Content uploaded by Richard Adamson
Author content
All content in this area was uploaded by Richard Adamson on Mar 07, 2017
Content may be subject to copyright.
1
Port Authority of New York and New Jersey Criteria Pollutant and Greenhouse Gas Emission Inventory –
1
Calendar Years 2006-2008 2
3
Stephen Colodner 4
Tel: (703) 813-6700, x148 5
E-mail: stephen.colodner@pechan.com 6
7
Maureen A. Mullen 8
Tel: (703) 813-6700, x160 9
E-mail: maureen.mullen@pechan.com 10
11
Manish Salhotra 12
Tel: (703) 813-6700, x173 13
E-mail: manish.salhotra@pechan.com 14
15
Jackson Schreiber 16
Tel: (703) 813-6700, x170 17
E-mail: jackson.schreiber@pechan.com 18
19
Melissa Spivey 20
Tel: (336) 638-6154 21
E-mail: melissa.spivey@pechan.com 22
23
Kirstin B. Thesing 24
Tel: (919) 493-3144, x115 25
E-mail: kirstin.thesing@pechan.com 26
27
James H. Wilson Jr. (Corresponding Author) 28
Tel: (703) 813-6700, x102 29
E-mail: jim.wilson@pechan.com 30
31
E.H. Pechan & Associates, Inc. 32
5528-B Hempstead Way 33
Springfield, VA 22151 34
35
Richard Adamson 36
Tel: (919) 282-1054 37
E-mail: adamson@southernresearch.org 38
39
Tim Hansen 40
Tel: (919) 282-1052 41
E-mail: hansen@southernresearch.org 42
43
Southern Research Institute 44
5201 International Drive 45
Durham, NC 27712 46
47
Lena M. DeSantis 48
Tel: (212) 435-5467 49
E-mail: ldesantis@panynj.gov 50
51
Rubi Rajbanshi 52
Tel: (212) 435-5466 53
rrajbanshi@panynj.gov 54
55
TRB 2011 Annual Meeting Paper revised from original submittal.
2
The Port Authority of New York & New Jersey
1
225 Park Avenue South – 12th Floor 2
New York, NY 10003 3
4
November 12, 2010 5
6
Word count (7,138) + 6 Tables and 1 Figures (1,750) = (8,888) 7
8
TRB 2011 Annual Meeting Paper revised from original submittal.
3
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
ABSTRACT
1
The Port Authority of New York and New Jersey (PANYNJ) has adopted a policy to reduce its greenhouse gas 2
(GHG) emissions by 80 percent by the year 2050. For this project, Pechan and Southern Research Institute 3
developed 2006, 2007, and 2008 calendar year GHG and criteria pollutant emission inventories for Port Authority 4
facilities and operations, including the emissions of its tenants (e.g., airlines and shippers) and patrons (e.g., airport 5
passengers, PATH riders). In addition, the consulting team developed and implemented systems that allow for 6
annual tracking and reporting of GHG emissions. 7
The PANYNJ manages and maintains the bridges, tunnels, bus terminals, airports, Port Authority Trans-8
Hudson (PATH) commuter rail system, and marine terminals that are critical to the metropolitan New York and 9
New Jersey region’s trade and transportation capabilities. Major facilities owned, managed, operated, or maintained 10
by the PANYNJ include John F. Kennedy International (JFK), Newark Liberty International, and LaGuardia 11
airports; the George Washington Bridge; the Lincoln and Holland tunnels; Port Newark and the Howland Hook 12
Marine Terminal; the Port Authority Bus Terminal; and the 16-acre World Trade Center site in Lower Manhattan. 13
This paper describes the methods used to develop consistent GHG and criteria pollutant emission estimates for a 14
diverse set of source types, and how these methods have been updated with time as new information and new 15
protocols have emerged. 16
TRB 2011 Annual Meeting Paper revised from original submittal.
4
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
BACKGROUND
1
The Port Authority of New York and New Jersey (PANYNJ) manages and maintains the bridges, tunnels, bus 2
terminals, airports, Port Authority Trans-Hudson (PATH) commuter rail system, and marine terminals that are 3
critical to the metropolitan New York and New Jersey region’s trade and transportation capabilities. Major facilities 4
owned, managed operated or maintained by the PANYNJ include John F. Kennedy International (JFK), Newark 5
Liberty International, and LaGuardia airports, the George Washington Bridge, the Lincoln and Holland tunnels, Port 6
Newark and the Howland Hook Marine Terminal, the Port Authority Bus Terminal, and the 16-acre World Trade 7
Center site in Lower Manhattan. 8
As a cornerstone in its broader sustainability program, PANYNJ has adopted a policy to reduce its 9
greenhouse gas (GHG) emissions by 80 percent, from 2006 levels, by the year 2050. To establish an initial baseline 10
required to monitor progress toward that goal, PANYNJ sponsored an effort with Southern Research Institute and 11
Pechan to conduct a GHG and criteria air pollutant (CAP) emission inventory of PANYNJ facilities for 2006. CAPs 12
are inventoried to ensure GHG reduction strategies maintain and enhance CAP reduction strategies. This effort has 13
been repeated for calendar years 2007 and 2008. 14
The following objectives were set for this emission inventory effort: (1) account for all six GHGs identified 15
by the Intergovernmental Panel on Climate Change (IPCC), (2) account for the following CAPs: oxides of nitrogen 16
(NOx), sulfur dioxide (SO2), and particulate matter (PM), (3) include direct and indirect emissions, (4) maximize 17
flexibility to prepare for future regulatory regimes, (5) ensure transparency, (6) refine the system established for the 18
calendar year 2006 to allow for ease in annual reporting, (7) adhere to the IPCC guidelines for conducting national 19
GHG emission inventories and incorporate expert techniques in the inventory of corporate emissions, as well as of 20
airports, marine terminals, and other transportation facilities. 21
22
Inventory Boundary 23
One of the first steps in developing this or any other GHG emission inventory is determining the organizational 24
boundary for reporting emissions. The organizational boundary decisions were made so that all methods for data 25
collection were applied consistently across all operations, facilities, and sources of the PANYNJ. An objective of 26
this exercise was to develop an inventory that meets the criteria for submittal to a GHG registry like The Climate 27
Registry. The Climate Registry and World Resources Institute GHG protocol have two main options for 28
determining the emissions that should be reported: management control or equity share. Under the management 29
control option, 100 percent of the emissions from operations, facilities and sources that the organization controls are 30
reported. Under the equity share option, an organization reports based on its share of financial ownership of an 31
entity, operation, or source. Management control is more appropriate than equity share for an entity like the 32
PANYNJ because it is a public organization. An important reason for choosing to report emissions based on 33
management control is that when the PANYNJ controls how an operation or a facility is managed, the organization 34
is able to control factors such as capital investment and technology choice, how energy is used, and the level of 35
emissions generated. 36
37
METHODS BY SECTOR 38
This section describes the GHG and CAP emission estimation methods for the most prominent source categories in 39
the PANYNJ inventory. While the methods section is limited to the most prominent source categories, the results 40
section includes emission estimates for all sources. 41
42
Aviation – Aircraft 43
This source category includes emissions from all civil-commercial use of airplanes, including civil and general 44
aviation. To date, aircraft emissions at PANYNJ facilities have been estimated using what is referred to in the IPCC 45
Guidelines(1) as Tier 2 methods. Operations of aircraft are broken down into landing-takeoff (LTO) and cruise 46
phases. To use the Tier 2 method, the number of LTO operations must be known for both domestic and 47
international aviation, preferably by aircraft type. In this method, a distinction is made between emissions below 48
and above 914 meters (3,000 feet). Emissions occurring above 3,000 feet (the mixing height), have been excluded 49
from the inventory. This is consistent with traditional criteria pollutant emission inventory methods. 50
The Tier 2 method breaks the aviation emission calculation into the following steps: 51
1. Estimate LTO fuel consumption for domestic and international operations. 52
2. Estimate the cruise fuel consumption for domestic and international aviation. 53
TRB 2011 Annual Meeting Paper revised from original submittal.
5
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
3. Estimate emissions from LTO and cruise phases for domestic and international aviation.
1
The IPCC guidelines for National Greenhouse Gas Inventories Table 3.6.9 “LTO Emission factors by 2
Typical Aircraft” were used as the source for the emission factors of all jet, turboprop, and propeller planes(1). 3
Table 3.6.3 : “Correspondence between Representative Aircraft and Other Aircraft Types”, from the same 4
document, lists some other aircraft designations that have the same emissions as those listing the number of arrivals 5
and departures from each airport by aircraft model for LaGuardia, JFK, Stewart, Teterboro, and Newark. The 6
aircraft models provided by the PANYNJ were matched to the models with IPCC emission factors either directly – 7
or approximately – using data taken from the Federal Aviation Administration’s (FAA’s) Emission Dispersion 8
Modeling System (EDMS). The majority of operations were directly matched with emission factors. The 9
information from EDMS was also used and provided the ability to match more of the aircraft types to engine types 10
that had emission factors. In the end, about 6 percent of the operations at the PANYNJ airports did not have aircraft 11
codes/types that matched with the IPCC emission factors, so emission factors for those aircraft were estimated using 12
the average emission factor for the aircraft at that airport. The aircraft type to engine type matching process was the 13
most time consuming part of the aircraft emission estimation method. 14
During 2009, the Airport Cooperative Research Program released a report(2) that is a guidebook for 15
preparing airport GHG emission inventories. There have been some preliminary discussions about how or whether 16
to change the PANYNJ methods according to the guidebook recommendations. 17
When the 2006 GHG/CAP emission inventory was developed for the PANYNJ, the FAA’s EDMS model 18
did not have the capability to estimate GHG emissions. Now that it does, more consideration is being given to use 19
EDMS as the primary tool for estimating GHG and CAP emissions for both aircraft and ground support equipment 20
at the airports. One of the benefits of doing so is that any resulting emission estimates can and should be able to be 21
used by the U.S. Environmental Protection Agency (EPA) in its National Emission Inventory (NEI), and the 22
emission estimates should also be consistent with the emission inventories used in relevant State Implementation 23
Plans (SIPs). 24
Planning for developing PANYNJ aviation emission estimates for calendar year 2009 and beyond is 25
considering using inventory methods that are more responsive to the initiatives being taken by the airlines at these 26
airports to reduce fuel use and associated GHG and criteria pollutant emissions. Key operational factors that are 27
important to consider include time-in-mode differences by airport and how these change with time. Default time-in-28
mode estimates are used in the IPCC emission factors. Auxiliary power units are now used to supply power to gated 29
aircraft so that aircraft engines can be turned off, but the IPCC Tier 2 emission methods do not allow this change to 30
be accounted for. In addition, it is not clear whether any specific tracking of APU use occurs at these airports. 31
One way to improve the emissions accounting at each airport is to track and report fuel sales by aircraft. 32
However, this only accounts for fuel purchased at that specific airport and ignores fuel consumed or purchased for 33
the flights prior and after PANYNJ facilities. 34
When the State of New Jersey was developing its statewide GHG emission inventory as part of its state 35
climate action planning process, it was determined that the fuel sales data for New Jersey airports overestimated 36
actual aviation fuel consumed in New Jersey, as a significant portion of the fuel purchased in New Jersey is actually 37
used for New York airports. In addition, a large portion of the flights to and from New Jersey airports are 38
international flights. Thus, the New Jersey Department of Environmental Protection felt that only a small portion of 39
New Jersey aviation fuel sales would be used on flights that New Jersey regulations could impact. Newark airport is 40
the largest New Jersey airport. 41
42
Aviation – Ground Support Equipment (GSE) 43
For the GSE at PANYNJ airports, the calendar year 2006 and 2007 emissions were estimated by performing a 44
survey of fuel sales by the major airlines and other identified fuel suppliers at each airport. This survey was not able 45
to be performed for calendar year 2008, so the GSE fuel consumption in that year was estimated using the 2007 46
survey-based estimates multiplied by the ratio of 2008 LTOS to 2007 LTOs at each airport. Once the GSE estimates 47
of gasoline, propane and diesel consumed were developed for each airport, GHG emissions were estimated using the 48
emission factors from the IPCC Guidelines, Volume 2, Tables 3.3.1 for these fuels. 49
Because the results of the fuel survey each year had some incomplete reporting, some gap filling was 50
needed to develop complete emission estimates for this source type. EPA’s NONROAD model was used as a 51
supplementary emissions and activity data source as well for GSE. NONROAD provided an additional data point 52
that was used either as a quality control check on the fuel survey-based results, or as an alternative data source for 53
TRB 2011 Annual Meeting Paper revised from original submittal.
6
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
estimating GHG emissions by airport. For Stewart airport, because no fuel survey data were available for calendar
1
years 2007 or 2008, the EPA NONROAD model was used to estimate airport GSE emissions for Orange County, 2
New York (where Stewart airport is located) and because Stewart is the only commercial airport in that county, all 3
of the county emissions were associated with that airport. 4
Because the EDMS model can provide estimates of criteria pollutant emissions for airport GSE, a 5
comparison was made of the criteria pollutant emission estimates from EDMS for 2006 with those estimated by 6
NONROAD. GSE emissions are modeled within EDMS using EPA NONROAD model emission factors. The 7
differences in emission estimates between the two models were generally more pronounced for GSE than for 8
aircraft. While there were some cases where EDMS CAP emissions were lower for an airport compared with the 9
NONROAD model-based estimates, there were more cases where EDMS estimates were higher. For example, the 10
NONROAD model showed very little GSE activity for Bergen County, which contains Teterboro airport, while 11
EDMS estimated higher emissions using its default assignments. Since both models use the same emission factors, 12
emission differences are attributable to how the models simulate equipment populations and activity. For the larger 13
airports, the error potential in the criteria pollutant estimates is in the range of 11 to 66 percent based on the EDMS 14
versus NONROAD analysis. EPA’s NONROAD model is an attractive option for estimating GHG and CAP 15
emissions because it has the capability to estimate carbon dioxide (CO2) and CAP emissions. While methane and 16
nitrous oxide (N2O) emissions cannot be estimated using NONROAD, emission factors for these pollutants are 17
readily available from other sources, plus the GHG emissions from these two gases are much lower than those of 18
CO2 for combustion sources. 19
20
Aviation – Attracted Travel 21
Emissions associated with vehicle trips that are attracted by the airports were computed for all of the calendar years 22
of the inventory that have been developed to date. Vehicle types and trip types captured in this analysis include 23
privately-owned vehicles, taxis, buses, rental cars, limousines, vans, shuttle buses, public buses, and light- and 24
heavy-duty goods vehicles. The GHG and CAP emission estimates for all of these vehicle trips were estimated 25
using the round trip distances to and from the airport. In estimating vehicle miles traveled (VMT), trip origin, travel 26
distance, trip distributions, and transport mode were utilized. The VMT for limousines, private cars, chartered 27
buses, hotel/motel shuttles, off-airport parking shuttles, and vans was estimated using the number of passengers 28
arriving at each via that mode at each airport as a surrogate. 29
VMT for rental cars servicing JFK, LaGuardia, Newark, and Stewart airports was estimated based on the 30
total number of rental vehicle transactions during 2008. The number of vehicle transactions for these facilities was 31
allocated by trip origin based on the percentage of airport passengers by trip origin. Air cargo truck movements 32
were estimated using a truck movement study that was performed for JFK(3). 33
34
Port Commerce – Commercial Marine Vessels (CMVs) 35
The Port Commerce Department of the PANYNJ includes commercial marine vessel (CMV) travel, docking and 36
berthing, cargo handling equipment (CHE) at the Port of New York and New Jersey (Port), travel to and from the 37
Port by trucks and rail locomotives, and buildings. The beginning methods for estimating GHG and criteria 38
pollutant emissions for CMVs and CHE relied on the information collected during 2000 as part of a study(4) that 39
provided SIP emission inventories for these sources to EPA and the States of New Jersey and New York. However, 40
as this study has evolved, the PANYNJ has sponsored efforts to have combined GHG and CAP emission estimates 41
developed for calendar year 2006(5) that have been projected to 2007 and 2008 using activity data surrogates. 42
Truck emission estimates have been developed from a special study of port attracted travel. Rail locomotive 43
emission estimates are based on recent activity estimates. The PANYNJ owns/operates relatively few buildings at 44
the Port, and the GHG emissions estimates are based on electricity and natural usage in those facilities. 45
The boundary selected for estimating CMV emissions corresponds to the New York-Northern New Jersey-46
Long Island ozone nonattainment area boundary, and includes all facilities that are under PANYNJ management 47
control. Emissions out to the three mile demarcation line off the eastern coast of the United States are included in 48
this boundary. Emissions from vessels calling on facilities that are not under the management control of the 49
PANYNJ are not included in this emission inventory. 50
The following Port facilities are included: (1) Auto Marine Terminal, (2) Port Newark, (3) Elizabeth 51
Marine Terminal, (4) Brooklyn/Red Hook Container Terminal, and (5) Howland Hook Terminal. 52
TRB 2011 Annual Meeting Paper revised from original submittal.
7
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
CMVs are classified into three major categories: ocean going vessels, towboats and harbor vessels. The
1
ocean-going vessel category includes the following ship types: containerships, car carriers/roll-on/roll-off vessels, 2
cruise ships, tankers and bulk carriers. The key harbor vessel sub-categories include assist tugs, dredging vessels, 3
ferry-excursion vessels, and government vessels. Of these, only assist tugs and dredging vessels were deemed to be 4
under the management control of the PANYNJ. 5
There are three major CMV emission sources: (1) the main engines, (2) auxiliary engines, and (3) and 6
boilers. Each CMV type has emissions from one or more of these source types. For all vessel activity except 7
dredging, activity information by vessel type was developed from a special study of Port activity that was sponsored 8
by the PANYNJ for calendar year 2000. This study was updated recently to provide a best estimate of calendar year 9
2006 activity and GHG/CAP emissions. Estimates of 2007 and 2008 CMV emissions use annual port-wide ship call 10
data from the PANYNJ compared with 2006 activity in order to estimate how emissions have changed during that 11
period. 12
Dredging activity data for each calendar year reflect volumes dredged from the PANYNJ/U.S. Army Corps 13
of Engineers Joint Harbor Deepening Project, as well as dredging from Port berths. All of this dredging activity is 14
considered to be within the PANYNJ’s boundary. Emission factors for dredging were derived from CAP emission 15
factors developed by Starcrest for the engines used on dredging vessels. GHG emission factors for CO2, methane 16
(CH4) and N2O were developed from relationships between GHG and criteria pollutant emission rates for similar 17
engine types. There have been significant year-to-year variations in dredging activity in the New York City Harbor. 18
The bottom-up activity estimates developed for CMVs are too time-consuming and expensive to be used to 19
develop emission estimates every year, so surrogate activity indicators are applied in this study to develop estimates 20
for intermediate years. Using fuels sales to estimate CMV emissions was considered, but only a fraction of the 21
ocean-going vessels in the New York City port purchase fuel in the port terminals themselves. Fuel is purchased in 22
other nearby ports and from barges located in or around the port. Other studies in the New York City area have tried 23
to use statewide fuel sales allocated to counties to estimate CMV fuel use, but these studies have produced emission 24
estimates that differ widely from the bottom-up estimates, and are extremely uncertain. 25
26
Port Commerce – Cargo Handling Equipment (CHE) 27
Another important emissions source at New York City Port terminals are the engines used in CHE. The 28
predominant types of equipment used at container terminals include: terminal tractors, straddle carriers, forklifts and 29
top loaders. In addition, several other types of off-road equipment are used at these terminals, including cranes. 30
Estimates of 2006 GHG and CAP container terminal CHE emissions were prepared by Starcrest for the Port 31
District(5). The 2006 CAP emissions were estimated using EPA’s NONROAD model. Activity data collected for 32
the Port District study were used in NONROAD instead of the default inputs. As noted earlier, NONROAD does 33
not address methane and N2O emissions, so emission factors from EPA’s national GHG inventory were used for 34
these pollutants. The change in the number of loaded and empty total energy use handled in the port between 2006 35
and 2008 was used as the surrogate indicator to estimate 2008 activity. The 2007 and 2008 GHG and CAP 36
emissions were estimated by applied the total energy use ratios for 2007 and 2008 versus 2006 to the 2006 calendar 37
year emission estimates. 38
39
Port Commerce – Rail 40
Emissions for Port Commerce were also estimated for the switcher locomotives that operate within the terminals as 41
well as the line haul locomotives that serve these ports. Line haul locomotive emissions were included for the travel 42
that occurred within the boundaries of the New York City ozone nonattainment area. Calendar year 2006 emissions 43
for switcher and line haul locomotives were estimated by Starcrest for the Port District. The number of containers 44
handled at Port terminals during 2007 and 2008 was used as a surrogate for estimating how these locomotive 45
emissions would be expected to change from 2006 to 2008. 46
47
Port Commerce – Heavy-Duty Vehicles (HDVs) 48
HDVs (trucks) also service the Port, so emissions were estimated for truck idling within the marine terminal areas, 49
truck travel within the marine terminal areas, and truck trips to and from the terminal areas to deliver or pick-up 50
containers. Activity estimates for each truck travel activity type were multiplied by GHG and CAP emission factors 51
to estimate emissions for this source type. HDV idling activity was expressed as the number of idling hours – and 52
this was estimated by multiplying the number of trucks entering the terminals in 2008 by an estimate of the average 53
TRB 2011 Annual Meeting Paper revised from original submittal.
8
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
amount of time spent idling at the terminal per trip. The activity indicator used for HDV travel within the terminal
1
area was VMT within the terminal area, which was calculated by multiplying the 2008 annual one-way gate count 2
by an estimate of the average VMT per terminal trip. The activity used for truck travel to and from these terminals 3
was the round trip mileage times the number of trucks making a trip of each trip length. A Vollmer terminal 4
study(6) report provided estimates of average trip length. This report summarizes the distribution of truck origins 5
and destinations by terminal. GHG emission factors for trucks were obtained from EPA’s national GHG Inventory 6
report. CAP emission factors for heavy-duty trucks were developed using EPA’s MOBILE6 emission factor model. 7
8
Port Commerce – Landfill 9
There is a landfill in Elizabeth, New Jersey that is on property that is leased by a tenant, but the PANYNJ included 10
an estimate of the methane emissions from this landfill in its inventory, although there is some uncertainty in the 11
protocols about which organization is really responsible for these emissions. EPA’s LandGEM model was used to 12
estimate the amount of landfill gas produced and the resultant annual emissions of methane from the landfill gas. 13
LandGEM is based on the gas generated from anaerobic decomposition of landfilled waste, which has a methane 14
content between 40 and 60 percent. The annual waste emplacement estimate was input to LandGEM for each year 15
of operation. Because there was no detailed and accurate data available on the yearly waste deposits and the 16
composition of waste deposited each year in the landfill, the LandGEM was used instead of the IPCC-based waste 17
model. 18
19
Tunnels, Bridges, and Terminals 20
The PANYNJ’s Tunnels, Bridges and Terminals Department operates four bridges and two tunnels in the New York 21
Metro area. Emission estimates for the vehicle travel across and through these facilities were included in the 22
GHG/CAP emission inventory. Queuing emissions at these facilities were also included in the emission inventory. 23
The boundaries established for measuring these emissions were the bridge span roadway lengths and the average 24
tunnel lengths. Activity data for the analysis were developed based on the annual reported traffic volumes and 25
facility roadway lengths. VMT was estimated by multiplying annual traffic volumes for each vehicle category by the 26
roadway length. Vehicle types in the annual traffic counts included autos, buses, small trucks and large trucks. The 27
CH4 and N2O emission factors by vehicle type used in the GHG emission estimates are from EPA’s GHG Inventory 28
report. CO2 emissions were estimated by dividing VMT by the average model year-specific fuel economy factors 29
and multiplying by fuel-specific emission factors expressed in pounds per gallon. Once emission estimates were 30
computed by vehicle category and model year group, emissions were summed for all model years and vehicle 31
categories for each GHG gas. 32
The queuing analysis boundary included the volume of queued vehicles accessing toll facilities on the 33
bridge and tunnel crossings, as well as the outbound queues that occur at the Lincoln tunnel. Queuing emissions 34
were estimated as a function of the number of hours of vehicle delay at each facility. The estimated number of 35
vehicle hours of delay was then multiplied by an estimate of idling fuel consumption to compute the amount of fuel 36
consumed by queuing vehicles at the toll gates. The PANYNJ was able to provide electronic data on the number of 37
hours of vehicle delay for four of its six facilities. For the other two facilities, there were aerial photographs taken 38
twice per year that were initially used to estimate vehicle delay at those facilities. However, it was found that the 39
queue lengths for the two sampled days (those with aerial photos) varied dramatically from year-to-year. Therefore, 40
it was decided to use the 2006 aerial photos to establish a baseline queue length for each facility and then estimate 41
vehicle hours of delay changes based on changes in annual traffic volumes. 42
One of the reasons for considering bridge and tunnel emissions in this inventory is to be able to measure the 43
sensitivity to policies such as fees to enter mid-town Manhattan in a vehicle. While such a policy was rejected by 44
the New York State Legislature, it or similar actions could be revisited. However, in developing emission estimates 45
for bridge and tunnel travel, it is acknowledged that double counting occurs for travel that is attracted by the Port 46
Authority airports and the airport attracted trip uses a Port Authority bridge or tunnel. 47
48
Bus Terminals 49
For the analysis of GHG emissions associated with the Port Authority bus terminals, the boundary was defined as 50
the property lines of the terminals. Emissions for the two bus terminals operated by the Port Authority were 51
estimated based on the bus and vehicle travel within the terminals, the idling emissions that occur when the buses 52
TRB 2011 Annual Meeting Paper revised from original submittal.
9
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
were parked in the facility, and the start-up emissions for vehicles parked within the facility. Defining the boundary
1
this way eliminates double counting emissions from trips through or across Port Authority tunnels and bridges. 2
Bus emissions were calculated in two parts: (1) emissions that occur while traveling within the bus 3
terminals and (2) emissions that occur when buses are idling. This VMT was estimated by multiplying the total 4
number of bus movements at each terminal by the estimated distance that the bus travels within the terminal. The 5
average time spent idling per bus was estimated from data in a PANYNJ report that surveyed and analyzed bus 6
movements within the Port Authority Bus terminal. Emission factors for buses were obtained from EPA’s latest 7
GHG Inventory report. 8
9
PATH 10
PATH runs commuter trains in the New York City area. Because PATH trains are electric, they are responsible for 11
indirect emissions from their power use. The GHG emissions associated with power generation for this electricity 12
were estimated using the Emissions & Generation Resource Integrated Database (eGRID) emission factors for the 13
eGRID region which includes Public Service Electric and Gas Company. eGRID emission factors for this eGRID 14
subregion were also used to estimate NOx and SO2 emissions. About 85 percent of the electricity purchased by 15
PATH is used to run the commuter trains, and the remainder is used in PATH buildings. 16
PATH GHG emissions also include attracted travel to and from its stations. This includes home-to-station 17
trips by bus and auto and returns. There is a large garage at the Journal Square Transportation Center and the idling 18
emissions at Journal Square are included in the emission inventory. Idling emissions at Journal Square are estimated 19
using the same methods used for the downtown bus terminals. 20
21
Mobile Sources 22
Key mobile source emitters in the various Port Authority departments are fleet vehicles, construction equipment, and 23
employee commuting. Direct GHG emissions were estimated for all motor vehicles in Port Authority fleets, with 24
the estimated fuel usage in each calendar year as the primary activity data for CO2 estimates. VMT was used as the 25
primary activity data for estimating CH4 and N2O emissions – with emission factors differentiated by vehicle type 26
and model year group. Emission estimates were based on the specific vehicles that PANYNJ operates; gallons of 27
fuel used, and fuel type. Construction equipment emissions were estimated for all equipment used in capital projects 28
funded by the Port Authority. For 2006-2008, no direct reporting of fuel use was available for this construction 29
equipment, so the relationship between annual construction spending by the PANYNJ by county, and overall 30
construction spending by county, was multiplied by EPA NONROAD model estimates of county-level CO2 and 31
criteria pollutant emissions to estimate the Port Authority’s share of these emissions. During the 2009 inventory 32
effort, more emphasis is expected to be placed on obtaining fuel use information from construction contractors. 33
Employee commuting emissions were estimated by surveying a significant sample of Port Authority staff 34
about their travel distances and modes of travel. The survey and resulting emission estimates were developed using 35
World Resources Institute protocols. Emissions from business travel by employees via plane, train, or non-fleet 36
vehicles was not captured in this inventory. 37
38
Real Estate and Development 39
This category includes all Real Estate and Development department operated buildings, buildings leased to tenants, 40
and office space that the department leases from other organizations. Emissions were estimated separately for direct 41
natural gas combustion for heating and indirect electricity usage. 42
43
Resource Recovery Facility 44
The Port Authority owns the Essex County Resource Recovery facility, which combusts municipal solid waste and 45
some auxiliary fuel. Emissions associated with tipping and hauling of waste were not included in the inventory. 46
One of the challenges associated with estimating emissions for this facility is the lack of a recent waste 47
characterization study. National waste characteristics were used. 48
49
RESULTS 50
The GHG emissions inventory for calendar year 2008 estimates that PANYNJ GHG direct and indirect emissions 51
total approximately 5.88 million metric tons of CO2 equivalent (CO2e). PANYNJ GHG direct and indirect 52
emissions were approximately 5.89 million metric tons of CO2e in 2007 and 5.77 million metric tons of CO2e in 53
TRB 2011 Annual Meeting Paper revised from original submittal.
10
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
2006. A comparison of annual emissions between 2006 – the baseline year – and 2008 can be found in Table 5.
1
Table 1 and Figure 1 show the 2008 CO2e emissions by department. The Aviation Department has the highest GHG 2
emissions (63.3 percent), followed by Port Commerce (14.7 percent), and Real Estate and Development (12.3 3
percent). Tunnels, Bridges and Terminals, PATH and mobile sources contribute the remaining 9.6 percent of 2008 4
GHG emissions. 5
Scope 1 encompasses an organization’s direct GHG emissions, whether from on-site energy production or 6
other industrial activities. Scope 2 accounts for energy that is purchased off-site (primarily electricity, but also 7
including energy such as steam). Scope 3 is much broader and can include anything from employee travel, to 8
upstream emissions imbedded in products purchased or processed by the firm, to downstream emissions associated 9
with transporting and disposing of products sold by the organization, or activities operated by third parties. 10
TABLE 1 Total (Scope 1, 2, and 3) PANYNJ CO2 Equivalent Emissions in 2008 11
Department
CO2 Equivalent Emissions
(metric tons)
Aviation 3,723,414
Port Commerce 867,271
Real Estate & Development 725,698
Tunnels, Bridges & Terminals 387,190
Mobile Sources 91,749
PATH 87,477
Totals 5,882,799
Figure 1 provides a breakdown of the sources of Scope 1 and 2 GHG emissions (under the direct 12
management control of the PANYNJ), irrespective of department. The figure shows that the Scope 1 and 2 GHG 13
emissions are dominated by indirect electricity use (approximately 71.7 percent of total Scope 1 and 2 emissions; 17 14
percent of which is from PATH trains). The second most important Scope 1 and 2 emissions source is Construction 15
Equipment operated at PANYNJ funded projects (approximately 18.3 percent). Most of this construction equipment 16
is diesel-powered. PANYNJ fleet vehicles also make a significant contribution to emissions (approximately 3.4 17
percent). Another important Scope 1 and 2 emissions source is heating fuel (primarily natural gas) combustion at 18
facilities under direct PANYNJ management control (approximately 5.1 percent). Other GHG sources under the 19
PANYNJ’s management control that contribute less than 2 percent of the GHG emissions include (in order of 20
importance): the Elizabeth Landfill; Direct Fugitive Emissions; and PATH Diesel Equipment. 21
22 FIGURE 1 GHG Emissions under direct management control 23
TRB 2011 Annual Meeting Paper revised from original submittal.
11
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
Table 2 provides Scope 1, 2, and 3 GHG emissions reported by department and broken down by sector.
1
The table also shows how the GHG emissions from energy use in buildings is allocated among direct energy use in 2
PANYNJ-occupied space (Scope 1 emissions), indirect electricity usage in PANYNJ-occupied space (Scope 2 3
emissions) and direct energy and indirect electricity usage in tenant-occupied space (Scope 3 emissions). The table 4
shows that Scope 3 GHG emissions comprise 94.2 percent of the total organizational emissions. Scope 3 emissions 5
are generated by tenants operating on PANYNJ properties. 6
TABLE 2 PANYNJ CO2 Equivalent Emissions in 2008 (metric tons) 7
Department
Direct GHG
Emissions Scope 1
Indirect
Electricity GHG
Emissions Scope 2
Other Indirect
GHG Emissions
Scope 3 Totals
Aviation
Aircraft 0 0 2,058,306 2,058,306
AirTrain 0 29,219 0 29,219
Ground Support Equipment 0 0 62,974 62,974
Attracted Travel 0 0 1,185,261 1,185,261
Buildings 14,449 140,618 167,724 322,791
JFK Co-generation Plant 0 0 60,117 60,117
Fleet Vehicles 4,233 0 0 4,233
Direct Fugitive Emissions (Refrigerants) 513 0 0 513
Port Commerce
Commercial Marine Vessels 0 0 187,943 187,943
Cargo Handling Equipment 0 0 131,863 131,863
Rail Locomotives 0 0 19,233 19,233
Heavy-Duty Vehicles 0 0 469,873 469,873
Buildings 0 0 53,965 53,965
Landfill 4,011 0 0 4,011
Fleet Vehicles 383 0 0 383
Tunnels and Bridges
Attracted Travel 0 0 332,377 332,377
Queuing 0 0 23,465 23,465
Buildings 720 10,600 0 11,320
Direct Fugitive Emissions (Refrigerants) 20 0 0 20
Fleet Vehicles 1,773 0 0 1,773
Bus Terminals
In Terminal Vehicle Emissions 0 0 4,676 4,676
Buildings 0 0 13,536 13,536
Fleet Vehicles 23 0 0 23
PATH
Trains 0 42,194 0 42,194
Attracted Travel 0 0 31,597 31,597
Buildings 0 12,983 0 12,983
Direct Fugitive Emissions (Refrigerants) 39 0 0 39
Diesel Equipment including Utility Track
Vehicles and Generators
373 0 0 373
Fleet Vehicles 291 0 0 291
Mobile Sources
Fleet Vehicles 66 0 0 66
Public Safety Department Fleet Vehicles 3,853 0 0 3,853
Direct Fugitive Emissions (Refrigerants) 295 0 0 295
Construction Equipment 62,586 0 0 62,586
Employee Commuting 0 0 24,949 24,949
TRB 2011 Annual Meeting Paper revised from original submittal.
12
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
Department
Direct GHG
Emissions Scope 1
Indirect
Electricity GHG
Emissions Scope 2
Other Indirect
GHG Emissions
Scope 3 Totals
Real Estate & Development
Buildings 2,101 9,404 232,381 243,886
Resource Recovery Facility 0 0 480,796 480,796
Fleet Vehicles 1,004 0 0 1,004
Engineering 12 0 0 12
Total 96,745 245,018 5,541,036 5,882,799
Table 3 provides estimates of calendar year 2008 CAP emissions by Port Authority department. NOx 1
emissions are higher than those of other criteria pollutants studied – SO2 and PM. Emissions for all scopes are 2
included in this table. NOx emissions are dominated by aircraft (Aviation Department), and commercial marine 3
vessels (Port Commerce Department). The Table 3 Port Authority (all scopes) NOx emissions total is about 9 4
percent of the New York City metropolitan area NOx emissions. 5
TABLE 3 2008 Criteria Air Pollutant Emissions by Department (metric tons per year) 6
NOx SO2 PM10 PM2.5
Aviation 12,266 1,629 663 599
Port Commerce 7,836 3,019 489 408
Tunnels, Bridges, and Terminals 986 26 32 20
PATH 177 502 38 33
Mobile Sources 1,361 61 35 33
Real Estate and Development 701 901 71 63
Totals 23,327 6,138 1,328 1,156
7
COMPARISON WITH PREVIOUS STUDY YEARS 8
This section compares the 2008 calendar year GHG emission estimates for the PANYNJ with those developed 9
previously for calendar years 2006 and 2007. The overall CO2 equivalent emissions went from 5,752,987 metric 10
tons in 2006 to 5,882,799 metric tons in 2008, a 2 percent increase. The tables that follow provide 2006 versus 2008 11
GHG emission comparisons at differing levels of detail. Table 4 shows Scope 1 plus Scope 2 CO2e emission 12
estimates for the three years by Department. Scope 1 plus Scope 2 emissions decreased by 7.3 percent from 2006 to 13
2007 as slightly higher fuel use being reported for heat at buildings in 2007 was offset by reduced electricity plus 14
steam use in these buildings, and then increased slightly between 2007 and 2008, so that CY2008 GHG emissions 15
are 4.0 percent below 2006 baseline levels. GHG mobile sources emissions are the only ones that have risen each 16
year during the three year period, and this is mostly attributable to construction equipment fuel usage. The methods 17
used to estimate construction equipment emissions use construction spending as a surrogate for construction activity, 18
and do not account for any efficiency improvements that may be occurring in PANYNJ construction projects. 19
TABLE 4 Comparison of Scope 1 and 2 CO2 Equivalent Emissions by Department 20
Department
Total CO2e Emissions (Metric Tons) Percent
Difference
(2008-2006)
2006 2007 2008
Difference
(2008-2006)
Aviation 214,334 183,841 189,032 (25,302) -11.8%
Port Commerce 4,550 4,395 4,394 (156) -3.4%
Tunnels, Bridges & Terminals 19,737 19,024 13,136 (6,601) -33.4%
PATH 49,363 53,299 55,880 6,517 13.2%
Mobile Sources 54,611 60,414 66,800 12,190 22.3%
Real Estate & Development 13,275 9,009 12,509 (766) -5.8%
Engineering 0 8 12 12 N/A
Total 355,870 329,990 341,763 (14,107) -4.0%
Table 5 compares the 2006, 2007, and 2008 total Scope 3 GHG emissions associated with each PANYNJ 21
department. Overall, Scope 3 GHG emissions increased by 2.5 percent from 2006 to 2008. 22
TRB 2011 Annual Meeting Paper revised from original submittal.
13
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
TABLE 5 Comparison of Scope 3 CO2 Equivalent Emissions by Department 1
Department
Total CO2e Emissions (Metric Tons) Percent
Difference
(2008-2006)
2006 2007 2008
Difference
(2008-2006)
Aviation 3,384,615 3,556,431 3,534,382 149,767 4.4%
Port Commerce 886,579 904,811 862,877 (23,702) -2.7%
Tunnels, Bridges & Terminals 390,965 382,735 374,054 (16,911) -4.3%
PATH 27,805 30,662 31,597 3,792 13.6%
Mobile Sources 27,080 27,198 24,949 (2,131) -7.9%
Real Estate & Development 690,243 662,622 713,177 22,934 3.3%
Total 5,407,287 5,564,459 5,541,036 133,749 2.5%
Table 6 compares the total GHG emissions for 2006, 2007, and 2008 by Department and source type. 2
Aircraft emissions increased by about 5 percent from 2006 to 2008. This increase really occurred between 2006 and 3
2007, when JFK increased the number of allowable flights per hour and LTOs increased. The PANYNJ took over 4
responsibility for Stewart Airport in November 2007, but including the LTOs from this airport in the GHG 5
emissions during 2008 was less of a factor in the overall increase in aircraft GHGs than the LTO increases at JFK 6
and increased helicopter activity at the downtown Manhattan Heliport. Newark, Teterboro, and LaGuardia airports 7
all had lower GHG emissions in 2008 than in 2006. The GHG emission estimation methods used for 2006-2008 8
account for differences in the aircraft types that used these airports, but it does not capture differences in operations 9
that may be occurring to save fuel. 10
Some increases in aviation attracted travel and buildings GHG emissions occurred between 2006 and 2008, 11
but these increases were smaller in magnitude than the aircraft emission increases. The JFK Cogeneration plant 12
GHG emissions (direct emissions from energy not used at the airport) dropped by 16 percent from 2006 to 2008 as 13
Kennedy International Airport Cogeneration burned a lower amount of natural gas in 2008 compared with 2006. 14
Port Commerce GHG emissions are fairly stable (a 1 percent overall reduction) over the 2006 to 2008 15
period as estimated increases in heavy-duty vehicle activity and buildings energy use is offset by reductions in 16
commercial marine vessel emissions and cargo handling equipment emissions. CMV emission reductions are 17
mostly attributable to reduced dredging activity in 2008. 18
Tunnels, bridges, and terminals GHG emissions in 2008 are below 2006 levels primarily because of lower 19
vehicle volumes on bridges and tunnels and because building energy consumption for this department declined 20
significantly from 2007 to 2008. 21
PATH train and attracted travel GHG emissions increased 6.6 percent from 2006 to 2008. It should be 22
recognized that this PATH system utilization provides a net GHG emission reduction for the New York City region 23
because PATH train travel is more GHG efficient than passenger car travel. 24
Overall increases in mobile source GHG emissions from 2006 to 2008 are attributable mostly to 25
construction equipment. Construction equipment GHG emissions are estimated using construction spending as a 26
surrogate for activity and emissions. Construction equipment GHG emissions increased by 30 percent from 2006 to 27
2008. 28
In the mobile sources category, there are significant year to year changes in the public safety department 29
vehicle GHG emission estimates with a significant increase between 2006 and 2007, and a large drop from 2007 to 30
2008. This suggests that there are anomalies in the fuel use and VMT reporting for this vehicle category in the 31
reporting period. 32
Changes in Real Estate and Development Department GHG emissions between 2006 and 2008 (almost a 10 33
percent increase) are directly related to changes in buildings energy consumption. Essex County Resource Recovery 34
Facility GHG emissions and activity are constant across the analysis years. 35
TABLE 6 Comparison of Overall CO2e Emissions by Department and Source 36
Total CO2e Emissions (Metric Tons) Percent
Department/Source 2006 2007 2008
Difference
(2008-2006)
Difference
(2008-2006)
Aviation
Aircraft 1,963,359 2,085,041 2,058,306 94,947 4.8%
AirTrain 26,919 29,219 29,219 2,300 8.5%
TRB 2011 Annual Meeting Paper revised from original submittal.
14
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
Total CO2e Emissions (Metric Tons) Percent
Department/Source 2006 2007 2008
Difference
(2008-2006)
Difference
(2008-2006)
Ground Support Equipment 63,575 61,502 62,974 (601) -0.9%
Attracted Travel 1,169,468 1,208,804 1,185,261 15,793 1.4%
Buildings 301,305 294,112 322,791 21,486 7.1%
JFK Co-generation Plant 71,360 57,815 60,117 (11,243) -15.8%
Fleet Vehicles 2,963 3,779 4,233 1,270 42.9%
Direct Fugitive Emissions (Refrigerants) - - 513 513 N/A
Port Commerce
Commercial Marine Vessels 227,735 211,788 187,943 (39,792) -17.5%
Cargo Handling Equipment 130,223 133,905 131,729 1,506 1.2%
Rail Locomotives 13,345 18,226 19,233 5,888 44.1%
Heavy-Duty Vehicles 449,871 471,399 469,873 20,002 4.4%
Buildings 50,569 53,774 53,965 3,396 6.7%
Direct Fugitive Emissions (Refrigerants) 18 - - (18) -100.0%
Landfill 4,221 3,958 4,011 (210) -5.0%
Fleet Vehicles 311 437 383 72 23.2%
Tunnels and Bridges
Attracted Travel 344,281 340,330 332,377 (11,904) -3.5%
Queuing 24,050 23,954 23,465 (585) -2.4%
Buildings 18,199 17,166 11,320 (6,879) -37.8%
Direct Fugitive Emissions (Refrigerants) 35 18 20 (15) -43.5%
Fleet Vehicles 1,491 1,827 1,773 282 18.9%
Bus Terminals
In Terminal Vehicle Emissions 6,345 4,588 4,676 (1,669) -26.3%
Buildings 16,289 13,863 13,536 (2,753) -16.9%
Fleet Vehicles 12 13 23 11 91.7%
PATH
Trains 40,828 40,206 42,194 1,366 3.3%
Attracted Travel 27,805 30,662 31,597 3,792 13.6%
Buildings 12,743 12,632 12,983 240 1.9%
Direct Fugitive Emissions (Refrigerants) 18 35 39 21 120.3%
Diesel Equipment including Utility Track
Vehicles and Generators
284 272 373 89 31.2%
Fleet Vehicles 156 154 291 135 86.5%
Mobile Sources
Fleet Vehicles 364 136 66 (298) -81.9%
Public Safety Department Fleet Vehicles 5,252 8,259 3,853 (1,399) -26.6%
Direct Fugitive Emissions (Refrigerants) 708 637 295 (413) -58.3%
Construction Equipment 48,287 51,382 62,586 14,299 29.6%
Employee Commuting 27,080 27,198 24,949 (2,131) -7.9%
Real Estate & Development
Buildings 222,075 195,856 243,886 21,811 9.8%
Resource Recovery Facility 480,073 474,668 480,796 723 0.2%
Fleet Vehicles 1,370 1,107 1,004 (366) -26.7%
Engineering 0 8 12 12 N/A
Total 5,752,987 5,878,730 5,882,799 129,812 2.3%
1
TRB 2011 Annual Meeting Paper revised from original submittal.
15
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
SUMMARY AND CONCLUSIONS
1
1. Methods have been developed that can be used to consistently track and report GHG and CAP emissions 2
for a large organization like the PANYNJ that has a complex set of sources. 3
2. Some fine-tuning of these methods is needed to reflect actions being taken by the PANYNJ to reduce 4
GHGs. 5
3. It should be recognized that there are actions taken by the PANYNJ that increase the organization’s GHG 6
emissions – like expanding PATH service – that serve to provide overall GHG emission reductions for the New 7
York Metro area. New York Metro area commuters taking PATH trains emit less GHGs that those traveling in 8
motor vehicles. 9
4. The emission models that were available for developing GHG and CAP emission estimates at the beginning 10
of this project (the 2006 calendar year) did not have the capability to estimate both GHG and CAP emissions for the 11
key PANYNJ source categories. It appears that models are becoming available – or are in the pipeline – that have at 12
least the capability to provide CO2 and CAP emission estimates (or emission factors). One such model is EPA’s 13
Motor Vehicle Emission Simulator (MOVES) 2010 model for onroad vehicles. Another example is FAA’s EDMS 14
model. Predecessors and predecessor versions to these models were limited to CAP emissions. Availability of 15
multi-pollutant model versions allows consistent inputs and outputs to be used to develop GHG and CAP emissions. 16
5. The bottom-up activity estimates developed for CMVs are too time-consuming and expensive to be used to 17
develop emission estimates every year, so surrogate activity indicators are applied in this study to develop estimates 18
for intermediate years. Using fuels sales to estimate CMV emissions was considered, but only a fraction of the 19
ocean-going vessels in the New York City port purchase fuel in the port terminals themselves. Fuel is purchased in 20
other nearby ports and from barges located in or around the port. Other studies in the New York City area have tried 21
to use statewide fuel sales allocated to counties to estimate CMV fuel use, but these studies have produced emission 22
estimates that differ widely from the bottom-up estimates, and are extremely uncertain. 23
6. In general, top down methods for estimating GHG emissions often focus on collecting fuel use data. Fuel 24
use drives CO2 emission estimates, but does not always provide the information needed to develop the best possible 25
estimate for CH4, N2O, and many criteria pollutants. 26
7. GHG emission estimation protocols have continued to be developed and updated during the course of this 27
project. For the 2006 calendar year emission inventory, key GHG protocols included those of the California Climate 28
Action Registry, the World Resources Institute, and the IPCC (guidelines). Another key emission factor source has 29
been the EPA national GHG inventory. More recently, the PANYNJ’s focus has been on The Climate Registry 30
protocols. Changing from one protocol to another can change emission factors and requires re-estimating previous 31
year’s emissions when adopted to avoid discontinuities because of method changes. For example, the California 32
Climate Action Registry protocol diesel vehicle CO2 emission factors were based on the properties of California 33
reformulated diesel, while The Climate Registry protocol emission factors are for U.S. conventional diesel. 34
8. It has been found that significant year-to-year differences in indirect electricity CO2e emissions can result 35
from changes to the electricity mix by the power production facilities in New York and New Jersey. This study uses 36
eGRID factors for these two states that serve the electricity customers in the respective states. Between 2006 and 37
2007, there was a substantial change in the New York State CO2 emission factor in eGRID, which produced a 38
significant change in the New York State indirect electricity emissions estimate, while the emissions from indirect 39
electricity usage in New Jersey stayed about the same. This change occurred despite there not being any change in 40
the purchasing practices by the organization. 41
9. For a large organization like the Port Authority, the number of facilities that are operated by the PANYNJ 42
changes with time. This requires re-estimation of the 2006 baseline, or a recognition that a portion of the emissions 43
increase or decrease each year is attributable to such changes and those emission changes need to be accounted for 44
separately. 45
46
REFERENCES 47
1. Intergovernmental Panel on Climate Change. 2006 IPCC Guidelines for National Greenhouse Gas 48
Inventories, Volume 2, 2006. 49
50
2. Airport Cooperative Research Program. Guidebook on Preparing Airport Greenhouse Gas Emissions 51
Inventories. ACRP Report 11. Transportation Research Board, Washington, DC, September 2009. 52
53
TRB 2011 Annual Meeting Paper revised from original submittal.
16
Stephen Colodner, Maureen A. Mullen, Manish Salhotra, Jackson Schreiber, Melissa Spivey,
Kirstin B. Thesing, James H. Wilson Jr., – E.H. Pechan & Associates, Inc.
Richard Adamson, Tim Hansen – Southern Research Institute
Lena M. DeSantis, Rubi Rajbanshi – The Port Authority of New York & New Jersey
3. URS Corporation. John F. Kennedy International Airport – Air Cargo Truck Movement Study. Prepared
1
for The Port Authority of New York and New Jersey Traffic Engineering, May 2002. 2
3
4. Starcrest Consulting Group, LLC. New York, Northern New Jersey, Long Island Non-attainment Area 4
Commercial Marine Vessel Emissions Inventory. Prepared for The Port Authority of New York and New 5
Jersey and the United States Army Corps of Engineers – New York District, 2003. 6
7
5. Starcrest Consulting Group, LLC. 2006 Baseline Multi-Facility Emissions Inventory of Cargo Handling 8
Equipment, Heavy-Duty Diesel Vehicles, Railroad Locomotives and Commercial Marine Vessels. Prepared 9
for The Port Authority of New York and New Jersey, November 2008. 10
11
6. Vollmer Associates, Eng-Wong, Taub & Associates, Stump/Hausman, New Jersey Institute of Technology, 12
Stevens Institute of Technology. Port Authority Marine Container Terminals Truck Origin-Destination 13
Survey 2005. Draft report prepared for The Port Authority of New York and New Jersey, February 27, 14
2006. 15
16
TRB 2011 Annual Meeting Paper revised from original submittal.