Health impacts of a randomized biomass cookstove intervention in northern Ghana.

BACKGROUND: Household air pollution (HAP) from cooking with solid fuels has adverse health effects. REACCTING (Research on Emissions, Air quality, Climate, and Cooking Technologies in Northern Ghana) was a randomized cookstove intervention study that aimed to determine the effects of two types of "improved" biomass cookstoves on health using self-reported health symptoms and biomarkers of systemic inflammation from dried blood spots for female adult cooks and children, and anthropometric growth measures for children only. METHODS: Two hundred rural households were randomized into four different cookstove groups. Surveys and health measurements were conducted at four time points over a two-year period. Chi-square tests were conducted to determine differences in self-reported health outcomes. Linear mixed models were used to assess the effect of the stoves on inflammation biomarkers in adults and children, and to assess the z-score deviance for the anthropometric data for children. RESULTS: We find some evidence that two biomarkers of oxidative stress and inflammation, serum amyloid A and C-reactive protein, decreased among adult primary cooks in the intervention groups relative to the control group. We do not find detectable impacts for any of the anthropometry variables or self-reported health. CONCLUSIONS: Overall, we conclude that the REACCTING intervention did not substantially improve the health outcomes examined here, likely due to continued use of traditional stoves, lack of evidence of particulate matter emissions reductions from "improved" stoves, and mixed results for HAP exposure reductions. CLINICAL TRIAL REGISTRY: ClinicalTrials.gov (National Institutes of Health); Trial Registration Number: NCT04633135 ; Date of Registration: 11 November 2020 - Retrospectively registered. URL: https://clinicaltrials.gov/ct2/show/NCT04633135?term=NCT04633135&draw=2&rank=1.

Photochemical Aging of Atmospheric Particulate Matter in the Aqueous Phase.

This study focused on the photoaging of atmospheric particulate matter smaller than 2.5 µm (PM2.5) in the aqueous phase. PM2.5 was collected during a winter, a spring, and a summer campaign in urban and rural settings in Colorado and extracted into water. The aqueous extracts were photoirradiated using simulated sunlight, and the production rate (r•OH) and the effects of hydroxyl radicals (•OH) were measured as well as the optical properties as a function of the photoaging of the extracts. r•OH was seen to have a strong seasonality with low mean values for the winter and spring extracts (4.8 and 14 fM s-1 mgC-1 L, respectively) and a higher mean value for the summer extracts (65.4 fM s-1 mgC-1 L). For the winter extracts, •OH was seen to mostly originate from nitrate photolysis while for the summer extracts, a correlation was seen between r•OH and iron concentration. The extent of photobleaching of the extracts was correlated with r•OH, and the correlation also indicated that non-•OH processes took place. Using the •OH measurements and singlet oxygen (1O2) measurements, the half-life of a selection of compounds was modeled in the atmospheric aqueous phase to be between 1.9 and 434 h.

Updated Emission Factors from Diffuse Combustion Sources in Sub-Saharan Africa and Their Effect on Regional Emission Estimates.

Diffuse emission sources outside of kitchen areas are poorly understood, and measurements of their emission factors (EFs) are sparse for regions of sub-Saharan Africa. Thirty-one in-field emission measurements were taken in northern Ghana from combustion sources common to rural regions worldwide. Sources sampled included commercial cooking, trash burning, kerosene lanterns, and diesel generators. EFs were calculated for carbon monoxide (CO), carbon dioxide (CO2), as well as carbonaceous particulate matter, specifically elemental carbon (EC) and organic carbon (OC). EC and OC emissions were measured from kerosene lighting events (EFEC = 25.1 g/kg-fuel SD = 25.7, EFOC = 9.5 g/kg-fuel SD = 10.0). OC emissions from trash burning events were large and highly variable (EFOC = 38.9 g/kg-fuel SD = 30.5). Combining our results with other recent in-field emission factors for rural Ghana, we explored updated emission estimates for Ghana using a region specific emissions inventory. Large differences are calculated for all updated source emissions, showing a 96% increase in OC and 78% decrease in EC compared to prior estimates for Ghana's emissions. Differences for carbon monoxide were small when averaged across all updated source types (-1%), though the household wood use and trash burning categories individually show large differences.

Light absorption of organic carbon and its sources at a southeastern U.S. location in summer.

Light-absorbing organic carbon (OC), also referred to as "brown carbon" (BrC), has been intensively investigated in atmospheres impacted by biomass burning. However, other BrC sources (e.g., secondary formation in the atmosphere) are rarely studied in ambient aerosols. In the current work, forty-five PM2.5 filter samples were collected in Research Triangle Park (RTP), NC, USA from June 1st to July 15th, 2013. The bulk carbonaceous components, including OC, elemental carbon (EC), water soluble OC (WSOC), and an array of organic molecular markers were measured; an ultraviolet/visible spectrometer was used to measure the light absorption of methanol extractable OC and WSOC. The average light absorption per OC and WSOC mass of PM2.5 samples in summer RTP are 0.36 ±â€¯0.16 m2 gC-1 and 0.29 ±â€¯0.13 m2 gC-1, respectively, lower than the ambient aerosol samples impacted by biomass burning and/or fossil fuel combustion (0.7-1.6 m2 gC-1) from other places. Less than 1% of the aqueous extracts absorption is attributed to the light-absorbing chromophores (nitroaromatic compounds) identified in this work. To identify the major sources of BrC absorption in RTP in the summer, Positive Matrix Factorization (PMF) was applied to a dataset containing optical properties and chemical compositions of carbonaceous components in PM2.5. The results suggest that the formation of biogenic secondary organic aerosol (SOA) containing organosulfates is an important BrC source, contributing up to half of the BrC absorption in RTP during the summertime.

Prices, peers, and perceptions (P3): study protocol for improved biomass cookstove project in northern Ghana.

BACKGROUND: Despite their potential health and social benefits, adoption and use of improved cookstoves has been low throughout much of the world. Explanations for low adoption rates of these technologies include prices that are not affordable for the target populations, limited opportunities for households to learn about cookstoves through peers, and perceptions that these technologies are not appropriate for local cooking needs. The P3 project employs a novel experimental design to explore each of these factors and their interactive effects on cookstove demand, adoption, use and exposure outcomes. METHODS: The P3 study is being conducted in the Kassena-Nankana Districts of Northern Ghana. Leveraging an earlier improved cookstove study that was conducted in this area, the central design of the P3 biomass stove experiment involves offering stoves at randomly varying prices to peers and non-peers of households that had previously received stoves for free. Using household surveys, electronic stove use monitors, and low-cost, portable monitoring equipment, we measure how prices and peers' experience affect perceptions of stove quality, the decision to purchase a stove, use of improved and traditional stoves over time, and personal exposure to air pollutants from the stoves. DISCUSSION: The challenges that public health and development communities have faced in spreading adoption of potentially welfare-enhancing technologies, like improved cookstoves, have highlighted the need for interdisciplinary, multisectoral approaches. The design of the P3 project draws on economic theory, public health practice, engineering, and environmental sciences, to more fully grasp the drivers and barriers to expanding access to and uptake of cleaner stoves. Our partnership between academic institutions, in the US and Ghana, and a local environmental non-governmental organization creates unique opportunities to disseminate and scale up lessons learned. TRIAL REGISTRATION: ClinicalTrials.gov NCT03617952 7/31/18 (Retrospectively Registered).

Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments.

Low-cost sensors have the potential to facilitate the exploration of air quality issues on new temporal and spatial scales. Here we evaluate a low-cost sensor quantification system for methane through its use in two different deployments. The first was a one-month deployment along the Colorado Front Range and included sites near active oil and gas operations in the Denver-Julesberg basin. The second deployment was in an urban Los Angeles neighborhood, subject to complex mixtures of air pollution sources including oil operations. Given its role as a potent greenhouse gas, new low-cost methods for detecting and monitoring methane may aid in protecting human and environmental health. In this paper, we assess a number of linear calibration models used to convert raw sensor signals into ppm concentration values. We also examine different choices that can be made during calibration and data processing, and explore cross-sensitivities that impact this sensor type. The results illustrate the accuracy of the Figaro TGS 2600 sensor when methane is quantified from raw signals using the techniques described. The results also demonstrate the value of these tools for examining air quality trends and events on small spatial and temporal scales as well as their ability to characterize an area - highlighting their potential to provide preliminary data that can inform more targeted measurements or supplement existing monitoring networks.

New Emission Factors and Efficiencies from in-Field Measurements of Traditional and Improved Cookstoves and Their Potential Implications.

Household cooking using solid biomass fuels is a major global health and environmental concern. As part of the Research on Emissions Air quality Climate and Cooking Technologies in Northern Ghana study, we conducted 75 in-field uncontrolled cooking tests designed to assess emissions and efficiency of the Gyapa woodstove, Philips HD4012, threestone fire and coalpot (local charcoal stove). Emission factors (EFs) were calculated for carbon monoxide (CO), carbon dioxide (CO2), and particulate matter (PM). Moreover, modified combustion (MCE), heat transfer (HTE) and overall thermal efficiencies (OTE) were calculated across a variety of fuel, stove and meal type combinations. Mixed effect models suggest that compared to traditional stove/fuel combinations, the Philips burning wood or charcoal showed significant fuel and energy based EF differences for CO, but no significant PM changes with wood fuel. MCEs were significantly higher for Philips wood and charcoal-burning stoves compared to the threestone fire and coalpot. The Gyapa emitted significantly higher ratios of elemental to organic carbon. Fuel moisture, firepower and MCE fluctuation effects on stove performance were investigated with mixed findings. Results show agreement with other in-field findings and discrepancies with some lab-based findings, with important implications for estimated health and air quality impacts.

Improving present day and future estimates of anthropogenic sectoral emissions and the resulting air quality impacts in Africa.

The African continent is undergoing immense social and economic change, particularly regarding population growth and urbanization, where the urban population in Africa is anticipated to increase by a factor of 3 over the next 40 years. To understand the potential health impacts from this demographical shift and design efficient emission mitigation strategies, we used improved Africa-specific emissions that account for inefficient combustion sources for a number of sectors such as transportation, household energy generation, waste burning, and home heating and cooking. When these underrepresented emissions sources are combined with the current estimates of emissions in Africa, ambient particulate matter concentrations from present-day anthropogenic activity contribute to 13 210 annual premature deaths, with the largest contributions (38%) coming from residential emissions. By scaling both the population and the emissions for projected national-scale levels of growth, the predicted health impact grows to approximately 78 986 annual premature deaths by 2030 with 45% now resulting from emissions related to energy combustion. In order to mitigate this resulting increase in premature deaths, three scenarios have been developed which reduce sector-specific future emissions based on prior targets for technological improvements and emission controls in transportation, energy production and residential activities. These targeted potential mitigation strategies can avoid up to 37% of the estimated annual premature deaths by 2030 with the largest opportunity being a reduction of 10 868 annual deaths from switching half of the energy generation in South Africa to renewable technologies.

Water soluble organic aerosols in the Colorado Rocky Mountains, USA: composition, sources and optical properties.

Atmospheric aerosols have been shown to be an important input of organic carbon and nutrients to alpine watersheds and influence biogeochemical processes in these remote settings. For many remote, high elevation watersheds, direct evidence of the sources of water soluble organic aerosols and their chemical and optical characteristics is lacking. Here, we show that the concentration of water soluble organic carbon (WSOC) in the total suspended particulate (TSP) load at a high elevation site in the Colorado Rocky Mountains was strongly correlated with UV absorbance at 254 nm (Abs254, r = 0.88 p < 0.01) and organic carbon (OC, r = 0.95 p < 0.01), accounting for >90% of OC on average. According to source apportionment analysis, biomass burning had the highest contribution (50.3%) to average WSOC concentration; SOA formation and motor vehicle emissions dominated the contribution to WSOC in the summer. The source apportionment and backward trajectory analysis results supported the notion that both wildfire and Colorado Front Range pollution sources contribute to the summertime OC peaks observed in wet deposition at high elevation sites in the Colorado Rocky Mountains. These findings have important implications for water quality in remote, high-elevation, mountain catchments considered to be our pristine reference sites.

The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study.

BACKGROUND: Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Daily concentrations of PM2.5 components were measured over five years in Denver to investigate whether specific PM2.5 components are associated with daily mortality. METHODS: Daily counts of total and cause-specific deaths were obtained for the 5-county Denver metropolitan region from 2003 through 2007. Daily 24-hour concentrations of PM2.5, elemental carbon (EC), organic carbon (OC), sulfate and nitrate were measured at a central residential monitoring site. Using generalized additive models, we estimated relative risks (RRs) of daily death counts for daily PM2.5 and four PM2.5 component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology. RESULTS: RR of total non-accidental mortality for an inter-quartile increase of 4.55 µg/m(3) in PM2.5 distributed over 4 days was 1.012 (95 % confidence interval: 0.999, 1.025); RRs for EC and OC were larger (1.024 [1.005, 1.043] and 1.020 [1.000, 1.040] for 0.33 and 1.67 µg/m(3) increases, respectively) than those for sulfate and nitrate. We generally did not observe associations with cardiovascular and respiratory mortality except for associations with ischemic heart disease mortality at lags 3 and 0-3 depending on the component. In addition, there were associations with cancer mortality, particularly for EC and OC, possibly reflecting advanced deaths of a frail population. CONCLUSIONS: PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.

Comparing multipollutant emissions-based mobile source indicators to other single pollutant and multipollutant indicators in different urban areas.

A variety of single pollutant and multipollutant metrics can be used to represent exposure to traffic pollutant mixtures and evaluate their health effects. Integrated mobile source indicators (IMSIs) that combine air quality concentration and emissions data have recently been developed and evaluated using data from Atlanta, Georgia. IMSIs were found to track trends in traffic-related pollutants and have similar or stronger associations with health outcomes. In the current work, we apply IMSIs for gasoline, diesel and total (gasoline + diesel) vehicles to two other cities (Denver, Colorado and Houston, Texas) with different emissions profiles as well as to a different dataset from Atlanta. We compare spatial and temporal variability of IMSIs to single-pollutant indicators (carbon monoxide (CO), nitrogen oxides (NOx) and elemental carbon (EC)) and multipollutant source apportionment factors produced by Positive Matrix Factorization (PMF). Across cities, PMF-derived and IMSI gasoline metrics were most strongly correlated with CO (r = 0.31-0.98), while multipollutant diesel metrics were most strongly correlated with EC (r = 0.80-0.98). NOx correlations with PMF factors varied across cities (r = 0.29-0.67), while correlations with IMSIs were relatively consistent (r = 0.61-0.94). In general, single-pollutant metrics were more correlated with IMSIs (r = 0.58-0.98) than with PMF-derived factors (r = 0.07-0.99). A spatial analysis indicated that IMSIs were more strongly correlated (r > 0.7) between two sites in each city than single pollutant and PMF factors. These findings provide confidence that IMSIs provide a transferable, simple approach to estimate mobile source air pollution in cities with differing topography and source profiles using readily available data.

Impact of gas/particle partitioning of semivolatile organic compounds on source apportionment with positive matrix factorization.

To quantify and minimize the influence of gas/particle (G/P) partitioning on receptor-based source apportionment using particle-phase semivolatile organic compound (SVOC) data, positive matrix factorization (PMF) coupled with a bootstrap technique was applied to three data sets mainly composed of "measured-total" (measured particle- + gas-phase), "particle-only" (measured particle-phase) and "predicted-total" (measured particle-phase + predicted gas-phase) SVOCs to apportion carbonaceous aerosols. Particle- (PM2.5) and gas-phase SVOCs were collected using quartz fiber filters followed by PUF/XAD-4/PUF adsorbents and measured using gas chromatography-mass spectrometry (GC-MS). Concentrations of gas-phase SVOCs were also predicted from their particle-phase concentrations using absorptive partitioning theory. Five factors were resolved for each data set, and the factor profiles were generally consistent across the three PMF solutions. Using a previous source apportionment study at the same receptor site, those five factors were linked to summertime biogenic emissions (odd n-alkane factor), unburned fossil fuels (light SVOC factor), road dust and/or cooking (n-alkane factor), motor vehicle emissions (PAH factor), and lubricating oil combustion (sterane factor). The "measured-total" solution was least influenced by G/P partitioning and used as reference. Two out of the five factors (odd n-alkane and PAH factors) exhibited consistent contributions for "particle-only" vs "measured-total" and "predicted-total" vs "measured-total" solutions. Factor contributions of light SVOC and n-alkane factors were more consistent for "predicted-total" vs "measured-total" than "particle-only" vs "measured-total" solutions. The remaining factor (sterane factor) underestimated the contribution by around 50% from both "particle-only" and "predicted-total" solutions. The results of this study confirm that when measured gas-phase SVOCs are not available, "predicted-total" SVOCs should be used to decrease the influence of G/P partitioning on receptor-based source apportionment.

Gas/particle partitioning of 2-methyltetrols and levoglucosan at an urban site in Denver.

In this study, a medium volume sampler incorporating quartz fiber filters (QFFs) and a polyurethane foam (PUF)/XAD/PUF sandwich (PXP) was used to collect 2-methyltetrols (isoprene tracer) and levoglucosan (biomass burning tracer) in gaseous and particle (PM2.5) phases. The measured gas/particle (G/P) partitioning coefficients (Kp,OMm) of 2-methyltetrols and levoglucosan were calculated and compared to their predicted G/P partitioning coefficients (Kp,OMt) based on an absorptive partitioning theory. The breakthrough experiments showed that gas-phase 2-methyltetrols and levoglucosan could be collected using the PXP or PUF adsorbent alone, with low breakthrough; however, the recoveries of levoglucosan in PXP samples were lower than 70% (average of 51.9­63.3%). The concentration ratios of 2-methyltetrols and levoglucosan in the gas phase to those in the particle phase were often close to or higher than unity in summer, indicating that these polar species are semi-volatile and their G/P partitioning should be considered when applying particle-phase data for source apportionment. The Kp,OMm values of 2-methyltetrols had small variability in summer Denver, which was ascribed to large variations in concentrations of particulate organic matter (5.14 ± 3.29 µg m­3) and small changes in ambient temperature (21.8 ± 4.05 °C). The regression between log Kp,OMm and log Kp,OMt suggested that the absorptive G/P partitioning theory could reasonably predict the measured G/P partitioning of levoglucosan in ambient samples.

Seasonal variability in bacterial and fungal diversity of the near-surface atmosphere.

Bacteria and fungi are ubiquitous throughout the Earth's lower atmosphere where they often represent an important component of atmospheric aerosols with the potential to impact human health and atmospheric dynamics. However, the diversity, composition, and spatiotemporal dynamics of these airborne microbes remain poorly understood. We performed a comprehensive analysis of airborne microbes across two aerosol size fractions at urban and rural sites in the Colorado Front Range over a 14-month period. Coarse (PM10-2.5) and fine (PM2.5) particulate matter samples were collected at weekly intervals with both bacterial and fungal diversity assessed via high-throughput sequencing. The diversity and composition of the airborne communities varied across the sites, between the two size fractions, and over time. Bacteria were the dominant type of bioaerosol in the collected air samples, while fungi and plants (pollen) made up the remainder, with the relative abundances of fungi peaking during the spring and summer months. As bacteria made up the majority of bioaerosol particles, we analyzed the bacterial communities in greater detail using a bacterial-specific 16S rRNA gene sequencing approach. Overall, bacterial taxonomic richness and the relative abundances of specific bacterial taxa exhibited significant patterns of seasonality. Likewise, airborne bacterial communities varied significantly between sites and across aerosol size fractions. Source-tracking analyses indicate that soils and leaves represented important sources of bacteria to the near-surface atmosphere across all locations with cow fecal bacteria also representing an important source of bioaerosols at the more rural sites during early fall and early spring. Together, these data suggest that a complex set of environmental factors, including changes in atmospheric conditions and shifts in the relative importance of available microbial sources, act to control the composition of microbial bioaerosols in rural and urban environments.

The sensitivity of health effect estimates from time-series studies to fine particulate matter component sampling schedule.

The US Environmental Protection Agency air pollution monitoring data have been a valuable resource commonly used for investigating the associations between short-term exposures to PM2.5 chemical components and human health. However, the temporally sparse sampling on every third or sixth day may affect health effect estimation. We examined the impact of non-daily monitoring data on health effect estimates using daily data from the Denver Aerosol Sources and Health (DASH) study. Daily concentrations of four PM2.5 chemical components (elemental and organic carbon, sulfate, and nitrate) and hospital admission counts from 2003 through 2007 were used. Three every-third-day time series were created from the daily DASH monitoring data, imitating the US Speciation Trend Network (STN) monitoring schedule. A fourth, partly irregular, every-third-day time series was created by matching existing sampling days at a nearby STN monitor. Relative risks (RRs) of hospital admissions for PM2.5 components at lags 0-3 were estimated for each data set, adjusting for temperature, relative humidity, longer term temporal trends, and day of week using generalized additive models, and compared across different sampling schedules. The estimated RRs varied somewhat between the non-daily and daily sampling schedules and between the four non-daily schedules, and in some instances could lead to different conclusions. It was not evident which features of the data or analysis were responsible for the variation in effect estimates, although seeing similar variability in resampled data sets with relaxation of the every-third-day constraint suggests that limited power may have had a role. The use of non-daily monitoring data can influence interpretation of estimated effects of PM2.5 components on hospital admissions in time-series studies.

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods.

In studies of coarse particulate matter (PM10-2.5), mass concentrations are often estimated through the subtraction of PM2.5 from collocated PM10 tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM10-2.5 estimation when using the possible combinations of PM10 and PM2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM10-2.5 mass and spatial characteristics due to the very low semivolatile PM10-2.5 concentrations in Colorado. Estimation using either a PM2.5 or PM10 monitor without FDMS introduced absolute biases of 2.4 microg/m3 (25%) to -2.3 microg/m3 (-24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM2.5 TEOM and PM10 TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM2.5 from total PM2.5 concentrations. By estimating nonvolatile PM2.5 concentrations from this relationship, PM10-2.5 was calculated as the difference between nonvolatile PM10 and PM2.5 concentrations.

Positive matrix factorization of a 32-month series of daily PM2.5 speciation data with incorporation of temperature stratification.

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.

Positive matrix factorization of PM(2.5): comparison and implications of using different speciation data sets.

To evaluate the utility and consistency of different speciation data sets in source apportionment of PM(2.5), positive matrix factorization (PMF) coupled with a bootstrap technique for uncertainty assessment was applied to four different 1-year data sets composed of bulk species, bulk species and water-soluble elements (WSE), bulk species and organic molecular markers (OMM), and all species. The five factors resolved by using only the bulk species best reproduced the observed concentrations of PM(2.5) components. Combining WSE with bulk species as PMF inputs also produced five factors. Three of them were linked to soil, road dust, and processed dust, and together contributed 26.0% of reconstructed PM(2.5) mass. A 7-factor PMF solution was identified using speciated OMM and bulk species. The EC/sterane and summertime/selective aliphatic factors had the highest contributions to EC (39.0%) and OC (53.8%), respectively. The nine factors resolved by including all species as input data are consistent with those from the previous two solutions (WSE and bulk species, OMM and bulk species) in both factor profiles and contributions (r = 0.88-1.00). The comparisons across different solutions indicate that the selection of input data set may depend on the PM components or sources of interest for specific source-oriented health study.

The temporal lag structure of short-term associations of fine particulate matter chemical constituents and cardiovascular and respiratory hospitalizations.

BACKGROUND: 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. OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.