首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 62 毫秒
1.
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   

2.
The respirable particle matter (PM10) concentration in urban areas has been a chronic cause concern and principal reason for increased morbidity rate among resident population. The present study aimed at estimating a discrete event like mortality rate associated and attributable to excess particulate matter pollution in the Kathmandu Valley area. The Government of Nepal conducts air monitoring of particulates at its air monitoring site network covering valley area. Adopting the data available with respect to PM10 and with several other considerations like cutoff value for PM10, mean annual concentration, demographic data of valley, exceedance to the reference cutoff value, attributable fraction evolution and computation relative risk attributable to PM10 was computed. Assumption was made about the relative risk of long-term average PM10 exposure on natural mortality estimated and reported from a previous study. The estimation or mortality rate in our case was 0.95% after all these considerations and computation. This implies that 95 deaths out of 10,000 deaths are due to particulate pollution existing in the Kathmandu Valley Area.  相似文献   

3.
Due to rapid economic growth of the country in the last 25 years, particulate matter (PM) has become a topic of great interest in China. The rapid development of industry has led to an increase in the haze created by pollution, as well as by high levels of urbanization. In 2012, the Chinese National Ambient Air Quality Standard (NAAQS) imposed ‘more strict’ regulation on the PM concentrations, i.e., 35 and 70 μg/m3 for annual PM2.5 and PM10 in average, respectively (Grade-II, GB3095-2012). The Pearson’s correlation coefficient was used to determine the linear relationship of pollution between pollution levels and weather conditions as well as the temporal and spatial variability among neighbouring cities. The goal of this paper was to investigate hourly mass concentration of PM2.5 and PM10 from June 1 to August 31, 2015 collected in the 11 largest cities of Gansu Province. This study has shown that the overall average concentrations of PM2.5 and PM10 in the study area were 26 and 66 μg/m3. In PM2.5 episode days (when concentration was more than 75 μg/m3 for 24 hrs), the average concentrations of PM2.5 was 2–3 times higher as compared to non-episode days. There were no observed clear differences during the weekday/weekend PM and other air pollutants (SO2, NO2, CO and O3) in all the investigated cities.  相似文献   

4.
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   

5.
Aeolian (wind) erosion is most common in arid regions. The resulted emission of PM10 (particulate matter that is smaller than 10 μm in diameter) from the soil has many environmental and socioeconomic consequences such as soil degradation and air pollution. Topsoil resistance to aeolian transport highly depends on the surface composition. The study aim was to examine variations in PM10 fluxes in a desert-dust source due to surface composition and topsoil disturbance. Aeolian field experiments using a boundary layer wind tunnel alongside soil composition analysis were integrated in this study. The results show variations in PM10 fluxes (ranging from 9.5 to 524.6 mg m?2 min?1) in the studied area. Higher wind velocity increased significantly the PM10 fluxes in all surface compositions. A short-term natural disturbance caused changes in the aggregate soil distribution (ASD) and increased significantly PM10 emissions. Considering that PM10 contains clays, organic matter, and absorbed elements, the recorded PM10 fluxes are indicative of the potential soil loss and degradation by wind erosion in such resource-limited ecosystems. The findings have implications in modeling dust emission from a source area with complex surfaces.  相似文献   

6.
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   

7.
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   

8.
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   

9.
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   

10.
Water soluble components of PM10 Chongqing, China   总被引：1，自引：0，他引：1  
The concentrations of water soluble ions (Na+, NH4 +, K+, Mg2+, Ca2+, NO3 -, Cl-, and SO 4 2- ) in PM10 samples collected on cellulose filters by a medium-volume cascade impactor were determined, which were obtained from three kinds of areas in Chongqing: industrial area (Jiulongpo district), commercial and residential area (Jiangbei district) and background area (Jinyun Mountain in the Beibei district). The results showed that except for the background site, the annual average values of PM10 are 23% – 61% higher than the national air quality standard (GradeII) (0.1 mg/m3), even that the value of the control site is still 20% higher than American standard (0.05 mg/m3). This implied that serious pollution of fine particles occurred in Chongqing. Nine kinds of soluble ions in water of PM10 were analyzed by ion chromatography (IC) and the annual average concentrations follow the order of [SO 4 2- ] > [NO3 -] > [Cl-] > [F-], and [Ca2+] > [NH4 +] > [K+] > [Na+] > [Mg2+]. Their values were different in these areas: the industrial area > the commercial and living area > the control area. As for NH4 +, K+, Ca2+, NO3 - and SO 4 2- , their seasonal average concentrations show a similar variation trend: the values in spring and fall were higher than those in summer and winter. The seasonal average concentrations of [Cl-], [F-], [Na+] and [Mg2+] are much lower than those of other ions. However, the concentrations of [Na+] changed more greatly in different seasons than those of the other three ions. Correlation coefficients showed that the three areas have been polluted by coal smoke and dust to different extents, while some local resources of pollution should be taken into consideration as well.  相似文献   

11.
Outdoor PM2.5 easily flows into indoor and seriously influences indoor air quality due to its characteristics of flow, diffusion and penetration. It is a proper ‘gas’ tracer similar to CO2 to study building ventilation. Therefore, in this paper, a model for calculating air change rates by removing indoor PM2.5 was deduced. Also, some factors influencing the air change rate were qualitatively analyzed and the expression of possible air change rate error was given. The comparison between the results from PM2.5 removal method and the data from CO2 decay method validated the model. The relative error between the results of the two methods is less than 10%. On the basis of validating the model, this paper presented the research of air change rates in ten naturally ventilated house rooms in three Chinese cities. It is found that the rooms with the ventilation rates of 1.15–6.75 m3/h/person have inadequate ventilation.  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.
Santiago, the capital of Chile, suffers from high air pollution levels, especially during winter. An extensive particulate matter (PM) monitoring and analysis program was conducted to quantify elemental concentrations of PM. Size-resolved PM samples (PM2.5 and PM10–2.5) from the La Paz and Las Condes stations in Santiago (2004–2005) were analyzed using ICP-MS. Most trace element concentrations (Cu, Pb, Zn, Mn, V, Sb, Pb and As) were higher during winter than during summer and were also higher at the La Paz station than at the Las Condes station. During the highest pollution events, As concentrations in PM2.5 (16 ng m?3) exceeded the annual average standard value (6 ng m?3). A 10-year time series showed decreasing Pb and As concentrations and slightly increasing Zn, Cu and Mn concentrations. Concentrations of Cr and Ni remained relatively constant. The implementation of new public policies in 1998 may explain the decreasing concentrations of Pb and As. Enrichment factor (EF) calculations identified two principal groups: elements with EF < 10 (Mg, Y, Zr, U Sr, Ca, Ti, and V) and EF > 10 (Rb, K, Cs, Fe, P, Ba, Mn, Ni, Cr, Co, Zn, Sn, Pb, Cu, Mo, Cd, As, Ag, and Sb), which were related to natural and anthropogenic PM sources, respectively. Three main PM sources were identified using factor analysis: a natural source (crustal matter and marine aerosol), combustion and copper smelting. Three other sources were identified using rare earth elements: fluid catalytic crackers, oil-fired power production and catalytic converters.  相似文献   

14.
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   

15.
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   

16.
The rapid urbanization, industrialization, modernization, and the frequent Middle Eastern dust storms have negatively impacted the ambient air quality in Bahrain. The objective of this study is to identify the most critical atmospheric air pollutants with emphasis on their potential risk to health based on calculated AQI (air quality index) values using EPA approach. The air quality datasets of particulate matters (PM10 and PM2.5), ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) were measured in January 2012 and August 2012 using five mobile air quality monitoring stations located at different governorates. The results of this study demonstrated that PM10 and PM2.5 are the most critical air pollutants in Bahrain with PM2.5 prevailing during January 2012 and PM10 prevailing during August 2012. The corresponding AQI categories were utilized to evaluate spatial variability of particulate matters in five governorates. The impact of meteorological factors such as ambient air temperature, wind speed, relative humidity, and total precipitation on ambient air quality were discussed. The analysis demonstrated that the highest PM10 concentrations were observed in the Northern Governorate while the highest PM2.5 concentrations were observed in the Capital, Central, and Northern Governorates during August 2012. It was observed that the levels of PM2.5 pollution were higher within proximity of the industrial zone. The results suggested that the average PM2.5/PM10 ratio in August 2012 was lower than in January 2012 due to the Aeolian processes. This study concludes that higher wind speed, total precipitation, relative humidity rates, and lower ambient air temperature in January 2012 assisted with the dissipation of particulate matter thus lowering the pollution levels of both PM10 and PM2.5 in comparison to August 2012.  相似文献   

17.
Temporal variation of PM10 using 2-year data (January, 2007–December, 2008) of Delhi is presented. PM10 varied from 42 to 200 μg m−3 over January to December, with an average 114.1 ± 81.1 μg m−3. They are comparable with the data collected by Central Pollution Control Board (National Agency which monitors data over the entire country in India) and are lower than National Ambient Air Quality (NAAQ) standard during monsoon, close to NAAQ during summer but higher in winter. Among CO, NO2, SO2, rainfall, temperature, and wind speed, PM10 shows good correlation with CO. Also, PM10, PM2.5, and PM1 levels on Deepawali days when fireworks were displayed are presented. In these festive days, PM10, PM2.5, and PM1 levels were 723, 588, and 536 μg m−3 in 2007 and 501, 389, and 346 μg m−3 in 2008. PM10, PM2.5, and PM1 levels in 2008 were 1.5 times lower than those in 2007 probably due to higher mixing height (446 m), temperature (23.8°C), and winds (0.36 ms−1).  相似文献   

18.
As most air quality monitoring sites are in urban areas worldwide, machine learning models may produce substantial estimation bias in rural areas when deriving spatiotemporal distributions of air pollutants. The bias stems from the issue of dataset shift, as the density distributions of predictor variables differ greatly between urban and rural areas. We propose a data-augmentation approach based on the multiple imputation by chained equations (MICE-DA) to remedy the dataset shift problem. Compared with the benchmark models, MICE-DA exhibits superior predictive performance in deriving the spatiotemporal distributions of hourly PM2.5 in the megacity (Chengdu) at the foot of the Tibetan Plateau, especially for correcting the estimation bias, with the mean bias decreasing from –3.4 µg/m3 to –1.6 µg/m3. As a complement to the holdout validation, the semi-variance results show that MICE-DA decently preserves the spatial autocorrelation pattern of PM2.5 over the study area. The essence of MICE-DA is strengthening the correlation between PM2.5 and aerosol optical depth (AOD) during the data augmentation. Consequently, the importance of AOD is largely enhanced for predicting PM2.5, and the summed relative importance value of the two satellite-retrieved AOD variables increases from 5.5% to 18.4%. This study resolved the puzzle that AOD exhibited relatively lower importance in local or regional studies. The results of this study can advance the utilization of satellite remote sensing in modeling air quality while drawing more attention to the common dataset shift problem in data-driven environmental research.  相似文献   

19.
The rapid growth of Riyadh—capital of Saudi Arabia—is pushing the area to more pollution and incentive for reorganization. The aim of this research is to assess air pollutants in southeast of Riyadh and detect opinion of the population about their environment. The assessment was done by analyzing 405 questionnaires, evaluating thermal band of Landsat 8, and spatial analyzing of particular matter and chemicals in 19 air samples by geostatistical tool in the ArcMap. Most of the inhabitants stated that they are suffering from bad odor, sewage leakage, and dust mainly from a cement factory. The thermal band of Landsat clarified the location of the pollution sources mainly the 1st industrial city, Yammama Cement Factory, and power plant in Farouq area. The ordinary kriging maps showed that the highest concentration of PM10 (>403 μg/m3) lied to the northern and western side of the study area and caused a health issue to most inhabitants.  相似文献   

20.
Ambient air and coarse, fine and particulate-bound mercury (Hg(p)) pollutants were collected and analyzed from March 17 to May 22 and September 3, 2009 to March 5, 2010 at a highway traffic site located in Sha-Lu, central Taiwan. This study has the following objectives: (1) to measure the coarse and fine particulates concentrations and the particulate-bound mercury Hg(p) which was attached to these particulate; (2) to determine the average Hg(p) compositions in coarse and fine particulates and (3) to compare the Hg(p) concentrations and compositions particulate in this study to the those obtained in other studies. The results obtained in this study indicated that the average ambient air PM2.5, PM2.5–10 and PM10 were 18.79 ± 6.71, 11.22 ± 4.93 and 30.01 ± 10.27 μg/m3, respectively. The ranges of concentrations for Hg(p) in PM2.5 were from 0.0016 to 0.0557 ng/m3, from 0.0006 to 0.0364 ng/m3 in PM2.5–10 and from 0.0022 to 0.0862 ng/m3 in PM10. In addition, the highest particle-bound mercury compositions in PM2.5 were 16.85 ng/g and the lowest particle-bound mercury concentrations were 0.55 ng/g. The highest particle-bound mercury compositions in PM2.5–10 were 13.88 ng/g and the lowest particle-bound mercury in PM2.5–10 were 0.22 ng/g.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号