Content uploaded by Kumar Biswajit Debnath
Author content
All content in this area was uploaded by Kumar Biswajit Debnath on Jul 03, 2023
Content may be subject to copyright.
CEES 2023 | 2nd International Conference on
Construction, Energy, Environment & Sustainability
27-30 June 2023, Funchal - Portugal
1
POTENTIAL OF RELATIVE HUMIDITY AS A PROXY OF AIR TEMPERATURE IN
DEVELOPING PASSIVE AND ADAPTIVE BUILDING FAÇADES WITH BIO-BASED
RESPONSIVE MATERIALS
Kumar B. Debnath1
Natalia Pynirtzi1
Jane Scott1
Colin Davie2
Ben Bridgens1
1 Hub for Biotechnology in the Built Environment, School of Architecture, Planning and Landscape, Newcastle
University, Newcastle Upon Tyne, NE1 7RU, United Kingdom
2 School of Engineering, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom
Corresponding author: kumar.debnath@newcastle.ac.uk
Keywords
Relative humidity; Air temperature; Climate data; Weather data; Responsive bio-based material
Abstract
There has been significant development in thermo-responsive materials for drug delivery and bio -medical use; some are bio-
based. However, the use of thermo-responsive bio-based materials in the built environment, especially on the building façade, is
almost non-existent due to complexities including difficulties manufacturing in bulk, cost and durability to weathering. On the
other hand, humidity-responsive materials such as wood are abundant and are used in buildings globally. Furthermore, new bio -
based humidity-responsive materials such as bacterial cellulose (BC) and natural fibres have the potential for building
applications. In this study, we hypothesised that if there was a relationship between the relative humidity and air temperature in
a location, humidity-responsive materials could be used to develop passive and adaptive building façades, which would indirectly
respond to temperature. Here, we selected two sites (New Delhi, India and Newcastle upon Tyne, UK) with temperate climates
— according to the Köppen-Geiger system— to analyse the relationship between relative humidity and air temperature from 37
years (1985-2022) of weather data and typical meteorological year (TMY) climate data for 2004-2018. This relationship
assessment used the Pearson correlation (coefficient and p-value) analysis. Our results showed a strong and statistically significant
negative correlation between the relative humidity and air temperature in all months in 37 years in New Delhi, with the stron gest
correlation in the summer and monsoon months. However, the correlation was strong only in some summer months for Newcastle
upon Tyne. We concluded that humidity-responsive bio-based materials have the potential to be used to actuate passive and
adaptive building façades in New Delhi (for all-year-round use) and Newcastle (only during summer) , which respond indirectly to
external temperature.
1. INTRODUCTION
There have been several thermo-responsive materials used for drug delivery and bio-medical use [1, 2]; some are bio-based [3].
However, the use of thermo-responsive bio-based materials in the built environment, especially on the building façade, is almost
non-existent due to complexities including difficulties manufacturing in bulk, cost, and durability to weathering. On the other
hand, humidity-responsive materials such as wood [4] are abundant and are used in buildings globally [5, 6, 7]. Furthermore, new
bio-based humidity-responsive materials such as bacterial cellulose (BC) and natural fibres have building applications potential.
In this study, we hypothesised that if there was a relationship between the relative humidity and air temperature in a location,
humidity-responsive materials could be used to develop passive and adaptive building façades, which would indirectly respond
to temperature. The objective of the study was to evaluate the correlation between relative humidity and air temperature in the
selected two sites (New Delhi, India and Newcastle upon Tyne, UK) with temperate climates — according to the Köppen-Geiger
system— from 37 years (1985-2022) of weather data and typical meteorological year (TMY) climate data for 2004-2018.
2
2. METHODOLOGY
Two sites (New Delhi, India and Newcastle upon Tyne, UK) with temperate climates — according to the Köppen-Geiger system
[1]— were selected to analyse the relationship between relative humidity and air temperature . For the climate analysis, typical
meteorological year (TMY) climate data based on 2004-2018 was collected from [2]. Furthermore, 37 years (1985-2022) of
weather data were provided by Meteoblue (www.meteoblue.com). We used the Pearson correlation (coefficient and p-value) for
the relationship analysis of the weather data. The Pearson coefficient and p-value were interpreted together to evaluate the
significance of the relationship [10]. The relationship was statistically significant when the coefficient value was as close as +1.0,
and the p-value was lower than 0.05. Satisfying only one was considered a statistically insignificant relationship. We used Python
for the data and statistical analysis with libraries such as pandas, numpy, matplotlib, s tatistics, scipy, csv and Math.
3. RESULT AND DISCUSSION
3.1. CLIMATE ANALYSIS
Within the hourly climate data, relative humidity (RH) and the air temperature were analysed over 24 hours. The results of climate
data analysis showed the RH and temperature annually fluctuated between 10-100% and 3.6-44⁰C, respectively, in New Delhi. In
the case of Newcastle upon Tyne (hereafter Newcastle), the RH and temperature annually wavered between 30-100% and -10 to
+24⁰C, respectively. In New Delhi, the RH decreased, and the temperature was daytime in all months. At night, the RH increased,
and the temperature dropped in the New Delhi climate in all months. In the case of Newcastle, the change in RH and temperature
were not as prominent as in New Delhi, other than the summer months. Furthermore, the next concern was if the change in RH
and temperature were happening simultaneously, which was not evident with the TMY dataset. For such time-dependent
relationship analysis, hourly weather data were analysed in the next section.
3.2. WEATHER ANALYSIS
The 37 years of hourly weather data were analysed to examine the correlation between RH and the temperature of New Delhi
and Newcastle. To show the detailed analysis, we presented the correlation analysis of 1985 and 2021 ( the start and end period
with complete annual data) for New Delhi and Newcastle in Table 1. The study showed that most months in New Delhi had a
statistically significant negative correlation between the RH and temperature, with a p-value lower than 0.01 in all months.
Although the coefficient was only higher than 0.5 in August-85, all the other months showed a high coefficient value for New
Delhi. However, the months in Newcastle did not establish statistically significant relationships apart from some summer months
(May-21 to Sep-21). In 1985, May, August and October showed a medium correlation between RH and temperature. Considering
the statistically significant correlation between RH and temperature, the humidity-responsive bio-based materials such as wood,
BC, and natural fibres might potentially be used to actuate passive and adaptive building façades in New Delhi (for all-year-round
use) and Newcastle (only during summer), which respond indirectly to external temperature.
Table 1: Pearson coefficient and p-value for monthly correlation analysis of hourly RH and temperature data of New Delhi and
Newcastle in 1985 and 2021; Red bold denotes the highest coefficient in the year.
Month-Year
New Delhi
Newcastle upon Tyne
Coefficient
p-value
Coefficient
p-value
Jan-85
-0.895
0.000
0.224
0.000
Feb-85
-0.912
0.000
-0.050
0.197
Mar-85
-0.859
0.000
-0.332
0.000
Apr-85
-0.835
0.000
-0.139
0.000
May-85
-0.749
0.000
-0.550
0.000
Jun-85
-0.779
0.000
-0.599
0.000
Jul-85
-0.918
0.000
-0.426
0.000
Aug-85
-0.921
0.000
-0.529
0.000
Sep-85
-0.897
0.000
-0.370
0.000
Oct-85
-0.468
0.000
-0.510
0.000
Nov-85
-0.872
0.000
0.101
0.007
Dec-85
-0.802
0.000
0.479
0.000
Jan-21
-0.601
0.000
0.043
0.239
Feb-21
-0.813
0.000
-0.274
0.000
Mar-21
-0.704
0.000
-0.570
0.000
Apr-21
-0.587
0.000
-0.538
0.000
May-21
-0.779
0.000
-0.423
0.000
Jun-21
-0.873
0.000
-0.743
0.000
Jul-21
-0.937
0.000
-0.784
0.000
Aug-21
-0.941
0.000
-0.721
0.000
3
Sep-21
-0.948
0.000
-0.722
0.000
Oct-21
-0.609
0.000
-0.131
0.000
Nov-21
-0.801
0.000
-0.018
0.624
Dec-21
-0.574
0.000
0.162
0.000
The data and statistical analysis results from the climate weather data would assist in developing a new generation of low-cost,
low-environmental impact, responsive building skins that moderate internal temperature and humidity by varying their porosity
for the ‘RESPIRE: Passive, Responsive, Variable Porosity Building Skins’ project. This study was an initial step towards
understanding the viability and potential of humid-responsive materials as thermo-responsive materials for building skin use for
particular climates, year-round or seasonal applications. This study would inform further studies on developing low-cost, low-
environmental impact, bio-based building skins.
4. CONCLUSION
The objective of the study was to evaluate the correlation between relative humidity and air temperature in the selected two
sites (New Delhi and Newcastle) with temperate climates from 37 years (1985-2022) of weather data and typical meteorological
year (TMY) climate data for 2004-2018. This relationship assessment used the Pearson correlation (coefficient and p-value)
analysis. The analysis showed a significant statistical correlation in most months in New Delhi; therefore, humidity-responsive
materials could be used to develop passive and adaptive building façades, which would indirectly respond to temperature. In the
case of Newcastle, the correlation was strong only in some summer months in recent times. Therefore, humidity-responsive bio-
based materials might have the potential to be used to actuate passive and adaptive building façades in New Delhi (for all -year-
round use) and Newcastle (only during summer), which respond indirectly to external temperature . This ongoing research would
inform further studies in developing low-cost, low-environmental impact and bio-based responsive building skins.
Acknowledgements
This research was funded by the ‘RESPIRE: Passive, Responsive, Variable Porosity Building Skins ’ project (ID/Ref: 91782) funded
by Leverhulme Trust. We want to thank Meteoblue (www.meteoblue.com) for the climate data collaboration.
References
[1]
S. Chatterjee and P. C.-l. Hui, “Review of applications and future prospects of stimuli-responsive hydrogel based on thermo-
responsive biopolymers in drug delivery systems,” Polymers, vol. 13, no. 13, p. 2086, 2021.
[2]
V. Gopinath, S. Saravanan, A. Al-Maleki, M. Ramesh and J. Vadivelu, “A review of natural polysaccharides for drug delivery
applications: Special focus on cellulose, starch and glycogen,” Biomedicine & Pharmacotherapy, vol. 107, pp. 96-108, 2018.
[3]
B. Das, M. Mandal, A. Upadhyay, P. Chattopadhyay and N. Karak, “Bio-based hyperbranched polyurethane/Fe3O4
nanocomposites: smart antibacterial biomaterials for biomedical devices and implants,” Biomedical Materials, vol. 8, no.
3, p. 035003, 2013.
[4]
A. Holstov, B. Bridgens and G. Farmer, “Hygromorphic materials for sustainable responsive architecture,” Construction and
Building Materials, vol. 98, pp. 570-582, 2015.
[5]
M. H. Ramage, H. Burridge, M. Busse-Wicher, G. Fereday, T. Reynolds, D. U. Shah, G. Wu, L. Yu, P. Fleming, D. Densle y-
Tingley, J. Allwood, P. Dupree, P. F. Linden and O. Scherman, “The wood from the trees: The use of timber in construction,”
Renewable and Sustainable Energy Reviews, vol. 68, pp. 333-359, 2017.
[6]
G. Wimmers, “Wood: a construction material for tall buildings,” Nature Reviews Materials, vol. 2, no. 12, pp. 1-2, 2017.
[7]
J. Hildebrandt, N. Hagemann and D. Thrän, “The contribution of wood -based construction materials for leveraging a low
carbon building sector in Europe,” Sustainable cities and society, vol. 34, pp. 405-418, 2017.
[8]
H. E. Beck, N. E. Zimmermann, T. R. McVicar, N. Vergopolan, A. Berg and E. F. Wood, “Present and future Köppen -Geiger
climate classification maps at 1-km resolution,” Scientific data, vol. 5, no. 1, pp. 1-12, 2018.
[9]
Climate.OneBuilding, “Repository of free climate data for building performance simulation,” 12 September 2022. [Online].
Available: https://climate.onebuilding.org/default.html. [Accessed 15 January 2023].
[10]
OPEX, “Interpreting the Pearson Coefficient,” OPEX Resources, 13 October 2017. [Online]. Available:
https://opexresources.com/interpreting-pearson-
coefficient/#:~:text=The%20Pearson%20coefficient%20helps%20to,be%20interpreted%20together%2C%20not%20indivi
dually.. [Accessed 05 April 2023].