Increased greenhouse gas emissions intensity of major croplands in China: Implications for food security and climate change mitigation.

Many agricultural regions in China are likely to become appreciably wetter or drier as the global climate warming increases. However, the impact of these climate change patterns on the intensity of soil greenhouse gas (GHG) emissions (GHGI, GHG emissions per unit of crop yield) has not yet been rigorously assessed. By integrating an improved agricultural ecosystem model and a meta‐analysis of multiple field studies, we found that climate change is expected to cause a 20.0% crop yield loss, while stimulating soil GHG emissions by 12.2% between 2061 and 2090 in China's agricultural regions. A wetter‐warmer (WW) climate would adversely impact crop yield on an equal basis and lead to a 1.8‐fold‐ increase in GHG emissions relative to those in a drier‐warmer (DW) climate. Without water limitation/excess, extreme heat (an increase of more than 1.5°C in average temperature) during the growing season would amplify 15.7% more yield while simultaneously elevating GHG emissions by 42.5% compared to an increase of below 1.5°C. However, when coupled with extreme drought, it would aggravate crop yield loss by 61.8% without reducing the corresponding GHG emissions. Furthermore, the emission intensity in an extreme WW climate would increase by 22.6% compared to an extreme DW climate. Under this intense WW climate, the use of nitrogen fertilizer would lead to a 37.9% increase in soil GHG emissions without necessarily gaining a corresponding yield advantage compared to a DW climate. These findings suggest that the threat of a wetter‐warmer world to efforts to reduce GHG emissions intensity may be as great as or even greater than that of a drier‐warmer world.

Agricultural disturbance has significantly boosted soil greenhouse gas (GHG) emissions such as methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). Biochar application is a potential option for regulating soil GHG emissions. However, the effects of biochar application on soil GHG emissions are variable among different environmental conditions. In this study, a dataset based on 129 published papers was used to quantify the effect sizes of biochar application on soil GHG emissions. Overall, biochar application significantly increased soil CH4 and CO2 emissions by an average of 15% and 16% but decreased soil N2O emissions by an average of 38%. The response ratio of biochar applications on soil GHG emissions was significantly different under various management strategies, biochar characteristics, and soil properties. The relative influence of biochar characteristics differed among soil GHG emissions, with the overall contribution of biochar characteristics to soil GHG emissions ranging from 29% (N2O) to 71% (CO2). Soil pH, the biochar C:N ratio, and the biochar application rate were the most influential variables on soil CH4, CO2, and N2O emissions, respectively. With biochar application, global warming potential (impact of the emission of different greenhouse gases on their radiative forcing by agricultural practices) and the intensity of greenhouse gas emissions (emission rate of a given pollutant relative to the intensity of a specific activity) significantly decreased, and crop yield greatly increased, with an average response ratio of 23%, 41%, and 21%, respectively. Our findings provide a scientific basis for reducing soil GHG emissions and increasing crop yield through biochar application.

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

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.

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.

Effects of different agricultural organic wastes on soil GHG emissions: During a 4-year field measurement in the North China Plain

Brazilian cattle production is mostly carried out in pastures, and the need to mitigate the livestock's greenhouse gas (GHG) emissions and its environmental footprint has become an important requirement. The adoption of well-suited breeds and the intensification of pasture-based livestock production systems are alternatives to optimize the sector's land use. However, further research on tropical systems is necessary. The objective of this research was to evaluate the effect of Holstein (HO) and Jersey–Holstein (JE x HO) crossbred cows in different levels of pasture intensification (continuous grazing system with low stocking rate–CLS; irrigated rotational grazing system with high stocking rate–RHS), and the interaction between these two factors on GHG mitigation. Twenty-four HO and 24 JE x HO crossbred dairy cows were used to evaluate the effect of two grazing systems on milk production and composition, soil GHG emissions, methane (CH4) emission, and soil carbon accumulation (0–100 cm). These variables were used to calculate carbon balance (CB), GHG emission intensity, the number of trees required to mitigate GHG emission, and the land-saving effect. The number of trees necessary to mitigate GHG emission was calculated, considering the C balance within the farm gate. The mitigation of GHG emissions comes from the annual growth rate and accumulation of C in eucalyptus trees' trunks. The CB of all systems and genotypes presented a deficit in carbon (C); there was no difference for genotypes, but RHS was more deficient than CLS (-4.99 to CLS and −28.72 to RHS ton CO2e..ha−1.year−1). The deficit of C on GHG emission intensity was similar between genotypes and higher for RHS (−0.480 to RHS and −0.299 to CLS kg CO2e..kg FCPCmilk−1). Lower GHG removals (0.14 to CLS higher than 0.02 to RHS kg CO2e..kg FCPCmilk−1) had the greatest influence on the GHG emission intensity of milk production. The deficit number of trees to abatement emissions was higher to HO (−46.06 to HO and −38.37 trees/cow to JE x HO) and to RHS (−51.9 to RHS and −33.05 trees/cow to CLS). However, when the results are expressed per ton of FCPCmilk, there was a difference only between pasture management, requiring −6.34 tree. ton FCPCmilk−1 for the RHS and −3.99 tree. ton FCPCmilk−1 for the CLS system. The intensification of pastures resulted in higher milk production and land-saving effect of 2.7 ha. Due to the reservation of the pasture-based dairy systems in increasing soil C sequestration to offset the GHG emissions, especially enteric CH4, planting trees can be used as a mitigation strategy. Also, the land-save effect of intensification can contribute to the issue, since the area spared through the intensification in pasture management becomes available for reforestation with commercial trees.

Mitigation of greenhouse gas emissions from beef production in western Canada – Evaluation using farm-based life cycle assessment

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 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.

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

Combining models to estimate the impacts of future climate scenarios on feed supply, greenhouse gas emissions and economic performance on dairy farms in Norway

CONTEXTSheep production industries face the challenge of increasing farm production and profit while reducing environmental impacts. OBJECTIVESGenetic selection using multi-trait breeding indices can be used to improve flock productivity, profitability, and greenhouse gas (GHG) emissions intensities (kg CO2-eq /kg of product), however validation of the improved performance of animals ranked higher on breeding indices at a flock level is required. METHODSPhenotypic data from 387,580 production records of animals born between 2018 and 2020 of known genetic merit in commercial flocks were inputted to an established bio-economic model. Two contrasting flocks were compared, a flock of ewes ranked High (top 20%) on the Irish replacement Index bred with rams ranked High on the replacement and terminal indices, and a flock of ewes ranked Low (bottom 20%) on the Irish replacement Index bred with rams ranked Low on the replacement and terminal indices. The two flocks were then simulated using life cycle assessment to estimate the GHG emissions profile for both systems. RESULTS AND CONCLUSIONFlock weaning rates were 1.70 and 1.53 lambs weaned per ewe presented for breeding for the High and Low genetic merit flocks, respectively. The flock of High genetic merit ewes sold 0.17 more lambs per ewe, equating to 3.29 kg more lamb carcass per ewe, than the flock of Low genetic merit ewes; lambs from the High genetic merit flock were also sold at an earlier age. The greater production of the High genetic merit flocks resulted in an additional €18/ewe net profit than the Low genetic merit flock. Although total flock GHG emissions were higher for the High genetic merit flock, GHG emissions intensities were lower at 21.7 and 23.3 kg CO2-eq /kg lamb carcass sold for the High and Low genetic merit flocks, respectively. The lower emissions intensity of the High genetic merit flock was due to the dilution effect of higher lamb production and lambs being drafted for slaughter ealier. SIGNIFICANCEThe results suggest Irish sheep producers can make substantial profit gains through selection according to the national breeding indices while also reducing their environmental impact, and farmers should consider genetic merit when purchasing their rams, particularly sires of replacement ewe lambs.

Greenhouse gas emissions and production cost footprints in Australian gold mines