Environmental and Sustainability Indicators最新文献

{"title":"Building high-resolution projections of temperature potential changes using statistical downscaling for the future period 2026–2100 in the highland region of Yemen – A supportive approach for empowering environmental planning and decision-making","authors":"Ali H. AL-Falahi ,&nbsp;Naeem Saddique ,&nbsp;Uwe Spank ,&nbsp;Christian Bernhofer","doi":"10.1016/j.indic.2024.100490","DOIUrl":"10.1016/j.indic.2024.100490","url":null,"abstract":"<div><div>Environmental resources and ecological systems are significantly affected by the steady rise of the global temperature. However, the degree of temperature change at the regional and local levels is uncertain. The uncertainty arises from various factors, but mostly due to the short length of ground data and dependency of local studies on the large-scale and spatially coarse output of Global Climate Models (GCMs). Therefore, the output of GCM cannot be directly used in impact assessment studies at a regional and local level. In this study, the Statistical Down-Scaling Model (SDSM) is employed to investigate the magnitude of temperature changes (Minimum and Maximum Temperature) for the future period 2026–2100. The SDSM builds relationships between large-scale predictors and local climate variables, allowing for finer-resolution projections at a regional level. The study utilized the Climate Hazard Infra-Red Temperature with Station (CHIRTS-daily) to complete daily missing records in more than 90 ground stations. Additionally, predictors of the National Center for Environmental Prediction (NCEP) for the historical period (1961–2010) and the Canadian Earth System Model (CanESM2) for the future period (2026–2100) are employed to calibrate SDSM and to build finer-resolution scenarios under two representative concentration pathways; RCP2.6 and RCP8.5. The methodology additionally involved validating the SDSM performance using observed historical data before applying it to future projections. The findings indicate that both minimum and maximum temperatures (T-min and T-max) will increase, with a more pronounced rise in minimum temperature (T-min). Over the future period (2026–2100), the projected average temperature rise is 1.10 °C (T-max) and 1.43 °C (T-min) under RCP2.6. For RCP8.5, the projected average increases are 1.56 °C and 2.3 °C for T-max and T-min, respectively. Overall, the most significant increase is projected to occur in the 2090s (2076–2100) under RCP8.5, particularly in the lowlands and wadis of Al Mahwit and Raymah governorate. In these areas, the minimum temperature (T-min) exhibited an increased absolute value of up to 3.2 °C. This high rise in temperatures is expected to result in increased evapotranspiration, prolonged droughts, and possibly breakouts of some plant diseases and pests. This would require effective adaptation measures such as harvesting rainwater and growing short-time and heat-resistance crops. Engaging in field visits and social discussions added depth to the study by introducing various traditional methods and indigenous practices. Valuable resources for future efforts to mitigate the potential impacts of climate change are offered by these insights.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100490"},"PeriodicalIF":5.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of dust emissions and their controlling factors on the Hoh Xil, north-central part of the Qinghai-Tibetan plateau","authors":"Yawei Fan ,&nbsp;Heqiang Du ,&nbsp;Zhiwen Han ,&nbsp;Xiufan Liu ,&nbsp;Xinlei Liu ,&nbsp;Zongxing Li","doi":"10.1016/j.indic.2024.100487","DOIUrl":"10.1016/j.indic.2024.100487","url":null,"abstract":"<div><div>Dust emissions can lead to a series of environmental hazards and are thus a global concern. However, due to the difficulties of dust source identification, there are still great uncertainties in the calculation of dust yield on a global scale. The Qinghai-Tibetan Plateau presents some challenges for understanding the region's calculation of the global dust budget. To address these issues, the Hoh Xil Plateau, a typical dust source on the Qinghai-Tibetan Plateau, was selected as the study area for analyzing dust emission processes and associated influencing factors via a robust model. The results showed that dust emissions on the Hoh Xil Plateau occurred mainly in spring and winter. The wide distribution of bare land and sandy land on the Hoh Xil Plateau is the main reason for the high dust emissions. Wind speed is the dominant factor influencing annual dust emission, while precipitation and temperature were negatively correlated with the dust emission. The recession of expansive lakes in the region resulted in an increase in sandy lake-shores, which induced a potential increase in dust emissions. In addition, the effects of human activities on dust emissions were evident. Positive and negative effects on dust emission changes coexisted on the Hoh Xil Plateau and depended on the development of the county-level economy and the implementation of ecological engineering measures. We believe that this study will clarify the dust yield of the Qinghai-Tibetan Plateau and provide valuable information for understanding the driving factors that cause variations in aeolian processes on the Qinghai-Tibetan Plateau.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100487"},"PeriodicalIF":5.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seagrass mapping of north-eastern Brazil using Google Earth Engine and Sentinel-2 imagery","authors":"Emma Deeks ,&nbsp;Karine Magalhães ,&nbsp;Dimosthenis Traganos ,&nbsp;Raymond Ward ,&nbsp;Iran Normande ,&nbsp;Terence P. Dawson ,&nbsp;Pavel Kratina","doi":"10.1016/j.indic.2024.100489","DOIUrl":"10.1016/j.indic.2024.100489","url":null,"abstract":"<div><div>Seagrass ecosystems are globally important blue carbon sinks and support significant marine and terrestrial biodiversity. However, human-induced climate change coupled with other anthropogenic pressures have substantially reduced seagrass distributions, making them one of the most threatened ecosystems on Earth. The challenges associated with seagrass conservation include substantial data gaps and limited low-cost, near-real monitoring methods. To address these challenges, we used 507 Sentinel-2 satellite images, filtered between August 2020 and May 2021, in the Google Earth Engine cloud computing environment for regional scale seascape habitat mapping in north-eastern Brazil, a region where conservation efforts are particularly hampered by data limitations. We mapped 9452 km² of coastline up to a depth of 10 m. We identified 328 km² of seagrass ecosystems, providing vital open access positional information for a variety of research applications. We also assessed the capability of Sentinel-2 in monitoring temporal changes in coastal habitats, and revealed up to 15.9% declines in seagrass meadow coverage in specific areas over a five-year period in north-eastern Brazil. Our results demonstrate that Sentinel-2 is an effective tool in mapping seagrass distributions at a regional scale. The resulting maps are critical for supporting the conservation of Neotropical coastal biota, including the endangered Antillean Manatee. Our study emphasises the importance of replicable and systematic monitoring methods in the race to conserve threatened coastal ecosystems globally.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100489"},"PeriodicalIF":5.4,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of hydrological variability on the sustainable use of water in a regional economy. An application to Tuscany","authors":"Gino Sturla,&nbsp;Bendetto Rocchi","doi":"10.1016/j.indic.2024.100488","DOIUrl":"10.1016/j.indic.2024.100488","url":null,"abstract":"<div><div>Existing input-output (IO) models have mainly focused on water demand. Some studies have incorporated water supply (availability), but do not take into account its natural variability, an essential element when performing a water stress analysis. The present study integrates the hydrological variability of water availability into a hydroeconomic IO model, considering its exogenous effects on water supply and its exogenous effects on water demand. Two endogenous effects are considered: i) changes in blue water requirements in the agricultural industry due to variations in precipitation and evapotranspiration, and ii) changes in grey water requirements in all discharging industries due to variations in runoff and groundwater recharge. By means of a T-years hydrological series and Monte Carlo simulations, the model allows estimating T values of the Extended Water Exploitation Index (EWEI), obtaining its empirical probability distribution and confronting it with scarcity thresholds. Additionally, the model includes a methodology to incorporate intra-annual variation, obtaining the critical month EWEI and defining a more transparent and endogenous scarcity threshold. Empirically tested for the Italian region of Tuscany considering a multivariate hydrological model for the generation of a 100-year hydrological series, our results allow a more in-depth analysis of water scarcity in the region.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100488"},"PeriodicalIF":5.4,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment and enhancement of community water supply system sustainability: A dual framework approach","authors":"Ranju Bhatta ,&nbsp;Ho Huu Loc ,&nbsp;Mukand S. Babel ,&nbsp;Kaushal Chapagain","doi":"10.1016/j.indic.2024.100486","DOIUrl":"10.1016/j.indic.2024.100486","url":null,"abstract":"<div><div>Population growth, pollution, and urbanization strain water sustainability, leading to the premature failure of community-managed water systems globally. This underscores the formidable task of precisely defining and quantifying sustainability within these community contexts. Based on the “You can't manage what you can't measure” adage, this study developed dual frameworks at community scale to assess and enhance the water supply system's sustainability. The assessment framework includes dimensions, indicators, and variables that convene into a Water Sustainability Index (WSI). WSI ranges from 1 to 4 where a score below 1.5 indicates poor water sustainability, while a score exceeding 3.5 signifies excellent sustainability. Likewise, the enhancement framework consists of dimensions, goals, and strategies. These frameworks relied on three specific dimensions, efficiency, resiliency, and community support. The identification of indicators, variables, and goals was based on SMART criteria. While the dimensions, indicators and goals are to remain consistent regardless of study areas, variables and strategies are site-specific and their selection needs to be based on each community's situations and data availability. The assessment framework suggested that the Asian Institute of Technology (AIT) community has achieved fair water sustainability status with a score of 2.25. The strategic framework yielded several recommendations aimed at enhancing the sustainability of the water supply system at the AIT. The study's outcomes offer tools to evaluate the current situation of sustainability and assists local community authorities in devising solutions to enhance sustainability in community supply systems. Looking ahead, these frameworks lay the groundwork for future investigations, to explore localized, community-centric strategies for sustainable water management.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100486"},"PeriodicalIF":5.4,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the determinants of the spatial variability of nitrogen sources use in the Lake Victoria basin, East Africa","authors":"Catherine Mathenge ,&nbsp;Stephen Mureithi ,&nbsp;Soul-Kifouly Midingoyi ,&nbsp;Benjamin Nyilitya ,&nbsp;Geoffrey Kironchi ,&nbsp;Cargele Masso","doi":"10.1016/j.indic.2024.100484","DOIUrl":"10.1016/j.indic.2024.100484","url":null,"abstract":"<div><div>As nitrogen pollution increasingly threatens water quality in the Lake Victoria Basin, it is essential to investigate the spatial factors influencing nitrogen source use. Understanding these determinants is crucial to inform effective strategies to combat eutrophication, enhance nutrient management, ensure food security and promote sustainable ecological development. This study investigated spatial variation of N sources, the farmers' socio-demographic and farm characteristics factors influencing farmers' choice of nitrogen sources. Data was collected from 1500 farmers between October and December 2020. The farmers were randomly selected in Kenya, Rwanda, Uganda, Burundi and Tanzania country sub-basins within the Lake Victoria basin (LVB). Spatial autocorrelation was used to evaluate the spatial variation of the nitrogen sources while the Optimized Parameter Geographical Detector (OPGD) model was used to identify the factors influencing the choice or use of N sources. The OPDG results indicate that the country of residence and livestock ownership are the primary factors accounting for 31.9% and 22.1% of the variation in nitrogen sources across the entire Lake Victoria Basin, respectively. The major sub-basin factors influencing the use of N sources were both farm characteristics (types of crops grown and farm size) and social socio-demographic factors of the farmer (education). These findings highlight the need for tailored strategies, accounting for geographical variations, farm characteristics and socio-demographic factors are essential when formulating nitrogen management strategies and policies at local and regional scales within the LVB.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100484"},"PeriodicalIF":5.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665972724001521/pdfft?md5=d502592eba795bb49ffdf207609e6f35&pid=1-s2.0-S2665972724001521-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling fractional vegetation cover dynamics: A spatiotemporal analysis using MODIS NDVI and machine learning","authors":"Shoaib Ahmad Anees ,&nbsp;Kaleem Mehmood ,&nbsp;Akhtar Rehman ,&nbsp;Nazir Ur Rehman ,&nbsp;Sultan Muhammad ,&nbsp;Fahad Shahzad ,&nbsp;Khadim Hussain ,&nbsp;Mi Luo ,&nbsp;Abdullah A. Alarfaj ,&nbsp;Sulaiman Ali Alharbi ,&nbsp;Waseem Razzaq Khan","doi":"10.1016/j.indic.2024.100485","DOIUrl":"10.1016/j.indic.2024.100485","url":null,"abstract":"<div><p>Understanding the dynamics of Fractional Vegetation Cover (FVC) is crucial for effective environmental monitoring and management, especially in regions like Pakistan that are sensitive to climate change. This study employs an innovative approach using MODIS NDVI data and the Pixel Dichotomy Model (PDM) to analyze the spatiotemporal dynamics of FVC across Pakistan from 2003 to 2020. Our findings reveal an overall increasing trend in FVC, with the highest value recorded in 2017 (0.37) and the lowest in 2004 (0.26). The Hurst exponent analysis (R/S ratio = 0.718) indicates a degree of long-term memory in the FVC time series. Rainfall was found to positively correlate with FVC (r = 0.6), while Land Surface Temperature (LST) and the Compounded Night Light Index (CNLI) exhibited negative correlations (r = −0.59 and r = −0.43, respectively). The Random Forest regression model highlighted CNLI as the most influential predictor (importance = 62.4%), emphasizing the need to consider human-induced factors in environmental management. These results provide critical insights for sustainable land management and contribute to understanding vegetation-climate interactions in arid and semi-arid environments.\"</p></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100485"},"PeriodicalIF":5.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665972724001533/pdfft?md5=b6636c03d511f8612631a5975f300255&pid=1-s2.0-S2665972724001533-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global environmental sustainability trends: A temporal comparison using a new interval-based composite indicator","authors":"Irene Petrosillo ,&nbsp;Erica Maria Lovello ,&nbsp;Carlo Drago ,&nbsp;Cosimo Magazzino ,&nbsp;Donatella Valente","doi":"10.1016/j.indic.2024.100482","DOIUrl":"10.1016/j.indic.2024.100482","url":null,"abstract":"<div><div>Assessing progress on the pursuit of the Sustainable Development Goals is crucial for evaluating the sustainability of a Country, although this is not easy, considering the interdependencies or interconnections of individual goals with others, and the fact that there are several indicators for each goal. The aims of this research are: (1) to propose a novel interval-based environmental sustainable composite index (ESI) suitable to monitor the worldwide environmental SDGs' implementation at national scale, (2) to solve the problem of missing data in large databases and the subjectivity in computing a composite index (CI), (3) to group and compare statistically countries according to the ESI, and (4) to represent spatially the results to identify areas of the world more or less environmentally sustainable than others. Clustering and Sankey diagrams have supported the temporal and spatial analysis of ESI trends, showing that Canada, Brazil, New Zealand, and several European countries have been the most sustainable in 2019. The novelty of this indicator is that each country presents an ESI central value, the most probable value of the composite indicator, and a range, which represents the uncertainty given by the lower and upper bounds. In this sense, it is possible to better interpret the results of the composite indicator, while simultaneously obtaining a measure of the uncertainty of the results. The composite indicator can be used to monitor countries’ vulnerability towards the unsustainability risk, as well as countries that are not able to escape from a sort of “unsustainability trap”.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100482"},"PeriodicalIF":5.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665972724001508/pdfft?md5=7df41dcfd7c5e9a57a63cbc62bcc787c&pid=1-s2.0-S2665972724001508-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing sustainability in smallholder vegetable farms in Benin Republic: A matrix approach","authors":"Nicodeme V. Fassinou Hotegni ,&nbsp;Alexandre Nouhougan Guidimadjègbè ,&nbsp;Mathieu A.T. Ayenan ,&nbsp;Ravi Gopal Singh ,&nbsp;Sylvanus Odjo","doi":"10.1016/j.indic.2024.100483","DOIUrl":"10.1016/j.indic.2024.100483","url":null,"abstract":"<div><p>This study aims to assess the level of sustainability in vegetable-based agrifood production systems in Benin and to propose actions to enhance sustainability, food safety, and year-round production in the vegetable production systems. Semi-structured interviews were conducted with 200 vegetable farmers in contrasting agroecological areas (with areas of extensive production of staples and intensive production of vegetables), using the “Indicateur de Durabilité des Exploitations Agricoles” (IDEA) framework (an on-farm sustainability index). Most of the surveyed vegetable farmers produced a wide range of crops, including leafy vegetables (amaranth, African eggplant, and African basil) and peppers, grown by more than 50% of the farmers. The average scores achieved by the vegetable farms regarding three dimensions of sustainability—ecological, social, and economic—were 35, 41, and 63, respectively, out of a maximum score of 100. All three sustainability dimensions of the vegetable farms were, on average, at a low level and improvements were needed for them to reach an acceptable standard. The vegetable farms located in the south of Benin had, on average, a higher sustainability score than those in the north: around 50% of vegetable farms in the south had a medium score, while the sustainability level of almost 75% of vegetable farms in the north was low. Interventions seeking to improve the sustainability of vegetable farms in Benin should focus on the promotion and adoption of eco-responsible practices that improve on-farm biodiversity, water conservation, and the effective allocation and management of land and labor, to mitigate the environmental impacts of vegetable production.</p></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100483"},"PeriodicalIF":5.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266597272400151X/pdfft?md5=25de5c02bcc5c0c9905053d4784c2f75&pid=1-s2.0-S266597272400151X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corporate climate scores, carbon emissions, and investment in decarbonisation in the steel industry. What do ratings tell us?","authors":"Charlie Cregan ,&nbsp;J. Andrew Kelly ,&nbsp;J. Peter Clinch","doi":"10.1016/j.indic.2024.100481","DOIUrl":"10.1016/j.indic.2024.100481","url":null,"abstract":"<div><p>Steel production is a critical economic activity and amongst the largest industrial consumers of energy. The industry faces a complex and costly task to decarbonise in line with global climate targets. This paper evaluates the performance of environmental and emissions scores within leading Environmental, Social and Governance (ESG) ratings products in capturing carbon emissions outcomes and investment in low-carbon production amongst major steel producers. We assess data for 75 steel producers, representing 65% of global production. We find no strong evidence that environmental or emissions scores reflect either levels of, or changes in, firms’ total greenhouse gas emissions or emissions intensity in the period 2013–2022. Overall, ‘good’ scores are not explained by available emissions or investment data. These findings for a critical industry emphasise the need for methodological transparency from all ratings providers, more research into ratings’ performance in reflecting outcomes and investments, and further policies to enhance disclosures from firms and rating agencies.</p></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"24 ","pages":"Article 100481"},"PeriodicalIF":5.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665972724001491/pdfft?md5=b3b5ced15c21479493e50f67df81767f&pid=1-s2.0-S2665972724001491-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}