Air Monitoring Stations Research Articles

INDICATIVE MEASUREMENTS OF FORMALDEHYDE CONTENT IN ATMOSPHERIC AIR OF MYKOLAEV

The article is devoted to the study of the possibility of using indicative measurements of formaldehyde (CH2O) content in the atmospheric air of the cities exposed to active vehicular transit flows. Motor transport is a fundamental factor of increased formaldehyde levels in the atmospheric air of such cities. Regional peculiarities affecting the increase of formaldehyde content and dispersion process in the surface layer of the atmosphere are added to the current situation, such as climatic and meteorological conditions, especially in summer, when high temperatures are combined with a lack of permanent winds; and the presence of a large unregulated automobile transit flow through the city. Within the framework of the Directive 2008/50/EU implementation into the national legislation of Ukraine it is necessary to introduce the ecological monitoring of the atmospheric air quality from the expansion of the fixed measurements by means of indicative measurements of air quality indices. The article raises the question of the consistency of the results of indicative and fixed measurements of formaldehyde content in the atmospheric air of cities. The purpose of the work is to study the peculiarities of the application of indicative measurements of formaldehyde content in the atmospheric air in the cities with heavy traffic, on the example of the city of Mykolaiv. The materials of the study are the results of measuring the formaldehyde content in the atmospheric air of the city by 7 stations of indicative measurements in Mykolaiv, as well as the results of determination of formaldehyde content at 4 stationary reference stations of atmospheric air monitoring in the city of Mykolaiv. It has been proved that there is a chronic excess of the maximum permissible concentrations of formaldehyde both during indicative measurements and at the fixed air monitoring stations in the airspace of the city of Mykolaiv. It has been shown that the results of indicative measurements of formaldehyde content in atmospheric air exceed in 1.5-1.6 times the corresponding values at fixed measurements, and the maximum values at fixed measurements exceed in 1.6-1.8 times the maximum values at indicative measurements. The necessity of calibration of indicative measurement stations in accordance with local conditions has been substantiated. The requirement of compulsory supplementing with indicative measurements of ecological monitoring of atmospheric air in the cities with intensive traffic flows has been shown.

The air pollution monitoring by sequential detection of transient changes

According to the World Health Organization, the air pollution is a serious problem that threatens the human health and the environmental balance. The goal of this paper is to study the on-line detection of the air pollution augmentation by monitoring the level of the micro particles concentrations in the outdoor air. The proposed statistical approach is tested by using the real PM10 pollution data, which are provided by the air monitoring stations located in Strasbourg. First, an autoregressive model with exogenous variables is designed to describe the PM10 concentrations of several stations. Next, a special sequential change detection test is used to detect a transient change in the PM10 concentrations. Two versions of this test are proposed: the centralized Finite Moving Average (FMA) test and the decentralized FMA test. The criterion is based on the minimization of the missed detection probability provided that the false alarm rate is upper bounded. The theoretical analysis and the comparison of the proposed approaches on real data are discussed.

A Study of PM 10, PM 2.5 Concentrations in the Atmospheric Air in Kraków, Poland

The air in Kraków is one of the most polluted in Europe. Polish standards for notification and alert levels for PM10 particulate matterare one of the the highest in Europe and exceed the recommendations of the World Health Organization (WHO) for safe daily concentrations by several times. The article presents the results of airborne dust measurements in three districts of Kraków. The study hasshown that the concentration of PM2.5 and PM10 particulate matter exceeded the annual average permissible levels. Empirical measurements of PM2.5 show significantly higher air pollution values than the data notified by stationary monitoring stations installed intwo locations. The high value of Pearson linear correlation coefficient confirms that weather conditions have a significant impact on airquality in Kraków. Wind speed in the autumn and winter seasons has by far the greatest influence on air quality in al. Krasińskiego,in the Ruczaj and Kurdwanów districts. A strong negative correlation was displayed. Manual measurements should be used to verifydata obtained from air monitoring stations. It is to be expected that, in Kraków, air purity will improve due to the implementation ofan anti-smog resolution and subsidies for the replacement of obsolete heating systems with more environmentally friendly solutions.

Towards Multi-Scale Space-Time Characteristics of Air Quality and Population Exposure Risk

In order to formulate policies to control regional air pollution and promote sustainable human–land system development, it is crucial to study the space–time distribution of air pollution and the population exposure risk. Existing studies are limited to individual fine particulate pollutants, which does not fully reflect the comprehensiveness of air quality. In addition, the spatiotemporal distribution of air quality and population exposure risk at different scales need to be further quantified. In this study, we used air monitoring station data and population spatial distribution data to analyze the spatiotemporal characteristics of air quality, including seasonal variations, variations before and during heating periods, and the occurrence frequency of priority pollutants in the traditional industrial areas of Northeast China in 2015. The population exposure–air pollution risk (PE-APR) model was used to calculate the population exposure risk at different spatial scales. The results suggest that GIS methods and air monitoring data help to establish a comprehensive air quality analysis framework, revealing spring–summer differentiation and the change trend of air quality with latitude. There are significant clustering features of air quality. A grid-scale population exposure–air pollution risk map is not restricted by administrative boundaries, which helps to discover high-risk areas of the main regional economic corridors and differences between inner cities and suburbs. This study provides a reference for understanding the space–time evolution of regional air pollution and formulating coordinated cross-regional air pollution strategies.

Air pollution and recurrence of cardiovascular events after ST-segment elevation myocardial infarction

Background and aimsThe effects of air pollution on discharged patients after ST-segment elevation myocardial infarction (STEMI) still remain uncertain. We examined the association between air pollutants and recurrent cardiovascular events in STEMI survivors. MethodsA retrospective cohort of 1641 discharged patients after STEMI was established in 2013 and followed until the end of 2019. Concentrations of air pollutants including fine particles <2.5 μm aerodynamic diameter (PM2.5), inhalable particles <10 μm aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and ozone (O3) measured by fixed ambient air monitoring stations were collected for exposure assessment. Multivariate-adjusted Cox proportional hazards models were used to estimate the increased risks of recurrent cardiovascular events. ResultsCompared with the first exposure quartile, for short-term exposure, hazard ratios (HRs) of recurrent cardiovascular events associated with the fourth exposure quartiles of PM2.5, PM10, NO2, SO2, CO, and O3 were 4.06 (95% CI: 2.62–6.30), 3.79 (95% CI: 2.57–5.58), 2.22 (95% CI: 1.67–2.94), 4.47 (95% CI: 3.08–6.48), 3.73 (95% CI: 2.54–5.48), and 5.35 (95% CI: 3.12–9.20), respectively. For long-term exposure, HRs associated with the fourth exposure quartiles of PM2.5, PM10, NO2, SO2, CO, and O3 were 6.43 (95% CI: 3.60–11.47), 4.77 (95% CI: 2.85–7.99), 3.22 (95% CI: 2.00–5.19), 3.20 (95% CI: 2.05–5.01), 4.44 (95% CI: 2.65–7.45), and 1.07 (95% CI: 0.80–1.42), respectively. The risks of recurrent cardiovascular events brought by air pollutants mostly increased nonlinearly. ConclusionsShort- and long-term exposure to air pollutants except ozone increases the risks of recurrent cardiovascular events in STEMI survivors. Better environmental policies and secondary prevention strategies should be developed to protect STEMI survivors as a susceptible population.

A GIS-Based Methodology to Determine Effect of Vehicular Pollution at Ward Level: Case Study of Jaipur City

To determine appropriate measures to reduce air pollution in any urban city, the first essential requirement is to estimate the spatial distribution of air pollution parameters in that area. In absence of air monitoring stations, alternative methods are required for the same. In the present work, a GIS-based methodology is presented to estimate the level of NO2 based on the road density of the road network of different categories of roads. Road network GIS layer and measured levels of the average value of NO2 for the year 2019 at 12 air pollution monitoring stations of Jaipur city are used to develop a large number of possible linear regression models for estimation of NO2 values based on road density values. Akaike Information Criterion (AIC) and adjusted r2 values are used to evaluate and arrive at the best-fitted model. Values from the cities of Jodhpur and Kota are used to validate the model. Using this model, NO2 levels are determined at 91 wards of Jaipur city and the output is compared with the similar map derived based on interpolation of NO2 values at the 12 monitoring stations. It is concluded that the methodology developed in this study generates better estimates of NO2 at the ward levels.

Prediction of COVID-19 Cases from the Nexus of Air Quality and Meteorological Phenomena: Bangladesh Perspective

An integrated approach was used to estimate the number of COVID-19 patients related to air quality and meteorological phenomena. Additionally, the air quality during pre-lockdown, lockdown, and post-lockdown stages of the COVID-19 pandemic was assessed to determine the effect of the infection containment measures taken in Bangladesh during the pandemic. The air quality was assessed based on measurements of nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), carbon monoxide (CO), black carbon, particulate matter (PM2.5 and PM10), and aerosol optical depth. Time-averaged maps of these parameters have been generated from NASA’s (National Aeronautics and Space Administration) website. Values of these parameters have also been collected from a continuous air monitoring station (CAMS) located in Bangladesh’s north-western city Rajshahi. The comparison shows that lockdown during the pandemic has brought significant improvements in air quality. However, the improvement was not sustained, since rapid increases in the air pollutant concentrations were observed in the post-lockdown period. Furthermore, Pearson correlation coefficients between each air quality variable and the daily new COVID-19 case rates were calculated. Different meteorological variables during the same time periods were determined to observe the variation in Rajshahi city. Relationships of these variables with the case rates were also established. Additionally, statistical analyses of the obtained data have been conducted for the measured variables using the Kruskal–Wallis test to assess the differences in the observed data among the pre-lockdown, lockdown, and post-lockdown periods. Dunn’s “Q” test was employed to test if the variables showed significance statistical difference during the Kruskal–Wallis test for pairwise comparisons. From the study, it has been observed that both meteorological variables and air quality parameters have significant relationship with daily new COVID-19 case rates. Both positive and negative associations of these parameters with the COVID-19 case rates have been observed. Very high air pollution has been observed in the post-lockdown period. Thus, it is recommended that appropriate authorities undertake corrective measures to protect the environment in cities with large populations. This study provides guidance for decision makers and health officials for future research and potentially reducing the spread of COVID-19.

Estimation of Prediction Error in Regression Air Quality Models

Combustion of energy fuels or organic waste is associated with the emission of harmful gases and aerosols into the atmosphere, which strongly affects air quality. Air quality monitoring devices are unreliable and measurement gaps appear quite often. Missing data modeling techniques can be used to complete the monitoring data. Concentrations of monitored pollutants can be approximated with regression modeling tools, such as artificial neural networks. In this study, a long-term set of data from the air monitoring station in Zabrze (Silesia, South Poland) was analyzed. Concentration prediction was tested for the main air pollutants, i.e., O3, NO, NO2, SO2, PM10, CO. Multilayer perceptrons were used to model the concentrations. The predicted concentrations were compared to the observed ones to evaluate the approximation accuracy. Prediction errors were calculated separately for the whole concentration range as well as for the specified concentration subranges. Some different measures of error were estimated. It was stated that the use of a single measure of the approximation accuracy may lead to incorrect interpretation. The application of one neural network to the entire concentration range results in different prediction accuracy in various concentration subranges. Replacing one neural network with several networks adjusted to specific concentration subranges should improve the modeling accuracy.

Exploring personal chemical exposures in China with wearable air pollutant monitors: A repeated-measure study in healthy older adults in Jinan, China.

The health impact of airborne contaminants has been challenging to assess due to current limitations in measurement technologies. The emergence of wearable passive samplers coupled with high resolution mass spectrometry (HR-MS) chemical analysis has enabled comprehensive characterization of personal exposures. We conducted a repeated-measure study among 84 older adults in Jinan, China, as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Study objectives were: 1) to characterize the occurrence, magnitude, and distribution of personal exposure to airborne contaminants; 2) to evaluate the temporal variation of chemical exposures across the study population; and 3) to identify behavioral and environmental factors that influence the observed variance in chemical exposures. The FreshAir wristband was worn by participants for three consecutive days each month from September 2018 to January 2019 and collected with paired time-activity logs. Passive air samplers were also deployed in parallel at a local outdoor air monitoring station. Spearman's Rho trend test and trajectory cluster analysis were used to identify exposure trends and variation patterns, respectively. Out of the 70 airborne compounds of potential concern screened, 26 compounds from 10 chemical classes were found to be above detection thresholds across >70% of the study population. Personal exposures were predominantly characterized by nine polycyclic aromatic hydrocarbons (PAHs), four phthalates, three nitroaromatics, and two volatile organic compounds (VOCs). Phthalate personal exposures were positively correlated with outdoor temperatures while the inverse relationship was observed for certain PAHs (p<0.05). Specifically, dimethyl phthalate (rs=0.31) decreased as temperatures declined, while nitrobenzene (rs=-0.35) and naphthalene (rs=-0.40) increased as temperatures decreased. Compared to levels measured at the outdoor air monitoring site, personal exposure of phthalates was elevated (p<0.05) and hexachlorobutadiene was lower across participants (p<0.01). Personal exposure of these chemicals was further found to be weakly associated with daily duration participants spent outdoors. Individuals formed distinct clusters based on trajectories of chemical exposures across the sampling period (September to January), potentially suggestive of distinct emission sources. In conclusion, we demonstrate the feasibility of characterizing the occurrence and magnitude of personal exposure to airborne chemical contaminants using passive wristband samplers. The temporal variability of these personal exposure profiles was highlighted and with distinct trends identified across different groups of individuals. Future studies will integrate this data with other omics datasets collected from this population of Chinese older adults to investigate associations between exposure profiles and health relevant biomarkers, to provide evidence in feasibility of disease prevention through environmental improvements.

Temporal air quality (NO2, O3, and PM10) changes in urban and rural stations in Catalonia during COVID-19 lockdown: an association with human mobility and satellite data.

In this study, changes in air quality by NO2, O3, and PM10 in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown with respect to pre-lockdown and to previous years (2018 and 2019) were evaluated. Selected air monitoring stations included 3 urban (Gràcia, Vall d’Hebron, and Granollers), 1 control site (Fabra Observatory), 1 semi-urban (Manlleu), and 3 rural (Begur, Bellver de Cerdanya, and Juneda). NO2 lockdown levels showed a diminution, which in relative terms was maximum in two rural stations (Bellver de Cerdanya, − 63% and Begur, − 61%), presumably due to lower emissions from the ceasing hotel and ski resort activities during eastern holidays. In absolute terms and from an epidemiologic perspective, decrease in NO2, also reinforced by the high amount of rainfall registered in April 2020, was more relevant in the urban stations around Barcelona. O3 levels increased in the transited urban stations (Gràcia, + 42%, and Granollers, + 64%) due to the lower titration effect by NOx. PM10 lockdown levels decreased, mostly in Gràcia, Vall d’Hebron, and Granollers (− 35, − 39%, and − 39%, respectively) due to traffic depletion (− 90% in Barcelona's transport). Correlation among mobility index in Barcelona (− 100% in retail and recreation) and contamination was positive for NO2 and PM10 and negative for O3 (P < 0.001). Satellite images evidenced two hotspots of NO2 in Spain (Madrid and Barcelona) in April 2018 and 2019 that disappeared in 2020. Overall, the benefits of lockdown on air quality in Catalonia were evidenced with NO2, O3 and PM10 levels below WHOAQG values in most of stations opposed to the excess registered in previous years.Graphical abstract Supplementary InformationThe online version of this article (10.1007/s11356-021-17137-7) contains supplementary material, which is available to authorized users.

Spatial variation of ambient PM2.5 and PM10 in the industrial city of Arak, Iran: A land-use regression

Land-use regression models (LUR) were developed to estimate the spatial patterns and seasonal variability of particulate matter with aerodynamic diameter ≤2.5 mm and ≤10 mm (PM2.5 and PM10) in the industrial city of Arak, Iran. PM2.5 and PM10 data were obtained from the air monitoring stations belonging to the Department of Environment from 2015 to 2020. Spatial interpolation of particles by ordinary kriging method was conducted to estimate pollutant variability in unmeasured areas. The predicted particles concentrations (PM2.5 and PM10) of the three hundred points were subsequently collected from the kriging map and accepted as a response variable in final LUR models. All available Geographic Information System (GIS) predictors in vector format were applied as potentially independent variables. The leave-one-out cross-validation (LOOCV) method was used to evaluate the performance of the LUR models. The annual mean PM2.5 and PM10 concentrations were 22.92 and 49.78 μg/m3 across the city. LUR models explained 88.5% of the variances (R2) for PM2.5 and 54.5% for PM10. For the PM2.5 and PM10 models, the mean LOOCV R2 values were 0.83 and 0.45, respectively. There were some variations between both LUR models for PM2.5 and PM10, but the heating and non-heating season models were nearly similar to the annual LUR models. These LUR models provide a spatial distribution of particles at the home addresses and predict concentrations for no-monitored areas. High cross-validation of this method confirms the robustness of the suggested approach to forecasting particle concentrations in another place.

Exposure to air pollution is associated with congenital anomalies in the population born by in vitro fertilization

BackgroundCongenital anomalies (CAs) are the leading causes for children's disabilities and mortalities worldwide. The associations between air pollution and CAs are not fully characterized in fetuses born by in vitro fertilization (IVF) who are at high risk of congenital anomalies. MethodsWe conducted a cross-sectional study including 16,971 IVF cycles from three hospitals in Hebei Province, China, 2014–2019. Air quality data was obtained from 149 air monitoring stations. Individual average daily concentrations of PM2.5, PM10, NO2, SO2, CO, and O3 were estimated by spatiotemporal kriging method. Exposure windows were divided into 5: preantral follicle period, antral follicle period, germinal period, embryonic period and early fetal period. Logistic generalized estimating equations were used to estimate the associations between air pollutants and overall or organ-system specific congenital anomalies. Negative control exposure method was used to detect and reduce bias of estimation. ResultsWe found increasing levels of PM2.5 and PM10 were associated with higher risk of overall congenital anomalies during early fetal period, equating gestation 10–12 weeks (OR: 1.05, 95% CI: 1.02–1.09, p = 0.013 for a 10 μg/m3 increase of PM2.5; OR: 1.03, 95% CI: 1.01–1.06, p = 0.021 for a 10 μg/m3 increase of PM10). Cleft lip and cleft palate were associated with PM10 in germinal period and early fetal period. The CAs of eye, ear, face and neck were related to CO in preantral follicle stage. We did not find an association between chromosome abnormalities and air pollution exposure. ConclusionsWe concluded that ambient air pollution was a risk factor for congenital anomalies in the fetuses conceived through IVF, especially exposure in early fetal period.

Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey

As in other countries of the world, the Turkish government is implementing many preventive partial and total lockdown practices against the virus’s infectious effect. When the first virus case has been detected, the public authorities have taken some restriction to reduce people and traffic mobility, which has also turned into some positive affect in air quality. To this end, the paper aims to examine how this pandemic affects traffic mobility and air quality in Istanbul. The pandemic does not only have a human health impact. This study also investigates the social and environmental effects. In our analysis, we observe, visualize, compare and discuss the impact of the post- and pre-lockdown on Istanbul’s traffic mobility and air quality. To do so, a geographic information system (GIS)-based approach is proposed. Various spatial analyses are performed in GIS with the statistical data used; thus, the environmental effects of the pandemic can be better observed. We test the hypothesis that this has reduced traffic mobility and improved air quality using traffic density cluster set and air monitoring stations (five air pollutant parameters) data for five months. The results shows that there are positive changes in terms of both traffic mobility and air quality, especially in April–May. PM10, SO2, CO, NO2 and NOx parameter values improved by 21.21%, 16.55%, 18.82%, 28.62% and 39.99%, respectively. In addition, there was a 7% increase in the average traffic speed. In order for the changes to be permanent, it is recommended to integrate e-mobility and sharing systems into the current transportation network.

COVID-19 Highlights an Environmental Injustice: Influence of Energy Insecurity on Urban Outdoor Air Pollution during Community Lockdown in South-Central Chile

BACKGROUND AND AIM: In south-central Chile, outdoor air pollution primarily originates as household air pollution from wood burning for heating. The effect of COVID-19 lockdowns on ambient air pollution levels in urban south-central Chile, may therefore be different from trends observed in cities where transportation/industrial emission sources dominate. This study investigates the impact of COVID-19 lockdown on outdoor fine (PM2.5) and coarse (PM10) particulate matter concentrations in Temuco, Chile. METHODS: Hourly PM2.5 and PM10 measurements from six air monitoring stations (three reference-grade beta attenuation monitors and three low-cost sensors) in commercial and low- and middle-income residential areas of Temuco were compared during winter months (March-September) in 2019 and 2020 (spanning COVID-19 lockdown). RESULTS:Average monthly PM2.5 concentrations in low-income residential areas of Temuco during winter 2019 ranged from (36-53 µg/m3), approximately twice as high as concentrations in commercial areas (12-29 µg/m3). During COVID-19 lockdown, average monthly ambient PM2.5 concentrations in a commercial and middle-income residential area of Temuco were up to 50% higher (12 µg/m3 to 18 µg/m3) and 59% higher (22 µg/m3 to 35 µg/m3) than 2019 levels, respectively. Conversely, PM2.5 levels decreased by up to 52% (43 µg/m3 to 21 µg/m3) in three low-income neighborhoods. The night-time mass percent of PM10 that was PM2.5 in April 2020 increased by 48% above April 2017-2019 proportions (50% to 74%) in a commercial area. CONCLUSIONS:Wood burning was responsible for a significantly higher proportion of ambient PM2.5 pollution in commercial areas and a middle-income neighborhood of Temuco during COVID-19 lockdown, compared to winter months in 2019. Energy insecure households likely refrained from wood heating during lockdown, leading to PM2.5 concentration declines in low-income neighborhoods. To reduce ambient air pollution and energy insecurity resulting from reliance on wood for heating in south-central Chile, affordability of clean heating fuels (e.g. electricity, liquefied petroleum gas) should be a policy priority. KEYWORDS: COVID-19, residential heating, household air pollution, particulate matter, energy insecurity, PM2.5

Associations of long-term PM10 exposure with cardiovascular mortality and morbidity in South Korea: investigating the regional heterogeneity

BACKGROUND AND AIM: Long-term exposure to ambient PM has long been linked to cardiovascular diseases. However, fewer studies have investigated non-fatal outcomes, especially in Asian regions, and little is known whether long-term health effects of PM are identical across the country. This study aimed to estimate the effects of long-term PM10 exposure on cardiovascular disease incidence and death in South Korea. We further examined effect modification by regional characteristics. METHODS: The study population comprised 317,204 subjects from the National Health Insurance Service-National Sample Cohort (2006-2015) residing in 120 districts where urban air monitoring stations are located. Incidence of cardiovascular disease was defined as the first occurrence of a hospital visit or admission among those with no previous history of cardiovascular disease. For each year of follow-up, we estimated a five-year moving window of past exposure to PM10 for each subject at the district-level. Time‐varying Cox proportional hazards models were used to assessing the relationship between PM10 and cardiovascular events. We conducted stratification analyses to explore effect modifications by metropolitan city indicator, district-level socioeconomic status indicators, and medical index. RESULTS:Each 10 μg/m³ increase in PM10 was associated with increased risk of both cardiovascular morbidity (hazard ratio, HR, 1.04; 95% CI, 1.02-1.07) and mortality (HR, 1.14; 95% CI, 1.03, 1.26). Subgroup analyses yielded competing results between cardiovascular mortality and morbidity. Effect estimate for cardiovascular morbidity was higher in the non-metropolitan area while the association with cardiovascular morbidity was higher in the metropolitan area. Districts with lower socioeconomic status had a larger increase in the risk of morbidity and had a lower increase in the risk of mortality CONCLUSIONS:This study supports the evidence that PM10 has long-term effects on cardiovascular health in South Korea. Regional vulnerability to PM10 might differ by the severity of the health outcome. KEYWORDS: Particulate matter, Long-term exposure, Cardiovascular diseases, Environmental justice, Environmental epidemiology

Effect modification of omega-3 fatty acids on short-term associations between ambient air temperature and heart rate variability

BACKGROUND AND AIM: Although the biological mechanisms remain uncertain, non-optimal air temperatures have been associated with cardiovascular mortality. Dietary intake of omega-3 fatty acids (n-3 FA) has been correlated with cardiovascular health. This panel study aimed to examine whether n-3 FA would modify associations between ambient air temperature and autonomic function measured by changes in heart rate variability (HRV). METHODS: Six-two healthy adults (age: 25–55 years) residing in North Carolina, U.S. were recruited into low (n=28) and high (n=34) omega-3 groups based on dietary n-3 FA intake and blood levels of omega-3 index. Each participant underwent 3-5 examinations separated by at least one week between October 2016 and September 2019. HRV was measured using 5-minute resting electrocardiography recorded at each examination. Daily meteorological data were obtained from a central air monitoring station. We applied mixed-effects models with a distributed lag non-linear approach to assess associations between air temperature (lag 0-6 days) and HRV stratified by omega-3 levels. RESULTS:We observed inverse U-shape relationships between HRV indices and temperature in the low omega-3 group, which were significant for high temperatures. No associations were observed in the high omega-3 group. An increase from 10 °C (approximate optimum temperature) to the 95th percentile (28 °C) of temperature was associated with decreases in standard deviation of NN intervals [SDNN, -40.6% (95% CI: -63.7, -2.7)], root mean square of successive RR interval differences [RMSSD, -63.9% (95% CI: -82.7, -24.8)], and high-frequency power [HF, -82.7% (95% CI: -97.2, 5.2)]. The between-group differences were significant for RMSSD and HF. CONCLUSIONS:Non-optimal air temperatures, especially high temperatures were associated with decreased parasympathetic autonomic function that might explain the temperature effects on cardiovascular events. In addition, n-3 FA intake was associated with beneficial effects on autonomic function against non-optimal temperatures. This abstract does not necessarily reflect EPA policy. KEYWORDS: Cardiovascular diseases, Climate, Environmental epidemiology, Short-term exposure, Temperature

Evidence of the correlation between a city's air pollution and human health through soft computing.

Huge quantities of pollutants are released into the atmosphere of many cities every day. These emissions, due to physicochemical conditions, can interact with each other, resulting in additional pollutants such as ozone. The resulting accumulation of pollutants can be dangerous for human health. To date, urban pollution is recognized as one of the main environmental risk factors. This research aims to correlate, through soft computing techniques, namely Artificial Neural Networks and Genetic Programming, the data of the tumours recorded by the Local Health Authority of the city of Benevento, in Italy, with those of the pollutants detected in the air monitoring stations. Such stations can monitor many pollutants, i.e. NO2, CO, PM10, PM2.5, O3 and Benzene (C6H6). Assuming possible effects on human health in the medium term, in this work we treat the data relating to pollutants from the 2012–2014 period while, the tumour data, provided by local hospitals, refer to the time interval 2016–2018. The results show a high correlation between the cases of lung tumours and the exceedance of atmospheric particulate matter and ozone. The explicit genetic programming knowledge representation allows also to measure the relevance of each considered pollutant on human health, evidencing the major role of PM10, NO2 and O3.

The effect of air pollution on the respiratory system in preschool children with contribution of urban heat islands and geographic data - the aim of the study and methodological assumptions.

It has been proven that outdoor and indoor air pollutants can cause adverse health effects and are able to promote the onset of atopic diseases. The current manuscript is focused on methodological issues. The aim of the study is to determine the effect of air pollution, urban environment, and urban heat islands (UHIs) on the occurrence of respiratory diseases including allergic rhinitis, asthma and wheezing in preschool children. The study group consists of 276 five-year-old children attending randomly selected kindergartens in the urban and rural areas of the Łódź Voivodeship. The questionnaire including data on the child's state of health and socio-economic data will be filled by the caregivers. The children will undergo skin prick testing and the measurement of volatile organic compounds in exhaled breath. The key components of air pollution - particulate matter (PM) will be measured by personal meters. The PM sampling planned in the study will take 12 h for PM2.5 and for PM10 alike. Data on the level of outdoor air pollution will be collected based on the results obtained from air monitoring stations. The impact of air pollution, UHIs and the environment on the respiratory system and the presence of allergies in children, including chronic respiratory diseases, will be assessed. The project results will provide a scientific basis for the development of preventive programs in the population of children in the Łódź Voivodeship, adapted to the real health needs of society. Int J Occup Med Environ Health. 2021;34(4):453-60.

The association between postpartum depression and air pollution during pregnancy and postpartum period: a national population study in Taiwan

Epidemiological evidence shows the association between air pollutants and several mental health outcomes, including depression, sleep disturbance, dementia, childhood neurodevelopment and suicide. Pregnant women are believed to be more susceptible and vulnerable to environmental pollutants, and postpartum depression (PPD) is a prevalent debilitating mental disorder. However, data on the effects of exposure to air pollution during pregnancy and postpartum period on the risk of PPD remain limited. This study aimed to evaluate the association between exposure to ambient air pollution during pregnancy and postpartum period and the incidence of PPD. The Taiwan Birth Cohort Study recruited representative 12% of all newborn in 2005 and their mothers by two-stage stratified sampling, including 21 248 mother–infant pairs. The occurrence of PPD was assessed by a self-reported questionnaire. Exposure to air pollutants during pregnancy and postpartum period was estimated using hybrid kriging/land-use regression (LUR) and integrated LUR-machine learning model based on data from the air monitoring stations. Logistic regression was then conducted to determine adjusted odds ratios (aORs) of PPD in relation to air pollutants. A total of 21 188 women were included in the final analysis, among whom 3,648 (17.2%) developed PPD within 6 months postpartum. The occurrence of PPD was significantly related to exposure to ambient concentrations of nitrogen dioxide (NO2) during first trimester after adjustment [aOR: 1.081 per interquartile range (10.67 ppb), 95% confidence interval: 1.003, 1.165], but not to particulate matter ⩽2.5 µm in diameter or carbon monoxide. Exposure to ambient NO2 during early pregnancy was significantly related to the occurrence of PPD among the women investigated in this population-based study.

Impact of the first induced COVID-19 lockdown on air quality in Israel

The coronavirus disease 2019 (COVID-19) induced a lockdown that has resulted in a sharp reduction in air and motor traffic and industrial activities. This in turn led to a reduction in air pollution around the world. It is important to quantify the extent of that reduction in order to estimate the weight of the impact of air and motor traffic and industrial activities over the total variation of air quality. An assessment of the extent of air pollution is aimed at facilitating the crafting of policies toward the reduction of pollution and the improvement in air quality. The aim of this paper is to evaluate the impact of the COVID-19 outbreak on air pollution in Israel. Particularly, we focus on Haifa and Greater Tel-Aviv (Gush-Dan), two regions with high air pollution, while examining different types of air monitoring stations. The period to which we refer to is March 8, 2020, to May 2, 2020. The results reveal two main findings: (1) During the COVID-19 lockdown, pollution emissions decreased relative to the same period in 2019. The biggest reduction was observed in NOx, which, on average, was 41%. Surprisingly, ground-level ozone (O3) increased, and appeared to behave similarly to the ozone weekend effect. (2) The total percentage variation in pollution emission that was explained by the lockdown was at most 26%. By adding the meteorological conditions (which included measures of wind direction, wind speed, and temperature) as a factor in addition to the lockdown effect, this percent increased to 47%.