Krish Vijayaraghavan, Rochelle Balmori, Shu-Yun Chen, Prakash Karamchandani and Christian Seigneur AER, San Ramon, CA Justin T. Walters and John J. Jansen Southern Company, Birmingham, AL Eladio M. Knipping EPRI, Palo Alto, CA CMAS Conference, Oct 1-4, 2007 Chapel Hill, NC Modeling of Atmospheric Nitrogen Deposition to the Escambia Bay and Watershed

2 Overview Objective –Estimate impact of NO x and SO 2 controls at the Crist power plant on nitrogen deposition in Escambia Bay and its watershed in Florida/Southern Alabama Tools –Three versions of CMAQ v

3 Escambia Bay and Watershed Escambia Bay Watershed

4 Air Quality Models CMAQ –CMAQ v with SOA modifications by VISTAS –CBM-IV for gas-phase chemistry –AERO4 aerosol module Heterogeneous nitrate formation in the PM phase only Includes sea salt emissions but does not account for coarse nitrate formation due to sea-salt/HNO 3 interactions CMAQ-MADRID –Based on CMAQ and also utilizes CBM-IV –Aerosols: Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution –Heterogeneous nitrate formation in aqueous and PM phase –Comprehensive sea-salt/HNO 3 chemistry (fine and coarse size ranges) CMAQ-MADRID-APT –Builds upon CMAQ-MADRID –Advance Plume Treatment (APT) for 40 power plants, including Plant Crist

5 Plume Chemistry & Dispersion Relevance to Nitrogen Chemistry Early Plume Dispersion NO/NO 2 /O 3 chemistry 1 2 Mid-range Plume Dispersion Reduced VOC/NO x /O 3 chemistry Slow PM formation from OH and NO 3 /N 2 O 5 chemistry Long-range Plume Dispersion 3 Full VOC/NO x /O 3 chemistry PM and O 3 formation Negligible PM formation (NO 3 -, SO 4 = )

6 ALGA Modeling Domain 2002 reference year 12 km horizontal grid resolution 19 layers up to 15 km altitude 40 power plants, including Plant Crist, with APT Inputs from VISTAS/GEPD

7 Emission Reductions at Plant Crist Anticipated emission reductions due to installation of FGD and SCR/SNCR Emissions in base case (tpy) Change in emissions (tpy) Relative change in emissions (%) NO x % SO % NH

8 Nitrogen Species Nitrogen GroupingModeled Species or Sub-groups NO x NO + NO2 Organic NO z (O-NO z )PAN + NTR Gas Inorganic NO z (Gas I-NO z )NO3 + N2O5 + HNO3 + HONO + PNA Gas NH x NH3 PM NH x (NH4_1 + NH4_2) or (ANH4I + ANH4J)* PM I-NO z (NO3_1 + NO3_2) or (ANO3I + ANO3J)* I-NO z Gas I-NO z + PM I-NO z Gas NO y NO x + Gas I-NO z + O-NO z PM NO y PM I-NO z * Coarse mode not present for CMAQ

9 Spatial Distribution of Total Nitrogen Deposition Change in annual dry + wet deposition flux due to controls on Plant Crist CMAQ CMAQ-MADRID CMAQ-MADRID-APT APT: Less oxidation of NO x to HNO 3 => Less dry deposition near the plant Maximum reduction in deposition flux 0.68 kg/ha0.85 kg/ha0.42 kg/ha

10 Dry Deposition of Nitrogen over the Escambia Bay Watershed (tpy) Highest contributor: Gas I-NO z (mostly HNO 3 ) Nitrogen Species Grouping CMAQ base MADRID base APT base CMAQ control- base MADRID control- base APT control- base NO x O – NO z Gas I-NO z PM 2.5 NO PM NO PM 2.5 NH PM NH NH TOTAL

11 Ammonia Dis-benefit due to SO 2 Controls SO 2 controls => Less PM ammonium sulfate => More gas NH 3 Dry deposition velocity of gas NH 3 > PM NH 4 + Increase in NH 3 deposition >> Decrease in PM NH 4 + deposition Outcome Planned controls result in an increase in the NH x component of nitrogen deposition. Caveat Downward revision of the NH 3 dry deposition velocities will decrease the dis-benefit. Difference between models APT has less dis-benefit because of less sulfate formation in the plume.

12 Sea-salt Dis-benefit due to NO x /SO 2 Controls MADRID and APT account for coarse NaNO 3 formation from sea-salt/HNO 3 SO 2 controls => Less fine and coarse sodium sulfate Less coarse sodium sulfate => More coarse sodium nitrate Outcome Planned controls result in a small increase in coarse nitrate deposition. Caveats There is enough HNO 3 so coarse nitrate formation is not affected by NO x controls. Dis-benefit will be lower if more fine NaCl in sea-salt emissions CMAQ will also exhibit sea-salt dis-benefit if it accounts for coarse NaNO 3. Difference between models APT has less dis-benefit than gridded models because of less sulfate/nitrate formation.

13 Wet Deposition of Nitrogen over the Escambia Bay Watershed (tpy) Models can not distinguish between gas and PM wet deposition Largest contributors: I-NO z followed by NH x Nitrogen Species Grouping CMAQ base MADRID base APT base CMAQ control- base MADRID control-base APT control- base NO x O – NO z I – NO z NH x TOTAL

14 Conclusions Three versions of CMAQ were used to estimate the decrease in atmospheric nitrogen deposition in Escambia Bay/watershed due to NO x and SO 2 emissions controls at the nearby Crist power plant. Differences in results between the three models are due to differences in model formulation and configuration CMAQ-MADRID has more comprehensive heterogeneous nitrate and coarse sea-salt nitrate chemistry than CMAQ. CMAQ-MADRID-APT includes plume-in-grid treatment of large point sources (here, 40 large power plants including Crist).

15 Conclusions Gaseous inorganic NO z (mostly HNO 3 ) has the largest contribution (~60%) to nitrogen dry deposition in all three models. Inorganic NO z (gaseous + particulate) is the largest contributor (~52%) to wet deposition with a slightly lower contribution from NH x. NO x emission controls result in reductions in nitrogen deposition but SO 2 controls result in an increase in nitrogen deposition due to an “ammonia dis-benefit”. NH 3 dry deposition velocities in CMAQ need to be investigated further.

16 Conclusions Over Escambia Bay and its watershed, CMAQ, MADRID and APT predict: –total N deposition reductions of 91, 100, and 106 tons/yr, respectively. –maximum reductions in gridded deposition fluxes of 0.68, 0.85, and 0.42 kg/ha/yr, respectively. APT simulates less dry deposition of HNO 3 and PM sulfate near Plant Crist than CMAQ and MADRID due to its correct treatment of plume dispersion and chemistry. It is important to use a plume-in-grid treatment of emissions from large elevated point sources so that nitrogen deposition can be correctly simulated. Air quality modeling results were subsequently used in a watershed modeling study to estimate net nitrogen loading to Escambia Bay.