Rare earth elements (REEs) have emerged as contaminants in airborne particulate matter (PM); however, their anthropogenic sources remain poorly quantified, and associated health risks are unknown. This study investigates the REE distribution across eight sizes of airborne PM during July and December in Qingdao, a major Chinese port city. Our results reveal a single coarse-mode distribution with REE concentrations. In contrast, fine PM (size: 0.43-2.1 μm) exhibits notable enrichment of La and Ce compared to Al and other REEs. This study traces La and Ce enrichment to fluid catalytic cracking catalysts (FCCC)-related sources, including refinery and ship emissions, by comparing the REE fractionation in samples with potential sources. We quantify the contributions from FCCC-related sources to La (July: 33.6 % ± 3.2 %, Dec.: 46.4 % ± 5.2 %) and Ce (July: 16.5 % ± 14.3 %, Dec.: 30.3 % ± 12.2 %) by comparing measured concentrations with predictions derived from neighboring REEs, a method previously used exclusively in aquatic systems. For the first time, supply ratios of refinery and ship to FCCC-related La are calculated using a two-component mixing model based on the [La]FCCC/[V]anth, revealing the dominance of refinery emissions (July: 97.3 % ± 0.6 %, Dec.: 99.6 % ± 0.1 %). Furthermore, a global review of La and Ce anomalies that integrates published REE data with our findings reveals a widespread distribution of positive anomalies. The significantly positive correlation between La and Ce anomalies underscores FCCC-related emissions as a global source in fine PM, contributing 0-92 % (mean: 35 % ± 33 %) for La and 0-72 % (mean: 21 % ± 24 %) for Ce. Although the non-carcinogenic health risks of Ce are generally low globally, concerns should be raised in areas near source emissions, where Ce health risks sharply increased along with its concentrations. There is urgently need to establish a threshold value for La, owing to its global enrichment. This study provides novel insights into the sources and health implications of REEs in airborne PM.

The widespread extensive use of synthetic polymers has led to a substantial environmental crisis caused by plastic pollution, with microplastics detected in various environments and posing risks to both human health and ecosystems. The possibility of plastic fragments to be dispersed in the air as particles and inhaled by humans may cause damage to the respiratory and other body systems. Therefore, there is a particular need to study microplastics as air pollutants. In this study, we tested a combination of analytical pyrolysis, gas chromatography-mass spectrometry, and gas and liquid chromatography-mass spectrometry to identify and quantify both microplastics and their additives in airborne particulate matter and settled dust within a workplace environment: a WEEE treatment plant. Using this combined approach, we were able to accurately quantify ten synthetic polymers and eight classes of polymer additives. The identified additives include phthalates, adipates, citrates, sebacates, trimellitates, benzoates, organophosphates, and newly developed brominated flame retardants.

Obesity is currently one of the most alarming pathological conditions due to the progressive increase in its prevalence. In the last decade, it has been associated with fine particulate matter suspended in the air (PM2.5). The purpose of this study was to explore the mechanistic interaction of PM2.5 with a high-fat diet (HFD) through the differential regulation of transcriptional signatures, aiming to identify the association of these particles with metabolically abnormal obesity. The research design was observational, using bioinformatic methods and an explanatory approach based on Rothman\'s causal model. We propose three new transcriptional signatures in murine adipose tissue. The sum of transcriptional differences between the group exposed to an HFD and PM2.5, compared to the control group, were 0.851, 0.265, and -0.047 (p > 0.05). The HFD group increased body mass by 20% with two positive biomarkers of metabolic impact. The group exposed to PM2.5 maintained a similar weight to the control group but exhibited three positive biomarkers. Enriched biological pathways (p < 0.05) included PPAR signaling, small molecule transport, adipogenesis genes, cytokine-cytokine receptor interaction, and HIF-1 signaling. Transcriptional regulation predictions revealed CpG islands and common transcription factors. We propose three new transcriptional signatures: FAT-PM2.5-CEJUS, FAT-PM2.5-UP, and FAT-PM2.5-DN, whose transcriptional regulation profile in adipocytes was statistically similar by dietary intake and HFD and exposure to PM2.5 in mice; suggesting a mechanistic interaction between both factors. However, HFD-exposed murines developed moderate metabolically abnormal obesity, and PM2.5-exposed murines developed severe abnormal metabolism without obesity. Therefore, in Rothman\'s terms, it is concluded that HFD is a sufficient cause of the development of obesity, and PM2.5 is a component cause of severe abnormal metabolism of obesity. These signatures would be integrated into a systemic biological process that would induce transcriptional regulation in trans, activating obesogenic biological pathways, restricting lipid mobilization pathways, decreasing adaptive thermogenesis and angiogenesis, and altering vascular tone thus inducing a severe metabolically abnormal obesity.

Air pollution is a worldwide environmental problem with an impact on human health. Particulate matter of ten micrometers or less aerodynamic diameter (PM10) as well as its fine fraction (PM2.5) is related to multiple pulmonary diseases. The impact of air pollution in Mexico City, and importantly, particulate matter has been studied and considered as a risk factor for two decades ago. Previous studies have reported the composition of Mexico City particulate matter, as well as the biological effects induced by this material. However, material collected and used in previous studies is a limited resource, and sampling and particle recovery techniques have been improved. In this study, we describe the methods used in our laboratory for Mexico City airborne particulate matter PM10 and PM2.5 sampling, considering the years 2017, 2018 and 2019. We also analyzed the PM10 and PM2.5 samples obtained to determine their composition. Finally, we exposed lung cell line cultures to PM10 and PM2.5 to evaluate the biological effect of the material in terms of cell viability, cell death, inflammatory response, and cytogenetic alterations. Our results showed that PM10 composition includes inorganic, organic and biological compounds, while PM2.5 is a mixture of more enriched organic compounds. PM10 and PM2.5 treatment in lung cells does not significantly impact cell viability/cell death. However, PM10 and PM2.5 increase the secretion levels of IL-6. Moreover, PM10 as well as PM2.5 induce cytogenetic alterations, such as micronuclei, anaphase bridges, trinucleated cells and apoptotic cells in lung cells. Our results update the evidence of the composition and biological effects of Mexico City particulate matter and provide us a reliable basis for future approaches.

Preterm deliveries are a major multifactorial public health problem in French Guiana. Desert dust episodes have been associated with preterm delivery in Guadeloupe, a territory with similarities to French Guiana. We thus tried to replicate this finding in the context of French Guiana. A retrospective ecological cohort study combined daily PM10 concentration measurements during pregnancy and term at delivery extracted from French Guiana\'s computerized pregnancy delivery registry. Daily PM10 concentrations during the course of pregnancy were analyzed as mean concentrations and as the proportion of intense dust episodes (≥55 μg PM10/m3). These exposure variables were studied in relation to the outcome of preterm delivery. Overall, 3,321 pregnant women with complete daily PM10 measurements were included, of whom 374 (11.26%) delivered prematurely. Among preterm deliveries, 168 (44.9%) were spontaneous deliveries and 206 (55.1%) were induced. Rank-sum tests showed that, for spontaneous and induced spontaneous deliveries, both mean PM10 concentrations and proportions of intense desert dust episodes were significantly greater among preterm births than among term births. Although the proportion of intense desert dust episodes during pregnancy was significantly associated with spontaneous preterm deliveries, the relation was U-shaped, with an adjusted odds ratio (AOR) = 2 (95%CI = 1.2-3.1) for lowest values relative to median values and AOR = 5.4 (95%CI = 3.2-8.9) for the highest values relative to median values. Similarly, the proportion of intense desert dust episodes during pregnancy was also significantly associated with induced preterm deliveries in a U-shaped manner (AOR = 2.7 (95%CI = 1.6-4.5) for the lowest relative to median values and AOR = 6.8 (95%CI = 3.9-11.9) for the highest relative to median values). Although in our study the relation between PM10 concentrations appeared non-linear, the highest mean concentrations and intense desert dust episodes were indeed associated with both spontaneous and induced preterm delivery.

Soil erosion is a severe problem in Taiwan due to the steep terrain, fragile geology, and extreme climatic events resulting from global warming. Due to the rapidly changing hydrological conditions affecting the locations and the amount of transported sand and fine particles, timely impact evaluation and riverine dust control are difficult, particularly when resources are limited. To comprehend the impact of desertification in estuarine areas on the variation of air pollutant concentrations, this study utilized remote sensing technology coupled with an air pollutant dispersion model to determine the unit contribution of potential pollution sources and quantify the effect of riverine dust on air quality. The images of the downstream area of the Beinan River basin captured by Formosat-2 in May 2006 were used to analyze land use and land cover (LULC) composition. Subsequently, the diffusion model ISCST-3 based on Gaussian distribution was utilized to simulate the transport of PM across the study area. Finally, a mixed-integer programming model was developed to optimize resource allocation for dust control. Results reveal that sand deposition in specific river sections significantly influences regional air quality, owing to the unique local topography and wind field conditions. The present optimal plan model for regional air quality control further showed that after implementing engineering measures including water cover, revegetation, armouring cover, and revegetation, total PM concentrations would be reduced by 51%. The contribution equivalent calculation, using the air pollution diffusion model, was effectively integrated into the optimization model to formulate a plan for reducing riverine dust with limited resources based on air quality requirements.

Emerging research findings suggest that airborne particulate matter might be a risk factor for gestational diabetes mellitus (GDM). However, the concentration-response relationships and the susceptible time windows for different types of particulate matter may vary. In this retrospective analysis, we employ a novel robust approach to assess the crucial time windows regarding the prevalence of GDM and to distinguish the susceptibility of three GDM subtypes to air pollution exposure. This study included 16,303 pregnant women who received routine antenatal care in 2018-2021 at the Maternal and Child Health Hospital in Chongqing, China. In total, 2482 women (15.2%) were diagnosed with GDM. We assessed the individual daily average exposure to air pollution, including PM2.5, PM10, O3, NO2, SO2, and CO based on the volunteers\' addresses. We used high-accuracy gridded air pollution data generated by machine learning models to assess particulate matter per maternal exposure levels. We further analyzed the association of pre-pregnancy, early, and mid-pregnancy exposure to environmental pollutants using a generalized additive model (GAM) and distributed lag nonlinear models (DLNMs) to analyze the association between exposure at specific gestational weeks and the risk of GDM. We observed that, during the first trimester, per IQR increases for PM10 and PM2.5 exposure were associated with increased GDM risk (PM10: OR = 1.19, 95%CI: 1.07~1.33; PM2.5: OR = 1.32, 95%CI: 1.15~1.50) and isolated post-load hyperglycemia (GDM-IPH) risk (PM10: OR = 1.23, 95%CI: 1.09~1.39; PM2.5: OR = 1.38, 95%CI: 1.18~1.61). Second-trimester O3 exposure was positively correlated with the associated risk of GDM, while pre-pregnancy and first-trimester exposure was negatively associated with the risk of GDM-IPH. Exposure to SO2 in the second trimester was negatively associated with the risk of GDM-IPH. However, there were no observed associations between NO2 and CO exposure and the risk of GDM and its subgroups. Our results suggest that maternal exposure to particulate matter during early pregnancy and exposure to O3 in the second trimester might increase the risk of GDM, and GDM-IPH is the susceptible GDM subtype to airborne particulate matter exposure.

Pesticides are frequently sprayed in greenhouses to ensure crop yields, where airborne particulate matter (PM) may serve as a carrier in depositing and transporting pesticides. However, little is known about the occurrence and fate of PM-borne pesticides in greenhouses. Herein, we examined the distribution, dissipation, and transformation of six commonly used pesticides (imidacloprid, acetamiprid, prochloraz, triadimefon, hexaconazole, and tebuconazole) in greenhouse PM (PM1, PM2.5, and PM10) after application as well as the associated human exposure risks via inhalation. During 35 days of experiment, the six pesticides were detected in all PM samples, and exhibited size- and time-dependent distribution characteristics, with the majority of them (>64.6%) accumulated in PM1. About 1.0-16.4% of initially measured pesticides in PM remained after 35 days, and a total of 12 major transformation products were elucidated, with six of them newly identified. The inhalation of PM could be an important route of human exposure to pesticides in the greenhouse, where the estimated average daily human inhalation dose (ADDinh) of the six individual pesticides was 2.1-1.2 × 104 pg/kg day-1 after application (1-35 days). Our findings highlight the occurrence of pesticides/transformation products in greenhouse PM, and their potential inhalation risks should be further concerned.

The recent United Kingdom (UK) Environment Act consultation had the intention of setting two targets for PM2.5 (particles with an aerodynamic diameter less than 2.5 μm), one related to meeting an annual average concentration and the second to reducing population exposure. As part of the consultation, predictions of PM2.5 concentrations in 2030 were made by combining European Union (EU) and UK government\'s emissions forecasts, with the Climate Change Committee\'s (CCC) Net Zero vehicle forecasts, and in London with the addition of local policies based on the London Environment Strategy (LES). Predictions in 2018 showed 6.4% of the UK\'s area and 82.6% of London\'s area had PM2.5 concentrations above the World Health Organization (WHO) interim target of 10 μg m-3, but by 2030, over 99% of the UK\'s area was predicted to be below it. However, kerbside concentrations in London and other major cities were still at risk of exceeding 10 μg m-3. With local action on PM2.5 in London, population weighted concentrations showed full compliance with the WHO interim target of 10 μg m-3 in 2030. However, predicting future PM2.5 concentrations and interpreting the results will always be difficult and uncertain for many reasons, such as imperfect models and the difficulty in estimating future emissions. To help understand the sensitivity of the model\'s PM2.5 predictions in 2030, current uncertainty was quantified using PM2.5 measurements and showed large areas in the UK that were still at risk of exceeding the WHO interim target despite the model predictions being below 10 μg m-3. Our results do however point to the benefits that policy at EU, UK and city level can have on achieving the WHO interim target of 10 μg m-3. These results were submitted to the UK Environment Act consultation. Nevertheless, the issues addressed here could be applicable to other European cities.

Tire wear particles (TWPs) are a major category of microplastic pollution produced by friction between tires and road surfaces. This non-exhaust particulate matter (PM) containing leachable toxic compounds is transported through the air and with stormwater runoff, leading to environmental pollution and human health concerns. In the present study, we collected airborne PM at varying distances (5, 15 and 30 m) along US Highway 278 in Oxford, Mississippi, USA, for ten consecutive days using Sigma-2 passive samplers. Particles (~ 1-80 μm) were passively collected directly into small (60 mL) wide-mouth separatory funnels placed inside the samplers. Particles were subsequently subjected to solvent extraction, and extracts were analyzed for TWP compounds by high resolution orbitrap mass spectrometry. This pilot study was focused solely on qualitative analyses to determine whether TWP compounds were present in this fraction of airborne PM. The abundance of airborne TWPs increased with proximity to the road with deposition rates (TWPs cm-2 day-1) of 23, 47, and 63 at 30 m, 15 m, and 5 m from the highway, respectively. Two common TWP compounds (6PPD-Q and 4-ADPA) were detected in all samples, except the field blank, at levels above their limits of detection, estimated at 2.90 and 1.14 ng L-1, respectively. Overall, this work suggests airborne TWPs may be a potential inhalation hazard, particularly for individuals and wildlife who spend extended periods outdoors along busy roadways. Research on the bioavailability of TWP compounds from inhaled TWPs is needed to address exposure risk.