Energy use, "food miles" and greenhouse gas emissions from New Zealand dairying - how efficient are we?

A life cycle assessment (LCA) study of a transition from semiintensive to semi-extensive Mediterranean dairy sheep farm suggests that the latter has a strong potential for offsetting greenhouse gas (GHG) emissions through the soil C sequestration (Cseq) in permanent grasslands. The extensification process shows clear environmental advantage when emission intensity is referred to the area-based functional unit (FU). Several LCA studies reported that extensive livestock systems have greater GHG emissions per mass of product than intensive one, due to their lower productivity. However, these studies did not account for soil Cseq of temporary and permanent grasslands, that have a strong potential to partly mitigate the GHG balance of ruminant production systems. Our LCA study was carried out considering the transition from a semiintensive (SI) towards a semi-extensive (SE) production system, adopted in a dairy sheep farm located in North-Western Sardinia (Italy). Impact scope included enteric methane emissions, feed production, on-farm energy use and transportation, infrastructures as well as the potential C sink from soil Cseq compared to emission intensity. In order to provide a more comprehensive analysis, we used the following FUs: 1 kg of fat and protein corrected milk (FPCM) and 1 ha of utilised agricultural area (UAA). We observed that the extensification of production system determined contrasting environmental effects when using different FUs accounting for soil Cseq. When soil Cseq in emission intensity estimate was included, we observed slightly lower values of GHG emissions per kg of FPCM in the SI production system (from 3.37 to 3.12 kg CO2 equivalents – CO2-eq), whereas a greater variation we observed in the SE one (from 3.54 to 2.90 kg CO2-eq). Considering 1 ha of UAA as FU and including the soil Cseq, the emission intensity in SI moved from 6257 to 5793 kg CO2-eq, whereas values varied from 4020 to 3299 kg CO2-eq in SE. These results indicated that the emission intensity from semi-extensive Mediterranean dairy sheep farms can be considerably reduced through the soil Cseq, although its measurement is influenced by the models used in the estimation. Highlights - Extensification of dairy sheep systems provides an environmental benefit when soil C sequestration is considered. - Extensification of dairy sheep systems determines lower environmental impact per hectare of utilized agricultural area. - Enteric methane emissions are the main source of GHG emissions of the sheep milk life cycle. - Carbon sequestration in permanent grasslands can considerably contribute to climate change mitigation.

Greenhouse gas (GHG) emissions is one of the major environmental concerns of shale gas development. To better understand this specific environmental impact, this chapter develops a hybrid life cycle inventory (LCI) model to estimate the energy use and greenhouse gas (GHG) emissions of China’s shale gas development. Results suggest a total average energy use per well of 123 TJ (range: 74–165 TJ) and total average GHG emissions per well of 9505 tCO2e (range: 5346–13551 tCO2e). Most of the energy use and GHG emissions are indirect impacts embodied in fuels and materials. Energy use and GHG emissions from the drilling stage comprise the largest share in both totals due to large amounts of diesel used as fuel in the well drilling process and the materials used in the well casing process. Furthermore, the comparison shows that the energy use and GHG emissions of shale gas development in China will be much higher than the U.S.KeywordsShale gas developmentLife-cycle analysisGHG emissionsEnergy useEmbodied energy

Present day European legislation focuses upon the reduction of greenhouse gas (GHG) emissions in buildings through better design and technological solutions, with a view to reduce operational energy use and embodied GHG emissions. Currently, environmental performance assessment tools for buildings lack in assessing these parameters over the entire lifecycle of a building. Life cycle assessment (LCA) is a well-established methodology that gives a clear insight into the potential environmental impacts during the service life of a building. However, architect, engineer and constructor (AEC) professionals consider LCA as complex and time consuming. This paper builds upon a methodology for the development of a parametric analysis tool (PAT), which comprehensively assesses operational energy use and embodied GHG emissions during the lifecycle of a building. In this phase of the PAT’s development, the complexity of the tool has been increased by expanding the number of parameters from four (i.e. insulation thickness, window types, North façade glazing area and South façade glazing area) to seven (i.e. climatic zones, solar shading and electricity emission factors). This has increased the amount of parametric permutations from 1,372 to 12,348. The PAT has been applied to a conceptual two-storey single-family house, developed by the Norwegian ZEB Research Centre, which is assumed to be in either Oslo (Norway) or Lecce (Italy). The results show that the choice of insulation thickness influences total energy use less than the selection of shading types or glazing areas. The results also show the parametric selection with the least amount of operational energy use (34kWh/m2/yr) in the Lecce climate consists of triple-glazed windows (0.5W/m2k), 10m2 of glazing on the north façade, 20m2 of glazing on the south facade. The results show the parametric selection with the lowest total GHG emissions in the Oslo climate (7.8kgCO2eq/m2/yr) consists of triple glazing (0.5W/m2k), 10m2 of glazing on the north facade and 20m2 glazing on the south facade. This is because a lower electricity emission factor (132gCO2eq/kWh for Norway and 290gCO2eq/kWh for Italy) was used for converting operational energy use to GHG emissions, even though the Oslo climate has a higher heating demand compared to Lecce. In conclusion, this paper shows how complex design options can be evaluated in a holistic way through PAT to ascertain the best selection of design criteria for low GHG emissions and low operational energy use.

Impacts of soil carbon sequestration on life cycle greenhouse gas emissions in Midwestern USA beef finishing systems

<p class="abstrak2">South Korea has declared to reduce greenhouse gas emissions by 30% compared to the current level by the year 2020. The greenhouse gas emissions from the cattle production sector in South Korea were evaluated in this study. The greenhouse gas emissions of dairy cattle, Non-Korean native cattle, and Korean native (Hanwoo) cattle production activities in 16 local administrative provinces of South Korea over a ten-year period (2005–2014) were estimated using the methodology specified by the Guidelines for National Greenhouse Gas Inventory of the IPCC (2006). The emissions studied herein included methane from enteric fermentation, methane from manure management, nitrous oxide from manure management and carbon dioxide from direct on-farm energy use. Over the last ten years, Hanwoo cattle production activities were the primary contributor of CH<sub>4</sub> from enteric fermentation, CH<sub>4</sub> from manure management, NO<sub>2</sub> from manure management and CO<sub>2</sub> from on-farm energy use in the cattle livestock sector of South Korea, which comprised to 83.52% of total emissions from cattle production sector.</p>

The goal of this study was to estimate the emissions of greenhouse gases (GHG), namely methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) from poultry and pig production in South Korea over the last 10 years (2005 through 2014). The calculations of GHG emissions were based on Intergovernmental Panel on Climate Change (IPCC) guidelines. Over the study period, the CH4 emission from manure management decreased in layer chickens, nursery to finishing pigs and gestating to lactating sows, but there was a gradual increase in CH4 emission from broiler chickens and male breeding pigs. Both sows and nursery to finishing pigs were associated with greater emissions from enteric fermentation than the boars, especially in 2009. Layer chickens produced lower direct and indirect N2O emissions from 2009 to 2014, whereas the average direct and indirect N2O emissions from manure management for broiler chickens were 12.48 and 4.93 Gg CO2-eq/yr, respectively. Annual direct and indirect N2O emissions for broiler chickens tended to decrease in 2014. Average CO2 emission from direct on-farm energy uses for broiler and layer chickens were 46.62 and 136.56 Gg CO2-eq/yr, respectively. For pig sectors, the N2O emission from direct and indirect sources gradually increased, but they decreased for breeding pigs. Carbon dioxide emission from direct on-farm energy uses reached a maximum of 53.93 Gg CO2-eq/yr in 2009, but this total gradually declined in 2010 and 2011. For boars, the greatest CO2 emission occurred in 2012 and was 9.44 Gg CO2-eq/yr. Indirect N2O emission was the largest component of GHG emissions in broilers. In layer chickens, the largest contributing factor to GHG emissions was CO2 from direct on-farm energy uses. For pig production, the largest component of GHG emissions was CH4 from manure management, followed by CO2 emission from direct on-farm energy use and CH4 enteric fermentation emission, which accounted for 8.47, 2.85, and 2.82 Gg-CO2/yr, respectively. The greatest GHG emission intensity occurred in female breeding sows relative to boars. Overall, it is an important issue for the poultry and pig industry of South Korea to reduce GHG emissions with the effective approaches for the sustainability of agricultural practices.

New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.

Life-cycle assessment of greenhouse gas emissions from dairy production in Eastern Canada: A case study

Greenhouse gas emission of Canadian cow-calf operations: A whole-farm assessment of 295 farms

In this study, we used Argonne National Laboratory's Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model to assess the life-cycle energy and greenhouse gas (GHG) emission impacts of four soybean-derived fuels: biodiesel fuel produced via transesterification, two renewable diesel fuels (I and II) produced from different hydrogenation processes, and renewable gasoline produced from catalytic cracking. Five approaches were employed to allocate the coproducts: a displacement approach; two allocation approaches, one based on the energy value and the other based on the market value; and two hybrid approaches that integrated the displacement and allocation methods. The relative rankings of soybean-based fuels in terms of energy and environmental impacts were different under the different approaches, and the reasons were analyzed. Results from the five allocation approaches showed that although the production and combustion of soybean-based fuels might increase total energy use, they could have significant benefits in reducing fossil energy use (>52%), petroleum use (>88%), and GHG emissions (>57%) relative to petroleum fuels. This study emphasized the importance of the methods used to deal with coproduct issues and provided a comprehensive solution for conducting a life-cycle assessment of fuel pathways with multiple coproducts.

This study provides an empirical assessment of energy use and greenhouse gas (GHG) emissions associated with high and low residential development. Three major elements of urban development are considered: construction materials for infrastructure (including residential dwellings, utilities, and roads), building operations, and transportation (private automobiles and public transit). Two case studies from the City of Toronto are analyzed. An economic input–output life-cycle assessment (EIO-LCA) model is applied to estimate the energy use and GHG emissions associated with the manufacture of construction materials for infrastructure. Operational requirements for dwellings and transportation are estimated using nationally and/or regionally averaged data. The results indicate that the most targeted measures to reduce GHG emissions in an urban development context should be aimed at transportation emissions, while the most targeted measures to reduce energy usage should focus on building operations. The results also show that low-density suburban development is more energy and GHG intensive (by a factor of 2.0–2.5) than high-density urban core development on a per capita basis. When the functional unit is changed to a per unit of living space basis the factor decreases to 1.0–1.5, illustrating that the choice of functional unit is highly relevant to a full understanding of urban density effects.

In order to manage strategies to curb climate change, systemic benchmarking at a variety of production scales and methods is needed. This study is the first life cycle assessment (LCA) of a large-scale, vertically integrated organic dairy in the United States. Data collected at Aurora Organic Dairy farms and processing facilities were used to build a LCA model for benchmarking the greenhouse gas (GHG) emissions and energy consumption across the entire milk production system, from organic feed production to post-consumer waste disposal. Energy consumption and greenhouse gas emissions for the entire system (averaged over two years of analysis) were 18.3 MJ per liter of packaged fluid milk and 2.3 kg CO(2 )equiv per liter of packaged fluid milk, respectively. Methane emissions from enteric fermentation and manure management account for 27% of total system GHG emissions. Transportation represents 29% of the total system energy use and 15% of the total GHG emissions. Utilization of renewable energy at the farms, processing plant, and major transport legs could lead to a 16% reduction in system energy use and 6.4% less GHG emissions. Sensitivity and uncertainty analysis reveal that alternative meat coproduct allocation methods can lead to a 2.2% and 7.5% increase in overall system energy and GHG, respectively. Feed inventory data source can influence system energy use by -1% to +10% and GHG emission by -4.6% to +9.2%, and uncertainties in diffuse emission factors contribute -13% to +25% to GHG emission.

Life Cycle Assessment of fossil energy use and greenhouse gas emissions in Chinese pear production

Agricultural activities emit about 10-12% greenhouse gases each year. Moreover, the total amount is on the rise, which can significantly contribute to global warming. To get governments to pay more attention to greenhouse gas emissions from agricultural activities, so that the necessary regulations can be implemented. This paper studies the relationship between agricultural land expansion and greenhouse gas emissions. My initial hypothesis was that ceteris paribus, the agricultural land expansion would cause a rise in greenhouse gas emissions. I obtained 25 years of data for 12 countries from the World Development Indicators Database of the World Bank. And created a panel data frame. The variables exist in it are: Total greenhouse gas emissions (kt of CO2 equivalent), Energy use (kg of oil equivalent per capita), Alternative and nuclear energy (% of total energy use), Agricultural land (% of land area), GDP per capita (current US$). In order to cope with the possible heteroscedasticity problem in the regression, several of the variables were processed logarithms. This paper used a Two-way Fixed effect model which controls fixed effects from both cross section and time. The explained variable is log (GHG emissions), and the explanatory variables are log (energy use per capita), log (GDP per capita), clean energy using rate, and percentage of agricultural land in total land. However due to the presence of multicollinearity, log (GDP per capita) was removed. This paper also tested the autocorrelation and used the Cochrane-Orcutt Iterative Process to estimate the autocorrelation coefficient to transform all variables so that solve the autocorrelation issue. The final regression model is as follows: ln(Greenhouse Gases emission)= + 1.06*ln(Energy use per capita) – 0.009*(Alternative and nuclear energy % of total energy use) + 0.0074*(Agricultural land % of land area). = . The overall F-test of this model is significant, and the individual t-tests of the coefficients of each variable are all significant. R2=92.18, adjR2=91.04. This shows that the explanatory power of the model is strong. This outcome is consistent with my initial hypothesis that agricultural land expansion does lead to an increase in greenhouse gas emissions. The other two coefficients are also consistent with our common sense. This result can help governments to decide on the planning of land use. If the current amount of energy used and the types of energy used do not change, a country develops agriculture, it will inevitably lead to more greenhouse gas emissions. More Importantly, it is not like industrial manufacture, normally there are few regulations and policies on agricultural GHG emissions. But the quantitative results of the model tell us that as agriculture expands, it is necessary for the government to implement regulations and policies on it.

Current agricultural practices contribute significantly to greenhouse gas emissions. The majority of non-CO2 emissions of agriculture include methane (54%), nitrous oxide (28%) and carbon dioxide (18%), which collectively account for 12% of the world's yearly greenhouse gas (GHG) emissions (7.1 Gt CO2 equivalent). GHG emissions contribute to agricultural activity in direct and indirect activities, accounting for 30% of total global anthropogenic GHG emissions. Agriculture serves a major role in climate change. Agricultural practices lead to the emission of greenhouse gases. Moreover, conventional farming uses synthetic fertilisers. Deforestation and soil degradation are examples of inappropriate land use practices that lower the amount of organic matter in soil. The inappropriate carbon footprint of agriculture is a result of these activities as well as the wasteful use of inputs like water. carbon-neutral methods that reduce greenhouse gas emissions from the production of crops and livestock, and agricultural rice, enteric fermentation, and manure. Agriculture use the renewable energy irrigation source they help to reduce the GHG emissions. It also help to Sustainable development goal climate change.it is crucial role in the climate resilience. These include switching to alternative rice farming techniques, using technologies for managing nitrogen fertilisers, decarbonising on-farm energy use, and developing feeding and breeding strategies that lower enteric methane. When taken as a whole, these actions can cut agricultural GHG emissions by as much as 45%. However, to achieve net-zero agriculture, carbon dioxide removal technology offsets will be needed to balance residual emissions of 3.8 Gt CO2 equivalent per year. Bioenergy with improved carbon collection and storage. Greenhouse Gas emissions profound influence on their effects. Here an overview of inventions and technology was provided with the aim of lowering greenhouse gas emissions from agriculture. The study concluded that the rate and amount of SOC sequestration differ with soil types, depths, land use and land cover and vary from one region to another. Sequestration of carbon in soil can improve soil health, and improvement in soil health will help in improving input use efficiency in agriculture. Thus sequestering carbon in soil and biota can mitigate climate change.