Flow Chart Specification




There is an enormous variety of biomass technologies which can be implemented to reduce greenhouse gas emissions on a national and international scale. This diversity presents significant challenges to the preparation of a practical software tool. However, this task can be simplified by using flow charts to summarise most of the fundamental data which characterise any given biomass technology. As such, a flow chart represents all the inter-linked processes which comprise a biomass technology. Each major processes is identified and essential data are specified for the inputs and outputs associated with each process. It should be noted that such flow charts are normally used to summarise the main flow of materials through the entire series of processes. Consequently, in terms of biomass technologies, the main materials are the initial input resources (seeds, cuttings, land, etc.) and the main products are forms of delivered energy 1 (solid, liquid and gaseous fuels, heat, electricity, etc.). Intermediate products exchanged between processes are included but other inputs (fossil fuels, machinery, equipment, etc.) are usually excluded for the sake of clarity. However, it is essential for the flow chart to indicate any co-products and by-products which occur at any stage in the biomass technology since these can have a very significant role in final evaluation through allocation procedures.

1 Delivered energy consists of the fuels, electricity, group or district heat, etc., which are purchased by consumers for use in their equipment, appliances, etc., to provide the energy services which they require.






































Greenhouse Gas Balance Calculation




A major component of the software tool which relies of relevant flow chart data is the means for calculating the GHG balance for any given biomass technology. There are three main sources of GHG emissions for a biomass technology. First, direct emissions can arise when the fuel provided by a biomass technology is burned. Since biomass technologies are frequently regarded as "carbon neutral" in terms of direct CO2 emissions, this may be viewed as an unnecessary complication. However, some proposed technologies can rely on unsustainable sources of biomass in which the original organic material is not replaced so that subsequent CO2 emissions are not re-absorbed by future growth. In such cases, all or part of the CO2 released during combustion must be included in the GHG balance calculations. Furthermore, other greenhouse gases, such as CH4 and N2O, can also be released during combustion. As these greenhouse gases will not be re-absorbed, even by sustainably-managed biomass schemes, these direct emissions must be included in the GHG balance calculations. Second, GHG sources and sinks can be associated with certain biomass technologies. For example, certain soils can release CO2 and, perhaps, CH4, when they are disturbed and exposed during cultivation activities, thereby constituting a GHG source. Conversely, some processing activities might result in the absorption of CO2 into long-lasting products, thereby giving rise to a GHG sink. Such considerations have to be taken into account in the GHG balance calculations. Finally, GHG emissions occur due to the direct and indirect combustion or related use of fossil fuels in the operation of a biomass technology. This requires the assessment of relevant emissions from the consumption of fossil fuels and fossil fuel-generated electricity and the manufacture of machinery, equipment, etc. Although most GHG emissions are associated with the direct and indirect combustion of fossil fuels, significant emissions of N2O can arise from the conventional manufacture of artificial fertilisers, such as ammonium nitrate, which are often involved in the cultivation of biomass. All GHG emissions resulting from such activities must be incorporated into GHG balance calculations.

































Cost-Effectiveness Saving Calculation



There are numerous definitions of the term "cost-effectiveness" (Davison, 2000) and it will be necessary to establish an agreed and precise version for current work. In general, cost-effectiveness can be represented by the "cost of avoided net emissions" for a biomass technology which is equal to the cost of the technology (construction, operation and decommissioning) per unit of net GHG saved. Although there are established methods from economics for the calculation of the cost of the technology, it will be necessary to take into account the effects of discounted cash flow analysis. The reason for this is that many biomass technologies include cycles of cultivation and harvesting which extend over considerable periods of time. Under normal circumstances, discounting must be applied to the investment and operating cash flows so that they can be combined on a common basis for the evaluation of total costs. Given the potentially long timescales, the choice of discount rate becomes a crucial consideration. Whilst there is no definitive choice for the discount rate, the approach adopted in this work must achieve a high degree of transparency regarding the actual value applied, along with other essential factors, such as the lifetime of the biomass technology. It must also be emphasised that the data and methods for calculating the costs of any biomass technology must be consistent with the data and methods used in calculating its GHG balance.

It should be noted that, in the calculation of cost-effectiveness, net GHG savings are determined by subtracting the GHG emissions of the biomass technology from the GHG emissions of the conventional source of delivered energy which it displaces. Hence, it could be concluded that this component of the software tool requires estimates of GHG emissions for conventional sources of delivered energy for all member states of the European Union. Although the direct GHG emissions for most common fossil fuels do not vary significantly from country to country, there are substantial variations in the GHG emissions associated with electricity across the European Union due to differences in the mix of generating plant. In theory, data published by the Statistical Office of the European Communities (EUROSTAT, 2001) and the European Environment Agency (EEA, 2002) should provide the ideal sources of such information since they provide regular results produced on a consistent basis for all European Union member states. The standard methodology for calculating these results is also provided by the Intergovernmental Panel on Climate Change (IPCC, 1995). However, data published by EUROSTAT and the EEA using the standard IPCC methodology aggregates GHG emissions for all energy industries. Consequently, it is not possible to adopt these sources to determine the GHG emissions associated with electricity for each member state of the European Union.
























TimberCAM

The main focus of TimberCAM is on the storage of carbon in wood products, and most of the data behind it was generated from several research projects within the CRCGA, It is envisaged that the tool will be of assistance particularly to public and private forest growing agencies with interest in carbon trading, the forest products industry and industry associations.

Content Information

Fabiano Ximenes (Research Officer)
Forest R&D; division - NSW Dept. of Primary Industries
PO BOX 100 - Breecroft NSW 2119
Australia
http://www.greenhouse.crc.org.au


RETScreen

In addition to the software, the tool includes product, cost and international weather databases; an online manual; a case study based college/university-level training course and electric textbook; and an Internet-based Marketplace.

The RETScreen software now has more than 49,200 users in 202 countries and is growing at more than 200 new users every week.


CAMFor

Simulations of fire and harvest scenarios, as well as accounting for natural turnover and mortality of biomass pools both above and below ground, are available. CAMFor accounts also for products removed from the forest, and for decay of that material (including its use for bio-energy) over time. It provides a seamless interface between the atmosphere and terrestrial carbon pools, having regard to the conservation of carbon at a particular site. The transfer of carbon between pools is reconciled with both the uptake of atmospheric CO2 and the release of carbon due to decomposition of materials on site and off site.

The AGO, as part of its work developing the National Carbon Accounting System, reviewed the operation of a number of existing accounting tools. On recognition of CO2 Fix as the preferred starting point, the AGO made the necessary changes to accommodate Australian conditions, including Australian management practices and an ability to accommodate the impact of fire. Changes include also the ability to move from the individual forest stand, or project scale accounting, to a mixed estate.

CAMFor operates in an easy-to-use Excel spreadsheet with a comprehensive User Manual. The AGO is developing sets of scenarios for Australian conditions which will serve as case studies in the use of the CAMFor model.


GORCAM

The model considers
  • changes of carbon (C) stored in vegetation, plant litter and soil,
  • reduction of C emissions because biofuels replace fossil fuels,
  • C storage in wood products,
  • reduction of C emissions because wood products replace energy-intensive materials like steel or concrete,
  • recycling or burning of waste-wood,
  • auxiliary fossil fuels used for production of biofuels and wood products.
The model makes use of approximately 200 input parameters. For each scenario a new set of input parameters can be defined. They describe the management regime (harvest cycle, growth rate etc.), the land use before the project, and the way in which the biomass is used for carbon mitigation. Various biomass growth functions are availabe (including Richards function, possibility of precommercial thinning, and selective logging). The soil and litter carbon uptake or release can either be prescribed with exogenous assumptions or a dynamic calculation scheme can be used.

The model can be used to assess the future carbon balance for scenarios involving
  • a forest stand,
  • a forest plantation system (normal forests), and
  • a forest with a given age-class distribution (to deal with natural disturbances).
The model output is presented in diagrams with cumulative carbon sequestration in various carbon pools over time. The model also allows to view the individual carbon fluxes. In addition to the regular model output, another mode is available where future carbon fluxes are discounted to give a net present value. The higher the discount rate and the longer the time horizon, the more the results will differ from the basic output.

GORCAM is implemented in MS Excel 5.0, and makes use of Visual Basic Macro Programming. Each scenario can be saved as an Excel file, that still carries with it all the model features, including macros, diagrams and equations. GORCAM allows the performance of sensitivity analyses, whereby the impact on any model output of varying an input parameter can be assessed. In combination with Excel-compatible risk analysis tools such as Crystal Ball or @Risk, Monte Carlo Analyses can be carried out to determine the uncertainty of the model results. Probability distributions can be defined or chosen for all input parameters, and the model derives the probability distribution for any model output, for example, the carbon sequestration of a given project after 20 years.


CBM-CFS

The models were developed to estimate and assess past and future carbon exchange between the Canadian forest sector and the atmosphere, and have been applied to forest areas as large as the whole of Canada and as small as a forest management unit. The ecosystem model was designed to use forest inventory data, existing soil profile data and historical (or projected) data on stand-replacing disturbances (fire, insect and harvesting). It is a landscape level model which represents the carbon dynamics associated with stand growth and dead organic matter accumulation over time. Growth curves, derived from forest inventory data, describe the accumulation of biomass carbon in vegetation (above and below ground) in each forest ecosystem type. The model also represents the population dynamics of the stands, based on changes in age-class distribution with disturbances over time and the effect of disturbances on carbon stocks in vegetation, forest floor and soil dead organic matter. Using forest inventory, climatic and disturbance data, the model estimates the storage and transfer of carbon between the atmosphere, standing biomass, soil and forest product carbon pools.

Improvements are being made to enhance the spatial resolution, and to investigate potential effects of climate change on the carbon budget of Canadian forests. With this modelling framework, the carbon stocks in Canadian forests and forest sector pools have been estimated together with historical changes in these stocks over the past century. The framework has also been used for scenario analyses to examine the potential changes in carbon stocks under different Kyoto accounting rules, different forest sector management strategies and under different climate scenarios.

References:

Apps MJ, Kurz WA, Beukema SJ, and Bhatti JS, 1999. Carbon budget of the Canadian forest product sector. Environmental Science and Policy 2, 25-41

Kurz WA and Apps MJ, 1999. A 70-year retrospective analysis of carbon fluxes in the Canadian forest sector. Ecological Applications 9(2): 526-547

Kurz WA, Apps MJ, Webb T, and MacNamee P, 1992. The Carbon Budget of the Canadian Forest Sector: Phase 1. ENFOR Information Report NOR-X-326, Forestry Canada Northwest Region, Edmonton, Alberta, 93 pg.



CO2FIX

Compared to the previous version of CO2FIX which was documented in Mohren and Klein Goldewijk (1990b), the present version
  • is a user friendly windows-based version.
  • is more precise in the allocation of harvested wood from thinnings and final fellings to wood product groups;
  • has an option to choose for recycling;
  • can directly sum the output of one forest type to larger areas;
  • directly presents some of the output in a graph.
The current version is under further development in an EU funded project, "Carbon sequestration in afforestation and sustainable forest management: presentation of a general evaluation tool and generic case studies, CASFOR".


REFUGE2

The original model has been used in the estimation of warming impacts of forestation projects or impacts of drainage for forestry. The model uses pulse response functions for the description of the removal of carbon or other greenhouse gases from the atmosphere. Avoided impacts, e.g. CH4 emissions from peatlands can be estimated and compared with possibly increased impacts of CO2 emissions. Simple compartment model structures can also be used for the description of carbon flows, especially accumulation in sinks can be estimated by using compartment structures.


ERGO

To achieve this ERGO needed to meet three important criteria, specifically the methods of energy and carbon budget estimation needed to be:
  1. general: the model can be applied without restriction to the study of widely differing types of bioenergy production system, both annual and perennial, as well as woody and non-woody.
  2. consistent: although the model is designed to be flexible, offering alternative methods of data input and calculation, at the same time the model imposes an essential discipline and structure on budget estimation, and ensures the use of common data sets where appropriate.
  3. transparent: assumptions and calculations are described in detail in the input and output files of the model. Gaps in understanding or limitations in data can be readily identified.
ERGO's role in providing fundamental calculations of energy and emissions budgets of bioenergy systems may be viewed as underpinning GORCAM's policy-level projections of carbon sequestration potential and greenhouse gas balance impacts. Currently the estimation of greenhouse gas balances in ERGO is limited to the carbon balance, but extension of the model to represent other gases is straightforward.


UK forest carbon models

An overview of United Kingdom forest carbon models - as presented at the Task 25 Modelling Workshop: Bioenergy, Greenhouse Gases and Carbon Sequestration, Zagreb, Croatia, 22-26 May, 2000.


GEMIS

Further data are stored for "meta" information: comments and description, references, data quality indicators, location and statistical group.

GEMIS determines full life-cycle impacts of energy, transport, and material technologies. In addition to the totals, GEMIS also gives the individual contributions of all processes to a calculated result (breakdown ), and can determine results for selected system boundaries (e.g. a special location, in- or exclusion of material acquisition, crediting).

GEMIS evaluates deviations from multiple objectives (trade-offs), e.g., costs vs. emissions, or emissions vs. land use. It further calculates CO2 and SO2 equivalents, and the total resource use (cumulative energy and material demands). Because of the modular approach of the database ("unit" processes), the sensitivity of any result can be determined quickly by copying original data, and adjusting key parameters - within seconds, GEMIS then calculates the new results which can be compared immediately with the original data.