Understanding the knowledge gaps between air pollution controls and health impacts including pathogen epidemic

Enhanced Intrusion of Exogenous Airborne Fine Particles toward Eyes in Humans and Animals: Where Damaged Blood-Ocular Barrier Plays a Crucial Role

Emerging data suggest a close correlation between ambient fine particle (AFP) exposure and eye disorders and pinpoint potential threats of AFPs to eye health in humans. However, the possible passage (including direct intrusion) and the interactions of AFPs with the eye microenvironment in addition to morphological and physiological injuries remain elusive. To this end, the likely transport of AFPs into the eyes via blood-ocular barrier (BOB) in humans and animals was investigated herein. Exogenous particles were recognized inside human eyes with detailed structural and chemical fingerprints. Importantly, comparable AFPs were found in sera with constant structural and chemical fingerprints, hinting at the translocation pathway from blood circulation into the eye. Furthermore, we found that the particle concentrations in human eyes from patients with diabetic retinopathy were much higher than those from patients with no fundus pathological changes (i.e., myopia), indicating that the damaged BOB increased the possibility of particle entrance. Our diseased animal model further corroborated these findings. Collectively, our results offer a new piece of evidence on the intrusion of exogenous particles into human eyes and provide an explanation for AFP-induced eye disorders, with substantially increased risk in susceptible individuals with BOB injuries.

Gaps and future directions in research on health effects of air pollution

Despite progress in many countries, air pollution, and especially fine particulate matter air pollution (PM2.5) remains a global health threat: over 6 million premature cardiovascular and respiratory deaths/yr. have been attributed to household and outdoor air pollution. In this viewpoint, we identify present gaps in air pollution monitoring and regulation, and how they could be strengthened in future mitigation policies to more optimally reduce health impacts. We conclude that there is a need to move beyond simply regulating PM2.5 particulate matter mass concentrations at central site stations. A greater emphasis is needed on: new portable and affordable technologies to measure personal exposures to particle mass; the consideration of a submicron (PM1) mass air quality standard; and further evaluations of effects by particle composition and source. We emphasize the need to enable further studies on exposure-health relationships in underserved populations that are disproportionately impacted by air pollution, but not sufficiently represented in current studies.

Extra-Pulmonary Translocation of Exogenous Ambient Nanoparticles in the Human Body

As one of the major pollutants in the air, ambient fine particles are gaining considerable attention in terms of public health concerns. Significant progress has been achieved in recent years in understanding the biological effects and mechanisms of ambient fine particles. The airborne particles can enter the human body through various pathways and translocate to a range of different organs and further stay in these organs for extended periods. Current studies are making substantial achievements, while many challenges remain. On one hand, the whole picture of the concurrent exposure pathways and the translocation of particles in the human body should be explored, requiring technological advances and systematic biobanking of human samples for analysis. On the other hand, the correlation between the environmental exposure concentration of ambient particles and internal fate (i.e., dose, distribution patterns, and kinetics) of invasive particles needs to be investigated. Moreover, the biotransformation of particles in vivo should be considered, and more information is needed to differentiate exogenous particles from biological macromolecules and biogenically formed particles. We recapitulate the current knowledge gaps in understanding the fate of exogenous ambient fine particles in extra-pulmonary organs of the human body and the related biological effects and also propose future research directions to support both fundamental studies and policy making.

Co-Exposure of Ambient Particulate Matter and Airborne Transmission Pathogens: The Impairment of the Upper Respiratory Systems

Recent evidence has pinpointed the positive relevance between air particulate matter (PM) pollution and epidemic spread. However, there are still significant knowledge gaps in understanding the transmission and infection of pathogens loaded on PMs, for example, the interactions between pathogens and pre-existing atmospheric PM and the health effects of co-exposure on the inhalation systems. Here, we unraveled the interactions between fine particulate matter (FPM) and Pseudomonas aeruginosa (P. aeruginosa) and evaluated the infection and detrimental effects of co-exposure on the upper respiratory systems in both in vitro and in vivo models. We uncovered the higher accessibility and invasive ability of pathogens to epithelial cells after loading on FPMs, compared with the single exposure. Furthermore, we designed a novel laboratory exposure model to simulate a real co-exposure scenario. Intriguingly, the co-exposure induced more serious functional damage and longer inflammatory reactions to the upper respiratory tract, including the nasal cavity and trachea. Collectively, our results provide a new point of view on the transmission and infection of pathogens loaded on FPMs and uncover the in vivo systematic impairments of the inhalation tract under co-exposure through a novel laboratory exposure model. Hence, this study sheds light on further investigations of the detrimental effects of air pollution and epidemic spread.

Passage of exogeneous fine particles from the lung into the brain in humans and animals

Addressing the knowledge gaps regarding the access to and harmful effects of airborne fine particles on the central nervous system is critical. Various exogenous fine particles were found in human cerebrospinal fluids, including commonly found particles and others that have not been reported previously. Animal experiments provided mechanistic explanations and verifications of the translocation of inhaled particles into the brain. Moreover, retention of particles in the brain for longer durations than in other organs was demonstrated through isotope labeling–based biodistribution studies in mice, suggesting possible long-term effects on the brain. This work unravels indications and associations between inhalation and particle transport and adds evidence on the relationship between air pollution and detrimental effects of exogenous particles on the brain.

There are still significant knowledge gaps in understanding the intrusion and retention of exogeneous particles into the central nervous system (CNS). Here, we uncovered various exogeneous fine particles in human cerebrospinal fluids (CSFs) and identified the ambient environmental or occupational exposure sources of these particles, including commonly found particles (e.g., Fe- and Ca-containing ones) and other compositions that have not been reported previously (such as malayaite and anatase TiO₂), by mapping their chemical and structural fingerprints. Furthermore, using mouse and in vitro models, we unveiled a possible translocation pathway of various inhaled fine particles from the lung to the brain through blood circulation (via dedicated biodistribution and mechanistic studies). Importantly, with the aid of isotope labeling, we obtained the retention kinetics of inhaled fine particles in mice, indicating a much slower clearance rate of localized exogenous particles from the brain than from other main metabolic organs. Collectively, our results provide a piece of evidence on the intrusion of exogeneous particles into the CNS and support the association between the inhalation of exogenous particles and their transport into the brain tissues. This work thus provides additional insights for the continued investigation of the adverse effects of air pollution on the brain.

Environmental endocrine disruptor concentrations in urine samples from Mexican Indigenous women

The Indigenous communities in Mexico show significant degrees of vulnerability to pollution due to the lack of knowledge of health risks, traditions, low levels of support, and restricted access to healthcare. As a result, exposure to environmental endocrine disruptors increases in these populations through plastic components or indoor air pollution. Therefore, the aim of the study was to evaluate the exposure to phthalate metabolites, 1-hydroxypyrene, and bisphenol A through biomonitoring data from indigenous Mexican women. A total of 45 women from the Tocoy community in San Luis Potosí, Mexico, were included. Urine samples were analyzed for Bisphenol A and 4 phthalate metabolites by ultra-performance liquid chromatography couples to tandem mass spectrometry; additionally, the 1-hydroxypyrene concentrations were evaluated by high-performance liquid chromatography coupled to a fluorescence detector. Among the main pollution sources were the use of plastic containers and burning garbage (98-100%). Indigenous women presented an exposure of 100% to mono-2-ethyl phthalate, mono-n-butyl phthalate, and 1-hydroxypyrene, with a median (25th-75th percentiles) of 17,478 (11,362-37,355), 113.8 (61.7-203.5), and 1.2 (0.9-1.7) µg/g creatinine, respectively. The major findings show urinary mono-2-ethyl phthalate concentrations higher than those measured from other studies. Therefore, these results show an impressive exposure to di(2-ethylhexyl) phthalate in Indigenous women. The current study reflects the absence of regulatory policies in marginalized populations. It highlights the need to design strategies that mitigate exposure and the importance of biological monitoring to evaluate and prevent health risk associated with exposure to environmental endocrine disruptors.

A systematic literature review of deep learning neural network for time series air quality forecasting

Rapid progress of industrial development, urbanization and traffic has caused air quality reduction that negatively affects human health and environmental sustainability, especially among developed countries. Numerous studies on the development of air quality forecasting model using machine learning have been conducted to control air pollution. As such, there are significant numbers of reviews on the application of machine learning in air quality forecasting. Shallow architectures of machine learning exhibit several limitations and yield lower forecasting accuracy than deep learning architecture. Deep learning is a new technology in computational intelligence; thus, its application in air quality forecasting is still limited. This study aims to investigate the deep learning applications in time series air quality forecasting. Owing to this, literature search is conducted thoroughly from all scientific databases to avoid unnecessary clutter. This study summarizes and discusses different types of deep learning algorithms applied in air quality forecasting, including the theoretical backgrounds, hyperparameters, applications and limitations. Hybrid deep learning with data decomposition, optimization algorithm and spatiotemporal models are also presented to highlight those techniques' effectiveness in tackling the drawbacks of individual deep learning models. It is clearly stated that hybrid deep learning was able to forecast future air quality with higher accuracy than individual models. At the end of the study, some possible research directions are suggested for future model development. The main objective of this review study is to provide a comprehensive literature summary of deep learning applications in time series air quality forecasting that may benefit interested researchers for subsequent research.

The impact of coal combustion, nitrous oxide emissions, and traffic emissions on COVID-19 cases: a Markov-switching approach

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread to more than 200 countries with a current case fatality ratio (CFR) of more than 2% globally. The concentration of air pollutants is considered a critical factor responsible for transmitting coronavirus disease among the masses. The photochemical process and coal combustions create respiratory disorders that lead to coronavirus disease. Based on the crucial fact, the study evaluated the impact of nitrous oxide (N₂O) emissions, coal combustion, and traffic emissions on COVID-19 cases in a panel of 39 most affected countries of the world. These three air pollution factors are considered to form a lethal smog that negatively affects the patient's respiratory system, leading to increased susceptibility to coronavirus worldwide. The study used the Markov two-step switching regime regression model for obtaining parameter estimates. In contrast, an innovation accounting matrix is used to assess smog factors' intensity on possibly increasing coronavirus cases over time. The results show that N₂O emissions, coal combustion, and traffic emissions increase COVID-19 cases in regime-1. On the other hand, N2O emissions significantly increase coronavirus cases in regime-2. The innovation accounting matrix shows that N2O emissions would likely have a more significant share of increasing coronavirus cases with a variance of 33.902%, followed by coal combustion (i.e., 6.643%) and traffic emissions (i.e., 2.008%) over the time horizon. The study concludes that air quality levels should be maintained through stringent environmental policies, such as carbon pricing, sustainable urban planning, green technology advancement, renewable fuels, and pollution less accessible vehicles. All these measures would likely decrease coronavirus cases worldwide.

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

Preparation, filtration, and photocatalytic properties of PAN@g-C3N4 fibrous membranes by electrospinning

Particulate matter and formaldehyde (HCHO) in closed indoor environments are seriously harmful to human health; hence, techniques for the improvement of air quality have attracted significant attention. PAN@g-C₃N₄ fibrous membranes with high efficiency, low resistance, and photocatalytic activity were prepared by electrospinning with polyacrylonitrile (PAN) and graphite carbon nitride (g-C₃N₄), followed by the high-temperature polycondensation of melamine. The addition of g-C₃N₄ to the nanofibrous membrane effectively improved the filtration efficiency of PM2.5. When the amount of added g-C₃N₄ was 3 wt%, the filtration efficiency of PM2.5 was 99.76 ± 0.3%, the filtration efficiency was stable for 24 hours at a continuous high concentration, and the filtration cycle stability was good. As a photocatalytic material, g-C₃N₄ causes the photocatalytic degradation of HCHO, and thus, significantly improves the filtration efficiency of the nanofibrous membrane to HCHO. When the amount of added g-C₃N₄ was 3 wt%, the filtration efficiency of the nanofibrous membrane to HCHO reached 78.0 ± 1.8%. The mechanism of catalytic degradation showed that the PAN fibres first adsorbed and intercepted the HCHO molecules. Under simulated sunlight irradiation, the photogenerated holes generated by the g-C₃N₄ nanosheets in the fibres oxidised and decomposed the adsorbed HCHO molecules. This study has broad application potential for high-efficiency filters to improve indoor air quality.

Particulate matter and formaldehyde (HCHO) in closed indoor environments are seriously harmful to human health; hence, techniques for the improvement of air quality have attracted significant attention.

Present cum future of SARS-CoV-2 virus and its associated control of virus-laden air pollutants leading to potential environmental threat - A global review

The world is presently infected by the biological fever of COVID-19 caused by SARS-CoV-2 virus. The present study is mainly related to the airborne transmission of novel coronavirus through airway. Similarly, our mother planet is suffering from drastic effects of air pollution. There are sufficient probabilities or evidences proven for contagious virus transmission through polluted airborne-pathway in formed aerosol molecules. The pathways and sources of spread are detailed along with the best possible green control technologies or ideas to hinder further transmission. The combined effects of such root causes and unwanted outcomes are similar in nature leading to acute cardiac arrest of our planet. To maintain environmental sustainability, the prior future of such emerging unknown biological hazardous air emissions is to be thoroughly researched. So it is high time to deal with the future of hazardous air pollution and work on its preventive measures. The lifetime of such an airborne virus continues for several hours, thus imposing severe threat even during post-lockdown phase. The world waits eagerly for the development of successful vaccination or medication but the possible outcome is quite uncertain in terms of equivalent economy distribution and biomedical availability. Thus, risk assessments are to be carried out even during the post-vaccination period with proper environmental surveillance and monitoring. The skilled techniques of disinfection, sanitization, and other viable wayouts are to be modified with time, place, and prevailing climatic conditions, handling the pandemic efficiently. A healthy atmosphere makes the earth a better place to dwell, ensuring its future lifecycle.

AIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures Based on Artificial Intelligence Algorithms and Multi-Source Data Processing

The aim of this concept paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for the fight and prevention of emergencies, such as the current COVID-19 pandemic. The tool is a cloud-based centralized system; a multi-user platform that relies on artificial intelligence (AI) algorithms for the processing of heterogeneous data, which can produce as an output the level of risk. The model includes a specific neural network which is first trained to learn the correlations between selected inputs, related to the case of interest: environmental variables (chemical–physical, such as meteorological), human activity (such as traffic and crowding), level of pollution (in particular the concentration of particulate matter) and epidemiological variables related to the evolution of the contagion. The tool realized in the first phase of the project will serve later both as a decision support system (DSS) with predictive capacity, when fed by the actual measured data, and as a simulation bench performing the tuning of certain input values, to identify which of them led to a decrease in the degree of risk. In this way, we aimed to design different scenarios to compare different restrictive strategies and the actual expected benefits, to adopt measures sized to the actual needs, adapted to the specific areas of analysis and useful for safeguarding human health; and we compared the economic and social impacts of the choices. Although ours is a concept paper, some preliminary analyses have been shown, and two different case studies are presented, whose results have highlighted a correlation between NO2, mobility and COVID-19 data. However, given the complexity of the virus diffusion mechanism, linked to air pollutants but also to many other factors, these preliminary studies confirmed the need, on the one hand, to carry out more in-depth analyses, and on the other, to use AI algorithms to capture the hidden relationships among the huge amounts of data to process.

Role of indoor aerosols for COVID-19 viral transmission: a review

The relationship between outdoor atmospheric pollution by particulate matter and the morbidity and mortality of coronavirus disease 2019 (COVID-19) infections was recently disclosed, yet the role of indoor aerosols is poorly known . Since people spend most of their time indoor, indoor aerosols are closer to human occupants than outdoors, thus favoring airborne transmission of COVID-19. Therefore, here we review the characteristics of aerosol particles emitted from indoor sources, and how exposure to particles affects human respiratory infections and transport of airborne pathogens. We found that tobacco smoking, cooking, vacuum cleaning, laser printing, burning candles, mosquito coils and incenses generate large quantities of particles, mostly in the ultrafine range below 100 nm. These tiny particles stay airborne, are deposited in the deeper regions of human airways and are difficult to be removed by the respiratory system. As a consequence, adverse effects can be induced by inhaled aerosol particles via oxidative stress and inflammation. Early epidemiological evidence and animal studies have revealed the adverse effects of particle exposure in respiratory infections. In particular, inhaled particles can impair human respiratory systems and immune functions, and induce the upregulation of angiotensin-converting enzyme 2, thus inducing higher vulnerability to COVID-19 infection. Moreover, co-production of inflammation mediators by COVID-19 infection and particle exposure magnifies the cytokine storm and aggravates symptoms in patients. We also discuss the role of indoor aerosol particles as virus carriers. Although many hypotheses were proposed, there is still few knowledge on interactions between aerosol articles and virus-laden droplets or droplet nuclei.