Journal of Industrial Ecology最新文献

The construction industry has been criticized for its negative environmental impacts, leading industry experts to advocate for a shift toward a circular economy (CE) model. However, there is a lack of research on stakeholder opinions regarding that. This research paper examines stakeholders’ perspectives on implementing CE principles in the construction industry by conducting artificial intelligence-powered natural language processing (NLP) through online sources. It answers three questions: What themes and concepts are associated with the CE in construction? How do opinions on the CE vary across different online platforms? And what factors shape positive attitudes toward the CE? The data obtained from various platforms showed that 57% of sentiments were positive, 28% were neutral, and 15% were negative. This research provides critical knowledge on the analysis of CE representation on social media in construction. Moreover, a webpage tool has been created that can assess any input opinion on the scale (positive, neutral, or negative) for further use (https://ce-sentiment.streamlit.app/). This NLP-based research of social media discourse in the construction sector can directly influence policy decisions by offering real-time insights into public sentiment and preferences, shaping regulations that align with societal needs. It also provides industry professionals with data-driven guidance, enabling them to identify growth opportunities and innovation pathways within the CE, ultimately fostering a more sustainable and prosperous future.

Life cycle inventory (LCI) databases, such as ecoinvent, are crucial for life cycle assessment (LCA), but lack country-specific resolution in activity details and trade between regional activities in the supply chain. For example, ecoinvent only provides rest-of-world and European datasets for photovoltaic panel production, consuming the same global consumption mix of photovoltaic cells. Global or continental activities and trade limit the use of existing country activities, such as electricity production, and the accuracy and granularity of LCA results. We addressed this issue by disaggregating ecoinvent's global and continental unit processes to the country level and by regionalizing trade using country-sector-specific consumption mixes of product origins from the multiregional input–output table EXIOBASE. This produced a consistently regionalized ecoinvent at country level. Comparing the climate change impacts of 195,708 non-market datasets in our regionalized ecoinvent with reference datasets in ecoinvent reveals manufacturing sectors as the most affected. The study of photovoltaic panel production shows that the differences in climate change impacts are mainly due to the different country-specific suppliers of components and their electricity mixes, which are lost in the aggregated original data. The water consumption impacts of wheat production show the country differences only when regionalized CFs are applied, indicating that regionalized biosphere and technosphere flow amounts are needed for better results. The mapping quality between ecoinvent and EXIOBASE and inconsistent market definitions were discussed along with further limitations. Our study highlights the potential of incorporating better trade information and regional disaggregation in LCI databases to improve the LCA outcomes.

The Belt and Road Initiative (BRI) has induced immense material consumption and environmental threats while fostering economic development along participating countries. Quantifying recent trends of the material footprint of BRI economies and identifying potential drivers are vital to inform sustainable resource use. However, an assessment on the determinants of BRI material consumption from an economic system viewpoint is lacking in the literature. To fill this gap, this study proposes a multi-region structural decomposition analysis model to assess the drivers of material footprints in BRI economies. To scrutinize the effects of transitioning economic structures, the effects of domestic and cross-border production activities are separated. The latter is further characterized by production technology and sourcing structure. Using global multi-region input–output tables of 2005–2015, this study reveals that shifting international sourcing patterns boosted BRI material footprint, with rising intermediate goods and services sourced from BRI regions substituting those from North America and the European Union. Capital formation in the construction sector took the primary role in driving BRI material footprint growth, followed by manufacturing sectors, especially since 2013. Disparities in the key drivers of material footprints have been identified among developed, emerging, and least developed economies. The results have relevant policy implications regarding alleviating BRI material pressure, including fostering material-efficient demand patterns, facilitating environmental technology improvements in local countries, and establishing stringent governance on material usage.

Quantifying the environmental impacts of a household waste-sorting policy on the household waste management system, including collection, transportation, and treatment, is the basis for evaluating the policy's effectiveness. Beijing, the capital of China, began to implement the mandatory domestic waste-sorting policy in May 2020. In this study, we aimed to evaluate the environmental impacts of the household waste management system in Beijing before and after implementing the sorting policy using the life cycle assessment method. Implementing the policy at the waste collection stage reduced the environmental impacts by minimizing the number of garbage bins consumed through their removal and consolidation. At the transportation stage, implementing the policy increased the environmental impacts per unit of waste via transportation structure changes. However, the overall impact was reduced because more recyclable materials were separated after waste sorting. The environmental impacts were reduced after implementing the policy at the treatment stage mainly because of the change in waste composition and the decrease in the total volume of treatment. Global warming potential (GWP) was the main contributor to the environmental impacts. After waste sorting, the GWP of the collection, transportation, and treatment stages decreased by −19.96%, −24.36%, and −38.08%, respectively, resulting in a total GWP reduction of −37.90%. However, incineration and biochemical treatments may offer environmental benefits.

Sustainable products are at the core of the circular economy, which is gaining momentum in scientific, economic, and policy fields. However, existing research in the field of circular product design remains fragmented. The literature has generally tended to focus on material or resource efficiency, while other complex issues related to product ecosystem also exist, such as the needs of the ecosystem (non-human) and human user, circular challenge, and circular business model. By using a co-creation approach, this study aims to create and validate a circular product design framework (CD-Framework) and a self-assessment tool for circular product design (CD-Tool) that facilitates an understanding of how product circularity can be improved from the product ideation. The proposed CD-Framework consists of 10 interconnected categories: circular challenge; circular business model; production; digital fabrication technologies; materials; branding and communication for circularity; packaging, distribution and logistics; user; usage; and after usage. The CD-Tool was designed as a tool to aid product developers from various industry sectors in the self-assessment of the circularity of product design. We contribute to developing tools that accelerate integration of circularity into product design through product-level and ecosystem-level considerations.

The evolution of cities follows distinct patterns that connect to the cultural and socioeconomic aspects of their populations and can be understood by studying their urban stocks. This paper examines the evolution of construction materials stocks (MS) in the building sector in five urban areas in Peru. The study employed a bottom-up methodology and focused on the city of Abancay in the Peruvian Andes, comparing it to the coastal cities of Chiclayo, Tacna, and San Isidro, as well as Lince. Additionally, regression models were employed to examine the influence of socioeconomic factors associated with urban stock. The research highlights a transition from residential building stock to distinct patterns of socioeconomic development, with urban population and economic growth emerging as pivotal drivers of material stock variation. Notably, large coastal cities like Chiclayo, Tacna, San Isidro, and Lince exhibit significantly higher concrete MS per capita, albeit with varying growth rates. In contrast, Abancay, with lower income levels, displays a higher per capita level of adobe MS, reflecting its historical connection to Peru's heartland. The correlation of urban stock components with the human development index (HDI) emphasizes the latter's significance in understanding the trends of the stocks of the different construction materials that constitute a city. By examining MS in various locations, unique Peruvian traits are unveiled, offering insights for urban development in the Global South. These findings provide valuable guidance for aligning urban stock growth and related environmental burdens with socioeconomic development, fostering sustainability, and promoting rational planning for economic growth.

The input–output (IO) model can be used to examine the flow of products and services within an economy, resembling a network with industries as nodes and transactions as links. Diverging significantly from commonly studied networks such as social, protein, and power grids, IO networks exhibit intricate interconnectivity, involving weighted nodes and both directional and weighted links. This uniqueness necessitates careful consideration when applying complex network analysis techniques to IO systems. We critically review current complex network metrics and attempt to link them with existing IO approaches. Based on our assessment, certain network metrics, such as degree centrality and eigenvector centrality, have been explicitly integrated into the IO theory. In contrast, there exist metrics whose definitions and interpretations expand when applied in the context of IO analysis, including closeness and betweenness centrality. Additionally, network metrics are usually used to study topological features, identify key sectors, and construct novel metrics to study related issues. Network metrics used in IO analysis can identify important driver and transmission sectors in resource flow and environmental emission network, facilitating the development of targeted and reliable strategies. Besides, network metrics are used to quantify topological features and structural changes of the IO network which help strengthen the supply chain and mitigate both direct and indirect impacts of disruptions. Our ultimate goal is to establish connections and offer a roadmap for developing network-based tools in IO analysis.

Battery electric vehicles (BEVs) are widely considered a pathway to achieve low carbon mobility. BEVs emit zero emissions from the tailpipe, but their life cycle carbon reduction compared to gasoline vehicles varies based on primary energy sources, electricity generation, and use efficiency. The Middle East and North Africa (MENA) region is an area rich in fossil fuels, meriting a detailed comparison between the emissions from BEV and other powertrains. We developed a MENA-specific life cycle model that estimates well-to-wheel (WTW) greenhouse gas (GHG) emissions from passenger transport with internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles, and BEVs. MENA's average WTW GHG emissions for all supply chain steps including combustion emissions from vehicle operation are 767 g/kWh and 84 g CO₂eq/MJ for electricity and gasoline, respectively, but are highly variable due to heterogeneity in upstream supply chains. The use of hybrid gasoline ICEVs provides the largest emission reduction opportunity for existing vehicle fleets in 9 of the 16 MENA countries. For these nine countries, replacing gasoline ICEVs with HEVs could, on average, reduce country-level life cycle GHG emissions by 47%. There is a similar emission reduction opportunity for 14 of the 16 MENA countries when normalizing vehicle efficiencies irrespective of the powertrain shares and other trends in existing vehicle fleets. Future scenario analysis shows that BEVs would have the lowest WTW GHG emissions among all powertrains in most MENA countries only if significantly reduced electricity transmission losses and cleaner grid mix are realized, although a high cost of infrastructure developments is expected.