Different Types Of Air Pollutants Research Articles

A deep learning model incorporating frequency domain information for ultra multi-step air pollutant forecasting: A case study of Shanghai

Multi-step forecasting of air pollutants extends the horizon for individuals and authorities to take informed actions for mitigating potential risks. Due to the instability of air pollutants, current research primarily focuses on relatively short-term forecasting, with achieving ultra multi-step forecasting presenting a significant challenge. In response to this issue, this study proposes a novel model: Frequency Enhanced Decomposed Temporal Convolution Networks (Fed-TCN) to achieve ultra multi-step forecasting. This study applies time-frequency transformation to explore the frequency characteristics of air pollutants and extract long-term patterns. These patterns are then fed into TCN to enhance the accuracy of ultra multi-step forecasting. Extensive experiments were conducted on eight air pollutants at four monitoring stations in Shanghai. The results indicate variations in forecastable ranges for different pollutants. NO and NOx can be forecasted up to one week, while NO2, CO, SO2, and O3 require forecasting within 1–3 days (approximately 24–72 steps ahead). Furthermore, PM2.5 and PM10 can only be forecasted for short-term periods, not exceeding 12 h. When compared to baseline models, Fed-TCN achieves a 4.3%–11% lower Mean Absolute Error. Moreover, Fed-TCN provides insights into the contribution of pollutant composition patterns to forecasting accuracy. In general, daily patterns, semi-commuting patterns, and residuals contribute 68.8%–81.7% to ultra multi-step forecasting. The proposed method is applicable for ultra multi-step forecasts of other regions and different types of air pollutants.

Reflection of prenatal exposure to wildfire smoke on reduced birth weight in 2015-2019

Wildfire smoke contains many different types of air pollutants which are cause for concern. Studies on epidemiology have identified correlations between PM2.5 exposure to wildfire smoke and mortality, respiratory and cardiovascular morbidities, and may result in a reduction in birth weight. However, evidence from Indonesia is limited. For this study, a retrospective cohort epidemiological study was undertaken to quantify the Indonesian population’s exposure to wildfire-PM2.5. We present 9652 (88%) records of newborns to identify an association between fire-sourced PM2.5 and birth weight in Palangka Raya, Indonesia from 2015 to 2019. On an annual basis, geospatial, and season variations in wildfire-PM2.5 concentrations were observed using a satellite-based dataset from CAMS and used for gestational exposure to wildfire smoke. Applying a general linear model with birth weight (yi) as a continuous outcome, the relationship between PM2.5 exposure and low birth weight was examined. In addition, the binary outcome of low birth weight was analysed. A statistically significant difference in the birth weight reduction between infants delivered to mothers exposed to high levels of wildfire smoke and those exposed to low levels of wildfire smoke was observed over the entire time frame (2015-2019) (ρ-value < 0.001). In comparison to infants born to mothers exposed to lower concentrations, the birth weight of infants delivered to mothers exposed to high concentrations of PM2.5 in the third trimester decreased by 19.96%. A 1.9% reduction in birth weight could be caused by exposure during the fire-prevalent in the first trimester of pregnancy (ρ-value < 0.001). Since an estimation model predicted a 10 g/m3 increase in PM2.5 exposure between the first and last trimesters of pregnancy, variations in the second trimester did not significantly affect the association (ρ-value = 0.761). This emphasizes the significance of foetal development during these two trimesters. Exposure to pollution from wildfires contributes significantly to the global burden of newborns’ birth weight.

Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review.

The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs. CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.

Short-term exposure to various ambient air pollutants and emergency department visits for cause-stable ischemic heart disease: a time-series study in Shanghai, China

Studying the impact of local meteorological conditions and air pollution on cardiovascular disease is crucial for reducing the burden of cardiovascular disease. However, there have been few studies on the acute effects of various air pollutants on stable ischemic heart disease (SIHD), and the effects of these factors are not well defined and require further investigation. We performed a time-series study aimed at exploring the association between short-term exposure to various air pollutants and emergency department (ED) visits for SIHD during 2013–2020 in Baoshan District Renhe Hospital of Shanghai, China. The associations between air pollution (NO2, PM2.5, PM10, SO2 O3-8 h and CO) and ED visits were analyzed using quasi-Poisson regression. Subgroup and sensitivity analyses were conducted. From 2013 to 2020, a total of 18,241 ED visits for SIHD were recorded. Elevated PM2.5, PM10, NO2, SO2 and CO were significantly associated with increased ED visits for SIHD at lag (0, 5), lag 0, lag (0-4, 01-03), lag (0-3, 5, 01-03) and lag (3-5). When the concentration of O3-8 h was lower than the threshold recommended by the WHO, exposure to O3-8 h was associated with a slightly decreased risk of SIHD. Moreover, the relationship between different types of air pollution and the frequency of ED visits exhibited variations based on gender, age, and seasonality. This study suggests that short-term exposure to PM2.5, PM10, NO2, SO2 and CO might induce SIHD, especially in old females. Air pollution control measures should be encouraged to prevent the occurrence and development of SIHD.

When and where to exercise: An assessment of personal exposure to urban tropical ambient airborne pollutants in Singapore

BackgroundPhysical activity is associated with health benefits and has been shown to reduce mortality risk. However, exposure to high levels of ambient fine particulate matter (PM2.5) during exercise can potentially reduce the health benefits of physical activity. This study aims to assess and compare the PM2.5 concentrations of different exercise venues in Singapore by their location attributes and time of day. MethodsPersonal PM2.5 exposures (μg/m3) at 24 common outdoor exercise venues in Singapore over 49 sampling days were collected using real-time personal sensors from September 2017 to January 2020. Wilcoxon rank-sum test and Kruskal–Wallis test were used to compare PM2.5 concentrations between different timings (peak (0700–0900; 1800–2000) vs. non-peak (0600–0700; 0900–1800; 2000–2300); weekend vs. weekday), and location attributes (near major roads (<50 m) vs. away from major roads (≥50 m)). Multivariable linear regression models were used to assess the associations between location attributes, timings and ambient PM2.5 with personal PM2.5 concentration, adjusting for potential confounders. ResultsCompared with peak hours, exercising during non-peak hours was associated with a significantly lower PM2.5 exposure (median, 17.8 μg/m3 during peak vs. 14.5 μg/m3 during non-peak; P = 0.006). Exercise venues away from major roads have significantly lower PM2.5 concentrations as compared to those located next to major roads (median, 14.4 μg/m3 away from major roads vs. 18.5 μg/m3 next to major roads; P < 0.001). Individuals who exercised in parks experienced the highest PM2.5 exposure (median, 55.0 μg/m3) levels in the afternoon during 1400–1500. Furthermore, ambient PM2.5 concentration was significantly and positively associated with personal PM2.5 exposure (β = 0.85, P < 0.001). ConclusionsOur findings suggest that exercising outdoors in the urban environment exposes individuals to differential levels of PM2.5 at different times of the day. Further research should investigate a wider variety of outdoor exercise venues, explore different types of air pollutants, and consider the varying activity patterns of individuals.

Green Walls as Mitigation of Urban Air Pollution: A Review of Their Effectiveness

Mitigation of urban air pollution has been constrained by the availability of urban spaces for greening. Green walls offer the prospect of greening spaces and surfaces without requiring large areas. Green walls can largely be divided into green facades where the aboveground parts of plants rooted in soil and pots grow directly on, and living walls holding bags, planter tiles, trays and vessels containing substrates in which plants are grown. Green facades and living walls can be continuous or modular with repeating units that can be assembled for extension. This review aims to present the effectiveness of green walls in removing different types of air pollutants in indoor and outdoor environments. It examined more than 45 peer-reviewed recently published scholarly articles to achieve the aim. It highlights that most of the studies on green walls focus on particulate matter removal and green walls could effectively remove particulate matter though the effectiveness varies with plant types, air humidity, rainfall and its intensity, leaf area index and contact angle, green wall surface coverage ratio, as well as the height of green walls. Increasing the height of green walls and optimizing their distance from roadsides could promote the deposition of particulate matter. Washing off could regenerate plant surfaces for capturing pollutants. Green walls are also effective in removing NO2, O3, SO2 and CO. Indoor active living walls, when properly designed, could have air purifying performance comparable to a HVAC system. The performance of green walls could be optimized through polycultures, selection of plants, surface coverage and height, and air inflow.

Causal effects of air pollution on mental health among Adults——An exploration of susceptible populations and the role of physical activity based on a longitudinal nationwide cohort in China

Long-term exposure to air pollutants is likely to be associated with mental disorders, but relevant studies remain limited and inconsistent, and evidence to assess causality is particularly lacking, especially in developing countries. In addition, there are few studies on the role of physical activity in this relationship. We investigated the causal relationship between air pollutant exposure and mental health among Chinese adults and whether physical activity could play a positive role in this relationship.Using the balanced panel data for 2014 and 2016 from the China Family Panel Study, a representative Chinese national cohort study, we selected and validated appropriate instrumental variable to explore the causal relationship between air pollution and mental health and explored the moderating effect of physical activity using an instrumental variable fixed effects model (IVFE) in a counterfactual causal inference framework. PM2.5 and ground surface ozone were selected as proxies for different types of air pollutants and extended the interpretability by studying them for populations with different characteristics.A total of 21,944 participants were included in this study. In the IVFE model, we found that both PM2.5 and ground surface ozone significantly negatively affected mental health, and that habitual physical activity counteracted this negative effect regardless of different types of air pollution. We also found that the findings held for adults with different characteristics.The findings suggest that habitual physical activity may offset the deterioration of mental health in adults in developing countries due to air pollution, regardless of age, gender, income, and the presence of chronic diseases.

The Impact of Low-Carbon City Pilot Policies on Air Quality: Quasi-Natural Experimental Evidence from China

Low-carbon cities have become a new trend in regional development around the world. Whether they can improve the environment in China, especially the air quality, remains to be tested. In this paper we take low-carbon city construction as a quasi-natural experiment and empirically test the net effects, influencing factors, and dynamic effects of low-carbon city construction on air quality by constructing a multistage propensity score matching and Difference-in-Differences model. After a series of robustness tests, the following conclusions are drawn: first, low-carbon city construction reduces the regional Air Quality Index, inhalable particulate matter, fine particulate matter, and NO2 concentrations. Among them, the construction effect in 2017 was the most significant. Therefore, it is necessary to continue to promote low-carbon city policies and accurately identify different types of air pollutants to improve the overall effectiveness of low-carbon city policies. Second, temperature, humidity, wind level, and other meteorological factors, as well as gross domestic product for the proportion of secondary industry, will affect air quality. Therefore, it is necessary to comprehensively consider meteorological, economic, social, and other influencing factors in an early stage of the construction of the next batch of low-carbon cities, so as to avoid falling into the trap of “building first and managing later”. Third, the impact of secondary industry on air quality is significantly greater than that of tertiary industry. Therefore, the upgrading of industrial structure promoted by low-carbon city policy is effective in improving air quality. Fourth, the construction of low-carbon cities in western China has the most significant impact on air quality improvement. Therefore, the joint prevention and control mechanism of air pollution control in urban agglomeration should be established.

Spatial heterogeneity of air pollution statistics in Europe

Air pollution is one of the leading causes of death globally, and continues to have a detrimental effect on our health. In light of these impacts, an extensive range of statistical modelling approaches has been devised in order to better understand air pollution statistics. However, the time-varying statistics of different types of air pollutants are far from being fully understood. The observed probability density functions (PDFs) of concentrations depend very much on the spatial location and on the pollutant substance. In this paper, we analyse a large variety of data from 3544 different European monitoring sites and show that the PDFs of nitric oxide (NO), nitrogen dioxide (NO_2) and particulate matter (PM_{10} and PM_{2.5}) concentrations generically exhibit heavy tails and are asymptotically well approximated by q-exponential distributions with a given width parameter lambda. We observe that the power-law parameter q and the width parameter lambda vary widely for the different spatial locations. For each substance, we find different patterns of parameter clouds in the (q, lambda ) plane. These depend on the type of pollutants and on the environmental characteristics (urban/suburban/rural/traffic/industrial/background). This means the effective statistical physics description of air pollution exhibits a strong degree of spatial heterogeneity.

STUDY THE EFFECTS OF (8-OXO-GUANINE DNA GLYCOSYLASE 1 RS1052133) POLYMORPHISM ON GENE EXPRESSION AS A PREDISPOSING FACTOR FOR DNA MUTATION IN MIDLAND REFINERIES COMPANY-DURA REFINERY WORKERS

Background: Refineries are exposed to different types of air pollutants, among them, polycyclic aromatic hydrocarbons (PAHs), they are a group of over hundred different kinds of hazardous organic chemicals (pollutants), which are formed primarily during the incomplete burning of oil, gas and coal. PAHs are metabolized in different organs of human body especially in the liver leading to generation of mutagenic metabolites, of them, the reactive oxygen species, which damage DNA by binding with guanine base leading to formation of 8-hydroxyguanine. The 8-oxo-guanine DNA glycosylase (hOGG1 rs1052133) gene, is a regulatory gene binds with 8-oxo-DG in the DNA to initiate base excision repair (BER) pathway. Objective: To investigate the role of (hOGG1 rs1052133) gene polymorphism in single nucleotide polymorphism repair. Methods: One hundred sixty-eight (168) subjects were participated in this study. They were they divided into three groups (country side, office workers and field workers). PAHs were analyzed in all participant by Gas Chromatography Coupled with a Mass Spectrophotometry GC/MS. SNP for hOGG1 and gene expression were detecting by real time polymerase chain reaction and quantitative polymerase chain reaction for each subject respectively. Results: PAH were detected in blood serum of refineries workers and not detected in country side participants. The level of hOGG1 gene expression was higher in GG genotype than GC and CC genotype. Conclusion: Refineries worker are at high risk of developing malignant transformation and serious disease due to high level of PAH compared to other population. hOGG1 plays an important role in DNA repair following DNA mutation. Keywords: Poly cyclic aromatic hydrocarbons, HOGGI, gene expression Citation: Al-Ani RH, Al-Wasiti EA, Shukur AS. Study the Effects of (8-oxo-Guanine DNA Glycosylase 1 rs1052133) Polymorphism on Gene Expression as a Predisposing Factor for DNA Mutation in Midland Refineries Company-Dura Refinery Workers. Iraqi JMS. 2022; 20(1): 90-97. doi: 10.22578/IJMS.20.1.12

Assessment of Pulmonary Function Test among Petrol Pump Workers in Bankura District

Background and Aim: Health problems posed by the pollutants at the working environment of an individual are linked to the nature and level of exposure to these hazardous chemicals. Petrol pump workers are exposed to high level of different types of air pollution along with petrol and diesel vapors exhibit a number of effects on the respiratory functions. The main objective of the study was to assess the pulmonary functions in petrol pump workers (filling attendants) who are continuously exposed to petrol/diesel vapors during duty hours and compare with the normal healthy individuals. Materials and Methods: This is a cross-sectional study was conducted at seven different petrol pumps of Bankura and 65 petrol pump workers (filling attendants) were included. Each subject’s age, smoking habits, the duration of exposure, health conditions, BMI and BP were recorded. Their PFT were assessed using spirometer and was compared with 65 normal healthy individuals. Results: A significant decrease in the values of Tidal Volume, Vital Capacity, Peak Expiratory Flow Rate, Maximum Voluntary Ventilation, Respiratory Rate and Oxygen saturation in petrol pump workers when compared to control group. Significant increase in BP was observed in case of petrol pump workers and reduction in muscle strength. Conclusion: The present findings demonstrate the adverse effects of petrol and diesel vapors and fumes, hydrocarbons markedly decreased the pulmonary functions.

Atmospheric oxidizing capacity in autumn Beijing: Analysis of the O3 and PM2.5 episodes based on observation-based model

Atmospheric oxidizing capacity (AOC) is the fundamental driving factors of chemistry process (e.g., the formation of ozone (O3) and secondary organic aerosols (SOA)) in the troposphere. However, accurate quantification of AOC still remains uncertainty. In this study, a comprehensive field campaign was conducted during autumn 2019 in downtown of Beijing, where O3 and PM2.5 episodes had been experienced successively. The observation-based model (OBM) is used to quantify the AOC at O3 and PM2.5 episodes. The strong intensity of AOC is found at O3 and PM2.5 episodes, and hydroxyl radical (OH) is the dominating daytime oxidant for both episodes. The photolysis of O3 is main source of OH at O3 episode; the photolysis of nitrous acid (HONO) and formaldehyde (HCHO) plays important role in OH formation at PM2.5 episode. The radicals loss routines vary according to precursor pollutants, resulting in different types of air pollution. O3 budgets and sensitivity analysis indicates that O3 production is transition regime (both VOC and NOx-limited) at O3 episode. The heterogeneous reaction of hydroperoxy radicals (HO2) on aerosol surfaces has significant influence on OH and O3 production rates. The HO2 uptake coefficient (γHO2) is the determining factor and required accurate measurement in real atmospheric environment. Our findings could provide the important bases for coordinated control of PM2.5 and O3 pollution.

RISK OF AIR POLLUTION FROM INDUSTRIALIZATION TOWARDS HEALTH: A COMPARATIVE RISK ASSESSMENT

ABSTRACT Palm oil mills generate large quantities of waste and by-products which consequently cause air pollution. Previous studies had investigated about the exposures of different types of air pollution toward certain age groups such as children, as well as targeting specific diseases. In this article, the assessment on the posed risk of air pollution in Sepang, Malaysia palm oil mills toward health are being investigated. In particular, we study the particulate matter of PM2.5 and PM10, in which exposures toward these fine particles may cause toxic effects in blood and other illnesses such as cancer that may lead to mortality. Our aim is to estimate the number of premature deaths in Malaysia due to all causes of ambient air pollutants and avoidable mortality rate using the comparative risk assessment framework. We also quantified the relative risk and attributable fraction by adopting the framework of air pollution health-risk assessment. Our findings estimated that there would be around 5692 for PM10 and 9287 for PM2.5 premature deaths in Malaysia due to all causes of ambient air pollutants. However, with the decrease in 20% of the pollutant’s concentration, there would be an avoidable mortality of 18.75% or 1067 and 17.98% or 1670 due to PM10 and PM2.5, respectively. This model can be extended into more detail assessment of each contributing particles for air pollution, as well as to water pollution.

A hybrid integrated deep learning model for predicting various air pollutants

ABSTRACT Air pollution is a significant urban issue, with practical applications for pollution control, urban environmental management planning, and urban construction. However, owing to the complexity and differences in spatiotemporal changes for various types of pollution, it is challenging to establish a framework that can capture the spatiotemporal correlations of different types of air pollution and obtain high prediction accuracy. In this paper, we proposed a deep learning framework suitable for predicting various air pollutants: a graph convolutional temporal sliding long short-term memory (GT-LSTM) model. The hybrid integrated model combines graph convolutional networks and long short-term networks based on a strategy with temporal sliding. Herein, the graph convolution networks gather neighbor information for spatial dependency modeling based on the spatial adjacency matrices of different pollutants and the graph convolution operator with parameter sharing. LSTM networks with a temporal sliding strategy are used to learn dynamic air pollution changes for temporal dependency modeling. The framework was applied to predict the average concentrations of PM2.5, PM10, O3, CO, SO2, and NO2 in the Bejing-Tianjin-Hebei (BTH) region for the next 24 hours. Experiments demonstrated that the proposed GT-LSTM model could extract high-level spatiotemporal features and achieve higher accuracy and stability than state-of-the-art baselines. Advancement in this methodology can assist in providing decision support capabilities to mitigate air quality issues.

Association between exposure level of air pollutants and incidence rate of circulatory disease in residential and industrial areas of South Korea

ABSTRACT This study investigated the correlation between the concentration of air pollutants in two metropolitan cities, Seoul and Incheon, located in South Korea with different urban characteristics and the number of patients with circulatory diseases among residents exposed to air pollution. The residential area was selected as Eunpyeong-gu of Seoul Metropolitan City and the industrial area as Jung-gu of Incheon Metropolitan City. The evaluation period is between 2015 and 2016. The relevant data provide by the Korea governmental agency were analysed to derive the purpose of this study. It was confirmed that PM10, PM2.5, nitrogen dioxide, carbon monoxide, and sulfur dioxide among air pollutants had an increasing impact on the incidence rate of circulatory diseases. The PM2.5 was positively correlated with the incidence rate of all circulatory diseases in residential area (p < 0.05). The carbon monoxide showed a positive correlation with circulatory system diseases except for hypertension in residential area. (p < 0.05). The sulfur dioxide was positively correlated with all circulatory diseases in both residential and industrial area (p < 0.05). Based on the results obtained from this study, it was found that there are different types of air pollutants that affect circulatory diseases in residential and industrial areas.

The association between Air Pollution and Kidney Function: results from the Korea National Health and Nutrition Examination Survey

BACKGROUND AND AIM: The incidence and prevalence of CKD are increasing worldwide. Recent epidemiological studies have shown that air pollution also contributes the renal health, however few studies have demonstrated the differential effects of different types of air pollutants on renal function. In this study, we evaluated the association between air pollution exposure, deterioration of kidney function and CKD prevalence using the 7th Korean National Health and Nutrition Examination Survey (KNHANES) data. METHODS: The KNHANES data (2016–2018) were used to estimate estimated glomerular filtration rate (eGFR) by the CKD–EPI equation and the CKD was defined as an eGFR of 60 mL/min/1.73 m2. Air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) were obtained from the AirKorea. Given the characteristic of this data (stratified, multistage, and cluster sampling design), all analyses were performed in a complex survey design. We conducted multivariate linear regression and logistic regression analysis to assess the association between air pollution exposure and kidney function after adjusting the covariates including gender, body mass index, education level, household income, smoking status, frequency of drinking, underling diseases, and serum triglyceride. RESULTS:A total of 15,308 adults aged 20 or older were included in the analyses. The exposure to PM2.5, PM10, NO2 and CO was associated with lower eGFR (PM2.5: -4.67, 95% CI: -6.16, -3.18; PM10: -2.19, 95% CI: -2.84, -1.54; NO2: -1.56, 95% CI: -2.16, -0.97; CO: -1.34, 95% CI: -1.96, -0.71). The prevalence of CKD was related to PM2.5 (OR: 1.97, 95% CI: 1.14, 3.42) and PM10 (OR: 1.45, 95% CI: 1.10, 1.91). association. CONCLUSIONS:Annual exposure to PM2.5, PM10, NO2, and CO was associated with a higher risk of lower eGFR and prevalent CKD. A significant exposure-response association was observed between PM2.5, PM10, and CO exposure and low eGFR. KEYWORDS: Air pollution, Chronic kidney disease, Glomerular filtration rate, Republic of Korea

Long-term exposure to fine particulate matter, lung function and cognitive performance: A prospective Dutch cohort study on the underlying routes

BackgroundExposure to fine particulate matter and black carbon is related to cognitive impairment and poor lung function, but less is known about the routes taken by different types of air pollutants to affect cognition. ObjectivesWe tested two possible routes of fine particulate matter (PM2.5) and black carbon (BC) in impairing cognition, and evaluated their importance: a direct route over the olfactory nerve or the blood stream, and an indirect route over the lung. MethodsWe used longitudinal observational data for 49,705 people aged 18+ from 2006 to 2015 from the Dutch Lifelines cohort study. By linking current home addresses to air pollution exposure data from ELAPSE in 2010, long-term average exposure to PM2.5 and BC was assessed. Lung function was measured by spirometry and Global Initiative (GLI) z-scores of forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) were calculated. Cognitive performance was measured by cognitive processing time (CPT) assessed by the Cogstate Brief Battery. Linear structural equation modeling was performed to test direct/indirect associations. ResultsHigher exposure to PM2.5 but not BC was related to higher CPT and slower cognitive processing speed [Total Effect PM2.5: FEV1 model = 8.31 × 10−3 (95% CI: 5.71 × 10−3, 10.91 × 10−3), FVC model = 8.30 × 10−3 (95% CI: 5.69 × 10−3, 10.90 × 10−3)]. The direct association of PM2.5 constituted more than 97% of the total effect. Mediation by lung function was low for PM2.5 with a mediated proportion of 1.32% (FEV1) and 2.05% (FVC), but higher for BC (7.01% and 13.82% respectively). DiscussionOur results emphasise the importance of the lung acting as a mediator in the relationship between both exposure to PM2.5 and BC, and cognitive performance. However, higher exposure to PM2.5 was mainly directly associated with worse cognitive performance, which emphasises the health-relevance of fine particles due to their ability to reach vital organs directly.

Air quality improvement from COVID-19 lockdown: evidence from China.

As we move through 2020, our world has been transformed by the spread of COVID-19 in many aspects. A large number of cities across the world entered “sleep mode” sequentially due to the stay-at-home or lockdown policies. This study exploits the impact of pandemic-induced human mobility restrictions, as the response to COVID-19 pandemic, on the urban air quality across China. Different from the “traditional” difference-in-differences analysis, a human mobility-based difference-in-differences method is used to quantify the effect of intracity mobility reductions on air quality across 325 cities in China. The model shows that the air quality index (AQI) experiences a 12.2% larger reduction in the cities with lockdown. Moreover, this reduction effect varies with different types of air pollutants (PM2.5, PM10, SO2, NO2, and CO decreased by 13.1%, 15.3%, 4%, 3.3%, and 3.3%, respectively). The heterogeneity analysis in terms of different types of cities shows that the effect is greater in northern, higher income, more industrialized cities, and more economically active cities. We also estimate the subsequent health benefits following such improvement, and the expected averted premature deaths due to air pollution declines are around 26,385 to 38,977 during the sample period. These findings illuminate a new light on the role of a policy intervention in the pollution emission, while also providing a roadmap for future research on the pollution effect of COVID-19 pandemic.

T125. AN ASSOCIATION BETWEEN OZONE, BUT NOT OTHER AIR POLLUTANTS, AND DAILY NUMBER OF VISITS TO PSYCHIATRIC EMERGENCY SERVICES

BackgroundAir pollution is a major environmental risk to health. Exposure to xenobiotic heavy metals such as lead and cadmium—constituents of air pollution such as particulate matter and nitrogen and sulfur oxides, organic solvents, and other environmental pollutants—could be component causes for schizophrenia and other psychotic disorders. Long-term exposure to ambient air pollution could be an independent risk factor for mental health disorders. Recent studies analysing the association between daily levels of air pollutants and hospital admissions for mental disorders showed significant results for different pollutants considered both for admissions for generic mental disorders and for specific diagnoses such as schizophrenia, depression and substance abuse. Aim of the present study is to investigate the associations between daily levels of air pollutants (particulate matter, ozone, carbon monoxide, nitrogen dioxide) and daily admissions for mental disorders to the emergency department of two general hospitals in Umbria region (Italy)MethodsWe collected data about daily admissions to psychiatric emergency services of two general hospitals, daily levels of respirable particular matter (PM10 and PM2.5), ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and meteorological data (daily average temperature, pressure, humidity, and maximum and average wind speed) for the time period 1 January 2015 until 31 December 2016 (731 days). We used air monitoring data for the different types of air pollutants which were averaged across up to 16 monitor stations dispersed in the region. We assessed the impact of an increase in air pollutants on the number of daily admissions using a time-series econometric framework.ResultsA total of 1860 cases of emergency department admissions for mental disorders were recorded over the study period.We observe a statistically significant impact of O3 levels on daily admissions. The estimated coefficient of O3 is statistically significant at the 1 percent level. According to our results, an increase of one µg/ m3 of O3 concentration (relative to the average concentration of the last 20 days) results in 0.013 more admissions to the hospitals.All other pollutants are not significantly associated with the number of daily admissions.DiscussionWe observed a statistically significant association of daily ozone levels and daily number of admissions to psychiatric emergency services. Ozone is a component of photochemical smog and a powerful oxidant, and is considered as one of the most important air pollutants. Ozone may have a relevant interference with CNS physiology, and its exposure may be linked to brain disease and contribute to inflammation and oxidative stress.Ozone exposure may be considered a potential environmental risk factor for impaired mental health. Epidemiological studies found evidence that ozone exposure may affect autism spectrum disorders, lead to motor disorders and cognitive impairment, and have an influence on the incidence of depression and suicide. In recent studies ozone air levels showed an association with increased risk of an emergency department visit for depression. This is one of the first studies worldwide investigating the association between daily concentration of air pollutants and the daily number of visits to a psychiatric emergency unit.Our results add to previous literature on existing evidence for air pollution to have a role in the cause or worsening of mental distress and psychiatric disorders. Contrary to our hypothesis, we did not find a positive association between most of the air pollutants considered in our study. This is in contrast with previous literature on this subject.This could be explained by the methodological limitations of our study.

Spatially differentiating the effects of long-term air pollution on specific causes of death from cardiovascular and respiratory mortality in Hong Kong: a territory-wide register-based study

Previous studies have evaluated the effects of air pollution on various causes of death. However, there are few studies directly differentiating the regional effects of air pollution on specific causes of death from cardiovascular and respiratory mortality. It is important to target specific diseases and air pollutants for environmental management, in order to develop a sustainable environment. Therefore, a territory-wide register-based study was developed with cause-specific mortality data in Hong Kong between 2007 and 2014 (n = 257,090). Five groups of decedents were directly compared with the two control groups (cardiovascular and respiratory deaths), separately, based on binomial logistic regressions. Three air pollutants (NO2, PM2.5, black carbon (BC)) were selected to evaluate how spatial distribution of long-term air pollution exposure can induce the difference in mortality risks from two control groups. Based on the results, different air pollutants can contribute to different impact on mortality risk. PM2.5 and BC contributed to higher effects on mortality associated with mental and behavioral disorders than those linked to cardiovascular and respiratory diseases. BC can contribute to a higher mortality risk for mortality associated with diseases of the nervous and digestive systems than with respiratory diseases. There was also a stronger influence of neighborhood PM2.5 on mortality associated with diseases of the genitourinary system than with cardiovascular and respiratory diseases, and a stronger impact of neighborhood NO2 and BC on cancer-related mortality than on respiratory mortality. In conclusion, several air pollutants have greater impact on cause-specific mortality than cardiovascular and respiratory mortality. Therefore, it is necessary to have a comprehensive and systematic investigation to evaluate how different types of air pollutants influence various types of cause-specific mortality. In addition, specific health protocols, enhancement of urban design and improvement of environmental hygiene should be conducted for specific types of air pollution and deprived populations, rather than targeting solely the people with cardiorespiratory diseases.