Regional spatial inventories (cadastres) of GHG emissions in the Energy sector: Accounting for uncertainty

An improvement of methods for the inventory of greenhouse gas (GHG) emissions is necessary to ensure effective control of commitments to emission reduction. The national inventory reports play an important role, but do not reflect specifics of regional processes of GHG emission and absorption for large-area countries. In this article, a GIS approach for the spatial inventory of GHG emissions in the energy sector, based on IPCC guidelines, official statistics on fuel consumption, and digital maps of the region under investigation, is presented. We include mathematical background for the spatial emission inventory of point, line and area sources, caused by fossil-fuel use for power and heat production, the residential sector, industrial and agricultural sectors, and transport. Methods for the spatial estimation of emissions from stationary and mobile sources, taking into account the specifics of fuel used and technological processes, are described. Using the developed GIS technology, the territorial distribution of GHG emissions, at the level of elementary grid cells 2 km?×?2 km for the territory of Western Ukraine, is obtained. Results of the spatial analysis are presented in the form of a geo-referenced database of emissions, and visualized as layers of digital maps. Uncertainty of inventory results is calculated using the Monte Carlo approach, and the sensitivity analysis results are described. The results achieved demonstrated that the relative uncertainties of emission estimates, for CO₂ and for total emissions (in CO₂ equivalent), depend largely on uncertainty in the statistical data and on uncertainty in fuels’ calorific values. The uncertainty of total emissions stays almost constant with the change of uncertainty of N₂O emission coefficients, and correlates strongly with an improvement in knowledge about CH₄ emission processes. The presented approach provides an opportunity to create a spatial cadastre of emissions, and to use this additional knowledge for the analysis and reduction of uncertainty. It enables us to identify territories with the highest emissions, and estimate an influence of uncertainty of the large emission sources on the uncertainty of total emissions. Ascribing emissions to the places where they actually occur helps to improve the inventory process and to reduce the overall uncertainty.     

Quantitative quality assessment of the greenhouse gas inventory for agriculture in Europe

The greenhouse gas inventory of the European Communities and its estimation of the uncertainty is built from 15 individual and independent greenhouse gas inventories. This presents a particular challenge and is possible only if homogeneous information is available for all member states and if a proper evaluation of correlation between member states is performed. To this end, we present a methodology that estimates a quantitative measure for the aggregated Tier-level as well as the uncertainty for the main categories in the agriculture sector. In contrast to the approach suggested in the IPCC guidelines, which uses uncertainty estimates for activity data and emissions factors for each source category, the method presented uses quantitative information from individual parameters used in the inventory calculations, in combination with a well defined procedure to aggregate the information. Not surprisingly, N₂O emissions from agricultural soils are found to dominate the uncertainty. The results demonstrate the importance of correlation, if uncertainties are combined for the whole of Europe. The biggest challenge seems to be to conceptually harmonize the uncertainty estimates for the activity data (which tend to be underestimated) and emission factors (which tend to be overestimated).     

Contributions of individual countries?? emissions to climate change and their uncertainty

We have compiled historical greenhouse gas emissions and their uncertainties on country and sector level and assessed their contribution to cumulative emissions and to global average temperature increase in the past and for a the future emission scenario. We find that uncertainty in historical contribution estimates differs between countries due to different shares of greenhouse gases and time development of emissions. Although historical emissions in the distant past are very uncertain, their influence on countries?? or sectors?? contributions to temperature increase is relatively small in most cases, because these results are dominated by recent (high) emissions. For relative contributions to cumulative emissions and temperature rise, the uncertainty introduced by unknown historical emissions is larger than the uncertainty introduced by the use of different climate models. The choice of different parameters in the calculation of relative contributions is most relevant for countries that are different from the world average in greenhouse gas mix and timing of emissions. The choice of the indicator (cumulative GWP weighted emissions or temperature increase) is very important for a few countries (altering contributions up to a factor of 2) and could be considered small for most countries (in the order of 10%). The choice of the year, from which to start accounting for emissions (e.g. 1750 or 1990), is important for many countries, up to a factor of 2.2 and on average of around 1.3. Including or excluding land-use change and forestry or non-CO₂ gases changes relative contributions dramatically for a third of the countries (by a factor of 5 to a factor of 90). Industrialised countries started to increase CO₂ emissions from energy use much earlier. Developing countries?? emissions from land-use change and forestry as well as of CH₄ and N₂O were substantial before their emissions from energy use.     

Uncertainty of forest carbon stock changes – implications to the total uncertainty of GHG inventory of Finland

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of the efforts needed for development of the inventory. This paper presents an uncertainty analysis of GHG emissions of all Kyoto sectors and gases for Finland consolidated with estimates of emissions/removals from LULUCF categories. In Finland, net GHG emissions in 2003 were around 69 Tg (±15 Tg) CO₂ equivalents. The uncertainties in forest carbon sink estimates in 2003 were larger than in most other emission categories, but of the same order of magnitude as in carbon stock change estimates in other land use, land-use change and forestry (LULUCF) categories, and in N₂O emissions from agricultural soils. Uncertainties in sink estimates of 1990 were lower, due to better availability of data. Results of this study indicate that inclusion of the forest carbon sink to GHG inventories reported to the UNFCCC increases uncertainties in net emissions notably. However, the decrease in precision is accompanied by an increase in the accuracy of the overall net GHG emissions due to improved completeness of the inventory. The results of this study can be utilised when planning future GHG mitigation protocols and emission trading schemes and when analysing environmental benefits of climate conventions.     

National greenhouse gas accounts: Current anthropogenic sources and sinks

This study provides estimates of greenhouse gas emissions from the major anthropogenic sources for 142 countries. The data compilation is comprehensive in approach, including emissions from CO, CH₄, and N₂O, and ten halocarbons, in addition to CO₂. The sources include emissions from fossil fuel production and use, cement production, halocarbons, landfills, land use changes, biomass burning, rice and livestock production and fertilizer consumption. The approach used to derive these estimates corresponds closely with the simple methodologies proposed by the Greenhouse Gas Emissions Task Force of the Intergovernmental Panel on Climate Change. The inventory includes a new estimate of greenhouse gas emissions from fossil fuel combustion based principally on data from the International Energy Agency. The research methodologies for estimating emissions from all sources is briefly described and compared with other recent studies in the literature.     

南京和长三角地区CO_2与CH_4人为排放清单估算的不确定性分析

目前温室气体清单的编制主要基于IPCC方法,该方法用于特定城市或区域清单编制时可能会引起较大的不确定性,而目前对城市/区域尺度清单的不确定性的分析还存在很大的欠缺。本文通过南京市和长三角温室气体排放因子甄选,应用IPCC方法计算了2009年南京市和长三角的人为温室气体排放量,并以其为个例利用蒙特卡洛方法开展城市和区域尺度的温室气体人为排放清单不确定性的初步探究。研究结果表明:南京市CH4和CO2排放量的95%的概率分布范围分别为(1.08~1.86)×105t和(6.50~7.41)×107t,不确定性分别为-21.74%~34.78%和-7.01%~5.87%;长三角CH4和CO2排放量的95%的概率分布范围分别为(4.07~5.89)×106t和(1.62~1.82)×109t,不确定性分别为-15.60%~22.24%和-6.04%~5.34%。     

Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture

Agricultural soils are a major source of atmospheric nitrous oxide (N₂O), a potent greenhouse gas (GHG). Because N₂O emissions strongly depend on soil type, climate, and crop management, their inventory requires the combination of biophysical and economic modeling, to simulate farmers’ behavior. Here, we coupled a biophysical soil-crop model, CERES-EGC, with an economic farm type supply model, AROPAj, at the regional scale in northern France. Response curves of N₂O emissions to fertilizer nitrogen (Nf) inputs were generated with CERES-EGC, and linearized to obtain emission factors. The latter ranged from 0.001 to 0.0225 kg N₂O-N kg^???1 Nf, depending on soil and crop type, compared to the fixed 0.0125 value of the IPCC guidelines. The modeled emission factors were fed into the economic model AROPAj which relates farm-level GHG emissions to production factors. This resulted in a N₂O efflux 20% lower than with the default IPCC method. The costs of abating GHG emissions from agriculture were calculated using a first-best tax on GHG emissions, and a second-best tax on their presumed factors (livestock size and fertilizer inputs). The first-best taxation was relatively efficient, achieving an 8% reduction with a tax of 11 €/ t-CO₂-equivalent, compared to 68 €/t-CO₂ eq for the same target with the second-best scheme.     

Uncertainty analysis for estimation of landfill emissions and data sensitivity for the input variation

Results of research and practical experience confirm that stabilization of GHG concentrations will require a tremendous effort. One of the sectors identified as a significant source of methane (CH₄) emissions are solid waste disposal sites (SWDS). Landfills are the key source of CH₄ emissions in the emissions inventory of Slovakia, and the actual emission factors are estimated with a high uncertainty level. The calculation of emission uncertainty of the landfills using the more sophisticated Tier 2 Monte Carlo method is evaluated in this article. The software package that works with the probabilistic distributions and their combination was developed with this purpose in mind. The results, sensitivity analysis, and computational methodology of the CH₄ emissions from SWDS are presented in this paper.     

Assessment of greenhouse gases emission from civil aviation in Russia

The greenhouse gases emission (CO₂, CH₄, and N₂O) from domestic and international aviation in the Russian Federation is assessed. In 2007, the total emission of CO₂, CH₄, and N₂O amounted to 18.4 million tons of CO₂-equivalent, which is 21% below the 1990 level. Carbon dioxide dominates in the component composition of the emissions, its part in 2007 accounted for 99.1% of the emission. Taking into account the tendency towards increasing fuel consumption due to intense aircraft traffic it can be expected that compared to the present level the greenhouse gases emissions in 2012 and 2020 will increase by 15 and 45%, respectively. Accounting for the increased aircraft emissions as well as plans of foreign countries to include the international aviation into the scheme of greenhouse gases emission allowance (trade credits) it is expedient to make more precise the greenhouse gases emissions from the Russian aviation based on the detailed flight data for all types of the aircraft.     

Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15

Total uncertainty in greenhouse gas (GHG) emissions changes over time due to “learning” and structural changes in GHG emissions. Understanding the uncertainty in GHG emissions over time is very important to better communicate uncertainty and to improve the setting of emission targets in the future. This is a diagnostic study divided into two parts. The first part analyses the historical change in the total uncertainty of CO₂ emissions from stationary sources that the member states estimate annually in their national inventory reports. The second part presents examples of changes in total uncertainty due to structural changes in GHG emissions considering the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) emissions scenarios that are consistent with the EU’s “20-20-20” targets. The estimates of total uncertainty for the year 2020 are made under assumptions that relative uncertainties of GHG emissions by sector do not change in time, and with possible future uncertainty reductions for non-CO₂ emissions, which are characterized by high relative uncertainty. This diagnostic exercise shows that a driving factor of change in total uncertainty is increased knowledge of inventory processes in the past and prospective future. However, for individual countries and longer periods, structural changes in emissions could significantly influence the total uncertainty in relative terms.     

Influence of soil C, N2O and fuel use on GHG mitigation with no-till adoption

Previous research has demonstrated that soil carbon sequestration through adoption of conservation tillage can be economically profitable depending on the value of a carbon offset in a greenhouse gas (GHG) emissions market. However adoption of conservation tillage also influences two other potentially important factors, changes in soil N₂O emissions and CO₂ emissions attributed to changes in fuel use. In this article we evaluate the supply of GHG offsets associated with conservation tillage adoption for corn-soy-hay and wheat-pasture systems of the central United States, taking into account not only the amount of carbon sequestration but also the changes in soil N₂O emission and CO₂ emissions from fuel use in tillage operations. The changes in N₂O emissions are derived from a meta-analysis of published studies, and changes in fuel use are based on USDA data. These are used to estimate changes in global warming potential (GWP) associated with adoption of no-till practices, and the changes in GWP are then used in an economic analysis of the potential supply of GHG offsets from the region. Simulation results demonstrate that taking N₂O emissions into account could result in substantial underestimation of the potential for GHG mitigation in the central U.S. wheat pasture systems, and large over-estimation in the corn-soy-hay systems. Fuel use also has quantitatively important effects, although generally smaller than N₂O. These findings suggest that it is important to incorporate these two effects in estimates of GHG offset potential from agricultural lands, as well as in the design of GHG offset contracts for more complete accounting of the effect that no-till adoption will have on greenhouse gas emissions.     

Safe policies in an uncertain climate: an application of FUND

Various aspects of the role of uncertainty in greenhouse gas emission reduction policy are analyzed with the integrated assessment model FUND. FUND couples simple models of economy, climate, climate impacts, and emission abatement. Probability distribution functions are assumed for all major parameters in the model. Monte Carlo analyses are used to study the effects of parametric uncertainties. Uncertainties are found to be large and grow over time. Uncertainties about climate change impacts are more serious than uncertainties about emission reduction costs, so that welfare-maximizing policies are stricter under uncertainty than under certainty. This is more pronounced without than with international cooperation. Whether or not countries cooperate with one another is more important than whether or not uncertainty is considered. Meeting exogenously defined emission targets may be more or less difficult under uncertainty than under certainty, depending on the asymmetry in the uncertainty and the central estimate of interest. The major uncertainty in meeting emissions targets in each of a range of possible future is the timing of starting (serious) reduction policies. In a scenario aiming at a stable CO₂ concentration of 550 ppm, the start date varies 20 years for Annex I countries, and much longer for non-Annex countries. Atmospheric stabilization at 550 ppm does not avoid serious risks with regard to climate change impacts. At the long term, it is possible to avoid such risks but only through very strict emission control at high economic costs.     

Valueloading And Uncertainty In A Sector-based Differentiation Scheme For Emission Allowances

The Triptych approach is a sectoral approach for differentiation of quantitative greenhouse gas emission reduction objectives. In this study we investigate the ranges in emission reduction targets that result from differences in valueladen assumptions and uncertainties in input data and parameters. In order to assess the effect of highly valueladen assumptions on resulting objectives we used two approaches. First we performed a sensitivity analysis. Then we elaborated the approach from four ideal-typical value-orientations: the administrator, the businessman, the campaigner and the survivor. For each of these value-orientations we specified corresponding sets of assumptions of highly valueladen parameters. Within each set, we also assessed uncertainties for the remaining parameters and input data. We assessed the strength and we quantified their inexactnesses with probability distribution functions. Next, we carried out Monte Carlo simulations in each of the four value-orientations to quantify error propagation from the inexactnesses in input data and parameters. We found targets for the year 2015 for Annex I countries differed up to around 20%-points over the four value-orientations. For developing countries differences in allowances were found up to the order of four. In addition, results are affected to a large extent by uncertainties in the other input data and parameters. Ranges in the outcome resulting from uncertainties are between 10 and 35%-points for Annex I countries, depending on the value-orientation chosen and between 20 and 120%-points for non-Annex I countries. However, the ranking of countries within the calculated differentiation remains roughly the same, an exception being the ranking that resulted from the businessman’s perspective. Other consistent combinations of valueladen assumptions may result in objectives that are outside the range that we based on the four value-orientations. We concluded that care should be taken when assessing valueloading in calculations schemes for emissions objectives based on a limited number of value-orientations only. Our analysis clearly underlines the relevance of making explicit policy variables in schemes for the differentiation of commitments. It is necessary to reach consensus on these variables if such schemes are to support negotiations on greenhouse gas emissions allowances.     

Spatial GHG inventory at the regional level: accounting for uncertainty

Methodology and geo-information technology for spatial analysis of processes of greenhouse gas (GHG) emissions from mobile and stationary sources of the energy sector at the level of elementary plots are developed. The methodology, which takes into account the territorial specificity of point, line, and area sources of emissions, is based on official statistical data surveys. The spatial distribution of emissions and their structure for the main sectors of the energy sector in the territory of the Lviv region of Ukraine are analyzed. The relative uncertainties of emission estimates obtained are calculated using knowledge of the spatial location of emission sources and following the Tier 1 and Tier 2 approaches of IPCC methodologies. The sensitivity of total relative uncertainty to change of uncertainties in input data uncertainties is studied for the biggest emission point sources. A few scenarios of passing to the alternative energy generation are considered and respective structural changes in the structure of greenhouse gas emissions are analyzed. An influence of these structural changes on the total uncertainty of greenhouse gas inventory results is studied.     

Estimated N2O and CO2 Emissions as Influenced by Agricultural Practices in Canada

The Denitrification-Decompostion (DNDC) model was used to estimate the impact of change in management practices on N₂O emissions in seven major soil regions in Canada, for the period 1970 to 2029. Conversion of cultivated land to permanent grassland would result in the greatest reduction in N₂O emissions, particularly in eastern Canada wherethe model estimated about 60% less N₂O emissions for thisconversion. About 33% less N₂O emissions were predicted for a changefrom conventional tillage to no-tillage in western Canada, however, a slight increase in N₂O emissions was predicted for eastern Canada. GreaterN₂O emissions in eastern Canada associated with the adoption of no-tillage were attributed to higher soil moisture causing denitrification, whereas the lower emissions in western Canada were attributed to less decomposition of soil organic matter in no-till versus conventional tilled soil. Elimination of summer fallow in a crop rotation resulted in a 9% decrease in N₂O emissions, with substantial emissions occurringduring the wetter fallow years when N had accumulated. Increasing N-fertilizer application rates by 50% increased average emissions by 32%,while a 50% decrease of N-fertilizer application decreased emissions by16%. In general, a small increase in N₂O emissions was predicted when N-fertilizer was applied in the fall rather than in the spring. Previous research on CO₂ emissions with the CENTURY model (Smith et al.,2001) allowed the quantification of the combined change in N₂O andCO₂ emissions in CO₂ equivalents for a wide range of managementpractices in the seven major soil regions in Canada. The management practices that have the greatest potential to reduce the combined N₂O andCO₂ emissions are conversion from conventional tillage to permanent grassland, reduced tillage, and reduction of summer fallow. The estimated net greenhouse gas (GHG) emission reduction when changing from cultivated land to permanent grassland ranged from 0.97 (Brown Chernozem) to 4.24 MgCO₂ equiv. ha^–1 y^–1 (BlackChernozem) for the seven soil regions examined. When changing from conventional tillage to no-tillage the net GHG emission reduction ranged from 0.33 (Brown Chernozem) to 0.80 Mg CO₂ equiv. ha^–1 y^–1 (Dark GrayLuvisol). Elimination of fallow in the crop rotation lead to an estimated net GHG emission reduction of 0.43 (Brown Chernozem) to 0.80 Mg CO₂ equiv.ha^–1 y^–1 (Dark Brown Chernozem). The addition of 50% more or 50% less N-fertilizer both resulted in slight increases in combined CO₂ and N₂O emissions. There was a tradeoff in GHG flux with greaterN₂O emissions and a comparable increase in carbon storage when 50% more N-fertilizer was added. The results from this work indicate that conversion of cultivated land to grassland, the conversion from conventional tillage to no-tillage, and the reduction of summerallow in crop rotations could substantially increase C sequestration and decrease net GHG emissions. Based on these results a simple scaling-up scenario to derive the possible impacts on Canada's Kyoto commitment has been calculated.     

Emissions of Nitrous Oxide and Methane from Conventional and Alternative Fuel Motor Vehicles

This paper provides estimates of emissions of two important but often not well-characterized greenhouse gas (GHG) emissions related to transportation energy use: methane (CH₄) and nitrous oxide (N₂O). The paper focuses on emissions of CH₄ and N₂O from motor vehicles because unlike emissions of CO₂, which are relatively easy to estimate, emissions of CH₄ and N₂O are a function of many complex aspects of combustion dynamics and of the type of emission control systems used. They therefore cannot be derived easily and instead must be determined through the use of published emission factors for each combination of fuel, end-use technology, combustion conditions, and emission control system. Furthermore, emissions of CH₄ and N₂O may be particularly important with regard to the relative CO₂-equivalent GHG emissions of the use of alternative transportation fuels, in comparison with the use of conventional fuels. By analyzing a database of emission estimates, we develop emission factors for N₂O and CH₄ from conventional vehicles, in order to supplement recent EPA and IPCC estimates, and we estimate relative emissions of N₂O and CH₄ from different alternative fuel passenger cars, light-duty trucks, and heavy-duty vehicles.     

The geography of global urban greenhouse gas emissions: an exploratory analysis

The purpose of this paper is to describe global urban greenhouse gas emissions by region and sector, examine the distribution of emissions through the urban-to-rural gradient, and identify covariates of emission levels for our baseline year, 2000. We use multiple existing spatial databases to identify urban extent, greenhouse gas emissions (CO₂, N₂O, CH₄ and SF₆) and covariates of emissions in a “top-down” analysis. The results indicate that urban activities are significant sources of total greenhouse gas emissions (36.8 and 48.6 % of total). The urban energy sector accounts for between 41.5 and 66.3 % of total energy emissions. Significant differences exist in the urban share of greenhouse gas emissions between developed and developing countries as well as among source sectors for geographic regions. The 50 largest urban emitting areas account for 38.8 % of all urban greenhouse gas emissions. We find that greenhouse gas emissions are significantly associated with population size, density, growth rates, and per capita income. Finally, comparison of our results to “bottom-up” estimates suggest that this research’s data and techniques are best used at the regional and global scales.     

Impacts of future Indian greenhouse gas emission scenarios on projected climate change parameters deduced from MAGICC model

The MAGICC (Model for the Assessment of Greenhouse gas Induced Climate Change) model simulation has been carried out for the 2000–2100 period to investigate the impacts of future Indian greenhouse gas emission scenarios on the atmospheric concentrations of carbon dioxide, methane and nitrous oxide besides other parameters like radiative forcing and temperature. For this purpose, the default global GHG (Greenhouse Gases) inventory was modified by incorporation of Indian GHG emission inventories which have been developed using three different approaches namely (a) Business-As-Usual (BAU) approach, (b) Best Case Scenario (BCS) approach and (c) Economy approach (involving the country’s GDP). The model outputs obtained using these modified GHG inventories are compared with various default model scenarios such as A1B, A2, B1, B2 scenarios of AIM (Asia-Pacific Integrated Model) and P50 scenario (median of 35 scenarios given in MAGICC). The differences in the range of output values for the default case scenarios (i.e., using the GHG inventories built into the model) vis-à-vis modified approach which incorporated India-specific emission inventories for AIM and P50 are quite appreciable for most of the modeled parameters. A reduction of 7% and 9% in global carbon dioxide (CO₂) emissions has been observed respectively for the years 2050 and 2100. Global methane (CH₄) and global nitrous oxide (N₂O) emissions indicate a reduction of 13% and 15% respectively for 2100. Correspondingly, global concentrations of CO₂, CH₄ and N₂O are estimated to reduce by about 4%, 4% and 1% respectively. Radiative forcing of CO₂, CH₄ and N₂O indicate reductions of 6%, 14% and 4% respectively for the year 2100. Global annual mean temperature change (incorporating aerosol effects) gets reduced by 4% in 2100. Global annual mean temperature change reduces by 5% in 2100 when aerosol effects have been excluded. In addition to the above, the Indian contributions in global CO₂, CH₄ and N₂O emissions have also been assessed by India Excluded (IE) scenario. Indian contribution in global CO₂ emissions was observed in the range of 10%–26%, 6%–36% and 10%–38% respectively for BCS, Economy and BAU approaches, for the years 2020, 2050 and 2100 for P50, A1B-AIM, A2-AIM, B1-AIM & B2-AIM scenarios. CH₄ and N₂O emissions indicate about 4%–10% and 2%–3% contributions respectively in the global CH₄ and N₂O emissions for the years 2020, 2050 and 2100. These Indian GHG emissions have significant influence on global GHG concentrations and consequently on climate parameters like RF and ∆T. The study reflects not only the importance of Indian emissions in the global context but also underlines the need of incorporation of country specific GHG emissions in modeling to reduce uncertainties in simulation of climate change parameters.     

Methods for exploring management options to reduce greenhouse gas emissions from tropical grazing systems

Increasing atmospheric concentrations of greenhouse gases are expected to result in global climatic changes over the next decades. Means of evaluating and reducing greenhouse gas emissions are being sought. In this study an existing simulation model of a tropical savanna woodland grazing system was adapted to account for greenhouse gas emissions. This approach may be able to be used in identifying ways to assess and limit emissions from other rangeland, agricultural and natural ecosystems.GRASSMAN, an agricultural decision-support model, was modified to include sources, sinks and storages of greenhouse gases in the tropical and sub-tropical savanna woodlands of northern Australia. The modified model was then used to predict the changes in emissions and productivity resulting from changes in stock and burning management in a hypothetical grazing system in tropical northeastern Queensland. The sensitivity of these results to different Global Warming Potentials (GWPs) and emission definitions was then tested.Management options to reduce greenhouse gas emissions from the tropical grazing system investigated were highly sensitive to the GWPs used, and to the emission definition adopted. A recommendation to reduce emissions by changing burning management would be toreduce fire frequency if both direct and indirect GWPs of CO₂, CH₄, N₂O, CO and NO are used in evaluating emissions, but toincrease fire frequency if only direct GWPs of CO₂, CH₄ and N₂O are used. The ability to reduce greenhouse gas emissions from these systems by reducing stocking rates was also sensitive to the GWPs used. In heavily grazed systems, the relatively small reductions in stocking rate needed to reduce emissions significantly should also reduce the degradation of soils and vegetation, thereby improving the sustainability of these enterprises.The simulation studies indicate that it is possible to alter management to maximise beef cattle production per unit greenhouse gases or per unit methane emitted, but that this is also dependent upon the emission definition used. High ratios of liveweight gain per unit net greenhouse gas emission were found in a broadly defined band covering the entire range of stocking rates likely to be used. In contrast, high values of liveweight gain per unit anthropogenic greenhouse gas emission were found only at very low stocking rates that are unlikely to be economically viable.These results suggest that policy initiatives to reduce greenhouse gas emissions from tropical grazing systems should be evaluated cautiously until the GWPs have been further developed and the implications of emission definitions more rigorously determined.     

Modeling N2O Emissions from Agricultural Fields in Southeast China

DNDC, a rainfall-driven and process-oriented model of soil carbon and nitrogen biogeochemistry, is applied to simulate the nitrous oxide emissions from agricultural ecosystem in Southeast China. We simulated the soil N₂O emission during a whole rice-wheat rotation cycle (from Nov. 1, 1996 to Oct. 31, 1997) under three different conditions, which are A) no fertilizer, B) both chemical fertilizer and manure and, C) chemical fertilizer only. The processes of N₂O emission were discussed in detail by comparing the model outputs with the results from field measurement. The comparison shows that the model is good at simulating most of the N₂O emission pulses and trends. Although the simulated N₂O emission fluxes are generally less than the measured ones, the model outputs during the dryland period, especially during the wheat reviving and maturing stages in spring, are much better than those during the paddy field period. Some sensitive experiments were made by simulating the N₂O emissions in spring, when there is a smallest gap between the simulated fluxes and the measured ones. Meanwhile, the effects of some important regulating factors, such as the rainfall, N deposition by rainfall, temperature, tillage, nitrogen fertilizer and manure application on N₂O emission during this period were analyzed. From the analysis, we draw a conclusion that soil moisture and fertilization are the most important regulating factors while the N₂O emission is sensitive to some other factors, such as temperature, manure, tillage and the wet deposition of atmospheric nitrate.