Toxic chemicals – contamination claims on the horizon

Advances in attribution science of chemicals and a change in environmental regulations have the potential to trigger property damage or bodily injury in the present day on account of chemicals having made it into the environment way back in the past.

Chemicals introduced decades ago are being scrutinised for their potential to harm people and the environment in the present day. The reasons are manifold and the associated factors have evolved over many years. Scientific progress and technology have strengthened capabilities to discover if an exposure to a chemical comes from a specific source. Compensation for losses in the case of bodily injury or physical damage can be more easily secured where a source is identified.

More sophisticated tools

Today scientific tools are better able to measure the levels of chemicals in the environment, the food chain and in humans. This applies not only to single compounds but also to chemical mixtures. In the past, most research evaluated the risk of individual substances. Due to their complexity and the lack of data, knowledge of the toxicity of chemical mixtures was limited. Today, state-of-the-art techniques enable the rapid analysis of chemical compounds in mixtures. Combining the findings with computational models facilitates improved understanding of the toxicity of chemical compounds and their impact on the environment.1

One example of this are Machine Learning (ML) techniques, which can be deployed to estimate the effects of chemicals on the environment. Recent ML achievements in predicting biological responses and environmental behaviour of chemicals are impressive. They include aspects like bioactivity (as relates to both toxicity and efficacy depending on the compound class and the living system impacted) and fate/persistence (in the body and in the environment). Based on large databases, ML algorithms can generate novel, testable and verifiable assumptions, facilitating more predictable results.2

Recent advances in modelling and the use of ML also open the door to attributing chemicals in the environment to point sources.3 The ML methodology has been used in processing data from satellites to obtain ground-level concentrations of atmospheric pollutants, pollution source apportionment, and spatial distribution modelling of water pollutants.4

Transparency and standardisation

The technological developments come parallel to efforts to establish global standards for the assessment of harmful chemicals and knowledge exchange. For example, the OECD is coordinating a Hazard Assessment Program for industrial chemicals;5 the Environment Programme of the United Nations (UNEP) provides a searchable chemical regulation database;6 the REACH Regulation7 of the European Union (EU) and the EU’s Sustainability Strategy for Chemicals8 contain a future risk assessment component for chemical mixtures; and the aim of the UN’s Globally Harmonized System of Classification and Labelling of Chemicals9 is transparency around hazardous chemicals for all.10

At the same, time legal changes to existing and the creation of new legislation can facilitate claims for property damage, environmental impairment, bodily injury and subsequent financial loss. Examples include the EU’s review of the Environmental Liability Directive,11 the aim of which is to protect natural resources, or the EU Directive on Representative Actions12 for the protection of the collective interests of consumers. These will bring class-action type claims to the EU. In certain jurisdictions, litigation by shareholders is also a possibility. This includes claims against corporates for not adequately disclosing chemical exposures or providing timely information to investors.13, 14

With these initiatives, in the future the connection between harm to people or the environment and a chemical may be easier to establish. This generates a new risk landscape. Appropriate underwriting measures in respect to policy wording (eg, claims made triggers, cost within the limit etc) are important tools to curtail future exposures. Here classical liability policies and potentially D&O covers could be in focus.

References

References

1 Luo, Y. et al., “Chemical and biological assessments of environmental mixtures: A review of current trends, advances, and future perspectives”, Journal of Hazardous Materials, 2022.
2 Wu, X. et al., “Machine learning in the identification, prediction and exploration of environmental toxicology: Challenges and perspectives”, Journal of Hazardous Materials, 2022.
3 “Where did the PFAS in your blood come from? These computer models offer clues”, Environmental Health News, 28 November 2022.
4 Lu, X. et al., “Data-Driven Machine Learning in Environmental Pollution: Gains and Problems”, Environ. Sci. Technol., 2022.
5 “Chemical Safety and Biosafety Progress Report”, OECD, 2022.
6 “Global Chemical Regulations Database”, UNEP (accessed 19th April 2023).
7 “REACH”, EU (accessed 19th April 2023).
8 “Chemicals Strategy for Sustainability”, European Chemicals Agency (ECHA).
9 “Globally Harmonized System of Classification and Labelling of Chemicals (GHS)”, UNECE.
10 “Globally Harmonized System of Classification and Labelling of Chemicals (GHS)”, UNECE.
11 “Environmental Liability Directive”, EU (accessed 19th April 2023).
12 “Injunctions Directive and Representative Actions Directive”, EU (accessed 19 April 2023).
13 “Ex-PG&E Execs Paying US dollars 117M To Settle California Wildfires Lawsuit”, Insurance Journal, 2022.
14 “Form 10-Q For the quarterly period ended September 30”, PG & E Corporation, 2020.

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