Mitigation of Forestation using Fuel-Saving Appliances

Mitigation of Forestation using Fuel-Saving Appliances | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mitigation of Forestation using Fuel-Saving Appliances Dawit Tessema Ebissa, Eshetu Getahun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4502157/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In this study, appropriate energy-saving cooking technologies were identified via comparison with traditional cooking technologies in the study area, Zenzelima Kebele , Amhara region, Ethiopia. Primary and secondary data were collected through different data collection tools, such as interviews, questionnaires, observation, and focus group discussion (FGD), and compiled reports were also reviewed as secondary data. For this observation, the sample size was taken as 60 households in the kebele . From this feasibility study, it was determined that the dominant fuel type was firewood, for which the percentage was 75%. According to the results of experimental performance tests and different research reviews, the efficiency of cookstoves was 10%, 25%, 48%, 50%, 54%, and 76% for 3-stone, lakech, mirt, gonze, tikikil , and pyrolysis stoves, respectively. From the total number of households with kebeles, i.e., 1986 households, only 87 households used improved cook stoves, and the rest used 3-stone stove types. The study showed that the highest fuel consumption rate and cooking time were observed for the 3-stone stove, and the lowest fuel consumption rate and cooking time were observed for the pyrolysis stove. The improvement stove reduced emissions, and the highest emission reduction stove was the gasifier stove, with a magnitude of 1.229 tons CO 2 /HH/Year. The majority of the societies did not utilize the biochar from the cook stoves. However, biochar is very important for soil amendment. Among cooking stoves, gasifier stoves have a great advantage in terms of the production of energy and biochar. The statistical analysis indicated that fuel consumption and cooking time are linearly related. Environmental Engineering Environmental Policy Forestry Agricultural Engineering bio char cooking technologies emission and household pyrolysis stove. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction Nearly half of the global population relies on solid fuel, such as biomass, coal, or dung, for cooking [ 1 , 2 ]. With a landmass of 1.1 million square kilometers, Ethiopia is the third largest and second most populous nation in Sub-Saharan Africa, with an estimated population of more than 95 million. The energy consumption of Ethiopia is predominantly based on biomass energy sources, 95% of which is derived from biomass sources, and only 4% is derived from modern energy, mainly petroleum fuels and electricity [ 3 ]. The ever-increasing demand for woody fuel and inefficient household biomass energy utilization, which results in a large amount of energy loss during baking, cooking, and lighting, are the main causes of subsequent degradation of woody biomass (high deforestation rate) and environmental degradation in Ethiopia. Unprocessed biomass (e.g., charcoal, wood, crop waste) remains a major household fuel source for most residents of low-income countries [ 4 ]. Inadequate ventilation and lack of combustion while cooking are widespread due to the use of primitive stoves or open fire pits. This results in acute and chronic exposure to indoor pollutants (particulate matter, carbon monoxide, nitrous oxides, carcinogens, and others)[ 5 , 6 ]. Exposure to household air pollution has been linked to a range of negative health outcomes in children and adults, including pneumonia, tuberculosis, chronic obstructive pulmonary disease, lung cancer, low birth weight, and premature mortality [ 7 ].Indoor air pollution (IAP) caused by solid fuel combustion inside poorly ventilated areas is responsible for 2 million premature deaths per year, or 3.3% of the world's disease stress, primarily among women and children [ 8 ]. The main cause of harmful health effects is the inhalation of small soot particles with an aerodynamic diameter less than 2.5µm [ 6 ]. Using conventional stoves has significant social repercussions in addition to negative health effects. For example, inefficient stoves require more time to cook and gather fuel, a burden usually borne by women and children, which diverts their time from education and income-producing activities. Local environmental impacts arise from damage to ambient air and local forest ecosystems (high deforestation rate). Because only a fraction of the IAP is deposited indoors, biomass burning contributes to ambient air pollution [ 9 ]. Additionally, the unsustainable harvest of fuelwood degrades local forests [ 10 ]. Sometimes even damages wildlife habitat and watershed functions and contributes to deforestation [ 11 ]. Cooking with biomass that has not been sustainably collected has the potential to impact climate change because incomplete combustion of fuels produces gases such as methane and carbon monoxide, which have greater potential to cause global warming than carbon dioxide. Biomass and fossil fuel cookstoves also emit 22% and 7%, respectively, of global carbon (BC) emissions and are the second strongest contributors to current global warming. Unlike globally distributed greenhouse gases, such as carbon dioxide, the shorter 8- to 10-day atmospheric lifetime of BC results in localized impacts [ 6 ]. Initially, improved cook stoves (ICSs) were created to address the detrimental effects of COVID-19 on human livelihoods and health. Since ICSs improve cooking efficiency compared with traditional cookstoves, ICSs can reduce the amount of fuel needed, fuel gathering time, and cooking time, all of which have the potential to improve health and increase household income[ 12 ]. In addition, these efficiencies can benefit the local environment and global climate through a reduction in fuel wood harvesting (which reduces deforestation) and particulate emissions[ 13 ]. Despite clear scientific evidence on the efficacy of these innovations, initial efforts to promote these technologies have run into challenges surrounding diffusion, dissemination, and implementation. Initially, research focused on finding the sources of demand due to the failure of attempts to force unproven technology on unwilling families and customers. The demand side of thinking has been bolstered by a small yet growing body of field evidence suggesting that potential consumers often do not invest in or maintain the use of environmental health technologies (e.g., improved stoves) because they do not know about or value the benefits of the technology. In addition, consumers are unwilling to finance or unable to pay the prevailing prices for technologies [ 14 ]. More generally, implementation and diffusion challenges may be due to ICSs that are unsuitable for local customs, ineffective financing, poor distribution channels, or insufficient social marketing. Several coinciding “game changers” may now make the large-scale deployment of ICSs more feasible: the development of a new generation of ICSs, significant experience in implementing small-scale credit operations, and new financing instruments and sources, especially those linked to climate change mitigation [ 15 ]. The influence of the game changers is further strengthened by general trends in low-income countries, such as the rising cost of fuel wood (because of increasing scarcity and forest sector reforms). To mitigate adverse health and livelihood impacts in Ethiopia, a partnership was established between Ethiopia and the German Society for International Cooperation (GIZ). The GIZ is a nongovernmental organization that provides training, outreach, and mobilization for community-based groups. The use of ICSs was designed to improve health, conserve fuelwood, and reduce emissions. The use of improved cookstoves is also appealing because it may translate into saving time and money used for gathering or purchasing fuel. Currently, the cook stove technologies (which have relatively low efficiency compared with gasifier/pyrolysis stoves) promoted and distributed by the Ethiopian government and GIZ include lakech, gonze, mirt , and rocket ( tikikil ) stoves. However, these stoves not only are less efficient but also have high indoor air pollution due to incomplete combustion (direct combustion) of the biomass. The rate of fuel consumption of these technologies is very high, which results in a high deforestation rate for fuel demand in households. Ethiopia plants have different solid biomass waste potentials, such as agricultural waste, sawdust, wood chips, coffee husks, rice husks, corncobs, and sesame husks; these wastes can be converted into useful energy forms if appropriate and more efficient cooking technologies, such as gasifier (pyrolysis) stoves, are available. Gasification/pyrolysis is the process of converting solid fuels, such as wood, agricultural residues, and coal, into combustible gases. The main components of a biomass gasifier are a reactor or container that receives fuel input and a restricted air supply (less than stoichiometric or the quantity needed for full combustion). The input material is partially burned to produce heat for gasification[ 16 ]. Producing gas is the term for flammable gas that is produced as a result of the subsequent chemical breakdown and internal reactions of fuel. The heating value of this gas ranges from 4–6 MJ/Nm 3 , or approximately 10–15% of the value of natural gas for heating [ 17 ]. Production gas is a blend of the combustible gases hydrogen (H 2 ), carbon monoxide (CO), and methane (CH 4 ) and the incombustible gases carbon dioxide (CO 2 ) and nitrogen (N 2 ); the actual gas composition may vary considerably depending on the fuel type and gasifier design. In small-scale gasifiers/pyrolyzers, solid fuels are gasified/pyrolyzed in a fixed bed; these can be divided into three types: updrafts, downdrafts, and cross-draft reactors. As shown in Fig. 1 , the gasifier has four stages consisting of a drying zone, pyrolysis zone, combustion zone, and reduction zone. With the escalating costs of fossil fuels and gas as a preferred cooking fuel (than fuel wood, residues, kerosene, etc.), biomass gasifiers are attracting renewed interest. Numerous campaigns to highlight the possible advantages of implementing biomass gasification technology in poor nations are being spurred by the potential use of this technology in culinary applications. Expanding the use of gasifier stoves in developing nations might reduce the cost of cooking fuel (deforestation), increase fuel supply dependability by empowering rural populations to become more self-sufficient, and enhance indoor air quality[ 18 ]. The high efficiency, smoke-free nature, clean combustion, uniformity, and steady flame conditions, simplicity of flame management, and potential for prolonged, attention-free operation are some of the very alluring qualities of gasifier/pyrolysis-based cooking systems. While these factors make them attractive choices in the kitchens of the developing world, there are cost and technology barriers that limit their wider adoption. Despite the use of environmentally friendly and efficient cooking technology, gasifier stove systems are found in infancy in Ethiopia. Gasifier/pyrolysis stoves provide lower emissions than conventional cook stoves do, in addition to being fuel efficient[ 19 ]. According to reports, incomplete combustion (PIC) products, which include different proportions of tar, account for approximately 10% of the carbon emissions from conventional cookstoves due to their extremely low efficiency. Moreover, each kilogram of wood emits between 100 and 180 grams of carbon monoxide and 7.7 grams of particulate matter. These mixtures are supplemented with gases, including methane, total nonmethane organic compounds (TNMOC), and N2O [ 20 ]. The main advantage of a gasifier/pyrolysis stove is that the byproduct of the stove is pure charcoal/biochar, which can be used for cooking as briquette or can be used as a soil amendment. The carbonaceous solid residue remaining after heating the biomass with little or no oxygen is called biochar. When biochar is added to soils, it can increase yields, improve soil properties, effectively store carbon for thousands to hundreds of years, and provide an opportunity to qualify for carbon sequestration credits available from international carbon markets. This study highlights appropriate energy-saving cooking technologies that could be promoted in kebeles . The main duties of the study were to identify appropriate energy-saving cook stoves that are adopted in the Kebele, to analyze the energy-saving stove utilization status of the Zenzelima Kebele, to analyze the shortcomings of the existing cooking/baking technologies, and to characterize the performance of the existing cooking stoves in terms of fuel consumption, efficiency and cooking time and to compare them with pyrolysis cooking/baking stoves. Study area The study was carried out in the Bahir Dar city administration, Zenzelma Kebele. Zenzelima is located in the Amhara region in the northwestern part of Ethiopia, as shown in Fig. 2 . Zenzelima belongs to the Bahir Dar city administration, which is part of the West Gojam administrative zone. The kebele is situated approximately 7 km from Bahir Dar city, which is the capital of the Amhara National Regional State. It is bordered by the country's largest lake, Lake Tana, where the Blue Nile originates. Zenzelima consists of three villages, Sesaberet, Gedro , and St. Michael, and has a total population of approximately 11,030 people, with a distribution of 5,643 females to 5,487 males [ 22 ]. The cooking technologies that most kebele residents use include three kinds of stone, mirt charcoal, and clay stoves. Some of those who are living in Kebele town also use an electric stove. The Study Methodology Several surveys and other information collection activities were completed to meet the objectives of the study. The data and information collection methods employed in this study can be grouped into primary and secondary data sources. Primary data collection tools Questionnaires A household head survey was carried out to collect qualitative and quantitative information regarding HH fuel-wood consumption, cooking time, fuel type, and impact on health. A simple systematic sampling technique was used to select the sample households from the Zenzelima Kebele . All the data related to fuel acquisition and cooking practices were collected from a sample of households in the Zenzelima Kebele settlements. To generate the quantitative and qualitative data and information required for the baseline, the data were collected from a sample of 60 households in the kebele through well-organized questionnaires. In-depth Interviews Semistructured interview schedule guidelines with relevant questions were developed for the key informants regarding their opinions on the determinants of energy-saving cooking stoves at Zenzelima Kebele through face-to-face communication. The interviews were conducted with a sample size of 60 households in the kebele. Focus Group Discussion The Focus Group discussion (FGD) guidelines were developed with checklists. Key informants from the environmental protection and health offices were interviewed to discuss the energy-saving stoves at the kebele. Observations To obtain a greater picture of fuel-saving cooking technology, observations were conducted through the households of kebele societies. The types of stoves, types of fuel, cooking/baking process, fuel consumption status, cooking time, and smoke level were observed and recorded as field notes in different households. Secondary data collection A preliminary assessment by the study team indicated that several study reports, resource maps, and similar documents dealing with woody biomass resource distribution and household energy acquisition and utilization patterns in the Zenzelima kebele are readily available. In addition to providing useful information for the current study, some of these secondary sources served as direct raw materials in our assessment of the fraction of fuel wood use that originates from a nonrenewable biomass base. As part of the document reviews, the Intergovernmental Panel on Climate Change Convention (IPCCC), Food and Agricultural Organization (FAO) websites, and relevant government policies were consulted for information on the methodology for assessing the nonrenewable fraction of biomass used for cooking. Sample size and sampling procedure Out of 1986 households, the majority use open-fire cooking technology for baking and cooking procedures. There are few improved cooking and baking technologies, such as mirt and lakech. Tikikil, gonze, and pyrolysis cooking technologies are limited in nature. According to the Office of Environmental Protection, Bahir Dar city administration (ANRS), only 87 mirt stoves were distributed by this office from 2010–2016. Therefore, for this study, a systematic sampling method was utilized, as indicated in Table 1 . Table 1 Systematic sampling methodology No. Type of stove Number of households Remarks 1 3-Stone 23 Interview and observation 2 Lakech 7 Interview and observation 3 Mirt 19 Interview and observation 4 Gonze 3 Secondary source 5 Tikikil 6 Secondary source 6 Gasifier 2 Secondary sourced Total 60 Data analysis All the data collected from the study area, as in the questionnaires, FGDs, in-depth interviews, and observation reports, were analyzed throughout the ongoing process. Quantitative data were processed, coded, and analyzed using computer statistical packages (SPSS version 20). The results are presented as descriptive statistics, namely, percentages and frequencies. Qualitative data were transcribed, and subsequently, themes and subthemes were derived. The themes and subthemes were then presented as they emerged. Ethical Consideration The study will be conducted by standard research ethics. Informed consent will be obtained before data collection. Anonymity and confidentiality will also be upheld. Definition of variables Dependent Variable: In this study, the dependent variables were efficiency, fuel consumption, and cooking time. Independent (explanatory) variable: The independent variables of importance in this investigation were those variables that are thought to influence the degree of fuel consumption of fuel-saving cooking technology. These included households' personal and demographic variables and sociocultural variables. Results and Discussions Fuel sources for cooking/baking stoves Figure 3 presents the descriptive statistics of the fuel sources used in the Zenzelima kebel . Out of the 60 sample households interviewed, most used biomass solid fuel sources for baking and cooking. In terms of fuel utilization, the data show that the households were used in descending order of firewood, crop residues, dung, and charcoal, and their percentage shares were 50%, 25%, 16.7%, and 8.3%, respectively. Electricity, gas, and kerosene were not utilized by societies for cooking/baking, unlike for biomass energy, but rather for lighting purposes. From this figure, biomass energy is the dominant energy source in the community for the cooking/baking process. Naturally, rural consumers, including rural households, collect their traditional fuel supplies freely in their surroundings. However, depending upon accessibility (both physically and financially) and the degree of commercialization of traditional fuels, some households may purchase traditional fuels from the market. The results of the baseline survey confirm this line of argument. The results of the survey also revealed that there is a negative correlation between traditional fuel availability and the amount of time required to freely collect fuels. As indicated in Fig. 4 , less than 10% of the freely collecting households in areas with a relative abundance of traditional fuels reported that it takes approximately one hour to collect their fuels, and the proportions reach 41% in areas where woody biomass resources are scarce and far from locals. Increasing land clearing for agriculture and growing demand for cooking fuels (both are needed to feed a growing population) were cited by households as the two most important reasons for the scarcity of traditional fuels. For that reason, some societies purchased fuel from the market. Stove efficiency Several reports indicate that the efficiency of cooking technology is 10%, 25%, 48%, 50%, and 54% for open fire, lakech, mirt, gonze, and tikikil, respectively [ 23 , 24 ]. However, the efficiency of the pyrolysis stove is approximately 76%, as determined experimentally in our previous study. The performances of the 3-stone and mirt stoves were determined in the laboratory, and the results were in good agreement with the literature values. Figure 5 indicates that the efficiency of the pyrolysis stove was the highest, and the open fire stove was the least efficient. The efficiencies of the other stoves were between these two ranges. Cooking time As shown in Fig. 6 , the cooking/baking time of the 3-stone stove was the highest, and the pyrolysis stove cooking/baking time was the lowest. This showed that open-fire stoves need more cooking and ignition time to cook or bake than other stove types due to energy loss and uncontrolled wind. Lakech, mirt, gonze, and tikikil have shorter cooking times in descending order. As the cooking time increases, fuel consumption also increases, which results in rising fuel costs and a high deforestation rate. Fuel consumption during cooking/baking Firewood, crop residue, and charcoal are the three most significant cooking fuels that rural families often utilize in the Zenzelima kebel . However, households in wood-scarce areas tend to diversify their fuel mix more and use low-grade cooking fuels such as cow dung and tree leaves to a limited extent. Table 2 Fuel consumption rate No Type of stove Fuel consumption Per week (kg fuel /food /HH) Fuel consumption Per month (kg fuel /food /HH) Fuel consumption Per year (kg fuel /Kgfood /HH) cooking baking cooking baking cooking baking 1 3-Stone 30.43 45.99 121.72 183.96 1460.64 2207.52 2 Lakech 22.4 89.6 1075.2 3 Mirt 19.95 79.8 957.6 4 Gonze 12.5 50 600 5 Tikikil 10.08 40.32 483.84 6 pyrolysis 3.36 13.44 161.28 The results of the study showed that, by using 3-stones, rural households in the Zenzelima kebele consumed the most fuel consumed−2207.52 fuel/kg dough per household per year in 2 shifts per week for baking injera and 1460. 64 kg fuel / food per household per year for cooking purposes in 4 shifts a day—and by using pyrolysis stove, they consumed the least amount of fuel consumed−161.28 kg fuel /kg food per household per year for cooking purposes in 4 shifts a day, as shown in Table 2 . Based on the findings of actual fuel consumption measurements in survey households, cooking energy consumption for rural households in the Zenzelima kebele by using 3 stones is estimated to be 141.250.7 tons of wood equivalents per annum. This indicated that a high degree of deforestation is occurring due to the cutting down of trees for firewood by societies in the kebele . According to the results of the study, firewood, crop waste, and dung are the three primary sources of energy commonly used by rural households in the Zenzelima kebele . From this study, approximately 75% of the cooking energy consumed by rural households in the Zenzelima kebele was firewood, as shown in Fig. 7 . With a 15% contribution to household cooking fuel consumption, crop waste comes in the next place, and dung (6%) in the third place. Additional energy sources, such as charcoal and leaves from tree leaves, were also used where wood scarcity was high. Fuel consumption also depends on the efficiency of cooking technologies. As shown in Fig. 8 , the open fire stove was the highest fuel consumer, and pyrolysis was the least fuel consumer stove. The fuel consumption of other stoves was between those of the other stoves. This means that improved cookstoves use less energy to cook the same quantity of meals than customary, open-fire, stoves. Additionally, the pyrolysis/gasifier type has the least impact. Therefore, the pyrolysis/gasifier stove type was the better type for fuel consumption or for reducing the deforestation rate. Impact of cook stove smoke on health It is estimated that approximately 3 billion people worldwide rely on wood, stubble, dung, and leaves for cooking fuel. Numerous dangerous contaminants are released when biomass fuels are burned over open flames or in ineffective stoves [ 25 ]. Women and children who inhale these contaminants have increased respiratory morbidity and death [ 26 ]. The amount of indoor air pollution decreases when households utilize upgraded stoves [ 27 ]. It is crucial to determine the knowledge of the negative health effects of indoor air pollution and readiness to change before attempting to intervene to lessen the health effects of biomass cooking smoke. As shown in Table 3 , the smoke release level from the 3 stone stoves in the 60 households surveyed was very high when compared to that from the other stoves due to direct burning and open fire systems. However, the smoke released by the Lakech, mirt, Tikikil , and Gonze stoves was at a medium level due to improvements in their efficiency. Moreover, the pyrolysis stove efficiency is superior to that of the stoves that are currently in use in Ethiopia, resulting in a low level of smoke release. The pyrolysis stove does not directly complete burning and releases combustible producer gases such as H2 and CO through a limited oxygen pyrolysis process. These gases are then burned completely without emitting any environmental pollutants. For a lake-type stove, the fuel source is pure charcoal, and the stove does not release too much smoke. Mirt, Tikikil, and Gonze stoves are not included in the complete buying process. They are partially oxidized, and the smock levels are intermediate. During the survey in the household, the women told us that they were suffering from smoke, as shown in Fig. 7 . This smoke resulted in breathing problems, soot on the ceiling and wall of the house, and inching of the skin and eyes of the family, especially mothers and children who cooked/baked with that type of stove. Table 3 Impact of cooking stoves on the health and education of the selected site area (Zenzelma kebele) societies N0. Type of stove Kebele Household(N = 60) Smoke release Burden to Fuel collection Ignition Fuel inserting Education 1 3 stone 23(38.3%) Very high Very high Very high Very high very high 2 Lakech 7(11.6%) Medium Medium High Low Medium 3 Mirt 19(31.6%) Medium High Low Medium Medium 4 Gonzeye 3(5%) Medium High Low Medium Medium 5 Tikikil 6(10%) Medium Medium Low Medium Medium 6 pyrolysis 2(3.3%) Low Low Very low Very low Low As the efficiency of the cooking stove decreased, the burden of fuel collection, ignition, and fuel insertion increased, as shown in Table 1 . The challenge with gasoline collecting had to go long distances, and they may have also been injured by insects and may have been raped. The burden of education for 3 stone types is very high due to the high consumption of fuel, especially for children; instead of attending their classes and studying, they spend their time cooking/baking, collecting fuels, igniting and fuel inserting fuels, and sometimes their health is affected by smoke, as demonstrated in Fig. 9 . Therefore, they cannot attend their lesson properly. However, in the pyrolysis stove, there is no waste of time for fuel insertion and ignition in time intervals. The appropriate fuel wood is inserted once, and there is no need to insert fuel wood or ignite. During this cooking time, women and children can perform other work, including homework and other education studies. Utilization of cook stove byproducts Biochar, a soil amendment, has potential as a valuable tool for the agricultural industry because of its unique ability to help build soil, conserve water, produce renewable energy, and sequester carbon. By influencing important soil processes, biochar enhances the quality of soil. The vast surface area and very porous structure of biochar are the main sources of its advantages. High surface area charges can increase cation exchange capacity (CEC), thereby increasing a soil’s ability to retain and supply nutrients. Increased porosity can increase the soil's ability to retain water, and small pore spaces with positively charged surfaces can improve soil water retention and in turn reduce nutrient (P, K, Ca, Mg, phosphorous, and nitrogen) loss through leaching. Charcoal in soils has also been linked to increased soil microbial populations, which may increase beneficial soil processes mediated by soil organisms, including nutrient availability. Since most biochar does not increase the amount of nutrients that are accessible to the soil, it is better to think of it as a soil conditioner rather than a fertilizer. If biochar is to be useful for sequestering carbon, it must be long-lived and resistant to chemical processes such as oxidation to carbon dioxide or reduction to methane. In this study, it was observed that traditional cookstoves produce little biochar and a large amount of ash from the cooking/baking process, and most societies cannot use the byproduct biochar for soil amendment. Simply, they discharged it to their surroundings. Some of these materials were used for compost purposes because of their soil fertility. Since the existing cooking stoves involve direct burning, the char is also burned during the combustion process, and the char yield is low. However, pyrolysis/gasifier stoves produce combustible gas without direct burning of char, and the byproduct is pure biochar, which is crucial for soil amendment in former farmlands. Biochar is also used as charcoal in briquettes for cooking. Cost analysis The current prices of cooking/baking stoves in Ethiopia are shown in Table 4 . Lakech has low prices, whereas Mirt, Gonze, and Tikikil have medium-range prices. If we look at pyrolysis stoves in terms of price, it seems highly costly compared to other stoves. However, considering the other advantages of pyrolysis stoves, they have many advantages, such as fuel efficiency, time efficiency, and useful byproduct production. The biochar produced from this pyrolysis stove can be used again for cooking, can reduce the cost of firewood, and can be sold to other customers for cooking and soil amendment purposes. Hence, these advantages outweigh the high cost of pyrolysis stoves in contrast to alternative stoves. Table 4 Comparison of different stoves in terms of price No. Type of stove Unit price (birr) 1 3-stone Free 2 Lakech 80.00–120.00 3 Mirt 180.00–200.00 4 Gonze 150.00–180.00 5 Tikikil 220.00 -300.00 6 Pyrolysis 500.00–600.00 Estimation of Emission Reduction For the estimation of emissions, the UNFCCC methodology for energy-saving techniques for thermal applications of nonrenewable biomass was used [ 22 ], as indicated in Eq. 1 . $${E}_{ry}{=B}_{y }(1- \raisebox{1ex}{${{\eta }}_{old}$}\!\left/ \!\raisebox{-1ex}{${{\eta }}_{new}$}\right.){f}_{NRB}NCV{EF}_{kerosene}$$ 1 Where E ry - Emission reduction per stove B y – Average quantity of biomass consumption by the household for cooking (or baking). η old – Efficiency of the stove being replaced η new – Efficiency of the stove being deployed f NRB – Nonrenewable fraction of biomass use NCV – Net calorific value of biomass fuel EF kerosene - Emission factor for the substitution of nonrenewable biomass Estimation was made for injera baking and other cooking processes. To estimate the emission reduction, improved cook stoves with overall efficiencies of 10%, 25%, 48%, 50%, 54%, and 76% for open fire, lakech, mirt, gonze, tikikil and pyrolysis stoves, respectively, were used for the cooking and injera baking processes, as shown in Table 5 . Table 5 Estimation of emissions reduction per stove per household per year for cooking No. Estimation of CERs/VERs Symbols Values Units 1 Percentage of nonrenewable biomass use in the Zenzelima kebele (estimated) f NRB 60 % 2 Average fuel wood consumption by HHs B y 2.2 tone/hh/yr 3 The efficiency of stove being replaced η old 10 % 4 Efficiency of stove to be deployed η new Lakech 25 % Mirt 48 Gonze 50 Tikikil 54 Gasifier 76 5 Net Calorific Value of biomass NCV 0.015 TJ/tone 6 Emission factor for the substitution of nonrenewable biomass EF kerosene 71.5 toneCO 2 /TJ 7 Emission Reductions per stove E ry 3-Stone 0.142 toneCO 2 /hh/year Lakech 0.849 Mirt 1.121 Gonze 1.133 Tikikil 1.153 Pyrolysis 1.229 From this study, it was observed that the emission reductions achieved by improved cook stoves are proportional to the efficiency of the cooking stove. As shown in Fig. 10 , the gasifier/pyrolysis stove has a greater emission reduction capability than the other improved cook stoves. It reduced CO2 emissions by 1.229 tons per household per year. According to our sample study, 60 households could reduce CO2 emissions by approximately 73.74 tons per year, which is a very significant reduction in emissions and is very important for the carbon credit market. However, for the 3-stone stove type, the emission reduction is 0.142 tons of CO 2 per household per year, which means that the reduction is very small compared to that of another type of stove; therefore, utilizing this type of stove is not recommended. General linear model of the data analysis The cooking stoves, fuel consumption, and cooking time were identified in this survey out of the 60 households listed as shown in Table 6 . The figure indicates that, from the total sampling of 60 households, the number of households interviewed and observed are 23HH for 3-stone, 7HH for Lakech, and 19HH for Mirt and from secondary sources 2HH for pyrolysis, 3HH for Gonze, and 6HH for Tikikil. As indicated in Table 6 , the greatest mean value stove type for fuel consumption and cooking time is 3 stones, which means that this type of stove utilizes more fuel and takes more time to cook than does another type of stove. On the other hand, pyrolysis stoves utilize less fuel and take less time to cook, so they have the lowest mean value. Therefore, the table indicates that the adoption of pyrolysis stove type is essential for minimizing the deforestation rate and saving time. Secondary data were collected for the analysis of the pyrolysis stove. Table 6 Number of stoves in the survey households and descriptive statistics Between-Subjects Factors N Cooking technology 3-Stone 23 pyrolysis 2 Gonze 3 Lakech 7 Mirt 19 Tikikil 6 Descriptive Statistics Cooking technology Mean Std. Deviation N Fuel consumption 3-Stone 3.1070 .63734 23 pyrolysis .1100 .01414 2 Gonze .4783 .15687 3 Lakech 2.2571 .64513 7 Mirt 1.1379 .55334 19 Tikikil .8250 .59477 6 Total 1.9248 1.19011 60 Cooking time 3-Stone 5.5217 1.15284 23 pyrolysis 1.7500 .35355 2 Gonze 2.2000 .52915 3 Lakech 4.7143 .48795 7 Mirt 3.3526 .70029 19 Tikikil 2.7667 .25820 6 Total 4.1733 1.49846 60 Post hoc analysis between cooking technologies The relationship between the cooking stove types is described in Table 7 . As shown in Table 6 , compared with other types of cooking stoves, the pyrolysis stove had significant differences in terms of fuel consumption and cooking time. The table shows the mean difference comparison of one cooking/baking stove with the other stoves in terms of fuel consumption and cooking times. For example, when we compared 3-stone cook stoves with other stoves in terms of fuel consumption and cooking time, a significant difference was detected for the pyrolysis stove, and the least significant difference was also detected for the lakech stove, as shown in Table 7 . Table 7 Post hoc analysis and multiple comparisons of cooking/baking technologies Multiple Compariso Dependent Variable (I) Cooking technology (J) Cooking technology Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Fuel consumption 3-Stone Pyrolysis 2.9970 * .43456 .000 1.4960 4.4979 Gonze 2.6286 * .36184 .000 1.3788 3.8784 Lakech .8498 .25445 .064 − .0291 1.7287 Mirt 1.9691 * .18274 .000 1.3379 2.6003 Tikikil 2.2820 * .27022 .000 1.3486 3.2153 Pyrolysis 3-Stone -2.9970 * .43456 .000 -4.4979 -1.4960 Gonze − .3683 .53810 .993 -2.2270 1.4903 Lakech -2.1471 * .47262 .003 -3.7796 − .5147 Mirt -1.0279 .43820 .371 -2.5415 .4857 Tikikil − .7150 .48129 .818 -2.3774 .9474 Gonze 3-Stone -2.6286 * .36184 .000 -3.8784 -1.3788 Pyrolysis .3683 .53810 .993 -1.4903 2.2270 Lakech -1.7788 * .40677 .005 -3.1838 − .3738 Mirt − .6596 .36621 .664 -1.9245 .6053 Tikikil − .3467 .41681 .983 -1.7864 1.0930 Lakech 3-Stone − .8498 .25445 .064 -1.7287 .0291 Pyrolysis 2.1471 * .47262 .003 .5147 3.7796 Gonze 1.7788 * .40677 .005 .3738 3.1838 Mirt 1.1192 * .26063 .006 .2190 2.0195 Tikikil 1.4321 * .32795 .005 .2994 2.5649 Mirt 3-Stone -1.9691 * .18274 .000 -2.6003 -1.3379 Pyrolysis 1.0279 .43820 .371 − .4857 2.5415 Gonze .6596 .36621 .664 − .6053 1.9245 Lakech -1.1192 * .26063 .006 -2.0195 − .2190 Tikikil .3129 .27604 .934 − .6406 1.2663 Tikikil 3-Stone -2.2820 * .27022 .000 -3.2153 -1.3486 Pyrolysis .7150 .48129 .818 − .9474 2.3774 Gonze .3467 .41681 .983 -1.0930 1.7864 Lakech -1.4321 * .32795 .005 -2.5649 − .2994 Mirt − .3129 .27604 .934 -1.2663 .6406 Cooking time 3-Stone Pyrolysis 3.7717 * .63855 .000 1.5662 5.9773 Gonze 3.3217 * .53170 .000 1.4852 5.1582 Lakech .8075 .37390 .467 − .4840 2.0989 Mirt 2.1691 * .26853 .000 1.2416 3.0966 Tikikil 2.7551 * .39707 .000 1.3836 4.1265 Pyrolysis 3-Stone -3.7717 * .63855 .000 -5.9773 -1.5662 Gonze − .4500 .79070 .997 -3.1811 2.2811 Lakech -2.9643 * .69448 .007 -5.3630 − .5655 Mirt -1.6026 .64390 .304 -3.8267 .6214 Tikikil -1.0167 .70722 .837 -3.4594 1.4261 Gonze 3-Stone -3.3217 * .53170 .000 -5.1582 -1.4852 Pyrolysis .4500 .79070 .997 -2.2811 3.1811 Lakech -2.5143 * .59771 .008 -4.5788 − .4498 Mirt -1.1526 .53812 .477 -3.0113 .7060 Tikikil − .5667 .61247 .972 -2.6822 1.5488 Lakech 3-Stone − .8075 .37390 .467 -2.0989 .4840 Pyrolysis 2.9643 * .69448 .007 .5655 5.3630 Gonze 2.5143 * .59771 .008 .4498 4.5788 Mirt 1.3617 * .38297 .040 .0389 2.6844 Tikikil 1.9476 * .48189 .012 .2831 3.6121 Mirt 3-Stone -2.1691 * .26853 .000 -3.0966 -1.2416 Pyrolysis 1.6026 .64390 .304 − .6214 3.8267 Gonze 1.1526 .53812 .477 − .7060 3.0113 Lakech -1.3617 * .38297 .040 -2.6844 − .0389 Tikikil .5860 .40562 .835 − .8151 1.9870 Tikikil 3-Stone -2.7551 * .39707 .000 -4.1265 -1.3836 Pyrolysis 1.0167 .70722 .837 -1.4261 3.4594 Gonze .5667 .61247 .972 -1.5488 2.6822 Lakech -1.9476 * .48189 .012 -3.6121 − .2831 Mirt − .5860 .40562 .835 -1.9870 .8151 Based on observed means. The error term is Mean Square (Error) = .750. *. The mean difference is significant at the .05 level. Curve fitting linear model The relationship between fuel consumption and cooking time of the cook stoves is displayed in Fig. 11 . The regression indicated that fuel consumption and cooking time had a linear relationship, as shown in Fig. 11 . Production process The pyrolysis/gasifier/stove production process is simple and is now already designed, licensed, and manufactured by the Epro Green Energy Company. Therefore, to disseminate mass production for society, appropriate training and consultation will be given for those societies that manufacture and utilize this material. To manufacture, 15 days of training are needed, and 10 days of training are required for the utilization of the stove. The training and the consultancy will be provided by the Epro Green Energy Company. Conclusions According to this feasibility assessment, firewood accounted for 75% of all fuel types. For crop waste, dung, tree leaves, and charcoal, the remaining amounts were 15%, 6%, 3%, and 1%, in that order. These findings showed that there is a high rate of deforestation because the majority of firewood is produced by felling trees for fuel. These rates of deforestation worsen soil fertility, increase farmland erosion, reduce production and food insecurity, and ultimately contribute to climate change. The results of several study reviews and experimental performance testing indicated that the efficiency of cook stoves for 3-stone, lakech, mirt, gonze, tikikil, and pyrolysis stoves was 10%, 25%, 48%, 50%, and 76%, respectively. Most of the societies in the kebele used 3-stone stove types. The study showed that the highest fuel consumption rate and cooking time were observed for the 3-stone stove, and the lowest fuel consumption rate and cooking time were observed for the pyrolysis stove. The other stove fuel consumption and cooking times were between the two ranges. The cost of a pyrolysis stove is high but has different advantages, such as the production of useful byproducts that can be used or sold for fuel purposes and for soil amendments. These advantages outweigh the high cost of stoves. The improved stove reduced emissions, and the highest emission reduction stove was the pyrolysis stove, with a magnitude of 1.229 tons CO 2 /HH/Year, and the least emission reduction stove was the 3-stone stove, with a magnitude of 0.142 tons CO 2 /HH/year. The statistical analysis indicated that fuel consumption and cooking time are linearly related. It was also observed that the 3-stone stove had enormous smoke during the cooking and baking process in the households, which hurts the health of women and children. However, compared with those of the 3-stone stove, the lakech, mirt, gonze, and tikikil had medium smoke release. However, pyrolysis stoves have no smoke release and have no negative implications for the health of women or children. The 3-stone, mirt, gonze, and tikikil have a burden on women and children in terms of their education since they have intensive fuel collection, insertion, and ignition times. A pyrolysis stove, on the other hand, does not have this burden because it uses less fuel and does not require any waiting time between the ignition and insertion of the fuel. Declarations Availability of Data The data used to support the findings of this study are available from the corresponding author upon request. Conflicting interests The author(s) declare no potential conflicts of interest concerning the research, authorship, and/or publication of this article. Credit authorship contribution statement Dawit Tessema Ebissa: Conceptualization, Formal analysis, Writing – review & editing, Software, Writing – original draft, Supervision, Visualization. Eshetu Getahun: Data curation, Investigation, Methodology, Resources, Validation. References E. Rehfuess, S. Mehta, A. 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Müller, Fuelwood Savings and Carbon Emission Reductions by the Use of Improved Cooking Stoves in an Afromontane Forest, Ethiopia, Land 3 (2014) 1137–1157. https://doi.org/10.3390/land3031137. M. Edelstein, E. Pitchforth, G. Asres, M. Silverman, N. Kulkarni, BMC International Health and Awareness of health effects of cooking smoke among women in the Gondar Region of Ethiopia : a pilot survey, 7 (2008) 4–10. https://doi.org/10.1186/1472-698X-8-10. A. Manuscript, NIH Public Access, 100 (2013) 1208–1215. https://doi.org/10.1016/j.rmed.2005.10.020.Relationship. N. Bruce, J. Mccracken, R. Albalak, M. Schei, K.R. Smith, V. Lopez, C. West, Impact of improved stoves , house construction and child location on levels of indoor air pollution exposure in young Guatemalan children, (2004). https://doi.org/10.1038/sj.jea.7500355. Additional Declarations The authors declare potential competing interests as follows: There is no any competing interests Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4502157","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308606744,"identity":"8431111b-9d06-4d3a-9440-9e1910f4bd8c","order_by":0,"name":"Dawit Tessema 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gasification\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/fc530ba0521fdee5dfbe1966.png"},{"id":57488124,"identity":"54707e4b-9702-47d5-9680-c3fa71f00ad9","added_by":"auto","created_at":"2024-05-31 10:43:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":349947,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study site, Zenzelima: (A) Map of Ethiopia, (B) Map of Amhara region, (C) Zenzelima[21].\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/16cc64dec0892b25018dc3b9.png"},{"id":57489106,"identity":"b542837b-fca5-4bae-a9f3-fff792a6726a","added_by":"auto","created_at":"2024-05-31 10:59:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":20533,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of sample households using energy sources\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/d9636513649a7a119eeed4e6.png"},{"id":57488121,"identity":"e27c8d3d-27b9-4aff-808a-58ffecdbad0c","added_by":"auto","created_at":"2024-05-31 10:43:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32438,"visible":true,"origin":"","legend":"\u003cp\u003eFuel collection time\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/6c955e6d56eb16800f730532.png"},{"id":57488122,"identity":"d5bbb5c7-99df-4b45-a8b4-16bb28f0d805","added_by":"auto","created_at":"2024-05-31 10:43:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":27722,"visible":true,"origin":"","legend":"\u003cp\u003eStove efficiency\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/98cee20290b0e463ac2967e8.png"},{"id":57488130,"identity":"1bebe598-580a-49bf-b549-fb796521fc36","added_by":"auto","created_at":"2024-05-31 10:43:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":23992,"visible":true,"origin":"","legend":"\u003cp\u003eCooking times of stoves\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/27988767e57cb451e0c6866a.png"},{"id":57488125,"identity":"a1a88884-b2eb-4cf0-b198-76176a057c41","added_by":"auto","created_at":"2024-05-31 10:43:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":17752,"visible":true,"origin":"","legend":"\u003cp\u003eProportions of Biomass Fuels Consumed by Rural Households in the Zenzelima Kebele\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/279c62fb6273506449ab0dce.png"},{"id":57488423,"identity":"ff026eff-3988-4833-9770-10d5401ee686","added_by":"auto","created_at":"2024-05-31 10:51:20","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":36827,"visible":true,"origin":"","legend":"\u003cp\u003eFuel consumption of stoves\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/6998729161c37935b76fc494.png"},{"id":57488129,"identity":"ec39117f-4b5a-44d1-9074-33484c9fe454","added_by":"auto","created_at":"2024-05-31 10:43:20","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":732356,"visible":true,"origin":"","legend":"\u003cp\u003eTypes of baking/cooking stoves on the Zenzelima kebele (A, B, C, D, and E are open fire stoves; F and G are more stoves; I is a rocket stove; and J is a pyrolysis stove).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/9c0ee9a03473201f48d6c555.png"},{"id":57488126,"identity":"004e3cb2-7b5b-4268-ab76-d93f965a4a13","added_by":"auto","created_at":"2024-05-31 10:43:20","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":14905,"visible":true,"origin":"","legend":"\u003cp\u003eEmission reductions of baking/cooking stoves\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4502157/v1/f0e8fd4d6539fbec2a1b87fb.png"},{"id":57489107,"identity":"9c6d1310-7514-46ad-914c-dff686f83472","added_by":"auto","created_at":"2024-05-31 10:59:20","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":34024,"visible":true,"origin":"","legend":"\u003cp\u003eRegression curve 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[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. With a landmass of 1.1\u0026nbsp;million square kilometers, Ethiopia is the third largest and second most populous nation in Sub-Saharan Africa, with an estimated population of more than 95\u0026nbsp;million. The energy consumption of Ethiopia is predominantly based on biomass energy sources, 95% of which is derived from biomass sources, and only 4% is derived from modern energy, mainly petroleum fuels and electricity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The ever-increasing demand for woody fuel and inefficient household biomass energy utilization, which results in a large amount of energy loss during baking, cooking, and lighting, are the main causes of subsequent degradation of woody biomass (high deforestation rate) and environmental degradation in Ethiopia. Unprocessed biomass (e.g., charcoal, wood, crop waste) remains a major household fuel source for most residents of low-income countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Inadequate ventilation and lack of combustion while cooking are widespread due to the use of primitive stoves or open fire pits. This results in acute and chronic exposure to indoor pollutants (particulate matter, carbon monoxide, nitrous oxides, carcinogens, and others)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Exposure to household air pollution has been linked to a range of negative health outcomes in children and adults, including pneumonia, tuberculosis, chronic obstructive pulmonary disease, lung cancer, low birth weight, and premature mortality [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].Indoor air pollution (IAP) caused by solid fuel combustion inside poorly ventilated areas is responsible for 2\u0026nbsp;million premature deaths per year, or 3.3% of the world's disease stress, primarily among women and children [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The main cause of harmful health effects is the inhalation of small soot particles with an aerodynamic diameter less than 2.5\u0026micro;m [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Using conventional stoves has significant social repercussions in addition to negative health effects. For example, inefficient stoves require more time to cook and gather fuel, a burden usually borne by women and children, which diverts their time from education and income-producing activities. Local environmental impacts arise from damage to ambient air and local forest ecosystems (high deforestation rate). Because only a fraction of the IAP is deposited indoors, biomass burning contributes to ambient air pollution [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, the unsustainable harvest of fuelwood degrades local forests [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Sometimes even damages wildlife habitat and watershed functions and contributes to deforestation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Cooking with biomass that has not been sustainably collected has the potential to impact climate change because incomplete combustion of fuels produces gases such as methane and carbon monoxide, which have greater potential to cause global warming than carbon dioxide. Biomass and fossil fuel cookstoves also emit 22% and 7%, respectively, of global carbon (BC) emissions and are the second strongest contributors to current global warming. Unlike globally distributed greenhouse gases, such as carbon dioxide, the shorter 8- to 10-day atmospheric lifetime of BC results in localized impacts [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Initially, improved cook stoves (ICSs) were created to address the detrimental effects of COVID-19 on human livelihoods and health. Since ICSs improve cooking efficiency compared with traditional cookstoves, ICSs can reduce the amount of fuel needed, fuel gathering time, and cooking time, all of which have the potential to improve health and increase household income[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, these efficiencies can benefit the local environment and global climate through a reduction in fuel wood harvesting (which reduces deforestation) and particulate emissions[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite clear scientific evidence on the efficacy of these innovations, initial efforts to promote these technologies have run into challenges surrounding diffusion, dissemination, and implementation. Initially, research focused on finding the sources of demand due to the failure of attempts to force unproven technology on unwilling families and customers. The demand side of thinking has been bolstered by a small yet growing body of field evidence suggesting that potential consumers often do not invest in or maintain the use of environmental health technologies (e.g., improved stoves) because they do not know about or value the benefits of the technology. In addition, consumers are unwilling to finance or unable to pay the prevailing prices for technologies [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. More generally, implementation and diffusion challenges may be due to ICSs that are unsuitable for local customs, ineffective financing, poor distribution channels, or insufficient social marketing. Several coinciding \u0026ldquo;game changers\u0026rdquo; may now make the large-scale deployment of ICSs more feasible: the development of a new generation of ICSs, significant experience in implementing small-scale credit operations, and new financing instruments and sources, especially those linked to climate change mitigation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The influence of the game changers is further strengthened by general trends in low-income countries, such as the rising cost of fuel wood (because of increasing scarcity and forest sector reforms). To mitigate adverse health and livelihood impacts in Ethiopia, a partnership was established between Ethiopia and the German Society for International Cooperation (GIZ). The GIZ is a nongovernmental organization that provides training, outreach, and mobilization for community-based groups. The use of ICSs was designed to improve health, conserve fuelwood, and reduce emissions. The use of improved cookstoves is also appealing because it may translate into saving time and money used for gathering or purchasing fuel. Currently, the cook stove technologies (which have relatively low efficiency compared with gasifier/pyrolysis stoves) promoted and distributed by the Ethiopian government and GIZ include \u003cem\u003elakech, gonze, mirt\u003c/em\u003e, and rocket (\u003cem\u003etikikil\u003c/em\u003e) stoves.\u003c/p\u003e \u003cp\u003eHowever, these stoves not only are less efficient but also have high indoor air pollution due to incomplete combustion (direct combustion) of the biomass. The rate of fuel consumption of these technologies is very high, which results in a high deforestation rate for fuel demand in households. Ethiopia plants have different solid biomass waste potentials, such as agricultural waste, sawdust, wood chips, coffee husks, rice husks, corncobs, and sesame husks; these wastes can be converted into useful energy forms if appropriate and more efficient cooking technologies, such as gasifier (pyrolysis) stoves, are available. Gasification/pyrolysis is the process of converting solid fuels, such as wood, agricultural residues, and coal, into combustible gases. The main components of a biomass gasifier are a reactor or container that receives fuel input and a restricted air supply (less than stoichiometric or the quantity needed for full combustion). The input material is partially burned to produce heat for gasification[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Producing gas is the term for flammable gas that is produced as a result of the subsequent chemical breakdown and internal reactions of fuel. The heating value of this gas ranges from 4\u0026ndash;6 MJ/Nm\u003csup\u003e3\u003c/sup\u003e, or approximately 10\u0026ndash;15% of the value of natural gas for heating [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Production gas is a blend of the combustible gases hydrogen (H\u003csub\u003e2\u003c/sub\u003e), carbon monoxide (CO), and methane (CH\u003csub\u003e4\u003c/sub\u003e) and the incombustible gases carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) and nitrogen (N\u003csub\u003e2\u003c/sub\u003e); the actual gas composition may vary considerably depending on the fuel type and gasifier design. In small-scale gasifiers/pyrolyzers, solid fuels are gasified/pyrolyzed in a fixed bed; these can be divided into three types: updrafts, downdrafts, and cross-draft reactors. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the gasifier has four stages consisting of a drying zone, pyrolysis zone, combustion zone, and reduction zone.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWith the escalating costs of fossil fuels and gas as a preferred cooking fuel (than fuel wood, residues, kerosene, etc.), biomass gasifiers are attracting renewed interest. Numerous campaigns to highlight the possible advantages of implementing biomass gasification technology in poor nations are being spurred by the potential use of this technology in culinary applications. Expanding the use of gasifier stoves in developing nations might reduce the cost of cooking fuel (deforestation), increase fuel supply dependability by empowering rural populations to become more self-sufficient, and enhance indoor air quality[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe high efficiency, smoke-free nature, clean combustion, uniformity, and steady flame conditions, simplicity of flame management, and potential for prolonged, attention-free operation are some of the very alluring qualities of gasifier/pyrolysis-based cooking systems. While these factors make them attractive choices in the kitchens of the developing world, there are cost and technology barriers that limit their wider adoption. Despite the use of environmentally friendly and efficient cooking technology, gasifier stove systems are found in infancy in Ethiopia. Gasifier/pyrolysis stoves provide lower emissions than conventional cook stoves do, in addition to being fuel efficient[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. According to reports, incomplete combustion (PIC) products, which include different proportions of tar, account for approximately 10% of the carbon emissions from conventional cookstoves due to their extremely low efficiency. Moreover, each kilogram of wood emits between 100 and 180 grams of carbon monoxide and 7.7 grams of particulate matter. These mixtures are supplemented with gases, including methane, total nonmethane organic compounds (TNMOC), and N2O [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The main advantage of a gasifier/pyrolysis stove is that the byproduct of the stove is pure charcoal/biochar, which can be used for cooking as briquette or can be used as a soil amendment. The carbonaceous solid residue remaining after heating the biomass with little or no oxygen is called biochar. When biochar is added to soils, it can increase yields, improve soil properties, effectively store carbon for thousands to hundreds of years, and provide an opportunity to qualify for carbon sequestration credits available from international carbon markets. This study highlights appropriate energy-saving cooking technologies that could be promoted in \u003cem\u003ekebeles\u003c/em\u003e. The main duties of the study were to identify appropriate energy-saving cook stoves that are adopted in the Kebele, to analyze the energy-saving stove utilization status of the Zenzelima Kebele, to analyze the shortcomings of the existing cooking/baking technologies, and to characterize the performance of the existing cooking stoves in terms of fuel consumption, efficiency and cooking time and to compare them with pyrolysis cooking/baking stoves.\u003c/p\u003e\n\u003ch3\u003eStudy area\u003c/h3\u003e\n\u003cp\u003eThe study was carried out in the Bahir Dar city administration, Zenzelma Kebele. Zenzelima is located in the Amhara region in the northwestern part of Ethiopia, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eZenzelima belongs to the Bahir Dar city administration, which is part of the West Gojam administrative zone. The \u003cem\u003ekebele\u003c/em\u003e is situated approximately 7 km from Bahir Dar city, which is the capital of the Amhara National Regional State. It is bordered by the country's largest lake, Lake Tana, where the Blue Nile originates. Zenzelima consists of three villages, \u003cem\u003eSesaberet, Gedro\u003c/em\u003e, and St. Michael, and has a total population of approximately 11,030 people, with a distribution of 5,643 females to 5,487 males [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The cooking technologies that most \u003cem\u003ekebele\u003c/em\u003e residents use include three kinds of stone, mirt charcoal, and clay stoves. Some of those who are living in \u003cem\u003eKebele\u003c/em\u003e town also use an electric stove.\u003c/p\u003e"},{"header":"The Study Methodology","content":"\u003cp\u003eSeveral surveys and other information collection activities were completed to meet the objectives of the study. The data and information collection methods employed in this study can be grouped into primary and secondary data sources.\u003c/p\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003ePrimary data collection tools\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003eQuestionnaires\u003c/h2\u003e\n \u003cp\u003eA household head survey was carried out to collect qualitative and quantitative information regarding HH fuel-wood consumption, cooking time, fuel type, and impact on health. A simple systematic sampling technique was used to select the sample households from the Zenzelima \u003cem\u003eKebele\u003c/em\u003e. All the data related to fuel acquisition and cooking practices were collected from a sample of households in the Zenzelima \u003cem\u003eKebele\u003c/em\u003e settlements. To generate the quantitative and qualitative data and information required for the baseline, the data were collected from a sample of 60 households in the kebele through well-organized questionnaires.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eIn-depth Interviews\u003c/h2\u003e\n \u003cp\u003eSemistructured interview schedule guidelines with relevant questions were developed for the key informants regarding their opinions on the determinants of energy-saving cooking stoves at Zenzelima Kebele through face-to-face communication. The interviews were conducted with a sample size of 60 households in the kebele.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eFocus Group Discussion\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eThe\u003c/strong\u003e Focus Group discussion (FGD) guidelines were developed with checklists. Key informants from the environmental protection and health offices were interviewed to discuss the energy-saving stoves at the kebele.\u003c/p\u003e\n\u003ch3\u003eObservations\u003c/h3\u003e\n\u003cp\u003eTo obtain a greater picture of fuel-saving cooking technology, observations were conducted through the households of kebele societies. The types of stoves, types of fuel, cooking/baking process, fuel consumption status, cooking time, and smoke level were observed and recorded as field notes in different households.\u003c/p\u003e\n\u003ch3\u003eSecondary data collection\u003c/h3\u003e\n\u003cp\u003eA preliminary assessment by the study team indicated that several study reports, resource maps, and similar documents dealing with woody biomass resource distribution and household energy acquisition and utilization patterns in the Zenzelima kebele are readily available. In addition to providing useful information for the current study, some of these secondary sources served as direct raw materials in our assessment of the fraction of fuel wood use that originates from a nonrenewable biomass base. As part of the document reviews, the Intergovernmental Panel on Climate Change Convention (IPCCC), Food and Agricultural Organization (FAO) websites, and relevant government policies were consulted for information on the methodology for assessing the nonrenewable fraction of biomass used for cooking.\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eSample size and sampling procedure\u003c/h2\u003e\n \u003cp\u003eOut of 1986 households, the majority use open-fire cooking technology for baking and cooking procedures. There are few improved cooking and baking technologies, such as mirt and lakech. Tikikil, gonze, and pyrolysis cooking technologies are limited in nature. According to the Office of Environmental Protection, Bahir Dar city administration (ANRS), only 87 mirt stoves were distributed by this office from 2010\u0026ndash;2016. Therefore, for this study, a systematic sampling method was utilized, as indicated in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSystematic sampling methodology\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of stove\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of households\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRemarks\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInterview and observation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInterview and observation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInterview and observation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary source\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary source\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGasifier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary sourced\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eData analysis\u003c/h2\u003e\n \u003cp\u003eAll the data collected from the study area, as in the questionnaires, FGDs, in-depth interviews, and observation reports, were analyzed throughout the ongoing process. Quantitative data were processed, coded, and analyzed using computer statistical packages (SPSS version 20). The results are presented as descriptive statistics, namely, percentages and frequencies. Qualitative data were transcribed, and subsequently, themes and subthemes were derived. The themes and subthemes were then presented as they emerged.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eEthical Consideration\u003c/h2\u003e\n \u003cp\u003eThe study will be conducted by standard research ethics. Informed consent will be obtained before data collection. Anonymity and confidentiality will also be upheld.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eDefinition of variables\u003c/h2\u003e\n \u003cp\u003eDependent Variable: In this study, the dependent variables were efficiency, fuel consumption, and cooking time.\u003c/p\u003e\n \u003cp\u003eIndependent (explanatory) variable: The independent variables of importance in this investigation were those variables that are thought to influence the degree of fuel consumption of fuel-saving cooking technology. These included households\u0026apos; personal and demographic variables and sociocultural variables.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results and Discussions","content":"\u003ch2\u003eFuel sources for cooking/baking stoves\u003c/h2\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e presents the descriptive statistics of the fuel sources used in the \u003cem\u003eZenzelima kebel\u003c/em\u003e. Out of the 60 sample households interviewed, most used biomass solid fuel sources for baking and cooking. In terms of fuel utilization, the data show that the households were used in descending order of firewood, crop residues, dung, and charcoal, and their percentage shares were 50%, 25%, 16.7%, and 8.3%, respectively. Electricity, gas, and kerosene were not utilized by societies for cooking/baking, unlike for biomass energy, but rather for lighting purposes. From this figure, biomass energy is the dominant energy source in the community for the cooking/baking process.\u003c/p\u003e\n\u003cp\u003eNaturally, rural consumers, including rural households, collect their traditional fuel supplies freely in their surroundings. However, depending upon accessibility (both physically and financially) and the degree of commercialization of traditional fuels, some households may purchase traditional fuels from the market. The results of the baseline survey confirm this line of argument.\u003c/p\u003e\n\u003cp\u003eThe results of the survey also revealed that there is a negative correlation between traditional fuel availability and the amount of time required to freely collect fuels.\u003c/p\u003e\n\u003cp\u003eAs indicated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, less than 10% of the freely collecting households in areas with a relative abundance of traditional fuels reported that it takes approximately one hour to collect their fuels, and the proportions reach 41% in areas where woody biomass resources are scarce and far from locals. Increasing land clearing for agriculture and growing demand for cooking fuels (both are needed to feed a growing population) were cited by households as the two most important reasons for the scarcity of traditional fuels. For that reason, some societies purchased fuel from the market.\u003c/p\u003e\n\u003ch2\u003eStove efficiency\u003c/h2\u003e\n\u003cp\u003eSeveral reports indicate that the efficiency of cooking technology is 10%, 25%, 48%, 50%, and 54% for open fire, lakech, mirt, gonze, and tikikil, respectively [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, the efficiency of the pyrolysis stove is approximately 76%, as determined experimentally in our previous study. The performances of the 3-stone and \u003cem\u003emirt\u003c/em\u003e stoves were determined in the laboratory, and the results were in good agreement with the literature values. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e indicates that the efficiency of the pyrolysis stove was the highest, and the open fire stove was the least efficient. The efficiencies of the other stoves were between these two ranges.\u003c/p\u003e\n\u003ch2\u003eCooking time\u003c/h2\u003e\n\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, the cooking/baking time of the 3-stone stove was the highest, and the pyrolysis stove cooking/baking time was the lowest. This showed that open-fire stoves need more cooking and ignition time to cook or bake than other stove types due to energy loss and uncontrolled wind. Lakech, mirt, gonze, and tikikil have shorter cooking times in descending order. As the cooking time increases, fuel consumption also increases, which results in rising fuel costs and a high deforestation rate.\u003c/p\u003e\n\u003ch2\u003eFuel consumption during cooking/baking\u003c/h2\u003e\n\u003cp\u003eFirewood, crop residue, and charcoal are the three most significant cooking fuels that rural families often utilize in the\u0026nbsp;\u003cem\u003eZenzelima kebel\u003c/em\u003e. However, households in wood-scarce areas tend to diversify their fuel mix more and use low-grade cooking fuels such as cow dung and tree leaves to a limited extent.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFuel consumption rate\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of stove\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFuel\u003c/p\u003e\n \u003cp\u003econsumption\u003c/p\u003e\n \u003cp\u003ePer week (kg \u003csub\u003efuel\u003c/sub\u003e/food\u003csub\u003e/HH)\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFuel\u003c/p\u003e\n \u003cp\u003econsumption\u003c/p\u003e\n \u003cp\u003ePer month (kg \u003csub\u003efuel\u003c/sub\u003e/food\u003csub\u003e/HH)\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFuel\u003c/p\u003e\n \u003cp\u003econsumption\u003c/p\u003e\n \u003cp\u003ePer year (kg \u003csub\u003efuel\u003c/sub\u003e/Kgfood\u003csub\u003e/HH)\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecooking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebaking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecooking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebaking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecooking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebaking\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e183.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1460.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2207.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1075.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e957.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e483.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e161.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe results of the study showed that, by using 3-stones, rural households in the Zenzelima kebele \u003csub\u003econsumed the most fuel consumed\u0026minus;2207.52 fuel/kg dough\u003c/sub\u003e per household per year in 2 shifts per week for baking injera and 1460.\u003csub\u003e64 kg fuel\u003c/sub\u003e/\u003csub\u003efood\u003c/sub\u003e per household per year for cooking purposes in 4 shifts a day\u0026mdash;and by using pyrolysis stove, they consumed the least \u003csub\u003eamount of fuel consumed\u0026minus;161.28 kg fuel\u003c/sub\u003e/kg \u003csub\u003efood\u003c/sub\u003e per household per year for cooking purposes in 4 shifts a day, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eBased on the findings of actual fuel consumption measurements in survey households, cooking energy consumption for rural households in the Zenzelima kebele by using 3 stones is estimated to be 141.250.7 tons of wood equivalents per annum. This indicated that a high degree of deforestation is occurring due to the cutting down of trees for firewood by societies in the \u003cem\u003ekebele\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eAccording to the results of the study, firewood, crop waste, and dung are the three primary sources of energy commonly used by rural households in the \u003cem\u003eZenzelima kebele\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eFrom this study, approximately 75% of the cooking energy consumed by rural households in the Zenzelima kebele was firewood, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. With a 15% contribution to household cooking fuel consumption, crop waste comes in the next place, and dung (6%) in the third place. Additional energy sources, such as charcoal and leaves from tree leaves, were also used where wood scarcity was high.\u003c/p\u003e\n\u003cp\u003eFuel consumption also depends on the efficiency of cooking technologies. As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, the open fire stove was the highest fuel consumer, and pyrolysis was the least fuel consumer stove. The fuel consumption of other stoves was between those of the other stoves. This means that improved cookstoves use less energy to cook the same quantity of meals than customary, open-fire, stoves. Additionally, the pyrolysis/gasifier type has the least impact. Therefore, the pyrolysis/gasifier stove type was the better type for fuel consumption or for reducing the deforestation rate.\u003c/p\u003e\n\u003ch2\u003eImpact of cook stove smoke on health\u003c/h2\u003e\n\u003cp\u003eIt is estimated that approximately 3\u0026nbsp;billion people worldwide rely on wood, stubble, dung, and leaves for cooking fuel. Numerous dangerous contaminants are released when biomass fuels are burned over open flames or in ineffective stoves [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Women and children who inhale these contaminants have increased respiratory morbidity and death [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. The amount of indoor air pollution decreases when households utilize upgraded stoves [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. It is crucial to determine the knowledge of the negative health effects of indoor air pollution and readiness to change before attempting to intervene to lessen the health effects of biomass cooking smoke.\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the smoke release level from the 3 stone stoves in the 60 households surveyed was very high when compared to that from the other stoves due to direct burning and open fire systems. However, the smoke released by the \u003cem\u003eLakech, mirt, Tikikil\u003c/em\u003e, and \u003cem\u003eGonze\u003c/em\u003e stoves was at a medium level due to improvements in their efficiency. Moreover, the pyrolysis stove efficiency is superior to that of the stoves that are currently in use in Ethiopia, resulting in a low level of smoke release. The pyrolysis stove does not directly complete burning and releases combustible producer gases such as H2 and CO through a limited oxygen pyrolysis process. These gases are then burned completely without emitting any environmental pollutants. For a lake-type stove, the fuel source is pure charcoal, and the stove does not release too much smoke. Mirt, Tikikil, and Gonze stoves are not included in the complete buying process. They are partially oxidized, and the smock levels are intermediate.\u003c/p\u003e\n\u003cp\u003eDuring the survey in the household, the women told us that they were suffering from smoke, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. This smoke resulted in breathing problems, soot on the ceiling and wall of the house, and inching of the skin and eyes of the family, especially mothers and children who cooked/baked with that type of stove.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eImpact of cooking stoves on the health and education of the selected site area (Zenzelma kebele) societies\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eN0.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eType of stove\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eKebele Household(N\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSmoke release\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eBurden to\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFuel collection\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIgnition\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFuel inserting\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23(38.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003every high\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7(11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonzeye\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs the efficiency of the cooking stove decreased, the burden of fuel collection, ignition, and fuel insertion increased, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The challenge with gasoline collecting had to go long distances, and they may have also been injured by insects and may have been raped. The burden of education for 3 stone types is very high due to the high consumption of fuel, especially for children; instead of attending their classes and studying, they spend their time cooking/baking, collecting fuels, igniting and fuel inserting fuels, and sometimes their health is affected by smoke, as demonstrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e. Therefore, they cannot attend their lesson properly. However, in the pyrolysis stove, there is no waste of time for fuel insertion and ignition in time intervals. The appropriate fuel wood is inserted once, and there is no need to insert fuel wood or ignite. During this cooking time, women and children can perform other work, including homework and other education studies.\u003c/p\u003e\n\u003ch2\u003eUtilization of cook stove byproducts\u003c/h2\u003e\n\u003cp\u003eBiochar, a soil amendment, has potential as a valuable tool for the agricultural industry because of its unique ability to help build soil, conserve water, produce renewable energy, and sequester carbon. By influencing important soil processes, biochar enhances the quality of soil. The vast surface area and very porous structure of biochar are the main sources of its advantages. High surface area charges can increase cation exchange capacity (CEC), thereby increasing a soil\u0026rsquo;s ability to retain and supply nutrients. Increased porosity can increase the soil\u0026apos;s ability to retain water, and small pore spaces with positively charged surfaces can improve soil water retention and in turn reduce nutrient (P, K, Ca, Mg, phosphorous, and nitrogen) loss through leaching. Charcoal in soils has also been linked to increased soil microbial populations, which may increase beneficial soil processes mediated by soil organisms, including nutrient availability. Since most biochar does not increase the amount of nutrients that are accessible to the soil, it is better to think of it as a soil conditioner rather than a fertilizer. If biochar is to be useful for sequestering carbon, it must be long-lived and resistant to chemical processes such as oxidation to carbon dioxide or reduction to methane.\u003c/p\u003e\n\u003cp\u003eIn this study, it was observed that traditional cookstoves produce little biochar and a large amount of ash from the cooking/baking process, and most societies cannot use the byproduct biochar for soil amendment. Simply, they discharged it to their surroundings. Some of these materials were used for compost purposes because of their soil fertility.\u003c/p\u003e\n\u003cp\u003eSince the existing cooking stoves involve direct burning, the char is also burned during the combustion process, and the char yield is low. However, pyrolysis/gasifier stoves produce combustible gas without direct burning of char, and the byproduct is pure biochar, which is crucial for soil amendment in former farmlands. Biochar is also used as charcoal in briquettes for cooking.\u003c/p\u003e\n\u003ch2\u003eCost analysis\u003c/h2\u003e\n\u003cp\u003eThe current prices of cooking/baking stoves in Ethiopia are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Lakech has low prices, whereas Mirt, Gonze, and Tikikil have medium-range prices. If we look at pyrolysis stoves in terms of price, it seems highly costly compared to other stoves. However, considering the other advantages of pyrolysis stoves, they have many advantages, such as fuel efficiency, time efficiency, and useful byproduct production. The biochar produced from this pyrolysis stove can be used again for cooking, can reduce the cost of firewood, and can be sold to other customers for cooking and soil amendment purposes. Hence, these advantages outweigh the high cost of pyrolysis stoves in contrast to alternative stoves.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of different stoves in terms of price\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of stove\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnit price (birr)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3-stone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLakech\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e80.00\u0026ndash;120.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMirt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e180.00\u0026ndash;200.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGonze\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e150.00\u0026ndash;180.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTikikil\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e220.00 -300.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePyrolysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e500.00\u0026ndash;600.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eEstimation of Emission Reduction\u003c/h2\u003e\n\u003cp\u003eFor the estimation of emissions, the UNFCCC methodology for energy-saving techniques for thermal applications of nonrenewable biomass was used [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e], as indicated in Eq.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e$${E}_{ry}{=B}_{y }(1- \\raisebox{1ex}{${{\\eta }}_{old}$}\\!\\left/ \\!\\raisebox{-1ex}{${{\\eta }}_{new}$}\\right.){f}_{NRB}NCV{EF}_{kerosene}$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere\u003c/p\u003e\n\u003cp\u003eE\u003csub\u003ery\u003c/sub\u003e - Emission reduction per stove\u003c/p\u003e\n\u003cp\u003eB\u003csub\u003ey\u003c/sub\u003e \u0026ndash; Average quantity of biomass consumption by the household for cooking (or baking).\u003c/p\u003e\n\u003cp\u003e\u0026eta;\u003csub\u003eold\u003c/sub\u003e \u0026ndash; Efficiency of the stove being replaced\u003c/p\u003e\n\u003cp\u003e\u0026eta;\u003csub\u003enew\u003c/sub\u003e \u0026ndash; Efficiency of the stove being deployed\u003c/p\u003e\n\u003cp\u003ef\u003csub\u003eNRB\u003c/sub\u003e \u0026ndash; Nonrenewable fraction of biomass use\u003c/p\u003e\n\u003cp\u003eNCV \u0026ndash; Net calorific value of biomass fuel\u003c/p\u003e\n\u003cp\u003eEF\u003csub\u003ekerosene\u003c/sub\u003e - Emission factor for the substitution of nonrenewable biomass\u003c/p\u003e\n\u003cp\u003eEstimation was made for injera baking and other cooking processes. To estimate the emission reduction, improved cook stoves with overall efficiencies of 10%, 25%, 48%, 50%, 54%, and 76% for open fire, lakech, mirt, gonze, tikikil and pyrolysis stoves, respectively, were used for the cooking and injera baking processes, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEstimation of emissions reduction per stove per household per year for cooking\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEstimation of CERs/VERs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSymbols\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValues\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnits\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage of nonrenewable biomass use in the Zenzelima kebele (estimated)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ef\u003csub\u003eNRB\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage fuel wood consumption by HHs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eB\u003csub\u003ey\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etone/hh/yr\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe efficiency of stove being replaced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u0026eta;\u003csub\u003eold\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eEfficiency of stove to be deployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026eta;\u003csub\u003enew\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGasifier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNet Calorific Value of biomass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTJ/tone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmission factor for the substitution of nonrenewable biomass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eEF\u003csub\u003ekerosene\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoneCO\u003csub\u003e2\u003c/sub\u003e/TJ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eEmission Reductions per stove\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eE\u003csub\u003ery\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003etoneCO\u003csub\u003e2\u003c/sub\u003e/hh/year\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFrom this study, it was observed that the emission reductions achieved by improved cook stoves are proportional to the efficiency of the cooking stove. As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e, the gasifier/pyrolysis stove has a greater emission reduction capability than the other improved cook stoves. It reduced CO2 emissions by 1.229 tons per household per year. According to our sample study, 60 households could reduce CO2 emissions by approximately 73.74 \u003csub\u003etons\u003c/sub\u003e per year, which is a very significant reduction in emissions and is very important for the carbon credit market. However, for the 3-stone stove type, the emission reduction is 0.142 tons of CO\u003csub\u003e2\u003c/sub\u003e per household per year, which means that the reduction is very small compared to that of another type of stove; therefore, utilizing this type of stove is not recommended.\u003c/p\u003e\n\u003ch2\u003eGeneral linear model of the data analysis\u003c/h2\u003e\n\u003cp\u003eThe cooking stoves, fuel consumption, and cooking time were identified in this survey out of the 60 households listed as shown in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. The figure indicates that, from the total sampling of 60 households, the number of households interviewed and observed are 23HH for 3-stone, 7HH for Lakech, and 19HH for Mirt and from secondary sources 2HH for pyrolysis, 3HH for Gonze, and 6HH for Tikikil. As indicated in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, the greatest mean value stove type for fuel consumption and cooking time is 3 stones, which means that this type of stove utilizes more fuel and takes more time to cook than does another type of stove. On the other hand, pyrolysis stoves utilize less fuel and take less time to cook, so they have the lowest mean value. Therefore, the table indicates that the adoption of pyrolysis stove type is essential for minimizing the deforestation rate and saving time. Secondary data were collected for the analysis of the pyrolysis stove.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003eTable 6 Number of stoves in the survey households and descriptive statistics Between-Subjects Factors\u003c/div\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"73.73737373737374%\" colspan=\"2\" valign=\"top\" style=\"width: 79.0425%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" valign=\"top\" style=\"width: 20.872%;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.494949494949495%\" rowspan=\"6\"\u003e\n \u003cp\u003eCooking technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.242424242424242%\" style=\"width: 29.5553%;\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.262626262626263%\" style=\"width: 20.8721%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48%\" style=\"width: 29.5553%;\"\u003e\n \u003cp\u003epyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52%\" style=\"width: 20.8721%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48%\" style=\"width: 29.5553%;\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52%\" style=\"width: 20.8721%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48%\" style=\"width: 29.5553%;\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52%\" style=\"width: 20.8721%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48%\" style=\"width: 29.5553%;\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52%\" style=\"width: 20.8721%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48%\" style=\"width: 29.5553%;\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52%\" style=\"width: 20.8721%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDescriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.510204081632654%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003eCooking technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.510204081632654%\" rowspan=\"7\"\u003e\n \u003cp\u003eFuel consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e3.1070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.63734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003epyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e.1100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.01414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e.4783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.15687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e2.2571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.64513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e1.1379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.55334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e.8250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.59477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e1.9248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e1.19011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.510204081632654%\" rowspan=\"7\"\u003e\n \u003cp\u003eCooking time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e5.5217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e1.15284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003epyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e1.7500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.35355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e2.2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.52915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e4.7143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.48795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e3.3526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.70029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e2.7667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e.25820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.61643835616438%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\"\u003e\n \u003cp\u003e4.1733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\" style=\"width: 12.6095%;\"\u003e\n \u003cp\u003e1.49846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.17808219178082%\" style=\"width: 8.2452%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003ePost hoc analysis between cooking technologies\u003c/h2\u003e\n\u003cp\u003eThe relationship between the cooking stove types is described in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. As shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, compared with other types of cooking stoves, the pyrolysis stove had significant differences in terms of fuel consumption and cooking time. The table shows the mean difference comparison of one cooking/baking stove with the other stoves in terms of fuel consumption and cooking times. For example, when we compared 3-stone cook stoves with other stoves in terms of fuel consumption and cooking time, a significant difference was detected for the pyrolysis stove, and the least significant difference was also detected for the lakech stove, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePost hoc analysis and multiple comparisons of cooking/baking technologies\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eMultiple Compariso\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e(I) Cooking technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e(J) Cooking technology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMean Difference (I-J)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% Confidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"30\"\u003e\n \u003cp\u003eFuel consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9970\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6286\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8784\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.8498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.25445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.0291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7287\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9691\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.18274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2820\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.27022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.9970\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.4979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.4960\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.3683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.2270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.1471\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.7796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.5147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.0279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.5415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.4857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.7150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.3774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.9474\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.6286\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.8784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.3788\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.3683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.4903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2270\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.7788\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.40677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.1838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.3738\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.6596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.9245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.6053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.3467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.41681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.7864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0930\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.8498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.25445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.7287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.0291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1471\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.5147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.7796\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7788\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.40677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.3738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1192\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.26063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.2190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4321\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.32795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.2994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5649\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.9691\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.18274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.6003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.3379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.4857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.6596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.6053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.1192\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.26063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.0195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.2190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.3129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.27604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.6406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2663\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.2820\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.27022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.2153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.3486\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.7150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.9474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.3467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.41681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.0930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7864\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.4321\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.32795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.5649\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.2994\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.3129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.27604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.2663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.6406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"30\"\u003e\n \u003cp\u003eCooking time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.7717\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.63855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9773\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3217\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.1582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.8075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.4840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0989\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1691\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.26853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0966\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7551\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.39707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1265\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.7717\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.63855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.9773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.5662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.4500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.79070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.1811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.9643\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.69448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.3630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.5655\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.6026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.64390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.8267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.6214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.0167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.70722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.4594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4261\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.3217\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.1582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.4852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.4500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.79070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.2811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.5143\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.59771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.5788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.4498\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.1526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.0113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.7060\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.5667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.61247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.6822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5488\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.8075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.0989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.4840\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9643\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.69448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.5655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5143\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.59771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.4498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5788\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3617\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.38297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.0389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6844\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9476\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.2831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.1691\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.26853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.0966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.2416\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.64390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.6214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.7060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.3617\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.38297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.6844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.0389\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.5860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.40562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.8151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eTikikil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.7551\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.39707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.1265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.3836\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePyrolysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.70722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.4261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGonze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.5667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.61247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.5488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6822\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLakech\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.9476\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.6121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.2831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMirt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.5860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.40562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.9870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.8151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eBased on observed means. The error term is Mean Square (Error)\u0026thinsp;=\u0026thinsp;.750.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e*. The mean difference is significant at the .05 level.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eCurve fitting linear model\u003c/h2\u003e\n\u003cp\u003eThe relationship between fuel consumption and cooking time of the cook stoves is displayed in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e. The regression indicated that fuel consumption and cooking time had a linear relationship, as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e.\u003c/p\u003e\n\u003ch2\u003eProduction process\u003c/h2\u003e\n\u003cp\u003eThe pyrolysis/gasifier/stove production process is simple and is now already designed, licensed, and manufactured by the Epro Green Energy Company. Therefore, to disseminate mass production for society, appropriate training and consultation will be given for those societies that manufacture and utilize this material. To manufacture, 15 days of training are needed, and 10 days of training are required for the utilization of the stove. The training and the consultancy will be provided by the Epro Green Energy Company.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAccording to this feasibility assessment, firewood accounted for 75% of all fuel types. For crop waste, dung, tree leaves, and charcoal, the remaining amounts were 15%, 6%, 3%, and 1%, in that order. These findings showed that there is a high rate of deforestation because the majority of firewood is produced by felling trees for fuel. These rates of deforestation worsen soil fertility, increase farmland erosion, reduce production and food insecurity, and ultimately contribute to climate change. The results of several study reviews and experimental performance testing indicated that the efficiency of cook stoves for 3-stone, lakech, mirt, gonze, tikikil, and pyrolysis stoves was 10%, 25%, 48%, 50%, and 76%, respectively. \u0026nbsp;Most of the societies in the kebele used 3-stone stove types. The study showed that the highest fuel consumption rate and cooking time were observed for the 3-stone stove, and the lowest fuel consumption rate and cooking time were observed for the pyrolysis stove. The other stove fuel consumption and cooking times were between the two ranges. The cost of a pyrolysis stove is high but has different advantages, such as the production of useful byproducts that can be used or sold for fuel purposes and for soil amendments. These advantages outweigh the high cost of stoves. The improved stove reduced emissions, and the highest emission reduction stove was the pyrolysis stove, with a magnitude of 1.229 tons CO\u003csub\u003e2\u003c/sub\u003e/HH/Year, and the least emission reduction stove was the 3-stone stove, with a magnitude of 0.142 tons CO\u003csub\u003e2\u003c/sub\u003e/HH/year. The statistical analysis indicated that fuel consumption and cooking time are linearly related. It was also observed that the 3-stone stove had enormous smoke during the cooking and baking process in the households, which hurts the health of women and children. However, compared with those of the 3-stone stove, the lakech, mirt, gonze, and tikikil had medium smoke release. However, pyrolysis stoves have no smoke release and have no negative implications for the health of women or children. The 3-stone, mirt, gonze, and tikikil have a burden on women and children in terms of their education since they have intensive fuel collection, insertion, and ignition times. A pyrolysis stove, on the other hand, does not have this burden because it uses less fuel and does not require any waiting time between the ignition and insertion of the fuel.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of Data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used to support the findings of this study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no potential conflicts of interest concerning the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDawit Tessema Ebissa: Conceptualization, Formal analysis, Writing – review \u0026amp; editing, Software, Writing – original draft, Supervision, Visualization. Eshetu Getahun: Data curation, Investigation, Methodology, Resources, Validation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eE. Rehfuess, S. Mehta, A. Pr\u0026uuml;ss-\u0026Uuml;st\u0026uuml;n, Assessing household solid fuel use: Multiple implications for the Millennium Development Goals, Environ. Health Perspect. 114 (2006) 373\u0026ndash;378. https://doi.org/10.1289/ehp.8603.\u003c/li\u003e\n \u003cli\u003eWHO, the Energy Access Situation in Developing Countries, UNDP WHO New York (2009) 142. http://www.who.int/indoorair/publications/PowerPoint_Energy_Access_paper-lr.pdf%0Ahttp://scholar.google.com/scholar?hl=en\u0026amp;btnG=Search\u0026amp;q=intitle:THE+ENERGY+ACCESS+SITUATION+IN+DEVELOPING+COUNTRIES+A+Review+Focusing+on+the#0.\u003c/li\u003e\n \u003cli\u003eD.D. Guta, Assessment of Biomass Fuel Resource Potential And Utilization in Ethiopia : Sourcing Strategies for Renewable Energies, Int. J. Renew. 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Koch, Clean fuel-saving technology adoption in urban Ethiopia, Energy Econ. 36 (2013) 605\u0026ndash;613. https://doi.org/10.1016/j.eneco.2012.11.003.\u003c/li\u003e\n \u003cli\u003eE. Dresen, B. DeVries, M. Herold, L. Verchot, R. M\u0026uuml;ller, Fuelwood Savings and Carbon Emission Reductions by the Use of Improved Cooking Stoves in an Afromontane Forest, Ethiopia, Land 3 (2014) 1137\u0026ndash;1157. https://doi.org/10.3390/land3031137.\u003c/li\u003e\n \u003cli\u003eM. Edelstein, E. Pitchforth, G. Asres, M. Silverman, N. Kulkarni, BMC International Health and Awareness of health effects of cooking smoke among women in the Gondar Region of Ethiopia : a pilot survey, 7 (2008) 4\u0026ndash;10. https://doi.org/10.1186/1472-698X-8-10.\u003c/li\u003e\n \u003cli\u003eA. Manuscript, NIH Public Access, 100 (2013) 1208\u0026ndash;1215. https://doi.org/10.1016/j.rmed.2005.10.020.Relationship.\u003c/li\u003e\n \u003cli\u003eN. Bruce, J. Mccracken, R. Albalak, M. Schei, K.R. Smith, V. Lopez, C. West, Impact of improved stoves , house construction and child location on levels of indoor air pollution exposure in young Guatemalan children, (2004). https://doi.org/10.1038/sj.jea.7500355.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"bio char, cooking technologies, emission, and household pyrolysis stove. ","lastPublishedDoi":"10.21203/rs.3.rs-4502157/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4502157/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, appropriate energy-saving cooking technologies were identified via comparison with traditional cooking technologies in the study area, Zenzelima \u003cem\u003eKebele\u003c/em\u003e, Amhara region, Ethiopia.\u003c/p\u003e\n\u003cp\u003ePrimary and secondary data were collected through different data collection tools, such as interviews, questionnaires, observation, and focus group discussion (FGD), and compiled reports were also reviewed as secondary data. For this observation, the sample size was taken as 60 households in the \u003cem\u003ekebele\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eFrom this feasibility study, it was determined that the dominant fuel type was firewood, for which the percentage was 75%. According to the results of experimental performance tests and different research reviews, the efficiency of cookstoves was 10%, 25%, 48%, 50%, 54%, and 76% for 3-stone, \u003cem\u003elakech, mirt, gonze, tikikil\u003c/em\u003e, and pyrolysis stoves, respectively. From the total number of households \u003cem\u003ewith kebeles, i.e., 1986 households,\u003c/em\u003e only 87 households used improved cook stoves, and the rest used 3-stone stove types. The study showed that the highest fuel consumption rate and cooking time were observed for the 3-stone stove, and the lowest fuel consumption rate and cooking time were observed for the pyrolysis stove. The improvement stove reduced emissions, and the highest emission reduction stove was the gasifier stove, with a magnitude of 1.229 tons CO\u003csub\u003e2\u003c/sub\u003e/HH/Year. The majority of the societies did not utilize the biochar from the cook stoves. However, biochar is very important for soil amendment. Among cooking stoves, gasifier stoves have a great advantage in terms of the production of energy and biochar. The statistical analysis indicated that fuel consumption and cooking time are linearly related.\u003c/p\u003e","manuscriptTitle":"Mitigation of Forestation using Fuel-Saving Appliances","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-31 10:43:16","doi":"10.21203/rs.3.rs-4502157/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6151b3ce-db23-441f-b09a-de4593f5123d","owner":[],"postedDate":"May 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32601959,"name":"Environmental Engineering"},{"id":32601960,"name":"Environmental Policy"},{"id":32601961,"name":"Forestry"},{"id":32601962,"name":"Agricultural Engineering"}],"tags":[],"updatedAt":"2024-05-31T10:43:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-31 10:43:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4502157","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4502157","identity":"rs-4502157","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}