A.J. Baca\ J. Vincent % M. Luna^F. Zhou\ S. LaDochy^ &
S.L. Nickolaisen*
Department of Chemistry and Biochemistry, California State University,Zoj: v4??gg/&?, la? ̂ Mgg/% C4 900 J2, [/ ̂. v4.Department of Geography and Urban Analysis, California StateUniversity, Los Angeles, Los Angeles, CA 90032, U. S. A.
Abstract
Continuous monitoring of metals (Mg, Al, Cu, Zn, Ni, Ti, Fe), nitrate,ammonium, and sulfate in airborne particles sampled on the eastern fringe ofLos Angeles was carried out throughout the summer of 1999. High-volume airsamplers were used to collect particulate matter along a high-traffic corridor inwhich sampling sites were less than one mile apart. Inductively coupled plasma-atomic emission spectrometry was used to analyze the metals of interest whileion chromatography was used to measure nitrate, ammonium, and sulfate.Metals such as Cu, Ti, Zn, and Al were found to be at levels ranging from0.0003 to 0.4 jug/m̂ . The average quantity of total nitrogen-containing specieswas measured to be around 10-30 |ig/m , while the sulfate content was found tobe around 2-20 u;g/rrv. Temporal and spatial variations of these species werestudied by comparing the measured results among the sampling sites. Weatherand seasonal conditions were taken into account in the analysis of the data byusing information acquired from a nearby weather station. Sites along the high-traffic corridor were found to have pollution levels related directly to varyingtraffic volume, with values decreasing with reduced traffic flows. The extent ofemission of pollutants also appeared to vary between weekdays and weekends,and between summer months. While the smog levels were at an all-time low, theparticulate air pollution continues to exceed federal standards.
Monitoring of pollutants in airborne particles and assessing their concentrationdependence on meteorological conditions, geographical locations, and pollutionsources in the Southern California Air Basin have been carried out by severallocal organizations (Ipps [1], SCAQMD [2]). While these reports provideinformation concerning temporal and spatial trends of paniculate matter,conclusions have been made based on results from either a widely separatedcollection grid (SCAQMD [2]) or a single monitoring station (Chow [3]). Thepresent study addresses the measurement of particulate matter on aneighborhood scale (Neighborhood scale has a nominal separation betweensamples of 1-10 km within a relatively uniform urban land use area). Pollutionconcentrations can vary considerably across a micro-scale environment due tolocal topography, emission sources, and meteorological factors. Perhaps one ofthe most important factors is the pollution caused by the huge number of cars inthe Los Angeles metropolitan area. Interestingly, the relationships betweentraffic flows and particulate air pollution have not been adequately addressed inneighborhood-scale studies.
During the summer of 1999, the authors collected particulate airpollution data from four sampling sites located along a busy residential sectionof Alhambra's Fremont Avenue, a heavily-used north-south connector roadbetween two Los Angeles freeways (see Figure 1 for the geographical locationsof the sampling sites). An extension of the Interstate 710 was originally plannedto assist traffic through this neighborhood, however, the more affluentresidential area to the north has successfully blocked the project. Alhambra, amiddle-class neighborhood to the south, has inherited the consequences ofincreased traffic congestion, particularly along Fremont Avenue. Gravimetricmeasurements indicated the extent of the traffic-pollution relation, whilechemical analyses showed variations in composition.
2. Experimental Section
Sampling of Airborne Particles. High-volume air samplers, donated by theSouth Coast Air Quality Management District (SCAQMD), were calibrated andplaced at the 4 locations in early July and running until late September. 24-hsamples were taken every other day, except for Station 1, which was onlyavailable on weekdays during school hours (7 am-2 pm). In order to comparevalues obtained at the Fremont site with those more distant from traffic flow,background values were obtained from the front of a residential home, 0.8 kmwest of Station 4. A second sampler was placed at Station 2, to compareparticulate concentrations collected for a 24-h period with the shorter 7 h takenat Station 1. Total suspended particulates (TSP) were collected using 8 x 10inch glass fiber filter papers, and analyzed for particulate concentrations andchemical composition.
In order to measure the impact of this congested traffic on localparticulate air pollution levels, the air samplers were placed along residentialportions of Fremont. In order of distance from the nearest freeway, Station 1(0.1 km distance) was located at an elementary school playground, about 5 mfrom Fremont and nearest the freeway offramp; Station 2 (1 km) was located onthe roof of a low, one-story restaurant, about 20 m from Fremont; Station 3 (1.8km) was placed at a corner of a parking lot for a government building, about 10m from the road; and Station 4 (2.6 km) was on the roof of a one-story officebuilding, approximately 14 m from Fremont (see Figure 1). Toward the end ofthe summer sampling, the sampler from Station 4 was moved 0.7 km to the westin a residential area away from heavy traffic. Samples from this site were usedas a background level to compare with samples taken along the busy FremontAvenue.
In order to monitor street level particulate levels, care should beexercised in monitoring for the consistency in distance between roadside and
that of elevation above ground. In a study examining the effect of distance froma road on PMio concentrations, Monn et al. (Monn [4]) found consistent declinesin PMio concentrations with distance, the most dramatic drop being within thefirst 15 meters, with highest concentrations at pedestrian level. Their studyshowed that mean concentrations at street level were 13% higher than those 15or more meters away horizontally, and 5 or more meters vertically. Thiscorrection was applied to the mean particulate concentrations at Stations 2 and 4to normalize data for distance from street and elevation. Another correction wasnecessary as Station 1 was sampled for a shorter period, during early traffichours and not at night when traffic would have been considerably less. Toobtain the relationship between the 7-h period and the 24-h sampling period, asecond sampler was placed side by side at Station 2. The second sampler wasrun during the same 7 has with Station 1. This allowed us to compare thepollution levels of this shorter period with the 24-h sample. Six samples weretaken simultaneously and compared. The shorter sampling period mean was30.2% higher than the 24-h period values for the same days. Station 1 also wasnot sampled on weekends and holidays. To compare with the other locations,we also made a correction for the weekend. As weekdays had readings 20%higher than weekends and holidays, and as weekends have 2 days versus 7 daysof a week, the week correction reduced mean concentrations by another 5.7%.
Reagents and Chemicals. Standard metal solutions were purchased fromAldrich (Milwaukee, WI). Standard solutions of nitrite, nitrate, and sulfate wereobtained from Spex Certiprep (Metuchen, NJ) while ammonium and potassiumstandards were acquired from GFS chemicals (Columbus, OH).
Sample Digestion Procedure. For the quantification of NH/" (cation mode)and that of NO/, NOg, and SO/ (anion mode), V* of each 8 x 1 0 inch glassmembrane filter containing airborne particles was cut and immersed overnight in100 mL solution of the corresponding mobile phase. Prior to each analysis, thesolution was filtered with a Whatman N2 filter paper. To extract the metalspecies from the particles, a different portion of the same membrane filter (alsoof a V4 size) was first dissolved in a HF/HNO] mixture (v/v = 1/3), followed byfiltration and a 200-fold dilution using a solution containing 1% HNOa and 0.1%HC1
Sample Analysis. At least three replicate measurements were made for eachsample and the resulting percent relative standard deviations were less than10%. To confirm that analytes have been completely extracted from the glassmembranes, we repeated certain selected samples a week after the initialanalyses and found that the values were essentially identical. For the ionchromatographic analysis of anions, a Hitachi L-6000 pump was used inconjunction with an lonPac AS 14 column, an ASRS-ULTRA suppressor, and aCD20 conductivity detector, which were all from Dionex. A mixture containing3.5 mM sodium carbonate and 1 mM sodium bicarbonate was used as the
mobile phase. For cation analysis, the column used was a Hamilton PRP-X200cation column and the suppressor was substituted with a Dionex CSRS-ULTRAsuppressor. The mobile phase was a 70% methanol/30% water with a HNO,concentration of 4 mM. The mobile phase flow rate for cation analysis was 2mL/min while that for anion was 1.2 mL/min. The amount of sample injectedwas 20 |LiL for each analysis. A Thermal-Jerral-Ash ICAP inductively coupledplasma-atomic emission spectrometer (ICP-AES) was used for the analysis ofthe selected metals present in airborne particles.
3. Results and Discussion
Table 1 summarizes the TSP values for the four Fremont stations as well as thebackground site. Although only three stations had 30 or more samples (Station 1was only sampled on weekdays), there was a definite decrease in values withincreasing distance from the freeway. Traffic flow, as measured by nearbycounters, also showed a relationship to TSP levels. Highest traffic flowoccurred at Station 2, where traffic from the end of the Interstate 710 freewayturn onto Fremont from the west. Although figures were not available, asubstantial percentage of vehicles passing this location were diesels. Many ofthe trucks turn off at intersections before Station 3, particularly one busy truckroute between Stations 2 and 3. Traffic decreases from Station 3 to Station 4.Although the lowest traffic count was recorded near Station 1, its locationnearest the freeway, with no sound barrier, constitutes a major source of trafficpollutants. Levels between Stations 1 and 4 dropped by over 50%, with a moregradual decrease from Stations 2 to 4, than between Stations 1 and 2. Thebackground Station 5, the farthest from the freeway and Fremont, shows thelowest paniculate mean.
Table 1. TSP Descriptive Statistics
Site
Station 1Station 2Station 3Station 4Station 5
N
153232304
Mean
145.10126.60122.1996.9372.39
Std. Deviation
37.1441.2438.5438.3219.42
Skewness
0.6170.7900.7490.981-0.122
Kurtosis
-0.1930.3650.5570.442-1.626
Federal standards for TSP are 150 Hg/nv annual, 260 for 24-hr period; California standardwas 100 Jig/nr for 24-hr, but has been replaced with PMio standard of 50 )ig/m\
Table 2 shows daily and monthly means for the 5 stations. Althoughthe sample size becomes quite small for individual locations, the means for alllocations are lower on weekends and holidays than weekdays, following trafficvolumes. Since Station 1 did not have weekend samples, the differences are notas great for sites 2, 3 and 4. Weekend levels averaged 20% less than for
weekdays. Monthly TSP increased from July to August, then decreased inSeptember. The 1999 summer in Los Angeles was unusually cool, with theSeptember sampling days cooler than those in July and August. July and Augustwere similar in terms of temperature.
In September, the school at Station 1 was not available. The authorsmoved that sampler to location 2, thus testing the samplers side-by-side. Bycomparing the 7 am-2 pm sampling period with the 24-h sampling at the samelocation, we found that the shorter period collected 30.2% higher particulateconcentrations than the longer sampling period. This period should reflecthigher traffic activity than the rest of the day, with the exception of the lateafternoon rush. However, late night through early morning should have the leasttraffic flow and lowest traffic-related pollution emissions. The 30% differencewas not unexpected. Also, meteorological conditions, discussed below, maylead to lower nighttime turbulence and transport of road materials toward thesamplers. Later in September, the roof underwent repairs at Station 4 and the airsampler was moved to a residential station 0.7 km to the west (Station 5).Station 5 represents the background residential readings for this study. Themean TSP for the 4 sampling days was 75.84 Jig/ml In comparison, Station 3,the closest site sampling for the same days averaged 134.15 jug/m̂ . While atStation 5 levels of particulates were below all those along Fremont, theymatched closely TSP means found at nearby SCAQMD monitoring stations inPasadena and Downtown Los Angeles, respectively.
Table 2. Daily and Monthly Averages of TSP (jig/rn̂ ) Along Fremont
To test how well Fremont stations correlate with each other, bivariatecorrelations employing Pearson's correlation coefficient and Spearman's p wereconducted (Table 3). All stations were significantly correlated with each otherat better than 99% levels of confidence, except that between Stations 1 and 2and that between Stations 1 and 4. Stations 2, 3 and 4 correlated the best witheach other, while Station 1 was the least correlated with the others. The
discrepancy is attributable to the sample size. Station 1 had only 15 days ofsampling as opposed to over 30 for the others. Station 1 was the only sitedirectly exposed to freeway-generated dust, being the closest to Interstate 10. Athird factor may have been related to the sampling period, since Station 1 wasthe only site sampling for 7 h/day.
Note: Fremont School (Station 1) correlations are Spearman's rank correlation coefficients.
Meteorological Factors. In order to investigate the relationship betweenobserved paniculate levels and meteorological conditions, pollution levels werecompared with weather observations collected at the nearby automatic weatherstation using backward linear regression. Weather variables used forcomparison include barometric pressure, temperature, relative humidity, windspeed, and wind direction (Table 4). Hourly and daily means were investigated,although comparisons used 24-h means. Bivariate correlations between TSPand meteorological variables showed significant 'correlations betweenparticulates and pressure and wind speed for Station 2; between particulates andpressure and temperature for Station 3; and between particulates and pressureand temperature for Station 4. Particulate levels at Stations 1 and 5 were notsignificantly correlated with any of the weather variables. For all stations, higherparticulates occurred with lower pressures, higher temperatures and lower windspeeds. Lower pressure generally causes greater vertical mixing and convection,which may enhance lifting of surface dust and traffic grit. Warmer temperaturesalso favor convection as well as increase photochemical reactions. A significantproportion of aerosols form through gas-to-particle conversion, especially inwarmer summer months (SCAQMD [2]). Lower horizontal winds reducedispersion. During summer months, the area studied experienced a prevailingsea breeze practically daily from the southwest. Stronger sea breezes tend topush the urban smog plume away from central Los Angeles eastward into thevalleys and foothills of the eastern Los Angeles Air Basin (LaDochy [5]).
Backward linear regression analysis using all of the availablemeteorological data as independent variables were conducted for explainingvariations in particulates. For Stations 3 and 4, significant explanatory modelsretained temperature and relative humidity as variables with R? values of 0.468
Note 1: Station 1&4 coefficients are Spearman's rank correlations.Note 2: Values in the first row for each site represent the correlation while those in the second roware the significance (2-tailed).
and 0.407, respectively. However, these two variables are highly inverselycorrelated, violating the regression model's assumptions. Removing relativehumidity resulted in lower R Squares. Models run on the other two stations didnot reveal significant explanatory abilities. Other variables that may improvethe models include inversion data, pressure gradients, and chemicalcomposition.
Chemical Composition. The toxicity of particulates in the Fremont corridor isas important as the quantity. Often the source of pollutants can be identified bythe particulate chemical composition. Was the source of particulates mainlylocal traffic or were there other elements present in the background ambientatmosphere from local or regional sources? Table 5 shows that nitrates andsulfates make up about 20% of TSP, with nitrates generally twice as abundant assulfates. Sulfates are nearly 5 times ammonium levels. Station 2, with its heavytruck traffic, shows highest nitrates and sulfates, while both Stations 2 and 3share highest ammonium values. The results for the metals show smallerconcentrations, although except for copper, they all show the same relationshipwith traffic volume, as does TSP. Previous studies (SCAQMD [2]) found that asubstantial proportion of particulate load was made of nitrates and sulfates.Nitrates have several sources, but mainly from combustion in high temperatureengines. Sulfates are also a result of combustion, a by-product of sulfur-containing fuels. Refineries, particularly in south LA county, are probably themain contributors.
4. Conclusions
The present study has shown that particulate air pollution along busy urbanstreets can reach unhealthy levels. People living, working or going to schoolnear high traffic flows are subject to TSP values above federal health
standards as well as the more stringent California standards. Particulate levelsalong Fremont correlate closely with traffic flow counts, which in this study alsoshow a relationship with distance from a nearby freeway. Variations in weatherelements, though significant, only explained up to 35% of particulate variability.Increasing temperatures, decreasing pressure and wind speeds lead to increasedparticulate levels, in general. Nitrates and sulfates do not show the samerelationship with traffic as TSP, however, Station 2, near a busy intersectionbringing freeway traffic from the Interstate 710 to Fremont, shows highestvalues for these pollutants. All metals tested, except copper, show decreasingconcentrations with lessening traffic flows. Although Station 1 shows thehighest concentrations of metals in most cases, the values are quite low,reflecting the lack of any significant industries in the study area. Mobile sourcessuch as traffic account for the high particulate levels and may be a health hazardparticularly for the elementary school children at Station 1.
Not only was the summer of 1999 cooler, but smog levels were at anall-time low (SCAQMD [6]). It was the first summer without a single Stage 1episode day for ozone in the Los Angeles Basin since efforts to reduce smogbegan about 50 years ago. However, particulate air pollution continues toexceed federal standards.
Acknowledgments
The authors would like to thank the South Coast Air Quality ManagementDistrict, especially Rudy Eden, for the loan of equipment used in this study. Wealso thank Joe Faliti, Bob Kirby, and Steve Berger for their help with thesampling. Support for this research by the Center for Research Excellence inScience and Technology Program of the National Science Foundation isgratefully acknowledged. A.J.B also acknowledges support from the NSF-Collaborative Research at Undergraduate Institutions program.
References
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