Ronita Bardhan

Dr. Ronita Bardhan

University of Cambridge
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 December 2024 in Communications Earth & Environment
Verified
Journal Article
Open access
PDF file
HLHaiwei Li
Haiwei Li
YZYONGLING ZHAO
YONGLING ZHAO
Chenghao WangChenghao Wang
Chenghao Wang
DÜDiana Ürge-Vorsatz
Diana Ürge-Vorsatz
JCJan Carmeliet
Jan Carmeliet
RBRonita Bardhan
Ronita Bardhan
Urban planners and other stakeholders often view trees as the ultimate panacea for mitigating urban heat stress; however, their cooling efficacy varies globally and is influenced by three primary factors: tree traits, urban morphology, and climate conditions. This study analyzes 182 studies on the cooling effects of urban trees across 17 climates in 110 global cities or regions. Tree implementation reduces peak monthly temperatures to below 26 °C in 83% of the cities. Trees can lower pedestrian-level temperatures by up to 12 °C through large radiation blockage and transpiration. In tropical, temperate, and continental climates, a mixed-use of deciduous and evergreen trees in open urban morphology provides approximately 0.5 °C more cooling than a single species approach. In arid climates, evergreen species predominate and demonstrate more effective cooling within compact urban morphology. Our study offers context-specific greening guidelines for urban planners to harness tree cooling in the face of global warming.

1 November 2015 in Cities
Verified
Journal Article
Closed access
RBRonita Bardhan
Ronita Bardhan
KKKiyo Kurisu
Kiyo Kurisu
KHKeisuke Hanaki
Keisuke Hanaki

1 December 2021 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
RDRamit Debnath
Ramit Debnath
RBRonita Bardhan
Ronita Bardhan
DRDavid M. Reiner
David M. Reiner
JMJ.R. Miller
J.R. Miller

11 September 2020 in PLOS ONE
Verified
Journal Article
Open access
PDF file
RDRamit Debnath
Ramit Debnath
RBRonita Bardhan
Ronita Bardhan
India locked down 1.3 billion people on March 25, 2020, in the wake of COVID-19 pandemic. The economic cost of it was estimated at USD 98 billion, while the social costs are still unknown. This study investigated how government formed reactive policies to fight coronavirus across its policy sectors. Primary data was collected from the Press Information Bureau (PIB) in the form press releases of government plans, policies, programme initiatives and achievements. A text corpus of 260,852 words was created from 396 documents from the PIB. An unsupervised machine-based topic modelling using Latent Dirichlet Allocation (LDA) algorithm was performed on the text corpus. It was done to extract high probability topics in the policy sectors. The interpretation of the extracted topics was made through a nudge theoretic lens to derive the critical policy heuristics of the government. Results showed that most interventions were targeted to generate endogenous nudge by using external triggers. Notably, the nudges from the Prime Minister of India was critical in creating herd effect on lockdown and social distancing norms across the nation. A similar effect was also observed around the public health (e.g., masks in public spaces; Yoga and Ayurveda for immunity), transport (e.g., old trains converted to isolation wards), micro, small and medium enterprises (e.g., rapid production of PPE and masks), science and technology sector (e.g., diagnostic kits, robots and nano-technology), home affairs (e.g., surveillance and lockdown), urban (e.g. drones, GIS-tools) and education (e.g., online learning). A conclusion was drawn on leveraging these heuristics are crucial for lockdown easement planning.

28 June 2022 in Scientific Data
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Journal Article
Open access
PDF file
BDBing Dong
Bing Dong
YLYapan Liu
Yapan Liu
WMWei Mu
Wei Mu
ZJZixin Jiang
Zixin Jiang
PPPratik Pandey
Pratik Pandey
XZXin Zhou
Xin Zhou
This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.

1 December 2015 in Habitat International
Verified
Journal Article
Closed access
RBRonita Bardhan
Ronita Bardhan
SSSayantani Sarkar
Sayantani Sarkar
AJArnab Jana
Arnab Jana
NVNagendra R. Velaga
Nagendra R. Velaga