Multi-criteria ranking of chemicals for toxicological impact assessments

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Highlights

  • Novel approach for comparing chemicals, based on a global toxicity concept.

  • Adaptation of multi-criteria analysis to assess chemical toxicity.

  • Two pilot applications of the new method for the textile sector are proposed.

  • Ranking of chemicals and level of criticality of samples/sites could be obtained.

Introduction

The global regulatory and societal trend of environmental awareness is strongly pushing companies to incorporate environmental sustainability into their business models. The adoption of environmental management systems (EMS) such as ISO 14001 can encompass compliance with regulatory requirements. However, growing ethical reasoning in customers' decision is motivating companies to go further in developing environmental programs extended to their supply chain, and disseminating them through the publication of up-to-date sustainability reports. The release of toxic substances from manufacturing plants and finished products are among the key variables to be included in an effective EMS. In order to set up efficient monitoring programs and corrective actions, priority chemicals must be identified based on their toxicological relevance. Still, toxicity data of a chemical substance may refer to a variety of exposure routes (e.g. inhalation, ingestion, dermal contact etc.) and effects (e.g. reversible injuries, acute or chronic lethality, carcinogenicity, etc.), which are not directly comparable. For this reason, toxicity evaluations are currently carried out by following risk assessment strategies based on single types of hazard or exposure route. The US Environmental Protection Agency (EPA) (2009) adopted this approach, providing a risk assessment guidance for the independent evaluation of carcinogenic and non carcinogenic inhalation risks, by comparing the exposure concentration to distinct reference values (the inhalation unit risk and the hazard quotient, respectively). However, this approach does not allow to obtain an univocal ranking of global toxicity. Some attempts have been made in this direction. For instance, a Safer Chemical Ingredient List was created by US EPA (2016) with the aim of help consumers in finding products that perform well and are safer for human health and the environment. Within this list, increasingly safer alternatives of commercial ingredients are marked with a yellow triangle, a green half-circle or a green circle. A similar classification is given by GreenScreen® For Safer Chemicals (Clean Production Action 2016), which sets out 4 benchmarks that define progressively safer chemicals. In both cases, the limited number of categories used for classification of chemicals may smooth down significant differences in toxicity among chemical compounds. In Europe REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals), the new regulation regarding the production and use of chemical substances, addresses in particular companies that may play a role as manufacturer, importers or downstream users. REACH defined a “List of restricted substances”, constituted of substances that cannot be used in the specified restriction conditions (European Chemical Agency (ECHA), 2018). Moreover, it introduced a procedure for the identification of the “Substances of Very High Concern” (SVHC), that are candidates for substitution. REACH SVHC criteria are severe hazardous properties such as carcinogenic, mutagenic, toxic for reproduction (Berges et al., 2014). REACH and the other resources could be a good starting point for companies that need to set-up corrective actions, but none of these classification methods permits to obtained a detailed order of priority to be given to substances for their replacement.

In this work, a novel approach for toxicological ranking of chemicals has been developed by designing a dedicated multi-criteria method. Multi-criteria analysis (MCA) is a family of decision-making tools that are mostly used in strategic environmental assessment procedures to ensure that environmental, societal and economic variables are all taken into consideration within (Convertino et al. 2013; Omo-Irabor et al. 2011; Srivastava et al. 2012; Valle Junior et al. 2015). All variables are integrated to extract a synthetic aggregated value for each case to be compared (e.g. each geographical region or intervention scenario). The aggregated values are then categorised based on evaluation criteria which represent utility values for the stakeholders, and finally ranked. The MCA approach has been successfully implemented in the fields of energy planning (Pohekar and Ramachandran 2004), agriculture (Hayashi 2000), water resource management (Hajkowicz and Collins 2007), and many others, but to our knowledge, has never been used with the aim of evaluating the global toxicity of chemicals in any kind of samples.

In this work, MCA was adapted to create a ranking strategy for chemicals by combining their hazard for humans and the environment, with the measured concentration in cases of interest (manufacturing plants, products, geographical regions etc.). The method goes beyond classical toxicological evaluations, based on a single and specific type of toxicity, because MCA can take into consideration a potentially unlimited number of parameters at the same time, leading to a ranking of compounds based on a global hazard concept. Since every criterion could be assigned a relative weight, the method leads to the construction of a dynamic ranking of compounds (or general scenarios) that may be updated at any change of the input values (measured concentration of chemicals) and relative importance of criteria. This feature makes the proposed MCA approach very versatile and applicable to a wide variety of fields. Two case studies are presented, focused on the textile sector, where MCA was implemented to evaluate: i) the chemical-toxicological impact of manufacturing facilities through wastewater effluents; ii) the direct impact of the pollutants' content in consumer goods (clothing). Despite available data were insufficient to achieve a complete overview of the impact of textile industry worldwide; they provide a representative view of method applicability, to be intended in combined use with classical statistical techniques. The method is of simple implementation, as it does not require experimental phases; reliable, because toxicological data are official and provided by universally recognised agencies; and versatile, as it can be used for environmental evaluations in various fields, and for different purposes.

Section snippets

Chemicals

Globally, 240 different chemical compounds of toxicological relevance were selected for the comparison. They belong to a wide variety of classes, including: alkylphenols, phthalates, flame retardants, dyes, organotin compounds, poly- and per-fluorinated substances (PFAS), chlorobenzenes, chlorotoluenes, solvents, phenols, short-chain chlorinated paraffins, metals and metalloids, cyanide, pesticides, biocides, organic phosphor acetic acid esters, volatile organic compounds (VOCs, − including

Ranking of chemicals

For substances which can be present in the environment in multiple forms, but are measured as a total concentration (i.e. heavy metals), the principle of precaution was followed, adopting the performance measure of the most toxic form, for each every type of toxicity.

The resulting GTSs for all chemicals in the two case-studies are reported in the Supplementary Material (Tables S.3 and S.4). 163 chemicals were analysed in wastewater and 151 chemicals in clothing. The first substances in the

Conclusions

Every chemical compound is characterised by a specific type and level of toxicity. Making a comparison and a toxicological ranking of chemicals is therefore a difficult task. In this work, MCA method was adapted to build a risk assessment strategy for toxicological ranking of chemical compounds: each compound was considered as an alternative, evaluated using its types of toxicity as criteria. The application of the method to two different case studies allowed to prove the versatility of the

Acknowledgments

This work was supported by Benetton Group S.r.l., Ponzano Veneto, Italy, which also kindly provided the experimental data used for the assessment.

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