Transport of atmospheric fine particulate matter: part 1--findings from recent field programs on the extent of regional transport within North America

A comprehensive SERS, SEM and EDX study of individual atmospheric PM2.5 particles in Chengdu, China

Characterization of atmospheric fine particulate matter (PM_2.5) in large cities has important implications for the study of their sources and formation mechanisms, as well as in developing effective measures to control air pollution. Herein, we report a holistic physical and chemical characterization of PM_2.5 by combining surface-enhanced Raman scattering (SERS) with scanning electron microscopy (SEM) and electron-induced X-ray spectroscopy (EDX). PM_2.5 particles were collected in a suburban area of Chengdu, a large city in China with a population over 21 million. A special SERS chip composed of inverted hollow Au cone (IHAC) arrays was designed and fabricated to allow direct loading of PM_2.5 particles. SERS and EDX were used to reveal the chemical composition, and particle morphologies were analyzed from SEM images. SERS data of atmospheric PM_2.5 indicated qualitatively the presence of carbonaceous particulate matter, sulfate, nitrate, metal oxides and bioparticles. The EDX showed the presence of the elements C, N, O, Fe, Na, Mg, Al, Si, S, K, and Ca in the collected PM_2.5. Morphology analysis showed that the particulates were mainly in the form of flocculent clusters, spherical, regular crystal shaped or irregularly shaped particles. Our chemical and physical analyses also revealed that the main sources of PM_2.5 are automobile exhaust, secondary pollution caused by photochemical reactions in the air, dust, emission from nearby industrial exhaust, biological particles, other aggregated particles, and hygroscopic particles. SERS and SEM data collected during three different seasons showed that carbon-containing particles are the principal sources of PM_2.5. Our study demonstrates that the SERS based technique, when combined with standard physicochemical characterization methods, is a powerful analytical tool to determine the sources of ambient PM_2.5 pollution. Results obtained in this work may be valuable to the prevention and control of PM_2.5 pollution in air.

Characterization of typical metal particles during haze episodes in Shanghai, China

Aerosol particles were collected during three heavy haze episodes at Shanghai in the winter of 2013. Transmission electron microscopy (TEM) coupled with energy dispersive X-ray spectroscopy was used to study the morphology and speciation of typical metal particles at a single-particle level. In addition, time-of-flight aerosol mass spectrometry (ATOFMS) was applied to identify the speciation of the Fe-containing particles. TEM analysis indicated that various metal-containing particles were hosted by sulfates, nitrates, and oxides. Fe-bearing particles mainly originated from vehicle emissions and/or steel production. Pb-, Zn-, and Sb-bearing particles were mainly contributed by anthropogenic sources. Fe-bearing particles were clustered into six groups by ATOFMS: Fe-Carbon, Fe-Inorganic, Fe-Trace metal, Fe-CN, Fe-PO_3, and Fe-NO₃. ATOFMS data suggested that Fe-containing particles corresponded to different origins, including industrial activities, resuspension of dusts, and vehicle emissions. Fe-Carbon and Fe-CN particles displayed significant diurnal variation, and high levels were observed during the morning rush hours. Fe-Inorganic and Fe-Trace metal particle levels peaked at night. Furthermore, Fe-Carbon and Fe-PO₃ were mainly concentrated in the fine particles. Fe-CN, Fe-Inorganic, and Fe-Trace metal exhibited bimodal distribution. The mixing state of the particles revealed that all Fe-bearing particles tended to be mixed with sulfate and nitrate. The data presented herein is essential for elucidating the origin, evolution processes, and health effects of metal-bearing particles.

Individual-level concentrations of fine particulate matter chemical components and subclinical atherosclerosis: a cross-sectional analysis based on 2 advanced exposure prediction models in the multi-ethnic study of atherosclerosis

Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches.

Challenges of studying viral aerosol metagenomics and communities in comparison with bacterial and fungal aerosols

Despite the obvious importance of viral transmission and ecology to medicine, epidemiology, ecology, agriculture, and microbiology, the study of viral bioaerosols and community structure has remained a vastly underexplored area, due to both unresolved technical challenges and unrecognized importance. High-throughput, culture-independent techniques such as viral metagenomics are beginning to revolutionize the study of viral ecology. With recent developments in viral metagenomics, characterization of viral bioaerosol communities provides an opportunity for high-impact future research. However, there remain significant challenges for the study of viral bioaerosols compared with viruses in other matrices, such as water, the human gut, and soil. Collecting enough biomass is essential for successful metagenomic analysis, but this is a challenge with viral bioaerosols. Herein, we provide a perspective on the importance of studying viral bioaerosols, the challenges of studying viral community structure, and the potential opportunities for improvements in methods to study viruses in indoor and outdoor air.

Endotoxin and polycyclic aromatic hydrocarbons in ambient fine particulate matter from Fresno, California initiate human monocyte inflammatory responses mediated by reactive oxygen species

In urban areas, a correlation between exposure to particulate matter (PM) from air pollution and increased cardiovascular morbidity and mortality has been observed. Components of PM include bacterial contaminants, transition metals, salts, polycyclic aromatic hydrocarbons (PAH), and carbonaceous material, which could interact with various cell types to produce systemic responses when inhaled. We examined the effects of PM collected from Fresno, California on activation of human monocytes and their interaction with vascular endothelium, a key event in atherogenesis. PM exposure increased cytokine expression and secretion from monocytes and enhanced monocyte adhesion to human aortic endothelial cells, both of which were attenuated by neutralizing endotoxin. PM also increased monocyte CYP1a1 expression, and inhibition of the aryl hydrocarbon receptor reduced the CYP1a1 and inflammatory responses. PM-treated monocytes accumulated intracellular reactive oxygen species (ROS), and antioxidants attenuated inflammatory and xenobiotic responses. Finally, supernatants from PM-treated pulmonary microvascular endothelial cells induced monocyte inflammatory responses that were not a consequence of endotoxin transfer. These results suggest that certain components of urban PM, namely endotoxin and PAH, activate circulating monocytes directly or indirectly by first stimulating other cells such as pulmonary endothelial cells, providing several mechanisms by which PM inhalation could induce pulmonary and/or systemic inflammation.

Impact of emissions from the Los Angeles port region on San Diego air quality during regional transport events

Oceangoing ships emit an estimated 1.2-1.6 million metric tons (Tg) of PM10 per year and represent a significant source of air pollution to coastal communities. As shown herein, ship and other emissions near the Los Angeles and Long Beach Port region strongly influence air pollution levels in the San Diego area. During time periods with regional transport, atmospheric aerosol measurements in La Jolla, California show an increase in 0.5-1 microm sized single particles with unique signatures including soot, metals (i.e., vanadium, iron, and nickel), sulfate, and nitrate. These particles are attributed to primary emissions from residual oil sourcessuch as ships and refineries, as well as traffic in the port region, and secondary processing during transport. During regional transport events, particulate matter concentrations were 2-4 times higher than typical average concentrations from local sources, indicating the health, environmental, and climate impacts from these emission sources must be taken into consideration in the San Diego region. Unless significant regulations are imposed on shipping-related activities, these emission sources will become even more important to California air quality as cars and truck emissions undergo further regulations and residual oil sources such as shipping continue to expand.

Predicting chronic fine and coarse particulate exposures using spatiotemporal models for the Northeastern and Midwestern United States

BACKGROUND

Chronic epidemiologic studies of particulate matter (PM) are limited by the lack of monitoring data, relying instead on citywide ambient concentrations to estimate exposures. This method ignores within-city spatial gradients and restricts studies to areas with nearby monitoring data. This lack of data is particularly restrictive for fine particles (PM with aerodynamic diameter < 2.5 microm; PM(2.5)) and coarse particles (PM with aerodynamic diameter 2.5-10 microm; PM(10-2.5)), for which monitoring is limited before 1999. To address these limitations, we developed spatiotemporal models to predict monthly outdoor PM(2.5) and PM(10-2.5) concentrations for the northeastern and midwestern United States.

METHODS

For PM(2.5), we developed models for two periods: 1988-1998 and 1999-2002. Both models included smooth spatial and regression terms of geographic information system-based and meteorologic predictors. To compensate for sparse monitoring data, the pre-1999 model also included predicted PM(10) (PM with aerodynamic diameter < 10 microm) and extinction coefficients (km(-1)). PM(10-2.5) levels were estimated as the difference in monthly predicted PM(10) and PM(2.5), with predicted PM(10) from our previously developed PM(10) model.

RESULTS

Predictive performance for PM(2.5) was strong (cross-validation R2 = 0.77 and 0.69 for post-1999 and pre-1999 PM(2.5) models, respectively) with high precision (2.2 and 2.7 microg/m3, respectively). Models performed well irrespective of population density and season. Predictive performance for PM(10-2.5) was weaker (cross-validation R2 = 0.39) with lower precision (5.5 microg/m3). PM(10-2.5) levels exhibited greater local spatial variability than PM(10) or PM(2.5), suggesting that PM(2.5) measurements at ambient monitoring sites are more representative for surrounding populations than for PM(10) and especially PM(10-2.5).

CONCLUSIONS

We provide semiempirical models to predict spatially and temporally resolved long-term average outdoor concentrations of PM(2.5) and PM(10-2.5) for estimating exposures of populations living in the northeastern and midwestern United States.