Pub Date : 2025-02-01DOI: 10.1016/j.indic.2025.100590
Francesco Caraceni, Matteo Cordara, Carlo Brondi, Andrea Ballarino
In light of the growing interest in circular bioeconomy issues, this study aims to present an adaptation of the Material Circularity Indicator (MCI) for the quantitative assessment of circularity in agri-food systems. Specifically, the adapted MCI (a-MCI) developed in this research is designed to evaluate meat production in industrial farming. This is achieved by incorporating parameters such as the Survival Rate (SR) and the Feed Conversion Ratio (FCR) into the calculation of the utilisation factor (X) already embedded in the original MCI framework. The a-MCI's application was tested using case study data from various animal species (e.g., broilers and pigs), with the latter exhibiting a slightly higher a-MCI in the analysed case studies. Nonetheless, the significant variability of data collected from literature sources lead to results inconsistency, as the small sample of data induce a relevant standard deviation.
{"title":"Adapting the Material Circularity Indicator to evaluate circularity in food systems: two case studies on livestock rearing","authors":"Francesco Caraceni, Matteo Cordara, Carlo Brondi, Andrea Ballarino","doi":"10.1016/j.indic.2025.100590","DOIUrl":"10.1016/j.indic.2025.100590","url":null,"abstract":"<div><div>In light of the growing interest in circular bioeconomy issues, this study aims to present an adaptation of the Material Circularity Indicator (MCI) for the quantitative assessment of circularity in agri-food systems. Specifically, the adapted MCI (a-MCI) developed in this research is designed to evaluate meat production in industrial farming. This is achieved by incorporating parameters such as the Survival Rate (S<sub>R</sub>) and the Feed Conversion Ratio (FCR) into the calculation of the utilisation factor (X) already embedded in the original MCI framework. The a-MCI's application was tested using case study data from various animal species (e.g., broilers and pigs), with the latter exhibiting a slightly higher a-MCI in the analysed case studies. Nonetheless, the significant variability of data collected from literature sources lead to results inconsistency, as the small sample of data induce a relevant standard deviation.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100590"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180329","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100558
Qianru Lu , Weifeng Qi , Dongye Yang , Mingyu Zhang
The phenomenon of urban thermal environment has become increasingly serious recently, with blue-green spaces playing a crucial role in cooling urban warming. However, the synergistic cooling effects of blue and green spaces, treated as distinct entities with unique cooling mechanisms, have not been extensively explored. This study addresses this gap by examining the internal spatial coupling characteristics of blue and green spaces and their impact on cooling benefit under varying high-temperature conditions and development densities in Hangzhou, China. This study uses the area-weighted cooling intensity and the mean land surface temperature to reflect the cooling benefit, and proposes an evaluation system for spatial coupling characteristics including internal scale relationships, distance relationships, and morphological relationships, while considering the built environment and integrated spatial features as control variables. Using stepwise multiple linear regression and geographically weighted regression, the study analyzes the correlation between these characteristics and cooling benefit across four days using 4 global datasets and 16 local datasets. Results indicate that spatial coupling significantly impact its cooling effects, with internal scale relationships having the greatest impact. The influence of spatial coupling relationships varies across different land-use densities, with more pronounced effects under typical high-temperature conditions compared to extreme heat. These findings offer urban planners valuable insights into optimizing the spatial relationship of blue-green spaces, helping to maximize their cooling benefit in limited space resource in metropolitan, ultimately enhancing urban resilience to climate change.
{"title":"The influence of internal spatial coupling characteristics of blue-green space on cooling benefit in metropolitan areas: Evidence form Hangzhou, China","authors":"Qianru Lu , Weifeng Qi , Dongye Yang , Mingyu Zhang","doi":"10.1016/j.indic.2024.100558","DOIUrl":"10.1016/j.indic.2024.100558","url":null,"abstract":"<div><div>The phenomenon of urban thermal environment has become increasingly serious recently, with blue-green spaces playing a crucial role in cooling urban warming. However, the synergistic cooling effects of blue and green spaces, treated as distinct entities with unique cooling mechanisms, have not been extensively explored. This study addresses this gap by examining the internal spatial coupling characteristics of blue and green spaces and their impact on cooling benefit under varying high-temperature conditions and development densities in Hangzhou, China. This study uses the area-weighted cooling intensity and the mean land surface temperature to reflect the cooling benefit, and proposes an evaluation system for spatial coupling characteristics including internal scale relationships, distance relationships, and morphological relationships, while considering the built environment and integrated spatial features as control variables. Using stepwise multiple linear regression and geographically weighted regression, the study analyzes the correlation between these characteristics and cooling benefit across four days using 4 global datasets and 16 local datasets. Results indicate that spatial coupling significantly impact its cooling effects, with internal scale relationships having the greatest impact. The influence of spatial coupling relationships varies across different land-use densities, with more pronounced effects under typical high-temperature conditions compared to extreme heat. These findings offer urban planners valuable insights into optimizing the spatial relationship of blue-green spaces, helping to maximize their cooling benefit in limited space resource in metropolitan, ultimately enhancing urban resilience to climate change.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100558"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180864","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100554
Tesfaye Etensa, Tekie Alemu, Mengesha Yayo
Given the severity of global environmental degradation, particularly in countries like Ethiopia, it is urgent to rethink its drivers and measurements for actionable policy development. The relationships among these predictors are complex, often nonlinear, non-additive, and include reverse causality, making it difficult for traditional econometric models to capture them. Conventional CO₂ metrics also tend to overlook unique emission sources in developing countries, where emissions are closely linked to energy production, unsustainable agriculture, deforestation, and land use rather than industry. To address these gaps, this study applies a kernel-based machine learning model and develops context-specific CO₂ metrics to analyze environmental degradation predictors and forecast their long-term impacts in Ethiopia using quarterly data from 2000Q1 to 2020Q4. The findings indicate that economic growth, industrialization, energy poverty, urbanization, ICT, and resource rent are significant predictors, exhibiting complex, nonlinear relationships. Long-term prediction analysis shows that energy poverty, economic growth, ICT, and urbanization initially worsen degradation but lead to stabilization over time. In contrast, industrialization and resource rent predominantly exacerbate environmental issues before leveling off. The study recommends policies to enhance energy access and efficiency through renewable energy subsidies and financial incentives, integrate green infrastructure into urban planning, incentivize clean industrial technologies, promote environmentally inclusive growth, regulate eco-friendly ICT, such as energy-efficient data centers and e-waste management, implement a resource rent tax, and use adaptive policies with real-time analytics to address degradation thresholds, balancing economic growth with resilience and sustainability.
{"title":"Rethinking the measurements and predictors of environmental degradation in Ethiopia: Predicting long-term impacts using a kernel-based machine learning approach","authors":"Tesfaye Etensa, Tekie Alemu, Mengesha Yayo","doi":"10.1016/j.indic.2024.100554","DOIUrl":"10.1016/j.indic.2024.100554","url":null,"abstract":"<div><div>Given the severity of global environmental degradation, particularly in countries like Ethiopia, it is urgent to rethink its drivers and measurements for actionable policy development. The relationships among these predictors are complex, often nonlinear, non-additive, and include reverse causality, making it difficult for traditional econometric models to capture them. Conventional CO₂ metrics also tend to overlook unique emission sources in developing countries, where emissions are closely linked to energy production, unsustainable agriculture, deforestation, and land use rather than industry. To address these gaps, this study applies a kernel-based machine learning model and develops context-specific CO₂ metrics to analyze environmental degradation predictors and forecast their long-term impacts in Ethiopia using quarterly data from 2000Q1 to 2020Q4. The findings indicate that economic growth, industrialization, energy poverty, urbanization, ICT, and resource rent are significant predictors, exhibiting complex, nonlinear relationships. Long-term prediction analysis shows that energy poverty, economic growth, ICT, and urbanization initially worsen degradation but lead to stabilization over time. In contrast, industrialization and resource rent predominantly exacerbate environmental issues before leveling off. The study recommends policies to enhance energy access and efficiency through renewable energy subsidies and financial incentives, integrate green infrastructure into urban planning, incentivize clean industrial technologies, promote environmentally inclusive growth, regulate eco-friendly ICT, such as energy-efficient data centers and e-waste management, implement a resource rent tax, and use adaptive policies with real-time analytics to address degradation thresholds, balancing economic growth with resilience and sustainability.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100554"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180126","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100574
Sileshi Tadesse , Asnake Mekuriaw , Mohammed Assen
Land surface phenology (LSP) is a crucial indicator of climate change and its impact on ecosystems. Therefore, this study was carried out to assess the spatiotemporal variations in LSP and its response to climate change across the agroecological zones (AEZs) of the upper Gelana watershed in the northeastern highlands of Ethiopia. The LSP metrics were derived from MODIS NDVI data using TIMESAT v3.3, and trends as well as correlations were analyzed using the statistical programming language R. The results indicate that the dega AEZ exhibits an earlier start of the season (SOS) and a longer length of the season (LOS) compared to the lower and upper weina dega (LWD and UWD) AEZs. A delay in SOS and end of season (EOS) was observed in 71.3% and 82% of the study area, respectively, while LOS increased in nearly half of the area. There is a positive correlation between SOS and maximum temperature, and a negative correlation with belg season rainfall and drought indices in large parts of the study area. Similarly, EOS exhibits a direct association with kiremt season maximum temperature, rainfall, and drought indices. Furthermore, a shorter LOS is associated with a higher annual maximum temperature, while a longer LOS is associated with the increasing trend in annual rainfall. These findings will help raise awareness on climate change adaptation activities, including crop diversification, alteration of planting dates, soil conservation, water harvesting and irrigation, particularly within rural communities of the study area that rely heavily rely on rainfed agriculture.
{"title":"Spatiotemporal dynamics of land surface phenology and its response to climate change in the upper Gelana watershed, northeastern highlands of Ethiopia","authors":"Sileshi Tadesse , Asnake Mekuriaw , Mohammed Assen","doi":"10.1016/j.indic.2024.100574","DOIUrl":"10.1016/j.indic.2024.100574","url":null,"abstract":"<div><div>Land surface phenology (LSP) is a crucial indicator of climate change and its impact on ecosystems. Therefore, this study was carried out to assess the spatiotemporal variations in LSP and its response to climate change across the agroecological zones (AEZs) of the upper Gelana watershed in the northeastern highlands of Ethiopia. The LSP metrics were derived from MODIS NDVI data using TIMESAT v3.3, and trends as well as correlations were analyzed using the statistical programming language R. The results indicate that the <em>dega</em> AEZ exhibits an earlier start of the season (SOS) and a longer length of the season (LOS) compared to the <em>lower</em> and <em>upper weina dega</em> (LWD and UWD) AEZs. A delay in SOS and end of season (EOS) was observed in 71.3% and 82% of the study area, respectively, while LOS increased in nearly half of the area. There is a positive correlation between SOS and maximum temperature, and a negative correlation with <em>belg</em> season rainfall and drought indices in large parts of the study area. Similarly, EOS exhibits a direct association with <em>kiremt</em> season maximum temperature, rainfall, and drought indices. Furthermore, a shorter LOS is associated with a higher annual maximum temperature, while a longer LOS is associated with the increasing trend in annual rainfall. These findings will help raise awareness on climate change adaptation activities, including crop diversification, alteration of planting dates, soil conservation, water harvesting and irrigation, particularly within rural communities of the study area that rely heavily rely on rainfed agriculture.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100574"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143179960","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100562
Ruben D. Cordero , Anaïs Lacoursière-Roussel , Ramón Filgueira , Julie Arseneau , Jeffrey Barrell , Timothy J. Barrett , Christopher W. McKindsey , Daria Gallardi , Olivia Gibb , Terri Sutherland , Thomas Guyondet
Coastal embayments are dynamic ecosystems facing environmental and anthropogenic pressures, including bivalve aquaculture and climate change. Mesozooplankton, essential for transferring energy from primary producers to higher trophic levels, serve as indicators of habitat changes. Size structure is a critical trait that reflects local community dynamics, trophic interactions, and ecosystem conditions, offering insights into the functioning and resilience of aquatic environments. This study examines the spatio-temporal variation in mesozooplankton size structure across nine bivalve aquaculture embayments in Atlantic and Pacific Canada from 2020 to 2022. Using high-resolution imaging (FlowCam®) to measure individual zooplankton, we assessed the effects of location, tide, sampling day, season, and aquaculture pressure on the size distribution variation among and within bays. Results indicate that bays with similar size distributions tend to have larger mesozooplankton, while those with more variable distributions are dominated by medium-sized individuals. Significant associations between environmental factors and size variation were observed in four of eleven sampling events. Notably, St. Peters Bay, with the highest aquaculture pressure, showed significant variation associated with station location and sampling day. However, the tide effect was significant only in two sampling events. Seasonal analysis revealed that colder months generally exhibited larger median sizes, with some exceptions influenced by local conditions. Despite high levels of aquaculture pressure in some bays, no consistent association between aquaculture pressure and size variation was found, highlighting the influence of local environmental factors. This study underscores the importance of monitoring mesozooplankton size structure as a bioindicator for effective ecosystem management and targeted conservation strategies.
{"title":"Comparative analysis of mesozooplankton size fraction structure in bivalve aquaculture embayments in Atlantic and Pacific Canadian coastal regions","authors":"Ruben D. Cordero , Anaïs Lacoursière-Roussel , Ramón Filgueira , Julie Arseneau , Jeffrey Barrell , Timothy J. Barrett , Christopher W. McKindsey , Daria Gallardi , Olivia Gibb , Terri Sutherland , Thomas Guyondet","doi":"10.1016/j.indic.2024.100562","DOIUrl":"10.1016/j.indic.2024.100562","url":null,"abstract":"<div><div>Coastal embayments are dynamic ecosystems facing environmental and anthropogenic pressures, including bivalve aquaculture and climate change. Mesozooplankton, essential for transferring energy from primary producers to higher trophic levels, serve as indicators of habitat changes. Size structure is a critical trait that reflects local community dynamics, trophic interactions, and ecosystem conditions, offering insights into the functioning and resilience of aquatic environments. This study examines the spatio-temporal variation in mesozooplankton size structure across nine bivalve aquaculture embayments in Atlantic and Pacific Canada from 2020 to 2022. Using high-resolution imaging (FlowCam®) to measure individual zooplankton, we assessed the effects of location, tide, sampling day, season, and aquaculture pressure on the size distribution variation among and within bays. Results indicate that bays with similar size distributions tend to have larger mesozooplankton, while those with more variable distributions are dominated by medium-sized individuals. Significant associations between environmental factors and size variation were observed in four of eleven sampling events. Notably, St. Peters Bay, with the highest aquaculture pressure, showed significant variation associated with station location and sampling day. However, the tide effect was significant only in two sampling events. Seasonal analysis revealed that colder months generally exhibited larger median sizes, with some exceptions influenced by local conditions. Despite high levels of aquaculture pressure in some bays, no consistent association between aquaculture pressure and size variation was found, highlighting the influence of local environmental factors. This study underscores the importance of monitoring mesozooplankton size structure as a bioindicator for effective ecosystem management and targeted conservation strategies.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100562"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180857","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}
This study evaluates the environmental suitability and water resource impact of photovoltaic (PV) and concentrated solar power (CSP) systems in the desert regions of Northwest China. A Multi-Criteria Decision Analysis (MCDA) approach is employed, integrating seven key indicators that encompass climate, geography, and location perspectives. Methods such as AHP, CRITIC, CVM, IWC, and EWM are integrated into the MCDA system, with sensitivity analysis conducted to ensure the robustness of weight coefficients. Additionally, the study employs the Water Resource Pressure (WRP) index and spatial Gini coefficient to quantify the Water-Energy conflict. The findings indicate that the Tengger and Kumtag Deserts exhibit higher environmental suitability, lower water resource pressure, and favorable spatial equilibrium, making them optimal for PV and CSP development. In contrast, the Ulan Buh, Badain Jaran, and Qaidam Deserts face significant water resource pressures, necessitating careful planning to avoid ecological impacts. This study introduces a comprehensive framework that combines suitability assessments with water resource evaluations at a fine spatial scale of 0.25-degree grids. The proposed “Water-Electricity-Road” network framework addresses water scarcity and infrastructure accessibility, thereby optimizing solar energy utilization in desert regions. These insights offer valuable guidance for sustainable solar energy planning in arid regions globally.
{"title":"Integrated assessment of environmental suitability and water-energy conflict for optimizing solar energy in Northwest China's desert regions","authors":"Weike Zhao , Zhangxinyue Zhao , Wenjuan Hou , Dezheng Jiang , Kaijin Zhang , Xueliang Zhang","doi":"10.1016/j.indic.2024.100564","DOIUrl":"10.1016/j.indic.2024.100564","url":null,"abstract":"<div><div>This study evaluates the environmental suitability and water resource impact of photovoltaic (PV) and concentrated solar power (CSP) systems in the desert regions of Northwest China. A Multi-Criteria Decision Analysis (MCDA) approach is employed, integrating seven key indicators that encompass climate, geography, and location perspectives. Methods such as AHP, CRITIC, CVM, IWC, and EWM are integrated into the MCDA system, with sensitivity analysis conducted to ensure the robustness of weight coefficients. Additionally, the study employs the Water Resource Pressure (WRP) index and spatial Gini coefficient to quantify the Water-Energy conflict. The findings indicate that the Tengger and Kumtag Deserts exhibit higher environmental suitability, lower water resource pressure, and favorable spatial equilibrium, making them optimal for PV and CSP development. In contrast, the Ulan Buh, Badain Jaran, and Qaidam Deserts face significant water resource pressures, necessitating careful planning to avoid ecological impacts. This study introduces a comprehensive framework that combines suitability assessments with water resource evaluations at a fine spatial scale of 0.25-degree grids. The proposed “Water-Electricity-Road” network framework addresses water scarcity and infrastructure accessibility, thereby optimizing solar energy utilization in desert regions. These insights offer valuable guidance for sustainable solar energy planning in arid regions globally.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100564"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180860","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100570
Chalachew Tesfa
The study area is one of the biggest gorges in southeast Ethiopia formed by the Wabe Shebelle river. The road was constructed to connect Gasera to Indeto. The study aimed to map and gives some mitigation strategies for geohazards along the road corridor in Southeast Ethiopia using a GIS with AHP & FR technique within the 3 km buffer zones along the road corridor. The study included field investigations and inventorying, characterization of geological situations, assessments of the hydrogeological conditions, and identification of slope instability variables. A GIS technique was used to map an LSM with the combination of two models (AHP and FR). The study used eight factors: slope, aspect, lithology, rainfall, altitude, road proximity, river proximity, and land use/cover. The results of the study revealed that LSZ maps performed using FR and AHP were 64.5 % and 69 % and-the inventory shows high and very high LSZ respectively. Rockfalls, debris/earth slides, and rockslides are commonly observed landslides in the area. Based on the analysis lithology (basaltic and limestone formations) showed the highest contributions for landslide in the area. Slope and aspects show the most frequent landslide hazards in >40, 30–40°, and east, and northeast respectively. Generally, the study found that lithology, slope, and aspect were the main factors contributing to slope instability in the study area. The produced landslide susceptibility map is very important for urban planners, agricultural studies, environmentalists, and future landslide hazardous prevention and mitigation strategies.
{"title":"Geohazard mapping and mitigations along the road corridor Gasera–Indeto, Southeast Ethiopia","authors":"Chalachew Tesfa","doi":"10.1016/j.indic.2024.100570","DOIUrl":"10.1016/j.indic.2024.100570","url":null,"abstract":"<div><div>The study area is one of the biggest gorges in southeast Ethiopia formed by the Wabe Shebelle river. The road was constructed to connect Gasera to Indeto. The study aimed to map and gives some mitigation strategies for geohazards along the road corridor in Southeast Ethiopia using a GIS with AHP & FR technique within the 3 km buffer zones along the road corridor. The study included field investigations and inventorying, characterization of geological situations, assessments of the hydrogeological conditions, and identification of slope instability variables. A GIS technique was used to map an LSM with the combination of two models (AHP and FR). The study used eight factors: slope, aspect, lithology, rainfall, altitude, road proximity, river proximity, and land use/cover. The results of the study revealed that LSZ maps performed using FR and AHP were 64.5 % and 69 % and-the inventory shows high and very high LSZ respectively. Rockfalls, debris/earth slides, and rockslides are commonly observed landslides in the area. Based on the analysis lithology (basaltic and limestone formations) showed the highest contributions for landslide in the area. Slope and aspects show the most frequent landslide hazards in >40, 30–40°, and east, and northeast respectively. Generally, the study found that lithology, slope, and aspect were the main factors contributing to slope instability in the study area. The produced landslide susceptibility map is very important for urban planners, agricultural studies, environmentalists, and future landslide hazardous prevention and mitigation strategies.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100570"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180863","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100555
Zakaria Al-Omari, Nour Khlaifat, Mike Haddad
Water availability and accessibility are the most significant challenges facing developing countries like Jordan, which is ranked as one of the world's worst countries in terms of water resources. In Jordan's isolated desert areas, where underground wells supply water for livestock and human consumption, water pumping systems (WPSs) are essential. Therefore, finding alternative energy sources is necessary to power underground WPSs. However, numerous diesel generator (DG) issues impact the energy supply. This article presents the design and evaluation of a hybrid renewable energy system (HRES) powering a WPS in an isolated desert region (Al-Mudawwara village/Ma'an governorate) with a daily demand of 40.71 kWh, which is economically viable, environmentally friendly, and sustainable. Using the HOMER simulation software, the most efficient scenario is determined considering the average monthly solar radiation, average wind speed of 3.79 kWh/m2 and 6.31 m/s, respectively, economic limitations, and the component's technical specifications. The net-present cost (NPC), cost of energy (CoE), and the percentage of renewable energy fraction (REF) and Greenhouse gas emissions (GHGE) are utilized as optimization criteria. The results obtained show that the scenario with minimum initial capital cost (ICC) and total NPC, respectively, was the one with DG/WT/storage batteries (SB) ($US 53,69) and ($US 59,611). The HRES (PV/WT/SBs) is the optimal scenario since it produces power at the lowest CoE ($US 0.241/kWh), leading to reliable energy and eliminating GHGE.
{"title":"A feasibility study of combining solar/wind energy to power a water pumping system in Jordan's Desert/Al-Mudawwara village","authors":"Zakaria Al-Omari, Nour Khlaifat, Mike Haddad","doi":"10.1016/j.indic.2024.100555","DOIUrl":"10.1016/j.indic.2024.100555","url":null,"abstract":"<div><div>Water availability and accessibility are the most significant challenges facing developing countries like Jordan, which is ranked as one of the world's worst countries in terms of water resources. In Jordan's isolated desert areas, where underground wells supply water for livestock and human consumption, water pumping systems (WPSs) are essential. Therefore, finding alternative energy sources is necessary to power underground WPSs. However, numerous diesel generator (DG) issues impact the energy supply. This article presents the design and evaluation of a hybrid renewable energy system (HRES) powering a WPS in an isolated desert region (Al-Mudawwara village/Ma'an governorate) with a daily demand of 40.71 kWh, which is economically viable, environmentally friendly, and sustainable. Using the HOMER simulation software, the most efficient scenario is determined considering the average monthly solar radiation, average wind speed of 3.79 kWh/m<sup>2</sup> and 6.31 m/s, respectively, economic limitations, and the component's technical specifications. The net-present cost (NPC), cost of energy (CoE), and the percentage of renewable energy fraction (REF) and Greenhouse gas emissions (GHGE) are utilized as optimization criteria. The results obtained show that the scenario with minimum initial capital cost (ICC) and total NPC, respectively, was the one with DG/WT/storage batteries (SB) ($US 53,69) and ($US 59,611). The HRES (PV/WT/SBs) is the optimal scenario since it produces power at the lowest CoE ($US 0.241/kWh), leading to reliable energy and eliminating GHGE.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100555"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180108","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100566
Buri Ha , Timur Borjigin
This study adopts a process-oriented research perspective to explore the mechanisms of grassland law enforcement and assess its efficacy. Through an extensive investigation of enforcement practices in the grasslands of X Banner, Inner Mongolia, it posits that “weak enforcement” reflects an inadequate response by enforcers to societal expectations. The study reveals that enforcement capacity and various factors from overlapping domains in the enforcement field influence the enforcement process. The key elements identified as critical influencers include the dual leadership structure of the bureaucratic system, the conflict between local development objectives and law enforcement goals, the ineffective supervision model used by higher authorities, and the diverse interaction modes among different law enforcement targets at the social space level. These factors collectively exert a complex array of forces on the enforcement process, synergistically contributing to weakened enforcement. Understanding the mechanisms shaping “weak enforcement” helps in diagnosing the root causes of enforcement dilemmas, offering theoretical and practical insights for enhancing grassland ecology governance and law enforcement practices.
{"title":"Why are grassland protection regulations in China Elusive in enforcement? Study of X Banner, Inner Mongolia","authors":"Buri Ha , Timur Borjigin","doi":"10.1016/j.indic.2024.100566","DOIUrl":"10.1016/j.indic.2024.100566","url":null,"abstract":"<div><div>This study adopts a process-oriented research perspective to explore the mechanisms of grassland law enforcement and assess its efficacy. Through an extensive investigation of enforcement practices in the grasslands of X Banner, Inner Mongolia, it posits that “weak enforcement” reflects an inadequate response by enforcers to societal expectations. The study reveals that enforcement capacity and various factors from overlapping domains in the enforcement field influence the enforcement process. The key elements identified as critical influencers include the dual leadership structure of the bureaucratic system, the conflict between local development objectives and law enforcement goals, the ineffective supervision model used by higher authorities, and the diverse interaction modes among different law enforcement targets at the social space level. These factors collectively exert a complex array of forces on the enforcement process, synergistically contributing to weakened enforcement. Understanding the mechanisms shaping “weak enforcement” helps in diagnosing the root causes of enforcement dilemmas, offering theoretical and practical insights for enhancing grassland ecology governance and law enforcement practices.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100566"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180109","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}
Pub Date : 2025-02-01DOI: 10.1016/j.indic.2024.100553
Hadi Saadi , Molood Behnia , Morteza Taki , Ali Kaab
The aim of this study was to compare energy consumption and damage assessment in different types of greenhouse structures used for vegetable production. The research focused on analyzing energy indicators in the production of greenhouse products, specifically Tunnel and Quonset greenhouse structures growing cucumber, tomato, and eggplant in Shushtar city. Data was collected from greenhouses with both types of structures, as well as from a random field survey of 20 greenhouses in the city. The results showed that energy consumption in Tunnel greenhouses for cucumber, tomato, and eggplant crops was 4.35 × 106, 3.85 × 106 and 3.33 × 106 MJ ha−1 respectively. For Quonset greenhouses, the energy consumption for the same crops was 4.86 × 106, 4.36 × 106 and 3.85 × 106 MJ ha−1, respectively. The energy efficiency for each crop and greenhouse type was also calculated. The study found that Quonset greenhouses had higher energy consumption compared to Tunnel greenhouses, with cucumber crops showing the highest energy consumption. The highest yield was achieved with cucumber crops in Quonset greenhouses, while the lowest yield was seen with eggplant crops in Tunnel greenhouses due to differences in structure dimensions. Environmental effects analysis revealed varying levels of pollution caused by resource usage, with eggplant production in Quonset greenhouses showing the highest pollution levels. Recommendations were made to optimize electricity, diesel fuel, and fertilizer use to reduce energy consumption and environmental impact. The study suggested the adoption of renewable energy sources like solar power to mitigate energy consumption in greenhouse production.
{"title":"A comparative study on energy use and environmental impacts in various greenhouse models for vegetable cultivation","authors":"Hadi Saadi , Molood Behnia , Morteza Taki , Ali Kaab","doi":"10.1016/j.indic.2024.100553","DOIUrl":"10.1016/j.indic.2024.100553","url":null,"abstract":"<div><div>The aim of this study was to compare energy consumption and damage assessment in different types of greenhouse structures used for vegetable production. The research focused on analyzing energy indicators in the production of greenhouse products, specifically Tunnel and Quonset greenhouse structures growing cucumber, tomato, and eggplant in Shushtar city. Data was collected from greenhouses with both types of structures, as well as from a random field survey of 20 greenhouses in the city. The results showed that energy consumption in Tunnel greenhouses for cucumber, tomato, and eggplant crops was 4.35 × 10<sup>6</sup>, 3.85 × 10<sup>6</sup> and 3.33 × 10<sup>6</sup> MJ ha<sup>−1</sup> respectively. For Quonset greenhouses, the energy consumption for the same crops was 4.86 × 10<sup>6</sup>, 4.36 × 10<sup>6</sup> and 3.85 × 10<sup>6</sup> MJ ha<sup>−1</sup>, respectively. The energy efficiency for each crop and greenhouse type was also calculated. The study found that Quonset greenhouses had higher energy consumption compared to Tunnel greenhouses, with cucumber crops showing the highest energy consumption. The highest yield was achieved with cucumber crops in Quonset greenhouses, while the lowest yield was seen with eggplant crops in Tunnel greenhouses due to differences in structure dimensions. Environmental effects analysis revealed varying levels of pollution caused by resource usage, with eggplant production in Quonset greenhouses showing the highest pollution levels. Recommendations were made to optimize electricity, diesel fuel, and fertilizer use to reduce energy consumption and environmental impact. The study suggested the adoption of renewable energy sources like solar power to mitigate energy consumption in greenhouse production.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"25 ","pages":"Article 100553"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180115","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}
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