An analysis of university sustainability reports from the GRI database: an examination of influential variables

In the business context, many papers have examined whether certain variables can affect sustainability disclosure practices. However, research on universities has mainly been addressed to explore the extent of sustainability information reported with little focus on determining the factors that may affect it. This paper analyzes the influence exerted by some variables concerning the extent of information reported in the university sustainability reports included in this study. To accomplish this task, data were collected using a content analysis of the university sustainability reports extracted from the GRI sustainability disclosure database. The findings reveal that sustainability disclosure practices by universities are explained by different factors, among which are institutionalization, geographical region, external assurance and leadership. Such results are supported jointly by the underpinnings of the institutional and legitimacy theories in response to coercive and mimetic pressures and by the need to improve reputation in society.     

Occurrence of <Emphasis Type="Italic">Pepper Mild Mottle Virus</Emphasis> (PMMoV) in Groundwater from a Karst Aquifer System in the Yucatan Peninsula,Mexico

The Yucatan Peninsula of Mexico hosts a karst aquifer system that is the only source of freshwater for the area; however, it is vulnerable to human-mediated contamination. Pepper mild mottle virus (PMMoV) is one of the most abundant RNA viruses associated with human feces, making it a viable indicator for tracking fecal pollution in aquatic environments, including groundwater. In this study, groundwater samples collected from a karst aquifer from fresh and brackish water locations were analyzed for fecal indicator bacteria, somatic and male F+ specific coliphages, and PMMoV during the rainy and dry seasons. Total coliform bacteria were detected at all sites, whereas Escherichia coli were found at relatively low levels <40 MPN/100 ml. The highest average concentrations of somatic and male F+ specific coliphages were 920 and 330 plaque forming units per 100 ml, respectively, detected in freshwater during the rainy season. PMMoV RNA was detected in 85% of the samples with gene sequences sharing 99–100% of nucleotide identity with PMMoV sequences available in GenBank. Quantification of PMMoV genome copies (GC) by quantitative real-time PCR indicated concentrations ranging from 1.7 × 10¹ to 1.0 × 10⁴ GC/L, with the highest number of GC detected during the rainy season. No significant correlation was observed between PMMoV occurrence by season or water type (p > 0.05). Physicochemical and indicator bacteria were not correlated with PMMoV concentrations. The abundance and prevalence of PMMoV in the karst aquifer may reflect its environmental persistence and its potential as a fecal indicator in this karst aquifer system.     

Between uncertainty and hope: Young leaders as agents of change in sustainable small-scale fisheries

The path to sustainable small-scale fisheries (SSF) is based on multiple learning processes that must transcend generational changes. To understand young leaders from communities with sustainable SSF management practices in Mexico, we used in-depth interviews to identify their shared motivations and perceptions for accepting their fishing heritage. These possible future decision-makers act as agents of change due to their organizational and technological abilities. However, young people are currently at a crossroads. Many inherited a passion for the sea and want to improve and diversify the fishing sector, yet young leaders do not want to accept a legacy of complicated socioenvironmental conditions that can limit their futures. These future leaders are especially concerned by the uncertainty caused by climate change. If fishing and generational change are not valued in planning processes, the continuity of fisheries, the success of conservation actions, and the lifestyles of young fishers will remain uncertain.Graphical abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01639-2.     

Progressive Optimal Technology-based Border Carbon Adjustment (POT BCA) - A New Approach to an Old Carbon Problem

The idea of Border Carbon Adjustment (BCA), which makes it possible to transform the standard tax on carbon emissions from production (origin principle) to a tax system imposed at the point of consumption (destination principle), has received a considerable amount of attention from academia and policymakers. In this paper, we go back to the source of environmental destination-based taxation and generalize the results of Markusen (Journal of International Economics, 5, 15–29, 1975) for optimal tax and tariff by extending domestic environmental policy on both goods featuring positive carbon intensities. Following Jakob et al. (Environmental and Resource Economics, 56(1), 47–72, 2013) we remove the strategic term from the optimal tariff and deal with the so-called optimal carbon tariff, targeting primarily environmental externality. Further, we develop a handy approximation for optimal tax and optimal carbon tariff structure in a multiple good setting. Such trade taxation is, however, likely to face further legal obstacles, which may hinder its implementation. This motivates us to adjust the results accordingly and to include refunds for low-carbon investments in a ‘dirty’ country granted proportionally to the difference in carbon intensities between trade partners. This new scheme, known as Progressive Optimal Technology-based Border Carbon Adjustment (POT BCA), mitigates several legal problems and increases political acceptance compared to the ‘standard’ BCA. It can also be seen as advantageous from the economic point of view: it mimics the performance of the optimal carbon tariff while aiming to decrease foreign carbon intensity over the long term.     

GIS-based modeling of the geographic distribution of Quercus emoryi Torr. (Fagaceae) in México and identification of significant environmental factors influencing the species’ distribution

The greatest concentration of oak species in the world is believed to be found in Mexico. These species are potentially useful for reforestation because of their capacity to adapt to diverse environments. Knowledge of their geographic distribution and of species–environment relations is essential for decision-making in the management and conservation of natural resources. The objectives of this study were to develop a model of the distribution of Quercus emoryi Torr. in Mexico, using geographic information systems and data layers of climatic and other variables, and to determine the variables that significantly influence the distribution of the species. The study consisted of the following steps: (A) selection of the target species from a botanical scientific collection, (B) characterization of the collecting sites using images with values or categories of the variables, (C) model building with the overlay of images that meet the habitat conditions determined from the characterization of sites, (D) model validation with independent data in order to determine the precision of the model, (E) model calibration through adjustment of the intervals of some variables, and (F) sensitivity analysis using precision and concordance non-parametric statistics applied to pairs of images. Results show that the intervals of the variables that best describe the species’ habitat are the following: altitude from 1650 to 2750 amsl, slope from 0 to 66°; average minimum temperature of January from −12 to −3 °C; mean temperature of June from 11 to 25 °C; mean annual precipitation from 218 to 1225 mm; soil units: lithosol, eutric cambisol, haplic phaeozem, chromic luvisol, rendzina, luvic xerosol, mollic planosol, pellic vertisol, eutric regosol; type of vegetation: oak forest, oak–pine forest, pine forest, pine–oak forest, juniperus forest, low open forest, natural grassland and chaparral. The resulting model of the geographic distribution of Quercus emoryi in Mexico had the following values for non-parametric statistics of precision and agreement: Kappa index of 0.613 and 0.788, overall accuracy of 0.806 and 0.894, sensitivity of 0.650 and 0.825, specificity of 0.963, positive predictive value of 0.945 and 0.957 and negative predictive value of 0.733 and 0.846. Results indicate that the variable average minimum temperature of January, with a maximum value of −3 °C, is an important factor in limiting the species’ distribution.     

POCIS passive samplers as a monitoring tool for pharmaceutical residues and their transformation products in marine environment

In the last years, several scientific studies have shown that carbamazepine (CBZ) is one of the most frequently detected pharmaceutical in aquatic environment. However, little data is available on its detection and its transformation products (TPs) in marine water. The use of polar organic chemical integrative sampling (POCIS) passive samplers as a semi-quantitative and qualitative tool for screening of pharmaceuticals and TPs in seawater has been studied. Furthermore, the uptake rates of the target compounds were also determined under laboratory experiments to characterize the levels accumulated in devices. The results confirmed the presence of residues of anticonvulsant CBZ as well as some of its main metabolites, over a 1-year monitoring campaign carried out in French coast on the Mediterranean Sea. The work reports for the first time the presence of two TPs (10,11-dihydro-10,11-trans-dihydroxycarbamazepine (TRANS) and 10-hydroxy-10,11-dihydrocarbamazepine (10OH)) in marine water. The results contribute in assessing the environmental and human health risk of pharmaceuticals on coastal areas.     

How researchers frame scientific contributions to sustainable development: a typology based on grounded theory

Given that research on sustainable development usually relates to real-world challenges, it requires researchers to align scientific knowledge production with concrete societal problem situations. To empirically explore how researchers frame scientific contributions when designing and planning projects, we conducted a qualitative study on land use–related projects based on the methodology of grounded theory. We identified major influence factors and various types of research design. Among the factors that influence project framing, scientific considerations were found to be more important than expected. Core characteristics of project framings concerned (a) type of scientific contributions envisaged; (b) real-world sustainability challenges addressed, and (c) researchers’ conceptions of how knowledge would reach its addressees. Three different types of project framing were found, suggesting that framing strongly depends on (the researchers’ perception of) how well a real-world problem situation is understood scientifically and how strongly are societal actors aware of the problem and act upon it. The spectrum of how researchers planned that knowledge would reach its addressees comprised communicating results to interactive conceptions allowing for mutual learning throughout the research process. The typology reveals a variety of useful and promising project framings for sustainable development research. The typology may serve to reconcile conceptual ideals and expectations with researchers’ realities.     

Mathematical modeling to predict residential solid waste generation

One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R(2) were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total.