Alexandra M. Lai

Neither dust nor black carbon causing apparent albedo decline in Greenland's dry snow zone: Implications for MODIS C5 surface reflectance

Remote sensing observations suggest Greenland ice sheet (GrIS) albedo has declined since 2001, even in the dry snow zone. We seek to explain the apparent dry snow albedo decline. We analyze samples representing 2012–2014 snowfall across NW Greenland for black carbon and dust light-absorbing impurities (LAI) and model their impacts on snow albedo. Albedo reductions due to LAI are small, averaging 0.003, with episodic enhancements resulting in reductions of 0.01–0.02. No significant increase in black carbon or dust concentrations relative to recent decades is found. Enhanced deposition of LAI is not, therefore, causing significant dry snow albedo reduction or driving melt events. Analysis of Collection 5 Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data indicates that the decline and spectral shift in dry snow albedo contains important contributions from uncorrected Terra sensor degradation. Though discrepancies are mostly below the stated accuracy of MODIS products, they will require revisiting some prior conclusions with C6 data.

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. Womens 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 womens 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.

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.

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 Womens 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 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.

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 ± 11%) and exposures (31 ± 6%) in both seasons, and ambient PM2.5 in winter (20 ± 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 ± 14%), but was present in all samples (summer: 10 ± 3% [household], 13 ± 6% [exposures]; winter: 18 ± 2% [ambient], 7 ± 2% [household], 8 ± 2% [exposures]). Dust concentrations and fractional contribution to total PM2.5 were higher in summer exposure samples (7 ± 4%) than in ambient or household samples (6 ± 1% and 2 ± 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.

Source apportionment of PM 2.5 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.