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Investigation of the Nocturnal PM Peaks for Evidence of Association with Population Health Risks in Two Border Cities.
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Investigation of the Nocturnal PM Peaks for Evidence of Association with Population Health Risks in Two Border Cities Jessica Gamez1; Donald J. Baca1; Hector A. Olvera1; Nancy Garcia1; Mario Garcia1; Fernando Astorga2; Jose H. Garcia3; Gerardo Mejia4; Kerry Kelly5; JoAnn Lighty5; Wen-Whai Li1,2 1 Department of Civil Engineering, 2 Environmental Science and Engineering, The University of Texas at El Paso; 3 Professional Department (Campus Ciudad Juárez), 4 Centro de Calidad Ambiental (Campus Monterrey), Instituto Tecnológico y de Estudios Superiores de Monterrey; 5 Institute for Combustion and Energy Studies, University of Utah
Abstract This paper presents the results of a study characterizing the physical and chemical properties associated with the nocturnal PM10 and PM2.5 spikes that occur in the calm early evening hours (from 6:00 p.m. to 9:00 p.m.) in the two sister border cities (El Paso and Ciudad Juarez) along the U.S.-Mexico border. It represents an ongoing task under a collaborative research effort among several SCERP universities to investigate the nocturnal PM peaks for evidence of association with population health risks. The nocturnal PM peaks previously observed at Sunland Park, New Mexico and several other cities along the U.S.-Mexico border were observed at the two new locations. The evening PM peak was observed to occur under low wind conditions (< 2 m/sec) with a strong correlation with preceding afternoon high to moderate wind conditions. The hourly PM particle count varied from less than 10,000 particles/cm3 in the afternoon to greater than 80,000 particles/cm3 in the evening hours during the study period. The total number of PM particles peaked in the morning as well as in the evening while the mode of the particle size changed from 20 nm to ~100 nm, indicating different PM sources may be responsible for the mass and number concentrations and agglomeration of particles in the atmosphere during the day may possibly plays a role. Larger particles (100 – 470 nm) were found to associate better than smaller particles (10 – 100 nm) with PM mass. Wind direction did not have an impact on the PM number concentrations whereas wind speed is negative correlated (although small) to both PM size fractions confirming the occurrence of PM peaks under low wind conditions. Further chemical and statistical analyses are underway.
Statement of Problem • insufficient continuous and time-resolved PM (PM10 and PM2.5) data and meteorological observations for the Ciudad Juarez metropolis • incomplete continuous and time-resolved PM (PM10 and PM2.5) data in El Paso to support the development of causal relationship between inhalation exposure and key physiological parameters, such as cardiopulmonary functions and blood chemistry. • Insufficient physical characterization of ambient PM
Research Objectives • Characterize the temporal and time-resolved PM2.5 and PM10 concentrations; • Identify the sources and locations of the PM evening peaks using the new data and existing data from the Sunland Park study; and • Associate the PM peaks to the concurrently monitored physiological data at two PdN locations
Study Locations CAMS12 ITESM
Experimental Setup • Instrumentation (CAMS 12, El Paso) • 1 TEOM for PM10; 1 TEOM for PM2.5 • 1 TSI 3321 APS for Particles between 0.5 and 20 μm • 1 Climet Particle Sizer for Particles between 0.5 and 20 μm • 1 TSI 3034 SMPS for Particles between 0.01 and 0.5 μm • Supplementary Meteorological Monitoring of Wind Speed, Wind Direction, Temperature, Pressure, Humidity, and others
Experimental Setup • Instrumentation (ITESM, Cd. Juarez) • 1 TEOM for PM10; 1 TEOM for PM2.5 • 1 DATARAM Continuous PM10 Monitors • 1 Climet Particle Sizer for Particles between 0.5 and 20 μm • 1 TSI 3034 SMPS for Particles between 0.01 and 0.5 μm • A METONE surface meteorological monitoring station for wind speed, wind direction, temperature, and pressure • (see presentation of “Near-instantaneous impacts of high PM episodes on cardiopulmonary function in healthy adults” by H.L.C. Meuzelaar)
Results • Multiple TEOM monitors (3 UTEP TEOMs for PM10 and PM2.5; 2 TCEQ TEOMs for PM10 and PM2.5) confirmed the existence of PM evening peak (> 50 % of time) at the site • PM peaks occur under low wind conditions (as previously reported by Li, et al 2005) and generally show a positive correlation to high wind events in the afternoons (Staniswalis, et al, in progress) • Associations with wind direction, health effects, and other variables are yet to be determined
Selected Daily Ultrafine and Fine Number Concentrations at CAMS 12
Selected Daily Ultrafine and Fine Number Concentrations at CAMS 12
Selected Daily Ultrafine and Fine Number Concentrations at CAMS 12
Average Ultrafine and Fine Particle Number Concentrations at CAMS 12
Average Ultrafine and Fine Particle Number Concentrations at CAMS 12
Average Ultrafine and Fine Particle Number Concentrations at CAMS 12
Transition of Particle Number Counts Between SMPS and APS in nm in μm
Results • Particle number concentrations appear to be bimodal at two ultrafine sizes (20 nm and 50 nm), but indistinguishable at coarse size. • The total number of particles vary diurnally with one peak in the morning (dominated by the 20 nm particles) and another in the evening (dominated by the 50 nm particles). • The total number of particles by hour vary from <10,000/cm3 in the afternoon to >80,000/cm3 in the morning or in the evening • PM mass concentrations are dominated by large (coarse) particles • PM mass determined from APS agreed well with that measured by TEOM. However, the APS is extremely sensitive to the sampling configuration and to isokinetic sampling. PM mass determined by APS may be manipulated by other factors less quantified (such as size-specific particle density, shape, humidity, agglomeration, etc).
Results • The angle between vectors in the bi-plot indicates the degree of linear relationship between the correspondent variables. The length of the vector represent the magnitude/strength of the variable in association with other variables • PM10 and PM2.5 (indicated as “Fine” in he figures) are closely correlated to each other, indicating the concurrence of the two PM mass fractions. • The hour of the day is positively correlated to both PM10 and PM2.5 meaning that both PM10 and PM2.5 peak at “highest hours” (nighttime) and that the signal of the evening peak is stronger than the morning peak. • Wind direction does not associate well with PM10 and PM2.5 mass concentrations since it is almost perpendicular (zero correlation) to each other.
Results • Wind speed is negative correlated (although small) to both PM size fractions, indicating that the occurrence of PM peaks under low wind conditions. • Particle counts in the range of 100 to 470 nm correlate well with the PM10 and PM2.5 mass concentrations • As expected, larger particles (100 – 470 nm) associate better than smaller particles (10 – 100 nm) with the PM mass. The results from APS are expected to support this trend • Again, wind direction does not have an impact on the number concentrations • The number of ultrafine particles do not contribute (or actually negatively correlated) to the PM mass while the contribution increases as the size of the particles increases
Summaries • Evening PM peaks occur frequently at CAMS 12 as well as previously observed in Sunland Park and Cd. Juarez indicating a regional phenomenon to be studied • PM particle number varies by hour ranging from a low of <10,000/cm3 to a high of >80,000/cm3. Health effects associated with exposures to these particles remained unresolved • The mode of PM particle number concentration changes from ~20 nm to >50 nm indicating either particle agglomeration during the day or potentially different PM sources in the region • Larger particles (100 – 470 nm) associate better than smaller particles (10 – 100 nm) with PM mass. • Wind direction does not have an impact on the number concentrations • Further statistical and chemical analyses will take place
ACKNOWLEDGMENTS This research was supported by a grant from the Southwest Consortium for Environmental Research and Policy (SCERP, Grant Number A-05-02). Some of the authors were partially supported by grants from the National Institute for Environmental Health Science (NIEHS-NIH, 5 S11 ESO 1339-02), Health Effects Institute grant (HEI, RFA 05-1B), U.S. EPA Undergraduate Research Experience, U.S. DOT Eisenhower Scholarship, UTEP ORSP, and/or UTEP College of Health Sciences. The contents of this research are solely the responsibilities of the authors and do not necessarily represent the official views of any of the above-mentioned agencies. The authors also appreciate the assistance received from Mr. Joe Bester and Dr. Manisha Singh of Thermo-Electron Inc. and support from UTEP CERM and Department of Civil Engineering.
