ENVIRONMENTAL CONSUMPTION TAXES ON ANIMAL FOOD PRODUCTS TO MITIGATE GREENHOUSE GAS EMISSIONS FROM THE EUROPEAN UNION

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.

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

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Simple SummaryLivestock accounts for an estimated 80% of total agricultural greenhouse gas emissions, making abatement of greenhouse gas emissions from livestock a high-priority challenge facing animal nutritionists. Mitigating greenhouse gases in ruminants without reducing animal production is desirable both as a strategy to reduce global greenhouse gas emissions and as a way of improving dietary feed efficiency. The inclusion of feed additives in the diets of ruminants can reduce energy losses as methane, which typically reduces animal performance and contributes to greenhouse gas emissions. The present study evaluated the abatement potential of nine essential oil blends to mitigate greenhouse gas emissions. The inclusion of the blends resulted in a reduction in greenhouse gas emissions and in vitro apparent dry matter digestibility with higher values noted for the control treatment. A similar trend was noted for in vitro truly dry matter digestibility with higher values noted in the control treatment. The efficiency of microbial production was greater for the blends. The inclusion of the blends affected the total and molar proportion of volatile fatty acid concentrations. Overall, inclusion of the blends modified the rumen function resulting in improved efficiency of microbial production.The current study evaluated nine essential oil blends (EOBs) for their effects on ruminal in vitro dry matter digestibility (IVDMD), efficiency of microbial production, total short-chain fatty acid concentration (SCFA), total gas, and greenhouse gas (GHG) emissions using two dietary substrates (high forage and high concentrate). The study was arranged as a 2 × 2 × 9 + 1 factorial design to evaluate the effects of the nine EOBs on the two dietary substrates at two time points (6 and 24 h). The inclusion levels of the EOBs were 0 µL (control) and 100 µL with three laboratory replicates. Substrate × EOBs × time interactions were not significant (p > 0.05) for total gas and greenhouse gas emissions. The inclusion of EOBs in the diets resulted in a reduction (p < 0.001) in GHG emissions, except for EOB1 and EOB8 in the high concentrate diet at 6 h and for EOB8 in the high forage diet at 24 h of incubation. Diet type had no effect on apparent IVDMD (IVADMD) whereas the inclusion of EOBs reduced (p < 0.05) IVADMD with higher values noted for the control treatment. The efficiency of microbial production was greater (p < 0.001) for EOB treatments except for EOB1 inclusion in the high forage diet. The inclusion of EOBs affected (p < 0.001) the total and molar proportion of volatile fatty acid concentrations. Overall, the inclusion of the EOBs modified the rumen function resulting in improved efficiency of microbial production. Both the apparent and truly degraded DM was reduced in the EOB treatments. The inclusion of EOBs also resulted in reduced GHG emissions in both diets, except for EOB8 in the high forage diet which was slightly higher than the control treatment.

In this study, a comparative analysis was presented to detect the quota of urban and rural areas from total greenhouse gas (GHG) emissions in 26 selected countries of the Middle East and Central Asia (MECA) during 1994–2014. For this purpose, 18 independent variables such as land area, population characteristics, energy use and consumption, gross domestic product (GDP), CO2 emissions, etc., were considered in addition to one dependent variable of total GHG emissions. Statistical modeling to investigate GHG emissions was constructed comprising the quantitative procedures of the correlation test and clustering analysis, which can be considered as the fundamental basis of each econometric analysis. The GHG emissions from the urban (rural) sector of total countries in 2014 were obtained as 3313.4 (1135.6) Mt of CO2 equivalents, which is about 74.5% (25.5%) of the total GHG emissions (4449.1 Mt of CO2 equivalents) in the MECA region. The correlation test between GHG emissions and urban indicators revealed the significant records (R from 0.745 to 0.981) compared with rural indicators (R from 0.337 to 0.890). Based on the clustering analysis of the countries, Cluster A, comprised of three countries of Iran, Saudi Arabia, and Turkey, was categorized as countries with very high contributing to the total GHG emissions in the MECA region (~ 43.3%). The quotas of emissions from urban and rural sectors in the Cluster A were estimated as 83.1% and 16.9% from the total GHG emissions in 2014 (1921.3 Mt of CO2), while the same quotas were predicted as 73.1% and 26.9% from the total GHG emissions in 2030 (1921.3 Mt of CO2). This study carried out comprehensive research on the GHG emissions from the urban and rural areas in a crucial region of the world, which is faced with the rising growth of population, urbanization, globalization, high-energy use, and fuel consumption.

The Republic of Korea submitted its updated Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change (UNFCCC) Secretariat in December 2021. The updated NDC target is to reduce total national greenhouse gas (GHG) emissions by 40% from the 2018 level, which is 727.6 Mt CO2eq, by 2030. According to the updated NDC, local governments are also required to revise their GHG reduction plans. In addition, local governments should self-inspect the progress and major achievements of the GHG reduction plan every year in accordance with the evaluation guideline of the Ministry of Environment. Of 6 metropolitan cities, Gyeonggi Province shows the highest GHG emissions in the country, which accounts for about 17% of the total national GHG emissions in 2021. Ironically, Goyang City, a basic local government of Gyeonggi Province, was selected as one of the seven best local governments for carbon neutrality in 2021. The City has set a reduction target of 32.8% below BAU by 2030 and prepared a plan to implement reduction targets by sector. Over the last decade, building and transportation sectors have been the major sources of GHG emissions in Goyang City, accounting for approx. 70% of the city&amp;#8217;s total GHG emissions. The city promotes zero-energy building (ZEB) for newly constructed buildings and encourages green remodeling for existing buildings in order to reduce GHG emissions in the building sector. It is essential to introduce renewable energy such as solar, geothermal, hydrothermal, etc. for ZEB and green remodeling. In this study, therefore, the potential for solar power generation, which is most easily applicable to the building sector, and GHG reduction were calculated for residential buildings in Goyang City. To calculate the available area for solar power on the roof of residential buildings, spatial data was constructed using high-resolution aerial photographs and the outline of the building roof was extracted through AI training data.&amp;#160;AcknowledgementsThis research was carried out as a part of KICT Research Program (Data-Centric Checkup Technique of Building Energy Performance) funded by the Ministry of Science and ICT.

Kupang city is growth rapidly and located in a strategic position between Australia and Timor Leste. A sharp increase of GHG emission along with environmental pollution, contamination of water, air and improper waste disposal practices as its consequence to the global environment. The city's government ambition to evaluate impact of economic activity on greenhouse gases (GHG) emission contribution. This paper outlined pollutant sectors that contribute substantially to GHG emission in Kupang along with its structure, and count an estimated amount of emission coefficients for 27 economy sectors. More in-depth explanation about indirect coefficient pollutant emission which beneficial not only for calculation of the emission amount but more as inventory data for LCA. The paper is investigated review the trends of some priority sectors, then introduction of indirect coefficients of pollutant sectors, and showed the Pollutant Emission Structure for Kupang. After that, an estimated amount of Kupang GHG emission under BAU is also counted and confirmed. The paper only considers GHG emission issues while air pollutant emission only be provided as inventory data but will not be used as exogenous data for this paper. In the final part a brief explanation and implications of GHG emission policy in Kupang are identified. A detailed of input-output data for individual process are provided includes all groups of processes or industry sectors relevant to economy activities in Kupang City. A time period for Global Warming Potential (GWP) 20 year and 100 years are used to forecasted amounts share of total GHG emission in Kupang and Indonesia by 2020 compared to 2010. As results first, the GHG emission and air pollutant coefficients for 27 sectors in Kupang based on method is presented in NIES which use to count the GHG emission. These also become an Inventory data for researchers of regional science in Indonesia, however, geography and socioeconomic conditions in every region is different, so that some criteria will be applied. Second, found total GHG emission in Kupang is $1.0164\mathrm{x} 10^{-3}$ Gt or around 0.047% compared to total GHG emission by 2010 and 0.034% compared to total GHG emission by 2020 in Indonesia. The study suggests to government consider a proper method in decide a reliable environmental policy and technical measures to reach GHG emission targets by 2020. Third, total share of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> e in Indonesia emitted from Kupang for GWP 20 years and 100 years respectively were came out as follow.

Which type of electric vehicle is worth promoting mostly in the context of carbon peaking and carbon neutrality? A case study for a metropolis in China

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system. The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis. The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 104 t CO2eq year−1, 64.9%) is the most significant for total GHG emissions (5.65 × 104 t CO2eq year−1) because a huge amount of CH4 (3.51 × 104 t CO2eq year−1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH4 emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions. This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

Studies on the sustainability of crop production systems should consider both the carbon (C) footprint and the crop yield. Knowledge is urgently needed to estimate the C cost of maize (Zea mays L.) production in a continuous monoculture or in rotation with a leguminous crop, the popular rotation system in North America. In this study, we used a 19-year field experiment with maize under different levels of synthetic N treatments in a continuous culture or rotation with forage legume (Alfalfa or red clover; Medicago sativa L./Trifolium pratense L.) or soybean (Glycine max L. Merr) to assess the sustainability of maize production systems by estimating total greenhouse gas (GHG) emissions (kg CO2 eq ha−1) and the equivalent C cost of yield or C footprint (kg CO2 eq kg−1 grain). High N application increased both total GHG emissions and the C footprint across all the rotation systems. Compared to continuous maize monoculture (MM), maize following forage (alfalfa or red clover; FM) or grain (soybean; SM) legumes was estimated to generate greater total GHG emissions, however both FM and SM had a lower C footprint across all N levels due to increased productivity. When compared to MM treated with 100 kg N ha−1, maize treated with 100 kg N ha−1, following a forage legume resulted in a 5 % increase in total GHG emissions while reducing the C footprint by 17 %. Similarly, in 18 out of the 19-year period, maize treated with 100 kg N ha−1, following soybean (SM) had a minimal effect on total GHG emissions (1 %), but reduced the C footprint by 8 %. Compared to the conventional MM with the 200 kg N ha−1 treatment, FM with the 100 kg N ha−1 treatment had 40 % lower total GHG emissions and 46 % lower C footprint. Maize with 100 kg N ha−1 following soybean had a 42 % lower total GHG emissions and 41 % lower C footprint than MM treated with 200 kg N ha−1. Clearly, there was a trade-off among total GHG emissions, C footprint and yield, and yield and GHG emissions or C footprint not linearly related. Our data indicate that maize production with 100 kg N ha−1 in rotation with forage or grain legumes can maintain high productivity while reducing GHG emissions and the C footprint when compared to a continuous maize cropping system with 200 kg N ha−1.

Whole-farm systems modelling of greenhouse gas emissions from pastoral suckler beef cow production systems

We used the Agriculture and Land Use National Greenhouse Gas Inventory Software to estimate the total greenhouse gas (GHG) emissions from the Nigerian agriculture sector in 2010. We went ahead to project future GHG emissions up to 2050. Two alternative GHG mitigation scenarios such as moderate (MS) and aggressive (AS) scenarios were developed and examined. Our results showed that total GHG emissions from Nigerian agriculture in 2010 were around 34.9million tonnes of carbon dioxide equivalent. GHG emissions from livestock accounted for about 69.2 % of the total emissions, making it the largest source of GHG emissions in the sector. Nigeria's agriculture GHG emissions are expected to increase by 94 % in 2050 relative to 2010 levels. Mitigation strategies in the Nigerian agriculture sector that do not compromise food security are limited. However, with the implementation of different GHG mitigation strategies in the alternative scenarios, emissions are expected to fall by around 13.2 % and 26.7 % by 2050 in the MS and AS, respectively, compared to the baseline scenario. While the mitigation potentials are significant, we argue that robust and dedicated policies are required to accelerate climate-smart agriculture in Nigeria.

Understanding urban spatial heterogeneity of greenhouse gas (GHG) emissions from sectoral household consumption is crucial to facilitate moves towards low-carbon cities. In this study, we use Xiamen city of China as a case study to reveal the emission characteristics of household GHG as well as spatial heterogeneity. We conducted a face-to-face questionnaire survey and calculated GHG emissions of districts from household energy consumption, food consumption, transportation, housing, household waste and wastewater treatment. The GHG emissions and the amount of urban residential household consumption shows obvious spatial heterogeneity across districts. Total GHG emissions of Xiamen city were 8.39 Mt. CO2e, and average household and per capita of GHG emissions were 8.11 and 2.72 tCO2e, respectively. While total GHG emissions vary from 0.41 to 2.45 Mt. CO2e across six districts and range from 0.16 to 3.39 Mt. CO2e among six sectors. Household GHG emissions differ from 7.08 to 9.40 tCO2e, while the per capita emissions range between 2.41 to 3.14 tCO2e among districts. Results also showed that more urbanized areas with higher population density have larger total urban residential GHG emissions, whereas household emissions were comparatively lower in these areas. In contrast, our study did not show an (inverted-) U relationship or linear relationship between emissions and population, nor between emissions and income level. Household energy use is the largest sector emitting GHGs. These findings will be useful to underpin policy making towards low-carbon cities.

The objective of the research was to create improved understanding of the significance of diverse factors for the total greenhouse gas (GHG) emissions of buildings. The specific focus of the study was on the assessment of the significance of building materials and embodied carbon. The scope of the study covers multi-storey residential buildings in Finland. This research was based on a literature survey and supported by a parametric case study. The parametric study assessed the building-material-related GHG emissions relative to total GHG emissions and the possible range of variation. The research assesses the minimum and maximum GHG emissions for production of buildings with similar spaces, to reveal the likely range of variation for the emissions. The calculations for the ‘minimum’ and ‘maximum’ scenarios assume a similar purpose of use, occupancy and spaces in the building, while the production methods, materials, site conditions and location are varied. The research also assesses the relative importance of various building components and other calculation parameters in terms of GHGs. Total material-related GHG emissions were compared with the GHG emissions caused by the operation of the building, at three distinct levels of energy performance. In addition, the material- and operation-related GHG emissions were compared with the location-related GHG emissions arising from people's mobility.

Livestock are by far the greatest contributor to Australian agricultural greenhouse gas (GHG) emissions and are projected to account for 72% of total agricultural emissions by 2020. This necessitates the development of GHG mitigation strategies from the livestock sector. Currently there are many research streams investigating the efficacy of GHG mitigation technologies, though most are at the individual animal level. Here we examine the effect of a promising animal-scale intervention - increasing ewe fecundity - on GHG emissions at the whole farm scale. This approach accounts for seasonal climatic influences on farm productivity and the dynamic interactions between variables. The study used a biophysical model and was based on real data from a property in south-eastern Australia that currently runs a self-replacing prime lamb enterprise. The breeding flock was a composite cross-bred genotype segregating for the FecB gene (after the 'fecundity Booroola' trait observed in Australian Merinos), with typical lambing rates of 150-200% lambs per ewe. Lambs were born in mid-winter (July) and were weaned and sold at 18 weeks of age at the beginning of summer (December). Livestock continuously grazed pastures of phalaris, cocksfoot and subterranean clover and were supplied with barley grain as supplementary feed in seasons when pasture biomass availability was low. Biophysical variables including pasture phenology and flock dynamics were simulated on a daily time-step using the model GrassGro with historical weather data from 1970 to 2012. Whole farm GHG emissions were computed with GrassGro outputs and methodology from the Australian National Greenhouse Accounts Inventory (DCCEE, 2012). Increasing ewe fecundity from 1.0 lamb per ewe at birth (equivalent to scanning rates at pregnancy of 80% of ewes with single lambs, 17% with twins and 3% empty) to 1.5 (scanning rates of 20% ewes with singles, 51% with twins, 26% with triplets and 3% empty as observed at the property) reduced mean emissions intensity from 9.3 to 7.3 t CO2-equivalents/t animal product and GHG emissions per animal sold by 32%. Increasing fecundity reduced average lamb sale liveweight from 42 to 40 kg, but this was offset by an increase in annual sheep sales from 8 to 12 head/ha and an increase in average annual meat production from 410 to 540 kg liveweight/ha. A key benefit associated with increasing sheep fecundity is the ability to increase enterprise productivity whilst remaining environmentally sustainable. For the same long-term average annual stocking rate as an enterprise running genotypes with lower fecundity, it was shown that genotypes with high fecundity such as those on the property could either increase meat and wool productivity from 449 to 571 kg/ha (clean fleece weight plus liveweight at sale) with little change in net GHG emissions, or reduce net GHG emissions from 4.1 to 3.2 t CO2-equivalents/ha for similar average annual farm productivity. In either case, GHG emissions intensity was reduced by about 2.1 t CO2-equivalents/t animal product. From a methodological perspective, this study revealed that differences in computing the relative effect of increased fecundity on total farm production, GHG emissions or emissions intensity either within or across years were relatively small. For example, the mean difference in emissions intensity of an enterprise obtaining 1.5 lambs per ewe relative to an enterprise obtaining 1.0 lamb per ewe computed within years was -25%, whereas the relative difference in mean emissions intensity across years was -27%. Such findings justify the traditional approach of previous GHG mitigation studies which compare differences (e.g. abatement potential) between values averaged across multiple-year simulation runs, as opposed to the method of computing the differences between intervention strategies within years then comparing the average difference.