Energy and CO<SUB align=right>2 efficiency dynamics in world regions

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Plastics and climate change—Breaking carbon lock-ins through three mitigation pathways

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia

Intensification pathways for beef and dairy cattle production systems: Impacts on GHG emissions, land occupation and land use change

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

The world population is expected to grow to about 10 billion in 2050. To supply the future human population with food while sustaining a liveable planet, food should be produced sustainably. One of the most urgent environmental issues is climate change, induced by greenhouse gas (GHG) emissions. The dairy sector is a large contributor to GHG emissions. Important GHGs related to milk production are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), mainly emitted during feed production, enteric fermentation, and manure management. Diseases in dairy cows can reduce milk production, reproduction performance and longevity, and increase the amount of discarded milk. The objectives of this thesis were to estimate the impact of diseases (subclinical ketosis, clinical mastitis, and foot lesions) on GHG emissions, and to understand the relation between impact of diseases on GHG emissions and economic performance. First, a dynamic stochastic simulation model was developed to simulate the dynamics of the diseases and the associated production losses (reduced milk production, discarded milk, a prolonged calving interval, and removal (culling or dying on the farm)) per cow during one lactation. This model was combined with a life cycle assessment to quantify the impact of diseases on GHG emissions per ton fat-and-protein-corrected milk (kg CO2equivalents/t FPCM) from cradle to farm gate. Processes included were feed production, enteric fermentation, and manure management. The emissions of GHGs of cows with a disease increased on average by 21 (2.3%) kg CO2e/t FPCM per case of subclinical ketosis, by 58 (6.2%) kg CO2e/t FPCM per case of clinical mastitis, by 4 (0.4%) kg CO2e/ t FPCM per case of digital dermatitis, by 39 (4.3%) kg CO2e/ t FPCM per case of white line disease, and by 33 (3.6%) kg CO2e/ t FPCM per case of sole ulcer. An economic analyses was performed to estimate the costs of subclinical ketosis and related diseases. The total costs of subclinical ketosis were €130 per case per year. Comparing the impact of production contributors from a GHG emissions and economic perspective showed that a reduction in milk production had the highest impact on the economic performance, whereas removal and discarded milk had the highest impact on increase in GHG emissions. Prevalence, pathogen type, farm management (e.g. culling, feed, and manure), and prices (e.g. milk and feed) will affect the impact of production contributors on GHG emissions and economic performance. Therefore, specific farm analyses are needed to estimate the impact of diseases for a specific dairy farm. Diseases in dairy cows increase GHG emissions by approximately 0.4 Mton per year, which equals 15% of the Dutch governmental goal of GHG emission reductions in agriculture in 2030. Reducing diseases can decrease GHG emissions, can increase the income of the farmer, and can improve animal welfare. Therefore, reducing diseases can contribute to sustainable development of the dairy sector.

Why carbon leakage matters and what can be done against it

Methods. This research employs econometric modeling and panel data analysis to investigate the intricate relationship between economic growth, environmental policies, and greenhouse gas (GHG) emissions within the European Union (EU). Panel data from 27 EU countries during the period from 2008 to 2021 is used to assess the impact of various factors on GHG emissions, including per capita GDP, primary energy consumption, renewable energy share, technological development, and extra-EU trade. Results. The study reveals that there is a positive correlation between GDP per capita and emissions, suggesting that the EU has not yet reached full decoupling of GDP growth and growth in GHG emissions. Increased primary energy consumption is associated with higher emissions, while a greater proportion of renewable energy sources is linked to reduced emissions. Technological advancements are found to mitigate GHG emissions. Importantly, the research uncovers a positive relationship between extra-EU trade and emissions, indicating the pollution leakage through trade. Novelty. This study contributes to the literature by offering a comprehensive examination of the dynamics between economic growth, changes in energy consumption, technological advancement, trade patterns, and GHG emissions within the EU. A more specific international trade variable is introduced into the model – the trade balance of EU countries with the outside EU countries. It explores the concept of pollution leakage, shedding light on how changes in foreign trade may impact emissions levels. Practical Value. The findings have significant policy implications, highlighting the need for a holistic approach to environmental policymaking within the EU. The study emphasizes that while progress has been made in adopting cleaner technologies and supporting renewable energy, challenges remain, including the potential for pollution leakage through international trade. This insight underscores the importance of globally impactful environmental policies and international cooperation to address GHG emissions effectively.

Abstract. The combustion of wood fuel for residential use is often not considered to be a source of greenhouse gas (GHG) emissions from households, as the emissions from wood fuel combustion can be offset by the CO2 absorbed by the growth of the forest (as a carbon sink) (IPCC, 2006). However, this only applies to wood that is harvested in a renewable way, i.e. at a rate not exceeding the regrowth rate of the forest from which it was harvested (Drigo et al., 2002). This paper estimates the share of GHG emissions attributable to non-renewable wood fuel harvesting for use in residential food activities, by country and with global coverage. It adds to a growing research base estimating GHG emissions from across the entire agri-food value chain, from the manufacture of farm inputs, through food supply chains, and finally to waste disposal (Tubiello et al., 2021). Country-level information is generated from United Nations Statistics Division (UNSD) and International Energy Agency (IEA) data on wood fuel use by households. We find that, in 2019, annual emissions from non-renewable wood fuel consumed for household food preparation were about 745×106 t (Mt CO2 eq. yr−1), with an uncertainty ranging from −63 % to +64 %. Overall, global trends were a result of counterbalancing effects: the emission increases were largely fuelled by countries in sub-Saharan Africa, southern Asia, and Latin America, whereas significant decreases were seen in countries in eastern Asia and South-East Asia. The Food and Agriculture Organization of the United Nations (FAO) has developed and regularly maintains a database covering GHG emissions from the various components of the agri-food sector, including pre- and post-production activities, by country and world regions. The dataset has been developed according to the International Panel on Climate Change guidelines (IPCC, 2006), which avoid overlaps between agriculture, forestry, and other land use (AFOLU) and energy components. The aforementioned dataset relies mainly on UNSD Energy Statistics data, which are used as activity data for the calculation of the GHG emissions (Tubiello et al., 2022). The information used in this work is available as open data at https://doi.org/10.5281/zenodo.7310932 (Flammini et al., 2022a).

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Understanding GHG emissions from Swedish consumption - Current challenges in reaching the generational goal

Nowadays, the global climate change has been a worldwide concern and the greenhouse gases (GHG) emissions are considered as the primary cause of that. The United Nations Conference on Environment and Development (UNCED) divided countries into two groups: Annex I Parties and Non-Annex I Parties. Since Iran and all other countries in the Middle East are among Non-Annex I Parties, they are not required to submit annual GHG inventory report. However, the global climate change is a worldwide phenomenon so Middle Eastern countries should be involved and it is necessary to prepare such a report at least unofficially. In this paper the terminology and the methods to calculate GHG emissions will first be explained and then GHG emissions estimates for the Iranian power plants will be presented. Finally the results will be compared with GHG emissions from the Canadian electricity generation sector. The results for the Iranian power plants show that in 2005 greenhouse gas intensity for steam power plants, gas turbines and combined cycle power plants were 617, 773, and 462 g CO2eq/kWh, respectively with the overall intensity of 610 g CO2eq/kWh for all thermal power plants. This GHG intensity is directly depend on efficiency of power plants. Whereas, in 2004 GHG intensity for electricity generation sector in Canada for different fuels were as follows: Coal 1010, refined petroleum products 640, and natural gas 523 g CO2eq/kWh, which are comparable with same data for Iran. For average GHG intensity in the whole electricity generation sector the difference is much higher: Canada 222 vs. Iran 610g CO2eq/kWh. The reason is that in Canada a considerable portion of electricity is generated by hydro-electric and nuclear power plants in which they do not emit significant amount of GHG emissions. The average GHG intensity in electricity generation sector in Iran between 1995 and 2005 experienced 13% reduction. While in Canada at the same period of time there was 21% increase. However, the results demonstrate that still there are great potentials for GHG emissions reduction in Iran’s electricity generation sector.

This study analyzed the greenhouse gas (GHG) emissions from the transportation sector in Korea from 1990 to 2013 using Logarithmic Mean Divisia Index (LMDI) factor decomposition methods. We decomposed these emissions into six factors: The population effect, the economic growth effect due to changes in the gross domestic product per capita, the energy intensity effect due to changes in energy consumption per gross domestic product, the transportation mode effect, the energy mix effect, and the emission factor effect. The results show that some factors can cause an increase in GHG emissions predominantly influenced by the economic growth effect, followed by the population growth effect. By contrast, others can cause a decrease in GHG emissions, predominantly via the energy intensity effect. Even though the transportation mode effect has contributed to a reduction of GHG emissions, it remains relatively small compared to other factors. The energy mix and emission factor effects contributed to the reduction of GHG emissions in the early 2000s, however the effects have led to an increase of GHG emissions since the mid-2000s. Altogether, based on these results, this study suggests some GHG mitigation policies aimed at achieving the national target for this sector.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

In 2000, the Intergovernmental Panel on Climate Change (IPCC) published a new set of baseline greenhouse gas (GHG) emissions scenarios in the Special Report on Emissions Scenarios (SRES) (Nakicenovic et al., 2000). The SRES team defined four narrative storylines (A1, A2, B1 and B2) describing the relationships between the forces driving GHG and aerosol emissions and their evolution during the 21st century. The SRES reports emissions for each of these storylines by type of GHG and by fuel type to 2100 globally and for four world regions (OECD countries as of 1990, countries undergoing economic reform, developing countries in Asia, rest of world). Specific assumptions about the quantification of scenario drivers, such as population and economic growth, technological change, resource availability, land-use changes, and local and regional environmental policies, are also provided. End-use sector-level results for buildings, industry, or transportation or information regarding adoption of particular technologies and policies are not provided in the SRES. The goal of this report is to provide more detailed information on the SRES scenarios at the end use level including historical time series data and a decomposition of energy consumption to understand the forecast implications in terms of end use efficiency to 2030. This report focuses on the A1 (A1B) and B2 marker scenarios since they represent distinctly contrasting futures. The A1 storyline describes a future of very rapid economic growth, low population growth, and the rapid introduction of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building, and increased cultural and social interactions, with a substantial reduction in regional differences in per capita income. The B2 storyline describes a world with an emphasis on economic, social, and environmental sustainability, especially at the local and regional levels. It is a world with moderate population growth, intermediate levels of economic development, and less rapid and more diverse technological change (Nakicenovic et al., 2000). Data were obtained from the SRES modeling teams that provide more detail than that reported in the SRES. For the A1 marker scenario, the modeling team provided final energy demand and carbon dioxide (CO{sub 2}) emissions by fuel for industry, buildings, and transportation for nine world regions. Final energy use and CO{sub 2} emissions for three sectors (industry, transport, buildings) for the four SRES world regions were provided for the B2 marker scenario. This report describes the results of a disaggregation of the SRES projected energy use and energy-related CO{sub 2} emissions for the industrial, transport, and buildings sectors for 10 world regions (see Appendix 1) to 2030. An example of further disaggregation of the two SRES scenarios for the residential buildings sector in China is provided, illustrating how such aggregate scenarios can be interpreted at the end use level.