National Inventory Report Research Articles

Hybrid bottom-up and top-down framework resolves discrepancies in Canada’s oil and gas methane inventories

Estimating accurate oil and gas methane emissions has been a global challenge, highlighted by a twofold discrepancy between atmospheric measurement-based estimates and emission inventories. The principle of continuous improvement in Canada’s National Inventory Report has led to an unstable baseline in recent years for tracking emission reduction progress. The gaps between previous inventory estimates and inversions exceeded 60%. Here we show that incorporating new source-resolved information derived from low-altitude aerial survey data has narrowed this gap by 80%, reducing the discrepancy to 10% for the 2010–2014 baseline. This study proposes a hybrid emission reporting framework, complemented by an ensemble inversion top-down method using continuous tower-based atmospheric measurements, to establish a stable baseline and provide independent verification. As the 2030 target year for emission reduction approaches, we report a significant 27% decline (19%–34%) in inverse oil and gas methane emissions from 2010 to 2022 in Alberta and Saskatchewan, Canada, and a 41% decline (26%–56%) as calculated using the 2024 official inventory.

GeoGOBLIN: A catchment-scale land balance model for assessment of climate mitigation pathways considering environmental trade-offs for multiple impact categories

GeoGOBLIN, a novel environmental impact and land balance assessment tool, builds upon the GOBLIN biophysical land use emissions model for Ireland, offering enhanced resolution and system-level detail. It combines remotely sensed data and national agricultural census data to model climate change, air quality, and eutrophication emissions at the catchment level. Integration of the CBM-CFS3 forest carbon modelling framework (utilised in Ireland's National Inventory Report) increases alignment with national emissions reporting. GeoGOBLIN disaggregates emissions by life cycle assessment impact categories, making it a valuable tool for policymakers and researchers evaluating environmental and economic trade-offs associated with land-use scenarios. Illustrative scenarios demonstrate GeoGOBLIN's ability to assess the multifaceted impacts of alternative land uses, supporting informed decision-making for sustainable land use, food production, and a circular bioeconomy.

Quantification of Methane Emissions from Cold Heavy Oil Production with Sand Extraction in Alberta and Saskatchewan, Canada.

Cold heavy oil production with sand (CHOPS) is an extraction process for heavy oil in Canada, with the potential to lead to higher CH4 venting than conventional oil sites, that have not been adequately characterized. In order to quantify CH4 emissions from CHOPS activities, a focused aerial measurement campaign was conducted in the Canadian provinces of Alberta and Saskatchewan in June 2018. Total CH4 emissions from each of 10 clusters of CHOPS wells (containing 22-167 well sites per cluster) were derived using a mass balance computation algorithm that uses in situ wind data measurement on board aircraft. Results show that there is no statistically significant difference in CH4 emissions from CHOPS wells between the two provinces. Cluster-aggregated emission factors (EF) were determined using correspondingly aggregated production volumes. The average CH4 EF was 70.4 ± 36.9 kg/m3 produced oil for the Alberta wells and 55.1 ± 13.7 kg/m3 produced oil for the Saskatchewan wells. Using these EF and heavy oil production volumes reported to provincial regulators, the annual CH4 emissions from CHOPS were estimated to be 121% larger than CHOPS emissions extracted from Canada's National Inventory Report (NIR) for Saskatchewan. The EF were found to be positively correlated with the percentage of nonpiped production volumes in each cluster, indicating higher emissions for nonpiped wells while suggesting an avenue for methane emission reductions. A comparison with recent measurements indicates relatively limited effectiveness of regulations for Saskatchewan compared to those in Alberta. The results of this study indicate the substantial contribution of CHOPS operations to the underreporting observed in the NIR and provide measurement-based EF that can be used to develop improved emissions inventories for this sector and mitigate CH4 emissions from CHOPS operations.

Estimating the uncertainty of the greenhouse gas emission accounts in global multi-regional input–output analysis

Abstract. Global multi-regional input–output (GMRIO) analysis is the standard tool to calculate consumption-based carbon accounts at the macro level. Recent inter-database comparisons have exposed discrepancies in GMRIO-based results, pinpointing greenhouse gas (GHG) emission accounts as the primary source of variation. A few studies have analysed the robustness of GHG emission accounts, using Monte Carlo simulations to understand how uncertainty from raw data propagates to the final GHG emission accounts. However, these studies often make simplistic assumptions about raw data uncertainty and ignore correlations between disaggregated variables. Here, we compile GHG emission accounts for the year 2015 according to the resolution of EXIOBASE V3, covering CO2, CH4 and N2O emissions. We propagate uncertainty from the raw data, i.e. the United Nations Framework Convention on Climate Change (UNFCCC) and EDGAR inventories, to the GHG emission accounts and then further to the GHG footprints. We address both limitations from previous studies. First, instead of making simplistic assumptions, we utilise authoritative raw data uncertainty estimates from the National Inventory Reports (NIRs) submitted to the UNFCCC and a recent study on uncertainty of the EDGAR emission inventory. Second, we account for inherent correlations due to data disaggregation by sampling from a Dirichlet distribution. Our results show a median coefficient of variation (CV) for GHG emission accounts at the country level of 4 % for CO2, 12 % for CH4 and 33 % for N2O. For CO2, smaller economies with significant international aviation or shipping sectors show CVs as high as 94 %, as seen in Malta. At the sector level, uncertainties are higher, with median CVs of 94 % for CO2, 100 % for CH4 and 113 % for N2O. Overall, uncertainty decreases when propagated from GHG emission accounts to GHG footprints, likely due to the cancelling-out effects caused by the distribution of emissions and their uncertainties across global supply chains. Our GHG emission accounts generally align with official EXIOBASE emission accounts and OECD data at the country level, though discrepancies at the sectoral level give cause for further examination. We provide our GHG emission accounts with associated uncertainties and correlations at https://doi.org/10.5281/zenodo.10041196 (Schulte et al., 2023) to complement the official EXIOBASE emission accounts for users interested in estimating the uncertainties of their results.

Including Methane Emissions from Agricultural Ponds in National Greenhouse Gas Inventories.

Agricultural ponds are a significant source of greenhouse gases, contributing to the ongoing challenge of anthropogenic climate change. Nations are encouraged to account for these emissions in their national greenhouse gas inventory reports. We present a remote sensing approach using open-access satellite imagery to estimate total methane emissions from agricultural ponds that account for (1) monthly fluctuations in the surface area of individual ponds, (2) rates of historical accumulation of agricultural ponds, and (3) the temperature dependence of methane emissions. As a case study, we used this method to inform the 2024 National Greenhouse Gas Inventory reports submitted by the Australian government, in compliance with the Paris Agreement. Total annual methane emissions increased by 58% from 1990 (26 kilotons CH4 year-1) to 2022 (41 kilotons CH4 year-1). This increase is linked to the water surface of agricultural ponds growing by 51% between 1990 (115 kilo hectares; 1,150 km2) and 2022 (173 kilo hectares; 1,730 km2). In Australia, 16,000 new agricultural ponds are built annually, expanding methane-emitting water surfaces by 1,230 ha yearly (12.3 km2 year-1). On average, the methane flux of agricultural ponds in Australia is 0.238 t CH4 ha-1 year-1. These results offer policymakers insights into developing targeted mitigation strategies to curb these specific forms of anthropogenic emissions. For instance, financial incentives, such as carbon or biodiversity credits, can mobilize widespread investments toward reducing greenhouse gas emissions and enhancing the ecological and environmental values of agricultural ponds. Our data and modeling tools are available on a free cloud-based platform for other countries to adopt this approach.

Satellite-Derived Estimate of City-Level Methane Emissions from Calgary, Alberta, Canada

Cities are important sources of anthropogenic methane emissions. Municipal governments can play a role in reducing those emissions to support climate change mitigation, but they need information on the emission rate to contextualize mitigation actions and track progress. Herein, we examine the application of satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) to estimate city-level methane emission rates in a case study of the City of Calgary, Alberta, Canada. Due to low and variable annual observational coverage, we integrated valid TROPOMI observations over three years (2020–2022) and used mass balance modeling to derive a long-term mean estimate of the emission rate. The resulting column-mean dry-air mole fraction (XCH4) enhancement over Calgary was small (4.7 ppb), but within the city boundaries, we identified local hot spots in the vicinity of known emission sources (wastewater treatment facilities and landfills). The city-level emission estimate from mass balance was 215.4 ± 132.8 t CH4/d. This estimate is approximately four times larger than estimates from Canada’s gridded National Inventory Report of anthropogenic CH4 emissions and six times larger than the Emissions Database for Global Atmospheric Research (EDGAR v8.0). We note that valid TROPOMI observations are more common in warmer months and occur during a narrow daily overpass time slot over Calgary. The limited valid observations in combination with the constrained temporal observational coverage may bias the emission estimate. Overall, the findings from this case study highlight an approach to derive a screening-level estimate of city-level methane emission rates using TROPOMI data in settings with low observational coverage.

Temporally dynamic carbon dioxide and methane emission factors for rewetted peatlands

Rewetting drained peatlands is recognized as a leading and effective natural solution to curb greenhouse gas emissions. However, rewetting creates novel ecosystems whose emission behaviors are not adequately captured by currently used emission factors. These emission factors are applied immediately after rewetting, thus do not reflect the temporal dynamics of greenhouse gas emissions during the period wherein there is a transition to a rewetted steady-state. Here, we provide long-term data showing a mismatch between actual emissions and default emission factors and revealing the temporal patterns of annual carbon dioxide and methane fluxes in a rewetted peatland site in northeastern Germany. We show that site-level annual emissions of carbon dioxide and methane approach the IPCC default emission factors and those suggested for the German national inventory report only between 13 to 16 years after rewetting. Over the entire study period, we observed a source-to-sink transition of annual carbon dioxide fluxes with a decreasing trend of −0.36 t CO2-C ha−1 yr−1 and a decrease in annual methane emissions of −23.6 kg CH4 ha−1 yr−1. Our results indicate that emission factors should represent the temporally dynamic nature of peatlands post-rewetting and consider the effect of site characteristics to better estimate associated annual emissions.

Tracking unaccounted greenhouse gas emissions due to the war in Ukraine since 2022

Accounting and reporting of greenhouse gas (GHG) emissions are mandatory for Parties under the Paris Agreement. Emissions reporting is important for understanding the global carbon cycle and for addressing global climate change. However, in a period of open conflict or war, military emissions increase significantly and the accounting system is not currently designed to account adequately for this source. In this paper we analyze how, during the first 18 months of the 2022/2023 full-scale war in Ukraine, GHG national inventory reporting to the UNFCCC was affected. We estimated the decrease of emissions due to a reduction in traditional human activities. We identified major, war-related, emission processes from the territory of Ukraine not covered by current GHG inventory guidelines and that are not likely to be included in national inventory reports. If these emissions are included, they will likely be incorporated in a way that is not transparent with potentially high uncertainty. We analyze publicly available data and use expert judgment to estimate such emissions from (1) the use of bombs, missiles, barrel artillery, and mines; (2) the consumption of oil products for military operations; (3) fires at petroleum storage depots and refineries; (4) fires in buildings and infrastructure facilities; (5) fires on forest and agricultural lands; and (6) the decomposition of war-related garbage/waste. Our estimate of these war-related emissions of carbon dioxide, methane, and nitrous oxide for the first 18 months of the war in Ukraine is 77 MtCO2-eq. with a relative uncertainty of +/−22 % (95 % confidence interval).

High emissions or carbon neutral? Inclusion of “anthropogenic” forest sinks leads to underreporting of forestry emissions

Recent research has shown forest-related emissions reported in national greenhouse gas inventories are much lower than global estimates from models summarized in Intergovernmental Panel on Climate Change reports. A substantial part of this discrepancy could be explained by conceptual differences in what is counted as part of the anthropogenic forest carbon sink and the way countries report on their forest harvesting sectors. With Canada as a case study, we used published National Inventory Report and Common Reporting Format tables to isolate emissions and removals directly associated with forestry from those associated with forests more broadly. Forestry-related factors that affect CO2 emissions and removals include tree harvesting, post-harvest forest regeneration and growth, and carbon storage in long-lived harvested wood products. We found that between 2005 and 2021, forestry in Canada represented a net source of carbon (annual mean = 90.8 Mt. CO2e), and that total area logged was a significant predictor of net forestry emissions. In contrast, Canada’s NIR reported a small net carbon sink during the same time period (annual mean = −4.7 Mt. CO2e). We show this discrepancy can be explained by Canada’s GHG reporting approach that claims GHG emissions from wildfires are natural, but GHG removals from forests at the age of commercial maturity, despite being primarily natural disturbance origin, are anthropogenic. This reporting approach may lead to climate mitigation policies that are ineffectual or detrimental to reducing net carbon in the global atmosphere.

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

BackgroundThe nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate variability.MethodsWe used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery.ResultsSOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions.ConclusionsIn the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.

Greenhouse Gas Emissions Efficiency in Polish Agriculture

Analysis of the efficiency of greenhouse gas emissions in agriculture is an important part of agricultural and environmental economics research. The theme is extremely important due to the deepening problem of climate change and the simultaneous need to ensure food security. However, counteracting climate change cannot be achieved at the expense of reducing agricultural productivity. Due to the need to study the economic-environmental relationship in agriculture, the main purpose of this study was to assess the changes in the level and structure of agricultural greenhouse gas emissions and to examine the changes in efficiency of agricultural greenhouse gas emissions. The authors also estimated the relative efficiency of emissions, which allowed for comparing the efficiency of emissions between agriculture and other sectors of the national economy. Analyzing the changes in agricultural emissions efficiency, as well as changes in relative efficiency of emissions, is an indirect way of assessing whether the ongoing trends are consistent with the sustainable development concept and if the country is effective enough in mitigating climate change in relation to its economic performance. The research conducted showed that agriculture has a significant share of greenhouse gas emissions among all sectors of the Polish economy. However, greenhouse gas emissions from agriculture decreased by a total of 23.5% in the years studied. The most significant changes occurred in the context of greenhouse gas emissions from intestinal fermentation. The research also shows that the efficiency of emissions from agriculture more than doubled in the years examined. However, it decreased compared to other sectors of the economy in the country. This study was based on emissions data retrieved from National Inventory Reports prepared by the National Center for Emissions Management and on the Agricultural Statistical Yearbooks of the Central Statistical Office. This paper also proposes some examples of measures that could be taken to reduce agricultural emissions. Some of them include reducing food losses, sustainable use of fertilizers, increasing energy efficiency, and greater use of renewable energy.

Increase in Arctic Oscillations explains most interannual variability in Russia’s wildfires

Over the past two decades, the escalating emissions of greenhouse gases from boreal wildfires in the Northern Hemisphere have drawn significant attention, underscoring an unprecedented wildfire season in 2021. Our calculations indicate that between 2002 and 2020, wildfires in Russia released approximately 726 ± 280 Tg CO2eqv yr−1. This aligns closely with similar estimates derived from remote sensing data, far surpassing the earlier approximations found in the Russian National Inventory Report (NIR) by a factor of 2 to 3. Notably, in 2021 alone, Russia’s wildfires emitted an exceptionally high amount of 1,700 Tg CO2eqv, exceeding the carbon emissions from the country’s fossil fuel consumption. Consequently, this situation led to an almost complete counterbalance of carbon assimilation by Russian forests. Our analysis attributes over 50% of the variation in wildfire frequency between 2002 and 2021 to shifts in the Arctic Oscillation (AO). This suggests a potential for utilizing AO as a predictive variable for wildfires. It’s noteworthy that the AO itself is influenced by the sustained regression of Arctic sea-ice. From this, it can be inferred that in the foreseeable future, Russian forests might undergo a transition from their role as carbon sinks to the potential net contributors of carbon to the atmosphere.

A Survey on Fluorinated Greenhouse Gases in Taiwan: Emission Trends, Regulatory Strategies, and Abatement Technologies

Fluorinated greenhouse gases (F-gases), including hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF6), and nitrogen trifluoride (NF3), are used in a variety of applications, but they are potent greenhouse gases (GHGs). Therefore, they have been blanketed into the list of items to be phased out under international protocols or treaties. During the desk research, the updated statistics of Taiwan’s National Inventory Report (NIR) were used to analyze the trends of F-gases (i.e., HFCs, PFCs, SF6, and NF3) emissions during the period of 2000–2020. Furthermore, the regulatory strategies and measures for the reduction of the four F-gas emissions will be summarized to be in accordance with the national and international regulations. With the rapid development in the electronics industry, the total F-gas emissions indicate a significant increase from 2462 kilotons of carbon dioxide equivalents (CO2eq) in 2000 to the peak value (i.e., 12,643 kilotons) of CO2eq in 2004. However, it sharply decreased from 10,284 kilotons of CO2eq in 2005 to 3906 kilotons of CO2eq in 2020 due to the ongoing efforts of the regulatory requirements and the industry’s voluntary reduction in time sequence. It was also found that the most commonly used method for controlling the emissions of F-gases from the semiconductor and optoelectronic industries in Taiwan is based on the thermal destruction-local scrubbing method.

Spatial distribution of CH4 emissions from livestock farming in Poland: a comparison of 2010 and 2020

ABSTRACT Among greenhouse gases (GHGs), methane (CH4) is a major contributor to global warming. Agriculture accounts for about 40% of CH4 emissions, with livestock being a crucial source. CH4 emissions from livestock primarily arise during enteric fermentation and manure management in livestock. This study aims to estimate Poland’s CH4 emissions from enteric fermentation and manure management in 2010 and 2020 at the municipal level (LAU-2). Data from the National Agricultural Census (NAC) and the UNFCCC National Inventory Report (NIR) for 2010 and 2020 were used for the analysis. The results reveal a slight overall increase in total CH4 emissions from livestock farming in Poland over the decade. The highest emissions were observed in regions where livestock farming was predominant, while significant changes in emissions occurred in regions experiencing considerable livestock production growth. Conversely, the lowest emissions were found in areas where the decrease in livestock population was most prominent. Understanding the spatial distribution of CH4 emissions from livestock farming at the municipal level is essential for effective climate change mitigation efforts. This study highlights the importance of continuous monitoring and analysis of livestock farming in Poland to assess its impact on GHG emissions and facilitate informed policy-making for sustainable agricultural practices.

Status and opportunities for improvement in greenhouse gas emission inventories for the cattle production in Latin America and the Caribbean region: A perspective

The Intergovernmental Panel on Climate Change (IPCC) provides the reference for national greenhouse gas emission (GHG) inventories towards standardized, accurate, measurable, and comparable National Inventory Reports (NIR). For compliance with the 1.5⁰C commitments under the Paris Agreement, most countries have made efforts to improve their inventory methods to tier 2 or 3. However, some relevant activities within Latin American and the Caribbean (LAC) countries, such as enteric methane emissions and methane and nitrous oxide emissions from cattle manure management are still estimated using tier 1 methods, which leads to a high uncertainty due to the importance of livestock emissions in the national totals for these countries. In this context, reducing the uncertainty in GHG inventories would not only improve the accuracy of national reports but it would also provide solid baselines for national mitigation initiatives e.g., Nationally Determined Contributions under the Paris Agreement, and accurate tools to venture into carbon bonds or payments for ecosystem services. The aim of this study was to review the status of national GHG inventories specifically for these three cattle emission categories in 11 LAC countries. We conducted a survey of GHG inventory experts in the 11 LAC countries, to identify the potential for improvement and the main barriers to achieving this. Despite some initiatives, there is still a large potential for reducing the uncertainty in LAC national GHG emission estimates, the barriers to or solutions can be categorized as technical, policy, and institutional issues. However, improving the GHG inventories of LAC countries, specifically for cattle emissions, is feasible in the medium term, as long as multilateral actions are considered, coherently linked under a comparable and verifiable methodology and including a commitment by countries to invest public funds in relevant research and innovations.

Life cycle GHG emissions of the Austrian building stock: A combined bottom-up and top-down approach

Construction and operation of buildings are responsible for 37% of global greenhouse gas (GHG) emissions. In contrast, the Austria’s National Inventory Report attributes a mere 10% of national emissions to buildings – including only direct operational emissions of residential and service sector buildings. This narrow definition of the buildings sector neglects important environmental hotspots attributable to building-related life cycle emissions and calls for a comprehensive analysis of GHG emissions of Austrian buildings. In this study, we assess annual building related GHG emissions for the Austrian building stock from a full life cycle perspective (i.e. including operational and embodied emissions). For embodied emissions, we model emissions using both a process-based and an input-output based life cycle assessment (LCA) approach. Building LCA case studies and statistical building stock data are used to estimate embodied emissions from a bottom-up perspective, which are complemented by estimated emissions from the input-output based LCA approach. Our work illustrates the importance of adopting a life-cycle perspective on building-related emissions to inform the different stakeholders and advance climate action in the built environment. While both the chosen system boundaries and methods significantly determine the results, we argue that emission reduction measures should be based on a comprehensive system boundary of building-related emissions to contribute towards the achievement of a climate-neutral built environment and the stringent climate targets. By adding indirect emissions and non-residential buildings to the officially reported building emissions, the operational emissions alone increase by a factor of 2.4. As expected, the process-based LCA yields lower embodied emissions than the input-output based approach. Depending on the method, they can be responsible for up to 40% of total buildings related emissions. Summing up, total buildings related emissions rise by a factor of 3 to 4 when extending the system boundaries to comprise the whole area of action buildings, and go from 7 Mt CO2-eq/a (direct operational emissions, 10% of national emissions), to 22-31 Mt CO2-eq/a for the case of Austria.

Spatially resolved inventory and emissions modelling for pea and lentil life cycle assessment

Pulses are an increasingly popular source of plant-based protein among food manufacturers, food service providers, and retailers globally. Canada is currently a global leader in pulse production and exports. Given the large geographical scope of their production within Canada, pulses are produced under a variety of conditions reflecting differences in soil, climate, and characteristic management practices. In order to understand the influence of regional factors on the impacts of pulse production, high-resolution, regionalized life cycle assessments (LCAs) were carried out using both region-specific input/output data and emissions modelling. Six hundred Canadian pea and lentil farmers were surveyed to collect detailed data regarding characteristic farm inputs, yields and management practices at the reconciliation unit level of spatial resolution, which reconciles Canadian provincial borders with terrestrial ecozones based on soil and climate factors. The process-based model DeNitrification DeComposition (DNDC) was used to estimate regionally specific N emissions. This was compared to emissions estimates generated using the IPCC Tier II empirical models, which are typically used to estimate greenhouse gas emissions for national inventory reports. The main contributors to the life cycle environmental impacts of pea and lentil production were fertilizer and fuel use. This was consistent across all levels of regional aggregation including the total Prairie province average, as well as ecozone and provincial levels. There was variation in the magnitude of the impacts in each region assessed, which was mainly attributable to differences in yield, as well as reported fertilizer application rates and related emissions and fuel use for field operations. Significant differences were found in N emissions estimates between the DNDC and IPCC models, the magnitude of which varied by region and by the N emissions model employed. DNDC was found to provide better-resolved emissions estimates at the ecozone scale. This demonstrates the relevance of regionally specific emissions modelling since local soil and climate conditions had a large impact on the emissions estimates. In addition, the levels of uncertainty in the models were generally higher at the provincial and prairie province scale than at the ecozone scale. This may indicate that farming practices and associated resource/environmental impacts are more strongly influenced by soil and climate conditions than by provincial standards and guidelines. These results underscore the necessity of spatially resolved data collection and modelling to provide accurate estimates of the environmental impacts of crop production and to support more sustainable management of arable crop production.

Marmara Bölgesindeki Fıstık Çamı Ormanlarında Ağaç Bileşenle-rine Ait Karbon Konsantrasyonlarının Belirlenmesi

In accordance with the Kyoto Protocol, countries prepare their national inventory reports (NIR) every year and present it to United Nations Secretariat of the Framework Convention on Climate Change (UNFCCC). These statements are based on AFOLU Guideline (IPCC Guidelines for National Greenhouse Gas Inventories for Agriculture, Forestry and Other Land Use). However, countries are required to produce parameters special to their own tree species in order to make more precise statements. The aim of this study was to determine to calculate both the carbon concentration of various components (needle, wood, bark, and root) of natural stone pine (Pinus pinea L.) and the weighted carbon concentration of above ground and total tree biomass. The study was conducted in natural stone pine forests in Marmara Region of Turkey. Samples were collected in 10 sampling plots that were at mature stage (dbh=20.0-51.9 cm) and had different site characteristics. Site characteristics of the sample plots were determined. Then, needle, wood, bark, and root samples were collected from 3 trees representing the top height in each sampling plot. Carbon analysis on plant samples collected from the sampling plots (10 plots × 3 replications × 4 components = 120 samples) was carried out in the laboratory. The obtained data were evaluated by using analysis of variance and Duncan test. Statistically significant differences were found between carbon concentrations of tree components (P<0.001). The lowest carbon concentrations were in needle (51.65%) and in roots (51.67%), while the highest carbon concentration was in wood (54.74 %) and in barks (54.93%). The weighted carbon concentration for natural stone pine forests were found to be 54.56% and 54.07% for the above-ground biomass and for the total tree biomass, respectively. The carbon concentrations found in this study can be used to calculate the carbon stocks stored in both trees and different components of trees in natural stone pine forests.

Estimating CO<sub>2</sub> emissions for 108 000 European cities

Abstract. City-level CO2 emissions inventories are foundational for supporting the EU's decarbonization goals. Inventories are essential for priority setting and for estimating impacts from the decarbonization transition. Here we present a new CO2 emissions inventory for all 116 572 municipal and local-government units in Europe, containing 108 000 cities at the smallest scale used. The inventory spatially disaggregates the national reported emissions, using nine spatialization methods to distribute the 167 line items detailed in the National Inventory Reports (NIRs) using the UNFCCC (United Nations Framework Convention on Climate Change) Common Reporting Framework (CRF). The novel contribution of this model is that results are provided per administrative jurisdiction at multiple administrative levels, following the region boundaries defined OpenStreetMap, using a new spatialization approach. All data from this study are available on Zenodo https://doi.org/10.5281/zenodo.5482480 (Moran, 2021) and via an interactive map at https://openghgmap.net (last access: 7 February 2022​​​​​​​).

A gridded inventory of Canada’s anthropogenic methane emissions

Canada’s anthropogenic methane emissions are reported annually to the United Nations Framework Convention on Climate Change through Canada’s National Inventory Report (NIR). Evaluation of this policy-relevant inventory using observations of atmospheric methane requires prior information on the spatial distribution of emissions but that information is lacking in the NIR. Here we spatially allocate the NIR methane emissions for 2018 on a 0.1° × 0.1° grid (≈10 km × 10 km) for individual source sectors and subsectors, with further resolution by source type for the oil/gas sector, using an ensemble of national and provincial geospatial datasets and including facility-level information from Canada’s Greenhouse Gas Reporting Program. The highest emissions are from oil/gas production and livestock in western Canada, and landfills in eastern Canada. We find 11 hotspots emitting more than 1 metric ton h−1 on the 0.1° × 0.1° grid. Oil sands mines in northeast Alberta contribute 3 of these hotspots even though oil sands contribute only 4% of national oil/gas emissions. Our gridded inventory shows large spatial differences with the EDGAR v5 inventory commonly used for inversions of atmospheric methane observations, which may reflect EDGAR’s reliance on global geospatial datasets. Comparison of our spatially resolved inventory to atmospheric measurements in oil/gas production fields suggests that the NIR underestimates these emissions. We also find strong spatial overlap between oil/gas, livestock, and wetland emissions in western Canada that may complicate source attribution in inversions of atmospheric data.