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Work Order No. 582-18-82809-31Contract # 582-15-50417
Texas Commercial Marine Modeling EmissionsInventory Report
PREPARED UNDER A CONTRACT FROM THETEXAS COMMISSION ON ENVIRONMENTAL QUALITY
The preparation of this report was financed through a contract from theState of Texas through the Texas Commission on Environmental Quality.
The content, findings, opinions and conclusions are the work of the author(s) anddo not necessarily represent findings, opinions or conclusions of the TCEQ.
Prepared for:Jim MacKay
Texas Commission on Environmental Quality121 Park 35 Circle MC 164
Austin, TX 78753
Prepared by:Timothy M. Sturtz, Leslie Nguyen,
Maria Zatko, Chris Lindhjem, and Greg YarwoodRamboll Environ
773 San Marin Drive, Suite 2115Novato, California, 94998
June 2018
1690007682
Work Order No. 582-18-82809-31Contract # 582-15-50417
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CONTENTS
GLOSSARY OF TERMS .............................................................................................................. II
1.0 INTRODUCTION ................................................................................................................. 1
1.1 Purpose ....................................................................................................................... 3
2.0 METHODOLOGY ................................................................................................................. 3
2.1 Data Preprocessing ..................................................................................................... 3
2.1.1 Voyage Determination ...................................................................................... 32.1.2 Segment Analysis .............................................................................................. 42.1.3 Ocean-Going Vessel and Harbor Craft Separation ............................................. 42.1.4 Activity Analysis ................................................................................................ 42.1.5 Berthing Treatment ........................................................................................... 5
2.2 Ocean-Going Vessels Emissions Approach ................................................................... 5
2.2.1 Propulsion Engines ............................................................................................ 52.2.2 Auxiliary Engines and Boilers ............................................................................. 62.2.3 Ocean-Going Vessel Emission Factors ............................................................... 7
2.3 Harbor Craft Emissions Approach ................................................................................ 8
2.3.1 Harbor Craft Emission Factors ........................................................................... 9
3.0 RESULTS ........................................................................................................................... 11
3.1 Vessel Activity ........................................................................................................... 11
3.2 Vessel Emissions ....................................................................................................... 12
4.0 FORECASTS ...................................................................................................................... 15
4.1 Economic Trends ....................................................................................................... 15
4.2 OGV Emissions Forecasting ....................................................................................... 20
4.3 Harbor Craft Emissions Forecasting ........................................................................... 23
5.0 CONCLUSIONS & RECOMMENDATIONS ........................................................................... 24
6.0 REFERENCES ..................................................................................................................... 25
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GLOSSARY OF TERMSAdjustment factors: Used to adjust emission factors or engine load factors or other situations
for non-standard conditions.
Anchorage: Vessels anchored off-shore waiting for berth or next assignment.
Assist mode: Period when a tugboat is engaged in assisting a ship to/from its berth ormaneuvering in the harbor.
Automatic Identification System (AIS): AIS is an automatic tracking system used on ships andby vessel traffic services (VTS) for identifying and locating vessels by electronicallyexchanging data with other nearby ships, AIS base stations, and satellites.
Auxiliary engine: Used to drive on-board electrical generators to provide electric power or tooperate equipment on board the vessel.
Auxiliary power: Typically electric power generated via the auxiliary engine.
Berth: A location alongside a pier to moor vessels.
Bulk: Vessels designed to transport dry bulk (e.g. grain, potash, sand and gravel, etc.).
Cargo: Vessels designed to transport break bulk too big to fit into containers (e.g.machinery, parts, etc.)
Container: Vessels designed to carry freight containers.
Cruise mode: The vessel mode while traveling in the open ocean or in an area without speedrestrictions.
Gross tonnage (GT): The internal volume of tween-decks and deck space used for cargo and is ameasurement of volume of all enclosed spaces on a ship with 100 cubic feet = toone ton.
Diesel-electric: Ship propulsion designs where sets of diesel engines generate electric power todrive propellers and primarily used on most cruise ships.
Emission Control Areas (ECAs): These areas must comply with international regulations on fuelsulfur and engine NOx emission standards, and applies to most U.S. and Canadianwaters.
Emission factor: The average emission rate of a given pollutant for a given source, relative to aunit of activity. Typical examples are grams per kilowatt of actual power or gramsper hour of engine operation.
Emissions inventory: A listing of all the pollutant emissions included in the study.
Gas turbines: An alternative engine type to internal combustion diesel engines used on somecruise ships.
Gross Tonnage (GT): Defined by the volume of space within the hull and enclosed space abovethe deck of a merchant ship which are available for cargo, stores, fuel, passengersand crew with units of 100 cubic feet of capacity equivalent to one gross ton.
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g/kW-hr: This is the unit for reporting emission or fuel consumption factors, and means thegrams per kilowatt-hour of work performed. Work and energy are usedsynonymously in this context.
Harbor Craft: The smaller vessels conducting business in the bay, including excursion vessels,pilot boats, assist tugs, and towing tugs.
Hotelling: On-board activities while a ship is in port and at its berth or at anchor.
IHS Fairplay: Database of vessel characteristics including speed, engine power, and otherinformation and is cross referenced with IMO or MMSI number.
Installed power: The engine power available on the vessel. The term most often refers only tothe propulsion power available on the vessel, but could incorporate auxiliaryengine power as well.
IMO ship identification number: The International Maritime Organization (IMO) number ismade of the three letters "IMO" followed by the seven-digit number assigned to allships by IHS Fairplay (formerly known as Lloyd's Register-Fairplay) whenconstructed.
Knot: A nautical unit of speed meaning one nautical mile per hour and is equal to about1.15 statute miles per hour.
Link: A defined portion of a vessel’s travel. For example a link was established extendingfrom Ports out to the ocean. A series of links defines all of the movements within adefined area or a trip.
LNG: Liquefied natural gas
Load: The actual power output of the vessel’s engines or generator. The load is typicallythe rated maximum power of the engine multiplied by the load factor if notmeasured directly.
Load factor: Average engine load expressed as a fraction or percentage of rated power.
LPG: Liquid petroleum gas, or primarily propane.
Maneuvering: Very slow transiting to position the ship.
Maritime Mobile Service Identity (MMSI): is a series of nine digits which are sent in digitalform over a radio frequency channel in order to uniquely identify ship stations,ship earth stations, coast stations, coast earth stations, and group calls.
Maximum power: A power rating usually provided by the engine manufacturer that states themaximum continuous power available for an engine.
Medium speed engine: A 4-stroke engine used for auxiliary power and rarely, for propulsion.Medium speed engines typically have rated speeds of greater than 130 revolutionsper minute.
Mode: Defines a specific set of activities, for example, a tug’s transit mode includes traveltime to/from a port berth while escorting a vessel.
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NOx: nitrogen oxides and includes all nitrogen oxide compounds.
Ocean-going vessels (OGV): Vessels equipped for travel across the open oceans. These do notinclude the vessels used exclusively in the harbor, which are covered in this reportunder commercial harbor craft. In this report, OGV are restricted to the deep draftvessels.
Operation mode: the current mode of operation for a ship – for example, cruising,maneuvering, or hotelling.
PM10: Particulate matter emissions less than 10 micrometers in diameter.
PM2.5: Particulate matter emissions less than 2.5 micrometers in diameter
Port of Call: A specified port where a ship docks.
Propulsion engine: Shipboard engine used to propel the ship.
Propulsion power demand: Power used to drive the propeller and the ship.
Rated power: A guideline set by the manufacturer as a maximum power that the engine canproduce continuously.
Reduce Speed Zone (RSZ): Mode where ship transit at slower speeds due to traffic or speedlimits.
ROG: Reactive organic gas; all hydrocarbon compounds that can assist in producingozone (smog). Includes hydrocarbons (HC) plus aldehyde and alcohol compoundsminus methane, often used interchangeably with HC although they are not quitethe same.
RoRo: Roll on/Roll off vessel usually designed to carry new vehicles but could includeother rolling freight
SOx: Oxides of sulfur. Interchangeable term with sulfur dioxide but include some otherminor forms of sulfur oxides.
Spatial allocation: Areas on a map allocating a specific set of activities.
Spatial scope: A specified area on a map that defines the area covered in study.
Slow speed engine: Typically a 2-stroke engine or an engine that runs below 130 rpm.
Steam boiler: Boiler used to create steam or hot water using external combustion.
Time in mode: The amount of time a vessel remains in a specified mode, for example theamount of time a ship spends in the reduced speed zone.
Tons: Represents short tons (2,000 lbs) unless otherwise noted.
Tonnes: Metric tons (1,000 kg)
Two-stroke engine: Engine designed so that it completes the four processes of internalcombustion (intake, compression, power, exhaust) in only two strokes of thepiston.
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1.0 INTRODUCTIONNitrogen oxides (NOx) and sulfur dioxide (SO2) emissions associated with shipping remain asignificant component of the total NOx and SO2 inventories. The purpose of this project is toestimate commercial marine vessel (CMV) emissions within 3-nautical miles of the Texascoastline, which includes emissions generated by freight, cruise, tug, support, and researchvessels. The current near-shore commercial marine emission inventory used by TCEQ is basedon 2007 vessel movements and includes port and transit emissions supplied by the Port ofHouston Authority for the Ports of Freeport, Galveston, and Texas City. The inventory alsoincludes vessel transit activity within 9 nautical miles of the Galveston Bay port and in thewaterways surrounding the Galveston-Bolivar jetties. While near and in-port emissions havebeen previously estimated at some ports along the Texas coast, port emission inventories havea spatial scope limited to near and in-harbor activity.
High-resolution Automatic Identification System (AIS) vessel-tracking data for 2017 is used todevelop an updated near-shore emission inventory. AIS data provides 5-minute vessel position,speed, and direction information that can be cross-referenced with IHS data to obtaincharacteristics such as ship type, model year, size, design speed, and engine properties used toestimate engine loads and emission rates. The emission inventory developed in this projectsupplements the previously developed Gulf of Mexico offshore shipping inventory andenhances the spatial and temporal resolution of commercial marine vessels within TCEQ’sCAMx air quality modeling domain. Emissions are generated for a base year of 2017 andemission projection factors are developed to estimate emissions in 2016, 2023, and 2028.
The near-shore commercial emission inventory complements the previously-developed Gulf ofMexico Region (GOMR) off-shore ocean-going vessel (OGV) and lightering emission inventories(Ramboll Environ, 2015, 2017). The OGV emission inventory used 2014 AIS data to quantifyemissions at off-shore locations not accessed in 2003 EPA OGV emission estimates (EPA, 2003).Since the 2014 analysis AIS regulations have changes and many additional smaller vessels (i.e.,surveying, off-shore support, and tug vessels) are now required to carry AIS transmitters,thereby enhancing the AIS data.
The 2014 OGV lightering emissions were calculated separate from the 2014 off-shoreemissions. Lightering occurs during the import or export of cargo when a smaller tanker vesselis needed to navigate nearshore waters and into ports. Lightering volatile liquids producesvolatile organic compound (VOC) emissions when vapor is displaced during the transferprocess. If these VOC emissions are uncontrolled they can approach 20 tons per million barrelsof oil transferred, which is equivalent to more than 40 tons of VOCs per large tanker lightered.Additionally, most tankers use steam-driven pumps to off-load liquids. Providing steam to thepumps requires an increased boiler load (approaching 3,000 kW) and results in higher boilerVOC, NOx, and particulate matter emissions during the lightering period. In 2017, Ramboll
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Environ performed a detailed review of lightering operations and used the 2014 AIS records todevelop an inventory of lightering emissions for the TCEQ (Ramboll Environ, 2017).
The OGV and lightering emission inventories focus on off-shore emissions in the GOMR and thisstudy provides highly-resolved spatial and temporal emissions for commercial marine vesselswithin 3-nautical miles of the Texas coastline. When considered together, the OGV, lightering,and near-shore commercial marine vessel inventories provide updated vessel activity andimproved spatial resolution of vessel emissions throughout TCEQ’s CAMx air quality modelingdomain. Accurate emissions estimates for marine vessels are critical to understanding airquality for coastal urban areas in Texas, especially for sensitive regions such as the Houston-Galveston-Brazoria (HGB) nonattainment area.
Figure 1-1 shows the domain for which Automatic Identification System (AIS) data wasobtained. Commercial marine vessel emissions estimates are provided for the region within 3-nautical miles (nm) of the Texas coast.
Figure 1-1. Domain for the Emission Inventory
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1.1 PurposeThis study was designed to estimate commercial marine vessel (CMV) emissions within 3 nm ofthe Texas coastline using AIS data to produce modeling input files and inventories. Near-shoreemissions are formatted for input to the Emission Processing System (EPS3) and complementthe previously developed off-shore OGV and lightering emission inventories (Ramboll Environ,2015; Ramboll Environ, 2017).1 Near-shore CMV emissions are back-cast to 2016 and forecastto 2023 and 2028.
2.0 METHODOLOGYRamboll obtained 5-minute resolution AIS ship position records for 2017 from the U.S. CoastGuard (USCG). These records include International Maritime Organization (IMO) and MaritimeMobile Service Identity (MMSI) vessel identification numbers, speed, vessel heading, navigationstatus, and ship type information. We use AIS data to quantify the activity of vessels within 3nm of the Texas shoreline and process data using the Python programming language. Initialprocessing cleaned the data to rectify ship naming schemes, selected only records within 3 nmof shore, and identified contiguous voyages by individual vessels. Vessel emissions depend oncharacteristics such as vessel type, propulsion engine power, engine stroke type, gross tonnage,engine speed, cruise speed, and build date. These characteristics are obtained by cross-referencing the AIS data’s MMSI and IMO numbers with Fairplay vessel registry data. Together,these data provide sufficient information to estimate CMV emissions within nm of the Texascoast.
The data analysis includes preprocessing, voyage determinations, activity calculations, andemission calculations. Each of these steps is discussed in the following subsections.
2.1 Data PreprocessingThe AIS data produced by the USCG includes approximately 117 million records of vesselmovements during 2017 within the full domain (Figure 1-1) and 93 million within 3 nm of shore.Initially, the AIS data was assessed for completeness of vessel IDs (IMO, MMSI, and Call Sign),spatially filtered to the 3-nm constraint, separated into distinct voyages (i.e., distinct vesseltrips), and cross-referenced with the Fairplay registry data to obtain additional vesselcharacteristics.
2.1.1 Voyage DeterminationIndividual vessel voyages across the domain were established to enable the ability todistinguish unique vessel trips when the same vessel arrives and departs multiple times within ayear. Here, a voyage is defined as an individual vessel’s contiguous set of points traversing the
1 TCEQ Air Quality Research and Contract Reportshttps://www.tceq.texas.gov/airquality/airmod/project/pj_report_ei.html
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domain (i.e., a voyage will not exit and reenter the domain). This definition of a voyagegenerally allows for the classification of distinct inbound and outbound movements.
Initially, the AIS data was sorted so each of the vessel movements are ordered by date andtime. The criteria for determining a new voyage are presented below:
1. If the timespan between two records with the same vessel identification number is greaterthan 8 hours, a new voyage is defined.
2. If a record has a different vessel identification number than the previous record, a newvoyage is defined.
After voyages are established, the remaining AIS data records beyond the 3 nm boundary wereexcluded. Additionally, any voyage with less than 10 records (generally corresponding to lessthan 1 hour) were dropped and assumed incomplete. After these exclusions, approximately100,000 voyages remained.
2.1.2 Segment AnalysisStatistics were performed to determine the average, maximum, and minimum distancesbetween each sequential record in each voyage. The typical distance between points was usedto determine whether segment midpoints could be used represent segment emissions for a 1-kilometer grid. The 2017 records had an average segment distance of 0.8 kilometers whichsuggested that the use of segment midpoints could be viable. However, additional review of thesegments revealed that some segments either contained erroneous points or representedvoyages that exited and reentered the 3-nm zone within the 8-hour voyage criteria – resultingin a long segment. The erroneous points and those identified as visiting multiple Texas portswere cleaned from the AIS records and the remaining segment midpoints were used to spatiallyrepresent the modeled emissions.
2.1.3 Ocean-Going Vessel and Harbor Craft SeparationAfter the segment analysis, the AIS data were divided into OGVs and harbor craft using thepairing of vessel IDs with ship characterization data in the IHS database. This separation ofvessel classifications was necessary because the methodologies used to calculate emissionsfrom OGVs and harbor craft differ.
2.1.4 Activity AnalysisThe activity, in kilowatt-hours, is determined for each segment and paired with emission factorsto calculate emissions. The segment transiting time duration was calculated using thedifference in time stamps between sequential records for a voyage. Engine energy wascalculated for the propulsion engines, auxiliary engines, and boilers using load (in kW)multiplied by the time for each sequence. Details of how energy was calculated are provided inthe following subsections.
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2.1.5 Berthing TreatmentWhen the vessel speed is less than 1 knot, the vessel is assumed to be at berth or anchorage.Given the proximity to the coast, no distinction is made between berthing and anchoringactivity in the modeling domain.
2.2 Ocean-Going Vessels Emissions Approach
2.2.1 Propulsion EnginesThe propulsion engine activity considers the total main engine power and load factor. The mainengine power is reported for nearly all ocean-going vessels by the Fairplay registry data. Wheregaps in engine power exist, the EPA’s Current Methodologies in Preparing Mobile Source Port-Related Emission Inventories (EPA CMEI, 2009) provides estimates by vessel type, as shown inTable 1.
Table 1. EPA Ocean-Going Vessel Default Propulsion and Auxiliary Engine Power
Ship Type
AveragePropulsion
Engine (kW)
Average Auxiliary EnginesEngineSpeed
Auxiliary toPropulsion
RatioNumberPower Each(kW)
Total Power(kW)
Auto Carrier 10,700 2.9 983 2,850 Medium 0.266Bulk Carrier 8,000 2.9 612 1,776 Medium 0.222Container Ship 30,900 3.6 1,889 6,800 Medium 0.220Cruise Ship 39,600 4.7 2,340 11,000 Medium 0.278General Cargo 9,300 2.9 612 1,776 Medium 0.191RORO 11,000 2.9 983 2,850 Medium 0.259Reefer 9,600 4 975 3,900 Medium 0.406Tanker 9,400 2.7 735 1,985 Medium 0.211
The load factor associated with these engines was calculated using the Propeller Law:
=
The actual speed was provided within the AIS data and cruise, or service, speed is reported inthe IHS Fairplay registry data, which is approximated as 94% of maximum speed (EPA CMEI,2009). After back-calculating the maximum speeds for each vessel, the load factor wascalculated for each movement record in the AIS data. Multiplying the propulsion power by theload factor provided an initial estimate of activity. Additional adjustments due to engineinefficiency at low loads are taken into account on a per pollutant basis as discussed in section2.2.3.
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2.2.2 Auxiliary Engines and BoilersThe auxiliary and boiler power reported within Fairplay registry data is often incomplete and, insome cases, erroneous. In an effort to obtain complete power data for the AIS records, theauxiliary and boiler power can be taken, by vessel type, from the EPA CMEI shown in Table 2and Table 3. Similarly, the auxiliary engine load factors are taken from EPA CMEI defaults andwere delineated by speed bin. This study binned speeds as cruise (>= 12 knots), reduced speedzone (>= 9 knots and < 12 knots), or maneuvering (> 1 knots and < 9 knots) and associated themwith the respective loads provided in the EPA CMEI. The default boiler energy consumption ratereported within the EPA CMEI was derived from fuel use data, thus the load is determinedwithout the use of a load factor. Activity from boilers are only calculated for vessels inmaneuvering and hoteling modes because boilers are not expected to be used when thepropulsion engines are generating sufficient heat (i.e., during cruising and reduced speed zonemovements). The boiler loads are identical for hoteling and maneuvering modes except fortankers where only the maneuvering load was used, because higher hoteling boiler loads fortankers are used to supply the steam pump demand only when tankers are off-loading product,such as during lightering operations. Lightering operations occur outside of 3 nm of shore andare not included in the emission estimates developed for this work.
Table 2. Auxiliary Engines Load FactorsShip Type Cruise RSZ Maneuver HotelAuto Carrier 0.15 0.30 0.45 0.26Bulk Carrier 0.17 0.27 0.45 0.10Container Ship 0.13 0.25 0.48 0.19Cruise Ship 0.80 0.80 0.80 0.64General Cargo 0.17 0.27 0.45 0.22Miscellaneous 0.17 0.27 0.45 0.22OG Tug 0.17 0.27 0.45 0.22RORO 0.15 0.30 0.45 0.26Reefer 0.20 0.34 0.67 0.32Tanker 0.24 0.28 0.33 0.26
Table 3. Boiler Load (kW)Ship Type Cruise RSZ Maneuver HotelAuto Carrier 0 0 371 371Bulk Carrier 0 0 109 109Container Ship 0 0 506 506Cruise Ship 0 0 1,000 1,000General Cargo 0 0 106 106Miscellaneous 0 0 371 371OG Tug 0 0 0 0RORO 0 0 109 109Reefer 0 0 464 464Tanker 0 0 371 3,000Tanker – Diesel Electric 0 0 346 346
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2.2.3 Ocean-Going Vessel Emission FactorsEmissions associated with the span between sequential records of a voyage were determinedusing the activity calculated in the previous section in conjunction with emission factors withunits of grams per kilowatt-hour. The appropriate emission factors were selected based on theengine speed, fuel, fuel sulfur content (0.1% in 2014), and propulsion engine load. The pre-controlled engine emission factors are presented in Table 4. These emission factors includeadjustments to particulate emissions associated with changes in fuel sulfur, but do not accountfor the nitrogen oxides changes due to fleet turnover. The emission rates for this analysisincluded adjustments to fleet turn over by using the EPA Emission Control Area propulsion andauxiliary adjustment factors for the year 2017.
Table 4. Pre-controlled Engine Emission Rates (g/kW-hr)
Engine TypeFuelType
FuelSulfur NOx PM10 PM2.5 HC CO SOx CO2 BSFC
Slow SpeedDiesel
RO 2.70% 18.1 1.42 1.31 0.6 1.4 10.29 620.62 195MDO 1.00% 17.0 0.45 0.42 0.6 1.4 3.62 588.79 185MGO 0.50% 17.0 0.31 0.28 0.6 1.4 1.81 588.79 185MGO 0.10% 17.0 0.19 0.17 0.6 1.4 0.36 588.79 185
Medium SpeedDiesel
RO 2.70% 14.0 1.43 1.32 0.5 1.1 11.24 677.91 213MDO 1.00% 13.2 0.47 0.43 0.5 1.1 3.97 646.08 203MGO 0.50% 13.2 0.31 0.29 0.5 1.1 1.98 646.08 203MGO 0.10% 13.2 0.19 0.17 0.5 1.1 0.4 646.08 203
Gas Turbine
RO 2.70% 6.1 1.47 1.35 0.1 0.2 16.1 970.71 305MDO 1.00% 5.7 0.58 0.53 0.1 0.2 5.67 922.97 290MGO 0.50% 5.7 0.35 0.32 0.1 0.2 2.83 922.97 290MGO 0.10% 5.7 0.17 0.15 0.1 0.2 0.57 922.97 290
Steam Turbine,& Auxiliary Boiler
RO 2.70% 2.1 1.47 1.35 0.1 0.2 16.1 970.71 305MDO 1.00% 2.0 0.58 0.53 0.1 0.2 5.67 922.97 290MGO 0.50% 2.0 0.35 0.32 0.1 0.2 2.83 922.97 290MGO 0.10% 2.0 0.17 0.15 0.1 0.2 0.57 922.97 290
Auxiliary
RO 2.70% 14.7 1.44 1.32 0.4 1.1 11.98 722.54 227MDO 1.00% 13.9 0.49 0.45 0.4 1.1 4.24 690.71 217MGO 0.50% 13.9 0.32 0.29 0.4 1.1 2.12 690.71 217MGO 0.10% 13.9 0.18 0.17 0.4 1.1 0.42 690.71 217
The engine speed, in revolutions per minute, was largely provided by the IHS Fairplay registrydata. Records were defined as slow (<130 RPM), medium (130 - 1,400 RPM), or high (>1,400RPM) based on the reported engine speed. Gaps in the IHS Fairplay registry were filled bychecking the engine stroke type. For IHS Fairplay data reporting 2-stroke engines, slow speedwas assumed and if reporting 4-stroke, medium speed was assumed. While 4-stroke enginescould be medium or high, medium was selected since it is much more prevalent in OGVs’propulsion engines. For the remaining records lacking either engine speed or stroke type within
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the IHS Fairplay registry, the engine speeds were filled using the most frequent engine speedwithin the populated records (counted by engine speed by voyage, not by record).
When a load factor is calculated to be below 20%, OGV engine efficiency worsens and emissionrates are adjusted upwards. To account for this worsening efficiency, low load multiplicativeadjustment factors were applied to records with such loads. These factors are shown in Table 5.
Table 5. Low-Load Emission Factor Adjustments (EPA CMEI, 2009)Load NOx HC CO PM SO2 CO2
1% 11.47 59.28 19.32 19.17 5.99 5.822% 4.63 21.18 9.68 7.29 3.36 3.283% 2.92 11.68 6.46 4.33 2.49 2.444% 2.21 7.71 4.86 3.09 2.05 2.015% 1.83 5.61 3.89 2.44 1.79 1.766% 1.60 4.35 3.25 2.04 1.61 1.597% 1.45 3.52 2.79 1.79 1.49 1.478% 1.35 2.95 2.45 1.61 1.39 1.389% 1.27 2.52 2.18 1.48 1.32 1.3110% 1.22 2.20 1.96 1.38 1.26 1.2511% 1.17 1.96 1.79 1.30 1.21 1.2112% 1.14 1.76 1.64 1.24 1.18 1.1713% 1.11 1.60 1.52 1.19 1.14 1.1414% 1.08 1.47 1.41 1.15 1.11 1.1115% 1.06 1.36 1.32 1.11 1.09 1.0816% 1.05 1.26 1.24 1.08 1.07 1.0617% 1.03 1.18 1.17 1.06 1.05 1.0418% 1.02 1.11 1.11 1.04 1.03 1.0319% 1.01 1.05 1.05 1.02 1.01 1.0120% 1 1 1 1 1 1
2.3 Harbor Craft Emissions ApproachEmissions from harbor craft were determined following the Streamlined/Alternative Approachfrom EPA’s CMEI. Because only 14% of the harbor craft records in the AIS database could bematched to the IHS Fairplay registry data, vessel characteristics were determined based on EPAaverage engine parameters, as shown in Table 6.
Table 6. EPA Default Harbor Craft Propulsion and Auxiliary Engine Power (EPA CMEI, 2009)
Vessel Category
Main Engines Auxiliary EnginesNumber of
Engines(per Vessel)
EnginePower(kW)
AnnualOperating
Hours
ModelYear
Number ofEngines
(per Vessel)
EnginePower(kW)
AnnualOperating
Hours
AverageModelYear
Commercial Fishing 1.9 368.7 114 1984 1.0 55.2 52 1984Crew and Supply 2.2 301.6 725 1987 1.1 76.1 628 1987Ferry-Excursion 1.9 857.5 1693 1997 1.2 81.9 1467 1994
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Pilot 2.0 820.3 2675 2000 2.0 35.0 1000 2000Work Boat 1.8 275.9 329 1989 0.6 55.7 368 1986Assist Tug 2.0 1540.1 1861 1994 1.9 100.2 2184 1994Harbor Tug 1.9 711.4 1130 1990 1.5 55.7 982 1990Ocean Tug 2.0 1399.4 350 1986 2.0 95.2 350 1987
The load factor associated with harbor craft engines is determined by vessel category based onload factors from EPA’s CMEI, as shown in Table 7. The propeller law does not adequatelycharacterize harbor craft engine loads because these vessels may be towing or conductingother operations that produced load that is not directly related to speed.
Table 7. EPA Default Harbor Craft Propulsion and Auxiliary Engine Power (EPA CMEI, 2009)Vessel Category Load FactorAssist Tugboat 31%Dredge Tenders 69%Recreational 21%Recreational, Auxiliary 32%Crew Boat 45%Excursion 42%Ferry 42%Government 51%Ocean Tug 68%Tugboat 31%Work Boat 43%Other Categories 43%Other Auxiliaries 43%
Fuel corrections for ultra-low sulfur diesel were also applied and are shown in Table 8.
Table 8. EPA Fuel Corrections (EPA CMEI, 2009)Fuel Type NOx VOC CO SO2 PM10 N2O CH4
ULSD 1 1 1 0.005 0.86 1 1
2.3.1 Harbor Craft Emission FactorsEmissions associated with harbor craft travel were determined using the activity calculated inthe previous section in conjunction with emission factors with units of grams per kilowatt-hour.The appropriate emission factors are selected based on the engine tier from the engineemission factors presented in Table 9. Engine tiers were selected based upon the averagemodel year shown in Table 6.
Table 9. Engine Emission Rates (g/kW-hr) (EPA CMEI, 2009)
Engine Tier MinimumPower (kW) NOx PM10 VOC CO SO2 CO2 N2O CH4
Tier 0Engines
37 11 0.9 0.27 2 1.3 690 0.02 0.0975 10 0.4 0.27 1.7 1.3 690 0.02 0.09
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Engine Tier MinimumPower (kW) NOx PM10 VOC CO SO2 CO2 N2O CH4
130 10 0.4 0.27 1.5 1.3 690 0.02 0.09225 10 0.3 0.27 1.5 1.3 690 0.02 0.09450 10 0.3 0.27 1.5 1.3 690 0.02 0.09560 10 0.3 0.27 1.5 1.3 690 0.02 0.09
1,000 13 0.3 0.27 2.5 1.3 690 0.02 0.09Cat 2 13.2 0.72 0.5 1.1 1.3 690 0.02 0.09
Tier 1Engines
37 9.8 0.9 0.27 2 1.3 690 0.02 0.0975 9.8 0.4 0.27 1.7 1.3 690 0.02 0.09
130 9.8 0.4 0.27 1.5 1.3 690 0.02 0.09225 9.8 0.3 0.27 1.5 1.3 690 0.02 0.09450 9.8 0.3 0.27 1.5 1.3 690 0.02 0.09560 9.8 0.3 0.27 1.5 1.3 690 0.02 0.09
1,000 9.8 0.3 0.27 2.5 1.3 690 0.02 0.09Cat 2 9.8 0.72 0.5 1.1 1.3 690 0.02 0.09
Tier 2Engines
37 6.8 0.4 0.27 5 1.3 690 0.02 0.0975 6.8 0.3 0.27 5 1.3 690 0.02 0.09
130 6.8 0.3 0.27 5 1.3 690 0.02 0.09225 6.8 0.3 0.27 5 1.3 690 0.02 0.09450 6.8 0.3 0.27 5 1.3 690 0.02 0.09560 6.8 0.3 0.27 5 1.3 690 0.02 0.09
1,000 6.8 0.3 0.27 5 1.3 690 0.02 0.09Cat 2 6.8 0.72 0.5 5 1.3 690 0.02 0.09
For both ocean-going vessels and harbor craft, the emissions spanning from one point to thenext within a voyage were estimated by multiplying the record-specific activity data andemission factor. The resulting emissions segments for each voyage, by vessel type, wereaggregated into a 1-kilometer grid overlaying the TCEQ domain to get total emissions by gridcell.
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3.0 RESULTS
3.1 Vessel ActivityThe AIS data was initially analyzed to assess each vessel’s movement activity within the domain,based upon the criteria discussed in section 2.1. AIS data was further split into two categories,OGV and harbor craft, to allow for two distinct emission calculation methods.
Figure 3-1 and Figure 3-2 show the distribution of unique EPA vessel types in the OGV andharborcraft datasets. The fraction of each unique vessel type compared to total number ofunique vessel counts in each dataset is presented. Harborcraft records with no indication ofvessel type are assigned to the tugboat category.
Figure 3-1. Fractional Counts of Unique Vessel Types in OGV Dataset
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Figure 3-2. Fractional Counts of Unique Vessel Types in Harborcraft Dataset
3.2 Vessel EmissionsFollowing the methodology described in sections 2.2 through 2.3, emissions were calculatedbetween each vessel’s sequential records within the 3 nm of the Texas coast. The domain-wideemission totals are provided in Table 10 for OGVs and Table 11 for harbor craft. Table 12presents the sum of OGV and harbor craft emissions within 3 nm of the Texas Coast. Emissionswere formatted for use with the photochemical modeling system used by the TCEQ. The TCEQconducts ozone modeling using the Comprehensive Air Quality Model with extensions (CAMx2)and prepares emission inventories for CAMx using the Emissions Processor System v3 (EPS33).
EPS3 has a data input module for shipping emissions (PRESHP) that allows emissions to belocated in shipping lanes (i.e., a link connecting two points that has non-zero width) or asgridded points. Formatting emissions in PRESHP provides flexibility because emissions can be
2 http://www.camx.com/3 ftp://amdaftp.tceq.texas.gov/pub/HGB8H2/ei/EPS3_manual/EPS3UG_UserGuide_200908.pdf
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gridded to any CAMx domain, plume rise (i.e., model layer distributions) and temporaldistribution factors can be applied.
Table 10. 2017 OGV Emissions within 3 nm of Texas Coast
Vessel TypeDomain-wide 2017 Emissions (tons/day)
NOx HC CO PM10 PM2.5 SO2 CO2
Bulk Carrier 1.96 0.10 0.23 0.04 0.04 0.09 150.94Container Ship 2.85 0.17 0.37 0.06 0.05 0.13 210.54Cruise Ship 1.50 0.07 0.18 0.03 0.03 0.07 121.87General Cargo 0.62 0.03 0.08 0.01 0.01 0.03 41.56Miscellaneous 0.10 0.00 0.01 0.00 0.00 0.00 8.07OG Tug 22.84 1.14 2.55 0.95 0.85 2.89 4,686.70Reefer 1.29 0.05 0.14 0.03 0.03 0.09 148.88RORO 0.09 0.00 0.01 0.00 0.00 0.00 6.00Tanker 1.41 0.06 0.16 0.03 0.03 0.06 103.44Total 32.7 1.6 3.7 1.2 1.0 3.4 5,478.0
Table 11. 2017 Harbor Craft Emissions within 3 nm of Texas Coast
Vessel TypeDomain-wide 2017 Emissions (tons/day)
NOx HC CO PM10 PM2.5 SO2 CO2
Assist Tugboat 0.11 0.00 0.01 0.00 0.00 0.00 6.17Crew Boat 0.36 0.01 0.05 0.01 0.01 0.00 24.67Dredge Tenders 15.04 0.54 1.25 0.71 0.68 0.01 786.11Ferry 1.42 0.03 0.26 0.03 0.03 0.00 78.77Ocean Tug 6.12 0.21 0.57 0.28 0.27 0.00 334.34Tugboat 24.56 0.51 4.61 0.56 0.55 0.01 1385.18Total 0.23 0.01 0.04 0.01 0.01 0.00 15.90
Table 12. 2017 OGV + Harbor Craft Emissions within 3 nm of Texas Coast
Vessel TypeDomain-wide 2017 Emissions (tons/year)
NOx HC CO PM10 PM2.5 SO2 CO2
OGV 11,918 602 1,361 423 380 1,231 1,999,468Harbor Craft 17,461 480 2,480 583 565 9 960,368Total 29,379 1,082 3,841 1,006 946 1,240 2,959,836
The individual link-level emissions were allocated by vessel type to a 1-kilometer resolution gridacross the near-shore domain. Examples of emissions with Galveston Bay are provided in Figure4. The emissions derived from this work were produced in EPS-ready format as a part of thedeliverable to TCEQ.
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Figure 3-3. Gridded Emissions of Harbor Craft Transiting NOx
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4.0 FORECASTSMarine emission forecasts are often based on the predicted change in vessel activity andexpected emission reductions due to scheduled changes in policy. Vessel activity can beapproximated using broad economic growth estimates (e.g., gross state product) and can berefined to ship-type detail by assessing the trends of the associated commodities which the shiptypes serve. Here, we assessed how the tonnage of cargo moved by ship-type varied from 2012to 2016 to understand how each commodity was trending. These trends were contrastedagainst the gross state product (GSP) and were used to inform future year activity estimates.
Additionally, policy implications on emission rates were assessed for engine NOx controls andfuel sulfur limits. The resulting activity forecast and emission rates for 2016, 2023, and 2028were compiled as scaling values for use with the AIS-derived 2017 gridded emissions.
4.1 Economic TrendsThe broad economic growth trends and, importantly, forecasts were taken from the Texas GSPestimates, shown in Table 13. The GSP relative to 2017 provides one mechanism for forecastingfrom the AIS-derived 2017 emissions to future years.
Table 13. Gross State Product (Billion 2009$)4
Estimate GSPRelativeto 2017
2016 1,499 0.972017 1,552 12018 1,606 12019 1,657 1.12020 1,707 1.12021 1,758 1.12022 1,812 1.22023 1,868 1.22024 1,922 1.22025 1,968 1.32026 2,018 1.32027 2,073 1.32028 2,132 1.4
4 https://comptroller.texas.gov/transparency/reports/forecasts/2017-18/
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To assess type-specific trends in vessel activity, tonnage data5 for the Texas ports were used tocompare yearly shipments from 2012 through 2016, as shown in Table 14.
The Texas ports are affected by world and regional trends in addition to the general businessclimate in Texas. The overall business activity growth in the past few years has been reflectedin the Port traffic. Trade disputes may also figure into the future year activity. In addition,unique factors may affect port traffic by freight type. Changes to crude oil, petroleum gases,and refined product marine shipments include domestic oil and gas production, lifting exportrestrictions on crude oil, natural gas shipping infrastructure improvements and other factors.However, one large factor affecting port business beyond overall business activity is thePanama Canal expansion.
The Panama Canal expansion, opened at the end of June 2016, will increase Gulf port trafficincrementally to the overall business climate. A TTI (2018) study6 outlines the rationale forforecasting freight trends with more ships to and from Texas ports due the Canal expansion. Asignificant upward step change is seen in the time frame from 2015 through 2017, so extendingthe trend from 2017 might overestimate the long-term growth trend out to 2028. However, thetraffic increase due to the Canal expansion will last several years as the ports’ infrastructure isimproved to handle the larger vessels, so using the freight trends only through 2017 mayunderestimate the overall movements. The ports’ infrastructure improvements includechannel deepening, berths and shipping facilities especially for petroleum gases like LNG andLPG that all take time to implement.
Table 14 shows that the recent trend of freight through Texas ports has been relatively flat withlittle growth in tonnage. The traffic through the ports has lagged the overall economic growthin Texas. However much of the freight tonnage through Texas port is liquid bulk freight that islargely affected by petroleum oil, gas, and associated products. Lower crude oil imports wereonly partially offset by increased exports7, so the demand for tanker traffic has been lower. Theoil import/export trend could stabilize, and port freight trend revert to overall business growth.The added impact of the Canal expansion is not reflected in these figures and the impact willpersist for many years. Also, unfortunately, freight trends through 2017 have yet to bepublished to begin to see these trends.
5 http://www.navigationdatacenter.us/wcsc/wcsc.htm6 TTI 2018. “The Potential Impacts of the Panama Canal Expansion on Texas Ports,” Prepared by the TexasTransportation Institute, January 2018. https://static.tti.tamu.edu/tti.tamu.edu/documents/PRC-17-78.pdf7 https://www.eia.gov/energyexplained/index.php?page=oil_imports
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Table 14. Major Texas Freight Ports (short tons) 8
Port 2012 2015 2016Beaumont 78,515,010 87,169,875 84,528,063Brownsville 5,600,977 7,779,109 7,275,272Corpus Christi 69,001,357 85,674,966 81,981,061Houston 238,185,582 240,933,410 247,981,663Freeport 22,084,551 21,132,931 19,635,949Galveston 11,618,368 10,380,588 9,880,157Port Arthur 30,618,123 35,787,331 35,198,425Port Lavaca 11,589,123 11,821,386 4,896,638Texas City 56,721,627 42,923,997 41,260,475Victoria 4,517,632 6,733,044 5,082,077Total 528,452,350 550,336,637 537,719,780Relative to 2012
1 1.041.02
0.4% CAGRGSP Relative to 2012
1 1.101.12
2.9% CAGRNote: Figures for 2017 are not due until late 2018
For an investigation into the other cargo types, the Port of Houston provided an overview ofrecent activity through a limit set of Houston facilities. The results in Figure 4-1 show thatnoncontainerized general cargo and bulk cargo fluctuates year to year but has been trendingdown for several years as containerized cargo increases. Most of the liquid bulk cargo comesthrough private terminals in Houston and are not shown in these figures.
8 http://www.aapa-ports.org/unifying/content.aspx?ItemNumber=21048 orhttps://www.iwr.usace.army.mil/About/Technical-Centers/WCSC-Waterborne-Commerce-Statistics-Center/
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Figure 4-1. Port Houston Authority Freight by Type (not including private facilities) 9
Container traffic has shown general growth trends perhaps augmented by the effects of thePanama Canal expansion. The overall growth has been strong and especially for 2017 comparedwith 2015 as the Canal expansion was opened at the end of June 2016, so the 2016 totals didnot fully reflect use of the Canal expansion. TTI (2018) reported that the Port of Houston hasseen increased traffic (ship calls) through the expanded Panama Canal, and that is reflected inthe Texas freight statistics for 2017. Because the 2017 year may not reflect full use of the Canalexpansion as infrastructure improves and carriers take advantage, we estimated that the highergrowth rate reflected in the 2012 – 2017 trend will continue through 2028. Table 15 providesthe major container port statistics between 2012 and 2017.
Table 15. Major Texas Container Ports TEU (Combined Annual Growth Rate, CAGR) 10
Port 2012 2013 2014 2015 2016 2017Houston 1,922,529 1,950,071 1,951,088 2,130,544 2,182,894 2,459,107Freeport 72,272 107,394 92,218 98,904 91,411 85,540Galveston 14,609 23,673 22,444 43,472 35,414 33,752Total 2,009,410 2,081,138 2,065,750 2,272,920 2,309,719 2,578,399TEU Relativeto 2012 1.04 1.03 1.13 1.15
1.285% CAGR
GSP Relativeto 2012 1.04 1.08 1.10 1.12
1.163% CAGR
Galveston cruise ship growth has been strong in recent years and 2018 is reported11 to alsoshow an increase over 2017 as indicated in Table 16. Part of the recent growth at Galveston is
9 http://porthouston.com/wp-content/uploads/5-Cargo-Tonnage-2017_REV.pdf10 http://www.aapa-ports.org/unifying/content.aspx?ItemNumber=2104811 https://www.portofgalveston.com/CivicAlerts.aspx?AID=73
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due to the Port of Houston abandoning its cruise ship terminal business in 2016.12 It is unlikelythat growth can continue at the 2012-2018 rate for many years, so we extended the Texas GDPgrowth for years after the expected 2018 increase.
Table 16. Texas Cruise Passenger Ship Activity13
Port 2013 2014 2015 2016 2017 Thru June2018
Houston 26,904 110,643 125,856 83,810 0 0Galveston 1,208,802 1,285,884 1,658,070 1,730,289 1,861,549 +18%Total 1,235,706 1,396,527 1,783,926 1,814,099 1,861,549 +18%Relative to2013 1.13 1.44 1.47 1.51
1.7812% CAGR
CALLSHouston 9 38 44 45 0Galveston 179 181 232 235 255Total 188 219 276 280 255 +18%Relative to2013 1.16 1.47 1.49 1.36
1.6010% CAGR
Crude oil import and exports have been relatively constant from 2016 to 2017, and we expectthe relative balance of imports and exports to continue. Crude shipping growth is notforecasted as exports and imports both occurred in 2017. Should there be any change indomestic oil production occur, we expect that import and export ship traffic increases anddecreases would offset.
For other tankers including LNG/LPG, we used the GSP trend. TTI (2018) estimated that thePanama Canal expansion will have a marked effect increasing LNG marine shipments becausethose ships required the expansion to be able to use the Canal, however, LNG portinfrastructure will take time to build out to accommodate those ships. For other oil products,we would expect the overall business climate to be the controlling factor. It is possible that gasshipments will be higher, and liquid bulk shipments lower than the prevailing GSP trend.Other cargo includes bulk, break bulk, general cargo, vehicle carriers, and other ships wereestimated to also follow the overall business climate. Bulk and general cargo may not grow atthis same rate because it has not recently at the Port of Houston, but most other freightcategories should be affected by the business climate. In summary, Table 17 shows ourexpected activity trends by ship type.
12 https://www.houstonchronicle.com/business/article/With-cruise-ships-gone-Port-of-Houston-decides-8425454.php13 http://www.aapa-ports.org/unifying/content.aspx?ItemNumber=21048
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Table 17. Expected Relative Shipping Activity for Texas PortsShip Type 2016 2017 2023 2028Cruise 0.98 1.00 1.41 1.56Container 0.90 1.00 1.34 1.71Crude tankers 1.00 1.00 1.00 1.00Others 0.97 1.00 1.24 1.37
For harbor craft, there is no readily available information for developing vessel-type growthprojections. We anticipate that harbor craft growth will closely follow projections of the GSP.
4.2 OGV Emissions ForecastingEmissions from ship engines and boilers have been regulated by the International MaritimeOrganization (IMO)14, which has limited fuel sulfur levels and new ship engine NOx emissionrates as well as other air emissions from ships including those from incineration, tanker venting,and ozone depleting substances. IMO regulations set worldwide maximum fuel sulfur levelsand NOx emission rates, and more stringent emission standards when ships operate withinemission control areas (ECAs).
For the US waters, an ECA was declared and began implementation, with the first level of fuelsulfur limits that began in August 2012 with further control beginning in 2015:
· Late 2012 <10,000 ppm (1.0%) sulfur· 2015 <1,000 ppm
NOx emission standards for Tier I and II apply worldwide and Tier III engine NOx emission rateslimits apply when operating within an ECA. The Tier emissions standards are outlined in Table18. Applying these emission levels for current and especially future years requires estimates ofthe ship fleet age distributions.
Table 18. International NOx Emission Limits for Ship Engines
TierShip construction dateon or after
Total weighted cycle emission limit (g/kWh)n = engine’s rated speed (rpm)
n < 130 n = 130 - 1999 n ≥ 2000
I January 1, 2000 17.0 45 x n(-0.2)
e.g., 720 rpm – 12.1 9.8
II January 1, 2011 14.4 44 x n(-0.23)
e.g., 720 rpm – 9.7 7.7
III January 1, 2016 whenoperating in an ECA 3.4 9 x n(-0.2)
e.g., 720 rpm – 2.42.0
14 http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Pages/Air-Pollution.aspx
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The emission factors used for the 2017 emission inventory estimates assumed 1.0% sulfurcontent fuel and the EPA estimated emission reduction from unregulated NOx emission rates.The application or determination of the fleet age distribution is not straightforward becauseeach ship transit was used in this work and has a unique activity profile as well as a ship orengine model year. Therefore, we applied average NOx levels forecasted by EPA (2009) whenevaluating the impact of the international emission regulations and ECA designation.
The emission control scenarios used for this work are based on EPA (2009) forecasted emissionfactor adjustments shown in Table 19. The ECA includes the entire region modeled, andtherefore all activity was assumed to be governed by the ECA. The ECA was declared in EPArulemaking with international approval in 2009, and emissions and fuel controls within the ECAbegan in August 2012 with a fuel sulfur limit of 1.0%. Additional fuel sulfur limits to 0.1% sulfurbegan in 2015 and require NOx controls for new ships built in 2016 or later. Ship NOx emissionswere adjusted by the emission reductions shown in Table 20. Interpolation of the NOxreduction estimates were used to estimate emission control factors for 2016, 2023, and 2028.
Table 19. PM and NOx Scaling Factors for Pre-controlled, 1% Sulfur Emission Factors (EPA2009)
Main
2015 2015 2020 2020 2030PM EF NOx EF NOx EF NOx EF NOx EF
ECA ECA Baseline ECA ECASSD (slow speed diesel) 0.1352 0.8020 0.9037 0.5967 0.3138MSD (medium speed diesel) 0.1328 0.8020 0.8987 0.5515 0.2559ST (steam boiler) 0.1108 1 1 0.9524 0.9524GT (gas turbine) 0.1108 1 1 0.9344 0.9344AuxiliaryPass (passenger) 0.1328 0.8059 0.9025 0.5869 0.3003Other (all except passenger) 0.1550 0.8059 0.9025 0.5940 0.3039*Average estimated as 80% slow speed propulsion, 10% medium speed propulsion, and 10%auxiliary 10,000 ppm required in 2010
EPA had assumed 1.0% sulfur would be used in 2010, but the implementation of the ECA didnot begin until fall of 2012. The final implementation schedule required 1,000 ppm (0.1%) fuelsulfur or equivalent engine particulate matter (PM) control beginning in 2015, benefits of whichare included in the back-cast and forecast emissions.
Table 20. Emission Adjustment of NOx Emission Rates Relative to 2017Emissions Engine Type 2016 2017 2023 2028
NOx
SSD (slow speed diesel) 1.103 1 0.627 0.627MSD (medium speed diesel) 1.099 1 0.567 0.567ST (steam boiler) 1.070 1 0.952 0.952GT (gas turbine) 1.050 1 0.934 0.934Auxiliary 2016 2017 2023 2028Other (all except passenger) 1.094 1 0.618 0.618
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The results from these forecasts were developed as growth and control tables for use with EPS,providing a method to readily change modeling year scenarios in CAMx. To accomplish thecontrol cross reference, we applied the emission factor adjustments in Table 20 to the 2017emissions and activity across main and auxiliary engines and boilers to develop relativeemissions by ship type and mode (either transiting or at anchor). The relative emissions factorsby ship type and mode are shown in Table 20 and can be used as a control factor table, andTable 17 provides an activity growth table.
Table 21. 2016, 2023, and 2028 Emission Factors Relative to 2017Calendar
Year1 Ship TypeNOx Scaling Factor
Anchorage Transit
2016
Bulk Carrier 1.05 1.06Container Ship 1.06 1.06Cruise Ship 1.06 1.06General Cargo 1.05 1.06Miscellaneous 1.05 1.06OG Tug 1.06 1.07RORO 1.06 1.06Reefer 1.06 1.06Tanker 1.03 1.06
2023
Bulk Carrier 0.84 0.83Container Ship 0.83 0.83Cruise Ship 0.83 0.81General Cargo 0.84 0.81Miscellaneous 0.85 0.81OG Tug 0.82 0.80RORO 0.83 0.83Reefer 0.83 0.83Tanker 0.92 0.82
2028
Bulk Carrier 0.48 0.43Container Ship 0.45 0.43Cruise Ship 0.43 0.40General Cargo 0.46 0.41Miscellaneous 0.49 0.41OG Tug 0.42 0.38RORO 0.43 0.43Reefer 0.45 0.43Tanker 0.72 0.43
1 Calendar year scaling values are relative to emission rates calculated for the2014 emissions developed from the AIS data2 PM scaling values are applicable to both PM10 and PM2.5
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4.3 Harbor Craft Emissions ForecastingThe change in harbor craft emissions due to fleet turnover was estimated using the EPA’sRegulatory Impact Assessment (RIA; EPA, 2008) data. The RIA provides an estimate of emissionchanges for category 1 and category 2 vessels between the years 2000 and 2040 byincorporating both fleet turnover and growth. For isolating fleet turnover, we assessed thechanges in between the RIA’s controlled and uncontrolled cases for each pollutant. Using thesevalues scaling factors relative to 2017 were calculated, as shown in Table 22.
Table 22. 2016, 2023, and 2028 Harbor Craft Emission Factors Relative to 2017YEAR VOC CO NOx PM2016 1.04 1.01 1.03 1.042017 1.00 1.00 1.00 1.002023 0.78 0.95 0.82 0.842028 0.66 0.93 0.72 0.74
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5.0 CONCLUSIONS & RECOMMENDATIONSRamboll assessed the commercial marine vessel emissions within 3 nautical miles of the TexasCoast by analyzing 2017 vessel AIS records. Near-shore commercial marine vessel emissionswere developed to help improve the modeling emission inventories for model years 2016,2023, and 2028. The emissions were tabulated and produced as EPS-ready emission files.
This work demonstrated how AIS records can be used to assess detailed near-shore activitiesfor the benefit of emission inventory development. Starting in March 2016, all commerciallyactive vessels were required to install AIS transponders, including many harbor craft. Thisproject takes advantage of a new expanded data set that allows for the determination of morehighly resolved near-port and/or near-platform emission inventories.
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6.0 REFERENCESEPA 2003. “Final Regulatory Support Document: Control of Emissions from New Marine
Compression-Ignition Engines at or Above 30 Liters per Cylinder,” EPA420-R-03-004,January 2003. https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-control-emissions-new-marine-compression
EPA, 2008. “Regulatory Impact Analysis: Control of Emissions of Air Pollution from LocomotiveEngines and Marine Compression Ignition Engines Less than 30 Liters Per Cylinder”, U.S.Environmental Protection Agency, March 2008. https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-control-emissions-air-pollution-locomotive
EPA CMEI, 2009. "Current Methodologies in Preparing Mobile Source Port-Related EmissionInventories." Prepared by ICF for the U.S. Environmental Protection Agency, April 2009.https://www.epa.gov/sites/production/files/2016-06/documents/2009-port-inventory-guidance.pdf
Ramboll Environ, 2015. “Final Report Link-based Modeling Emissions Inventory of MarineVessels (Ocean Going Vessels) in Transit and at Anchor in the Gulf of Mexico”, FinalReport prepared for Texas Commission on Environmental Quality. Work Order No. 582-15-52910-03, 2015.https://www.tceq.texas.gov/assets/public/implementation/air/am/contracts/reports/ei/5821550417FY1531-20150730-environ-AIS_Vessel_Emissions.pdf
Ramboll Environ, 2017. “Final Report Ocean-Going Vessel Lightering Emissions in the Gulf ofMexico”, Final Report prepared for Texas Commission on Environmental Quality. WorkOrder No. 582-17-72097-24, 2017.https://www.tceq.texas.gov/assets/public/implementation/air/am/contracts/reports/ei/582177209724-20170630-environ-OceanGoingTankerVesselLighteringEmissionsGulfMexico.pdf
