From Pollution to Prediction: The Role of Air pollution and Artificial intelligence in Asthma

NVL Suvarchala Reddy, M. Ganga Raju, Nisha Shri C., N. Maheswari, D. Krishnaveni, P. Saritha,

doi:10.5281/zenodo.15582272

Review Paper | Open Access
Volume 02 | Issue 06 | Article Id IJSRT/250305122

From Pollution to Prediction: The Role of Air pollution and Artificial intelligence in Asthma
NVL Suvarchala Reddy* M. Ganga Raju Nisha Shri C. N. Maheswari D. Krishnaveni P. Saritha
Department of Pharmacology, Gokaraju Rangaraju College of Pharmacy, Bachupally, 500090, Hyderabad, India

Abstract

Asthma is a chronic inflammatory disorder of the airways influenced by a combination of environmental and genetic factors, with air pollution being one of the major contributors to its development and exacerbation. Airborne pollutants such as particulate matter (PM), ozone (O?), nitrogen dioxide (NO?), and sulfur dioxide (SO?) can trigger airway inflammation, bronchoconstriction, and impaired lung function, leading to increased asthma attacks and severity. The health burden is particularly significant in children and the elderly, who are more susceptible to pollution-induced respiratory complications. In recent years, artificial intelligence (AI) has emerged as a powerful tool in asthma diagnosis, monitoring, and management. Through machine learning algorithms, predictive models, and real-time data from IoT-based sensors, AI can analyze environmental data and clinical records to predict asthma exacerbations, personalize treatment plans, and monitor pollutant exposure effectively. These AI systems not only enhance patient care by facilitating early intervention but also reduce emergency visits and healthcare costs. Moreover, the integration of AI with environmental monitoring platforms helps identify pollution hotspots and supports informed policymaking to improve air quality. Despite the promise of AI in respiratory health, challenges such as algorithm transparency, data variability, and equitable access remain. Further interdisciplinary collaboration between clinicians, environmental scientists, and data scientists is essential to fully harness AI’s potential. This review highlights the impact of air pollution on asthma and explores how AI technologies can revolutionize asthma care and reduce the global burden of respiratory disease.

Keywords

Artificial intelligence, Asthma management, Environmental pollutants, Machine learning applications, respiratory disease

Introduction

ASTHMA

Asthma is a chronic respiratory disease that affects the airways, leading to inflammation, excessive mucus production, and bronchospasm, which cause breathing difficulties ^[1]. Although asthma is a long-term condition, symptoms such as coughing, wheezing, and shortness of breath may not be present daily. Instead, individuals may experience intermittent episodes of respiratory distress. When asthma symptoms suddenly worsen, leading to an "asthma attack," immediate intervention is required which is depicted in figure 1. Patients are advised to follow their emergency action plans and seek urgent medical attention if symptoms do not improve ^[2].

Figure 1. Development mechanism of allergic reactions in human (a) allergic sensitization and (b) allergic reaction ^[3].

PREVALANCE

Asthma prevalence has been on the rise in many countries, with air pollution identified as a significant contributing factor ^[4]. Outdoor pollutants, in particular, play a crucial role in influencing respiratory health by contributing to both the onset and worsening of asthma symptoms. While there is strong evidence linking short-term exposure to pollutants with asthma exacerbations, the connection between pollution and the development of new asthma cases remains less certain ^[5]. Few studies have examined long-term asthma trends using objective measures. One notable investigation analyzed data from three surveys conducted over a 15-year period in the same school populations, using a standardized approach that included parental questionnaires and exercise challenge tests. The aim of the 2003 survey was to determine whether the increase in asthma symptoms and exercise-induced bronchoconstriction had persisted ^[6]. Asthma severity is now defined primarily by the level of disease control rather than lung function, as reflected in both German and international clinical guidelines. Tools such as the Asthma Control Test (ACT) and Asthma Control Questionnaire (ACQ) are commonly used to evaluate a patient’s control status. Despite advances in therapy that have led to a reduction in hospitalizations and emergency visits, a subset of patients with severe asthma continues to have uncontrolled symptoms, leading to substantial healthcare costs ^[7].

SYMPTOMS

Asthma is a long-term inflammatory disorder affecting the airways, leading to recurring episodes of wheezing, chest tightness, shortness of breath, and airflow blockage. This condition involves increased sensitivity of the airways and temporary narrowing of air passages ^[8], which can cause sudden breathing difficulties. The disease arises from interactions between immune cells like mast cells, eosinophils, and T lymphocytes, along with structural changes in airway tissues. Ongoing inflammation makes the airways prone to frequent symptom flare-ups, particularly during nighttime or early morning hours ^[9].

CAUSES OF ASTHMA

Environmental Irritants

Research indicates that fewer than half of asthma cases are directly linked to allergic sensitivity (atopy) or allergen exposure ^[10]. Emerging focus highlights the potential impact of repeated low-to-moderate exposure to irritants, especially in occupational settings ^[11], where chemicals, dust, or fumes may contribute to asthma development. While irritants alone may have inconsistent effects, their interaction with inhaled allergens could worsen or trigger asthma symptoms ^[12].

Respiratory Infections

Viral and bacterial respiratory infections significantly worsen asthma, often causing severe flare-ups that result in hospitalizations and absenteeism ^[2]. For individuals with asthma, these infections prolong wheezing and breathing difficulties. Early-life infections like respiratory syncytial virus (RSV) are strongly tied to wheezing episodes, though not all cases lead to chronic asthma ^[13]. While most childhood wheezing resolves by adolescence, certain infections m ay impair lung function long-term and elevate asthma risk. Effective management, including adherence to personalized treatment plans, is critical to reducing infection-related complications and improving disease control ^[2].

Impact of Airpollution On Respiratory Health

Air pollution, along with ongoing psychosocial stress, increases oxidative stress in the body, and exposure to pollutants both before and after birth may have a combined negative impact on asthma and lung function given in figure 2 below ^[14]. The connection between air pollution and asthma has become more significant as the global prevalence of asthma and allergic diseases rises ^[15]. Air pollution is a well-established factor that worsens asthma symptoms and is linked to both the development and aggravation of asthma ^[16]. Short-term exposure to pollutants such as particulate matter (PM), nitrogen dioxide (NO?), and sulfur dioxide (SO?) has been shown to increase asthma attacks and respiratory distress ^[17]. These substances can heighten airway sensitivity, increase mucus production, and reduce lung function, making asthma symptoms more severe and raising the risk of other respiratory problems ^[18]. Children and older adults are particularly at risk; even brief exposure to high pollution levels can lead to more emergency department visits for asthma in these groups ^[9]. Additionally, prolonged exposure to pollutants like PM2.5, PM10, and NO? raises the chances of developing chronic respiratory diseases, including asthma, especially in those with genetic susceptibility or unhealthy lifestyles. Overall, both short- and long-term exposure to air pollution significantly harms respiratory health by promoting airway inflammation, decreasing lung function, and increasing the frequency and severity of asthma and other respiratory symptoms ^[19].

Figure 2. Burden of air pollutants on asthma outcomes and socio-economic impact ^[1].

Particulate Matter and Its Impact on Asthma

Particulate matter (PM), particularly fine particles like PM?. ? from combustion sources, is a significant contributor to airway inflammation and asthma morbidity. These particles can penetrate deeply into the lungs, especially in children who are more susceptible due to mouth breathing ^[20]. Exposure to PM is strongly associated with asthma exacerbations, increased use of medication, emergency visits, hospital admissions, and reduced lung function ^[21]. Metal-rich PM—containing vanadium, iron, nickel, and copper—further intensifies inflammation by promoting oxidative stress and immune activation. Studies from regions like Utah Valley and those involving residual oil fly ash (ROFA) demonstrate that lower metal content in PM corresponds with reduced respiratory inflammation ^[22]. Additionally, diesel exhaust particles have been shown to enhance IgE-mediated immune responses and cytokine production, linking PM exposure not only to worsened asthma symptoms but also to increased risks of respiratory illness, especially in polluted environments ^[23].

Ozone and Respiratory Health

Ozone is a significant air pollutant formed through photochemical reactions involving sunlight, nitrogen dioxide, and hydrocarbons—mainly from vehicle emissions. Paradoxically, ozone levels can be higher in rural areas than urban centers due to the breakdown of ozone by nitric oxide in city air ^[24]. Short-term exposure to ozone, particularly during warmer seasons, is consistently linked to increased asthma exacerbations and emergency department visits, with 1- to 8-hour maximum concentrations showing a stronger correlation than 24-hour averages ^[25]. Even at environmental levels (0.1–0.3 ppm), ozone can trigger mild airway inflammation and heightened airway responsiveness, especially during prolonged exposure or physical activity. In individuals with extrinsic asthma, ozone exacerbates allergic airway inflammation by increasing neutrophil and eosinophil infiltration, enhancing allergen sensitivity, and intensifying late-phase allergic responses ^[26]. However, reactions may vary depending on asthma severity, and corticosteroid use appears to mitigate some of these inflammatory effects ^[27].

Nitrogenn Dioxide and Its Effects on Asthma

Nitrogen oxides (NO?), primarily emitted from vehicle engines and fossil fuel power plants, are produced during high-temperature combustion ^[15]. Although it is difficult to isolate the effects of nitrogen dioxide (NO?) due to its coexistence with other pollutants, evidence suggests it plays a synergistic role in exacerbating lower respiratory illnesses, particularly in children. Studies from London, Japan, and California have linked ambient NO? exposure to increased respiratory symptoms, asthma exacerbations, and reduced lung function growth ^[28]. NO?, a key component of traffic-related air pollution (TRAP), is also released indoors during cooking with gas stoves. It penetrates deep into the lungs, inducing oxidative stress and airway inflammation, especially in asthmatics. Even short-term exposures at levels within current regulatory limits can enhance allergic responses and trigger symptoms like wheezing and chest tightness. Long-term exposure has been associated with pediatric asthma and chronic lung diseases, raising concern over the need for stricter short-term exposure standards due to variability in individual sensitivity ^[22].

Sulpher Dioxide and Its Impact on Asthma

Sulfur dioxide (SO?) has a notable impact on asthma, particularly due to its ability to increase airway resistance and trigger respiratory symptoms ^[22]. Asthmatic individuals are far more sensitive to SO? than non-asthmatics, with even low-level exposure capable of causing bronchoconstriction and exacerbating asthma symptoms. While some studies found no direct association between ambient SO? levels and asthma attacks, others using advanced analytical methods have demonstrated its contribution to reduced lung function in asthmatics ^[29]. Experimental models and human exposure data further indicate that SO? can cause airway inflammation and damage resembling chronic bronchitis. Additionally, SO? is metabolized into sulfite and bisulfite ions in the body, forming protein S-sulfonates—potential biomarkers of exposure—especially elevated in asthmatics ^[30]. Though the exact correlation with impaired lung function remains to be fully established, SO?’s role in aggravating asthma and respiratory outcomes is increasingly evident ^[31].

Pathophysiology of Asthma

Role of Immune Cells in Asthma

Immune cells play a central role in the pathogenesis of asthma. Mast cells contribute by releasing mediators such as histamine, prostaglandin D2 (PGD2), and leukotriene C4 (LTC4), leading to bronchoconstriction, inflammation, and mucus secretion. They also produce proinflammatory cytokines and proteases that promote IgE synthesis, eosinophilic inflammation, and airway remodeling, with evidence of chronic activation in both atopic and non-atopic asthma ^[32]. Eosinophils drive airway inflammation through the release of TH2 cytokines and toxic granule proteins that damage the epithelium, with their recruitment and survival supported by IL-5 and exotoxins ^[33]. In acute and severe asthma, neutrophils also accumulate significantly, and their presence is associated with worsened asthma control—particularly in response to inhaled corticosteroids, which reduce eosinophilic inflammation but increase IL-8 expression and neutrophil recruitment ^[34]. Basophils, traditionally known as circulating IgE-responsive cells, are also detected in asthmatic airways and often accompany eosinophil infiltration, although their precise role in acute and chronic asthma is still not fully understood ^[35].

Role of Airway Epithelial Cells

The airway epithelium plays a crucial role in asthma by producing inflammatory mediators in response to cell activation and viral infections. In asthmatic individuals, epithelial injury and abnormal repair may contribute to persistent inflammation and the development of obstructive airway lesions ^[36].

Airway Remodeling in Asthma

Airway remodeling refers to a series of structural changes in the airways, likely resulting from repeated inflammation and epithelial injury, leading to excess matrix protein deposition and growth factor release. These changes, including increased smooth muscle mass and mucosal edema, may reduce airway elasticity and limit responsiveness to bronchodilators ^[37].

Artificial Intelligence [Ai] In Asthma Diagnosis and Treatment

AI and machine learning (ML) have enhanced asthma care by improving diagnosis, classification, monitoring, and treatment. Using tools like neural networks and natural language processing (NLP), these technologies accurately analyze data from electronic health records (EHRs), respiratory sounds, and biomarkers, predict exacerbations, and help personalize treatment—showing potential even in evaluating responses to herbal therapies ^[38]. AI-powered air quality monitoring has advanced through IoT-based sensor networks and cloud platforms, enabling real-time pollutant detection and prediction. By using models like LSTM and SARIMA-LSTM, these tools improve forecast accuracy and help link pollution levels to asthma risks, aiding in timely health interventions ^[39]. AI-integrated indoor air quality systems, using IoT sensors and platforms like Air Cloud, enable real-time, low-cost pollutant monitoring and alerts, while wearable devices track respiratory markers such as FeNO. Together, they support personalized, remote asthma management and early symptom detection ^[40]. AI tools, including machine learning and deep learning models, accurately forecast pollutant levels like PM2.5, NO?, SO?, and VOCs by analyzing complex spatial-temporal data. These forecasts help identify pollution hotspots, enabling timely interventions to prevent asthma exacerbations and improve environmental health management ^[41]. Machine learning models applied to electronic health records (EHRs) can predict asthma attacks more effectively than traditional methods by analyzing complex risk factors. Although these tools show potential for early intervention and reduced hospitalizations, challenges like model interpretability and limited clinical integration still hinder widespread use ^[42]. Machine learning models, including neural networks and support vector machines, are being used to predict asthma exacerbations by integrating clinical and environmental data. While these AI tools show promise for personalized asthma management, issues like class imbalance, lack of validation, and explainability need to be addressed for broader implementation ^[43]. Machine learning and deep learning models trained on large datasets like EHRs can predict asthma exacerbations by analyzing clinical, behavioral, and environmental factors. These tools support personalized care, though data inconsistency and healthcare disparities still challenge their clinical use ^[44]. AI plays a crucial role in predicting air quality, diagnosing asthma, and linking pollution to asthma outcomes by analyzing large datasets. It supports real-time monitoring, personalized asthma management, and optimized pollution control through advanced machine learning and deep learning techniques ^[45]. AI technologies enhance air pollution monitoring, asthma diagnosis, and personalized care by leveraging machine learning, big data, and predictive modeling. These tools improve pollution forecasting, identify exposure sources, support early asthma detection, and offer tailored interventions—ultimately aiding in reducing health burdens and improving respiratory outcomes ^[46]. AI-powered systems play a pivotal role in air quality monitoring and asthma management by predicting pollution levels, identifying sources, and analyzing environmental and health data. Through big data integration and predictive modeling, AI enhances early diagnosis, personalized treatment, and informed healthcare decisions for improved respiratory health outcomes ^[47].

CONCLUSION

Asthma remains a significant global health concern, with air pollution recognized as a major factor in exacerbating symptoms and increasing disease severity. Pollutants such as particulate matter (PM), nitrogen dioxide (NO?), sulfur dioxide (SO?), and ozone contribute directly to airway inflammation, trigger asthma attacks, and impair lung function. These findings underscore the urgent need for stringent environmental regulations and innovative strategies to reduce pollution-related health burdens. In parallel, artificial intelligence (AI) has emerged as a transformative tool in asthma care. Through machine learning algorithms, real-time IoT-enabled sensors, and predictive modeling, AI supports early detection of asthma exacerbations, personalized treatment plans, and real-time air quality monitoring. These technological advances offer the potential to improve individual health outcomes and ease the burden on healthcare systems. Future research should aim to integrate AI tools more effectively into clinical settings, addressing current limitations such as data variability, algorithm transparency, and equitable access. Collaboration between environmental scientists, clinicians, and policymakers is essential to fully leverage AI innovations in combating air pollution and managing asthma. Overall, the intersection of AI and environmental health science presents a promising avenue for advancing respiratory healthcare. Embracing these tools can lead to more effective asthma management and a reduction in pollution-induced respiratory complications. Asthma remains a widespread health issue globally, with air pollution playing a major role in worsening symptoms and increasing the frequency of attacks. Pollutants like particulate matter (PM), nitrogen dioxide (NO?), sulfur dioxide (SO?), and ozone are directly linked to airway inflammation, asthma exacerbations, and reduced lung function, resulting in millions of emergency hospital visits each year. These facts emphasize the urgent need for stronger environmental regulations and innovative solutions to reduce the health risks associated with air pollution. Simultaneously, artificial intelligence (AI) is revolutionizing asthma care. Machine learning, real-time sensor technology, and predictive analytics are enabling earlier identification of asthma flare-ups, more personalized treatment approaches, and continuous monitoring of air quality. These technological advances have the potential to improve patient outcomes and alleviate the burden on healthcare systems. Looking forward, it is essential for research to focus on integrating AI more thoroughly into clinical practice, addressing challenges like data reliability, algorithm transparency, and equitable access to these technologies. Effective collaboration among environmental scientists, clinicians, and policymakers will be key to maximizing the benefits of AI in addressing air pollution and managing asthma. In conclusion, combining AI with environmental health science offers a promising direction for improving respiratory health. Utilizing these tools can lead to better asthma management and a significant decrease in pollution-related respiratory illnesses.

ACKNOWLEDGEMENTS

The authors are grateful to the Principal Prof. M. Ganga Raju and Management of the Gokaraju Rangaraju College of Pharmacy, for the constant support and encouragement during the course of the work.

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