Long-term exposure to particulate matter, NO2 and the oxidative potential of particulates and diabetes prevalence in a large national health survey

Ambient air fine particulate matter (PM10 and PM2.5) and risk of type 2 diabetes mellitus and mechanisms of effects: a global systematic review and meta-analysis

Type 2 diabetes causes early mortality worldwide. Air pollution's relationship with T2DM has been studied. The association between them is unclear because of inconsistent outcomes. Studies on this topic have been published since 2019, but not thoroughly evaluated. We conducted a systematic review and meta-analysis using relevant data. The study protocol was registered in PROSPIRO and conducted according to MOOSE guidelines. In total, 4510 manuscripts were found. After screening, 46 studies were assessed using the OHAT tool. This meta-analysis evaluated fine particles with T2DM using OR and HR effect estimates. Evaluation of publication bias was conducted by Egger's test, Begg's test, and funnel plot analysis. A sensitivity analysis was conducted to evaluate the influence of several studies on the total estimations. Results show a significant association between PM2.5 and PM10 exposure and T2DM. Long-term exposure to fine air particles may increase the prevalence and incidence of T2DM. Fine air pollution increases the chance of developing T2DM mainly via systemic inflammation, oxidative stress, and endoplasmic reticulum stress.

Oxidative potential of particulate matter and its association to respiratory health endpoints in high-altitude cities in Bolivia

Exposure to particulate matter (PM) pollution is a significant health risk, driving the search for innovative metrics that more accurately reflect the potential harm to human health. Among these, oxidative potential (OP) has emerged as a promising health-based metric, yet its application and relevance across different environments remain to be further explored. This study, set in two high-altitude Bolivian cities, aims to identify the most significant sources of PM-induced oxidation in the lungs and assess the utility of OP in assessing PM health impacts. Utilizing two distinct assays, OPDTT and OPDCFH, we measured the OP of PM samples, while also examining the associations between PM mass, OP, and black carbon (BC) concentrations with hospital visits for acute respiratory infections (ARI) and pneumonia over a range of exposure lags (0-2 weeks) using a Poisson regression model adjusted for meteorological conditions. The analysis also leveraged Positive Matrix Factorization (PMF) to link these health outcomes to specific PM sources, building on a prior source apportionment study utilizing the same dataset. Our findings highlight anthropogenic combustion, particularly from traffic and biomass burning, as the primary contributors to OP in these urban sites. Significant correlations were observed between both OPDTT and PM2.5 concentration exposure and ARI hospital visits, alongside a notable association with pneumonia cases and OPDTT levels. Furthermore, PMF analysis demonstrated a clear link between traffic-related pollution and increased hospital admissions for respiratory issues, affirming the health impact of these sources. These results underscore the potential of OPDTT as a valuable metric for assessing the health risks associated with acute PM exposure, showcasing its broader application in environmental health studies.

Sources of acellular oxidative potential of water-soluble fine ambient particulate matter in the midwestern United States

Ambient fine particulate matter (PM2.5) is associated with numerous health complications, yet the specific PM2.5 chemical components and their emission sources contributing to these health outcomes are understudied. Our study analyzes the chemical composition of PM2.5 collected from five distinct locations at urban, roadside and rural environments in midwestern region of the United States, and associates them with five acellular oxidative potential (OP) endpoints of water-soluble PM2.5. Redox-active metals (i.e., Cu, Fe, and Mn) and carbonaceous species were correlated with most OP endpoints, suggesting their significant role in OP. We conducted a source apportionment analysis using positive matrix factorization (PMF) and found a strong disparity in the contribution of various emission sources to PM2.5 mass vs. OP. Regional secondary sources and combustion-related aerosols contributed significantly (> 75 % in total) to PM2.5 mass, but showed weaker contribution (43-69 %) to OP. Local sources such as parking emissions, industrial emissions, and agricultural activities, though accounting marginally to PM2.5 mass (< 10 % for each), significantly contributed to various OP endpoints (10-50 %). Our results demonstrate that the sources contributing to PM2.5 mass and health effects are not necessarily same, emphasizing the need for an improved air quality management strategy utilizing more health-relevant PM2.5 indicators.

Association between birth weight/joint exposure to ambient air pollutants and type 2 diabetes: a cohort study in the UK Biobank

Early life events and environmental factors are associated with type 2 diabetes (T2D) development. We assessed the combined effect of birth weight andambient air pollutants, and effect of their interaction on T2D risk. Totally, 6,474 T2D incidents were recorded over an 8.7-year follow-up period. The adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were 1.31 (1.26, 1.36) for each kilogram decrease in birth weight, and 1.08 (1.05, 1.11) for each standard deviation increase in air pollution score (APS). Birth weight<3000 g amplified the T2D risk associated with high APS. A combination of the lowest birth weight (<2500 g) and the highest quintile of APS led to over two-fold increase in T2D risk (aHR: 2.17; 95% CI: 1.79-2.64). There was a significant additive interaction between them. In conclusion, ambient air pollutants increase the risk for T2D, particularly in populations with low birth weight.

Inter-continental variability in the relationship of oxidative potential and cytotoxicity with PM2.5 mass

Most fine ambient particulate matter (PM2.5)-based epidemiological models use globalized concentration-response (CR) functions assuming that the toxicity of PM2.5 is solely mass-dependent without considering its chemical composition. Although oxidative potential (OP) has emerged as an alternate metric of PM2.5 toxicity, the association between PM2.5 mass and OP on a large spatial extent has not been investigated. In this study, we evaluate this relationship using 385 PM2.5 samples collected from 14 different sites across 4 different continents and using 5 different OP (and cytotoxicity) endpoints. Our results show that the relationship between PM2.5 mass vs. OP (and cytotoxicity) is largely non-linear due to significant differences in the intrinsic toxicity, resulting from a spatially heterogeneous chemical composition of PM2.5. These results emphasize the need to develop localized CR functions incorporating other measures of PM2.5 properties (e.g., OP) to better predict the PM2.5-attributed health burdens.

Associations between long-term exposure to air pollution, diabetes, and hypertension in metropolitan Iran: an ecologic study

Epidemiological studies on air pollution, diabetes, and hypertension conflict. This study examined air pollution, diabetes, and hypertension in adults in 11 metropolitan areas of Iran (2012-2016). Local environment departments and the Tehran Air Quality Control Company provided air quality data. The VIZIT website and Stepwise Approach to Chronic Disease Risk Factor Surveillance study delivered chronic disease data. Multiple logistic regression and generalized estimating equations evaluated air pollution-related diabetes and hypertension. In Isfahan, Ahvaz, and Tehran, PM2.5 was linked to diabetes. In all cities except Urmia, Yasuj, and Yazd, PM2.5 was statistically related to hypertension. O3 was connected to hypertension in Ahvaz, Tehran, and Shiraz, whereas NO2 was not. BMI and gender predict hypertension and diabetes. Diabetes, SBP, and total cholesterol were correlated. Iran's largest cities' poor air quality may promote diabetes and hypertension. PM2.5 impacts many cities' outcomes. Therefore, politicians and specialists have to control air pollution.

Key drivers of the oxidative potential of PM2.5 in Beijing in the context of air quality improvement from 2018 to 2022

The mass concentration of atmospheric particulate matter (PM) has been continuously decreasing in the Beijing-Tianjin-Hebei region. However, health endpoints do not exhibit a linear correlation with PM mass concentrations. Thus, it is urgent to clarify the prior toxicological components of PM to further improve air quality. In this study, we analyzed the long-term oxidative potential (OP) of water-soluble PM2.5, which is generally considered more effective in assessing hazardous exposure to PM in Beijing from 2018 to 2022 based on the dithiothreitol assay and identified the crucial drivers of the OP of PM2.5 based on online monitoring of air pollutants, receptor model, and random forest (RF) model. Our results indicate that dust, traffic, and biomass combustion are the main sources of the OP of PM2.5 in Beijing. The complex interactions of dust particles, black carbon, and gaseous pollutants (nitrogen dioxide and sulfur dioxide) are the main factors driving the OP evolution, in particular, leading to the abnormal rise of OP in Beijing in 2022. Our data shows that a higher OP is observed in winter and spring compared to summer and autumn. The diurnal variation of the OP is characterized by a declining trend from 0:00 to 14:00 and an increasing trend from 14:00 to 23:00. The spatial variation in OP of PM2.5 was observed as the OP in Beijing is lower than that in Shijiazhuang, while it is higher than that in Zhenjiang and Haikou, which is primarily influenced by the distribution of black carbon. Our results are of significance in identifying the key drivers influencing the OP of PM2.5 and provide new insights for advancing air quality improvement efforts with a focus on safeguarding human health in Beijing.

Exposure to PM2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China

Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.

A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023

Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.

Measuring magnetic susceptibility of particulate matter collected on filters

The magnetic susceptibility (κ) of particulate matter (PM) is a useful tool in estimation concentration of iron-rich particles and provides useful information on the emission sources and pathways of spread of PM in the atmosphere. However, there is currently no established protocol for measuring the magnetic susceptibility of PM collected on filters used in standard monitoring of PM concentration. This paper presents a step-by-step process for collecting PM on filters in automatic samplers and measuring their κ. The procedure outlines requirements for data quality, measurement uncertainty, exposure time and conditions, and the amount of material collected on the filters. The study analyzed a 2-year dataset of magnetic susceptibility measurements by MFK-1 kappabridge (Agico, Czech Republic) for PM10 and PM2.5 collected at two locations, Warsaw and Cracow, in Poland using low-volume PM samplers. By strictly following the procedure for conditioning filters, measuring magnetic susceptibility and mass of PM, the study found that it is possible to obtain repeatable data with good measurement accuracy and acceptable errors. This makes magnetic susceptibility an additional reliable parameter for tracking of emission sources of iron-rich particles. Successful implementation of this magnetic method as a standard procedure for monitoring PM in addition to the PM mass collected on filters could be used to analyze sources of emission of Fe-particles and their contribution to the PM mass, especially in urban and industrial environments.

Acute effects of air pollution on type II diabetes mellitus hospitalization in Lanzhou, China

Studies on the effects of short-term air pollution exposure on hospitalization for type 2 diabetes mellitus (T2DM) are relatively scarce in developing regions. The time-series study was used to explore the acute effects of air pollutants on hospitalization for T2DM in Lanzhou, China. A distribution lag nonlinear model based on the generalized additive model was used to analyze the hospitalization impact of air pollution on T2DM. Stratified analysis by gender, age and season was obtained. The results were indicated as the relative risk (RR) with 95% confidence interval (CI) for single-day lags (from lag0 to lag7) and cumulative lag days (from lag0-1 to lag0-7). The strongest correlations (RR, 95% CI) of hospitalization for T2DM and PM10 (RR = 1.003, 95% CI 1.000, 1.001) at lag7 and NO2 (RR = 1.022, 95% CI 1.000, 1.045) at lag0-4 were observed for an increase of 10 µg/m3 in the concentrations and CO (RR = 1.091, 95% CI 1.017, 1.170) at lag0-4 for an increase of 1 mg/m3 in the concentration. The hazardous impacts of PM10, NO2 and CO were greater for females, people aged ≥ 65 years and in the cold season. However, there was no significant association between PM2.5, SO2 and O38h and the number of hospitalizations for T2DM.

Metabolic pathways altered by air pollutant exposure in association with lipid profiles in young adults

Mounting evidence suggests that air pollution influences lipid metabolism and dyslipidemia. However, the metabolic mechanisms linking air pollutant exposure and altered lipid metabolism is not established. In year 2014-2018, we conducted a cross-sectional study on 136 young adults in southern California, and assessed lipid profiles (triglycerides, total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, very-low-density lipoprotein (VLDL)-cholesterol), and untargeted serum metabolomics using liquid chromatography-high-resolution mass spectrometry, and one-month and one-year averaged exposures to NO2, O3, PM2.5 and PM10 air pollutants at residential addresses. A metabolome-wide association analysis was conducted to identify metabolomic features associated with each air pollutant. Mummichog pathway enrichment analysis was used to assess altered metabolic pathways. Principal component analysis (PCA) was further conducted to summarize 35 metabolites with confirmed chemical identity. Lastly, linear regression models were used to analyze the associations of metabolomic PC scores with each air pollutant exposure and lipid profile outcome. In total, 9309 metabolomic features were extracted, with 3275 features significantly associated with exposure to one-month or one-year averaged NO2, O3, PM2.5 and PM10 (p < 0.05). Metabolic pathways associated with air pollutants included fatty acid, steroid hormone biosynthesis, tryptophan, and tyrosine metabolism. PCA of 35 metabolites identified three main PCs which together explained 44.4% of the variance, representing free fatty acids and oxidative byproducts, amino acids and organic acids. Linear regression indicated that the free fatty acids and oxidative byproducts-related PC score was associated with air pollutant exposure and outcomes of total cholesterol and LDL-cholesterol (p < 0.05). This study suggests that exposure to NO2, O3, PM2.5 and PM10 contributes to increased level of circulating free fatty acids, likely through increased adipose lipolysis, stress hormone and response to oxidative stress pathways. These alterations were associated with dysregulation of lipid profiles and potentially could contribute to dyslipidemia and other cardiometabolic disorders.

Transportation-related Environmental Mixtures and Diabetes Prevalence and Control in Urban/Metropolitan Counties in the United States

Diabetes rates in the United States are staggering and climbing. Importantly, traditional risk factors fail to completely account for the magnitude of the diabetes epidemic. Environmental exposures, including urban and metropolitan transportation quality, are implicated as contributors to disease. Using data from the county-level Environmental Quality Index (EQI) developed for the United States, we analyzed associations between transportation and air quality environmental metrics with overall diabetes prevalence and control within urban/metropolitan counties in the United States from 2006 to 2012. Additionally, we examined effect modification by race/ethnicity through stratification based on the county-level proportion of minority residents. Last, we applied mixture methods to evaluate the effect of simultaneous poor transportation factors and worse air quality on the same outcomes. We found that increased county-level particulate matter air pollution and nitrogen dioxide along with reduced public transportation usage and lower walkability were all associated with increased diabetes prevalence. The minority proportion of the population influences some of these relationships as some of the effects of air pollution and the transportation-related environment are worse among counties with more minority residents. Furthermore, the transportation and air quality mixtures were found to be associated with increased diabetes prevalence and reduced diabetes control. These data further support the burgeoning evidence that poor environments amplify diabetes risk. Future cohort studies should explore the utility of environmental policies and urban planning as tools for improving metabolic health.

Chemical composition, oxidative potential and identifying the sources of outdoor PM2.5 after the improvement of air quality in Beijing

Air pollution poses a serious threat to human health. The implementation of air pollution prevention and control policies has gradually reduced the level of atmospheric fine particles in Beijing. Exploring the latest characteristics of PM_2.5 has become the key to further improving pollution reduction measures. In the current study, outdoor PM_2.5 samples were collected in the spring and summer of Beijing, and the chemical species, oxidative potential (OP), and sources of PM_2.5 were characterized. The mean PM_2.5 concentration during the entire study period was 41.6 ± 30.9 μg m^-3. Although the PM_2.5 level in summer was lower, its OP level was significantly higher than that in spring. SO₄^2-, NH₄⁺, EC, NO^3-, and OC correlated well with volume-normalized OP (OP_v). Strong positive correlations were found between OP_v and the following elements: Cu, Pb, Zn, Ni, As, Cr, Sn, Cd, Al, and Mn. Seven sources of PM_2.5 were identified, including traffic, soil dust, secondary sulfate, coal and biomass burning, oil combustion, secondary nitrate, and industry. Multiple regression analysis indicated that coal and biomass combustion, industry, and traffic were the main contributors to the OP_v in spring, while secondary sulfate, oil combustion, and industry played a leading role in summer. The source region analysis revealed that different pollution sources were related to specific geographic distributions. In addition to local emission reduction policies, multi-provincial cooperation is necessary to further improve Beijing's air quality and reduce the adverse health effects of PM_2.5.

The oxidative potential of airborne particulate matter in two urban areas of Chile: More than meets the eye

Oxidative potential (OP) has gained attention as a parameter that can reveal the ability of different properties of particulate matter (PM) to generate reactive oxygen species (ROS) as one single value. Moreover, OP is also believed to be a predictor of toxicity and hence the health effects of PM. This study evaluated the OP of PM₁₀, PM_2.5,and PM_1.0samples using dithiothreitol assays in two cities of Chile (Santiago and Chillán). The results showed that the OP was different between cities, PM size fractions, and seasons. Additionally, OP was strongly correlated with certain metals and meteorological variables. Higher mass-normalized OP was observed during cold periods in Chillán and warm periods in Santiago and was associated with PM_2.5 and PM₁. On the other hand, volume-normalized OP was higher during winter in both cities and for PM₁₀. Additionally, we compared the OP values to the Air Quality Index (AQI) scale and found cases of days that were classified as having "good" air quality (supposed to be less harmful to health) showing extremely high OP values that were similar to those on days that were classified as "unhealthy". Based on these results,we suggest using the OP as a complementary measure to the PM mass concentration because it includes important new information related to PM properties and compositions that could help improvecurrent air quality management tools.

Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents

The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM_2.5 and NO₂) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM_2.5 and NO₂) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (OR_{per unit increase} = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.

How long-term air pollution and its metal constituents affect type 2 diabetes mellitus prevalence? Results from Wuhan Chronic Disease Cohort

BACKGROUND

Epidemiological evidence linking type 2 diabetes mellitus (T2DM) with air pollution is discrepant and most are restricted to the influences of air-pollutant mass concentration. This study aims to explore the effects of long-term exposure to air pollution and its metal constituents on T2DM prevalence in China.

METHODS

We used data on 10,253 adult residents from the baseline survey of Wuhan Chronic Disease Cohort in 2019. Ambient PM_2.5, PM₁₀ and NO₂ exposure were estimated at residences based on Chinese Air Quality Reanalysis Dataset. Concentrations of 10 metal constituents were measured by 976 PM_2.5 filter samples collected from four monitoring stations. Logistic regression models were employed to examine associations of T2DM prevalence with 3-year mean concentrations of each air pollutant and PM_2.5 metal constituents prior to the baseline investigation.

RESULTS

A total of 673 T2DM cases (6.6%) were identified. The 3-year mean exposures to PM_2.5, PM₁₀ and NO₂ were 50.89 μg/m³, 82.86 μg/m³, and 39.79 μg/m³, respectively. And interquartile range (IQR) of 10 metals in PM_2.5 varied from 0.03 ng/m³ to 78.30 ng/m³. For 1 μg/m³ increment in PM_2.5, PM₁₀ and NO₂, the odds of T2DM increased by 7.2% (95%CI: 1.026, 1.136), 3.1% (95%CI: 1.013, 1.050), and 2.1% (95%CI: 1.005, 1.038) after adjusting for potential confounders. Cd and Sb in PM_2.5 were significant risk factors to T2DM with odds ratios of 1.350 (95%CI: 1.089, 1.673) and 1.389 (95%CI: 1.164, 1.658) for per IQR increase, respectively. Stratification analyses indicated that males and those aged ≥45 years were more susceptive to long-term air pollution.

CONCLUSIONS

Long-term exposure to PM_2.5, PM₁₀ and NO₂ increased T2DM prevalence in a Wuhan population, especially for men and middle-aged and elderly people. Moreover, T2DM was significantly associated with Cd and Sb in PM_2.5. Further research to validate these results and to clarify the underlying mechanisms is warranted.

Association of long-term exposure to PM2.5 in workplace with fasting plasma glucose among asymptomatic adults: A multicenter study in North China

BACKGROUND

The impacts of long-term high exposure to PM2.5 in workplace on glucose metabolism in asymptomatic working adults (AWAs) have rarely been explored.

OBJECTIVES

To assess the relationship between long-term exposure to workplace PM2.5 and glucose metabolism in asymptomatic general working adults in heavily polluted regions.

METHODS

We used the baseline data of the asymptomatic working participants from the Beijing-Tianjin-Hebei Medical Examination Cohort, which recruited adults undergoing medical examinations. A machine learning-based spatial-temporal model was used to estimate daily average PM2.5 concentrations in the participants' workplaces. We assessed the association of long-term PM2.5 concentrations (three years prior to the interview) and fasting plasma glucose (FPG) using generalized linear mixed-effects models (GLMM) with inclusion of potential confounders. Stratified analyses by sex, age, BMI and smoking status, and two pollutant models were further performed.

RESULTS

A total of 37,619 individuals were interviewed and 28,865 were included in the analyses. The mean FPG was 5.20 (0.96) mmol/L, and the estimated three-year average concentration of PM2.5 exposure was 69.51 (6.92) μg/m3. We detected a significant association of long-term exposure to workplace PM2.5 and FPG, a 10 µg/m3 increase in the long-term workplace PM2.5 exposure was associated with 0.075 (95%CI: 0.050-0.100) mmol/L elevated FPG and 25% (OR = 1.25, 95%CI: 1.05-1.50) elevated odds of abnormal fasting glucose metabolism with control of the potential confounding. The detected association between workplace PM2.5 and FPG metabolism remained significant in males, individuals aged > 44 years, overweight and/or obese people, both smokers and non-smokers, and when NO2, SO2, O3, and CO were included in the model.

CONCLUSIONS

Long-term exposure to workplace PM2.5 was associated with elevated FPG and/or odds of abnormal glucose metabolism among AWAs. Male, middle-aged, overweight and/or obese AWAs were more susceptible to workplace PM2.5 regardless of smoking status.

A correlational analysis of COVID-19 incidence and mortality and urban determinants of vitamin D status across the London boroughs

One of the biggest challenges of the COVID-19 pandemic is the heterogeneity in disease severity exhibited amongst patients. Among multiple factors, latest studies suggest vitamin D deficiency and pre-existing health conditions to be major contributors to death from COVID-19. It is known that certain urban form attributes can impact sun exposure and vitamin D synthesis. Also, long-term exposure to air pollution can play an independent role in vitamin D deficiency. We conducted a correlational analysis of urban form and air quality in relation to the demographics and COVID-19 incidence and mortality across 32 London boroughs between March 2020 and January 2021. We found total population, number of residents of Asian ethnicity, 4-year average PM10 levels and road length to be positively correlated with COVID-19 cases and deaths. We also found percentage of households with access to total open space to be negatively correlated with COVID-19 deaths. Our findings link COVID-19 incidence and mortality across London with environmental variables linked to vitamin D status. Our study is entirely based on publicly available data and provides a reference framework for further research as more data are gathered and the syndemic dimension of COVID-19 becomes increasingly relevant in connection to health inequalities within large urban areas.

Contribution of Physical and Chemical Properties to Dithiothreitol-Measured Oxidative Potentials of Atmospheric Aerosol Particles at Urban and Rural Sites in Japan

Dithiothreitol-measured oxidative potential (OPDTT) can chemically quantify the adverse health effects of atmospheric aerosols. Some chemical species are characterized with DTT activities, and the particle diameter and surface area control DTT oxidizability; however, the physical contribution to OPDTT by atmospheric aerosols is controversial. Therefore, we performed field observations and aerosol sampling at urban and rural sites in Japan to investigate the effect of both physical and chemical properties on the variation in OPDTT of atmospheric aerosols. The shifting degree of the representative diameter to the ultrafine range (i.e., the predominance degree of ultrafine particles) was retrieved from the ratio between the lung-deposited surface area and mass concentrations. The chemical components and OPDTT were also elucidated. We discerned strong positive correlations of K, Mn, Pb, NH4+, SO42−, and pyrolyzable organic carbon with OPDTT. Hence, anthropogenic combustion, the iron–steel industry, and secondary organic aerosols were the major emission sources governing OPDTT variations. The increased specific surface area did not lead to the increase in the OPDTT of atmospheric aerosols, despite the existing relevance of the surface area of water-insoluble particles to DTT oxidizability. Overall, the OPDTT of atmospheric aerosols can be estimated by the mass of chemical components related to OPDTT variation, owing to numerous factors controlling DTT oxidizability (e.g., strong contribution of water-soluble particles). Our findings can be used to estimate OPDTT via several physicochemical parameters without its direct measurement.

COVID-19 lockdown and environmental pollution: an Indian multi-state investigation

Originating from China, COVID-19 became the first-ever coronavirus pandemic, wreaking havoc in 218 nations. The lack of a potential treatment exacerbated by the inability of the healthcare infrastructure to contain the viral trajectory led to a worldwide lockdown. The anthropogenic halt presented an unprecedented background to quantify the effect of the anthroposphere on environmental pollution. Consequently, we analyzed the variations in the air (PM₁₀, PM_2.5, NO₂, SO₂) and water pollutants (BOD, COD, DO, coliform) using real-time monitoring data in the majorly hit Indian metropolitan states during the lockdown in contrast to 2019 levels. The overall AQI (air quality index) de-escalated by -31.35%, -34.35%, -32.63%, -29.25% in Delhi, Tamil Nadu, West Bengal, and Karnataka, respectively, from the 2019 levels. The daily concentrations of NO₂, PM_2.5, and PM₁₀ plunged tremendously. The exact pre-disposing factors responsible for higher COVID-19 transmission in some geographical centers remain elusive. Investigations have corroborated putative links between air pollutants and COVID-19 mortalities. Therefore, we further mapped PM_2.5, PM₁₀, NO₂, and SO₂ to co-relate with COVID-19 infectivity and mortality across the study states. Significant (P < 0.001) positive correlation between COVID-19 transmission was established for all pollutants with maximum co-relation with AQI followed by NO₂. River Ganga water in Uttarakhand was deemed "fit for drinking" for the first time in two decades. An aggregate of -71.94, -61.32, and -77.94 decrease in BOD, COD, total coliform levels, and an 11.75 rise in the average DO levels from 2019 data. This study will better assist the future framework of health and environment restoration policies.

The effect of adjustment to register-based and questionnaire-based covariates on the association between air pollution and cardiometabolic disease

OBJECTIVE

Recent studies on air pollution and disease have been based on millions of participants within a region or country, relying entirely on register-based confounder adjustment. We aimed to investigate the effects of increasing adjustment for register- and questionnaire-based covariates on the association between air pollution and cardiometabolic diseases.

METHODS

In a population-based cohort of 246,766 eligible participants randomly selected across Denmark in 2010 and 2013 and followed up until December 31, 2017, we identified 3,247 myocardial infarction (MI) cases, 4,166 stroke cases and 6,366 type 2 diabetes cases. Based on historical address-information, we calculated 5-year time-weighted exposure to PM_2.5 and NO₂ modelled using a validated air pollution model. We used Cox proportional hazards models to calculate hazard ratios (HR) with increasing adjustment for a number of individual- and area-level register-based covariates as well as lifestyle covariates assessed through questionnaires.

RESULTS

We found that a 5 μg/m³ higher PM_2.5 was associated with HRs (95% CI) for MI, stroke and diabetes, of respectively, 1.18 (0.91-1.52), 1.11 (0.88-1.40) and 1.24 (1.03-1.50) in the fully adjusted models. For all three diseases, adjustment for either individual-level, area-level or lifestyle covariates, or combinations of these resulted in higher HRs compared to HRs adjusted only for age, sex and calendar-year, most marked for MI and diabetes. Further adjustment for lifestyle in models with full register-based individual- and area-level adjustment resulted in only minor changes in HRs for all three diseases.

CONCLUSIONS

Our findings suggest that in studies of air pollution and cardiometabolic disease, which use an adjustment strategy with a broad range of register-based socioeconomic variables, there is no effect on risk estimates from subsequent lifestyle adjustment.

The Risk of Hearing Impairment From Ambient Air Pollution and the Moderating Effect of a Healthy Diet: Findings From the United Kingdom Biobank

The link between hearing impairment and air pollution has not been established, and the moderating effect of a healthy diet has never been investigated before. The purpose of this study was to investigate the association between air pollution and hearing impairment in British adults aged 37-73 years, and whether the association was modified by a healthy diet. We performed a cross-sectional population-based study with 158,811 participants who provided data from United Kingdom Biobank. A multivariate logistic regression model was used to investigate the link between air pollution and hearing impairment. Subgroup and effect modification analyses were carried out according to healthy diet scores, gender, and age. In the fully adjusted model, we found that exposure to PM₁₀, NO_X, and NO₂ was associated with hearing impairment [PM₁₀: odds ratio (OR) = 1.15, 95% confidence interval (95% CI) 1.02-1.30, P = 0.023; NO_X: OR = 1.02, 95% CI 1.00-1.03, P = 0.040; NO₂: OR = 1.03, 95% CI 1.01-1.06, P = 0.044], while PM_2.5 and PM_2.5 absorbance did not show similar associations. We discovered an interactive effect of age and air pollution on hearing impairment, but a healthy diet did not. The findings suggested that exposure to PM₁₀, NO_X and NO₂ was linked to hearing impairment in British adults, whereas PM_2.5 and PM_2.5 absorbance did not show similar associations. These may help researchers focus more on the impact of air pollution on hearing impairment and provide a basis for developing effective prevention strategies.

Associations between the fast-food environment and diabetes prevalence in the Netherlands: a cross-sectional study

BACKGROUND

Diabetes is a major health concern and is influenced by lifestyle, which can be affected by the neighbourhood environment. Specifically, a fast-food environment can influence eating behaviours and thus diabetes prevalence. Therefore, our aim was to assess the relationship between fast-food environment and diabetes prevalence for urban and rural environments in the Netherlands, using multiple indicators and buffer sizes.

METHODS

In this cross-sectional study, data on a nationwide sample of adults older than 19 years in the Netherlands were taken from the 2012 Dutch national health survey (from Public Health Monitor), in which participants were surveyed on topics related to health and lifestyle behaviour. Fast-food outlet exposures were determined within street-network buffers of 100 m, 400 m, 1000 m, and 1500 m around residential addresses. For each of these buffers, three indicators were calculated: presence (yes or no) of fast-food outlets, fast-food outlet density, and ratio. Logistic regression analyses were carried out to assess associations of these indicators with diabetes, adjusting for potential confounders and stratifying into urban and rural areas.

FINDINGS

387 195 adults were surveyed, 284 793 of whom were included in the study. 22 951 (8%) reported having diabetes. Fast-food outlet exposures were positively associated with diabetes prevalence. We did not observe large differences between urban and rural areas. The effect estimates were small for all indicators. For example, in the 400 m buffer in the urban environment, the odds ratio (OR) for having diabetes among people with a fast-food outlet present compared with those without, was 1·006 (95% CI 1·003-1·009) using the presence indicator. The presence indicator showed higher effect estimates and the most consistent results across buffer sizes (ranging from OR 1·005 [95% CI 1·000-1·010] with the 1000 m buffer to 1·016 [1·005-1·028] with the 1500 m buffer in urban areas and from 1·002 [0·998-1·005] with the 1500 m buffer to 1·009 [1·006-1·018] with the 100 m buffer in rural areas) compared with the density and ratio indicators.

INTERPRETATION

The results confirm the evidence that the fast-food outlet environment is a diabetes risk factor. All data included were at the individual level and the variability was ensured by the spatial distribution and number of participants. In this study, we only accounted for residential exposure because we were unable to account for exposure outside the residential environment. The findings of this study encourage local governments to consider the potential adverse effects of fast-food exposures and aim at minimising unhealthy food access.

FUNDING

Global Geo Health Data Centre, Utrecht University, Netherlands.

Investigating the association between long-term exposure to air pollution and greenness with mortality from neurological, cardio-metabolic and chronic obstructive pulmonary diseases in Greece

Long-term exposure to air pollution has been associated with increased natural-cause mortality, but the evidence on diagnoses-specific mortality outcomes is limited. Few studies have examined the potential synergistic effects of exposure to pollutants and greenness. We investigated the association between exposure to air pollution and greenness with nervous system related mortality, cardiometabolic and chronic obstructive pulmonary diseases (COPD) mortality in Greece, using an ecological study design. We collected socioeconomic and mortality data for 1035 municipal units from the 2011 Census. Annual PM_2.5, NO₂, BC and O₃ concentrations for 2010 were predicted at 100 × 100 m grids by hybrid land use regression models. The normalized difference vegetation index (NDVI) was used for greenness. We applied single and two-exposure Poisson regression models on standardized mortality rates accounting for spatial autocorrelation. We assessed interactions between pollutants and greenness. An interquartile range increase in PM_2.5, NO₂ and BC was associated with increased risk in mortality from diseases of the nervous system (relative risk (RR): 1.14, 95% confidence interval (CI): 1.01, 1.28); 1.03 (95% CI: 0.99, 1.07); 1.05 (95% CI: 1.00, 1.10) respectively) and from cerebrovascular disease (RR: 1.14, 95% CI: 1.10, 1.18); 1.02 (95% CI: 1.01, 1.04); 1.02 (95% CI: 1.00, 1.04) respectively). PM_2.5 was associated with ischemic heart disease mortality (RR: 1.05, 95% CI: 1.01, 1.10). We estimated inverse associations for all outcomes with O₃ and for mortality from diseases of the nervous system or COPD with greenness. Estimates were mostly robust to co-exposure adjustment. Interactions were identified between NDVI and O₃ or PM_2.5 on mortality from the diseases of the nervous system, with higher effect estimates in greener areas. Our findings support the adverse effects of air pollution and the beneficial role of greenness on cardiovascular and nervous system related mortality. Further research is needed on diabetes mellitus.

PM2.5 exposure as a risk factor for type 2 diabetes mellitus in the Mexico City metropolitan area

BACKGROUND

Exposure to air pollution is the main risk factor for morbidity and mortality in the world. Exposure to particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5) is associated with cardiovascular and respiratory conditions, as well as with lung cancer, and there is evidence to suggest that it is also associated with type II diabetes (DM). The Mexico City Metropolitan Area (MCMA) is home to more than 20 million people, where PM2.5 levels exceed national and international standards every day. Likewise, DM represents a growing public health problem with prevalence around 12%. In this study, the objective was to evaluate the association between exposure to PM2.5 and DM in adults living in the MCMA.

METHODS

Data from the 2006 or 2012 National Health and Nutrition Surveys (ENSANUT) were used to identify subjects with DM and year of diagnosis. We estimated PM2.5 exposure at a residence level, based on information from the air quality monitoring system (monitors), as well as satellite measurements (satellite). We analyzed the relationship through a cross-sectional approach and as a case - control study.

RESULTS

For every 10 μg/m3 increase of PM2.5 we found an OR = 3.09 (95% CI 1.17-8.15) in the 2012 sample. These results were not conclusive for the 2006 data or for the case - control approach.

CONCLUSIONS

Our results add to the evidence linking PM2.5 exposure to DM in Mexican adults. Studies in low- and middle-income countries, where PM2.5 atmospheric concentrations exceed WHO standards, are required to strengthen the evidence.

Atmospheric NO2 Distribution Characteristics and Influencing Factors in Yangtze River Economic Belt: Analysis of the NO2 Product of TROPOMI/Sentinel-5P

Nitrogen dioxide (NO2) has a great influence on atmospheric chemistry. Scientifically identifying the temporal-spatial characteristics of NO2 distribution and their driving factors will be of realistic significance to atmospheric governance in the Yangtze River Economic Belt (YREB). Based on the NO2 data derived from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 satellite (2017~present), spatial autocorrelation analysis, standard deviation ellipse (SDE), and geodetectors were used to systematically analyze the spatial-temporal evolution and driving factors of tropospheric NO2 vertical column density (NO2 VCD) in the YREB from 2019 to 2020. The results showed that the NO2 VCD in the YREB was high in winter and autumn and low in spring and summer (temporal distribution), and high in the northeast and low in the southwest (spatial distribution), with significant spatial agglomeration. High-value agglomeration zones were collectively and stably distributed in the east region, while low-value zones were relatively dispersed. The explanatory power of each potential factor for the NO2 VCD showed regional and seasonal variations. Surface pressure was found to be a core influencing factor. Synergistic effects of factors presented bivariate enhancement or nonlinear enhancement, and interaction between any two factors strengthened the explanatory power of a single factor for the NO2 VCD.

How do air pollution and meteorological parameters contribute to the spread of COVID-19 in Saudi Arabia?

The current global health crisis is unprecedented in modern times. It has killed numerous people, caused great suffering, and turned many people's lives upside down. This study seeks to investigate the role of some pollutants and the meteorological parameters in the transmission of the virus (SARS-CoV-2). The number of infections identified in Saudi Arabia, a country with a hot climate, was studied for a period between March 9, 2020 and November 19, 2020, which was characterized by a single wave with a peak of 4,919 cases on June 17, 2020. Based on count data models, we observed that air pollution and meteorological parameters considerably influenced the daily evolution of infections in most affected cities of Saudi Arabia (Riyadh, Jeddah, and Makkah) where the prevalence of the disease was relatively high during summer 2020. Our study suggests that air pollution could be a significant risk factor for respiratory infections and virus transmission. On the other hand, meteorological factors and high concentration of air pollutants should be taken into account by public decision-makers in Saudi Arabia when seeking to limit COVID-19 transmission.

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

BACKGROUND

Air 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 FINDINGS

A 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 (PM2.5), between 2.5 μm and 10 μm (PM2.5-10), 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.

CONCLUSIONS

We found that various air pollutants PM2.5, PM2.5-10, NO2, 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.

Assessment of long-range oriented source and oxidative potential on the South-west shoreline, Korea: Molecular marker receptor models during shipborne measurements

In order to determine the quantitative contributions of PM_2.5 on the South-west shoreline of Korea, filter based samplings were conducted in the summertime of 2017 and 2018 (total 32 days) via shipborne measurements using both a high volume and middle volume air sampler. Water-soluble organic carbon, water-soluble ions, organic carbon and elemental carbon, elemental species, and organic molecular markers by Liquid Chromatography-tandem Mass Spectrometry were utilized to characterize the collected substrates. The current study investigates the (1) chemical characteristics of PM_2.5, (2) source apportionment using positive matrix factorization (PMF), and (3) relationship between sources and the dithiothreitol (DTT) assay during the two sampling periods. A mean PM_2.5 concentration of 19.3 μg/m³ was observed along the entire sampling route. The ratio of water-soluble to organic carbon implies that secondary aerosol formation is dominant. The result of methanesulfonic acid (MSA) suggests the contribution of a marine-oriented biogenic source of PM_2.5. The PMF source apportionment model showed six source categories with reasonably stable profiles: 1) sulfate-rich, 2) MSA-rich, 3) nitrate-rich, 4) secondary organic, 5) continental, and 6) biomass burning sources. The PMF showed three strong events (i.e., long-range transport, mixed (ocean and long-range stay), and domestic origin events) in the contributions of sources, as well as a dependence on wind transport. Higher associations with DTT oxidative potential normalized to PM_2.5 mass concentration (DTT-OP_m) related to long-range transport, hence, confirming the impacts of the highest intrinsic oxidative potential.

Biological treatments of mercury and nitrogen oxides in flue gas: biochemical foundations, technological potentials, and recent advances

Nitrogen oxides (NO_x) and mercury (Hg) are commonly found coexistent pollutants in combustion flue gas. Ever-increasing emission of atmospheric Hg and NO_x has caused considerable environmental risks. Traditional flue gas demercuration and denitration techniques have many socioeconomic, technological and environmental drawbacks. Biotechnologies can be a promising and prospective alternative strategy. This article discusses theoretical foundation (biochemistry and genomic basis) and technical potentials (Hg⁰ bio-oxidation coupled to denitrification) of bioremoval of Hg and NO_x in flue gas and summarized recent experimental and technological advances. Finally, several specific technical perspectives have been put forward to better guide future researches.

Effects of ambient temperature and cold starts on excess NOx emissions in a gasoline direct injection vehicle

Studies have demonstrated that vehicles with gasoline direct injection (GDI) engines produce significantly higher emissions during a cold start than under hot-stabilized periods. A cold start is typically defined by the temperature of the engine or the catalytic converter; its extended effect on emissions, after the vehicle reaches the warm-up stage, has seldom been investigated. In this study, the influence of the post cold start period on nitrogen oxides (NO_x) emissions was evaluated using real-world measurements. Vehicle on-board diagnostic data, fuel consumption, and emissions of multiple pollutants were collected on a 2020 GDI sports utility vehicle equipped with a Portable Emission Measurement System (PEMS). A total of 31 trips, with two drives per day, were conducted along arterial roads and highways in Toronto, Canada. The results indicate that during the first trip of the day after an overnight soak, the average NO_x emission rate was 0.27 g/litre and 0.037 g/km, 384% and 299% higher than the emission rate on the second trip of the day. The amount of trip total NO_x emissions is positively associated with the length of the catalytic converter warm-up period with correlation coefficient 0.67. We also observe that the catalyst warm-up time is negatively correlated with ambient temperature, and a negative relationship between ambient temperature and NO_x emissions throughout the trip is depicted with correlation coefficient -0.44. The measured data reveal an extended effect of the cold start on NO_x emissions even after the temperatures of the engine coolant and catalyst reach a stable level.

Analysis of lockdown for CoViD-19 impact on NO2 in London, Milan and Paris: What lesson can be learnt?

Nitrogen dioxide (NO₂) can have harmful effects on human health and can act as a precursor for the formation of other air pollutants in urban environment such as secondary PM_2.5 and ozone. The lockdown measures for CoViD-19 allowed to simulate on a large scale the massive and prolonged reduction of road traffic (the main source for NO₂ in urban environment). This work aims to selectively assess the maximum impact that total traffic blocking measures can have on NO₂. For this reason, three megacities (London, Milan and Paris) were chosen which had similar characteristics in terms of climatic conditions, population, policies of urban traffic management and lockdown measures. 52 air quality control units have been used to compare data measured in lockdown and in the same periods of previous years, highlighting a significant decrease in NO₂ concentration due to traffic (London: 71.1 % - 80.8 %; Milan: 8.6 % - 42.4 %; Paris: 65.7 % - 79.8 %). In 2020 the contribution of traffic in London, Milan and Paris dropped to 3.3 ± 1.3 μg m^-3, 6.1 ± 0.8 μg m^-3, and 13.4 ± 1.5 μg m^-3, respectively. Despite the significant reduction in the NO₂ concentration, in UT stations average NO₂ concentrations higher than 40 μg m^-3 were registered for several days. In order to reduce the pollution, the limitation of road traffic could be not enough, but a vision also aimed at rethink the vehicles and their polluting effects should be developed.

Links between air pollution and COVID-19 in England

In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People's Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM_2.5 was a major contributor to COVID-19 cases in England, as an increase of 1 m³ in the long-term average of PM_2.5 was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic.

Links between air pollution and COVID-19 in England

In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People's Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM2.5 was a major contributor to COVID-19 cases in England, as an increase of 1 m3 in the long-term average of PM2.5 was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic.

Long-term characteristics of criteria air pollutants in megacities of Harbin-Changchun megalopolis, Northeast China: Spatiotemporal variations, source analysis, and meteorological effects

The hourly concentration of six criteria air pollutants in the Harbin-Changchun region were used to investigate the status and spatiotemporal variation of target air pollutants and their relationships with meteorological factors. The annual concentrations of particulate matters during 2013-2017 were two times higher than the Chinese Ambient Air Quality Standards (CAAQS) Grade Ⅱ. The annual O₃ concentration increased by two times during 2013-2018 in Harbin. The concentration of PM, SO₂, NO₂, and CO depicted a similar seasonal trend with an order of winter > autumn > spring > summer. The consistent interannual variation trends of PM_2.5/CO, NO₂ and SO₂ indicated that the formation of secondary inorganic aerosols in the annual scale was dominated by the concentrations of NO₂ and SO₂. The interannual variations of the individual meteorological factors causing on PM_2.5 and O₃ during 2013-2018 varied significantly in seasonal scale. The interannual variations were stable in annual scale indicating that the continuous decline of PM_2.5 during 2014-2018 can be attributed to the comprehensive and strict prohibition of small coal-fired boilers and straw burning in the study area. Meanwhile, the increase in O₃ during 2013-2018 in the study area were mainly attributed to the rapid growth of the emission of its precursor (VOCs and NOx). The influence of meteorology on PM_2.5 and ozone were the most stable and strongest in winter than that in the other three seasons.

A Bimodal Protein Fabric Enabled via In Situ Diffusion for High-Performance Air Filtration

Design and fabrication of bimodal structures are essential for successful development of advanced air filters with ultralow airflow resistance. To realize this goal, simplified processing procedures are necessary for meeting the practical needs. Here, a bimodal protein fabric with high-performance air filtration, and effectively lowered airflow resistance is reported. The various functional groups of proteins provide versatile interactions with pollutants. By utilizing a novel and cost-effective "cross-axial" configuration with an optimized condition (75° of contacting angle between solution nozzle and cospinning solvent nozzle), the diffusion in Taylor cone is in situ controlled, which results in the successful production of bimodal protein fabric. The bimodal protein fabric (16.7 g/m² areal density) is demonstrated to show excellent filtration performance for removing particulate matter (PM) pollutants and only causes 17.1 Pa air pressure drop. The study of multilayered protein fabric air filters shows a further improvement in filtration performance of removing 97% of PM_0.3 and 99% of PM_2.5 with a low airflow resistance (34.9 Pa). More importantly, the four-layered bimodal protein fabric shows an exceptional long-term performance and maintains a high removal efficiency in the humid environment. This study presents an effective and viable strategy for fabricating bimodal fibrous materials for advanced air filtration.

Association between ambient particulate matter (PM10) and incidence of diabetes in northwest of China: A prospective cohort study

OBJECTIVES

We aimed to assess the association between long-term exposure to ambient PM₁₀ and risk of diabetes incidence, based on the "Jinchang Cohort" platform in the Northwest of China.

METHODS

We selected 19884 subjects who had not yet developed diabetes in the baseline and had completed survey information from "Jinchang Cohort". The residential address was used to match the nearest pollution monitoring station for each subject, and the average concentration of PM₁₀ from baseline to follow-up were used as an estimate of individual exposure level. Cox regression model and restricted cubic splines functions were used to evaluate the effects of PM₁₀ on the incidence of diabetes and the dose-response relationship after adjusting for confounding covariates.

RESULTS

We observed 791 new-onset diabetics with a total follow-up of 45254.16 person-years (incidence rate of 17.48 per 1000 person-years). The risk of diabetes incidence increased by 17% (HR = 1.17, 95%CI: 1.08-1.26) per 10μg/m³ increase in environmental PM₁₀, and the risk rises gradually with the rise of PM₁₀ concentration. Comparing with the first quartile of PM₁₀, the fully adjusted HRs (95%CI) for incident diabetes from the second to the fourth quartile of PM₁₀ were 1.15 (95%CI: 0.93-1.43), 1.50 (95%CI: 1.22-1.84) and 1.44 (95%CI: 1.15-1.79), respectively (P for trend<0.001). Stratified analyses suggested that the risk of diabetes incidence associated with ambient PM₁₀ was higher in female, young to middle-aged people, overweight and obese subjects, and subjects with FPG level at baseline lower than 5.6 mmol/L.

CONCLUSIONS

Long-term exposure to ambient PM₁₀ significantly associated with a higher risk of diabetes development. Some urgent strategies may be advocated to reduce air pollution that can aid in preventing the prevalence of diabetes in the population.

A Global Analysis of Associations between Fine Particle Air Pollution and Cardiovascular Risk Factors: Feasibility Study on Data Linkage

Background

This paper presents a feasibility study of data linkage between global air pollution data and clinical medical data to assess the associations of PM2.5 with cardiovascular risk factors.

Methods

Cardiovascular risk factor data were obtained from the SUrvey of Risk Factors (SURF) for coronary heart disease (CHD) patients from 10 countries in Europe, Asia, and the Middle-East. Annual average PM2.5 concentrations were estimated using recent global WHO PM2.5 maps combining satellite and surface monitoring data for the location of the 71 participating centers. Associations of PM2.5 with risk factors were assessed by mixed-effect generalized estimation equation models adjusted by sex, age, exercise, body mass index, and smoking. In the final model there was further adjustment for country.

Results

Linkage between cardiovascular risk factor data and PM2.5 via the postal address of participating hospitals was shown to be feasible, however with several limitations noted.Eight thousand three hundred and ninety two patients (30% women) were included. Globally, an increase of 10 μg/m3 in PM2.5 was significantly associated with decreased BP and increased glucose. After controlling for country, an increase of 10 μg/m3 in PM2.5 was associated with decreased BP and increased LDL (SBP: -0.45 mmHg [95% CI: -0.85, -0.06]; DBP: -0.47 mmHg [-0.73, -0.20]; LDL: 0.04 mmol/L [0.01, 0.08]). The association with glucose attenuated (0.08 mmol/L [-0.23, 0.16]).

Conclusion

It is feasible to link PM2.5 and cardiovascular risk factors but it is still challenging to interpret these observed associations due to unavailability of potential confounders. After country adjustment, PM2.5 was associated with small increases in LDL and small decreases in BP.

Highlights

- There are limited studies on the association between air pollution and cardiovascular risk factors for patients with established coronary heart disease in low- and middle-income countries;- Data linkage is an efficient and cost-effective method to maximize the use of existing data to investigate more health related research questions;- It is feasible to determine global associations of air pollution and cardiovascular risk factors by data linkage but it is still challenging in terms of interpretation.

Effects of Ultrafine Particles in Ambient Air on Primary Health Care Consultations for Diabetes in Children and Elderly Population in Ljubljana, Slovenia: A 5-Year Time-Trend Study

Epidemiological studies indicate that exposure to ultrafine particles (UFP) in ambient air represents an important environmental public health issue. The aim of this study was to determine the association between UFP in ambient air and the daily number of consultations in the primary health care unit due to diabetes mellitus in children and elderly population of the Municipality of Ljubljana. A 5-year time-trend ecological study was carried out for the period between 1 January 2013 and 31 December 2017. The daily number of primary health care consultations due to diabetes mellitus among children and elderly population was observed as the health outcome. Daily mean UFP concentrations (different size from 10 to 100 nm) were measured and calculated. Poisson regression analysis was used to investigate the association between the observed outcome and the daily UFP, particulate matter fine fraction (PM_2.5), and particulate matter coarse fraction (PM₁₀) concentrations, adjusted to other covariates. The results show that the daily number of consultations due to diabetes mellitus were highly significantly associated with the daily concentrations of UFP (10 to 20 nm; p ≤ 0.001 and 20 to 30 nm; p ≤ 0.001) in all age groups and in the elderly population. In observed the population of children, we did not confirm the association. Findings indicate that specified environmental challenges should be addressed by comprehensive public health strategies leading to the coordinated cross-sectoral measures for the reduction of UFP in ambient air and the mitigation of adverse health effects.

Associations between the incidence and mortality rates of type 2 diabetes mellitus and long-term exposure to ambient air pollution: A 12-year cohort study in northern China

BACKGROUND

Ambient air pollution has recently been related to type 2 diabetes mellitus (T2DM), a disease that has caused an economic and health burden worldwide. Evidence of an association between air pollution and T2DM was reported in the United States and Europe. However, few studies have focused on the association with high levels of air pollutants in a developing country.

OBJECTIVES

We conducted a 12-year cohort study to assess the incidence and mortality of T2DM associated with long-term exposure to PM₁₀, SO₂, and NO₂.

METHODS

A retrospective cohort with participants from four cities in northern China was conducted to assess mortality and incidence of T2DM from 1998 to 2009. Incidence of T2DM was self-reported, and incident intake of an antidiabetic drug or injection of insulin simultaneously and mortality of T2DM was obtained from a family member and double checked against death certificates provided from the local center for disease control and prevention. Individual pollution exposures were the mean concentrations of pollutants estimated from the local environmental monitoring centers over the survival years. Hazard ratios (HRs) were estimated using Cox regression models after adjusting for potential confounding factors.

RESULTS

A total of 39 054 participants were recruited into the mortality cohort, among which 59 subjects died from T2DM; 38 529 participants were analyzed in the incidence cohort, and 1213 developed new cases of T2DM. For each 10 μg/m³ increase in PM₁₀, SO₂, and NO₂, the adjusted HRs and 95% confidence interval (CI) for diabetic incidence were 1.831 (1.778, 1.886), 1.287 (1.256, 1.318), and 1.472 (1.419, 1.528), respectively. Similar results can be observed in the analysis of diabetic mortality with HRs (95% CI) up to 2.260 (1.732, 2.950), 1.130 (1.042, 1.225), and 1.525 (1.280, 1.816), respectively.

CONCLUSIONS

Our results suggested that long-term exposure to high levels of PM₁₀, SO₂, and NO₂ increase risk of incident and mortality of T2DM in China.

Elevated NO2 damages the photosynthetic apparatus by inducing the accumulation of superoxide anions and peroxynitrite in tobacco seedling leaves

This study aimed to further understand the toxicity of high concentrations of nitrogen dioxide (NO2) to plants, especially to plant photosynthesis. Tobacco plants in the six-leaf stage were exposed to 16.0 μL L-1 NO2 to determine the activities of photosystem II (PSII) and photosystem I (PSI) reaction centers, the blocking site of PSII electron transport, the degree of membrane peroxidation and the relative expression of PsbA, PsbO and PsaA genes in the third fully expanded leaves by using gas exchange and chlorophyll fluorescence techniques, biochemical and RT-PCR analysis. The results showed that 16.0 μL L-1 NO2 caused necrotic lesions to form on leaves and significantly increased the generation rate of superoxide anions (O2-) and the content of peroxynitrite (ONOO-) in leaves of tobacco seedling, leading to damage to cell membrane, chlorophyll content and net photosynthetic rate reduction, and photosynthetic apparatus destruction. Fumigation with 16.0 μL L-1 NO2 decreased the activity of PSII reaction center and oxygen evolution complex, and the relative expression of PabA in leaves of tobacco seedlings to inhibit the electron transport from the donor side to the receptor side of PSII, especially blocking the electron transport from QA to QB on the receptor side. The activity of the PSI reaction center and the relative expression of PsaA decreased, weakening the ability to accept electrons and inhibiting the electron transfer from PSII to PSI, which further increased the damage of PSII of tobacco seedling leaves caused by 16.0 μL L-1 NO2. Therefore, 16.0 μL L-1 NO2 leaded to the accumulation of O2- and ONOO-, which damaged the cell membrane and thylakoid membrane, inhibit the electron transport, and destroyed the photosynthetic apparatus in leaves of tobacco seedlings. The results from this study emphasized the importance of reducing the NO2 concentration in the atmosphere.

Connecting Air Quality with Emotional Well-Being and Neighborhood Infrastructure in a US City

Cities in the United States have announced initiatives to become more sustainable, healthy, resilient, livable, and environmentally friendly. However, indicators for measuring all outcomes related to these targets and the synergies between them have not been well defined or studied. One such relationship is the linkage between air quality with emotional well-being (EWB) and neighborhood infrastructure. Here, regulatory monitoring, low-cost sensors (LCSs), and air quality modeling were combined to assess exposures to PM2.5 and traffic-related NOx in 6 Minneapolis, MN, neighborhoods of varying infrastructure parameters (median household income, urban vs suburban, and access to light rail). Residents of the study neighborhoods concurrently took real-time EWB assessments using a smart phone application, Daynamica, to gauge happiness, tiredness, stress, sadness, and pain. Both LCS PM2.5 observations and mobile-source-simulated NOx were calibrated using regulatory observations in Minneapolis. No statistically significant (α = 0.05) PM2.5 differences were found between urban poor and urban middle-income neighborhoods, but average mobile-source NOx was statistically significantly (α = 0.05) higher in the 4 urban neighborhoods than in the 2 suburban neighborhoods. Close proximity to light rail had no observable impact on average observed PM2.5 or simulated mobile-source NOx. Home-based exposure assessments found that PM2.5 was negatively correlated with positive emotions such as happiness and to net affect (the sum of positive and negative emotion scores) and positively correlated (ie, a higher PM2.5 concentration led to higher scores) for negative emotions such as tiredness, stress, sadness, and pain. Simulated mobile-source NOx, assessed from both home-based exposures and in situ exposures, had a near-zero relationship with all EWB indicators. This was attributed to low NOx levels throughout the study neighborhoods and at locations were the EWB-assessed activities took place, both owing to low on-road mobile-source NOx impacts. Although none of the air quality and EWB responses were determined to be statistically significant (α = 0.05), due in part to the relatively small sample size, the results are suggestive of linkages between air quality and a variety of EWB outcomes.

Ambient particulate matter oxidative potential: Chemical determinants, associated health effects, and strategies for risk management

Exposure to ambient air pollution has an adverse influence on human health. There is increasing evidence that oxidative potential (OP), the capacity of airborne pollutants to oxidize target molecules by generating redox oxidizing species, is a plausible metric for particulate matter (PM) toxicity. Here we describe the commonly used acellular techniques for measuring OP (respiratory tract lining fluid, dithiothreitol, ascorbic acid, and electron paramagnetic resonance assays) and review the PM chemical constituents that have been identified to drive the OP response. We further perform a review of the epidemiologic literature to identify studies that reported an association between exposure to ambient PM and a health outcome in a human population, and in which exposure was measured by both PM mass concentration and OP. Laboratory studies have shown that specific redox-active metals and quinones are able to contribute OP directly. However, interactions among PM species may alter the redox properties of PM components. In ambient PM measurements, all OP assays were found to be correlated with metals (Fe, Cu) and organic species (photochemically aged organics). Across the epidemiological studies reviewed, associations between fine PM (PM_2.5) mass and cardio-respiratory outcomes were found to be stronger at elevated OP levels but findings varied across the different OP measurement techniques. Future work should aim to identify specific situations in which PM OP can improve air pollution exposure assessment and/or risk management. This may be particularly useful in countries with low PM_2.5 mass concentrations over broad spatial scales where such information may greatly improve the efficiency of risk management activities.

Association between long-term exposure to ambient air pollution and prevalence of diabetes mellitus among Malaysian adults

Background

Malaysia has the highest rate of diabetes mellitus (DM) in the Southeast Asian region, and has ongoing air pollution and periodic haze exposure.

Methods

Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NO_x, NO₂, SO₂, O₃ and PM₁₀) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.

Results

The PM₁₀ concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NO_x decreased while O₃ increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM₁₀, 1.553 (95% CI, 1.328, 1.816) for O₃, 1.271 (95% CI, 1.088, 1.486) for SO₂, 1.124 (95% CI, 1.048, 1.207) for NO₂, and 1.087 (95% CI, 1.024, 1.153) for NO_x for NHMS 2006. The adjusted annual average levels of PM₁₀ [1.187 (95% CI, 1.088, 1.294)], O₃ [1.701 (95% CI, 1.387, 2.086)], NO₂ [1.120 (95% CI, 1.026, 1.222)] and NO_x [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO₂, and 0.910 for NO_x].

Conclusion

The findings of this study suggest that long-term exposure to O₃ is an important associated factor of underdiagnosed DM risk in Malaysia. PM₁₀, NO₂ and NO_x may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.

Workflow for Comparison of Chemical and Biological Metrics of Filter Collected PM2.5

There is limited understanding of adverse health effect associations with chemical constituents of fine particulate matter (PM2.5) as well as the underlying mechanisms. We outlined a workflow to assess metrics, beyond concentration, using household and personal PM2.5 filter samples collected in India as a proof of concept for future large-scale studies. Oxidative potential, chemical composition (polycyclic aromatic hydrocarbons and elements), and bioactivity (developmental exposures in zebrafish) were determined. Significant differences were observed in all metrics between personal and household PM2.5 samples. This work established methods to characterize multiple metrics of PM2.5 to ultimately support the identification of more health-relevant metrics than concentration.

DNA methylation is associated with lung function in never smokers

BACKGROUND

Active smoking is the main risk factor for COPD. Here, epigenetic mechanisms may play a role, since cigarette smoking is associated with differential DNA methylation in whole blood. So far, it is unclear whether epigenetics also play a role in subjects with COPD who never smoked. Therefore, we aimed to identify differential DNA methylation associated with lung function in never smokers.

METHODS

We determined epigenome-wide DNA methylation levels of 396,243 CpG-sites (Illumina 450 K) in blood of never smokers in four independent cohorts, LifeLines COPD&C (N = 903), LifeLines DEEP (N = 166), Rotterdam Study (RS)-III (N = 150) and RS-BIOS (N = 206). We meta-analyzed the cohort-specific methylation results to identify differentially methylated CpG-sites with FEV₁/FVC. Expression Quantitative Trait Methylation (eQTM) analysis was performed in the Biobank-based Integrative Omics Studies (BIOS).

RESULTS

A total of 36 CpG-sites were associated with FEV₁/FVC in never smokers at p-value< 0.0001, but the meta-analysis did not reveal any epigenome-wide significant CpG-sites. Of interest, 35 of these 36 CpG-sites have not been associated with lung function before in studies including subjects irrespective of smoking history. Among the top hits were cg10012512, cg02885771, annotated to the gene LTV1 Ribosome Biogenesis factor (LTV1), and cg25105536, annotated to Kelch Like Family Member 32 (KLHL32). Moreover, a total of 11 eQTMS were identified.

CONCLUSIONS

With the identification of 35 CpG-sites that are unique for never smokers, our study shows that DNA methylation is also associated with FEV₁/FVC in subjects that never smoked and therefore not merely related to smoking.

Associations of long-term exposure to PM1, PM2.5, NO2 with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations

OBJECTIVES

To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM1 and PM2.5), nitrogen dioxide (NO2) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations.

MATERIAL AND METHODS

A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to September 2017 in rural areas of Henan province, China. Three-year average residential exposure levels of PM1, PM2.5, NO2 for each subject were estimated by a spatiotemporal model. Logistic regression and linear regression models were applied to estimate the associations between PM1, PM2.5, NO2 exposure and type 2 diabetes prevalence and fasting blood glucose levels.

RESULTS

The mean 3-year residential exposure concentrations of PM1, PM2.5 and NO2 was 57.4 μg/m3, 73.4 μg/m3 and 39.9 μg/m3, respectively. Higher exposure concentrations of PM1, PM2.5, NO2 by 1 μg/m3 was positively related to a 4.0% (95%CIs: 1.026, 1.054), 6.8% (1.052, 1.084) and 5.0% (1.039, 1.061) increase in odds of type 2 diabetes in the final adjusted models. Besides, a 1 μg/m3 increase of PM1, PM2.5 and NO2 was related to a 0.020 mmol/L (95%CIs: 0.014, 0.026), 0.036 mmol/L (95%CIs: 0.030, 0.042) and 0.030 mmol/L (95%CIs: 0.026, 0.034) mmol/L higher fasting blood glucose levels.

CONCLUSIONS

Higher exposure concentrations of air pollutants were positively related to the increased odds of type 2 diabetes, as well as higher fasting blood glucose levels in Chinese rural populations.

Seasonal Variations and Chemical Predictors of Oxidative Potential (OP) of Particulate Matter (PM), for Seven Urban French Sites

Epidemiological studies suggest that the main part of chronic effects from air pollution is likely to be linked with particulate matter (PM). Oxidative potential (OP) of PM is gaining strong interest as a promising health exposure metric. This study combined atmospheric detailed composition results obtained for seven different urban background environments over France to examine any possible common feature in OP seasonal variations obtained using two assays (acid ascorbic (AA) and dithiothreitol (DTT)) along a large set of samples ( N > 700 ). A remarkable homogeneity in annual cycles was observed with a higher OP activity in wintertime at all investigated sites. Univariate correlations were used to link the concentrations of some major chemical components of PM and their OP. Four PM components were identified as OP predictors: OC, EC, monosaccharides and Cu. These species are notably emitted by road transport and biomass burning, targeting main sources probably responsible for the measured OP activity. The results obtained confirm that the relationship between OP and atmospheric pollutants is assay- and location-dependent and, thus, the strong need for a standardized test, or set of tests, for further regulation purposes.