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Impact of New North American Emissions Inventories on Urban Mobile Source Emissions for High-Resolution Air Quality Mode

This study examines the impact of recent changes to on-road emissions inventories on urban mobile source emissions and its implications for high-resolution air quality modeling. The case study focuses on New York City (NYC) and the Greater Toronto and Hamilton Area (GTHA).

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Impact of New North American Emissions Inventories on Urban Mobile Source Emissions for High-Resolution Air Quality Mode

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  1. Impact of New North American Emissions Inventories on Urban Mobile Source Emissions for High-Resolution Air Quality Modelling Junhua Zhang, Qiong Zheng, and Michael Moran Air Quality Research Division, ECCC, Toronto, Ontario, Canada 8th International Workshop on Air Quality Forecasting Research, Toronto, Ontario, Canada10-12 Jan. 2017

  2. Outline • Motivation for this study • Recent changes to on-road emissions processing - base year - emissions estimation tools - spatial surrogates - temporal profiles - chemical speciation • Example of impacts of changes to processed on-road emissions for 2 high-resolution sub-grids covering 2 large North America metropolitan areas: New York city (NYC) and Greater Toronto and Hamilton Area (GTHA) • Summary and conclusions

  3. Motivation • On-road mobile sources are an important source of emissions, especially in cities. In 2011, 23% of total anthropogenic NOx emissions in Canada were from on-road mobile sources and 40% in the US. • In recent years the tool to estimate on-road mobile emissions has changed from MOBILE6 to MOVES (MOtor Vehicle Emission Simulator) • MOVES has also undergone frequent updates from version 2010 to version 2014a, resulting in relatively large changes of on-road emissions estimates from inventory to inventory • Spatial and temporal allocation of on-road mobile emissions become increasingly important when AQ model resolution approaches the kilometer level • It is important to understand the impact of the above changes for high-resolution AQ modelling

  4. Changes to Recent Canadian and US On-road Emissions Inventories (1) • Replacement of MOBILE6 by MOVES started with the preparation of the US 2005 (and projected 2012) and Canadian 2010 inventories • Unlike MOBILE, MOVES differentiates between on-roadway emission processes and off-network emission processes for engine starts, idling, fuel vapor venting, etc. In addition to 12 road types, a new road type, off-network, with large emissions was introduced in MOVES MOVES-Based 2010 Canadian Monthly On-road NOx Emissions by Road Type

  5. Changes to Recent Canadian and US On-road Emissions Inventories (2) • A new set of on-road Source Classification Codes (SCC) was introduced in MOVES2014 and SMOKE v3.6 (https://www.cmascenter.org/smoke/smoke_release_notes.html) • List of recently used/analyzed US and Canadian on-road inventories Structure of Old SCC Structure of New SCC

  6. Changes to Spatial Surrogates – surrogates for old SCCs • 12 road types (6 rural + 6 urban  6 surrogates (3 rural + 3 urban)

  7. Changes to Spatial Surrogates – surrogates for new SCCs (MOVES2014) • 5 road types (2 rural + 2 urban + 1 off-network) • 4 surrogates for on-network (2 rural + 2 urban); 11 surrogates for off-network for 2011V2 and projected 2017 • various surrogates such as population also used previously for off-network emissions

  8. Changes to Temporal Profiles - temporal profiles for old SCCs • E.g., 12 weekday and 12 weekend diurnal profiles for 12 road types

  9. Changes to Temporal Profiles - temporal profiles for new SCCs • Very detailed weekly and hourly profiles were created based on U.S. VTRIS (Vehicle Travel Information System, https://www.fhwa.dot.gov/ohim/ohimvtis.cfm) national/state/county statistics. • For NY state there are 52 weekly profiles and 156 diurnal profiles. In addition to weekday and weekend profiles, day-specific and vehicle-specific diurnal profiles have also been created and are used

  10. Changes to Chemical Speciation • Many new on-road VOC speciation profiles have been introduced in recent SPECIATE databases. For example, SPECIATE 4.4 (released Feb. 2014) has 43 new exhaust/evaporative gas profiles for on-road mobile emissions and SPECIATE 4.5 (released Sept. 2016) has another 33 exhaust-gas profiles • Previously only one NOx speciation profile was used (NO:0.891, NO2:0.1, and HONO:0.009) • Recent US inventories (2011v2, projected 2017) based on MOVES2014 include pre-speciated SCC-specific NOx emissions: NO, NO2, and HONO, in addition to NOx emissions (beware potential for double-counting)

  11. Model Grid and Analysis Subgrids GTHA subgrid,Population 8M • Consider two 60x60 subgrids of PanAm 2.5-km high-resolution AQ modelling grid • Subgrids cover the metropolitan areas of Toronto (GTHA) and New York city (NYC) NYC subgrid, Population 19M

  12. Seven Emissions Cases Considered (4 for the NYC subgrid, 3 for the GTHA subgrid)

  13. Subgrid Total NO Emissions for July for Seven Cases NYC subgrid population 19M GTHA subgrid population 8M • Variation of subgrid total NO emissions is consistent with variation of input emissions inventories shown on Slide 5 • Difference of the subgrid total NO emissions between the two subgrids also reflects the difference in total population between them • NOx emissions are reduced by 40% from the 2011v2 inventory to the projected 2017 inventory for the NYC subgrid. This will help to reduce the reported high model NOx (NOy) bias (e.g., Simon, et al., 2016, 15th CMAS Conf.) when the 2011 US inventory is used

  14. Spatial Distribution of July NO Emissions - NYC Subgrid (1) • Case NYC-C1: • Projected 2012v1 US inventory (released in 2010 ) • Emissions were mainly distributed along major highways

  15. Spatial Distribution of July NO Emissions - NYC Subgrid (2) NYC-C2: 2011v1 NYC-C1: Projected 2012v1 • For NYC-C2 vs. NYC-C1, more emissions allocated to populated areas due to the large off-network emissions, for which population was used as spatial surrogate • For NYC-C3, 11 spatial surrogates were used for off-network emissions, resulting in less emissions than NYC-C2 but more emissions than NYC-C1 in populated areas • NYC-C4 has significantly less emissions than other 3 cases due to the reduction of NOx emissions in projected 2017 inventory NYC-C4: projected 2017 NYC-C3: 2011v2

  16. Spatial Distribution of July NO Emissions - GTHA Subgrid (1) • Case GTHA-C1: • 2010v1 Cdn inventory (released in 2013) • Similar to NYC-C1 case, emissions were mainly distributed along major highways

  17. Spatial Distribution of July NO Emissions - GTHA Subgrid GTHA-C1: 2011v1 GTHA-C2/GTHA-C1 • For GTHA-C2 vs. GTHA-C1, use of capped population as surrogate for emissions from local roads reduced emissions by 20%-50% in densely populated areas • For GHTA-C3 more emissions were allocated to populated areas than for GTHA-C1 and GTHA-C2 due to the large off-network emissions, even though capped population was used as spatial surrogate for off-network emissions GTHA-C2: 2011v1 GTHA-C3: 2013v3

  18. Time Series of NO Emissions - NYC Subgrid NYC Subgrid Total NO Emissions – One Week • Time series of the 2011v1 emissions is very similar to that of the projected 2012v1 emissions, although spatial distribution is much different • Time series of 2011v2 emissions is very different from the time series of 2011v1 due to different temporal profiles used • Time series of projected 2017 emissions is similar to 2011v2, but day-time emissions were reduced by about 50% Relative Difference between 2011v1 (C2) and v2 (C3) Weekday Hourly NO Emissions 0%

  19. Time Series of NO Emissions - GTHA Subgrid GTHA Subgrid Total NO Emissions – One Week • Diurnal variation of emissions is similar between the 2010v1 and the 2013v3 inventories, although spatial distribution is quite different • NOx emissions are increased by about 15% over the GTHA when the 2013v3 inventory is used

  20. Summary and Conclusions • Recent changes to Canadian and US on-road mobile emissions inventories have significant impacts on model-ready urban mobile emissions in terms of magnitude, spatial and temporal allocation, and chemical speciation • The projected 2017 US inventory released by the US EPA is likely to help reduce the large positive NOx bias predicted by air quality models using the 2011 US inventory • Due to changes in spatial surrogates, a larger portion of the mobile emissions will be allocated to populated areas • Changes to US temporal profiles will increase on-road emissions during the morning rush hours but reduce emissions during the afternoon rush hours and overnight • Whether these changes will improve AQ model predictions in North American urban areas still needs to be tested, particularly by high-resolution models

  21. QUESTIONS?

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