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Characteristics and source identification study of ambient suspended particulates and ionic pollutants in an area abutting a highway
Available online at www.sciencedirect.com
Powder Technology 185 (2008) 223 – 230 www.elsevier.com/locate/powtec
Characteristics and source identification study of ambient suspended particulates and ionic pollutants in an area abutting a highway Guor-Cheng Fang ⁎, Yuh-Shen Wu, Jie-Feng Lee, Chia-Chi Chang Air Toxic and Environmental Analysis Laboratory, Department of Environmental Engineering, HungKuang University, No.34, Chung-Chie Rd., Sha-Lu, Taichung 43302, Taiwan, ROC Received 30 January 2007; received in revised form 15 October 2007; accepted 18 October 2007 Available online 1 November 2007
Abstract Ambient suspended particulates in an area abutting a highway were gathered using a Partisol Model 2300 Speciaton Sampler (RP2300). Major ionic species with different particle sizes and with possible sources close to the sampling site were evaluated using Principal Component Analysis (PCA). Observational results indicate that average PM2.5 and PM10 concentrations were 66.33 and 108.28 μg/m3, respectively. The average ratio of PM2.5/PM10 was 62% at this sampling site, whereas the average PM2.5/PM10 ratio in this study was less than those in urban (Seoul, Korea), + suburban (Basel, Switzerland) and rural (Chaumont, Switzerland) settings. Average concentrations for ionic species of NO−3 , SO2− 4 and NH4 were + 10.46, 12.63 and 7.87 μg/m3 in PM2.5, respectively. Average concentrations for ionic species of NO−3 , SO2− and NH were 17.28, 15.59 and 4 4 9.48 μg/m3 in PM10, respectively. Principal component analysis identified soil, secondary aerosols and marine salt as possible major pollutant sources at this sampling site. © 2007 Elsevier B.V. All rights reserved. Keywords: PCA; Spearman; Highway; Ionic species; PM
1. Introduction Highways connect urban, suburban and rural areas. However, highways also generate atmospheric pollutant-related problems and impact local ecosystems. Particulate air pollution describes both solid and liquid particles, such as diesel soot, road and agricultural dust, and particles resulting from manufacturing processes, directly emitted into the air [1]. Particles are also generated through photochemical reactions involving pollutant gases, such as sulfur and nitrogen oxides, which are byproducts of fuel combustion [2]. Most trip mileage in Taiwan is logged by taxis, which use diesel as a low-cost fuel. Consequently, PM10 and PM2.5 concentrations have become the principal source of streetlevel air pollution [3]. Large particles are markedly influenced by gravity, whereas fine particles are influenced by diffusion more than gravity [4]. Particles with aerodynamic diameters b10 μm ⁎ Corresponding author. Tel.: +886 4 2631 8652x1111; fax: +886 4 2350 2102. E-mail address: [email protected] (G.-C. Fang). 0032-5910/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.powtec.2007.10.020
are known as respiratory particulates or particulate matter10 (PM10), whereas PM2.5 denotes fine particles with aerodynamic diameters of b 2.5 μm [5]. However, atmospheric aerosols represent a multi-component system of materials in solid or liquid states (excluding pure water) that enter the air naturally or anthropogenically [6]. Atmospheric aerosols in PM10 are generally dominated by particles from the following three sources: (1) primary fine particles emitted from industrial sources and road vehicles; (2) secondary aerosols, predominantly ammonium sulfate and ammonium nitrate—these secondary aerosol particles are generally transported over long ranges and have relatively weak spatial gradients; and, (3) wind blown soil and re-suspended street dust, which are largely coarse (2.5– 10 μm) in particle fraction [7]. Aerosols can be classified as primary and secondary pollutants based on their source. Primary aerosols are usually emitted in particulate form directly from sources. Secondary aerosols comprise particles generated in the atmosphere that are predominantly submicron size and produced by heterogeneous or homogeneous chemical reactions. Sulfate is a common secondary pollutant. Numerous studies have proved
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that sulfur dioxide is converted to sulfate via oxidation hydrolysis [8]. The SO2 is generated by combustion of coal and fuel burned by industrial plants. The principal sources of NOx are fossil fuel combustion for industrial processes, electricity and automobile emissions, which are responsible for roughly 50% of such emissions. Atmospheric nitrogen, particularly NH3 and NO4+ compounds, have significant potential to impact adversely the environment. Atmospheric nitrogen compounds have numerous anthropogenic and natural sources. These nitrogen compounds are transported by and transformed in the atmosphere prior to deposition in sensitive ecosystems. Base cations such as Ca2+, K+ and Mg2+ are necessary plant nutrients. Their associated anions, principally oxides, hydroxides, carbonates and silicates, can decrease air precipitation acidity and increase soil base saturation. Base cations primarily derive from mechanical erosion and wind mobilization of soil particles, and particles from volcanic eruptions, forest fires, industrial processes, biological mobilization, or combustion of fuels such as wood or peat. The primary anthropogenic sources of mineral dust are power production, cement, ferrous and other industries. Marine aerosols, which are transferred from marine to continental areas by monsoon, are considered the predominant source of Na. This study characterizes ambient air particles at a sampling site abutting a major highway. Total atmospheric aerosols were
sampled using a Partisol Model 2300 Speciaton Sampler (RP2300). Moreover, ion chromatography (DIONEX DX100) was utilized to examine ionic species for PM2.5 particles (aerodynamic diameters b2.5 μm) and PM10 particles (aerodynamic diameters b10 μm) at the sampling site. Finally, the predominant ionic species were identified based on diameter differences and possible sources near the sampling site via Principal Component Analysis (PCA). 2. Experimental methods 2.1. Sampling program Fig. 1 presents the sampling location utilized in this study. Ambient particle concentrations were sampled on the roof of the Medical and Industrial Building at Hungkuang University, an eight-story building (25 m height) located on the top of Da Du Mountain. Site elevation is 500 m. The sampling location was thus close to both a major highway and the Taiwan Strait, which were located 50 m and 15 km from the sampling site, respectively. The Partisol Model 2300 Speciaton Sampler (RP2300) was utilized, and ran from March 4 to April 2, 2006. Each group was sampled over a 24-hour period.
Fig. 1. The sampling position and its relative location.
G.-C. Fang et al. / Powder Technology 185 (2008) 223–230
2.2. Partisol Model 2300 Speciaton Sampler (RP2300) Particulate matter (PM2.5 and PM10) were gathered using the Partisol Model 2300 Speciaton Sampler (RP2300) (Rupprecht & Patashnick Co., USA) which incorporated a four-channel sampling platform for particulate matter and related gaseous species (Fig. 2). Honeycomb denuders (HCs) are small, rugged, and have a large internal surface area. These HCs are 47 mm in diameter and 38 mm long. Their internal surface area of 508 cm2 has 212 hexagonal flow channels that are 2 mm wide on each side. The entire ChemComb cartridge is b30 cm long [9]. The HCs, which are made of glass, avoid gas losses
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resulting from nitric acid and ammonia adsorption on the epoxy resin sometimes used in annular denuders [10]. The use of the same material throughout the denuder eliminates cracking that can occur as a result of large temperature changes. These HCs are efficient collectors of inorganic gases, such as HONO, HNO3 and NH3, via different coatings applied in the laboratory. Denuders can be coated with different substances following each use. A sodium carbonate/glycerol coating is generally utilized to collect acidic gases such as SO2, HONO and HNO3. A second denuder in series is frequently coated with a citric acid/glycerol solution for collecting basic gases such as NH3. Ion chromatography is commonly used as the method for
Fig. 2. Diagram of sampling system (RP2300) used in this study.
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analyzing those chemical compounds. The four-stage 47 mm in diameter filter pack is made of Teflon to minimize interference. Each stage of the filter holder does not need a collection filter. A typical application of the ChemComb cartridge involves the following three filters, each 47 mm in diameter: (1) a 2.0 μm pore-size Teflon filter for collecting fine PM; (2) a glass–fiber filter coated with sodium carbonate (Na2CO3) for collecting nitric acid (HNO3); and, (3) a glass–fiber filter coated with citric acid for collecting ammonia (NH3). The sampling device is a single cartridge containing a wellcharacterized inlet with a PM2.5 or PM10 impactor, with up to two HCs for removing and collecting selected gases, and a fourstage filter pack 47 mm in diameter for collecting particle-related components. The PM2.5 inlets can handle flow rates of 10 and 16.7 L/min; the PM10 inlet can handle flow rates up to 10 L/min. The mass flow controllers, which are controlled by the sampler microprocessor, maintain sample streams at a constant volumetric flow rate via ambient temperature and pressure sensors. Furthermore, systems with honeycomb denuders operate at 10 L/min to maximize denuder collection efficiency. These units can also be configured without honeycomb denuders and operated as multistage filter packs for PM2.5 or PM10. This study utilized the filter pack system fitted with an RP2300 sampler to collect PM2.5 and PM10 only. The flow rates of the PM2.5 and PM10 inlets were both 10 L/min. Uncoated quartz filters in a filter pack system were employed to sample PM2.5 and PM10. 2.3. Mass measurements The filter utilized to collect PM2.5 and PM10 was a quartz–fiber filter (2500QAT-UP, Pall) with a diameter of 47 mm (Pall Corporation, NY, USA). The filter had a collection efficiency of 99.999% for particulates N 0.5 μm and 99.99% for particulates b 0.3 μm. The filters were first conditioned for 24 h in an electric chamber under 50 ± 5% humidity and 25 ± 5 °C before on and off weighing. The particulate mass measurement method for weighing after sampling in atmosphere allowed the filters to equilibrate. This procedure comprised the following steps. 1. Weighing after achieving moisture equilibrium (W0). 2. Collecting atmospheric particulates in the field and recording sampling time (T) and sampler flow rate (Q). 3. Reweighing after achieving moisture equilibrium (W1). The particulate concentration was derived by concentration ¼
W1 W0 ðmgÞ : T ðminÞ QðL=minÞ
Additionally, an analytical microbalance (Sartorius MC-5 balance) was employed during this weighting process, with a minimum detectable balance mass of 1 μg and maximum of 5 g. 2.4. Meteorological analysis Meteorological analysis was performed using a WatchDog weather station (Model 525) (Spectrum Technologies, Inc., USA).
The weather station generated atmospheric pressure, wind speed, wind direction, temperature and relative humidity data. 2.5. Ionic species analysis Following final weighing, filters were analyzed for ionic species. The filters analyzed for ionic species filters were placed into 25 mL bottles for each sampling group. Distilled de-ionized water was added to each bottle and the bottles were sent for ultrasonic processing lasting roughly 90 min. Ion chromatography (DIONEX DX-100) was utilized to examine the following water-soluble ions in the RP2300 sampler: F−, Cl−, NO2−, NO3−, PO43−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+. 2.6. Quality control 2.6.1. Blank test A blank test assesses background contamination resulting from analysis. Background contamination was routinely monitored using operational blanks (unexposed filters) processed simultaneously with field samples. In this study, background contamination was insignificant and therefore ignored. Concentrations of background contaminations were 0.02, 0.02, 0.04, 0.03, 0.06, 0.04, 0.04, 0.03, 0.06, 0.06, and 0.05 μg/m3 for F−, Cl−, NO2−, NO3−, PO43−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+, respectively. 2.6.2. Detection limit The detection limit is the lowest concentration level that can be detected as statistically different. Detection limits for elements in this study were as follows: F−, 0.013 mg/L; Cl−, 0.010 mg/L; NO2−, 0.020 mg/L; NO3−, 0.015 mg/L; PO43−, 0.020 mg/L; SO42−, 0.015 mg/L; Na+, 0.015 mg/L; NH4+, 0.021 mg/L; K+, 0.023 mg/L; Mg2+, 0.016 mg/L; and, Ca2+, 0.024 mg/L. 3. Results and discussion 3.1. Sampling information Table 1 lists sampling information, including the sampling date, and PM2.5, PM10 and meteorological data for sampling site during March 4 to April 2, of 2006. Average PM2.5 and PM10 concentrations were 66.33 and 108.28 μg/m3, respectively. The average ratio of PM2.5/PM10 was 62%. This analytical result demonstrates that the main component in the PM10 was PM2.5 at this sampling site. Average pressure, temperature, relative humidity and wind speed was 1011.3 hpa, 20.4 °C, 75.3% and 3.8 m/s, respectively, at the sampling site. In comparison, the average ratios of PM2.5/PM10 were 77% for urban (Seoul, Korea), 76% for suburban (Basel, Switzerland) and 71% for rural (Chaumont, Switzerland) areas [11,12]. Comparison with these areas suggests that average PM2.5/PM10 ratios in this study were lower than those in urban (Seoul, Korea), suburban (Basel, Switzerland) and rural (Chaumont, Switzerland) areas. The average PM10 concentration was 108.28 μg/m3 during the sampling period. However, the PM10 concentration in this study was 44.07–161.61 μg/m3. The average PM10 concentration for the six sample groups (all N 125 μg/m3) was 149.38 μg/m3. This
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Table 1 Sampling information for particulate mass and meteorological conditions at this sampling site during March 4 to April 2, 2006 Date
Sampling no.
PM2.5 (μg/m3)
PM10 (μg/m3)
PM2.5/PM10
P (hpa)
Temp. (°C)
RH (%)
WS (m/s)
PWD
4-Mar 7-Mar 8-Mar 10-Mar 11-Mar 12-Mar 14-Mar 15-Mar 16-Mar 17-Mar 18-Mar 19-Mar 20-Mar 21-Mar 22-Mar 30-Mar 31-Mar 1-Apr 2-Apr
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Average S.D.
83.73 63.29 100.56 89.56 59.47 28.01 55.32 91.11 65.63 57.80 52.27 65.51 74.14 68.52 48.82 90.03 54.72 77.02 46.39 66.33 20.84
152.36 96.32 156.78 128.63 87.36 44.07 82.71 140.95 102.18 120.81 84.42 155.93 104.70 93.05 68.45 161.61 106.55 121.80 78.10 108.28 35.87
0.55 0.66 0.64 0.70 0.68 0.64 0.67 0.65 0.64 0.48 0.62 0.42 0.71 0.74 0.71 0.56 0.51 0.63 0.59 0.62 0.10
1015.8 1012.7 1013.2 1012.2 1009.1 1012.5 1017.5 1013.1 1009.8 1009.2 1009.6 1012.1 1011.5 1008.3 1006.6 1013.9 1011.7 1009.2 1009.4 1011.3 2.6
17.4 18.9 18.9 20.1 22.0 14.9 15.1 18.7 21.1 22.2 24.2 19.5 19.5 19.7 23.2 21.2 21.9 25.0 24.9 20.4 3.0
80.7 85.0 84.2 77.2 69.2 72.4 71.1 77.5 74.5 75.9 73.4 61.5 79.8 83.0 79.5 67.4 71.3 69.5 81.2 75.3 6.7
3.3 5.6 3.9 4.3 2.5 10.3 5.0 3.3 4.3 2.5 4.1 6.6 1.9 2.7 2.2 3.1 2.1 2.4 2.5 3.8 2.3
NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW ES NNW NNW WSW NNW – –
P: Atmospheric pressure; Temp.: Temperature; RH: Relative humidity; WS: Wind speed; PWD: Prevalent wind direction.
average was roughly 12% higher than the standard value for PM10 concentrations (daily average, 125 μg/m3) [13]. The PM10 concentrations for the remaining five sampling groups (average, 111.21 μg/m3) were all N100 μg/m3. These values, which were below the Taiwan air quality standard, were all around 125 μg/m3. This experimental result demonstrates that air quality at the sampling site was considerable and detrimental to human health. Average daytime and nighttime PM10 concentrations were 35.9 and 27.7 μg/m3, respectively, during 1998 [14]. These analytical results suggest that the PM10 concentration increased significantly compared to those eight years before for both daytime and nighttime sampling periods. Highway construction at this sampling site accounted for this increased PM10 concentration. 3.2. Ionic specie concentrations in PM2.5 and PM10 Table 2 lists the ionic concentrations for PM2.5 and PM10. The average concentrations for ionic species of Cl−, NO2−, NO3−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+ were 1.52, 3.28, 1046, 12.63, 0.26, 7.87, 0.54, 0.07, 0.28 μg/m3 in PM2.5, respectively. Furthermore, average concentrations for ionic species of Cl−, NO2−, NO3−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+ were 2.97, 3.79, 17.28, 15.59, 1.24, 9.45, 0.61, 0.34 and 1.38 μg/m3 in PM10, respectively. However, levels of ionic species F− and PO43− were undetectable in fractions from ion chromatography (DIONEX DX-100 Ion chromatography). 3.3. Main ionic species in PM2.5 and PM10 Fig. 3 shows the average concentration percentages of Cl−, NO2−, NO3− , SO42− , Na+, NH4+, K+, Mg2+ and Ca2+ in PM2.5 and PM10. The analytical results demonstrate that average concentration percentages of ionic species Cl−, NO2−, NO3−, SO42−, Na+,
NH4+, K+, Mg2+ and Ca2+ were 4%, 9%, 28%, 35%, 1%, 21%, 1% and 0%, respectively, in PM2.5. The average concentration percentages of ionic species Cl−, NO2− , NO3−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+ were 6%, 7%, 32%, 30%, 2%, 18%, 1% and 1%, respectively in PM10. The three predominant ionic species were NO3−, SO42− and NH4+ at this sampling site. 3.4. Non-parametric (Spearman) correlation analysis The non-parametric (Spearman) correlation analysis was applied to examine the correlations between area pollutants and environment factors. Tables 3 and 4 list the correlation analysis of the elements and data. Table 3 shows the correlation between mass particle pollutants (PM2.5 and PM10) atmospheric pressure, temperature, relative humidity and wind speed. The analytical results suggest that the particulate mass was weakly correlated with atmospheric pressure, wind speed, temperature and relative humidity. This experimental finding demonstrates that meteorological conditions do not influence particulate mass concentrations (PM2.5 and PM10) at the sampling site. Table 4(a) and (b) list the ionic species (Cl−, NO2−, NO3−, SO42−, + Na , NH4+, K+, Mg2+ and Ca2+) in PM2.5 and PM10 that correlated with atmospheric pressure, temperature, relative humidity and wind speed. The ionic species of Cl− in PM2.5 were strongly correlated (rsp = 0.75) with relative humidity (Table 4(a)). The ionic species of NH4+ in PM2.5 was strongly correlated (rsp = 0.63 and 0.72) with NO3− and SO42−. The ionic species Mg2+ in PM2.5 was strongly correlated (rsp = 0.75) with SO42−. Analytical results also demonstrate that the ionic species in PM2.5 are weakly correlated with atmospheric pressure, wind speed, temperature and relatively humidity. The ionic species Cl− in PM10 was strongly correlated (rsp = 0.80 and 0.70) with Na+ and Mg2+
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Table 2 Ionic species concentrations of PM2.5 and PM10 at this sampling site Sampling PM2.5 (μg/m3) no. Cl− NO−2 NO−3 F−
PO3− SO2− Na+ 4 4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Average S.D.
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
2.43 1.54 2.61 1.64 0.89 1.15 1.22 2.38 1.17 1.39 1.02 0.88 2.33 2.06 1.14 1.20 1.05 1.19 1.66 1.52 0.55
5.93 2.54 3.31 4.00 2.18 1.07 2.92 3.94 4.23 3.11 1.62 3.21 2.89 2.01 5.63 2.40 2.71 4.87 3.69 3.28 1.25
11.71 7.68 11.26 10.57 6.68 3.28 10.84 14.25 13.90 8.98 8.89 6.47 14.58 15.32 10.40 13.46 8.10 14.35 8.10 10.46 3.23
PM10 (μg/m3)
16.02 12.23 16.81 16.80 15.30 5.53 8.99 14.11 13.45 11.26 12.02 17.74 9.33 10.20 8.83 15.17 12.32 13.08 10.82 12.63 3.16
NH+4
K+
Mg2+ Ca2+ F−
0.31 9.97 0.36 0.05 0.23 6.37 0.84 0.03 0.19 11.22 0.18 0.05 0.20 9.59 0.43 0.06 0.20 7.20 0.89 0.19 0.43 1.91 0.29 0.02 0.35 6.29 0.43 0.02 0.25 10.50 0.54 0.04 0.20 9.50 0.24 0.05 0.29 6.12 0.76 0.06 0.27 6.27 1.11 0.03 0.42 7.53 1.21 0.30 0.45 8.66 0.54 N.D. 0.19 9.43 0.24 0.01 0.14 5.99 0.35 0.02 0.24 10.38 0.56 0.03 0.14 7.20 0.34 0.14 0.18 9.25 0.24 0.04 0.22 6.11 0.77 0.03 0.26 7.87 0.54 0.07 0.09 2.21 0.30 0.07
0.26 0.19 0.31 0.33 0.21 0.51 0.12 0.08 0.17 0.19 0.15 1.15 0.05 0.13 0.23 0.35 0.46 0.35 0.15 0.28 0.24
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
Cl−
NO−2 NO−3
PO3− SO2− Na+ 4 4
NH+4
K+
Mg2+ Ca2+
7.13 3.67 4.09 2.95 1.33 1.32 1.61 5.62 1.66 4.82 2.32 3.18 3.40 2.26 1.53 2.69 2.05 2.42 2.45 2.97 1.51
0.93 3.33 2.32 5.46 3.21 3.64 3.77 4.24 3.90 7.50 3.84 4.53 3.58 0.79 5.50 2.68 3.57 3.80 5.47 3.79 1.53
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
14.70 8.08 14.00 11.03 8.13 1.93 6.90 15.25 11.21 8.69 8.37 8.75 8.18 9.64 5.68 12.18 8.23 11.66 6.89 9.45 3.18
0.45 0.83 0.57 0.64 1.06 0.17 0.22 0.63 0.44 1.05 1.17 1.42 0.75 0.21 0.23 0.41 0.37 0.42 0.60 0.61 0.35
0.55 0.27 0.30 0.37 0.22 0.18 0.09 0.47 0.19 0.81 0.41 0.70 0.22 0.08 0.13 0.41 0.36 0.38 0.28 0.34 0.19
21.63 11.99 16.52 17.84 11.17 4.69 13.26 27.61 19.69 22.93 17.08 15.48 16.55 17.44 12.20 26.67 17.25 25.62 12.61 17.28 5.68
22.52 15.30 23.35 19.59 18.03 6.15 9.82 20.24 16.30 15.55 15.46 23.06 10.19 10.99 9.25 17.62 15.30 14.87 12.54 15.59 4.79
2.49 1.30 1.07 1.41 0.78 0.43 0.29 2.00 0.62 2.82 1.28 1.99 1.13 0.46 0.47 1.27 1.11 1.51 1.17 1.24 0.68
1.26 0.45 0.83 0.88 0.75 0.76 0.73 1.51 0.76 2.44 1.14 4.08 0.92 0.53 0.71 3.36 2.64 1.67 0.74 1.38 1.00
※F− and PO3− 4 levels were below the detection limit in the fractions from the ion chromatography (DIONEX DX-100 Ion chromatography).
(Table 4(b)). This analytical result shows that ionic species Cl−, Na+ and Mg2+ may originate from similar sources as PM10. The correlation coefficients of ionic species had an rsp value of 0.92, between those of Na+ and Mg2+ in PM10, whereas ionic species Ca2+ was strongly correlated with Na+ and Mg2+ in PM10. Ionic species NH4+ was strongly correlated (rsp = 0.83 and 0.75) with NO3− and SO42− in PM10. These analytical results indicate that ionic species in PM10 were weakly correlated with atmospheric conditions of pressure, wind speed, temperature and relative humidity at this sampling site. 3.5. Principal component analysis Principal component analysis with Varimax rotation and retention of principal components with eigenvalues N 1 (SPSS 10.0) was utilized to identify possible pollutant sources.
Table 5 lists the PCA results for PM2.5 and PM10 ionic species concentrations during the sampling period. These PCA results suggest that two factors account for the majority of data variance; one element for each factor was selected as a tracer. For the case where of PM2.5, factor 1 explained 40.58% of total variance of data and had a high loading for NO3− (0.78) and SO42− (0.71) and NH4+ (0.96), providing a possible indicator of secondary aerosols. These ionic species were most likely deriving from traffic emissions. The large volume of traffic on the highway near the sampling site was thus the principal reason for these analytical results. Factor 2 is related to re-suspended highway dust, and has high loadings for Mg2+ (0.93) and Ca2+ (0.82). Furthermore, PM10 was 51.99% for factor 1. High loadings of NH4+ (0.96), NO3− (0.80), Cl− (0.81), and SO42− (0.78) were from secondary aerosol (traffic) and marine salt (Cl−). Furthermore, Factor 2 had high loadings for Mg2+ (0.83), K+ (0.77) and NO2− (0.70) derived from re-suspended
Fig. 3. Average percentage of ionic species in various particle sizes (PM2.5 and PM10) at the sampling site.
G.-C. Fang et al. / Powder Technology 185 (2008) 223–230 Table 3 Non-parametric (Spearman) correlation analysis results for different particle sizes and meteorological conditions
PM2.5 PM10 P Temperature RH WS
PM2.5
PM10
1 0.84⁎⁎ 0.40 − 0.26 0.14 0.01
1 0.44 − 0.14 − 0.10 0.01
P
Temperature
1 − 0.74⁎⁎ − 0.01 0.54
RH
1 −0.19 −0.59
1 −0.08
WS
1
⁎⁎Correlation is significant at the 0.01 level (2-tailed).
highway dust (Mg2+ and K+) and secondary aerosols (NO2−), the most likely source of which was traffic. 4. Conclusion
Table 5 The PCA results for PM2.5 and PM10 ionic species concentrations at this sampling site Variables
PM2.5
Cl− NO−2 NO−3 SO2− 4 Na+ NH+4 K+ Mg2+ Ca2+ Eigenvalue Proportion of variance (%) Cumulative (%) Origin
This study obtained the following conclusions. 1. The predominant component in PM10 was PM2.5. The average ratio of PM2.5/PM10 was 62% at this sampling site, and the average PM2.5/PM10 ratio was less obtained by studies conducted in urban (Seoul, Korea), suburban (Basel, Chaumont) and rural (Chaumont, Chaumont) areas. 2. Average concentrations of ionic species NO3−, SO42− and NH4+ in PM2.5 were 10.46, 12.63 and 7.87 μg/m3, respectively. Analytical results indicate that average concentrations of
229
PM10
Factor 1
Factor 2
Factor 1
Factor 2
0.61 0.63 0.78 0.71 – 0.96 – – – 3.65 40.58
– – – 0.64 0.37 – 0.63 0.93 0.82 2.33 25.86
0.81 – 0.80 0.78 0.65 0.96 0.10 0.51 0.30 4.68 51.99
0.22 0.70 0.14 0.31 0.68 – 0.77 0.83 0.65 1.90 21.13
40.58 Atmospheric reactions, Secondary aerosols
66.44 Dust/ soil
51.99 Atmospheric reactions, Secondary aerosols, Marine salt
73.12 Marine salt, Dust/soil, Secondary aerosols
Note: Only loading factor values with moduli N0.1 and factor loading values with moduli N0.7 are in bold.
ionic species NO3−, SO42− and NH4+ in PM10 were 17.28, 15.59 and 9.48 μg/m3, respectively.
Table 4 (a)–(b) Non-parametric (Spearman) correlation analysis results for different particle sizes for ionic species and meteorological conditions Cl−
NO−2
NO−3
SO2− 4
Na+
NH+4
K+
Mg2+
Ca2+
P
Temperature
RH
WS
Cl NO−2 NO−3 SO2− 4 Na+ NH+4 K+ Mg2+ Ca2+ P Temperature RH WS
1 0.30 0.58 0.06 0.08 0.51 − 0.32 − 0.22 − 0.43 0.37 − 0.39 0.75⁎⁎ − 0.08
1 0.33 0.31 − 0.26 0.31 − 0.29 0.24 0.04 0.03 0.11 0.19 − 0.17
1 0.01 −0.16 0.63⁎ −0.50 −0.24 −0.45 0.02 −0.02 0.25 −0.35
1 − 0.13 0.72⁎⁎ 0.12 0.75⁎⁎ 0.40 0.32 − 0.05 − 0.17 0.20
1 − 0.15 0.46 − 0.04 − 0.18 0.45 − 0.52 − 0.15 0.42
1 − 0.31 0.32 0.02 0.42 − 0.27 0.10 0.03
1 0.24 − 0.14 − 0.02 0.17 − 0.24 0.12
1 0.40 0.00 0.13 − 0.32 − 0.09
1 0.12 0.05 −0.45 0.18
1 − 0.74⁎⁎ − 0.01 0.54
1 −0.19 −0.59
1 − 0.08
1
PM10
Cl−
NO−2
NO−3
SO2− 4
Na+
NH+4
K+
Mg2+
Ca2+
P
Temperature
RH
WS
Cl− NO−2 NO−3 SO2− 4 Na+ NH+4 K+ Mg2+ Ca2+ P Temperature RH WS
1 − 0.02 0.50 0.59 0.80⁎⁎ 0.61⁎ 0.47 0.70⁎⁎ 0.40 0.39 − 0.22 0.42 0.01
1 0.02 − 0.12 0.26 − 0.25 0.27 0.22 0.12 − 0.33 0.40 − 0.15 − 0.01
1 0.40 0.56 0.83⁎⁎ −0.01 0.57 0.61⁎ 0.13 0.14 −0.10 −0.22
1 0.58 0.75⁎⁎ 0.54 0.68⁎ 0.49 0.34 − 0.11 − 0.06 0.23
1 0.53 0.62⁎ 0.92⁎⁎ 0.63⁎ 0.13 0.15 0.01 − 0.04
1 0.12 0.56 0.53 0.32 − 0.10 0.02 0.02
1 0.57 0.28 − 0.10 0.21 − 0.03 0.07
1 0.82⁎⁎ 0.23 0.15 − 0.22 0.01
1 0.21 0.14 −0.54 −0.14
1 − 0.74⁎⁎ − 0.01 0.54
1 −0.19 −0.59
1 − 0.08
1
PM2.5 −
⁎Correlation is significant at the 0.05 level (2-tailed). ⁎⁎Correlation is significant at the 0.01 level (2-tailed).
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3. Non-parametric (Spearman) correlation analysis results indicate that particle mass was weakly correlated with atmospheric pressure, wind speed, temperature and relative humidity. 4. Non-parametric (Spearman) correlation analysis results demonstrate that ionic species in PM10 and PM2.5 were weakly correlated with wind speed, temperature and relative humidity. 5. Ionic species Cl−, Na+, Mg2+ may be from similar sources in the form of PM10 at this sampling site. 6. Ionic species NH4+ was strongly correlated (rsp = 0.63 and 0.72; rsp = 0.63 and 0.72) with NO3− and SO42− in PM2.5 and PM10, respectively. 7. Principal component analysis demonstrates that the soil, secondary aerosols and marine salt sources were likely the predominant pollutant source at this sampling site.
[4] [5]
[6]
[7]
[8]
[9]
Acknowledgments The authors would like to thank the National Science Council of the Republic of China, Taiwan, for financially supporting this research under Contract No. NSC 96-2628-E-241-001-MY3. Ted Knoy is appreciated for his editorial assistance. References [1] G.C. Fang, C.N. Chang, Y.S. Wu, D.G. Yang, C.C. Chu, Characterization of chemical species in universal sampler (PM2.5 and PM2.5–10) aerosols in suburban area of central Taiwan, Toxicological and Environmental Chemistry 71 (1999) 341–355. [2] B. Ostro, L. Chestnut, Assessing the health benefits of reducing particulate matter air pollution in the United States, Environmental Research 76 (1998) 94–106. [3] G.C. Fang, C.N. Chang, C.C. Chu, Y.S. Wu, P.C.P., I.L. Yang, M.H. Chen, Characterization of particulate, metallic elements of TSP, PM2.5 and
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PM2.5–10 aerosols at a farm sampling site in Taiwan, Taichung, The science of the Total Environment 308 (2003) 157–166. L.Y. Chen, W.S. Kwok, Vertical dispersion of suspended particulates in urban area of Hong Kong, Atmospheric Environment 34 (2000) 4403–4412. M.O. Ohlstrom, K.E.J. Lehitinen, M. Moisio, J.K. Jokiniemi, Fine-particle emissions of energy production in Finland, Atmospheric Environment 34 (2000) 3701–3711. A. Alastuey, X. Querol, S. Rodriguez, F. Plana, A. Lopez-Soler, C. Ruiz, E. Mantilla, Monitoring of atmospheric particulate matter around sources of secondary inorganic aerosol, Atmospheric Environment 38 (2004) 4979–4992. R.M. Harrison, J.P. Shi, M.R. Jones, Continuous measurements of aerosol physical properties in the urban atmosphere, Atmospheric Environment 33 (1999) 1037–1047. W. Alfred, H.C. Hansson, Formation of ammonium chloride particles from hydrogen chloride and ammonia in the atmosphere, Journal of Aerosol Science 26 (1995) 463–464. P. Koutrakis, C. Sioutas, S.T. Ferguson, J.M. Wolfson, J.D. Mulik, Development and evaluation of a glass honeycomb denuder/filter pack system to collect atmospheric gases and particles, Environmental Science & Technology 27 (1993) 2497–2501. C. Sioutas, P.Y. Wang, S.T. Ferguson, P. Koutrakis, J.D. Mulik, Laboratory and field evaluation of an improved glass honeycomb denuder/filter pack sampler, Atmospheric Environment 30 (1996) 885–895. K.H. Kim, V.K. Mishra, C.H. Kang, K.C. Choi, Y.J. Kim, D.S. Kim, The ionic compositions of fine and coarse particle fractions in the two urban areas of Korea, Journal of Environmental Management 78 (2006) 170–182. C. Hueglin, R. Gehrig, U. Baltensperger, M. Gysel, C. Monnd, H. Vonmonta, Chemical characterisation of PM2.5, PM10 and coarse particles at urban, near-city and rural sites in Switzerland, Atmospheric Environment 39 (2005) 637–651. Environmental Protection Administration, Taiwan, R.O.C.. Air Quality Standards. w3.epa.gov.tw/epalaw/docfile/040060.pdf. G.C. Fang, C.N. Chang, Y.S. Wu, P.P.C. Fuc, K.F. Chang, D.G. Yang, The characteristic study of TSP, PM2.5∼10 and PM2.5 in the rural site of central Taiwan, The Science of the Total Environment 232 (1999) 177–184.
Powder Technology 185 (2008) 223 – 230 www.elsevier.com/locate/powtec
Characteristics and source identification study of ambient suspended particulates and ionic pollutants in an area abutting a highway Guor-Cheng Fang ⁎, Yuh-Shen Wu, Jie-Feng Lee, Chia-Chi Chang Air Toxic and Environmental Analysis Laboratory, Department of Environmental Engineering, HungKuang University, No.34, Chung-Chie Rd., Sha-Lu, Taichung 43302, Taiwan, ROC Received 30 January 2007; received in revised form 15 October 2007; accepted 18 October 2007 Available online 1 November 2007
Abstract Ambient suspended particulates in an area abutting a highway were gathered using a Partisol Model 2300 Speciaton Sampler (RP2300). Major ionic species with different particle sizes and with possible sources close to the sampling site were evaluated using Principal Component Analysis (PCA). Observational results indicate that average PM2.5 and PM10 concentrations were 66.33 and 108.28 μg/m3, respectively. The average ratio of PM2.5/PM10 was 62% at this sampling site, whereas the average PM2.5/PM10 ratio in this study was less than those in urban (Seoul, Korea), + suburban (Basel, Switzerland) and rural (Chaumont, Switzerland) settings. Average concentrations for ionic species of NO−3 , SO2− 4 and NH4 were + 10.46, 12.63 and 7.87 μg/m3 in PM2.5, respectively. Average concentrations for ionic species of NO−3 , SO2− and NH were 17.28, 15.59 and 4 4 9.48 μg/m3 in PM10, respectively. Principal component analysis identified soil, secondary aerosols and marine salt as possible major pollutant sources at this sampling site. © 2007 Elsevier B.V. All rights reserved. Keywords: PCA; Spearman; Highway; Ionic species; PM
1. Introduction Highways connect urban, suburban and rural areas. However, highways also generate atmospheric pollutant-related problems and impact local ecosystems. Particulate air pollution describes both solid and liquid particles, such as diesel soot, road and agricultural dust, and particles resulting from manufacturing processes, directly emitted into the air [1]. Particles are also generated through photochemical reactions involving pollutant gases, such as sulfur and nitrogen oxides, which are byproducts of fuel combustion [2]. Most trip mileage in Taiwan is logged by taxis, which use diesel as a low-cost fuel. Consequently, PM10 and PM2.5 concentrations have become the principal source of streetlevel air pollution [3]. Large particles are markedly influenced by gravity, whereas fine particles are influenced by diffusion more than gravity [4]. Particles with aerodynamic diameters b10 μm ⁎ Corresponding author. Tel.: +886 4 2631 8652x1111; fax: +886 4 2350 2102. E-mail address: [email protected] (G.-C. Fang). 0032-5910/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.powtec.2007.10.020
are known as respiratory particulates or particulate matter10 (PM10), whereas PM2.5 denotes fine particles with aerodynamic diameters of b 2.5 μm [5]. However, atmospheric aerosols represent a multi-component system of materials in solid or liquid states (excluding pure water) that enter the air naturally or anthropogenically [6]. Atmospheric aerosols in PM10 are generally dominated by particles from the following three sources: (1) primary fine particles emitted from industrial sources and road vehicles; (2) secondary aerosols, predominantly ammonium sulfate and ammonium nitrate—these secondary aerosol particles are generally transported over long ranges and have relatively weak spatial gradients; and, (3) wind blown soil and re-suspended street dust, which are largely coarse (2.5– 10 μm) in particle fraction [7]. Aerosols can be classified as primary and secondary pollutants based on their source. Primary aerosols are usually emitted in particulate form directly from sources. Secondary aerosols comprise particles generated in the atmosphere that are predominantly submicron size and produced by heterogeneous or homogeneous chemical reactions. Sulfate is a common secondary pollutant. Numerous studies have proved
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that sulfur dioxide is converted to sulfate via oxidation hydrolysis [8]. The SO2 is generated by combustion of coal and fuel burned by industrial plants. The principal sources of NOx are fossil fuel combustion for industrial processes, electricity and automobile emissions, which are responsible for roughly 50% of such emissions. Atmospheric nitrogen, particularly NH3 and NO4+ compounds, have significant potential to impact adversely the environment. Atmospheric nitrogen compounds have numerous anthropogenic and natural sources. These nitrogen compounds are transported by and transformed in the atmosphere prior to deposition in sensitive ecosystems. Base cations such as Ca2+, K+ and Mg2+ are necessary plant nutrients. Their associated anions, principally oxides, hydroxides, carbonates and silicates, can decrease air precipitation acidity and increase soil base saturation. Base cations primarily derive from mechanical erosion and wind mobilization of soil particles, and particles from volcanic eruptions, forest fires, industrial processes, biological mobilization, or combustion of fuels such as wood or peat. The primary anthropogenic sources of mineral dust are power production, cement, ferrous and other industries. Marine aerosols, which are transferred from marine to continental areas by monsoon, are considered the predominant source of Na. This study characterizes ambient air particles at a sampling site abutting a major highway. Total atmospheric aerosols were
sampled using a Partisol Model 2300 Speciaton Sampler (RP2300). Moreover, ion chromatography (DIONEX DX100) was utilized to examine ionic species for PM2.5 particles (aerodynamic diameters b2.5 μm) and PM10 particles (aerodynamic diameters b10 μm) at the sampling site. Finally, the predominant ionic species were identified based on diameter differences and possible sources near the sampling site via Principal Component Analysis (PCA). 2. Experimental methods 2.1. Sampling program Fig. 1 presents the sampling location utilized in this study. Ambient particle concentrations were sampled on the roof of the Medical and Industrial Building at Hungkuang University, an eight-story building (25 m height) located on the top of Da Du Mountain. Site elevation is 500 m. The sampling location was thus close to both a major highway and the Taiwan Strait, which were located 50 m and 15 km from the sampling site, respectively. The Partisol Model 2300 Speciaton Sampler (RP2300) was utilized, and ran from March 4 to April 2, 2006. Each group was sampled over a 24-hour period.
Fig. 1. The sampling position and its relative location.
G.-C. Fang et al. / Powder Technology 185 (2008) 223–230
2.2. Partisol Model 2300 Speciaton Sampler (RP2300) Particulate matter (PM2.5 and PM10) were gathered using the Partisol Model 2300 Speciaton Sampler (RP2300) (Rupprecht & Patashnick Co., USA) which incorporated a four-channel sampling platform for particulate matter and related gaseous species (Fig. 2). Honeycomb denuders (HCs) are small, rugged, and have a large internal surface area. These HCs are 47 mm in diameter and 38 mm long. Their internal surface area of 508 cm2 has 212 hexagonal flow channels that are 2 mm wide on each side. The entire ChemComb cartridge is b30 cm long [9]. The HCs, which are made of glass, avoid gas losses
225
resulting from nitric acid and ammonia adsorption on the epoxy resin sometimes used in annular denuders [10]. The use of the same material throughout the denuder eliminates cracking that can occur as a result of large temperature changes. These HCs are efficient collectors of inorganic gases, such as HONO, HNO3 and NH3, via different coatings applied in the laboratory. Denuders can be coated with different substances following each use. A sodium carbonate/glycerol coating is generally utilized to collect acidic gases such as SO2, HONO and HNO3. A second denuder in series is frequently coated with a citric acid/glycerol solution for collecting basic gases such as NH3. Ion chromatography is commonly used as the method for
Fig. 2. Diagram of sampling system (RP2300) used in this study.
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G.-C. Fang et al. / Powder Technology 185 (2008) 223–230
analyzing those chemical compounds. The four-stage 47 mm in diameter filter pack is made of Teflon to minimize interference. Each stage of the filter holder does not need a collection filter. A typical application of the ChemComb cartridge involves the following three filters, each 47 mm in diameter: (1) a 2.0 μm pore-size Teflon filter for collecting fine PM; (2) a glass–fiber filter coated with sodium carbonate (Na2CO3) for collecting nitric acid (HNO3); and, (3) a glass–fiber filter coated with citric acid for collecting ammonia (NH3). The sampling device is a single cartridge containing a wellcharacterized inlet with a PM2.5 or PM10 impactor, with up to two HCs for removing and collecting selected gases, and a fourstage filter pack 47 mm in diameter for collecting particle-related components. The PM2.5 inlets can handle flow rates of 10 and 16.7 L/min; the PM10 inlet can handle flow rates up to 10 L/min. The mass flow controllers, which are controlled by the sampler microprocessor, maintain sample streams at a constant volumetric flow rate via ambient temperature and pressure sensors. Furthermore, systems with honeycomb denuders operate at 10 L/min to maximize denuder collection efficiency. These units can also be configured without honeycomb denuders and operated as multistage filter packs for PM2.5 or PM10. This study utilized the filter pack system fitted with an RP2300 sampler to collect PM2.5 and PM10 only. The flow rates of the PM2.5 and PM10 inlets were both 10 L/min. Uncoated quartz filters in a filter pack system were employed to sample PM2.5 and PM10. 2.3. Mass measurements The filter utilized to collect PM2.5 and PM10 was a quartz–fiber filter (2500QAT-UP, Pall) with a diameter of 47 mm (Pall Corporation, NY, USA). The filter had a collection efficiency of 99.999% for particulates N 0.5 μm and 99.99% for particulates b 0.3 μm. The filters were first conditioned for 24 h in an electric chamber under 50 ± 5% humidity and 25 ± 5 °C before on and off weighing. The particulate mass measurement method for weighing after sampling in atmosphere allowed the filters to equilibrate. This procedure comprised the following steps. 1. Weighing after achieving moisture equilibrium (W0). 2. Collecting atmospheric particulates in the field and recording sampling time (T) and sampler flow rate (Q). 3. Reweighing after achieving moisture equilibrium (W1). The particulate concentration was derived by concentration ¼
W1 W0 ðmgÞ : T ðminÞ QðL=minÞ
Additionally, an analytical microbalance (Sartorius MC-5 balance) was employed during this weighting process, with a minimum detectable balance mass of 1 μg and maximum of 5 g. 2.4. Meteorological analysis Meteorological analysis was performed using a WatchDog weather station (Model 525) (Spectrum Technologies, Inc., USA).
The weather station generated atmospheric pressure, wind speed, wind direction, temperature and relative humidity data. 2.5. Ionic species analysis Following final weighing, filters were analyzed for ionic species. The filters analyzed for ionic species filters were placed into 25 mL bottles for each sampling group. Distilled de-ionized water was added to each bottle and the bottles were sent for ultrasonic processing lasting roughly 90 min. Ion chromatography (DIONEX DX-100) was utilized to examine the following water-soluble ions in the RP2300 sampler: F−, Cl−, NO2−, NO3−, PO43−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+. 2.6. Quality control 2.6.1. Blank test A blank test assesses background contamination resulting from analysis. Background contamination was routinely monitored using operational blanks (unexposed filters) processed simultaneously with field samples. In this study, background contamination was insignificant and therefore ignored. Concentrations of background contaminations were 0.02, 0.02, 0.04, 0.03, 0.06, 0.04, 0.04, 0.03, 0.06, 0.06, and 0.05 μg/m3 for F−, Cl−, NO2−, NO3−, PO43−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+, respectively. 2.6.2. Detection limit The detection limit is the lowest concentration level that can be detected as statistically different. Detection limits for elements in this study were as follows: F−, 0.013 mg/L; Cl−, 0.010 mg/L; NO2−, 0.020 mg/L; NO3−, 0.015 mg/L; PO43−, 0.020 mg/L; SO42−, 0.015 mg/L; Na+, 0.015 mg/L; NH4+, 0.021 mg/L; K+, 0.023 mg/L; Mg2+, 0.016 mg/L; and, Ca2+, 0.024 mg/L. 3. Results and discussion 3.1. Sampling information Table 1 lists sampling information, including the sampling date, and PM2.5, PM10 and meteorological data for sampling site during March 4 to April 2, of 2006. Average PM2.5 and PM10 concentrations were 66.33 and 108.28 μg/m3, respectively. The average ratio of PM2.5/PM10 was 62%. This analytical result demonstrates that the main component in the PM10 was PM2.5 at this sampling site. Average pressure, temperature, relative humidity and wind speed was 1011.3 hpa, 20.4 °C, 75.3% and 3.8 m/s, respectively, at the sampling site. In comparison, the average ratios of PM2.5/PM10 were 77% for urban (Seoul, Korea), 76% for suburban (Basel, Switzerland) and 71% for rural (Chaumont, Switzerland) areas [11,12]. Comparison with these areas suggests that average PM2.5/PM10 ratios in this study were lower than those in urban (Seoul, Korea), suburban (Basel, Switzerland) and rural (Chaumont, Switzerland) areas. The average PM10 concentration was 108.28 μg/m3 during the sampling period. However, the PM10 concentration in this study was 44.07–161.61 μg/m3. The average PM10 concentration for the six sample groups (all N 125 μg/m3) was 149.38 μg/m3. This
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Table 1 Sampling information for particulate mass and meteorological conditions at this sampling site during March 4 to April 2, 2006 Date
Sampling no.
PM2.5 (μg/m3)
PM10 (μg/m3)
PM2.5/PM10
P (hpa)
Temp. (°C)
RH (%)
WS (m/s)
PWD
4-Mar 7-Mar 8-Mar 10-Mar 11-Mar 12-Mar 14-Mar 15-Mar 16-Mar 17-Mar 18-Mar 19-Mar 20-Mar 21-Mar 22-Mar 30-Mar 31-Mar 1-Apr 2-Apr
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Average S.D.
83.73 63.29 100.56 89.56 59.47 28.01 55.32 91.11 65.63 57.80 52.27 65.51 74.14 68.52 48.82 90.03 54.72 77.02 46.39 66.33 20.84
152.36 96.32 156.78 128.63 87.36 44.07 82.71 140.95 102.18 120.81 84.42 155.93 104.70 93.05 68.45 161.61 106.55 121.80 78.10 108.28 35.87
0.55 0.66 0.64 0.70 0.68 0.64 0.67 0.65 0.64 0.48 0.62 0.42 0.71 0.74 0.71 0.56 0.51 0.63 0.59 0.62 0.10
1015.8 1012.7 1013.2 1012.2 1009.1 1012.5 1017.5 1013.1 1009.8 1009.2 1009.6 1012.1 1011.5 1008.3 1006.6 1013.9 1011.7 1009.2 1009.4 1011.3 2.6
17.4 18.9 18.9 20.1 22.0 14.9 15.1 18.7 21.1 22.2 24.2 19.5 19.5 19.7 23.2 21.2 21.9 25.0 24.9 20.4 3.0
80.7 85.0 84.2 77.2 69.2 72.4 71.1 77.5 74.5 75.9 73.4 61.5 79.8 83.0 79.5 67.4 71.3 69.5 81.2 75.3 6.7
3.3 5.6 3.9 4.3 2.5 10.3 5.0 3.3 4.3 2.5 4.1 6.6 1.9 2.7 2.2 3.1 2.1 2.4 2.5 3.8 2.3
NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW NNW ES NNW NNW WSW NNW – –
P: Atmospheric pressure; Temp.: Temperature; RH: Relative humidity; WS: Wind speed; PWD: Prevalent wind direction.
average was roughly 12% higher than the standard value for PM10 concentrations (daily average, 125 μg/m3) [13]. The PM10 concentrations for the remaining five sampling groups (average, 111.21 μg/m3) were all N100 μg/m3. These values, which were below the Taiwan air quality standard, were all around 125 μg/m3. This experimental result demonstrates that air quality at the sampling site was considerable and detrimental to human health. Average daytime and nighttime PM10 concentrations were 35.9 and 27.7 μg/m3, respectively, during 1998 [14]. These analytical results suggest that the PM10 concentration increased significantly compared to those eight years before for both daytime and nighttime sampling periods. Highway construction at this sampling site accounted for this increased PM10 concentration. 3.2. Ionic specie concentrations in PM2.5 and PM10 Table 2 lists the ionic concentrations for PM2.5 and PM10. The average concentrations for ionic species of Cl−, NO2−, NO3−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+ were 1.52, 3.28, 1046, 12.63, 0.26, 7.87, 0.54, 0.07, 0.28 μg/m3 in PM2.5, respectively. Furthermore, average concentrations for ionic species of Cl−, NO2−, NO3−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+ were 2.97, 3.79, 17.28, 15.59, 1.24, 9.45, 0.61, 0.34 and 1.38 μg/m3 in PM10, respectively. However, levels of ionic species F− and PO43− were undetectable in fractions from ion chromatography (DIONEX DX-100 Ion chromatography). 3.3. Main ionic species in PM2.5 and PM10 Fig. 3 shows the average concentration percentages of Cl−, NO2−, NO3− , SO42− , Na+, NH4+, K+, Mg2+ and Ca2+ in PM2.5 and PM10. The analytical results demonstrate that average concentration percentages of ionic species Cl−, NO2−, NO3−, SO42−, Na+,
NH4+, K+, Mg2+ and Ca2+ were 4%, 9%, 28%, 35%, 1%, 21%, 1% and 0%, respectively, in PM2.5. The average concentration percentages of ionic species Cl−, NO2− , NO3−, SO42−, Na+, NH4+, K+, Mg2+ and Ca2+ were 6%, 7%, 32%, 30%, 2%, 18%, 1% and 1%, respectively in PM10. The three predominant ionic species were NO3−, SO42− and NH4+ at this sampling site. 3.4. Non-parametric (Spearman) correlation analysis The non-parametric (Spearman) correlation analysis was applied to examine the correlations between area pollutants and environment factors. Tables 3 and 4 list the correlation analysis of the elements and data. Table 3 shows the correlation between mass particle pollutants (PM2.5 and PM10) atmospheric pressure, temperature, relative humidity and wind speed. The analytical results suggest that the particulate mass was weakly correlated with atmospheric pressure, wind speed, temperature and relative humidity. This experimental finding demonstrates that meteorological conditions do not influence particulate mass concentrations (PM2.5 and PM10) at the sampling site. Table 4(a) and (b) list the ionic species (Cl−, NO2−, NO3−, SO42−, + Na , NH4+, K+, Mg2+ and Ca2+) in PM2.5 and PM10 that correlated with atmospheric pressure, temperature, relative humidity and wind speed. The ionic species of Cl− in PM2.5 were strongly correlated (rsp = 0.75) with relative humidity (Table 4(a)). The ionic species of NH4+ in PM2.5 was strongly correlated (rsp = 0.63 and 0.72) with NO3− and SO42−. The ionic species Mg2+ in PM2.5 was strongly correlated (rsp = 0.75) with SO42−. Analytical results also demonstrate that the ionic species in PM2.5 are weakly correlated with atmospheric pressure, wind speed, temperature and relatively humidity. The ionic species Cl− in PM10 was strongly correlated (rsp = 0.80 and 0.70) with Na+ and Mg2+
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Table 2 Ionic species concentrations of PM2.5 and PM10 at this sampling site Sampling PM2.5 (μg/m3) no. Cl− NO−2 NO−3 F−
PO3− SO2− Na+ 4 4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Average S.D.
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
2.43 1.54 2.61 1.64 0.89 1.15 1.22 2.38 1.17 1.39 1.02 0.88 2.33 2.06 1.14 1.20 1.05 1.19 1.66 1.52 0.55
5.93 2.54 3.31 4.00 2.18 1.07 2.92 3.94 4.23 3.11 1.62 3.21 2.89 2.01 5.63 2.40 2.71 4.87 3.69 3.28 1.25
11.71 7.68 11.26 10.57 6.68 3.28 10.84 14.25 13.90 8.98 8.89 6.47 14.58 15.32 10.40 13.46 8.10 14.35 8.10 10.46 3.23
PM10 (μg/m3)
16.02 12.23 16.81 16.80 15.30 5.53 8.99 14.11 13.45 11.26 12.02 17.74 9.33 10.20 8.83 15.17 12.32 13.08 10.82 12.63 3.16
NH+4
K+
Mg2+ Ca2+ F−
0.31 9.97 0.36 0.05 0.23 6.37 0.84 0.03 0.19 11.22 0.18 0.05 0.20 9.59 0.43 0.06 0.20 7.20 0.89 0.19 0.43 1.91 0.29 0.02 0.35 6.29 0.43 0.02 0.25 10.50 0.54 0.04 0.20 9.50 0.24 0.05 0.29 6.12 0.76 0.06 0.27 6.27 1.11 0.03 0.42 7.53 1.21 0.30 0.45 8.66 0.54 N.D. 0.19 9.43 0.24 0.01 0.14 5.99 0.35 0.02 0.24 10.38 0.56 0.03 0.14 7.20 0.34 0.14 0.18 9.25 0.24 0.04 0.22 6.11 0.77 0.03 0.26 7.87 0.54 0.07 0.09 2.21 0.30 0.07
0.26 0.19 0.31 0.33 0.21 0.51 0.12 0.08 0.17 0.19 0.15 1.15 0.05 0.13 0.23 0.35 0.46 0.35 0.15 0.28 0.24
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
Cl−
NO−2 NO−3
PO3− SO2− Na+ 4 4
NH+4
K+
Mg2+ Ca2+
7.13 3.67 4.09 2.95 1.33 1.32 1.61 5.62 1.66 4.82 2.32 3.18 3.40 2.26 1.53 2.69 2.05 2.42 2.45 2.97 1.51
0.93 3.33 2.32 5.46 3.21 3.64 3.77 4.24 3.90 7.50 3.84 4.53 3.58 0.79 5.50 2.68 3.57 3.80 5.47 3.79 1.53
N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D.
14.70 8.08 14.00 11.03 8.13 1.93 6.90 15.25 11.21 8.69 8.37 8.75 8.18 9.64 5.68 12.18 8.23 11.66 6.89 9.45 3.18
0.45 0.83 0.57 0.64 1.06 0.17 0.22 0.63 0.44 1.05 1.17 1.42 0.75 0.21 0.23 0.41 0.37 0.42 0.60 0.61 0.35
0.55 0.27 0.30 0.37 0.22 0.18 0.09 0.47 0.19 0.81 0.41 0.70 0.22 0.08 0.13 0.41 0.36 0.38 0.28 0.34 0.19
21.63 11.99 16.52 17.84 11.17 4.69 13.26 27.61 19.69 22.93 17.08 15.48 16.55 17.44 12.20 26.67 17.25 25.62 12.61 17.28 5.68
22.52 15.30 23.35 19.59 18.03 6.15 9.82 20.24 16.30 15.55 15.46 23.06 10.19 10.99 9.25 17.62 15.30 14.87 12.54 15.59 4.79
2.49 1.30 1.07 1.41 0.78 0.43 0.29 2.00 0.62 2.82 1.28 1.99 1.13 0.46 0.47 1.27 1.11 1.51 1.17 1.24 0.68
1.26 0.45 0.83 0.88 0.75 0.76 0.73 1.51 0.76 2.44 1.14 4.08 0.92 0.53 0.71 3.36 2.64 1.67 0.74 1.38 1.00
※F− and PO3− 4 levels were below the detection limit in the fractions from the ion chromatography (DIONEX DX-100 Ion chromatography).
(Table 4(b)). This analytical result shows that ionic species Cl−, Na+ and Mg2+ may originate from similar sources as PM10. The correlation coefficients of ionic species had an rsp value of 0.92, between those of Na+ and Mg2+ in PM10, whereas ionic species Ca2+ was strongly correlated with Na+ and Mg2+ in PM10. Ionic species NH4+ was strongly correlated (rsp = 0.83 and 0.75) with NO3− and SO42− in PM10. These analytical results indicate that ionic species in PM10 were weakly correlated with atmospheric conditions of pressure, wind speed, temperature and relative humidity at this sampling site. 3.5. Principal component analysis Principal component analysis with Varimax rotation and retention of principal components with eigenvalues N 1 (SPSS 10.0) was utilized to identify possible pollutant sources.
Table 5 lists the PCA results for PM2.5 and PM10 ionic species concentrations during the sampling period. These PCA results suggest that two factors account for the majority of data variance; one element for each factor was selected as a tracer. For the case where of PM2.5, factor 1 explained 40.58% of total variance of data and had a high loading for NO3− (0.78) and SO42− (0.71) and NH4+ (0.96), providing a possible indicator of secondary aerosols. These ionic species were most likely deriving from traffic emissions. The large volume of traffic on the highway near the sampling site was thus the principal reason for these analytical results. Factor 2 is related to re-suspended highway dust, and has high loadings for Mg2+ (0.93) and Ca2+ (0.82). Furthermore, PM10 was 51.99% for factor 1. High loadings of NH4+ (0.96), NO3− (0.80), Cl− (0.81), and SO42− (0.78) were from secondary aerosol (traffic) and marine salt (Cl−). Furthermore, Factor 2 had high loadings for Mg2+ (0.83), K+ (0.77) and NO2− (0.70) derived from re-suspended
Fig. 3. Average percentage of ionic species in various particle sizes (PM2.5 and PM10) at the sampling site.
G.-C. Fang et al. / Powder Technology 185 (2008) 223–230 Table 3 Non-parametric (Spearman) correlation analysis results for different particle sizes and meteorological conditions
PM2.5 PM10 P Temperature RH WS
PM2.5
PM10
1 0.84⁎⁎ 0.40 − 0.26 0.14 0.01
1 0.44 − 0.14 − 0.10 0.01
P
Temperature
1 − 0.74⁎⁎ − 0.01 0.54
RH
1 −0.19 −0.59
1 −0.08
WS
1
⁎⁎Correlation is significant at the 0.01 level (2-tailed).
highway dust (Mg2+ and K+) and secondary aerosols (NO2−), the most likely source of which was traffic. 4. Conclusion
Table 5 The PCA results for PM2.5 and PM10 ionic species concentrations at this sampling site Variables
PM2.5
Cl− NO−2 NO−3 SO2− 4 Na+ NH+4 K+ Mg2+ Ca2+ Eigenvalue Proportion of variance (%) Cumulative (%) Origin
This study obtained the following conclusions. 1. The predominant component in PM10 was PM2.5. The average ratio of PM2.5/PM10 was 62% at this sampling site, and the average PM2.5/PM10 ratio was less obtained by studies conducted in urban (Seoul, Korea), suburban (Basel, Chaumont) and rural (Chaumont, Chaumont) areas. 2. Average concentrations of ionic species NO3−, SO42− and NH4+ in PM2.5 were 10.46, 12.63 and 7.87 μg/m3, respectively. Analytical results indicate that average concentrations of
229
PM10
Factor 1
Factor 2
Factor 1
Factor 2
0.61 0.63 0.78 0.71 – 0.96 – – – 3.65 40.58
– – – 0.64 0.37 – 0.63 0.93 0.82 2.33 25.86
0.81 – 0.80 0.78 0.65 0.96 0.10 0.51 0.30 4.68 51.99
0.22 0.70 0.14 0.31 0.68 – 0.77 0.83 0.65 1.90 21.13
40.58 Atmospheric reactions, Secondary aerosols
66.44 Dust/ soil
51.99 Atmospheric reactions, Secondary aerosols, Marine salt
73.12 Marine salt, Dust/soil, Secondary aerosols
Note: Only loading factor values with moduli N0.1 and factor loading values with moduli N0.7 are in bold.
ionic species NO3−, SO42− and NH4+ in PM10 were 17.28, 15.59 and 9.48 μg/m3, respectively.
Table 4 (a)–(b) Non-parametric (Spearman) correlation analysis results for different particle sizes for ionic species and meteorological conditions Cl−
NO−2
NO−3
SO2− 4
Na+
NH+4
K+
Mg2+
Ca2+
P
Temperature
RH
WS
Cl NO−2 NO−3 SO2− 4 Na+ NH+4 K+ Mg2+ Ca2+ P Temperature RH WS
1 0.30 0.58 0.06 0.08 0.51 − 0.32 − 0.22 − 0.43 0.37 − 0.39 0.75⁎⁎ − 0.08
1 0.33 0.31 − 0.26 0.31 − 0.29 0.24 0.04 0.03 0.11 0.19 − 0.17
1 0.01 −0.16 0.63⁎ −0.50 −0.24 −0.45 0.02 −0.02 0.25 −0.35
1 − 0.13 0.72⁎⁎ 0.12 0.75⁎⁎ 0.40 0.32 − 0.05 − 0.17 0.20
1 − 0.15 0.46 − 0.04 − 0.18 0.45 − 0.52 − 0.15 0.42
1 − 0.31 0.32 0.02 0.42 − 0.27 0.10 0.03
1 0.24 − 0.14 − 0.02 0.17 − 0.24 0.12
1 0.40 0.00 0.13 − 0.32 − 0.09
1 0.12 0.05 −0.45 0.18
1 − 0.74⁎⁎ − 0.01 0.54
1 −0.19 −0.59
1 − 0.08
1
PM10
Cl−
NO−2
NO−3
SO2− 4
Na+
NH+4
K+
Mg2+
Ca2+
P
Temperature
RH
WS
Cl− NO−2 NO−3 SO2− 4 Na+ NH+4 K+ Mg2+ Ca2+ P Temperature RH WS
1 − 0.02 0.50 0.59 0.80⁎⁎ 0.61⁎ 0.47 0.70⁎⁎ 0.40 0.39 − 0.22 0.42 0.01
1 0.02 − 0.12 0.26 − 0.25 0.27 0.22 0.12 − 0.33 0.40 − 0.15 − 0.01
1 0.40 0.56 0.83⁎⁎ −0.01 0.57 0.61⁎ 0.13 0.14 −0.10 −0.22
1 0.58 0.75⁎⁎ 0.54 0.68⁎ 0.49 0.34 − 0.11 − 0.06 0.23
1 0.53 0.62⁎ 0.92⁎⁎ 0.63⁎ 0.13 0.15 0.01 − 0.04
1 0.12 0.56 0.53 0.32 − 0.10 0.02 0.02
1 0.57 0.28 − 0.10 0.21 − 0.03 0.07
1 0.82⁎⁎ 0.23 0.15 − 0.22 0.01
1 0.21 0.14 −0.54 −0.14
1 − 0.74⁎⁎ − 0.01 0.54
1 −0.19 −0.59
1 − 0.08
1
PM2.5 −
⁎Correlation is significant at the 0.05 level (2-tailed). ⁎⁎Correlation is significant at the 0.01 level (2-tailed).
230
G.-C. Fang et al. / Powder Technology 185 (2008) 223–230
3. Non-parametric (Spearman) correlation analysis results indicate that particle mass was weakly correlated with atmospheric pressure, wind speed, temperature and relative humidity. 4. Non-parametric (Spearman) correlation analysis results demonstrate that ionic species in PM10 and PM2.5 were weakly correlated with wind speed, temperature and relative humidity. 5. Ionic species Cl−, Na+, Mg2+ may be from similar sources in the form of PM10 at this sampling site. 6. Ionic species NH4+ was strongly correlated (rsp = 0.63 and 0.72; rsp = 0.63 and 0.72) with NO3− and SO42− in PM2.5 and PM10, respectively. 7. Principal component analysis demonstrates that the soil, secondary aerosols and marine salt sources were likely the predominant pollutant source at this sampling site.
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