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Copyright of Plants, People, Planet is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To establish if highly eutrophic lakes generate higher N2O emissions than non-eutrophic aquatic environments in New Zealand, we monitored N2O emissions from hypereutrophic Lake Horowhenua, near Levin, and the oligotrophic Turitea dam reservoir, near Palmerston North, used as control. Based on more than 12 months of monitoring data, N2O emissions from Lake Horowhenua were estimated to −0.05–6.93 mg-N2O·m−2·d−1 (n = 66), with a median of 0.30 mg-N2O·m−2·d−1. At the Turitea reservoir, N2O emissions ranged from −0.02–1.51 mg-N2O·m−2·d−1 with a median of 0.15 mg-N2O·m−2·d−1 (n = 53). No correlation was found between N2O emissions and the water temperature, sunlight, dissolved oxygen, nutrient concentration or chlorophyll a. When extrapolating the emission data to NZ, we estimated NZ lakes could release 83 kt of N2O as CO2eq each year, which is low in comparison to other sectors such as agriculture. Following the Intergovernmental Panel on Climate Change methodology, the N2O emission factor for Lake Horowhenua was estimated at 0.0019 kg N2O-N per kg of N-NO3− input into the lake. [ABSTRACT FROM AUTHOR]

The shipping sector is one of the major contributors to greenhouse gas (GHG) emissions. We aimed to calculate GHG emissions categorized by ship type for all vessels registered in South Korea. Hence, for the first time in South Korea, a bottom-up method based on ship activity data was employed, estimating energy consumption and emissions by ship type. Data from ships registered from 2019 to 2021 were collected and reclassified by ship type, and operational profiles were developed. Based on these profiles, the emissions of major GHGs, including CO2, CH4, and N2O, were estimated for the 3-year period. Cargo ships accounted for the highest percentage of annual fuel consumption, approximately 62.7%–64.7% of the total fuel consumption for all ships. The GHG emissions were calculated to be an average of 4.644 million tonCO2e, which is approximately 6.5 times higher than those from oil tankers (0.710 million tonCO2e), the second-highest emitter. This highlights the need for intensified GHG reduction measures specifically targeting cargo ships, providing clear evidence for prompt and enhanced implementation. The research findings are expected to be utilized as substantiated data for developing specific and systematic GHG reduction policies tailored to each ship type. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Natural Hazards & Environment (JNHE) / Doğal Afetler ve Çevre Dergisi (DACD) is the property of Artvin Coruh University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In South Korea, Agriculture, Forestry, and Other Land Use (AFOLU) collates greenhouse gas (GHG) inventories. However, the settlement category lacks a clear definition of land use and activity data. This study proposed a method for examining the settlement spatial extent and constructing activity data to estimate GHG emissions and absorption as a pilot calculation, as well as to provide data for land use classification. Utilizing cadastral maps (CDMs), settlement spatial extents were determined, with settlements occupying approximately 11% of the total land area in 2019, or 9% excluding overlaps. Activity data for settlements were established through a sampling method and analysis of aerial orthoimages from 2000 and 2019. After removing overlaps with digital forest type maps and smart farm maps, settlement activity data covered approximately 18.47% based on CDMs, or 12.66% excluding overlaps. In 2019, CO2 emissions and absorptions were estimated at 622.16 ktCO2yr−1 based on CDMs and 242.16 ktCO2yr−1, excluding overlaps. To enhance GHG inventory calculation consistency and compliance with TACCC principles, clear spatial extents for settlements must be established. This entails constructing activity data and assessing GHG inventories accordingly. GHG inventory statistics should also inform future nationally determined contributions. [ABSTRACT FROM AUTHOR]

The global steel industry is integral to the development of modern infrastructure, yet it stands as one of the most significant contributors to greenhouse gas (GHG) emissions worldwide. This dichotomy brings forth the imperative for an in-depth analysis of GHG inventory practices and the pursuit of sustainable production methods. This mini-review paper addresses the current methodologies for GHG accounting within the steel sector, emphasizing the critical role of accurate and transparent emissions data as the basis for effective climate change mitigation strategies. Evaluating the prevalent carbon-intensive blast furnace-basic oxygen furnace (BF-BOF) production route, this paper contrasts traditional practices with innovative reduction initiatives, particularly those aligned with the emergence of green steel. We delve into the advancements in electric arc furnace (EAF) technology, direct reduced iron (DRI) processes utilizing green hydrogen, and the potential of carbon capture, utilization, and storage (CCUS) systems. The analysis extends to a critical examination of the challenges and opportunities these technologies face, including economic viability, scalability, and the readiness of energy infrastructure to support such a transition. Further, this review highlights the significance of verification and validation in reinforcing the credibility of GHG inventories. We scrutinize the materiality of reported emissions in the context of evolving regulatory frameworks and stakeholder expectations, stressing the need for standardized and rigorous assurance practices. Highlights: • The global steel industry is a major contributor to greenhouse gas emissions, and there is a need for accurate emissions data to address climate change. • Transitioning to green steel production, using technologies like electric arc furnace (EAF) and direct reduced iron (DRI) with green hydrogen, can significantly reduce emissions. • Verification and validation of greenhouse gas inventories are crucial for credibility in the context of evolving regulatory frameworks. [ABSTRACT FROM AUTHOR]

Greenhouse gases trap heat in the atmosphere, causing the Earth's surface temperature to rise. The main greenhouse gases are carbon dioxide, methane, nitrous oxide, perfluorocarbons, hydrofluorocarbons, and sulfur hexafluoride. Human activities are increasing greenhouse gas concentrations rapidly, which is causing global climate change. Global climate change is increasing environmental and public health problems. To reduce greenhouse gas emissions, it is necessary to identify where the emissions are coming from, develop a plan to reduce them, and then implement and monitor the plan to ensure that emissions are actually reduced. Anthropogenic global climate change has large and increasingly adverse economic effects. Cities emit the most greenhouse gas due to fossil fuel burning and power usage. The four major greenhouse gas emitters are energy, transportation, waste management, and urban land use sectors. Organizations should prepare action plans to lower their greenhouse gas emissions and stop the worst consequences of climate change. These action plans require companies and local authorities to submit their greenhouse gas emissions reports on a yearly basis. A greenhouse gas emissions management system includes several processes and tools created by organizations to understand, measure, monitor, report, and validate their greenhouse gas emissions. Two of the most widely adapted frameworks for greenhouse gases inventory reporting are ISO 14064 and the greenhouse gas protocol. This review paper aims to identify some of the key points of GHG inventory preparation and mitigation strategies. [ABSTRACT FROM AUTHOR]

The land use sector is a crucial pillar in achieving the EU climate goals set for 2050. A significant part of the climate change mitigation potential of the land use sector is inherent to agroforestry. Windbreaks are important agroforestry elements of Hungarian agricultural landscapes. The new and improved agroforestry subsidy system may positively affect the extension of windbreaks in Hungary, making it relevant to assess their carbon sequestration potential. In our study, we examined the carbon sequestration of windbreaks at the country level and in two sample areas of 24,000 hectares based on National Forestry Database volume stock data, as well as information collected from the Hungarian Forest Cover Map using orthophoto interpretation. We estimated the total annual carbon sequestration realized in the aboveground biomass pool of Hungarian windbreaks to be −33.1 ktCO2/year, which is 0.67% of the total annual carbon sequestration of the aboveground biomass pool of all Hungarian forests, as reported by the Hungarian Greenhouse Gas Inventory. On the other hand, according to our estimate, the weighted mean annual carbon sequestration in the aboveground biomass of windbreaks was −2.4 tCO2/ha/year in the 2010–2020 period. This value is very close to the average mean annual carbon sequestration per hectare value of all forests, as reported by the Hungarian Greenhouse Gas Inventory. This means that planting a given area of windbreaks in between agricultural fields can have similar climate change mitigation effects as planting forests in the same given area. [ABSTRACT FROM AUTHOR]

Improvements in the calculated monitoring system (CMS) of anthropogenic emissions of greenhouse gases (GHG) and black carbon (BC) in the Russian Federation are carried out in three main areas: identification of gaps in the statistical information necessary for estimating emissions; development of updated national coefficients for certain source categories; automation and digitalization of monitoring data. The detailed statistical information missing in the monitoring system determines the accuracy of estimates for more than 80% of total GHG emissions and almost 30% of GHG removals. The coefficients planned to be developed for estimating emissions from key categories until 2024 will make it possible to clarify more than 30% of total net emissions in Russia. Subject to successful digitalization, the Russian CRM of anthropogenic GHG flows can take the leading positions in the world in terms of the quality of the data provided. The country is creating an integrated system of emissions and atmospheric transport of BC, which includes subsystems of calculated monitoring of BC emissions on the territory of Russia and neighboring countries, model assessment of atmospheric transport and impact on the Arctic region. The improved CMS of anthropogenic GHG and BC fluxes is the central element of the most important innovative project of national importance to create a unified monitoring system for climate-active substances and the basis for planning measures to reduce emissions and increase GHG removals and evaluate their effectiveness. [ABSTRACT FROM AUTHOR]

Background: Five ministries are involved in estimating the greenhouse gas (GHG) inventory in the South Korean land use, land-use change, and forestry (LULUCF) sectors. However, these ministries have not established a consistent land classification standard between land-use categories. Therefore, the GHG inventory is estimated at the approach 1 level with no spatial clarity between land-use categories. Moreover, the settlements category is not estimated because activity data and the spatial scope are lacking. This study proposed a methodology for constructing a land-use change (LUC) matrix in the LULUCF sector for improving approach level and estimating the GHG inventory in the settlements. Result: We examined 10 sets of spatiotemporal data in South Korea to construct a LUC matrix. To maintain consistency in the spatial land classification, we constructed a LUC matrix using cadastral maps, which provide useful data for consistent land-use classification in South Korea. The LUC matrix was divided into remaining and land-converted settlements between 2005 and 2019 with estimated areas of 878,393.17 and 203,260.42 ha, respectively. CO2 emissions, according to Intergovernmental Panel Climate Change's Guideline Tier 1, were estimated at 18.94 MtCO2 for 15 years, with an annual CO2 emission of 1.26 MtCO2 yr−1. CO2 emission by land conversion type was found to be the largest at 16.93 MtCO2 in the case of forest converted to settlements. In addition, the area with the largest CO2 emission density was Sejong-si at 7.59 tCO2/ha. Conclusion: Based on reviewing available spatial data in South Korea, it is possible to improve Approach 3, which is more advanced than previous Approach 1 in the settlement category. In addition, the national GHG inventory also can be estimated by our constructed LUC matrix and activity data in this study. Under the many discussions about developing the Approach system, this study can provide in-detail information on developing LUC in South Korea in the settlement category as well as suggesting a methodology for constructing the LUC matrix for countries with similar problems to South Korea. [ABSTRACT FROM AUTHOR]

With global greenhouse gas emissions on the rise, the higher education sector has recognised the part it must play in reducing its carbon footprint, setting an example for others to follow in the global fight against climate change. In 2019 University College Cork undertook the complex task of designing and developing a Climate Action Plan, beginning with the compilation of a detailed inventory of the university's greenhouse gas emissions and followed by a period of engaged research during which potential climate action measures were identified by key stakeholders. In response to the start of the Covid-19 pandemic and introduction of public health restrictions, a structured dialogue – modified Delphi – approach was employed as part of the engaged research. This mixed-methods approach proved successful at identifying a number of potential opportunities for reducing the university's carbon footprint, with the structured dialogue method in particular offering the researchers numerous advantages for conducting engaged research during the unique circumstances arising as a result of the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

With global greenhouse gas emissions on the rise, the higher education sector has recognised the part it must play in reducing its carbon footprint, setting an example for others to follow in the global fight against climate change. In 2019 University College Cork undertook the complex task of designing and developing a Climate Action Plan, beginning with the compilation of a detailed inventory of the university's greenhouse gas emissions and followed by a period of engaged research during which potential climate action measures were identified by key stakeholders. In response to the start of the Covid-19 pandemic and introduction of public health restrictions, a structured dialogue - modified Delphi - approach was employed as part of the engaged research. This mixed-methods approach proved successful at identifying a number of potential opportunities for reducing the university's carbon footprint, with the structured dialogue method in particular offering the researchers numerous advantages for conducting engaged research during the unique circumstances arising as a result of the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

High levels of greenhouse gas (GHG) emission, coupled with native forest and jungle deforestation, have led to a worldwide temperature increase. Cities are home to over half of the world's population and generate over 80% of GHG emissions. Consequently, urban areas must become facilitation centers in the battle against climate change. The main objective of this manuscript is to estimate the carbon footprint of the La Serena-Coquimbo conurbation, seeking to determine the contribution of the area to climate change. To this end, the following steps were taken: Identification of sectors and subsectors contributing to GHG emissions in the conurbation; gathering data on selected sectors to develop a GHG inventory; and the quantification of the carbon dioxide equivalent (CO2eq) in selected sectors. The results revealed that 2,102,887 t CO2eq were generated in the conurbation by the stationary energy, transport, and waste sectors, the former being the largest contributor. We conclude that there is a need for greater environmental development in cities in order to facilitate formulation and implementation of GHG reduction proposals. [ABSTRACT FROM AUTHOR]

Key message: Using satellite-based maps, Ceccherini et al. (Nature 583:72-77, 2020) report abruptly increasing harvested area estimates in several EU countries beginning in 2015. Using more than 120,000 National Forest Inventory observations to analyze the satellite-based map, we show that it is not harvested area but the map's ability to detect harvested areas that abruptly increases after 2015 in Finland and Sweden. [ABSTRACT FROM AUTHOR]

Purpose: By applying a framework for implementation analysis, the authors aim to examine the evolution of Japan's national greenhouse gas (GHG) inventory, assess the extent to which each condition for effective implementation has been met and identify factors that may contribute to transparency-related capacity building in developing countries. Design/methodology/approach: The case description was based on interviews and document reviews. The authors coded the collected data into the variables as identified under the framework for implementation analysis, and they evaluated the effectiveness according to the code of assessment. Findings: First, this study finds that the development of the endogenous research base can contribute to the continuous improvement in GHG inventories. Second, it highlights the boundary-spanning role played by a private-sector actor's facilitation of interactions among relevant actors. Third, the assessment revealed the criticality of the causal linkage, pointing to the importance of a commitment to emission reductions as a strong driver for the quality improvement of GHG inventories. Lastly, this study indicates a lack of data compatibility, which may potentially hinder effective policy implementation, suggesting the importance of integrated development of the national statistics. Originality/value: The primary contribution of this paper lies in its use of a framework for implementation analysis, creating new possibilities for both practitioners and researchers. The present study pays attention to the fact that the national GHG inventory preparation, although a highly technical task, is crucial to each country's climate change policy implementation, an aspect that has not been focused on by prior studies. [ABSTRACT FROM AUTHOR]

The transparency framework under the Paris Agreement hinges to a large extent on the capacities for developing countries to regularly update their national greenhouse gas (GHG) inventories. The present study aims to understand how such capacities are developed at the organizational level and how this process is influenced by changes in the institutional environments. To this end, we selected the case of Indonesia, a country where the task of producing a national GHG inventory was once outsourced to experts but is now managed within the Ministry of Environment and Forestry. This paper probes why and how this is possible through two different lenses: a model of strategic issue diagnosis and the framework for implementation analysis. Based on data obtained through participant observation, interviews, and document reviews, both approaches were vital in studying the importance of clarity and consistency of basic policy decisions. This study also highlighted the role of capacity development and found that these factors interacted with each other to create positive impacts on the implementation of a national GHG inventory in Indonesia. The analytical frameworks we used can be applied to contexts in other countries. While the model of strategic issue diagnosis enables us to check each aspect of issue interpretations by decision-makers and other organizational participants (urgency, feasibility, and interdependence), the framework for implementation analysis assists with determining if the necessary conditions exist for effective policy implementation. These results are useful for governments and/or donor agencies to identify priority areas of intervention. [ABSTRACT FROM AUTHOR]

A transparency framework has been enhanced under the Paris Agreement. Developing countries need to develop the capacity to regularly update national greenhouse gas (GHG) inventories, thereby tracking progress toward climate change mitigation goals under their nationally determined contributions (NDCs). Although much study in recent years has been focused on the challenges faced by developing countries in building the long-term institutional capabilities required for more frequent inventory reporting, little work has been done to analyze the institutional linkage between the national GHG inventories and NDCs in the respective countries. Against this backdrop, we examined the cases of Vietnam and the Philippines. Through desktop reviews and a series of interviews conducted in 2018, the present study characterized their institutional designs for the national GHG inventory. It also evaluated observed outcomes of institutional performance in the following dimensions: (1) the frequency and quality of national GHG inventory reporting and (2) the effectiveness of the national GHG inventory at informing the process to formulate mitigation actions under NDCs. The study found that there are differences in performance outcomes between the two countries, which may be linked to the differences in institutional designs. It also found potential trade-offs: A good performance outcome in one dimension may not necessarily translate into a similar result in the other. The findings have implications for transparency-related capacity building assistance: A sound understanding of institutional arrangements and their potential consequences is important for development partners to facilitate the interplay between the national GHG inventory and NDCs in developing countries. [ABSTRACT FROM AUTHOR]

Waste heat utilization is shown to have the potential to decrease greenhouse gas emissions globally. The purpose of this case study is to illustrate how the utilization of waste heat to decrease municipal boundary greenhouse gas emissions may increase such emissions within wider boundaries. The case study assesses the utilization of waste heat generated by a data center. In this paper, we analyze the implications within Scopes 1-3 of the Greenhouse Gas Protocol together with attributional and consequential life cycle assessment principals. Only Scope 1 showed negative greenhouse gas emission implications. In order to achieve negative Scope 2 emissions, approximately half of the waste heat would need to be utilized, which is the purpose of further site development. In order for negative Scope 3 emission implications, electricity production changes are needed or local municipal replaceable greenhouse gas emissions would need to be much higher. [ABSTRACT FROM AUTHOR]

The Cuajimalpa campus of the Autonomous Metropolitan University (UAM) is located in the western region of Mexico City. In 2016, its global average population (students, faculty and staff) was around 2750 people. Campus policies include sustainability as one of its main aims. To evaluate and eventually reduce the environmental impact of the campus, its greenhouse gas (GHG) inventory was assessed and the carbon footprint was calculated, using the GHG protocol (GHGP): Scope 1: direct GHG emissions; Scope 2: indirect GHG emissions; and Scope 3: other indirect GHG emissions, on a calendar year basis. Scope 1 includes mobile and stationary sources and leakage of refrigerants; Scope 2 includes electrical energy usage; Scope 3 includes consumption of paper, food, water, gases, cleaning products, solvents, wastewater treatment, municipal and hazardous wastes and academic travel. In 2016, the campus produced around 3000 tons of CO2 equivalent, with Scope 1, 2 and 3 accounting for 4%, 24% and 72%, respectively. Emissions analysis by activity indicated 51% for commuting; 24% for electricity usage; 14% for academic travel; 11% for other activities. The inventory will aid the establishment of policies for reduction and mitigation of GHG, resulting in environmental and potential economic benefits. [ABSTRACT FROM AUTHOR]

Land use and land use change calculation matrix is one of the most important parts of the national greenhouse gas (GHG) inventory in land use, land use change and forestry (LULUCF) sector providing information of an overall summary and changes in land use at a national level over a specified period of time. Information on land use and land use changes are further used to calculate other parameters important for determination of GHG emissions and carbon stock changes in living and dead biomass, soil and litter, as well as basic information on the impact of applied climate change mitigation measures. Calculations of land use change can be carried out in a partly automated process using GIS tools, which makes calculations easier to perform, reduces time consumption for this task and occasional mistakes due to manual operations. The aim of this study is to improve the methodology for development of land use and land use change matrix in the national GHG inventory system using geospatial data of National forest inventory (NFI) and auxiliary data sources. The developed system uses geospatial NFI data and auxiliary information provided by the land parcel information system (LPIS) and stand-wise forest inventory, and it improves accuracy and consistency of the land use and land use change matrix, providing the ability to apply the same land use accounting method for the whole reporting period since 1990 without a significant increase of uncertainty. The developed method determines land use changes in a 5-year period by comparing three successive NFI cycles. To determine the actual land use category in a particular year, we adjusted weights for different land use categories. Interpolation is used to determine year-by-year transitions. [ABSTRACT FROM AUTHOR]

National greenhouse gas inventories often use variations of the gain–loss approach whereby emissions are estimated as the products of estimates of areas of land-use change characterized as activity data and estimates of emissions per unit area characterized as emission factors. Although the term emissions is often intuitively understood to mean release of greenhouse gases from terrestrial sources to the atmosphere, in fact, emission factors can also be negative, meaning removal of the gases from the atmosphere to terrestrial sinks. For remote and inaccessible forests for which ground sampling is difficult if not impossible, emission factors may be based on map-based estimates of biomass or biomass change obtained from regional maps. For the special case of complete deforestation, the emission factor for the aboveground biomass pool is simply mean aboveground, live-tree, biomass per unit area prior to the deforestation. If biomass maps are used for these purposes, estimates must still comply with the first IPCC good practice guideline regarding accuracy relative to the true value and the second guideline regarding uncertainty. Accuracy assessment for a map-based estimate entails comparison of the estimate to a second estimate obtained using independent reference data. Assuming ground sampling is not feasible, a map of greater quality than the regional map may be considered as a source of reference data where greater quality connotes attributes such as finer resolution and/or greater accuracy. For a local, sub-regional study area in Minnesota in the USA, the accuracy of an estimate of mean aboveground, live-tree biomass per unit area (AGB, Mg/ha) obtained from a coarser resolution, regional, MODIS-based biomass map was assessed using reference data sampled from a finer resolution, local, airborne laser scanning (ALS)-based biomass map. The rationale for a local assessment of a regional map is that, although assessment of a regional map would be difficult for the entire extent of the map, it can likely be assessed for multiple local sub-regions in which case expected local regional accuracy for the entire map can perhaps be inferred. For this study, the local assessment was in the form of a test of the hypothesis that the local sub-regional estimate from the regional map did not deviate from the local true value. A hybrid approach to inference was used whereby design-based inferential techniques were used to estimate uncertainty due to sampling from the finer resolution map, and model-based inferential techniques were used to estimate uncertainty resulting from using the finer resolution map unit values which were subject to prediction error as reference data. The test revealed no statistically significant difference between the MODIS-based and ALS-based map estimates, thereby indicating that for the local sub-region, the regional, MODIS-based estimate complied with the first IPCC good practice guideline for accuracy. [ABSTRACT FROM AUTHOR]

Fugitive methane emissions from coal mining activities have been frequently talked about in the literature due to concerns about climate change. However, indirect and direct CO2 emissions may also result from coal mining processes. The indirect CO2 emissions include those from diesel combustion from equipment while direct CO2 emissions are a relatively new area of research and have been recently brought into the purview of the Intergovernmental Panel on Climate Change (IPCC) inventory guidelines. We discuss some of the preliminary results which can give some directions into the potential research areas for better accounting of greenhouse gas emissions from coal mining activities. These have been derived from practical studies undertaken at selected coal mines in India. [ABSTRACT FROM AUTHOR]

Large-area forest inventories are often undertaken following a stratified random or systematic design. Yet the strata rarely correspond to the reporting areas of interest (domains) over which the country wants to report specific variables. The process is exemplified by a country aiming to use national forest inventory data to obtain average biomass estimates per forest type for GHGI international reporting, where activity data (areas of land use or land use changes) and emission factors (carbon coefficients) are typically compiled from disparate sources and estimated using different sampling schemes. This study aims to provide a decision tree for the choice of the estimator to be used in forest surveys to draw conclusions about population sub-groups created after (and independently of) the sample selection. This manuscript describes two unbiased estimators that can be used to estimate reporting-strata means, regardless of the sampling design adopted, and extends the result to the common situation in which the reporting-strata are spatially explicit, where a nested group estimator outperforms in terms of both bias and precision other more traditional estimators. From this estimator, an optimal sample allocation scheme is also derived. [ABSTRACT FROM AUTHOR]

In this study, an attempt has been made to develop inventory of greenhouse gas (GHG) emissions for Pakistan at the national and sectoral level. The emission profile includes carbon dioxide (CO), methane (CH), and nitrous oxide (NO). In 2012, GHG emissions from different sectors of economy are estimated at 367 Tg COeq. Out of this, CO emissions were 179 Tg; CH emissions were 107 Tg COeq; and NO emissions were 81 Tg COeq. Energy and agriculture sectors contribute approximately 89% of national GHG emissions. Industrial processes, waste, and land use change and forestry (LUCF) sectors contribute the remaining 11% GHG emissions. A comparison with the 1994 GHG emission inventory of Pakistan shows that GHG emissions in Pakistan from 1994 to 2012 have increased at an annual growth rate of 4.1% and yet anticipated to increase further for meeting the national developmental goals; however, the per capita emissions in Pakistan will remain low when compared with the global average. [ABSTRACT FROM AUTHOR]

While some countries disaggregate NO emission factors for urine and dung deposited onto pastures, in Canada, distinct NO emission factors for beef cattle urine and dung have not been defined. To help address this knowledge gap, we conducted a 1-year study to quantify NO fluxes from beef cattle urine and dung patches on a semiarid tame pasture in western Canada, as well as to quantify the NO emission factors (EF3) for urine and dung as the percentage of applied N emitted as NO-N. Urine and dung were deposited when soil water-filled pore space was nearly 60%, a wet soil condition for the grazing season in the semiarid study region, which led to a burst of NO from urine in the first 14 days of the study (42% of total N emitted). Urine emitted more cumulative NO ( P < 0.001) and had a greater NO emission factor ( P = 0.002) than dung. The urine patch emitted 1.30 ± 0.47 g NO-N m year, while the dung patch emitted 0.083 ± 0.020 g NO-N m year (mean values ± SD). The NO emission factor for urine was 1.32 ± 0.49%, while for dung it was 0.03 ± 0.02%. We conclude that more study is needed to determine if distinct NO emission factors are required for urine and dung deposited onto pasture in western Canada to more accurately estimate national NO inventories. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on Earth; this pool plays a critical role in ecosystem processes and climate change. Given the cost and time required to measure SOC, and particularly changes in SOC, many signatory nations to the United Nations Framework Convention on Climate Change report estimates of SOC stocks and stock changes using default values from the Intergovernmental Panel on Climate Change or country-specific models. In the United States, SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the U.S. Department of Agriculture, Forest Service. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forest land in the conterminous United States and southeast and southcentral coastal Alaska. That said, the FIA program has been using country-specific predictions of SOC based, in part, upon a model using SOC estimates from the State Soil Geographic (STATSGO) database compiled by the Natural Resources Conservation Service. Estimates obtained from the STATSGO database are averages over large map units and are not expected to provide accurate estimates for specific locations, e.g., NFI plots. To improve the accuracy of SOC estimates in U.S. forests, NFI SOC observations were used for the first time to predict SOC density to a depth of 100 cm for all forested NFI plots. Incorporating soil-forming factors along with observations of SOC into a new estimation framework resulted in a 75% (48 ± 0.78 Mg/ha) increase in SOC densities nationally. This substantially increases the contribution of the SOC pool, from approximately 44% (17 Pg) of the total forest ecosystem C stocks to 56% (28 Pg), in the forest C budget of the United States. [ABSTRACT FROM AUTHOR]

Combustion of lignite and coal comprises the most important part of CO2emissions in the Czech Republic (CR). The IPCC methodology on national greenhouse gas inventories provides default values of emission factors for the basic tier (the simplest level of methodological approach), including those for lignite and coal, which do not represent the specific national conditions. Therefore, this methodology indicates that more accurate country-specific emission factors based on national data should be used for the significant categories of sources, called key categories. This paper presents the results of recent research that was concerned with updating country-specific emission factors, which would be able to accurately describe CO2emissions from combustion of coal and lignite in the Czech Republic for the whole time period from 1990 to the present year (2016). Development of these factors was based on the evaluation of relevant correlation dependence of emission factor on net calorific value. In addition, the research was supplemented by assessment of relevant country-specific oxidation factors for lignite and coal. [ABSTRACT FROM AUTHOR]

Copyright of Galician Journal of Economics / Revista Galega de Economía is the property of Universidad de Santiago de Compostela, Servicio de Publicaciones and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article conducts an assessment of what should be considered best practice in municipal GHG accounting, contrasting the call for increased global harmonization with the need for local relevance and applicability. Taking as its point of departure an analysis of GHG accounting methodologies applied by local governments in Denmark, we identify eight Danish methodologies and assess them based on international good practice criteria. We observe a high degree of convergence among the Danish approaches in the application of data sources, quantification approaches, and scope, identifying data availability as the key barrier to improving the specificity and dynamic properties of local GHG accounts. In furthering an international best practice, the Danish approaches indicate that relevance to local planning necessarily involves an adaptation to the context of local systems and data sources, and that best practice guidelines should acknowledge limitations in inventory quality and provide guidelines for weighing trade-offs and exploring synergetic improvements. In Denmark, synergies can be found in improved data quality and regional cooperation on account development, which may improve relevance, quality, and comparability simultaneously, and act as an adaptive approach to methodology harmonization, without thereby reducing inventory relevance. [ABSTRACT FROM AUTHOR]

Inland waters were recently recognized to be important sources of methane ( CH4) and carbon dioxide ( CO2) to the atmosphere, and including inland water emissions in large scale greenhouse gas ( GHG) budgets may potentially offset the estimated carbon sink in many areas. However, the lack of GHG flux measurements and well-defined inland water areas for extrapolation, make the magnitude of the potential offset unclear. This study presents coordinated flux measurements of CH4 and CO2 in multiple lakes, ponds, rivers, open wells, reservoirs, springs, and canals in India. All these inland water types, representative of common aquatic ecosystems in India, emitted substantial amounts of CH4 and a major fraction also emitted CO2. The total CH4 flux (including ebullition and diffusion) from all the 45 systems ranged from 0.01 to 52.1 mmol m−2 d−1, with a mean of 7.8 ± 12.7 (mean ± 1 SD) mmol m−2 d−1. The mean surface water CH4 concentration was 3.8 ± 14.5 μ m (range 0.03-92.1 μ m). The CO2 fluxes ranged from −28.2 to 262.4 mmol m−2 d−1 and the mean flux was 51.9 ± 71.1 mmol m−2 d−1. The mean partial pressure of CO2 was 2927 ± 3269 μatm (range: 400-11 467 μatm). Conservative extrapolation to whole India, considering the specific area of the different water types studied, yielded average emissions of 2.1 Tg CH4 yr−1 and 22.0 Tg CO2 yr−1 from India's inland waters. When expressed as CO2 equivalents, this amounts to 75 Tg CO2 equivalents yr−1 (53-98 Tg CO2 equivalents yr−1; ± 1 SD), with CH4 contributing 71%. Hence, average inland water GHG emissions, which were not previously considered, correspond to 42% (30-55%) of the estimated land carbon sink of India. Thereby this study illustrates the importance of considering inland water GHG exchange in large scale assessments. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to report on the results of a case study in Botswana, aimed at raising awareness on climate issues. Higher-education institutions play a leading role in sustainability efforts, as their research role often lays the groundwork for social transformation. Design/methodology/approach – The Clean Air-Cool Planet (CACP) campus calculator was used to calculate emissions from various sections within the college. Findings – Total greenhouse gas (GHG) emissions from the college is 3,432.66 metric tons CO2e resulting in per capita GHG emissions of 3.20 metric tons CO2e, which is high compared to other universities. Options for reducing emissions are proposed. Practical implications – The procedure in carrying out the study provided learners with an opportunity to appreciate emissions from developing countries and also gain technical skills in conducting a GHG inventory. It also sensitized campus administrators about the scale of emissions and possible ways of reducing them. Originality/value – This paper is original in that it provides campus greenhouse inventory within a developing country, a unique undertaking. Furthermore, it highlights the fact that developing countries also produce significant emissions, hence the need for mitigation measures. [ABSTRACT FROM AUTHOR]

The Good Practice Guidance (GPG) for reporting emissions and removals of greenhouse gases from the land use, land-use change, and forestry (LULUCF) sector of the United Nation's Framework Convention on Climate Change states that uncertainty estimates should always accompany the estimates of net emissions. Two basic procedures are suggested: simple error propagation and Monte-Carlo simulation. In this article, we argue that these methods are not very well-suited for uncertainty assessments in connection with sample-based surveys such as national forest inventories (NFIs), which provide a majority of the data for the LULUCF sector reporting in several countries. We suggest that a more straightforward approach would be to use standard sampling theory for assessing the sampling errors; however, it may be important to also include the error contribution from biomass and other models that are applied and this requires new methods for the variance estimation. In this article, a method for sample-based uncertainty assessment, including both model and sampling errors, is developed and applied using data from the NFIs of Finland and Sweden. The study revealed that the model error contribution to the combined sampling-model mean square error of ratio estimators of mean aboveground biomass on forestland amounted to about 10% in both countries. In estimating 5-year change of the corresponding biomass stocks, using permanent sampling units, the model error contribution was reduced to less than 1%. The smaller impact in the case of change estimation is due to the fact that any tendency of models to either over- or underestimate due to random parameter estimation errors will be the some both at the beginning and the end of a study period. The fairly small model error contributions in our study are due to the large number of sample trees used in the fitting of biomass models in Finland and Sweden; with less sample trees the model error contributions could be expected to be substantial. The proposed framework applies not only to greenhouse gas inventories but also to traditional NFI estimates of, e.g., growing stock in which uncertainties due to model errors typically are neglected in applications. [ABSTRACT FROM AUTHOR]

Urban areas are the main sources of greenhouse gas (GHG) emissions. Previous studies have identified the effectiveness of better urban design on mitigating climate change and land-use patterns in cities as important factors in reducing GHG by local governments. However, studies documenting the link between land-use and GHG emissions are scant. Therefore, this study explores the driving forces of land-use change and GHG emission increments in urban areas and investigates their correlations. The study area, Xinzhuang, is a satellite city of Taipei that has rapidly urbanized in the past few decades. Twenty-one potential variables were selected to determine the driving forces of land-use change and GHG emission increments by binomial logistic regression based on the investigation data of national land use in 1996 and 2007. The correlation of land-use change and GHG increments was examined by Spearman rank-order analysis. Results of logistic regression analysis identified that population and its increasing density rate are main driving forces on both land-use change and GHG increments. The Spearman rank correlation matrix indicates that fluctuating urbanization level is significantly correlated with the increase of total GHG emissions, the emissions of residence, commerce, and transportation sectors in neighborhoods; and the emissions of residence and transportation sectors seem closely connected to current urbanization level. The findings suggest that relationships among land-use, urbanization, and GHG emissions in urban areas vary greatly according to residence and transportation characteristics. Land-based mitigation may provide the most viable mechanism for reducing GHG emissions through residence and transportation sectors. [ABSTRACT FROM AUTHOR]

To meet the mitigation targets set by California's Global Warming Solutions Act there is a need for locally adapted greenhouse gas (GHG) inventory methods and policy principles that help rural communities prioritize opportunities for agricultural GHG mitigation. Here, inventory methods prescribed by the Intergovernmental Panel on Climate Change and local activity data on agricultural land uses and inputs were used to conduct an inventory of agricultural emissions for a rural county in California for 1990 and 2008. Total emissions from agriculture in Yolo County were found to decline by 10.4% during this period, due to a reduction in irrigated cropland acreage, a shift towards crops which require less N, and a reduction in N rate for some crops. Average emissions per hectare of urban land were >70 times more than our estimate for irrigated cropland. This suggests that policies which protect farmland and encourage ‘smart growth’ may help curb future emissions. Opportunities also exist to reduce emissions through voluntary, incentive-based, and market-driven initiatives which promote the adoption of innovative agricultural practices. To be effective, local policy makers must work closely with agricultural stakeholders to anticipate and adapt to the practical tradeoffs and co-benefits of new climate policies. [ABSTRACT FROM PUBLISHER]

Purpose -- The purpose of this paper is to understand how cities at different stages of development each subject to its own challenges in adapting to climate change can manage greenhouse gas (GHG) emissions. Design/methodology/approach -- Case studies are undertaken for three cities: Amman, Jakarta and Dar es Salaam, including determination of GHG emissions and analysis of climate change data (where available) for each. Findings -- In Amman, the most climate-sensitive municipal service is water; Jordan is exceptionally dry, and nearly 15 per cent of all electricity consumption is by the water authority. Jakarta has already experienced extreme flooding. The climate vulnerabilities associated with sea-level rise are intensified by subsidence in parts of Jakarta. Alternating floods and droughts are climate impacts already experienced in Dar es Salaam. Droughts have impacted Tanzania's electricity infrastructure disrupting hydroelectricity production, requiring new natural gas infrastructure to maintain power, thereby increasing GHG emissions. Nonetheless, Dar es Salaam's GHG emissions at 0.56t CO[sub 2]e/cap are small compared to Amman and Jakarta at 3.66 and 4.92 t CO[sub 2]e/cap., respectively. Originality/value -- Synergist development strategies, addressing climate change mitigation and adaptation are suggested. In Amman an increased share of photovoltaic electricity production might be used for service provision, especially for energy needs surrounding water supply. Advanced slum upgrading in Jakarta could see relocation of the at-risk poor to safe areas with energy efficient homes connected to public transit and decentralized, community-based electricity generation. The focus in Dar es Salaam community-based waste-to-energy facilities would reduce climate change impacts and vulnerabilities while addressing energy poverty in poor communities. [ABSTRACT FROM AUTHOR]

Estimating tree volume and biomass constitutes an essential part of the forest resources assessment and the evaluation of the climate change mitigation potential of forests through biomass accumulation and carbon sequestration. This research article provides stem volume and biomass equations applicable to five tree species, namely Afzelia africana Sm. (Caesalpiniaceae), Anogeissus leiocarpa (DC.) Guill. and Perr. (Combretaceae), Ceiba pentandra (L.) Gaertn. (Bombacaceae), Dialium guineense Willd. (Caesalpiniaceae), Diospyros mespiliformis Hochst. ex A.DC. (Ebenaceae) in natural protected tropical forests and, in addition, Tectona grandis L.f. (Verbenaceae) in plantations. In addition to the tree species specific equations, basic wood density, as well as carbon, nitrogen, organic matter and ash content were determined for these tree species in tropical conditions in West Africa. One hundred and sixty-two sample trees were measured through non-destructive sampling and analysed for volume and biomass. Stem biomass and stem volume were modelled as a function of diameter (at breast height; Dbh) and stem height (height to the crown base). Logarithmic models are presented that utilise Dbh and height data to predict tree component biomass and stem volumes. Alternative models are given that afford prediction based on Dbh data alone, assuming height data to be unavailable. Models that include height are preferred, having better predictive capabilities. Ranges in carbon, nitrogen and ash contents are given as well. The successful development of predictive models through the use of non-destructive methods in this study provide valuable data and tools for use in determining the contribution of these major African rainforest tree species to global carbon stocks, while ensuring the preservation of this valued African resource. This study needs to be expanded to further regions and tree species to complete a full inventory of all tree species, emphasising the relevance of African trees to carbon stocks at a global scale. [ABSTRACT FROM AUTHOR]

Higher education institutions play a leading role in sustainability efforts nationwide. Not only do these institutions require large quantities of energy to function but also their research role often lays the groundwork for social transformation. The purpose of this study was to estimate the annual greenhouse gas emissions primarily from energy usage at Louisiana State University. Total energy use is 2.43 million MMBtu resulting in per capita GHG emissions of 6.1 Metric Tons CO2e, which is low compared to many other universities because of lower utility costs. This calculation does not account for total indirect energy use by the university community. Several alternatives for reducing energy use and emissions are considered. [ABSTRACT FROM AUTHOR]

A geoinformation technology for creating spatially distributed greenhouse gas inventories based on a methodology provided by the Intergovernmental Panel on Climate Change and special software linking input data, inventory models, and a means for visualization are proposed. This technology opens up new possibilities for qualitative and quantitative spatially distributed presentations of inventory uncertainty at the regional level. Problems concerning uncertainty and verification of the distributed inventory are discussed. A Monte Carlo analysis of uncertainties in the energy sector at the regional level is performed, and a number of simulations concerning the effectiveness of uncertainty reduction in some regions are carried out. Uncertainties in activity data have a considerable influence on overall inventory uncertainty, for example, the inventory uncertainty in the energy sector declines from 3.2 to 2.0% when the uncertainty of energy-related statistical data on fuels combusted in the energy industries declines from 10 to 5%. Within the energy sector, the ‘energy industries’ subsector has the greatest impact on inventory uncertainty. The relative uncertainty in the energy sector inventory can be reduced from 2.19 to 1.47% if the uncertainty of specific statistical data on fuel consumption decreases from 10 to 5%. The ‘energy industries’ subsector has the greatest influence in the Donetsk oblast. Reducing the uncertainty of statistical data on electricity generation in just three regions – the Donetsk, Dnipropetrovsk, and Luhansk oblasts – from 7.5 to 4.0% results in a decline from 2.6 to 1.6% in the uncertainty in the national energy sector inventory. [ABSTRACT FROM AUTHOR]

Forest biomass and its change over time have been measured at both local and large scales, an example for the latter being forest greenhouse gas inventories. Currently used methodologies to obtain stock change estimates for large forest areas are mostly based on forest inventory information as well as various factors, referred to as biomass factors, or biomass equations, which transform diameter, height or volume data into biomass estimates. However, while forest inventories usually apply statistically sound sampling and can provide representative estimates for large forest areas, the biomass factors or equations used are, in most cases, not representative, because they are based on local studies. Moreover, their application is controversial due to the inconsistent or inappropriate use of definitions involved. There is no standardized terminology of the various factors, and the use of terms and definitions is often confusing. The present contribution aims at systematically summarizing the main types of biomass factors (BF) and biomass equations (BE) and providing guidance on how to proceed when selecting, developing and applying proper factors or equations to be used in forest biomass estimation. The contribution builds on the guidance given by the IPCC (Good practice guidance for land use, land-use change and forestry, 2003) and suggests that proper application and reporting of biomass factors and equations and transparent and consistent reporting of forest carbon inventories are needed in both scientific literature and the greenhouse gas inventory reports of countries. [ABSTRACT FROM AUTHOR]

Copyright of Annals of Forest Science (BioMed Central) is the property of BioMed Central and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study was designed to estimate the variation in non-volatile carbon (C) content in different above- and belowground tree parts (stem, living branches, dead branches, stumps, coarse roots and small roots) and to develop country-specific weighted mean C content values for the major tree species in hemiboreal forests in Latvia: Norway spruce (Picea abies (L.) H. Karst.), Scots pine (Pinus sylvestris L.), birch spp. (Betula spp.) and European aspen (Populus tremula L.). In total, 372 sample trees from 124 forest stands were selected and destructively sampled. As the tree samples were pre-treated by oven-drying before elemental analysis, the results of this study represent the non-volatile C fraction. Our findings indicate a significant variation in C content among the tree parts and studied species with a range of 504.6 ± 3.4 g·kg−1 (European aspen, coarse roots) to 550.6 ± 2.4 g·kg−1 (Scots pine, dead branches). The weighted mean C content values for whole trees ranged from 509.0 ± 1.6 g·kg−1 for European aspen to 533.2 ± 1.6 g·kg−1 for Scots pine. Only in Norway spruce was the whole tree C content significantly influenced by tree age and size. Our analysis revealed that the use of the Intergovernmental Panel on Climate Change (IPCC) default C content values recommended for temperate and boreal ecological zones leads to a 5.1% underestimation of C stock in living tree biomass in Latvia's forests. Thus, the country-specific weighted mean C content values for major tree species we provide may improve the accuracy of National Greenhouse Gas Inventory estimates. [ABSTRACT FROM AUTHOR]

Dendrochronological studies and forest inventory surveys have reported increased growth and biospheric carbon (C) sequestration for European forests in the recent past. The potential of concomitant changes in forest soil C stocks are not accounted for in the IPCC guidelines for national greenhouse gas inventories. We developed a model-based approach to address this problem and assess the role of soils in forest C balance in the European Alps. The decomposition model FORCLIM-D was driven by long-term (that is, 1900–1985 AD) litter input scenarios constructed from forest inventory data, region-specific dendrochronological basal area indices, and time series of anthropogenic litter removal. The effect of spatial climate variability on organic matter decomposition across the case study region (Switzerland) was explicitly accounted for by constant long-term annual means of actual evapotranspiration and temperature. Uncertainties in forest development, litter removal, fine root litter input, and dynamics of forest soil C were studied by an explorative factorial sensitivity analysis. We found that forest soils contribute substantially to the biospheric C sequestration for Switzerland: Our “best estimate” yielded an increase of 0.35 Mt C/y or 0.33 t C/(ha y) in forest soils for 1985, that is, 27% of the C sequestered by forest trees (BUWAL 1994). Uncertainties regarding C accumulation in forest soils were substantial (0.11–0.58 Mt C/y) but could be reduced by estimating forest soil C stocks in the future. Whereas soils can be important for the C balance in naturally regrowing forests, their C sequestration is negligible (less than 5%) relative to anthropogenic CO2 emissions in Western Europe at present. [ABSTRACT FROM AUTHOR]

Research Highlights: The estimation of soil and litter carbon stocks by the Land Use, Land-Use Changes, and Forestry (LULUCF) sectors has the potential to improve reports on national greenhouse gas (GHG) inventories. Background and Objectives: Forests are carbon sinks in the LULUCF sectors and therefore can be a comparatively cost-effective means and method of GHG mitigation. Materials and Methods: This study was conducted to assess soil at 0–30 cm and litter carbon stocks using the National Forest Inventory (NFI) data and random forest (RF) models, mapping their carbon stocks. The three main types of forest in South Kora were studied, namely, coniferous, deciduous, and mixed. Results: The litter carbon stocks (t C ha−1) were 4.63 ± 0.18 for coniferous, 3.98 ± 0.15 for mixed, and 3.28 ± 0.13 for deciduous. The soil carbon stocks (t C ha−1) were 44.11 ± 1.54 for deciduous, 35.75 ± 1.60 for mixed, and 33.96 ± 1.62 for coniferous. Coniferous forests had higher litter carbon stocks while deciduous forests contained higher soil carbon stocks. The carbon storage in the soil and litter layer increased as the forest grew older; however, a significant difference was found in several age classes. For mapping the soil and litter carbon stocks, we used four random forest models, namely RF1 to RF4, and the best performing model was RF2 (root mean square error (RMSE) (t C ha−1) = 1.67 in soil carbon stocks, 1.49 in soil and litter carbon stocks). Our study indicated that elevation, accessibility class, slope, diameter at breast height, height, and growing stock are important predictors of carbon stock. Soil and litter carbon stock maps were produced using the RF2 models. Almost all prediction values were appropriated to soil and litter carbon stocks. Conclusions: Estimating and mapping the carbon stocks in the soil and litter layer using the NFI data and random forest models could be used in future national GHG inventory reports. Additionally, the data and models can estimate all carbon pools to achieve an accurate and complete national GHG inventory report. [ABSTRACT FROM AUTHOR]

In the context of greenhouse gas emissions, CO2 emissions from fuels are not arising only from combustion of the fuels, but also from non-energy use of fuels. In order to keep the inventory transparent, comparable, accurate, consistent, and complete, it is necessary to carefully assess such emissions in order to neither not omit nor double count them. The paper presents the methodological guidance of non-energy use of fuels given by Intergovernmental Panel on Climate Change (IPCC) 2006 Guidelines. Further, approaches of the Czech Republic, Slovak Republic, and Hungary, three neighboring countries, for reporting CO2 emissions from non-energy use of fuels are presented and discussed. [ABSTRACT FROM AUTHOR]