Using emissions derived from atmospheric observations to inform the reported UK inventory

<p align="justify">Verification of the nationally reported greenhouse gas (GHG) inventories using inverse modelling and atmospheric observations is considered to be best practice by the United Nations Framework Convention on Climate Change (UNFCCC). It allows for an independent assessment of the nationally reported GHG emissions using a comprehensively different approach to the inventory methods. Significant differences in the emissions estimated using the two approaches are a means of identifying areas worthy of further investigation.</p><p align="justify"> </p><p align="justify"><span>An inversion methodology called Inversion Technique for Emission Modelling (InTEM) has been developed that uses a non-negative least squares minimisation technique to determine the emission magnitude and distribution that most accurately reproduces the observations. By estimating the underlying </span><span><em>baseline</em></span><span> time series, atmospheric concentrations where the short-term impact of regional pollution has been removed, and by modelling where the air has passed over on route to the observation stations on a regional scale, estimates of UK emissions are made. </span>In this study we use an extensive network of observations with six stations across the UK and six more in neighbouring countries<span>. InTEM uses information from a</span> Lagrangian dispersion model NAME (Numerical Atmospheric dispersion Modelling Environment), driven by three-dimensional, modelled meteorology, to understand how the air mixes during transport from the emission sources to observation points. <span>The InTEM inversion results are submitted annually by the UK as part of their National Inventory Report to the UNFCCC. They are used within the UK inventory team to highlight areas for investigation and have led to significant improvements to the submitted UK inventory. The latest UK comparisons will be shown along with examples of how the inversion results have informed the inventory.</span></p>

Emissions from prescribed fires in temperate forest in south-east Australia: implications for carbon accounting

We estimated emissions of carbon, as equivalent CO2 (CO2e), from planned fires in four sites in a south-eastern Australian forest. Emission estimates were calculated using measurements of fuel load and carbon content of different fuel types, before and after burning, and determination of fuel-specific emission factors. Median estimates of emissions for the four sites ranged from 20 to 139 Mg CO2e ha−1. Variability in estimates was a consequence of different burning efficiencies of each fuel type from the four sites. Higher emissions resulted from more fine fuel (twigs, decomposing matter, near-surface live and leaf litter) or coarse woody debris (CWD; > 25 mm diameter) being consumed. In order to assess the effect of declining information quantity and the inclusion of coarse woody debris when estimating emissions, Monte Carlo simulations were used to create seven scenarios where input parameters values were replaced by probability density functions. Calculation methods were (1) all measured data were constrained between measured maximum and minimum values for each variable; (2) as in (1) except the proportion of carbon within a fuel type was constrained between 0 and 1; (3) as in (2) but losses of mass caused by fire were replaced with burning efficiency factors constrained between 0 and 1; and (4) emissions were calculated using default values in the Australian National Greenhouse Accounts (NGA), National Inventory Report 2011, as appropriate for our sites. Effects of including CWD in calculations were assessed for calculation Method 1, 2 and 3 but not for Method 4 as the NGA does not consider this fuel type. Simulations demonstrate that the probability of estimating true median emissions declines strongly as the amount of information available declines. Including CWD in scenarios increased uncertainty in calculations because CWD is the most variable contributor to fuel load. Inclusion of CWD in scenarios generally increased the amount of carbon lost. We discuss implications of these simulations and how emissions from prescribed burns in temperate Australian forests could be improved.

Emissions from prescribed fire in temperate forest in south-east Australia: implications for carbon accounting

We estimated of emissions of carbon, as CO2-equivalents, from planned fire in four sites in a south-eastern Australian forest. Emission estimates were calculated using measurements of fuel load and carbon content of different fuel types, before and after burning, and determination of fuel-specific emission factors. Median estimates of emissions for the four sites ranged from 20 to 139 T CO2–e ha−1. Variability in estimates was a consequence of different burning efficiencies of each fuel type from the four sites. Higher emissions resulted from more fine fuel (twigs, decomposing matter, near-surface live and leaf litter) or coarse woody debris (CWD; > 25 mm diameter) being consumed. In order to assess the effect of estimating emissions when only a few fuel variables are known, Monte-Carlo simulations were used to create seven scenarios where input parameters values were replaced by probability density functions. Calculation methods were: (1) all measured data were constrained between measured maximum and minimum values for each variable, (2) as for (1) except the proportion of carbon within a fuel type was constrained between 0 and 1, (3) as for (2) but losses of mass caused by fire were replaced with burning efficiency factors constrained between 0 and 1; and (4) emissions were calculated using default values in the Australian National Greenhouse Accounts (NGA), National Inventory Report 2011, as appropriate for our sites. Effects of including CWD in calculations were assessed for calculation Method 1, 2 and 3 but not for Method 4 as the NGA does not consider this fuel type. Simulations demonstrate that the probability of estimating true median emissions declines strongly as the amount of information available declines. Including CWD in scenarios increased uncertainty in calculations because CWD is the most variable contributor to fuel load. Inclusion of CWD in scenarios generally increased the amount of carbon lost. We discuss implications of these simulations and how emissions from prescribed burns in temperate Australian forests could be improved.