Particulate matter and carbon monoxide multiple regression models using environmental characteristics in a high diesel-use area of Baguio City, Philippines

In Baguio City, Philippines, a mountainous city of 252,386 people where 61% of motor vehicles use diesel fuel, ambient particulate matter <2.5 microm (PM(2.5)) and <10 microm (PM(10)) in aerodynamic diameter and carbon monoxide (CO) were measured at 30 street-level locations for 15 min apiece during the early morning (4:50-6:30 am), morning rush hour (6:30-9:10 am) and afternoon rush hour (3:40-5:40 pm) in December 2004. Environmental observations (e.g. traffic-related variables, building/roadway designs, wind speed and direction, etc.) at each location were noted during each monitoring event. Multiple regression models were formulated to determine which pollution sources and environmental factors significantly affect ground-level PM(2.5), PM(10) and CO concentrations. The models showed statistically significant relationships between traffic and early morning particulate air pollution [(PM(2.5)p=0.021) and PM(10) (p=0.048)], traffic and morning rush hour CO (p=0.048), traffic and afternoon rush hour CO (p=0.034) and wind and early morning CO (p=0.044). The mean early morning, street-level PM(2.5) (110+/-8 microg/m3; mean+/-1 standard error) was not significantly different (p-value>0.05) from either rush hour PM(2.5) concentration (morning=98+/-7 microg/m3; afternoon=107+/-5 microg/m3) due to nocturnal inversions in spite of a 100% increase in automotive density during rush hours. Early morning street-level CO (3.0+/-1.7 ppm) differed from morning rush hour (4.1+/-2.3 ppm) (p=0.039) and afternoon rush hour (4.5+/-2.2 ppm) (p=0.007). Additionally, PM(2.5), PM(10), CO, nitrogen dioxide (NO2) and select volatile organic compounds were continuously measured at a downtown, third-story monitoring station along a busy roadway for 11 days. Twenty-four-hour average ambient concentrations were: PM(2.5)=72.9+/-21 microg/m3; CO=2.61+/-0.6 ppm; NO2=27.7+/-1.6 ppb; benzene=8.4+/-1.4 microg/m3; ethylbenzene=4.6+/-2.0 microg/m3; p-xylene=4.4+/-1.9 microg/m3; m-xylene=10.2+/-4.4 microg/m3; o-xylene=7.5+/-3.2 microg/m3. The multiple regression models suggest that traffic and wind in Baguio City, Philippines significantly affect street-level pollution concentrations. Ambient PM(2.5) levels measured are above USEPA daily (65 microg/m3) and Filipino/USEPA annual standards (15 microg/m3) with concentrations of a magnitude rarely seen in most countries except in areas where local topography plays a significant role in air pollution entrapment. The elevated pollution concentrations present and the diesel-rich nature of motor vehicle emissions are important pertaining to human exposure and health information and as such warrant public health concern.     

Remote sensing of PM, NO, CO and HC emission factors for on-road gasoline and diesel engine vehicles in Las Vegas, NV

A novel light detection and ranging-based remote sensing system was assembled and used to measure mass particulate matter (PM) emissions per unit of fuel burned from in-use on-road vehicles. A commercially available remote sensing system was concurrently used to measure emissions of carbon monoxide (CO), nitrogen oxide (NO) and hydrocarbons (HC). The two systems were used to measure 61,207 gasoline and 1180 diesel powered vehicle emissions in Las Vegas, NV from 4/4/2000 to 5/16/2002. Emission factors were related to vehicle age, weight class and fuel type by matching license IDs to the state registration data. Measurements of vehicle speed and acceleration permitted the analysis of emission factors by vehicle specific power (VSP). Average emission factors were calculated for light-duty (<3863 kg [8500 lbs]) gasoline vehicles (LDGV), light-duty diesel vehicles (LDDV), heavy-duty (>3863 kg [8500 lbs]) gasoline vehicles (HDGV) and heavy-duty diesel vehicles (HDDV). LDDV and HDDV emitted approximately 25 times more PM per mass of fuel than LDGV and HDGV. Sufficient numbers of LDGV were measured to relate VSP with CO, HC and NO emissions. No relationship was observed between PM emissions and VSP. PM emission factors from LDGV increased with vehicle age. Fuel-based emission factors measured by remote sensing were compared with MOBILE6 and PART5 emissions model factors. Good agreement was observed for HC emission factors for vehicles less than 20 years old. MOBILE6 CO emission factors were approximately 2 times greater than measured CO emission factors for vehicles less than 13 years old. Measured NO emission factors were approximately 50% greater than MOBILE6 factors for vehicles 7-15 years old but in good agreement for vehicles less than 7 years old. Measured PM emission factors showed a clear increase with vehicle age, however, PART5 uses only a single PM emission factor for LDGV less than 18 years old. The PM emission factors for the fleet of LDGV, HDGV, LDDV and HDDV were 0.06, 0.05, 1.6 and 1.5 g/kg, respectively.     

Traffic emission scenarios in Lombardy region in 1998-2015

This study assesses and discusses the current and future contribution of road traffic to primary PM10 and PM10 main precursors (i.e. NO(x), SO(2), NH(3), VOC) in the Lombardy region (Italy). It defines a coherent and updated set of input parameters (emission factors, mileage and fleet composition) for traffic emission estimation between 1998 and 2015. 1998-2004 emissions are assessed basing on historical data, while 2005-2015 rely on different hypothesis about mobility development and vehicular turnover rate. The work shows that road traffic emissions of PM10 and PM10 precursors are expected to decrease in the period 2005-2015, with a reduction greater than 70% in scenarios with a fast vehicle turnover and a decrease in fuel usage. Increase in fuel consumption could substantially lower the emission reduction expected, off-setting a substantial part of the new technology benefits. The introduction of DPF (diesel particulate filter) vehicles will determine a reduction of PM10 exhaust, however this could potentially be stalled by the increase in diesel usage in the vehicle fleet and an increase in mileage driven, as the latter causes a rise in the contribution of PM10 from abrasion. Concerning the total atmospheric emissions in Lombardy, SO(2) (-6%) and NH(3) (<-2%) emission will remain constant, while PM10, VOC and NO(x) emission will decrease, respectively by 2-30%, 6-15% and 2-32% in the period 2001-2015.     

Characterization of emissions from burning incense

The primary objective of this study was to improve the characterization of particulate matter emissions from burning incense. Emissions of particulate matter were measured for 23 different types of incense using a cyclone/filter method. Emission rates for PM2.5 (particulate matter less than 2.5 microm in aerodynamic diameter) ranged from 7 to 202 mg/h, and PM2.5 emission factors ranged from 5 to 56 mg/g of incense burned. Emission rates were also determined using an electrical low pressure impactor (ELPI) and a small electrostatic precipitator (ESP), and emission rates were compared to those determined using the cyclone/filter method. Emission rates determined by the ELPI method were consistently lower than those determined by the cyclone/filter method, and a linear regression correlation was found between emission rates determined by the two methods. Emission rates determined by the ESP method were consistently higher than those determined by the cyclone/filter method, indicating that the ESP may be a more effective method for measuring semivolatile particle emissions. A linear regression correlation was also found between emission rates determined by the ESP and cyclone/filter methods. Particle size distributions were measured with the ELPI, and distributions were found to be similar for most types of incense that were tested. Size distributions by mass typically ranged from approximately 0.06 to 2.5 microm in aerodynamic diameter, with peak values between 0.26 and 0.65 microm. Results indicated that burning incense emits fine particulate matter in large quantities compared to other indoor sources. An indoor air quality model showed that indoor concentrations of PM25 can far exceed the outdoor concentrations specified by the US EPA's National Ambient Air Quality Standards (NAAQS), so incense smoke can pose a health risk to people due to inhalation exposure of particulate matter. Emissions of carbon monoxide (CO), nitric oxide (NO), and sulfur dioxide (SO2) were also measured for seven types of incense. Emission rates of the gaseous pollutants were sufficient to cause indoor concentrations, estimated using the indoor air quality model, to exceed the outdoor concentrations specified by the NAAQS under certain conditions. However, the incense samples that were tested would fill a room with thick smoke under these conditions.     

Emission factors and characteristics of criteria pollutants and volatile organic compounds (VOCs) in a freeway tunnel study

Carbon monoxide (CO), nitrogen oxide (NO(x)), hydrocarbon (HC), sulfur oxide (SO(2)), particulate matter <10 microm (PM(10)), and 57 VOC species of emissions were confirmed in a freeway tunnel in southern Taiwan. Emission factors were 1.89 (CO), 0.73 (NO(x)), 0.46 (HC), 0.02 (SO2) and 0.06 (PM(10)) g/km-vehicle for all vehicle fleets. Heavy-duty truck and trailer vehicles contributed 20% of the emissions on workdays and 9.5% on weekends in this study. Paraffins and aromatics were the main VOC groups in the tunnel. Isopentane, toluene, n-pentane, isoprene, 2,3-dimethylbutane, acetone, 2-methylpentane, 1-hexene, 1,2,4-trimethybenzene, 1-butene and propene emissions were the major VOC species. Their emission factors were over 10 mg/km-vehicle. Rainfall and high humidity in the tunnel could have reduced the VOC concentrations and increased the portion of aromatics. In addition to paraffins, olefins, and aromatic compounds, oxygenated compounds (i.e., acetone) were found. The pollutant ratios between the inside center and the outside of the tunnel were about 2-3 for CO, SO2, and PM(10) and 42 for NO(x). In addition, the emission factors of the vehicles could reflect real-world vehicle emissions on the highway and be used as baseline information for development of a vehicle control strategy.     

Estimating national exhaust emissions from railway vehicles in Turkey

The estimated exhaust emissions from railway vehicles in Turkey were presented. The emissions of nitrogen oxides (NO(X)), hydrocarbon compounds (HC), carbon monoxide (CO), particulate matter (PM), sulfur dioxide (SO(2)) and carbon dioxide (CO(2)) from the diesel locomotives and railcars were calculated using the railway traffic data recorded by Turkish State Railways (TSR) for the period of 2000-2005. EPA emission factors were used for different vehicle types and operation modes such as shunting and line-hauling. Total emissions from railway vehicles in Turkey were estimated as 384 t y(-1) for HC, 1016 t y(-1) for CO, 6799 t y(-1) for NO(X), 256 t y(-1) for PM, 357 t y(-1) for SO(2) and 383 537 t y(-1) for CO(2) for the year 2005. The distribution of emissions with respect to type of railway vehicles shows that the mainline locomotives contribute approximately 91% to the total emissions. The increases of 22%, 39% and 49% in the current numbers of mainline locomotives, shunting locomotives and diesel railcars, respectively corresponding to the full capacity of railway network in Turkey will increase the annual emissions to 431 t y(-1) for HC, 1121 t y(-1) for CO, 7399 t y(-1) for NO(X), 342 t y(-1) for PM, 552 t y(-1) for SO(2) and 420 256 t y(-1) for CO(2). Total railway emissions constitute 0.15%, 0.08% and 4.21% of total Turkish traffic emissions for HC, CO and NO(X), respectively.     

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.     

Investigation of the impact of intensive broiler rearing on local fine particulate matter concentrations

During the review and assessment of air quality process, South Norfolk Council identified that poultry rearing could be a significant source of particulate matter and therefore required more detailed study. Using standard emission data for poultry rearing dispersion modelling confirmed that there was potential for an exceedance of the UK objective for fine particulate matter (PM₁₀). However, it was recognised that the emission data available were based on very limited information and further monitoring was required to investigate the issue fully. Accordingly, an air quality monitoring programme was set up to measure PM₁₀ concentrations around a large broiler‐rearing facility. This used both a TEOM‐ and Partisol‐type instrument to allow direct comparison with the UK objective and to provide continuous results to use with wind direction monitoring to assist in identifying the source of particulate matter in the area. The results from the monitoring showed that an exceedance of the UK objective was unlikely, although the broiler sheds did appear to result in a significant increase in PM₁₀ concentrations in the area, with average concentrations increasing by nearly 12 μg/m³ when the wind direction carried emissions from the sheds to the monitoring site. Given that the test site was located near a very large broiler farm, it was considered that it was unlikely that broiler‐rearing activities would result in an exceedance of the UK objective for PM₁₀.     

Performance of a high-volume cascade impactor in six European urban environments: mass measurement and chemical characterization of size-segregated particulate samples

The performance of a modified Harvard high-volume cascade impactor (HVCI) was evaluated in six field campaigns with size-segregated particulate samplings for chemical and toxicological characterization. The 7-week sampling campaigns in 2002-2003 in Duisburg (autumn), Prague (winter), Amsterdam (winter), Helsinki (spring), Barcelona (spring), and Athens (summer) were selected to represent contrasting urban environments and seasons of public health interest due to high particulate concentrations or previous findings in epidemiological studies. Particulate samples were collected in parallel with the HVCI (PM(10-2.5), PM(2.5-1), PM(1-0.2), PM(0.2)), a virtual impactor (VI; PM(10-2.5), PM(2.5)), and a Berner low-pressure impactor (BLPI; 10 stages between 0.035 and 10 mum in particle diameter) using a 3- or 4-day sampling duration. The campaigns exhibited different profiles with regard to particulate mass concentration, size distribution, chemical composition and meteorological conditions, thus providing a demanding setup for an overall field comparison of the HVCI with the VI and BLPI reference samplers. Size-segregated particulate mass concentration could be reasonably well measured with the present HVCI configuration. The coarse (PM(10-2.5)) and fine (PM(2.5)) particulate mass agreed within 10% with the low-volume reference samplers, and the four-stage size distribution of the HVCI followed the modal pattern of urban aerosol. The concentrations of chemical constituents measured and integrated especially for the HVCI-PM(2.5) differed to some extent from those measured from the corresponding VI-PM(2.5) samples. This implies that when investigating the association of toxicological responses with the chemical constituents of particulate matter, it is necessary to use the chemical composition data of the same samples as used in toxicological experiments.     

A combined analysis of backward trajectories and aerosol chemistry to characterise long-range transport episodes of particulate matter: the Madrid air basin, a case study

This study has investigated the influence of synoptic weather patterns and long-range transport episodes on the concentration levels of airborne particulate matter (TSP, PM10 and PM2.5) and some major ions (SO(4)(2-), NO(3)(-) and NH(4)(+)) at a background rural station in central Spain. Air mass back-trajectories arriving at the site in 1999-2005 have been analysed by statistical methods. First, cluster analysis was used to group trajectories into 8 clusters depending on their direction and speed. Meteorological scenarios associated to each cluster have been obtained and interpreted. Then, the incidence of different air mass transport patterns on particle concentrations and composition recorded at this station was evaluated. This evaluation included PM10 and PM2.5 concentrations and chemical composition data, obtained at three representative sites of the Madrid air basin during sampling campaigns carried out in the course of the 1999-2005 period. Finally, a residence time analysis of trajectories was also performed to detect remote sources and transport pathways. Significantly elevated concentrations of TSP and PM10 were observed for Northern African flows as a consequence of the transport of mineral dust. Significant inter-cluster differences were also observed for PM2.5 and secondary inorganic compounds, with the highest concentrations associated with low baric gradient situations and Southern European flows. The residence time analysis confirmed that current TSP and PM10 concentrations in central Spain are likely to be influenced significantly by long-range transport of desert dust from different desert regions in North Africa. Furthermore, emissions from continental Europe with a high time of residence in the western and central areas of the Mediterranean basin, seem to significantly influence PM2.5 and secondary inorganic aerosol concentrations in this region.     

Comparisons of commuter's exposure to particulate matters while using different transportation modes

This study compared commuters' exposures to particulate matter (PM) while using motorcycles, cars, buses, and the mass rapid transit (MRT) on the same routes in Taipei, Taiwan. Motorcycle commuters who had the shortest travel time (28.4+/-4.2 min) were exposed to the highest concentrations of PM(10) (112.8+/-38.3 microg/m(3)), PM(2.5) (67.5+/-31.3 microg/m(3)), and PM(1.0) (48.4+/-24.7 microg/m(3)) among four commuting modes. By contrast, car commuters were exposed to the lowest PM concentrations and had the second shortest travel time among them. Motorcycle commuters' high trip-averaged PM concentrations and bus commuters' long commuting time (43.1+/-5.1 min) resulted in their high whole-trip PM exposures. Size fractions of PM were relatively consistent across PM exposures of the four commuting modes with fine particles (PM(2.5)) contributing to 53-60% of PM(10) and submicron particle (PM(1)) contributing to 39-43% of PM(10). Motorcycles idled at traffic lights and bus doors opened at stops increased commuters' PM exposures. Fixed-site monitoring data explained well the variation of whole-trip PM(10) exposure of car (r(2)=0.63) and MRT (r(2)=0.52) commuters, and of whole-trip PM(2.5) exposure of car (r(2)=0.76), MRT (r(2)=0.73) and motorcycle (r(2)=0.64) commuters in regression analyses. The coefficients (slopes) of regression between fixed-site monitoring data and PM(2.5) exposures were less than 1 for car and MRT commuters but greater than 1 for motorcycle commuters. In conclusion, proximity to traffic emissions contributes to a person's high PM exposure during his or her daily commute. This proximity occurs when people use motorcycles on roads and when bus/MRT commuters walk or wait along commuting routes. Fixed-site air monitoring data can under-estimate motorcycle commuters' PM(2.5) exposures but over-estimate car and MRT commuters' PM(2.5) exposures.     

The effect of temperature inversions on ground-level nitrogen dioxide (NO2) and fine particulate matter (PM2.5) using temperature profiles from the Atmospheric Infrared Sounder (AIRS)

We investigate the effects of temperature inversions on the levels of nitrogen dioxide (NO₂) and fine particulate matter (PM2.5) in the atmosphere over the Hamilton Census Metropolitan Area and environs in Ontario, Canada, for the period 2003 to 2007. Vertical temperature profiles extracted from data acquired by the Atmospheric Infrared Sounder (AIRS) were used to determine the occurrences of daytime and nighttime temperature inversions over the region. NO₂ and PM2.5 data were obtained from three in situ air quality monitoring stations located in the study area. The results indicate increases of 49% and 54% in NO₂ and PM2.5 respectively, during nighttime inversion episodes. Daytime inversions resulted in an 11% increase in NO₂ but a 14% decrease in PM2.5. Decreases occurred predominantly in the summer. We discuss these results and possible explanations for the reduced PM2.5 concentrations on inversion days. Weekday and seasonal analysis, with associated meteorological parameters are also discussed.     

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.     

Particle-associated polycyclic aromatic hydrocarbons in the atmospheric environment of Zonguldak, Turkey

Airborne fine (PM(2.5)) and coarse (PM(2.5-10)) particulate matter was collected from January to December in 2007 in Zonguldak, Turkey using dichotomous Partisol 2025 sampler. Fourteen selected polycyclic aromatic hydrocarbons (PAHs) in particulate matter were determined simultaneously by high-performance liquid chromatography with fluorescence detection (HPLC-FL) and seasonal distributions were examined. The source identification of PAHs in airborne particulates was performed by principal component analysis (PCA) in combination with diagnostic ratios. The predominant PAHs determined in PM(2.5) were pyrene, fluoranthene, benzo[a]anthracene, chrysene, benzo[b]fluoranthene and benzo[a]pyrene. The total concentrations of PAHs were up to 464.0 ng m(-3) in fine and 28.0 ng m(-3) in coarse fraction in winter, whereas in summer times were up to 22.9 and 3.0 ng m(-3) respectively. Approximately 93.3% of total PAHs concentration was determined in PM(2.5) in winter and 84.0% in summer. The concentration levels of PAHs fluctuate significantly within a year with higher means and peak concentrations in the winter compared to that of summer times. Higher benzo(a)pyrene-equivalent (BaPE) concentrations of PAHs were obtained for PM(2.5) especially in winter. The results obtained from PCA in combination with diagnostic ratios revealed that coal combustion and vehicle emissions were the major pollutant sources for both PM(2.5) and PM(2.5-10) associated PAHs in studied area. Two principal components for PM(2.5) and three for PM(2.5-10) were identified and these accounted for 89.4 and 85.2% of the total variance respectively. The emissions from coal combustion were estimated to be the main source of PAHs in the ambient air particulates with contributions of 80.8% of total variance for PM(2.5) and 53.8% for PM(2.5-10).     

Characteristics of emissions of air pollutants from burning of incense in temples, Hong Kong

Field investigations of target air pollutants at two of the most famous temples in Hong Kong were conducted. The air pollution problems in these two temples during peak and non-peak periods were characterized. The target air pollutants included particulate matters (PM(10), PM(2.5)), volatile organic compounds (VOCs), carbonyl compounds, carbon monoxide (CO), nitrogen oxides (NO(x)), methane (CH(4)), non-methane hydrocarbons (NMHC), organic carbon (OC), elemental carbon (EC), and inorganic ions (Cl(-), NO(3)(-), SO(4)(2-), Na(+), NH(4)(+), and K(+)). The pollutant levels of the two temples during peak period were shown to be significantly higher than those during non-peak period. The highest average CO level was obtained at Temple 1 during peak period, which exceeded IAQO 8-h Good Class criteria. In general, the average PM(2.5)/PM(10) ratios were approximately 82%. The results revealed that the fine particulates (PM(2.5)) constituted the majority of suspended particulates at both temples. It was noted that formaldehyde was the most abundant carbonyl compounds, followed by acetaldehyde. At Temple 1 during peak period, the average benzene concentration exceeded almost 8 times more than Indoor Air Quality Objectives for Office Buildings and Public Places (IAQO) [HKEPD, 2003. Guidance notes for the management of indoor air quality in offices and public places. Indoor air quality management group, The Government of the Hong Kong Special Administrative Region.] Good Class criteria. The average OC/EC ratios ranged from 2.6 to 17 in PM(10) and from 4.2 to 18 in PM(2.5) at two temples, which suggested that OC measured in these two temple areas may be due to both direct emission from incense burning and secondary formation by chemical reactions. The total mass of inorganic ions, organic carbon, and elemental carbon accounted for about 71% in PM(2.5) and 72% in PM(10).     

不同植被结构校园绿地对空气颗粒物浓度影响研究

通过2017年4月—2018年3月连续监测陕西省宝鸡文理学院5种不同植被结构绿地内的空气颗粒物总量(TSP)、PM_(10)、PM_(2.5)的浓度以及相关气象因子的变化,探究时间、气象和植被结构等因子对空气颗粒物浓度的影响,结果表明:1)监测日期和时间对PM_(2.5)、PM_(10)、TSP浓度有极显著的影响,在监测期内PM_(2.5)、PM_(10)和TSP在7月份最低,12月达到峰值;2)温度、湿度和风速对PM_(2.5)、PM_(10)及SP浓度均有极显著影响;在微风条件下,温度和风速与空气颗粒物PM_(2.5)、PM_(10)和TSP的浓度呈负相关,湿度与其呈正相关。在同样的气象条件下,粗颗粒物对于气象因素的响应大于细颗粒物;3)5种不同校园绿地植被结构类型对PM_(2.5)、PM_(10)、TSP浓度的削减作用在统计学上虽无显著差异,但不同植被结构的绿地对空气颗粒物均有一定滞留能力,整体上表现为在相同的气象条件下,绿地内的空气颗粒物浓度大于硬质铺装。     

Characteristic of polycyclic aromatic hydrocarbon concentrations and source identification for fine and coarse particulates at Taichung Harbor near Taiwan Strait during 2004-2005

Fine (PM(2.5)) and coarse (PM(2.5-10)) particulate concentrations of ambient air polycyclic aromatic hydrocarbons (PAHs) were measured simultaneously from February 2004 to January 2005 at the Taichung Harbor (TH) sampling site near Taiwan of central Taiwan. Particle-bound polycyclic aromatic hydrocarbons (PAHs) were collected on quartz filters; the collected sample was Soxhlet extracted with a dichloromethane (DCM)/n-hexane mixture (50/50, v/v) for 24 h, and then the extracts were analyzed by gas chromatography-mass spectrometry (GC-MS). The results indicated that vehicle emissions, coal combustion, incomplete combustion and pyrolysis of fuel and oil burning were the main source of PAHs near Taiwan Strait of central Taiwan. Diagnostic ratios and principal component analysis (PCA) were also used to characterize and identify PAHs emission sources in this study.     

A non-linear analysis to detect the origin of PM10 concentrations in Northern Italy

This work presents the formalization and the application of the factor separation technique in order to investigate the impact of precursor emission and their nonlinear interaction (in particulate matter accumulation processes). By processing the simulations of a 3D multiphase modeling system, the factor separation methodology can support the Environmental Authority in quantifying the impact of precursor emissions on PM10 production and consequently in assessing the feasible efficiency of different emission control strategies over a considered domain. The case study proposed by this paper focuses on the Po Valley region (Northern Italy), characterized by critical PM10 levels claiming for sound emission reduction policies. The results show the heavy nonlinearities and the strong seasonal dependence in the formation of PM10, over the study domain. Furthermore the results highlight that peak PM10 concentrations are mainly related to primary PM emissions in urban areas, and gas emissions (mainly NOx and NH3) in rural areas.     

Source apportionment of PM2.5 in Beijing using principal component analysis/absolute principal component scores and UNMIX

Source apportionment of fine particulate matter (PM2.5, i.e., particles with an aerodynamic diameter of 2.5 microm or less) in Beijing, China, was determined using two eigenvector models, principal component analysis/absolute principal component scores (PCA/APCS) and UNMIX. The data used in this study were from the chemical analysis of 24-h samples, which were collected at 6-day intervals in January, April, July, and October 2000 in the Beijing metropolitan area. Both models identified five sources of PM2.5: secondary sulfate and secondary nitrate, a mixed source of coal combustion and biomass burning, industrial emission, motor vehicles exhaust, and road dust. On average, the PCA/APCS and UNMIX models resolved 73% and 85% of the PM2.5 mass concentrations, respectively. The results were comparable to previous estimate using the positive matrix factorization (PMF) and chemical mass balance (CMB) receptor models. Secondary products and the emissions from coal combustion and biomass burning dominated PM2.5. Such comparison among various receptor models, which contain different physical constraints, is important for better understanding PM2.5 sources.     

Characterization of chemical species in PM2.5 and PM10 aerosols in suburban and rural sites of central Taiwan.

Aerosol samples for PM2.5 (particulate matter with aerodynamic diameters less than 2.5 microns), PM2.5-10 (particulate matter with aerodynamic diameters between 2.5 and 10 microns) and TSP were collected from June to September 1998 at THU (suburban) and HKIT (rural) sites in central Taiwan. The ratios of PM2.5/PM10 averaged 0.70 for the daytime and 0.63 for the nighttime at THU, respectively. At HKIT, the PM2.5/PM10 ratios averaged 0.56 for the daytime and 0.72 in the nighttime, respectively. These results indicated that the PM2.5 concentrations contribute the majority of the PM10 concentration and PM10 concentrations contribute the majority of the TSP at both sites. The averaged PM2.5 concentrations at THU are higher than those measured at HKIT during the daytime period. However, the average PM2.5-10 concentrations in THU are lower than those measured at HKIT during nighttime. The samples collected were also analyzed by atomic absorption spectrophotometry for the elemental analysis of Ca, Fe, Pb, Zn, Cu, Mn and Cr. Meanwhile ion chromatography was used to analyze for the water-soluble ions: sulphate, nitrate and chloride in the Universal samples. The concentrations of heavy metals in PM10 during daytime were all higher than nighttime at THU. However, the averaged concentrations of metal elements in PM10 during day and night period were distributed irregularly at HKIT. The results indicated that for metal elements collected at HKIT have different emission sources. The concentrations of metal elements during daytime in PM10 at THU were generally higher than HKIT. The phenomena owing to the averaged PM2.5 particle concentrations at THU (suburban) were higher than those measured at HKIT (rural) and PM2.5 occupied the major portions of PM10 for both sites during the day period. For anion species, there are no significant differences between day and night period in PM10 concentrations at both suburban and rural sites.