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The purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.

This study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.

The implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.

These findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.

This study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.

The study aims to identify the evoked “sense of place” that the campus community attributes to a watershed area in a Malaysian higher institution, aiming to enhance their participation in watershed conservation. Central to this objective is the incorporation of the concept of a watershed as a place, serving as the conceptual framework for analysis.

This case study explores an urban lake at Universiti Malaya, Malaysia’s oldest higher institution. It uses diverse qualitative data, including document analysis, semi-structured interviews, vox-pop interviews and a co-production workshop, to generate place-based narratives reflecting the meanings and values that staff and students associate with the watershed. Thematic analysis is then applied for further examination.

The data patterns reveal shared sense of place responses on: campus as a historic place, student, staff and campus identity, in-place learning experiences and interweaving of community well-being and watershed health. Recommendations advocate translating these narratives into campus sustainability communication through empirical findings and continuous co-production of knowledge and strategies with the campus community.

The research findings play a critical role in influencing sustainable campus planning and community inclusion by integrating place-based frameworks into sustainable development and watershed management. The study recommends the process of identifying place-based narratives with implications for the development of sustainability communication in a campus environment.

This paper contributes both conceptually and empirically to the sustainable management of a campus watershed area through place-based thinking. It outlines a process for enhancing campus sustainability communication strategies.

The purpose of this paper reporting an exploratory pilot study is to examine how participant engagement in design thinking varies when playing and fixing (playfixing) three partially complete games (broken games).

The data for this study consist of transcripts of five playfixing sessions with a total of 16 participants. Each session focused on one of three games. The authors used Winn’s (2009) design-play-experience framework to analyze features of each game that might relate to differences in design thinking. Next, the authors coded each playfixing session’s transcript to identify patterns of design thinking. Finally, these findings were used to make conjectures about how design features and flaws might encourage particular forms of design thinking.

The findings indicate how playfixing tabletop games with varied levels of complexity, playability and rule definition lead to different patterns of design thinking.

This is a first step toward understanding how the constraints associated with various elements of broken games might direct participants toward desired modes of design thinking and more broadly, contributes to the literature on the educational uses of game making.

The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data.

For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model.

Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM_2.5 concentration level than bagging and boosting ensemble models.

A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast.

The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system

This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM_2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM_2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from IoT emission sensors that can be purchased for research, consultancy and policymaking.

Environmental pollution has increased as a result of modern settlements' expanding demand and rapid population growth. In Ebonyi State, Nigeria, quarrying is one of the activities that has an impact on the environment and ecosystem. The aim of the study is to assess stream water’s quality in order to ascertain how quarry operations affect the streams’ water quality. The present study investigated the environmental impact of quarrying on the physicochemical properties of surface water in Ebonyi State, Nigeria.

A total of 288 surface water samples were taken in 2018, 2019 and 2020 from quarry locations and a Control location for the determination of physicochemical properties and heavy metal contents using standard analytical methods. Datasets were analysed using Fisher’s significance least difference (F-LSD) at the 0.05 probability level.

This study discovered that surface waters around quarries are severely polluted, according to the results of the physico-chemical and heavy metal contents of the surface waters. Most of the physical and chemical properties of the water downstream of the Ishiagu, Umuoghara and Ngbo did not meet World Health Organisation (WHO) standards, such as colour and pH. The heavy metal levels in the Ishiagu, Umuoghara and Ngbo streams were above WHO criteria for Pb, Cd and Fe. The results point to the obvious conclusion, without prejudice to other unexplained factors that the pollution is most likely the result of quarry contamination. Strict measures should be taken to regularly monitor the water quality of the streams.

This study focused on the assessment of physicochemical properties using standard analytical methods to evaluate the environmental impact of quarrying on surface water qualities. The study used the World Health Organisation (WHO, 2011) water guideline as a standard to compare with the study dataset and control measures.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

Today’s world is struggling with the hardship of climate change that has drastically disturbed human life, wildlife and the earth’s biological system. This study aims to show how implementing climate change mitigation strategies and environmental protection measures can ensure sustainable development through collaborative efforts between governmental authorities and the nation’s populace.

An extensive literature review of studies is conducted from across the world concentrating on holistic, sustainable development, enabling a showcase of various conferences, action plans initiated and resolutions passed. VOSviewer software is used to quantify the results of bibliometric analysis and cluster analysis. A total of 260 research studies released between 1993 and 2022 on the Scopus platform are quantified in terms of topmost publications, collaborations among authors, citations index and year-wise publication. The search string has keywords including “climate change,” “sustainable development” and “environment protection.”

The study results revealed a steep increase in research publications in the last three years, from 2017 to 2021, which serves as the basis of the emergence of high-impact articles. The most cited document in this context throws light on assessing vulnerability to climatic risk and building adaptive capacity. It also draws attention to voluntary carbon markets’ rationale while condemning emission trading systems for climate change due to structural flaws, negative consequences and questionable emission-cutting effectiveness. Low energy demand, zero energy buildings and shared socioeconomic pathways should be implemented as strategies for sustainable development.

This study provides a significant opportunity to construct a valuable addition to mitigate climate change. Also, it shows a positive and significant correlation between mitigation and adaptation policies by analyzing publication efforts worldwide considering local climate risks and national adaptation mandates.

The originality of this study lies in its comprehensive approach, combining literature review, bibliometric analysis and cluster analysis to provide insights into current research trends, challenges and potential strategies for addressing climate change and promoting sustainable development. The study’s emphasis on the correlation between mitigation and adaptation policies adds practical significance to its findings.

In addition to agriculture, energy production, and industries, potable water plays a significant role in many fields, further increasing the demand for potable water. Purification and desalination play a major role in meeting the need for clean drinking water. Clean water is necessary in different areas, such as agriculture, industry, food industries, energy generation and in everyday chores.

The authors have used the different search engines like Google Scholar, Web of Science, Scopus and PubMed to find the relevant articles and prepared this mini review.

The various stages of water purification include coagulation and flocculation, coagulation, sedimentation and disinfection, which have been discussed in this mini review. Using nanotechnology in wastewater purification plants can minimize the cost of wastewater treatment plants by combining several conventional procedures into a single package.

In society, we need to avail clean water to meet our everyday, industrial and agricultural needs. Purification of grey water can meet the clean water scarcity and make the environment sustainable.

This mini review will encourage the researchers to find out ways in water remediation to meet the need of pure water in our planet and maintain sustainability.

The purpose of this study is to examine the impact of public open spaces (POS) on host community in Kano Metropolis.

Two sets of questionnaires and participant observation were used to collect data for the study. The questionnaires were used to elicit information on the socioeconomic characteristics of residents and users, a total of 140 residents and 70 users were selected for the study using random sampling without replacement.

Findings revealed majority of the residents earn above 25,000 naira monthly with a percentage of 32.85% while patrons were dominated by respondents that earn below 25,000 monthly. Also, majority of the respondents (94%) have received formal education. Further findings revealed that POS in Kano Metropolis plays an important role in encouraging recreational activities; although some of the open spaces were to some extent declined, the study confirmed the existence of 28 open spaces from the underlying 35 POS within the metropolis. It is noteworthy to note that males were found to be more (80.9%) among users of all the open spaces in the study area with the least participation from their female counterparts. The study further revealed that the adverse effects faced by users of POS and members of the host communities comprised of lack of facilities within the open space, inadequate security, inadequate lighting, lack of vegetation cover, poor parking spaces, breaching the public peace while the residents perceived the open space as means of obstruction of public facilities, causes accident, causes traffic congestion, environmental pollution, increase in accident, obstruction of public facilities, increased accident, degrades the environment, breaching of public peace, traffic congestion and obstruction of public facilities.

The outcome of the study will raise the awareness of the people on the importance, conditions of facilities and the impact associated with the usage of open spaces on adjoining residence. It will also inform stakeholders the modalities to prevent further decline or conversation of open space to other land use and promote proper management of open space facilities and mitigate its likely negative impact on the environment. This will contribute toward achieving Sustainable Development Goal 11.

This study aims to examine the links between carbon emissions, electric vehicles, economic growth, energy use, and urbanisation in 15 countries from 2010 to 2020.

This study adopts seminal panel methods of moments quantile regression with fixed effects to trace the distributional aspect of the relationship. The reliability of methods is confirmed via fully modified ordinary least squares coefficients.

This study reveals that fossil fuel use, economic activity, and urbanisation negatively impact environmental quality, whereas renewable energy sources have a significant positive long-term effect on environmental quality in the selected panel of countries.

The main limitation of this study is the generalisability of the findings, as the study is confined to a limited number of countries, and focuses on non-renewable and renewable energy sources.

Finally, this study proposes several policy recommendations for decision-makers and policymakers in the 15 nations to address climate change, boost sales of electric vehicles, and increase the use of renewable energy sources.

This study calls for a comprehensive transition towards green energy in the transportation sector, enhancing economic growth, fostering employment opportunities, and improving environmental quality.