spatial differences in outdoor pm 10 mass and aerosol composition in...

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Spatial Differences in Outdoor PM10 Mass and AerosolComposition in Mexico CityJudith C. Chow a , John G. Watson a , Sylvia A. Edgerton b , Elizabeth Vega c & Elba Ortiz ca Desert Research Institute , Reno , Nevada , USAb National Science Foundation , Arlington , Virginia , USAc Instituto Mexicano del Petróleo , Mexico , DF , MexicoPublished online: 27 Dec 2011.

To cite this article: Judith C. Chow , John G. Watson , Sylvia A. Edgerton , Elizabeth Vega & Elba Ortiz (2002) SpatialDifferences in Outdoor PM10 Mass and Aerosol Composition in Mexico City, Journal of the Air & Waste Management Association,52:4, 423-434, DOI: 10.1080/10473289.2002.10470791

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Chow et al.

Volume 52 April 2002 Journal of the Air & Waste Management Association 423

ISSN 1047-3289 J. Air & Waste Manage. Assoc. 52:423-434

Copyright 2002 Air & Waste Management Association

TECHNICAL PAPER

ABSTRACTTwenty-five MiniVol samplers were operated throughoutthe Mexico City metropolitan region from February 22through March 22, 1997, to evaluate the variability of PM10

concentrations and composition. The highest PM10 con-centrations were found in neighborhoods with unpavedor dirty roads, and elements related to crustal materialwere the main cause of differences from nearby (<200 m)monitors that were not adjacent to the roadbed. SO4

2–

concentrations were homogeneous across the city. SO42–

measured at the city boundaries was about two-thirds ofthe concentrations measured within the urbanized area,indicating that most SO4

2– is of regional origin. Elementalcarbon (EC) and organic carbon (OC) concentrations werehighly variable, with higher concentrations in areas thathad high diesel traffic and older vehicles. Spatial correla-tions among PM10 concentrations were high, even thoughabsolute concentrations were variable, indicating a com-mon effect of meteorology on the concentration or dis-persion of local emissions.

INTRODUCTIONPM2.5 and PM10 (particles with aerodynamic diameters lessthan 2.5 and 10 µm, respectively) concentrations mea-sured at a monitoring site result from sources that are

close by (< ~0.5 km), that are mixed throughout the lo-cal neighborhood (~0.5–4 km), that affect an entire city(~4–100 km), and that are mixed throughout a region(>100 km). The zone of representation for a monitoringsite depends on the relative contributions from sourceemissions distributed within these domains.1 U.S. Na-tional Ambient Air Quality Standards (NAAQS) for PM2.5

and PM10 rely on measurement locations that representexposures of large populations to determine compliance.Source-oriented and background sites support the NAAQSto understand sources that need to be controlled, butthey are not used for compliance monitoring.2 To un-derstand the distribution of PM10 mass and chemicalcompositions in the Valle de Mexico, a spatially densemonitoring network was operated from February 23 toMarch 22, 1997, as part of the Investigación sobre Mate-ria Particulada y Deterioro Atmosférico–Aerosol and Vis-ibility Evaluation Research (IMADA-AVER).3,4 Theobjectives of this paper are to (1) examine the nature,causes, and variability of elevated PM10 concentrations;(2) determine the zones of influence of fugitive dust andother emitters on PM10 concentrations; and (3) evaluatethe zones of representation of fixed site measurementsfor community exposure to PM10.

AEROSOL MEASUREMENTSMexico City is situated in an elevated (~2250 m abovemean sea level) air basin with an area of ~13,000 km2 thatis bounded by mountains exceeding 1000 m above thevalley floor on all sides except the north. The urbanizedarea includes ~30,000 industries (e.g., metalworks, cornmilling, electronic and chemical manufacturing, quarry-ing, ready-mix cement, and stone cutting), ~3 milliondiesel and gasoline vehicles, and ~20 million inhabitants.5

The climate is generally dry and temperate in this elevated

Spatial Differences in Outdoor PM10 Mass and AerosolComposition in Mexico City

Judith C. Chow and John G. WatsonDesert Research Institute, Reno, Nevada

Sylvia A. EdgertonNational Science Foundation, Arlington, Virginia

Elizabeth Vega and Elba OrtizInstituto Mexicano del Petróleo, Mexico, DF, Mexico

IMPLICATIONSMonitoring of PM10 at satellite sites around long-termmonitors meant to quantify human exposure in MexicoCity showed that monitors in the city center representlarge neighborhoods, but that monitors in the northeast-ern portion of the city are biased by local emitters. Differ-ences in silicon (a marker for fugitive dust) and black car-bon (a marker for vehicle exhaust) indicate that primaryemissions are the major causes of this bias.

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424 Journal of the Air & Waste Management Association Volume 52 April 2002

air basin, with frequent and intense thunderstorms fromJune through October. Detailed meteorological character-istics during the study period are reported by Doran et al.3

Ten long-term PM10 monitoring sites are operated bythe Red Automática de Monitoreo Atmosférico (RAMA)to represent population exposure. As shown in Figure 1,six of these RAMA core sites were supplemented with 21satellite sites and four urban/regional-scale boundary sitesto better understand how well the core sites represent theoutdoor exposure of their surrounding population. Thesix core sites represent various land uses (industrial/com-mercial/residential in urban and suburban areas), differ-ent socioeconomic conditions, and distinct mixtures ofemission sources.

Site selection for the spatially dense satellite networkwas primarily based on a systematic sampling grid supple-mented by judgments of proximity to local emissions,accessibility, and security.2 Systematic sampling6 assigns

one monitor to each cell of a grid superimposed on theurban area. A grid system of 20 5 × 5 km cells was estab-lished for this study. Judgmental sampling7 uses knowl-edge of source emissions and sensitive receptor locations,coupled with mechanisms for pollutant transport, to lo-cate sampling sites. This method was used to select moni-toring locations inside each grid cell. Within the studydomain (25 km N-S × 20 km E-W), 21 satellite sites werelocated in 15 of the 20 available cells. Because a spatiallyallocated PM10 inventory did not exist in 1997, most ofthe satellite sites were chosen to evaluate the zones ofrepresentation of the six core sites and to examine thezones of influence from primary fugitive dust and motorvehicle, industrial, and other emitters.

The satellite network (summarized in Table 1) included(1) two source (S) sites located adjacent to fugitive dustsources, (2) four receptor (R) sites located near the core sitesto evaluate deviations over short distances, and (3) 15 gra-dient (G) sites located between or around the core sites todiscern concentration changes between the core sites. Thefour urban/regional boundary sites located outside of theurbanized area in the northeast (Teotihuacan), northwest(Cuautitlan), south (Chalco), and south/southwest (Ajusco)quadrants were intended to represent nonurban agricul-tural settings ~50 km beyond the city center. The satellitesites within the air basin represented middle-scale (0.1–0.5km) to neighborhood-scale (0.5–4 km) influences aroundthe core sites, whereas the four boundary sites representedurban-scale (4–100 km) to regional-scale (100–1000 km)influences.1 The coordinates of satellite and boundary sites,along with the corresponding distances and directions fromthe nearest core sites, site descriptions, and dominantsources, are summarized in Table 1.

Battery-powered MiniVol portable PM10 samplers(Airmetrics) were used to collect daily 24-hr PM10 samplesat the satellite and boundary sites.8 Each sampler was hungfrom a hook attached to a utility pole, lamppost, or roof-top stand. Two filter pack configurations were used: (1)Teflon-membrane/citric acid–impregnated cellulose-fiberfilter packs and (2) quartz-fiber/NaCl–impregnated cellu-lose-fiber filter packs. The front Teflon-membrane filterwas used to measure mass by gravimetry, light absorption(babs) by densitometry, and 40 elements (Na, Mg, Al, Si, P,S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se,Br, Rb, Sr, Y, Zr, Mo, Pd, Ag, Cd, In, Sn, Sb, Ba, La, Au, Hg,Tl, Pb, and U) by X-ray fluorescence (XRF),9 and the backupcitric acid-impregnated cellulose-fiber filter was used tomeasure gaseous NH3 by automated colorimetry. On aparallel unit, the front quartz-fiber filter was used to mea-sure water-soluble ions (Na+ and K+ by atomic absorptionspectrometry;10 Cl–, non-volatilized NO3

–, and SO42– by ion

chromatography11) and carbon [organic carbon (OC) andelemental carbon (EC) by the IMPROVE thermal evolution

Figure 1. Monitoring network for the Mexico City Aerosol Character-ization study. Core sites (Tlalnepantla, Xalostoc, La Merced,Netzahualcoyotl, Pedregal, and Cerro de la Estrella) are indicated by +.Urban/regional boundary sites (Cuautitlan, Teotihuacan, Chalco, andAjusco) are indicated by *. Satellite sites are indicated by • .

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Table 1. Description of core, satellite, and boundary monitoring sites for the Mexico City Aerosol Characterization study.

Dominant SourcesSite Code Location Latitude Longitude Description Geological Motor Vehicle

Core SitesTLA Tlalnepantla—Av. 19.52889 –99.20472 Located on a platform 4 m high in X X

Toluca and front of a water storage tank.Atlacomulco, Surrounded by moderately traveledTlalnepantla roads, industries (electronic

manufacturing, corn milling, andmetal fabricating facilities), andresidences.

XAL Xalostoc—inside a 19.52611 –99.07972 Located on a platform 4.3 m high. X Xvehicular service Adjacent to heavily traveled pavedcenter on the 14.5-km and unpaved roads with old and newMexico-Pachuca gasoline and diesel vehicles in amotorway and highly industrialized area.Hierro St., Ecatepec

NET Netzahualcoyotl— 19.42222 –99.02639 Located 10 km south of Lake Texcoco X XAv. Netzahualcoyotl on a rooftop 4 m high near a landfilland Av. Xochiaca in a commercial and low-income

residential area close to heavilytraveled paved and unpaved roadswith loose dirt surfaces, athletic field,and open landfill nearby.

MER La Merced—Av. 19.42222 –99.11945 Located on a rooftop 8 m high in a XCongreso de la residential, commercial, andUnion in La Merced government district adjacent to

moderately traveled, paved, curbedsurface streets.

CES Cerro de la 19.33663 –99.07759 Located on a platform 4 m high in a X XEstrella—inside a commercial and residential areawater treatment adjacent to heavily traveled paved andplant on Av. San unpaved roads. Several small stone-Lorenzo in Iztapalapa cutting operations nearby.

PED Pedregal—in 19.325 –99.20417 Located on a platform 4 m higha schoolyard on surrounded by volcanic stone in anCañada Street and affluent residential area adjacent toAv. Crater in San Angel lightly traveled paved roads.

Satellite SitesG02a Av. Gob. Gustavo 19.4559 –99.0696 ~3.2 km SSE of the XAL site near X

Baz, Miguel unpaved roads with visible vehicle-Alemán y Veracruz suspended dust

G05 Bulev. de los 19.5343 –99.0224 ~5.7 km ENE of the XAL site in a XAztecas y commercial/residential area in a less-Tepozteco populated area

G06 Maravillas y 19.5185 –99.0607 ~1.9 km SE of the XAL site in an XAgustin Villa industrial area

G08 Calle 606 between 19.4568 –99.0572 ~4.7 km NW of the NET site near an XCalle 661 and Calle 699 industrial incinerator, adjacent to

light rail construction withcongested traffic

G09 Via Tapo and Via 19.4425 –99.0472 ~3.1 km NW of the NET site near the XExpress Tapo sewage treatment plant, 2 km to the

NE corner of the Mexico Cityinternational airport

aSites with both Teflon/citric acid and quartz/NaCl filter pack configurations.

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Table 1. (cont.)


Satellite SitesG12a Sitio Universidad 19.3642 –99.0705 ~2.9 km N of the CES site on the campus X

Autonoma away from well-traveled roadwaysMetropolitana-Iztapalapa

G17 Instituto Mexicano 19.4869 –99.1461 ~7.6 km SE of the TLA site inside of Xdel Petróleo Instituto Mexicano del Petróleo’s courtyard

G18a Colégio Militar de 19.5201 –99.1252 ~5.1 km WSW of the XAL site next X XMéxico y Presa to a heavily traveled roadway in a

commercial, residential, and lightindustrial area

G20 Plaza Rio de Janeiro 19.4189 –99.1586 ~4.3 km W of the MER site in a Xbetween Durango commercial area with moderate toand Orizaba heavy traffic

G21a Fernando y La 19.3687 –99.1666 ~6.3 km NE of the PED site in a XQuebrada commercial area with moderate to

heavy trafficG22 Carmen y Refugio, 19.3826 –99.1354 ~5.0 km SSW of the MER site near X

Col. Nativitas, Delegación the commercial district with moderateBenito Juarez to heavy traffic

G23a Paseos de las Naranjos 19.3475 –99.1219 ~5.3 km WNW of the CES site in a Xy Paseos de Las Magnolias, commercial/residential area withCo. Paseos de Taxqueña, moderate to heavy trafficDelegración Coyoacán

G25a Manuel Carpio y 19.4482 –99.1566 ~4.8 km NW of the MER site in a city XTorres Bodet park near the commercial district with

moderate to heavy trafficG26a Del 14 y Estaño 19.4461 –99.1214 ~3.2 km N of the MER site in a paved X

school playground in acommercial/residential area

G27a Eje 4 Sur y Sur 159 19.3958 –99.0933 ~3.9 km SE of the MER site on the XUniversidad AutonomaMetropolitana-Azcapotzalco campus

R04 Plaza Juárez y 19.5142 –99.0692 ~1.7 km NE of the XAL site near XEcatepec open sewage

R13 Av. 11 y Nautla 19.3361 –99.0972 ~1.0 km W of the CES site near a Xsmall cement plant and market withmoderate traffic

R16a Miguel Hidalgo y 19.5282 –99.1924 ~1.21 km E of the TLA site in the X XToltecas median of a heavily traveled roadway

in a light industrial area (silo, grainelevator, corn mill)

R24 Sitio La Merced 19.4222 –99.1194 Collocated with the MER site at the Xcenter of the commercial/government district

S03 Siderurgla y Carlos 19.5142 –99.0812 ~1.5 km SSW of the XAL site X XB. Zetina surrounded by misc. industries (e.g.,

cement, soap, polyester) with brokenpavement, unpaved shoulders, andheavy traffic in the area

S11 Antiguo Camino a 19.3196 –99.0429 ~3.5 km SE of the CES site near a XTialtenco U. Hab. sand/gravel operation, mining, cementMagueyera plant, and unpaved road


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protocol12,13], and the backup NaCl-impregnated cellulose-fiber filter was used to measure volatilized NO3

– by ionchromatography. All of the sampling sites used the Teflon/citric acid filter pack configuration, and about half of thesites used both configurations sampling side by side.

Measurements of babs were used to estimate EC whenonly a Teflon-membrane filter (which cannot be ana-lyzed for EC) was available. Measurements of babs are ac-quired by densitometry that has been used byphotographers to evaluate black-and-white negatives.This method estimates filter transmission (babs) by mea-suring optical density with an incandescent broadbandlamp (400–650 nm, peaking at 575 nm) transmittedthrough a glass diffuser. Transmittance is measured be-fore and after Teflon-membrane exposure, and the dif-ference in the logarithms of the transmitted light isproportional to the absorption of the particulate deposit.

PM10 measurements at the six core sites were acquiredwith dual-channel, medium-volume sequential filter sam-plers (SFS).15 Sampling substrates, chemical analyses, andrelevant quality assurance/quality control procedures at thesatellite and boundary sites were consistent with those ofthe core sites as specified in Chow et al.15 Daily PM10 massand babs were acquired on 28 days between February 23and March 22, 1997, with chemical speciation performedon samples collected between March 2 and March 19.

RESULTSCollocated Precision

To establish consistency between the SFS and MiniVol,pairwise comparisons were made for the collocated mea-surements at the La Merced core site. Linear regressionshowed that both samplers were comparable for PM10 masswith an effective-variance-weighted linear regression slopeequal to unity within ±10% (0.95 ± 0.07), intercept close tozero (–2.8 ± 3.7 µg/m3), and high correlation (r = 0.97). Aconsistent relationship (r = 0.88) was also found for babs, with

the SFS (independent variable) yielding higher babs measure-ments (slope = 0.78 ± 0.11) than the MiniVol, with a no-table intercept (10.5 ± 7.8 Mm–1). Forcing the interceptthrough zero resulted in a slope of 0.93 ± 0.11. High correla-tions were found for all elements except bromine (0.89 < r <0.99 for Al, Si, K, Ca, Ti, V, Mn, Fe, Ni, Cu, Zn, Sr, Zr, and Pb;r = 0.7 for Br), which may be due to the volatile nature of Br.Comparable agreement was also found for S, with a slope of0.98 ± 0.05, intercept of –0.10 ± 0.08 µg/m3, and correlationof 0.95. Variations in size-selective inlets (Sierra AndersonSA2541 medium-volume PM10 inlet vs. Airmetrics impac-tor), sampling flow rates (30 L/min vs. 5 L/min), and flowcontrol devices (differential pressure gauge vs. pressure sen-sor) between the SFS and MiniVol, respectively, may havecontributed to the observed differences. These comparisonsdemonstrate that spatial differences exceeding ±10% are notdue to measurement uncertainty but represent real differ-ences in ambient concentrations.

Distribution of PM10 MassTable 2 summarizes the 24-hr PM10 mass statistics for allsites. The two source-oriented sites near an unpaved road(S11) and an industrial area with congested diesel trafficand vehicle-suspended dust (S03) averaged 134 ± 56 µg/m3

and 130 ± 60 µg/m3, respectively. These two sites super-imposed large local contributions onto areawide PM10

concentrations and were excluded from spatial averages.The temporal/spatial average PM10 was 66 ± 28 µg/m3 forthe remaining 19 satellite sites. Site averages of the north-ern sites (G02, R04, G05, G06, R16, and G18) were ~10%higher than the all-site average. More uniform concen-trations were found for the gradient sites surrounding thecentral La Merced site, located in the downtown com-mercial and financial district.15 The highest 24-hr averagePM10 concentration was 273 µg/m3, found on March 4 atthe S03 site. The two source-oriented sites frequentlyexceeded the U.S. 24-hr PM10 NAAQS of 150 µg/m3, with 14

Table 1. (cont.)


Boundary SitesAJUa Ajusco 19.0522 –99.2452 ~19.8 km SW of the city center on the

rooftop of a schoolCHAa Chalco 19.2353 –98.9167 ~29.4 km SE of the city center X

adjacent to a university farm withcows and sheep

CUAa Cuautitlan 19.7133 –99.1886 ~30.5 km NW of the city center in themiddle of an agricultural field

TEOa Teotihuacan 19.6850 –98.8664 ~39.9 km NE of the city center inPirámides Park


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occurrences found at site S11 and 8 occurrences at site S03.Exceedances of the daily PM10 NAAQS were also found atthe three northern sites (G02, G05, and G18) on three dif-ferent days (February 27, March 1, and March 3, respectively).

Local sources had a large influence on the highestconcentrations that did not affect nearby sites. Daily av-erages across the satellite sites showed that March 4 (97 ±19 µg/m3) and 5 (99 ± 21 µg/m3) were the highest PM10

concentration days. With the one exception at G21 on

March 4 (54.8 µg/m3), PM10 concentrations at all sites ex-ceeded the temporal-spatial 19-site average by 11–200%on March 4 and 5. Higher concentrations at the core siteswere also measured on these days.15 High wind speeds(6–13 m/sec) were recorded during the afternoon of March5 at Benito Juarez International Airport.15 Dry winterweather coupled with high winds facilitated the entrain-ment and suspension of particles, resulting in elevated PM10

mass and crustal concentrations thoughout the air basin.

Table 2. Statistical summary of PM10

mass concentrations for the Mexico City Aerosol Characterization Study between February 23 and March 22, 1997.

Date of Average ± TotalMaximum Maximum Minimum Standard Deviation Temporala Spatialb Number

Site Type Site (µg/m3) Value (µg/m3) (µg/m3) Variation Variation in Average

Gradient satellite G02 159.0 02/27/97 30.0 84.9 ± 31.8 37.5% 29.5% 26G05 166.8 03/01/97 20.2 69.6 ± 34.2 49.1% 6.2% 27G06 127.4 03/05/97 29.9 76.5 ± 25.1 32.8% 16.7% 27G08 128.7 03/05/97 28.3 68.6 ± 24.5 35.6% 4.7% 28G09 126.5 02/24/97 5.5 67.4 ± 29.4 43.6% 2.8% 28G12 122.0 03/16/97 1.3 56.7 ± 25.0 44.1% –13.6% 26G17 91.2 03/04/97 23.5 58.1 ± 17.8 30.6% –11.4% 26G18 229.4 03/03/97 41.7 94.8 ± 35.0 36.9% 44.5% 26G20 90.0 03/06/97 19.2 52.3 ± 15.9 30.5% –20.2% 28G21 78.5 03/03/97 0.4 44.8 ± 16.1 36.0% –31.7% 27G22 85.3 03/05/97 15.9 51.2 ± 18.0 35.1% –21.9% 28G23 83.2 03/04/97 11.1 44.4 ± 15.9 35.7% –32.2% 26G25 143.1 03/17/97 5.3 63.7 ± 26.0 40.8% –2.8% 27G26 106.1 03/05/97 16.0 61.2 ± 19.6 32.0% –6.7% 27G27 102.1 03/04/97 16.0 54.5 ± 18.8 34.5% –17.0% 24

Receptor satellite R04 145.9 02/25/97 41.6 95.8 ± 30.9 32.2% 46.1% 27R13 144.2 02/24/97 28.3 70.9 ± 25.3 35.6% 8.2% 28R16 102.5 03/06/97 35.7 72.3 ± 17.2 23.8% 10.2% 25R24 115.4 03/04/97 14.2 58.4 ± 27.0 46.2% –10.9% 27Average of gradient andreceptor satellite sites (19) 229.4 03/03/97 0.4 65.6 ± 28.2 43.0% 508

Source satellite S03 272.8 03/04/97 45.7 130.0 ± 59.7 46.0% –1.6% 28S11 227.5 02/26/97 17.5 134.3 ± 55.6 41.4% 1.6% 28Average of sourcesatellite sites (2) 272.8 03/04/97 17.5 132.2 ± 57.2 43.3% 56

Boundary Ajusco 94.9 03/04/97 10.9 47.8 ± 24.3 50.7% –8.8% 23Chalco 122.2 03/21/97 10.6 69.7 ± 27.9 40.0% 33.0% 22Cuautitlan 70.5 03/04/97 10.6 42.9 ± 18.2 42.5% –18.1% 18Teotihuacan 245.8 02/28/97 4.7 48.1 ± 52.7 109.6% –8.3% 24Average of boundary sites (4) 245.8 02/28/97 4.7 52.4 ± 35.4 67.6% 87

Core Tlalnepantla (TLA) 77.7 03/10/97 26.2 57.9 ± 12.7 21.9% –18.2% 24Xalostoc (XAL) 181.4 03/04/97 42.2 103.6 ± 32.7 31.6% 46.3% 28La Merced (MER) 126.7 03/05/97 2.4 57.2 ± 22.2 38.9% –19.2% 28Netzahualcoyotl (NET) 267.3 02/25/97 15.8 108.3 ± 60.0 55.4% 53.0% 22Cerro de la Estrella (CES) 104.9 02/27/97 21.2 61.2 ± 20.1 32.8% –13.6% 25Pedregal (PED) 60.0 03/04/97 12.4 39.4 ± 12.2 31.0% –44.3% 26Average of core sites (6) 267.3 02/25/97 2.4 70.8 ± 39.2 55.3% 153

aTemporal coefficient of variation is the standard deviation divided by the average for each site; bDifference between the site average and the area-wide spatial average of the 19 gradientand receptor sites divided by this 19-site average.

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Average PM10 concentrations at the boundary siteswere 40–50 µg/m3, except at the Chalco site (70 µg/m3).PM10 concentrations exceeded 150 µg/m3 twice at theTeotihuacan site on February 28 (246 µg/m3) and March7 (170 µg/m3). These did not correspond to days whenvalley-wide elevated concentrations were found. This callsinto question the original designation of this site as rep-resenting regional-scale PM10 levels.

Spatial coefficients of variation for gradient and re-ceptor sites were examined for each day to evaluate spa-tial homogeneity and site-specific deviations. Site-averagePM10 concentrations varied by more than twofold (44–96 µg/m3) within the study domain. The day-to-day spa-tial coefficients of variation among all sites ranged from20% (March 4 and 9) to 56% (March 17), similar to thesingle-site temporal coefficients of variation that rangedfrom 24% (site R16) to 49% (site G05). Meteorology af-fected PM10 in the entire Valle de Mexico, along withlocal and neighborhood source emissions. The averageareawide coefficient of variation was 43% among the 19gradient and receptor satellite sites. The greatest varia-tions were found in the north near industrial areas withheavy traffic. Differences between single- and all-siteaverages ranged from –32% (G23) to 46% (R04).

Zones of RepresentationFigure 2 illustrates average PM10 concentration contoursfor the 21 satellite sites and six core sites. Zones of influ-ence for the two fugitive dust-dominated sites (S03 andS11) are small, as PM10 concentrations decreased by 20–40% within 2–3 km. This zone probably would have beensmaller yet if additional samplers had been located alongthe strong gradients. Chow et al.,16 with a denser PM10 sam-pling network, found that zones of influence around indi-vidual fugitive dust emitters were less than 1 km in Nevada’sLas Vegas Valley. The difference was even greater for thehigh valley-wide PM10 concentrations on March 5. PM10

concentrations at the S11 site (212 µg/m3) were ~50% higherthan at the nearby R13 site ~4 km NW. Similarly, PM10 con-centrations at the S03 site (265 µg/m3) were ~70% higherthan at the nearby R04 site ~3 km NNE. A cluster of highPM10 concentrations >120 µg/m3 was found at the gradi-ent sites (G02, G05, G06, G08, and G18) around theXalostoc core site, but these levels were half the concentra-tions at the S03 site. Figure 2 shows that the Xalostoc site,situated in the urban/industrial sector with congestedheavy-truck/older-vehicle traffic, was at the center of a NNEcluster with elevated PM10 concentrations caused by largenearby or neighborhood-scale influences. This was also ob-served at the Netzahualcoyotl site, which was surroundedby paved and unpaved roads, athletic fields with loose dirtsurfaces, open landfills, and lower-income housing with-out ground cover. The Netzahualcoyotl site received large

middle- to neighborhood-scale source contributions.Table 3 examines the zone of representation of PM10

mass for each of the six core sites by comparing it with spa-tial averages for the surrounding satellite sites. The numberof sites included in a spatial average increases as distancefrom the core site increases. Spatial uniformity of ±1% wasfound for the 12 satellite sites located within a 10-km radiusof the La Merced site. The zone of representation of the LaMerced site is large, as seen from the concentration con-tours shown in Figure 2. Spatial uniformity of ±10 µg/m3

was found to extend 10–15 km from the NW, W, to the SSEfrom the site. This implies that La Merced represented gen-eral population exposure within a neighborhood-scale(0.5–4 km) to urban-scale (4–100 km) domain. The Cerro dela Estrella site also showed ±10% spatial uniformity for thetwo neighborhood-scale sites around it and ±25% unifor-mity for the three sites located between 4 and 10 km awayand the 14 sites located beyond 10 km. There were no neigh-borhood-scale sites around the Pedregal site. The three sites

Figure 2. Concentration contours of average PM10 mass interpolatedfrom the six core sites and 21 satellite sites for the period of February23–March 22, 1997. The six core sites are Tlalnepantla (TLA), Xalostoc(XAL), La Merced (MER), Netzahualcoyotl (NET), Pedregal (PED), andCerro de la Estrella (CES). The 21 satellite sites include 15 gradient (G)sites, four receptor (R) sites, and two source (S) sites.

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located 4–10 km from Pedregal were also within ±20% ofaverage PM10 at that site. The Xalostoc and Tlalnepantlasites showed ±20% spatial uniformity for the neighborhood-scale sites and exceeded 20% for sites beyond 4 km. TheNetzahualcoyotl site represents a local-scale spatial domain.

CorrelationsIntersite correlation coefficients were calculated for PM10

mass, Si, babs, S, and NH3 as indicators of different sourcescausing the non-homogeneity. Si is a good indicator for fu-gitive dust, babs is an indicator of vehicle exhaust, and S is anindicator of secondary aerosol. NH3 (which originates fromsewers, animals, and wastewater treatment) reacts withH2SO4 and HNO3. Coefficients of >0.8 mean fairly strongcorrelation, those 0.5–0.8 indicate moderate correlations,and those <0.5 are negligible correlations. Strong correla-tions were observed when pairs of variables originated fromthe same source, were equally affected by transport and

dispersion, or were similarly affected by chemical transfor-mation. Strong correlations were found for PM10 mass amonggradient sites (G22, G25, and G26) that were ~0.5–4 km fromthe La Merced site, and among gradient sites (G17, G12,and G27) between the La Merced site and other core sites.Moderate correlations were found among satellite sites (R04,G02, G05, and G06) in the northeastern industrial area thatwere ~2–6 km from the Xalostoc site. Time-series plotsshowed that average Si concentrations followed the peaksand valleys of PM10 mass and constituted ~15–20% of PM10

mass. Intersite correlations of Si were high for most pairs ofsites, even those that were widely separated, indicating theabundance of area-wide resuspended dust and the effects ofcommon meteorology on dust availability, suspension, andmixing throughout the urban area.

Urban-scale correlations were not found for babs, withfour to five localized covariance clusters within the basin.These babs correlations depended more on proximity to

Table 3. Comparison of PM10

mass between core sites and spatial averages of PM10

mass from surrounding satellite sites in Mexico City.

Spatial Average PM10

(µg/m3)Core Site between Feb 23 and March 22, 1997 Difference of

Average PM10

Neighborhood Urban Urban Core SiteCore Concentration # in Scale Scale Scale Average fromSite (µg/m3) Average (<4 km)a (4–10 km)b (>10 km)c Spatial Averaged Surrounding Satellite Sites

TLA 57.9 ± 12.7 24 72.3 ± 17.2 –20% aR1676.4 ± 26.0 –24% bG17 G18

63.8 ± 14.0 –9% cG02, G05, G06, G08, G09, G12, G20, G21, G22, G23, G25, G26, G27,R04, R13, R24

XAL 103.6 ± 32.7 28 85.7 ± 9.6 21% aG02, G06, R0469.9 ± 13.0 48% bG05, G08, G09, G17, G18, G26

56.9 ± 9.7 82% cG12, G20, G21, G22, G23, G25, G27, R13, R16, R24

MER 57.2 ± 22.2 28 58.0 ± 3.4 –1% aG26, G27, R24e

56.4 ± 9.0 1% bG08, G09, G12, G17, G20, G21, G22, G23, G2580.7 ± 11.2 –29% cG02, G05, G06, G18, R04, R13, R16

NET 108.3 ± 60.0 22 67.4 ± 29.4 61% aG0964.6 ± 12.6 68% bG02, G08, G12, G27, R24

65.8 ± 16.6 65% cG05, G06, G17, G18, G20, G21, G22, G23, G25, G26, R04, R13, R16

CES 61.2 ± 20.1 25 63.8 ± 10.1 –4% aG12 R1350.0 ± 5.1 22% bG22, G23, G27

69.2 ± 14.9 –12% cG02, G05, G06, G08, G09, G17, G18, G20, G21, G25, G26, R04, R16,R24

PED 39.4 ± 12.2 26 39.4 ± 12.2 0% anone46.8 ± 3.8 –16% bG21, G22, G23

69.1 ± 13.3 –43% cG02, G05, G06, G08, G09, G12, G17, G18, G20, G25, G26, G27, R04,R13, R16, R24

aSites <4 km from core site; bSites 4–10 km from core site; cSites >10 km from core site; dDifference between the core site average PM10

and the spatial average PM10

of the satellite siteswithin the specified spatial scales; eR24 was collocated with MER. The spatial average and difference do not change appreciably when R24 is removed.

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heavily traveled roads than on site classification. Figure 3shows that babs concentration contours were distinctly dif-ferent from those of PM10 mass, with strong concentrationgradients surrounding the two northern industrial sites (i.e.,R16, near the Tlalnepantla site, and S03, near the Xalostocsite). PM10 S concentrations were highly correlated (r > 0.80)among all sites with smooth concentration contours. Fig-ure 4 shows that S concentrations in the city center andnorthern portion were ~10% higher than in other areas,with higher concentration gradients found around theXalostoc site. Secondary SO4

2– that forms in the atmospherewas more homogeneously distributed throughout the areathan were the primary emissions from dust and vehicleexhaust. Spatial correlations of NH3 were high (r > 0.8) forsites surrounding the La Merced site (G12, G17, G20, G21,G22, G23, G25, G26, and G27). Figure 5 shows that theconcentration contours exhibited a strong spatial gradientaround the G09 site, located 3.1 km NW of the Netzahual-coyotl site near the sewage treatment plant.

Spatial Patterns of PM10 ComponentsMaterial balances shown in Table 4 include geologicalmaterial, (NH4)2SO4, NH4NO3, organics, soot, salt, andother-than-geological trace elements. Consistent (r =0.95) and linear relationships (SO4

2– vs. S slope = 2.98 ±0.08, intercept = –0.07 ± 0.17 µg/m3) were found betweenwater-soluble SO4

2– and total S measurements, indicat-ing that most S was of secondary origin and was prob-ably neutralized by NH3. SO4

2– was estimated from Smeasurements at the 12 sites with the single-filter-packsampling configuration. The stoichiometric ratios of NH4,SO4

2–, and NO3– were used to calculate (NH4)2SO4 and

NH4NO3 concentrations. Site-specific EC, or soot, was alsoestimated from babs for sites without quartz filters usingrelationships from nearby sites with both measurements.Table 4 shows that the regression coefficients were simi-lar, in the range of 7.5–8.6 m2/g. For the nine sites whereorganics and NH4NO3 were not measured, the unidenti-fied mass was larger.

Figure 3. Concentration contours of average PM10 babs at the sixcore sites and 21 satellite sites for the period of February 23–March22, 1997. The six core sites are TLA, XAL, MER, NET, PED, and CES.The 21 satellite sites include 15 gradient (G) sites, four receptor (R)sites, and two source (S) sites.

Figure 4. Concentration contours of average PM10 S at the six coresites and 21 satellite sites for the period of February 23–March 22,1997. The six core sites are TLA, XAL, MER, NET, PED, and CES. The21 satellite sites include 15 gradient (G) sites, four receptor (R) sites,and two source (S) sites.

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A comparison of non-volatilized NO3– to total NO3

–

(sum of non-volatilized NO3– from the front quartz-fiber

filter and volatilized NO3– from the backup NaCl-impreg-

nated cellulose-fiber filter) showed that average NO3– vola-

tilization was as much as ~20% (r = 0.88) at the satellitesites and ~7% (r = 0.98) at the boundary sites. Because theMiniVol did not use denuders as did the SFS, some HNO3

was collected with volatilized particles on the backup fil-ter. Because NO3

– volatilization was site-dependent, onlynon-volatilized NO3

– was used in the material balance.Geological material was the largest PM10 component,

accounting for 38–58% of measured PM10 mass and rang-ing from 20.3 µg/m3 at G21 (gradient site between LaMerced and Pedregal) to 55.4 µg/m3 at G18 (gradient sitebetween Tlalnepantla and Xalostoc with heavy vehicletraffic). Organics were the second-largest component,accounting for 18–33% of PM10 and ranging from 11.8µg/m3 at G12 (gradient site between La Merced and Cerrode la Estrella) to 23.7 µg/m3 at R16 (receptor site nearTlalnepantla surrounded by traffic, grain elevators, and

corn mills). Soot accounted for 2–18% of PM10 and rangedfrom 1.6 µg/m3 at G05 (the most northeastern commer-cial/residential site) to 13.0 µg/m3 at R16. The two siteswith the highest combustion and fugitive dust compo-nents (R16 and G18, respectively) were both situated inthe northern valley with heavy vehicle traffic nearby.However, the geological component at the R16 site (27.7µg/m3) was only half of that found at the G18 site.

Average (NH4)2SO4 concentrations were similar at allsites, ranging from 7.1 µg/m3 at G12 to 9.5 µg/m3 at G18and accounting for 9–18% of PM10. Non-volatilizedNH4NO3, present at 40–64% of (NH4)2SO4 levels, exhib-ited similar spatial homogeneity ranging from 3.5 to 4.9µg/m3. Non-geological trace elements (Na, Mg, P, K, Ti, V,Cr, Mn, Co, Ni, Cu, Zn, Ga, As, Se, Br, Rb, Sr, Y, Zr, Mo, Pd,Ag, Cd, In, Sn, Sb, Ba, La, Au, Hg, Tl, Pb, and U), presentat 2–4% levels, showed the lowest concentration (1.1µg/m3) at G21 and the highest (2.9 µg/m3) at G18. Thesetrace metals may have been suspended with geologicalcomponents or as separate entities. Salt content was low(<1.5%), typically less than 0.5 µg/m3, with the exceptionof the four northern sites (G02, R04, G06, and G18) closeto dry Lake Texcoco; salt levels were greater than 1 µg/m3

at these sites. For the sites with comprehensive chemis-try, the material balance explained PM10 mass within±10%. For sites without the quartz-fiber filter measure-ments, 20–30% of PM10 mass could not be accounted forbecause organics and NO3

– were not directly measured.The S03 and S11 source-oriented sites were dominated

by geological components (63–64% of PM10 mass) of 30–65µg/m3 more than the other satellite sites. Higher trace ele-ment concentrations (2.4–2.8 µg/m3) were also found, indi-cating that most of these concentrations were in the roaddust. (NH4)2SO4 and soot contributed ~6 µg/m3 each. Fugitivedust emitters in the vicinity of these monitoring sites hadconsiderable impact on the high and localized PM10 loadings.

The four boundary sites displayed subregional ratherthan regional or boundary characteristics. Geological com-ponents contributed 48 µg/m3 at the Chalco site and 20–21µg/m3 at the other sites. Organic material was also high atthe Chalco site (11.9 µg/m3), compared with 6.5–8.8 µg/m3

at the other sites. Soot was similar at all boundary sites, inthe range of 2.1–2.8 µg/m3. NH4NO3 ranged from 1 µg/m3 atthe Teotihuacan site to 4.5 µg/m3 at the Ajusco site, prob-ably reflecting receipt of HNO3 from the urban areas undernortherly airflows as well as higher NH3 levels at Ajusco. Saltand trace elements were less than 2.5% of PM10 at each site.(NH4)2SO4 was highest at the Cuautitlan site (8.6 µg/m3) and4.5–5.7 µg/m3 at the other sites. The Cuautitlan site is lo-cated south of the city of Tula, where approximately half ofthe SO2 in Mexico is emitted.17,18 Based on the boundarySO4

2– at Teotihuacan, about two-thirds of the SO42– in Mexico

City derives from sources external to the Valle de Mexico.

Figure 5. Concentration contours of average NH3 at the 21 satellitesites for the period of February 23–March 22, 1997. The 21 satellitesites include 15 gradient (G) sites, four receptor (R) sites, and twosource (S) sites.

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Tabl

e 4.

Ave

rage

PM

10 m

ateria

l bala

nce a

t the

satel

lite a

nd b

ound

ary s

ites d

urin

g th

e Mex

ico C

ity A

eros

ol C

hara

cteriz

ation

Stu

dy.

Soot

vs.

bab

sLi

near

Reg

ress

ion

Stat

istic

sSa

mpl

erCa

lcul

ated

Mea

sure

dSo

urce

of

Filte

r Pac

kGe

olog

ical

b O

rgan

icsb

Soo

tbSO

42–b

NO3–b

Saltb

Elem

ents

bUn

iden

tifie

dbM

ass

Mas

sSl

ope

Inte

rcep

tRe

gres

sion

Site

Conf

ig.a

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(µg/

m3 )

(m2 /g

)(M

m–1

)Da

ta

Grad

ient

and

Rec

epto

r Sat

ellit

e Si

tes

G02

TC an

d QN

43.8

915

.04

4.27

8.51

3.52

1.09

1.92

6.68

78.2

384

.91

G05

TC o

nly

31.5

01.

627.

880.

791.

5426

.29

43.3

469

.63

7.92

41.6

4XA

LG0

6TC

onl

y42

.48

3.30

8.57

1.19

1.97

19.0

257

.50

76.5

37.

9241

.64

XAL

G08

TC o

nly

36.4

44.

537.

930.

701.

5417

.50

51.1

368

.63

7.92

41.6

4XA

LG0

9TC

onl

y29

.01

5.41

7.25

0.62

1.36

23.7

443

.65

67.3

88.

2629

.42

MER

G12

TC an

d QN

27.5

211

.76

4.24

7.14

3.95

0.51

1.37

0.19

56.4

756

.67

G17

TC o

nly

26.4

85.

628.

700.

602.

0114

.64

43.4

258

.06

7.51

35.8

6G1

8G1

8TC

and

QN55

.41

20.8

87.

359.

474.

541.

292.

87–7

.04

101.

8194

.77

G20

TC o

nly

22.4

03.

398.

280.

341.

2916

.60

35.7

052

.30

8.26

29.4

2M

ERG2

1TC

and

QN20

.26

13.0

63.

967.

824.

840.

191.

07–6

.42

51.2

144

.79

G22

TC o

nly

24.4

64.

418.

700.

321.

3511

.96

39.2

351

.19

8.26

29.4

2M

ERG2

3TC

and

QN22

.12

12.2

43.

577.

364.

480.

221.

13–6

.67

51.1

244

.45

G25

TC an

d QN

30.2

113

.29

4.32

7.99

4.59

0.50

1.59

1.26

62.4

963

.74

G26

TC an

d QN

26.4

814

.15

5.30

8.96

4.79

0.56

1.75

–0.7

961

.99

61.1

9G2

7TC

and

QN24

.13

14.0

46.

027.

684.

880.

311.

33–3

.94

58.3

954

.45

R04

TC o

nly

53.8

25.

938.

391.

202.

2124

.22

71.5

495

.77

7.92

41.6

4XA

LR1

3TC

onl

y32

.85

4.98

7.53

0.54

1.49

23.5

547

.38

70.9

38.

5724

.44

CES

R16

TC an

d QN

27.7

223

.73

13.0

49.

043.

730.

772.

31–8

.06

80.3

472

.29

R24

TC o

nly

25.9

44.

468.

680.

401.

5417

.37

41.0

358

.40

8.26

29.4

2M

ERAv

erag

e31

.77

15.2

85.

048.

204.

390.

641.

66–1

.41

66.9

865

.57

Sour

ce S

atel

lite

Site

sS0

3TC

onl

y81

.96

6.29

9.08

1.66

2.81

28.2

210

1.80

130.

027.

9241

.64

XAL

S11

TC o

nly

85.4

76.

328.

610.

842.

4430

.63

103.

6713

4.30

8.57

24.4

4CE

SAv

erag

e83

.72

6.30

8.85

1.25

2.62

31.5

610

2.74

132.

16Bo

unda

ry S

ites

Ajus

coTC

and

QN21

.30

8.77

2.25

5.65

4.47

0.15

0.90

4.32

43.4

947

.81

Chalc

oTC

and

QN48

.34

11.9

02.

815.

162.

460.

331.

56–2

.88

72.5

769

.69

Cuau

titlan

TC an

d QN

21.8

16.

502.

638.

642.

060.

161.

030.

1142

.83

42.9

3Te

otih

uaca

nTC

and

QN20

.55

7.00

2.07

4.51

1.04

0.06

0.83

11.9

936

.07

48.0

5Av

erag

e28

.23

8.64

2.44

5.99

2.58

0.18

1.08

3.27

49.1

352

.40

a TC =

Teflo

n-m

embr

ane f

ront

filter

with

citri

c acid

-impr

egna

ted ce

llulo

se-fi

ber b

acku

p filt

er. Q

N = Q

uartz

-fibe

r fro

nt fil

ter w

ith N

aCl-i

mpr

egna

ted ce

llulo

se-fi

ber b

acku

p filt

er. Li

near

regr

essio

n stat

istics

are u

sed t

o calc

ulate

soot

and S

O 42– co

mpo

sitio

ns at

sites

with

out Q

N fil

ters.

Regr

essio

n sta

tistic

s for

bab

s vs. E

C ar

e bas

ed o

n da

ta fro

m th

e site

with

the h

ighe

st co

rrelat

ion

with

in th

e clu

ster . R

egre

ssio

n sta

tistic

s for

SO 42–

vs. S

are d

erive

d fro

m al

l data

sets

(slo

pe =

2.9

8, in

terce

pt =

–0.

07 µ

g/m

3 ); b Th

e geo

logi

cal

com

pone

nt is

estim

ated

as 1

.89

× Al

+ 2

.14

× Si

+ 1

.4 ×

Ca +

1.4

3 ×

Fe to

acco

unt fo

r unm

easu

red

oxid

es. O

rgan

ic m

atter

is es

timate

d as

1.2

× O

C to

acco

unt fo

r unm

easu

red

hydr

ogen

and

oxyg

en. S

oot is

estim

ated

to eq

ual E

C at

sites

with

QN

filter

pac

ks,

or as

(bab

s–lin

ear r

egre

ssio

n int

erce

pt)/l

inea

r reg

ress

ion s

lope

at si

tes w

ith on

ly TC

filter

pack

s. (N

H 4) 2SO4 is

estim

ated a

s 1.3

75 ×

SO 42–

at si

tes w

ith Q

N filt

er pa

cks,

or as

1.37

5 × 2.

98 ×

S at

sites

with

only

TC fil

ter pa

cks.

NH4NO

3 is es

timate

d as 1

.29 ×

NO 3– . S

altis

estim

ated

by 1

.65

× Cl

. Elem

ents

are t

he o

ther-

than

-geo

logi

cal e

lemen

ts (e

xclu

ding

Al,

Si, C

a, Fe

, Cl,

and

S). U

nide

ntifi

ed is

the d

if fer

ence

betw

een

the s

um o

f the

mate

rial b

alanc

e (ca

lculat

ed m

ass)

and

mea

sure

d m

ass.

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CONCLUSIONSThe spatially dense monitoring network is useful for un-derstanding PM10 levels in the Valle de Mexico and forevaluating spatial representation of the fixed monitoringsites. On average, PM10 concentrations varied from 20 to56% about the site average within the study period andfrom 24 to 49% among the 19 non-source-oriented satel-lite sites. This implies that influences from neighborhood-scale emitters and meteorology on elevated PM10

concentrations are equally important. Geological materialwas the largest PM10 component (38–58% of PM10 mass)throughout the city, followed by organic aerosol (18–33%of PM10 mass). Satellite sites located in the median of heavilytraveled divided streets (e.g., R16 and G18) showed thehighest impacts from vehicle exhaust, with elevated or-ganics, soot, and geological contributions. Abundances oftrace metals, present at 2–4% of PM10, covaried with thefugitive dust contribution, indicating that these were alsopresent in the geological source material. Salt contributionswere low (<1.5%), with >1 µg/m3 found only at sites in thenorthern valley (G02, R04, G06, G18) near a dry lakebed.Average (NH4)2SO4 and NH4NO3 changed by less than 2.4and 1.4 µg/m3, respectively, throughout the city. NH4NO3

concentrations were present at 40–64% of the (NH4)2SO4

levels. The transport of primary and secondary SO42– from

north to south was apparent and accounted for about two-thirds of the SO4

2– observed in Mexico City.Spatial correlations and isopleths show that the long-

term urban/industrial Tlalnepantla and Xalostoc sites andthe commercial/residential Netzahualcoyotl site repre-sent middle-scale (0.1–0.5 km) to neighborhood-scale(0.5–4 km) PM10 concentrations with spatial uniformityof 20–60%. This is due to industrial/commercial activi-ties and vehicle-related emissions in the area. The ur-ban/commercial La Merced site represents neighborhood-and urban-scale (4–100 km) exposures. Zones of influ-ence from fugitive dust emitters (S03 and S11) are small,with rapid concentration decreases at a short distancefrom the source.

ACKNOWLEDGMENTSThis work was sponsored by the Atmospheric ChemistryProgram of the U.S. Department of Energy, Office of Bio-logical and Environmental Research, Environmental Sci-ences Division. The authors acknowledge the support fromthe Instituto Mexicano del Petróleo, with special thanksto Marisa Ruiz and Teresa Limón for their invaluable fieldsupport. The authors also acknowledge DouglasLowenthal, Steven Kohl, Matt Gonzi, and NormanMankim from the Desert Research Institute for their helpwith graphics and assembly of this manuscript. Mr. PeterLunn and Mr. Rick Petty from the U.S. Department ofEnergy provided substantial support and encouragement.

REFERENCES1. Ambient Air Quality Surveillance. Code of Federal Regulations, Appendix

D, Subpart G, Part 58, Title 40; U.S. Government Printing Office: Wash-ington, DC, 2001; pp 244-273.

2. Watson, J.G.; Chow, J.C.; DuBois, D.W.; Green, M.C.; Frank, N.H.;Pitchford, M.L. Network Design Principles for Population-OrientedMonitoring of Suspended Particles. In Proceedings, Health Effects ofParticulate Matter in Ambient Air; Vostal, J.J., Ed.; Air & Waste Manage-ment Association: Pittsburgh, PA, 1998; pp 461-472.

3. Doran, J.C.; Abbott, J.L.; Archuleta, J.; Bian, X.; Chow, J.C.; Coulter,R.L.; de Wekker, S.F.J.; Edgerton, S.A.; Fernandez, A.; Fast, J.D.; et al.The IMADA-AVER Boundary Layer Experiment in the Mexico CityArea; Bull. Amer. Meteorolog. Soc. 1998, 79 (11), 2497-2508.

4. Edgerton, S.A.; Arriaga, J.L.; Archuleta, J.; Bian, X.; Bossert, J.E.; Chow,J.C.; Coulter, R.L.; Doran, J.C.; Doskey, P.V.; Elliot, S.; et al. Particu-late Air Pollution in Mexico City: A Collaborative Research Project; J.Air & Waste Manage. Assoc. 1999, 49 (10), 1221-1229.

5. Streit, G.E.; Guzman, F. Mexico City Air Quality: Progress of an Inter-national Collaborative Project to Define Air Quality Management Op-tions; Atmos. Environ. 1996, 30, 723-733.

6. Noll, K.E.; Miller, T.L. Air Monitoring Survey Design; Ann Arbor Sci-ence: Ann Arbor, MI, 1977.

7. Nesbitt, K.J.; Carter, K.R. Integration of Immunoassay Field Analyti-cal Techniques into Sampling Plans. In Principles of Environmental Sam-pling, 2nd ed.; Keith, L.H., Ed.; American Chemical Society:Washington, DC, 1996; pp 727-735.

8. Watson, J.G.; Chow, J.C. Ambient Air Sampling. In Aerosol Measure-ment: Principles, Techniques and Applications; Willeke, K., Baron, P.,Eds.; Wiley & Sons: New York, 2001; pp 821-844.

9. Watson, J.G.; Chow, J.C.; Frazier, C.A. X-Ray Fluorescence Analysis ofAmbient Air Samples. In Elemental Analysis of Airborne Particles, Vol.1; Landsberger, S., Creatchman, M., Eds.; Gordon and Breach Sci-ence: Amsterdam, 1999; pp 67-96.

10. Chow, J.C.; Watson, J.G.; Hackett, E.I.; Hinsvark, B.A. Method No.303A: General Method for the Preparation and Extraction of Envi-ronmental Samples for Trace Metal or Ion Analysis. In Methods of AirSampling and Analysis, 4th ed.; Lodge, J.P., Ed.; Air & Waste Manage-ment Association: Pittsburgh, PA, 2002; accepted for publication.

11. Chow, J.C.; Watson, J.G. Ion Chromatography in Elemental Analysis. InElemental Analysis of Airborne Particles, Vol. 1; Landsberger, S., Creatchman,M., Eds.; Gordon and Breach Science: Amsterdam, 1999; pp 97-137.

12. Chow, J.C.; Watson, J.G.; Pritchett, L.C.; Pierson, W.R.; Frazier, C.A.;Purcell, R.G. The DRI Thermal/Optical Reflectance Carbon AnalysisSystem: Description, Evaluation and Applications in U.S. Air QualityStudies; Atmos. Environ. 1993, 27A (8), 1185-1201.

13. Chow, J.C.; Watson, J.G.; Crow, D.; Lowenthal, D.H.; Merrifield, T.Comparison of IMPROVE and NIOSH Carbon Measurements; AerosolSci. Technol. 2001, 34 (1), 23-34.

14. Horvath, H. Atmospheric Light Absorption: A Review; Atmos. Environ.1993, 27A (3), 293-317.

15. Chow, J.C.; Watson, J.G.; Edgerton, S.A.; Vega, E. Chemical Compo-sition of PM10 and PM2.5 in Mexico City during Winter 1997; Sci. TotalEnviron., in press.

16. Chow, J.C.; Watson, J.G.; Green, M.C.; Lowenthal, D.H.; DuBois, D.W.;Kohl, S.D.; Egami, R.T.; Gillies, J.A.; Rogers, C.F.; Frazier, C.A.; Cates,W. Middle- and Neighborhood-Scale Variations of PM10 Source Con-tributions in Las Vegas, Nevada; J. Air & Waste Manage. Assoc. 1999,49 (6), 641-654.

17. Carabias-Lillo, J.; Quadri de la Torre, G.; Fernández-Bremauntz, A.;Páramo-Figueroa, V.H.; Martínez-Castillejos, J. Primer Informe Sobre laCalidad del Aire en Ciudades Mexicanas 1996; Instituto Nacional deEcología: México City, 1997.

18. Carabias-Lillo, J.; Provencio-Durazo, E.; Fernández-Bremauntz, A.;Páramo-Figueroa, V.H.; Gutiérrez-Avedoy, V.; Martínez-Castillejos, J.Segundo Informe Sobre la Calidad del Aire en Ciudades Mexicanas 1997;Instituto Nacional de Ecología: México City, 1998.

About the AuthorsJudith C. Chow and John G. Watson are research profes-sors at the Desert Research Institute, University and Com-munity College System of Nevada, 2215 Raggio Pkwy.,Reno, NV 89512. Sylvia A. Edgerton is an associate pro-gram director for the Atmospheric Chemistry Program atthe National Science Foundation, 4201 Wilson Blvd., Suite775, Arlington, VA 22230. Elizabeth Vega and Elba Ortiz areatmospheric scientists with the Instituto Mexicano delPetróleo, Eje Central Lazaro Cardenas Num. 152, 07730Mexico DF, Mexico.

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