Cleaner Environmental Systems最新文献

This study compared the technical-economic and life cycle environmental (LCA) performance of a bulk carrier, powered by different biofuels that could potentially be produced in Brazil, with a ship powered by low-sulfur fuel oil (LSFO). Six biofuel pathways and two power systems (two-stroke diesel engine and solid oxide fuel cell) were evaluated. The technical-economic assessment estimated the minimum fuel selling price (MFSP), and the impacts on the levelized cost of shipping (LCOS). All biofuels showed reductions ranging from 63.12% to 89.98% in GHG emissions per t.km compared to LSFO. Biofuels also performed better in terms of fine particulate matter formation and fossil resource scarcity, while results for the other environmental categories varied according to the production pathway. From an economic perspective, all biofuels showed higher MFSP (2.46–3.75 times) and LCOS (1.58–3.08 times) compared to LSFO. The results showed the potential of biofuels to reduce the carbon footprint and the economic challenges to overcome. In this sense, governmental programs and incentives can allow marine biofuels bridge the competitivity gap with fossil fuels. In the short-term, the adoption of different strategies, such as offsetting schemes, may be necessary for the international shipping decarbonization.

This study conducts a Social Life Cycle Assessment (S-LCA) of Rainwater Harvesting Systems (RWHS) in Mexico City to evaluate their social performance. Given the city's pressing water scarcity, RWHS have become critical for promoting water autonomy and sustainable urban development. The research integrates quantitative data from surveys and interviews with RWHS users and organizational employees, along with qualitative analysis using the Product Social Impact Assessment (PSIA) approach. This methodology allows for a thorough examination of socio-environmental dynamics influenced by RWHS adoption. Our findings show high acceptance of RWHS among users and highlight progressive labor practices, underscoring RWHS's potential to transform urban water management. This study, the first to evaluate this ecotechnology through an S-LCA, identifies the need for a multidimensional approach to understand socio-economic and environmental intersections with water systems. It also underscores NGOs' role in facilitating technology transfer and adoption in urban communities. Recommendations include extending the S-LCA methodology to cover the entire RWHS lifecycle and incorporating broader social science theories to deepen understanding of water sustainability interventions. The results offer new insights into RWHS assessment, emphasizing the complexities of deploying decentralized water technologies in a mega-city and laying groundwork for policy recommendations that support sustainable, equitable water access.

Production companies’ ambition to reach sustainable development goals, has resulted in a rapid strategic movement towards circularity in production. Previous studies have indicated that a transition to circular production is affirmed and a prioritised action. However, few studies describe how to operate a circular production, and how to perform the transition from linear to circular. To fill this gap, this paper aims to explore strategies for a seamless transition and to add new knowledge in this area. A multiple case study was employed for this purpose, based on production companies located in Sweden. Collected data were analysed by an inductive coding process. The coding process generated managerial themes that characterise the transition process in production operations. From the themes, three main incubators: management systems, standards and strategy, form together with drivers and blockers a framework called Integrated Circularity Management Systems (ICMS). The research presented in this study adds new knowledge to the field of circular production operations management as well as gives practical guidance for decision-makers in the manufacturing industry on how to initiate a circularity transition in an established production system.

The present study conducts a Life Cycle Assessment (LCA) to evaluate the environmental impacts of heating technologies commonly used in Chile based on six environmental indicators: Climate Change (CC), Human Toxicity (HT), Formation of Particulate Matter (PM), Formation of Photochemical Oxidants (PO), Ozone Destruction (OD), and Water Depletion (WD). Due to the extensive length of the territory studied, it is demonstrated that the environmental impacts depend on the geographical location where the heating equipment is used. Stoves that use wet firewood presented the highest environmental impact in CC, PM, HT, and PO. Using dry firewood could reduce pollution by 14%–81%, compared to wet firewood. Replacing wood heating with natural gas, LPG, and kerosene stoves reduces the CC and HT indicators. On the other hand, switching to electric heating, such as split inverter heat pumps, could transfer these impacts to areas where electricity is generated using coal. When the pellet is a byproduct of the forestry industry and transportation distances are not very high, the pellet stove stands out for its lower CC. In Magallanes, electric heating appears environmentally attractive due to using natural gas for electricity generation.

By 2050, 68% of the global population will reside in cities, driving rapid urban growth and intensifying demand for scarce ecological resources within the Water-Food-Energy nexus. Social metabolism quantifies energy and material transformations with a social focus, building upon urban metabolism. Its application in resource-scarce informal settlements (ISs) has the potential to enhance their sustainability significantly. As community dynamics evolve, acknowledging society as a dynamic variable within this framework becomes increasingly relevant. Our study employs the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) framework, focusing on key variables: human activity, land use, money, energy, water, waste, and food. Based on surveys, interviews, GIS datasets, and statistical information, the study investigates the Ciudad de Gosen IS in Lima, Peru. The results show that, in the socio-economic dimension, 43% of the time employed is directed to the unpaid work sector. Notably, 71% of women and 29% of men spend a mean of 44 h/week/person caring for children or elderly. In the paid work sector, there are gender asymmetries; men have a salary 54% higher than women. In the ecological dimension, more than 78% of the homes have access to basic services, unlike other informal settlements in Latin America and Africa.

Thermochemical conversion technologies are emerging as preferred resource recovery practices for managing animal manure in agricultural regions. Although the implementation of such technologies has been previously studied, difficulties exist in maintaining balance between high rate of resource recovery and low environmental, economic, and social impacts, particularly in rural regions with limited resources. We developed a data-driven framework by integrating machine learning with life cycle thinking that can be used as an open-source tool to help overcome these barriers. The framework was applied to compare two emerging technologies: pyrolysis versus hydrothermal carbonization for managing the excess poultry litter in a rural agricultural region. Among different machine learning models, random forest regression was the most successful to predict resource recovery of both technologies. Next, sustainability analysis indicated that the environmental (global warming), economic (annual worth), and social (system intrusiveness) impacts of pyrolysis was lower than hydrothermal carbonization. Finally, the framework revealed that implementation of pyrolysis at 600 °C for 1 h with the heating rate of 20 °C/min would result in the highest rate of resource recovery that corresponded to the lowest impacts. These results can be helpful in providing operational conditions for implementing emerging resource recovery technologies in rural agricultural regions.

On the way to climate neutrality manufacturing companies need to assess the Carbon dioxide (CO₂) emissions of their products as a basis for emission reduction measures. The evaluate this so-called Product Carbon Footprint (PCF) life cycle analysis as a comprehensive method is applicable, but means great effort and requires interdisciplinary knowledge. Nevertheless, assumptions must still be made to assess the entire supply chain. To lower these burdens and provide a digital tool to estimate the PCF with less input parameter and data, we make use of machine learning techniques and develop an editorial framework called MINDFUL. This contribution shows its realization by providing the software architecture, underlying CO₂ factors, calculations and Machine Learning approach as well as the principles of its user experience. Our tool is validated within an industrial case study.

Adopting a circular economy (CE) in the built environment contributes to lower the consumption of natural resources, limiting waste generation, and reducing greenhouse gas emissions. Effective data management is critical during the implementation of circular strategies; however, the academic literature does not explicitly address the subject, and a shared approach to data governance is still lacking. This study contributes to filling this gap by providing a holistic perspective to the state-of-the-art literature to identify the role of data in the implementation of CE strategies. The findings were obtained through the review of 40 articles. It was found that the literature can be classified into four interrelated thematic groups: the need for information and data, information and data management, the digitalisation of data and information, and digital tools and technologies. The study identifies the highlights for each thematic group and suggests opportunities to improve circularity through the effective use of data. It is important to recognize that accessible, open, and standardised information about construction products can accelerate the implementation of circular strategies in a project, but it is critical to ensure effective data management and interoperability throughout the asset life cycle. Therefore, data management tools and data templates need to be further investigated and adopted in the industry. Digital technologies can support data management and interoperability and, consequently, increase the possibility of successful CE implementation. Finally, future research should investigate a strategic approach to data exploitation that can enhance circularity in the built environment.

In the context of rapid global population growth and climate change, balancing agricultural productivity with environmental sustainability has never been more important. Precision farming technologies, including robotics, are touted as having huge potential to increase farm productivity, reduce energy and resource use and compact soil, while reducing the overall environmental impact of on-farm production. This comprehensive study presents, for the first time, a detailed analysis and environmental benchmarking of two organic sugar beet production (SBP) systems, conventional (CONV) and robotic (RBT), based on field experiments in Lithuanian conditions where a solar-powered robot is integrated into the production system to carry out sowing and weeding operations. In order to reduce the potential environmental impact and to understand the consequences of using the robot in agriculture, a Life Cycle Assessment (LCA) of the entire SBP process up to the factory gate was carried out. The results of the analysis show that the conventional system has higher total GHG emissions than the robotic system, 36.98 and 27.18 kg CO_2eq t⁻¹, respectively, with poultry manure being the largest contributor. The higher beet yield in the RBT system, mainly due to effective weed control, resulted in a higher GHG emissions ratio (14.72) and a higher sustainability index (13.72). The LCA results showed that the CONV system had a higher negative environmental impact than the RBT in all eleven environmental impact categories assessed, with the most pronounced difference in the Ozone Depletion (OD) category. Diesel fuel was identified as the most important environmental factor for organically growing sugar beet in all considered impact categories, with the most notable environmental impact (about 94%) in the terrestrial ecotoxicity category in both systems. Normalization of the results showed that marine aquatic ecotoxicity (ME) had the greatest (78%) influence of all exposure categories for both cultivation systems, CONV – 22079.82, and RBT 18121.61 kg 1.4-DB_eq per ton of produced sugar beet. The study found that increasing yields and reducing fossil fuel use in organic farming are the two most promising strategies for achieving sustainability and efficiency in food production.