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Architects use local materials and merge traditional techniques with modern technology to make schools and orphanages cool, welcoming places

Abstract The livestock sector emits harmful gases and bioaerosols, impacting animals, plants, and human health. Ventilation systems in livestock buildings disperse polluted air, affecting nearby air quality depending on the wind patterns and atmospheric stability. Understanding pollutant emission and transmission is crucial for environmental mitigation. This study focuses on fine dust dispersion from dairy cattle buildings. Chemical and microscopic analyses were conducted to...

Indoor particle number size distribution (0.3-10 μm), equivalent black carbon (eBC), and Ångström absorption exponent (AAE) data were collected in real conditions, over a ten-month period at a research area building, in a semirural site, to characterize indoor aerosol loading. Additionally, during the campaign, emissions from four indoor sources commonly used at the site (incense, traditional cigarettes, electronic cigarettes, and heat-not-burn products) were studied during short-term...

The use of Artificial Intelligence (AI) technologies in buildings can assist in reducing energy consumption through enhanced control, automation, and reliability. This review aims to explore the use of AI to enhance energy efficiency throughout various stages of the building lifecycle, including building design, construction, operation and control, maintenance, and retrofit. The review encompasses multiple studies in the field published between 2018 and 2023. These studies were identified...

Predicting the thermal comfort of operators in enclosed cabins under extreme operational conditions is crucial for the enhanced and optimal design of cabin air circulation systems. In this study, an improved supervised machine learning algorithm, namely a Grey Principal Component Analysis (G-PCA) was proposed to evaluate the operators’ thermal comfort. The comprehensive dataset was first attained and constructed from the proposed 32 indicators, which recorded each tested object’s EEG and...

In Hong Kong, 45 % of the population live in public housing buildings. This study aimed to develop deep neural network (DNN) models for efficiently predicting the ventilation rates in public housing buildings in Hong Kong in the era of modular flat design. First, a database of ventilation rates in Cheung Tai House, a representative public housing building, under 23 wind conditions and 32 different ventilation settings, was obtained by means of computational fluid dynamic (CFD) and multi-zone...

An output of the EdTech Hub, https://edtechhub.org/

Two of the development challenges that Belize has recently worked on, with support from the IDB Group, are vulnerability to climate change and educational quality. The measures implemented on both fronts have allowed relevant achievements. In terms of climate resilience, flooding has been significantly reduced, as a result of investments in infrastructure and, especially, in nature-based solutions. Regarding the quality of education, progress has been made with innovative pedagogical models...

Objective To better understand the state of research on the effects of climate change on human health, including exposures, health conditions, populations, areas of the world studied, funding sources, and publication characteristics, with a focus on topics that are relevant for populations at risk. Design Cross sectional study. Data sources The National Institute of Environmental Health Sciences climate change and human health literature portal, a curated bibliographical database of global...

This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Department (IMD) for model training and testing, 70% and 30%, respectively. To anticipate future hydrological shifts, the study harnessed the EC-Earth3 data, presenting an innovative methodology tailored to the unique hydrological dynamics of the...

Urban air pollution is a pressing global issue driven by factors such as swift urbanization, population expansion, and heightened industrial activities. To address this challenge, the integration of Machine Learning (ML) into smart cities presents a promising avenue. Our article offers comprehensive insights into recent advancements in air quality research, employing the PRISMA method as a cornerstone for the reviewing process, while simultaneously exploring the application of frequently...

An output of the Open Development & Education, https://opendeved.net/

High ambient air temperatures in Africa pose significant health and behavioral challenges in populations with limited access to cooling adaptations. The built environment can exacerbate heat exposure, making passive home cooling adaptations a potential method for protecting occupants against indoor heat exposure.

This study explores the imperative need for decolonizing climate change adaptation strategies by focusing on Indigenous knowledge and perspectives. Focusing on the Munda Indigenous communities residing in the coastal areas of Bangladesh, the research offers critical insights into the intricate relationship between Indigenous wisdom and sustainable climate adaptation. By engaging with the Munda Indigenous people and their traditions, this study explores how traditional ecological knowledge...

This study explores the imperative need for decolonizing climate change adaptation strategies by focusing on Indigenous knowledge and perspectives. Focusing on the Munda Indigenous communities residing in the coastal areas of Bangladesh, the research offers critical insights into the intricate relationship between Indigenous wisdom and sustainable climate adaptation. By engaging with the Munda Indigenous people and their traditions, this study explores how traditional ecological knowledge...

As smart thermostats become increasingly available in residential buildings, there is an opportunity to use measured building data to calibrate models for community and district applications, instead of relying on high-fidelity simulations. This study used smart thermostat data from 60,000 houses in North America to create single-zone models. The model structure was defined with an automated forward selection procedure. 61% of the final models were classified as good fits and the structure...

To meet the thermal comfort requirements of room occupants, a fast and accurate method for predicting indoor high-resolution 3D airflow distribution is necessary, which can be combined with heating, ventilation, and air conditioning (HVAC) systems to adjust the indoor environment. Artificial neural networks (ANN) can establish complex mappings between variables with nonlinear relationships. The aim of this study was to verify the feasibility of an ANN for the fast and accurate prediction of...