Acute myocardial infarction and COPD attributed to ambient SO2 in Iran

Long-term effects of air quality on hospital readmission for heart failure in patients with acute myocardial infarction

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization.

METHODS

We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups.

RESULTS

After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 μg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 μg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064).

CONCLUSION

NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 μg/m3 and PM10 exceeds 55 μg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran

In big and industrial cities of developing countries, illness and mortality from long-term exposure to air pollutants have become a serious issue. This research was carried out in 2019-2020 to estimate the health impacts of PM10, NO2 and O3 pollutants by using AirQ+ and R statistical programming software in Arak, Isfahan, Tabriz, Shiraz, Karaj, and Mashhad. Mortality statistics, number of people in required age groups, and amount of pollutants were gathered respectively from different agencies like Statistics and Information Technology of the Ministry of Health, Statistical Center, and Department of Environment and by using Excel, the average 24-hour and 1-hour concentration and maximum 8-hour concentration for PM10, NO2 and O3 pollutants were gathered. We used linear mixed impacts model to account for the longitudinal observations and heterogeneity of the cities. The results of the study showed high number of deaths due to chronic bronchitis in adults, premature death of infants, and respiratory diseases in Mashhad. This research highlights the importance of estimation of health impacts from exposure to air pollutants on residents of the studied cities.

In-depth characterization of particulate matter in a highly polluted urban environment at the foothills of Himalaya-Karakorum Region

In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth's system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10 µm, i.e., PM10 are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM10 samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24 h average PM10 mass concentration along with standard deviation was investigated to be 586.83 ± 217.70 µg/m3, which was around 13 times greater than the permissible limit of the world health organization (45 µg/m3) and 4 times the Pakistan national environmental quality standards for ambient PM10 (150 µg/m3). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90 µg/m3, respectively. Water-soluble ions K+ and OC show a substantial association (R = 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of PM10, which are vital for preparing an air quality management plan in the urban environment of Peshawar.

Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Dispersion of SO2 emissions in a gas refinery by AERMOD modeling and human health risk: a case study in the Middle East

This study aimed to model the dispersion of emitted SO2 from stacks and flares in one of the largest Gas Refinery Companies in the Middle East . Pollutant emission coefficients and air pollution's various sources contributions were determined based on the collected data after measuring SO2 concentrations in a fixed monitoring station (stack) and across different distances from it for a year. The SO2 release pattern was simulated, and annual pollutant concentrations in average periods of 1-hr and 24-hr were predicted using AERMOD 8.9.0. The maximum simulated ambient SO2 were 27,447 and 4592 µg/m3 in average sampling times of 1-hr and 24-hr, respectively. The hazard quotient of 95% percentile for children, teenagers, and adults due to inhalation of SO2 was more than one.The maximum concentration of SO2 in the 1-hour and 24-hour period in the study area was higher than the amount introduced by Iran's clean air standard and the WHO standard.

Investigating seasonal air quality variations consequent to the urban vegetation in the metropolis of Faisalabad, Pakistan

Urban atmospheric pollution is global problem and and have become increasingly critical in big cities around the world. Issue of toxic emissions has gained significant attention in the scientific community as the release of pollutants into the atmosphere rising continuously. Although, the Pakistani government has started the Pakistan Clean Air Program to control ambient air quality however, the desired air quality levels are yet to be reached. Since the process of mapping the dispersion of atmospheric pollutants in urban areas is intricate due to its dependence on multiple factors, such as urban vegetation and weather conditions. Therefore, present research focuses on two essential items: (1) the relationship between urban vegetation and atmospheric variables (temperature, relative humidity (RH), sound intensity (SI), CO, CO2, and particulate matter (PM0.5, PM1.0, and PM2.5) and (2) the effect of seasonal change on concentration and magnitude of atmospheric variables. A geographic Information System (GIS) was utilized to map urban atmospheric variables dispersion in the residential areas of Faisalabad, Pakistan. Pearson correlation and principal component analyses were performed to establish the relationship between urban atmospheric pollutants, urban vegetation, and seasonal variation. The results showed a positive correlation between urban vegetation, metrological factors, and most of the atmospheric pollutants. Furthermore, PM concentration showed a significant correlation with temperature and urban vegetation cover. GIS distribution maps for PM0.5, PM1.0, PM2.5, and CO2 pollutants showed the highest concentration of pollutants in poorly to the moderated vegetated areas. Therefore, it can be concluded that urban vegetation requires a rigorous design, planning, and cost-benefit analysis to maximize its positive environmental effects.

Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forcasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran)

Air pollution is one of the major concerns for the population and the environment due to its hazardous effects. PM10 has affected significant scientific and regulatory interest because of its strong correlation with chronic health such as respiratory illnesses, lung cancer, and asthma. Forcasting air quality and assessing the health impacts of the air pollutants like particulate matter is crucial for protecting public health.This study incorporated weather, traffic, green space information, and time parameters, to forcst the AQI and PM10. Traffic data plays a critical role in predicting air pollution, as it significantly influences them. Therefore, including traffic data in the ANN model is necessary and valuable. Green spaces also affect air quality, and their inclusion in neural network models can improve predictive accuracy. The key factors influencing the AQI are the two-day lag time, the proximity of a park to the AQI monitoring station, the average distance between each park and AQI monitoring stations, and the air temperature. In addition, the average distance between each park, the number of parks, seasonal variations, and the total number of vehicles are the primary determinants affecting PM10.The straightforward effective Multilayer Perceptron Artificial Neural Network (MLP-ANN) demonstrated correlation coefficients (R) of 0.82 and 0.93 when forcasting AQI and PM10, respectively. This study also used the forcasted PM10 values from the ANN model to assess the health effects of elevated air pollution. The results indicate that elevated levels of PM10 can increase the likelihood of respiratory symptoms. Among children, there is a higher prevalence of bronchitis, while among adults, the incidence of chronic bronchitis is higher. It was estimated that the attributable proportions for children and adults were 6.87% and 9.72%, respectively. These results underscore the importance of monitoring air quality and taking action to reduce pollution to safeguard public health.

Global Chronic obstructive pulmonary disease burden attributable to air pollution from 1990 to 2019

BACKGROUND

The disease burden attributable to chronic obstructive pulmonary disease (COPD) is significant worldwide. Some studies have linked exposure to air pollution to COPD, but there has been little research on this.

METHODS

We aimed to assess the COPD-related disease burden attributable to air pollution from multiple epidemiological perspectives. This study conducted a three-stage analysis. Firstly, we reported on the burden of disease worldwide in 2019 by different subgroups including sex, age, region, and country. Secondly, we studied the trends in disease burden from 1990 to 2019. Finally, we explored the association of some national indicators with disease burden to look for risk factors.

RESULTS

In 2019, the death number of COPD associated with air pollution accounted for 2.32% of the total global death, and the number of DALY accounted for 1.12% of the global DALY. From 1990 to 2019, the death number of COPD associated with air pollution increased peaked at 1.41 million in 1993, fluctuated, and then declined. We found the same temporal pattern of DALY. The corresponding age-standardized rates had been falling. At the same time, the burden of COPD associated with air pollution was also affected by some national indicators.

CONCLUSIONS

This study indicated that air pollution-related COPD contributed to a significant global disease burden. We called for health policymakers to take action and interventions targeting vulnerable countries and susceptible populations.

Human exposure to dust and heavy metals in industrial regions and its relationship with the prevalence of multiple sclerosis disease

In recent decades, multiple sclerosis (MS) diseases have been significantly prevalent in some industrial areas of Iran, such as steel industrial areas in Isfahan province (central Iran). In this study, the environmental impacts of two steel mill factories in Isfahan province and their effects on the spread of MS in the region were investigated. To examine the extent of exposure, seasonal dust samples were collected from 15 sites around the two investigated factories. The annual dust deposition rate (DDR) was then determined and the concentrations of lead (Pb), cadmium (Cd), nickel (Ni), cobalt (Co), and manganese (Mn) in the dust samples were measured. Furthermore, the concentration of the mentioned elements was determined in the nail samples taken from 40 MS patients and 40 healthy people (control) living in the study region. The interpolated map extracted from the DDR values showed the highest dust deposition around the two studied steel factories, which decreases with increasing distance from them. The enrichment factor (EF) of heavy metals was the highest at the distance between the two steel factories, decreasing by moving away from them which indicate that these two steel factories are the source of investigated heavy metals in the region. The statistical analysis also revealed significant differences (P < 0.01) between the concentration of heavy metals measured in nail samples taken from MS patients and healthy people. The mean Pb concentration measured in the nail sample taken from MS patients was more than 18 times that of healthy people (93.45 and 5.02 mg/kg, respectively). These results revealed a buildup of heavy metals in the body of MS patients much more than usual, originating from the activities of two investigated steel companies in the region.

Assessment of Low-Level Air Pollution and Cardiovascular Incidence in Gdansk, Poland: Time-Series Cross-Sectional Analysis

(1) Background: More than 1.8 million people in the European Union die every year as a result of CVD, accounting for 36% of all deaths with a large proportion being premature (before the age of 65). There are more than 300 different risk factors of CVD, known and air pollution is one of them. The aim of this study was to investigate whether daily cardiovascular mortality was associated with air pollutants and meteorological conditions in an urban environment with a low level of air pollution. (2) Methods: Data on daily incidence of strokes and myocardial infarctions in the city of Gdansk were obtained from the National Health Fund (NHF) and covered the period from 1 January 2014 to 31 December 2018. Data on the level of pollution, i.e., SO2, NO, NO2, NOx, CO, PM10, PM2.5, CO2, O3 and meteorological conditions came from the foundation: Agency of Regional Air Quality Monitoring in the Gdańsk metropolitan area (ARMAG). Using these data, we calculated mean values with standard deviation (SD) and derived the minimum and maximum values and interquartile range (IQR). Time series regression with Poisson distribution was used in statistical analysis. (4) Results: Stroke incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.019 (95%CI: 1.001–1.036), 1.036 (95%CI: 1.008–1.064) and 1.017 (95%CI: 1.000–1.034) for every increase in IQR by 14.12, 14.62 and 22.62 μg/m3, respectively. Similarly, myocardial infarction incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.030 (95%CI: 1.011–1.048), 1.053 (95%CI: 1.024–1.082) and 1.027 (95%CI: 1.010–1.045) for every increase in IQR by 14.12, 14.62 and 22.62 μg/m3, respectively. Both PM10 and PM2.5 were positively associated with myocardial infarction incidence. (5) Conclusions: In this time-series cross-sectional study, we found strong evidence that support the hypothesis that transient elevations in ambient PM2.5, PM10, NO2, SO2 and CO are associated with higher relative risk of ischemic stroke and myocardial infarction incidents.

Association between ambient carbon monoxide levels and hospitalization costs of patients with myocardial infarction: Potential effect modification by ABO blood group

Previous researches have reported the association between air pollution and various diseases. However, few researches have investigated whether air pollutants are associated with the economic loss resulting from patients' hospitalization, especially the economic loss of hospitalization due to acute cardiovascular events. The purpose of our research was to explore the association between the levels of carbon monoxide (CO), taken as an index of pollution, and the hospitalization costs of myocardial infarction (MI), and the potential effect modification by the ABO blood group. A total of 3237 MI inpatients were included in this study. A multiple linear regression model was used to evaluate the association between ambient CO levels and hospitalization costs of MI patients. Moreover, we performed stratified analyses by age, gender, body mass index (BMI), season, hypertension, and ABO blood types. There was a positive association between the levels of CO in the air and the costs of hospitalization caused by MI. Furthermore, such association was stronger in males, BMI ≥25, <65 years, with hypertension, and non-O blood group. Interestingly, we found the association was particularly significant in patients with blood group B. Overall, our study first found that ambient CO levels could have an impact on the hospitalization costs for MI patients, and those with blood group B can be more sensitive.

Comparison of machine learning and deep learning techniques for the prediction of air pollution: a case study from China

The adverse effect of air pollution has always been a problem for human health. The presence of a high level of air pollutants can cause severe illnesses such as emphysema, chronic obstructive pulmonary disease (COPD), or asthma. Air quality prediction helps us to undertake practical action plans for controlling air pollution. The Air Quality Index (AQI) reflects the degree of concentration of pollutants in a locality. The average AQI was calculated for the various cities in China to understand the annual trends. Furthermore, the air quality index has been predicted for ten major cities across China using five different deep learning techniques, namely, Recurrent Neural Network (RNN), Bidirectional Gated Recurrent unit (Bi-GRU), Bidirectional Long Short-Term Memory (BiLSTM), Convolutional Neural Network BiLSTM (CNN-BiLSTM), and Convolutional BiLSTM (Conv1D-BiLSTM). The performance of these models has been compared with a machine learning model, eXtreme Gradient Boosting (XGBoost) to discover the most efficient deep learning model. The results suggest that the machine learning model, XGBoost, outperforms the deep learning models. While Conv1D-BiLSTM and CNN-BiLSTM perform well among the deep learning models in the estimation of the air quality index (AQI), RNN and Bi-GRU are the least performing ones. Thus, both XGBoost and neural network models are capable of capturing the non-linearity present in the dataset with reliable accuracy.

Ambient air pollutants and respiratory health outcomes in Tabriz and Urmia, two metropolises of Iran

Polluted air affects human life and it is crucial to assess air pollutants to inform policy and protect human lives. In this study, we sought to assess the respiratory outcomes associated with PM₁₀, O₃, SO₂, and NO₂ in the Iranian population. The required data, which included concentrations of air pollutants, meteorology, and population size, were obtained from the department of environment and meteorological organizations. The validity of the data was evaluated, and appropriate calculations were conducted on the data to extract the required values and parameters for modeling (using the AirQ2.2.3). This study was conducted in two megacities of Iran (Tabriz and Urmia) with over 2 million population. The annual averages of SO₂, NO₂, and PM₁₀ concentrations were 9, 73, and 43 μg/m³ in Tabriz and 76, 29, and 76 μg/m³ in Urmia, respectively. Excess deaths from respiratory diseases associated with PM₁₀ and SO₂ were estimated to be 33.1 and 1.2 cases in Tabriz and 31.6 and 24.7 cases in Urmia, respectively. The proportions of hospitalizations for chronic obstructive pulmonary disease (COPD) attributable to SO₂ and NO₂ in Tabriz were 0.07% and 1.61%, respectively, whereas they were 2.84% and 0.48% in Urmia. O₃ had an annual average of 56 μg/m³ in Tabriz and with 44.5 excess respiratory deaths and 42.5 excess hospital admissions for COPD, it had the greatest health impacts among the pollutants studied. Findings from this study add to the growing literature, especially from developing countries, that provides insights to help authorities and decision-makers develop and implement effective interventions to curb air pollution and save lives.

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Economic development is responsible for excessive sulfur dioxide (SO₂) emissions, environmental pressure increases, and human and environmental risks. This study used spatial autocorrelation, the Environmental Kuznets Curve (EKC), and the Logarithmic Mean Divisia Index model to study the spatiotemporal variation characteristics and influencing factors of SO₂ emissions in the Yangtze River Economic Belt (YREB) from 1997 to 2017. Our results show that the total SO₂ emissions in the YREB rose from 513.14 × 10⁴ t to 974.00 × 10⁴ t before dropping to 321.97 × 10⁴ t. The SO₂ emissions from 11 provinces first increased and then decreased, each with different turning points. For example, the emission trends changed in Yunnan in 2011 and in Anhui in 2015, while the other nine provinces saw their emission trends change during 2005-2006. Furthermore, the SO₂ emissions in the YREB showed a significant agglomeration phenomenon, with a Moran index of approximately 0.233-0.987. Moreover, the EKC of SO₂ emissions and per capita GDP in the YREB was N-shaped. The EKCs of eight of the 11 provinces were N-shaped (Shanghai, Zhejiang, Anhui, Jiangxi, Sichuan, Guizhou, Hunan, and Chongqing) and those of the other three were inverted U-shaped (Jiangsu, Yunnan, and Hubei). Thus, economic development can both promote and inhibit the emission of SO₂. Finally, during the study period, the technical effect (approximately -1387.97 × 10⁴-130.24 × 10⁴ t) contributed the most, followed by the economic (approximately 27.81 × 10⁴-1255.59 × 10⁴ t), structural (approximately -56.45 × 10⁴-343.90 × 10⁴ t), and population effects (approximately 4.25 × 10⁴-39.70 × 10⁴ t). Technology was the dominant factor in SO₂ emissions reduction, while economic growth played a major role in promoting SO₂ emissions. Therefore, to promote SO₂ emission reduction, technological innovations and advances should be the primary point of focus.

Air pollutant spatiotemporal evolution characteristics and effects on human health in North China

North China, the political, economic, and cultural center of China, has been greatly harmed by frequent air pollution incidents. Therefore, it is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations of air pollutants (PM_2.5, PM₁₀, CO, SO₂, NO₂, and O₃) in North China from 2016 to 2019. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ_2.2.3 model was used to quantify health effects. The results showed that the major pollutant in the cities surrounding Beijing was PM_2.5, while PM₁₀ dominated in distant cities. Annual concentrations decreased (except for O₃), which is related to governmental emission reduction policies. However, O₃ concentrations increased owing to the complex precursor emissions. The AQI underestimated air pollution, while the AAQI and HAQI were accurate; the latter indicated that 55% of the study region population was exposed to polluted air. The AirQ_2.2.3 model quantified the total mortality proportions attributable to PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃, which were 1.87%, 3.12%, 1.11%, 1.40%, 4.19%, and 2.52%, respectively. In high concentrations, PM₁₀ and PM_2.5 pose significant health risks. The health effects of SO₂, NO₂, CO, and O₃ at lower concentrations were more obvious, indicating that the expected mortality rate due to low concentrations of some pollutants was much higher than that due to high concentrations of other pollutants.

Assessment of the Factors Influencing Sulfur Dioxide Emissions in Shandong, China

Sulfur dioxide (SO2) is a serious air pollutant emitted from different sources in many developing regions worldwide, where the contribution of different potential influencing factors remains unclear. Using Shandong, a typical industrial province in China as an example, we studied the spatial distribution of SO2 and used geographical detectors to explore its influencing factors. Based on the daily average concentration in Shandong Province from 2014 to 2019, we explored the influence of the diurnal temperature range, secondary production, precipitation, wind speed, soot emission, sunshine duration, and urbanization rate on the SO2 concentration. The results showed that the diurnal temperature range had the largest impact on SO2, with q values of 0.69, followed by secondary production (0.51), precipitation (0.46), and wind speed (0.42). There was no significant difference in the SO2 distribution between pairs of sunshine durations, soot emissions, and urbanization rates. The meteorological factors of precipitation, wind speed, and diurnal temperature range were sensitive to seasonal changes. There were nonlinear enhancement relationships among those meteorological factors to the SO2 pollution. There were obvious geographical differences in the human activity factors of soot emissions, secondary production, and urbanization rates. The amount of SO2 emissions should be adjusted in different seasons considering the varied effect of meteorological factors.

Effects of SO2 Pollution on Household Insurance Purchasing in China: A Cross-Sectional Study

There have been considerable concerns regarding the effects of air pollution on health and economy over the past decades across the world. As insurance coverage has been closely related to household welfare, we aim to investigate the influence of air pollution, in particular, the sulfur dioxide (SO2) pollution on household purchases of commercial health insurance using data from the 2017 China Household Financial Survey (CHFS). The results show that the rise in SO2 emission has a significant positive association with tendency of residents to participate in commercial health insurance. The possibility of household commercial health insurance purchasing increases by 4% per 1,000 tons of SO2 emission. In addition, the proportion of commercial health insurance expenditure in household annual income increases by 29% per 1,000 tons of SO2 emission. The effects are also found to differ among resident groups. Residents in eastern parts of China are more likely to buy commercial health insurance facing SO2 pollution compared to those in western parts of China; people with higher income are more likely to be affected compared to those with lower income; families with the household head being female are more likely to be affected compared to those with the household head being male. This research provides baseline information on the formulation and implementation of future operation strategy in commercial health insurance companies of China.

A 10-year assessment of ambient fine particles and related health endpoints in a large Mediterranean city

Fine particles i.e., with an aerodynamic diameter lower than 2.5 μm (PM_2.5) have potentially the most significant effects on human health compared to other air pollutants. The main objectives of this study were to i) investigate the temporal variations of ambient PM_2.5 in Marseille (Southern France), where air pollution is again a major public health issue, and ii) estimate their short-term health effects and annual trend (Mann-Kendall test) over a 10-year period from 2010 to 2019. In Marseille, the main sources of PM_2.5 could be related to road traffic, industrial complexes, and oil refineries surrounded the city. The number of premature deaths and hospital admissions attributable to ambient PM_2.5 exposure for non-accidental causes, cardiovascular and respiratory diseases were estimated by using in-situ air quality data, city-specific relative risk values and baseline incidence. Despite significant reduction of PM_2.5 (- 0.80 μg m^-3 year^-1), Marseille citizens were exposed to PM_2.5 levels exceeding the World Health Organization (WHO) Air Quality Guideline for human health protection (10 μg m^-3) during entire study period. Exposure to ambient PM_2.5 substantially contributed to mortality and hospital admissions: 871 deaths for non-accidental causes, 515 deaths for cardiovascular diseases, 47 deaths for respiratory diseases, as well as 1034 hospital admissions for cardiovascular diseases and 834 for respiratory diseases were reported between 2010 and 2019. Compliance with WHO annual limit values can result in substantial socio-economic benefits by preventing premature deaths and hospital admissions. For instance, based on the value of a statistical life and average cost of a hospital admission, the associated benefit for healthcare would have been €131 million in 2019. Between 2010 and 2019, the number of PM_2.5-related non-accidental deaths decreased by 1.15 per 10⁵ inhabitants annually. Compared to 2010-2019, the restrictive measures associated to COVID-19 pandemic led to a reduction in PM_2.5 of 11% in Marseille, with 2.6 PM_2.5-related deaths averted in 2020.

Short-Term Exposure to Ambient Air Pollution and Mortality From Myocardial Infarction

BACKGROUND

Short-term exposure to ambient air pollution has been linked to occurrence of myocardial infarction (MI); however, only a limited number of studies investigated its association with death from MI, and the results remain inconsistent.

OBJECTIVES

This study sought to investigate the association of short-term exposure to air pollution across a wide range of concentrations with MI mortality.

METHODS

A time-stratified case-crossover study was conducted to investigate 151,608 MI death cases in Hubei province (China) from 2013 to 2018. Based on each case's home address, exposure to particulate matter with an aerodynamic diameter ≤2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤10 μm (PM₁₀), sulfur dioxide, nitrogen dioxide (NO₂), carbon monoxide, and ozone on each of the case and control days was assessed as the inverse distance-weighted average concentration at neighboring air quality monitoring stations. Conditional logistic regression models were implemented to quantify exposure-response associations.

RESULTS

Exposure to PM_2.5, PM₁₀, and NO₂ (mean exposure on the same day of death and 1 day prior) was significantly associated with increased odds of MI mortality. The odds associated with PM_2.5 and PM₁₀ exposures increased steeply before a breakpoint (PM_2.5, 33.3 μg/m³; PM₁₀, 57.3 μg/m³) and flattened out at higher exposure levels, while the association for NO₂ exposure was almost linear. Each 10-μg/m³ increase in exposure to PM_2.5 (<33.3 μg/m³), PM₁₀ (<57.3 μg/m³), and NO₂ was significantly associated with a 4.14% (95% confidence interval [CI]: 1.25% to 7.12%), 2.67% (95% CI: 0.80% to 4.57%), and 1.46% (95% CI: 0.76% to 2.17%) increase in odds of MI mortality, respectively. The association between NO₂ exposure and MI mortality was significantly stronger in older adults.

CONCLUSIONS

Short-term exposure to PM_2.5, PM₁₀, and NO₂ was associated with increased risk of MI mortality.

The impact of life behavior and environment on particulate matter in chronic obstructive pulmonary disease

BACKGROUND

The effect of exposure to particulate matter (PM) on human health is a global public health concern. To develop an effective strategy to reduce PM exposure, we performed detailed questionnaire surveys regarding the type of lifestyle required to avoid PM exposure in patients with chronic obstructive pulmonary disease (COPD). We correlated the data with real-time PM concentration during the winter season.

METHODS

We enrolled 104 patients with COPD aged 40 years or older. Detailed questionnaire surveys were conducted among participants, and internet of things-based sensors were installed at their homes to measure the indoor PM_2.5 concentration, which was continuously monitored between December 2019 and February 2020. The associations among PM_2.5 concentration, patients' lifestyles, and the impact of both concentration and lifestyle on COPD exacerbation were analyzed.

RESULTS

Mean outdoor PM_2.5 concentration was higher than mean indoor PM_2.5 concentration during the study period (21.28 ± 5.09 μg/m³ vs. 12.75 ± 7.64 μg/m³), with a mean difference of 8.53 ± 7.99 μg/m³. Among the various social factors and practices that aim to avoid exposure to PM, six practices and economic statuses were confirmed to reduce indoor PM_2.5 concentration compared to outdoor concentration; Contrarily, these practices created a significant difference between the outdoor and indoor PM_2.5 concentrations. The six practice items that showed a significant difference were 1) checking air quality forecast (the difference: -13.31 ± 1.35 μg/m³, p = 0.013), 2) indoor air filter operated (-15.43 ± 1.32 μg/m³, p < 0.001), 3) ventilating home by opening the windows (-13.14 ± 1.28 μg/m³, p = 0.013), 4) checking filters of the air filter (-13.95 ± 1.50 μg/m³, p = 0.002), 5) refraining from going out when outside PM is high (-12.52 ± 1.37 μg/m³, p = 0.039), 6) wearing a mask when going out (-13.38 ± 1.32 μg/m³, p = 0.017). The higher the household income and economic level, the more significant the difference in the PM_2.5 concentration. Severe exacerbation was more prevalent among patients with acute exacerbation as the exposure time of PM_2.5≥35 μg/m³ or PM_2.5≥75 μg/m³.

CONCLUSION

Lifestyle and economic levels can affect the indoor PM_2.5 concentration, which may impact COPD exacerbation.

Multiple performances and paradoxical effects of China's vehicle emission reduction policy

As the living standards of urban residents in China continue to improve, the number of motor vehicle trips is increasing, thus aggravating air pollution. Such pollution causes great harm to human health and the global environment. Using a system dynamics approach, this study analyzed the effect of implementation mode on China's air pollution charging fee (APCF) policy and identified potentially negative medium- and long-term effects. The results indicated that the APCF policy has a dual effect under the single-charge mode (i.e., fees are charged on a daily basis). On the one hand, it has multiple effects of reducing emissions, relieving traffic congestion, and improving the happiness index. On the other hand, the higher the charge, the stronger the trip demand (possibly due to the sunk-cost fallacy and loss-aversion effect), which encourages motorists to weaken the cost of losses (i.e., from air pollution fees) by increasing the number of trips per day to seek short-term psychological balance, regardless of the extra costs and the amount of pollution generated. It was also found that APCF implementation mode significantly affected passenger car trips but not truck trips (perhaps because truck trips are mainly based on the demand of supply, and the daily number of trips is relatively stable). Overall, as APCF increases, it can have some paradoxical long-term effects on emissions, congestion, the happiness index, and road bearing capacity. This study's findings can help the Chinese government improve and optimize its long-term air pollution control strategies.

Health effects of particulate matter in major Indian cities

Background: Particulate matter (PM) is one among the crucial air pollutants and has the potential to cause a wide range of health effects. Indian cities ranked top places in the World Health Organization list of most polluted cities by PM. Objectives: Present study aims to assess the trends, short- and long-term health effects of PM in major Indian cities. Methods: PM-induced hospital admissions and mortality are quantified using AirQ+ software. Results: Annual PM concentration in most of the cities is higher than the National Ambient Air Quality Standards of India. Trend analysis showed peak PM concentration during post-monsoon and winter seasons. The respiratory and cardiovascular hospital admissions in the male (female) population are estimated to be 31,307 (28,009) and 5460 (4882) cases, respectively. PM_2.5 has accounted for a total of 1,27,014 deaths in 2017. Conclusion: Cities with high PM concentration and exposed population are more susceptible to mortality and hospital admissions.

Temporal fluctuations of PM2.5 and PM10, population exposure, and their health impacts in Dezful city, Iran

Morbidity and mortality impacts of particulate matter (PM) are globally important health critical parameters. In this ecological-descriptive study, the health impact of PM10 and PM2.5 associated with there temporal variations in Dezful city were assessed from 2013 to 2015. AirQ+ software handles the PM air pollutants by addressing impact evaluation and life table evaluation. We used a new method to analysis fine particles feature by using regular daily observations of PM10. In this method, relationship between PM2.5 and PM10 mass concentrations were analyzed and calculated. The annual average concentrations of PM10 were 147.1, 114.3 and 158.8 μg/m3, and the annual average concentration of PM2.5 were 57.8, 50.7 and 58.2 μg/m3 in 2013, 2014 and 2015, respectively. PM10 also had obvious diurnal variations with highest hourly concentrations in 13:00 and 22:00 but the lowest concentrations often occurred in 05:00 and 16:00. Unexpectedly, in weekends the concentration of PM pollutants appeared to have increased from 18:00 to midnight. The daily based analysis showed that there are 147 dusty days in the study period during which the most severe dusty day occurred in 2014. Over the study period, mean levels of PM10 and PM2.5 in both conditions were higher in 2015 compare to 2013 and 2014, which probably is due to higher frequency of dust storms in 2015. Hence, during 2015 and 2013 they're were higher morbidity and mortality compare to 2014 due to exposure to higher polluted air with PMs in all cases except lung cancer (LC).

Relationship between the number of hospitalized cardiovascular and respiratory disease and the average concentration of criteria air pollutants (CAP) in Ahvaz

This study aims to investigate the relationship between the number of hospitalized cardiovascular and respiratory patients and the average concentration of criteria air pollutants, including NO₂, SO₂, CO, O₃ and PM₁₀ in Ahvaz in the period of 10 years (2007-2017). Data on referrals and the number of hospitalized cardiovascular and respiratory patients and also on air pollutants are obtained through Hospital Information System and air quality monitoring stations including Department of Environment Protection Station, Naderi Square Station, University Square Station and the Meteorological Organization Station. The data were analyzed by SPSS version 4 and Poisson distribution regression model to evaluate the effects of each pollutant and the rate of hospitalization. In this study, confidence interval and the significance level are considered at 95% and 5%, respectively. Changes in air pollution indices and number of patients with cardiovascular diseases were evaluated using Excel, Stata and ARIMA models. Based on the results of Poisson regression analysis, there was a significant relationship between the average concentration of NO₂, O₃, CO and SO₂ and hospitalization of patients with cardiovascular disease, with a confidence level of less than 5%. This was the case with NO₂ more than other pollutants. Furthermore, there was a significant relationship between the average concentrations of NO₂, CO and O₃ and the hospitalization rate of patients with respiratory problems and a confidence level of 5%. The effect of NO₂ was also higher here. Due to the results, NO₂, CO, and O₃ had a significant direct correlation with cardiovascular and respiratory rates. The effect of NO₂ has been higher than other pollutants. In the study of time intervals of patients with cardiovascular, the results of time-interval analysis indicate the relationship between cardiovascular clients with the "t" time of 7 days earlier and NO₂ as a pollutant. The results of this analysis also revealed the relationship between respiratory patients at the time "t" up to 7 days before and O₃.

Estimation of cardiovascular and respiratory diseases attributed to PM10 using AirQ model in Urmia during 2011-2017

Background: Quantification of the attributed effects of air pollution determines the impact of air pollutants on the community and shows the critical condition of air quality. This study aimed to quantify and estimate the cardiovascular and respiratory diseases attributed to PM10 in Urmia during 2011-2016.

Methods: In this descriptive-analytic study, at first, hourly data of pollutant PM10 concentrations were received from air pollutants station located in the Department of Environmental Protection. The data were evaluated using AirQ2.2.3 software after primary and secondary processes and filtering.

Results: The results showed that the mean annual concentration of PM10 during 2011-2016 was 88.66, 92.45, 81.22, 78.38, 113.78, and 92.67 μg /m3, respectively. The number of hospitalized cases due to respiratory diseases attributed to PM10 in this period was 486, 525, 459, 453, 684, and 552, respectively, and the number of cases due to cardiovascular diseases was 188, 203, 177, 175, 263, and 213, respectively.

Conclusion: Considering the attributed health effects of PM10, the necessary measures should be taken to identify the causative agents and to understand the mechanisms of these processes and correct them.

Regeneration Performance of Activated Carbon for Desulfurization

This study explored the regenerated performance of activated carbon (AC) as SO2 adsorbent. The optimal conditions of SO2 removal were determined by experiment, and then the adsorption efficiency of AC was studied by a method of thermal regeneration. The characteristics of regenerated AC were analyzed by Brunauer-Emmett-Teller (BET) and Scanning Electron Microscopy (SEM) methods. The test results showed that the most suitable adsorption conditions were using 4 g of activated carbon, 1.65 L/min gas flue rate, and 5% O2. During the ten regenerations, the desulfurization efficiency and sulfur capacity of AC still maintained a high level. The characterization results showed that the increase of material surface area and pore volume were 101 m2 g−1, and 0.13 cm3 g−1, respectively, after the cycles.

Air pollution characteristics and human health risks in key cities of northwest China

Air pollution events occur frequently in northwest China, which results in serious detrimental effects on human health. Therefore, it is essential to understand the air pollution characteristics and assess the risks to humans. In this study, we analyzed the pollution characteristics of criteria pollutants in six key cities in northwest China from 2015 to 2018. We used the air quality index (AQI), aggregate AQI (AAQI), and health-risk based AQI (HAQI) to assess the health risks and determine the proportion of people exposed to air pollution. Additionally, on this basis, the AirQ_2.2.3 model was used to quantify the health effects of the pollutants. The results showed that PM₁₀ pollution occurred mainly in spring and winter and was caused by frequent dust storms. PM_2.5 pollution was caused mainly by anthropogenic activities (especially coal-fired heating in winter). Because of a series of government policies and pollutant reduction measures, PM_2.5, SO₂, NO₂, and CO concentrations showed a downward trend during the study period (except for a small increase in the case of NO₂ in some years.). However, O₃ showed high concentrations due to the high intensity of solar radiation in summer and inadequate emission reduction measures. The air quality levels based on their classification were generally higher than the Chinese ambient air quality standard classified by the AQI index. We also found that the higher the AQI index was, the more serious the air pollution classified based on the AAQI and HAQI indices was. The HAQI index could better reflect the impact of pollutants on human health. Based on the HAQI index, 20% of the population in the study area was exposed to polluted air. The total mortality values attributable to PM₁₀, PM_2.5, SO₂, O₃, NO₂, and CO, quantified by the AirQ_2.2.3 model, were 3.00%, 1.02%, 1.00%, 4.22%, 1.57%, and 0.95% (Confidence Interval:95%), respectively; the attributable proportions of mortality for respiratory system and cardiovascular diseases were consistent with the change rule of total mortality, because the number of deaths attributable to the latter was greater than that for the former. According to the exposure reaction curves of pollutants, PM₁₀ and PM_2.5 still showed a large change at high concentrations. However, the tendencies of SO₂, NO₂, CO, and O₃ were more obvious under low concentration exposure, which indicated that the expected mortality rate due to lower air pollution concentrations was much higher than the mortality due to high air pollution concentrations.

Short-term associations between ambient fine particulate matter pollution and hospital visits for chronic obstructive pulmonary disease in Yinzhou District, China

Ambient particulate matter is one of the main risk factors of chronic obstructive pulmonary disease (COPD) in developing countries. However, the studies were scant in China concerning the health effects of the fine particulate matter (PM_2.5; particulate matter ≤ 2.5 μm in diameter) on hospital visits for COPD. We applied a generalized additive model (GAM) to calculate relative risks (RRs) with 95% confidence intervals (CIs) for the associations between hospital visits for COPD and an interquartile range (24.50 μg/m³) increment of ambient PM_2.5 concentrations in Yinzhou District between 2016 and 2018. The ambient PM_2.5 concentration was positively associated with hospital visits for COPD at a distributed lag of 0-7 days (RR = 1.073, 95% CI, 1.016, 1.133). In the stratified analysis, we found that the association between ambient PM_2.5 and COPD was stronger during the warm season (April to September) than that during the cold season (October to March), but we did not observe statistically significant differences in age groups (< 60 years and ≥ 60 years) or gender groups (male and female) related to the effects of PM_2.5. The associations between ambient PM_2.5 and COPD became partially attenuated after the adjustment for gaseous pollutants in subgroups. Our findings could provide evidence that regulations for controlling both PM_2.5 and gaseous pollutants should be implemented to protect the overall population.

Effect of air pollution on hospitalization for acute exacerbation of chronic obstructive pulmonary disease, stroke, and myocardial infarction

This study aims to analyze the acute effects of PM_2.5, PM₁₀, SO₂, NO₂, and O₃ on hospitalizations for acute exacerbation of chronic obstructive pulmonary disease (AECOPD), stroke, and myocardial infarction (MI) from 2014 to 2017 in Shenyang, China. Hospitalization records for AECOPD (17,655), stroke (276,736) and MI (26,235) and air pollutions concentration data (PM_2.5, PM₁₀, SO₂, NO₂, and O₃) were collected. A generalized additive model (GAM) was utilized to determine the impact of air pollutants on the relative risk (RR) of hospitalization for AECOPD, stroke, and MI. Stratified analysis for AECOPD was based on gender and age. It was based on gender, age, hypertension, and diabetes for stroke, and for MI it was based on gender, age, and coronary atherosclerosis. The lag effect for AECOPD in terms of gender analysis occurred at lag3-lag5. The hospitalization risk for stroke with hypertension due to SO₂ and NO₂ was greater than that of stroke without hypertension. The risk of hospitalization for stroke with hypertension as a comorbidity due to O₃ was lower than without hypertension. The risk of hospitalization for MI combined with coronary atherosclerosis due to PM_2.5, PM₁₀, or NO₂ was higher than that of hospitalizations for MI without coronary atherosclerosis. Air pollution increased the rate of hospitalization for AECOPD. SO₂ and O₃ appeared protective for stroke patients with coronary atherosclerosis. PM_2.5, PM₁₀, and NO₂ had no influence on total hospitalization for myocardial infarction.

The hospitalization attributable burden of acute exacerbations of chronic obstructive pulmonary disease due to ambient air pollution in Shijiazhuang, China

Few studies have investigated the acute exacerbations of chronic obstructive pulmonary disease (AECOPD)-associated attributable burden under exposure to high levels of air pollution among Asians. Data on hospitalization for AECOPD, air pollution and meteorological factors from 1 January 2013 to 31 December 2016 were collected in Shijiazhuang, China. We used a Poisson generalized linear regression model combined with a distributed lag nonlinear model (DLNM) to evaluate the relative cumulative risk for a lag of 0-7 days and examined the potential effect modifications by age and sex via stratification analyses, controlling for long-term trends, seasonal patterns, meteorological factors, and other possible confounders. Then, we computed hospitalization percentages attributable to air pollutants. The AECOPD-associated relative cumulative risks for PM_2.5, PM₁₀, NO₂, SO₂, and CO for a lag of 0-7 days were significantly positively correlated with hospitalization. The associations were stronger in females and retired patients. The NO₂ Cum RR of AECOPD admission was the greatest. A 10μg/m³ increase in daily NO₂ concentration was associated with 6.7% and 5.7% increases in COPD hospitalizations in the retired and female groups, respectively. The results showed that 13%, 9.4%, 1.7%, 9.7%, and 8.8% of AECOPD hospitalizations were attributable to exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO, respectively. If the air pollutant concentration was reduced to the 24-h average grade II levels of NAAQS of China, the AECOPD attributable percentage for PM_2.5 and PM₁₀ would decrease by 80%. The air pollutants PM_2.5, PM₁₀, SO₂, NO₂, and CO were significantly relevant to AECOPD-associated hospitalization. The associations differed by individual characteristics. The retired and female populations were highly vulnerable.

Effect of particulate matter-bound metals exposure on prothrombotic biomarkers: A systematic review

Environmental pollution is an important modifiable determinant for preventing cardiovascular diseases. Acute exposure to air pollution is linked to severe adverse cardiovascular events, including venous thromboembolism risk. The adverse health effects seem to arise from blood-borne metals and transition metal components from exposure to particulate matter that, when breathed, passes through the lungs into the heart and the blood stream. Pollution affects health via mechanisms including oxidative stress and inflammation, and metals may have a detrimental effect on both the blood cells, particularly platelets, and circulation. Some evidences demonstrates atherotrombotic consequences of acute and chronic exposure to air pollution, but few studies have examined exposure effects on the prothrombotic biomarkers leading to venous thromboembolism. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, we performed a systematic review (14 papers) of the past twelve years, focusing on the relationship between inhalable airborne metal exposures and coagulative biomarker disorders leading to lower limb venous thromboembolisms, e.g., deep vein thrombosis. Results support the hypothesis that exposure to inhalable metals, as elemental compounds in particulate matter, cause changes or activation of a number of human prothrombotic hemostatic biomarkers.

A novel optimal-hybrid model for daily air quality index prediction considering air pollutant factors

Accurate and reliable air quality index (AQI) forecasting is extremely crucial for ecological environment and public health. A novel optimal-hybrid model, which fuses the advantage of secondary decomposition (SD), AI method and optimization algorithm, is developed for AQI forecasting in this paper. In the proposed SD method, wavelet decomposition (WD) is chosen as the primary decomposition technique to generate a high frequency detail sequence WD(D) and a low frequency approximation sequence WD(A). Variational mode decomposition (VMD) improved by sample entropy (SE) is adopted to smooth the WD(D), then long short-term memory (LSTM) neural network with good ability of learning and time series memory is applied to make it easy to be predicted. Least squares support vector machine (LSSVM) with the parameters optimized by the Bat algorithm (BA) considers air pollutant factors including PM_2.5, PM₁₀, SO₂, CO, NO₂ and O₃, which is suitable for forecasting WD(A) that retains original information of AQI series. The ultimate forecast result of AQI can be obtained by accumulating the prediction values of each subseries. Notably, the proposed idea not only gives full play to the advantages of conventional SD, but solve the problem that the traditional time series prediction model based on decomposition technology can not consider the influential factors. Additionally, two daily AQI series from December 1, 2016 to December 31, 2018 respectively collected from Beijing and Guilin located in China are utilized as the case studies to verify the proposed model. Comprehensive comparisons with a set of evaluation indices indicate that the proposed optimal-hybrid model comprehensively captures the characteristics of the original AQI series and has high correct rate of forecasting AQI classes.

Estimate annual and seasonal PM1, PM2.5 and PM10 concentrations using land use regression model

Exposure to ambient particulate matter (PM) can increase mortality and morbidity in urban area. In this study, annual and seasonal spatial pattern of PM₁, PM_2.5 and PM₁₀ pollutants were assessed using land use regression (LUR) models in Sabzevar, Iran. The studied pollutants were measured at 26 monitoring stations of different microenvironments in the study area. Sampling was conducted during four campaigns from April 2017 to February 2018. LUR models were developed based on 104 potentially predictive variables (PPVs) subdivided in six categories and 22 sub-categories. The annual mean (standard deviation) of PM₁, PM_2.5 and PM₁₀ were 36.46 (8.56), 39.62 (10.55) and 51.99 (16.25) μg/m³, respectively. The R² values and root mean square error for leave-one-out cross validations (RMSE for LOOCV) of PM₁ models ranged from 0.23 to 0.79 and 3.43-22.5, respectively. Further, R² and RMSE for LOOCV of PM_2.5 models ranged from 0.56 to 0.93 and 3.66-28.3, respectively. For PM₁₀ models the R² ranged from 0.31 to 0.82 and the RMSE for LOOCV ranged from 9.16 to 33.9. The generated models can be useful for population based epidemiologic studies and to estimate these pollutants in different parts of the study area for scientific decision making.

Ambient carbon monoxide and increased risk of daily hospital outpatient visits for respiratory diseases in Dongguan, China

BACKGROUND

The toxicity of high-concentration carbon monoxide (CO) on human health has previously been documented. However, the epidemiological evidence on the association between acute exposure to ambient CO and respiratory diseases is relatively lacking and controversial.

OBJECTIVES

To examine the short-term association between ambient CO and hospital outpatient visits for respiratory diseases in Dongguan, China.

METHODS

The number of daily hospital outpatient visits for respiratory diseases, and air pollution and meteorological data were collected from January 2013 to August 2017. A generalized additive model with a quasi-Poisson link was used to estimate the association between ambient CO concentration and the total number of hospital outpatient visits for all respiratory diseases and those for asthma, bronchiectasis, chronic obstructive pulmonary disease (COPD) and pneumonia. We further analyzed the effect of ambient CO by gender and age.

RESULTS

Over the study period, a 24-h mean concentration of ambient CO of 0.88 mg/m³ (below the limit for CO in China) and a total of 89,484 hospital outpatient visits for respiratory diseases were recorded. Ambient CO was found to increase the risk for asthma, bronchiectasis, pneumonia and the total number of respiratory diseases. The per interquartile range (IQR) increase in ambient CO at lag₀₃ day corresponded to a 5.62% (95% confidence interval (CI): 3.24%, 8.05%), 8.86% (95% CI: 4.89%, 12.98%), 6.67% (95% CI: 0.87%, 12.81%) and 7.20% (95% CI: 2.35%, 12.29%) increased risk in outpatient visits for all respiratory diseases, asthma, bronchiectasis and pneumonia, respectively. Each association was partially weakened after adjusting for co-pollutants. The effect of ambient CO on respiratory diseases appeared to be greater for females and the elderly.

CONCLUSIONS

Short-term exposure to ambient CO was associated with increased risk of outpatient visits for respiratory diseases. Our analysis may help to understand the health effects of low-levels of CO and provide evidence for the creation of air quality standards.

A comprehensive evaluation of the association between ambient air pollution and adverse health outcomes of major organ systems: a systematic review with a worldwide approach

Ambient air pollution is nowadays one of the most crucial contributors to deteriorating health status worldwide. The components of air pollution include PM_2.5 and PM₁₀, NO₂, SO₂, CO, O₃, and organic compounds. They are attributed to several health outcomes, for instance, cardiovascular diseases (CVD), respiratory diseases, birth outcomes, neurologic diseases, and psychiatric diseases. The objective of this study is to evaluate the association between different ambient air pollutants and the above-mentioned health outcomes. In this systematic review, a total of 76 articles was ultimately selected from 2653 articles, through multiple screening steps by the aid of a set of exclusion criteria as non-English articles, indoor air pollution assessment, work-related, occupational and home-attributed pollution, animal studies, tobacco smoking effects, letters to editors, commentaries, animal experiments, reviews, case reports and case series, out of 19,862 published articles through a systematic search in PubMed, Web of Science, and Scopus. Then, the associations between air pollution and different health outcomes were measured as relative risks and odds ratios. The association between air pollutants, PM_2.5 and PM₁₀, NO₂, SO₂, CO, O₃, and VOC with major organ systems health was investigated through the gathered studies. Relative risks and/or odds ratios attributed to each air pollutant/outcome were ultimately reported. In this study, a thorough and comprehensive discussion of all aspects of the contribution of ambient air pollutants in health outcomes was proposed. To our knowledge up to now, there is no such comprehensive outlook on this issue. Growing concerns in concert with air pollution-induced health risks impose a great danger on the life of billions of people worldwide. Should we propose ideas and schemes to reduce ambient air pollutant, there will be dramatic reductions in the prevalence and occurrence of health-threatening conditions.

Role of Emerging Environmental Risk Factors in Thyroid Cancer: A Brief Review

Environmental factors are recognized as risk factors of thyroid cancer in humans. Exposure to radiation, both from nuclear weapon or fallout or medical radiation, and to some organic and inorganic chemical toxicants represent a worldwide public health issue for their proven carcinogenicity. Halogenated compounds, such as organochlorines and pesticides, are able to disrupt thyroid function. Polychlorinated biphenyls and their metabolites and polybrominated diethyl ethers bind to thyroid, transport proteins, replace thyroxin, and disrupt thyroid function as phthalates and bisphenolates do, highly mimicking thyroid hormones. A better knowledge of environmental risks represents a very important tool for cancer prevention through true risks prevention and management. This approach is very important because of the epigenetic origin’s theory of cancer. Therefore, the aim of this review was study the association between environmental agents and thyroid cancer promotion.

A general method for evaluating the effects of air pollutants on lung cancer prevalence

It is widely accepted that some air pollutants are related to lung cancer prevalence. An effective method is proposed to quantitatively evaluate the effects of air pollutants and the interactions between them. The method consisted of three parts: data decomposition, comparable data generation and relationship inference. Firstly, very limited monitoring data published by Geographic Information System were applied to calculate the inhalable air pollution of relatively massive patient samples. Then the investigated area was partitioned into a number of districts, and the comparable data containing air pollutant concentrations and lung cancer prevalence in all districts were generated. Finally, the relationships between pollutants and lung cancer prevalence were concluded by an information fusion tool: Choquet integral. As an example, the proposed method was applied in the investigation of air pollution in Tianjin, China. Overall, SO₂, O₃ and PM_2.5 were the top three factors for lung cancer. And there was obvious positive interaction between O₃ and PM_2.5 and negative interaction among SO₂, O₃ and PM₁₀. The effect of SO₂ on men was larger than on women. O₃ and SO₂ were the most important factors for the adenocarcinoma and squamous cell carcinoma, respectively. The effect of SO₂ or NO₂ on squamous cell carcinoma is obviously larger than that on adenocarcinoma, while the effect of O₃ or PM_2.5 on adenocarcinoma is obviously larger than that on squamous cell carcinoma. The results provide important suggestions for management of pollutants and improvement of environmental quality. The proposed method without any parameter is general and easily realized, and it sets the foundation for further researches in other cities/countries. Implications: For total lung cancer prevalence, male and female lung cancer prevalence, and adenocarcinoma and squamous cell carcinoma prevalence, the proposed method not only quantify the effect of single pollutant (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) but also reveals the correlations between different pollutants such as positive interaction or negative interaction. The proposed method without any geographic predictor and parameter is much easier to realize, and it sets the foundation for further research in other cities/countries. The study results provide important suggestions for the targeted management of different pollutants and the improvement of human lung health.

Should we see urban trees as effective solutions to reduce increasing ozone levels in cities?

Outdoor air pollution is considered as the most serious environmental problem for human health, associated with some million deaths worldwide per year. Cities have to cope with the challenges due to poor air quality impacting human health and citizen well-being. According to an analysis in the framework of this study, the annual mean concentrations of tropospheric ozone (O₃) have been increasing by on average 0.16 ppb year^-1 in cities across the globe over the time period 1995-2014. Green urban infrastructure can improve air quality by removing O₃. To efficiently reduce O₃ in cities, it is important to define suitable urban forest management, including proper species selection, with focus on the removal ability of O₃ and other air pollutants, biogenic emission rates, allergenic effects and maintenance requirements. This study reanalyzes the literature to i) quantify O₃ removal by urban vegetation categorized into trees/shrubs and green roofs; ii) rank 95 urban plant species based on the ability to maximize air quality and minimize disservices, and iii) provide novel insights on the management of urban green spaces to maximize urban air quality. Trees showed higher O₃ removal capacity (3.4 g m^-2 year^-1 on average) than green roofs (2.9 g m^-2 year^-1 as average removal rate), with lower installation and maintenance costs (around 10 times). To overcome present gaps and uncertainties, a novel Species-specific Air Quality Index (S-AQI) of suitability to air quality improvement is proposed for tree/shrub species. We recommend city planners to select species with an S-AQI>8, i.e. with high O₃ removal capacity, O₃-tolerant, resistant to pests and diseases, tolerant to drought and non-allergenic (e.g. Acer sp., Carpinus sp., Larix decidua, Prunus sp.). Green roofs can be used to supplement urban trees in improving air quality in cities. Urban vegetation, as a cost-effective and nature-based approach, aids in meeting clean air standards and should be taken into account by policy-makers.

Association between cancer risk and polycyclic aromatic hydrocarbons' exposure in the ambient air of Ahvaz, southwest of Iran

Nowadays, a large number of health endpoints such as disease rates, treatment costs, and death, by air pollutants, have been a serious health problem for humans. One of the most hazardous air pollutants, which is highly dangerous for human health, is polycyclic aromatic hydrocarbons (PAHs). The existence of the emission of industries' pollutants and seasonal variations are the primary agents affecting PAHs' concentration. The purposes of this study were to calculate the cancer risk and measure PAHs' exposure in the ambient air of Ahvaz, southwest of Iran, during 2017. Three distinct areas ((S1) industrial, (S2) high traffic, and (S3) residential) of Ahvaz metropolitan were selected. Omni sampler equipped with polytetrafluoroethylene (PTFE) filters were used for active sampling of PAHs. To detect the level of PAHs, gas chromatography with mass spectrometry (GC/MS) was used. Incremental lifetime cancer risk (ILCR) and lifetime average daily dose (LADD) were used to estimate the health risk caused by PAHs. The results showed that the residential and industrial areas had the lowest and highest level of PAHs. Moreover, the average levels of PAHs in industrial, high traffic, and residential areas were 8.44 ± 3.37, 7.11 ± 2.64, and 5.52 ± 1.63 ng m^-3, respectively. Furthermore, ILCR in autumn and winter was higher than EPA standard, 0.06307 and 0.04718, respectively. In addition, ILCR in different areas was significantly higher than standard. Research findings imply that the levels of exposure to PAHs can increase ILCR and risk of health endpoint. The cancer risk attributed to PAHs should be further investigated from the perspective of the public health in metropolitans.

Health risk assessment on human exposed to heavy metals in the ambient air PM10 in Ahvaz, southwest Iran

Heavy metals (HM) are one of the main components of urban air pollution. Today, megacities and industrial regions in southwest of Iran are frequently suffering from severe haze episodes, which essentially caused by PM₁₀-bound heavy metals. The purpose of this study was to evaluate the health risk assessment on human exposed to heavy metals (Cr, Ni, Pb, and Zn) in the ambient air PM₁₀ in Ahvaz, southwest Iran. In this study, we estimated healthy people from the following scenarios: (S3) residential site; (S2) high-traffic site; (S1) industrial site in Ahvaz metropolitan during autumn and winter. In the current study, high-volume air samplers equipped with quartz fiber filters were used to sampling and measurements of heavy metal concentration. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was utilized for detection of heavy metal concentration (ng m^-3). Also, an estimate of the amount of health risk assessment (hazard index) of Cr, Ni, Pb, and Zn of heavy metal exposure to participants was used. Result of this study showed that the residential and industrial areas had the lowest and the highest level of heavy metal. Based on the result of this study, average levels of heavy metal in industrial, high-traffic, and residential areas in autumn and winter were 31.48, 30.89, and 23.21 μg m^-3 and 42.60, 37.70, and 40.07 μg m^-3, respectively. Based on the result of this study, the highest and the lowest concentration of heavy metal had in the industrial and residential areas. Zn and Pb were the most abundant elements among the studied PM₁₀-bound heavy metals, followed by Cr and Ni. The carcinogenic risks of Cr, Pb, and the integral HQ of metals in PM₁₀ for children and adults via inhalation and dermal exposures exceeded 1 × 10^-4 in three areas. Also, based on the result of this study, the values of hazard index (HI) of HM exposure in different areas were significantly higher than standard. The health risks attributed to HM should be further investigated from the perspective of the public health in metropolitans. The result of this study showed increasing exposure concentrations to heavy metal in the studied scenarios have a significant potential for generating different health endpoints, while environmental health management in ambient air can cause disorders in citizenship and causing more spiritual and material costs.

Chronic obstructive pulmonary diseases related to outdoor PM10, O3, SO2, and NO2 in a heavily polluted megacity of Iran

This study was conducted to quantify, by an approach proposed by the World Health Organization (WHO), the daily hospital admissions for chronic obstructive pulmonary disease (COPD) related to exposure to particulate matter (PM₁₀) and oxidants such as ozone (O₃), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂) in a heavily polluted city in Iran. For the health impact assessment, in terms of COPD, the current published relative risk (RR) and baseline incidence (BI) values, suggested by the WHO, and the 1-h O₃ concentrations and daily PM₁₀, NO₂, and SO₂ concentrations were compiled. The results showed that 5.9, 4.1, 1.2, and 1.9% of the COPD daily hospitalizations in 2011 and 6.6, 1.9, 2.3, and 2.1% in 2012 were attributed to PM₁₀, O₃, SO₂, and NO₂ concentrations exceeding 10 μg/m³, respectively. This study indicates that air quality and the high air pollutant levels have an effect on COPD morbidity. Air pollution is associated with visits to emergency services and hospital admissions. A lower relative risk can be achieved if some stringent control strategies for reducing air pollutants or emission precursors are implemented.