SNC-Lavalin F+G 16x9 Template...BB101 Overheating Risk Assessment • Criterion 1 of CIBSE TM52 is...

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Tim Taylor Faithful+Gould ‘Climate Change Adaptation for Schools’

Transcript of SNC-Lavalin F+G 16x9 Template...BB101 Overheating Risk Assessment • Criterion 1 of CIBSE TM52 is...

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Tim Taylor

Faithful+Gould

‘Climate Change Adaptation for Schools’

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Overview

1. Introduce on-going work on climate change adaptation by CIBSE School

Design Group (SDG) and the Department for Education (DfE)

2. Modelling impacts of 2°C and 4°C global warming on overheating risk in

schools

3. Monitoring thermal performance of existing schools

4. Q&A

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Adaptation vs. Mitigation

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Mitigation

•Measures or strategies that aim to limit or prevent emissions of greenhouse gases that causeclimate change

Adaptation•Measures or strategies that aim to limit the negative impacts of climate change

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CIBSE Schools Climate Change Adaptation

The CIBSE School Design Group has

convened a Climate Change Adaptation

working group to share knowledge and

promote good practice in adapting

school buildings to future climate.

The work of the group aims to engage

industry-wide stakeholders to develop a

balanced and collaborative range of

recommendations.

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Working Group Activities

Modelling workstream

Testing performance of recent school

designs to future climate scenarios

Monitoring workstream

Gathering data on how school buildings

are performing under current climate

conditions

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Impacts of higher

temperatures on school buildings

Assess performance

of adaptation measures

Modelling

Validate predictive power of thermal models

Monitoring

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Climate Change Adaptation Modelling

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CIBSE SDG Climate Change Adaptation Working Group

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BB101 Overheating Risk Assessment

• Criterion 1 of CIBSE TM52 is used as the

minimum requirement for demonstrating

compliance with BB101 (threshold of 40

hours exceedance)

• CIBSE DSY1 2020 50% weather file (high

emissions)

• Occupied throughout summer period,

09:00 to 16:00, Monday-Friday

• No internal gains in teaching spaces

during the lunch period 12:00 to 13:00

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Primary School

Equipment: 5W/m2

Lighting: 7.2W/m2

People: 60W (pupil), 70W (teacher)

Secondary School

Equipment: 10W/m2

Lighting: 7.2W/m2

People: 70W/person

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CIBSE SDG Climate Change Adaptation Working Group

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4°C global warming by the end of the century

Note: A correction to the baseline period (1980-2000) of

approx. 0.55°C is required in order to define the extent of

global warming relative to the pre-industrial period.

Image source: https://www.ipcc.ch/site/assets/uploads/2018/02/fig-10-26.jpg

In the A1FI scenario, 4°C warming in Global Mean Surface

Temperature (GMST) might be reached by around 2065 with the

mean projections for mid-range carbon cycle assumptions predicting

this degree of warming to occur by approximately 2075. For weather

file selection, the best match is therefore given by the “high”

emissions, 50th percentile in the current CIBSE future weather files i.e.

with the 2080s weather file representing a “4°C world”.

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2020

(2010 to 2039)

2050

(2040 to 2069)

2080

(2070 to 2099)

BB101 / CIBSE TM59 CIBSE DSY1 (50th

percentile range) High

Emissions

GLA Additional testing with

CIBSE DSY2 and DSY3

BREEAM 2018 HEA04 –

Design for Future Thermal

Comfort

CIBSE DSY2 and DSY3

(50th percentile range)

Medium Emissions

CIBSE SDG 2°C warming

scenario

CIBSE DSY1 (50th

percentile range) Low

Emissions

CIBSE SDG 4°C warming

scenario

CIBSE DSY1 (50th

percentile range) High

Emissions

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Future Climate Modelling Brief

• Modelling based on BB101 overheating risk assessment methodology

• Data collected on schools designed to the most recent standards (i.e. to

the requirements of the Facilities Output Specification 2013 or later)

• Spreadsheet pro-forma circulated to consultants and contractors

engaged on DfE procurement frameworks

• Results anonymised and checked

• 11 schools included in dataset

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0%

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School A School B School C School D School E School F School G School H School I School J School K

% Classrooms failing - CIBSE DSY1 2020 (Criterion 1)

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School A School B School C School D School E School F School G School H School I School J School K

% Classrooms failing - 2°C warming (Criterion 1)

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School A School B School C School D School E School F School G School H School I School J School K

% Classrooms failing - 4°C warming (Criterion 1)

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School Characteristics

• Majority are new-build secondary schools, with one primary school and a

SEN/special school. Generally located in urban or suburban contexts.

• Locations represented by four different CIBSE weather files: Birmingham,

Norwich, Leeds and London (London Weather Centre).

• Floor area of the schools ranged from 1,370m2 to 9,480m2. Mix of

building form typologies, from simple rectangular plan to “superblock”.

• Glazing proportion for standard classrooms ranged from 25% to 52%.

• Majority of schools used a hybrid, single-sided ventilation strategy. Most

have thermal mass. All incorporated some form of night-purge strategy.

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Results

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• All consultants used IES

Virtual Environment software

• Window opening profiles

• Night purge ventilation controls

• Most schools incorporated

internal blinds, only one had

external shading

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100%

School A School B School C School D School E School F School G School H School I School J School K

% Classrooms failing - 2°C and 4°C warming (Criterion 1)

Sum of % Classrooms failing - 2020 Criterion 1

Sum of % Classrooms failing - 2°C warming Criterion 1

Sum of % Classrooms failing - 4°C warming Criterion 1

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Findings

• Some incidences of classrooms failing the BB101 overheating risk

assessment with 2°C global warming. Majority of classrooms are failing

the BB101 overheating risk assessment with 4°C global warming.

• Application of cooling hierarchy: some design strategies may have

greater resilience than others e.g. cross-ventilation vs. single-sided.

• Differences in modelling methodologies:

• Ventilation openings and systems

• Use of internal blinds

• Modelling needs to reflect school user and management behaviours.

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Climate Change Adaptation Monitoring

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CIBSE SDG Climate Change Adaptation Working Group

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Building In-Use Surveys

• Why – The DfE are entrusted with billions of pounds of public money. We

must continue to ask how this money can be spent most effectively.

• What – Functionality, Health and Safety , Standardisation, Future

proofing, Minimum Life Expectancy & Sustainable Design

• Where – 70 school buildings across major capital programmes

• When – Buildings open 2-3 years on average

• Who – Technical and Non-Technical end users

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Performance In-Use Environmental Data

Data Source – Data provided to iSERV (K2n Platform)

Notes – Analysis excludes review of:

• Operation strategy and user behaviour

• Any maintenance carried out

• System specification

• The severity of overheating

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BB101 Overheating Performance In-Use

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that are occupied for more than 30 minutes at a time

that,during the school day,

the average internal air temperature does not exceed the average

external air temperaturemeasured over an occupied

day by more than 5ºC;

both temperatures being averaged over the time

period when the external air temperature is 20ºC, or

higher

except when the diurnal temperature range is less

than 4ºC.

▪ It shall be possible to demonstrate within spaces……

BB101 (2018) – Section 7.7.1

The buildings shall be able to achieve temperatures

within the acceptable range when windows, fans and

ventilation systems are operated to reduce

summertime temperatures, and the space has the

intended number of occupants, numbers and types of

computers, data projectors and other ICT equipment.

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CIBSE SDG Climate Change Adaptation Working Group

Classroom Internal Temperatures

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SchoolA B C D E F G H I J K L M N O P

Cross Flow

Yes | NoYes Yes Yes Yes No No No No No No No No No No No No

Thermal Mass

Yes | NoYes Yes Yes Yes Yes Yes No No Yes Yes Yes Yes No Yes Yes Yes

Room Depth (m)

=<7.2m | >7.2m7.2 7.2 7.2 7.2 7.2 7.8 7.2 7.2 7.8 7.8 7.8 7.8 7.8 7.8 7.8 7.8

Room Height (m)

=>3.2m | <3.2m3.2 3.2 3.2 3.2 3.2 3.2 2.7 2.7 3.2 3.2 3.2 3.2 2.7 3.2 3.2 3.2

0%

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Percentage of Rooms Overheating

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Joe Jack Williams

Feilden Clegg Bradley Studios

‘Climate Change Adaptation for Schools’

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Why Model and Monitor?

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Why Model and Monitor?

In short, the performance gap.

Carbonbuzz collated considerable

data on the design and actual

performance of schools.

The schools included used nearly

twice the amount predicted.

So we need to verify the assumptions

of our models.

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Source: Carbonbuzz.org

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Monitoring Methodology

The modelling of the buildings enables us to

understand the future impact of climate change, but

how are we performing now?

Within the monitoring section, we’re trying to

establish:

- Are the occupants comfortable?

- How is the building performing?

- Are there any underlying trends across the building

stock?

We can then start to understand how the impact of

the modelled data.

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nvironmental erformance

uilding Characteristics

odelled erformance

ccupant atisfaction

onitoring odelling

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Collecting Large Scale Operational Data

Collecting energy data is comparatively straightforward:

• Limited number of aspects to measure (e.g. gas, electric, renewables)

• Units are widely understood (kWh)

• Energy can be totalled from sub-meters to provide a building-wide overview

• nergy meters into buildings are commissioned and reliable (mostly…)

Environmental data is more complex:

• Large number of variables and units (temperature, RH, CO2, illuminance, etc.)

• Large number of collection methods (loggers, spot measurements, questionnaires,

etc.)

• Metrics difficult to total/average to create a building wide view

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Monitoring Structure

Monitoring data has been focused on those

that may be impacted by climate change.

The building characteristics are the same

variables as those collected within modelling,

to simplify alignment where possible.

We don’t expect any POE to collect every

aspect of data, but any data can provide

key insights.

All data collected is being treated

anonymously.

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Building CharacteristicsSchool type, GIFA, Age, Building Form, Orientation, U-values,

Thermal Mass, Ventilation Type

Occu

pa

nt S

atisfa

ctio

n

En

viro

nm

en

tal P

erf

orm

ance

Thermal Comfort

Air Quality

Daylighting

Acoustics

Environmental

Control

Overall

Satisfaction

Temperature

Air Quality

Daylighting

Acoustics

Energy

Room

Characteristics

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Monitoring Details – Occupant Data

It is important to understand how the

occupants feel about their building in the

first instance.

There are a number of scales, but we’re

capturing just percentage of positive or

neutral responses, e.g.:

percentage of responses that felt the

summer temperatures were comfortable

The responses should be grouped by role

(i.e. students split from staff).

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Role – staff/student

Thermal Comfort – Summer/Winter

Air Quality – Stuffy/Fresh

Daylighting – Enough, Glare

Acoustics – Noise from outside, noise

from inside

Environmental Control – heating/cooling,

ventilation, daylight

Overall Satisfaction

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Monitoring Details – Environmental Data

Environmental data needs to summarised to

enable clear understanding.

It also needs to be split out by room,

isolating the influence of the room itself.

Many of the metrics relate to those

measured in the modelling data (particularly

TM52).

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Temperature – dry bulb, operative,

indoor/outdoor differential, Min/Mean/Max,

TM52 criteria compliance

Air Quality – CO2, min/mean/max, BB101

threshold exceedances, other pollutants

Daylighting – average daylight factor

Acoustics – LAeq,30mins exceedance

Energy – annual electricity, heating

consumption by end use

Room Characteristics – room type,

orientation, glazing ratio, depth, ceiling

height, ventilation type, thermal mass

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Monitoring Details – Other Data

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A key aspect of revisiting our schools is the broader findings

that are often not directly measurable. This rich data is often

more useful than the quantitative data.

We are asking for key findings from your studies to add

depth to your data.

Some typical examples:

- Doors left open to help with ventilation

- Blinds blocking the openable windows

They all help to build a rounder picture of the current issues

affecting schools.

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Monitoring Details – Results

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Monitoring Details – Results

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Despite the workshops and the wide support we had a very limited response so

won’t be presenting any results as yet…

ut it’s important to understand why this data is difficult to obtain.

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Good reasons not to share data

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From discussions, we have found the following reasons to avoid POEs and

sharing monitored data:

• Finding design defects

• Finding client defects

• Confidentiality of data

• Risk of exacerbating difficult relationships

• Find non-compliant aspects

• Reputational damage

• Enabling the competition

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Good reasons not to share data

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From discussions, we have found the following reasons to avoid POEs and

sharing monitored data:

• Finding design defects

• Finding client defects

• Confidentiality of data

• Risk of exacerbating difficult relationships

• Find non-compliant aspects

• Reputational damage

• Enabling the competition

Liability

PR

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Good reasons not to share data

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From discussions, we have found the following reasons to avoid POEs and

sharing monitored data:

• Finding design defects

• Finding client defects

• Confidentiality of data

• Risk of exacerbating difficult relationships

• Find non-compliant aspects

• Reputational damage

• Enabling the competition

Liability

PR

But do these

reasons stack up?

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Good reasons to share data

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POEs and sharing the data have a number of clear

benefits:

• Quality Assurance

• Improve client relationships

• De-risking future projects

• Improve efficiency of design

• Sustainability Rating Tool Points (e.g. BREEAM)

• Demonstrate excellent performance

• Demonstrate new technologies/techniques

• Demonstrate increased awareness of building issues

• Improve the next generation of buildings

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Good reasons to share data

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POEs and sharing the data have a number of clear

benefits:

• Quality Assurance

• Improve client relationships

• De-risking future projects

• Improve efficiency of design

• Sustainability Rating Tool Points (e.g. BREEAM)

• Demonstrate excellent performance

• Demonstrate new technologies/techniques

• Demonstrate increased awareness of building issues

• Improve the next generation of buildings

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Why as an industry?

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If we don’t share data, there are only 5 schools between now and 2050, including time.

By 2030, we must reduce

CO2e emissions by 45% over

2010 to meet the IPCC 1.5oC

target.

If we don’t meet that target,

climate change adaptation

may be impossible.

Schools constructed linearly

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Why as an industry?

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If we share data, we can design, construct and monitor many more than 5 schools.

This is the only way to ensure

that we not only adapt to the

changing climate, but also

prevent climate change from

becoming far worse.

School performance data

shared within industry.

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Wrap Up• The CIBSE School Design group will still try to collect this

monitoring data

• We will be publishing this when it reaches a useful scale

• The monitoring will be analysed and published when possible

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CIBSE SDG Climate Change Adaptation Working Group

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Questions for the audience…

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CIBSE SDG Climate Change Adaptation Working Group

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Questions for the audienceWe want to know what you think about climate change adaptation in

schools.

Use the cards on your chairs to vote “yes” or “no” to the following

questions.

We will then count the votes and feedback through the group

website.

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CIBSE SDG Climate Change Adaptation Working Group

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Do you think passive measures alone will be enough to mitigate rising UK temperatures in new schools?

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CIBSE SDG Climate Change Adaptation Working Group

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Audience VotingGreen / Yes = 10Red / No = 22

Passive measures alone sufficient in new schools to mitigate rising temperatures

44

CIBSE SDG Climate Change Adaptation Working Group

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Do you think passive measures alone will be enough to mitigate rising UK temperatures in existing schools?

45

CIBSE SDG Climate Change Adaptation Working Group

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Audience VotingGreen / Yes = 5Red / No = 14

Passive measures alone insufficient in existing schools to mitigate rising temperatures

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CIBSE SDG Climate Change Adaptation Working Group

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Do you think comfort cooling will be needed to mitigate rising UK temperatures in new schools?

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CIBSE SDG Climate Change Adaptation Working Group

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Audience VotingGreen / Yes = 16Red / No = 13

Comfort cooling is needed in new schools to mitigate rising temperatures

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CIBSE SDG Climate Change Adaptation Working Group

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Do you think comfort cooling will be needed to mitigate rising UK temperatures in existing schools?

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CIBSE SDG Climate Change Adaptation Working Group

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5050

Audience VotingGreen / Yes = 15Red / No = 7

Comfort cooling is needed in existing schools to mitigate rising temperatures

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CIBSE SDG Climate Change Adaptation Working Group

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5151

Do you think that changing the school day is the solution to climate change adaptation?

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CIBSE SDG Climate Change Adaptation Working Group

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5252

Audience VotingGreen / Yes = 16Red / No = 13

Changing the school day is the solution for climate change adaptation

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CIBSE SDG Climate Change Adaptation Working Group

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5353

Thank you,any questions?

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CIBSE SDG Climate Change Adaptation Working Group