Energy Consumption and Greenhouse Gas Emission of Korean Offshore Fisheries

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.

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.

Greenhouse gas (GHG) emissions is one of the major environmental concerns of shale gas development. To better understand this specific environmental impact, this chapter develops a hybrid life cycle inventory (LCI) model to estimate the energy use and greenhouse gas (GHG) emissions of China’s shale gas development. Results suggest a total average energy use per well of 123 TJ (range: 74–165 TJ) and total average GHG emissions per well of 9505 tCO2e (range: 5346–13551 tCO2e). Most of the energy use and GHG emissions are indirect impacts embodied in fuels and materials. Energy use and GHG emissions from the drilling stage comprise the largest share in both totals due to large amounts of diesel used as fuel in the well drilling process and the materials used in the well casing process. Furthermore, the comparison shows that the energy use and GHG emissions of shale gas development in China will be much higher than the U.S.KeywordsShale gas developmentLife-cycle analysisGHG emissionsEnergy useEmbodied energy

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.

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

This study presents a holistic approach to evaluate energy performance and greenhouse gas (GHG) emissions from urban water supply and sanitation stages, which are important for sustainable water management and climate change mitigation. The study was conducted for Antalya city of Turkey to compare baseline and improved scenario conditions using the Energy Performance and Carbon Emissions Assessment and Monitoring (ECAM) tool. The current application of urban water and wastewater services was defined as the baseline scenario. For the improved urban water cycle, the reduction of non-revenue water, onsite sanitation prevention, increase in energy efficiency, biogas production and reuse of treated wastewater were investigated. Water supply and sanitation stages contributed to approximately 26 and 74% of total GHG emissions and 70 and 30% of energy consumption for the baseline scenario, respectively. GHG emissions were determined approximately as 52,423 tCO2eq/year for CO2 (40%), 47,029 tCO2eq/year for CH4 (35%) and 33,006 tCO2eq/year for N2O (25%) for the baseline scenario. The total GHG emissions of 132,457 tCO2eq/year and energy consumption of 136,328 MWh/year were reduced by 27.65% for GHG emissions and 16.48% for energy consumption for the improved urban water cycle. The outcomes of this research are expected to achieve sustainable cities and combat climate change.

This study investigates the effect of energy consumption on greenhouse gas (GHG) emissions in 33 African countries from 1995–2017. It contributes to the literature by investigating the effect of disaggregated measures of energy consumption (coal, oil and other liquids, renewable energy, and electricity) on GHG emissions (CO2, N2O, CH4, and total GHG emissions) in Africa and identifies the transmission channels through which energy consumption affects GHG emissions. The system GMM is used in the study as it accounts for possible endogeneity and the potential correlation between the error term and the country fixed effects. The results show that coal consumption significantly increases CO2, CH4, and total GHG emissions and reduces N2O emissions. Oil consumption increases CO2 and total GHG emissions but reduces N2O and CH4 emissions. Renewable energy consumption reduces CO2 and CH4 emissions but increases N2O emissions. Finally, electricity consumption promotes CO2, N2O, CH4 and total GHG emissions in Africa. Further analyses show that foreign trade and economic growth are the channels through which oil consumption increases GHG emissions. The adverse effect of electricity is through urbanization. Renewable consumption could decrease GHG emissions through sustainable urbanization and trade policies. The findings suggest that countries should gradually reduce coal consumption and encourage renewable energy consumption, which has the lowest impact on the environment.

The potential challenge for the effective GHG emissions mitigation of urban energy consumption: A case study of Macau

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.

Comparison of energy consumption and GHG emissions of open field and greenhouse strawberry production

As part of the Net Zero Carbon Water Cycle Program (NZCWCP) for Victoria state in Australia, we have sought to understand the potential to reduce household energy consumption and related Greenhouse Gas (GHG) emissions by influencing water use. Digital metering data disaggregated into 57 million discrete water usage events across 105 households at a resolution of 10 millilitres at 10 second intervals from June 2017 to March 2020, from a previous Yarra Valley Water (Melbourne, Australia) study, was analysed, together with the dynamic relationship between the multiple energy sources (natural gas, grid electricity, solar) used to heat water for showers in each hour of the day. Water-related energy (WRE) use, including water desalination and treatment, pumping, heating, wastewater collection and treatment, comprised 12.6% of Australia’s primary energy use in 2019. Water heating (by natural gas and electricity) comprised the largest component of WRE use for across residential, commercial, and industrial sectors. Furthermore, 69% of Victoria’s total water usage was by residential customers in 2020-2021. WRE GHG emissions were around 3.8% of Victoria’s total GHG emissions in 2018. Showers (~50% of residential WRE), system losses (~27% of residential WRE), and clothes washers (~9% of residential WRE) are the three largest components of WRE consumption. The main objective of this work is the creation of industry-accessible tools to improve knowledge and management options from the understanding of reductions in cost and GHG emissions from household showering WRE use. Potential options considered, to reduce water and energy use, as well as associated GHG emissions and customer utility bills, include (a) behaviour management such as water and energy pricing to change time of use behaviours, and (b) the adoption of efficient shower head improvements. Shower WRE and GHG emissions were found able to be strongly impacted by small changes in daily routines. GHG emissions reduction from showering could be reduced up to 20 (in summer) - 22% (in winter) by shifting demand time of showering or replacing residential showerheads. Extrapolated to state and Australian scales, reductions in water usage could be up to 14 GL (Victoria) and 144 GL (Australia), and reductions in GHG emissions 1,600 ktCO2eq (Victoria) and 17,300 ktCO2eq (Australia). It provides fundamental new information which could inform a suite of new management options to impact water-related energy from showers, and related GHG emissions and customer water and energy cost.

The decarbonisation of the construction sector is critical to meet national and international climate goals. Literature gives many examples of measures for the reduction of greenhouse gas (GHG) emissions from buildings. However, few studies investigate the trade-offs between potentially conflicting GHG emission reduction measures or the affordability of these measures. Ydalir is a Zero Emission Neighbourhood (ZEN) pilot area in the Norwegian research centre for Zero Emission Neighbourhoods in smart cities. One of the major challenges Ydalir faces is how to reduce GHG emissions from the neighbourhood towards a net zero emission building (nZEB). Additional challenges include retaining social, environmental, and economical sustainability for both the project developer and building owners and avoid suboptimal solutions. This paper investigates the trade-offs between energy efficiency and material use for two scenarios. The scenarios are a Norwegian building code scenario and a passive house scenario. The analysis ascertains total energy demand, whole life cycle GHG emissions, and cost assessment for two housing units within Ydalir Torg. The results show lower total GHG emissions and lower GHG emissions from operational energy use in the passive house scenario, and an increase in GHG emissions from the production phase due to thicker levels of insulation. The cost assessment shows increased investment costs for the project developer in the passive house scenario, despite lower operational costs for the building owner. Total GHG emission payback times for the passive house scenario are at 18 - 19 years. Cost payback time varies between 10 - 37 years. This paper is useful for practitioners that wish to balance GHG emission reduction requirements between operational energy use, material use and affordability.

In order to manage strategies to curb climate change, systemic benchmarking at a variety of production scales and methods is needed. This study is the first life cycle assessment (LCA) of a large-scale, vertically integrated organic dairy in the United States. Data collected at Aurora Organic Dairy farms and processing facilities were used to build a LCA model for benchmarking the greenhouse gas (GHG) emissions and energy consumption across the entire milk production system, from organic feed production to post-consumer waste disposal. Energy consumption and greenhouse gas emissions for the entire system (averaged over two years of analysis) were 18.3 MJ per liter of packaged fluid milk and 2.3 kg CO(2 )equiv per liter of packaged fluid milk, respectively. Methane emissions from enteric fermentation and manure management account for 27% of total system GHG emissions. Transportation represents 29% of the total system energy use and 15% of the total GHG emissions. Utilization of renewable energy at the farms, processing plant, and major transport legs could lead to a 16% reduction in system energy use and 6.4% less GHG emissions. Sensitivity and uncertainty analysis reveal that alternative meat coproduct allocation methods can lead to a 2.2% and 7.5% increase in overall system energy and GHG, respectively. Feed inventory data source can influence system energy use by -1% to +10% and GHG emission by -4.6% to +9.2%, and uncertainties in diffuse emission factors contribute -13% to +25% to GHG emission.

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

The reliance on groundwater for irrigation is increasing in Australia and India, which is causing concerns to policy makers about energy consumption and greenhouse gas (GHG) emissions. Therefore, it is important to quantify the GHG emissions of all components of the groundwater‐based irrigation systems, over the entire life cycle to develop more environmentally friendly groundwater management strategies. This study identified and analysed energy use and GHG emissions associated with different components in the supply chain of groundwater‐based irrigation systems. An existing GHG emissions and energy‐accounting framework was adapted to enhance its capabilities by considering drilling techniques, water distribution and irrigation application methods. The results of this study highlighted that embodied and direct GHG emissions from drilling tube wells were higher in the Musi catchment, India, compared to South Australia. The study also highlighted that GHG emissions associated with water conveyance were higher for concrete and plastic‐lined channels than unlined channels. Drip irrigation systems in both countries were found to have more GHG emissions than gravity‐fed systems. Centre pivot systems were found to be emitting more than the drip systems in South Australia. We conclude that different components of the system have an impact on total GHG emissions and energy consumption for both countries. Any change in the most commonly used methods of drilling bore wells, water distribution in channels, and the irrigation methods, will have distinct impacts on energy consumption rates and GHG emissions. The developed conceptual framework provided a systematic complete analysis of the energy‐consuming and GHG‐emitting components associated with groundwater‐based irrigation systems. Policy makers and decision makers may use the developed framework to compare different system components to develop strategies that have minimal impact on the environment. Copyright © 2015 John Wiley & Sons, Ltd.