Railroads: emissions, analysis, impacts, and the potential for improvement

Transcription

1 Railroads: emissions, analysis, impacts, and the potential for improvement Michelle Bergin and Jim Boylan Georgia EPD Air Protection Branch MARAMA Workshop on Energy and Air Quality September 23, 2008

2 Outline Railroads Extent, Activity, and Emissions GA Railroad/Railyard Description, Analysis, and Plan Modeling and Data Analysis (Jim Boylan) Emissions Reductions Program Emissions Inventory Improvement Growth and Potential for Improvement

3 Inman (NS) and Tilford (CSX) Railyards in Atlanta, GA (RailPictures.Net, Adam Wright) Atlanta nonattainment area monitors, Inman Railyard is near FS#8

4 Railroad Extent and Type Railroad Category Definition by Revenue GA # % of track Class I (7+2 in US, 1.8T ton/m) $346.8M Class II (Regional) Class III (Shortline) $346.8M to $40M less than $40M Locomotives Line-Haul ~ HP, 40+ years, between cities and states. Switchers ~ up to 2500 HP (road and yard), generally retired linehaul locomotives, older and high emitting

5 Georgia Rail Shipments Coal Originating All other commodities Nonmetallic minerals Chemicals 11% 0% 23% Farm 9% products 14% 19% Glass and stone 24% 0% 0% products Lumber and wood products Mixed freight Pulp and paper products Plot data from Bureau of Transportation Statistics, Georgia Transportation Profile Approximately 70% of rail freight tonnage represents through traffic. (ARC Atlanta Regional Freight Mobility Plan, Feb. 2008)

6 North American Railroad Statistics

7 Benefits of Rail Cost effective freight services. Increased safety compared with trucks. Reduce highway congestion (a typical train is equivalent to several hundred trucks). Three or more times more fuel efficient than trucks. Produces less emissions compared with moving similar tons of freight by truck.

8 However (CARB, 2004) Smokestacks on Rails: Getting clean air solutions for locomotives on track, Environmental Defense, 2006

9 Railroad Emissions of Interest Line-haul, shortline, and yard locomotives and associated equipment: Engine specific emission factors Species Resulting Pollutant(s) NO x Ozone, PM 2.5 (nitrate, OC), NO x PM 2.5 PM 2.5 (as elemental carbon, toxic) SO 2 VOCs (HC) CO, CO 2 Toxics Soil dust and metals PM 2.5 (to sulfate), acid rain Ozone, PM 2.5 (to organic carbon), Greenhouse Gases CO, Greenhouse Gases HAPs and Mobile Source Air Toxics (gas and particle phases) PM 2.5, toxics

10 GA Air Quality, Population, and Railroads Red: PM 2.5 and ozone nonattainment Purple: Ozone nonattainment Green: 5 Urban Core Counties (Cobb, Fulton, Gwinnett, Dekalb, Clayton) Blue lines: Railroad tracks Blue squares: population density

11 Rail Activity in the Urban Core Rail Yards GA DOT Traffic Density (GTM) GA DOT Source: GA DOT

12 Inman and Tilford Railyards and the Fire Station #8 Monitor Fire Station 8

13 Location of Core Urban Monitors and Annual Average PM2.5 Doraville Health F.S.#8 E.Rivers Jeff. St. South- DeKalb East Point Forest Park 2 mi 5 km

14 Air Quality Management Tools: Photochemical, dispersion, and receptor modeling Air Quality Goals Air Quality/Health Impacts Control Chemistry Pollutant Distributions Predictions Observations Air Quality Model Emissions Basecase performance Future case control analysis Meteorology Receptor Model (e.g. PMF) Photochemical Modeling Dispersion Modeling (no chem.)

15 Quantifying Rail Yard Contributions to PM in Atlanta, GA Jim Boylan, GA EPD Air Protection Branch, Planning and Support, Manager of Data and Modeling Unit Outline Photochemical Modeling 2009 PM2.5 Attainment Modeling with CMAQ Dispersion Modeling Local Scale AERMOD Data Analysis and Receptor Modeling (PMF)

16 CMAQ Modeling for PM 2.5 Attainment

17 Future PM 2.5 Concentrations (BaseG emissions)

18 PM 2.5 Sensitivity at FS #8 Sensitivity Summer (μg/m 3 ) Winter (μg/m 3 ) Annual (μg/m 3 ) Annual (ng/m 3 /TPD) 10% Atlanta PC % Atlanta SO % Atlanta NOx % Atlanta NH % Atlanta VOCs Scrubbers at Bowen Scrubbers at Branch Scrubbers at McDonough Scrubbers at Scherer Scrubbers at Wansley Scrubbers at Yates

19 Railroad Tracks on 12 km Grid

20 Railroad Tracks on 4 km Grid

21 Summary of CMAQ Modeling Fire Station #8 will likely not show attainment for annual PM2.5 in 2009 Control of Primary Carbon emissions from local sources may be important at Fire Station #8 CMAQ modeling at 12 km is not adequate to quantify impacts of local sources CMAQ modeling at 4 km still may not be adequate Need local scale dispersion modeling for primary PM2.5 emissions (next section)

22 AERMOD Modeling for Local Sources

23 Nearby Stationary Sources

24 Potential Local Sources Inman and Tilford Railyards Diesel traffic sources along Marietta Blvd. Local crushed stone quarry Local asphalt and concrete batch plants Georgia Power s Plant McDonough Coal-fired EGU Meadwestvaco Packaging Systems

25 Model Set-Up 2002 Annual Simulation Preliminary flat plane terrain Five-hundred meter receptors Hartsfield Airport meteorology

26 Model Domain (500m 2, 15.5km x 12km)

27 Railyard Emissions Started with Norfolk Southern s estimate of yard-engine emissions operating in Inman Yard, doubled to account for local line-haul emissions in Inman Yard (underestimate) Assumed same emissions at adjacent CSX Tilford Yard (overestimate) Railyards were modeled as volume emission sources and located on the appropriate railyard site Initial railyard emissions thought to be low Revised run with emissions increased by 5 times based on XRF/PMF analysis (discussed later)

28 Initial Annual PM 2.5 Impacts

29 Revised Annual PM 2.5 Impacts (Emissions increased by 5 times)

30 Annual PM 2.5 Averages (stations <3 miles from Fire Station #8)

31 Annual PM2.5 Impacts Initial modeling showed an annual average PM 2.5 impact of 0.3 μg/m 3 at Fire Station # 8 Revised modeling (emission rates times 5) showed an annual average PM 2.5 concentration of 1.5 μg/m 3 at Fire Station # 8 Revised modeling shows a 1.4 μg/m 3 concentration increase at FS#8 over E. Rivers Similar to observations Currently refining dispersion model application

32 Data Analysis and Receptor Modeling (based on analysis by Amit Marmur) - Wind direction - Filter analysis - Positive Matrix Factorization (PMF) factor analysis (EPA-PMF 1.1 model)

33 FS#8 PM 2.5 vs. Wind Direction (measured at JST),

34 PM 2.5 vs. WD additional sites

35 Receptor vs. Emissions-Based Models Emissions Inventory Chemistry Meteorology Source-compositions Source Impacts Receptor (monitor) Air Quality Receptor Model (e.g., PMF) Emissions-based Model (3D Air-quality Model) (e.g., CMAQ)

36 Application of PMF at F.S.#8 PMF was applied to a set of ambient PM 2.5 measurements collected at the Fire Station #8 site Since the site is NOT a speciation site (STN), selected PM 2.5 filters were sent for XRF analysis, to quantify the concentrations of trace metals on the filters Ions and carbon data could not be derived from the (teflon) filters PMF analysis performed using metals data only A total of 118 samples were available for the analysis, during the period of Jan 2002 Jan 2005 Samples were selected to represent the distribution of differences in PM 2.5 levels at F.S.#8 and two other nearby sites, Jeff. St. (2.2 miles SE) and E.Rivers (2.9 miles NE)

37 Factors identified by PMF Six factors were identified by PMF, likely indicative of the following sources: Aluminum/Silicon factor Soil dust Calcium/Vanadium factor Cement operations Potassium factor Biomass burning Sulfur factor Secondary sulfate (from coal combustion) Iron/Manganese/Copper/Nickel factor Steel particles Zinc factor Mobile sources

38 Explaining the increment in PM 2.5 concentrations at F.S.#8 - results Factor Avg. contribution (μg/m 3 ) p-value Soil 0.25 ± Cement 0.21 ± Biomass burning 0.23 ± Sec. sulfate 0.08 ± Steel 1.18 ± E-08 Mobile sources 0.60 ± Quality of fit: R = 0.76; Mod./Obs. = 0.97

39 Explaining the increment in PM 2.5 concentrations at F.S.#8 - results

40 Explaining the increment in PM 2.5 concentrations at F.S.#8 - summary Solid all data Striped excluding negatives, 4/14/02 Soil Cement Biomass burning Sec. sulfate Steel Mobile sources

41 Summary of findings The steel and mobile-sources factors are the most correlated with the increment in PM 2.5 levels at F.S.#8 The steel factor is likely an indicator of steel dust generated at the nearby rail yard Columbia & Harvard 2004 study finds elevated levels of Fe/Mn/Cr at NYC subway compared to outside ambient air (>100 times greater; Chillrud et al., ES&T 38, 2004) Fe/Mn/Cu levels at F.S.#8 are >2 times greater compared to Jeff. St. Note: While the steel factor serves as an indicator for activity at the rail yard, most mass emissions from the moving locomotives are in the form of carbon ( soot ) particles The mobile-source factor may be an indicator of either local truck traffic, idling locomotive engines or activity at the fire station (idling of fire trucks etc.)

42 GA EPD Rail Program/Plan Railroad Workgroup Meeting (3/07) Emission Reductions CMAQ proposals (12/07), near final award Emission Inventory Improvement internal efforts and questionnaires (9/07) monitoring and analysis (CMAQ subproject, pending) ERTAC Rail Subcommittee (1/09 goal) Refine Dispersion Modeling Sensitivity Analysis (photochemical, 4km?)

43 The CMAQ Program Congestion Mitigation and Air Quality Program (SAFETEA-LU, US DOT) FY2008 $1.75B, FY2009 $1.78B Minimum apportionment to each state (0.5%), then nonattainment areas (ozone and CO) For use in ozone, PM, or CO nonattainment areas State DOT, Air Quality Partners, Metropolitan/Regional Planning Organizations, and Environmental Protection Agencies (in Atlanta, GDOT, ARC, GRTA, EPD, also Macon and Rome).

44 Response to GDOT CMAQ call GA EPD held an informational workgroup meeting with railroads and other stakeholders in March GDOT released a call for proposals focused on reduction of PM2.5 (Aug 2007). Extended for FY (Oct 2007). GA EPD evaluated options and submitted 3 rail-related proposals (Atlanta, Macon, Rome) with letters of support from Norfolk Southern, CSX, the Southern Alliance for Clean Energy, and the Clean Air Task Force (Dec 2007).

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46 Genset Switcher Conversions Gensets also use 25-35% less fuel, with associated decreases in other emissions (e.g. CO 2, toxics)

47 Overview/Status Including 20% - 50% matching funds NAA Request *Award Potential # Gensets (award) o Potential emission reduction over 5 years (tons) PM2.5 NOx Atlanta $50.56M + $36.2M Macon $12M $4.5M Rome $1.2M $900k Total $63.76M $41.6M * Final award to EPD is near completion pending GDOT and GA DNR Board decisions. o Estimates are based on updated emission factors (Sierra Research for SESARM, Report No. SR , June 2008) and a 76% NO x and 93% PM 2.5 reduction factor for Genset use. + Atlanta proposal cost includes monitoring and analysis project around the Fire Station 8 monitor. Final project results will be based on upcoming proposals and negotiations.

48 Building an Emissions Inventory Types of sources (point, area, biogenic, on-road and non-road mobile) Spatial and temporal patterns of release (elevated/ground level, hourly, weekly, seasonal, ) Chemical composition ( speciation profile ) Public domain figures, references available

49 Current Calculation Method for Railroad Emissions (EPA) Class I Line-haul locomotives System-wide (not statewide) annual fuel use National fleet average line-haul emission factors (EPA) County level track length and annual traffic density (in GTM), often system-wide (fuel consumption index) Switcher locomotives No database of railyard locations or extent (poss. FRA) Number of switchers per yard (estimated or voluntarily submitted) National average annual fuel use estimate (EPA) National average switcher emission factors (EPA) Class II/III no common data, voluntary submission or surrogates Locomotive activity assumed constant (daily, annually) Other (maintenance/inspection, cargo handling equipment, yard related trucking?) EPA NONROAD mobile emissions model maintenance equip

50 Emission Level Uncertainty NYSERDA CLEAN DIESEL TECHNOLOGY: Non-road Field Demonstration Program, Development of the 2002 Locomotive Survey for New York State (Feb 2007)

51 ERTAC Rail Subcommittee Member agencies represented States (12): AL DEM, GA EPD, IL EPA, ME DE, MI DEQ, MO DNR, NC DENR, NY DEC, OH EPA, PA DEP, SC DHEC, WI DNR RPOs (3): LADCO (ERTAC lead), MARAMA, VISTAS/ASIP Progress Common understanding of issues and skills. Discussions of potential methodologies. Sub-group assignment to Class I, yards, Class II/III, and commuter/passenger rail. Initial contact with stakeholder groups (FRA, BTS, AAR). Survey of available and derivable data, contact with potential sources. Goal: methodology and known data sources by Jan 2009.

52 Future Demand for Freight Transportation Will Continue to Grow Billions of Tons of Freight Transported in the U.S p p U.S. DOT projects 88% increase in demand Will require a $148B infrastructure investment over the next 28 years. Study commissioned by the AAR at the request of the National Surface Transportation Policy and Revenue Study Commission. Freight Railroad Infrastructure and Capacity Issues presentation by Craig F. Rockey, VP of Policy & Economics, Association of American Railroads, Chicago, Illinois, Oct. 17, 2007

53 Future Corridor Volumes Compared to Current Corridor Capacity 2035 without improvements Below capacity Near capacity At capacity Above capacity Freight Railroad Infrastructure and Capacity Issues Craig F. Rockey, VP Policy & Economics, Association of American Railroads, National Rail Conference, Chicago, Il. Oct. 17, 2007

54 % Growth in Trains Per Day From 2005 to 2035 by Primary Rail Corridor Freight Railroad Infrastructure and Capacity Issues Craig F. Rockey, VP Policy & Economics, Association of American Railroads, National Rail Conference, Chicago, Il. Oct. 17, 2007

55 Thank You Contact Info: Michelle Bergin

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