Estimating Exposure to Traffic-Related Air Pollution and Its Consequences on Respiratory Health in Population Working or Living along the Trunk Road: A Systematic Review

Introduction: Urban Air pollution is increasingly becoming a major health and sustainable development issue. Several studies showed that Traffic-related air pollution (TRAP) is one of the main sources of urban air pollution and has serious consequences on respiratory health. As no systematic review focused on the traffic-related air pollution and respiratory health in the target population of individuals working in a shop or in an office or individuals living along the trunk road, the authors conducted the current study to try to fill this gap. Methods: A systematic review search was conducted using MEDLINE (PubMed), Scientific Research Publishing: SCIRP, Web of Science, Google scholar. Studies were included if they meet the following selection criteria: 1) focus on population working or living along a major/trunk road; 2) studies had reported clearly at least on the exposure variables related to TRAP; 3) the association between TRAP and development of respiratory symptoms or respiratory diseases was established. Results: 13 articles were selected on the 192 articles that were retrieved in the initial research. Exposure to traffic-related air pollution was determined by using distance to road, traffic intensity and pollutants measured. The main respiratory health problems found were cough, wheeze, asthma and bronchitis. No article discussed about roundabouts in characterizing exposure to traffic-related air pollution. Conclusion: Distance to road, traffic density and pollutants measured are the usual methods to characterize the exposure to traffic-related air pollution and its consequences on respiratory health. Regarding the context of area occupations in African cities, it is necessary to focus on population around roundabouts and see if they are not more exposed to TRAP.

Psychosocial Stress Modifies the Acute Cardiac Health Effects of Traffic-Related Air Pollution

Previous studies have shown that exposure to black carbon(BC,a tracer of traffic-related air pollution)and psychosocial stress are both associated with adverse cardiac effects,but whether psychosocial stress could modify the cardiac effects of BC is unclear.To investigate the potential modifying effect of psychosocial stress on the associations between acute exposure to BC and typical cardiac health variables,real-time personal 24 h measurements were conducted in a repeated-measure study among adults with elevated blood pressure(high-risk group)and a panel study among normal adults(low-risk group)in China.Measured cardiac health variables included ST-segment depression events,heart rate,and heart rate variability(HRV)variables.Perceived Stress Scale,State Anxiety Inventory and Self-rating Depression Scale were used to assess the recent psychosocial stress status of the participants,and a composite stress index was established based on these scales.Generalized linear mixed-effects model was used to analyze the associations between BC exposure and cardiac health variables and potential effect modification by psychosocial stress.A total of 9724 h measurements among 97 participants in the repeated-measure study and 20224 h measurements among 87 participants in the panel study were included in the final analysis.Acute BC exposure was significantly associated with increased ST-segment depression events and heart rate and decreases in HRV in both studies.The marginal effects of acute BC exposure on most cardiac health variables generally tended to be amplified under higher vs low levels of psychosocial stress in both studies,with the composite stress index apparently modifying the associations of BC exposure with most ST-segment depression events and HRV variables.These findings suggest that psychosocial stress may increase the participants’cardiac susceptibility to BC exposure,which could be helpful for the identification of susceptible individuals in the context of traffic-related air pollution.

Impact of air pollution on urbanization:evidence at China’s city level

This paper investigates the effect and transmission mechanism of air pollution on urbanization based on data from China’s 107 cities during 2005–2018.In order to identify the impact of air pollution on China’s urbanization,we utilized night light data to represent the level of urbanization and used temperature inversion as an instrumental variable to mitigate endogeneity within the two-stage least squares framework.The results suggest that air pollution significantly slowed China’s urbanization process with economic growth acting as the transmission mechanism.The heterogeneity analyses revealed that air pollution had a greater negative impact on urbanization in northern regions than that in southern regions,and a greater negative impact in resource-oriented cities than that in non-resource-based cities.We also find that air pollution was to the detriment of urbanization in larger cities,which have more than 3 million residents,while it did not have a significant impact on Type II large cities,which have fewer than 3 million residents.

The Influence of Air Pollution Concentrations on Solar Irradiance Forecasting Using CNN-LSTM-mRMR Feature Extraction

Maintaining a steady power supply requires accurate forecasting of solar irradiance,since clean energy resources do not provide steady power.The existing forecasting studies have examined the limited effects of weather conditions on solar radiation such as temperature and precipitation utilizing convolutional neural network(CNN),but no comprehensive study has been conducted on concentrations of air pollutants along with weather conditions.This paper proposes a hybrid approach based on deep learning,expanding the feature set by adding new air pollution concentrations,and ranking these features to select and reduce their size to improve efficiency.In order to improve the accuracy of feature selection,a maximum-dependency and minimum-redundancy(mRMR)criterion is applied to the constructed feature space to identify and rank the features.The combination of air pollution data with weather conditions data has enabled the prediction of solar irradiance with a higher accuracy.An evaluation of the proposed approach is conducted in Istanbul over 12 months for 43791 discrete times,with the main purpose of analyzing air data,including particular matter(PM10 and PM25),carbon monoxide(CO),nitric oxide(NOX),nitrogen dioxide(NO_(2)),ozone(O₃),sulfur dioxide(SO_(2))using a CNN,a long short-term memory network(LSTM),and MRMR feature extraction.Compared with the benchmark models with root mean square error(RMSE)results of 76.2,60.3,41.3,32.4,there is a significant improvement with the RMSE result of 5.536.This hybrid model presented here offers high prediction accuracy,a wider feature set,and a novel approach based on air concentrations combined with weather conditions for solar irradiance prediction.

Ensemble Deep Learning Based Air Pollution Prediction for Sustainable Smart Cities

Big data and information and communication technologies can be important to the effectiveness of smart cities.Based on the maximal attention on smart city sustainability,developing data-driven smart cities is newly obtained attention as a vital technology for addressing sustainability problems.Real-time monitoring of pollution allows local authorities to analyze the present traffic condition of cities and make decisions.Relating to air pollution occurs a main environmental problem in smart city environments.The effect of the deep learning(DL)approach quickly increased and penetrated almost every domain,comprising air pollution forecast.Therefore,this article develops a new Coot Optimization Algorithm with an Ensemble Deep Learning based Air Pollution Prediction(COAEDL-APP)system for Sustainable Smart Cities.The projected COAEDL-APP algorithm accurately forecasts the presence of air quality in the sustainable smart city environment.To achieve this,the COAEDL-APP technique initially performs a linear scaling normalization(LSN)approach to pre-process the input data.For air quality prediction,an ensemble of three DL models has been involved,namely autoencoder(AE),long short-term memory(LSTM),and deep belief network(DBN).Furthermore,the COA-based hyperparameter tuning procedure can be designed to adjust the hyperparameter values of the DL models.The simulation outcome of the COAEDL-APP algorithm was tested on the air quality database,and the outcomes stated the improved performance of the COAEDL-APP algorithm over other existing systems with maximum accuracy of 98.34%.

Climate change,ambient air pollution,and students'mental health

The impact of global climate change and air pollution on mental health has become a crucial public health issue.Increased public awareness of health,advancements in medical diagnosis and treatment,the way media outlets report environmental changes and the variation in social resources affect psychological responses and adaptation methods to climate change and air pollution.In the context of climate change,extreme weather events seriously disrupt people's living environments,and unstable educational environments lead to an increase in mental health issues for students.Air pollution affects students'mental health by increasing the incidence of diseases while decreasing contact with nature,leading to problems such as anxiety,depression,and decreased cognitive function.We call for joint efforts to reduce pollutant emissions at the source,improve energy structures,strengthen environmental monitoring and governance,increase attention to the mental health issues of students,and help student groups build resilience;by establishing public policies,enhancing social support and adjusting lifestyles and habits,we can help students cope with the constantly changing environment and maintain a good level of mental health.Through these comprehensive measures,we can more effectively address the challenges of global climate change and air pollution and promote the achievement of the United Nations Sustainable Development Goals.

Analysis of Characteristics and Meteorological Influencing Factors of Air Pollution in Luojiang District,Deyang City

Based on the monitoring data of ambient air quality and meteorological observation data,the characteristics and meteorological influencing factors of air pollution in Luojiang District of Deyang City from 2018 to 2022 were analyzed.The results show that from 2018 to 2022,the main air pollutants affecting the air quality of Luojiang District of Deyang City were PM_(2.5) and PM_(10),and the primary pollutant on heavy pollution days was basically PM_(2.5).PM_(2.5) and PM_(10) pollution showed obvious seasonal differences,and PM_(2.5) concentration exceeded the limit mainly in spring and winter,among which it was the most serious in early spring,especially in January and February,followed by December.PM_(10) exceeding the standard had a high seasonal correlation with PM_(2.5) exceeding the standard,mainly in spring and winter,among which it was the most serious in winter,especially in December,followed by January.PM_(2.5) and PM_(10) pollution showed an overall weakening trend.PM_(2.5) and PM_(10) concentration were closely related to meteorological factors such as temperature,relative humidity,wind speed,precipitation and air pressure,and were mainly affected by rainfall.

Seasonal Influence in Traffic-Related Air Pollutants Concentrations in Urban Parks from Porto Alegre,Brazil

Traffic-related air pollution is an alarming source of pollutants exposure and consequently to the development of several adverse health effects. Otherwise, green spaces are reported to improve health status. Although, in an urban scenario most of these areas are located near air pollutants sources, as vehicle fleet. Thus, the aim of the present study was to determine, during one year, the levels of nitrogen dioxide (NO2) and ozone (O3) in the main parks from Porto Alegre—Brazil. This study focused on three urban parks: Germania, Moinhos de Vento and Marinha do Brasil Park. Nitrogen dioxide and ozone measurements were accessed by passive monitoring in four campaigns including all seasons and performed at distances of 0 m, 15 m, 30 m, 45 m, 60 m and 75 m from the main road at each park. NO2 and O3 concentration among the parks was not different (p > 0.05), as well as the mean concentration of NO2 and O3 of all parks in the six sites did not differ (p > 0.05). However, season 1 and 3 showed increased NO2 and O3 concentration. Temperature were decreased in season 1 and 3 (p p > 0.05). Traffic flow was higher in Moinhos de Vento Park and Marinha do Brasil Park compared to Germania Park (p 2 and O3 concentration in urban parks from Porto Alegre.

Characteristics of Fluoride Contents in Plants and Soils in Kaili City Under Air Pollution

Fluoride contents in plants and soils in Kaili City were measured with fluorinion as per electrode method and the related characteristics were analyzed in order to explore effects of air fluoride pollution on plant and soil.The results indicated that fluoride content in plants tended to be volatile in 135.62-1 420.97 μg/g and averaged 513.99 μg/g;fluoride content in soils changed from 240.50-340.36 μg/g and averaged 279.60 μg/g.The contents of plant and soil both exceeded background value,suggesting that plants and soils in the region have been polluted.In addition,fluoride contents differ significantly upon plants.In detail,the maximal content was in Camelliaolelfera Abel and the minimal in Camelliaolelfera Abel.The contents of fluoride in different plant species vary,as follows：shrub vine herbaceous plant arbor;evergreen plants deciduous plant;fluoride contents in plants and soils also differ in varying degrees upon research sites.

Association between Ambient Air Pollution and Hospital Emergency Admissions for Respiratory and Cardiovascular Diseases in Beijing: a Time Series Study

Objective To investigate the association between ambient air pollution and hospital emergency admissions in Beijing. Methods In this study, a semi-parametric generalized additive model （GAM） was used to evaluate the specific influences of air pollutants （PM10, SO2, and NO2） on hospital emergency admissions with different lag structures from 2009 to 2011, the sex and age specific influences of air pollution and the modifying effect of seasons on air pollution to analyze the possible interaction. Results It was found that a 10μg/m3 increase in concentration of PMlo at lag 03 day, SO2 and NO2 at lag 0 day were associated with an increase of 0.88%, 0.76%, and 1.82% respectively in overall emergency admissions. A 10 lag/m3 increase in concentration of PM10, SO2 and NO2 at lag 5 day were associated with an increase of 1.39%, 1.56%, and 1.18% respectively in cardiovascular disease emergency admissions. For lag 02, a 10 μg/m3 increase in concentration of PM10, SO2 and NO2 were associated with 1.72%, 1.34%, and 2.57% increases respectively in respiratory disease emergency admissions. Conclusion This study further confirmed that short-term exposure to ambient air pollution was associated with increased risk of hospital emergency admissions in Beijing.

Evaluation of mercury speciation and removal through air pollution control devices of a 190 MW boiler

Air pollution control devices （APCDs） are installed at coal-fired power plants for air pollutant regulation. Selective catalytic reduction （SCR） and wet flue gas desulftLrization （FGD） systems have the co-benefits of air pollutant and mercury removal. Configuration and operational conditions of APCDs and mercury speciation affect mercury removal efficiently at coal-fired utilities. The Ontario Hydro Method （OHM） recommended by the U.S. Environmental Protection Agency （EPA） was used to determine mercury speciation simultaneously at five sampling locations through SCR-ESP-FGD at a 190 MW unit. Chlorine in coal had been suggested as a factor affecting the mercury speciation in flue gas; and low-chlorine coal was purported to produce less oxidized mercury （Hg^2＋） and more elemental mercury （Hg^0） at the SCR inlet compared to higher chlorine coal. SCR could oxidize elemental mercury into oxidized mercury when SCR was in service, and oxidation efficiency reached 71.0%. Therefore, oxidized mercury removal efficiency was enhanced through a wet FGD system. In the non-ozone season, about 89.5%-96.8% of oxidized mercury was controlled, but only 54.9%-68.8% of the total mercury was captured through wet FGD. Oxidized mercury removal efficiency was 95.9%-98.0%, and there was a big difference in the total mercury removal efficiencies from 78.0% to 90.2% in the ozone season. Mercury mass balance was evaluated to validate reliability of OHM testing data, and the ratio of mercury input in the coal to mercury output at the stack was from 0.84 to 1.08.

A Time Series Analysis of Outdoor Air Pollution and Preterm Birth in Shanghai, China

Objective To investigate the relation between air pollution exposure and preterm birth in Shanghai, China. Methods We examined the effect of ambient air pollution on preterm birth using time-series approach in Shanghai in 2004. This method can eliminate potential confounding by individual risk factors that do not change over a short period of time. Daily numbers of preterm births were obtained from the live birth database maintained by Shanghai Municipal Center of Disease Control and Prevention. We used the generalized additive model （GAM） with penalized splines to analyze the relation between preterm birth, air pollution, and covariates. Results We observed a significant effect of outdoor air pollution only with 8-week exposure before preterm births. An increase of 10 μg/m^3 of 8-week average PM10, SO2, NO2, and O3 corresponded to 4.42% （95%CI 1.60%, 7.25%）, 11.89% （95%CI 6.69%, 17.09%）, 5.43% （95%CI 1.78%, 9.08%）, and 4.63% （95%CI 0.35%, 8.91%） increase of preterm birth. We did not find any significant acute effect of outdoor air pollution on preterm birth in the week before birth. Conclusion Ambient air pollution may contribute to the risk of preterm birth in Shanghai. Our analyses also strengthen the rationale for further limiting air pollution level in the city.

Diurnal Variations of Air Pollution and Atmospheric Boundary Layer Structure in Beijing During Winter 2000/2001

The diurnal variations of gaseous pollutants and the dynamical and thermodynamic structures of the atmospheric boundary layer (ABL) in the Beijing area from January to March 2001 are analyzed in this study using data from the Beijing City Air Pollution Observation Field Experiment (BECAPEX). A heavy pollution day (22 February) and a good air quality day (24 February) are selected and individually analyzed and compared to reveal the relationships between gaseous pollutants and the diurnal variations of the ABL. The results show that gaseous pollutant concentrations exhibit a double-peak-double-valley-type diurnal variation and have similar trends but with different magnitudes at different sites in Beijing. The diurnal variation of the gaseous pollutant concentrations is closely related to (with a 1-2 hour delay of) changes in the atmospheric stability and the mean kinetic energy in the ABL.

Characteristics of Surface Solar Radiation under Different Air Pollution Conditions over Nanjing, China: Observation and Simulation

Surface solar radiation (SSR) can affect climate, the hydrological cycle, plant photosynthesis, and solar power. The values of solar radiation at the surface reflect the influence of human activity on radiative climate and environmental effects, so it is a key parameter in the evaluation of climate change and air pollution due to anthropogenic disturbances. This study presents the characteristics of the SSR variation in Nanjing, China, from March 2016 to June 2017, using a combined set of pyranometer and pyrheliometer observations. The SSR seasonal variation and statistical properties are investigated and characterized under different air pollution levels and visibilities. We discuss seasonal variations in visibility, air quality index (AQI), particulate matter (PM10 and PM2.5), and their correlations with SSR. The scattering of solar radiation by particulate matter varies significantly with particle size. Compared with the particulate matter with aerodynamic diameter between 2.5 μm and 10 μm (PM2.5-10), we found that the PM2.5 dominates the variation of scattered radiation due to the differences of single-scattering albedo and phase function. Because of the correlation between PM2.5 and SSR, it is an effective and direct method to estimate PM2.5 by the value of SSR, or vice versa to obtain the SSR by the value of PM2.5. Under clear-sky conditions (clearness index ≥0.5), the visibility is negatively correlated with the diffuse fraction, AQI, PM10, and PM2.5, and their correlation coefficients are ?0.50,?0.60,?0.76, and ?0.92, respectively. The results indicate the linkage between scattered radiation and air quality through the value of visibility.

Tobacco, air pollution, environmental carcinogenesis, and thoughts on conquering strategies of lung cancer

Each year there will be an estimated 2.1 million new lung cancer cases and 1.8 million lung cancer deaths worldwide.Tobacco smoke is the No.1 risk factors of lung cancer,accounting for>85%lung cancer deaths.Air pollution,or haze,comprises ambient air pollution and household air pollution,which are reported to cause 252,000 and 304,000 lung cancer deaths each year,respectively.Tobacco smoke and haze(hereafter,smohaze)contain fine particles originated from insufficient combustion of biomass or coal,have quite similar carcinogens,and cause similar diseases.Smohaze exert hazardous effects on exposed populations,including induction of a large amount of mutations in the genome,alternative splicing of mRNAs,abnormalities in epigenomics,initiation of tumor-promoting chronic inflammation,and facilitating immune escape of transformed cells.Tackling smohaze and development of multi-targets-based preventive and therapeutic approaches targeting smohaze-induced carcinogenesis are the key to conquer lung cancer in the future.

Progress of Air Pollution Control in China and Its Challenges and Opportunities in the Ecological Civilization Era

China’s past economic growth has substantially relied on fossil fuels,causing serious air pollution issues.Decoupling economic growth and pollution has become the focus in developing ecological civilization in China.We have analyzed the three-decade progress of air pollution controls in China,highlighting a strategic transformation from emission control toward air quality management.Emission control of sulfur dioxide(SO2)resolved the deteriorating acid rain issue in China in 2007.Since 2013,control actions on multiple precursors and sectors have targeted the reduction of the concentration of fine particulate matter(PM2.5),marking a transition to an air-quality-oriented strategy.Increasing ozone(O3)pollution further requires O3 and PM2.5 integrated control strategies with an emphasis on their complex photochemical interactions.Fundamental improvement of air quality in China,as a key indicator for the success of ecological civilization construction,demands the deep de-carbonization of China’s energy system as well as more synergistic pathways to address air pollution and global climate change simultaneously.

Application of DALYs in Measuring Health Effect of Ambient Air Pollution:A Case Study in Shanghai,China

Objective To investigate the effect of ambient air pollution on human health and the subsequent disabillty-adjusted life years （DALYs） lost in Shanghai. Methods We used epidemiology-based exposure-response functions to calculate the attributable number of cases due to air pollution in Shanghai in 2000, and then we estimated the corresponding DALYs lost in Shanghai based on unit DALYs values of the health consequences. Results Ambient air pollution caused 103 064 DALYs lost in Shanghai in 2000. Among all the health endpoints, premature deaths and chronic bronchitis predominated in the value of total DALYs lost. Conclusion The air pollution levels have an adverse effect on the general population health and strengthen the rationale for limiting the levels of air pollution in outdoor air in Shanghai.

Leaching behavior of Pb and Zn in air pollution control residues and their modeling prediction

Increasing attention has been paid to air pollution control （APC） residues in China recently due to the rising proportion of waste incineration and the hazardous characteristics of the residues, among which heavy metal leaching toxicity plays an important role. Leaching behavior and potential risk of Pb and Zn in the APC residues from a Shanghai municipal solid waste （MSW） incinerator was studied, based on the leaching tests under different conditions and theoretical calculation using a geochemical thermodynamic equilibrium model MINTEQA2. Results showed that, extractant species and liquid to solid （L/S） ratio predominantly controlled the leaching toxicity of Pb and Zn, while ionic strength, vibration method and leaching time had less effect on the metals release. Leachate/final pH determined the metal leaching behavior, which changed the speciation of heavy metals in the extraction system. The equilibrium aqueous speciation, precipitation-dissolution of Pb and Zn was investigated according to the model computation, which was well in agreement with the experimental results.

Health and Economic Impacts of Air Pollution in China: A Comparison of the General Equilibrium Approach and Human Capital Approach

In China, combustion of fossil fuels and biomass has produced serious air pollution that does harm to human health. Based on dose-response relationships derived from epidemiological studies, the authors calculated the number of deaths and people with health problems which were thought to be attributable to China＇s air pollution in the year of 2000. In order to estimate the corresponding economic impacts from the national point of view, the general equilibrium approach was selected as an analysis tool for this study. A computable general equilibrium （CGE） model was constructed involving 39 sectors and 32 commodities. The human capital approach （HCA） was also used for comparison. The economic burden of disease for people estimated by HCA was equivalent to 1.26‰ （ranging from 0.44‰ to 1.84‰） of China＇s gross domestic product （GDP）. China＇s GDP loss estimated by the general equilibrium approach reached 0.38‰ （ranging from 0.16‰ to 0.51‰）. The difference between the two approaches and the implications of the results were discussed.

Characteristics of air pollution events over Hotan Prefecture at the southwestern edge of Taklimakan Desert, China

Hotan Prefecture is located at the southwestern edge of Taklimakan Desert, the world＇s largest shifting sand desert, of China. The desert is one of the main sources for frequent sand-dust weather events which strongly affect the air quality of Hotan Prefecture. Although this region is characterized by the highest annual mean PMlo concentration values that are routinely recorded by environmental monitoring stations across China, both this phenomenon and its underlying causes have not been adequately addressed in previous researches. Reliable pollutant PM_10 data are currently retrieved using a tapered element oscillating microbalance （TEOM） 1400a, a direct real-time monitor, while additional concentration values including for PM_2.5, sulfur dioxide （SO_2）, nitrogen dioxide （NO_2）, carbon monoxide （CO） and ozone （O_3） have been collected in recent years by the Hotan Environmental Monitoring Station. Based on these data, this paper presents a comparison of the influences of different kinds of sand-dust weather events on PM_10 （or PM_2.5） as well as the concentrations of other gaseous pollutants in Hotan Prefecture. It is revealed that the highest monthly average PM_10 concentrations are observed in the spring because of the frequent occurrence of three distinct kinds of sand-dust weather events at this time, including dust storms, blowing dust and floating dust. The floating dust makes the most significant contribution to PM_10 （or PM_2.5） concentration in this region, a result that differs from eastern Chinese cities where the heaviest PM_10 pollution occurs usually in winter and air pollution results from the excess emission of local anthropogenic pollutants. It is also shown that PM_10 concentration varies within wpical dust storms. PM_10 concentrations vary among 20 dust storm events within Hotan Prefecture, and the hourly mean concentrations tend to sharply increase initially then slowly decreasing over time. Data collected from cities in eastern China show the opposite with the hourly mean PM_10 （or PM_2.5） concentration tending to slowly increase then sharply decrease during heavy air pollution due to the excess emission of local anthropogenic pollutants. It is also found that the concentration of gaseous pollutants during sand-dust weather events tends to be lower than those cases under clear sky conditions. This indicates that these dust events effectively remove and rapidly diffuse gaseous pollutants. The analysis also shows that the concentration of SO_2 decreases gradually at the onset of all three kinds of sand-dust weather events because of rapidly increasing wind velocity and the development of favorable atmospheric conditions for diffusion. In contrast, changes in O_3 and NO_2 concentrations conformed to the opposite pattern during all three kinds of sand-dust weather events within this region, implying the inter transformation of these gas species during these events.