Constituents Of PM2 Research Articles

Chemical Fingerprinting of PM2.5 via Sequential Speciation Analysis Using Electrochemical Mass Spectrometry.

Chemical fingerprinting to characterize the occurrence state and abundance of organic and inorganic constituents within fine particulate matter (PM2.5) is useful in evaluating the associated health risks and tracing pollution sources. Herein, an analytical strategy for the rapid analysis of metal and organic constituents in PM2.5 was developed employing a combination of sequential chemical extraction coupled with mass spectrometry detection. H2O, CH3OH, EDTA-2Na, electrochemical oxidation, and electrochemical reduction were sequentially utilized to extract the chemical constituents in PM2.5 samples on a homemade device employing simultaneous online detection using two linear trap quadrupole mass spectrometers (LTQ-MS) with electrospray ionization (ESI) in positive and negative modes. After a single analytical procedure, dozens of metals (e.g., Pb, Cr, and Cu), organic compounds (e.g., amines, polycyclic aromatic hydrocarbons, and aliphatic acids), and negative ions (e.g., NO3-, NO2-, and Cl-) were comprehensively detected in the water-soluble, liposoluble, insoluble, oxidizable, and reducible fractions of PM2.5 samples, and their physical and chemical relationships were established.

Impact of fine particulate pollution exposures on respiratory health in a megacity of Pakistan

Air pollution poses a substantial barrier to global environmental sustainability and citizen well-being. However, there is a lack of research that specifically examines the effects of short-term exposure to PM2.5 and its components on health outcomes in developing nations in Asia, regions often cited as having some of the most severe urban air quality issues globally. The present study evaluated the associations between PM2.5 components and hospital admissions (HA) and emergency room visits (ERV) for respiratory diseases in the megacity of Karachi, Pakistan. We measured PM2.5 constituents, including black carbon (BC) and ionic species (sulfate - SO42−; nitrate - NO3−; and ammonium - NH4+) at two sites (August 2008 to August 2009) in Karachi. The HA and ERV, respiratory disease outcome data, were collected from three local, large tertiary care hospitals. We assessed the lag structure of excess risk (ER) of the pollutants-outcomes association (0–6 single and cumulative lag days) using time-series quasi-Poisson models after adjusting for temperature, humidity, and day of the week. Among a total 13,827 patients, the highest ERs for all respiratory urgent care use (UCU) were observed for PM2.5 (10.3, 95% CI: 2.59%-18.59), NH4+ (9.58%, 95% CI: 1.50%–18.30%), air quality index (9.11%, 95%CI: 2.54%–16.09%) and SO42− (7.26%, 95% CI: 1.03%–13.87%) within 0–4 lag days. Additionally, patients with chronic obstructive pulmonary disease (COPD), tuberculosis (TB), or other pulmonary diseases and older or male patients were more vulnerable to these pollutants. This first study in Pakistan found that PM2.5 and its constituents were associated with respiratory HAs and ERVs for the inhabitants of the megacity of Karachi. These associations varied by different PM constituents, disease subtypes, age, and gender. Our results provide important information to policymakers for developing regulations for improving air quality and public health. Further studies are urgently needed in other developing countries to disentangle the air pollution health effects.

Exposure to PM2.5 Metal Constituents and Liver Cancer Risk in REVEAL-HBV.

Ambient particulate matter is classified as a human Class 1 carcinogen, and recent studies found a positive relationship between fine particulate matter (PM2.5) and liver cancer. Nevertheless, little is known about which specific metal constituent contributes to the development of liver cancer. To evaluate the association of long-term exposure to metal constituents in PM2.5 with the risk of liver cancer using a Taiwanese cohort study. A total of 13,511 Taiwanese participants were recruited from the REVEAL-HBV in 1991-1992. Participants' long-term exposure to eight metal constituents (Ba, Cu, Mn, Sb, Zn, Pb, Ni, and Cd) in PM2.5 was based on ambient measurement in 2002-2006 followed by a land-use regression model for spatial interpolation. We ascertained newly developed liver cancer (ie, hepatocellular carcinoma [HCC]) through data linkage with the Taiwan Cancer Registry and national health death certification in 1991-2014. A Cox proportional hazards model was utilized to assess the association between exposure to PM2.5 metal component and HCC. We identified 322 newly developed HCC with a median follow-up of 23.1 years. Long-term exposure to PM2.5 Cu was positively associated with a risk of liver cancer. The adjusted hazard ratio (HR) was 1.13 (95% confidence interval [CI], 1.02-1.25; P = 0.023) with one unit increment on Cu normalized by PM2.5 mass concentration in the logarithmic scale. The PM2.5 Cu-HCC association remained statistically significant with adjustment for co-exposures to other metal constituents in PM2.5. Our findings suggest PM2.5 containing Cu may attribute to the association of PM2.5 exposure with liver cancer.

Ambient fine particulate matter chemical composition associated with in-hospital case fatality, hospital expenses, and length of hospital stay among patients with heart failure in China.

Previous studies have observed the adverse effects of ambient fine particulate matter pollution (PM2.5) on heart failure (HF). However, evidence regarding the impacts of specific PM2.5 components remains scarce. We included 58 129 patients hospitalised for HF between 2013 and 2017 in 11 cities of Shanxi, China from inpatient discharge database. We evaluated exposure to PM2.5 and its components ((sulphate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM) and black carbon (BC)), along with meteorological factors using bilinear interpolation at each patients' residential address. We used multivariable logistic and linear regression models to assess the associations of these components with in-hospital case fatality, hospital expenses, and length of hospital stay. Increase equivalents to the interquartile range (IQR) in OM (odds ratio (OR) = 1.13; 95% confidence interval (CI) = 1.02, 1.26) and BC (OR = 1.14; 95% CI = 1.02, 1.26) were linked to in-hospital case fatality. Per IQR increments in PM2.5, SO42-, NO3-, OM, and BC were associated with cost increases of 420.62 (95% CI = 285.75, 555.49), 221.83 (95% CI = 96.95, 346.71), 214.93 (95% CI = 68.66, 361.21), 300.06 (95% CI = 176.96, 423.16), and 303.09 (95% CI = 180.76, 425.42) CNY. Increases of 1 IQR in PM2.5, SO42-, OM, and BC were associated with increases in length of hospital stay of 0.10 (95% CI = 0.02, 0.19), 0.09 (95% CI = 0.02, 0.17), 0.10 (95% CI = 0.03, 0.17), and 0.16 (95% CI = 0.08, 0.23) days. Our findings suggest that ambient SO42-, OM, and BC might be significant risk factors for HF, emphasising the importance of formulating customised guidelines for the chemical constituents of PM and controlling the emissions of the most dangerous components.

PollutionMapper: Identifying Global Air Pollution Sources

Air pollution adversely impacts public health. The National Capital Region (Delhi-NCR) is among the most polluted urban areas in the world. One component of air pollution is PM2.5, which accounts for around 80% of deaths due to air pollution. Solutions for lowering PM2.5 levels in Delhi have been ineffective due to their unscientific design. In this article, we build a mixed-methods model that captures the interplay of various factors—geographical, chemical, meteorological—that contribute to the concentration of PM2.5. Using domain knowledge and KDE sampling from NASA’s GEOS-CF dataset, we identify the major sources of each of the seven constituents of PM2.5. From the 68 sources thus selected, we run the NOAA’s HYSPLIT wind dispersion model to track the movement of released particles to the sink, i.e., Delhi. Using the concentration of pollutants at the sources and by tracking their movement, we can predict the PM2.5 levels at the sink and identify polluting sources. Our model performed significantly better than the baseline fixed-effects model and captured seasonal variations in all seven constituents of PM2.5. It also uncovered the impact of polluting sources hundreds of kilometers away on the air of Delhi. Policymakers can use such a model to design data-driven policy interventions.

Residential Wood Combustion in Germany: A Twin-Site Study of Local Village Contributions to Particulate Pollutants and Their Potential Health Effects.

Residential wood combustion contributing to airborne particulate matter (PM10) was studied for 1 year at two sites in the village of Melpitz. Significant excess pollution was observed at the Melpitz center compared to that at the TROPOS research station Melpitz reference site, situated only 700 m away. Local concentration increments at the village site for the combustion PM constituents organic carbon, elemental carbon, levoglucosan, and benzo[a]pyrene were determined under appropriate wind directions, and their winter mean values were 0.7 μg m-3, 0.3 μg m-3, 0.1 μg m-3, and 0.4 ng m-3, representing relative increases over the regional background concentration of 24, 70, 61, and 107%, respectively. Yearly, weekly, and diurnal profiles of village increments suggest residential heating as the dominant source of this excess pollution, mainly originating from wood combustion. Receptor modeling using positive matrix factorization quantified 4.5 μg m-3 wood combustion PM at the village site, representing an increment of 1.9 μg m-3 and an increase of ∼75% over the 2.6 μg m-3 regional background wood combustion PM. This increment varied with season, temperature, and boundary layer height and reached daily mean values of 4-6 μg m-3 during unfavorable meteorological conditions. Potential health effects were estimated and resulted in an all-cause mortality from short-term exposure to wood combustion PM of 2.1 cases per 100,000 inhabitants and year for areas with similar wood smoke levels as observed in Melpitz. The excess cancer risk from the concentrations of polycyclic aromatic hydrocarbons was 6.4 per 100,000. For both health metrics, the very local contributions from the village itself were about 40-50%, indicating a strong potential for mitigation through local-scale policies. A compilation of literature data demonstrates wood combustion to represent a major source of PM pollution in Germany, with average winter-time contributions of 10-20%. The present study quantifies the negative impacts of heating with wood in rural residential areas, where the continuous monitoring of air quality is typically lacking. Further regulation of this PM source is warranted in order to protect human health.

Association of Antepartum and Postpartum Air Pollution Exposure With Postpartum Depression in Southern California

Women are especially vulnerable to mental health matters post partum because of biological, emotional, and social changes during this period. However, epidemiologic evidence of an association between air pollution exposure and postpartum depression (PPD) is limited. To examine the associations between antepartum and postpartum maternal air pollution exposure and PPD. This retrospective cohort study used data from Kaiser Permanente Southern California (KPSC) electronic health records and included women who had singleton live births at KPSC facilities between January 1, 2008, and December 31, 2016. Data were analyzed between January 1 and May 10, 2023. Ambient air pollution exposures were assessed based on maternal residential addresses using monthly averages of particulate matter less than or equal to 2.5 μm (PM2.5), particulate matter less than or equal to 10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) from spatial interpolation of monitoring station measurements. Constituents of PM2.5 (sulfate, nitrate, ammonium, organic matter, and black carbon) were obtained from fine-resolution geoscience-derived models based on satellite, ground-based monitor, and chemical transport modeling data. Participants with an Edinburgh Postnatal Depression Scale score of 10 or higher during the 6 months after giving birth were referred to a clinical interview for further assessment and diagnosis. Ascertainment of PPD was defined using a combination of diagnostic codes and prescription medications. The study included 340 679 participants (mean [SD] age, 30.05 [5.81] years), with 25 674 having PPD (7.54%). Increased risks for PPD were observed to be associated with per-IQR increases in antepartum and postpartum exposures to O3 (adjusted odds ratio [AOR], 1.09; 95% CI, 1.06-1.12), PM10 (AOR, 1.02; 95% CI, 1.00-1.04), and PM2.5 (AOR, 1.02; 95% CI, 1. 00-1.03) but not with NO2; PPD risks were mainly associated with PM2.5 organic matter and black carbon. Overall, a higher risk of PPD was associated with O3 during the entire pregnancy and postpartum periods and with PM exposure during the late pregnancy and postpartum periods. The study findings suggest that long-term exposure to antepartum and postpartum air pollution was associated with higher PPD risks. Identifying the modifiable environmental risk factors and developing interventions are important public health issues to improve maternal mental health and alleviate the disease burden of PPD.

Early-life exposure to residential black carbon and childhood cardiometabolic health

BackgroundEarly life exposure to air pollution, such as particulate matter ≤2.5 μm (PM2.5), may be associated with obesity and adverse cardiometabolic health outcomes in childhood. However, the toxicity of PM2.5 varies according to its chemical composition. Black carbon (BC) is a constituent of PM2.5, but few studies have examined its impact on childhood cardiometabolic health. Therefore, we examined relationships between prenatal and early childhood exposure to BC and markers of adiposity and cardiometabolic health in early childhood. MethodsThis study included 578 mother-child pairs enrolled in the Healthy Start study (2009–2014) living in the Denver-metro area. Using a spatiotemporal prediction model, we assessed average residential black carbon levels during pregnancy and in the year prior to the early childhood follow-up visit at approximately 5 years old. We estimated associations between prenatal and early childhood BC and indicators of adiposity and cardiometabolic biomarkers in early childhood (mean 4.8 years; range, 4.0, 8.3), using linear regression. ResultsWe found higher early childhood BC was associated with higher percent fat mass, fat mass index, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and lower leptin and waist circumference at approximately 5 years old, after adjusting for covariates. For example, per interquartile range (IQR) increase in early childhood BC (IQR, 0.49 μg/m3) there was 3.32% higher fat mass (95% CI; 2.05, 4.49). Generally, we did not find consistent evidence of associations between prenatal BC and cardiometabolic health outcomes in early childhood, except for an inverse association between prenatal BC and adiponectin, an adipocyte-secreted hormone typically inversely associated with adiposity. ConclusionsHigher early childhood, but not in utero, ambient concentrations of black carbon, a component of air pollution, were associated with greater adiposity and altered insulin homeostasis at approximately 5 years old. Future studies should examine whether these changes persist later in life.

Long-term exposure to ambient fine particulate matter-bound polycyclic aromatic hydrocarbons and cancer mortality: A difference-in-differences approach

The association of ambient fine particulate matter (PM2.5) exposure with cancer mortality was controversial, which may ascribe to the difference in PM2.5 constituents. Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic constituents in PM2.5, which are suspected to account for PM2.5-induced cancer mortality but are yet to be investigated. We aimed to assess the association between long-term exposure to PM2.5-bound PAHs and cancer mortality and estimate the attributable mortality. A difference-in-differences approach was used to investigate the causal effect of long-term exposure to PM2.5-bound PAHs on cancer mortality. We divided Jiangsu province, China into 53 spatial units and summarized the annual number of cancer deaths in each spatial unit during 2016–2020. Annual population-weighted exposure to PM2.5-bound PAHs of each spatial unit was assessed by an inverse distance weighting method. The association between PM2.5-bound PAHs exposures and cancer mortality was evaluated by controlling spatial differences, temporal trends, PM2.5 mass exposures, temperatures, and socioeconomic status. Records of 793,269 cancer deaths were identified among 84.7 million population. Each ln-unit increase of exposure to total benzo[a]pyrene equivalents (∑BaPeq), total carcinogenic PAHs (∑PAH7c), and total PAHs (∑PAHs) was significantly associated with a 3.21%, 3.48%, and 2.64% increased risk of cancer mortality, respectively; the risk increased monotonically at low-level exposures but attenuated or flattened afterward (all p for nonlinearity <0.05). Similar exposure-response associations were identified for specific PAHs except that the associations for both fluoranthene and benzo[a]anthracene were linear. We estimated that exposure to ∑BaPeq, ∑PAH7c, and ∑PAHs contributed to 5.73%, 8.73%, and 7.33% of cancer deaths, respectively. In conclusion, long-term exposure to PM2.5-bound PAHs was associated with an increased risk of cancer mortality and contributed to substantial cancer deaths. Our findings highlight the importance to prevent deaths from cancer by reducing PM2.5-bound PAHs exposures and the necessity to take into consideration specific constituents in particulate pollution management in future.

Association between long-term exposure to PM2.5 constituents and electrocardiographic abnormality: A nationwide longitudinal study in China

BackgroundElectrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM2.5 constituents and changes in ECG diagnoses. MethodsWe designed a longitudinal study among participants with repeated records of ECG examination based on the China National Stroke Screening Survey 2013–2018. Logistic regressions with multiple adjustment, estimated by the generalized estimating equation to incorporate repeated measurements, were used to assess the associations between the occurrence of any physician-diagnosed ECG abnormalities and long-term exposure to PM2.5 constituents. ResultsWe included 61,094 participants with 132,249 visits. All five constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) were significantly associated with an increased risk of ECG abnormalities. The excess risk of ECG abnormalities per interquartile-range increase in exposure was the highest for sulfate (26%, 95% confidence interval [CI] 23–29%), followed by ammonium (22%, 19–26%), nitrate (21%, 17–24%), black carbon (16%, 13–10%) and organic matter (9%,6%-11%). We also found that atrial fibrillation patients might be susceptible to the adverse effects of PM2.5 constituents on ECG. ConclusionDifferential associations between various constituents of PM2.5 and ECG abnormalities were found. The unequal toxicities for different chemical constituents of ambient particles on cardiovascular electrophysiological endpoints should be taken into consideration when considering the biological pathways linking PM2.5 and cardiovascular conditions.

Short-term effects of fine particulate matter constituents on mortality considering the mortality displacement in Zhejiang province, China

BackgroundEvidence linking mortality and short-term exposure to particulate matter (PM2.5) constituents was sparse. The mortality displacement was often unconsidered and may induce incorrect risk estimation. ObjectivesTo assess the short-term effects of PM2.5 constituents on all-cause mortality considering the mortality displacement. MethodsDaily data on all-cause mortality and PM2.5 constituents, including sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), organic matters (OM), and black carbon (BC), were collected from 2009 to 2020. The mortality effect of PM2.5 and its constituents was estimated using a distributed lag non-linear model. Stratified analyses were performed by age, sex, and season. ResultsPer interquartile range increases in SO42−, NO3−, NH4+, OM, and BC were associated with the 1.42% (95%CI: 0.98, 1.87), 3.76% (3.34, 4.16), 2.26% (1.70, 2.83), 2.36% (2.02, 2.70), and 1.26% (0.91, 1.61) increases in all-cause mortality, respectively. Mortality displacements were observed for PM2.5, SO42−, NH4+, OM, and BC, with their overall effects lasting for 7–15 days. Stratified analyses revealed a higher risk for old adults (>65 years) and females, with stronger effects in the cold season. ConclusionsShort-term exposures to PM2.5 constituents were positively associated with increased risks of mortality. The mortality displacement should be considered in future epidemiological studies on PM constituents. Data availabilityData will be made available on request.

Fine micro- and nanoplastics particles (PM2.5) in urban air and their relation to polycyclic aromatic hydrocarbons

Microplastics and nanoplastics have been reported in nearly all environmental compartments, the dataset about their contributions and their role as a sink and carrier for other hydrophobic compounds in the atmosphere however is limited. This study presents, for the first time, atmospheric concentrations of ultrafine microplastics and nanoplastics (UFMNP) on the single polymer level and their correlations with atmospheric concentrations of 23 polycyclic aromatic hydrocarbons (PAHs). Measurements of UFMNP in ambient particulate matter (PM2.5) were performed for an urban sampling site in Graz, Austria. During the sampling period of 02.01. – 31.03.2017 the average UFMNP concentration was 238 ng/m3, reaching up to 557 ng/m3. This accounts for an average contribution of 0.67% to PM2.5 mass and 1.7% of organic matter. The individual polymer types were polyethylene terephthalate (PET), polypropylene (PP) and polyethylene (PE), which sum up the most demanded polymer types in Europe. PET was found to be the most prominent polymer in the urban samples contributing to 50% of the overall UFMNP mass, followed by PP (27%) and PE (23%). However, the relative contributions vary with time. PET was observed during the entire time period, while PP and PE were quite variable and linked to the origin of the air masses. A possible carrier function of PP and PE for selected micropollutants can be deduced from the significant monotonic correlations between these polymers and selected PAHs. High correlations were predominantly found for low molecular weight congeners and correlations were more pronounced than those investigated for PAHs and other constituents of PM2.5, i.e. elemental carbon and organic matter again pointing to special interactions of those emerging pollutants.

Prenatal exposure to tailpipe and non-tailpipe tracers of particulate matter pollution and autism spectrum disorders

BackgroundTraffic-related air pollution exposure is associated with increased risk of autism spectrum disorder (ASD). It is unknown whether carbonaceous material from vehicular tailpipe emissions or redox-active non-tailpipe metals, eg. from tire and brake wear, are responsible. We assessed ASD associations with fine particulate matter (PM2.5) tracers of tailpipe (elemental carbon [EC] and organic carbon [OC]) and non-tailpipe (copper [Cu]; iron [Fe] and manganese [Mn]) sources during pregnancy in a large cohort. MethodsThis retrospective cohort study included 318,750 children born in Kaiser Permanente Southern California (KPSC) hospitals during 2001–2014, followed until age 5. ASD cases were identified by ICD codes. Monthly estimates of PM2.5 and PM2.5 constituents EC, OC, Cu, Fe, and Mn with 4 km spatial resolution were obtained from a source-oriented chemical transport model. These exposures and NO2 were assigned to each maternal address during pregnancy, and associations with ASD were assessed using Cox regression models adjusted for covariates. PM constituent effect estimates were adjusted for PM2.5 and NO2 to assess independent effects. To distinguish ASD risk associated with non-tailpipe from tailpipe sources, the associations with Cu, Fe, and Mn were adjusted for EC and OC, and vice versa. ResultsThere were 4559 children diagnosed with ASD. In single-pollutant models, increased ASD risk was associated with gestational exposures to tracers of both tailpipe and non-tailpipe emissions. The ASD hazard ratios (HRs) per inter-quartile increment of exposure) for EC, OC, Cu, Fe, and Mn were 1.11 (95% CI: 1.06–1.16), 1.09 (95% CI: 1.04–1.15), 1.09 (95% CI: 1.04–1.13), 1.14 (95% CI: 1.09–1.20), and 1.17 (95% CI: 1.12–1.22), respectively. Estimated effects of Cu, Fe, and Mn (reflecting non-tailpipe sources) were largely unchanged in two-pollutant models adjusting for PM2.5, NO2, EC or OC. In contrast, ASD associations with EC and OC were markedly attenuated by adjustment for non-tailpipe sources. ConclusionResults suggest that non-tailpipe emissions may contribute to ASD. Implications are that reducing tailpipe emissions, especially from vehicles with internal combustion engines, may not eliminate ASD associations with traffic-related air pollution.

Isoprene Epoxydiol-Derived Sulfated and Nonsulfated Oligomers Suppress Particulate Mass Loss during Oxidative Aging of Secondary Organic Aerosol.

Acid-driven multiphase chemistry of isoprene epoxydiols (IEPOX) with inorganic sulfate aerosols contributes substantially to secondary organic aerosol (SOA) formation, which constitutes a large mass fraction of atmospheric fine particulate matter (PM2.5). However, the atmospheric chemical sinks of freshly generated IEPOX-SOA particles remain unclear. We examined the role of heterogeneous oxidation of freshly generated IEPOX-SOA particles by gas-phase hydroxyl radical (•OH) under dark conditions as one potential atmospheric sink. After 4 h of gas-phase •OH exposure (∼3 × 108 molecules cm-3), chemical changes in smog chamber-generated IEPOX-SOA particles were assessed by hydrophilic interaction liquid chromatography coupled with electrospray ionization high-resolution quadrupole time-of-flight mass spectrometry (HILIC/ESI-HR-QTOFMS). A comparison of the molecular-level compositional changes in IEPOX-SOA particles during aging with or without •OH revealed that decomposition of oligomers by heterogeneous •OH oxidation acts as a sink for •OH and maintains a reservoir of low-volatility compounds, including monomeric sulfate esters and oligomer fragments. We propose tentative structures and formation mechanisms for previously uncharacterized SOA constituents in PM2.5. Our results suggest that this •OH-driven renewal of low-volatility products may extend the atmospheric lifetimes of particle-phase IEPOX-SOA by slowing the production of low-molecular weight, high-volatility organic fragments and likely contributes to the large quantities of 2-methyltetrols and methyltetrol sulfates reported in PM2.5.

Associations of fine particulate matter and its metal constituents with blood pressure: A panel study during the seventh World Military Games

Evidence is needed to elucidate the association of blood pressure (BP) changes with metal constituents in fine particulate matter (PM2.5). Therefore, we designed a longitudinal panel study enrolling 70 healthy students from Wuhan University in the context of the seventh World Military Games (the 7th WMG) from September 2019 to January 2020. A total of eight visits were conducted before, during, and after the 7th WMG. During every visit, each participant was asked to carry a personal PM2.5 monitor to measure hourly PM2.5 levels for three consecutive days. Questionnaire investigation and physical examination were completed on the fourth day. We analyzed ten metal constituents of ambient PM2.5 collected from the fixed station, and blood pressure was recorded during each visit. The linear mixed-effects models were performed to evaluate associations of metal constituents and blood pressure measurements. We observed a dramatic variation of PM2.5 concentration ranging from 7.38 to 132.04 μg/m3. A 10 μg/m3 increment of PM2.5 was associated with an increase of 0.64 mmHg (95% CI: 0.44, 0.84) in systolic BP (SBP), 0.40 mmHg (0.26, 0.54) in diastolic BP (DBP), 0.31 mmHg (0.15, 0.47) in pulse pressure (PP) and 0.44 mmHg (0.26, 0.62) in mean artery pressure (MAP), respectively. For metal constituents in PM2.5, robust positive associations were observed between BP and selenium, manganese, arsenic, cadmium, and thallium. For example, for an IQR (0.93 ng/m3) increment of selenium, SBP and MAP elevated by 0.98 mmHg (0.09, 1.87) and 0.71 mmHg (0.03, 1.39), respectively. Aluminum was found to be robustly associated with decreased SBP, DBP, and MAP. The study indicated that exposure to PM2.5 total mass and metal constituents including selenium, manganese, arsenic, cadmium, and thallium were associated with the elevated BP.

Associations between short-term exposure of PM2.5 constituents and hospital admissions of cardiovascular diseases among 18 major Chinese cities

Previous studies showed different risk effects on exposure of fine particulate matter (PM2.5) mass for cardiovascular disease (CVD) globally, which is likely due to different constituents of PM2.5. This study aimed to investigate the association between short-term exposure of PM2.5 constituents and hospital admissions of CVD. Daily counts of city-specific hospital admissions for CVD in 18 cities in China between 2014 and 2017 were extracted from the national Urban Employee Basic Medical Insurance database and the Beijing Municipal Commission of Health and Family Planning Information Center database. Directly measured PM2.5 constituents, including ions and polycyclic aromatic hydrocarbons, were collected by the Chinese Environmental Public Health Tracking system. We used the time-stratified case-crossover design to estimate the association between PM2.5 constituents and hospital admissions of CVD. Concentrations of ions accounted for the majority of the detected constituents. Excess risk (ER) of average ions concentrations for CVD was highest as 2.30% (95% CI: 1.62–2.99%) for NH4+, whose major sources are residential and agricultural emissions. This was followed by 1.85% (1.30–2.41%) for NO3- (generally from vehicles), 0.95% (0.28–1.63%) for SO42- (often from fossil fuel burning) respectively. The association for ions were generally consistent with ischemic heart disease (IHD) and ischemic stroke, e.g., NH4+ was associated with IHD (2.50%; 1.52–3.48%) and ischemic stroke (1.77%; 0.65–2.9%). For polycyclic aromatic hydrocarbons (PAHs), mainly from coal and vehicle-related oil combustion, the constituents were all associated with ischemic stroke but not for IHD. The ER for ischemic stroke was highest at 1.69% (0.99–2.39%) for indeno (123-cd) pyrene. Thus, in terms of the subtypes of CVD, the risks of hospital admissions varied with exposure to different PM2.5 constituents. Exposed to NH4+ had the highest risk to IHD and ischemic stroke, whereas PAHs were predominately associated with ischemic stroke only.

Analyze the Effect of Steaming on the Chemical Constituents, Defecation and Liver Injury of Polygonum Multiflorum Radix (Heshouwu) by Multiple Analysis Techniques Combined with Multivariate Statistics.

Steaming is a characteristic pharmaceutical skill in Traditional Chinese Medicine (TCM). Polygonum multiflorum radix (PM) and its steamed products have been used in Asia for centuries. Raw Polygonum multiflorum radix (RPM) is commonly used to promote defecation but can exert toxicity, especially in liver injury. However, RPM can be made converted into Polygoni multiflori radix praeparata (PMP) by steaming; this is considered a good method to reduce defecation and liver injury caused by PM in Asia. The chemical constituents of TCM are the key to its action. We systematically analyzed the effect of steaming on PM constituents, defecation, and liver injury. We identified 13 main constituents from PM and PMP; the results showed that after being steamed, two constituents (TSG, catechin) had decreased, six constituents (such as procyanidin B1 or B2) had disappeared, four constituents (such as emodin, physcion) had increased, emodin-8-O-β-D-glucoside remained unchanged in PMP. Pharmacological experiments showed that PM could promote defecation; however, there were no obvious effects in response to PMP. Only a high dose of PM for 14 days caused some degree of liver injury, although this injury disappeared after 14 days of drug withdrawal. Network pharmacology and molecular docking studies showed that TSG, emodin and physcion were the most effective in promoting defecation and causing liver injury. Collectively, our findings show that steaming can reduce the effect of PM on promoting defecation and reducing liver injury. TSG may be one of the important constituents in PM that can promote defecation and cause liver injury.

Metal Constituents of Fine Particulate Matter Mass and Incident Depression: A Community-based Cohort Study in China

BACKGROUND AND AIM: Little is known about the effects of chemical constituents of fine particulate matter (particles with aerodynamic diameter &amp;#x2264; 2.5 &amp;#x3bc;m, PM2.5). This study aims to estimate the associations between constituents of PM2.5 and incident depression. METHODS: This large cohort study recruited the local adults in Ningbo, a southeastern coastal city in China. Depression cases were ascertained from local Health Information System. Daily PM2.5 samples were collected at seven monitoring sites for the 10th-16th seven consecutive days and further measured for ten PM2.5-bound metals. Land-use regression models were conducted to predict the residential PM2.5-bound metals exposure. We conducted three cox proportional hazards models which respectively employed single constituent, constituent adjusting for PM2.5 and constituent residual calculated by PM2.5 as exposures to estimate the effect of constituents on incident depression. Environmental Risk Score (ERS) and Weighted Quintile Score (WQS) were utilized to estimate the overall effect of all metals. RESULTS: In fully adjusted constituent models, the higher concentrations of ambient Lead(Pb), Nickel(Ni), Mercury(Hg), Chromium(Cd) and Beryllium(Be) were significantly associated with higher risk of incident depression. In ERS analyses, one main effect (Tl), three squared terms (Hg, Cd and Al) and twelve pairwise interactions (Tl &amp;#x26; Pb, Tl &amp;#x26; Be, et al) were selected by adaptive elastic-net (AENET) for construction of ERS of incident depression-related ambient metal mixtures. The ERS index was positively and significantly associated with depression incidence. And similar results were found for WQS index which suggesting that Al, Sb, Hg, Tl, Mn and Be contributed the most to the association. CONCLUISIONS: These findings highlighted the associations of exposure to PM2.5-bound metals with incident depression. Further studies are needed to confirm the findings and examine the underlying mechanisms. KEYWORDS: PM2.5-bound Metal, depression, Cox Proportional Hazardous Regression, ERS, WQS.

Acute effects of black carbon on mortality in nine megacities of China, 2008-2016: a time-stratified case-crossover study.

Black carbon (BC) may have more adverse effects on human health than other constituents of PM2.5. The daily mean concentrations of BC in China are much higher than those in developed countries and are estimated to account for more than a quarter of global anthropogenic BC emissions. However, reports on the health effects of BC in China have been limited. Thus, a time-stratified case-crossover study was conducted to evaluate the impacts of BC on daily mortality risk in nine Chinese megacities from 2008-2016. Our results show that for all-cause mortality, when compared to the interquartile range (IQR) of BC concentration increased, odds ratios (ORs) were in the range of 1.01-1.06 (95% CIs: 0.99-1.10). For cardiovascular mortality, ORs were in the range of 1.02-1.07 (95% CIs: 1.003-1.12), and for respiratory mortality, ORs were in the range of 1.01-1.15 (95% CIs: 1.00-1.18). The effects of BC in the nine cities were robust after adjusting for PM2.5, or even became more prominent. Furthermore, BC had stronger effects in spring and winter in northern cities, whereas in mid-latitude cities, BC had stronger effects in the warm seasons. In southern cities, BC had stronger effects in the cool and dry seasons. Our findings support an association between residential exposure to BC and mortality and thus provide further evidence that BC negatively impacts human health and is helpful for decision-making.

Interrogating common clarification models for unit operation systems with dynamic similitude

Surface overflow rate (SOR), plug flow reactor (PFR) and continuously stirred tank reactor (CSTR) are common models for clarification unit operations (UO). With wide deployment in engineering practice and regulation, through tools from spreadsheets to complex numerical codes, these models are formulated based upon conceptualized system geometry (e.g., rectangular channel) and idealized hydrodynamics (plug flow or well-mixed conditions). Yet the hydrodynamics and geometry of actual UO systems can be complex and substantially different from these assumptions. As a result, the applicability and generalizability of these models require critical and systematic interrogation. This study examines the predictive capability and generalizability of these common models for a hydrodynamic separator (HS), tanks, rectangular clarifiers and an urban drainage basin based on physical model data and high-fidelity large-eddy simulation (LES). Moreover, this study presents a novel application of dynamic similitude to developing a more generalized and physically interpretable model based on the hypothesis that PM and PM-partitioned constituent separation in a UO can be approximated solely through the dimensionless settling velocity W (Hazen number). Based on this hypothesis and dynamic similitude, a similarity modified gamma model (SMG) is proposed and tested. With dynamic similitude and W, results show common models are not robust and generalizable for predicting PM separation with error ranging from 30 to 50% and can significantly oversize a clarifier up to 904%. The non-linear characteristics of PM separation are shown to have a critical role in clarifications system design scalability and economics. In contrast, the SMG model is robust and generalizes the PM separation for geometrically similar systems, irrespective of particle density, particle size distribution (PSD), and loading conditions. The developed theory and proposed SMG model also can simplify and reduce the effort as well as expense of physical model testing while serving as an adjuvant for numerical simulations of clarification systems. Results also reveal commercial HS systems do not outperform simple plain tank geometries. The complex turbulence vortical structures pose significant challenges for UO system analysis and design.