• Energy Research

Abstract Technology acceptance plays a critical role in adopting thermal comfort strategies. Not only economic but socio-cultural context becomes pivotal when preference is considered. Yet, the fuzziness of what is acceptable remains under-researched in thermal comfort studies. This work intends to determine an optimal set of strategies for providing thermal comfort in low-income dwellings through a socio-technical methodology. A novel energy target pinch analysis (ETPA) method is developed for identifying optimal solution using a weighted Aggregate Acceptability Index . Data on thermal comfort and their willingness to acceptance was collected from 1267 low-income households in Mumbai, India. The study suggests that there exists a considerable gap in the acceptance of effective thermal comfort strategies by occupants of low-income housing and the interventions at community and policy level could be helpful in bridging this gap. The pinch analysis identified four sets of strategies in order of priority ranking involving adaptive actions and retrofit techniques for achieving thermal comfort under the acceptability constraints. The contribution of this study to thermal comfort literature is through a new ETPA optimisation method, for including the human choices function into the building energy efficiency and thermal comfort thereby providing pragmatic solutions for implementation.

With ‘good health and well-being’ being set as one of the targets of the Sustainable Development Goal (SDG), this paper proposes the application of Pinch Analysis, a quantitative method originally applied to conserve scarce resources in source-demand allocation networks, for identifying gaps in health care service delivery. This method is also found to be useful for health care infrastructure capacity planning and policy testing. The major contribution of this method in this context is identification of marginalized sections and testing specific policies targeted towards them, which will justify release of financial aid and infrastructure development for appropriate sections. We explored this concept for investigating the in-patient health care delivery system in the context of developing nations, where the health care facilities (both public and private) thrive by offering services at drastically different prices. A novel framework is developed in this paper, supported by a case study of Kolkata, India where both the gaps and surplus faced by different sections of population are identified. In order to offset these gaps, we offer recommendations for possible policy implementation. A few hypothetical scenarios are also examined in order to understand the importance of Pinch Analysis for policy testing. We conclude by proving that Pinch Analysis can be a robust integrated decision-making framework for the health care sector, especially in resource-constrained communities.

Future cities of the Global South will not only rapidly urbanise but will also get warmer from climate change and urbanisation induced effects. It will trigger a multi-fold increase in cooling demand, especially at a residential level, mitigation to which remains a policy and research gap. This study forwards a novel residential energy stress mitigation framework called REST to estimate warming climate-induced energy stress in residential buildings using a GIS-driven urban heat island and energy modelling approach. REST further estimates rooftop solar potential to enable solar photo-voltaic (PV) based decentralised energy solutions and establish an optimised routine for peer-to-peer energy sharing at a neighbourhood scale. The optimised network is classified through a decision tree algorithm to derive sustainability rules for mitigating energy stress at an urban planning scale. These sustainability rules established distributive energy justice variables in urban planning context. The REST framework is applied as a proof-of-concept on a future smart city of India, named Amaravati. Results show that cooling energy stress can be reduced by 80 % in the study area through sensitive use of planning variables like Floor Space Index (FSI) and built-up density. It has crucial policy implications towards the design and implementation of a national level cooling action plans in the future cities of the Global South to meet the UN-SDG - 7 (clean and affordable energy) and SDG - 11 (sustainable cities and communities) targets.

The Indian State of Andhra Pradesh is in the process of designing and constructing a planned capital city on the southern banks of the Krishna River at Amaravati. This region will see a significant increase in urban land cover and impervious surface area (ISA) under the 2050 draft perspective plan from the Andhra Pradesh Capital Region Development Authority. As the city central zone sits on the former floodplain of the Krishna River and is subject to concentrated rainfall during monsoon seasons—this increase in ISA risks increasing flood risk through preventing infiltration of storm water and causing increased peak storm water flow (NRSC 2014). The State has announced plans for a “zero-flooding city” through implementation of technologies including green roofs, porous pavement, and detention ponds (ADC 2017). This study aims to facilitate these efforts through mapping of present and future land usage, regional flood risk, and environmental services utilizing open-source data in order to maximize efficiency of installed green infrastructure and minimize future flood damages. A map of relative soil infiltration capacity was created through fuzzy overlay of sand percentage, clay percentage, and bulk density at several depths. Relative flood risk maps for both present-day land cover and a 2050 scenario were developed using several factors: elevation, flow accumulation, surface runoff, and soil properties. A novel Relative Environmental Services Provided Index is proposed here to in order to encourage cost-effective and ecologically sound development through composite visualization of carbon storage, greenery, runoff coefficients, and soil flood prevention.

Abstract Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries. The data were collected between November 2022 and August 2023 as part of the global Many Labs study “Trust in Science and Science-Related Populism” (TISP). The questionnaire contained comprehensive measures for individuals’ trust in scientists, science-related populist attitudes, perceptions of the role of science in society, science media use and communication behaviour, attitudes to climate change and support for environmental policies, personality traits, political and religious views and demographic characteristics. Here, we describe the dataset, survey materials and psychometric properties of key variables. We encourage researchers to use this unique dataset for global comparative analyses on public perceptions of science and its role in society and policy-making.

Urban areas are experiencing excessive heating. Addressing the heat is a challenging but essential task where not only engineering and climatic knowledge matters but also a deep understanding of social and economic dimensions. We synthesize the state of the art in heat mitigation technologies and develop an ‘ITE index’ framework that evaluates the investment (I), time for implementation (T), and effectiveness (E) of candidate heat mitigation measures. Using this framework, we assess 247 multimeasure-centric solution sets composed of all possible combinations of 8 individual measures. The multidimensional ITE index is quantified for heat mitigation effectiveness based on different urban scales, investment levels, the impact of local climate zones (LCZs), and professionals' perceptions using the analytical hierarchy process. The top 50 unique solution sets consist of 4–7 individual measures across all LCZs, with the use of thermally efficient buildings and high-efficiency indoor cooling being the two recurrent measures contributing to the best solution sets. While every city varies in terms of its ideal solution sets, we provide a multimeasure-centric framework for decision-making in which different dimensions can be integrated, understood, and quantified. Renewable and Sustainable Energy Reviews, 186 ISSN:1364-0321