Energy efficiency and greenhouse gas emission intensity of petroleum products at U.S. refineries.

Life-cycle analysis on energy consumption and GHG emission intensities of alternative vehicle fuels in China

Life-cycle fossil energy consumption and greenhouse gas emission intensity of dominant secondary energy pathways of China in 2010

Environmental pollution and climate change have become nontraditional global security threats. As China's economy grows, the country faces an increasing number of challenges associated with improving atmospheric quality and reducing greenhouse gas emissions. Based on China's dynamic noncompetitive input-output tables and data on energy consumption and emissions from 1994 to 2016, a hybrid input-output model is constructed to identify high-energy-consuming sectors and to quantify the impact of industrial restructuring on the intensity of air pollutant and greenhouse gas emissions from these sectors. The empirical results indicate that the impact of industrial restructuring on the intensity of air pollutant and greenhouse gas emissions from high-energy-consuming sectors was nonlinear and has undergone a "promotion reduction" shift. This study also found that the impact of industrial restructuring is more significant on the intensity of greenhouse gas emissions than on the intensity of air pollutant emissions; furthermore, the reduction in greenhouse gas emission intensity achieved by industrial restructuring after 2008 began to show results. Based on the findings of this study, we make recommendations such as the need for the Chinese government to continue to promote supply-side structural reforms in the energy sector.

This article explores therelationship among farm‐level productivity growth, scale, and greenhouse gas (GHG) emission intensity during a time period of significant agricultural policy change affecting Ireland's dairy industry. Specifically, we focus on the 2015 EU milk quota abolition, which initiated major dairy expansion in Ireland. We use a representative sample of Irish dairy farms from 2000 to 2017, that includes data on farm specific GHG emissions. Based on this detailed farm level panel data set, we estimate productivity with a control function approach. We then apply fixed effects and dynamic panel data methods to explore the implications of productivity and scale on GHG emission intensity. Our findings indicate that increased productivity is negatively associated with GHG emission intensity, which changes with distinct milk quota abolition phases. Overall, our findings are important for understanding the relationship between policy reforms and GHG emissions in agriculture, and how to improve agricultural mitigation strategies.

Adjusting transportation structure to reduce the intensity of greenhouse gas emissions is an effective way to address climate change issues. This paper selects six transport sectors and constructs a hybrid input-output model to study the impact of transportation restructuring on the intensity of CO2 and non-CO2 greenhouse gas emissions in each sector during different periods. The results show that the effect of transportation restructuring on greenhouse gas emissions is manifested differently in different time periods. After 2008, transportation restructuring had a significant effect on reducing the intensity of greenhouse gas emissions in all sectors. However, the impact of transportation restructuring on the intensity of non-CO2 greenhouse gas emissions is limited. It is also found that the railway transport sector has been a low-impact transport sector in terms of greenhouse gas emissions since 2004, which provides insights for the optimization of China’s transportation structure.

This research aims to evaluate the relationship between greenhouse gas emissions and economic growth [measured by GDP (gross domestics product) and GDP per capital] in Vietnam. The authors used the data compiled from the WB (word bank) database and time series estimation method. The results from models show that the factors affecting the intensity of CO2 emissions in Vietnam are statistically significant, at 1%, 5% and 10%, with the impact level of emission intensity (with a lag of 2 ) at -0.48; economic growth rate at 29180.49 (with a lag of 1); and the square of economic growth rate at - 14588.66 (with a lag of 1), with the model's explanatory level of 56.54%. In addition, the coefficient of the quadratic function is negative, illustrated by a downward curve in the graph representing the relationship between economic growth and emissions, reflecting correctly the environmental Kuznet curve. At the same time, the figures of Granger Causality Tests reveal that there is a causal relationship between the economic growth rate and the intensity of CO2 greenhouse gas emissions in Vietnam during the research period, with a significance level of 5. %. Economic growth exacerbates the intensity of greenhouse gas (CO2) emissions, and this increase has a return effect on growth (positive effect). However, with the square of economic growth rate doubling, this relationship will tend to be negative. On the basis of the analysis results, the study also proposes some policy implications which reduce the intensity of greenhouse gas emissions and aim to promote green growth in Vietnam: (1) reducing emission sources in economic fields: industry, agriculture, services; (2) reducing the use of fossil energy which should be replaced by Renewable energy (energy from wind and solar); (3) applying modern science and technology in production and economic activities; (4) completing the legal framework to encourage economic sectors and businesses to use natural resources effectively; (5) The Government should enact policies to encourage all economic sectors to apply modern technology in production.

Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil

To achieve net zero emissions, the global transportation sector needs to reduce emissions by 90% from 2020 to 2050, and road freight has a significant potential to reduce emissions. In this context, emission reduction paths should be explored for road freight over the fuel life cycle. Based on panel data from 2015 to 2020 in China, China's version of the GREET model was established to evaluate the impact of crude oil mix, electricity mix, and vehicle technology on China's reduction in road freight emissions. The results show that the import share of China's crude oil has increased from 2015 to 2020, resulting in an increase in the greenhouse gas (GHG) emission intensity of ICETs in the well-to-tank (WTT) stage by 7.3% in 2020 compared with 2015. Second, the share of China's coal-fired electricity in the electricity mix decreased from 2015 to 2020, reducing the GHG emission intensity of battery electric trucks (BETs), by approximately 6.5% in 2020 compared to 2015. Third, different vehicle classes and types of BETs and fuel cell electric trucks (FCETs) have different emission reduction effects, and their potentials for energy-saving and emission reduction at various stages of the fuel life cycle are different. In addition, in a comparative study of vehicle technology, the results show that (1) for medium-duty trucks (MDTs) and heavy-duty trucks (HDTs), FCETs have lower GHG emission intensity than BETs, and replacing diesel-ICETs can significantly reduce GHG emissions from road freight; (2) for light-duty trucks (LDTs), BETs and FCETs have the highest GHG emission reduction potential; thus, improving technologies such as electricity generation, hydrogen fuel production, hydrogen fuel storage, and transportation will help to improve the emission reduction capabilities of BETs and FCETs. Therefore, policymakers should develop emission standards for road freight based on vehicle class, type, and technology.

Recent regulatory and voluntary initiatives to estimate supply chain greenhouse gas (GHG) emissions intensity of liquefied natural gas (LNG) have emphasized the use of direct measurements as activity-based national inventories tend to systematically underestimate GHG emission intensities. In this work, we synthesize results from a three-year measurement campaign across production, midstream, and liquefaction stages into a life cycle assessment (LCA) framework to assess the GHG emissions intensity of U.S. LNG supply chains. Measurement-informed GHG emission intensity ranges from 13.8 – 17.2 gCO2e/MJ LNG produced, about 19-39% higher than those derived from an activity-based inventory assessment. We also observe large variation in the contribution of each stage to the total supply chain emission intensity. Critically, we find that stages downstream of gas production account for up to 73% of the production to liquefaction GHG emission intensity of LNG. Thus, relying on aggregate production-only emission intensities as the basis to assess the emissions impact of the LNG or gas placed in the destination market is likely to underestimate, leading to potentially ineffective public or corporate policies.

Resource use and greenhouse gas intensity of Australian beef production: 1981–2010

The environmental sustainability of food production systems, including net greenhouse gas (GHG) emissions, is of increasing importance. In Norwegian pork production, animal performance is high in terms of reproduction, growth, and health. The development and use of an IPCC methodology-based model for estimating GHG emissions from pork production could be helpful in identifying the effects of progress in genetics and management. The objective was to investigate whether an IPCC methodology-based model was able to reflect the effects of the progress in genetics and management in pork production on the GHG emissions per kg carcass weight (CW). It is hypothesized that this progress has led to low GHG emissions intensities in Norwegian pork compared to global levels and that expected improvements will give a lasting reduction in GHG emissions intensities. A model ‘HolosNorPork’ for estimating net farm gate GHG emissions intensities was developed, including allocation procedures, at the pig production unit level. The model was run with pig production data from in average 632 farms from 2014 to 2019. The estimates include emissions of enteric and manure storage methane, manure storage nitrous oxide emissions, as well as GHG emissions from production and transportation of purchased feeds, and direct and indirect GHG emissions caused by energy use in pig-barns. The model was able to estimate the effects on net GHG emissions intensities from pork production on the basis of production characteristics. The estimated net GHG emissions intensity was found to have decreased from on average 2.49 to 2.34 kg CO2 eq. kg−1 CW over the investigated period. For 2019 the net GHG emission for the one-third lower performing farms was estimated to 2.56 kg CO2 eq. kg−1 CW, whereas for the one-third medium and one-third best performing farms the estimates were 2.36 and 2.16 kg CO2 eq. kg−1 CW, respectively. The net GHG emissions intensity for pork carcasses from boars was estimated to be 2.07 kg CO2 eq. kg−1 CW. For the health regimes investigated, Conventional and Specific-Pathogen Free (SPF), the estimated GHG emissions intensities for 2019 were 2.37 and 2.24 kg CO2 eq. kg−1 CW, respectively. The effects on net GHG emissions intensities of breeding and management measures were estimated to be profound, and this progress in pig production systems contributes to an on-going strengthening of pork as a sustainable source for human food supply.

A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms

In 2022, New York (NY) had over 620 000 dairy cows producing more than 7 million Mg (15 billion lb) of milk, ranking fifth in dairy producing states in the United States. The objectives of this work were to (1) estimate total farm-gate greenhouse gas (GHG) emissions and GHG emission intensity (GHGei) of 36 medium to large (>300 mature cows) commercial NY dairies, (2) determine the contribution of main GHGs (on-farm methane [CH4], nitrous oxide [N2O], and carbon dioxide [CO2], plus embedded emissions [CO2 equivalents; CO2eq]) and sources (enteric fermentation, feed production, manure management, grazing, fuel and energy) to farm-gate GHGei, and (3) identify key performance indicators (KPIs) driving farm-gate GHGei. Assessments were done for 2022 using The Cool Farm Tool. Farm size ranged from 345 to 6 350 head of predominantly Holstein cows with animal densities between 1.76 and 4.85 animal units ha-1 (0.71 to 1.96 AU ac-1) and heifer to cow ratios between 0.02 and 0.49. Herds produced an average fat and protein corrected milk (FPCM) yield of 12.7 Mg (29 000 lb) FPCM cow-1 per year using 64% homegrown feed. Total FPCM production was 873 000 Mg (1.92 billion lb), representing approximately 12% of total NY milk production in 2022. The GHGei ranged from 0.63 to 1.06 kg CO2eq kg FPCM-1 (mean GHGei = 0.86kg CO2eq kg FPCM-1). Methane was the biggest contributor, accounting for 60% of total GHG emissions on average, with enteric CH4 as the largest contributor (45% of total farm emissions). Among farms, feed production emissions accounted for about 25%, with approximately 7% from homegrown feed production. Manure management practices accounted for about 20% of emissions and explained the largest amount of variation in GHGei among farms. Potential KPIs for GHGei included manure management system, heifer to cow ratio, herd feed consumption intensity, percentage of homegrown feed, and crop nutrient source (fertilizer versus manure). Emission intensity reflected the high proportion of good quality homegrown feed, careful nutrient management and use of manure treatment systems (covered liquid slurry storages, anaerobic digesters) on several dairies. The influence of replacement rate and heifer to cow ratio on animal density, herd feed consumption intensity, and subsequent GHGei requires more detailed analysis. The farms in this study represent a considerable proportion of NY's 2022 FPCM production. Greater participation by smaller farms is necessary to draw conclusions for NY's dairy industry as a whole.

Balancing crop production and greenhouse gas (GHG) emissions from agriculture soil requires a better understanding and quantification of crop GHG emissions intensity, a measure of GHG emissions per unit crop production. Here we conduct a state-of-the-art estimate of the spatial-temporal variability of GHG emissions intensities for wheat, maize, and rice in China from 1949 to 2012 using an improved agricultural ecosystem model (Dynamic Land Ecosystem Model-Agriculture Version 2.0) and meta-analysis covering 172 field-GHG emissions experiments. The results show that the GHG emissions intensities of these croplands from 1949 to 2012, on average, were 0.10-1.31kgCO2 -eq/kg, with a significant increase rate of 1.84-3.58×10-3 kgCO2 -eqkg-1 year-1 . Nitrogen fertilizer was the dominant factor contributing to the increase in GHG emissions intensity in northern China and increased its impact in southern China in the 2000s. Increasing GHG emissions intensity implies that excessive fertilizer failed to markedly stimulate crop yield increase in China but still exacerbated soil GHG emissions. This study found that overfertilization of more than 60% was mainly located in the winter wheat-summer maize rotation systems in the North China Plain, the winter wheat-rice rotation systems in the middle and lower reaches of the Yangtze River and southwest China, and most of the double rice systems in the South. Our simulations suggest that roughly a one-third reduction in the current N fertilizer application level over these "overfertilization" regions would not significantly influence crop yield but decrease soil GHG emissions by 29.60%-32.50% and GHG emissions intensity by 0.13-0.25kgCO2 -eq/kg. This reduction is about 29% and 5% of total agricultural soil GHG emissions in China and the world, respectively. This study suggests that improving nitrogen use efficiency would be an effective strategy to mitigate GHG emissions and sustain China's food security.

Climate-smart livestock production at landscape level in Kenya