Modeling of NO x Emissions from Oil Refinery Furnaces

The current paper investigates the possibility of establishing an empirically based model for predicting the emission rate of nitrogen oxides (NO _x ) from oil refinery furnaces, in order to continually track emissions with respect to environmental licence limits. Model input data were collected by direct stack monitoring using an electrochemical cell NO _x analyser, as well as a range of telemetry sensors to obtain refinery process parameters. Principal Component Analysis (PCA), in conjunction with Partial Least Squares (PLS) regression was then used to build a series of models able to predict NO _x emissions from the furnaces. The models produced were proven to be robust, with a relatively high accuracy, and are able to predict NO _x levels over the range of operating conditions which were sampled. It was found that due to structural/operational variations a separate model is usually required for each furnace. The models can be integrated with the refinery operating system to predict NO _x emission rates on a continuous basis. Two models representing structurally different furnaces are considered in this paper. This revised version was published online in July 2006 with corrections to the Cover Date.     

A Wavelet-based Neural Network Model to Predict Ambient Air Pollutants’ Concentration

The present paper proposes a wavelet based recurrent neural network model to forecast one step ahead hourly, daily mean and daily maximum concentrations of ambient CO, NO₂, NO, O₃, SO₂ and PM_2.5 — the most prevalent air pollutants in urban atmosphere. The time series of each air pollutant has been decomposed into different time-scale components using maximum overlap wavelet transform (MODWT). These time-scale components were made to pass through Elman network. The number of nodes in the network was decided on the basis of the strength (power) of the corresponding input signals. The wavelet network model was then used to obtain one-step ahead forecasts for a period extending from January 2009 to June 2010. The model results for out of sample forecast are reasonably good in terms of model performance parameters such as mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), normalized mean absolute error (NMSE), index of agreement (IOA) and standard average error (SAE). The MAPE values for daily maximum concentrations of CO, NO₂, NO, O₃, SO₂ and PM2.5 were found to be 9.5%, 17.37%, 21.20%, 13.79%, 17.77% and 11.94%, respectively, at ITO, Delhi, India. Bearing in mind that the forecasts are for daily maximum concentrations tested over a long validation period, the forecast performance of the model may be considered as reasonably good. The model results demonstrate that a judicious selection of wavelet network design may be employed successfully for air quality forecasting.     

Spatial concentration distributions of sulfur dioxide and nitrogen oxides in Patras, Greece, in a winter period

An economic and quick methodology for performing a preliminary spatial assessment of a city air quality with the purpose to identify locations and zones susceptible to high pollution levels is proposed. A Patras case-study is selected, regarding the air pollutants of sulfur dioxide (SO₂) and oxides of nitrogen (NO_x). A total number of 451 samples of short duration, of which 225 were randomly picked in morning rush hours and 226 within evening rush hours, were collected from 50 locations of the major Patras area during a year period, when peaks of primary air pollutants usually occur. Concentration measurements at prescribed locations used to statistically calculate spatial average concentrations approximating 1-h mean values with mean probable errors less than 25.9% for SO₂, NO and NO_x and less than 15.5% for NO₂. Then iso-concentration contour diagrams plotted indicate high pollution zones and possibly appropriate locations for continuous or random monitoring according to the European Community (EC) Directives. The 1-h mean concentrations were in good correlation to the corresponding traffic rates and useful relationships are given (0.54 ≤ r ≤ 0.63). In addition, comparisons with data available for other cities, as well as with the limit and guide values provided by the EC and the World Health Organization (WHO) were given. The present data could be useful for the design and optimization of a city network of stations for monitoring air quality, for environmental impact assessments, future reference and comparisons due to city development needs, as well as for validating dispersion models.     

广州主要工业源排放的气态污染物扩散模拟研究

以广州省控工业污染源排放的气态污染物(SO₂、NO_x为主要研究对象,通过中尺度气象模式MM5与空气质量模式CALPUFF耦合,模拟11月典型气象条件下, SO₂和NO_x的扩散传输过程,研究其时空分布特征,并分析省控工业污染源排放对特定区域(主要针对2010年亚运场馆)空气质量的影响。结果表明,主要受典型风速的影响,SO₂和NO_x浓度具有明显的时空分布不均匀性。浓度高峰值主要出现在晚间至凌晨时段,而浓度低峰值主要出现在白天至中午时段。受污染源分布、排放高度和风向的影响,荔湾区和越秀区污染物浓度较高,且在广州西南部形成较明显的污染带;且这些省控污染源对南沙体育馆空气质量有较大影响。 研究结果对广州空气污染来源分析具有一定参考意义。     

An Analysis of Secondary Pollutants in Buenos Aires City

Air pollutant concentrations from a monitoring campaign in Buenos Aires City, Argentina, are used to investigate the relationships between ambient levels of ozone (O₃), nitric oxide (NO) and nitrogen dioxide (NO₂) as a function of NO _x (=NO + NO₂). This campaign undertaken by the electricity sector was aimed at elucidating the apportionment of thermal power plants to air quality deterioration. Concentrations of carbon monoxide (CO) and sulphur dioxide (SO₂) were also registered. Photo stationary state (PSS) of the NO, NO₂, O₃ and peroxy radicals species has been analysed. The ‘oxidant’ level concept has been introduced, OX (=O₃ + NO₂), which varies with the level of NO _x . It is shown that this level is made up of NO _x -independent and NO _x -dependent contributions. The former is a regional contribution that equates the background O₃ level, whereas the latter is a local contribution that correlates with the level of primary pollution. Furthermore, the anticorrelation between NO₂ and O₃ levels, which is a characteristic of the atmospheric photo stationary cycle has been verified.The analysis of the concentration of the primary pollutants CO and NO strongly suggests that the vehicle traffic is the principal source of them. Levels of continuous measurements of SO₂ for Buenos Aires City are reported in this work as a complement of previously published results.     

Status of air pollution caused by coal washery projects in India

The importance of coal washeries in India is growing as local coals have a high ash content. At present, there are 23 coal washeries with an annual rated input of 45 Million Tonnes. During the various operations in washeries, large amounts of dusts and gaseous pollutants are generated. Four coal washery projects were surveyed to study their air pollution characteristics. Air monitoring stations were set up in local industrial, residential and sensitive areas and air pollution samples were collected along with micro-meteorological data. Diurnal variations of SPM, SO₂ NO_x and CO are discussed. SPM concentrations were found to exceed the permissible limits at all locations. SO₂ and NO_x were also found to exceed the permissible limit in residential and sensitive areas. It was observed that about 50% of the dust particles were less than 10 µ in diameter. Benzene soluble matter in SPM ranged from 45–62%.     

The impact assessment of Diwali fireworks emissions on the air quality of a tropical urban site, Hyderabad, India, during three consecutive years

Diwali is one of the largest festivals for Hindu religion which falls in the period October–November every year. During the festival days, extensive burning of firecrackers takes place, especially in the evening hours, constituting a significant source of aerosols, black carbon (BC), organics, and trace gases. The widespread use of sparklers was found to be associated with short-term air quality degradation events. The present study focuses on the influence of Diwali fireworks emissions on surface ozone (O₃), nitrogen oxides (NO _x ), and BC aerosol concentration over the tropical urban region of Hyderabad, India during three consecutive years (2009–2011). The trace gases are analyzed for pre-Diwali, Diwali, and post-Diwali days in order to reveal the festivity’s contribution to the ambient air quality over the city. A twofold to threefold increase is observed in O₃, NO _x , and BC concentrations during the festival period compared to control days for 2009–2011, which is mainly attributed to firecrackers burning. The high correlation coefficient (~0.74) between NO _x and SO₂ concentrations and higher SO₂/NO _x (S/N) index suggested air quality degradation due to firecrackers burning. Furthermore, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation-derived aerosol subtyping map also confirmed the presence of smoke aerosols emitted from firecrackers burning over the region. Nevertheless, the concentration level of pollutants exhibited substantial decline over the region during the years 2010 and 2011 compared to 2009 ascribed to various awareness campaigns and increased cost of firecrackers.     

Emissions of SO2, NO x and particulates from a pipe manufacturing plant and prediction of impact on air quality

Integrated pipe manufacturing industry is operation intensive and has significant air pollution potential especially when it is equipped with a captive power production facility. Emissions of SO₂, NO _x , and particulate matter (PM) were estimated from the stationary sources in a state-of-the-art pipe manufacturing plant in India. Major air polluting units like blast furnace, ductile iron spun pipe facility, and captive power production facility were selected for stack gas monitoring. Subsequently, ambient air quality modeling was undertaken to predict ground-level concentrations of the selected air pollutants using Industrial Source Complex (ISC 3) model. Emissions of SO₂, NO _x , and particulate matter from the stationary sources in selected facilities ranged from 0.02 to 16.5, 0.03 to 93.3, and 0.09 to 48.3 kg h^???1, respectively. Concentration of SO₂ and NO _x in stack gas of 1,180-kVA (1 KW = 1.25 kVA) diesel generator exceeded the upper safe limits prescribed by the State Pollution Control Board, while concentrations of the same from all other units were within the prescribed limits. Particulate emission was highest from the barrel grinding operation, where grinding of the manufactured pipes is undertaken for giving the final shape. Particulate emission was also high from dedusting operation where coal dust is handled. Air quality modeling indicated that maximum possible ground-level concentration of PM, SO₂, and NO _x were to the tune of 13, 3, and 18 μg/m³, respectively, which are within the prescribed limits for ambient air given by the Central Pollution Control Board.     

Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network

In recent years, a significant part of the studies on air pollutants has been devoted to improve statistical techniques for forecasting the values of their concentrations in the atmosphere. Reliable predictions of pollutant trends are essential not only for setting up preventive measures able to avoid risks for human health but also for helping stakeholders to take decision about traffic limitations. In this paper, we present an operating procedure, including both pollutant concentration measurements (CO, SO₂, NO₂, O₃, PM10) and meteorological parameters (hourly data of atmospheric pressure, relative humidity, wind speed), which improves the simple use of neural network for the prediction of pollutant concentration trends by means of the integration of multivariate statistical analysis. In particular, we used principal component analysis in order to define an unconstrained mix of variables able to improve the performance of the model. The developed procedure is particularly suitable for characterizing the investigated phenomena at a local scale.     

Monitoring of Criteria Air Pollutants in Bursa, Turkey

The concentrations of criteria air pollutants such as CO, NO_x (NO + NO₂), SO₂ and PM were measured in the period of May 2001 and April 2003 in the city of Bursa, Turkey. The average concentrations for this period were 1115±1600 μg/m³, 29±50 μg/m³, 51±24 μg/m³, 79±65 μg/m³, 40±35 μg/m³, 98±220 μg/m³, for CO, NO, NO₂, NO_x, SO₂ and PM, respectively. Temporal changes in concentrations were analyzed using meteorological factors. Correlations among pollutant concentrations and meteorological parameters showed weak relations nearly in all data. Lower concentrations were observed in the summer months while higher concentrations were measured in the winter months. The increase in winter concentrations was probably due to residential heating. Pollutants were associated with each other in order to have information about their origin. NO_x/SO₂ ratio was also examined to bring out the source origin contributing on air pollution (i.e., traffic or stationary).     

A comparative study of respirable particulate microenvironmental concentrations and personal exposures

Personal monitoring (PM) for respirable suspended particulate matter (RSP) of thirty subjects was performed as part of an air pollution health effects study conducted in Houston, Texas. Parallel RSP measurements were performed in the study subjects' homes and two fixed site monitoring stations. The participants' daytime activities were independently recorded by study techicians. These data were used to characterize RSP concentrations in each microenvironment visited by the participants. Four estimates of daytime exposure to RSP were calculated based on two different microenvironmental models, and home and fixed site mean daytime RSP concentrations. These estimates were compared to mean daytime personal exposure from PM. Hourly estimates of exposure were calculated from a microenvironmental model and mean hourly home RSP concentrations and compared to hourly PM data. The results of the study indicate that, as in the case of NO₂, it is important to characterize indoor microenvironmental RSP concentrations according to location, sources, and concurrent activities, both qualitatively and quantitatively. Stratification of concentrations according to sources present and self-reported activity can lead to misclassification of exposures. For RSP and, probably, other pollutants with indoor sources and with short exposure integration times, adequate measures of exposure can only be obtained with very detailed and complex microenvironmental models or comprehensive personal monitoring.     

Influence of indoor air quality (IAQ) objectives on air-conditioned offices in Hong Kong

It is costly to sample all air pollutants of a general community. Air sampling should be conducted based on a practical assessment strategy and monitoring plan. In Hong Kong, the Environmental Protection Department (HKEPD) launched an Indoor Air Quality (IAQ) certification scheme to grade workplace IAQ as 'Excellent' or 'Good' by measuring the levels of nine common indoor air pollutants, namely carbon dioxide (CO(2)), carbon monoxide (CO), respirable suspended particulates (RSP), nitrogen dioxide (NO(2)), ozone (O(3)), formaldehyde (HCHO), total volatile organic compounds (TVOC), radon (Rn), and airborne bacteria count (ABC). Although average office IAQ performance has been improved since the implementation of this certification scheme, there are still resource issues and technical difficulties. To streamline the assessment of office IAQ performance, this study proposes a simple index of IAQ benchmarks formulated in compliance with the HKEPD requirements. In particular, three of the nine listed common air pollutants were selected as the 'representatives' for the overall satisfactory IAQ. Together with the assessment results of 422 Hong Kong air-conditioned offices, the index was evaluated in terms of test sensitivity, specificity and predictive values. Proved to be feasible to describe the IAQ of some air-conditioned offices, this IAQ index would be a useful tool for policymakers, building owners and professionals to quantify IAQ performance in offices and to make decisions on resources and manpower management for efficient mitigation actions.     

Photoacoustic measurements of black carbon light absorption coefficients in Irbid city, Jordan

The goal of this work is the analysis of air quality levels in the area of Volos, a city of average size on the eastern seaboard of Central Greece. For this purpose, concentration measurements of sulfur dioxide, nitrogen oxide, and nitrogen dioxide, for a 4-year period (2001–2004) are analyzed. Air pollution data were obtained by a monitoring station, fully automated, which was established by the Hellenic Ministry of the Environment, Physical Planning, and Public Works, in order to measure air pollution levels in Volos, a medium-sized city, which faces the effects of industrialization. The main conclusions from the statistical analysis of the 4-year measurements of hourly SO₂, NO₂, and NO concentrations in the city of Volos, showed that the mean seasonal variation of the examined air pollutant concentration presents a minimum during the warm period of the year and a maximum during the cold period. Although the local geomorphology and meteorology encourage particularly the accumulation of air pollutants, the analysis shows that the SO₂ and NO₂ concentration levels remain lower than corresponding thresholds for human health protection set by the European Union, in this urban measuring site, during the examined period. The application of harmonic analysis revealed the difference between the annual variation of the SO₂ and NO _x concentrations. Regarding NO _x , the variation is mainly due to the first harmonic term (anthropogenic factor), while the SO₂ variation is interpreted by the two harmonic terms, which represent the anthropogenic and meteorological factors, respectively.     

Seasonal Differences in the Levels of Gaseous Air Pollutants in the Vicinity of a Waste Dump

Hydrogen sulphide, ammonia, nitrogen dioxide, mercaptans and sulphur dioxide (H₂S, NH₃, NO₂, R-SH, SO₂) concentrations were measured at the location in the vicinity of the waste dump to determine the air pollution level of these pollutants prior to the operation of the Mobile Thermal Treatment Plant. Samples were collected over one year period. Seasonal differences, and the influence of meteorological parameters (temperature, relative humidity, pressure and wind direction) on the air pollution levels were studied. Results show relatively low concentrations of H₂S, NO₂, R-SH and SO₂, while NH₃ levels were higher compared to the guideline values. Good weather conditions (high air pressure and low relative humidity) are connected to long range transport of NO₂, while higher temperatures result in elevated NH₃ and R-SH concentrations. Because of the predominant northeast wind direction (the same as the waste dump direction), the contribution of air pollution from the direction of the waste dump at the measuring site is significant, but that does not necessarily mean that the pollutants originated from that source.     

Extreme Nitrogen Oxide and Ozone Concentrations in Athens Atmosphere in Relation to Meteorological Conditions

In the present study, we investigate the variation of NO _x (NO + NO₂) and O₃ concentrations and the relation between the extreme events (episodes) of NO _x and O₃ concentrations and the relevant meteorological conditions in the urban atmosphere of the Athens basin. Hourly data of NO, NO₂ and O₃ concentrations from 10 representative monitoring sites located in the Athens basin were used, covering the 10-year time period from 1994 to 2003. The results of our analysis show that the concentrations of air pollutants differ significantly from one monitoring site to another, due to the location and proximity of each station to the emission sources. For each site, there are also significant differences in NO _x and O₃ concentrations from day to day, as well as from month to month and/or from season to season. The annual and seasonal variations show higher NO values in winter and lower in summer. On the contrary, NO₂ and O₃ values are higher in summer (photochemical production of O₃) and lower in winter. These differences are attributed, to a large extent, to the prevailing synoptic and meteorological conditions, the most important between them being the wind direction and speed as well as the atmospheric pressure. Our analysis of the identified 179 extreme NO _x air pollution events shows that most of them took place under anticyclonic conditions, associated with calm or weak winds (speed <2.5 ms⁻¹) of mostly southern to southwestern directions, as well as with low air temperatures and intense stable surface atmospheric conditions. There exists a significant decreasing tendency in NO _x air pollution episodic events over the 10-year study period, resulting in very few to none events in the period from 2000 to 2003. As far as it concerns the extreme O₃ concentrations, 34 air pollution events were identified, occurring under high air temperatures, variable weak winds and intense solar irradiation. The trends of O₃ concentrations are stronger in suburban sites than in urban ones.     

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl^?), calcium (Ca²⁺), total alkalinity, total hardness, nitrate nitrogen (NO₃-N), and ammonical nitrogen (NH₄-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO₃-N, NH₄-N, and Ca²⁺. Cl^? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.     

杭州市大气污染物排放清单及特征

以杭州市区为研究区域,通过调查整合多套污染源数据库及其他统计资料,研究文献报道及模型计算的各种污染源排放因子,获得杭州市区各行业PM10、PM2.5、SO2、NOx、CO、VOCs、NH3等污染物的排放量,建立了杭州市区2010年1 km×1 km大气污染物排放清单。结果表明,2010年杭州市区PM10、PM2.5、SO2、NOx、CO、VOCs和NH3的排放总量分别为7.96×104、4.02×104、7.23×104、8.98×104、73.90×104、39.56×104、3.32×104t。从排放源的行业分布来看,机动车尾气排放是杭州市区大气污染物最重要排放源之一,对PM10、PM2.5、NOx、CO和VOCs的贡献分别达到14.4%、27.1%、40.3%、21.4%、31.1%。道路扬尘、电厂锅炉、工业炉窑、植被、畜禽养殖对不同污染物分别有着重要贡献,道路扬尘对PM10和PM2.5的贡献分别为44.6%和20.0%、电厂锅炉对SO2和NOx的贡献分别为37.0%和25.7%、工业炉窑对CO的贡献为41.5%、植被排放对VOCs的贡献为27.1%、畜禽养殖对NH3的贡献为76.5%。从空间分布来看,萧山区和余杭区对SO2、NH3和植被排放BVOC的贡献要显著高于主城区;而主城区机动车对PM2.5、NOx和VOCs的贡献分别达到36.3%、56.0%和47.4%,较市区范围内显著增加,表明机动车尾气排放已成为杭州主城区大气污染最重要的来源之一。     

Assessment of environmental impact on air quality by cement industry and mitigating measures: a case study

In this study, environmental impact on air quality was evaluated for a typical Cement Industry in Nigeria. The air pollutants in the atmosphere around the cement plant and neighbouring settlements were determined using appropriate sampling techniques. Atmospheric dust and CO₂ were prevalent pollutants during the sampling period; their concentrations were recorded to be in the range of 249–3,745 mg/m³ and 2,440–2,600 mg/m³, respectively. Besides atmospheric dust and CO₂, the air pollutants such as NO _x , SO _x and CO were in trace concentrations, below the safe limits approved by FEPA that are 0.0062–0.093 mg/m³ NO _x , 0.026 mg/m³ SO _x and 114.3 mg/m³ CO, respectively. Some cost-effective mitigating measures were recommended that include the utilisation of readily available and low-cost pozzolans material to produce blended cement, not only could energy efficiency be improved, but carbon dioxide emission could also be minimised during clinker production; and the installation of an advance high-pressure grinding rolls (clinker–roller-press process) to maximise energy efficiency to above what is obtainable from the traditional ball mills and to minimise CO₂ emission from the power plant.     

Assessment of Air Quality After the Implementation of Compressed Natural Gas (CNG) as Fuel in Public Transport in Delhi, India

Public transport in Delhi was amended by the Supreme Court of India to use Compressed Natural Gas (CNG) instead of diesel or petrol. After the implementation of CNG since April 2001, Delhi has the highest fraction of CNG-run public vehicles in the world and most of them were introduced within 20 months. In the present study, the concentrations of various criteria air pollutants (SPM, PM₁₀, CO, SO₂ and NO_x) and organic pollutants such as benzene, toluene, xylene (BTX) and polycyclic aromatic hydrocarbons (PAHs) were assessed before and after the implementation of CNG. A decreasing trend was found for PAHs, SO₂ and CO concentrations, while the NO_x level was increased in comparison to those before the implementation of CNG. Further, SPM, PM₁₀, and BTX concentrations showed no significant change after the implementation of CNG. However, the BTX concentration demonstrated a clear relation with the benzene content of gasoline. In addition to the impact of the introduction of CNG the daily variation in PAHs levels was also studied and the PAHs concentrations were observed to be relatively high between 10 pm to 6 am, which gives a proof of a relation with the limited day entry and movement of heavy vehicles in Delhi.     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.