HomeMy WebLinkAbout2020-07-08 Planning & transportation commission Agenda Packet_______________________
1. Spokespersons that are representing a group of five or more people who are identified as present at the meeting at the
time of the spokesperson’s presentation will be allowed up to fifteen (15) minutes at the discretion of the Chair, provided
that the non-speaking members agree not to speak individually.
2. The Chair may limit Oral Communications to 30 minutes for all combined speakers.
3. The Chair may reduce the allowed time to speak to three minutes or less to accommodate a larger number of speakers.
Planning & Transportation Commission
Regular Meeting Agenda: July 8, 2020
Virtual Meeting
6:00 PM
https://zoom.us/join Meeting ID: 955 0337 0484 Phone number: 1 669 900 6833
****BY VIRTUAL TELECONFERENCE ONLY***
Pursuant to the provisions of California Governor’s Executive Order N-29-20,
issued on March 17, 2020, to prevent the spread of Covid-19, this meeting will be
held by virtual teleconference only, with no physical location. The meeting will be
broadcast live on Cable TV Channel 26 and Midpen Media Center at
https://midpenmedia.org/local-tv/watch-now/.
Members of the public may comment by sending an email to
planning.commission@cityofpaloalto.org or by attending the Zoom virtual
meeting to give live comments. Instructions for the Zoom meeting can be found
on the last page of this agenda.
TIME ESTIMATES
Listed times are estimates only and are subject to change at any time, including while the
meeting is in progress. The Commission reserves the right to use more or less time on any item,
to change the order of items and/or to continue items to another meeting. Particular items may
be heard before or after the time estimated on the agenda. This may occur in order to best
manage the time at a meeting or to adapt to the participation of the public.
Call to Order / Roll Call
Oral Communications
The public may speak on items not on the agenda. Each member of the public may address the Commission for up
to three (3) minutes per speaker.1,2
Agenda Changes, Additions, and Deletions
The Chair or Commission majority may modify the agenda order to improve meeting management.
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1. Spokespersons that are representing a group of five or more people who are identified as present at the meeting at the
time of the spokesperson’s presentation will be allowed up to fifteen (15) minutes at the discretion of the Chair, provided
that the non-speaking members agree not to speak individually.
2. The Chair may limit Oral Communications to 30 minutes for all combined speakers.
3. The Chair may reduce the allowed time to speak to three minutes or less to accommodate a larger number of speakers.
City Official Reports 6:00PM-6:15 PM
1. Directors Report, Meeting Schedule and Assignments
Study Session
Public Comment is permitted. Each member of the public may address the Commission for up to five (5) minutes
per speaker.1,3
6:15PM-7:15 PM
2. Study Session on Update to the City’s Transportation Analysis Methodology Under
CEQA to Comply with California Senate Bill 743
7:15PM-8:45 PM
3. Study Session on Plan Bay Area 2050 and the State 6th Cycle Regional Housing Needs
Allocation (RHNA) Process
Action Items
Public Comment is permitted. Applicants/Appellant Teams: Fifteen (15) minutes, plus three (3) minutes rebuttal.
All others: Up to five (5) minutes per speaker.1,3
Approval of Minutes 8:45PM-8:50 PM
Public Comment is Permitted. Three (3) minutes per speaker.1,3
4. June 10, 2020 Draft PTC Meeting Minutes
Committee Items
Commissioner Questions, Comments, Announcements or Future Agenda Items
8:50PM-9:05 PM
Adjournment
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1. Spokespersons that are representing a group of five or more people who are identified as present at the meeting at the
time of the spokesperson’s presentation will be allowed up to fifteen (15) minutes at the discretion of the Chair, provided
that the non-speaking members agree not to speak individually.
2. The Chair may limit Oral Communications to 30 minutes for all combined speakers.
3. The Chair may reduce the allowed time to speak to three minutes or less to accommodate a larger number of speakers.
Palo Alto Planning & Transportation Commission
Commissioner Biographies, Present and Archived Agendas and Reports are available online:
http://www.cityofpaloalto.org/gov/boards/ptc/default.asp. The PTC Commission members are:
Chair Carolyn Templeton
Vice Chair Giselle Roohparvar
Commissioner Michael Alcheck
Commissioner Bart Hechtman
Commissioner Ed Lauing
Commissioner William Riggs
Commissioner Doria Summa
Get Informed and Be Engaged!
View online: http://midpenmedia.org/category/government/city-of-palo-alto/ or on Channel
26.
Public comment is encouraged. Email the PTC at: Planning.Commission@CityofPaloAlto.org.
Material related to an item on this agenda submitted to the PTC after distribution of the
agenda packet is available for public inspection at the address above.
Americans with Disability Act (ADA)
It is the policy of the City of Palo Alto to offer its public programs, services and meetings in a
manner that is readily accessible to all. Persons with disabilities who require materials in an
appropriate alternative format or who require auxiliary aids to access City meetings, programs,
or services may contact the City’s ADA Coordinator at (650) 329-2550 (voice) or by emailing
ada@cityofpaloalto.org. Requests for assistance or accommodations must be submitted at least
24 hours in advance of the meeting, program, or service.
_______________________
1. Spokespersons that are representing a group of five or more people who are identified as present at the meeting at the
time of the spokesperson’s presentation will be allowed up to fifteen (15) minutes at the discretion of the Chair, provided
that the non-speaking members agree not to speak individually.
2. The Chair may limit Oral Communications to 30 minutes for all combined speakers.
3. The Chair may reduce the allowed time to speak to three minutes or less to accommodate a larger number of speakers.
Public Comment Instructions
Members of the Public may provide public comments to teleconference meetings via email,
teleconference, or by phone.
1. Written public comments may be submitted by email to
planning.commission@CityofPaloAlto.org
2. Spoken public comments using a computer will be accepted through the
teleconference meeting. To address the Board, click on the link below for the
appropriate meeting to access a Zoom-based meeting. Please read the following
instructions carefully.
A. You may download the Zoom client or connect to the meeting in-browser. If
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may be disabled in older browsers including Internet Explorer.
B. You will be asked to enter an email address and name. We request that you
identify yourself by name as this will be visible online and will be used to notify
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C. When you wish to speak on an agenda item, click on “raise hand”. The
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D. When called, please limit your remarks to the time limit allotted.
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3. Spoken public comments using a smart phone will be accepted through the
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below. Please follow instructions B-E above.
4. Spoken public comments using a phone use the telephone number listed below. When
you wish to speak on an agenda item hit *9 on your phone so we know that you wish to
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remarks to the agenda item and time limit allotted.
https://zoom.us/join
Meeting ID: 955 0337 0484 Phone number: 1 669 900 6833 (you may need to exclude the
initial “1” depending on your phone service)
Planning & Transportation Commission
Staff Report (ID # 11475)
Report Type: City Official Reports Meeting Date: 7/8/2020
City of Palo Alto
Planning & Development Services
250 Hamilton Avenue
Palo Alto, CA 94301
(650) 329-2442
Summary Title: City Official Report
Title: Directors Report, Meeting Schedule and Assignments
From: Jonathan Lait
Recommendation
Staff recommends that the Planning and Transportation Commission (PTC) review and
comment as appropriate.
Background
This document includes the following items:
• PTC Meeting Schedule
• PTC Representative to City Council (Rotational Assignments)
• Tentative Future Agenda
Commissioners are encouraged to contact Vinh Nguyen (Vinhloc.Nguyen@CityofPaloAlto.org)
of any planned absences one month in advance, if possible, to ensure availability of a PTC
quorum.
PTC Representative to City Council is a rotational assignment where the designated
commissioner represents the PTC’s affirmative and dissenting perspectives to Council for quasi-
judicial and legislative matters. Representatives are encouraged to review the City Council
agendas (http://www.cityofpaloalto.org/gov/agendas/council.asp) for the months of their
respective assignments to verify if attendance is needed or contact staff. Prior PTC meetings are
available online at http://midpenmedia.org/category/government/city-of-palo-alto/boards-
and-commissions/planning-and-transportation-commission.
The Tentative Future Agenda provides a summary of upcoming projects or discussion items.
Attachments:
• Attachment A: July 8, 2020 PTC Meeting Schedule and Assignments (DOCX)
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Planning & Transportation Commission
2020 Meeting Schedule & Assignments
2020 Schedule
Meeting Dates Time Location Status Planned Absences
1/08/2020 6:00 PM Council Chambers Cancelled
1/29/2020 6:00 PM Council Chambers Regular
2/12/2020 6:00 PM Council Chambers Regular Riggs
2/26/2020 6:00 PM Council Chambers Regular
3/11/2020 6:00 PM Council Chambers Cancelled
3/25/2020 6:00 PM Council Chambers Cancelled
4/8/2020 6:00 PM Council Chambers Cancelled
4/15/2020 6:00 PM Council Chambers Cancelled
4/29/2020 6:00 PM Virtual Meeting Regular Riggs
5/13/2020 6:00 PM Virtual Meeting Regular
5/27/2020 6:00 PM Virtual Meeting Regular
6/10/2020 6:00 PM Virtual Meeting Regular
6/24/2020 6:00 PM Virtual Meeting Regular
7/08/2020 6:00 PM Virtual Meeting Regular
7/29/2020 6:00 PM Virtual Meeting Regular Hechtman
8/12/2020 6:00 PM Virtual Meeting Regular
8/20/2020 9:00 AM Virtual Meeting ARB Joint Study Session
8/26/2020 6:00 PM Virtual Meeting Regular
9/9/2020 6:00 PM To Be Determined Regular
9/30/2020 6:00 PM To Be Determined Regular
10/14/2020 6:00 PM To Be Determined Regular
10/28/2020 6:00 PM To Be Determined Regular
11/11/2020 6:00 PM Cancelled Cancelled Veteran’s Day
11/25/2020 6:00 PM Cancelled Cancelled Day Before Thanksgiving
12/09/2020 6:00 PM To Be Determined Regular
12/30/2020 6:00 PM Cancelled Cancelled Day Before New Year’s Eve
2020 Assignments - Council Representation (primary/backup)
January February March April May June
Doria Summa Billy Riggs Michael Alcheck Billy Riggs Ed Lauing Cari Templeton
Michael Alcheck Cari Templeton Ed Lauing Bart Hechtman Giselle Roohparvar Doria Summa
July August September October November December
Giselle Roohparvar Doria Summa Bart Hechtman Michael Alcheck Billy Riggs Ed Lauing
Bart Hechtman Michael Alcheck Billy Riggs Ed Lauing Cari Templeton Giselle Roohparvar
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Planning & Transportation Commission
2020 Tentative Future Agenda
The Following Items are Tentative and Subject to Change:
Meeting Dates Topics
August 12, 2020 • Ordinance Amending 18.42.110 (Wireless Communication Facilities)
Upcoming items:
Topics
• Receive Castilleja Final Environmental Impact Report and Applicant’s Presentation
• Recommendation on Castilleja Tentative Map, Conditional Use Permit and Variance
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Planning & Transportation Commission
Staff Report (ID # 11453)
Report Type: Study Session Meeting Date: 7/8/2020
City of Palo Alto
Planning & Development Services
250 Hamilton Avenue
Palo Alto, CA 94301
(650) 329-2442
Summary Title: Senate Bill 743 Implementation
Title: Study Session on Update to the City’s Transportation Analysis
Methodology Under CEQA to Comply with California Senate
Bill 743
From: Philip Kamhi
Recommendation
Staff recommends the Planning and Transportation Commission (PTC) conduct a study session
to receive a presentation and to discuss:
• Vehicle Miles Traveled (VMT) as the new metric for conducting transportation analyses
under the California Environmental Quality Act (CEQA),
• CEQA thresholds of significance related to VMT, and
• Screening criteria to limit review for projects presumed to have a ‘less-than-significant’
VMT impact based on substantial evidence.
Summary
Based on revisions in State law to implement Senate Bill (SB) 743, public agencies in California
must use vehicle miles traveled (VMT) as the metric for CEQA transportation analyses starting
July 1, 2020. In addition, the State prohibited the use of Level of Service (LOS) as a threshold
of significance for performing CEQA transportation analyses. On June 15, 2020, after its May
18 study session on VMT, the City Council adopted new thresholds of significance for CEQA
transportation analyses. The Council also adopted a separate Local Transportation Analysis
(LTA) Policy, which retains LOS to determine if projects create local transportation impacts.
This report supports staff’s presentation to the PTC. The PTC’s purview includes review of
certain development projects and associated CEQA analyses, reports, and other
documentation. Staff’s intention is that this presentation will provide the PTC a knowledge base
regarding VMT and understanding associated thresholds for development review.
When lead agencies prepare CEQA documents, they are required to identify feasible
mitigation measures to avoid or substantially reduce VMT impacts above the adopted CEQA
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thresholds of significance. Transportation Demand Management (TDM) programs are a critical
component to achieve VMT reduction targets, thus potentially reducing a project’s significant
environmental impacts. Staff will bring forward a TDM Ordinance with draft mitigation
policies and a menu of mitigation measures in alignment with the new CEQA methodology to
PTC and Council in the fall.
Council’s adoption of the VMT thresholds of significance under CEQA and the LTA Policy was
the first in a series of critical actions related to transportation in the coming year. The PTC
received staff’s presentation on the 2020 Sustainability and Climate Action Plan (S/CAP). Staff
will return to Council later this year for adoption of that plan.
Background
Greenhouse Gas Emission Reduction
Pursuant to California Senate Bill (SB) adoptions in 2013 and 2018 (SB 743 and SB 375), the
focus of CEQA transportation analyses shifted from vehicle delay to reducing greenhouse gas
(GHG) emissions, creation of multimodal transportation networks, and promotion of a mix of
land uses that reduces the need to drive. SB 743 required the Governor’s Office of Planning
and Research (OPR) to prepare amendments to the CEQA guidelines with respect to
transportation analyses to use an alternative metric to LOS that better balances the needs of
congestion management with statewide goals related to GHG emission reduction targets per
SB 375.
The California Air Resources Board (CARB) adopted the State’s current GHG reduction targets
at the March 22, 2018 Board Hearing. Subsequently in late 2018, the California Natural
Resources Agency adopted OPR’s recommended updates to the CEQA Guidelines. The
updated Guidelines became effective on December 28, 2018 and require agencies to use
vehicle miles traveled (VMT) as the metric for CEQA transportation analyses by July 1, 2020.
Palo Alto’s goals for greenhouse gas emission reductions are more aggressive than state goals
(as outlined in the adopted S/CAP Framework). Therefore, Council may choose to realign VMT
thresholds of significance following completion of the S/CAP Update to better meet reductions
targets. More detailed information on the S/CAP Update is available in the staff report to
Council in June 2020 (CMR #114041).
Understanding LOS and VMT
OPR has posted video presentations explaining the rationale for the move away from LOS and
towards VMT. Staff encourages Commission members to view these videos in order as they
provide an excellent introduction to this topic:
• Problems with LOS – https://tinyurl.com/Problems-with-LOS
• Benefits of VMT – https://tinyurl.com/Benefits-of-VMT
• Methods for Land Use Projects – https://tinyurl.com/Methods-for-Land-Use-Projects
1 https://tinyurl.com/SCAP-Update-June-2020
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Council Review of VMT, Screening Criteria and Thresholds of Significance
• May 18, 2020: At the Council study session on May 18, 2020, Transportation staff and
the City’s consultant, Fehr and Peers, presented materials on the legislative change
which included:
(1) goals and requirements of the new CEQA statute,
(2) technical advice for compliance from the Office of Planning and research (OPR), and
(3) the City’s proposed approach to VMT implementation.
Council discussed staff’s likely recommendation that screening criteria and thresholds of
significance should parallel the OPR technical advisory document, which can be found
here: https://tinyurl.com/OPR-Technical-Advisory.
• June 15, 2020: Council adopted staff’s recommendation for screening criteria and
thresholds of significance by Resolution.
For additional information, staff reports for the Council study session and hearing can be
found here:
• Council Study Session on May 18, 2020 (CMR #113332)
• Council Meeting on June 15, 2020 (CMR #112563)
Discussion
Council adopted thresholds of significance for VMT that align with the State’s
recommendations and screening criteria for projects that may be presumed to have a less
than significant VMT impact outlined in tables 1 and 2 below. Substantial evidence to support
the establishment of these thresholds was included in Attachment C in staff report (CMR
#11256) to Council in June 2020.
Screening Criteria
The Governor’s Office of Planning and Research (OPR) recommends agencies use screening
criteria to identify projects known to reduce VMT or be low VMT generators and that are thus
expected to have a less than significant VMT impact and would exempt such projects from
quantitative VMT analyses. The use of screening criteria streamlines project analysis for projects
that are already presumed to have a less than significant impact on VMT, based on substantial
evidence. Comprehensive Plan policies encourage housing development to protect local-serving
retail and to reduce traffic on the roadway network. Therefore, staff recommended and Council
adopted screening criteria so these types of projects that are aligned with City policies do not
have to procure costly and redundant transportation analyses that will show they are low-VMT
generators under CEQA.
2 https://tinyurl.com/SB-743-Study-Session
3 https://tinyurl.com/SB-743-Council-Adoption
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If a project meets the adopted screening criteria, a quantitative VMT analysis will not be
required; however, the CEQA analysis will include a qualitative discussion of VMT, discussing the
site and its location characteristics. If substantial evidence showed that the presumption did not
apply for a particular project, a quantitative analysis will be completed.
According to the Local Transportation Analysis adopted by Council in Attachment B, staff may
still analyze these projects for consistency with LOS standards established in the LTA Policy. If the
project is found to exceed LOS standards established in the LTA Policy, conditions of approval
may be required for a project to enable remediation and therefore address consistency with the
LTA Policy.
Because of the City’s land uses and job-housing imbalance, staff recommended and Council
adopted slightly adjusted screening criteria based on the City’s development policies. Table 1
below presents a comparison between OPR’s suggested screening criteria and staff
recommended (now Council adopted) screening criteria for Palo Alto.
Table 1: Screening Criteria
Land Use/Project
Type
OPR’s Suggested Screening Criteria City Adopted
Screening Criteria
Small Developments Projects that generate fewer than 110 trips
per day. This may equate to non-residential
projects of 10,000 sq. ft., or less and
residential projects of 20 units or less.
Recommend OPR
Criteria
Projects in Low-VMT
Areas
Residential and office projects located in
low-VMT areas4 that have similar features
(i.e., density, mix of uses, transit
accessibility) as existing developments in
these areas.
Recommend OPR
Criteria
4 Residential projects located in areas where baseline VMT is 15% below the existing county average per resident,
and office projects located in areas where baseline VMT is 15% below the existing regional average per employee
could be considered to be in low-VMT areas and presumed to have a less than significant VMT impact.
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Projects in Proximity
to Major Transit
Stops
Projects that are located within a half mile
of an existing or planned high-quality transit
corridor or major transit stations, and meet
the following additional criteria: (1) is high
density (minimum floor area ratio of 0.75),
(2) does not exceed parking requirements,
(3) is consistent with Plan Bay Area 2040
(http://2040.planbayarea.org/), and (4) does
not replace affordable units with smaller
numbers of moderate- or above moderate-
income units.
Recommend OPR
Criteria
Affordable Housing 100% affordable housing projects in infill
locations.
Recommend OPR
Criteria
Local-Serving Retail Retail projects of 50,000 sq. ft. or less. Retail projects of
10,000 sq. ft. or less.5
Transportation
Projects
Roadway, transit, bicycle and pedestrian
projects that do not lead to a measurable
increase in vehicle travel.
Recommend OPR
Criteria
Source: OPR Technical Advisory on Evaluating Transportation Impacts in CEQA, December 2018, and
Palo Alto Comprehensive Plan 2030
Thresholds of Significance
Individual land use projects that are not screened out will require quantitative VMT analyses,
and their VMT must be below pre-determined thresholds to be considered as having a less
than significant impact. OPR’s technical advisory document recommends thresholds that vary
by project and land use type. The recommended OPR thresholds are based on substantial
evidence that aligns CEQA transportation analysis to meet statewide targets for greenhouse
gas (GHG) emission reductions. When applying the thresholds, a project’s VMT is compared to
a baseline VMT value that is typically either a citywide, countywide, or regional average. In
the case of the City of Palo Alto, the “county” would be Santa Clara County and the “region”
would be the nine-county Bay Area. The baseline thresholds are chosen to be the most
environmentally protective and are consistent with the City’s Comprehensive Plan 2030.
Council adopted thresholds of significance for VMT that are consistent with OPR’s
recommendations. These thresholds are outlined in Table 2 below.
Table 2: VMT Thresholds of Significance by Project Type
Land Use/Project
Type
City Adopted VMT Thresholds of Significance
5 OPR indicates that local-serving retail up to 50,000 sq.ft. may be presumed to create less-than-significant VMT
impact. Local-serving retails and lots in Palo Alto are typically smaller. Thus, staff is recommending 10,000 sq.ft. as
the City’s local-serving retail screening criteria, which also constitutes a small project that would be screened out
under CEQA.
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Residential Projects A proposed project exceeding a level of 15% below existing (baseline)
County home-based VMT per resident may indicate a significant
transportation impact.
Office Projects A proposed project exceeding a level of 15% below existing (baseline)
regional home-based work VMT per employee may indicate a
significant transportation impact.
Retail Projects A proposed project that results in a net increase in total (boundary)
VMT may indicate a significant transportation impact.
Mixed-Use Projects Each component of a proposed mixed-use project should be
evaluated independently and apply thresholds of significance for
each project type separately (i.e., residential, office, and retail).
Other Project Types The City will either develop an ad hoc (i.e., project specific) VMT
threshold for a unique land use type or apply the most applicable of
the above thresholds depending on project characteristics.
Redevelopment
Projects
Where a proposed project replaces existing VMT-generating land
uses, if the replacement leads to a net overall decrease in VMT, the
project may cause a less than significant transportation impact. If the
redevelopment project leads to a net overall increase in VMT, it may
cause a significant transportation impact if proposed new residential,
office, or retail land uses would individually exceed their respective
thresholds.
The City’s Sustainability and Climate Action Plan (S/CAP) Framework has GHG emission
reduction goals that are more aggressive than statewide goals. Therefore, Council may
consider refining VMT thresholds of significance in the future to reflect GHG emissions
reductions goals in the S/CAP Update, once it has been adopted.
Transportation Demand Management and Mitigation Measures
For a project analyzed under CEQA that yields transportation impacts greater than the City’s
adopted thresholds defined in the section above, the project is said to result in significant
VMT impact and must identify mitigation measures to avoid or substantially reduce these
effects.
The City has discretion in selecting VMT mitigation measures. The most common strategies
for mitigating VMT impacts include:
1. Change the project land use mix or density,
2. Reduce proposed vehicle parking supply levels,
3. Implement on-site or off-site capital improvements for transit, bicycle, or pedestrian
travel, and/or
4. Implement trip reduction programs usually as a Transportation Demand Management
(TDM) program. TDM programs can include several components such as
telecommuting, transit subsidies, shuttles, carpool matching, parking cash-out
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programs, and unbundled parking.6
As currently mandated in the City’s Municipal Code and further defined in the City’s
Comprehensive Plan Program T-1.2.3, a project is subjected to a specific percentage reduction
in peak hour vehicle trips using TDM programs if a project:
1. Generates 50 or more net new peak hour trips, or
2. Claims a reduction in net new trips due to proximity to public transit, or
3. Requests a parking reduction.
Staff will return to PTC and Council with a TDM Ordinance in the fall of 2020. The ordinance
will include a menu of mitigation measures designed to effectively reduce VMT impacts for
CEQA projects. Additionally, it will incorporate a monitoring structure to ensure TDM plans for
local development projects are compliant with City plans and policies. Per Comprehensive
Plan Program T.1.2.3, the TDM Ordinance will also require new projects citywide to reduce
the number of peak hour vehicle trips by 20% to 45% depending on the location in the City.
Policy Implications
The City’s Comprehensive Plan 2030, adopted in December 2017, already acknowledged and
incorporated the regulatory changes mandated by SB 743. While the Comprehensive Plan noted
that VMT would be used as the metric for analyzing potential transportation impacts under
CEQA, the Plan directed adoption of LOS standards to analyze the potential for local-level project
consistency. Council’s adoption of the LTA Policy has accomplished this task.
This item supports the following Comprehensive Plan goals, policies, and programs:
GOAL T-1: Create a sustainable transportation system, complemented by a mix of land uses,
that emphasizes walking, bicycling, use of public transportation and other methods to reduce
GHG emissions and the use of single-occupancy motor vehicles.
Policy T-1.3: Reduce GHG and pollutant emissions associated with transportation by reducing
VMT and per-mile emissions through increasing transit options, supporting biking and walking,
and the use of zero-emission vehicle technologies to meet City and State goals for GHG
reductions by 2030.
GOAL T-2: Decrease delay, congestion and VMT with a priority on our worst intersections and
our peak commute times, including school traffic.
Policy T-2.3: Use motor vehicle LOS at signalized intersections to evaluate the potential impact
of proposed projects, including contributions to cumulative congestion. Use signal warrants and
other metrics to evaluate impacts at unsignalized intersections.
6 Unbundling parking creates a separation of leasing or purchasing parking spaces from the lease or purchase of
the residential or commercial use.
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Program T2.3.1: When adopting new CEQA significance thresholds for VMT for compliance with
SB 743 (2013), adopt standards for vehicular LOS analysis for use in evaluating the consistency
of a proposed project with the Comprehensive Plan, and also explore desired standards for
MMLOS, which includes motor vehicle LOS, at signalized intersections.
GOAL T-3: Maintain an efficient roadway network for all users.
Policy T-3.3: Avoid major increases in single-occupant vehicle capacity when constructing or
modifying roadways unless needed to remedy severe congestion or critical neighborhood traffic
problems. Where capacity is increased, balance the needs of motor vehicles with pedestrians
and bicyclists.
Policy L-1.9: Participate in regional strategies to address the interaction of jobs, housing balance
and transportation issues.
Policy L-2.3: As a key component of a diverse, inclusive community, allow and encourage a mix
of housing types and sizes, integrated into neighborhoods and designed for greater
affordability, particularly smaller housing types, such as studios, co-housing, cottages, clustered
housing, accessory dwelling units and senior housing.
Policy L-2.4: Use a variety of strategies to stimulate housing, near retail, employment, and
transit, in a way that connects to and enhances existing neighborhoods.
Program L2.4.7: Explore mechanisms for increasing multi-family housing density near
multimodal transit centers.
Policy L-2.5: Support the creation of affordable housing units for middle to lower income level
earners, such as City and school district employees, as feasible.
Policy L-4.2: Preserve ground-floor retail, limit the displacement of existing retail from
neighborhood centers and explore opportunities to expand retail.
Policy L-4.5: Support local-serving retail, recognizing that it provides opportunities for local
employment, reduced commute times, stronger community connections and neighborhood
orientation.
Program L4.5.1: Revise zoning and other regulations as needed to encourage the preservation
of space to accommodate small businesses, start-ups and other services.
Resource Impact
This work to develop VMT methodology, thresholds, and mitigation measures to implement SB
743 is funded through the current S/CAP consultant contract with AECOM (Fehr & Peers is a
subconsultant to AECOM). Implementation of SB 743 and new CEQA Guidelines will involve the
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use of the VTA VMT Estimation Tool and staff training. Along with other jurisdictions in Santa
Clara County, the City paid additional Congestion Management Program (CMP) dues to VTA in
Fiscal Year 2020 (FY20) to support development of the estimation tool. Use of the estimation
tool does not incur any additional expense. Training costs would be absorbed by the Office of
Transportation and Planning and Development Services Department in the FY 2021 budget.
Funding for future years or any additional expenses is subject to City Council approval through
the annual budget development process. The cost of performing VMT and other environmental
analysis under CEQA for private development projects would be billed to applicants in
accordance with the City’s standard application review cost recovery process.
Timeline
Staff will return to PTC and Council with a Transportation Demand Management (TDM)
Ordinance and mitigation measures in the fall. Following the S/CAP Update adoption, staff will
return to PTC and Council for direction on whether to adjust CEQA thresholds of significance
to align with S/CAP policies and to revisit the LTA policy
Environmental Review
The adoption of new transportation screening criteria and reduction thresholds of significance
under the California Environmental Quality Act (CEQA) in accordance with CEQA Guidelines
Section 15064.7 does not require environmental review. This activity is not a project pursuant
to State CEQA Guidelines Sections 15060(c)(3) and 15378. The establishment and
implementation of a VMT threshold is a state-mandated requirement under SB 743 and Section
15064.3 of the CEQA Guidelines.
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Planning & Transportation Commission
Staff Report (ID # 11400)
Report Type: Study Session Meeting Date: 7/8/2020
City of Palo Alto
Planning & Development Services
250 Hamilton Avenue
Palo Alto, CA 94301
(650) 329-2442
Summary Title: Study Session on Plan Bay Area 2050 & the State 6th Cycle
Regional Housing Needs Allocation Process
Title: Study Session on Plan Bay Area 2050 and the State 6th Cycle
Regional Housing Needs Allocation (RHNA) Process
From: Jonathan Lait
Recommendation
Staff recommends the Planning and Transportation Commission (PTC) receive the staff report
and hold a study session on the Plan Bay Area 2050 process and the State 6th Cycle Regional
Housing Needs Allocation (RHNA) process.
Report Summary
This report provides an overview of two planning processes: (1) the regional Plan Bay Area 2050
process and (2) the 6th Cycle Regional Housing Needs Allocation (RHNA) process. Plan Bay Area
2050 and the RHNA process are two distinct, yet related processes. Together, these processes
seek to help Palo Alto and the Bay Area plan and prepare for regional changes.
The report and study session prepare the Planning and Transportation Commission (PTC) and
Palo Alto community for the upcoming release of the Plan Bay Area 2050 Draft Blueprint and
the release of the Draft Regional Housing Needs Allocation methodology (Draft RHNA
methodology). Likewise, this report and study session allow the PTC and members of the public
to provide feedback and ask questions regarding these processes. The report explains both
planning efforts and their associated components.
Palo Alto staff will endeavor to answer questions and relay additional questions and feedback
to the Association of Bay Area Governments (ABAG) and Metropolitan Transportation
Commission (MTC). Staff hope through discussion, to gain an understanding of PTC and
community perspectives on the information available to date.
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Lastly, the study session and report can help prepare the PTC and Palo Alto community
members to participate in the public outreach activities hosted by ABAG/MTC regarding these
regional planning processes. This discussion is timely, as the Plan Bay Area 2050 Draft Blueprint
and the Draft RHNA methodology to allocate housing needs to local jurisdictions are anticipated
to be released during summer 2020 and fall 2020, respectively. The report adds to an
informational report transmitted to City Council on June 22, 2020.1
Background
A. Plan Bay Area 2050
Plan Bay Area 2050 is the San Francisco Bay Area’s update to its “sustainable communities
strategy” and its “regional transportation plan.” Senate Bill 375 (2008)2 requires each
metropolitan planning organization in California adopt a “sustainable communities strategy” in
conjunction with a regional transportation plan in order to achieve greenhouse gas emission
reduction targets established by the California Air Resources Board. ABAG serves as the San
Francisco Bay Area’s metropolitan planning organization and MTC serves as the regional
transportation agency. 3 Plan Bay Area 2040 serves as the current regional transportation plan
and sustainable communities strategy, but the plans require periodic updates. The update,
currently underway, is led by ABAG/MTC.4
Plan Bay Area 2050 will outline the strategies for regional growth and investment through the
year 2050. Plan Bay Area 2050 focuses on four key issues: the economy, the environment,
housing and transportation. It proposes to identify pathways to promote equity for residents
and greater regional resiliency. Plan Bay Area 2050 will pinpoint policies and infrastructure
investments necessary to advance the identified goals of a more affordable, connected, diverse,
healthy and vibrant Bay Area. Plan Bay Area 2050 does not change local policies; cities and
counties retain all local land use authority.
MTC/ABAG staff requested direction and received approval in February 2020 to explore 25
strategies outlined in the Draft Blueprint and see how close the strategies could bring the
region toward meeting critical regional goals for transportation, environment, economy, and
housing.5,6 The 25 strategies were organized into nine (9) major objectives with an equity lens:
1 June 22, 2020 Informational Report to City Council:
https://www.cityofpaloalto.org/civicax/filebank/documents/77349
2 Institute for Local Government SB 375 Resource Center website: https://www.ca-ilg.org/sb-375-resource-center
3 California Transportation Commission Regional Transportation Plan (RTP) Guidelines:
https://catc.ca.gov/programs/transportation-planning
4 Plan Bay Area 2050 website: https://www.planbayarea.org/
5 February 14, 2020 Joint MTC Planning Committee with the ABAG Administrative Committee Agenda Item 5b Plan
Bay Area 2050: Draft Blueprint – Strategies staff memo and staff presentation:
https://www.planbayarea.org/sites/default/files/pdfs_referenced/Strategies_for_Plan_Bay_Area_2050_Blueprint-
Feb_2020_Memo_and_Attachement_B.pdf;
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1. Maintain and Optimize Existing Infrastructure
2. Create Healthy and Safe Streets
3. Enhance Regional and Local Transit
4. Reduce Risks from Hazards
5. Reduce Our Impact on the Environment
6. Spur Housing Production and Create Inclusive Communities
7. Protect, Preserve, and Produce More Affordable Housing
8. Improve Economic Mobility
9. Shift the Location of Jobs.
As part of the Draft Blueprint study and preparation, MTC/ABAG staff are working to outline
three fiscally constrained versions of the Blueprint and include different portions of the
strategies within them. Any of the three versions below might move forward in Fall 2020:
(1) Blueprint Basic: Includes available revenues, but does not include new revenues from future
regional measures.
(2) Blueprint Plus Crossing: Includes available revenues as well as new revenues for
transportation, housing, economic development, and environmental resilience, with a key focus
of new transportation monies being for a new trans-bay rail crossing.
(3) Blueprint Plus Fix It First: Includes available revenues as well as new revenues for
transportation, housing, economic development, and environmental resilience, with a key focus
of new transportation monies being for system maintenance.
MTC/ABAG staff anticipate releasing the Draft Blueprint for public comment in Summer 2020,
currently scheduled for July 2020 and running through August 2020. Workshops and other
public engagement opportunities will be provided in a manner consistent with COVID-19 State
and County Orders. Significant digital and online components are planned.
COVID-19 Pandemic and Long-Range Planning
On May 8, 2020, MTC/ABAG staff presented a report to ABAG and MTC on the potential
regional impacts from the COVID-19 pandemic and the 2020 recession.7 MTC/ABAG staff noted
anticipated impacts would primarily affect the early years of Plan Bay Area 2050 due to a rapid
change in baseline economic conditions. Additionally, the ripple effects of some anticipated
impacts, such as growth in telecommuting, could persist in the years and decades ahead.
https://www.planbayarea.org/sites/default/files/pdfs_referenced/Strategies_for_Plan_Bay_Area_2050_Blueprint-
Feb_2020_MTC_Commission_Presentation.pdf
6 Plan Bay Area 2050: Draft Blueprint Fact Sheet (February 2020):
https://www.planbayarea.org/sites/default/files/pdfs_referenced/PBA50_DraftBlueprint_FAQ_Booklet.pdf
7 May 8, 2020 Joint MTC Planning Committee with the ABAG Administrative Committee Meeting Agenda and Video
Recording: https://mtc.ca.gov/whats-happening/meetings/meetings-archive/joint-mtc-planning-committee-abag-
administrative-43
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MTC/ABAG staff noted that the recently completed Horizon Initiative explored strategies for an
uncertain future. MTC/ABAG staff reported four key takeaways that aid the region in planning
for the future in light of the COVID-19 pandemic. These can be read in the June 5, 2020
newsletter. 8 Though COVID-19 inserts uncertainty into the future of the Bay Area, the initiative
to develop and adopt a sustainable communities strategy continues.
B. Regional Housing Needs Allocation (RHNA) Process
Since 1969, the State of California has required local governments to use their Housing
Elements to plan to adequately meet their community’s housing needs. Housing Elements are
required by law to be updated on a set schedule. The RHNA process is part of the state housing
element law used to determine the number of new homes, and the affordability levels of those
homes, local governments must plan and zone for in their Housing Elements. The State
Department of Housing and Community Development (HCD) first determines each region’s
housing need by income level for an 8-year projection period; this is called the “regional
housing need determination.” This projection period is the “RHNA Cycle.” The State of
California is entering its 6th RHNA Cycle, which covers years 2022-2030.
HCD released the Bay Area’s regional housing need determination to ABAG on June 9, 2020
(Attachment A). HCD indicated a minimum regional housing needs determination of 441,176
total units among four income categories (Table 1). As of the release of this staff report, the
ABAG Executive Board has declined to appeal the regional housing needs determination.
Appeals must be received by HCD by July 10, 2020.
Table 1: HCD Regional Housing Need Determination-ABAG: 6-30-2022 to 12-21-2030
Income Category Percent Housing Unit Need
Very-Low* 25.9% 114,442
Low 14.9% 65,892
Moderate 16.5.% 72,712
Above-Moderate 42.6% 188,130
Total 100% 441,176
*Extremely-Low 15.5% Included in Very-Low Category
Notes:
Income Distribution:
Income categories are prescribed by California Health and Safety Code (Section 50093, et seq.). Percents are derived based on
Census/ACS reported household income brackets and county median income, then adjusted on the percent of cost-burdened
households in the region compared with the percent of cost burdened households nationally.
ABAG is responsible for allocating the regional housing need determination amongst San
Francisco Bay Area cities and counties. Toward this goal, ABAG convened the current Housing
8 June 5, 2020 Plan Bay Area 2050 newsletter:
https://content.govdelivery.com/accounts/CAMTC/bulletins/28f234a
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Methodology Committee (HMC) in October 2019.9 The Housing Methodology Committee is
currently evaluating potential RHNA methodologies, any of which could be used for the
allocation of the total number of housing units to each local jurisdiction.
The Housing Methodology Committee started discussing methodology options using ten
factors. The factors are exploratory and help the Committee, jurisdictions, and the public
understand how weighting the different factors could distribute the housing need across the
region. The ten factors are described in Attachment B and are listed below:10
1. Access to High Opportunity Areas – Percentage of a jurisdiction’s households living in High
Resource Census tracts or Highest Resource on the California Tax Credit Allocation
Committee (TCAC)/Housing and Community Development (HCD)Opportunity Map.
2. Divergence Index – Percentage of a jurisdiction’s households living in census tracts where
racial demographics differ greatly from the region and where there is a high proportion of
high-income households compared to the region.
3. Job Proximity – Auto - Share of region’s total jobs that can be accessed from a jurisdiction
by a 30-minute auto commute.
4. Job Proximity – Transit - Share of region’s total jobs that can be accessed from a jurisdiction
by a 45-minute transit commute.
5. Vehicle Miles Travelled (VMT) – Total vehicle miles traveled per worker in a jurisdiction,
estimated for 2020 using Plan Bay Area 2040 data.
6. Jobs-Housing Balance – Ratio of jobs in a jurisdiction to housing units in the jurisdiction.
7. Jobs-Housing Fit – Ratio of low-wage jobs (less than $3,333/month) within a jurisdiction to
the number of low-cost rental units (less than $1,500/month) in the jurisdiction.
8. Future Jobs – Jurisdiction’s share of forecasted regional jobs based on Plan Bay Area 2050.
9. Transit Connectivity – Jurisdiction’s percentage of the region’s total acres in Transit Priority
Areas (TPAs).
10. Natural Hazards – Percentage of acres within a jurisdiction’s urbanized area with low risk
from natural hazards according to the Modified MTC/ABAG Multi-Hazard Index.
In addition to considering these factors, the Housing Methodology Committee is also
considering two potential “income allocation” approaches. Income allocation methodologies
are used to allocate the number of units at each level of housing affordability across the
jurisdictions. As shown in Table 1, the State recognizes 4 income levels. The Discussion section
of this report elaborates on the income allocation approaches.
The Housing Methodology Committee will have an opportunity to continue refining the RHNA
methodology prior to making a recommendation. No decisions or recommendations have been
9 ABAG Regional Housing Needs Allocation (RHNA) Housing Methodology Committee Roster:
https://abag.ca.gov/sites/default/files/hmc_roster_january_2020_0.pdf
10 Explanation of Potential Methodology Factors website: https://rhna-
factors.mtcanalytics.org/data/RHNA_tool_factors_overview.pdf
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made to date. Though ABAG staff reported initial consensus on the following topics and
anticipates that these topics will guide future Housing Methodology Committee discussions:
1. More housing should go to jurisdictions with more jobs than housing and to communities
exhibiting racial and economic exclusion.
2. The RHNA methodology should focus on:
a. Equity, as represented by High Opportunity Areas
b. Relationship between housing and jobs
3. Equity factors need to be part of the total allocation, not just the income allocation part of
the RHNA methodology
4. Do not limit 6th Cycle RHNA allocations based upon the past RHNA allocations
5. Housing in high natural hazard areas is a concern, but RHNA may not be the best tool to
address this.11
Staff anticipates that the Housing Methodology Committee and ABAG will propose a draft
RHNA methodology in Fall 2020. The RHNA methodology would then be sent to HCD in Winter
2021 for consideration relative to the RHNA statutory objectives (Attachment C).12 Cities and
counties can then anticipate the release of the draft RHNA numbers for local jurisdictions in
Spring 2021; City and public appeals of the draft RHNA numbers in Summer 2021; and final
RHNA numbers in Winter 2021.
The Housing Methodology Committee may also utilize Plan Bay Area 2050, although the
Committee indicated a preference to see the results of the Draft Blueprint before deciding how
or if at all to use the Plan as an input for the methodology. At the forthcoming July 9, 2020
meeting, the Housing Methodology Committee is scheduled to discuss how to achieve
consistency between RHNA and Plan Bay Area 2050. This will include any potential use of the
Plan Bay Area Draft and Final Blueprint as the baseline input for the RHNA methodology and/or
utilization of further modified RHNA methodology factors and weights.
C. Plan Bay Area 2050 and Regional Housing Needs Allocation (RHNA)
The RHNA process is distinct from Plan Bay Area 2050. While Plan Bay Area focuses on growth
and development over a 30-year time frame, RHNA focuses on an 8-year projection period. The
two planning processes are occurring simultaneously. Additionally, by statute, Plan Bay Area
2050 must be consistent with RHNA. For example, the allocated housing units in RHNA cannot
exceed the projected population growth in Plan Bay Area. Table 2 outlines of key milestones for
Plan Bay Area 2050, RHNA, and forthcoming Housing Element update processes.
11 Reported during the June 25, 2020 ABAG General Assembly Special Meeting:
http://baha.granicus.com/MediaPlayer.php?view_id=1&clip_id=7275
12 Statutory Objectives for RHNA summary website: https://rhna-
factors.mtcanalytics.org/data/RHNA_Statutory_Objectives.pdf
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Table 2: ABAG 2023-2031 RHNA and Plan Bay Area 2050 Key Milestones:13
ABAG 2023 RHNA and Plan Bay Area 2050 Key Milestones Proposed Deadline
Housing Methodology Committee Kick-Off October 2019
Subregions Form February 2020
Plan Bay Area 2050 Regional Growth Forecast April 2020
HCD Regional Housing Need Determination Summer 2020 (June 9, 2020)
Plan Bay Area 2050 Draft Blueprint July 2020
ABAG & Housing Methodology Committee Proposed RHNA
Methodology, Draft Subregion Shares
Fall 2020
Plan Bay Area 2050 Final Blueprint December 2020
Final Subregion Shares December 2020
Draft RHNA Methodology to HCD for Review Winter 2021
Final RHNA Methodology, Draft Allocation Spring 2021
RHNA Appeals Summer 2021
Final Plan Bay Area 2050 September 2021
Final RHNA Allocation Winter 2021
Housing Element Due Date January 2023
Dates are tentative and subject to change
There may be some interplay between Plan Bay Area 2050 and RHNA. Some potential overlaps
include the following:
• A City’s RHNA cannot be higher than the growth projected in Plan Bay Area 2050, although
this cap is unlikely to come into effect because Plan Bay Area is a 30-year horizon document
and Housing Elements are eight-year horizon documents.
• The Housing Methodology Committee might decide to use the Plan Bay Area 2050 growth
geographies as a basis for its suggested methodology for allocating the HCD RHNA
determination. The committee might also use the growth geographies in combination with
other factors. The RHNA methodology must be “consistent” with Plan Bay Area.
• Plan Bay Area 2050 will affect the region’s RHNA, however, the extent of the influence will
be determined in coming months.
Discussion
A. Plan Bay Area 2050
While Plan Bay Area 2050 remains under development, City staff have discussed the plan and
identified several specific areas where further refinement, clarity, and/or reconsideration of
definitions might lead to improved long-range planning. These areas are elaborated below.
Staff plan to draft a letter to the ABAG/MTC requesting several updates and providing feedback
13 April 27, 2020 Revised RHNA Timeline: https://abag.ca.gov/sites/default/files/abag_rhna_timelineapril.pdf
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for the development of the Plan. Staff welcome additional feedback from the PTC, as well as
questions, that can be put forward to ABAG/MTC regarding Plan Bay Area 2050.
Plan Bay Area 2050 Growth Geographies
Plan Bay Area 2050 will utilize “growth geographies.” Growth geographies are the areas within
the region that MTC/ABAG staff will overlay the strategies in the Plan. The Plan identifies
different types of growth geographies with distinct characteristics. These types include:
• Priority Development Areas (PDAs) – Locally nominated, urban areas within ½ mile of high-
quality transit that are planned or will be planned for housing and/or job growth.
• Transit Rich Areas (TRAs) – Areas within ½ mile of a rail station, ferry terminal, or bus stop
with peak headways of 15 minutes or less.
• High Resource Areas (HRAs) – Areas that offer opportunities for economic advancement,
high educational attainment, and good physical and mental. Area are identified in the
TCAC/HCD Opportunity Map.14
• Priority Production Areas (PPAs) – locally nominated industrially zoned areas or areas with
a high concentration of production, distribution, and repair activities.
As Attachment D shows, the growth geographies cover portions of Palo Alto. While many of the
objectives of Plan Bay Area 2050 align with Palo Alto values and even the Palo Alto
Comprehensive Plan, the growth geographies may not always align with practical means to
realize these objectives. Consequently, Palo Alto staff plan to raise several topics in our
correspondence with ABAG/MTC.
First, the map shows a ½ mile radius around transit stations and bus stops as proposed growth
geographies. While this is meant to indicate an ability to walk or bike to high-quality transit, the
reality is that this might not always be the case. These transit-oriented growth geographies may
not accurately represent the accessibility of current transit in Palo Alto. As examples:
• Transit service to some bus stops might have changed due to the COVID-19 pandemic. Palo
Alto staff will reconfirm that MTC/ABAG staff are using accurate transit headway
information for pre-COVID-19 and post-COVID-19 routes and service levels.
• The train tracks sometimes create a physical barrier preventing easy access to the station;
while as the crow flies, Caltrain may be ½ mile away, the true walking, biking, or driving
distance could be greater. During discussions Palo Alto staff, MTC/ABAG staff noted that
other communities face similar challenges and suggested that Palo Alto plan for
infrastructure improvements to make such transit accessible via walking and biking.
Second, staff questions that all areas identified as growth geographies are well suited to
accommodate the strategies in Plan Bay Area 2050. Staff was somewhat encouraged to hear
from MTC/ABAG staff that the strategies will consider both single-family home areas, as well as
historic districts and open space areas. MTC/ABAG staff recognize that redevelopment of such
14 TCAC/HCD 2020 Opportunity Maps (June 2020) and Mapping Methodology:
https://belonging.berkeley.edu/tcac-opportunity-map-2020; https://belonging.berkeley.edu/tcac-2020-preview.
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single-family home areas into higher density housing requires site assembly that is
unpredictable and unlikely. Likewise, they recognize the limitations of redevelopment in
historic districts and open space. Although already provided in 2019, Palo Alto staff will resend
and reconfirm that MTC/ABAG staff will incorporate historic districts, open space, single-family
residential zoning districts, and other relevant zoning into the growth geographies.
Third, Palo Alto staff take issue with the process by which ABAG communicated the connection
between growth geographies and PDAs. The City of Palo Alto responded to MTC/ABAG’s first
call to update the growth geographies on January 13, 2020.15 In February 2020, ABAG and MTC
approved pursuit of a second call for more PDA geographies from Bay Area jurisdictions by May
31, 2020.16 Consequently, staff spoke to MTC/ABAG staff explicitly in several phone
conversations and email correspondence to understand the reasons for and the pros/cons for
responding to the second call for PDAs. At no time did MTC/ABAG staff express that
communities that designate up to 50% of their eligible growth geography area as Priority
Development Areas may have the rest of the eligible growth geography removed from
consideration in Plan Bay Area 2050. Only after the May 31, 2020 deadline for designating new
or expanding existing PDAs had passed and after staff inquired why a neighboring city’s transit
station area was not indicated to be a growth geography did MTC/ABAG explicitly explained this
connection. Such difficulty in obtaining information impairs a jurisdiction’s ability to make fully
informed decisions.
Nevertheless, the PTC and City Council did consider designating additional areas of the City as
PDAs during the first call for PDAs. The PTC was supportive at its November 13, 2019 meeting
for designating both Downtown/University Avenue and a narrow area along either side of El
Camino Real.17 The City Council designated Downtown/University Avenue, but declined to
designate the El Camino Real corridor as a PDA at its January 13, 2020 meeting. Even had
Council designated the narrow area along El Camino Real as a PDA, this would not have brought
Palo Alto to designation of 50% of PDA eligible areas.
Finally, while the COVID-19 pandemic has not eliminated the housing crisis in the State or
region, the impacts of COVID-19 on population growth and job growth remain to be seen.
While working to address the housing crisis is absolutely necessary, conducting long-range
planning processes for a thirty-year cycle may be unwise given the unknown impact of COVID-
15 January 13, 2020 Council Staff Report on PDAs and PCAs:
https://www.cityofpaloalto.org/civicax/filebank/documents/74728; Palo Alto City Council adopted two new
Priority Conservation Areas (PCAs) – the Baylands PCA and the Foothills PCA – and the new Downtown/University
Avenue Priority Development Area (PDA). Palo Alto previously adopted the California Avenue PDA. Both PDAs are
viewable on the growth geographies interactive website:
https://mtc.maps.arcgis.com/apps/webappviewer/index.html?id=9cf8663fabf4478788312de1bcc2977c. Other
cities and counties responded to MTC/ABAG’s second call for local adoption of PDAs, the deadline for which was
May 31, 2020. Palo Alto did not participate in this second call, as the City had already participated in and
responded to the first call as described above.
16 ABAG Final Call for PDAs website: https://abag.ca.gov/news/final-call-pdas-open-through-may-31-2020
17 November 13, 2019 Planning & Transportation Commission Staff Report:
https://www.cityofpaloalto.org/civicax/filebank/documents/74018
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19 on critical variables. A temporary extension of the timeline may provide sufficient time to
gather data, for circumstances to change so that the Plan is more useful to the region and to
jurisdictions.
Plan Bay Area 2050 Draft and Final Blueprints
Once the Draft and Final Blueprint for Plan Bay Area 2050 are released, staff will review the
documents and provide both PTC and City Council with the analysis. Part of the analysis will be
confirming the accuracy of the growth geographies for Palo Alto, as discussed above. Other
aspects of the analysis will involve understanding how the Draft and Final Blueprint support,
coincide, or conflict with the Palo Alto Comprehensive Plan, especially regarding housing
density, jobs concentrations, community character, and transit investments. It’s important to
note that Plan Bay Area 2050 does not impact a jurisdiction’s local land use authority. Palo Alto
still retains authority to adopt local land use regulations, including zoning.
B. Regional Housing Needs Allocation (RHNA)
ABAG, through the work of the Housing Methodology Committee, will allocate the regional
housing need determination among the region’s jurisdictions. To assist the members of the
Housing Methodology Committee in its work, as well as board members, planners, and the
general public, ABAG created a tool that allows users to visualize how the regional housing
need determination would look if mapped over the Bay Area. ABAG then updated the
visualization tool to incorporate the HCD regional housing need determination received on June
9, 2020.
Palo Alto has a hypothetical baseline allocation in the visualization tool of 4,475 housing units
out of the RHND of 441,176 new housing units for the region (Table 1). This “hypothetical
baseline allocation” represents what Palo Alto’s RHNA could be if the allocation was based
entirely on Palo Alto’s existing share of the region’s households in 2019 and if each jurisdiction
in the region experienced the same hypothetical 16% growth rate.
Factors and Weighting
The Housing Methodology Committee developed their top three RHNA methodology options
during Winter 2019 into Spring 2020.18 Figure 1 shows a summary of the factors and weighting
in these top three options. For definitions of the phrases in the Figure, please see attachments
B and E. Figure 2 shows how the top three options could translate into hypothetical allocations
by Bay Area County in comparison with the final RHNA methodology for the previous 5th Cycle
and with the household growth predicted in Plan Bay Area 2040. Table 3 shows the top three
RHNA methodology options relative to the hypothetical baseline allocation for Palo Alto. The
18 April 27, 2020 Housing Methodology Committee discussion summary, including a summary of the Committee-
developed initial RHNA methodology options:
https://abag.ca.gov/sites/default/files/hmc_rhna_methodology_update_april2020.pdf
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equity factor “Access to High Opportunity Areas” plays a large role in each of the options, as
shown in Figure 1.
Figure 1: Summary of Factors and Weights for Top Three Methodology Options (March 2020 Options)
Given the interplay between the factors, and the ways placing homes near jobs and transit in a
high opportunity community advances regional objectives, Palo Alto could end up with RHNA
higher than the “hypothetical baseline allocation.”
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Figure 2: Summary of Allocations by Bay Area County for Top Three Methodology Options
Table 3: Influence of Top Three RHNA Methodology Options on Hypothetical Palo Alto
RHNA Housing Units
Hypothetical Growth Rate
(% Increase over Housing
Units in 2019)
Hypothetical
Housing Units
+/- Housing Units
from Hypothetical
Baseline
Palo Alto Hypothetical
Baseline Allocation 16% 4,475 -
Top Three RHNA Methodology Options (Using HMC Identified Factors & Weights):
Housing/Jobs Crescent 21% 5,819 +1,344 units
Code Red to Address
Housing Need 22% 6,087 +1612 units
Balanced Equity-Jobs-
Transportation 24% 6,532 +2,057 units
City staff explored further how the 10 factors identified by the Housing Methodology
Committee independently influence hypothetical growth rates in Palo Alto. Table 4 shows the
influence of each factor compared to the hypothetical baseline allocation for Palo Alto. Staff ran
the visualization tool separately for each factor with weighting of only that factor at 100%. Half
of the factors reduced the growth rate below the hypothetical 16% growth rate, while the other
half resulted in an increase. The equity factor “Access to High Opportunity Areas” has the
highest influence for Palo Alto. Factors “Future Jobs,” “Job Proximity to Transit,” “Transit
Connectivity” result in lower growth rates and a lower number of housing units when compared
with the hypothetical Palo Alto baseline allocation. There appeared to be less interest in
utilizing the “Natural Hazards” factor during discussion at the June 19, 2020 meeting.
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Table 4: RHNA Methodology Factor Influence on Hypothetical Palo Alto RHNA Housing Units
Hypothetical Growth Rate
(% Increase over Housing
Units in 2019)
Hypothetical
Housing Units
+/- Housing Units from
Hypothetical Baseline
Palo Alto Hypothetical
Baseline Allocation 16% 4,475 -
RHNA Methodology Factors:
Access to High
Opportunity Areas 26% 7,226 +2,751 units
Jobs-Housing Balance 24% 6,678 +2,203 units
Job Proximity - Auto 23% 6,482 +2,007 units
Vehicle Miles Travelled 19% 5,119 +644 units
Jobs-Housing Fit 19% 5,118 +643 units
Natural Hazards 15% 4,161 -314 units
Divergence Index 15% 4,064 -411 units
Future Jobs 13% 3,691 -784 units
Job Proximity - Transit 13% 3,459 -1,016 units
Transit Connectivity 11% 3,113 -1,362 units
Income Allocation and Affordability Levels
Four income groups are used to establish affordability levels for housing distributed within the
RHNA methodology. The RHNA must be allocated in accordance with statutory requirements,
including (1) increase affordability in an equitable manner; (2) improve the balance between
low-wage jobs and housing affordable to low-wage workers (jobs-housing fit); (3) allocate less
RHNA in an income category when a jurisdiction already has a disproportionately high share of
households in that income category; (4) affirmatively further fair housing.
Income Groups Household Income in Reference to Area Median Income
Very Low Income Households earning less than 50 percent of AMI
Low Income Households earning 50 - 80 percent of AMI
Moderate Income Households earning 80 - 120 percent of AMI
Above Moderate Income Households earning 120 percent or more of AMI
The Housing Methodology Committee is considering 2 approaches to allocating the income
groups across the region: Income Shift or Bottom Up. The income shift approach applies a
selected income allocation to the total housing allocation. The bottom-up approach uses the
income allocation to build the total allocation.
Figure 3 illustrates an income shift approach. It provides a hypothetical example of how
a jurisdiction’s total housing unit allocation could be distributed between the affordability
levels using different income shift percentages. At a 0% income shift, a “high opportunity
area”
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City of Palo Alto
Planning & Development Services Department Page 14
jurisdiction, such as Palo Alto, could receive an income allocation that reflects the jurisdiction’s
current income distribution. The RHNA assigned to that jurisdiction would then require most
units be above moderate income. A 100% income shift means the jurisdiction’s income
allocation reflects the average income allocation across the entire region. In discussions,
Housing Methodology Committee members have expressed support for a 125% or 150%
income shift.
The bottom up approach breaks out the region’s allocation into the affordable housing units
(very-low income to moderate income) and the market-rate housing units (above moderate
income). It then further allocates these units based on either two or three factors. The two-
factor bottom-up approach allocates half of the affordable units to high opportunity areas and
half based on jobs-housing fit. The market-rate units are allocated half to jobs-proximity
auto and the remaining half based on jobs-housing balance. Figure 4 shows the allocation
for a three-factor bottom up approach. Using this approach, the income allocation is
based on characteristics of areas across the region (e.g.: high opportunity, jobs-housing
balance) instead of simply allocating the income groups across jurisdictions.
Figure 3: Illustration of Income Shift Method for Income Allocation RHNA Methodology
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City of Palo Alto
Planning & Development Services Department Page 15
At their May and June 2020 meetings, the Housing Methodology Committee indicated that they
would like this 6th Cycle to take a more tailored bottom-up approach to the income allocation
portion of the RHNA methodology, as utilization of a simplified percentage income shift
methodology shown in Figure 3 could result in localized housing displacement impacts and
other considerations for some cities. Figure 4 shows an example of the bottom-up approach.
Past Progress and Upcoming Work
For context, Palo Alto received 1,988 housing units during the 5th Cycle RHNA process. At
the end of 2019, Palo Alto had issued building permits for 554 housing units. Palo Alto is
not on pace to meet its RHNA for the 5th Cycle. Many jurisdictions face the same challenge
(Table 5).
Table 5: Bay Area Regional Housing Needs Allocation Progress: 1999-201819
RHNA Permits Percent of RHNA Permitted
Cycle Total
Need
Permits
Issued
All Very Low
Income
Low
Income
Moderate
Income
Above
Moderate
Income
1999-2006 230,743 213,024 92% 44% 79% 38% 153%
2007-2014 214,500 123,098 57% 29% 26% 28% 99%
2015-2023* 187,994 121,973 65% 15% 15% 25% 126%
2023-2031** 441,176 TBD TBD TBD TBD TBD TBD
*Only includes building permits issued in 1025-2018
**Recently issued by HCD
Staff intends to correspond with the Housing Methodology Committee. Staff will share
19 Reported during the June 25, 2020 ABAG General Assembly Special Meeting:
http://baha.granicus.com/MediaPlayer.php?view_id=1&clip_id=7275
3
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Figure 4: Bottom-Up Three-Factor Concept
City of Palo Alto
Planning & Development Services Department Page 16
feedback on the methodology, including questions and suggestions for improving the
methodology. Staff welcome the PTC’s feedback and questions, so those can be included in the
correspondence. Should PTC and members of the public like additional background
information, recent Housing Methodology Committee staff reports are included as Attachment
E.These staff reports include detailed information on potential income allocation
methodologies.
Ultimately, once finalized, the RHNA for Palo Alto will form the basis for the update of the City’s
Housing Element. The Housing Element, which must be adopted by January 2023 and certified
by HCD, must include zoning that accommodates the RHNA housing units within the City of Palo
Alto.
Environmental Review
Discussion of Plan Bay Area 2050 or RHNA in a study session does not constitute a project
under the California Environmental Quality Act (CEQA). There will be no motion or
recommendation by the PTC resulting from this study session. Plan Bay Area 2050 does require
environmental review under CEQA and an Environmental Impact Report (EIR) will be prepared
by the lead agencies.
Public Notification, Outreach & Comments
Notification of this study session was sent to the Palo Alto Daily Post on June 26, 2020. City
Council has received some public comments on Plan Bay Area 2050 and RHNA. Topics
mentioned in the comments include requests for public study session(s) in Palo Alto specifically
and for Palo Alto to weigh in early on the RHNA methodology being discussed by the Housing
Methodology Committee. Comments also advocated for MTC/ABAG to address the jobs-
housing imbalances in the region, ensure that the Plan Bay Area 2050 modeling is realistic,
make adjustments to the pace of the Plan Bay Area 2050 and RHNA processes due to COVID-19
circumstances, and MTC/ABAG to hold effective public forums.
Next Steps
City staff will continue to follow the preparation of Plan Bay Area 2050, the 6th Cycle RHNA
process, and keep City Council, PTC, and the Palo Alto community abreast of these regional
planning initiatives. Staff anticipates scheduling a discussion before City Council in August.
Alternative Actions
None.
Report Author & Contact Information PTC20 Liaison & Contact Information
Rebecca Atkinson, Planner Rachael Tanner, Assistant Director
(650) 329-2596 (650) 329-2441
rebecca.atkinson@cityofpaloalto.org rachael.tanner@cityofpaloalto.org
20 Emails may be sent directly to the PTC using the following address: planning.commission@cityofpaloalto.org
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City of Palo Alto
Planning & Development Services Department Page 17
Attachments:
•Attachment A: HCD Regional Housing Needs Determination Letter (June 9, 2020) (PDF)
•Attachment B: Potential RHNA Factors Overview (PDF)
•Attachment C: RHNA Statutory Objectives (PDF)
•Attachment D: Draft Growth Geographies (February 2020) (PDF)
•Attachment E: Housing Methodology Committee Staff Reports (PDF)
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ATTACHMENT 1
HCD REGIONAL HOUSING NEED DETERMINATION
ABAG: June 30, 2022 through December 31, 2030
Income Category Percent
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Housing Unit Need
Total 100.0% 441,176
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ATTACHMENT 2
HCD REGIONAL HOUSING NEED DETERMINATION:
ABAG June 30, 2021 through December 31, 2030
Methodology
ABAG: PROJECTION PERIOD (8.5 years)
HCD Determined Population, Households, & Housing Unit Need
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Total 6th Cycle Regional Housing Need Assessment (RHNA)441,176
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Fair Housing and Equity Factors
1. Access to High Opportunity Areas
Impact More housing units allocated to jurisdictions with the most access to opportunity.
Definition The percentage of a jurisdiction’s households living in census tracts labelled High Resource or Highest Resource based on opportunity index scores.
Data source HCD/TCAC 2020 Opportunity Maps1
2. Divergence Index
Impact More housing allocated to jurisdictions that are more segregated compared to the rest of the region.
Definition The divergence index score for a jurisdiction, which is a calculation of how different a jurisdiction’s demographics are from the region.
Data source U.S. Census Bureau, American Community Survey 2014-2018, Tables B03002 and
B19013
Jobs and Jobs-Housing Fit Factors
3a. Job Proximity - Auto
Impact More housing allocated to jurisdictions with easy access to region’s job centers.
Definition Share of region’s total jobs that can be accessed from a jurisdiction by a 30-minute auto commute.
Data source MTC, Travel Model One
3b. Job Proximity - Transit
Impact More housing allocated to jurisdictions with easy access to region’s job centers.
Definition Share of region’s total jobs that can be accessed from a jurisdiction by a 45-minute transit commute.
Data source MTC, Travel Model One
4. Vehicle Miles Travelled (VMT)
Impact More housing allocated to jurisdictions with a high number of vehicle miles travelled per worker.
Definition Total modeled vehicle miles traveled per worker in 2020 from Plan Bay Area 2040.2
Data source MTC
5. Jobs-Housing Balance
Impact More housing allocated to jurisdictions with a high number of jobs relative to the amount of housing.
Definition Ratio of jobs within a jurisdiction to housing units in the jurisdiction.
Data source MTC; U.S. Census Bureau, ACS 2014-2018; Census LEHD LODES for 2015-2017
1 For more information on the Opportunity Map, see pages 10-13 of this document from the March 2020 HMC meeting’s agenda packet. 2 Data from Plan Bay Area 2050 would be used once it is available.
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HMC Meeting #5 | March 12, 2020 | Page 2
6. Jobs-Housing Fit
Impact More housing allocated to jurisdictions with a high number of low-wage jobs relative to the number of low-cost rental units.
Definition Ratio of low-wage jobs (less than $3,333/month) within a jurisdiction to the number of low-cost rental units (less than $1,500/month) in the jurisdiction.
Data source MTC; U.S. Census Bureau, ACS 2014-2018; Census LEHD LODES for 2015-2017
7. Future Jobs3
Impact More housing allocated to jurisdictions with a higher share of projected jobs.
Definition Jurisdiction’s share of the region’s forecasted jobs based on Plan Bay Area 2050.
Data source MTC
Transportation Factor
8. Transit Connectivity
Impact More housing allocated to jurisdictions with existing and planned transit infrastructure.
Definition Jurisdiction’s percentage of the region’s total acres within Transit Priority Areas.
Data source MTC
Other Factors of Importance
9. Natural Hazards
Impact More housing is allocated to areas with low natural hazard risk.
Definition Percentage of acres within a jurisdiction’s urbanized area in locations with low risk from natural hazards according to the Modified MTC/ABAG Multi-Hazard Index.4
Data source MTC; USGS liquefaction susceptibility; CAL FIRE FRAP LRA/SRA data; FEMA (flood
zones); Alquist-Priolo Fault Zones (California Geological Survey)
3 Although ABAG would likely use data for year 2031 once Plan Bay Area 2050 data is available, this factor is currently based on data for year 2050 from the Clean and Green future due to greater reliability for using year 2050 for this data source. 4 For more information on the Modified MTC/ABAG Multi-Hazard Index, see pages 14-15 of this document from the March 2020 HMC meeting’s agenda packet.
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Statutory Objectives for RHNA
California Government Code Section 65584(d)
1) Increasing the housing supply and the mix of housing types, tenure, and
affordability in all cities and counties within the region in an equitable
manner, which shall result in each jurisdiction receiving an allocation of
units for low- and very low-income households.
2) Promoting infill development and socioeconomic equity, the protection of
environmental and agricultural resources, the encouragement of efficient
development patterns, and the achievement of the region’s greenhouse
gas reductions targets provided by the State Air Resources Board pursuant
to Section 65080.
3) Promoting an improved intraregional relationship between jobs and
housing, including an improved balance between the number of low-wage
jobs and the number of housing units affordable to low-wage workers in
each jurisdiction.
4) Allocating a lower proportion of housing need to an income category when
a jurisdiction already has a disproportionately high share of households in
that income category, as compared to the countywide distribution of
households in that category from the most recent American Community
Survey.
5) Affirmatively furthering fair housing, which means taking meaningful
actions, in addition to combating discrimination, that overcome patterns of
segregation and foster inclusive communities free from barriers that restrict
access to opportunity based on protected characteristics. Specifically,
affirmatively furthering fair housing means taking meaningful actions that,
taken together, address significant disparities in housing needs and in
access to opportunity, replacing segregated living patterns with truly
integrated and balanced living patterns, transforming racially and ethnically
concentrated areas of poverty into areas of opportunity, and fostering and
maintaining compliance with civil rights and fair housing laws.
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6) Pending state legislation: Reducing development pressure within very high
fire risk areas.
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Attachment D: Plan Bay Area 2050: DRAFT Blueprint Growth Geographies for Study
(Adopted by ABAG Executive Board and MTC Commission, February 2020, for Study in Draft Plan Bay Area 2050)
(https://mtc.maps.arcgis.com/apps/webappviewer/index.html?id=9cf8663fabf4478788312de1bcc2977c)
(enlarged map on next page)
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TO: Housing Methodology Committee DATE: April 27, 2020
FR: Deputy Executive Director, Policy
RE: Initial RHNA Methodology Options
Overview
The Housing Methodology Committee’s (HMC) objective is to recommend an allocation
methodology for dividing up the Bay Area’s Regional Housing Need Determination among the
region’s jurisdictions. This Regional Housing Needs Allocation (RHNA) methodology is a formula
that calculates the number of housing units assigned to each city and county, and the formula also
distributes each jurisdiction’s housing unit allocation among four affordability levels. At the last
several meetings, the HMC has identified and prioritized potential factors to include in the
methodology for determining a jurisdiction’s total housing need. The HMC will have an
opportunity to consider factors for the income allocation at its meeting in May.
Initial Methodology Options
At the January HMC meeting, ABAG staff presented maps showing the regional distribution
among jurisdictions for potential factor topics (e.g., jobs-housing fit, transit proximity, etc.).1 For
the March HMC meeting, staff translated the priority factor topics identified at the January
meeting into allocation factors and made adjustments to the factors based on HMC feedback. The
revised set of factors was incorporated into an online visualization tool2 that allowed HMC
members, working in small groups, to continue to prioritize factors and to explore sample RHNA
methodologies by applying a weight to each factor used. Each group used the tool to create
several methodology options, chose a name for the methodology it favored, and presented it to
the rest of the committee. HMC members and audience members then voted for the
methodologies they liked best. Figure 1 shows the results of the voting.
Figure 1: Results of Dot Voting for Methodology Options3
1 The maps from the January HMC meeting can be viewed at https://abag.ca.gov/rhna-maps
2 The visualization tool is available at: https://rhna-factors.mtcanalytics.org/
3 Maps for each group’s methodology are available at: https://abag.ca.gov/our-work/housing/rhna-regional-housing-
needs-allocation/housing-methodology-committee
0 5 10 15 20 25 30
Slightly Better Than our First One
Opportunity - Jobs - Transit
Balanced Equity-Jobs-Transportation
Code Red to Address Housing Need
Housing / Jobs Crescent
HMC Votes Public Votes
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Figure 2 compares the factors and weights for the three methodology options that received the
most votes.4 The choices made by the HMC members in developing these options demonstrate
that equity is a top priority for most participants. The methodology options also emphasize the
importance of linking housing and jobs. Some of the methodologies recognized the importance
of encouraging growth near transit and considering natural hazards, but these received less
emphasis than equity and jobs-housing relationships.
Figure 2: Summary of Factors and Weights for Top Three Methodology Options
Housing/Jobs Crescent Code Red to Address
Housing Need
Balanced Equity-Jobs-
Transportation
Figure 3 compares the share of units allocated to the jurisdictions in each county for the three
methodology options that received the most votes. The chart indicates that there were minimal
differences in how units were distributed at the county level among the three methodology
options. Figure 3 also shows each county’s share of housing unit growth from ABAG’s 5th Cycle
RHNA methodology and Plan Bay Area 2040 as points of reference. In general, the three
methodology options would direct more units to jurisdictions in the North Bay and San Mateo
4 For more information on the factors included in the methodology visualization tool, see pages 5-9 of this memo
from the March 2020 HMC agenda packet.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
30% Equity
• Access to High-
Opportunity Areas
60% Jobs
• Jobs Proximity - Auto
• Jobs-Housing Balance
10% Hazards
60% Equity
• Access to High-
Opportunity Areas
20% Jobs
• Jobs-Housing Fit
10% Hazards
10% Transit
50% Equity
• Access to High-
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40% Jobs
• Jobs Proximity - Transit
• Jobs-Housing Balance
• Jobs-Housing Fit
• Future Jobs
10% Transit
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County and fewer units to jurisdictions in Alameda and Santa Clara counties relative to ABAG’s
5th Cycle RHNA and Plan Bay Area 2040.
Figure 3: Allocations by County for Top Three Methodology Options
Output by Jurisdiction Geography
ABAG staff also analyzed the output of the top three methodologies by jurisdiction geography
using a framework developed as part of prior Plan Bay Area processes, simply to understand the
general distribution across different typologies of places. This framework assigns each
jurisdiction to one of four geographies that reflect its role and spatial location within the region.
The four categories are: Big Three; Bayside; Inland, Delta and Coastal; and Unincorporated.5
Figure 4 shows the share of units that would be allocated to each of these four areas from the
5 The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland;
Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte
Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules,
Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno,
Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San
Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito,
South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside; Inland, Delta and Coastal: American Canyon,
Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy,
Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda,
Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma,
St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville; Unincorporated: all unincorporated areas
0%
5%
10%
15%
20%
25%
30%
35%
Alameda Contra
Costa
Marin Napa San
Francisco
San Mateo Santa Clara Solano Sonoma
Housing / Jobs Crescent
Code Red to Address Housing Need
Balanced Equity - Job - Transportation
ABAG RHNA Cycle 5 (2013)
Plan Bay Area 2040 (2017) Household Growth
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three methodology options. Figure 4 also shows each county’s share of household growth from
ABAG’s 5th Cycle RHNA methodology and Plan Bay Area 2040 as points of reference. Compared
to ABAG’s 5th Cycle RHNA methodology and Plan Bay Area 2040, the three methodology
options would direct more housing growth to jurisdictions in the Bayside and Unincorporated
areas, less household growth to the Big Three cities, and similar amounts of housing growth to
jurisdictions in the Inland, Delta, and Coastal area.
Figure 4: Allocations by Jurisdiction Type for Top Three Methodology Options
Next Steps
Now that the HMC has identified several options for determining a jurisdiction’s total allocation,
for the May HMC meeting, ABAG staff will introduce ideas for how to determine the income
distribution of those units. Staff will also revisit the discussion around potential criteria for
evaluating the methodology outputs to ensure that the RHNA meets statutory objectives. An
understanding of these topics among HMC members will set the stage for a discussion in
Summer 2020 about how to achieve consistency between RHNA and Plan Bay Area 2050,
including potential use of the Plan’s Blueprint as the baseline input for the RHNA methodology
and/or modification of the RHNA methodology factors and weights.
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Bayside Big Three Inland, Delta and Coastal Unincorporated
Housing / Jobs Crescent
Code Red to Address Housing Need
Balanced Equity - Job - Transportation
ABAG RHNA Cycle 5 (2013)
Plan Bay Area 2040 (2017)
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Item 5, Attachment A
TO: Housing Methodology Committee DATE: May 14, 2020
FR: Deputy Executive Director, Policy
RE: Options for the Income Distribution Component of the RHNA Methodology
Overview The Association of Bay Area Governments (ABAG), with guidance from the Housing Methodology Committee (HMC), must allocate the Regional Housing Needs Determination (RHND) to the cities and counties in the nine-county Bay Area. The RHND is the total number of housing units assigned to a region by the California Department of Housing and Community Development (HCD). HCD also divides a region’s RHND across four levels of housing affordability that correspond to different income categories. Ultimately, the HMC will need to recommend a Regional Housing Needs Allocation (RHNA) methodology that both assigns a total number of housing units to each Bay Area jurisdiction and distributes each jurisdiction’s allocation among the four affordability levels. Jurisdictions in turn must update their housing elements to show how they will accommodate their share of housing needs for each income group. RHNA Income Categories A healthy and inclusive housing market is characterized by housing options for a range of workers, family types, and incomes. Both the number of units available is important and the cost at which these units are provided are critically important. For the Bay Area, one of the most expensive housing markets in the country, the urgency of providing a range of housing opportunities is even more pronounced. Pursuant to state housing element law (Government Code section 65584, et seq.), HCD is charged with determining the regional housing needs for the Bay Area for the period from 2023 to 2031. HCD divides the region’s housing need among four separate income groups:
• Very Low Income: households earning less than 50 percent of Area Median Income (AMI)
• Low Income: households earning 50 - 80 percent of AMI
• Moderate Income: households earning 80 - 120 percent of AMI
• Above Moderate Income: households earning 120 percent or more of AMI ABAG has not yet received the RHND from HCD; this is anticipated to occur in the next one to two months. In lieu of the RHND, Table 1 shows the distribution of Bay Area households by income from the most recent Census Bureau data for reference purposes. Table 1 Bay Area Households, By Major Income Group
Income Group Income Limit Households Percent
Very Low Income 0 - $47,350 678,673 25.3% Low Income $47,351 - $75,760 411,670 15.3% Moderate Income $75,760 - $113,640 459,169 17.1% Above Moderate Income $113,640 + 1,136,896 42.3% Source: U.S. Census Bureau, American Community Survey PUMS data, 2018 5-year release
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Considerations for the Income Allocation The Bay Area is a large and complex region: close to 8 million people reside in 109 jurisdictions across a 7,000 square mile geography with a number of distinctive subregions and economies. The region contains a range of community types and economic situations, with some communities encompassing a range of income groups, while others skew to either the low-income or high-income side of the spectrum. Housing Element Law includes the objective that RHNA “[a]llocat[e] a lower proportion of housing need to an income category when a jurisdiction already has a disproportionately high share of households in that income category,”1 meaning the RHNA methodology will in part be assessed by HCD in terms of how the allocation works to counter-balance existing concentrations of wealth or poverty. As noted in previous HMC meetings, meeting this objective will require that the RHNA methodology direct market-rate units to jurisdictions that currently have a higher concentration of lower-income households, which could exacerbate the potential for displacement of existing residents. The RHNA methodology must also improve coordination between the locations of low-wage jobs and housing affordable to low-wage workers (jobs-housing fit) and affirmatively further fair housing, which will require allocating more lower income units to communities that historically have not provided affordable housing. Examples of Income Allocation Methodologies from Other Regions At the December 2019 HMC meeting, ABAG staff presented a summary of the methodologies created by other regions for the current RHNA cycle, as well as ABAG’s methodology for the previous RHNA cycle (2015-2023).2 Although these RHNA methodologies differ substantially, they have primarily used one of two approaches for the income allocation: an income shift or an income shift modified by equity-focused factors. These two approaches are described below. Income Shift – used by the San Diego region3 this cycle and by ABAG last cycle4 In this approach, a jurisdiction’s distribution of households by income is compared to the distribution for the region or county the jurisdiction is in. The jurisdiction’s allocation of units by income category is then adjusted so the jurisdiction will move toward the region’s income distribution over time. Thus, jurisdictions that have a higher percentage of existing households in a given income category compared to the region receive a smaller share of units in that income category. In some cases, the income shift multiplier applied to a jurisdiction varies based on how much the jurisdiction’s household income distribution differs from the region or county. In the simplest example, ABAG’s 2015-2023 RHNA methodology moved each jurisdiction’s income distribution 175 percent toward the region’s income distribution. A 100 percent shift means a jurisdiction’s allocation of units by income category mirrors the region’s existing income distribution. The 175 percent shift would close the gap between a jurisdiction’s income distribution and the region’s distribution more quickly. The first step in this calculation is to 1 See California Government Code Section 65584(d). 2 See this document from the December 2019 HMC meeting agenda packet. 3 See page 6 of the San Diego Association of Governments RHNA methodology document. 4 See pages 11-12 of ABAG’s Final Regional Housing Need Plan for the San Francisco Bay Area: 2015–2023.
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compare a jurisdiction’s share of households in each income category to the region’s share of households in that income category. The difference between the region and the jurisdiction is then multiplied by 175 percent to create an adjustment factor. The adjustment factor is added to the jurisdiction's existing proportion of households in the income category to determine the total share of the jurisdiction's housing unit allocation for that income category. Figure 1 shows a visual representation of the income shift from ABAG’s last RHNA methodology. This process is repeated for each of the four income categories. The result is that a jurisdiction with a higher proportion of households in an income category compared to the region receives a smaller allocation of housing units in that same category, and vice versa. Figure 1 Income Shift from ABAG 5th Cycle RHNA Methodology
Income Shift Plus Equity-Focused Factors – used by the Los Angeles and Sacramento regions This approach uses an income shift approach conceptually similar to the one described above paired with other factors related to affirmatively furthering fair housing and improving jobs-housing fit. After the jurisdiction is compared to the region or county, the factors included in the methodology are used to increase or decrease the amount that the jurisdiction’s income distribution is adjusted. The factors used by the Sacramento region’s income methodology are the share of housing units in high opportunity areas, as defined by the State’s Opportunity Map, and a jurisdiction’s jobs-housing fit ratio.5 Jurisdictions receive more very low- and low-income units if they have a higher share of housing units in high opportunity areas or a higher ratio of low-wage workers to housing units affordable to those workers. In the Los Angeles region’s income methodology,6 a larger income shift multiplier is applied to a jurisdiction where more than 70 percent of the population lives in “high segregation and poverty”/”low resource” or “highest resource” census tracts as defined by the State’s Opportunity Map.7 Notably, the potential methodologies developed by the HMC in March 2020 include equity-focused factors related to high opportunity areas and jobs-housing fit in the determination of a jurisdiction’s total allocation, while other regions use these equity-focused factors solely in the income allocation.
5 See pages 29-34 of the Sacramento Area Council of Governments RHNA methodology document. 6 See pages 13-17 of the Southern California Association of Governments RHNA methodology document. 7 For more information on the Opportunity Map, see pages 10-13 of this document from the March 2020 HMC meeting’s agenda packet.
Existing Regional Proportion in Income Category
Existing Jurisdiction Proportion in Income Category
1.75 Income Shift Multiplier
Adjustment Factor
Existing Jurisdiction Proportion in Income Category
Share of Jurisdiction RHNA in Income Category
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Potential Approaches to the Income Allocation ABAG staff has developed three relatively distinct methodological approaches to the income distribution component of RHNA, described in more detail below. The first two—the income shift and factor-based approach—are aligned with the methodologies used by other regions. Both approaches are proposed to be applied as a second step in the allocation process, after the use of a factor-based methodology to determine a jurisdiction’s total allocation. The third approach would take an entirely different tack and use different weights and/or factors for different income categories, with the sum of the results for the four income categories determining a jurisdiction’s total allocation. Approaches A and B: Income Methodologies that are Applied to the Total Allocation At the March HMC meeting, committee members used an online visualization tool to experiment with different factors-based methodologies for allocating a total number of housing units to jurisdictions based on a hypothetical RHND. Figure 2 shows the three methodology options developed during the small group discussions that received the most votes from HMC members and members of the audience.8 As noted above, these potential methodologies developed by the HMC include equity-focused factors in the determination of a jurisdiction’s total allocation, while other regions’ methodologies for the current RHNA cycle do not use equity-focused factors for this purpose. The other regions relied on either the long-range regional plan or factors related to jobs and transit to determine a jurisdiction’s total allocation, while using equity-focused factors related to affirmatively furthering fair housing and jobs-housing fit solely in the income allocation. Figure 2 Comparison of Top Three Methodology Options from March 2020 HMC Meeting
Housing/Jobs Crescent Code Red to Address Housing Need Balanced Equity-Jobs-Transportation
8 See the summary of the initial methodology options from the March HMC meeting.
30% Equity
●Access to High-Opportunity Areas
60% Jobs
●Jobs Proximity - Auto
●Jobs-Housing Balance
10% Hazards
60% Equity
●Access to High-Opportunity Areas
20% Jobs
●Jobs-Housing Fit
10% Hazards
10% Transit
50% Equity
●Access to High-Opportunity Areas
40% Jobs
●Jobs Proximity - Transit
●Jobs-Housing Balance
●Jobs-Housing Fit
●Future Jobs
10% Transit 0%
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Approach A: Income Shift Applied to Total Allocation This approach resembles the income allocation method from ABAG’s 2015-2023 RHNA, using an income shift approach where the local and regional income distributions are compared. For this approach, the income allocation shifts the local distribution closer to or beyond the regional distribution, depending on the income shift multiplier. In the last cycle, the income shift multiplier used by ABAG was 175 percent (see Figure 1 for more information on how the income shift multiplier impacts the income allocation). In theory, setting the income shift multiplier above 100 percent could close the gap between a jurisdiction’s income distribution and the region’s distribution in a shorter period of time, but this more aggressive shift could also increase the potential for displacement by directing more market-rate units to jurisdictions with higher proportions of existing lower-income households. To illustrate the shift approach on cities with different income profiles, Figure 3 shows the effect of using an income shift approach with a 175 percent multiplier. City A is a relatively high-income city with good access to jobs. City B has a lower income profile, with less job access. City C is somewhere in between, falling close to the regional income distribution. We will use these same sample cities to illustrate how they fare with each income allocation approach. Figure 3 Hypothetical Example of Income Shift Approach, Using 175 Percent Multiplier
This approach directly addresses the state objective of “[a]llocating a lower proportion of housing need to an income category when a jurisdiction already has a disproportionately high share of households in that income category.”9 A smaller shift than 175 percent is also possible and may be appropriate given HMC members’ previously stated concerns about assigning large numbers of above moderate-income housing in lower income jurisdictions at risk of gentrification.
9 See California Government Code Section 65584(d)(4).
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Approach B: Using Factors Applied to Total Allocation Similar to Approach A, this option is also applied after determining a jurisdiction’s total allocation using a factor-based methodology. In this income allocation approach, factors are used to assign units for the lower two income groups (very low- and low-income units). As an initial example, staff used the Jobs-Housing Fit and High Opportunity Areas factors. The Jobs-Housing Fit factor specifically relates to the relationship between lower-wage workers and housing units affordable to those workers and the High Opportunity Areas factor affirmatively furthers fair housing by assigning more lower-income units to high opportunity areas, both objectives call for in Housing Element law.10 As noted earlier, other regions often paired the factor-based approach with the income shift. However, these are approaches are not dependent on one another, and ABAG is presenting them independently to make them easier to understand. In this approach, each jurisdiction starts with the same income distribution, as determined by HCD for the RHND. A jurisdiction’s share of units in the lower income categories is then adjusted up or down based on whether a city has relatively high or low scores compared to the region for the Jobs-Housing Fit and High Opportunity Areas factors. ABAG staff capped a jurisdiction’s adjustment from the RHND income distribution at 30 percent (15 percent for each of the two factors). Once the total share of lower income units is determined, the remainder of a jurisdiction’s units (as determined by the total allocation methodology) are assigned to the higher income categories (moderate- and above moderate-income units). Once these totals are set, the allocation is disaggregated into the four income categories using shares from the regional income distribution. Figure 4 shows the effect of this factor-based income approach for three hypothetical cities with different income profiles. Both City A (higher income) and City C (average income) received the same income distribution, which demonstrates the impact of the cap that limits the extent to which the distribution can deviate from the regional distribution. Setting this cap at a different level would potentially result in different outcomes.
10 See California Government Code Section 65584(d)(3) and (5).
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Figure 4 Hypothetical Example of Factor-Based Income Allocation Approach
Approach C: Using Bottom-Up Income Allocation to Build the Total Allocation In contrast to Approaches A and B, this income allocation approach does not start with a total allocation assigned with a factor-based methodology. Instead, this approach uses factors to determine allocations for the four income categories, and the sum of these income group allocations represents a jurisdiction’s total allocation. Factors and weights could be modified, as appropriate, by the HMC. As an initial example, ABAG staff used the Jobs-Housing Fit and High Opportunity Areas factors to determine the allocation of lower income units (very low- and low-income) and the Jobs-Housing Balance and Job Proximity-Auto factors to determine the allocation of higher income units (moderate- and above-moderate income).11 A jurisdiction’s income distribution is determined based on how the jurisdiction scores relative to the rest of the region on the selected factors. The jurisdiction’s total allocation is calculated by summing the results for each income category. As noted above for Approach B, the Jobs-Housing Fit factor specifically relates to the relationship between lower-wage workers and housing units affordable to those workers and the High Opportunity Areas factor supports affirmatively further fair housing by assigning more lower-income units to high opportunity areas. The Jobs-Housing Balance and Job Proximity-Auto are included because of their emphasis on the relationships between housing and jobs for moderate- and higher-income households. While many other combinations of factors are possible, staff selected these factors to make this approach conceptually similar to Approach B for a more meaningful comparison.
11 These factors used the same definitions and methodology as those used in the total income allocation.
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Figure 5 Hypothetical Example of Bottom-Up Income Allocation Approach
Similarities and Differences of the Potential Income Methodology Approaches The approaches represent different ways to distribute a jurisdiction’s RHNA across the four income categories. Approaches A and B both start with a total allocation and then divide it into income groups. Approach A uses an income shift multiplier to bring a jurisdiction’s income distribution toward the regional income distribution. Approach B, however, relies on how a jurisdiction scores relative to the region on two factors (high opportunity areas and jobs-housing fit), which impacts the allocation of lower income units. Approach A may be the simpler and more mechanical approach: it does not use factors and focuses solely on rebalancing income distributions in jurisdictions. Approach B, on the other hand, uses factors to move the income distribution rather than just shifting it towards the regional distribution. Unlike the first two options, Approach C does not start with a total allocation created by a factor-based methodology. While it uses the same factor-based data as the other approaches, Approach C could become more complex since the HMC needs to select factors and weights for each of the four income groups. Consequently, Approach A may be preferable for having a more standardized method for assigning the total allocations to jurisdictions. However, Approach C may offer more control over the allocations to individual income groups within jurisdictions. Approach B represents somewhat of a hybrid of the other two: this approach builds off a factor-based methodology for total allocation like Approach A, but offers more flexibility than Approach A’s straightforward income shift.
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Table 2 Summary of Benefits and Drawbacks for Income Allocation Approaches
Income Allocation Approach Benefits Drawbacks
Approach A: Income Shift • Builds on work HMC has already done on total allocation
• Allows narrative focus to be on factors for total allocation
• Simpler concept, easier to explain
• Directly related to statutory objective
• Multiplier can be adjusted to complement underlying total allocation methodology
• Does not include ability to finetune income allocations based on factors
Approach B: Factor-Based • Builds on work HMC has already done on total allocation
• Retains the two-step methodology approach of total income first, then income allocation, which may be more familiar from other RHNA methodologies
• Allows opportunity to finetune results for a particular income category
• Using factors also included in the total allocation methodology may result in overweighting those factors
• Additional complexity compared to Income Shift Approach may not be warranted, given that equity-related factors already included in total allocation
Approach C: Bottom-Up • Allows more fine-grained control over allocations for a particular income category
• Could be simpler than Approach B, depending on number of factors used
• New approach that departs from work HMC has done to date
• Could be more complex, depending on number of factors used
Next Steps At the May HMC meeting, committee members will have an opportunity to use the online visualization tool to apply the income shift approach to hypothetical total allocation methodologies and explore the impact of selecting different income shift multipliers (Approach A). Staff will also seek feedback from the committee about pursuing the other approaches presented here.
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TO: Housing Methodology Committee DATE: May 14, 2020
FR: Deputy Executive Director, Policy
RE: Potential Metrics for Evaluating the RHNA Methodology
Overview The Housing Methodology Committee’s (HMC) objective is to recommend an allocation methodology for dividing up the Bay Area’s Regional Housing Need Determination among the region’s jurisdictions. This Regional Housing Needs Allocation (RHNA) methodology is a formula that calculates the number of housing units assigned to each city and county, and the formula also distributes each jurisdiction’s housing unit allocation among four affordability levels. ABAG will submit the methodology to the Department of Housing and Community Development (HCD) for approval, and HCD will determine whether the methodology furthers the five objectives identified in Housing Element Law. Developing the methodology is a complex process; therefore, staff proposes to identify metrics that can be used to evaluate different methodology options developed by the HMC. These metrics can help ensure that any proposed methodology will meet the statutory RHNA objectives and further regional planning goals. The five RHNA statutory objectives embody many different policy goals, some of which are not always aligned with each other. One purpose of these metrics is to inform the HMC’s decisions about how to effectively balance these goals while developing a methodology that meets the required objectives. Importantly, any evaluation metrics the HMC chooses need to reflect the narrow scope of RHNA. The primary role of the RHNA methodology is to encourage a regional pattern of housing growth for the Bay Area, and RHNA does not play a role in identifying specific locations within a jurisdiction that will be zoned for housing. Accordingly, this memo presents options for evaluation metrics that can assess whether a methodology furthers the statutory objectives and other high priority regional policy goals directly related to RHNA. Staff seeks the HMC’s feedback on what measures might be the most relevant or helpful for evaluating potential RHNA methodologies. Potential Evaluation Framework for the RHNA Methodology Staff has developed a set of potential metrics for evaluating RHNA methodology options suggested by the HMC (Tables 1 and 2). In the tables below, each statutory objective has been reframed as a question to help the HMC assess how well a methodology option achieves state requirements and regional planning goals. The wording of the question reflects the language the statute uses to define the objectives.1 Each statutory objective is accompanied by potential quantitative metrics for evaluating the allocation produced by a methodology. This question-oriented evaluation framework can assist the HMC with developing a cohesive narrative for
1 See California Government Code Section 65584(d).
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explaining how a methodology produces optimal outcomes for the region and achieves the objectives required by law. Metrics Identified by HCD At the January 2020 HMC meeting, staff presented an overview of the analysis conducted by HCD in evaluating the RHNA methodologies completed by other regions in California. Staff reviewed the approval letters HCD provided to the Sacramento Area Council of Governments (SACOG), San Diego Association of Governments (SANDAG), and Southern California Association of Governments (SCAG).2 In these letters, HCD describes how the RHNA methodologies further each of the five statutory objectives. While the letters do not provide specific measures for evaluating the methodologies, these documents give a sense of the criteria HCD will use to determine whether the draft methodology selected by ABAG sufficiently achieves the statutory objectives.3 The metrics in Table 1 come directly from statements HCD made in the letters to SACOG, SANDAG, and SCAG explaining why their methodologies achieve the statutory objectives. HCD’s explanations vary across the letters and mention some metrics more consistently than others. Table 1 notes which metrics appear in all three letters sent by HCD. In addition to considering the metrics identified in HCD’s letters, the HMC may wish to incorporate additional measures for evaluating proposed RHNA methodologies. Table 2 presents evaluation metrics developed by staff related to Objective 24, Objective 55, and a possible new sixth objective (pending state legislation, more details provided below). In its letters to other regions, HCD discussed how RHNA methodologies achieved Objective 2 by either aligning with the existing locations of jobs and transit or by being based on long-range regional plans, similar to Plan Bay Area 2050. ABAG staff wanted to provide the HMC with more specific quantitative measures for assessing whether a methodology achieves this objective, which are listed in Table 2. The paragraphs below provide more context for the metrics in Table 2 related to Objective 5 and the pending sixth objective. Additional Metrics for Fair Housing and Racial Equity One of the statutory objectives for RHNA is that the methodology must affirmatively further fair housing. Housing Element Law defines affirmatively furthering fair housing as: “taking meaningful actions, in addition to combating discrimination, that overcome patterns of segregation and foster inclusive communities free from barriers that restrict access to
2 For copies of letters HCD sent to other regions, see this document from the January 2020 HMC meeting agenda packet.
3 For a summary of the evaluation metrics alluded to in the HCD letters, see this document from the January 2020 HMC meeting agenda packet.
4 Objective 2 is “Promoting infill development and socioeconomic equity, the protection of environmental and agricultural resources, the encouragement of efficient development patterns, and the achievement of the region’s greenhouse gas reductions targets provided by the State Air Resources Board.” See California Government Code Section 65584(d)(2) for more information. 5 Objective 5 is “Affirmatively furthering fair housing.” See California Government Code Section 65584(d)(5) for more information.
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opportunity based on protected characteristics. Specifically, affirmatively furthering fair housing means taking meaningful actions that, taken together, address significant disparities in housing needs and in access to opportunity, replacing segregated living patterns with truly integrated and balanced living patterns, transforming racially and ethnically concentrated areas of poverty into areas of opportunity, and fostering and maintaining compliance with civil rights and fair housing laws.”6 HCD’s discussion of affirmatively furthering fair housing in its letters to SACOG, SANDAG, and SCAG centers solely on data from the Opportunity Map produced by the California Tax Credit Allocation Committee (TCAC) and HCD. HCD’s evaluation of whether other regions’ methodologies further this objective focused on whether a methodology directs lower income RHNA to jurisdictions with a high percentage of households living in census tracts labelled High Resource or Highest Resource on the Opportunity Map.7 However, the HMC could use other evaluation metrics—in addition to the Opportunity Map scores—to ensure the RHNA methodology has a maximum impact on overcoming patterns of segregation and fostering inclusive communities. For example, some HMC members and community stakeholders have expressed interest in evaluation metrics that consider racial segregation more explicitly and specifically focus on areas with housing markets characterized by socioeconomic and racial exclusion. The metrics in Table 2 accompanying Objective 5 reflect this input from stakeholders as well as staff’s interpretation of statutory language related to affirmatively furthering fair housing. Pending Addition of Sixth Statutory Objective Senate Bill 182 (Jackson) would add a new RHNA objective to Housing Element Law and add wildfire risk to the list of factors that must be considered for the RHNA methodology. Indications are that this bill will be passed this year and apply to this RHNA cycle for ABAG. Although the bill includes specifics about addressing fire risks, nothing in the bill prohibits ABAG from considering wildfire risk in addition to other hazards. Additionally, throughout the methodology development process, the HMC has expressed an interest in minimizing the number of households who face high risk from natural hazards. Hazard risk reduction is also a priority within ABAG/MTC’s long-range planning efforts. Table 2 proposes a metric related to this potential sixth objective that uses the revised ABAG/MTC Multi-Hazard Index presented to the HMC at its March 2020 meeting.8
6 See California Government Code Section 65584(d). 7 For more information on the Opportunity Map, see pages 10-13 of this document from the March 2020 HMC meeting’s agenda packet. 8 For more information on the revised ABAG/MTC Multi-Hazard Index, see pages 14-15 of this document from the March 2020 HMC meeting’s agenda packet.
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Table 1. Metrics Based on HCD’s Evaluation of Other Region’s Methodologies
*Metrics highlighted in bold with asterisks (**) appear in all three letters sent by HCD to other regions.
Statutory Objective Possible Metric Data Source
Objective 1: Does the allocation increase the housing supply and the mix of housing types, tenure, and affordability in all cities and counties within the region in an equitable manner?
1a. Higher percentage of RHNA as lower income units for jurisdictions with the highest housing costs**
Census ACS for 2014-2018
1b. Higher percentage of RHNA as lower income units for jurisdictions with highest percent of single-family homes
Census ACS for 2014-2018
Objective 2: Does the allocation promote infill development and socioeconomic equity, the protection of environmental and agricultural resources, the encouragement of efficient development patterns, and the achievement of the region’s greenhouse gas reductions targets?
2a. Higher percentage of RHNA total unit allocations to jurisdictions with highest percentage of the region’s jobs
MTC, Census LEHD for 2017
Objective 3: Does the allocation promote an improved intraregional relationship between jobs and housing, including an improved balance between the number of low-wage jobs and the number of housing units affordable to low wage workers in each jurisdiction?
3a. Higher percentage of RHNA as lower income units for jurisdictions with the highest ratio of low-wage jobs to housing units affordable to low-wage workers
MTC, Census ACS for 2014-2018, Census LEHD for 2017
Objective 4: Does the allocation direct a lower proportion of housing need to an income category when a jurisdiction already has a disproportionately high share of households in that income category?
4a. Lower percentage of RHNA as lower income units for jurisdictions with a higher share of lower-income households9
Census ACS for 2014-2018
4b. Higher percentage of RHNA as lower income units for jurisdictions with a higher share of higher-income households10
Census ACS for 2014-2018
Objective 5: Does the allocation affirmatively further fair housing? 5a. Higher percentage of RHNA as lower income units for jurisdictions with the most households in High Resource/Highest Resource tracts**
HCD/TCAC 2020 Opportunity Maps
9 Lower-income households includes households in the very low- and low-income groups (<80% of Area Median Income). 10 Higher-income households includes households in the moderate- and above moderate-income groups (>=80% of Area Median Income).
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Table 2. Additional Evaluation Metrics Proposed by ABAG Staff
Statutory Objective Possible Metric Data Source
Objective 2: Does the allocation
promote infill development and socioeconomic equity, the protection
of environmental and agricultural resources, the encouragement of efficient development patterns, and
the achievement of the region’s greenhouse gas reductions targets?
2b. Higher RHNA total unit allocations for jurisdictions with the highest percent of the region’s total Transit Priority Area acres
MTC
2c. Percentage of jurisdictions whose RHNA housing growth through 2031 is less than or equal to housing growth projected in Plan Bay Area 2050 through 2050
MTC
Objective 5: Does the allocation affirmatively further fair housing? 5b. Higher percentage of RHNA total unit allocations compared to the jurisdiction percentage of regional households, calculated for jurisdictions with a higher share of higher-income households with highest divergence scores
Census ACS for 2014-2018
5c. Higher percentage of RHNA as lower income units for jurisdictions with a higher share of higher-income households with highest divergence scores
Census ACS for 2014-2018
Objective 6 (pending state legislation): Does the allocation
promote resilient communities, including reducing development pressure within very high fire risk
areas?
6a. Lower total units allocated per household for jurisdictions with highest percent of urbanized area at high risk from natural hazards11
MTC; Census ACS for 2014-2018; USGS
liquefaction susceptibility; CAL FIRE FRAP LRA/SRA
data; FEMA (flood zones), Alquist-Priolo Fault Zones (California Geological Survey)
Next Steps ABAG staff has added many of the proposed evaluation metrics to the online visualization tool (https://rhna-factors.mtcanalytics.org) to enable users to evaluate different methodology options. HMC members will have an opportunity at the May meeting to assess the three methodology options created in March as a starting place for exploring the use of these metrics. Staff will be seeking feedback about the metrics prior to their use at future meetings.
11 For more information ABAG/MTC Multi-Hazard index used to assess hazard risk, see pages see pages 14-15 of this document from the March 2020 HMC meeting’s agenda packet.
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Item 5, Attachment A
TO: Housing Methodology Committee DATE: June 19, 2020
FR: Deputy Executive Director, Policy
RE: Options for the Income Distribution Component of the RHNA Methodology
Overview The Regional Housing Needs Allocation (RHNA) methodology must assign a total number of housing units to each Bay Area jurisdiction and distribute each jurisdiction’s allocation among four income categories that include households at all income levels. In a letter dated June 9, 2020, the California Department of Housing and Community Development (HCD) provided ABAG with the Regional Housing Needs Determination (RHND) for the Bay Area (Table 1). Table 1: ABAG Regional Housing Needs Determination from HCD Income Category Percent Housing Unit Need Very Low 25.9% 114,442 Low 14.9% 65,892 Moderate 16.5% 72,712 Above Moderate 42.6% 188,130 Total 100% 441,176 The RHNA methodology’s income allocation component is crucial for creating a methodology that successfully achieves the statutory objectives of RHNA. This memo delves deeper into the income allocation methodology approaches that received the most support from Housing Methodology Committee (HMC) members and the audience at the May HMC meeting. For the purpose of the memo and analysis, we have updated the numbers to reflect the RHND from HCD. Refresher on Statutory Requirements Housing Element Law includes the objective that RHNA “[a]llocat[e] a lower proportion of housing need to an income category when a jurisdiction already has a disproportionately high share of households in that income category”1 meaning the RHNA methodology will in part be assessed by HCD in terms of how the allocation works to counter-balance existing concentrations of wealth or poverty. State law also requires the RHNA methodology to improve coordination between the locations of low-wage jobs and housing affordable to low-wage workers (jobs-housing fit). The RHNA methodology must also affirmatively further fair housing, which will require allocating more lower income units to communities that historically have not provided affordable housing. Potential Income Allocation Methodologies Presented at May HMC Meeting At the May HMC meeting, staff presented several possible methodologies for allocating units by income that are aligned with the statutory objectives of RHNA. The options presented represent two fundamentally different processes for determining units by income:
1 See California Government Code Section 65584(d).
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• Income Shift. In this approach, the total number of units allocated to a jurisdiction is identified first, and the income allocation methodology is used to distribute that total among the four income categories.2 Two variants of this approach can be seen in other regions’ RHNA methodologies: Income Shift (used by the San Diego region and ABAG last RHNA cycle) and Income Shift Plus Equity-Focused Factors (used by the Los Angeles and Sacramento regions).
• Bottoms-Up. In this approach, the income allocation methodology is used to identify the number of units for each income category, and the sum of units in the four income categories equals a jurisdiction’s total allocation. This approach was developed based on feedback provided by HMC members. After presenting these options, staff asked HMC members and members of the audience for feedback about which income allocation approach they preferred and which multiplier they liked best for the Income Shift approach. Voting results are displayed in Figure 1 and Figure 2. The comment received by email is in Appendix A. Figure 1 shows that the Bottom-Up and Income Shift approaches received the most support. There was only minimal support for the Income Shift Plus Equity-Focused Factors approach, which indicates this approach is not as complementary to the total allocation methodologies the HMC is considering. Notably, the regions that used the Income Shift Plus Equity-Focused Factors approach used equity-related factors solely in the income allocation methodology. The HMC, however, has expressed support for using equity-related factors in the total allocation methodology, which makes the addition of equity-related factors in the income allocation less imperative. Figure 1: Feedback About Income Allocation Methodology Approaches Based on today’s presentation and your experience using the online visualization tool, do you feel that using the income shift approach in ABAG’s RHNA methodology will successfully achieve the statutory objectives?
2 State law defines the following RHNA income categories:
• Very Low Income: households earning less than 50 percent of Area Median Income (AMI)
• Low Income: households earning 50 - 80 percent of AMI
• Moderate Income: households earning 80 - 120 percent of AMI
• Above Moderate Income: households earning 120 percent or more of AMI
0 5 10 15 20
No, I’ll email comments
No, please explore bottom up approach
No, please explore factor-based adjustment oflower-income units applied to total allocation
Yes
HMC Public
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Figure 2 shows there is strong support for an income shift multiplier between 100% and 150%, if the Income Shift approach is selected to move forward. Figure 2: Feedback About Income Shift Multiplier What level of income shift combined with the HMC’s total allocation methodologies from March seems to most effectively accomplish the statutory objectives and further regional planning goals?
Income Shift In the Income Shift approach, a jurisdiction’s distribution of households by income is compared to the distribution for the region. The Income Shift moves the local income distributions closer to or beyond the regional distribution, depending on the income shift multiplier. A jurisdiction that has a higher percentage of existing households in a given income category compared to the region receives a smaller share of units in that income category, and vice versa. This approach directly addresses the state objective of “[a]llocating a lower proportion of housing need to an income category when a jurisdiction already has a disproportionately high share of households in that income category.”3 Figure 3 shows the steps in the Income Shift process. This process is repeated for each of the four income categories. Figure 3: Income Shift Methodology
An income shift multiplier of 100% results in every jurisdiction’s RHNA mirroring the region’s existing income distribution. In theory, setting the income shift multiplier above 100 percent could close the gap between a jurisdiction’s income distribution and the region’s distribution in a shorter period of time. However, this more aggressive shift could also increase the potential for displacement by directing more market-rate units to jurisdictions with higher proportions of existing lower-income households.
3 See California Government Code Section 65584(d)(4).
0 5 10 15 20 25
150% - 200%
100% - 150%
50% - 100%
0% - 50%
HMC Public
Existing Regional Proportion in Income Category
Existing Jurisdiction Proportion in Income Category
X% Income Shift Multiplier
Adjustment Factor
Existing Jurisdiction Proportion in Income Category
Share of Jurisdiction RHNA in Income Category
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Based on the feedback from the May meeting, staff has developed charts to demonstrate the impacts of applying the income shift multipliers of 100 percent, 125 percent, and 150 percent. Figure 4 shows the results for cities with different income profiles.4 City A’s residents are largely higher-income households and the city has good access to jobs. City B has a lower income profile, with less job access. City C is somewhere in between, falling close to the regional income distribution. Figure 4: Hypothetical Comparison of Effects of Different Income Shift Multipliers
Bottom-Up Income Allocation to Build the Total Allocation In contrast to the Income Shift, the Bottom-Up income allocation approach does not start with a total allocation assigned with a factor-based methodology. Instead, this approach uses factors to determine allocations for the four income categories, and the sum of these income group allocations represents a jurisdiction’s total allocation. Staff has developed two concepts for the Bottom-Up approach, using some of the same factors that have received the most attention and support from the HMC for use in the total allocation (see Table 2). Staff also chose factors where there was more variation in the scores that jurisdictions received, since greater variation increases the factor’s impact in creating distinctions between the allocations jurisdictions receive. A jurisdiction’s allocation within each income category is determined based on how the jurisdiction scores relative to the rest of the region on the selected factors. The jurisdiction’s total allocation is calculated by summing the results for each income category.
4 Figure 4 shows the results from applying the three Income Shift multipliers to the Balanced Equity-Jobs-Transportation methodology developed by HMC members at the March meeting. The results from the three sample methodology options from March were very similar, so staff is only presenting one set of results for the sake of simplicity. The use of the Balanced Equity-Jobs-Transportation option is not an endorsement of this option. View a summary of the sample methodology options from the March meeting for more information.
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Table 2: Factors and Weights for Bottom-Up Income Allocation Variations
Bottom-Up 2-Factor Concept
Affordable: Very Low and Low
• Access to High Opportunity Areas 50%
• Jobs-Housing Fit 50%
Bottom-Up 3-Factor Concept
Affordable: Very Low and Low
• Access to High Opportunity Areas 40%
• Jobs-Housing Fit 40%
• Job Proximity – Transit 20%
Market-Rate: Moderate and Above Moderate
• Job Proximity – Auto 50%
• Jobs-Housing Balance 50%
Market-Rate: Moderate and Above Moderate
• Job Proximity – Auto 50%
• Job Proximity – Transit 30%
• Jobs-Housing Balance 20%
The Bottom-Up 2-Factor Concept uses two factors, weighted equally at 50 percent, for each combined income group. 5 It includes the Jobs-Housing Fit and High Opportunity Areas factors to determine the allocation of affordable units (very low- and low-income). The Jobs-Housing Fit factor specifically relates to the relationship between lower-wage workers and housing units affordable to those workers and the High Opportunity Areas factor supports affirmatively further fair housing by assigning more lower-income units to high opportunity areas. The two factors used to determine the allocation of market-rate units (moderate- and above-moderate income) are the Jobs-Housing Balance and Job Proximity-Auto factors. The Jobs-Housing Balance and Job Proximity-Auto factors are included in the methodology for higher-income units because of their emphasis on the relationships between housing and jobs. Locating market-rate housing close to jobs can provide more options for these households to live near their work, which aligns with the statutory objectives and the HMC’s policy priorities. The Bottom-Up 3-Factor Concept uses three factors to determine the allocation for each income category. It includes the High Opportunity Areas (40 percent weight), Jobs-Housing Fit (40 percent weight), and Job Proximity – Transit (20 percent weight) factors for allocating affordable units. The market-rate units are allocated using the Job Proximity – Auto (50 percent weight), Job Proximity – Transit (30 percent weight), and Jobs-Housing Balance (20 percent weight) factors. This concept includes the same factors as the Bottom-Up 2-Factor Concept, but with different weights. It also adds Job Proximity – Transit as the third factor to encourage more housing near transit, in alignment with the goal of reducing greenhouse gas emissions. Figure 5 shows the pattern for how very low-income units are allocated throughout the Bay Area for several of the Income Shift options and the Bottom-Up options. Jurisdictions shown in dark red have a higher share of very low-income units as a portion of their allocation. Figure 6 shows the same information for above moderate-income units.
5 These factors used the same definitions and methodology as those used in the total income allocation.
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Figure 5: Comparison of Shares of Very Low-Income Units for Income Allocation Options
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Figure 6: Comparison of Shares of Above Moderate-Income Units for Income Allocation Options
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Figure 7 compares the results, including the total allocation and share of units in each income category, for the three multipliers for the Income Shift approach and the two concepts for the Bottom-Up approach. One issue HMC members have raised about the Income Shift is that a higher multiplier is desirable for allocating affordable housing units to communities with more higher-income households but a higher multiplier also directs more market-rate housing to communities with more lower-income households, raising concerns about possible displacement. One benefit of the Bottom-Up approach is that it allows for the allocations for affordable and market-rate units to be set independently, so directing more affordable units to communities with more higher-income households would not necessarily result in more market-rate units going to communities with more lower-income households. For City A (the disproportionately higher-income hypothetical jurisdiction), the two Bottom-Up concepts result in shares of very low- and low-income units that are consistent with the 125 percent Income Shift. For City B (the disproportionately lower-income hypothetical jurisdiction), the share of Above Moderate-Income units is slightly above the 100 percent Income Shift. Although the share of Above Moderate-Income units for City B is smaller in the Bottom-Up concepts, City B still receives a higher share of Above Moderate-Income units than City A or City C. The Bottom-Up concepts seem to provide balance between directing affordable units to communities with more higher-income households while also directing a smaller share of market-rate housing to communities with more lower-income households. The Income Shift approach has only minimal effects on hypothetical City C, since its share of households in each income category is similar to the shares for the region as a whole. The income shift multiplier is applied to the difference between the region and the jurisdiction, and it has only a minimal impact when this difference is small. The Bottom-Up concepts both result in higher shares of affordable units for City C compared to the Income Shift options. One feature of the Bottom-Up approach is that there is less predictability about what the total allocation will be. For City A, one variation resulted in a similar number of total units as the Income Shift, while the second variation resulted in a smaller total allocation. There is a similar pattern in the results for City C. For City B, both Bottom-Up concepts resulted in higher total allocations.
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Figure 7: Hypothetical Comparison of Total Allocations by Income
16%26%28%31%29%29%9%15%16%18%17%17%13%
16%17%18%15%15%
61%43%38%33%39%39%
0
1,000
2,000
3,000
4,000
5,000
Existing
Distribution
100% Shift 125% Shift 150% Shift Bottom-Up
2-Factor
Bottom-Up
3-Factor
City A
(disproportionately higher-income today)
Very Low Low Moderate Above Moderate
47%26%28%31%29%29%
26%
15%16%18%17%17%
16%
16%17%18%15%15%
10%
43%50%58%46%46%
0
200
400
600
800
1,000
1,200
1,400
Existing
Distribution
100% Shift 125% Shift 150% Shift Bottom-Up
2-Factor
Bottom-Up
3-Factor
City B
(disproportionately lower-income today)
Very Low Low Moderate Above Moderate
25%26%26%26%31%32%
17%15%15%14%18%18%
16%16%17%17%14%14%
42%43%43%43%36%36%
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
Existing
Distribution
100% Shift 125% Shift 150% Shift Bottom-Up
2-Factor
Bottom-Up
3-Factor
City C
(similar to region's current income profile)
Very Low Low Moderate Above Moderate
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Table 3: Pros/Cons for Income Shift and Bottom-Up Income Allocation Approaches
Income Shift Bottom-Up Pros
• Allows greater control over total unit allocations
• Directly addresses statutory objective to balance disproportionate concentrations in each income category
Pros
• Allows more fine-grained control for income allocation: allocations for affordable units and market-rate units can be set independently
Cons
• Increasing the share of affordable units in higher-income jurisdictions means more market-rate units must be directed to other jurisdictions
• No ability to finetune income allocations using factors
Cons
• Less predictability for the total unit allocations to jurisdictions
Next Steps At the June meeting, HMC members will have an opportunity to provide feedback about the different income allocation options. The discussion will focus on the following questions:
• Based on the RHND, 41 percent of the units that must be allocated by the RHNA methodology are affordable (very low- and low-income units). What is the right balance for allocating affordable housing?
o Should jurisdictions that are mostly high-income households receive a larger percentage of their RHNA (above 41%) as affordable housing?
o Should jurisdictions with significant populations of low-income households receive a larger percentage of their RHNA (above 41%) as affordable housing?
• Based on the RHND, 59 percent of the units that must be allocated by the RHNA methodology are market-rate (moderate- and above moderate-income units). What is the right balance for allocating market-rate housing?
o Due to concerns about displacement in low-income communities, should jurisdictions that are mostly high-income households receive a larger percentage of their RHNA (above 59%) as market-rate housing?
o Should communities with more low-income residents receive a larger percentage of their RHNA (above 59%) as market-rate units so that jurisdictions that are mostly high-income households are allocated more affordable housing?
• Feedback to staff about refining options:
o If ABAG uses an income shift methodology, what income shift multiplier would you feel most comfortable with?
o If ABAG uses a bottom-up methodology, do you like the factors staff selected for allocating affordable units?
o If ABAG uses a bottom-up methodology, do you like the factors staff selected for allocating market-rate units?
o Do you prefer the income shift approach or the bottom up approach?
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Appendix A: Comments Emailed to Staff about Income Allocation Approaches Only one HMC member submitted written comments related to the survey. Response from Pat Eklund: 1. What level of income shift combined with the HMC's total allocation methodologies from March seems to most effectively accomplish the statutory objectives and further regional planning goals? b. 50% - 100% 2. Based on today's presentation and your experience using the online visualization tool, do you feel that using the income shift approach in ABAG's RHNA methodology will successfully achieve the statutory objectives? d. No, and I’ll email comments to rhna@thecivicedge.com -- We need to re-do today. Due to COVID-19, we need to reduce what we think we can get done in these meetings. Limit them to 2 hours and focus on 1 issue. Maybe do preparation ahead of time if there is a tool that needs to be used. I feel as though my comments have not been captured since I was not able to participate even as a member. This is my 3rd RHNA cycle I have participated in .. and, probably one of the more frustrating ones. We are trying to accomplish too much and what is being sacrificed is our input. There is NO time for input .. My suggestion – limit each meeting to 1 issue .. if we are still on a time crunch .. then meet twice a month. These 3-4 hour meetings are NOT appropriate or good .. again what gets sacrificed is the quality of our input and getting input from all of us. There are some that already have made up their minds and their input is being characterized for the group. By the way, my abstention on these items was NOT noted by Brad Paul. I did not vote or really participate because it took me almost the whole time to figure out
how to get in to the break out session by phone. That technological glitch was
forgotten when this was set up. I want to thank Paisley for trying to help me .. she did a great job given the challenges .. but, bottom line – we are trying to do too much too fast .. SLOW DOWN! The quality of the input is being sacrificed.
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Planning & Transportation Commission
Staff Report (ID # 11476)
Report Type: Approval of Minutes Meeting Date: 7/8/2020
City of Palo Alto
Planning & Development Services
250 Hamilton Avenue
Palo Alto, CA 94301
(650) 329-2442
Summary Title: June 10, 2020 Draft Meeting Minutes
Title: June 10, 2020 Draft PTC Meeting Minutes
From: Jonathan Lait
Recommendation
Staff recommends that the Planning and Transportation Commission (PTC) adopt the meeting
minutes.
Background
Draft minutes from the June 10, 2020 Planning and Transportation Commission (PTC) meetings
were made available to the Commissioners prior to the July 8, 2020 meeting date. The draft PTC
minutes can be viewed on line on the City’s website at
http://www.cityofpaloalto.org/gov/boards/ptc/default.asp.
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