Search Results (82)

Climate change poses one of the greatest challenges of our time, with greenhouse gas (GHG) emissions significantly contributing to global warming. The agriculture, forestry, and land-use (AFOLU) sectors not only emit GHGs but also offer the potential for carbon sequestration, which can mitigate climate change. This study presents a methodological framework for estimating soil organic carbon (SOC) changes based on carbon farming practices in northern Lithuania. Using satellite-derived indicators of cover crops, no-till farming, and residue retention combined with soil and climate data, SOC dynamics were modeled across the Joniškis municipality for the period 2019–2020 using the Rothamsted Carbon Model (RothC) model. The integration of geospatial data and process-based modeling allowed for spatial estimation of SOC change, revealing positive trends ranging from 0.23 to 0.32 t C ha⁻¹ year⁻¹. Higher increases were observed in areas where multiple carbon farming practices overlapped. The proposed workflow demonstrates the potential of combining Earth observation and modeling approaches for regional-scale carbon assessment and provides a basis for future applications in sustainable land management and climate policy support. Full article

Improving forest carbon sink efficiency (FCSE) is the key to mitigating climate change and achieving sustainable forest resource management in China. However, current research on FCSE remains predominantly focused on static perspectives and singular linear effects. Based on panel data from 30 provinces (autonomous regions and municipalities) in China from 2008 to 2022, this study integrated the super-efficiency Slack-Based Measure (SBM)-Malmquist–Luenberger (ML) model, spatial autocorrelation analysis, and dynamic fuzzy set qualitative comparative analysis (fsQCA) to reveal the spatiotemporal differentiation characteristics of FCSE and the multi-factor synergistic driving mechanism. The results showed that (1) the average value of the FCSE in China was 1.1. Technological progress (with an average technological change of 1.21) is the core growth driver, but the imbalance of technological efficiency change (EC) among regions restricts long-term sustainability. (2) The spatial distribution exhibited a U-shaped gradient pattern of “eastern—southwestern”, and the synergy effect between nature and economy is significant. (3) The dynamic fsQCA identified three sustainable improvement paths: the “precipitation–economy” collaborative type, the multi-factor co-creation type, and “precipitation–industry-driven” type; precipitation was the universal core condition. (4) Regional differences exist in path application; the eastern part depends on economic coordination, the central part is suitable for industry driving, and the western part requires multi-factor linkage. By introducing a dynamic configuration perspective, analyzing FCSE’s spatiotemporal drivers. We propose a sustainable ‘Nature–Society–Management’ interaction framework and region-specific policy strategies, offering both theoretical and practical tools for sustainable forestry policy design. Full article

The effective use of biowaste resources becomes crucial for the development of bioprocessing alternatives to current oil- and chemical-based value chains. Targeting the development of multi-product biorefinery approaches benefits the viability and profitability of these process schemes. Certain oleaginous microorganisms, such as oleaginous red yeast, can co-produce industrially relevant bio-based products. This work aims to explore the use of industrial and urban waste as cost-effective feedstock for producing microbial oil and carotenoids using Rhodosporidium toruloides. The soluble fraction, resulting from homogenization, crushing, and centrifugation of discarded vegetable waste, was used as substrate under a pulse-feeding strategy with a concentrated enzymatic hydrolysate from municipal forestry residue obtained after steam explosion pretreatment (190 °C, 10 min, and 40 mg H₂SO₄/g residue). Additionally, the initial nutrient content was investigated to enhance process productivity values. The promising results of these cultivation strategies yield a final cell concentration of 36.4–55.5 g/L dry cell weight (DCW), with an intracellular lipid content of up to 42–45% (w/w) and 665–736 µg/g DCW of carotenoids. These results demonstrate the potential for optimizing the use of waste resources to provide effective alternative uses to current biowaste management practices, also contributing to the market of industrially relevant products with lower environmental impacts. Full article

Low-carbon liquid fuels are needed for decarbonization of hard-to-decarbonize segments of the transportation sector. This decarbonization can be limited by the amount of renewable carbon. Thermochemical conversion of biomass/municipal solid waste (MSW) through gasification is a promising route for producing low-carbon fuels. There are two major opportunities for increasing the amount of low-carbon liquid fuel that can be produced from gasification in any region. One is to increase the amount of liquid fuel from a given amount of biomass/MSW, particularly by hydrogen-enhancement of gasification synthesis gas. Second is the potential for large expansion of use of biomass feedstocks from its present level. Such biomass feedstocks include agricultural waste, forestry waste, MSW, and specially grown biomass that does not interfere with food production. The use of MSW may provide advantages of an established network for pickup and transportation of feedstock to disposal sites and the avoidance of methane produced from landfilling of MSW. As a case study, we looked at potential expansion of US low-carbon fuel production, considering the recent projections of the 2024 USDOE report, which estimated potential production of a billion tons/yr of biomass/MSW feedstocks in the US. This report included an estimated potential for liquid biofuel production of 60 billion gallons/yr of diesel energy equivalent fuel without the use of hydrogen enhancement. By hydrogen-enhanced biomass/MSW gasification, this projection could be doubled to 120 billion gallons/yr of diesel energy equivalent fuel. Furthermore, the co-location potential of biomass/MSW resources with potential renewable energy generation sites is explored. This overlap of hydrogen production and biomass production in the US are located in regions such as the US Midwest, Texas, and California. This co-location strategy enhances logistical feasibility, reducing transport costs and optimizing energy system integration; and can be applied to other geographical locations. Hydrogen-enhanced biomass/MSW gasification offers a promising route to substantially increase low-carbon liquid fuel production (e.g., methanol) and support increased liquid fuel production and greenhouse gas reduction goals. Full article

Wildfires represent an increasing global concern, threatening ecosystems, human settlements, and economies. Chile, characterized by diverse climatic zones and extensive forested areas, has been particularly vulnerable to wildfire events over recent decades. In this context, real, long-term data are essential to understand wildfire dynamics and to design effective early warning and prevention systems. This paper introduces a unique dataset containing detailed wildfire occurrence and damage information across Chilean municipalities from 1985 to 2024. Derived from official records by the National Forestry Corporation of Chile CONAF, this dataset encompasses key variables such as the number of fires, total burned area, estimated material damages, and the number of affected individuals. It provides an invaluable resource for researchers and policymakers aiming to improve fire risk assessments, model fire behavior, and develop AI-driven early detection systems. The temporal span of nearly four decades offers opportunities for longitudinal analyses, the study of climate change impacts on fire regimes, and the evaluation of historical prevention strategies. Furthermore, by presenting a complete spatial coverage at the municipal level, it allows fine-grained assessments of regional vulnerabilities and resilience. Full article

Smoke tree (Cotinus coggygria) is an important component of the urban landscape and represents red-leaf scenery in Beijing; however, Verticillium wilt, caused by Verticillium dahliae, has caused high mortality of smoke trees. Traditional control methods, such as chemical root irrigation and trunk injection, are problematic due to environmental pollution and potential plant damage. This study aimed to explore effective prevention and control methods for Verticillium wilt of smoke tree across different regions of red-leaf scenery in Beijing. In 2023, 240 smoke trees from the Pofengling Park of Beijing were selected for the study. Four different fungicides, a plant growth regulator and a biocontrol agent were tested. Three application methods (root irrigation, trunk spraying, and a combination of both) were used in the different trials. Based on the results of the 2023 trial, control trials were conducted under the disease classification in 2024 at key red-leaf scenery regions, such as Xiangshan Park, Xishan Park, and Pofengling Park. The bioagents of Bacillus subtilis root irrigation combined with the trunk spraying treatment group showed the best disease control effects. Calculated by the change in disease index in the treatment and blank groups, the corrective control effect in the treatment group reached 104.55%, and 60% of the plants remained healthy, indicating that this method of disease control was the most effective. Propiconazole root irrigation also had a significant effect on diseased smoke trees. Furthermore, validation experiments conducted in 2024 confirmed that various combinations of root irrigation and trunk spraying provided strong preventive and therapeutic effects on Verticillium wilt. In conclusion, the graded control measures demonstrated effective control of wilt at different disease index grades. This study offers an effective and practical solution for controlling Verticillium wilt, benefiting both environmental sustainability and landscape health. Full article

Forest growing stock volume (GSV) is a fundamental indicator for assessing the status of forest resources. It reflects forest carbon storage levels and serves as a key metric for evaluating the carbon sequestration capacity of forest ecosystems, thereby playing a crucial role in supporting national “dual-carbon” objectives. Traditional allometric models typically estimate GSV using tree species, diameter at breast height (DBH), and canopy height. However, at larger spatial scales, these models often neglect stand density, resulting in substantial estimation errors in regions characterized by significant density variability. To enhance the accuracy of large-scale GSV estimation, this study incorporates high-resolution, spatially continuous forest structural parameters—including dominant tree species, stand density, canopy height, and DBH—extracted through the synergistic utilization of active (e.g., Sentinel-1 SAR, ICESat-2 photon data) and passive (e.g., Landsat-8 OLI, Sentinel-2 MSI) multi-source remote sensing data. Within an allometric modeling framework, stand density is introduced as an additional explanatory variable. Subsequently, GSV is modeled in a stratified manner according to tree species across distinct ecological zones within Kunming City. The results indicate that: (1) the total estimated GSV of Kunming City in 2020, based on remote sensing imagery and second-class forest inventory data collected in the same year, was 1.01 × 10⁸ m³, which closely aligns with contemporaneous statistical records. The model yielded an R² of 0.727, an RMSE of 537.566 m³, and a MAE of 239.767 m³, indicating a high level of overall accuracy when validated against official ground-based inventory plots organized by provincial and municipal forestry authorities; (2) the incorporation of the dynamic stand density parameter significantly improved model performance, which elevated R² from 0.565 to 0.727 and significantly reduced RMSE. This result confirms that stand density is a critical explanatory factor; and (3) GSV exhibited pronounced spatial heterogeneity across both tree species and administrative regions, underscoring the spatial structural variability of forests within the study area. Full article

As the climate continues to warm, and municipal leaders look for cost-effective and timely approaches to urban sustainability, one increasingly sought-out approach is the use of tree canopy to cool neighborhoods. Despite widespread efforts to expand tree canopy in cities, an overwhelming body of evidence suggests that urban green space is declining across the U.S., yet little is known about the factors that propel these changes. Understanding the institutional and governance systems can help identify the opportunities for slow consistent declines. Using social network analysis (SNA) metrics, we examined stakeholder roles in power structures and decision-making processes within Portland, Oregon’s urban forest management. Our results reveal a highly decentralized urban forestry network (density = 0.0079), with weak cohesion (5.4%) among 162 stakeholders. Moving forward, while network governance may face obstacles from conflicting interests among community and interagency groups, transforming governance models at all levels will require developing periodic, collaborative urban forestry management plans to address nature-based planning challenges. These planning documents should strongly emphasize not only the prioritization of tree equity-related ordinances but also the optimization of eco-literacy and awareness through virtual reality (VR) technology. As a novel approach, immersive simulations demonstrate practical potential for showcasing urban forestry benefits in network governance outreach and consensus-building. Full article

This study utilized data from 300 prefecture-level cities in China, spanning from 2000 to 2020, and employed a difference-in-differences (DID) model to investigate the influence of land development rights on agricultural land prices, alongside the mechanisms underlying this relationship. The primary aim of this research was to analyze the manner in which land development rights affect agricultural land prices through the implementation of policies and market forces. Via empirical analysis, the study elucidated the effects of land development rights on agricultural land prices within China. The key findings include the following: (1) Land development rights positively influence the increase in agricultural land prices. (2) Land development rights significantly narrow the urban–rural income disparity at municipal and county levels, which in turn impacts agricultural land prices. (3) The effect of land development rights on agricultural land prices is negatively moderated by regional economic growth. (4) While land development rights significantly enhance the prices of arable land, their impact on sectors such as agriculture, forestry, animal husbandry, fishing, and food processing remains minimal. (5) In northern regions and economically underdeveloped areas, land development rights substantially boost agricultural land prices, underscoring their role in fostering local economic development and enhancing land use efficiency. Full article

Urban street trees often exhibit distinct architectural characteristics compared to their counterparts in natural forests. Allometric equations for the stem (M_S), branches (M_B), and total dry aboveground biomass of urban trees (M_T) were developed, based on 52 destructively sampled specimens, belonging to 10 different species, growing in the Municipality of Athens, Greece. Linear, log-linear, and nonlinear regression analyses were applied, and fit statistics were used to select the most appropriate model. The results indicated that diameter at breast height (D_1.3) and tree height (H) are needed for accurately predicting M_S, while M_B may be estimated based on D_1.3. To circumvent the caveat of the additivity property for estimating the biomass of different tree component, nonlinear seemingly unrelated regression (NSUR) was implemented. The 95% prediction intervals for M_S, M_B, and M_T efficiently captured the variability of the sampled trees. Finally, the predictions were compared with estimates from i-Tree, the most widely used model suite for urban and rural forestry analysis, and a mean deviation of 134% (ranging from 3% to 520%) was reported. Therefore, in the absence of urban-specific allometries, the obtained empirical models are proposed for estimating biomass in street trees, particularly in cities with Mediterranean-like climatic influences. Full article

The degradation of ecosystem services (ES) poses a significant obstacle to regional sustainable development. Land-use change is widely recognized as a pivotal factor driving the spatio-temporal dynamics of ES supply and demand. However, the future impact of land-use changes on supply–demand risks remains largely unknown. To fill this knowledge gap, we conducted a study in the Gansu section of the Yellow River Basin. By integrating Cellular Automata (CA) and an enhanced Markov model within the GeoSOS-FLUS framework, we dynamically simulated land-use changes under three scenarios—the Normal Development Scenario (NDS), Ecological Protection Scenario (EPS), and Rapid Socio-economic Development Scenario (RDS)—spanning from 2020 to 2050. Furthermore, we employed the InVEST model to analyze the spatio-temporal pattern of supply, demand, supply-to-demand ratios, and supply–demand risks for water provision, carbon storage, and soil conservation under all scenarios. Firstly, all scenarios project an increase in built-up land, primarily from unused land, shrubland, grassland, and cropland. Forest land and water bodies remain stable. Secondly, water provision increases, but demand grows faster, leading to supply–demand imbalances, with high-risk areas in the north, central, and east. Soil conservation shows balanced supply and demand with high-risk areas in the north. Carbon storage remains stable, with high-risk areas in the central and east regions. Thirdly, high-risk areas for water provision increase under all scenarios, particularly under the Rapid Socio-economic Development scenario. Full article

This paper explores the advantages of the co-pyrolysis of municipal sewage sludge with agricultural and forestry biomass, emphasizing its potential for environmental and economic benefits. Co-pyrolysis with lignocellulosic biomass significantly enhances biochar quality, reduces the heavy metal content, increases porosity, and improves nutrient retention, which are essential for soil applications. The biochar produced through co-pyrolysis demonstrates enhanced stability and a lower oxygen-to-carbon (O/C) ratio, making it more suitable for long-term carbon (C) sequestration and pollutant adsorption. Additionally, co-pyrolysis generates bio-oil and syngas with improved calorific value, contributing to renewable energy recovery from sewage sludge. This synergistic process also addresses waste management challenges by reducing harmful emissions and immobilizing heavy metals, thus mitigating the environmental risks associated with sewage sludge disposal. This paper covers key sections on the properties of waste materials, improvements in biochar quality and energy products, and the environmental benefits of co-pyrolysis, such as emissions reduction and heavy metal immobilization. The paper highlights trends and challenges in co-pyrolysis technology, aiming to optimize parameters for maximizing biochar yield and energy recovery while aligning with sustainability and circular economy goals. The paper concludes with recommendations for optimizing co-pyrolysis processes and scaling applications to support sustainable waste management. Overall, co-pyrolysis represents a sustainable approach to valorizing sewage sludge, transforming it into valuable resources while supporting environmental conservation. Full article

Urban tree canopy (UTC) coverage, or area, is an important metric for monitoring changes in UTC over large areas within a municipality. Several methods have been used to obtain these data, but remote sensing image classification is one of the fastest and most reliable over large areas. However, most studies have tested only one or two classification methods to accomplish this while using costly satellite imagery or LiDAR data. This study seeks to compare three urban tree canopy cover classifiers by testing a deep learning U-Net convolutional neural network (CNN), support vector machine learning classifier (SVM) and a random forests machine learning classifier (RF) on cost-free 2012 aerial imagery over a small southern USA city and midsize, growing southern USA city. The results of the experiment are then used to decide the best classifier and apply it to more recent aerial imagery to determine canopy changes over a 10-year period. The changes are subsequently compared visually and statistically with recent urban heat maps derived from thermal Landsat 9 satellite data to compare the means of temperatures within areas of UTC loss and no change. The U-Net CNN classifier proved to provide the best overall accuracy for both cities (89.8% and 91.4%), while also requiring the most training and classification time. When compared spatially with city heat maps, city periphery regions were most impacted by substantial changes in UTC area as cities grow and the outer regions get warmer. Furthermore, areas of UTC loss had higher temperatures than those areas with no canopy change. The broader impacts of this study reach the urban forestry managers at the local, state/province, and national levels as they seek to provide data-driven decisions for policy makers. Full article

Enhancing forest ecological functioning by optimizing stand structure is essential in high-quality, sustainable forests. We examined this in 38 plots (20 m × 20 m) of Pinus tabuliformis forests in the mountainous area of Beijing. We investigated and analyzed the spatial structure and functional characteristics of these plots. Structural equation modeling and response surface methodology were used to identify spatial structural stand factors affecting soil nutrient levels and understory biodiversity. We examined the pathways and strengths of the coupling relationships between structure and function and the ranges and thresholds of changes in these structural factors. Mingling degree, openness degree, competition index, and forest layer index substantially affected the understory herbaceous species diversity and soil nutrient levels. Mingling degree significantly impacted understory biodiversity and soil nutrient levels (direct path coefficient (DPC), 0.48 and 0.70, respectively). Openness degree significantly affected understory species diversity (DPC, 0.37). The competition index and forest layer index exerted less significant direct impacts on these functions; competition influenced herbaceous diversity primarily indirectly. The optimal features were as follows: mingling degree, 0.8; openness degree, 1.1; competition index, 0.3; and forest layer index, 0.5. Average understory herbaceous species diversity and soil nutrient levels are projected to increase by ca. 47.74% and 52.29%, respectively, post optimization. These findings provide a reference for precise regulated stand structures and establish multifunction management optimization objectives in Beijing’s mountainous Pinus tabuliformis forests. Full article

Wood construction waste circularity presents enormous potential to significantly de-crease total greenhouse gas (GHG) emissions in the European Union (EU). Latvia could become a frontrunner due to its historic relationship with forestry, wood construction practises and unused potential of the innovative application of wood. This research examines what the potential of “circular wood” in Latvia is, how ready the Latvian wood house construction sector is to engage in a circular economy and wood waste circularity and whether the legal framework is ready to support wood waste management in the country. This study presents a combined approach for systematic wood construction product circularity assessment that includes a review of existing EU and Latvian frameworks for construction and demolition waste (CDW) management and wood construction, a general analysis of wood waste recycling systems and technologies, a quantitative data analysis of construction waste management in Latvia and qualitative data analysis of the Latvian wood house construction sector, and interviews with a focus group of Latvian wood industry representatives. The Latvian scope has allowed us to clarify the pattern methodology and impact points to be replicated, tested and measured further on a broader scale, in other countries, or throughout the whole EU. The main findings reveal a potential life cycle assessment (LCA) verifying the circularity of wood and limitations of wood construction waste circularity in Latvia in terms of wood house construction industry readiness and a legal framework as well as overall social prejudices for circular construction. Findings indicate an overall awareness and level of willingness to participate and engage in the circular construction models among Latvians; however, proactiveness and support (legal and financial) is expected from the government and municipalities. The recommendations point towards improvements in wood waste data management, the wood construction sector and the overall impact on sustainable development goals. Full article