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1.
The concentrations of criteria air pollutants such as CO, NOx (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, NOx, 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. NOx/SO2 ratio was also examined to bring out the source origin contributing on air pollution (i.e., traffic or stationary).  相似文献   

2.
Surface coal mining creates more air pollution problems with respect to dust than underground mining . An investigation was conducted to evaluate the characteristics of the airborne dust created by surface coal mining in the Jharia Coalfield. Work zone air quality monitoring was conducted at six locations, and ambient air quality monitoring was conducted at five locations, for a period of 1 year. Total suspended particulate matter (TSP) concentration was found to be as high as 3,723 μg/m3, respirable particulate matter (PM10) 780 μg/m3, and benzene soluble matter was up to 32% in TSP in work zone air. In ambient air, the average maximum level of TSP was 837 μg/m3, PM10 170 μg/m3 and benzene soluble matter was up to 30%. Particle size analysis of TSP revealed that they were more respirable in nature and the median diameter was around 20 μm. Work zone air was found to have higher levels of TSP, PM10 and benzene soluble materials than ambient air. Variations in weight percentages for different size particles are discussed on the basis of mining activities. Anionic concentration in TSP was also determined. This paper concludes that more stringent air quality standards should be adopted for coal mining areas and due consideration should be given on particle size distribution of the air-borne dust while designing control equipment.  相似文献   

3.
Aerosol samples for dry deposition and total suspend particulates (TSP) were collected from August to November of 2003 in central Taiwan. Ion chromatography was used to analyze the related water-soluble ionic species (Cl, NO3 , SO4 2−, Na+, NH4 +, K+, Mg2+ and Ca2+). The results obtained in this study indicated that the ambient air particulate mass concentrations in the daytime period (averaged 975.4 μg m−3) were higher than the nighttime period (averaged 542.1 μg m−3). And the daytime dry deposition fluxes (averaged 58.12 μg m−2 sec−1) were about 2.2 times as that of nighttime dry deposition fluxes (averaged 26.54 μg m−2 sec−1) of the downward dry deposition. The average values downward and upward of dry deposition fluxes for the weekend period were almost higher than the weekday period for either daytime or nighttime period. Furthermore, the average daytime dry deposition fluxes (averaged 26.37 μg m−2 sec−1) were also about 2.3 times as that of nighttime dry deposition fluxes (averaged 11.52 μg m−2 sec−1). Moreover, the results also indicate that SO4 2− and Ca2+ have higher average composition for total suspended particulates in the daytime period while Ca2+, SO4 2−, and Na+ have the higher average composition for total suspends particulates in the nighttime period.  相似文献   

4.
This research paper aims at establishing baseline PM10 and PM2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM2.5) and coarser fractions (PM10-2.5) to PM10 fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM10 concentration was 304 μg/m3, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM10 concentration was due to fine fraction (PM2.5) released by vehicular exhaust. The 24h average PM2.5 concentration was found 179 μg/m3, which is exceeded USEPA and EU standards of 65 and 50 μg/m3 respectively for the winter. India does not have any PM2.5 standards. The 24 h average PM10-2.5 concentrations were found 126 μg/m3. The PM2.5 constituted more than 59% of PM10 and whereas PM10-PM2.5 fractions constituted 41% of PM10. The correlation between PM10 and PM2.5 was found higher as PM2.5 comprised major proportion of PM10 fractions contributed by vehicular emissions.  相似文献   

5.
An ambient air quality study was undertaken in two cities (Pamplona and Alsasua) of the Province of Navarre in northern Spain from July 2001 to June 2004. The data were obtained from two urban monitoring sites. At both monitoring sites, ambient levels of ozone, NOx, and SO2 were measured. Simultaneously with levels of PM10 measured at Alsasua (using a laser particle counter), PM10 levels were also determined at Pamplona (using a beta attenuation monitor). Mean annual PM10 concentrations in Pamplona and Alsasua reached 30 and 28 μg m−3, respectively. These concentrations are typical for urban background sites in Northern Spain. By using meteorological information and back trajectories, it was found that the number of exceedances of the daily PM10 limit as well as the PM10 temporal variation was highly influenced by air masses from North Africa. Although North African transport was observed on only 9% of the days, it contributed the highest observed PM10 levels. Transport from the Atlantic Ocean was observed on 68% of the days; transport from Europe on 13%; low transport and local influences on 7%; and transport from the Mediterranean region on 3% of the days. The mean O3 concentrations were 45 and 55 μg m−3 in Pamplona and Alsasua, respectively, which were above the values reported for the main Spanish cities. The mean NO and NO2 levels were very similar in both sites (12 and 26 μg m−3, respectively). Mean SO2 levels were 8 μg m−3 in Pamplona and 5 μg m−3 in Alsasua. Hourly levels of PM10, NO and NO2 showed similar variations with the typically two coincident maximums during traffic rush hours demonstrating a major anthropogenic origin of PM10, in spite of the sporadic dust outbreaks.  相似文献   

6.
An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM10), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM2.5, PM10, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m−3 and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m−3. Values at Delhi were well above the standard limit for 24-h PM2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m−3), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM2.5 standards. The position of PM10 in Delhi is drastic and needs an immediate attention. PM10 levels at Delhi were also well above the standard limit for 24-h PM10 National Ambient Air Quality Standards (NAAQS; 150 μg m−3), while levels at Satna remained under the standard limit. PM2.5/PM10 values were also calculated to determine PM2.5 contribution. At Satna, PM2.5 contribution to PM10 was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m−3). At Satna, the PM10 contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM10, PM2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.  相似文献   

7.
The objective of the study is to investigate seasonal and spatial variations of PM10 (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM10 and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM10 and TSP were found in the range 68.2–280.6 μg/m3 and 139.3–580.3 μg/m3 for residential (Kasba) area, while 62.4–401.2 μg/m3 and 125.7–732.1 μg/m3 for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM10 is about 52% of TSP at residential area and 54% at industrial area.  相似文献   

8.
The objective of the present study is the exploitation of active sampling personal exposure data in assessing the factors that affect exposure to benzene in combination with the widely accepted scheme of passive sampling—time microenvironment–activity diaries (TMAD). The campaign included personal exposure measurements with both passive and active sampling in several microenvironments, evaluation of TMAD kept by the volunteers, and a variety of environmental data (ambient air benzene determination, traffic and meteorological observations). Due to the relatively elevated benzene traffic emissions, average personal exposure was determined to be equal to 8.9 μg/m3, ranging between 5 and 20 μg/m3, which is a value highly related to the average urban concentration (9.2 μg/m3). The information gained from TMAD was embedded (in terms of spatial and temporal distribution) into three zones respectively, in order to draw statistically significant conclusions about the exposure levels and the activity patterns. The contribution of the activities to the overall amount of exposure was further quantified and refined by active sampling measurements. These data revealed that driving in a traffic-congested road was the main activity leading to elevated exposure levels (up to 70 μg/m3), followed by walking on the roadside of a congested road (up to 35 μg/m3). Indoor exposure to benzene was in general lower than outdoor (indicating that traffic is the dominant source of benzene emissions in the wider area), and it was significantly affected by the presence of environmental tobacco smoke. The higher significance of the regression coefficients obtained by statistical analysis of the active sampling data was fundamental for the development of a regression-based prediction exposure model. The model was evaluated through comparison with the passive sampling data, which were considered as an unknown but realistic data exposure pattern. The model performed very well in terms of expressing the variance of the exposure data with an average score of R 2 equal to 0.935. All of the above indicate that active sampling is a necessary albeit more laborious tool that needs to be used as a complement to passive sampling for precise quantification of the factors determining personal exposure patterns.  相似文献   

9.
Development of baseline (air quality) data in Pakistan   总被引:1,自引:0,他引:1  
During 2003–2004, SUPARCO, the Pakistan Space and Upper Atmosphere Research Commission has conducted a year long baseline air quality study in country’s major urban areas (Karachi, Lahore, Quetta, Rawalpindi, Islamabad and Peshawar). The objective of this study was to establish baseline levels and behavior of airborne pollutants in urban centers with temporal and spatial parameters. This study reveals that the highest concentrations of CO were observed at Quetta (14 ppm) while other pollutants like SO2 (52.5 ppb), NO x (60.75 ppb) and O3 (50 ppb) were higher at Lahore compared to other urban centers like Karachi, Peshawar etc. The maximum particulate (TSP) and PM10 levels were observed at Lahore (996 ug/m3 and 368 ug/m3 respectively), Quetta (778 ug/m3, 298 ug/m3) and in Karachi (410 ug/m3, 302 ug/m3). In all major cities the highest levels were recorded at major intersections and variations were directly correlated with traffic density. These pollutants showed highest levels in summer and spring while lowest were observed in winter and monsoon. A data bank has been generated for future planning and air pollution impact studies.  相似文献   

10.
In a field study carried out at three different locations, the dissipation of spiromesifen on cotton and chili was studied and its DT50, and DT99 were estimated at each location. Spiromesifen was sprayed on chili at 96 and 192 g a.i. ha−1 and cotton at 120 and 240 g a.i. ha−1. Samples of chili fruits were drawn at 0, 1, 3, 5, 7, 10, 15, 21, 30 days after treatment and that of cotton seed and lint at first picking and harvest. Soil samples were drawn 30 days after treatment from 0 to 15 and 15 to 30 cm layer. Quantification of residues was done on GC–MS in Selected Ion Monitoring (SIM) mode in mass range 271–274 m/z. The LOQ of this method was found 0.033 μg g−1, LOD being 0.01 μg g−1. The DT50 of spiromesifen when applied at recommended doses in chili fruits was found to be 2.18–2.40 days. Ninety-nine percent degradation was found to occur within 14.5–16.3 days after application. Residues of spiromesifen were not detected in cotton seed and lint samples at the first picking. In soil, no residues of spiromesifen were detectable 15 days after treatment.  相似文献   

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