stationarity. In this paper, we explore: (1) the suitability of nonstationary (NS) models in the presence of statistically significant trends, and (2) their potential in modeling out-of-sample data to improve frequency analysis of extreme precipitation. We analyze the benefits of using a nonstationary Generalized Extreme Value (GEV) model for annual extreme precipitation records from Southern Brazil. The location of the GEV distribution is allowed to change with time. The unknown GEV model parameters are estimated using Bayesian techniques coupled with Markov chain Monte Carlo simulation. Next, we use GAME sampling to compute the evidence (and their ratios, the so-called Bayes factors) for stationary and nonstationary models of annual maximum precipitation. Our results show that the presence of a statistically significant trend in annual maximum precipitation alone does not justify the use of a NS model. The location parameter of the GEV distribution must also be well defined, otherwise, stationary models of annual maximum precipitation receive more support by the data. These findings reiterate the importance of accounting for GEV model parameters and predictive uncertainty in frequency analysis and hypothesis testing of annual maximum precipitation data records. Furthermore, a meaningful EVA demands detailed knowledge about the origin and persistence of observed changes. [ABSTRACT FROM AUTHOR]

Pastureland maintenance is seen as a land-based measure to reduce dependency on feed concentrates and mitigate greenhouse gas (GHG) emissions from livestock production in the EU, while providing other ecosystems services. This paper assesses potential market-mediated impacts, including global Land Use Change (LUC) and GHG emissions, from increased subsidies to pasture-based livestock production in the EU. A tax recycling strategy (TRS) is simulated against a baseline up to 2030 under the shared socioeconomic pathway 2 (SSP2). This implies a budget-neutral increase in the level of pasture subsidies in individual Member States, as land subsidies for other cropping activities decrease. We employ the computable general equilibrium (CGE) model GTAP in its recursive-dynamic version, GTAP-RDEM, extended with the Multi-Regional Input-Output (MRIO) database FABIO to disaggregate agri-food sectors from 21 to 31. This approach allows considering price- and income-dependent feedbacks when assessing long-run changes in the global economy, improving the sectoral resolution relative to GTAP v10. The policy increases pastureland areas and cattle production in almost all EU Member States, whereas cropland and crop production decrease, causing significant changes across EU agri-food markets. Crop prices increase, leading to the reduced output of intensive animal production sectors, mainly pig and poultry. Cropland areas decrease and most EU countries increase imports of grain, oilseeds, and cakes, essentially soybean cake from Brazil and North America. While GHG emissions decrease in those EU countries where pasturelands expand mainly at the cost of croplands, GHG emissions increase in those countries where pastureland expansion comes with forest loss. As a result, net GHG emissions increase in the EU-27 in 2030 (+2.49 Mt CO 2 -eq). Emissions from LUC in major non-EU grain- and oilseed-exporting countries increase, e.g., by 102.52 Mt CO 2 -eq in Brazil and by 129.17 Mt CO 2 -eq in North America. The simulated policy shows that promoting extensive livestock per se does not meet the objectives of the Common Agricultural Policy and the EU Green Deal. The TRS should be complemented with policies to foster crop diversification and promote the use of domestic feed sources (e.g., legumes) to effectively ensure feed self-sufficiency and that extensive cattle production in the EU does not lead to deforestation in carbon-rich countries. [ABSTRACT FROM AUTHOR]

The use of wind power has gained prominence on the world stage, especially in Brazil. In addition to generating energy free of emissions, wind technology is the second cheapest generation option in Brazil. At the same time, it has contributed to reducing hydrological vulnerability caused by climate variation. Although wind power has experienced a steady expansion in the last decade, recent poor outcomes of wind auctions produced uncertainty about the future of this technology in the country. This paper analyses the influence of contract mechanisms used in Brazilian energy auctions for the growth of wind generation. To do this, a scenario analysis based on a hybrid simulation model is used, combining agent-based modelling (ABM) and system dynamics (SD). From the hybrid simulation, the effect of the wind project cancellation policy is analysed, on the one hand, and different ceiling prices for competing sources in the auctions are assessed, on the other. Moreover, the simulation model shows how hydro conditions affect reserve energy auctions. [ABSTRACT FROM AUTHOR]