Maximum Ground Level Concentration Research Articles

SAPERI: An Emergency Modeling Chain for Simulating Accidental Releases of Pollutants into the Atmosphere

Timely forecast of atmospheric pollutants fallout due to accidental fires can provide decision-makers with useful information for effective emergency response, for planning environmental monitoring and for conveying essential alerts to the population to minimize health risks. The SAPERI project (Accelerated simulation of accidental releases in the atmosphere on heterogeneous platforms—from its Italian initials) implements a modeling chain to quickly supply evidence about the dispersion of pollutants accidentally released in the atmosphere, even in the early stages of the emergency when full knowledge of the incident details is missing. The SAPERI modeling chain relies on SPRAY-WEB, a Lagrangian particle dispersion model openly shared for research purposes, parallelized on a GPU to take advantage of local or cloud computing resources and interfaced with open meteorological forecasts made available by the Meteo Italian SupercompuTing PoRtAL (MISTRAL) consortium over Italy. The operational model provides a quantitative and qualitative estimate of the impact of the emergency event by means of a maximum ground level concentration and a footprint map. In this work, the SAPERI modeling chain is tested in a real case event that occurred in Beinasco (Torino, Italy) in December 2021, mimicking its use with limited or missing local input data as occurs when an alert message is first issued. An evaluation of the meteorology forecast is carried out by comparing the wind and temperature fields obtained from MISTRAL with observations from weather stations. The concentrations obtained from the dispersion model are then compared with the observations at three air quality monitoring stations impacted by the event.

Modelling the atmospheric dispersion of ammonia in an industrial area in northern Greece

Air pollution is one of the greatest challenges for ecosystems globally, as it adversely affects not only human health, but also water resources, land, animals and plants. The composition of atmospheric air is changing due to urbanization, industry, land surface alteration, climate change and global population increase. Studying the dispersion of atmospheric pollutants is a crucial issue for better urban, regional and global predictions of air quality. Dispersion models have proven a valuable tool in estimating the concentration of air pollutants produced by industrial facilities, as well as predicting future concentrations under specific scenarios (e.g., changes in emission sources or emission rates). The objective of this research was to examine a number of hypothetical industrial accident scenarios, including the local spread of ammonia from an industrial zone located 5 km east of the coastal city of Kavala in northern Greece. For that, the Atmospheric Dispersion Modeling System 5 (ADMS-5) was used as a safety and emergency planning tool, in order to model instantaneous releases (puffs) of ammonia and to investigate changes in ground-level concentration. To determine the structure of the atmospheric boundary layer, seven different meteorological conditions which correspond to the Pasquill-Gifford stability categories A-G were considered. The maximum ground-level concentration (1400 - 2400 μg/m3) occurred in slightly stable and moderately stable conditions (categories E and F) very close to the source, while in extremely stable conditions (category G) the puff remained stagnant for over 600 s after release. The lowest ground-level concentration (300 μg/m3) occurred with slightly unstable conditions (category C). The obtained results can be used for safety and emergency planning reasons and highlight the importance of atmospheric stability on the fate of accidental industrial releases.

Maximum ground level concentration for Gaussian plume formula using standard and Briggs methods

AbstractThis work aims to determine the maximum concentration and downwind distance at the earth's surface in two methods Briggs and standard for two conditions are slightly unstable and neutral by using the Gaussian equation at different effective heights and wind seeped at (8.9, 8.5 and 8 m/s) under lateral and vertical dispersion coefficient measurement.

Evaluation of Source Emissions Dispersion Potential Near a Coastal Village of Maharashtra, India

Industrial emissions are a serious environmental problem worldwide due to particulates and toxic gases. This study aims to generate an activity-specific emission inventory and estimate emissions dispersion extent in the vicinity of the coastal industrial village by simulating the existing coke oven and pellet plant emissions using the steady-state plume model. Continuous air quality monitoring results were compared with the predicted consequential emissions for the year 2018-19. The maximum ground-level concentrations of particulate and gases within the modeling simulation domain were observed at 9005 m away from the center. They were predicted to be 116.39 μg.m-3, 79.14 μg.m-3, 52.97 μg.m-3, and 211.86 μg.m-3. Data analysis showed that air mass transport from the project to the receptor sites resulted in ambient air concentrations higher than those observed in the other sites. Overall predicted results obtained from AERMOD Cloud simulations were shown to have less bias than the measured results. They recommended considering it as appropriate for the prediction of annual average concentration.

Ten-year emission characteristics of atmospheric pollutants from incineration of sacrificial offerings in China

The incineration of sacrificial offerings is a significant widely practiced custom that is also a kind of neglected air pollution source in China. Our results showed that the emission factors of particulate matter, SO2, CO, NOx, and VOCs emitted from the incineration of sacrificial offerings with purification systems were reduced by 95%, 19%, 9%, 82%, and 42%, respectively, compared with those without a purification system, revealing a significant effect of the flue gas purification system on reducing particulate matter and gaseous pollutants. The emission level of air pollutants from the incineration of sacrificial offerings remained stable before 2013 and then showed a remarkable decrease after the implementation of China´s Air Pollution Prevention Action Plan in 2013. The emissions of TSP (total suspended particulate), PM10, PM2.5, and NOx in 2009 were 8222, 6106, 5656 and 15,878 ton, respectively, obviously higher than 3434, 2551, 2305 and 8579 ton in 2019. Such trend was affected by both the quantity of incineration and the installation rate of purification systems after the Emission Standard of Air Pollutants for Crematory (GB 13801-2015) issued in China. Distinct spatial distribution of atmospheric pollutants from incineration of sacrificial offerings was found with higher in the east and south of China than the west and north of China, which is proportional to the regional economy and population. The maximum ground-level concentration typically occurred at 0.12-0.2 km from the pollution source, posing potential health risks to people entering and exiting funeral and burial sites and nearby residents.

Demarcation of Pollution-Prone Areas around the Manyoni Uranium Project, Tanzania

This study employed PM10 source parameters and pre-processed topographical and meteorological data as input into the AERMOD atmospheric dispersion model to demarcate pollution-prone areas around the Manyoni Uranium Project. Knowing these areas before mining is an important step toward establishing efficient and effective environmental baseline data. This is because resources for collecting the data will be concentrated in areas with higher contamination potential. In this regard, AERMOD predicted that the regions suitable for pollution demarcation would be 25.55 km2, 25.85 km2, and 27.96 km2 if the prospective mine at Playa C1 operated for 5, 7, and 10 years, respectively. Within the demarcated areas, AERMOD predicted that the maximum annual ground level concentration of PM10 averaged over 5, 7, and 10 years would be 22.2 µg m-3, 22.8 µg m-3, and 25.7 µg m-3, respectively. These values are 11%, 14%, and 28.5% higher than the WHO annual limit of 20 µg m-3 for PM10. This information can help mine owners and government agencies figure out ways to protect people and the environment from the expected pollution.

A machine learning model to estimate ground-level ozone concentrations in California using TROPOMI data and high-resolution meteorology

Estimating ground-level ozone concentrations is crucial to study the adverse health effects of ozone exposure and better understand the impacts of ground-level ozone on biodiversity and vegetation. However, few studies have attempted to use satellite retrieved ozone as an indicator given their low sensitivity in the boundary layer. Using the Troposphere Monitoring Instrument (TROPOMI)'s total ozone column together with the ozone profile information retrieved by the Ozone Monitoring Instrument (OMI), as TROPOMI ozone profile product has not been released, we developed a machine learning model to estimate daily maximum 8-hour average ground-level ozone concentration at 10 km spatial resolution in California. In addition to satellite parameters, we included meteorological fields from the High-Resolution Rapid Refresh (HRRR) system at 3 km resolution and land-use information as predictors. Our model achieved an overall 10-fold cross-validation (CV) R2 of 0.84 with root mean square error (RMSE) of 0.0059 ppm, indicating a good agreement between model predictions and observations. Model predictions showed that the suburb of Los Angeles Metropolitan area had the highest ozone levels, while the Bay Area and the Pacific coast had the lowest. High ozone levels are also seen in Southern California and along the east side of the Central Valley. TROPOMI data improved the estimate of extreme values when compared to a similar model without it. Our study demonstrates the feasibility and value of using TROPOMI data in the spatiotemporal characterization of ground-level ozone concentration.

Ecological impact on the environment of industrial mining of bentonite clays

The object of the study is the Kattakurgan deposit of bentonite clays. During the implementation of the project, an environmental analysis of the design solution and the facility itself was carried out in terms of emissions, discharges, waste generation, and the degree of their impact on the environment was assessed. As a result of the environmental analysis, 6 sources of emission of pollutants, 4 unorganized sources of emissions of harmful substances of the area type were identified. The main source of air pollution is the bentonite clay quarry. In terms of ingredients, inorganic dusts account for the bulk of emissions. Analysis of the dispersion fields of pollutant emissions showed that the maximum ground-level concentrations of the considered harmful substances outside the enterprise do not exceed the values established by quotas. The water supply of the enterprise is carried out at the expense of imported water. Wastewater only includes domestic wastewater. An inventory of production and consumption wastes was carried out. It has been established that 5 types of waste are generated in the process of production activities of the deposit. The waste is non-toxic and low-hazard. Calculation of limits for disposal of production waste.

Methodology and examples for assessing the environmental performance of certain road traffic management measures

The article describes the methodology for assessing the impact of road traffic management (RTM) measures on the environment and public health. As an approbation of the methodology, such measures as ban on the movement of heavy trucks, ban on the movement of cars worse than the third ecological class and organizing the movement of non-motorized transport (NMT) are considered. Assessment of these measures impact on the environment was to provide an assessment of the pollutant emissions by the transport flow, the maximum and annual average ground-level concentrations of pollutants at the adjoining territory, the traffic flow noise characteristics (TFNC) and the equivalent sound levels at the adjoining territory. These estimates formed the basis for calculating public health risk indicators. Studies have shown that the greatest efficiency can be provided by measures to organize the movement of NMT and ban on the low environmental classes’ vehicles movement. It is also shown, that in addition to the traffic flows characteristics, specific features of the territory under consideration also have a significant impact on the results.

Plume Model: A Simple Approach to Air Quality Control

Air is an essential element in the life of humans, and everyone deserves to breathe in clean air. But anthropogenic activities from industrialization and modernization, as well as some natural disasters such as earth quake and volcanic eruption pollute the air. Consequently, air pollution threatens the health of people living in close proximity to the source of pollution by causing or aggravating sicknesses like, heart problem, cancer and respiratory disorder. The dispersion of air from a point source tends to follow the shape of Gaussian or normal statistical distribution. The present paper aims at examining Gaussian plume model as the easiest and simplest model among the lists of air dispersion models evaluated, stating the various issues from the source to the receptors. Gaussian Plume model is mostly used in the analysis of air dispersion with the concentration of a given place, having function of the distance from the source, emission rate and the meteorological data, mostly temperature, wind speed and wind direction, with the help of some various assumptions, in order to estimate how much air has reduced or travelled from the source and the concentration at the ground level. The model uses Briggs coefficients sigma y and z to get both vertical and horizontal dispersion. Plume rise determines dispersion and transportation levels, and thereby affect the distance to maximum ground level concentration and the maximum ground level concentration, the taller the stack or chimney (source), the larger the plume and the lower the concentration at the ground. A week analysis on pollutants generated from Larfarge cement factory Sagamu, Ogun State was carried out. The result shows mathematical simulation of Gaussian plume model of pollutants concentrations from the source and the applicability of the model.

Improvement of environmental conditions by applying heat recovery technologies of boiler plants

Purpose. Analysis of the effectiveness of using methods of heat and humidity treatment of flue gases to improve the operational modes of chimneys for heating gas-consuming boiler plants with heat recovery systems. Methodology. The known normative methods of thermal calculation of boiler plants and methods of dispersion of pollutants emitted by chimneys of these plants were used. To determine the thermal and moisture parameters of flue gases during their deep cooling, an original method developed at the Institute of Engineering Thermophysics of the National Academy of Sciences of Ukraine was used. Findings. The efficiency of applying the proposed thermal methods to improve environmental conditions and magnification of the operational reliability of chimneys of boiler plants equipped with systems for deep heat recovery of exhaust gases has been studied. The methods which are usually used in boiler-houses to prevent condensate formation in chimneys were considered. Adecrease in the maximum ground-level concentration of nitrogen oxides and carbon monoxide emissions was determined when using these methods. A comparative analysis of the effectiveness of the proposed methods for brick and metal chimneys in different modes of operation of heating boiler plants has been carried out. It is shown that these methods allow improving significantly (up to 32%) the indicators of ecological efficiency of chimneys in conditions of 58% reduction of fuel use in boilers. Originality. For the first time to improve the environmental performance of chimneys of boiler plants with deep heat recovery systems of flue gases has been justified the use of thermal methods of their heat and moisture treatment. Practical value. The possibility of using the results of the work in the design of heat recovery systems for gas-consuming heating boilers.

Mercury from crematoriums: human health risk assessment and estimate of total emissions in British Columbia.

Mercury occurs in the environment as a result of natural processes and human activities, including when individuals with amalgam dental fillings are cremated. This work aimed to estimate the quantity of mercury emitted to the atmosphere from crematoriums in British Columbia (BC) and assess the human health risk. A BC-specific emissions factor for mercury from crematoriums was developed and applied to an estimate of the quantity of mercury released annually to the atmosphere from crematoriums. The maximum ground-level mercury vapour concentrations resulting from crematorium emissions were estimated. In BC, it is estimated that approximately 1.20g of mercury is emitted to the atmosphere per body cremated and about 30,000 cremations were conducted in the province in 2016. It is estimated that almost 36kg of elemental mercury was released to the atmosphere as a result. The maximum estimated peak short-term and long-term average ground-level mercury vapour concentrations associated with crematorium emissions were 0.31μg/m3 and 7.9 × 10-3μg/m3 respectively, which are far lower than the reference concentration (hazard quotient of less than 1). Mercury from crematoriums accounts for more than 7% of total mercury emissions to the atmosphere in BC, but risk assessment found no indication that ground-level exposures to elemental mercury vapour from crematoriums poses a significant risk to human health. If the number of cremations increases, it might reach considerable levels, highlighting the need for developing a national plan similar to other countries.

Relation between the Actual and Estimated Maximum Ground Level Concentration of Air Pollutant and Its Downwind Locations

In this work we used the Gaussian plume model to calculate the actual maximum ground level concentration (MGLC) of air pollutant and its downwind location by using different systems of dispersion parameters and for different stack heights. An approximate formula for the prediction of downwind position that produces the MGLC of a pollutant based on the Gaussian formula was derived for different diffusion parameters. The derived formula was used to calculate the approximate MGLC. The actual and estimated values are presented in tables. The comparison between the actual and estimated values was investigated through the calculation of the relative errors. The values of the relative errors between the actual and estimated MGLC lie in the range from: 0 to 70.2 and 0 to 1.6 for Pasquill Gifford system and Klug system respectively. The errors between the actual and estimated location of the MGLC lies in the range from: 0.2 to 227 and 0.7 to 9.4 for Pasquill Gifford system and Klug system respectively.

P.117 Antipsychotic effects on the synaptic plasticity-related gene Homer1a are dependent on dose, receptor profile, timing of administration, and brain regions

In a sodium cooled Fast Reactors (SFRs), in the event of secondary sodium circuit failure (cracks developed in the fluid carrying pipe), the hot sodium is exposed to atmosphere, burns to produce sodium combustion aerosols and is released into the atmosphere. Of the released aerosols, sodium hydroxide (NaOH) poses inhalation health hazard (Threshold Limit Value (TLV) of NaOH is 2.0 ∗ 10−6 kg/m3 for inhalation) due to its corrosive nature. In the context of fast reactor safety analysis studies, the quantity of sodium aerosols reaching various locations in the downwind direction and its chemical composition are very important. In this study sodium aerosol dispersion experiments in the open environment were conducted, by burning 50 kg of sodium. Aerosols were released through a 10 m high chimney and sampling was done in a range of up to 700 m distance. About 100 aerosol samples were collected in a 30° field sector with 170° as a bisector line. Aerosol characteristics were measured and atmospheric dispersion simulations were performed to predict the ground level concentration and deposition using Gaussian Plume and FLEXPART models. The simulation results were compared with experimental measurements and models were validated. Both experimental results and model predictions showed that, the maximum ground level concentration occurred at 100 m distance from the release point and that the concentrations increased with increase of the release rate. About 14% of the total quantity of burnt mass of sodium was deposited as aerosols between 50 and 700 m distance. The chemical species at all the arc distances was found to be sodium bi-carbonate. The study is found useful in hazard evaluation of sodium aerosols released from a sodium fire event in SFRs or from a sodium handling facility, to determine the aerosol concentration and chemical species in the downwind direction, in particular, the chemical species is found to be bi-carbonate reducing the chemical hazard to greater extent. A model shall be applied to the site specific condition to predict the sodium aerosol concentration and deposition for any sodium fire incidents and subsequent release of aerosols.

Landfill air and odour emissions from an integrated waste management facility.

A mixture of gases and obnoxious odours are major components of landfill emission. A dispersion modelling on air pollutants and odour emissions anticipated from a proposed Integrated Waste Management Facility was conducted considering five operating scenarios. Impacts of the predicted ground level concentrations of air pollutants (including carbon monoxide, CO; oxides of nitrogen, NOX; sulphur dioxide, SO2; particulate matter, PM and hydrocarbons, HC) and odour on ambient air quality were investigated using the 10-min 1 OU/m3 odour limit, CH4 Lower Explosive Limit (LEL) and the daily limits of CO, NOx, SO2, PM and HC. The anticipated maximum ground level concentration of emitted odour and CH4 are 0.0040 OU/m3 and 0.0349ppm, respectively. Simultaneous operations of all the major components of the facility will generate the daily maximum concentrations of 7.34, 2.60, 7.31, 29.72 and 0.42μg/m3, for CO, NOX, SO2, PM and HC, respectively. Generally, the facility impacts on ambient air quality will be within the acceptable limit.

Measuring of industrial emission parameters

The current system for estimating an air pollution level in the Russian Federation is based on the calculation of the maximum concentrations of pollutants reduced to a 20-minute time interval. The maximum ground level concentration of a pollutant, Cmax, mg·m−3, is calculated by the formula, which includes both reference values and parameters determined by the results of instrumental measurements. Measuring off-gas parameters from the air pollution source requires simultaneous monitoring of all parameters for 20 minutes. Deviation from this requirement and carrying out measurements not simultaneously can lead to errors in the estimation of emission efficiency. Continuous Emission Monitoring System can cope with such a task the significance of which increases after approval of the Federal Law 7-FZ “On Environmental Protection”. These systems allow getting the real picture of pollutant emissions into the atmosphere, and in case of exceeding parameters, immediately make decisions in order to reduce the negative impact on the environment.

Studies on sodium aerosols dispersion in open environment for fast reactor safety

In a sodium cooled Fast Reactors (SFRs), in the event of secondary sodium circuit failure (cracks developed in the fluid carrying pipe), the hot sodium is exposed to atmosphere, burns to produce sodium combustion aerosols and is released into the atmosphere. Of the released aerosols, sodium hydroxide (NaOH) poses inhalation health hazard (Threshold Limit Value (TLV) of NaOH is 2.0 ∗ 10−6 kg/m3 for inhalation) due to its corrosive nature. In the context of fast reactor safety analysis studies, the quantity of sodium aerosols reaching various locations in the downwind direction and its chemical composition are very important. In this study sodium aerosol dispersion experiments in the open environment were conducted, by burning 50 kg of sodium. Aerosols were released through a 10 m high chimney and sampling was done in a range of up to 700 m distance. About 100 aerosol samples were collected in a 30° field sector with 170° as a bisector line. Aerosol characteristics were measured and atmospheric dispersion simulations were performed to predict the ground level concentration and deposition using Gaussian Plume and FLEXPART models. The simulation results were compared with experimental measurements and models were validated. Both experimental results and model predictions showed that, the maximum ground level concentration occurred at 100 m distance from the release point and that the concentrations increased with increase of the release rate. About 14% of the total quantity of burnt mass of sodium was deposited as aerosols between 50 and 700 m distance. The chemical species at all the arc distances was found to be sodium bi-carbonate. The study is found useful in hazard evaluation of sodium aerosols released from a sodium fire event in SFRs or from a sodium handling facility, to determine the aerosol concentration and chemical species in the downwind direction, in particular, the chemical species is found to be bi-carbonate reducing the chemical hazard to greater extent. A model shall be applied to the site specific condition to predict the sodium aerosol concentration and deposition for any sodium fire incidents and subsequent release of aerosols.

The effect of heat recovery on near-source plume dispersion of a simple cycle gas turbine

The waste heat recovery (HR) systems are employed to increase the overall thermal efficiency of electric generation units (EGUs). Although the emission factors (in terms of gram of pollutants per unit of thermal energy consumed or electric energy generated) generally decreases after installing HR systems, the emission rates in terms of grams of pollutants per unit of time remain unchanged. However, HR systems reduce stack exit temperature, resulting in lower effective emission heights, which lead to higher near-source ground level concentrations (GLCs) of air pollutants. In order to comprehensively evaluate the near-source air quality impact from deploying HR systems, we proposed a new modeling framework by integrating a computationally efficient Gaussian-based dispersion model (AERMOD) and a (relatively) more accurate computational fluid dynamics (CFD) model. As a demonstration of the proposed framework, we investigated the HR impact on NOx concentrations near a simple cycle gas turbine located in Brentwood, NY. Specifically, we applied the AERMOD modeling system to screen the hourly GLCs over five years, and highest values (and the corresponding hours) were shown to cluster into two main meteorological conditions: the stable atmospheric boundary layer with relatively high wind speed (Stable, HW) and the unstable atmospheric boundary layer with relatively low wind speed (Unstable, LW). These two conditions were further simulated using a CFD model that have been extensively evaluated previously for detailed analysis. By setting different stack exit temperatures, the near-source air quality impact of different waste heat conversion rates was evaluated. We introduced a concept called the heat recovery amplified factor (HRAF), defined as the ratio between the maximum GLC with HR system and that without HR system, as an indicator of HR impact. HRAF was shown to be much more sensitive to temperature in the Unstable, LW condition than in the Stable, HW condition. Although the results were limited to a specific simple cycle gas turbine, the proposed modeling framework and HRAF can be used for evaluating the HR systems impact for other emission sources.

ESTIMASI POLA DISPERSI DEBU, SO2 DAN NOX DARI INDUSTRI SEMEN MENGGUNAKAN MODEL GAUSS YANG DIINTEGRASI DENGAN SCREEN3

Industrial activities are sources of air pollution. Pollutants dispersion in air influenced by meteorological condition, such as wind speed, wind direction, air temperarture, air turbulence and atmospheric stability. Air quality monitoring is important in controling the worst condition of pollutants concentration. Air quality monitoring is not easy to do, because it is time consuming, costly and need technology, so that air quality model is developed as an alternative air quality monitoring. This research used gaussian model, a model for predicting pollutant concentrations in downwind area. This model is applied in cement industry, focusing on major pollutants of the cement industry. Sources of pollutants consist of dust, SO 2 and NOx. The modeling results showed maximum ground level concentration of dust, SO 2 and NOx occur at night (7-10 PM). The maximum ground level concentration of dust, SO 2 and NOx at night respectively were 13.16 μg / Nm 3 , 32.69 μg / Nm 3 , 100.21 μg / Nm 3 (N1 stack) and 14.65 μg / Nm 3 , 36.65 μg / Nm 3 , 128.10 μg / Nm 3 (N2 stack) based from downwind scenarios at night when atmospheric condition was stable. The distance where the maximum ground level concentration occured has a strong correlation with wind speed (-0.82 ≤ r ≤ -1). Based on gaussian model output, air quality monitoring should be executed at night time (stable atmospheric condition) and located at ground level where maximum concentration occured. Increasing 50m of stack can decrease 57% pollutant concentrations in stable condition.

Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model

The investigation of pollutants concentrations affected by the multiple sources is essential for air quality management. In this study, the spatial variations of SO2, NO2 and PM10 emitted from multiple industrial sources in Pasir Gudang industrial area, Johor, Malaysia were predicted using American Meteorological Society/Environmental Protection Regulatory Model (AERMOD) air dispersion model coupled with Weather Research and Forecasting (WRF). The WRF model was applied to simulate the hourly surface and upper air meteorological variables for the period of two weeks. The output parameters from WRF such as temperature, wind speed and wind direction were also statistically evaluated in the study. The results of comparing the wind roses from the observed and simulated data in Pasir Gudang station showed the difficulty of prognostic WRF model in predicting wind direction in Malaysia located in a coastal site. The results showed that the maximum ground level concentration of SO2, NO2 and PM10 simulated through AERMOD-WRF in the industrial area was 36.2, 59.8 and 5.4 μg/m3, respectively. The evaluation of AERMOD through the Quantile-Quantile (Q-Q) plots showed that most of the predicted and observed pair points are lying close to the one-to-one line indicating that there is a good agreement between predicted and observed concentrations in the study. The findings of this study can facilitate and assist the local government authorities and policy makers in managing the urban air quality.