SB 743 An Evolutionary Change to Transportation Impact Analysis - - PowerPoint PPT Presentation

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SB 743 An Evolutionary Change to Transportation Impact Analysis Bob Grandy, Ronald Milam and Ian Barnes March 16, 2017 INNOVA VATION B BY SB 743 IMPLEMENTATION TIMELINE nd Draft o Ja Jan. 2 n. 2016 2 nd of Guid ideli lines

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SLIDE 1

INNOVA VATION B BY

SB 743

An Evolutionary Change to Transportation Impact Analysis

Bob Grandy, Ronald Milam and Ian Barnes March 16, 2017

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SLIDE 2

INNOVA VATION B BY

SB 743

IMPLEMENTATION TIMELINE

  • Ja
  • Jan. 2
  • n. 2016 – 2nd

nd Draft o

  • f Guid

ideli lines

  • Fina

inal D l Draft t to Natural R l Reso source Age gency e y early y 2017 17

  • Imple

lementatio ion in n in la late-2017 17

  • Tw

Two-year g gra race p peri eriod

  • d?
  • Potentia

ial a l acceleratio ion in in sc schedule due t to Calt ltrans gu s guid idanc nce

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SLIDE 3

INNOVA VATION B BY

NEW LAWS

Change

SB 375 AB 32 SB 9 SB 97 SB 226 SB SB 74 743 AB 2245 AB 417 AB 1358

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SLIDE 4

INNOVA VATION B BY

SB 743 LEGISLATIVE INTENT

Change

(1) Ensure that the environmental impacts of traffic, such as noise, air pollution, and safety concerns, continue to be properly addressed and mitigated through the California Environmental Quality Act. (2) More appropriately balance the needs of congestion management with statewide goals related to infill development, promotion of public health through active transportation, and reduction

  • f

greenhouse gas emissions.

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SLIDE 5

INNOVA VATION B BY

TRANSPORTATION PLANNING

Change

What at S SB 7 743 43 Do Does N Not Do… Do…

No c change to g genera ral l pl plan ans, t traf affic im impac act f fee progra rams, S , State Const stit itutio ion, s subdiv divis isio ion map ac map act, e etc.

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SLIDE 6

INNOVA VATION B BY

IMPACT ANALYSIS & MITIGATION

Change

Mobil ilit ity Acces cessib ibil ilit ity

What at S SB 7 743 43 Do Does Do… Do…

  • Elimi

iminat ates L s LOS/D S/Delay

  • Adds V

dds VMT

  • Saf

Safety?

  • Methods a

ds and Thresh sholds ds Guidance ce

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SLIDE 7

INNOVA VATION B BY

Isn’t VMT quantification already included under CEQA?

  • Yes, but it is not specifically reported in the

transportation section

  • It is used to quantify other metrics used for energy,

greenhouse gas, and air pollution analyses

  • Reducing VMT for transportation purposes requires the

project to change in some way that reduces the amount

  • f vehicle trips or their length

IMPACT ANALYSIS & MITIGATION

Change

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SLIDE 8

INNOVA VATION B BY

SB 743 looks at VMT differently

  • For Residential: automobile VMT for home-based

trips (passenger cars and light trucks only)

  • For Office: automobile VMT generated by workers
  • For Retail: exempt if less than 50 Ksf, can provide total

VMT generated or cumulative project effect

IMPACT ANALYSIS & MITIGATION

Change

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SLIDE 9

INNOVA VATION B BY

VMT FORECASTING

Methods

VMT = Volume x Distance or Trips x Trip Length

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SLIDE 10

INNOVA VATION B BY

Data

AVAILABLE SOURCES Statewide Model

  • Not Locally

Calibrated

  • 78 Sonoma

County Zones

  • Omits local

trips

MTC Model

  • Locally

Calibrated

  • Roadway,

Transit, and Land Use More Refined

  • 86 Sonoma

County Zones

  • More

accurate measure of VMT

Census Data

  • Does not

provide specific VMT information

  • Journey-to-

Work data

  • nly provides

information for work trips (about 20% of daily trips)

HPMS Data

  • Boundary

method only

  • OPR

guidelines recommend per capita methods for residential and office

  • Can be based
  • n old data
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SLIDE 11

INNOVA VATION B BY

Data

AVAILABLE SOURCES

SCTA Model

  • Locally

Calibrated

  • Roadway,

Transit, and Land Use More Refined than MTC

  • 900+ Sonoma

County Zones

  • Truncates trip

length/VMT at County boundaries

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SLIDE 12

INNOVA VATION B BY

VMT FORECASTING

Methods

VMT = Volume x Distance or Trips x Trip Length

  • OPR guidelines provide 3 basic methodologies

for VMT quantification:

  • Activity-Based Modeling
  • Trip-Based Modeling
  • Spreadsheet Method/Sketch Models
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SLIDE 13

INNOVA VATION B BY

VMT FORECASTING

Methods

VMT = Volume x Distance or Trips x Trip Length

  • There are sub-methodologies within each

method:

  • Boundary Method
  • Origin-Destination Method
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SLIDE 14

INNOVA VATION B BY

Boun

  • undar

dary y VMT MT Me Metho hod

  • Calc

lculates V VMT MT that t

  • ccurs

s in a a de desig signat ated d ar area ( (i. i.e. a a cit ity)

  • Can b

be used f for

  • r re

retail pr projects

  • Cit

Citrus Heig ights = s = 1,000, 000,110 d daily V VMT (weekday) y) AIR POLLUTION = GHG

Methods

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SLIDE 15

INNOVA VATION B BY

Orig igin in- Des Destin ination ( ion (OD) D) VMT MT Me Metho hod

  • Calc

lculates V VMT MT from m indiv ividu idual t trips ips to/

  • /fr

from a an are rea

  • Cit

Citrus Heig ights = s = 1,39 397, 7,340 340 dail daily V VMT (weekday) y) FULL ACCOUNTING

Methods

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SLIDE 16

INNOVA VATION B BY

FULL/SHARED ACCOUNTING

Methods

  • Full A

Acco ccounting: all V ll VMT MT generated by pr project is is at attributed t d to pr proje ject

  • Share

red-Acco counting: g: VMT is sh is shar ared d between o n origina nating ng an and de d dest stination lan and u d use se

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SLIDE 17

INNOVA VATION B BY

WHAT VMT COUNTS?

Methods

Project Generated VMT vs. the Project’s Effect on VMT

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SLIDE 18

INNOVA VATION B BY

Mode

  • del B

Bas ased d O-D V VMT MT

  • Calc

lculates V VMT p MT per r re resident of

  • f are

rea or

  • r

worker in in ar area

  • MTC M

C Mode del So Sonoma Co County dail daily V VMT pe per Capi Capita g a generated b d by Resid sidents = s = 17.9 FULL ACCOUNTING

Methods

0.0 5.0 10.0 15.0 20.0 25.0

MTC M Model: V VMT Per C Capita a - Residen ents ts

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SLIDE 19

INNOVA VATION B BY

Cotati 10% | 28% Windsor

  • 7% | 9%

Unincorporated 12% | 36% Petaluma 6% | 25% Rohnert Park

  • 2% | 15%

Sonoma 8% | 26% Santa Rosa

  • 25% | -13%

Healdsburg

  • 22% | -8%

Cloverdale

  • 13% | 2%

Sebastopol 16% | 36% % vs. Sonoma County % vs. Bay Area

LEGEND

Jurisdiction VMT Santa Rosa 13.4* Healdsburg 14.0* Bay Area 15.3 Cloverdale 15.6* Windsor 16.6* Rohnert Park 17.6 Sonoma County 17.9* Petaluma 19.1* Sonoma 19.3* Cotati 19.6* Unincorporated 20.1* Sebastopol 20.8 * CHTS data suggests higher VMT per capita. MTC model may be truncating trips.

MTC Model: Residence-Based VMT

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SLIDE 20

INNOVA VATION B BY

Cotati

  • 8% | -10%

Windsor

  • 11% | -13%

Unincorporated 13% | 12% Petaluma 11% | 9% Rohnert Park

  • 6% | -8%

Sonoma 30% | 28% Santa Rosa

  • 20% | -21%

Healdsburg

  • 3% | -5%

Cloverdale

  • 40% | -41%

Sebastopol 13% | 11% % vs. Sonoma County % vs. Bay Area

LEGEND

Jurisdiction VMT Cloverdale 13.3 Santa Rosa 17.9 Windsor 19.8 Cotati 20.5 Rohnert Park 20.9 Healdsburg 21.6 Sonoma County 22.4 Bay Area 22.7 Petaluma 24.7 Sebastopol 25.2 Unincorporated 25.3 Sonoma 29.1

MTC Model: Worker-Based VMT

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SLIDE 21

INNOVA VATION B BY

Project’s ‘Au Autom

  • mobi
  • bile’

le’ VM VMT  AB 32 AB 32  Gover ernor’s

  • r’s E

EOs  SB 375 T 75 Targets  SB 743 O 43 Objectives  Calt ltra rans S SMP P Targe rget  Loc

  • cal C

CAP APs  ARB M Mobile bile Source Strate tegy

VMT

Thresholds

OPR is basing their recommendations

  • n subst

stan antial ial e evidence based on adopted State plans, pending State plans, and Executive Orders of the current and previous governors.

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SLIDE 22

INNOVA VATION B BY

OPR GUIDANCE

Thresholds

OPR OPR suggests a threshold of 15 percent b belo low b baselin ine (cond nditions ns when n NOP i is s relea eased ed) But, thresholds in the Technical Advisory are non

  • n-bindin

ing. In general, the 15 percent reduction threshold is tied to statewide greenhouse gas reduction goals.

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SLIDE 23

INNOVA VATION B BY

VMT FORECASTING

Methods

So, it is up to the lead agency to decide on what quantification methodology they want to use (with substantial supporting evidence) Thresholds must be based on this method

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SLIDE 24

INNOVA VATION B BY

OPR GUIDANCE

Thresholds

YES ES: No im impac act. No VMT Analysis NO: Further Analysis Needed.

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SLIDE 25

INNOVA VATION B BY

 Tran ansi sit Se Service ce  Bic icycle le F Facil ilit ities  Pedes estria ian F Facili lities ies  Safety

  • Dire

irect

  • Indire

ndirect

OTHER MODES AND SAFETY

Thresholds

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SLIDE 26

INNOVA VATION B BY

TRIPS OR TRIP LENGTH

Mitigation

The project needs to change in some way.

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SLIDE 27

INNOVA VATION B BY

De Dens nsity Distance to T Transit Destinations Diversity Design gn Demograph phics cs Develop

  • pment

Scal ale

7Ds Ds

Tha That i infl fluence T Tri rip Ge Gene neration ( (and nd VM VMT) BUILT ENVIRONMENT

Mitigation

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SLIDE 28

INNOVA VATION B BY

SB 743

UNCERTAINTY

What about disruptive trends?

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SLIDE 29

INNOVA VATION B BY

PROJECT TYPES

Examples

 16-unit it R Residen dentia ial  Ju Just Ov Over 1 r 100 Trip rip Thre Threshold ld  Not in in TP TPA  Auto V VMT T for home me- ba based t trips rips  Use average ge t trip rip le lengt ngth x x trip rip ge gen  “Spreadsheet” Ap Approach

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SLIDE 30

INNOVA VATION B BY

PROJECT TYPES

Examples

 Of Offic ice B Build ildin ing  Ov Over 1 r 100 T Trip rip Thre Threshold ld  Does

  • es n

not

  • t m

meet eet scre reeni ning c crit riteri ria  Au Auto V

  • VMT for work

rk- ba based t trips rips fro rom employees  Ca Can u use a averages o

  • r

mode del ru runs ns, , dep epending on

  • n size

e and c comp mplexi xity

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SLIDE 31

INNOVA VATION B BY

PROJECT TYPES

Examples

 Re Retail  Over 5 50,00 000 s 0 square feet eet  Does no not m meet othe her r scre reeni ning c crit riteri ria  EITHE THER  All V ll VMT T ge gene nera rated b by sit ite (O/ O/D o

  • r

r Trip rip Averag ages) s)  Cu Cumu mulative e effect in in are rea ( (bo boundary method)

  • d)
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SLIDE 32

INNOVA VATION B BY

PROJECT TYPES

Examples

 Transpor portation

  • n

Infras astruc uctur ure  Does

  • es t

the e proj

  • ject a

add roadw dway c capacit ity? y?  Does

  • es t

the e proj

  • ject h

have po potential t l to indu induce demand? d?  Bik ike/Ped projec ects, ro road die diets, t tra ransit proj

  • jects d

do n

  • not
  • t

re requ quir ire V VMT T ana nalysis  OPR OPR is is still ill devel elopin

  • ping g

g guidance e for o r othe her r transpor portation ion proj

  • ject t

typ ypes es

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SLIDE 33

INNOVA VATION B BY

SB 743

Latest Developments

  • Calt

ltrans I s IGR R comments

  • Status o

s of fina inal l gu guid idanc nce f from O OPR

  • Status o

s of gr grace perio iod

http://www.dot.ca.gov/hq/tpp/sb743.html

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SLIDE 34

INNOVA VATION B BY

SB 743

Addressing VMT Impacts

How h have VMT im VMT impacts been addre n addressed?

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SLIDE 35

INNOVA VATION B BY

SB 743

Caltrans Letter

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SLIDE 36

INNOVA VATION B BY

SB 743

Caltrans Letter

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SLIDE 37

INNOVA VATION B BY

SB 743

Nishi Site (Land Use Project)

Basically, a ana nalyze VM VMT a and nd u use T TDM a as miti itigation

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SLIDE 38

INNOVA VATION B BY

SB 743

City of Woodland General Plan

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SLIDE 39

INNOVA VATION B BY

SB 743

Q&A

Questio ions? ns?

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SLIDE 40

INNOVA VATION B BY

What’s the difference between SB 375 and SB 743?

  • SB 375 establishes greenhouse gas reduction

expectations

  • Targets are based on 2005 conditions
  • VMT is only part of mobile source emissions
  • SB 743 changes CEQA transportation impact analysis
  • Prohibition on using vehicle LOS as the sole basis
  • Focus on automobile travel (i.e., passenger cars and

light trucks) and specific types of land uses

  • Comparing project effects to baseline

IMPACT ANALYSIS & MITIGATION

Change

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SLIDE 41

INNOVA VATION B BY

Data

AVAILABLE SOURCES

Are there general guidelines for when a model should be used?

  • For a 15-unit development: probably not due to the

aggregate nature of models

  • For a 200-unit development: possibly but still may not

be appropriate

  • For a 500-unit development: probably
  • For a large specific plan or general plan: most likely
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SLIDE 42

INNOVA VATION B BY

Data

AVAILABLE SOURCES

How do we quantify VMT for a 15-unit development that would trigger the 100 trip threshold?

  • OPR recommends using the same methodology for

setting thresholds, performing project estimates and evaluating mitigation

  • Model may be appropriate but could have limited

sensitivity for a project of this size

  • A spreadsheet model that relies on Countywide model

data such as trip lengths by TAZ could be used

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SLIDE 43

INNOVA VATION B BY

Belvedere 35% | 59% Tiburon 12% | 32% Corte Madera

  • 10% | 7%

Unincorporated 18% | 40% Larkspur

  • 5% | 13%

Mill Valley

  • 9% | 8%

Ross

  • 13% | 3%

San Anselmo

  • 7% | 10%

San Rafael

  • 7% | 10%

Novato

  • 3% | 15%

Sausalito 42% | 68% Fairfax 1% | 20%

% vs. Marin County % vs. Bay Area

LEGEND

Area VMT Per Trip Bay Area 5.4 Ross 5.6 Corte Madera 5.8 Mill Valley 5.8 San Anselmo 5.9 San Rafael 6.0 Larkspur 6.1 Novato 6.2 Marin County 6.4 Fairfax 6.5 Tiburon 7.2 Unincorporated 7.6 Belvedere 8.6 Sausalito 9.1

TRAVEL MODEL ONE PER TRIP: O-D BASED

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SLIDE 44

INNOVA VATION B BY

Belvedere 2% | 20% Tiburon 4% | 22% Corte Madera

  • 7% | 9%

Unincorporated 12% | 32% Larkspur

  • 19% | -4%

Mill Valley

  • 19% | -4%

Ross

  • 17% | -3%

San Anselmo

  • 16% | -1%

San Rafael 1% | 19% Novato 26% | 48% Sausalito 5% | 23% Fairfax

  • 14% | 1%

% vs. Marin County % vs. Bay Area

LEGEND

Area VMT Per Trip Mill Valley 6.6 Larkspur 6.6 Ross 6.7 San Anselmo 6.8 Bay Area 6.9 Fairfax 7.0 Corte Madera 7.5 Marin County 8.1 San Rafael 8.2 Belvedere 8.3 Tiburon 8.4 Sausalito 8.5 Unincorporated 9.1 Novato 10.2

MOBILE DEVICE DATA PER TRIP: O-D BASED

Model VMT Per Trip 5.8 6.1 5.6 5.9 5.4 6.5 5.8 6.4 6.0 8.6 7.2 9.1 7.6 6.2 Delta 0.8 0.5 1.1 0.9 1.5 0.5 1.7 1.7 2.2

  • 0.3

1.2

  • 0.6

1.5 4.0

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SLIDE 45

INNOVA VATION B BY

Census Journey-to-Work Data

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SLIDE 46

INNOVA VATION B BY

Census Journey-to-Work Data

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SLIDE 47

INNOVA VATION B BY

Belvedere

  • 64% | -56%

Tiburon

  • 80% | -76%

Corte Madera

  • 64% | -56%

Unincorporated

  • 50% | -38%

Larkspur

  • 63% | -54%

Mill Valley

  • 38% | -24%

Ross

  • 76% | -71%

San Anselmo

  • 64% | -56%

San Rafael

  • 65% | -57%

Novato

  • 70% | -64%

Sausalito

  • 78% | -73%

Fairfax

  • 51% | -39%

% vs. Marin County % vs. Bay Area

LEGEND

Area Total VMT VMT per Capita Tiburon

53,000 5.8

Sausalito

46,000 6.4

Ross

17,000 7.0

Novato

470,000 8.7

San Rafael

610,000 10.3

Belvedere

22,000 10.5

Corte Madera

100,000 10.6

San Anselmo

133,000 10.6

Larkspur

133,000 10.9

Fairfax

110,000 14.5

Unincorporated

1,000,000 14.7

Mill Valley

260,000 18.2

Bay Area

170,000,000 23.8

Marin County

7,575,000 29.3

State Highways

4,528,000

  • HPMS: BOUNDARY METHOD

VMT on State Highways reported separately Likely due to visitors