Supporting Information for Cookstoves illustrate the need for a comprehensive carbon market

Transcription

1 Supporting Information for Cookstoves illustrate the need for a comprehensive carbon market Luke Sanford & Jennifer Burney July 10, 2015 Contents S1 SI Text 2 S1.1 General offset information S1.2 Existing cookstove offset calculations S1.3 Offset calculation for modified (new) protocol S1.4 Summary of cookstove emissions studies included in analysis S1.5 Calculation of stove-class fuel use and emissions factor averages, standard deviations, and standard errors S1.6 Calculation of BC emissions factors from different measures of particulate matter.. 11 S1.7 Analysis of uncertainty due to GWP estimates S1.8 Using prediction intervals to observe variation within stove classes S2 SI Figures 13 1

2 S1 SI Text S1.1 General offset information A distinguishing characteristic of some carbon accounting standards ( carbon markets ) is that they sell Certified Emissions Reductions (CERs), which function as a part of mandatory carbon reduction systems, like cap and trade. The largest CER market in the world is the Clean Development Mechanism (CDM) established under the Kyoto protocol; this mechanism facilitates offset trading under the EU cap and trade program.[1, 2, 3] In addition, there are carbon accounting standards that operate outside of mandatory emissions reduction programs; they sell Voluntary Emissions Reductions (VERs) to those who want to decrease their carbon footprint for reasons other than regulation. CERs trade at a single price within a carbon market, with spot price data readily available through (for example) the EU cap and trade data portal. Conversely, VERs do not have a single price; they trade at a price that is determined by the effects of any specific project. As of late 2014, Gold Standard (considered the highest quality and thus most expensive) VERs sold at approximately $7 per ton of CO 2. Currently four carbon markets include protocols for improved cookstove projects: the Clean Development Mechanism (CDM)[4], the Verified Carbon Standard (VCS)[5], the American Carbon Registry (ACR)[6] and the Gold Standard (GS)[7]. The CDM offers CERs, while the VCS and ACR offer only VERs. The GS offers both CER and VER certifications. The CDM has two cookstove methodologies: AMS II.G applies to projects that seek to improve efficiency of non-renewable biomass-burning stoves. AMS I.E applies to projects that seek to implement a renewable energy technology (the AMS I.E is not considered in this analysis, but we mention it here because inclusion of PICs in a comprehensive carbon market would have significant impacts on projects under the AMS I.E protocol as well). The Gold Standard has its own methodology for improved efficiency projects, and also offers offsets under the AMS II.G and AMS I.E protocols if several additional standards are met. The ACRs methodology is similar to AMS I.E in that it uses the same formula, but with different default emissions factor values and monitoring methods. VCS uses AMS II.G and I.E exactly.[8] About two thirds of emissions reductions from currently registered projects are projected to occur in Africa, one third in Asia, and less than 5% in South America. These offsets total around 10 million tons of CO 2 over the next 10 years, which is the first accounting period.[8] For comparison, this is equivalent to about 1% of all voluntary carbon market trading per year.[3] Interestingly, most CDM projects seek and obtain GS certification in addition to CER status, which further emphasizes the importance of voluntary markets in the landscape of cookstove offset-based financing. With near-zero pricing of carbon offsets in the CDM, it is likely, at least for the near future, that most projects will seek certification in at least one of the voluntary markets. Like all offset protocols, cookstove emission protocols have some similarities in structure across markets, and include the following four components a project scope, an emission reduction calculation, a statement of additionality, and assessment of leakage. 2

3 Scope defines project size, including its geographical boundaries, which users it targets, what fuel types and stove types it applies to, and other requirements for the project to count under the protocol. An example is a project that targets 15,000 households in Tanzania currently using traditional 3-rock stoves, relying on 30% non-renewable acacia hardwood biomass. The other three protocol components come from a comparison between a baseline (or counterfactual) scenario, like the one described above, and project scenarios. Project scenarios might include distributing improved cookstoves to the 15,000 Tanzanian households, incentivizing households to transition to a greater fraction of renewable fuels, or some combination of the two. The emission reduction calculation is the formula by which any protocol determines the size of the offset generated by the project. Current methodologies are based on the net change in fuel consumption for a stove over a given period of time, calculating the CO2 emissions footprint associated with the combustion of that fuel, and then scaling that number by number of stoves and number of time periods. Following the Tanzania example, the net offset would be a product of the average size of the shift to renewable fuels in a household and the efficiency gained by the new technology, summed over all households for the specified length of time. Beyond quantifying the scope and potential carbon impact of a project, any offset must meet the requirement of additionality. That is, the implementer must demonstrate that the baseline scenario is distinct from the project scenario, or, put differently, that the reductions in emissions would not have happened on their own, absent any project. This requirement is both nebulous and difficult to meet convincingly; weak definitions of additionality that is, projects or reductions that likely would have happened with or without the use of carbon funding have been cited as a factor contributing to an offset glut and low carbon prices in the CDM. As an example, a cookstove project with weak additionality might be a project that received a health-related grant to introduce improved cookstoves to a village without charge that then applied for carbon offset funding for those stoves. Because the project would have happened with or without carbon funding, it does not meet the standards of additionality. The projects with weak additionality blamed for driving down the price of CO2 offsets in the CDM, were generally created by actors who wanted to be paid not to cut down large areas of forest or pollute excessively, where it was uncertain that they would have done so absent the carbon funding. Finally, leakage describes a situation where a carbon-reducing intervention might indirectly increase carbon emissions in a different area. For example, an improved cookstove project that decreases the use of firewood for cooking might result in an increase in the use of firewood for in-home heating, or the availability of fuel for brick kilns in the region, reducing the total carbon impact of the project. Methodologies generally assume a small amount of leakage ( 5%), but also have monitoring requirements to make sure that there is not additional leakage. 3

4 S1.2 Existing cookstove offset calculations The CDM, ACR, and VCS all use Equation 3 to calculate the size of the carbon offset of a project: ER y,i = where: y a=1 B y,savings,i,a N y,i,a µ y,i 365 fnrb y NCV biomass EF projected fossilfuel LE y (1) ER y,i is the reduction in CO 2 emissions in year y for stove type i B y,savings,i,a is the quantity of biomass saved relative to baseline in year y for stove type i of age a N y,i,a is the number of stoves of type i and age a operating in year y mu y,i is the number of days of operation of stove type i in year y fnrb y is the fraction of biomass saved by the project that can be established to be nonrenewable in year y NCV biomass is the net caloric value of non-renewable biomass that is substituted (default is TJ/tonne) EF projected fossilfuel is the emissions factor of the fuels expected to be substituted for the nonrenewable woody biomass. (This value or its derivative varies by standard and is discussed below.) LE y is the leakage emissions in year y, default value of 0.05 B y,savings,i,a This formula yields the net reduction in emissions (in tons of CO 2 ) after project intervention. That is, it is the sum total of emissions that would have been emitted but were not as a result of the project. This calculation rests on the mass of non-renewable biomass fuel saved, and the emissions factor associated with whatever fuel replaces it. The CDM assumes that non-renewable biomass is replaced by fossil fuels, and emissions factor is thus a weighted average of emissions factors from coal (50%), kerosene (25%) and propane (25%), a value of kg CO 2 kg 1 biomass. As has been noted elsewhere[9], this substitution calculation is not well justified anywhere in the protocol. The ACR uses an estimated emission factor for wood of kg CO 2 kg 1 biomass and assigns a separate emission factor for charcoal fuel: kg CO 2 kg 1 charcoal. Most important for this analysis, Equation 3 includes two key assumptions: (1) CO 2 is the only climate forcing agent generated by cookstoves, or, stated conversely, all biomass fuel is converted to CO 2 ; and (2) burning of renewable biomass (e.g., biomass generated on an annual basis, like crop residues) has a net-zero impact on climate. Again, this assumes that all fuel, including renewable biomass, is converted to CO 2 and that fuel sources are stable over time. As a result, the emission reduction can be 4

5 calculated purely from the net decrease in fuel used and the percent of the fuel savings that is renewable. where: The GS protocol makes one fewer assumption, and as a result is slightly more complex: ER y = x to y 0 to 1 y is the year of the crediting period x = y 1 N y P y U y (fnrb y EF CO2 + EF nonco2 ) (1 F b y ) (2) ER y is the CO 2 equivalent reduction in greenhouse gas emissions in year y N y is the number of project cookstoves of each age group operational in year y P y is the quantity of firewood saved in year y U y is the usage rate of cookstoves in year y, based on adoption rate and drop off rate revealed by usage surveys (fraction) fnrb y is the fraction of biomass, used in year y for baseline scenario, which can be established as non-renewable EF CO2 is the CO 2 emissions factor of the firewood that is substituted or reduced (default is tco2/tonne of wood) EF nonco2 is the non-co 2 emission factor of firewood that is substituted or reduced (default is tco 2 e/tonne of wood) F b y iis the usage of baseline stove (fraction) during the year y in the project scenario The quantity of biomass saved (P y ) can be estimated using: where: P y = B y (1 η b η py ) B y is the quantity of firewood consumed in baseline year y (tons per household) η b is the efficiency of the baseline stove (default value of 10%) η py is the efficiency of the project cookstove in year y, to be determined by historical data, survey of local usage, minimum service level, or KPT 5

6 The main difference in the GS protocol versus the CDM, VCS, and ACR protocols is that the latter consider only CO 2 emissions. In contrast, the GS protocol includes a term for two non-co2 greenhouse gas (GHG) emissions, namely nitrous oxide (N 2 O) and methane (CH 4 ). These are applied to the total biomass savings of the improved stove, not just non-renewable biomass. The GS protocol recognizes that these non-co 2 emissions result from combustion of both renewable and non-renewable biomass. While this represent improvement toward a more accurate assessment of cookstove climate impacts, the GS protocol still assumes: (1) that these three greenhouse gases are the only significant climate forcing agents present in cookstove emissions, and (2) that all types of stoves, including unimproved cookstoves, have the same emissions profile for the same quantity of wood burned. As a result, the GS protocol also calculates the emissions reduction of a cookstove project using only the change in fuel consumption and the proportion of renewable fuel. GS also uses set emissions factors for CO 2 (1.747 kg of CO 2 kg 1 of wood) and non-co 2 greenhouse gas forcing agents (0.455 kg of CO 2 e kg 1 of wood). The one advantage of both of these formulae is that they do not require emissions tests for stoves before a project is implemented; they only require a test that measures the fuel savings of the stove or a study measuring the total fuel savings of the project. The CDM, ACR, and VCS protocols accept any of the three accepted cookstove testing methods: the water boiling test (WBT), the controlled cooking test (CCT) and the kitchen performance test (KPT). The GS accepts only the KPT method. The WBT is the simplest of the three tests in that it measures the amount of fuel necessary to bring a certain quantity of water to a boil and then simmer for 45 minutes. It is relatively easy to perform, easier than other tests to control and is the best measure of thermal efficiency of stoves assuming that the same pot and fuel are used. As varying data from different tests confirm, it is still far from a perfect measure, even in controlled conditions. The CCT measures the fuel consumed in a variety of local cooking tasks. It is more difficult to perform, but gives a better idea of the actual fuel use of a certain stove type in a specific area. A downside of the CCT is that it is difficult to compare results across locations and customs. The KPT evaluates the usage of fuel over a set time period (usually one week) for a household performing normal cooking tasks. It is the most resource intensive test, but may yield the most representative fuel use results.[8] S1.3 Offset calculation for modified (new) protocol The new offset protocol takes into account emissions factors of black carbon, organic carbon, and carbon dioxide. Additionally, it uses emissions factors for CO 2, BC, OC, and CO that are specific to stove classes. With better testing, these values could be specific to individual stove models. ER y = where: x to y 0 to 1 N y,z P y U y,z (fnrb y EF CO2,z+EF GSnonCO2,z+EF BC,z +EF OC,z +EF CO,z ) (1 F b y ) (3) 6

7 y is the year of the crediting period x = y 1 z is the class or type of improved stove ER y,z is the CO 2 equivalent reduction in greenhouse gas emissions in year y for stove class z N y,z is the number of project cookstoves (of class z) of each age group operational in year y P y is the quantity of firewood saved in year y U y,z is the usage rate of cookstoves of class z in year y, based on adoption rate and drop off rate revealed by usage surveys (fraction) fnrb y is the fraction of biomass, used in year y for baseline scenario, which can be established as non-renewable EF CO2,z is the CO 2 emissions factor of the firewood that is substituted or reduced by using a stove of class z EF GSnonCO2,z is the Gold Standard estimated emission factor for N 2 O and CH 4 of firewood that is substituted or reduced (default is tco 2 e/tonne of wood) EF BC,z is the black carbon emission factor for firewood that is substituted or reduced by a stove of class z EF OC,z is the organic carbon emission factor for firewood that is substituted or reduced by a stove of class z EF CO,z is the carbon monoxide emission factor for firewood that is substituted or reduced by a stove of class z F b y iis the usage of baseline stove (fraction) during the year y in the project scenario The quantity of biomass saved (P y ) can be estimated using: where: P y = B y (1 η b η py ) B y is the quantity of firewood consumed in baseline year y (tons per household) η b is the efficiency of the baseline stove (default value of 10%) η py is the efficiency of the project cookstove in year y, to be determined by historical data, survey of local usage, minimum service level, or KPT 7

8 S1.4 Summary of cookstove emissions studies included in analysis See Table 1 in the main manuscript for a summary of these studies. The accompanying SI spreadsheet contains test information from all of the studies described here and the calculation of emissions factors described in Sections S1.5 and S1.6. Joshi et al 1989 [10] sought to test emissions from woody fuels against crop residues and dungcakes using a variety of stoves. They report total suspended particulates (TSP) concentrations and fuel use per test. We converted this into our standardized measure of pollutants per kg of fuel. They also report stove efficiency, which we convert to fuel used per task. They report one stove type (CP) for which no information is available, so we omitted that stove from our analysis. Furthermore, a second stove type (PA) was only used in tests that used dungcakes a fuel source. The Ballard-Tremeer et al 1996 study [11] examined efficiencies and emissions (including PICs) of stoves including a traditional open fire, an improved open fire, and metal and ceramic stoves (natural draft). We recorded their open fire as a traditional stove, and the three stoves as improved ND stoves (as they had statistically equivalent efficiencies). The authors reported TSPs per task, which we converted to TSP/kg. We did this by generating a fuel use per test number based on reported data for CO emissions per test and CO emissions per kg of fuel burned. We then used this number to generate emissions per kg of fuel used for the other pollutants. This conversion resulted in CO 2 emissions that fell well outside of the 95% CI of CO 2 emissions from other ND stoves. The other pollutants emitted were consistent with other tests. Smith et al 2000 [12] created a database of the complete emissions profile of common household combustion devices. They measured CO 2, CO, CH 4, TNMOC (non-methane organic compounds), N 2 O, SO 2, and TSP, but did not measure any optical properties of the particulate matter. Their study generally revealed that higher efficiency devices and fuels tend to produce fewer TSPs, which is consistent with our conclusion that current offsets are probably underestimated (based only on fuel savings, not on cleaner emissions profiles). We aggregate data for stoves of the same class (T, C, ND). This study showed that charcoal stoves consumed more fuel on a per task basis, a result that is not replicated in other studies. Venakataraman et al 2001 [13] tested emissions from cookstoves using a variety of fuel types, including wood, animal dung, and crop residues, finding that wood burns substantially cleaner than the other fuels. This study suggests that there are likely offsets that are at least as large to be gained from implementing improved cookstoves in areas where fuels other than wood are used (these fuels are considered renewable, so they do not even register on current protocols). We used emissions from the wood-burning stove tests, all of which were of the natural draft stove class, but included metal and ceramic stoves. We converted efficiency estimates to fuel used per task. 8

9 Roden and Bond 2006 [14] performed field tests on traditional stoves to determine emissions, with specific regard to OC and BC composition of the emissions. They found that in general, PM levels in the field were higher than experienced in the laboratory, and mapped emissions over the course of a cooking event. Their study suggests that many of the other laboratorybased tests are likely under-estimates of particulate emissions. Johnson 2008 [15] compared traditional and Patsari (ND) stoves in different settings to test whether lab results are a good measure of field performance. We averaged their results across their three different settings, and across stove classes. Their emissions results were originally reported in terms of grams of carbon emitted as CO, CO 2, and BC. We converted these to grams of pollutant per grams of fuel burned. MacCarty et al 2008 [16] examined the specific emissions of traditional, natural draft (rocket), forced draft, gasifier, and charcoal stoves, disaggregating PICs into BC and OC and presenting efficiency and GWP of stove use. Their results demonstrate that failing to account for BC as a climate forcing agent underestimates the size of the difference between emissions profiles of unimproved vs improved cookstoves, and also leads to a more accurate GWP profile of each stove than you would get by only measuring CO 2 emissions. Efficiency was calculated by assuming that the CO 2 output is constant across stoves, and reflects the level of fuel burned. This study is one of the few that provides estimates for BC emissions from different stove types, but it does not offer any estimate of uncertainty. Jetter and Kariher 2009 [17] tested a variety of stove types for efficiency and emissions for a variety of fuel types. They measure PM 2.5 emissions, but do not measure optical properties of the particulates. They adjusted PM emissions for fuel burned, using the EPA model, and calculated efficiency using the WBT. We combined their results for the two natural draft stoves that they tested. They reported fuel use per task. McCarty et al 2010 [18] examined the performance of 50 different stove types, including traditional, natural draft, natural draft (rocket), forced draft, gasifier, and charcoal stoves. They use the WBT to calculate CO and PM emissions, fuel used, and energy produced. We averaged results across stove class and calculated PM/kg of fuel. Jetter et al 2012 [19] examined efficiencies and emissions from a range of cookstoves and fuels including traditional stoves, forced draft stoves, rocket stoves, natural draft (non-rocket) stoves, gasifier stoves, and charcoal stoves. They tested these stoves under conditions including cold starts, hot starts, and simmering for both wet and dry fuel. We averaged across stove classes using dry fuel, and averaged cold starts and simmering emissions. We used the reported measure of overall thermal efficiency to calculate fuel use per task. Preble et al 2014 [20] compared emissions from the Berkeley-Darfur natural draft stove to emissions from a traditional cookstove. Fuel use was directly recorded. 9

10 There are a few notable studies that examined emissions from stoves of different classes but were not included in this study. In particular, Bond et al 2004 [21] examines the GWP from a variety of combustion sources and fuels. They inventory the existing studies of cookstove emissions, and report ranges of emissions from studies that measured PICs from cookstoves, disaggregated by traditional cookstoves, open fires, and improved cookstoves and reports point estimates and standard error terms for the aggregated results. The results are not sufficiently disaggregated to inform our own estimates in this analysis, but they do provide a useful benchmark. We find that Bond et al s point estimates for fuelwood emissions from traditional, charcoal, and improved stoves lie within the ranges of our estimated emissions for those stove classes. Grieshop et al 2011 present an analysis of mitigation options in residential biomass burning; this study was not included because it does not contain independent emissions measurements but rather uses those from other studies. Kar et al 2012 [22] examined BC profiles of different stove models and classes in Indian kitchens using a CCT, but they present concentration data (not emissions), and no species other than BC. S1.5 Calculation of stove-class fuel use and emissions factor averages, standard deviations, and standard errors Taking into account the number of tests for individual stoves, we then aggregated and averaged results by stove class (traditional or 3-rock stoves, natural draft or rocket stoves, forced draft stoves, gasifier, and charcoal stoves). While this blurs distinctions between individual stoves within a class, it does capture much of the technology differentiation in the improved cookstove landscape and helps provide generalized insight into the offset protocols. It should be noted that studies collect the same data in very different ways: as emissions per unit of energy output, emissions per kg of biomass, and molar ratios of carbon, to name a few. We calculated conversions to standardize the units in terms of g of emission per kg of biomass. Averages across models and within class were weighted by number of tests conducted by each study using: n i avg i i Average class = (4) N class where i is a given stove model in a study, n is the number of tests of that stove model conducted within the study, and N is the total number of tests of a given stove class across studies. Standard deviations were similarly weighted across studies: (n i 1) σ i 2 i σ class = (N class 2) Standard errors were then constructed based on standard deviations and the total number of tests in the sample: (5) SE class = σ class N (6) 10

11 S1.6 Calculation of BC emissions factors from different measures of particulate matter We included all studies that measured black carbon (or optical properties of particulate matter). However, the only study that measured BC emissions from charcoal, forced draft, and gasifier stoves was MacCarty et al 2008 [16], which did not include estimates of uncertainty. To estimate the standard error of BC emissions, we assumed that the coefficient of variance (COV) was the same for PM emissions and BC emissions an assumption that holds true for the stove classes for which variance data were available for BC emissions. In theory, for stoves sampled from the same population (or stove model or class) the BC fraction of PM should remain constant; that is, more variation in overall PM emissions ought to lead to more variation in BC emissions. However, the possibility that the COV for BC might be higher or lower than that of total PM illustrates the need for more comprehensive (and standardized) testing of improved cookstoves. S1.7 Analysis of uncertainty due to GWP estimates In addition to the uncertainties that are directly examined in the manuscript, we also recognize that the global warming impacts of short-lived pollutants are not universally agreed upon. In the manuscript we used estimates for the GWP of BC, OC, and CO that have been used in previous cookstove emissions studies and are well-supported in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5).[23, 24] However, the AR5 contains other estimates and sets bounds on the likely maximum and minimum global warming impact of these pollutants. We tested our new emissions offset protocol at the bounds of these emissions estimates. The results can be found in Figure S4. The higher bound generates larger offsets across the board, though those offsets grow less for Charcoal stoves (because those stoves emit a high quantity of CO). At the lower bound Charcoal stoves would generate no marketable offset. This is due to the reduced global warming impact of BC in this scenario, making their high CO 2 emissions a more prominent part of their emissions profile. For the other stoves, though the offset size shrinks, it remains statistically significant at 95% confidence. As the GWP impact of short-lived PICs is location-dependent, ideally the calculation of the offsets generated by cookstove projects should include region-specific GWPs.[25] Unfortunately, at present even continent-level estimates of the warming impact of short-lived PICs have very high uncertainty [23, 26, 24]. S1.8 Using prediction intervals to observe variation within stove classes In the manuscript we use 95% confidence intervals to compare emissions and offset estimates between stove classes. These confidence intervals are based on the standard error of the mean within a stove class, that is, they represent our confidence about the average traditional, natural draft, forced draft, gasifier, and charcoal stoves. While these average stoves do not exist in practice, imagining them can help compare the use of different stove classes, and further serves to illustrate 11

12 that if whole classes shouldn t receive an offset based solely on how much wood they consume, individual stoves certainly shouldn t. However, using the 95% CI risks glossing over the wide variation among stoves within a class. We found that for most stove classes there were examples of individual stoves (or individual tests) in which an improved stove performed no better than its traditional counterpart. We have included figures showing the distribution of stove tests (rather than the distribution of mean values) in Figure S5 and Figure S6. In situations where the prediction interval includes zero, a significant number of simulated tests showed the improved stove having an equal or greater global warming impact than a traditional stove. In the case of Charcoal stoves, even though the mean stove produces an offset at 95% confidence, a significant portion of the testing distribution is below zero, showing that there are almost certainly stoves in the charcoal class that should generate 0 marketable offsets. This is true in varying degrees for different stoves across different fnrb values, with the notable exception of forced draft stoves, which produce a net positive offset in well over 95% of tests. 12

13 S2 SI Figures 3,000 Protocol Values Literature Values ACR Emissions [g CO2 / kg fuel] 2,500 2,000 1,500 Traditional Gasifier Natural Draft Forced Draft Charcoal excludes outside values 2,000 Protocol Values Literature Values ACR Emissions [g CO2 / task] 1,500 1, Traditional Gasifier Natural Draft Forced Draft Charcoal excludes outside values Figure S1: American Carbon Registry (ACR) calculated emissions by stove class on (top) a perkg basis, and (bottom) a per-task basis. In each plot, the green boxes show the offset using the protocol-specified CO 2 emission factor and the blue boxes show the distribution in emissions when the literature-derived CO 2 emissions factors are used. The per-task plot (bottom) additionally incorporates the literature-derived fuel use distributions for each stove class. 13

14 3,000 Protocol Values Literature Values CDM Emissions [g CO2 / kg fuel] 2,500 2,000 1,500 1,000 Traditional Gasifier Natural Draft Forced Draft Charcoal excludes outside values 2,000 Protocol Values Literature Values CDM Emissions [g CO2 / task] 1,500 1, Traditional Gasifier Natural Draft Forced Draft Charcoal excludes outside values Figure S2: Clean Development Mechanism (CDM) calculated emissions by stove class on (top) a per-kg basis, and (bottom) a per-task basis. In each plot, the green boxes show the offset using the protocol-specified CO 2 emission factor and the blue boxes show the distribution in emissions when the literature-derived CO 2 emissions factors are used. The per-task plot (bottom) additionally incorporates the literature-derived fuel use distributions for each stove class. 14

15 3,500 Protocol Values Literature Values GS Emissions [g CO2 / kg fuel] 3,000 2,500 2,000 Traditional Gasifier Natural Draft Forced Draft Charcoal excludes outside values 2,500 Protocol Values Literature Values GS Emissions [g CO2 / task] 2,000 1,500 1,000 Traditional Gasifier Natural Draft Forced Draft Charcoal excludes outside values Figure S3: Gold Standard (GS) calculated emissions by stove class on (top) a per-kg basis, and (bottom) a per-task basis. In each plot, the green boxes show the offset using the protocol-specified CO 2 emission factor and the blue boxes show the distribution in emissions when the literaturederived CO 2 emissions factors are used. The per-task plot (bottom) additionally incorporates the literature-derived fuel use distributions for each stove class. 15

16 Emissions Offset [g CO 2 / kg fuel] 4,000 3,000 2,000 1,000 Max Mean Min 0 Natural Draft Gasifier Forced Draft Charcoal excludes outside values Figure S4: Emissions as calculated by our modified protocol given different estimates for the Global Warming Potential of CO, OC, and BC in the AR5.[23, 24] Max shows the offset sizes for each stove at the upper bound of GWP values: CO: 7.6, OC: -18, BC: Mean shows the GWP values used in the manuscript: CO: 1.9, OC: -46, BC: 900. Min shows the lower bound of GWP values in the AR5. CO: 1.6, OC: -92, BC:

17 Mean Offset [g CO 2 e / task] Mean Offset [g CO 2 e / task] Mean Offset [g CO 2 e / task] (a) 100% Non-renewable biomass ACR CDM GS New Protocol Current Protocol C FD G ND C FD G ND C FD G ND (b) 50% Non-renewable biomass ACR CDM GS New Protocol Current Protocol C FD G ND C FD G ND C FD G ND (c) 0% Non-renewable biomass ACR CDM GS New Protocol Current Protocol C FD G ND C FD G ND C FD G ND Figure S5: Offset values (versus traditional stove) assigned to each improved cookstove class by the the American Carbon Registry (ACR), Clean Development Mechanism (CDM), and Gold Standard (GS), for existing protocols using literature-derived values (blue bars) and modified protocols taking into account emissions of black carbon and carbon monoxide with literature-derived emissions factors (green bars). Values shown for (a) 100% non-renewable biomass (in which all true CO 2 emissions reductions are credited); (b) 50% non-renewable biomass (in which half of all true CO 2 emissions reductions are credited; the other half are assumed to be sequestered by the renewable fuel source); and (c) 0% non-renewable biomass (all CO 2 emitted in combustion is assumed to be sequestered again by the renewable fuel source; offset credit is only given for non-co 2 emissions). In this figure the error bars show the 95% prediction interval, defined by the mean value +/ times the standard deviation, derived from resampling literature-derived distributions of emissions factors and fuel use for each stove class: C = Charcoal, FD = Forced Draft, G = Gasifier, ND = Natural Draft. 17

18 Emissions Offset [g CO 2 / task] 3,000 2,000 1,000 0 ACR CDM GS New -1,000 Charcoal Forced Draft Gasifier Natural Draft excludes outside values Figure S6: Offset values relative to traditional stoves assigned to each cookstove class by the the American Carbon Registry (ACR), Clean Development Mechanism (CDM), Gold Standard (GS), and the protocol proposed in this study (New). Values are shown for 50% non-renewable biomass. Error bars show 95% prediction interval (2.5th to 97.5th percentile), derived from resampling literature-derived distributions of emissions factors and fuel use for each stove class. 18

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