Relative toxicities of major particulate matter constituents on birthweight in Massachusetts.
ABSTRACT: Background:Maternal exposure to fine particulate air pollution (PM2.5) during pregnancy has been linked to lower newborn birthweight, making it a toxic exposure because lower birthweight is a risk factor for chronic disease and mortality. However, the toxicity of major constituents of PM2.5 and how they compare to each other remain uncertain. Methods:We assigned address-specific exposure to PM2.5, elemental carbon (EC), organic carbon (OC), nitrate, and sulfate averaged over the entire period of pregnancy for each birth in Massachusetts from 2001 to 2012 using a high-resolution exposure model. Using multivariate regression adjusted for total PM2.5, we estimated the relative toxicity of each constituent on continuous birthweight. Results:EC was more toxic per interquartile range increase compared with remaining PM2.5 in single constituent models that estimated the effect of a constituent with adjustment for PM2.5. OC, nitrate, and sulfate were each less toxic than their respective remaining PM2.5 per interquartile range increase. When all constituents and total PM2.5 were included in the same model, EC was most toxic, followed by nitrate, then OC and sulfate with similar toxicities. Sensitivity analyses using term low birth weight and small for gestational age also showed that EC was most detrimental as did averaging exposures over the third trimester of pregnancy. Scaling to unit mass increases also showed EC to be most toxic. Conclusion:Four major constituents of PM2.5 had different relative toxicities on continuous birthweight. Our findings suggest that EC was most toxic, followed by nitrate, OC, and sulfate.
Project description:Seasonal variation and regional heterogeneity have been observed in the estimated effect of fine particulate matter (PM2.5) mass on mortality. Differences in the chemical compositions of PM2.5 may cause this variation. We investigated the association of the daily concentration of PM2.5 components with mortality in Nagoya, Japan.We combined daily mortality counts for all residents aged 65 years and older with concentration data for PM2.5 mass and components in Nagoya from April 2003 to December 2007. A time-stratified case-crossover design was used to examine the association of daily mortality with PM2.5 mass and each component (chloride, nitrate, sulfate, sodium, potassium, calcium, magnesium, ammonium, elemental carbon [EC], and organic carbon [OC]).We found a stronger association between mortality and PM2.5 mass in transitional seasons. In analysis for each PM2.5 component, sulfate, nitrate, chloride, ammonium, potassium, EC, and OC were significantly associated with mortality in a single-pollutant model. In a multi-pollutant model, an interquartile range increase in the concentration of sulfate was marginally associated with an increase in all-cause mortality of 2.1% (95% confidence interval, -0.1 to 4.4).These findings suggest that some specific PM components have a more hazardous effect than others and contribute to seasonal variation in the health effects of PM2.5.
Project description:Although the association between PM2.5 mass and mortality has been extensively studied, few national-level analyses have estimated mortality effects of PM2.5 chemical constituents. Epidemiologic studies have reported that estimated effects of PM2.5 on mortality vary spatially and seasonally. We hypothesized that associations between PM2.5 constituents and mortality would not vary spatially or seasonally if variation in chemical composition contributes to variation in estimated PM2.5 mortality effects.We aimed to provide the first national, season-specific, and region-specific associations between mortality and PM2.5 constituents.We estimated short-term associations between nonaccidental mortality and PM2.5 constituents across 72 urban U.S. communities from 2000 to 2005. Using U.S. Environmental Protection Agency (EPA) Chemical Speciation Network data, we analyzed seven constituents that together compose 79-85% of PM2.5 mass: organic carbon matter (OCM), elemental carbon (EC), silicon, sodium ion, nitrate, ammonium, and sulfate. We applied Poisson time-series regression models, controlling for time and weather, to estimate mortality effects.Interquartile range increases in OCM, EC, silicon, and sodium ion were associated with estimated increases in mortality of 0.39% [95% posterior interval (PI): 0.08, 0.70%], 0.22% (95% PI: 0.00, 0.44), 0.17% (95% PI: 0.03, 0.30), and 0.16% (95% PI: 0.00, 0.32), respectively, based on single-pollutant models. We did not find evidence that associations between mortality and PM2.5 or PM2.5 constituents differed by season or region.Our findings indicate that some constituents of PM2.5 may be more toxic than others and, therefore, regulating PM total mass alone may not be sufficient to protect human health.
Project description:There is a rising concern that fine particle (PM2.5) compositions may play an important role in explaining PM2.5-related mortality risks. However, PM2.5 constituents responsible for these risks have not yet been determined. To date, there are few PM2.5 constituent health studies in developing countries. We adopted a time-series approach, using generalized linear regression models to examine associations between short-term exposure to PM2.5 constituents and mortality. We analyzed data stratified by sex and by age groups (<65, 65-74, and >74) from 2013 to 2015 in Beijing, China. We also investigated seasonal patterns of such associations. For a 0 day lag, interquartile range increases in potassium, calcium, magnesium, and organic carbon were associated with 0.51% (95% CI: 0.17-0.85), 2.07% (95% CI: 0.71-3.44), 0.26% (95% CI: 0.08-0.44), and 2.65% (95% CI: 0.18-5.18) increases in respiratory mortality, and sulfate with a 1.57% (95% CI: 0.04-3.12) increase in cardiovascular mortality. In the season-stratified analysis, the association of some constituents (potassium, calcium, magnesium, nitrate, sulfate, and organic carbon) with respiratory mortality appeared to be stronger in cold seasons than in warm seasons. Older adults (65-74) may be susceptible to certain compositions. Our findings provide evidence that link PM2.5 constituents with mortality and suggest that adverse effects vary among constituents in different seasons.
Project description:Research efforts to better characterize the differential toxicity of PM2.5 (particles with aerodynamic diameters less than or equal to 2.5 ?m) speciation are often hindered by the sparse or non-existent coverage of ground monitors. The Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA's Terra satellite is one of few satellite aerosol sensors providing information of aerosol shape, size and extinction globally for a long and continuous period that can be used to estimate PM2.5 speciation concentrations since year 2000. Currently, MISR only provides a 17.6 km product for its entire mission with global coverage every 9 days, a bit too coarse for air pollution health effects research and to capture local spatial variability of PM2.5 speciation. In this study, generalized additive models (GAMs) were developed using MISR prototype 4.4 km-resolution aerosol data with meteorological variables and geographical indicators, to predict ground-level concentrations of PM2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) in Southern California between 2001 and 2015 at the daily level. The GAMs are able to explain 66%, 62%, 55% and 58% of the daily variability in PM2.5 sulfate, nitrate, OC and EC concentrations during the whole study period, respectively. Predicted concentrations capture large regional patterns as well as fine gradients of the four PM2.5 species in urban areas of Los Angeles and other counties, as well as in the Central Valley. This study is the first attempt to use MISR prototype 4.4 km-resolution AOD (aerosol optical depth) components data to predict PM2.5 sulfate, nitrate, OC and EC concentrations at the sub-regional scale. In spite of its low temporal sampling frequency, our analysis suggests that the MISR 4.4 km fractional AODs provide a promising way to capture the spatial hotspots and long-term temporal trends of PM2.5 speciation, understand the effectiveness of air quality controls, and allow our estimated PM2.5 speciation data to be linked with common spatial units such as census tract or zip code in epidemiological studies. This modeling strategy needs to be validated in other regions when more MISR 4.4 km data becoming available in the future.
Project description:Several epidemiological studies have reported that long-term exposure to fine particulate matter (PM2.5) is associated with higher mortality. Evidence regarding contributions of PM2.5 constituents is inconclusive.We assembled a data set of 12.5 million Medicare enrollees (? 65 years of age) to determine which PM2.5 constituents are a) associated with mortality controlling for previous-year PM2.5 total mass (main effect); and b) elevated in locations exhibiting stronger associations between previous-year PM2.5 and mortality (effect modification).For 518 PM2.5 monitoring locations (eastern United States, 2000-2006), we calculated monthly mortality rates, monthly long-term (previous 1-year average) PM2.5, and 7-year averages (2000-2006) of major PM2.5 constituents [elemental carbon (EC), organic carbon matter (OCM), sulfate (SO42-), silicon (Si), nitrate (NO3-), and sodium (Na)] and community-level variables. We applied a Bayesian hierarchical model to estimate location-specific mortality rates associated with previous-year PM2.5 (model level 1) and identify constituents that contributed to the spatial variability of mortality, and constituents that modified associations between previous-year PM2.5 and mortality (model level 2), controlling for community-level confounders.One-standard deviation (SD) increases in 7-year average EC, Si, and NO3- concentrations were associated with 1.3% [95% posterior interval (PI): 0.3, 2.2], 1.4% (95% PI: 0.6, 2.4), and 1.2% (95% PI: 0.4, 2.1) increases in monthly mortality, controlling for previous-year PM2.5. Associations between previous-year PM2.5 and mortality were stronger in combination with 1-SD increases in SO42- and Na.Long-term exposures to PM2.5 and several constituents were associated with mortality in the elderly population of the eastern United States. Moreover, some constituents increased the association between long-term exposure to PM2.5 and mortality. These results provide new evidence that chemical composition can partly explain the differential toxicity of PM2.5.
Project description:In air pollution time-series studies, the temporal pattern of the association of fine particulate matter (PM2.5; particulate matter ? 2.5 µm in aerodynamic diameter) and health end points has been observed to vary by disease category. The lag pattern of PM2.5 chemical constituents has not been well investigated, largely because daily data have not been available.We explored the lag structure for hospital admissions using daily PM2.5 chemical constituent data for 5 years in the Denver Aerosol Sources and Health (DASH) study.We measured PM2.5 constituents, including elemental carbon, organic carbon, sulfate, and nitrate, at a central residential site from 2003 through 2007 and linked these daily pollution data to daily hospital admission counts in the five-county Denver metropolitan area. Total hospital admissions and subcategories of respiratory and cardiovascular admissions were examined. We assessed the lag structure of relative risks (RRs) of hospital admissions for PM2.5 and four constituents on the same day and from 1 to 14 previous days from a constrained distributed lag model; we adjusted for temperature, humidity, longer-term temporal trends, and day of week using a generalized additive model.RRs were generally larger at shorter lags for total cardiovascular admissions but at longer lags for total respiratory admissions. The delayed lag pattern was particularly prominent for asthma. Elemental and organic carbon generally showed more immediate patterns, whereas sulfate and nitrate showed delayed patterns.In general, PM2.5 chemical constituents were found to have more immediate estimated effects on cardiovascular diseases and more delayed estimated effects on respiratory diseases, depending somewhat on the constituent.
Project description:BACKGROUND: Although ambient fine particulate matter (PM(2.5); particulate matter ? 2.5 µm in aerodynamic diameter) has been linked to adverse human health effects, the chemical constituents that cause harm are unknown. To our knowledge, the health effects of PM(2.5) constituents have not been reported for a developing country. OBJECTIVES: We examined the short-term association between PM(2.5) constituents and daily mortality in Xi'an, a heavily polluted Chinese city. METHODS: We obtained daily mortality data and daily concentrations of PM(2.5), organic carbon (OC), elemental carbon (EC), and 10 water-soluble ions for 1 January 2004 through 31 December 2008. We also measured concentrations of fifteen elements 1 January 2006 through 31 December 2008. We analyzed the data using overdispersed generalized linear Poisson models. RESULTS: During the study period, the mean daily average concentration of PM(2.5) in Xi'an was 182.2 µg/m³. Major contributors to PM(2.5) mass included OC, EC, sulfate, nitrate, and ammonium. After adjustment for PM(2.5) mass, we found significant positive associations of total, cardiovascular, or respiratory mortality with OC, EC, ammonium, nitrate, chlorine ion, chlorine, and nickel for at least one lag period. Nitrate demonstrated stronger associations with total and cardiovascular mortality than PM(2.5) mass. For a 1-day lag, interquartile range increases in PM(2.5) mass and nitrate (114.9 and 15.4 µg/m³, respectively) were associated with 1.8% [95% confidence interval (CI): 0.8%, 2.8%] and 3.8% (95% CI: 1.7%, 5.9%) increases in total mortality. CONCLUSIONS: Our findings suggest that PM(2.5) constituents from the combustion of fossil fuel may have an appreciable influence on the health effects attributable to PM(2.5) in Xi'an.
Project description:Exposure to particulate matter air pollution with a nominal mean aerodynamic diameter less than or equal to 2.5 ?m (PM2.5) has been associated with health effects including cardiovascular disease and death. Here, we add to the understanding of urban and rural PM2.5 concentrations over large spatial and temporal scales in recent years. We used high-quality, publicly-available air quality monitoring data to evaluate PM2.5 concentration patterns and changes during the years 2000-2015. Compiling and averaging measurements collected across the U.S. revealed that PM2.5 concentrations from urban sites experienced seasonal maxima in both winter and summer. Within each year from 2000 to 2008, the maxima of urban summer peaks were greater than winter peaks. However, from 2012 to 2015, the maxima of urban summertime PM2.5 peaks were smaller than the urban wintertime PM2.5 maxima, due to a decrease in the magnitude of summertime maxima with no corresponding decrease in the magnitude of winter maxima. PM2.5 measurements at rural sites displayed summer peaks with magnitudes relatively similar to those of urban sites, and negligible to no winter peaks through the time period analyzed. Seasonal variations of urban and rural PM2.5 sulfate, PM2.5 nitrate, and PM2.5 organic carbon (OC) were also assessed. Summer peaks in PM2.5 sulfate decreased dramatically between 2000 and 2015, whereas seasonal PM2.5 OC and winter PM2.5 nitrate concentration maxima remained fairly consistent. These findings demonstrate that PM2.5 concentrations, especially those occurring in the summertime, have declined in the U.S. from 2000 to 2015. In addition, reduction strategies targeting sulfate have been successful and the decrease in PM2.5 sulfate contributed to the decline in total PM2.5.
Project description:Daily PM10and PM2.5 sampling was conducted during four seasons from December 2013 to October 2014 at three monitoring sites over Yulin, a desert margin city. PM10 and PM2.5 levels, water soluble ions, organic carbon (OC), and elemental carbon (EC) were also analyzed to characterize their chemical profiles. b ext (light extinction coefficient) was calculated, which showed the highest in winter with an average of 232.95 ± 154.88 Mm-1, followed by autumn, summer, spring. Light extinction source apportionment results investigated (NH4)2SO4 and NH4NO3 played key roles in the light extinction under high RH conditions during summer and winter. Sulfate, nitrate and Ca2 + dominated in PM10/PM2.5 ions. Ion balance results illustrated that PM samples were alkaline, and PM10 samples were more alkaline than PM2.5. High SO4 2-/K+ and Cl-/K+ ratio indicated the important contribution of coal combustion, which was consistent with the OC/EC regression equation intercepts results. Principal component analysis (PCA) analyses results showed that the fugitive dust was the most major source of PM, followed by coal combustion & gasoline vehicle emissions, secondary formation and diesel vehicle emissions. Potential contribution source function (PSCF) results suggested that local emissions, as well as certain regional transport from northwesterly and southerly areas contributed to PM2.5 loadings during the whole year. Local government should take some measures to reduce the PM levels.
Project description:This study presents source apportionment results for PM2.5 from applying positive matrix factorization (PMF) to a 32-month series of daily PM2.5 compositional data from Denver, CO, including concentrations of sulfate, nitrate, bulk elemental carbon (EC) and organic carbon (OC), and 51 organic molecular markers (OMMs). An optimum 8-factor solution was determined primarily based on the interpretability of the PMF results and rate of matching factors from bootstrapped PMF solutions with those from the base case solution. These eight factors were identified as inorganic ion, n-alkane, EC/sterane, light n-alkane/polycyclic aromatic hydrocarbon (PAH), medium alkane/alkanoic acid, PAH, winter/methoxyphenol and summer/odd n-alkane. The inorganic ion factor dominated the reconstructed PM2.5 mass (sulfate + nitrate + EC + OC) in cold periods (daily average temperature < 10 °C; 43.7% of reconstructed PM2.5 mass) whereas the summer/odd n-alkane factor dominated in hot periods (> 20 °C; 53.1%). The two factors had comparable relative contributions of 26.5% and 27.1% in warm periods with temperatures between 10 °C and 20 °C. Each of the seven factors resolved in a previous study (Dutton et al., 2010b) using a 1-year data set from the same location matches one factor from the current work based on comparing factor profiles. Six out of the seven matched pairs of factors are linked to similar source classes as suggested by the strong correlations between factor contributions (r = 0.89 - 0.98). Temperature-stratified source apportionment was conducted for three subsets of the data in the current study, corresponding to the cold, warm and hot periods mentioned above. The cold period (7-factor) solution exhibited a similar distribution of reconstructed PM2.5 mass as the full data set solution. The factor contributions of the warm period (7-factor) solution were well correlated with those from the full data set solution (r = 0.76 - 0.99). However, the reconstructed PM2.5 mass was distributed more to inorganic ion, n-alkane and medium alkane/alkanoic acid factors in the warm period solution than in the full data set solution. For the hot period (6-factor) solution, PM2.5 mass distribution was quite different from that of the full data set solution, as illustrated by regression slopes as low as 0.2 and as high as 4.8 of each matched pair of factors across the two solutions.