Estimating GHG Emission Level from Oil and Gas Offshore Production Facility

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

The Intergovernmental Panel on Climate Change (IPCC) was established in 1988 to assess the risks and possible consequences of anthropogenic climate change. The IPCC includes a task force on national inventories, which develops methodological documents for national greenhouse gas inventories. The report 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories was adopted and accepted during the 49th Session of the IPCC in May 2019. The development of 2019 Refinement is related to the improvement of existing and the emergence of new technologies in the world economy, which has led to the need to update emission parameters and take into account new sources of greenhouse gas emissions and removals. The purpose of the article is to study and apply changes in the methods of estimating fugitive emissions in Ukraine’s gas industry, taking into account 2019 Refinement to the 2006 IPCC Guidelines for national greenhouse gas inventories. The article examines the state of greenhouse gas emissions in the gas industry in 2019 according to the Ukraine’s Greenhouse Gas Inventory Report data. The formation methane and carbon dioxide fugitive emissions in the last National Inventory Report according to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories is analyzed. The changes in the methods for national inventories in the energy sector 2019 Refinement are compared to the 2006 IPCC Guidelines. The estimation methane and carbon dioxide fugitive emissions in Ukraine’s gas industry in 2019 according to 2019 Refinement is made (taking into account the new emission factors and a new subcategory of abandoned wells). The article provides a comparative analysis the results with fugitive emissions in the gas industry in 2019 according to data of National Inventory Report. A study of the results shows that the use of 2019 Refinement for future greenhouse gas inventories will reduce methane and carbon dioxide emissions. Keywords: gas industry, greenhouse gas emissions, methane, carbon dioxide, inventory

Evaluation of the effect of accounting method, IPCC v. LCA, on grass-based and confinement dairy systems’ greenhouse gas emissions

城市温室气体排放清单编制研究进展

ABSTRACTThe open lots and manure stockpiles of dairy farm are major sources of greenhouse gas (GHG) emissions in typical dairy cow housing and manure management system in China. GHG (CO2, CH4 and N2O) emissions from the ground level of brick-paved open lots and uncovered manure stockpiles were estimated according to the field measurements of a typical dairy farm in Beijing by closed chambers in four consecutive seasons. Location variation and manure removal strategy impacts were assessed on GHG emissions from the open lots. Estimated CO2, CH4 and N2O emissions from the ground level of the open lots were 137.5±64.7 kg hd-1 yr-1, 0.45±0.21 kg hd-1 yr-1 and 0.13±0.08 kg hd-1 yr-1, respectively. There were remarkable location variations of GHG emissions from different zones (cubicle zone vs. aisle zone) of the open lot. However, the emissions from the whole open lot were less affected by the locations. After manure removal, lower CH4 but higher N2O emitted from the open lot. Estimated CO2, CH4 and N2O emissions from stockpile with a stacking height of 55±12 cm were 858.9±375.8 kg hd-1 yr-1, 8.5±5.4 kg hd-1 yr-1 and 2.3±1.1 kg hd-1 yr-1, respectively. In situ storage duration, which estimated by manure volatile solid contents (VS), would affect GHG emissions from stockpiles. Much higher N2O was emitted from stockpiles in summer due to longer manure storage.Implications: This study deals with greenhouse gas (GHG) emissions from open lots and stockpiles. It’s an increasing area of concern in some livestock producing countries. The Intergovernmental Panel on Climate Change (IPCC) methodology is commonly used for estimation of national GHG emission inventories. There is a shortage of on-farm information to evaluate the accuracy of these equations and default emission factors. This work provides valuable information for improving accounting practices within China or for similar manure management practice in other countries.

The effect of methodology on estimates of greenhouse gas emissions from grass-based dairy systems

Solely economic mitigation strategy suggests upward revision of nationally determined contributions

Combating climate change requires reducing greenhouse gas (GHG) emissions from human activities and enhancing carbon dioxide removal (CDR) through blue carbon ecosystems (BCEs). Progress is measured by international reporting of national GHG inventories under the UNFCCC, following IPCC guidelines. The EU Green Deal, particularly the EU Biodiversity Strategy to 2030, recognizes BCEs’ potential by advocating for the restoration of carbon-rich habitats. However, the IPCC Wetlands Supplement is underutilized in national GHG reporting, and few countries, especially in Europe, include blue carbon in their Nationally Determined Contributions (NDCs) under the Paris Agreement. This is due to limited awareness, the non-mandatory nature of the IPCC Wetlands Supplement, and data gaps. Our research aims to advance blue carbon knowledge, promoting BCEs as nature-based solutions, and addressing key gaps and scientific uncertainties to improve quantification and reporting of blue carbon under the UNFCCC in GHG inventory reporting under the Paris Agreement. The C-BLUES project, part of the Joint EU-China Flagship Initiative on Climate Change & Biodiversity, seeks to enhance the IPCC Wetlands Supplement, increase BCE inclusion in national GHG inventories, and explore additional BCEs like natural and farmed kelp systems. We document best practices for monitoring and verifying BCE actions, model BCE sequestration capacity, and upscale GHG budgets to estimate BCE contributions to EU and Chinese inventories. We assess carbon stock changes, GHG emissions, and removals from various management interventions, and evaluate the integration of BCEs into national reporting mechanisms. We present a roadmap and invite participation with the scientific community, policy makers and the wider civil society to generate knowledge, raise awareness of BCEs and build capacity for BC research, as well as provide guidance on voluntary reporting on BCE.

Making sense of methods to audit emissions – various audit methods to estimate dairy production carbon footprint

Comparison of greenhouse gas emission accounting methods for steel production in China

The Intergovernmental Panel on Climate Change (IPCC) estimate indirect N2O emissions from agriculture as 2.5% of nitrate leached, which is itself estimated as a proportion of manure/fertiliser inputs. However, this assumes leaching losses are linearly related to N inputs, over-simplifying a complex N loss function which depends on the interactions between over-winter rainfall, soil type, cropping, and the rate/timing of fertiliser/manure applications. Consideration of these factors would produce a more robust method for estimating N losses. Three alternatives were compared for estimating nitrate leaching and hence indirect N2O loss in England & Wales: (i) IPCC method, (ii) IPCC method using UK-specific manure inputs, (iii) NEAP-N, a model developed for modelling N losses at a national scale. Introducing UK-specific livestock manure data into the IPCC calculation reduced the mean indirect N2O loss from agricultural land from 19980 t N a−1 using default IPCC data (method (i)) to 14335 t N a−1 (method (ii)), indicating that IPCC default data are inappropriate for representing agricultural conditions in the UK. Adopting the NEAP-N method reduced the calculated indirect N2O flux further to 8890 t N a−1. The IPCC approach generated unrealistically low losses from peas/beans and ``zero'' loss estimates from fallow and set-aside land due to their nil fertiliser N additions, highlighting a limitation in this method which assumes all nitrate leaching is derived from fertiliser or manure additions. NEAP-N uses spatially distributed agricultural census information to relate land use and crop type to dominant soil type and hydrologically effective rainfall (HER), as it is these factors which strongly influence nutrient loss. In contrast, IPCC methods (i) and (ii) do not take account of soil type and HER factors, and simply compute nitrate leached as a function of nitrogen applied. Furthermore, the IPCC method, which is based solely on the amount of nitrogen applied, will not characterise reductions in nitrate loss arising from changes to the timing of fertiliser and/or manure applications. This is an important component of strategies to reduce agricultural nitrate loss (e.g. Nitrate Vulnerable Zone regulations). NEAP-N predictions of nitrate leaching losses compare favourably with measurements of stream nitrate fluxes, whereas IPCC methods repeatedly overestimate measured loss two or threefold. We conclude that, for the UK, country-specific estimates using NEAP-N should be used in national greenhouse gas inventories in preference to values using the default IPCC method.

The energy mix serves as the basis for calculating the greenhouse gas (GHG) emission factor of electricity, and therefore has a significant impact not only on the evaluation of GHG-related policies but also on the carbon footprint of industries that use electricity in life cycle assessments (LCA). As such, there is a need to annually publish GHG emission factors that reflect changes in the energy mix. The purpose of this study is to present IPCC- and LCA-based GHG emission factors and GHG emissions for the energy sector based on changes in the energy mix, and to assess whether the nationally determined contribution (NDC) can be achieved under these conditions. To achieve this, the study applies Intergovernmental Panel on Climate Change (IPCC) and LCA-based GHG emission factors for each power source to the energy mix outlined in the 10th Basic Plan for Electricity Supply and Demand, calculating annual (2018~2036) national electricity GHG emission factors and emissions, and analyzing the feasibility of meeting the NDC target. The analysis revealed that GHG emission factors fluctuate significantly with changes in the energy mix, underscoring the need for annual calculations. Under the planned energy mix, GHG emissions from the energy transition sector are projected to reach 159.9 million tons CO2eq, which exceeds the NDC target of 149.9 million tons CO2eq. However, reducing coal-fired power generation by 10% and replacing it with offshore wind and solar power could make achieving the target feasible. Additionally, the LCA-based GHG emission factors indicate that expanding offshore wind and solar power instead of relying on hydrogen and ammonia in the energy mix could achieve a 2.5% reduction. Therefore, adopting methodologies such as those used in this study to calculate annual GHG emission factors would allow efforts to transition the energy mix to be immediately reflected. Furthermore, when planning the energy mix, an LCA-based approach rather than an IPCC-based approach would provide a more effective means of responding to practical environmental regulations

Abstract. The Paris Agreement commits 197 countries to achieve climate stabilisation at a global average surface temperature less than 2 ∘C above pre-industrial times using nationally determined contributions (NDCs) to demonstrate progress. Numerous industrialised economies have targets to achieve territorial climate neutrality by 2050, primarily in the form of “net zero” greenhouse gas (GHG) emissions. However, particular uncertainty remains over the role of countries' agriculture, forestry, and other land use (AFOLU) sectors for reasons including the potential trade-offs between GHG mitigation and food security, a non-zero emission target for methane as a short-lived GHG, and the requirement for AFOLU to act as a net sink to offset residual emissions from other sectors. These issues are represented at a coarse level in integrated assessment models (IAMs) that indicate the role of AFOLU in global pathways towards climate stabilisation. However, there is an urgent need to determine appropriate AFOLU management strategies at a national level within NDCs. Here, we present a new model designed to evaluate detailed AFOLU scenarios at national scale using the example of Ireland, where approximately 40 % of national GHG emissions originate from AFOLU. GOBLIN (General Overview for a Backcasting approach of Livestock INtensification) is designed to run randomised scenarios of agricultural activities and land use combinations within biophysical constraints (e.g. available land area, livestock productivities, fertiliser-driven grass yields, and forest growth rates). Using AFOLU emission factors from national GHG inventory reporting, GOBLIN calculates annual GHG emissions out to the selected target year for each scenario (2050 in this case). The long-term dynamics of forestry are represented up to 2120 so that scenarios can also be evaluated against the Paris Agreement commitment to achieve a balance between emissions and removals over the second half of the 21st century. Filtering randomised scenarios according to compliance with specific biophysical definitions (GHG time series) of climate neutrality will provide scientific boundaries for appropriate long-term actions within NDCs. We outline the rationale and methodology behind the development of GOBLIN, with an emphasis on biophysical linkages across food production, GHG emissions, and carbon sinks at a national level. We then demonstrate how GOBLIN can be applied to evaluate different scenarios in relation to a few possible simple definitions of “climate neutrality”, discussing opportunities and limitations.

The European Union (EU) has proposed legislative revisions to achieve climate neutrality in EU by 2050. The Land Use, Land-Use Change and Forestry (LULUCF) Regulation, adopted in 2018, is being revised to ensure that accounted greenhouse gas (GHG) emissions from LULUCF are balanced by equivalent accounted removals of carbon dioxide (CO2) from the atmosphere. This study focuses on the impact of targeted tree introduction in agricultural land in Latvia, specifically afforestation of drained organic soil and implementation of agroforestry systems (riparian buffer strips), on national GHG reduction targets for the LULUCF sector. The potential contributions of selected measures were evaluated using evaluation methods including GHG emissions factors based on the Intergovernmental Panel on Climate Change (IPCC) guidelines and recent scientific studies. The study differentiated between different land use categories by GHG emissions from soil and CO2 removals in living biomass, dead wood, litter, mineral soil, and organic soil. Basic scenarios were compared with additional scenarios that included afforestation of drained organic soils and implementation of agroforestry systems. The study analysed the possibilities of achieving LULUCF sector goals for 2030, 2035, and 2050 with the selected scenarios. According to the basic scenarios, the LULUCF sector has been a continuous source of GHG emissions since 2019, partly compensated by forest management by 2040, but after 2040 forest management becomes a source of GHG emissions as well. The study shows that afforestation of organic soils currently used for agricultural production can reduce GHG emissions and ensure the achievement of national LULUCF targets for 2021-2025, with a significant decrease in GHG emissions by 3.9 million t CO2 eq. during the 2021-2025 period if compared to the basic scenario. However, the study finds that national target of net GHG removals is not achieved for 2026-2030 according to both basic and afforestation scenarios if no additional measures, e.g., establishment of the shelter belts, are implemented.

The activity of exploration and production in oil and gas industry is significant greenhouse gas (GHG) emission source. PT. XYZ is one of upstream oil and gas industry in Indonesia and it have large crude oil and gas potential with it reserves that not manage yet. Therefore, GHG emission potential from the activity of exploration and production in PT. XYZ is very large. This study is done for estimate GHG emission reduction potential in PT. XYZ from various activities. Emission inventory is the first step to estimate GHG released to atmosphere. Method of estimation use the method developed by American Petroleum Institute (API). This study considers three types of mitigation measures options, including technical options (scenario 1), behavior option (scenario 2), and policy option (scenario 3). Based on emission inventory, flare and oil storage tank are primary source of GHG emissions in PT. XYZ. Scenario 1 prefers control of GHG emissions in flare and storage tank as primary emission source. While others scenario prefers to control GHG emission from transportation sector. Scenario 1 has potential to reduce emissions by 48.3 %. While scenario 2, and 3 in sequences have potential to reduce emissions by 0.15%, and 0.52%. Emissions flare and oil storage tank can be reduced through the installation of flaring gas recovery unit and vapor recovery unit. Both are effective and efficient in reducing GHG emissions in PT. XYZ. In addition, all mitigation measures of transportation sector provide benefits even though the amount of GHG that can be reduced is not significant.