Characterization of products formed in the reaction of ozone with alpha-pinene: case for organic peroxides

The generation of reactive oxygen species (ROS) and their subsequent induced pulmonary and systemic oxidative stress has been implicated as an important molecular mechanism of PM-mediated toxicity. However, recent work has shown that there is significant ROS associated with ambient PM. In order to understand the formation mechanisms as well as understand the potential health effects of particle-bound oxidative species, the alpha-pinene-O(3) oxidation chemical system was studied to elucidate the structures of reaction products using liquid chromatography-multiple stage mass spectrometry (LC-MS(n)). The classes of compounds identified based on their multiple stage-MS fragmentation patterns, mechanistic considerations of alpha-pinene-O(3) oxidation, and general fragmentation rules, of the products from this reaction system were highly oxygenated species, predominantly containing hydroperoxide and peroxide functional groups. The oxidant species observed were clearly stable for the 1-3 h that elapsed during aerosol collection and analysis, and probably for much longer, thus rendering it possible for these species to bind onto particles forming fine particulate organic peroxides that concentrate on the particles and could deliver concentrated doses of ROS in vivo to tissue.     

The detection of SARS-CoV-2 RNA in indoor air of dental clinics during the COVID-19 pandemic

Environmental Science and Pollution Research - In the indoor environment of dental clinics, dental personnel and patients are exposed to a risk of infection because of the transmission of...     

Determination of the sources of toxic elements in environmental particles using microscopic and statistical analysis techniques

Samples of urban dust were physically fractionated into subsamples having unique size, density, ferromagnetism, and elemental compositional characteristics. The high density fractions containing the majority of each of the potentially toxic metals (Pb, Cd, Zn, Cr, Co, Mn) were subjected to X-ray microanalysis and to bulk analysis using instrumental neutron activation. Microanalysis was used to classify individual particles with respect to primary sources. The bulk analytical results were subjected to factor analysis to delineate the underlying factors (particle sources) responsible for the compositional variation in the subsamples. The advantages of the combined use of microanalytical and statistical techniques for source definition are described. X-ray microanalysis is used to substantiate the attribution of a given factor to a suspected particle source, to aid in the determination of the number of factors (sources) present, and to assess the extent to which a given factor represents a unique source of particles. Bulk analysis/factor analysis promotes the most effective use of X-ray microanalysis to characterize major particle types, and provides data on some toxic trace metals (e.g., Cd) that are not detectable using X-ray microanalysis. Target transformation factor analysis also is more useful in the quantitative determination of the relative mass contributions of major sources to the total dust sample.     

Estimation of organic carbon blank values and error structures of the speciation trends network data for source apportionment

Because the particulate organic carbon (OC) concentrations reported in U.S. Environment Protection Agency Speciation Trends Network (STN) data were not blank corrected, the OC blank concentrations were estimated using the intercept in particulate matter < or = 2.5 microm in aerodynamic diameter (PM2.5) regression against OC concentrations. The estimated OC blank concentrations ranged from 1 to 2.4 microg/m3 showing higher values in urban areas for the 13 monitoring sites in the northeastern United States. In the STN data, several different samplers and analyzers are used, and various instruments show different method detection limit (MDL) values, as well as errors. A comprehensive set of error structures that would be used for numerous source apportionment studies of STN data was estimated by comparing a limited set of measured concentrations and their associated uncertainties. To examine the estimated error structures and investigate the appropriate MDL values, PM2.5 samples collected at a STN site in Burlington, VT, were analyzed through the application of the positive matrix factorization. A total of 323 samples that were collected between December 2000 and December 2003 and 49 species based on several variable selection criteria were used, and eight sources were successfully identified in this study with the estimated error structures and min values among different MDL values from the five instruments: secondary sulfate aerosol (41%), secondary nitrate aerosol (20%), airborne soil (15%), gasoline vehicle emissions (7%), diesel emissions (7%), aged sea salt (4%), copper smelting (3%), and ferrous smelting (2%). Time series plots of contributions from airborne soil indicate that the highly elevated impacts from this source were likely caused primarily by dust storms.     

Source apportionment of fine particles in Washington, DC, utilizing temperature-resolved carbon fractions

Integrated ambient particulate matter < or =2.5 microm in aerodynamic diameter (PM2.5) samples were collected at a centrally located urban monitoring site in Washington, DC, on Wednesdays and Saturdays using Interagency Monitoring of Protected Visual Environments samplers. Particulate carbon was analyzed using the thermal optical reflectance method that divides carbon into four organic carbon fractions, pyrolyzed organic carbon, and three elemental carbon fractions. A total of 35 variables measured in 718 samples collected between August 1988 and December 1997 were analyzed. The data were analyzed using Positive Matrix Factorization and 10 sources were identified: sulfate (SO4(2-))-rich secondary aerosol I (43%), gasoline vehicle (21%), SO4(2-)-rich secondary aerosol II (11%), nitrate-rich secondary aerosol (9%), SO4(2-)-rich secondary aerosol III (6%), incinerator (4%), aged sea salt (2%), airborne soil (2%), diesel emissions (2%), and oil combustion (2%). In contrast to a previous study that included only total organic carbon and elemental carbon fractions, motor vehicles were separated into fractions identified as gasoline vehicle and diesel emissions containing carbon fractions whose abundances were different between the two sources. This study indicates that the temperature-resolved carbon fraction data can be utilized to enhance source apportionment, especially with respect to the separation of diesel emissions from gasoline vehicle sources. Conditional probability functions using surface wind data and deduced source contributions aid in the identifications of local sources.     

Measurement of fine particulate matter nonvolatile and semi-volatile organic material with the Sunset Laboratory Carbon Aerosol Monitor

Semi-volatile organic material (SVOM) in fine particles is not reliably measured with conventional semicontinuous carbon monitors because SVOM is lost from the collection media during sample collection. We have modified a Sunset Laboratory Carbon Aerosol Monitor to allow for the determination of SVOM. In a conventional Sunset monitor, gas-phase organic compounds are removed in the sampled airstream by a diffusion denuder employing charcoal-impregnated cellulose filter (CIF) surfaces. Subsequently, particles are collected on a quartz filter and the instrument then determines both the organic carbon and elemental carbon fractions of the aerosol using a thermal/optical method. However, some of the SVOM is lost from the filter during collection, and therefore is not determined. Because the interfering gas-phase organic compounds are removed before aerosol collection, the SVOM can be determined by filtering the particles at the instrument inlet and then replacing the quartz filter in the monitor with a charcoal-impregnated glass fiber filter (CIG), which retains the SVOM lost from particles collected on the inlet filter. The resulting collected SVOM is then determined in the analysis step by measurement of the carbonaceous material thermally evolved from the CIG filter. This concept was tested during field studies in February 2003 in Lindon, UT, and in July 2003 in Rubidoux, CA. The results obtained were validated by comparison with Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) results. The sum of nonvolatile organic material determined with a conventional Sunset monitor and SVOM determined with the modified Sunset monitor agree with the PC-BOSS results. Linear regression analysis of total carbon concentrations determined by the PC-BOSS and the Sunset resulted in a zero-intercept slope of 0.99 +/- 0.02 (R2 = 0.92) and a precision of sigma = +/- 1.5 microg C/m3 (8%).     

Characterization of ambient fine particles in the northwestern area and Anchorage, Alaska

Ambient PM2.5 (particulate matter less than 2.5 microm in aerodynamic diameter) in the northwestern United States and Alaska is dominated by carbonaceous compounds associated with wood burning and transportation sources. PM2.5 source characterization studies analyzing recent PM2.5 speciation data have not been previously reported for these areas. In this study, ambient PM2.5 speciation samples collected at two monitoring sites located in the northwestern area, Olympic Peninsula, WA, and Portland, OR, and one monitoring site located in Anchorage, AK, were characterized through source apportionments. Gasoline vehicle, secondary sulfate, and wood smoke were the largest sources of PM2.5 collected at the Anchorage, Olympic, and Portland monitoring sites, respectively. Secondary sulfates showed an April peak at Anchorage and a November peak at Portland that are likely related to the increased photochemical reaction and long-range transport in Anchorage and meteorological stagnation in Portland. Secondary nitrate at the Olympic site showed a weak summer high peak that could be caused by seasonal tourism in the national park. Backward trajectories suggested that the elevated aged sea salt concentrations at the Portland monitoring site could be regional transport of sea salt that passed through other contaminated air sheds along the coast. Oil combustion emissions that might originate from ships and ferries were observed at the Olympic monitoring site.     

A new indicator of fireworks emissions in Rochester, New York

In ambient particle source apportionment studies, data for holidays such as July 4 (US Independence Day) are normally removed because of the high concentrations of chemical species and unusually high particle mass concentrations that are due to fireworks. Many cultures celebrate events with fireworks. A near real-time measurement that could indicate fireworks would be useful in indicating their impact on air quality. Commonly monitored ambient pollutants include PM_2.5, CO, SO₂, O₃, 10–500-nm particle number, and black carbon (BC). Using a two-wavelength aethalometer, another parameter, delta-C (UVBC_370?nm–BC_880?nm, aethalometer), can be calculated. These variables were continuously monitored during July 1–7, 2005–2010, in Rochester, New York. High delta-C values are normally associated with biomass combustion particles. However, statistically higher delta-C values were observed on Independence Day compared to the other period. Back trajectory analysis showed transport of local fireworks smoke to the sampling site on the night of July 4. An enhanced correlation between delta-C and BC during the fireworks episodes suggests changes from the usual BC sources. Fireworks emissions changed the ambient carbonaceous particulate species during these intervals. The delta-C value was found to be a readily measured indicator of fireworks emissions during periods when wood combustion was not likely to be present and provides a tool for monitoring such emissions where they might be more common such as amusement parks.     

Sources of fine particulate species in ambient air over lake Champlain Basin, VT

This study is a part of an ongoing investigation of the types and locations of emission sources that contribute fine particulate air contaminants to Underhill, VT. The air quality monitoring data used for this study are from the Interagency Monitoring of Protected Visual Environments network for the period of 2001-2003 for the Underhill site. The main source-receptor modeling techniques used are the positive matrix factorization (PMF) and potential source contribution function (PSCF). This new study is intended as a comparison to a previous study of the 1988-1995 Underhill data that successfully revealed a total of 11 types of emission sources with significant contributions to this rural site. This new study has identified a total of nine sources: nitrate-rich secondary aerosol, wood smoke, East Coast oil combustion, automobile emission, metal working, soil/dust, sulfur-rich aerosol type I, sulfur-rich aerosol type II, and sea salt/road salt. Furthermore, the mass contributions from the PMF identified sources that correspond with sampling days with either good or poor visibility were analyzed to seek possible correlations. It has been shown that sulfur-rich aerosol type I, nitrate aerosol, and automobile emission are the most important contributors to visibility degradation. Soil/dust and sea salt/road salt also have an added effect.     

Factor analysis of submicron particle size distributions near a major United States-Canada trade bridge

A factor analytic model has been applied to resolve and apportion particles based on submicron particle size distributions downwind of a United States-Canada bridge in Buffalo, NY. The sites chosen for this study were located at gradually increasing distances downwind of the bridge complex. Seven independent factors were resolved, including four factors that were common to all of the five sites considered. The common factors were generally characterized by the existence of two or more number and surface area modes. The seven factors resolved were identified as follows: fresh tail-pipe diesel exhaust, local/street diesel traffic, aged/evolved diesel particles, spark-ignition gasoline emissions, background urban emissions, heavy-duty diesel agglomerates, and secondary/transported material. Submicron (<0.5 microm) and ultrafine (<0.1 microm) particle emissions downwind of the bridge were dominated by commercial diesel truck emissions. Thus, this study obtained size distinction between fresh versus aged vehicle exhaust and spark-ignition versus diesel emissions based on the measured high time-resolution particle number concentrations. Because this study mainly used particles <300 nm in diameter, some sources that would usually exhibit number modes >100 nm were not resolved. Also, the resolved profiles suggested that the major number mode for fresh tailpipe diesel exhaust might exist below the detection limit of the spectrometer used. The average particle number contributions from the resolved factors were highest closest to the bridge.