Air Pollution Issues Research Articles

Insight into the defective sites of TiO2/sepiolite composite on formaldehyde removal and H2 evolution

TiO2/sepiolite composites (T–S–R) with different contents of Ti3+ and oxygen vacancy were successfully prepared through 0D/1D structural assembly and thermal treatment under various atmospheres (R = Air, O2, N2, Ar and H2). The content of Ti3+ and oxygen vacancy was confirmed through electron paramagnetic resonance (EPR) and X-ray photoelectron spectroscopy (XPS), which exhibited significant effect on the photocatalytic formaldehyde (HCHO) removal and H2 evolution. The T–S–Ar composite exhibited much higher formaldehyde degradation efficiency (91.8% within 90 min) and H2 production performance (1974.8 μmol/h/g) than other samples under simulated solar light. According to the material characterizations and DFT calculations, the improved photocatalytic activity could be ascribed to the synergistic effect between natural sepiolite and TiO2. Besides, the generation of mid-gap levels induced by the appropriate content of Ti3+ and oxygen vacancy led to the larger specific surface area, smaller nano-sized TiO2 and higher photogenerated carriers’ separation efficiency. Furthermore, it was found that higher content of oxygen vacancies would act as the recombination centers for electron–hole pairs, thereby greatly reducing the photocatalytic performance. Notably, our study provides a promising candidate for effectively addressing the air pollution (e.g. HCHO removal) and energy issues (e.g. H2 production) based on the defect engineering and mineral support technology.

Can the nation-wide COVID-19 lockdown help India identify region-specific strategies for air pollution?

Air pollution is a serious concern with the developing economics in India and gets more severe when it has major cities ranked among the top 30 polluted cities worldwide. To find a solution, different programs and/or policies have been launched for air quality management country-wide. Unfortunately, no such plan could effectively solve the purpose rather than an unexpected COVID-19 pandemic situation in India. Our study focused on the air pollution status and air quality index (AQI) in 42 cities (that includes 6 metros) representing North, South, East, West, Central, and North-East region of India during the pre-lockdown, four lockdowns and unlock phases. The results depict most of the pollutants except ozone (O3) were significantly reduced in the lockdown-1, and marginally increased in subsequent lockdown phases. Regarding the average AQI, its value was highest in North Indian cities (227), followed by East India (172), Central India (141), North-East India (130), West India (124), and South India (83) during the pre-lockdown. Due to COVID-19 induced lockdown, North Indian cities observed the highest dip in average AQI (108), followed by Central India (113), East India (82), West India (73), South India (55), and North-East India (49) in the lockdown and unlock phases. Thus, the study gave a conspicuous vision on mitigation of air pollution under this pandemic; and, if strategic centralized policies are sensibly implemented and by involving the participation of people of India, then there is a feasibility of air pollution issue management.Supplementary InformationThe online version contains supplementary material available at 10.1007/s41324-021-00426-1.

Air Pollution Modelling by Machine Learning Methods

Precise environmental modelling of pollutants distributions represents a key factor for addresing the issue of urban air pollution. Nowadays, urban air pollution monitoring is primarily carried out by employing sparse networks of spatially distributed fixed stations. The work in this paper aims at improving the situation by utilizing machine learning models to process the outputs of multi-sensor devices that are small, cheap, albeit less reliable, thus a massive urban deployment of those devices is possible. The main contribution of the paper is the design of a mathematical model providing sensor fusion to extract the information and transform it into the desired pollutant concentrations. Multi-sensor outputs are used as input information for a particular machine learning model trained to produce the CO, NO2, and NOx concentration estimates. Several state-of-the-art machine learning methods, including original algorithms proposed by the authors, are utilized in this study: kernel methods, regularization networks, regularization networks with composite kernels, and deep neural networks. All methods are augmented with a proper hyper-parameter search to achieve the optimal performance for each model. All the methods considered achieved vital results, deep neural networks exhibited the best generalization ability, and regularization networks with product kernels achieved the best fitting of the training set.

The Role of Discrete Emotions in Risk Perception and Policy Support during Public Health Crises: The Moderation Effect of SNS Dependency.

People often experience strong emotions during public health crises. This study examines how these emotions shape the perception of risk and support for policies to address the risk. In particular, this study explores the moderating effects of social network services (SNS) use in the process, considering that SNS have become a prominent communication platform during crises. Using a nationwide online survey conducted on the issue of fine dust air pollution in South Korea, this study found that feelings of anxiety, anger, and sadness about the risk issue were positively related to risk perception and policy support, while the relative effects of these emotions varied. Furthermore, the results demonstrated that reliance on SNS for learning (i.e., SNS learning dependency) moderated the influence of anxiety: the positive impact of anxiety was greater among those who used SNS for learning, while no such effects were found among those who used SNS for play or entertainment (i.e., SNS entertainment dependency). The implications of this study are discussed in terms of the distinct role emotions play in public responses to risks and the importance of considering the impact of SNS on public perceptions and judgments in this era of social media.

Prediction of Carbon Monoxide (CO) Atmospheric Pollution Concentrations with Machine Learning and Time Series Analysis in Langkawi, Malaysia

Carbon monoxide (CO) is a non-irritant toxic and odourless gas produced from the incomplete combustion of fossil fuels. Long-term exposures to lower levels of carbon monoxide have wide implications for human health. Thus, an early warning system for CO atmospheric concentration with an accurate and reliable forecasting method is crucial. Studies for predicting CO atmospheric concentration are still limited in Malaysia especially using data science approaches. This study aims to develop and predict future CO concentration for the next few hours by using the statistical time series approach and machine learning approach. The data used for the project is the air quality data of the monitoring station in Langkawi, Malaysia. The data mining tool used for this project is RapidMiner Studio. Based on the results, it showed that Time Series analysis with deep learning gave a reasonably good CO concentration prediction for the next 3 hours with a relative error of approximate 10%. The model developed in this project can be used by authorities as public health’s protection measure to provide an early alarm for alerting the Malaysian populations on the air pollution issue.

Effect of Electric Vehicles Charging Loads on Realistic Residential Distribution System in Aqaba-Jordan

In recent years, air pollution and climate change issues have pushed people worldwide to switch to using electric vehicles (EVs) instead of gas-driven vehicles. Unfortunately, most distribution system facilities are neither designed nor well prepared to accommodate these new types of loads, which are characterized by random and uncertain behavior. Therefore, this paper provides a comprehensive investigation of EVs’ effect on a realistic distribution system. It provides a technical evaluation and analysis of a real distribution system’s load and voltage drop in the presence of EVs under different charging strategies. In addition, this investigation presents a new methodology for managing EV loads under a dynamic response strategy in response to the distribution system’s critical hours. The proposed methodology is applied to a real distribution network, using the Monte Carlo method and the CYME program. Random driver behavior is taken into account in addition to various factors that affect EV load parameters. Overall, the results show that the distribution system is significantly affected by the addition of EV charging loads, which create a severe risk to feeder limits and voltage drop. However, a significant reduction in the impact of EVs can be achieved if a proper dynamic demand response programme is implemented. We hope that the outcomes of this investigation will provide decision-makers and planners with prior knowledge about the expected impact of using EVs and, consequently, enable them to take the proper actions needed to manage such load.

Green technologies for air pollution treatment by microalgae in tubular photobioreactor

Air pollution in general and motorcycle exhaust, in particular, is a big problem attracting a lot of attention from people and researchers worldwide because of the significant impacts it has on humans and the environment. The issue of air pollution is growing, and the impact is more evident than ever. Carbon dioxide represents a series of problems that we face daily but have not yet been effectively solved. Currently, microalgae are known to photosynthesize and use free CO2, bicarbonate ions as a source of nutrients to grow. Microalgae are developed under appropriate environmental conditions, which will bring admirable CO2 treatment efficiency and obtain biomass for other applications. The study approach was an inexpensive and natural air purification solution by microalgae, which is designed as a tubular photobioreactor. The study was conducted by evaluating the ability of Chlorella Vulgaris to grow and absorb CO2 emissions in the newly established system with exhaust gas supplied from a mini motorcycle engine. The results showed that microalgae grew stably in the tubular photobioreactor system with a biomass concentration of 6×106 cells/ml after 42 days of the experiment. Simultaneously with the stable growth of microalgae, the CO2 emission concentration was reduced with 26.59% absorption efficiency after 11 days of the experiment. Finally, establishing the tubular photobioreactor technology system has yielded impressive initial results in cultivating stable growing microalgae combined with CO2 emission treatment.

Green transportation for sustainability: Review of current barriers, strategies, and innovative technologies

The sustainability of a transportation system is a major concerning factor for urbanisation, as evidenced by the ever-growing problems of air pollution issues in major cities. While the growing population and migration don't have too much control to overcome the widespread use of public and personalised vehicles, it has destroyed our global environment. Therefore, the expansion of the transportation system should be carefully planned for global sustainability: so-called green transportation or sustainable transportation. In this paper, factors that should be considered when implementing green transportation for global sustainability have been critically reviewed. Firstly, barriers and challenges associated with current travel demands and blocking the implementation of green transportation have been identified. A three-step strategy (so-called ASI strategy, i.e., avoid, shift, and improve strategy), which had been proposed to overcome the challenges and barriers, was investigated. Identification of innovative technologies or management approaches has been proposed for greening the public transportation system. Finally, some well-recognised success stories of the ASI strategy were presented, in which Avoid can reduce 146–312 kgCO2/y, Shift can be reduced 0.27 kgCO2/revolution of vehicles use and Improve can be reduced 12.4% CO2 emissions. This review guides successful urban planning through the green transportation system.

Air pollution in the cities in Asian Russia: problems and prospects

in this article, we look at the issue of air pollution in cities in the Asian part of Russia, which are the industrial centres of the regions. Air pollution is shaped by a number of factors, including natural ones. In recent years, studies have been carried out in Russia and in foreign countries to determine the impact of pollutants emitted into the atmospheric air. There is a direct correlation between the state of public health and the amount of pollutants in the atmospheric air. Exceeding the maximum allowable concentrations in the air of territories threatens the life and health of people living in them. We have looked at the level of air pollution in cities, including the most polluted ones, and the measures taken by the government and large companies to mitigate the negative effects.

Ambient Air Quality and General Health Outcomes in Nigde (Turkey) between 2011 and 2017

Background:We aimed to provide information for health practitioners and other related people about the association between ambient air quality and adverse health outcomes in the general population of Nigde, a central Turkish city, within the context of current health data epidemiological evidence.Methods:The present study highlights the connection between health problems and time series of particulate matter (PM10) and sulphur dioxide (SO2) in Nigde, Turkey between 2011 and 2017. Significant morbidity is linked to ambient air pollution, resulting in a significant economic cost to society.Results:We found that the required funds to treat cancers and chronic obstructive pulmonary disease triggered by ambient air pollution in Nigde, exceed 9 million US dollars per year, even when only the city center is taken into account.Conclusion:As Turkish cities grow and urban population density increases, air pollution issues need to be given priority in order to protect the health of the public and support sustainable development for future generations. It is recommended that particulate matter concentration in this urban center should be significantly reduced to minimize health problems.

Dynamic Pore Modulation of Stretchable Electrospun Nanofiber Filter for Adaptive Machine Learned Respiratory Protection.

The recent emergence of highly contagious respiratory disease and the underlying issues of worldwide air pollution jointly heighten the importance of the personal respirator. However, the incongruence between the dynamic environment and nonadaptive respirators imposes physiological and psychological adverse effects, which hinder the public dissemination of respirators. To address this issue, we introduce adaptive respiratory protection based on a dynamic air filter (DAF) driven by machine learning (ML) algorithms. The stretchable elastomer fiber membrane of the DAF affords immediate adjustment of filtration characteristics through active rescaling of the micropores by simple pneumatic control, enabling seamless and constructive transition of filtration characteristics. The resultant DAF-respirator (DAF-R), made possible by ML algorithms, successfully demonstrates real-time predictive adapting maneuvers, enabling personalizable and continuously optimized respiratory protection under changing circumstances.

Decrease in life expectancy due to COVID-19 disease not offset by reduced environmental impacts associated with lockdowns in Italy

The consequence of the lockdowns implemented to address the COVID-19 pandemic on human health damage due to air pollution and other environmental issues must be better understood. This paper analyses the effect of reducing energy demand on the evolution of environmental impacts during the occurrence of 2020-lockdown periods in Italy, with a specific focus on life expectancy. An energy metabolism analysis is conducted based on the life cycle assessment (LCA) of all monthly energy consumptions, by sector, category and province area in Italy between January 2015 to December 2020. Results show a general decrease (by ∼5% on average) of the LCA midpoint impact categories (global warming, stratospheric ozone depletion, fine particulate matter formation, etc.) over the entire year 2020 when compared to past years. These avoided impacts, mainly due to reductions in fossil energy consumptions, are meaningful during the first lockdown phase between March and May 2020 (by ∼21% on average). Regarding the LCA endpoint damage on human health, ∼66 Disability Adjusted Life Years (DALYs) per 100,000 inhabitants are estimated to be saved. The analysis shows that the magnitude of the officially recorded casualties is substantially larger than the estimated gains in human lives due to the environmental impact reductions. Future research could therefore investigate the complex cause-effect relationships between the deaths occurred in 2020 imputed to COVID-19 disease and co-factors other than the SARS-CoV-2 virus.

Impacts of reducing air pollutants and CO2 emissions in urban road transport through 2035 in Chongqing, China

The road transport sector in megacities is confronted with pressing local air pollution and carbon dioxide (CO2) control issues. To determine effective policy instruments for saving energy and the co-control of air pollutants and CO2, several mainstream measures were examined and compared in Chongqing's road transport sector from 2017 to 2035. An integration assessment framework was developed by combining the Long-range Energy Alternatives Planning (LEAP) system and a set of quantitative methods for evaluating the co-benefits of emission reductions (including the air pollutant equivalent (APeq), co-control coordinate system, and pollutant reduction cross-elasticity (Elsa/b)). Results showed that the shifting transportation modes scenario presented the most significant potential for energy-saving and emission reductions, reducing energy use by 30.9% and air pollutants and CO2 emissions by approximately 27–32% compared with the business as usual (BAU) scenario in 2035. The improving energy efficiency scenario also provided significant co-benefits for reducing air pollutants and CO2 emissions. Nevertheless, the promoting alternative fuel scenario may increase fine particulate matter (PM2.5) emissions by 2.2% compared to BAU in 2035 under the cleanness of regional electricity in 2017. Our findings suggest that the shifting transportation modes were effective measures to reduce air pollutants and CO2 in the short term synergistically, and highlighted the importance of cleaner electricity generation to develop electric vehicles in the medium and long term.

Air protection policy in the 2019 parliamentary campaign in Poland. An analysis of positions

This article seeks to investigate whether the election committees that won seats in the 2019 parliamentary elections had noted the public concerns about the issue of air not meeting the normative standards, and whether they offered Poles a specific vision of an air protection policy in their election manifestoes. This analysis concerns the proposals of election committees to limit low-stack emissions. Answering the research questions posed: (1) to what extent do election manifestoes address the issue of air pollution in Poland?; (2) are the tools for the implementation of environmental policy as concerns the reduction of low-stack emissions indicated, and can they be effective? leads to the conclusion that the successful election committees noted public concerns about air pollution, and addressed air protection policy to a varied extent, though not always presenting specific solutions to eliminate low-stack emissions To achieve the purpose of the research the methods of source and comparative analysis were used.

Mobility-based environmental justice: Understanding housing disparity in real-time exposure to air pollution and momentary psychological stress in Beijing, China

Environmental justice is a crucial environmental and social problem. Previous research in the cities of developed countries has found that ethnic minorities and low-income people were disproportionately exposed to the residential environment with more serious environmental risks. This study proposed a transition from the residence-based perspective to a mobility-based and context-aware approach to reinterpret environmental justice with a focus on the air pollution issue in urban China. A novel research protocol combining geographic ecological momentary assessment and portable air pollutant sensors was developed to collect and analyze real-time data of air pollution exposure and psychological stress for residents living in the same residential neighborhood of Beijing, China. The results show that residents of different types of housing were exposed to varying PM2.5 concentrations although they experienced similar levels of air pollution in their residential neighborhoods. Residents of public low-rent housing were the disadvantaged group because of their limited mobility, exposure to serious air pollution at home, and insensitive stress responses to air pollution. These findings not only uncover the mobility-based environmental justice issue in the context of government-led and egalitarianism-pursuing urban China, but also provide references for the residential mix policy on how to narrow the disparity in environmental pollution exposure from the perspective of human mobility.

A hybrid ant lion optimization chicken swarm optimization algorithm for charger placement problem

Transportation electrification is known to be a viable alternative to deal with the alarming issues of global warming, air pollution, and energy crisis. Public acceptance of Electric Vehicles (EVs) requires the availability of charging infrastructure. However, the optimal placement of chargers is indeed a complex problem with multiple design variables, objective functions, and constraints. Chargers must be placed with the EV drivers’ convenience and security of the power distribution network being taken into account. The solutions to such an emerging optimization problem are mostly based on metaheuristics. This work proposes a novel metaheuristic considering the hybridization of Chicken Swarm Optimization (CSO) with Ant Lion Optimization (ALO) for effectively and efficiently coping with the charger placement problem. The amalgamation of CSO with ALO can enhance the performance of ALO, thereby preventing it from getting stuck in the local optima. Our hybrid algorithm has the strengths from both CSO and ALO, which is tested on the standard benchmark functions as well as the above charger placement problem. Simulation results demonstrate that it performs moderately better than the counterpart methods.

Assessment of air pollution by PM10 suspended particles in the urban agglomeration of Central Europe in the period from 2001 to 2018

The paper deals with the assessment of PM10 suspended particles air pollution level in the urban agglomeration of Olomouc in the Czech Republic. The evaluation also presents an example of completion of an incomplete PM10 data series in Olomouc between the years 2007 and 2011, when no measurement of this pollutant was performed in the city. An incomplete series of measurements in the city of Olomouc was supplemented by dependencies with measurements in Přerov and Prostějov located in the same urban agglomeration. The limit value of daily PM10 concentration is exceeded in this area. The assessment provides a detailed analysis of the suspended particles pollution trends in the area of interest. PM10 concentrations show a decreasing trend for spring, autumn and particularly summer months. In contrast, during winter months such trend was not observed, which proves the hypothesis of ongoing emissions from local domestic heating in the winter. Knowledge of the development of concentrations of suspended PM10 particles is an important basis for regional and international bodies dealing with the issue of air pollution, especially in evaluating the effectiveness of the measures taken. Local domestic heating is the biggest problem of air pollution by PM10 in the Czech Republic. The methodology used to complete missing concentration data as well as to assess PM10 trends can also be used for other localities especially with a similar composition of pollution sources, meteorological and geographical conditions.

Current problems of environmental monitoring in urban agglomerations at the regions of Russia

This article outlines the results of a study of environmental problems and environmental monitoring conducted in large cities located in the territories of the subjects of the Russian Federation, in particular, at the territory of Krasnoyarsk Krai, a subject of the Russian Federation. Meanwhile, the main trends in the development of cities and the urban environment as a whole are indicated. The paper provides data on the pollution of water resources of the Krasnoyarsk Krai, caused, among other things, by the anthropogenic impact on the environment, and identifies environmental problems arising from the functioning and development of large urban agglomerations. In addition, the tasks and problems associated with the realization of environmental monitoring have been investigated, the prospects for its application in cities have been determined, and the tasks solvable by using data on the state of the natural urban environment, as well as areas close to the city and experiencing serious impacts due to the livelihood of the urban population, have been identified. Within the study, sufficient attention is paid to the issues of ensuring the purity of water resources used in urban agglomerations, the issues of environmental pollution caused by accumulations of waste of the urban population at urban landfills, as well as landfills positioned in areas adjacent to cities, the problems of changes in the landscape, soil, and vegetation cover in large cities. The issues of atmospheric air pollution in large urban agglomerations are also considered.

Making sense of sensing: Scaffolding community knowledge in an online informal scientific engagement

In the relatively understudied area of online informal scientific engagements, this paper aims to unpack the process of creating and sharing knowledge and understanding through dialogue. This is done through online ethnography in an initiative where members with their own air pollution monitors are discussing matters of air pollution, monitoring, data, and technical issues in a public Facebook group. By analysing a sample of text-based dialogue through the framework of exploratory talk, this paper addresses how knowledge and changes of understanding are negotiated, and situated, through social interaction within the community. The findings provide detailed and empirical insights into the ways in which the members of this informal online scientific community create and share meaning through social interaction. The use of low-cost sensors, active participation in the Facebook group, and a shared interest in understanding their own air pollution data are here shown to mediate further engagement and informal learning. Through social interaction and by sharing resources, members are enabled to engage in productive dialogue where common knowledge is created and scaffolded in the community over time. By unpacking the content and context dependent aspects of dialogue, this paper argues for the importance of meaningful participation for productive dialogues. • Productive and social interactions stimulated and guided idea development. • Explicit reasoning enabled peers to contribute to a change of understanding. • Sharing detailed information and resources confirmed possible explanations. • Implicit and specific referencing situated common community knowledge.

Barriers in Nigeria’s public hospital green buildings implementation initiatives

PurposeThe high consumption of energy by buildings may have enhanced land degradation, flooding, air pollution and many other hazardous environmental issues. However, green practices in buildings have been proved as one of the successful technologies to mitigate these issues. Past studies have shown lax green practices in Nigerian buildings. Concerning public hospital buildings, this is yet to be explored. Therefore, this paper aims to investigate the barriers to green practices and proffer possible policy solutions to promote hospital green buildings.Design/methodology/approachIn attaining these objectives, the view of hospital building contractors, design team, hospital management and policymakers in the relevant ministries/agencies was engaged via virtual interviews. The collated data were analysed and presented in the thematic pattern.FindingsFindings show that green building construction is extremely low in Nigeria, but the worst hit is the health-care buildings across the states. Government/policy-related, organisational/leadership-related, financial-related, technical-related, design team-related and stakeholders’ behaviour-related barriers emerged as the main six themes of barriers affecting public hospital green buildings implementation initiatives. Findings show that proffering possible policies to addressing these barriers may improve public hospital green construction across the states.Research limitations/implicationsThis paper is limited to barriers to green buildings implementation in public hospitals in Nigeria, and data collection was through virtual interviews but does not affect the strength of the findings. Thus, this paper suggests that the sub-themes and variables/items that emerged from the collated data as presented in Figure 1 can be further developed quantitatively via questionnaire survey to validate and improve the reliability of results from this paper.Practical implicationsAs part of this study’s implications, suggestions from this paper will stir up policymakers’ decisions, to be tailored towards achieving green buildings implementation initiatives in Nigerian public hospitals.Originality/valueTo the best of the authors’ knowledge, this paper is probably the first that attempted to investigate the barriers to green buildings implementation in public hospitals in Nigeria.