https://orcid.org/0000-0002-8855-626X
Figures
Abstract
Tea sector is a major contributor to Kenya’s economy through foreign exchange via export. However, extensive amount of energy is required to produce one kilogram of tea, making tea processing energy-intensive. Comparing greenhouse gas emissions from different types of energy consumed in tea factories is imperative to enable policymakers make informed intervention in emission reduction. Reducing greenhouse gas emissions in tea factories is one of the pathways to meeting Kenya’s nationally determined 32% reduction of carbon emissions by 2030 and commitment to the Paris Agreement. This paper assesses greenhouse gas emissions from different sources of energy used in four tea factories in Kenya. The Intergovernmental Panel on Climate Change emission factor is used to calculate the total emissions of each type of energy used for 5 years. Life cycle assessment using SimaPro 8 software, Eco-indicator 99 method and Eco invent database was used to assess the specific compound causing the emission. The findings reveal that the 5-year greenhouse gas emissions by biogas, solar, wood, briquettes, and electricity are 336.111, 7.108, 3057.729, and 1,338.28 kg CO2/MWh, respectively. Firewood has the highest concentration of carbon dioxide, while solar energy has the least. Analysis of variance confirms significant difference (0.05>p = 0.0272) in greenhouse gas emissions from the different energy sources. Post-hoc analyses shows a significant difference in emissions between solar and firewood (p<0.0125) and no significant difference between other sources of energy. The key environmental hotspot is the energy intensive processes such as drying involved in tea production and processing, which leads to consumption of fossil fuel in the factories. To reduce such key hotspot, switching to renewable energy sources is key. Sustainability in the tea sector can therefore be achieved through switching to macadamia briquettes as a source of thermal energy and a combination of electricity and solar for electrical energy.
Citation: Kibet JJ, Letema S (2024) Energy use and greenhouse gas emissions in selected tea factories in Kenya. PLOS Clim 3(10): e0000329. https://doi.org/10.1371/journal.pclm.0000329
Editor: Zhihua Zhang, Shandong University, CHINA
Received: December 12, 2023; Accepted: September 16, 2024; Published: October 16, 2024
Copyright: © 2024 Kibet, Letema. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data to support and conclude the findings of this article are included within the article (and its additional files).
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Tea is an essential beverage globally and ranks second among the most consumed drinks, with water being the first [1]. China is the leading tea producer globally, followed by India, Kenya, Vietnam, and Sri Lanka [2]. Global tea production was 6.29 million tons in 2020, showing an increase of 3.5% in 2021 [3]. Energy consumption globally is constantly increasing, resulting in increased emissions of gases and global warming [4]. The thermal energy needs of the tea industry are mostly met by low-sulfur diesel and coal, both of which are fossil fuels that significantly harm the environment. Suitable renewable energy technologies may replace convectional fuel so as to meet the energy demand of tea plantation and industries [5] Growing concerns about emissions are attributed to the use of fossil fuels as sources of energy [6]. The burning of fossil fuels raises CO2 and greenhouse gas (GHG) levels in the atmosphere, which leads to increased global climatic changes, especially warming [7]. The continuous use of fossils leads to increased concentration of carbon gases in the atmosphere by 35%, which increases the earth’s temperature [7]. Energy-related CO2 emissions globally are estimated to be 7% higher in 2030 due to increase in demand for energy, which is estimated to be 6% in 2030 [8]. Due to the rise in global warming, emissions of GHG, fluctuating oil prices, and rising electricity demand in developing countries, alternative energy solutions are required [9]. Using alternative energy resources like renewable energy helps reduce the carbon content in the atmosphere, hence reducing the problem of global warming [10]. The use of solar energy as a source of electricity results in less environmental impact [11]; whereas the consumption of biogas as an alternative fuel source reduces CO by 46% and CO2 by 88.27% [12]. Agricultural activities contribute between 10% and 12% of the world’s CO2 emissions [13]. Energy combustion while drying tea leads to emission of GHG like CO2 and unburnt particulates into the atmosphere [10]. Tea production uses a lot of energy, which is a major worry considering the high expenses and CO2 emissions that come with using fossil fuels. In order to attain a net-zero carbon balance in tea industry there is need of advancing renewable energy technology as a way to reduce CO2 emissions from fossil fuels [14]. Tea factories in Kenya still consume fuel wood extensively [15]. The burning of wood energy sources leads to the release of CO2 absorbed during a tree’s life cycle, which impacts the environment by contributing to climate change [16]. Wood waste can cause environmental footprints, especially in the boilers used in industries where the equipment used for the operation emits more than 32kgCO2 eqMg−1 of the combusted wood from ash deposits [17]. Carbon emissions significantly vary from country to country, ranging between 2.51 and 5.41kgCO2/kg of made tea (MT) [18]. For instance, the specific CO2 emission to produce 1 kg MT is 2.49 kg CO2 /kg in Sri Lanka, 2.15 kg CO2 /kg in India and 2.86 kg CO2 /kg in Vietnam [18].
A research by Niyonzima et al.estimated a total annual emission from the tea life cycle in Rwanda as 365.31kgCO2eq/kg MT, with the most significant emissions coming from nitrous oxide (N2O) equating to 0.696kgCO2eq/kg MT [19]. Among the three GHGs, the key contributors to global warming are CO2 (98%), N2O (1.3%), and methane (CH4) gas (0.7%) [20]. The GHG emissions in tea processing are obtained using data from production and utilities, which include the amount of energy used in tea processing [21].
2. Material and methods
2.1 Ethics statement
Authorization to collect data was obtained from National Commission for Science, Technology and Innovation (NACOSTI) which is mandated by the Government of Kenya to regulate and assure quality in the research, science, technology and innovation under permit number 836833.Additionally, permission was also obtained from the directors of the organizations where data was collected. For instance, permission was granted at the head office of the Kenya Tea Development Authority (KTDA) for two factories and the head office of Finlay’s Kenya Company for the other two factories. NACOSTI and KTDA granted us permission through written document while Finlays Kenya granted us permission through email. The study utilized interviews to the management of the tea factories management team, the respondents were allowed to act independently by giving them informed consent to participate in the study. Written informed consent was administered to the participants such as disclosure of information, which stated that participant personal information would not be disclosed. Another informed consent was the voluntary nature of decisions where the participants were allowed to act voluntarily. Data collection was conducted from 25th November, 2021 to 30th March, 2022 where interviewing of key informants and obtaining of the secondary data for the study was carried out.
2.2. Description of study area
The paper is based on four tea factories located in different counties of Kenya. The tea factories are Chemogondany in Kericho, Kitumbe in Bomet, Kagwe in Kiambu, and Makomboki in Murang’a County. Kagwe is located at 1°00’17"S 36°43’35"E, Makomboki at 0°99’26"S 37°26’19"E, Chemogondany at 0°28’45"S 35°18’30" E, and Kitumbe at 0°24’53"S 35°18’30"E “Fig 1” (.The choice of Kagwe tea factory for wood fuel use is that the factory is among the biggest factories and it still uses wood fuel for its tea processing. The factory faces challenges in meeting its demand due reduced firewood supply. The choice of Makomboki tea factory is that the factory is the only one using Macadamia briquettes with few wood briquettes as their source of energy. The choice of Chemogondany tea is that the factory is the only one utilizing biogas as an energy source for its tea processing and has been established for more than five years. The choice of Kitumbe tea factory is that the solar plant has been in operation for a long time, making it possible to get the required data. The four tea factories were therefore purposely selected for this study as they are different energy sources.
2.3 Data collection and analysis approaches and techniques
The paper is based on a descriptive-comparative research design, which helps in determining the relationship between more than one variable [22] One-on-one survey interviews were conducted to get information about energy sources and usage in the tea factories. The major source of primary data was interviews with tea factory managers and technical heads in charge of tea processing. In addition, primary data was collected from tea factory reports, records, systems, and historical operational data. The data include the tea factories’ energy consumption of different energy sources (electricity, solar, biogas, briquettes, and firewood) for a 5-year period.
The paper uses the Intergovernmental Panel on Climate Change (IPCC) impact factor for each energy source to get the total GHG emissions [23]. SimaPro 8 software and Eco-indicator 99 assessment method was used to identify the specific elements of the emissions. The emission model is run to get the specific GHG based on each system’s material or energy requirement. The Eco-indicator 99 method was utilised since it combines emissions from a single high-level score and the lowest level single score with carbon capture storage (CCS), which has been employed before [24]. Eco-indicator 99 is a damage-oriented method that focuses on impacts on three main categories: ecosystem quality, human health, and resources. For the Eco-indicator 99 method, “E” is the eco-indicators score for materials and processes used in the life cycle assessment (LCA) resulting in emissions [25]. All the units are then combined to form a point (Pt), which is the sum of the total impacts [26]. The point is the total environmental load expressed as a single score of characterization normalization, damage assessment and weighing; combined as one [26]. Data validation and reliability was conducted using Microsoft excel to prevent incomplete or inconsistent data being processed or stored based on acceptable Cronbach’s alpha value of 0.70 (Tables 1 and 2; Eq 1).
Eq 1
Where, α is Cronbach’s alpha, k is the number of items, ∑s2 is the sum of item variance and s2x is the variance of total score.
The reliability and validity of the LCA process was done through the definition of system boundaries. A system boundary curve model of the LCA was developed using Monte Carlo uncertainty analysis “Fig 2” and the threshold rule and judging satisfied the research requirements. Environmental, temporal, and technical dimension criteria were used to limit the LCA boundaries as recommended by [27]. The principal method employed in defining the concept of the system was process tree (PT). The method was valid as it includes the process involved and the transportation processing production and disposal of the energy sources.
The paper covered the GHG emissions associated with the use of energy in tea production and processing. Energy sources for the production of thermal energy used for drying tea in tea factories were the purchased electricity from the national grid, biogas, solar, firewood and briquettes. The system boundary covered the energy used during the production and processing of tea, withering, rolling, oxidation, and drying. The functional units of carbon emissions is tons of carbon dioxide equivalent (tCO2equivalent). GHG inventory was associated with energy usage during the production and processing of tea. The emissions of carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), nitrous oxide (N2O), Nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulates associated with tea production and processing were obtained from SimaPro modeling of emissions. The LCA model was created using SimaPro 8 software and the Ecoinvent 3 database, based on International Organization for Standardization (ISO) ISO 14,040:2006. The four steps of the LCA framework followed are:
- 1. Goal and scope definitions
The goal of the research was to assess the greenhouse gas emissions from energy usage in four tea factories. The emissions includes the total set of greenhouse gas emissions caused by energy production and its usage. The process includes the raw materials for the energy, the processing and the consumption. The raw materials for the different sources of energy includes their sources (solar energy including the transportation of the solar panels, biogas including the production of the gas, firewood including forest production, and briquettes including its raw material processing and production). The processing stage entail the process involved in obtaining the different energy while consumption stage includes the amount of energy used in tea production and processing. Tea processing includes all the stages from tea harvesting to packaging and dispatch. All the inputs for energy production and consumption were used to calculate the total GHG emissions associated with the life cycle of the production and use of the energy sources. The system boundaries of processes considered for LCA analysis are:
Raw materials → Processing → Consumption → End life
- 2. Life cycle inventory
The life cycle inventory involves five stages, process, product stage, system description, waste type and parameters. A process in SimaPro contains data on environmental flows, such as emissions to air, soil and water, final waste (solid waste), non-material emissions such as radiation and noise, and use of raw materials that are used to model depletion. However, non-material emission was not included in the process since the study only modelled for emissions. Product stages are used to describe the composition of the product, the use phase and the disposal route of the product. Stages for each product was identified from the assembly, life cycle, disposal scenario, disassembly and reuse. The boundaries between technological system and nature were determined by selection of the energy sources and their raw materials. Additionally, for waste disposal, landfills were included in the technological system inventory. Geographical area was defined in the system in order to get the required results that includes transportation and the sensitivity of the environment to the pollutants. Time horizon of years was also defined in the system as to model the impacts over the period under review. The parameter identifications stage included specification of the data distribution and the standard deviation, obtained from the Monte Carlo analysis. A life cycle inventory considers the amount of each input and output, which take place during the life cycle of a product. Life cycle inventory is an essential step in carrying out LCA analysis. The inputs in terms of energy and the materials used were obtained from the tea factories energy bills over a period of five years. Every energy source was calculated cautiously and classifies according to its raw material such as macadamia nuts, firewood, biogas, and solar. The inventory data is presented in the table of energy bills obtained from the tea factories (Tables 3 and 4). All the inputs were used to calculate the GHG emissions associated with life cycle of production and the use of energy.
- 3. Impact Assessment
The greenhouse gasses assessment of energy production and consumption used in tea production and processing involves two major steps. The first involved calculating the total gasses produced in each process and the second step involved converting the gasses identifies into CO2-equivalent. After impact categories were identified, further analysis was done by extraction of GHGs and presented in charts.
- 4. Interpretation
The interpretation in SimaPro is designed to cover the relevant issues mentioned in the ISO standard hence forming a checklist. Eco-indicator 99 is a damage-oriented method that focuses on impacts on three main categories, ecosystem quality, human health, and resources. The midpoint impact assessment categories utilized in the study include fossil fuel, ozone layer and climate change. Other midpoint impacts were not included because the study focused on GHGs only rather than general environmental impacts. The selected damage (endpoint) categories are human health, ecosystem quality, and climate change, in line with the recommendation by Brackley et al. [28]. Climate change and ozone layer depletion was measured by the unit disability adjusted life years (DALY). Fossil fuels and minerals were measured by Mega Joule. For Eco-indicator 99 method, “E” is the eco indicators scores for materials and process used in the LCA resulting to environmental impacts [25].
The emission factor for different energy uses in this paper is based on the IPPC [23] standard emission factor (Table 5).
The emission factor (Table 5) was derived [29] as follows:
Eq 2
In which:
Greenhouse gas emission was determined as follows:
For analysis purposes, it was assumed that all the thermal and electric energy are utilized directly in production. The following conversions were used for comparison and analysis purposes:
- 1m3 of firewood produces the equivalent of 1750kWh while 1 unit of electricity costs 0.16 USD/kWh. 1kWh of energy is equivalent to 3.6 mega joules (MJ) of thermal or electrical energy from sources like solar, biogas, wood fuel, or briquettes energy and 40.28MJ/L of fuel oil.
- 1m3 of firewood is equivalent to1800Kg of steam/m3, 1 kg of bagasse containing 30% moisture content (MC) is equivalent to 12.6MJ energy, and 1kg of macadamia husks is equivalent to 15.1MJ. 29.9Gj/t MT.
After obtaining the LCA impact category was obtained, the study went further and extract the modelled GHGs emissions from SimaPro data on emissions to air. Other environmental impacts were not considered in the final analysis of the GHG emissions since they are not considered as greenhouse gasses.
2.4 Data analysis
Data from tea factories’ energy bills and survey interviews were used to derive the total GHG emissions for five years using Eq 2. Per impact category emission was modelled using SimaPro software and Eco-indicator 99 method based on the IPCC emission factor and emission to the air, followed by normalization to allow comparison of the impacts to the system-referenced values as recommended by Helder and Bruno [30]. Analysis of variance was done to determine whether there is a significant difference between the GHG emissions of different energy sources. Post-hoc analysis was also performed to determine multiple comparison between the factories’ energy sources.
3. Results and discussion
3.1 Consumption of biogas energy and greenhouse gas emission by Chemogondany tea factory
Production of biogas by Chemogondany tea factory is through anaerobic digestion in a digester with 1700m3 holding capacity that can hold up to 1600 tonnes of the mixture. The materials used as feedstock are spent waste leaves from the tea factory and a small amount of septic waste. The feeding stock materials are preferred as they are readily available, environmentally friendly, and are a sustainable way of managing waste. On average, 625m3 of gas is produced per day, and the volume of the gas depends on the amount and nature of the substrate fed into the digester.
The emission factor for biogas is 0.098tCO2/MWh (Table 6), which is slightly lower than that of wood and briquettes. The total amount of GHG produced for five years for biogas production in the factory is 336.111tCO2/MWh (Table 2). Sejahrood et al. [12] indicated that biogas energy could reduce carbon emissions by 40–88% compared to firewood. However, this study shows a reduction in carbon emissions of 34.5% compared to firewood, with the difference attributed to the different nature of biogas feedstock. Additionally, wood combustion produces heat and emission in the form of organic vapours, water, gases, and particles, resulting in an increased emission factor.
“Fig 3” shows the impact category for biogas LCA indicating fossil fuels having the highest concentration of the environmental load, followed by resporatory inorganics, ecotoxic ity, climate change, among others.
Research by Manyuchi and Mbohwa [31] reported CH4 gas as the highest composition in biogas production, ranging from 60–65% followed by CO2 that range from 30–35%. This study “Fig 4” indicates different substances causing emissions, with 52% caused by N2O and 22% by CO2. The difference between this study and that of Manyuchi and Mbohwa [31], is the difference in the feedstock of the biogas plant, which generates different emission substances. The other substances causing GHG emissions are CO2, SO2, particles from mobile and stationary objects, and arsenic. The total compartmentalization of emissions to environmental for biogas energy is 0.038233points of environmental load. The key environmental hotspot in biogas production and consumption is during anaerobic digestion process that leads to production of methane (CH4) if not properly managed. The environmental hotspot is reduced by implementing best practices in anaerobic digestion such as maximizing gas capture, monitoring and minimizing methane emission as well as maintaining optimum temperature and pH.
3.2 Solar energy use and greenhouse gas emission by Kitumbe tea factory
The solar system at Kitumbe factory has a total of 120 solar panels, each 1.5m by 1m in dimension. The panels are connected directly to the power grid, and the solar system generates no waste materials. The direct current solar panels have an output of 30kWh per day, indicating that one solar panel produces approximately 0.25kW of electricity per day. Table 7 shows the energy production from solar energy has an emission factor of 0.035 tCO2/MWh, which is the lowest among other fuel sources except electricity since solar panels are less carbon-intensive sources of energy. The total amount of GHG emissions from the solar plant in the five years is 7.108 tCO2/MWh (Table 7). The use of solar energy in tea processing minimizes carbon emissions and health hazards, as reported by Magu, Kiragu and Mwenda [32], which is similar to what this study indicates.
Further extraction was done to obtain the GHGs emissions and “Fig 6” shows the emission damage assessment per substance, where N2O is the major contributor to GHG at 44% and CO2 at 29%. A study by Niyonzima et al. [19] reported a high concentration of CO2, equating to 0.696kgCO2eq/kg emission in a tea factory in Rwanda, followed by NO2, unlike this study’s result that shows N2O having a higher concentration. The difference is the type of solar technology used; in this study, it is a grid-connected system while the compared study is a stand-alone system. The total compartmentalization of emissions to environmental for solar energy is 2.77E-07points of environmental load. The key environmental hotspot in solar production and consumption is the energy payback time, which the time is taken for a solar panel to generate the amount of energy used in its production. The period depends on factors such as the location, type of solar technology and its efficiency. The environmental hotspot is reduced by LCA and optimization to ensure use of information to optimize design, manufacturing and installation practices to minimize environmental footprints.
3.3 Briquettes and firewood energy consumption and emission by Kagwe tea factory
Kagwe tea factory (Table 8) consumes firewood, briquettes, and electricity in their tea processing. Over the five-year period under review, firewood produced a total of 3057.729 tCO2/MWh of emissions. Firewood energy consumption has a high emission compared to briquettes, with a similar finding reported by Morris [33].
The impact categories of solar LCA shows climate change having the highest concentration of environmental load followed by respiratory inorganics, lands use and fossil fuels with substantial environmental load “Fig 7”.
Further analysis of GHGs emission damage assessment per substance for firewood consumption by Kagwe factory “Fig 8” shows CO2 from burning of fossils having the highest concentration with 45% followed by CO2 from biogenic substances with 32%. Other substances causing GHG emissions are particulates, SO2, and N2O, and NO2. Similar results were reported in the research by Taulo and Sebitosi [20] in Malawi, where CO2 had the highest concentration over other substances. The total compartmentalization of emissions to environmental for solar energy is 0.104771 points of environmental load. The key environmental hotspot in macadamia briquettes production and consumption is the combustion emissions. Burning of macadamia, briquettes release CO2, particulate matter and other pollutants to the atmosphere if not combusted well. The environmental pollution is reduces by efficient combustion by the use of high efficiency and clean burning boilers to maximize energy output and minimize emissions.
3.4 Macadamia briquettes emission by Makomboki tea factory
Makomboki tea factory uses firewood, macadamia briquettes, and electricity for their tea processing. Macadamia briquettes had a total emission of 1,337.26 tCO2/MWh over the same period (Table 9). The emission factor for briquette fuel is slightly lower than that for wood fuel (Table 1), but macadamia briquettes are consumed in large quantities. The total GHG emissions from the macadamia briquettes are 1,337.2 tCO2/MWh. The increase in GHG emission from wood consumption is due to the emission of waste material from wood combustion and ash materials. Similar findings were reported by Morris [33].
The impact categories of briquettes LCA shows indicated that minerals depletion id the major environmental load and other categories include respiratory inorganics, climate change, and land use among others “Fig 9”.
Emission damage assessment per substance “Fig 10” indicates CO2 biogenic has the highest concentration at 73%. The other substances causing GHG emission are particulates, CO2 from biogenic matter, and SO2 and CO2 from fossils. A similar trend was reported by Morris [33], with CO2 having the highest substance concentration. In contrast, N2O was not found in the substance, but instead in particulate matter. The results show that wood briquettes emit different substances from those emitted by firewood.
3.5 Electricity emissions by the four tea factories
Kitumbe factory produced 17,547,791.29 kg CO2/kW (Table 10) of GHG emissions due to electricity consumption, which is higher than the other three factories. The emission factor for electricity is 0.73576632 kg CO2/kWh, which is lower than that of biogas, briquettes, solar, and firewood. Kagwe tea factory recorded the lowest GHG gas emission of 11,155,450.56 kg CO2/kWh as a result of electricity consumption for a period of 5 years. Chemogondany tea factory recorded GHG emissions slightly lower than Kitumbe factory while Makomboki factory recorded GHG emissions slightly higher than Kagwe but lower than Chemogondany factory. Liang et al. [34] reported a higher GHG emission by tea processing, contrary to this study, as they recorded 28,750,000 kg CO2/kWh in five years. The variation in the results is because of the different amounts of energy used.
Electricity damage assessment “Fig 12” indicate CO2 from fossils as the significant damage resulting from electricity use with 54%. There is a similar concentration of substances for damage assessment across all four factories. Similar results were reported by Liang et al. [34] on the substances causing GHG through electricity consumption. The key environmental hotspot in production and consumption of electricity is the transmission and distribution process. The process of transmission and distribution of electricity requires infrastructure such as power lines and power stations that affect landscape and ecosystem. Additionally, energy losses during transmission also contribute to inefficiencies in electricity grid. The environmental impact in electricity production and consumption is reduced by improving efficiency of power plants, upgrading infrastructure to reduce transmission losses and implementing energy-saving technologies and practices in industries and transportation.
3.6 Emission comparison analysis
The total 5-year GHG emissions by the four tea factories reveal that firewood has the highest emission of 3057.729 tCO2/MWh (Table 11) compared to biogas, solar, and briquettes that had 336.111 tCO2/MWh, 7.108 tCO2/MWh and 1,338.28 kg CO2/kWh, respectively. Electricity has the lowest emission of all other sources due to its lower emissions factor. Regarding per-substance emission, wood has the highest concentration, with CO2 being the highest with 0.040286 points of total environmental load for five years. Biogas production is the second with 0.038233 points of environmental load, and briquettes are the third with 0.029378 points. Solar energy has the lowest emissions with 2.77E-07 points of environmental load, which is lower than other forms of energy, including electricity. The high emission of wood energy is due to the loss of biomass by the felling of trees and the emission of ash, which is the waste product from wood consumption. The lower emission of solar energy is due to its lower emission factor, coupled with its little used in tea processing. Similar findings were reported by Morris [33], stating the same reasons for the wood energy emission.
The analysis of variance (ANOVA) on the significance of greenhouse gas emission (Table 12) of different types of energy source consumption demonstrates that the p value (0.0272) is less than the significant level (p<0.05) whereas the F value (3.762492) is greater than the F-critical value (3.098391). The results confirm that there is a significant difference in greenhouse gas emissions attributed to different energy uses by the four tea factories. The mean greenhouse gas emission between the four tea factories over five years is different (Table 13).
Post-hoc analyses to determine multiple comparison show that there is no significant difference (p>0.0125) between the GHGs emission between biogas, briquettes and solar sources of energy. However, there is a significant difference (p>0.0125) between GHG emissions in the use of solar and firewood as sources of energy. This means that the use of solar energy to boost the national grid leads to reduced GHG emissions; whereas the use of firewood leads to more GHG emissions (Tables 14 and 15).
4. Conclusion
This paper show that the total greenhouse gas (GHG) emission for biogas production to produce 3,429,705 kWh of electricity is 336.111 tCO2/MWh, with the substances causing damage to the environment being carbon dioxide (CO2) with 73% emission to the air, followed by ammonia gas (CH4) with 20%, and the lowest emission is particulate matter. Solar energy emits 7.108 tCO2/MWh of GHG to produce 203,090 kWh of electricity, with the low emission attributed to low emission factor of solar technology and its small size. The total emission of macadamia and wood briquettes to generate energy equivalent to 7,429,240 kWh of electricity is 1,337.263 tCO2/MWh, with CO2 being the highest damage to the environment. Emission by use of firewood to produce heat equivalent to 100,253 kWh of electricity is 20.201 tCO2/MWh, with the substance causing damage to the environment most being CO2 from fossil fuels and lowest being nitrous dioxide (N2O).
The paper concludes that there are differences in GHG emission by different energy source (p>0.05) from analysis of variance test. Post-hoc analyses to determine multiple comparison show that there is no significant difference (p>0.0125) between the GHGs emission between biogas, briquettes and solar energies. However, there is a significant difference (p>0.0125) between GHG emissions by the use of solar and firewood as the sources of energy. The difference is attributed to the higher emission factor of firewood and the lower emission factor of solar technology.
The paper contributes to Sustainable Development (SDG) 17 on affordable and clean energy, which targets to increase the use of renewable energy by switching to energy sources with less GHG emissions. Tea factories can contribute to the attainment of Kenya’s nationally determined 32% reduction of carbon emissions by ensuring energy sustainability in tea factories. The key environmental hotspot is the energy intensive processes involved in tea production and processing that leads to consumption of fossils fuel in the factories. To reduce such key hotspot, implementation of energy efficient measures is key as well as switching to renewable energy sources. Energy sustainability in tea sector can be achieved through GHG reduction by switching to macadamia briquettes as a source of thermal energy and a combination of electricity and solar energy for electrical energy. Biogas energy from tea waste can be used in areas where there is less solar intensity. Therefore, there is need for the government to give clear guidelines on the type of energy to be used in tea factories.
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