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1.
Mass concentrations of PM10, PM2.5, and black smoke (BS) were measured in April 2003 during a 3-week campaign in a small village and at a nearby background location in the central part of the Czech Republic. In a pilot analysis, concentrations of selected trace elements (Al, Ti, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Sr, Cd, Sb, Cs, Pb) in the collected aerosol were determined by means of ICP-MS. Average concentrations of both PM fractions and BS were higher in the village (37, 26 and 26 μg m−3) than at the background location (26, 19 and 11 μg m−3) for PM10, PM2.5 and BS, respectively. Both PM10 and PM2.5 were reasonably correlated in the village (r = 0.80) and also at the background location (r = 0.79). Correlation between same fractions from the village and from the background site were even higher (r = 0.97 and r = 0.95 for the PM10 and PM2.5, respectively) suggesting that most of the aerosol in both locations may be influenced by similar sources. The ratio between PM10 and PM2.5 showed that sources in the village contributed about 33% and 35% to local aerosol concentration for PM10 and PM2.5, respectively. When the data from the two rural locations were compared with corresponding 24-h averages of PM10 concentrations obtained for the period of the campaign from fixed site monitors situated near larger towns, the highest concentration was found in Prague the Czech capital (49 μg m−3) followed by a district town Beroun (41 μg m−3) and the village (37 μg m−3). The lowest PM10 concentration was found in the village background (26 μg m−3). Elemental analysis revealed higher concentrations for most of the elements characteristic of combustion aerosol (namely Zn, Pb, As, Mn and Ti) in the PM collected in the village. The results support the idea that traditional heating in villages may contribute a great extent to local air pollution and may represent an important problem.  相似文献   

2.
This paper presents results of an atmospheric particulate matter (PM) monitoring and source apportionment study conducted during summer and fall 2010 in Cairo. These results are compared to those of similar studies in 1999 and 2002. Concentrations of PM2.5 and PM10 mass and their chemical constituents were determined and chemical mass balance modeling was conducted to estimate the source contributions to ambient PM. Emphasis was placed on characterizing the long-term trends in atmospheric lead (Pb) concentrations and their sources in Cairo. PM2.5 and PM10 concentrations were highest during fall 1999 at four of the five study sites. This was also the case for open (vegetative/trash) burning contributions, which showed a smaller increase during fall 2010. Burning of agricultural waste after the fall harvest continues to be a major source of PM in Cairo. Both PM2.5 and PM10 mass decreased dramatically at Shobra, an industrial site, from 1999 to 2010. A reduction of lead smelting has resulted in a decrease of ambient Pb concentrations of up to two orders of magnitude from 1999 to 2010 at Shobra, El-Zamalek, and El-Qualaly. From 1999 to 2010, the mobile source contribution has been relatively stable at most of the study sites. Future efforts to reduce ambient PM should focus on controlling emissions from motor vehicles and open burning and implementing mitigation strategies for reducing resuspended road and construction dust.  相似文献   

3.
The objective of the study is to investigate spatio-temporal variations of PM10, PM2.5, and PM1 concentrations at seven residential sites, located in the vicinity of opencast coal projects, Basundhara Garjanbahal Area (BGA), India. Meteorological parameters such as wind speed, wind direction, relative humidity, and temperature were collected simultaneously with PM concentrations. Mean concentrations of PM10 in the range 215 ± 169–526 ± 412 μg m?3, PM2.5 in the range of 91 ± 79–297 ± 107 μg m?3, PM1 in the range of 68 ± 60–247 ± 84 μg m?3 were obtained. Coarse fractions (PM2.5–10) varied from 27 to 58% whereas fine fractions (PM1–2.5 and PM1) varied in the range of 51–73%. PM2.5 concentration was 41–74% of PM10 concentration, PM1 concentration was 31–62% of PM10 concentration, and PM1 concentration was 73–83% of PM2.5 concentration. Role of meteorology on PM concentrations was assessed using correlation analysis. Linear relationships were established among PM concentrations using least square regression analysis. With the aid of principal component analysis, two components were drawn out of eight variables, which represent more than 75% of variance. The results indicated that major sources of air pollutants (PM10, PM2.5, PM1, CO, CO2) at the residential sites are road dust raised by vehicular movement, spillage of coal generated during transportation, spontaneous combustion of coal, and biomass burning in village area.  相似文献   

4.
This paper is concerned with the estimation of the removal efficiency of PM10 by large-scale precipitation under no-wind conditions in a background (rural) and urban areas. The changes in PM10 concentrations before, during and after the presence of rainfall were studied from 2007 to 2013. The study was conducted in two different locations identified with regard to air quality. DAVIS weather stations were used to determine the meteorological conditions. The concentration of PM10 was calculated with the use of the gravimetric reference method. Two hundred and ninety-nine measurement series were carried out. A linear relationship was found between the intensity and duration of rainfall and the value of the removal coefficient (ΔC). It was proved that except light rains, for the near-to-ground troposphere, the effectiveness of the removal of PM10 (ΔC) did not assume different values at various locations for rainfall with the same intensity and duration. It was found that a temporary interaction of the effect of the purification by wet deposition was being minimised in areas characterised by low air quality. It was confirmed that intense rains resulted in the maintenance of higher values of air quality.  相似文献   

5.
Arid and semi‐arid environments are important sources for the atmospheric loading of PM10 (particulate matter <10 μm), although the emission of this material is often limited by surface crusts. This study investigates the emission and vertical flux of PM10 from a clay‐crusted playa, with and without saltating grains to abrade the surface. Using a portable field wind tunnel, it was found that, despite disturbance to the surface, the emission of PM10 decays rapidly without abrasion. Only in the presence of saltating grains was PM10 continuously liberated from the surface, such that the emission rate (the total amount of PM10 emitted from the surface expressed as a horizontal flux) varied linearly with the saltation transport rate. Although the emission of PM10 was found to depend on saltation abrasion, past studies have tended to focus on the relationship between the vertical flux of PM10 (the amount of PM10 being transported vertically through the boundary layer) and the shear velocity. In this study, the vertical flux of PM10 was found to vary with the shear velocity to the power of 2·14. Although the vertical PM10 flux is a proportion of the emission rate (the horizontal flux), no statistically significant relationship was observed between the emission rate and the shear velocity. The disparity of these results is explained by the lack of a consistent relationship between the shear velocity and the saltation transport rate in this supply‐limited environment. This suggests that the observed relationship between the vertical PM10 flux and the shear velocity is a spurious correlation, resulting from the use of shear velocity to calculate the vertical dust flux. It is thus concluded that shear velocity is not an appropriate variable for emission modelling in supply‐limited environments and that improvements in dust emission modelling will only be realized if the abrasion process is the focus of a concerted research effort.  相似文献   

6.
Compliance with U.S. air quality regulatory standards for atmospheric fine particulate matter (PM2.5) is based on meeting average 24 hour (35 μ m?3) and yearly (15 μg m?3) mass‐per‐unit‐volume limits, regardless of PM2.5 composition. Whereas this presents a workable regulatory framework, information on particle composition is needed to assess the fate and transport of PM2.5 and determine potential environmental/human health impacts. To address these important non‐regulatory issues an integrated approach is generally used that includes (1) field sampling of atmospheric particulate matter on filter media, using a size‐limiting cyclone, or with no particle‐size limitation; and (2) chemical extraction of exposed filters and analysis of separate particulate‐bound fractions for total mercury, trace elements and organic constituents, utilising different USGS laboratories optimised for quantitative analysis of these substances. This combination of sampling and analysis allowed for a more detailed interpretation of PM2.5 sources and potential effects, compared to measurements of PM2.5 abundance alone. Results obtained using this combined approach are presented for a 2006 air sampling campaign in Shenandoah National Park (Virginia, USA) to assess sources of atmospheric contaminants and their potential impact on air quality in the Park. PM2.5 was collected at two sampling sites (Big Meadows and Pinnacles) separated by 13.6 km. At both sites, element concentrations in PM25 were low, consistent with remote or rural locations. However, element/Zr crustal abundance enrichment factors greater than 10, indicating anthropogenic input, were found for Hg, Se, S, Sb, Cd, Pb, Mo, Zn and Cu, listed in decreasing order of enrichment. Principal component analysis showed that four element associations accounted for 84% of the PM2.5 trace element variation; these associations are interpreted to represent: (1) crustal sources (Al, REE); (2) coal combustion (Se, Sb), (3) metal production and/or mobile sources (Mo, Cd, Pb, Cu, Zn) and (4) a transient marine source (Sr, Mg). Concentrations of Hg in PM2.5 at background levels in the single pg m?3 were shown by collection and analysis of PM2.5 on filters and by an automated speciation analyser set up at the Big Meadows air quality site. The speciation unit revealed periodic elevation of reactive gaseous mercury (RGM) that co‐occurred with peaks in SO2, indicating an anthropogenic source. GC/MS total ion current chromatograms for the two sites were quite similar indicating that organic signatures were regional in extent and/or that the same compounds were present locally at each site. Calculated carbon preference index values for n‐alkanes indicated that plant waxes rather than anthropogenic sources, were the dominant alkane source. Polycyclic aromatic hydrocarbons (PAHs) were detected, with a predominance of non‐alkylated, and higher molecular weight PAHs in this fraction, suggestive of a combustion source (fossil fuel or forest fires).  相似文献   

7.
In order to examine the spatial variability of the aerosol characteristics across the Brahmaputra valley, a land campaign was conducted during late winter (February 3–March 2) 2011. Measurements of particulate matter (PM, PM10, PM2.5) and black carbon (BC) concentrations were made onboard an interior redesigned vehicle. The length of the campaign trail stretched about 700 km, covering the longitude belt of 89.97°–95.55°E and latitude belt of 26.1°–27.6°N, comprising 13 measurement locations. The valley is divided into three sectors longitudinally: western sector (R1: 89.97°–91.75°E), middle sector (R2: 92.5°–94.01°E) and eastern sector (R3: 94.63°–95.55°E). Spatial heterogeneity in aerosol distribution has been observed with higher PM10 and PM2.5 concentrations at the western and middle sectors compared to the eastern sector. The locations in the western sector are found to be rich in BC compared to the other two sectors and there is a gradual decrease in BC concentrations from west to east of the Brahmaputra valley. Two hotspots within the western and middle sectors with high PM and BC concentrations have been identified. The associated physico-optical parameters of PM reveal abundance of PM2.5 aerosols along the entire valley. High population density in the western and middle sectors, together with the contribution of remote aerosols, leads to higher anthropogenic aerosols over those regions. Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) slightly underestimates the measured PM10 and PM2.5 at the eastern sector while the model overestimates the measurements at a number of locations in the western sector. In general, BC is underestimated by the model. The variation of BC within the campaign trail has not been adequately captured by the model leading to higher variance in the western locations as compared to the middle and eastern locations.  相似文献   

8.
This paper presents the analysis and interpretation of ambient particulate matter concentrations measured as PM10 at a network of six air monitoring stations in Kathmandu valley during the years, 2003 through 2005. The purpose was to understand the pollution trends associated with different areas considering levels particulate matter concentrations representing the ambient air quality of Kathmandu valley. The study indicate that particulate concentrations (PM10) measured are persistently higher at air sampling sites representing roadside areas compared to the background sites. The inter-station network variability with respect the particulate pollution suggests optimizing resources. The comparison of annual average PM10 concentration observed at six air-monitoring sites in Kathmandu Valley with standard annual average concentration prescribed by World Health Organization as well as Europe Union indicates serious PM10 pollution in Kathmandu valley.  相似文献   

9.
The purpose of this paper was to perform the experimental and numerical analyses of PM10 and PM2.5 concentrations in Imam Khomeini (IKH) underground subway station in Tehran. The aim was to provide fundamental data in order to fulfill workers and passengers respiratory health necessities. Experimental measurements was done at three different locations (entrance, middle and exit) inside the platform and also outdoor ambient of the station. The Dust-Trak was applied to measure continuous PM2.5 and PM10 concentrations at a logging interval of 30 s. The measurements were recorded during rush hours (8:00 am–12:00 pm) for one week per each season from June 2015–June 2016.Moreover, computational fluid dynamic (CFD) simulation was done for the platform of the above station and the necessary boundary conditions were provided through field measurements. Those basic parameters which were considered for numerical analysis of particulate matters concentrations included air velocity, air pressure and turbulence. Furthermore, the piston effect caused by train movement inside the station provided natural ventilation in the platform. The results showed that seasonal measured PM2.5 and PM10 indoor concentrations had a variety range from 40–98 µg/m3 to 33–102 µg/m3, respectively, and were much higher than national indoor air quality standard levels. Meanwhile, PM2.5 and PM10 concentrations in the IKH underground subway station were approximately 2.5–2.9 times higher than those in outdoor ambient, respectively. Numerical simulation indicated that the predicted concentrations were underestimated by a factor of 8% in comparison with the measured ones.  相似文献   

10.
The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R2 =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM2.5 ground concentrations. Finally, we studied the relationship between PM2.5 and AOD at the intra-urban scale (?10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM2.5 relationship does not depend on relative humidity and air temperatures below ～7 °C. The correlation improves for temperatures above 7–16 °C. We found no dependence on the boundary layer height except when the former was in the range 250–500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM2.5 concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM2.5 relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM2.5 mass concentrations are highly correlated with the actual observations (out-of-sample R2 of 0.86). Therefore, adjustment for the daily variability in the AOD-PM2.5 relationship provides a means for obtaining spatially-resolved PM2.5 concentrations.  相似文献   

11.
Agriculture tillage can result in the high concentration of particulate matter with an aerodynamic diameter of 10 μm or less (PM10) that can cause serious health problems. To understand how different agriculture tillage methods and wind conditions affect the transmission and distribution of PM10, four model runs were performed using the high resolution Weather Research and Forecasting model coupled with a chemistry component (WRF-Chem). In these runs, the observed emission rates under the conventional and combined tillage methods and different wind speeds were inputted into WRF-Chem. The simulated results show that the WRF-Chem model can reasonably capture the meteorological conditions at 500 m horizontal resolution over an agricultural field in California. The atmospheric concentration of particulate matter increases significantly with an increase in the emission area. Substantial reduction, 50%, of aerosolized PM10 dust emissions can be achieved by using combined tillage, when considered under the same meteorological conditions when compared to that caused by the conventional tillage method. Using the same conventional tillage emission rates, the lower velocity wind produces larger airborne concentrations of pollutants than does a stronger wind. Conversely, a stronger wind distributes the particulate matter over a larger area though with a diminished concentration when compared to a weaker wind. The atmospheric concentration of particulate matter was found to have a direct relationship to its emission intensity and area and wind conditions.  相似文献   

12.
People living in the urban area and the surrounding suburban area have disparities in exposure and health risks due to different levels of ambient air pollutants. The main objective of this study is to investigate the concentrations, seasonal variations, and related health risks of ambient air pollutants (PM10, NO2, and SO2) in urban and suburban areas of Ningbo, China. The results showed that the average PM10, NO2, and SO2 concentrations in the urban area were 85.2, 49.3, and 37.4 μg/m3, which were 1.13, 1.25, and 1.41 times the values of the suburban area during the period of March 2009 to February 2010. For the potential health risk analysis, the residents have been divided into four age categories namely, infants, children (1 year), children (8–10 years), and adults. The analysis took into account age-specific breathing rates, body weights for different age categories. The results showed that the potential health risks to respiratory disease for all age categories living in urban area were higher than those in suburban area.  相似文献   

13.
Based on long-term PM2.5 data observed at high temporal and spatial resolution, the relationships between PM2.5, primary emission, and weather factors in China during four seasons were examined using statistical analysis. The results reveal that primary emission plays a decisive role in the spatial distribution and seasonal variability of PM2.5, except in western China, where PM2.5 is controlled by dust weather. In addition to the accumulation of primary emissions, unfavorable meteorological conditions for the diffusion of air pollution lead to the occurrence of PM2.5 pollution. The significant dynamic factors affecting PM2.5 concentration are surface wind speed, planet boundary layer height, and ventilation coefficient, especially in winter. The ventilation coefficient is inversely correlated with PM2.5. Better ventilation is more favorable for the dilution and outflow of local PM2.5. However, in spring and autumn, ventilation coefficient and PM2.5 are positively correlated over the southern regions with low emission, indicating that ventilation also affects the inflow of PM2.5 from outside the region. Wind shear, 850 hPa divergence, and vertical velocity have insignificant effects on the long-term variations in PM2.5. The significant thermal factor is 850 hPa temperature in winter, except in the Pearl River Delta and Xinjiang regions. In spring, the influence of each thermal factor is weak. In summer, the influences of temperature and humidity are more significant than in spring. In autumn, the influence of humidity is relatively obvious, compared with other thermal factors. The correlation coefficients between multi-factors regressed and observed PM2.5 concentrations pass the 95% confidence test, and are higher than that of single-factor regression over most regions. The observed data from December 2016 to February 2017 were chosen to test the regression equation. The test result reveals that the regression equation is effective for predicting PM2.5 concentrations over regions with high primary emission.  相似文献   

14.
分析了2014~2018年北方5个典型中小盆地城市(兰州、银川、临汾、太原、南阳)PM10与PM2.5的浓度变化特征和大致来源类型。除2018年银川PM2.5浓度外,各市PM10和PM2.5年均浓度均超标;兰州、银川和南阳PM10与PM2.5呈逐年下降趋势,南阳下降最明显;临汾PM10与PM2.5呈逐年上升趋势;太原PM10与PM2.5稳定维持在一个高浓度状态。5个城市颗粒物浓度的季节变化特征一致:冬春高、夏秋低。对PM2.5/PM10值而言,冬季和夏季该比值较高,分别受取暖和降水的影响;春季和秋季该比值较低,分别受沙尘和秸秆焚烧及高强度建筑施工的影响。5市PM2.5和PM10浓度具有良好的线性关系,细颗粒占比大小顺序为临汾>南阳>太原>银川>兰州。  相似文献   

15.
The objective of this paper is to analyze temporal and seasonal trends of air pollution in Bahrain between 2006 and 2012 by utilizing datasets from five air quality monitoring stations. The non-parametric and robust Theil-Sen approach is employed to study quantitatively temporal variations of particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). The calculated annual concentrations for PM10 and PM2.5 in Bahrain were substantially higher than recommended World Health Organization (WHO) guideline standards. Results showed increasing trends for PM10, PM2.5, and SO2 whereas O3 and its precursor NO2 showed decreasing behavior. The general increase in air pollution trends is in agreement with prediction of air pollution models for Middle East region due to economic growth, industrialization, and urbanization. The significances of long-term trends were examined. Additional to actual (unadjusted) trends, meteorological adjusted (deseasonalized) trends and seasonal trends were quantified. The box-plot analysis visually illustrated monthly variations of key air pollutants. It showed that only PM10 and PM2.5 exhibited seasonal pattern, and their concentrations increased during summer and decreased during winter. The effects of ambient air temperature, relative humidity, wind speed, and rainfall on particulate matter (PM) concentrations were further investigated. The Spearman correlation coefficient results demonstrated significant negative correlation between relative humidity and PM concentrations (??0.595 for PM10 and ??0.526 for PM2.5) while significant positive correlation was observed between temperature and PM concentrations (0.420 for PM10 and 0.482 for PM2.5).  相似文献   

16.
The 19th Common Wealth Games was organized at Delhi, India, during October 3 to 14, 2010, where more than 8,000 athletes from 71 Commonwealth Nations have participated. In order to give them better environment information for proper preparedness, mass concentrations of particulate matters below 10 microns (PM10) and 2.5 microns (PM2.5), black carbon (BC) particles and gaseous pollutants such as carbon monoxide (CO) and nitrogen oxide (NO) were monitored and displayed online for ten different locations around Delhi, including inside and outside the stadiums. This extensive information system for air quality has been set up for the period from September 24 to October 21, 2010, and data have been archived at 5-min interval for further research. During the study period, average concentration of PM10 and PM2.5 was observed to be 229.7 ± 85.5 and 112.1 ± 56.0 μg m?3, respectively, which is far in excess of the corresponding annual averages, stipulated by the national ambient air quality standards. Significant large and positive correlation (r = 0.93) between PM10 and PM2.5 implies that variations in PM10 mass are governed by the variations in PM2.5 mass. The mass concentrations of PM2.5 inside the stadium were found to be ~18 % lower than those outside; however, no large variations were observed in PM10. Mean concentrations of BC, CO and NO for the observation period were 10.9 μg m?3 (Min, 02 μg m?3; Max, 31 μg m?3), 1.83 ± 0.89 ppm (Min, 0.48 ppm; Max, 4.55 ppm) and 37.82 ppb (Min, 2.4 ppb; Max, 206.05 ppb), respectively. BC showed positive correlation (r = 0.73) with CO suggests unified source for both of them, mainly from combustion emissions. All the measured parameters, however, show a significant diurnal variation with enhanced peaks in the morning and late night hours and lower values during daytime.  相似文献   

17.
Eight selected heavy metals and phosphorus (Fe, Zn, Pb, Cu, Cr, Cd, Ni and P) were analyzed in the dust fall samples collected from the surrounding areas adjacent to Al-Hisa phosphate mine central Jordan during summer 2008. The chemical analysis was done using the ICP-AES, after being digested with (HNO3/HCl/HF) acid mixture, beside the identification of their mineral constituents using the XRD. Moreover, the particulate matter (PM) size was investigated and divided into four fractions (PM2.5, PM2.5–10, PMC10–100 and PM>100). The PM10–PM100 were found to be the most abundant in the local atmosphere followed by PM2.5–PM10, while the respirable fraction (PM2.5) and giant fraction (PM>100) showed lower levels. The studied samples contain less PM2.5 and PM10 particulates (9.39 and 28.67), respectively, than samples located far from the mine area (blank samples) (17.32 and 51.7) for PM2.5 and PM10, respectively. The meteorological effects, mainly the prevailing wind direction beside the distance to emission sources affect the distribution of dust particle sizes. Heavy metal contents in studied samples are similar to some extent to those found in Isa Town (Bahraian), which related to similar arid and low precipitation climatic conditions. The effect of phosphate mining activities was obvious as indicated from the presence of apatite as the main mineral phase and the higher P contents. Moreover, the studied samples contain higher Zn, Ni, Cu and to lesser extent Cr than blank samples. They exhibited a significant positive correlation with P, as they are usually associated with the phosphate rocks.  相似文献   

18.
Based on data from ground-based air quality stations, space–time variations of six principal atmospheric pollutants, such as particulate matter (PM2.5 and PM10) and gas pollutants (SO2, NO2, СО, and O3), obtained from January 1, 2014 to December 31, 2017 in the city of Lanzhou, have been studied. Average total concentrations of PM2.5 and PM10 were 53.2?±?26.91 and 124.54?±?82.33 µg/m3, respectively; however, the results showed that in 75.53% and 84.85% days, concentrations of these pollutants exceeded Chinese National Ambient Air Quality Standard and in 100% days exceeded World Health Organization guidelines standards. Daily mean values of aerosol optical depth and Ångström exponent based on data, received by satellite Moderate Resolution Imaging Spectroradiometer, show a broad range of values for aerosol optical depth (from 0.018 to 1.954) and Ångström exponent (from 0.003 to 1.8). Results of principal components analysis revealed three factor loadings. Thus, Factor 1 has the relevant loadings for PM2.5, PM10, CO, SO2, and NO2 (36%) and closely associated with transport emissions and industrial sources, which contribute to air pollution in Lanzhou. Factor 2 was heavily loaded with temperature and visibility (16.94%). Factor 3 consisted of relative humidity (14.11%). Cluster analysis revealed four subgroups: cluster 1 (PM2.5, NO2, SO2), cluster 2 (CO), cluster 3 (PM10) and cluster 4 (relative humidity, visibility, temperature, O3, wind speed), which were compliant with results, obtained from principal components analysis. Positive correlation was found among all pollutants, other than O3. According to processed backward trajectories obtained by Hybrid Single-Particle Lagrangian Integrated Trajectory model, it was found that movement of air masses occur from north, northwest, and west directions—the location of principal natural sources of aerosols.  相似文献   

19.
Size distribution of PM10 mass aerosols and its ionic characteristics were studied for 2 years from January 2006 to December 2007 at central Delhi by employing an 8-stage Andersen Cascade Impactor sampler. The mass of fine (PM2.5) and coarse (PM10?2.5) mode particles were integrated from particle mass determined in different stages. Average concentrations of mass PM10 and PM2.5 were observed to be 306 ± 182 and 136 ± 84 μg m?3, respectively, which are far in excess of annual averages stipulated by the Indian National Ambient Air Quality Standards (PM10: 60 μg m?3 and PM2.5: 40 μg m?3). The highest concentrations of PM10?2.5 (coarse) and PM2.5 (fine) were observed 505 ± 44 and 368 ± 61 μg m?3, respectively, during summer (June 2006) period, whereas the lower concentrations of PM10?2.5 (35 ± 9 μg m?3) and PM2.5 (29 ± 13 μg m?3) were observed during monsoon (September 2007). In summer, because of frequent dust storms, coarse particles are more dominant than fine particles during study period. However, during winter, the PM2.5 contribution became more pronounced as compared to summer probably due to enhanced emissions from anthropogenic activities, burning of biofuels/biomass and other human activities. A high ratio (0.58) of PM2.5/PM10 was observed during winter and low (0.24) during monsoon. A strong correlation between PM10 and PM2.5 (r 2 = 0.93) was observed, indicating that variation in PM10 mass is governed by the variation in PM2.5. Major cations (NH4 +, Na+, K+, Ca2+ and Mg2+) and anions (F?, Cl?, SO4 2? and NO3 ?) were analyzed along with pH. Average concentrations of SO4 2? and NO3 ? were observed to be 12.93 ± 0.98 and 10.33 ± 1.10 μg m?3, respectively. Significant correlation between SO4 2? and NO3 ? in PM1.0 was observed indicating the major sources of secondary aerosol which may be from thermal power plants located in the southeast and incomplete combustion by vehicular exhaust. A good correlation among secondary species (NH+, NO3 ? and SO4 2?) suggests that most of NH4 + is in the form of ammonium sulfate and ammonium nitrate in the atmosphere. During winter, the concentration of Ca2+ was also higher; it may be due to entrainment of roadside dust particles, traffic activities and low temperature. The molar ratio (1.39) between Cl? and Na+ was observed to be close to that of seawater (1.16). The presence of higher Cl? during winter is due to western disturbances and probably local emission of Cl? due to fabric bleaching activity in a number of export garment factories in the proximity of the sampling site.  相似文献   

20.
The influence of reduction in emissions on the inherent temporal characteristics of PM2.5 and NO2 concentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuation Analysis (DFA) during the lockdown period (March 24–April 20, 2020) and the corresponding period during the previous two years (i.e., 2018 and 2019). The analysis suggests the anticipated impact of confinement on the PM2.5 and NO2 concentration in urban cities, causing low concentrations. It is observed that the original PM2.5 and NO2 concentration time series is persistent but filtering the time series by fitting the autoregressive process of order 1 on the actual time series and subtracting it changes the persistence property significantly. It indicates the presence of linear correlations in the PM2.5 and NO2 concentrations. Hurst exponent of the PM2.5 and NO2 concentration during the lockdown period and previous two years shows that the inherent temporal characteristics of the short-term air pollutant concentrations (APCs) time series do not change even after withholding the emissions. The meteorological variations also do not change over the three time periods. The finding helps in developing the prediction models for future policy decisions to improve urban air quality across cities.  相似文献   

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