Long-range aerosol transport affects locations hundreds of kilometers from the point of emission, leading to distant particle sources influencing rural environments that have few major local sources. Source apportionment was conducted using real-time aerosol chemistry measurements made in July 2014 at the forested University of Michigan Biological Station near Pellston, Michigan, a site representative of the remote forested Great Lakes region. Size-resolved chemical composition of individual 0.5–2.0 µm particles was measured using an aerosol time-of-flight mass spectrometer (ATOFMS), and non-refractory aerosol mass less than 1 µm (PM1) was measured with a high-resolution aerosol mass spectrometer (HR-AMS). The field site was influenced by air masses transporting Canadian wildfire emissions and urban pollution from Milwaukee and Chicago. During wildfire-influenced periods, 0.5–2.0 µm particles were primarily aged biomass burning particles (88 % by number). These particles were heavily coated with secondary organic aerosol (SOA) formed during transport, with organics (average O∕C ratio of 0.8) contributing 89 % of the PM1 mass. During urban-influenced periods, organic carbon, elemental carbon–organic carbon, and aged biomass burning particles were identified, with inorganic secondary species (ammonium, sulfate, and nitrate) contributing 41 % of the PM1 mass, indicative of atmospheric processing. With current models underpredicting organic carbon in this region and biomass burning being the largest combustion contributor to SOA by mass, these results highlight the importance for regional chemical transport models to accurately predict the impact of long-range transported particles on air quality in the upper Midwest, United States, particularly considering increasing intensity and frequency of Canadian wildfires.

Significant amounts of amines were detected in fine particulate matter (PM) during ambient wintertime conditions in Yakima, WA, using a high resolution time- of-flight aerosol mass spectrometer (HR-ToF-AMS). Positive matrix factorization (PMF) of the organic aerosol (OA) signal resulted in a six-factor solution that included two previously unreported amine OA factors. The contributions of the amine factors were strongly episodic, but the concentration of the combined amine factors was as high as 10-15 mu g m(-3) (2-min average) during those episodes. In one occasion, the Amine-II component was 45% of total OA signal. The Amine-I factor was dominated by spectral peaks at m/z 86 (C5H12N+) and m/z 100 (C6H14N+), while the Amine-II factor was dominated by spectral peaks at m/z 58 (C3H8N+ and C2H6N2+) and m/z 72 (C4H10N+ and C3H8N2+). The ions dominating each amine factor showed distinct time traces, suggesting different sources or formation processes. Investigation into the chemistry of the amine factors suggests a correlation with inorganic anions for Amine-I, but no evidence that the Amine-II was being neutralized by the same inorganic ions. We also excluded the presence of organonitrates (ON) in the OA. The presence of C2H4O2+ at m/z 60 (a levoglucosan fragment) in the Amine-I spectrum suggests some influence of biomass burning emissions (more specifically residential wood combustion) in this PMF factor, but wind direction suggested that the most likely sources of these amines were agricultural activities and feedlots to the S-SW of the site.

The Yakima Air Wintertime Nitrate Study (YAWNS) was conducted in January 2013 to investigate the drivers of elevated levels of fine particulate matter (PM2.5) frequently present in the region during winter stagnation periods. An extended stagnation period occurred during the study. For the first four days of the event, skies were clear and the strong diel variation in air pollution patterns were consistent with the expected effects of strong low-level nighttime temperature inversions with moderate mixing during daylight hours. Later in the event a low-level cloud layer formed that persisted over the Yakima Valley for the next seven days while regional conditions remained stagnant. Coincident with the onset of cloud, the levels of all measured primary pollutants, including CO2, CO, NOx, particle number concentration, and black carbon, dropped dramatically and remained low with negligible diel variation for as long as the cloud layer was present. The observed patterns for these air pollutants are consistent with decreased stability and enhanced mixing associated with the cloud-topped boundary layer. Interestingly, levels of secondary pollutants, most notably particulate ammonium nitrate, did not exhibit the same decline. This difference may be due to shifts in the chemical production of secondary pollutants during cloudy conditions, or may merely reflect a further influence of mixing. The results imply that the best strategies for managing wintertime air quality during episodes of persistent cloud are likely different from those needed during clear-sky stagnation events.

A multiple linear regression (MLR) chemical mass balance model was applied to data collected during an air quality field experiment in Yakima, WA, during January 2013 to determine the relative contribution of residential wood combustion (RWC) and vehicle emissions to ambient pollutant levels. Acetonitrile was used as a chemical tracer for wood burning and nitrogen oxides (NOx) as a chemical tracer for mobile sources. RWC was found to be a substantial source of gas phase air toxics in wintertime. The MLR model found RWC primarily responsible for emissions of formaldehyde (73%), acetaldehyde (69%), and black carbon (55%) and mobile sources primarily responsible for emissions of carbon monoxide (CO; 83%), toluene (81%), C2-alkylbenzenes (81%), and benzene (64%). When compared with the Environmental Protection Agency's 2011 winter emission inventory, the MLR results suggest that the contribution of RWC to CO emissions was underestimated in the inventory by a factor of 2. Emission ratios to NOx from the MLR model agreed to within 25% with wintertime emission ratios predicted from the Motor Vehicle Emissions Simulator (MOVES) 2010b emission model for Yakima County for all pollutants modeled except for CO, C-2-alkylbenzenes, and black carbon. The MLR model results suggest that MOVES was overpredicting mobile source emissions of CO relative to NOx by a factor of 1.33 and black carbon relative to NOx by about a factor of 3.

Gas-phase biogenic volatile organic compounds (BVOCs) are oxidized in the troposphere to produce secondary pollutants such as ozone (O3), organic nitrates (RONO2), and secondary organic aerosol (SOA). Two coupled zero-dimensional models have been used to investigate differences in oxidation and SOA production from isoprene and α-pinene, especially with respect to the nitrate radical (NO3), above and below a forest canopy in rural Michigan. In both modeled environments (above and below the canopy), NO3 mixing ratios are relatively small (< 0.5 pptv); however, daytime (08:00–20:00 LT) mixing ratios below the canopy are 2 to 3 times larger than those above. As a result of this difference, NO3 contributes 12 % of total daytime α-pinene oxidation below the canopy while only contributing 4 % above. Increasing background pollutant levels to simulate a more polluted suburban or peri-urban forest environment increases the average contribution of NO3 to daytime below-canopy α-pinene oxidation to 32 %. Gas-phase RONO2 produced through NO3 oxidation undergoes net transport upward from the below-canopy environment during the day, and this transport contributes up to 30 % of total NO3-derived RONO2 production above the canopy in the morning (∼ 07:00). Modeled SOA mass loadings above and below the canopy ultimately differ by less than 0.5 µg m−3, and extremely low-volatility organic compounds dominate SOA composition. Lower temperatures below the canopy cause increased partitioning of semi-volatile gas-phase products to the particle phase and up to 35 % larger SOA mass loadings of these products relative to above the canopy in the model. Including transport between above- and below-canopy environments increases above-canopy NO3-derived α-pinene RONO2 SOA mass by as much as 45 %, suggesting that below-canopy chemical processes substantially influence above-canopy SOA mass loadings, especially with regard to monoterpene-derived RONO2.

The northern Great Lakes region of North America is a large, relatively pristine area. To date, there has only been limited study of the atmospheric aerosol in this region. During summer 2009, a detailed characterization of the atmospheric aerosol was conducted at the University of Michigan Biological Station (UMBS) as part of the Community Atmosphere-Biosphere Interactions Experiment (CABINEX). Measurements included particle size distribution, water-soluble composition, and CCN activity. Aerosol properties were strongly dependent on the origin of the air masses reaching the site. For similar to 60% of the study period, air was transported from sparsely populated regions to the northwest. During these times aerosol loadings were low, with mean number and volume concentrations of 1630 cm(-3) and 1.91 mu m(3) cm(-3), respectively. The aerosol during clean periods was dominated by organics, and exhibited low hygroscopicities (mean K = 0.18 at s = 0.3%). When air was from more populated regions to the east and south (similar to 29% of the time), aerosol properties reflected a stronger anthropogenic influence, with 85% greater particle number concentrations, 2.5 times greater aerosol volume, six times more sulfate mass, and increased hygroscopicity (mean K = 0.24 at s = 0.3%). These trends are have the potential to influence forest-atmosphere interactions and should be targeted for future study. (C) 2015 Elsevier Ltd. All rights reserved.

The largest global source of volatile organic compounds (VOCs) in the atmosphere is from biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. This study investigated the effects of one global change stressor, increased herbivory, on plant emissions from five different coniferous species: bristlecone pine (Pinus aristata), blue spruce (Picea pungens), western redcedar (Thuja plicata), grand fir (Abies grandis), and Douglas-fir (Pseudotsuga menziesii). Herbivory was simulated in the laboratory via exogenous application of methyl jasmonate (MeJA), a herbivory proxy. Gas-phase species were measured continuously with a gas chromatograph coupled to a mass spectrometer and flame ionization detector (GC–MS–FID). Stress responses varied between the different plant types and even between experiments using the same set of saplings. The compounds most frequently impacted by the stress treatment were alpha-pinene, beta-pinene, 1,8-cineol, beta-myrcene, terpinolene, limonene, and the cymene isomers. Individual compounds within a single experiment often exhibited a different response to the treatment from one another.

The largest global source of secondary organic aerosol (SOA) in the atmosphere is derived from the oxidation of biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. Alterations to the biogenic volatile organic compound (BVOC) profile could impact the characteristics of the SOA formed from those emissions. This study investigated the impacts of one global change stressor, increased herbivory, on the composition of SOA derived from real plant emissions. Herbivory was simulated via application of methyl jasmonate (MeJA), a proxy compound. Experiments were repeated under pre- and post-treatment conditions for six different coniferous plant types. Volatile organic compounds (VOCs) emitted from the plants were oxidized to form SOA via dark ozone-initiated chemistry. The SOA chemical composition was measured using a Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS). The aerosol mass spectra of pretreatment biogenic SOA from all plant types tended to be similar with correlations usually greater than or equal to 0.90. The presence of a stressor produced characteristic differences in the SOA mass spectra. Specifically, the following m/z were identified as a possible biogenic stress AMS marker with the corresponding HR ion(s) shown in parentheses: m/z 31 (CH3O+), m/z 58 (C2H2O2+, C3H6O+), m/z 29 (C2H5+), m/z 57 (C3H5O+), m/z 59 (C2H3O2+, C3H7O+), m/z 71 (C3H3O2+, C4H7O+), and m/z 83 (C5H7O+). The first aerosol mass spectrum of SOA generated from the oxidation of the plant stress hormone, MeJA, is also presented. Elemental analysis results demonstrated an O: C range of baseline biogenic SOA between 0.3 and 0.47. The O: C of standard MeJA SOA was 0.52. Results presented here could be used to help identify a biogenic plant stress marker in ambient data sets collected in forest environments.

This article presents a new methodology to potentially quantify polycyclic aromatic hydrocarbon (PAH) isomers using high-resolution time of flight aerosol mass spectrometer (HR-AMS). The fragmentation of PAHs within the HR-AMS is such that significant signal remains at the molecular ion. After quantifying the molecular ion signal and taking into account potential interferences, the amount of the parent PAH in the aerosol may be inferred once its fragmentation pattern is also known. The potential of this approach was evaluated using mixed gasoline and diesel engine exhaust sampled under varying conditions. This dataset led to the identification and quantification within the aerosol mass spectra of the molecular ions associated with 53 PAH isomers, including both unsubstituted and functionalized species. An evaluation of anticipated interferences shows that interferences from larger molecular weight PAHs (i.e., PAH/PAH interferences) could be constrained based on the fragmentation behavior of PAHs from existing HR-AMS laboratory spectra. Other signal interferences for this data set are typically less than 5% of the total signal or, for C-13 isotopic interferents, are well constrained by measurements of the dominant isotope. The experimental data reveal that the fractional PAH molecular ion signal remained stable despite dramatic temporal variability of the total particulate organic signal. The fractional contributions of the molecular ions for grouped PAH species and even individual compounds were remarkably consistent across experiments. The distribution of PAHs showed no apparent dependence on engine load or exhaust type. Full application of this approach will require a greater number of standard HR-AMS spectra for PAHs, so that the relationship between compounds and their molecular ions may be understood more precisely.Copyright 2015 American Association for Aerosol Research

10 The largest global source of volatile organic compounds (VOCs) in the atmosphere is from 11 biogenic emissions. Plant stressors associated with a changing environment can alter both the 12 quantity and composition of the compounds that are emitted. This study investigated the 13 effects of one global change stressor, increased herbivory, on plant emissions from five 14 different coniferous species: bristlecone pine (Pinus aristata), blue spruce (Picea pungens), 15 western redcedar (Thuja plicata), grand fir (Abies grandis), and Douglas-fir (Pseudotsugas 16 menziesii). Herbivory was simulated in the laboratory via exogenous application of methyl 17 jasmonate, an herbivory proxy. Gas-phase species were measured continuously with a gas 18 chromatograph coupled to a mass spectrometer and flame ionization detector (GC-MS-FID). 19 Stress responses varied between the different plant types and even between experiments using 20 the same set of saplings. The compounds most frequently impacted by the stress treatment 21 were alpha-pinene, beta-pinene, 1,8-cineol, beta-myrcene, terpinolene, limonene, and the 22 cymene isomers. Individual compounds within a single experiment often exhibited a different 23 response to the treatment from one another. 24

Abstract. A pollen model that simulates the timing and production of wind-dispersed allergenic pollen by terrestrial, temperate vegetation has been developed to quantify how pollen occurrence may be affected by climate change and to investigate how pollen can interact with anthropogenic pollutants to affect human health. The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model is driven by local meteorological conditions and is designed to be sensitive to climate shifts, as well as flexible with respect to the vegetation species and plant functional types (trees, grasses, etc.) represented and the climate zones simulated. The initial focus for the model is the simulation of the pollen emission potential of important allergenic tree and grass species that typically flower between March–June in Southern California (S. CA), which is characterized by moderate Mediterranean and oceanic climate zones as well as regions of arid desert and arid steppe. Vegetation cover and species composition data are obtained from numerous datasets and a database of allergenic vegetation species, their pollen production potential and relative allergenicities has been developed. For the selected allergenic species and spring-early summer simulation period, temperature is the main driver controlling the timing of pollen release, while precipitation (and temperature, for some species) controls the magnitude of pollen produced. The model provides species-specific pollen potential maps for each day of the simulation period; these are then used by a pollen transport model to simulate ambient pollen concentrations as described in a companion paper (Zhang et al., 2013a), which also presents model evaluation results for the S. CA model domain. The STaMPS model was also used to quantify the possible impact of climate change on pollen season under the IPCC SRES A1B scenario as simulated by the ECHAM5 global climate model. Current (1995–2004) and future (2045–2054) meteorological conditions downscaled using the Weather Research and Forecasting (WRF) model were used to drive STaMPS and generate estimates of the relative magnitude and timing of pollen season for important allergenic tree and grass species that bloom from March through June in a larger domain that covers all of CA and Nevada. Differences in the simulated timing and magnitude of pollen season for the selected allergenic species under current and future climate scenarios are presented. The results suggest that across all of the simulated species, pollen season starts an average of 5–6 days earlier under predicted future climatic conditions with an associated average annual domain-wide temperature increase of about 1°C compared to simulated current conditions. Differences in the amount of pollen produced under the two scenarios vary by species and are affected by the selected simulation period (1 March–30 June). Uncertainties associated with the STaMPS model and future model development plans are also discussed.

Wind erosion of soil is a major concern of the agricultural community, as it removes the most fertile part of the soil and thus degrades soil productivity. Furthermore, dust emissions due to wind erosion degrade air quality, reduce visibility, and cause perturbations to regional radiation budgets. PM10 emitted from the soil surface can travel hundreds of kilometers downwind before being deposited back to the surface. Thus, it is necessary to address agricultural air pollutant sources within a regional air quality modeling system in order to forecast regional dust storms and to understand the impact of agricultural activities and land-management practices on air quality in a changing climate. The Wind Erosion Prediction System (WEPS) is a new tool in regional air quality modeling for simulating erosion from agricultural fields. WEPS represents a significant improvement, in comparison to existing empirical windblown dust modeling algorithms used for air quality simulations, by using a more process-based modeling approach. This is in contrast with the empirical approaches used in previous models, which could only be used reliably when soil, surface, and ambient conditions are similar to those from which the parameterizations were derived. WEPS was originally intended for soil conservation applications and designed to simulate conditions of a single field over multiple years. In this work, we used the EROSION submodel from WEPS as a PM10 emission module for regional modeling by extending it to cover a large region divided into Euclidean grid cells. The new PM10 emission module was then employed within a regional weather and chemical transport modeling framework commonly used for comprehensive simulations of a wide range of pollutants to evaluate overall air quality conditions. This framework employs the Weather Research and Forecasting (WRF) weather model along with the Community Multi-scale Air Quality (CMAQ) model to treat ozone, particulate matter, and other air pollutants. To demonstrate the capabilities of the WRF/EROSION/CMAQ dust modeling framework, we present here results from simulations of dust storms that occurred in central and eastern Washington during 4 October 2009 and 26 August 2010. Comparison of model results with observations indicates that the modeling framework performs well in predicting the onset and timing of the dust storms and the spatial extent of their dust plumes. The regional dust modeling framework is able to predict elevated PM10 concentrations hundreds of kilometers downwind of erosion source regions associated with the windblown dust, although the magnitude of the PM10 concentrations are extremely sensitive to the assumption of surface soil moisture and model wind speeds. Future work will include incorporating the full WEPS model into the regional modeling framework and targeting field measurements to evaluate the modeling framework more extensively.

Soil and leaf litter are significant global sources of small oxidized volatile organic compounds, VOCs (e.g., methanol and acetaldehyde). They may also be significant sources of larger VOCs that could act as precursors to secondary organic aerosol (SOA) formation. To investigate this, soil and leaf litter samples were collected from the University of Idaho Experimental Forest and transported to the laboratory. There, the VOC emissions were characterized and used to drive SOA formation via dark, ozone-initiated reactions. Monoterpenes dominated the emission profile with emission rates as high as 228 μg-C m(-2) h(-1). The composition of the SOA produced was similar to biogenic SOA formed from oxidation of ponderosa pine emissions and α-pinene. Measured soil and litter monoterpene emission rates were compared with modeled canopy emissions. Results suggest surface soil and litter monoterpene emissions could range from 12 to 136% of canopy emissions in spring and fall. Thus, emissions from leaf litter may potentially extend the biogenic emissions season, contributing to significant organic aerosol formation in the spring and fall when reduced solar radiation and temperatures reduce emissions from living vegetation.

Research has shown that high school and college students have a lack of conceptual understanding of global warming, ozone, and the greenhouse effect. Most research in this area used survey methodologies and did not include concepts of atmospheric chemistry and ozone formation. This study investigates college students' understandings of atmospheric ozone formation using established clinical interview methodologies and qualitative data analysis techniques. Three prevalent naive conceptions were identified: (1) that there is only one atmospheric mechanism for ozone formation; (2) that pollutants and gases only react after being transported up high in the atmosphere; and (3) that concerns about ozone in the atmosphere are due primarily to its role as a greenhouse gas. The existence of these naive conceptions prevented students from forming correct mental models of atmospheric ozone formation. Existing conceptual change approaches may provide pathways for addressing these naive conceptions, but further research is required before specific solutions are proposed.

The purpose of this study is to evaluate the performance, costs, energy, and greenhouse gas emission of cementitious high-carbon fly ash (CHCFA)-stabilised recycled pavement materials (RPMs) as base course. Three test road cells were built in Minnesota. These cells have the same pavement structure except different base courses: conventional crushed aggregates, untreated RPM, and CHCFA-stabilised RPM. Results of laboratory and field tests were used in the Mechanistic-empirical pavement design guide (MEPDG) to predict the pavement performance. MEPDG performance prediction indicated that Cell 79 containing CHCFA-stabilised RPM had the longest service life in the three cells. The life-cycle analysis indicated that the usage of the CHCFA-stabilised RPM as the base of the flexible pavement can significantly reduce the life-cycle cost, energy consumption, and greenhouse gas emission.