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Bangladesh is one of the leading countries that has been facing serious air pollution issues, with an exponentially higher death rate attributed to it than other environmental pollution. This study aims to identify the sources and dynamics of particulate matter (PM) pollution across different micro-environments in Rajshahi City.

PMs’ concentration data were collected from 60 sampling stations, located across the six micro-environments of the study area, throughout the year using “HT 9600 Particle Counter.” To assess the level of pollution, the air quality index (AQI) was calculated, and different methods, including observation, group discussion, interview and questionnaire survey, were used to identify the pollution sources.

Both PM_2.5 and PM₁₀ exhibit varied concentrations in different micro-environments, and the area covered by different AQI classes differs considerably throughout the year. The monthly average concentration of PM_2.5 and PM₁₀ was highest in January, 200 and 400 µg/m³ and was lowest in September, 46 and 99 µg/m³, respectively. Among the total 1,440 observations, 853 observations (59.24%) exceeded the national standard. Based on the pollution level, different months and micro-environments in the city have been ranked in descending order as January > December > February > March > April > November > October > May > June > July > August > September and traffic > commercial > industrial > residential > green cover > riverine environment.

Although numerous research has been conducted on air pollution in Bangladesh, the authors are certain that no attempt has been made to address the issue from a multi- micro-environmental perspective. This makes the methodology and findings truly unique and significant in the context of air pollution research in Bangladesh.

This study aims to examine the relationship between pollution and life expectancy in oil producing communities, where there is a dearth of empirical evidence on how knowledge and coping strategy, agriculture and foreign capital inflows mediate the relationship between pollution and life expectancy.

The study employed a cross sectional survey design to analyze the roles of knowledge and coping strategy, agriculture and foreign capital inflows in the relationship between pollution and life expectancy in Benekuku and Okpai oil producing communities in the Niger Delta. The study employed the modern structural equation modeling (SEM) estimator.

Estimates show the mediating effect of agriculture on air pollution-longevity (coeff. = 0.398; t-value = 4.425; p < 0.05) and (coeff. = −0.120; t-value = −3.862; p < 0.05) mediating effect of foreign capital. The result revealed that agriculture and foreign capital inflows are significant mediators in pollution-life expectancy relations, affirming the Niger Delta as a pollution haven. However, knowledge and coping strategy with estimate of (coeff. = 0.233; t-value = 6.150; p < 0.05) spurs life expectancy.

The study suggests knowledge of hazard identification and reporting and awareness of coping strategy as the panacea to poor life expectancy rate in these local oil producing communities.

The study departs from existing works by estimating the mediating roles of agriculture and foreign capital inflow in air pollution-Life expectancy by controlling for knowledge and coping strategy using the structural equation model with ethical approval from Health Ethics Research Committee.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0734

This paper aims to present the case for critical realism (CR) as a framework in steering the anticipatory and participatory activities an appropriate analysis of complex problems, aiming toward a transformative change.

Through observation, interview and facilitation for Circular Design Lab and Thai Clean Air Network, this paper unpacks their foresight activities, their key findings and subsequently connects to the Morphogenesis analysis based on an alternative foresight epistemology of CR.

Foresight based on CR philosophy provides a deeper understanding of the complexity and invisibility of air pollution issues in Thailand. Acknowledging the transitive reality beyond this study’s perception, the activity design applies the iceberg models to investigate problem framing and illustrate the stratified reality in three domains: the empirical based on emission reports and legislative regulations; the actual based on patterns of farmers practice and industrial development, activated by causal mechanisms; the real based on structural and mental models, driven by cultural and belief systems in Thailand. At the bottom layer of the iceberg, the real lies the generative mechanisms of pre-existing structural and cultures that constrain Thai citizen from acting on social change.

CR’s emancipatory theory provides an immanent critique towards social improvement by illustrating comprehensive causal explanations of complex problems such as air pollution; while morphogenesis theory elaborates on the unconscious domination of the existing social structures, agencies, and cultures. Thus, the ethical inquiry of CR research is committed to the emancipation of false beliefs and creating conditions for “human prosperity”. However, this non-neutral value commitment is debated in the futures studies field.

The anticipatory activities on air pollution in Thailand bring to light the reality of power and oppression beyond human perception and illustrate the connection to the belief systems and its consequential action or lack thereof in dealing with the issues. The insight to power relationship provides an unconventional way to empower citizens in creating transformative change.

Modern foresight practice has developed under western cultures and societies. Recent efforts are made to investigate the epistemology underlying this field, for the future issues are ever more complex and interrelated across multiple sectors. This requires this study’s consideration of the meaning of knowledge and knowing, influencing the research paradigm. This paper proposes CR as a suitable foresight approach to emancipate this study from the widely accepted epistemologies and examine this study’s presupposition about social reality by a philosophical explanation based on the elements of ontology, causation, structure and persons.

The present study aims to examine the households’ attitudes and intentions to adopt an indoor air purifier against the smog crisis in India by using a comprehensive theoretical framework based on the combination of the Protective Action Decision Model (PADM) and the Theory of Planned Behavior (TPB). The United Nations Sustainable Development Goals (SDGs) 2030 also emphasized ensuring a healthy and safe life, especially by achieving SDG-3, SDG-11 and SDG-13.

Using purposive sampling, the data were collected through a survey questionnaire distributed to 382 households, and study hypotheses were assessed by using partial least squares structural equation modeling employing SmartPLS.

The results revealed that mental health risk perception (MHRP) was the most influential determinant of households’ attitudes toward adopting air purifiers, followed by smog knowledge, physical health risk perception (PHRP), information seeking and product knowledge. Notably, results revealed that households’ attitude is a leading determinant of their adoption intention toward the air purifier compared to subjective norms (SN) and perceived behavioral control (PBC).

To the best of the authors’ knowledge, the present study is the first to provide new insights into an individual’s protective behavior response toward ecological hazards by examining the households’ adoption intention toward the air purifier against the smog crisis using PADM and TPB model inclusively. In addition, the present study analyzes the impact of both PHRP and MHRP on individuals’ protective behavior separately. Also, this study provides theoretical contributions and important practical implications for the government, manufacturers and air purifier sellers.

The purpose of this paper is to evaluate the current situation of buying external technology in Vietnamese manufacturing small and medium enterprises (SMEs) from 2013 to 2018. This paper also aims to examine the effect of buying technology on employment and environmental quality in Vietnam.

External technology purchase and its impact on employment and environmental quality are taken from the Vietnam annual enterprise survey and the using technology in production survey from 2013 to 2018. The estimation is based on a feasible generalized least squares method.

This study finds that external technology purchase in manufacturing SMEs increases the employment rate in the industries. External technology purchase in Vietnamese manufacturing SMEs also increases the level of environmental pollution. This is a negative side of purchasing technology for production because if the technology used is old, outdated and of poor quality, it will increase environmental pollution. In addition, the growth in employment increases air pollution. This shows that purchasing advanced technology selectively helps to increase the employment rate in Vietnamese manufacturing sector, which is followed by a positive impact on environmental quality.

The limitation of this study is that the research period was only investigated from 2013 to 2018 because the General Statistics Office of Vietnam no longer surveys the dataset about using technology in production surveys after 2018. This study has been conducted at the firm level, so results cannot be easily extended to the macroeconomic level, also taking into account the data limitations in terms of sector coverage.

This paper provides necessary policy recommendations for the government and manufacturing SMEs to solve negative technology issues related to the labour market and air quality in Vietnam. The results are expected to help policymakers in Vietnam propose appropriate national science and technology programmes towards sustainable development in the coming decades.

This paper focuses on assessing the effects of buying external technology by Vietnamese small and medium-sized manufacturing enterprises on employment and air quality.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

This study conducts an analysis of the interplay between governance quality, environmental expenditure of the government, and pollution emissions (measured as CO2 emissions) within the BRIC economies.

Utilizing the FMOLS model and marginal effects, we investigate the influence of governance quality and environmental expenditure on environmental quality (CO2 emissions) over the period 1996–2020. We took data for Brazil, Russia, India and China. We excluded South Africa due to its due to its small economic size relative to other BRIC economies, sluggish industrial growth and deteriorating foreign trade which gives contrast outliers to our data.

Results indicate that government investments in environmental protection contribute to a reduction in CO2 emissions. However, the effectiveness of these expenditures is contingent upon the quality of governance. This underscores the significance of robust governance for realizing meaningful reductions in air pollution through environmental spending. Further, increase in GDP per capita and the industrial sector's share of GDP are associated with a significant rise in CO2 emissions across BRIC economies. Conversely, FDI and trade openness exhibit a negative impact on CO2 emissions, with this effect gaining greater resilience when accounting for governance factors.

Like any other studies, the present study also suffers from some limitations. First, besides air quality, environmental quality encompasses multiple dimensions and various characteristics such as water purity, noise pollution, open space access, visual effects of buildings etc. But the present study included only CO2 (air quality) as a proxy of environmental quality due to various problems of data and methods. Second, CO2 (carbon dioxide) emission, which is the dependent variable in our model, is actually influenced by various quantitative and qualitative (both natural and man-made) factors. We included only nine independent variables. However, we could not include many variables due to lack of consistent data. Third, this study included only four countries – Brazil, Russia, India and China (BRIC) and excluded South Africa which is a member of the BRICS block due to its economic size, sluggish industrial growth and deteriorating foreign trade which gives contrast outliers to our data set of the four BRIC countries. Therefore, the future research may be carried out by addressing those issues for better understanding of the environmental problems, governance and policies thereon.

(i) Establish environmental governance committees – The four BRIC countries including South Africa should form a committee comprising government, civil society, and private sector representatives for comprehensive oversight and collaboration in environmental governance. (ii) Invest in capacity building for environmental institutions – Allocate resources to enhance environmental institutions' capacity through training, data improvement, and enforcement strengthening. (iii) Implement green procurement policies – Encourage green procurement in government agencies to drive demand for eco-friendly products and services, promoting sustainable practices. (iv) Incentivize green technology development – Offer tax credits or subsidies to stimulate green technology adoption, including renewable energy and sustainable agriculture. (v) Promote sustainable urban development – Prioritize sustainable urban strategies like public transportation investment and green space promotion to mitigate urbanizations' environmental impacts. (vi) Enhance cross-border cooperation – Foster collaboration on transboundary environmental issues among four BRIC nations including South Africa, including joint research and policy responses. (vii) Promote green finance and investment – Mobilize green finance to support sustainable development projects through instruments like green investment funds and bonds.

This study distinguishes itself by offering a unique analysis of both individual and combined effects of governance and environmental expenditure on environmental quality. Additionally, it encompasses various dimensions of governance, an aspect rarely explored in the BRIC countries.

This study aims to assess the status of sustainable performance, given the significance of indoor air quality related to health and the environment. This research focus on the current status of indoor air quality management in these universities and simplifies its relevance and criticality in safeguarding the well-being of the academic community and the environment.

This study used the Unit-based Sustainability Assessment Tool (USAT) as a comprehensive instrument to assess sustainability performance across various modules: Operations Management, Research, Education and Social/Community. In-depth interviews were conducted across the 11 public universities in Thailand to gain a comprehensive understanding of the current practices, challenges and initiatives related to indoor air quality and sustainability management. The approach provides a foundation for future research to identify causal factors and potential solutions for the observed indoor air quality management gaps.

The research outcomes underscore the outstanding efforts in academic research, with many institutions showcasing advanced measures and a solid dedication to mitigating air pollution. However, there is a noticeable disparity in the practical management of indoor air quality, with many universities presenting unsatisfactory conditions for professors, academic staff and students.

Recognizing that proficient indoor air quality (IAQ) management strengthens the practical and scholarly intersection, this document highlights a crucial alignment with the Sustainable Development Goals (SDGs) and health implications. It advocates for carefully implementing pragmatic IAQ strategies within academic institutions, guiding the pathway towards sustainable, health-conscious environments.

This research addressed indoor air quality (IAQ) within universities. The document intertwines health implications and Sustainable Development Goals (SDGs), revealing a significant gap between academic research and practical IAQ management. While universities are committed to sustainability and community engagement, inconsistencies in IAQ management practices impact staff and student well-being and productivity. This exploration underscores the universal applicability of IAQ management strategies, driving educational institutions towards cultivating healthier, sustainable indoor environments globally.

This research introduces a new approach integrating air quality assessment and sustainability management in Thai universities. It aims to bridge the gap between environmental health and education. The Unit-based Sustainability Assessment Tool is developed as a part of this research, which provides new insights into improving indoor environments. This tool is fundamental for health and learning. The significance of this research lies in guiding policy and campus management towards sustainable, health-promoting practices, thereby adding value to the discourse on educational sustainability. This work can pave the way for enhanced well-being in academic settings, marking a significant step forward in sustainable educational practices.

Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.

The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.

There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.

The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.