Urban transport and dispersion model sensitivity to wind direction uncertainty and source location

Rodriguez, Luna M.; Bieringer, Paul E.; Warner, Thomas T.

doi:10.1016/j.atmosenv.2012.08.037

Cited by 17 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In real conditions wind velocity has three, and not two, components u x , u y , u z , which change in time and which sum up with disturbances in the airflow generated by buildings (the surrounding of a canyon), street intersections, vehicle motion and other topographic elements and technical factors. Rodriguez et al (2013) say as in the areas of compact settlement considerable fluctuations of wind direction and its velocity lead to a general velocity reduction. − Air convection in the wake of the local heat sources (local heat island) -apart from considerable heat emissions from vehicles, it can also be heat emitted from heated buildings, air conditioners and wall surfaces that absorb sun rays.…”

Section: Introductionmentioning

confidence: 99%

Traffic air quality index

Bagieński

2015

Science of The Total Environment

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Traffic air quality index

Bagieński

2015

Science of The Total Environment

View full text Add to dashboard Cite

“…There is a direct relationship between the meteorological conditions such as wind speed and ambient temperature on the plume characteristics. Therefore, any uncertainty in the meteorological input data will be directly reflected in the output (Mahanta et al 2013;Rodriguez et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Dispersion modeling of thermal power plant emissions on stochastic space

Gorle

Sambana

2015

Theor Appl Climatol

View full text Add to dashboard Cite

This study aims to couple a deterministic atmospheric dispersion solver based on Gaussian model with a nonintrusive stochastic model to quantify the propagation of multiple uncertainties. The nonintrusive model is based on probabilistic collocation framework. The advantage of nonintrusive nature is to retain the existing deterministic plume dispersion model without missing the accuracy in extracting the statistics of stochastic solution. The developed model is applied to analyze the SO 2 emission released from coal firing unit in the second stage of the National Thermal Power Corporation (NTPC) in Dadri, India using Burban^conditions. The entire application is split into two cases, depending on the source of uncertainty. In case 1, the uncertainties in stack gas exit conditions are used to construct the stochastic space while in case 2, meteorological conditions are considered as the sources of uncertainty. Both cases develop 2D uncertain random space in which the uncertainty propagation is quantified in terms of plume rise and pollutant concentration distribution under slightly unstable atmospheric stability conditions. Starting with deterministic Gaussian plume model demonstration and its application, development of stochastic collocation model, convergence study, error analysis, and uncertainty quantification are presented in this paper.

show abstract

“…Dentre as pesquisas relacionadas às partículas atmosféricas, destaca-se o grande número das que tiveram o objetivo de estudar o processo de dispersão do poluente. Estudos têm mostrado que o vento é um fator ambiental importante para a dispersão dos particulados (STEINKE, 2012;CHINA;RODRIGUEZ et al, 2013). Por exemplo, na Holanda, Hendriks et al (2013) identificaram que 2/3 da concentração de MP10 é de origem de outros países.…”

Section: Particuladosunclassified

“…Vale destacar que os particulados também podem ser classificados como secundários, após os processos de remoção e formação de particulados na atmosfera (ASSUNÇÃO, 2004;CHRISTOPHERSON, 2012;ANDREAE, 2013;BECHLE et al, 2013). (TANG et al, 2001;WALLACE et al, 2009;RODRIGUEZ et al, 2013).…”

Section: Gasesunclassified

“…Sugere-se que a dispersão das partículas atmosféricas decorrentes do solo exposto no DF a longas distâncias está sendo influenciadas por condições meteorológicas, por exemplo, o vento. Estudos anteriores (WALLACE et al, 2009;RODRIGUEZ et al, 2013) mostram que a velocidade do vento podem contribuir significativamente para a existência do risco decorrentes de material particulado vindo do solo em distâncias maiores que 2.520 m.…”

Section: Categoriaunclassified

See 1 more Smart Citation

Modelagem espacial da exposição humana às fontes de poluição do ar no Distrito Federal : o uso e ocupação do solo como variável preditora

Júnior¹,

João²

View full text Add to dashboard Cite

Air pollution sources are associated with harmful effects on human health. Cardiorespiratory diseases occurrence are indicators of human exposure to air pollutants. The measurement of this exposure is used as collaborative toll for sources control and management in order to promote quality of life to population. Among the methods for measurement (monitoring station, remote sensing, land use models, biomonitoring, portables devices), the challenge is related to the equilibrium between the aim of the measurement and the cost. Faced with this operational and economic challenge, most of the urban centers still have a gap to measure human exposure to air pollution, for example, the Federal District (FD). The method which represents the land use models is prominent for the challenges in urban areas as the FD, and also for urban areas which already have a monitoring system consolidated. However, the land use models are in initial process of research, which need more development. For instance, it is still unclear the understanding of the spatial relationship between land use, air pollution sources and human health. Therefore, this research tested the hypothesis that in the FD human exposure to air pollution sources can be estimated by classification and measurement of land use. It was considered as land use in this study three categories: vehicular traffic, conventional land use, and land use related to urban typology-Urban Structure Types (UST). It was addressed seven specific objectives in this research: 1) to estimate emissions from the roads; 2) to create a geodatabase for health data; 3) to assess the relationship between health and vehicle emissions; 4) to evaluate spatial patterns of cardiorespiratory diseases; 5) to identify high-priority areas to measure human exposures to air pollution sources; 6) to estimate the cardiorespiratory disease risk related to land use; and 7) to evaluate the relationship between UST and cardiorespiratory diseases risk. The methods are as follows: bottom-up to calculate vehicular emissions; Modeling in Geographic Information System (GIS) for geodatabase creation; Geostatistical analysis with Global Moran's I, Getis-Ord General G, semivariogram analysis and k-function; Analytic Hierarchy Process (AHP) for decision making and values judgment, and; Ordinary Least Square regression (OLS) and quantile regression for assessment of the relationship between sources and human health. The findings are as follows: the light vehicles presented a different (cluster) spatial patters of air pollution emissions; Spatial patterns of cardiorespiratory diseases are clustered; There are no air pollution monitoring stations in areas which were identified with high priorities levels to measure human exposures; the number of light vehicles was associated with hospital admissions risk (risk = 6 admissions; 95% CI: 2.6; 14.6); A 2,500 m increase in highways was associated with a 46% increase in cardiorespiratory diseases; A 6,000 m increase in streets and avenues was associated with a 51% increase in cardior...

show abstract

Urban transport and dispersion model sensitivity to wind direction uncertainty and source location

Cited by 17 publications

References 5 publications

Traffic air quality index

Traffic air quality index

Dispersion modeling of thermal power plant emissions on stochastic space

Modelagem espacial da exposição humana às fontes de poluição do ar no Distrito Federal : o uso e ocupação do solo como variável preditora

Contact Info

Product

Resources

About