Air Pollution Research Articles

Assessment of Air Pollution and Lagged Meteorological Effects in an Urban Residential Area of Kenitra City, Morocco

Complex mixtures of air pollutants, including ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), black carbon (BC), and fine particulate matter (PM2.5), present significant health risks. To understand the factors influencing air pollution levels and their temporal variations, comprehensive high-resolution long-term air pollution data are essential. This study analyzed the characteristics, lagged meteorological effects, and temporal patterns of six air pollutant concentrations over a one-year period at an urban residential site in Kenitra, Morocco. The results reveal pronounced seasonal and diurnal variations in pollutant levels, shaped by meteorological factors, emission sources, and local geographic conditions. PM2.5, SO2, and CO concentrations peaked during winter, while NO2 and CO exhibited consistent diurnal peaks during morning and evening rush hours across all seasons, driven by traffic emissions and nocturnal pollutant accumulation. In contrast, O3 concentrations were highest during summer afternoons due to photochemical reactions fueled by strong UV radiation, while winter levels were the lowest due to reduced sunlight. Lagged meteorological effects further highlighted the complexity of air pollutant dynamics. Meteorological factors, including temperature, wind speed, humidity, and pressure, significantly influenced pollutant levels, with both immediate and lagged effects observed. Lag analyses revealed that PM2.5 and BC levels responded to wind speed, temperature, and humidity over time, highlighting the temporal dynamics of dispersion and accumulation. CO is sensitive to temperature and pressure changes, with delayed impacts, while O3 formation was primarily influenced by temperature and wind speed, reflecting complex photochemical processes. SO2 concentrations were shaped by both immediate and lagged meteorological effects, with wind direction playing a key role in pollutant transport. These findings emphasize the importance of considering both immediate and lagged meteorological effects, as well as seasonal and diurnal variations, in developing air quality management strategies.

The establishment of blue-sky index: how to quantify the aerosol optical impacts on sky color

Abstract Color of the sky serves as a direct indicator of haze, while also exerting substantial influence on human physiological and psychological well-being, as well as the overall environmental scenery. However, quantifying color changes is quite challenging. This research develops a quantitative approach for evaluating the influence of atmospheric aerosol pollution on the appearance of the sky. We first calculated the influence of atmospheric aerosols on the sky’s diffuse radiation, which is the source of sky color. Then, we mapped the diffuse radiation onto a perceptually uniform color space to quantify alterations in sky color. The results reveal that the relationship between aerosol concentration and sky color change follows a logarithmic-like distribution: the higher the concentration, the weaker the change in sky color per unit increase in aerosol concentration. Consequently, during the early phases of air pollution control implementation, there may be minimal observable changes in the color of the sky. However, as these measures are further enforced, a discernible bluing effect on the sky will become evident. Based on the quantification of the change of sky color, a blue-sky index (BSI) was established. We find that concurrent with improvements in air quality resulting from emission reduction measures, the BSI has significantly decreased in recent years in China. This trend indicates an increase in the frequency of blue-sky occurrences.

Collaboration, accountability pressure, and local air pollution governance: evidence from China

Collaboration, accountability pressure, and local air pollution governance: evidence from China

Numerical study on the application of low-turbulence air curtain surrounding laminar airflow distribution in operating rooms

Abstract Laminar airflow (LAF) is essential for maintaining a sterile environment in operating rooms, but its rapid unidirectional flow decay leads to low airflow efficiency and increases energy consumption. The objective of this study is to investigate the energy-saving and air quality benefits of using a low-turbulence air curtain around laminar airflow, which is referred to as protective laminar airflow (PLAF). Numerical simulations were used to model airflow and particle transport, and a series of experiments were conducted in a real operating room at St. Olavs Hospital, Norway, to validate the simulation results. The findings indicate that when the unidirectional airflow supply velocity is maintained at 0.25 m/s, combined with an air curtain that has the width of 2 cm and the velocity of 1.5 m/s, the PLAF system outperforms the conventional LAF system operating at a unidirectional airflow supply velocity of 0.30 m/s. This configuration results in a 17.3% energy saving, showing the potential of this airflow distribution strategy to enhance both cleanliness and energy efficiency.

Toward Sustainable Non‐Emitting Asphalts: Understanding Diffusion–Adsorption Mechanisms of Hazardous Organic Compounds

AbstractAdvancing sustainable materials requires addressing their environmental impacts, particularly emissions. This study contributes to the development of sustainable, non‐emitting asphalt by providing a detailed understanding of the diffusion and adsorption behaviors of hazardous organic compounds (HOCs) emitted from asphalt. Using molecular simulations and quantum analysis, it is investigated how the diffusion and adsorption characteristics of sulfur‐ and oxygen‐containing HOCs change as aging progresses in asphalt. The results show that oxidation reduces the diffusion rate of HOCs and increases their adsorption energy. Dispersion forces and electrostatic attractions are key mechanisms stabilizing HOCs within the asphalt matrix. As oxidation progresses, hydrogen bonding and polar interactions between asphaltenes and highly polar HOCs become dominant. Among the asphalt components, asphaltenes, followed by resins, have the most significant impact on HOC binding. Additionally, non‐aromatic HOCs exhibit higher diffusion rates than aromatic HOCs. These findings provide crucial insights into the emission mechanisms of asphalt over its service life and offer guidance for designing future, sustainable, emission‐free asphalts. By reducing harmful emissions, this research contributes to pollution control, improved air quality, and the broader goal of sustainable pavement development.

Investigation of Vertical Profiles of Particulate Matter and Meteorological Variables up to 2.5 km in Altitude Using a Drone-Based Monitoring System

In this study, a drone-based measurement system equipped with miniaturized optical and condensation particle counters was deployed to investigate the vertical distribution of particulate matter and meteorological variables up to 2.5 km in altitude. Measurements captured at various altitudes demonstrated notable vertical variations in particle concentration and significant correlations with meteorological factors, particularly relative humidity (RH). Near the surface, within a well-mixed boundary layer, particle concentrations remained stable despite RH changes, indicating both anthropogenic and natural influences. At higher altitudes, a clear positive relationship between RH and particle number concentration emerged, particularly for smaller particles, while temperature inversions and distinct wind patterns influenced aerosol dispersion. The unmanned aerial vehicle system’s robust performance, validated against standard meteorological tower data, underscores its potential for high-resolution atmospheric profiling. These insights are crucial for understanding particle behavior in diverse atmospheric layers and have implications for refining air quality monitoring and climate models. Future work should incorporate chemical analysis of aerosols to further expand these findings and assess their environmental impact.

Air quality protection behaviour and stock returns of public companies: Sectoral aspects

In the new economic reality, air quality protection behaviour of companies remains a burning issue shifting the em phasis towards saving human life and health. The article explores the relationship between the air quality protection behav iour of public companies and stock returns in different economic sectors. The research methodology is based on environmental management theory, financial management theory, and stakeholder theory. The analytical procedures performed on the data involved cross-sectoral economic analysis and econometric analysis. Empirical data are retrieved from the Federal State Statistics Service (Rosstat) and the Moscow Exchange and cover statistics on 45 public joint-stock companies (PAOs) from five sectors of the economy for the period of 2014–2022. Cross-sectoral economic analysis has shown that investors lack interest in PAOs’ air quality protection behaviour and invariably favour companies from the sectoral indices paying higher dividends compared to the Moscow Exchange, such as Chemicals and Petrochemicals, Metals and Mining, Oil and Gas. By integrating air quality protection factors into the Fama-French-Carhart model through econometric modelling, we estimated the dependence of returns of indus try portfolios on these factors and classical risk premiums. The study demonstrates a positive impact of market premium and size premium on returns of industry portfolios. No statistically significant impact of air quality protection factors on stock returns was found. Our empirical findings confirm that businesses are poorly motivated to take air environment protection measures and air pollution-reducing behaviour should be encouraged at the state level.

Air quality and the risk of acute atrial fibrillation (EP-PARTICLES study): A nationwide study in Poland

Abstract Aim Air pollution remains the single largest environmental health risk factor, while atrial fibrillation (AF) is the most prevalent arrhythmia globally. The study aimed to investigate the relationship between short-term exposure to air pollution and acute AF admissions. Methods Individual data on AF hospitalization in the years 2011-2020 were collected from the National Health Fund in Poland (ICD-10: I48.XX). To obtain high-resolution data on air pollution we applied a modelling method using the GEM-AQ model. Associations between air pollution exposure and acute AF admissions were estimated using generalized additive models with Poisson regression. Results Over the analysed period, we recorded 252,566 acute admissions due to AF. Each 10 µg/m3 increment of PM2.5 and NO2 concentration, 1 µg/m3 of SO2 and 10 ng/m3 of benzo(a)pyrene (BaP) concentration on the day of exposure resulted in 1.13% (0.70%−1.55%), 1.65% (1.05%−2.26%), 0.11% (0.01%−0.21%), and 0.3% (0.04%−0.55%) increases in acute AF admissions, respectively. The estimates are larger for women and older people. Stronger associations between PM2.5 and BaP concentrations and AF admissions in poorly urbanized areas were noted. Areas with high gross domestic product levels were more affected by the increase in NO2 concentrations, resulting in a 0.2% (1.001-1.003) increase in AF admissions. Exposure-response functions show steeper slopes of the pollutant-outcome associations in the lower ranges of exposures, far below World Health Organization (WHO) air quality guideline norms. For the zero-emission scenario, we estimate avoidable AF admissions - 5,873 for PM2.5 (95% CI 3,679 to 8,047) and 3,295 for NO2 (2,108-4,477). Conclusions Air pollution acts as a triggering factor and can be associated with acute AF hospitalisations. PM2.5 and NO2 have an impact on AF even at concentrations levels below WHO air quality guideline norms.

Research on the impact of land use and land cover changes on local meteorological conditions and surface ozone in the north China plain from 2001 to 2020

Land use and land cover changes (LULCC) alter local surface attributes, thereby modifying energy balance and material exchanges, ultimately impacting meteorological parameters and air quality. The North China Plain (NCP) has undergone rapid urbanization in recent decades, leading to dramatic changes in land use and land cover. This study utilizes the 2020 land use and land cover data obtained from the MODIS satellite to replace the default 2001 data in the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model. It simulates and analyzes the direct impact of LULCC on meteorological parameters and the indirect impact on surface ozone (O3) concentration through physical and chemical processes in the North China Plain during July in the summer. Six rapidly urbanizing cities were selected to represent the North China Plain. The results show that LULCC significantly increased sensible heat flux and 2-m temperature in rapidly urbanizing areas throughout the diurnal cycle, with more pronounced effects during the daytime, ranging from 6.49 to 23.46 W/m2 and 0.20–0.59 °C, respectively. The 10-m wind speed decreased at night and increased during the day, with changes ranging from − 0.43 to 0.27 m/s at night and − 0.16 to 0.15 m/s during the day. The planetary boundary layer height generally increased, with a larger rise during the daytime, ranging from 23.63 to 84.74 m. Simultaneously, surface O3 concentrations increased during both daytime and nighttime. The daytime increase ranged from 2.89 to 9.82 μg/m3, while the nighttime increase ranged from 1.76 to 7.77 μg/m3. LULCC enhanced meteorological and chemical processes as well as vertical transport, leading to an increase in O3. At the same time, it reduced the increase in O3 through horizontal transport and dry deposition processes. These changes are related to the meteorological variations. The impact on O3 concentrations was not limited to the surface but extended to the top of the planetary boundary layer (approximately 1500 m). Below 500 m, vertical transport increased O3 concentrations, while horizontal transport decreased O3 concentrations. Additionally, the meteorological and chemical processes induced by LULCC showed enhanced effects above the surface, whereas the dry deposition process had a smaller impact on O3 concentrations above the surface. This study reveals the significant impact of urban expansion on regional meteorological parameters and air quality. It optimizes the model’s simulation of regional air quality and provides new insights into understanding the effects of urbanization on meteorological conditions and air quality.

Development of the next-generation air quality prediction system in the Unified Forecast System framework: Enhancing predictability of wildfire air quality impacts

Abstract The National Oceanic and Atmospheric Administration (NOAA) has developed an advanced regional air quality prediction system (AQPS) within the Unified Forecast System (UFS) framework to improve representations of wildfire emissions and their impacts on air quality predictions. This innovative system integrates the Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) model as a column chemistry model with the UFS-based atmospheric model, operating in an online mode. The calculation of wildfire gas and particulate emissions relies on satellite-derived fire products, high-resolution Regional Hourly Advanced Baseline Imager (ABI) and Visible Infrared Imaging Radiometer Suite (VIIRS) Emissions (RAVE). A period in June and July 2023 with Quebec Canadian wildfires, which severely impacted air quality in the United States (US), was chosen as a case study to assess the predictive capability of the UFS-AQM system. The UFS-AQM predictions of fine particulate (PM2.5) and ozone (O3) were evaluated against AirNow observations from June 15 to July 14, 2023. The results indicate a substantial improvement in PM2.5 predictions when compared to the previous operational forecast. Meanwhile, the system demonstrates a strong ability of predicting O3 exceedance events during the dissipation phase of the wildfire. Furthermore, the online system shows more realistic predictions of aerosol optical depth (AOD) as compared to the previous operational forecast and satellite retrieval data. Finally, this study outlines a plan for further advancing a comprehensive regional AQPS at NOAA.

Analysis of COVID-19 Lockdown to Understand Air Pollution Processes and Their Impacts on Health: A Case Study in the Western Balkans

The effect of COVID-19 lockdown (LD) on many ambient air pollutants (NO, NO2, PM2.5, PM10, O3 and SO2) was assessed for the first time in the Western Balkans with an innovative approach that evaluates a variety of factors including the stringency of the LD measures, the type of location, the pollution sources, the correlation with traffic fluxes and the meteorology. To that end, observations from 10 urban sites were compared with historical time series. The time window 1 February–30 May 2020 was classified in sub-periods on the basis of the stringency of the circulation restrictions. NO2 and O3 are the pollutants most affected by restrictions to population circulation due to lockdown during the first phase of the COVID-19 pandemic, and are well correlated with traffic fluxes. A reduction in fine particulate matter (PM2.5 and PM10) concentrations is observed in all sites only during the full LD periods, while the relation between SO2 average and maximum hourly concentrations and LD periods in industrial and traffic sites vary from site to site. The reduction in NO2 concentrations during the LD resulted in a reduction in mortality associated with air pollution in the largest cities, while the interpretation of the changes in O3 and particulate matter is less clear.

Effects of Gas Flaring On Air and Groundwater Quality in Ebedei and Ashaka, Located in Ukwuani, Delta State, Nigeria

This research examines the effects of gas flaring on air and groundwater quality in Ebedei and Ashaka, located in Ukwuani, Delta State, Nigeria. Data on air pollutants, including sulphur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon dioxide (CO₂), as well as groundwater quality parameters, were collected during both the wet and dry seasons through systematic sampling techniques. The findings indicate that levels of SO₂ and NO₂ exceeded the permissible limits set by the World Health Organization (WHO), posing significant threats to air quality and public health. Conversely, CO₂ concentrations remained within acceptable ranges. Groundwater analysis revealed slightly acidic pH levels, elevated biochemical oxygen demand (BOD), and high concentrations of iron, lead, and phosphates, all surpassing WHO standards and pointing to contamination caused by industrial emissions and acid rain. Statistical analyses demonstrated strong links between SO₂ and NO₂ emissions and groundwater quality, highlighting their harmful effects. Seasonal differences in pollutant levels were minor, suggesting that human activities are the primary source of pollution. The study emphasizes the urgent need for stricter environmental policies, effective pollution control measures, and ongoing monitoring to protect local communities and ecosystems.

Estimation of flint hills tallgrass prairie productivity and fuel loads: a model-based synthesis and extrapolation of experimental data

ContextThe > 25,000 km2 Flint Hills ecoregion in eastern Kansas and northeastern Oklahoma, USA, is an economically and ecologically important area encompassing the largest remaining tallgrass prairie ecosystem in North America. Prescribed fires are used routinely to control invasive woody species and improve forage production for the beef-cattle industry. However, burning releases harmful pollutants that, at times, contribute to air quality problems for communities across a multi-state area.ObjectivesEstablish a modeling framework for synthesizing long-term ecological data in support of Flint Hills tallgrass prairie management goals for identifying how much, where, and when rangeland burning can be conducted to maximize ecological and economic benefits while minimizing regional air quality impacts.MethodsWe used EPA’s VELMA ecohydrology model to synthesize long-term experimental data at the 35 km2 Konza Prairie Biological Station (KPBS) describing the effects of climate, fire, grazing, topography, and soil moisture and nutrient dynamics on tallgrass prairie productivity and fuel loads; and to spatially extrapolate that synthesis to estimate grassland productivity and fuel loads across the nearly 1000 times larger Flint Hills ecoregion to support prescribed burning smoke trajectory modeling using the State of Kansas implementation of the U.S. Forest Service BlueSky framework.ResultsVELMA provided a performance-tested synthesis of KPBS data from field observations and experiments, thereby establishing a tool for regionally simulating the combined effects of climate, fire, grazing, topography, soil moisture, and nutrients on tallgrass prairie productivity and fuel loads. VELMA’s extrapolation of that synthesis allowed difficult-to-quantify fuel loads to be mapped across the Flint Hills to support environmental decision making, such as forecasting when, where, and how prescribed burning will have the least impact on downwind population centers.ConclusionsOur regional spatial and temporal extrapolation of VELMA’s KPBS data synthesis posits that the effects of integrated ecohydrological processes operate similarly across tallgrass prairie spatial scales. Based on multi-scale performance tests of the VELMA-BlueSky toolset, our multi-institution team is confident that it can assist stakeholders and decision makers in realistically exploring tallgrass prairie management options for balancing air quality, tallgrass prairie sustainability, and associated economic benefits for the Flint Hills ecoregion and downwind communities.

Application of Statistical Models in Air Quality Monitoring

Currently, statistical models are vital instruments for examining and forecasting diverse environmental variables, including air quality analysis. With the development of big data, foundational statistical techniquesincluding regression and time series analysisare adapting to manage larger datasets and complex environmental dynamics. This paper examines the recent applications of statistical models used to assess and forecast air quality in Chinese cities based on existing literature and data research. By focusing on various modeling approaches, such as Poisson regression, grey correlation, and neural networks, it discusses the advantages and drawbacks of each model. Furthermore, it examines the enhancement of classical analytical methodologies inside a big data framework to augment the accuracy of air quality analysis and forecasting. The result shows that although datasets have been more extensive, to increase the accuracy of pollution forecasting, diverse data and more excellent computational capabilities are still needed. Advances in machine learning and optimisation algorithms show promise for overcoming these challenges in the future

Moving from monitoring to real-time interventions for air quality: are low-cost sensor networks ready to support urban digital twins?

Modern cities now have an increasing multitude of Internet-of-Things data streams on urban phenomena, including transport, mobility, and meteorology. One area of development has been the use of low-cost sensors to complement (or in some cases, substitute for) regulatory monitoring of ambient air pollution. As part of a bigger integrated approach to monitoring cities, such as Urban Observatories, disparate live data streams can now readily be collated and disseminated via a platform to facilitate the use of hyperlocal data for real-time decision making whilst supporting longer term sustainable development goals. Urban digital twins are the next logical step on this journey and these are becoming increasingly popular as a tool, at least conceptually, to better interpret this data as well as better understand the consequences of management interventions. To date, there are few examples of true digital twins of environmental challenges with many limited to the ‘digital shadow’ stage of development, characterized by lack of bi-directional feedback between the digital model and physical world. Urban Observatories present an opportunity to change this by providing the often overlooked, but crucial, underpinning foundations of urban digital twins. This paper focuses on the utilization of live stream data and demonstrates that air quality applications can provide a realistic target given the density of observations available, which can routinely be combined with other urban datasets to provide the added value and insights needed for urban air pollution management. However, the availability and standardization of live streams of big data is a major challenge and there are issues with interoperability, metadata management, communicating uncertainty, network longevity, data ownership and transparency. This paper contributes insights concerning how to overcome these challenges and calls for common practice in generating and managing live streams of big data.

Allergology : what's new in 2024

In recent years, studies have focused on the in vitro diagnosis of immediate drug reactions, with new recommendations concerning the use of the basophil activation test. Air pollution, particularly fine particles with a diameter of less than or equal to 2.5 m (PM2.5) and less than or equal to 10 m (PM10), is contributing to an increase in emergency room visits and hospital admissions for asthma exacerbations. Skin tests and specific immunoglobulin E assays have highly variable sensitivity and specificity depending on the type of food. Finally, new collaborations between allergists and oncologists have led to the adoption of joint positions, highlighting the possible protective effect of atopy on the development of gliomas.

Weak coupling of observed surface PM2.5 in Delhi-NCR with rice crop residue burning in Punjab and Haryana

Air pollution impacts on human health are of serious concern in northern India, and over the Delhi National Capital Region (NCR) in particular. The Kharif crop residue burning (CRB) is often blamed for degradation of Delhi-NCR’s seasonal air quality. However, the concentration of fine particulate matter (PM2.5) remained stable in Delhi, while the fire detection counts (FDCs) from satellites over Punjab and Haryana declined by 50% or more during 2015–2023. We measured PM2.5, carbon monoxide (CO) and related parameters over Delhi-NCR, Haryana and Punjab from a network of 30 low-cost sensors (CUPI-Gs) in a selected period (September–November) of 2022 and 2023. Measured PM2.5 showed lower concentration in 2023 compared to 2022 at Punjab and Haryana sites, in compliance with FDC reductions. Using the CUPI-G measurements, airmass trajectories, particle dispersion and chemical-transport model simulations, we show that the CRB emissions over Punjab contributed only a meagre ~14% to the overall PM2.5 over Delhi-NCR during October-November 2022. This indicates that there exists only a very weak coupling between PM2.5 mass over Delhi-NCR and the CRB over Punjab, highlighting the effectiveness of the Graded Response Action Plan (GRAP) in controlling air pollution in the region.

Associations Between Ambient PM2.5 and Thyroid Hormones in Pregnant Persons in Puerto Rico

Introduction: This study investigates associations between fine particulate air pollution (PM2.5) exposure and thyroid hormone levels during pregnancy in Puerto Rican individuals, a vulnerable population facing socioeconomic and environmental disparities. Methods: This research draws on data from the PROTECT cohort study and involves 1040 participants to measure the effect of PM2.5 on developmentally important thyroid hormones (TSH, T3, T4, and FT4). Pollution concentrations were linked to participant locations using EPA air quality data and analyzed across two visits during gestational weeks 16–20 and 24–28. Results: The results suggest that PM2.5 exposure is positively associated with maternal T3, T4, and FT4 levels but not TSH. These effects vary by timing, with T3 showing stronger associations later in pregnancy and T4/FT4 earlier. Nonlinear dose–response relationships were observed, suggesting thresholds for certain hormones. Discussion: These findings support previous studies linking altered thyroid hormones to adverse birth outcomes and highlight the potential role of air pollution in disrupting maternal thyroid function and its implications for fetal development, calling for further research into mechanisms and interventions to mitigate these risks.

Genetic and Environmental Influences on Autism Spectrum Disorder: A Multi-Center Study Exploring Gene-Environment Interactions and Biomarkers in Indonesia

Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental condition with a complex etiology involving genetic and environmental factors. This multi-center study investigated gene-environment interactions and potential biomarkers associated with ASD in the Indonesian population. Methods: Children diagnosed with ASD (n=500) and age-matched typically developing controls (n=500) were recruited across five major Indonesian cities. Whole-exome sequencing targeted genotyping, and environmental risk factor assessments were conducted. Biomarker analyses included cytokine levels, oxidative stress markers, and neurotransmitters. Results: Genetic analysis revealed both rare and common variants associated with ASD risk, including variants in CHD8, SCN2A, NRXN1, and novel genes. Prenatal exposures (maternal medication use, infections), perinatal complications (preterm birth, low birth weight), and postnatal factors (pesticide exposure, air pollution) were associated with increased ASD risk. Children with ASD exhibited elevated inflammatory markers (TNF-α, IL-6, IL-1β), increased oxidative stress (higher MDA, lower GSH), and altered neurotransmitter levels (lower serotonin and dopamine) compared to controls. Conclusion: This study provides insights into the interplay of genetic and environmental factors contributing to ASD risk in Indonesia. The identified genetic variants, environmental risk factors, and potential biomarkers may contribute to our understanding of ASD etiology and inform the development of targeted interventions and early detection strategies.

Association between air pollution and lifestyle with the risk of developing mild cognitive impairment and dementia in individuals with cardiometabolic diseases

Lifestyle factors and ambient air pollution are linked to dementia and CMDs, yet few studies have investigated their impact on dementia risk in CMDs patients at the same time. The Cox proportional hazards model was used to evaluate the influence of lifestyle and ambient air pollution on the dementia risk of the CMDs population among 438,681 participants in the UK Biobank. It is found that the risk of developing mild cognitive impairment and dementia in the population seems to increase with the increase in the number of CMDs. There appears to be a statistically significant association between high levels of ambient air pollution, unhealthy lifestyles, and a higher risk of developing mild cognitive impairment and dementia in the CMDs population. It is found that a healthy lifestyle may have an effect modifier role in the association between ambient air pollution and the risk of mild cognitive impairment and the development of dementia in patients with CMDs. Therefore, maybe people with CMDs can lessen the impact of ambient air pollution on their risk of developing mild cognitive impairment and dementia by improving their lifestyle.