Adverse health effects of outdoor air pollutants

A hybrid model for enhanced forecasting of PM2.5 spatiotemporal concentrations with high resolution and accuracy

Forecasting concentrations of PM2.5 is important due to its known impacts on public health and environment. However, PM2.5 concentrations can vary significantly over short distances and time, which can be influenced by local emissions and short-term weather patterns. This spatiotemporal variability makes accurate PM2.5 forecasting an inherently complex and challenging task. This study presented novel methodologies for short-term PM2.5 concentration forecast by combining the atmospheric chemistry transport model Community Multiscale Air Quality Modeling System (CMAQ) with data-driven machine learning methods, namely long short-term memory (LSTM) and random forest (RF) models. The combined model system forecast PM2.5 with 1 h, 1km × 1 km spatiotemporal resolution. The LSTM system forecast time-dependent PM2.5 concentrations at observation sites with a maximum root mean square error (RMSE) of 3.66 μg/m3 for 1-hr forecast and 23.75 μg/m3 for 72-hr forecast, leveraging results obtained from the atmospheric transport model with RMSE of 45.81 μg/m3. Wavelet transform in the LSTM system allowed learning and prediction of PM2.5 concentrations at different frequencies, capturing temporal variability of PM2.5 at various time scales. The RF model predicted distributions of PM2.5 concentrations by learning LSTM results and integrating crucial features such as CMAQ results, meteorological and topographical information. The feature significance of CMAQ results was the highest among the input features in RF models. Overall, the hybrid model could help with managing and mitigating the adverse effects of air pollution by enabling informed decision-making at the individual, community and policy levels.

Impacts of daily household activities on indoor particulate and NO2 concentrations; a case study from oxford UK

This study explores indoor air pollutant (PM1, PM2.5 and NO2) concentrations over a 15-week period during the COVID-19 pandemic in a typical suburban household in Oxford, UK. A multi-room intensive monitoring study was conducted in a single dwelling using 10 air quality sensors measuring real-time pollutant concentrations at 10 second intervals to assess temporal and spatial variability in PM1, PM2.5 and NO2 concentrations, identify pollution-prone areas, and investigate the impact of residents' activities on indoor air quality. Significant spatial variations in PM concentrations were observed within the study dwelling, with highest hourly concentrations (769.0 & 300.9 μg m-3 for PM2.5, and PM1, respectively) observed in the upstairs study room, which had poor ventilation. Cooking activities were identified as a major contributor to indoor particulate pollution, with peak concentrations aligning with cooking events. Indoor NO2 levels were typically higher than outdoor levels, particularly in the kitchen where a gas-cooking appliance was used. There was no significant association observed between outdoor and indoor PM concentrations; however, a clear correlation was evident between kitchen PM emissions and indoor levels. Similarly, outdoor NO2 had a limited influence on indoor air quality compared to kitchen activities. Indoor sources were found to dominate for both PM and NO2, with higher Indoor/Outdoor (I/O) ratios observed in the upstairs bedroom and the kitchen. Overall, our findings highlight the contribution of indoor air pollutant sources and domestic activities to indoor air pollution exposure, notably during the COVID-19 pandemic when people were typically spending more time in domestic settings. Our novel findings, which suggest high levels of pollutant concentrations in upstairs (first floor) rooms, underscore the necessity for targeted interventions. These interventions include the implementation of source control measures, effective ventilation strategies and occupant education for behaviour change, all aimed at improving indoor air quality and promoting healthier living environments.

Bayesian predictive modeling for gas purification using breakthrough curves

This study proposes a predictive model for assessing adsorber performance in gas purification processes, specifically targeting the removal of chemical warfare agents (CWAs) using breakthrough curve analysis. Conventional parameter estimation methods, such as Brunauer-Emmett-Teller analysis, encounter challenges due to the limited availability of kinetic and equilibrium data for CWAs. To overcome these challenges, we implement a Bayesian parametric inference method, facilitating direct parameter estimation from breakthrough curves. The model's efficacy is confirmed by applying it to H2S purification in a fixed-bed setup, where predicted breakthrough curves aligned closely with previous experimental and numerical studies. Furthermore, the model is applied to sarin with ASZM-TEDA carbon, estimating key parameters that could not be assessed through conventional experimental techniques. The reconstructed breakthrough curves closely match actual measurements, highlighting the model's accuracy and robustness. This study not only enhances filter performance prediction for CWAs but also offers a streamlined approach for evaluating gas purification technologies under limited experimental data conditions.

Assessment of spatial air quality on the East Coast of Peninsular Malaysia utilizing environmetric techniques

The presence of harmful substances in the atmosphere poses significant risks to the environment and public health. These pollutants can come from natural sources like dust and wildfires, or from human activities such as industrial, transportation, and agricultural practices. The objective of this study was to assess air quality on the East Coast of Peninsular Malaysia by analyzing historical data from the Department of Environment, Malaysia. Daily measurements of PM10, O3, SO2, NO2, and CO were collected from eight monitoring stations over 11 years (2011-2021) and analyzed using environmetric techniques. Hierarchical agglomerative cluster analysis (HACA) classified two stations as belonging to the high pollution cluster (HPC), three stations as part of the moderate pollution cluster (MPC), and three stations as the low pollution cluster (LPC). Discriminant analysis revealed a correct assignment rate of 90.50%, indicating that all five parameters were able to differentiate pollution levels with high significance (p < 0.0001). Principal component analysis (PCA) was conducted to validate the pattern of air quality variables in relation to the identified clusters (HPC, MPC, and LPC). The results showed that two verifactors (VFs) were extracted in HPC and LPC, while three VFs were identified in MPC. The cumulative variance explained by the PCA for HPC, MPC, and LPC was 69.43%, 82.32%, and 62.16%, respectively. Finally, an artificial neural network (ANN) was used to forecast the air pollutant index (API) levels, using the R2 and RMSE performance metrics. The PCA-MLP Model A yielded an R2 value of 0.8470 and an RMSE of 6.6470, while PCA-MLP Model B achieved an R2 value of 0.8591 and an RMSE of 6.3000, both indicating a significant and strong correlation.

The Challenges and Opportunities for TiO2 Nanostructures in Gas Sensing

Chemiresistive gas sensors based on metal oxides have been widely applied in industrial monitoring, medical diagnosis, environmental pollutant detection, and food safety. To further enhance the gas sensing performance, researchers have worked to modify the structure and function of the material so that it can adapt to different gas types and environmental conditions. Among the numerous gas-sensitive materials, n-type TiO2 semiconductors are a focus of attention for their high stability, excellent biosafety, controllable carrier concentration, and low manufacturing cost. This Perspective first introduces the sensing mechanism of TiO2 nanostructures and composite TiO2-based nanomaterials and then analyzes the relationship between their gas-sensitive properties and their structure and composition, focusing also on technical issues such as doping, heterojunctions, and functional applications. The applications and challenges of TiO2-based nanostructured gas sensors in food safety, medical diagnosis, environmental detection, and other fields are also summarized in detail. Finally, in the context of their practical application challenges, future development technologies and new sensing concepts are explored, providing new ideas and directions for the development of multifunctional intelligent gas sensors in various application fields.

Effects of environmental exposure to iron powder on healthy and elastase-exposed mice

Prolonged exposure to iron powder and other mineral dusts can threaten the health of individuals, especially those with COPD. The goal of this study was to determine how environmental exposure to metal dust from two different mining centers in Brazil affects lung mechanics, inflammation, remodeling and oxidative stress responses in healthy and elastase-exposed mice. This study divided 72 male C57Bl/6 mice into two groups, the summer group and the winter group. These groups were further divided into six groups: control, nonexposed (SAL); nonexposed, given elastase (ELA); exposed to metal powder at a mining company (SAL-L1 and ELA-L1); and exposed to a location three miles away from the mining company (SAL-L2 and ELA-L2) for four weeks. On the 29th day of the protocol, the researchers assessed lung mechanics, bronchoalveolar lavage fluid (BALF), inflammation, remodeling, oxidative stress, macrophage iron and alveolar wall alterations (mean linear intercept-Lm). The Lm was increased in the ELA, ELA-L1 and ELA-L2 groups compared to the SAL group (p < 0.05). There was an increase in the total number of cells and macrophages in the ELA-L1 and ELA-L2 groups compared to the other groups (p < 0.05). Compared to the ELA and SAL groups, the exposed groups (ELA-L1, ELA-L2, SAL-L1, and SAL-L2) exhibited increased expression of IL-1β, IL-6, IL-10, IL-17, TNF-α, neutrophil elastase, TIMP-1, MMP-9, MMP-12, TGF-β, collagen fibers, MUC5AC, iNOS, Gp91phox, NFkB and iron positive macrophages (p < 0.05). Although we did not find differences in lung mechanics across all groups, there were low to moderate correlations between inflammation remodeling, oxidative stress and NFkB with elastance, resistance of lung tissue and iron positive macrophages (p < 0.05). Environmental exposure to iron, confirmed by evaluation of iron in alveolar macrophages and in air, exacerbated inflammation, initiated remodeling, and induced oxidative stress responses in exposed mice with and without emphysema. Activation of the iNOS, Gp91phox and NFkB pathways play a role in these changes.

The association between ambient air pollution exposure and connective tissue sarcoma risk: a nested case-control study using a nationwide population-based database

A nationwide population-based database was utilized in a nested case-control study to explore the association between ambient air pollution exposure and the likelihood of developing connective tissue sarcoma. The study examined 280 cases of connective tissue sarcoma diagnosed between 2000 and 2012. A random sample of 1120 control subjects was selected from a subpopulation of claim records without a connective tissue sarcoma diagnosis in a 1:4 ratio. The control subjects were selected based on similar characteristics as the connective tissue sarcoma patients, including gender, birth year, and the year of diagnosis of the case group with medical records. Risk factors for connective tissue sarcoma were collected for analysis. Our data on exposure to air pollutants was collected from Taiwan's Air Quality Monitoring Network, which has been gathering air quality data from a growing network of sampling stations (now 76) throughout the country since 1997. It was discovered that the risk of connective tissue sarcoma was significantly increased by the Charlson comorbidity index (CCI), elevated levels of specific air pollution indices (e.g., total hydrocarbons (THC), fine particulate matter (PM2.5), and O3_8 (the annual mean of the daily maximum 8-h average concentration of O3), the High Pollutant Standards Index (hPSI) (the percentage of days in a given year in Taiwan where the PSI exceeds 100), and an insurable monthly wage over US$1100. Further investigation is needed to explore the involvement of these air pollutants in the formation of connective tissue sarcoma.

Understanding lifetime and dispersion of cough-emitted droplets in air

To understand the exact transmission routes of SARS-CoV-2 and to explore effects of time, space and indoor environment on the dynamics of droplets and aerosols, rigorous testing and observation must be conducted. In the current work, the spatial and temporal dispersions of aerosol droplets from a simulated cough were comprehensively examined over a long duration (70 min). An artificial cough generator was constructed to generate reliably repeatable respiratory ejecta. The measurements were performed at different locations in front (along the axial direction and off-axis) and behind the source in a sealed experimental enclosure. Aerosols of 0.3-10 µm (around 20% of the maximum nuclei count) were shown to persist for a very long time in a still environment, and this has a substantial implication for airborne disease transmission. The experiments demonstrated that a ventilation system could reduce the total aerosol volume and the droplet lifetime significantly. To explain the experimental observations in more detail and to understand the droplet in-air behaviour at various ambient temperatures and relative humidity, numerical simulations were performed using the Eulerian-Lagrangian approach. The simulations show that many of the small droplets remain suspended in the air over time instead of falling to the ground.

The effect of long-term exposure to toxic air pollutants on the increased risk of malignant brain tumors

Toxic air pollutants are one of the most agent that have many acute, chronic and non-communicable diseases (NCDs) on human health under long or short-term exposure has been raised from the past to the present. The aim of this study was investigation effect of long-term exposure to toxic air pollutants on the increased risk of malignant brain tumors. Databases used to for searched were the PubMed, Web of Science, Springer and Science Direct (Scopus) and Google Scholar. 71 papers based on abstract and article text filtered. In the end after sieve we selected 7 papers. Identify all relevant studies published 1970-2022. The literature showed that exposure to toxic air pollutants and their respiration can cause disorders in different parts of the brain by transmission through the circulatory system and other mechanisms. Various unpleasant abnormalities are caused by the inhalation of toxic air pollutants in the human body that some of the most common of them include chronic lung disease, coronary heart disease and heart attacks, strokes and brain diseases (Parkinson's, Alzheimer's and multiple Sclerosis), cancers (liver, blood, prostate and brain) and eventually death. According to the finding brain health and proper functioning can be easily disrupted by various genetic or external factors such as air pollution, causing a wide range of abnormalities in the brain and malignant brain tumors. The results of this study showed that reducing the concentration of toxic pollutants in the air, that exposure to them play an increasing role in the development of brain diseases can slow down the process of abnormalities in the brain and will have significant impacts on reducing the number of people affected by them.

The effect of toxic air pollutants on fertility men and women, fetus and birth rate

Human health is affected by various factors such as air pollutants. Exposure to toxic air pollutants is impaired fertility in men and women. The purpose of this review study was investigation of the effect of toxic air pollutants on fertility and birth rate. Databases used to for searched were the PubMed, Web of Science, Springer and Science Direct (Scopus) and Google Scholar. Identify all relevant studies published 1999-2022. In this study, according to databases five hundred articles were retrieved. 33 studies were screened after review and 19 full-text articles entered into the analysis process. Finally, 11 articles were selected in this study. The literature signs a notable health effects from toxic air pollutants and increase risk of infertility in men and women and having a variety of reproductive system cancers such as prostate, bladder, ovary, kidney and uterus. According to the finding toxic air pollutants can increase the risk infertility in men and women, incidence of cancers of reproductive system and decrease the birth rate. Activities that play an important role in reducing the health effects of toxic air pollutants such as infertility in men and women and reducing the population rate of communities are improving the quality of fuel used in the home, car, industries, changing production processes in large industries, installing catalysts to reduce emissions in cars, use more public transportation, plant trees and increase green space per capita, increase public awareness about various effects of toxic air pollutants and protective measures.

Using energy expenditure to estimate the minute ventilation and inhaled load of air pollutants: a pilot survey in young Chinese adults

Existing equations to estimate ventilation (VE) may not represent the Chinese population. The objective is to develop regression equations to predict the basal metabolic rate (BMR) for ventilation estimation. 80 participants underwent the incremental tests on a bicycle ergometer, wearing a fitted facial mask with an airflow sensor connected to the cardiopulmonary gas analyzer, where the energy expenditure, metabolic factors and VE were monitored simultaneously. Linear regression models were established between BMR and body weight, which were used to estimate energy expenditure and VE. Extrapolation of the regression model was evaluated by the five-fold cross-validation. And we also assessed the inhaled load of air pollutants in subgroups at the same exposure levels. Regression models for males and females were BMR (kJ/d) = 107.58 × weight (kg)-172.61 and BMR (kJ/d) = 105.61 × weight (kg)-26.94, respectively. The model showed good fitness between the measured and predicted VE. Differences between the measured and predicted VE of this model are smaller than that of other models. There were significant differences in inhaled load participants in the same exposure concentrations. The regression model showed that weight and BMR are highly correlated and can be used to estimate individual VE.

Nanoremediation strategies to address environmental problems

A rapid rise in population, extensive anthropogenic activities including agricultural practices, up-scaled industrialization, massive deforestation, etc. are the leading causes of environmental degradation. Such uncontrolled and unabated practices have affected the quality of environment (water, soil, and air) synergistically by accumulating huge quantities of organic and inorganic pollutants in it. Environmental contamination is posing a threat to the existing life on the Earth, therefore, demands the development of sustainable environmental remediation approaches. The conventional physiochemical remediation approaches are laborious, expensive, and time-consuming. In this regard, nanoremediation has emerged as an innovative, rapid, economical, sustainable, and reliable approach to remediate various environmental pollutants and minimize or attenuate the risks associated with them. Owing to their unique properties such as high surface area to volume ratio, enhanced reactivity, tunable physical parameters, versatility, etc. nanoscale objects have gained attention in environmental clean-up practices. The current review highlights the role of nanoscale objects in the remediation of environmental contaminants to minimize their impact on human, plant, and animal health; and air, water, and soil quality. The aim of the review is to provide information about the applications of nanoscale objects in dye degradation, wastewater management, heavy metal and crude oil remediation, and mitigation of gaseous pollutants including greenhouse gases.

Uncovering the Critical Factors that Enable Extractive Desulfurization of Fuels in Ionic Liquids and Deep Eutectic Solvents from Simulations

Environmental regulatory agencies have implemented stringent restrictions on the permissible levels of sulfur compounds in fuel to reduce harmful emissions and improve air quality. Problematically, traditional desulfurization methods have shown low effectiveness in the removal of refractory sulfur compounds, e.g., thiophene (TS), dibenzothiophene (DBT), and 4-methyldibenzothiophene (MDBT). In this work, molecular dynamics (MD) simulations and free energy perturbation (FEP) have been applied to investigate the use of ionic liquids (ILs) and deep eutectic solvents (DESs) as efficient TS/DBT/MDBT extractants. For the IL simulations, the selected cation was 1-butyl-3-methylimidazolium [BMIM] and the anions included chloride [Cl], thiocyanate [SCN], tetrafluoroborate [BF₄], hexafluorophosphate [PF₆], and bis(trifluoromethylsulfonyl)amide [NTf₂]. The DESs were composed of choline chloride with ethylene glycol (CCEtg) or with glycerol (CCGly). Calculation of excess chemical potentials predicted the ILs to be more promising extractants with energies lower by 1-3 kcal/mol compared to DESs. Increasing IL anion size was positively correlated to enhanced solvation of S-compounds, which was influenced by energetically dominant solute-anion interactions and favorable solute-[BMIM] π-π stacking. For the DESs, the solvent components offered a range of synergistic, yet comparatively weaker, electrostatic interactions that included hydrogen bonding and cation-π interactions. An in-depth analysis of the structure of IL and DES systems is presented, along with a discussion of the critical factors behind experimental trends of S-compound extraction efficiency.

Association between ambient air pollutant interaction with kidney function in a large Taiwanese population study

The associations and interactions between kidney function and other air pollutants remain poorly defined. Therefore, the aim of this study was to evaluate associations among air pollutants, including particulate matter (PM) with a diameter ≤ 2.5 μm (PM_2.5), PM₁₀ (PM with a diameter ≤ 10 μm), carbon monoxide (CO), nitrogen oxide (NO), nitrogen oxides (NO_x), sulfur dioxide (SO₂), and ozone (O₃) with kidney function, and explore interactions among these air pollutants on kidney function. We used the Taiwan Air Quality Monitoring and Taiwan Biobank databases to derive data on community-dwelling individuals in Taiwan and daily air pollution levels, respectively. We enrolled 26,032 participants. Multivariable analysis showed that high levels of PM_2.5, PM₁₀, O₃ (all p < 0.001), and SO₂ (p = 0.001) and low levels of CO, NO (both p < 0.001), and NO_x (p = 0.047) were significantly correlated with low estimated glomerular filtration rate (eGFR). With regard to negative effects, the interactions between PM_2.5 and PM₁₀ (p < 0.001), PM_2.5 and PM₁₀ (p < 0.001), PM_2.5 and SO₂, PM₁₀ and O₃ (both p = 0.025), PM₁₀ and SO₂ (p = 0.001), and O₃ and SO₂ (p < 0.001) on eGFR were significantly negatively. High PM₁₀, PM_2.5, O₃, and SO₂ were associated with a low eGFR, whereas high CO, NO, and NO_x were associated with a high eGFR. Furthermore, negative interactions between PM_2.5 and PM₁₀, O₃ and SO₂, PM₁₀ and O₃, PM_2.5 and SO₂, and PM₁₀ and SO₂ on eGFR were observed. The findings of this study have important implications for public health and environmental policy. Specifically, the results of this study may be useful in individuals and organizations to take action to reduce air pollution and promote public health.

Impact of air pollution on human health in different geographical locations of Nepal

According to a recent survey, Nepal's urban air quality has been classified as one of the worst in the globe. A large portion of the country's population is subjected to health risks caused by air pollution. As Nepal has a wide variation in altitude coupled with socio-cultural and biological diversities, it is important to understand the different health hazards in the different geographical regions - Terai, Hills and Mountains. Constantly increasing physical infrastructures (such as transport vehicles, open burning of plastics and other fuels) are the main reasons for the escalating air pollution in the country. This study aims to critically review the current air pollution status in different geographical locations along with its impacts on public health in the country. It has been revealed that irrespective of geographic location, the air pollutants interfere with different human physiological systems related to respiration as well as cardiovascular, ophthalmic, and gastrointestinal functioning. Further, the research findings highlighting the influence of prolonged exposure of the population to the air pollution leading to the significant number of deaths have been presented. A notable rise in the number of hospitalized patients suffering from illnesses related to above mentioned pollution borne cases has been reported.

Association between air pollutants with calcaneus ultrasound T-score change in a large Taiwanese population follow-up study

Exposure to ambient air pollution has been associated with increased rates of mortality and morbidity and a shorter life expectancy. Few studies have evaluated the associations between air pollution and change in calcaneus ultrasound T-score (∆T-score). Therefore, in this longitudinal study, we explored these associations in a large group of Taiwanese participants. We used data from the Taiwan Biobank database and Taiwan Air Quality Monitoring Database, which contains detailed daily data on air pollution. We identified 27,033 participants in the Taiwan Biobank database who had both baseline and follow-up data. The median follow-up period was 4 years. The studied ambient air pollutants included particulates of 2.5 μm or less (PM_2.5), particulates of 10 μm or less (PM₁₀), ozone (O₃), carbon monoxide (CO), sulfur dioxide (SO₂), nitric oxide (NO), nitrogen dioxide (NO₂), and nitrogen oxide (NO_x). Multivariable analysis showed that PM_2.5 (β, -0.003; 95% confidence interval (CI), -0.004 to -0.001; p < 0.001), PM₁₀ (β, -0.005; 95% CI, -0.006 to -0.004, p < 0.001), O₃ (β, -0.008; 95% CI, -0.011 to -0.004; p < 0.001), and SO₂ (β, -0.036; 95% CI, -0.052 to -0.020; p < 0.001) were negatively associated with ∆T-score, and that CO (β, 0.344; 95% CI, 0.254, 0.433; p < 0.001), NO (β, 0.011; 95% CI, 0.008 to 0.015; p < 0.001), NO₂ (β, 0.011; 95% CI, 0.008 to 0.014; p < 0.001), and NO_x (β, 0.007; 95% CI, 0.005 to 0.009; p < 0.001) were positively significantly associated with ∆T-score. Furthermore, PM_2.5 and SO₂ (β, -0.014; 95% CI, -0.016 to -0.013; p < 0.001) and PM₁₀ and SO₂ (β, -0.008; 95% CI, -0.009 to -0.007; p < 0.001) had synergistic negative effects on ∆T-score. In conclusion, we found that high PM_2.5, PM₁₀, O₃, and SO₂ were associated with a rapid decline in T-score, whereas high CO, NO, NO₂, and NO_x were associated with a slow decline in T-score. Furthermore, PM_2.5 and SO₂ and PM₁₀ and SO₂ had synergistic negative effects on ∆T-score, causing an acceleration in T-score decline. These findings may be helpful when developing policies on air pollution regulation.

Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements

PM₁₀-associated potential toxic elements (PTEs) can enter the respiratory system and cause health problems. In the current study, the health risk indices caused by PM₁₀ inhalation by adults, children, and infants in 158 European cities between 2013 and 2019 were studied to determine if Europeans were adversely affected by carcinogenic and non-carcinogenic factors or not. The Mann-Kendall trend test examined PM₁₀'s increasing or decreasing trend. Random Forest analysis was also used to analyse meteorological factors affecting PM₁₀ in Europe. Hazard quotient and cancer risk were estimated using PM₁₀-associated PTEs. Our results showed a decline in continental PM₁₀ concentrations. The correlation between PM₁₀ concentrations and temperature (-0.40), PBLH (-0.39), and precipitation were statistically strong (-0.21). The estimated Pearson correlation coefficients showed a statistically strong positive correlation between As & Pb, As & Cd, and Cd & Pb during 2013-2019, indicating a similar origin. PTEs with hazard quotients below one, regardless of subpopulation type, posed no noncancerous risk to Europeans. The hazard quotient values positively correlated with time, possibly due to elevated PTE levels. In our study on carcinogen pollution in Europe between 2013 and 2019, we found unacceptable levels of As, Cd, Ni, and Pb among adults, children, and infants. Carcinogenic risk rates were highest for children, followed by infants, adult women, and adult men. Therefore, besides monitoring and mitigating PM concentrations, effective control of PM sources is also needed.

The Effects of Yoga Practice on Lung Function and sIL-2R Biomarkers in Individuals Working and Living in the Lonavala Industrial Area: A Randomized Controlled Trial

Context

Pollution-related health hazards are very common among people living and/or working in industrial areas, particularly near industries and metro cities. These air pollutants contribute to allergens, increase inflammation, and affect lung function.

Aim

The present study aimed to examine the effect of yoga training on lung functions and inflammation in terms of soluble interleukin-2 receptor (sIL-2R) in people working and living in a polluted area.

Settings and Design

This is a randomized controlled interventional pilot study.

Methods and Materials

Forty-eight male volunteers from the industrial area, aged 20-50 years, were randomly assigned to the experimental group and the control group. Each group comprises 24 study participants. Lung function and sIL-2R were studied at the baseline and post-yoga intervention period of 16 weeks.

Statistical Analysis Used

Study data were analyzed using descriptive methods, a one-tailed t-test, a paired t-test, and an independent t-test.

Result

Study results showed directional and significant improvements in forced vital capacity, forced expiratory volume in the first second, and peak expiratory flow rate compared to the control group participants. The results pertaining to sIL-2R showed a directional and significant decrease in the experimental group compared to the control group.

Conclusion

The present study showed that yoga helps to promote better health, improve lung function and reduce inflammation among people residing in polluted environments.

The influence of air pollution exposure on the short- and long-term health benefits associated with active mobility: A systematic review

Active mobility (AM), defined as walking and cycling for transportation, can improve health through increasing regular physical activity. However, these health improvements could be outweighed by harm from inhaling traffic-related air pollutants during AM participation. The interaction of AM and air pollutants on health is complex physiologically, manifesting as acute changes in health indicators that may lead to poor long-term health consequences. The aim of this study was to systematically review the current evidence of effect modification by air pollution (AP) on associations between AM and health indicators. Studies were included if they examined associations between AM and health indicators being modified by AP or, conversely, associations between AP and health indicators being modified by AM. Thirty-three studies met eligibility criteria. The main AP indicators studied were particulate matter, ultrafine particles, and nitrogen oxides. Most health indicators studied were grouped into cardiovascular and respiratory indicators. There is evidence of a reduction by AP, mainly ultrafine particles and PM_2.5, in the short-term health benefits of AM. Multiple studies suggest that long-term health benefits of AM are not negatively associated with levels of the single traffic-related pollutant NO₂. However, other studies reveal reduced long-term health benefits of AM in areas affected by high levels of pollutant mixtures. We recommend that future studies adopt consistent and rigorous study designs and include reporting of interaction testing, to advance understanding of the complex relationships between AM, AP, and health indicators.

Particulate matter concentrations and characterization in urban subway system-case study Tehran, Iran

The present work aims to evaluate the indoor and outdoor air quality in the stations of the Tehran subway system. In this study, the particulate sampling of the four Tehran subway stations was conducted in March-July 2018 during different seasons to determine indoor and outdoor PM10 and PM2.5 concentrations and elemental composition. The samples were analyzed to determine 11 elements such as Pb(Lead), Cd(Cadmium), Ni(Nickel), Co(Cobalt), Mn(Manganese), Zn(Zink), Fe(Iron), Cu(Copper), As(Arsenic), Al(Aluminum) and Cr(Chromium) qualitatively. The experimental results indicated that the average concentrations of both PM10 and PM2.5 in indoor stations (platforms) were approximately 2-5 times higher than those in the outdoors (ambient air). In addition, PM10 and PM2.5 concentrations exceeded the daily-standard values (US-EPA; PM10 = 50 µg.m-3, PM2.5 = 25 µg.m-3) in 100% indoor measurements and 84% outdoor measurements. Moreover, the average indoor PM10 and PM2.5 concentrations in weekday values were 1.4 and 1.5 times higher than those measured on weekends, which may be related to the lower frequency of trains. Further, indoor and outdoor correlation of PM10 concentrations (Pearson r = 0.6) was more than that of PM2.5 concentrations (Pearson r = 0.2), indicating the additional sources for PM2.5 in indoor stations. Additionally, the average PM2.5 / PM10 ratio was 0.52 for indoor measurements and 0.34 for outdoors, indicating that PM10 particles were the dominant particle type in both sampling areas and passengers in indoor stations exposed to higher PM2.5 concentrations than those in outdoor stations. Finally, based on elemental analysis, Fe was the most enriched element in indoor and outdoor PM10 and PM2.5 samples. The concentration of Fe ranged from 16 to 81 µg.m-3 in indoor stations and 0.6 to 2.5 µg.m-3 in outdoors. Other enriched elements were Al, Cu, Zn, and Mn, respectively.

PM2.5 exposure and incident attention-deficit/hyperactivity disorder during the prenatal and postnatal periods: A birth cohort study

Only a few studies have assessed the effects of fine particulate matter (PM_2.5) exposure during the prenatal and postnatal periods on the development of attention-deficit/hyperactivity disorder (ADHD). We investigated the association of exposure to PM_2.5 during pregnancy and early life with ADHD. This birth cohort consisted of 425,736 singleton live-term births between 2004 and 2015 in Taiwan. Daily PM_2.5 concentrations were derived from a 1-km satellite-based estimation model. A time-dependent Cox model was used to assess the effects of PM_2.5 on ADHD during the first, second, and third trimesters and from age 1-5 years after birth. The distributed lag nonlinear model was utilized to explore the dose-response relationship. Total 9,294 children were diagnosed with ADHD during the study period. The hazard ratio (HR) of ADHD was significantly associated with a 10 μg/m³ increase in PM_2.5 during the first trimester (HR = 1.26; 95% confidence interval [CI]: 1.13-1.40) and increased at PM_2.5 over 16 μg/m³. For postnatal periods, the HR of ADHD was significantly associated with increased PM_2.5 at the first to third year of life (HR ranged between 1.40 and 1.87). According to the dose-response relationship of exposure to PM_2.5 at the third year of life, the HR of ADHD was significantly associated with PM_2.5 above 16 μg/m³ and sharply increased as PM_2.5 >50 μg/m³. We did not observe a significant modification of sex on the relation between PM_2.5 and ADHD. Exposure of pregnant women to PM_2.5 above 16 μg/m³ from conception to the early life of their children may increase the risk of ADHD. The government should improve the criteria for air quality control and meet the WHO air quality guidelines to protect pregnant women and children from developing ADHD in the future.

Promoted Carbon Monoxide Sensing Performance of a Bi2Mn4O10-Based Mixed-Potential Sensor by Regulating Oxygen Vacancies

The YSZ-based mixed-potential sensor has exhibited promising application prospects for in situ carbon monoxide (CO) monitoring owing to its excellent thermal stability. However, the way to further enhance the sensitivity and selectivity of the sensor remains challenging due to the limitation of the sensing material. In the present work, we proposed a strategy of introducing moderate oxygen vacancies in the transition metal oxide sensing material to enhance CO sensing performance. More importantly, the oxygen vacancies of the sensing electrode were regulated by adjusting the volatilization of the Bi element at different sintering temperatures. Meanwhile, the stable mullite structure and variable valency of Mn were also exploited to maintain the phase structure stability and charge balance brought by the loss of Bi. The relationship between CO sensing properties and the proportion of both Mn³⁺/Mn⁴⁺ and oxygen vacancies was elucidated from XPS and EIS measurements. By contrast, the 800 °C-sintered Bi₂Mn₄O₁₀ possesses the highest oxygen vacancy content and thus exhibits preferable sensing performance including a lower detecting limit (10 ppm), swifter response/recovery processes, and enhanced CO sensitivity (-70.47 mV/decade operated at 450 °C) with satisfactory selectivity and stability, indicating a promising prospect for CO monitoring under exhaust environments.

Improving the air quality with Functionalized Carbon Nanotubes: Sensing and remediation applications in the real world

With the world developing exponentially every day, the collateral damage to air is incessant. There are many methods to purify the air but using carbon nanotubes (CNTs) as adsorbents remains one of the most efficient and reliable methods, due to their high maximum adsorption capacity which renders them extremely useful for removing pollutants from the air. The different types of CNTs, their synthesis, functionalization, purification, functioning, and advantages over conventional filters are deliberated along with diverse types of CNTs like single-walled (SWCNTs), multiwalled (MWCNTs), and others, which can be functionalized and deployed for the removal of harmful gases like oxides of nitrogen and sulphur, and ozone, and volatile organic compounds (VOCs), among others. A comprehensive description of CNTs is provided in this overview with illustrative examples from the past five years. The fabrication methods and target gases of many CNTs-based gas sensors are highlighted, in addition to the comparison of their properties, mainly sensitivity. The effect of functionalization on sensors has been discussed in detail for various composites targeting specific gases, including the future outlook of functionalized CNTs in assorted practical applications.

Traffic and Pollution Modelling for Air Quality Awareness: An Experience in the City of Zaragoza

Air pollution due to the presence of small particles and gases in the atmosphere is a major cause of health problems. In urban areas, where most of the population is concentrated, traffic is a major source of air pollutants (such as nitrogen oxides or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {NO}_x$$\end{document}NOx and carbon monoxide or CO). Therefore, for smart cities, carrying out an adequate traffic monitoring is a key issue, since it can help citizens to make better decisions and public administrations to define appropriate policies. Thus, citizens could use these data to make appropriate mobility decisions. In the same way, a city council can exploit the collected data for traffic management and for the establishment of suitable traffic policies throughout the city, such as restricting the traffic flow in certain areas. For this purpose, a suitable modelling approach that provides the estimated/predicted values of pollutants at each location is needed. In this paper, an approach followed to model traffic flow and air pollution dispersion in the city of Zaragoza (Spain) is described. Our goal is to estimate the air quality in different areas of the city, to raise awareness and help citizens to make better decisions; for this purpose, traffic data play an important role. In more detail, the proposal presented includes a traffic modelling approach to estimate and predict the amount of traffic at each road segment and hour, by combining historical measurements of real traffic of vehicles and the use of the SUMO traffic simulator on real city roadmaps, along with the application of a trajectory generation strategy that complements the functionalities of SUMO (for example, SUMO’s calibrators). Furthermore, a pollution modelling approach is also provided, to estimate the impact of traffic flows in terms of pollutants in the atmosphere: an R package called Vehicular Emissions INventories (VEIN) is used to estimate the amount of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {NO}_x$$\end{document}NOx generated by the traffic flows by taking into account the vehicular fleet composition (i.e., the types of vehicles, their size and the type of fuel they use) of the studied area. Finally, considering this estimation of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {NO}_x$$\end{document}NOx, a service capable of offering maps with the prediction of the dispersion of these atmospheric pollutants in the air has been established, which uses the Graz Lagrangian Model (GRAL) and takes into account the meteorological conditions and morphology of the city. The results obtained in the experimental evaluation of the proposal indicate a good accuracy in the modelling of traffic flows, whereas the comparison of the prediction of air pollutants with real measurements shows a general underestimation, due to some limitations of the input data considered. In any case, the results indicate that this first approach can be used for forecasting the air pollution within the city.

Ten questions concerning the paradox of minimizing airborne transmission of infectious aerosols in densely occupied spaces via sustainable ventilation and other strategies in hot and humid climates

Airborne disease transmission in indoor spaces and resulting cross-contamination has been a topic of broad concern for years - especially recently with the outbreak of COVID-19. Global recommendations on this matter consist of increasing the outdoor air supply in the aim of diluting the indoor air. Nonetheless, a paradoxical relationship has risen between increasing amount of outdoor air and its impact on increased energy consumption - especially densely occupied spaces. The paradox is more critical in hot and humid climates, where large amounts of energy are required for the conditioning of the outdoor air. Therefore, many literature studies investigated new strategies for the mitigation of cross-contamination with little-to-no additional cost of energy. These strategies mainly consist of the dilution and/or the capture and removal of contaminants at the levels of macroenvironment room air and occupant-adjacent microenvironment. On the macroenvironment level, the dilution occurs by the supply of large amounts of outdoor air in a sustainable way using passive cooling systems, and the removal of contaminants happens via filtering. Similarly, the microenvironment of the occupant can be diluted using localized ventilation techniques, and contaminants can be captured and removed by direct exhaust near the source of contamination. Thus, this work answers ten questions that explore the most prevailing technologies from the above-mentioned fronts that are used to mitigate cross-contamination in densely occupied spaces located in hot and humid climates at minimal energy consumption. The paper establishes a basis for future work and insights for new research directives for macro and microenvironment approaches.

Stacked ResNet-LSTM and CORAL model for multi-site air quality prediction

As the global economy is booming, and the industrialization and urbanization are being expedited, particulate matter 2.5 (PM2.5) turns out to be a major air pollutant jeopardizing public health. Numerous researchers are committed to employing various methods to address the problem of the nonlinear correlation between PM2.5 concentration and several factors to achieve more effective forecasting. However, a considerable space remains for the improvement of forecasting accuracy, and the problem of missing air pollution data on certain target areas also needs to be solved. Our research work is divided into two parts. First, this study presents a novel stacked ResNet-LSTM model to enhance prediction accuracy for PM2.5 concentration level forecast. As revealed from the experimental results, the proposed model outperforms other models such as boosting algorithms or general recurrent neural networks, and the advantage of feature extraction through residual network (ResNet) combined with a model stacking strategy is shown. Second, to solve the problem of insufficient air quality and meteorological data on some research areas, this study proposes the use of a correlation alignment (CORAL) method to carry out a prediction on the target area by aligning the second-order statistics between source area and target area. As indicated from the results, this model exhibits a considerable accuracy even in the absence of historical PM2.5 data in the target forecast area.

Overcoming Skin Damage from Pollution via Novel Skincare Strategies

Urban pollution is one of the main problems encountered worldwide with major impact on public health as well as the environment. Health impact of urban pollution is not limited to respiratory conditions but also encompasses major skin problems including irritation, skin ageing, and skin cancer. Toxic gases and particulate matter are the main pollutants and exhibit extensive local variability. The aforementioned pollutants are small particles that attach to the skin or penetrate into it, enhancing free radicals' production inside the inner skin layers. This urges the need to propose cosmetic products that help prevent and/or minimise pollutants' effects on the skin whether irritation, ageing and cancer. Furthermore, intrinsic and extrinsic factors contributed to skin irritation and ageing. Intrinsic factors are within skin factors and include genetic and physiological characteristics of individuals. Moreover, extrinsic factors comprise environmental factors such as humidity, temperature, and smoke. Subsequently active ingredients with antipollutant properties addressed the intrinsic and extrinsic factors by four mechanisms being: free radical neutralisation, film-forming ability, skin barrier enhancement and fortification. Such ingredients include vitamin A derivatives, vitamin C derivatives, carbohydrates, and plant-based products. Yet, very limited studies have evaluated the effectiveness of the aforementioned active ingredients against irritation or ageing and this should be considered in future work.

Understanding NO2 Concentration Dynamics within Tema Metropolitan Area of Ghana Using Generalized Linear Model

The concentration of nitrogen dioxide (NO2) is worsening across the globe alongside growth in industrial and general anthropogenic activities. Due to its serious health implications with long-term exposure, studies on NO2 concentration have gained space in the academic literature. In this study, awareness is created on the levels of NO2 across four (4) locations within the Tema Metropolitan area, with specific interest in selecting locations and periods significantly saturated with NO2 within the study area. NO2 was measured using RKI Eagle, an instrument with a built-in sensor for a specific gas measurement. Measurements were taken day and night at sampling points around 100 meters apart in each location. Data collection was performed over a nine (9)-month period. The Generalized Linear model is explored for selecting locations and periods significantly affected by NO2. From the results, the fourth week (26th–31st) of July 2020, the fourth week (27th–31st) of December 2020, the first week (1st–7th) of January 2021, and the fourth week (24th–31st) of January 2021 recorded severe concentrations of NO2. Additionally, the lives of residents in the Oil Jetty and the VALVO hospital areas were found to be the most endangered, as they recorded significantly high concentrations of NO2. In a developing country such as Ghana, this study is useful for monitoring NO2 concentrations in similar areas to inform decision making and environmental policy formulation.

From Theory to Praxis: 'Go Sustainable Living' Survey for Exploring Individuals Consciousness Level of Decision-Making and Action-Taking in Daily Life Towards a Green Citizenship

This study aims at embedding sustainability practices by exploring sustainable actions of individuals consisting the educated workforce of Greece. A tailored questionnaire was created and sent via e-mails to 500 respondents, to identify a snapshot of participants daily buying and consuming actions. 483 responses received and analyzed using statistical tools. They respond to recommendations for enhancing sustainability consciousness at individual level, inspiring people to buy sustainable, creating new consumption attitudes that are key factors for moving towards a sustainable citizenship. The findings will further provide information for a second paper on developing the ‘Go Sustainable Living’ digital application to be uploaded in individuals’ mobile phones, for rewarding users with points that correspond to each sustainable action and can later be used for discounts in all participating stores. The analysis showed that <30% of consumers are considered sustainability-conscious, 57.6% are in a transition phase, while 13% fell into the category of non-conscious. To make sustainable decisions and actions in every daily life, individuals need to have knowledge of sustainability, awareness, consciousness of their actions, and be active citizens. An educated workforce armed with sustainability perceptions and competencies is an asset for societies and businesses poised to respond to the sustainability call. Sustainability should not be only an ‘utopia’ in our societies but an ‘eutopia’ entailing a life with ecological and social health and prosperity at a local, regional, and global level.

Effects of deployment of electric vehicles on air quality in the urban area of Turin (Italy)

This study aims to evaluate and quantify the environmental, health, and economic benefits due to the penetration of electric vehicles in the fleet composition by replacing conventional vehicles in an urban area. This study has been performed for the city of Turin, where road transport represents one of the main primary emission sources. Air pollution data were evaluated by ADMS-Roads, the flow traffic data used for simulation come from a real-time monitoring. Instead, statistics on mortality and hospitalizations due to cardiovascular and respiratory diseases were collected from the regional health information system and the National Health Institute and implemented in the BenMap software to evaluate the health and economic impacts. In both cases, two scenarios to evaluate the annual benefits of reducing PM₁₀, PM_2.5 and NO₂ were used: reduction to the levels gained by the assumptions of 2025 and 2030 Scenario and the PM₁₀, PM_2.5 and NO₂ concentrations were considered for evaluating short-term and long-term effects. The analysis performed doesn't include background pollution levels, i.e. the concentrations percentage reductions are only related to the local contribution, therefore derived from the contribution only of traffic source. The results show that fleet electrification has a potential benefit for concentrations reduction in comparison to the base Scenario, especially related to NO₂, less for PM₁₀ and PM_2.5. Regarding 2025 Scenario (4 % (passenger car) and 5 % (light-duty vehicles) electric vehicles), reductions of 52 % of NO2, 35 % of PM10 and 49 % of PM2.5 are observed. Meanwhile, as regards 2030 Scenario reductions of 87 % of NO2, 36 % of PM10 and 50 % of PM2.5 are reached. Also, in terms of social costs a decrease of 47 % for the 2025 Scenario and 66 % for the 2030 Scenario in comparison to the base Scenario is arise.

Simulated vehicle exhaust exposure induces sex-dependent behavioral deficits in rats

Chronic exposure to vehicle exhaust emissions are known to cause several adverse health effects. In this study, we examined the impact of several parameters of behavioral, cardiovascular and biochemical functions upon exposure of pro-oxidants CO2, NO2 and CO (simulated vehicle exhaust exposure: SVEE) in male and female rats. Adult rats were subjected to SVEE or ambient air in whole body chambers (5 h/day, 2 weeks). Male, but not female, rats developed memory deficits, and exhibited anxiety- and depression-like behavior, accompanied with significantly high levels of serum corticosterone, oxidative stress, and inflammatory markers (CRP and TNFα), associated with lower levels of total antioxidant capacity, glutathione, glyoxalase and superoxide dismutase (SOD) activities. Brain region-specific downregulation of Cu/Zn SOD, Mn SOD, GSR, PKCα, ERK1/2, CaMKIV, CREB, BDNF and NMDAR subunit protein expression were also observed in male, but not female, rats. Blood pressure, heart rate and eGFR were not negatively impacted by SVEE. Our results suggest that SVEE, through its pro-oxidant content, induces oxido-inflammation in susceptible brain regions in a sex-dependent manner.

Ingestion of contaminated kelps by the herbivore Tetrapygus niger: Negative effects on food intake, growth, fertility, and early development

Macrocystis pyrifera reaches distant areas after detachment, accumulate heavy metals, and serve as trophic subsidy. In this context, effects on both adults and larvae of Tetrapygus niger fed with polluted kelps were determined by assessing growth, fertility, and early larval development. Results revealed that sea urchins fed with polluted kelps from highly impacted zone (HIZ) showed a lower growth (3.6% gained weight) and gamete release (358 cells mL^-1) than those fed with non-impacted kelps (NIZ) (19.3% and 945 cells mL^-1). The HIZ treatment showed a developmental delay in comparison to NIZ, accounted mainly by the abundance of malformed 2-arm pluteus larvae (10-15%) during most of the culture. Malformed 4-arm pluteus larvae showed a constant increase, reaching 37% at the end of the culture. Thus, the pollutants ingested by sea urchins can be transferred to their offspring and cause negative effects in their early development, categorizing M. pyrifera as a pollutant carrier.

Spatial variability of nitrogen dioxide and formaldehyde and residential exposure of children in the industrial area of Viadana, Northern Italy

Chipboard production is a source of ambient air pollution. We assessed the spatial variability of outdoor pollutants and residential exposure of children living in proximity to the largest chipboard industry in Italy and evaluated the reliability of exposure estimates obtained from a number of available models. We obtained passive sampling data on NO₂ and formaldehyde collected by the Environmental Protection Agency of Lombardy region at 25 sites in the municipality of Viadana during 10 weeks (2017-2018) and compared NO₂ measurements with average weekly concentrations from continuous monitors. We compared interpolated NO₂ and formaldehyde surfaces with previous maps for 2010. We assessed the relationship between residential proximity to the industry and pollutant exposures assigned using these maps, as well as other available countrywide/continental models based on routine data on NO₂, PM₁₀, and PM_2.5. The correlation between NO₂ concentrations from continuous and passive sampling was high (Pearson's r = 0.89), although passive sampling underestimated NO₂ especially during winter. For both 2010 and 2017-2018, we observed higher NO₂ and formaldehyde concentrations in the south of Viadana, with hot-spots in proximity to the industry. PM₁₀ and PM_2.5 exposures were higher for children at < 1 km compared to the children living at > 3.5 km to the industry, whereas NO₂ exposure was higher at 1-1.7 km to the industry. Road and population densities were also higher close to the industry. Findings from a variety of exposure models suggest that children living in proximity to the chipboard industry in Viadana are more exposed to air pollution and that exposure gradients are relatively stable over time.

Susceptibility of individuals with chronic obstructive pulmonary disease to respiratory inflammation associated with short-term exposure to ambient air pollution: A panel study in Beijing

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide. There is no clear evidence of whether COPD patients are more susceptible to respiratory inflammation associated with short-term exposure to air pollutants than those without COPD.

OBJECTIVES

This study directly compared air pollutant-associated respiratory inflammation between COPD patients and healthy controls.

METHODS

This study is based on the COPDB panel study (COPD in Beijing). Fractional exhaled nitric oxide (FeNO) was repeatedly measured in 53 COPD patients and 82 healthy controls at up to four clinical visits. Concentrations of carbon monoxide (CO), nitrogen monoxide, nitrogen dioxide (NO₂), sulfur dioxide (SO₂), fine particulate matter (PM_2.5), black carbon (BC), ultrafine particles (UFPs), and accumulated-mode particles (Acc) were monitored continuously at a fixed-site monitoring station. Linear mixed-effects models were used to compare the associations between ln-transformed FeNO and average 1-23 h concentrations of air pollutants before the clinical visits.

RESULTS

FeNO was positively associated with interquartile range (IQR) increases in average concentrations of CO, NO₂, SO₂, BC, UFPs, and Acc in all participants, with the strongest associations in different time-windows (range from 6.6% for average 1 h NO₂ exposure to 32.1% for average 7 h SO₂ exposure). Associations between FeNO and average 13-23 h PM_2.5 exposure differed significantly according to COPD status. Increases in FeNO associated with average 1-2 h NO exposure were significant in COPD patients (range 8.9-10.2%), while the associations were nonsignificant in healthy controls. Associations between FeNO and average 1-23 h CO and SO₂ exposure tended to be higher in COPD patients than in healthy controls, although the differences were not significant. UFPs-associated respiratory inflammation was robust in both subgroups.

CONCLUSIONS

COPD patients are more susceptible to respiratory inflammation following PM_2.5, NO, CO, and SO₂ exposure than individuals without COPD.

Color Changes in Ag Nanoparticle Aggregates Placed in Various Environments: Their Application to Air Monitoring

Fresh Ag nanoparticles (NPs) dispersed on a transparent SiO₂ exhibit an intense optical extinction band originating in localized surface plasmon resonance (LSPR) in the visible range. The intensity of the LSPR band weakened when the Ag NPs was stored in ambient air for two weeks. The rate of the weakening and the LSPR wavelength shift, corresponding to visual chromatic changes, strongly depended on the environment in which Ag NPs were set. The origin of a chromatic change was discussed along with both compositional and morphological changes. In one case, bluish coloring followed by a prompt discoloring was observed for Ag NPs placed near the ventilation fan in our laboratory, resulted from adsorption of large amounts of S and Cl on Ag NP surfaces as well as particle coarsening. Such color changes deduce the presence of significant amounts of S and Cl in the environment. In another case, a remarkable blue-shift of the LSPR band was observed for the Ag NPs stored in the desiccator made of stainless steel, originated in the formation of CN and/or HCN compounds and surface roughening. Their color changed from maroon to reddish, suggesting that such molecules were present inside the desiccator.

The impact of air pollution on skin and related disorders: A comprehensive review

As the largest organ in the body, human skin is constantly exposed to harmful compounds existing in the surrounding environment as the first-line barrier. Studies have indicated that exposure to high concentrations of many environmental factors, such as ultraviolet (UV) radiation, outdoor air pollutants, including polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), particulate matter (PM), heavy metals, gaseous pollutants, such as carbon monoxide (CO), nitric oxides (NO_x ), sulfur oxide (SO₂ ), ozone (O₃ ), and indoor air pollutants (solid fuels consumption), might interrupt the skin's normal barrier function. Besides, the intensity of the pollutants and the length of exposure might be a contributing factor. Air pollutants are believed to induce or exacerbate a range of skin conditions, such as aging, inflammatory diseases (atopic dermatitis, cellulitis, and psoriasis), acne, hair loss, and even skin cancers (mainly melanoma and Squamous Cell Carcinoma) through various mechanisms. The interaction between pollutants and the skin might differ based on each agent's particular characteristics. Also, damaging the skin barrier seems to be closely related to the increased production of reactive oxygen species (ROS), induction of oxidative stress, activation of aryl hydrocarbon receptor (AhR), and inflammatory cytokines. This article reviews recent studies on the correlation between air pollutants and skin diseases, along with related mechanisms.

Analysis of lockdown for CoViD-19 impact on NO2 in London, Milan and Paris: What lesson can be learnt?

Nitrogen dioxide (NO₂) can have harmful effects on human health and can act as a precursor for the formation of other air pollutants in urban environment such as secondary PM_2.5 and ozone. The lockdown measures for CoViD-19 allowed to simulate on a large scale the massive and prolonged reduction of road traffic (the main source for NO₂ in urban environment). This work aims to selectively assess the maximum impact that total traffic blocking measures can have on NO₂. For this reason, three megacities (London, Milan and Paris) were chosen which had similar characteristics in terms of climatic conditions, population, policies of urban traffic management and lockdown measures. 52 air quality control units have been used to compare data measured in lockdown and in the same periods of previous years, highlighting a significant decrease in NO₂ concentration due to traffic (London: 71.1 % - 80.8 %; Milan: 8.6 % - 42.4 %; Paris: 65.7 % - 79.8 %). In 2020 the contribution of traffic in London, Milan and Paris dropped to 3.3 ± 1.3 μg m^-3, 6.1 ± 0.8 μg m^-3, and 13.4 ± 1.5 μg m^-3, respectively. Despite the significant reduction in the NO₂ concentration, in UT stations average NO₂ concentrations higher than 40 μg m^-3 were registered for several days. In order to reduce the pollution, the limitation of road traffic could be not enough, but a vision also aimed at rethink the vehicles and their polluting effects should be developed.

Nitrogen dioxide and asthma emergency department visits in California, USA during cold season (November to February) of 2005 to 2015: A time-stratified case-crossover analysis

Nitrogen dioxide (NO₂) is responsible for aggravating respiratory diseases, particularly asthma. The aim of this study is to investigate the association between NO₂ exposure and asthma emergency department (ED) visits during the cold season (November-February) in five populated locations (Sacramento, San Francisco, Fresno, Los Angeles, and San Diego) of California from 2005 to 2015 (1320 Days). Conditional logistic regression models were used to obtain the odds ratio (OR) and 95% confidence interval (CI) associated with a 5 ppb increase in NO₂ concentration for the 19,735 ED visits identified. An increase in NO₂ exposure increased the odds of having asthma ED visits for the studied population. The potential effect modification by sex (female and male), race (White, Black, Hispanic, and Asian), and age (2-5, 6-18, 19-40, 41-64, and ≥65) was explored. A 5 ppb increase in the concentration of NO₂ during lag 0-30 was associated with a 56% increase in the odds of having an asthma ED visit (OR = 1.560, CI: 1.428-1.703). Sex was not found to be a modifier. Asthma ED visits among all the races/ethnicities (except Asians) were associated with NO₂ exposure. Whites had the highest OR 75% (OR = 1.750, CI: 1.417-2.160) at lag 0-30 in response to NO₂ exposure. The association between NO₂ exposure and asthma ED visits was positive among all age groups except for 19 to 40 years old; the OR was higher among 2 to 18 year old (at lag 0-30: age group 2-5 (OR = 1.699, CI: 1.399-2.062), and age group 6-18 (OR = 1.568, CI 1.348-1.825)). For stratification by location, San Diego and Fresno were found to have the highest OR, compared to the other studied locations.

Challenges and Opportunities in Early Stage Planning of Transport Infrastructure Projects: Environmental Aspects in the Strategic Choice of Measures Approach

The Strategic Choice of Measures (SCM) approach aims to integrate different perspectives and identify measures to adapt new infrastructure projects to their local context at an early stage of Swedish transport planning. SCM is a loosely structured framework for collaboration between actors from, e.g., municipalities and the Swedish Transport Administration, in order to facilitate the coordination of transport planning and land use planning. This paper aims to explore the consideration of environmental aspects in early-stage transport planning by analyzing the SCM approach. An explorative research approach is applied based on literature studies, semi-structured interviews, and a focus group interview. The result shows that in the SCM process, environmental aspects such as noise and air pollution generated by road traffic in urban areas, engage the actors, whereas aspects related to landscape and water were perceived as poorly addressed and received less attention. The consideration of environmental aspects in the SCM process is affected by the local and national authorities’ different interests and the competences involved. To consolidate environmental aspects in early transport planning, these aspects need to be explicitly addressed in the SCM guidelines and the link between the SCM and preceding and following planning stages needs to be strengthened.

Assessing the Respiratory Effects of Air Pollution from Biomass Cookstoves on Pregnant Women in Rural India

Background: In India, biomass fuel is burned in many homes under inefficient conditions, leading to a complex milieu of particulate matter and environmental toxins known as household air pollution (HAP). Pregnant women are particularly vulnerable as they and their fetus may suffer from adverse consequences of HAP. Fractional exhaled nitric oxide (FeNO) is a noninvasive, underutilized tool that can serve as a surrogate for airway inflammation. We evaluated the prevalence of respiratory illness, using pulmonary questionnaires and FeNO measurements, among pregnant women in rural India who utilize biomass fuel as a source of energy within their home. Methods: We prospectively studied 60 pregnant women in their 1st and 2nd trimester residing in villages near Nagpur, Central India. We measured FeNO levels in parts per billion (ppb), St. George’s Respiratory Questionnaire (SGRQ-C) scores, and the Modified Medical Research Council (mMRC) Dyspnea Scale. We evaluated the difference in the outcome distributions between women using biomass fuels and those using liquefied petroleum gas (LPG) using two-tailed t-tests. Results: Sixty-five subjects (32 in Biomass households; 28 in LPG households; 5 unable to complete) were enrolled in the study. Age, education level, and second-hand smoke exposure were comparable between both groups. FeNO levels were higher in the Biomass vs. LPG group (25.4 ppb vs. 8.6 ppb; p-value = 0.001). There was a difference in mean composite SGRQ-C score (27.1 Biomass vs. 10.8 LPG; p-value < 0.001) including three subtotal scores for Symptoms (47.0 Biomass vs. 20.2 LPG; p-value< 0.001), Activity (36.4 Biomass vs. 16.5 LPG; p-value < 0.001) and Impact (15.9 Biomass vs. 5.2 LPG; p-value < 0.001). The mMRC Dyspnea Scale was higher in the Biomass vs. LPG group as well (2.9 vs. 0.5; p < 0.001). Conclusion: Increased FeNO levels and higher dyspnea scores in biomass-fuel-exposed subjects confirm the adverse respiratory effects of this exposure during pregnancy. More so, FeNO may be a useful, noninvasive biomarker of inflammation that can help better understand the physiologic effects of biomass smoke on pregnant women. In the future, larger studies are needed to characterize the utility of FeNO in a population exposed to HAP.

Particulate matter concentrations and fluxes within an urban park in Naples

Airborne particulate matter can represent a serious issue for human health, especially in densely populated urban areas. Moreover, the inhalation of particulate can be more harmful with decreasing particles diameter. Vegetation can provide many ecosystem services to the citizens, including the removal of many different pollutants in the air, but while the effect on many gaseous compounds has already been widely proved, the capability of particulate matter (PM) sequestration driven by vegetation and its resulting benefit on air quality has not been deeply investigated yet at larger spatial scale, especially in Mediterranean environment. This study was conducted in the Real Bosco di Capodimonte, a green area of about 125 ha located inside the urban area of Naples (Italy) containing different species typical of the Mediterranean forest ecosystem. To better understand the interaction between PM and the park area, we measured fluxes of PM₁₀, PM_2.5 and PM₁ with a fast acquisition analyser, according to the Eddy Covariance technique. We found that the particle deposition was higher during the central hours of the day and it was more evident for smaller size particles. Furthermore, the daily PM fluxes found accorded with evapotranspiration and carbon sequestration operated by plants, suggesting a possible active role of vegetation on the particulate deposition.

Panel study using novel sensing devices to assess associations of PM2.5 with heart rate variability and exposure sources

BACKGROUND/OBJECTIVE

This work applied a newly developed low-cost sensing (LCS) device (AS-LUNG-P) and a certified medical LCS device (Rooti RX) to assessing PM_2.5 impacts on heart rate variability (HRV) and determining important exposure sources, with less inconvenience to subjects.

METHODS

Observations using AS-LUNG-P were corrected by side-by-side comparison with GRIMM instruments. Thirty-six nonsmoking healthy subjects aged 20-65 years were wearing AS-LUNG-P and Rooti RX for 2-4 days in both Summer and Winter in Taiwan.

RESULTS

PM_2.5 exposures were 12.6 ± 8.9 µg/m³. After adjusting for confounding factors using the general additive mixed model, the standard deviations of all normal to normal intervals reduced by 3.68% (95% confidence level (CI) = 3.06-4.29%) and the ratios of low-frequency power to high-frequency power increased by 3.86% (CI = 2.74-4.99%) for an IQR of 10.7 µg/m³ PM_2.5, with impacts lasting for 4.5-5 h. The top three exposure sources were environmental tobacco smoke, incense burning, and cooking, contributing PM_2.5 increase of 8.53, 5.85, and 3.52 µg/m³, respectively, during 30-min intervals.

SIGNIFICANCE

This is a pioneer in demonstrating application of novel LCS devices to assessing close-to-reality PM_2.5 exposure and exposure-health relationships. Significant HRV changes were observed in healthy adults even at low PM_2.5 levels.

The Health Opportunity Index: Understanding the Input to Disparate Health Outcomes in Vulnerable and High-Risk Census Tracts

The Health Opportunity Index (HOI) is a multivariate tool that can be more efficiently used to identify and understand the interplay of complex social determinants of health (SDH) at the census tract level that influences the ability to achieve optimal health. The derivation of the HOI utilizes the data-reduction technique of principal component analysis to determine the impact of SDH on optimal health at lower census geographies. In the midst of persistent health disparities and the present COVID-19 pandemic, we demonstrate the potential utility of using 13-input variables to derive a composite metric of health (HOI) score as a means to assist in the identification of the most vulnerable communities during the current pandemic. Using GIS mapping technology, health opportunity indices were layered by counties in Ohio to highlight differences by census tract. Collectively we demonstrate that our HOI framework, principal component analysis and convergence analysis methodology coalesce to provide results supporting the utility of this framework in the three largest counties in Ohio: Franklin (Columbus), Cuyahoga (Cleveland), and Hamilton (Cincinnati). The results in this study identified census tracts that were also synonymous with communities that were at risk for disparate COVID-19 related health outcomes. In this regard, convergence analyses facilitated identification of census tracts where different disparate health outcomes co-exist at the worst levels. Our results suggest that effective use of the HOI composite score and subcomponent scores to identify specific SDH can guide mitigation/intervention practices, thus creating the potential for better targeting of mitigation and intervention strategies for vulnerable communities, such as during the current pandemic.

Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach

Increasing waste generation has become a significant issue over the globe due to the rapid increase in urbanization and industrialization. In the literature, many issues that have a direct impact on the increase of waste and the improper disposal of waste have been investigated. Most of the existing work in the literature has focused on providing a cost-efficient solution for the monitoring of garbage collection system using the Internet of Things (IoT). Though an IoT-based solution provides the real-time monitoring of a garbage collection system, it is limited to control the spreading of overspill and bad odor blowout gasses. The poor and inadequate disposal of waste produces toxic gases, and radiation in the environment has adverse effects on human health, the greenhouse system, and global warming. While considering the importance of air pollutants, it is imperative to monitor and forecast the concentration of air pollutants in addition to the management of the waste. In this paper, we present and IoT-based smart bin using a machine and deep learning model to manage the disposal of garbage and to forecast the air pollutant present in the surrounding bin environment. The smart bin is connected to an IoT-based server, the Google Cloud Server (GCP), which performs the computation necessary for predicting the status of the bin and for forecasting air quality based on real-time data. We experimented with a traditional model (k-nearest neighbors algorithm (k-NN) and logistic reg) and a non-traditional (long short term memory (LSTM) network-based deep learning) algorithm for the creation of alert messages regarding bin status and forecasting the amount of air pollutant carbon monoxide (CO) present in the air at a specific instance. The recalls of logistic regression and k-NN algorithm is 79% and 83%, respectively, in a real-time testing environment for predicting the status of the bin. The accuracy of modified LSTM and simple LSTM models is 90% and 88%, respectively, to predict the future concentration of gases present in the air. The system resulted in a delay of 4 s in the creation and transmission of the alert message to a sanitary worker. The system provided the real-time monitoring of garbage levels along with notifications from the alert mechanism. The proposed works provide improved accuracy by utilizing machine learning as compared to existing solutions based on simple approaches.

Characterization, Pollution Sources, and Health Risk of Ionic and Elemental Constituents in PM2.5 of Wuhan, Central China

Atmospheric PM2.5 samples from Wuhan, China were collected during a winter period of February and a summer period of August in 2018. The average PM2.5 mass concentration in winter reached 112 μg/m3—about two-fold higher than that found in summer. Eight ionic species constituted 1/3 of PM2.5, whereas more than 85% represented secondary ionic aerosols (NO3−, SO42− and NH4+). Higher ratios of NO3−/SO42− (0.95–2.62) occurred in winter and lower ratios (0.11–0.42) occurred in summer showing the different contribution for mobile and stationary sources. Seventeen elemental species constituted about 10% of PM2.5, with over 95% Na, Mg, Al, Ca, Fe, K and Zn. Higher K-concentration occurred in winter indicating greater contribution from biomass and firework-burning. Carcinogenic risks by Cr, As, Cd, Ni and Pb in PM2.5 indicated that about 6.94 children and 46.5 adults among per million may risk getting cancer via inhalation during surrounding winter atmospheric sampling, while about 5.41 children and 36.6 adults have the same risk during summer. Enrichment factors (EFs) and elemental ratios showed that these hazardous elements were mainly from anthropogenic sources like coal and oil combustion, gasoline and diesel vehicles.

Cumulative exposure to air pollution and subsequent mortality among older adults in China

BACKGROUND

Research on the health effects of exposure to air pollution is growing. However, relatively little attention has been paid to the effects of long-term and cumulative exposure to air pollutants. Individual-level studies on the health consequences of air pollution in China are especially scarce. The purpose of this study is to examine the effect of cumulative exposure to sulfur dioxide (SO2), an air pollutant of particular concern in China, on all-cause mortality in older Chinese adults.

METHODS

Using a nationally representative sample of older adults in China (N = 11 199), we tracked mortality over an 11-year period (2000-11). Air pollution data were linked to respondents using provincial identifiers. To examine the effect of cumulative SO2 exposure on mortality, we employed multilevel multinomial logistic regression models that account for within subject clustering of observations over time and clustering at the province level.

RESULTS

We found that every 10-μg/m3 increase in cumulative exposure to SO2 increased the odds of death by nearly 1% (OR = 1.008; 95% CI: 1.002-1.014), controlling for province- and individual-level social and economic characteristics.

CONCLUSIONS

Our analysis shows that air pollution is a risk factor for morality in older Chinese adults. Findings suggest that stronger SO2 regulations may enhance longevity.

Temperature-Related Corrosion Resistance of AISI 1010 Carbon Steel in Sulfolane

Sulfolane-induced corrosion can lead to severe impairment in industrial systems. Therefore, determination of solvent corrosivity is valid. Under standard conditions, pure sulfolane is considered to be thermally stable and chemically inert, hence non-aggressive towards carbon/stainless steel. Unfortunately, the sulfolane-evoked corrosion of the industrial installations is observed for sulfolane-based systems polluted by small quantities of oxygen, water and some oxidizing agents. Moreover, sulfolane decomposition with formation of corrosive (by-)products can be escalated by some process parameters, e.g., temperature. The main objective of this study was to determine the corrosion resistance of AISI 1010 steel immersed in sulfolane at temperatures ranging from 25 to 230 °C. Evaluation of the corrosion damage was carried out using electrochemical techniques and scanning probe/electron microscopy, respectively. The general corrosion tendency, corrosion rate and surface corrosion degree were taken into account as well. It was noticed that the corrosion rate linearly increases with the enhancement of sulfolane temperature. Moreover, the interfacial reaction of steel with sulfolane resulted in the formation of corrosion product layer, which is a physical barrier between the corrosive environment and steel improving corrosion resistance of the latter. In fact, the increment of the sulfolane temperature caused a gradual breakdown of the protective layer and the increase in the corrosion degree of the investigated steel. Finally, it was found that the corrosion degree doubles approximately every 42 °C.

Interaction of Particles with Langmuir Monolayers of 1,2-Dipalmitoyl-Sn-Glycero-3-Phosphocholine: A Matter of Chemistry?

Lipid layers are considered among the first protective barriers of the human body against pollutants, e.g., skin, lung surfactant, or tear film. This makes it necessary to explore the physico-chemical bases underlying the interaction of pollutants and lipid layers. This work evaluates using a pool of surface-sensitive techniques, the impact of carbon black and fumed silica particles on the behavior of Langmuir monolayers of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC). The results show that the incorporation of particles into the lipid monolayers affects the surface pressure–area isotherm of the DPPC, modifying both the phase behavior and the collapse conditions. This is explained considering that particles occupy a part of the area available for lipid organization, which affects the lateral organization of the lipid molecules, and consequently the cohesion interactions within the monolayer. Furthermore, particles incorporation worsens the mechanical performance of lipid layers, which may impact negatively in different processes presenting biological relevance. The modification induced by the particles has been found to be dependent on their specific chemical nature. This work tries to shed light on some of the most fundamental physico-chemical bases governing the interaction of pollutants with lipid layers, which plays an essential role on the design of strategies for preventing the potential health hazards associated with pollution.