Life-Cycle Assessment as a Next Level of Transparency in Denim Manufacturing

Abstract

Increased consumer awareness and new regulations about climate change accelerated the need for solid, provable, transparent actions leading to results to support the sustainability claims and initiatives of fashion brands. However, progress on transparency is still very limited despite the alarming signals of climate change. As stated in Fashion Revolution’s Transparency Index 2023, brands have achieved an overall average score of 24%, up 1% from last year. Transparency is a tool for transformation. A productive conversation toward the targets can only start with a certain level of transparency to lead to the desired change. Life cycle assessment (LCA) methodology represents the next level of transparency. LCA can help brands collect, analyze and monitor their sustainability performance with science-based results. It is a tool that is used to quantify the environmental performance of a product taking the complete life cycle into account (from raw material production to transport, fabric production, garment manufacturing, consumer use, and final disposal. This book chapter focuses on how brands can use LCA as a transparency tool, its advantages and challenges in generalizing the science-based data. A framework will be generated on how to build the LCA model and use the data to compare different products and production practices in denim industry.

1. Introduction

As UN Secretary-General António Guterres said at Conference of the Parties (COP) on November 20th, 2022, the world should take more action to drastically reduce emissions immediately [1]. Unfortunately, action to transform the business practices continues to stay incremental, including the ones in the fashion industry. According to the Business of Fashion Sustainability Index 2022, the biggest players in the industry are still moving too slowly to achieve the set targets by 2030 [2]. Fashion brands need to measure their social and environmental impact continuously and act vigorously to decrease them. Consumer communication remains vital in this process with a certain level of transparency to lead to the desired change. However, “Green Washing” appears as a threat to real action as marketing activities without any solid and provable data become common practices for many brands in the fashion industry.

Life cycle assessment (LCA) methodology serves as a solution to “Green Washing” and represents the next level of transparency since LCA can help brands collect, analyze and monitor their sustainability performance with science-based results. Sustainable fibers and certified materials occur to be the most important choice for brands who would like to have green claims [3]. Although materials represent a significant role in the calculation of overall environmental impact of the products, other input and process parameters also are important in the overall calculation.

This chapter addresses the impact of the textile industry and processes, and the denim-related LCA studies first. It, then, offers a framework on how to build an LCA model in denim fabric manufacturing and use data to compare different products and production practices in this very industry.

2. Textile industry and its environmental impact

The global textile industry generates notable environmental impacts through the phases of raw material production, fiber, yarn and garment manufacturing, and garment use. The rise of global population and improved living standards have resulted in consistent increase in the production and consumption of textiles and fibers in the past few decades. According to the Global Fashion Industry Statistics, the world population was 7.84 billion in 2021 [4]. Despite the fact that the global apparel and footwear market has been affected by the COVID-19 pandemic and shrunk to $1.45 billion by −18.1% in 2020, the industry grew by 18% in 2020–2021, to $1.71 billion dollars. The global apparel retail market is expected to witness a 7.5% growth in 2021–2022 period and a 6.1% growth in 2022–2023 period.

Textiles generally count on petrochemical products, and fashion accounts for up to 10% of global carbon dioxide output. Polyester, which is a form of plastic derived from oil, has experienced an explosive growth and overtaken cotton in the textile production. Garments made from synthetic fibers such as polyester are the main prime source of microplastic pollution, which harms mainly the marine life [5, 6]. In Europe, clothing is the 4th most environment polluting category after food, housing, and transport industries. The way people dispose unwanted clothes has also changed, and about 87% of the total fibers used for clothing are ultimately incinerated or sent to a landfill. Only a small fraction is recycled. Fashion brands either destroy unsold products or send piles of them to landfills across the Global South.

2.1 Estimating the environmental impact of textile processing

In order to identify the environmental impacts caused by the long supply chain of textiles and to control them, there are various environmental standards applicable to textile products. This environmental information is related to the life cycle of a product and to each step of its manufacturing line. There are many important concepts related to environmental sustainability, and life cycle assessment (LCA) is the most important and common technique for assessing the overall environmental impact of a product, process, or service [7]. LCA is based on the ISO standards 14,040:2006 and ISO 14044:2018, which outline the processes required to carry out the study [8, 9, 10].

LCA comprises four major phases, as defined by ISO, which are [11].

1. definition of goal and scope,

2. life cycle inventory (LCI) analysis,

3. life cycle impact assessment (LCIA)

4. life cycle interpretation

The analyses require collection of data of the inventory substances, the emissions, and resources, involved in the product life cycle and are performed using specific software tools with;

data provided directly from companies and/or collected through audits;

data gathered from previous studies (LCA studies, literature); and

data from databases such as Ecoinvent, ELCD [12].

The effects of resources consumed and emissions released are detailed in the LCIA step which comprises the selection of impact categories such as depletion of abiotic resources, climate change, human toxicity, acidification, eutrophication, ecotoxicity, photo-oxidant formation, stratospheric ozone depletion, land use, water depletion, depletion of minerals, and use of fossil fuels. There are two different approaches to derive characterization factors namely, midpoint and endpoint approaches. In the midpoint approach, category impacts are translated into environmental topics such as climate change, acidification, water use, fossil depletion, freshwater eutrophication, etc. In the endpoint approach, the indicators are grouped into damage categories, including resources, ecosystems, and human health.

The midpoint indicators are calculated based on the data of relevant inventory data. The endpoint, on the other hand, assesses the environmental impact tracking to the end of the impact chain. Environmental impact indicators of LCA method are given in Figure 1 [12].

Figure 1.

Environmental impact indicators of LCA (as adopted from [12]).

A number of methods are available to quantify life cycle impacts [7, 13]. ReCiPe is one of the most recent and updated impact assessment methods available to LCA users. The method addresses 18 environmental concerns at the midpoint level and then collects the midpoints into a set of three endpoint categories [14]. CML method, created by the University of Leiden in the Netherlands in 2001, is a database that contains characterization factors for life cycle impact assessment (LCIA) [15]. The method is divided into baseline and non-baseline characterization methods, the former being the most common impact categories used in LCA. The impact assessment method implemented as CML-IA methodology is defined for the midpoint approach. In LIME-3 methodology, there are nine impact categories (climate change, air pollution, photochemical oxidants creation, water consumption, land use, mineral resource consumption, fossil fuel consumption, forest resource consumption, and solid waste) and four endpoints (human health, social assets, biodiversity, and primary production) for characterization. The conjoint analysis for weighting was conducted in all G20 countries [16]. TRACI is another environmental impact assessment tool that provides characterization factors for LCIA, industrial ecology, and sustainability metrics. The potential impacts of inputs and releases on specific impact categories are quantified in common equivalence units. Ozone depletion, climate change, acidification, eutrophication, smog formation, human health impacts, and ecotoxicity are the included impact categories in TRACI.

Resource uses of fossil fuels are also characterized [17]. For the characterization of human and ecotoxicological impacts of chemicals USEtox model, endorsed by UNEP’s (the United Nations Environment Program) Life Cycle Initiative, provides midpoint and endpoint characterization factors for human toxicological and freshwater ecotoxicological impacts of chemical emissions in life cycle assessment. Main output is a database of characterization factors including exposure, effecting parameters, etc. [18]. A free web-based biodiversity broadcasting tool, BioScope, calculates the biodiversity footprint of products, companies, and investments provides businesses and financial institutions with a fast and simple indication of the main impacts their supply chains and financial products have on biodiversity [19].

These methods are linked to the software programs used in LCA. LCA software packages calculate the potential environmental impacts in a transparent way, based on inventory data. However, depending on the activity, whether the software has access to the right database needs to be checked. The differences among LCA softwares are categorized by Bach based on the following [20, 21]:

1. The origin: Broad variety of available LCA software programs are grouped regarding the developer, country of origin, and year of publication.

2. User knowledge: LCA software tools are designed for users who have no previous knowledge of LCA, who have basic knowledge, and for expert users.

3. Data source: Use of a predefined database that cannot be changed, or use of different databases that are open to software programs.

4. Entry format: Mass- and volume-related input data can be supplied in spreadsheet or geometric-based format.

5. Optimization: Optimization can either be conducted manually or computationally.

6. Default settings: Provide a basic structure to ease the applicability and execution of the LCA for the user. In some programs, default settings are introduced to simplify and speed up the execution of the LCA.

7. Life cycle phases: In general, LCA is divided into three groups of life cycle phases as production, use phase, and end-of-life. A distinction is made between three levels such that some programs consider only part of the production process while others also include part of the deconstruction and recycling process, and some consider parts of all life cycle phases.

A set of criteria for qualitative comparison of LCA software tools was also presented by Silva et.al as; software origin and version, dataset format, user interface, LCA result presentation, uncertainty/sensitivity analysis of results, support facilities for users, positive and negative modeling aspects, and other relevant aspects [22].

SimaPro, GaBi, Umberto, and Open-LCA are some of the most popular and widely known tools used for LCA. A broad list of tools is available in the LCA resources directory of the European Commission’s website [23]. GaBi and Simapro programs were introduced in the early 90s and are regarded as the earliest softwares. Following them, Umberto was developed to address material assessment. Today, the softwares have evolved into LCA expert tools based on elaborate information [24, 25, 26, 27]. The topics covered by different LCA softwares are diverse and it is important to consider the particularities of the softwares when selecting an appropriate LCA tool.

In a study conducted in order to assess whether the use of different softwares namely, SimaPro and GaBi, can cause a difference for the LCA results used for modeling a product system or doing an impact assessment, differences were identified in particular for the implementation of the impact assessment methods. It appeared that the observed differences came primarily from differences/errors in the different databases of the softwares [28].

In another study in which a gate-to-gate product system (particleboards production in Brazil) was assessed with the same functional unit using GaBi, openLCA, SimaPro, and Umberto NXT, the modeling principles, hotspots, and impacts for each software tool compared in. Acidification, climate change, ecotoxicity, human toxicity, and photochemical ozone formation from the ILCD/PEF method were the selected midpoint impact categories. It was identified that up to 22.7% more impacts were calculated by SimaPro to acidification, and up to 66.7% more impacts to photochemical ozone formation than compared to other software tools. Thus, depending on the software tool a user chooses, LCA results showed variations [22]. LCA software tools are also widely used for textile products.

3. An overview of denim-related life cycle assessment (LCA) studies

The global denim jeans market is expected to reach almost $60 billion in 2023. Besides, it is well known that the entire lifecycle of one pair of denim jeans has a significant environmental impact so far as the world’s ecological balance is concerned. As a result, with the effect of increasing consumer awareness, denim industry has shifted toward adopting more sustainable manufacturing processes, which in turn makes it necessary more than ever for the industry to systematically evaluate the environmental impacts of denim fabric production from a life cycle perspective in an attempt to effectively handle consumer related activities.

Despite the sizeable consumption of denim garments, there are very limited studies regarding LCA of such products. Levi Strauss and Co. was one of the first brands conducting an LCA to analyze the environmental impact of a pair of Levi jeans for its entire life span. Their study indicated that about 3781 L of freshwater was consumed and 33.4 kg CO2 eq of greenhouse gas (GHG) was emitted throughout the entire lifespan of a pair of cotton jeans. Moreover, it showed that consumer care had the largest impact (37%) on climate change over the life cycle, which was followed by the fabric product (27%) [29].

Hackett et al. studied the cradle-to-gate phases of the life cycle assessment of a pair of denim jeans and a T-shirt utilizing ReCiPe 2008 methodology. The study demonstrated that cotton fiber cultivation and harvesting most significantly contributed to the overall environmental impacts, and that the use of fertilizers, pesticides, and irrigation water had a direct influence on this very impact [30].

Karthik and Murugan studied carbon foot print (CF) values for all activities involved in manufacturing denim and identified the relevant processes and technologies contributing most to greenhouse gases (GHG) emissions [31].

Vos performed a water footprint (WF) assessment on a pair of blue jeans using a hybrid approach of the LCA and water footprint assessment (WFA) methods. The results revealed that raw materials (64%) and consumer washing (32%) dominated the blue WF [32].

Morita et al. in their study, investigated the environmental (climate changes [CC]) and energy performance (primary energy demand [PED]) of jeans manufacture in Brazil using LCA method. They found that CC and PED impacts associated with the production of one pair of jeans were 7.86 kg CO₂ eq and 124 MJ, respectively. Moreover, they proposed scenarios based on cotton and yarn imports as well as jeans themselves from the United States, in addition to the replacement of natural gas for wood. They demonstrated that the decreased impact of CC (4.44 kg CO₂ eq/FU) belongs to the production of jeans in Brazil using wood for heating [33].

Akı et al. conducted an experimental work regarding the life cycle assessment of a denim fabric with and without recycled fiber content using SimaPro software as assessment tool and the inventory based on denim production figures of a denim company in Turkey. They concluded that global warming potential decreases by 5%, eutrophication drops by 8% and abiotic resource depletion by 3% with each addition of 10% recycled content in the fiber blend used for denim production. In their following study, the authors mapped and discussed the environmental impact of recycled and bio-based polymeric fibers in a denim fabric using LCA as a framework. In doing so, the methodology given in the authors’ previous study was employed and all of the calculations were performed from cradle to denim factory gate. Furthermore, the inventory was based on the 2020 denim production figures of a denim company in Turkey. The results indicated that Tencel and Refibra scored the lowest in every impact category analyzed, except for the land use. They also showed that PLA appeared to have better values in every environmental impact category, when compared to PET, though recycled PET performed better than PLA for Global Warming Potential, Eutrophication and Abiotic Depletion impacts [34, 35].

Zhao et al. analyzed the virtual carbon and water flows in the global denim-product trade using the footprint methods. The findings of the study indicated that virtual carbon in the global denim trade increased from 14.8 Mt. CO₂e in 2001 to 16.0 Mt. CO₂e in 2018 whereas the virtual water consumption decreased from 5.6 billion m³ in 2001 to 4.7 billion m³ in 2018. Moreover, the results revealed that both the denim fabric and cotton fiber production contributed the most of the carbon emissions and water consumption, and that polyester blended denim had 5% greater carbon footprint and 72% lower water footprint than its cotton counterpart [36].

Fidan et al. performed an integrated sustainability assessment of denim fabric made from mechanically recycled cotton fiber by applying combined heat and power plant (CHP) for fabric production. In that study, global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), water use, and cumulative energy demand (CED) were taken as environmental impact categories, and accordingly, the LCA results revealed that the highest environmental impact improvements were obtained as 98% water use, 90%EP, 74% AP, 63% CED, and 54% GWP when 100% recycled cotton and CHP plant were used in the production [37]. Fidan et al., in another study did investigate the benefits of organic cotton fiber use in denim production with the help of life cycle assessment methodology based on four different scenarios. The environmental impact categories of global warming potential, eutrophication, terrestrial ecotoxicity, acidification, and freshwater ecotoxicity potential were analyzed using CML-IA method. The results showed that the lowest environmental impacts were obtained when 100% organic cotton fiber (scenario 4) was employed as raw material, such that it improved terrestrial ecotoxicity and freshwater ecotoxicity potential by 87% and 59%, respectively [38].

Luo et al. extended the LCA research boundary to the entire life cycle of textile products by adopting the process-level modular water footprint (WF) assessment method proposed by Li et al. [39] into both carbon and water footprints assessment of textile products. In doing so, the key issues such as module decomposition based on complex process flows and technology options, together with assembly methodology of process modules in varying product life cycle stages, were taken into account. They accordingly utilized a case study of a pair of cotton jeans to verify the feasibility as well as flexibility of the method. The results of the study revealed that the greenhouse (GHG) emissions, water consumption, water eutrophication and water eco toxicity impacts for the life cycle of one pair of jeans from cotton cultivation to product disposal were 90.37 kg CO2 eq, 13.74 m3 H2O eq, 1.67 × 10⁻² kg PO₄³⁻ eq and 112.41 m3 H2O eq, respectively, and that finishing, cotton cultivation and laundering processes were major contributors to the environmental impacts under discussion. Finally, the study proposed 12 scenarios based on the Chinese consumers’ care patterns, which pointed out that the washing with top loader washing machine, line drying, and no ironing once a month in 2-year lifetime of jeans was the best combination by contributing 1.86%, 4.86%, 19.00%, and 1.08% to the total CF, WSF, water eutrophication footprint, and water ecotoxicity footprint, in turn [40].

The existing studies on LCA analysis of denim products (fabrics, garments), majority of which focuses on cotton based denim, imply that the scope of researches may be broadened toward the works on both renewable resources and recycling of materials to see the sustainability rate of a product.

4. Building a life cycle assessment (LCA) model for denim fabric manufacturing

The motivation or the reason for doing denim LCA helps practitioners to structure their LCA model. The main framework for LCA studies is ISO 14040/44 standards [8, 9]. In addition, the communication way or tool of LCA study is also a determinative indicator for the construction of LCA study for such as determining the functional unit and the scope and/or system boundary of the study. A denim fabric mill can perform a cradle to gate LCA study including the production of raw materials, transport of all materials to a factory, production steps and packaging of the final fabric or a gate-to-gate study to cover only production stages of the fabric.

Following an Environmental Product Declaration (EPD) format is another way of constructing an LCA study and communicating its results. Defined by ISO 14025, an EPD document is an ISO type III Environmental Declaration that reports comparable and third-party verified data about products and services’ environmental performances from a lifecycle perspective [41]. EPDs are registered in the framework of a program and the study behind of an EPD is constructed according to these programs’ Product Category Rules (PCR) guidelines and rules. The International EPD® System is one of the framework programs used for EPD construction and registration [42].

In the following sections, constructing a LCA model for denim fabric will be explained via a case study based on the production practices of denim fabrics by a Turkish denim mill.

4.1 Defining a functional unit/declared unit

One of the fundamental steps of product LCA’s is to define functional unit of the study. The selling unit for denim fabric is meters or yards depending on the market geography. The weight of the denim fabric is, on the other hand, communicated in oz./yd² or gr/m² units. And the width of the fabric determines how garment manufacturers place their cutting patterns on fabric and minimize their cutting waste and use optimum amount of fabrics. Therefore, using a weight unit as a functional unit in a fabric LCA is not feasible.

The PCR for the fabrics states that a declared unit for fabrics should be used instead of a functional unit as the fabrics are intermediate products with many different potential uses and a functional unit cannot be defined from functional aspects of a fabric. Therefore, m² is used as the declared unit in fabric LCAs [43].

4.2 The scope and system boundary

As stated in Section 2.1, the scope of LCA studies are divided into four sections: cradle-to-gate (upstream), gate-to-gate(core), gate-to-grave(downstream) or cradle-to-grave which covers all of the steps in the lifecycle. Denim fabrics are intermediate products that can be used in many different garment styles with the application of different washes. And the use and the life span of the denim garment vary for individuals (consumers) depending on their lifestyle, culture, geography, etc. This makes the construction of the use phase life cycle stage of a denim fabric very complicated and scenario-based.

Therefore, a fabric mill can choose to practice a cradle-to-gate LCA for their products covering the upstream processes including the production of raw materials and packaging materials and core processes including all relevant transport down to factory gate, energy, and water consumption during manufacturing operations by the denim mill including spinning, warping, sizing, weaving, finishing, rolling, and packaging processes (cradle-to-gate).

A representation of the system boundary of a cradle-to-gate and cradle-to-grave denim fabric LCA and activities covered within is given in Figure 2.

Figure 2.

System boundary of the LCA study.

If a mill chooses to proceed with an EPD, the PCR should be followed when defining the system boundary. The life cycle stages with the relative modules are given in Table 1. In line with the system boundary, for EPDs the calculation procedure should also be separated into three life cycle stages as upstream processes (cradle-to-gate), core processes (gate-to-gate), and downstream processes (gate-to-grave) and shall be reported as such [43].

Life cycle stage	Life cycle module	Life cycle module group	Mandatory/optional
Upstream	A1) Raw material supply	A1–A3) Product stage	Mandatory
	A2) Transport		Mandatory
Core	A3) Manufacturing		Mandatory
Downstream	A4) Transportation of the fabric to retailer	A4–A5) Forming stage	Optional
	A5) Further processing of the fabric		Optional
	B1) Transportation of the fabric to the use phase	B1–B2) Use stage	Optional
	B2) Use of the fabric by the consumer		Optional
	C1) Disassembling/sorting	C1–C3) End-of-life stage	Mandatory (but may be excluded for fabric if specific criteria are met)
	C2) Transport to recovery/disposal		Mandatory (but may be excluded for fabric if specific criteria are met)
	C3) Final disposal		Mandatory (but may be excluded for fabric if specific criteria are met)

Table 1.

The life cycle module groups according to PCR for fabrics [43].

4.3 Life cycle inventory (LCI) and “data”/“background data” quality

Primary or site-specific and secondary data is used in LCAs. Primary data are those collected directly from the production site relevant to the life cycle stages modeled. If there is no primary data available, then data from the LCI databases are used as secondary data.

Apart from environmental impacts from upstream supply chain of raw materials production, all production data are collected from production lines with reference to a base year. A general practice is to use average data of at least 1 year of a recent production period per declared unit production and should reflect actual production at the specific location.

Necessary background data (secondary data) relevant to life cycle stages are taken from the databases. While no guidelines indicate a timeframe or recommendations for databases, it is a good practice to share the versions and date of database releases used in the background study with the communication of the results.

4.4 Life cycle impact analysis (LCIA) methods

One of the most important parts of an LCA is the outputs. With a Life Cycle Analysis software, SimaPro, for example, it is possible to calculate many impacts via a number of impact assessment methods [44].

The mill that is currently taken into consideration as the case study reviewed the industry guidelines and standards to determine which environmental impacts to focus on for their LCA studies. After scanning process, 5 impact categories were chosen to be assessed. These impacts, their definitions and calculation methodologies within the SimaPro 9.0.0 software are given in Table 2.

Impact category	Unit	Description	Example impact	Calculation method within SimaPro 9.0.0
Global Warming Potential	kg CO2 eq	Emission of greenhouse gases (GHGs)	Climate change	IPCC 2013 GWP 100a: methodology developed by the Intergovernmental Panel on Climate Change [45]
Freshwater use	lt	Freshwater taken from the environment	Excessive use leads to water scarcity	LCA inventory data
Land use	m^2a	The amount of agricultural area occupied	Deforestation	ReCiPe 2016 midpoint method: created by RIVM, Radboud University, Norwegian University of Science and Technology and PRé Consultants [46, 47]
Eutrophication potential	kg PO4^3− eq	Emission of substances to water contributing to oxygen depletion	Nutrient loading to stream – water pollution	CML-IA baseline methodology: LCA methodology developed by the Center of Environmental Science (CML) of Leiden University in The Netherlands [48, 49]
Abiotic Resource depletion	kg Sb eq	Measure of mineral, metal and fossil fuel resources used to produce a product	Mineral scarcity	CML-IA baseline methodology (version 3.05, updated on November 2017): LCA methodology developed by the Center of Environmental Science (CML) of Leiden University in The Netherlands [48, 49]

Table 2.

Selected environmental impact categories for the case study.

For EPDs, PCR documents guide the LCA practitioner on impact analysis. Defined in the PCR for fabrics, the calculated environmental impacts and inventory indicators should be separated into three life cycle stages as upstream processes (cradle-to-gate), core processes (gate-to-gate), and downstream processes (gate-to-grave) and shall be reported as such. The environmental impact indicators that should be declared in EPDs and the calculation methodologies are described in the EPD program website [43, 50].

For example, the environmental impact indicator Global Warming Potential should be calculated for each life cycle module stated in Table 1 in terms of fossil, biogenic, land use and land transformation and as total by using the calculation method GWP100, EN 15804. Version: August 2021 as stated in the program website as shown in Table 3 [50].

Parameter		Unit	Upstream		Core
			A1) Raw material supply	A2) Transport	A3) Manufacturing
Global Warming (GWP100a)	Fossil	kg CO2 eq	—	—	—
	Biogenic		—	—	—
	Land use and land transformation		—	—	—
	Total		—	—	—

Table 3.

LCA results framework for Global Warming (GWP100a) indicator with mandatory life cycle stages and modules [50].

In addition to the environmental impact categories, use of resources, output flows and waste categories are declared in EPD documents per declared unit for each life cycle stage according to the relevant PCR guidelines [43]. The use of resources and output flows and waste categories are given in Tables 4 and 5, respectively.

Parameter		Unit
Primary energy resources, renewable	Use as energy carrier	MJ, net calorific value
	Use as raw materials	MJ, net calorific value
	Total	MJ, net calorific value
Primary energy resources, non-renewable	Use as energy carrier	MJ, net calorific value
	Use as raw materials	MJ, net calorific value
	Total	MJ, net calorific value
Secondary material		kg
Renewable secondary fuels		MJ, net calorific value
Non-renewable secondary fuels		MJ, net calorific value
Net use of fresh water		m^3

Table 4.

Use of resources per declared unit.

Parameter	Unit
Hazardous waste disposed (HWD)	kg
Non-Hazardous waste disposed (NHWD)	kg
Radioactive waste disposed (RWD)	kg
Components for reuse (CRU)	kg
Material for recycling (MFR)	kg
Materials for energy recovery (MER)	kg
Exported energy, electricity	MJ
Exported energy, thermal	MJ

Table 5.

Output flows and waste categories.

5. An environmental impact assessment framework for denim fabrics

There are five main steps in product development that affect the sustainability score of a denim fabric:

1. Elasticity of the denim fabric

2. Weight of the denim fabric

3. Composition of the denim fabric

4. Dyeing method of the denim fabric

5. Finish of the denim fabric

Product developers and/or designers in brands decide for each step to construct the desired look. This decision also determines the environmental impact of the fabric (Table 6). An environmental impact assessment framework for different types of denim fabrics is developed based on an LCA model to use scientific data to compare different products and production practices in denim industry (Figure 3).

Choose your denim fabric’s elasticity	Choose your denim fabric’s weight	Choose your denim fabric’s composition	Choose your denim fabric’s dyeing method	Choose your denim fabric’s finish
Rigid	Lightweight (6–10 oz)	100% cotton	Indigo	Standard
Comfort stretch	Midweight (10–12 oz)	100% organic cotton	Indigo flow	Sanfor
Bi-stretch	Heavyweight (12–16 oz)	Recycled cotton	Sulfur	Alchemy
Super stretch		Cotton rich – cellulosic blend	Sulfur Top/Bottom	I-core
		Cotton rich – synthetic blend	Reactive	Coating
		ZERO-MAX®	Ready to dye/NTE	Overdye
				Flat optic
				Natural finish
				Optic finish
				Ready to dye

Table 6.

Five main steps in the framework of the study.

Figure 3.

An environmental impact assessment framework for denim fabrics.

Accordingly, the details of the five main steps in product development that are influential on the sustainability score of a denim fabric is given as follows:

5.1 Elasticity of the denim fabric

According to the elasticity of the denim fabric, the route of the production and process parameters change. This affects energy usage, water usage, waste and chemical usage, hence the selected environmental impacts. For denim fabrics, four stretch levels are used in the framework (Figure 3), namely:

• Rigid: 100% rigid denim fabric with no stretch property.

• Comfort Stretch: Denim fabric with up to 35% elasticity added for comfort.

• Super Stretch: Denim fabric with highly engineered constructions and stretching blends that achieves more than 35% stretch.

• Bi-stretch: Denim with elasticity, in both warp and weft direction, that offers slimming and sculpting effect to the wearer.

5.2 Weight of the denim fabric

Weight of the fabric determines the amount of raw material required. Primary and secondary data of the upstream processes are incorporated into the calculations as a weight unit, kg/oz. Hence, the selected impact category values differ based on the weight of the fabric. For denim fabrics, three categories are constructed into the framework (Figure 3).

• Lightweight (6–10 oz)

• Midweight (10–12 oz)

• Heavyweight (12–16 oz)

5.3 Composition of the denim fabric

Different raw materials; cotton, cellulosic or man-made fibers as input materials and data associated with these raw materials’ production should be included in the calculations when cradle-to-gate approach is selected. Several blend alternatives are taken into consideration in the framework (Figure 3)

• 100% Cotton

• 100% Organic Cotton

• 80% Organic Cotton and 20% Recycled Cotton

• Cotton-rich and Cellulosic Fiber Blend: Denim fabric with cotton-rich composition, blended with cellulosic content, such as lyocell, viscose, and modal.

• Cotton-rich and Synthetic Fiber Blend: Denim fabric with cotton-rich composition, blended with synthetic content, such as polyester.

• Zero-Virgin Cotton: Denim fabric with no virgin cotton content that contains regenerated cellulosic fibers, recycled cotton, and synthetic fibers.

5.4 Warp dyeing method of the denim fabric

Warp dyeing methodology affects energy usage, water usage, waste and chemical usage during production, hence the magnitude of the selected environmental impacts (Figure 3).

• Indigo Dyeing: Conventional indigo warp dyeing process that produces conventional blue color and shade alike to blue color.

• Indigo Dyeing with less water consumption (LWC): This is a sustainable indigo dyeing process in which up to 70% water saving can be achieved.

• Reactive Dyeing: In reactive dyeing process, water-soluble reactive dyes form strong covalent bonds with cellulosic fibers which result in good wash fastness. This requires different chemicals and process parameters than regular indigo dyeing.

• Sulfur Dyeing: In sulfur dyeing process, sulfur dyestuff which is a form of vat dyes (water insoluble dye) is applied through chemical reduction process. This dyeing process is commonly used for dark shades such as black, navy, brown, khaki, and green.

• Sulfur Top/Bottom Dyeing: Sulfur top dyeing is an application of sulfur dye after indigo dyeing. Sulfur bottom dyeing is an application of sulfur dye before indigo dyeing to decrease the amount of time needed to achieve deeper colors and obtaining a different cast.

5.5 Finish of the denim fabric

Finishing steps in denim fabric production are essential for the performance and appearance of the fabric. After weaving, fabric is mechanically and chemically treated to give it a soft hand feel, to correct the dimensional stability, to add a new shade or color on the original warp color or to add performance feature to the fabric (Figure 3).

• Standard Finish: Standard finish is the main process that involves removing the sizing agent from the fabric and adjusting the dimensional stability.

• Liquid Ammonia Finish: Alchemy is an eco-finishing process that adds softness as well as anti-pilling and wrinkle-free properties to denim while using about 90% of chemicals in close circuit and near zero water.

• Foam Finish: This finish process is an environmental-friendly sulfur and indigo coating. I-Core is a foam finishing process technology that achieves low chemical, water and energy use.

• Coating: This process covers the surface or back of denim fabric with chemicals and dyestuff in order to gain or improve various surface properties or to achieve a shade/cast on the original warp color.

• Overdye: Denim fabric is dyed in this process in finishing stage to achieve a shade/cast on the original warp color.

• Flat Optic Finish: This is a finish to achieve flat and lustrous look.

• Natural Finish: This is a finishing process for undyed denim fabric that involves removing the sizing agent from the fabric and adjusting the dimensional stability.

• Optic Finish: This is a finishing process which is applied to undyed denim fabric to achieve bright white color.

In the framework (Figure 3), the fabric compositions are accumulated to three different groups for each rigid and comfort/stretch elasticity levels. The impacts coming from fiber compositions are constructed according to the weight of fibers used in each composition group and weight level. The following production stages, namely spinning, warping, sizing, unwarping, weaving, packaging, and quality control, are taken as fixed processes for all design variations and based on 1 meter of fabric production. The impacts originated from dyeing and finishing processes are allocated according to the yearly production of 1 meter of dyed warp yarn and finishing of 1 meter of raw fabric, respectively, for each dyeing and finishing recipe.

Warp dyeing method of a denim fabric is independent from the raw material or elasticity choices. Figure 4 shows the difference in the selected environmental impacts based on different warp dyeing methods. Regular indigo dyeing has the highest impact compared to the other methods in four categories-global warming potential, eutrophication potential, abiotic depletion and water use out of five. In terms of land use, the environmental impact of sulfur dyes is almost doubled compared to indigo dyeing.

Figure 4.

Effect of warp dyeing methodology.

Figure 5 shows the difference in the selected environmental impacts based on different finishing processes of a denim fabric. Optic finish and i-core finish have the highest impact in all of the impact categories. Coating and overdyeing follow these finishes.

Figure 5.

Effect of finishing processes for a denim fabric.

As may be seen from both Figures 5 and 6, percentages are used as a measure to compare the different methods, as the absolute values are in different scales for each impact category and for the relevant routes.

Figure 6.

An example of an impact calculation for rigid, mid-weight, indigo dyed, and coated denim fabric made with 100% cotton.

In the impact assessment for each indicator, the burden coming from each composition per different weights, warp dyeing methodologies and finishing processes is added on top of the impacts coming from the fixed processes. Figure 6 is an example of the global warming potential calculation of a rigid, mid-weight, indigo dyed, and coated 100% cotton denim.

A comparison model can be developed for distinctive denim fabric designs based on normalizing and scoring each step in the LCA. Particular routes in the framework can be selected and results can be compared to a defined standard denim (Figure 7).

Figure 7.

An example of a route selection for rigid, mid-weight, indigo dyed, and coated denim fabric made with 100% cotton.

6. Conclusions

This chapter introduces an environmental impact assessment framework for denim fabrics. This framework provides an opportunity to calculate impacts of product developers’ and/or designers’ choices in defining the denim fabric they would like to develop using scientific LCA data. One can even compare the impact results of different types of denim fabrics without even producing the fabric itself. Calculating and sharing this detailed science-based data also represents a new level of transparency. On the contrary to the common belief of raw materials being the main impact generators in denim fabrics, the framework also proves that impacts occurred during denim fabric manufacturing, during the production of the raw and auxiliary materials, and impacts of the background processes should all be taken into consideration.

There are challenges in LCA calculations since the primary data is highly company-specific. Therefore, the chapter focused on normalizing the data and creating a scaling that can be used in decision-making.

Greenwashing is not only denims but today’s one of the growing problems in every sector, in every product. Baseless claims and marketing statement caused this problem and now it is really hard to clean it up. Certifications and labels were seen as one of the solutions to this problem however, industry experiences misapplications during the certification process in the last couple of years. There is an information pollution in the market on what is sustainable denim. This framework will help designers/companies compare their choices about their sustainable denim fabric definitions via science-based data.

Conflict of interest

The authors declare no conflict of interest.