Alaska WEP/AOI and PSC Analysis - December 17, 2020

An Area of Influence (AOI) and Weighted Emissions Potential (WEP) analysis was performed for the IMPROVE sites in Alaska to identify the anthropogenic sources of emissions within and nearby the state that had the potential to contribute the most to visibility impairment on the Most Impaired Days (MID) from 2014 to 2018 at Class I Areas (CIA) in the state. A Potential Source Contributions (PSC) analysis was also performed to characterize the relative potential contributions of natural (e.g., volcano) and anthropogenic (e.g., on-road mobile sources) emission sources groups to the ammonium sulfate (Amm_SO4) extinction on the MID. The input data, methods, and resulting data products for the WEP/AOI and PSC analyses are described separately in the following sections.  Although the procedures used to conduct the Alaska WEP/AOI analysis of anthropogenic emissions and PSC analysis of natural and anthropogenic SOx emissions are similar, they are very different analysis and need to be viewed separately.

The CIA and representative IMPROVE monitors included in the analyses are provided in Table 1. No IMPROVE monitoring data is available for the Bering Sea Wilderness CIA, and so it was not included in the analysis. The Tuxedni IMPROVE site (TUXE1) stopped operating in 2014 so the MID from 2012 to 2014 were used. The Kenai Peninsula Borough (KPBO1) site was added across the Cook Inlet from TUXE1 in 2016 to replace TUXE1, but KPBO1 could not be included in the WEP/AOI nor PSC analysis as no MID metric data is available for the site. Instead, an AOI and WEP analysis was performed for the 20% highest measured visibility extinction for ammonium sulfate (Amm_SO4), ammonium nitrate (Amm_NO3), and coarse mass (CM) at TUXE1 and KPBO1 for the 3 most recent years of available data (2012 to 2014 and 2016 to 2018, respectively).

Class I Area IMPROVE Site Analysis Period
Denali National Park and Preserve Denali Headquarters Site (DENA1) 2014 - 2018
Trapper Creek Site (TRCR1) 2014 - 2018
Simeonof Wilderness Area Simeonof (SIME1) 2014 - 2018
Tuxedni National Wildlife Refuge Tuxedni (TUXE1) 2012 - 2014
Kenai Peninsula Borough (KPBO1) 2016 - 2018*
Table 1. Alaska Class I Areas and IMPROVE monitoring sites included in the Area of Influence and Weighted Emissions Potential analysis; Sources: https://dec.alaska.gov/air/air-monitoring/improve-network, Memo and Technical Addendum on Ambient Data Usage and Completeness for the Regional Haze Program (June 3, 2020), Technical Guidance on Tracking Visibility Progress for the Second Implementation Period of the Regional Haze Program (December 20, 2018);
*The KPBO1 IMPROVE site started operating in 2016 and was not included in the analysis of Most Impaired Days as no impairment metric data is available for the site.

Weighted Emissions Potential (WEP)/Area of Influence (AOI) Analysis

Input Data and Analysis Domain

IMPROVE Data for Most Impaired Days

The MID at DENA1, TRCR1, SIME1, and TUXE1 were identified as those assigned to impairment group 90 in the IMPROVE Impairment Daily Budgets dataset. The impairment group metric includes days in which missing data was patched using statistical approaches. The 20% highest Amm_SO4, Amm_NO3, and CM days at TUXE1 and KPBO1 were identified using the IMPROVE Daily Budgets dataset. Days with patched or substituted data for the species being examined were not included when determining the 20% highest Amm_SO4, Amm_NO3 and CM extinction days.

HYSPLIT Back Trajectory Modeling

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model (Stein et al., 2015; Rolph et al., 2017) was used to calculate 72-hour back trajectories arriving on each of the MID at four times per day (6:00, 12:00, 18:00, 24:00 local standard time) and at four heights above the ground (100 meter (m), 200 m, 500 m and 1,000 m). The archived NAM hybrid sigma-pressure gridded (NAMS) meteorological data for Alaska was downloaded for 2012 to 2018 from the NOAA Air Resources Laboratory FTP server for use in HYSPLIT model. The NAMS data is output hourly and covers Alaska at 12 km resolution. The HYPSLIT model was configured to provide trajectory endpoints every 10 minutes of the simulation period.

Analysis Domain

The analysis performed using the 9-kilometer (km) domain of EPA’s Regional Haze Modeling platform for Alaska aggregated to 27-km resolution. Trajectory endpoints located outside the EPA 9-km domain were dropped from the analysis. The analysis domain and IMPROVE sites are shown in Figure 1.

Emissions

The WEP analysis was performed using both gridded emissions from the EPA’s 2016 Alaska modeling platform and 2014 and 2017 facility-level National Emissions Inventory data provided by ADEC in a May 20, 2020 e-mail from Molly Birnbaum. The EPA’s gridded emissions for 2016 were aggregated into the following source sectors for the WEP analysis:

  • TOTAL_ANTHRO – All anthropogenic emissions
  • PT_EGU – Electric generating unit emissions
  • PT_NON-EGU – Point source emissions from industrial activities
  • OG_AREA_POINT – Oil and Gas area and point sources (Upstream and Midstream)
  • NON-POINT – Low-level area source emissions including non-point, agricultural, residential wood combustion, and fugitive dust emissions
  • ON-ROAD – On-road mobile source emissions
  • NON-ROAD – Off highway mobile source emissions including non-road, airport, commercial marine (C1, C2, and C3), and rail sources

For the MID analysis, EPA 2016 gridded emissions of nitrogen oxides (NOx), sulfur oxides (SOx), primary organic aerosol (POA), and primary elemental carbon (PEC) were used for the analysis of Amm_NO3, Amm_SO4, OC, and EC, respectively. The analysis of the facility-level WEP on the MID used point source emissions of NOx and SO2.

The gridded WEP and AOI analysis of the 20% highest extinction days of Amm_NO3, Amm_SO4, and CM at TUXE1 and KPBO1 was conducted in the same manner as for the MID described above only using EPA 2016 emissions of NOx, SOx, and coarse primary mass (CPRM), respectively.  The facility level emissions analysis was based on 2014 and 2017 point source emissions of NOx, SO2, and PM10 for the TUXE1 and KPBO1 sites, respectively.

Figure 1. Alaska IMPROVE monitors and the EPA 9-kilometer modeling domain used for the AOI and WEP analysis

WEP/AOI Products

The WEP/AOI analysis products are provided for the 100 m and 1000 m trajectory heights and for a combined analysis in which data from all four trajectory heights are aggregated (All). The products include:

  • Plots of residence time (RT), extinction weighted residence time (EWRT), and WEP for each CIA
  • Plots of the gridded 2016 EPA emissions used in the WEP analysis for each of the source sectors described above (EMISSIONS)
  • Excel spreadsheets of facility-level 2014 and 2017 precursor emissions and the corresponding WEP at each CIA (RANK_POINT)

The RT, EWRT, WEP, and EMISSIONS plots are provided at the following link using the directory structure shown below with TUXE1 as an example. The analysis plots for the 20% highest Amm_SO4 (20pctHigh_SO4) and CM (20pctHigh_CM) at TUXE1 and KPBO1 are provided using the same directory structure as 20% highest nitrate extinction days (20pctHigh_NO3) shown below. Descriptions of each analysis product are provided in the following sections.

AOI, WEP, and Gridded Emissions Plots

├── MID
│   ├── TUXE1
│       ├── RT
│       ├── EWRT
│           ├── EC
│           ├── NO3
│           ├── OC
│           ├── SO4
│       ├── WEP
│           ├── EC
│           ├── NO3
│           ├── OC
│           ├── SO4
├── 20pctHigh_NO3
│   ├── TUXE1
│       ├── RT
│       ├── EWRT
│           ├── NO3
│       ├── WEP
│           ├── NO3
├── EMISSIONS
    ├── NOX
    ├── SOX
    ├── POA
    ├── PEC
    ├── CPRM

Shapefiles of the RT, EWRT, and WEP results by source sector are provided for the MID and 20 percent highest Amm_NO3, Amm_SO4 and CM days at the link below (WEP_SHP). In each CIA subdirectory there is a zip file for each source sector containing the ESRI shapefile (.shp) and related files (.cpg, .dbf, .prj, .shx). The RT, EWRT, and WEP results data are available within the attribute tables of the shapefiles provided which can be accessed in ArcMap or ArcCatalog. The attribute tables can be exported to csv, then opened in Excel. Files are provided for the 100m and 1000m trajectory heights and for a combined analysis in which data from all four trajectory heights are aggregated (All). The directory structure for the WEP_SHP is shown below using the TUXE1 results aggregated across all trajectory heights as an example. The shapefiles for 20pctHigh_SO4 and 20pctHigh_CM at TUXE1 and KPBO1 are provided using the same directory structure as the 20pctHigh_NO3.

WEP/AOI Shapefiles

├── MID
│   ├── TUXE1
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_NON-POINT__All.zip
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_NON-ROAD__All.zip
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_OG_AREA_POINT__All.zip
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_ON-ROAD__All.zip
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_PT_EGU__All.zip
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_PT_NON-EGU__All.zip
│       ├── TUXE1_AOI_WEP_MID_Emis_EPA2016_TOTAL_ANTHRO__All.zip
├── 20pctHigh_NO3
│   ├── TUXE1
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_NON-POINT__All.zip
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_NON-ROAD__All.zip
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_OG_AREA_POINT__All.zip
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_ON-ROAD__All.zip
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_PT_EGU__All.zip
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_PT_NON-EGU__All.zip
│       ├── TUXE1_AOI_WEP_20pctHigh_NO3_Emis_EPA2016_TOTAL_ANTHRO__All.zip

The facility-level RANK_POINT results for the MID and 20 percent highest Amm_NO3, Amm_SO4 and CM days are provided at the link below. The results are provided in Excel spreadsheets with the 2014 and 2017 results provided in separate tabs. The directory structure is shown below using TUXE1 as an example.

RANK_POINT Spreadsheets

├── RANK_POINT
│   ├── MID
│       ├── TUXE1.RANK_POINT.MID.1000m.xlsx
│       ├── TUXE1.RANK_POINT.MID.100m.xlsx
│       ├── TUXE1.RANK_POINT.MID.All.xlsx
│   ├── 20pctHigh_NO3
│       ├── TUXE1.RANK_POINT.20pctHigh_NO3.1000m.xlsx
│       ├── TUXE1.RANK_POINT.20pctHigh_NO3.100m.xlsx
│       ├── TUXE1.RANK_POINT.20pctHigh_NO3.All.xlsx
│   ├── 20pctHigh_SO4
│       ├── TUXE1.RANK_POINT.20pctHigh_SO4.1000m.xlsx
│       ├── TUXE1.RANK_POINT.20pctHigh_SO4.100m.xlsx
│       ├── TUXE1.RANK_POINT.20pctHigh_SO4.All.xls
│   ├── 20pctHigh_CM
│       ├── TUXE1.RANK_POINT.20pctHigh_CM.1000m.xlsx
│       ├── TUXE1.RANK_POINT.20pctHigh_CM.100m.xlsx
│       ├── TUXE1.RANK_POINT.20pctHigh_CM.All.xlsx

Residence Time (RT):  The RT folder contains plots showing the AOI that back trajectories of air parcels traveling from a given location arrived at the IMPROVE monitor on the 2014-2018 MID.  HYSPLIT 72-hour back trajectories are calculated to arrive on each of the MID four times a day (6:00, 12:00, 18:00, 24:00 local standard time) and at four heights above the ground (100 m, 200 m, 500 m and 1,000 m). Plots are provided for the 100m and 1000m heights and for a combined analysis in which data from all trajectory heights are aggregated (All). RT plots for the MID at DENA1 are provided as an example in Figure 2.

Figure 2. Residence Time (RT) analysis for DENA1 IMPROVE monitoring site and back trajectories that arrive at the site on the Most Impaired Days for each year 2014-2018 at 100 m (left), 1000 m (middle) and All (right) heights above ground

Extinction Weighted Residence Time (EWRT):  EWRT are calculated by weighting the HYSPLIT trajectories by the monitored extinction at the IMPROVE site on each MID. Plots of EWRT for Amm_SO4, Amm_NO3, OA and EC are provided for the MID analysis, while plots of EWRT for Amm_SO4, Amm_NO3, and CM are provided for the 20% highest extinction day analysis of TUXE1 and KPBO1.  Figure 3 shows the EWRT plots for sulfate and nitrate at DENA1 on the MID using the aggregated trajectory height analysis (All) as an example.

Figure 3. Extinction Weighted Residence Time (EWRT) analysis for ammonium sulfate (Amm_SO4) and ammonium nitrate (Amm_NO3) at the DENA1 IMPROVE monitor for the Most Impaired Days during 2014-2018 aggregated across all trajectory heights

Weighted Emissions Potential (WEP):  WEP is obtained by overlaying the EWRT results with the EPA 2016 emissions of light extinction precursors (e.g., NOx emissions for ammonium nitrate extinction) in each grid cell divided by the distance of the source to the IMPROVE monitor. The gridded WEP values for each source sector are then normalized by the sum of the WEP for the total anthropogenic emissions (TOTAL_ANTHRO) across all grid cells. Using the sum of the total anthropogenic values as a common denominator allows for the WEP results to be compared across source sectors. The WEP folder for the MID contains four subfolders corresponding to the precursor emissions for four major components of light extinction: EC (Elemental Carbon), NOx (Ammonium Nitrate), POA (Organic Aerosol) and SOx (Ammonium Sulfate).  The WEP folder for the 20% percent highest extinction days for TUXE1 and KPBO1 contain subfolders for NOx, SOx, and coarse primary mass (CPRM). Each precursor species subfolder contains 21 plots in which the EWRT at three heights above ground are overlaid with 2016 emissions from 7 gridded Source Sectors (21 = 3 x 7). The source sectors are described in the Emissions section above, and example plots for DENA1 on MID are shown in Figure 4.  The dark green and light green isopleths in the WEP plots correspond to the, respectively, 0.5 and 0.1 percent frequency from the corresponding EWRT results.

Figure 4. Weighted Emissions Potential (WEP) analysis for ammonium nitrate extinction at the DENA1 IMPROVE monitor on the Most Impaired Days during each year of 2014-2018 for NOx emissions from four Source Sectors:  (1) total anthropogenic (top left), (2) Oil and Gas (top right), (3) EGU point source (bottom left) and (4) Non-road mobile sources (bottom right). Results are aggregated across all trajectories’ heights.

As described above, shapefiles of the WEP results (along with RT and EWRT) for each CIA and source sector are also provided. The columns of the attribute tables of these files are described in Table 2 below.

ColumnDescription
iThe column of the grid cell in the EPA’s 9-km AK modeling domain (aggregated to 27 km resolution)
jThe row of the grid cell in the EPA’s 9-km AK modeling domain (aggregated to 27 km resolution)
ijThe grid cell of the facility in the EPA’s 9-km AK modeling domain (aggregated to 27 km resolution). Format is row (i) *1000 + column (j)
distanceDistance in meters between the grid cell and the IMPROVE monitor that represents the Class I area (D in Q/D calculations). Distances are calculated using the Lambert Conformal Conic projection of the EPA’s 9-km AK modeling domain
rtResidence time of the grid cell
pct_rtResidence time of the grid cell as a percentage of the total residence time across all grid cells in the domain
ewrt_SO4The Amm_SO4 extinction weighted residence time (EWRT) for the grid cell
ewrt_NO3The Amm_NO3 extinction weighted residence time (EWRT) for the grid cell
ewrt_ocThe OA extinction weighted residence time (EWRT) for the grid cell
ewrt_ecThe EC extinction weighted residence time (EWRT) for the grid cell
ewrt_cmThe CM extinction weighted residence time (EWRT) for the grid cell
pctewrtso4The Amm_SO4 extinction weighted residence time (EWRT) for the grid cell as a percentage of the total EWRT for Amm_SO4 across all grid cells
pctewrtno3The Amm_NO3 extinction weighted residence time (EWRT) for the grid cell as a percentage of the total EWRT for Amm_NO3 across all grid cells
pctewrtocThe OA extinction weighted residence time (EWRT) for the grid cell as a percentage of the total EWRT for OA across all grid cells
pctewrtecThe EC extinction weighted residence time (EWRT) for the grid cell as a percentage of the total EWRT for EC across all grid cells
pctewrtcmThe CM extinction weighted residence time (EWRT) for the grid cell as a percentage of the total EWRT for CM across all grid cells
Q_NOXEPA 2016 NOx emission rate of grid cell in tons pers year for source sector (Q in Q/D calculations)
Q_SOXEPA 2016 SOx emission rate of grid cell in tons pers year for source sector (Q in Q/D calculations)
Q_PECEPA 2016 EC emission rate of grid cell in tons pers year for source sector (Q in Q/D calculations)
Q_POAEPA 2016 OA emission rate of grid cell in tons pers year for source sector (Q in Q/D calculations)
Q_CPRMEPA 2016 CPRM emission rate of grid cell in tons pers year for source sector (Q in Q/D calculations)
QD_NOXThe grid cell’s NOx emissions (Q_NOX) in tons/year for the given source sector divided by the distance to the IMPROVE monitor (D) in kilometers
QD_SOXThe grid cell’s SOx emissions (Q_SOX) in tons/year for the given source sector divided by the distance to the IMPROVE monitor (D) in kilometers
QD_PECThe grid cell’s EC emissions (Q_PEC) in tons/year for the given source sector divided by the distance to the IMPROVE monitor (D) in kilometers
QD_POAThe grid cell’s OA emissions (Q_POA) in tons/year for the given source sector divided by the distance to the IMPROVE monitor (D) in kilometers
QD_CPRMThe grid cell’s CPRM emissions (Q_CPRM) in tons/year for the given source sector divided by the distance to the IMPROVE monitor (D) in kilometers
wep_noxThe Amm_NO3 EWRT (ewrt_no3) multiplied by the Q/D for NOx (QD_NOX) for the grid cell
wep_soxThe Amm_SO4 EWRT (ewrt_so4) multiplied by the Q/D for SOx (QD_SOX) for the grid cell
wep_pecThe PEC EWRT (ewrt_ec) multiplied by the Q/D for EC (QD_PEC) for the grid cell
wep_poaThe PEC EWRT (ewrt_oa) multiplied by the Q/D for OA (QD_POA) for the grid cell
wep_cprmThe CM EWRT (ewrt_cm) multiplied by the Q/D for CPRM (QD_CPRM) for the grid cell
pctwepnoxThe Amm_NO3 EWRT (ewrt_no3) multiplied by the Q/D for NOx (QD_NOX) for the grid cell as a percentage of the total WEP for the Total Anthropogenic NOx emissions summed across all grid cells
pctwepsoxThe Amm_SO4 EWRT (ewrt_so4) multiplied by the Q/D for SOx (QD_SOX) for the grid cell as a percentage of the total WEP for the Total Anthropogenic SOx emissions summed across all grid cells
pctweppecThe PEC EWRT (ewrt_ec) multiplied by the Q/D for EC (QD_PEC) for the grid cell as a percentage of the total WEP for the Total Anthropogenic EC emissions summed across all grid cells
pctweppoaThe POA EWRT (ewrt_oa) multiplied by the Q/D for OA (QD_POA) for the grid cell as a percentage of the total WEP for the Total Anthropogenic OA emissions summed across all grid cells
pctwepcprmThe CM EWRT (ewrt_cm) multiplied by the Q/D for CPRM (QD_CPRM) for the grid cell as a percentage of the total WEP for the Total Anthropogenic CPRM emissions summed across all grid cells
Table 2. Column listing and description for the WEP_SHP files

Rank Point (RANK_POINT):  The RANK_POINT spreadsheets consist of facility level 2014 and 2017 precursor emissions overlaid with the corresponding EWRT for 3 trajectory height scenarios (100m, 1000m and All).  There is a separate directory for each scenario (MID, 20pctHigh_NO3, 20pctHigh_SO4, 20pctHigh_CM) containing the various RANK_POINT Excel spreadsheets. The results for 2014 and 2017 are provided in separate tabs.

These results can be used to assess the potential contributions of specific facilities to visibility impairment at each Class I Area in various ways. We recommend sorting the facilities by the WEP metrics (e.g. WEP_NO3 column for Amm_NO3 extinction). These metrics account the air parcel trajectories and extinction on the MID, facility precursor emissions, and facility distance from the IMPROVE monitor. The columns of the RANK_POINT sheets are described in Table 3, and the other metrics provided in the RANK_POINT files are described below.

The QD columns provide the simple emissions over distance metric (Q/D) using the 2014 and 2017 facility-level precursor emissions.  While the Q/D metric can be used to screen the potential contributions of sources to visibility impairment at a given Class I area, it is simply based on the emission rate and distance from the IMPROVE monitor and does not account for the air parcel trajectories on the MID.

The EWRTxQ and WEP metrics do account for the air parcel trajectories on MID as they are calculated by multiplying the EWRT of the grid cell of the facility with the facility’s emission rate (Q) and Q/D, respectively.

ColumnDescription
FacilityIDPlant identification code
FacilityNamePlant name
LatitudeLatitude
LongitudeLongitude
County_FIPS, County_NameCounty FIPS code and name
NAICSNorth American Industry Classification System (NAICS) - an industry classification system
NAICSDescDescription of NAICS code
Q_NOX, Q_SO2, Q_PM10Facility-level emission rate in tons pers year (Q in Q/D calculations)
ijThe grid cell of the facility in the EPA 9km modeling domain (aggregated to 27 km resolution). Format is row (i)*1000 + column(j)
distanceDistance in meters between the facility and the IMPROVE monitor that represents the Class I area (D in Q/D calculations). Distances are calculated using the Lambert Conformal Conic projection of the 12WUS2 modeling domain
EWRT_NO3_IJ, EWRT_SO4, IJ, EWRT_CM_IJThe Amm_NO3 extinction weighted residence time (EWRT) for the grid cell of the facility (ij)
QD_NOX, QD_SO2, QD_PM10The facility's precursor emissions (Q) in tons/year divided by the distance to the IMPROVE monitor (D) in kilometers
EWRTxQ_NO3, EWRTxQ_SO4, EWRTxQ_CMThe EWRT for the grid cell of the facility (ij) multiplied by the facility-level precursor emissions (Q)
WEP_NO3, WEP_SO4, WEP_CMThe EWRT for the grid cell of the facility (ij) multiplied by the facility's Q/D for the precursor
Table 3. Column listing and description for the Rank_Point csv files

Table 4 shows a subset of the results for 2014 NOx sources at DENA1 on the MID aggregated across all trajectory heights. The sources are ranked by [WEP_NO3] (last column) for ammonium nitrate, and the top 30 facilities whose NOx emissions potentially contribute to visibility impairment on the 2014-2018 IMPROVE MID at DENA1 are shown.

FacilityID FacilityName County_Name distance Q_NOX EWRT_NO3_IJ QD_NOX WEP_NO3
229000002 Golden Valley Electric Association; Healy Power Plant Denali Borough (068) 14041.1 355.6 3289.1 25.3 83286.2
229000003 US Air Force (Clear); Clear Air Force Station Denali Borough (068) 63870.0 254.1 1508.7 4.0 6001.3
209000081 Doyon Utilities, LLC; Fort Wainwright (Privatized Emission Units) Fairbanks North Star Borough (090) 137559.7 1129.9 333.5 8.2 2739.5
209000001 US Air Force (Eielson); Eielson Air Force Base Fairbanks North Star Borough (090) 139141.9 739.8 326.5 5.3 1736.0
209000011 Golden Valley Electric Association; North Pole Power Plant Fairbanks North Star Borough (090) 136548.4 644.9 326.5 4.7 1542.0
209000002 Aurora Energy LLC; Chena Power Plant Fairbanks North Star Borough (090) 137883.4 613.6 333.5 4.5 1484.2
212200031 Chugach Electric Association; Beluga River Power Plant Kenai Peninsula Borough (122) 300712.0 1862.2 168.5 6.2 1043.7
202000001 Anchorage Municipal Light & Power; George Sullivan Plant Two Anchorage Borough (020) 279165.9 893.7 232.4 3.2 743.8
209000007 University of Alaska; Fairbanks Campus Power Plant Fairbanks North Star Borough (090) 136809.7 302.3 333.5 2.2 737.0
212200046 Hilcorp Alaska, LLC ; Swanson River Field Kenai Peninsula Borough (122) 346110.0 1704.6 91.9 4.9 452.4
218500075 BP Exploration (Alaska) Inc.; Central Compressor Plant (CCP) North Slope Borough (185) 731743.7 9474.6 29.0 12.9 375.0
218500022 BP Exploration (Alaska) Inc.; Central Gas Facility (CGF) North Slope Borough (185) 731770.0 5672.1 43.4 7.8 336.3
217000005 Titan Alaska LNG, LLC (formerly Fairbanks Natural Gas, LLC); LNG Plant #1 Matanuska-Susitna Borough (170) 261006.7 103.9 546.6 0.4 217.6
212200062 Hilcorp Alaska, LLC ; Platform C, Middle Ground Shoal, Cook Inlet Kenai Peninsula Borough (122) 353283.2 339.9 216.6 1.0 208.4
226100031 Copper Valley Electric Association; Glennallen Diesel Plant Valdez-Cordova Census Area (261) 248383.1 123.8 384.7 0.5 191.7
212200104 Alaska Electric and Energy Cooperative; Nikiski Combined Cycle Plant Kenai Peninsula Borough (122) 360196.3 392.0 166.2 1.1 180.9
209000003 Golden Valley Electric Association; Zehnder Facility Fairbanks North Star Borough (090) 138780.8 74.1 333.5 0.5 178.0
212200066 Tesoro Alaska Company, LLC; Kenai Refinery Kenai Peninsula Borough (122) 359054.4 332.5 166.2 0.9 153.9
212200061 Hilcorp Alaska, LLC ; Platform A Kenai Peninsula Borough (122) 349843.6 244.3 216.6 0.7 151.2
Table 4. Rank_Point results showing top 20 facilities ranked by [WEP_NO3] whose 2014 NOx emissions have the potential to contribute to visibility impairment due to Ammonium Nitrate at DENA1 on the Most Impaired Days for each year in 2014-2018

Potential Source Contributions (PSC) Analysis

A PSC analysis was performed to assess the relative potential contributions of anthropogenic and natural emission source groups within the EPA 27-km Alaska modeling domain to Amm_SO4 extinction on the MID at each CIA. PSC was calculated by integrating (i.e., summing) the WEP across the modeling domain for each source group.

Unlike the WEP analysis, which only considered anthropogenic emission sources, the PSC analysis also included volcanic emissions of sulfur dioxide (SO2) and oceanic emissions of dimethyl sulfide (DMS). An analysis of 2014 GEOS-Chem emissions for a region essentially equivalent to EPA’s CMAQ Alaska 27-km domain found that ~70% of the reactive sulfur emissions were from volcano degassing and DMS (Guo and Morris, 2020). Including these sources in the PSC allows for characterization of potential natural contributions to visibility impairment on the MID and provides context for the potential anthropogenic source contributions.

Input Data and Analysis Domain

IMPROVE Data for Most Impaired Days

The MID at DENA1, TRCR1, SIME1, and TUXE1 for the site-specific analysis periods provided in Table 1 were identified as those assigned to impairment group 90 in the IMPROVE Impairment Daily Budgets dataset. The impairment group metric includes days in which missing data was patched using the statistical approaches. KPBO1 could not be included in the PSC analysis as no MID impairment metric data is available for the site.

Analysis Domain

The PSC analysis was performed using the 27-kilometer (km) domain of EPA’s Regional Haze Modeling platform. Trajectory endpoints located outside the EPA 27-km domain were dropped from the analysis. This is different than the WEP/AOI analysis which used the extent of the EPA 9-km domain at 27-km resolution. Figure 5 displays the 27-km and 9-km domains used in EPA’s CMAQ modeling and the, respectively, PSC and WEP/AOI analysis.

Figure 5. 27-km and 9-km grid resolution modeling domains used in EPA’s Alaska CMAQ 2016 PGM modeling platform as well as in the PSC and WEP/AOI analyses
HYSPLIT Back Trajectory Modeling

The HYSPLIT back trajectories generated for the WEP/AOI analysis were used to calculate PSC. The HYSPLIT configuration and meteorology data used are document in the WEP/AOI section above.

Emissions

The PSC analysis for Amm_SO4 included both anthropogenic and natural emission sources of sulfur oxides (SOx). Anthropogenic emissions are from the EPA’s 2016 27-km modeling platform and were aggregated into the following source sectors for the PSC analysis:

  • PT_EGU – Electric generating unit emissions
  • PT_NON-EGU – Point source emissions from industrial activities
  • OG_AREA_POINT – Oil and Gas area and point sources (Upstream and Midstream)
  • NON-POINT – Low-level area source emissions including non-point, agricultural, residential wood combustion, and fugitive dust emissions
  • ON-ROAD – On-road mobile source emissions
  • NON-ROAD – Off highway mobile source emissions including non-road, airport, commercial marine (C1, C2, and C3), and rail sources
  • International – point, area, on road and fugitive dust sources from Canada. No emissions from Russia were included in the 2016 EPA modeling platform

In reviewing the results of the gridded WEP/AOI analysis ADEC noticed that the EPA modeling platform did not include emissions from the Healy Power Plant. For the PSC analysis, ADEC provided the reported SO2 emissions for Healy in 2016 (427.2 tons per year) and these emissions were added to the PT_EGU sector.

Annual SO2 emissions from volcanoes within the analysis domain were estimated using NASA’s satellite derived volcanic emissions inventory. The annual emissions were averaged across the analysis period for each IMPROVE site (see Table 1) for the PSC analysis. DMS emissions were estimated for the year 2016 using monthly climatologies of surface ocean DMS concentration and sea-to-air emission flux. The DMS emissions were scaled by a 0.6 factor to account for the amount of DMS that is likely ultimately oxidized to SO2/SO4 based on the work of Chen et al., (2018) who estimate that approximately 75% of the DMS is converted to SO2 and Veres et al., (2020) who found a new DMS product species (HPMTF) that results in approximately 25% of the DMS oxidation products in the Gulf of Alaska (0.6 ~ 0.75 x 0.75). Table 5 summarizes the total SO2 or SO2 equivalent (i.e., DMS) emissions within the 27-km domain for the various source sectors.  The anthropogenic emissions are from EPA’s 2016 CMAQ modeling, DMS was calculated using 2016 meteorology and volcanic emissions were based on satellite inventories for 2014-2018.  The volcanic and DMS natural emissions contribute 83% of the SO2 emissions within the 27-km CMAQ domain.  This is higher percentage of natural SO2 emissions than the 71% contribution estimated analyzing 2014 GEOS-Chem inventories for a similar size domain as documented in a June 30, 2020 Memorandum to the Alaska Department of Environmental Conservation. These differences are due in part to the CMAQ 2016 modeling not including emissions from Russia as a large portion of Russia is included in the 27-km domain (see Figure 5), although uncertainties in calculating volcanic and DMS emissions may also have contributed to the differences.

Source Sector SO2 Emissions
(TPY) (%)
US EGU Point1,747.30.14%
US Non-EGU Point1,434.90.12%
US On-Road Mobile40.20.00%
US Oil & Gas1,739.20.14%
US+CMV Non-Road Mobile187,801.315.17%
US Non-Point1,598.00.13%
International15,707.21.27%
DMS454,063.936.68%
Biogenic0.00.00%
Volcanic573,775.346.35%
Total1,540,616.6100.00%
Table 5. Total 2016 SO2 emissions (tons per year, TPY) within the 27-km domain by source sector

Differences in the WEP/AOI and PSC analyses

There are several differences between the WEP/AOI and PSC analyses:

  • WEP/AOI was based on the EPA’s 9-km modeling domain extent, while PSC used the larger 27-km domain. Both analyses were performed at 27-km grid resolution (see Figure 5).
  • The PSC analysis was only calculated for Amm_SO4, while the WEP/AOI analysis also included Amm_NO3, EC and OC.
  • Emissions from the Healy Power Plant were included in the PSC analysis, but were missing in the gridded WEP/AOI analysis (although Healy was included in the 2014 and 2017 RANK_POINT results).
  • Volcanic and DMS emissions were included in the PSC analysis but not in the WEP/AOI.

PSC Products

Just like the WEP/AOI, plots of the gridded residence time (RT), extinction weighted residence time (EWRT), and WEP for each CIA are provided along with plots of the emissions for each source group. Each of these metrics is described in detail in the WEP/AOI section above. In addition, pie charts showing the PSC for each source group as a percentage of the total are provided for each CIA. The plots are provided at the following link using the directory structure shown below with TUXE1 as an example.

Potential Source Contribution Plots

├── MID_PSC
│   ├── TUXE1
│       ├── RT
│       ├── EWRT
│       ├── WEP
│       ├── PSC
├── EMISSIONS
    ├── SOX

The pie charts of PSC for SO2 emission source sector potential contributions from sources within the 27-km domain to AmmSO4 extinction at the DENA1, TRCR1, TUXE1 and SIME1 CIAs on the MID are shown in Figures 6 through 9. A significant fraction of the PSC for DENA1 and TRCR1 were from anthropogenic emission sources (approximately 83% and 27%, respectively), while the PSC for TUXE1 and SIME1 were dominated by DMS and volcanic emissions (approximately 3% and 2% from the anthropogenic emission sources, respectively). DMS constitutes a significant fraction (8-23%) of the PSC at all four IMPROVE sites. Volcanic emissions also constitute a significant fraction at all sites but were the dominant source at TRCR1, TUXE1 and SIME1. The volcanic contribution increased with proximity to the Alaska Peninsula and Aleutian Islands.

It is important to note that the PSC is not source apportionment for many reasons, not the least of which is that source apportionment needs to account for contributions from all sources and the PSC just integrates the SO2 emissions WEP within the 27-km modeling domain. There are contributions to sulfate extinction from outside the domain used for the PSC analysis so the PSC does not include all sources. In addition, the PSC analysis does not consider chemical transformation, dispersion or deposition and has a very simplified representation of transport. However, it can be useful to provide a rough approximation of the ranking of potential contributions of in-domain SO2 emissions to sulfate extinction at the IMPROVE sites on the MID.

Figure 6. Potential Source Contribution by Source Sector for SOx emission contributions to AmmSO4 extinction at DENA1 on the 20% Most Impaired Days (2014-2018)
Figure 7. Potential Source Contribution by Source Sector for SOx emission contributions to AmmSO4 extinction at TRCR1 on the 20% Most Impaired Days (2014-2018)
Figure 8. Potential Source Contribution by Source Sector for SOx emission contributions to AmmSO4 extinction at TUXE1 on the 20% Most Impaired Days (2012-2014)
Figure 9. Sulfate Potential Source Contribution by Source Sector for SOx emission contributions to AmmSO4 extinction at SIME1 on the 20% Most Impaired Days (2014-2018)

References

Chen, Q., T. Sherwen, M. Evans and B. Alexander. 2018. DMS oxidation and sulfur aerosol formation in the marine troposphere: a focus on reactive halogen and multiphase chemistry. Atmos. Chem. Phys., 18, 13617-13637. http://eprints.whiterose.ac.uk/136782/1/acp_18_13617_2018.pdf

Guo, J. and R. Morris.  2020.  Identification of Potential Emissions Sources that can Contribute to Sulfate at Alaska IMPROVE Sites. Technical Memorandum to Molly Birnbaum, Alaska Department of Environmental Conservation.  Ramboll US Corporation. June 30.

Stein, A.F., Draxler, R.R, Rolph, G.D., Stunder, B.J.B., Cohen, M.D., and Ngan, F., (2015). NOAA's HYSPLIT atmospheric transport and dispersion modeling system, Bull. Amer. Meteor. Soc., 96, 2059-2077, http://dx.doi.org/10.1175/BAMS-D-14-00110.1

Rolph, G., Stein, A., and Stunder, B., (2017). Real-time Environmental Applications and Display sYstem: READY. Environmental Modelling & Software, 95, 210-228, https://doi.org/10.1016/j.envsoft.2017.06.025

Veres, P.R., et al., 2020. Global airborne sampling reveals a previously unobserved dimethyl sulfide oxidation mechanism in marine atmosphere. PNAS March 3, 2020 117 (9) 4505-4510. https://www.pnas.org/content/117/9/4505