Climate and Health Report - San Francisco Climate and ...

Understanding the Risk:An Assessment of San Francisco’s Vulnerability to Extreme Heat Events

P R o g R a m o n H e a lt H , e q U i t y a n d S U S ta i n a b i l i t y

Climate and Health

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table of Contents

AcknowledgmentsThis report was made possible through funding from cooperative agreement from the Centers for Disease Control and Prevention (CDC) and the commitment of many individuals who contributed their time and expertise to its development.

For more information contact:San Francisco Department of Public HealthProgram on Health, Equity and Sustainability1390 Market Street, Suite 822San Francisco, CA 94102Program Director: Cynthia [email protected]://www.sfphes.org/elements/climate

Introduction

Background

Methods

Results

Discussion

Recommendations

References

3

4

6

7

9

11

12

San Francisco Department of Public Health 3

in t roduct ion

Climate change results in extreme weather events that are not only detrimental to the environment, but also human health. Extreme heat events in San Francisco are anticipated to increase due to climate change. As a result, San Franciscans will be at higher risk for heat related illness, a largely preventable illness. Heat related illness is a broad range of disease from mild heat stress to the most severe, life threatening—heat stroke. Extreme heat events increase all-cause mortality, and mortality related to heat, respiratory, and cardiovascular causes, resulting in a significant public health burden. As such, the San Francisco Department of Public Health (SFDPH) has been awarded CDC funding to conduct an environmental health assessment of vulnerability to heat waves and air quality.

For the last decade, cities have invested in developing climate action plans to reduce their greenhouse gas emissions, yet lesser attention has been paid to developing adaptive measures to protect the public’s health in the event of climate change-related extreme weather events, or to expanding the capacity of public health departments to plan and prepare for such events. The goal of this project is to conduct an environmental health assessment to identify the community determinants of heat vulnerability and the associated air quality impacts in order to inform climate change adaptation planning efforts. This information will help forecast the specific public health consequences of climate change within San Francisco and inform a heat wave disaster response plan.

Due to San Francisco’s temperate climate, most people don’t view San Francisco as a place of concern for extreme heat events, but climate change models project that heat waves will increase in frequency and severity and San Francisco is particularly vulnerable because of our lack of physiologic and technologic adaptations. It typically takes human biology two weeks to adapt to temperature extremes. Since we do not regularly experience extreme heat events for extended durations, as a population, their bodies have a more difficult time thermoregulating, which can cause

heat stress and increase risk of heat related illness and sometimes death. In San Francisco, we have fewer technologic adaptations because our housing stock is less likely to have central air conditioning both because of its age and because of the typically cooler climate.

While everyone is vulnerable to heat-related illness, certain populations are more at risk, including the elderly, low-income and those with chronic mental disorders and pre-existing medical conditions. Community vulnerability to heat-related morbidity and mortality can be defined by many factors, including individual pre-existing conditions, environmental determinants for exposure and socioeconomic and demographic factors. By taking a comprehensive approach to understanding vulnerability, interventions will target those communities and populations at highest risk for illness in order to advance urban health, social justice and environmental justice.

This report provides an overview of the health department’s approach to identifying and planning for vulnerability to extreme heat events and associated air quality issues including:

1) An overview of the relevant climate change literature, including the identification of factors that increase risk for extreme heat-related morbidity or mortality in San Francisco; 2) The development of a Heat Vulnerability Index (HVI) to determine the spatial distribution of heat wave vulnerability and associated air quality impacts in San Francisco;3) Recommended actions in order to prepare for extreme heat events and their impacts on vulnerable populations; and 4) Next steps to expand public health capacity, and plan and implement adaptations to reduce human health effects of climate change.


background

Climate Change Impacts on San FranciscoWhile climate change is a global problem, its impacts will be local, threatening the security and well-being of San Francisco. Climate change is expected to increase temperatures and increase the frequency and severity of extreme weather events, which will have significant impacts on San Francisco’s environment, health, and economy. California is already experiencing the effects of climate change. Since 1920, average annual temperatures have been increasing across California, including in the San Francisco Bay Area. The July 2006 California heat wave—which was felt in San Francisco—was the largest heat wave on record since 1948.1

Temperature rise from climate change is expected to exacerbate air pollution problems in California. Concentrations of air pollutants, including ozone and fine particulate matter (PM) in particular, may change in response to climate change. Higher temperatures increase the formation of ground-level ozone (smog), and other harmful air pollutants, including particulate matter and nitrogen dioxide.2 These pollutants have many health impacts, including the exacerbation of respiratory diseases.3,4

Extreme heat events and human healthEven relatively moderate temperature increases can lead to death and illness to populations not accustomed to the heat, and tolerance level can be lower for certain populations.5 An analysis of the 2006 California heat wave found significant

increases in a wide range of morbidities statewide, with the highest rates of emergency room visits for heat-related illness in cooler climates, including San Francisco.6 Heat waves are associated with short-term increases in mortality directly related to extreme heat events.7,8,9,10 In addition to deaths directly due to heat, cardiovascular,10,11,12,13,14,15 respiratory,11,13,14,15 cerebrovascular disease,15 and nervous system disorders 9,14 are commonly reported as the underlying cause of death during a heat wave, because people with these pre-existing diseases are more susceptible to death.16

Individual, Social and Environmental Factors that Affect Vulnerability to Climate Change Although exposure to heat and climate conditions influences heat-related health impacts, many other factors, such as physiology, culture, infrastructure, behavior, and social and demographic characteristics, also affect risk. Analyses of historic heat waves in the United States and Europe reveal indicators that modify the relationship between extreme heat events and morbidity and mortality. Table 1 outlines many of the variables that impact heat vulnerability, including individual pre-existing factors (asthma) and socioeconomic factors (age, race, educational attainment, language, income, poverty, living alone, living in a nursing home, population density and employment density), and their effects on health during an extreme heat event.

In addition, only recently has research on the health impacts of heat waves begun to look at not only who is vulnerable to heat waves, but what places are vulnerable.17 Social and place vulnerability is determined by social inequalities—social factors that influence groups’ susceptibility and ability to respond to harm, and place based inequalities—community and built environment characteristics.18 Variables at these levels include environmental exposure factors (temperature, air quality, tree density, proximity to parks/green space, living on top floor), and infrastructure conditions (building age, mobility/access to transportation, air conditioning).

Urban Heat IslandsThe impacts of heat waves are often exacerbated in cities due to urban heat islands. Heat islands are geographical areas where cities have replaced natural land cover—such as trees, soil, and vegetation, with buildings, roads, and other structures. Heat islands create higher temperatures in urban areas because the cooling effects of natural shade and evapotranspiration are lost and replaced with materials that often absorb and trap more heat, such as asphalt.


San

Fran

cisc

o D

epar

tmen

t of P

ublic

Hea

lth

3

Tabl

e 1:

Hea

t Vul

nera

bilit

y V

aria

bles

Fac

tors

H

eat

Vu

lner

abili

ty

Var

iab

le

Dat

a C

olle

cted

E

ffec

ts o

f V

aria

ble

on

Illn

ess

Dur

ing

Ext

rem

e H

eat

Eve

nts

Individual pre-

existing factors

Ast

hma

Rat

e A

ge-a

dju

sted

rat

e of

ast

hma

hosp

italiz

atio

ns p

er 1

0,00

0 re

side

nts

per

yea

r, fo

r th

e ye

ars

2006

-200

8

Man

y p

re-e

xist

ing

heal

th c

ond

ition

s ar

e ex

acer

bat

ed, i

nclu

din

g re

spira

tory

dis

ease

s, 1

6 ca

rdio

vasc

ular

d

isea

se,19

,20

neur

olog

ical

dis

ease

s,14

, 19 an

d m

enta

l illn

ess.

14,1

9,21

,22,

23 D

ue t

o lim

its in

cur

rent

dat

a, a

sthm

a ho

spita

lizat

ion

rate

s w

ere

the

only

dat

a av

aila

ble

.

Demographic and socioeconomic factors

Age

: Inf

ants

, You

ng

child

ren

Pro

por

tion

of p

opul

atio

n ag

ed 0

-4

Chi

ldre

n an

d in

fant

s un

der

the

age

of 5

are

at h

igh

risk

due

to

thei

r re

duc

ed a

bilit

y to

the

rmor

egul

ate,

in

crea

sed

ris

k fo

r d

ehyd

ratio

n, a

nd r

educ

ed a

bilit

y to

com

mun

icat

e d

isco

mfo

rt t

o ca

regi

vers

.

Age

: Eld

erly

P

rop

ortio

n of

pop

ulat

ion

aged

≥65

P

opul

atio

ns a

bov

e th

e ag

e of

65

are

at in

crea

sed

ris

k fo

r m

orta

lity,

10,

11,1

3,6,

5,24

,21 em

erge

ncy

dep

artm

ent

adm

issi

ons

for

resp

irato

ry d

isea

se 3

2 an

d ot

her

heat

-rel

ated

illn

esse

s. 1

0,6

Rac

e P

rop

ortio

n of

non

-whi

te p

opul

atio

n R

ace/

ethn

icity

has

bee

n sh

own

to b

e a

com

mon

ris

k fa

ctor

.10,2

5,26

,27 D

urin

g th

e 20

06 C

alifo

rnia

hea

t wav

e,

ther

e w

ere

sign

ifica

nt in

crea

ses

in t

he r

ates

of e

mer

genc

y d

epar

tmen

t vi

sits

for

mos

t rac

e/et

hnic

ity g

roup

s.6

Ed

ucat

iona

l A

ttai

nmen

t P

rop

ortio

n of

pop

ulat

ion

25+

with

out

a hi

gh s

choo

l deg

ree

Ind

icat

ors

of s

ocio

econ

omic

sta

tus,

incl

udin

g th

e p

erce

ntag

e of

per

sons

with

out

a hi

gh s

choo

l ed

ucat

ion,

low

m

edia

n ho

useh

old

inco

mes

, and

the

per

cent

age

of t

hose

livi

ng in

pov

erty

are

ass

ocia

ted

with

incr

ease

d h

eat

stre

ss,28

mor

talit

y fr

om h

igh

tem

pera

ture

s 11,

26 a

nd in

crea

sed

risk

of h

eat-

rela

ted

mor

bid

ity.10

In

com

e A

vera

ge h

ouse

hold

inco

me

Pov

erty

P

rop

ortio

n p

opul

atio

n be

low

U.S

. Fed

eral

pov

erty

line

Lang

uage

bar

rier

Pro

por

tion

of p

opul

atio

n d

efin

ed a

s lin

guis

tical

ly is

olat

ed

The

abse

nce

of li

ngui

stic

ally

ap

pro

pria

te w

arni

ng s

yste

ms

and

the

inab

ility

for

heal

th-c

are

wor

kers

to

com

mun

icat

e w

ith n

on-E

nglis

h sp

eake

rs m

ay in

crea

se v

ulne

rab

ility

.29

Nur

sing

Hom

e P

rop

ortio

n p

opul

atio

n liv

ing

in a

nur

sing

hom

e E

lder

ly li

ving

in s

enio

r fa

cilit

ies

have

bee

n fo

und

to

be

at in

crea

sed

risk

for

mor

talit

y.25

, 9, 3

0

Soc

ial I

sola

tion

Pro

por

tion

pop

ulat

ion

livin

g al

one

Nei

ghb

orho

ods

and

ind

ivid

uals

with

less

soc

ial c

ohes

ion

are

mor

e vu

lner

able

to

heat

.28, 2

5

Pop

ulat

ion

Den

sity

P

opul

atio

n d

ensi

ty (p

erso

ns/s

qua

re m

ile)

Pla

ces

that

are

mor

e d

ense

ly s

ettle

d h

ave

bee

n as

soci

ated

with

hig

her

heat

str

ess

leve

ls.28

Em

plo

ymen

t D

ensi

ty

Em

plo

ymen

t den

sity

(wor

kers

/sq

uare

mile

)

Environmental Exposure Factors

Sur

face

tem

per

atur

e M

ean

dai

ly t

emp

erat

ure

colle

cted

05/

12/0

8 R

emot

e se

nsor

s ca

n ac

cura

tely

acq

uire

a v

arie

ty o

f gro

und

pro

per

ties

of e

lect

rom

agne

tic r

adia

tion

refle

cted

an

d e

mitt

ed fr

om g

roun

d o

bjec

ts. R

emot

e se

nsin

g is

a v

ery

imp

orta

nt t

ool t

o st

udy

the

urb

an m

icro

clim

ate

supp

lem

entin

g in

situ

mea

sure

men

ts o

n th

e gr

ound

.

Mea

n d

aily

tem

per

atur

e co

llect

ed 0

9/01

/08

Air

Qua

lity

Max

imum

PM

2.5

conc

entr

atio

n (u

g/m

3)

Cha

nges

in w

eath

er p

atte

rns

may

aff

ect t

he c

once

ntra

tion

of lo

cal a

nd r

egio

nal a

ir p

ollu

tant

s.3

Res

earc

h d

emon

stra

tes

that

clim

ate

chan

ge in

duc

ed h

eat w

aves

may

incr

ease

the

con

cent

ratio

n of

air

pol

luta

nts,

in

clud

ing

ozon

e, p

artic

ulat

es, n

itrog

en d

ioxi

de

exac

erb

ate

air

pol

lutio

n-re

late

d m

orta

lity.

2

No

acce

ss t

o P

arks

P

rop

ortio

n of

pop

ulat

ion

that

doe

s no

t liv

e w

ithin

200

m

eter

s of

a p

ark

Res

earc

h su

gges

ts t

hat a

ir te

mp

erat

ure

is r

educ

ed a

roun

d 1

.8 F

for

ever

y 10

0 m

2 of

veg

etat

ion

add

ed t

o a

par

k.31

Tree

Den

sity

N

umb

er o

f tre

es p

er s

qua

re m

ile

The

pre

senc

e of

veg

etat

ion

and

tre

es in

an

urb

an e

nviro

nmen

t pro

vid

es n

atur

al s

had

e an

d e

vap

otra

nsp

iratio

n

that

hel

p co

mba

t th

e ur

ban

hea

t is

land

effe

ct, l

ead

ing

to d

ecre

ases

in a

ir te

mp

erat

ure.

31, 1

4

Hou

sing

Con

diti

ons:

Li

ving

on

the

Top

Fl

oor

Pro

por

tion

of p

opul

atio

n liv

ing

in th

e b

uild

ing’

s to

p fl

oor

Livi

ng o

n th

e to

p flo

or in

a m

ulti-

stor

y b

uild

ing

has

bee

n fo

und

to in

crea

se t

he r

isk

of h

eats

trok

e an

d m

orta

lity

dur

ing

extr

eme

heat

eve

nts.

14, 3

2

Infrastructure Conditions

Bui

ldin

g S

tock

A

vera

ge a

ge o

f bui

ldin

gs

One

of t

he m

ain

risk

fact

ors

rela

ted

to

mor

talit

y d

urin

g a

pas

t he

at w

ave

was

lack

of t

herm

al in

sula

tion

in

dw

ellin

g un

its, w

hich

can

be

asse

ssed

by

bui

ldin

g ag

e.14

Air

Con

diti

on

Pre

vale

nce

Pro

por

tion

pop

ulat

ion

with

out

cent

ral a

ir co

nditi

onin

g O

ne o

f the

mos

t d

ocum

ente

d f

acto

rs d

eter

min

ing

heat

-rel

ated

mor

bid

ity a

nd m

orta

lity

is a

cces

s to

wor

king

ce

ntra

l air

cond

ition

ing.

7,11

,12,

21,2

0

No

acce

ss t

o Tr

ansp

orta

tion

Pro

por

tion

of p

opul

atio

n th

at d

oes

not

live

with

in 0

.5 m

iles

of a

reg

iona

l tra

nsit

stat

ion

Res

earc

h de

mon

stra

tes

that

acc

ess

to t

rans

por

tatio

n (e

ither

car

, bus

, or

trai

n) r

educ

es t

he r

isk

of h

eat-

rela

ted

dea

th.12

Fac

tors

Hea

t Vu

lner

abili

tyVa

riab

le

Individualpre-

existingfactors

Environmental Exposure Factors InfrastructureConditions

Demographic and socioeconomic factorsD

ata

Co

llect

edE

ffec

ts o

f Va

riab

le o

n Ill

ness

Dur

ing

Ext

rem

e H

eat

Eve

nts

Tabl

e 1:

Hea

t Vul

nera

bilit

y Va

riabl

es

61

Figure 5: Surface Temperature Maps (a) upper left: 2008/5/12 Ts Map by NASA; (b) upper right: 2008/5/12 Ts Map by ERSDAC; (c) lower left: 2008/9/1 Ts Map by NASA; (d) lower right: 2008/9/1 Ts Map by ERSDAC.

The two images on the left were post-processed by NASA, while the other two on the right were post-

processed by ERSDAC. Though the surface temperatures were calculated differently by the two agencies, the

relative heat distributions were almost identical. To give an overview of which part of the city generates more

heat, it is sufficient to use one for instance since there is no need to be quantitative at this point. Therefore,

NASA post-processed surface temperature maps on 2008/5/12 and 2008/9/1 were chosen for further

inspection.

61

Figure 5: Surface Temperature Maps (a) upper left: 2008/5/12 Ts Map by NASA; (b) upper right: 2008/5/12 Ts Map by ERSDAC; (c) lower left: 2008/9/1 Ts Map by NASA; (d) lower right: 2008/9/1 Ts Map by ERSDAC.

The two images on the left were post-processed by NASA, while the other two on the right were post-

processed by ERSDAC. Though the surface temperatures were calculated differently by the two agencies, the

relative heat distributions were almost identical. To give an overview of which part of the city generates more

heat, it is sufficient to use one for instance since there is no need to be quantitative at this point. Therefore,

NASA post-processed surface temperature maps on 2008/5/12 and 2008/9/1 were chosen for further

inspection.

Figure 1

Figure 2


methods

The health department identified data from the literature that were found to modify the relationship between heat and illness. Data were collected from 21 variables to investigate the complex interactions of individual, social and environmental vulnerability to extreme heat events and associated air quality impacts in San Francisco (see Table 1). Each variable was mapped by each of the City’s 574 census block groups and the data were analyzed to create several heat vulnerability indices. Thermal remote sensed data were collected on May 12, 2008 representing spring (see Figure 1) and September 1, 2008 representing summer (see Figure 2) to measure the distribution of maximum surface temperature across the City. Variables were aggregated with temperature data in May and again in September. With no information on the true relationship between variables and vulnerability, the interaction of the variables themselves, or the relative contribution each variable makes to vulnerability, assumptions were made including a linear relationship between each variable and vulnerability, and that each variable contributes to vulnerability equally. To address potential colinearities among variables, principle component analysis was employed, creating an additional heat vulnerability index, as described in the Results section.


Resul ts

Variables were standardized by transforming the data into z-scores with a variance of one and mean of zero, such that increasing values correspond with increasing vulnerability. The May and September aggregated z-scores were mapped by census block group, as described above. A Pearson’s correlation matrix revealed that some of the variables appear correlated, in particular and unsurprisingly, many of the socioeconomic variables. To address correlation among multiple variables, a principle components analysis of z-scores was performed, creating a composite index of components that each include a subset of heat vulnerability variables that are

independent of each other and thus can be added together to determine a more accurate composite heat vulnerability index.

The principle components analysis of the z-scores resulted in six categories, or components, explaining 68.82% of the variability. These components include socioeconomic vulnerability, social isolation, air quality, urban density, no vegetation, and elderly. The factor scores of the six components were summed and mapped for each block group to create a cumulative Heat Vulnerability Index (see Figure 3).

Figure 3


Resul ts

To validate the satellite derived surface temperature, it was compared with ground derived temperature sensors. Both surface temperature acquired through remote sensed data (Surface Temp) and air temperature (Air Temp) acquired through local weather stations demonstrate that warm and cool areas are similarly distributed across San Francisco.

Figure 4 depicts the most heat intensive areas of the City resulting from both surface and air temperature data. Indicative of the urban heat island effect, the more urbanized areas of the city to the East and Southeast emit the most heat, while the coolest areas are mostly lakes and natural parks where water and vegetation are dominant, such as the Presidio, Lincoln Park, Golden Gate Park, and Lake Merced Park.

Figure 4


discuss ion

While the different index-creation techniques created slightly different patterns of vulnerability, a few neighborhoods were identified as highly vulnerable by all methods. These neighborhoods include Chinatown, Downtown Civic Center, Bayview, and Mission.

In addition to identifying where residents who exhibit relative heat vulnerability live, the index identifies by geographic location what cause might be driving the vulnerability. For the City as a whole, socio-economic vulnerability accounted for the most variability of all the variables (18.5%), suggesting that socioeconomic factors have the greatest effect on an individual’s ability to prepare and respond to an extreme heat event. For instance, many residents may lack access to health care and services; have an inability to receive and understand heat warnings and emergency preparedness tips, lack the ability to forgo working outdoors during the work day, may not have sufficient capital to purchase and use technologic adaptations, or to live in an area with protective resources like parks and other green spaces. This vulnerability assessment reveals that factors such as ethnicity, linguistic isolation, and low education contribute significantly to relative heat vulnerability. In addition to socioeconomic vulnerability, social isolation, and air quality are also substantial contributors to heat vulnerability, accounting for 14.9% and 13.4% of the variability, respectively. This demonstrates the importance of individual and neighborhood-wide social support, and the dangers of poor air quality on health outcomes during extreme heat events. Table 2 describes how each of the 6 components contributes to citywide relative heat vulnerability, and the variables that describe that component.


from both surface and air temperature data. Indicative of the urban heat island effect, the more urbanized areas of the city to the East and Southeast emit the most heat, while the coolest areas are mostly lakes and natural parks where water and vegetation are dominant, such as the Presidio, Lincoln Park, Golden Gate Park, and Lake Merced Park. DISCUSSION While the different index-creation techniques created somewhat different patterns of vulnerability, a few neighborhoods were identified as highly vulnerable by all methods. These neighborhoods include Chinatown, Downtown Civic Center, Bayview, and Mission.

In addition to identifying where residents who exhibit relative heat

vulnerability live, the index identifies by geographic location what cause might be driving the vulnerability. For the City as a whole, socio-economic vulnerability accounted for the most variability of all the variables (18.5%), suggesting that socioeconomic factors have the greatest effect on an individual’s ability to prepare and respond to an extreme heat event. For instance, many residents may lack access to health care and services; have an inability to receive and understand heat warnings and emergency preparedness tips; lack the ability to forgo working outdoors during the work day; may not have sufficient capital to purchase and use technologic adaptations or to live in an area with protective resources like parks and other green spaces. This vulnerability assessment reveals that factors such as ethnicity, linguistic isolation, and low education contribute significantly to relative heat vulnerability. In addition to socioeconomic vulnerability, social isolation, and air quality are also substantial contributors to heat vulnerability, accounting for 14.9% and 13.4% of the variability, respectively. This demonstrates the

importance of individual and neighborhood-wide social support, and the dangers of poor air quality on health outcomes during extreme heat events. Table 2 describes how each of the 6 components contributes to citywide relative heat vulnerability, and the variables that describe that component. In addition to the citywide analysis, individual components for each block group were mapped allowing for a more nuanced understanding of which areas in the city are impacted by which vulnerability factor. Table 3 describes the major

Table 2: Contributors to Citywide Relative Heat Vulnerability

Contribution to Variability

Component Highly correlated variables

18.5% Socioeconomic vulnerability

Ethnicity; linguistic isolation; low education; low income; low tree density

14.9% Social isolation Living alone; employment density

13.4% Air quality Air quality; asthma; September temperature

9.8% Urban density Population density; building age; May temperature

6.97% No Green Space

No park access; low tree density; September and May temperature

5.28% Elderly Proportion of residents living in nursing homes; proportion of residents over the age of 65

Figure 3: Warm Urban/Downtown Areas (May 12, 2008)

Table 3: Contributors to Neighborhood-Specific Relative Heat Vulnerability


components that contribute to neighborhood-specific heat vulnerability. The maps in Figure 3 highlight some of these warm areas (red indicates warm, blue indicates cool), including areas near US Highway 101 and Interstate 80 freeways, which implies the presence of traffic-related anthropogenic heating, and areas the lack vegetation and tree coverage, including Candlestick Park in Bayview and parts of Downtown and Treasure Island. In contrast, the blue areas of Treasure Island overlay dense vegetation, demonstrating the associated cooling effects. According to the heat vulnerability index, the heat intense areas are likely to be the east and southeast peninsula. Locations with the following features predict more near surface heat:

• Less or no vegetated land cover • Downtown, office, school, production and mixed use land uses • Heavy traffic • Populated bare landsw

It is important to note that this index measures relative vulnerability and not absolute vulnerability. Just because a variable does not load highly on any factor does not necessarily mean it should be ignored when engaging in prevention planning efforts. RECOMMENDATIONS The study of heat distribution and predictions of neighborhoods that are especially vulnerable to extreme heat in San Francisco is valuable for local government agencies to prevent potential damage to the public’s health from the consequences of climate change. The identification of block groups that are particularly vulnerable can aid in public health planning as efforts can be targeted geographically. For instance, the vulnerability map can inform the placement and designation of cooling centers. In addition to location of people who exhibit many factors that create relative heat vulnerability, the index helps identify potential risk factors for vulnerability. This vulnerability assessment reveals that factors such as ethnicity, linguistic isolation, and low education contribute significantly to relative heat vulnerability. In light of this, and with the high percentage of minorities in the San Francisco Bay Area, protecting human health and safety of all communities during a heat wave will require ensuring emergency preparedness efforts reach the linguistically and culturally isolated. Strategies being adopted to reach minority communities include conducting community needs assessments and surveys; increasing community engagement through working with neighborhood councils, local community based organizations (CBOs), and having community representatives on program steering committees; increasing funding for programs and resources, such as interpreters; and increasing programmatic flexibility to allow local agencies to innovate and tailor plans to communities’ distinct and specific needs.33

The other factors identified from this analysis include air quality, social isolation, the lack of green space, urban density, and elderly. Many of these factors deal with built environment conditions. Long term planning efforts to reduce air pollution and to reduce urban heat island effects may help curb increased health risks during extreme heat events. In addition, vehicular restrictions can be put in

Table 3: Contributors to Neighborhood-Specific Relative Heat Vulnerability

Neighborhood(s) Component(s)

Chinatown Socioeconomic vulnerability; high urban density/old buildings

Downtown Civic Center Socioeconomic vulnerability, social isolation, and high urban density/old buildings

Mission district Temperature/air quality; high urban density/old buildings

South of Market, and Potrero Hill

Temperature/air quality; no vegetation

Bayview No vegetation Nob Hill, Haight Ashbury, and portions of Castro/Upper Market, and Noe Valley

High urban density/old buildings

Table 2: Contributors to Citywide Relative Heat Vulnerability

discuss ion


In addition to the citywide analysis, individual components for each block group were mapped allowing for a more nuanced understanding of which areas in the city are impacted by which vulnerability factor. Table 3 describes the major components that contribute to neighborhood-specific heat vulnerability. The maps in Figure 5 highlight some of these warm areas (red indicates warm, blue indicates cool), including areas near US Highway 101 and Interstate 80 freeways, which implies the presence of traffic-related anthropogenic heating and areas that lack vegetation and tree coverage, including Candlestick Park in Bayview and parts of Downtown and Treasure Island. In contrast, the blue areas of Treasure Island overlay dense vegetation, demonstrating the associated cooling effects.

According to the heat vulnerability index, the heat intense areas are likely to be the east and southeast peninsula. Locations with the following features predict more near surface heat:

• Lessornovegetatedlandcover• Downtown,office,school,productionand mixed use land uses• Heavytraffic• Populatedbarelands

It is important to note that this index measures relative vulnerability and not absolute vulnerability. Just because a variable does not load highly on any factor does not necessarily mean it should be ignored when engaging in prevention planning efforts.

Figure 5: Warm Urban/Downtown Areas (May 12, 2008)


Recommendat ions

The study of heat distribution and predictions of neighborhoods that are especially vulnerable to extreme heat in San Francisco is valuable for local government agencies to prevent potential damage to the public’s health from the consequences of climate change. The identification of block groups that are particularly vulnerable can aid in public health planning as efforts can be targeted geographically. For instance, the vulnerability map can inform the placement and designation of cooling centers.

In addition to the location of people who exhibit many factors that create relative heat vulnerability, the index helps identify potential risk factors for vulnerability. This vulnerability assessment reveals that factors such as ethnicity, linguistic isolation, and low education contribute significantly to relative heat vulnerability. In light of this, and with the high percentage of minorities in the San Francisco Bay Area, protecting human health and safety of all communities during a heat wave will require ensuring emergency preparedness efforts reach the linguistically and culturally isolated. Strategies being adopted to reach minority communities include conducting community needs assessments and surveys; increasing community engagement through working with neighborhood councils, local community based organizations (CBOs), and having community representatives on program steering committees; increasing funding for programs and resources, such as interpreters; and increasing programmatic flexibility to allow local agencies to innovate and tailor plans to communities’ distinct and specific needs.33

The other factors identified from this analysis include air quality, social isolation, the lack of green space, urban density, and elderly. Many of these factors deal with built environment conditions. Long term planning efforts to reduce air pollution and to reduce urban heat island effects may help curb increased health risks during extreme heat events. In addition, vehicular restrictions can be put in place to reduce the negative impacts of air pollution during an extreme heat event. The other factors, including social isolation and the elderly, may require a check-up system, using city health workers, or neighborhood groups such as churches and CBOs to make sure those who are isolated or physically impaired are adequately protected during a heat event.

The interactions between climate change and health are numerous. Not only will climate change have significant health impacts, but how we prepare to mitigate and adapt to our changing climate will also influence health. Many climate change mitigation and adaptation efforts also achieve significant public health co-benefits that improve health disparities in many cases. SFDPH should be an essential partner on all climate change adaptation and mitigation plans developed for San Francisco. Responding to climate change is a powerful opportunity to improve the health of our City’s residents.


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