Temporal variations and spatial distribution of ambient PM2.2 and PM10 concentrations in Dhaka, Bangladesh

Concentrations and characteristics of airborne particulate matter (PM(10), PM(2.2) and BC) on air quality have been studied at two air quality-monitoring stations in Dhaka, the capital of Bangladesh. One site is at the Farm Gate area, a hot spot with very high pollutant concentrations because of its proximity to major roadways. The other site is at a semi-residential area located at the Atomic Energy Centre, Dhaka Campus, (AECD) with relatively less traffic. The samples were collected using a 'Gent' stacked filter unit in two fractions of 0-2.2 mum and 2.2-10 mum sizes. Samples of fine (PM(2.2)) and coarse (PM(2.2-10)) airborne particulate matter fractions collected from 2000 to 2003 were studied. It has been observed that fine particulate matter has a decreasing trend, from prior year measurements, because of Government policy interventions like phase-wise plans to take two-stroke three-wheelers off the roads in Dhaka and finally banned from January 1, 2003. Other policy interventions were banning of old buses and trucks to ply on Dhaka city promotion of the using compressed natural gas (CNG), introducing air pollution control devices in vehicles, etc. It was found that both local (mostly from vehicular emissions) and possibly some regional emission sources are responsible for high PM(2.2) and BC concentrations in Dhaka. PM(2.2), PM(2.2-10) and black carbon concentration levels depend on the season, wind direction and wind speed. Transport related emissions are the major source of BC and long-range transportation from fossil fuel related sources and biomass burning could be another substantial source of BC.     

Chemometrics in monitoring spatial and temporal variations in drinking water quality

This case study reports multivariate techniques applied for the evaluation of temporal/spatial variations and interpretation of monitoring data obtained by the determination of chloro/bromo disinfection by-products in drinking water at 12 locations in the Gdańsk area (Poland), over the period 1993-2000. The complex data matrix (1756 observations) was treated with various multivariate techniques. Cluster analysis (CA) was successful, yielding two different groups of similarity reflecting different types of drinking water supplied (surface and groundwater). The locations supplied in general with groundwater could be further classified into two subgroups, depending on whether the groundwater was mixed with surface water or not. Analysis of variance (ANOVA) was used to classify and thus confirm the groups found by means of cluster analysis and proved the existence of statistically significant differences between the concentration levels of CHCl3, CHBrCl2+C2HCl3, CHBr2Cl, and CH2Cl2 in the samples collected. Of all the variables evaluated, only three were characterized by statistically significant correlations (CHCl3, CHBrCl2+C2HCl3, CHBr2Cl). The analysis of correlation coefficients revealed that chloroform formed as the main chlorinated disinfection by-product and, furthermore, the natural presence of bromide in water (both ground and surface) results in the formation of brominated disinfection by-products (DBPs). Temporal variations of volatile organic chlorinated compounds (VOCls) were also evaluated by multidimensional ANOVA. Observation of temporal changes in the concentration of VOCls at the location supplied with both surface and groundwater reveals a steady improvement in drinking water quality. In general, the study shows the importance of drinking water monitoring in connection with simple but powerful statistical tools to better understand spatial and temporal variations in water quality.     

The PM2.5 and PM10 particles in urban areas of Taiwan

This study conducted an atmospheric aerosol sampling to measure the PM10 (particles < 10 microns in aerodynamic diameter) and PM2.5 (particles < 2.5 microns in aerodynamic diameter) mass concentrations from October 1996 to June 1997 in northern (Taipei), central (Taichung) and southern (Kaohsiung), the three largest cities of Taiwan. Seventy-eight samples were obtained to measure the mass concentrations of PM10 and PM2.5 from nine sampling sites. According to those results, the PM10 mass concentrations in Taipei, Taichung and Kaohsiung were 42.19, 60.99 and 77.10 micrograms/m3, respectively. The corresponding PM2.5 mass concentrations were 23.09, 39.97 and 48.47 micrograms/m3, respectively. The PM2.5 fraction accounted for 61-67% of the PM10 mass in central and southern Taiwan, but was lower (54-59%) in northern Taiwan. Some samples in which the PM2.5 fraction was overwhelmingly dominant could reach as high as 80-95% of the PM10 mass. In addition, the PM2.5, PM10 levels and PM2.5/PM10-2.5 (particles with aerodynamic diameters ranging from 2.5 to 10 microns) ratios in metropolitan Taiwan significantly fluctuated from site-to-site and over time. Moreover, ambient daily PM2.5 and PM10-2.5 mass concentrations did not correlate well with each other at most of the sampling sites, indicated that they originated from different kinds of sources and emitted variedly over time.     

Monitoring the temporal variations of PM2.5 and gases close to the highway in Sohar,Oman

The aim of this study was to identify the relationship between the concentrations of PM_2.5 (particulate matter less than 2.5 μm) and the temporal variation of the monitored gases at Sohar highway, Oman, from November 2014 to February 2015. The hourly concentrations of surface ozone (O₃), nitric dioxide (NO₂) and sulphur dioxide (SO₂) were measured by an open-path differential optical absorption spectroscopy instrument installed across Sohar highway. Additionally, the same gases and the meteorological parameters were measured in the same location of the PM_2.5 analyser. The findings of this study show that on the hourly time scale, PM_2.5 and O₃ were very weakly and negatively correlated. In contrast, on the daily time scale, PM_2.5 and O₃ were positively rather weakly correlated. Stronger correlation coefficient was found between 24 h averages of PM_2.5 and daily maximum O₃ concentrations. A policy implication of these findings could be that reducing the emissions of O₃ precursors reduces the levels of PM_2.5 as well.     

Organic compounds of PM2.5 in Mexico Valley: spatial and temporal patterns, behavior and sources

A longitudinal study on spatial and temporal behavior of particles less than 2.5 μm (PM_2.5), solvent extracted organic matter (SEOM), polycyclic aromatic hydrocarbons (PAH), n-alkanes and nitro-PAH was carried out for a full year in 2006, at five sites simultaneously around the Metropolitan Zone of Mexico Valley (MZMV). There is rather uniform distribution of PM_2.5 and SEOM in the MZMV regarding gravimetric mass concentration, while some specific organic chemical components showed mass heterogeneity. The highest mass concentrations of target compounds occurred in the dry seasons with respect to the rainy season. Bonfires and fireworks are probably responsible for extreme values of PM_2.5, SEOM and PAH (≥ 228 g mol^− 1). Benzo[ghi]perylene was the most abundant PAH, with C₂₄-C₂₆ the most abundant n-alkanes and 2-nitrofluoranthene and 9-nitroanthracene the most abundant nitro-PAH. The northeast zone was the area with the greatest presence of sources of incomplete diesel combustion, while the central for gasoline combustion. In the southwest, the biogenic sources were more abundant over the anthropogenic sources. This was opposite to the other sites. Factor analysis allowed us to relate different compounds to emitting sources. Three main factors were associated with combustion, pyrolysis and biogenic primary sources while the other factors were associated with secondary organic aerosol formation and industry. Correlation analyses indicated that SEOM originates from different primary emission sources or is formed by different processes than the other variables, except in southwest. Associations among variables suggest that PM_2.5 in the northwest and in the southeast originated mainly from primary emissions or consisted of primary organic compounds. PM_2.5 in the northeast, central and southwest contains a greater proportion of secondary organic compounds, with the less oxidized organic aerosols in the northeast and the most aged organic aerosol in the southwest. This follows the trends in the prevailing wind directions in MZMV during 2006.     

The smart city and its publics: insights from across six UK cities

In response to policy-makers’ increasing claims to prioritise ‘people’ in smart city development, we explore the publicness of emerging practices across six UK cities: Bristol, Glasgow, London, Manchester, Milton Keynes, and Peterborough. Local smart city programmes are analysed as techno-public assemblages invoking variegated modalities of publicness. Our findings challenge the dystopian speculative critiques of the smart city, while nevertheless indicating the dominance of ‘entrepreneurial’ and ‘service user’ modes of the public. We highlight the risk of bifurcation within smart city assemblages, such that the ‘civic’ and ‘political’ roles of the public become siloed into less obdurate strands of programmatic activity.     

Characterisation and quantification of the sources of PM10 during air pollution episodes in the UK

Data for concentrations of PM(10) and gaseous pollutants from sites in the UK Automatic Urban and Rural Network have been examined during periods of elevated concentrations of PM(10). The ratios of concentrations of PM(10) to those of the other pollutants were used to determine the most probable source of the additional particles. The hypothesis is that because the concentrations of PM(10) were divided by those of the other pollutants, the ratio should decrease when PM(10) and the other pollutants have a common source. Conversely, the ratio should increase when the sources are different. During episodes where road traffic was the most probable source of the additional particles, the ratios of concentrations of PM(10) to carbon monoxide and oxides of nitrogen did decrease, but the comparable ratios for sulphur dioxide and ozone increased. In contrast, during episodes known to have been caused by construction activity, all these ratios increased. This is taken to show that the basic hypothesis is valid. For prolonged episodes, it was possible to use data averaged over the total duration of the episode for the purposes of source identification. For sporadic construction, or other short-duration episodes, it was necessary to use time series data. The data have also been used to calculate the differences between hourly average concentrations of pollutants measured during episodes and long-term hourly average concentrations. These have been used to model the additional PM(10) during air pollution episodes associated with construction activities and road traffic emissions. This confirms the lack of relationship between PM(10) and other pollutants during construction works. During episodes arising from road traffic emissions, there was good agreement between measured and modelled additional concentrations of PM(10) when an appropriate factor, F, related to the contribution of road traffic emissions to PM(10) at different site types was applied. The values used were 0.2 (Suburban), 0.3 (Urban Background/Urban Centre), and 0.5 (Roadside), representing 20%, 30%, and 50% contributions from road traffic, respectively.     

The magnetic properties of particles deposited on Platanus x hispanica leaves in Madrid, Spain, and their temporal and spatial variations

Magnetic phases are a common component of atmospheric particles and as such are being increasingly exploited in air quality studies. In this context the magnetic properties of Platanus x hispanica leaves were determined during the spring and summer months of 2001 and 2004 in Madrid, Spain. The leaves exhibited a stable magnetic signal carried by partially oxidized magnetite grains. Most or all of the material resided on the leaf surfaces as a net result of accumulation with time and removal through precipitation. Concentration and grain-size trends indicated that roads act as the source of the magnetic signal. The relationships between IRM(1T) (magnetic concentration) and the concentration of NO(x) and PM(10) showed that the magnetic signal is specific to traffic-related emissions and not to total particle mass. City-wide maps of magnetic concentration were produced which describe the medium-term net accumulation of traffic-related particles. They showed the same pattern of concentration lows and highs in both years, with lower concentrations in 2004. Consistently high values were observed in south-central Madrid, in an area of high traffic activity. The effects of precipitation make establishing quantitative relationships between magnetic concentration and air quality parameters difficult when using tree leaves as a passive sampling system. However, a qualitative relationship is maintained which permits the mapping and identification of persistent features of particle accumulation.     

Intraurban variations of PM10 air pollution in Christchurch, New Zealand: implications for epidemiological studies

Epidemiological studies relating air pollution to health effects often utilise one or few central monitoring sites for estimating wider population exposures to outdoor particulate air pollution. These studies often assume that highly correlated particulate concentrations between intraurban sites equate to a uniform concentration field. Several recent studies have questioned the universal validity of this assumption, noting that in some cities, the uniformity assumption may lead to exposure misclassification in health studies. Few studies have compared central fixed site concentrations to intraurban population background sites using actual monitored data in cities with higher levels of pollution. This research examines daily concentration variations in particulate matter less than 10 microm in diameter (PM10) at the neighbourhood scale over two winter months in Christchurch, New Zealand, a city with high winter pollution concentrations. Daily concentrations of PM10 data were collected for two winter months at ten background monitoring sites within 9.3 km of the central fixed monitoring site typically used for estimating exposure in epidemiological studies. Results indicate that while the correlation between PM10 concentrations measured at the central monitoring site and most background sites is strong (r>0.76), absolute daily concentration differences between the central monitoring site and population background sites were substantial (mean 90th percentile absolute difference=17.6 microg m-3). In Christchurch, a central monitoring site does not therefore appear to accurately depict wider area population exposures to PM10. Local intraurban variations in particulates should be well understood before applying central monitoring site concentrations as proxies for population exposure in epidemiological studies.     

Source apportionment of PM(10) and PM(2.5) using positive matrix factorization and chemical mass balance in Izmir, Turkey

Atmospheric particulate matter (PM) fractions (PM(10) and PM(2.5)) were sampled concurrently between June 2004 and May 2005 at two sites (urban and suburban) in Izmir, Turkey. The elemental composition of PM (Al, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, V, and Zn) was determined using inductively coupled plasma-optical emission spectrometer. Elemental compositions of several PM sources were also characterized. Positive matrix factorization (PMF) and chemical mass balance modeling (CMB) were applied to determine the PM sources and their contributions to air concentrations. The major contributors to PM were fossil fuel burning, traffic emissions, mineral industries and marine salt according to the PMF results. However, undetermined parts were more than 40%. On the other hand, the contributions to PM could be determined completely by CMB, and the dominant contributor was traffic with >70% at the two sites. Fossil fuel burning, mineral industries, marine salt and natural gas-fired power plant were the minor contributors.     

The cytotoxicities induced by PM 10 and particle-bound water-soluble species

A 1-year field sampling of PM(10) was performed at a town that usually has the worst air quality in Taiwan to examine if PM(10) is a good indicator for pollutant-induced cytotoxicity. The average PM(10) concentration in summer was the lowest, while the other three seasons did not show statistical difference in their PM(10) means. The pollutant-induced cytotoxicity presented as the cumene-hydroperoxide equivalent concentration (CEC) was found to positively correlate with PM(10) concentrations and this study yielded a yearly average of the seasonal CEC 12.+/-8.54 microM with the magnitudes in sequence for the four seasons as: fall>winter>spring>summer. Positive relationship was also found between seasonal PM(10) and their corresponding CECs. The exponential regression model obtained from this study shows: CEC=3.305 exp(0.0118 PM(10)) (R(2)=0.634). The CEC correlates more significantly with NO(3)(-), SO(4)(2-), NH(4)(+) and Cl(-) (secondary aerosol species) than with the Na(+), K(+), Ca(2+) and Mg(2+) (crust-related species) in PM(10). However, the best multivariable model obtained from this study to relate CEC with the concentrations of PM(10)-bearing water-soluble species shows: CEC=exp(1.4751+0.0470[SO(4)(2-)]+0.0143[NO(3)(-)]) (R(2)=0.550).     

Chemical composition of PM2.5 and PM10 in Mexico City during winter 1997

PM2.5 and PM10 were measured over 24-h intervals at six core sites and at 25 satellite sites in and around Mexico City from 23 February to 22 March 1997. In addition, four 6-h samples were taken each day at three of the core sites. Sampling locations were selected to represent regional, central city, commercial, residential, and industrial portions of the city. Mass and light transmission concentrations were determined on all of the samples, while elements, ions and carbon were measured on approximately two-thirds of the samples. PM10 concentrations were highly variable, with almost three-fold differences between the highest and lowest concentrations. Fugitive dust was the major cause of PM10 differences, although carbon concentrations were also highly variable among the sampling sites. Approximately 50% of PM10 was in the PM2.5 fraction. The majority of PM mass was comprised of carbon, sulfate, nitrate, ammonium and crustal components, but in different proportions on different days and at different sites. The largest fine-particle components were carbonaceous aerosols, constituting approximately 50% of PM2.5 mass, followed by approximately 30% secondary inorganic aerosols and approximately 15% geological material. Geological material is the largest component of PM10, constituting approximately 50% of PM10 mass, followed by approximately 32% carbonaceous aerosols and approximately 17% secondary inorganic aerosols. Sulfate concentrations were twice as high as nitrate concentrations. Sulfate and nitrate were present as ammonium sulfate and ammonium nitrate. Approximately two-thirds of the ammonium sulfate measured in urban areas appears to have been transported from regions outside of the study domain, rather than formed from emissions in the urban area. Diurnal variations are apparent, with two-fold increases in concentration from night-time to daytime. Morning samples had the highest PM2.5 and PM10 mass, secondary inorganic aerosols and carbon concentrations, probably due to a shallow surface inversion and rush-hour traffic.     

地铁车站PM2.5和PM10颗粒物浓度实测及分析

为了进一步了解地铁车站内环境中的颗粒物浓度分布情况,在2015年11月对上海市A、B两个地铁车站进行了实地监测,分析了PM2.5和PM10颗粒物浓度在一天中的变化规律及其影响因素.测试结果显示站厅公共区,站台公共区与轨行区的PM2.5浓度在监测时段内逐时变化规律相似.站厅公共区,站台公共区PM10与PM2.5在监测时段...     

Hospital indoor PM10/PM2.5 and associated trace elements in Guangzhou, China

PM10 and PM2.5 samples were collected in the indoor environments of four hospitals and their adjacent outdoor environments in Guangzhou, China during the summertime. The concentrations of 18 target elements in particles were also quantified. The results showed that indoor PM2.5 levels with an average of 99 microg m(-3) were significantly higher than outdoor PM2.5 standard of 65 microg m(-3) recommended by USEPA [United States Environmental Protection Agency. Office of Air and Radiation, Office of Air Quality Planning and Standards, Fact Sheet. EPA's Revised Particulate Matter Standards, 17, July 1997] and PM2.5 constituted a large fraction of indoor respirable particles (PM10) by an average of 78% in four hospitals. High correlation between PM2.5 and PM10 (R(2) of 0.87 for indoors and 0.90 for outdoors) suggested that PM2.5 and PM10 came from similar particulate emission sources. The indoor particulate levels were correlated with the corresponding outdoors (R(2) of 0.78 for PM2.5 and 0.67 for PM10), demonstrating that outdoor infiltration could lead to direct transportation into indoors. In addition to outdoor infiltration, human activities and ventilation types could also influence indoor particulate levels in four hospitals. Total target elements accounted for 3.18-5.56% of PM2.5 and 4.38-9.20% of PM10 by mass, respectively. Na, Al, Ca, Fe, Mg, Mn and Ti were found in the coarse particles, while K, V, Cr, Ni, Cu, Zn, Cd, Sn, Pb, As and Se existed more in the fine particles. The average indoor concentrations of total elements were lower than those measured outdoors, suggesting that indoor elements originated mainly from outdoor emission sources. Enrichment factors (EF) for trace element were calculated to show that elements of anthropogenic origins (Zn, Pb, As, Se, V, Ni, Cu and Cd) were highly enriched with respect to crustal composition (Al, Fe, Ca, Ti and Mn). Factor analysis was used to identify possible pollution source-types, namely street dust, road traffic and combustion processes.     

Approaching PM(2.5) and PM(2.5-10) source apportionment by mass balance analysis, principal component analysis and particle size distribution

A chemical characterization was carried out for PM(2.5) and PM(2.5-10) samples collected in a suburban area and the concentrations of 12 elements were determined in 8 size segregated fractions using a Berner Impactor. Two main objectives were proposed in this work: 1) to test for closure among chemical and gravimetric measurements of PM(2.5) and PM(2.5-10) and 2) evaluate the performance of Multilinear Regression Analysis (MLRA) and Mass Balance Analysis (MBA) in the determination of source contribution to Particulate Matter (PM) concentrations. The fraction unaccounted for by chemical analysis comprised on average 17% and 34% of gravimetric PM(2.5) and PM(2.5-10), respectively. The lack of closure in PM(2.5) and PM(2.5-10) mass (i.e., constituent concentrations not adding up to gravimetrically measured) could partly result from the presence of water associated with particles and errors in the estimation of unmeasured species. MLRA and MBA showed very similar results for the temporal variation of the source contributions. However, quantitatively important discrepancies could be observed, principally due to the lack of mass closure in PM(2.5) and PM(2.5-10). Both methods indicated that the major PM(2.5) aerosol mass contributors included secondary aerosol and vehicle exhaust. In the coarse fraction, marine and mineral aerosol contributions were predominant.     

可吸入颗粒物特性对大学校园规划的影响

通过对可吸入颗粒物PM10的来源及危害性的介绍，以及对太原市某大学新建校区颗粒物的实地采样和分析，说明此校区颗粒物污染程度的严重性，并从校区规划的角度初步探讨了如何控制可吸入颗粒物，并提出了相关建议。     

PM2.5 chemical composition in Hong Kong: urban and regional variations

Chemically speciated PM2.5 measurements were made at roadside, urban, and rural background sites in Hong Kong for 1 year during 2000/2001 to determine the spatial and temporal variations of PM2.5 mass and chemical composition in this highly populated region. Annual average PM2.5 concentrations at the urban and rural sites were 34.1 and 23.7 microg m(-3), respectively, approximately 50-100% higher than the United States' annual average National Ambient Air Quality Standard (NAAQS) of 15 microg m(-3). Daily PM2.5 concentrations exceeded the U.S. 24-h NAAQS of 65 microg m(-3) on 19 days, reaching 131+/-8 microg m(-3) at the roadside site on 02/28/2001. Carbonaceous aerosol is the largest contributor to PM2.5 mass (explaining 52-75% of PM2.5 mass at the two urban sites and 32% at the background site), followed by ammonium sulfate (ranging from 23% to 37% at the two urban sites and 51% at the background site). Ammonium sulfate and crustal concentrations showed more uniform spatial distributions, while the largest urban-rural contrasts found in carbonaceous aerosol (likely due to emissions from on-road gasoline and diesel vehicles). Marine influences accounted for 7% of the mass at the background site (more than twice as much as at the two urban sites). Ternary diagrams are utilized to illustrate the different spatial patterns.     

不同建筑环境空气中颗粒物PM1.0、PM2.5和PM10的污染水平及对比研究

为了解人们常停留的建筑室内空气中不同粒径段颗粒物的污染水平,本文对写字楼、地铁站台、餐饮环境、大学教室和宿舍等不同类型建筑室内和室外空气中的颗粒物PM10、PM2.5和PM10的质量浓度水平进行了测试、统计分析和对比研究,同时对不同建筑环境内不同粒径段颗粒物的浓度大小、占比情况和主要来源进行了分析探讨.结果 表明:1)...     

Source apportionment of PM10 and PM2.5 in Milan (Italy) using receptor modelling

In this paper a source apportionment of particulate matter pollution in the urban area of Milan (Italy) is given. Results of PM10 and PM2.5 mass and elemental concentrations from a 1-year monitoring campaign are presented. Mean annual and daily PM10 levels are compared with the limits of the EU Air Quality Directive EC/30/1999 and the results show that the limit values established would not be met in the urban area of Milan or the large surrounding area. Moreover, high levels of PM2.5 are registered and this fraction constitutes a high portion of the PM10 mass. In Milan the winter period is characterised by a high degree of air pollution due to a greater contribution of emissions and to adverse meteorological and thermodynamic conditions of the atmosphere. The application of multivariate techniques and receptor modelling (PCFA, APCFA) to the whole data-set led to the identification of the main emitting sources and to the source apportionment of PM10 and PM2.5 in Milan. The most important sources were identified as 'soil dust', 'traffic', 'industry' and 'secondary compounds' for PM10 and as 'soil dust', 'anthropogenic' and 'secondary compounds' for PM2.5, explaining the greatest part of the total variance (91% and 75%, respectively).     

The characteristic study of TSP, PM2.5-10 and PM2.5 in the rural site of central Taiwan.

The total suspended particle (TSP), PM2.5-10 (aerodynamic diameter less than 10 microns) and PM2.5 concentration (aerodynamic diameter less than 2.5 microns) concentrations were sampled by PS-1 and Universal sampler on the roof (25 m) of the Medical and Engineering Building in the campus of Hungkuang Institute of Technology (HKIT) which is located at a height of 500 m on Da Du Mountain. The results indicated that average TSP, PM2.5-10 and PM2.5 concentrations are 0.42, 0.34 and 0.019 mg/m3 in the day time, respectively and are 0.32, 0.26 and 0.017 mg/m3 in the night time, respectively. The ratios of PM2.5-10/TSP were from 76% to 85% and from 50% to 91% for day and night period, respectively. It indicated that the major composition in the total suspended particles was PM2.5-10 in the rural site. The relationship between TSP and PM2.5-10 is TSP = 1.16PM2.5-10 + 0.027 and TSP = 1.01 PM2.5-10 + 0.058 in the day and night time, respectively. The correlation coefficient (R2) is 0.98 and 0.97 for day and night period, respectively. The relationship between PM2.5-10 and PM2.5 is PM2.5 = 0.0005PM2.5-10 + 0.019 and PM2.5 = 0.037PM2.5-10 + 0.0076 in the day and night period, respectively. The correlation coefficient (R2) is 3E-5 and 0.67 for day and night period, respectively. The relationships between TSP, PM2.5-10, PM2.5 particle concentrations and wind speed (R2) in the day time are 0.71, 0.64, 0.43, respectively and are 0.83, 0.79, 0.57, respectively in the night time. The proposed reasons are that there are more activities caused by people (students) and natural living animals which absorbed some of the particles during the day time. Thus, the correlation coefficients for the night time are better than those of day time. The particle size distributions are both bimodel in the day and night time. The major peaks in the day time appear in the particle diameter between 0.031-0.056 micron and 3.16-5.62 microns in the day period and appear between 0.017-0.031 micron and 1.78-3.16 microns in the night period. The results indicate that the particle size distribution in the day time tends to be of larger particle size mode than the night time.