The Impact of Restaurant Menu Eco Labels on Consumer Meal Selections: An RCT.

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

The rapid growth of vehicle sales and usage has highlighted the need for greenhouse gas (GHG) emission reduction in Macau, a special administrative region (SAR) of China. As the most primary vehicle type, light-duty vehicles (LDV, including light-duty gasoline vehicles (LDGVs) and light-duty diesel vehicles (LDDVs)) play a key role in promoting the GHG reduction and development of green transportation system in Macau. This study, on the basis of real-world tested and statistical data, firstly performed a streamlined life-cycle assessment (SLCA) on LDVs, to evaluate the potential GHG emissions and reduction through shifting to hybrid electric vehicles (HEVs) and electric vehicles (EVs). The results show that the mean GHG emissions from the LDGVs, LDDVs, and HEVs per 100 km were 25.16, 20.30, and 15.00 kg CO2 eq, respectively. Under the current electricity mix in Macau, EVs with the emissions of 12.39 kg CO2 eq/100 km can achieve a significant GHG emission reduction of LDVs in Macau. The total GHG emissions from LDVs increased from 124.99 to 247.82 thousand metric tons over the periods 2001–2014, with a 5.42% annual growth rate. A scenario analysis indicated that the development of HEVs and EVs—especially EVs—has the potential to control the GHG emissions from LDVs. Under the electricity mix of natural gas (NG) and solar energy (SE), the GHG emissions from EVs would drop by about 22 and 28%, respectively, by 2030. This study develops a useful approach to evaluate the potential GHG emissions and its reduction strategies in Macau. All the obtained results could be useful for decision makers, providing robust support for drawing up an appropriate plan for improving green transportation systems in Macau.

Relationship Between Nutrient Density and Greenhouse Gas Emissions of Lunches Served at a Large Urban School District

Devising policies for a low carbon city requires a careful understanding of the characteristics of urban residential lifestyle and consumption. The production-based accounting approach based on top-down statistical data has a limited ability to reflect the total greenhouse gas (GHG) emissions from residential consumption. In this paper, we present a survey-based GHG emissions accounting methodology for urban residential consumption, and apply it in Xiamen City, a rapidly urbanizing coastal city in southeast China. Based on this, the main influencing factors determining residential GHG emissions at the household and community scale are identified, and the typical profiles of low, medium and high GHG emission households and communities are identified. Up to 70% of household GHG emissions are from regional and national activities that support household consumption including the supply of energy and building materials, while 17% are from urban level basic services and supplies such as sewage treatment and solid waste management, and only 13% are direct emissions from household consumption. Housing area and household size are the two main factors determining GHG emissions from residential consumption at the household scale, while average housing area and building height were the main factors at the community scale. Our results show a large disparity in GHG emissions profiles among different households, with high GHG emissions households emitting about five times more than low GHG emissions households. Emissions from high GHG emissions communities are about twice as high as from low GHG emissions communities. Our findings can contribute to better tailored and targeted policies aimed at reducing household GHG emissions, and developing low GHG emissions residential communities in China.

Could urban electric public bus really reduce the GHG emissions: A case study in Macau?

Agricultural industries are under increasing pressure to measure and reduce greenhouse gas emissions from the supply chain. The Australian pork industry has established proactive goals to improve greenhouse-gas (GHG) performance across the industry, but while productivity indicators are benchmarked by industry, similar data have not previously been collected to determine supply chain GHG emissions. To assess total GHG emissions from Australian pork production, the present study conducted a life-cycle assessment of six case study supply chains and the national herd for the year 2010. The study aimed to determine total GHG emissions and hotspots, and to determine the mitigation potential from alternative manure treatment systems. Two functional units were used: 1 kg of pork liveweight (LW) at the farm gate, and 1 kg of wholesale pork (chilled, bone-in) ready for packaging and distribution. Mean GHG emissions from the case study supply chains ranged from 2.1 to 4.5 kg CO2-e/kg LW (excluding land-use (LU) and direct land use-change (dLUC) emissions). Emissions were lowest from the piggeries that housed grower-finisher pigs on deep litter and highest from pigs housed in conventional systems with uncovered anaerobic effluent ponds. Mean contribution from methane from effluent treatment was 64% of total GHG at the conventional piggeries. Nitrous oxide arose from both grain production and manure management, comprising 7–33% of the total emissions. The GHG emissions for the national herd were 3.6 kg CO2-e/kg LW, with the largest determining factor on total emissions being the relative proportion of pigs managed with high or low emission manure management systems. Emissions from LU and dLUC sources ranged from 0.08 to 0.7 kg CO2-e/kg LW for the case study farms, with differences associated with the inclusion rate of imported soybean meal in the ration and feed-conversion ratio. GHG intensity (excluding LU, dLUC) from the national herd was 6.36 ± 1.03 kg CO2-e/kg wholesale pork, with the emission profile dominated by methane from manure management (50%), followed by feed production (27%) and then meat processing (8%). Inclusion of LU and dLUC emissions had a minor effect on the emission profile. Scenarios testing showed that biogas capture from anaerobic digestion with combined heat and power generation resulted in a 31–64% reduction in GHG emissions. Finishing pigs on deep litter as preferred to conventional housing resulted in 38% lower GHG emissions than conventional finishing.

Well-to-wheel greenhouse gas emissions of electric versus combustion vehicles from 2018 to 2030 in the US

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

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.

Simple SummaryDairy farm system practices aimed at reducing nitrate leaching can also reduce emissions of the greenhouse gases methane and nitrous oxide. A study comparing ‘current’ and ‘improved’ grazed dairy system practices showed that ‘improved’ systems generally produced lower greenhouse gas emissions while milk production was maintained. The amount of feed eaten per hectare was the key driver of total greenhouse gas emissions per area, with ‘improved’ systems generally exhibiting lower total enteric methane and less N flowing through the herd.An important challenge facing the New Zealand (NZ) dairy industry is development of production systems that can maintain or increase production and profitability, while reducing impacts on receiving environments including water and air. Using research ‘farmlets’ in Waikato, Canterbury, and Otago (32–200 animals per herd), we assessed if system changes aimed at reducing nitrate leaching can also reduce total greenhouse gas (GHG) emissions (methane and nitrous oxide) and emissions intensity (kg GHG per unit of product) by comparing current and potential ‘improved’ dairy systems. Annual average GHG emissions for each system were estimated for three or four years using calculations based on the New Zealand Agricultural Inventory Methodology, but included key farmlet-specific emission factors determined from regional experiments. Total annual GHG footprints ranged between 10,800 kg and 20,600 kg CO2e/ha, with emissions strongly related to the amount of feed eaten. Methane (CH4) represented 75% to 84% of the total GHG footprint across all modelled systems, with enteric CH4 from lactating cows grazing pasture being the major source. Excreta deposition onto paddocks was the largest source of nitrous oxide (N2O) emissions, representing 7–12% of the total GHG footprint for all systems. When total emissions were represented on an intensity basis, ‘improved’ systems are predicted to generally result in lower emissions intensity. The ‘improved’ systems had lower GHG footprints than the ‘current’ system, except for one of the ‘improved’ systems in Canterbury, which had a higher stocking rate. The lower feed supplies and associated lower stocking rates of the ‘improved’ systems were the key drivers of lower total GHG emissions in all three regions. ‘Improved’ systems designed to reduced N leaching generally also reduced GHG emissions.

Polyethylene film mulch (PM) is a kind of widely used technology to improve crop yields worldwide; however, because of a problem related with plastic residual pollution, it has gradually been replaced by biodegradable plastic film mulch (BDP). Although BDP has helped to solve the plastic residual pollution, its consequences in terms of greenhouse gas (GHG) emissions have rarely been revealed. Related knowledge is important for forming low-carbon development strategies for the plastic industry and agriculture. The objective of this study is to evaluate the influence of BDP on GHG emissions at different stages of its life cycle, and determine whether replacing polyethylene (PE) film with BDP film is a helpful way to reduce national GHG emissions. The results of this study suggest that the application of BDP improved the GHG emissions associated with agricultural inputs, but induced lower GHG emissions at the growing stage and the waste disposal stage, and resulted in lower total area-scale GHG emissions. Compared to the no mulch (NM) cultivation system, the yield-scale carbon footprint was reduced in both the PM and BDP cultivation systems, which meant that both PM and BDP produced lower GHG emissions than NM for the production of the same amount of grain. It was concluded that BDP is not only a measure to control the problem of plastic residue pollution in agriculture, but it can also mitigate the GHG emissions.

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.

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 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’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. 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.