The carbon footprint of the tea agrifood system in the context of SDG 13 (climate action): a systematic literature review

This study contributes to the growing interest and the need to enhance overtime transformational changes in the agrifood systems through understanding the environmental impacts of the tea agrifood system operations and identifying greenhouse gas emissions channels for improving and designing sustainable solutions to achieve SDG 13 (Climate action). It explores the main sources of greenhouse gas emissions (GHG) and methods used to measure carbon footprint and global warming potential. The study identifies different adaptation and mitigation strategies that reduce emissions from the tea agrifood system. Focusing on carbon footprint as the main factor in environmental sustainability and agrifood system resilience, 60 articles were systematically analyzed using MAXQDA software. The study found that the life cycle assessment of tea agrifood systems was highly conducted using SimaPro, different unspecified tools, and spreadsheets under ISO14040:2006, ISO14044, and PAS 2050:2011 impact evaluation standards. Moreover, electricity and energy were revealed as the leading sources of carbon emissions (CO 2), followed by the overuse of chemical fertilizers, which emit other greenhouse gasses (CH 4 and N 2 O) at the cultivation stage, and the use of coal and firewood in the processing and packaging stages. Likewise, the highest environmental footprint was due to consumption activities (47%), processing (27%), cultivation (17%), and packaging (9%). The study highlighted that various adaptation and mitigation strategies, including improving energy use efficiency, use of organic fertilizers, and waste composting from tea processing, can reduce carbon footprints, improve environmental sustainability, and enhance resilient, greener agrifood systems.

The increased demand, production, and complex supply channel between tea-producing and tea-consuming countries exacerbate the environmental crisis from cultivation, processing, and consumption, including pollution, emissions, and material use (FAO, 2024; Shah and Pate, 2016). Conversely, the tea agrifood system is driven by multiple archetypes, including the limit to growth, the tragedy of the commons, and shifting of the burden. Its production is highly affected by the existence of geopolitical tensions and other external shocks, such as pandemics and climate change (Hu et al., 2019; Mkumbukiy et al., 2025, 2026). They induce stress through trade restrictions and extreme weather events, which demoralize farmers’ efforts on farming activities and affect their livelihoods, reducing yields and quality. On the other hand, tea farming is an important agrifood system that plays a significant role in responding to climate change through its ability to capture and store greenhouse gasses, including carbon dioxide (Chiu, 2019; FAO, 2024; Geng et al., 2024; He et al., 2023; Liang et al., 2020; Soheili-Fard et al., 2014).

To investigate further the tea carbon sink potential and the related environmental crisis when system operations are mismanaged through unsustainable activities, studies have been conducted addressing the challenge. Various scholars conducted life cycle assessment (LCA) methodological approaches with different frameworks to address the carbon footprint challenge from the tea agrifood system. A few of them include Tagne et al. (2023), Zhang et al. (2023a), and Xu et al. (2019), who employed life cycle assessment with the primary focus on evaluating key environmental metrics to identify potential improvements across the entire black tea system in China under the boundaries covering both the cultivation and production phases. The ‘cradle to grave’ system boundary (Azapagic et al., 2016) focuses on the impacts of potential global warming on the production and consumption of Kenyan black tea. Also, with the same study boundaries, Üçtuğ et al. (2025) conducted a life cycle assessment (LCA) of the tea agrifood system in Türkiye, identifying environmental hotspots and proposing sustainable solutions using CCaLC2 software. However, despite the observed research on the carbon footprint through the life cycle assessment of the tea agrifood system, much research with robust methodological approaches and frameworks was extensively steered in the major food crops like rice, maize, and soybeans. This gap persists because of the complexity of the tea cultivation system, which involves multiple systems like agroforestry and mixed cropping systems, making it complex to calculate the carbon footprint compared to monocropping systems.

To the best of our knowledge, there has not yet been any research compiling different life cycle assessment (LCA) methods evaluating carbon footprint and its related impacts evaluation standards on the tea agrifood system, so that providing broader understanding and a way forward to global initiatives responding to the changing climate and enhancing environmental sustainability for greener agrifood systems.

Addressing this gap, this study proposes a systematic literature review under the MAXQDA research tool to understand the environmental impact of the tea agrifood system operations and identify greenhouse gas emissions channels for improving and designing sustainable solutions to facilitate achieving SDG 13 (Climate action). In more detail, our study explores the main sources of Greenhouse gas emissions (GHG), methods used to measure carbon footprint and global warming potential, and identifies different adaptation and mitigation strategies that reduce emissions from the tea agrifood system. Further, it highlights how the tea agrifood system contributes to achieving sustainable development goals (SDGs) with the primary focus of SDG 13 (Climate action). On top of this, the proposed holistic approach enhances our understanding of the carbon footprint and global warming potential of the complex agrifood systems and opens a new arena for global response to the changing climate and environmental sustainability.

This research study unfolds across multiple sections, each contributing to a comprehensive understanding of the carbon footprint and global response to climate change for environmental sustainability. In Section 2, the research methodology is explained in depth with a specific focus on six main steps in systematic literature review: study context and research questions development, document search and screening, as well as deductive and inductive factors compilation and in-depth analysis. Following this, in Section 3, different results were presented, disclosing the year of publication and the country in which the study was conducted, the life cycle assessment through the application of different frameworks and impact evaluation standards, and the main boundaries considered while conducting the study. Apart from that, more results revealed carbon footprint quantification methods and life cycle assessment of the tea agrifood system, as well as environmental footprint, carbon sources, and implemented strategies in the tea agrifood system. Based on the discovered results, Section 4 then discusses carbon footprint and environmental impacts in the tea agrifood system, focusing on the employed methodological approaches, most applied research tools, and their impact evaluation standard, as well as the key carbon emission sources and mitigation strategies. Finally, section 5 provides the conclusion of the study with a focus on the obtained results and discussed points of importance and delivers a limitation of the study so as to avoid bias and enhance the applicability of the findings at a given geographical scope.

This study was carried out following the six main steps as indicated by Figure 1;

Step 1: study context and research questions development

The first step involves understanding the study context on the quantification of the carbon footprints and global warming potential in the tea agrifood system. The discovered study’s main problem and knowledge gap facilitate the development of the research questions that follow the CoCoPop (Condition-Context-Population) framework for environmental sustainability. In this review, Condition (Co) is represented by carbon footprint, greenhouse gas emissions, and global warming potential, while Context (Co) is captured by tea agrifood systems, which implicate tea farms, tea processing, and the whole value chain, and Population (Pop) is represented by stakeholders involved in related activities in the tea agrifood systems. These three themes guided the review by the following research questions: What are the main sources of carbon emissions in the tea agrifood system?

What methods are used to measure the carbon footprint and global warming potential within the tea agrifood system operations?

What carbon footprint mitigation strategies have been identified across the tea agrifood system?

How does the tea agrifood system contribute to or hinder achieving SDG 13?

Step 2: document search

To facilitate the retrieval of documents related to the study’s topic, research questions, and objectives, the search string was developed using the topic keywords. The search string focuses on retrieving records on carbon footprint, global warming potential, and greenhouse gas emissions through a life cycle assessment of the tea agrifood system. The records search was conducted in February 2025, where 44 documents were retrieved from the Scopus database, and only 28 articles were considered for review, while 107 records were obtained from other methods, and 32 documents were retained for study analysis (Table 1).

Steps 3 and 4: document screening

These steps involve three main stages (Figure 2); between the period of 2009 and 2025, documents were identified from different databases, where 44 articles were retrieved from the Scopus database, and 107 records were obtained via other methods. Other methods include manual screening of reference lists from different research papers, citation tracking, and searches of relevant literature. Then, a total of 151 articles were screened at the second stage using different inclusion and exclusion criteria; duplicate records, not retrieved, titles and abstracts that do not relate to the topic, and lack of clarity, which refer to studies that has unclear objectives, did not provide sufficient detail on methodology, insufficient details on data sources, and language used other than English (Figure 1). The last stage shows all the documents included after the screening. A total of 60 articles were included in the study: 28 articles from the database and 32 articles from other methods.

Steps 5 and 6: deductive and inductive factors, compilation, and in-depth analysis

These steps were conducted to discover different sources of carbon footprint and greenhouse gas emissions, methodological approaches, and implemented strategies to facilitate greener, sustainable agrifood systems to achieve SDG 13 (Climate action). After the screening process, the full texts of the selected research studies were imported into MAXQDA for in-depth content analysis. Each retrieved article was evaluated as an individual document within MAXQDA and contributed to the unit of analysis (Kirsten et al., 2025; Mkumbukiy et al., 2025). Moreover, MAXQDA was used to analyze qualitative data in various formats, such as text, audio, video, images, and surveys.

The analysis adopted a systematic systems thinking approach to address the proposed research questions. This methodological approach explored descriptive analysis of the documents based on the year of publication, the country in which the study was conducted, the life cycle assessment through the application of different frameworks and impact evaluation standards, and the main boundaries. Also, thematic coding was conducted to identify environmental footprints based on the value chain stages of the tea agrifood systems, their main sources of emissions, and implemented strategies responding to the consequences of the GHG emissions.

The deductive and inductive dimensions were formulated for the systematic literature review guidance and structuring of the analysis (Loghmani-Khouzani et al., 2024). In the first stage, a deductive coding framework was developed with the focus of study objective, research questions, and theoretical perspectives, covering: life cycle assessment, resource nexus theory, and sustainable agriculture and policy frameworks (Figure 1). The scope of the study uses these deductive dimensions to focus on the existing theories and frameworks facilitating analysis to understand the interconnection between various factors related to the carbon footprint in the tea agrifood system. However, these predefined codes were used to guide the initial coding of all selected research articles used in this study to ensure consistency across literature.

Also, the inductive dimensions were considered to discover crucial information, patterns, and relationships emerging from previous reviews. It builds theories from observations and evidence without pre-established frameworks, allowing new insights to emerge organically. The emergent inductive codes include climate adaptation and resilience strategies, study chain dynamics and tradeoffs, and consideration of the geographical scope. All selected studies were coded by the first author using the developed coding framework in MAXQDA. To enhance the credibility and transparency of the analysis, all coding decisions and the codebook were continuously discussed, reviewed, and validated with the co-authors throughout the analysis until no new concepts emerged, providing a clear audit trail of analytical decisions.

Moreover, using MAXQDA, the coded text segments were systematically created and organized to allow a comparative analysis of evidence across studies. The thematic analysis focused on various criteria as reflected by the inductive and deductive dimensions. Also, the document synthesis reflects other factors, such as environmental footprints across different stages of the tea agrifood system value chain, major sources of GHG emissions from production to consumption, and mitigation strategies reported in the literature. The purpose of using the deductive dimensions is to ensure that the analysis remained anchored in established theoretical and policy frameworks, while the inductive scopes enabled us to identify emerging evidence, novel patterns, and previously underexplored relationships within the tea agrifood system.

The combination of these dimensions provided a broader understanding of carbon footprint dynamics and informed the development of evidence-based conclusions regarding sustainable tea production.

Descriptive analysis

The systematic literature review was carried out on the 60 documents retrieved from different sources, including articles, conference papers, and reviews covering the publication period from 2009 to 2025. The largest number of documents were published from the subject areas of environmental science (25) agricultural and biological sciences (14), energy (11), engineering (11), business, management and accounting(7), social sciences (7), computer science 7, biochemistry, genetics and molecular biology4, decision science (4), earth and planetary sciences (3) and other topics like mathematics, chemistry, medicine and multidisciplinary which counts 2 to each, refer to Figure 3.

Further, the analysis was carried out based on the year of publication, the country in which the study was conducted, the life cycle assessment through the application of different frameworks and impact evaluation standards, and the main boundaries considered while conducting the study. Figure 4 shows that between 2009 and 2025, a highly increased number of papers published on the topic related to the quantification of carbon footprint and global warming potential of tea was observed in the year 2024, whereas the publications on the same topic for the previous years, excluding 2023, were very low.

Referring to the location of the study conducted, Figures 5, 6 shows geographical distribution by country and continent. The publication distribution is dominated by countries such as China, 18%; Italy, 15%; Spain, 8%; the UK, the US, India, and Australia, 5%. Countries such as Kenya, France, Greece, and Switzerland (3% each), while the remaining countries such as Argentina, Nepal, Belgium and others cover (2% each).

Carbon footprint quantification methods and life cycle assessment of the tea agrifood system

The study proposed to explore different methodological approaches used to quantify the carbon footprint in the tea agrifood system with reference to life cycle assessment (LCA). This approach is widely used to determine the environmental footprint of agrifood systems and their related products through their general life cycle from production to consumption. Moreover, LCA is used to determine and understand the importance of environmental assessment with sustainable development goals. The study discovered several LCA data syntheses from 42 (Figure 7) research studies, while 18 studies out of 60 did not use any LCA tool. These tools used to quantify the carbon footprint through life cycle assessment of the tea agrifood system life cycle, namely: SimaPro 33%, followed by other tools that are not specified 24%, Use of spreadsheet for LCA data synthesis 14%, and manual mathematical modeling 12% while Openlca and CCaLC2 scored 5% each, and EX-ACT, EX-ACT VC, and EX-ACT+VC 2% per framework. Also, reviewed studies mentioned ISO14040:2006 as the most used impact evaluation standard (46%), followed by ISO14044 (28%), PAS 20250:2011 (12%), GHG protocol (9%), ISO 2006(4%), and ISO/TS 14067 by 1%, referring to Figure 8. The frameworks were implemented under two major boundaries (Figure 9), which are cradle-to-gate (59%) and cradle-to-grave (41%).

Tea’s agrifood environmental footprint, carbon sources, and implemented strategies

The study determined that the tea value chain involves several stages, including production or cultivation, processing, packaging, and consumption. Further, all the stages were discovered to emit greenhouse gasses; for instance, at the cultivation stage, CO 2, NH 3, and N 2 O are the most produced GHGs, while CO 2 is more emitted at the processing, packaging, and consumption stages, followed by other gasses. In this study, the results presented in Figure 10 are interpreted as the frequency distribution of greenhouse gas (GHG) emissions reported in the reviewed studies across the stages of the tea agrifood value chain in the reviewed literature. Based on the available carbon footprint assessments, consumption accounted for the highest share of total estimated emissions (47%), followed by the processing stage (27%), cultivation (17%), and packaging (10%). The stage-wise emissions are influenced by various activities, including; energy use or electricity (33%), followed by overuse of chemical fertilizers (20%), uses of fossil fuels (13%), coal and firewood (13%), insecticides (8%), herbicides (5%) and other activities such as uses of mulching as weed control method (2%) and artificial grass covering (0.6%) (Figure 11).

The study explores different adaptation and mitigation strategies introduced to facilitate the sustainability and resilience of the tea agrifood system through the reduction of GHG emissions. Figure 12 shows that most of the suggested improvements in energy use efficiency of (36% of reported strategies), followed by using biomass instead of coal for energy in tea processing (21%), use of organic fertilizers 15%, and methods like composting tea waste, enhancing processing technology by 9% each.

Although the life cycle assessment (LCA) is widely applied to assess the environmental performance of tea agrifood systems, the reviewed studies demonstrated heterogeneity in reported carbon footprints. This is due to differences in prioritized methodological approaches and standards, value chain stage conditions, and the general system behavior. These perceived variations from different reviewed studies limit direct comparison of carbon footprint values among studies; also, it highlights the importance of considering the interpretation of results based on their specific assessment contexts and standards (Finkbeiner, 2014; Lal, 2004; Lee and Inaba, 2004; Mavrakis, 2011; Nemecek et al., 2007). This study identified different main sources of heterogeneity, including tea type and production system, system boundary, functional unit, geographical location, energy mix and management practices.

Tea type manufacturing systems

In this study, tea type differences were identified as a crucial factor that explains existing variations in environmental impacts; the tea agrifood system is composed of different categories of processed tea made from different countries. Black tea, green tea, oolong tea, white tea, and organic tea systems differ in terms of manufacturing methods, withering and drying requirements, and handling intensity (Hao et al., 2026; Kouchaki-Penchah et al., 2017; Kumarihami and Song, 2018; Kurniawan et al., 2026; Vera-Guerrero et al., 2025; Wong et al., 2022). The observed emissions, in combination with various carbon sources like coal and firewood consumption in the processing stages, result in an increased environmental footprint that poses challenges to sustainable production (Ahmed et al., 2017; Alom et al., 2021; Cichorowski et al., 2015; Mitra and Roy, 2016). Various studies identify that in the tea agrifood system; energy utilization is the main hotspot for greenhouse gas emissions. Compared to different types of tea systems, this state is highly experienced in the black tea processing systems due to intensive withering, rolling, fermentation, and drying operations (Azapagic et al., 2016; Munasinghe et al., 2017; Tagne et al., 2023; Zhang et al., 2023a; Zhang et al., 2023b).

Geographical location, energy mix and agricultural management practices

Moreover, the reviewed studies demonstrated that geographical location and energy mix further contributed to differences in recorded estimates of the carbon footprint. Most of the countries that are growing and processing tea green leaf differ in the types of energy used and technologies (Premalatha et al., 2024; Zeng et al., 2013). Compared to other sources of energy such as firewood, electricity, and different renewable energy-based alternatives, studies conducted in regions dependent on fossil fuels reported higher energy-related emissions. For instance, Kibet and Letema (2024) highlighted moderate to low emissions from Kenyan tea processing through electricity and firewood consumption, while a study conducted by Vidanagama and Lokupitiya (2018) reported fuel and electricity use as important contributors in Sri Lankan tea manufacturing. Conversely, Aditya et al. (2023) and Dutta and Baruah (2014) demonstrated that reduced emissions from tea processing could be achieved when prioritizing adoption of renewable energy and biomass-based alternatives.

In contrast, some studies reported that not only is energy the hotspot of GHG emissions, but greater contributions are also observed from farm operation practices such as synthetic fertilizer production and application, and utilization of farm machinery that uses fossil fuel to operate (Ding et al., 2024; He et al., 2023; Sun et al., 2024; Wijeratne and Gunasekare 2018; Xu et al., 2019). It represents another major source of heterogeneity where the application of Nitrogenous fertilizers has been identified to contribute directly and indirectly to greenhouse gas emissions through manufacturing, distribution, and soil nitrogen transformation processes. This is also emphasized by Chiu (2019) and Hu et al. (2019), where tea production in Taiwan, especially oolong and Dongshan, contributes highly to emissions due to the utilization of agricultural inputs such as industrial fertilizers and herbicides. The cultivation stage involves the emission of CO 2, CH 4, and N 2 O through disturbing the land and overusing chemical fertilizers (De Costa et al., 2015; Harper, 2023; Hazarika et al., 2025; Owuor et al., 2010; Wang et al., 2001; Yao et al., 2015). However, this study determines that the magnitude of fertilizer-related emissions differed depending on application rates, fertilizer type, and management practices. Although Owuor et al. (2010) showed that nitrogen application influences tea productivity and quality, while Yao et al. (2015) demonstrated that the same fertilizer affects nitrogen cycling, which also causes N₂O emissions in tea plantations. The rule of thumb reflects that increased unsustainable agricultural practices stimulate a rise in GHG emissions (He et al., 2023; Huang et al., 2025; Pramanik and Phukan, 2020; Sun et al., 2024). In turn, it influences global warming potential and consequently decreases food production. Likewise, a decrease in food production influences growers’ willingness to increase the application of unsustainable agrifood activities. This challenge will persist and worsen agrifood system development and environmental sustainability if no sustainable strategy is initiated (Li et al., 2025; Senadheera, 2014; Sutton et al., 2024). This implies that the global initiative to reduce carbon footprints from the agrifood systems, including the tea subsector, is set to address environmental challenges triggered by increased climate change Moreover, studies conducted in China, India, and Sri Lanka consistently identified utilization of chemical fertilizers as a critical determinant of cultivation emissions (He et al., 2023; Wang et al., 2001; Xu et al., 2019).

Functional unit and system boundaries

In this study, functional unit and system boundaries were among additional methodological factors influencing reported carbon footprints. Various studies applied different functional units, which are basically based on mass and other consumer-based functional units. For instance, some of the studies use kg CO₂e per kg of tea product (Azapagic et al., 2016; Bockel et al., 2017; Zhang et al., 2023a; Zhang et al., 2023b), carbon emissions per hectare (Aditya et al., 2023; Li et al., 2025), while others applied emissions per consumer serving (Doublet and Jungbluth, 2010; Eneroth et al., 2022). Moreover, the application of Mass-based functional units mainly reflects production efficiency, whereas consumer-based functional units incorporate all activities conducted from the gate to the grave, including water boiling, packaging, and waste management (Khanali et al., 2021). On the other hand, the tea agrifood system operation is characterized by cradle-to-gate and cradle-to-grave assessment boundaries, which include multiple stages of production, processing, distribution, consumption, and waste management. Each stage contributes to carbon emissions to different extents. Understanding the primary sources of the environmental footprint within the operating system is crucial for identifying opportunities for reducing emissions and improving overall ecological sustainability through implemented strategies (Cammarata et al., 2023; Liang et al., 2021; Zhang et al., 2023b). Moreover, this study identifies that packaging, and transportation behaviors contribute to differences among reported carbon footprints, particularly among cradle-to-grave studies. Most of carbon dioxide equivalents were found to be released from off farm activities, especially transportation of tea greenleaf from farm to factory and processed tea from factory to consumer (Niyonzima et al., 2020). Compared to farm-to-gate studies that are conducted based on the cradle-to-grave boundary that includes final stages such as packaging, distribution, and waste management, reported higher environmental impacts (Huang et al., 2025; Üçtuğ et al., 2025). This situation explains why cradle-to-gate studies are frequently reported, which mainly focus on cultivation and processing emissions while neglecting contributions from all other downstream activities with minor emissions contributions, compared with cradle-to-grave studies captures the GHG contributions of the agrifood system from the beginning to the end point.

This study contributes to the growing global interest and urgent need to address the consequences of the carbon footprint from the tea agrifood system on environmental sustainability with the broader climate action goals under SDG 13. By reviewing widely applied life cycle assessment (LCA) frameworks, impact evaluation standards, key emission sources and mitigation pathways, the study provides an integrated understanding of the climate-related challenges to environments and sustainability opportunities across the tea value chain. The findings from this study declared that the environmental footprint of the tea agrifood system is highly driven by different activities performed during the consumption stage, followed by the processing, cultivation, and packaging stages. Energy-intensive practices, dependence on fossil fuels, inefficient processing systems, and unsustainable agricultural inputs remain key drivers of emissions. However, the evidence also highlighted the key mitigation strategies implemented to facilitate zero-carbon tea production, including stakeholders’ initiatives to improve energy use efficiency during processing, switching from fossil fuels and coal to renewable energy sources, reducing the overuse of chemical fertilizers and other synthetic agricultural inputs that are dangerous to environmental health, and increasing the use of organic alternative agro-inputs, and leveraging closed-loop industrial production activities through implementing sustainable waste composting practices.

In conclusion, bridging the gap between the current observed environmental footprints of the tea agrifood system and all targets set by SDG 13 requires inclusive coordinated efforts at all levels of the tea supply chain, from governments, businesses, citizens, and international organizations. By adopting carbon-reduction strategies, enhancing climate resilience, and leveraging life-cycle assessments to measure progress, the tea sector can contribute to global climate action goals while fostering sustainable and resilient agrifood systems. Moreover, the stakeholders’ willingness to reduce their carbon footprint presents a strategic opportunity to contribute to the sustainability of the tea agrifood system and global sustainable development goals in line with the targets of SDG 13. With the implementation of the discovered sustainable interventions, technological innovations, and industry-wide collaboration, the tea agrifood system will successfully transition toward a more sustainable, low-carbon future while enhancing environmental resilience and ensuring long-term food security.