ASSESSING CONTROL STRATEGIES FOR GROUND-LEVEL OZONE

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1 ASSESSING CONTROL STRATEGIES FOR GROUND-LEVEL OZONE NEELESH V. SULE, Ph.D., P.E. North Central Texas Council of Governments November 5, 2013

2 Overview Introduction Research Objective Decision Making Framework (DMF) Purpose of DMF DFW Case study Results Conclusions Recommendations 2

3 Introduction Developing cost effective control strategies for ozone has been a challenge to air quality modelers. The control strategies are applied across-the board to the region. This research studied targeted reductions, in which emission sources of various types were reduced at various times and locations. 3

4 Targeted Control Measures Conventional Strategy Reducing NOx emissions by 80% from Source Type A throughout the day from all nonattainment regions (counties) Targeted Control Reducing NOx emissions from Source Type A in Region 1 during 6 am 12 noon by 80% & Reducing NOx emissions from Source Type A in Region 1 during 12 noon 7 pm by 50% 4

5 Decision Making Framework (DMF) Initialization Experimental design & Data Mining Metamodeling Optimization 5

6 Decision Making Framework Initialization Phase : Identify critical monitoring stations, potential control strategies, emission source types, control time periods, control regions, monitoring time periods and monitoring regions. 6

7 Decision Making Framework Experimental Design and Data Mining Phase : Organize first set of CAMx runs, run CAMx, and conduct data mining to identify the significant predictor variables for 8-hour maximum ozone. Organize more CAMx runs, as needed. 7

8 Decision Making Framework Metamodeling Phase: Build a metamodel to predict the maximum 8- hour ozone average in each monitoring time period for each monitoring region. 8

9 Decision Making Framework Optimization Phase: Set up an Integer Program (IP) to optimize the selection of cost effective targeted control strategies. 9

10 Purpose of DMF Identifying the effectiveness of targeted control strategies that are focused in certain regions and time periods. Providing an efficient, yet comprehensive, approach for identifying the most cost-effective combination of targeted control strategies that achieves attainment. 10

11 DALLAS-FORT WORTH (DFW) 8-HOUR OZONE CASE STUDY FOR

12 Background 2009 NOx emissions 394 tpd 2009 VOC emissions 340 tpd The control strategies by TCEQ and NCTCOG offered about tpd of NOx reductions against the required tpd reduction. Source: DFW 8-hour SIP, May

13 Models Used Comprehensive Air Quality Model With Extensions (CAMx). Emissions Preprocessing Systems (EPS) version 3. 13

14 Data Used DFW future year 2009 case Premerged Area & Line sources EPS files for 2009 Pre EPS (AFS) Point source files for

15 Modeling Domain The 4 km CAMx modeling domain for DFW Source: DFW 8-hour SIP, May

16 DMF: Initialization Phase S. No Critical Monitoring Station 1 Frisco C31 2 Hinton C60 3 Dallas N C63 4 Redbird C402 5 Denton C56 6 Midlothian C94 7 Arlington C57 8 Ft W NW C13 9 Ft W Keller C17 10 Johnson 11 Parker 12 Kaufman 13 Rockwall 16

17 DMF: Initialization Phase A list of control strategies along with emission reductions and cost was obtained from NCTCOG Control Strategies Emissions Affected Amount of Emission Reduction (tons/day) and Cost ($/ton of emission reduction) NO x Cost VOC Cost 1 Idle Reduction Infrastructure 9 counties Control Strategy No. 2 Intelligent Transportation Systems 9 counties

18 DMF: Initialization Phase Time periods by type of source Source category # of types Control time periods # of emission variables Point source (Mon Sun) 7 12 mid 6 am 6 am 12 noon 12 noon 7 pm 7 pm 12 mid 7 4 = 28 Area (Mon Sun) 1 6 am 9 am 9 am 3 pm 3 pm 7 pm 1 3 = 3 Line (Mon Thur) 1 6 am 9 am 9 am 3 pm 3 pm 7 pm 1 3 = 3 Line (Friday) 1 6 am 9 am 9 am 5 pm 5 pm 12 mid 1 3 = 3 Line (Sat Sun) 1 6 am 3 pm 3 pm 12 mid 1 2 = 2 18

19 DMF: Initialization Phase The total number of emission variables for a week day (Monday - Thursday) (28 point + 3 area + 3 line) (2 pollutants) (9 control regions) = 612 variables The total number of emission variables for a weekend (Fri.) (28 point + 3 area + 3 line) (2 pollutants) (9 control regions) = 612 variables The total number of emission variables for a weekend (Saturday-Sunday)) (28 point + 3 area + 2 line) (2 pollutants) (9 control regions) = 594 variables 19

20 DMF: Initialization Phase S. No Monitoring Region 1 Collin 2 Dallas 3 Denton 4 Ellis 5 Tarrant 6 Kaufman & Rockwall 7 Johnson & Parker Monitoring Time Periods 12 mid 6 am 6 am 12 noon 12 noon 3 pm 3 pm 7 pm 7 pm 12 pm 20

21 DMF: Experimental Design Phase A C-code was developed to implement each of these 30 scenarios on the 2009 future case emission inventory to be preprocessed through EPS. The output obtained from the EPS was run in CAMx to obtain the 8-hour maximums for each monitoring region in each of 5 monitoring time periods. 21

22 DMF: Experimental Design Phase Sample output of CAMx runs for August 17 in Dallas monitoring region RUN BL Dallas 12 mnight - 6a noon 7pm - 6a noon - 3p 3p - 7p 12mn

23 DMF: Data Mining Phase 3 data mining techniques were used to evaluate 612 emission sources and timelagged 8-hour maximum ozone concentrations. Classification and Regression Tree (CART) Multivariate Adaptive Regression Spline (MARS) False Discovery Rate (FDR) 23

24 DMF: Data Mining Phase Union of variables selected by 3 data mining methods was taken. Significant variables consisted of a mix of point, area, non-road, line and time-lagged 8-hour daily maximum ozone concentrations variables. Data mining reduced the number of variables from 612 to a maximum of 126 for August

25 DMF: Metamodeling Phase The CAMx output data was used to construct metamodels. The metamodels included statistically significant variables from data mining. The mathematical model acts as a surrogate to CAMx simulations in the Optimization Phase. 25

26 DMF: Metamodeling Phase Multiple linear regression was used to construct preliminary regression model. A stepwise model selection method at significance level (α) of 0.10 for each monitoring region and time period was used to select best model. 26

27 DMF: Metamodeling Phase Monitoring region: Dallas, Aug midnight 6 am: R 2 = (P4Ka12-6a N) am 12 noon: R 2 = (AEl6-9a V) (Da12-6a) (KR12-6a) noon 3 pm: R 2 = (Co6-12n) (Da6-12n) (Ta6-12n) (P4Ta12-6a N) pm 7 pm: R 2 = (Da12n-3pm) (De6-12n) (De12n-3pm) (Co12n-3pm) (Co6-12n) pm 12 midnight: R 2 = (AEl3-7pV) (KR3-7p)

28 DMF: Optimization Phase The main aim of the optimization was to identify the most cost-effective combination of targeted control strategies that would bring the region into attainment for the 8-hour ozone standards. Supplemental control measures were introduced into the optimization if the existing control measures failed to satisfy the constraints. Three types of supplemental controls were considered: 90 % reduction of emission from the source 100% reduction of emission from the source Reducing previous day s ozone 28

29 DMF: Optimization Phase A higher cost was allocated to the 90 % emission reduction supplemental controls, while highest cost was allocated to the 100 % emission reduction and for reducing previous day s ozone. If the above supplemental controls or its combinations did not satisfy the constraints then the constraint on the ozone metamodel was relaxed. 29

30 DMF: Optimization Phase Optimization result for August 16 30

31 DMF: Optimization Phase Important Observations 6 am - 12 noon and 12 noon - 3 pm were the two main critical time periods where the ozone exceeded the constraint. Additional emission reductions over the existing controls were required. Despite these additional emission reductions, the ozone was not totally controlled (previous day s ozone had to be controlled, and constraint had to be relaxed). 31

32 DMF: Optimization Phase Probable Reasons The DMF developed in this research used the list of control measures adopted by TCEQ for 8-hour DFW. The point source categorization was based on the list of controls provided by NCTCOG. 32

33 Conclusions The research demonstrated the applicability of the DMF in identifying key emission sources and targeted controls. Key sources and locations to be controlled include: Point Area Line NOx NOx VOC NOx VOC Dallas Denton Ellis Kaufman Denton Ellis Johnson Ellis Kaufman Tarrant 33

34 Conclusions Key emission time periods to be controlled include: Point Area Line 12 midnight 6 am 6 am 9 am 6 am 9 am 6 am 12 noon 9 am 3 pm Further reductions at the sources beyond the existing list of NCTCOG control strategies were required. 34

35 Recommendations NCTCOG could use this DMF to access the ozone strategies in DFW for the new SIP by: Individual or group of source categories Specific location (county) Specific time period 35

36 Recommendations DMF will also use a: New Optimization technique Mixed integer linear programming New baseline ozone episode June 2006 New CAMx model version (v5.20) New emissions inventory 36

37 Thank you! QUESTIONS 37

38 For additional information: Neelesh V. Sule, Ph.D., P.E. Phone: (972) Cell: (817)

39 Monitoring Regions Source: DFW 8-hour SIP, May

40 Point Sources 1. Brick kilns 2. EGU 3. Industrial, Commercial and Institutional Boilers Medium size (40-80 MMBtu/hr) Large size (> 100 MMBtu/hr) 4. Lime kilns 5. Process heaters 6. Midlothian Cement kilns 40

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