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1.
Atmos Environ (1994) ; 174: 214-226, 2017 Nov 21.
Artigo em Inglês | MEDLINE | ID: mdl-29456452

RESUMO

The objective of this research is to learn how the near-road gradient, in which NO2 and NOX (NO + NO2) concentrations are elevated, varies with changes in meteorological and traffic variables. Measurements of NO2 and NOX were obtained east of I-15 in Las Vegas and fit to functions whose slopes (dCNO2 /dx and dCNOX /dx, respectively) characterize the size of the near-road zone where NO2 and NOX concentrations from mobile sources on the highway are elevated. These metrics were used to learn about the near-road gradient by modeling dCNO2 /dx and dCNOX /dx as functions of meteorological variables (e.g., wind direction, wind speed), traffic (vehicle count), NOX concentration upwind of the road, and O3 concentration at two fixed-site ambient monitors. Generalized additive models (GAM) were used to model dCNO2 /dx and dCNOX /dx versus the independent variables because they allowed for nonlinearity of the variables being compared. When data from all wind directions were included in the analysis, variability in O3 concentration comprised the largest proportion of variability in dCNO2 /dx, followed by variability in wind direction. In a second analysis constrained to winds from the west, variability in O3 concentration remained the largest contributor to variability in dCNO2 /dx, but the relative contribution of variability in wind speed to variability in dCNO2 /dx increased relative to its contribution for the all-wind analysis. When data from all wind directions were analyzed, variability in wind direction was by far the largest contributor to variability in dCNOX /dx, with smaller contributions from hour of day and upwind NOX concentration. When only winds from the west were analyzed, variability in upwind NOX concentration, wind speed, hour of day, and traffic count all were associated with variability in dCNOX /dx. Increases in O3 concentration were associated with increased magnitude near-road dCNO2 /dx, possibly shrinking the zone of elevated concentrations occurring near roads. Wind direction parallel to the highway was also related to an increased magnitude of both dCNO2 /dx and dCNOX /dx, again likely shrinking the zone of elevated concentrations occurring near roads. Wind direction perpendicular to the road decreased the magnitude of dCNO2 /dx and dCNOX /dx and likely contributed to growth of the zone of elevated concentrations occurring near roads. Thus, variability in near-road concentrations is influenced by local meteorology and ambient O3 concentration.

2.
Sci Total Environ ; 407(10): 3357-64, 2009 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-19250655

RESUMO

An air quality study was performed outside a cluster of schools in the East Harlem neighborhood of New York City. PM(2.5) and black carbon concentrations were monitored using real-time equipment with a one-minute averaging interval. Monitoring was performed at 1:45-3:30 PM during school days over the period October 31-November 17, 2006. The designated time period was chosen to capture vehicle emissions during end-of-day dismissals from the schools. During the monitoring period, minute-by-minute volume counts of idling and passing school buses, diesel trucks, and automobiles were obtained. These data were transcribed into time series of number of diesel vehicles idling, number of gasoline automobiles idling, number of diesel vehicles passing, and number of automobiles passing along the block adjacent to the school cluster. Multivariate regression models of the log-transform of PM(2.5) and black carbon (BC) concentrations in the East Harlem street canyon were developed using the observation data and data from the New York State Department of Environmental Conservation on meteorology and background PM(2.5). Analysis of variance was used to test the contribution of each covariate to variability in the log-transformed concentrations as a means to judge the relative contribution of each covariate. The models demonstrated that variability in background PM(2.5) contributes 80.9% of the variability in log[PM(2.5)] and 81.5% of the variability in log[BC]. Local traffic sources were demonstrated to contribute 5.8% of the variability in log[BC] and only 0.43% of the variability in log[PM(2.5)]. Diesel idling and passing were both significant contributors to variability in log[BC], while diesel passing was a significant contributor to log[PM(2.5)]. Automobile idling and passing did not contribute significant levels of variability to either concentration. The remainder of variability in each model was explained by temperature, along-canyon wind, and cross-canyon wind, which were all significant in the models.


Assuntos
Carbono/análise , Monitoramento Ambiental , Material Particulado/análise , Instituições Acadêmicas , Emissões de Veículos/análise , Tempo (Meteorologia) , Veículos Automotores , Cidade de Nova Iorque , Tamanho da Partícula , Fatores de Tempo , Saúde da População Urbana
3.
Sci Total Environ ; 409(11): 2085-93, 2011 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-21406309

RESUMO

A study was performed to assess the relationship between black carbon (BC), passing traffic, and vehicular idling outside New York City (NYC) schools during student dismissal. Monitoring was performed at three school sites in East Harlem, the Bronx, and Brooklyn for 1month per year over a two-year period from November 2006-October 2008. Monitoring at each site was conducted before and after the Asthma Free School Zone (AFSZ) asthma reduction education program was administered. Real-time equipment with a one-minute averaging interval was used to obtain the BC data, while volume counts of idling and passing school busses, trucks, and automobiles were collected each minute by study staff. These data were matched to ambient PM(2.5) and meteorology data obtained from the New York State Department of Environmental Conservation. A generalized additive model (GAM) model was run to examine the relationship between BC concentration and each variable while accounting for site-to-site differences. F-tests were employed to assess the significance of each of the predictor variables. The model results suggested that variability in ambient PM(2.5) concentration contributed 24% of the variability in transformed BC concentration, while variability in the number of idling busses and trucks on the street during dismissal contributed 20% of the variability in transformed BC concentration. The results of this study suggest that a combination of urban scale and local traffic control approaches in combination with cessation of school bus idling will produce improved local BC concentration outside schools.


Assuntos
Poluentes Atmosféricos/análise , Poluição do Ar/estatística & dados numéricos , Automóveis/estatística & dados numéricos , Instituições Acadêmicas/estatística & dados numéricos , Fuligem/análise , Poluentes Atmosféricos/normas , Atmosfera/química , Monitoramento Ambiental , New York , Material Particulado/análise , Material Particulado/normas , Fuligem/normas , Emissões de Veículos/análise , Tempo (Meteorologia)
4.
Indoor Air ; 16(1): 48-55, 2006 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-16420497

RESUMO

The objective of this study is to test a technique used to analyze contaminant transport in the wake of a bluff body under controlled experimental conditions for application to aerosol transport in a complex furnished room. Specifically, the hypothesis tested by our work is that the dispersion of contaminants in a room is related to the turbulence kinetic energy and length scale. This turbulence is, in turn, determined by the size and shape of furnishings within the room and by the ventilation characteristics. This approach was tested for indoor dispersion through computational fluid dynamics simulations and laboratory experiments. In each, 3 mum aerosols were released in a furnished room with varied contaminant release locations (at the inlet vent or under a desk). The realizable k approximately epsilon model was employed in the simulations, followed by a Lagrangian particle trajectory simulation used as input for an in-house FORTRAN code to compute aerosol concentration. For the experiments, concentrations were measured simultaneously at seven locations by laser photometry, and air velocity was measured using laser Doppler velocimetry. The results suggest that turbulent diffusion is a significant factor in contaminant residence time in a furnished room. This procedure was then expanded to develop a simplified correlation between contaminant residence time and the number of enclosing surfaces around a point containing the contaminant. Practical Implications The work presented here provides a methodology for relating local aerosol residence time to properties of room ventilation and furniture arrangement. This technique may be used to assess probable locations of high concentration by knowing only the particle release location, furniture configuration, inlet and outlet locations, and air speeds, which are all observable features. Applications of this method include development of 'rules of thumb' for first responders entering a room where an agent has been released and selection of sampler locations to monitor conditions in sensitive areas.


Assuntos
Movimentos do Ar , Poluentes Atmosféricos/química , Poluição do Ar em Ambientes Fechados , Simulação por Computador , Humanos , Decoração de Interiores e Mobiliário , Exposição Ocupacional
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