Estimating baseline carbon emissions for the Eastern Panama Canal watershed

To participate in the potential market for carbon credits based on changes in the use and management of the land, one needs to identify opportunities and implement land-use based emissions reductions or sequestration projects. A key requirement of land-based carbon (C) projects is that any activity developed for generating C benefits must be additional to business-as-usual. A rule-based model was developed and used that estimates changes in land-use and subsequent carbon emissions over the next twenty years using the Eastern Panama Canal Watershed (EPCW) as a case study. These projections of changes in C stocks serve as a baseline to identify where opportunities exist for implementing projects to generate potential C credits and to position Panama to be able to participate in the emerging C market by developing a baseline under scenarios of business-as-usual and new-road development. The projections show that the highest percent change in land use for the new-road scenario compared to the business-as-usual scenario is for urban areas, and the greatest cause of C emission is from deforestation. Thus, the most effective way to reduce C emissions to the atmosphere in the EPCW is by reducing deforestation. In addition to affecting C emissions, reducing deforestation would also protect the soil and water resources of the EPCW. Yet, under the current framework of the Clean Development Mechanism (CDM), only credits arising from reforestation are allowed, which after 20 years of plantation establishment are not enough to offset the C emissions from the ongoing, albeit small, rate of deforestation in the EPCW. The study demonstrates the value of spatial regional projections of changes in land cover and C stocks: The approach helps a country identify its potential greenhouse gas (GHG) emission liabilities into the future and provides opportunity for the country to plan alternative development pathways. It could be used by potential project developers to identify which types of projects will generate the largest C benefits and provide the needed baseline against which a project is then evaluated. Spatial baselines, such as those presented here, can be used by governments to help identify development goals. The development of such a baseline, and its expansion to other vulnerable areas, well positions Panama to respond to the future market demand for C offsets. It is useful to compare the projected change in land cover under the business-as-usual scenario to the goals set by Law 21 for the year 2020. Suggested next steps for analysis includeusing the modeling approach to exploreland-use, C dynamics and management ofsecondary forests and plantations, soilC gains or losses, sources ofvariability in the land use and Cstock projections, and other ecologicalimplications and feedbacks resulting fromprojected changes in land cover.     

Carbon emissions from land-use change: an analysis of causal factors in Chiapas, Mexico

This study examines the correlation between deforestation, carbon dioxide emissions and potential causal factors of land-use change within an area of 2.7 million ha in Chiapas, southern Mexico between 1975 and 1996. Digitized land-use maps and interpreted satellite images were used to quantify land-use changes. Geo-referenced databases of population and digitized maps of roads and topography were used to determine which factors could be used to explain observed changes in land-use. The study analyzed the relationship between carbon emissions during this period and two types of possible causal factors: “predisposing” factors that determine the susceptibility of a particular area of forest to change (slope, distance to agriculture and roads, land tenure) and “driving” factors representing the pressures for change (population density, poverty). The correlated factors were combined in risk matrices, which show the proportion of vulnerable carbon stocks lost in areas with defined social, economic and environmental characteristics. Such matrices could be used to predict future deforestation rates and provide a verifiable evidence-base for defining baseline carbon emissions for forest conservation projects. Based on the results of the analysis, two matrices were constructed, using population density as the single most important driving factor and distance from roads and distance from agriculture as the two alternatives for the predisposing factors of deforestation.     

Application of the ‘Climafor’ Approach to Estimate Baseline Carbon Emissions of a Forest Conservation Project in the Selva Lacandona,Chiapas, Mexico

We present a methodology for testing and applying a regional baseline for carbon (C) emissions from land-use change, using a spatial modelling approach (hereafter called the Climafor approach). The methodology is based on an analysis of causal factors of previous land-use change (Castillo et al. 2005). Carbon risk matrices constructed from the spatial correlation analysis between observed deforestation and driving factors (Castillo et al. 2005), are used to estimate future carbonemissions within acceptable limits for a forest conservation project. The performance of two risk matrices were tested by estimating carbon emissions between 1975 and 1996 from randomly selected sample plots of sizes varying from 1,600 to 10,000 ha and comparing the results of the observed emissions from these sample plots with the model estimations. Expected emissions from continued land-use change was estimated for the community applying the risk matrices to the current land cover. The methodology provides an objective means of constructing baseline scenarios including confidence intervals, using the sum of variances of the various data sources, such as measured carbon densities, classification errors, errors in the risk matrices, and differences between the model prediction and observed emissions of sample plots due to sample size. The procedures applied in this study also give an indication of the impact of the variance in the various data sources on the size of the confidence intervals, which allows project developers to decide what data sources are essential to improve his baseline. The modelling approach to estimate the deforestation pattern is based on readily available cartographic and census data, whereas data on carbon densities are required to assess the potential for forest conservation projects to offset carbon emissions.     

Setting greenhouse gas emission targets under baseline uncertainty: the Bush Climate Change Initiative

There is substantial uncertainty regarding baseline greenhouse gas (GHG) emissions forecasts—i.e., how GHG emissions will grow over time in the absence of policy intervention. Thus baseline uncertainty should be a key consideration in setting GHG emissions targets as a mitigation strategy to respond to global climate change. At a minimum, the emissions target must be less than the baseline level to induce changing behavior and new investment. Despite this fundamental policy criterion, baseline considerations have played only a minor role in target setting under international climate policy. Baseline uncertainty applies to both absolute and intensity based emissions targets. It is demonstrated that one advantage of intensity targets is reduced uncertainty in the projected baseline, however there will always be some residual uncertainty in model projections. To illustrate the importance of considering baseline uncertainty in GHG target setting, the Bush Climate Change Initiative is analyzed against its projected baseline as a case study of a modest intensity target. Based on comparison with historical data, the range of projections by major energy-economic models, past discrepancies in the accuracy of model projections and the added complexity of sector-specific drivers for non-CO₂ GHGs, it is shown that the Bush Initiative cannot be guaranteed or even expected to deliver actual reductions against an uncertain baseline. This finding emphasizes the importance of setting a target that accounts for baseline uncertainty to achieve genuine mitigation of GHG emissions.

A participatory approach to the establishment of a baseline scenario for a reforestation Clean Development Mechanism project

This paper is part of a two-year study to investigate the feasibility of initiating a Clean Development Mechanism (CDM) project in an indigenous community of Eastern Panamá, Ipetí-Emberá. We use participatory mapping and matrices as well as household surveys to develop a land-use/land-cover baseline scenario and examine the role of local participation in assessing land-use change. In Ipetí, land-use change has not occurred in a linear way over the last decades, and our data unveils socio-economic factors as potential key drivers of change. The concordance that we observed between geographic information and individual and collective perceptions of land-use change substantiates the possibility of using local knowledge in the establishment of baseline data for CDM projects. Our calculations suggest that the total carbon (C) stocks in the Tierra Colectiva (TC) of Ipetí-Emberá in 2004 represents a 47% reduction from the estimated C stock at the onset of settlement in the early 1970’s. Results from the participatory assessments predict that, in 2024 and in absence of a CDM project, the C stocks will decline from 301,859 t C in 2004 to 155,730 t C, which constitutes a reduction of 52%. The scenario with CDM estimates C stocks of 305,853 t C for 2024, a value slightly superior to the 2004 value. In the TC there is ground to believe that cattle ranching is likely to become an ever more important activity as the population is young and growing and cannot easily move elsewhere. Forests tend to be cleared for cultivation while pastures are established on short fallows. Our baseline scenario underlines the potential for a CDM project to make a significant difference in the future C stocks of this landscape.     

Development of regional climate mitigation baseline for a dominant agro-ecological zone of Karnataka,India

Setting a baseline for carbon stock changes in forest and land use sector mitigation projects is an essential step for assessing additionality of the project. There are two approaches for setting baselines namely, project-specific and regional baseline. This paper presents the methodology adopted for estimating the land available for mitigation, for developing a regional baseline, transaction cost involved and a comparison of project-specific and regional baseline. The study showed that it is possible to estimate the potential land and its suitability for afforestation and reforestation mitigation projects, using existing maps and data, in the dry zone of Karnataka, southern India. The study adopted a three-step approach for developing a regional baseline, namely: (i) identification of likely baseline options for land use, (ii) estimation of baseline rates of land-use change, and (iii) quantification of baseline carbon profile over time. The analysis showed that carbon stock estimates made for wastelands and fallow lands for project-specific as well as the regional baseline are comparable. The ratio of wasteland Carbon stocks of a project to regional baseline is 1.02, and that of fallow lands in the project to regional baseline is 0.97. The cost of conducting field studies for determination of regional baseline is about a quarter of the cost of developing a project-specific baseline on a per hectare basis. The study has shown the reliability, feasibility and cost-effectiveness of adopting regional baseline for forestry sector mitigation projects.

Drivers of deforestation and REDD+ benefit-sharing: A meta-analysis of the (missing) link

REDD+ (reducing emissions from deforestation and forest degradation and related forest activities) is a climate change mitigation mechanism currently being negotiated under the United Nations Framework Convention on Climate Change (UNFCCC). It calls for developed countries to financially support developing countries for their actions to reduce forest-sector carbon emissions. In this paper, we undertake a meta-analysis of the links, if any, between multiple and diverse drivers of deforestation operating at different levels and the benefits accruing from and being shared through REDD+ projects. We do so by assessing the nature of this link in (a) scholarly analysis, through an in-depth analysis of the posited relationship between drivers and REDD+ benefit-sharing, as examined in the peer-reviewed literature; and (b) in policy practice, through analysing how this link is being conceptualised and operationalised, if at all, in REDD+ project design documents. Our meta-analysis suggests that while some local, direct drivers and a few regional indirect drivers of deforestation and forest degradation are being targeted by specific REDD+ interventions and associated benefit-sharing mechanisms at the project-level, most national and international indirect drivers are not. We conclude that the growing academic analyses of REDD+ projects do not (as yet) advance viable theories of change, i.e. there is currently little focus on how REDD+ benefits could play a transformative role in catalysing action on drivers.     

Land use as a mitigation strategy for the water-quality impacts of global warming: a scenario analysis on two watersheds in the Ohio River Basin

This study uses an integrative approach to study the water-quality impacts of future global climate and land-use changes. In this study, changing land-use types was used as a mitigation strategy to reduce the adverse impacts of global climate change on water resources. The climate scenarios were based on projections made by the Intergovernmental Panel on Climate Change (IPCC) and the United Kingdom Hadley Centre's climate model (HadCM2). The Thornthwaite water-balance model was coupled with a land-use model (L-THIA) to investigate the hydrologic effects of future climate and land-use changes in the Ohio River Basin. The land-use model is based on the Soil Conservation Service's curve-number method. It uses the curve number, an index of land use and soil type, to calculate runoff volume and depth. The ArcView programming language, Avenue, was used to integrate the two models into a geographic information system (GIS). An output of the water-balance model, daily precipitation values adjusted for potential evapotranspiration, served as one of the inputs into the land-use model. Two watersheds were used in the present study: one containing the city of Cincinnati on the main stem of the Ohio River, and one containing the city of Columbus on a tributary of the Ohio River. These cities represent two major metropolitan areas in the Ohio River Basin with different land uses experiencing different rates of population growth. The projected hypothetical land-use changes were based on linear extrapolations of current population data. Results of the analyses indicate that conversion from agricultural land use to low-density residential land use may decrease the amount of surface runoff. The land-use practices which generate the least amount of runoff are forest, low-density residential, and agriculture; whereas high-density residential and commercial land-use types produce the highest runoff. The hydrologic soil type present was also an important factor in determining the amount of runoff and non-point-source pollution. A runoff-depth matrix and total nitrogen matrix were created for Cincinnati and Columbus to describe possible land-use mitigation measures in response to global climate change. The differences in Cincinnati and Columbus were due to differences in geographic location, air temperature, and total runoff. The results of this study may be useful to planners and policy makers for defining the possible impacts of future global climate and land-use changes on water resources.     

Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

The main objective of this work is to identify and evaluate the potential impacts produced by climate and land-use changes in six European test-bed basins (Llobregat, Guadalhorce, Gardon d’Anduze, Linth, Verzasca and Sambuco). Data to build future scenarios that can modify the different basins’ flash flood and debris flow risk level has been analyzed in this paper. High resolution climate scenarios have been obtained from several European projects and/or National initiatives, depending on each case. Climatic variables have been widely analyzed, with a special focus on extreme precipitation. Typical generalized extreme value (GEV) distributions have been fitted to observed and projected rainfall data to assess impacts in the frequency distributions of extreme rainfall up to 2100. Regarding climate, the main conclusion is the importance of using data at the maximum spatial and temporal resolution applying downscaling methodologies adapted to basin scale (test-bed areas ranging from approx 200 to 5000 km²) and oriented to obtain extreme rainfall values.In general, high variability has been detected, obtaining very different results for the different models and scenarios. Data corrections may lead to better representations of present situations and, therefore, more reliable future projections, but currently some of them are not suitable for extreme precipitation assessment.Regarding land-use changes, a cellular automata-based model has been used (MOLAND) to simulate the 2000–2040 period taking the CORINE land-use dataset as input data. Llobregat, Guadalhorce and Gardon d’Anduze basins have been identified as potentially interesting for simulating urban land-use dynamics due to the existence of important urban areas within their limits. The assessment of the rural land-use changes has been carried out using the results from the EURURALIS project (2000–2030 period), available for all the basins.The results of this paper are framed in the FP7 project IMPRINTS that has the aim of analyzing impacts of future changes to provide guidelines for mitigation and adaptation measures and, in general, to improve the application of the EC Flood Risk Management Directive.     

Baseline Standardisation with Optimising Energy-System Models

Determining adequate baselinesis a major methodological problem whenquantifying emissions reductions achievedwith the project-based flexibilitymechanisms. Possible methodologies forbaseline setting may be classified intomulti-project and project-specificapproaches. While multi-project approachesprovide baselines for a series of typicalprojects within a certain geographicregion, a sector, or a load range,project-specific (orproject-by-project/single-project)approaches only cover one specific project.Project-by-project baseline approaches havebeen tested extensively within theActivities Implemented Jointly (AIJ) pilotphase; multi-project methodologies, on theother hand, have only rarely been applieddue to the (perceived) political andeconomic complexity of the issue, whichmakes the process of introducingstandardised baselines a very sensitivetask. In particular, there is a lack ofmulti-project baseline approaches takingadvantage of optimising computer modelswithin the electricity sector, even thoughother fields of research have made use ofsuch models quite successfully in the past.Experiences made in the PROBASE projectwith the calculation of standardised,aggregated multi-project baselines forJI/CDM projects using optimising energysystem models are illustrated in this paperfor South Africa, Russia, and Indonesia.Increased transparency and credibility ofstandardised approaches along withpotentially lower transaction costs areidentified as the main arguments for theiruse and further development. In addition,the text gives recommendations wheremodel-based baseline standardisation canpreferentially be applied.     

Future land-use change scenarios for the Black Sea catchment

Plausible future scenarios have been created for the Black Sea catchment, focussing on spatially explicit alternatives for land-use changes. Four qualitative storylines (HOT, ALONE, COOP and COOL) were first developed, based on interpretation of the respective global scenarios (A1, A2, B1 and B2) produced by the Intergovernmental Panel on Climate Change. Quantitative statistical downscaling techniques were then used to disaggregate the outputs of global scenarios at a regional level. The resulting land-use maps were spatially allocated at 1 km resolution in the Metronamica model, using a set of factors related to the identified drivers of change. The land-use change model was calibrated on historical trends of land-cover change (MODIS 2001 and 2008) translated into spatial allocation rules, and future land-use projections (IMAGE, 2001) were adopted. Suitability and constraint maps and population trends were used to regulate the modelling process. The calibrated model was validated by statistical procedures, visual evaluation and stakeholder involvement in order to ensure its plausibility and accuracy. This methodology bridged the gap between the global and regional scales. Four simulated future states were produced for the main land-use classes–forest, grassland, cropland and built-up areas, as well as scrublands, crops/natural vegetation and barren land–for 2025 and 2050. The results suggest that the features highlighted in these scenarios are guided by global trends, such as population rise and decreasing agriculture, but with different growth rates and a variety of spatial patterns, with regional variations resulting from local backgrounds and policy objectives. This study aims to provide future land-use data as a potential geographical tool to assist policy makers in addressing environmental emergencies such as water stress and pollution. In particular, the exploration of plausible futures can support future assessments to comply with the EU Water Framework Directive and Integrated Coastal Zone Management policies around the Black Sea.     

The Kyoto Protocol could make a difference for the optimal forest-based CO2 mitigation strategy: some results from GORCAM

The Kyoto Protocol was agreed on by more than 150 nations in December, 1997 and (if and when ratified) will establish international commitments to reduce emissions of greenhouse gases to the atmosphere. Under the Kyoto Protocol, some of the carbon emissions and removals within the land-use change and forestry sector can be counted toward a country's commitments for greenhouse gas emissions reductions. In addition to the impacts that land-use practices have on CO₂ emissions from fossil-fuel combustion, changes in the carbon stocks of forests (possibly including forest soils) caused by the direct human activities afforestation, reforestation and deforestation and taking place in the `first commitment period' (2008–2012), are to be accounted for under the Kyoto Protocol. Credits for carbon sinks in the biosphere are limited to projects initiated since 1990. A modified version of the model GORCAM has been used to assess eligible emission-reduction credits under the Kyoto regime and to illustrate how the optimal forest-based strategy for carbon dioxide mitigation might change under the provisions of the Kyoto Protocol. The Kyoto Protocol offers rewards for only some of the changes in carbon stocks that might occur and hence the forestry project that produces the most emission reduction credits under the Kyoto Protocol is not necessarily the same project that produces the greatest benefit for net emissions of carbon dioxide to the atmosphere. Supplementing the Protocol with appropriate definitions, interpretations and agreements could help to make sure that it does not provide incentive for activities that run counter to the objectives of the Framework Convention on Climate Change.     

Land use change and forestry climate project regional baselines: a review

Climate change programs have largely used the project-specific approach for estimating baseline emissions of climate mitigation projects. This approach is subjective, lacks transparency, can generate inconsistent baselines for similar projects, and is likely to have high transaction costs. The use of regional baselines, which partially addresses these issues, has been reported in the literature on forestry and agriculture projects, and in greenhouse gas (GHG) mitigation program guidance for them (e.g., WRI/WBCSD GHG Project Protocol, USDOE’s 1605(b) registry, UNFCCC’s Clean Development Mechanism). This paper provides an assessment of project-specific and regional baselines approaches for key baseline tasks, using project and program examples. The regional experience to date is then synthesized into generic steps that are referred to as Stratified Regional Baselines (SRB). Regional approaches generally, and SRB in particular explicitly acknowledge the heterogeneity of carbon density, land use change, and other key baseline driver variables across a landscape. SRB focuses on providing guidance on how to stratify lands into parcels with relatively homogeneous characteristics to estimate conservative baselines within a GHG assessment boundary, by applying systematic methods to determine the boundary and time period for input data.

Spatial and temporal analysis of vegetation change in agricultural landscapes: A case study of two brigalow (Acacia harpophylla) landscapes in Queensland, Australia

The majority of landscapes around the world have been modified or transformed by human activities to meet the needs of human societies. The loss of native vegetation for agricultural development affects the sustainability of growing proportion of the world's ecosystems. Factors such as land tenure, roads and agricultural intensification, together with biophysical properties, have been cited as drivers of deforestation. This paper combined analysis of the historical drivers of change with analysis of the trends of deforestation since 1945 in two brigalow landscapes (100,000 ha) in sub-tropical Australia. A selection of these drivers were then applied at a property-level (1000 ha) to test their influence on native vegetation retention. Regression trees were used to identify significant human drivers and biophysical properties, and then a generalised linear modelling approach was used to quantify the effect of these factors on the proportion of remnant native vegetation. Results showed that until the mid-20th century, government policies to intensify settlement did not result in increased agricultural production, but since this time, landscape change has been rapid, and has particularly affected ecosystems on fertile clay soils. Although socio-economic factors were critical in driving deforestation, after 60 years of agricultural intensification by far the most significant explanatory variable determining the proportion of native vegetation retained at a property scale was the suitability of the soil for agriculture. Property size was an important secondary influence. The results were not, by and large, consistent with other studies of landscape change and suggest that generalised principles explaining deforestation may be elusive. Solutions to the problem of over-clearance of native vegetation, therefore, need to be tailored to the specific regional situations encountered.     

Spatial and temporal land use and carbon stock changes in Uganda: implications for a future REDD strategy

Using a map overlay procedure in a Geographical Information System environment, we quantify and map major land use and land cover (LULC) change patterns in Uganda period 1990–2005 and determine whether the transitions were random or systematic. The analysis reveals that the most dominant systematic land use change processes were deforestation (woodland to subsistence farmland—3.32%); forest degradation (woodland to bushland (4.01%) and grassland (4.08%) and bush/grassland conversion to cropland (5.5%) all resulting in a net reduction in forests (6.1%). Applying an inductive approach based on logistic regression and trend analyses of observed changes we analyzed key drivers of LULC change. Significant predictors of forest land use change included protection status, market access, poverty, slope, soil quality and presence/absence of a stream network. Market access, poverty and population all decreased the log odds of retaining forests. In addition, poverty also increased the likelihood of degradation. An increase in slope decreased the likelihood of deforestation. Using the stock change and gain/loss approaches we estimated the change in forest carbon stocks and emissions from deforestation and forest degradation. Results indicate a negligible increase in forest carbon stocks (3,260 t C yr-1) in the period 1990–2005 when compared to the emissions due to deforestation and forest degradation (2.67 million t C yr-1). In light of the dominant forest land use change patterns, the drivers and change in carbon stocks, we discuss options which could be pursued to implement a future national REDD plus strategy which considers livelihood, biodiversity and climate change mitigation objectives.     

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.     

Sensitivity of amounts and distribution of tropical forest carbon credits depending on baseline rules

One of the largest sources of global greenhouse gas emissions can be addressed through conservation of tropical forests by channeling funds to developing countries at a cost-savings for developed countries. However, questions remain to be resolved in negotiating a system for including reduced emissions from deforestation and forest degradation (REDD) in a post-Kyoto climate treaty. The approach to determine national baselines, or reference levels, for quantifying REDD has emerged as central to negotiations over a REDD mechanism in a post-Kyoto policy framework. The baseline approach is critical to the success of a REDD mechanism because it affects the quantity, credibility, and equity of credits generated from efforts to reduce forest carbon emissions. We compared outcomes of seven proposed baseline approaches as a function of country circumstances, using a retrospective analysis of FAO-FRA data on forest carbon emissions from deforestation. Depending upon the baseline approach used, the total credited emissions avoided ranged over two orders of magnitude for the same quantity of actual emissions reductions. There was also a wide range in the relative distribution of credits generated among the five country types we identified. Outcomes were especially variable for countries with high remaining forest and low rates of deforestation (HFLD). We suggest that the most credible approaches measure emissions avoided with respect to a business-as-usual baseline scenario linked to historic emissions data, and allow limited adjustments based on forest carbon stocks.     

Potential carbon sequestration in China’s forests

Forests are believed to be a major sink for atmospheric carbon dioxide. There are 158.94 million hectares (Mha) of forests in China, accounting for 16.5% of its land area. These extensive forests may play a vital role in the global carbon (C) cycle as well as making a large contribution to the country’s economic and environmental well-being. Currently there is a trend towards increased development in the forests. Hence, accounting for the role and potential of the forests in the global carbon budget is very important.In this paper, we attempt to estimate the carbon emissions and sequestration by Chinese forests in 1990 and make projections for the following 60 years based on three scenarios, i.e. “baseline”, “trend” and “planning”. A computer model F-CARBON 1.0, which takes into account the different biomass density and growth rates for the forests in different age classes, the life time for biomass oxidation and decomposition, and the change in soil carbon between harvesting and reforestation, was developed by the authors and used to make the calculations and projections. Climate change is not modelled in this exercise.We calculate that forests in China annually accumulate 118.1 Mt C in growth of trees and 18.4 Mt in forest soils, and release 38.9 Mt, resulting in a net sequestration of 97.6 Mt C, corresponding to 16.8% of the national CO₂ emissions in 1990. From 1990 to 2050, soil carbon accumulation was projected to increase slightly while carbon emissions increases by 73, 77 and 84%, and net carbon sequestration increases by −21, 52 and 90% for baseline, trend and planning scenarios, respectively. Carbon sequestration by China’s forests under the planning scenario in 2000, 2010, 2030 and 2050 is approximately 20, 48, 111 and 142% higher than projected by the baseline scenario, and 8, 18, 34 and 26% higher than by the trend scenario, respectively. Over 9 Gt C is projected to accumulate in China’s forests from 1990 to 2050 under the planning scenario, and this is 73 and 23% larger than projected for the baseline and trend scenarios, respectively. During the period 2008–2012, Chinese forests are likely to have a net uptake of 667, 565 and 452 Mt C, respectively, for the planning, trend and baseline scenarios. We conclude that China’s forests have a large potential for carbon sequestration through forest development. Sensitivity analysis showed that the biggest uncertainty in the projection by the F-CARBON model came from the release coefficient of soil carbon between periods after harvesting and before reforestation.     

Impact of climate change at species level: a case study of teak in India

In this study, we model the long-term effect of climate change on commercially important teak (Tectona grandis) and its productivity in India. This modelling assessment is based on climate projections of the regional climate model of the Hadley Center (HadRM3) and the dynamic vegetation model, IBIS. According to the model projections, 30% of teak grids in India are vulnerable to climate change under both A2 and B2 SRES scenarios because the future climate may not be optimal for teak at these grids. However, the net primary productivity and biomass are expected to increase because of elevated levels of CO₂. Given these directions of likely impacts, it is crucial to further investigate the climate change impacts on teak and incorporate such findings into long-term teak plantation programs. This study also demonstrates the feasibility and limitations of assessing the impact of projected climate change at the species level in the tropics.     

Preserving Environmental Integrity in standardised baselines: The role of additionality and uncertainty

The European Union EU project PROBASE hasexplored a range of possible multi projectstandardised benchmarks as a way ofencouraging projects under Joint Implementation (JI) and the Clean Development Mechanism (CDM)by minimising transaction costs. The aim ofthis paper is to examine the environmentalintegrity of the use of standardisedbaselines and to explore the role ofadditionality. The environmental integritydepends on the uncertainty in emissionreductions, which was estimated bygenerating scenario baselines and comparingthese with the standardised baselines. Thishas allowed a comparison of selected multiproject baselines with the envelope ofuncertainty on the reductions. The projectsincluded a range of electricity supply,heat sector, cogeneration and methane(CH$_{4}$) projects in different countries. Theanalysis showed that the key uncertaintieswere in the technology fuel selection inthe baseline, the continued additionalityof the project emission reductions,uncertainties in some project emissions(e.g. spinning reserve emissions for wind)and data uncertainties. The effect on theestimation of reductions was in the range±12% to ±46% for the electricityprojects and from ±19% to ±57%for the heat and Combined Heat and Power CHP sector projects.Comparison with the envelope of uncertaintyfor the range of projects showed that multiproject electricity sector baselines whichhave been weighted or use high technologyperformance benchmarks (e.g. Organization for Economic Cooperation and Development OECD)can provide conservative estimates buttheir general nature can lead to variationsbetween countries. We would recommend thatthe country-specific context must be takeninto account so that standardised baselinesfor the electricity sector are generated onthe basis of country specificcharacteristics, the project type, andwhether it provides new or existing demand.The conservative scenario produced shouldthen be weighted. Whereas weightings havebeen applied to account for uncertaintiesor to bias towards renewables, we havesuggested a weighting factor of 25% on theelectricity baseline for large projectsbased on an analysis of the effect ofnon-additionality on emission reductionuncertainty. For heat projects, theappropriate benchmark is a technology/fuelbenchmark which is deemed relevant for theheat sector in that (part of the) country.Again we suggest that a weighted sectorbaseline is required to take account of theuncertainties. These recommendations applyto large projects only for a 10-yearcrediting lifetime.