Search Results (365)

Mining (1) operations in remote areas (2) face significant challenges related to energy supply, high fuel costs, and limited infrastructure. This study investigates the potential for achieving energy independence (3) and resilience (4) in such environments through the integration of renewable energy sources (5) and battery–electric mining equipment. Using the “Studena Vrila” underground bauxite mine as a case study, a comprehensive techno-economic and environmental analysis was conducted across three development models. These models explore incremental scenarios of solar and wind energy adoption combined with electrification of mobile machinery. The methodology includes calculating levelized cost of energy (LCOE), return on investment (ROI), and greenhouse gas (GHG) reductions under each scenario. Results demonstrate that a full transition to RES and electric machinery can reduce diesel consumption by 100%, achieve annual savings of EUR 149,814, and cut GHG emissions by over 1.7 million kg CO₂-eq. While initial capital costs are high, all models yield a positive Net Present Value (NPV), confirming long-term economic viability. This research provides a replicable framework for decarbonizing mining operations in off-grid and infrastructure-limited regions. Full article

Electricity is a significant factor in the life cycle of many products, so the reliability of greenhouse gas (GHG) emissions data is crucial. The article presents publicly available sources of emission factors representative of Poland. The aim of the study is to assess their strengths and weaknesses in the context of the calculation requirements of carbon footprint analysis in accordance with the GHG Protocol. The article presents the results of carbon footprint calculations for different ranges of emissions in the life cycle of 1 kWh of electricity delivered to a hypothetical organization. Next, a discussion on the quality of the emissions factors has been provided, taking account of data quality indicators. It was concluded that two of the emissions factors that are compared—those based on the national consumption mix and the residual mix for Poland—have been recognized as suitable for use in carbon footprint calculations. Beyond the calculation results, the research highlights the significance of the impact of the selection of emissions factors on the reliability of environmental analysis. The article identifies methodological challenges, including the risk of double counting, limited transparency, methodological inconsistency, and low correlation of data with specific locations and technologies. The insights presented contribute to improving the robustness of carbon footprint calculations. Full article

This article examines the role of managed ecosystems, and particularly forests, in achieving carbon neutrality in Russia. The range of estimates of Russia’s forests’ net carbon balance in different studies varies by up to 7 times. The. A comparison of Russia’s National GHG inventory data for 2023 and 2024 (with the latter showing 37% higher forest sequestration) is presented and explained. The possible changes in the Long-Term Low-Emission Development Strategy of Russia (LT LEDS) carbon neutrality scenario due to new land use, land use change and forestry (LULUCF) data in National GHG Inventory Document (NID) 2024 are discussed. It is demonstrated that the refined net carbon balance should not impact the mitigation ambition in the Russian forestry sector. An assessment of changes in the drafts of the Operational plan of the LT LEDS is presented and it is concluded that its structure and content have significantly improved; however, a delay in operationalization nullifies efforts. The article highlights the problem of GHG emissions increases in forest fires and compares the gap between official “ground-based” and Remote Sensing approaches in calculations of such emissions. Considering the intention to increase net absorption by implementing forest carbon projects, the latest changes in the regulations of such projects are discussed. The limitations of reforestation carbon projects in Russia are provided. Proposals are presented for the development of the national forest policy towards increasing the net forest carbon absorption, including considering the projected decrease in annual net absorption by Russian forests by 2050. The role of government and private investment in improving the forest management of structural measures to adapt forestry to modern climate change and the place of forest climate projects need to be clearly defined in the LT LEDS. Full article

The transportation sector significantly contributes to greenhouse gas (GHG) emissions and remains a key research focus on emission quantification and mitigation. Although numerous models exist for estimating vehicle-based emissions, most lack accuracy at regional scales, particularly in remote or underdeveloped areas, including backcountry national parks and mountainous regions lacking basic infrastructure. This study addresses that gap by developing and applying a terrain-adjusted, segment-based methodology to estimate GHG emissions from tourist vehicles in Altai Tavan Bogd National Park, one of Mongolia’s most remote protected areas. The proposed method uses Tier 1 IPCC emission factors but incorporates field-segmented route analysis, vehicle categorization, and terrain-based fuel adjustments to achieve a spatially disaggregated Tier 1 approach. Results show that carbon dioxide (CO₂) emissions increased from 118.7 tons in 2018 to 2239 tons in 2024. Tourist vehicle entries increased from 712 in 2018 to 13,192 in 2024, with 99.1% of entries occurring between May and October. Over the same period, cumulative methane (CH₄) and nitrous oxide (N₂O) emissions were estimated at 300.9 kg and 45.75 kg, respectively. This modular approach is especially suitable for high-altitude, infrastructure-limited regions where real-time emissions monitoring is not feasible. By integrating localized travel patterns with global frameworks such as the IPCC 2006 Guidelines, this model enables more precise and context-sensitive GHG estimates from vehicles in national parks and similar environments. Full article

Personal lifestyle choices contribute up to 75% of national emissions and yet the greenhouse gas (GHG) inventories included in the National Inventory Report (NIR) of Canada provide limited insight on these choices. Better insight can be found using carbon footprint calculators that estimate individual emissions; however, they vary in regard to their input parameters, output data, and calculation methods. This study assessed five calculators, which are popular with the public, or compatibility with the Canadian NIR. A quantitative scoring matrix was developed to assess the output depth, academic proficiency, and effectiveness of the calculators to inform lifestyle changes, alongside NIR alignment. The results showed that the calculator with the overall highest cumulative score across all the comparative criteria was the one offered by Carbon Footprint Ltd. The other calculators that scored highly include CoolClimate Calculator and Carbon Independent. The potential of the calculators in regard to informing low-carbon lifestyles can be improved through the incorporation of more depth in terms of capturing the purchase information of goods and services and providing detailed secondary information to users, including mitigation strategies and carbon offset options. The main driver of incompatibility between the calculator tools and the NIR was the different approaches taken to the emissions inventory, with the NIR using a territorial framework and the calculators being consumption driven. The outcomes of this study demonstrate a global need for the evolution of NIR structuring to increase its relatability with citizens and for the improved standardization of publicly available tools. Full article

Cheese production is an ancient practice that is associated with the food and cultural identity of different peoples. There are over 500 cheese types globally, including 207 with protected denomination of origin (PDO) and 70 with protected geographical indication (PGI) status in the European Union (EU). Each cheese has various biochemical compositions, production methods, and maturation environments. This study has provided a critical review of the environmental impacts of cheese production, focusing on energy consumption, greenhouse gas (GHG) emissions, and the integration of renewable energy sources as sustainable strategies for this sector. Based on case studies and life cycle assessment (LCA) methodologies, the analysis revealed significant variability in energy use (3.0 to 70.2 MJ/kg) and GHG emissions (up to 22.13 kg CO₂ eq/kg), influenced by factors such as the cheese type, production complexity, system boundaries, and the technological or geographical context. Particular attention was given to heat treatment, refrigeration, and maturation processes, which contribute substantially to the overall energy footprint. The paper also discusses the methodological challenges in LCA studies, including the role of co-product allocation and database limitations. Finally, strategic renewable energy options, such as biogas recovery and solar thermal integration, are discussed as sustainable alternatives to reduce the environmental footprint of the dairy sector and support its sustainability. Full article

Livestock farming is a vital component of global food security, yet it remains a major contributor to greenhouse gas (GHG) emissions, particularly methane (CH₄), which has a global warming potential 28 times greater than carbon dioxide (CO₂). This review provides a comprehensive synthesis of current knowledge surrounding the sources, biological mechanisms, and mitigation strategies related to CH₄ emissions from ruminant livestock. We first explore the process of methanogenesis within the rumen, detailing the role of methanogenic archaea and the environmental factors influencing CH₄ production. A thorough assessment of both direct and indirect methods used to quantify CH₄ emissions is presented, including in vitro techniques (e.g., syringe method, batch culture, RUSITEC), in vivo techniques (e.g., respiration chambers, Greenfeed, laser CH₄ detectors), and statistical modeling approaches. The advantages and limitations of each method are critically analyzed in terms of accuracy, cost, feasibility, and applicability to different farming systems. We then examine a wide range of mitigation strategies, organized into four core pillars: (1) animal and feed management (e.g., genetic selection, pasture quality improvement), (2) diet formulation (e.g., feed additives such as oils, tannins, saponins, and seaweed), (3) rumen manipulation (e.g., probiotics, ionophores, defaunation, vaccination), and (4) manure management practices and policy-level interventions. These strategies are evaluated not only for their environmental impact but also for their economic and practical viability in diverse livestock systems. By integrating technological innovations with sustainable agricultural practices, this review highlights pathways to reduce CH₄ emissions while maintaining animal productivity. It aims to support decision-makers, researchers, and livestock producers in the global effort to transition toward climate-smart, low-emission livestock farming. Full article

Methods for the improvement of regional lignocellulosic resources (wood and agriculture waste) were studied and analyzed using blends with optimized compositions and a selective pretreatment of the blends using microwaves to enhance their thermochemical conversion and energy production efficiency. A batch-size pilot device was used to provide the thermochemical conversion of biomass blends of different compositions, analyzing the synergy of the effects of thermal and chemical interaction between the components on the yield and thermochemical conversion of volatiles, responsible for producing heat energy at various stages of flame formation. To control the thermal decomposition of the biomass, improving the flame characteristics and the produced heat, a selective pretreatment of blends using microwaves (2.45 GHz) was achieved by varying the temperature of microwave pretreatment. Assessing correlations between changes in the main characteristics of pretreated blends (elemental composition and heating value) on the produced heat and composition of products suggests that selective MW pretreatment of biomass blends activates synergistic effects of thermal and chemical interaction, enhancing the yield and combustion of volatiles with a correlating increase in produced heat energy, thus promoting the wider use of renewable biomass resources for sustainable energy production by limiting the use of fossil fuels for heat-energy production and the formation of GHG emissions. Full article

Agriculture faces a dual challenge in the context of climate change, serving as both a significant contributor to greenhouse gas (GHG) emissions and a sector highly vulnerable to its impacts. Addressing this requires a transition toward climate-resilient agriculture (CRA). Emerging technologies, including geospatial tools (e.g., Geographic Information Systems (GISs) and remote sensing (RS)), as well as artificial intelligence (AI), offer promising methods to support this transition. However, their individual capabilities, limitations, and appropriate applications are not always well understood or clearly delineated in the literature. A common issue is the frequent overlap between GISs and RS, with many studies assessing GIS contributions while concurrently employing RS techniques, without explicitly distinguishing between the two (or vice versa). In this sense, the objective of this review is to conduct a critical analysis of the existing state of the art in terms of the distinct roles, limitations, and complementarities of GISs, RS, and AI in advancing CRA, guided by an original definition we propose for CRA (structured around three key dimensions and their corresponding targets). Furthermore, this review introduces a synthesis matrix that integrates both the individual contributions and the synergistic potential of these technologies. This synergy-focused matrix offers not just a summary, but a practical decision support matrix that could be used by researchers, practitioners, and policymakers in selecting the most appropriate technological configuration for their objectives in CRA-related work. Such support is increasingly needed, especially considering that RS and AI have experienced exponential growth in the past five years, while GISs, despite being the more established “big brother” among these technologies, remain underutilized and is often insufficiently understood in agricultural applications. Full article

Livestock contributes to global warming through greenhouse gas (GHG) emissions. Reducing these emissions is an ongoing challenge for the small ruminant sector. Despite its significant role in national economies, limited studies on the carbon footprint (CF) of dairy small ruminants in Mediterranean countries exist. The study aimed to achieve the following: (a) estimate the GHG emissions of eleven semi-extensive sheep and goat farms in a mountainous region of southern Greece, using the Tier 1 and Tier 2 methodologies; (b) compare the outcomes of both methods; and (c) calculate farms’ CF, as a means of their environmental impact evaluation. All on-farm activities (except machinery or medicine use) related to sheep or goat production were considered to estimate GHG emissions. The results show differences between Tier 1 and Tier 2 estimates, reflecting the simplified computational approach of Tier 1. The average CF values estimated via Tier 1 for goat and sheep farms were 2.12 and 2.87 kg CO₂-eq./kg FPCM, respectively. Using Tier 2, these values increased to 2.73 and 3.99 kg CO₂-eq./kg FPCM. To mitigate environmental impact, farms could enhance productivity by improving herd management and feeding strategies. Full article

The imperative to decarbonize global energy systems and enhance energy security necessitates a transition towards ecofuels, broadly classified as biofuels, waste-derived fuels, and electrofuels (e-Fuels). The primary goal of this review is to provide a holistic and comparative evaluation of these three pivotal ecofuel pillars under a unified framework, identifying their strategic niches in the energy transition by critically assessing their interconnected technical, economic, and policy challenges. It offers a comparative dissection of inherent resource constraints, spanning biomass availability, the immense scale of renewable electricity required for e-Fuels, sustainable carbon dioxide (CO₂) sourcing, and the complexities of utilizing non-biodegradable wastes, identifying that true feedstock sustainability and holistic lifecycle management are paramount, cross-cutting limitations for all pathways. This review critically highlights how the current global reliance on fossil fuels for electricity production (approx. 60%) and the upstream emissions embodied in renewable energy infrastructure challenge the climate neutrality claims of ecofuels, particularly e-Fuels, underscoring the necessity for comprehensive well-to-wheels (WtW) lifecycle assessments (LCAs) over simpler tank-to-wheels (TtW) approaches. This perspective is crucial as emerging regulations demand significant greenhouse gas (GHG) emission reductions (70–100%) compared to fossil fuels. Ultimately, this synthesis argues for a nuanced, technologically neutral deployment strategy, prioritizing specific ecofuels for hard-to-abate sectors, and underscores the urgent need for stable, long-term policies coupled with robust and transparent LCA methodologies to guide a truly sustainable energy transition. Full article

This research discusses the application of Sentinel satellite data for monitoring air pollution in port areas. The Scopus and Web of Science databases were comprehensively analysed to identify relevant peer-reviewed literature and assess research publications. The systematic literature review was conducted using the PRISMA methodology for inclusion and exclusion criteria. A total of 519 articles were identified from which 70 relevant articles were finally selected and discussed in detail for their relevancy to the maritime environment. Sentinel-5P was found to have several use cases in the literature that are useful for measuring maritime air pollution, while Sentinel 1 and 2 were mainly used for other applications like oil spills and water quality, respectively. Although aerial surveys, like those conducted using unmanned aerial vehicles (UAVs), offer more precise estimates of greenhouse gases (GHGs), they are only useful for certain applications because the technology is costly and impractical for daily monitoring. Satellite-based sensors are the state of the art for obtaining remote observations of emissions in open sea. Sentinel-5P measurements offer daily data for air quality monitoring, which supports ground surveys to identify and penalize major emission sources and consequently support environmental management in accordance with contemporary policies. Pollutant concentration levels for the maritime sector can be analysed both spatially and temporally using Sentinel-5P data. In the future, addressing the limitations of the Sentinel-5P data, such as underestimation and source separation, could improve air pollution assessments. Full article

Understanding the trends and drivers of greenhouse gases (GHGs) is vital to making effective climate mitigation strategies and benefiting human health. In this study, we investigate carbon dioxide (CO₂) trends in the top three emitting states in the U.S. (i.e., Texas, California, and Florida) using column-averaged CO₂ concentrations (XCO₂) from the Greenhouse Gases Observing Satellite (GOSAT) from 2010 to 2022. Annual XCO₂ enhancements are derived by removing regional background values (XCO_{2, enhancement}), and their interannual changes (ΔXCO_{2, enhancement}) are analyzed against key influencing factors, including population, gross domestic product (GDP), nonrenewable and renewable energy consumption, and normalized vegetation difference index (NDVI). Overall, interannual changes in socioeconomic factors, particularly GDP and energy consumption, are more strongly correlated with ΔXCO_{2, enhancement} in Florida. In contrast, NDVI and state-specific environmental policies appear to play a more influential role in shaping XCO₂ trends in California and Texas. These differences underscore the importance of regionally tailored approaches to emissions monitoring and mitigation. Although renewable energy use is increasing, CO₂ trends remain primarily influenced by nonrenewable sources, limiting progress toward atmospheric CO₂ reduction. Full article

Intergovernmental Panel on Climate Change (IPCC) guidelines have been standardized and widely used to calculate methane (CH₄) emissions from paddy fields. The emission factor (EF) is a key parameter in these guidelines, and it is different for each location globally and regionally. However, limited studies have been conducted to measure locally specific EFs (EFlocal) through on-site assessments and modeling their spatial distribution effectively. This study aims to investigate the potential of multisensor satellite data to develop a spatial model of CH₄ emission estimation on rice paddy fields under different water management practices, i.e., continuous flooding (CF) and alternate wetting and drying (AWD) in Subang, West Java, Indonesia. The model employed the national EF (EFnational) and EFlocal using the IPCC guidelines. In this study, we employed the multisensor satellite data to derive the key parameters for estimating CH₄ emission, i.e., rice cultivation area, rice age, and EF. Optical high-resolution images were used to delineate the rice cultivation area, Sentinel-1 SAR imagery was used for identifying transplanting and harvesting dates for rice age estimation, and ALOS-2/PALSAR-2 was used to map the water regime for determining the scaling factor of the EF. The closed-chamber method has been used to measure the daily CH₄ flux rate on the local sites. The results revealed spatial variability in CH₄ emissions, ranging from 1–5 kg/crop/season to 20–30 kg/crop/season, depending on the water regime. Fields under CF exhibited higher CH₄ emissions than those under AWD, underscoring the critical role of water management in mitigating CH₄ emissions. This study demonstrates the feasibility of combining remote sensing data with the IPCC model to spatially estimate CH₄ emissions, providing a robust framework for sustainable rice cultivation and greenhouse gas (GHG) mitigation strategies. Full article

The intensive use of nitrogen (N) fertilizers in maize (Zea mays L.) cropping in sub-Saharan Africa (SSA) contributes significantly to nitrous oxide (N₂O) emissions. Due to limited data on emissions and emission factors (EFs) in SSA, this study investigates GHG emissions and proposes EFs under different fertilization regimes in maize cropping in Burkina Faso (West Africa). A randomized complete block design was used with five treatments: (i) control: no fertilizer (CK), (ii) cattle manure (M), (iii) chemical fertilizer (NPK), (iv) a combination of chemical fertilizer and cattle manure (NPKM) at the national recommended rate, and (v) farmers’ practices, which involve chemical fertilizer combined with manure at the farmers’ rate (NPKM+). Cumulative N₂O emissions varied significantly among treatments (p < 0.05), with the highest under NPKM (2.86 kg N₂O-N ha⁻¹) and the lowest under CK (1.93 ± 0.11 kg N₂O-N ha⁻¹). NPKM also showed the highest methane (CH₄) uptake (−0.62 kg CH₄-C ha⁻¹; p < 0.001), while CK exhibited an increasing trend (0.74 kg CH₄-C ha⁻¹). The highest N₂O EF was recorded for NPK (0.37 ± 0.05%), 63% lower than the Intergovernmental Panel on Climate Change default value. Although NPKM treatment resulted in the highest global warming potential and maize yield, it also achieved the lowest greenhouse gas intensity per unit of yield, highlighting a more efficient trade-off between productivity and climate impact with nitrogen fertilizer use. NPKM+ was the most effective in maintaining high maize productivity with lower yield-scaled N₂O emissions and GHG intensity. These findings suggest that an integrated approach combining organic and inorganic fertilizers can mitigate soil GHG emissions. Further research is needed to refine climate-smart fertilizer combinations for sustainable maize production in SSA. Full article