PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing,China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R ² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.     

Acute Effects of Particulate Air Pollution on the Incidence of Coronary Heart Disease in Shanghai,China

Introduction

Evidence based on ecological studies in China suggests that short-term exposure to particulate matter (PM) is associated with cardiovascular mortality. However, there is less evidence of PM-related morbidity for coronary heart disease (CHD) in China. This study aims to investigate the relationship between acute PM exposure and CHD incidence in people aged above 40 in Shanghai.

Methods

Daily CHD events during 2005–2012 were identified from outpatient and emergency department visits. Daily average concentrations for particulate matter with aerodynamic diameter less than 10 microns (PM₁₀) were collected over the 8-year period. Particulate matter with aerodynamic diameter less than 2.5 microns (PM_2.5) were measured from 2009 to 2012. Analyses were performed using quasi-poisson regression models adjusting for confounders, including long-term trend, seasonality, day of the week, public holiday and meteorological factors. The effects were also examined by gender and age group (41–65 years, and >65 years).

Results

There were 619928 CHD outpatient and emergency department visits. The average concentrations of PM₁₀ and PM_2.5 were 81.7μg/m³ and 38.6μg/m³, respectively. Elevated exposure to PM₁₀ and PM_2.5 was related with increased risk of CHD outpatients and emergency department visits in a short time course. A 10 μg/m³ increase in the 2-day PM₁₀ and PM_2.5 was associated with increase of 0.23% (95% CI: 0.12%, 0.34%) and 0.74% (95% CI: 0.44%, 1.04%) in CHD morbidity, respectively. The associations appeared to be more evident in the male and the elderly.

Conclusion

Short-term exposure to high levels of PM₁₀ and PM_2.5 was associated with increased risk of CHD outpatient and emergency department visits. Season, gender and age were effect modifiers of their association.     

Estimating PM2.5 Concentrations in Xi'an City Using a Generalized Additive Model with Multi-Source Monitoring Data

Particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) represents a severe environmental problem and is of negative impact on human health. Xi''an City, with a population of 6.5 million, is among the highest concentrations of PM_2.5 in China. In 2013, in total, there were 191 days in Xi’an City on which PM_2.5 concentrations were greater than 100 μg/m³. Recently, a few studies have explored the potential causes of high PM_2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM_2.5 concentrations and other pollutants, including CO, NO₂, SO₂, and O₃, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM_2.5 concentrations. This model contains linear functions of SO₂ and CO, univariate smoothing non-linear functions of NO₂, O₃, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM_2.5 concentrations, with R² = 0.691, which improves the result of a stepwise linear regression (R² = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO₂, NO₂, and O₃ account for 10.88% of the total deviance. These results show that in Xi''an City, the traffic and other industrial emissions are the primary source of PM_2.5. Temperature, location, and wind variables also non-linearly related with PM_2.5.     

Effect of Vitamin E and Omega-3 Fatty Acids on Protecting Ambient PM2.5-Induced Inflammatory Response and Oxidative Stress in Vascular Endothelial Cells

Although the mechanisms linking cardiopulmonary diseases to ambient fine particles (PM_2.5) are still unclear, inflammation and oxidative stress play important roles in PM_2.5-induced injury. It is well known that inflammation and oxidative stress could be restricted by vitamin E (Ve) or omega-3 fatty acids (Ω-3 FA) consumption. This study investigated the effects of Ve and Ω-3 FA on PM_2.5-induced inflammation and oxidative stress in vascular endothelial cells. The underlying mechanisms linking PM_2.5 to vascular endothelial injury were also explored. Human umbilical vein endothelial cells (HUVECs) were treated with 50 μg/mL PM_2.5 in the presence or absence of different concentrations of Ve and Ω-3 FA. The inflammatory cytokines and oxidative stress markers were determined. The results showed that Ve induced a significant decrease in PM_2.5-induced inflammation and oxidative stress. Malondialdehyde (MDA) in supernatant and reactive oxygen species (ROS) in cytoplasm decreased by Ve, while the superoxide dismutase (SOD) activity elevated. The inflammatory cytokines interleukin 6 (IL-6) and tumor necrosis factor α (TNF-α) also reduced by Ve. Moreover, Ω-3 FA played the same role on decreasing the inflammation and oxidative stress. IL-6 and TNF-α expressions were significantly lower in combined Ve with Ω-3 FA than treatment with Ve or Ω-3 FA alone. The Ve and Ω-3 FA intervention might abolish the PM_2.5-induced oxidative stress and inflammation in vascular endothelial cells. There might be an additive effect of these two nutrients in mediating the PM_2.5-induced injury in vascular endothelial cells. The results suggested that inflammation and oxidative stress might be parts of the mechanisms linking PM_2.5 to vascular endothelial injury.     

Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

Objective

Ambient fine particulate matter (PM_2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM_2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM_2.5 mass concentrations for urban residences in Beijing.

Methods

In this study, 24-h real-time indoor and ambient PM_2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM_2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM_2.5 mass concentration.

Results

Hourly ambient PM_2.5 mass concentrations were 3–280 μg/m³ with a median of 58 μg/m³, and hourly indoor counterpart were 4–193 μg/m³ with a median of 34 μg/m³. The median indoor/ambient ratio of PM_2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM_2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM_2.5 mass concentrations on the community basis (coefficients: r≥0.90, p<0.0001), and the ambient data explained ≥84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM_2.5 mass concentrations.

Conclusions

PM_2.5 of ambient origin made dominant contribution to residential indoor PM_2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM_2.5 raised the concern of exposure misclassification when using ambient PM_2.5 mass concentrations as exposure surrogates. PM_2.5 of indoor origin still had minor influence on indoor PM_2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM_2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models.     

Lacrimal Cytokines Assessment in Subjects Exposed to Different Levels of Ambient Air Pollution in a Large Metropolitan Area

Background

Air pollution is one of the most environmental health concerns in the world and has serious impact on human health, particularly in the mucous membranes of the respiratory tract and eyes. However, ocular hazardous effects to air pollutants are scarcely found in the literature.

Design

Panel study to evaluate the effect of different levels of ambient air pollution on lacrimal film cytokine levels of outdoor workers from a large metropolitan area.

Methods

Thirty healthy male workers, among them nineteen professionals who work on streets (taxi drivers and traffic controllers, high pollutants exposure, Group 1) and eleven workers of a Forest Institute (Group 2, lower pollutants exposure compared to group 1) were evaluated twice, 15 days apart. Exposure to ambient PM_2.5 (particulate matter equal or smaller than 2.5 μm) was 24 hour individually collected and the collection of tears was performed to measure interleukins (IL) 2, 4, 5 and 10 and interferon gamma (IFN-γ) levels. Data from both groups were compared using Student’s t test or Mann- Whitney test for cytokines. Individual PM_2.5 levels were categorized in tertiles (lower, middle and upper) and compared using one-way ANOVA. Relationship between PM_2.5 and cytokine levels was evaluated using generalized estimating equations (GEE).

Results

PM_2.5 levels in the three categories differed significantly (lower: ≤22 μg/m³; middle: 23–37.5 μg/m³; upper: >37.5 μg/m³; p<0.001). The subjects from the two groups were distributed unevenly in the lower category (Group 1 = 8%; Group 2 = 92%), the middle category (Group 1 = 89%; Group 2 = 11%) and the upper category (Group 1 = 100%). A significant relationship was found between IL-5 and IL-10 and PM_2.5 levels of the group 1, with an average decrease of 1.65 pg/mL of IL-5 level and of 0.78 pg/mL of IL-10 level in tear samples for each increment of 50 μg/m3 of PM_2.5 (p = 0.01 and p = 0.003, respectively).

Conclusion

High levels of PM_2.5 exposure is associated with decrease of IL-5 and IL-10 levels suggesting a possible modulatory action of ambient air pollution on ocular surface immune response.     

Clean air actions in China,PM2.5 exposure,and household medical expenditures: A quasi-experimental study

BackgroundExposure to air pollution, a leading contributor to the global burden of disease, can cause economic losses. Driven by clean air policies, the air quality in China, one of the most polluted countries, has improved rapidly since 2013. This has enabled a unique, quasi-experiment to assess the economic impact of air pollution empirically.Methods and findingsUsing a series of nation-scale longitudinal surveys in 2011, 2013, and 2015, we first examined the questionnaire-based medical expenditure changes before and after the policy intervention for air pollution. Using a state-of-the-art estimator of the historical concentration of particulate matters with diameter less than 2.5 μm (particulate matter (PM)_2.5), we further quantified the association between household medical expenditure and PM_2.5 using mixed-effect models of the repeated measurements from 26,511 households in 126 cities. Regression models suggest a robust linear association between reduced PM_2.5 and saved medical expenditures, since the association did not vary significantly across models with different covariate adjustments, subregions, or subpopulations. Each 10 μg/m³ reduction in PM_2.5 was associated with a saving of 251.6 (95% CI: 30.8, 472.3; p-value = 0.026) Yuan in per capita annual medical expenditure. However, due to limitations in data quality (e.g., self-reported expenditures), and imperfect control for unmeasured confounders or impact from concurrent healthcare reform in China, the causality underlying our findings should be further confirmed or refuted.ConclusionIn this study, we observed that compared with the PM_2.5 reduction in 2013, the PM_2.5 reduction in 2017 was associated with a saving of 552 (95% CI: 68, 1036) Yuan / (person × year), or approximately 736 billion Yuan (equivalent to 111 billion US dollar) per year nationally, which is equivalent to approximately 1% of the national gross domestic product of China.

In this observational study, Tao Xue and colleagues explore associations between medical expenses and changes to clean air policies in China since 2013.     

Asthma and PM10

PM₁₀ (the mass of particles present in the air having a 50% cutoff for particles with an aerodynamic diameter of 10 μm) is the standard measure of particulate air pollution used worldwide. Epidemiological studies suggest that asthma symptoms can be worsened by increases in the levels of PM₁₀. Epidemiological evidence at present indicates that PM₁₀ increases do not raise the chances of initial sensitisation and induction of disease, although further research is warranted. PM₁₀ is a complex mixture of particle types and has many components and there is no general agreement regarding which component(s) could lead to exacerbations of asthma. However pro-inflammatory effects of transition metals, hydrocarbons, ultrafine particles and endotoxin, all present to varying degrees in PM₁₀, could be important. An understanding of the role of the different components of PM₁₀ in exacerbating asthma is essential before proper risk assessment can be undertaken leading to advice on risk management for the many asthmatics who are exposed to air pollution particles.     

Fine Particulate Air Pollution and Hospital Emergency Room Visits for Respiratory Disease in Urban Areas in Beijing,China, in 2013

BackgroundHeavy fine particulate matter (PM_2.5) air pollution occurs frequently in China. However, epidemiological research on the association between short-term exposure to PM_2.5 pollution and respiratory disease morbidity is still limited. This study aimed to explore the association between PM_2.5 pollution and hospital emergency room visits (ERV) for total and cause-specific respiratory diseases in urban areas in Beijing.MethodsDaily counts of respiratory ERV from Jan 1 to Dec 31, 2013, were obtained from ten general hospitals located in urban areas in Beijing. Concurrently, data on PM_2.5 were collected from the Beijing Environmental Protection Bureau, including 17 ambient air quality monitoring stations. A generalized-additive model was used to explore the respiratory effects of PM_2.5, after controlling for confounding variables. Subgroup analyses were also conducted by age and gender.ResultsA total of 92,464 respiratory emergency visits were recorded during the study period. The mean daily PM_2.5 concentration was 102.1±73.6 μg/m³. Every 10 μg/m³ increase in PM_2.5 concentration at lag₀ was associated with an increase in ERV, as follows: 0.23% for total respiratory disease (95% confidence interval [CI]: 0.11%-0.34%), 0.19% for upper respiratory tract infection (URTI) (95%CI: 0.04%-0.35%), 0.34% for lower respiratory tract infection (LRTI) (95%CI: 0.14%-0.53%) and 1.46% for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) (95%CI: 0.13%-2.79%). The strongest association was identified between AECOPD and PM_2.5 concentration at lag_0-3 (3.15%, 95%CI: 1.39%-4.91%). The estimated effects were robust after adjusting for SO₂, O₃, CO and NO₂. Females and people 60 years of age and older demonstrated a higher risk of respiratory disease after PM_2.5 exposure.ConclusionPM_2.5 was significantly associated with respiratory ERV, particularly for URTI, LRTI and AECOPD in Beijing. The susceptibility to PM_2.5 pollution varied by gender and age.     

Particulate matter exposure predicts residence in high-risk areas for community acquired pneumonia among hospitalized children

Particulate matter exposure is a risk factor for lower respiratory tract infection in children. Here, we investigated the geospatial patterns of community-acquired pneumonia and the impact of PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) on geospatial variability of pneumonia in children. We performed a retrospective analysis of prospectively collected population-based surveillance study data of community-acquired pneumonia hospitalizations among children <18 years residing in the Memphis metropolitan area, who were enrolled in the Centers for Disease Control and Prevention sponsored Etiology of Pneumonia in the Community (EPIC) study from January 2010 to June 2012. The outcome measure, residence in high- and low-risk areas for community-acquired pneumonia, was determined by calculating pneumonia incidence rates and performing cluster analysis to identify areas with higher/lower than expected rates of community-acquired pneumonia for the population at risk. High PM_2.5 was defined as exposure to PM_2.5 concentrations greater than the mean value (>10.75 μg/m³), and low PM_2.5 is defined as exposure to PM_2.5 concentrations less than or equal to the mean value (≤10.75 μg/m³). We also assessed the effects of age, sex, race/ethnicity, history of wheezing, insurance type, tobacco smoke exposure, bacterial etiology, and viral etiology of infection. Of 810 (96.1%) subjects with radiographic community-acquired pneumonia, who resided in the Memphis metropolitan area and had addresses which were successfully geocoded (Supplementary Figure F2), 220 (27.2%) patients were identified to be from high- (n = 126) or low-risk (n = 94) community-acquired pneumonia areas. Community-acquired pneumonia in Memphis metropolitan area had a non-homogenous geospatial pattern. PM_2.5 was associated with residence in high-risk areas for community-acquired pneumonia. In addition, children with private insurance and bacterial, as opposed to viral, etiology of infection had a decreased risk of residence in a high-risk area for community-acquired pneumonia. The results from this paper suggest that environmental exposures as well as social risk factors are associated with childhood pneumonia.     

A Pilot Study to Assess Effects of Long-Term Inhalation of Airborne Particulate Matter on Early Alzheimer-Like Changes in the Mouse Brain

Exposure to air pollutants, including particulate matter, results in activation of the brain inflammatory response and Alzheimer disease (AD)-like pathology in dogs and humans. However, the length of time required for inhalation of ambient particulate matter to influence brain inflammation and AD pathology is less clear. Here, we studied the effect of 3 and 9 months of air particulate matter (<2.5 μm diameter, PM_2.5) exposure on brain inflammatory phenotype and pathological hallmarks of AD in C57BL/6 mice. Using western blot, ELISA, and cytokine array analysis we quantified brain APP, beta-site APP cleaving enzyme (BACE), oligomeric protein, total Aβ 1–40 and Aβ 1–42 levels, inducible nitric oxide synthase (iNOS), nitrotyrosine-modified proteins, HNE-Michael adducts, vascular cell adhesion molecule 1 (VCAM-1), glial markers (GFAP, Iba-1), pre- and post- synaptic markers (synaptophysin and PSD-95), cyclooxygenase (COX-1, COX-2) levels, and the cytokine profile in PM_2.5 exposed and filtered air control mice. Only 9 month PM_2.5 exposure increased BACE protein levels, APP processing, and Aβ 1–40 levels. This correlated with a concomitant increase in COX-1 and COX-2 protein levels and a modest alteration in the cytokine profile. These data support the hypothesis that prolonged exposure to airborne particulate matter has the potential to alter brain inflammatory phenotype and promote development of early AD-like pathology.     

Collection and characterization of a bulk PM2.5 air particulate matter material for use in reference materials

A contemporary PM_2.5 (particulate matter smaller than 2.5 Μm aerodynamic diameter) aerosol material from an urban site has been collected for the production of a new standard reference material that will be made available for the development of new PM_2.5 air quality standards. Air particulate matter corresponding to the PM_2.5 fraction was collected at an established Environmental Protection Agency monitoring site in Baltimore, Maryland. The air-sampling system that has been constructed for this collection separates fine particles with a cyclone separator and deposits them onto an array of Teflon membrane filters. The fine air particulate material is removed by ultrasonication or by mechanical means and collected for further preparation of standards. The composition of the collected PM_2.5 aerosol, as well as the composition of the deposited PM_2.5 aerosol, are determined by instrumental nuclear activation analysis and other techniques.     

Study of PM10, PM2.5, and PM1 levels in during dust storms and local air pollution events in urban and rural sites in Tehran

The aim of this study is to survey the PM₁₀, PM_2.5, and PM₁ concentrations in rural and urban areas in Tehran province during cold, warm and dust storm days from December 22, 2016 to June 5, 2017 using Grimm Model aerosol spectrometer. During the study period, daily PM₁₀, PM_2.5, and PM₁ concentrations ranged from 27.2 to 244.96, 8.4 to 77.9, and 6.5 to 56.8 μg/m³ in urban sites, and 22.8 to 286.4, 6 to 41.1, and 2.1 to 20.2 μg/m³ in rural parts, respectively. Particularly, both daily WHO limits for outdoor PM₁₀ (50.0 μg/m³) and PM_2.5 (25.0 μg/m³) exceeded in 95% and 83% of the outdoor measurements in winter and 82% and 58% in total sampled days in urban site, respectively. The 24-h average PM₁₀ and PM_2.5 concentrations also exceeded by 59% and 18% in winter and by 36% and 14% of all sampling days in rural site, respectively. During the dust storm, the 24-h average PM₁₀, PM_2.5, and PM₁ concentrations were, respectively 4.7, 2, and 1.96 times higher than those in urban site and 2, 1.7, and 1.3 times more than those in rural site in all sampled days.     

Effects of Urban Landscape Pattern on PM2.5 Pollution—A Beijing Case Study

PM_2.5 refers to particulate matter (PM) in air that is less than 2.5μm in aerodynamic diameter, which has negative effects on air quality and human health. PM_2.5 is the main pollutant source in haze occurring in Beijing, and it also has caused many problems in other cities. Previous studies have focused mostly on the relationship between land use and air quality, but less research has specifically explored the effects of urban landscape patterns on PM_2.5. This study considered the rapidly growing and heavily polluted Beijing, China. To better understand the impact of urban landscape pattern on PM_2.5 pollution, five landscape metrics including PLAND, PD, ED, SHEI, and CONTAG were applied in the study. Further, other data, such as street networks, population density, and elevation considered as factors influencing PM_2.5, were obtained through RS and GIS. By means of correlation analysis and stepwise multiple regression, the effects of landscape pattern on PM_2.5 concentration was explored. The results showed that (1) at class-level, vegetation and water were significant landscape components in reducing PM_2.5 concentration, while cropland played a special role in PM_2.5 concentration; (2) landscape configuration (ED and PD) features at class-level had obvious effects on particulate matter; and (3) at the landscape-level, the evenness (SHEI) and fragmentation (CONTAG) of the whole landscape related closely with PM_2.5 concentration. Results of this study could expand our understanding of the role of urban landscape pattern on PM_2.5 and provide useful information for urban planning.     

Obesity and the relation between joint exposure to ambient air pollutants and incident type 2 diabetes: A cohort study in UK Biobank

BackgroundAir pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship.Methods and findingsA total of 449,006 participants from UK Biobank free of T2D at baseline were included. Of all the study population, 90.9% were white and 45.7% were male. The participants had a mean age of 56.6 (SD 8.1) years old and a mean body mass index (BMI) of 27.4 (SD 4.8) kg/m². Ambient air pollutants, including particulate matter (PM) with diameters ≤2.5 μm (PM_2.5), between 2.5 μm and 10 μm (PM_2.5–10), nitrogen dioxide (NO₂), and nitric oxide (NO) were measured. An air pollution score was created to assess the joint exposure to the 4 air pollutants. During a median of 11 years follow-up, we documented 18,239 incident T2D cases. The air pollution score was significantly associated with a higher risk of T2D. Compared to the lowest quintile of air pollution score, the hazard ratio (HR) (95% confidence interval [CI]) for T2D was 1.05 (0.99 to 1.10, p = 0.11), 1.06 (1.00 to 1.11, p = 0.051), 1.09 (1.03 to 1.15, p = 0.002), and 1.12 (1.06 to 1.19, p < 0.001) for the second to fifth quintile, respectively, after adjustment for sociodemographic characteristics, lifestyle factors, genetic factors, and other covariates. In addition, we found a significant interaction between the air pollution score and obesity status on the risk of T2D (p-interaction < 0.001). The observed association was more pronounced among overweight and obese participants than in the normal-weight people. Genetic risk score (GRS) for T2D or obesity did not modify the relationship between air pollution and risk of T2D. Key study limitations include unavailable data on other potential T2D-related air pollutants and single-time measurement on air pollutants.ConclusionsWe found that various air pollutants PM_2.5, PM_2.5–10, NO_2, and NO, individually or jointly, were associated with an increased risk of T2D in the population. The stratified analyses indicate that such associations were more strongly associated with T2D risk among those with higher adiposity.

Xiang Li and co-workers study the potential influence of obesity on associations between air pollutants and incidence of type 2 diabetes.     

广州大夫山雨季林内外空气TSP和PM2.5浓度及水溶性离子特征

采用平行同步采样法,于2012年雨季,对广州市大夫山森林公园林内外空气的总悬浮颗粒物(TSP)和细颗粒物(PM_2.5)样品进行了24 h收集,测定了TSP和PM_2.5的质量浓度并分析了样品中水溶性无机离子成分。结果表明:林内外PM_2.5的质量浓度平均值分别为(40.18±10.47)和(55.79±13.01) g/cm³;林内外TSP的质量浓度分别为(101.32 ± 33.19)和(116.61±35.36) g/cm³。林内与林外比,PM_2.5和TSP平均质量浓度都显著减少(P < 0.05),表明森林能显著改善空气环境质量。TSP和PM_2.5中SO₄^2-、Na⁺、NH₄⁺和NO₃^-为水溶性无机离子主要成分,占总离子质量的80%以上,林外这些离子的浓度高于林内(NH₄⁺除外)。这4种离子雨季在空气中的主要存在方式为NaCl、Na₂SO₄、NH₄HSO₄和NH₄NO₃。计算表明,采样期间海盐对大夫山空气TSP和PM_2.5的水溶性组分中Na⁺和Cl^-贡献最大,其它元素主要源自陆地源。林内外TSP和PM_2.5的c(NO₃^-)/c(SO₄^2-)比值在0.3以下,表明固定源是大夫山森林公园空气主要污染贡献者,TSP中c(NO₃^-)/c(SO₄^2-)的比值大于PM_2.5的比值,说明移动源对TSP的贡献大于PM_2.5。     

武汉市15种阔叶乔木滞尘能力与叶表微形态特征

以武汉市15种常见的阔叶乔木为研究对象,通过3级滤膜过滤法测定了各乔木单位叶面积滞留不同粒径颗粒物(TSP、PM_>10、PM₁₀、PM_2.5)的质量,并通过扫描电镜观察比较了15种乔木的叶表面微形态结构,分析了微形态对植物滞尘能力的影响。结果表明:15种乔木单位叶面积的滞尘量存在显著差异(P<0.05),综合滞尘能力最强的植物为二球悬铃木、桂花和石楠,除以上3者外,女贞和广玉兰分别具有较强的滞留PM₁₀和PM_2.5的能力;加杨滞留TSP和PM_>10的能力最弱,玉兰滞留PM₁₀和PM_2.5的能力最弱。各乔木单位叶面积滞留PM_2.5和PM₁₀的质量分别占总粉尘量的0.7%—8.9%和3.6%—33.9%。叶表面微结构观察表明,叶表面粗糙、褶皱较多,或被有蜡质层的植物有利于粉尘颗粒物的附着。相关性分析表明,植物单位叶面积的滞尘量与叶表面沟槽的宽度呈显著相关,...     

Short-Term Effects of Particulate Matter on Stroke Attack: Meta-Regression and Meta-Analyses

Background and Purpose

Currently there are more and more studies on the association between short-term effects of exposure to particulate matter (PM) and the morbidity of stroke attack, but few have focused on stroke subtypes. The objective of this study is to assess the relationship between PM and stroke subtypes attack, which is uncertain now.

Methods

Meta-analyses, meta-regression and subgroup analyses were conducted to investigate the association between short-term effects of exposure to PM and the morbidity of different stroke subtypes from a number of epidemiologic studies (from 1997 to 2012).

Results

Nineteen articles were identified. Odds ratio (OR) of stroke attack associated with particular matter (“thoracic particles” [PM₁₀]<10 µm in aerodynamic diameter, “fine particles” [PM_2.5]<2.5 µm in aerodynamic diameter) increment of 10 µg/m³ was as effect size. PM₁₀ exposure was related to an increase in risk of stroke attack (OR per 10 µg/m³ = 1.004, 95%CI: 1.001∼1.008) and PM_2.5 exposure was not significantly associated with stroke attack (OR per 10 µg/m³ = 0.999, 95%CI: 0.994∼1.003). But when focused on stroke subtypes, PM_2.5 (OR per 10 µg/m³ = 1.025; 95%CI, 1.001∼1.049) and PM₁₀ (OR per 10 µg/m³ = 1.013; 95%CI, 1.001∼1.025) exposure were statistically significantly associated with an increased risk of ischemic stroke attack, while PM_2.5 (all the studies showed no significant association) and PM₁₀ (OR per 10 µg/m³ = 1.007; 95%CI, 0.992∼1.022) exposure were not associated with an increased risk of hemorrhagic stroke attack. Meta-regression found study design and area were two effective covariates.

Conclusion

PM_2.5 and PM₁₀ had different effects on different stroke subtypes. In the future, it''s worthwhile to study the effects of PM to ischemic stroke and hemorrhagic stroke, respectively.     

Air Pollution and Stillbirth Risk: Exposure to Airborne Particulate Matter during Pregnancy Is Associated with Fetal Death

Objective

To test the hypothesis that exposure to fine particulate air pollution (PM_2.5) is associated with stillbirth.

Study Design

Geo-spatial population-based cohort study using Ohio birth records (2006-2010) and local measures of PM_2.5, recorded by the EPA (2005-2010) via 57 monitoring stations across Ohio. Geographic coordinates of the mother’s residence for each birth were linked to the nearest PM_2.5 monitoring station and monthly exposure averages calculated. The association between stillbirth and increased PM_2.5 levels was estimated, with adjustment for maternal age, race, education level, quantity of prenatal care, smoking, and season of conception.

Results

There were 349,188 live births and 1,848 stillbirths of non-anomalous singletons (20-42 weeks) with residence ≤10 km of a monitor station in Ohio during the study period. The mean PM_2.5 level in Ohio was 13.3 μg/m³ [±1.8 SD, IQR(Q1: 12.1, Q3: 14.4, IQR: 2.3)], higher than the current EPA standard of 12 μg/m³. High average PM_2.5 exposure through pregnancy was not associated with a significant increase in stillbirth risk, _adjOR 1.21(95% CI 0.96,1.53), nor was it increased with high exposure in the 1^st or 2^nd trimester. However, exposure to high levels of PM_2.5 in the third trimester of pregnancy was associated with 42% increased stillbirth risk, _adjOR 1.42(1.06,1.91).

Conclusions

Exposure to high levels of fine particulate air pollution in the third trimester of pregnancy is associated with increased stillbirth risk. Although the risk increase associated with high PM_2.5 levels is modest, the potential impact on overall stillbirth rates could be robust as all pregnant women are potentially at risk.     

Production of Beauvericin, Moniliformin, Fusaproliferin, and Fumonisins B1, B2, and B3 by Fifteen Ex-Type Strains of Fusarium Species

Fifteen Fusarium species were analyzed by high-performance liquid chromatography for the production of six mycotoxins in corn grits cultures. Production of mycotoxins ranged from 66 to 2,500 μg/kg for fumonisin B₁, 0.6 to 1,500 μg/g for moniliformin, 2.2 to 720 μg/g for beauvericin, and 12 to 130 μg/g for fusaproliferin. Fumonisin B₂ (360 μg/kg) was produced by two species, fumonisin B₃ was not detected in any of the 15 species examined, and Fusarium bulbicola produced none of the six mycotoxins that we analyzed.