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Risk Assessment Techniques and Methods of Approach
Published in D. Kofi Asante-Duah, Hazardous Waste Risk Assessment, 2021
Atmospheric dispersion modeling is an APA approach that can provide calculated contaminant concentrations at potential receptor locations of interest based on emission rate and meteorological data. Thus, atmospheric dispersion modeling (for Superfund and other activities) has become an integral part of the planning and decision-making process for the protection of public health and the environment. The following information, at a minimum, need to be collected and reviewed to support the air modeling program design: Source data (including contaminant toxicity factors, offsite sources, etc.)Receptor data (including identification of sensitive receptors, local land use, etc.)Environmental data (including dispersion data, climatology, topographic maps, soil and vegetation, etc.)Previous APA data (including ARARs summary, air monitoring, emission rate monitoring and modeling, dispersion modeling, etc.).
Contaminant Fate and Behavior Assessment
Published in Kofi Asante-Duah, Management of Contaminated Site Problems, 2019
Atmospheric dispersion modeling has become an integral part of the planning and decision-making process in the assessment of public health and environmental impacts from various chemical release and contaminated site problems. It is an approach that can indeed be used to provide contaminant concentrations at potential receptor locations of interest based on emission rate and meteorological data. Naturally, the accuracy of the model predictions depends on the accuracy and representativeness of relevant input data. Broadly speaking, key model input data will include emissions and release parameters, meteorological data, and receptor locations. Typically, existing air monitoring data (if any) for the locale/area of interest can be utilized to facilitate the design of a receptor grid, as well as to select “indicator chemicals” to be modeled. This can also provide insight into likely background concentrations. Indeed, in all situations, case-specific data should be used whenever possible—in order to increase the accuracy of the emission rate estimates.
Odors and Volatile Organic Compounds
Published in Epstein Eliot, The Science of Composting, 2017
Atmospheric dispersion modeling is a technique for estimating pollutant concentrations caused by source emissions. While it is impossible to fully model the complexities of the atmosphere and the exact transport and dispersion of pollutants, a series of mathematical formulae have been developed from empirical and theoretical studies to reliably estimate pollutant concentrations.
Advection - diffusion model for indoor-outdoor exchange of air pollutants from electric power generators servicing buildings
Published in Cogent Engineering, 2022
Olumuyiwa Akintola, Jacob Sonibare
The transportation of contaminants in the atmosphere can be described mathematically and this refers to atmospheric dispersion modelling. This dispersion describes the combination of factors occurring within the air near the earth’s surface including diffusion and advection (Stockie, 2010). Advection and diffusion are the main physical processes that occur when pollutants disperse in the atmosphere. Advection is the air movement which transports pollutants by wind as a bulk motion, while diffusion is the particle movement from high concentration to low concentration due to collision between the particles with movement stopping at the point of equilibrium. Diffusion is caused by turbulent eddy motion; it is the irregular air movement where by the wind constantly varies in speed and direction. The mathematical formulation of the air pollution dispersion is based on the conservation of mass equation which describes advection, turbulent diffusion, chemical reaction among others (Agarwal and Tandon, 2009). The advection-diffusion equation is stated as:
Performance of AERMOD and CALPUFF models on SO2 and NO2 emissions for future health risk assessment in Tema Metropolis
Published in Human and Ecological Risk Assessment: An International Journal, 2019
Patrick Amoatey, Hamid Omidvarborna, Hannah A. Affum, Mahad Baawain
There are several advanced air quality dispersion models including the regulatory model for long transport dispersion called California Puff Model (CALPUFF) (Affum et al.2016), the US EPA Regulatory Model (AERMOD) (Seangkiatiyuth et al.2011), Industrial Source Complex Model (ISCST3) (Rama Krishna et al.2005), and Atmospheric Dispersion Modeling Software (ADMS) (Ali and Athar 2010). These models are developed based on the Gaussian plume model, which determines the vertical and horizontal spread of the plume, in both simple and complex terrains (Daly and Zannetti 2007). The models are being used to estimate the concentration level of different pollutants, which help to assess health risk assessment analysis. For example, Seangkiatiyuth et al. (2011) used AERMOD to assess the impact of NO2 emissions from a cement plant in Bangkok, Thailand. Mokhtar et al. (2014) assessed the health risk effect of SO2 from a coal-fired power plant by using AERMOD. AERMOD was employed for the prediction of hydrogen sulfide (H2S) emissions, a neighborhood claimed issue, from a sewage treatment plant (STP) in Oman (Baawain et al.2017). AERMOD predictions performed well with measured NOx and PM10 concentrations through the application of Weather Research Forecasting (WRF) model (Kumar et al.2017). Likewise, AERMOD was used to study the line sources of SO2 and NOx in Nova Scotia, Canada (Gibson et al.2013). Although AERMOD offers an opportunity to carry out a wide array of air quality applications, Mohan et al. (2011) concluded that AERMOD could underpredict suspended PM (SPM) with low bias between the measured the modeling results.