A harmonised systems-wide re-analysis of greenhouse gas emissions from sunflower oil production

Intensive cultivation and post-harvest vegetable oil production stages are major sources of greenhouse gas (GHG) emissions. Variation between production systems and reporting disparity have resulted in discordance in previous emissions estimates. The aim of this study was to assess global systems-wide variation in GHG emissions resulting from palm, soybean, rapeseed and sunflower oil production. Such an analysis is critical to understand the implications of meeting increasing edible oil demand. To achieve this, we performed a unified re-analysis of life cycle input data from diverse palm, soybean, rapeseed, and sunflower oil production systems, from a saturating search of published literature. The resulting dataset reflects almost 6000 producers in 38 countries, and is representative of over 71% of global vegetable oil production. Across all oil crop systems, median GHG emissions were 3.81 kg CO2e per kg refined oil. Crop specific median emissions ranged from 2.49 kg CO2e for rapeseed oil to 4.25 kg CO2e for soybean oil per kg refined oil. Determination of the carbon cost of agricultural land occupation revealed that carbon storage potential in native compared to agricultural land cover drives variation in production GHG emissions, and indicates that expansion of production in low carbon storage potential land, whilst reforesting areas of high carbon storage potential, could reduce net GHG emissions whilst boosting productivity. Nevertheless, there remains considerable scope to improve sustainability within current production systems, including through increasing yields whilst limiting application of inputs with high carbon footprints, and in the case of palm oil through more widespread adoption of methane capture technologies in processing stages.

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Dairy farming is a major source of greenhouse gas (GHG) emissions in agriculture. There are numerous scientific studies analysing GHG flows and testing GHG reduction methods in dairy farming, yet very few scientific papers cover all the relevant GHG flows. GHG flows that are difficult to quantify, such as C sequestration in soils, the effects of land-use change (LUC) or the energy input used to produce capital equipment, are not always considered.This paper describes the development and application of a model for energy and GHG accounting in dairy farming. This new model enables all relevant nutrient, energy and GHG flows to be modelled at farm level. This then forms the basis for system analysis and derivation of GHG mitigation strategies. The model was used on 18 organic and 18 con-ventional farms in Germany. Calculated CO2-eq emissions per kg of Energy Corrected Milk (ECM) were 995 g on average for organic farms (org) and 1,048 g on average for conventional farms (con). The largest contribution (55 % (org) and 43 % (con)) to total GHG emissions came from enteric methane emissions (549 g CO2-eq (kg ECM)-1 (org) and 449 g CO2-eq (kg ECM)-1 (con)). On the organic dairy farms, there was an increase in soil humus and therefore carbon storage and sequestration in soils, whereas the GHG emissions for the conventional farms included CO2 emissions from LUC due to soybean usage. The significantly higher energy input in the conventional systems resulted from the production of energy-intensive concentrates, mineral fertilisers and pesticides, and transportation (imported feed).This study shows that there are many factors that influence GHG emissions in dairy farming, and that these factors often interact with each other. An increase in productivity is one of several optimisation strategies; however, it must not be at the expense of productive lifetime or require an extremely high amount of concentrates. GHG reduction in dairy farming requires farm-specific optimisation approaches due to the heterogeneity of production systems.

Effect of production system and farming strategy on greenhouse gas emissions from commercial dairy farms in a life cycle approach

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

In the context of global climate change, carbon footprint (CF) becomes an important sustainability indicator for dairy production systems. To mitigation the CF of the dairy sector, insight into greenhouse gases (GHG) emissions from individual farms is required. The objective of this study was to determine the primary contributors to GHG emissions at the farm-gate level, expressed as a carbon dioxide equivalents (CO2-eq), to produce one kg of fat-and protein corrected milk (FPCM). Primary data about farms’ management and feeding practices were collected from twelve dairy farms that belong to Gyeonggi-do province, which represent the most important region for milk production in South Korea. Allocation of GHG emissions between meat and milk was assessed as a physical allocation, 98% allocated to milk and 2% to meat (surplus of calves and culled cows). The CF of the evaluated farms averaged to 0.61 CO2-eq/kg of FPCM and ranged from 0.49 to 0.78 CO2-eq/kg of FPCM. Results indicated that the largest source of GHG comes mostly from enteric fermentation (83%), followed by manure management (6%), manure and fertilizer land application (8%) and energy consumption (3%). By type of gas emitted, methane accounted for 86% of total emissions, originating from enteric fermentation and manure management. Nitrous oxide and carbon dioxide accounted for 11.6 % and 2.8% of total GHG emissions, respectively. Lactating cows contributed by 70% of total GHG emissions, whereas dry cows, heifers and calves contributed by 5, 22 and 3%, respectively. Differences in GHG emissions from the evaluated farms could be explained by differences in feed quality and management practices through manure and fertilizers application on cropland. This study contributes to identify the main sources of GHG production in dairy farms, which can help to define mitigation strategies towards the transition to neutral carbon emissions of the dairy sector.

Whole-farm systems modelling of greenhouse gas emissions from pastoral suckler beef cow production systems

Many consumers are trying to reduce their food's environmental impact by purchasing more locally sourced food. One choice for local food is Community Supported Agriculture (CSA), in which farmers provide a share of produce on a regular basis to pre-paying farm members. The number of CSAs in the USA has grown from two in the mid-1980s to perhaps as many as 12,617 according to the latest US census of agriculture (2014). We use a case study approach to investigate the greenhouse gas (GHG) emissions associated with five CSA operations in the Sacramento Valley of California. By understanding the GHG emissions of CSAs and the practices that might be improved, we hope to support innovative strategies to reduce GHG emissions in these agricultural production systems. Input, production and distribution data were collected from each farm and reported in CO2e emissions for 1 kg CSA produce at the pickup location. Results show large variation in total emissions, ranging from 1.72 to 6.69 kg CO2e kg−1 of produce with an average of 3.94 kg CO2e kg−1 produce. The largest source of emissions was electricity, contributing over 70% of total CO2e emissions on average. Based on our findings, despite the seemingly similarities between these operations in terms of production site, acreage, customers and production practices, there is still a large amount of variability with regard to total GHG. Thus we argue coming up with a standardized production function for diversified production and deriving GHGs or calculating average total emissions overlooks the heterogeneity of the system. Food systems can never be reduced to a simple binary of local is better and conventional is worse, or its inverse local is worse and conventional is better, because of the complexities of the production and distribution systems and their relationship to GHG emissions. Yet, we can say that localized production systems that are low in electricity use (or use renewable energy sources) and use efficiently-produced compost use have lower GHG emissions than those that do not.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Based on the localized data of environmental load, this study has establishedthe life cycle assessment (LCA) model of battery electric passenger vehicle(BEPV) that be produced and used in China, and has evaluated the energyconsumption and greenhouse gases (GHGs) emission during vehicle pro-duction and operation. The results show that the total energy consumptionand GHG emissions are 438GJ and 37,100kg (in terms of CO2 equivalent)respectively. The share of GHG emissions in total emissions at the productionstage is 24.6%, and 75.4% GHG emissions are contributed by the operationalstage. The main source of energy consumption and GHG emissions at vehicleproduction stage is the extraction and processing of raw materials. TheGHG emissions of raw materials production accounts for 75.0% in the GHGemissions of vehicle production and 18.0% in the GHG emissions of fulllife cycle. The scenario analysis shows that the application of recyclablematerials, power grid GHG emission rates and vehicle energy consumption rates have significant influence on the carbon emissions in the life cycle ofvehicle. Replacing primary metals with recycled metals can reduce GHGemissions of vehicle production by about 7.3%, and total GHG emissionscan be reduced by about 1.8%. For every 1% decrease in GHG emissionsper unit of electricity, the GHG emissions of operation stage will decrease byabout 0.9%; for every 1.0% decrease in vehicle energy consumption rate, thetotal GHG emissions decrease by about 0.8%. Therefore, developing cleanenergy, reducing the proportion of coal power, optimizing the productionof raw materials and increasing the application of recyclable materials areeffective ways to improve the environmental performance of BEPV.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Greenhouse gas and ammonia emissions and mitigation options from livestock production in peri-urban agriculture: Beijing – A case study

Kupang city is growth rapidly and located in a strategic position between Australia and Timor Leste. A sharp increase of GHG emission along with environmental pollution, contamination of water, air and improper waste disposal practices as its consequence to the global environment. The city’s government ambition to evaluate impact of economic activity on greenhouse gases (GHG) emission contribution. This paper outlined pollutant sectors that contribute substantially to GHG emission in Kupang along with its structure, and count an estimated amount of emission coefficients for 27 economy sectors. More in-depth explanation about indirect coefficient pollutant emission which beneficial not only for calculation of the emission amount but more as inventory data for LCA. The paper is investigated review the trends of some priority sectors, then introduction of indirect coefficients of pollutant sectors, and showed the Pollutant Emission Structure for Kupang. After that, an estimated amount of Kupang GHG emission under BAU is also counted and confirmed. The paper only considers GHG emission issues while air pollutant emission only be provided as inventory data but will not be used as exogenous data for this paper. In the final part a brief explanation and implications of GHG emission policy in Kupang are identified. A detailed of input-output data for individual process are provided includes all groups of processes or industry sectors relevant to economy activities in Kupang City. A time period for Global Warming Potential (GWP) 20 year and 100 years are used to forecasted amounts share of total GHG emission in Kupang and Indonesia by 2020 compared to 2010. As results first, the GHG emission and air pollutant coefficients for 27 sectors in Kupang based on method is presented in NIES which use to count the GHG emission. These also become an Inventory data for researchers of regional science in Indonesia, however, geography and socioeconomic conditions in every region is different, so that some criteria will be applied. Second, found total GHG emission in Kupang is $1.0164\mathrm{x} 10^{-3}$ Gt or around 0.047% compared to total GHG emission by 2010 and 0.034% compared to total GHG emission by 2020 in Indonesia. The study suggests to government consider a proper method in decide a reliable environmental policy and technical measures to reach GHG emission targets by 2020. Third, total share of CO 2 e in Indonesia emitted from Kupang for GWP 20 years and 100 years respectively were came out as follow.

The decrease in the level of greenhouse gas (GHG) emissions from industry and agriculture is one of the biggest challenges that European Union (EU) countries have to face. Their economic development should occur under the conditions of limiting the pressure on the environment. The agricultural and industrial sectors play a key role in ensuring food security, technological progress, job security, social well-being, economic competitiveness, and sustainable development. The main purpose of this article was to identify and compare the level, trends, and variability in greenhouse gas emissions from industry and agriculture in EU countries in 2010–2019, to create classes of countries with similar gas emissions, and to analyze the average values of their economic conditions. The original contribution to the article was to investigate whether there is a relationship between the level of greenhouse gas emissions and the economic development of countries and other economic indicators characterizing the sectors of industry and agriculture. Empirical data were obtained from the Eurostat and Ilostat databases. Basic descriptive statistics, classification methods, multiple regression, and correlation methods were used in the study. The industrial and agricultural sectors in EU countries emit similar amounts of greenhouse gases into the environment. In the years 2010–2019, the percentage share of emissions from these sectors in total gas emissions was growing dynamically, but no evidence was found indicating that those countries that emitted the most greenhouse gases significantly reduced their emissions in the decade under review. Moreover, EU countries are still significantly and invariably differentiated in this respect. Greenhouse gas emissions from industry and agriculture are influenced by the economic characteristics of these sectors, such as the level of GDP per capita, the scale of investment by enterprises, the expenditure on research and development, as well as employment in these sectors. The findings of this study show that total greenhouse gas emissions from all sources increase with countries’ economic growth, while a higher level of support of EU countries for research and development, and a greater share of employment in both industry and agriculture, translate into higher greenhouse gas emissions from these sectors. These conclusions may be useful for decision makers in developed and developing countries, as well as those in the industrial and agricultural sectors, in controlling and verifying the possible causes of greenhouse gas emissions in terms of the need to reduce their negative role on the environment and human health.

Climate-smart livestock production at landscape level in Kenya