Analysis of Carbon Footprint Including Process-Level Calculation and Its Influencing Factors of Process for Low-Carbon and Sustainable Textile Industry

Abstract

Climate change stands out as a significant environmental issue on a global scale, with greenhouse gases being one of its primary drivers. The greenhouse gas process provides a critical framework for understanding the sources, emissions, and environmental impacts of these gases. This article presents an overview of the fundamental elements of the greenhouse gas process in the textile sector and discusses how it should be managed in line with sustainability goals. Carbon dioxide (CO₂), methane (CH₄), nitrous oxides (N₂O), and fluorinated gases are the most common greenhouse gases, each derived from different sources. The textile sector is particularly associated with high greenhouse gas emissions, especially in areas such as energy consumption, water usage, and waste management. Therefore, measurements taken in factories are crucial for identifying emission sources and developing reduction strategies. This article examines in detail the greenhouse gas emissions resulting from various activities at Kıvanç Textile. Energy consumption, particularly the emissions resulting from the fuels used in electricity and heating processes, is evaluated. Additionally, emissions from other important sources such as refrigerant gas leaks, waste management, and transportation are analyzed. The measurement process was carried out in accordance with national and international standards. The greenhouse gas inventory includes data on energy consumption, fuel consumption, refrigerant gas usage, transportation, production process management, and waste management throughout the factory. Based on these data, the total amount and sources of emissions were determined. This study presents a systematic method for calculating a company’s carbon footprint, with data collected in accordance with national and international standards. Such data can provide a reference point for other companies when making similar calculations. All of the businesses of the facility where the study was conducted were examined and calculations were made on a total of 1350 employees. As a result of the detailed study, Kıvanç Textile’s corporate carbon footprint for 2023 was calculated as a total of 68,746.86 tons ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$. According to this data obtained, Kıvanç Textile emitted 50.92 tons of ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$ greenhouse gases per employee. At the same time, it was determined that the production in 2023 was 4,427,082 tons and a greenhouse gas emission of 15.53 tons of ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$ per production (ton) was calculated. This study also includes proposed strategies for reducing emissions. These strategies include energy efficiency measures, the use of renewable energy sources, waste reduction, and the adoption of efficient production processes. In conclusion, this article emphasizes the importance of efforts to measure and reduce greenhouse gas emissions in textile factories. Kıvanç Textile’s greenhouse gas measurements provide a fundamental reference for achieving sustainability goals in the sector. The data obtained will support the factory’s efforts to reduce its carbon footprint and minimize its environmental impacts.

1. Introduction

Our planet is becoming increasingly sensitive to the impacts of global climate change. In regions like the Mediterranean Basin, a 2 °C increase in temperature could lead to severe consequences such as unexpected weather events, heatwaves, increased forest fires, drought, and loss of biodiversity. Since our country is located in this vulnerable region, it is likely to experience these effects directly.

According to the WWF-Turkiye’s “Turkiye’s Tomorrows Project Results Report”, the main impacts of climate change are as follows:

• Temperature increase is projected to remain limited until the end of the 2030s, but rapid escalation is expected thereafter.
• Seasonal and regional variations in temperature increase are anticipated, with winter temperatures potentially rising by around 4 °C and summer temperatures by about 6 °C compared to the 1960–1990 period.
• A general decrease in winter precipitation is expected, except for an increase in precipitation in the eastern part of Northern Anatolia.

The Climate Change National Action Plan published in 2011 predicts that Turkiye will experience a temperature increase ranging from 2.5 °C to 4 °C in the coming years. Specifically, it forecasts a temperature rise of 4 °C in the Aegean and Eastern Anatolia regions, and up to 5 °C in inland areas. This indicates that Turkiye will face a climate characterized by higher temperatures, increased aridity, and more uncertain rainfall patterns.

The Climate Change Action Plan predicts that Turkiye will be significantly affected by adverse effects such as reduced water resources, forest fires, drought, and desertification. Turkiye’s climate change policy is based on the premise that its industrialization efforts do not bear historical responsibility for the increase in greenhouse gas emissions in the atmosphere. Instead, it aims to participate in climate action within the framework of the “common but differentiated responsibilities” principle.

In our country, the largest share of the total ecological footprint, amounting to 46%, is attributed to the carbon footprint. The period between 1961 and 2007 saw the largest increase in the carbon footprint, with greenhouse gas emissions rising by 115% compared to 1990 levels, reaching 401.9 million tons in 2010. Per capita greenhouse gas emissions also increased during the same period, rising from 3.39 tons to 5.52 tons.

As of 2010, the energy sector accounts for 71% of Turkey’s total greenhouse gas emissions. The nation’s energy, transportation, industrial, and urban planning policies all represent its attempts to halt climate change. It should be underlined, nonetheless, that Turkiye’s climate policy has not yet sufficiently addressed the pressing nature of the climate change crisis.

Although Turkiye has been pursuing policies to effectively combat global climate change since the 1990s and became a party to the United Nations Framework Convention on Climate Change in 2004, it has not set any reduction targets even though the Kyoto Protocol was signed in 2009. The Paris cut was adopted at the 21st Conference of the Parties to the UNFCCC held in 2015 and stipulated that all countries would commit to reducing greenhouse gas emissions after 2020. However, Türkiye has not yet become a party as of 2016.

The Paris Agreement regulates the responsibilities of developed and developing countries in combating climate change. The agreement specifies how certain topics, including national contributions, financing, technology development and transfer, capacity building, mitigation, adaptation, loss/damage, transparency, and situation assessment, will be implemented. In this context, National Contribution Declarations, which include countries’ goals to combat climate change, play an important role. Türkiye has announced its Intended National Contribution Declaration with a target of up to 21% reduction by 2030.

Our country signed the Paris Agreement in 2016 and approved the agreement by completing the domestic law approval process in 2021. Additionally, the Presidency has declared a net zero emission target for 2053.

Kıvanç Textile is committed to conducting studies to control emissions, align with reduction targets, and calculate and reduce the greenhouse gas inventory. With this awareness, efforts are being made to take effective steps in the fight against climate change. The company places great importance on its work, aiming to be a pioneer in creating an environmentally friendly and sustainable industry. The general process steps of Kıvanç Textile production are shown in Figure 1.

They made statements that the reason for the increase in industrial carbon emissions in Liaoning Province was economic growth, and the main reason for the decrease was energy efficiency. In addition, it has been determined that large industrial countries have a positive impact on carbon emissions, but medium and low industrial countries are more effective in limiting carbon emissions [1]. They explained that the definition of what causes a carbon footprint can change globally, and that the most important data show how organizations, countries, and entire planets respond, and is an important first step in reducing carbon emissions in a quantitative way. It is foreseen that it may be possible to reduce the carbon footprint by investing in clean, low-carbon technologies such as alternative energy sources, and energy efficient and working lighting [2]. They stated that the production sector, which is completely closed to energy, is the most affected by the worldwide collapse of fossil fuels, climate temperatures, and the increase in carbon emissions. In their studies, for example, the textile production process, the product most recommended for sale abroad, was programmed for the carbon footprint and reduced in terms of energy efficiency and the use of green energy [3]. It has been discussed that the activities of the activities on the effects of textile preferred dyes and chemicals on human health, ecosystems, water, soil, and air emissions can be combined in a way that the sustainable growth activities of denim, which is an important area of the textile sector, can be significantly reduced and the product sustainability can be increased. Proliferation of sustainably renewable, environmentally friendly dyes contributes to the circular economy [4]. The sustainability of the textile regime has been attributed to the complexity and diversity of production and consumption in its management and distribution. Relationships with this factor have used methods such as life analysis evaluations, the density footprint, the eco-efficiency, and the Higg index for the sustainability of profitability. It has been emphasized that geographical distribution, product diversity, and technical complexity are the obstacles to the loss of sustainability (ES) of textile and ready-made clothing abundance [5]. It is the production, preparation, and operation of energy-intensive raw materials at points that provide serious storage in the production of carbon emissions. Many habits have been studied and analyzed. As a result, it was observed that the total cost increased by approximately 2% due to investments in green technology, but there was a significant decrease in the amount of carbon emissions of 23% [6]. The study investigated the temperatures relative to the carbon emissions of Chinese individuals’ green investments and the dynamic ranges between the two. It determined whether the company can reduce its carbon emissions per activity through such investments and how management decisions implement such initiatives. The research was conducted on samples from companies traded on the Shanghai and Shenzhen Stock Exchanges during the 2010–2020 period. The data were generated from platforms such as the China Stock Market and Accounting Research (CSMAR) and DIB. The payoff of the study shows that corporate carbon emissions can be reduced by increasing investments in exemplary green initiatives. It was also determined that quality of life, such as using the management sentiment ratio, plays a role when the links between life, corporate green investments, and carbon vulnerability reduction are strengthened. This study not only increases the theoretical understanding of the link between green investments and carbon emission reductions, but also enriches the theory of production. Importantly, it highlights the key role of management in encouraging sustainable investment choices to shine [7]. The carbon footprint and water footprint calculations of original polyester and recycled polyester textile products were made and compared in another study. It was calculated that the carbon footprint of original polyester production is 119.59 kgCO₂/100 kg, and the total carbon footprint of waste polyester recycling is 1154.15 kgCO₂/100 kg, approximately ten times greater than the original polyester textile production. It was stated that the terephthalic acid production process had the largest rate, at 45.83%, followed by the polyester fabric production process, ethylene production process, paraxylene production process, ethylene glycol production process, and polyester fiber production process [8].

In another study, the impact of factors such as the origin of imported machinery and equipment, the origin of imported materials, the management of industrial zones, and the presence of foreign direct investment companies on the environmental efficiency of the industry was evaluated. The results showed that the average score for environmental efficiency was 0.233 [9]. It has been emphasized that consumer actions, design solutions, and transparent data sharing are needed to implement CE strategies in polyester garments with maximum benefit, as they have the potential to alleviate the global environmental burden of textile products and the burden on circular economy (CE) strategies. It is predicted that by reducing the frequency of washing, the environmental impact will be reduced by 37%, and by reusing shirts, doubling the number of uses will reduce the impact by 18% [10]. In line with the European Union’s carbon neutral target in 2050, 27 member states examined the relationship between emissions and economic growth between 2008 and 2018. The need for improvements in energy efficiency and cleaner use of energy resources to achieve further reductions in greenhouse gas emissions has been emphasized. This would offset the potential increase in the industry’s emissions as a result of the relative increase in gross value added [11]. The study was conducted to highlight the problems caused by linear management in the textile sector, causing environmental damage and high amounts of post-consumer waste, and to indicate that the circular economy is a promising solution. An analysis was conducted on workwear using data collected from eight companies in Switzerland in 2019. According to estimates, it has been determined that 0.4 kg of workwear is consumed per person per year and an average of 1.6 kg of workwear is supplied per worker per year. In terms of waste management, 0.6 kg/year is reused, 0.7 kg/year is incinerated, and 0.3 kg/year is recycled [12]. Another study investigated the environmental sustainability of knit dyeing facilities associated with fast fashion production in Bangladesh. The assessment, using the Sustainable Apparel Coalition’s (SAC) Index Tool 2.0 and Higg’s Facility Environment Module (FEM), reveals the technical, managerial, and resource limitations of sustainable production approaches in knitted textile facilities and calls for greater attention from all stakeholders in the sector to reduce environmental impacts [13]. Another study investigated the impact of green industrial transformation in reducing carbon intensity in Pakistan between 1975 and 2020. The findings show that green industrial transformation plays an important role in reducing carbon emissions. However, it has been determined that foreign direct investment and technological innovations have increasing effects on carbon emissions. The study also predicts that environmental policies may have different impacts on carbon emissions over time, with these impacts predicted to increase from 2023, 2024, and 2028 to 2030, and decrease from 2025 to 2027 and 2031 [14]. Another study examined the relationship between temperature, time, and carbon content for the production of carbon fiber fabric from end-of-life cotton textiles. Optimum carbon fiber production requires over 90% carbon content at 1150 °C for 30 min. For lower grade carbon fiber, 80% carbon content at 650 °C for 30 min is sufficient. The research aimed to minimize energy requirements in textile recycling and support industries to achieve sustainable purchasing targets by reducing their carbon footprint [15]. With increasing population, urbanization, and industrialization, environmental problems, especially climate change, are rapidly emerging. Reducing greenhouse gas emissions plays a critical role in solving this problem. Carbon footprint calculation is an important tool in the fight against climate change and is of great importance in the industrial sector. Companies try to reduce their environmental impact by calculating their carbon footprint due to legal obligations, customer demands, and corporate image. This study provides an overview of greenhouse gas emissions, corporate sustainability, and carbon footprint calculation methods and shows how businesses can take steps in this regard [16]. It aims to discuss the relationship between the corporate carbon footprint (CFP) and sustainable supply chain. The literature review and analysis have revealed that CFP management is an important component of sustainable development. The research highlights the role of supply chain sustainability in reducing carbon emissions, particularly in the food, energy, and electricity sectors [17].

The aim of this study is to examine the possibility of determining the carbon footprint of consumers and producers of goods and services, which should be understood at the level of the state and producers, as well as raising awareness among the public about the need and culture of controlling and reducing carbon emissions for everyone [18]. The environmental impacts of the fashion industry are highlighted, such as 3.6 billion metric tons of carbon dioxide emissions annually, 342 million barrels of oil used in plastic-based fiber production, and 92 million tons of textile waste. These impacts contribute to major problems such as global warming and climate change. Research shows that effective Environmental, Social, and Corporate Governance (ESG) impacts companies’ overall profits by 60%. This study aims to explain the effects and nature of the fashion industry to consumers, encouraging them to make more informed purchasing decisions. It also explores in depth how sustainability practices impact the roles of governments, companies, and consumers, and the impact of the fashion industry’s business models on environmental sustainability. Finally, the research paper offers recommendations for companies to strengthen their environmental responsibility and improve their sustainability practices [19]. Research over 20 years reveals the following three main research areas: consumer behavior and sustainable clothing related to sustainability in the textile, apparel, and fashion industries, circular economy initiatives, and sustainability challenges across the entire supply chain. Gaps in the literature are highlighted and recommendations for future research are provided for each research area. As a result, this study guides researchers and academics working on sustainability, and aims to help businesses and managers understand sustainability trends and improve their business models accordingly [20]. Higher education institutions (HEIs) play a critical role in educating future leaders to create a sustainable system. In this study, Scope 1, Scope 2, and Scope 3 greenhouse gas emissions were calculated for the main urban campuses of Universidad Nacional de Colombia, Medellín. The carbon footprint in 2019 reached approximately 7250.52 tons of CO₂ equivalent. The biggest sources of emissions are the transportation process, wastewater process, electricity consumption, and sent emails. HEIs in Colombia exhibit the lowest tons of CO₂ per capita. The research is important as it is the first carbon footprint calculation made taking into account local conditions and offers a methodological contribution to the country’s higher education institutions [21]. Despite scientific and technological advances, the production activities of the textile industry have changed little compared to the original production systems, especially in poor and developing countries. This situation causes serious damage to the environment. The current research examines the textile production chain and the negative effects of each part on the environment. Additionally, by evaluating the problems in these processes from an ecological perspective, eco-responsible solutions that can be applied to increase sustainability have been investigated. This work aims to rethink traditional textile processes and make them more environmentally friendly [22]. Green production aims to reduce hazardous substances used in design, production, and technology processes. This approach covers a wide range of areas such as air, water, and soil pollution, energy use, and waste management. Carbon footprint calculations show that greenhouse gas emissions affect global warming. Green production is seen as an important tool to control greenhouse gas emissions in industries. This article will examine the application of green production in sectors such as transportation, electricity, and cement [23]. Its goal is to look at the institutional, organizational, and personal impediments that prevent enterprises in the European textile and apparel (T&C) industry from incorporating sustainability into their corporate plans. The approach is based on a case study of the environmentally conscious outdoor clothing manufacturer VAUDE. The findings are consistent with hypotheses put out by stakeholders and institutions to explain why businesses pursue sustainability. According to the investigation, there are persistent driving forces at all levels (individual, organizational, and institutional) that impact the integration of sustainability. Only at the institutional and organizational levels were barriers discovered. The results provide other T&C organizations significant practical implications for incorporating sustainability into their corporate strategy, as well as guidance on how to surmount possible obstacles to the successful integration of sustainability [24]. The article addresses the recent surge in carbon dioxide (CO₂) emissions, highlighting it as a major factor behind frequent extreme climate events. Accurate CO₂ emission data are essential for policymaking and setting reduction targets, especially for the electric power sector, which accounts for the largest share of emissions. The paper provides an overview of electricity carbon emissions accounting, distinguishing between direct emissions from electricity production and indirect emissions from electricity consumption. It reviews current methods used to account for these emissions, analyzes their limitations, and discusses advancements in improved accounting approaches. Finally, the article explores future prospects for carbon emissions accounting technology [25]. This research explores how economic uncertainty (EU) influences carbon emissions across Chinese provinces, using media data and the Latent Dirichlet Allocation method to develop a provincial EU index. Findings reveal that the EU significantly increases carbon emissions at the provincial level by hampering green innovation, reducing enterprise profits, and lowering carbon efficiency. Companies delay innovations, make cautious decisions, and opt for cheaper, environmentally harmful materials. Economic strength in a province reduces the impact of the EU on emissions, whereas foreign direct investment amplifies it. Developed areas better manage the EU’s negative effects, while foreign firms prioritize short-term gains over environmental concerns. The EU’s impact on emissions is notably strong in central and northeast China, but less so in the east and west. Sectors like transportation and industry are more affected than daily life activities. Additionally, the EU also influences emissions from neighboring provinces. The study suggests that these insights are relevant for other regions and countries and calls for policymakers to prioritize carbon emission management [26]. The primary aluminum industry (PAI), a major energy-intensive sector, ranks as the third largest source of greenhouse gas (GHG) emissions globally, with China as its top producer and consumer. This review examines low-carbon strategies and technological improvements for the PAI, emphasizing their potential, cost, and future prospects. Using a life cycle assessment (LCA) framework, the study estimates CO₂-equivalent emissions at 14.98 tons per ton of primary aluminum, compared to only 0.32 tons per ton of recycled aluminum, highlighting the vast emissions savings from recycling. With China’s emissions peak for the PAI set for 2030, key strategies include clean energy adoption, waste aluminum recycling, and low-carbon technology. The study recommends a phased approach, focusing on cost-effective technologies in the short term, power decarbonization and recycling in the medium term, and high-cost but impactful emission reduction technologies in the long term [27]. Global climate change, urbanization, and economic development necessitate sustainable practices and low-carbon strategies. This study focuses on the Beijing-Tianjin-Hebei (BTH) region, evaluating carbon neutrality rates from 2000 to 2019 and developing a Carbon Neutrality Simulation Model (CNSM) to identify optimal pathways for carbon neutrality. Findings show that carbon emissions initially rose and then stabilized, while carbon sequestration remained largely unchanged, leading to a decrease in the carbon neutrality rate. Under the baseline scenario, the region fails to meet the “dual carbon” targets, with emissions projected to grow through 2060. However, industrial restructuring demonstrated the greatest carbon reduction potential among single-factor scenarios, and multi-factor scenarios achieved peak emissions by various years, with the high-constraint scenario reaching the carbon neutrality target. These results offer scientific guidance for achieving carbon neutrality and advancing regional sustainability in the BTH region [28]. This study analyzes the carbon emission reduction potential of China’s major industries under the IPCC’s 2 °C and 1.5 °C global warming limits. It assesses key sectors, examining their capabilities and strategies to align with these targets, which are crucial for climate mitigation. The research identifies potential pathways, focusing on energy-intensive industries like steel, cement, and power generation. Findings suggest that significant emissions cuts are achievable through advanced technology, energy efficiency improvements, and the adoption of cleaner energy sources. The study highlights the importance of sector-specific strategies and provides insights into how each industry can contribute to China’s overall emissions goals within the 2 °C and 1.5 °C frameworks [29]. This study estimates greenhouse gas (GHG) emissions from Iraq’s energy industry, specifically focusing on oil refining and electricity generation, by applying IPCC methodologies. It calculates emissions based on fuel types, consumption rates, and industry-specific factors, providing a detailed account of CO₂, CH₄, and N₂O emissions. The findings reveal that Iraq’s energy industry is a major contributor to national GHG emissions, with oil refining and electricity generation as the primary sources. Using the IPCC guidelines enables accurate emissions estimation, helping policymakers understand the industry’s environmental impact and identify potential areas for reduction. The study underscores the importance of transitioning to cleaner energy sources and improving efficiency to reduce Iraq’s carbon footprint in alignment with international climate targets [30]. Environmental damage and global warming are seriously triggered by the textile and fashion industries. Clothing purchases have increased as consumer habits have changed, which has increased the use of environmentally harmful chemicals. The textile production process produces large amounts of toxic waste and greenhouse gases, so sustainability strategies are gaining importance [31].

Environmentally friendly textiles, ecolabeling, and sustainability standards are changing both consumer and producer behaviors. Sustainable production practices and developing expertise in the design process are critical for a more sustainable textile industry. This article explores environmentally friendly textiles and ecolabeling requirements, and the importance of sustainability expertise in the design process [32]. As the demand for sustainable products increases, ecolabels are a useful tool for environmentally conscious consumers. However, the diversity of ecolabels and the lack of harmonization in evaluation methods can hinder their effectiveness. This article examines the evaluation methods used by ecolabels in the textile and clothing industry. Using 10 ecolabel examples from the Ecolabel Index, a new framework for classifying ecolabels is proposed. The framework includes two categories of label assignments and six types of evaluation methods. This framework provides a roadmap to ensure consistent performance and traceability in ecolabeling. Consequently, this framework can be extended to enable the classification of other ecolabels [33]. The Carbon Border Adjustment Mechanism (CBAM) attempts to guarantee adherence to EU environmental standards by industrial sectors that operate outside the EU. By estimating the carbon footprint of products and services imported into the EU, this mechanism adjusts for carbon. The transition phase will start in 2023 and will be completed in 2025. The textile industry consumes large amounts of energy in the production process and contributes to greenhouse gas emissions. This study evaluates the environmental impacts of two synthetic products (polyester and polypropylene) using the “cradle to customer plus waste” life cycle assessment (LCA). Monte Carlo analysis was used to evaluate uncertainties in LCA calculations. Findings based on real data show that the carbon footprint of polyester is 13.40 t-${\mathrm{C}\mathrm{O}}_2\mathrm{e}$q (t PES)-1, while that of polypropylene is 6.42 t ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$q (t PP)-1. Polypropylene yarn has been found to have a lower carbon footprint and is more environmentally friendly. These results can be used to develop policies aimed at reducing greenhouse gas emissions and provide guidance for the production of synthetic yarn [34]. The environmental impacts of the fashion industry have raised widespread concerns. Globalization has led to the fragmentation of the textile and fashion system and the unequal distribution of environmental resources. Denim production has been evaluated especially in terms of carbon and water footprints. Between 2001 and 2018, carbon emissions in global denim trade increased from 14.8 Mt ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$ to 16.0 Mt ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$, while water consumption increased from 5.6 billion m³ to 4.7 billion m³. It has decreased to billion m3. Denim fabric production and cotton fiber production make the biggest contribution to carbon emissions and water consumption. Polyester blend denim has a 5% larger carbon footprint than cotton denim, but a 72% lower water footprint. While carbon and water flows in global denim trade have shifted in the last twenty years, developed countries have shifted production to developing countries. Climate-related risks and water crises are increasing. South–South cooperation can help reduce resource consumption and environmental emissions. Denim production and consumption should be shifted to sustainable and circular ways and new business models should be developed [34]. An essential instrument for evaluating an organization’s ecological consequences and directing sustainability initiatives is the Urban Carbon Footprint (UCF). The UCF for Sarıçam Municipality (SM), Adana Province, Turkiye, was calculated in this study for the year 2022. The following are factored in: staff travel, customer and visitor emissions, business travel, electricity usage, generator fuel consumption, refrigerant gas leakage, car fuel consumption, and emissions from purchases. SM’s total UCF in 2022 is estimated to be 10,862.46 tons ${\mathrm{C}\mathrm{O}}_2\mathrm{e}$q. The goal of this study is to limit greenhouse gas emissions in order to give SM a foundation for their reduction efforts [35]. In this study, a multihead attention-based convolutional neural network (MHA-CNN) model is proposed for the multi-objective prediction of CO₂ emission performance indices (CEPIs) and industrial structure optimization [36].

The province of Adana’s major district is Seyhan. The district’s socioeconomic structure is influenced by the regional and geographical structures. Seyhan has a young, vibrant population that is generally densely populated. One of the key elements influencing the socioeconomic structure of the district is the average age and educational attainment of the populace. The district’s economy is composed on the trade, industry, service, and agricultural sectors. The production of fruits and vegetables, in particular, can play a significant role in the district’s economy. Additionally, production takes place in both small- and large-scale industrial zones across a variety of sectors. In Seyhan, jobs are mostly found in the industrial, agricultural, and service industries. Employment in the agriculture sector is significant, particularly in rural areas. Due to the district’s manufacturers and production facilities, the industrial sector generates jobs. In Seyhan, health care and education are very important. The district’s residents’ socioeconomic circumstances are influenced by the schools and medical facilities that are located there. Transportation is provided by the TEM Highway in the north, the D400 Highway in the south, and the Airport Connector Road, which passes through the district center. Adana Central Bus Terminal and Adana Şakirpaşa Airport are also located in the Seyhan neighborhood. The localization of Kıvanç Textile business and Seyhan District is depicted in Figure 2.

Rapidly increasing industrialization and technological developments have caused many positive and negative factors depending on energy demand. The development of the world, the development of information systems, and the rapid learning of human beings are some of the positive factors. However, despite all of the positive factors, this process causes serious and irreversible destruction and damage. The rapid increase in energy demand, the unabated production frenzy, and the acceleration of consumption have deteriorated the greenhouse gas concentration in the atmosphere. In order to leave a cleaner and more livable world to future generations, this destruction must be slowed down and then stopped completely. Important steps are being taken around the world, led by some developed countries. As a result of these steps, the existing damage must first be identified and then action plans must be created and implemented.

The “Climate Change Action Plan” research’s initial step, the calculation of the greenhouse gas inventory, is included in this study. The creation of the inventory was predicated on the reference year (2023), which is a necessary component of any mitigation action plan. The primary result of this study will be the Greenhouse Gas Inventory that was computed in order to prepare the Sustainability Report and Climate Change Action Plan for Kıvanç Textile Factory. The first step in creating the Climate Change Action Plan is figuring out Kıvanç Textile company emissions. In this case, the Carbon Footprint Inventory was made and business emissions were first recorded and assessed in accordance with international norms. Additionally, this inventory will serve as a helpful starting point for recalculating emissions and tracking reductions in relation to predetermined goals.

This is why the Seyhan district of Adana province’s Kıvanç Textile campus greenhouse gas inventory was calculated for this study. Using the estimates performed for this study, Kıvanç Textile intends to control greenhouse gas emissions, laying the groundwork for future reduction efforts. The following points summarize this article’s primary contributions:

• A detailed Greenhouse Gas Emission Inventory was created, which was included in Scope 5, and detailed emission amounts were calculated for all processes in the factory, thus ensuring the sustainability of all units.
• By analyzing this detailed emission report, it has been determined at which stage and process the emissions are excessive, and the prioritization planning of places with emission reduction potential will be made more easily.
• This detailed study will make a positive contribution to the fight against emissions by increasing awareness of the importance of environmental impacts in similar sectors.
• By giving a comprehensive understanding of the organization’s resource consumption, emissions, and energy use, the study will encourage accountability and transparency.
• The outputs of this detailed study will contribute to controlling emissions and achieving the climate-neutral target in the future.
• These study outputs will contribute to Kıvanç Textile’s sustainability process and reporting process.

2. Materials and Methods

The inventory of greenhouse gas emissions resulting from all activities at Kıvanç Textile’s main campus in the Seyhan District of Adana province between 1 January 2023, and 31 December 2023, falls under Scope 1, Scope 2, Scope 3, and Scope 5 of this study. The following factors are taken into account in the calculations: fuel used in company-owned or controlled vehicles, electricity and natural gas consumption, generator fuel consumption, leaks and fillings caused by these activities, fuel from production, emissions from operation, and emissions from personnel travel, customers and visitors, business trips, purchases, etc. Emissions from the transit of waste and emissions from goods purchased are included. Included are emissions from the transit of trash and emissions from items that have been acquired. The greenhouse gases CO₂, CH₄, and N₂O were utilized to evaluate emissions within the inventory’s bounds, and the emissions of CH₄ and N₂O were presented using CO₂ equivalent units. This report was prepared using the ideas presented in TSE Greenhouse Gases—Part 1: Guidelines and standards for estimating and reporting greenhouse gas emissions and removals at the organizational level [37].

2.1. Scope of Emission Sources

The scope approach aims to simplify the process of reporting and computing emissions. For this computation period and report, the organization’s emission sources fall within Scope 1, Scope 2, Scope 3, Scope 4, and Scope 5. Figure 3 displays the elements of the business carbon footprint as established by the scopes of the Greenhouse Gas (GHG) Protocol.

2.1.1. Scope 1: Direct Greenhouse Gas Emissions

This includes the quantity of greenhouse gases emitted straight from sources that an institution owns or controls. Scope 1 includes activities including process emissions, fugitive emissions, stationary combustion, and mobile combustion emissions for SM. It consists of greenhouse gas emissions from the burning of fuel in automobiles, emissions from company-funded cars, emissions from the burning of fuel in generators used for office and technical tasks, and emissions from the filling or leakage of refrigerant gas.

2.1.2. Scope 2: Indirect Greenhouse Gas Emissions from Imported Energy

This includes greenhouse gas emissions from the generation of heat, steam, or electricity that is purchased from outside sources and used by an organization. Since SM controls all of its activities related to power usage in the study’s covered sites, these operations fall within the establishment’s borders.

2.1.3. Scope 3: Indirect Greenhouse Gas Emissions from Transportation

The origins of these pollutants are not inside the organization’s walls. These are mobile sources, and the primary cause of emissions is fuel combustion in transportation machinery. The emissions that come from employees traveling to and from work, clients and visitors being transported, and business travel are all included in Scope 3 emissions for SM.

2.1.4. Scope 4: Indirect Greenhouse Gas Emissions from Products Used by the Organization

These emissions are greenhouse gas emissions that originate from emission sources beyond the organization’s borders and are connected to the products the company uses. These sources, which cover all product categories that the reporting organization has bought, might be stationary or mobile. Scope 4 emissions relate to purchased completed goods, semi-finished goods, raw materials, and other items used by SM in the product’s manufacture. It is made up of solid and liquid trash as well as emissions from wastewater.

2.1.5. Scope 5: Emissions and Removals from Use of the Product

Products sold by the organization during the life stages that follow the organization’s manufacturing process are the source of greenhouse gas emissions linked to the usage of products owned by the organization. Under this category, greenhouse gas removals are also assessed.

2.2. Calculation Methodology

The basic method used to calculate the greenhouse gas emissions from the activities carried out by SM in the locations evaluated under the scope of this inventory between 1 January 2023 and 31 December 2023 was to multiply the designated activity data by the applicable emission factors. A method was chosen to lessen outcome uncertainty and generate accurate, dependable, and adaptable results based on the activity data that was available. As a result, the Tier 1 approach described in the Uncertainty Management in National Greenhouse Gas Inventories and the 2006 IPCC Good Practice Guidelines was applied. Since CO₂ emissions resulting only from energy consumption were estimated using the national emission factor (EF) obtained from foreign sources, the Tier 2 approach was applied.

The unit used to express emission factors is the carbon dioxide equivalent (CO₂-eq). The greenhouse gas emissions of N₂O, CH₄, and CO₂ are measured individually and converted to the CO₂ equivalent. Each greenhouse gas’s ability to cause global warming is increased by its emission quantities during this cycle.

Table 1. Global warming potentials [38].

Greenhouse Gas	GWP for 100 Years
Carbon dioxide (CO2)	1
Methane (CH4)	27.9
Nitrous oxide (N2O)	273
R407C	973.016
R22	1960
R32	771
R134 A	1530
R410 A	2255.5
SF6	24,300
R600 A	0.006

displays the greenhouse gases assessed for this inventory as well as the Global Warming Potentials (GWPs) that were employed. Table 1 provides a detailed list of the emission calculation techniques for stationary and mobile combustion sources. A detailed explanation of the emission computation methodologies for rectified emissions originating from greenhouse gas leaks in anthropogenic systems may be found in

Table 2. A list of the sources of greenhouse gas emissions in 2023.

Greenhouse Gas Emission Source	Category	Activity	Calculation Method
Generator (Diesel)	1	Electricity generation	Multiplication of the emission factors with activity data (IPCC Tier 1)
Boiler (Natural Gas-LPG)		Heating/electricity
Refrigerant Gas Leaks (Air Conditioner Refrigerator, Dispenser)	1	Cooling systems—office coolers and refrigerators	Multiplication of the leakage gas rates by the global warming potentials (GSPs)
Refrigerant Gas (Air Conditioner Filling)	1	Cooling systems—office coolers	Multiplication of the gas filling rates by global warming potentials (GSPs)
Gas Filling (Fire Tube)	1	Fire tube filling	Multiplication of the gas filling rates by global warming potentials (GSPs)
Fire Tube Leaks	1	Fire tube	Multiplication of the leakage gas rates by the global warming potentials (GSPs)
Diesel—vehicles	1	On-road/off-road vehicle fuel consumption	Multiplication of the emission factors with activity data (IPCC Tier 1)
Electric	2	Building operating system—burning for heating, cooling, lighting purposes	Multiplication of the emission factors with activity data (IPCC Tier 1)
Diesel	3	Emissions from combustion for personnel transportation	Emission factors multiplied by activity data (IPCC Tier 1)
Transportation and Accommodation Data	3	Emissions from transportation of customers and visitors	Emission factors multiplied by activity data (IPCC Tier 1)
Transportation and Accommodation Data	3	Emissions from business travel	Multiplication of the emission factors with activity data (IPCC Tier 1)
Emissions Arising from the Transportation or Distribution of Goods Arriving at the Organization	3	Transport emissions	Multiplication of the emission factors with activity data (IPCC Tier 1)
Purchased Products	4	The purchased raw material/finished product/semi-finished product, etc., which is associated with the manufacture of the production of emissions	Multiplication of the emission factors with activity data (IPCC Tier 1)
Solid and Liquid Waste Transportation	4	Emissions from the disposal of solid and liquid wastes	Multiplication of the emission factors with activity data (IPCC Tier 1)
Consultancy	4	Emissions from the purchase of consulting services	Multiplication of the emission factors with activity data (IPCC Tier 1)
Emissions and Removals Caused by the Use of the Product	5	Sold products and emissions and removals from GES sources	Multiplication of the emission factors with activity data (IPCC Tier 1)

. The technique and emission parameters for electrical emissions are provided in

Table 3. Electricity consumption amounts in 2023.

Months (2023)	Factory Electricity Production	Tedaş	Cogeneration	Pmum Sales	Total Energy
January	3,211,931	2,398,145	814,390	605	3,212,535
February	2,452,303	2,207,293	246,389	1380	2,453,682
March	3,643,305	3,142,238	504,847	3780	3,647,085
April	2,409,228	1,627,063	797,698	15,533	2,424,761
May	2,977,500	1,971,705	1,016,568	10,773	2,988,273
Jun	2,419,051	2,343,600	84,315	8864	2,427,915
July	2,517,411	622,490	1,910,551	15,630	2,533,041
August	2,858,778	725,004	2,147,231	13,457	2,872,235
September	2,953,682	808,372	2,160,543	15,233	2,968,915
October	2,834,959	579,115	2,276,615	20,771	2,855,730
November	2,889,797	1,484,482	1,408,906	3591	2,893,388
December	2,473,448	1,574,986	907,326	8864	2,482,312
Total	33,641,391	19,484,493	14,275,379	118,481	33,759,872

. The calculation technique and emission factors for indirect greenhouse gas emissions from transportation are provided in

Table 4. Natural gas consumption in 2023.

Kıvanc Natural Gas Consumption in 2023 (sm3)
Months	Electricity Generation	Dyeing Part Steam + Process	Kitchen	Total
January	196,717	167,969	5198	369,884
February	62,991	159,757	4435	227,183
March	147,344	259,208	4226	410,778
April	211,483	203,921	3779	419,183
May	276,785	203,924	4642	485,350
June	26,052	161,997	3789	191,837
July	538,693	183,912	4635	727,240
August	566,932	175,994	4834	747,760
September	598,841	267,539	4968	871,349
October	613,714	214,795	4665	833,174
November	379,702	363,714	4088	747,504
December	234,471	187,248	3761	425,479

.

Within the scope of this study, Table 2 lists the sources of greenhouse gas emissions over the period computed and reported for 2023.

3. Results

UCF is a method for calculating and assessing how an organization’s operations affect the environment. This computation takes into account the energy usage, waste handling, greenhouse gas emissions, and other environmental aspects of the company. Scoping, data collecting, emissions calculation, reporting and monitoring, mitigation, and improvement initiatives are the fundamental steps in this process. The quantities of greenhouse gas emissions and other environmental parameters are calculated using the data that have been gathered. Metric tons are used to express carbon emissions. Table 3 displays the amount of power consumed in 2023. The relevant department’s data collection and provision is treated as kWh and is incorporated into the computations. The distribution of electricity supply in 2023 is detailed in Figure 4, and the distribution of electricity consumption in 2023 by months on an annual basis is detailed in Figure 5.

Natural gas consumptions are detailed monthly in Table 4. The monthly distribution is detailed in Figure 6.

The refrigerant gas consumptions we used in the calculations within the scope of Scope 2 are shown in

Table 5. The refrigerant gas consumptions in 2023.

The Name of the Gas	The Amount of Consumption (ton)
R407 C	0.0672
R22	0.0272
R32	0
R134 A	0.0544
R410 A	0.03405
R134 A	0
SF6	0
R600 A	0
CO2	0.425

. Percentage distributions are given in Figure 7.

The emission amounts resulting from raw materials purchased for production are shown in

Table 6. The emission amounts from raw materials purchased for production in 2023.

Source of Greenhouse Gas Emissions	Activity Data	Unit	Value	Unit	${\mathbf{C}\mathbf{O}}_2\mathbf{e}$ (ton)	%
Domestic Water	341,218.00	m3	0.177	kg CO2 equivalent/m3	60.40	0.444
Cotton	5303.54	kg	11.612	kg CO2 equivalent/m2	61.58	0.453
Polyester	1,400,481.71	kg	5.626	kg CO2 equivalent/m2	7879.05	57.944
Wool	226,008.10	kg	3.241	kg CO2 equivalent/m2	732.46	5.387
Viscose	742,704.90	kg	5.626	kg CO2 equivalent/m2	4178.43	30.729
Chemical (inorganic)	19,930.85	kg	1.875	kg CO2 equivalent/kg	37.36	0.275
Chemical (organic)	83,466.77	kg	2.018	kg CO2 equivalent/kg	168.46	1.239
Chemical (other)	18,600.00	kg	1.292	kg CO2 equivalent/kg	24.04	0.177
Food	554,289.25	USD	0.816	kg CO2 equivalent/USD	452.16	3.325
Cleaning	7045.82	USD	0.539	kg CO2 equivalent/USD	3.80	0.028
				Total	13,597.74	100

. Product-based distributions are also shown in Figure 8.

Table 7. Fuel consumption in 2023.

	liter	kg/m3	kg	ton
Onroad	85,002.00	845	71,826.69	71.82669	diesel
Offroad	178,131.00	845	150,520.70	150.52070	diesel

displays the fuel and diesel consumptions for generators and SM off-road and on-road vehicles.

Consumption and carbon emissions resulting from the products produced and sold by the facility are shown in

Table 8. Consumption and carbon emissions resulting from the products produced and sold by the facility in 2023.

Source of Greenhouse Gas Emissions	Activity Data	Unit	Value	Unit	Value (tons)
FABRIC (cotton)	66,4062.3	kg	11.6118	kg CO2/kg	7710.95862
FABRIC (polyester)	1,992,186.9	kg	5.62596	kg CO2/kg	11,207.9638
FABRIC (wool)	442,708.2	kg	3.24087	kg CO2/kg	1434.75972
FABRIC (viskon/viscose)	1,328,124.6	kg	5.62596	kg CO2/kg	7471.97587

.

Table 9. Greenhouse gas emissions related to 5 headings calculated within the scope of the prepared inventory.

Scope 1
Emissions	CO2	CH4	N2O	Total (CO2e)
1.1	12,973.16	31.9	6.24	13,011.30
1.2	708.47	1.09	53.52	763.08
1.4	828.8947	-	-	828.89
Scope 1 Total	14,510.52	32.99	59.76	14,603.27
Scope 2
Emissions	CO2	CH4	N2O	Total (CO2e)
2.1	8553.69	-	-	8553.69
Scope 2 Total	8553.69	-	-	8553.69
Scope 3
Emissions	CO2	CH4	N2O	Total (CO2e)
3.1	533.63	-	-	533.63
3.3	334.98	0.02	0.02	335.02
3.4	2.78	0.03	1.763	4.57
3.5	9.8	0.09	11.02	20.91
Scope 3 Total	881.19	0.14	12.803	894.13
Scope 4
Emissions	CO2	CH4	N2O	Total (CO2e)
4.1	16,851.87	0	0	16,851.87
4.3	11.5	-	-	11.50
4.5	2.65	-	-	2.65
Scope 4 Total	16,866.02	-	-	16,866.02
Scope 5
Emissions	CO2	CH4	N2O	Total (CO2e)
5.1	27,825.66	-	-	27,825.66
Scope 5 Total	27,825.66			27,825.66

displays greenhouse gas emissions associated with five categories that were determined as part of the prepared inventory. The CO₂-eq distribution by five scopes is seen in Figure 9.

As a result of the study, carbon emission measurements were made in five categories and the data were calculated. As a result, it was revealed that Category 5 caused the highest carbon emissions and Category 3 caused the lowest carbon emissions. Studies can be started based on the fact that the emissions caused by production significantly increase the overall emissions of the factory, and that the raw materials used can be controlled; studies can also be started on the use of raw materials that will cause lower emissions. It is also foreseen that emissions can be reduced with renewable energy supplements for Category 1 and Category 2.

For every emission source, the uncertainty levels for the emission components in Kıvanç Textile’s Greenhouse Gas Emission Inventory Report for 2023 have been computed independently. All of the data used in the calculations—aside from the levels of refrigerant gas leakage—were derived from the current bills. For every category, the proportion of uncertainty activity data (C) has been established at 5%. For every category, the percentage of uncertainty emission factor (F) has been established at 10%. The calculated emission uncertainty percentage (I) is determined by the equation I = √(C² + F²). The first auxiliary variable (K) is obtained by multiplying the I value with the tCO₂e value of the corresponding category. The second auxiliary variable is calculated as K2. Finally, the uncertainties are calculated as a percentage and the data in

Table 10. Distribution of 2023 emissions by the scopes.

Source of Greenhouse Gas Emissions		Data Type	Total (CO2e)	CO2	CH4	N2O
1	Category 1: Direct greenhouse gas emissions and removals (CO2e)		14,603.56	14,510.52	32.98	60.07
1.1	Direct greenhouse gas emissions from stationary combustion	Primary	13,011.29	12,973.16	31.90	6.24
1.2	Direct greenhouse gas emissions from mobile combustion	Primary	763.37	708.47	1.09	53.82
1.4	Direct greenhouse gas emissions from the leakage of greenhouse gases in anthropogenic systems	Primary	828.89	828.89	0.00	0.00
2	Category 2: Indirect greenhouse gas emissions from imported energy		8553.69	8553.69	0.00	0.00
2.1	Indirect greenhouse gas emissions from imported electricity	Primary	8553,69	8553,69	0.00	0.00
3	Category 3: Indirect greenhouse gas emissions from transportation		897.92	881.19	0.13	12.80
3.1	Emissions from transportation or distribution of goods (into the organization).	Secondary	533.63	533.63	0.00	0.00
3.3	Greenhouse gas emissions from staff commuting to work	Secondary	340.29	334.98	0.02	0.02
3.4	Greenhouse gas emissions from transportation of customers and visitors	Primary	3.10	2.78	0.03	1.76
3.5	Greenhouse gas emissions from business travel	Primary	20.91	9.80	0.09	11.02
4	Category 4: Indirect greenhouse gas emissions from products used by the organization		16,866.02	16,863.36	0.00	0.00
4.1	Greenhouse gas emissions from purchased raw materials/finished products/semi-finished products associated with the manufacturing of the product	Primary	16,851.87	16,851.87	0.00	0.00
4.3	Greenhouse gas emissions from the disposal of solid and liquid waste	Primary	11.50	11.50	0.00	0.00
4.5	Consultancy, cleaning, maintenance, courier, banking, etc., emissions from service procurement	Primary	2.65	2.65
5	Category 5: Indirect greenhouse gas emissions from post-production use of products		27,825.66	27,825.66	0.00	0.00
5.1	Emissions and removals due to use of the product	Primary	27,825.66	27,825.66
Total:			68,746.86	CO2e (Ton)
Per person (1350)			50.92	CO2e (Ton)
Per Production (4,427,082 kg)			15.53	CO2e (Ton)

are obtained. The cumulative total uncertainty percentage is also calculated by the following Equation (1):

$$\mathrm{Cumulative}\mathrm{Total}\mathrm{Uncertainly}=\pm {\displaystyle \frac{\sqrt{{\displaystyle \sum _{i=1}^n(tCO2e_i\ast I_i}{)}^2}}{tCO2e*}}$$

(1)

where ∗ symbolizes the total t CO₂e.

The total uncertainty ratio based on the whole category, subcategory, and cumulative is given in

Table 11. Distribution of 2023 emissions by scopes.

Category-Based Uncertainty Calculation
Category	The Value of Uncertainty
1	9.36%
2	11.18%
3	7.88%
4	6.12%
5	11.18%
Uncertainty Calculation Based on Subcategory
Subcategory	The Value of Uncertainty
1.1	11.18%
1.2	8.49%
1.4	5.64%
2.1	11.18%
3.1	11.18%
3.3	11.18%
3.4	11.18%
3.5	7.42%
4.1	6.12%
4.3	11.18%
4.5	11.18%
5.1	11.18%
Cumulative Sum of Uncertainty
5.32%

. The Greenhouse Gas Uncertainty Calculation Document was used.

In the report, materiality assessment was made for Category 3, Category 4, and Category 5. The size of greenhouse gas emissions, data quality, reduction, industry specificity, target user expectations, and risks and opportunities were evaluated and the risk impact size was determined. This determined risk is categorized as “significant” and “not significant” in

Table 12. Table of materiality for the year 2023.

Category	Definition of Emission	Degree of Importance
3.1	Emissions arising from the transport or distribution of goods (arriving at the organization)	Important
3.3	Greenhouse gas emissions caused by personnel’s commutes to and from work	It will not matter
3.4	Greenhouse gas emissions from the transportation of customers and visitors	It will not matter
3.5	Greenhouse gas emissions from business trips	It will not matter
4.1	The purchased raw material/finished product/semi-finished product, etc., which is associated with the manufacture of the production of greenhouse gas emissions	Important
4.3	Greenhouse gas emissions from the disposal of solid and liquid wastes	It will not matter
4.5	Consulting, cleaning, maintenance, courier, banking, etc., emissions from service purchases	It will not matter
5.1	Emissions and removals caused by the use of the product	Important

according to the effect size. Since 2023 is the base year, Category 3.3, Category 3.4, Category 3.5, Category 4.3, and Category 4.5 data, which are “not important”, are included in the calculation for Kıvanç Textile. The Greenhouse Gas Materiality Determination Document was used.

4. Discussion

Within the scope of the detailed inventory study, all data in the five categories were examined together with their evidence and greenhouse gas emission calculations were made. As a result of the calculations, it was determined that the highest emissions were in Categories 5, 4, and 1, respectively. While determining targets for carbon neutrality, data in this category were examined and action plans were prepared accordingly.

Since the facility where the study was conducted is a large-scale industrial establishment, its consumption is very high, there is a constant circulation, and the number of employees is high, which are among the other reasons for the high amount of greenhouse gases. In Category 1, a significant amount of emissions has been calculated resulting from the energy consumed in the facility. Implemented energy efficiency projects, process improvements, and instantaneous energy consumption monitoring will contribute to limiting these emissions. In Category 4, high emissions were calculated due to the raw materials used in the production processes at the facility. Projects such as selecting raw materials, controlling the amount of waste and wastage, using more efficient processes, and reducing chemical consumption will help limit these emissions. In Category 5, the emission amounts resulting from the products sold as a result of the production of the facility were calculated. It is not possible to take action regarding this process during this period. The flow diagram details of Kıvanç Textile production steps for the areas used in the calculations are shown in Figure 10.

After the inventory is prepared, efforts will be made to reduce emissions in the facility. In Turkiye, we are a party to the green agreement and the Paris Agreement, so reducing emission processes is very important. In Turkiye, where energy demand is increasing significantly and consumption records are being broken day by day, energy efficiency, green energy conversions, and renewable energy investments will make a significant contribution to reducing greenhouse gas emissions. In this framework, Kıvanç Textile is envisaged to make renewable energy investments and energy efficiency studies. Turkiye plans to enact the Climate Law in 2024, reducing greenhouse gases and promoting green energy within the framework of respect for nature and humanity. Kıvanç Textile also contributes to this process by determining sustainability targets for this purpose. The goals in question are as follows:

• Making new solar energy investments.
• Creating a Kıvanç Textile Climate Change Action Plan for 2024–2026.
• Keeping energy consumption under control with energy efficiency projects.
• Providing awareness training to blue-collar and white-collar workers.
• Carrying out studies to prepare projects to reduce the use of secondary energy resources.

The average per capita emissions must be significantly reduced in order to meet the Paris Agreement’s goal of keeping the rise in global temperature to 1.5 °C or less by 2050. By 2030, the goal is to bring down per capita emissions to about 2 tons of CO₂e per person. To achieve this challenging goal, nations, corporations, and people everywhere must work together to develop low-carbon economies, embrace renewable energy sources, boost energy efficiency, and introduce sustainable practices across a range of industries. In order to mitigate the impacts of climate change and protect the earth for coming generations, this aim must be accomplished. The study’s conclusion is that the total carbon footprint for Kıvanç Textile in 2023 was 68,746.86 tons of CO₂e. Furthermore, the facility employs 1350 people, and the carbon footprint of each employee is estimated to be 50.92 tons CO₂e based on the data that were analyzed. If we need to compare the production, the production in 2023 was 4,427,082 kg, which is equivalent to 15.53 tons of CO₂e at the start of production.

5. Conclusions

In this study, a detailed examination of the greenhouse gas emissions resulting from the activities of the Kıvanç Textile company, located in the Seyhan District of Adana Province, between 1 January 2023, and 31 December 2023, was made, an inventory list was prepared, and the emission amount was calculated. All of the businesses of the facility where the study was conducted were examined and calculations were made on a total of 1350 employees. As a result of the detailed study, Kıvanç Textile l’s corporate carbon footprint for 2023 was calculated as a total of 68,746.86 tons CO₂e. According to these data obtained, Kıvanç Textile emitted 50.92 tons of CO₂e greenhouse gases per employee. At the same time, it was determined that the production in 2023 was 4,427,082 tons and a greenhouse gas emission of 15.53 tons of CO₂e per production (ton) was calculated. Reduction targets for greenhouse gas emissions can be created and action plans can be taken by using the inventory list prepared in the light of these data. Thanks to the detailed nature of the study, emissions were detected at the source and an opportunity was provided to take action at the source. This study will contribute to Kıvanç Textile’s sustainability process in the future and will be a pioneer in the preparation of the Sustainability Report.