ESG Environmental Indicators Review

The environmental pillar has been at the center of stakeholders’ attention in recent years. This also indicates the shift from voluntary to mandatory sustainability reporting, which has led to the appearance of many new and sometimes redundant indicators, this abundance of available data often results in significant statistical noise. Although the theoretical links between financial performance and sustainability are currently being analysed in the existing literature, there is a challenge in distinguishing which indicators are truly relevant from the hundreds of granular indicators available. Empirical studies continue to investigate the impact of ESG indicators (e.g., Yin et al., 2025), but there is growing uncertainty regarding environmental indicators (Shi et al., 2025). It is difficult to distinguish between actual performance (e.g., environmental) and administrative compliance (Meyer & Rowan, 1977), due to indicators that often exhibit high dimensionality and multicollinearity. Given this methodological challenge, this study uses Principal Component Analysis to factorise a dataset containing 56 environmental indicators from the Refinitiv database for companies included in the S&P 500 index. The aim of the research is to group the aggregated scores by identifying the key factors that define companies’ environmental footprint. According to the results, the environmental pillar is not a single concept; rather, it consists of several distinct dimensions, namely: Environmental Management, Carbon Footprint, Green Finance, and Eco-Innovation. One of the most important findings is the clear distinction between tangible physical impacts, such as emission intensity, and institutional commitment, which typically involves the adoption of internal policies, indicating that more rigorous strategic governance does not necessarily lead to a reduction in the carbon footprint. The contribution of this paper provides a founded scientific framework to help stakeholders filter out aggregate noise and evaluate environmental performance based on relevant structural factors, without relying on redundant reporting indicators.