Seasonal evaluation and spatial variability of suspended particulate matter in the vicinity of a large coal-fired power station in India—A case study

Coal combustion in the power sector gives rise to the emission of primary and secondary particulate pollutants. Since the emission of pollutants depends on coal quality and combustion technology, and given that transport, transformation and deposition of contaminants depend on regional climatic conditions, specific studies for the power stations is needed to evaluate their environmental impacts. Monitoring of ambient respirable suspended particulate matter (RSPM) and suspended particulate matter (SPM) levels around a large coal-fired power station in India was carried out. The specific objectives were the determination of spatial and seasonal variability in RSPM and SPM levels, and their relationship with meteorological parameters such as wind velocity and relative humidity. The results have shown a marked seasonal trend and spatial variability in RSPM and SPM levels in the study area. Higher concentrations of ambient RSPM and SPM were found in downwind monitoring stations compared to upwind direction. Ratios of RSPM to SPM and correlation coefficient values between RSPM and SPM along with meteorological parameters were also worked out. Relative humidity and wind velocity have shown an inverse relation with particulate deposition pattern.     

Study of size and mass distribution of particulate matter due to crop residue burning with seasonal variation in rural area of Punjab, India

Emission from field burning of agricultural crop residue is a common environmental hazard observed in northern India. It has a significant potential health risk for the rural population due to respirable suspended particulate matter (RSPM). A study on eight stage size segregated mass distribution of RSPM was done for 2 wheat and 3 rice crop seasons. The study was undertaken at rural and agricultural sites of Patiala (India) where the RSPM levels remained close to the National Ambient Air quality standards (NAAQS). Fine particulate matter (PM(2.5)) contributed almost 55% to 64% of the RSPM, showing that, in general, the smaller particles dominated during the whole study period with more contribution during the rice crop as compared to that of wheat crop residue burning. Fine particulate matter content in the total RSPM increased with decrease in temperature. Concentration levels of PM(10) and PM(2.5) were higher during the winter months as compared to that in the summer months. Background concentration levels of PM(10), PM(2.5) and PM(10-2.5) were found to be around 97 ± 21, 57 ± 15 and 40 ± 6 μg m(-3), respectively. The levels increased up to 66, 78 and 71% during rice season and 51, 43 and 61% during wheat crop residue burning, respectively. Extensive statistical analysis of the data was done by using pair t-test. Overall results show that the concentration levels of different size particulate matter are greatly affected by agricultural crop residue burning but the total distribution of the particulate matter remains almost constant.     

Characterisation of particulate matter for toxic metals in ambient air of Kochi City, India

Measurement of respirable suspended particulate matter (RSPM) and analysis of toxic metals in air of Kochi city was carried out for a period of one year, 1997. Seasonal variations of RSPM and toxic metals are analysed to identify the influence of meteorological parameters. The air pollution problem with respect to RSPM and lead is moderately significant especially in winter season. The profile of other toxic metals in RSPM is not much significant. Domestic fuel used mainly coal/wood and petrol/diesel fueled motor vehicles are the major contributors to the RSPM and toxic metals. Various control strategies are delineated for reduction of ambient RSPM and toxic metals in air of Kochi city.     

Efficient control of air pollution through plants, a cost-effective alternative: studies on Dalbergia sissoo Roxb

Plants can be used as both passive biomonitors and biomitigators in urban and industrial environments to indicate the environmental quality and to ameliorate pollution level in a locality. Many studies reveal that plants are negatively affected by the ambient levels of air pollutants. The present study was conducted to evaluate the impact of air pollution on comparative basis with reference to changes in photosynthetic pigments, plant height, leaves, as well as, biochemical parameters of plants of different sites around Udaipur city receiving varying levels of pollution load. The investigated tree species Dalbergia sissoo Roxb. (Family: Fabaceae) exhibited a reduction in various physiological and biochemical growth parameters that correspond with air pollution levels at different sites. The tree species growing in polluted and control areas were compared with respect to foliar dust load, leaf area, and chlorophyll and total carbohydrate and total protein concentration in the leaves. Our studies suggest that D. sissoo Roxb. can successfully be grown in an area for monitoring air pollution, where it is mild and droughts are common. It will prove as an ideal tree species to control pollution effectively beside acting as a shade tree and being a source of food for birds and animals. By plantation of D. sissoo Roxb., mitigative measure at the polluted sites to control generation of particulate matter and the air quality required can be ensured. Our results also confirm that industrial and vehicular air pollution level in Udaipur city is shifting beyond limits.     

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.     

Assessing Respiratory Morbidity Through Pollution Status and Meteorological Conditions for Delhi

The study focuses on assessing the status of respiratory morbidity in Delhi over a four years period from 2000–2003. An attempt was made to investigate the role of important pollutants (SO₂, NO₂, SPM and RSPM) and various meteorological factors (temperature minimum & maximum, relative humidity at 0830 and 1730 hrs. and wind speed) in being responsible for respiratory admissions on account of COPD, asthma and emphysema. The study showed that winter months had greater exposure risk as pollutants often get trapped in the lower layers of atmosphere resulting in high concentrations. Statistical analysis revealed that two pollutants have significant positive correlation with the number of COPD cases viz., SPM (r = 0.474; p < 0.01) and RSPM (r = 0.353; p < 0.05), while a meteorological factor temperature (minimum) has a significant negative correlation (r = −0.318; p < 0.05) with COPD. Stepwise multiple regression analysis was performed for COPD as dependent variable and R² value of 0.33 was obtained indicating that SPM and RH(1730) were able to explain 33 percent variability in COPD. The partial correlation of SPM and RH(1730) on COPD was higher than any other combination and therefore they can be regarded as important contributing variables on COPD.     

Accumulation of different sulfur fractions in Chinese forest soil under acid deposition

Atmogenic sulfur (S) deposition loading by acid rain is one of the biggest environmental problems in China. It is important to know the accumulated S stored in soil, because eventually the size (and also the "desorption" rate) determines how rapidly the soil water pH responds to decrease in S deposition. The S fractions and the ratio of total carbon/total sulfur (C/S) of forest soil in 9 catchments were investigated by comparing soils at the rural and urban sites in China. The S fractions included water-soluble sulfate-S (SO(4)-S), adsorbed SO(4)-S, insoluble SO(4)-S and organic S. The ratio of C/S in soil at the rural site was significantly (p < 0.05) greater than that at the urban site. C/S of soil in the A horizon was significantly (p < 0.05) and negatively correlated with the wet S-deposition rate. The ratio of C/S presents a better indicator for atmogenic S loading. Organic S was the dominant form in soils at rural sites; contributing more than 69% of the total S in the uppermost 30 cm soil. Organic S and adsorbed SO(4)-S were the main forms of S in soil at urban sites. High contents of water-soluble SO(4)-S and adsorbed SO(4)-S were found in uppermost 30 cm soils at urban sites but not at rural sites. Decades of acid rain have caused accumulation of inorganic SO(4)-S in Chinese forest soil especially at the urban sites. The soil at urban sites had been firstly acidified, and the impacts on the forest ecosystem in these areas should be noticed.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).     

江苏省环境空气质量趋势监测点的优选

介绍了江苏省环境空气监测网络的构成和环境空气质量趋势监测点的优选方法。通过对1993年-2000年全省13个少辖市60个监测点的SO2、TSP监测结果的相关指标统计，分别优选出代表全省及省辖市的环境空气质量趋势监测点12个和25个。     

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.     

Spatio-Temporal Fluxes in Particulate Organic Carbon in a Tropical Coastal Lagoon

Temporal and spatial variations in particulate organic carbon (POC) in relation to primary production, chlorophyll a, phaeophytin, plankton abundance, secondary production and suspended particulate matter (SPM) were studied monthly for 1 year from April 1996 to March 1997 in a shallow tropical coastal lagoon on the southwest coast of India. Though temporal variations in all components were significant, spatial variabilities were not statistically significant. POC values range from 200 to 5690 mg C m³ h⁻¹, while primary production, chlorophyll a, and phaeophytin varied between 0.02 and 14.53 mg C m⁻³ h⁻¹, 0.87 and 23.11 mg m⁻³ and 3.02 and 30.581 mg m⁻³, respectively. Phytoplankton and zooplankton abundance varied from 0.01 to 655.5×10⁵ no m⁻³ and negligible to 7.08×10⁵ no m⁻³ respectively; secondary production from 10 to 490 mg C m⁻³ and SPM between 0.38 and 74.43×10⁴ mg m⁻³ during this study. Temporally, postmonsoon months were observed to have the highest concentrations of POC in the lagoon waters. The bulk of the POC pool in the lagoon was composed of secondary producers (72%), followed by chlorophyll a (21%), phaeophytin (7%) and suspended particulate matter of inorganic origin (< 0.1%).     

Air Quality Status of an Open Pit Mining Area in India

This investigation presents the assessment of ambient air quality carried out at an open pit coal mining area in Orissa state of India. The 24-h average concentrations of suspended particulate matter (SPM), respirable particulate matter (RPM, particles of less than 10 m aerodynamic diameter), sulphur dioxide (SO₂) and oxides of nitrogen (NO_x) were determined at regular interval throughout one year at 13 monitoring stations in residential area and four stations in mining/industrial area. During the study period, the 24-h and annual average SPM and RPM concentrations exceeded the respective standards set in the Indian ambient air quality standard (NAAQS) protocol in most of the residential and industrial areas. However, the 24-h and annual average concentrations of SO₂ and NO_x were well within the prescribed limit of the NAAQS in both residential and industrial areas. A management strategy is formulated for effective control of particulate matter at source and other mitigative measures are recommended including implementation of green belts around the sensitive areas.     

SO2气体对树木叶片叶绿素含量的影响

应用分光光度法研究乌鲁木齐市常见行道树种新疆扬、大叶白腊和新疆大叶榆受ＳＯ２气体危害后，树木叶片叶绿素（ＣＡ、ＣＢ、Ｃｒ）含量的动态变化，以了解其抗性特点。表明，名树种在受危害全进程中其表现不同，树木一身亦具有一定的自调节能力。同时叶绿素在各阶段相对含量的动态变化特点是衡量树种抗性大小的可供参考的有价值指标之一。     

Suspended particulate matter estimates using optical and acoustic sensors: application in Nestos River plume (Thracian Sea,North Aegean Sea)

The present study investigates the use of combined methods of optical and acoustic sensors, in collaboration with direct in situ measurements, for the calibration and validation of a model transforming acoustic backscatter intensity series into suspended particulate matter (SPM) concentration datasets. The model follows previously elaborated techniques, placing particular attention to the parameterization of the acoustic absorption index as a function of water physical properties. Results were obtained from the annual deployment (during 2007–2008) of an upward-facing acoustic Doppler current profiler (ADCP) (307 kHz), equipped with a Wave Array, and an optical backscatter sensor (OBS), at the bottom of Thassos Passage near Nestos River plume (Thracian Sea, Northern Greece). The OBS was calibrated through linear regression, using 2007 and 2012 field sampling data, exhibiting an error of 13–14 % due to chlorophyll presence. The ADCP signal was calibrated through simultaneous measurements of backscatter intensity and turbidity profiles. Harmonic analysis on the model-produced SPM concentrations explained the tidal influence on their variability, especially during the summer. Empirical orthogonal functions analysis revealed the impact of waves and wave-induced currents on SPM variability. Finally, Nestos River sediment load was found uncorrelated to the SPM change in Thassos Passage, due to the dispersal and sediment deposition near the river mouth.     

Evaluation of air pollution phytotoxicity in a seasonally dry tropical urban environment

This study was conducted in the urban environment of Varanasi, India, to evaluate the plant responses to urban air pollution. Twenty sites were selected in four different zones of the city. At each site, seven woody perennials of same age classes were selected. Out of the four zones (I, II, III and IV), zone IV was used as a reference (control) zone as it received the minimum pollution input. Plant species growing in polluted and control areas were compared with respect to foliar dust load, per cent leaf area injury, leaf area, specific leaf weight and chlorophyll, ascorbic acid, SO ₄ ^2– S and total N concentration in the leaves. Results indicated that the air pollution level in Varanasi causes leaf damage, reduces leaf area, specific leaf weight and chlorophyll, ascorbic acid and total N concentrations in the leaves. Sulphur concentration in leaves increased with increasing level of SO₂ in the ambient air. The magnitude of such changes was maximum at the zone receiving maximum pollution load. Carissa carandas was found to be the most sensitive species and Bougainvillea spectabilis, the least. The study shows that the urban air pollution level in Varanasi is detrimental for the growth of plants involved in this study.     

A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?

Trends in atmospheric acid deposition and in soil solution acidity from 1995 or later until 2007 were investigated at several forest sites throughout Switzerland to assess the effects of air pollution abatements on deposition and the response of the soil solution chemistry. Deposition of the major elements was estimated from throughfall and bulk deposition measurements at nine sites of the Swiss Long-Term Forest Ecosystem Research network (LWF) since 1995 or later. Soil solution was measured at seven plots at four soil depths since 1998 or later. Trends in the molar ratio of base cations to aluminum (BC/Al) in soil solutions and in concentrations and fluxes of inorganic N (NO(3)-N + NH(4)-N), sulfate (SO(4)-S), and base cations (BC) were used to detect changes in soil solution chemistry. Acid deposition significantly decreased at three out of the nine study sites due to a decrease in total N deposition. Total SO(4)-S deposition decreased at the nine sites, but due to the relatively low amount of SO(4)-S load compared to N deposition, it did not contribute to decrease acid deposition significantly. No trend in total BC deposition was detected. In the soil solution, no trend in concentrations and fluxes of BC, SO(4)-S, and inorganic N were found at most soil depths at five out of the seven sites. This suggests that the soil solution reacted very little to the changes in atmospheric deposition. A stronger reduction in base cations compared to aluminum was detected at two sites, which might indicate that acidification of the soil solution was proceeding faster at these sites.     

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.     

Atmospheric aerosol concentration level and chemical characteristics of water-soluble ionic species in wintertime in Beijing,China

Total suspended particulate (TSP) samples were collected during wintertime from November 24, 1998 to February 12, 1999 in Beijing. Ionic species including Cl-, NO3(-), SO4(2-), Na+, NH4(+), K+, Mg2+ and Ca2+ were determined by Ion Chromatography (IC). The sum average concentration of all the determined ions accounted for 18.9% of the TSP concentration, and SO4(2-) appeared the dominant ion with an average concentration of 30.84 microg m(-3); the sum mass concentration of SO4(2-), NO3(-), Ca2+ and NH4(+) accounted for about 83.2% of all the eight ions measured. The study indicated that the chemical form of sulfate and ammonium varies with TSP concentration levels. During heavy pollution periods, the average TSP concentration was 0.66 mg m(-3), and the NH4(+)/SO4(2-) molar ratio was low (0.58). It indicated that sulfate may present as CaSO4 and (NH4)2SO4 x CaSO4 x 2H2O. When TSP concentration (average 0.186 mg m(-3)) was relatively low, the NH4(+)/SO4(2-) molar ratio was 1.94, close to the theoretical ratio of 2 of (NH4)2SO4. Under this condition (NH4)2SO4 is expected to exist as the major form of sulfate. When the TSP concentration level was medium (average 0.35 mg m(-3)), the NH4+/SO4(2-) molar ratio appeared an average value (1.27), (NH4)2SO4, (NH4)2SO4 x CaSO4 x 2H2O and CaSO4 are expected to be present in those aerosol particles. Meteorological conditions including wind speed and wind direction were related to the TSP concentration level.     

Investigation of heavy metal content in the suspended particulate matter and sediments of inner Gokova Bay and creeks

The Bay of Gokova in Southeastern Aegean Sea (Turkey) is important by the potential of agricultural, municipal, and tourism activities. In addition, there is no industrial plant within the area in the Aegean Sea. Kad?n Creek (Azmak) and Ak?ap?nar Creek (Azmak) flowing into the inner Gokova Bay are one of the important factors in determining the character of the inner Gokova Bay. In this study, nine stations were selected in the inner Gokova Bay, Kad?n Creek, and Akcap?nar Creek. The concentrations of Cd, Cu, Fe, Pb, and Zn were measured in suspended particulate matter (SPM) and sediments. The samples of sediments and SPM were collected in between February 2008 and September 2008. The aim of the study is searching the change of concentrations of Cd, Cu, Fe, Pb, and Zn in suspended particulate matter and sediments in the inner Gokova bay, Kad?n Creek, and Ak?ap?nar Creek. It has been identified that the metal concentrations in the creeks are higher than the metal concentrations in the marine environment. It has also been observed that the concentrations of Pb, Cd, and Cu in summer season have been higher than in the winter season, but the concentrations of Fe and Zn have not shown a significant difference between in summer and winter seasons. The obtained results show that the some heavy metals are caused by the agricultural, municipal, and tourism activities operating in the coastal areas and terrestrial environment, and they are transported from the creeks to the Gokova Bay by suspended particulate matter.