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Atmosphere, Volume 2, Issue 2 (June 2011), Pages 21-200

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Research

Open AccessArticle An Analytical Simple Formula for the Ground Level Concentration from a Point Source
Atmosphere 2011, 2(2), 21-35; doi:10.3390/atmos2020021
Received: 30 January 2011 / Revised: 2 March 2011 / Accepted: 8 March 2011 / Published: 24 March 2011
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Abstract
The Advection-Diffusion Equation is solved for a constant pollutant emission from a point-like source placed inside an unstable Atmospheric Boundary Layer. The solution is obtained adopting the novel analytical approach: Generalized Integral Laplace Transform Technique. The concentration solution of the equation is [...] Read more.
The Advection-Diffusion Equation is solved for a constant pollutant emission from a point-like source placed inside an unstable Atmospheric Boundary Layer. The solution is obtained adopting the novel analytical approach: Generalized Integral Laplace Transform Technique. The concentration solution of the equation is expressed through an infinite series expansion. After setting a realistic scenario through the wind and diffusivity parameterizations, the Ground Level Concentration (GLC) is determined, and an explicit approximate expression is provided for it, allowing an analytically simple expression for the position and value of the maximum. Remarks arise regarding the ability to express value and position of the GLC as explicit functions of the parameters defining the Atmospheric Boundary Layer scenario and the source height. Full article
(This article belongs to the Special Issue Air Pollution Modeling: Reviews of Science Process Algorithms)
Figures

Open AccessArticle Challenges and Approaches for Developing Ultrafine Particle Emission Inventories for Motor Vehicle and Bus Fleets
Atmosphere 2011, 2(2), 36-56; doi:10.3390/atmos2020036
Received: 2 February 2011 / Revised: 13 March 2011 / Accepted: 19 March 2011 / Published: 24 March 2011
Cited by 5 | PDF Full-text (246 KB) | HTML Full-text | XML Full-text
Abstract
Motor vehicles in urban areas are the main source of ultrafine particles (diameters < 0.1 µm). Ultrafine particles are generally measured in terms of particle number because they have little mass and are prolific in terms of their numbers. These sized particles are of particular interest because of their ability to enter deep into the human respiratory system and contribute to negative health effects. Currently ultrafine particles are neither regularly monitored nor regulated by ambient air quality standards. Motor vehicle and bus fleet inventories, epidemiological studies and studies of the chemical composition of ultrafine particles are urgently needed to inform scientific debate and guide development of air quality standards and regulation to control this important pollution source. This article discusses some of the many challenges associated with modelling and quantifying ultrafine particle concentrations and emission rates for developing inventories and microscale modelling of motor vehicles and buses, including the challenge of understanding and quantifying secondary particle formation. Recommendations are made concerning the application of particle emission factors in developing ultrafine particle inventories for motor vehicle fleets. The article presents a précis of the first published inventory of ultrafine particles (particle number) developed for the urban South-East Queensland motor vehicle and bus fleet in Australia, and comments on the applicability of the comprehensive set of average particle emission factors used in this inventory, for developing ultrafine particle (particle number) and particle mass inventories in other developed countries. Full article
(This article belongs to the Special Issue Particulate Pollution Related to Vehicle Emission)
Open AccessArticle Diurnal Cycle of the North American Monsoon in a Mesoscale Model Simulation: Evolution of Key Parameters in Relation to Precipitation
Atmosphere 2011, 2(2), 57-66; doi:10.3390/atmos2020057
Received: 12 February 2011 / Revised: 7 March 2011 / Accepted: 25 March 2011 / Published: 6 April 2011
Cited by 1 | PDF Full-text (1846 KB) | HTML Full-text | XML Full-text
Abstract
The diurnal cycle of the North American monsoon is analyzed based on the output from a mesoscale model simulation. Statistically significant diurnal cycle in precipitation is identified, with heavy precipitation—essentially convective—dominating in local afternoons. Temporal evolution of key parameters in relation to [...] Read more.
The diurnal cycle of the North American monsoon is analyzed based on the output from a mesoscale model simulation. Statistically significant diurnal cycle in precipitation is identified, with heavy precipitation—essentially convective—dominating in local afternoons. Temporal evolution of key parameters in relation to precipitation is investigated, based on which a sequence of the dynamic/thermodynamic processes underlying precipitation development is proposed. Particularly, the afternoon peak in precipitation is found preceded by enhanced static instability and low-level convergence. Full article
Open AccessArticle The Importance of Lateral Boundaries, Surface Forcing and Choice of Domain Size for Dynamical Downscaling of Global Climate Simulations
Atmosphere 2011, 2(2), 67-95; doi:10.3390/atmos2020067
Received: 5 March 2011 / Revised: 4 April 2011 / Accepted: 14 April 2011 / Published: 11 May 2011
Cited by 3 | PDF Full-text (1713 KB) | HTML Full-text | XML Full-text
Abstract
Dynamical downscaling by atmospheric Regional Climate Models (RCMs) forced with low-resolution data should produce climate details and add quality and value to the low-resolution data. The aim of this study was to explore the importance of (i) the oceanic surface forcing (sea-surface [...] Read more.
Dynamical downscaling by atmospheric Regional Climate Models (RCMs) forced with low-resolution data should produce climate details and add quality and value to the low-resolution data. The aim of this study was to explore the importance of (i) the oceanic surface forcing (sea-surface temperature (SST) and sea-ice), (ii) the lateral boundary condition data, and (iii) the size of the integration domain with respect to improved quality and value in dynamically downscaled data. Experiments addressing the three aspects were performed and the results were investigated for mean sea level pressure (mslp), 2 m air temperature (T2m) and daily precipitation. Although changes in SST gave a clear response locally, changes in the lateral boundary data and the size of the integration domain turned out to be more important with our geographical scope being Norway. The T2m turned out less sensitive to the changes in lateral forcing and the size of the integration domain than mslp and precipitation. The sensitivity for all three variables differed between Norwegian regions; northern parts of Norway were the most sensitive. Even though the sensitivities found in this study might be different in other regions and for other RCMs, these results call for careful consideration when choosing integration domain and driving lateral boundary data when performing dynamical downscaling. Full article
(This article belongs to the Special Issue Regional Climate Change and Variability)
Open AccessArticle Effects of Floor Level and Building Type on Residential Levels of Outdoor and Indoor Polycyclic Aromatic Hydrocarbons, Black Carbon, and Particulate Matter in New York City
Atmosphere 2011, 2(2), 96-109; doi:10.3390/atmos2020096
Received: 11 April 2011 / Revised: 27 April 2011 / Accepted: 4 May 2011 / Published: 16 May 2011
Cited by 15 | PDF Full-text (621 KB) | HTML Full-text | XML Full-text
Abstract
Consideration of the relationship between residential floor level and concentration of traffic-related airborne pollutants may predict individual residential exposure among inner city dwellers more accurately. Our objective was to characterize the vertical gradient of residential levels of polycyclic aromatic hydrocarbons (PAH; dichotomized into Σ8PAHsemivolatile (MW 178–206), and Σ8PAHnonvolatile (MW 228–278), black carbon (BC), PM2.5 (particulate matter) by floor level (FL), season and building type. We hypothesize that PAH, BC and PM2.5 concentrations may decrease with higher FL and the vertical gradients of these compounds would be affected by heating season and building type. PAH, BC and PM2.5 were measured over a two-week period outdoor and indoor of the residences of a cohort of 5–6 year old children (n = 339) living in New York City’s Northern Manhattan and the Bronx. Airborne-pollutant levels were analyzed by three categorized FL groups (0–2nd, 3rd–5th, and 6th–32nd FL) and two building types (low-rise versus high-rise apartment building). Indoor Σ8PAHnonvolatile and BC levels declined with increasing FL. During the nonheating season, the median outdoor Σ8PAHnonvolatile, but not Σ8PAHsemivolatile, level at 6th–2nd FL was 1.5–2 times lower than levels measured at lower FL. Similarly, outdoor and indoor BC concentrations at 6th–32nd FL were significantly lower than those at lower FL only during the nonheating season (p < 0.05). In addition, living in a low-rise building was associated significantly with higher levels of Σ8PAHnonvolatile and BC. These results suggest that young inner city children may be exposed to varying levels of air pollutants depending on their FL, season, and building type. Full article
(This article belongs to the Special Issue Indoor Air Pollution)
Open AccessArticle Improving Ammonia Emission Modeling and Inventories by Data Mining and Intelligent Interpretation of the National Air Emission Monitoring Study Database
Atmosphere 2011, 2(2), 110-128; doi:10.3390/atmos2020110
Received: 26 January 2011 / Revised: 16 April 2011 / Accepted: 2 May 2011 / Published: 16 May 2011
Cited by 5 | PDF Full-text (300 KB) | HTML Full-text | XML Full-text
Abstract
Ammonia emission is one of the greatest environmental concerns in sustainable agriculture development. Several limitations and fundamental problems associated with the current agricultural ammonia emission modeling and emission inventories have been identified. They were associated with a significant disconnection between field monitoring [...] Read more.
Ammonia emission is one of the greatest environmental concerns in sustainable agriculture development. Several limitations and fundamental problems associated with the current agricultural ammonia emission modeling and emission inventories have been identified. They were associated with a significant disconnection between field monitoring data and knowledge about the data. Comprehensive field measurement datasets have not been fully exploited for scientific research and emission regulations. This situation can be considerably improved if the currently available data are better interpreted and the new knowledge is applied to update ammonia emission modeling techniques. The world’s largest agricultural air quality monitoring database with more than 2.4 billion data points has recently been created by the United States’ National Air Emission Monitoring Study. New approaches of data mining and intelligent interpretation of the database are planned to uncover new knowledge and to answer a series of questions that have been raised. The expected results of this new research idea include enhanced fundamental understanding of ammonia emissions from animal agriculture and improved accuracy and scope in regional and national ammonia emission inventories. Full article
(This article belongs to the Special Issue Regional Climate Change and Variability)
Open AccessArticle Climate Signals on the Regional Scale Derived with a Statistical Method: Relevance of the Driving Model’s Resolution
Atmosphere 2011, 2(2), 129-145; doi:10.3390/atmos2020129
Received: 14 January 2011 / Revised: 5 April 2011 / Accepted: 16 May 2011 / Published: 23 May 2011
Cited by 9 | PDF Full-text (1732 KB) | HTML Full-text | XML Full-text
Abstract
When assessing the magnitude of climate signals in a regional scale, a host of optional approaches is feasible. This encompasses the use of regional climate models (RCM), nested into global climate models (GCM) for an area of interest as well as employing [...] Read more.
When assessing the magnitude of climate signals in a regional scale, a host of optional approaches is feasible. This encompasses the use of regional climate models (RCM), nested into global climate models (GCM) for an area of interest as well as employing empirical statistical downscaling methods (ESD). In this context the question is addressed: Is an empirical statistical downscaling method capable of yielding results that are comparable to those by dynamical RCMs? Based on the presented ESD method, the comparison of RCM and ESD results show a high amount of agreement. In addition the empirical statistical downscaling can be applied directly to a GCM or a GCM-RCM cascade. The paper aims at comparing the consequences of employing various CGM-RCM-ESD combinations on the derived future changes of temperature and precipitation. This adds to the insight on the scale dependency of downscaling strategies. Results for one GCM with several scenario runs driving several RCMs with and without subsequent empirical statistical downscaling are presented. It is shown that there are only small differences between using the GCM results directly or as a GCM-RCM-ESD cascade. Full article
(This article belongs to the Special Issue Regional Climate Change and Variability)
Open AccessArticle An Ensemble of Arctic Simulations of the AOE-2001 Field Experiment
Atmosphere 2011, 2(2), 146-170; doi:10.3390/atmos2020146
Received: 13 April 2011 / Revised: 29 April 2011 / Accepted: 10 May 2011 / Published: 25 May 2011
Cited by 2 | PDF Full-text (2135 KB) | HTML Full-text | XML Full-text
Abstract
An ensemble of model runs with the COAMPS© regional model is compared to observations in the central Arctic for August 2001 from the Arctic Ocean Experiment 2001 (AOE-2001). The results are from a 6-km horizontal resolution 2nd, inner, nest of the [...] Read more.
An ensemble of model runs with the COAMPS© regional model is compared to observations in the central Arctic for August 2001 from the Arctic Ocean Experiment 2001 (AOE-2001). The results are from a 6-km horizontal resolution 2nd, inner, nest of the model while the outermost model domain covers the pan-Arctic region, including the marginal ice zone and some of the land areas around the Arctic Ocean. Sea surface temperature and ice cover were prescribed from satellite data while sea-ice surface properties were modeled with an energy balance model, assuming a constant ice thickness. Five ensemble members were generated by altering the initialization time for the innermost nest, the surface roughness and the turbulent mixing scheme for clouds. The large size of the outer domain means that the model simulations have substantial deviations from the observations at synoptic-scale time scales. Therefore the evaluation focuses on statistical measures, rather than in details of individual ensemble member performance as compared directly to observations. In this context, the ensemble members are surprisingly similar even though details differ significantly. The ensemble average results features two main systematic problems: a consistent temperature bias, with too low temperatures below 2–3 km and slightly high temperatures through the rest of the troposphere, and a significant underestimation of the lowest clouds. In terms of total cloud cover, however, the model produces a realistic result; it is the very lowest clouds that are essentially missing. The temperature bias initially appears to be related to an interaction between clouds and radiation; the shape of the mean radiative heating-rate profile is very similar to that of the temperature bias. The lack of the lowest clouds could be due to the too low temperatures in conjunction with a cloud scheme that overestimates the transfer of cloud droplets to ice particles that precipitate. The different terms in the surface energy balance as well as the surface stress has only small systematic errors and are surprisingly consistent between the members. Full article
(This article belongs to the Special Issue Regional Climate Change and Variability)
Open AccessArticle No Borders for Tobacco Smoke in Hospitality Venues in Vienna
Atmosphere 2011, 2(2), 171-181; doi:10.3390/atmos2020171
Received: 7 May 2011 / Revised: 2 June 2011 / Accepted: 3 June 2011 / Published: 17 June 2011
Cited by 2 | PDF Full-text (235 KB) | HTML Full-text | XML Full-text
Abstract
In public places many countries banned smoking as the most important indoor source of fine airborne particulate matter. In Austria partial bans have been in force since 2009, with exemptions for the hospitality industry. From February to October 2010 we investigated PM2.5 concentrations in the breathing area of guests in well frequented Viennese establishments of all sizes, and compared these chance indoor samples with PM2.5 concentrations measured during the same half hour at the next outdoor monitoring station. The laser particle counter (OPC1.108, Grimm®) used for indoor measurements had been calibrated by ß-attenuation (FH 62 I-R, Eberline®), which was used outdoors. 48% of 112 venues visited did not fully comply with the law, notwithstanding its weakness.  Highest median concentrations (in µg/m3) were found in bars (443.7), followed by nightclubs/discotheques (421.1), pubs (147.7), cafes (106.1) and restaurants (23.4). Concentrations increased with number of smokers present (p < 0.01), with medians of 282.4/241,3/67.6/6.9 µg/m³ in smoking venues/smoking rooms/adjacent non-smoking rooms/exclusive non-smoking venues. Only for the latter, a significant correlation was found with outdoor concentrations (r = 0.48, p < 0.01), while concentrations in non-smoking rooms were higher (p < 0.01) and unrelated to outdoor concentrations, but significantly dependent on concentrations in the adjacent smoking room (r = 0.64, p < 0.01). In conclusion, the partial smoking ban failed and guests of Viennese hospitality venues continue to risk disease from passive smoking, even in so-called “non-smoking rooms”, which are second-hand smoke rooms. Full article
Open AccessArticle Emissions from Ethanol-Gasoline Blends: A Single Particle Perspective
Atmosphere 2011, 2(2), 182-200; doi:10.3390/atmos2020182
Received: 8 May 2011 / Revised: 29 May 2011 / Accepted: 13 June 2011 / Published: 22 June 2011
Cited by 16 | PDF Full-text (1280 KB) | HTML Full-text | XML Full-text
Abstract
Due to its agricultural origin and function as a fuel oxygenate, ethanol is being promoted as an alternative biomass-based fuel for use in spark ignition engines, with mandates for its use at state and regional levels. While it has been established that [...] Read more.
Due to its agricultural origin and function as a fuel oxygenate, ethanol is being promoted as an alternative biomass-based fuel for use in spark ignition engines, with mandates for its use at state and regional levels. While it has been established that the addition of ethanol to a fuel reduces the particulate mass concentration in the exhaust, little attention has been paid to changes in the physicochemical properties of the emitted particles. In this work, a dynamometer-mounted GM Quad-4 spark ignition engine run without aftertreatment at 1,500 RPM and 100% load was used with four different fuel blends, containing 0, 20, 40 and 85 percent ethanol in gasoline. This allowed the effects of the fuel composition to be isolated from other effects. Instrumentation employed included two Aerosol Time-of-Flight Mass Spectrometers covering different size ranges for analysis of single particle composition, an Aethalometer for black carbon, a Scanning Mobility Particle Sizer for particle size distributions, a Photoelectric Aerosol Sensor for particle-bound polycyclic aromatic hydrocarbon (PAH) species and gravimetric filter measurements for particulate mass concentrations. It was found that, under the conditions investigated here, additional ethanol content in the fuel changes the particle size distribution, especially in the accumulation mode, and decreases the black carbon and total particulate mass concentrations. The molecular weight distribution of the PAHs was found to decrease with added ethanol. However, PAHs produced from higher ethanol-content fuels are associated with NO2 (m/z—46) in the single-particle mass spectra, indicating the presence of nitro-PAHs. Compounds associated with the gasoline (e.g., sulfur-containing species) are diminished due to dilution as ethanol is added to the fuel relative to those associated with the lubricating oil (e.g., calcium, zinc, phosphate) in the single particle spectra. These changes have potential implications for the health effect impacts of particulate emissions from biofuel blends. Full article
(This article belongs to the Special Issue Particulate Pollution Related to Vehicle Emission)

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