Juan Matute
I'm a sustainability professional operating at the intersection of policy and business. I develop solutions to help communities and organizations thrive in a low-carbon economy.
- Areas of Expertise
measuring greenhouse gas emissions, greenhouse gas markets, local economic development through climate action planning, transportation planning and policy, SB 375, & AB 32 - Available for
lectures and speaking engagements, limited-term projects, consulting, & general inquiries - Email me
- Download my CV
Profile
Experience
- Jul 2009 - PresentDirector, Luskin Center Climate Change Initiative / UCLAThe UCLA Luskin Center for Innovation's Climate Change Initiative identifies and supports research needed to strengthen local governments’ capacity to reduce greenhouse gas emissions and translates that research into a form useful to those working in or leading local governments.
Projects:
Measuring Progress Toward Transportation GHG Goals - UCLA Symposium on long term challenges for transportation GHG measurement (March 2010)
Service:
Technical Advisory Committee, Southern California Association of Governments Climate and Economic Development Project
Transportation Technical Advisory Committee, ICLEI Community GHG Protocol Development Process
Education
-
2006 - 2009University of California, Los Angeles
-
2006 - 2009University of California, Los Angeles - The Anderson School of Management
-
2000 - 2004Pomona College
Additional Information
Posts
The UCLA Luskin Center for Innovation is currently working on two EV-Related research projects that will add new knowledge to the challenge local governments face in integrating electric vehicles. More electric vehicles will be sold in 2011 than ever before, and many cities and counties have questions about how electric vehicles will integrate into their existing built environment. At this page, you'll find introductory information and links to our memos and outside resources that will help you understand the opportunities and challenges of electric vehicle integration in your city. More at luskin.ucla.edu
RED/PURPLE - WESTLAKE / MACARTHUR PARK | 2530.5 |
RED/PURPLE - WILSHIRE / VERMONT | 1784.8 |
PURPLE - WILSHIRE / NORMANDIE | 1711.1 |
RED - VERMONT / SANTA MONICA | 1172.4 |
RED - VERMONT / SUNSET | 743.3 |
RED - HOLLYWOOD / WESTERN | 610.5 |
RED - VERMONT / BEVERLY | 601.1 |
BLUE - ANAHEIM | 461.4 |
ORANGE - RESEDA STATION | 431.4 |
ORANGE - VAN NUYS STATION | 297.6 |
GREEN - I-105 / AVIATION | 8.24% |
BLUE - WILLOW | 6.19% |
GOLD - S WEST MUSEUM / FIGUEROA | 5.95% |
GOLD - ALLEN AVE | 5.62% |
RED - VERMONT / SUNSET | 4.23% |
ORANGE - DE SOTO STATION | 4.12% |
GREEN - I-105 / AVALON | 4.09% |
GOLD - MISSION ST | 4.05% |
GREEN - NASH / MARIPOSA | 3.92% |
GOLD - HOLLY ST | 3.57% |
The Governor's Office of Planning and Research is offering a preliminary flow chart that will help navigate a project's CEQA implications after a region updates its Regional Transportation Plan along with a Sustainable Communities Strategy or Alternative Planning Strategy. As a reminder, regions around the state must demonstrate their ability to meet per capita transportation GHG targets when they next update their RTPs:
MPO Expected Update
SANDAG Oct. 2011
SACOG Dec. 2011
SCAG May 2012
Tahoe RPA Oct. 2012
Butte CAG Dec. 2012
MTC April 2013
Santa Barbara Aug. 2013
Regions which fail to receive's ARB approval for their GHG reduction strategies will sacrifice CEQA streamlining and exemptions that will reduce the monetary costs of transit oriented infill development.
When policymakers think about greenhouse gas reductions from the regional transportation network, they usually spend more time considering light duty vehicles than goods movement. There are a few reasons for this. First, light duty vehicles are subject to SB 375’s greenhouse gas reduction targets; medium and heavy duty vehicles involved in commerce are not. Second, light duty vehicles make up a much higher proportion of greenhouse gas emissions. Thirdly, the dollar amount of economic productivity associated with a ton of greenhouse gas emissions is much higher for goods movement, and there are fewer mobility alternatives (a pallet of Blu-ray players can’t take the blue line). Thus, planners and policymakers aren’t actively looking for reductions in travel activity from goods movement. Most policies focus on efficiency or fuel switching (truck stop electrification, natural gas tractor trailers, etc). Very few land use strategies consider goods movement and commerce.
Currently most goods entering into Los Angeles come from the ports of LA and Long Beach. They are then trucked to warehouses or cross-docking facilities near the ports, or in the Inland Empire (and other areas).
The majority of these goods then proceed to other areas of the country. However, a sizable portion is distributed to serve the LA market. These goods backtrack, creating additional goods movement vehicle activity and costs associated with transport.
New warehouses and manufacturing facilities need large parcels. The area around the ports and the gateway cities is largely built-out. Large vacant or underutilized parcels are located in the Inland Empire, Apple Valley, and Lancaster/Palmdale.
One strategy to concentrate more warehouses and light industrial facilities near the ports would be to densify existing land uses. This would include multi-story warehouses (with truck ramps serving multiple levels), and industrial facilities. Multistory industrial buildings were more common before World War II, when there was a higher premium on proximity and non-vehicle accessibility. New multistory industrial facilities are virtually unheard of now. I’d be interested in whether this is due to constraints of the market (it’s just too expensive to acquire parcels and build viable multistory manufacturing facilities), or constraints of zoning regulations (FARs and height limits in industrial districts would prohibit such buildings).
If the constraint is zoning regulations, then planners could accomplish a number of policy objectives by allowing the densification of industrial parcels.
1. The intensification of jobs per acre would help with the economic revitalization of the area around the ports and gateway cities.
2. Regional congestion could be reduced compared to the counterfactual where new industrial development occurs further away from the ports. Drayage may continue to occur during the daytime based on logistics requirements of ports (ship in port for limited time, limited storage available at port facility). However, long distance trucking to move vehicle out of the LA basin could occur at night.
3. Graduated density zoning could assist in efforts to assemble parcels to increase new building footprints. Parcel assemblage is a frequent problem for infill industrial developers – one holdout can kill a project. Allowing greater density for larger parcels will increase the value of land for large parcels, provide (see Donald Shoup’s work on graduated density zoning). Local governments could even look at the vacation of air rights along streets in industrial areas to help with the creation of large multistory industrial buildings. Streets would remain, but would be bridged over by building structures.
4. Densification of warehousing facilities would also provide a larger market for initiatives to shift more goods from trucks to rail, or to concentrate rail traffic on a single grade separated right of way as opposed to multiple tracks with at-grade crossings.
Your thoughts?
In a continuous effort to make SB 375 more accessible, I bring you the process map:
A concern of planners and communities everywhere is: if you build it, where will they park? The New York City City Council just approved a new skyscraper near the Empire State Building at 15 Penn Plaza. The new building will be 67 or 68 stories high and 1,190 or 1,216 feet tall. It is adjacent to Penn Station, and the developer will invest $100 million in the transit hub. For this, the developer (office REIT Vornado) gets a 20% density bonus, boosting the FAR from 15 to 18.
But where will the people park? Simply put, they won't. Looking into the environmental impact documents, I found that there are two potential configurations for the building. As a single-tenant building, it would have 2.04 million square feet of office space, 11,126 square feet of retail space, and up to 100 parking spots. As a multi-tenant building, it would have 1.756 million square feet of office, 296,390 square feet of retail, and no parking at all!
I wondered what this building would be like in the Nations second-biggest city, Los Angeles. How many parking spaces would be required? Well, according to code the building would need a minimum of:
In single-tenant configuration: 4,125 spaces
In multi-tenant configuration: 4,698 spaces
If the retail included restaurants, even more spaces would be required.
15 Penn Plaza is on a 60,000 square foot lot. Given this limited footprint, I wondered how many floors of the hypothetical Los Angeles building would need to be devoted to parking. The single-tenant configuration would require 23 floors, while the multi-tenant building would require 26 floors, or roughly twice as tall as the garage at 1100 Wilshire (pictured below):
On Monday, the California Air Resources Board released its SB 375 staff report with more precise draft targets. I had blogged earlier about the original draft target ranges released at the end of June.
The Southern California Association of Governments has the most aggressive per capita greenhouse gas reduction target, at 8%. The other three large MPOs (Bay Area, San Diego, and Sacramento) all have reduction targets of 7%.
What are the main differences between these regions that could explain the slight difference in target? One major difference is that the central SCAG region (Los Angeles County) will significantly expand its rail transit system in the next thirty years, and as few as ten years. As a goal of SB 375 is to concentrate new development near transit stations to increase the proportion of trip origins and destinations which are accessible using transit, this aggressive transit-building program will bring rail transit to existing density, shifting some existing trips to transit and allowing for new trips to be made via transit.
However, this increase in transit ridership comes at a cost. No large transit system in the United States achieves a farebox recovery ratio of 100% or higher, all receive some operating subsidies. This means that a system is losing money with each additional passenger. No U.S. system has been able to completely close this gap with increased ridership . While small systems with low vehicle occupancy ratios raise less of their operating expenses from fare revenues, even large, well-traveled systems in New York City, Philadelphia, and Washington D.C., raise only 3/5ths of their operating expenses from fares.
Los Angeles Metro has a farebox recovery ratio of approximately 30%. In order for the system to increase ridership without increasing its required operating subsidy, it must increase fare revenue to match increases in operating expenses. If it cannot do this, it must seek additional operating subsidies to provide the transit service needed to reduce regional greenhouse gas emissions and make transit a preferred alternative travel mode.
Yesterday, the California Air Resources Board released draft regional transportation GHG emissions reduction targets. This may sound very boring, but these targets are the performance target upon which California's anti-sprawl and GHG reduction will be based. Weak targets will mean that regional and local transportation policymakers can relax and not worry to much about infill development or transit. Overly strong targets could mean that regions must introduce a level of transportation pricing that goes beyond creating system efficiencies and hurts Gross Regional Product. Finding a reduction target that is just right will help the state ease the transition to a low carbon economy and mitigate the effects of sudden fuel price spikes, like the state experienced in 2007-2008:
The ARB's Draft targets are really a range of GHG reductions resulting from scenarios the MPOs (regional governments) had presented to the ARB. The lower end of this range represents the reductions expected from Regional Transportation Plans adopted before SB 375. The upper end of this range represents the scenarios each MPO thought to be most ambitious.
| MPO Regions | 2020 Draft Targets |
| Metropolitan Transportation Commission (MTC) Sacramento Area Council of Governments (SACOG) San Diego Association of Governments (SANDAG) Southern California Association of Governments (SCAG) | 5 - 10% |
| Council of Fresno County Governments Madera County Transportation Commission Merced County Association of Governments Kern Council of Governments Kings County Association of Governments San Joaquin Council of Governments Stanislaus County Council of Governments Tulare County Association of Governments | 1-7% |
| Association of Monterey Bay Area Governments Butte County Association of Governments San Luis Obispo County Council of Governments Santa Barbara County Association of Governments Shasta County Regional Transportation Planning Agency Tahoe Metropolitan Planning Organization | TBD |
Targets are expressed as a percentage reduction in regional per capita GHGs versus 2005 levels. But what do these targets actually mean? How will they translate into policy changes? This all depends on whether or not these targets are too weak, too strong, or just right. The 4 large MPOs with the 5-10% reduction target contain the vast majority of the state's population and vehicle activity. For purposes of this analysis, we'll look at only these MPOs.
The first question to ask is how the absolute level of emissions in 2020 would compare to 2005. The background information on regional VMT, GHG emissions, and population levels the ARB provided the public is denominated in weekday pounds of CO2 per capita. There are some problems with using a weekday number rather than an annual number (leakage to weekends), but I won't elaborate here. Using these figures, we can get an idea of a region's weekday pounds of CO2 in 2005 and what the reduction targets would mean for 2020:
| MPO | 2005 AGGREGATE WEEKDAY EMISSIONS (lbs CO2) | 2020 REDUCTION TARGET (LOW) | 2020 AGGREGATE WEEKDAY EMISSIONS (LOW TARGET, lbs CO2) | ABSOLUTE CHANGE 2005-2020 EMISSIONS | 2020 REDUCTION TARGET (HIGH) | 2020 AGGREGATE WEEKDAY EMISSIONS (HIGH TARGET, lbs CO2) | ABSOLUTE CHANGE IN EMISSIONS |
| SCAG | 380,346,939 | 5% | 427,254,427 | 12.3% | 10.0% | 404,767,352 | 6.4% |
| MTC | 148,992,501 | 5% | 159,106,058 | 6.8% | 10.0% | 150,732,055 | 1.2% |
| SANDAG | 79,686,197 | 5% | 88,039,954 | 10.5% | 10.0% | 83,406,272 | 4.7% |
| SACOG | 50,326,254 | 5% | 60,467,865 | 20.2% | 10.0% | 57,285,346 | 13.8% |
One of the things we see here is that even under the 10% scenario, absolute regional emissions will increase. [EDIT: An earlier version of this entry had compared this absolute increase versus Scoping Plan reduction amounts (provided as a placeholder). I had erroneously compared the 2020 projections as if they were versus a 2005 versus 2020 2020 Business As Usual baseline.]
The next step in our analysis is to compare these targets to current greenhouse gas emissions. Unfortunately, I'll have to use VMT as a proxy for CO2. VMT doesn't account for additional emissions caused by traffic congestion, but because reductions in CO2 per mile from vehicle fuel efficiency and low carbon fuels are controlled for in SB 375 reduction numbers, and the state's method to calculate vehicle CO2 also somewhat ignores congestion, it's fine for our purposes. Using VMT by county data from Caltrans, I calculated 2005 and 2008 (the most recent year available) VMT for California's large MPOs. Incorporating population data, I came up with an end result of change in per capita VMT between 2005 and 2008, which will proxy for change in per capita transportation CO2 between those years.
| MPO | 2005 VMT | 2008 VMT | 2005 PER CAPITA VMT | 2008 PER CAPITA VMT | PERCENT CHANGE |
| SCAG | 83,065,900,000 | 81,521,500,000 | 4,576 | 4,343 | -5.1% |
| MTC | 35,397,300,000 | 33,809,800,000 | 4,994 | 4,665 | -5.1% |
| SANDAG | 16,405,900,000 | 15,618,800,000 | 5,371 | 4,977 | -6.3% |
| SACOG | 7,733,400,000 | 7,503,800,000 | 4,479 | 4,177 | -12.7% |
From this data, it appears that SCAG, MTC, and SANDAG already achieved their low end 2020 targets in 2008 and SACOG achieved their high end 2020 target. A combination of the economic downturn and higher gasoline prices resulted in a reduction in driving between 2005 and 2008.
However, what we are really interested in is what might happen between 2008 and 2020 that would increase VMT and GHG per capita, if not for a change in regional transportation policy and local land use policies. Renewed economic growth could create more demand for driving (more people going to and from shopping and jobs) and the reductions observed between 2005 and 2008 could be eroded. Additionally, gas prices could decrease and people could respond by driving more. Unfortunately, I can't predict these effects and neither can the ARB or MPOs. What we can predict, however is demographics. In 2020, we know that people will be 10 years older. We also know that older people drive less:
We are learning information that younger people are driving less as well, drive less as well. So, economic factors held constant, we could expect a further reduction in per capita driving in the future, without regions adopting land use and transportation policies designed to reduce travel demand and promote alternative modes to driving. This reduction is not reflected in the SB 375 draft targets.
Helping America’s Metropolitan Regions Build Prosperity and Expand Opportunity
April 2010-Upcoming Climate and Energy Webcasts for State and Local Governments
- Smart Grid for Local Governments, April 29
- Green Roofs, late May
- Purchasing and Procuring Efficient Equipment, April 21
- Portfolio Manager for EECBG Grantees and State and Local Governments, April 21
- Benchmarking Water/Wastewater Plants in Portfolio Manager, April 28
- ENERGY STAR and Green Building Rating Programs, April 29
- Financing Energy Efficient Upgrades with ENERGY STAR, May 11
- K-12 Benchmarking 101, May 13
- DOE: Midsize Wind Turbines for the U.S. Community Wind Market, April 28
- CHP Partnership: District Heating, May 20
***Local Climate and Energy Webcasts
This site may be useful for cities looking for resources on transit-oriented development. Mixed income TOD's are a good way to increase the transit utilization from new TOD projects as 1) new product is often more expensive than existing product in a neighborhood (just the way the market functions) and 2) lower income groups have a higher propensity to use transit (but can't afford to buy or rent in new TOD projects).
From the U.S. EPA:
HUD and FTA Sponsor Transit Oriented Development Guide; Upcoming Smart Growth Opportunities
The Mixed Income Transit-Oriented Development Action Guide is an online tool designed to help local jurisdictions and planners develop strategies to create mixed income transit oriented development (MITOD) around planned transit stations. This interactive site was developed by the Center for Transit Oriented Development in cooperation with the Federal Transit Administration and the U.S. Department of Housing and Urban Development.
The Action Guide walks users through three critical data gathering and analysis components of plan development: Existing Conditions Analysis, MITOD Strategies Analysis, and MITOD Opportunities Analysis. These three areas of analysis are composed of questions—to be answered by the planner—that span several subjects: demographics, housing, real estate markets, land capacity, and neighborhood stability. Each question highlights key information that will be used to help local jurisdictions select and direct policy tools to achieve their MITOD goals.
The Action Guide is available at: http://www.mitod.org
from the U.S. EPA:
EPA has released its second annual ranking of U.S. metropolitan areas with the most energy-efficient buildings that earned the ENERGY STAR rating in 2009. The city with the most ENERGY STAR labeled buildings is Los Angeles, which also ranked #1 in 2008. Washington, DC, had the second-highest number of ENERGY STAR labeled buildings in 2008, followed by San Francisco, Denver, and Chicago. New York City entered the top 10 for the first time in 2009.
EPA awards the Energy Star to commercial buildings that perform in the top 25 percent of buildings nationwide compared to similar buildings. Thirteen types of buildings can earn the Energy Star, including schools, hospitals, office buildings, retail stores and supermarkets. During 2009 alone, 3,900 commercial buildings earned the ENERGY STAR, a 40 percent increase over the previous year. Annual utility savings have increased to almost $1.6 billion while avoiding greenhouse gas emissions equivalent to those of more than one million homes.
To see the list of the Top 25 Cities in 2009, visit: http://www.energystar.gov/ia/business/downloads/2009_Top_25_cities_chart.pdf
The modeled reference case is that California Economy would grow at an annual average rate of 2.4% between 2006 and 2020 and fuel expenditures grow at 1.7% per year. This reference case does not capture any of the consequences of inaction (adaptation costs or fuel price volatility). With the Scoping Plan, economic growth is still 2.4% per year, but fuel expenditures are reduced 4.9% (by 2020) and GHG emissions are reduced 15% relative to the reference case. Emissions reductions programs help limit cap and trade allowance price to $21/MTCO2e. In the worst case sensitivity analysis scenario, where all major emissions-reductions programs fail to provide forecast reductions, there is only a small decrease in California’s economy relative to the reference case.
ARB used the Energy 2020 model to simulate fuel demand for 40 industry category, 3 residential categories, and 3 transportation types. It also predicts supply, and hence price, for 30 different fuel products. For each category, the model simulates investment in energy efficiency, fuel choice changes, and end-use demand. It does this using information on costs (of energy and of energy efficiency capital investments), and other attributes, such as the convenience or acceptance of an energy efficiency investment.
Here’s a visual of how Energy 2020 works:
With the information on energy prices produced by the Energy 2020 model, ARB used the Environmental Dynamic Revenue Assessment Model (E-DRAM) to calculate a future year reference case and alternatives analysis for various policy bundle scenarios. (See Section 5 of the report for details on these scenarios). The model is capable of assessing 120 industrial sectors, labor, capital, 8 household sectors, 9 consumption sectors, 1 investment sector, 45 government sectors, and the rest of the world (188 sectors in total).
Here’s a visual of how E-DRAM works:
And how the 2 models interact:
After calculating the effects on each sector, the ARB used the models to combine these results in a macroeconomic analysis. The table below summarizes this analysis:
Chapter 8 discusses the effects of AB 32 implementation on small business, which are found to be “insignificant” overall, although certain sectors (mining, unities) while others would gain. UCLA’s own Matthew Kahn played a role in this analysis.
Overall, the report is quite robust in its analysis and key result: that shifting California to a lower carbon economy will have a negligible aggregate economic impact by 2020. The report should withstand academic criticism quite well. Certain findings, such as how AB 32 could cause small businesses which operate coin-operated laundry services to raise rates, could be misconstrued and used as an argument against Scoping Plan implementation. However, the report makes it clear that Scoping Plan implementation can give rise to new business opportunities which will enjoy revenue and employment growth as California, and the rest of the world, move to a low carbon economy.
Obama is now looking at spending the unexpected TARP windfall on stimulus, including home energy efficiency. While I haven't studied any of the proposal specifics, I would like to discuss the difference between loans and rebates in the context of financing residential energy efficiency.
First, it's worth noting that lower income property owners will likely bear a disproportionate amount of the climate mitigation and adaptation burden. This is for a variety of reasons.
- Homeowners of lower incomes tend to live in older housing stock. At least in California, the pre mid 70's housing stock in relatively inefficient. These homes have less energy-efficient appliances, HVAC and lighting systems, and are less well insulated so require more use of this relatively inefficient equipment.
- Smart investments in energy efficiency are NPV-positive and have a relatively short payback period, but these investments require up-front financing. Lower income homeowners have less of an ability to finance energy efficiency projects than homeowners with higher incomes.
- The combination of energy prices increases and a warming climate will place a significant burden on households unable to adapt. As these factors increase the relative costs of inefficiency, homeowners that are able to weatherize and make their homes more energy efficient will do so.
Up-front rebates are a good economic stimulus policy, as they will, lower the direct private cost of an energy efficiency and weatherization retrofit. This will spur new demand, which will drive both construction and manufacturing job growth. The homeowner will benefit from lower energy bills, and more monthly free cashflow, which will further stimulate the economy (provided it is spent in a sector with a higher multiplier than energy, and most consumer sectors do).
However, unless they eliminate all financing needs, up-front rebates do not assist those who are least able to afford a home retrofit. To serve these households, a financing system is needed. The state of California allows a financing system that allows households to engage in NPV-positive investments that will decrease energy bills and increase free-cash-flows. California's AB 811 allows property tax financing of renewable energy and energy efficiency. Property tax financing has many advantages to a private loan.
- Debt is a tax lien and is senior to all other claims on the house (first mortgage, subsequent mortgages). Thus, it is very low-risk and the interest rate can be substantially lower than for a private loan.
- No money down. No credit check required. Because of the low risk, the loan can be provided at no up-front cost. This eliminates all financing barriers for homeowners.
- The loan term can be 5, 10, 15, or 20 years. The burden of higher property taxes is spread over a long time, and the homeowner can immediately reap the benefits of decreased energy costs. The homeowner is cash-flow positive from month 1, and provided the investment was smart, remains better off after the semi-annual payments.
- The cost of the improvements are passed to subsequent owners of the house, virtually eliminating the possibility that a homeowner's energy efficiency investment will be unrecouped on-sale. This removes a significant barrier: energy efficiency investments can be hard to value in residential real estate markets.
The UCLA Program on Local Government Climate Action Policies and Lewis Center for Regional Policy Studies proudly present the fall speaker series: Perspectives on Local Climate Planning. In this series leading academics, policymakers, and practitioners discuss how cities, counties, and regions can meet the challenges of mitigating and adapting to climate change. While much attention is focused on the federal American Clean Energy and Security Act and the international UNFCCC meeting in Copenhagen, we will examine what can be done at the local level to reduce emissions and adapt to climate change.
Mondays at 2pm in the UCLA School of Public Affairs Room 1246. (directions: driving, bus)
Free and open to the public. Please RSVP.
Monday, October 5 - Katherine Trisolini, Professor, Loyola Law School, and local government climate change response legal scholar will discuss the legal and political context for local climate action |
Monday, November 2nd - Tim Kohut, AIA and LEED AP, Vice President and Director of Architecture of Abode Communities speaks about challenges to building green affordable housing. -- See the Program on Local Government Climate Action Policies Web site for more information. |
Because I was unsure of the findings, I spent some time looking at the Booz Allen Hamilton/Department for Transport High Speed Rail Study (Estimated Carbon Impact of a New North-South Line) mentioned in a Freakonomics Blog Post.
First, I went to look at the source documents. This was a bit difficult, because footnote xii is actually a link to the AEA study source document. None of the links on footnote x, which is supposedly the AEA study, lead to any usable data for this study.
Looking at the AEA study for DfT, I'm able to see how they got the AEA figures. 49 for average passenger rail, 109 for all cars, 76 for bus, 180 for plane. However, they leave out the Class 373 EMU (high speed rail train).
I was unsuccessful in searching for the June 2007 DEFRA statistics released in the study, but I did find the updated 2009 statistics. Each year, DEFRA (UK's EPA) publishes statistics that they have businesses use to calculate their scope 3 (indirect) emissions from rail travel. This study shows a figure of 17 g/pkm for Eurostar, specifically the high speed rail route between London and Paris. This figure could be a bit low, because France derives a high proportion of their energy from a non-ghg-emitting source (nuclear).
| Taxi, Bus, Rail and Ferry Passenger Transport Conversion Factors |
|
|
| CO2 |
|
| Method of travel |
| Vehicle kms travelled (vkm) | x | kg CO2 per vkm | Total kg CO2 |
| Taxi 1 | Regular taxi |
| x | 0.2217 |
|
|
| Black cab |
| x | 0.2558 |
|
| Method of travel |
| Passenger kms travelled (pkm) | x | kg CO2 per pkm | Total kg CO2 |
| Taxi 1 | Regular taxi |
| x | 0.1583 |
|
|
| Black cab |
| x | 0.1705 |
|
| Bus | Local bus 2 |
| x | 0.1104 |
|
|
| London bus 3 |
| x | 0.0830 |
|
|
| Average bus |
| x | 0.1035 |
|
|
| Coach 4 |
| x | 0.0300 |
|
|
| Average bus and coach |
| x | 0.0682 |
|
| Rail | National rail 5 |
| x | 0.0577 |
|
|
| International rail (Eurostar) 6 |
| x | 0.0177 |
|
|
| Light rail and tram 7 |
| x | 0.0834 |
|
|
| London Underground 8 |
| x | 0.0780 |
|
| Ferry (Large RoPax) 9 | Foot passengers |
| x | 0.0191 |
|
|
| Car passengers |
| x | 0.1322 |
|
|
| Average (all passengers) |
| x | 0.1152 |
|
| Total |
|
|
|
| 0 |
Looking at the Center for Neighborhood Technology study's figure for the Danish IC3 Diesel Multiple-Train Unit and converting lb/pmi to g/pkm, I get 72.71, which is the same (73 g/pkm) as the study. However, the IC3 is diesel-powered conventional rail train capable of a top service speed of 112 mph, not a high speed rail train. Better comparables would be the ICE line 6 in Germany or the TGV in France, which have lower g/pkm emissions.
At this point I was left wondering if the report's authors meant to analyze the impact of a mid-speed diesel powered train line instead of a high speed line. Although the report was light on specifics, the authors did mention that they meant to analyze the effects of efficiency gains in "traction electricity," although this may refer to maglev. They could have also assumed much lower load factors for these routes, although they did not state this in their assumptions.
Needless to say, I'm convinced that the study is flawed.
However, assuming it is not flawed, the energy mix still differs from region to region (different power pools have different generation and emissions profiles). I found the UK-wide electricity emissions-factor on DEFRA's site, which is 546.67 kG of CO2 per mWh. Using the EPA's eGRID data for the California region, I converted lbs/kWh to 398.57 kG of CO2 per mWh. So, California's electricity results in about 73% of the emissions in the UK, per unit of delivered electricity.
|
| raw | convert |
| UK, From DEFRA | 0.54667 | 546.67 |
| California, from eGRID | 878.71 | 398.5766 |
|
|
|
|
So, even if the report was correct, and high speed rail emissions in the UK would emit 88 g/pkm (which I highly doubt), the equivalent technology would only emit 64 g/pkm operating in California.
I've heard and read a fair amount about how cities can be rewarded for early action or, in the case of SB 375, exceeding targets. Many policymakers think that cities should be able to monetize or receive additional funding for reductions they make beyond reduction mandates. On the surface, this seems like a great idea: to financially reward cities that do more than their fair share in reducing emissions. However, there are some drawbacks. As pointed out in UC Davis ITS Researcher Deborah Salon et al's paper on City Carbon Budgets, doing so would necessitate greenhouse gas emissions caps at the local level. While there are many concerns to tying local funding to greenhouse gas performance, my point is that cities that reduce emissions more than their neighbors will experience additional benefits. However, these benefits will not be channeled directly to the local government.
A number of publications, including Growing Cooler, have exalted the numerous co-benefits to reducing emissions in terms of urban design, property values, and transportation alternatives. However, under a carbon constrained economy, a major benefit to living in an area with low greenhouse gas emissions per capita will be the monetary savings: at $18 per ton of CO2e the difference in per capita emissions between the U.S. (around 24) and San Francisco (around 13) is about $200. This translates to about $160M of annual purchasing power to the City's residents.
While $200 pales in comparison to the differences in the cost of living between San Francisco and Los Baños, it's still $200.
This is the blog of Juan Matute, Director of the UCLA Program on Local Government Climate Action Policies.
