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Abstract
Based on epidemiological records of workers at Ni operations, regulatory guidelines often target specific Ni compounds for setting exposure limits. Thus, reliable methods of Ni speciation in airborne dust samples are required for effective monitoring of workplace exposure. In this study, Ni speciation of dust collected from a stainless steel operation was performed using a variety of methods: Zatka sequential leaching (original and modified protocols), soluble and insoluble Ni as described in ISO 15202, and quantitative mineralogy (QEMSCAN). Mineral characterization was also performed on bulk material collected from selected work areas at the plant. The quantitative mineralogical analysis determined that the Ni dust is composed of oxidic Ni (Ni in chromite and trevorite, > 80 % of the Ni in most samples) and metallic Ni (Ni-Fe alloy), and the results were validated against chemical assays and alternate methods of mineral characterization (Electron Probe Microanalysis, EPMA). In contrast, the original Zatka method erroneously identified soluble Ni as a major Ni contributor, whereas the modified Zatka method identified sulfidic Ni. The mineralogy identified ambient dust and grain sizes and textures of individual Ni compounds as potential factors that can affect leaching selectivity. Improving methods of sequential leaching is important because the resolution of quantitative mineralogical techniques diminishes at < 3 µm (respirable dust fraction). We recommend that quantitative mineralogy be performed in parallel with methods of sequential leaching to provide a robust system of characterization.

Abstract
ECHA classified TiO2 particles with an aerodynamic diameter ≤10 μm as carcinogen. Although the OELV for TiO2 is still related to inhalable particles in many jurisdictions, NIOSH recommended a REL of 2.4 mg/m3 for fine TiO2, and 0.3 mg/m3 for ultrafine TiO2. The latter implies the development of a more robust method for measuring TiO2 in workplace air. X-ray diffraction (XRD) is a powerful laboratory method for quantifying crystalline matter and is frequently used to measure respirable crystalline silica in workplaces. Rutile and anatase powders were obtained from a commercial vendor and a size fraction smaller than 10 µm was separated from these powders and used to prepare a calibration series in a calm-air dust chamber. The methodology for quantifying the rutile or anatase is performed as described in ISO 16258-1:2015 for measuring respirable crystalline silica. The limit of detection and quantification (LOD/LOQ) were for rutile 0.8/1.4 µg and anatase 0.6/1.1 µg, respectively. From these measurements, we conclude that direct on filter XRD is a powerful method for analyzing respirable TiO2 samples. Further validation of the XRD method was performed by comparing the results of 177 respirable personal samples collected on 25 mm MCE filters using Casella-HD cyclone samplers at nine TiO2 production plants with ICP-MS data gained from the same samples. Excellent correlations were obtained between the XRD and ICP-MS data for each sampling site but observed consistent site-dependent deviations explained by differences in crystallinity of the TiO2 phases and the presence of titanium-containing minerals other than rutile and anatase.

Abstract
To ensure that regulatory compliance is maintained at mineral processing operations, worker exposure is regularly monitored. Determining the quantity and type of airborne particles permits the operation to identify the sources of dust, implement proper dust suppressant strategies, and ultimately, limit worker exposure. Conventional methods of analysis, such as chemical assay, are unable to rigorously differentiate between phases containing the same elements and may result in ambiguity related to identifying the source of airborne dust. A combination of Quantitative Evaluation of Materials by Scanning Electron Microscope (QEMSCAN) and chemical characterization has been used to evaluate personally taken size selective aerosol samples at key locations throughout a Cu smelter in Europe. Surface samples were also examined using higher resolution measurements. The Cu phases present in the workplace air samples are reflective of the activities performed at specific locations. Near the anode and electric furnace, the majority of Cu in the airborne dust is carried in metals and oxide phases (60-70%), and in the batch preparation area where Cu concentrate is received, significant amounts of Cu are carried in sulfide minerals (chalcocite, chalcopyrite/bornite, >40%). The results of the analysis will aid in the identification of the origin of emissions specific to location and activity, assist personnel in developing the appropriate mitigation strategies to limit workers exposure, and further understanding of the health risks associated with exposure. Additional metals of concern (e.g, Pb, As, and Cd) are also considered throughout this program.
Speaker Biography
Michelle Kelvin is a geoscientist and environmental mineralogist. She specializes in characterizing dust emissions that originate from industrial operations using modern geochemical methods and X-ray beam technologies.

Background: The Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation requires the establishment of Conditions of Use (CoU) for all exposure scenarios to ensure good communication of safe working practices. Setting CoU requires the risk assessment of all relevant Contributing Scenarios (CSs) in the exposure scenario. A new CS has to be created whenever an Operational Condition (OC) is changed, resulting in an excessive number of exposure assessments. An efficient solution is to quantify OC concentrations and to identify reasonable worst-case scenarios with probabilistic exposure modeling. Methods: Here, we appoint CoU for powder pouring during the industrial manufacturing of a paint batch by quantifying OC exposure levels and exposure determinants. The quantification was performed by using stationary measurements and a probabilistic Near-Field/Far-Field (NF/FF) exposure model. Work shift and OC concentration levels were quantified for pouring TiO 2 from big bags and small bags, pouring Micro Mica from small bags, and cleaning. The impact of exposure determinants on NF concentration level was quantified by (1) assessing exposure determinants correlation with the NF exposure level and (2) by performing simulations with different OCs. Results: Emission rate, air mixing between NF and FF and local ventilation were the most relevant exposure determinants affecting NF concentrations. Potentially risky OCs were identified by performing Reasonable Worst Case (RWC) simulations and by comparing the exposure 95 th percentile distribution with 10% of the occupational exposure limit value (OELV). The CS was shown safe except in RWC scenario (ventilation rate from 0.4 to 1.6 1/h, 100 m 3 room, no local ventilation, and NF ventilation of 1.6 m 3/min). Conclusions: The CoU assessment was considered to comply with European Chemicals Agency (ECHA) legislation and EN 689 exposure assessment strategy for testing compliance with OEL values. One RWC scenario would require measurements since the ...

Immune-mediated, noncommunicable diseases-such as autoimmune and inflammatory diseases-are chronic disorders, in which the interaction between environmental exposures and the immune system plays an important role. The prevalence and societal costs of these diseases are rising in the European Union. The EXIMIOUS consortium-gathering experts in immunology, toxicology, occupational health, clinical medicine, exposure science, epidemiology, bioinformatics, and sensor development-will study eleven European study populations, covering the entire lifespan, including prenatal life. Innovative ways of characterizing and quantifying the exposome will be combined with high-dimensional immunophenotyping and-profiling platforms to map the immune effects (immunome) induced by the exposome. We will use two main approaches that "meet in the middle"-one starting from the exposome, the other starting from health effects. Novel bioinformatics tools, based on systems immunology and machine learning, will be used to integrate and analyze these large datasets to identify immune fingerprints that reflect a person's lifetime exposome or that are early predictors of disease. This will allow researchers, policymakers, and clinicians to grasp the impact of the exposome on the immune system at the level of individuals and populations.

Immune-mediated, noncommunicable diseases-such as autoimmune and inflammatory diseases-are chronic disorders, in which the interaction between environmental exposures and the immune system plays an important role. The prevalence and societal costs of these diseases are rising in the European Union. The EXIMIOUS consortium-gathering experts in immunology, toxicology, occupational health, clinical medicine, exposure science, epidemiology, bioinformatics, and sensor development-will study eleven European study populations, covering the entire lifespan, including prenatal life. Innovative ways of characterizing and quantifying the exposome will be combined with high-dimensional immunophenotyping and -profiling platforms to map the immune effects (immunome) induced by the exposome. We will use two main approaches that "meet in the middle"-one starting from the exposome, the other starting from health effects. Novel bioinformatics tools, based on systems immunology and machine learning, will be used to integrate and analyze these large datasets to identify immune fingerprints that reflect a person's lifetime exposome or that are early predictors of disease. This will allow researchers, policymakers, and clinicians to grasp the impact of the exposome on the immune system at the level of individuals and populations.

AbstractIn this article, we have responded to the key statements in the article by Koivisto et al. (2022) that were incorrect and considered to be a biased critique on a subset of the exposure models used in Europe (i.e. ART and Stoffenmanager®) used for regulatory exposure assessment. We welcome scientific discussions on exposure modelling (as was done during the ISES Europe workshop) and criticism based on scientific evidence to contribute to the advancement of occupational exposure estimation tools. The tiered approach to risk assessment allows various exposure assessment models from screening tools (control/hazard banding) through to higher-tiered approaches. There is a place for every type of model, but we do need to recognize the cost and data requirements of highly bespoke assessments. That is why model developers have taken pragmatic approaches to develop tools for exposure assessments based on imperfect data. We encourage Koivisto et al. to focus on further scientifically robust work to develop mass-balance models and by independent external validations studies, compare these models with alternative model tools such as ART and Stoffenmanager®.