A Review of Airborne Particulate Matter Effects on Young Children’s Respiratory Symptoms and Diseases

Analyzing COVID-19 and Air Pollution Effects on Pediatric Asthma Emergency Room Visits in Taiwan

(1) Background: An asthma exacerbation that is not relieved with medication typically requires an emergency room visit (ERV). The coronavirus disease 2019 (COVID-19) pandemic began in Taiwan in January of 2020. The influence of the COVID-19 pandemic on pediatric ERVs in Taiwan was limited. Our aim was to survey pediatric asthma ERVs in the COVID-19 era; (2) Methods: Data were collected from the health quality database of the Taiwanese National Health Insurance Administration from 2019 to 2021. Air pollution and climatic factors in Taipei were used to evaluate these relationships. Changes in the rates of pediatric asthma ERVs were assessed using logistic regression analysis. Poisson regression was used to evaluate the impact of air pollution and climate change; (3) Results: The rate of pediatric asthma ERVs declined in different areas and at different hospital levels including medical centers, regional and local hospitals. Some air pollutants (particulate matter ≤ 2.5 µm, particulate matter ≤ 10 µm, nitrogen dioxide, and carbon monoxide) reduced during the COVID-19 lockdown. Ozone increased the relative risk (RR) of pediatric asthma ERVs during the COVID-19 period by 1.094 (95% CI: 1.095-1.12) per 1 ppb increase; (4) Conclusions: The rate of pediatric asthma ERVs declined during the COVID-19 pandemic and ozone has harmful effects. Based on these results, the government could reduce the number of pediatric asthma ERVs through healthcare programs, thereby promoting children's health.

Air change rates and infection risk in school environments: Monitoring naturally ventilated classrooms in a northern Italian urban context

The importance of building ventilation in avoiding long-distance airborne transmission has been highlighted with the advent of the COVID-19 pandemics. Among others, school environments, in particular classrooms, present criticalities in the implementation of ventilation strategies and their impact on indoor air quality and risk of contagion. In this work, three naturally ventilated school buildings located in northern Italy have undergone monitoring at the end of the heating season. Environmental parameters, such as CO2 concentration and indoor/outdoor air temperature, have been recorded together with the window opening configurations to develop a two-fold analysis: i) the estimation of real air change rates through the transient mass balance equation method, and ii) the individual infection risk via the Wells-Riley equation. A strong statistical correlation has been found between the air change rates and the windows opening configuration by means of a window-to-volume ratio between the total opening area and the volume of the classroom, which has been used to estimate the individual infection risk. Results show that the European Standard recommendation for air renewal could be achieved by a window opening area of at least 1.5 m2, in the most prevailing Italian classrooms. Furthermore, scenarios in which the infector agent is a teacher show higher individual infection risk than those in which the infector is a student. In addition, the outcomes serve school staff as a reference to ensure adequate ventilation in classrooms and keep the risk of infection under control based on the number of the students and the volume of the classroom.

Fine particulate matter exposure and pediatric mental health outcomes: An integrative review

INTRODUCTION

Climate change is expected to worsen air pollution globally, which contributes to a multitude of negative health outcomes in humans.

AIM

The purpose of this integrative review is to examine the relationship between exposure to fine particulate matter (PM2.5 ) and mental health outcomes in children and adolescents.

METHODS

This review utilized Whittemore and Knafl's methodology for conducting an integrative review. After a thorough search of the literature, 17 articles were selected for this review and evaluated utilizing the Johns Hopkins Evidence Based Practice Appraisal Tool.

RESULTS

Of the 17 articles, all were quantitative observational study designs. The studies were then synthesized into four outcome themes. These themes included emergent and general psychiatric outcomes, neurodevelopmental disorders, stress and anxiety, and depression.

DISCUSSION

The strongest evidence supports a possible correlation between PM2.5 exposure and adolescent mental health outcomes, although there were some studies that contradicted these associations. While research on this topic is in its early stages, more needs to be conducted to determine causality with any of the associations presented to improve generalizability of the findings.

IMPLICATIONS FOR PRACTICE

Nurses must be aware of and part of the solution to address climate change and resulting air pollution, as it is a potentially significant threat to children's mental health in the 21st century.

Residential exposure to air pollution and adverse respiratory and allergic outcomes in children and adolescents living in a chipboard industrial area of Northern Italy

BACKGROUND

Chipboard production is a source of wood dust, formaldehyde, and combustion-related pollutants such as nitrogen dioxide (NO₂) and particulate matter (PM). In this cohort study, we assessed whether exposures to NO₂, formaldehyde, PM₁₀, PM_2.5, and black carbon were associated with adverse respiratory and allergic outcomes among all 7525 people aged 0-21 years residing in the Viadana district, an area in Northern Italy including the largest chipboard industrial park in the country.

METHODS

Data on hospitalizations, emergency room (ER) admissions, and specialist visits in pneumology, allergology, ophthalmology, and otorhinolaryngology were obtained from the Local Health Unit. Residential air pollution concentrations in 2013 (baseline) were derived using local (Viadana II), national (EPISAT), and continental (ELAPSE) exposure models. Associations were estimated using negative binomial regression models for counts of events occurred during 2013-2017, with follow-up time as an offset term and adjustment for sex, age, nationality, and a census-block socio-economic indicator.

RESULTS

Median annual exposures to NO₂, PM₁₀, and PM_2.5 were below the European Union annual air quality standards (40, 40, and 25 μg/m³) but above the World Health Organization 2021 air quality guideline levels (10, 15, and 5 μg/m³). Exposures to NO₂ and PM_2.5 were significantly associated with higher rates of ER pneumology admissions (13 to 30 % higher rates per interquartile range exposure differences, all p < 0.01). Higher rates of allergology and ophthalmology visits were found for participants exposed to higher pollutants' concentrations. When considering the 4-km buffer around the industries, associations with respiratory hospitalizations became significant, and associations with ER pneumology admissions, allergology and ophthalmology visits became stronger. Formaldehyde was not associated with the outcomes considered.

CONCLUSION

Using administrative indicators of health effects a priori attributable to air pollution, we documented the adverse impact of long-term air pollution exposure in residential areas close to the largest chipboard industries in Italy. These findings, combined with evidence from previous studies, call for an action to improve air quality through preventive measures especially targeting emissions related to the industrial activities.

Environmental Regulation and Chronic Conditions: Evidence from China's Air Pollution Prevention and Control Action Plan

In January 2013, a dense haze covered 1.4 million kilometers of China and affected more than 800 million people. Air pollution in China had become a serious threat to the daily lives of people. The State Council of China enacted the "Air Pollution Prevention and Control Action Plan" (APPCAP) in 2013 to lower the particulate matter (PM) level. Between 2013 and 2017, each administrative division established its own environmental preservation strategy in accordance with the APPCAP. We examined the effects of the nationwide air pollution control policy, APPCAP, on chronic health conditions among adults using a nationally representative survey, CFPS, conducted in 2012, 2014, and 2016. We applied a difference-in-differences model, using the time gap when each administrative division implemented the APPCAP. We found that the APPCAP significantly reduced doctor-diagnosed chronic conditions of the respiratory and circulatory systems in the last six months. In respiratory diseases and circulatory system diseases, the treatment effect of the APPCAP was a 34.6% and 11.5% reduction in the sample mean, respectively. The poorest socioeconomic groups and the elderly benefited the most. The stronger the goal, the more positive the effects were on health; the longer the policy intervention, the better the health outcomes were.

Environmental factors linked to hospital admissions in young children due to acute viral lower respiratory infections: A bidirectional case-crossover study

OBJECTIVE

This study evaluated the association of the short-term exposure to environmental factors (relative humidity, temperature, NO₂, SO₂, O₃, PM₁₀, and CO) with hospital admissions due to acute viral lower respiratory infections (ALRI) in children under two years before the COVID-19 era.

METHODS

We performed a bidirectional case-crossover study in 30,445 children with ALRI under two years of age in the Spanish Minimum Basic Data Set (MBDS) from 2013 to 2015. Environmental data were obtained from Spain's State Meteorological Agency (AEMET). The association was assessed by conditional logistic regression.

RESULTS

Lower temperature one week before the day of the event (hospital admission) (q-value = 0.012) and higher relative humidity one week (q-value = 0.003) and two weeks (q-value<0.001) before the day of the event were related to a higher odds of hospital admissions. Higher NO₂ levels two weeks before the event were associated with hospital admissions (q-value<0.001). Moreover, higher concentrations on the day of the event for SO₂ (compared to lag time of 1-week (q-value = 0.026) and 2-weeks (q-value<0.001)), O₃ (compared to lag time of 3-days (q-value<0.001), 1-week (q-value<0.001), and 2-weeks (q-value<0.001)), and PM₁₀ (compared to lag time of 2-weeks (q-value<0.001)) were related to an increased odds of hospital admissions for viral ALRI.

CONCLUSION

Short-term exposure to environmental factors (climatic conditions and ambient air contaminants) was linked to a higher likelihood of hospital admissions due to ALRI. Our findings emphasize the importance of monitoring environmental factors to assess the odds of ALRI hospital admissions and plan public health resources.

A Real-Time Approach to Detect PM2.5 in a Seriously Polluted Environment Based on Pressure Drop

A differential pressure-based low-cost PM2.5 detection system was developed for particulate matter measurement in polluted environments. The PM2.5 monitor consists of a sampling device, a pump, a pressure sensor, and a control circuit. Two sampling devices including a foam penetration-filter tube and a cyclone-filter holder were applied. Tests were conducted in a haze environment and laboratory particle chambers with varying PM2.5 concentration. The pressure data were related to the PM2.5 concentration recorded by Dusttrak to show the calibration process and the performance of this instrument. Results showed the concentration information given by the instrument was consistent with the actual concentration in the experiment, and this instrument was more suitable for seriously polluted environment detection. Concentration oscillation of the pressure-based PM2.5 monitor caused by turbulent flow could be reduced by a longer calculation interval and data averaging in the calculation process. As a low-cost sensor, the pressure-based PM2.5 monitor still has good performance and application value for detecting high-concentration PM2.5 in atmospheric environments or workplaces.

Traffic pollution tracers in the lymphatic system tissue of children-possible link to chronic tonsillitis development: pilot study

The origin of metal elements in tonsillar tissues of children patients was investigated in order to establish the link between environmental pollution and tonsilitis diagnosis. The children lived either in a polluted, industrial region (Moravian-Silesian Region, North-East Czechia) or a clean, predominantly agricultural region (South Bohemian Region, South-East Czechia). Simultaneously, the distance of the address of the patients to the closest main road was assessed. The elemental content of the present particulate matter in the tonsil samples, coming from indicated tonsillectomies, was analysed using scanning electron microscopy equipped with an X-ray microprobe. No significant association of the elemental composition and the region was found using both bivariate and multivariate methods; however, an association with the distance to the closest main road was found. The study presents a novel assessment of the tonsillar tissues and supports the link between environmental factors (traffic-related particulate pollution) and the onset of chronic, idiopathic diseases in children, which has been debated recently.

Contribution of Particles to Air Pollution in Green Parks

Parks can aid in the regulation of microclimates and the improvement of air quality. They can be utilized in real-world systems to choose the best model for explaining the source of pollutant emissions, indicating the requirement for pollution concentration monitoring. Monitoring concentration trends is critical to formulating a strategy to reduce CO2 emissions and the contribution of these gasses to the greenhouse effect, as well as to curbing the rising levels of PM in the air. The research background of this study was performed in the green parks of Novi Sad, Serbia. The results are represented in terms of the quantity of the pollutants, and the correlation of the examined phenomena through statistical analysis. Aeroqual monitors with laser sensors were used to take measurements of particle pollution (PM2.5/10). The constant was confirmed by inter-comparison laboratory measurements of air-quality quantitative control. The measurement findings revealed a minor variance in concentration values for PM2.5/10 from 26–30 μg/m3, which were within the allowed limits, indicating that the air was moderately clean. The linear link between particle concentrations and nitrogen dioxide in the sample was also validated using simple linear regression, as was the high influence of humidity on particle concentrations.

Air Quality Forecast by Statistical Methods: Application to Portugal and Macao

Air pollution is a major concern issue for most countries in the world. In Portugal and Macao, the values of nitrogen dioxide (NO₂), particulate matter (PM) and ozone (O₃) are frequently above the concentration thresholds accepted as “good air quality.” Portugal follows the European Union (EU) legislation (Directive 2008/50/EC) on air quality and Macao the air quality guidelines (AQG) from the WHO. Air quality forecasts are very important mitigation tools because of their ability to anticipate pollution events, and issue early warnings, allowing to take preventive measures and reduce impacts, by avoiding exposure. The work presented here refers to the statistical forecast of air pollutants for three regions: Greater Lisbon Area, Madeira Autonomous Region (both located in Portugal), and Macao Special Administrative Region (in Southern China). The presented statistical approach combines Classification and Regression Tree (CART) and multiple regression (MR) analysis to obtain optimized regression models. This consolidated methodology is now in operation for more than a decade in Portugal, and is subject to regular updates that reflect the ongoing research and the changes in the air quality monitoring network. Recently, the same methodology was applied to Macao in collaboration with the Macao Meteorological and Geophysical Bureau (SMG). Here, a statistical approach for air quality forecasting is described that has been proven to be successful, being able to forecast PM₁₀, PM_2.5, NO₂, and O₃ concentrations, for the next day, with a good performance. In general, all the models have shown a good agreement between the observed and forecasted concentrations (with R² from 0.50 to 0.89), and were able to follow the concentration evolution trend. For some cases, there is a slight delay in the prediction trend. Moreover, the results obtained for pollution episodes have proven that statistical forecast can be an effective way of protecting public health.

Monitoring Rainwater Properties and Outdoor Particulate Matter in a Former Steel Manufacturing City in Romania

Wet deposition is influencing air quality because air pollutants are washed away from the surrounding air. Consequently, particulate matter and associated compounds are transported in the rainwater and enter into soil, surface waters, and groundwater. Nonpoint sources of heavy metals from stormwater runoff have increased in urban areas due to industrialization and the increasing impervious surfaces. In this work, we present an assessment of the rainwater composition regarding the nutrients and other physicochemical characteristics measured in three locations selected in Targoviste city, Romania, a city that had a specialized steel factory and important metallurgical facilities. The rainwater was collected using three PALMEX rain samplers and then was transferred to high-density polyethylene bottles and analyzed using ICP-MS. PM2.5 concentrations were also monitored continuously using optical monitors calibrated using a gravimetric sampler. A detailed analysis of the heavy metals content in rainwater and PM was presented for the pollution episodes occurring in October and November 2019. Backward trajectories were computed using the HYSPLIT model for these periods. The results showed that the PM2.5 ranged from 11.1 to 24.1 μg/m3 in 2019, while the heavy metals in collected rainwater were (µg L−1): 0.25 (Cd) − CV = 26.5%, 0.10 (Co) − CV = 58.1%, 1.77 (Cr) − CV = 24.3%, 377.37 (Ni) − CV = 27.9%, 0.67 (Pb) − CV = 74.3%, and 846.5 (Zn) − CV = 20.6%. Overall, Ni, Pb, Cr, and V had significant correlations between the concentrations from rainwater and PM. Negative associations were found between precipitation events and heavy metals both from rainwater and PM, but only a few showed statistical significance. However, this could explain the “washing” effect of the rain on the heavy metals from PM2.5. The potential sources of nitrogen in the rainwater collected in Targoviste could be from burning fossil fuels and the soils, including both biological processes and fertilization resulting from the intensive agriculture in the piedmont plain in which the city is located. Based on the results, rainwater monitoring can constitute a reliable method for air quality characterization. Additional research is required to better understand seasonality and sources of heterogeneity regarding the associations between PM and rainwater composition.

Indoor Particulate Matter in Urban Households: Sources, Pathways, Characteristics, Health Effects, and Exposure Mitigation

Particulate matter (PM) is a complex mixture of solid particles and liquid droplets suspended in the air with varying size, shape, and chemical composition which intensifies significant concern due to severe health effects. Based on the well-established human health effects of outdoor PM, health-based standards for outdoor air have been promoted (e.g., the National Ambient Air Quality Standards formulated by the U.S.). Due to the exchange of indoor and outdoor air, the chemical composition of indoor particulate matter is related to the sources and components of outdoor PM. However, PM in the indoor environment has the potential to exceed outdoor PM levels. Indoor PM includes particles of outdoor origin that drift indoors and particles that originate from indoor activities, which include cooking, fireplaces, smoking, fuel combustion for heating, human activities, and burning incense. Indoor PM can be enriched with inorganic and organic contaminants, including toxic heavy metals and carcinogenic volatile organic compounds. As a potential health hazard, indoor exposure to PM has received increased attention in recent years because people spend most of their time indoors. In addition, as the quantity, quality, and scope of the research have expanded, it is necessary to conduct a systematic review of indoor PM. This review discusses the sources, pathways, characteristics, health effects, and exposure mitigation of indoor PM. Practical solutions and steps to reduce exposure to indoor PM are also discussed.

Modeling and forecasting of monthly PM2.5 emission of Paris by periodogram-based time series methodology

In this study, monthly particulate matter (PM_2.5) of Paris for the period between January 2000 and December 2019 is investigated by utilizing a periodogram-based time series methodology. The main contribution of the study is modeling the PM_2.5 of Paris by extracting the information purely from the examined time series data, where proposed model implicitly captures the effects of other factors, as all their periodic and seasonal effects reside in the air pollution data. Periodicity can be defined as the patterns embedded in the data other than seasonality, and it is crucial to understand the underlying periodic dynamics of air pollutants to better fight pollution. The method we use successfully captures and accounts for the periodicities, which could otherwise be mixed with seasonality under an alternative methodology. Upon the unit root test based on periodograms, it is revealed that the investigated data has periodicities of 1 year and 20 years, so harmonic regression is utilized as an alternative to Box-Jenkins methodology. As the harmonic regression displayed a better performance both in and out-of-sample forecasts, it can be considered as a powerful alternative to model and forecast time series with a periodic structure.

Performance Evaluation of Particulate Matter and Indoor Microclimate Monitors in University Classrooms under COVID-19 Restrictions

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 μg m⁻³ and PM10 ranged between 30 and 42 μg m⁻³. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10⁻⁴ mg/kg-day (CV = 14.3%) for the 20–40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.

3D Printer Particle Emissions: Translation to Internal Dose in Adults and Children

Desktop fused deposition modeling (FDM®) three-dimensional (3D) printers are becoming increasingly popular in schools, libraries, and among home hobbyists. FDM® 3D printers have been shown to release ultrafine airborne particles in large amounts, indicating the potential for inhalation exposure and consequent health risks among FDM® 3D printer users and other room occupants including children. These particles are generated from the heating of thermoplastic polymer feedstocks during the FDM® 3D printing process, with the most commonly used polymers being acrylonitrile butadiene styrene (ABS) and poly-lactic acid (PLA). Risk assessment of these exposures demands estimation of internal dose, especially to address intra-human variability across life stages. Dosimetry models have proven to effectively translate particle exposures to internal dose metrics relevant to evaluation of their effects in the respiratory tract. We used the open-access multiple path particle dosimetry (MPPD v3.04) model to estimate inhaled particle deposition in different regions of the respiratory tract for children of various age groups from three months to eighteen years old adults. Mass concentration data for input into the MPPD model were calculated using particle size distribution and density data from experimental FDM® 3D printer emissions tests using both ABS and PLA. The impact of changes in critical parameters that are principal determinants of inhaled dose, including: sex, age, and exposure duration, was examined using input parameter values available from the International Commission on Radiological Protection. Internal dose metrics used included regional mass deposition, mass deposition normalized by pulmonary surface area, surface area of deposited particles by pulmonary surface area, and retained regional mass. Total mass deposition was found to be highest in the 9-year-old to 18-year-old age groups with mass deposition by pulmonary surface area highest in 3-month-olds to 9-year-olds and surface area of deposited particles by pulmonary surface area to be highest in 9-year-olds. Clearance modeling revealed that frequent 3D printer users are at risk for an increased cumulative retained dose.

Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality

Air pollution in urban areas is a huge concern that demands an efficient air quality control to ensure health quality standards. The hotspots can be located by increasing spatial distribution of ambient air quality monitoring for which the low-cost sensors can be used. However, it is well-known that many factors influence their results. For low-cost Particulate Matter (PM) sensors, high relative humidity can have a significant impact on data quality. In order to eliminate or reduce the impact of high relative humidity on the results obtained from low-cost PM sensors, a low-cost dryer was developed and its effectiveness was investigated. For this purpose, a test chamber was designed, and low-cost PM sensors as well as professional reference devices were installed. A vaporizer regulated the humid conditions in the test chamber. The low-cost dryer heated the sample air with a manually adjustable intensity depending on the voltage. Different voltages were tested to find the optimum one with least energy consumption and maximum drying efficiency. The low-cost PM sensors with and without the low-cost dryer were compared. The experimental results verified that using the low-cost dryer reduced the influence of relative humidity on the low-cost PM sensor results.

Potential of ARIMA-ANN, ARIMA-SVM, DT and CatBoost for Atmospheric PM2.5 Forecasting in Bangladesh

Atmospheric particulate matter (PM) has major threats to global health, especially in urban regions around the world. Dhaka, Narayanganj and Gazipur of Bangladesh are positioned as top ranking polluted metropolitan cities in the world. This study assessed the performance of the application of hybrid models, that is, Autoregressive Integrated Moving Average (ARIMA)-Artificial Neural Network (ANN), ARIMA-Support Vector Machine (SVM) and Principle Component Regression (PCR) along with Decision Tree (DT) and CatBoost deep learning model to predict the ambient PM2.5 concentrations. The data from January 2013 to May 2019 with 2342 observations were utilized in this study. Eighty percent of the data was used as training and the rest of the dataset was employed as testing. The performance of the models was evaluated by R2, RMSE and MAE value. Among the models, CatBoost performed best for predicting PM2.5 for all the stations. The RMSE values during the test period were 12.39 µg m−3, 13.06 µg m−3 and 12.97 µg m−3 for Dhaka, Narayanganj and Gazipur, respectively. Nonetheless, the ARIMA-ANN and DT methods also provided acceptable results. The study suggests adopting deep learning models for predicting atmospheric PM2.5 in Bangladesh.

Variations in Reactive Oxygen Species Generation by Urban Airborne Particulate Matter in Lung Epithelial Cells-Impact of Inorganic Fraction

Air pollution is associated with numerous negative effects on human health. The toxicity of organic components of air pollution is well-recognized, while the impact of their inorganic counterparts in the overall toxicity is still a matter of various discussions. The influence of airborne particulate matter (PM) and their inorganic components on biological function of human alveolar-like epithelial cells (A549) was investigated in vitro. A novel treatment protocol based on covering culture plates with PM allowed increasing the studied pollutant concentrations and prolonging their incubation time without cell exposure on physical suffocation and mechanical disturbance. PM decreased the viability of A549 cells and disrupted their mitochondrial membrane potential and calcium homeostasis. For the first time, the difference in the reactive oxygen species (ROS) profiles generated by organic and inorganic counterparts of PM was shown. Singlet oxygen generation was observed only after treatment of cells with inorganic fraction of PM, while hydrogen peroxide, hydroxyl radical, and superoxide anion radical were induced after exposure of A549 cells to both PM and their inorganic fraction.

Impact of indoor air pollution in nursery and primary schools on childhood asthma

Poor indoor air quality in scholar environments have been frequently reported, but its impact on respiratory health in schoolchildren has not been sufficiently explored. Thus, this study aimed to evaluate the associations between children's exposure to indoor air pollution (IAP) in nursery and primary schools and childhood asthma. Multivariate models (independent and multipollutant) quantified the associations of children's exposure with asthma-related health outcomes: reported active wheezing, reported and diagnosed asthma, and lung function (reduced FEV₁/FVC and reduced FEV₁). A microenvironmental modelling approach estimated individual inhaled exposure to major indoor air pollutants (CO₂, CO, formaldehyde, NO₂, O₃, TVOC, PM_2.5 and PM₁₀) in nursery and primary schools from both urban and rural sites in northern Portugal. Questionnaires and medical tests (spirometry pre- and post-bronchodilator) were used to obtain information on health outcomes and to diagnose asthma following the newest international clinical guidelines. After testing children for aeroallergen sensitisation, multinomial models estimated the effect of exposure to particulate matter on asthma in sensitised individuals. The study population were 1530 children attending nursery and primary schools, respectively 648 pre-schoolers (3-5 years old) and 882 primary school children (6-10 years old). This study found no evidence of a significant association between IAP in nursery and primary schools and the prevalence of childhood asthma. However, reported active wheezing was associated with higher NO₂, and reduced FEV₁ was associated with higher O₃ and PM_2.5, despite NO₂ and O₃ in schools were always below the 200 μg m^-3 threshold from WHO and National legislation, respectively. Moreover, sensitised children to common aeroallergens were more likely to have asthma during childhood when exposed to particulate matter in schools. These findings support the urgent need for mitigation measures to reduce IAP in schools, reducing its burden to children's health.

Liaison between exposure to sub-micrometric particulate matter and allergic response in children from a petrochemical industry city

The study examines the association between exposure to sub-micrometric Particulate Matter (PM₁) and allergic response in a group of sensitive young children (age: 2-10 years) from Ploiesti city, Romania. The city is the only urban agglomeration in Europe surrounded by four oil refineries. A panel study was conducted by collecting medical information from children with respiratory illnesses and atopy (n = 135). Hot Spot Analysis revealed the areas of the city that are susceptible to high levels of PM₁. We found a close interaction between exposure to PM₁ outdoor concentrations and various physiological changes and clinical symptoms in children including triggering of allergic reactions, rhinitis, alteration of lung function, upper and lower respiratory tract symptoms, and bronchial asthma. During the 2-year study period, the incidence of hospitalizations was 40.7%. Strong correlations (p < 0.001) were observed between the PM₁ exposure and hospitalizations, and exposure and Immunoglobulin E (IgE). PM₁ exposure was also correlated with eosinophils (p < 0.05). Another positive correlation was observed between hospitalizations and IgE levels (p < 0.05). The mean results of tested indicators were as follows: wheezing (5.3, 95% CI (1.4-1.8); Coeff. of var. (CV) = 30%), IgE (382, 95% CI (349-445); CV = 102%), and EO% (5.3, 95% CI (3.3-4.2); CV = 69.5%). We can conclude that exposure to PM₁ influenced the frequency of wheezing episodes, increased hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers. CAPSULE: Exposure to sub-micrometric particles (PM₁) influences the frequency of wheezing episodes, hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers.

Interactions of particulate matter and pulmonary surfactant: Implications for human health

Particulate matter (PM), which is the primary contributor to air pollution, has become a pervasive global health threat. When PM enters into a respiratory tract, the first body tissues to be directly exposed are the cells of respiratory tissues and pulmonary surfactant. Pulmonary surfactant is a pivotal component to modulate surface tension of alveoli during respiration. Many studies have proved that PM would interact with pulmonary surfactant to affect the alveolar activity, and meanwhile, pulmonary surfactant would be adsorbed to the surface of PM to change the toxic effect of PM. This review focuses on recent studies of the interactions between micro/nanoparticles (synthesized and environmental particles) and pulmonary surfactant (natural surfactant and its models), as well as the health effects caused by PM through a few significant aspects, such as surface properties of PM, including size, surface charge, hydrophobicity, shape, chemical nature, etc. Moreover, in vitro and in vivo studies have shown that PM leads to oxidative stress, inflammatory response, fibrosis, and cancerization in living bodies. By providing a comprehensive picture of PM-surfactant interaction, this review will benefit both researchers for further studies and policy-makers for setting up more appropriate regulations to reduce the adverse effects of PM on public health.

Levels of PM10 and PM2.5 and Respiratory Health Impacts on School-Going Children in Kenya

BACKGROUND

The respiratory system of children is vulnerable to exposure to particulate matter (PM) with a diameter of less than 2.5 and 10 μm (PM2.5 and PM10) or even lower.

OBJECTIVE

This study assessed PM10 and PM2.5 levels and respiratory health impacts on children in schools located in an industrialized suburb in Kenya.

METHOD

The PM10 and PM2.5 levels were sampled from five public primary schools in Athi River Township and a control school during the wet and dry seasons. Outdoor and classroom samples were collected concurrently on an 8-hour mean during school hours on two consecutive days in each school and analyzed using gravimetric techniques. Five hundred and seventy-eight (n = 578) pupils aged 9-14 years from these schools were also evaluated for symptoms of respiratory illnesses and lung function using a questionnaire and spirometric method, respectively, during the same periods.

RESULTS

Indoor median PM10 levels (μg/m3) ranged from 60.8-269.1 and 52.8-232.3 and PM2.5 values (μg/m3) of 17.7-52.4 and 28.5-75.5 during the dry and wet seasons, respectively. The control classrooms had significantly (p <0.05) lower median PM10 levels (μg/m3) of 5.2 and 4.2, and PM2.5 levels (μg/m3) of 3.5 and 3.0 during the respective seasons. Nearly all the classrooms in Athi River schools had PM2.5 and PM10 median levels that exceeded the World Health Organization (WHO) recommended levels. The indoor-to-outdoor ratios varied from 0.35-1.40 and 0.80-2.40 for PM10 and 0.30-0.80 and 0.80-1.40 for PM2.5 during the dry and wet seasons, respectively, suggesting higher levels in the classrooms during the wet season. The relative risk (RR) and odds ratio (OR) presented higher prevalence of respiratory diseases following PM exposure in all the Athi River schools than the control during the dry and wet seasons. At 95% CI, the RR and OR showed strong associations between high PM10 and PM2.5 levels and lung function deficits and vice versa. The association was more prevalent during the wet season.

CONCLUSIONS

The study calls for effective indoor air management programs in school environments to reduce PM exposure and respiratory health impacts.

PARTICIPANT CONSENT

Obtained.

ETHICS APPROVAL

The research permit and approvals were obtained from the University of Nairobi/Kenyatta National Hospital Ethics and Research Committee (KNH-UoN ERC Reference: P599/08/2016) and the National Commission for Science, Technology and Innovation (Reference: NACOSTI/P/18/4268/25724).

COMPETING INTERESTS

The authors declare no competing financial interests.

The response ranges of pulmonary function and the impact criteria of weather and industrial influence on patients with asthma living in Vladivostok

PURPOSE

To determine the response of pulmonary function (PF) to the influence of environmental factors in patients with different levels of asthma control.

MATERIALS AND METHODS

Patients with controlled (136 people) and uncontrolled (96 people) asthma living in the conditions of monsoon climate and technogenic pollution in Vladivostok were examined. Discriminant analysis that provides the basis for dividing initial data into classes, as according to standards and expert estimates, was used to calculate ranges of PF response in asthma patients. The selection of discriminant functions with the highest values of constant and coefficient made it possible to identify the optimal quantitative ranges.

RESULTS

Analysis of the discriminant value of Wilks' lambda (α) has shown that the intensity of PF response to climatic and technogenic factors varies depending on level of disease control (controlled asthma - α = 0.67-0.79, uncontrolled asthma - α =0.05-0.44). The criteria and ranges of PF response also differ depending on level of disease control. In controlled asthma, PF response reflects an adaptive-compensatory dependence. The reaction to the environmental factors is rather weak; therefore, it could be detected by only more sensitive examination method (body plethysmography). In uncontrolled asthma, the response to the influence of environment quality is active and could be clearly identified by spirography.

CONCLUSIONS

The climatic and technogenic environment of Vladivostok causes strong pathogenic impact on patients with uncontrolled asthma. The effects of dust fraction 0-1 μm, deeply penetrating into respiratory organs, and day-to-day variability of wind speed, which induces weather sensitivity, are particularly adverse.

Hardware Efficient Solutions for Wireless Air Pollution Sensors Dedicated to Dense Urban Areas

This paper proposes novel solutions for the application of air pollution monitoring systems in so called ‘smart cities’. A possibility of the implementation of a relatively dense network of wireless air pollution sensors that can collect and process data in real time was the motive behind our research and investigations. We discuss the concept of the wireless sensor network, taking into account the structure of the urban development in cities and we present a novel signal processing algorithm that may be used to control the communication scheme between particular sensors and an external network. We placed a special emphasis on the computational complexity to facilitate the implementation directly at the transistor level of particular sensors. The algorithm was verified using real data obtained from air pollution sensors installed in Krakow, Poland. To ensure sufficient robustness of the variability of input data, we artificially added high amplitude noise to the real data we obtained. This paper demonstrates the performance of the algorithm. This algorithm allows for the reduction of the noise amplitude by 23 dB and enables a reduction of the number of wireless communication sessions with a base station (BS) by 70%–80%. We also present selected measurement results of a prototype current-mode digital-to-analogue converter to be used in the sensors, for signal resolutions up to 7 bits.

Establishment of Regional Concentration-Duration-Frequency Relationships of Air Pollution: A Case Study for PM2.5

Poor air quality usually leads to PM2.5 warnings and affects human health. The impact of frequency and duration of extreme air quality has received considerable attention. The extreme concentration of air pollution is related to its duration and annual frequency of occurrence known as concentration-duration-frequency (CDF) relationships. However, the CDF formulas are empirical equations representing the relationship between the maximum concentration as a dependent variable and other parameters of interest, i.e., duration and annual frequency of occurrence. As a basis for deducing the extreme CDF relationship of PM2.5, the function assumes that the extreme concentration is related to the duration and frequency. In addition, the spatial pattern estimation of extreme PM2.5 is identified. The regional CDF identifies the regional extreme concentration with a specified duration and return period. The spatial pattern of extreme air pollution over 8 h duration shows the hotspots of air quality in the central and southwestern areas. Central and southwestern Taiwan is at high risk of exposure to air pollution. Use of the regional CDF analysis is highly recommended for efficient design of air quality management and control.

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

The fine particulate matter baseline (PMB), which includes PM_2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM_2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM_2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km² CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM_2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM_2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.

Protecting Children from Toxic Waste: Data-Usability Evaluation Can Deter Flawed Cleanup

Nearly 25 percent of US children live within 2 km of toxic-waste sites, most of which are in urban areas. They face higher rates of cancer than adults, partly because the dominant contaminants at most US hazardous-waste sites include genotoxic carcinogens, like trichloroethylene, that are much more harmful to children. The purpose of this article is to help protect the public, especially children, from these threats and to improve toxics-remediation by beginning to test our hypothesis: If site-remediation assessments fail data-usability evaluation (DUE), they likely compromise later cleanups and public health, especially children’s health. To begin hypothesis-testing, we perform a focused DUE for an unremediated, Pasadena, California toxic site. Our DUE methods are (a) comparing project-specific, remediation-assessment data with the remediation-assessment conceptual site model (CSM), in order to identify data gaps, and (b) using data-gap directionality to assess possible determinate bias (whether reported toxics risks are lower/higher than true values). Our results reveal (1) major CSM data gaps, particularly regarding Pasadena-toxic-site risks to children; (2) determinate bias, namely, risk underestimation; thus (3) likely inadequate remediation. Our discussion shows that if these results are generalizable, requiring routine, independent, DUEs might deter flawed toxic-site assessment/cleanup and resulting health threats, especially to children.

Impact of Open Burning Refuse on Air Quality: In the Case of "Hidar Sitaten" at Addis Ababa, Ethiopia

Open burning of refuse is one of the key sources that causes high air pollution in Metropolitan cities. This paper identifies pollutant concentration of particulate matter (PM_2.5) emission and air quality index categories with the peak hour interval on Hidar Sitaten day, and present analysis of air quality in Addis Ababa from August 2016 to November 2019. Daily records, with a 1-hour interval, of raw concentration of air pollutant and air quality index data, were obtained from the AirNow website of Addis Ababa central monitoring station. The data collected were analyzed using descriptive statistics of the mean air quality index and concentration of PM_2.5. Accordingly, the study revealed that the peak hour for high pollutant concentration emission ranges between 8 pm to 11 pm hours, and the mean air quality index was more than a moderate level. Particularly, on Hidar Sitaten in 2019 at 9 pm the maximum concentration of PM_2.5 was 8.6 times higher than WHO air quality guideline standard of daily allowance. The highest mean of air quality index and concentration of PM_2.5 recorded was 112 and 44.2 µg/m³ on 21 November 2017, respectively, and it was found to be unhealthy for sensitive groups. This implies that the concentration of PM_2.5 was harmful to people who are unusually sensitive to particulate pollution and have health problems. Therefore, public participation and strong regulations are needed on air quality management to strike a balance between a cultural practice of Hidar Sitaten and healthy air quality.

Long-Range Transport Influence on Key Chemical Components of PM2.5 in the Seoul Metropolitan Area, South Korea, during the Years 2012–2016

This study identified the key chemical components based on an analysis of the seasonal variations of ground level PM2.5 concentrations and its major chemical constituents (sulfate, nitrate, ammonium, organic carbon, and elemental carbon) in the Seoul Metropolitan Area (SMA), over a period of five years, ranging from 2012 to 2016. It was found that the mean PM2.5 concentration in the SMA was 33.7 μg/m3, while inorganic ions accounted for 53% of the total mass concentration. The component ratio of inorganic ions increased by up to 61%–63% as the daily mean PM2.5 concentration increased. In spring, nitrate was the dominant component of PM2.5, accounting for 17%–32% of the monthly mean PM2.5 concentrations. In order to quantify the impact of long-range transport on the SMA PM2.5, a set of sensitivity simulations with the community multiscale air-quality model was performed. Results show that the annual averaged impact of Chinese emissions on SMA PM2.5 concentrations ranged from 41% to 44% during the five years. Chinese emissions’ impact on SMA nitrate ranged from 50% (winter) to 67% (spring). This result exhibits that reductions in SO2 and NOX emissions are crucial to alleviate the PM2.5 concentration. It is expected that NOX emission reduction efforts in China will help decrease PM2.5 concentrations in the SMA.

Household Dust: Loadings and PM10-Bound Plasticizers and Polycyclic Aromatic Hydrocarbons

Residential dust is recognized as a major source of environmental contaminants, including polycyclic aromatic hydrocarbons (PAHs) and plasticizers, such as phthalic acid esters (PAEs). A sampling campaign was carried out to characterize the dust fraction of particulate matter with an aerodynamic diameter smaller than 10 µm (PM10), using an in situ resuspension chamber in three rooms (kitchen, living room, and bedroom) of four Spanish houses. Two samples per room were collected with, at least, a one-week interval. The PM10 samples were analyzed for their carbonaceous content by a thermo-optical technique and, after solvent extraction, for 20 PAHs, 8 PAEs and one non-phthalate plasticizer (DEHA) by gas chromatography-mass spectrometry. In general, higher dust loads were observed for parquet flooring as compared with tile. The highest dust loads were obtained for rugs. Total carbon accounted for 9.3 to 51 wt% of the PM10 mass. Plasticizer mass fractions varied from 5 µg g−1 to 17 mg g−1 PM10, whereas lower contributions were registered for PAHs (0.98 to 116 µg g−1). The plasticizer and PAH daily intakes for children and adults via dust ingestion were estimated to be three to four orders of magnitude higher than those via inhalation and dermal contact. The thoracic fraction of household dust was estimated to contribute to an excess of 7.2 to 14 per million people new cancer cases, which exceeds the acceptable risk of one per million.

Spatial Distribution, Chemical Speciation and Health Risk of Heavy Metals from Settled Dust in Qingdao Urban Area

Settled dust samples were collected from Qingdao urban area to analyze the spatial distribution, chemical speciation and sources of metals, and to evaluate the health risk of metals from atmospheric dust. The average contents of Hg, Cd, Cr, Cu, Ni, Pb and Zn in the atmospheric settled dust of Qingdao were 0.17, 0.75, 153.1, 456.7, 60.9, 176.0 and 708.3 mg/kg, respectively, which were higher than soil background values. The mean exchangeable metal and carbonated-associated fraction proportions of Cd, Zn and Pb were 43.6%, 26.1% and 15%, which implies that they have high mobility and bioavailability. Higher contents of heavy metals appeared in old city areas because of the historical accumulation of metals. Principal component analysis showed that combustion sources partially contributed to Pb, Zn and other trace metals. Hg, Pb and Zn mainly originated from business, human activities and municipal construction. Cd and Cu from settled dust of the old city originated from the erosion and ageing of construction materials. The non-carcinogenic risk rankings for the seven determined heavy metals were ingestion > dermal > inhalation. Cd, Cr and Ni from settled dust showed a low carcinogenic risk. The health risks of Cr, Cu and Pb were higher in old city areas and, therefore, need special attention.

Particulate matters and gaseous pollutants in indoor environment and Association of ultra-fine particulate matters (PM1) with lung function

Real-time particulate matters (PM₁, PM_2.5, PM₄, PM₇, PM₁₀, and TSP) with AEROCET 531S (USA), gaseous pollutants (NO₂ and TVOC) with Aeroquel 500 gas sampler (NZ) were measured from the indoor air of houses at four residential locations in Dhaka, Bangladesh. PM₁₀ samples were collected on quartz filters with a dual channel dust sampler (IPM-FDS 2510, India) for selected trace metal determination from five houses of Dhaka. Respiratory function of the occupants was assessed by using a peak expiratory flow meter (Rossmax PF 120). Mean PM₁, PM_2.5, and PM₁₀ concentrations were 46.1 ± 13.4, 76.0 ± 16.2, and 203.9 ± 44.8 μg m^-3, respectively. Higher enrichment factors of Pb, Zn, and Ni were found for traffic, industrial, and constructional activities. The correlation between indoor and outdoor PM_2.5 (R² = 0.42) and ratios (I/O < 1) suggesting indoor air was effected by outdoor air. The concentration of NO₂ (0.076 ± 0.007 ppm) and TVOC (90.0 ± 46.0 ppm) was found above than other studies. The average total hazard ratio (THR) in Dhaka was 9.06 and has the highest exposure to air pollutants (PM_2.5, PM₁₀, NO₂) in Khilkhet (THR 10.1) residents. A negative association between ultra-fine particles (PM₁) and peak flow rate measurements of the residents living in these houses indicates that inhalations of ultra-fine particles has great influence on the reduced lung efficiency.

Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, Norway

The very low-cost Nova particulate matter (PM) sensor SDS011 has recently drawn attention for its use for measuring PM mass concentration, which is frequently used as an indicator of air quality. However, this sensor has not been thoroughly evaluated in real-world conditions and its data quality is not well documented. In this study, three SDS011 sensors were evaluated by co-locating them at an official, air quality monitoring station equipped with reference-equivalent instrumentation in Oslo, Norway. The sensors’ measurement results for PM2.5 were compared with data generated from the air quality monitoring station over almost a four-month period. Five performance aspects of the sensors were examined: operational data coverage, linearity of response and accuracy, inter-sensor variability, dependence on relative humidity (RH) and temperature (T), and potential improvement of sensor accuracy, by data calibration using a machine-learning method. The results of the study are: (i) the three sensors provide quite similar results, with inter-sensor correlations exhibiting R values higher than 0.97; (ii) all three sensors demonstrate quite high linearity against officially measured concentrations of PM2.5, with R2 values ranging from 0.55 to 0.71; (iii) high RH (over 80%) negatively affected the sensor response; (iv) data calibration using only the RH and T recorded directly at the three sensors increased the R2 value from 0.71 to 0.80, 068 to 0.79, and 0.55 to 0.76. The results demonstrate the general feasibility of using these low cost SDS011 sensors for indicative PM2.5 monitoring under certain environmental conditions. Within these constraints, they further indicate that there is potential for deploying large networks of such devices, due to the sensors’ relative accuracy, size and cost. This opens up a wide variety of applications, such as high-resolution air quality mapping and personalized air quality information services. However, it should be noted that the sensors exhibit often very high relative errors for hourly values and that there is a high potential of abusing these types of sensors if they are applied outside the manufacturer-provided specifications particularly regarding relative humidity. Furthermore, our analysis covers only a relatively short time period and it is desirable to carry out longer-term studies covering a wider range of meteorological conditions.