1. March 26, 2004EAS 4/88031 EAS 4/8803: Experimental Methods in AQ Week 11: Air Quality Management (AQM) Clean Air Act (History, Objectives, NAAQS) Emissions and Atmospheric Trends (Links) Principal Measurement Techniques (NOx, CO, SO 2 ) Measurement of CO (Exp 5) NDIR Method (Interferences, Stability, DL, Precision, Accuracy) Controlling O 3 and PM 2.5 Principal Measurement Techniques (O 3, PM 2.5 ) Atmospheric Transport & Photochemistry (NOx vs VOC, SOA) Controlling O 3, Emissions and Trends (GA) Measurement of O 3 (Exp 6) UV Absorption (Interferences, Stability, DL, Precision, Accuracy)

2. March 26, 2004EAS 4/88032

3. March 26, 2004EAS 4/88033

4. March 26, 2004EAS 4/88034

5. March 26, 2004EAS 4/88035

6. March 26, 2004EAS 4/88036 Attain “Good” NAAQS Nonattain “Bad” Can we expect recent cool & wet summers to continue?

7. March 26, 2004EAS 4/88037 If we can’t depend on the weather, then what can we control? Volatile Organic Compounds (VOCs) Nitrogen Oxides (NOx) Fuels, Paints, Solvents, & Vegetation Combustion Processes Ozone (O 3 ) Smog +

8. March 26, 2004EAS 4/88038 Photochemical Processes Leading to O 3 and PM SOA NOz An Assessment of Tropospheric Ozone Pollution, A North American Perspective, NARSTO, National Acad. Press, 2000.

9. March 26, 2004EAS 4/88039 VOC Sources in Columbus MSA (2000) Anthropogenic Sources: Gasoline Vehicles Solvents (Paints, Automotive Products, Adhesives, etc.) Carbon Black Lawn & Garden Bakeries Total: 385 tons per day

10. March 26, 2004EAS 4/880310 Ozone Isopleths Area of effective VOC control (most often highly populated areas) Volatile Organic Compounds (VOC) Nitrogen Oxides (NO x ) Constant [O 3 ] Low [O 3 ] High [O 3 ] NOx control effective (areas with high biogenics)

11. March 26, 2004EAS 4/880311 NO x Sources in Columbus MSA (2000) Total: 42 tons per day

12. March 26, 2004EAS 4/880312 Implementation of NOx Controls Since 2000, Full Implementation Expected by 2007 Annual, stricter vehicle emissions inspections Open burning ban in 45 counties Georgia Power phasing in NOx controls 30 ppm sulfur gasoline in 45 counties GA Power plants achieve NOx reduction in 45 counties Stricter peaking generator rule Large industrial source NOx reductions

13. March 26, 2004EAS 4/880313 2007 NOx Emissions in GA by Region and Source If Fully Implemented Georgia Total: 1480 tons/day Alabama Total (not shown): 998 tons/day

14. March 26, 2004EAS 4/880314 Significant improvements in regional air quality by 2007 with no additional controls (current SIP fully implemented)

15. March 26, 2004EAS 4/880315 Estimated Change in Regional Peak 8-hour Surface Ozone from August 17 th, 2000 to 2007 under the Existing Federal Control Strategies (ppbv) RegionAtlantaAugustaColumbusMacon Observed139111114134 4-km grid132 118100 89108 96143 128 % reduction11% 10% Region Maximum Daily Peak 8-hour Ozone Observed / Simulated 2000  2007 But will these existing controls be enough?

16. March 26, 2004EAS 4/880316 Attain “Good” NAAQS Nonattain “Bad”

17. March 26, 2004EAS 4/880317 Attain “Good” NAAQS Nonattain “Bad” Reality Theory Goal

18. March 26, 2004EAS 4/880318 Clarification CO Accuracy Assessment Time (minutes) CO span4,0 CO span1,0 CO span1 CO ZA CO span2 CO span3 CO span4 CO Analyzer Signal (V) Zero-air/Zero-mode = baseline Zero-air CO 0  CO nom ] 1 5 V  CO nom ] 2  CO nom ] 3  CO nom ] 4 zero-mode CO sensi (ppb/V) =  [CO nomi ] /  CO spani ZT effi = (CO spani – CO spani,0 ) / (CO spani – CO 0 ) > 0.9!! CO net (V) = CO raw – CO 0ipol  CO (ppb) = CO net * CO sens DL (ppb) = t * STD(CO 0 * ) * CO sens P (%) = t * STD(CO sens ) / AVG(CO sens ) *100 A 1 (%) = (slope{  [CO nomi ] /  CO spani } -1000)/1000 *100 Rel. diff. of slope to nom. detector sens = 1000 ppb/V A 2 (%) = {  [(  (X j )) 2 (  CO sens /  X j ) 2 ]} 1/2 …from error propagation analysis.

19. March 26, 2004EAS 4/880319 O 3 Method: UV Absorption I = I 0 e -  c l  = 308 cm -1 (@STP: 0 o C, 760Torr) l = 38 cm 254 nm

20. March 26, 2004EAS 4/880320 O 3 Primary Standard Calibrator I = I 0 e -  c l  = 308 cm -1 (@STP: 0 o C, 760Torr) l = 38 cm To analyzer under cal capped Zero Air 254 nm internal vent [O 3 ] nomC

21. March 26, 2004EAS 4/880321 Goals 1.Basic Functionality Test 2.Determine Analyzer Performance (DL, sensitivity, precision and accuracy) 3.Determine the NO 2 Photolysis Rate from PSS assumptions and discuss 4.Discuss differences in O 3 measured between outdoor and indoor air

22. March 26, 2004EAS 4/880322 1. Functionality Tests Detectors Performance check System Leaks and Pump check Ozone scrubber efficiency check

23. March 26, 2004EAS 4/880323 2. Analyzer Performance Time (minutes) O3 span1 O3 0 O3 span2 O3 span3 O3 span4 O 3 Analyzer Signal (V) Zero-air  O3 nom ] 1 10 V  O3 nom ] 2  O3 nom ] 3  O3 nom ] 4 O3 sensi (ppb/V) =  [O3 nomi ] /  O3 spani O3 (ppb) = O3 raw * O3 sens DL 1 (ppb) = t * STD(O3 0 ) * O3 sens DL 2 (ppb) = i-cept{  [O3 nomi ] /  O3 spani } P (%) = t * STD(O3 sensi ) / AVG(O3 sensi ) *100 A 1 (%) = (slope{  [O3 nomi ] /  O3 spani } -20)/20 *100 Rel. diff. of slope to nom. detector sens = 20 ppb/V A 2 (%) = {  [(  (X j )) 2 (  O3 sens /  X j ) 2 ]} 1/2 …from error propagation analysis. Groups look for their individual “O3raw__.xls” data file on http://arec.gatech.edu/teaching

24. March 26, 2004EAS 4/880324 3.1 Determine j NO2 from PSS Assuming ambient O3 in photochemical steady-state (PSS) with NO and NO2, calculate jNO2 and discuss by comparing with literature values. NO 2 + hv (j NO2 )  NO + O(R1) O + O 2 + M  O 3 + M (fast, not rate-limiting) (R2) O 3 + NO (k 3 )  NO 2 + O 2 (R3) Assuming first-order homogeneous reaction (R3),and d[NO 2 ]/dt = k 3 [O 3 ][NO] - j NO2 [NO 2 ] = 0 yielding j NO2 = k 3 [NO] [O 3 ] / [NO 2 ] in s -1

25. March 26, 2004EAS 4/880325 3.2 Discuss j NO2 Diurnal Profile The photolysis rate coefficients (j NO2 ) provided here exemplarily, were calculated using a radiative transfer model (Zeng et al., 1996), which is based upon the Stamnes discrete ordinates model modified to solve the radiative transfer equation in pseudo-spherical coordinates. The discrete ordinates code was run with eight streams. The surface albedo was assumed to be 5%, and the total aerosol optical depth was parameterized in terms of visual range. The model assumes a constant visual range of 25 km for the lowest 2 km, a logarithmically decreasing aerosol optical depth above this, as well as a single scattering albedo of 0.99 and an asymmetry parameter of 0.61, which are both wavelength-independent. The j NO2 values were then scaled linearly by the flat-plate Eppley-UV (290-385 nm) measurements and by their ratio to the radiative transfer model clear-sky irradiance to account for the actual cloud and aerosol effects on j NO2. This scaling helps to correct for any errors made by the visual range assumptions. Consult references Volz et al., 1996, and Zeng et al., 1996. Retrieve above sample data as “jNO2sampleday.xls” from http://arec.gatech.edu/teaching

26. March 26, 2004EAS 4/880326 4. Discuss O 3 indoor vs outdoor differences Determine indoor and outdoor O 3 mixing ratios for a sample data set. Evaluate diurnal profiles of both individually and as difference. Discuss observed differences. Look for “O3inoutday.xls” At http://arec.gatech.edu/teaching