A meta-analysis approach to examining the greenhouse gas implications of including dry peas (Pisum sativum L.) and lentils (Lens culinaris M.) in crop rotations in western Canada

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

Change in carbon footprint of canola production in the Canadian Prairies from 1986 to 2006

Differences among OECD countries’ GHG emissions: Causes and policy implications

Effects of nitrogen fertilizer substitution by cow manure on yield, net GHG emissions, carbon and nitrogen footprints in sweet maize farmland in the Pearl River Delta in China

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

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.

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

Life cycle and economic assessment of Western Canadian pulse systems: The inclusion of pulses in crop rotations

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

To clarify the characteristics of greenhouse gas emissions （CO2, CH4, and N2O） and the comprehensive greenhouse effect from vegetable fields with different organic planting years, the differences in greenhouse gas emission flux, emission intensity （GHGI）, and global warming potential （GWP） and their influencing factors among vegetable fields with different organic planting years in Songhuaba, including 10 years, 6 years, 3 years, and conventional planting, were analyzed. The results showed that the CO2 emissions from organic planting treatments were higher than those from conventional planting, whereas the N2O and CH4 emissions were the opposite. Compared to those from conventional planting, the CO2 emission fluxes and cumulative emissions from organic cultivation for 10, 6, and 3 years increased by 121.28% and 40.44%, 144.61% and 51.39%, and 130.10% and 41.77% （P < 0.05）, respectively, and the N2O emission fluxes and cumulative emissions decreased by 26.08% and 186.03%, 9.6% and 3.55%, and 35.9% and 151.78%, respectively. The CH4 emission flux was shown as follows： conventional planting > organic planting for 10 years > organic planting for 6 years > organic cultivation for 3 years, and the CH4 emissions from cultivational planting and organic planting for 10 years were shown as "source," while the CH4 emissions from organic planting for 6 years and 3 years were shown as "sink." Compared with those from conventional planting, the GWP and GHGI from organic planting for 10 years and 3 years were reduced by 40.57% and 61.43%, 43.83% and 57.98% （P < 0.05）, respectively. Organic planting slightly reduced the vegetable yield but significantly reduced GWP and GHGI （P < 0.05）. Soil temperature and humidity, SOC, and inorganic nitrogen were the key factors affecting the difference in greenhouse gas emissions between treatments. Organic planting significantly reduced greenhouse gas emissions from vegetable fields, and the differences in greenhouse gas emissions among different years of organic planting were closely related to soil organic carbon and inorganic nitrogen. The research results can provide a scientific basis for carbon sequestration, emission reduction, and the green development of organic vegetable production systems.

Characteristics of greenhouse gases emission from wastewater treatment plants operation in China (2009–2016): A case study using operational data integrated method (ODIM)

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

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.

Relationships between greenhouse gas emissions and cultivable bacterial populations in conventional, organic and long-term grass plots as affected by environmental variables and disturbances

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.