Quantification of the Hygroscopic Effect of Soot Aging in the Atmosphere: Laboratory Simulations

A satellite-driven model to estimate long-term particulate sulfate levels and attributable mortality burden in China

Ambient fine particulate matter (PM2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m-3. But the sulfate level dramatically decreased to 7.7 µg m-3 in 2018, with a change rate of -28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate.

Industrial and wildfire aerosol pollution over world heritage Lake Baikal

Lake Baikal is the biggest reservoir of fresh water with unique flora and fauna; presently it is negatively affected by climate change, water warming, industrial emissions, shipping, touristic activities, and Siberian forest fires. The assessment of air pollution - related Baikal's ecosystem damage is an unsolved problem. Ship, based expedition exploring the Baikal atmospheric aerosol loading, was performed over the lake area in July 2018. We combine the aerosol near - water and vertical distributions over the Lake Baikal basin with meteorological observations and air mass transportation simulations. Lidar sounding of aerosol fields in the troposphere assesses the atmospheric background in the pristine areas and the pollution during fire-affected periods. Aerosol optical properties (scattering and spectral absorption) converted to the particle number size, black carbon (BC) mass, and Absorption Angstrom Exponent (AAE) provide the inside into aerosol characterization. Transport of industrial emissions from Krasnoyarsk and Irkutsk regions, and wildfire plumes from Republic of Yakutia relates the pollution sources to the increased concentrations of fine particle numbers, PM₁₀ and BC mass over Southern and Northern/Central Baikal, respectively. The highest PM₁₀ and BC are associated to the harbor and touristic areas of intensive shipping and residential biomass burning. Deposition estimates applied to aerosol data exhibit the pollution fluxes to water surface over the whole Baikal area. AAE marks the impact of coal combustion, residential biomass burning, and wildfires indicating the high pollution level of the Lake Baikal ecological system .

Light-absorption enhancement of black carbon in the Asian outflow inferred from airborne SP2 and in-situ measurements during KORUS-AQ

We investigated the changes in the size distribution, coating thickness, and mass absorption cross-section (MAC) of black carbon (BC) with aging and estimated the light absorption enhancement (E_abs) in the Asian outflow from airborne in-situ measurements during 2016 KORUS-AQ campaign. The BC number concentration decreased, but mass mean diameter increased with increasing altitude in the West Coast (WC) and Seoul Metropolitan Area (SMA), reflecting the contrast between freshly emitted BC-containing particles at the surface and more aged aerosol associated with aggregation during vertical mixing and transport. Contradistinctively, BC number and mass size distributions were relatively invariant with altitude over the Yellow Sea (YS) because sufficiently aged BC from eastern China were horizontally transported to all altitudes over the YS, and there are no significant sources at the surface. The averaged inferred MAC of refractory BC in three regions reflecting differences in their size distributions increased to 9.8 ± 1.0 m² g^-1 (YS), 9.3 ± 0.9 m² g^-1 (WC), and 8.2 ± 0.9 m² g^-1 (SMA) as BC coating thickness increased from 20 nm to 120 nm. The absorption coefficient of BC calculated from the coating thickness and MAC were highly correlated with the filter-based absorption measurements with the slope of 1.16 and R² of 0.96 at 550 nm, revealing that the thickly coated BC had a large MAC and absorption coefficient. The E_abs due to the inferred coatings was estimated as 1.0-1.6, which was about 30% lower than those from climate models and laboratory experiments, suggesting that the increase in the BC absorption by the coatings in the Asian outflow is not as large as calculated in the previous studies. Organics contributed to the largest E_abs accounting for 69% (YS), 61% (WC), and 64% (SMA). This implies that organics are largely responsible for the lensing effect of BC rather than sulfates in the Asian outflow.

Associations between long-term exposure to PM2.5 component species and blood DNA methylation age in the elderly: The VA normative aging study

BACKGROUND

Long-term PM2.5 exposure and aging have been implicated in multiple shared diseases; studying their relationship is a promising strategy to further understand the adverse impact of PM2.5 on human health.

OBJECTIVE

We assessed the relationship of major PM2.5 component species (ammonium, elemental carbon, organic carbon, nitrate, and sulfate) with Horvath and Hannum DNA methylation (DNAm) age, two DNA methylation-based predictors of chronological age.

METHODS

This analysis included 552 participants from the Normative Aging Study with multiple visits between 2000 and 2011 (n=940 visits). We estimated 1-year PM2.5 species levels at participants' addresses using the GEOS-chem transport model. Blood DNAm-age was calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. We fit linear mixed-effects models, controlling for PM2.5 mass and lifestyle/environmental factors as fixed effects, with the adaptive LASSO penalty to identify PM2.5 species associated with DNAm-age.

RESULTS

Sulfate and ammonium were selected by the LASSO in the Horvath DNAm-age models. In a fully-adjusted multiple-species model, interquartile range increases in both 1-year sulfate (95%CI: 0.28, 0.74, P<0.0001) and ammonium (95%CI: 0.02, 0.70, P=0.04) levels were associated with at least a 0.36-year increase in Horvath DNAm-age. No PM2.5 species were selected by the LASSO in the Hannum DNAm-age models. Our findings persisted in sensitivity analyses including only visits with 1-year PM2.5 levels within US EPA national ambient air quality standards.

CONCLUSION

Our results demonstrate that sulfate and ammonium were most associated with Horvath DNAm-age and suggest that DNAm-age measures differ in their sensitivity to ambient particle exposures and potentially disease.

Novel Phenanthrene Sorption Mechanism by Two Pollens and Their Fractions

A pair of pollens (Nelumbo nucifera and Brassica campestris L.) and their fractions were characterized by elemental analysis and advanced solid-state (13)C NMR techniques and used as biosorbents for phenanthrene (Phen). Their constituents were largely aliphatic components (including sporopollenin), carbohydrates, protein, and lignin as estimated by (13)C NMR spectra of the investigated samples and the four listed biochemical classes. The structure of each nonhydrolyzable carbon (NHC) fraction is similar to that of sporopollenin. The sorption capacities are highly negatively related to polar groups largely derived from carbohydrates and protein but highly positively related to alkyl carbon, poly(methylene) carbon, and aromatic carbon largely derived from sporopollenin and lignin. The sorption capacities of the NHC fractions are much higher than previously reported values, suggesting that they are good sorbents for Phen. The Freundlich n values significantly decrease with increasing concentrations of poly(methylene) carbon, alkyl C, aromatic moieties, aliphatic components, and the lignin of the pollen sorbents, suggesting that aliphatic and aromatic structures and constituents jointly contribute to the increasing nonlinearity. To our knowledge, this is the first investigation of the combined roles of alkyl and aromatic moiety domains, composition, and accessibility on the sorption of Phen by pollen samples.

Indirect Nanoplasmonic Sensing to Probe with a High Sensitivity the Interaction of Water Vapor with Soot Aerosols

We demonstrate in this work that the indirect nanoplasmonic sensing lets us follow the adsorption/desorption of water molecules on soot particles that are a major contributor of the global warming. Increasing the relative humidity of the surrounding medium we measure a shift in wavelength of the localized surface plasmon resonance response of gold nanodisks on which soot particles are deposited. We show a singular and reversible blue shift with hydrophilic aircraft soot particles interpreted from a basic model as a reversible morphological change of the soot aggregates. This new method is highly sensitive and interesting to follow the change of optical properties of aerosols during their aging in the atmosphere, where they can adsorb and react with different gas molecules.