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BACKGROUND: Exposure to fine or respirable particulate matter has been linked to an elevated risk of gestational diabetes mellitus (GDM). However, the association between exposure to particulate matter with an aerodynamic diameter ≤ 1 µm (PM1) and GDM has not been explored. METHODS: We conducted a cohort study involving 60,173 pregnant women from nine hospitals in Beijing, China, from February 2015 to April 2021. Daily concentrations of PM1 and ozone were obtained from a validated spatiotemporal artificial intelligence model. We used a modified Poisson regression combined with distributed lag models to estimate the association between weekly-specific PM1 exposure and the risk of GDM after adjusting for individual-level covariates. RESULTS: Among the 51,299 pregnant women included in the final analysis, 4008 were diagnosed with GDM. Maternal exposure to PM1 during preconception and gestational periods was generally associated with an increased risk of GDM. The most pronounced associations were identified during the 12th week before pregnancy, the 5th-8th weeks of the first trimester, and the 23rd-24th weeks of the second trimester. Each 10 µg/m3 increase in PM1 was associated with a relative risk of GDM of 1.65 (95 % CI: 1.59, 1.72) during the preconception period, 1.67 (95 % CI: 1.61, 1.73) in the first trimester, 1.52 (95 % CI: 1.47, 1.58) in the second trimester, and 2.54 (95 % CI: 2.45, 2.63) when considering the first and second trimester combined. CONCLUSIONS: Exposure to PM1 before and during pregnancy was associated with an increased risk of GDM, particularly during the 12 weeks before pregnancy and gestational weeks 5-8 and 23-24.

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The article evaluates air pollution by particulate matter (PM) in indoor and outdoor air in one of the Polish health resorts, where children and adults with respiratory diseases are treated. The highest indoor PM concentrations were recorded during the winter season. Therefore, the maximum average daily concentration values in indoor air for the PM10, PM2.5, and PM1 fractions were 50, 42 and 23 µg/m3, respectively. In the case of outdoor air, the highest average daily concentrations of PM2.5 reached a value of 40 µg/m3. The analyses and backward trajectories of episodes of high PM concentrations showed the impact of supra-regional sources and the influx of pollutants from North Africa on the variability of PM concentrations. The correlation between selected meteorological parameters and PM concentrations shows the relationship between PM concentrations and wind speed. For example, the correlation coefficients between PM1(I) and PM1(O) concentrations and wind speed were - 0.8 and - 0.7 respectively. These factors determined episodes of high PM concentrations during winter periods in the outdoor air, which were then transferred to the indoor air. Elevated concentrations in indoor air during summer were also influenced by chimney/gravity ventilation and the appearance of reverse chimney effect.

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Gastric cancer (GC) remains a significant health concern in Gansu province, China, with morbidity and mortality rates surpassing national averages. Despite the recognized health risks associated with ambient particulate matter with an aerodynamic diameter <1 µm (PM1), the relationship between PM1 exposure and GC incidence has not been extensively studied. Data on GC cases from 2013 to 2021 were gathered from 262 hospitals in Gansu, China. Concurrently, data on the normalized vegetation index (NDVI), gross domestic product (GDP), drinking and smoking behavioral index (DSBI), PM1, PM2.5, and PM2.5-1 were collected. Utilizing a Bayesian conditional autoregressive (CAR) combined generalized linear model (GLM) with quasi-Poisson regression, we evaluated the impact of PM1, PM2.5, PM2.5-1, NDVI, DSBI, and GDP on GC morbidity while adjusting for potential confounders. Our analysis indicated that exposure to PM1 (µg/m3) is significantly positively correlated with GC incidence in regions with an overall age-standardized incidence rate (ASIR) >40 (relative risks [RR]: 1.023, 95% confidence intervals [CI, 1.007, 1.039]), male ASIR >50 (RR: 1.014, 95% CI [1.009, 1.019]), and female ASIR >20 (RR: 1.010, 95% CI [1.002, 1.018]). PM2.5, PM2.5-1, DSBI, and GDP were positively correlated with GC incidence, while NDVI was negatively correlated in the study regions. Our findings provided evidence of a positive correlation between PM1 exposure and GC incidence in high-risk areas of GC within arid regions. Further research is warranted to elucidate the complex nonlinear relationships between environmental factors and GC. These insights could inform strategies for improving the control and prevention of GC in Gansu and similar regions.

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The airport and its surrounding areas are home to a variety of pollution sources, and air pollution is a recognized health concern for local populated regions. Submicron particulate matter (PM1 with an aerodynamic diameter of <1 mm) is a typical pollutant at airports, and the enrichment of heavy metals (HMs) in PM1 poses a great threat to human health. To comprehensively assess the source-specific health effects of PM1-bound HMs in an airport community, PM1 filter samples were collected around the Tianjin Binhai International Airport for 12 h during the daytime and nighttime, both in the spring and summer, and 10 selected HMs (V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb) were analyzed. The indicatory elements of aircraft emissions were certified as Zn and Pb, which accounted for more than 60% of the sum concentration of detected HMs. The health risks assessment showed that the total non-cancer risks (TNCRs) of PM1-bound HMs were 0.28 in the spring and 0.23 in the summer, which are lower than the safety level determined by the USEPA, and the total cancer risk (TCR) was 2.37 × 10-5 in the spring and 2.42 × 10-5 in the summer, implying that there were non-negligible cancer risks in the Tianjin Airport Community. After source apportionment with EF values and PMF model, four factors have been determined in both seasons. Consequently, the source-specific health risks were also evaluated by combining the PMF model with the health risk assessment model. For non-cancer risk, industrial sources containing high concentrations of Mn were the top contributors in both spring (50.4%) and summer (44.2%), while coal combustion with high loads of As and Cd posed the highest cancer risk in both seasons. From the perspective of health risk management, targeted management and control strategies should be adopted for industrial emissions and coal combustion in the Tianjin Airport Community.

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BACKGROUND: Limited attention has been paid to the health effects of long-term PM1 exposure on stroke admission. Current investigations exploring the long-term PM exposure effect are largely based on observational studies, and PM generally is not allocated randomly to participants. Using traditional regression models might confuse messaging and hinder policy recommendations for pollution control and disease prevention policies. METHODS: We conducted a cohort study among 36,271 adults from one of the largest cities in China in 2015 and followed up through 2020. Hazard ratios of stroke admissions following long-term PM1 exposure were estimated via a causal inference approach, marginal structural time-varying Cox proportional hazard model, accounting for multiple confounders. Additionally, several sensitivity analyses and impact modification analyses were carried out. RESULTS AND DISCUSSION: Associations with 1 µg/m3 increase in long-term PM1 were identified for total (HR, 1.079; 95 %CI, 1.012-1.151) and ischemic stroke admissions (HR, 1.092; 95 %CI, 1.018-1.171). The harmful associations varied with exposure duration, initially increasing and then decreasing. The 2-3 years cumulative exposure was associated with a 3.3-5.4 % raised risk for total stroke. For every 1 µg/m³ increase in long-term PM1 exposure, females exhibited a higher risk of both total and ischemic stroke (13 % and 16 %) than men (4 % and 5 %). Low-exposure individuals (whose annual PM1 concentrations were under the third quartile among the annual concentrations for all the participants) exhibited greater sensitivity to PM1 effects (total stroke: 1.079 vs. 1.107; ischemic stroke: 1.092 vs. 1.116). The results underline the importance of safeguarding low-exposed people in highly polluted areas and suggest that long-term PM1 exposure may increase stroke admission risk, warranting attention to vulnerable groups.

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Carbonaceous aerosols exhibit seasonal variations due to a complex interplay of emission sources, meteorological conditions, and chemical processes. This study presents the first year-round dual­carbon isotopic analysis of carbonaceous aerosols in Northeastern Europe (Lithuania). The emphasis was placed on the processes affecting carbonaceous submicron particle (PM1) concentrations and their isotopic composition (δ13CTC, fc) during different seasons. Aerosol particles were collected in the two distinct sites: at an urban background site (Vilnius) and a coastal site (Preila). The concentrations of total carbon (TC) and black carbon (BC) varied both spatially and temporally. The annual average concentrations were 4 µg/m3 for TC and 2.3 µg/m3 for BC at the urban background site. They were considerably lower at the coastal site with 2.9 µg/m3 for TC and 0.74 µg/m3 for BC. The peak concentrations of TC and BC that occur during the cold season indicate a significant impact from residential heating. The δ13C in aerosols exhibited a distinct seasonal cycle with depleted δ13CTC values during the warm season (April-October). Through the integration of isotopic composition, contemporary carbon (fc), and BC source apportionment, we achieved precise predictions of isotopic parameter changes, encompassing pollution sources and the influence of meteorological parameters. To better understand the respective contributions of local and regional sources, air mass trajectories, wind patterns (speed and direction), and the polar conditional probability function (CPF) were studied in parallel. The study indicates that the isotopic composition of PM1 at both sites is primarily controlled by emission sources (local and regional), while meteorological conditions (temperature and mixing layer height) have less influence. These variations have important implications for regional air quality, climate dynamics, and public health, which are persistently subject to continuous research and monitoring.

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Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 µm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 µg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.

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This prospective birth cohort study evaluated the association of exposure to PM2.5 (diameter ≤2.5 µm), PM1-2.5 (1-2.5 µm), and PM1 (≤1 µm) with maternal thyroid autoimmunity and function during early pregnancy. A total of 15,664 pregnant women were included at 6 to 13+6 gestation weeks in China from 2018 to 2020. Single-pollutant models using generalized linear models (GLMs) showed that each 10 µg/m3 increase in PM2.5 and PM1-2.5 was related with 6% (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.01, 1.12) and 15% (OR = 1.15, 95% CI: 1.08, 1.22) increases in the risk of thyroid autoimmunity, respectively. The odds of thyroid autoimmunity significantly increased with each interquartile range increase in PM2.5 and PM1-2.5 exposure (P for trend <0.001). PM1 exposure was not significantly associated with thyroid autoimmunity. GLM with natural cubic splines demonstrated that increases in PM2.5 and PM1-2.5 exposure were associated with lower maternal FT4 levels, while a negative association between PM1 and FT4 levels was found when exposure exceeded 32.13 µg/m3. Only PM2.5 exposure was positively associated with thyrotropin (TSH) levels. Our findings suggest that high PM exposure is associated with maternal thyroid disruption during the early pregnancy.

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COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 µg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 µg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

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The concentrations of anhydrosugars (levoglucosan, mannosan, and galactosan), polyols (inositol, xylitol, sorbitol, and mannitol), and glucose were measured in PM1 and PM10 samples collected during 1 year at a traffic site in the city of Elche (southeastern Spain). Levoglucosan, mannosan, and galactosan were mainly found in the PM1 fraction since they are mainly emitted from biomass burning (BB). Likewise, inositol, xylitol, and sorbitol were primarily distributed in the fine mode, suggesting a non-negligible contribution from anthropogenic sources (specifically BB) to the levels of these compounds. This was supported by their seasonal variations, with higher concentrations during winter, and their correlations with levoglucosan concentrations. The average contributions of biomass burning and biogenic sources to OC and PM levels were calculated using levoglucosan and mannitol, respectively, as tracers. On average, BB accounted for 12% and 16% of the OC in PM1 and PM10, while the estimated contribution of fungal spores to OC and PM10 levels was 1.2 and 0.8%, respectively. The results of the present study suggest that, at least in the study area, most sugar alcohols are not appropriate tracers of biogenic emissions.

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Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.

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Previous studies have reported the association between particulate matter (PM) and childhood allergic rhinitis (AR). However, it is unclear whether food allergy (FA) modifies the PM-AR association. We aimed at evaluating the effect of the modification of FA on PM-AR association in preschool children. We adopted a cross-sectional study and conducted a questionnaire survey among preschool children aged 3-6 years in 7 cities in China from June 2019 to June 2020 to collect information on AR and FA. We used a combination of multilevel logistic regression and restricted cubic spline functions to quantitatively assess whether FA modifies the associations between size-specific PM exposure (1 × 1 km) and the risk of AR. The adjusted odds ratios (ORs) for AR among the children with FA as per a 10 µg/m3 increase in early life PM1, PM2.5, and PM10 were significantly higher than the corresponding ORs among the children without FA [e.g., OR: 1.58, 95% CI: (1.32, 1.90) vs 1.29, 95% CI: (1.18, 1.41), per 10 µg/m3 increase in PM1]. The interactions between FA and size-specific PM exposure and their effects on AR were statistically significant (all p-int < 0.001). FA, as an important part of the allergic disease progression, may modify the PM-AR association in preschool children.

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Rapid social and industrial development has resulted in an increasing demand for fossil fuel energy, which increases particulate matter (PM) pollution. In this study, we employed a simple one-step electrospinning technique to fabricate polysulfone (PSF) fiber membranes for PM filtration. A 0.3 g/mL polymer solution with an N,N-dimethylformamide:tetrahydrofuran volume ratio of 3:1 yielded uniform and bead-free PSF fibers with a diameter of approximately 1.17 µm. The PSF fiber membrane exhibited excellent hydrophobicity and mechanical properties, including a tensile strength of 1.14 MPa and an elongation at break of 116.6%. Finally, the PM filtration performance of the PSF fiber membrane was evaluated. The filtration efficiencies of the membrane for PM2.5 and PM1.0 were approximately 99.6% and 99.2%, respectively. The pressure drops were 65.0 and 65.2 Pa, which were significantly lower than those of commercial air filters. Using this technique, PSF fiber membrane filters can be easily fabricated over a large area, which is promising for numerous air filtration systems.

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BACKGROUND: Airborne particulate matter pollution has been linked to occurrence of childhood allergic rhinitis (AR). However, the relationships between exposure to particulate matter with an aerodynamic diameter ≤1 µm (PM1) during early life (in utero and first year of life) and the onset of childhood AR remain largely unknown. This study aims to investigate potential associations of in utero and first-year exposures to size-segregated PMs, including PM1, PM1-2.5, PM2.5, PM2.5-10, and PM10, with childhood AR. METHODS: We investigated 29286 preschool children aged 3-6 years in 7 Chinese major cities during 2019-2020 as the Phase II of the China Children, Families, Health Study. Machine learning-based space-time models were utilized to estimate early-life residential exposure to PM1, PM2.5, and PM10 at 1 × 1-km resolutions. The concentrations of PM1-2.5 and PM2.5-10 were calculated by subtracting PM1 from PM2.5 and PM2.5 from PM10, respectively. Multiple mixed-effects logistic models were used to assess the odds ratios (ORs) and 95% confidence intervals (CIs) of childhood AR associated with per 10-µg/m3 increase in exposure to particulate air pollution during in utero period and the first year of life. RESULTS: Among the 29286 children surveyed (mean ± standard deviation, 4.9 ± 0.9 years), 3652 (12.5%) were reported to be diagnosed with AR. Average PM1 concentrations during in utero period and the first year since birth were 36.3 ± 8.6 µg/m3 and 33.1 ± 6.9 µg/m3, respectively. Exposure to PM1 and PM2.5 during pregnancy and the first year of life was associated with an increased risk of AR in children, and the OR estimates were higher for each 10-µg/m3 increase in PM1 than for PM2.5 (e.g., 1.132 [95% CI: 1.022-1.254] vs. 1.079 [95% CI: 1.014-1.149] in pregnancy; 1.151 [95% CI: 1.014-1.306] vs. 1.095 [95% CI: 1.008-1.189] in the first year of life). No associations were observed between AR and both pre- and post-natal exposure to PM1-2.5, indicating that PM1 rather than PM1-2.5 contributed to the association between PM2.5 and childhood AR. In trimester-stratified analysis, childhood AR was only found to be associated with exposure to PM1 (OR = 1.077, 95% CI: 1.027-1.128), PM2.5 (OR = 1.048, 95% CI: 1.018-1.078), and PM10 (OR = 1.032, 95% CI: 1.007-1.058) during the third trimester of pregnancy. Subgroup analysis suggested stronger PM-AR associations among younger (<5 years old) and winter-born children. CONCLUSIONS: Prenatal and postnatal exposures to ambient PM1 and PM2.5 were associated with an increased risk of childhood AR, and PM2.5-related hazards could be predominantly attributed to PM1. These findings highlighted public health significance of formulating air quality guideline for ambient PM1 in mitigating children's AR burden caused by particulate air pollution.

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Antibiotic resistome could be loaded by bioaerosols and escape from wastewater or sludge to atmosphere environments. However, until recently, their profile, mobility, bacterial hosts, and risks in submicron bioaerosols (PM1.0) remain unclear. Here, metagenomic sequencing and assembly were employed to conduct an investigation of antibiotic resistome associated with PM1.0 within and around a full-scale wastewater treatment plant (WWTP). More subtypes of antibiotic resistant genes (ARGs) with higher total abundance were found along the upwind-downwind-WWTP transect. ARGs in WWTP-PM1.0 were mainly mediated by plasmids and transposases were the most prevalent mobile genetic elements (MGEs) co-occurring with ARGs. A contig-based analysis indicated that very small proportions (15.32%-19.74%) of ARGs in WWTP-PM1.0 were flanked by MGEs. Proteobacteria was the most dominant host of ARGs. A total of 28 kinds of potential pathogens, such as Pseudomonas aeruginosa and Escherichia coli, carried multiple ARG types. Compared to upwind, WWTP and corresponding downwind were characterized by higher PM1.0 resistome risk. This study emphasizes the vital role of WWTPs in discharging PM1.0-loaded ARGs and antibiotic resistant pathogens to air, and indicates the need for active safeguard procedures, such as that employees wear masks and work clothes, covering the main emission sites, and collecting and destroying of bioaerosols.

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BACKGROUND: China has a serious air pollution problem and a high prevalence of obesity. The interaction between the two and its impact on all-cause mortality is a public health issue of great concern. OBJECTIVES: This study aimed to investigate the association between long-term exposure to particulate matter with aerodynamic diameter ≤ 1 µm (PM1) and all-cause mortality, as well as the interaction effect of body mass index (BMI) in the association. METHODS: A total of 33,087 participants from 162 counties in 25 provinces in China were included, with annual average PM1 exposure being estimated based on the county address. The PM1-mortality relation was evaluated using the time-varying Cox proportional hazards models, with the dose-response relationship being fitted using the penalized splines. Besides, the potential interaction effect of BMI in the PM1-mortality relation was evaluated. RESULTS: The incidence of all-cause deaths was 76.99 per 10,000 person-years over a median of 8.2 years of follow-up. After controlling for potential confounders, the PM1-mortality relation was approximately J-shaped. The full-adjustment analysis observed the hazard ratio (HR) of all-cause mortality was 1.114 [95 % confidence interval (CI): 1.017-1.220] corresponding to a 10 µg/m3 rise in PM1 concentration. Further stratified analyses suggested the adverse effects of PM1 might be more pronounced among the underweight. DISCUSSION: Higher PM1 concentrations were associated with an increase in all-cause mortality. The BMI might further alter the relation, and the underweight population was the sensitive subgroup of the population that needed to be protected.

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Objective To quantitatively evaluate the association of short-term exposure to ambient submicron particulate matter (PM1) with hospital admissions for angina in older adults. Methods A case-crossover study was conducted among 46 687 older adults hospitalized for angina from 2016 to 2019 in Guangzhou medical institutions. Grid data on ambient PM1 concentrations in Guangzhou were obtained from the ChinaHighAirPollutants (CHAP) dataset. Exposure to PM1 was assessed according to each subject's residential addresses. Conditional logistic regression model was used to analyze the the exposure-response association between PM1 and hospital admissions for angina. Results From 2016 to 2019, the average exposure level of PM1 on the same day of hospital admissions (lag 0) for angina was 21.0 ± 11.5 μg/m3. The results of main model analysis showed that lag 0 day exposure to ambient PM1 was significantly associated with a higher odds of hospital admissions for angina in older adults. Each 10 μg/m3 increase of PM1 exposure level was significantly associated with a 1.31% (95% CI: 0.05%, 2.59%) increased odds of angina admissions. Results from a two-pollutant model adjusting for O3 showed that the association between short-term exposure to PM1 and odds of hospitalization for angina remained stable. According to the results of the above model, it was estimated that the excess hospitalization attributable to ambient PM1 exposure accounted for 2.46% (95% CI: 0.09%, 4.76%) of the total admissions in Guangzhou during 2016-2019, corresponding to 1539 (95% CI: 54, 2976) admissions. No significant effect modification on the associations was observed by sex, age, or season. Conclusion Short-term exposure to ambient PM1 was significantly associated with an increased odds of hospital admissions for angina in older adults.

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Based on the PM1 mass concentration data from all the air quality monitoring stations in China from 2014 to 2017, the temporal and spatial distribution characteristics of PM1 concentration were studied using the time series statistical and spatial hierarchical clustering methods, and the PM1 spatiotemporal evolution characteristics were revealed. Combined with AOD data of the MODIS remote-sensing satellite, the temporal and spatial variation in PM1-AOD correlation was analyzed on a fine scale. The results showed that, from 2014 to 2017, the annual average PM1 concentration in China decreased yearly, the seasonal PM1 concentration showed the characteristics of "high in winter and low in summer," and the monthly average PM1 concentration showed a "U"-shaped variation. An "M"-shaped PM1 variation pattern was presented before and after the holidays. Weekly variation showed that high PM1 values occurred on Mondays and Fridays, and low ones occurred on Sundays. Based on the spatial clustering method, the national average annual PM1 concentration in China was divided into seven categories, and the overall spatial distribution pattern was "high in the east and low in the west and high in the north and low in the south." The highest and the lowest values of average PM1 concentration occurred in central China(54.59 µg·m-3) and in Xinjiang-Qinghai-Xizang(11.37 µg·m-3), respectively. The PM1-AOD relationship was positively correlated as a whole, the highest correlation coefficient was 0.55 in central China, and the lowest value was 0.36 in central and southern China.

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The present study explored the potential role of cold-regulated plasma membrane protein COR413PM1 isolated from Saussurea involucrata (Matsum. & Koidz)(SikCOR413PM1), in enhancing cotton (Gossypium hirsutum) tolerance to cold and drought stresses through transgenic methods. Under cold and drought stresses, the survival rate and the fresh and dry weights of the SikCOR413PM1-overexpressing lines were higher than those of the wild-type plants, and the degree of leaf withering was much lower. Besides, overexpressing SikCOR413PM1 overexpression increased the relative water content, reduced malondialdehyde content and relative conductivity, and elevated proline and soluble sugar levels in cotton seedlings. These findings suggest that SikCOR413PM1 minimizes cell membrane damage and boosts plant stability under challenging conditions. Additionally, overexpression of this gene upregulated antioxidant enzyme-related genes in cotton seedlings, resulting in enhanced antioxidant enzyme activity, lowered peroxide content, and reduced oxidative stress. SikCOR413PM1 overexpression also modulated the expression of stress-related genes (GhDREB1A, GhDREB1B, GhDREB1C, GhERF2, GhNAC3, and GhRD22). In field trials, the transgenic cotton plants overexpressing SikCOR413PM1 displayed high yields and increased environmental tolerance. Our study thus demonstrates the role of SikCOR413PM1 in regulating stress-related genes, osmotic adjustment factors, and peroxide content while preserving cell membrane stability and improving cold and drought tolerance in cotton.

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Cooking can emit high concentrations of particles and gaseous pollutants. Cooking has contributed to the major source of indoor air pollutants, especially for particle pollutants in residential buildings. Many studies already analyzed the emission characteristics of Chinese cooking-related UFPs and PM2.5, while less for the fine particle size distributions. Currently, the fine particle emission characteristics of Chinese cooking need to be further investigated, since the mass size distribution of Chinese cooking is dominated by fine particles. This study determined the emission characteristics of PM1 and fine particles from three Chinese cooking methods. The capture efficiencies of particles were also measured by a modified indirect approach, including the impact of particle decay. The results showed that stir-fried vegetable and pan-fried meat dishes generated more fine particles at 0.542-1.5 µm. Besides, pan-fried and deep-fried meat dishes produce a higher generation of PM1. The fine particles (0.542-10 µm) number-based and volume-based size distributions of six dishes both presented a monodisperse behavior. The cooking methods are not a sensitive factor to the volume frequency of fine particle ranging from 0.542 to 10 µm. The averaged volume median and mode diameter for six typical Chinese dishes are 2.5 µm and 3.3 µm, respectively. The Sauter and DeBroukere mean diameter is 4.7 µm and 5.6 µm, respectively. The decay of fine particles increases with the particle diameter. The impact of particle decay on capture efficiency for 2-3 µm particles is about 5%. The capture efficiencies of pan-fried and deep-fried meat dishes are lower than that of vegetable dishes. In contrast, the capture efficiency for stir-fried meat dishes is higher than that of vegetable dishes. The capture efficiency for PM1 and 0.542-5 µm particles from six typical Chinese dishes were 60-90% on the IEC recommended exhaust flowrate.

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