Clarifying the relationship between PM2.5 and ozone complex pollution and synoptic patterns in a typical petrochemical city in the Bohai Rim region of China:Implications for air pollution forecasting and control

Meteorological conditions are vital to PM_(2.5)and ozone(O_(3))complex pollution.Herein,the T-mode principal com-ponent analysis method was employed to objectively classify the 925-hPa geopotential height field of Dongying from 2017 to 2022.Synoptic patterns associated with four pollution types-namely,PM_(2.5)-only pollution,O_(3)-only pollution,Co-occurring of PM_(2.5)and O_(3)pollution,Non-occurring of PM_(2.5)and O_(3)pollution-were characterized at different time scales.The results indicated that synoptic classes conducive to PM_(2.5)-only pollution were“high-pressure top front”,“offshore high-pressure rear”,and“high-pressure inside”,while those conducive to O_(3)-only pollution were“offshore high-pressure rear”,“subtropical high”,and“high and low systems”.The Co-occurring of PM_(2.5)and O_(3)pollution were influenced by high pressure,and the Non-occurring of PM_(2.5)and O_(3)pollution were linked to precipitation and strong northerly winds.The variation in dominant synoptic patterns is crucial in the frequency changes of the four pollution types,which was further validated through the analysis of typical cases.Under the favorable meteorological conditions of high-pressure control with strong northerly winds or a subtropical high and inverted trough both with strong precipitation,there is potential to achieve coordinated control of PM_(2.5)and O_(3)in Dongying.Additionally,measures like artificially manipulating local humidity could be adopted to alleviate pollution levels.This study reveals the importance of comprehending the meteorological factors contributing to the formation of PM_(2.5)and O_(3)complex pollution for the improvement of urban air quality in the Bohai Rim region of China when emissions are high and the concentration of air pollutants exhibits high meteorological sensitivity.

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.

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.

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.

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.

TYPICAL WEATHER CHARACTERISTICS ASSOCIATED WITH AIR POLLUTION IN HONG KONG AREA

With the hourly data of Air Pollution Index （AP1） by Hong Kong Environmental Protection Department （HKEPD） during the 6 years of 2000 - 2005 and NCEP / NCAR reanalysis data of 2.5°× 2.5° wind and pressure fields, the characteristics of API in Hong Kong area and the impacts of typical weather characteristics on the air pollution in Hong Kong have been studied. The results are shown as follows. （1） The API exhibits obvious seasonal variability as the number of air pollution days increases by the year. For most of the local monitoring stations, it is the most from January to March, a little less from July to September and the least from April to June. （2） There are four typical types of weather situations that are responsible for the air pollution in Hong Kong： tropical cyclones, continental cold highs, transformed highs that have moved out to sea and low pressure troughs.

Comprehensive Review on Air Pollution Control Measures for Non-Attainment Cities of Uttar Pradesh, India

Introduction: The Indian state of Uttar Pradesh (UP) for the past many years has been reported to have many cities with highly polluted air quality. The state has been taking meticulous steps in combating air pollution in the form of action plans, introduced especially in its 17 non-attainment cities (NAC). To assess the progress and development of these action plans in UP, the present study has done an in-depth analysis and review of the state’s action plans and city micro action plans. Materials and Methods: In this research study, the analysis of the latest action plan reports, micro action plan reports as well as the recommendations for combating air pollution-related issues in the 17 NAC of the UP state has been well documented. Uttar Pradesh Pollution Control Board (UPPCB) has prepared these reports to highlight the progress of the plans in response to the growing air pollution in these cities. The information present in the reports has been used to further study sector-specific, category-specific action plans, institutional responsibility, and the present status of the action plans. Results: On average, the highest weightage in action plans was given to sector-specific categories such as Road dust and construction activities (24%). It was also observed that Urban local bodies (~50%) were majorly responsible to implement the action points and 56% of the action points were jointly implemented by multiple agencies.

Impact of Air Pollution on Community’s Health, Evidence of Industrial Zone in Masoro, Ndera Sector, Rwanda

Air pollution is among the leading global risks for mortality and responsible for increasing risk for chronic diseases. The aim of this study was to explore the impact of industrial zone air pollution on Masoro community and identify some health problems which are experienced in the communities. The key informants were selected using a purposive sampling technique and random sampling based on polluted areas. During this research, Kibagabaga hospital was consulted to identify different illness associated with air pollution in Ndera industrial zone. Respondents illustrated that a great part of emission came from industry, related activities and vehicles. The findings from the hospital illustrated that the respiratory, hypertension and diabetes dominated the illness in community due to air pollution from industrial zone, which was confirmed in this research with reference to the survey results. Air pollution is one of the greatest environmental threats and has been implicated for several adverse cardiovascular effects including arterial hypertension and diabetes. Air contamination provokes oxidative stress, systemic inflammation, and autonomic nervous system imbalance that subsequently induce endothelial dysfunction and vasoconstriction leading to increased blood pressure. The respondents confirmed that the communities are aware of pollution and experienced the consequences of pollution such as cancer and other complicated illness.

Air Pollution in the Gulf of Mexico

An integral analysis of Air Pollution in the Gulf of Mexico was made considering pollutants emissions assessment and diagnosis;air pollution monitoring;and modeling of air pollution dispersion. Combustion sources considered in this work were: thermoelectric power plants and open flares;and pollutants considered were sulfur dioxide, nitrogen dioxides, particulate matter (PM10 and PM2.5), Total suspended particles (TSP) and carbon monoxide (CO). This study made evident a lack of more recent information and a homogenization in emissions factors in order to know the conditions of air pollution in the Gulf of Mexico in a more reliable way.

The impact of air pollution on the incidence and mortality of COVID-19

Air pollution is the most significant environmental risk factor for all-cause mortality,and it has caused substantial disability-adjusted life-years and economic loss.Air pollution intensified the mortality during past pandemics,Spanish flu in 1918 and SARS-CoV-1 in 2003.It increases host susceptibility and virulence of respiratory infections and reduces viral clearance.Thus,a question arises whether there will be any impact of air pollution on the current pandemic coronavirus disease 2019(COVID-19)?Thus far,history and science are directing towards an immense potential impact of air pollution on the COVID-19 pandemic.Some of the devastated countries with the current pandemic are those with a poor air quality index.Further epidemiological and ecological studies are necessary to confirm this association.Also,countries must mobilize funding for mitigation of air pollution to benefit environmental health and ameliorate its potential effects on pandemics of 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.

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.

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.

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.

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.

Characterization of Air Pollution in Urban Areas of Yangtze River Delta,China

The hallmark of development in the Yangtze River Delta(YRD) of East China has been sprawling urbanization. However, air pollution is a significant problem in these urban areas. In this paper, we investigated and analyzed the air pollution index(API) in four cities(Shanghai, Nanjing, Hangzhou and Ningbo) in the YRD from 2001 to 2012. We attempted to empirically examine the relationship between meteorological factors and air quality in the urban areas of the YRD. According to the monitoring data, the API in Shanghai, Nanjing, Hangzhou slightly declined and that in Ningbo increased over the study period. We analyzed the inter-annual, seasonal, and monthly variations of API, from which we found that the air quality had different temporal changes in the four cities. It was indicated that air quality was poor in winter and spring and best in summer. Furthermore, different weather conditions affected air quality level. The wind direction was considered as an important and influential factor to air pollution, which has an impact on the accumulating or cleaning processes of pollutants. The air quality was influenced by the different wind directions that varied with seasons and cities.

Short-term effects of air pollution on acute myocardial infarctions in Shanghai, China, 2013-2014

Background Although particulate matter, with diameters 〈 2.5 μm （PM2.5） and 〈 10 μm （PM10）, and other pollutants have been associated with cardiovascular morbidity and mortality, the effect of pollutants on acute myocardial infarctions （AMIs） has rarely been investigated in Asia, especially in Shanghai, China. Methods Between 1 November 2013 and 27 April 2014, 972 patients from the Pudong District, Shanghai City, were assessed by the Emergency Medical Service. A case-crossover design was used to analyze exposure to air pollution and the AMI risk. Exposures to PM2.5, PM10, nitrogen dioxide （NO2）, sulphurdioxide （SO2）, and carbon monoxide （CO） were based on the mean urban background levels. The associations among AMI admissions, the included pollutants, temperature, and relative humidity were analyzed using correlation and logistic regression. Results The urban background levels of PM2.5, PM10 and CO were associated with an increased risk of AMI, unlike NO2 and SO2 levels. The OR （95% CI） for AMI were 1.16 （1.03-1.29）, 1.05 （1.01-1.16）, 0.82 （0.75-1.02）, 0.87 （0.63-1.95）, and 1.08 （1.02-1.21） for PM2.5, PM10, NO2, SO2, and CO, respectively. Increases in the air quality index （AQI） were associated with more AMI occurrences. There was no correlation between fluctuations in temperature and relative humidity with AMI hospital admissions. Conclusions Short-term exposure to moderate-serious pollution levels is associated with increased risk of AMI. Increased PM2.5, PM10 and CO levels are related to increased AMI admissions.

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.