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1.
Personal exposure to particulate matter of aerodynamic diameter under 2.5 μm (PM2.5) was monitored using a DustTrak nephelometer. The battery-operated unit, worn by an adult individual for a period of approximately one year, logged integrated average PM2.5 concentrations over 5 min intervals. A detailed time-activity diary was used to record the experimental subject’s movement and the microenvironments visited. Altogether 239 days covering all the months (except April) were available for the analysis. In total, 60 463 acceptable 5-min averages were obtained. The dataset was divided into 7 indoor and 4 outdoor microenvironments. Of the total time, 84% was spent indoors, 10.9% outdoors and 5.1% in transport. The indoor 5-min PM2.5 average was higher (55.7 μg m?3) than the outdoor value (49.8 μg m?3). The highest 5-min PM2.5 average concentration was detected in restaurant microenvironments (1103 μg m?3), the second highest 5-min average concentration was recorded in indoor spaces heated by stoves burning solid fuels (420 μg m?3). The lowest 5-min mean aerosol concentrations were detected outdoors in rural/natural environments (25 μg m?3) and indoors at the monitored person’s home (36 μg m?3). Outdoor and indoor concentrations of PM2.5 measured by the nephelometer at home and during movement in the vicinity of the experimental subject’s home were compared with those of the nearest fixed-site monitor of the national air quality monitoring network. The high correlation coefficient (0.78) between the personal and fixed-site monitor aerosol concentrations suggested that fixed-site monitor data can be used as proxies for personal exposure in residential and some other microenvironments. Collocated measurements with a reference method (β-attenuation) showed a non-linear systematic bias of the light-scattering method, limiting the use of direct concentration readings for exact exposure analysis.  相似文献   

2.
In developed nations people spend about 90% of their time indoors. The relationship between indoor and outdoor air pollution levels is important for the understanding of the health effects of outdoor air pollution. Although other studies describe both the outdoor and indoor atmospheric environment, few excluded a priori major indoor sources, measured the air exchange rate, included more than one micro-environment and included the presence of human activity. PM2.5, soot, NO2 and the air exchange rate were measured during winter and summer indoors and outdoors at 18 homes (mostly apartments) of 18 children (6–11-years-old) and also at the six schools and 10 pre-schools that the children attended. The three types of indoor environments were free of environmental tobacco smoke and gas appliances, as the aim was to asses to what extent PM2.5, soot and NO2 infiltrate from outdoors to indoors. The median indoor and outdoor PM2.5 levels were 8.4 μg m?3 and 9.3 μg m?3, respectively. The median indoor levels for soot and NO2 were 0.66 m?1 × 10?5 and 10.0 μg m?3, respectively. The respective outdoor levels were 0.96 m?1 × 10?5 and 12.4 μg m?3. The median indoor/outdoor (I/O) ratios were 0.93, 0.76 and 0.92 for PM2.5, soot and NO2, respectively. Their infiltration factors were influenced by the micro-environment, ventilation type and air exchange rate, with aggregated values of 0.25, 0.55 and 0.64, respectively. Indoor and outdoor NO2 levels were strongly associated (R2 = 0.71), followed by soot (R2 = 0.50) and PM2.5 (R2 = 0.16). In Stockholm, the three major indoor environments occupied by children offer little protection against combustion-related particles and gases in the outdoor air. Outdoor PM2.5 seems to infiltrate less, but indoor sources compensate.  相似文献   

3.
Particulate pollution has been clearly linked with adverse health impacts from open fire cookstoves, and indoor air concentrations are frequently used as a proxy for exposures in health studies. Implicit are the assumptions that the size distributions for the open fire and improved stove are not significantly different, and that the relationship between indoor concentrations and personal exposures is the same between stoves. To evaluate the impact of these assumptions size distributions of particulate matter in indoor air were measured with the Sioutas cascade impactor in homes using open fires and improved Patsari stoves in a rural Purepecha community in Michoacan, Mexico. On average indoor concentrations of particles less than 0.25 μm were 72% reduced in homes with improved Patsari stoves, reflecting a reduced contribution of this size fraction to PM2.5 mass concentrations from 68% to 48%. As a result the mass median diameter of indoor PM2.5 particulate matter was increased by 29% with the Patsari improved stove compared to the open fire (from 0.42 μm to 0.59 μm, respectively). Personal PM2.5 exposure concentrations for women in homes using open fires were approximately 61% of indoor concentration levels (156 μg m?3 and 257 μg m?3 respectively). In contrast personal exposure concentrations were 77% times indoor air concentration levels for women in homes using improved Patsari stoves (78 μg m?3and 101 μg m?3 respectively). Thus, if indoor air concentrations are used in health and epidemiologic studies significant bias may result if the shift in size distribution and the change in relationship between indoor air concentrations and personal exposure concentrations are not accounted for between different stove types.  相似文献   

4.
Thoracic (PM10), fine thoracic (PM2.5) and sub-micrometer (PM1) airborne particulate matter was sampled during day and night. In total, about 100 indoor and outdoor samples were collected for each fraction at ten different office environments. Energy-dispersive X-ray fluorescence spectrometry and ion chromatography were applied for the quantification of some major and minor elements and ions in the collected aerosols. During daytime, mass concentrations were in the ranges: 11–29, 8.1–24, and 6.6–18 μg m?3, with averages of 20 ± 1, 15.0 ± 0.9, and 11.0 ± 0.8 μg m?3, respectively. At night, mass concentrations were found to be significantly lower for all fractions. Indoor PM1 concentrations exceeded the corresponding outdoor levels during office hours and were thought to be elevated by office printers. Particles with diameters between 1 and 2.5 μm and 2.5 and 10 μm were mainly associated with soil dust elements and were clearly subjected to distinct periods of settling/resuspension. Indoor NO3? levels were found to follow specific microclimatic conditions at the office environments, while daytime levels of sub-micrometer Cl? were possibly elevated by the use of Cl-containing cleaning products. Indoor carbon black concentrations were sometimes as high as 22 μg m?3 and were strongly correlated with outdoor traffic conditions.  相似文献   

5.
Indoor and outdoor particulate matter (PM0.3-10) number concentrations were established in two medieval churches in Cyprus. In both churches incense was burnt occasionally during Mass. The highest indoor PM0.5-1 concentrations compared with outdoors (10.7 times higher) were observed in the church that burning of candles indoors was allowed. Peak indoor black carbon concentration was 6.8 μg m−3 in the instances that incense was burning and 13.4 μg m−3 in the instances that the candles were burning (outdoor levels ranged between 0.6 and 1.3 μg m−3). From the water soluble inorganic components determined in PM10, calcium prevailed in all samples indoors or outdoors, whilst high potassium concentration indoors were a clear marker of combustion. Indoor sources of PM were clearly identified and their emission strengths were estimated via modeling of the results. Indoor estimated PM0.3-10 mass concentrations exceeded air quality standards for human health protection and for the preservation of works of art.  相似文献   

6.
Measurements carried out in Paris Magenta railway station in April–May 2006 underlined a repeatable diurnal cycle of aerosol concentrations and optical properties. The average daytime PM10 and PM2.5 concentrations in such a confined space were approximately 5–30 times higher than those measured in Paris streets. Particles are mainly constituted of dust, with high concentrations of iron and other metals, but are also composed of black and organic carbon. Aerosol levels are linked to the rate at which rain and people pass through the station. Concentrations are also influenced by ambient air from the nearby streets through tunnel ventilation. During daytime approximately 70% of aerosol mass concentrations are governed by coarse absorbing particles with a low Angström exponent (~0.8) and a low single-scattering albedo (~0.7). The corresponding aerosol density is about 2 g cm?3 and their complex refractive index at 355 nm is close to 1.56–0.035 i. The high absorption properties are linked to the significant proportion of iron oxides together with black carbon in braking systems. During the night, particles are mostly submicronic, thus presenting a greater Angström exponent (~2). The aerosol density is lower (1.8 g cm?3) and their complex refractive index presents a lower imaginary part (1.58–0.013 i), associated to a stronger single-scattering albedo (~0.85–0.90), mostly influenced by the ambient air. For the first time we have assessed the emission (deposition) rates in an underground station for PM10, PM2.5 and black carbon concentrations to be 3314 ± 781(?1164 ± 160), 1186 ± 358(?401 ± 66) and 167 ± 46(?25 ± 9) μg m?2 h?1, respectively.  相似文献   

7.
This paper presents results from an in-vehicle air quality study of public transit buses in Toledo, Ohio, involving continuous monitoring, and experimental and statistical analyses to understand in-vehicle particulate matter (PM) behavior inside buses operating on B20-grade biodiesel fuel. The study also focused on evaluating the effects of vehicle’s fuel type, operating periods, operation status, passenger counts, traffic conditions, and the seasonal and meteorological variation on particulates with aerodynamic diameter less than 1 micron (PM1.0). The study found that the average PM1.0 mass concentrations in B20-grade biodiesel-fueled bus compartments were approximately 15 μg m?3, while PM2.5 and PM10 concentration averages were approximately 19 μg m?3 and 37 μg m?3, respectively. It was also observed that average hourly concentration trends of PM1.0 and PM2.5 followed a “μ-shaped” pattern during transit hours.Experimental analyses revealed that the in-vehicle PM1.0 mass concentrations were higher inside diesel-fueled buses (10.0–71.0 μg m?3 with a mean of 31.8 μg m?3) as compared to biodiesel buses (3.3–33.5 μg m?3 with a mean of 15.3 μg m?3) when the windows were kept open. Vehicle idling conditions and open door status were found to facilitate smaller particle concentrations inside the cabin, while closed door facilitated larger particle concentrations suggesting that smaller particles were originating outside the vehicle and larger particles were formed within the cabin, potentially from passenger activity. The study also found that PM1.0 mass concentrations at the back of bus compartment (5.7–39.1 μg m?3 with a mean of 28.3 μg m?3) were higher than the concentrations in the front (5.7–25.9 μg m?3 with a mean of 21.9 μg m?3), and the mass concentrations inside the bus compartment were generally 30–70% lower than the just-outside concentrations. Further, bus route, window position, and time of day were found to affect the in-vehicle PM concentrations significantly. Overall, the in-vehicle PM1.0 concentrations inside the buses operating on B20-grade biodiesel ranged from 0.7 μg m?3 to 243 μg m?3, with a median of 11.6 μg m?3.Statistical models developed to study the effects of vehicle operation and ambient conditions on in-vehicle PM concentrations suggested that while open door status was the most important influencing variable for finer particles and higher passenger activity resulted in higher coarse particles concentrations inside the vehicle compartments, ambient PM concentrations contributed to all PM fractions inside the bus irrespective of particle size.  相似文献   

8.
Behavioral and environmental determinants of PM2.5 personal exposures were analyzed for 201 randomly selected adult participants (25–55 years old) of the EXPOLIS study in Helsinki, Finland. Personal exposure concentrations were higher than respective residential outdoor, residential indoor and workplace indoor concentrations for both smokers and non-smokers. Mean personal exposure concentrations of active smokers (31.0±31.4 μg m−3) were almost double those of participants exposed to environmental tobacco smoke (ETS) (16.6±11.8 μg m−3) and three times those of participants not exposed to tobacco smoke (9.9±6.2 μg m−3). Mean indoor concentrations of PM2.5 when a member of the household smoked indoors (20.8±23.9 μg m−3) were approximately 2.5 times the concentrations of PM2.5 when no smoking was reported (8.2±5.2 μg m−3). Interestingly, however, both mean (8.2 μg m−3) and median (6.9 μg m−3) residential indoor concentrations for non-ETS exposed participants were lower than residential outdoor concentrations (9.5 and 7.3 μg m−3, respectively). In simple linear regression models residential indoor concentrations were the best predictors of personal exposure concentrations. Correlations (r2) between PM2.5 personal exposure concentrations of all participants, both smoking and non-smoking, and residential indoor, workplace indoor, residential outdoor and ambient fixed site concentrations were 0.53, 0.38, 0.17 and 0.16, respectively. Predictors for personal exposure concentrations of non-ETS exposed participants identified in multiple regression were residential indoor concentrations, workplace concentrations and traffic density in the nearest street from home, which accounted for 77% of the variance. Subsequently, step-wise regression not including residential and workplace indoor concentrations as input (as these are frequently not available), identified ambient PM2.5 concentration and home location, as predictors of personal exposure, accounting for 47% of the variance. Ambient fixed site PM2.5 concentrations were closely related to residential outdoor concentrations (r2=0.9, p=0.000) and PM2.5 personal exposure concentrations were higher in summer than during other seasons. Personal exposure concentrations were significantly (p=0.040) higher for individuals living downtown compared with individuals in suburban family homes. Further analysis will focus on comparisons of determinants between Helsinki and other EXPOLIS centers.  相似文献   

9.
An indoor/outdoor monitoring programme of PM10 was carried out in two sports venues (a fronton and a gymnasium). Levels always below 50 μg m?3 were obtained in the fronton and outdoor air. Due to the climbing chalk and the constant process of resuspension, concentrations above 150 μg m?3 were registered in the gymnasium. The chalk dust contributed to CO3 2? concentrations of 32?±?9.4 μg m?3 in this sports facility, which represented, on average, 18 % of the PM10 mass. Here, the carbonate levels were 128 times higher than those registered outdoors. Much lower concentrations, around 1 μg m?3, were measured in the fronton. The chalk dust is also responsible for the high Mg2+ concentrations in the gym (4.7?±?0.89 μg m?3), unfolding a PM10 mass fraction of 2.7 %. Total carbon accounted for almost 30 % of PM10 in both indoor spaces. Aerosol size distributions were bimodal and revealed a clear dependence on physical activities and characteristics of the sports facilities. The use of climbing chalk in the gymnasium contributed significantly to the coarse mode. The average geometric mean diameter, geometric standard deviation and total number of coarse particles were 0.77 μm, 2.79 cm?3 and 28 cm?3, respectively.  相似文献   

10.
Lahore, Pakistan is an emerging megacity that is heavily polluted with high levels of particle air pollution. In this study, respirable particulate matter (PM2.5 and PM10) were collected every sixth day in Lahore from 12 January 2007 to 19 January 2008. Ambient aerosol was characterized using well-established chemical methods for mass, organic carbon (OC), elemental carbon (EC), ionic species (sulfate, nitrate, chloride, ammonium, sodium, calcium, and potassium), and organic species. The annual average concentration (±one standard deviation) of PM2.5 was 194 ± 94 μg m?3 and PM10 was 336 ± 135 μg m?3. Coarse aerosol (PM10?2.5) was dominated by crustal sources like dust (74 ± 16%, annual average ± one standard deviation), whereas fine particles were dominated by carbonaceous aerosol (organic matter and elemental carbon, 61 ± 17%). Organic tracer species were used to identify sources of PM2.5 OC and chemical mass balance (CMB) modeling was used to estimate relative source contributions. On an annual basis, non-catalyzed motor vehicles accounted for more than half of primary OC (53 ± 19%). Lesser sources included biomass burning (10 ± 5%) and the combined source of diesel engines and residual fuel oil combustion (6 ± 2%). Secondary organic aerosol (SOA) was an important contributor to ambient OC, particularly during the winter when secondary processing of aerosol species during fog episodes was expected. Coal combustion alone contributed a small percentage of organic aerosol (1.9 ± 0.3%), but showed strong linear correlation with unidentified sources of OC that contributed more significantly (27 ± 16%). Brick kilns, where coal and other low quality fuels are burned together, are suggested as the most probable origins of unapportioned OC. The chemical profiling of emissions from brick kilns and other sources unique to Lahore would contribute to a better understanding of OC sources in this megacity.  相似文献   

11.
PM10 measurements were started in November 1992 at Melpitz site. The mean PM10 concentration in 1993 was 38 μg m?3 in the summer season (May until October) and about 44 μg m?3 in the winter season (November until April). The mean PM10 level decreased until 1999 and varies now in ranges from 20–34 μg m?3 to 17–24 μg m?3 (minimum and maximum mean values for 1999–2008) in winter and summer seasons, respectively. High volume filter samples of particles PM10, PM2.5 and PM1 were characterized for mass, water-soluble ions, organic and elemental carbon from 2004 until 2008. The percentage of PM2.5 in PM10 varies between summer (71.6%) and winter seasons (81.9%). Mean concentrations of PM10, PM2.5 and PM1 in Melpitz were 20, 15, and 13 μg m?3 in 2004, 22, 18, and 13 μg m?3 in 2005, 24, 19, and 12 μg m?3 in 2006 and 22, 17, and 12 μg m?3 in 2007, respectively. In the four winters the rural background concentration PM10 at Melpitz exceeded the daily 50 μg m?3 limit for Europe on 8, 8, 7 and 6 days, respectively.Findings for a simple two-sector-classification of the samples (May 2004 until April 2008) using 96-h backward trajectories for the identification of source regions are: Air masses were transported most of time (60%) from the western sector and secondly (17%) from the eastern sector. The lowest daily mean mass concentration PM10 were found during western inflow in summer (17 μg m?3) containing low amounts of sulphate (2.4 μg m?3), nitrate (1.7 μg m?3), ammonium (1.1 μg m?3) and TC (3.7 μg m?3). In opposite the highest mean mass concentration PM10 was found during eastern inflow in winter (35 μg m?3) with high amounts of sulphate (6.1 μg m?3), nitrate (5.4 μg m?3), ammonium (3.8 μg m?3) and TC (9.4 μg m?3). An estimation of secondary formed OC (SOA) shows 0.8–0.9 μg m?3 for air masses from West and 2.1–2.2 μg m?3 from East. The seasonal difference can be neglected.The half-hourly measurements of the particle mass concentration PM10 evaluated as mean daily courses using a TEOM® show low values (14–21 μg m?3) in summer and winter for air masses transported from West and the highest concentrations (31–38 μg m?3) in winter for air masses from East.The results demonstrate the influence of meteorological parameters on long-range transport, secondary particle mass formation and re-emission which modify mass concentration and composition of PM10, PM2.5 and PM1. Melpitz site is located in the East of Germany faraway from strong local anthropogenic emissions (rural background). Therefore, this site is suitable for investigation of the influence of long-range transport of air pollution in continental air masses from the East with source regions inside and outside of the European Union.  相似文献   

12.
PM2.5 (particulate matter with an aerodynamic diameter <2.5 μm) samples were collected in the indoor environments of 15 urban homes and their adjacent outdoor environments in Alexandria, Egypt, during the spring time. Indoor and outdoor carbon dioxide (CO2) levels were also measured concurrently. The results showed that indoor and outdoor PM2.5 concentrations in the 15 sites, with daily averages of 45.5 ± 11.1 and 47.3 ± 12.9 µg/m3, respectively, were significantly higher than the ambient 24-hr PM2.5 standard of 35 µg/m3 recommended by the U.S. Environmental Protection Agency (EPA). The indoor PM2.5 and CO2 levels were correlated with the corresponding outdoor levels, demonstrating that outdoor convection and infiltration could lead to direct transportation indoors. Ventilation rates were also measured in the selected residences and ranged from 1.6 to 4.5 hr?1 with median value of 3.3 hr?1. The indoor/outdoor (I/O) ratios of the monitored homes varied from 0.73 to 1.65 with average value of 0.99 ± 0.26 for PM2.5, whereas those for CO2 ranged from 1.13 to 1.66 with average value of 1.41 ± 0.15. Indoor sources and personal activities, including smoking and cooking, were found to significantly influence indoor levels.

Implications: Few studies on indoor air quality were carried out in Egypt, and the scarce data resulted from such studies do not allow accurate assessment of the current situation to take necessary preventive actions. The current research investigates indoor levels of PM2.5 and CO2 in a number of homes located in the city of Alexandria as well as the potential contribution from both indoor and outdoor sources. The study draws attention of policymakers to the importance of the establishment of national indoor air quality standards to protect human health and control air pollution in different indoor environments.  相似文献   

13.
Indoor particulate matter samples were collected in 17 homes in an urban area in Alexandria during the summer season. During air measurement in all selected homes, parallel outdoor air samples were taken in the balconies of the domestic residences. It was found that the mean indoor PM2.5 and PM10 (particulate matter with an aerodynamic diameter ≤2.5 and ≤10 μm, respectively) concentrations were 53.5 ± 15.2 and 77.2 ± 15.1 µg/m3, respectively. The corresponding mean outdoor levels were 66.2 ± 16.5 and 123.8 ± 32.1 µg/m3, respectively. PM2.5 concentrations accounted, on average, for 68.8 ± 12.8% of the total PM10 concentrations indoors, whereas PM2.5 contributed to 53.7 ± 4.9% of the total outdoor PM10 concentrations. The median indoor/outdoor mass concentration (I/O) ratios were 0.81 (range: 0.43–1.45) and 0.65 (range: 0.4–1.07) for PM2.5 and PM10, respectively. Only four homes were found with I/O ratios above 1, indicating significant contribution from indoor sources. Poor correlation was seen between the indoor PM10 and PM2.5 levels and the corresponding outdoor concentrations. PM10 levels were significantly correlated with PM2.5 loadings indoors and outdoors and this might be related to PM10 and PM2.5 originating from similar particulate matter emission sources. Smoking, cooking using gas stoves, and cleaning were the major indoor sources contributed to elevated indoor levels of PM10 and PM2.5.

Implications: The current study presents results of the first PM2.5 and PM10 study in homes located in the city of Alexandria, Egypt. Scarce data are available on indoor air quality in Egypt. Poor correlation was seen between the indoor and outdoor particulate matter concentrations. Indoor sources such as smoking, cooking, and cleaning were found to be the major contributors to elevated indoor levels of PM10 and PM2.5.  相似文献   

14.
For the first time eye safe lidar measurements were performed at 355 nm simultaneously to in situ measurements in an underground station so as to test the potential interest of active remote sensing measurements to follow the spatiotemporal evolution of aerosol content inside such a confined microenvironment. The purpose of this paper is to describe different methods enabling the conversion of lidar-derived aerosol extinction coefficient into aerosol mass concentrations (PM2.5 and PM10). A theoretical method based on a well marked linear regression between mass concentrations simulated from the size distribution and extinction coefficients retrieved from Mie calculations provides averaged mass to optics' relations over the campaign for traffic (6.47 × 105 μg m?2) or no traffic conditions (3.73 × 105 μg m?2). Two empirical methods enable to significantly reduce CPU time. The first one is based upon the knowledge of size distribution measurements and scattering coefficients from nephelometer and allows retrieving mass to optics' relations for well determined periods or particular traffic conditions, like week-ends, with a good accuracy. The second method, that is more direct, is simply based on the ratio between TEOM concentrations and extinction coefficients obtained from nephelometer. This method is easy to set up but is not suitable for nocturnal measurements where PM stabilization time is short. Lidar signals thus converted into PM concentrations from those approaches with a fine accuracy (30%) provide a spatiotemporal distribution of concentrations in the station. This highlights aerosol accumulation in one side of the station, which can be explained by air displacement from the tunnel entrance. Those results allow expecting a more general use of lidar measurement to survey indoor air quality.  相似文献   

15.
Particulate matter is an important air pollutant, especially in closed environments like underground subway stations. In this study, a total of 13 elements were determined from PM10 and PM2.5 samples collected at two subway stations (Imam Khomeini and Sadeghiye) in Tehran’s subway system. Sampling was conducted in April to August 2011 to measure PM concentrations in platform and adjacent outdoor air of the stations. In the Imam Khomeini station, the average concentrations of PM10 and PM2.5 were 94.4?±?26.3 and 52.3?±?16.5 μg m?3 in the platform and 81.8?±?22.2 and 35?±?17.6 μg m?3 in the outdoor air, respectively. In the Sadeghiye station, mean concentrations of PM10 and PM2.5 were 87.6?±?23 and 41.3?±?20.4 μg m?3 in the platform and 73.9?±?17.3 and 30?±?15 μg m?3, in the outdoor air, respectively. The relative contribution of elemental components in each particle fraction were accounted for 43 % (PM10) and 47.7 % (PM2.5) in platform of Imam Khomeini station and 15.9 % (PM10) and 18.5 % (PM2.5) in the outdoor air of this station. Also, at the Sadeghiye station, each fraction accounted for 31.6 % (PM10) and 39.8 % (PM2.5) in platform and was 11.7 % (PM10) and 14.3 % (PM2.5) in the outdoor. At the Imam Khomeini station, Fe was the predominant element to represent 32.4 and 36 % of the total mass of PM10 and PM2.5 in the platform and 11.5 and 13.3 % in the outdoor, respectively. At the Sadeghiye station, this element represented 22.7 and 29.8 % of total mass of PM10 and PM2.5 in the platform and 8.7 and 10.5 % in the outdoor air, respectively. Other major crustal elements were 5.8 % (PM10) and 5.3 % (PM2.5) in the Imam Khomeini station platform and 2.3 and 2.4 % in the outdoor air, respectively. The proportion of other minor elements was significantly lower, actually less than 7 % in total samples, and V was the minor concentration in total mass of PM10 and PM2.5 in both platform stations.  相似文献   

16.
Biomass burning is one of many sources of particulate pollution in Southeast Asia, but its irregular spatial and temporal patterns mean that large episodes can cause acute air quality problems in urban areas. Fires in Sumatra and Borneo during September and October 2006 contributed to 24-h mean PM10 concentrations above 150 μg m?3 at multiple locations in Singapore and Malaysia over several days. We use the FLAMBE model of biomass burning emissions and the NAAPS model of aerosol transport and evolution to simulate these events, and compare our simulation results to 24-h average PM10 measurements from 54 stations in Singapore and Malaysia. The model simulation, including the FLAMBE smoke source as well as dust, sulfate, and sea salt aerosol species, was able to explain 50% or more of the variance in 24-h PM10 observations at 29 of 54 sites. Simulation results indicated that biomass burning smoke contributed to nearly all of the extreme PM10 observations during September–November 2006, but the exact contribution of smoke was unclear because the model severely underestimated total smoke emissions. Using regression analysis at each site, the bias in the smoke aerosol flux was determined to be a factor of between 2.5 and 10, and an overall factor of 3.5 was estimated. After application of this factor, the simulated smoke aerosol concentration averaged 20% of observed PM10, and 40% of PM10 for days with 24-h average concentrations above 150 μg m?3. These results suggest that aerosol transport models can aid analysis of severe pollution events in Southeast Asia, but that improvements are needed in models of biomass burning smoke emissions.  相似文献   

17.
Agra, one of the oldest cities “World Heritage site”, and Delhi, the capital city of India are both located in the border of Indo-Gangetic Plains (IGP) and heavily loaded with atmospheric aerosols due to tourist place, anthropogenic activities, and its topography, respectively. Therefore, there is need for monitoring of atmospheric aerosols to perceive the scenario and effects of particles over northern part of India. The present study was carried out at Agra (AGR) as well as Delhi (DEL) during winter period from November 2011 to February 2012 of fine particulate (PM2.5: d?<?2.5 μm) as well as associated carbonaceous aerosols. PM2.5 was collected at both places using medium volume air sampler (offline measurement) and analyzed for organic carbon (OC) and elemental carbon (EC). Also, simultaneously, black carbon (BC) was measured (online) at DEL. The average mass concentration of PM2.5 was 165.42?±?119.46 μg m?3 at AGR while at DEL it was 211.67?±?41.94 μg m?3 which is ~27 % higher at DEL than AGR whereas the BC mass concentration was 10.60 μg m?3. The PM2.5 was substantially higher than the annual standard stipulated by central pollution control board and United States Environmental Protection Agency standards. The average concentrations of OC and EC were 69.96?±?34.42 and 9.53?±?7.27 μm m?3, respectively. Total carbon (TC) was 79.01?±?38.98 μg m?3 at AGR, while it was 50.11?±?11.93 (OC), 10.67?±?3.56 μg m?3 (EC), and 60.78?±?14.56 μg m?3 (TC) at DEL. The OC/EC ratio was 13.75 at (AGR) and 5.45 at (DEL). The higher OC/EC ratio at Agra indicates that the formation of secondary organic aerosol which emitted from variable primary sources. Significant correlation between PM2.5 and its carbonaceous species were observed indicating similarity in sources at both sites. The average concentrations of secondary organic carbon (SOC) and primary organic carbon (POC) at AGR were 48.16 and 26.52 μg m?3 while at DEL it was 38.78 and 27.55 μg m?3, respectively. In the case of POC, similar concentrations were observed at both places but in the case of SOC higher over AGR by 24 in comparison to DEL, it is due to the high concentration of OC over AGR. Secondary organic aerosol (SOA) was 42 % higher at AGR than DEL which confirms the formation of secondary aerosol at AGR due to rural environment with higher concentrations of coarse mode particles. The SOA contribution in PM2.5 was also estimated and was ~32 and 12 % at AGR and DEL respectively. Being high loading of fine particles along with carbonaceous aerosol, it is suggested to take necessary and immediate action in mitigation of the emission of carbonaceous aerosol in the northern part of India.  相似文献   

18.
The PM10, PM2.5, and PM1 (particulate matter with aerodynamic diameters <10, <2.5, and <1 μm, respectively) concentrations were monitored over a 90-day period in a naturally ventilated school building located at roadside in Chennai City. The 24-hr average PM10, PM2.5, and PM1 concentrations at indoor and outdoor environments were found to be 136 ± 60, 36 ± 15, and 20 ± 12 and 76 ± 42, 33 ± 16, and 23 ± 14 μg/m3, respectively. The size distribution of PM in the classroom indicated that coarse mode was dominant during working hours (08:00 a.m. to 04:00 p.m.), whereas fine mode was dominant during nonworking hours (04:00 p.m. to 08:00 a.m.). The increase in coarser particles coincided with occupant activities in the classrooms and finer particles were correlated with outdoor traffic. Analysis of indoor PM10, PM2.5, and PM1 concentrations monitored at another school, which is located at urban reserved forest area (background site) indicated 3–4 times lower PM10 concentration than the school located at roadside. Also, the indoor PM1 and PM2.5 concentrations were 1.3–1.5 times lower at background site. Further, a mass balance indoor air quality (IAQ) model was modified to predict the indoor PM concentration in the classroom. Results indicated good agreement between the predicted and measured indoor PM2.5 (R2 = 0.72–0.81) and PM1 (R2 = 0.81–0.87) concentrations. But, the measured and predicted PM10 concentrations showed poor correlation (R2 = 0.17–0.23), which may be because the IAQ model could not take into account the sudden increase in PM10 concentration (resuspension of large size particles) due to human activities.
Implications:The present study discusses characteristics of the indoor coarse and fine PM concentrations of a naturally ventilated school building located close to an urban roadway and at a background site in Chennai City, India. The study results will be useful to engineers and policymakers to prepare strategies for improving the IAQ inside classrooms. Further, this study may help in the development of IAQ standards and guidelines in India.  相似文献   

19.
This study uses monitoring data collected at the Taipei Aerosol Supersite from March 2002 to February 2008 to analyze characteristics such as seasonal fluctuations, diurnal variations, and photochemical-related variations of PM2.5 chemical compositions. The results indicate that the average of PM2.5 mass concentration in Taipei during this period is 30.3 ± 16.0 μg m?3. The highest average concentration of PM2.5 components is that of sulfate, which accounts for 21.1% of the PM2.5 mass, followed by organic carbon (OC) at 15.9%, nitrate at 5.8%, and elemental carbon (EC) at 5.4%. Concentrations of EC, OC, and nitrate have distinctive but similar seasonal fluctuations, which is highest in spring and lowest in fall. Sulfate concentration has less seasonal fluctuations, and the highest value appears during the fall. Similarly, concentrations of EC, OC, and nitrate have notable diurnal variations; however, the diurnal variation of sulfate concentration is not very apparent. These observation data show that EC, OC, and nitrate in PM2.5 in the Taipei metropolis come mainly from local emissions, while sulfate comes mainly from the regional transport of pollutants. This is likely because Taiwan is located on the lee zone of the Asian prevailing winds from fall to spring; its air quality is frequently affected by the transport of air pollutants from Mainland China. In addition, the extent of increase in aerosols is much higher than that of CO, indicating the formation of secondary aerosol when photochemical activity is strong. Based on six years of observation data, this study explores three potential scenarios to set up Taiwan's PM2.5 air quality standard (AQS). The analysis indicates that the optimum standard for 24-h air quality of PM2.5 should be around 50 μg m?3.  相似文献   

20.
Methylcyclopentadienyl manganese tricarbonyl (MMT) is a manganese-based gasoline additive used to enhance automobile performance. MMT has been used in Canadian gasoline for about 20 yr. Because of the potential for increased levels of Mn in particulate matter resulting from automotive exhausts, a large-scale population-based exposure study (∼1000 participant periods) was conducted in Toronto, Canada, to estimate the distribution of 3-day average personal exposures to particulate matter (PM2.5 and PM10) and Mn. A stratified, three-stage, two-phase probability, longitudinal sample design of the metropolitan population was employed. Residential indoor and outdoor, and ambient levels (at a fixed site and on a roof) of PM2.5, PM10, and Mn were also measured. Supplementary data on traffic counts, meteorology, MMT levels in gasoline, personal occupations, and activities (e.g. amount of vehicular usage) were collected. Overall precision (%RSD) for analysis of duplicate co-located samples ranged from 2.5 to 5.0% for particulate matter and 3.1 to 5.5% for Mn. The detection limits were 1.47 and 3.45 μg m-3 for the PM10 and PM2.5 fractions, respectively, and 5.50 and 1.83 ng m-3 for Mn in PM10 and PM2.5, respectively. These low detection limits permitted the reporting of concentrations for >98% of the samples. For PM10, the personal particulate matter levels (median 48.5 μg m-3) were much higher than either indoor (23.1 μg m-3) or outdoor levels (23.6 μg m-3). The median levels for PM2.5 for personal, indoor, and outdoor were 28.4, 15.4 and 13.2 μg m-3, respectively. The correlation between PM2.5 personal exposures and indoor concentrations was high (0.79), while correlations between personal and the outdoor, fixed site and roof site were low (0.16–0.27). Indoor Mn concentration distributions (in PM2.5 and PM10), unlike particulate matter, exhibited much lower and less variable levels that the corresponding outdoor data. The median personal exposure was 8.0 ng m-3, compared with 4.7 and 8.6 ng m-3, respectively, for the indoor and outdoor distributions. The highest correlations occurred for personal vs indoor data (0.56) and for outdoor vs roof site data (0.66), and vs fixed site data (0.56). The concentration of Mn in particulate matter, expressed in ppm (w/w), revealed that the fixed site was the highest, followed by the roof site, outdoor, indoor, and personal. The personal and indoor data showed a statistically significant correlation (0.68) while all other correlations between personal or indoor data and outdoor or fixed-site data were quite small. The low correlations of personal and indoor levels with outdoor levels suggest that different sources in the indoor and outdoor microenvironments produce particle matter with dissimilar composition. The correlation results indicate that neither the roof- nor fixed-site concentrations can adequately predict personal particulate matter or Mn exposures.  相似文献   

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