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Atmospheric Environment (v.45, #10)

Editorial board (pp. i).

Air pollution exposure: Who is at high risk? by Ronit Peled (pp. 1781-1785).
This article reviews the sub-population groups who are at high risk and first to be harmed by air pollution coming from anthropogenic combustions. Epidemiological studies from the last few decades contributed to the understanding of the different levels of susceptibility to air pollution. Older people and young infants, people who suffer from allergies, pulmonary and heart diseases, pregnant women and newborn babies, and deprived populations that suffer from low socio-economic status have all been described as populations at risk. A better understanding of the role of air pollution on large as well as specific populations’ health, will promote a better protection policy.► Older people (65+ years of age). ► Newborn babies, young children and toddlers. ► People who suffer from respiratory, cardiovascular and other chronic diseases. ► People who are in special medical conditions: pregnant women, people who suffer from allergy. ► Deprived population: people who belong to the lower socio-economic status.

Keywords: Air pollution; Population at risk


Modeling study on the air quality impacts from emission reductions and atypical meteorological conditions during the 2008 Beijing Olympics by Jia Xing; Yang Zhang; Shuxiao Wang; Xiaohuan Liu; Shuhui Cheng; Qiang Zhang; Yaosheng Chen; David G. Streets; Carey Jang; Jiming Hao; Wenxing Wang (pp. 1786-1798).
Understanding of the relative impacts of emission reductions and meteorological variations on air quality during the 2008 Beijing Olympics has an important policy implication. In this work, detailed process analyses and sensitivity simulations under different emission and meteorology scenarios were conducted using CMAQ and the Process Analysis tool to quantify the air quality benefits from emission reductions and meteorological variations in August 2008. The results indicate that emission-driven changes dominate surface concentration reductions of SO2, NO2, VOCs, daily maxima O3 and PM2.5 by −11% to −83%. The effect of meteorology-driven changes on species concentrations can be either ways (by −46% to 105%) at different locations. The dominant processes contributing to O3, PM2.5, SO42−, NO3−, and secondary organic aerosol (SOA) are identified. Gas-phase chemistry is a major process for O3 production, and PM processes are dominant sources for PM2.5 in the planetary boundary layer (PBL). The reduced emissions weaken the source contributions of gas-phase chemistry to O3 and those of PM processes to PM2.5, with weaker vertical mixing processes and horizontal transport in the PBL. Compared with 2007, 2008 has a higher humidity, lower temperature and more precipitation that benefit O3 reduction within the PBL, and a weaker vertical mixing that disbenefits reductions of all pollutants concentrations. Stronger process contributions of cloud processes (e.g., below- and in-cloud scavenging, and wet deposition) in 2008 help reduce concentrations of PM2.5, NO3−, and SOA, but they (e.g., aqueous-phase chemistry) enhance surface SO42− concentrations. Smaller process contributions of aerosol processes help reduce the concentrations of SOA and SO42− but enhance NO3− and PM2.5 in lower layers (1–6) due to the evaporation of NO3−. The ratios ofPH2O2/PHNO3 increase under the controlled simulation, indicating that the emission control actions enforced during the 2008 Olympics weakened the sensitivity of O3 chemistry to VOC emissions in urban areas.► Emission controls are important despite of positive changes in meteorology. ► Emission controls benefit for all pollutants reductions. ► Effect of meteorology changes can be either ways at different locations. ► Synergistic controls on both NOx and VOCs are essential to reduce urban O3.

Keywords: Beijing Olympics; Emission control; CMAQ; Process analysis; Sensitivity simulation


Polycyclic aromatic hydrocarbons in gas and particulate phases of indoor environments influenced by tobacco smoke: Levels, phase distributions, and health risks by Dionísia Castro; Klara Slezakova; Cristina Delerue-Matos; Maria da Conceição Alvim-Ferraz; Simone Morais; Maria do Carmo Pereira (pp. 1799-1808).
As polycyclic aromatic hydrocarbons (PAHs) have a negative impact on human health due to their mutagenic and/or carcinogenic properties, the objective of this work was to study the influence of tobacco smoke on levels and phase distribution of PAHs and to evaluate the associated health risks. The air samples were collected at two homes; 18 PAHs (the 16 PAHs considered by U.S. EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) were determined in gas phase and associated with thoracic (PM10) and respirable (PM2.5) particles.At home influenced by tobacco smoke the total concentrations of 18 PAHs in air ranged from 28.3 to 106ngm−3 (mean of 66.7±25.4ngm−3), ∑PAHs being 95% higher than at the non-smoking one where the values ranged from 17.9 to 62.0ngm−3 (mean of 34.5±16.5ngm−3). On average 74% and 78% of ∑PAHs were present in gas phase at the smoking and non-smoking homes, respectively, demonstrating that adequate assessment of PAHs in air requires evaluation of PAHs in both gas and particulate phases. When influenced by tobacco smoke the health risks values were 3.5–3.6 times higher due to the exposure of PM10. The values of lifetime lung cancer risks were 4.1×10−3 and 1.7×10−3 for the smoking and non-smoking homes, considerably exceeding the health-based guideline level at both homes also due to the contribution of outdoor traffic emissions. The results showed that evaluation of benzo[a]pyrene alone would probably underestimate the carcinogenic potential of the studied PAH mixtures; in total ten carcinogenic PAHs represented 36% and 32% of the gaseous ∑PAHs and in particulate phase they accounted for 75% and 71% of ∑PAHs at the smoking and non-smoking homes, respectively.► Tobacco smoke increased the concentrations of PM10 and PM2.5 by 260% and 290%. ► Total concentration of 18 PAHs was 95% higher when smoking. ► Correct PAHs assessment in air requires evaluation of PAHs in gas and particles. ► Lifetime lung cancer risk values considerably exceeded health-based guideline level.

Keywords: Indoor air; Tobacco smoke; Polycyclic aromatic hydrocarbons (PAHs); Phase distribution; Health risks; Microwave-assisted extraction (MAE)


Seasonal and spatial variations of methane emissions from montane wetlands in Northeast China by Xiaoxin Sun; Changcheng Mu; Changchun Song (pp. 1809-1816).
To evaluate the seasonal and spatial variations of CH4 emissions and understand the controlling factors, we measured CH4 fluxes and their environmental variables from seven natural wetlands in mountainous regions in northeast China using a static chamber technique during a growing season from May to October in 2008. Four sites were significant atmospheric CH4 sources, ranked in order from highest to lowest according to their seasonal mean CH4 release; these sites were a marsh (34.18mgCH4m−2h−1), two deciduous forested swamps (0.83–18.21 mgCH4 m−2h−1) and a thicket swamp (0.43mgCH4m−2h−1). Coniferous forested swamps, forested fens and bogs are unique wetlands in northeast China and represent large wetland coverage in this zone, but they were observed to be weak sinks of atmospheric CH4 (−0.08 to −0.01mgCH4m−2h−1). Similar seasonal variations can be observed at marsh, thicket swamp and two deciduous forested swamps sites, with peaks were observed during the summer and early autumn (July to early September). However, no seasonal pattern was found at the other three sites. Seasonal variations of CH4 fluxes were primarily affected by the soil temperature. However, spatial variation among wetlands was mainly controlled by the water table, the soil temperature, plant aboveground biomass and potential CH4 production. A high water table and herb-dominant sites had high potential CH4 production rates and thus induced high CH4 fluxes. In contrast, a low water table and tree- or moss-dominant sites had low potential CH4 production rates and induced low CH4 fluxes.► Wetlands could act as both atmospheric CH4 sources and sinks. ► CH4 fluxes were mainly controlled by water table, soil temperature and plant biomass. ► Spatial variations of CH4 fluxes were correlated with potential methane production. ► Herbs are better predictors for evaluating CH4 fluxes from wetlands than shrubs.

Keywords: CH; 4; flux; Seasonal variation; Spatial variation; Wetlands; Xiaoxing’an Mountains


Impacts of aerosols on summertime tropospheric photolysis frequencies and photochemistry over Central Eastern China by J. Li; Z. Wang; X. Wang; K. Yamaji; M. Takigawa; Y. Kanaya; P. Pochanart; Y. Liu; H. Irie; B. Hu; H. Tanimoto; H. Akimoto (pp. 1817-1829).
Aerosols in the troposphere influence photolysis frequencies and hence the concentrations of chemical species. We used a three-dimensional regional chemical transport model (NAQPMS) coupled with an accurate radiative transfer model to examine the impacts of aerosols on summertime photochemistry in Central Eastern China (CEC) via changing photolysis frequencies. In addition to looking at changes in concentrations as previous studies have done, we examined the changes in ozone (O3) budgets and the uncertainties related to our estimations. The 1st–12th June 2006 was selected as the simulation period when high aerosol optical depth at 550nm (AOD550) and O3 were found. A comparison of measurements showed that the model was capable of reproducing the spatial and temporal variations in photolysis frequencies, ultraviolet (UV) radiation, AOD550, cloud optical depth, O3 and other chemical constitutes in CEC. Aerosols have important impacts on atmospheric oxidation capacity in CEC. On a regional scale, aerosols decreased the average O3→O (1D) photolysis frequency by 53%, 37% and 21% in the lower, middle and upper troposphere in CEC. The uncertainties of these estimations were 37%, 25% and 14%, respectively. Mean OH concentrations decreased by 51%, 40% and 24% in layers below 1km, 1–3km and 3–10km, with uncertainties of 39%, 28% and 9%, respectively. The changes in HO2 concentrations were smaller but significant. In contrast, NOx showed a significant increase at 0–1km and 1–3km in CEC, with magnitudes of 6% and 8%. The largest relative enhancement occurred in downwind regions below 1km. Summertime boundary layer O3 (below 1km and 1–3km) was reduced by 5% with a maximum of 9% in highly polluted regions. The reduced ozone production (P (O3)) was responsible for this reduction below 3km.► A 3D chemical transport model was coupled with an accurate radiative transfer model. ► The siginificant impacts of aerosols on summertime photochemistry in Central China. ► Summertime boundary layer ozone reduced by 5% in polluted regions.

Keywords: Photolysis frequencies; Aerosols optical depths; Photochemistry; Central Eastern China


Traffic flow pattern and meteorology at two distinct urban junctions with impacts on air quality by Sharad Gokhale (pp. 1830-1840).
Traffic during operation at a junction undergoes different flow conditions and modal events which result into dynamic fleet characteristics generating more emissions and stronger vehicle-induced heat and wakes generating obscure dispersion. Traffic in a manner operated at junctions often creates pockets of higher concentrations the locations of which shift as a result of the combine effects of traffic dynamics and random airflow. This research examined the impacts of traffic dynamics and meteorology on the levels and locations of higher concentrations of pollutant CO, NO2 and PM within the influence of signalized traffic intersection and a conventional two-lane roundabout in a response to varying flow conditions and emissions resulted from the traffic operations. Three line source dispersion models have been used to determine the impact on air quality. Emissions have been calculated for different scenarios developed from different combinations of semi-empirical and field based time and space-mean speeds and lane-width based density when traffic undergoes free, interrupted and congested-flow conditions during operation. It has been found that the locations of highest concentrations within the domain change as traffic with different modal share encounters different flow conditions at different times of a day.► Traffic flow of mixed modal share generates dissimilar road density with time. ► Scale of pollutant dispersion depends upon different traffic flow conditions. ► Spatial distribution of concentrations changes with the traffic flow pattern. ► Level and location of peak concentration changes with different states of congestion.

Keywords: Pollutant emission; Urban air quality; Traffic flow; Traffic junction; Pollution episode


Volatile organic compound emissions from green waste composting: Characterization and ozone formation by Anuj Kumar; Christopher P. Alaimo; Robert Horowitz; Frank M. Mitloehner; Michael J. Kleeman; Peter G. Green (pp. 1841-1848).
Composting of green waste separated from the disposed solid waste stream reduces biodegradable inputs into landfills, and contributes valuable soil amendments to agriculture. Agencies in regions with severe air quality challenges, such as California’s San Joaquin Valley (SJV), have raised concerns about gases emitted during the composting process, which are suspected to contribute to persistent high levels of ground-level ozone formation. The goal of the current study is to thoroughly characterize volatile organic compound (VOC) emissions from green waste compost piles of different ages (fresh tipped piles, 3–6 day old windrows, and 2–3 week old windrows). Multiple sampling and analytical approaches were applied to ensure the detection of most gaseous organic components emitted. More than 100 VOCs were detected and quantified in this study, including aliphatic alkanes, alkenes, aromatic hydrocarbons, biogenic organics, aldehydes, ketones, alcohols, furans, acids, esters, ether, halogenated hydrocarbons and dimethyl disulfide (DMDS). Alcohols were found to be the dominating VOC in the emissions from a compost pile regardless of age, with fluxes ranging from 2.6 to 13.0mgm−2min−1 with the highest emissions coming from the younger composting windrows (3–6 days). Average VOC emissions other than alcohols were determined to be 2.3mgm−2min−1 from younger windows, which was roughly two times higher than either the fresh tipping pile (1.2mgm−2min−1) or the older windrows (1.4mgm−2min−1). It was also observed that the older windrows emit a slightly larger proportion of more reactive compounds. Approximately 90% of the total VOCs were found to have maximum incremental reactivity of less than 2. Net ozone formation potential of the emissions was also assessed.► Characterization of VOC emissions from green waste compost of different ages. ► Emissions are dominated by small alcohols ranging from 66–85% of the total. ► Young windrows (3–6 days) had the highest flux, but less reactivity to form ozone. ► Older compost windrows (2–3 weeks) exhibited lower fluxes, but more reactivity. ► Field ozone assays and model calculations confirm low ozone formation potential.

Keywords: Green waste; Compost; VOC; Organic matter; Chemical emissions


Source apportionment of ambient particles: Comparison of positive matrix factorization analysis applied to particle size distribution and chemical composition data by Jianwei Gu; Mike Pitz; Jürgen Schnelle-Kreis; Jürgen Diemer; Armin Reller; Ralf Zimmermann; Jens Soentgen; Matthias Stoelzel; H.-Erich Wichmann; Annette Peters; Josef Cyrys (pp. 1849-1857).
Positive matrix factorization (PMF) method was used to identify the sources of ambient particles (PM10) in Augsburg in winter 2006/07. The analyses were carried out separately with particulate chemical composition (PCC) data at an urban traffic site and with particle size distribution (PSD) data at an urban background site on daily and hourly base, respectively. For PCC data, six factors are identified and associated with NaCl (6.7% of PM10), secondary sulfate (13.0%), biomass burning (13.3%), secondary nitrate (30.5%), traffic emission (16.5%) and re-suspended dust (20.0%). For PSD data, seven factors are identified and are associated with fresh and aged traffic sources, secondary aerosols, stationary combustion, nucleation particles, re-suspended dust and long range transported dust. The two traffic factors were dominated by ultrafine particles (diameter<100nm), and accounted for 25% and 40% of total particle number concentration (NC). Stationary combustion factor, consisting of particles around 100nm, accounted for 26% of total NC. Re-suspended dust was mainly composed of particles with diameters>2.5μm. The two different approaches (PCC and PSD data) led to comparable results with strong correlations for secondary nitrate and sulfate/secondary aerosols ( r=0.92), which are considered to origin mainly from long range transport. Traffic emissions ( r=0.52) and re-suspended dust ( r=0.62) showed weaker correlation due to influences of local sources at the different sites.► 6 PM10 factors were characterized using chemical composition (PCC) data. ► 7 factors were characterized using particle size distribution (PSD) data. ► Secondary aerosols were in good agreement between two methods. ► Sources influenced by local emissions show weaker agreement. ► Two methods with their advantages and disadvantages were compared.

Keywords: Particulate matter; Positive matrix factorization; Source apportionment; Size distribution; Chemical composition; Augsburg


Solubility and speciation of atmospheric iron in buffer systems simulating cloud conditions by Nabin Upadhyay; Brian J. Majestic; Pierre Herckes (pp. 1858-1866).
The solubility of iron (Fe) in atmospheric particulate matter (PM) is important to understand its chemistry and potential bioavailability to ocean phytoplankton. However, current studies on Fe solubility and its speciation are highly uncertain partly due to inconsistencies in analytical protocols. In this study, cloud-processing of atmospheric PM was simulated in acetate, formate, and oxalate buffers (pH=4.30±0.05) at 0.5, 1, 5, and 20mM. Colorimetric analysis of Fe(II)–ferrozine complex showed that Fe solubility increased by an order of magnitude when acetate and formate concentrations increased from 0.5mM to 5mM, with a higher fraction of soluble Fe in acetate than in formate at lower buffer concentration (0.5mM). Measured pH of sample extracts revealed that weak buffers are unable to maintain pH, presumably due to acidic or alkaline components of PM, requiring an optimum concentration (5mM in this study) of acetate and formate for Fe solubility measurements. Similar extraction procedures revealed that oxalate buffer inhibits the formation of Fe(II)–ferrozine complex, especially with Fe(III)-containing solutions, rendering it unsuitable for Fe solubility measurements by Ferrozine method. Application of the optimized analytical method to PM samples from different environments showed quite variable Fe solubility, with the lowest (<1%) in dust-impacted samples and the highest (5%) in urban samples. The highest solubility (6.8%) was observed in ambient PM2.5 samples influenced by anthropogenic sources (car emissions) with more than 90% of soluble Fe in the form of Fe(II). Results from this study highlight the importance of the type and strength of buffer at a given pH for Fe solubility and provide further evidence of a higher Fe solubility in urban PM samples compared to desert dust.► We discuss the effect of extracting buffer solutions on iron solubility and speciation. ► A robust extraction method is proposed and applied to a variety of atmospheric environments. ► Results show a variable but low (<10%) iron solubility. ► Most soluble iron was under the form of iron (II).

Keywords: Particulate matter; Iron solubility; Speciation; Soluble iron; Buffer solution; Clouds


Evaluation of passive air sampler calibrations: Selection of sampling rates and implications for the measurement of persistent organic pollutants in air by Lisa Melymuk; Matthew Robson; Paul A. Helm; Miriam L. Diamond (pp. 1867-1875).
Polyurethane foam (PUF) passive air samplers (PAS) are a common and highly useful method of sampling persistent organic pollutants (POP) concentrations in air. PAS calibration is necessary to obtain reasonable and comparable semi-quantitative measures of air concentrations. Various methods are found in the literature concerning PAS calibration. 35 studies on PAS use and calibration are examined here, in conjunction with a study involving 10 PAS deployed concurrently in outdoor air with a low-volume air sampler in order to measure the sampling rates of PUF-PAS for polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), polycyclic musks (PCMs), and polycyclic aromatic hydrocarbons (PAHs). Based on this analysis it is recommended that (1) PAS should be assumed to represent bulk rather than gas-phase compound concentrations due to the sampling of particle-bound compounds, (2) calibration of PAS sampling rates is more accurately achieved using an active low-volume air sampler rather than depuration compounds since the former measures gas- and particle-phase compounds and does so continuously over the deployment period of the PAS, and (3) homolog-specific sampling rates based on KOA groupings be used in preference to compound/congener-specific or single sampling rates.► Recommendations for PUF passive sampler calibration are made based on an assessment of 35 papers and new data. ► PAS results should be treated as bulk rather than gas-phase compound data. ► Active low-volume samplers are best used to calibrate PAS sampling rates. ► Sampling rates should be homolog-specific based on KOA groupings.

Keywords: Passive samplers; Persistent organic pollutants; Calibration


Development of metamodels for predicting aerosol dispersion in ventilated spaces by Shamia Hoque; Bakhtier Farouk; Charles N. Haas (pp. 1876-1887).
Artificial neural network (ANN) based metamodels were developed to describe the relationship between the design variables and their effects on the dispersion of aerosols in a ventilated space. A Hammersley sequence sampling (HSS) technique was employed to efficiently explore the multi-parameter design space and to build numerical simulation scenarios. A detailed computational fluid dynamics (CFD) model was applied to simulate these scenarios. The results derived from the CFD simulations were used to train and test the metamodels. Feed forward ANN’s were developed to map the relationship between the inputs and the outputs. The predictive ability of the neural network based metamodels was compared to linear and quadratic metamodels also derived from the same CFD simulation results. The ANN based metamodel performed well in predicting the independent data sets including data generated at the boundaries. Sensitivity analysis showed that particle tracking time to residence time and the location of input and output with relation to the height of the room had more impact than the other dimensionless groups on particle behavior.► The paper outlines a systematic method for developing predictive metamodels for particle behavior in ventilated spaces from computational fluid dynamic simulations. ► Compared to linear and quadratic metamodels, artificial neural network based metamodels predicted particle behavior more accurately. ► The study showed a way of analyzing a very complex and highly non-linear problem and obtaining meaningful insight. ► Sensitivity analysis showed that particle tracking time to residence time and the location of input and output with relation to the height of the room had more impact than the other dimensionless groups on particle behavior.

Keywords: Metamodel; Artificial neural networks; Hammersley sequence sampling; Aerosols; CFD


Polycyclic aromatic hydrocarbons (PAHs) in indoor emission from decorative candles by Santino Orecchio (pp. 1888-1895).
This study investigates PAHs indoor emissions from burning decorative candle in an indoor environment because emissions from burning wax in home have rarely been addressed. A total of 12 air samples were collected during the entire burning period of the decorative candles. Particulate and gaseous PAHs emissions were simultaneously measured by passing effluent through a filter (to collect particulate-phase PAHs), a cold trap and ORBO 43 tubes (to capture gaseous-phase PAHs). Analysis involved ultrasound extraction, followed by gas chromatography–mass spectrometry (GC–MS).The measured total PAHs concentration (particulate + aqueous phase + gas phases) for the candles, reported as mass of PAHs emitted/mass of candle burning, was between 2.3 and 49.8 μg kg−1 and mean 15 μg kg−1. Considering the volume of sampled air, the concentrations of total PAHs ranged from 7 ng m−3 to 267 ng m−3. Concentrations of B[ a]P emitted by candles ranged from 0.1 to 7.5 ng m−3, while total carcinogenic PAHs, expressed as B[a]eq, ranged from 0.2 to 10.7 ng m−3. The values of all the isomeric indices calculated in this research are in good agreement to literature data for emissions from high temperature processes.► Paper describes a simple sampling and analysis procedure to analyze 18 PAHs indoor. ► The method involves a combination of cold trap, glass filter and sorbent cartridges. ► The analysis was carried out without purification steep, by GC/MS. ► The domestic use of decorative candles is increasing; PAHs tend to accumulate in homes. ► PAHs indoor exceeded background concentrations indicating that the candles were a source.

Keywords: Indoor; Candles; PAHs; GC–MS
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