Pub Date : 2024-12-21DOI: 10.1016/j.resenv.2024.100188
Dong Wu , Yong Geng , Ziyan Gao , Yifan Wu
Vanadium has been classified as one critical metal by multiple countries. China has the largest vanadium reserve and production capacity in the world and plays a vital role in the global vanadium supply chain. This study aims to uncover China’s vanadium cycle and market features for the period of 2000–2022 by applying dynamic material flow analysis method. The results show that the supply of vanadium had increased more than tenfold from 2000 to 2022, with an accumulated amount of 856 Kt. The majority of vanadium were used for meeting with the domestic demand (679 Kt). Vanadium-containing steel alloys dominated the largest share (87%), while the demand for vanadium redox flow battery increased rapidly, with an average annual growth rate of 21%. Secondary vanadium resources were predominantly recovered from the slags generated from the production stage, with a smaller share from the old scraps collected from end-of-life vanadium-containing products. China mainly imported primary vanadium resources from developing countries and exported intermediate products to developed countries. However, vanadium trade was seriously disrupted by the global financial crisis in 2008 and the recent COVID-19 pandemic. Several policies are proposed to promote stable supply and sustainable utilization of vanadium resources from the perspectives of economic incentives, technological development, industrial adjustment, trade structure and strategic reserve.
{"title":"Uncovering the evolution of vanadium cycle in China during 2000–2022","authors":"Dong Wu , Yong Geng , Ziyan Gao , Yifan Wu","doi":"10.1016/j.resenv.2024.100188","DOIUrl":"10.1016/j.resenv.2024.100188","url":null,"abstract":"<div><div>Vanadium has been classified as one critical metal by multiple countries. China has the largest vanadium reserve and production capacity in the world and plays a vital role in the global vanadium supply chain. This study aims to uncover China’s vanadium cycle and market features for the period of 2000–2022 by applying dynamic material flow analysis method. The results show that the supply of vanadium had increased more than tenfold from 2000 to 2022, with an accumulated amount of 856 Kt. The majority of vanadium were used for meeting with the domestic demand (679 Kt). Vanadium-containing steel alloys dominated the largest share (87%), while the demand for vanadium redox flow battery increased rapidly, with an average annual growth rate of 21%. Secondary vanadium resources were predominantly recovered from the slags generated from the production stage, with a smaller share from the old scraps collected from end-of-life vanadium-containing products. China mainly imported primary vanadium resources from developing countries and exported intermediate products to developed countries. However, vanadium trade was seriously disrupted by the global financial crisis in 2008 and the recent COVID-19 pandemic. Several policies are proposed to promote stable supply and sustainable utilization of vanadium resources from the perspectives of economic incentives, technological development, industrial adjustment, trade structure and strategic reserve.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"19 ","pages":"Article 100188"},"PeriodicalIF":12.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167547","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 : 2024-12-10DOI: 10.1016/j.resenv.2024.100185
Linchao Li , Qinsi He , Matthew Tom Harrison , Yu Shi , Puyu Feng , Bin Wang , Yajie Zhang , Yi Li , De Li Liu , Guijun Yang , Meixue Zhou , Qiang Yu , Ke Liu
Extreme precipitation poses a significant threat to crop production, often underestimated by process-based models. State-of-the-art models also struggle with high-resolution spatial applications due to process complexity. Here, we developed a Knowledge-Guided Machine Learning (KGML) framework that integrates machine learning with a waterlogging-enabled APSIM (Agricultural Production Systems sIMulator) to simulate wheat yield change under climate change in the Yangtze River Basin, China. Using transfer learning, this KGML framework transferred waterlogging processes to eight gridded crop models, enabling more accurate yield projections. We found that KGML could accurately replicate the behavior of the improved APSIM model under waterlogging conditions, achieving an R2 of 0.83 and an RMSE of 272.3 kg/ha for yield loss simulations. Soil properties were identified as the primary factors influencing yield losses under waterlogging, highlighting the importance of optimizing soil conditions to mitigate the adverse impacts of excessive water. Across different scenarios, the improved crop model ensembles projected greater crop yield losses compared to the original simulated outputs, with additional losses (compared to the historical period) around 5.9%–7.3% during the two periods. Although global climate models were the primary source of uncertainty in T1 (2029–2059), crop models contributed more to uncertainty in T2 (2069–2099). The improved ensemble reduced uncertainty from crop models compared to the original. This study highlights the potential of KGML to improve crop models, offering valuable insights for climate impact assessments and resource management. We believe our results can help national and local authorities make informed crop yield decisions under climate change.
{"title":"Knowledge-guided machine learning for improving crop yield projections of waterlogging effects under climate change","authors":"Linchao Li , Qinsi He , Matthew Tom Harrison , Yu Shi , Puyu Feng , Bin Wang , Yajie Zhang , Yi Li , De Li Liu , Guijun Yang , Meixue Zhou , Qiang Yu , Ke Liu","doi":"10.1016/j.resenv.2024.100185","DOIUrl":"10.1016/j.resenv.2024.100185","url":null,"abstract":"<div><div>Extreme precipitation poses a significant threat to crop production, often underestimated by process-based models. State-of-the-art models also struggle with high-resolution spatial applications due to process complexity. Here, we developed a Knowledge-Guided Machine Learning (KGML) framework that integrates machine learning with a waterlogging-enabled APSIM (Agricultural Production Systems sIMulator) to simulate wheat yield change under climate change in the Yangtze River Basin, China. Using transfer learning, this KGML framework transferred waterlogging processes to eight gridded crop models, enabling more accurate yield projections. We found that KGML could accurately replicate the behavior of the improved APSIM model under waterlogging conditions, achieving an R<sup>2</sup> of 0.83 and an RMSE of 272.3 kg/ha for yield loss simulations. Soil properties were identified as the primary factors influencing yield losses under waterlogging, highlighting the importance of optimizing soil conditions to mitigate the adverse impacts of excessive water. Across different scenarios, the improved crop model ensembles projected greater crop yield losses compared to the original simulated outputs, with additional losses (compared to the historical period) around 5.9%–7.3% during the two periods. Although global climate models were the primary source of uncertainty in T1 (2029–2059), crop models contributed more to uncertainty in T2 (2069–2099). The improved ensemble reduced uncertainty from crop models compared to the original. This study highlights the potential of KGML to improve crop models, offering valuable insights for climate impact assessments and resource management. We believe our results can help national and local authorities make informed crop yield decisions under climate change.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"19 ","pages":"Article 100185"},"PeriodicalIF":12.4,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168540","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 : 2024-12-10DOI: 10.1016/j.resenv.2024.100186
Ganesh Pandey , Sarah Lyden , Evan Franklin , Matthew Tom Harrison
Agrivoltaic systems (AVS) – wherein solar photovoltaics (PV) and agriculture are co-located on the same land parcel – offer a sustainable approach to achieving the Sustainable Development Goals (SDGs) by enabling concurrent renewable electricity and agri-food production. Here, we elucidate plausible co-benefits and trade-offs of agri-food production and electricity generation in AVS across manifold socio-enviro-economic contexts, with the aim of understanding the contextualized interplay between AVS implementation and progress towards the SDGs. We modeled three AVS designs with varying solar panel densities (high, mid, low) at case study locations in Australia, Chad, and Iran using various models (System Advisor Model for PV and GrassGro for livestock systems). The findings suggest that in regions conducive to high biomass production per unit area, such as in parts of Australia, AVS design with high solar panel density can reduce meat production by almost 50%, which can jeopardize food security and impede achieving SDG 2 (Zero Hunger). In these regions, AVS design with low solar panel density enables meeting SDGs aligned with agri-food production and renewable energy generation. In contrast, in semi-arid regions, such as Iran, AVS design with a high density of solar panels can improve agricultural production via the alleviation of water deficit, thereby supporting the prioritization of solar power generation, with food production as a co-benefit. In developing countries such as Chad, AVS can enhance economic development by providing electricity, food, and financial benefits. We call for policymakers to incentivize AVS deployment in such regions and stimulate public and private investment to enable progress towards SDGs.
{"title":"Agrivoltaics as an SDG enabler: Trade-offs and co-benefits for food security, energy generation and emissions mitigation","authors":"Ganesh Pandey , Sarah Lyden , Evan Franklin , Matthew Tom Harrison","doi":"10.1016/j.resenv.2024.100186","DOIUrl":"10.1016/j.resenv.2024.100186","url":null,"abstract":"<div><div>Agrivoltaic systems (AVS) – wherein solar photovoltaics (PV) and agriculture are co-located on the same land parcel – offer a sustainable approach to achieving the Sustainable Development Goals (SDGs) by enabling concurrent renewable electricity and agri-food production. Here, we elucidate plausible co-benefits and trade-offs of agri-food production and electricity generation in AVS across manifold socio-enviro-economic contexts, with the aim of understanding the contextualized interplay between AVS implementation and progress towards the SDGs. We modeled three AVS designs with varying solar panel densities (high, mid, low) at case study locations in Australia, Chad, and Iran using various models (System Advisor Model for PV and GrassGro for livestock systems). The findings suggest that in regions conducive to high biomass production per unit area, such as in parts of Australia, AVS design with high solar panel density can reduce meat production by almost 50%, which can jeopardize food security and impede achieving SDG 2 (Zero Hunger). In these regions, AVS design with low solar panel density enables meeting SDGs aligned with agri-food production and renewable energy generation. In contrast, in semi-arid regions, such as Iran, AVS design with a high density of solar panels can improve agricultural production via the alleviation of water deficit, thereby supporting the prioritization of solar power generation, with food production as a co-benefit. In developing countries such as Chad, AVS can enhance economic development by providing electricity, food, and financial benefits. We call for policymakers to incentivize AVS deployment in such regions and stimulate public and private investment to enable progress towards SDGs.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"19 ","pages":"Article 100186"},"PeriodicalIF":12.4,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168539","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 : 2024-12-09DOI: 10.1016/j.resenv.2024.100183
Guofei Liu , Ye Li , Jie Hou , Yajun Wang , Dasong Lin
Human activities have discharged large quantities of pollutants into the water body. Industrial wastes have demonstrated potential for water remediation, and further modifications can enhance their sorption capacities for pollutants. Over the past few decades, various modification techniques have been conducted to improve the sorption performance of industrial wastes and achieved encouraging results. However, the limited availability of relevant summaries hinders our ability to gain a deeper and more detailed understanding of the advantages of modification methods, restricting the advancement of industrial wastes modification. Therefore, an extensive list of various modification techniques for industrial waste materials were compiled and their adsorption capacities under optimal conditions for the removal of pollutants were presented in this review. Modification categories and their effects on the adsorption mechanism were introduced in detail along with discussing the key advancement on the preparation of adsorbents. Furthermore, knowledge gaps, uncertainties, and future challenges involved in the fabrication of modified industrial wastes based adsorbents are also identified. This review provides an important insight on using industrial waste materials for preparing adsorbents in water remediation, which will give quite valuable information for developing industrial waste based adsorbents.
{"title":"A review on the industrial waste based adsorbents for the removal of pollutants from water: Modification methods and adsorption study","authors":"Guofei Liu , Ye Li , Jie Hou , Yajun Wang , Dasong Lin","doi":"10.1016/j.resenv.2024.100183","DOIUrl":"10.1016/j.resenv.2024.100183","url":null,"abstract":"<div><div>Human activities have discharged large quantities of pollutants into the water body. Industrial wastes have demonstrated potential for water remediation, and further modifications can enhance their sorption capacities for pollutants. Over the past few decades, various modification techniques have been conducted to improve the sorption performance of industrial wastes and achieved encouraging results. However, the limited availability of relevant summaries hinders our ability to gain a deeper and more detailed understanding of the advantages of modification methods, restricting the advancement of industrial wastes modification. Therefore, an extensive list of various modification techniques for industrial waste materials were compiled and their adsorption capacities under optimal conditions for the removal of pollutants were presented in this review. Modification categories and their effects on the adsorption mechanism were introduced in detail along with discussing the key advancement on the preparation of adsorbents. Furthermore, knowledge gaps, uncertainties, and future challenges involved in the fabrication of modified industrial wastes based adsorbents are also identified. This review provides an important insight on using industrial waste materials for preparing adsorbents in water remediation, which will give quite valuable information for developing industrial waste based adsorbents.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"19 ","pages":"Article 100183"},"PeriodicalIF":12.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167193","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 : 2024-12-01DOI: 10.1016/j.resenv.2024.100181
Huijun Wu , Yongxin Liu , Ling Zhang , Huimin Zhu , Weixin Fang , Wei Mei
Through the whole process of large-scale pig production, feed production puts great environmental pressure in terms of greenhouse gas (GHG) emissions and nitrogen (N) emission. Additionally, different feedstuffs will have different results. While previous studies seldom analyzed carbon footprint and nitrogen footprint from feed components or diet choices. Thus, we selected China, the largest producer and consumer of pork in the world, to analyze both nitrogen footprint and carbon footprint through the life cycle of pig production with different feed components. We used life-cycle environmental footprint and scenario analysis to compare carbon footprints, nitrogen footprints, and feed prices of large-scale pig production with different feedstuffs in China. The life cycle of the pig production includes feed crop cultivation, feed processing, pig raising, and manure management. The functional unit is the weight of 1 kg of live pig. The results showed that the carbon footprints, nitrogen footprints, and feed prices ranged from 1.67 kg CO2-eq FU−1 to 1.70 kg CO2-eq FU−1, 35.3 g Nr FU−1 to 38.9 g Nr FU−1, and 1.42 CNY kg −1 to 2.15 CNY kg −1, respectively. Feed crop production and manure management contributed the largest carbon footprint (54%) and the largest nitrogen footprint (64%), respectively. The four scenarios exhibited various results. Scenario 3 (S3), substituting soybean meal in the original feed with distillers dried grains with soluble (DDGS), presented a more favorable outcome with respect to carbon and nitrogen footprints as well as feed prices. This was mainly attributed to feed crop cultivation, manure management, crude protein contents of feeds, and prices of the feed crops. Concerning the uneven feed crop production, number of pig farrowed, feed consumption, and inter-provincial transportation across China, we conducted the spatial analysis under the optimal S3. It revealed that the northern provinces in China exhibited both higher carbon and nitrogen footprints than the southern provinces, due to the northern regions cultivating the crop feed. Finally, we proposed recommendations from perspectives of cultivation practice, feed adjustment, manure management, and strategic zoning. The study not only highlighted the importance of environmental footprint for analyzing environmental impacts of pig production, but also provided the implications for enhancing the sector’s environmental sustainability from perspective of feed adjustment.
{"title":"Insights into carbon and nitrogen footprints of large-scale intensive pig production with different feedstuffs in China","authors":"Huijun Wu , Yongxin Liu , Ling Zhang , Huimin Zhu , Weixin Fang , Wei Mei","doi":"10.1016/j.resenv.2024.100181","DOIUrl":"10.1016/j.resenv.2024.100181","url":null,"abstract":"<div><div>Through the whole process of large-scale pig production, feed production puts great environmental pressure in terms of greenhouse gas (GHG) emissions and nitrogen (N) emission. Additionally, different feedstuffs will have different results. While previous studies seldom analyzed carbon footprint and nitrogen footprint from feed components or diet choices. Thus, we selected China, the largest producer and consumer of pork in the world, to analyze both nitrogen footprint and carbon footprint through the life cycle of pig production with different feed components. We used life-cycle environmental footprint and scenario analysis to compare carbon footprints, nitrogen footprints, and feed prices of large-scale pig production with different feedstuffs in China. The life cycle of the pig production includes feed crop cultivation, feed processing, pig raising, and manure management. The functional unit is the weight of 1 kg of live pig. The results showed that the carbon footprints, nitrogen footprints, and feed prices ranged from 1.67 kg CO<sub>2</sub>-eq FU<sup>−1</sup> to 1.70 kg CO<sub>2</sub>-eq FU<sup>−1</sup>, 35.3 g Nr FU<sup>−1</sup> to 38.9 g Nr FU<sup>−1</sup>, and 1.42 CNY kg <sup>−1</sup> to 2.15 CNY kg <sup>−1</sup>, respectively. Feed crop production and manure management contributed the largest carbon footprint (54%) and the largest nitrogen footprint (64%), respectively. The four scenarios exhibited various results. Scenario 3 (S3), substituting soybean meal in the original feed with distillers dried grains with soluble (DDGS), presented a more favorable outcome with respect to carbon and nitrogen footprints as well as feed prices. This was mainly attributed to feed crop cultivation, manure management, crude protein contents of feeds, and prices of the feed crops. Concerning the uneven feed crop production, number of pig farrowed, feed consumption, and inter-provincial transportation across China, we conducted the spatial analysis under the optimal S3. It revealed that the northern provinces in China exhibited both higher carbon and nitrogen footprints than the southern provinces, due to the northern regions cultivating the crop feed. Finally, we proposed recommendations from perspectives of cultivation practice, feed adjustment, manure management, and strategic zoning. The study not only highlighted the importance of environmental footprint for analyzing environmental impacts of pig production, but also provided the implications for enhancing the sector’s environmental sustainability from perspective of feed adjustment.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"18 ","pages":"Article 100181"},"PeriodicalIF":12.4,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093317","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 : 2024-11-20DOI: 10.1016/j.resenv.2024.100182
Zheng Fang , Guangqi Xiong , Zongxuan Shao , Shuai Zhou , Guangfeng Ou , Lei Liu , Michio Suzuki , Chong Wang , Yuya Sakai
Rapid urbanization produces billions of tons of concrete waste annually, with recycled concrete powder (RCP) posing significant challenges due to its high porosity and limited reusability. To overcome RCP’s inherent limitations and maximize resource utilization, we developed a novel “Recycled Concrete Powder Electrolyzer” for selective recovery of key components. This electrochemical method efficiently extracted Ca2＋ ions from RCP, achieving a 96% calcium extraction efficiency comparable to acid leaching. The process produced high-purity portlandite (94% purity; 65.58% yield) with crystal sizes below , ideal for cement manufacturing, while also recovering fine sand powder and silica-containing products. A Ca(NO3)2 electrolyte enhanced Ca2＋ migration and prevented membrane fouling, resulting in lower energy consumption compared to the NaNO3 system. By converting RCP into a carbon-free cement precursor and recovering valuable components, this approach demonstrates the feasibility of transforming problematic waste into sustainable construction materials. It offers a circular economy solution for concrete waste recycling, reducing landfill burden while providing a low-emission alternative for cement production.
{"title":"Electrochemical recycling of recycled concrete powder: Selective recovery of calcium and silica to enable sustainable construction materials","authors":"Zheng Fang , Guangqi Xiong , Zongxuan Shao , Shuai Zhou , Guangfeng Ou , Lei Liu , Michio Suzuki , Chong Wang , Yuya Sakai","doi":"10.1016/j.resenv.2024.100182","DOIUrl":"10.1016/j.resenv.2024.100182","url":null,"abstract":"<div><div>Rapid urbanization produces billions of tons of concrete waste annually, with recycled concrete powder (RCP) posing significant challenges due to its high porosity and limited reusability. To overcome RCP’s inherent limitations and maximize resource utilization, we developed a novel “Recycled Concrete Powder Electrolyzer” for selective recovery of key components. This electrochemical method efficiently extracted Ca<sup>2＋</sup> ions from RCP, achieving a 96% calcium extraction efficiency comparable to acid leaching. The process produced high-purity portlandite (94% purity; 65.58% yield) with crystal sizes below <span><math><mrow><mn>30</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span>, ideal for cement manufacturing, while also recovering fine sand powder and silica-containing products. A Ca(NO<sub>3</sub>)<sub>2</sub> electrolyte enhanced Ca<sup>2＋</sup> migration and prevented membrane fouling, resulting in lower energy consumption compared to the NaNO<sub>3</sub> system. By converting RCP into a carbon-free cement precursor and recovering valuable components, this approach demonstrates the feasibility of transforming problematic waste into sustainable construction materials. It offers a circular economy solution for concrete waste recycling, reducing landfill burden while providing a low-emission alternative for cement production.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"18 ","pages":"Article 100182"},"PeriodicalIF":12.4,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142722473","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 : 2024-11-15DOI: 10.1016/j.resenv.2024.100179
Sara Giarola , Iván García Kerdan , Peter Johnston , Nick Macaluso , Baltazar Solano Rodriguez , Ilkka Keppo , Adam Hawkes , David Daniels
The implementation of asymmetric emission reduction policies can not only increase the cost of reducing emissions but also reduce the effectiveness of climate policies themselves, leading to policy inefficiencies such as carbon leakage. This paper investigates the impact of asymmetric emission reduction policies on the cost-effectiveness and efficiency of climate strategies in North America. Using a model inter-comparison approach, which combines two bottom-up global models and one top-down global model, this study assesses the effects of such policies on fuel substitution, global fossil fuel trade, and emissions in North America and globally. It is the first work where a multi-model approach is used for exploring how different energy systems react to asymmetric carbon policies. This provides critical insights into regional policy design within a global emissions framework. Quantitatively, the study reveals that asymmetric carbon pricing can lead to more than 60% global emissions reduction in certain models, but can also drive trade distortions, where U.S. exemptions result in emissions rising by more than 10% compared to reference scenarios. Qualitatively, significant fuel substitution patterns across Canada, Mexico, and the U.S. demonstrate increased coal consumption when carbon prices are unevenly applied. While no global emission increase was observed, asymmetric policies result in inefficiencies between local policy costs and emissions reduction outcomes, such as rising fossil fuel trade in non-abating regions. The findings suggest that harmonising carbon policies across regions would reduce inefficiencies and minimise carbon leakage.
{"title":"Effects of asymmetric policies to achieve emissions reduction on energy trade: A North American perspective","authors":"Sara Giarola , Iván García Kerdan , Peter Johnston , Nick Macaluso , Baltazar Solano Rodriguez , Ilkka Keppo , Adam Hawkes , David Daniels","doi":"10.1016/j.resenv.2024.100179","DOIUrl":"10.1016/j.resenv.2024.100179","url":null,"abstract":"<div><div>The implementation of asymmetric emission reduction policies can not only increase the cost of reducing emissions but also reduce the effectiveness of climate policies themselves, leading to policy inefficiencies such as carbon leakage. This paper investigates the impact of asymmetric emission reduction policies on the cost-effectiveness and efficiency of climate strategies in North America. Using a model inter-comparison approach, which combines two bottom-up global models and one top-down global model, this study assesses the effects of such policies on fuel substitution, global fossil fuel trade, and emissions in North America and globally. It is the first work where a multi-model approach is used for exploring how different energy systems react to asymmetric carbon policies. This provides critical insights into regional policy design within a global emissions framework. Quantitatively, the study reveals that asymmetric carbon pricing can lead to more than 60% global emissions reduction in certain models, but can also drive trade distortions, where U.S. exemptions result in emissions rising by more than 10% compared to reference scenarios. Qualitatively, significant fuel substitution patterns across Canada, Mexico, and the U.S. demonstrate increased coal consumption when carbon prices are unevenly applied. While no global emission increase was observed, asymmetric policies result in inefficiencies between local policy costs and emissions reduction outcomes, such as rising fossil fuel trade in non-abating regions. The findings suggest that harmonising carbon policies across regions would reduce inefficiencies and minimise carbon leakage.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"18 ","pages":"Article 100179"},"PeriodicalIF":12.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142698525","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 : 2024-11-14DOI: 10.1016/j.resenv.2024.100180
Jiawei Quan , Yumei Wang , Yu Wang , Chunxing Li , Zengwei Yuan
The increasing generation of food waste (FW) poses a significant challenge to global food security and environmental sustainability. Composting is an effective way to recycle FW, while the disease risk of immature compost and the long durations needed for mature compost restrict the application. To address these concerns, black soldier fly larvae (BSFL) were applied in the maturation phase to improve composting efficiency. The results demonstrated that adding BSFL expedited the composting process, achieving the fully mature compost within 25 days. This was evidenced by the elevated nitrate content (1057.52–1475.58 mg/kg) and germination index (GI) (100.2%–107.03%), along with a decreased nitrification index (0.19–0.24) of the BSFL-treated composts. Microbial analysis revealed a discernible elevation in the relative abundance of Ureibacillus, Lysinibacillus, Paneibacills, and Brevibacillus within the compost attributed to the addition of BSFL. Furthermore, BSFL introduction might enhance metabolic functions such as glycolysis, inosine monophosphate biosynthesis, gluconeogenesis, and lysine biosynthesis. As composting progressed, the relative abundance of certain bacteria, like Moheibacter and Actinomadura (initially more prevalent in the compost pile), gradually increased in the gut of BSFL. These findings suggest the existence of complex microbial interactions between the BSFL gut and compost, reshaping the mutual bacterial community and exerting some influence on the compost’s metabolic functions. Furthermore, redundancy analysis indicated significant associations between compost’s physiochemical properties (i.e., electrical conductivity, moisture content, GI, pH, and NH-N) and microbial community across all experimental groups. The discoveries provide valuable insights for the further evolution and functional research of BSFL gut microbiota.
{"title":"An efficient strategy to promote food waste composting by adding black soldier fly (Hermetia illucens) larvae during the compost maturation phase","authors":"Jiawei Quan , Yumei Wang , Yu Wang , Chunxing Li , Zengwei Yuan","doi":"10.1016/j.resenv.2024.100180","DOIUrl":"10.1016/j.resenv.2024.100180","url":null,"abstract":"<div><div>The increasing generation of food waste (FW) poses a significant challenge to global food security and environmental sustainability. Composting is an effective way to recycle FW, while the disease risk of immature compost and the long durations needed for mature compost restrict the application. To address these concerns, black soldier fly larvae (BSFL) were applied in the maturation phase to improve composting efficiency. The results demonstrated that adding BSFL expedited the composting process, achieving the fully mature compost within 25 days. This was evidenced by the elevated nitrate content (1057.52–1475.58 mg/kg) and germination index (GI) (100.2%–107.03%), along with a decreased nitrification index (0.19–0.24) of the BSFL-treated composts. Microbial analysis revealed a discernible elevation in the relative abundance of <em>Ureibacillus</em>, <em>Lysinibacillus</em>, <em>Paneibacills</em>, and <em>Brevibacillus</em> within the compost attributed to the addition of BSFL. Furthermore, BSFL introduction might enhance metabolic functions such as glycolysis, inosine monophosphate biosynthesis, gluconeogenesis, and lysine biosynthesis. As composting progressed, the relative abundance of certain bacteria, like <em>Moheibacter</em> and <em>Actinomadura</em> (initially more prevalent in the compost pile), gradually increased in the gut of BSFL. These findings suggest the existence of complex microbial interactions between the BSFL gut and compost, reshaping the mutual bacterial community and exerting some influence on the compost’s metabolic functions. Furthermore, redundancy analysis indicated significant associations between compost’s physiochemical properties (i.e., electrical conductivity, moisture content, GI, pH, and NH<span><math><msubsup><mrow></mrow><mrow><mn>4</mn></mrow><mrow><mo>+</mo></mrow></msubsup></math></span>-N) and microbial community across all experimental groups. The discoveries provide valuable insights for the further evolution and functional research of BSFL gut microbiota.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"18 ","pages":"Article 100180"},"PeriodicalIF":12.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142698523","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 : 2024-11-04DOI: 10.1016/j.resenv.2024.100178
Ran Xing , Yaojie Li , Zhihan Luo , Rui Xiong , Jiaqi Liu , Ke Jiang , Yatai Men , Huizhong Shen , Guofeng Shen , Shu Tao
The inefficient combustion of traditional biomass fuels in the Tibetan Plateau, the world’s highest region, impacts both local ecosystems and global climate change despite the substantial renewable energy potential and ongoing economic growth of the area. However, the utilization of clean household energy sources and the enablers supporting their sustained use in this region remain underexplored. Through the regional household survey and fuel-weighing campaign, we observed that clean modern energy sources, such as gas and electricity, were used for over 85% of the year in urban areas but only 25% in rural areas. Approximately 3.98 million residents still predominantly rely on traditional solid fuels for daily cooking and/or heating. A substantial energy inequality was identified, with Gini coefficients of 0.65 and 0.55 for cooking and heating, respectively. Despite the disparity in clean energy adoption across income groups being relatively small, the regional utilization of clean energy is severely constrained by limited accessibility and affordability. This has minimized the impact of household characteristics, such as gender, age, and education level, and diminished the effect of rising incomes on accelerating clean cooking practices. The findings highlight the urgent need for targeted residential energy interventions and incentives to promote a clean energy transition in the Tibetan Plateau, as achieving universal clean energy access by 2030 is unlikely without significant efforts.
{"title":"Household energy use and barriers in clean transition in the Tibetan Plateau","authors":"Ran Xing , Yaojie Li , Zhihan Luo , Rui Xiong , Jiaqi Liu , Ke Jiang , Yatai Men , Huizhong Shen , Guofeng Shen , Shu Tao","doi":"10.1016/j.resenv.2024.100178","DOIUrl":"10.1016/j.resenv.2024.100178","url":null,"abstract":"<div><div>The inefficient combustion of traditional biomass fuels in the Tibetan Plateau, the world’s highest region, impacts both local ecosystems and global climate change despite the substantial renewable energy potential and ongoing economic growth of the area. However, the utilization of clean household energy sources and the enablers supporting their sustained use in this region remain underexplored. Through the regional household survey and fuel-weighing campaign, we observed that clean modern energy sources, such as gas and electricity, were used for over 85% of the year in urban areas but only 25% in rural areas. Approximately 3.98 million residents still predominantly rely on traditional solid fuels for daily cooking and/or heating. A substantial energy inequality was identified, with Gini coefficients of 0.65 and 0.55 for cooking and heating, respectively. Despite the disparity in clean energy adoption across income groups being relatively small, the regional utilization of clean energy is severely constrained by limited accessibility and affordability. This has minimized the impact of household characteristics, such as gender, age, and education level, and diminished the effect of rising incomes on accelerating clean cooking practices. The findings highlight the urgent need for targeted residential energy interventions and incentives to promote a clean energy transition in the Tibetan Plateau, as achieving universal clean energy access by 2030 is unlikely without significant efforts.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"18 ","pages":"Article 100178"},"PeriodicalIF":12.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659853","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 : 2024-11-03DOI: 10.1016/j.resenv.2024.100177
Songliang Chen , Qinglin Mao , Youcan Feng , Hongyan Li , Donghe Ma , Yilian Zhao , Junhui Liu , Hui Cheng
Accurate hydrological predictions are often hindered by the lack of stream gauges in data-scarce regions, where traditional transfer learning (TL) models like Long Short-Term Memory (LSTM) networks often face limitations due to reduced accuracy and adaptability. To enhance runoff prediction in such regions, we developed DAformer, a novel TL approach that integrates domain adversarial neural networks with the Informer model. Trained on comprehensive runoff data from U.S. basins, DAformer was applied to three basins in Chile and the Chaersen basin in China, demonstrating an effective transfer from data-rich to data-scarce environments. Results show that DAformer significantly outperforms LSTM-based models, improving forecast accuracy by 16.1% for 1-day lead time and by 100.5% for 5-day lead time. These improvements indicate that the DAformer model not only enhances prediction accuracy but also holds substantial practical implications for flood risk management and water resource planning in regions with limited data availability. By clustering basins based on Shuttle Radar Topography Mission (SRTM) and other geographical data, we found that relying on multiple source basins further enhances the performance. DAformer, therefore, serves as a robust and scalable method for enhancing runoff prediction for regions with limited data.
{"title":"Enhancing the performance of runoff prediction in data-scarce hydrological domains using advanced transfer learning","authors":"Songliang Chen , Qinglin Mao , Youcan Feng , Hongyan Li , Donghe Ma , Yilian Zhao , Junhui Liu , Hui Cheng","doi":"10.1016/j.resenv.2024.100177","DOIUrl":"10.1016/j.resenv.2024.100177","url":null,"abstract":"<div><div>Accurate hydrological predictions are often hindered by the lack of stream gauges in data-scarce regions, where traditional transfer learning (TL) models like Long Short-Term Memory (LSTM) networks often face limitations due to reduced accuracy and adaptability. To enhance runoff prediction in such regions, we developed DAformer, a novel TL approach that integrates domain adversarial neural networks with the Informer model. Trained on comprehensive runoff data from U.S. basins, DAformer was applied to three basins in Chile and the Chaersen basin in China, demonstrating an effective transfer from data-rich to data-scarce environments. Results show that DAformer significantly outperforms LSTM-based models, improving forecast accuracy by 16.1% for 1-day lead time and by 100.5% for 5-day lead time. These improvements indicate that the DAformer model not only enhances prediction accuracy but also holds substantial practical implications for flood risk management and water resource planning in regions with limited data availability. By clustering basins based on Shuttle Radar Topography Mission (SRTM) and other geographical data, we found that relying on multiple source basins further enhances the performance. DAformer, therefore, serves as a robust and scalable method for enhancing runoff prediction for regions with limited data.</div></div>","PeriodicalId":34479,"journal":{"name":"Resources Environment and Sustainability","volume":"18 ","pages":"Article 100177"},"PeriodicalIF":12.4,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659852","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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