Spatial and temporal variations of SPM, RPM, SO2 and NOx concentrations in an opencast coal mining area

A study for assessment and management of air quality was carried out in the Ib Valley area of the Ib Valley coalfield in Orissa state, India. The 24 h average concentrations of suspended particulate matter (SPM), respirable particulate matter (RPM), sulfur dioxide (SO(2)) and oxides of nitrogen (NO(x)) were determined at regular intervals throughout one year at twelve monitoring stations in residential areas and six monitoring stations in mining/industrial areas. The 24 h average SPM and RPM concentrations were 124.6-390.3 microg m(-3) and 25.9-119.9 microg m(-3) in residential areas, and were 146.3-845.2 microg m(-3) and 45.5-290.5 microg m(-3) in industrial areas. During the study period, 24 h and annual average SPM and RPM concentrations exceeded the respective standards set in the Indian national ambient air quality standard (NAAQS) protocol as well as USEPA, EU, WHO and World Bank standards at most of the residential and industrial areas. However, concentrations of SO(2)(annual average: 24.6-36.1 microg m(-3) and 24 h average: 17.0-46.3 microg m(-3)) and NO(x)(annual average: 23.6-40.9 microg m(-3) and 24 h average: 18.3-53.6 microg m(-3)) were well within the prescribed limit of the NAAQS and international standards in both residential and industrial areas. The temporal variations of SPM and RPM fitted polynomial trends well and on average in the mining area 31.91% of the SPM was RPM. The linear regression correlation coefficients between SPM and RPM and between NO(x) and SO(2) were 0.94 (+/-0.04) and 0.66 (+/-0.10), respectively. The optimum interpolation technique, kriging, determined that maximal concentrations of SPM and RPM occurred within the mining site. Highest concentrations of particulate matter were observed during the winter season followed by summer, autumn and rainy seasons. An action plan is formulated for effective control of air pollution at source, and mitigative measures should include implementation of green belts around the sensitive areas where the concentration of air pollutants exceeds the standard limit.     

Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City

The monthly maximum of the 24-h average time-series data of ambient air quality-sulphur dioxide (SO(2)), nitrogen dioxide (NO(2)) and suspended particulate matter (SPM) concentration monitored at the six National Ambient Air Quality Monitoring (NAAQM) stations in Delhi, was analysed using Box-Jenkins modelling approach (Box et al. 1994). Univariate linear stochastic models were developed to examine the degree of prediction possible for situations where only the past record of pollutant data are available. In all, 18 models were developed, three for each station for each of the respective pollutant. The model evaluation statistics suggest that considerably satisfactory real-time forecasts of pollution concentrations can be generated using the Box-Jenkins approach. The developed models can be used to provide short-term, real-time forecasts of extreme air pollution concentrations for the Air Quality Control Region (AQCR) of Delhi City, India.     

Air Quality Status of Visakhapatnam (India) – Indices Basis

Industrial development in Visakhapatnam is conspicuous to urban agglomeration and the city is located in a topographical bowl formed by two-hill ranges. A major portion of the city is within the bowl area wherein most of the industrial and commercial activities are existing and lies within a distance of 10 km from the shore of the Bay of Bengal. Due to the peculiar geographic location of city, wind movement is either eastern or western and is engulfed within the hill ranges. Hence, there is a possibility of buildup of air pollution levels within the city. Due to gravity of prevailing situation, air quality status of Visakhapatnam on indices basis is analyzed using a non-linear equation for variable parameters i.e. Suspended particulate matter (SPM). Sulfur dioxide (SO2) and Oxides of nitrogen (NO(x)), which are main criteria pollutants in India. For current analysis seasonal air quality data is used, which indicates SPM values in winter at most of the sites and in summer at few sites are exceeding the prescribed standards. Calculated indices reveal that, in winter as well as in summer, most of the locations experienced poor or bad air quality, which is mainly due to higher concentration of SPM and certain extent of SO2 values. Application of Oak Ridge Air Quality Index (ORAQI) type equations (non-linear) are helpful for air quality management plan in the region on long-term basis and it has been also observed that there are certain lapses of weightage assignment for individual pollutant in application.     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Determination of O3, NO2, SO2, CO and PM10 measured in Belgrade urban area

O(3), NO(2), SO(2), CO and PM(10) concentrations, simultaneously determined for the first time in Belgrade urban area in the autumnal period of 2005, are presented. The obtained results display similar behaviour of SO(2), NO(2), CO, PM(10) opposite from that of O(3). The weekend effect was also investigated showing diminution of average daily concentrations of SO(2), NO(2), PM(10) and CO for 72, 40, 37 and 42% respectively, and increase of the average daily concentration of O(3) for 56%. Influence of meteorological conditions on observed concentration levels was studied, too. The observed influence of wind speed on the O(3) nightly concentration levels was analyzed pointing to the phenomena of O(3) transport during episodic measurements. To make an identification of possible pollution sources and analyse the influence of meteorological parameters on pollution levels, air back trajectories for high level concentrations episodes were calculated and analysed. A multivariate receptor modelling (Principal Component Analysis, Cluster Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone transport.     

Air Quality and Monitoring Strategy in the Helsinki Metropolitan Area, Finland

The Helsinki Metropolitan Area Council (YTV) is responsible for air quality monitoring in the Helsinki area. Air quality has been monitored periodically since the late 1950s. An automatic SO2 monitoring network was constructed in 1975 and TSP measurements were added in 1978. Since then the network has been expanded and currently five automatic multicomponent stations form the basis of the network monitoring SO2, NO, NO2, CO, PM10 and O3 concentrations. Manual TSP and PM10 measurements are also conducted. Mobile monitoring units are also being used as well as special measurement campaigns. The effects of air pollution on nature are studied in bioindicator monitoring. An air quality index is used in order to inform the public of the current air quality situation. Changes in air quality are reflected in monitoring strategy. SO2 concentrations have decreased in the past two decades. Annual averages in 1995 were at or below 5 µg/m3. Traffic is the major source for pollutants even though catalytic converters have lowered traffic emissions somewhat. The highest annual average NO2 concentration at an urban site was 49 µg/m3 in 1995, and there has been no clear change in NO2 levels. There has been a decreasing trend in CO concentrations. Maximum annual TSP and PM10 averages in 1995 were 92 and 32 µg/m3, respectively. The highest average lead concentration was 0.01 µg/m3. Elevated concentrations are experienced from time to time. During the spring daily TSP and PM10 concentrations can go up to around 300 and 150 µg/m3, respectively. This is caused by resuspension mainly due to street sanding. Also a major winter NO2 episode occurred in December 1995. The highest hourly NO2 concentrations reached 400 µg/m3.     

Distribution of vehicular pollutants in street canyons of Varanasi, India: a different case

In present study horizontal and vertical distribution of traffic-related pollutants (CO and SO(2)) within the street canyons in (CO and SO(2)) Varanasi, India was monitored. The results showed that average horizontal profiles of traffic-related pollutant concentrations within street canyon at leeward side were approximately same as that of windward side. However, the vertical concentration of both the pollutants decreases with height above the ground and study indicated that CO and SO(2) concentrations at different heights below the roof showed clear vertical self-gradient. CO and SO(2) concentration decreased with height and the minimum value occurred at the roof. It was concluded from the observed results that pollutants from vehicular exhaust emissions in the street canyon of Varanasi were evenly distributed. This result may be due to the fact that wind vortices are not formed. Therefore, urban planners can use this type of streets so that there is proper ventilation and dispersal of pollutants.     

Joint application of an empirical and mechanistic model for regional lake acidification

The empirical direct distribution model for lake acidification is calibrated for use in an integrated assessment model which predicts the regional impact of an acid deposition control strategy. The calibration is based on the mechanistic Model of Acidification of Groundwater in Catchments (MAGIC). The models are applied jointly to a set of 33 statistically-selected lakes in the Adirondack region of New York. Calibration of the direct distribution model is based on a step-function application of acid deposition to MAGIC. Comparative evaluations of the resulting model predictions are made using historic deposition estimates and two alternative future deposition scenarios. The predictions of the direct distribution model match well the shapes and patterns of change of the regional distributions of ANC and pH predicted by MAGIC, the short- and medium-term dynamics of these changes, and the effect of including organic acids. However, small, long-term decreases in the fraction of incoming acid deposition neutralized by lakes and their watersheds predicted by MAGIC are not reproduced.     

Inventory of emissions of primary air pollutants in the city of Kocaeli, Turkey

This study aims to obtain a reliable inventory of the emission rates of the principal air pollutants including PM, SO2, NOx) and CO in Kocaeli, Turkey. In the first stage, the pollutant sources classified as point, area and line sources are determined in the area. Then the annual emission rates of the pollutants released from these sources are estimated by the emission factors given by USEPA and CORINAIR. Results show that the annual emission rates for PM, SO2, NOx) and CO are 2195 tons, 5342 tons, 14632 tons and 23095 tons, respectively. On the other hand, the pollutant group with the highest contribution to total emission rate is determined as the point sources for NOx, which is responsible for 73% of total NOx emission, while it is the area sources for PM, SO2 and CO with the contribution percentages of 75, 76 and 69, respectively.     

睢宁地区大气PM_(2.5)及气态污染物季节性变化特征

根据2014年全年实时在线观测数据,分析了徐州睢宁地区大气细颗粒物(PM_(2.5))和气态污染物(包括SO_2、CO、NO_x、O_3)质量浓度的季节性变化特征。结合后向轨迹模型,分析不同气团对该地区大气污染浓度的影响。PM_(2.5)与O_3值在夏季最低,呈显著相关,表明夏季PM_(2.5)主要受控于本地大气光化学活性。在冬季,除O_3外,PM_(2.5)、SO_2、CO、NO_x值最高,且大气颗粒物主要以细粒子为主。O_3在春季最高,并与远程传输的气团且经过我国东部污染源密集地区相对应。高浓度的PM_(2.5)主要与冬季缓慢移动的气团相对应,这可能将PM_(2.5)及其气态前体物传输至该地区进而加重大气污染程度。     

Abundance and sources of hydrophilic and hydrophobic water-soluble organic carbon at an urban site in Korea in summer

In this study, the characteristics of total water-soluble organic carbon (WSOC) and isolated WSOC fractions were examined to gain a better understanding of the pathway of organic aerosol production. 24 h PM(2.5) samples were collected during the summer (July 28-August 28, 2009) at an urban site in Korea. A glass column filled with XAD7HP resin was used to separate the filtered extracts into hydrophilic (WSOC(HPI)) and hydrophobic (WSOC(HPO)) fractions. The origins of air mass pathways arriving at the sampling site were mostly classified into three types, those originating over the East Sea of Korea that passed over the eastern inland urban and industrial regions (type I); those from the marine (western/southwestern/southern marine) and passed over the national industrial complex regions (type II); and those from northeastern China that passed through North Korea and metropolitan areas of South Korea (type III). Measurements showed an increase in the average WSOC fraction of total OC from the type II to III air mass (53 to 64%) periods. Also, higher SO(4)(2-)/SO(x) (=SO(2) + SO(4)(2-)) was observed in the type III air mass (0.70) than those in the types I (0.49) and II (0.43). According to the average values of WSOC/OC and SO(4)(2-)/SO(x), measurements suggest that the aerosols collected during the type III air mass period were more aged or photo-chemically processed than those during the types I and II air mass periods. The relationship between the SO(4)(2-)/SO(x) and WSOC/OC (R(2) = 0.64) suggests that a significant fraction of the observed WSOC at the site could be formed by an oxidation process similar to SO(4)(2-) aerosols, probably the oxidation process using OH radicals, or in-cloud processing. The photochemical production of WSOC(HPO) was also observed to significantly contribute to the total OC.     

Health risk estimation due to carbon monoxide pollution at different spatial levels in Santiago, Chile

The Metropolitan Region of Santiago has been declared as nonattainment area for carbon monoxide (CO). The data was based on seven air monitoring stations that do not necessarily represent the real population exposure. Usually, a series of coefficients that relates the concentration of pollutants with health effects (betas of the concentration–response equations) are used. For the calculation of these betas, normally, a city average air pollution concentration is used; nevertheless, these betas do not necessarily represent the real risk of exposure that the inhabitants are experimented. For this reason, this study estimates two aspects that are unknown and that are necessary to policymakers in public health decisions. First, estimate the exposure at a lower spatial resolution level and, second, estimate a concentration–response curve that differs spatially and depends on the proportion of susceptible groups. We followed the Air Pollution and Health, European Approach/Spanish Multicenter Study on the Relationship Between Air Pollution and the Mortality methodology for the determination of the short-term health effect due to CO population exposure at the three spatial levels (city, zone, and county). We found that there are different risks in cardiorespiratory mortality in the group over 64 years old associated to an unequal exposure to CO in Santiago city. The higher risks are in counties located to the south–east of the city. These finding confirm the necessity to face, in a different way, the approach when evaluating control strategies and policy decision to control air pollution in Santiago.     

基于LS-SVR、BP-ANN和MLR模型的PM10浓度预测

利用宁东能源化工基地PM10和气象监测数据,分别采用LS-SVR、BP-ANN和传统MLR模型预测PM10浓度变化。结果表明,较BP-ANN模型、MLR模型,LS-SVR模型能更好地刻画PM10浓度与各气象因素间的非线性相依关系,更准确地预测PM10浓度。     

Validation of two air quality models for Indian mining conditions

All major mining activity particularly opencast mining contributes to the problem of suspended particulate matter (SPM)directly or indirectly. Therefore, assessment and prediction are required to prevent and minimize the deterioration of SPM due tovarious opencast mining operations. Determination of emission rate of SPM for these activities and validation of air quality models are the first and foremost concern. In view of the above, the study was taken up for determination of emission rate for SPMto calculate emission rate of various opencast mining activitiesand validation of commonly used two air quality models for Indianmining conditions. To achieve the objectives, eight coal and three iron ore mining sites were selected to generate site specific emission data by considering type of mining, method of working, geographical location, accessibility and above all resource availability. The study covers various mining activitiesand locations including drilling, overburden loading and unloading, coal/mineral loading and unloading, coal handling orscreening plant, exposed overburden dump, stock yard, workshop, exposed pit surface, transport road and haul road. Validation of the study was carried out through Fugitive Dust Model (FDM) and Point, Area and Line sources model (PAL2) by assigning the measured emission rate for each mining activity, meteorologicaldata and other details of the respective mine as an input to the models. Both the models were run separately for the same set ofinput data for each mine to get the predicted SPM concentrationat three receptor locations for each mine. The receptor locationswere selected such a way that at the same places the actual filedmeasurement were carried out for SPM concentration. Statisticalanalysis was carried out to assess the performance of the modelsbased on a set measured and predicted SPM concentration data. The value of coefficient of correlation for PAL2 and FDM was calculated to be 0.990-0.994 and 0.966-0.997, respectively, which shows a fairly good agreement between measured and predicted values of SPM concentration. The average index of agreement values for PAL2 and FDM was found to be 0.665 and0.752, respectively, which represents that the prediction by PAL2 and FDM models are accurate by 66.5 and 75.2%, respectively. These indicate that FDM model is more suited for Indian mining conditions.     

Hybrid Neural Networks and Boosted Regression Tree Models for Predicting Roadside Particulate Matter

This paper examines the application of artificial neural network (ANN) and boosted regression tree (BRT) methods in air quality modelling. The methods were applied to developing air quality models for predicting roadside particle mass concentration (PM₁₀, PM_2.5) and particle number counts (PNC) based on air pollution, traffic and meteorological data from Marylebone Road in London. Elastic net, Lasso and principal components analysis were used as feature selection methods for the ANN models to reduce the number of predictor variables and improve their generalisation. The performance of the ANN with feature selection (ANN hybrid) and the BRT models was evaluated and compared using statistical performance metrics. The performance parameters include root mean square error (RMSE), fraction of prediction within a factor of two of the observation (FAC2), mean bias (MB), mean gross error (MGE), the coefficient of correlation (R) and coefficient of efficiency (CoE) values. The input variables selected by the elastic net produced the best performing ANN models. The ANN hybrid produced models performed only slightly better than the BRT models. The R values of the ANN elastic net and BRT models were 0.96 and 0.95 for PM₁₀, 0.96 and 0.96 for PM_2.5 and 0.89 and 0.87 for PNC, respectively. Their corresponding CoE values were 0.72 and 0.70 for PM₁₀, 0.74 and 0.76 for PM_2.5 and 0.81 and 0.71 for PNC respectively. About 80–99% of all the model predictions are within a factor of two of the observed particle concentrations. The BRT models offer more advantages regarding model interpretation and permit feature selection. Therefore, the study recommends the use of BRT over ANN where the model interpretation is a priority.     

Chemical trends in background air quality and the ionic composition of precipitation for the period 1980-2004 from samples collected at Valentia Observatory, Co. Kerry, Ireland

A major Irish study, based upon more than 8000 samples collected over the measurement period of 22 years, for sulfur dioxide (SO2-S), sulfate (SO4-S) and nitrogen dioxide (NO2-N) concentrations (microg m(-3)) within air, and the ionic composition of precipitation samples based on sodium (Na+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), chloride (Cl-), sulfate (SO4-S), non-sea salt sulfate (nssSO4-S), ammonium (NH4-N), and nitrate (NO3-N) weighted mean concentrations (mg l(-1)), has been completed. For the air samples, the sulfur dioxide and sulfate concentrations decreased over the sampling period (1980-2004) by 75% and 45%, respectively, whereas no significant trend was observed for nitrogen dioxide. The highest concentrations for sulfur dioxide, sulfate and nitrogen dioxide were associated with wind originating from the easterly and northeasterly directions i.e. those influenced by Irish and European sources. The lowest concentrations were associated with the westerly directions i.e. for air masses originating in the North Atlantic region. This was further verified with the use of backward (back) trajectory analysis, which allowed tracing the movement of air parcels using the European Centre for Medium range Weather Forecasting (ECMWF) ERA-40 re-analysis data. High non-sea salt sulfate levels were being associated with air masses originating from Europe (easterlies) with lower levels from the Atlantic (westerlies). With the precipitation data, analysis of the non-sea salt sulfate concentrations showed a decrease by 47% since the measurements commenced.     

Measurements of SO2, NO X and SPM in an industrial area at the Aegean coast of Turkey

Data from continuous measurements of SO₂ NO _x , suspended particulate matter (SPM) and meteorological parameters at seven sites around a highly industrialized region in the Aegean coast of Turkey, between July 15, 1991 to July 31, 1992 were used to evaluate spatial and temporal variations of air quality parameters. Low annual averages and insignificant differences between day and night concentrations were observed at stations far from sources. At stations close to sources, annual average concentrations were high and diurnal patterns were significant. Annual average SO₂ and SPM concentrations in all stations used the Krigging technique to assess the impact of industries on air quality in the surrounding airshed. Results have demonstrated that Turkish air quality standards for SO₂ were exceeded in a circle with a radius of 4 km and which was centered on the petrochemical complex and refinery. Similarly, standards for SPM were exceeded in a circle with a radius of 1.2 km and which was centered on the ironwork plants. Both SO₂ and SPM showed well defined diurnal variations, particularly in stations close to sources. The SO₂ concentrations showed a maximum during day-time, while SPM concentrations peaked after midnight. Although annual average SO₂ and SPM concentrations were highly variable depending on distances between stations and sources, background concentrations of the same pollutants, calculated by stripping episodes from data, did not change significantly from one station to another. Long range transport and resuspension of local soil were suggested as sources of background SO₂ and SPM, respectively. The difference between observed and background concentrations of SO₂ and SPM in each station was related to the impact of industries on air quality at that particular site.     

Long-term relationships between SO2 and NOx emissions and SO4(2-) and NO3- concentration in bulk deposition at the Hubbard Brook Experimental Forest, NH

A highly significant second-order polynomial relation between SO(2) emissions and SO(4)(2-) concentrations during 1970-2000 (r(2)= 0.80, p= <0.001), and a linear relation between NO(x) and NO(3)(-) concentrations during 1991-2000 (r(2)= 0.67, p= 0.004) in bulk precipitation were found for the Hubbard Brook Experimental Forest, NH based on emissions from a 24 h, back-trajectory determined source area. Earlier periods (1965-1980) for SO(2)ratio SO(4)(2-) and longer periods (1965-2000) for NO(x)ratio NO(3)(-) had poorer linear relations, r(2)= 0.03, p= 0.51 and r(2)= 0.22, p= 0.004, respectively. Methodology by the US Environmental Protection Agency for calculating emissions data during this period has changed significantly and frequently, making trend analysis difficult. Given the large potential for errors in estimating emissions and to a lesser extent, deposition, the robust relations between SO(2) emissions and SO(4)(2-) concentrations in bulk precipitation at the Hubbard Brook Experimental Forest show that careful, long-term measurements from a single monitoring site can provide sound and reasonable data on trends in air pollution.     

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.     

兰州市汽车尾气污染状况调查

通过对兰州市汽车尾气污染状况的调查与分析，认为兰州市街道空气污染较重，ＣＯ、ＮＯｘ、ＳＯ２、ＴＳＰ、Ｐｂ各项污染均超标，其污染程度与车流强度、时间、季节、路面宽度、风速及不同形式的交通路口相关。汽车尾气排放已成为兰州市空气污染的重要来源。