Health effects of PM2.5 sources on children's allergic and respiratory symptoms in Fukuoka, Japan

PM2.5 induces developmental neurotoxicity in cortical organoids

There is mounting evidence implicating the potential neurotoxic effects of PM2.5 during brain development, as it has been observed to traverse both the placental barrier and the fetal blood-brain barrier. However, the current utilization of 2D cell culture and animal models falls short in providing an accurate representation of human brain development. Consequently, the precise mechanisms underlying PM2.5-induced developmental neurotoxicity in humans remain obscure. To address this research gap, we constructed three-dimensional (3D) cortical organoids that faithfully recapitulate the initial stages of human cerebral cortex development. Our goal is to investigate the mechanisms of PM2.5-induced neurotoxicity using 3D brain organoids that express cortical layer proteins. Our findings demonstrate that exposure to PM2.5 concentrations of 5 μg/mL and 50 μg/mL induces neuronal apoptosis and disrupts normal neural differentiation, thereby suggesting a detrimental impact on neurodevelopment. Furthermore, transcriptomic analysis revealed PM2.5 exposure induced aberrations in mitochondrial complex I functionality, which is reminiscent of Parkinson's syndrome, potentially mediated by misguided axon guidance and compromised synaptic maintenance. This study is a pioneering assessment of the neurotoxicity of PM2.5 pollution on human brain tissues based on 3D cortical organoids, and the results are of great significance in guiding the formulation of the next air pollution prevention and control policies in China to achieve the sustainable improvement of air quality and to formulate pollution abatement strategies that can maximize the benefits to public health.

Prenatal and postnatal early life exposure to greenness and particulate matter of different size fractions in relation to childhood rhinitis - A multi-center study in China

The impact of early life exposure to residential greenness on childhood rhinitis and its interaction with particulate matter (PM) of different size fractions remain inconsistent. Herein, we recruited 40,486 preschool children from randomly selected daycare centers in 7 cities in China from 2019 to 2020, and estimated exposure to residential greenness by the normalized difference vegetation index (NDVI) with a 500 m buffer. Exposure to ambient PM (PM1, PM2.5, and PM10) was evaluated using a satellite-based prediction model (daily, at a resolution of 1 km × 1 km). By mixed-effect logistic regression, NDVI values during pregnancy, in the first (0-1 year old) and the second (1-2 years old) year of life were negatively associated with lifetime rhinitis (LR) and current rhinitis (CR) (P < 0.001). PM in the same time windows was associated with increased risks of LR and CR in children, with smaller size fraction of PM showing greater associations. The negative associations between prenatal and postnatal NDVI and LR and CR in preschool children remained robust after adjusting for concomitant exposure to PM, whereas the associations of postnatal NDVI and rhinitis showed significant interactions with PM. At lower levels of PM, postnatal NDVI remained negatively associated with rhinitis and was partly mediated by PM (10.0-40.9 %), while at higher levels of PM, the negative associations disappeared or even turned positive. The cut-off levels of PM were identified for each size fraction of PM. In conclusion, prenatal exposure to greenness had robust impacts in lowering the risk of childhood rhinitis, while postnatal exposure to greenness depended on the co-exposure levels to PM. This study revealed the complex interplay of greenness and PM on rhinitis in children. The exposure time window in prenatal or postnatal period and postnatal concomitant PM levels played important roles in influencing the associations between greenness, PM and rhinitis.

Intricate synergistic effects between air pollution and carbon emission: An emerging evidence from China

Due to global climate change and intensifying anthropogenic pollution, China confronts the dual challenge of controlling particulate matter 2.5 μm (PM2.5) pollution and reducing carbon emissions. Quantifying the characteristics of PM2.5 concentrations and CO2 emissions, as well as identifying the driving factors and synergistic effects of PM2.5 reduction and CO2 mitigation, are crucial steps in promoting sustainable urban development and achieving the Sustainable Development Goals (SDGs) in China. In this study, we selected 168 cities as our case-study, and quantified spatial characteristics of PM2.5 concentrations and CO2 emissions from 2015 to 2020 in China. Then we analyzed driving factors affecting the spatial heterogeneity of PM2.5 reduction and CO2 mitigation applying Multi-scale Geographically Weighted Regression (MGWR) model. By employing coupling coordination degree (CCD) model, we further detected the spatiotemporal evolution patterns of the synergistic effects between PM2.5 reduction and CO2 mitigation in key Chinese cities. The result showed that: (a) From 2015 to 2020, PM2.5 concentrations experienced a significant reduction from 59.78 μg/m3 to 49.83 μg/m3, while CO2 emissions increased from 44.88 × 106 t in 2015 to 45.77 × 106 t in 2020; (b) Green economy efficiency (gee), government attention (gover), and environmental regulation (envir) demonstrate the most pronounced synergistic effect on pollution reduction and carbon mitigation, with the drivers exhibiting obvious spatial heterogeneity; (c) The overall coupling coordination level of PM2.5 pollution and CO2 emissions in China dropped from 0.49 in 2015 to 0.46 in 2020, and the coupling coordination grade in northern cities was notably higher than that in southern cities. The result enhances our understanding of spatiotemporal patterns of synergistic effects between PM2.5 reduction and CO2 mitigation, and provides the theoretical basis for policy decision-making to realize pollution decrease and carbon neutral and regional environment governance.

Linkage between Airborne Particulate Matter and Viral Pandemic COVID-19 in Bucharest

The long-distance spreading and transport of airborne particulate matter (PM) of biogenic or chemical compounds, which are thought to be possible carriers of SARS-CoV-2 virions, can have a negative impact on the incidence and severity of COVID-19 viral disease. Considering the total Aerosol Optical Depth at 550 nm (AOD) as an atmospheric aerosol loading variable, inhalable fine PM with a diameter ≤2.5 µm (PM2.5) or coarse PM with a diameter ≤10 µm (PM10) during 26 February 2020-31 March 2022, and COVID-19's five waves in Romania, the current study investigates the impact of outdoor PM on the COVID-19 pandemic in Bucharest city. Through descriptive statistics analysis applied to average daily time series in situ and satellite data of PM2.5, PM10, and climate parameters, this study found decreased trends of PM2.5 and PM10 concentrations of 24.58% and 18.9%, respectively compared to the pre-pandemic period (2015-2019). Exposure to high levels of PM2.5 and PM10 particles was positively correlated with COVID-19 incidence and mortality. The derived average PM2.5/PM10 ratios during the entire pandemic period are relatively low (<0.44), indicating a dominance of coarse traffic-related particles' fraction. Significant reductions of the averaged AOD levels over Bucharest were recorded during the first and third waves of COVID-19 pandemic and their associated lockdowns (~28.2% and ~16.4%, respectively) compared to pre-pandemic period (2015-2019) average AOD levels. The findings of this research are important for decision-makers implementing COVID-19 safety controls and health measures during viral infections.

Associations between hemoglobin levels and source-specific exposure to ambient fine particles among children aged <5 years in low- and middle-income countries

OBJECTIVE

We investigated associations between source-specific fine particulate matter (PM2.5) exposure and hemoglobin levels among children in low- and middle-income countries (LMICs).

METHOD

36,675 children aged < 5 years were collected in 11 LMICs during 2017. We associated child hemoglobin with 20 source-specific PM2.5, and calculated changes in hemoglobin that could be attributed to different PM2.5-mixture scenarios, established using real-world data from 88 Asian and African LMICs (AA-LMICs).

RESULTS

Multiple-source analysis revealed PM2.5 produced by solvents (change in hemoglobin for 1-μg/m3 increment in PM2.5: -10.34 g/L, 95% CI -14.88 to -5.91), industrial coal combustion (-0.51 g/L, 95% CI -9.25 to -0.08), road transportation (-0.50 g/L, 95% CI -6.96 to -0.29), or waste handling and disposal (-0.34 g/L, 95% CI -4.38 to -0.23) was significantly associated with a decrease in hemoglobin level. Decreases in hemoglobin attributable to the PM2.5 mixtures were co-determined by the concentrations and their source profiles. The largest PM2.5-related change in hemoglobin was -10.25 g/L (95% CI -15.54 to -5.27) for a mean exposure of 61.01 μg/m3 in India.

CONCLUSION

Association between PM2.5 and a decrease in hemoglobin was affected by variations in PM2.5 source profiles. Source-oriented interventions are warranted to protect children in LMICs from air pollution.

Particulate matter concentration effects on attention to environmental issues: a cross-sectional study among residents in Korea's Pohang Industrial Complex

Background

With modernization, air pollution has become increasingly serious, and its effects on health have been revealed. As a result, public interest in environmental pollution has become critical for regulating air pollution. In our study, we aim to evaluate the impact of air pollution levels on public attention to environmental issues and examine whether awareness of the residential environment's impact on health acts as a mediator in this relationship.

Methods

We conducted an analysis on 400 individuals surveyed in the preliminary feasibility study on adverse health effects in the Pohang Industrial Complex, to examine the relationship between particulate matter 2.5 (PM2.5) and attention to environmental issues. Logistic regression analysis was performed, and mediation analysis was used to determine whether awareness of the residential environment's impact on health mediated the relationship.

Results

The logistic regression analysis results showed that PM2.5 levels were associated with attention to environmental issues (adjusted odds ratio [AOR]: 2.1; 95% confidence interval [CI]: 1.3-3.5; p = 0.003) and awareness of health impacts (AOR: 3.4; 95% CI: 1.6-7.1; p = 0.001). The PM2.5 levels showed 9.9% (95% CI: 5.4-14.0) increase in the prevalence of high attention to environmental issues, of which, only 1.0% (95% CI: 0.2-2.3) were mediated by health impact awareness. In the overall analysis, 10% of the total effect of PM2.5 on attention to environmental issues was mediated by health impact awareness.

Conclusions

According to this study's results, there was a correlation between air pollution levels and attention to environmental issues. Awareness of the health impacts of air pollution partially mediated the effect of air pollution levels on attention to environmental issues. In future studies, it is recommended to identify other mediators to further understand this structure.

Ambient fine particulate matter and allergic symptoms in the middle-aged and elderly population: results from the PIFCOPD study

BACKGROUND

The associations between short- and long-term exposure to ambient fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM_2.5) and allergic symptoms in middle-aged and elderly populations remain unclear, particularly in China, where most cities have severe air pollution.

METHODS

Participants (n = 10,142; age = 40-75 years) were recruited from ten regions in China from 2018 to 2021 for the Predictive Value of Inflammatory Biomarkers and Forced Expiratory Volume in 1 s (FEV₁) for Chronic Obstructive Pulmonary Disease (PIFCOPD) study. Short-term (lag0 and lag0-7 day) and long-term (1-, 3- and 5-year) PM_2.5 concentrations at residences were extracted from the air pollutant database known as Tracking Air Pollution (TAP) in China. Multivariate logistic regression models were used to estimate associations for short- and long-term PM_2.5 exposure concentrations and long-term exposure models were additionally adjusted for short-term deviations.

RESULTS

A 10 µg/m³ increase in PM_2.5 on the day the allergic symptoms questionnaire was administered (lag0 day) was associated with higher odds of allergic nasal (1.09, 95% CI 1.05, 1.12) and eye symptoms (1.08, 95% CI 1.05, 1.11), worsening dyspnea caused by allergens (1.06, 95% CI 1.02, 1.10), and ≥ 2 allergic symptoms (1.07, 95% CI 1.03, 1.11), which was similar in the lag0-7 day concentrations. A 10 µg/m³ increase in the 1-year average PM_2.5 concentration was associated with an increase of 23% for allergic nasal symptoms, 22% for eye symptoms, 20% for worsening dyspnea caused by allergens, and 21% for ≥ 2 allergic symptoms, similar to the 3- and 5-year average PM_2.5 concentrations. These associations between long-term PM_2.5 concentration and allergic symptoms were generally unchanged after adjustment for short-term deviations.

CONCLUSIONS

Short- and long-term exposure to ambient PM_2.5 was associated with an increased risk of allergic nasal and eye symptoms, worsening dyspnea caused by allergens, and ≥ 2 allergic symptoms.

TRIAL REGISTRATION

Clinical trial ID: NCT03532893 (29 Mar 2018).

The variation of PM2.5 from ship emission under low-sulfur regulation: A case study in the coastal suburbs of Kitakyushu, Japan

From January 1, 2020, the International Maritime Organization (IMO) regulation about the limit of fuel sulfur content to 0.5 % become effective, and ships commonly install sulfur scrubbers or use low-sulfur fuel or liquefied natural gas to replace sulfur-rich heavy fuel oil. In this study, the 4-year PM_2.5 sampling in the coastal suburbs of Kitakyushu, Japan clearly indicated the significant effects of relevant regulation and countermeasures on particle emissions in this receptor site. From the perspective of air quality, an obvious decrease in the mass concentration of ship-emitted particles was observed in 2020, and the contribution of sulfate could reach 60 %. The ammonium concentration was mainly controlled by sulfate and nitrate, and its reduction also could not be ignored, accounting for about 17 %. In terms of public health, the particle exposure risk also changed greatly, mainly due to the reduction of risk levels for As, W, Sb, V, Ni, and Cd; the lowest non-carcinogenic risk and carcinogenic risk for both adults (HI = 1.2 and CR = 5.7 × 10^-5) and children (HI = 9.9 and CR = 1.1 × 10^-4) all occurred in 2020. However, these reduced health risks were still not within the safe level (except for the carcinogenic risk for adults), a fact that requires continued attention. This result exposed the deficiency of current countermeasures regarding the IMO's fuel sulfur content limit in Kitakyushu City, and increasing the proportion of ships using clean fuels (liquefied natural gas, methanol, etc.) would surely alleviate the particle pollution caused by ship emissions.

Regional Transport of PM2.5 from Coal-Fired Power Plants in the Fenwei Plain, China

The Fenwei Plain (FWP) remains one of the worst PM2.5-polluted regions in China, although its air quality has improved in recent years. To evaluate the regional transport characteristics of PM2.5 emitted by coal-fired power plants in the FWP in wintertime, the primary PM2.5, SO2, and NOx emissions from coal-fired power plants with large units (≥300 MW) in 11 cities of the area in January 2019 were collected based on the Continuous Emission Monitoring System (CEMS). The spatial distribution and source contribution of primary and secondary PM2.5 concentrations were investigated using the Weather Research and Forecast (WRF) model and the California Puff (CALPUFF) model. The results showed that secondary PM2.5 was transported over a larger range than primary PM2.5 and that secondary nitrate was the main component of the total PM2.5 concentration, accounting for more than 70%. High concentrations of primary, secondary, and total PM2.5 mainly occurred in the Shaanxi region of the FWP, especially in Xianyang, where the PM2.5 concentrations were the highest among the 11 cities, even though its pollutant emissions were at moderate levels. The PM2.5 concentrations in Sanmenxia and Yuncheng primarily came from regional transport, accounting for 64% and 68%, respectively, while those in other cities were dominated by local emissions, accounting for more than 63%. The results may help to understand the regional transport characteristics of pollutants emitted from elevated point sources over a complex terrain.

Landscape fire smoke enhances the association between fine particulate matter exposure and acute respiratory infection among children under 5 years of age: Findings of a case-crossover study for 48 low- and middle-income countries

BACKGROUND

Fine particulate matter (PM2.5) produced by landscape fires is thought to be more toxic than that from non-fire sources. However, the effects of "fire-sourced" PM2.5 on acute respiratory infection (ARI) are unknown.

METHODS

We combined Demographic and Health Survey (DHS) data from 48 countries with gridded global estimates of PM2.5 concentrations from 2003 to 2014. The proportions of fire-sourced PM2.5 were assessed by a chemical transport model using a variety of PM2.5 source data. We tested for associations between ARI and short-term exposure to fire- and "non-fire-sourced" PM2.5 using a bidirectional case-crossover analysis. The robustness and homogeneity of the associations were examined by sensitivity analyses. We also established a nonlinear exposure-response relationship between fire- and non-fire-sourced PM2.5 and ARI using a two-dimensional spline function.

RESULTS

The study included 36,432 children under 5 years who reported ARI symptoms. Each 1 µg/m3 increment of fire-sourced PM2.5 was associated with a 3.2 % (95 % confidence interval [CI] 0.2, 6.2) increment in the risk of ARI. This effect was comparable to that of each ∼5 µg/m3 increment in PM2.5 from non-fire sources (3.1 %; 95 % CI 2.4, 3.7). The association between ARI and total PM2.5 concentration was significantly mediated by the proportion of fire-sourced particles. Nonlinear analysis showed that the risk of ARI was increased by both fire- and non-fire-sourced PM2.5, but especially by the former.

CONCLUSIONS

PM2.5 produced by landscape fire was more strongly associated to ARI among children under 5 years than that from non-fire sources.

Extraction of multi-scale features enhances the deep learning-based daily PM2.5 forecasting in cities

Characterising the daily PM2.5 concentration is crucial for air quality control. To govern the status of the atmospheric environment, a novel hybrid model for PM2.5 forecasting was proposed by introducing a two-stage decomposition technology of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD); subsequently, a deep learning approach of long short-term memory (LSTM) was proposed. Five cities with unique meteorological and economic characteristics were selected to assess the predictive ability of the proposed model. The results revealed that PM2.5 pollution was generally more severe in inland cities (66.98 ± 0.76 μg m^-3) than in coastal cities (40.46 ± 0.40 μg m-3). The modelling comparison showed that in each city, the secondary decomposition algorithm improved the accuracy and prediction stability of the prediction models. When compared with other prediction models, LSTM effectively extracted featured information and achieved relatively accurate time-series prediction. The hybrid model of CEEMDAN-VMD-LSTM achieved a better prediction in the five cities (R2 = 0.9803 ± 0.01) compared with the benchmark models (R2 = 0.7537 ± 0.03). The results indicate that the proposed approach can identify the inherent correlations and patterns among complex datasets, particularly in time-series analysis.

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.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM_2.5 in typical industrial areas of North China, manual sampling and analysis of PM_2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM_2.5 was 53.4 ± 43.9 μg·m^-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO₃^- ion, at 14.6 ± 14.2 μg·m^-3, followed by organic carbon (OC), SO₄^2-, and NH₄⁺, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m^-3, respectively. The concentrations of OC, NO₃^-, and SO₄^2- were highest in winter and lowest in summer, whereas the NH₄⁺ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO₂ emission and conversion rates in winter, resulting in the SO₄^2- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m^-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m^-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM_2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM_2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Impacts of particulate matter (PM2.5) on the health status of outdoor workers: observational evidence from Malaysia

Ambient air pollution is a significant contributor to disease burden, leading to an estimated 4.2 million premature deaths and 103.1 million disability-adjusted life years (DALYs) annually worldwide. As industrialization and urbanization surge in Asia, air pollution and its corresponding health issues follow suit. Findings on disease burden in developing countries are extremely scanty. This study aimed to determine the concentration of PM_2.5 and its impact on respiratory health of outdoor workers in Malaysia. A 2-cycled 3-month cohort study involving 440 participants was conducted. Workers' health status was assessed via (1) Total Ocular Symptom Score (TOSS), (2) Total Nasal Symptom Score (TNSS), (3) St. George's Respiratory Questionnaire (SGPQ), and (4) Asthma Control Test (ACT). The maximum PM_2.5 concentration was measured at 122.90 ± 2.07 µg/m³ during third week of August 2016. Meanwhile, the minimum concentration was measured at 57.47 ± 3.80 µg/m³ and 57.47 ± 1.64 µg/m³ during fourth week of July 2016 and first week of August 2017 respectively. Findings revealed that TOSS, TNSS, and SGPQ changes were significantly (p < 0.05) associated with the concentration of PM_2.5. Outdoor workers were more significantly (p < 0.05) affected by changes in PM_2.5 compared to indoor workers with a moderate correlation (r value ranged from 0.4 to 0.7). Ironically, no significant association was found between ACT assessment and PM_2.5. Collectively, our findings suggested that changes in the concentration of PM_2.5 threatened the respiratory health of outdoor workers. The existing policy should be strengthened and preventive measures to be enforced safeguarding health status of outdoor workers.

Exposure to ambient air pollution during trimesters of pregnancy and childhood allergic diseases in Wuhan, China

The study explored the associations between maternal exposure to air pollution during different trimesters and allergic diseases including asthma, allergic rhinitis, allergic conjunctivitis or/and eczema. Individual exposure to air pollutants was assessed by an inverse distance weighted (IDW) method using daily concentrations of SO₂, NO₂, PM₁₀, and PM_2.5 from air quality monitoring stations. Multiple logistic regression model was performed to estimate the associations between air pollution during each trimester of pregnancy and childhood allergic diseases. A total of 332 children (51.3%) were reported by their parents having been diagnosed with allergic diseases. After adjusting for covariates, allergic diseases were significantly associated with per interquartile range (IQR) increase in NO₂, PM₁₀, PM_2.5 during the second trimester with odds ratios (ORs) and 95% confidence intervals (95%CIs) being 1.292 (1.005,1.662), 1.210 (1.042,1,405) and 1.270 (1.004,1.606), respectively. These findings suggest that maternal exposure to certain air pollutants during pregnancy, especially in the second trimester, is associated with childhood allergic diseases.

Impacts of exposure to air pollution, radon and climate drivers on the COVID-19 pandemic in Bucharest, Romania: A time series study

During the ongoing global COVID-19 pandemic disease, like several countries, Romania experienced a multiwaves pattern over more than two years. The spreading pattern of SARS-CoV-2 pathogens in the Bucharest, capital of Romania is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation. Through descriptive statistics and cross-correlation analysis applied to daily time series of observational and geospatial data, this study aims to evaluate the synergy of COVID-19 incidence and lethality with air pollution and radon under different climate conditions, which may exacerbate the coronavirus' effect on human health. During the entire analyzed period 1 January 2020-21 December 2021, for each of the four COVID-19 waves were recorded different anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere, and favorable stability conditions during fall-early winter seasons for COVID-19 disease fast-spreading, mostly during the second, and the fourth waves. As the temporal pattern of airborne SARS-CoV-2 and its mutagen variants is affected by seasonal variability of the main air pollutants and climate parameters, this paper found: 1) the daily outdoor exposures to air pollutants (particulate matter PM2.5 and PM10, nitrogen dioxide-NO₂, sulfur dioxide-SO₂, carbon monoxide-CO) and radon - ²²²Rn, are directly correlated with the daily COVID-19 incidence and mortality, and may contribute to the spread and the severity of the pandemic; 2) the daily ground ozone-O₃ levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance are anticorrelated with the daily new COVID-19 incidence and deaths, averageingful for spring-summer periods. Outdoor exposure to ambient air pollution associated with radon is a non-negligible driver of COVID-19 transmission in large metropolitan areas, and climate variables are risk factors in spreading the viral infection. The findings of this study provide useful information for public health authorities and decision-makers to develop future pandemic diseases strategies in high polluted metropolitan environments.

A Case-Crossover Analysis of the Association between Exposure to Total PM2.5 and Its Chemical Components and Emergency Ambulance Dispatches in Tokyo

A limited number of studies have investigated the association between short-term exposure to PM_2.5 components and morbidity. The present case-crossover study explored the association between exposure to total PM_2.5 and its components and emergency ambulance dispatches, which is one of the indicators of morbidity, in the 23 Tokyo wards. Between 2016 and 2018 (mean mass concentrations of total PM_2.5 13.5 μg/m³), we obtained data, from the Tokyo Fire Department, on the daily cases of ambulance dispatches. Fine particles were collected at a fixed monitoring site and were analyzed to estimate the daily mean concentrations of carbons and ions. We analyzed 1038301 cases of health-based all-cause ambulance dispatches by using a conditional logistic regression model. The average concentrations of total PM_2.5 over one and the previous day were positively associated with the number of ambulance dispatches. In terms of PM_2.5 components, the percentage increase per interquartile range (IQR) increase was 0.8% for elemental carbon (IQR = 0.8 μg/m³; 95% CI = 0.3-1.3%), 0.9% for sulfate (2.1 μg/m³; 0.5-1.4%), and 1.1% for ammonium (1.3 μg/m³; 0.4-1.8%) in the PM_2.5-adjusted models. This is the first study to find an association between some specific components in PM_2.5 and ambulance dispatches.

Issue 1 - "Update on adverse respiratory effects of outdoor air pollution" Part 2): Outdoor air pollution and respiratory diseases: Perspectives from Angola, Brazil, Canada, Iran, Mozambique and Portugal

OBJECTIVE

To analyse the GARD perspective on the health effects of outdoor air pollution, and to synthesise the Portuguese epidemiological contribution to knowledge on its respiratory impact.

RESULTS

Ambient air pollution has deleterious respiratory effects which are more apparent in larger, densely populated and industrialised countries, such as Canada, Iran, Brazil and Portugal, but it also affects people living in low-level exposure areas. While low- and middle-income countries (LMICs), are particularly affected, evidence based on epidemiological studies from LMICs is both limited and heterogeneous. While nationally, Portugal has a relatively low level of air pollution, many major cities face with substantial air pollution problems. Time series and cross-sectional epidemiological studies have suggested increased respiratory hospital admissions, and increased risk of respiratory diseases in people who live in urban areas and are exposed to even a relatively low level of air pollution.

CONCLUSIONS

Adverse respiratory effects due to air pollution, even at low levels, have been confirmed by epidemiological studies. However, evidence from LMICs is heterogeneous and relatively limited. Furthermore, longitudinal cohort studies designed to study and quantify the link between exposure to air pollutants and respiratory diseases are needed. Worldwide, an integrated approach must involve multi-level stakeholders including governments (in Portugal, the Portuguese Ministry of Health, which hosts GARD-Portugal), academia, health professionals, scientific societies, patient associations and the community at large. Such an approach not only will garner a robust commitment, establish strong advocacy and clear objectives, and raise greater awareness, it will also support a strategy with adequate measures to be implemented to achieve better air quality and reduce the burden of chronic respiratory diseases (CRDs).

Real-time image-based air quality estimation by deep learning neural networks

Air quality profoundly impacts public health and environmental equity. Efficient and inexpensive air quality monitoring instruments could be greatly beneficial for human health and air pollution control. This study proposes an image-based deep learning model (CNN-RC) that integrates a convolutional neural network (CNN) and a regression classifier (RC) to estimate air quality at areas of interest through feature extraction from photos and feature classification into air quality levels. The models were trained and tested on datasets with different combinations of the current image, the baseline image, and HSV (hue, saturation, value) statistics for increasing model reliability and estimation accuracy. A total of 3549 hourly air quality datasets (including photos, PM2.5, PM10, and the air quality index (AQI)) collected at the Linyuan air quality monitoring station of Kaohsiung City in Taiwan constituted the case study. The main breakthrough of this study is to timely produce an accurate image-based estimation of several pollutants simultaneously by using only one single deep learning model. The test results show that estimation accuracy in terms of R² for PM_2.5, PM_10, and AQI based on daytime (nighttime) images reaches 76% (83%), 84% (84%), and 76% (74%), respectively, which demonstrates the great capability of our method. The proposed model offers a promising solution for rapid and reliable multi-pollutant estimation and classification based solely on captured images. This readily scalable measurement approach could address major gaps between air quality data acquired from expensive instruments worldwide.

Composition and sources of particulate matter in the Beijing-Tianjin-Hebei region and its surrounding areas during the heating season

This paper aimed to analyze the composition and pollution sources of particulate matter (PM) in the Beijing-Tianjin-Hebei region and its surrounding areas (henceforth the BTH region) during the heating season to support the mitigation and control of regional air pollution. Manual monitoring data from the China National Environmental Monitoring Network for Atmospheric PM in the BTH region were collected and analyzed during the 2016 and 2018 heating seasons. The positive definite matrix factor analysis (PMF) model was used to analyze the PM sources in BTH cities during the heating season. The main PM components were organic matter (OM), nitrate (NO₃^-), sulfate (SO₄^2-) and ammonium salt (NH₄⁺). Direct emission sources have decreased since 2016, indicating the effectiveness of governmental controls on these sources; however, secondary pollution showed an increasing trend, suggesting control measures should be strengthened. Daily regional average concentrations of OM, SO₄^2-, NH₄⁺, elemental carbon (EC), chloride (Cl^-) and trace elements all showed similar trends. When air quality worsened, the concentrations of the main PM components increased, but trends of change varied among components. In 2018, concentrations of OM and chloride were highest in the Taihang Mountains, and NO₃ concentrations were highest in Anyang, Hebi, Jiaozuo and Xinxiang. The SO₄^2- concentration was highest in the southern section of the Taihang Mountains. The NH₄⁺ and EC concentrations were generally highest in the central and southern regions. The concentration of crustal substances was highest in some cities in the north and central parts of the BTH region. In the 2018 heating season, the pollution level of five transmission channels showed an increasing trend in the Northwest, Southeast, Yanshan, South and Taihang Mountain channels. These findings provide a scientific basis for the continued management of atmospheric PM pollution.

Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain

While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020-1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future.

Risk assessment and management of PM2.5-bound heavy metals in the urban area of Kitakyushu, Japan

The sampling campaign of PM_2.5 was carried out in Kitakyushu City on the western edge of Japan from 2013 to 2019, and 29 heavy metals loaded in PM_2.5 were measured in this study. During the whole sampling period, the PM_2.5 mass concentration ranged from 6.3 μg·m^-3 to 57.5 μg·m^-3, with a median value of 21.3 μg·m^-3, and the sum concentration of heavy metals only accounted for 3%. According to the enrichment factor (EF) and geo-accumulation index (Igeo) analysis, it can be known that Se, Mo, Pb, As, Zn, W, Sb, Cu, V, Cr, Ni, and Cs were mainly from anthropogenic sources, which had EF values larger than 10 and Igeo values larger than 0. The comprehensive ecological risk index for these 12 anthropogenic metals was far greater than 600. This large index showed severe metal pollution and very high ecological risk in the urban area of Kitakyushu, Japan, which should be paid great attention. The human health assessment result further revealed that children living at the sampling site faced severe non-carcinogenic risk (HI = 7.8) and moderate carcinogenic risk (CR = 1.2 × 10^-4), and oral ingestion was basically the most important exposure pathway, followed by dermal contact and inhalation. The priority control metals included Mo, Se, As, Pb, Sb, and Cr; moreover, the concentration-weighted trajectory analysis (CWT) indicated that Mo, Sb, and Cr were from ship emissions because some shipping routes around the Kyushu area were identified as their potential pollution source regions, while Se, As, and Pb were carried by the air masses from the Asian landmass. Overall, although the PM_2.5 concentration in the urban area of Kitakyushu, Japan was not high, the heavy metal risk cannot be overlooked; it is necessary to strengthen the source control of high-risk metals and raise public protection awareness.

Full-coverage spatiotemporal mapping of ambient PM2.5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions

Ambient concentrations of particulate matters (PM_2.5 and PM₁₀) are significant indicators for monitoring the air quality relevant to living conditions. At present, most remote sensing based approaches for the estimation of PM_2.5 and PM₁₀ employed Aerosol Optical Depth (AOD) products as the main variate. Nevertheless, the coverage of missing data is generally large in AOD products, which can cause deviations in practical applications of estimated PM_2.5 and PM₁₀ (e.g., air quality monitoring and exposure evaluation). To efficiently address this issue, our study explores a novel approach using the datasets of the precursors & chemical compositions for PM_2.5 and PM₁₀ instead of AOD products. Specifically, the daily full-coverage ambient concentrations of PM_2.5 and PM₁₀ are estimated at 5-km (0.05°) spatial girds across China based on Sentinel-5P and assimilated datasets (GEOS-FP). The estimation models are acquired via an advanced ensemble learning method named Light Gradient Boosting Machine in this paper. For comparison, the Deep Blue AOD product from VIIRS is adopted in a similar framework as a baseline (AOD-based). Validation results show that the ambient concentrations are well estimated through the proposed approach, with the space-based Cross-Validation R²s and RMSEs of 0.88 (0.83) and 11.549 (22.9) μg/m³ for PM_2.5 (PM₁₀), respectively. Meanwhile, the proposed approach achieves better performance than the AOD-based in different cases (e.g., overall and seasonal). Compared to the related previous works over China, the estimation accuracy of our method is also satisfactory. Regarding the mapping, the estimated results through the proposed approach display consecutive spatial distribution and can exactly express the seasonal variations of PM_2.5 and PM₁₀. The proposed approach could efficiently present daily full-coverage results at 5-km spatial grids. It has a large potential to be extended for providing global accurate ambient concentrations of PM_2.5 and PM₁₀ at multiple temporal scales (e.g., daily and annual).

Spatiotemporal variations and risk assessment of ambient air O3, PM10 and PM2.5 in a coastal city of China

Rapid industrialization and urbanization has created significant air pollution problems that have recently begin to impact the lives and health of human beings in China. This study systematically investigated the spatiotemporal variations and the associated health risks of ambient O₃, PM₁₀ and PM_2.5 between 2016 and 2019. The relationships between the target air pollutants and meteorological conditions were further analyzed using the Spearman rank correlation coefficient method. The results demonstrated that the annual mean concentrations of PM₁₀ and PM_2.5 experienced a decreasing trend overall, and PM_2.5 significantly decreased from 1.54 μg/m³ in 2016 to 1.48 μg/m³ in 2019. In contrast, the annual mean concentrations of O₃ were nearly constant during the study period with a slight increasing trend. The pollutants exhibited different seasonal variations and cyclical diurnal variations. The most highest O₃ pollution was seen in spring and summer, while spring and winter were the seasons with the most PM₁₀ and PM_2.5 pollution. The highest concentrations of O₃ appeared in periods of strong solar radiation intensity and photochemical reactions. The highest concentrations of PM₁₀ and PM_2.5 appeared at commuting time. The pollutant concentrations were significantly affected by meteorological conditions. Finally, the non-carcinogenic risks from exposure to O₃, PM₁₀ and PM_2.5 were at an acceptable level (HI < 0.96) and O₃ accounted for ~50% of the total non-carcinogenic risks. However, PM_2.5 posed highly carcinogenic risks (2.5 × 10^-4 < CR < 1.6 × 10^-1) and O₃ exposure showed high potential ecological impacts on vegetation (AOT40: 23.3 ppm-h; W126: 29.0 ppm-h).

Seasonal and areal variability in PM2.5 poses differential degranulation and pro-inflammatory effects on RBL-2H3 cells

PM_2.5 pollution is a widespread environmental and health problem, particularly in China. Besides leading to well-known diseases in the respiratory system, PM_2.5 can also alter immune function to induce or aggravate allergic diseases. To determine whether there are temporal and spatial differences in the allergic responses to PM_2.5, monthly samples were collected from four regions (urban, industrial, suburban, and rural areas) through a whole year in Nanjing city, China. Inorganic chemical components (metals and water-soluble ions) of PM_2.5 were analyzed, and the rat basophil cells (RBL-2H3) exposed to PM_2.5 were assessed through quantitative measures of degranulation (β-hex and histamine) and pro-inflammation cytokine (IL-4 and TNF-α) expression. The highest levels of β-hex were measured in winter and spring PM_2.5 from urban and industrial areas, or autumn PM_2.5 from suburban and rural areas. With respect to histamine, autumn PM_2.5 samples were most potent irrespective of the location. Autumn and winter PM_2.5 induced higher levels of IL-4 than spring and summer samples. However, spring and autumn PM_2.5 caused higher levels of TNF-α. The concentrations of water-soluble ions (NH₄⁺, K⁺ and Cl^-), as well as heavy metals (Pb and Cr), were directly and statistically correlated to the inflammation observed in vitro. In general, the differences between regional and seasonal PM_2.5 in stimulating cell degranulation may depend on endotoxin and airborne allergen content of PM_2.5. The heavy metals and water-soluble ions in PM_2.5 were mostly anthropogenic, which increased the particles' mass-based cellular inflammatory potential, therefore, their health risks, e.g. from vehicular exhaust, coal, and biomass combustion, cannot be ignored.

Health and economic impacts from PM2.5 pollution transfer attributed to domestic trade in China: a provincial-level analysis

In recent years, severe air pollution has had a serious impact on the health and economy of residents and has attracted great attention. Due to the spatial separation between consumption and production, the transfer of PM_2.5 pollution and its health and economic effects caused by interprovincial trade have not been taken seriously. In this study, economic, atmospheric, and epidemiological models were combined to assess air pollution transfer and its health and economic impacts that are attributed to provincial trade in China. The analyses were performed under the PM_2.5 transfer scenario in which economically developed areas in eastern China transferred many health and economic impacts to inland areas through interprovincial trade in 2012. As a result of interprovincial trade, 1980 (95% CI 0, 4114) extra deaths and 208,000 (95% CI 74.5, 395.6) additional illnesses accrued, but 0.184 (95% CI 0.017, 0.372) billion USD of residents' economic loss was avoided in China. The results illustrate the serious impact of domestic trade on regional health and economics. It is necessary to comprehensively consider supply chains in designing policies to mitigate the negative health and economic impacts of air pollution across China.

Biological Response-Enhancing Activity with Antigens in A549 Cells Exposed to Representative Polycyclic Aromatic Hydrocarbons

The question of what kinds of airborne particles, including diesel exhaust particles and their adherent chemical constituents, exacerbate the activity of allergic and inflammatory respiratory diseases has not been elucidated in detail. Therefore, chemicals that have amplifying actions on Dermatophagoides farinae (Df) body extract-induced IL-8, the inflammatory cytokines of the innate immune system, were comprehensively examined using commonly used human alveolar epithelial cells, A549, as simple screening for 17 polycyclic aromatic hydrocarbons (PAHs), which are representative organic constituents in atmospheric samples. The significant amplifying actions of two PAHs, dibenzo[a,l]pyrene (DB[a,l]P) at 50 nM and dibenzo[a,i]pyrene (DB[a,i]P) at 2 μM for 48 h, for IL-8 protein release induced by mite antigens in epithelial cells were observed for the first time. In contrast, the enhancement of IL-8 was not observed in protein levels for these PAHs without the antigens. Meanwhile, the significant synergistic amplifying effect of DB[a,l]P at 50 nM on proinflammatory actions was measured in gene expression (i.e., IL-8, IL-6, ICAM-1, and TNF-α) levels in the experimental setting; for the results, the induction of TNF-α may have been the essential factor that enhanced the amplifying activity of DB[a,l]P for IL-8 gene expression and protein release. Examining the exacerbating effect on allergic pathophysiological states for DB[a,l]P is planned for further study.

Exploring the linkage between seasonality of environmental factors and COVID-19 waves in Madrid, Spain

Like several countries, Spain experienced a multi wave pattern of COVID-19 pandemic over more than one year period, between spring 2020 and spring 2021. The transmission of SARS-CoV-2 pandemics is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation.This study aims to quantify the impact of climate and air pollution factors seasonality on incidence and severity of COVID-19 disease waves in Madrid metropolitan region in Spain. We employed descriptive statistics and Spearman rank correlation tests for analysis of daily in-situ and geospatial time-series of air quality and climate data to investigate the associations with COVID-19 incidence and lethality in Madrid under different synoptic meteorological patterns. During the analyzed period (1 January 2020-28 February 2021), with one month before each of three COVID-19 waves were recorded anomalous anticyclonic circulations in the mid-troposphere, with positive anomalies of geopotential heights at 500 mb and favorable stability conditions for SARS-CoV-2 fast diffusion. In addition, the results reveal that air temperature, Planetary Boundary Layer height, ground level ozone have a significant negative relationship with daily new COVID-19 confirmed cases and deaths. The findings of this study provide useful information to the public health authorities and policymakers for optimizing interventions during pandemics.

High-time-resolution PM2.5 source apportionment based on multi-model with organic tracers in Beijing during haze episodes

Fine particulate matter (PM_2.5) is a prominent atmospheric pollutant that poses serious adverse effects on air quality and human health. PM_2.5 source apportionment based on receptor model suggests that Beijing is polluted by mixed emission sources, but the model is limited by a lack of organic tracers and an inability to distinguish between contributions from local and regional transport. In this study, positive matrix factorization (PMF) model with organic tracers was employed to analyze refined PM_2.5 pollution sources at 1-h time resolution, and the contribution of regional transport was quantified using Particulate source apportionment technology (PSAT) in the Comprehensive Air Quality Model with Extensions (CAMx). The results identified nine source types using PMF model based on offline data for PM_2.5 concentrations, organic carbon, elemental carbon, water-soluble ions, trace elements and organic species. Gasoline and diesel exhausts were distinguished by adding polycyclic aromatic hydrocarbons (PAHs), C19-C24 n-alkanes as key organic tracers. In addition, levoglucosan and hexadecanoic acid are important additions for identifying biomass burning and cooking, respectively. Furthermore, the contribution of specific sources and source regions, from the formation to dissipation of two typical haze episodes (EP1 and EP2) in Beijing, was quantitatively analyzed. EP1 was primarily caused by local emissions with an average contribution rate of 67.5%, characterized by secondary source, gasoline and diesel exhausts, as well as industrial source. EP2 was dominated by secondary source from regional transport contributing approximately 50%. Short-range transport from Baoding (9.1%) and Langfang (5.8%) in Hebei Province was the largest external contributor, and long-range transport contributed 20% of the PM_2.5 concentration. This study suggests that combining receptor model-based source apportionment with air quality model has practical significance for understanding the causes of haze episodes, setting city-specific emission reduction measures and improving air quality in the Beijing-Tianjin-Hebei (BTH) region.

Environmental and Air Pollution Factors Affecting Allergic Eye Disease in Children and Adolescents in India

The aim of this study was to describe the correlation between the meteorological and air pollution parameters with the temporal pattern of presentation of recent onset allergic eye disease (AED). This cross-sectional hospital-based study included new patients (≤21 years of age) presenting between January 2016 and August 2018 from the district of Hyderabad with a clinical diagnosis of AED and an acute exacerbation of recent onset of symptoms of less than 3 months duration. Correlation analysis was performed with the local environmental rainfall, temperature, humidity, windspeed, and air pollution. Of the 25,354 new patients hailing from the district of Hyderabad, 2494 (9.84%) patients were diagnosed with AED, of which 1062 (4.19%) patients had recent onset of symptoms. The mean monthly prevalence in this cohort was 4.13%, and the month of May (6.09%) showed the highest levels. The environmental parameters of humidity (r² = 0.83/p = < 0.0001) and rainfall (r² = 0.41/p = 0.0232) showed significant negative correlation, while temperature (r² = 0.43/p = 0.0206) and ground-level ozone (r² = 0.41/p = 0.0005) showed significant positive correlation with the temporal pattern of AED in the population. An increase in rainfall and humidity was associated with a lower prevalence, and an increase of temperature and ground-level ozone was associated with a higher prevalence of AED cases during the year among children and adolescents.

Sources, environmental levels, and health risks of PM2.5-bound polycyclic aromatic hydrocarbons in energy-producing cities in northern China

We collected 170 samples of airborne fine particulate matter from five coal-producing cities and one oil-producing city in northern China during both heating and non-heating periods to quantify the concentrations of 12 polycyclic aromatic hydrocarbons, estimate their bioaccessible fraction, and calculate the incremental lifetime cancer risk (ILCR) of this fraction. The major sources of the particulate matter were analyzed using the chemical mass balance model. We found that the main emission sources were coal combustion during the heating period and open sources during the non-heating period. The ILCR was initially calculated as 2.65 × 10^-9 for coal-producing cities and 4.60 × 10^-9 for the oil-producing city during the heating period and 1.17 × 10^-8 and 3.34 × 10^-8, respectively, during the non-heating period. When only the bioaccessible fraction was used, the ILCR in coal-producing cities and the oil-producing city decreased by 87.2% and 82.1%, respectively, for the heating period and by 89.0% and 80.1%, respectively, for the non-heating period. The findings suggest that bioaccessibility should be considered when assessing the carcinogenic risk of polycyclic aromatic hydrocarbons. This study provides insights into the contribution of major emission sources to air pollution related to the long-term exploitation, transportation, and use of coal and oil.

The Impact of Particulate Matter (PM2.5) on Human Retinal Development in hESC-Derived Retinal Organoids

Increasing evidence demonstrated that PM2.5 could cross the placenta and fetal blood-brain barrier, causing neurotoxicity of embryonic development. The retina, an embryologic extension of the central nervous system, is extremely sensitive and vulnerable to environmental insults. The adverse effects of PM2.5 exposure on the retina during embryonic neurodevelopment are still largely unknown. Our goal was to investigate the effect of PM2.5 on human retinal development, which was recapitulated by human embryonic stem cell (hESC)-derived retinal organoids (hEROs). In the present study, using the hEROs as the model, the influences and the mechanisms of PM2.5 on the developing retina were analyzed. It demonstrated that the formation rate of the hERO-derived neural retina (NR) was affected by PM2.5 in a concentration dosage-dependent manner. The areas of hEROs and the thickness of hERO-NRs were significantly reduced after PM2.5 exposure at the concentration of 25, 50, and 100 μg/ml, which was due to the decrease of proliferation and the increase of apoptosis. Although we did not spot significant effects on retinal differentiation, PM2.5 exposure did lead to hERO-NR cell disarranging and structural disorder, especially retinal ganglion cell dislocation. Transcriptome analysis showed that PM2.5 treatment was significantly associated with the mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/AKT pathways and reduced the level of the fibroblast growth factors (FGFs), particularly FGF8 and FGF10. These results provided evidence that PM2.5 exposure potentially inhibited proliferation and increased apoptosis at the early development stage of the human NR, probably through the MAPK and PI3K/Akt pathway. Our study suggested that exposure to PM2.5 suppressed cell proliferation and promoted cell apoptosis, thereby contributing to abnormal human retinal development.

Assessing the relationship between surface levels of PM2.5 and PM10 particulate matter impact on COVID-19 in Milan, Italy

The novel coronavirus disease (COVID-19) is a highly pathogenic, transmittable and invasive pneumococcal disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which emerged in December 2019 and January 2020 in Wuhan city, Hubei province, China and fast spread later on the middle of February 2020 in the Northern part of Italy and Europe. This study investigates the correlation between the degree of accelerated diffusion and lethality of COVID-19 and the surface air pollution in Milan metropolitan area, Lombardy region, Italy. Daily average concentrations of inhalable particulate matter (PM) in two size fractions PM2.5, PM10 and maxima PM10 ground level atmospheric pollutants together air quality and climate variables (daily average temperature, relative humidity, wind speed, atmospheric pressure field and Planetary Boundary Layer-PBL height) collected during 1 January-30 April 2020 were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces, or direct human-to-human personal contacts, it seems that high levels of urban air pollution, weather and specific climate conditions have a significant impact on the increased rates of confirmed COVID-19 Total number, Daily New and Total Deaths cases, possible attributed not only to indoor but also to outdoor airborne bioaerosols distribution. Our analysis demonstrates the strong influence of daily averaged ground levels of particulate matter concentrations, positively associated with average surface air temperature and inversely related to air relative humidity on COVID-19 cases outbreak in Milan. Being a novel pandemic coronavirus (SARS-CoV-2) version, COVID-19 might be ongoing during summer conditions associated with higher temperatures and low humidity levels. Presently is not clear if this protein "spike" of the new coronavirus COVID-19 is involved through attachment mechanisms on indoor or outdoor airborne aerosols in the infectious agent transmission from a reservoir to a susceptible host in some agglomerated urban areas like Milan is.

Assessing the relationship between surface levels of PM2.5 and PM10 particulate matter impact on COVID-19 in Milan, Italy

The novel coronavirus disease (COVID-19) is a highly pathogenic, transmittable and invasive pneumococcal disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which emerged in December 2019 and January 2020 in Wuhan city, Hubei province, China and fast spread later on the middle of February 2020 in the Northern part of Italy and Europe. This study investigates the correlation between the degree of accelerated diffusion and lethality of COVID-19 and the surface air pollution in Milan metropolitan area, Lombardy region, Italy. Daily average concentrations of inhalable particulate matter (PM) in two size fractions PM2.5, PM10 and maxima PM10 ground level atmospheric pollutants together air quality and climate variables (daily average temperature, relative humidity, wind speed, atmospheric pressure field and Planetary Boundary Layer-PBL height) collected during 1 January-30 April 2020 were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces, or direct human-to-human personal contacts, it seems that high levels of urban air pollution, weather and specific climate conditions have a significant impact on the increased rates of confirmed COVID-19 Total number, Daily New and Total Deaths cases, possible attributed not only to indoor but also to outdoor airborne bioaerosols distribution. Our analysis demonstrates the strong influence of daily averaged ground levels of particulate matter concentrations, positively associated with average surface air temperature and inversely related to air relative humidity on COVID-19 cases outbreak in Milan. Being a novel pandemic coronavirus (SARS-CoV-2) version, COVID-19 might be ongoing during summer conditions associated with higher temperatures and low humidity levels. Presently is not clear if this protein "spike" of the new coronavirus COVID-19 is involved through attachment mechanisms on indoor or outdoor airborne aerosols in the infectious agent transmission from a reservoir to a susceptible host in some agglomerated urban areas like Milan is.

Atmospheric fine particulate matter and epithelial mesenchymal transition in pulmonary cells: state of the art and critical review of the in vitro studies

Exposure to fine particulate matter (PM_2.5) has been associated with several diseases including asthma, chronic obstructive pulmonary disease (COPD) and lung cancer. Mechanisms such as oxidative stress and inflammation are well-documented and are considered as the starting point of some of the pathological responses. However, a number of studies also focused on epithelial-mesenchymal transition (EMT), which is a biological process involved in fibrotic diseases and cancer progression notably via metastasis induction. Up until now, EMT was widely reported in vivo and in vitro in various cell types but investigations dealing with in vitro studies of PM_2.5 induced EMT in pulmonary cells are limited. Further, few investigations combined the necessary endpoints for validation of the EMT state in cells: such as expression of several surface, cytoskeleton or extracellular matrix biomarkers and activation of transcription markers and epigenetic factors. Studies explored various cell types, cultured under differing conditions and exposed for various durations to different doses. Such unharmonized protocols (1) might introduce bias, (2) make difficult comparison of results and (3) preclude reaching a definitive conclusion regarding the ability of airborne PM_2.5 to induce EMT in pulmonary cells. Some questions remain, in particular the specific PM_2.5 components responsible for EMT triggering. The aim of this review is to examine the available PM_2.5 induced EMT in vitro studies on pulmonary cells with special emphasis on the critical parameters considered to carry out future research in this field. This clarification appears necessary for production of reliable and comparable results.

Fine Particulate Matter (PM2.5) upregulates expression of Inflammasome NLRP1 via ROS/NF-κB signaling in HaCaT Cells

Skin, as the major organ of a human body, is constantly exposed to PM2.5 stimulation, which may exert specific toxic influences on the physiology of skin. This study aims to investigate the effect of PM2.5 on the formation of inflammasomes in skin cells and to explore the potential mechanism linking PM2.5 and skin inflammation. Changes in mRNA and protein levels of inflammasome-related genes were detected by real-time PCR and western blot in human immortalized epidermal cells (HaCaT) treated with PM2.5 at multiple concentrations for 24 hours. The expression of NLRP1 was increased significantly both in mRNA and protein levels after PM2.5 exposure while the elevated secretory protein level of IL-1β in cell culture was detected by ELISA, which is one of the main downstream factors of NLRP1. In addition, the upregulation of NLRP1 and IL-1β could be reversed by NF-κB inhibitor indicating that PM2.5 may promote NLRP1 expression through activating NF-κB pathway. Furthermore, high ROS level was also found in cells treated with PM2.5 and inhibition of ROS could also reverse NK-κB production stimulated by PM2.5 that means ROS is involved in this skin inflammation process.

Determination of oxoanions and water-soluble species of arsenic, selenium, antimony, vanadium, and chromium eluted in water from airborne fine particles (PM2.5): effect of acid and transition metal content of particles on heavy metal elution

Heavy metals in particulate matter (PM) are of great concern, and their effects on the environment and human health depend on their solubilities and species present. In this study, the solubility of As, Se, Sb, V and Cr and their species eluted in water was investigated. As, Se, Sb, and V were present mostly in fine particles, and they were predominantly water-soluble in fine particles (<2.5 μm, PM_2.5) but insoluble in coarse particles (>2.5 μm). Solubility of Cr was poor even in fine particles. It was found that for fine particles, solubilities of the heavy metals were related to the nitrate and sulfate contents. This suggests that the higher the acidity of the particles, the higher the solubility of the heavy metals. Oxoanions of the five kinds of heavy metals in water extracts of fine particles were determined by inductively coupled plasma mass spectrometry preceded by ion chromatography. The results suggested the presence of atmospheric oxidation during the aerosol transportation. Also, the As(iii)/As(v) (arsenite/arsenate) ratios for the fine particle extracts were related to the transition metal concentrations, which indicated that Fe, Cu, etc. in fine particles affected the As redox equilibrium. It was suggested that the heavy metals exist as complexes with iron hydroxide and dissolved organic matter in addition to the free oxoanions. These investigations were performed for PM samples collected in winter and summer in Kumamoto, west Japan, where the site is strongly exposed to westerly winds from continental East Asia. The obtained results improve our understanding of the behavior of the heavy metals in airborne PM after depositing on a wet environment and biota.