The textile and apparel industry are integral to the socio-economic development of many countries, especially in the developing world. However, this growth comes at a significant environmental cost. From the extensive use of water, energy, and chemicals to the rapid rise of fast fashion contributing to waste and pollution, the industry’s environmental footprint is substantial. Environmental Sustainability (ES)—which emphasises the balance between economic growth and environmental protection—has become an essential consideration in this sector.

Given the complexity of textile production and the consumption process, evaluating ES is not straightforward. This article provides a critical review of the current methods used to assess the environmental impact of textiles and apparel and proposes future research directions for more holistic and practical evaluation frameworks.

Industry Context and Challenges
The textile and apparel sector are characterised by a highly fragmented supply chain, with most production taking place in small and medium-sized enterprises (SMEs) across developing countries. These SMEs often lack the resources and technical capacity to conduct comprehensive ES evaluations. Furthermore, the industry’s lifecycle—from raw material extraction to product disposal—is long, not standardised, and data-intensive, making it difficult to gather consistent and reliable environmental data.

Additionally, the rise of fast fashion has accelerated production cycles, contributing to overconsumption and a significant increase in textile waste. Brands like Zara and H&M introduce new collections frequently, which amplify the environmental burden and complicate ES assessments.

Existing Evaluation Methods
Currently, there are four major methods used to evaluate environmental sustainability in the textiles and apparel industry:

1. Life Cycle Assessment (LCA)
LCA is a comprehensive method that evaluates the environmental impact of a product throughout its entire lifecycle—from raw material extraction to disposal. It provides both ‘midpoint’ indicators (e.g., water use, fossil fuel depletion) and ‘endpoint’ indicators (e.g., impact on human health and ecosystems).

While LCA is methodologically robust, it is data-intensive and often impractical for SMEs. Data collection is time-consuming and costly, and databases used for LCA often lack region-specific data relevant to developing countries.

2. Environmental Footprint
This method breaks down sustainability into specific indicators such as:

  • Carbon Footprint: Measures greenhouse gas emissions in CO₂ equivalents.
  • Water Footprint: Assesses water use and pollution, including blue (surface and groundwater), green (rainwater), and grey (pollution assimilation) water.
  • Chemical Footprint: Evaluates the environmental hazard of chemicals used in production.

These indicators have been used to assess individual garments, manufacturing facilities, and the overall sector. For instance, carbon and water footprints are commonly applied in analysing cotton garments, while chemical footprints are used in life cycle toxicity assessments. While easier to implement for targeted metrics, these indicators often overlook the broader lifecycle impacts and fail to integrate socio-economic factors.

3. Eco-efficiency
Eco-efficiency measures the ratio between the economic value of a product or service to its environmental impact. Originally developed by the World Business Council for Sustainable Development (WBCSD), it aims to create more value with fewer environmental resources and is suitable for evaluating performance at enterprise or product levels.  

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Eco-efficiency has been used to compare the performance of textile factories and product lines. It can be enhanced by incorporating LCA results and monetising environmental costs (eco-costs).

Though this method integrates economic considerations, it primarily reflects internal benefits (e.g., cost savings or revenue generation) and often misses external socio-economic contributions such as job creation and community development.

4. Higg Index
Developed by the Sustainable Apparel Coalition (now Cascale), the Higg Index is a commercial tool designed specifically for the apparel and footwear industry. It includes modules to assess environmental, social, and labour impacts at the product, facility, and brand levels.

Despite its comprehensiveness, the Higg Index relies heavily on self-reported data and qualitative assessments which may reduce reliability. It lacks inclusion of broader socio-economic impacts like regional development or long-term employment.

Limitations of Current Methods
There are several limitations in the application of these methods within the textiles and apparel context:

1. Due to the vast diversity in product types, production stages, and geographic distribution, collecting standardised data is very complex and challenging.

2. Most environmental databases were developed in and for developed countries, making them ill-suited for assessing impacts in production-heavy regions like South Asia or China. Due to unavailability of region-specific data, it is very difficult for accurate measurement of the environmental impact.

3. Impact of fast fashion results in rapid product turnover and disposal. Therefore, it becomes extremely difficult for tracking the lifecycle of a product and environmental impact.

4. The tools used for data collection and evaluation are too narrowly focused on environmental dimensions, often overlooking the interconnected social and economic roles the industry plays in developing countries.

5. Tools like LCA and footprint assessments provide limited insight into broader sustainability trade-offs, such as balancing environmental harm against job creation or economic upliftment. Thus, they lack the multi-dimensionality in impact assessment.

Proposed Directions for Future Research
To overcome the identified limitations, there is a pressing need to develop holistic tools that would integrate environmental, social, and economic dimensions. Social benefits such as employment, income generation, skills development; economic dimensions such as enterprise profitability, regional economic growth and environmental dimensions such as resource use, waste generation, waste management, emissions, chemicals and carbon footprint may be studied in totality so that a holistic and sustainable ecosystem can be created.

As data collection across the supply chain, cross-country or region specific is a challenging task, mixed method approach can be created. For e.g., quantitative data for resource use, emissions etc can be used while qualitative data about HR policies, labour practices, economic development can be evaluated. To assess such data for decision-making, techniques like AHP (Analytic Hierarchy Process), FCE (Fuzzy Comprehensive Evaluation), DEA (Data Envelopment Analysis), PLSM (Partial Least Squares Modelling), Delphi Method etc can be used.