The increasing mass and complexity of chemicals being produced and transported has resulted in more rigorous demands on both authorities as well as chemical-handling industries to assess the risks involved. The Environment-Accident Index (EAI), has been proposed as a planning tool created as an equation in which chemical properties (variables describing the chemical involved) are combined with site-specific properties (variables describing the accident site). The EAI is intended to facilitate assessment of the environmental effects related to chemical accident scenarios and hence assist the organisation of preventative programs. The main objective of the work described in this thesis was to evaluate, develop and improve the proposed EAI. The steps involved in the development process included I) evaluation of the feasibility of the EAI approach, II) selection of a representative and diverse set of chemical accidents to be used in the development III) the use of questionnaires and expert judgements to develop response values for environmental effects of a chemical accident, and IV) to create a new EAI model using multivariate modelling (PLS). The EAI approach proved to be useful in the work to protect the environment in case of a chemical accident. A representative set of accidents was selected by means of statistical multivariate design (PCA) based on assembled data related to a set of 55 chemical accidents. The selection generated a set of accidents representing a diverse spectrum of chemical accident scenarios. To develop a measure of environmental effects of the chemical accidents i.e. responses, an expert panel was asked to judge their environmental effects (such as effects on animal life in the aquatic or terrestrial environment). The results showed that the judgements give a rough estimate of environmental effects that could be used as responses in the development of the EAI. The developed responses were then related to the chemical and site-specific properties to create a new EAI model. This resulted in a PLS-based EAI connected to a new classification scale. The advantages of the new EAI are that it can be calculated without the use of tables; it can estimate the effects for all included responses, and make a rough classification of chemical accidents according to the new classification scale. Finally, the new EAI is a more stable model than the previously proposed EAI, and it is founded on a valid base of accident scenarios, making its use for a variety of chemicals and situations more reliable since it covers a broader spectrum of accident scenarios. The new EAI can be expressed as a regression model to facilitate calculation of the index for people that do not have access to PLS. The highest priorities for further refining the new EAI in the future are: external validation of the EAI; further refinement of the formula’s structure; adjustment of the new classification scale; and real-life evaluation of the EAI.