Search Results (427)

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 objective of this analysis was to compare the greenhouse gas (GHG) emissions from contemporary grazing cattle production with bison grazing, both modern and historical. The data sets used in this analysis were derived from existing research and conservation properties located outside of Manhattan, KS (USA), which are home to stocker cattle, cow–calf production (CCS), and grazing bison. For stocker cattle, 10 years of animal production data (2007–2016) from season-long stocking (SLS, grazing 156 d) and intensive early stocking systems (IES; 76 grazing d and 2× stocking density) were used for GHG calculations. Enteric CH₄, manure CH₄, and direct nitrous oxide emissions were estimated using the IPCC tier 2 methodology. Historic bison (HGB) enteric CH₄ estimates were calculated using a stocking density of 0.15 ha/animal and assuming that only 13% of grassland was used by bison each year. Within contemporary systems, IES had the lowest emissions (463.3 kg CO₂-eq./ha/yr), while SLS, CCS, and MGB had the highest estimates (494.7, 493.9, and 595.9 kg CO₂-eq./ha/yr, respectively). HGB had the lowest estimated annual emissions at 295.7 kg CO₂-eq./ha/yr. These results imply that the historic grazing baseline of this grassland system is lower but similar to that of contemporary grazing cattle in the Great Plains region. 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

Climate change is one of the most important environmental problems of the modern world. Without an effective solution to this problem, it is not possible to implement sustainable development. For this reason, in the European development strategies, including the European Green Deal (EGD), the reduction in greenhouse gas (GHG) emissions is one of the priorities. This also applies to sectoral strategies, including those related to agriculture. In this context, the monitoring of changes in GHG emissions becomes particularly important, and its key condition is an applicative estimation method, adapted to the available data and levels of assessment (globally, country, sector, economic unit). GHG emission calculations at the level of the agricultural sector are officially estimated by the state and non-governmental organisations. However, calculations at the level of the agricultural unit-farm remain a challenge due to the lack of detailed data or its incomplete scope to estimate GHG emissions. The other issue is the necessity of a representative data nature, taking into consideration the different profiles of various farms. The research focused on presenting a methodological approach to utilising FADN (Farm Accountancy Data Network) data for estimating GHG emissions at the farm level. The Intergovernmental Panel on Climate Change (IPCC) methodology was adopted to use available farm-level data. Some assumptions were needed to achieve this goal. The article presents the subsequent stages of GHG calculation using the FADN data. The results reveal significant differences in GHG emissions among farm types. The presented results indicated the primary sources of emissions from agriculture, including energy (e.g., fuel and electricity consumption), thus outlining the scope of action that should be taken to reduce emissions effectively. The study confirms that the method used helps estimate emissions at the farm level. Its application can lead to better targeting of climate policy in agriculture. 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

In this study, we selected the production processes and main products of three typical chemical enterprises in Shanghai, namely SH Petrochemical (part of the oil-refining sector), SK Ethylene, and HS Chlor-Alkali, to quantitatively assess the synergistic effects across technology, policy, and emission mechanisms. The localized air pollutant levels and greenhouse gas emissions of the three enterprises were calculated. The synergistic effects between the end-of-pipe emission reductions for air pollutants and greenhouse gas emissions were analyzed using the pollutant reduction synergistic and cross-elasticity coefficients, including technology comparisons (e.g., acrylonitrile gas incineration (AOGI) technology vs. traditional flare). Based on these data, we used the SimaPro software and the CML-IA model to conduct a life cycle environmental impact assessment regarding the production and upstream processes of their unit products. By combining the life cycle method and the scenario simulation method, we predicted the trends in the environmental impacts of the three chemical enterprises after the implementation of low-carbon development policies in the chemical industry in 2030. We also quantified the synergistic effects of localized air pollutant and greenhouse gas (GHG) emission reductions within the low-carbon development scenario by using cross-elasticity coefficients based on life cycle environmental impacts. The research results show that, for every ton of air pollutant reduced through end-of-pipe treatment measures, the HS Chlor-Alkali enterprise would increase its maximum CO₂ emissions, amounting to about 80 tons. For SK Ethylene, the synergistic coefficient for VOC reduction and CO₂ emissions when using AOGI thermal incineration technology is superior to that for traditional flare thermal incineration. The activities of the three enterprises had an impact on several environmental indicators, particularly the fossil fuel resource depletion potential, accounting for 69.48%, 53.94%, and 34.23% of their total environmental impact loads, respectively. The scenario simulations indicate that, in a low-carbon development scenario, the overall environmental impact loads of SH Petrochemical (refining sector), SK Ethylene, and HS Chlor-Alkali would decrease by 3~5%. This result suggests that optimizing the upstream power structure, using “green hydrogen” instead of “grey hydrogen” in hydrogenation units within refining enterprises, and reducing the consumption of electricity and steam in the production processes of ethylene and chlor-alkali are effective measures in reducing carbon emissions in the chemical industry. The quantification of the synergies based on life cycle environmental impacts revealed that there are relatively strong synergies for air pollutant and GHG emission reductions in the oil-refining industry, while the chlor-alkali industry has the weakest synergies. Full article

The maritime industry remains a significant contributor to global greenhouse gas (GHG) emissions. In this article, a systematic study has been performed on the alternative fuel emissions of large cargo ships under different route scenarios and propulsion systems. For this purpose, a set of key performance indicators (KPIs) are evaluated, including total equivalent CO₂ emissions (CO_2eq), CO_2eq emissions per unit of transport mass and CO_2eq emissions per unit of transport mass per distance. The emissions analysis demonstrates that Liquified Natural Gas (LNG) paired with Marine Gas Oil (MGO) emerges as the most viable short-term solution in comparison with the conventional fuel oil propulsion. Synthetic methanol (eMeOH) paired with synthetic diesel (eDiesel) is identified as the most promising long-term fuel combination. When comparing the European Union (EU) emission calculation system (FuelEU) with the International Maritime Organization (IMO) emission metrics, a discrepancy in emissions reduction outcomes has been observed. The IMO approach appears to favor methanol (MeOH) and liquefied natural gas (LNG) over conventional fuel oil. This is attributed to the fact that the IMO metrics do not consider unburned methane emissions (methane slip) and emissions in the production of fuels (Well-to-Tank). Full article

Machine learning (ML) models are widely used to analyze the spatiotemporal impacts of agricultural practices on environmental sustainability, including the contribution to global greenhouse gas (GHG) emissions. Management practices, such as organic amendment applications, are critical pillars of Climate-smart agriculture (CSA) strategies that mitigate GHG emissions while maintaining adequate crop yields. This study investigated the critical threshold of soil moisture level associated with soil CO₂ emissions from organically amended plots using the classification and regression tree (CART) algorithm. Also, the study predicted the short-term soil CO₂ emissions from organically amended systems using soil moisture and weather variables (i.e., air temperature, relative humidity, and solar radiation) using multilinear regression (MLR) and generalized additive models (GAMs). The different organic amendments considered in this study are biochar (2268 and 4536 kg ha⁻¹) and chicken and dairy manure (0, 224, and 448 kg N/ha) under a sweet corn crop in the greater Houston area, Texas. The results of the CART analysis indicated a direct link between soil moisture level and the magnitude of CO₂ flux emission from the amended plots. A threshold of 0.103 m³m⁻³ was calculated for treatment amended by biochar level I (2268 kg ha⁻¹) and chicken manure at the N recommended rate (CXBX), indicating that if the soil moisture is less than the 0.103 m³m⁻³ threshold, then the median soil CO₂ emission is 142 kg ha⁻¹ d⁻¹. Furthermore, applying biochar at a rate of 4536 kg ha⁻¹ reduced the soil CO₂ emissions by 14.5% compared to the control plots. Additionally, the results demonstrate that GAMs outperformed MLR, exhibiting the highest performance under the combined effect of chicken and biochar. We conclude that quantifying soil moisture thresholds will provide valuable information for the sustainable mitigation of soil CO₂ emissions. Full article

This research aims to calculate the Carbon Footprint for Organization of a plant manufacturing frozen processed seafood and propose strategies to reduce greenhouse gas (GHG) emissions following the Net-Zero Pathway, using 2024 as the baseline year. The findings indicate that Scope 1 emissions amounted to 12,685 tons of CO₂ eq, Scope 2 emissions totaled 15,403 tons of CO₂eq, and Scope 3 emissions reached 31,564 tons of CO₂eq, leading to a combined total of 59,652 tons of CO₂eq across all scopes, with an additional 34,027 tons of CO₂eq from other GHG sources. To achieve net-zero emissions by 2050, annual reductions of 3.46% per category are required. The short-term target for 2028f aims to reduce emissions to 10,929 tons of CO₂eq for Scope 1, 13,270 tons of CO₂eq for Scope 2, and 27,194 tons of CO₂eq for Scope 3, resulting in total emissions of 51,392 tons of CO₂eq. The proposed reduction strategies include optimizing Scope 1 emissions by preventing leaks in R507 refrigerant systems, replacing corroded pipelines, installing shut-off valves, and switching to low-GHG refrigerants. For Scope 2, measures focus on reducing electricity consumption through energy conservation initiatives, carrying out regular machinery maintenance, installing Variable Speed Drives (VSDs), upgrading to high-efficiency motors, and integrating renewable energy sources such as solar power. For Scope 3, emissions from raw material procurement can be minimized by sourcing from certified suppliers with established product carbon footprints, prioritizing carbon reduction labeling, and selecting nearby suppliers to reduce transportation-related emissions. These strategies will support the organization in achieving carbon neutrality and progressing toward the net-zero goal. Full article

Ship carbon-emission monitoring is critical for implementing the IMO’s GHG reduction strategy. This study comprehensively introduces four methods for ship carbon monitoring and carbon calculation and systematically compares four vessel CO₂-monitoring methodologies, assessing their accuracy, influencing factors, real-time performance, and regulatory applicability. The analysis of China’s current carbon supervision framework informs proposed enhancements for low-carbon shipping governance. 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

As the population increases, the growing demand for residential housing escalates construction activities, significantly impacting global warming by contributing 42% of primary energy use and 39% of global greenhouse gas (GHG) emissions. This study addresses a gap in research on lifecycle assessment (LCA) for Indian residential buildings by evaluating the full cradle-to-grave carbon footprint of a typical single-family house in Northern India. A BIM-based LCA framework was applied to a 110 m² single-family dwelling over a 60-year life span. Operational use performance and climate analysis was evaluated via cove tool. The total carbon footprint over a 60-year lifespan was approximately 5884 kg CO₂e, with operational energy use accounting for about 87% and embodied carbon approximately 11%. Additional impacts came from maintenance and replacements. Energy usage was calculated as 71.76 kWh/m²/year and water usage as 232.2 m³/year. Energy consumption was the biggest driver of emissions, but substantial impacts also stemmed from material production. Cement-based components and steel were the largest embodied carbon contributors. Under the business-as-usual (BAU) scenario, the operational emissions reach approximately 668,000 kg CO₂e with HVAC and 482,000 kg CO₂e without HVAC. The findings highlight the necessity of integrating embodied carbon considerations alongside operational energy efficiency in India’s building codes, emphasizing reductions in energy consumption and the adoption of low-carbon materials to mitigate the environmental impact of residential buildings. Future work should focus on the dynamic modeling of electricity decarbonization, improved regional datasets, and scenario-based LCA to better support India’s transition to net-zero emissions by 2070. Full article

Land managers across the United States (U.S.) are developing plans to mitigate climate change. Effective implementation and monitoring of these climate action plans require standardized methods and timely, accurate geospatial data at appropriate resolutions. Despite the abundance of geospatial and statistical data in the U.S., a significant gap remains in translating these data into actionable insights. To address this gap, we developed the Land Emissions and Removals Navigator (LEARN), an online tool that automates subnational greenhouse gas (GHG) inventories of forests and trees in nonforest lands using a standardized analytical framework consistent with national and international guidelines. LEARN integrates multiple datasets to calculate land cover and tree canopy changes, delineate areas of forest disturbance, and estimate carbon emissions and removals. To demonstrate the application of LEARN, this paper presents case studies in Jefferson County, Washington; Montgomery County, Maryland; and federally owned forests across the conterminous U.S. Our results highlight LEARN’s capacity to provide localized insights into carbon dynamics, enabling subnational entities to develop tailored climate strategies. By enhancing accessibility to standardized data, LEARN empowers community land managers to more effectively mitigate climate change. Future developments aim to expand LEARN’s scope to cover nonforest landscapes and incorporate additional decision-making functionalities. Full article

Climate change has driven global awareness of environmental issues, leading to the adoption of clean technologies aimed at reducing Greenhouse Gas (GHG) emissions. An effective method to assess environmental mitigation is the quantification of the Product Carbon Footprint (PCF) in the Life Cycle Assessment (LCA) of production processes. In the oil extraction industry, artificial lift systems use electro submersible pumps (ESPs) that can now incorporate new operating principles based on permanent magnet motors (PMMs) and CanSystem (CS) as an alternative to traditional normal induction motors (NIMs) and can help lower the carbon footprint. This study compares the PCF of ESPs equipped with PMMs and CS versus NIMs, using LCA methodologies in accordance with ISO 14067:2018 for defining the Functional Unit (FU) and ISO 14064-1:2019 to calculate the GHG inventory and the amount of CO₂ equivalent per year. The analysis spans five key stages and 14 related activities. For ESPs with NIMs, this study calculated 999.9 kg of raw materials, 1491.66 kW/h for manufacturing and storage, and 5.77 × 10⁴ kW/h for use. In contrast, ESPs with PMMs and CS required 656 kg of raw materials and consumed 4.44 × 10⁴ kW/h during use, resulting in an 23% reduction in energy consumption. This contributed to an 21.9% decrease in the PCF. The findings suggest that PMMs and CS offer a sustainable solution for reducing GHG emissions in oil extraction processes globally. Full article