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Exposure to poor indoor air in refurbished buildings is a matter of health concern due to the growing concentrations of various contaminants as a result of building airtightness without amendment of ventilation, or the use of building materials such as glue, paint, thinner and varnishes. Recent studies have been conducted to measure indoor air pollutants and assess the health risks affecting the quality of life, productivity and well-being of human beings. However, limited review studies have been recently conducted to provide an overview of the state of knowledge. This study aims to conduct a scoping review of indoor air quality (IAQ) in the context of refurbished or energy-retrofitted buildings.

A systematic screening process based on the PRISMA protocol was followed to extract relevant articles. Web of Science, Scopus, Google Scholar and PubMed were searched using customised search formulas. Among 276 potentially relevant records, 38 studies were included in the final review covering a period from 2015 to 2022.

Researchers mapped out the measured compounds in the selected studies and found that carbon dioxide (CO₂) (11%) and total volatile organic compounds (11%) were among the most commonly measured contaminants. Two trends of research were found including (1) the impact of ventilative properties on IAQ and (2) the impact of introducing building materials on IAQ.

The contribution of this study lies in summarising evidence on IAQ measurements in refurbished buildings, discussing recent advancements, revealing significant gaps and limitations, identifying the trends of research and drawing conclusions regarding future research directions on the topic.

The purpose of this article is to investigate on changes of the microbial load and the chemical and physical properties of date fruits stored for 6 months under two different temperatures.

A composite sample of 100 kg date fruits from the Khalas variety, season 2019, was collected from the local market in Al Ahsa Province, Saudi Arabia, packaged in 1 kg lots, stored at room and refrigerator temperatures and the microbial contamination and the chemical and physical properties monitored over a period of six months of storage. Total bacteria, lactic acid bacteria, Enterobacteriaceae, yeasts and molds were counted and representatives of yeast and mold contaminants were identified using morphological, physiological and molecular typing techniques. Changes in the color and texture of the samples were also monitored during storage.

The yeasts detected were two strains of each of Lachancea thermotolerans and Rhodosporidiobolus fluvialis and one strain of Cystofilobasidium lacus-mascardii. For molds, one strain of each of Aspergillus niger, Aspergillus flavus, Penicillium chrysogenum and Aspergillus caespitosus have been detected. No significant growth of these microorganisms was observed, but enough load persisted during storage that makes the samples not meeting the microbiological standards. There were significant changes in the color and texture of the fruits during storage.

These findings add important information that can help producers and processors to improve quality and promote marketing of date fruits, especially to international markets.

Exposure to indoor air pollutants poses a significant health risk, contributing to various ailments such as respiratory and cardiovascular diseases. These unhealthy consequences are specifically alarming for athletes during exercise due to their higher respiratory rate. Therefore, studying, predicting and curtailing exposure to indoor air contaminants during athletic activities is essential for fitness facilities. The objective of this study is to develop a neural network model designed for predicting optimal (in terms of health) occupancy intervals using monitored indoor air quality (IAQ) data.

This research study presents an innovative approach employing a long short-term memory (LSTM) recurrent neural network (RNN) to determine optimal occupancy intervals for ensuring the safety and well-being of occupants. The dataset was collected over a 3-month monitoring campaign, encompassing 15 meteorological and indoor environmental parameters monitored. All the parameters were monitored in 5-min intervals, resulting in a total of 77,520 data points. The dataset collection parameters included the building’s ventilation methods as well as the level of occupancy. Initial preprocessing involved computing the correlation matrix and identifying highly correlated variables to serve as inputs for the LSTM network model.

The findings underscore the efficacy of the proposed artificial intelligence model in forecasting indoor conditions, yielding highly specific predicted time slots. Using the training dataset and established threshold values, the model effectively identifies benign periods for occupancy. Validation of the predicted time slots is conducted utilizing features chosen from the correlation matrix and their corresponding standard ranges. Essentially, this process determines the ratio of recommended to non-recommended timing intervals.

Humans do not have the capacity to process this data and make such a relevant decision, though the complexity of the parameters of IAQ imposes significant barriers to human decision-making, artificial intelligence and machine learning systems, which are different. Present research utilizing multilayer perceptron (MLP) and LSTM algorithms for evaluating indoor air pollution levels lacks the capability to predict specific time slots. This study aims to fill this gap in evaluation methodologies. Therefore, the utilized LSTM-RNN model can provide a day-ahead prediction of indoor air pollutants, making its competency far beyond the human being’s and regular sensors' capacities.

Modern human society has continuous advancements that have a negative impact on the quality of the air. Daily transportation, industrial and residential operations churn up dangerous contaminants in our surroundings. Addressing air pollution issues is critical for human health and ecosystems, particularly in developing countries such as Egypt. Excessive levels of pollutants have been linked to a variety of circulatory, respiratory and nervous illnesses. To this end, the purpose of this research paper is to forecast air pollution concentrations in Egypt based on time series analysis.

Deep learning models are leveraged to analyze air quality time series in the 6th of October City, Egypt. In this regard, convolutional neural network (CNN), long short-term memory network and multilayer perceptron neural network models are used to forecast the overall concentrations of sulfur dioxide (SO₂) and particulate matter 10 µm in diameter (PM₁₀). The models are trained and validated by using monthly data available from the Egyptian Environmental Affairs Agency between December 2014 and July 2020. The performance measures such as determination coefficient, root mean square error and mean absolute error are used to evaluate the outcomes of models.

The CNN model exhibits the best performance in terms of forecasting pollutant concentrations 3, 6, 9 and 12 months ahead. Finally, using data from December 2014 to July 2021, the CNN model is used to anticipate the pollutant concentrations 12 months ahead. In July 2022, the overall concentrations of SO₂ and PM₁₀ are expected to reach 10 and 127 µg/m³, respectively. The developed model could aid decision-makers, practitioners and local authorities in planning and implementing various interventions to mitigate their negative influences on the population and environment.

This research introduces the development of an efficient time-series model that can project the future concentrations of particulate and gaseous air pollutants in Egypt. This research study offers the first time application of deep learning models to forecast the air quality in Egypt. This research study examines the performance of machine learning approaches and deep learning techniques to forecast sulfur dioxide and particular matter concentrations using standard performance metrics.

Hydraulic slide valve failure often results from competing failure modes, termed competitive failure. To enhance prediction accuracy for hydraulic slide valve remaining useful life, the authors propose a method incorporating competitive failure and Monte Carlo simulation. This method allows for more accurate prediction of hydraulic slide valve remaining useful life.

In this paper, the competitive failure mode of the hydraulic slide valve is analyzed by studying the two failure modes of the hydraulic slide valve, and the prediction of the remaining useful life of the hydraulic slide valve is studied by using the sample set generated by Monte Carlo simulation and the competitive failure joint model.

The results show that the proposed prediction method based on competitive failure and Monte Carlo simulation is more accurate than the traditional Bayesian joint model prediction method when dealing with the failure mode competition phenomenon of hydraulic slide valve.

In this paper, the remaining useful life prediction of hydraulic slide valve with competitive failure characteristics is studied, which provides a new idea for the remaining useful life prediction method.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0361/

The purpose of this study is the synthesis and characterization of a CMYK palette (cyan of Cr-BiVO₄, magenta of Pr-CeO₂, yellow of Bi-(Ce,Zr)O₂ composite and black of YMnO₃) as an eco-friendly polyfunctional palette that combines (a) high near-infrared reflectance (cool pigments) that allows moderate temperatures in indoor environments and the urban heat island effect; (b) photocatalytic activity for the degradation of organic contaminants of emerging concern of substrates in solution (such as Orange II or methylene blue) and gaseous (NO_x and volatile organic compounds such as acetaldehyde or toluene); (c) X-ray radiation attenuators associated with bismuth ions; and (d) biocidal effect combined with co-doping with bactericidal agents.

Pigments were prepared by a solid-state reaction and characterized by X-ray diffraction, diffuse reflectance spectroscopy, photocatalytic activity over Orange II and scanning electron microscopy.

The behaviour of the proposed palette was compared to that of a commercial inkjet palette, and an improvement in all functionalities was observed.

The functionalities of pigments allow the building envelope and indoor walls to exhibit temperature-moderating effects (with the additional effects of moderating global warming and increasing air conditioning efficiency), purification and disinfection of both indoor and outdoor air, and radiation attenuation.

The proposed palette and its polyfunctional characterization are novel.

Although many health and safety (H&S) studies have widely examined safety risk perception in the construction industry, few studies have explored how this perception influences site workers' risk-taking behaviours during construction. This study aims to examine how construction site workers perceive and judge safety risks in risk-taking behaviours of site workers for intervention safety policy framework that may encourage safe work.

The study employed Pictorial-based Q-Methodology, which documented 63 picture scenarios of risk-taking behaviours from building sites and submitted them for validation from H&S inspectors. In total, 33 pictures emerged as having great potential to cause harm. After using these 33 pictures to elicit data from randomised site workers, the study used Frequency Tabulation, Relative Importance Index (RII) and Kruskal–Wallis Test to analyse the collected data. To fully explain the analysed data for deeper understanding, the study conducted Focus Group Discussions (FGDs) with these site workers to share the thoughts of site workers on these pictures.

Two distinctive pictures emerged from these analyses: one showing risk-taking behaviour likely to contract internal and skin disease and the other likely to fall from height. One of the implications is that construction site workers are unfamiliar with the dangerous contaminants in the materials the site workers use to work, which can potentially harm the site workers' skin and internal organs. Hence, site workers continue engaging in risk-taking behaviours. The other is that site workers are aware of and can mention catastrophic physical injuries attached to site workers' jobs. However, site workers continue engaging in risk-taking behaviours because of site workers' safety plights and rely on the favour and mercies of a supreme being as coping strategies to escape from these physical injuries.

This study is original in that the study uses picture scenarios of risk-taking behaviours to amass an empirical-based understanding of how site workers perceive and respond to H&S risks during construction. This piece of evidence is missing in the numerous research studies in this area. Again, the findings contribute to the state-of-the-art literature regarding risk-taking behaviours on construction sites.

During the COVID-19 pandemic in 2020–2021 in Indonesia, the indoor environmental quality (IEQ) of local houses occupied by infected occupants was adversely affected. This paper aims to appraise the IEQ of the affected Banda Aceh houses with insights into enabling them to be resilient against the negative impacts of the pandemic.

Quantitative field measurement in the case study of five concrete houses located in urban areas which are affected by IEQ factors: (1) indoor air quality (IAQ), (2) thermal comfort and (3) visual comfort, compared against the Indonesian National standard (SNI). The case study involved measurement of the first two factors over 24 h, while the third factor was measured during sun hours. Considering the limitations of the measuring tools for logging available data in this research, air quality is measured from 8 am to 10 pm.

Thermal comfort in the affected houses is generally regarded as warm, optimal and cool comfort, indicated by the effective temperatures of between 20.5 and 27.1°C. Frequently closed windows, limited land area and access had caused a lack of air circulation, with air velocity of dominantly 0 m/s in the houses. The illuminance of natural light received in three houses was insufficient – less than 120 lux as compared with the other two. This study found an uptrend of higher air temperature and relative humidity in the affected houses resulting in poorer IAQ; conversely, the higher the air velocity in the houses, the fewer the indoor air pollutants such as formaldehyde (HCHO), total volatile organic compounds (TVOC) and carbon dioxide (CO₂₎.

This study is a pioneer in evaluating IEQ in houses occupied by COVID-19 patients in Indonesia, especially in dwelling cases in Aceh Province. It also encompasses environmental and societal challenges to sustaining resilient buildings in pandemic hit regions.

Lead is a well-established environmental contaminant that over the last 50 years has become recognized as a neurotoxin with its greatest concern for the developing child (i.e. both in-utero and postnatally). What is problematic is that children exposed to lead often come from lower socioeconomic status (SES), are largely Black communities and are further at increased risk for developing adverse childhood experiences (ACEs). The literature on ACEs had focused much on trauma, single parenting, child abuse, lack of finances and stress, etc., but has not considered the intersectionality of these ACEs as risk factors within environmental neurotoxic exposures such as lead poisoning. This is important as most low SES communities are Black. In particular, within the New York City Housing Authority (NYCHA), Black families have been neglected of proper lead-abatement to their apartments for nearly 70 years.

This is a viewpoint/perspective paper that examines the lived experiences of Black folxs in NYCHA through a Black critical theory (BlackCrit) and antiblackness framework pertaining to ACEs, and lead poisoning within the NYCHA system of New York City. This perspective paper draws upon the last three years of news reports, five decades of publicly available data sets from NYCHA and the comptroller to raise an awareness of how Black children are treated by NYCHA generation after generation which can be argued as a mass atrocity against NYCHA residents. Furthermore, the systematic and institutionalized racism and environmental injustices by NYCHA and the state can also be considered as a crime against humanity. As such, BlackCrit could help to position awareness, advocacy and knowledge about Black folxs residing in NYCHA to achieve fair, safe and affordable public housing to experience Black joy across future generations.

Thus, rather than civic and state government response efforts focusing their full attention and resources to serving and supporting individuals affected by ACEs they should equally consider the environments in which Black people live and also allocate funds proportionally to address these areas often overlooked. Moreover, proportions of these funds should be redirected especially to lead-abatement and removal of known sources of lead exposures, evaluation of suspected sources of lead exposures (i.e. drinking water, baby food and formula, children’s juice and cereal products, superfund and other waste sites, electronic recycling plants, etc.) and accompanied by all affected children undergoing full and comprehensive neuropsychological testing and follow up studies paid for by the state. The goal should have two fundamental objectives: (1) accepting accountability for failing to address these preventable neuropsychological issues directly affecting Black children generation after generation and (2) offering the proper waived or reimbursable supports and resources to help Black children sustain the best quality of life (QOL) trajectory possible when diagnosed with lead poisoning.

The manuscript is a viewpoint/perspective paper grounded in BlackCrit and an antiblackness framework. There are ample public news reports and public data available from NYCHA on these matters over the last three years. However, the scope of this paper was not to delve too deep into these numbers per se, but rather to address the concerns leading up to and arguably contributing to, at least in part, to these numbers of lead-exposed Black children in NYCHA. Lead poisoning has never been considered as an ACE and its relationship to mass atrocity research is novel which may pave a new avenue for research of this kind through the utility of BlackCrit and antiblackness framework to support and advocate for change so that Black children can be provided with a basic human right of safe housing and experience Black joy.

BlackCrit has not been used in the context of lead poisoning research. Mostly individuals and families of middle- and low-income have been studied in the context of poverty and lead poisoning. However, many people who live in poverty, in public housing, within New York are Black. Thus, Black children are generation after generation exposed to unaddressed lead-abatement and it appears that now more than ever BlackCrit should become the framework for how this work should be discussed in the literature to raise awareness to state governments regarding Black folx's persistent lead poisoning, NYCHA's neglect and mass atrocity research as a long overdue advocacy effort to bring the necessary voice, authentic narrative, and actual knowledge of the lived experiences of Black families in NYCHA with lead poisoning.

The goal of this viewpoint/perspective paper should have two fundamental objectives (1) NYCHA and New York State accepting accountability for failing to address these preventable lead poisoning issues directly affecting Black children; and (2) offering the proper support and resources to help Black children sustain the best QOL trajectory possible when diagnosed with lead poisoning.

Lead poisoning research has never been approached through a mass atrocity and BlackCrit framework and perspective. This is the first report on bridging these fields within the context of NYCHA public housing neglect of lead-abatement and continued poisoning of current and future generations of Black children. This failure of NYCHA lead-abatement contributes annually to economic loss in New York State for many years to come which could be entirely avoided.

This study aimed to characterize the concentrations of indoor pollutants (such as carbon dioxide (CO₂), ozone (O₃), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂), as well as particulate matter (PM) (PM₁, PM_2.5 and PM₁₀) in Akure, Nigeria, as well as the relationship between the parameters’ concentrations.

The evaluation, which lasted four months, used a low-cost air sensor that was positioned two meters above the ground. All sensor procedures were correctly carried out.

CO₂ (430.34 ppm), NO₂ (93.31 ppb), O₃ (19.94 ppb), SO₂ (40.87 ppb), PM₁ (29.31 µg/m3), PM_2.5 (43.56 µg/m³), PM₁₀ (50.70 µg/m³), temperature (32.4°C) and relative humidity (50.53%) were the average values obtained. The Pearson correlation depicted the relationships between the pollutants and weather factors. With the exception of April, which had significant SO₂ (18%) and low PM₁₀ (49%) contributions, NO₂ and PM₁₀ were the most common pollutants in all of the months. The mean air quality index (AQI) for NO₂ indicated that the AQI was “moderate” (51–100). In contrast to SO₂, whose AQI ranged from “moderate” to “very unhealthy,” O₃'s AQI ranged from “good” (50) to “unhealthy” (151–200). Since PM₁, PM_2.5 and PM₁₀ made up the majority of PC1’s contribution, both PM_2.5 and PM₁₀ were deemed “hazardous.”

The practical implication of indoor air pollution is long-term health effects, including heart disease, lung cancer and respiratory diseases such as emphysema. Indoor air pollution can also cause long-term damage to people’s nerves, brain, kidneys, liver and other organs.

Lack of literature in terms of indoor air quality (IAQ) in Akure, Ondo State. With this work, the information obtained will assist all stakeholders in policy formulation and implementation. Again, the low-cost sensor used is new to this part of the world.