Impacts of stove/fuel use and outdoor air pollution on chemical composition of household particulate matter.

Biomass combustion for cooking and heating releases particulate matter (PM2.5 ) that contributes to household air pollution. Fuel and stove types affect the chemical composition of household PM, as does infiltration of outdoor PM. Characterization of these impacts can inform future exposure assessments and epidemiologic studies, but is currently limited. In this study, we measured chemical components of PM2.5 (water-soluble organic matter [WSOM], ions, black carbon, elements, organic tracers) in rural Chinese households using traditional biomass stoves, semi-gasifier stoves with pelletized biomass, and/or non-biomass stoves. We distinguished households using one stove type (traditional, semi-gasifier, or LPG/electric) from those using multiple stoves/fuels. WSOM concentrations were higher in households using only semi-gasifier or traditional stoves (31%-33%) than in those with exclusive LPG/electric stove (13%) or mixed stove use (12%-22%). Inorganic ions comprised 14% of PM in exclusive LPG/electric households, compared to 1%-5% of PM in households using biomass. Total PAH content was much higher in households that used traditional stoves (0.8-2.8 mg/g PM) compared to those that did not (0.1-0.3 mg/g PM). Source apportionment revealed that biomass burning comprised 27%-84% of PM2.5 in households using biomass. In all samples, identified outdoor sources (vehicles, dust, coal combustion, secondary aerosol) contributed 10%-20% of household PM2.5 .

Seasonal and Diurnal Air Pollution from Residential Cooking and Space Heating in the Eastern Tibetan Plateau.

Residential combustion of solid fuel is a major source of air pollution. In regions where space heating and cooking occur at the same time and using the same stoves and fuels, evaluating air-pollution patterns for household-energy-use scenarios with and without heating is essential to energy intervention design and estimation of its population health impacts as well as the development of residential emission inventories and air-quality models. We measured continuous and 48 h integrated indoor PM2.5 concentrations over 221 and 203 household-days and outdoor PM2.5 concentrations on a subset of those days (in summer and winter, respectively) in 204 households in the eastern Tibetan Plateau that burned biomass in traditional stoves and open fires. Using continuous indoor PM2.5 concentrations, we estimated mean daily hours of combustion activity, which increased from 5.4 h per day (95% CI: 5.0, 5.8) in summer to 8.9 h per day (95% CI: 8.1, 9.7) in winter, and effective air-exchange rates, which decreased from 18 ± 9 h(-1) in summer to 15 ± 7 h(-1) in winter. Indoor geometric-mean 48 h PM2.5 concentrations were over two times higher in winter (252 µg/m(3); 95% CI: 215, 295) than in summer (101 µg/m(3); 95%: 91, 112), whereas outdoor PM2.5 levels had little seasonal variability.

Assessment of forest fire impacts on carbonaceous aerosols using complementary molecular marker receptor models at two urban locations in California's San Joaquin Valley.

Two hundred sixty-three fine particulate matter (PM2.5) samples were collected over fourteen months in Fresno and Bakersfield, California. Samples were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and 160 organic molecular markers. Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) source apportionment models were applied to the results in order to understand monthly and seasonal source contributions to PM2.5 OC. Similar source categories were found from the results of the CMB and PMF models to PM2.5 OC across the sites. Six source categories with reasonably stable profiles, including biomass burning, mobile, food cooking, two different secondary organic aerosols (SOAs) (i.e., winter and summer), and forest fires were investigated. Both the CMB and the PMF models showed a strong seasonality in contributions of some sources, as well as dependence on wind transport for both sites. The overall relative source contributions to OC were 24% CMB wood smoke, 19% CMB mobile sources, 5% PMF food cooking, 2% CMB vegetative detritus, 17% PMF SOA summer, 22% PMF SOA winter, and 12% PMF forest fire. Back-trajectories using the Weather Research and Forecasting model combined with the FLEXible PARTicle dispersion model (WRF-FLEXPART) were used to further characterize wind transport. Clustering of the trajectories revealed dominant wind patterns associated with varying concentrations of the different source categories. The Comprehensive Air Quality Model with eXtensions (CAMx) was used to simulate aerosol transport from forest fires and thus confirm the impacts of individual fires, such as the Rough Fire, at the measurement sites.

Chemical composition and source apportionment of ambient, household, and personal exposures to PM2.5 in communities using biomass stoves in rural China.

Fine particulate matter (PM2.5) has health effects that may depend on its sources and chemical composition. Few studies have quantified the composition of personal and area PM2.5 in rural settings over the same time period. Yet, this information would shed important light on the sources influencing personal PM2.5 exposures. This study investigated the sources and chemical composition of 40 personal exposure, 40 household, and 36 ambient PM2.5 samples collected in the non-heating and heating seasons in rural southwestern China. Chemical analysis included black carbon (BC), water-soluble components (ions, organic carbon), elements, and organic tracers. Source apportionment was conducted using organic tracer concentrations in a Chemical Mass Balance model. Biomass burning was the largest identified PM2.5 source contributor to household (average, SD: 48 ±â€¯11%) and exposures (31 ±â€¯6%) in both seasons, and ambient PM2.5 in winter (20 ±â€¯4%). Food cooking also contributed to household and personal PM, reaching approximately half of the biomass contributions. Secondary inorganic aerosol was the major identified source in summertime ambient PM2.5 (32 ±â€¯14%), but was present in all samples (summer: 10 ±â€¯3% [household], 13 ±â€¯6% [exposures]; winter: 18 ±â€¯2% [ambient], 7 ±â€¯2% [household], 8 ±â€¯2% [exposures]). Dust concentrations and fractional contribution to total PM2.5 were higher in summer exposure samples (7 ±â€¯4%) than in ambient or household samples (6 ±â€¯1% and 2 ±â€¯1%, respectively). Indoor sources comprised up to one-fifth of ambient PM2.5, and outdoor sources (vehicles, secondary aerosols) contributed up to 15% of household PM2.5. While household sources were the main contributors to PM2.5 exposures in terms of mass, inorganic components of personal exposures differed from household samples. Based on these findings, health-focused initiatives to reduce harmful PM2.5 exposures may consider a coordinated approach to address both indoor and outdoor PM2.5 source contributors.

Seasonal variations in the oxidative stress and inflammatory potential of PM2.5 in Tehran using an alveolar macrophage model; The role of chemical composition and sources.

The current study was designed to assess the association between temporal variations in urban PM2.5 chemical composition, sources, and the oxidative stress and inflammatory response in an alveolar macrophage (AM) model. A year-long sampling campaign collected PM2.5 samples at the Sharif University in Tehran, Iran. PM-induced reactive oxygen species (ROS) production was measured both with an acellular dithiothreitol consumption assay (DTT-ROS; ranged from 2.1 to 9.3 nmoles min-1 m-3) and an in vitro macrophage-mediated ROS production assay (AM-ROS; ranged from 125 to 1213 µg Zymosan equivalents m-3). The production of tumor necrosis factor alpha (TNF-α; ranged from ~60 to 518 pg TNF-α m-3) was quantified as a marker of the inflammatory potential of the PM. PM-induced DTT-ROS and AM-ROS were substantially higher for the colder months' PM (1.5-fold & 3-fold, respectively) compared with warm season. Vehicular emission tracers, aliphatic diacids, and hopanes exhibited moderate correlation with ROS measures. TNF-α secretion exhibited a markedly different pattern than ROS activity with a 2-fold increase in the warm months compared to the rest of the year. Gasoline vehicles and residual oil combustion were moderately associated with both ROS measures (R ≥ 0.67, p < 0.05), while diesel vehicles exhibited a strong correlation with secreted TNF-α in the cold season (R = 0.89, p < 0.05). mRNA expression of fourteen genes including antioxidant response and pro-inflammatory markers were found to be differentially modulated in our AM model. HMOX1, an antioxidant response gene, was up-regulated throughout the year. Pro-inflammatory genes (e.g. TNF-α and IL1ß) were down-regulated in the cold season and displayed moderate to weak correlation with crustal elements (R > 0.5, p < 0.05). AM-ROS activity showed an inverse relationship with genes including SOD2, TNF, IL1ß and IL6 (R ≥ -0.66, p < 0.01). Our findings indicate that Tehran's PM2.5 has the potential to induce oxidative stress and inflammation responses in vitro. In the current study, these responses included NRF2, NF-κB and MAPK pathways.

Source apportionment of PM2.5 organic carbon in the San Joaquin Valley using monthly and daily observations and meteorological clustering.

Two hundred sixty-three fine particulate matter (PM2.5) samples collected on 3-day intervals over a 14-month period at two sites in the San Joaquin Valley (SJV) were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and organic molecular markers. A unique source profile library was applied to a chemical mass balance (CMB) source apportionment model to develop monthly and seasonally averaged source apportionment results. Five major OC sources were identified: mobile sources, biomass burning, meat smoke, vegetative detritus, and secondary organic carbon (SOC), as inferred from OC not apportioned by CMB. The SOC factor was the largest source contributor at Fresno and Bakersfield, contributing 44% and 51% of PM mass, respectively. Biomass burning was the only source with a statistically different average mass contribution (95% CI) between the two sites. Wintertime peaks of biomass burning, meat smoke, and total OC were observed at both sites, with SOC peaking during the summer months. Exceptionally strong seasonal variation in apportioned meat smoke mass could potentially be explained by oxidation of cholesterol between source and receptor and trends in wind transport outlined in a Residence Time Analysis (RTA). Fast moving nighttime winds prevalent during warmer months caused local emissions to be replaced by air mass transported from the San Francisco Bay Area, consisting of mostly diluted, oxidized concentrations of molecular markers. Good agreement was observed between SOC derived from the CMB model and from non-biomass burning WSOC mass, suggesting the CMB model is sufficiently accurate to assist in policy development. In general, uncertainty in monthly mass values derived from daily CMB apportionments were lower than that of CMB results produced with monthly marker composites, further validating daily sampling methodologies. Strong seasonal trends were observed for biomass and meat smoke OC apportionment, and monthly mass averages had lowest uncertainty when derived from daily CMB apportionments.

Seasonal trends in the composition and sources of PM2.5 and carbonaceous aerosol in Tehran, Iran.

Currently PM2.5 is a major air pollution concern in Tehran, Iran due to frequent high levels and possible adverse impacts. In this study, which is the first of its kind to take place in Tehran, composition and sources of PM2.5 and carbonaceous aerosol were determined, and their seasonal trends were studied. In this regard, fine PM samples were collected every six days at a residential station for one year and the chemical constituents including organic marker species, metals, and ions were analyzed by chemical analysis. The source apportionment was performed using organic molecular marker-based CMB receptor modeling. Carbonaceous compounds were the major contributors to fine particulate mass in Tehran, as OC and EC together comprised on average 29% of PM2.5 mass. Major portions of OC in Tehran were water insoluble and are mainly attributed to primary sources. Higher levels of several PAHs, which are organic tracers of incomplete combustion, and hopanes and steranes as organic tracers of mobile sources were obtained in cold months and compared to the warm months. The major contributing source to particulate OC was identified as vehicles, which contributed about 72% of measured OC. Among mobile sources, gasoline-fueled vehicles had the highest impact with a mean contribution of 48% to the measured OC. Mobile sources also were the largest contributor to total PM2.5 (40%), followed by dust (24%) and sulfate (11%). In addition to primary emissions, mobile sources also directly and indirectly played an important role in another 27% of fine particulate mass (secondary organics and ions), which highlights the impact of vehicles in Tehran. Our results highlighted and quantified the role of motor vehicles in fine PM production, particularly during winter time. The results of this study could be used to set more effective regulations and control strategies particularly upon mobile sources.

The oxidative potential of PM2.5 exposures from indoor and outdoor sources in rural China.

BACKGROUND: Airborne particulate matter (PM) is a widespread environmental exposure and leading health risk factor. The health effects of PM may be mediated by its oxidative potential; however, the combustion and non-combustion sources and components of PM responsible for its oxidative potential are poorly understood, particularly in low- and middle-income rural settings where coal and biomass burning for cooking and heating contribute to PM exposure. METHODS: We measured 24-h personal exposures to fine particulate matter (PM2.5) of 20 rural women in northern (Inner Mongolia) and southern (Sichuan) Chinese provinces who used solid fuels (i.e., coal, biomass). PM2.5 exposures were characterized for mass, black carbon, water-soluble organic carbon, major water-soluble ions, and 47 elements. The oxidative potential of PM2.5 exposures was measured using acellular (dithiothreitol-based) and cellular (macrophage-based) assays. We performed factor and correlation analyses using the chemical components of PM2.5 to identify sources of exposure to PM2.5 and their chemical markers. Associations between oxidative potential and chemical markers for major sources of PM2.5 exposure were assessed using linear regression models. RESULTS: Women's geometric mean PM2.5 exposures were 249µgm(-3) (range: 53.9-767) and 83.9µgm(-3) (range: 73.1-95.5) in Inner Mongolia and Sichuan, respectively. Dust, biomass combustion, and coal combustion were identified as the major sources of exposure to PM2.5. Markers for dust (iron, aluminum) were significantly associated with intrinsic oxidative potential [e.g., one interquartile range increase in iron (ppm) was associated with an 85.5% (95% CI: 21.5, 149) increase in cellular oxidative potential (µgZymosanmg(-1))], whereas markers for coal (arsenic, non-sulfate sulfur) and biomass (black carbon, cadmium) combustion were not associated with oxidative potential. CONCLUSIONS: Dust was largely responsible for the intrinsic oxidative potential of PM2.5 exposures of rural Chinese women, whereas biomass and coal combustion were not significantly associated with intrinsic oxidative potential.

Seasonal variation in outdoor, indoor, and personal air pollution exposures of women using wood stoves in the Tibetan Plateau: Baseline assessment for an energy intervention study.

Cooking and heating with coal and biomass is the main source of household air pollution in China and a leading contributor to disease burden. As part of a baseline assessment for a household energy intervention program, we enrolled 205 adult women cooking with biomass fuels in Sichuan, China and measured their 48-h personal exposure to fine particulate matter (PM2.5) and carbon monoxide (CO) in winter and summer. We also measured the indoor 48-h PM2.5 concentrations in their homes and conducted outdoor PM2.5 measurements during 101 (74) days in summer (winter). Indoor concentrations of CO and nitrogen oxides (NO, NO2) were measured over 48-h in a subset of ~80 homes. Women's geometric mean 48-h exposure to PM2.5 was 80µg/m(3) (95% CI: 74, 87) in summer and twice as high in winter (169µg/m(3) (95% CI: 150, 190), with similar seasonal trends for indoor PM2.5 concentrations (winter: 252µg/m(3); 95% CI: 215, 295; summer: 101µg/m(3); 95% CI: 91, 112). We found a moderately strong relationship between indoor PM2.5 and CO (r=0.60, 95% CI: 0.46, 0.72), and a weak correlation between personal PM2.5 and CO (r=0.41, 95% CI: -0.02, 0.71). NO2/NO ratios were higher in summer (range: 0.01 to 0.68) than in winter (range: 0 to 0.11), suggesting outdoor formation of NO2 via reaction of NO with ozone is a more important source of NO2 than biomass combustion indoors. The predictors of women's personal exposure to PM2.5 differed by season. In winter, our results show that primary heating with a low-polluting fuel (i.e., electric stove or wood-charcoal) and more frequent kitchen ventilation could reduce personal PM2.5 exposures. In summer, primary use of a gaseous fuel or electricity for cooking and reducing exposure to outdoor PM2.5 would likely have the greatest impacts on personal PM2.5 exposure.