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This paper addresses some questions that climate change raises for international law. It focuses in particular on the request for an advisory opinion submitted by the United Nations General Assembly to the International Court of Justice (ICJ) on 29 March 2023. This request is analysed as a further manifestation of the international community’s concern to clarify the international responsibility of states to prevent, mitigate and remedy the damage caused by climate change. The study argues that the ICJ could clarify obligations under existing treaties. There may also be a particular opportunity for the Court to expand its jurisprudence on other sources of international law. In particular, it asks whether the ICJ could confirm the emergence of a specific customary rule on the issue.

The objective of this paper is to analyze the factors influencing the success of real estate crowdfunding projects in Spain. This type of crowdfunding invests in real estate assets. We analyzed 60 projects published on the Housers platform, a kind of participative platform that uses the lending and equity crowdfunding modalities. These projects have involved around 36,623 investment decisions and have raised a total amount of almost 26 million euros. The empirical analysis is based on ordinary least squares and negative binomial regression. Our main findings reveal that success differs depending on the type of project; in fact, buy-to-sell projects are less successful than development loan projects. In addition, while total return has a positive impact on project success, in the case of risk level and project term, the impact is negative.

SummaryInequality has recently become a major concern in economics. Leaving aside its social and economic effects is also possible to trace its environmental consequences, which this article attempts to assess. The indicator to be measured is the household's carbon footprint (CF) for different social groups. The deep economic crisis in the Spanish economy between 2008 and 2013 has increased consumption inequality and doubled the number of households below the poverty line. When focusing on domestic consumption, we found that the shopping basket of all income groups has very similar emissions intensities; therefore, the differences among the household CFs depend mainly on the scale effect (i.e., the size of consumption). However, when international trade is also considered, we found that the emission intensity of imports is bigger than the intensity of all the respective domestic goods. Therefore, the share of imported goods and services by social class will be an important determinant of the respective total CF. Before the crisis, households with higher incomes imported 30% of their total consumption items whereas households with lower income imported only 20% of their consumption. During the crisis, the imports of medium‐high‐income households fell to 20%, whereas low‐ and middle‐income families maintained the same import share, which contributed to the reduction of the total household CF.

Nowadays, the issues related with environment preservation assume an increasing importance. Progressively, more sustainable solutions/techniques are being developed to combat environmental destruction. The decision to include themes related to the environment in the curriculum of technological courses in higher education aims to promote more sustainable behaviors and in an indirect way, increase the environmental literacy of the population. Thus, this study aims to evaluate the environmental literacy focusing on four topics, i.e., air pollution, water pollution, global warming, and energy resources. For this purpose, a questionnaire was developed and applied to a convenience sample, formed by individuals of both genders, aged between 20 and 81 years old. The questionnaire intended to collect data to characterize the sample and assess the literacy regarding environmental issues. In order to carry out the environmental literacy assessment, the respondents were asked to express their degree of agreement with some statements related with the environmental themes mentioned above. The data collected was analyzed using data mining tools. The results suggest that the population’s literacy is satisfactory in relation to some issues, but insufficient in relation to others, equally important, but less disseminated.

Coupling between the UEDGE (edge fluid model), GINGRED (grid generation) and CAKE (equilibrium reconstruction) codes opens the door for automated interpretative scrape-off-layer (SOL) analysis over entire discharges, providing information that is essential in efforts to couple the SOL to core transport codes. In this work, we utilize new developments in the autoUEDGE code (Izacard et al. 2018) to investigate the behavior of the DIII-D SOL during the temporal evolution of an edge-localized mode (ELM) cycle. Modeled temperature and density profiles in UEDGE are automatically matched to experimental measurements by iteratively and self-consistently adjusting transport coefficient profiles in the plasma edge. This analysis is completed over multiple ELM cycles of a well-diagnosed discharge with long (∼100ms) inter-ELM periods. Directly after the ELM crash, a short period of high-density, low-temperature conditions is observed in Langmuir probe measurements at the outer divertor. This regime is associated with enhanced Dαemission and incident particle flux, suggesting that the divertor enters a period of high recycling after an ELM crash. After about ∼25ms, divertor conditions return to their pre-ELM conditions and remain there for several tens of milliseconds. Using the autoUEDGE code, the SOL is modeled as a function of ELM cycle using upstream profiles as input. The 2D modeling successfully reproduces both divertor Thomson scattering measurements and the experimentally observed divertor dynamics. Though the recycling is kept fixed throughout the modeling, changes in particle fluxes are consistent with local experimental recycling changes induced by ELMs. Agreement between modeling and observation suggests a strong link between upstream profiles and the high-recycling divertor conditions directly following large type-I ELMs.

The incorporation of cover crops into the maize (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation in the U.S. upper Midwest may improve sustainability. Long, cold winters in the region make identifying successful cover crop species and management practices a challenge. Two experiments were conducted in Minnesota, USA from fall 2016 through spring 2019 to examine the effect of cover crops interseeded at four- to six-leaf collar (early-interseeded) and dent to physiological maturity (late-interseeded) on biomass and grain yield of maize. Annual ryegrass (Lolium multiflorum L.) and cereal rye (Secale cereale L.) were evaluated as monocultures and in mixtures with crimson clover (Trifolium incarnatum L.) and forage radish (Raphanus sativus L.). Differences in canopy cover and biomass of late-interseeded cover crops were observed at the southernmost location in 2018. Additional accumulated growing-degree days in fall 2018 did not translate into increased cover crop canopy coverage of late-interseeded cover crops. Differences in cover crop canopy cover and biomass of early-interseeded cover crops were observed by fall frost at all locations in 2017 and at the northernmost location in 2018. Cover crop canopy cover and biomass at termination before planting maize, soil moisture at maize planting as well as maize aboveground biomass and yield were not affected by spring cereal rye regrowth of cover crops late-interseeded the previous year. Similarly, early-interseeded cover crops did not affect maize aboveground biomass or yield. We attribute these results to limited cover crop growth. This highlights the potential of a variety of cover crop strategies interseeded into maize in the U.S. upper Midwest; however, efforts to fine-tuning cover crop management and weather conditions are needed to benefit from such practice.

Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.