NO2 Dispersion Research Articles

Health Risk Assessment of Ambient Nitrogen Dioxide Concentrations in Urban and Industrial Area in Rayong Province, Thailand

Nitrogen dioxide (NO2) is a hazardous gas and an air pollutant that is released from a variety of sources, including fossil fuel mining and burning, automobile emissions and other sources. The inhalation of NO2 has been linked to the exact causes of a variety of health issues, including respiratory disorders and a variety of other maladies. The largest source of NO2 exposure is through traffic density emissions. The concentrations of ambient NO2 in Rayong province’s urban, industrial and background areas were measured during rainy, winter and summer seasons. Samples of NO2 were collected with the use of passive samplers during September 2017 to April 2018. The result of the analysis revealed that NO2 concentration of urban area, industrial area and background area were 13.9 - 43.0, 10.4 - 34.0 and 5.8 - 35.2 µg/m3, respectively. It is to be noted that NO2 concentrations in urban and industrial areas were significantly higher than those in background areas (p < 0.05). The dominant source is located nearby high traffic density and industrial establishments. However, the NO2 values obtained from seasonal variations were not significantly different (p > 0.05). A weak correlation was observed between NO2 concentrations and total precipitation (r = −0.237). The low wind speed has no effect on NO2 dispersion. As a result of the geographical and seasonal variation of NO2 concentrations, it was determined that local activities such as traffic density had a much greater impact on NO2 levels than meteorological factors. The hazard quotient (HQ) values from NO2 exposure in Rayong province were less than 1, indicating that the risk was negligible. The inhalation of NO2 by residents who live near the roadside and highway, on the other hand, may endanger their health.
 HIGHLIGHTS
 
 NO2 concentrations in Rayong province related to traffic density and industrial establishments
 The ambient NO2 levels in urban and industrial areas were approximately 1.4 times higher than those in background areas (p < 0.05)
 Residents of Rayong province who live near the roadside and highway road may put their health at risk due to NO2 inhalation
 
 GRAPHICAL ABSTRACT

Enhanced inhibition performance of NO2- intercalated MgAl-LDH modified with nano-SiO2 on steel corrosion in simulated concrete pore solution

This article aims to enhance the inhibition performance of NO2- intercalated Mg-Al layered double hydroxides(LDH) modified with nano-SiO2 on steel corrosion in simulated concrete pore solution containing chloride ions. The results indicate that the modification of nano-SiO2 can obviously improve the dispersion of NO2- intercalated LDH. Compared to pure LDH intercalated with NO2-, the LDH modified with nano-SiO2 exhibits a better corrosion inhibition effect. The reason can be attributed to the enhanced chloride binding and more simultaneously released NO2- due to the highly dispersed LDH modified with nano-SiO2. The produced C-S-H gel additionally contributes to the chloride binding.

Spatiotemporal variability of nitrogen dioxide (NO2) pollution in Manchester (UK) city centre (2017–2018) using a fine spatial scale single-NOx diffusion tube network

Nitrogen dioxide (NO2) is linked to poor air quality and severe human health impacts, including respiratory and cardiovascular diseases and being responsible annually for approximately 23,500 premature deaths in the UK. Automated air quality monitoring stations continuously record pollutants in urban environments but are restricted in number (need for electricity, maintenance and trained operators), only record air quality proximal to their location and cannot document variability of airborne pollutants at finer spatial scales. As an alternative, passive sampling devices such as Palmes-type diffusion tubes can be used to assess the spatial variability of air quality in greater detail, due to their simplicity (e.g. small, light material, no electricity required) and suitability for long-term studies (e.g. deployable in large numbers, useful for screening studies). Accordingly, a one passive diffusion tube sampling approach has been adapted to investigate spatial and temporal variability of NO2 concentrations across the City of Manchester (UK). Spatial and temporal detail was obtained by sampling 45 locations over a 12-month period (361 days, to include seasonal variability), resulting in 1080 individual NO2 measurements. Elevated NO2 concentrations, exceeding the EU/UK limit value of 40 µg m−3, were recorded throughout the study period (N = 278; 26% of individual measurements), particularly during colder months and across a wide area including residential locations. Of 45 sampling locations, 24% (N = 11) showed annual average NO2 above the EU/UK limit value, whereas 16% (N = 7) showed elevated NO2 (> 40 µg m−3) for at least 6 months of deployment. Highest NO2 was recorded in proximity of highly trafficked major roads, with urban factors such as surrounding building heights also influencing NO2 dispersion and distribution. This study demonstrates the importance of high spatial coverage to monitor atmospheric NO2 concentrations across urban environments, to aid identification of areas of human health concern, especially in areas that are not covered by automated monitoring stations. This simple, reasonably cheap, quick and easy method, using a single-NOx diffusion tube approach, can aid identification of NO2 hotspots and provides fine spatial detail of deteriorated air quality. Such an approach can be easily transferred to comparable urban environments to provide an initial screening tool for air quality and air pollution, particularly where local automated air quality monitoring stations are limited. Additionally, such an approach can support air quality assessment studies, e.g. lichen or moss biomonitoring studies.

Gaseous air pollutants dispersion emitted from point and line sources by coupling WRF-AERMOD models (Case study: Lowshan, Guilan Province, Iran)

The cement factories in urban areas can affect the air quality of cities due to the variety of pollutants emitted from cement production processes. In the present study, the impacts of the Khazar cement factory and two transportation axes between Guilan and Qazvin provinces were investigated on the air quality of Lowshan in Guilan Province, Iran in 2019. Due to the lack of suitable meteorological data for dispersion modeling, the WRF model was used to predict the meteorological parameters. The pollutants dispersion modeling was conducted by AERMOD software and the accuracy of results was confirmed by field measurements of NO2 obtained by passive samplers. The CO and NO2 dispersion modeling results showed that the air quality of Lowshan is in an acceptable situation compared to the ambient air quality standards. So that, the maximum one-hour concentration of NO2 in most residential areas was lower than the ambient standard, and only in small parts of the areas close to line sources, the concentration value was close to the standard limits. The maximum value of annually-averaged concentration of NO2 and the maximum one-hour concentration of CO were 17 ppb and 2.5 ppm, respectively, which are much lower than the clean air standards. Further investigation showed that in the cold weather seasons, due to the less vertical displacement of air and the decrease in the boundary layer height, the concentration of pollutants in the urban environment is higher than that in the warm weather seasons. Considering the night and day time wind roses showed that despite the existence of valley-mountain structure in the city, the air quality of the city is not affected by the mountain and valley breezes and also night and day wind roses do not follow the trend of these breezes.

Dispersion of NO2 and SO2 pollutants in the rolling industry with AERMOD model: a case study to assess human health risk.

Steel and rolling industry are the most important industries polluting the environment. Therefore, aim of this study is to make an emission model for SO2 and NO2 pollutants released from the rolling industry of Sepid-Farab Kavir Steel (SKS) complex using the AERMOD model and health risk assessment. Sampling pollutants released from SKS complex was performed in January 2017 at 10 different sites. Distribution of these pollutants was investigated by AERMOD model, domain site of AERMOD was designed for area around the factory with a radius of 30km, and also SO2 and NO2 modeling was performed for both natural gas and liquid fuel. Human health risk assessment was also studied. The results of this study demonstrated the emission of SO2 and NO2 from this complex is less than the maximum allowable, when used natural gas as the main fuel. The hourly concentration of SO2 reached about 324μg/m3, which in higher than the standard value for 1h. Considering the findings, the urban gas is considered as a clean source in terms of furnace air output and the concentration of emitted pollutants. Also, it has no side effects on workers' health.

Global and local sensitivity analysis of the Emission Dispersion Model input parameters

PurposeThe objectives of this paper are the application of sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersion of NO2 generated by an industrial fire, whose results are useful for fire safety applications. The EDM is used to predict the level concentration of nitrogen dioxide (NO2) emitted by an industrial fire in a plant located in an industrial region site in Algeria.Design/methodology/approachThe SA was defined for the following input parameters: wind speed, NO2 emission rate and viscosity and diffusivity coefficients by simulating the air quality impacts of fire on an industrial area. Two SA methods are used: a local SA by using a one at a time technique and a global SA, for which correlation analysis was conducted on the EDM using the standardized regression coefficient.FindingsThe study demonstrates that, under ordinary weather conditions and for the fields near to the fire, the NO2 initial concentration has the most influence on the predicted NO2 levels than any other model input. Whereas, for the far field, the initial concentration and the wind speed have the most impact on the NO2 concentration estimation.Originality/valueThe study shows that an effective decision-making process should not be only based on the mean values, but it should, in particular, consider the upper bound plume concentration.

Association between NO2 concentrations and spatial configuration: a study of the impacts of COVID-19 lockdowns in 54 US cities

The massive lockdown of global cities during the COVID-19 pandemic is substantially improving the atmospheric environment, which for the first time, urban mobility is virtually reduced to zero, and it is then possible to establish a baseline for air quality. By comparing these values with pre-COVID-19 data, it is possible to infer the likely effect of urban mobility and spatial configuration on the air quality. In the present study, a time-series prediction model is enhanced to estimate the nationwide NO2 concentrations before and during the lockdown measures in the United States, and 54 cities are included in the study. The prediction generates a notable NO2 difference between the observations if the lockdown is not considered, and the changes in urban mobility can explain the difference. It is found that the changes in urban mobility associated with various road textures have a significant impact on NO2 dispersion in different types of climates.

Dispersion and emission patterns of NO2 from gas flaring stations in the Niger Delta, Nigeria

The dispersion of nitrogen dioxide (NO2) emitted from gas flaring stacks affect the environment and human health negatively. This study assessed the spatial and temporal patterns of NO2 emissions from gas flaring stations in the Niger Delta between January 2017 and December 2018. NO2 was measured using Aeroqual gas monitor. The data of NO2 concentrations were analysed using SPSS for Windows. Hybrid Single Particle Lagrangian Integrated Trajectory Model was adopted to predict the dispersion of NO2 from the gas flaring stations. Results revealed that flare stations in Rivers State emitted the highest concentrations of NO2 varying from 0.029 to 0.036 mg/m3 in 2017 and 0.031 to 0.034 mg/m3 in 2018. NO2 emissions from each gas flaring station were generally higher in 2017 than 2018 by about 0.002 mg/m3. There was an increase in the concentration of NO2 by about 0.002 mg/m3 in the wet season over the dry season. Increase in temperature might have led to increase in NO2 concentrations (r = 0.047–0.377). An inverse relationship was recorded between relative humidity and NO2 (r = − 0.005 to − 0.412). Wind speed showed negative correlations with NO2 in the dry season (r = − 0.148 to − 0.139) and weak positive correlation (r = 0.104–0.074) in the wet season. Many states in Nigeria were identified as the receptors of the dispersed NO2 from the gas flaring stations. The study concluded that people susceptible to respiratory ailments should protect themselves from the impacts of NO2 pollution in the Niger Delta.

Compreensão da formação de NO2 proveniente das operações de transporte urbano e suas relações com agentes causais

Os problemas oriundos da mobilidade urbana estão relacionados ao crescimento acelerado e não planejado das cidades, à distribuição espacial das atividades, ao crescimento expressivo do uso do automóvel, as deficiências do transporte público e a ocorrência de impactos negativos nos âmbitos sociais e ambientais, tendo como um dos principais impactos a concentração de NO2. Dessa forma, o presente trabalho tem por objetivo avaliar a influência dos fatores (gabarito das edificações, uso do solo e volume de tráfego) nas concentrações de NO2. Para tal, a complexidade do uso do solo urbano foi traduzida por meio do indicador que mede a diversidade do uso do solo urbano, entropia. As concentrações de NO2 foram medidas através de um método de amostragem passiva. Como principais resultados verificou-se que o volume de tráfego veicular aliado a elevada entropia se relacionam diretamente com as concentrações de NO2. O gabarito das edificações se relaciona com estas concentrações mas não de forma tão direta, pois tal fator pode ser suprimido pelo tráfego veicular ou influenciado por fenômenos naturais que facilitam ou não a dispersão de NO2.

Current state of atmospheric air pollution in Ukraine based on Sentinel-5P satellite data

Introduction. Industrial development and increasing traffic emissions cause air quality problems. The most accurate for air pollution analysis are ground-based data; however, it is very limited in space. Modelling could solve this problem, but huge amount of input information and limits of computational power make it difficult to analyze big territories with high resolution. Sentinel-5P satellite with TROPOMI instrument nowadays gives opportunities to monitor the air pollution with good spatial resolution. The purpose of the study is to analyse nitrogen dioxide, sulfur dioxide, carbon monoxide and formaldehyde spatial and temporal distribution over Ukraine and Black Sea and Azov Sea. Methods and raw data. There were selected Sentinel-5P data of NO2, SO2, CO and HCHO for the period from first data release in 2018 to June, 2019. Data processing implemented in Google Earth Engine using JavaScript programming in The Earth Engine Code Editor. Results and discussion. Joint analysis of NO2 tropospheric, stratospheric and total columns showed the prevailing of tropospheric NO2 content and therefore crucial role of anthropogenic emission sources. While background NO2 total column varies from 4·10-5 mol/m2 to 7·10-5 mol/m2, in the most polluted cities content exceeds 1·10-4 mol/m2. The highest values are observed in Kyiv and industrial cities in Donbas region. Some of them are situated in the area of Joint Forces Operation outside the demarcation line. Sentinel-5P data catch the large emissions from the local industries; however, no official confirmations about production volume are available. NO2 dispersion increase during winter with the values range from 1·10-5 mol/m2 to 3·10-5 mol/m2 over clean territories and 8·10-5 mol/m2 to 1·10-3 mol/m2 in industrial cities. Seasonal maximal observed during warm period in unpolluted regions and during winter in the cities. Cold seasonal NO2 content outbreaks in the mountains are the result of its transportation from industrial cities. Spatial distribution of CO total column over Ukraine is rather homogeneous because of CO lifetime in the atmosphere up to several months. It could be transported on the long distances, which makes identification of polluted regions difficult. However, several cities with maximal average values of more than 0.037mol/m2 prove the existence of extreme anthropogenic emissions. Overall background CO contents vary within 0.033–0.035 mol/m2. Coastal regions of the Black Sea and Azov Sea are more polluted by CO compared to the mainland, which could be the consequences of ships emissions. Temporal analysis of CO total column found 4 powerful emissions: three of them are anthropogenic in industrial cities and one is natural, connected with forest fires in Belarus and northern part of Rivne region in April, 2019. There is one location with huge SO2 emission in Ukraine, observed in Novyi Svit (Donetsk region) outside the demarcation line of Joint Forces Operation, which corresponds to Starobeshivska thermal power station. In general, higher SO2 contents are observed over Donetsk, Zaporizhia and Dnipro regions; also over the Black Sea and Azov Sea. For HCHO spatial distribution minimal values are typical for the Carpathians. It is well seen that SO2 content are higher in the Southern part of Ukraine than in the Western part. The research finds regularities in spatial distribution of pollutants over the sea area. During cold season higher concentrations could be observed over the main merchant vessels tracks in the Black Sea. In summer months, which coincide with the main tourist season, most polluted are shoreline area because of emissions from cabotage and fishing vessels. The study updates information about most polluted cities in Ukraine, especially in the regions with absence of ground-based measurements. Some of them are mentioned for the first time among other research. Air quality analysis in many industrial cities significantly changed over the last two years. It shows difficulties of long-term pollution forecast and scenarios based on historical data and observed trends. It is recommended to use ensemble modelling for this purpose with scenarios of emission reduction, increasing and temporal stability. Sentinel-5P data confirm the conclusions of previous research about dependence of NO2 annual cycle and seasonality phases shift from the level of anthropogenic load. Prospects for further research. Sentinel-5P spatial resolution expands the horizons for air pollution research. The most relevant are monitoring of short-term anthropogenic and natural emissions, pollutants’ seasonality changes in different macroclimatic conditions, research of ships emissions in Black Sea and Azov Sea, combination of satellite air pollution data with methods of “artificial intelligence” for individual emissions detection.

Observations of urban NOx plume dispersion using mobile and satellite DOAS measurements around the megacity of St.Petersburg (Russia)

ABSTRACTMobile DOAS (Differential Optical Absorption Spectroscopy) circular measurements of tropospheric nitrogen dioxide (NO2) were performed on a number of days in 2012 and 2014–2016 around St.Petersburg. These observations figured out an evolution of urban pollution plume, released from the megacity. The HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectories) model was configured to simulate the observed NO2 dispersion, taking into account the municipal inventory database of urban nitrogen oxides (NOx = NO+ NO2) emission. The simulation results were found consistent with the data of mobile measurements, allowing to fit an estimate of integral NOx emission rate from St.Petersburg (about 60 kt year−1 on the average). Coincident satellite measurements the Aura Ozone Monitoring Instrument (OMI) of tropospheric NO2 mostly agree with the data of simulation on the days of mobile observations. In general, presented results demonstrate the capabilities of joint interpretation of disparate tropospheric NO2 data in the vicinity of a megacity.

Intra-pixel variability in satellite tropospheric NO<sub>2</sub> column densities derived from simultaneous space-borne and airborne observations over the South African Highveld

Abstract. Aircraft measurements of NO2 using an imaging differential optical absorption spectrometer (iDOAS) instrument over the South African Highveld region in August 2007 are presented and compared to satellite measurements from OMI and SCIAMACHY. In situ aerosol and trace-gas vertical profile measurements, along with aerosol optical thickness and single-scattering albedo measurements from the Aerosol Robotic Network (AERONET), are used to devise scenarios for a radiative transfer modelling sensitivity study. Uncertainty in the air-mass factor due to variations in the aerosol and NO2 profile shape is constrained and used to calculate vertical column densities (VCDs), which are compared to co-located satellite measurements. The lower spatial resolution of the satellites cannot resolve the detailed plume structures revealed in the aircraft measurements. The airborne DOAS in general measured steeper horizontal gradients and higher peak NO2 vertical column density. Aircraft measurements close to major sources, spatially averaged to the satellite resolution, indicate NO2 column densities more than twice those measured by the satellite. The agreement between the high-resolution aircraft instrument and the satellite instrument improves with distance from the source, this is attributed to horizontal and vertical dispersion of NO2 in the boundary layer. Despite the low spatial resolution, satellite images reveal point sources and plumes that retain their structure for several hundred kilometres downwind.

Modelling of NO2 Dispersion based on Receptor Position Due to Transport Sector in Padang City, Indonesia

Modelling of NO2 Dispersion based on Receptor Position Due to Transport Sector in Padang City, Indonesia

Ranking current and prospective NO2 pollution mitigation strategies: An environmental and economic modelling investigation in Oxford Street, London

Air pollution continues to be a problem in the urban environment. A range of different pollutant mitigation strategies that promote dispersion and deposition exist, but there is little evidence with respect to their comparative performance from both an environmental and economic perspective. This paper focuses on examining different NO2 mitigation strategies such as trees, buildings facades coated with photocatalytic paint and solid barriers in Oxford Street in London. The case study findings will support ranking the environmental and economic impacts of these different strategies to improve personal exposure conditions on the footpath and on the road in a real urban street canyon. CFD simulations of airflow and NO2 dispersion in Oxford Street in London were undertaken using the OpenFOAM software platform with the k-ε model, taking into account local prevailing wind conditions. Trees are shown to be the most cost-effective strategy, with a small reduction in NO2 concentrations of up to 0.7% on the road. However, solid barriers with and without the application of photocatalytic paint and an innovative material (20 times more expensive than trees) can improve air quality on the footpaths more substantially, up to 7.4%, yet this has a significant detrimental impact on NO2 concentrations (≤23.8%) on the road. Photocatalytic paint on building surfaces presented a minimal environmental reductions (1.2%) and economic (>100 times more expensive than trees) mitigation strategy. The findings recognised the differences between footpath and road concentrations occurred and that a focused examination of three pollution hotspots can provide more cost effective pollution mitigation. This study considers how a number of pollutant mitigation measures can be applied in a single street canyon and demonstrates the strengths and weaknesses of these strategies from economic and environmental perspectives. Further research is required to extrapolate the findings presented here to different street geometries.

Spatio-Temporal Variation and Futuristic Emission Scenario of Ambient Nitrogen Dioxide over an Urban Area of Eastern India Using GIS and Coupled AERMOD-WRF Model.

The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth’s surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)–Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD–WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario.

CFD modeling of reactive pollutant dispersion in simplified urban configurations with different chemical mechanisms

Abstract. An accurate understanding of urban air quality requires considering a coupled behavior between the dispersion of reactive pollutants and atmospheric dynamics. Currently, urban air pollution is mostly dominated by traffic emission, where nitrogen oxides (NOx) and volatile organic compounds (VOCs) are the primary emitted pollutants. However, modeling reactive pollutants with a large set of chemical reactions, using a computational fluid dynamic (CFD) model, requires a large amount of computational (CPU) time. In this sense, the selection of the chemical reactions needed in different atmospheric conditions becomes essential in finding the best compromise between CPU time and accuracy. The purpose of this work is to assess the differences in NO and NO2 concentrations by considering three chemical approaches: (a) passive tracers (non-reactive), (b) the NOx–O3 photostationary state and (c) a reduced complex chemical mechanism based on 23 species and 25 reactions. The appraisal of the effects of chemical reactions focuses on studying the NO and NO2 dispersion in comparison with the tracer behavior within the street. In turn, the effect of including VOC reactions is also analyzed taking into account several VOC ∕ NOx ratios of traffic emission. Given that the NO and NO2 dispersion can also be affected by atmospheric conditions, such as wind flow or the background concentration from season-dependent pollutants, in this work the influence of wind speeds and background O3 concentrations are studied. The results show that the presence of ozone in the street plays an important role in NO and NO2 concentrations. Therefore, greater differences linked to the chemical approach used are found with higher O3 concentrations and faster wind speeds. This bears relation to the vertical flux as a function of ambient wind speed since it increases the pollutant exchange between the street and the overlying air. This detailed study allows one to ascertain under which atmospheric conditions the inclusion of chemical reactions are necessary for the study of NO and NO2 dispersion. The conclusions can be applied to future studies in order to establish the chemical reactions needed in terms of an accurate modeling of NO and NO2 dispersion and the CPU time required in a real urban area.

Uso de modelos CFD para estimar la representatividad espacial de estaciones de medida de la contaminación atmosférica urbana y la idoneidad de sus ubicaciones

A methodology to estimate the spatial representativeness of air pollution monitoring sites is applied to two urban districts. This methodology is based on high resolution maps of air pollution computed by using Computational Fluid Dynamics (CFD) modelling tools. Traffic-emitted NO2 dispersion is simulated for several meteorological conditions taking into account the effect of the buildings on air flow and pollutant dispersion and using a steady state CFD-RANS approach. From these results, maps of average pollutant concentrations for January–May 2011 are computed as a combination of the simulated scenarios. Two urban districts of Madrid City were simulated. Spatial representativeness areas for 32 different sites within the same district (including the site of the operative air quality stations) have been estimated by computing the portion of the domains with average NO2 concentration differing less than a 20% of the concentration at each candidate monitoring site. New parameters such as the ratio AR between the representativeness area and the whole domain area or the representativeness index (IR) has been proposed to discuss and compare the representativeness areas. Significant differences between the spatial representativeness of the candidate sites of both studied districts have been found. The sites of the Escuelas Aguirre district have generally smaller representativeness areas than those of the Plaza de Castilla. More stations are needed to cover the Escuelas Aguirre district than for the Plaza de Castilla one. The operative air quality station of the Escuelas Aguirre district is less representative than the station of the Plaza de Castilla district. The cause of these differences seems to be the differences in urban structure of both districts prompting different ventilation.

Modeling results of atmospheric dispersion of NO2 in an urban area using METI–LIS and comparison with coincident mobile DOAS measurements

Synergetic use of in–situ measurements, remote sensing observations and model simulations can provide valuable information about atmospheric chemistry and air quality. In this work we present for the first time a qualitative comparison between modeled NO2 concentrations at ground level using dispersion model METI–LIS and tropospheric NO2 columns obtained by mobile DOAS technique. Experimental and modeling results are presented for a Romanian city, Braila (45.26 ° N, 27.95 ° E). In–situ observations of NO2 and meteorological data from four ground stations belonging to the local environmental agency were used to predict the concentration of NO2 at ground level by atmospheric dispersion modeling on two days when mobile DOAS measurements were available. The mobile DOAS observations were carried out using a UV–VIS spectrometer mounted on board a car. The tropospheric Vertical Column Density (VCD) of NO2 is deduced from DOAS observations. The VCD was obtained using complementary ground and space observations. The correlation between model and DOAS observations is described by a correlation coefficient of 0.33. Also, model results based on averaged in–situ measurements for a period of 5 years (2008–2012) are used for an overview of the background NO2 evolution in time and space for the selected urban area.

Method for comparison of the maximum range of chemical pollutants

This paper analyzes the oil and petrochemical complex with four scenarios (for different threshold limit values of pollutants concentrations) from whence the following conclusions have been made: Based on the results of modeling and analysis of aggregate data it can be concluded that the application of software ALOHA (model) it is possible to plan and manage the set limit values for concentrations of pollutants in industrial plants along with monitoring the dispersion of pollutants in the oil and petrochemical complex. The model was applied, which based on Gaussian distribution calculates maximum range of pollutants and pollutant concentrations. These researches are specific, highly complex and rare, and for the first time conducted by using the model of SO2 and NO2 dispersion, the dominant pollutants in the oil and petrochemical industry complex. The paper provides relevant information based on which emitters were detected with the highest level of environmental and working environment pollution. By the analysis of the used data conclusions were obtained about the effects of pollutants on pollution that provide safe and reliable conclusion on the emitters, causes of pollution of industrial plants of oil and petrochemical complex.

Industrial fire simulation and uncertainty associated with the Emission Dispersion Model

The use of numerical modeling in the field of industrial fire accidentology has become common nowadays and this tendency is expected to increase with the development of performance simulation tools. Despite the constant development of fire modeling tools, the current state of the art is not yet able to accurately predict fire phenomena. This gap between the reality and simulations is probably due to the presence of some level of uncertainty, which may occur from the meteorological inputs, diffusion assumptions, plume dynamics, or emission production. To cope with the presence of uncertainties in the input data, we propose an uncertainty analysis enabling to avoid as much as possible bad decisions that may have a large impact in domains such as safety. In this study, we are interested in the uncertainty propagation related to NO2 atmospheric dispersion resulting from a crude oil tank fire. Uncertainties were defined a priori for each of the following input parameters: wind speed, NO2 emission rate, and viscosity and diffusivity coefficients. For that purpose, a Monte Carlo approach has been used. In order to evaluate the importance of the considered parameters on the NO2 dispersion, new sensitivity indicator has been developed. The obtained results showed that the viscosity coefficient and the wind speed are the most significant input parameters with respect to NO2 concentration near to the source of fire, while the wind speed and the initial concentration are the important parameters for distant areas.