Regional and global contributions of air pollution to risk of death from COVID-19

Socioeconomic and sociodemographic correlations to COVID-19 variability in the United States in 2020

The COVID-19 pandemic provided an additional spotlight on the longstanding socioeconomic/health impacts of redlining and has added to the myriad of environmental justice issues, which has caused significant loss of life, health, and productive work. The Centers for Disease Control and Prevention (CDC) reports that a person with any selected underlying health conditions is more likely to experience severe COVID-19 symptoms, with more than 81% of COVID-19-related deaths among people aged 65 years and older. The effects of COVID-19 are not homogeneous across populations, varying by socioeconomic status, PM2.5 exposure, and geographic location. This variability is supported by analysis of existing data as a function of the number of cases and deaths per capita/1,00,000 persons. We investigate the degree of correlation between these parameters, excluding health conditions and age. We found that socioeconomic variables alone contribute to ~40% of COVID-19 variability, while socioeconomic parameters, combined with political affiliation, geographic location, and PM2.5 exposure levels, can explain ~60% of COVID-19 variability per capita when using an OLS regression model; socioeconomic factors contribute ~28% to COVID-19-related deaths. Using spatial coordinates in a Random Forest (RF) regressor model significantly improves prediction accuracy by ~120%. Data visualization products reinforce the fact that the number of COVID-19 deaths represents 1% of COVID-19 cases in the US and globally. A larger number of democratic voters, larger per-capita income, and age >65 years is negatively correlated (associated with a decrease) with the number of COVID cases per capita. Several distinct regions of negative and positive correlations are apparent, which are dominated by two major regions of anticorrelation: (1) the West Coast, which exhibits high PM2.5 concentrations and fewer COVID-19 cases; and (2) the middle portion of the US, showing mostly high number of COVID-19 cases and low PM2.5 concentrations. This paper underscores the importance of exercising caution and prudence when making definitive causal statements about the contribution of air quality constituents (such as PM2.5) and socioeconomic factors to COVID-19 mortality rates. It also highlights the importance of implementing better health/lifestyle practices and examines the impact of COVID-19 on vulnerable populations, particularly regarding preexisting health conditions and age. Although PM2.5 contributes comparable deaths (~7M) per year, globally as smoking cigarettes (~8.5M), quantifying any causal contribution toward COVID-19 is non-trivial, given the primary causes of COVID-19 death and confounding factors. This becomes more complicated as air pollution was reduced significantly during the lockdowns, especially during 2020. This statistical analysis provides a modular framework, that can be further expanded with the context of multilevel analysis (MLA). This study highlights the need to address socioeconomic and environmental disparities to better prepare for future pandemics. By understanding how factors such as socioeconomic status, political affiliation, geographic location, and PM2.5 exposure contribute to the variability in COVID-19 outcomes, policymakers and public health officials can develop targeted strategies to protect vulnerable populations. Implementing improved health and lifestyle practices and mitigating environmental hazards will be essential in reducing the impact of future public health crises on marginalized communities. These insights can guide the development of more resilient and equitable health systems capable of responding effectively to similar future scenarios.

Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study

BACKGROUND

Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine.

OBJECTIVE

This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants.

METHODS

We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States.

RESULTS

The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons.

CONCLUSIONS

These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

Association of transportation noise with cardiovascular diseases

This comprehensive article delves into the intricate and multifaceted issue of noise pollution, shedding light on its diverse sources, profound health implications, and the economic burden it imposes on societies. Noise pollution is an increasingly prevalent environmental challenge, impacting millions of people worldwide, often without their full awareness of its adverse effects. Drawing from a wealth of scientific research, the article underscores the well-established links between noise pollution and a spectrum of health issues, including cardiovascular diseases, sleep disturbances, and psychological stress. While exploring the sources and consequences of noise pollution, the article highlights the urgent need for a holistic and collaborative approach to mitigate its impact. This entails a combination of regulatory measures, technological innovations, urban planning strategies, and public education campaigns. It is increasingly evident that the detrimental effects of noise pollution extend beyond physical health, encompassing mental and social well-being. The article also addresses the synergistic relationship between noise pollution and other environmental stressors, emphasizing the importance of considering noise in conjunction with factors like air pollution and access to green spaces. It examines the potential of green spaces to mitigate the effects of noise pollution and enhance overall health.

Epithelial MAPK signaling directs endothelial NRF2 signaling and IL-8 secretion in a tri-culture model of the alveolar-microvascular interface following diesel exhaust particulate (DEP) exposure

BACKGROUND

Particulate matter 2.5 (PM2.5) deposition in the lung's alveolar capillary region (ACR) is significantly associated with respiratory disease development, yet the molecular mechanisms are not completely understood. Adverse responses that promote respiratory disease development involve orchestrated, intercellular signaling between multiple cell types within the ACR. We investigated the molecular mechanisms elicited in response to PM2.5 deposition in the ACR, in an in vitro model that enables intercellular communication between multiple resident cell types of the ACR.

METHODS

An in vitro, tri-culture model of the ACR, incorporating alveolar-like epithelial cells (NCI-H441), pulmonary fibroblasts (IMR90), and pulmonary microvascular endothelial cells (HULEC) was developed to investigate cell type-specific molecular responses to a PM2.5 exposure in an in-vivo-like model. This tri-culture in vitro model was termed the alveolar capillary region exposure (ACRE) model. Alveolar epithelial cells in the ACRE model were exposed to a suspension of diesel exhaust particulates (DEP) (20 µg/cm2) with an average diameter of 2.5 µm. Alveolar epithelial barrier formation, and transcriptional and protein expression alterations in the directly exposed alveolar epithelial and the underlying endothelial cells were investigated over a 24 h DEP exposure.

RESULTS

Alveolar epithelial barrier formation was not perturbed by the 24 h DEP exposure. Despite no alteration in barrier formation, we demonstrate that alveolar epithelial DEP exposure induces transcriptional and protein changes in both the alveolar epithelial cells and the underlying microvascular endothelial cells. Specifically, we show that the underlying microvascular endothelial cells develop redox dysfunction and increase proinflammatory cytokine secretion. Furthermore, we demonstrate that alveolar epithelial MAPK signaling modulates the activation of NRF2 and IL-8 secretion in the underlying microvascular endothelial cells.

CONCLUSIONS

Endothelial redox dysfunction and increased proinflammatory cytokine secretion are two common events in respiratory disease development. These findings highlight new, cell-type specific roles of the alveolar epithelium and microvascular endothelium in the ACR in respiratory disease development following PM2.5 exposure. Ultimately, these data expand our current understanding of respiratory disease development following particle exposures and illustrate the utility of multicellular in vitro systems for investigating respiratory tract health.

New Methodology to Evaluate and Optimize Indoor Ventilation Based on Rapid Response Sensors

The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS). This methodology innovatively assesses the ventilation of a space by combining a quantitative estimation of the real air exchange in the space-obtained from CO2 experimental RRS measurements and the characteristics of and activity in the space-and indoor and outdoor RRS measurements of other pollutants, with healthy recommendations from different organisations. The methodology allows space managers to easily evaluate, in a continuous form, the appropriateness of their ventilation strategy, thanks to modern RRS measurements and direct calculations (implemented here in a web app), even in situations of full activity. The methodology improves on the existing standards, which imply the release of tracer gases and expert intervention, and could also be used to set a control system that measures continuously and adapts the ventilation to changes in indoor occupancy and activity, guaranteeing safe and healthy air in an energy-efficient way. Sample public concurrence spaces with different conditions are used to illustrate the methodology.

[Air pollution, noise and hypertension : Partners in crime]

Air pollution and traffic noise are two important environmental risk factors that endanger health in urban societies and often act together as "partners in crime". Although air pollution and noise often co-occur in urban environments, they have typically been studied separately, with numerous studies documenting consistent effects of individual exposure on blood pressure. In the following review article, we examine the epidemiology of air pollution and noise, especially regarding the cardiovascular risk factor arterial hypertension and the underlying pathophysiology. Both environmental stressors have been shown to lead to endothelial dysfunction, oxidative stress, pronounced vascular inflammation, disruption of circadian rhythms and activation of the autonomic nervous system, all of which promote the development of hypertension and cardiovascular diseases. From a societal and political perspective, there is an urgent need to point out the potential dangers of air pollution and traffic noise in the American Heart Association (AHA)/American College of Cardiology (ACC) prevention guidelines and the European Society of Cardiology (ESC) guidelines on prevention. Therefore, an essential goal for the future is to raise awareness of environmental risk factors as important and, in particular, preventable risk factors for cardiovascular diseases.

Impact of social vulnerability on comorbid COVID-19 and acute myocardial infarction mortality in the United States

The trajectory of several cardiovascular diseases (CVD), including acute myocardial infarction (AMI), has been adversely impacted by COVID-19, resulting in a worse prognosis. The Social Vulnerability Index (SVI) has been found to affect certain CVD outcomes. In this cross-sectional analysis, we investigated the association between the SVI and comorbid COVID-19 and AMI mortality using the CDC databases. The SVI percentile rankings were divided into four quartiles, and age-adjusted mortality rates were compared between the lowest and highest SVI quartiles. Univariable Poisson regression was utilized to calculate risk ratios. A total of 5779 excess deaths and 1.17 excess deaths per 100,000 person-years (risk ratio 1.62) related to comorbid COVID-19 and AMI were attributable to higher social vulnerability. This pattern was consistent across the majority of US subpopulations. Our findings offer crucial epidemiological insights into the influence of the SVI and underscore the necessity for targeted therapeutic interventions.

Observational studies generate misleading results about the health effects of air pollution: Evidence from chronic air pollution and COVID-19 outcomes

Several observational studies from locations around the globe have documented a positive correlation between air pollution and the severity of COVID-19 disease. Observational studies cannot identify the causal link between air quality and the severity of COVID-19 outcomes, and these studies face three key identification challenges: 1) air pollution is not randomly distributed across geographies; 2) air-quality monitoring networks are sparse spatially; and 3) defensive behaviors to mediate exposure to air pollution and COVID-19 are not equally available to all, leading to large measurement error bias when using rate-based COVID-19 outcome measures (e.g., incidence rate or mortality rate). Using a quasi-experimental design, we explore whether traffic-related air pollutants cause people with COVID-19 to suffer more extreme health outcomes in New York City (NYC). When we address the previously overlooked challenges to identification, we do not detect causal impacts of increased chronic concentrations of traffic-related air pollutants on COVID-19 death or hospitalization counts in NYC census tracts.

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.

Planetary health: an imperative for pediatric radiology

The global temperature has been increasing resulting in climate change. This negatively impacts planetary health that disproportionately affects the most vulnerable among us, especially children. Extreme weather events, such as hurricanes, tornadoes, wildfires, flooding, and heatwaves, are becoming more frequent and severe, posing a significant threat to our patients' health, safety, and security. Concurrently, shifts in environmental exposures, including air pollution, allergens, pathogenic vectors, and microplastics, further exacerbate the risks faced by children. In this paper, we provide an overview of pediatric illnesses that are becoming more prevalent and severe because of extreme weather events, global temperature increases, and shifts in environmental exposures. As members of pediatric health care teams, it is crucial for pediatric radiologists to be knowledgeable about the impacts of climate change on our patients, and continue to advocate for safe, healthier environments for our patients.

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes.

METHODS

On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality.

RESULTS

A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality.

CONCLUSION

This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.

Air pollution deaths attributable to fossil fuels: observational and modelling study

OBJECTIVES

To estimate all cause and cause specific deaths that are attributable to fossil fuel related air pollution and to assess potential health benefits from policies that replace fossil fuels with clean, renewable energy sources.

DESIGN

Observational and modelling study.

METHODS

An updated atmospheric composition model, a newly developed relative risk model, and satellite based data were used to determine exposure to ambient air pollution, estimate all cause and disease specific mortality, and attribute them to emission categories.

DATA SOURCES

Data from the global burden of disease 2019 study, observational fine particulate matter and population data from National Aeronautics and Space Administration (NASA) satellites, and atmospheric chemistry, aerosol, and relative risk modelling for 2019.

RESULTS

Globally, all cause excess deaths due to fine particulate and ozone air pollution are estimated at 8.34 million (95% confidence interval 5.63 to 11.19) deaths per year. Most (52%) of the mortality burden is related to cardiometabolic conditions, particularly ischaemic heart disease (30%). Stroke and chronic obstructive pulmonary disease both account for 16% of mortality burden. About 20% of all cause mortality is undefined, with arterial hypertension and neurodegenerative diseases possibly implicated. An estimated 5.13 million (3.63 to 6.32) excess deaths per year globally are attributable to ambient air pollution from fossil fuel use and therefore could potentially be avoided by phasing out fossil fuels. This figure corresponds to 82% of the maximum number of air pollution deaths that could be averted by controlling all anthropogenic emissions. Smaller reductions, rather than a complete phase-out, indicate that the responses are not strongly non-linear. Reductions in emission related to fossil fuels at all levels of air pollution can decrease the number of attributable deaths substantially. Estimates of avoidable excess deaths are markedly higher in this study than most previous studies for these reasons: the new relative risk model has implications for high income (largely fossil fuel intensive) countries and for low and middle income countries where the use of fossil fuels is increasing; this study accounts for all cause mortality in addition to disease specific mortality; and the large reduction in air pollution from a fossil fuel phase-out can greatly reduce exposure.

CONCLUSION

Phasing out fossil fuels is deemed to be an effective intervention to improve health and save lives as part the United Nations' goal of climate neutrality by 2050. Ambient air pollution would no longer be a leading, environmental health risk factor if the use of fossil fuels were superseded by equitable access to clean sources of renewable energy.

Redox and inflammatory mechanisms linking air pollution particulate matter with cardiometabolic derangements

Air pollution is the largest environmental risk factor for disease and premature death. Among the different components that are present in polluted air, fine particulate matter below 2.5 μm in diameter (PM2.5) has been identified as the main hazardous constituent. PM2.5 mainly arises from fossil fuel combustion during power generation, industrial processes, and transportation. Exposure to PM2.5 correlates with enhanced mortality risk from cardiovascular diseases (CVD), such as myocardial infarction and stroke. Over the last decade, it has been increasingly suggested that PM2.5 affects CVD already at the stage of risk factor development. Among the multiple biological mechanisms that have been described, the interplay between oxidative stress and inflammation has been consistently highlighted as one of the main drivers of pulmonary, systemic, and cardiovascular effects of PM2.5 exposure. In this context, PM2.5 uptake by tissue-resident immune cells in the lung promotes oxidative and inflammatory mediators release that alter tissue homeostasis at remote locations. This pathway is central for PM2.5 pathogenesis and might account for the accelerated development of risk factors for CVD, including obesity and diabetes. However, transmission and end-organ mechanisms that explain PM2.5-induced impaired function in metabolic active organs are not completely understood. In this review, the main features of PM2.5 physicochemical characteristics related to PM2.5 ability to induce oxidative stress and inflammation will be presented. Hallmark and recent epidemiological and interventional studies will be summarized and discussed in the context of current air quality guidelines and legislation, knowledge gaps, and inequities. Lastly, mechanistic studies at the intersection between redox metabolism, inflammation, and function will be discussed, with focus on heart and adipose tissue alterations. By offering an integrated analysis of PM2.5-induced effects on cardiometabolic derangements, this review aims to contribute to a better understanding of the pathogenesis and potential interventions of air pollution-related CVD.

Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia

The relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants (PM10, PM2.5, O3, NO2, NO and NOX) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and SpO2/FiO2 at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to PM10, NO2, NO and NOX, while higher exposure to NO2, NO and NOX was associated with lower SpO2/FiO2 ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (SpO2/FiO2) in these patients were significantly related to exposure to air pollution.

Acute and subchronic exposure to urban atmospheric pollutants aggravate acute respiratory failure in infants

Urban air pollution is a major factor that affects the respiratory health of children and adolescents. Less studied is exposure during the first two years of life. This study analyzed the influence of acute and subchronic exposure to urban air pollutants on the severity of acute respiratory failure (ARF) in the first two years of life. This population-based study included 7364 infants hospitalized with ARF. Acute exposure was considered to have occurred 1, 3 and 7 days before hospitalization and subchronic exposure was considered the mean of the last 30 and 60 days. We found that for acute exposure, significant increases in days of hospitalization (LOS) occurred at lag 1 day for NO2 (0.24), SO2 (6.64), and CO (1.86); lag 3 days for PM10 (0.30), PM2.5 (0.37), SO2 (10.8), and CO (0.71); and lag 7 days for NO2 (0.16), SO2 (5.07) and CO (0.87). Increases in the risk of death occurred at lag 1 day for NO2 (1.06), SO2 (3.64), and CO (1.28); and lag 3 days for NO2 (1.04), SO2 (2.04), and CO (1.19). Subchronic exposures at 30 and 60 days occurred for SO2 (9.18, 3.77) and CO (6.53, 2.97), respectively. The associations were more pronounced with higher temperatures and lower relative humidity levels. We concluded that acute and subchronic exposure to higher atmospheric concentrations of all the pollutants studied were associated with greater severity of ARF. The greatest increases in LOS and risk of death occurred with hot and dry weather.

Asymmetric effects of fine particulate matter and stringency policy on COVID-19 intensity

This study aims to examine the influence of environmental performance (PM2.5) on COVID-19 intensity . For this purpose, we employ the newly introduced Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag model. Results indicate the asymmetric linkages between PM2.5 and COVID-19 intensity, as the positive shock in PM2.5 raises the COVID-19 intensity by 21%, whereas the negative shock in PM2.5 decreases COVID-19 intensity by 12% in long-run. On the contrary, the positive shock in stringency measures decreases COVID-19 intensity by 42.8%, while the negative shock in stringency policy increases COVID-19 intensity by 66.7%. These findings imply that higher pollution increases the COVID-19 severity while higher stringency measures slow down people's movement and reduce COVID-19 intensity. However, a sudden negative shock in lockdown increases people's interaction, leading to a higher spread of the virus. These results suggest that governments should adopt stringent action plans to contain the transmissibility of COVID-19.

Too Loud to Handle? Transportation Noise and Cardiovascular Disease

The World Health Organization reported that more than 1.6 million healthy life-years are lost yearly from traffic-related noise in western Europe. In addition, the number of studies on health side effects in response to traffic noise is steadily growing, mainly cardiovascular disease, such as acute and chronic ischemic heart disease, heart failure, arrhythmia, and stroke. Pathophysiologically nighttime noise has been shown to cause sleep disturbances, including too short sleep periods and frequent interruption of sleep leading to an increase in the levels of circulating stress hormones and subsequently to a significant increase in the production of reactive oxygen species (oxidative stress) and inflammation in the vasculature and the brain. The consequence is arterial hypertension and vascular (endothelial) dysfunction, which might increase the risk of cardiovascular disease. With the present review, we give an overview of the "so-called" nonauditory cardiovascular health effects of noise, which have been proposed to be responsible for the future development of cardiovascular disease. We present epidemiological evidence but also evidence provided by translational human and experimental noise studies. Finally, we discuss manoeuvres to mitigate noise effectively.

On fine particulate matter and COVID-19 spread and severity: An in vitro toxicological plausible mechanism

COVID-19 pandemic had a significant impact on global public health. The spread of the disease was related to the high transmissibility of SARS-CoV-2 virus but incidence and mortality rate suggested a possible relationship with environmental factors. Air pollution has been hypothesized to play a role in the transmission of the virus and the resulting severity of the disease. Here we report a plausible in vitro toxicological mode of action by which fine particulate matter (PM2.5) could promote a higher infection rate of SARS-CoV-2 and severity of COVID-19 disease. PM2.5 promotes a 1.5 fold over-expression of the angiotensin 2 converting enzyme (ACE2) which is exploited by viral particles to enter human lung alveolar cells (1.5 fold increase in RAB5 protein) and increases their inflammatory state (IL-8 and NF-kB protein expression). Our results provide a basis for further exploring the possible synergy between biological threats and air pollutants and ask for a deeper understanding of how air quality could influence new pandemics in the future.

Characterizing the effects of structural fires on fine particulate matter with a dense sensing network

Short-term increases in air pollution levels are linked to large adverse effects on health and productivity. However, existing regulatory monitoring systems lack the spatial or temporal resolution needed to capture localized events. This study uses a dense network of over 100 sensors, deployed across the city of Chicago, Illinois, to capture the spread of smoke from short-term structural fire events. Examining all large structural fires that occurred in the city over a year (N = 21), we characterize differences in PM[Formula: see text] concentrations downwind versus upwind of the fires. On average, we observed increases of up to 10.7 [Formula: see text]g/m[Formula: see text] (95% CI 5.7-15.7) for sensors within 2 km and up to 7.7 [Formula: see text]g/m[Formula: see text] (95% CI 3.4-12.0) for sensors 2-5 km downwind of fires. Statistically significant elevated concentrations were evident as far as 5 km downwind of the location of the fire and persisted over approximately 2 h on average. This work shows how low-cost sensors can provide insight on local and short-term pollution events, enabling regulators to provide timely warnings to vulnerable populations.

Association between short-term exposure to PM2.5 and nasal microbiota dysbiosis, inflammation and oxidative stress: A panel study of healthy young adults

Fine particulate matter (PM_2.5) is the primary environmental stressor and a significant threat to public health. However, the effect of PM_2.5 exposure on human nasal microbiota and its pathophysiological implication remain less understood. This study aimed to explore the associations of PM_2.5 exposure with indices of nasal microbiota and biomarkers of nasal inflammation and oxidative stress. We conducted a panel study with 75 students in Xinxiang, Henan Province, China, from September to December 2017. Biomarkers of nasal inflammation and oxidative stress including interleukin-6 (IL-6), IL-8, tumor necrosis factor-α (TNF-α), 8-epi-prostaglandin F2 alpha (8-epi-PGF2α) and indices of nasal microbiota diversity and phenotypes were measured. Linear mixed-effect models and bioinformatic analyses were performed to assess the association of PM_2.5 concentrations with the abovementioned biomarkers and indices. It was found that per 1 μg/m³ increase in PM_2.5 was associated with increments of 13.15% (95 % CI: 5.53-20.76 %) and 78.98 % (95 % CI: 21.61-136.36 %) in TNF-α on lag2 and lag02. Indices of microbial diversity and phenotypes including equitability, Shannon index, biofilm forming, and oxidative stress tolerant decreased to different extent with the increment in PM_2.5. Notably, thirteen differential microbes in Clostridia, Bacilli, and Gammaproteobacteria classes were recognized as keystone taxa and eight of them were associated with TNF-α, IL-6, or 8-epi-PGF2α. Moreover, environmental adaptation was the most critical functional pathway of nasal microbiota associated with PM_2.5 exposure. In summary, short-term exposure to PM_2.5 is associated with nasal inflammation, microbiota diversity reduction, and the microbiota phenotype alterations.

Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic

An impressive number of COVID-19 data catalogs exist. However, none are fully optimized for data science applications. Inconsistent naming and data conventions, uneven quality control, and lack of alignment between disease data and potential predictors pose barriers to robust modeling and analysis. To address this gap, we generated a unified dataset that integrates and implements quality checks of the data from numerous leading sources of COVID-19 epidemiological and environmental data. We use a globally consistent hierarchy of administrative units to facilitate analysis within and across countries. The dataset applies this unified hierarchy to align COVID-19 epidemiological data with a number of other data types relevant to understanding and predicting COVID-19 risk, including hydrometeorological data, air quality, information on COVID-19 control policies, vaccine data, and key demographic characteristics.

Twitterati on COVID-19 pandemic-environment linkage: Insights from mining one year of tweets

The COVID-19 pandemic seems to have had positive (although short-lived, e.g., reduction in pollution due to lockdown) as well as negative (e.g., increasing plastic pollution due to use of disposable masks, etc.) impacts on the environment. The pandemic-environment linkage also includes circumstances when regions experienced extreme weather events, such as floods and cyclones, and disaster management became challenging. This study aims to examine the trends in public discourses on Twitter on these interactions between the pandemic and environment. The present study follows the most recent literature on understanding public perceptions - which acknowledges Twitter to be an abundant source of information on public discussions on any global issue, including the pandemic. A Python-based code is developed to extract Twitter data spanning over a year, and analyze the presence of covid-environment related keywords and other attributes. It is found that the Twitterati aggressively viewed the impacts (such as economic slowdown and high mortality) of the pandemic as miniatures of the results of future climate change. The community was also highly concerned about the varying air and plastic pollution levels with the change in lockdown and covid prevention policies. Extreme weather events were a high-frequency topic when they impacted countries such as India, the USA, Australia, the Philippines and Vietnam. This study makes a novel attempt to provide an overview of public discourses on the pandemic-environment linkage and; can be a crucial addition to the literature on assessing public perception of environmental threats through Twitter data mining.

Air pollution in Iran: The current status and potential solutions

Air pollution has been integrated into global challenges over the last few years due to its negative impact on the health of human beings, increasing socio-economic risks, and its contribution to climate change. This study attempts to evaluate the current status of Iran's air pollution with regard to the sources of emissions, control policies, and the health and climate consequences that have resulted through available data from monitoring stations reported in the literature, official documents, and previously published papers. Many large cities in Iran surpass the permissible concentration of air pollutants, particularly particulate matter, sulfur dioxide, black carbon, and ozone. Although regulations and policies are in place and enormous efforts are being made to address air pollution issues in the country, implementation and enforcement are not as effective as they could be. The significant challenges may be regarded as the inefficiency of regulation and supervision systems, the lack of air quality monitoring systems and technology, particularly in industrial cities rather than Tehran, and the lack of continual feedback and investigations on the efficiency of regulation. Providing such an up-to-date report can bring opportunities for international collaboration, which is essential in addressing air pollution worldwide. We suggest that a way forward could be more focused on conducting systematic reviews using scientometric methods to show an accurate picture and trend in air pollution and its association in Iran, implementing an integrated approach for both climate change and air pollution issues, collaborating with international counterparts to share knowledge, tools, and techniques.

Air pollution and respiratory infections: the past, present, and future

Air pollution levels across the globe continue to rise despite government regulations. The increase in global air pollution levels drives detrimental human health effects, including 7 million premature deaths every year. Many of these deaths are attributable to increased incidence of respiratory infections. Considering the COVID-19 pandemic, an unprecedented public health crisis that has claimed the lives of over 6.5 million people globally, respiratory infections as a driver of human mortality is a pressing concern. Therefore, it is more important than ever to understand the relationship between air pollution and respiratory infections so that public health measures can be implemented to ameliorate further morbidity and mortality. This article aims to review the current epidemiologic and basic science research on interactions between air pollution exposure and respiratory infections. The first section will present epidemiologic studies organized by pathogen, followed by a review of basic science research investigating the mechanisms of infection, and then conclude with a discussion of areas that require future investigation.

Global ambient air quality monitoring: Can mosses help? A systematic meta-analysis of literature about passive moss biomonitoring

Surging incidents of air quality-related public health hazards, and environmental degradation, have prompted the global authorities to seek newer avenues of air quality monitoring, especially in developing economies, where the situation appears most alarming besides difficulties around 'adequate' deployment of air quality sensors. In the present narrative, we adopt a systematic review methodology (PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses) around recent global literature (2002-2022), around moss-based passive biomonitoring approaches which might offer the regulatory authorities a complementary means to fill 'gaps' in existing air quality records. Following the 4-phased search procedure under PRISMA, total of 123 documents were selected for review. A wealth of research demonstrates how passive biomonitoring, with strategic use of mosses, could become an invaluable regulatory (and research) tool to monitor atmospheric deposition patterns and help identifying the main drivers of air quality changes (e.g., anthropogenic and/or natural). Besides individual studies, we briefly reflect on the European Moss Survey, underway since 1990, which aptly showcases mosses as 'naturally occurring' sensors of ambient air quality for a slew of metals (heavy and trace) and persistent organic pollutants, and help assessing spatio-temporal changes therein. To that end, we urge the global research community to conduct targeted research around various pollutant uptake mechanisms by mosses (e.g., species-specific interactions, environmental conditions, land management practices). Of late, mosses have found various environmental applications as well, such as in epidemiological investigations, identification of pollutant sources and transport mechanisms, assessment of air quality in diverse and complex urban ecosystems, and even detecting short-term changes in ambient air quality (e.g., COVID-19 Lockdown), each being critical for the authorities to develop informed and strategic regulatory measures. To that end, we review current literature and highlight to the regulatory authorities how to extend moss-based observations, by integrating them with a wide range of ecological indicators to assess regional environmental vulnerability/risk due to degrading air quality. Overall, an underlying motive behind this narrative was to broaden the current regulatory outlook and purview, to bolster and diversify existing air quality monitoring initiatives, by coupling the moss-based outputs with the traditional, sensor-based datasets, and attain improved spatial representation. However, we also make a strong case of conducting more targeted research to fill in the 'gaps' in our current understanding of moss-based passive biomonitoring details, with increased case studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03043-0.

Host–Pathogen Interactions Influencing Zoonotic Spillover Potential and Transmission in Humans

Emerging infectious diseases of zoonotic origin are an ever-increasing public health risk and economic burden. The factors that determine if and when an animal virus is able to spill over into the human population with sufficient success to achieve ongoing transmission in humans are complex and dynamic. We are currently unable to fully predict which pathogens may appear in humans, where and with what impact. In this review, we highlight current knowledge of the key host–pathogen interactions known to influence zoonotic spillover potential and transmission in humans, with a particular focus on two important human viruses of zoonotic origin, the Nipah virus and the Ebola virus. Namely, key factors determining spillover potential include cellular and tissue tropism, as well as the virulence and pathogenic characteristics of the pathogen and the capacity of the pathogen to adapt and evolve within a novel host environment. We also detail our emerging understanding of the importance of steric hindrance of host cell factors by viral proteins using a “flytrap”-type mechanism of protein amyloidogenesis that could be crucial in developing future antiviral therapies against emerging pathogens. Finally, we discuss strategies to prepare for and to reduce the frequency of zoonotic spillover occurrences in order to minimize the risk of new outbreaks.

Substantial Changes in Selected Volatile Organic Compounds (VOCs) and Associations with Health Risk Assessments in Industrial Areas during the COVID-19 Pandemic

During the COVID-19 pandemic, governments in many countries worldwide, including India, imposed several restriction measures, including lockdowns, to prevent the spread of the infection. COVID-19 lockdowns led to a reduction in gaseous and particulate pollutants in ambient air. In the present study, we investigated the substantial changes in selected volatile organic compounds (VOCs) after the outbreak of the coronavirus pandemic and associations with health risk assessments in industrial areas. VOC data from 1 January 2019 to 31 December 2021 were collected from the Central Pollution Control Board (CPCB) website, to identify percentage changes in VOC levels before, during, and after COVID-19. The mean TVOC levels at all monitoring stations were 47.22 ± 30.15, 37.19 ± 37.19, and 32.81 ± 32.81 µg/m³ for 2019, 2020, and 2021, respectively. As a result, the TVOC levels gradually declined in consecutive years due to the pandemic in India. The mean TVOC levels at all monitoring stations declined from 9 to 61% during the pandemic period as compared with the pre-pandemic period. In the current study, the T/B ratio values ranged from 2.16 (PG) to 26.38 (NL), which indicated that the major pollutant contributors were traffic and non-traffic sources during the pre-pandemic period. The present findings indicated that TVOC levels had positive but low correlations with SR, BP, RF, and WD, with correlation coefficients (r) of 0.034, 0.118, 0.012, and 0.007, respectively, whereas negative correlations were observed with AT and WS, with correlation coefficients (r) of -0.168 and -0.150, respectively. The lifetime cancer risk (LCR) value for benzene was reported to be higher in children, followed by females and males, for the pre-pandemic, pandemic, and post-pandemic periods. A nationwide scale-up of this study's findings might be useful in formulating future air pollution reduction policies associated with a reduction in health risk factors. Furthermore, the present study provides baseline data for future studies on the impacts of anthropogenic activities on the air quality of a region.

Impact of air pollution on ischemic heart disease: Evidence, mechanisms, clinical perspectives

Ambient air pollution, and especially particulate matter (PM) air pollution <2.5 μm in diameter (PM_2.5), has clearly emerged as an important yet often overlooked risk factor for atherosclerosis and ischemic heart disease (IHD). In this review, we examine the available evidence demonstrating how acute and chronic PM_2.5 exposure clinically translates into a heightened coronary atherosclerotic burden and an increased risk of acute ischemic coronary events. Moreover, we provide insights into the pathophysiologic mechanisms underlying PM_2.5-mediated atherosclerosis, focusing on the specific biological mechanism through which PM_2.5 exerts its detrimental effects. Further, we discuss about the possible mechanisms that explain the recent findings reporting a strong association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, increased PM_2.5 exposure, and morbidity and mortality from IHD. We also address the possible mitigation strategies that should be implemented to reduce the impact of PM_2.5 on cardiovascular morbidity and mortality, and underscoring the strong need of clinical trials demonstrating the efficacy of specific interventions (including both PM_2.5 reduction and/or specific drugs) in reducing the incidence of IHD. Finally, we introduce the emerging concept of the exposome, highlighting the close relationship between PM_2.5 and other environmental exposures (i.e.: traffic noise and climate change) in terms of common underlying pathophysiologic mechanisms and possible mitigation strategies.

Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California

Globally, wildfires have seen remarkable increase in duration and size and have become a health hazard. In addition to vegetation and habitat destruction, rapid release of smoke, dust and gaseous pollutants in the atmosphere contributes to its short and long-term detrimental effects. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a public health concern worldwide that primarily target lungs and respiratory tract, akin to air pollutants. Studies from our lab and others have demonstrated association between air pollution and COVID-19 infection and mortality rates. However, current knowledge on the impact of wildfire-mediated sudden outburst of air pollutants on COVID-19 is limited. In this study, we examined the association of air pollutants and COVID-19 during wildfires burned during August-October 2020 in California, United States. We observed an increase in the tropospheric pollutants including aerosols (particulate matter [PM]), carbon monoxide (CO) and nitrogen dioxide (NO₂) by approximately 150%, 100% and 20%, respectively, in 2020 compared to the 2019. Except ozone (O₃), similar proportion of increment was noticed during the peak wildfire period (August 16 - September 15, 2020) in the ground PM_2.5, CO, and NO₂ levels at Fresno, Los Angeles, Sacramento, San Diego and San Francisco, cities with largest active wildfire area. We identified three different spikes in the concentrations of PM_2.5, and CO for the cities examined clearly suggesting wildfire-induced surge in air pollution. Fresno and Sacramento showed increment in the ground PM_2.5, CO and NO₂ levels, while San Diego recorded highest change rate in NO₂ levels. Interestingly, we observed a similar pattern of higher COVID-19 cases and mortalities in the cities with adverse air pollution caused by wildfires. These findings provide a logical rationale to strategize public health policies for future impact of COVID-19 on humans residing in geographic locations susceptible to sudden increase in local air pollution.

Unanswered questions on the airborne transmission of COVID-19

Policies and measures to control pandemics are often failing. While biological factors controlling transmission are usually well explored, little is known about the environmental drivers of transmission and infection. For instance, respiratory droplets and aerosol particles are crucial vectors for the airborne transmission of the severe acute respiratory syndrome coronavirus 2, the causation agent of the coronavirus 2019 pandemic (COVID-19). Once expectorated, respiratory droplets interact with atmospheric particulates that influence the viability and transmission of the novel coronavirus, yet there is little knowledge on this process or its consequences on virus transmission and infection. Here we review the effects of atmospheric particulate properties, vortex zones, and air pollution on virus survivability and transmission. We found that particle size, chemical constituents, electrostatic charges, and the moisture content of airborne particles can have notable effects on virus transmission, with higher survival generally associated with larger particles, yet some viruses are better preserved on small particles. Some chemical constituents and surface-adsorbed chemical species may damage peptide bonds in viral proteins and impair virus stability. Electrostatic charges and water content of atmospheric particulates may affect the adherence of virion particles and possibly their viability. In addition, vortex zones and human thermal plumes are major environmental factors altering the aerodynamics of buoyant particles in air, which can strongly influence the transport of airborne particles and the transmission of associated viruses. Insights into these factors may provide explanations for the widely observed positive correlations between COVID-19 infection and mortality with air pollution, of which particulate matter is a common constituent that may have a central role in the airborne transmission of the novel coronavirus.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10311-022-01557-z.

Co-exposure to urban particulate matter and aircraft noise adversely impacts the cerebro-pulmonary-cardiovascular axis in mice

Worldwide, up to 8.8 million excess deaths/year have been attributed to air pollution, mainly due to the exposure to fine particulate matter (PM). Traffic-related noise is an additional contributor to global mortality and morbidity. Both health risk factors substantially contribute to cardiovascular, metabolic and neuropsychiatric sequelae. Studies on the combined exposure are rare and urgently needed because of frequent co-occurrence of both risk factors in urban and industrial settings. To study the synergistic effects of PM and noise, we used an exposure system equipped with aerosol generator and loud-speakers, where C57BL/6 mice were acutely exposed for 3d to either ambient PM (NIST particles) and/or noise (aircraft landing and take-off events). The combination of both stressors caused endothelial dysfunction, increased blood pressure, oxidative stress and inflammation. An additive impairment of endothelial function was observed in isolated aortic rings and even more pronounced in cerebral and retinal arterioles. The increase in oxidative stress and inflammation markers together with RNA sequencing data indicate that noise particularly affects the brain and PM the lungs. The combination of both stressors has additive adverse effects on the cardiovascular system that are based on PM-induced systemic inflammation and noise-triggered stress hormone signaling. We demonstrate an additive upregulation of ACE-2 in the lung, suggesting that there may be an increased vulnerability to COVID-19 infection. The data warrant further mechanistic studies to characterize the propagation of primary target tissue damage (lung, brain) to remote organs such as aorta and heart by combined noise and PM exposure.

Air Quality Index prediction using an effective hybrid deep learning model

Environmentalism has become an intrinsic part of everyday life. One of the greatest challenge to the environment's long-term existence is the air pollution. Delhi, the capital of India, has experienced decreasing of air quality for several years. The poor air quality has a significant impact on the lives of individuals. Air Quality Index (AQI) prediction can help to its beneficiaries in taking safeguards about their health before moving to any polluted area. In this study, a variety of data forecasting approaches is evaluated to predict the AQI value for Particulate Matter (PM_2.5) μm at a particular area of Delhi and several error-prone strategies such as R-Squared (R²), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) methods are catalogued. In the proposed approach two deep learning models like Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) are combined to predict the AQI of the environment. Several stand alone machine learning (ML) and deep learning (DL) models such as LSTM, Linear-Regression (LR), GRU, K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are also trained on the same dataset to compare their performances with the proposed hybrid (LSTM-GRU) model and it is found that the proposed hybrid model shows supremacy in the performance with the MAE value 36.11 and R² value 0.84.

The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America

BACKGROUND

Air pollution is speculated to increase the risks of COVID-19 spread, severity, and mortality.

OBJECTIVES

We systematically reviewed studies investigating the relationship between air pollution and COVID-19 cases, non-fatal severity, and mortality in North America and Europe.

METHODS

We searched PubMed, Web of Science, and Scopus for studies investigating the effects of harmful pollutants, including particulate matter with diameter ≤2.5 or 10 μm (PM_2.5 or PM₁₀), ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and carbon monoxide (CO), on COVID-19 cases, severity, and deaths in Europe and North America through to June 19, 2021. Articles were included if they quantitatively measured the relationship between exposure to air pollution and COVID-19 health outcomes.

RESULTS

From 2,482 articles screened, we included 116 studies reporting 355 separate pollutant-COVID-19 estimates. Approximately half of all evaluations on incidence were positive and significant associations (52.7%); for mortality the corresponding figure was similar (48.1%), while for non-fatal severity this figure was lower (41.2%). Longer-term exposure to pollutants appeared more likely to be positively associated with COVID-19 incidence (63.8%). PM_2.5, PM₁₀, O₃, NO₂, and CO were most strongly positively associated with COVID-19 incidence, while PM_2.5 and NO₂ with COVID-19 deaths. All studies were observational and most exhibited high risk of confounding and outcome measurement bias.

DISCUSSION

Air pollution may be associated with worse COVID-19 outcomes. Future research is needed to better test the air pollution-COVID-19 hypothesis, particularly using more robust study designs and COVID-19 measures that are less prone to measurement error and by considering co-pollutant interactions.

Evaluating the potential of suburban and rural areas for tourism and recreation, including individual short-term tourism under pandemic conditions

Limited mobility and restrictions in social life caused by the COVID-19 pandemic changed people's recreational behavior and made them seek more contact with nature. As a result, the provision of new recreational spaces in the vicinity of cities gained importance. In conditions of social distancing, rural and suburban areas can be an attractive alternative to individual short-term tourism, satisfying the need for recreation and mental and physical health restoration of urban residents. In the study a methodology for assessing the tourist and recreational potential of the area (METPRET) concerning the recreational behaviors identified in the pandemic was proposed. It includes the Recreational Potential Index (RPI), which comprises four criteria: landscape values and socio-economic conditions; environmental protection; air quality; transportation accessibility. The application of the methodology is exemplified in the Mazovia Voivodeship, Poland. The research allows the determination of characteristics that potential recreation areas should have under pandemic conditions. The RPI makes it possible to select new rural and suburban areas attractive for short-term tourism. Designating additional recreational areas may contribute to the dispersion of users in existing green areas in cities, which is particularly important during a pandemic.

Air quality in Germany as a contributing factor to morbidity from COVID-19

BACKGROUND

The SARS-CoV-2 virus has been spreading in Germany since January 2020, with regional differences in incidence, morbidity, and mortality. Long-term exposure to air pollutants as nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), and particulate matter (<10 μm PM₁₀, <2.5 μm PM_2.5) has a negative impact on respiratory functions. We analyze the association between long-term air pollution and the outcome of SARS-CoV-2 infections in Germany.

METHODS

We conducted an observational study in Germany on county-level, investigating the association between long-term (2010-2019) air pollutant exposure (European Environment Agency, AirBase data set) and COVID-19 incidence, morbidity, and mortality rate during the first outbreak of SARS-CoV-2 (open source data Robert Koch Institute). We used negative binominal models, including adjustment for risk factors (age, sex, days since first COVID-19 case, population density, socio-economic and health parameters).

RESULTS

After adjustment for risk factors in the tri-pollutant model (NO₂, O₃, PM_2.5) an increase of 1 μg/m³ NO₂ was associated with an increase of the need for intensive care due to COVID-19 by 4.2% (95% CI 1.011-1.074), and mechanical ventilation by 4.6% (95% CI 1.010-1.084). A tendency towards an association of NO₂ with COVID-19 incidence was indicated, as the results were just outside of the defined statistical significance (+1.6% (95% CI 1.000-1.032)). Long-term annual mean NO₂ level ranged from 4.6 μg/m³ to 32 μg/m³.

CONCLUSIONS

Our results indicate that long-term NO₂ exposure may have increased susceptibility for COVID-19 morbidity in Germany. The results demonstrate the need to reduce ambient air pollution to improve public health.

The impact of COVID-19 on the sustainability of the environment, animal health and food security, and safety

COVID-19 pandemic influenced the environment, animal health, and food security. Due to reduced human mobility, the air and water quality increased. Other environmental consequences were the personal protective types of equipment and their haphazard disposal. Atmospheric pollution could be a cofactor leading to an increased COVID-19 mortality rate. Lockdown, however, caused a reduction in air and water pollution. Noise pollution affects the health of individuals and communities in terms of cardiovascular disorders and sleeping problems. Meanwhile, the COVID-19 lockdown controls human activities that reduce noise pollution. Municipal waste affects the environment. Recycling has been reduced in some countries but not in Saudi Arabia. COVID-19 had a drastic effect on livestock production on national, regional, and global levels, affecting countries' capacities to prevent and control diseases of animals and increasing global poverty, becoming a threat to the sustainability of global food security and safety. Many lessons have been learned from the COVID-19 pandemic, so it is wise to study and analyze the previous lessons and shed some light on past pandemics such as the Spanish flu to understand the readings and earn experiences. This paper is focused on the interaction between the pandemic and environmental health from the public health concern rather than other health classifications.

Cumulative effects of air pollution and climate drivers on COVID-19 multiwaves in Bucharest, Romania

Over more than two years of global health crisis due to ongoing COVID-19 pandemic, Romania experienced a five-wave pattern. This study aims to assess the potential impact of environmental drivers on COVID-19 transmission in Bucharest, capital of Romania during the analyzed epidemic period. Through descriptive statistics and cross-correlation tests applied to time series of daily observational and geospatial data of major outdoor inhalable particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) or ≤ 10 µm (PM10), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), carbon monoxide (CO), Aerosol Optical Depth at 550 nm (AOD) and radon (²²²Rn), we investigated the COVID-19 waves patterns under different meteorological conditions. This study examined the contribution of individual climate variables on the ground level air pollutants concentrations and COVID-19 disease severity. As compared to the long-term average AOD over Bucharest from 2015 to 2019, for the same year periods, this study revealed major AOD level reduction by ~28 % during the spring lockdown of the first COVID-19 wave (15 March 2020-15 May 2020), and ~16 % during the third COVID-19 wave (1 February 2021-1 June 2021). This study found positive correlations between exposure to air pollutants PM2.5, PM10, NO₂, SO₂, CO and ²²²Rn, and significant negative correlations, especially for spring-summer periods between ground O₃ levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance with COVID-19 incidence and deaths. For the analyzed time period 1 January 2020-1 April 2022, before and during each COVID-19 wave were recorded stagnant synoptic anticyclonic conditions favorable for SARS-CoV-2 virus spreading, with positive Omega surface charts composite average (Pa/s) at 850 mb during fall- winter seasons, clearly evidenced for the second, the fourth and the fifth waves. These findings are relevant for viral infections controls and health safety strategies design in highly polluted urban environments.

Research on COVID-19 and air pollution: A path towards advancing exposure science

The COVID-19 pandemic has resulted in an extraordinary incidence of morbidity and mortality, with almost 6 million deaths worldwide at the time of this writing (https://covid19.who.int/). There has been a pressing need for research that would shed light on factors - especially modifiable factors - that could reduce risks to human health. At least several hundred studies addressing the complex relationships among transmission of SARS-CoV-2, air pollution, and human health have been published. However, these investigations are limited by available and consistent data. The project goal was to seek input into opportunities to improve and fund exposure research on the confluence of air pollution and infectious agents such as SARS-CoV-2. Thirty-two scientists with expertise in exposure science, epidemiology, risk assessment, infectious diseases, and/or air pollution responded to the outreach for information. Most of the respondents expressed value in developing a set of common definitions regarding the extent and type of public health lockdown. Traffic and smoking ranked high as important sources of air pollution warranting source-specific research (in contrast with assessing overall ambient level exposures). Numerous important socioeconomic factors were also identified. Participants offered a wide array of inputs on what they considered to be essential studies to improve our understanding of exposures. These ranged from detailed mechanistic studies to improved air quality monitoring studies and prospective cohort studies. Overall, many respondents indicated that these issues require more research and better study design. As an exercise to solicit opinions, important concepts were brought forth that provide opportunities for scientific collaboration and for consideration for funding prioritization. Further conversations on these concepts are needed to advance our thinking on how to design research that moves us past the documented limitations in the current body of research and prepares us for the next pandemic.

Environmental and societal factors associated with COVID-19-related death in people with rheumatic disease: an observational study

Background

Differences in the distribution of individual-level clinical risk factors across regions do not fully explain the observed global disparities in COVID-19 outcomes. We aimed to investigate the associations between environmental and societal factors and country-level variations in mortality attributed to COVID-19 among people with rheumatic disease globally.

Methods

In this observational study, we derived individual-level data on adults (aged 18-99 years) with rheumatic disease and a confirmed status of their highest COVID-19 severity level from the COVID-19 Global Rheumatology Alliance (GRA) registry, collected between March 12, 2020, and Aug 27, 2021. Environmental and societal factors were obtained from publicly available sources. The primary endpoint was mortality attributed to COVID-19. We used a multivariable logistic regression to evaluate independent associations between environmental and societal factors and death, after controlling for individual-level risk factors. We used a series of nested mixed-effects models to establish whether environmental and societal factors sufficiently explained country-level variations in death.

Findings

14 044 patients from 23 countries were included in the analyses. 10 178 (72·5%) individuals were female and 3866 (27·5%) were male, with a mean age of 54·4 years (SD 15·6). Air pollution (odds ratio 1·10 per 10 μg/m3 [95% CI 1·01-1·17]; p=0·0105), proportion of the population aged 65 years or older (1·19 per 1% increase [1·10-1·30]; p<0·0001), and population mobility (1·03 per 1% increase in number of visits to grocery and pharmacy stores [1·02-1·05]; p<0·0001 and 1·02 per 1% increase in number of visits to workplaces [1·00-1·03]; p=0·032) were independently associated with higher odds of mortality. Number of hospital beds (0·94 per 1-unit increase per 1000 people [0·88-1·00]; p=0·046), human development index (0·65 per 0·1-unit increase [0·44-0·96]; p=0·032), government response stringency (0·83 per 10-unit increase in containment index [0·74-0·93]; p=0·0018), as well as follow-up time (0·78 per month [0·69-0·88]; p<0·0001) were independently associated with lower odds of mortality. These factors sufficiently explained country-level variations in death attributable to COVID-19 (intraclass correlation coefficient 1·2% [0·1-9·5]; p=0·14).

Interpretation

Our findings highlight the importance of environmental and societal factors as potential explanations of the observed regional disparities in COVID-19 outcomes among people with rheumatic disease and lay foundation for a new research agenda to address these disparities.

Funding

American College of Rheumatology and European Alliance of Associations for Rheumatology.

Ambient Air Pollutant Exposures and COVID-19 Severity and Mortality in a Cohort of Patients with COVID-19 in Southern California

Rationale: Ecological studies have shown air pollution associations with coronavirus disease (COVID-19) outcomes. However, few cohort studies have been conducted. Objectives: To conduct a cohort study investigating the association between air pollution and COVID-19 severity using individual-level data from the electronic medical record. Methods: This cohort included all individuals who received diagnoses of COVID-19 from Kaiser Permanente Southern California between March 1 and August 31, 2020. One-year and 1-month averaged ambient air pollutant (particulate matter ⩽2.5 μm in aerodynamic diameter [PM_2.5], NO₂, and O₃) exposures before COVID-19 diagnosis were estimated on the basis of residential address history. Outcomes included COVID-19-related hospitalizations, intensive respiratory support (IRS), and ICU admissions within 30 days and mortality within 60 days after COVID-19 diagnosis. Covariates included socioeconomic characteristics and comorbidities. Measurements and Main Results: Among 74,915 individuals (mean age, 42.5 years; 54% women; 66% Hispanic), rates of hospitalization, IRS, ICU admission, and mortality were 6.3%, 2.4%, 1.5%, and 1.5%, respectively. Using multipollutant models adjusted for covariates, 1-year PM_2.5 and 1-month NO₂ average exposures were associated with COVID-19 severity. The odds ratios associated with a 1-SD increase in 1-year PM_2.5 (SD, 1.5 μg/m³) were 1.24 (95% confidence interval [CI], 1.16-1.32) for COVID-19-related hospitalization, 1.33 (95% CI, 1.20-1.47) for IRS, and 1.32 (95% CI, 1.16-1.51) for ICU admission; the corresponding odds ratios associated with 1-month NO₂ (SD, 3.3 ppb) were 1.12 (95% CI, 1.06-1.17) for hospitalization, 1.18 (95% CI, 1.10-1.27) for IRS, and 1.21 (95% CI, 1.11-1.33) for ICU admission. The hazard ratios for mortality were 1.14 (95% CI, 1.02-1.27) for 1-year PM_2.5 and 1.07 (95% CI, 0.98-1.16) for 1-month NO₂. No significant interactions with age, sex or ethnicity were observed. Conclusions: Ambient PM_2.5 and NO₂ exposures may affect COVID-19 severity and mortality.

Assessing the impact of long-term exposure to nine outdoor air pollutants on COVID-19 spatial spread and related mortality in 107 Italian provinces

This paper investigates the air quality in 107 Italian provinces in the period 2014-2019 and the association between exposure to nine outdoor air pollutants and the COVID-19 spread and related mortality in the same areas. The methods used were negative binomial (NB) regression, ordinary least squares (OLS) model, and spatial autoregressive (SAR) model. The results showed that (i) common air pollutants-nitrogen dioxide (NO₂), ozone (O₃), and particulate matter (PM_2.5 and PM₁₀)-were highly and positively correlated with large firms, energy and gas consumption, public transports, and livestock sector; (ii) long-term exposure to NO₂, PM_2.5, PM₁₀, benzene, benzo[a]pyrene (BaP), and cadmium (Cd) was positively and significantly correlated with the spread of COVID-19; and (iii) long-term exposure to NO_2, O₃, PM_2.5, PM₁₀, and arsenic (As) was positively and significantly correlated with COVID-19 related mortality. Specifically, particulate matter and Cd showed the most adverse effect on COVID-19 prevalence; while particulate matter and As showed the largest dangerous impact on excess mortality rate. The results were confirmed even after controlling for eighteen covariates and spatial effects. This outcome seems of interest because benzene, BaP, and heavy metals (As and Cd) have not been considered at all in recent literature. It also suggests the need for a national strategy to drive down air pollutant concentrations to cope better with potential future pandemics.

Toxicity of different biodiesel exhausts in primary human airway epithelial cells grown at air-liquid interface

Biodiesel is created through the transesterification of fats/oils and its usage is increasing worldwide as global warming concerns increase. Biodiesel fuel properties change depending on the feedstock used to create it. The aim of this study was to assess the different toxicological properties of biodiesel exhausts created from different feedstocks using a complex 3D air-liquid interface (ALI) model that mimics the human airway. Primary human airway epithelial cells were grown at ALI until full differentiation was achieved. Cells were then exposed to 1/20 diluted exhaust from an engine running on Diesel (ULSD), pure or 20% blended Canola biodiesel and pure or 20% blended Tallow biodiesel, or Air for control. Exhaust was analysed for various physio-chemical properties and 24-h after exposure, ALI cultures were assessed for permeability, protein release and mediator response. All measured exhaust components were within industry safety standards. ULSD contained the highest concentrations of various combustion gases. We found no differences in terms of particle characteristics for any of the tested exhausts, likely due to the high dilution used. Exposure to Tallow B100 and B20 induced increased permeability in the ALI culture and the greatest increase in mediator response in both the apical and basal compartments. In contrast, Canola B100 and B20 did not impact permeability and induced the smallest mediator response. All exhausts but Canola B20 induced increased protein release, indicating epithelial damage. Despite the concentrations of all exhausts used in this study meeting industry safety regulations, we found significant toxic effects. Tallow biodiesel was found to be the most toxic of the tested fuels and Canola the least, both for blended and pure biodiesel fuels. This suggests that the feedstock biodiesel is made from is crucial for the resulting health effects of exhaust exposure, even when not comprising the majority of fuel composition.

The association of airborne particulate matter and benzo[a]pyrene with the clinical course of COVID-19 in patients hospitalized in Poland

Air pollution can adversely affect the immune response and increase the severity of the viral disease. The present study aimed to explore the relationship between symptomatology, clinical course, and inflammation markers of adult patients with coronavirus disease 2019 (COVID-19) hospitalized in Poland (n = 4432) and air pollution levels, i.e., mean 24 h and max 24 h level of benzo(a)pyrene (B(a)P) and particulate matter <10 μm (PM₁₀) and <2.5 μm (PM_2.5) during a week before their hospitalization. Exposures to PM_2.5 and B(a)P exceeding the limits were associated with higher odds of early respiratory symptoms of COVID-19 and hyperinflammatory state: interleukin-6 > 100 pg/mL, procalcitonin >0.25 ng/mL, and white blood cells count >11 × 10³/mL. Except for the mean 24 h PM₁₀ level, the exceedance of other air pollution parameters was associated with increased odds for oxygen saturation <90%. Exposure to elevated PM_2.5 and B(a)P levels increased the odds of oxygen therapy and death. This study evidences that worse air quality is related to increased severity of COVID-19 and worse outcome in hospitalized patients. Mitigating air pollution shall be an integral part of measures undertaken to decrease the disease burden during a pandemic of viral respiratory illness.

Systematic review of climate change effects on reproductive health

Climate change is a major risk factor for overall health, including reproductive health, and well-being. Increasing temperatures, due mostly to increased greenhouse gases trapping excess heat in the atmosphere, result in erratic weather patterns, wildfires, displacement of large communities, and stagnant water resulting in vector-borne diseases that, together, have set the stage for new and devastating health threats across the globe. These conditions disproportionately affect disadvantaged and vulnerable populations, including women, pregnant persons, young children, the elderly, and the disabled. This review reports on the evidence for the adverse impacts of air pollution, wildfires, heat stress, floods, toxic chemicals, and vector-borne diseases on male and female fertility, the developing fetus, and obstetric outcomes. Reproductive health care providers are uniquely positioned and have an unprecedented opportunity to educate patients and policy makers about mitigating the impact of climate change to assure reproductive health in this and future generations.

Effects of Meteorological Factors and Air Pollutants on COVID-19 Transmission under the Action of Control Measures

At present, COVID-19 is still spreading, and its transmission patterns and the main factors that affect transmission behavior still need to be thoroughly explored. To this end, this study collected the cumulative confirmed cases of COVID-19 in China by 8 April 2020. Firstly, the spatial characteristics of the COVID-19 transmission were investigated by the spatial autocorrelation method. Then, the factors affecting the COVID-19 incidence rates were analyzed by the generalized linear mixed effect model (GLMMs) and geographically weighted regression model (GWR). Finally, the geological detector (GeoDetector) was introduced to explore the influence of interactive effects between factors on the COVID-19 incidence rates. The results showed that: (1) COVID-19 had obvious spatial aggregation. (2) The control measures had the largest impact on the COVID-19 incidence rates, which can explain the difference of 34.2% in the COVID-19 incidence rates, while meteorological factors and pollutant factors can only explain the difference of 1% in the COVID-19 incidence rates. It explains that some of the literature overestimates the impact of meteorological factors on the spread of the epidemic. (3) The influence of meteorological factors was stronger than that of air pollution factors, and the interactive effects between factors were stronger than their individual effects. The interaction between relative humidity and NO2 was stronger. The results of this study will provide a reference for further prevention and control of COVID-19.