Air Pollution Research Articles

Distribution of Air pollutant Concentration and Ammonium conversion rate in Livestock Areas: Focusing on Boryeong

Objectives:The association between the generation of fine particulate matter (PM2.5) and ammonia is well-established, highlighting the importance of managing ammonia as a primary means to reduce particulate matter. However, domestic research on ammonia emissions, particularly in livestock areas, which are major sources of ammonia, is insufficient. This study aims to contribute to pollutant management on a national scale by conducting air pollutant measurements and analyses in livestock areas. Methods:Real-time analysis and monitoring of air and weather conditions were carried out in Boryeong, Chungcheongnam-do, from 2021 to 2022. Statistical analysis was then employed to investigate the correlation between observed air pollutants (ammonia, nitrogen oxides, sulfur oxides, ozone and particle matters) and PM2.5. Results and Discussion:As a result of the analysis, the concentration of air pollutants in Boryeong showed a seasonal tendancy to decrease in summer and increase after that. Most substances such as NO2, SO2, and PM10 were observed within the standard values. In the case of ammonia, domestic air environment standards are not in place, but the annual average was found to be 61.5 ± 55.3 ppb, higher than in other research results. This discrepancy is attributed to the influence of nearby livestock houses. It was also observed that PM2.5 exceeded the annual standard value of 15 μg/m3 in spring (30.1 μg/m3), summer (18.3 μg/m3), autumn (25.3 μg/m3) and winter (31.7 μg/m3), respectively. During this period, ammonium (NH4+, 32.8%), nitrate (NO3-, 35.9%), and sulfate (SO42-, 19.7%) comprised the majority of particulate pollutants in PM2.5. The ammonia-ammonium conversion rate (NHR) was 0.08 annual average, and it was found that gas/ion phase changes were affected by seasonal weather conditions (temperature and relative humidity). As a result of analyzing the NHR according to the PM2.5 concentration, it was found that the higher the PM2.5 concentration, the higher the NHR. Furthermore, although the measurement area of this study exhibited high ammonia concentration, the NHR was low. This suggests that the contribution rate of ammonia to PM2.5 was relatively low compared to the other studies.Conclusion:As a result, there is a need for measures to reduce the high concentrations of ammonia in livestock areas. Simultaneously, considering the diverse mechanisms involved in particulate matter formation, it is suggested that management of pollutants such as nitrogen oxides, sulfur oxides including ammonia should be implemented.

Effective Air Pollution Monitoring System for Eco Balance

Air pollution in urban areas is increasingly driven by vehicle emissions, which release harmful gases include such things as carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC), and particulate matter (PM). These pollutants pose significant risks to both environmental quality and public health, highlighting the urgent need for effective monitoring and control systems. This project presents the development of an automated Effective Air Pollution Monitoring System for Eco Balance, designed to detect exhaust gas levels in real-time as vehicles pass designated points. The system employs advanced sensors to monitor pollutant concentrations and utilizes a camera- based recognition system to capture the number plates of vehicles that exceed permissible emission levels. The collected data, including pollution metrics and vehicle details, is transmitted to the Regional Transport Office (RTO) for necessary enforcement actions. By promoting compliance with emission standards, this automated system aims to significantly reduce vehicle-related air pollution, fostering a cleaner and healthier urban environment

Evaluation of Machine Learning Application on the Prediction of Particulate Matter Concentrations in Small/Medium-Sized City

Objectives:In this study, Machine Learning (ML) algorithms were evaluated to predict the concentration of particulate matter (PM10 and PM2.5) using air quality and meteorological data in small/medium-sized city.Methods:ML models, including Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest (RF), Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGB), were used to predict PM10 and PM2.5 concentrations. Five air quality variables, including NO2, SO2, CO, PM10 and PM2.5, and seven meteorological variables, including temperature, humidity, vapor pressure, wind speed, precipitation, local atmospheric pressure, and sea-level atmosphere pressure, were collected from three air quality monitoring stations and one meteorological observatory from 2017 to 2022. A total of 52,583 sets of data were used for ML. The prediction accuracies of the applied ML models were evaluated using the Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of determination (R2).Results and Discussion:Higher ML performance was obtained when using the data including PM10 and PM2.5 compared to the data excluding these variables. Among five different ML models, the XGB model showed the highest accuracy in predicting PM10 and PM2.5 one hour in the future. However, poorer performance was obtained as the predicted period increased from one hour to 72 hours.Conclusion:The application of ML algorithms for the short-term prediction of PM10 and PM2.5 was successful in this study. However, more input variables and deep learning algorithms are needed for long-term prediction of PM10 and PM2.5.

Indoor Air Quality Monitoring System

The awareness of the risks associated with contaminated indoor air quality is often lacking among individuals. This study employs a prototyping method, utilizing an Arduino Uno integrated with various sensors to monitor air quality. A sound buzzer alerts users when the sensor readings indicate hazardous conditions. Additionally, a Wi-Fi module connects the Arduino Uno to the internet, facilitating data uploads to the IoT platform ThingSpeak.

Comparative Study of Biosorption and Traditional Methods for Heavy Metal Removal from Industrial Wastewater in Panipat

In this research paper, I have thoroughy described about the topic Comparative Study of Biosorption and Traditional Methods for Heavy Metal Removal from Industrial Wastewater in Panipat.” Industrial wastewater contamination by toxic heavy metals poses a significant environmental threat globally, especially in rapidly industrializing regions like Panipat District in Haryana, India. Panipat, renowned for its extensive textile and chemical industries, generates substantial volumes of wastewater laden with heavy metals such as lead (Pb), cadmium (Cd), and mercury (Hg). Recent studies have revealed that the concentrations of these metals in Panipat's industrial effluents frequently surpass the permissible limits set by environmental regulations. Traditional methods for heavy metal removal, including chemical precipitation and ion exchange, are widely utilized but often entail high operational costs and the generation of secondary pollutants like sludge. Biosorption, an emerging and sustainable technology, offers a promising alternative by utilizing biological materials such as algae, bacteria, and agricultural waste to adsorb heavy metals from wastewater. This study aims to investigate the effectiveness, cost-effectiveness, and environmental impact of biosorption compared to traditional methods in Panipat District. By examining heavy metal removal efficiencies, conducting cost analysis, and assessing environmental implications, this research seeks to provide valuable insights into sustainable wastewater treatment practices.

Distribution of air quality data across stratified areas of Port Harcourt metropolis

Distribution of Air Quality Data across seven stratified areas of Port Harcourt Metropolis was carried out. The study utilized a total of 18 parameters from four different air quality datasets obtained from 24 sampling points during field data collection. The sampling points were structured and stratified into residential, industrial, commercial, recreational, transport, dumpsite and abattoir areas. Air quality data were acquired using a multi-digital potable tool, Aerosol Gas Monitor and TESTO Gas Analyser for meteorological data, particulate matters (PM), gaseous emissions and heavy metals. Results showed that the concentrations of air quality data were not evenly distributed across the seven stratified areas, an indication of the influence of location-based activities on the distribution of air quality parameters. The minimum and maximum values of wind speed, temperature and relative humidity were obtained within Residential and Transport Areas, Abattoir and Dumpsite Areas, and, Industrial and Recreational Areas with numerical values of 1.1ms-1 and 3.7ms-1, 27.20C and 350C, and, 67.8% and 923% for wind speed, temperature and relative humidity respectively. The values of TSP, PM2.5 and PM10 ranged from 53 to 255 μg/m3, 13 to 90 μg/m3 and 40 to 169μg/m3 for TSP, PM2.5 and PM10 respectively with the lowest and highest values obtained within Residential and Dumpsite Areas respectively. The concentrations of NO2 and SO2 exceeded the standards of WHO, NAAQS and FMEnv in Industrial, Dumpsite and Abattoir Areas. Lead ( Pb) showed very high values within Dumpsite Area (0.954mg/kg), Industrial Area (0.372mg/kg) and Transport Area (0.077mg/kg).

State of atmospheric pollution between vulnerabilities and criticalities from 2007 to 2022 and a projection in 2030 focused on the proliferation of gasoline sales in the city of N'Djamena

According to the World Health Organization (2008), 1.3 million annual deaths worldwide are attributable to air pollution, and that the latter is the cause of 16% of the total number of deaths. Among air pollutants, particles play an important role in worsening air quality in urban areas. The city of Ndjamena has recorded an increased proliferation of hydrocarbon stations since 2007 to the present day. The analysis of the vulnerability and criticality of pollutants from 2007 to 2022 and a projection to 2030 were made. For a response relating to the subject of our research, we chemically characterized two types of gasoline by following the recommended parameters. The result obtained following these analyses shows that street gasoline has a more or less negative result compared to gasoline produced, stored and sold in accordance with standards and regulations in Chad. We note that the analyzed contraband gasolines have negative results unlike other types of gasoline sold at the pump (some service stations) in terms of: - ASTM distillation, confirming the presence of significant heavy fractions, the Octane Index, presenting a minimum limit required by the standard for super 90 gasoline. Total sulfur, which reaches the maximum limit required and finally, Corrosion giving the maximum limit required by the standard in terms of corrosion. We also noted the presence of traces of water and unidentified solid debris at the bottom of most of our contraband samples.

Urban green spaces and public realm design in Cairo: Enhancing quality of life and environmental sustainability

The paper explores the pressing challenges and promising initiatives in enhancing urban green spaces and the public realm in Cairo, a metropolis grappling with rapid population growth and environmental degradation. As the city struggles with density, air pollution, and a shortage of green areas—far below the recommended standard for urban health—the article highlights key efforts to revitalize public spaces. Notable projects include the creation of large parks like Al-Azhar Park, the redevelopment of the Nile riverfront through projects such as Mamsha Ahl Misr, and the introduction of green infrastructure solutions like street trees, green roofs, and sustainable urban drainage systems. Despite these advancements, Cairo faces significant obstacles, including limited public land, budget constraints, and water scarcity. However, there are opportunities to address these challenges through innovative urban agriculture, public-private partnerships, and community participation in green space development. The paper suggests that through continued investment and thoughtful urban design, Cairo can foster a more sustainable, livable environment. By integrating green infrastructure into future development projects, the city holds potential to transform its landscape and improve the quality of life for its residents in the coming decades.

Aspects of Developing an Innovative, Energy-Efficient, Low-Emission Co-Generator

Purpose. To develop a model and construct an experimental, innovative co-generator with high energy efficiency and low emissions. This involves developing a system that can efficiently generate both electricity and heat simultaneously while minimizing emissions, contributing to sustainability efforts, and addressing energy demands in a more environmentally friendly manner. Methodology. To achieve the goal, a system approach is utilized, enabling the selection of modelling types for the development of an experimental, cutting-edge co-generation system capable of efficiently producing both electricity and heat with superior energy efficiency and minimal emissions. For this purpose, the following steps were completed: processing and summarizing available literature and patent sources, analysing scientific and technical papers on the selection and application of modelling types in co-generation systems, and considering principles and individual approaches to input data formation for mathematical modelling. This process enables the selection of a mechanism and the creation of simulation models for effective energy production at various enterprises. Findings. Assessment is performed of the energy efficiency of the co-generator system under various operating conditions, comparing it with existing conventional methods of electricity and heat generation. Results are presented of performance testing to determine the system’s capability to simultaneously generate electricity and heat efficiently, considering factors such as output stability, load responsiveness, and overall reliability. Identification and evaluation are performed of innovative technologies and methodologies integrated into the co-generator design, highlighting their effectiveness in enhancing energy efficiency and reducing emissions. Insights into any operational challenges encountered during the construction, testing, and optimization phases, along with proposed solutions or improvements to solve these problems. The analysis of the overall environmental impact of deploying the co-generator showed potential benefits in terms of reduced greenhouse gas emissions and local air quality improvement. Originality. Using a combination of scientific approaches encompassing physics and heat transfer engineering, in accordance with the first law of thermodynamics, such as the conservation laws of energy and entropy, and principles of heat exchange employed to transfer heat between different mediums, gas kinetics have yielded values for the energy transformation coefficient, indicating qualitative characteristics of fuel thermolysis and power generation as the final product. Practical value. The results provide for developing a comprehensive model of an advanced co-generation system capable of efficiently producing both electricity and heat with superior energy efficiency and minimal emissions. It also entails determining the types of models for mathematical modelling at all management levels and establishing a new method for input data formation for both technologies and their subsystems, incorporating additional technological implementations.

Mycological analysis in three schools over four seasons using passive air sedimentation

The aim of the study is the isolation and identification of fungi using passive air sedimentation. This study analyzed 540 mycological samples from three primary schools in Zenica, collected in September, December, February, and May. Each season, 135 samples were taken from five rooms (two classrooms, a gym, a locker room, and a library) in each school. Samples were collected three times daily at three different heights with 15-minute exposure times. Samples were refrigerated and transported in sterile bags, incubated for 24 hours, and inoculated on specific agars with and without additives. Plates were incubated at 37°C and 25°C for up to 7 days, followed by examinations. Petri dishes were used for passive air sampling, and colonies were counted after incubation. The average number of microorganisms (CFU/m³) was calculated using Omeliansky’s method. Statistical methods included the Chi-squared test and p-value. Colony appearance was assessed visually and microscopically using a light microscope. Growth rate, size, structure, and color changes were monitored. In September, the highest mold concentrations were at H. Kikić Primary School (796 CFU/m³, not significant), M. Dizdar Primary School (1260 CFU/m³, not significant), and A. Šantić Primary School (3980 CFU/m³, significant). Penicillium spp. and Alternaria spp. were most prevalent, with Alternaria spp. significant at H. Kikić Primary School. In December, the highest mold/yeast concentrations were at H. Kikić Primary School (4578 CFU/m³, not significant), M. Dizdar Primary School (1924 CFU/m³, significant), and A. Šantić Primary School (2587 CFU/m³, not significant). Penicillium spp. was most prevalent. In February, the highest mold concentrations were at H. Kikić Primary School (4578 CFU/m³, not significant), M. Dizdar Primary School (2786 CFU/m³, not significant), and A. Šantić Primary School (5838 CFU/m³, significant). Aspergillus spp. and Penicillium spp. were equally prevalent. In May, the highest mold/yeast concentrations were at H. Kikić Primary School (6568 CFU/m³, significant), M. Dizdar Primary School (3516 CFU/m³, significant), and A. Šantić Primary School (7431 CFU/m³, significant). Aspergillus spp. was most prevalent. These findings highlight the importance of regular monitoring and implementing appropriate ventilation measures to manage air quality and health concerns in schools.

Forecasting mortality and DALYs from air pollution in SAARC nations

This study investigates the projected impact of air pollution on mortality and Disability-Adjusted Life Years (DALYs) across SAARC countries. Utilizing Time Series and Machine Learning methodologies such as Autoregressive Integrated Moving Average, Exponential Smoothing, and Neural Network, the research aims to accurately forecast the mortality and DALYs attributed to air pollution from 2020 to 2030. Statistical analyses reveal a consistent upward trend in deaths and DALYs during the forecasting period, primarily driven by Ambient Particulate Matter Pollution (APM) and Ambient Ozone Pollution (AOP). Comparing the predictive accuracy of the models, Neural Network outperformed other methods, as indicated by Root Mean Square Error (RMSE) values. Specifically, the study finds that deaths and DALYs due to Ambient Particulate Matter pollution are least prevalent in the Maldives, while India and Pakistan exhibit the highest rates, and deaths and DALYs due to Ambient Ozone pollution are lowest in the Maldives and highest in Bangladesh and Pakistan. Moreover, deaths and DALYs attributed to Household Air Pollution (HAP) are lowest in Pakistan and highest in Nepal. These findings underscore the urgent need for air pollution control measures and informed policymaking in SAARC countries to mitigate the escalating health burden associated with air pollution.

Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions

Abstract. Urban air quality is an important part of human well-being, and its detailed and precise modeling is important for efficient urban planning. In this study the potential sources of errors in large eddy simulation (LES) runs of the PALM model in stable conditions for a high-traffic residential area in Prague, Czech Republic, with a focus on street canyon ventilation, are investigated. The evaluation of the PALM model simulations against observations obtained during a dedicated campaign revealed unrealistically high concentrations of modeled air pollutants for a short period during a winter inversion episode. To identify potential reasons, the sensitivities of the model to changes in meteorological boundary conditions and adjustments of model parameters were tested. The model adaptations included adding the anthropogenic heat from cars, setting a bottom limit of the subgrid-scale turbulent kinetic energy (TKE), adjusting the profiles of parameters of the synthetic turbulence generator in PALM, and limiting the model time step. The study confirmed the crucial role of the correct meteorological boundary conditions for realistic air quality modeling during stable conditions. Besides this, the studied adjustments of the model parameters proved to have a significant impact in these stable conditions, resulting in a decrease in concentration overestimation in the range 30 %–66 % while exhibiting a negligible influence on model results during the rest of the episode. This suggested that the inclusion or improvement of these processes in PALM is desirable despite their negligible impact in most other conditions. Moreover, the time step limitation test revealed numerical inaccuracies caused by discretization errors which occurred during such extremely stable conditions.

8.E. Skills building seminar: Methods for measuring the true health cost of pollution

Abstract Healthy environments are essential for physical and mental wellbeing. Air pollution is considered to be one of the most significant environmental risk factors for ill health and premature death within the European Union. Poor air and noise quality have been linked to the exacerbation of symptoms, hospital admissions, and even premature deaths, especially for those with cardiorespiratory diseases. The associated medical costs and productivity losses therefore also impose a large economic cost. Exposure to environmental stressors disproportionately affects socially disadvantaged groups, and therefore contributes to the large socioeconomic inequities in health observed persistently in Europe. The EU has prioritised action on causes of pollution. For example, its Green Deal outlines ambitious plans to address climate challenges such as pollution and align air quality ambitions closer to the World Health Organization guidelines. Likewise, the European Environmental Agency routinely monitors the mortality burden associated with air pollution, while the impact of environmental noise on European citizens is examined through the Environmental Noise Directive. While in the political scene there is interest to advance the reduction of pollution, efforts are hindered by the lack of an harmonized methodology to quantify the socioeconomic cost of environmental stressors. Currently, researchers working with the burden of disease framework face many challenges in its application in the context of environmental stressors. Among others, these challenges include unmet data needs and major lack of transparency in methodological developments. In this skills-building seminar, we will outline an integrated approach for measuring the true health cost of pollution. This approach is currently being trialled in the EU-funded BEST-COST project, which sets out to improve methodologies for understanding the socioeconomic cost of environmental stressors, focusing on air and noise pollution. The project brings together a consortium of 17 partners from Europe and the USA, and is led by Sciensano, the Belgian institute for health. Through a synergy of theoretical outlines and real-life examples, seminar participants will gain methodological insights in the three key components of this integrated approach - i.e., the quantification of the health burden of environmental stressors via comparative risk assessment, the monetization of Disability-Adjusted Life Years to assess economic impact, and the quantification of environmental health inequalities via a novel area-level based framework. Key messages • There are significant unmet needs with respect to both data and methodologies for quantifying the socioeconomic cost of environmental stressors. • We outline an integrated approach for measuring the true health cost of pollution, combining health burden, economic burden, and environmental health inequalities.

6.E. Practice session: Using European environmental data in public health: datasets and applications

Abstract The European Environment Agency collects, quality-assures and quality-checks data on environment, climate and sustainability. It does so through its network and other institutional partners across 38 European countries. Most of these validated environmental data are publicly available and many can be used by practitioners to assess environmental risks to the health of their communities, as well as for designing and evaluating policies’ effectiveness. The objective of this workshop is to provide public health practitioners and scientists with an overview of the EEA data streams of public health relevance, including on air pollution, noise, water pollution, industrial emissions and climate impacts, among others. It will also highlight existing examples of local and national assessments and communication products based on these data, as well as demonstrating how specifically data on air pollution can be used for a quick health impact evaluation. The format of the workshop will be a practice session of 60 minutes with four presentations, the last being a live example demonstration, and an ample session of questions and answers. Key messages • The EEA collects and publishes large, validated datasets of public health from across 38 member countries, including on air and water pollution, industrial emissions, noise and climate change. • These data can be directly used by practitioners to assess environmental risks to the health of their communities, and to design and evaluate policies, with publicly available models and tools.

Healthy air for healthy minds

Abstract Background The adverse health effects from exposure to air pollution is increasingly known. A recent report shows that at least 95% of the world’s population breathe air containing dangerous levels of pollutants. According to estimates from the World Health Organization (WHO), ambient air pollution is related to 4.2 million deaths every year. Less is known about the association between indoor air (especially particulate matter 2.5 and volatile organic compounds (VOC) pollution and mental health conditions. Many sources of indoor air pollution exist, such as pressed wood products, pesticides, secondhand smoke, stoves, heaters, overcrowding and fireplaces. Aims We aim to synthesize knowledge on the effects of particulate matter 2.5 in indoor air and mental health conditions. Methods We systematically reviewed the association of indoor air pollution with mental health conditions using the databases Pubmed and EMBASE. Results Exposure to indoor air pollutants is associated with increased anxiety and depression and less cognitive performance. These results are robust; however, the impact of PM2.5 is larger for less-educated and female respondents. Females cook with solid fuels and biomass more often. Physical exposure and gender factors overlap in the exposure to indoor air pollutants. Discussion Poor indoor air quality should be part of a comprehensive assessment of factors influencing mental health and cognition. Neuroinflammation might explain the effects of poor air on mental health and cognition. Further research is needed to combine research on the social determinants of mental health and the effects of indoor air. Studies in different settings such as home, work, and hospitals are needed to better understand the specific exposures of indoor air pollution and mental health conditions in different population groups.

Direct current cardioversion and the impact of short-term exposure to air pollution: a report from the nationwide EP-PARTICLES study

Abstract Background Air pollution and atrial fibrillation (AF) represent significant public health challenges, impacting global health considerably. Numerous studies have focused on areas with high or very high air pollution concentrations, our study examines a unique area in Poland characterized by low to moderate air pollution levels. Our research also addresses a commonly overlooked in research type of pollution - Polish smog. Due to its composition rich in particulate matter and the conditions in which it is formed - is characterized by extremely adverse health effects. Aim To explore the correlation between short-term air pollution exposure and the incidence of acute direct current cardioversion (DCC) for AF treatment. Methods The study area encompassed three voivodeships from Eastern Poland at the NUTS-2 level, with a population of 5,429,378 individuals. Data on hospitalizations from 2011 to 2020 were obtained from the National Health Fund. We combined air pollution and weather condition data from both ground monitoring stations and satellite observations. Emergency visits for AF and DCC were identified using ICD-9 and ICD-10 codes. For a national perspective, we applied meta-analytical strategies to the municipality-specific outcomes. The results are presented as percentage increases in admissions (% IR) with 95% confidence intervals (95%CI). Results Over the decade, 190,454 hospitalizations for AF were reported with a standardized hospitalization rate (SHR) of 358 per 100,000/year (SD=113) and 30,291 DCC admissions (SHR=56.9 [SD]=26). The mean age for AF vs. DCC cohort was 69.6 (SD=11.2) vs. 68.7 (SD=10.4) years, with females representing 56.1% (N=106,822) of AF cases vs. 46.1% (N=13,953) of DCC admissions (P<0.001). Each 10 µg/m3 increase in PM2.5, PM10, and NO2 concentration on the exposure day led to 1.6% (1.1%–2.1%), 1% (0.8%–1.6%), and 1.8% (1.1%–2.6%) increases in acute AF admissions, respectively, with effects lasting up to 6 days. Women and older individuals were more vulnerable to AF episodes induced by air pollution (P<0.001). A 10 µg/m3 increase in PM2.5 on the day of admission increased DCC admissions by 1.5% (0.1%–2.9%, P=0.04), with effects persisting for up to 3 days. The impact of PM10 was time-delayed: 1.3% (0.2%–2.4%, P=0.02) for LAG1 (i.e. one day after exposure), and 1.1% (0.1%–2.2%, P=0.4) for LAG2. No significant effects of gaseous pollutants on DCC (SO2, NO2, and BaP) were observed, nor any differences in the effects by age or sex. Exposure-response functions show steeper slopes of the PM2.5 associations in the lower ranges of exposures, far below air quality norms set by the World Health Organization. Conclusions Air pollution acts as a triggering factor for acute AF hospitalizations and DCC. The differential impact of air pollution on AF events between groups highlights that women and older individuals are particularly vulnerable. Air pollution exposure should be considered into AF management and prevention strategies.Pooled exposure–response function: % inc

The Synergy Between CO2 and Air Pollution Emissions in Chinese Cities by 2060: An Assessment Based on the Emissions Inventory and Dynamic Projection Model

Synergizing air pollution control and climate change mitigation has been of significant academic and policy concern. The synergy between air pollution and carbon emissions is one of the measures to understand the characteristics and process of the air pollution–carbon synergistic control, which will also provide valuable information for collaboratively achieving Sustainable Development Goals (SDGs) (such as SDGs 11 and 13). This study establishes a systematic framework integrating emissions inventory and projection models, correlation mining and typology analysis methods to predictively evaluate the synergy and comprehensive coordination between air pollution and carbon dioxide (CO2) emissions in Chinese cities by 2030, 2050, and 2060 under different policy scenarios for air pollution and CO2 emissions control. The results reveal the significant effects of synergistically implementing clean air and aggressive carbon-reducing policies on mitigating air pollution and CO2 emissions. Under the On-time Peak-Net Zero-Clean Air and Early Peak-Net Zero-Clean Air scenarios, the total reduction and synergy for air pollution and CO2 emissions will be more significant, particularly by 2050 and 2060. This study is the first to integrate scenario projection and synergy evaluation in air pollution and CO2 research, providing a novel supplement to the air pollution–climate change synergy methodology based on co-benefit estimation. The methods and findings will also contribute to measuring the achievement and analyzing the interaction of the SDGs.

Climate Change, Air Pollution, African Dust Impacts on Public Health and Sustainability in Europe

Abstract Climate change poses a significant threat to environmental sustainability and public health, leading to extreme weather events, rising sea levels, and biodiversity loss. Research on air pollution from African dust adversely associated with climate change highlights its significant role in trapping heat in the atmosphere and causing heat-related illnesses, cardiovascular disorders, and respiratory ailments. Smog, dust, acid rain, and ozone depletion also negatively impact ecosystems. The methods of the study also include the dynamics of climate change-induced air pollution. The implications for public health and environmental sustainability through GWR modeling and MODIS-NDVI analysis of controlling air pollution are crucial for reducing the climate crisis, safeguarding public health, and maintaining ecosystem sustainability. Results from particulate matter (PM 2.5-10), which consists of tiny particles with varying diameters, can enter the respiratory system through inhalation. This can lead to a diameter of less than 10 μm (PM 2.5-10). According to the relevant legislation, the limit value refers to the daily average value and must not exceed 50 μg/m3. While ozone in the stratosphere serves a protective function against ultraviolet radiation, excessive levels at ground level can be harmful and have been recorded in atmospheric samples ranging from 146.6 μg/m3 up to 702.3 μg/m3. impacting the respiratory and cardiovascular systems. Policy leaders, businesses, and individuals need to be proactive in reducing air pollution, adopting clean energy technology, and implementing stricter pollution rules. Stricter pollution rules, environmentally friendly transportation choices, and the adoption of clean energy technology. The sustainability of the ecosystem and public health are significantly impacted by climate change linked to air pollution. To solve these global problems and move toward a healthier, cleaner future for future generations, we must act now on climate justice. Key messages • Examine the impact of African dust air pollution on public health and its significant impacts from climate change, provide solutions to mitigate its effects on environmental sustainability in Europe. • Public health workers, Policymakers and stakeholders must prioritize reducing emissions and enforcing strict air quality laws to mitigate the negative impact of African dust on European populations.

Air Pollution Reduces the Individuals’ Life Satisfaction Through Health Impairment

Abstract Background The impact of air pollution on individuals’ happiness and life satisfaction (LS), and its relationship to other factors became the focus of recent research. Though, the underlying mechanism of how air pollution impacts LS remains unclear. In this study, we examined the direct and indirect effect of air pollution on individuals’ LS through health mediation. Methods We used longitudinal individual-level data from “Understanding-Society: the UK Household-Longitudinal Study” on 59,492 individuals with 347,377 repeated responses across 11 years (2009-2019) that was linked to yearly concentrations of NO2, SO2, and particulate-matter (PM10, PM2.5) pollution. Generalized structural equation models with multilevel ordered-logistic regression were used to examine the direct effect of air pollution on LS and the indirect effect from health impairment. Results Higher concentrations of NO2 (coefficient = 0.009, 95%CI = 0.007,0.012, p < 0.001), SO2 (coefficient = 0.025, 95%CI = 0.017,0.034, p < 0.001), PM10 (coefficient = 0.019, 95%CI = 0.013, 0.025, p < 0.001), and PM2.5 (coefficient = 0.025, 95%CI = 0.017,0.033, p < 0.001) pollutants were associated with poorer health, while poorer health was associated with reduced LS (coefficient = -0.605, 95%CI = -0.614,-0.595, p < 0.001). Mediation path analysis showed that air pollution impacted individuals’ LS directly and indirectly. The percent of total effect mediated through health was 44.03% for NO2, 73.95% for SO2, 49.88% for PM10, and 45.42% for PM2.5 and the ratio of indirect to direct effect was 0.79 for NO2, 2.84 for SO2, 0.99 for PM10, and 0.83 for PM2.5. Conclusions Health plays a major mediating role in the relationship between air pollution and LS. To alleviate the impact of air pollution on LS, future strategies should focus on health promotion besides reducing air pollution emissions. Key messages • Air pollution is related to lower life satisfaction directly and indirectly through health impairment. • Strategies and policies aiming at reducing air pollution emissions and better health would improve the individual’s life satisfaction and lower the mental health burden.

Cancer mortality attributable to air pollution in Slovakia

Abstract Introduction Air pollution is considered one of the most significant global environmental health risks. According to the Global Burden of Disease estimates, fine particulate matter, a key component of ambient air pollution, was the fifth leading risk factor for mortality worldwide in 2015, contributing to 4.2 million deaths (7.6% of total global deaths). In 2019, ambient air pollution was responsible for 4.5 million deaths. This rise is attributed to the growing levels of air pollution and the increasing incidence of NCDs associated with air pollution. Aim This contribution aims to clarify the possible association between environmental air pollution and cancer in Slovakia in the years 2015-2019 overall and by gender and age. Methodology This ecological study focuses on the population of Slovakia from 2015 to 2019. The data used are from the Global Burden of Disease study (IHME, 2019), the Statistical Office of the Slovak Republic and the Slovak Hydrometeorological Institute. Results In 2019, mortality from NCDs related to environmental pollution accounted for 6.6% of total mortality in Slovakia, which is lower than the global average of 8.3%. Cancer mortality attributable to ambient particulate matter pollution (APMP) was lower in 2019 (2.97 per 100,000, CI 95% 4.43-1.76) than in 2015. Higher cancer mortality rates attributable to APMP, were observed mainly in men (7.18 per 100,950, CI % 10.67-4.31 in 2015) and especially in the 80-84 age group (59.49 per 100,000; CI 95 % 94.60-32.20) in 2015 and in men aged 75-79 (510.76 per 510.76 per 100,000) in 2019. Conclusions While Slovakia has experienced a long-term decline in cancer mortality, bucking the global trend, challenges persist due to the country’s relatively poorer outcomes associated with environmental pollution. Addressing environmental pollution remains a critical aspect of ongoing efforts to enhance population health through targeted strategies and policies. Key messages • The significant impact of environmental pollution on cancer mortality underscores the urgent need for targeted interventions and policies to improve public health outcomes in Slovakia. • Cancer mortality attributable to air pollution differs by gender.