Search Results (613)

The European Union’s enhanced greenhouse gas (GHG) reduction targets for 2030 make the large-scale deployment of carbon capture and storage (CCS) technologies essential to achieve deep decarbonization goals. Within this context, this study aims to advance CCS research by developing and testing a pilot-scale system that integrates gasification for syngas and power production with CO₂ absorption and solvent regeneration. The work focuses on improving and validating the operability of a pilot plant section designed for CO₂ capture, capable of processing up to 40 kg CO₂ per day through a 6 m absorber and stripper column. Experimental campaigns were carried out using different amine-based absorbents under varied operating conditions and liquid-to-gas (L/G) ratios to evaluate capture efficiency, stability, and regeneration performance. The physical properties of regenerated and CO₂-saturated solvents (density, viscosity, pH, and CO₂ loading) were analyzed as potential indicators for monitoring solvent absorption capacity. In parallel, a process simulation and optimization study was developed in Aspen Plus, implementing a split-flow configuration to enhance energy efficiency. The combined experimental and modeling results provide insights into the optimization of solvent-based CO₂ capture processes at pilot scale, supporting the development of next-generation capture systems for low-carbon energy applications. Full article

Peatlands provide essential ecological services but are highly vulnerable to degradation from drainage, leading to greenhouse gas emissions, land subsidence, and increased fire susceptibility. This study investigates peat hydrology and its relationship to fire risk in a fire-prone area in South Sumatra, Indonesia. Groundwater levels and soil moisture were continuously monitored using automated loggers, and recession analysis quantified their rates of decline. Multispectral drone imagery (NDVI, NDWI) over a 44.1-ha area assessed vegetation and surface wetness, while fire occurrences (2019–2024) were analyzed using the Fire Information for Resource Management System (FIRMS). During a 58-day dry period, groundwater depth reached 78.5 cm with a recession rate of 9.68 mm day⁻¹, while soil moisture decreased by 0.00291 m³ m⁻³ per day over 27 consecutive dry days. Drone imagery revealed that unhealthy and dead grass covered nearly 90% of the site, although wetness remained moderate (NDWI = 0.02–0.58). FIRMS data indicated that rainfall below 2000 mm year⁻¹ and prolonged dry spells (>30 days) strongly trigger peat fires. These findings correspond with early-warning model outputs based on soil moisture recession and ignition thresholds. Maintaining a high groundwater level is, therefore, crucial for reducing peat fire vulnerability under extended dry conditions. Full article

Piggery farming is the largest source of livestock manure in South Korea, yet greenhouse gas (GHG) data from piggery wastewater treatment systems remain limited. This study quantified methane (CH₄) and nitrous oxide (N₂O) fluxes from a full-scale treatment facility to develop stage-, seasonal-, and diurnal-specific emission factors. Continuous laser-based monitoring using a PVC air-pool chamber was applied across raw wastewater storage, an anoxic nitrogen-conversion reactor, and strongly aerated nitrification units. Mean CH₄ fluxes ranged from 1.1 to 15.6 mg s⁻¹ m⁻² peaking in summer, while N₂O fluxes ranged from 0.01 to 17,971 mg s⁻¹ m⁻², with maxima in fall. Emissions were dominated by two functional zones: aerated basins where vigorous mixing enhanced CH₄ stripping, and an upstream anoxic reactor where oxygen instability and nitrite accumulation produced extreme N₂O peaks. Derived emission factors were 0.11 kg CH₄ head⁻¹ yr⁻¹ and 45.2 kg N₂O head⁻¹ yr⁻¹, equivalent to 3.1 and 12,300 kg CO₂-eq head⁻¹ yr⁻¹. CH₄ variability was controlled mainly by treatment stage and temperature, whereas N₂O was governed by internal redox conditions. These results refine emission factors for inventories and underscore the need for improved aeration stability and denitrification control to reduce GHG emissions from piggery wastewater systems. Full article

This study evaluates the operational performance and carbon emissions of an air-source heat pump (ASHP) system based on a one-year field monitoring campaign conducted at a single-family detached house in Gongju, South Korea. The system, equipped with a 9 kW air-to-water ASHP, supplied both space heating (SH) and domestic hot water (DHW), achieving average coefficients of performance (COPs) of 2.27 for SH and 2.06 for DHW. To estimate nominal COPs, a bi-quadratic regression model was developed using manufacturer catalog data and compared against field measurements. The analysis revealed a significant performance decline during winter: a paired t-test using 7119 samples confirmed a statistically significant discrepancy under low-temperature conditions. Annual CO₂-equivalent (CO₂eq) emissions were also evaluated. Under current grid emission factors, the ASHP system emitted 1532 kgCO₂eq—approximately 8.6% more than a condensing gas boiler (1411 kgCO₂eq), primarily due to winter performance degradation and the relatively high carbon intensity of electricity. These findings underscore the importance of incorporating actual operating conditions, seasonal variability, and the national electricity emission factor when assessing ASHP performance and life cycle climate performance (LCCP). Full article

The rapid proliferation of Electric Vehicles (EVs) offers a promising pathway toward reducing greenhouse gas emissions and fostering a sustainable environment. However, the large-scale integration of EVs presents significant challenges to distribution networks, potentially increasing stress on grid infrastructure. To address these challenges, this study proposes the integration of a Virtual Power Plant (VPP) framework within EV charging stations as a novel approach to facilitate dynamic power management. The proposed framework integrates electric vehicle (EV) scheduling, battery energy storage (BES) charging, and vehicle-to-grid (V2G) support, while dynamically monitoring energy generation and consumption. This approach aims to enhance voltage regulation and minimize both EV charging durations and waiting periods. A modified IEEE 13-bus test network, equipped with six strategically placed EV charging stations, has been employed to evaluate the performance of the proposed model. Simulation results indicate that the proposed VPP-based method enables dynamic power coordination through EV scheduling, significantly improving the voltage stability margin of the distribution system and efficiently reduces charging times for EV users. Full article

Strawberry (Fragaria × ananassa (Weston) Rozier) is a high-value crop whose market success depends on fruit quality traits such as sweetness, firmness, and pigmentation. In sustainable agriculture, wood distillates are gaining interest as natural biostimulants. This study evaluated the effects of foliar application of two commercial wood distillates (WD1 and WD2) and one produced in a pilot plant at the Institute for Bioeconomy of the National Research Council of Italy (IBE-CNR) on strawberry physiology, fruit yield, and fruit quality under greenhouse conditions. Non-destructive ecophysiological measurements were integrated using optical sensors for proximal phenotyping, enabling continuous monitoring of plant physiology and fruit ripening. Leaf gas exchange and chlorophyll fluorescence were measured with a portable photosynthesis system, while vegetation indices and pigment-related parameters were obtained using spectroradiometric sensors and fluorescence devices. To assess the functional relevance of vegetation indices, a linear regression analysis was performed between net photosynthetic rate (A) and the Photochemical Reflectance Index (PRI), confirming a significant positive correlation and supporting PRI as a proxy for photosynthetic efficiency. All treatments improved photosynthetic efficiency during fruiting, with significant increases in net photosynthetic rate, quantum yield of photosystem II, and electron transport rate compared to control plants. IBE-CNR and WD2 enhanced fruit yield, while all treatments increased fruit soluble solids content. Non-invasive monitoring enabled real-time assessment of physiological responses and pigment accumulation, confirming the potential of wood distillates as biostimulants and the value of advanced sensing technologies for sustainable, data-driven crop management. Full article

This study addressed the core challenge of intelligent pest and disease monitoring and early warning in smart horticultural production by proposing a multimodal deep learning framework based on multi-parameter environmental sensor arrays. The framework integrates visual information with electrical signals to overcome the inherent limitations of conventional single-modality approaches in terms of real-time capability, stability, and early detection performance. A long-term field experiment was conducted over 18 months in the Hetao Irrigation District of Bayannur, Inner Mongolia, using three representative horticultural crops—grape (Vitis vinifera), tomato (Solanum lycopersicum), and sweet pepper (Capsicum annuum)—to construct a multimodal dataset comprising illumination intensity, temperature, humidity, gas concentration, and high-resolution imagery, with a total of more than $2.6\times {10}^6$ recorded samples. The proposed framework consists of a lightweight convolution–Transformer hybrid encoder for electrical signal representation, a cross-modal feature alignment module, and an early-warning decision module, enabling dynamic spatiotemporal modeling and complementary feature fusion under complex field conditions. Experimental results demonstrated that the proposed model significantly outperformed both unimodal and traditional fusion methods, achieving an accuracy of $0.921$, a precision of $0.935$, a recall of $0.912$, an F1-score of $0.923$, and an area under curve (AUC) of $0.957$, confirming its superior recognition stability and early-warning capability. Ablation experiments further revealed that the electrical feature encoder, cross-modal alignment module, and early-warning module each played a critical role in enhancing performance. This research provides a low-cost, scalable, and energy-efficient solution for precise pest and disease management in intelligent horticulture, supporting efficient monitoring and predictive decision-making in greenhouses, orchards, and facility-based production systems. It offers a novel technological pathway and theoretical foundation for artificial-intelligence-driven sustainable horticultural production. Full article

This paper aims to provide an analytical assessment of country-level experience in moving towards agricultural decarbonization—from ideas around decarbonization measures to assessment of their potential, including evaluations of political goals and practical implementation success. This paper is based on 10-year cycle that highlights the main steps in building decarbonization awareness using an approach that can monitor, quantify, and evaluate the contribution of agricultural practices to climate change mitigation. This approach is based on a marginal abatement cost curve (MACC), which serves as a convenient visual tool for evaluating the effectiveness of various greenhouse gas emission reduction measures in agriculture, as well as climate policy planning. This study reveals the experiences to date and the main directions for developing the MACC approach, which serves as a basis for analyzing the potential of moving towards decarbonization in agriculture for a specific European Union Member state, i.e., Latvia. The results of the study are of practical use for the development of agricultural, environmental, and climate policies or legal frameworks, policy analysis, and impact assessment. Additionally, the findings are useful for educating farmers and the public about measures to reduce GHG and ammonia emissions. Full article

Constructed wetlands (CWs) are nature-based solutions that integrate ecological processes for water purification, climate regulation, and biodiversity enhancement. However, biodiversity monitoring in CWs has often been underprioritized, limiting its recognition as a functional driver of ecosystem service performance. This study first developed the Biodiversity-based Ecosystem Service Index (BBESI), a hierarchical framework for evaluating biodiversity contributions to regulating services, and then systematically identified representative indicators from the literature to operationalize this framework. Following PRISMA 2020 guidelines, 39 studies spanning tropical, temperate, and arid climatic regions were reviewed across six ecosystem functions: pollutant removal, nutrient retention, biological uptake, carbon storage, greenhouse gas regulation, and microclimate control. Indicators were considered representative when they demonstrated clear functional relevance to CW ecosystem processes and were repeatedly supported across the reviewed studies. These included microbial diversity metrics, nutrient-cycling functional genes, plant–microbe functional complementarity, and vegetation structural attributes. Each indicator was mapped to the Essential Biodiversity Variables (EBV) framework, spanning Genetic Composition, Species Traits, Community Composition, Ecosystem Structure, and Ecosystem Function to provide a standardized basis for biodiversity assessment, using a rule-based assignment that prioritized the biological signal of each indicator rather than its functional category. Although all EBV classes were represented, this pattern reflects the available literature and is influenced by uneven reporting across microbial and plant indicators and across climatic regions, which limits broad generalization of indicator strength. The BBESI offers a transferable framework because its EBV-aligned structure and commonly measured indicators allow application across diverse CW designs and environmental contexts provided that multiple EBV co-signals are present rather than reliance on single-indicator measurements, with flexibility for future integration of various quantitative weighting approaches. Full article

In 2022, Korea became the first country to introduce a climate change impact assessment (CCIA) system that requires prior analysis and evaluation of climate impacts for major development projects, delivering a relevant analysis and management framework for such purposes. This study reviews Korea’s CCIA system from a policy perspective, organizing its structural components, assessment procedures, and reporting methods according to the domains of greenhouse gas (GHG) mitigation and climate crisis adaptation. The system’s characteristics and assessment procedures of this system are also analyzed via a case study review of urban development projects. In the GHG mitigation category, emissions and absorptions should be investigated at each project stage and quantitative reduction amounts and targets established based on scientific and statistical evidence. Regarding climate crisis adaptation, regional climate risks should be analyzed and adaptation strategies for priority management areas developed based on impact prediction results. CO₂ concentrations recorded in Seoul’s central and background areas confirmed spatial differences in city-level GHG concentrations, proposing the CCIA’s potential practical use for enhancing future monitoring frameworks. To enhance the effectiveness of the CCIA and its consequences for future sustainability, the opinions of various stakeholders and linking the system with existing environmental impact (EIA) assessment frameworks are paramount. Full article

The aim of this paper is to investigate the measures adopted by higher education institutions (HEIs) for sustainable water management in university campuses. Rain and storm water harvesting and treatment, rain and storm water reuse, wastewater treatment and reuse and technologies for runoff reduction were found to be frequently undertaken. Sustainable approaches to water supply such as water-efficient appliances, irrigation algorithms and the use of drought-resistant plants have been adopted as well. In support, monitoring of consumed water and of rain and storm waters has been a widespread practice. Important considerations were given to the impact of the identified measures on campuses’ energy consumption and greenhouse gas emissions. Nature-based solutions, employment of renewable energies and sustainable disinfection methods are measures to prioritize. Some wastewater technologies may deserve priority in virtue of their positive contribution to circular economy. Drawbacks such as groundwater and soil contamination due to wastewater reuse and the release of pollutants from fertilized nature-based technologies were identified. Despite their variety, it must be noted that many of these measures have generally involved rather limited portions of campuses, taken more for demonstration or pilot/full-scale research purposes. Additional measures not identified in the current review—for instance the prevention of pollution from micropollutants and waste mismanagement—should be implemented to boost HEIs’ environmental sustainability. The findings of this review pave the way for a more structured implementation of water sustainability measures in university campuses. Full article

Nitrous oxide is a potent greenhouse gas, with N fertilizers being one of its major sources. Plant growth-promoting bacteria have been used to mitigate N₂O emissions by improving N use efficiency in plants. In addition, some of these microorganisms are capable of reducing N₂O to N₂, a process that could be further explored as a complementary mitigation strategy. This study aimed to test whether Azospirillum brasilense strains Ab-V5 and Ab-V6, and strain Wa3, as well as Nitrospirillum viridazoti strain BR 11145, already used in commercial inoculants for N-fertilized crops and known to carry the nosZ gene encoding nitrous oxide reductase, could act as biological sinks for this gas. In the pot experiment, soils fertilized with N and inoculated with N. viridazoti exhibited consistently lower N₂O emissions, but not when A. brasilense strains were used. The mitigation effect was observed both in bare soil (72% emission reduction) and in the presence of millet plants (60% emission reduction), confirming the ability of N. viridazoti strain BR 11145 to consume N₂O. In a field experiment conducted with maize, inoculation with N. viridazoti again reduced N₂O fluxes during the first two weeks after fertilization compared with the urea-only treatment. However, no significant differences were detected comparing emission factors, whose calculation requires consideration of the entire monitoring period, thereby adding more variability. While N₂O mitigation was observed, no significant effects of inoculation or N fertilization were found on maize growth or yield. Nonetheless, the consistent reduction in N₂O emissions achieved with N. viridazoti strain BR 11145 suggests that inoculants with this bacterium represent a promising biological sink for N₂O, offering a novel nature-based solution to enhance the sustainability of tropical crop management. Full article

Quantifying the time and space scale variability in air–sea fluxes is challenging. This study adopts tower-based in situ observations in the northern South China Sea (SCS) to evaluate widely used reanalysis and CO₂ flux products. For heat and momentum fluxes, three reanalysis products were considered: the fifth-generation European Centre for Medium-Range Weather Forecast reanalysis (ERA5), the NCEP Climate Forecast System Version 2 reanalysis (CFSv2), and third-generation Japanese Meteorological Agency reanalysis (JRA55). Comparisons of surface state variables show that these three reanalysis products generally agree well with observations on both the daily and monthly scales. On the daily scale, the correlation coefficients between observations and ERA5 exceed 0.93 for wind, air temperature, relative humidity, and longwave radiation. On the monthly scale, seasonal variations in wind, air temperature, and relative humidity are well captured. Nevertheless, the three reanalysis products all overestimate (underestimate) the latent (sensible) heat flux, with a root mean square error above 90.50 (33.35) ${\mathrm{W}/\mathrm{m}}^2$. For momentum fluxes, the three reanalysis datasets tend to underestimate 0.07∼0.08 ${\mathrm{N}/\mathrm{m}}^2$ with a high correlation coefficient above 0.71. In terms of CO₂ fluxes, the Multi-observation Carbon Assimilation System (MCAS), Surface Ocean CO₂ Atlas (SOCAT), and Global ObservatioN-based system for monitoring Greenhouse GAs (GONGGA) inversion CO₂ flux datasets were evaluated. SOCAT performs best with a correlation coefficient of 0.75, and GONGGA follows with 0.64, while MCAS demonstrates the lowest performance with a value of 0.36. In addition, the spatial patterns of the monthly mean surface CO₂ flux in the northern SCS illustrate significant discrepancies between MCAS, SOCAT, and GONGGA. These results can provide valuable insights for reducing uncertainties in air–sea flux products over coastal areas in the future. Full article

Methane (CH₄) is a potent greenhouse gas and a key target for near-term climate mitigation, yet major uncertainties remain in quantifying emissions from landfills, particularly in rapidly urbanizing regions of the Global South. Here, we present a systematic satellite-based assessment of CH₄ emissions from landfills and related sites across northern and central Brazil, based on plume detections from the Carbon Mapper public data portal. Using imaging spectroscopy data from the Earth Surface Mineral Dust Source Investigation (EMIT) onboard the International Space Station and the dedicated Tanager-1 satellite, we analyzed 40 plume detections across 16 sites in nine Brazilian states spanning the Amazon forest biome and the Cerrado transition region. An adaptive thresholding algorithm was applied to each detection to quantify plume strength (ppm·m³), areal extent, and recurrence across multiple overpasses. Our results reveal a strongly heavy-tailed distribution of emissions, with most sites exhibiting modest plume strengths in the 10⁶–10⁷ ppm·m³ range, while a small number of facilities dominated the upper tail. Two detections at Brasília (2.22 × 10⁸ and 2.14 × 10⁸ ppm·m³) and one at Marituba (1.66 × 10⁸ ppm·m³) were classified as super-emitters, exceeding all other sites by more than an order of magnitude. These facilities also demonstrated high persistence across overpasses, in contrast to smaller landfills such as Macapá and Boa Vista, where emissions were weaker (<10⁷ ppm·m³) and episodic. Regional contrasts were also evident: sites in the Cerrado transition zone, (e.g., Brasília, Campo Grande) generally showed stronger and more frequent emissions than those in the Amazon basin. These findings underscore the disproportionate role of a few persistent super-emitters in shaping the regional CH₄ budget. Targeted mitigation at these high-impact sites could yield rapid and cost-effective emission reductions, directly supporting Brazil’s commitments under the Paris Agreement and the Global CH₄ Pledge. More broadly, this study demonstrates the power of high-resolution satellite imaging spectroscopy for identifying, monitoring, and prioritizing CH₄ mitigation opportunities in the waste sector. Full article

Climate change mitigation involves carbon sequestration that can be supported by Voluntary Carbon Markets (VCMs) and counted as Nationally Determined Contributions (NDCs) in national climate change strategies. Integrating these allows for the determination of greenhouse gas (GHG) emissions and carbon sequestration at the national level. The case for Egypt and other nontropical dryland nations is made in this systematic review article through consideration of monitoring, reporting, and verification (MRV) protocol challenges and initiatives. Improvements are indicated based on the literature, encompassing the academic literature as well as organizational reports and governmental policy documents. Agricultural MRV protocols depending on soil organic carbon (SOC) measurements are specifically considered, delineating the challenges and barriers for SOC MRV methods. Considering the impacts of climate zones affecting soils and providing as much standardization as possible for MRV protocols will improve the accuracy and generalizability of data. Measurements in carbon sequestration monitoring based on SOC MRV protocols need to be informed by soil experts alongside climatologists and policymakers in a multidisciplinary approach. Full article