Future Year 2017 Source Apportionment Modeling Plan Denver Ozone SIP Modeling using 2011 Modeling Platform Draft#2, March 21, 2016

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Future Year 2017 Source Apportionment Modeling Plan Denver Ozone SIP Modeling using 2011 Modeling Platform Draft#2, March 21, 2016 INTRODUCTION The Denver Regional Air Quality Council (RAQC) and

1 Future Year 2017 Source Apportionment Modeling Plan Denver Ozone SIP Modeling using 2011 Modeling Platform Draft#2, March 21, 2016 INTRODUCTION The Denver Regional Air Quality Council (RAQC) and Colorado Department of Health and Environment (CDPHE) Air Pollution Control Division (APCD) are in the process of preparing an ozone State Implementation Plan (SIP) for the Denver Metropolitan Area (DMA)/North Front Range (NFR) ozone nonattainment area (NAA). The DMA/NFR NAA has been bumped up to Moderate ozone NAA so is required to achieve the March ppm ozone National Ambient Air Quality Standard (NAAQS) by The RAQC/APCD is using a 2011 photochemical grid model (PGM) modeling platform that was developed by the Western Air Quality Study (WAQS) and is available through the Intermountain West Data Warehouse (IWDW 1 ). The Comprehensive Air-quality Model with extensions (CAMx) PGM is being used with a 36 km CONUS, 12 km WESTUS and 4 km Colorado (CO) modeling domains as depicted in Figure 1. The contracting team of Ramboll Environ US Corporation (RE) and Alpine Geophysics, LLC (AG) is conducting the photochemical modeling for the 2017 Denver ozone attainment demonstration modeling. Figure 1. Denver 36 km CONUS, 12 km WESTUS and 4 km Colorado CAMx modeling domains

2 Purpose Ozone source apportionment modeling is a useful tool for identifying the source regions and source sectors that contribute the most to ozone concentrations so when controlled would likely result in the largest ozone reductions. For the Denver 2017 ozone attainment demonstration modeling, two types of ozone source apportionment are being performed using the Ozone Source Apportionment Technology (OSAT) tool in the CAMx photochemical grid model: Local Source Analysis that will examine the 2017 contributions of different source sectors within the DMA/NFR NAA and Colorado to elevated ozone concentrations in the DMA/NFR NAA; and Regional Transport Analysis that will examine the 2017 contributions of upwind states and international transport to elevated ozone concentrations in the DMA/NFR NAA. This document presents the scope of work for conducting these two types of 2017 ozone source apportionment modeling for the Denver 2017 ozone attainment demonstration modeling study. DENVER OZONE SOURCE APPORTIONMENT MODELING SCOPE OF WORK For the Denver ozone SIP, potentially two key questions are expected to be answered through source apportionment modeling: What are the contributions of different source sectors within the DMA/NFR NAA and Colorado on 2017 ozone concentrations in the DMA/NFR NAA (Local Sources Analysis); and What are the contribution of sources and regions outside of Colorado to ozone concentrations within the DMA/NFR NAA including upwind states, international sources and other contributions through the 36 km CONUS domain boundary conditions (BCs). New Version of Ozone and Particulate Matter Source Apportionment We propose to use a new version of the CAMx ozone source apportionment that has improved the accuracy two ways: (1) by keeping track of the source(s) of O 3 removed by reaction with NO to form NO 2 and subsequently returned as O 3 when the NO 2 is destroyed by photolysis; and (2) by keeping track of so-called NO X recycling when NO X is converted to a different form of oxidized nitrogen, such as NHO 3, and later converted back to NO X. In essence, the improved source apportionment is tracking VOC and NO X contributions to odd oxygen (i.e., oxygen atoms and ozone) and reactive nitrogen atoms and may result in more ozone being attributed to more 2

3 distant sources and less ozone being attributed to nearby sources. Details on the improved ozone source apportionment algorithms can be found in Yarwood and Koo ( ) with a summary given under Agenda item number 3 of the January 12, 2016 IWDW/WAQS Technical Committee meeting 3. Local Source Analysis Ozone Source Apportionment The Local Source Analysis ozone source apportionment modeling will be conducted using the 2017c 4 km CAMx modeling database using 4 km CO domain Boundary Conditions (BCs) based on the CAMx 2017c 36/12 km simulation. The 4 km CO modeling domain is shown in Figure 2. The Anthropogenic Precursor Culpability Assessment (APCA 4 ) version of the CAMx Ozone Source Apportionment Technology (OSAT) will be used using the new OSAT/APCA source apportionment algorithms (Yarwood and Koo ( ). Figure 2. Denver 4 km Colorado modeling domain with ozone monitors that were operating during some portion of Improved OSAT, APCA and PSAT Algorithms for CAMx. Gregory Yarwood and Bonyoung Koo, Ramboll Environ US Corporation, Novato, California. August, improved_osat_apca_psat_for_camx.pdf 3 WAQS-TechComm-Meeting-Agenda htm 4 APCA differs from OSAT in that ozone is only allocated to Natural emissions when it is formed due to Natural NOX emissions interacting with Natural VOC emissions. For example, when ozone is formed due to the interaction of biogenic VOC with anthropogenic NO X emissions under VOC-limited ozone conditions, OSAT will assign that ozone formed to the biogenic VOC source category, however APCA recognizes that biogenic VOC cannot be controlled so redirects the ozone formed to the anthropogenic NO X emissions category. 3

4 Local Source Analysis Source Apportionment Groups Although the CAMx source apportionment tool is quite flexible and can be configured many ways, the usual configuration is to define Source Regions of geographic areas of interest and Source Categories of different source sector types and obtain separate ozone contributions for each Source Group that is defined as the intersection between the Source Regions and Source Categories. For the Denver 2017 Local Source Analysis ozone source apportionment modeling, we propose to use the following Source Regions and Source Categories; Source Regions (see Figure 3) (4) 9 counties that are included in the DMA/NFR NAA (see Figure 4); 5 Western Colorado; Eastern Colorado; and Slivers of Surrounding States Source Categories (7) Natural Emissions (Biogenic, All Fires and Lightning NO X ) Oil and Gas Emissions; On-Road Mobile; Non-Road Mobile; EGU Point; Non-EGU Point; and Remainder Anthropogenic. With 4 Source Regions and 7 Source Categories and the need to always include initial concentrations (IC) and Boundary Conditions (BCs) as their own separate Source Groups that results in a total of 30 Source Groups for which separate ozone source contributions will be obtained. The Western and Eastern Colorado Source Regions will be defined as west and east of the DMA/NFR NAA as shown in Figure 3. The use of separate Western and Eastern Colorado Source Regions will allow a better identification of the contributing sources. For example, separating the contributions from oil and gas emissions from the Denver-Julesburg Basin (east) versus the Piceance Basin (west). 5 The northern portions of Larimer and Weld Counties are not part of the Nonattainment Area, but segregating those areas the Source Region would have minimal impact on the Source Apportionment. 4

5 The CAMx 2017c 4 km Local Analysis Source Apportionment will be conducted for May 1 through August 31using the 2011c WRF meteorology and 2017c base year emission inventory. Figure 3. Proposed local scale source apportionment source regions. 5

Figure 4. Nine county DMA/NFR ozone NAA and locations of ozone monitoring sites operating in 2011 (whole counties depicted, actual NAA excludes the northern portions of Larimer and Weld Counties).

6 Figure 4. Nine county DMA/NFR ozone NAA and locations of ozone monitoring sites operating in 2011 (whole counties depicted, actual NAA excludes the northern portions of Larimer and Weld Counties). Local Source Analysis Ozone Source Apportionment Post-Processing The CAMx 2017c 4 km Local Analysis ozone source apportionment modeling results will be post-processed to obtain the ozone contributions of each Source Group to the maximum daily 8-hour average (MDA8) ozone concentrations at each monitoring site for each day of the modeling period. Graphical displays (e.g., pie charts, ranked and stacked bar charts, etc.) can then be generated for key monitoring sites and key days. The CAMx 2017c Local Analysis ozone source apportionment would also be post-processed to determine each Source Groups contributions to the 2017 projected ozone Future Design Value (DVF). EPA s Modeled Attainment Test Software (MATS 6 ) would be used with a given 6 6

7 configuration (e.g., EPA default) to obtain the projected 2017 ozone DVFs under the 2017c base case conditions. MATS would then be run using the CAMx 2017c output with the ozone contributions from each of the 30 Source Groups separately removed. This will give the separate contributions of each of the 30 Source Groups to the projected 2017 DVF at each monitoring site. MATS can also be run using its Unmonitored Area Analysis (UAA) mode in order to obtain the spatial distribution of each of the 30 Source Groups contributions to the spatial distribution of the projected 2017 DVFs. OZONE TRANSPORT ANALYSIS The 2017 ozone source apportionment transport analysis will run the CAMx APCA ozone source apportionment tool using a fully linked two-way nested 36/12/4 km or 36/12 km 2017c modeling platform (Figure 1). The Ozone Transport Analysis will be used to obtain the contributions of anthropogenic emissions in each western state and the portions of Mexico and Canada within the 36 km CONUS domain (Figure 1) to elevated ozone concentrations in the DMA/NFR NAA (and elsewhere). The Ozone Transport Analysis will also obtain the ozone contributions due to natural emissions and fires within the CONUS domain as well as the Boundary Conditions (BCs) around the 36 km CONUS domain and above the model top that include contributions due to international sources, global natural sources and stratospheric ozone. The Ozone Transport Analysis will use the following Source Group definitions as follows: Source Regions (21) 17 Western States (see Figure 5); Eastern US; Mexico (Mex); Canada (Can); and Offshore Shipping/Development (OSS). Source Categories (2) Natural Emissions (Biogenic, All Fires and Lighting NOX); and Anthropogenic Emissions. 7

8 ICBC (6) IC; East BC; West BC; North BC; South BC; and Top BC. With 21 Source Region time 2 Source Categories plus 6 stratifications of ICBC that results in separate ozone source apportionment contributions for 48 Source Groups. Ozone Source Apportionment Transport Analysis Post-Processing The post-processing of the transport ozone source apportionment modeling results would include the 2017 ozone DVF analysis using MATS. For each western State, the State s anthropogenic emissions contributions to projected 2017 ozone DVFs at monitoring sites in the DMA/NFR will be obtained by running MATS twice: (1) once using the CAMx output for the 2011c and 2017c base case emissions scenarios (DVF Base ); and (2) a second time running with the CAMx output for the 2011c base case and the 2017c base case with the ozone contributions from the State removed (DVF State ). The State s contribution to ozone DVFs in the DMA/NFR is then obtained by taking the difference of the two MATS runs (DVF Base DVF State ). The contributions of the 6 categories of ICBCs to ozone DVFs can be obtained the same way. Similarly, the United States Background (USB) and North American Background (NAB) ozone DVFs can also be obtained by running MATS with the CAMx 2017 output with the contributions of all US anthropogenic emissions and all US, Mexico and Canada anthropogenic emissions removed, respectively. The absolute 2017c CAMx source apportionment modeling results can also be post-processed to obtain the contributions of states anthropogenic emissions as well as USB and NAB background to daily maximum average 8-hour (MDA8) ozone concentrations from which the highest and fourth highest and other metrics can be obtained. Note that the source apportionment versions of USB and NAB ozone is not true USB and NAB ozone that is obtained by performing a CAMx sensitivity simulation with all US anthropogenic and all US, Mexico and Canada anthropogenic emissions removed. The source apportionment versions of USB/NAB ozone will tend to be lower than the actual USBNAB CAMx sensitivity simulations since the presence of the anthropogenic emissions will destroy some of the ozone due to BCs that would not occur with the USB/NAB CAMx sensitivity simulation. Although the 8

9 new versions of OSAT that tracks odd oxygen should provide a closer estimate of USB/NAB ozone than the old OSAT/APCA. Use of 4 km Domain The CAMx 2017 Ozone Transport Analysis source apportionment run time will depend on three factors: (1) the modeling periods; (2) the number and size of grid cells; and (3) the number of Source Groups. As discussed above, 48 Source Groups will be used. It may be possible to not model the first part of May 2011 if none of those days are used in the MATS 2017 DVF projections. Given the schedule of the Denver 2017 ozone attainment demonstration modeling, the use of the 4 km Colorado grid may not be possible. In addition to adding a large number of additional grids to the simulation, the use of a 4 km grid will also require use of a smaller integration time step so that the CAMX run time using the b36/12/4 km domain would be 3-4 times that of just using the 36/12 km domain. We will perform a quick benchmark and report on the different run times for the CAMx 2017 Ozone Transport Analysis using the 36/12 km and 36/12/4 km domains and make a decisions on the domains with the RAQC/APCD. 9

10 Figure 5. Potential Source Regions with separate contributions due to emissions from western states. 10

Southern New Mexico Ozone Modeling Study Project Summary

Southern New Mexico Ozone Modeling Study Project Summary Project Summary Ramboll-Environ (RE) University of North Carolina (UNC-IE) June 29, 2016 http://www.wrapair2.org/snmos.aspx SNMOS Background and Objectives The southern Doña Ana County region has the highest