Environmental and Sustainability Indicators最新文献

{"title":"Analyzing financial development's moderating role on the investment-environmental quality nexus: Evidence from Australia using Autoregressive Distributed Lag approach","authors":"Ambepitiya Wijethunga Gamage Champa Nilanthi Wijethunga ,&nbsp;Mohammad Mafizur Rahman ,&nbsp;Tapan Sarker","doi":"10.1016/j.indic.2024.100568","DOIUrl":"10.1016/j.indic.2024.100568","url":null,"abstract":"<div><div>Understanding the impact channels of financial development on environmental quality is vital for achieving desired environmental targets. While the direct impact of financial development on environmental quality has been extensively addressed, its indirect channel through investment has not been broadly explored. Thus, how financial development moderates the impact of domestic investments and foreign direct investments on environment can be an important research agenda. Therefore, this research purposes to study whether financial development moderates the impact of investments on environmental quality in Australia for the period from 1980 to 2021 using the Autoregressive Distributed Lag (ARDL) model. The key findings emphasize that financial development degrades environmental quality in Australia. Moreover, foreign direct investments have a positive effect on environmental quality, confirming the validity of the Pollution Halo Hypothesis in Australia. In contrast, domestic investments worsen environmental quality. Additionally, financial development does not mitigate the harmful impact of domestic investments on environmental quality. However, financial development plays a neutral role in moderating the impact of foreign direct investments on environmental quality while moderating the impact of domestic investment-environmetal quality relationship. These empirical findings provide diverse policy implications for ensuring environmental quality in Australia by strategically supporting both foreign and domestic investments.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100568"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180322","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 future urban flood risk of Thailand's bangkok metropolis using geoprocessing and machine learning algorithm","authors":"Duangporn Garshasbi ,&nbsp;Jarunya Kitiphaisannon ,&nbsp;Tanaphoom Wongbumru ,&nbsp;Nawhath Thanwiset Thanvisitthpon","doi":"10.1016/j.indic.2024.100559","DOIUrl":"10.1016/j.indic.2024.100559","url":null,"abstract":"<div><div>Thailand's capital Bangkok is no stranger to floods and the disruption caused by repetitive flooding. Rapid urbanization, inadequate infrastructure, and climate change exacerbate the situation as urban flooding becomes increasingly more frequent and severe. The aim of this study is to assess future urban flood risk of Bangkok metropolitan at the district level for three future periods: 2033, 2043, and 2053. In the assessment of flood risk, the future values of six dynamic urban flood indicators are first projected using an integrative geoprocessing and random forest machine learning algorithm. The projected future indicator values are subsequently used to assess urban flood risk across Bangkok's 50 districts. The six dynamic indicators of urban flood risk are average monthly rainfall, wet days, vegetation cover, population density, flood waste, and anti-flood infrastructure. The findings indicate a steady increase in average monthly rainfall and wet days, highlighting the need for improved floodwater drainage systems and flood resilience. Ongoing urbanization and decreasing vegetation cover exacerbate flood risks. Densely populated areas remain highly susceptible to flooding, underscoring the significance of effective population and waste management strategies. This study also proposes three-timescale urban flood mitigation plans (10-, 20- and 30-year plans) to mitigate future urban flood risk, focusing on short-, medium-, and long-term measures. This research is the first to integrate geoprocessing with machine learning to enhance the prediction performance and accuracy of future urban flood risk projections.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100559"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180024","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 dynamic coastal vulnerability to climate hazards: A geospatial approach in Kakinada District, Andhra Pradesh, India","authors":"Ganni Satya Venkata Sai Aditya Bharadwaz ,&nbsp;Indrajit Pal ,&nbsp;Chitrini Mozumder ,&nbsp;Mokbul Morshed Ahmad","doi":"10.1016/j.indic.2025.100622","DOIUrl":"10.1016/j.indic.2025.100622","url":null,"abstract":"<div><div>This study assesses the dynamic coastal vulnerability of Kakinada district in India by integrating various geophysical and socioeconomic factors within a geospatial framework. The analysis examines data from 2001, 2011, and 2021, evaluating dynamic components like cyclone track density, tsunami surge, coastal erosion, temperature rainfall, population, land use/land cover, elevation, slope and drainage density, and transport network. The findings indicate that coastal residents are at high risk due to climate change and coastal hazards. The composite assessment of dynamic coastal vulnerability was estimated and mapped annually, revealing significant impacts across the district. In 2021, 91.17 km² of coastal tracts in Thallarevu, Kakinada Urban, Kakinada Rural, Kothapallei, and Thondangi were classified as very high vulnerability zones. An additional 239.98 km² was categorized as high vulnerability and 267.17 km² as moderate vulnerability. Overall, 598.32 km² out of 1647.68 km² exhibited moderate to very high vulnerability, highlighting the threats from coastal erosion and human encroachment. Significant coastal erosion was identified, with shoreline changes ranging from 604.35 to 1016.25 m over the past two decades, particularly in the southern district. Sea level rise was a critical factor, especially in Kajuluru and Thallarevu, and rapid population growth and urban development exacerbated vulnerability by reducing vegetation cover and increasing built-up areas. Thondangi and Kakinada urban were identified as the most vulnerable blocks, requiring urgent adaptation and mitigation strategies. The study recommends enhancing local services such as clean water, sanitation, primary healthcare, skill development, and flood shelters linked by efficient transportation networks could improve living standards and reduce vulnerability.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100622"},"PeriodicalIF":5.4,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098949","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":"Derivation of allometric equations and carbon content estimation in mangrove forests of Malaysia","authors":"Waseem Razzaq Khan ,&nbsp;Michele Giani ,&nbsp;Stanislao Bevilacqua ,&nbsp;Shoaib Ahmad Anees ,&nbsp;Kaleem Mehmood ,&nbsp;M. Nazre ,&nbsp;Abdul Aziz Bin Abdul Haddy ,&nbsp;Abang Norizan Bin Abang Median ,&nbsp;Japanie Bin Bujang ,&nbsp;Fatin-Norliyana Mohamad-Ismail ,&nbsp;Johar Mohamed ,&nbsp;Zaiton Samdin ,&nbsp;Rambod Abiri ,&nbsp;Tuan-Marina Tuan-Ibrahim ,&nbsp;Lydia-Suzieana Mohammad ,&nbsp;Hamid-Reza Naji ,&nbsp;Seemab Akram ,&nbsp;Hazandy Abdul-Hamid ,&nbsp;Timothy Dube","doi":"10.1016/j.indic.2025.100618","DOIUrl":"10.1016/j.indic.2025.100618","url":null,"abstract":"<div><div>Mangrove forests play a vital role in carbon sequestration and climate change mitigation, yet comprehensive data on their carbon storage capacity in Malaysia remain limited. This study investigated allometric relationships and carbon content in Malaysian mangrove forests, aiming to develop site species-specific allometric equations, determine carbon content in tree components, and assess total carbon stock. Research was conducted in four compartments of the Sg. Pulai Permanent Reserved Forest, representing a mixed-species mangrove stand. We measured 1403 trees across ten species, with <em>Rhizophora apiculata</em> identified as the dominant species. Using diameter at breast height (DBH) and tree height, we developed site species-specific allometric equations to estimate aboveground biomass. The total aboveground biomass ranged from 183.30 t ha⁻¹ to 187.06 t ha⁻¹ across the study area. We calculated the total carbon stock at 91.01 t C ha⁻¹, incorporating measurements from trees below 5 cm in diameter, dead and downed wood, and litter. An economic valuation of carbon storage was conducted using two approaches: the social cost of carbon method estimated a value of USD 4054.76 per hectare. In contrast, the market price approach yielded USD 1064.34 per hectare. This study provides essential data for improving biomass and carbon stock estimation methods in Malaysian mangrove ecosystems. Our findings highlight these forests' economic and ecological importance, supporting their integration into climate change mitigation strategies and informing sustainable management and conservation policies for mangrove forests in Malaysia and similar regions.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100618"},"PeriodicalIF":5.4,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143283596","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":"Evaluation of sustainable energy use in sugarcane production: A holistic model from planting to harvest and life cycle assessment","authors":"Molood Behnia ,&nbsp;Mohammad Ghahderijani ,&nbsp;Ali Kaab ,&nbsp;Marjan Behnia","doi":"10.1016/j.indic.2025.100617","DOIUrl":"10.1016/j.indic.2025.100617","url":null,"abstract":"<div><div>The study evaluates energy consumption in sugarcane production at the Salman Farsi Sugarcane Agro-Industrial Company in Khuzestan province, Iran, comparing plant cane and ratoon cycles. Plant cane show higher energy input (124,912.32 MJ ha^-1) and output (107,530.44 MJ ha^-1) than ratoon farms (80,317.81 MJ ha^-1 input and 87,586.68 MJ ha^-1 output). However, ratoon cycles are more energy efficient. To lessen energy use in plant cane, the research recommends strategies like minimizing machinery use, adopting reduced and no-tillage practices, and employing efficient irrigation and spraying methods. The environmental assessment reveals that plant cane have greater negative impacts on human health, ecosystems, and resources. Specifically, human health impacts are 3.69 DALY for planted systems versus 1.54 for ratoon systems, indicating greater health risks from initial plantings. Ecosystem impacts also show more local species loss in planted systems (6.25E-04 species.yr compared to 4.11E-04 for ratoon). Moreover, resource costs are higher for planted systems at 320.12 USD2013 of sugarcane, compared to 210.46 USD2013 for ratoon production. The analysis compares Artificial Neural Network and Adaptive Neuro-Fuzzy Inference Systems models for predicting energy outputs and environmental effects. Artificial Neural Network models excel in predicting impacts for planted sugarcane, whereas Adaptive Neuro-Fuzzy Inference Systems models are more accurate for ratoon production and are computationally more efficient. The findings emphasize the need for improved sustainability and efficiency in sugarcane production through better energy management and reduced environmental impacts.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100617"},"PeriodicalIF":5.4,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098932","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":"Developing an indicator system and assessing China's progress on climate change adaptation in 2010–2022 from dual-dimension","authors":"Yang Song ,&nbsp;Xiu Yang ,&nbsp;Huimin Li ,&nbsp;Mingyu Liu","doi":"10.1016/j.indic.2025.100613","DOIUrl":"10.1016/j.indic.2025.100613","url":null,"abstract":"<div><div>China, as one of the regions most severely impacted by climate change globally, has consistently prioritized the issue of climate change adaptation. The Chinese government has implemented a series of measures to adapt to climate change in alignment with national economic and social development plans, yielding positive outcomes. Based on relevant theories, practices, and domestic and international strategic arrangements, we have developed an assessment indicator system from dual-dimension, encompassing both the adaptive stage and the adaptive sector, to assess China's progress in adapting to climate change over the period from 2010 to 2022. This system encompasses indicators related to the impacts of climate change, work progress indicators, effectiveness indicators, among others. The preliminary assessment reveals that since 2010, the influence of climate risks on China has exhibited an upward trajectory. Notably, China has continuously advanced its efforts in promoting adaptation concepts; enhancing monitoring and early warning systems; implementing disaster prevention and mitigation strategies; addressing public health concerns; while significantly improving adaptive capacities within key areas such as agriculture, forestry ecosystems; water resources management; infrastructure development. These endeavors have resulted in substantial adaptation effects and enhanced resilience. Looking ahead, this study will track the progress of climate adaptation actions in China, deepen the analysis of the sensitivity and relevance of adaptation actions, and aim to propose quantitative scientific methods to provide decision support for climate adaptation strategies. Horizontal gap analysis with countries shows that China's climate risks are higher than the global average. China's adaptive capacity and effectiveness still lag behind the international advanced values in 4 areas: disaster prevention, agriculture, forestry and ecology, and freshwater and Marine. In the areas of public health and infrastructure, China has reached or even exceeded the international advanced level. Future research should address issues such as incorporating adaptation costs into the indicator system, establishing long-term monitoring mechanisms for dynamic adjustments, developing local-level indicators, and analyzing the sensitivity and correlation of adaptation actions to enhance the scientific support for climate change adaptation work.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100613"},"PeriodicalIF":5.4,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098950","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":"Link of dragonflies and damselflies with the aquatic environment is differently expressed in adult and larval stages","authors":"Edwin THM. Peeters ,&nbsp;Anton AM. Gerritsen ,&nbsp;Froukje Rienks ,&nbsp;Michiel Wilhelm","doi":"10.1016/j.indic.2025.100621","DOIUrl":"10.1016/j.indic.2025.100621","url":null,"abstract":"<div><div>Aquatic insects like dragonflies and damselflies link the aquatic and terrestrial world through their life-cycle. Adults and larvae are frequently regarded as indicators of good environmental quality. The relationship between adults and the water quality in a nearby water system is not well known as well as to what extent adults reflect the presence of their larvae in that water system. To explore these relationships, ideally adults and larvae should be recorded at the same time. In a Dutch citizen science project, adult Odonata were recorded while collecting aquatic macroinvertebrates in 364 sampling events in 2023.</div><div>Regression analyses showed that the presence of adult dragonflies was weakly correlated with the presence of their larvae in a nearby water system, while the presence of adult damselflies was a much better indicator. Damselfly larvae were associated with a moderate to reasonable biological water quality and dragonfly larvae with reasonable to good. Higher vegetation cover coincided with the presence of adult Odonata, but vegetation cover was insignificant to their larvae. Abiotic conditions were more important for larvae than biotic variables. Dragonfly larvae were better indicators of good water quality than damselfly larvae and adult Odonata were not at all associated with water quality in the nearby water system. However, adult Odonata do indicate the presence of aquatic vegetation in a nearby water system. Since volunteers frequently sampled other waters than professionals, public available data of these recordings can be very beneficial for water managers to know more about water quality in their areas.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100621"},"PeriodicalIF":5.4,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098933","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":"River water quality monitoring using machine learning with multiple possible in-situ scenarios","authors":"Dani Irwan ,&nbsp;Saerahany Legori Ibrahim ,&nbsp;Sarmad Dashti Latif ,&nbsp;Chris Aaron Winston ,&nbsp;Ali Najah Ahmed ,&nbsp;Mohsen Sherif ,&nbsp;Amr H. El-Shafie ,&nbsp;Ahmed El-Shafie","doi":"10.1016/j.indic.2025.100620","DOIUrl":"10.1016/j.indic.2025.100620","url":null,"abstract":"<div><div>Water quality is influenced by a wide range of factors, but it is expensive and technically difficult to take into account every factor, which leaves out quality variations. The assessment process is made more difficult by the need for different evaluation indicators for various water uses. Furthermore, many water quality factors have complex nonlinear relationships that are difficult for these methods to handle. On the other hand, because machine learning can quickly identify underlying principles and handle complex data with efficiency, it offers a promising approach. The gap involves addressing complex relationship and environmental factors when predicting water quality in rivers. The purpose of this study is to evaluate the feasibility of estimating the Gombak River's Water Quality Index (WQI) using machine learning, and to identify appropriate models based on statistical performance metrics. The study looks into the possibility of estimating WQI solely using dissolved oxygen (DO) and pH as predictors because the chemical parameters in the current Malaysian WQI calculation method takes some time to compute. This research provides insight into the accuracy, precision, and general performance of these models in predicting water quality by looking at the residuals of various scenarios and evaluating performance metrics across different machine learning models. This study provides insights into the potential of machine learning for improving water quality assessment and management practices. Future studies should concentrate on resolving these issues and investigating other elements, such as environmental variables, land use patterns, and human activity, that may affect the forecast of water quality.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100620"},"PeriodicalIF":5.4,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143283598","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":"Geosystem services from the subsurface: A literature review and a proposed set of indicators tailored to a Swedish setting","authors":"Emrik Lundin-Frisk ,&nbsp;Lars O. Ericsson ,&nbsp;Paula Lindgren ,&nbsp;Lorena Melgaço ,&nbsp;Fredrik Mossmark ,&nbsp;Olof Taromi Sandström ,&nbsp;Victoria Svahn ,&nbsp;Tore Söderqvist ,&nbsp;Yevheniya Volchko ,&nbsp;Maria de Lourdes Melo Zurita ,&nbsp;Jenny Norrman","doi":"10.1016/j.indic.2025.100609","DOIUrl":"10.1016/j.indic.2025.100609","url":null,"abstract":"<div><div>In this study, a literature review was conducted to identify indicators that can be utilised to assess and visualise the potential of the geophysical environment to deliver geosystem services. The literature review identified 24 studies and 22 technical reports, resulting in a list of 75 geosystem services indicators for 23 geosystem services associated with the subsurface. Building upon these findings, a country-specific set of 21 indicators pertinent to the geological setting of Sweden was developed. Each developed indicator was further subdivided into different ‘capacity classes’ to denote the potential of the geophysical environment to deliver a specific geosystem service. Most of these proposed indicators can be directly applied (19 out of 21), as there is readily available information in open-access maps and databases. However, some of the assigned capacity classes need to be adjusted according to the spatial scale of application. Furthermore, to convey the benefit or value of a given geosystem service, the proposed indicators must also be complemented with estimates of accessibility and societal importance of said service. Nonetheless, the proposed set of indicators represents an initial step towards a comprehensive mapping of geosystem services that can be used to highlight the multitude of ways the subsurface contributes to society.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100609"},"PeriodicalIF":5.4,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143283597","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":"To what extent cultivar selection can affect the environmental impact of rapeseed production?","authors":"Seyedeh Samira HabibTabar Shiadeh ,&nbsp;Yaser Feizabadi ,&nbsp;Armaghan Kosari-Moghaddam","doi":"10.1016/j.indic.2025.100619","DOIUrl":"10.1016/j.indic.2025.100619","url":null,"abstract":"<div><div>Rapeseed (<em>Brassica napus</em> L.), ranked as the second most crucial oil crop globally, holds a prominent position in world agriculture, playing a pivotal role in meeting the increasing demand for edible oil and biodiesel. Pursuing sustainable goals in rapeseed production systems becomes paramount to addressing this growing demand. This study focuses on cultivar selection, a key factor for decision-makers striving to establish sustainable production systems. The investigation, conducted in Mazandaran province, Iran, the country's third-largest rapeseed producer, examines five commonly used cultivars: Zafar, Hyola, Traper, RGS003, and Neptune. Employing Life Cycle Assessment (LCA) with the IMPACT2002+ method, the study reveals varying environmental impacts among cultivars, contingent on the selected functional unit. Accordingly, based on one ton of harvested mass, RGS003 emerges as the most pollutant cultivar, while considering 1 ha of rapeseed farms, Traper exhibits the highest environmental impacts. nitrogen-based fertilizers stand out as major hotspots, contributing to over half of the negative effects across various categories. In conclusion, while factors like drought tolerance and disease resistance are crucial in cultivar selection, the environmental performance of cultivars also significantly influences the decision-making process.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"26 ","pages":"Article 100619"},"PeriodicalIF":5.4,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428638","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}