4.1.2. Need for Data Quality Management System
During the comprehensive investigation for this study, it was noticed that there is a lack of a systematic quality assurance for GHG data which are collected with static chambers and measured via gas chromatography. Many studies that assess the quality of GHG measurements either deal with the effects of chambers on GHG emissionsfrom soil and the technical improvement of chamber construction (e.g. Klein and Harvey (2012), Pihlatie et al. (2013)) or focus on the optimization of GHG flux calculation models (e.g. Kutzbach et al. (2007), Kroon et al. (2008), Pedersen et al. (2010), Pihlatie2013). From the state of knowledge, there are only few information about the quality control of GHG data obtained fromgas chromatography and the controlled removal of outliers based on objective criteria. Many previous studies had no need for the development of a structured data quality management system which checks GHG data from static chamber measurements regarding their suitability for subsequent flux calculation, because the collected data either showed a good linear fit (Gao and Yates, 1998; Yamulki and Jarvis, 1999; Conen and Smith, 2000) or non-linear fit (Livingston et al., 2005; Livingston et al., 2006; Kutzbach et al., 2007; Kroon et al., 2008). Some studies, such as Kutzbach et al. (2007), assume that potential errors of static chamber measurements are negligible and violations of their physically based model assumptions can be minimised by careful planning and performance. However, stable conditions during sampling, such as headspace temperature, humidity, headspace turbulence and pressure perturbations during chamber placement as well as the avoidance of leaks, are difficult to implement under real field conditions (Kutzbach et al., 2007). Nowadays GHG research is also conducted in remote areas with poor infrastructure and eventually unreliable power supply. GHG samples from those regions often have to be stored for long periods and transported over long distances until analysis is performed. Despite utmost diligence during sample preparation and field work, the integrity of arriving samples can be questionable and obtained data can show an unsatisfying fit to the selected flux calculation approach.
Agriculture is a signi ﬁcant source of greenhousegas (GHG) emissions, directly from nitrogen fertilizer use, biomass burning, rice cultivation, livestock manure management, and enteric fermentation from animals and indirectly fromlandusechange [Davidson, 2009; Houghton et al., 2012]. Currently, direct GHG emissionsfrom agriculture account for approximately 12% of annual anthropogenic emissions, a reduction from 14% in 2007 [Intergovernmental Panel on Climate Change (IPCC), 2014]. Despite the decline in relative impact of agriculture versus other GHG sources, the quantity of agriculturalemissions in absolute terms has increased and is expected to further increase due to population growth and dietary shifts [Tilman and Clark, 2014; Tubiello et al., 2014]. Soils managed for agriculture are both sources and sinks for GHGs [Kirschke et al., 2013; Smith et al., 2008]. The magnitude of exchange of CO 2 , N 2 O, and CH 4 between the biosphere and the atmosphere caused by bio- genic processes including autotrophic and heterotrophic respiration, nitri ﬁcation and denitriﬁcation, and methanogenesis and methanotrophy depends on carbon (C) and nitrogen (N) availability, land management, and environmental conditions (e.g., soil moisture, temperature, and pH) [Butterbach-Bahl et al., 2011, 2013; Davidson et al., 2000b, 2002; Verchot et al., 2000]. The net consequence of these factors is that agricultural soils contribute approximately 39% of global agricultural GHG emissions and 87% of total agricultural N 2 O emissions [FAOSTAT, 2014a].
Disaggregation of carbon stocks in land is necessary for the estimation of LUC – GHG emissions. Consistent work has been put into representing carbon stock heterogeneity in land and the estimation of carbon stock changes. For example, Houghton and Hackler  provided annual estimates of the net change in carbon from deliberate changes in land-cover and land-use. Emission factors are especially estimated for forest clearing for agriculture and the harvest of wood for wood products or energy. In the context of the assessment of biofuel LUC – GHG emissions, Winrock International  estimated the extent of recent land- cover change at national and sub-national scales for all countries using data derived from satellite imagery. GHG emission factors for various land-cover conversions are estimated using guidelines of the Intergovernmental Panel on Climate Change (IPCC) . Results from Winrock ’ s analysis were incorporated into the EPA ’ s RFS program . Speci ﬁ c land-use classes important for LUC – GHG emissions, such as wetlands, have been de ﬁ ned. However, in terms of disaggregation, more efforts are required in, for example, the disaggregation of carbon stocks by crop types.
Stein, E., D, Dark, S., Longcore, T., Grossinger, R., Hall, N., & Beland, M. (2010). Historical Ecology as a Tool for Assessing Landscape Change and Informing Wetland Restoration Priorities. Wetlands, 30, 589-601. doi:DOI 10.1007/s13157-010-0050-x
Tiner, R. W., Bergquest, H. C., DeAlessio, G. P., & Starr, M. J. (2002). Geographically Isolated Wetlands: A Preliminary Assessment of Their Characteristics and Status in Selected Areas of the United States. Retrieved from Northwest Region, Hadley, MA:
Evaluation of greenhousegasemissions using three-level model was carried out for St. Petersburg and the Leningrad Region (Russian Federation), they shown the possibility of reducing by 2030 by 3.2 ... 12.4% of gross GHG emissions by motor transport of the Russian Federation in comparison with 2015. For St. Petersburg and the Leningrad Region, both the reduction of gross GHG emissions by road transport (12.7% innovative scenario) and their growth (4.8% inertial scenario) are expected during the forecast period. At the same time, both for the St. Petersburg and the Leningrad Region and for the state as a whole, a significant reduction in gross GHG emissions by road transport is expected in the period after 2025 due to the intensive replacement of cars on oil fuel by electric vehicles and hybrids, changes in the transport behavior of the population, the development of public passenger transport and cycling, the introduction of autonomous vehicles, etc.
3 Charging farmers for their land-useemissions
As a signatory to the Kyoto Protocol, the government is obliged to reduce New Zealand’s annual emissions to the 1990 level during the 2008-2012 period or buy assigned amount units on the international market to make up the difference. Although agriculturalemissions have been rising at a much slower rate than New Zealand’s overall emissions, in which growth is driven largely driven by the transport sector, agriculturallanduseemissions, caused mostly by methane produced by grazing animals and nitrous oxide derived from animal excrement, constitute approximately half of New Zealand’s overall greenhousegasemissions (Brown and Plume, 2004). Therefore, reducing land-useemissions could significantly help New Zealand to meet its target and contribute efficiently to controlling greenhouse gases. A potential policy to help encourage emission reductions would be to charge farmers in proportion to the amount of emissions that their animal production produces. This would lead farmers to reduce area in livestock and particularly in dairy, reduce stocking rates and, if possible, change farm management to reduce emissions per animal. Current methane and nitrous oxide monitoring technology makes accurate animal or farm-scale monitoring of emissions impossible. The proposed policy related payments only to livestock numbers, which can be monitored. Because of current limitations in LURNZ, we model an even simpler policy where the government simply charges farmers in proportion to their land area in each landuse, and assumes that each farm emits an average amount per hectare. This is a less flexible policy because farmers cannot change their stocking rates in response to the charge. We therefore underestimate the size of the likely response to a charge based on livestock numbers.
(matching reflectance levels of invariant targets in the images), to further improve confidence in eventual change detection analyses.
IsoData and K-Means classifications, which don’t require user inputs to train their classification processes, were conducted upon several of the Landsat images to identify natural spectral breaks in land cover class separability. This technique is similar to research conducted by Gillanders, Coops et al. on the use of Landsat for monitoring the Athabasca oil sand region (3). The Landsat images, rendered in both true color and in color infrared, were then compared to the IsoData and K-Means classifications, using spectral signatures from the Landsat images that corresponded to the matching locations within the K-Means and IsoData classified images. The Landsat images where then compared with Google Earth’s high spatial resolution 2013 DigitalGlobe imagery, land cover data from the Alberta Biodiversity Monitoring Institute (ABMI 2013), and wetland map and field data from Vitt, Halsey et al. (4) and Beilman, Vitt et al. (5), to establish ideal spectral signatures for soil, water, shrubs, mixed forest/peatlands, coniferous forest, and broad leaf forest, which were recognized as the predominate land cover types within this study’s regions of interest.
Agricultural input and management information, including yield of major crops grown in India, were obtained from the Directorate of Economics and Statistics of the Government of India ( http://eands.dacnet.nic.in [accessed 01.10.2015]). The Govern- ment of India conducts cost of cultivation surveys at the Indian district level using multi-stage sampling. Districts within states, and villages within districts, formed the ﬁrst and second stage unit of sampling with the ultimate unit of data collection being the household ( CSO, 2002 ). The district and villages were selected in order to cover the major crops grown in the country. Fig. 1 shows the locations of households selected for the survey, which forms the foundation of the activity data used in this study. In total, there were 34,577 data points across India used in the study. Of these, 53% of data points were for paddy rice and wheat, representing the proportionate area under rice and wheat cultivation in India. Data on temperature and rainfall were obtained from the WorldClim global climate database ( http://worldclim.org/ [accessed 01.10.2015]), and soil data (soil texture, soil organic carbon, soil pH, bulk density) were obtained from Shangguan et al. (2014) . The water management system before and during rice cultivation was determined from databases at national and state levels ( Gupta et al., 2009 ), and expert opinion (experts from CIMMYT). The analysis includes a representative distribution of irrigation management strategies for rice, from ﬂooded to alternative wetting and drying systems. In India, agricultural residues left in the ﬁeld after harvest are sometimes burnt in-situ to facilitate cultivation of subsequent crops, or used for other purposes off-site. The information on residue management of different crops, including burning, was obtained from Gadde et al. (2009) and
Palm oil imports to the EU have significantly expanded over the period 2000-2012 (see Figure 36). Parts of these imports have been driven by a direct use by the industrial sector, in particular biofuels. But one third of these imports have also been absorbed by the food sector. The food sector has absorbed a similar quantity of sunflower oil, half of it being imported. These products compensated in the food sector for rapeseed and soybean oil transferred to the industrial uses. For instance, we analysed whether the food consumption varied for the different oils types in the EU, or whether difference of price between rapeseed and palm oil could explain some changes in trade patterns. On the basis of this analysis, we concluded that some substitution of vegetable oil was observed in food demand but was overall relatively limited compared to the industrial demand. Therefore, a relatively low elasticity of substitution should be used in the case of the EU. On the model side, in order to implement this limited substitution effect, we created an aggregated vegetable oil food item, in which the fluctuation of the different oil shares is relatively constrained. For this purpose, the objective function of GLOBIOM was modified to include some non-linear costs associated to the change in composition of the vegetable oil aggregate. In the version of IFPRI- MIRAGE used in Al-Riffai, Dimaranan & Laborde (2010), an elasticity of substitution of 2 was used in the different regions for substitution of vegetable oils and a trade Armington elasticity of 10. 132 When prices increase, both rapeseed imports and other oil demand react to compensate the shock.
The global demand for livestock products has grown over the years and is likely continue that growth in the future . Increasing overall livestock output has implications for the environment. The sources of GHG emis- sions from the livestock sector can be segregated into two broad categories: 1) emissions that emanate fromlanduse changes due to livestock production; typically when forest land is converted into pasture or cropland to ac- commodate increased livestock production, it results in increased GHG emissions due to land clearing and re- duced long term carbon sequestration; 2) emissions which are attributed to non-landusechange sources such as enteric fermentation, feed production and processing, manure handling, and processing and transportation of animal products.
et al., 2009; Smeets et al., 2009; Snyder et al., 2009; Panichelli et al., 2009; Smaling et
al., 2008; Reijnders and Huijbregts, 2008; Miller, 2010; Miller et al., 2006).
The transportation of soybean can represent an important contribution to the GHG balance (Prudêncio da Silva et al., 2010). Soybean is transported long distances by road and 42% of the soybean produced in Brazil (and 25% in Argentina) was exported for processing in other countries (Product Board MVO, 2011). Although long distance transoceanic transport might increase GHG emissions slightly, Prudêncio da Silva et al. (2010) showed that the place of origin of soybean within Brazil strongly affects its environmental impact, due to the current predominance of road transport.
over a period of one hundred or more years – eventually reach a new equilibrium and net carbon sequestration will decline to zero 1,22 . Actively managing the carbon sink by growing bioenergy crops or by managing forests for fuel-wood or timber might in some circumstances extend the timeframe for mitigation 23 , but might also compromise biodiversity objectives. Secondly, climate change feedbacks might affect our findings by altering soil carbon dynamics and the yields of food crops, livestock, bioenergy crops and trees. However, these effects are likely to be reduced by adaptation measures 15,24 , and provided that non-farmed habitats continue to store much more carbon than farmland we think our conclusions will hold. Thirdly, it is essential to assess the sustainability of yield increases 25 . For example, due regard for animal welfare, local air and water quality and soil function is essential when increasing yields 8,25 . Encouragingly, the techniques we consider that increase yield also have the potential to reduce externalities per unit of production (Supplementary Table 5) and modern livestock breeding techniques allow multiple traits, including health, welfare and productivity, to be considered simultaneously 8 (see Supplementary Discussion). Last, managing water resources in higher-yielding landscapes will require a focus on improving water use efficiency in crops alongside careful spatial planning of spared land.
4.3.2 Experimental design
Each of the 72 mesocosms comprising the soil in the PVC pipe were weighed, numbered and placed in sturdy 13-L plastic containers (315 mm × 275 mm) (Smithers-Oasis Company, Washington, UK). All mesocosms were kept in a controlled temperature room at 11° C (temperature at which GHG in situ emissions peaked, Chapter 3) for the duration of the experiment. To limit the effects of understory plants on soil GHG emissions any visible vegetation (mainly grasses) were carefully removed before starting the experiment. To maintain water tables at one of two set levels (“high” and “low”), 5 mm holes were drilled into the mesocosm at either 3 cm from the surface or 27 cm from the surface. The mesocosms were allowed to equilibrate at 11° C for 1 week prior to water table treatment application to allow time for the soil environment to stabilise and recover following disturbance. Half of the mesocosms from each combination of block and microtopograhy were assigned to either a high or low water table treatment, and water was added to the buckets to a level that aligned with the top of the drilled holes. Mesocosms were then allowed to equilibrate for 18 days before starting measurements, with water table monitored by daily inspection and maintained by manually topping up with deionised water when required. An additional set of 12 test mesocosms were used to monitor volumetric moisture content (VMC) using a ML2x Theta Probe and HH2 Meter (Delta T Devices, Cambridge, UK) to avoid disturbing the mesocosms from which GHG measurements were made.
The present work has shown that change in nutritional habits can have a great influence on agricultural energy consumption and greenhousegasemissions. Above all, eating less meat would lead to a decrease in negative agricultural environmental impacts. This research involves some uncertainties caused by the simplifications necessarily involved with treating Austrian agriculture as a single ‘average’ farm. As a result, it was not possible to consider the different conditions of production specific to various farming regions. Despite these uncertainties, the positive effects of reducing meat consumption and basing nutrition on plants to a greater extent on the agricultural energy and emission balance are obvious from the modeling and well attested in the literature. Furthermore, changed nutritional habits can contribute to the achievement of policy targets defined for renew- able energy use through the release of redundant land, where a large part of which can be used for renewable energy crops. So, the solution to the problem of increased competition for land for bioenergy production might well be not to increase the area under cultivation in sensitive regions, not to plow up grassland for crop cultivation, nor to increase the agricultural output by applying more pesticides and fertilizers. Even under con- sistent agricultural production methods in Austria, changed nutritional habits make more arable land avail- able for renewable energy crops. As a consequence, changing nutritional habits would be desirable not only because of the potential benefits that might be obtained in terms of human health, but also because of these sec- ondary emissions and renewable energy benefits.
Emisije stakleničkih plinova po stanovniku u zemljama sa snažnim gospodarskim uzletom još uvijek su relativno male u odnosu na emisije u visokorazvijenim zemljama. Tako su pred-metne emisije u Kini 2010. g. iznosile 6,2 t ugljičnog dioksida po stanovniku, u Indiji 1,7, u Indoneziji 2,0, u Brazilu 2,2, dok je emisija u SAD iznosila 17,6 t, u Njemačkoj 9,3, u Rusiji 12,0, u Saudijskoj Arabiji 18,2, u Australiji 16,0 i u Kanadi 18,2 t ( List of countries by carbon dioxide emissions – Wikipedia, 05. 10. 2013 . ). S obzirom da je svjetski prosjek iznosio 4,9 t ugljičnog dioksida po stanovniku, za očekivati je porast emisija stakleničkih plinova u pojedinim zemljama, što će, s obzirom na njihovu veličinu, odnosno broj stanovnika (2013. g. Kina: 1,39 milijardi stanovnika, Indija: 1,25 milijardi, Indonezija: 250 milijuna, Nigerija: 174 milijuna, Brazil: 200 milijuna ( prema: World Population Prospects, 2013: 51-60.) imati znakoviti utjecaj na porast emisija stakleničkih plinova na svjetskoj razini.
This report does not present a model for estimating the full environmental impactfrom the entire livestock sector, rather it focuses on GHG emissions, notably carbon dioxide, methane and nitrous oxide, from the dairy cattle sector. The assessment takes a food chain approach in estimating emissions generated during the production of inputs into the production process, dairy production, landusechange (deforestation related to soybean production), and milk transport (farm to dairy and from processor to retailer) and processing. Given the global scope of the assessment and the complexity of dairy systems, several hypotheses and generalisations have been used to overcome the otherwise excessive data requirements of the assessment. The uncertainties introduced by these assumptions were estimated and used to compute a confidence interval for the assessment results.
Using a hypothetical scenario creates a number of issues that makes it difficult to actually make conclusions on the potential of wetland afforestation. Since Sweden is such a long spread country from north to south the temperature difference with the reference scenario can be very big, which has impacts both on greenhousegasemissionsfromwetlands and potential forest growth. According to the wetland inventory many of Sweden’s fens are located in the north where both emissions and forest growth potential are smaller than in the reference scenario. Also a big part of the wetlands in Sweden are bogs. Bogs have not been studied in this thesis but have a lower methane carbon dioxide ratio than fens and a lower post drainage potential, since they are nutrient poor. If many of the wetlands in class four of the inventory are bogs and/or located in the north the value and potential of wetland afforestation is lower than suggested in the study. However the opposite is of course true if the conditions are better than in the reference scenario. The average numbers used in this hypothetical study give a good picture of how the situation most likely looks but it is of course the best suitable wetlands that should be drained. The wetland inventory determines which wetlands not to use but among the rest each specific site needs to be evaluated economically and emissions measured to determine if the benefits are higher than the costs.
Playa wetlands exist as the dominant surface water feature on the High Plains landscape and their natural functioning provides critical ecosystem services that are not provided elsewhere . Cropland agriculture is the major threat to playa hydrology and concomitant functioning, with impacts from physical mod- ifications to sediment accumulation  .  estimated that 60% of playa wetlands in the Southern High Plains have been physically lost due to sediment filling and 95.3% of playas have been modified. Increased sediment loads in playas force water to spread over a larger area, thus increasing evaporation loss and water infiltration into porous upland soils .  found that water loss rates were higher in playas with highly cultivated upland watersheds compared to native grasslands. Decreased ponding times of playas favor the establishment of more xeric flora that are often less productive than wetland species . Im- pacts from native grassland conversion to cropland result in diminished playa service capacity  and ultimately change the basic biogeochemical drivers mediating influxes and effluxes of GHGs.
The objectives of this study are to identify the energy balance of Indonesian palm oil biodiesel production, including the stages of landusechange,
transport and milling and biodiesel processing, and to estimate the amount of greenhousegasemissionsfrom different production systems, including large and small holder plantations either dependent or independent, located in Kalimantan and in Sumatra. Results show that the accompanied implications of palm oil biodiesel produced in Kalimantan and Sumatra are different: energy input in Sumatra is higher than in Kalimantan, except for transport processes; the input/output ratios are positive in both regions and all production systems. The findings demonstrate that there are considerable differences between the farming systems and the locations in net energy yields (43.6 to 49.2 GJ t -1 biodiesel yr -1 ) as well as greenhousegasemissions (1969.6 to 5626.4 kg CO 2eq t -1 biodiesel yr -1 ). The output to input ratios are positive in all cases. The largest greenhousegasemissions result fromlandusechange effects, followed by the transesterification, fertilizer production, agricultural production processes, milling and transportation. Ecosystem carbon payback times range from 11 to 42 years.
2013), manure physical parameters (Chadwick 2005) and temperature (Dobbie and Smith 2001), are likely very different in Switzerland than Australia. For example, emissionsfrom the manure in Külling et al. ’ s (2003) study were assessed at 20 C. By contrast, temperatures on Australian beef feedlot surfaces of 45 C are common (Redding et al. in press) and can reach up to 60 C (Queensland Department of Agriculture, Fisheries and Forestry, pers. comm., 2013). Manure on feedlot surfaces is often cracked and moisture content varies considerably from the surface to the base, in contrast with the manure assessed by Külling et al. (2003), which was a wet slurry. In short, the vastly differing conditions of Külling et al.’s (2003) study compared with beef feedlots in Australia raise serious questions concerning the use of the northern hemisphere default factors in the Australian GHG Inventory.