Multiple xenoestrogen air pollutants and breast cancer risk: Statistical approaches to investigate combined exposures effect.

Studies suggested that exposure to air pollutants, with endocrine disrupting (ED) properties, have a key role in breast cancer (BC) development. Although the population is exposed simultaneously to a mixture of multiple pollutants and ED pollutants may act via common biological mechanisms leading to synergic effects, epidemiological studies generally evaluate the effect of each pollutant separately. We aimed to assess the complex effect of exposure to a mixture of four xenoestrogen air pollutants (benzo-[a]-pyrene (BaP), cadmium, dioxin (2,3,7,8-Tétrachlorodibenzo-p-dioxin TCDD)), and polychlorinated biphenyl 153 (PCB153)) on the risk of BC, using three recent statistical methods, namely weighted quantile sum (WQS), quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR). The study was conducted on 5222 cases and 5222 matched controls nested within the French prospective E3N cohort initiated in 1990. Annual average exposure estimates to the pollutants were assessed using a chemistry transport model, at the participants' residence address between 1990 and 2011. We found a positive association between the WQS index of the joint effect and the risk of overall BC (adjusted odds ratio (OR) = 1.10, 95% confidence intervals (CI): 1.03-1.19). Similar results were found for QGC (OR = 1.11, 95%CI: 1.03-1.19). Despite the association did not reach statistical significance in the BKMR model, we observed an increasing trend between the joint effect of the four pollutants and the risk of BC, when fixing other chemicals at their median concentrations. BaP, cadmium and PCB153 also showed positive trends in the multi-pollutant mixture, while dioxin showed a modest inverse trend. Despite we found a clear evidence of a positive association between the joint exposure to pollutants and BC risk only from WQS and QGC regression, we observed a similar suggestive trend using BKMR. This study makes a major contribution to the understanding of the joint effects of air pollution.

Response of biogenic secondary organic aerosol formation to anthropogenic NOx emission mitigation.

This study investigates the effects of anthropogenic nitrogen oxide (NOx) mitigation reduction on secondary organic aerosol (SOA) formation from monoterpene and sesquiterpene precursors across Europe, using the three-dimensional (3-D) Chemical Transport Model (CTM) CHIMERE. Two SOA mechanisms of varying complexity are employed: the GENOA-generated Biogenic Mechanism (GBM) and the Hydrophobic/Hydrophilic Organic mechanism (H2O). GBM is a condensed SOA mechanism generated by automatic reduction from near-explicit chemical mechanisms (i.e., the Master Chemical Mechanism - MCM and the peroxy radical autoxidation mechanism - PRAM) using the GENerator of Reduced Organic Aerosol Mechanisms version 2.0 (GENOA v2.0). Conversely, the H2O mechanism is developed primarily based on experimental data, with simplified chemical pathways and SOA formation yields reflecting those from chamber experiments. In the 3-D simulations conducted for the summer of 2018 over Europe, the implementation of GBM significantly improved the model's performance in comparison to simulations using the H2O mechanism, yielding results more consistent with measured aerosol concentrations extracted from the EBAS database. In response to NOx emission mitigation, simulated SOA concentrations increase with GBM but decrease when using the H2O mechanism, unless a highly oxygenated molecules (HOMs) formation scheme is incorporated. The SOA composition becomes more oxidized and concentrations elevate after NOx reduction, particularly in simulations using GBM. These higher concentrations are likely due to enhanced reaction rates of organic peroxy radicals (RO2) with HO2, resulting in more oxidized products from monoterpene degradation that favors HOM formation. The results suggest that detailed SOA mechanisms including autoxidation are necessary for accurate predictions of SOA concentrations in 3-D modeling.

Long-term exposure to nitrogen dioxide air pollution and breast cancer risk: A nested case-control within the French E3N cohort study.

Nitrogen dioxide (NO2) is an important air pollutant due to its adverse effects on human health. Yet, current evidence on the association between NO2 and the risk of breast cancer lacks consistency. In this study, we investigated the association between long-term exposure to NO2 and breast cancer risk in the French E3N cohort study. Association of breast cancer risk with NO2 exposure was assessed in a nested case-control study within the French E3N cohort including 5222 breast cancer cases identified over the 1990-2011 follow-up period and 5222 matched controls. Annual mean concentrations of NO2 at participants' residential addresses for each year from recruitment 1990 through 2011, were estimated using a land use regression (LUR) model. Multivariable conditional logistic regression models were used to compute odds ratios (ORs) and their 95% confidence intervals (CIs). Additional analyses were performed using NO2 concentrations estimated by CHIMERE, a chemistry transport model. Overall, the mean NO2 exposure was associated with an increased risk of breast cancer. In all women, for each interquartile range (IQR) increase in NO2 levels (LUR: 17.8 µg/m3), the OR of the model adjusted for confounders was 1.09 (95% CI: 1.01-1.18). The corresponding OR in the fully adjusted model (additionally adjusted for established breast cancer risk factors) was 1.07 (95% CI: 0.98-1.15). By menopausal status, results for postmenopausal women were comparable to those for all women, while no association was observed among premenopausal women. By hormone receptor status, the OR of estrogen receptor positive breast cancer = 1.07 (95% CI: 0.97-1.19) in the fully adjusted model. Additional analyses using the CHIMERE model showed slight differences in ORs estimates. The results of this study indicate an increased risk of breast cancer associated with long-term exposure to NO2 air pollution. Observing comparable effects of NO2 exposure estimated by two different models, reinforces these findings.

Emissions of Carbonaceous Particulate Matter and Ultrafine Particles from Vehicles-A Scientific Review in a Cross-Cutting Context of Air Pollution and Climate Change.

Airborne particulate matter (PM) is a pollutant of concern not only because of its adverse effects on human health but also on visibility and the radiative budget of the atmosphere. PM can be considered as a sum of solid/liquid species covering a wide range of particle sizes with diverse chemical composition. Organic aerosols may be emitted (primary organic aerosols, POA), or formed in the atmosphere following reaction of volatile organic compounds (secondary organic aerosols, SOA), but some of these compounds may partition between the gas and aerosol phases depending upon ambient conditions. This review focuses on carbonaceous PM and gaseous precursors emitted by road traffic, including ultrafine particles (UFP) and polycyclic aromatic hydrocarbons (PAHs) that are clearly linked to the evolution and formation of carbonaceous species. Clearly, the solid fraction of PM has been reduced during the last two decades, with the implementation of after-treatment systems abating approximately 99% of primary solid particle mass concentrations. However, the role of brown carbon and its radiative effect on climate and the generation of ultrafine particles by nucleation of organic vapour during the dilution of the exhaust remain unclear phenomena and will need further investigation. The increasing role of gasoline vehicles on carbonaceous particle emissions and formation is also highlighted, particularly through the chemical and thermodynamic evolution of organic gases and their propensity to produce particles. The remaining carbon-containing particles from brakes, tyres and road wear will still be a problem even in a future of full electrification of the vehicle fleet. Some key conclusions and recommendations are also proposed to support the decision makers in view of the next regulations on vehicle emissions worldwide.

Modelling aerosol molecular markers in a 3D air quality model: Focus on anthropogenic organic markers.

We developed and implemented in the 3D air quality model CHIMERE the formation of several key anthropogenic aerosol markers including one primary anthropogenic marker (levoglucosan) and 4 secondary anthropogenic markers (nitrophenols, nitroguaiacols, methylnitrocatechols and phthalic acid). Modelled concentrations have been compared to measurements performed at 12 locations in France for levoglucosan in winter 2014-15, and at a sub-urban station in the Paris region over the whole year 2015 for secondary molecular markers. While a good estimation of levoglucosan concentrations by the model has been obtained for a few sites, a strong underestimation was simulated for most of the stations especially for western locations due to a probable underestimation of residential wood burning emissions. The simulated ratio between wood burning organic matter and particulate phase levoglucosan is constant only at high OM values (>10 µg m-3) indicating that using marker contribution ratio may be valid only under certain conditions. Concentrations of secondary markers were well reproduced by the model for nitrophenols and nitroguaiacols but were underestimated for methylnitrocatechols and phthalic acid highlighting missing formation pathways and/or precursor emissions. By comparing modelled to measured Gas/Particle Partitioning (GPP) of markers, the simulated partitioning of Semi-Volatile Organic Compounds (SVOCs) was evaluated. Except for nitroguaiacols and nitrophenols when ideality was assumed, the GPP for all the markers was underestimated and mainly driven by the hydrophilic partitioning. SVOCs GPP, and more generally of all SVOC contributing to the formation of SOA, could therefore be significantly underestimated by air quality models, especially when only the partitioning on the organic phase is considered. Our results show that marker modelling can give insights on some processes (such as precursor emissions or missing mechanisms) involved in SOA formation and could prove especially useful to evaluate the GPP in 3D air quality models.

Differential impact of government lockdown policies on reducing air pollution levels and related mortality in Europe.

Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO2 compared to PM2.5 and PM10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.

Simulating the impact of volatilization on atmospheric concentrations of pesticides with the 3D chemistry-transport model CHIMERE: Method development and application to S-metolachlor and folpet.

A module to simulate the volatilization of pesticides from soils and plants was implemented in the air quality model CHIMERE in order to simulate spatiotemporal distribution of pesticide atmospheric concentrations. Pesticide applications are spatially distributed according to the quantities of pesticides sold per municipality in France (recorded in the French BNVD-S database) and are temporally distributed according to the application periods determined with enquiries. The model was applied to S-metolachlor and folpet. In the first stage of the study, pesticide emissions simulated by the CHIMERE and Volt'Air models are compared. In the second stage, measured concentrations of S-metolachlor and folpet from mid-April to the end of June are compared to the simulation results at the French and PACA (Southeastern region of France) scales. The model can reproduce the spatial distribution of S-metolachlor concentrations (spatial correlation over France of 0.79) with a bias ranging from -50 to 50% for most stations during the application period. The simulation of folpet concentrations remains challenging with a lack of correlation between model results and measurements, that could possibly be due to a lack of precision in the temporalization of applications.

Long-term atmospheric exposure to PCB153 and breast cancer risk in a case-control study nested in the French E3N cohort from 1990 to 2011.

BACKGROUND: Although the genetic and hormonal risk factors of breast cancer are well identified, they cannot fully explain the occurrence of all cases. Epidemiological and experimental studies have suggested that exposure to environmental pollutants, especially those with potential estrogenic properties, as polychlorinated biphenyls (PCBs) may have a role in breast cancer development. Being the most abundantly detected in human tissues and in the environment, congener 153 (PCB153) is widely used in epidemiological studies as indicator for total PCBs exposure. OBJECTIVES: We aimed to estimate the association between cumulative atmospheric exposure to PCB153 and breast cancer risk. METHODS: We conducted a case-control study of 5222 cases and 5222 matched controls nested within the French E3N cohort from 1990 to 2011. Annual atmospheric PCB153 concentrations were simulated with the deterministic chemistry-transport model (CHIMERE) and were assigned to women using their geocoded residential history. Their cumulative PCB153 exposure was calculated for each woman from their cohort inclusion to their index date. Breast cancer odds ratios (ORs) associated with cumulative PCB153 exposure and their 95% confidence intervals (95% CIs) were estimated using multivariate conditional logistic regression models. RESULTS: Overall, our results showed a statistically significant linear increase in breast cancer risk related to cumulative atmospheric exposure to PCB153 as a continuous variable (adjusted OR = 1.19; 95% CI: 1.08-1.31, for an increment of one standard deviation among controls (55 pg/m3)). Among women who became postmenopausal during follow-up, the association remained statistically significant (adjusted OR = 1.23; 95% CI: 1.09-1.39). In analyses by hormone receptors status, the positive association remained significant only for ER-positive breast cancer (adjusted OR = 1.18; 95% CI: 1.05-1.33). DISCUSSION: This study is the first to have estimated the impact of atmospheric exposure to PCB153 on breast cancer risk. Our results showed a statistically significant increase in breast cancer risk, which may be limited to ER-positive breast cancer. These results warrant confirmation in further independent studies but raise the possibility that exposure to PCB153 increase breast cancer risk.

Risk of breast cancer associated with long-term exposure to benzo[a]pyrene (BaP) air pollution: Evidence from the French E3N cohort study.

BACKGROUND: Benzo[a]pyrene (BaP) is an endocrine-disrupting pollutant formed during incomplete combustion of organic materials. It has been recognized as a reproductive and developmental toxicant, however epidemiological evidence of the long-term effect of ambient air BaP on breast cancer (BC) is limited. Thus we evaluated associations between ambient air BaP exposure and risk of BC, overall and according to menopausal status and molecular subtypes (estrogen receptor negative/positive (ER-/ER+) and progesterone receptor negative/positive (PR-/PR+)), stage and grade of differentiation of BC in the French E3N cohort study. METHODS: Within a nested case-control study of 5222 incident BC cases and 5222 matched controls, annual BaP exposure was estimated using a chemistry-transport model (CHIMERE) and was assigned to the geocoded residential addresses of participants for each year during the 1990-2011 follow-up period. Multivariable conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Overall, cumulative airborne BaP exposure was significantly associated with the overall risk of BC, for each 1 interquartile range (IQR) increase in the concentration levels of BaP (1.42 ng/m3), the OR = 1.15 (95% CI: 1.04-1.27). However, by menopausal status, the significant positive association remained only in women who underwent menopausal transition (i.e. premenopausal women at inclusion who became postmenopausal at diagnosis), OR per 1 IQR = 1.20 (95% CI: 1.03-1.40). By hormone receptor status, positive associations were observed for ER+, PR + and ER + PR + BC, with ORs = 1.17 (95% CI: 1.04-1.32), 1.16 (95% CI: 1.01-1.33), and 1.17 (95% CI: 1.01-1.36) per 1 IQR, respectively. There was also a borderline positive association between BaP and grade 3 BC (OR per 1 IQR = 1.15 (95% CI: 0.99-1.34). CONCLUSIONS: We provide evidence of increased risk of BC associated with cumulative BaP exposure, which varied according to menopausal status, hormone receptor status, and grade of differentiation of BC. Our results add further epidemiological evidence to the previous experimental studies suggesting the adverse effects of BaP.

Chronic Low-Dose Exposure to Xenoestrogen Ambient Air Pollutants and Breast Cancer Risk: XENAIR Protocol for a Case-Control Study Nested Within the French E3N Cohort.

BACKGROUND: Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status. OBJECTIVE: The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium. METHODS: Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated. RESULTS: The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk. CONCLUSIONS: The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15167.

Modeled deposition of nitrogen and sulfur in Europe estimated by 14 air quality model systems: evaluation, effects of changes in emissions and implications for habitat protection.

The evaluation and intercomparison of air quality models is key to reducing model errors and uncertainty. The projects AQMEII3 and EURODELTA-Trends, in the framework of the Task Force on Hemispheric Transport of Air Pollutants and the Task Force on Measurements and Modelling, respectively (both task forces under the UNECE Convention on the Long Range Transport of Air Pollution, LTRAP), have brought together various regional air quality models to analyze their performance in terms of air concentrations and wet deposition, as well as to address other specific objectives. This paper jointly examines the results from both project communities by intercomparing and evaluating the deposition estimates of reduced and oxidized nitrogen (N) and sulfur (S) in Europe simulated by 14 air quality model systems for the year 2010. An accurate estimate of deposition is key to an accurate simulation of atmospheric concentrations. In addition, deposition fluxes are increasingly being used to estimate ecological impacts. It is therefore important to know by how much model results differ and how well they agree with observed values, at least when comparison with observations is possible, such as in the case of wet deposition. This study reveals a large variability between the wet deposition estimates of the models, with some performing acceptably (according to previously defined criteria) and others underestimating wet deposition rates. For dry deposition, there are also considerable differences between the model estimates. An ensemble of the models with the best performance for N wet deposition was made and used to explore the implications of N deposition in the conservation of protected European habitats. Exceedances of empirical critical loads were calculated for the most common habitats at a resolution of 100 × 100 m2 within the Natura 2000 network, and the habitats with the largest areas showing exceedances are determined. Moreover, simulations with reduced emissions in selected source areas indicated a fairly linear relationship between reductions in emissions and changes in the deposition rates of N and S. An approximate 20 % reduction in N and S deposition in Europe is found when emissions at a global scale are reduced by the same amount. European emissions are by far the main contributor to deposition in Europe, whereas the reduction in deposition due to a decrease in emissions in North America is very small and confined to the western part of the domain. Reductions in European emissions led to substantial decreases in the protected habitat areas with critical load exceedances (halving the exceeded area for certain habitats), whereas no change was found, on average, when reducing North American emissions in terms of average values per habitat.

Organic aerosol molecular composition and gas-particle partitioning coefficients at a Mediterranean site (Corsica).

Molecular speciation of atmospheric organic matter was investigated during a short summer field campaign performed in a citrus fruit field in northern Corsica (June 2011). Aimed at assessing the performance on the field of newly developed analytical protocols, this work focuses on the molecular composition of both gas and particulate phases and provides an insight into partitioning behavior of the semi-volatile oxygenated fraction. Limonene ozonolysis tracers were specifically searched for, according to gas chromatography-mass spectrometry (GC-MS) data previously recorded for smog chamber experiments. A screening of other oxygenated species present in the field atmosphere was also performed. About sixty polar molecules were positively or tentatively identified in gas and/or particle phases. These molecules comprise a wide range of branched and linear, mono and di-carbonyls (C3-C7), mono and di-carboxylic acids (C3-C18), and compounds bearing up to three functionalities. Among these compounds, some can be specifically attributed to limonene oxidation and others can be related to α- or ß-pinene oxidation. This provides an original snapshot of the organic matter composition at a Mediterranean site in summer. Furthermore, for compounds identified and quantified in both gaseous and particulate phases, an experimental gas/particle partitioning coefficient was determined. Several volatile products, which are not expected in the particulate phase assuming thermodynamic equilibrium, were nonetheless present in significant concentrations. Hypotheses are proposed to explain these observations, such as the possible aerosol viscosity that could hinder the theoretical equilibrium to be rapidly reached.

Subalpine Pyrenees received higher nitrogen deposition than predicted by EMEP and CHIMERE chemistry-transport models.

Deposition of reactive nitrogen (N) from the atmosphere is expected to be the third greatest driver of biodiversity loss by the year 2100. Chemistry-transport models are essential tools to estimate spatially explicit N deposition but the reliability of their predictions remained to be validated in mountains. We measured N deposition and air concentration over the subalpine Pyrenees. N deposition was found to range from 797 to 1,463 mg N m(-2) year(-1). These values were higher than expected from model predictions, especially for nitrate, which exceeded the estimations of EMEP by a factor of 2.6 and CHIMERE by 3.6. Our observations also displayed a reversed reduced-to-oxidized ratio in N deposition compared with model predictions. The results highlight that the subalpine Pyrenees are exposed to higher levels of N deposition than expected according to standard predictions and that these levels exceed currently recognized critical loads for most high-elevation habitats. Our study reveals a need to improve the evaluation of N deposition in mountains which are home to a substantial and original part of the world's biodiversity.

Investigating the impact of aqueous-phase chemistry and wet deposition on organic aerosol formation using a molecular surrogate modeling approach.

A molecular surrogate representation of secondary organic aerosol (SOA) formation is used to investigate the effect of aqueous-phase (in clouds and particles) chemical processing and wet deposition on SOA atmospheric concentrations. To that end, the hydrophilic/hydrophobic organic (H(2)O) model was augmented to account for several gas/aqueous-phase equilibria and aqueous-phase processes, including the formation of oxalic, glyoxilic and pyruvic acids, the oxidation of methyl vinyl ketone (MVK) and methacrolein (MACR), the formation of tetrols and organosulfates from epoxydiols (IEPOX), and further oxidation of water-soluble SOA (aging). Among those processes, SOA chemical aging and IEPOX reactions led to the most significant increases (up to 1 µg m(-3) in some areas) in SOA concentrations in a one-month summer simulation over Europe. However, large uncertainties remain in the gas/aqueous-phase partitioning of oxalic acid, MVK, and MACR. Below-cloud scavenging of SOA precursor gases and of gas-phase SVOC was found to affect SOA concentrations by up to 20%, which suggests that it should be taken into account in air quality models.

Comparison of different gas-phase mechanisms and aerosol modules for simulating particulate matter formation.

The effects of two gas-phase chemical kinetic mechanisms, Regional Atmospheric Chemistry Mechanism version 2 (RACM2) and Carbon-Bond 05 (CB05), and two secondary organic aerosol (SOA) modules, the Secondary Organic Aerosoi Model (SORGAM) and AER/EPRI/Caltech model (AEC), on fine (aerodynamic diameter < or =2.5 microm) particulate matter (PM2.5) formation is studied. The major sources of uncertainty in the chemistry of SOA formation are investigated. The use of all major SOA precursors and the treatment of SOA oligomerization are found to be the most important factors for SOA formation, leading to 66% and 60% more SOA, respectively. The explicit representation of high-NO, and low-NOx gas-phase chemical regimes is also important with increases in SOA of 30-120% depending on the approach used to implement the distinct SOA yields within the gas-phase chemical kinetic mechanism; further work is needed to develop gas-phase mechanisms that are fully compatible with SOA formation algorithms. The treatment of isoprene SOA as hydrophobic or hydrophilic leads to a significant difference, with more SOA being formed in the latter case. The activity coefficients may also be a major source of uncertainty, as they may differ significantly between atmospheric particles, which contain a myriad of SOA, primary organic aerosol (POA), and inorganic aerosol species, and particles formed in a smog chamber from a single precursor under dry conditions. Significant interactions exist between the uncertainties of the gas-phase chemistry and those of the SOA module.