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Air pollution is a growing concern due to severe threats to public health and the environment. The need for reliable air quality monitoring solutions has never been more critical. This research paper introduces an innovative approach to addressing this challenge by deploying a low-cost Internet of Things (IoT) air monitoring station and providing a blockchain technology solution to enhance environmental data transparency, reliability, and accessibility. Our paper adopts a concept of merging IoT and blockchain technologies and collecting some parameters that help to assess air quality by using three sensors, DHT11, MQ7, and MQ135, to collect temperature, humidity, carbon monoxide, and carbon dioxide parameters, respectively, to measure the gases and thus indicate the air quality within the surrounding area. Collecting and sharing these types of valuable data will be very important for various stakeholders, such as governmental bodies, researchers, and the public. This approach is consistent with the principles of sustainable development, facilitating informed decision-making and promoting eco-friendly policies. This research explores the technical architecture of the IoT air monitoring stations, offering a promising solution for addressing air pollution concerns while promoting sustainable development goals. The proposed system is a model for leveraging emerging technologies to advance environmental monitoring and create smarter, livable cities. This approach aligns with the principles of sustainable development and eco-friendly initiatives. This research offers a promising model for enhancing environmental monitoring efforts and advancing the creation of smarter, more sustainable urban environments. The proposed IoT, cloud platform and blockchain-based system not only addresses pressing air pollution challenges but also sets a benchmark for leveraging emerging technologies in environmental science. [ABSTRACT FROM AUTHOR]

Research on the quality of the air in rural areas is essential for determining base emissions of air pollutants, evaluating the effects of dust pollutants particular to rural areas, modeling the dispersion of pollutants, and developing appropriate pollution mitigation systems. The absence of a systematic review based on the assessment of air quality levels in agricultural settings based on integrated weather variables and air pollutants in the literature draws attention to the deficiencies and the necessity of further research in this area. Hence, our study aimed to develop an Arduino monitoring system with related sensors to acquire some air pollutants and weather parameters. Additionally, we proposed an innovative solution to compare air quality levels by suggesting a new criterion called an integrated indicator for air quality assessment (IAQA). It was created based on the weighted average method to combine the investigated air pollutants and weather parameters. This criterion was evaluated while conducting field measurements in 29 environmentally different agricultural regions located within the Kingdom of Saudi Arabia. To determine the integrated indicator, all the values of the variables were normalized between 0 and 1. The agricultural setting with the lowest integrated indicator was the best environmentally. The lowest and highest values of the integrated indicator ranged from 37.03% and 66.32%, respectively, with an arithmetic average of 48.24%. The developed criterion can change its value depending on the change in the weight value of the variables involved, and it is suitable for application to any other agricultural or non-agricultural setting to evaluate the pollution level in the air. Although similar research has been published, this paper presents novelty findings based on integrated values of air pollutants and weather variables for defining a new criterion called IAQA. Additionally, this paper presents original results for air pollutants and weather aspects in different agricultural settings. [ABSTRACT FROM AUTHOR]

Simple Summary: Dairy farming is a significant source of pollutant gas emissions, contributing to climate change and air quality degradation. Understanding these emissions in milk production promotes productive efficiency and sustainable resource use. The aim of this paper is to provide a comprehensive analysis of ammonia and greenhouse gas emissions in dairy farming, utilizing bibliometric analysis methods. Articles featuring experimental data collection were selected, exclusively in English. The databases considered were Scopus and Web of Science. The analyses were conducted using Bibliometrix version 4.0.0 and VOSviewer version 1.6.20 tools to create knowledge maps visualizing information on research countries, institutions, author collaborations, and keyword networks. The search yielded 187 articles related to major pollutant gases such as methane, ammonia, carbon dioxide, nitrous oxide, and hydrogen sulfide. This study provided valuable insights into gas emission sources, air quality, environmental sustainability, and animal welfare, as well as identifying gaps and critical points in research on the topic. Ammonia and greenhouse gas emissions in dairy farming are crucial for climate change mitigation and sustainable agriculture. This research can contribute to academic interests while enhancing agricultural practices and informing environmental policies. The relevance of this research will persist with the growing demand for sustainable practices, as more researchers and organizations recognize the importance of gas emissions and mitigation research. A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April 2024) were reviewed. Publications notably increased from 1997, with the highest number of papers published in 2022. Research mainly focuses on ammonia and methane emissions, including quantification, volatilization, and mitigation strategies. Other gases like carbon dioxide, nitrous oxide, and hydrogen sulfide were also studied. Key institutions include the University of California–Davis and Aarhus University. Bibliometric analysis revealed research evolution, identifying trends, gaps, and future research opportunities. This bibliometric analysis offers insights into emissions, air quality, sustainability, and animal welfare in dairy farming, highlighting areas for innovative mitigation strategies to enhance production sustainability. This research contributes to academia, enhancing agricultural practices, and informing environmental policies. It is possible to conclude that this research is a valuable tool for understanding the evolution of research on gas emissions in dairy cattle facilities, providing guidance for future studies and interventions to promote more sustainable production. [ABSTRACT FROM AUTHOR]

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase in mining activities, PM10 (air-borne particles with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The present study was initiated to quantitatively examine the spatial and temporal variability of PM10 pollution in the region. An earlier paper of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns were quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology–air pollution relationships were visualised and interpreted on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs. the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs. elevated PM10 pollution in the valley. Two local meteorological patterns, the hot–dry–northwesterly wind conditions and the hot–dry–calm conditions, were found to be the most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of an eastward migrating continental high-pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere. [ABSTRACT FROM AUTHOR]

Syndemics, the adverse interaction of two or more coterminous diseases or other negative health conditions, have probably existed since human settlement, plant and animal domestication, urbanization, and the growth of social inequality beginning about 10–12,000 years ago. These dramatic changes in human social evolution significantly increased opportunities for the spread of zoonotic infectious diseases in denser human communities with increased sanitation challenges. In light of a growing body of research that indicates that anthropogenic air pollution causes numerous threats to health and is taking a far greater toll on human life and wellbeing than had been reported, this paper proposes the possibility that air pollution is now the primary driver of infectious disease syndemics. In support of this assertion, this paper reviews the growth and health impacts of air pollution, the relationship of air pollution to the development and spread of infectious diseases, and reported cases of air pollution-driven infectious disease syndemics, and presents public health recommendations for leveraging the biosocial insight of syndemic theory in responding to infectious disease. [ABSTRACT FROM AUTHOR]

New digital interventions have shown potential in managing asthma and improving patients' quality of life compared with conventional interventions. Our objective was to conduct an exhaustive survey of the application of digital health technologies in evaluating, treating, and self-managing psychological and psychopathological elements linked to asthma. We analyzed a compendium of research papers pertaining to asthma, encompassing themes such as outdoor air pollution, early life wheezing disorders, atopic dermatitis, digital strategies for asthma self-management, psychiatric conditions and asthma, familial impacts on pediatric asthma, and the utilization of mobile health apps for managing asthma. We scrutinized six chosen studies to evaluate the capacity of digital health technologies to enhance the management and treatment outcomes of psychological factors related to asthma. The studies under review indicate that eHealth interventions, mixed reality instruments, mHealth technology-augmented nurse-led interventions, and smartphone apps incorporating Bluetooth-enabled sensors for asthma inhalers can markedly enhance self-management of symptoms, quality of life, and mental health outcomes, particularly in children and adolescents with asthma. Nonetheless, additional research is required to ascertain their efficacy and practicability across diverse populations and environments. Customized interventions that cater to the unique needs and preferences of asthma patients and associated psychological elements are vital to ensure the persistent and equitable adoption of these technologies. We underscore the significance of addressing psychological elements in the management and treatment of asthma and advocate for ongoing research and development in this domain. [ABSTRACT FROM AUTHOR]

The external insulation strength of the power equipment sleeve in the substation and converter station will be reduced with the increase in altitude and atmosphere pollution. The weakness of external insulation seriously threatens the safe operation of electrical equipment. At present, there are few studies and conclusions that focus on the flashover characteristics of power equipment bushing in high-altitude polluted areas. Therefore, this paper takes the 220 kV voltage level bushing as the research object and studies the Alternating Current (AC) pollution flashover characteristics and lightning and switching impulse flashover characteristics at low pressure. The insulation configuration at high-altitude polluted areas is analyzed. Finally, the insulation configuration scheme, which is suitable for high-altitude polluted areas, is proposed. The results show that the AC pollution flashover voltages of the bushing decrease with the decrease in the atmospheric pressure and the increase in the salt density as a power exponent function. The impulse flashover voltages also decrease with the decrease in the atmospheric pressure as a power exponent function. The atmospheric pressure/pollution impact characteristic index is related to the type of voltage, the value of the atmospheric pressure, and the value of the salt density. The test bushing does not meet the insulation configuration requirements in some high-altitude polluted areas. Through the analysis and calculation of the test results, the bushing insulation configuration scheme in high-altitude polluted areas is proposed. The research results can provide a reference for the external insulation design of bushings in substations and converter stations in high-altitude polluted areas. [ABSTRACT FROM AUTHOR]

Due to concerns with air pollution and climate change, governments and transport operators around the world have engaged in transforming their fossil-fueled vehicles into electric vehicles (EVs). It is essential to build a model for the electrifying process to minimize the operation costs. This paper presents a systematic analytical approach for the electrification of a fire ambulance service station. This approach begins with the selection of suitable EVs to replace the current service vehicles. Subsequently, an in-depth analysis is conducted to determine the practical utilization of EVs at the station. The model proposes two charging strategies: immediate charging upon an EVs' return and smart charging. Based on the chosen EVs and charging strategies, a comprehensive assessment of the load profiles for the planned EV charging station is performed. In accordance with the load profiles, a mathematical model to minimize the infrastructure and operation costs of the charging station is proposed. Various pricing schemes are compared to identify the most efficient pricing scheme for the charging station, and economic analyses of the EVs and traditional ambulance vehicles are proposed in this paper. The test results indicate that the progressive pricing scheme is well suited for immediate charging strategies, whereas smart charging should opt for the time-of-use pricing scheme. Selecting the appropriate pricing scheme has the potential to significantly reduce electric energy costs. [ABSTRACT FROM AUTHOR]

As the world grapples with the pressing challenge of environmental sustainability, the need for innovative solutions to combat air pollution has become paramount. Air pollution is a complex issue that necessitates real-time monitoring of pollution sources for effective mitigation. This paper explores the potential of swarm algorithms applied as a novel and efficient approach to address this critical environmental concern. Swarm algorithms offer a promising framework for coordinating fleets of drones to collaboratively monitor and analyze air pollution sources. The unique capabilities of drones, including their agility, accessibility, and versatility, make them ideal candidates for aerial data collection. When harnessed in a swarm, these drones can create a dynamic and adaptable network that provides a more comprehensive and fine-grained understanding of air pollution dynamics. This paper delves into the conceptual foundations of using swarm algorithms in drone-based air pollution monitoring. [ABSTRACT FROM AUTHOR]

Despite their key role in integrated waste management, direct (incineration) and indirect (gasification/pyrolysis) waste combustion processes are still opposed by some of the general public due to the past emission levels of air pollutants. In fact, although the release of air pollutants (especially dioxin) to the atmosphere from waste combustion processes has gradually decreased over the years, thanks to the introduction of stricter regulations and more advanced removal technologies, there is still an unsolved problem regarding the public acceptance of waste-to-energy facilities. The aim of this paper is to provide an overview of the state-of-the-art air pollution control (APC) technologies used in waste combustion facilities. Air pollution control technologies are designed to reduce or eliminate the emissions of harmful pollutants into the atmosphere. These technologies are important for safeguarding public health, protecting ecosystems, complying with regulations, and promoting a more sustainable and resilient future for both local and global communities. This paper will highlight the complexity behind emission control and the efforts made by this sector over the years. This paper will also propose suggested configurations based on the interactions/complementarity between different APC technologies and recent findings to improve their performance. [ABSTRACT FROM AUTHOR]

Air pollution is recognized as a critical global health risk, yet there has been no comprehensive assessment of its impact on public health in Libya until now. This study evaluates the burden of disease associated with ambient particulate matter (PM 2.5 ) in Libya, drawing on data from the Global Burden of Disease Study 2019. By integrating satellite-based estimates, chemical transport models, and ground-level measurements, PM 2.5 exposure and its effects on mortality and disability-adjusted life years (DALYs) across the different sexes and all age groups from 1990 to 2019 are estimated. Our findings reveal that the annual population-weighted mean PM 2.5 concentration in Libya was 38.6 μg/m 3 in 2019, marking a 3% increase since 1990. In the same year, PM 2.5 was responsible for approximately 3368 deaths, accounting for 11% of all annual deaths in the country. Moreover, a total of 107,207 DALYs were attributable to PM 2.5 , with ischemic heart disease being the leading cause, representing 46% of these DALYs. The analysis also highlights a significant burden of years of life lost (YLLs) at 89,113 and years lived with disability (YLDs) at 18,094, due to PM 2.5 . Given the substantial health risks associated with air pollution, particularly from ambient particulate matter, Libyan authorities must implement effective policies aimed at reducing air pollution to enhance healthcare outcomes and preventive services., Competing Interests: Author Mohini Kak was employed by the World Bank. Author Sameh El Saharty was employed by the World Bank. Author Christopher H. Herbst was employed by the World Bank. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Air pollution poses a significant health hazard in urban areas across the globe, with India being one of the most affected countries. This paper presents environmental monitoring study conducted in Jodhpur, Rajasthan, India, to assess air quality in diverse urban environments. The study involved continuous indoor and outdoor air quality monitoring, focusing on particulate matter (PM 2.5 ) levels, bioaerosols, and associated meteorological parameters. Laser sensor-based low-cost air quality monitors were utilized to monitor air quality and Anderson 6-stage Cascade Impactor & Petri Dish methods for bioaerosol monitoring. The study revealed that PM 2.5 levels were consistently high throughout the year, highlighting the severity of air pollution in the region. Notably, indoor PM 2.5 levels were often higher than outdoor levels, challenging the common notion of staying indoors during peak pollution. The study explored the spatial and temporal diversity of air pollution across various land-use patterns within the city, emphasizing the need for tailored interventions in different urban areas. Additionally, bioaerosol assessments unveiled the presence of pathogenic organisms in indoor and outdoor environments, posing health risks to residents. These findings underscore the importance of addressing particulate matter and bioaerosols in air quality management strategies. Despite the study's valuable insights, limitations, such as using low-cost air quality sensors and the need for long-term data collection, are acknowledged. Nevertheless, this research contributes to a better understanding of urban air quality dynamics and the importance of public awareness in mitigating the adverse effects of air pollution. In conclusion, this study underscores the urgent need for effective air quality management strategies in urban areas. The findings provide valuable insights for policymakers and researchers striving to address air pollution in rapidly urbanizing regions.

Current evidence suggests that airborne pollutants have a detrimental effect on fetal growth through the emergence of small for gestational age (SGA) or term low birth weight (TLBW). The study's objective was to critically evaluate the available literature on the association between environmental pollution and the incidence of SGA or TLBW occurrence. A comprehensive literature search was conducted across Pubmed/MEDLINE, Web of Science, Cochrane Library, EMBASE, and Google Scholar using predefined inclusion and exclusion criteria. The methodology adhered to the PRISMA guidelines. The systematic review protocol was registered in PROSPERO with ID number: CRD42022329624. As a result, 69 selected papers described the influence of environmental pollutants on SGA and TLBW occurrence with an Odds Ratios (ORs) of 1.138 for particulate matter ≤ 10 μm (PM10), 1.338 for particulate matter ≤ 2.5 μm (PM2.5), 1.173 for ozone (O3), 1.287 for sulfur dioxide (SO2), and 1.226 for carbon monoxide (CO). All eight studies analyzed validated that exposure to volatile organic compounds (VOCs) is a risk factor for SGA or TLBW. Pregnant women in the high-risk group of SGA occurrence, i.e., those living in urban areas or close to sources of pollution, are at an increased risk of complications. Understanding the exact exposure time of pregnant women could help improve prenatal care and timely intervention for fetuses with SGA. Nevertheless, the pervasive air pollution underscored in our findings suggests a pressing need for adaptive measures in everyday life to mitigate worldwide environmental pollution. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions while controlling air pollution is a dual challenge for China. However, few studies have analyzed whether there is a synergy between the two. In view of this, this paper takes the urban agglomeration in Central Henan as an example, uses multi-source remote sensing and panel data from 2000 to 2022 and analyzes the spatiotemporal evolution patterns and synergistic benefits of air pollution and carbon emissions based on the spatial distribution direction analysis model, coupling coordination degree model and multi-scale geographic weighting model. The results indicate the following: (1) Carbon emissions show a growing trend, but the difference in the carbon emissions of different cities is relatively large, showing the characteristics of "one center and two zones" in space. Air pollution shows a trend of first increasing and then decreasing. (2) The synergistic benefits have been continuously enhanced, and the overall unbalanced state has gradually become coordinated. There is no obvious aggregation feature. (3) The impact of socioeconomic factors on the synergistic benefit is obviously stronger than that of natural ecological factors, among which the total energy consumption, population density and industrial structure are the leading factors of the synergistic benefit of carbon emissions and air pollution. This study offers valuable insights for green development, high-quality growth and collaborative environmental governance within the Central Henan urban agglomeration. [ABSTRACT FROM AUTHOR]

Non-exhaust road transport emissions in cities contribute to poor air quality and have an impact on human health. This paper presents a new study of particles emitted by tyre wear in real driving conditions and gives their emission factors. The most frequently emitted particles were collected in urban, suburban and road areas. They were identified and analysed physically and chemically. Their level of toxicity is well known. An overall analysis of the measured pollutants was carried out to assess their emission factors in real driving situations. The highest emitting pollutants, considered separately, were found to have high emission factors. The values obtained exceed the Euro standard for vehicles but are below those of vehicles not equipped with particle filters. Significant test analysis confirmed that the inertia of chemical pollutants is homogeneous. Emission factors have also been provided for PM10 and PM2.5. These results should contribute to the emergence of future regulations of non-exhaust emissions and should help to analyse the exposure-impact relationship for particles from tyre wear. [ABSTRACT FROM AUTHOR]

With the continuous acceleration of urbanization, air pollution has become an increasingly serious threat to public health. Strengthening the detection and control of pollutants has become a focal point in current society. In light of the increasing amount of literature in the field of air pollution control with every passing year, numerous reviews have been compiled; however, only a limited number employ bibliometric methods to comprehensively review and summarize research trends in this field. Herein, this study utilizes two bibliometric analysis tools, namely, CiteSpace (6.1.R6) and VOSviewer (1.6.20), to conduct a visual and comprehensive analysis of air pollution literature spanning 2000 to 2023. By doing so, it establishes a knowledge framework for research on air pollution control. Simultaneously, collaborative network analysis, reference co-citation network analysis, keyword co-occurrence network analysis, and keyword prominence are employed to undertake an exhaustive and profound visual examination within this domain. Results indicate that, over time, the number of relevant papers has exponentially increased, while interdisciplinary cooperation trends have gradually formed. Additionally, this study describes key areas of current research, including air pollution control residue treatment, regional joint air pollution control, and air pollution control mechanism analysis. Finally, challenges faced by researchers in this field and their different perspectives are discussed. To better integrate research findings on air pollution control, we explore the correlations among data and systematically present their developmental trends. This confirms the interdisciplinary nature of air pollution control research, in the hope of its guiding air pollution control in the future. [ABSTRACT FROM AUTHOR]

In a global society that is increasingly interrelated and focused on mobility, carbon monoxide emissions derived from internal combustion vehicles remain the most important factor that must be addressed to improve environmental quality. Certainly, air pollution generated by internal combustion engines threatens human health and the well-being of the planet. In this regard, this paper aims to address the urgent need to understand and face the CO emissions produced by internal combustion vehicles; therefore, this work proposes a mathematical model based on Auto-Regressive Exogenous that predicts the CO percentages produced by an internal combustion engine during its start-up. The main goal is to establish a strategy for diagnosing excessive CO emissions caused by changes in the engine temperature. The proposed CO emissions modeling is evaluated under a real dataset obtained from experiments, and the obtained results make the proposed method suitable for being implemented as a novel diagnosis tool in automotive maintenance programs. [ABSTRACT FROM AUTHOR]

This paper presents the development of a miniaturized sensor device for selective detection of pathogens, specifically Influenza A Influenza virus, as an enveloped virus is relatively vulnerable to damaging environmental impacts. In consideration of environmental factors such as humidity and temperature, this particular pathogen proves to be an ideal choice for our study. It falls into the category of pathogens that pose greater challenges due to their susceptibility. An impedance biosensor was integrated into an existing platform and effectively separated and detected high concentrations of airborne pathogens. Bio-functionalized hydrogel-based detectors were utilized to analyze virus-containing particles. The sensor device demonstrated high sensitivity and specificity when exposed to varying concentrations of Influenza A virus ranging from 0.5 to 50 μg/mL. The sensitivity of the device for a 0.5 μg/mL analyte concentration was measured to be 695 Ω· mL/μg. Integration of this pathogen detector into a compact-design air quality monitoring device could foster the advancement of personal exposure monitoring applications. The proposed sensor device offers a promising approach for real-time pathogen detection in complex environmental settings.

In recent years, atmospheric composite pollution has become increasingly serious, and accelerating VOC governance has become the focus of and difficulty in atmospheric governance. Volatile organic compounds (VOCs) come from a wide range of sources, and industrial sources are the main source of anthropogenic VOC emissions in China. Chemicals, oil refining, and solvents are three typical VOC-emitting industries, and their control is an important part of accelerating and optimizing VOC governance. It can be controlled by source control, process control, and pipe end treatment; among these, pipe end treatment is divided into recovery technology and destruction technology. In pipeline end treatment, with the key materials of adsorption, absorption, catalytic oxidation, and catalytic combustion, the research and development of adsorbents, absorbents and catalysts has become a hot spot in recent years. This paper summarizes the chemical materials used in typical VOC pipe end-treatment technology (including adsorbents used in the adsorption method, absorbents used in the adsorption method, and catalysts used in the catalytic oxidation and catalytic combustion methods), summarizes the advantages and disadvantages of various materials and their application range, and looks forward to the direction of future developments. [ABSTRACT FROM AUTHOR]

Disruption of the airway epithelium triggers a defensive immune response that begins with the production and release of alarmin cytokines. These epithelial-derived alarmin cytokines, including thymic stromal lymphopoietin (TSLP), are produced in response to aeroallergens, viruses, and toxic inhalants. An alarmin response disproportionate to the inhaled trigger can exacerbate airway diseases such as asthma. Allergens inhaled into previously sensitized airways are known to drive a T2 inflammatory response through the polarization of T cells by dendritic cells mediated by TSLP. Harmful compounds found within air pollution, microbes, and viruses are also triggers causing airway epithelial cell release of TSLP in asthmatic airways. The release of TSLP leads to the development of inflammation which, when unchecked, can result in asthma exacerbations. Genetic and inheritable factors can contribute to the variable expression of TSLP and the risk and severity of asthma. This paper will review the various triggers and consequences of TSLP release in asthmatic airways. [ABSTRACT FROM AUTHOR]

Contaminated air is unhealthy for people to breathe and live in. To maintain the sustainability of clean air, air pollution must be analyzed and controlled, especially after unhealthy events. To do so, the characteristics of unhealthy events, namely intensity, duration, and severity are studied using multivariate modeling. In this study, the vine copula approach is selected to study the characteristics data. Vine copula is chosen here because it is more potent than the standard multivariate distributions, and multivariate copulas, especially in modeling the tails related to extreme events. Here, all nine different vine copulas are analyzed and compared based on model fitting and the comparison of models. In model fitting, the best model obtained is Rv123-Joint-MLE, a model with a root nodes sequence of 123, and optimized using the joint maximum likelihood. The components for the best model are the Tawn type 1 and Rotated Tawn type 1 180 degrees representing the pair copulas of (intensity, duration), and (intensity, severity), respectively, with the Survival Gumbel for the conditional pair copula of (duration, severity; intensity). Based on the best model, the tri-variate dependence structure of the intensity, duration, and severity relationship is positively correlated, skewed, and follows an asymmetric distribution. This indicates that the characteristic's, including intensity, duration, and severity, tend to increase together. Using comparison tests, the best model is significantly different from others, whereas only two models are quite similar. This shows that the best model is well-fitted, compared to most models. Overall, this paper highlights the capability of vine copula in modeling the asymmetric dependence structure of air pollution characteristics, where the obtained model has a better potential to become a tool to assess the risks of extreme events in future work. [ABSTRACT FROM AUTHOR]

Hydrogen cyanide gas is a dangerous and fatal gas that is one of the causes of air pollution in the environment. A small percentage of this gas causes poisoning and eventually death. In this paper, a new PCF is designed that offers high sensitivity and low confinement loss in the absorption wavelength of hydrogen cyanide gas. The proposed structure consists of circular layers that are located around the core, which is also composed of circular microstructures. The finite element method (FEM) is used to simulate the results. According to the results, the PCF gives a high relative sensitivity of 65.13% and a low confinement loss of 1.5 × 10−3 dB/m at a wavelength of 1.533 µm. The impact of increasing the concentration of hydrogen cyanide gas on the relative sensitivity and confinement loss is investigated. The high sensitivity and low confinement losses of the designed PCF show that this optical structure could be a good candidate for the detection of this gas in industrial and medical environments. [ABSTRACT FROM AUTHOR]

Motor vehicle exhaust is an important cause of atmospheric pollution. Nowadays, mainstream exhaust emission aftertreatment technologies, such as TWC, DOC, SCR, and DPF, usually require sufficient temperature to perform good purification or maintain normal working conditions. Compared with exhaust gas heating technologies such as engine enrichment and fuel injection, electric heating technology can quickly increase the temperature of exhaust gas aftertreatment devices without adverse effects on engine operating conditions. This article introduces the research and progress of electric heating technology combined with traditional aftertreatment devices on major types of vehicles, such as gasoline vehicles, diesel vehicles, motorcycles, and hybrid vehicles, to improve exhaust purification efficiency and its accompanying fuel consumption impact. In addition, the common structure and characteristics of electric heaters, as well as the current status and development trend of electric heating unit technologies such as electric heating power supply are introduced. [ABSTRACT FROM AUTHOR]

Sustainable development and the creation of smart, green cities requires cooperation in many scientific fields, including those related to ecology, mobility, or sustainable management, among others. Environmental protection is a particularly important element here. Atmospheric pollution, due to air movements, spreads over very large areas; therefore, air quality monitoring is crucial to ensure protection from harmful substances. One of the most severe sources of air pollution, accounting for as much as approximately 25% of total annual emissions within the EU, is road transport. Therefore, the European Union has set an ambitious target to reduce total emissions to 55% for cars and 50% for vans by 2030. In recent years, unmanned aerial vehicles (UAVs) have become increasingly popular in many scientific fields, including environmental protection and photogrammetry. The use of UAVs to identify harmful pollutants allows them to gain an advantage over conventional detection methods, due to the possibility of remote (therefore safe for humans), faster, and area-based measurements. Given the ever-expanding scale of the use of this technology, this paper presents the possibilities of using UAVs to identify and visualize (map) pollution. The examples presented in the foreign literature, as well as our own research, in imaging the altitude distribution of air pollutants; gaseous pollutants: C6H6, HCHO, SO2; and particulate matter: PM1, PM2.5, PM10 demonstrate the validity of such measures. This research was carried out in the area of one of Poland's key A4 highways. The maps obtained allow for an area-wise and altitude-wise presentation of one of the significant air pollutants in the EU. In addition, they can be a valuable source of information for the implementation of future projects and the improvement of road infrastructure, thus contributing to the reduction of air pollution and the creation of so-called "green cities". [ABSTRACT FROM AUTHOR]

This research aims to explore the use of vegetation and nets to collect water from fog on facades to meet the needs of buildings' functional requirements, particularly outdoor thermal comfort, water demands, and encouraging sustainability by suggesting a new architectural green–blue wall system. The system is posited to be applicable within an urban context, given its minimal spatial requirements and adaptability to existing structures. However, similar challenges to those encountered by green walls are anticipated, wherein the provision of sustainable benefits is offset by the demands of maintenance and associated additional costs. For this reason, this paper is mainly divided into two parts: in the first part, green facades are explained, referring to their effect on urban environment, including thermal comfort, pollution absorption, noise pollution, and well-being, as well as types of plants to apply on green walls; the second part focuses on the fog collector as an irrigation system for green walls, analyzing its components, structure, and fabric, to identify its development margins in the construction industry. Fog harvesting initiatives predominantly focus on rural regions to cater to agricultural demands; however, limiting fog harvesting to agricultural settings is considered insufficient, as it represents a crucial solution for addressing water challenges in specific urban environments. Nevertheless, it is worth investigating the fog collector's potential for integrating water supply in urban environments as well. The study focuses on exploring the environmental benefits of fog harvesting and green walls, particularly through their combined implementation. The proposed review is significant for guiding the integration of a device into green facades, ensuring water self-sufficiency while concurrently addressing air purification, noise reduction, and thermal comfort for pedestrians and urban inhabitants. Nevertheless, it is worth investigating the fog collector's potential for integrating water supply in urban environments as well. The proposed review is, therefore, useful for integrating a device represented by the fog harvesting system, also identified in the text as the blue system, into the design of green facades, identified in the text as the green system, integrating the blue element in the design of the green wall to make them water self-sufficient and at the same time purifying the air, reducing noise pollution, or giving thermal comfort to pedestrians and inhabitants of the urban context. [ABSTRACT FROM AUTHOR]

Numerous studies have examined the impact of urban form on microclimate and thermal comfort at street level. However, the relationship between air pollution concentration and urban form, particularly vegetation and building arrangement, is less considered among planners and designers, and not many case study examples are available in the literature. To address this gap, this paper provides additional evidence and a case study example, illustrating the impact of the built environment on air pollution in urban areas. The Golden Lane Estate, a residential development that has valuable and repeatable urban design and architectural features and is located near a highly congested and polluted area in central London, was selected as the study site. The analysis involved a combination of fieldwork spot measurements and computational modelling (ENVI-met), considering physical features of urban blocks, levels of air pollution, and meteorological parameters (using data from local meteorological stations). The site modelling simulated current conditions and a condition without vegetation to better understand the impact of vegetation on pollutant concentration. The results indicate that urban form and vegetation arrangements significantly affect wind speed and direction, exacerbating air pollution within street canyons of varying aspect ratios. Such findings contribute to the expanding field of hyperlocal scale measurement and underscore the need for guidelines regarding the optimal placement, scale, type, and distribution of vegetation within street canyons. [ABSTRACT FROM AUTHOR]

In recent years, the issue of air pollution has garnered significant public attention globally, with a particular emphasis on the challenge of atmospheric fine particulate matter (PM2.5) pollution. The efficient and precise simulation of changes in pollutant concentrations, as well as their spatial and temporal distribution, is essential for effectively addressing the air pollution issue. In this paper, the WRF-Chem model is used to simulate the meteorological elements including temperature (T), relative humidity (RH), wind speed (WS), and pressure (P), and the concentrations of PM2.5 and PM10 atmospheric pollutants in December 2020 in Xuzhou City. Simultaneously, the ADMS-Urban model was employed to conduct a higher spatial resolution study of PM2.5 concentrations during the heavy pollution days of 11–12 December 2020 in Xuzhou City. The study shows that the WRF-Chem model can simulate the meteorological conditions of the study time period better, and the correlation coefficients (R) of pressure, temperature, wind speed, and relative humidity are 0.99, 0.87, 0.75, and 0.70, respectively. The WRF-Chem model can accurately simulate the PM2.5 concentration on clean days (R of 0.66), but the simulation of polluted days is not satisfactory. Therefore, the ADMS-Urban model was chosen to simulate the PM2.5 concentration on polluted days in the center of Xuzhou City. The ADMS-Urban model can simulate the distribution characteristics and concentration changes of PM2.5 around roads and buildings in the center of Xuzhou City. Comparing the simulation results of the two models, it was found that the two models have their own advantages in PM2.5 concentration simulation, and how to better couple the two models is the next research direction. [ABSTRACT FROM AUTHOR]

Particulate Matter (PM) air pollution has been linked to major adverse health effects. Road transport still contributes significantly to ambient PM concentrations, but mainly due to the non-exhaust emissions from vehicles. For the first time worldwide, limits for non-exhaust emissions have been proposed by the European Union for the upcoming Euro 7 step. For these reasons, interest in brake emissions has increased in the past few years. Realistic emission factors are necessary to accurately calculate the contribution of brake emissions to air pollution but also to estimate the emissions reduction potential of new or existing technologies and improved brake formulations. This paper reviews emission factors from light-duty vehicles reported in the literature, with a focus on those that followed the recently introduced Global Technical Regulation (GTR 24) methodology on brakes in light-duty vehicles. Reduction efficiencies of non-asbestos organic (NAO) pads, brake dust filters, ceramic discs, coated discs, and regenerative braking are also discussed. Finally, the emission factors are compared with roadside measurements of brake emissions and emission inventories worldwide. The findings of this study can be used as an input in emission inventories to estimate the contribution of brakes to air pollution. [ABSTRACT FROM AUTHOR]

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m−3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m−3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020–2021. Despite a 22~62% decline in NOx levels in 2020–2021, the increased O3 caused a similar NO3− concentration (20.69~23.00 μg m−3) in 2020–2021 to that (22.93 μg m−3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019–2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future. [ABSTRACT FROM AUTHOR]

The profound impacts of severe air pollution on human health, ecological balance, and economic stability are undeniable. Precise air quality forecasting stands as a crucial necessity, enabling governmental bodies and vulnerable communities to proactively take essential measures to reduce exposure to detrimental pollutants. Previous research has primarily focused on predicting air quality using only time-series data. However, the importance of remote-sensing image data has received limited attention. This paper proposes a new multi-modal deep-learning model, Res-GCN, which integrates high spatial resolution remote-sensing images and time-series air quality data from multiple stations to forecast future air quality. Res-GCN employs two deep-learning networks, one utilizing the residual network to extract hidden visual information from remote-sensing images, and another using a dynamic spatio-temporal graph convolution network to capture spatio-temporal information from time-series data. By extracting features from two different modalities, improved predictive performance can be achieved. To demonstrate the effectiveness of the proposed model, experiments were conducted on two real-world datasets. The results show that the Res-GCN model effectively extracts multi-modal features, significantly enhancing the accuracy of multi-step predictions. Compared to the best-performing baseline model, the multi-step prediction's mean absolute error, root mean square error, and mean absolute percentage error increased by approximately 6%, 7%, and 7%, respectively. [ABSTRACT FROM AUTHOR]

The intensive exploitation and usage of fossil fuels has led to serious environmental consequences, including soil, water, and air pollution and climate changes, and it has compromised the natural resources available for future generations. In this context, identifying new energy storage technologies can be considered a sustainable solution to these problems, with potential long-term effects. In this work, were analyzed different alternatives that can be suitable for replacing non-renewable sources, where hydrogen, wave, wind, or solar energies were considered. Although they have numerous advantages in terms of usage and substantially reducing the environmental impact, this paper is focused on lithium-ion batteries, whose high performance and safety during operation have made them attractive for a wide range of applications. The study of potential replacement technologies and the technical requirements for the main materials used is the starting point in reducing the environmental footprint, without affecting the technical capabilities, followed by the transition toward economic circularity and climate neutrality. [ABSTRACT FROM AUTHOR]

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM2.5 and PM10 were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM10 (50 μg/m3) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area. [ABSTRACT FROM AUTHOR]

Air pollution, particularly particulate matter such as PM2.5 and PM10, has become a focal point of global concern due to its significant impact on air quality and human health. Macau, as one of the most densely populated cities in the world, faces severe air quality challenges. We leveraged daily pollution data from 2015 to 2023 and hourly meteorological pollution monitoring data from 2020 to 2022 in Macau to conduct an in-depth analysis of the temporal trends of and seasonal variations in PM2.5 and PM10, as well as their relationships with meteorological factors. The findings reveal that PM10 concentrations peak during dawn and early morning, whereas PM2.5 distributions are comparatively uniform. PM concentrations significantly increase in winter and decrease in summer, with relative humidity, temperature, and sea-level atmospheric pressure identified as key meteorological determinants. To enhance prediction accuracy, a Stacking-based ensemble learning model was developed, employing LSTM and XGBoost as base learners and LightGBM as the meta-learner for predicting PM2.5 concentrations. This model outperforms traditional methods such as LSTM, CNN, RF, and XGB across multiple performance metrics. [ABSTRACT FROM AUTHOR]

Over the past decade, surface ozone has emerged as a significant air pollutant in China, especially in the North China Plain (NCP). For effective ozone management in the NCP, it is crucial to accurately estimate the surface ozone levels and identify the primary influencing factors for ozone pollution in this region. This study utilized ozone precursors such as volatile organic compounds (VOCs) and nitrogen oxides (NOX), meteorological data, land cover, normalized difference vegetation index (NDVI), terrain, and population data to build an extreme gradient boosting (XGBoost)-based ozone estimation model in the NCP during 2019 to 2021. Four ozone estimation models were developed using different NO2 and formaldehyde (HCHO) datasets from the Sentinel-5 TROPOMI observations and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data. Site-based validation results of these four models showed high accuracy with R2 values above 0.86. Among these four models, two models with higher accuracy and higher spatial coverage ratio were selected, and their results were averaged to produce the final ozone estimation products. The results indicated that VOCs and NOX were the two main pollutants causing ozone pollution in the NCP, and their relative contributions accounted for more than 23.34% and 10.23%, respectively, while HCHO also played a significant role, contributing over 5.64%. Additionally, meteorological factors also had a notable impact, contributing 28.63% to ozone pollution, with each individual factor contributing more than 2.38%. The spatial distribution of ozone pollution identified the Hebei–Shandong–Henan junction as a pollution hotspot, with the peak occurring in summer, particularly in June. Therefore, for this hotspot region in the NCP, promoting the reduction in VOCs and NOx can play an important role in the mitigation of O3 pollution and the improvement in air quality in this region. [ABSTRACT FROM AUTHOR]

Identifying impact factors and spatial variability of pollutants is essential for understanding environmental exposure and devising solutions. This research focused on PM2.5 as the target pollutant and developed land use regression models specific to the Shenyang metropolitan area in 2020. Utilizing the Least Absolute Shrinkage and Selection Operator approach, models were developed for all seasons and for the annual average, explaining 62–70% of the variability in PM2.5 concentrations. Among the predictors, surface pressure exhibited a positive correlation with PM2.5 concentrations throughout most of the year. Conversely, both elevation and tree cover had negative effects on PM2.5 levels. At a 2000 m scale, landscape aggregation decreased PM2.5 levels, while at a larger scale (5000 m), landscape splitting facilitated PM2.5 dispersion. According to the partial R2 results, vegetation-related land use types were significant, with the shrubland proportion positively correlated with local-scale PM2.5 concentrations in spring. Bare vegetation areas were the primary positive factor in autumn, whereas the mitigating effect of tree cover contrasted with this trend, even in winter. The NDVI, an index used to assess vegetation growth, was not determined to be a primary influencing factor. The findings reaffirm the function of vegetation cover in reducing PM2.5. Based on the research, actionable strategies for PM2.5 pollution control were outlined to promote sustainable development in the region. [ABSTRACT FROM AUTHOR]

The distribution of air pollutants in urban areas is significantly influenced by the presence of various geometric structures, including buildings, bridges, and tunnels. In built-up environments, meteorological conditions may influence the accumulation or dispersion of air pollutants in specific zones. This study examines the impact of wind and atmospheric stability on the dispersion of air pollutants around an apartment building situated in close proximity to a busy boulevard in a residential district of Sofia, Bulgaria. A series of dispersion simulations were conducted using the Graz Lagrangian Model (GRAL v.22.09) for a range of meteorological conditions, defined as combinations of the direction and velocity of the approaching flow, and of stability conditions within the study area of 1 × 1 km, with a horizontal resolution of 2 m. The resulting spatial distribution revealed the presence of hotspots and strong gradients in the concentration field. A simulation with meteorological data was also conducted, which was aligned with a campaign to monitor vehicular traffic. The sensitivity tests indicate that GRAL is capable of reproducing high-resolution pollutant fields, accounting for building effects at relatively low computational costs. This makes the model potentially attractive for city-wide simulations as well as for air pollution exposure estimation. [ABSTRACT FROM AUTHOR]

Several heatwaves (HWs) have been recorded in Egypt in recent years. Some of these HWs were mild, while others were severe and resulted in mortalities and morbidities. On the other hand, air pollution is considered a health issue in Egypt's megacities, especially the capital city, Cairo, and its surroundings, the Greater Cairo (GC) region. In this study, we examine a number of HWs that have hit Egypt in recent years, along with the state of air quality, in terms of PM10, NO2, and O3, during the period of HW incidence, with a focus on the GC region. During the period of study, the frequency, intensity, and duration of HWs have been observed to increase. The total number of recorded HW events was 190, encompassing 376 HW days. The time series of daily mean NO2 showed no correlation with temperature during the months that experienced HWs cases. Conversely, PM10 and O3 concentrations exhibited a similar pattern as that of the daily maximum temperature. This increase in the two pollutant concentrations led to a degradation of the air quality, as demonstrated by the fact that the Air Quality Health Index went from "moderate risk", on normal days, to "high risk" during the HWs. [ABSTRACT FROM AUTHOR]

The seasonal characteristics of air pollutant concentrations are important for understanding variations in emissions released into the air and in atmospheric chemistry. The patterns seen can be influenced by anthropogenic emissions, meteorological conditions, and the transport of pollutants over long and short distances. Whilst seasonality is well understood for some pollutants such as ozone and polycyclic aromatic hydrocarbons, it is poorly understood and under-investigated for heavy metals in particulate matter (PM). This work studies long-term datasets of heavy metals in PM from a relevant UK air quality monitoring network, demonstrating the seasonal characteristics of the concentrations of these metals for the first time. Surprisingly, both 'high in winter–low in summer' and 'low in winter–high in summer' seasonality was observed, with some metals showing little or no seasonality. The 'high in winter–low in summer' seasonality (particularly for As) is attributable to the dominant contribution being from local primary sources, such as burning process producing larger PM sizes. The 'low in winter–high in summer' seasonality (particularly for V) is attributable to weak or non-seasonal local sources being dominated by contributions from medium and long-range transport during the summer months, when pollutant transport is more efficient. The findings contribute significantly to our understanding of the seasonality of metals in PM concentrations and the role played by the long-range transport of pollutants. Conclusions are also drawn about the implications for the calculation of annual averages on compliance-based air quality networks if data from a time series of a pollutant that displays seasonal characteristics are missing. [ABSTRACT FROM AUTHOR]

Objectives: A growing body of evidence highlights the effects of air pollution on chronic and acute cardiovascular diseases, such as associations between PM10 and several cardiovascular events. However, evidence of the impact of fine air pollutants on the development and progression of peripheral arterial aneurysms is not available. Methods: Data were obtained from the multicenter PAA outcome registry POPART and the German Environment Agency. Means of the mean daily concentration of PM10, PM2.5, NO2, and O3 concentrations were calculated for 2, 10, and 3650 days prior to surgery for each patient. Additionally, weighted ten-year averages were analyzed. Correlation was assessed by calculating Pearson correlation coefficients, and regression analyses were conducted as multiple linear or multiple logistic regression, depending on the dependent variable. Results: For 1193 patients from the POPART registry, paired air pollution data were available. Most patients were male (95.6%) and received open surgical repair (89.9%). On a regional level, the arithmetic means of the daily means of PM10 between 2000 and 2022 were neither associated with average diameters nor runoff vessels. Negative correlations for mean PAA diameter and mean NO2, as well as a positive correlation with mean O3, were found; however, they were not statistically significant. On patient level, no evidence for an association of mean PM10 exposure over ten years prior to inclusion in the registry and PAA diameter or the number of runoff vessels was found. Weighted PM10, NO2, and O3 exposure over ten years also did not result in significant associations with aneurysm diameter or runoff vessels. Short-term air pollutant concentrations were not associated with symptomatic PAAs or with perioperative complications. Conclusions: We found no indication that long-term air pollutant concentrations are associated with PAA size or severity, neither on a regional nor individual level. Additionally, short-term air pollution showed no association with clinical presentation or treatment outcomes. [ABSTRACT FROM AUTHOR]

Chiang Mai province of Thailand is known for having the highest natural background radiation in the country, as well as being recognized as one of the world's most polluted cities for air quality. This represents the major contributor to the development of lung cancer. This research aims to estimate the comprehensive dose of both internal and external exposure due to natural background radiation and related health perspectives in the highly polluted area of Chiang Mai. The average values of indoor radon and thoron concentrations in 99 houses over 6 months were 40.8 ± 22.6 and 17.8 ± 16.3 Bq/m3, respectively. These results exceed the worldwide value for indoor radon and thoron (40 and 10 Bq/m3), respectively. During burning season, the average values of indoor radon (56.7 ± 20 Bq/m3) and thoron (20.8 ± 20.4 Bq/m3) concentrations were higher than the world-wide averages. The radon concentration in drinking water (56 samples) varied from 0.1 to 91.9 Bq/L, with an average value of 9.1 ± 22.8 Bq/L. Most of the drinking water samples (87%) fell below the recommended maximum contamination limit of 11.1 Bq/L. The average values of natural radionuclide (226Ra, 232Th and 40K) in 48 soil samples were 47 ± 20.9, 77.9 ± 29.7 and 700.1 ± 233 Bq/kg, respectively. All values were higher than the worldwide average of 35, 30 and 400 Bq/kg, respectively. The average value of outdoor absorbed gamma dose rate (98 ± 32.5 nGy/h) exceeded the worldwide average of 59 nGy/h. Meanwhile, the average activity concentrations of 226Ra, 232Th and 40K in 25 plant food samples were 2.7 ± 0.1, 3.2 ± 1.6 and 1000.7 ± 1.9 Bq/kg, respectively. The 40K concentration was the most predominant in plant foods. The highest concentrations of 226Ra, 232Th and 40K were found in Chinese cabbage, celery and cilantro, respectively. The total annual effective dose for residents in the study area varied from 0.6 to 4.3 mSv, with an average value of 1.4 mSv. This indicates a significant long-term public health hazard due to natural background radiation and suggests a heightened radiation risk for the residents. The excess lifetime cancer risk value (5.4) associated with natural background radiation was found to be higher than the recommended value. Moreover, the number of lung cancer cases per year per million average of 25.2 per million persons per year was in the limit range 170–230 per million people. Overall, our results will be used for future decision making in the prevention of lung cancer risk associated with natural background radiation. [ABSTRACT FROM AUTHOR]

Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health. [ABSTRACT FROM AUTHOR]

Ischemic stroke (IS), chronic obstructive pulmonary disease (COPD) and diabetes mellitus (DM) account for a large burden of premature deaths. However, few studies have investigated the associations between fine particular matter (PM2.5) components and mortality of IS, COPD and DM. We aimed to examine these associations in Beijing, China. Data on daily mortality, air pollutants and meteorological factors from 2008 to 2011 in Beijing were collected. Daily concentrations of five PM2.5 components, namely, sulfate ion (SO42−), ammonium ion (NH4+), nitrate ion (NO3−), organic matter (OM) and black carbon (BC), were obtained from the Tracking Air Pollution (TAP) database in China. The association between PM2.5 components and daily deaths was explored using a quasi-Poisson regression with the distributed lag nonlinear model (DLNM). The average daily concentrations of SO42−, NH4+, NO3−, OM and BC were 11.24, 8.37, 12.00, 17.34 and 3.32 μg/m3, respectively. After adjusting for temperature, relative humidity, pressure, particulate matter less than 10 μm in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2), an IQR increase in OM at lag day 2 and lag day 6 was associated with an increased DM mortality risk (RR 1.038; 95% CI: 1.005–1.071) and COPD mortality risk (RR 1.013; 95% CI: 1.001–1.026). An IQR increase in BC at lag day 0 and lag day 6 was associated with increased COPD mortality risk (RR 1.228; 95% CI: 1.017–1.48, RR 1.059; 95% CI: 1.001–1.121). Cumulative exposure to SO42− and NH4+ was associated with an increased mortality risk for IS, with the highest effect found for lag of 0–7 days (RR 1.085; 95% CI: 1.010–1.167, RR 1.083; 95% CI: 1.003–1.169). These effects varied by sex and age group. This study demonstrated associations of short-term exposure to PM2.5 components with increased risk of IS, COPD and DM mortality in the general population. Our study also highlighted susceptible subgroups. [ABSTRACT FROM AUTHOR]

Current petrochemical-based adhesives adversely affect the environment through substantial volatile organic compound (VOC) emissions during production, contributing to air pollution and climate change. In contrast, vegetable oils extracted from bio-resources provide a compelling alternative owing to their renewability, abundance, and compatibility with adhesive formulation chemistry. This review aimed to critically examine and synthesize the existing scholarly literature on environmentally friendly, sustainable, and high-performance polyurethane adhesives (PUAs) developed from vegetable oils. The use of PUAs derived from vegetable oils promises to provide a long-term replacement while simultaneously maintaining or improving adhesive properties. This quality renders these adhesives appropriate for widespread use in various sectors, including construction, automotive manufacturing, packaging, textile, and footwear industries. This review intended to perform a comprehensive assessment and integration of the existing research, thereby identifying the raw materials, strengths, weaknesses, and gaps in knowledge concerning vegetable oil-based PUAs. In doing so, it responded to these gaps and proposes potential avenues for future research. Therefore, this review accomplishes more than merely evaluating the existing research; it fosters the advancement of greener PUA technologies by identifying areas for improvement and innovation towards more sustainable industrial practices by showcasing vegetable oil-based PUAs as viable, high-performance alternatives to their petroleum-based counterparts. [ABSTRACT FROM AUTHOR]

Urban science plays a pivotal role in understanding the complex interactions between fireworks, air quality, and urban environments. Dense firework smoke worsens air quality and poses a health hazard to the public. In this study, we show a situation where extremely foggy meteorological conditions coincided with intense anthropogenic emissions, including fireworks, in an urban area. For the first time, the chemical composition and sources of non-refractory submicron aerosol (NR-PM1) in outdoor and indoor air were characterized in Vilnius (Lithuania) using an aerosol chemical speciation monitor (ACSM) and Positive Matrix Factorization for the period before the fireworks, on New Year's Eve, and after the fireworks in 2020/2021; thus, typical changes were assessed. Due to stagnant weather conditions and increased traffic, the highest concentrations of black carbon (BC) (13.8 μg/m3) were observed before the fireworks display. The contribution of organic (Org) fraction to the total NR-PM1 mass concentration, in the comparison of the values of a typical night and New Year's Eve (from 9 p.m. to 6 a.m.), increased from 43% to 70% and from 47% to 60% in outdoor and indoor air, respectively. Biomass-burning organic aerosol (BBOA, 48% (44%)) and hydrocarbon-like organic aerosol (HOA, 35% (21%)) dominated the organic fraction indoors and outdoors, respectively. HOA was likely linked to increased traffic during the event, while BBOA may have been related to domestic heating and fireworks. [ABSTRACT FROM AUTHOR]

This study aims to investigate the influence of air pollution and physical exercise on residents' health using data from the Chinese General Social Survey (CGSS) 2018. The research is based on the Grossman Health Production Function and employs the ordered logit model to analyze the relationship between air pollution, physical exercise, and residents' health. We find that among the Chinese population aged 18 and above, air pollution negatively affects residents' physical health, whereas physical exercise has a significantly positive effect. Introducing gender-stratified and urban–rural stratified models, the research reveals that the negative effects of air pollution on residents' health vary among different groups. On one hand, men and residents living in urban areas will bear heavier health damages due to air pollution. On the other hand, physical exercise positively affect the health of both men and women, whether in rural or urban areas. Additionally, age and higher income are associated with better physical health, whereas education does not show a significant impact. Based on these findings, a series of policy recommendations have been proposed to comprehensively and systematically promote ecological governance and sustainable development. The government should strengthen environmental regulations, reduce residents' exposure to air pollution risks, improve the equality of basic public services, invest in rural sports infrastructure, promote healthy lifestyles, and provide personalized health guidance through health education and mobile health services. Moreover, when formulating policies, the government should consider the specific needs of different groups to ensure the fairness and sustainability of the policies. [ABSTRACT FROM AUTHOR]

Objective: The aim was to evaluate and optimize the performance of sensor monitors in measuring PM2.5 and PM10 under typical emission scenarios both indoors and outdoors. Method: Parallel measurements and comparisons of PM2.5 and PM10 were carried out between sensor monitors and standard instruments in typical indoor (2 months) and outdoor environments (1 year) in Shanghai, respectively. The optimized validation model was determined by comparing six machining learning models, adjusting for meteorological and related factors. The intra- and inter-device variation, measurement accuracy, and stability of sensor monitors were calculated and compared before and after validation. Results: Indoor particles were measured in a range of 0.8–370.7 μg/m3 and 1.9–465.2 μg/m3 for PM2.5 and PM10, respectively, while the outdoor ones were in the ranges of 1.0–211.0 μg/m3 and 0.0–493.0 μg/m3, correspondingly. Compared to machine learning models including multivariate linear model (ML), K-nearest neighbor model (KNN), support vector machine model (SVM), decision tree model (DT), and neural network model (MLP), the random forest (RF) model showed the best validation after adjusting for temperature, relative humidity (RH), PM2.5/PM10 ratios, and measurement time lengths (months) for both PM2.5 and PM10, in indoor (R2: 0.97 and 0.91, root-mean-square error (RMSE) of 1.91 μg/m3 and 4.56 μg/m3, respectively) and outdoor environments (R2: 0.90 and 0.80, RMSE of 5.61 μg/m3 and 17.54 μg/m3, respectively), respectively. Conclusions: Sensor monitors could provide reliable measurements of PM2.5 and PM10 with high accuracy and acceptable inter and intra-device consistency under typical indoor and outdoor scenarios after validation by RF model. Adjusting for both climate factors and the ratio of PM2.5/PM10 could improve the validation performance. [ABSTRACT FROM AUTHOR]

Air pollution has become an increasing concern in the Mekong region due to seasonal vegetative burning triggered by related anthropogenic activities and climate change. While the assumption of a correlation between agriculture burning and air pollution is a common postulation, little evidence exists on the association between fire incidents and air pollution concentrations. The current study explores the relationship between satellite-derived fire occurrence, land surface characteristics, and particulate matter 2.5 (PM2.5) concentrations for the five Lower Mekong countries, namely Cambodia, Laos, Myanmar, Thailand, and Vietnam, in an effort to gain new insights into fire distributions related to air quality. Publicly available daily active fire hotspots from the VIIRS satellite instrument, annual land cover products from the MODIS satellite, and mean monthly ground-level PM2.5 estimates from the V5.GL.04 database were analyzed in two relational assessments; first, the distribution of VIIRS active fire counts and fire radiative power (FRP) temporally and spatially and secondly, the correlations between the monthly VIIRS active fire counts, cumulative monthly FRP and mean monthly PM2.5 estimates per country and land cover type. The results suggest a statistically significant positive correlation between monthly fire counts, cumulative FRP, and PM2.5 estimates for each country, which differ based on land cover. The strongest correlation between monthly fire incidences and PM2.5 estimates was found in the case of Myanmar. For all countries combined, fires detected in forests displayed the highest correlation with monthly PM2.5 estimates. This study demonstrates the use of the VIIRS active fire product and provides important insights into temporal and spatial fire distributions as baseline information for fire prevention and mitigation strategies in the Mekong region. [ABSTRACT FROM AUTHOR]

N-acetylcysteine (NAC) is a mucolytic agent with antioxidant and anti-inflammatory properties. The respiratory syncytial virus (RSV) is one of the most important etiological factors of lower respiratory tract infections, and exposure to air pollution appears to be additionally associated with higher RSV incidence and disease severity. We aimed to systematically review the existing literature to determine which molecular mechanisms mediate the effects of NAC in an RSV infection and air pollution, and to identify the knowledge gaps in this field. A search for original studies was carried out in three databases and a calibrated extraction grid was used to extract data on the NAC treatment (dose, timing), the air pollutant type, and the most significant mechanisms. We identified only 28 studies conducted in human cellular models (n = 18), animal models (n = 7), and mixed models (n = 3). NAC treatment improves the barrier function of the epithelium damaged by RSV and air pollution, and reduces the epithelial permeability, protecting against viral entry. NAC may also block RSV-activated phosphorylation of the epidermal growth factor receptor (EGFR), which promotes endocytosis and facilitates cell entry. EGFR also enhances the release of a mucin gene, MUC5AC, which increases mucus viscosity and causes goblet cell metaplasia; the effects are abrogated by NAC. NAC blocks virus release from the infected cells, attenuates the cigarette smoke-induced shift from necrosis to apoptosis, and reverses the block in IFN-γ-induced antiviral gene expression caused by the inhibited Stat1 phosphorylation. Increased synthesis of pro-inflammatory cytokines and chemokines is induced by both RSV and air pollutants and is mediated by the nuclear factor kappa-B (NF-κB) and mitogen-activated protein kinase (MAPK) signaling pathways that are activated in response to oxidative stress. MCP-1 (monocyte chemoattractant protein-1) and RANTES (regulated upon activation, expressed and secreted by normal T cells) partially mediate airway hyperresponsiveness (AHR), and therapeutic (but not preventive) NAC administration reduces the inflammatory response and has been shown to reduce ozone-induced AHR. Oxidative stress-induced DNA damage and cellular senescence, observed during RSV infection and exposure to air pollution, can be partially reversed by NAC administration, while data on the emphysema formation are disputed. The review identified potential common molecular mechanisms of interest that are affected by NAC and may alleviate both the RSV infection and the effects of air pollution. Data are limited and gaps in knowledge include the optimal timing or dosage of NAC administration, therefore future studies should clarify these uncertainties and verify its practical use. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD), the major leading cause of mortality worldwide, is a progressive and irreversible respiratory condition characterized by peripheral airway and lung parenchymal inflammation, accompanied by fibrosis, emphysema, and airflow limitation, and has multiple etiologies, including genetic variance, air pollution, and repetitive exposure to harmful substances. However, the precise mechanisms underlying the pathogenesis of COPD have not been identified. Recent multiomics-based evidence suggests that the plasticity of alveolar macrophages contributes to the onset and progression of COPD through the coordinated modulation of numerous transcription factors. Therefore, this review focuses on understanding the mechanisms and functions of macrophage polarization that regulate lung homeostasis in COPD. These findings may provide a better insight into the distinct role of macrophages in COPD pathogenesis and perspective for developing novel therapeutic strategies targeting macrophage polarization. [ABSTRACT FROM AUTHOR]

Research on climate change mitigation has increasingly considered carbon pricing, with these efforts concentrating on reductions in carbon dioxide (CO2) emissions. Our comprehensive cross-country analysis extends this focus by quantitatively evaluating the effects of carbon pricing on four major pollutants: CO2, nitrous oxide (N2O), methane (CH4), and particulate matter (PM). We use regressions and introduce entropy balancing to this research area. Analyzing data from 132 countries from 1992 to 2019, we find that carbon pricing is associated with an average annual reduction in CO2 emissions by 3 percentage points. A one-unit increase in a coverage-weighted carbon price is associated with reductions in N2O emissions by approximately 0.1 percentage points. A shorter panel for 2010–2017 shows a larger impact of 0.3 percentage points for PM. These findings underline the efficacy of carbon pricing not just in curtailing CO2 but in significantly mitigating other harmful pollutants on a global scale. Reductions in pollutants beyond CO2 provide further motivation for policymakers to pursue carbon pricing. [ABSTRACT FROM AUTHOR]