Air pollution, genetic susceptibility, and the risk of atrial fibrillation: A large prospective cohort study.

To date, no study has explored the extent to which genetic susceptibility modifies the effects of air pollutants on the risk of atrial fibrillation (AF). This study was designed to investigate the separate and joint effects of long-term exposure to air pollutants and genetic susceptibility on the risk of AF events. This study included 401,251 participants without AF at baseline from UK Biobank. We constructed a polygenic risk score and categorized it into three categories. Cox proportional hazards models were fitted to assess the separate and joint effects of long-term exposure to air pollutants and genetics on the risk of AF. Additionally, we further evaluated the effect modification of genetic susceptibility. The hazard ratios and corresponding 95% confidence intervals of incident AF for per interquartile range increase in particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5) or 10 µm (PM10), nitrogen dioxide (NO2), and nitrogen oxide (NOx) were 1.044 (1.025, 1.063), 1.063 (1.044, 1.083), 1.061 (1.042, 1.081), and 1.039 (1.023, 1.055), respectively. For the combined effects, participants exposed to high air pollutants levels and high genetic risk had approximately 149.2% (PM2.5), 181.7% (PM10), 170.2% (NO2), and 157.2% (NOx) higher risk of AF compared to those with low air pollutants levels and low genetic risk, respectively. Moreover, the significant additive interactions between PM10 and NO2 and genetic risk on AF risk were observed, with around 16.4% and 35.1% of AF risk could be attributable to the interactive effects. In conclusion, long-term exposure to air pollutants increases the risk of AF, particularly among individuals with high genetic susceptibility.

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study.

BACKGROUND AND AIMS: Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown. METHODS: This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset. RESULTS: Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx. CONCLUSIONS: In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Genetic Susceptibility Modifies Relationships Between Air Pollutants and Stroke Risk: A Large Cohort Study.

BACKGROUND: The extent to which genetic susceptibility modifies the associations between air pollutants and the risk of incident stroke is still unclear. This study was designed to investigate the separate and joint associations of long-term exposure to air pollutants and genetic susceptibility on stroke risk. METHODS: The participants of this study were recruited by the UK Biobank between 2006 and 2010. These participants were followed up from the enrollment until the occurrence of stroke events or censoring of data. Hazard ratios (HRs) and 95% CIs for stroke events associated with long-term exposure to air pollutants were estimated by fitting both crude and adjusted Cox proportional hazards models. Additionally, the polygenic risk score was calculated to estimate whether the polygenic risk score modifies the associations between exposure to air pollutants and incident stroke. RESULTS: A total of 502 480 subjects were included in this study. After exclusion, 452 196 participants were taken into the final analysis. During a median follow-up time of 11.7 years, 11 334 stroke events were observed, with a mean age of 61.60 years, and men accounted for 56.2% of the total cases. Long-term exposures to particulate matter with an aerodynamic diameter smaller than 2.5 µm (adjusted HR, 1.70 [95% CI, 1.43-2.03]) or particulate matter with an aerodynamic diameter smaller than 10 µm (adjusted HR, 1.50 [95% CI, 1.36-1.66]), nitrogen dioxide (adjusted HR, 1.10 [95% CI, 1.07-1.12]), and nitrogen oxide (adjusted HR, 1.04 [95% CI, 1.02-1.05]) were pronouncedly associated with increased risk of stroke. Meanwhile, participants with high genetic risk and exposure to high air pollutants had ≈45% (31%, 61%; particulate matter with an aerodynamic diameter smaller than 2.5 µm), 48% (33%, 65%; particulate matter with an aerodynamic diameter smaller than 10 µm), 51% (35%, 69%; nitrogen dioxide), and 39% (25%, 55%; nitrogen oxide) higher risk of stroke compared with those with low genetic risk and exposure to low air pollutants, respectively. Of note, we observed additive and multiplicative interactions between genetic susceptibility and air pollutants on stroke events. CONCLUSIONS: Chronic exposure to air pollutants was associated with an increased risk of stroke, especially in populations at high genetic risk.

Ambient Air Pollution and Depressed Mood in the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave IV.

Depression is a major contributor to the global burden of disease. There is limited understanding of how environmental exposures may contribute to depression etiology. We used Wave IV of the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine associations between low-level ambient air pollution exposure and depressed mood in a generally healthy population of over 10,000 24-32 year olds. Annual mean PM2.5 levels in the 2008-2009 study were close to the current U.S. standard. In fully adjusted quasi-binomial logistic regression models, there were no meaningful associations between IQR increases in air pollutant and change in depressed mood status regardless of specific pollutant or moving average lags. In interaction effects models, an IQR increase in lag day 0-30 PM2.5 resulted in 1.20 (95% CI, 1.02-1.41) times higher likelihood of having depressed mood, but only for persons with chronic lung disease (interaction P=0.04); the association was null for participants without chronic lung disease (OR 0.98, 95% CI, 0.91, 1.05). Our findings suggest that among persons with a lifetime history of chronic lung disease, greater exposure to even low-level PM2.5, PM10, and sulfate may be associated with modest increases in the likelihood of having depressed mood.

Large-scale genome-wide association studies reveal the genetic causal etiology between air pollutants and autoimmune diseases.

BACKGROUND: Epidemiological evidence links a close correlation between long-term exposure to air pollutants and autoimmune diseases, while the causality remained unknown. METHODS: Two-sample Mendelian randomization (TSMR) was used to investigate the role of PM10, PM2.5, NO2, and NOX (N = 423,796-456,380) in 15 autoimmune diseases (N = 14,890-314,995) using data from large European GWASs including UKB, FINNGEN, IMSGC, and IPSCSG. Multivariable Mendelian randomization (MVMR) was conducted to investigate the direct effect of each air pollutant and the mediating role of common factors, including body mass index (BMI), alcohol consumption, smoking status, and household income. Transcriptome-wide association studies (TWAS), two-step MR, and colocalization analyses were performed to explore underlying mechanisms between air pollution and autoimmune diseases. RESULTS: In TSMR, after correction of multiple testing, hypothyroidism was causally associated with higher exposure to NO2 [odds ratio (OR): 1.37, p = 9.08 × 10-4] and NOX [OR: 1.34, p = 2.86 × 10-3], ulcerative colitis (UC) was causally associated with higher exposure to NOX [OR: 2.24, p = 1.23 × 10-2] and PM2.5 [OR: 2.60, p = 5.96 × 10-3], rheumatoid arthritis was causally associated with higher exposure to NOX [OR: 1.72, p = 1.50 × 10-2], systemic lupus erythematosus was causally associated with higher exposure to NOX [OR: 4.92, p = 6.89 × 10-3], celiac disease was causally associated with lower exposure to NOX [OR: 0.14, p = 6.74 × 10-4] and PM2.5 [OR: 0.17, p = 3.18 × 10-3]. The risky effects of PM2.5 on UC remained significant in MVMR analyses after adjusting for other air pollutants. MVMR revealed several common mediators between air pollutants and autoimmune diseases. Transcriptional analysis identified specific gene transcripts and pathways interconnecting air pollutants and autoimmune diseases. Two-step MR revealed that POR, HSPA1B, and BRD2 might mediate from air pollutants to autoimmune diseases. POR pQTL (rs59882870, PPH4=1.00) strongly colocalized with autoimmune diseases. CONCLUSION: This research underscores the necessity of rigorous air pollutant surveillance within public health studies to curb the prevalence of autoimmune diseases.

Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN) in World Trade Center exposed firefighters: a case-control observational study protocol.

BACKGROUND: Particulate matter exposure (PM) is a cause of aerodigestive disease globally. The destruction of the World Trade Center (WTC) exposed first responders and inhabitants of New York City to WTC-PM and caused obstructive airways disease (OAD), gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE). GERD not only diminishes health-related quality of life but also gives rise to complications that extend beyond the scope of BE. GERD can incite or exacerbate allergies, sinusitis, bronchitis, and asthma. Disease features of the aerodigestive axis can overlap, often necessitating more invasive diagnostic testing and treatment modalities. This presents a need to develop novel non-invasive biomarkers of GERD, BE, airway hyperreactivity (AHR), treatment efficacy, and severity of symptoms. METHODS: Our observational case-cohort study will leverage the longitudinally phenotyped Fire Department of New York (FDNY)-WTC exposed cohort to identify Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN). Our study population consists of n = 4,192 individuals from which we have randomly selected a sub-cohort control group (n = 837). We will then recruit subgroups of i. AHR only ii. GERD only iii. BE iv. GERD/BE and AHR overlap or v. No GERD or AHR, from the sub-cohort control group. We will then phenotype and examine non-invasive biomarkers of these subgroups to identify under-diagnosis and/or treatment efficacy. The findings may further contribute to the development of future biologically plausible therapies, ultimately enhance patient care and quality of life. DISCUSSION: Although many studies have suggested interdependence between airway and digestive diseases, the causative factors and specific mechanisms remain unclear. The detection of the disease is further complicated by the invasiveness of conventional GERD diagnosis procedures and the limited availability of disease-specific biomarkers. The management of reflux is important, as it directly increases risk of cancer and negatively impacts quality of life. Therefore, it is vital to develop novel noninvasive disease markers that can effectively phenotype, facilitate early diagnosis of premalignant disease and identify potential therapeutic targets to improve patient care. TRIAL REGISTRATION: Name of Primary Registry: "Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BADBURN)". Trial Identifying Number: NCT05216133 . Date of Registration: January 31, 2022.

Associations between air pollutants and acute exacerbation of drug-resistant tuberculosis: evidence from a prospective cohort study.

BACKGROUND: Short-term exposure to air pollution may trigger symptoms of drug-resistant tuberculosis (DR-TB) through stimulating lung tissue, damaging tracheobronchial mucosa, the key anti-mycobacterium T cell immune function, and production and release of inflammatory cytokines. OBJECTIVE: To investigate the association between acute exacerbations of DR-TB and short-term residential exposure to air pollutants (PM10, PM2.5, SO2, NO2, CO and O3) based on a large prospective cohort in Anhui Province, China. METHOD: Patients were derived from a prospective cohort study of DR-TB in Anhui Province. All DR-TB patients underwent drug-susceptibility testing and prefecture-level reference laboratories confirmed their microbiologies. The case-crossover design was performed to evaluate the association between the risk of acute exacerbations of DR-TB and short-term residential exposure to air pollution. RESULTS: Short-term NO2 exposure was significantly related to an elevated risk of first-time outpatient visit due to acute exacerbations of DR-TB(relative risk:1.159, 95% confidence interval:1.011 ~ 1.329). Stratification analyses revealed that the relationship between the risk of acute exacerbations and NO2 exposure was stronger in the elderly (age ≥ 65) DR-TB patients, and in individuals with a history of TB treatment. CONCLUSIONS: NO2 Exposure was significantly associated with an elevated risk of acute exacerbation of DR-TB in Anhui Province, China.

In Situ and Rapid Toxicity Assessment of Air Pollution by Self-Assembly Passive Colonization Hydrogel.

Air pollution is a leading environmental health risk factor, and in situ toxicity assessment is urgently needed. Bacteria-based bioassays offer cost-effective and rapid toxicity assessments. However, the application of these bioassays for air toxicity assessment has been challenging, due to the instability of bacterial survival and functionality when directly exposed to air pollutants. Here, we developed an approach employing self-assembly passive colonization hydrogel (SAPCH) for in situ air toxicity assessment. The SAPCH features a core-shell structure, enabling the quantitatively immobilization of bacteria on its shell while continuously provides nutrients from its core. An antimicrobial polyelectrolyte layer between the core and shell confines bacteria to the air-liquid interface, synchronizing bacterial survival with exposure to air pollutants. The SAPCH immobilized a battery of natural and recombinant luminescent bacteria, enabling simultaneous detection of various toxicological endpoints (cytotoxicity, genotoxicity and oxidative stress) of air pollutants within 2 h. Its sensitivity was 3-5 orders of magnitude greater than that of traditional liquid-phase toxicity testing, and successfully evaluating the toxicity of volatile organic compounds and combustion smoke. This study presents a method for in situ, rapid, and economical toxicity assessment of air pollution, making a significant contribution to future air quality monitoring and control.

Light Precipitation rather than Total Precipitation Determines Aerosol Wet Removal.

Precipitation scavenging is an important sink for both organic and inorganic pollutants in the atmosphere. However, there has been controversy over the relative importance of different precipitation characteristics (i.e., the precipitation amount, intensity, frequency, and duration) in the removal of air pollutants. It is critical to reach a consensus on which precipitation characteristics are most significant for aerosol wet removal. In this study, the analysis of multisource in situ observations of aerosol wet deposition worldwide indicates that the precipitation frequency plays a first-order role in scavenging aerosols. This is because large amounts of air pollutants are efficiently removed at precipitation initiation. As the duration and amount of precipitation increase, the scavenging efficiency decreases sharply. Consequently, it is featured that light precipitation, due to its high frequency of occurrence, rather than total precipitation, determines climatological aerosol wet deposition. To further confirm this, a state-of-the-art global climate model with convection resolved is modified to reduce the light precipitation frequency in both stratiform and convective cloud regimes. Results show widespread increases in aerosol optical depth (AOD) due to the reduced wet deposition. The spatial distribution of aerosol wet deposition changes resembles that of changes in the light precipitation frequency rather than that of total precipitation changes. These findings are consistent with those from the Coupled Model Intercomparison Project Phase 6 multimodel simulations, which show that the intermodel uncertainty in simulated AOD correlates more strongly with the uncertainty in light precipitation frequency than with that in total precipitation.

Upgrading Passenger Vehicle Emission Standard Helps to Reduce China's Air Pollution Risk from Uncertainty in Electrification.

Upgrading to the CHINA 7 standard is crucial for managing air pollution from passenger vehicles in China. Meanwhile, China aims to achieve carbon neutrality by 2060, which necessitates large-scale replacement of gasoline vehicles with electric vehicles in the future. Consequently, the public might view upgrading gasoline vehicles to the CHINA 7 standard as redundant. However, the emission reduction benefits of upgrading standards in the context of uncertain electrification ambitions have not received adequate attention. Here, we show that upgrading standards will compensate for the absence of emissions reductions due to hindered electrification efforts. In the best scenario, China's CO2 emissions can be reduced to 0.047 Gt and NOx to 8.2 × 103 t in 2050. In nonextreme electrification scenarios with CHINA 7 standard, the emission intensity reduction will remain the main driver for emission reductions, outweighing the electrification contribution. In extreme electrification scenarios, upgrading standards will tackle the increased emissions from plug-in hybrid electric vehicles. Our fleet-level results advocate for early standards upgrades to enhance resilience against air pollution risks arising from uncertainties in electrification. Our evidence from China, with one of the most stringent emission standards, can provide a reference point for the world on the upgrading passenger vehicle emission standard issue.

Evolution of Reactive Organic Compounds and Their Potential Health Risk in Wildfire Smoke.

Wildfires are an increasing source of emissions into the air, with health effects modulated by the abundance and toxicity of individual species. In this work, we estimate reactive organic compounds (ROC) in western U.S. wildland forest fire smoke using a combination of observations from the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign and predictions from the Community Multiscale Air Quality (CMAQ) model. Standard emission inventory methods capture 40-45% of the estimated ROC mass emitted, with estimates of primary organic aerosol particularly low (5-8×). Downwind, gas-phase species abundances in molar units reflect the production of fragmentation products such as formaldehyde and methanol. Mass-based units emphasize larger compounds, which tend to be unidentified at an individual species level, are less volatile, and are typically not measured in the gas phase. Fire emissions are estimated to total 1250 ± 60 g·C of ROC per kg·C of CO, implying as much carbon is emitted as ROC as is emitted as CO. Particulate ROC has the potential to dominate the cancer and noncancer risk of long-term exposure to inhaled smoke, and better constraining these estimates will require information on the toxicity of particulate ROC from forest fires.

Ethylene Oxide in Southeastern Louisiana's Petrochemical Corridor: High Spatial Resolution Mobile Monitoring during HAP-MAP.

Ethylene oxide ("EtO") is an industrially made volatile organic compound and a known human carcinogen. There are few reliable reports of ambient EtO concentrations around production and end-use facilities, however, despite major exposure concerns. We present in situ, fast (1 Hz), sensitive EtO measurements made during February 2023 across the southeastern Louisiana industrial corridor. We aggregated mobile data at 500 m spatial resolution and reported average mixing ratios for 75 km of the corridor. Mean and median aggregated values were 31.4 and 23.3 ppt, respectively, and a majority (75%) of 500 m grid cells were above 10.9 ppt, the lifetime exposure concentration corresponding to 100-in-one million excess cancer risk (1 × 10-4). A small subset (3.3%) were above 109 ppt (1000-in-one million cancer risk, 1 × 10-3); these tended to be near EtO-emitting facilities, though we observed plumes over 10 km from the nearest facilities. Many plumes were highly correlated with other measured gases, indicating potential emission sources, and a subset was measured simultaneously with a second commercial analyzer, showing good agreement. We estimated EtO for 13 census tracts, all of which were higher than EPA estimates (median difference of 21.3 ppt). Our findings provide important information about EtO concentrations and potential exposure risks in a key industrial region and advance the application of EtO analytical methods for ambient sampling and mobile monitoring for air toxics.

Cleaning up while Changing Gears: The Role of Battery Design, Fossil Fuel Power Plants, and Vehicle Policy for Reducing Emissions in the Transition to Electric Vehicles.

Plug-in electric vehicles (PEVs) can reduce air emissions when charged with clean power, but prior work estimated that in 2010, PEVs produced 2 to 3 times the consequential air emission externalities of gasoline vehicles in PJM (the largest US regional transmission operator, serving 65 million people) due largely to increased generation from coal-fired power plants to charge the vehicles. We investigate how this situation has changed since 2010, where we are now, and what the largest levers are for reducing PEV consequential life cycle emission externalities in the near future. We estimate that PEV emission externalities have dropped by 17% to 18% in PJM as natural gas replaced coal, but they will remain comparable to gasoline vehicle externalities in base case trajectories through at least 2035. Increased wind and solar power capacity is critical to achieving deep decarbonization in the long run, but through 2035 we estimate that it will primarily shift which fossil generators operate on the margin at times when PEVs charge and can even increase consequential PEV charging emissions in the near term. We find that the largest levers for reducing PEV emissions over the next decade are (1) shifting away from nickel-based batteries to lithium iron phosphate, (2) reducing emissions from fossil generators, and (3) revising vehicle fleet emission standards. While our numerical estimates are regionally specific, key findings apply to most power systems today, in which renewable generators typically produce as much output as possible, regardless of the load, while dispatchable fossil fuel generators respond to the changes in load.

Wood heater smoke and mortality in the Australian Capital Territory: a rapid health impact assessment.

OBJECTIVES: To estimate the number of deaths and the cost of deaths attributable to wood heater smoke in the Australian Capital Territory. STUDY DESIGN: Rapid health impact assessment, based on fine particulate matter (PM2.5 ) data from three outdoor air pollution monitors and published exposure-response functions for natural cause mortality attributed to PM2.5 exposure. SETTING: Australian Capital Territory (population, 2021: 454 000), 2016-2018, 2021, and 2022 (2019 and 2020 excluded because of the impact of extreme bushfires on air quality). MAIN OUTCOME MEASURES: Proportion of PM2.5 exposure attributable to wood heaters; numbers of deaths and associated cost of deaths (based on the value of statistical life: $5.3 million) attributable to wood heater smoke. RESULTS: Wood heater emissions contributed an estimated 1.16-1.73 µg/m3 to the annual mean PM2.5 concentration during the three colder years (2017, 2018, 2021), or 17-25% of annual mean exposure, and 0.72 µg/m3 (15%) or 0.89 µg/m3 (13%) during the two milder years (2016, 2022). Using the most conservative exposure-response function, the estimated annual number of deaths attributable to wood heater smoke was 17-26 during the colder three years and 11-15 deaths during the milder two years. Using the least conservative exposure-response function, an estimated 43-63 deaths per year (colder years) and 26-36 deaths per year (milder years) were attributable to wood heater smoke. The estimated annual equivalent cost of deaths was $57-136 million (most conservative exposure-response function) and $140-333 million (least conservative exposure-response function). CONCLUSIONS: The estimated annual number of deaths in the ACT attributable to wood heater PM2.5 pollution is similar to that attributed to the extreme smoke of the 2019-20 Black Summer bushfires. The number of wood heaters should be reduced by banning new installations and phasing out existing units in urban and suburban areas.

Ambient temperature and the risk of childhood epilepsy hospitalizations: Potentially neglected risk of temperature extremes and modifying effects of air pollution.

PURPOSE: Extreme temperatures and air pollution are increasingly important risk factors for human health in the background of climate change, with limited evidence available for neurological disorders. This study intended to investigate the short-term effects of extreme temperatures on childhood epilepsy and explore the potential modifying effect of air pollution. METHODS: Daily childhood epilepsy hospitalization, meteorological and air pollution data were collected from 10 cities in Anhui Province of China during 2016-2018. We firstly employed a space-time-stratified case-crossover design and conditional logistic regression model to fit the short-term relationship between temperature and epilepsy. Then, we conducted stratified analyses by the level of air pollution and individual characteristics. RESULTS: Both extreme heat and extreme cold increased the risk of hospitalization for childhood epilepsy. The effect of extreme heat [97.5th vs. minimum hospitalization temperature (MHT)] on hospitalization was acute and emerged at lag0 [OR: 1.229 (95 %CI: 1.035 to 1.459)], while the effect of extreme cold (2.5th vs. MHT) was delayed and appeared at lag5 [OR: 1.098 (95 %CI: 1.043 to 1.156)]. We also found children aged 6-18 years were more susceptible to extreme cold than children aged 0-5 years. Besides, extreme heat and cold effects differed by the level of air pollutants. CONCLUSION: This study suggests that extreme temperatures might be the novel but currently neglected risk factor for childhood epilepsy, and air pollution could further amplify the adverse effect of temperature.

Long-term prediction of the effects of climate change on indoor climate and air quality.

Limiting the negative impact of climate change on nature and humans is one of the most pressing issues of the 21st century. Meanwhile, people in modern society spend most of the day indoors. It is therefore surprising that comparatively little attention has been paid to indoor human exposure in relation to climate change. Heat action plans have now been designed in many regions to protect people from thermal stress in their private homes and in public buildings. However, in order to be able to plan effectively for the future, reliable information is required about the long-term effects of climate change on indoor air quality and climate. The Indoor Air Quality Climate Change (IAQCC) model is an expediant tool for estimating the influence of climate change on indoor air quality. The model follows a holistic approach in which building physics, emissions, chemical reactions, mold growth and exposure are combined with the fundamental parameters of temperature and humidity. The features of the model have already been presented in an earlier publication, and it is now used for the expected climatic conditions in Central Europe, taking into account various shared socioeconomic pathway (SSP) scenarios up to the year 2100. For the test house examined in this study, the concentrations of pollutants in the indoor air will continue to rise. At the same time, the risk of mold growth also increases (the mold index rose from 0 to 4 in the worst case for very sensitive material). The biggest problem, however, is protection against heat and humidity. Massive structural improvements are needed here, including insulation, ventilation, and direct sun protection. Otherwise, the occupants will be exposed to increasing thermal discomfort, which can also lead to severe heat stress indoors.

An evaluation of in utero polycyclic aromatic hydrocarbon exposure on the neonatal meconium microbiome.

INTRODUCTION: In utero exposure to environmental polycyclic aromatic hydrocarbon (PAH) is associated with neurodevelopmental impairments[1-8], prematurity[9-12] and low birthweight[9,13-15]. The gut microbiome serves as an intermediary between self and external environment; therefore, exploring the impact of PAH on microbiota may elucidate their role in disease. Here, we evaluated the effect of in utero PAH exposure on meconium microbiome. METHODS: We evaluated 49 mother-child dyads within Fair Start Birth Cohort with full term delivery and adequate meconium sampling. Prenatal PAH was measured using personal active samplers worn for 48 h during third trimester. Post-processing, 35 samples with adequate biomass were evaluated for association between tertile of PAH exposure (high (H) vs low/medium (L/M)) and microbiome diversity. RESULTS: No significant differences were observed in alpha diversity metrics, Chao1 and Shannon index, between exposure groups for total PAH. However, alpha diversity metrics were negatively associated with log benzo[a]anthracene (BaA) and log chrysene (Chry) with high exposure, but positively associated with log benzo[a]pyrene (BaP) with low/medium exposure. After adjustment for birthweight and sex, alpha diversity metrics were negatively associated with log BaA, BaP, Chry, Indeno (Zhang et al., 2021; Perera et al., 2018)pyrene (IcdP) and total PAH with high exposure. Conversely, with low/medium exposure, alpha diversity metrics positively correlated with log BaP and benzo[b]fluoranthane (BbF). No significant difference in beta diversity was observed across groups using UniFrac, weighted UniFrac, or Bray-Curtis methods. Differential expression analysis showed differentially abundant taxa between exposure groups. CONCLUSION: Bacterial taxa were detectable in 35/49 (71%) meconium samples. Altered alpha diversity metrics and differentially abundant taxa between groups suggest in utero PAH exposure may impede early colonization. Sample size is limited, but these findings provide supporting evidence for wider scale research. Research on long-term impact of prenatal PAH exposure on childhood health outcomes is ongoing. Differential effects of specific PAHs need further evaluation.

Residential ambient air pollution exposure and the development of white matter microstructure throughout adolescence.

BACKGROUND: Recent evidence suggests an association of air pollution exposure with brain development, but evidence on white matter microstructure in children is scarce. We investigated how air pollution exposure during pregnancy and childhood impacts longitudinal development of white matter microstructure throughout adolescence. METHODS: Our study population consisted of 4108 participants of Generation R, a large population-based birth cohort from Rotterdam, the Netherlands. Residential air pollution exposure to 14 air pollutants during pregnancy and childhood was estimated with land-use regression models. Diffusion tensor images were obtained around age 10 and 14, resulting in a total of 5422 useable scans (n = 3082 for wave 1 and n = 2340 for wave 2; n = 1314 for participants with data on both waves). We calculated whole-brain fractional anisotropy (FA) and mean diffusivity (MD) and performed single- and multi-pollutant analyses using mixed effects models adjusted for life-style and socioeconomic status variables. RESULTS: Higher exposure to PM2.5 during pregnancy, and PM10, PM2.5, PM2.5-10, and NOX during childhood was associated with a consistently lower whole-brain FA throughout adolescence (e.g. - 0.07 × 10-2 FA [95%CI -0.12; -0.02] per 1 standard deviation higher PM2.5 exposure during pregnancy). Higher exposure to silicon (Si) in PM2.5 and oxidative potential of PM2.5 during pregnancy, and PM2.5 during childhood was associated with an initial higher MD followed by a faster decrease in MD throughout adolescence (e.g. - 0.02 × 10-5 mm2/s MD [95%CI -0.03; -0.00] per year of age per 1 standard deviation higher Si exposure during pregnancy). Results were comparable when performing the analysis in children with complete data on the outcome for both neuroimaging assessments. CONCLUSIONS: Exposure to several pollutants was associated with a consistently lower whole-brain FA throughout adolescence. The association of few pollutants with whole-brain MD at baseline attenuated throughout adolescence. These findings suggest both persistent and age-limited associations of air pollution exposure with white matter microstructure.

Detection of morphological and eco-physiological traits of ornamental woody species to assess their potential Net O3 uptake.

Urban greening can improve cities' air quality by filtering the main gaseous pollutants such as tropospheric ozone (O3). However, the pollutant removal capacity offered by woody species strongly depends on eco-physiological and morphological traits. Woody species with higher stomatal conductance (gs) can remove more gases from the atmosphere, but other species can worsen air quality due to high O3 forming potential (OFP), based on their emitting rates of biogenic volatile organic compounds (bVOCs) and Leaf Mass per Area (LMA). Presently, there is a lack of data on eco-physiological (gs, bVOCs emissions) and foliar traits (LMA) for several ornamental species used in urban greening programs, which does not allow assessment of their O3 removal capacity and OFP. This study aimed to (i) parameterize gs, assess bVOCs emissions and LMA of 14 ornamental woody species commonly used in Mediterranean urban greening, and (ii) model their Net O3 uptake. The gs Jarvis model was parameterized considering various environmental conditions alongside isoprene and monoterpene foliar bVOCs emission rates trapped in the field and quantified by gas chromatography-mass spectrometry. The results are helpful for urban planning and landscaping; suggesting that Catalpa bignonioides and Gleditsia triacanthos have excellent O3 removal capacity due to their high maximum gs (gmax) equal to 0.657 and 0.597 mol H2O m-2 s-1. Regarding bVOCs, high isoprene (16.75 µg gdw-1 h-1) and monoterpene (13.12 µg gdw-1 h-1) emission rates were found for Rhamnus alaternus and Cornus mas. In contrast, no bVOCs emissions were detected for Camellia sasanqua and Paulownia tomentosa. In conclusion, 11 species showed a positive Net O3 uptake, while the use of large numbers of R. alaternus, C. mas, and Chamaerops humilis for urban afforestation planning are not recommended due to their potential to induce a deterioration of outdoor air quality.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort.

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.