Evaluation of a New Screening Technique for Regional Haze Impacts Using Standard AERMOD Output

Transcription

1 Evaluation of a New Screening Technique for Regional Haze Impacts Using Standard AERMOD Output Bret Anderson, US Forest Service Jason Reed, SLR International Corporation James Zapert, Carter Lake Consulting

2 Background FLAG 2010 adopted the emissions/distance concept as a Tier I screening approach (Q/D). The ratio of 10 was derived by examining prior PSD projects using CALPUFF. The derivation is thus limited to source types which would have been observed in the PSD process in the 2000 s. Source types and emission characteristics vary more significantly in more recent years. In summer of 2015, EPA proposed removal of CALPUFF as preferred model for refined LRT assessments FLAG 2010 recommends using EPA approved version of CALPUFF for AQRV assessments for PSD, thus FLAG guidance affected by rulemaking. This would in turn impact Q/D.

3 Q/D Reexamined Q/D has been a useful first tier screening approach to reduce the overall burden of modeling for sources. However, in the context of FLAG revisions and potential shift in modeling platforms, several questions arise: Is the Q/D concept translatable between different source types? Can Q/D be applied in same manner to different modeling systems without modification? Does Q/D respect fundamentals of meteorology, which governs source-receptor relationships?

4 Examining the Role of Meteorology in Governing Source- Receptor Relationships

5 Q/D Reexamined Testing for all model platforms Elevated and low level pseudo-source placed in center of modeling domain Consistent emissions 40 TPY SO2/40 TPY NOx to 4000 TPY SO2/4000 TPY NOx Gridded results are extracted to examine peak visibility response as a function of downwind distance 5

6 Examining Q/D Closer by Model and Source Type

7 The Need for an Alternative Given the dependency of the Q/D concept on the underlying model platform used to derive the ratio, if the FLM agencies adopt a new modeling platform for AQRV analyses, we must go through the process of numerous model runs of the new modeling platform to determine what a new ratio should be, or develop a new approach which retains the relative conservatism of a screening approach, but respects the meteorology which governs source-receptor relationships, which the current Q/D concept does not do.

8 IWAQM Phase 1 Adaptations The approach is adapted from IWAQM Phase I recommendations. The Tier I approach from IWAQM Phase I recommends use of a plume model, and using factors of and 1.29 to account for ammonia neutralization for SO4 and NO3, respectively. The latest form of the IMPROVE reconstruction equation is used for estimating visibility impacts. The Tier II approach offers slight refinement over the Tier I approach by the following: Use of 1-hour concentrations, adjusting the SO4 and NO3 concentrations by the amount of available ammonia, similar to the POSTUTIL ALM=1 approach. 1-hour concentrations are summed for 24-hour concentrations and then visibility impacts are estimated in same manner as Tier I.

9 AERMOD as a Screening Tool In 2016, the USDA-FS developed a post-processor to AERMOD called AerVisPost as a potential replacement to the Q/D concept. AerVisPost uses the tiered approach to tiered approach to visibility screening described previously. AerVisPost outputs two AERMOD PST formatted files. provides sequential daily impacts at the maximum receptor. provides ranked impacts from high to low, along with date and location information.

10 Evaluation Overview 3 Projects - 2 PSD projects and 1 NEPA project Look at CALPUFF vs. Q/D vs. AerVisPost Processing steps: 1. Convert project emissions to Q value (FLAG 2010): SOx, NOx and PM 2. Generate receptors that are representative of the Class I area of concern At the actual distances and terrain elevations of that Class I area 3. Rerun AERMOD with one source that is representative of the project e.g., M-factor (EPA, 1992), highest emitting source, etc. produce POST file: 24-hour unit impacts at each receptor, for each day of the modeling period 4. Update AerVisPost input file 5. Run AerVisPost 6. Get results!

11 Evaluation - Inputs 1 number files to read unit80km.post AERMOD POST file NS.80km.UNIT.OUT unsorted AERPOSTVIS output S.80km.UNIT.OUT sorted AERPOSTVIS output moad Class I area name (used for look ups) smallrh.csv FLAG 2010 small RH values, by Class I area largerh.csv FLAG 2010 large RH values, by Class I area natcond.csv FLAG 2010 SVR values, by Class I area annual.csv FLAG 2010 visibility speciation, by Class I area seasaltrh.csv FLAG 2010 sea salt RH values, by Class I area 1.7 Project SO 2 emissions (g/s) 11.2 Project NOx emissions (g/s) 3.8 Project PM emissions (g/s)

12 Evaluation Execute Program Run on Windows 10 PC - quick Produces a non-sorted output maximum dbext for each day Produces a sorted output maximum dbext for each each day Select results were reproduced in spreadsheet using inputs and equations from FLAG 2010

13 Evaluation Case 1 Natural gas-fired combined cycle turbine triggered PSD, circa year onsite meteorological data Evolving project and FLM guidance First, CALPUFF modeling: H1H = 2.4% H8H = 1.6% Then, Q/D Q = 302 D = 81 km Q/D = 3.7 Now Case 1 Q Composition 10% 29% 61% SOx NOx PM10

14 Evaluation Case 1 Simplified Layout

15 Evaluation Case 1 Sorted Results (top 10) * X Y dbext fso4 fno3 focm AVE GRP DATE NET ID HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT HR CC1ALT

16 Evaluation Case 1 Sorted Results (top 100)

17 Evaluation Case 1 Analysis Spatial Distribution of dbext dbext by Month

18 Evaluation Case 1 Analysis dbext vs. Terrain (m)

19 Evaluation Case 2 Same specs as Case 1, but also includes a simple cycle turbine triggered PSD, circa 2016 Case 1 Q Composition Q/D 1 year onsite meteorological data Q = 582 D = 81 km Q/D = 7.2 No CALPUFF modeling, but Q2/Q1 ~ 2 with nearly identical speciation, so: H1H = 2.4 x 2 impacts > 5% change? H8H = 1.6 x 2 impacts > 3.5% change? 10% 29% SOx NOx PM10 61% Case 2 Q Composition 10% 23% SOx NOx PM10 67%

20 Evaluation Case 2 Simplified Layout

21 Evaluation Case 2 Sorted Results (top 10) * X Y dbext fso4 fno3 focm AVE GRP DATE NET ID HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT HR CC2ALT

22 Evaluation Case 2 Sorted Results (top 100)

23 Evaluation Case 2 Analysis Spatial Distribution of dbext dbext by Month

24 Evaluation Case 3 Gas plant expansion triggered NEPA, circa year onsite meteorological data CALPUFF modeling: H1H = 1.3% H8H = 0.4% Q/D not used, but calculated as: Q = 577 D = 68 km Q/D = 8.5 Use TO as primary source 40% Case 3 Q Composition 10% 51% SOx NOx PM

25 Evaluation Case 3 Layout

26 Evaluation Case 3 Sorted Results (top 10) * X Y dbext fso4 fno3 focm AVE GRP DATE NET ID HR ALL HR ALL HR ALL HR ALL HR ALL HR ALL HR ALL HR ALL HR ALL HR ALL

27 Evaluation Case 3 Sorted Results (top 100)

28 Evaluation Case 3 Analysis Spatial Distribution of dbext

29 Evaluation Case 3 Analysis dbext vs. Terrain (m) dbext vs. Distance from Source dbext by Month

30 Conclusions Parameter Case 1 Case 2 Case 3 Q value (tpy) D (km) Q/D CALPUFF Bext Rank: >5 1.3 CALPUFF Bext Rank: > AerVisPost Bext Rank AerVisPost Bext Rank < 5% at 94 th percentile 77 th percentile 100 th percentile CALPUFF ddv converted to Bext by multiplying by 10

31 Future Alternatives FS is examining several alternatives to enhance the tool set for screening for AQRV impacts. Tier II Screening: Adding PLUVUE II linear chemistry concepts into AerVisPost to limit SO2 SO4 transformation; and the Ammonia Limiting Method similar to that used in POSTUTIL to rebalance HNO3/PNO3 Requires calculation of solar angle, incoming solar radiation to determine which sulfur chemistry pathway to use (daytime v. nighttime chemistry). Modify AERMOD or other Gaussian model to incorporate features of the defunct Reactive Plume Model (RPM). RPM was an EPA Gaussian model in the 1990 s that had the CB-IV chemical pathways for ozone. Modularity of system allows for updating to CB-V including aerosol chemistry pathways.

32 Conclusions Simple to use: FLAG 2010 inputs and methodology Existing model setup and project emissions Maintains: Pollutant-specific contribution to visibility impairment Importance of meteorology for source-receptor relationships and seasonality Terrain effects of Class I area Case 2 showed strong response to approximate doubling of emissions dbext increased by factor of 3 Needs additional testing of sources types, receptor assumptions Determination of threshold

33 Questions?