# Can "Hazard-Cost-Effectiveness Analysis" improve the risk management of chemicals under REACH?

Jean-Marc Brignon, Jean-Christophe Vergnaud, Sandrine Andres, Enrico Mombelli, Tsarafara Rambolarimanana

## ► To cite this version:

Jean-Marc Brignon, Jean-Christophe Vergnaud, Sandrine Andres, Enrico Mombelli, Tsarafara Rambolarimanana. Can "Hazard-Cost-Effectiveness Analysis" improve the risk management of chemicals under REACH?. Regulatory Toxicology and Pharmacology, 2024, 147, pp.105561. 10.1016/j.yrtph.2024.105561. ineris-04492408

HAL Id: ineris-04492408

https://ineris.hal.science/ineris-04492408

Submitted on 6 Mar 2024

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

# Can “Hazard-Cost-Effectiveness Analysis” improve the risk management of chemicals under REACH?

Jean-Marc Brignon<sup>a, *,</sup>, Jean-Christophe Vergnaud<sup>b</sup>, Sandrine Andres<sup>a</sup>, Enrico Mombelli<sup>a</sup>, Tsarafara Rambolarimanana<sup>a</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

Handling Editor: Dr. Martin Van den berg

Keywords:

Chemicals

Cost effectiveness analysis

Prioritization

REACH

PBT

vPvB

Restriction

## ABSTRACT

Cost-Effectiveness Analysis (CEA) is a decision-making framework to prioritize policy decisions for chemicals. Differences in hazard profiles among chemicals are not integrated in CEA under the EU REACH Regulation, which could limit its relevance. Another concern is that two different economic decision support methods (CEA for chemicals considered as PBTs or vPvBs from a regulatory perspective and Cost Benefit Analysis (CBA) for others) are used under REACH. To address this situation, we define “Hazard” CEA by integrating a hazard score, based on persistence, bioaccumulation and (eco)toxicity, in the effect indicator of CEA. We test different designs and parameterizations of Hazard-CEA on a set of past socio-economic assessments under REACH for PBT and non-PBT chemicals. Weighing and thresholds in hazard scores do not have a significant impact on the outcome of Hazard-CEA but the design of the hazard scoring method does. We suggest using an integrated and unweighted scoring method with a multiplicative formulation based on the notion of risk. Hazard-CEA could be used for both PBT and non-PBT chemicals, to use a single method in REACH and therefore improve consistency in policy decisions. Our work also suggests that using Hazard-CEA could help make decision easier.

## 1. Introduction

In the European Union, the REACH Regulation<fnref n="1" /> requires that a “socio-economic analysis” (SEA) is performed to support decisions regarding the withdrawal of hazardous chemicals from the market. In practice, this SEA is often a Cost Benefit Analysis (CBA) that compares benefits to human health and the environment from avoided exposures, to substitution costs for industry and authorities (including monitoring, enforcement, etc …) (ECHA, 2011; ECHA, 2008). For Persistent, Bio-accumulative and Toxic (PBT) chemicals, CBA cannot be applied because the use of PBTs leads to unpredictable exposures over very long timeframes and their impacts on health and the environment cannot be assessed (Oosterhuis et al., 2017). Similarly, for very Persistent and very Bioaccumulative chemicals (vPvBs), there is currently no known toxicity, the concern is about very long-term irreversible exposure and there is no impact on health and the environment. For decisions on chemicals considered as PBTs and vPvBs under REACH, the European

Chemicals Agency recommends the use of Cost-Effectiveness Analysis (CEA) instead of CBA. In CEA for PBTs and vPvBs under REACH, CEA is expressed as ratios of the substitution costs to ban a given chemical, to avoid effects (for which avoided emissions or quantities not placed on the market are used as the best available proxy). These ratios expressed in €/kg can then be compared with benchmarks provided by similar accepted past decisions to help decide on risk management measures. Even in the absence of valid or agreed benchmarks, when Cost Effectiveness (C/E) ratios are computed for a list of risk reduction actions, priorities can be made by comparing these C/E ratios, giving the highest priority to actions with lower C/E ratio (most cost-efficient). An advantage of CEA over CBA that makes it attractive to aid decisions on chemicals more widely than for PBTs and vPvBs only is its simplicity and lower data requirement, because in CEA health and environmental impacts do not need to be quantified (Oka, 2003). CEA does not require knowledge of dose/response functions and allows for the implementation of hazard-based management of chemicals, that can better integrate

<footnote><sup>a</sup> INERIS, Parc Technologique ALATA, BP 2, 60550, Verneuil-en-Halatte, France</footnote>

<footnote><sup>b</sup> Centre D'Economie de La Sorbonne, CNRS Université Paris-1 Sorbonne, Paris, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: Jean-Marc.Brignon@ineris.fr (J.-M. Brignon).</footnote>

<footnote n="1">¹ (Registration, Evaluation, Authorisation and restriction of Chemicals (REACH) Regulation (EC) No 1907/2006 of the European Parliament and of the Council of 18 December.).</footnote>
the precautionary principle (Foss Hansen et al., 2007). Regulatory frameworks define precisely with threshold which chemicals are PBT/vPvBs and which are not from a regulatory perspective. However, persistence and bioaccumulation are continuums, and chemicals that are not considered as PBT/vPvBs from a regulatory point of view, can still to a certain extent exhibit some persistency, and bioaccumulation below these thresholds (Abelkop et al., 2015). Therefore, further to the interest of improving CEA for regulatory PBTs and vPvBs, there is a case for using more extensively CEA for chemicals management.

However, so far, the application of CEA under REACH does not consider differences in the level of hazard between chemicals (Oosterhuis et al., 2017). This limitation could limit their informational value in priority setting for decisions by putting more emphasis on costs than on hazard (Gabbert and Hilber, 2020). ECHA, the European Agency in charge of the operation of REACH, states that “ideally, the damage potential of different PBT and vPvB substances could be weighted” [...] but [that] a systematic approach to weight the damage that would be applicable for all the cases does not currently exist” (ECHA, 2016). The aim of this study is to take a step in the direction towards such a “systematic approach” and to develop and to test improvements of the current application of CEA by the introduction of a chemical-specific hazard score in the CEA ratio. This “Hazard-CEA” should be able to provide consistent priorities, as far as possible independent from the choice for a particular relevant chemicals’ hazard scoring method. Therefore, we tested whether different versions of the Hazard-CEA with different chemicals’ hazard scoring methods gave consistent priorities. Our approach builds on and extends existing hazard scoring methods, and also includes our own novel proposals.

The aim of this work is also to test and apply Hazard-CEA to any chemical. This would avoid having two different methods (CBA and CEA) for different groups of chemicals and would therefore increase the overall consistency of decisions under REACH.

An intermediate result of the study was the construction and comparison of several hazard scores for chemicals. In this study we focussed on persistence, bioaccumulation, and ecotoxicity but other hazards could be easily and similarly integrated (such as toxicity to humans, or mobility for instance) or further detailed. In terms of scoring methods, we worked on additive scoring, non-additive scoring, and partial order rankings, and compared them in terms of providing, or not, similar orderings of chemicals by priority.

## 2. Materials and methods

### 2.1. Chemicals' hazard scoring methods

Criteria used to prioritize the degree of concern among chemicals in a regulatory perspective have been changing over time, along with the development of regulatory frameworks, and advances in scientific understanding of the fate and effects of chemicals (Matthies et al., 2016). They usually rely on a scoring system, with different formulations and thresholds depending on authors, and the most salient ones are reviewed hereafter.

Under the European Prometheus project, a multiplicative scoring system building on workflows to establish normalized values for P, B and T has been developed (Benfenati et al., 2016). Other scoring systems work with partial scores on several or all of the persistence, bioaccumulation, and (eco)toxicity dimensions (Rorije et al., 2011; Strempel et al., 2012; Reppas-Chrysovitsinos et al., 2017), and can also include consideration of existing stocks of the chemical in the environment (Nendza et al., 2023), or of mobility (Arp et al., 2017; Gramatica et al., 2015; Pizzo et al., 2016) developed a scoring system fully relying on Quantitative Structure-Activity Relationship (QSAR) modelling, that is using such models to predict Persistency, Bioaccumulation and Toxicity characteristics from the molecular structure of the chemicals.

Such scoring systems can be sensitive to their parametrization. Partial order methods are alternative ranking techniques that do not require

the computation of scores, therefore avoiding the need of weighing parameters, and tend in general to be more robust (Roy and Bouyssou, 1993; Department for Communities and Local Government, 2009). These methods also have been used to prioritize chemicals (Sailaukhuly et al., 2013; Karr et al., 2014).

This study compared three different approaches for scoring chemicals. The first scoring system (further denoted PBT-score) is based on (Rorije et al., 2011) and integrates persistence (P score) and bioaccumulation (B score). We propose to extend it to integrate ecotoxicity by adding a T-score to the Rorije et al. proposal (Eq. (1)):

$$ \text{PBT} - \text{Score} = \text{P Score} + \text{B Score} + \text{T Score} \quad (\text{Eq. 1}) $$

Where:

$$ \text{P score} = e^{(-\ln(2)+40)/H} $$

$$ \text{B score} = e^{(-\ln(2)+2000)/BCF} $$

$$ \text{T score} = e^{(-\ln(2)+\text{PNEC})/0.01} $$

With H the half-life of chemicals, BCF the Bio Concentration Factor and PNEC the Predicted Non-Effect Concentration.

(Rorije et al., 2011) designed the P and B Scores with a log-logistic law so that it varies between 0 and 1, and that its value is 0.5 for the respective regulatory thresholds for P and B values used to define a PBT under Annex XIII of the REACH Regulation, that are respectively Half-life>40 days and BCF>2000We follow the same logic for ecotoxicity, for which the regulatory threshold under REACH is a PNEC of 0.01 mg/l. This normalization allows to add P, B and T scores into a single score.

This scoring system is structurally linked to regulatory thresholds that are somewhat arbitrary. In order to assess the impacts of these thresholds, we also defined four modified PBT-scores to let the level associated with thresholds vary: 1) "vPvBT" uses REACH thresholds for very persistent chemicals ("vP" half-life> 60 days) and for very bioaccumulative chemicals ("vB" BCF> 5000) without changing the PNEC threshold, 2) "PBvT" uses P and B thresholds unchanged, but a PNEC threshold divided by 10, 3) "PBvvT" uses a threshold PNEC divided by 100, and 4) "vPvBvvT" combines 1 and 3.

We also built a novel scoring system (M, standing for Multiplicative) that avoids normalization and associated thresholds by adopting a Multiplicative formulation (Eq. (2)). This alternative scoring also intends to better reflect risk, since it can be regarded as proportional to the duration of presence in the environment (with H), exposure of organisms (BCF) and inversely proportional to the toxicity (PNEC). Positive feedback of risk between persistence, bioaccumulation, and toxicity effects is also better embedded in this score.

$$ M - \text{Score} = H * \text{BCF} * \frac{1}{\text{PNEC}} \quad (\text{Eq. 2}) $$

We introduce a third scoring system denoted C1 (and its variation C2, C standing for Comparison) that is based on outranking methods. Outranking methods work with the exhaustive pairwise comparison of all couples of chemicals under criteria, here P, B, and T. They provide a different perspective than previous PBT score (and its variants) and M because they simulate the human qualitative comparison process to establish priorities. The specific outranking method we used for C1 and C2 is ELECTRE III (Roy and Bouyssou, 1993; Figueira et al., 2005). Among outranking methods, ELECTRE III has the particular feature of using a fuzzy outranking relation to make comparisons. ELECTRE methods rely on assessing for each pair of objects (here chemicals, for instance a and b) and for each criterion if a "surpasses" b. The surpassing relation is assessed based on the two notions of concordance and non-discordance that are built on respectively the number of criteria
confirming the surpassing relation, and on how strong is the discordance on the other criteria. In C2, after establishing the degree of veracity of all surpassing relations, the method uses an algorithm (called “distillation”) to rank highest in a list those objects that are overall most surpassing others than being surpassed. The distillation algorithm produces a ranking of objects. In C1, instead of an algorithm, the position of each object in the hierarchy is computed by a score, that is based on all surpassing scores of that object with other objects. Since C2 only provides ranking, but no score, only C1 could be used for Hazard-CEA in the second part of this study. Mathematical formulations and details on ELECTRE III and specifically on C2 can be found in (Figueira et al., 2005), and further details on the C1 variant are in (Bouyssou, 1992).

## 2.2. Hazard based cost/effectiveness

We then introduce chemicals' hazard scores into Cost/Effectiveness ratios, in order to define “hazard-based” cost/effectiveness. For that purpose, we complement the physical representation of effects in terms of avoided use or emission in standard Cost-Effectiveness indicator of (Eq. (3)) with the biological effects representation in terms of the chemical's hazard, as proposed in (Eq. (4)), and using hazard scores described in the previous section.

$$ \text{StandardCost-Effectiveness} = \frac{\text{Substitution Costs} (\xi)}{\text{Avoided use or emission (Kg)}} \quad (\text{Eq. 3}) $$

$$ \text{Hazard-basedCost-Effectiveness} = \frac{\text{Substitution Costs} (\xi)}{\text{Avoided use or emission (Kg)} * \text{Hazard Score}} \quad (\text{Eq. 4}) $$

In Eq. (4), since avoided use (or emissions) is in indicator (proxy) of exposure, its product with the hazard indicator can be regarded as an effect indicator. We will test the different hazard scores defined in 2.1, but we believe that it seems a priori more justified to use the M score because, since it is closer to the definition of risk, the denominator it forms with avoided use (or emissions) in Eq. (4) is also closer to an actual effect of chemicals on human health and the environment.

## 2.3. Discounting

From an economic perspective, the effect of long-term persistence of a chemical raises the question of the relative importance of its impacts occurring in the present time or near future, compared to those occurring in the distant future. The practice of economic discounting is based on the empirical finding that consequences further in the future are less valued by people. Discounting allows to convert into comparable “present values” costs or effects that happen over different future periods. In CEA, discounting can intervene for both the costs (numerator in Eq. (3)&4), to account for the temporal evolution of both investment and operation costs related to the substitution of chemicals, or for the effects (denominator in Eq. (3)&4).

Regarding the discounting of costs, costs were extracted from regulatory REACH Dossiers in which they are discounted, in general at 4%. Regarding the discounting of the future effects of chemicals it can be justified, per se, and to mirror the parallel discounting of risk management costs (Gabbert et al., 2014).

On the other hand, since the very concern about persistence is that impacts can spread over very long and intergenerational timeframes, and can be almost irreversible, the relevance of discounting can be questioned (Sáez and Requena, 2007). Therefore, we did not make a choice between discounting and not discounting and preferred to look at

the sensitivity of policy priorities with respect to discounting and the value of the discount rate. Discounting was applied to the half-life parameter that embeds the time dimension in the effect indicator. Simple calculations show that discounting future impacts of a given chemical of half-life H, at discount rate d, is mathematically equivalent to replacing H by the following “discounted” half-life (Eq. (5)):

$$ H_{disc} = \frac{\ln 2 * H}{\ln 2 + d * H} \quad (\text{Eq. 5}) $$

This makes obvious that a significant and debatable feature of discounting (at rate d) future impacts is that it is equivalent to cap the maximum value of the half-life of any chemical to ln(2)/d. For example, with an annual discount rate of 4% (modal value in a survey of economist's views (Drupp et al., 2018) regarding the choice of a discount rate) this represents 17.3 years. This is similar as neglecting impacts beyond the present generation, which is of course highly debatable. Since the legitimacy of discounting and the choice of any discounting rate appear questionable, insensitivity to the discounting rate would be an asset for a decision support method.

## 2.4. Measuring distance between rankings

This work involved comparing different orderings of hazard scores of chemicals, and of C/E ratios for risk management decisions on chemicals. We used as a measure of similarity between two orderings the classical Kendall's tau distance (Kendall, 1938). The Kendall's tau distance is counting all inversions of priority between all pairs of items

between the two rankings. We further introduced weighing as proposed in (Kumar and Vassilvitskii, 2010) to account for the fact that inversions occurring near the head of the list (when items are sorted in decreasing priority order) are a more important difference than when they occur at its tail. We also weighed the distance to account for the fact that inversions between close items are less significant than when those items are distant within each of the rankings. Distances were further normalized between 0 and 1, the maximum distance being the expected distance between two random orderings. Distance between random orderings was computed by generating pairs of random orderings and calculating their distance until observing its convergence.

## 2.5. Database for chemicals' hazard scores

A database of P, B, and T (ecotoxicity) properties for 111 chemicals (being or not classified as PBT or vPvB from a regulatory point of view), was assembled with information collected from the Ineris Chemicals Information Portal that provides detailed information on ecotoxicological, toxicological and physico-chemical properties of chemicals (substances.ineris.fr).

The indicator used for overall persistence is the half-life DT50 in fresh water (denoted elsewhere in the paper by H). The overall persistence (Pov) would generally be preferred over half-life to define persistence because it considers the persistence in all environmental compartments and the degree of migration of the substance between compartments (OECD, 2002). However, the Pov is difficult to measure and very few substances have a documented Pov.

Bioaccumulation is the potential for a chemical to accumulate in the tissues of an organism. Generally, the level of bioaccumulation of a substance is expressed by the bioaccumulation factor (BAF), which describes the relationship between the concentration in the surrounding
<table><caption>**Table 1**
Summary statistics of hazard scores for chemicals.</caption><thead><tr><th></th><th>PBT</th><th>vPvBT</th><th>PBvT</th><th>PBvvT</th><th>vPvBvvT</th><th>C1</th><th>M</th></tr></thead><tbody><tr><td>Mean</td><td>1,20</td><td>1,09</td><td>0,97</td><td>0,74</td><td>0,63</td><td>5,58</td><td>3,18E+12</td></tr><tr><td>Median</td><td>1,14</td><td>1,03</td><td>0,89</td><td>0,70</td><td>0,58</td><td>5,83</td><td>472500,00</td></tr><tr><td>Mode</td><td>0,16</td><td>0,06</td><td>0,16</td><td>0,16</td><td>0,06</td><td>3,55</td><td>12222,22</td></tr><tr><td>Standard deviation</td><td>0,76</td><td>0,72</td><td>0,77</td><td>0,68</td><td>0,63</td><td>2,46</td><td>2,76E+13</td></tr><tr><td>Variance</td><td>0,58</td><td>0,52</td><td>0,59</td><td>0,46</td><td>0,39</td><td>6,07</td><td>7,62E+26</td></tr><tr><td>Kurstosis</td><td>-0,69</td><td>-0,49</td><td>-0,47</td><td>0,35</td><td>1,06</td><td>-1,04</td><td>109,16</td></tr><tr><td>Minimum</td><td>0,00</td><td>0,00</td><td>0,00</td><td>0,00</td><td>0</td><td>1</td><td>0,64</td></tr><tr><td>Maximum</td><td>2,98</td><td>2,96</td><td>2,95</td><td>2,74</td><td>2,68</td><td>10,00</td><td>2,96E+14</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Mean relative distances between lists of chemicals prioritized with different scoring systems.</figcaption></figure>

environment (often aquatic), and the concentration of the chemical in the living organism. The BAF is usually defined by the product between the biomagnification factor (BMF) and the bioconcentration factor (BCF). The BMF is the level of accumulation through the food chain while the BCF represents the assimilation through direct exposure (dermal exposure and respiration) (Kidd et al., 2019). This study used the BCF and not the BAF because of the limited availability of data on the BMF for many chemicals. Another reason to use the BCF was the possibility, in future studies, to extend the database of BCFs to more chemicals, using QSAR modelling.

In this study we focussed on the toxicity for ecosystems, and used

therefore the Predicted No Effect Concentrations (PNEC for different media and different species). The PNEC corresponds to the Non-Observed Effects Concentration (NOEC), or LC50 default data, modified by a safety factor (10, 100, ... specific to each chemical). This safety factor is defined by experts and takes into account extrapolation and uncertainties.

## 2.6. Data for cost-effectiveness analysis

This study compares priorities for chemicals risk management policy measures (REACH restrictions), when using C/E ratio without hazard score, or Hazard-based C/E with the PBT (and variants), M, and C1 scores detailed above.

Given the limited information on substitution costs and limited number of available regulatory past C/E assessments under REACH, this comparison has been conducted for a limited selection of 18 risk management proposals on the 11 following chemicals or groups of chemicals, intentionally mixing classified PBTs, vPvBs, under REACH, and other chemicals: Decabromodiphenyl Ether (DecaBDE), Hexabromocyclododecane (HBCDD), Perfluorooctanoic acid (PFOA), Perfluorohexanoic acid (PFHxA), Mercury (Hg), Lead (Pb), Nonylphenol, Four Phthalates (DEHP, BBP, DBP, DIBP), Bisphenol A (BPA), Cyclosiloxanes (D4/D5/D6), and Calcium Cyanamide.

The costs and on emission reductions for these 18 risk management proposals were taken directly from the corresponding Restriction Dossiers elaborated under REACH (all available on the ECHA Website at https://echa.europa.eu/fi/registry-of-restriction-intentions). For phthalates, the Restriction Dossier did not assess the emission reductions (but instead reductions in quantities placed on the market), and (Chapon et al., 2023) was used to convert quantities not placed on the market to emissions reductions, using emission factors. Cost and emission

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Chemicals more often prioritized across all ranking systems (expressed in % of chemicals that occur more frequently among the first fifteen priorities).</figcaption></figure>
<table><caption>**Table 2**
Scores for the first 15 chemicals in each scoring system.</caption><thead><tr><th>Chemical</th><th>vPvBT</th><th>Chemical</th><th>PBvT</th><th>Chemical</th><th>PBvvT</th><th>Chemical</th><th>vPvBvvT</th><th>Chemical</th><th>PBT</th><th>Chemical</th><th>M</th><th>Chemical</th><th>C1</th></tr></thead><tbody><tr><td>Hg</td><td>2.957</td><td>Hg</td><td>2.952</td><td>DDT</td><td>2.744</td><td>Hg</td><td>2.682</td><td>Hg</td><td>2.981</td><td>Hg</td><td>2.96E+14</td><td>Hg</td><td>10.000</td></tr><tr><td>HBCDD</td><td>2.804</td><td>DDT</td><td>2.849</td><td>Hg</td><td>2.706</td><td>DDT</td><td>2.657</td><td>HBCDD</td><td>2.905</td><td>HBCDD</td><td>5.84E+13</td><td>HBCDD</td><td>9.710</td></tr><tr><td>DDT</td><td>2.773</td><td>HBCDD</td><td>2.733</td><td>Benzo[a]pyrene (BaP)</td><td>2.516</td><td>Benzo[a]pyrene (BaP)</td><td>2.368</td><td>DDT</td><td>2.860</td><td>DecaBDE</td><td>2.00E+13</td><td>DecaBDE</td><td>9.669</td></tr><tr><td>D4</td><td>2.589</td><td>Benzo[a]pyrene (BaP)</td><td>2.643</td><td>Dicofol</td><td>2.403</td><td>Dicofol</td><td>2.144</td><td>D4</td><td>2.775</td><td>PFOS</td><td>1.40E+12</td><td>DDT</td><td>9.590</td></tr><tr><td>Benzo[a]pyrene (BaP)</td><td>2.508</td><td>D4</td><td>2.560</td><td>Pyrene</td><td>2.238</td><td>HBCDD</td><td>1.942</td><td>Benzo[a]pyrene (BaP)</td><td>2.656</td><td>Chlordane</td><td>1.33E+12</td><td>Benzo[a]pyrène (BaP)</td><td>9.530</td></tr><tr><td>Dicofol</td><td>2.272</td><td>Dicofol</td><td>2.519</td><td>HBCDD</td><td>2.043</td><td>Pyrene</td><td>1.936</td><td>Dicofol</td><td>2.531</td><td>DDT</td><td>7.12E+11</td><td>Pyrene</td><td>9.347</td></tr><tr><td>DecaBDE</td><td>2.170</td><td>DecaBDE</td><td>2.433</td><td>DecaBDE</td><td>2.000</td><td>Chlordane</td><td>1.912</td><td>DecaBDE</td><td>2.493</td><td>Heptachlore</td><td>5.18E+11</td><td>Chlordane</td><td>9.220</td></tr><tr><td>PFOS</td><td>2.160</td><td>Pyrene</td><td>2.374</td><td>Chlordane</td><td>1.964</td><td>Heptachlore</td><td>1.850</td><td>PFOS</td><td>2.480</td><td>Benzo[a]pyrene (BaP)</td><td>2.33E+11</td><td>Dicofol</td><td>9.103</td></tr><tr><td>Pyrene</td><td>2.087</td><td>Fluorene</td><td>2.269</td><td>Heptachlore</td><td>1.937</td><td>Triazophos</td><td>1.767</td><td>Fluorene</td><td>2.411</td><td>Pyrene</td><td>2.29E+11</td><td>1,2,3,4-Tetrachloronaphthalene</td><td>9.085</td></tr><tr><td>Fluorene</td><td>2.035</td><td>Anthracene</td><td>2.020</td><td>Plomb</td><td>1.874</td><td>D4</td><td>1.679</td><td>Pyrene</td><td>2.389</td><td>Dicofol</td><td>4.05E+10</td><td>heptachlore</td><td>9.067</td></tr><tr><td>Triazophos</td><td>1.952</td><td>2,2',6,6'-tétrabromo-4,4'-isopropylidenediphenol</td><td>1.991</td><td>D4</td><td>1.865</td><td>DecaBDE</td><td>1.677</td><td>Nonylphenol</td><td>2.147</td><td>D4</td><td>9.05E+09</td><td>Triazophos</td><td>9.048</td></tr><tr><td>Chlordane</td><td>1.913</td><td>Nonylphenol</td><td>1.965</td><td>Triazophos</td><td>1.790</td><td>1,2,3,4-Tetrachloronaphthalene</td><td>1.520</td><td>DIBP</td><td>2.146</td><td>Triazophos</td><td>8.62E+09</td><td>D4</td><td>8.937</td></tr><tr><td>PFHxA</td><td>1.908</td><td>Chlordane</td><td>1.964</td><td>PFOS</td><td>1.609</td><td>Lead</td><td>1.402</td><td>2,2',6,6'-tetrabromo-4,4'-isopropylidenediphenol</td><td>2.139</td><td>Lead</td><td>6.84E+09</td><td>Fluorene</td><td>8.710</td></tr><tr><td>1,2,3,4-Tetrachloronaphthalene</td><td>1.896</td><td>Triazophos</td><td>1.957</td><td>Fluorene</td><td>1.605</td><td>PFOS</td><td>1.289</td><td>Anthracene</td><td>2.131</td><td>2,4-dinitrotoluene</td><td>6.00E+09</td><td>Plomb</td><td>8.661</td></tr><tr><td>2,4-dinitrotoluene</td><td>1.871</td><td>Heptachlore</td><td>1.937</td><td>1,2,3,4-Tetrachloronaphthalene</td><td>1.579</td><td>Fluorene</td><td>1.229</td><td>BBP</td><td>1.990</td><td>Fluorene</td><td>2.14E+09</td><td>Trifluraline</td><td>8.583</td></tr></tbody></table>

<table><thead><tr><th>Chemical</th><th>vPvBT</th><th>Chemical</th><th>PBvT</th><th>Chemical</th><th>PBvvT</th><th>Chemical</th><th>vPvBvvT</th><th>Chemical</th><th>PBT</th><th>Chemical</th><th>M</th><th>Chemical</th><th>C1</th></tr></thead><tbody><tr><td>Hg</td><td>2957</td><td>Hg</td><td>2952</td><td>DDT</td><td>2744</td><td>Hg</td><td>2682</td><td>Hg</td><td>2981</td><td>Hg</td><td>2,96E+14</td><td>Hg</td><td>10,000</td></tr><tr><td>HBCDD</td><td>2804</td><td>DDT</td><td>2849</td><td>Hg</td><td>2706</td><td>DDT</td><td>2657</td><td>HBCDD</td><td>2905</td><td>HBCDD</td><td>5,84E+13</td><td>HBCDD</td><td>9710</td></tr><tr><td>DDT</td><td>2773</td><td>HBCDD</td><td>2733</td><td>Benzo[a]pyrene (BaP)</td><td>2516</td><td>Benzo[a]pyrene (BaP)</td><td>2368</td><td>DDT</td><td>2860</td><td>DecaBDE</td><td>2,00E+13</td><td>DecaBDE</td><td>9669</td></tr><tr><td>D4</td><td>2589</td><td>Benzo[a]pyrene (BaP)</td><td>2643</td><td>Dicofol</td><td>2403</td><td>Dicofol</td><td>2144</td><td>D4</td><td>2775</td><td>PFOS</td><td>1,40E+12</td><td>DDT</td><td>9590</td></tr><tr><td>Benzo[a]pyrene (BaP)</td><td>2508</td><td>D4</td><td>2560</td><td>Pyrene</td><td>2238</td><td>HBCDD</td><td>1942</td><td>Benzo[a]pyrene (BaP)</td><td>2656</td><td>Chlordane</td><td>1,33E+12</td><td>Benzo[a]pyrène (BaP)</td><td>9530</td></tr><tr><td>Dicofol</td><td>2272</td><td>Dicofol</td><td>2519</td><td>HBCDD</td><td>2043</td><td>Pyrene</td><td>1936</td><td>Dicofol</td><td>2531</td><td>DDT</td><td>7,12E+11</td><td>Pyrene</td><td>9347</td></tr><tr><td>DecaBDE</td><td>2170</td><td>DecaBDE</td><td>2433</td><td>DecaBDE</td><td>2000</td><td>Chlordane</td><td>1912</td><td>DecaBDE</td><td>2493</td><td>Heptachlore</td><td>5,18E+11</td><td>Chlordane</td><td>9220</td></tr><tr><td>PFOS</td><td>2160</td><td>Pyrene</td><td>2374</td><td>Chlordane</td><td>1964</td><td>Heptachlore</td><td>1850</td><td>PFOS</td><td>2480</td><td>Benzo[a]pyrene (BaP)</td><td>2,33E+11</td><td>Dicofol</td><td>9103</td></tr><tr><td>Pyrene</td><td>2087</td><td>Fluorene</td><td>2269</td><td>Heptachlore</td><td>1937</td><td>Triazophos</td><td>1767</td><td>Fluorene</td><td>2411</td><td>Pyrene</td><td>2,29E+11</td><td>1,2,3,4-Tetrachloronaphthalene</td><td>9085</td></tr><tr><td>Fluorene</td><td>2035</td><td>Anthracene</td><td>2020</td><td>Plomb</td><td>1874</td><td>D4</td><td>1679</td><td>Pyrene</td><td>2389</td><td>Dicofol</td><td>4,05E+10</td><td>heptachlore</td><td>9067</td></tr><tr><td>Triazophos</td><td>1952</td><td>2,2',6,6'-tétrabromo-4,4'-isopropylidenediphenol</td><td>1991</td><td>D4</td><td>1865</td><td>DecaBDE</td><td>1677</td><td>Nonylphenol</td><td>2147</td><td>D4</td><td>9,05E+09</td><td>Triazophos</td><td>9048</td></tr><tr><td>Chlordane</td><td>1913</td><td>Nonylphenol</td><td>1965</td><td>Triazophos</td><td>1790</td><td>1,2,3,4-Tetrachloronaphthalene</td><td>1520</td><td>DIBP</td><td>2146</td><td>Triazophos</td><td>8,62E+09</td><td>D4</td><td>8937</td></tr><tr><td>PFHxA</td><td>1908</td><td>Chlordane</td><td>1964</td><td>PFOS</td><td>1609</td><td>Lead</td><td>1402</td><td>2,2',6,6'-tetrabromo-4,4'-isopropylidenediphenol</td><td>2139</td><td>Lead</td><td>6,84E+09</td><td>Fluorene</td><td>8710</td></tr><tr><td>1,2,3,4-Tetrachloronaphthalene</td><td>1896</td><td>Triazophos</td><td>1957</td><td>Fluorene</td><td>1605</td><td>PFOS</td><td>1289</td><td>Anthracene</td><td>2131</td><td>2,4-dinitrotoluene</td><td>6,00E+09</td><td>Plomb</td><td>8661</td></tr><tr><td>2,4-dinitrotoluene</td><td>1871</td><td>Heptachlore</td><td>1937</td><td>1,2,3,4-Tetrachloronaphthalene</td><td>1579</td><td>Fluorene</td><td>1229</td><td>BBP</td><td>1990</td><td>Fluorene</td><td>2,14E+09</td><td>Trifluraline</td><td>8583</td></tr></tbody></table>
information and therefore C/E ratios used in REACH dossiers are in general very uncertain and we used for our comparison the central C/E ratios provided in the regulatory Dossiers.

# 3. Results and discussion

## 3.1. The ranking of chemicals and its sensitivity to prioritization systems

As an intermediate result, we first obtained scores and priority rankings (directly rankings for C2) for the 111 chemicals in our database. Table 1 provides descriptive statistics for the scores. By construction, scores PBT, vPvB, PBvT, PBvvT, vPvBvvT are between 0 and 1, C1 varies between 1 and 10, whereas M, also by design, varies over a vast range of orders of magnitude and has a sharper distribution around its mean (a few chemicals only having either much lower or higher scores). In the design of the M score, the use of original and non-normalized hazard values and the multiplicative formulation both intend to stick as much possible to the definition of risk and are the reasons for these different statistics.

We assess the sensitivity of rankings of prioritized chemicals to the type of scoring system, to regulatory thresholds, and to discounting of the impact indicator.

Fig. 1 shows, for each ranking, the mean of all its distances to all other rankings and is therefore an overall depiction of the extent to which each scoring system is providing similar prioritized lists of chemicals compared to others.

Overall, all the prioritized lists of chemicals appear statistically very close (distance far below 1). However, changes in thresholds of the PBT-score, especially the T-threshold of the PBT regulatory definition, has sometimes more impact than changing the scoring/ranking system itself. This confirms that introducing thresholds could impair the ranking robustness, since choosing a particular threshold necessarily involves some arbitrariness (Abelkop A.D.K. et al., 2015). It also appears that the outranking methods ELECTRE III (C1 and C2) that rank chemicals without requiring a score are the closest to all other rankings overall, while presenting the advantage of not relying on a particular mathematical formula or numerical threshold, and therefore this work tends to confirm this advantage already highlighted by (Sailaukhanuly et al., 2013).

Regarding the impact of the scoring/ranking system on top priority chemicals, only 9 chemicals appear in the 15 first priorities for all the 8 rankings we tested. Fig. 2 illustrates that there is some discrepancy between these top priorities, and that the level of consensus decays quite rapidly after the 9 chemicals that occur in all rankings. Table 2 provides the values of scores for the first 15 chemicals.

This aspect would call for using either several prioritization methods at the same time, or for the adoption of the methods that appear to be the close to all others (C1 or C2). Moreover, considering a collective expert and stakeholder judgement appears to be important in addition to automatic ranking, because uncertainties, lack of knowledge, and other qualitative information not included in the cost/effectiveness approach should be taken into account (ECHA, 2022).

Rankings were finally also tested to check their sensitivity to discounting, using 4% for that purpose. We find that the distances between PBT M, C1 and C2 rankings and their respective "discounted" counterparts are negligible (at least two orders of magnitude lower than those reported in Fig. 1). Therefore, the variety of prioritization methods for chemicals studied in this research are in practice quite insensitive to discounting the half-life characterizing chemical persistence.

## 3.2. Ranks of risk management actions and their sensitivity to chemical's hazard scores

The final objective of the study is to study whether priorities for actions to reduce the risk of chemicals, established with Hazard-CEA, depend on the specific chemical's hazard score. As already mentioned,

we worked on 18 REACH dossiers involving 14 chemicals (or groups of chemicals). Fig. 3 displays the ranks of these chemicals with the different hazard scores. As expected, policy interventions under REACH have overall targeted priority chemicals (especially for scores PBT, C1, M).

We first checked and found that, as was found when ranking chemicals, discounting the half-life (i.e the effect term) has no or negligible impact on the order of priorities provided by CEA. This could be an argument to use more widely CEA since CBA results (in terms of Net Present Values) are often sensitive to discount rates.

Table 3 provides all the C/E scores for all risk management measures. Fig. 4 provides a complete overview of how ranks change between different versions of Hazard-based and Standard CEA. It appears that all versions of PBT-Hazard CEA provide relatively close priorities. However, changing the design of the hazard scoring methods appears to have contrasting impacts: not significant for C1, but a strong impact for M. The M-Hazard CEA gives a quite different prioritized list of risk management measures, and tends to sharply increase priority for acting on some non-regulatory PBT/vPvB chemicals (Bisphenol A, Calcium cyanamide), and on Perfluorinated chemicals. This difference could be explained by the fact that the M-score is, in contrast to PBT (and its variations) and C, constructed as a proxy for risk integrating strong risk feedbacks between P, B and T, and not based on more arbitrary regulatory thresholds put independently on each criterion P, B and T. This raises the question whether using M-Hazard CEA would have changed past decisions. It is difficult to answer this question in general because decision under REACH is made case-by-case and uses other qualitative arguments. We however hereafter discuss the BPA and Calcium cyanamide cases. Regarding BPA, the benefits of this restriction were "unlikely to be proportionate" to its costs, and the decision was supported by arguments of affordability for consumers and equity considerations (European Union, 2016). Given the high priority for regulating BPA in thermal paper shown by M-Hazard CEA, using M-Hazard CEA might have demonstrated the proportionality better than CBA and made the decision easier. The situation is similar for calcium cyanamide, because the standard C/E analysis alone did not allow a proportionality conclusion because of the uncertainty on costs (ECHA, 2020). These two cases support the idea that using M-hazard CEA, further to making better decisions, could help make decision easier.

Both PBT/vPvB and non-PBT/vPvB chemicals appear in top priorities, and top priorities found consistently in all rankings include several phthalates, that are not regulated as PBT/vPvB under REACH. Therefore it seems interesting to have an integrated assessment within a unique economic Hazard-CEA and avoid that two different methods are applied to the two categories in REACH. Hazard-based management of chemicals is currently on the policy agenda in the EU, to avoid long and burdensome health and environmental impact assessments of chemicals prior to decision-making, and better implementation of the precautionary principle. In this context, CEA looks more adapted than CBA, and Hazard-CEA could therefore be a convenient decision support tool.

Our results also suggest that weighing and thresholds in hazard scores do not appear to have a significant impact on the outcome of Hazard-CEA. However, the design of the scoring method for hazard does seem to have one. An adequate hazard scoring system should be used, and we suggest using an integrated and unweighted scoring method such as M, in which trade-offs between the different dimensions of hazards are based on the notion of risk, and that better represents an actual effect when combined to avoided use/emissions in Eq. (4).

Our findings would need to be confirmed by extending the list of risk management measures used for our comparison, but given that this list currently spans over around 10 orders of magnitudes for M-Hazard-based CEA ratios (as shown in Fig. 5), and over 5 orders of magnitude for the Standard, PBT and C1 CEA ratios, it is already based on a wide range of cost/effectiveness situations. The higher variability for M-Hazard-based CEA ratios is an expected and direct consequence of the design of the M score (see section 3.1).
<figure><img src="image_6.png" /><figcaption>Fig. 3. Hazard-based ranks of chemicals involved in the comparative assessment of Hazard-based Cost/Effectiveness.</figcaption></figure>

<table><caption>**Table 3**
C/E scores (for all Hazard-based and standard C/E) and for all risk management measures.</caption><thead><tr><th>Chemical Risk Management Measure</th><th>vPvBvvT</th><th>vPvBT</th><th>PBvT</th><th>PBvvT</th><th>PBT</th><th>M</th><th>C1</th><th>Standard</th></tr></thead><tbody><tr><td>DecaBDE</td><td>1,3E-03</td><td>9,9E-04</td><td>8,9E-04</td><td>1,1E-03</td><td>8,6E-04</td><td>1,1E-16</td><td>2,2E-04</td><td>4,6E+02</td></tr><tr><td>D4 in cosmetics</td><td>1,5E-03</td><td>9,7E-04</td><td>9,8E-04</td><td>1,3E-03</td><td>9,0E-04</td><td>2,8E-13</td><td>2,7E-04</td><td>4,0E+02</td></tr><tr><td>Hg in measuring devices</td><td>9,1E-05</td><td>8,2E-05</td><td>8,3E-05</td><td>9,0E-05</td><td>8,2E-05</td><td>8,3E-19</td><td>2,5E-05</td><td>4,1E+03</td></tr><tr><td>HBCDD in expended polystyrene</td><td>1,0E-04</td><td>6,9E-05</td><td>7,1E-05</td><td>9,5E-05</td><td>6,7E-05</td><td>3,3E-18</td><td>3,3E-05</td><td>5,1E+03</td></tr><tr><td>PFOA (general)</td><td>5,2E-04</td><td>5,2E-04</td><td>4,0E-04</td><td>4,0E-04</td><td>4,0E-04</td><td>5,1E-12</td><td>6,1E-05</td><td>1,6E+03</td></tr><tr><td>Lead in PVC</td><td>2,3E-03</td><td>2,2E-03</td><td>1,7E-03</td><td>1,7E-03</td><td>1,7E-03</td><td>4,7E-13</td><td>3,6E-04</td><td>3,1E+02</td></tr><tr><td>Lead in Ammunitions</td><td>0,08</td><td>0,08</td><td>0,06</td><td>0,06</td><td>0,06</td><td>0,00</td><td>0,01</td><td>9,00</td></tr><tr><td>Nonylphenol in textiles</td><td>0,01</td><td>0,01</td><td>0,01</td><td>0,01</td><td>0,01</td><td>0,00</td><td>0,00</td><td>83,00</td></tr><tr><td>DEHP in indoor consumer articles</td><td>5,49</td><td>0,32</td><td>0,43</td><td>1,01</td><td>0,25</td><td>0,00</td><td>0,06</td><td>3,23</td></tr><tr><td>BBP in indoor consumer articles</td><td>0,43</td><td>0,30</td><td>0,33</td><td>0,33</td><td>0,25</td><td>0,00</td><td>0,06</td><td>2,03</td></tr><tr><td>DBP in indoor consumer articles</td><td>1,38</td><td>0,43</td><td>0,64</td><td>0,73</td><td>0,34</td><td>0,00</td><td>0,09</td><td>2,03</td></tr><tr><td>DIBP in indoor consumer articles</td><td>0,58</td><td>0,28</td><td>0,29</td><td>0,41</td><td>0,23</td><td>0,00</td><td>0,09</td><td>2,03</td></tr><tr><td>PFHxA in fluoropolymers manufacture</td><td>5,6E-05</td><td>2,9E-05</td><td>4,1E-05</td><td>5,6E-05</td><td>2,9E-05</td><td>7,3E-13</td><td>6,5E-06</td><td>1,8E+04</td></tr><tr><td>PFHxA in greaseproof papers</td><td>1,2E-03</td><td>6,1E-04</td><td>8,4E-04</td><td>1,2E-03</td><td>6,1E-04</td><td>1,5E-11</td><td>1,9E-04</td><td>8,6E+02</td></tr><tr><td>Calcium Cyanamide (fertilizer)</td><td>3,7E-03</td><td>1,0E-03</td><td>1,1E-03</td><td>2,9E-03</td><td>9,4E-04</td><td>5,0E-09</td><td>1,6E-04</td><td>9,4E+02</td></tr><tr><td>D4/D5 in wash-off cosmetics</td><td>1,4E-03</td><td>9,3E-04</td><td>9,4E-04</td><td>1,3E-03</td><td>8,7E-04</td><td>2,7E-13</td><td>3,1E-04</td><td>4,2E+02</td></tr><tr><td>D4/D5/D6 (consumer uses and dry cleaning)</td><td>6,0E-04</td><td>3,9E-04</td><td>3,9E-04</td><td>5,4E-04</td><td>3,6E-04</td><td>1,1E-13</td><td>1,5E-04</td><td>1,0E+03</td></tr><tr><td>BPA in thermal papers</td><td>5,0E-04</td><td>3,3E-05</td><td>6,4E-05</td><td>2,0E-04</td><td>3,0E-05</td><td>2,3E-11</td><td>3,8E-06</td><td>3,2E+04</td></tr></tbody></table>

Our work is complementary to other work that seeks to improve the physical “Avoided use or emission” indicator in (Eq. (3)&4) to take into account the avoided building of stock of chemical in the environment (Gabbert et al., 2023), or in the technosphere (Chapon et al., 2023), that are currently disregarded in the risk management of chemicals under REACH. Improvements in the assessment of substitution costs of chemicals can also improve the reliability of Cost-effectiveness analysis. In the future, combining our work with these other developments could be fruitful.

### 3.3. Conclusion

The aim of this study was to test the extension of the current standard application of CEA for supporting decisions on chemicals policy, by introducing a hazard score in the effect term of the CEA ratio.

Our results for this “Hazard CEA” suggest that weighing and thresholds in hazard scores do not appear to have a significant impact on

the outcome of Hazard-CEA. However, the design of the scoring method for hazard does seem to have one. An adequate hazard scoring system should be used, and we suggest using an integrated and unweighted scoring method in which trade-offs between the different dimensions of hazards are based on the notion of risk.

It seems useful to use Hazard-CEA for both PBT/vPvB and non-PBT/vPvB chemicals, since priorities appear to mix both categories of chemicals, and to avoid that two different methods are applied to the two categories in REACH. Hazard-CEA is less burdensome than cost-benefit analysis, and avoids its methodological difficulties and debates around economic valuation of impacts, and therefore could be a tool to implement the new chemicals strategy of the European Union and accelerate the substitution of harmful chemicals. Our work also supports the idea that using M-hazard CEA, further to making better decisions, could help make decision easier.

The relevance of Hazard-based CEA could however be limited by data availability, since persistence in fresh water (and not in all
<figure><img src="image_7.png" /><figcaption>Fig. 4. ranks of Risk management measures and their fluctuations between CEA indicators used (“Std” stands for Standard CEA without hazard scoring factor).</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 5. B-Hazard-based C/E ratios of Risk management actions ranked by decreasing cost/effectiveness (in logarithmic units).</figcaption></figure>

environmental compartments) or BCFs and not BAFs are available in general.

Finally, considering non-quantified information on costs and benefits of the public interventions, resorting to collective judgement with experts and stakeholders beyond mathematical classifications and assessments is also important to ensuring progress in decision making on chemicals.

## Funding

This work was supported by ANSES, the French Agency for Health and the Environment.

## CRediT authorship contribution statement

**Jean-Marc Brignon:** Conceptualization, Funding acquisition, Methodology, Project administration, Writing – original draft, Writing – review & editing. **Jean-Christophe Vergnaud:** Conceptualization, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing. **Sandrine Andres:** Conceptualization, Data curation, Methodology, Writing – original draft, Writing – review & editing.

**Enrico Mombelli:** Conceptualization, Methodology, Writing – original draft, Writing – review & editing. **Tsarafara Rambolarimanana:** Data curation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing.
Declaration of competing interest

The authors declare the following financial interests/personal re-
lationships which may be considered as potential competing interests:
Jean-Marc BRIGNON reports financial support was provided by French
Agency for Food, Environmental and Occupational Health & Safety.

Data availability

Data will be made available on request.

References

Abelkop, A.D.K., Graham, J.D., Royer, T.V., 2015. Persistent, Bioaccumulative, and Toxic (PBT) Chemicals: Technical Aspects, Policies, and Practices. CRC Press, Boca Raton, FL.

Arp, H.P.H., Brown, T.N., Berger, U., Hale, S.E., 2017. Ranking REACH registered neutral, ionizable and ionic organic chemicals based on their aquatic persistency and mobility. In: Environmental Science: Processes and Impacts, 19. Royal Society of Chemistry (RSC), pp. 939–955. https://doi.org/10.1039/c7em00158d.

Benfenati, E., et al., 2016. "PROMETHEUS - Prioritization of Chemicals: a METHodology Embracing PBT Parameters into a Unified Strategy," Umweltbundesamt Report No. (UBA-FB) 002233/ENG.

Bouyssou, D., 1992. Ranking methods based on valued preference relations: a characterization of the net flow method. Eur. J. Oper. Res. 60, 61–67, 1992.

Chapon, V., Brignon, J.-M., Gasperi, J., 2023. Non-persistent chemicals in polymer and non-polymer products can cause persistent environmental contamination: evidence with DEHP in Europe. In: Environmental Science and Pollution Research, 30. Springer Science and Business Media LLC, pp. 44952-44962. https://doi.org/10.1007/s11356-023-25405-x.

Drupp, M.A., Freeman, M.C., Groom, Nesje, F., 2018. Discounting disentangled. Am. Econ. J. Econ. Pol. 10 (4), 109–134.

Department for Communities and Local Government. 2009. Multicriteria analysis : a manual. https://assets.publishing.service.gov.uk/government/uploads/system/uplo-
ads/attachment_data/file/7612/1132618.pdf.

ECHA, 2008. Guidance on socio-economic analysis – restrictions. https://www.echa.europa.eu/documents/10162/2324906/sea_restrictions_en.pdf/2d7c8e06-b5dd-40fc-b646-3467b5082a9d.

ECHA, 2011. Guidance on the preparation of socio-economic analysis as part of an application for authorisation. https://echa.europa.eu/documents/10162/2324906/sea_authourisation_en.pdf/aadf96ec-fbfa-4bc7-9740-a3f6ceb68e6e.

ECHA, 2016. Evaluation of restriction reports and applications for authorisation for PBT and vPvB substances in SEAC. SEAC/31/2016/05 Rev.1. https://echa.europa.eu/documents/10162/13580/evaluation_pbt_vpb_substances_seac_en.pdf/af4a7207-f7ad-4ef3-ac68-685f70ab2db3.

ECHA, 2020. Committee for Risk Assessment (RAC), Committee for Socio-Economic Analysis (SEAC), Opinion on an Annex XV Dossier Proposing Restrictions on Calcium Cyanamide, ECHA/RAC/RES-O-0000006784-64-01/F, ECHA/SEAC/RES-O-0000006970-62-01/F.

ECHA, 2022. SEAC's Evaluation of Qualitative Assessments in Restriction Reports, SEAC/57/2022/01. https://echa.europa.eu/documents/10162/17087/evaluation_qualifiedAssessments_seac_en.pdf/40903c2b-341e-b52c-0968-72f105e28faa?t=1681969785805.

European Union, 2016. Commission Regulation (EU) 2016/2235 of 12 December 2016 Amending Annex XVII to Regulation (EC) No 1907/2006 of the European Parliament and of the Council Concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) as Regards Bisphenol A (Text with EEA Relevance) C/2016/7895.

Figueira, J., et al., 2005. Multiple Criteria Decision Analysis: State of the Art Surveys. Springer.

Gabbert, S., Scheringer, M., Ng, C.A., Stolzenberg, H.-C., 2014. Socio-economic analysis for the authorisation of chemicals under REACH: a case of very high concern?. In: Regulatory Toxicology and Pharmacology, 70. Elsevier BV, pp. 564–571. https://doi.org/10.1016/j.yrtph.2014.08.013.

Gabbert, S., Hilber, I., 2020. Socio-economic analysis in REACH restriction dossiers for chemicals management: a critical review. Ambio 49, 1394-1411.

Foss Hansen, S., Carlsen, L., Tickner, J.A., 2007. Chemicals regulation and precaution: does REACH reallyincorporate the precautionary principle. Environ. Sci. Pol. 10, 395-404.

Gabbert, S., de Blaeij, A., Quik, J.T.K., Bakker, J., de Knecht, J., Verbruggen, E., Luit, R., 2023. Can cost-effectiveness analysis of control measures for persistent chemicals be improved? A critical evaluation of approaches for assessing “effectiveness.”. J. Ind. Ecol. 27, 155-169. https://doi.org/10.1111/jiec.13329.

Gramatica, P., Cassani, S., Sangion, A., 2015. PBT assessment and prioritization by PBT Index and consensus modeling: comparison of screening results from structural models. Environ. Int. 77, 25-34.

Karr, G., Boudet, C., Le-Gall, A.-C., Brignon, J.-M., Rouil, L., Ramel, M., 2014. Aide au choix de substances prioritaires en santé environnementale : un processus associant un avis d'expert et une analyse multicritère participative. Environnement, Risques & Santé 13, n82.

Kendall, M., 1938. A new measure of rank correlation. Biometrika 30 (1-2), 81-89.

Kidd, K.A., Burkhard, L.P., Babut, M., Borga, K., Muir, D.C., Perceval, O., Ruedel, H., Woodburn, K., et Embry, M.R., 2019. Practical advice for selecting or determining trophic magnification factors for application under the European Union Water Framework Directive. Integrated Environ. Assess. Manag. 15 (2), 266-277.

Kumar, R., Vassilvitskii, S., 2010. Generalized distances between rankings. In: Proceedings of the 19th International Conference on World Wide Web, WWW '10. ACM, New York, NY, USA, pp. 571-580.

Matthies, M., Solomon, K., Vighi, M., Gilmand, A., Tarazona, J.V., 2016. The origin and evolution of assessment criteria for persistent, bioaccumulative and toxic (PBT) chemicals and persistent organic pollutants (POPs). Environ. Sci. J. Integr. Environ. Res.: Process. Impacts 18, 1114-1128.

Nendza, M., Hahn, S., Klein, M., Klaschka, U., Gabbert, S., 2023. Scoring scheme for Comparative Ranking of impact potential of chemical Alternatives (SCoRA). In: Environmental Sciences Europe, 35. Springer Science and Business Media LLC. https://doi.org/10.1186/s12302-023-00718-3.

OECD, 2002. Series on Testing and Assessment, Number 36, Report of the OECD/UNEP 12 Workshop on the Use of Multimedia Models for Estimating Overall Environmental Persistence 13 and Long-Range Transport in the Context of PBTs/POPs Assessment. ENV/JM/MONO(2002)15 14 (available at: 15. http://www.oecd.org/officialclements/publicdisplaydocumentpdf/cote=env/jm/mono(2002)1165&do language=en. (Accessed 18 September 2020).

Oka, T., 2003. Cost-effectiveness analyses of chemical risk control policies in Japan. Chemosphere 53 (4), 413–419. https://doi.org/10.1016/s0045-6535(03)00007-9.

Oosterhuis, F., Brouwer, B., Janssen, M., Verhoeven, J., Luttikhuizen, C., 2017. Towards a proportionality assessment of risk reduction measures aimed at restricting the use of persistent and bioaccumulative substances. Integrated Environ. Assess. Manag. 13 (6), 1100-1112.

Pizzo, F., Lombardo, A., Manganaro, A., Cappelli, C.I., Petoumenou, M.I., Albanese, F., Roncaglioni, A., Brandt, M., Benfenati, E., 2016. Integrated in silico strategy for PBT assessment and prioritization under REACH. Environ. Res. 151, 478-492.

Reppas-Chrysovitsinos, E., Sobek, A., MacLeod, M., 2017. Screening-level exposure-
based prioritization to identify potential POPs, vPvBs and planetary boundary
threats among Arctic contaminants. Emerging Contam. 3 (2), 85-94. https://doi.
org/10.1016/j.emcon.2017.06.001.

Rorije, E., et al., 2011. Identifying Potential POP and PBT Substances Development of a New Persistence/Bioaccumulation Score, RIVM Report 601356001/2011.

Roy, B., Bouyssou, D., 1993. Aide multicritère à la décision: Méthodes et cas. Economica, Paris.

Sáez, C.A., Requena, J.C., 2007. Reconciling Sustainability and discounting in cost-benefit analysis: a methodological proposal. Ecol. Econ. 60 (4), 712-725. https://doi.org/10.1016/j.ecolecon.2006.05.002.

Sailaukhанuly, Y., Zhakupbekova, A., Amutova, F., Carlsen, L., 2013. On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example. Chemosphere 90 (1), 112-117.

Strempel, S., Scheringer, M., Carla, A. Ng, Hungerbühler, K., 2012. Screening for PBT chemicals among the “existing” and “new” chemicals of the EU. Environ. Sci. Technol. 46 (11), 5680-5687.