### WEIGHTED EMISSIONS POTENTIAL ANALYSIS

Introduction
The Weighted Emissions Potential analysis (WEP) was developed as a screening tool for states to decide which source regions have the potential to contribute to haze formation at specific Class I areas, based on both the 2002 and 2018 emi ssions inventories. This method does not produce highly accurate results because, unlike the air quality model and associated PSAT analysis, it does not account for chemistry and removal processes. Instead, it relies on an integration of gridded emissions data, back trajectory residence time data, a one-over-distance factor to approximate deposition, and a normalizat ion of the final results. Residence time over an area is indicative of general flow patterns, but does not necessa rily imply the area contributed significantly to haze at a given receptor. Therefore, users are cautioned to view the WEP as one piece of a larger, more comprehensive weight of evidence analysis.
Emissions Data Inputs
The emissions data used were the annual, 36km grid SMOKE-processed, model-ready emissions inventories provided by the WRAP Regional Modeling Center (RMC) . The analysis was performed for nine (9) pollutants (maps were generated for all but the last three):

 Sulfur oxides

 Nitrogen oxides

 Organic carbon

 Elemental carbon

 Fine particulate matter

 Coarse particulate matter

 Ammonia

 Volatile organic carbon

 Carbon monoxide.
The following source categories for each polluta nt were identified and preserved through the analysis:

 Biogenic

 Natural fire

 Point

 Area

 WRAP oil and gas

 Off-shore

 On-road mobile

 Off-road mobile

 Road dust

 Fugitive dust

 Windblown dust

 Anthropogenic fires

1Residence Time Inputs
The back trajectory residence ti m es were provided by the WRAP Causes of Haze Assessment (COHA) . The COHA project used NOAA’s HYSPLIT model to generate eight (8) back trajectories daily for each WRAP Class I area for the entire five-year baseline period (2000-04). The major model parameters selected for this an alysis are presented in Table 1. From these individual trajectories, reside nce time fields were generate d for one-degree latitude by onedegree longitude grid cells. Residence time anal ysis computes the amount of time (e.g., number of hours) or percent of time an ai r parcel is in a horizontal grid cell. Plotted on a map, residence time is shown as percent of total hours in each grid cell across the domain, thus allowing an interpretation of general air flow patterns for a given Class I area. The residence time fields for the 20% worst and best IMPROVE-monitored ex tinction days were selected for the WEP analysis to highlight the potential emissi ons sources during those specific periods.

Table 1 Back Trajectory Model Paramete rs Selected for WEP Analysis

Model Parameter Value Trajectory duration 192 hours (8 days) backward in time Top of model domain 14,000 meters Vertical motion option used model data Receptor height 500 meters Meteorological Field EDAS and FNL (location dependent)

Integration of Emissions and Residence Time Data
The WEP analysis consisted of weighting the a nnual gridded emissions (by pollutant and source category) by the worst and best extinction days re sidence times for the five -year baseline period. To account for deposition along the trajectories, the result was fu rther weighted by a one-overdistance factor, measured as the distance in km be tween the centroid of each emissions grid cell and the centroid of the grid cell containing the Cl ass I area monitoring s ite under investigation. (The “home” grid cell of the monitoring site wa s weighted by one fourth of the 36km grid cell distance, or one-over-9km, to a void a large response in that grid cell.) The resulting weighted emissions field was normalized by the highe st grid cell to ease interpretation.
An example series of maps illustrating the WEP an alysis is presented in Figure 1. This example shows the annual emissions for NOx across the do main, the specific resi dence time pattern for the 20% worst monitored days at a Class I area, and the resulting weighted emissions map. Both the 2002 and 2018 cases are presente d. Interpretation of the results should fo cus on which grid cells (or larger regions) have significant potential to affect the Class I area, and on changes between 2002 and 2018.
An example of associated bar charts showing the estimated contributi on by source category and region is presented in Figure 2. It is important to note that these charts show normalized values with no direct connection to original emissions values. Inte rpretation of the re sults should focus

23 on the relative contributions by each source cat egory and region, and the changes between 2002 and 2018.

Caveats
The WEP is not a rigorous, stand- alone analysis, but a simple, st raightforward use of existing data. As such, there are several caveats to keep in mind when using WEP results as part of a comprehensive weight of evidence analysis:

 This analysis does not take into account any emissions chemistry.

 While actual emissions may vary considerably throughout the year, this analysis pairs up annual emissions data with 20% worst/bes t extinction days residence times – this is likely most problematic for carbon and dust emissions, which can be highly episodic.

 Coarse particle and some fine particle dus t emissions tend not to be transported long distances due to their large mass.

 The WEP results are unitless numbers, normali zed to the largest-valued grid cell. Effective use of these results requires an understanding of actual emissions values and their relative contribution to haze at a given Class I area.2002 NOx Emissions (TPY)Residence Time Field, Worst 20% MonitoredDays (2000-2005)2002 NOx Emissions Weighted by ResidenceTime and One-Over-Distance2018 NOx Emissions (TPY)Residence Time Field, Worst 20% MonitoredDays (2000-2005)2018 NOx Emissions Weighted by ResidenceTime and One-Over-DistanceFigure 1. Example series of maps for WEPanalysis at Bridger Wilderness, WY. Fromleft to right: single-year annual emissions densitymap; five-year residence time map; emissionsweighted by residence time, by one-over-distance, and normalized to the highest grid cell. Toprow presents 2002 results, bottom row presents 2018 results.4Sources and Areas of Potential Nitrogen Oxide Emissions Influence 2000-2004 Baseline for Bridger Wilderness, WY 20% Worst Visibility Days

4.8 12.6

0.8 22.1

3.4 4.3

0.5 0.2 4.6

0.1 19.9

3.7 15.1

3.2 1.3 0.3 0.7 2.3

0 10 20 30 40

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E a s t er

n US Me x i c o CanadaPercent of Total Distance Weighted Emis x ResTime Biogenic Natural Fire Point Area WRAP Area O&G Off-Shore On-Road Mobile Off-Road Mobile Road Dust Fugitive Dust WB Dust Anthro Fire

Sources and Areas of Potential Nitrogen Oxide Emissions Influence 2018 Projections for Bridger Wilderness, WY 20% Worst Visibility Days

3.2 7.7

0.6 20.6

3.1 3.7
0.6 0.2 3.3

0.1 13.9

2.2 33.1

2.7 1.0 0.2 0.7 3.2

0 10 20 30 40

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n US Me x i c o CanadaPercent of Total Distance Weighted Emis x ResTime Biogenic Natural Fire Point Area WRAP Area O&G Off-Shore On-Road Mobile Off-Road Mobile Road Dust Fugitive Dust WB Dust Anthro Fire

Figure 2. Example source categor y bar charts based on WEP anal ysis at Bridger Wilderness, WY. Top chart presents 2002 results, bottom chart presents 2018 results. 5