Using the EMF for Development of Temporal Profiles for Non-CAMD EGUs

Transcription

1 Maryland Department of the Environment Using the EMF for Development of Temporal Profiles for Non-CAMD EGUs Hannah Ashenafi MARAMA EMF Peer Workgroup Showcase September 9, 2015

2 Background There is interest in whether or not our modeling is getting peak day emissions right. Some of these emissions come from small electric generating units, which typically operate for limited periods of time. Large units operating profiles are developed from CEMS data, so we know their profiles are reasonable but what about the smaller units those without CEMS? Annual emissions for non-camd EGUs are known, and a temporal profile is applied during SMOKE processing to allocate annual emissions to the hour. Analysis in EMF showed us that default profiles applied by SMOKE smear emissions across 365 days. 2

3 MDE s Temporalization Process Analyze 2011 operating patterns of large peaking EGUs > 25 MW (using CAMD data) to create 12 peaking profiles 4 regions: MANE-VU, LADCO, SESARM, CenSARA 3 fuel bins: coal, oil, gas Apply peaking profiles to non-camd EGUs in the MARAMA Alpha 2011 inventory Prepare SMOKE input files for a screening run to assess the impacts on peak day ozone 3

4 Use of EMF for Analysis Today s webinar: How can we locate these specific units in the inventory files? MARAMA Alpha 2011 point inventory files: smallegu and ptnonipm Future webinar discussion: How are their emissions allocated by temporal profiles within SMOKE? How will daily NOx emissions be affected if we apply a new peaking temporal profile to these units? 4

5 Units we know of in MD ORIS ID Facility Unit IDs Total Size (MW) Fuel Plant Type Total 2011 Emissions MARAMA Alpha Inventory 2011 MARAMA Alpha Inventory File 6565 Berlin 1A - 5A 8.55 Oil RICE 4.36 Tons ptnonipm 1552 Crane GT1 14 Oil Combustion Turbine 5.41 Tons ptnonipm 1571 Chalk Point GT1 18 Oil Combustion Turbine 3.08 Tons small EGU 1563 Crisfield CRIS, CRS Oil RICE 9.20 Tons ptnonipm 1572 Dickerson GT1 13 Oil Combustion Turbine Tons ptnonipm 1580 Easton 8 9, 11, Oil Combustion Turbine Tons ptnonipm 1580 Easton 7, 10, Oil RICE 4257 Easton , Oil RICE Tons ptnonipm 4257 Easton Oil Combustion Turbine 1573 Morgantown GT Oil Combustion Turbine Tons small EGU 1555 Notch Cliff GT Gas Combustion Turbine Tons ptnonipm 1557 Philadelphia GT Oil Combustion Turbine 24.80Tons ptnonipm 1559 Riverside CT Oil Combustion Turbine 5.20 Tons small EGU 1564 Vienna Oil Combustion Turbine 2.22 Tons ptnonipm 1554 Wagner GT Oil Combustion Turbine Tons ptnonipm 5

6 Point Inventory Files Used MARAMA_Alpha_output_for_NEI_smallEGUpt_from_ NEI_EGU_.csv NEI2011v2 point sources included in the ERTAC UAF but not included in the ERTAC EGU projection tool; and any IPM units not included in the ERTAC forecasting tool MARAMA_Alpha_ptnonipm_2011NEIv2_POINT_ _revised_ _08oct2014_nf_v1_csv_23oct 2014_v NEIv2 point sources that are not included in EPA s EGU or oil/gas sectors 6 Additional analysis involved other files: EPA_SCC_list.csv (SCC Description with Levels) ERTAC Modeling files OTC, LADCO, SESARM, CENSARA

7 Identifying Units in the 2011 Inventory Initial search of the NEEDS 5.13 database identified approximately 3,500 coal, oil, and gas-fired EGUs <25 MW within the modeling domain. No crosswalk between EIS and NEEDS/EIA identifiers to match the units in the NEEDS database to their emissions in the 2011 MARAMA Alpha modeling inventory Chose to query inventory files based on a combination of NAICS/SCC codes to identify EGUs <25 MW NAICS code for electric generating facilities: 22111, List of SCCs for coal, oil, and gas-fired engines Challenge: many of these units have very small emissions so their SCCs are not as thoroughly QA d. Looked at SCCs attributed to known MD small EGUs to help create a list of SCCs that will capture as many units as possible that feed power to the grid, and avoid capture of auxiliary boilers, HRSG, and other industrial processes. 7

8 Poll: What inventory files were analyzed to identify units that might produce power primarily on HEDD days? Choose all that apply. a) afdust b) ERTAC_EGU c) ptnonipm d) smallegu 8

9 Use of SCC Levels From SMOKE v3.5.1 User s Manual, Section What SCC levels are attributed to MD s list of non-camd EGUs? 8

10 Check SCCs for MD Non-CAMD EGUs QA step to join ptnonipm or smallegu file with SCC levels and descriptions select e.*, substring(e.scc,1,1) as one, a.scc_level_one, substring(e.scc,2,2) as two, a.scc_level_two, substring(e.scc,4,3) as three, a.scc_level_three, substring(e.scc,7,2) as four, a.scc_level_four, a.short_name from $TABLE[1] e LEFT JOIN $DATASET_TABLE["EPA_SCC_list.csv",1] a on e.scc=a.scc where substring(e.region_cd,1,2)='24' and e.poll='nox' and e.naics in ('22111','221112') We encourage everyone to use the query above to look at SCCs for units in your own state! 9

11 10 Final List of Selected SCCs smallegu file only Coal boilers: 85 SCCs Oil boilers: 30 SCCs Gas boilers: 19 SCCs Both smallegu file and ptnonipm Oil ICEs: 25 SCCs Gas ICEs: 50 SCCs *Included SCCs for both boilers and ICEs in the small EGU file to capture as many units as possible. Included only ICEs from the ptnonipm file to prevent capture of auxiliary boilers, industrial processes, etc. *Also included units with SCCs for ICI boilers, as NAICS code was used to determine if that unit is at an EGU facility.

12 Poll: Which level of the SCC code is the most specific? a) First level b) Fourth level 12

13 Creating a List of Units for the Domain Separate units by region and fuel type: 12 categories 4 regions: MANEVU, LADCO, SESARM, CENSARA 3 fuel bins: coal, oil, gas Query each of the two inventory files MARAMA_Alpha_output_for_NEI_smallEGUpt_from_NEI_EGU_. csv MARAMA_Alpha_ptnonipm_2011NEIv2_POINT_ _revis ed_ _08oct2014_nf_v1_csv_23oct2014_v0 based on NAICS/SCCs from previous slide Smaller subset of SCCs from ptnonipm file focusing on NOx emissions 11

14 Sample Query for MANEVU Oil Units smallegu file select e.* from $TABLE[1] e where e.poll= NOX and substring(e.region_cd,1,2) in ('23', '33', '50', '25', '44', '09', '36', '34', '10', '42', '24', '11', '51') and e.naics in ( 22111, ) and e.scc in (' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ') ptnonipm file Repeat with only SCCs for Oil ICEs Repeat for all regions and fuel bins 12

15 Assessing Double Counting of Units Analysis of top ten units for each region/fuel bin showed some overlap with ERTAC units (EGUs >25MW). Additional QA steps were added to identify double counted units in ERTAC modeling file. 13 Ex. Match smallegu file to OTC ERTAC flat file: select e.*, e.ann_value as smallegu_nox, a.ann_value as ERTAC_NOX from $TABLE[1] e join $DATASET_TABLE["Name OTC_2011_ERTACEGUv23_150227_MENHVTMARICTNYNJDEPAMDDCVA.csv",1] a on e.agy_facility_id = a.agy_facility_id and e.region_cd = a.region_cd and e.agy_unit_id = a.agy_unit_id and e.agy_rel_point_id = a.agy_rel_point_id and e.agy_process_id = a.agy_process_id and e.scc = a.scc and e.poll = a.poll where e.poll='nox Also did queries in Access to match to ERTAC UAF (not in EMF)

16 Additional Analysis Done Outside of EMF Compiled full list of units from both inventory files into one Excel workbook. Examined top ten list for each region/fuel bin. Removed ERTAC EGUs and units that were listed as non-egus in ERTAC UAF. Determined contribution by state and number of units by state. Feel free to do QA steps to determine the number of units and tons of NOX for your state! Try it out! 14

17 Temporal Analysis Used default temporal profiles within EMF temporalization tool to allocate emissions as they are currently allocated in our modeling inventory. Created new peaking temporal files to be input into EMF and re-ran temporalization tool using new files. Subtracted peaking profile allocation from default temporal allocation to determine increase in peak day NOx emissions. Added to NOx emissions from ERTAC EGUs to determine % increase on peak days. Determined contribution by state on peak days. Lots more. Let us know if you are interested in another webinar on this topic 15

18 Next Steps for the Project Finish collecting comments from states on whether or not units selected are coal, oil, or gas EGUs < 25 MW that feed power to the grid. Compile a final database of units for temporalization, and create a new sector modeling file in EMF to facilitate analysis of these units separately. Temporalize new file to daily emissions, and use a QA step to convert daily temporal allocation results into a SMOKE-ready hourly input file. Incorporate changes into the MARAMA Beta Inventory. 16

19 For more information about the project, please contact Hannah Ashenafi Emily Bull

20 Maryland Department of the Environment ARMA Planning Program 1800 Washington Boulevard Baltimore, MD TTY Users: