Abstract
OBJECTIVE
Air pollution, particularly particulate matter (PM), is a leading environmental risk factor contributing to global morbidity and premature mortality. The World Health Organization’s (WHO) AirQ+© software is a vital tool for assessing the health impacts of air pollution. Our study used this software to estimate premature deaths attributable to long-term particulate matter (PM2.5) exposure in Türkiye in 2019 and explored its relationship with each province’s socio-economic status.
MATERIAL AND METHODS
We conducted an ecological study using annual average PM2.5 levels from air quality stations. Due to limited PM2.5 measurements (only 16% of stations), we derived PM2.5 values from PM10 data using WHO’s conversion coefficient for Türkiye.
RESULTS
We identified the provinces with the highest PM2.5 concentrations and associated mortality: Iğdır, Şırnak, Çorum, Düzce, and Kahramanmaraş had the highest concentrations, while Erzurum, Çorum, Iğdır, Sinop, and Kütahya had the highest mortality rates per 100,000 population. No significant correlation was found between premature deaths and the socio-economic development index of each province. Our study estimated 37,768 premature deaths attributed to long-term PM2.5 exposure in adequately monitored provinces.
CONCLUSION
In 2019, Türkiye faced persistent air pollution, with PM2.5 levels exceeding WHO’s 2021 limits across all provinces and stations. Türkiye lacks specific PM2.5 limits legislation. Our findings provide a fresh insight into the literature, highlighting policy reform needs. However, data deficiencies hindered analysis in some provinces, affecting nearly 20% of the population aged 30 and above and 31% of the total surface area. Therefore, the actual burden of air pollution-related deaths may be higher than our estimates, underscoring the need to address these challenges urgently.
INTRODUCTION
Air pollution is a major public health issue globally, with 99% of the world’s population breathing air exceeding World Health Organization (WHO) pollutant limits.1 Key pollutants include particulate matter (PM10, PM2.5), nitrogen oxides (NO2, NOx), ozone (O3), volatile organic compounds, carbon monoxide (CO), and sulfur dioxide (SO2). PM is composed of solid/liquid particles, including dust, dirt, soot, smoke, and airborne liquid droplets.2 These pollutants, which are among the main air pollutants in Türkiye, consist of carbon, heavy metals, inorganic ions, and polycyclic aromatic hydrocarbons. Wood stoves and forest fires are examples of primary PM sources, while power plants and coal burning are examples of secondary PM sources, which are generated in the atmosphere through intricate chemical reactions involving compounds like SO2 and NO. Factories, cars, trucks, and construction sites can be primary or secondary sources of pollution.2
Particles ranging from 2.5 to 10 µm in diameter are categorized as PM10, also known as coarse particles, while those with a diameter of ≤2.5 µm are labeled as PM2.5, referred to as fine particles.3 Air pollution affects human health in a variety of ways, with particularly prominent health issues in the respiratory, cardiovascular, and cerebrovascular systems. It has been proven that the pathogenic effect of PM2.5 is greater on various body systems through the systemic circulation.4, 5 Epidemiological studies indicate that PM2.5 poses a greater risk factor compared to PM10 concerning premature mortality and long-term health impacts.6 WHO reports that air pollution causes about 7 million premature deaths annually.1 Studies, such as those by Badyda et al.7 in Poland, link PM2.5 exposure to increased mortality rates from lung cancer and cardiopulmonary diseases.
According to the United States Environmental Protection Agency (EPA), vulnerable groups include children, pregnant women, elderly individuals, and those with pre-existing heart and lung conditions.8 Socio-economic status (SES) also influences susceptibility to air pollution. Air pollution is associated with low education and low income.9, 10 PM2.5 exposure is assessed with a comprehensive socio-economic indicator [Socio-economic Development Ranking Research (SEGE)] that is not limited to education and income. Segments of society with low socio-economic levels live in air-polluted regions and industrial peripheries. The relationship between PM2.5 exposure and SES remains complex and context dependent. While some studies indicate that higher SES regions may experience increased PM2.5-related mortality due to greater industrial activity, energy consumption, and urbanization, others suggest a protective effect driven by improved healthcare infrastructure, environmental regulations, and economic investments in pollution control.11 The variability in findings highlights the importance of considering spatial and socio-economic heterogeneity when analyzing air pollution’s health impacts. Studies that rely on broader geographic units, such as province- or city-level data, may overlook localized inequalities, limiting the accuracy of assessments. Therefore, understanding the interaction between PM2.5 exposure and SES at a finer spatial resolution is crucial for developing targeted policies that address environmental justice and public health disparities. An investigation conducted under the Air Pollution and Health: A European Approach 2 project examined the short-term effects of ambient particles on mortality across 29 European cities, highlighting modifications in effects. It revealed that a 10 µg/m3 increase in PM10 or black smoke concentrations in short-term exposures resulted in a 0.6% rise in mortality (95% confidence interval=0.4-0.8%), with slightly higher impacts among the elderly. Additionally, the study demonstrated that variations in effect parameters among cities indicate genuine effect modifications, attributed to distinct city characteristics.12 The countries that suffer the highest exposure to air pollution are low- and middle-income countries.1 It is understood that both outdoor air pollution and SES have negative effects on respiratory outcomes.13, 14 While the direct impact of PM2.5 on mortality has received extensive attention in research, its function as a modifier in relation to the SES-mortality relationship has been infrequently assessed.15 A recent study indicates that neglecting SES factors might underestimate the influence of PM2.5.16 Another recent study revealed that, in general, each 10 µg/m3 increase in the annual mean PM2.5 level corresponded to a 3.8% increase in all-cause mortality.11 Stratified analysis of the same study revealed that districts with lower SES experienced significantly greater health effects from PM2.5 exposure. The analysis was conducted by dividing districts into quartiles based on key SES indicators, including literacy rate, university education rate, urbanization rate, and gross domestic product (GDP) per capita. The impact estimates for the lowest quartile of these indicators were 6.0%, 4.4%, 3.5%, and 4.9%, respectively, compared to their counterparts in the highest quartile. This demonstrates that populations in districts with lower SES are more vulnerable to the adverse health effects of PM2.5 exposure, likely due to reduced access to healthcare, higher baseline exposure levels, and compounded environmental inequalities. These results were statistically significant (P < 0.05).11
Outdoor air pollution is also a public health problem for Türkiye. Research indicates that solely due to coal-fired power plants, Türkiye experiences approximately 2,876 premature deaths, 4,311 hospitalizations, and 637,643 instances of workplace absenteeism annually.17 In a study conducted in Türkiye in 2018, it was found that a total of 44,617 individuals had premature mortality as a result of long-term exposure to PM2.5. This study revealed that the provinces of Iğdır and Kahramanmaraş exhibited the highest estimated mortality rates associated with PM2.5, while the provinces of Manisa and Afyonkarahisar recorded the highest estimated number of deaths per 100,000 population.18
Türkiye lacks a comprehensive analysis of PM2.5 exposure and its associated burden on premature mortality, particularly in the context of socio-economic disparities. Existing studies often focus on global or regional scales, leaving country-specific data for Türkiye underrepresented. Moreover, the integration of socio-economic development indicators in assessing the health burden of PM2.5 exposure remains limited. The aim of this study is to explore the relationship between PM2.5-related mortality in Türkiye for 2019 and the socio-economic development levels of cities, using the WHO’s AirQ+© software, providing a unique framework for understanding the interplay between air pollution and social determinants of health. By highlighting the regional disparities and the magnitude of the problem, this research aims to contribute to the existing literature and guide national strategies for air quality improvement and public health protection.
MATERIAL AND METHODS
This ecological study used WHO’s AirQ+© (v.2.2) software (Regional Office for Europe, European Centre for Environment and Health, Bonn office, Germany), developed by the WHO Regional Office for Europe, to calculate the health impact of air pollution on specific populations.19 AirQ+© has the ability to determine the proportion of a particular health outcome attributable to specific air pollutants in any urban area, country, or region. Additionally, it can predict potential changes in health impacts resulting from changes in air pollution levels compared to current conditions. Concentration/response functions and epidemiological studies provide the foundation for all of AirQ+©’s computations. The software’s concentration/response functions are derived from a meta-analysis and systematic review of epidemiological studies. AirQ+© was employed to predict premature mortality from long-term PM2.5 exposure.20 Calculations involved using the annual average PM2.5 level, converted from PM10 using WHO’s conversion coefficient for Türkiye (0.66327),21, 22 since it is measured only in 16.6% of the stations. Additional components of the calculations included the region’s surface area, the population aged 30+, and the mortality rate of this population, excluding external injuries. Data from 2019 were used to avoid Coronavirus disease-2019 impacts on air pollution levels and mortality rates. The annual average PM2.5 levels for the provinces in 2019 were sourced from the Ministry of Environment, Urbanization, and Climate Change’s air quality stations with sufficient data (90% and above).23 The annual PM10 averages were obtained from the validated data shared in the 2019 Air Quality Bulletin.24 According to these data, provinces with a data availability rate below 90% were excluded. To determine the annual average PM2.5 concentration for a province in 2019, we summed the measured or converted annual average PM2.5 concentrations from all air quality stations in that province and divided the total by the number of stations.
Provincial surface areas were sourced from the data in the document “Provincial and District Surface Areas” of General Directorate of Maps,25 and population aged 30+ data from the Turkish Statistical Institute (TUIK) “Population by Age Groups-2019 Year” database.26 The number of deaths for the 30+ population was calculated by excluding the total number of deaths from external injuries and poisonings in the 0-29 age group by using TUIK “Statistical Regional Units Classification, deaths by gender and age group, 2019” and “External injuries and poisonings” databases.27 To obtain the death rate (per thousand) for the population aged 30+ years, excluding external injuries and poisonings, divide the number of deaths calculated according to provinces by the population aged 30+, and then multiply by 1,000. The map and graphic works were created using the Aldus FreeHand program.
The socio-economic development of the provinces was determined according to the index value of the “SEGE-2017” prepared by the Republic of Türkiye Ministry of Industry and Technology for the year 2017.28 SEGE-2017 is a comprehensive study aimed at measuring the socio-economic development levels of districts in Türkiye. The research evaluates various indicators, including education, health, income levels, employment, infrastructure, social services, and environmental factors. Specifically, SEGE-2017 assesses income levels, literacy rates, accessibility and quality of health services, construction and infrastructure investments, industrial and commercial activities, and overall environmental conditions and quality of life at the district level. Since this study used publicly available air quality and statistical data and did not involve any human participants or identifiable personal information, it did not require ethical committee approval or informed consent.
Statistical Analysis
Data were analyzed statistically using IBM Statistical Package for the Social Sciences statistics, version 29.0 software (IBM Corp., Armonk, NY, USA), and correlation coefficient analyses were performed to assess relationships between variables.
RESULTS
Twenty provinces (Afyonkarahisar, Ağrı, Artvin, Bingöl, Bitlis, Bolu, Denizli, Elazığ, Eskişehir, Hakkari, Karabük, Kastamonu, Konya, Malatya, Mersin, Muğla, Muş, Tunceli, Uşak, Zonguldak) out of 81 were not included in the study due to the data rate being below 90%. Adana and Hatay were not included in the study due to the average PM2.5 level being below 10 µg/m3, which is the WHO-recommended limit value from 2005. As a result, the study contained data from 59 different cities. PM10 was measured in 64% of a total of 347 stations, and only 37.5% of these stations had measurement data covering more than 90% of the time period. PM2.5 was not measured in 71% of the total 347 stations, and only about half (54.5%) of the measuring stations had sufficient PM2.5 measurements. Overall, 16% of the total stations had measurements above 90%.
The annual mean PM2.5 concentration for Türkiye in 2019, based on data from cities with adequate measurements, was found to be 32.2 µg/m3. The provinces with the highest PM2.5 concentration (µg/m3), were Iğdır (78.93), Şırnak (54.27), Çorum (52.45), Düzce (44.14) and Kahramanmaraş (42.48) and the lowest ones were Hatay (8.84), Adana (9.31), Rize (15.61), Afyonkarahisar (16.08) and Nevşehir (16.75) (Figures 1, 2).
Iğdır (33.94), Şırnak (23.38), Çorum (22.56), Düzce (18.55), and Kahramanmaraş (17.76) were the provinces with the highest mortality rate (%) attributable to PM2.5 exposure, while Rize (3.31), Nevşehir (3.95), Kırşehir (6.12), Bayburt (7.08), and Balıkesir (7.09) had the lowest rates (Table 1).
Erzurum (614.4), Çorum (263.7), Iğdır (228.8), Sinop (228.68), and Kütahya (196.05) were the provinces with the highest number of mortality cases per 100,000 population attributable to PM2.5 pollution, while Rize (35.25), Nevşehir (40.11), Van (53.5), Diyarbakır (53.51), and Mardin (59.36) were the lowest (Table 1, Figure 3).
In provinces with adequate measurements, the total number of premature deaths attributed to air pollution in 2019 was found to be 37,768, with which 5,869 in İstanbul, 2,709 in Ankara, 2,534 in Bursa, 2,394 in Erzurum, and 2018 in İzmir (Table 1).
The correlation of premature deaths related to PM2.5 with the socio-economic development index of the provinces was examined. There was no correlation found between the SES of the provinces and premature deaths related to PM2.5.
DISCUSSION
In 2019, Türkiye continued to face significant air pollution issues, with annual average PM2.5 levels exceeding WHO’s recommended limits across all provinces and stations.
Short- and long-term PM exposure is a major cause of morbidity and mortality, linked to respiratory and cardiovascular diseases.4, 5, 14 Additionally, PM and outdoor air pollution are classified as human group 1 carcinogens by the International Agency for Research on Cancer, correlating with bladder and lung cancer.29 Pope et al.’s30 study indicates a 4% increase in overall mortality and a 6% increase in heart-lung disease mortality for every 10 µg/m3 increase in PM2.5. In Türkiye, circulatory system diseases (36.8%), neoplasms (18.4%), and respiratory system diseases (12.9%) were the leading causes of death in 2019.27 39.1% of deaths from circulatory system diseases were attributable to ischemic heart disease, followed by cerebrovascular diseases (22.2%), other heart diseases (25.7%), and hypertensive disorders (7.9%). One important etiological factor of these common diseases, which are responsible for the majority of deaths that occurred in Türkiye in 2019, is continuous exposure to PM2.5. Our findings align with these outcomes, highlighting that air pollution significantly reduces life expectancy, as shown by studies indicating a 0.61±0.20-year increase in life expectancy with a 10 µg/m3 reduction in PM2.5 levels.5 That’s why air pollution, particularly that which is caused by PM2.5, represents a highly significant issue for public health, with its preventability being a crucial aspect.
Despite the severe health impacts, PM pollution monitoring in Türkiye was inadequate. PM10 was measured in 64% of stations, with only 37.5% providing sufficient data. PM2.5 was measured in only 16% of stations with sufficient data. The scarcity of reliable data, especially in regions with high pollution levels and vulnerable populations, clearly demonstrates the urgent need for improved and widespread monitoring capabilities to address the concrete reality of the public health crisis caused by air pollution in Türkiye.
The estimated mortality rate from long-term PM2.5 exposure exceeded 20% in Iğdır, Şırnak, and Çorum, and surpassed 10% in 36 other provinces. We could not determine how PM2.5 exposure contributes to Türkiye’s leading causes of death due to insufficient data, highlighting the need for further research.
In 2019, PM2.5 exposure led to an estimated 37,768 premature deaths in Türkiye (95% confidence interval 25,211-48,970). While this figure is lower than the 44,617 deaths estimated in 2018, it is important to note that the 2019 study covered fewer provinces (59 vs. 72) and used stricter data criteria (90% vs. 75% station data) (Table 2). These stricter criteria were implemented to ensure higher data accuracy but led to the exclusion of 20 provinces due to insufficient data coverage and two provinces due to average PM2.5 levels falling below the limit value. These exclusions represent a significant portion of Türkiye, raising concerns about the underrepresentation of certain regions. These exclusions represent 20.3% of Türkiye’s population aged 30+ and 31.2% of the country’s total area, creating a significant gap in the study’s geographic and demographic representation. The underrepresentation of these regions introduces significant uncertainty into the analysis. Many of the excluded provinces, especially in rural and industrialized areas, may have different pollution profiles or high exposure levels due to local PM2.5 emission sources such as agricultural burning, industrial processes, or transportation corridors. Moreover, the population and geographic areas excluded from this study are not evenly distributed, which may skew the findings. For example, rural areas often lack adequate monitoring infrastructure despite potentially higher exposure levels due to unregulated pollution sources. On the other hand, urban centers such as İstanbul, Ankara, and İzmir, where most premature deaths are recorded, benefit from more comprehensive monitoring. This urban bias further emphasizes the need for even distribution of monitoring stations to ensure that the health impacts of air pollution are fully captured across all regions of the country. The lack of data from these regions may underestimate the true burden of premature PM2.5-related deaths in Türkiye.
When compared to European Union (EU) member countries, where the highest annual mean PM2.5 concentrations in urban areas were recorded in Bulgaria (19.6 µg/m3), Poland (19.3 µg/m3), and Romania (16.4 µg/m3) in 2019, the findings in Türkiye indicate a substantially higher pollution burden.31 The overall annual mean PM2.5 concentration in Türkiye, based on cities with adequate measurements, was 32.2 µg/m3-more than double the EU average (12.6 µg/m3) and far exceeding the WHO-recommended limit of 10 µg/m3. Additionally, certain provinces, such as Iğdır, Şırnak, Çorum, Düzce, and Kahramanmaraş, exhibit PM2.5 levels that are significantly higher than those reported in the most polluted EU countries. In comparison with Poland, which holds the highest concentration of PM2.5 among EU countries, where PM2.5-related deaths ranged from 106 to 242 per 100,000, Türkiye’s 11 largest cities (İstanbul, Ankara, İzmir, Kocaeli, Bursa, Konya, Şanlıurfa, Gaziantep, Antalya, Adana, Mersin) had PM2.5 levels of 9.3-40.1 µg/m3, with premature death rates between 60-176 per 100,000. Poland’s geographical structure, energy resources, and industrial and heating policies may contribute to higher values compared to our country. From another point of view, if sufficient measurements were taken at the stations in these 11 largest cities in Türkiye, similar results could be obtained.
Despite a 23% decrease in air pollution-related deaths in 27 European countries between 2009 and 2019, Türkiye saw no reduction and ranked as the third worst in Europe for preventing air pollution-related premature deaths.32 In 2019, European countries averaged 59.78 PM2.5-related deaths per 100,000, while this study found rates in Türkiye between 35.25 and 614.40. A global meta-analysis estimated 25.3 PM2.5-related deaths per 100,000, which is a figure below Türkiye’s lowest estimate, highlighting the country’s challenges in addressing air pollution.33
In 2019, Türkiye’s crude mortality rate was 5.3 per thousand, with 435,941 total deaths.27 In other words, approximately one-ninth of the total number of deaths can be interpreted as premature deaths attributable to PM2.5. Erzurum province had the highest estimated PM2.5-related mortality, surpassing even the crude death rate of 530 per 100,000.
Vulnerable populations, particularly those of lower SES, are more susceptible to the effects of air pollution.34 It is well known that SES and outdoor air pollution have a negative impact on the functioning of the respiratory and cardiovascular systems.13, 14 A study showed a 3.8% increase in all-cause mortality for every 10 µg/m3 rise in PM2.5, with greater impacts in districts with lower SES.11 Districts with lower SES had greater health effects from exposure, according to stratified analysis. The districts with the lowest quartiles of literacy, university enrollment, urbanization rate, and GDP per capita were estimated to have had an impact of 6.0%, 4.4%, 3.5%, and 4.9%, respectively. There was strong evidence that districts in the lowest quartile compared to those in the highest quartile had a higher risk of PM2.5-related mortality across all socio-economic factors (P < 0.05). A meta-analysis suggests that the negative effects of PM2.5 on mortality may be underestimated if SES factors are disregarded.16 However, this study found no correlation between SES and PM2.5-related premature deaths in Türkiye. This may be sourced from several situations. First of all, in Türkiye, there is a need to investigate the relationship between SES, social classes, air pollution, and individual health levels in the smallest possible settlements. Another issue is that PM2.5 was not measured at all stations, and the stations were far from representing the districts and the city. Additionally, the lack of correlation may stem from the geographic scale of the analysis. Most studies on SES and air pollution focus on smaller regions, such as neighborhoods or districts, where environmental inequalities are more pronounced. However, due to data availability and the current air pollution monitoring structure in Türkiye, province-level analysis remains the most feasible approach. While this broader scale may obscure localized disparities, it provides the best possible assessment within the existing framework. Future research incorporating finer spatial analyses would offer a more nuanced understanding of the relationship between SES and PM2.5-related health outcomes, but this would require an extensive monitoring network, which is currently lacking.
WHO recommends a 5 µg/m3 annual mean PM2.5 limit and a 15 µg/m3 annual mean PM10 limit.35 In the relevant regulations, only a national limit is specified for PM10. As of January 1, 2019, the national annual average limit for PM10 has been set at 40 µg/m3, according to the Air Quality Assessment and Management Regulation (Official Gazette No: 26898, 2008). The lack of a national limit value for PM2.5 in Türkiye is an important problem. Therefore, Türkiye should accept the PM10 limits recommended by WHO as soon as possible and determine the national PM2.5 limit. This will be an important milestone toward preventing the morbidity and mortality caused by air pollution. According to WHO, national conversion coefficients can be used to calculate PM2.5 values, over PM10 values in the event that PM2.5 is not directly measured at stations. However, these calculated values may differ from region to region, and PM2.5 calculations based on PM10 measurements may fail to reflect actual PM2.5 concentrations.
Worldwide, several additional studies utilized the AirQ+© program. Cardito et al.36 conducted an analysis of the concentration levels of six air pollutants (benzene, ground-level O3, CO, nitrogen dioxide, and PM) that were observed by 37 stations in Campania, Italy, in the years 2019-2021. Based on the AirQ+© software’s assessment of the health effects of air pollution, there was a notable decrease in adult mortality in 2020 compared to 2019 and 2021. The potential health benefits of reducing PM2.5 exposure in Eastern Mediterranean Region (EMR), countries in 2019 were estimated by Faridi et al.37 using WHO AirQ+© (v.2.1) software. In different EMR countries, it was estimated that lowering the annual mean PM2.5 exposure level to 5 µg/m3 would result in a 16.9-42.1% decrease in all natural-cause mortality in adults (ages 30+). Reaching the 25 µg/m3 annual mean PM2.5 would help all countries, as it would lower all-cause mortality by 3-37.5%. The health effects of long-term PM2.5 exposure on years of life lost (YLL) and expected life remaining (ELR) indices in Ahvaz city between 2008 and 2017 were investigated by Zallaghi et al.38 using the AirQ+© software. According to the results, over a ten-year period, the highest and lowest YLLs for all age groups were respectively, 137,760.49 (2010) and 5035.52 (2014). Additionally, the ELR index strongly correlated with the PM2.5 concentration and was lower than the EPA and Iranian standards. Using PM data from 25 monitoring stations spread across the region between 2011 and 2019, Arregocés et al.39 estimated the mortality rate attributed to yearly PM2.5 exposure in Colombia’s northern Caribbean region. An estimated 11.6% of acute lower respiratory disease deaths in children under 4 years old, 16.1% of deaths from chronic obstructive pulmonary disease (COPD), and 26.6% of deaths from ischemic heart disease in adults are attributed to prolonged exposure to PM2.5. It was estimated that the annual rates of lung cancer and stroke attributable to PM exposure were 9.1% and 18.9%, respectively. It is estimated that PM pollution directly causes 738 deaths annually. The adult population (aged 18+) had the highest annual death rate, averaging 401 events. The annual average risk of bronchitis prevalence in children due to air pollution was 109 per 100,000 individuals.
In order to quantitatively estimate the number of specific health outcomes from long- and short-term exposure to atmospheric pollutants in São Paulo, Southeastern Brazil, Wikuats et al.40 applied the AirQ+© model to analyze the 2021 data. Lowering São Paulo’s PM2.5 levels, as recommended by WHO, could avert 113 COPD deaths and 24 lung cancer deaths annually. Additionally, it might prevent 258 hospital admissions for respiratory disorders and 163 admissions for cardiovascular disorders, both, brought on by PM2.5 exposure. The findings showed that O3-related excess deaths from cardiovascular and respiratory illnesses were 228 and 443, respectively. In the Marmara Region, which is the area with the highest concentration of urban and industrial mobility in Türkiye between 2016 and 2019, Kahraman and Sivri41 used AirQ+© software to estimate mortality rates in the metropolitan cities of İstanbul, Bursa, Kocaeli, Balıkesir, Sakarya, and Tekirdağ. From 2016 to 2019, a total of 46,920 premature deaths were attributed to exceeding the WHO limit values, with 11,895, 13,853, 11,748, and 9,429 recorded for each year. Thus, AirQ+© is a helpful software that facilitates the development and application of air pollution control measures, to reduce death and economic costs associated with PM2.5 exposure in Türkiye.
The strength of our study lies in its contribution to the body of literature by using AirQ+© software to calculate, for the first time, the estimated number of premature deaths in Türkiye in 2019 that can be attributed to long-term exposure to PM2.5. It is also unique in that it considers the particular conditions of Türkiye and employs data specific to that country. It serves as a catalyst for related research, helps clarify the impacts of air pollution, and establishes the framework for further investigation. This enables us to better comprehend the connection between public health outcomes and air pollution. Calculating the risk of premature death from PM2.5 can help influence political changes such as updating environmental regulations and air quality standards, thereby improving the creation of health policies through public health measures.
This study has several notable limitations. Premature deaths attributable to PM2.5 exposure could not be calculated for the entire population aged 30 and above, and across the entire area, due to data deficiencies and values falling below the threshold in some provinces. These excluded provinces account for a significant portion of Türkiye’s population, meaning the overall burden of PM2.5-related health outcomes may be underestimated.
Additionally, PM2.5 was not measured in 71% of all air quality monitoring stations, and even where measurements were taken, only a small fraction (16%) had data above the 90% reliability threshold. Due to the limited availability of direct PM2.5 measurements, PM2.5 values were derived from PM10 using a conversion coefficient. This situation may limit the accuracy of the analysis. Understanding the actual PM2.5 levels is essential for revealing the morbidity and mortality associated with long-term exposure. However, in Türkiye, there is currently no specified limit value for PM2.5 in air quality regulations, which further complicates efforts to quantify the full scope of health impacts.
Lastly, the analysis was conducted at the provincial level, which may obscure localized environmental inequalities and their associated health impacts. Studies focusing on smaller geographic units, such as districts or neighborhoods, are needed to better capture these disparities.
CONCLUSION
Despite these limitations, this study is the first in Türkiye to estimate premature deaths attributed to PM2.5 using AirQ+© software for 2019. The findings indicate that 37,768 premature deaths could have been prevented in 2019 alone if the PM2.5 limit value recommended by the WHO had been adopted and implemented. Considering the limitations in PM2.5 measurement capabilities, the actual number of deaths attributed to air pollution is likely underestimated. These findings highlight the necessity of establishing a more comprehensive air quality monitoring network and ensuring direct PM2.5 measurements to enhance the reliability of health burden assessments. Expanding the measurement infrastructure would provide more accurate data, allowing for better estimation of the true health impacts of air pollution. Additionally, these findings reinforce the importance of annual measurement and control strategies to evaluate and improve national ambient air quality standards, which are critical for protecting public health and reducing premature mortality caused by air pollution. By addressing existing gaps, this study contributes to the scientific literature and strengthens advocacy efforts for improved air quality policies and monitoring infrastructure.
