An introduction to the monitoring of forestry carbon sequestration projects

Transcription

1 An introduction to the monitoring of forestry carbon sequestration projects By: Igino M. Emmer PhD, Face Foundation Contents -Introduction -Basic principles of carbon monitoring -References Introduction This is an introduction to carbon monitoring to make you acquainted with general issues regarding this subject, based on existing material and my personal experience. The information provided is by no means exhaustive, but references below allow you to find relevant literature for further reading. This introduction assumes you have basic knowledge of UNFCCC policies and climate change terminology. Forest carbon monitoring quantifies changes in carbon stocks in various carbon pools of the forest, which may differ considerably in measurability and spatial and temporal variability. It is therefore a field for experts. Required expertise is in many cases available locally or regionally. Effective communication with and supervision over monitoring experts is essential for the success of a monitoring campaign. This introduction is meant to serve as a first step to help, for example, project developers and intermediaries in performing their tasks. Why carbon monitoring? Carbon sequestration projects can be designed for the CDM, but also for a voluntary market. Whereas the market for CDM or CDM-precursor projects is relatively new (with for example World Bank s PCF, BioCarbonFund and Netherlands CERUPT as early players), the voluntary market already exists for more than a decade (Face Foundation, TNC s Noel Kempff, Scolel Te). In both cases there is need for transparency in project implementation, and the achievements in terms of carbon offsets must be verified independently. The verification is usually based on the monitoring of project performance, with periodical measurements over its lifetime. Monitoring approaches for CDM and voluntary projects are essentially the same, and therefore this introduction may give guidance to both. At last -during CoP9 in December the modalities and procedures for afforestation and reforestation project activities under the CDM in the first commitment period of the Kyoto Protocol have been adopted [1]. Monitoring plans and execution are under strict scrutiny and quality control of the CDM Executive Board. A CDM project will have to obtain approval by the CDM Executive Board of the monitoring methodology, just as is the case with baseline methodologies. For reasons of credibility, voluntary projects will employ similar methodologies. There will be simpler rules, however, for small-scale

2 projects, which are expected to sequester less than 8,000 tonnes of CO 2 per year (ca ha maximum) and are developed and implemented by low-income communities or individuals in the host country. These rules will be discussed during the course of the year The CDM Executive Board requires the CDM project to include in the project design document a monitoring plan that provides for the collection and archiving of all relevant data necessary for estimating or measuring emissions and sinks in both the baseline and with-project scenario, and for assessing the nature and quality of the monitoring methodology and execution. It also must address remedial measures dealing with negative environmental and socio-economic impacts and possible changes in project boundaries. This introduction will focus on the technicalities of carbon monitoring, but it is important to realise that a good monitoring plan has a somewhat wider scope. Reference material There exists a vast body of literature on the monitoring of terrestrial ecosystems focussing on forest and biomass. For this introduction a limited set of background information is used, which is easily accessible, for example via the internet. Wherever text is not original the reference is given between brackets. At CoP8 in Marrakesh the Intergovernmental Panel on Climate Change was invited to elaborate methods to estimate, measure, monitor, and report changes in carbon stocks resulting from LULUCF activities under the Kyoto Protocol based on the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories and to prepare the IPCC Good Practice Guidance for LULUCF [2]. This document, which is still under review, presents the state-of-the-art in forest monitoring and outlines what good practice in this field is. Other reference material is from Winrock International, an early player in the development of carbon monitoring programmes, for example A guide to monitoring carbon storage in forestry and agroforestry projects (Winrock International 1997,[3]), and Guidelines for inventory and monitoring carbon offsets in forestry-based projects (Winrock International 1999, [4]). Basic principles of carbon monitoring First considerations for planning Greenhouse gasses involved Through photosynthesis, the carbon in carbon dioxide (CO 2 ) is converted into organic tissue of trees and plants. CO 2 is not the only greenhouse gas involved in emission and sequestration in forest and other terrestrial ecosystem. Due to changes in soil moisture and temperature as a result of forestation or deforestation, and possible fertiliser application, methane (CH 4 ) and nitrous oxide (N 2 O) may also become an important component in the greenhouse gas balance of the forest. This depends on site conditions, 2

3 which differ from place to place. Certain expertise is required to assess whether methane or nitrous oxide must be included in the monitoring scheme. For simplicity this introduction will focus on carbon alone. The standard unit for reporting greenhouse gas emissions and sinks is CO 2 e (CO 2 - equivalent). All greenhouse gasses can be converted into this unit based on their specific global warming potential. For example, the effect of CH 4 is 23 times stronger than that of CO 2. For N 2 O this is 296! Baseline versus with-project scenario In CDM AR projects the net carbon sequestration must be assessed by comparison of the with-project scenario against the baseline scenario. The carbon stock in the with-project scenario can be quantified by repeated measurement of the carbon contained in the various pools. Many times the baseline scenario will be counterfactual (seized to exist) once the project has been implemented, i.e. it cannot be recognised in the field anymore. In this case the monitoring of carbon stock changes is not possible and the project must rely on models for assessing the future changes in carbon stocks. Even if certain plots in the project area are excluded from project activities, these plots may in time be significantly influenced by the project, hence not being representative for the baseline anymore. Therefore, the monitoring of baseline carbon stocks should only be catered for if one is certain that the baseline scenario is really the reference case. Required frequency Monitoring takes up financial resources of the project and therefore the effort must be reduced to the minimum; CDM projects are not necessarily scientific research projects. For CDM AR projects an interval of 5 years is prescribed for project verification [1]. Therefore, there is little need for a higher frequency than once per 5 years. The monitoring should take place just before the verification to avoid outdated results. The sampling frequency can also be assessed from a statistical viewpoint. If stock changes are slow while spatial variation is considerable it may take a long time before statistically significant changes can be identified, unless effort is put in taking many samples. This is further explained below. Detectable changes in soil carbon usually take more than a decade. 3

4 Project design: CO 2 Uptake Over Time Short tons CO2 / acre Time (years) Possible variation in carbon stock in measured plots over the lifetime a a growing forest stand. Initial growth during the first 10 years is slow and changes may be difficult to detect. Later on this is much less of a problem. (Courtesy: Bernhard Schlamadinger, Joanneum Research, Austria, ESI (Environmental Synergy, Inc) and Winrock International.) Carbon content(unit) M easurem entyear A likely situation in soil carbon assessment: individual samples (dots) from a sampling area will give a rather large spread of carbon content values. A large number of samples is required to minimize the confidence interval for these measurements (dashes) for a statistically significant difference between two consecutive sampling campaigns. In any case, the monitoring design should be based on pre-defined precision and accuracy. Precision standards for CDM projects can be found in the IPCC guidelines. Fieldwork for carbon monitoring should be planned to take place in an as short as possible time period (weeks to months) particularly in case of fast-growing species. For subsequent samplings preferably the same season should be chosen and this season should have weather and terrain condition conducive to field work. The latter minimises the chance of obtaining poor quality results of the field work. 4

5 Availability of expertise For designing and executing a monitoring programme, specific expertise is required in the areas of sampling design and statistics, execution of field campaigns and data elaboration and analysis. This requires appropriate supervision and quality control, which in most cases ca be done by the project itself. Costs Monitoring of forest carbon may be labour intensive and time consuming, and therefore relatively expensive. It is worthwhile to optimise the methodology so as to obtain the maximum result from the least effort. The more information is available about the pools prior to measurement, from similar projects or from other literature sources, the better. Before significant resources are being allocated to a monitoring campaign, it might be even advisable to first perform a less extensive pilot sampling, which provides intelligence on the variability of carbon in the various pools. With this information available, the big job can usually be designed and executed much more efficiently, thus reducing overall costs. More on this under Data collection in the field. Particularly if the market price for a carbon credit (1 tonne of CO 2 e) is low, the monitoring approach must be fine-tuned to leave out expensive measurements that yield only small amounts of credits. Data requirement Ecosystem carbon pools involved Carbon makes up 50% of dry biomass or organic matter. The following carbon pools can be identified: -Above-ground biomass and necromass -Below-ground biomass -Soil carbon -Litter 5

6 (From the IPCC Good Practice Guidance for LULUCF [2].) In principle all carbon pools within the project boundary must be considered. Only if transparent and verifiable information is provided, pools that are shown not to be a source may be excluded from the monitoring [1, 2]. Whereas the measurement of above-ground biomass is fairly straightforward and simple, it is virtually impossible for below-ground biomass (roots). Therefore, most monitoring approaches depend on the availability of literature on the ratio between the two pools in similar ecosystems or plantations. Thus, above-ground biomass is measured, belowground biomass is estimated. This approach may be acceptable to the verifier or certifier of the project if a very conservative value is taken, underestimating below-ground biomass. Soil carbon and litter are likely to change significantly as a result of afforestation or reforestation. These pools should therefore not be overseen. However, in certain cases one may be able to demonstrate that the afforestation will only lead to an increase in soil carbon. If this increase will not be counted towards the carbon benefits of the project, there may be a case for not including soil carbon in the monitoring. For example, agricultural plots in the humid tropics or degraded land will accumulate soil carbon again once trees take over. Evidently, not including soil carbon will reduce the costs of monitoring, but introduces the risk of not being entirely transparent or credible. 6

7 Above-ground biomass The volume of wood can be calculated from a combination of stem diameter, height of the tree, and canopy geometry. These attributes of trees can be readily measured in the field. st 1 diameter nd 2 diameter two measurements For many tree species growing at various sites, equations for calculating above-ground biomass have been established. It is recommended to make use of regional biomass tables. An allometric biomass regression equation may have the following form [3]: B = a + b * D 2 * H where B: biomass (kg), D: stem diameter (cm) at breast height (); H: total height (m); a-b: regression parameters from the data, depending on tree species and site conditions. Other equations allow for the calculation of the wood volume. If the density of the wood is known, the biomass in kg can be deduced. The IPCC guidelines recommend to verify allometric equations by destructively sampling a limited number of trees of different size in the project [2]. Non-tree vegetation can be measured by harvesting techniques using sampling frames. This carbon pool is insignificant in old forests or tree stands, or dense and dark stands, but may be relevant to quantify in young open plantations. 7

8 Below-ground biomass The average below-ground to above-ground ratio for tropical, boreal and temperate forest listed in the IPCC guidelines is 0.26, varying little among latitudes (boreal-temperatetropical) or soil texture. According to the IPCC guidelines given the lack of standard methods and the time-consuming nature of monitoring below-ground biomass in forests, it is good practice to estimate below-ground biomass from either estimated aboveground biomass based on various equations or from locally derived data [2]. Soil carbon Soil carbon requires entirely different techniques. Remote sensing techniques exist but usually soil carbon is measured by destructive sampling and testing for organic matter or carbon. A general formula for calculating soil organic carbon is [2]: SOC = [SOC] * BulkDensity * Volume * (1-CoarsFragments) * 10 where SOC: soil carbon stock (Mg C/ha); [SOC]: concentration of soil carbon (g C/kg); BulkDensity (Mg/m 3 ); CoarseFragments: fraction in %. It is good practice to sample to a depth of at least 30 cm [2]. Tools for data collection Good monitoring depends on an adequate land classification scheme, an appropriate spatial and temporal resolution, a proper standard for precision and accuracy, a transparent methodology and measures to assure consistency and availability over time. All this can be greatly supported by selecting appropriate tools for data collection. Remote sensing Remote sensing is measuring from a distance, without the need for visiting the project area. Three categories are distinguished: -aerial photography -satellite imagery -radar imagery Although large land surfaces can be covered using remote sensing, the data obtained must always be calibrated and verified against the reality on the ground. The process of obtaining ground information to verify remotely sensed data is called ground truthing. This implies that even with remote sensing techniques plots must be established on the ground that are then measured with more or less conventional techniques. Remote sensing maps can be processes and used in geographical information systems. GIS has become an indispensable tool in storage of spatially explicit information (with reference to the field in coordinates), as well as their analysis. A GIS can also contain and process plot-based data obtained in ground-based surveys. 8

9 Ground-based surveys; sampling design Ground-based surveys require field visits for measuring selected attributes. The way these attributes are measured in terms of how many times and where is the sampling design. The sampling design must prevent any bias in measurements, allow for efficient execution of the work and allow for independent verification. There are four options for sampling design [3]: complete enumeration, simple random sampling, systematic sampling and stratified random sampling. A proper choice is based on required accuracy and precision, and costs. In carbon monitoring in most cases the latter two are preferred. It is wise nor necessary to measure all trees in the project. According to the IPCC guidelines [2] it is good practice to stratify the project area into sub-populations (strata) that form relatively homogeneous units, if the project is not homogeneous. Stratification decreases the costs because less effort is required due to less variance within each stratum. Evidently, stratification must be related to the variables that are measured. There is no gain in defining many strata. Quadruple plots which cater for the measurement of small trees inside one small circle and large trees inside 4 large circles. Measurements must be done within a pre-defined and constant area to relate results to carbon stocks on an area basis (e.g. tonnes C per hectare). This sample unit usually is a permanent sample plot. Advantages over non-permanent plots include the greater reliability of information on stock changes and the fact that the permanent plots can be revisited and thus independently verified. For this purpose the plot co-ordinates must be recorded, which today is done with GPS. 9

10 Plot layouts vary but a key rule is that they must allow for the efficient measurement of attributes that occur in different spatial scales. For example, for measuring numerous saplings in a regenerating forest a much smaller plot is necessary than for tall trees that are scattered over the area. If only one plot size is used the standard error of the mean for the large trees will be much larger than for the small trees and the precision standard for the large trees may not be met. The sample size or number of plots greatly determines the cost of the monitoring. Nevertheless, a higher precision requires a larger number of plots to be measured, increasing the effort. Therefore, the sample size must be optimised based on required precision and available recourses (or market price of carbon credits). Since it is likely that not all permanent plots can be recovered, it is advisable to add 10% to the minimum sample size. (Taken from [2].) 10

11 Regular grid with plot clusters as used in Face Foundation s carbon sequestration project in Mt. Elgon National Park, Uganda. Here stratification would only have been possible according to year of tree planting. Equipment Conventional techniques make use of simple equipment and supplies, such as measurement tape, compass, clinometer, paper and pencil. More sophisticated equipment includes laser, electronic calliper, electronic compass, GPS, and field computers. These are sometimes integrated into one system. An example of such a system is FieldMap. 11

12 Advantages of integrated electronic devices and computers are in all stages of executing monitoring campaigns: preparation of field forms, establishment of plots in the field, actual measurements in the field and mapping, elaboration of data and reporting. This, however, is all at a cost: the price of the package. In large-scale monitoring campaigns which will be repeated periodically these systems may however still provide cost savings, while at the same time great progress can be made in accuracy (no typing mistakes, no empty fields on forms; real-time check on outliers). Quality electronic equipment has shown to be tropics proof, even more so than human beings. Carbon calculations Carbon stocks The main purpose of carbon monitoring is to assess carbon stock changes in time, which can be translated into carbon credits that can be sold on the market. To this end the carbon stock is calculated as the mean of all the sample plots. To be able to assess the reliability of this value, confidence limits must be defined and the confidence interval calculated [3]: ConfidenceInterval = Mean ± (t * standard error of mean) where t: two-sided t value for a probability level of 0.05, available from statistical tables. Electronic spreadsheets and simple statistical packages can perform these calculations. Note that the statistical calculations for a carbon monitoring campaign with stratification are much more sophisticated than the above. 12

13 Sample size As outlined above, the sample size is an important parameter in the setup of a carbon monitoring programme. An insufficient number of samples renders the measurements unreliable while, reversely, with too many measurements the costs will be unnecessarily high. The sample size can be determined by performing a pilot sampling of a small number of plots. The statistics obtained allow, under certain assumptions, for the estimation of the sample size required for a certain precision level [3]. Time intervals A monitoring campaign must be setup in a way that with the available resources and the related sample size stock changes can be detected. With an established or expected variance in measurements in combination with a growth model, measurement intervals can be identified. Leakage, risks and uncertainties A carbon sink project must deal with greenhouse gas emissions not intentionally caused by its activities (leakage). For example, an afforestation scheme that involves the harvesting of trees at some stage will cause CO 2 emissions due to the use of sawing equipment and trucks, while harvest residues are left to rot. These emissions must be assessed in the project design document and subsequently monitored. There are many sources of uncertainties regarding project performance and monitoring results (e.g. model error, sampling error). A minimum basis for a simple quantitative estimate of uncertainty is provided by the confidence interval [2] from which for example a virtually risk-free part of the carbon sequestration can be derived. Projects should put effort in reducing uncertainties. Likewise in reducing risks, such as fire and illegal logging. Insurance companies have great expertise is assessing risk for determining insurance fees. The same is true for certifiers, who assess various risk categories for quantifying the amount of carbon credits that are not or less likely to be delivered. Monitoring key parameters, such as fire or logging occurrences in the project may lead to a significant enhancement of the amount of virtually risk-free credits at a later stage. References [1] Modalities and procedures for afforestation and reforestation project activities under the CDM in the first commitment period of the Kyoto Protocol, UNFCCC 2003, ( [2] IPCC Good Practice Guidance for LULUCF ( [3] A guide to monitoring carbon storage in forestry and agroforestry projects, Winrock International 1997, ( [4] Guidelines for inventory and monitoring carbon offsets in forestry-based projects. Winrock International 1999, ( 13