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

A dominance analysis of greenhouse gas emissions, beef output and land use of German dairy farms

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

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.

Statistical analysis of greenhouse gas emissions of South Korean residential buildings

The Australian dairy industry contributes ~1.6% of the nation’s greenhouse gas (GHG) emissions, emitting an estimated 9.3 million tonnes of carbon dioxide equivalents (CO2e) per annum. This study examined 41 contrasting Australian dairy farms for their GHG emissions using the Dairy Greenhouse Gas Abatement Strategies calculator, which incorporates Intergovernmental Panel on Climate Change and Australian inventory methodologies, algorithms and emission factors. Sources of GHG emissions included were pre-farm embedded emissions associated with key farm inputs (i.e. grains and concentrates, forages and fertilisers), CO2 emissions from electricity and fuel consumption, methane emissions from enteric fermentation and animal waste management, and nitrous oxide emissions from animal waste management and nitrogen fertilisers. The estimated mean (±s.d.) GHG emissions intensity was 1.04 ± 0.17 kg CO2 equivalents/kg of fat and protein-corrected milk (kg CO2e/kg FPCM). Enteric methane emissions were found to be approximately half of total farm emissions. Linear regression analysis showed that 95% of the variation in total farm GHG emissions could be explained by annual milk production. While the results of this study suggest that milk production alone could be a suitable surrogate for estimating GHG emissions for national inventory purposes, the GHG emissions intensity of milk production, on an individual farm basis, was shown to vary by over 100% (0.76–1.68 kg CO2e/kg FPCM). It is clear that using a single emissions factor, such as milk production alone, to estimate any given individual farm’s GHG emissions, has the potential to either substantially under- or overestimate individual farms’ GHG emissions.

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.

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 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.

Ratoon rice can improve rice yield by increasing the multiple cropping index in China. However, the greenhouse gas (CH4 and N2O) emission characteristics from ratoon rice fields and the cultivation methods to reduce CH4 and N2O emissions are rarely reported. This study first conducted the analysis of genotype differences in greenhouse gas emission fluxes using five strong ratoon ability rice varieties in 2020. Second, water management methods, including alternating the wet–dry irrigation (AWD) pattern and conventional flooding irrigation (CF) during the main season, were carried out in 2021. CH4 and N2O emission flux, agronomic traits, and rice yield during both main and ratoon seasons were investigated. The results showed that the CH4 emission flux during the main and ratoon seasons was 157.05–470.73 kg·ha–1 and 31.03–84.38 kg·ha–1, respectively, and the total N2O emission flux was 0.13–0.94 kg·ha–1 in the ratoon rice system over the two seasons (RRSTS). Compared with the main season, the CH4 emission flux during the ratoon season was significantly reduced, thus decreasing the greenhouse gas global warming potential (GWP) and greenhouse gas emission intensity (GHGI) in the ratoon rice system. Cliangyouhuazhan (CLYHZ) showed a high yield, and the lowest GWP and GHGI values among the five rice varieties in RRSTS. Compared with CF, the AWD pattern reduced the CH4 emission flux during the main and ratoon seasons by 67.4–95.3 kg·ha–1 and 1.7–5.1 kg·ha–1, respectively, but increased the N2O emission flux by 0.1–0.6 kg·ha–1 during the RRSTS. Further, compared with CF, the AWD pattern had a declined GWP by 14.3–19.4% and GHGI by 30.3–34.3% during the RRSTS, which was attributed to the significant reduction in GWP and GHGI during the main season. The AWD pattern significantly increased rice yield by 21.9–22.9% during the RRSTS, especially for YX203. Correlation analysis showed that CH4, GWP, and GHGI exhibited significant negative correlations with spikelet number per m2 and the harvest index during the main and ratoon seasons. Collectively, selecting the high-yield, low-emission variety CLYHZ could significantly reduce greenhouse gas emissions from ratoon rice while maintaining a high yield. The AWD pattern could reduce total CH4 emission during the main season, reducing the GWP and GHGI while increasing the ratoon rice system yield. It could be concluded that a variety of CLYHZ and AWD patterns are worthy of promotion and application to decrease greenhouse gas emissions in the ratoon rice area in the upper reaches of Yangtze River, China.

Smallholder dairy farms face enormous challenges in increasing milk production while mitigating greenhouse gas (GHG) emissions, thereby enhancing climate resilience. The carbon footprint (CF) of smallholder milk production is expected to increase with increasing demand for dairy products under the business-as-usual scenario. This study estimates the carbon footprint of smallholder milk production and examines variation across farms using data from 480 households to identify viable options for mitigating GHG emissions. We applied a cradle to farm-gate life cycle assessment (LCA) approach to examine the effects of farming systems on GHG emission intensities across intensification gradients of smallholder farms (SHF) from four potential dairy districts in the central highlands of Ethiopia. According to our findings, enteric fermentation was the primary source of GHG emissions, and methane(CH4) emissions from enteric fermentation and manure management accounted for the majority of total emissions across farms. The estimated average CF varies depending on farming systems, global warming potential (GWP), and allocation methods used. When GHG emissions were allocated to multiple products using economic allocation and based on IPCC (2007)and IPCC (2014)GWPs, the overall average CF of milk production was 1.91 and 2.35kg CO2e/kg fat and protein-corrected milk (FPCM), respectively. On average, milk accounted for 72% of total greenhouse gas emissions. In terms of farm typology, rural SHF systems produced significantly more CF per kg of milk than urban and peri-urban SHF systems. Variations in milk yield explained more than half of the variation in GHG emissions intensity at the farm level. Feed digestibility and feed efficiency had a negative and significant (P < 0.01) association with CF of SHF. Our findings suggested that improving feed digestibility and feed efficiency by increasing the proportion of concentrate and improved forage as well as chemically upgrading straw and crop residue could provide an opportunity to both increase milk yield and reduce the CF of milk production of SHF in the study area. Supporting SHF to realize strategies contributing to climate-resilient dairy development require interventions at several levels in the dairy value chain.

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.

Variations of GHG emission patterns from waste disposal processes in megacity Shanghai from 2005 to 2015

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.

Greenhouse gas emissions and production cost footprints in Australian gold mines

In order to explore the effective management measures of increasing yield and reducing non-CO2 greenhouse gas (CH4 and N2O) emission in the cold black soil paddy field, field experiments were carried out.This paper analyzed the impact of straw returning and different irrigation methods on rice field yield, greenhouse gas emissions, global warming potential (GWP) and greenhouse gas emission intensity (GHGI).The results showed that compared with the treatment without straw returning, the yield of straw returning treatment increased by 11.79% annually, CH4 emissions increased by 62.71% annually, N2O emissions decreased by 1.28% annually, GWP and GHGI increased by 60.90% and 45.58% annually, respectively.Compared with conventional flooding treatment, the yield of controlled irrigation treatment increased by 2.68% annually, the difference was not significant, CH4 emissions decreased by 56.42% annually, N2O emissions increased by 133.41%,GWP and GHGI decreased by 54.89% and 55.93% annually, respectively.Straw returning and controlled irrigation had significant interaction on GWP and GHGI, but not significant interaction on yield.The GHGI values of the four treatments were as follows: KFH0< KFHS< CFH0< CFHS.Therefore, controlled irrigation is an irrigation method with stable rice yield and good greenhouse gas emission reduction effect.Straw returning and controlled irrigation can achieve the double goals of increasing yield and reducing greenhouse gas emissions of rice fields in cold regions.