Enhanced weathering (EW) of rocks and minerals can be used as a carbon dioxide removal (CDR) technique. EW relies on accelerated geochemical reactions between carbonic acid in rainwater and slightly alkaline minerals to permanently sequester carbon atoms as bicarbonate ions in runoff water. The material needs to be crushed into a fine powder to increase its reactive surface area and then spread on land at a rate calibrated to local weather and soil conditions. However, large-scale EW using virgin material will increase outputs and carbon footprints across various economic sectors to support the CDR system. Input-output analysis is used to model such indirect effects when basalt EW is used in all oil palm plantations in Malaysia to cut greenhouse gas emissions. Results at a fixed electricity carbon intensity show that about half of the direct CDR will be offset by incremental carbon footprints from the mining, electricity generation, and transportation sectors due to the requirements of EW operations; total greenhouse gas emissions are reduced by up to 11.0% to 213.7 Mt CO₂ equivalent (CO₂e)/y. Cutting the carbon intensity of electricity supply in half reduces emissions further to 126.9 Mt CO₂e/y. The scenario analyses demonstrate the synergy between renewable energy deployment and EW implementation, supporting the development of carbon management policies in Malaysia.

Solar photovoltaic (PV) systems face significant challenges, including low energy conversion efficiency, performance degradation due to overheating, and operational risks from environmental factors such as rainfall and dust. To address these issues, this study presents an innovative solar energy solution aimed at enhancing panel efficiency and operational reliability through mechanical and environmental integration. The system incorporates a Mylar-based reflector to boost solar irradiance, an automated rain protection cover activated by sensors, a dual-axis solar tracking system for continuous sun alignment, and a temperature-controlled cooling system that activates above 35 °C. Implemented on a 20W Mono PERC (Passivated Emitter Rear Cell) panel, the system was tested under real-world conditions. Results showed a cumulative efficiency improvement compared to a conventional fixed panel. The reflector and tracking system contributed most to output gains, while the rain cover and cooling system improved durability and thermal performance. Overall, the integrated system achieved 50%-55% higher energy production than the conventional fixed panel. These findings highlight a cost-effective approach to advance low-carbon energy transitions and promote renewable adoption in semi-arid urban areas.

The circular economy is a strategic approach to optimizing resource use, offering potential to mitigate Food Loss and Waste. This study aims to analyze Loss and Waste from the perspective of the circular economy, focusing on the agro-industrial cheese production chain of Laticínios Alto Uruguai, located in the municipality of Lajeado do Bugre. Based on interviews and collected data, Loss and Waste were quantified over a 12-month period, grounded in the Mass Balance methodology of the “Loss and Waste Standard”. Drawing from the literature, reuse and recycling strategies aligned with the circular economy were proposed. A Loss and Waste value ranging from 35.2 g was identified for every 2.0 kg of cheese produced in the chain. Solutions such as water recovery from whey and energy generation via anaerobic reactors stand out as promising alternatives for Laticínios Alto Uruguai. It is recommended that future studies integrate quantification of greenhouse gas emissions using approaches such as Life Cycle Assessment or carbon inventories, enabling estimation of the mitigation potential associated with the circularity strategies discussed in this study.

This paper presents a systematic review of the current research landscape in the field of “Artificial Intelligence (AI) + Carbon”. Utilizing bibliometric and visual analysis methods, it identifies and examines key research themes, regional distribution patterns, and evolutionary trajectories within this domain. Findings indicate that a coherent thematic structure centered on carbon emissions has emerged, in which AI technologies play a critical role across various dimensions, including carbon monitoring, simulation, and system optimization. Geographically, research efforts exhibit distinct developmental pathways influenced by divergent national energy strategies and governance frameworks. China leads in applied research and implementation, whereas the United States predominates in foundational theoretical innovations. Other nations engage in context-specific explorations tailored to local priorities. Keyword network analysis reveals a profound coupling between technological capabilities and application scenarios. Temporally, the field has evolved from initial exploratory integrations toward more systematic and holistic approaches, reflecting a growing synergy between technological advances and carbon management imperatives. This review not only offers a structured understanding of the intellectual architecture and emerging hotspots in AI applications for carbon management and footprint research but also provides a foundation for fostering international collaboration and guiding future scholarly and practical endeavors.

Carbon capture and utilization (CCU) mitigates climate change by converting CO₂ into fuels, chemicals, and construction materials. From a life-cycle perspective, CCU benefits arise from preventing point-source emissions, substituting for carbon-intensive products, and coupling with renewable energy to lower upstream impacts. However, high energy needs, feedstock costs, and capture requirements continue to limit large-scale deployment. This perspective reframes CCU beyond conventional cycling by outlining three strategic pathways: replacing high-emission fossil products such as urea to maximize substitution benefits even when CO₂ is later re-emitted; sourcing CO₂ from biogenic streams to create near-neutral cycles; and using CO₂ as a hydrogen carrier that transports energy and enables subsequent permanent storage through concrete mineralization. Combined with falling renewable electricity costs, industrial co-location, and targeted policy support, CCU can progress from niche demonstrations to a scalable contributor to industrial decarbonization and climate-neutral production.

Amid China’s “dual-carbon” goals and mounting environmental pressures, cross-sector synergy is essential for sustainable urban development. We develop an integrated assessment framework to evaluate synergistic governance across four subsystems - carbon mitigation, air-pollution abatement, solid-waste management, and water conservation - for 289 prefecture-level cities during 2011-2020. An obstacle degree model diagnoses which subsystems constrain overall synergy, while a machine-learning random forest model interpreted with Shapley Additive Explanations (SHAP) values quantifies the relative importance and nonlinear effects of twelve socioeconomic drivers. Results indicate broad improvements in synergistic level across most cities, with marked gains in air-pollution control and water conservation driving overall progress. In contrast, only moderate advances in carbon mitigation and high volatility in solid-waste management emerge as the principal barriers to further improvement. Spatial heterogeneity is pronounced: major urban agglomerations generally outperform other areas, with Pearl River Delta, Yangtze River Delta, and Chengdu-Chongqing (Chengyu) exhibiting strong cross-system improvement, whereas Central-Southern Liaoning and the Guanzhong Plain face persistent structural constraints. Machine-learning diagnostics further highlight energy intensity, energy structure, and the dominance of mining and electricity-supply sectors as top predictors of city-level synergistic performance, showing clear threshold effects. Based on these findings, we offer targeted and region-specific policy pathways to accelerate coordinated environmental governance across China’s leading urban agglomerations.

Food systems account for about 30% of anthropogenic emissions, of which agriculture contributes 12%-14%. Agro-ecosystems have large ecological footprints (EFP). Thus, the objective of the review is to examine land-use and management practices that can reduce EFP and sequester carbon (C) in soil. Decomposition of soil organic matter is accelerated by plow tillage and on-farm burning of crop residues. Livestock are also a source of CH₄ through enteric fermentation and manure management. Approaches to reducing the global EFP of agroecosystems are discussed with the objective of adaptation and mitigation of anthropogenic climate change. Sequestration of atmospheric carbon dioxide (CO₂) in soil, as soil organic carbon and soil inorganic carbon, can offset emissions. Examples of best management practices include conservation agriculture, judicious use of chemicals, drip fertigation, agroforestry, improved livestock grazing and manure management. The rate of C sequestration varies widely depending on soil, climate, and management. Soils of agroecosystems have the potential to sequester 4 to 10 Pg CO₂ equivalents (CO₂eq) per year (Pg = petagram = 10¹⁵g = 1 giga ton or Gt = 1 billion metric ton). However, the gross rate of C sequestration in soil varies among soils, eco-regions and management. The EFP of agro-ecosystems can be reduced by enhancing use efficiency of inputs, decreasing leakage of chemicals into the environment, conserving soil and water, and adopting regenerative agriculture. The importance of C farming and approaches to its adoption are discussed as payments for ecosystem services and the establishment of the Soil Health Act. Reducing EFP of agro-ecosystems is narrated in relation to Sustainable Development Goals of the United Nations.

Anticipated growth in global palm oil demand is driving an expansion of Indonesian production, frequently necessitating land-use change (LUC). This study employs consequential life cycle assessment (LCA) integrated with Monte Carlo simulations to estimate the carbon footprint (CF) due to LUC and investigate the sensitivity of these results to modeling choices. Understanding the CF of palm oil, particularly from LUC and through rigorous LCA modeling, is paramount for providing sound advice on greenhouse gas (GHG) mitigation. Converting peatland to oil palm plantations represents the most detrimental scenario regarding climate impact. For example, a10% LUC from peatland alone leads to 5.4 t CO_2eq ha^-1 a^-1, i.e., 54 t ha^-1 peatland converted and 1,350 t CO_2eq ha^-1 over 25 years. Furthermore, the modeling choice for by-product substitution significantly influences CF results, potentially limiting the comparability of findings across different studies. Our analysis demonstrates that the CF of crude palm oil (CPO) varies from 0.26E3 to 1.4E3 kg CO_2eq t^-1 without LUC and 0.85E3 to 1.9E3 kg CO_2eq t^-1 when LUC is included, depending on by-product modeling. Transparency in these modeling choices is paramount for providing robust decision support to policymakers. Finally, a high-potential mitigation strategy involves supporting the smallholder sector, which managed approximately 40% of the 17 million hectares of oil palm plantations in 2021. Increasing smallholder yields from 11 t to 20 t of fresh fruit bunches (FFB) ha^-1 would generate an additional 14 million tons of CPO without further LUC - effectively sparing 3 million ha of land.

Soil organic carbon (SOC) plays an important role in carbon and nutrient cycling, agricultural productivity, and climate regulation, yet its variability and environmental controls remain poorly constrained in tropical regions characterized by a diversity of soils, climates, and land-use histories. We conducted a regional-scale assessment of SOC across Puerto Rico to evaluate how land use, soil properties, and climate influence SOC variability and to examine the applicability of existing benchmark frameworks in tropical agroecosystems. We compiled SOC data from 586 soil pedons representing nine US Department of Agriculture (USDA) soil orders and multiple land-use categories, with SOC concentrations standardized to the 0-30 cm depth. We evaluated land-use effects and relationships between SOC and environmental variables. SOC concentrations differed by land use, with greater values generally observed in wetlands and forests, intermediate values in pastures or grazing lands, and lower values in agricultural lands. Environmental factors associated with SOC variability differed by land use, with climate and soil suborder more strongly associated with SOC in forests, soil texture and suborder in pastures, and a combination of soil order, texture, temperature, and pH in agricultural systems. We also compared the effectiveness of two SOC benchmarking approaches: the Soil Health Gap model and a Scores Benchmark based on empirical cumulative distributions applied to soils of the tropics in our database. The limited availability of primary forests poses a challenge for applying benchmarks that require undisturbed reference conditions, while the island’s broad climatic range allows for testing the robustness of SOC benchmarks across a diversity of soil environmental conditions. The Soil Health Gap showed differences among soil orders and climate, whereas the Scores Benchmark provided a more flexible framework for contextualizing SOC across heterogeneous tropical landscapes. Our findings support the use of context-specific SOC benchmarks to evaluate land-use change and soil assessment efforts in tropical regions without assuming undisturbed reference conditions.

The production of industrial enterprises is accompanied by pollution and carbon emissions, while the environmental consequences of their relocation remain unclear. Using the Annual Surveys of Industrial Firms from 2003 to 2015, we identify the enterprises that relocated and construct theoretical and two-way fixed effect models to analyze the effects of industrial enterprise relocation (IER). We find that IER significantly improved the performance of carbon mitigation and pollution reduction in both origin and destination cities. The positive outcomes stem from technological innovation and economic structure adjustment triggered by relocation. Moreover, the benefits are more pronounced in western regions and in areas with lower industrial development. Resource endowment weakens the environmental improvement in destination cities and enhances it in origin cities, validating the effectiveness of industrial gradient transfer in improving the environment. Stricter environmental regulations are one of the reasons driving IER. This research provides new insights into how industrial spatial reallocation can contribute to win-win outcomes in carbon mitigation and air pollution reduction, advancing the goal of low-carbon and sustainable regional development.

Biodiesel is recognized as a promising and sustainable alternative to petroleum-derived diesel fuel. The use of biodiesel as fuel can be considered as a closed carbon cycle. In fact, CO₂ emission under combustion is balanced by the fixed CO₂ consumed by growing biomass. Furthermore, biodiesel combustion generates lower emissions of sulfur oxides and solid particles compared with hydrocarbon-derived diesel, reinforcing the environmental advantages. A wide range of renewable feedstocks, including vegetable oils, waste cooking oils, and animal fats, can be utilized for biodiesel synthesis; however, the efficiency of the process strongly depends on the design of catalytic system applied. Homogeneous and enzymatic catalysts demonstrated significant success; however, in industry, heterogeneous catalysts were preferred due to their easy separation, high stability, and recycling potential. Calcium oxide (CaO) and CaO-based materials were considered as appropriate catalysts due to strong basicity, low cost, and abundance in nature. Nevertheless, the catalytic performance is limited by many issues, e.g., precursor type, loading, surface area, and stability under reuse. Understanding the structure-activity relationship of CaO-based catalysts is therefore essential for optimizing the design of catalysts. This review analyzes the performance of CaO-based catalysts for biodiesel production considering key development stages - source sustainability, catalyst loading, specific surface area, and reusability - to critically examine the impact of parameters on catalytic efficiency and potential industrial implementation. The review highlights the nonlinearity and interdependence of key catalyst parameters affecting biodiesel yield in transesterification. All the reviewed studies were summarized in tables at the end of the relevant review chapter.

Urban areas in small islands are highly vulnerable to the effects of climate change and related hazards, underscoring the need for sustainable, resilient practices. This study investigates the potential impacts of urbanization on precipitation and temperature in the Colombo Metropolitan Area of Sri Lanka. To explore temperature and precipitation trends, this research employs diverse modeling and methodological strategies, including the precipitation-temperature relationship, super-scaling, structural equation modeling, and dynamic structural equation modeling. The findings suggest that ongoing urbanization is influencing both temperature and precipitation patterns. Results show relative impacts of different land-use changes on the regional climate, highlighting the complex relationships among vegetation, urbanization, and climate dynamics. A significant relationship is observed between urbanization and both temperature and precipitation, indicating that urbanization is a crucial driver of local environmental change affecting regional climate and land cover. The results can be utilized to support the development of adaptive measures aligned with sustainable development goals. This research supports and addresses two Sustainable Development Goals (SDGs), specifically Goal 11: Sustainable Cities and Communities, and Goal 13: Climate Action. By incorporating regional climatic influences in future research, the analysis could further enhance understanding of these interactions and strengthen adaptation strategies for sustainable development.

Valorizing solid wastes in concrete production has the potential to deliver three-fold benefits of minimizing landfill, reducing material costs, and improving concrete properties, therefore adding value to both economic development and environmental management. Despite such significant potential, the practical utilization of solid wastes in concrete has been limited due to various factors. This paper overviews solid wastes utilized in concrete production, aiming to clarify the capabilities and limitations through surveying solid wastes that serve as alternative raw materials of concrete, underlying mechanisms, concrete properties, and emerging technologies toward upcycling. The types of wastes reviewed include industrial, agricultural, municipal, and construction streams, which play roles as binders, aggregates, or fillers, impacting the fresh, mechanical, durability, and multifunctional properties of concrete. The underlying physical and chemical mechanisms that govern concrete properties are discussed. Advancements in nanotechnology, carbon sequestration, artificial intelligence, and advanced manufacturing are examined as emerging techniques. Key challenges and new opportunities are discussed to provide a roadmap for future research and development of green concrete technologies.