COVID-19 fatality and DALYs, and associated metabolic disorders and ambient air pollutants in pre-Omicron era of the pandemic: an international comparative study.

BACKGROUND: Air pollution and a number of metabolic disorders have been reported to increase the risk of severe COVID-19 outcomes. This study explored the association between severe COVID-19 outcomes, metabolic disorders and environmental air pollutants, at regional level, across 38 countries. METHODS: We conducted an ecological study using COVID-19 data related to countries of the Organization for Economic Cooperation and Development (OECD), with an estimated population of 1.4 billion. They were divided into 3 regions: 1. Europe & Middle east; 2. Americas (north, central & south America); 3. East-Asia & West Pacific. The outcome variables were: COVID-19 case-fatality rate (CFR) and disability-adjusted life years (DALYs) at regional level. Freely accessible datasets related to regional DALYs, demographics and other environmental pollutants were obtained from OECD, WHO and the World in Data websites. Generalized linear model (GLM) was performed to determine the regional determinants of COVID-19 CFR and DALYs using the aggregate epidemiologic data (Dec. 2019-Dec. 2021). RESULTS: Overall cumulative deaths were 65,000 per million, for mean CFR and DALYs of 1.31 (1.2)% and 17.35 (2.3) years, respectively. Globally, GLM analysis with adjustment for elderly population rate, showed that COVID-19 CFR was positively associated with atmospheric PM2.5 level (beta = 0.64(0.0), 95%CI: 0.06-1.35; p < 0.05), diabetes prevalence (beta = 0.26(0.1), 95%CI: 0.12-0.41; p < 0.001). For COVID-19 DALYs, positive associations were observed with atmospheric NOx level (beta = 0.06(0.0), 95%CI: 0.02-0.82; p < 0.05) and diabetes prevalence (beta = 0.32(0.2), 95%CI: 0.04-0.69; p < 0.05). At regional level, adjusted GLM analysis showed that COVID-19 CFR was associated with atmospheric PM2.5 level in the Americas and East-Asia & Western Pacific region; it was associated with diabetes prevalence for countries of Europe & Middle east and East-Asia & Western Pacific region. Furthermore, COVID-19 DALYs were positively associated with atmospheric PM2.5 and diabetes prevalence for countries of the Americas only. CONCLUSION: These findings confirm that diabetes and air pollution increase the risk of disability and fatality due to COVID-19, with disparities in terms of their impact. They suggest that efficient preventive and management programs for diabetes and air pollution countermeasures would have curtailed severe COVID-19 outcome rates.

[Pollution Characteristics, Source, and Health Risk Assessment of Metal Elements in PM2.5 Between Winter and Spring in Zhengzhou].

A total of 18 metal elements in ambient PM2.5 in Zhengzhou were continuously determined using an online heavy metal observation instrument in January and April, 2021, and the changes in element concentrations were analyzed. Metal elements were traced via enrichment factors, positive matrix factorization (PMF), and a characteristic radar chart. The US EPA health risk assessment model was used to assess the health risks of heavy metals, and the backward trajectory method and the concentration-weighted trajectory (CWT) method were used to evaluate the potential source regions of health risks. The results showed that the element concentrations were higher in spring, and the sum of Fe, Ca, Si, and Al concentrations accounted for 89.8% and 87.5% of the total element concentrations in winter and spring, respectively. Cd was enriched significantly, which was related to human activities. The concentrations of Pb, Se, Zn, Ni, Sb, and K in winter and Cr, Ni, Fe, Mn, V, Ba, Ca, K, Si, and Al in spring increased with the increasing pollution level. The results of PMF and the characteristic radar chart showed that the main sources of metal elements in winter and spring were industry, crust, motor vehicles, and mixed combustion, with industry and mixed combustion pollution occurring more often in winter and crust pollution occurring more often in spring. Significant non-carcinogenic risks existed in both winter and spring with more severe health risks in winter, and Mn caused significant non-carcinogenic risks. The health risks in winter were mainly influenced by Zhengzhou and surrounding cities and long-distance transport in the northwest, and the health risks in spring were mainly influenced by Zhengzhou and surrounding cities.

[Characteristics, Sources Apportionment, and Health Risks of PM2.5-bound PAHs and Their Derivatives Before and After Heating in Zibo City].

Atmospheric polycyclic aromatic hydrocarbons (PAHs) and their derivatives are a global problem that influences the environment and threatens human health. To investigate the characteristics, sources, and health risk assessment of PM2.5-bound PAHs and their derivatives, PM2.5 were collected at an urban site in Zibo from November 5 to December 26, 2020, and the concentrations of 16 conventional PAHs, nine NPAHs, and five OPAHs in PM2.5 were analyzed using gas chromatography-mass spectrometry. Source apportionment of PAHs and their derivatives was conducted using diagnostic ratios and a PMF model, and the health risks of PAHs and their derivatives to adult men and women were evaluated using the source-dependent incremental lifetime cancer risk (ILCR) model. The results showed that the average concentrations of ∑16pPAHs, ∑9NPAHs, and ∑5OPAHs in PM2.5 of Zibo City during the sampling period were (41.61 ± 13.40), (6.38 ± 5.70), and (53.20 ± 53.47) ng·m-3, respectively. The concentrations of the three PAHs increased significantly after heating, which were 1.31, 2.04, and 5.24 times larger than those before heating. During the sampling period, Chr, BaP, and BaA were the dominant components of pPAHs; 9N-Ant and 2N-Flt + 3N-Flt were the dominant components of NPAHs; and ATQ and BZO were the dominant components of OPAHs. Source apportionment results showed that motor vehicles were the main source of PAHs and their derivatives in PM2.5 before heating, whereas after heating, the main sources were the mixed source of coal and biomass combustion and secondary formation. The total BaP equivalent (TEQ) was 14.5 ng·m-3 during the sampling period, and the TEQ increased significantly after heating, which was approximately 1.2 times of that before heating. Assisted by the individual PAH source apportionment results, the ILCR of PM2.5-boundPAHs and NPAHs in Zibo City had a certain potential carcinogenic risk for adult males (1.06 × 10-5) and females (9.32 × 10-6). Among them, the health risks of PAHs from gasoline vehicles, diesel vehicles, and coal/biomass combustion were significantly higher than those from other emission sources.

[Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020].

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

Toxic Potencies of Particulate Matter from Typical Industrial Plants Mediated with Acidity via Metal Dissolution.

Acidity is an important property of particulate matter (PM) in the atmosphere, but its association with PM toxicity remains unclear. Here, this study quantitively reports the effect of the acidity level on PM toxicity via pH-control experiments and cellular analysis. Oxidative stress and cytotoxicity potencies of acidified PM samples at pH of 1-2 were up to 2.8-5.2 and 2.1-13.2 times higher than those at pH of 8-11, respectively. The toxic potencies of PM samples from real-world smoke plumes at the pH of 2.3 were 9.1-18.2 times greater than those at the pH of 5.6, demonstrating a trend similar to that of acidified PM samples. Furthermore, the impact of acidity on PM toxicity was manifested by promoting metal dissolution. The dramatic increase by 2-3 orders of magnitude in water-soluble metal content dominated the variation in PM toxicity. The significant correlation between sulfate, the pH value, water-soluble Fe, IC20, and EC1.5 (p < 0.05) suggested that acidic sulfate could enhance toxic potencies by dissolving insoluble metals. The findings uncover the superficial association between sulfate and adverse health outcomes in epidemiological research and highlight the control of wet smoke plume emissions to mitigate the toxicity effects of acidity.

Microalgal biochar assisted simultaneous removal of particulate matter, formaldehyde, and total volatile organic compounds (TVOC's) from indoor air.

Biochar-based materials for air treatment have gained significant attention for removing health-detrimental volatile organic compounds (VOCs) and particulate matter (PM) in indoor air settings. However, high turnaround time, multiple pretreatment processes involved, and high pore size and low surface area (>10 µm, <100 m2 g-1) of lignocellulosic feedstocks demand alternative biochar feedstock material. Considering this, we designed a simple first-of-its-kind indoor air scrubbing material using diatoms-enriched microalgae biochar. In the present study, the microalgae were cultivated on waste anaerobic digestate (biogas slurry) and were pyrolyzed at three different temperatures: 300 °C (BC300), 500 °C (BC500), and 700 °C (BC700). The BC500 and BC700 showed the highest removal efficiencies (99 %) for total volatile organic carbons (TVOCs) and formaldehyde (HCHO) at concentrations of 1.22 mg m-3 HCHO and 8.57 mg m-3 TVOC compared to 50% efficiency obtained with commercially available surgical, cloth, and N95 masks. The biochar obtained showed a high Brunauer-Emmett-Teller (BET) surface area of 238 m2 g-1 (BC500) and 480 m2 g-1 (BC700) and an average pore size of 9-11 nm due to the mesoporous characteristic of diatom frustules. The comparatively poor performance of BC300 was due to lower surface area (150 m2 g-1) arising from incomplete organic removal, as evidenced by FESEM-EDX and FTIR. The high removal efficiencies in BC500 and BC700 were also attributed to the presence of reactive functional groups such as -OH and R-NH2. Concurrently, the average particulate matter (PM10, PM2.5, and PM1) removal efficiency for BC500 and BC 700 ranged between 66 and 82.69 %. The PM removal performance of BC500 and BC700 was lower (15-20%) than commercially available masks. Overall, the present study highlights the importance of diatoms (reactive Si) present inside the pores of microalgal biochar for enhanced removal of PM, TVOCs, and HCHO at temperatures above 500 °C. This complete approach signifies a step towards establishing a self-sustainable and circular process characterized by minimal waste generation for indoor air treatment.

Emission characteristics of condensable particulate matter during the production of solid waste-based sulfoaluminate cement: Compositions, heavy metals, and preparation impacts.

Recycling solid waste for preparing sulfoaluminate cementitious materials (SACM) represents a promising approach for low-carbon development. There are drastic physical-chemical reactions during SACM calcination. However, there is a lack of research on the flue gas pollutants emissions from this process. Condensable particulate matter (CPM) has been found to constitute the majority of the primary PM emitted from various fuel combustion. In this study, the emission characteristics of CPM during the calcination of SACM were determined using tests in both a real-operated kiln and laboratory experiments. The mass concentration of CPM reached 96.6 mg/Nm3 and occupied 87% of total PM emission from the SACM kiln. Additionally, the mass proportion of SO42- in the CPM reached 93.8%, thus indicating that large quantities of sulfuric acid mist or SO3 were emitted. CaSO4 was one key component for the formation of main mineral ye'elimite (3CaO·3Al2O3·CaSO4), and its decomposition probably led to the high SO42- emission. Furthermore, the use of CaSO4 as a calcium source led to SO42- emission factor much higher than conventional calcium sources. Higher calcination temperature and more residence time also increased SO42- emission. The most abundant heavy metal in kiln flue gas and CPM was Zn. However, the total condensation ratio of heavy metals detected was only 40.5%. CPM particles with diameters below 2.5 µm and 4-20 µm were both clearly observed, and components such as Na2SO4 and NaCl were conformed. This work contributes to the understanding of CPM emissions and the establishment of pollutant reduction strategies for waste collaborative disposal in cement industry.

Association between Fine Particulate Matter Exposure and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease among a Cognitively Healthy Population-Based Cohort.

BACKGROUND: Epidemiological evidence suggests air pollution adversely affects cognition and increases the risk of Alzheimer's disease (AD), but little is known about the biological effects of fine particulate matter (PM2.5, particulate matter with aerodynamic diameter ≤2.5µm) on early predictors of future disease risk. OBJECTIVES: We investigated the association between 1-, 3-, and 5-y exposure to ambient and traffic-related PM2.5 and cerebrospinal fluid (CSF) biomarkers of AD. METHODS: We conducted a cross-sectional analysis using data from 1,113 cognitively healthy adults (45-75 y of age) from the Emory Healthy Brain Study in Georgia in the United States. CSF biomarker concentrations of Aß42, tTau, and pTau, were collected at enrollment (2016-2020) and analyzed with the Roche Elecsys system. Annual ambient and traffic-related residential PM2.5 concentrations were estimated at a 1-km and 250-m resolution, respectively, and computed for each participant's geocoded address, using three exposure time periods based on specimen collection date. Associations between PM2.5 and CSF biomarker concentrations, considering continuous and dichotomous (dichotomized at clinical cutoffs) outcomes, were estimated with multiple linear/logistic regression, respectively, controlling for potential confounders (age, gender, race, ethnicity, body mass index, and neighborhood socioeconomic status). RESULTS: Interquartile range (IQR; IQR=0.845) increases in 1-y [ß:-0.101; 95% confidence interval (CI): -0.18, -0.02] and 3-y (ß:-0.078; 95% CI: -0.15, -0.00) ambient PM2.5 exposures were negatively associated with Aß42 CSF concentrations. Associations between ambient PM2.5 and Aß42 were similar for 5-y estimates (ß:-0.076; 95% CI: -0.160, 0.005). Dichotomized CSF variables revealed similar associations between ambient PM2.5 and Aß42. Associations with traffic-related PM2.5 were similar but not significant. Associations between PM2.5 exposures and tTau, pTau tTau/Aß42, or pTau/Aß42 levels were mainly null. CONCLUSION: In our study, consistent trends were found between 1-y PM2.5 exposure and decreased CSF Aß42, which suggests an accumulation of amyloid plaques in the brain and an increased risk of developing AD. https://doi.org/10.1289/EHP13503.

Quantifying the impact of urban road traffic on air quality: activity pre-pandemic and during partial and full lockdowns.

The impact of partial and full COVID lockdowns in 2020 on vehicle miles traveled (VMT) in Kuwait was estimated using data extracted from the Directions API of Google Maps and a Python script running as a cronjob. This approach was validated by comparing the predictions based on the app to measuring traffic flows for 1 week across four road segments considered in this study. VMT during lockdown periods were compared to VMT for the same calendar weeks before the pandemic. NOx emissions were estimated based on VMT and were used to simulate the spatial patterns of NOx concentrations using an air quality model (AERMOD). Compared to pre-pandemic periods, VMT was reduced by up to 25.5% and 42.6% during the 2-week partial and full lockdown episodes, respectively. The largest reduction in the traffic flow rate occurred during the middle of these 2-week periods, when the traffic flow rate decreased by 35% and 49% during the partial and full lockdown periods, respectively. The AERMOD simulation results predicted a reduction in the average maximum concentration of emissions directly related to VMT across the region by up to 38%, with the maximum concentration shifting to less populous residential areas as a result of the lockdown.

Association Between Maternal Prenatal Exposure to Household Air Pollution and Child Respiratory Health: A Systematic Review and Meta-analysis.

Maternal prenatal exposure to household air pollution (HAP) is a critical public health concern with potential long-term implications for child respiratory health. The objective of this study is to assess the level of association between prenatal household air pollution and child respiratory health, and to identify which HAP pollutants are associated with specific respiratory illnesses or symptoms and to what degree. Relevant studies were retrieved from PubMed databases up to April 27, 2010, and their reference lists were reviewed. Random effects models were applied to estimate summarized relative risks (RRs) and 95% confidence intervals (CIs). The analysis involved 11 studies comprising 387 767 mother-child pairs in total, assessing various respiratory health outcomes in children exposed to maternal prenatal HAP. Children with prenatal exposure to HAP pollutants exhibited a summary RR of 1.26 (95% CI=1.08-1.33) with moderate between-study heterogeneity (I²=49.22%) for developing respiratory illnesses. Specific associations were found between prenatal exposure to carbon monoxide (CO) (RR=1.11, 95% CI: 1.09-1.13), Nitrogen Oxides (NOx) (RR=1.46, 95% CI: 1.09-1.60), and particulate matter (PM) (RR=1.26, 95% CI: 1.2186-1.3152) and child respiratory illnesses (all had I² close to 0%, indicating no heterogeneity). Positive associations with child respiratory illnesses were also found with ultrafine particles (UFP), polycyclic aromatic hydrocarbons (PAH), and ozone (O3). However, no significant association was observed for prenatal exposure to sulfur dioxide (SO2). In summary, maternal prenatal exposure to HAP may contribute to a higher risk of child respiratory health issues, emphasizing the need for interventions to reduce this exposure during pregnancy. Targeted public health strategies such as improved ventilation, cleaner cooking technologies, and awareness campaigns should be implemented to minimize adverse respiratory effects on children.

Multiple dietary patterns and the association between long-term air pollution exposure with type 2 diabetes risk: Findings from UK Biobank cohort study.

BACKGROUND: Evidence of modifying effect of various dietary patterns (DPs) on risk of type 2 diabetes (T2D) induced by long-term exposure to air pollution (AP) is still rather lacking, which therefore we aimed to explore in this study. METHODS: We included 78,230 UK Biobank participants aged 40-70 years with at least 2 typical 24-hour dietary assessments and without baseline diabetes. The annual average concentration of particulate matter with diameter micrometers ≤2.5 (PM2.5) and ≤10 (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOX) estimated by land use regression model was the alternative proxy of long-term AP exposure. Three well-known prior DPs such as Mediterranean diet (MED), dietary approaches to stop hypertension diet (DASH), and empirical dietary inflammatory pattern (EDIP), as well as three posterior DPs derived by the rank reduced regression model were used to capture participants' dietary habits. Cox regression models were used to estimate AP-T2D and DP-T2D associations. Modifying effect of DPs on AP-T2D association was assessed using stratified analysis and heterogeneity test. RESULTS: During a median follow-up 12.19 years, 1,693 participants developed T2D. PM2.5, PM10, NO2, and NOX significantly increased the T2D risk (P <0.05), with hazard ratio (HR) and 95% confidence interval (95% CI) for per interquartile range increase being 1.09 (1.02,1.15), 1.04 (1.00, 1.09), 1.11 (1.04, 1.18), and 1.08 (1.03, 1.14), respectively. Comparing high with low adherence, healthy DPs were associated with a 14-41% lower T2D risk. Participants with high adherence to MED, DASH, and anti-EDIP, alongside the posterior anti-oxidative dietary pattern (AODP) had attenuated and statistically non-significant NO2-T2D and NOX-T2D associations (Pmodify <0.05). CONCLUSIONS: Multiple forms of healthy DPs help reduce the T2D risk associated with long-term exposure to NO2 and NOX. Our findings indicate that adherence to healthy DPs is a feasible T2D prevention strategy for people long-term suffering from NO2 and NOX pollution.

Ambient air pollution exposure and the risk of probable sarcopenia: A prospective cohort study.

BACKGROUND: Sarcopenia is characterized by decreased muscle mass and strength, posing threat to quality of life. Air pollutants are increasingly recognized as risk factors for diseases, while the relationship between the two remains to be elucidated. This study investigated whether exposure to ambient air pollution contributes to the development of sarcopenia. METHODS: We employed the data from the UK Biobank with 303,031 eligible participants. Concentrations of PM2·5, NO2, and NOx were estimated. Cox proportional hazard regression models were applied to investigate the associations between pollutants and sarcopenia. RESULTS: 30,766 probable sarcopenia cases was identified during the follow-up. We observed that exposure to PM2.5 (HR, 1.232; 95% CI, 1.053-1.440), NO2 (HR, 1.055; 95% CI, 1.032-1.078) and NOx (HR, 1.016; 95% CI, 1.007-1.026) were all significantly associated with increased risk for probable sarcopenia for each 10 µg/m3 increase in pollutant concentration. In comparison with individuals in the lowest quartiles of exposure, those in the upper quartiles had significantly increased risk of probable sarcopenia. Sarcopenia-related factors, e.g., reduced lean muscle mass, diminished walking pace, and elevated muscle fat infiltration ratio, also exhibited positive associations with exposure to ambient air pollution. On the contrary, high level physical activity significantly mitigated the influence of air pollutants on the development of probable sarcopenia. CONCLUSIONS: Air pollution exposure elevated the risk of developing sarcopenia and related manifestations in a dose-dependent manner, while physical activity maintained protective under this circumstance. Efforts should be made to control air pollution and emphasize the importance of physical activity for skeletal muscle health under this circumstance.

Association of ambient air pollution with hemoglobin levels and anemia in the general population of Korean adults.

BACKGROUND: Emerging evidence has suggested significant associations between ambient air pollution and changes in hemoglobin levels or anemia in specific vulnerable groups, but few studies have assessed this relationship in the general population. This study aimed to evaluate the association between long-term exposure to air pollution and hemoglobin concentrations or anemia in general adults in South Korea. METHODS: A total of 69,830 Korean adults from a large-scale nationwide survey were selected for our final analysis. Air pollutants included particulate matter with an aerodynamic diameter less than or equal to 10 micrometers (PM10), particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers, nitrogen dioxide, sulfur dioxide (SO2), and carbon monoxide (CO). We measured the serum hemoglobin concentration to assess anemia for each participant. RESULTS: In the fully adjusted model, exposure levels to PM10, SO2, and CO for one and two years were significantly associated with decreased hemoglobin concentrations (all p < 0.05), with effects ranging from 0.15 to 0.62% per increase in interquartile range (IQR) for each air pollutant. We also showed a significant association of annual exposure to PM10 with anemia (p = 0.0426); the odds ratio (OR) [95% confidence interval (CI)] for anemia per each increase in IQR in PM10 was estimated to be 1.039 (1.001-1.079). This association was also found in the 2-year duration of exposure (OR = 1.046; 95% CI = 1.009-1.083; adjusted Model 2). In addition, CO exposure during two years was closely related to anemia (OR = 1.046; 95% CI = 1.004-1.091; adjusted Model 2). CONCLUSIONS: This study provides the first evidence that long-term exposure to air pollution, especially PM10, is significantly associated with reduced hemoglobin levels and anemia in the general adult population.

Association Between Individual Air Pollution (PM10, PM2.5) Exposure and Adverse Pregnancy Outcomes in Korea: A Multicenter Prospective Cohort, Air Pollution on Pregnancy Outcome (APPO) Study.

BACKGROUND: Prenatal exposure to ambient air pollution is linked to a higher risk of unfavorable pregnancy outcomes. However, the association between pregnancy complications and exposure to indoor air pollution remains unclear. The Air Pollution on Pregnancy Outcomes research is a hospital-based prospective cohort research created to look into the effects of aerodynamically exposed particulate matter (PM)10 and PM2.5 on pregnancy outcomes. METHODS: This prospective multicenter observational cohort study was conducted from January 2021 to June 2023. A total of 662 women with singleton pregnancies enrolled in this study. An AirguardK® air sensor was installed inside the homes of the participants to measure the individual PM10 and PM2.5 levels in the living environment. The time-activity patterns and PM10 and PM2.5, determined as concentrations from the time-weighted average model, were applied to determine the anticipated exposure levels to air pollution of each pregnant woman. The relationship between air pollution exposure and pregnancy outcomes was assessed using logistic and linear regression analyses. RESULTS: Exposure to elevated levels of PM10 throughout the first, second, and third trimesters as well as throughout pregnancy was strongly correlated with the risk of pregnancy problems according to multiple logistic regression models adjusted for variables. Except for in the third trimester of pregnancy, women exposed to high levels of PM2.5 had a high risk of pregnancy complications. During the second trimester and entire pregnancy, the risk of preterm birth (PTB) increased by 24% and 27%, respectively, for each 10 µg/m3 increase in PM10. Exposure to high PM10 levels during the second trimester increased the risk of gestational diabetes mellitus (GDM) by 30%. The risk of GDM increased by 15% for each 5 µg/m3 increase in PM2.5 during the second trimester and overall pregnancy, respectively. Exposure to high PM10 and PM2.5 during the first trimester of pregnancy increased the risk of delivering small for gestational age (SGA) infants by 96% and 26%, respectively. CONCLUSION: Exposure to high concentrations of PM10 and PM2.5 is strongly correlated with the risk of adverse pregnancy outcomes. Exposure to high levels of PM10 and PM2.5 during the second trimester and entire pregnancy, respectively, significantly increased the risk of PTB and GDM. Exposure to high levels of PM10 and PM2.5 during the first trimester of pregnancy considerably increased the risk of having SGA infants. Our findings highlight the need to measure individual particulate levels during pregnancy and the importance of managing air quality in residential environment.

Characterization of VOC emissions and health risk assessment in the plastic manufacturing industry.

Volatile organic compounds (VOCs) significantly contribute to ozone pollution formation, and many VOCs are known to be harmful to human health. Plastic has become an indispensable material in various industries and daily use scenarios, yet the VOC emissions and associated health risks in the plastic manufacturing industry have received limited attention. In this study, we conducted sampling in three typical plastic manufacturing factories to analyze the emission characteristics of VOCs, ozone formation potential (OFP), and health risks for workers. Isopropanol was detected at relatively high concentrations in all three factories, with concentrations in organized emissions reaching 322.3 µg/m3, 344.8 µg/m3, and 22.6 µg/m3, respectively. Alkanes are the most emitted category of VOCs in plastic factories. However, alkenes and oxygenated volatile organic compounds (OVOCs) exhibit higher OFP. In organized emissions of different types of VOCs in the three factories, alkenes and OVOCs contributed 22.8%, 67%, and 37.8% to the OFP, respectively, highlighting the necessity of controlling them. The hazard index (HI) for all three factories was less than 1, indicating a low non-carcinogenic toxic risk; however, there is still a possibility of non-cancerous health risks in two of the factories, and a potential lifetime cancer risk in all of the three factories. For workers with job tenures exceeding 5 years, there may be potential health risks, hence wearing masks with protective capabilities is necessary. This study provides evidence for reducing VOC emissions and improving management measures to ensure the health protection of workers in the plastic manufacturing industry.

A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation.

Accurate air quality index (AQI) prediction is essential in environmental monitoring and management. Given that previous studies neglect the importance of uncertainty estimation and the necessity of constraining the output during prediction, we proposed a new hybrid model, namely TMSSICX, to forecast the AQI of multiple cities. Firstly, time-varying filtered based empirical mode decomposition (TVFEMD) was adopted to decompose the AQI sequence into multiple internal mode functions (IMF) components. Secondly, multi-scale fuzzy entropy (MFE) was applied to evaluate the complexity of each IMF component and clustered them into high and low-frequency portions. In addition, the high-frequency portion was secondarily decomposed by successive variational mode decomposition (SVMD) to reduce volatility. Then, six air pollutant concentrations, namely CO, SO2, PM2.5, PM10, O3, and NO2, were used as inputs. The secondary decomposition and preliminary portion were employed as the outputs for the bidirectional long short-term memory network optimized by the snake optimization algorithm (SOABiLSTM) and improved Catboost (ICatboost), respectively. Furthermore, extreme gradient boosting (XGBoost) was applied to ensemble each predicted sub-model to acquire the consequence. Ultimately, we introduced adaptive kernel density estimation (AKDE) for interval estimation. The empirical outcome indicated the TMSSICX model achieved the best performance among the other 23 models across all datasets. Moreover, implementing the XGBoost to ensemble each predicted sub-model led to an 8.73%, 8.94%, and 0.19% reduction in RMSE, compared to SVM. Additionally, by utilizing SHapley Additive exPlanations (SHAP) to assess the impact of the six pollutant concentrations on AQI, the results reveal that PM2.5 and PM10 had the most notable positive effects on the long-term trend of AQI. We hope this model can provide guidance for air quality management.

Air Pollutants and Mortality Risk in Patients with Aortic Dissection: Evidence from a Clinical Cohort, Single-Cell Sequencing, and Proteomics.

We aimed to evaluate the association between air pollutants and mortality risk in patients with acute aortic dissection (AAD) in a longitudinal cohort and to explore the potential mechanisms of adverse prognosis induced by fine particulate matter (PM2.5). Air pollutants data, including PM2.5, PM10.0, nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3), were collected from official monitoring stations, and multivariable Cox regression models were applied. Single-cell sequencing and proteomics of aortic tissue were conducted to explore the potential mechanisms. In total, 1,267 patients with AAD were included. Exposure to higher concentrations of air pollutants was independently associated with an increased mortality risk. The high-PM2.5 group carried approximately 2 times increased mortality risk. There were linear associations of PM10, NO2, CO, and SO2 exposures with long-term mortality risk. Single-cell sequencing revealed an increase in mast cells in aortic tissue in the high-PM2.5 exposure group. Enrichment analysis of the differentially expressed genes identified the inflammatory response as one of the main pathways, with IL-17 and TNF signaling pathways being among the top pathways. Analysis of proteomics also identified these pathways. This study suggests that exposure to higher PM2.5, PM10, NO2, CO, and SO2 are associated with increased mortality risk in patients with AAD. PM2.5-related activation and degranulation of mast cells may be involved in this process.

Unaddressed Uncertainties When Scaling Regional Aircraft Emission Surveys to Basin Emission Estimates.

Wide-area aerial methods provide comprehensive screening of methane emissions from oil and gas (O & G) facilities in production basins. Emission detections ("plumes") from these studies are also frequently scaled to the basin level, but little is known regarding the uncertainties during scaling. This study analyzed an aircraft field study in the Denver-Julesburg basin to quantify how often plumes identified maintenance events, using a geospatial inventory of 12,629 O & G facilities. Study partners (7 midstream and production operators) provided the timing and location of 5910 maintenance events during the 6 week study period. Results indicated three substantial uncertainties with potential bias that were unaddressed in prior studies. First, plumes often detect maintenance events, which are large, short-duration, and poorly estimated by aircraft methods: 9.2 to 46% (38 to 52%) of plumes on production were likely known maintenance events. Second, plumes on midstream facilities were both infrequent and unpredictable, calling into question whether these estimates were representative of midstream emissions. Finally, 4 plumes attributed to O & G (19% of emissions detected by aircraft) were not aligned with any O & G location, indicating that the emissions had drifted downwind of some source. It is unclear how accurately aircraft methods estimate this type of plume; in this study, it had material impact on emission estimates. While aircraft surveys remain a powerful tool for identifying methane emissions on O & G facilities, this study indicates that additional data inputs, e.g., detailed GIS data, a more nuanced analysis of emission persistence and frequency, and improved sampling strategies are required to accurately scale plume estimates to basin emissions.