RIVM Publications Repository

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  • Publication
    Chain length and chlorine position affect biotransformation of chlorinated paraffins in an in vitro hepatic model.
    (2025-05-26) Ji, Yiran; Brandsma, Sicco H; Hamers, Timo; Cenijn, Peter; Gorovoy, Alexey; Liu, Huiling; van Mourik, Louise; Leonards, Pim E G
    Chlorinated paraffins (CPs) are emerging environmental contaminants with limited biotransformation data because of the complexity of CP technical mixtures and the lack of single congener standards. In this study, novel single CP congeners, with similar chlorine patterns to those found in technical mixtures, were incubated for 60 min with rat hepatic subcellular fractions to evaluate their relative biotransformation extent and identify their potential metabolites. Results demonstrated that these CP congeners were metabolized by phenobarbital and 5,6-benzoflavone-induced rat liver S9, following 1st-order kinetics. The 1st-order rate constants were logarithmically inversely related to the chain lengths at a given number of chlorine atoms. In turn, the chlorine positions affected the biotransformation pathways, resulting in the formation of different metabolites. Metabolites identified by high-resolution mass spectrometric analysis included (multi-)hydroxylated, carbonyl, carboxylic, and chain-shortened products. Hydrolytic and oxidative dechlorination, stepwise hydroxylation/oxidation, and C-C bond cleavage were identified as potential biotransformation pathways. A notable transformation of initial hydroxylated metabolites further into aldehydes and carboxylic acids (ω-oxidation) was emphasized. The study's results fill the knowledge gap in CP biotransformation and provide structural information on potentially bioactive CP metabolites for future synthesis and toxicity studies.
  • Item
    Verkenning proxies voor nitraat
    (Rijksinstituut voor Volksgezondheid en Milieu RIVM, 2025-07-11) van Mourik, LM; Spijker, J; van Duijnen, R
  • Publication
    Navigating the black box of fair national emissions targets
    (2025-06-16) Dekker, Mark M; Hof, Andries F; du Robiou Pont, Yann; van den Berg, Nicole; Daioglou, Vassilis; den Elzen, Michel; van Heerden, Rik; Hooijschuur, Elena; Schmidt Tagomori, Isabela; Würschinger, Chantal; van Vuuren, Detlef P
    Current national emissions targets fall short of the Paris Agreement goals, prompting the need for equitable ways to close this gap. Fair emissions allowances rely on efort-sharing formulas based on fairness principles, yielding diverse outcomes. These variations, shaped by normative decisions, complicate policymaking and legal assessments of climate targets. Here we provide up-to-date numbers, comprehensively accounting for three dimensions — physical and social uncertainties, global strategies and equity — and the relative impact of them on each country’s emissions allowance. In the short run, normative considerations substantially impact fair emissions allowances — directing current discussions to this debate — while global discussions on temperature targets and non-CO2 emissions take over in the long run. We identify many countries with insufcient nationally determined contributions in light of fairness and discuss implications for increased domestic mitigation and fnancing emissions reductions abroad — yielding a total international fnance fux of $US0.5–7.4 trillion in 2030.
  • Publication
    Incorporation of microbial strategies for carbon-utilization in interpreting soil priming effects induced by microplastics
    (2025-05-30) Liu, Yang; Zhang, Tingqin; Zhu, Lihua; Wu, Rongjia; Pan, Bo; Qiu, Hao; Vijver, Martina G; Peijnenburg, Willie JGM; Xing, Baoshan
  • Publication
    Modelling Near-Field Aerosol Exposure for Respiratory Infection Risk Assessment
    (2025-06-09) Delmaar, Christiaan JE; Vermeulen, Lucie C; Schijven, Jack F
    Quantitative microbiological risk assessment (QMRA) is a method to estimate the risk of infectious disease transmission from human exposure to pathogens. QMRA is a helpful tool to inform health policies to control the impact of infectious disease transmission from human-to-human transmissible infectious respiratory diseases. QMRA combines an estimate of pathogen exposure with information on the probability of infection given the dose. The infection risk of respiratory diseases is generally assumed to depend on the interpersonal distance between the infectious person (index) and the exposed recipient. To account for close-proximity exposure in QMRA, specific generic models are required. To be helpful in policy information, these models should be sufficiently accurate in describing elevated air concentrations of pathogens near the index. On the other hand, they should be sufficiently generic and flexible to be applied in generalized situations without requiring very specific and detailed situational information. In this work, we identified different models to account for near-field exposure in the literature: multizone, diffusion, and jet models. These methods were tested with respect to their applicability in QMRA. We evaluated them on the criteria of ease of use, the availability of parameter values for generic application, and their ability to describe air concentrations in realistic situations as replicated in experiments. It was found that only diffusion modelling appeared to be both flexible enough to describe experimental data and to be supported by sufficient information to allow for parametrization in a wide variety of situations. The multizone models were found to be easy to use but difficult to parametrize given the arbitrariness of aspects of the modelling method. The jet models were found to be more complex to implement and adapt to specific exposure scenarios.

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