نتایج جستجو برای: air quality dispersion model
تعداد نتایج: 2944826 فیلتر نتایج به سال:
Background: Air Quality Index (AQI) quantifies the relationship between air quality and the level of health. The value of AQI may be predicted using neural network model for a day in advance, based on the meteorological variables and autocorrelation behavior of the index in Kermanshah, a city in western Iran. Methods: Data for air pollution and meteorological variables, collected during thre...
background: in the past few decades, indoor air pollution (iap) has become a primary concern to the point. it is increasingly believed to be of equal or greater importance to human health compared to ambient air. however, due to the lack of comprehensive indices for the integrated assessment of indoor air quality (iaq), we aimed to develop a novel, fuzzy-based indoor air quality index (fiaqi) t...
AERMOD was used to model the air dispersion of point and major line emissions of PM2.5 in Halifax and Pictou, NOX in Halifax and SO2 in Halifax, Sydney and Port Hawkesbury, Nova Scotia, Canada. Emission inventory data for 2004 were used in simulations within four, 50 km x 50 km, domains over annual, monthly and 1–hour averaging periods. Annual averaged surface concentration maps are reported...
OBJECTIVE Odor exposure is an environmental stressor that is responsible of many citizens complains about air pollution in non-urban areas. However, information about the exposure-response relation is scarce. One of the main challenges is to identify a measurable compound that can be related with odor annoyance responses. We investigated the association between regional and temporal variation o...
background: air pollution and concerns about health impacts have been raised in metropolitan cities like tehran. trend and prediction of air pollutants can show the effectiveness of strategies for the management and control of air pollution. artificial neural network (ann) technique is widely used as a reliable method for modeling of air pollutants in urban areas. therefore, the aim of current ...
Background and Objective: Concentration prediction with Gaussian dispersion models is highly sensitive to meteorological data. The lack of sounding data station in developing countries may lead to large error and uncertainty in air pollution modeling results. In this paper, the effects of estimated upper air data on the model output concentration values were investigated. Materials and Met...
Epidemiological studies of the health effects of air pollution require estimation of individual exposure. It is not possible to obtain measurements at all relevant locations so it is necessary to predict at these space-time locations, either on the basis of dispersion from emission sources or by interpolating observations. This study used data obtained from a low-cost sensor network of 32 air q...
Background: Air Quality software is a useful tool for assessing the health risks associated with air pollutants. Quantifying the effects of exposure to air pollutants in terms of public health has become a critical component of policy discussion. The present study purposed to quantify the health effects of particulate matters on mortality and morbidity in a Bukan city hospital from 2015-2016. ...
Dispersion modeling approach was applied for the determination of SO2 and NO2 pollution in the ambient air. The model performance has been evaluated by comparing the measured and predicted concentrations of SO2 and NO2. This has been tested to measure the air quality and predicted incremental value of pollutant’s concentrations by using the data avail...
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