Short-term association between air pollutants and outpatient visits for conjunctivitis in an arid industrial city of Northwest China: A time-series study

Short-term association between air pollutants and outpatient visits for conjunctivitis in an arid industrial city of Northwest China: A time-series study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Short-term association between air pollutants and outpatient visits for conjunctivitis in an arid industrial city of Northwest China: A time-series study Yanan Zhang, Guorui Song, Bo Zheng, Fei Chen, Lijun Ma, Xiaofeng Luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8454171/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Purpose : This study aims to quantify the short-term association between ambient air pollutants and outpatient visits for conjunctivitis using empirical data. Methods : This study collected daily outpatient visits for conjunctivitis in Jiayuguan City from January 1, 2023 to December 31, 2024, as well as meteorological and air pollutant data during the same period. We used a quasi-Poisson generalized linear regression model that incorporates a distributed lag nonlinear model to analyze the nonlinear relationship and lag effect between pollutant exposure and the risk of outpatient visits for conjunctivitis, and conducted stratified analysis by gender, age and season to identify susceptible populations. Results : A total of 14,598 cases of conjunctivitis were included during the study. The results showed that particulate matter (PM 2.5 and PM 10 ) was not statistically significantly associated with outpatients for conjunctivitis, and the exposure-response curve showed a downward trend. Conversely, gaseous pollutants (NO 2 and CO) showed a significant positive linear correlation with outpatients for conjunctivitis, with the effect being stronger in the cold season. NO 2 was significant at lag1-3, lag5 days and lag02–07 days, with each 10 μg/m 3 increase corresponding to an RR of 1.126 (95%CI: 1.050, 1.208), corresponding to a 12.60% increase in patient visits. CO had the strongest effect at lag07 days (RR =1.836, 95% CI: 1.126, 2.991). Furthermore, NO 2 primarily increases conjunctivitis visits in women and children (0-14 years), while CO exposure is significantly associated with conjunctivitis visits in men and older adults (≥65 years). Conclusions : In this arid, industrial city in Northwest China, gaseous pollutants (rather than particulate matter) are the key environmental factor driving the increase in conjunctivitis outpatient visits. This study reveals the differentiated effects of specific pollutants on populations with different demographic characteristics, highlighting the public health significance of strengthening ocular surface health protection for specific vulnerable subgroups during the cold season. Air pollution Conjunctivitis Distributed lag non-linear model Nitrogen dioxide Carbon monoxide Arid region Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction Conjunctivitis is an inflammation of the conjunctiva, the delicate, transparent mucous membrane covering the anterior sclera and the inner eyelids, clinically manifesting as conjunctival hyperemia, chemosis, epiphora, pruritus, foreign body sensation, and increased discharge. Uncontrolled, these symptoms impair visual comfort and daily functioning. Epidemiologically, conjunctivitis ranks among the most prevalent ocular pathologies globally; in the United States, annual incidence approximates six million cases, exerting a significant economic impact estimated at up to $ 857 million for bacterial management (Azari AA et al. 2013; Schneider JE et al. 2014 ). In China, data from the National Health Commission show that the prevalence of eye and adnexal diseases, including conjunctivitis, reached 3.8‰ in urban areas and 3.6‰ in rural areas by 2018, with a significant upward trend compared to 2013 (Yan K et al. 2023 ). Additionally, the Chinese Center for Disease Control and Prevention reported 289,518 cumulative cases of acute hemorrhagic conjunctivitis between 2013 and 2020, with an average annual incidence of 2.63 per 100,000 population, indicating that conjunctivitis remains a non-negligible public health issue affecting the quality of life and healthcare resources in China (Hu T et al. 2021 ). The etiology of conjunctivitis is multifaceted, encompassing infectious, allergic, environmental, and occupational factors. Infectious conjunctivitis is caused by pathogenic microorganisms, including viruses and bacteria, accounting for over 85% of acute conjunctivitis cases (Azari AA et al. 2013). Allergic conjunctivitis is triggered by allergens like pollen and dust mites, often presenting as a chronic and mild condition (Bilkhu PS et al. 2012 )Other risk factors include physical and chemical irritants, occupational exposure to chemicals or radiation, and improper use of cosmetics or contact lenses (Nichols JJ et al. 2006; Jones AL et al. 2016). In recent decades, rapid global urbanization and industrialization have increased environmental exposure, particularly air pollution, which plays a significant role in the development of conjunctivitis. The conjunctiva, as the ocular surface that contacts the external environment and possesses an extensive blood supply, is particularly vulnerable to airborne pollutants such as particles and gases. These pollutants can disrupt the tear film barrier, induce oxidative stress and inflammation, and ultimately trigger or exacerbate conjunctival inflammation (Upaphong P et al. 2024 ; Alryalat SA et al. 2024 ). A growing body of epidemiologic research associates key air pollutants, including particulate matter (PM 2.5 , PM 10 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), ozone (O 3 ), and carbon monoxide (CO), with elevated risks of outpatient visits or emergency department admissions for conjunctivitis (Zhou J et al. 2023 ; Cheng P et al. 2023 ; Gui S-Y et al. 2023 ; Liu D et al. 2024 ; Ruan Z et al. 2024 ). Time-series and case-crossover studies across East Asia and beyond have consistently reported positive short-term associations in single- and multi-pollutant models. For example, Taiwan and Shanghai studies linked increases in PM and gaseous pollutants to higher conjunctivitis outpatient volumes (Chang C-J et al. 2012 ; Hong J et al. 2016 ); a Japanese study related ambient PM 2.5 to allergic conjunctivitis prevalence (Mimura T et al. 2014 ); Hangzhou and multi-city analyses in China found robust short-term pollution–conjunctivitis associations (Fu Q et al. 2017 ; Lu P et al. 2019 ); city-specific investigations in Hefei and Jinan identified NO 2 as a notable risk factor (Guo H et al. 2021 ; Bao N et al. 2021 ); and a time-series analysis in Tai’an observed cumulative lag effects across multiple pollutants (Chen R et al. 2021 ). Evidence from Korea and Israel using public big data or emergency department records further substantiates generalizability across settings (Khalaila S et al. 2021 ; Nam S et al. 2022 ). Meta-analytic and narrative reviews converge on the conclusion that ambient pollution adversely affects the ocular surface and increases conjunctivitis burden (Chen R et al. 2019 ; Lin C-C et al. 2022 ). Notwithstanding this progress, key knowledge gaps remain. First, a geographic bias is evident: many studies have concentrated on humid or subtropical cities in eastern and southern China, whereas arid and desert climates, characterized by high winds, low humidity, and frequent dust events, are underrepresented (Yan K et al. 2023 ; Cheng P et al. 2023 ; Lu P et al. 2019 ). Although recent analyses from Northwest China began to address this gap, additional evidence from diverse arid settings is needed to improve external validity (Liu D et al. 2024 ). Second, vulnerability patterns require clarification. While some studies suggest stronger effects among females, youths, or in warm seasons, findings are inconsistent across regions and pollutants (Yan K et al. 2023 ; Lu P et al. 2019 ; Nam S et al. 2022 ). Third, nonlinear exposure–response functions and lag structures, including thresholds at which risks accelerate and the duration of cumulative effects, are not fully characterized across climates and pollutant mixtures (Cheng P et al. 2023 ; Trentalange A et al. 2024 ). These gaps are particularly salient in arid environments, where low ambient humidity destabilizes the tear film and may amplify pollutant-induced ocular surface stress. Additionally, dust storm events have been linked to spikes in pediatric conjunctivitis visits ( Abusharha AA et al. 2013; Chien L-C et al. 2014 ). Jiayuguan City in northwestern China (Hexi Corridor, Gansu Province) exemplifies an arid, wind-swept setting with frequent dust episodes and marked seasonal variability. Industrial emissions and regionally transported particulates yield distinctive pollution profiles dominated by PM with winter peaks, while the dry climate plausibly heightens ocular surface susceptibility. Addressing the aforementioned gaps, the present study focuses on conjunctivitis outpatient visits in Jiayuguan to: (1) quantify short-term associations between ambient pollutants (PM 2.5 , PM 10 , NO 2 , CO) and daily conjunctivitis outpatient counts; (2) delineate potential nonlinear exposure–response relationships and distributed lag effects; and (3) identify susceptible subgroups by sex and age, as well as seasonal heterogeneity. To these ends, we analyze daily conjunctivitis outpatient data using a quasi-Poisson generalized linear model coupled with a distributed lag nonlinear model (DLNM). By providing evidence from an under-studied arid region, our study aims to refine risk estimates relevant to desert climates and inform targeted public health strategies for ocular surface protection. 2 Materials and methods 2.1 Study area This study was conducted in Jiayuguan, a prefecture-level city located in the northwestern of Gansu Province, China. As of 2024, Jiayuguan had a population of 315,600 residents. As a major industrial base in northwest China, Jiayuguan pillar industries center on metallurgy, building materials, and equipment manufacturing, with steel metallurgy being particularly prominent. This has formed an industrial system anchored by heavy industry. Jiayuguan experiences a temperate continental desert climate characterized by scarce precipitation, dry air, and abundant sunshine, with significant annual and diurnal temperature variations. Compared to most northern cities, Jiayuguan has a longer heating season, and coal-fired heating remains the primary source for residential warmth during winter. In recent years, through multiple measures including retrofitting coal-fired boilers, optimizing industrial structure, and strengthening pollution emission controls, the city’s ambient air quality has demonstrated an overall trend of gradual improvement. 2.2 Data collection We obtained daily outpatient data visits for conjunctivitis cases from January 1, 2023 to December 31, 2024 from all public hospitals located within the urban district of Jiayuguan. We gathered data on conjunctivitis outpatients classified under ICD-10 codes (including H10.0, H10.1, H10.2, H10.3, H10.4, H10.5, H10.6, H10.7, H10.8, H10.9, etc.) as per the International Classification of Diseases, Tenth Revision (ICD-10), encompassing gender, age, date of visit, and clinical diagnosis. Following the exclusion of patients residing outside Jiayuguan, we quantified the daily outpatient visits for conjunctivitis and subsequently categorized them based on gender (male, female), age (0–14 years, 15–64 years, ≥ 65 years), and season (cold season: October to March, warm season: April to September). We collected daily mean concentrations of PM 2.5 , PM 10 , SO 2 , NO 2 , and CO, in addition to the daily maximum 8-hour average (O 3 8h) for ozone, from the Jiayuguan Ecology and Environment Bureau, covering the period from January 1, 2023 to December 31, 2024. CO concentrations were reported in mg/m 3 , while the concentrations of the other five ambient air pollutants were measured in µg/m 3 . Ambient air pollutant concentrations were continuously recorded at all air quality monitoring stations within Jiayuguan. We calculated the mean concentrations across all stations to represent daily ambient air pollutant exposure levels in Jiayuguan. Concurrently, daily mean temperature (Tem, unit: °C) and relative humidity (RH, unit: %) were obtained from the Gansu Meteorological Bureau for the same period. The locations of air pollutants monitoring stations and hospitals are shown in Fig. 1 . 2.3 Statistical analysis Since that daily outpatient visits constitute a low-probability event generally conforming to a Poisson distribution, and considering that numerous prior studies have indicated the presence of non-linear and lagged associations between air pollutants and conjunctivitis (Yan K et al. 2023 ; Lu P et al. 2019 ; Bao N et al. 2021 ; Chen R et al. 2021 ; Gui Z-H et al. 2024 ). Given the overdispersal Poisson distribution observed in outpatient visit data, this study utilized a distributed lag nonlinear model (DLNM) in conjunction with a quasi-Poisson generalized additive model to examine the relationship between ambient air pollutants and the risk of outpatient visits for conjunctivitis. Meteorological variables (Tem and RH) and temporal parameters were included into the model via the natural cubic spline (ns) function to account for time and confounding influences. The final model incorporated the weekday and holiday variables to account for the effects of the day of the week and holidays. Concurrently, to mitigate multicollinearity, Spearman’s rank correlation analysis was employed for covariate selection; variables exhibiting correlation coefficients exceeding 0.7 were not concurrently included in our models. The finalized models are presented as follows: Log(µt)= α + βXt,l + ns(Temt, df ) + ns(rht, df ) + ns(Timet, df ) + Dow + Holiday In the model above, t represents the day of the day of observation; µt denotes the number of outpatient visits for conjunctivitis on day t; is the constant term; Xt,l is the DLNM cross-basis matrix for each air pollutant and l denotes the number of lag days; β refers to the vector of coefficients for Xt,l, and we defined the matrix for the linear and lagged of air pollutants applying the linear function and the natural cubic spline function. ns denotes natural cubic spline function. Tem t and RH t are daily mean temperature and relative humidity, respectively. Timet is the time variable, which is used to adjust for seasonality and long-term trend. Dow is the dummy variable of the day of week and was controlled in the model; the binary variable Holiday was applied to adjust for the effects of public holidays. The optimal degrees of freedom (df) for meteorological factors, and time was determined by the minimum quasi-Poisson Akaike information criterion and previous similar studies (Yan K et al. 2023 ; Lu P et al. 2019 ; Chen R et al. 2021 ). 3 df was selected to adjust for Tem and RH; a natural spline smooth function of time with 7 df every year was applied to control for seasonality and long-term trend. Given that the harmful effects of pollutants may exhibit a delayed onset, their impact is predominantly observed within the initial week post-exposure. To investigate the temporal lagged effects of multiple air pollutant exposures on conjunctivitis, we employed a maximum lag period of 7 days. This study utilized both single- lag models (lag0–lag7 days) and cumulative lag models (lag01–lag07 days) to estimate the associations between air pollutants and conjunctivitis across varying lag periods. We selected the lag time corresponding to the maximum RR value for each pollutant, then fit the exposure–response curve, and sensitivity analyses. Furthermore, we performed stratification analyses by gender, age and season. Several sensitivity analyses were implemented to assess the robustness of the primary findings. Initially, the degrees of freedom (df) in the single-pollutant model were varied, evaluating 6–10 df per year for the temporal variable in alignment with established methodologies (Fu Q et al. 2017 ; Lu P et al. 2019 ; Guo H et al. 2021 ). Subsequently, two-pollutant models were constructed, restricting inclusion to pollutant pairs with Spearman correlation coefficients below 0.7, to further investigate the potential confounding effects of co-pollutants on conjunctivitis outpatient visits. Baseline concentrations for all pollutants were established at 0 µg/m³ (0 mg/m³ for CO). Relative risks (RR) and corresponding 95% confidence intervals (CI) for conjunctivitis outpatient consultations were estimated per 10 µg/m³ increment in PM2.5, PM10, and NO2 concentrations, as well as per 1 mg/m³ increase in CO levels. All statistical analyses were conducted utilizing R software (version 4.5.1) alongside the R packages “dlnm”, “splines” and “tsModel”. P value below 0.05 (two-sided) indicated statistical significance of the difference. 3 Results Table 1 presents the basic information for daily number of conjunctivitis outpatient visits, as well as air pollutant and meteorological data in Jiayuguan City during the study period. A total of 14,598 outpatient records were recorded, with an average daily outpatient of 20. A marginally greater percentage of male outpatients had conjunctivitis (50.80%) compared to female (49.20%). Adult aged 15-64 years accounted for 59.74% of the total outpatient visits, followed by children aged 0-14 years and older more than 65 year of age (12.88%). Daily mean levels of air pollutants were as follows: PM2.5 for 32.66 μg/m3; PM10 for 112.98 μg/m3; SO2 for 15.36 μg/m3; NO2 for 21.25 μg/m3; O38h for 79.95 μg/m3 and 0.49 mg/m3 for CO. In addition, the daily mean temperature was 9.45°C, and relative humidity was 41.74%. Table 2 illustrates the relationships between air contaminants and meteorological conditions. SO2, NO2, and CO exhibited significant associations among themselves (r range: 0.42 to 0.71) and with PM2.5 (r range: -0.052 to 0.16). O38h had slight associations with other air pollutants and relative humidity, although demonstrated a robust positive link with temperature (r=0.83). Furthermore, in addition to the relationship between temperature and O38h, temperature and relative humidity exhibited modest associations with all other air pollutants (r range: -0.49 to 0.14). Table 3 displays the RR with 95 %CI in daily conjunctivitis outpatient visits at different lag days associated with a 10 μg/m 3 increment in air pollutant level (per 1 mg/m 3 increase in CO level). Among the air pollutants analyzed (PM 2.5 , PM 10 , NO 2 , and CO), all except PM displayed similar effects on daily conjunctivitis outpatient visits across different lag days. NO 2 was significant at lag1-3, lag5 days and lag02–07 days, with each 10 μg/m 3 increase corresponding to an RR of 1.126 (95%CI: 1.050,1.208). CO was significant at lag05-07days, with the strongest effect observed at lag07 days (RR =1.836, 95% CI: 1.126, 2.991). In contrast, no significant association was observed between PM 2.5 , PM 10 and conjunctivitis outpatient visits. Fig 2 illustrates a gender-stratified examination of the influence of air pollution on outpatient visits for conjunctivitis. The findings indicate that exposure to PM 2.5 , PM 10 , and NO 2 elevated the risk of conjunctivitis outpatient visits among females, with significant correlations to NO 2 observed exclusively in this demographic. The impact of PM 2.5 and PM 10 on outpatient visits for conjunctivitis among females was marginally favorable and not statistically significant. Our findings suggested that fluctuations in CO levels only affect the single and cumulative delayed effect of conjunctivitis outpatient visits in males, but not in females. Fig 3 illustrates the RR with 95%CI for daily conjunctivitis outpatient visits attributable to air pollutants across varying lag periods, stratified by age. The results demonstrate an elevated risk of daily conjunctivitis outpatient visits associated with NO 2 exposure specifically among children aged 0-14 years. In contrast, neither single lag nor cumulative lag analyses revealed any statistically significant association between increased levels of PM 2.5 or PM 10 and conjunctivitis outpatient visits across different age groups. Notably, elevated CO concentrations predominantly affected old people aged ≥65 years. Seasonal analysis (Table 4) further indicated that positive associations between short-term exposure to NO 2 and CO and conjunctivitis outpatient attendance were confined to the cold season, while PM 2.5 and PM 10 exposures showed no significant associations with outpatient visits, regardless of season. Figure 4 illustrates the exposure-response (E-R) relationships between the four air pollutants and daily conjunctivitis outpatient visits. Notably, the E-R curves for NO 2 and CO displayed a positive linear association, suggesting that increased exposure to these air pollutants correlates with a corresponding rise in conjunctivitis outpatient visits. In contrast, the E-R curves for PM 2.5 and PM 10 showed a gradual decline, with these associations failing to reach statistical significance. The correlations between four air pollutant and outpatient visits for conjunctivitis in the two-pollutant models remained consistent after sequentially adjusting for additional air pollutants (Table S1). Sensitivity analyses varying the df value for the time variable (per year) produced broadly consistent outcomes, further supporting the robustness of our findings (Table S2). 4 Discussion In the current study, we found no significant association between particulate air pollutants (PM2.5 and PM10) and conjunctivitis outpatient visits; however, short-term exposures to NO2 and CO were significantly associated with conjunctivitis outpatient visits. Furthermore, the adverse effects of gaseous air pollutants on the risk of conjunctivitis outpatient visits varied by gender and age. Subgroup analysis suggested that NO 2 was significantly associated only with female patients and children aged 0–14 years, while CO exposure was significantly associated only with male patients and those aged ≥ 65 years. The impact of gaseous air pollutants on conjunctivitis was more evident in cold season. Several prior investigations have examined the associations between particulate air pollutants (PM2.5 and PM10) and outpatient visits for conjunctivitis (Yan K et al. 2023 ; Zhou J et al. 2023 ; Fu Q et al. 2017 ; Chen R et al. 2021 ; Gui Z-H et al. 2024 ). The study in Hangzhou, China demonstrated a significant correlation between PM2.5 and PM10 and outpatient visits for conjunctivitis (Fu Q et al. 2017 ). A study conducted across four cities in China also indicated that short-term elevations in ambient PM2.5 and PM 10 were significantly correlated with an uptick in conjunctivitis outpatient visits (Lu P et al. 2019 ). Another research in Tai’an, China revealed that elevated concentrations of PM 2.5 and PM 10 —were associated with an increased risk of conjunctivitis outpatient visits (Chen R et al. 2021 ). Regrettably, our findings regarding particulate air pollutants (PM 2.5 and PM 10 ) diverge from some of the prior literature. Our results observed no significant associations between particulate matter (PM 2.5 and PM 10 ) and outpatient visits for conjunctivitis, aligning with recent studies conducted in China (Hong J et al. 2016 ; Khalaila S et al. 2021 ). Variations in the magnitude of observed outcome associations are likely attributable to disparities in geographical features, meteorological conditions, pollutant concentrations, chemical compositions of pollutants, or human activity patterns. For example, Jiayuguan, located at the western end of the Hexi Corridor, experiences a typical arid continental climate characterized by strong winds, dry air, and minimal precipitation throughout the year. Local particulate matter (PM 10 , PM 2.5 ) primarily consists of natural windblown sand and dust, with toxicity and chemical reactivity generally lower than coal-burning and vehicle exhaust-type particulates found in heavy industrial cities. Concurrently, the city’s small scale, low population density, and favorable ventilation conditions result in air pollution primarily manifesting as short-term fluctuations rather than sustained high-level exposure. Existing research and local monitoring data indicate that overall PM 2.5 concentrations in Jiayuguan remain low. While PM 10 levels are influenced by sandstorms, they show weak temporal correlation with acute conjunctivitis visits. In contrast, conjunctivitis is more strongly driven by intense sunlight and UV exposure, dry eye caused by extreme air dryness, spring pollen and allergens, personal eye habits, and viral or bacterial infections. Therefore, in Jiayuguan’s environment characterized by dryness, sandstorms, and intense sunlight, particulate pollution is neither sufficiently “dirty” nor sufficiently “persistent”. Its concentration fluctuations are statistically unlikely to translate into significant variations in outpatient volumes, as evidenced by the negligible impact of PM2.5 and PM10 on local conjunctivitis outpatient visits. Consistent with our findings, growing evidence supports the link between short-term NO2 and outpatient visits for conjunctivitis(Yan K et al. 2023 ; Gui S-Y et al. 2023 ; Fu Q et al. 2017 ; Lu P et al. 2019 ; Guo H et al. 2021 ; Chen R et al. 2021 ). A four cities study in China showed a 1.20% increase in conjunctivitis outpatient visits with a 10 µg/m3 increase in NO2 levels (Lu P et al. 2019 ). Similar studies in Tai’an, Hefei, Jinan, Hanzhou, and in Urumqi, China found conjunctivitis outpatient visits increased by 2.50%, 6.40%, 1.00%, 2.80% and 1.90% per 10 µg/m3 increase in NO2, respectively (Yan K et al. 2023 ; Gui S-Y et al. 2023 ; Guo H et al. 2021 ; Bao N et al. 2021 ; Chen R et al. 2021 ). We observed an increase of 12.60% in daily conjunctivitis outpatient visits per 10 µg/m 3 increase in NO 2 concentration, respectively higher than the values reported in the aforementioned studies. This is primarily because Jiayuguan is situated at the western end of the Hexi Corridor, where low temperatures, temperature inversions, and calm winds are relatively common during winter and spring. NO₂ formed from motor vehicle emissions and localized industrial combustion tends to accumulate near the ground surface, leading to significant short-term concentration spikes. Research indicates that NO₂, a potent oxidizing gas, dissolves in the tear film and generates reactive products such as nitrous acid and nitric acid. These damages the corneal-conjunctival epithelial barrier, induces oxidative stress, and stimulates the release of inflammatory mediators, thereby exacerbating symptoms such as conjunctival hyperemia, foreign body sensation, and dryness. This effect is particularly pronounced in arid regions where inherently dry air and strong winds accelerate tear film evaporation, thereby compromising ocular surface defenses. Irritation tends to be further amplified under these conditions. Jiayuguan is a relatively small city with commuter traffic concentrated during morning and evening rush hours. Many individuals with underlying conditions such as conjunctivitis or dry eye are exposed to higher NO₂ levels outdoors during these periods, further amplifying NO2’s pro-inflammatory effects. Consequently, this significantly impacts local conjunctivitis outpatient numbers. In this study, we found a statistically significant association between CO level and conjunctivitis outpatient visits. Previous studies from different regions have suggested that not all short-term exposures to CO contribute to conjunctivitis (Yan K et al. 2023 ; Gui S-Y et al. 2023 ; Fu Q et al. 2017 ) On one hand, exposure to low concentrations of CO might have shown elevated risks for conjunctivitis (Fu Q et al. 2017 ). On the other hand, estimates from two studies conducted in Hangzhou and Urumqi, China, indicated no adverse effects of CO on conjunctivitis outpatient visits(Yan K et al. 2023 ; Gui S-Y et al. 2023 ). As discussed in the preceding section on NO₂, Jiayuguan is situated in an arid continental climate zone characterized by frequent calm winds and temperature inversions during winter and spring, which facilitate the accumulation of pollutants near the ground surface. Although CO emissions from motor vehicles generally exhibit low concentrations, they can form a relatively stable pattern of “low-concentration continuous exposure” during peak emission periods, such as morning and evening commutes and heating seasons. The literature indicates that while CO itself causes minimal direct ocular surface irritation, chronic low-dose exposure can induce oxidative stress and upregulation of inflammatory mediators through mild carboxyhemoglobin formation and tissue hypoxia. This synergizes with concurrent exposure to NO₂, PM, and ozone to amplify damage to the corneal conjunctival epithelium and tear film homeostasis. Against the backdrop of strong winds, extreme dryness, and intense UV radiation in Jiayuguan, where ocular surface barrier function is already compromised, such subclinical hypoxia and inflammation are more readily converted into clinical symptoms, manifesting as increased foreign body sensation, dryness, and hyperemia. Furthermore, the highly concentrated travel patterns of local residents and repeated exposure to low concentrations of CO and co-pollutants during similar time periods make this indirect pro-inflammatory effect easier to capture in time-series analysis. This is reflected in a relatively significant correlation between low CO concentrations and the number of outpatient visits for conjunctivitis In the present study, as well as in related research (Yan K et al. 2023 ; Gui S-Y et al. 2023 ; Lu P et al. 2019 ; Chen R et al. 2021 ), certain air pollutants were found to exert more pronounced detrimental effects on conjunctivitis outpatient visits among females compared to males. For instance, a multi-city investigation conducted in China demonstrated that females exhibited greater sensitivity to PM 2.5 , PM 10 , and NO 2 (Lu P et al. 2019 ). Similarly, Yan et al. (2021) observed a stronger association between exposure to PM 2.5 , PM 10 , and NO 2 and adverse health outcomes in females than in males in Hangzhou, China. In contrast, an analysis in Tai’an, China showed that male was more sensitive to PM 10 and NO 2 , whereas female children were more sensitive to PM 2.5 (Chen R et al. 2021 ). Another study published in 2023 found that PM 10 and NO 2 increased female conjunctivitis outpatient visits, while PM 2.5 increased male conjunctivitis outpatient visits (Gui S-Y et al. 2023 ). This is primarily because PM 2.5 , PM 10 , and NO₂ irritate the ocular surface and induce inflammation. Females, however, experience more pronounced effects from these pollutants due to narrower nasolacrimal ducts, hormonal fluctuations causing abnormal tear secretion, greater exposure to cosmetics, and weaker conjunctival defenses. In contrast, for males, they are more likely to work in outdoor environments, exposing them to higher levels of air pollutants. The high susceptibility to NO 2 and CO observed in children aged 0–14 years and elderly (≥ 65 years) may be attributable to diminished metabolic and immunological function, as well as the alignment of outdoor activities with periods of elevated NO 2 and CO air pollution. Seasonal study revealed that the rise in conjunctivitis outpatient visits due to air pollution was more pronounced during colder seasons. This is mainly attributable to local heating methods and temperature inversion during the cold season in Jiayuguan, resulting in increased levels of PM 2.5 and NO 2 . Reduced humidity and frigid winds expedite tear film evaporation and exacerbate dry eye symptoms, undermining the mucosal barrier. Extended indoor confinement promotes the buildup of allergens and pathogens, hence increasing the likelihood of pollutants triggering or worsening conjunctival irritation. 5 Conclusions This study provides empirical evidence from a typical arid industrial city in Northwest China, revealing a significant short-term association between exposure to ambient air pollutants and the risk of outpatient visits for conjunctivitis. Contrary to the intuitive impression that the region is prone to sandstorms, our analysis shows that gaseous pollutants (NO 2 and CO), rather than particulate matter (PM 2.5 and PM 10 ), are the key environmental factors driving the increased risk of conjunctivitis. This finding suggests that in industrialized cities in arid and semi-arid regions, chemical irritants from industrial emissions and traffic exhaust may pose a greater acute hazard to ocular health than physical dust from natural sources. Furthermore, this study elucidates the time lag characteristics of risk and its significant population heterogeneity. The adverse effects are more pronounced during the cold season, and the impact of different pollutants varies on susceptible subgroups: NO 2 primarily threatens the eye health of women and children aged 0–14 years, while CO exposure is significantly associated with increased outpatient visits for conjunctivitis in men and older adults aged ≥ 65 years. Based on the above findings, we recommend: When formulating strategies for the prevention and control of eye diseases in arid regions, local environmental protection and health departments should not only focus on sand control and desertification prevention, but also attach great importance to the coordinated control of gaseous pollutants from industrial and transportation sources. Besides, during cold seasons and when gaseous pollutant concentrations are high, eye protection recommendations are issued for specific vulnerable groups. Despite limitations such as the lack of individual-level exposure data and the absence of consideration for indoor allergens, our findings fill a gap in research on ocular environmental health under special climatic conditions and provide important scientific evidence for subsequent public health interventions aimed at reducing the burden of environmentally induced eye diseases. Appendix List of abbreviations Particulate matter 2.5 PM2.5 Particulate matter 10 PM10 NO2 Nitrogen dioxide SO2 Sulfur dioxide O3 Ozone CO Carbon monoxide DLNM Distributed Lag Nonlinear Model ICD-10 International Classification of Diseases, Tenth Revision Tem Daily mean temperature RH Daily mean relative humidity CI Confidence Intervals RR Relative Risks Declarations Funding : This work was supported by the Natural Science Foundation of Gansu Province, China (Grant No. 24JRRA407). Competing interests: The authors declare that they have no competing interests. Ethics approval and consent to participate: Not applicable. Consent for publication : Not applicable. Availability of data and material: Data cannot be shared for privacy or ethical reasons. Authors’ contributions: Yanan Zhang contributed to the conception and design of the work. Yanan Zhang, guorui Song, Bo Zheng, Fei Chen, Lijun Ma and Xiaofeng Luo contributed to the acquisition, analysis, or interpretation of data for the work. Yanan Zhang drafted the manuscript and provided funding support. Fei Chen, Lijun Ma and Xiaofeng Luo critically revised the manuscript and supervised the development of research. All gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy. Acknowledgements: Not applicable. References Abusharha, A.A., Pearce, E.I. (2013). The effect of low humidity on the human tear film. Cornea 32, 429–434. https://doi.org/10.1097/ICO.0b013e31826671ab Alryalat, S.A., Toubasi, A.A., Patnaik, J.L., Kahook, M.Y. (2024). The impact of air pollution and climate change on eye health: a global review. Reviews on Environmental Health 39, 291–303. https://doi.org/10.1515/reveh-2022-0209 Azari, A.A., Barney, N.P. (2013). Conjunctivitis: A Systematic Review of Diagnosis and Treatment. JAMA 310, 1721–1730. https://doi.org/10.1001/jama.2013.280318 Bao N, Lu Y, Huang K, et al (2021) Association between short-term exposure to ambient nitrogen dioxide and the risk of conjunctivitis in Hefei, China: A time-series analysis. Environ Res 195:110807. https://doi.org/10.1016/j.envres.2021.110807 Bilkhu, P.S., Wolffsohn, J.S., Naroo, S.A. (2012). A review of non-pharmacological and pharmacological management of seasonal and perennial allergic conjunctivitis. Cont Lens Anterior Eye 35, 9–16. https://doi.org/10.1016/j.clae.2011.08.009 Chang, C.-J., Yang, H.-H., Chang, C.-A., Tsai, H.-Y. (2012). Relationship between air pollution and outpatient visits for nonspecific conjunctivitis. Invest Ophthalmol Vis Sci 53, 429–433. https://doi.org/10.1167/iovs.11-8253 Chen, R., Yang, J., Chen, D., Liu, W.-J., Chunlin, Wang, H., Li, B., Xiong, P., Wang, B., Wang, Y., Li, S., Guo, Y. (2021). Air pollution and hospital outpatient visits for conjunctivitis: a time-series analysis in Tai’an, China. Environmental science and pollution research international 28. https://doi.org/10.1007/s11356-020-11762-4 Chen, R., Yang, J., Zhang, C., Li, B., Bergmann, S., Zeng, F., Wang, H., Wang, B. (2019). Global Associations of Air Pollution and Conjunctivitis Diseases: A Systematic Review and Meta-Analysis. Int J Environ Res Public Health 16, 3652. https://doi.org/10.3390/ijerph16193652 Cheng, P., Liu, C., Tu, B., Zhang, X., Chen, F., Xu, J., Qian, D., Wang, X., Zhou, W. (2023). Short-Term effects of ambient ozone on the risk of conjunctivitis outpatient visits: a time-series analysis in Pudong New Area, Shanghai. Int J Environ Health Res 33, 348–357. https://doi.org/10.1080/09603123.2022.2030465 Chien, L.-C., Lien, Y.-J., Yang, C.-H., Yu, H.-L. (2014). Acute Increase of Children’s Conjunctivitis Clinic Visits by Asian Dust Storms Exposure - A Spatiotemporal Study in Taipei, Taiwan. PLoS One 9, e109175. https://doi.org/10.1371/journal.pone.0109175 Fu, Q., Mo, Z., Lyu, D., Zhang, L., Qin, Z., Tang, Q., Yin, H., Xu, P., Wu, L., Lou, X., Chen, Z., Yao, K. (2017). Air pollution and outpatient visits for conjunctivitis: A case-crossover study in Hangzhou, China. Environ Pollut 231, 1344–1350. https://doi.org/10.1016/j.envpol.2017.08.109 Gui, S.-Y., Wang, X.-C., Qiao, J.-C., Xiao, D.-C., Hu, C.-Y., Tao, F.-B., Liu, D.-W., Yi, X.-L., Jiang, Z.-X. (2023). Short-term exposure to air pollution and outpatient visits for conjunctivitis: a time-series analysis in Urumqi, China. Environ Sci Pollut Res 30, 66400–66416. https://doi.org/10.1007/s11356-023-26995-2 Gui, Z.-H., Guo, Z.-Y., Zhou, Y., Dharmage, S., Morawska, L., Heinrich, J., Cheng, Z.-K., Gan, H., Lin, Z.-W., Zhang, D.-Y., Huang, J.-W., Lin, L.-Z., Liu, R.-Q., Chen, W., Sun, B., Dong, G.-H. (2024). Long-term ambient ozone exposure and childhood asthma, rhinitis, eczema, and conjunctivitis: A multi-city study in China. Journal of Hazardous Materials 478, 135577. https://doi.org/10.1016/j.jhazmat.2024.135577 Guo, H., Zhang, S., Zhang, Z., Zhang, J., Wang, C., Fang, X., Lin, H., Li, H., Ruan, Z. (2021). Short-term exposure to nitrogen dioxide and outpatient visits for cause-specific conjunctivitis: A time-series study in Jinan, China. Atmospheric Environment 247, 118211. https://doi.org/10.1016/j.atmosenv.2021.118211 Hong, J., Zhong, T., Li, H., Xu, Jianming, Ye, X., Mu, Z., Lu, Y., Mashaghi, A., Zhou, Y., Tan, M., Li, Q., Sun, X., Liu, Z., Xu, Jianjiang (2016). Ambient air pollution, weather changes, and outpatient visits for allergic conjunctivitis: A retrospective registry study. Sci Rep 6, 23858. https://doi.org/10.1038/srep23858 Hu, T., Zhao, H., Duan, X., Huang, X., Wang, X., Wang, Y. (2021). Epidemiological characteristics of acute hemorrhagic conjunctivitis in China, 2013–2019. Disease Surveillance 36, 440–444. https://doi.org/10.3784/jbjc.202011130385 Jones, A.L., Kramer, R.S.S. (2016). Facial Cosmetics and Attractiveness: Comparing the Effect Sizes of Professionally-Applied Cosmetics and Identity. PLoS One 11, e0164218. https://doi.org/10.1371/journal.pone.0164218 Khalaila, S., Coreanu, T., Vodonos, A., Kloog, I., Shtein, A., Colwell, L.E., Novack, V., Tsumi, E. (2021). Association between ambient temperature, particulate air pollution and emergency room visits for conjunctivitis. BMC Ophthalmol 21, 100. https://doi.org/10.1186/s12886-021-01854-1 Kim, B.E., Hui-Beckman, J.W., Nevid, M.Z., Goleva, E., Leung, D.Y.M. (2024). Air pollutants contribute to epithelial barrier dysfunction and allergic diseases. Annals of Allergy, Asthma & Immunology 132, 433–439. https://doi.org/10.1016/j.anai.2023.11.014 Lin, C.-C., Chiu, C.-C., Lee, P.-Y., Chen, K.-J., He, C.-X., Hsu, S.-K., Cheng, K.-C. (2022). The Adverse Effects of Air Pollution on the Eye: A Review. Int J Environ Res Public Health 19, 1186. https://doi.org/10.3390/ijerph19031186 Liu, D., Gui, S., Wang, X., Wang, Q., Qiao, J., Tao, F., Tao, L., Jiang, Z., Yi, X. (2024). Long-term effects of air pollution on daily outpatient visits for allergic conjunctivitis from 2013 to 2020: a time-series study in Urumqi, China. Front. Public Health 12. https://doi.org/10.3389/fpubh.2024.1325956 Lu, P., Zhang, Y., Xia, G., Zhang, W., Li, S., Guo, Y. (2019). Short-term exposure to air pollution and conjunctivitis outpatient visits: A multi-city study in China. Environ Pollut 254, 113030. https://doi.org/10.1016/j.envpol.2019.113030 Mimura, T., Ichinose, T., Yamagami, S., Fujishima, H., Kamei, Y., Goto, M., Takada, S., Matsubara, M. (2014). Airborne particulate matter (PM2.5) and the prevalence of allergic conjunctivitis in Japan. Sci Total Environ 487, 493–499. https://doi.org/10.1016/j.scitotenv.2014.04.057 Nam, S., Shin, M.Y., Han, J.Y., Moon, S.Y., Kim, J.Y., Tchah, H., Lee, H. (2022). Correlation between air pollution and prevalence of conjunctivitis in South Korea using analysis of public big data. Scientific Reports 12, 10091. https://doi.org/10.1038/s41598-022-13344-5 Nichols, J.J., Sinnott, L.T. (2006). Tear film, contact lens, and patient-related factors associated with contact lens-related dry eye. Invest Ophthalmol Vis Sci 47, 1319–1328. https://doi.org/10.1167/iovs.05-1392 Ruan, Z., Högdén, A., Zhang, T., Li, Y., Xu, Y., Wang, J., Chai, D., Wang, Z., Shan, W., Liao, Y., Song, Z., Liu, W., Guo, H., Zhang, Z., Wang, X., Qiu, Y. (2024). Daily gaseous air pollution and pediatric conjunctivitis: A case-crossover study across ten cities in China’s southeastern coastal region. Journal of Hazardous Materials 480, 136032. https://doi.org/10.1016/j.jhazmat.2024.136032 Schneider, J.E., Scheibling, C.M., Segall, D., Sambursky, R., Ohsfeldt, l (2014). Epidemiology and Economic Burden of Conjunctivitis: A Managed Care Perspective. Journal of Managed Care Medicine 17, 78–83. Trentalange, A., Renzi, M., Michelozzi, P., Guizzi, M., Solimini, A.G. (2024). Association between air pollution and emergency room admission for eye diseases in Rome, Italy: A time-series analysis. Environmental Pollution 343, 123279. https://doi.org/10.1016/j.envpol.2023.123279 Upaphong, P., Thonusin, C., Wanichthanaolan, O., Chattipakorn, N., Chattipakorn, S.C. (2024). Consequences of exposure to particulate matter on the ocular surface: Mechanistic insights from cellular mechanisms to epidemiological findings. Environmental Pollution 345, 123488. https://doi.org/10.1016/j.envpol.2024.123488 Yan, K., Wang, M., Cheng, Y., Zou, J., Zhang, Y., Hu, S., Chen, Y., Lv, Q., Ying, S. (2023). An update on the association between ambient short-term air pollution exposure and daily outpatient visits for conjunctivitis: a time-series study in Hangzhou, China. Environ Sci Pollut Res 30, 102790–102802. https://doi.org/10.1007/s11356-023-29647-7 Zhou, J., Fan, L., Lin, H., Zheng, D., Yang, L., Zhuo, D., Zhuoma, J., Li, H., Zhang, S., Ruan, Z. (2023). Size-specific particulate matter and outpatient visits for allergic conjunctivitis in children: a time-stratified case-crossover study in Guangzhou, China. Environ Sci Pollut Res Int 30, 33949–33959. https://doi.org/10.1007/s11356-022-24564-7 Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstract.tif Tables.docx TableS1ands2.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 05 May, 2026 Reviews received at journal 05 May, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviews received at journal 06 Mar, 2026 Reviewers agreed at journal 01 Mar, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 29 Dec, 2025 Submission checks completed at journal 29 Dec, 2025 First submitted to journal 26 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8454171","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597539152,"identity":"51122ae0-e4f9-4f09-96a1-ce97d3c10bc2","order_by":0,"name":"Yanan 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12:08:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":211220,"visible":true,"origin":"","legend":"\u003cp\u003eThe RR (95% CI) of outpatient visits for conjunctivitis stratified by gender\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8454171/v1/692a5e1b7cf2c73172ccedff.png"},{"id":103731642,"identity":"f4027ea2-0e71-48c9-904c-eaeb8090a248","added_by":"auto","created_at":"2026-03-02 09:16:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":247255,"visible":true,"origin":"","legend":"\u003cp\u003eThe RR (95% CI) of outpatient visits for conjunctivitis stratified by age\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8454171/v1/4d40f0b36da2749d745cb82f.png"},{"id":103731643,"identity":"647a5871-27ac-4522-895e-194a7a6e0259","added_by":"auto","created_at":"2026-03-02 09:16:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":160347,"visible":true,"origin":"","legend":"\u003cp\u003eThe exposure-response curves between air pollutants and outpatient visits for conjunctivitis\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8454171/v1/7ed58ca5d2f8d5e5aa482e16.png"},{"id":104835008,"identity":"339ff248-95fc-44d6-9497-c32fddcd13cc","added_by":"auto","created_at":"2026-03-17 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12:07:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":38253,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8454171/v1/655ff5b05ab73edf54a94c6c.docx"},{"id":103731641,"identity":"fa7aab88-5ca2-4f83-84f0-782f977e8a65","added_by":"auto","created_at":"2026-03-02 09:16:50","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":22940,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1ands2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8454171/v1/b0df6fbc00bba93c64a596f4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Short-term association between air pollutants and outpatient visits for conjunctivitis in an arid industrial city of Northwest China: A time-series study","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eConjunctivitis is an inflammation of the conjunctiva, the delicate, transparent mucous membrane covering the anterior sclera and the inner eyelids, clinically manifesting as conjunctival hyperemia, chemosis, epiphora, pruritus, foreign body sensation, and increased discharge. Uncontrolled, these symptoms impair visual comfort and daily functioning. Epidemiologically, conjunctivitis ranks among the most prevalent ocular pathologies globally; in the United States, annual incidence approximates six million cases, exerting a significant economic impact estimated at up to \u003cspan\u003e$\u003c/span\u003e857\u0026nbsp;million for bacterial management (Azari AA et al. 2013; Schneider JE et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In China, data from the National Health Commission show that the prevalence of eye and adnexal diseases, including conjunctivitis, reached 3.8\u0026permil; in urban areas and 3.6\u0026permil; in rural areas by 2018, with a significant upward trend compared to 2013 (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, the Chinese Center for Disease Control and Prevention reported 289,518 cumulative cases of acute hemorrhagic conjunctivitis between 2013 and 2020, with an average annual incidence of 2.63 per 100,000 population, indicating that conjunctivitis remains a non-negligible public health issue affecting the quality of life and healthcare resources in China (Hu T et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe etiology of conjunctivitis is multifaceted, encompassing infectious, allergic, environmental, and occupational factors. Infectious conjunctivitis is caused by pathogenic microorganisms, including viruses and bacteria, accounting for over 85% of acute conjunctivitis cases (Azari AA et al. 2013). Allergic conjunctivitis is triggered by allergens like pollen and dust mites, often presenting as a chronic and mild condition (Bilkhu PS et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)Other risk factors include physical and chemical irritants, occupational exposure to chemicals or radiation, and improper use of cosmetics or contact lenses (Nichols JJ et al. 2006; Jones AL et al. 2016). In recent decades, rapid global urbanization and industrialization have increased environmental exposure, particularly air pollution, which plays a significant role in the development of conjunctivitis. The conjunctiva, as the ocular surface that contacts the external environment and possesses an extensive blood supply, is particularly vulnerable to airborne pollutants such as particles and gases. These pollutants can disrupt the tear film barrier, induce oxidative stress and inflammation, and ultimately trigger or exacerbate conjunctival inflammation (Upaphong P et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Alryalat SA et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA growing body of epidemiologic research associates key air pollutants, including particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e), nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e), sulfur dioxide (SO\u003csub\u003e2\u003c/sub\u003e), ozone (O\u003csub\u003e3\u003c/sub\u003e), and carbon monoxide (CO), with elevated risks of outpatient visits or emergency department admissions for conjunctivitis (Zhou J et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cheng P et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liu D et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ruan Z et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Time-series and case-crossover studies across East Asia and beyond have consistently reported positive short-term associations in single- and multi-pollutant models. For example, Taiwan and Shanghai studies linked increases in PM and gaseous pollutants to higher conjunctivitis outpatient volumes (Chang C-J et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Hong J et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e); a Japanese study related ambient PM\u003csub\u003e2.5\u003c/sub\u003e to allergic conjunctivitis prevalence (Mimura T et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e); Hangzhou and multi-city analyses in China found robust short-term pollution\u0026ndash;conjunctivitis associations (Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); city-specific investigations in Hefei and Jinan identified NO\u003csub\u003e2\u003c/sub\u003e as a notable risk factor (Guo H et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bao N et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); and a time-series analysis in Tai\u0026rsquo;an observed cumulative lag effects across multiple pollutants (Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Evidence from Korea and Israel using public big data or emergency department records further substantiates generalizability across settings (Khalaila S et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nam S et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Meta-analytic and narrative reviews converge on the conclusion that ambient pollution adversely affects the ocular surface and increases conjunctivitis burden (Chen R et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lin C-C et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotwithstanding this progress, key knowledge gaps remain. First, a geographic bias is evident: many studies have concentrated on humid or subtropical cities in eastern and southern China, whereas arid and desert climates, characterized by high winds, low humidity, and frequent dust events, are underrepresented (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cheng P et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Although recent analyses from Northwest China began to address this gap, additional evidence from diverse arid settings is needed to improve external validity (Liu D et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Second, vulnerability patterns require clarification. While some studies suggest stronger effects among females, youths, or in warm seasons, findings are inconsistent across regions and pollutants (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Nam S et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Third, nonlinear exposure\u0026ndash;response functions and lag structures, including thresholds at which risks accelerate and the duration of cumulative effects, are not fully characterized across climates and pollutant mixtures (Cheng P et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Trentalange A et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These gaps are particularly salient in arid environments, where low ambient humidity destabilizes the tear film and may amplify pollutant-induced ocular surface stress. Additionally, dust storm events have been linked to spikes in pediatric conjunctivitis visits ( Abusharha AA et al. 2013; Chien L-C et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eJiayuguan City in northwestern China (Hexi Corridor, Gansu Province) exemplifies an arid, wind-swept setting with frequent dust episodes and marked seasonal variability. Industrial emissions and regionally transported particulates yield distinctive pollution profiles dominated by PM with winter peaks, while the dry climate plausibly heightens ocular surface susceptibility. Addressing the aforementioned gaps, the present study focuses on conjunctivitis outpatient visits in Jiayuguan to: (1) quantify short-term associations between ambient pollutants (PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, NO\u003csub\u003e2\u003c/sub\u003e, CO) and daily conjunctivitis outpatient counts; (2) delineate potential nonlinear exposure\u0026ndash;response relationships and distributed lag effects; and (3) identify susceptible subgroups by sex and age, as well as seasonal heterogeneity. To these ends, we analyze daily conjunctivitis outpatient data using a quasi-Poisson generalized linear model coupled with a distributed lag nonlinear model (DLNM). By providing evidence from an under-studied arid region, our study aims to refine risk estimates relevant to desert climates and inform targeted public health strategies for ocular surface protection.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eThis study was conducted in Jiayuguan, a prefecture-level city located in the northwestern of Gansu Province, China. As of 2024, Jiayuguan had a population of 315,600 residents. As a major industrial base in northwest China, Jiayuguan pillar industries center on metallurgy, building materials, and equipment manufacturing, with steel metallurgy being particularly prominent. This has formed an industrial system anchored by heavy industry. Jiayuguan experiences a temperate continental desert climate characterized by scarce precipitation, dry air, and abundant sunshine, with significant annual and diurnal temperature variations. Compared to most northern cities, Jiayuguan has a longer heating season, and coal-fired heating remains the primary source for residential warmth during winter. In recent years, through multiple measures including retrofitting coal-fired boilers, optimizing industrial structure, and strengthening pollution emission controls, the city\u0026rsquo;s ambient air quality has demonstrated an overall trend of gradual improvement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection\u003c/h2\u003e \u003cp\u003eWe obtained daily outpatient data visits for conjunctivitis cases from January 1, 2023 to December 31, 2024 from all public hospitals located within the urban district of Jiayuguan. We gathered data on conjunctivitis outpatients classified under ICD-10 codes (including H10.0, H10.1, H10.2, H10.3, H10.4, H10.5, H10.6, H10.7, H10.8, H10.9, etc.) as per the International Classification of Diseases, Tenth Revision (ICD-10), encompassing gender, age, date of visit, and clinical diagnosis. Following the exclusion of patients residing outside Jiayuguan, we quantified the daily outpatient visits for conjunctivitis and subsequently categorized them based on gender (male, female), age (0\u0026ndash;14 years, 15\u0026ndash;64 years, \u0026ge;\u0026thinsp;65 years), and season (cold season: October to March, warm season: April to September).\u003c/p\u003e \u003cp\u003eWe collected daily mean concentrations of PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, SO\u003csub\u003e2\u003c/sub\u003e, NO\u003csub\u003e2\u003c/sub\u003e, and CO, in addition to the daily maximum 8-hour average (O\u003csub\u003e3\u003c/sub\u003e8h) for ozone, from the Jiayuguan Ecology and Environment Bureau, covering the period from January 1, 2023 to December 31, 2024. CO concentrations were reported in mg/m\u003csup\u003e3\u003c/sup\u003e, while the concentrations of the other five ambient air pollutants were measured in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e. Ambient air pollutant concentrations were continuously recorded at all air quality monitoring stations within Jiayuguan. We calculated the mean concentrations across all stations to represent daily ambient air pollutant exposure levels in Jiayuguan. Concurrently, daily mean temperature (Tem, unit: \u0026deg;C) and relative humidity (RH, unit: %) were obtained from the Gansu Meteorological Bureau for the same period. The locations of air pollutants monitoring stations and hospitals are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eSince that daily outpatient visits constitute a low-probability event generally conforming to a Poisson distribution, and considering that numerous prior studies have indicated the presence of non-linear and lagged associations between air pollutants and conjunctivitis (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bao N et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gui Z-H et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given the overdispersal Poisson distribution observed in outpatient visit data, this study utilized a distributed lag nonlinear model (DLNM) in conjunction with a quasi-Poisson generalized additive model to examine the relationship between ambient air pollutants and the risk of outpatient visits for conjunctivitis. Meteorological variables (Tem and RH) and temporal parameters were included into the model via the natural cubic spline (ns) function to account for time and confounding influences. The final model incorporated the weekday and holiday variables to account for the effects of the day of the week and holidays. Concurrently, to mitigate multicollinearity, Spearman\u0026rsquo;s rank correlation analysis was employed for covariate selection; variables exhibiting correlation coefficients exceeding 0.7 were not concurrently included in our models. The finalized models are presented as follows:\u003c/p\u003e \u003cp\u003eLog(\u0026micro;t)= α\u0026thinsp;+\u0026thinsp;βXt,l\u0026thinsp;+\u0026thinsp;ns(Temt, df )\u0026thinsp;+\u0026thinsp;ns(rht, df )\u0026thinsp;+\u0026thinsp;ns(Timet, df )\u0026thinsp;+\u0026thinsp;Dow\u0026thinsp;+\u0026thinsp;Holiday\u003c/p\u003e \u003cp\u003eIn the model above, t represents the day of the day of observation; \u0026micro;t denotes the number of outpatient visits for conjunctivitis on day t; \u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e is the constant term; Xt,l is the DLNM cross-basis matrix for each air pollutant and l denotes the number of lag days; β refers to the vector of coefficients for Xt,l, and we defined the matrix for the linear and lagged of air pollutants applying the linear function and the natural cubic spline function. \u003cem\u003ens\u003c/em\u003e denotes natural cubic spline function. \u003cem\u003eTem\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eRH\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e are daily mean temperature and relative humidity, respectively. Timet is the time variable, which is used to adjust for seasonality and long-term trend. Dow is the dummy variable of the day of week and was controlled in the model; the binary variable Holiday was applied to adjust for the effects of public holidays.\u003c/p\u003e \u003cp\u003eThe optimal degrees of freedom (df) for meteorological factors, and time was determined by the minimum quasi-Poisson Akaike information criterion and previous similar studies (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). 3 df was selected to adjust for Tem and RH; a natural spline smooth function of time with 7 df every year was applied to control for seasonality and long-term trend.\u003c/p\u003e \u003cp\u003eGiven that the harmful effects of pollutants may exhibit a delayed onset, their impact is predominantly observed within the initial week post-exposure. To investigate the temporal lagged effects of multiple air pollutant exposures on conjunctivitis, we employed a maximum lag period of 7 days. This study utilized both single- lag models (lag0\u0026ndash;lag7 days) and cumulative lag models (lag01\u0026ndash;lag07 days) to estimate the associations between air pollutants and conjunctivitis across varying lag periods. We selected the lag time corresponding to the maximum RR value for each pollutant, then fit the exposure\u0026ndash;response curve, and sensitivity analyses. Furthermore, we performed stratification analyses by gender, age and season.\u003c/p\u003e \u003cp\u003eSeveral sensitivity analyses were implemented to assess the robustness of the primary findings. Initially, the degrees of freedom (df) in the single-pollutant model were varied, evaluating 6\u0026ndash;10 df per year for the temporal variable in alignment with established methodologies (Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Guo H et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Subsequently, two-pollutant models were constructed, restricting inclusion to pollutant pairs with Spearman correlation coefficients below 0.7, to further investigate the potential confounding effects of co-pollutants on conjunctivitis outpatient visits.\u003c/p\u003e \u003cp\u003eBaseline concentrations for all pollutants were established at 0 \u0026micro;g/m\u0026sup3; (0 mg/m\u0026sup3; for CO). Relative risks (RR) and corresponding 95% confidence intervals (CI) for conjunctivitis outpatient consultations were estimated per 10 \u0026micro;g/m\u0026sup3; increment in PM2.5, PM10, and NO2 concentrations, as well as per 1 mg/m\u0026sup3; increase in CO levels.\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted utilizing R software (version 4.5.1) alongside the R packages \u0026ldquo;dlnm\u0026rdquo;, \u0026ldquo;splines\u0026rdquo; and \u0026ldquo;tsModel\u0026rdquo;. P value below 0.05 (two-sided) indicated statistical significance of the difference.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003eTable 1 presents the basic information for daily number of conjunctivitis outpatient visits, as well as air pollutant and meteorological data in Jiayuguan City during the study period. A total of 14,598 outpatient records were recorded, with an average daily outpatient of 20. A marginally greater percentage of male outpatients had conjunctivitis (50.80%) compared to female (49.20%). Adult aged 15-64 years accounted for 59.74% of the total outpatient visits, followed by children aged 0-14 years and older more than 65 year of age (12.88%). Daily mean levels of air pollutants were as follows: PM2.5 for 32.66 \u0026mu;g/m3; PM10 for 112.98 \u0026mu;g/m3; SO2 for 15.36 \u0026mu;g/m3; NO2 for 21.25 \u0026mu;g/m3; O38h for 79.95 \u0026mu;g/m3 and 0.49 mg/m3 for CO. In addition, the daily mean temperature was 9.45\u0026deg;C, and relative humidity was 41.74%.\u003c/p\u003e\n\u003cp\u003eTable 2 illustrates the relationships between air contaminants and meteorological conditions. SO2, NO2, and CO exhibited significant associations among themselves (r range: 0.42 to 0.71) and with PM2.5 (r range: -0.052 to 0.16). O38h had slight associations with other air pollutants and relative humidity, although demonstrated a robust positive link with temperature (r=0.83). Furthermore, in addition to the relationship between temperature and O38h, temperature and relative humidity exhibited modest associations with all other air pollutants (r range: -0.49 to 0.14).\u003c/p\u003e\n\u003cp\u003eTable 3 displays the RR with 95 %CI in daily conjunctivitis outpatient visits at different lag days associated with a 10 \u0026mu;g/m\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eincrement in air pollutant level (per 1 mg/m\u003csup\u003e3\u003c/sup\u003e increase in CO level). Among the air pollutants analyzed (PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, NO\u003csub\u003e2\u003c/sub\u003e, and CO), all except PM displayed similar effects on daily conjunctivitis outpatient visits across different lag days.\u0026nbsp;NO\u003csub\u003e2\u003c/sub\u003e was significant at lag1-3, lag5 days and lag02\u0026ndash;07 days, with each 10 \u0026mu;g/m\u003csup\u003e3\u003c/sup\u003e increase corresponding to an RR of 1.126 (95%CI: 1.050,1.208). CO was significant at lag05-07days, with the strongest effect observed at lag07 days (RR =1.836, 95% CI: 1.126, 2.991). In contrast, no significant association was observed between PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e and conjunctivitis outpatient visits.\u003c/p\u003e\n\u003cp\u003eFig 2 illustrates a gender-stratified examination of the influence of air pollution on outpatient visits for conjunctivitis. The findings indicate that exposure to PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, and NO\u003csub\u003e2\u003c/sub\u003e elevated the risk of conjunctivitis outpatient visits among females, with significant correlations to NO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eobserved exclusively in this demographic. The impact of PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e on outpatient visits for conjunctivitis among females was marginally favorable and not statistically significant. Our findings suggested that fluctuations in CO levels only affect the single and cumulative delayed effect of conjunctivitis outpatient visits in males, but not in females.\u003c/p\u003e\n\u003cp\u003eFig 3 illustrates the RR with 95%CI for daily conjunctivitis outpatient visits attributable to air pollutants across varying lag periods, stratified by age. The results demonstrate an elevated risk of daily conjunctivitis outpatient visits associated with NO\u003csub\u003e2\u003c/sub\u003e exposure specifically among children aged 0-14 years. In contrast, neither single lag nor cumulative lag analyses revealed any statistically significant association between increased levels of PM\u003csub\u003e2.5\u003c/sub\u003e or PM\u003csub\u003e10\u003c/sub\u003e and conjunctivitis outpatient visits across different age groups. Notably, elevated CO concentrations predominantly affected old people aged \u0026ge;65 years. Seasonal analysis (Table 4) further indicated that positive associations between short-term exposure to NO\u003csub\u003e2\u003c/sub\u003e and CO and conjunctivitis outpatient attendance were confined to the cold season, while PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u0026nbsp;\u003c/sub\u003eexposures showed no significant associations with outpatient visits, regardless of season.\u003c/p\u003e\n\u003cp\u003eFigure 4 illustrates the exposure-response (E-R) relationships between the four air pollutants and daily\u0026nbsp;conjunctivitis\u0026nbsp;outpatient visits. Notably, the E-R curves for NO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eand CO displayed a positive linear association, suggesting that increased exposure to these air pollutants correlates with a corresponding rise in conjunctivitis outpatient visits. In contrast, the E-R curves for PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e showed a gradual decline, with these associations failing to reach statistical significance.\u003c/p\u003e\n\u003cp\u003eThe correlations between four air pollutant and outpatient visits for conjunctivitis in the two-pollutant models remained consistent after sequentially adjusting for additional air pollutants (Table S1). Sensitivity analyses varying the df value for the time variable (per year) produced broadly consistent outcomes, further supporting the robustness of our findings (Table S2).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eIn the current study, we found no significant association between particulate air pollutants (PM2.5 and PM10) and conjunctivitis outpatient visits; however, short-term exposures to NO2 and CO were significantly associated with conjunctivitis outpatient visits. Furthermore, the adverse effects of gaseous air pollutants on the risk of conjunctivitis outpatient visits varied by gender and age. Subgroup analysis suggested that NO\u003csub\u003e2\u003c/sub\u003e was significantly associated only with female patients and children aged 0\u0026ndash;14 years, while CO exposure was significantly associated only with male patients and those aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years. The impact of gaseous air pollutants on conjunctivitis was more evident in cold season.\u003c/p\u003e \u003cp\u003eSeveral prior investigations have examined the associations between particulate air pollutants (PM2.5 and PM10) and outpatient visits for conjunctivitis (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhou J et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gui Z-H et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The study in Hangzhou, China demonstrated a significant correlation between PM2.5 and PM10 and outpatient visits for conjunctivitis (Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A study conducted across four cities in China also indicated that short-term elevations in ambient PM2.5 and PM\u003csub\u003e10\u003c/sub\u003e were significantly correlated with an uptick in conjunctivitis outpatient visits (Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Another research in Tai\u0026rsquo;an, China revealed that elevated concentrations of PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e\u0026mdash;were associated with an increased risk of conjunctivitis outpatient visits (Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regrettably, our findings regarding particulate air pollutants (PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e) diverge from some of the prior literature. Our results observed no significant associations between particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e) and outpatient visits for conjunctivitis, aligning with recent studies conducted in China (Hong J et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Khalaila S et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Variations in the magnitude of observed outcome associations are likely attributable to disparities in geographical features, meteorological conditions, pollutant concentrations, chemical compositions of pollutants, or human activity patterns. For example, Jiayuguan, located at the western end of the Hexi Corridor, experiences a typical arid continental climate characterized by strong winds, dry air, and minimal precipitation throughout the year. Local particulate matter (PM\u003csub\u003e10\u003c/sub\u003e, PM\u003csub\u003e2.5\u003c/sub\u003e) primarily consists of natural windblown sand and dust, with toxicity and chemical reactivity generally lower than coal-burning and vehicle exhaust-type particulates found in heavy industrial cities. Concurrently, the city\u0026rsquo;s small scale, low population density, and favorable ventilation conditions result in air pollution primarily manifesting as short-term fluctuations rather than sustained high-level exposure. Existing research and local monitoring data indicate that overall PM\u003csub\u003e2.5\u003c/sub\u003e concentrations in Jiayuguan remain low. While PM\u003csub\u003e10\u003c/sub\u003e levels are influenced by sandstorms, they show weak temporal correlation with acute conjunctivitis visits. In contrast, conjunctivitis is more strongly driven by intense sunlight and UV exposure, dry eye caused by extreme air dryness, spring pollen and allergens, personal eye habits, and viral or bacterial infections. Therefore, in Jiayuguan\u0026rsquo;s environment characterized by dryness, sandstorms, and intense sunlight, particulate pollution is neither sufficiently \u0026ldquo;dirty\u0026rdquo; nor sufficiently \u0026ldquo;persistent\u0026rdquo;. Its concentration fluctuations are statistically unlikely to translate into significant variations in outpatient volumes, as evidenced by the negligible impact of PM2.5 and PM10 on local conjunctivitis outpatient visits.\u003c/p\u003e \u003cp\u003eConsistent with our findings, growing evidence supports the link between short-term NO2 and outpatient visits for conjunctivitis(Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Guo H et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A four cities study in China showed a 1.20% increase in conjunctivitis outpatient visits with a 10 \u0026micro;g/m3 increase in NO2 levels (Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similar studies in Tai\u0026rsquo;an, Hefei, Jinan, Hanzhou, and in Urumqi, China found conjunctivitis outpatient visits increased by 2.50%, 6.40%, 1.00%, 2.80% and 1.90% per 10 \u0026micro;g/m3 increase in NO2, respectively (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Guo H et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bao N et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We observed an increase of 12.60% in daily conjunctivitis outpatient visits per 10 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e increase in NO\u003csub\u003e2\u003c/sub\u003e concentration, respectively higher than the values reported in the aforementioned studies. This is primarily because Jiayuguan is situated at the western end of the Hexi Corridor, where low temperatures, temperature inversions, and calm winds are relatively common during winter and spring. NO₂ formed from motor vehicle emissions and localized industrial combustion tends to accumulate near the ground surface, leading to significant short-term concentration spikes. Research indicates that NO₂, a potent oxidizing gas, dissolves in the tear film and generates reactive products such as nitrous acid and nitric acid. These damages the corneal-conjunctival epithelial barrier, induces oxidative stress, and stimulates the release of inflammatory mediators, thereby exacerbating symptoms such as conjunctival hyperemia, foreign body sensation, and dryness. This effect is particularly pronounced in arid regions where inherently dry air and strong winds accelerate tear film evaporation, thereby compromising ocular surface defenses. Irritation tends to be further amplified under these conditions. Jiayuguan is a relatively small city with commuter traffic concentrated during morning and evening rush hours. Many individuals with underlying conditions such as conjunctivitis or dry eye are exposed to higher NO₂ levels outdoors during these periods, further amplifying NO2\u0026rsquo;s pro-inflammatory effects. Consequently, this significantly impacts local conjunctivitis outpatient numbers.\u003c/p\u003e \u003cp\u003eIn this study, we found a statistically significant association between CO level and conjunctivitis outpatient visits. Previous studies from different regions have suggested that not all short-term exposures to CO contribute to conjunctivitis (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) On one hand, exposure to low concentrations of CO might have shown elevated risks for conjunctivitis (Fu Q et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). On the other hand, estimates from two studies conducted in Hangzhou and Urumqi, China, indicated no adverse effects of CO on conjunctivitis outpatient visits(Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As discussed in the preceding section on NO₂, Jiayuguan is situated in an arid continental climate zone characterized by frequent calm winds and temperature inversions during winter and spring, which facilitate the accumulation of pollutants near the ground surface. Although CO emissions from motor vehicles generally exhibit low concentrations, they can form a relatively stable pattern of \u0026ldquo;low-concentration continuous exposure\u0026rdquo; during peak emission periods, such as morning and evening commutes and heating seasons. The literature indicates that while CO itself causes minimal direct ocular surface irritation, chronic low-dose exposure can induce oxidative stress and upregulation of inflammatory mediators through mild carboxyhemoglobin formation and tissue hypoxia. This synergizes with concurrent exposure to NO₂, PM, and ozone to amplify damage to the corneal conjunctival epithelium and tear film homeostasis. Against the backdrop of strong winds, extreme dryness, and intense UV radiation in Jiayuguan, where ocular surface barrier function is already compromised, such subclinical hypoxia and inflammation are more readily converted into clinical symptoms, manifesting as increased foreign body sensation, dryness, and hyperemia. Furthermore, the highly concentrated travel patterns of local residents and repeated exposure to low concentrations of CO and co-pollutants during similar time periods make this indirect pro-inflammatory effect easier to capture in time-series analysis. This is reflected in a relatively significant correlation between low CO concentrations and the number of outpatient visits for conjunctivitis\u003c/p\u003e \u003cp\u003eIn the present study, as well as in related research (Yan K et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), certain air pollutants were found to exert more pronounced detrimental effects on conjunctivitis outpatient visits among females compared to males. For instance, a multi-city investigation conducted in China demonstrated that females exhibited greater sensitivity to PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, and NO\u003csub\u003e2\u003c/sub\u003e (Lu P et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similarly, Yan et al. (2021) observed a stronger association between exposure to PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, and NO\u003csub\u003e2\u003c/sub\u003e and adverse health outcomes in females than in males in Hangzhou, China. In contrast, an analysis in Tai\u0026rsquo;an, China showed that male was more sensitive to PM\u003csub\u003e10\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e, whereas female children were more sensitive to PM\u003csub\u003e2.5\u003c/sub\u003e (Chen R et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Another study published in 2023 found that PM\u003csub\u003e10\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e increased female conjunctivitis outpatient visits, while PM\u003csub\u003e2.5\u003c/sub\u003e increased male conjunctivitis outpatient visits (Gui S-Y et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This is primarily because PM\u003csub\u003e2.5\u003c/sub\u003e, PM\u003csub\u003e10\u003c/sub\u003e, and NO₂ irritate the ocular surface and induce inflammation. Females, however, experience more pronounced effects from these pollutants due to narrower nasolacrimal ducts, hormonal fluctuations causing abnormal tear secretion, greater exposure to cosmetics, and weaker conjunctival defenses. In contrast, for males, they are more likely to work in outdoor environments, exposing them to higher levels of air pollutants. The high susceptibility to NO\u003csub\u003e2\u003c/sub\u003e and CO observed in children aged 0\u0026ndash;14 years and elderly (\u0026ge;\u0026thinsp;65 years) may be attributable to diminished metabolic and immunological function, as well as the alignment of outdoor activities with periods of elevated NO\u003csub\u003e2\u003c/sub\u003e and CO air pollution. Seasonal study revealed that the rise in conjunctivitis outpatient visits due to air pollution was more pronounced during colder seasons. This is mainly attributable to local heating methods and temperature inversion during the cold season in Jiayuguan, resulting in increased levels of PM\u003csub\u003e2.5\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e. Reduced humidity and frigid winds expedite tear film evaporation and exacerbate dry eye symptoms, undermining the mucosal barrier. Extended indoor confinement promotes the buildup of allergens and pathogens, hence increasing the likelihood of pollutants triggering or worsening conjunctival irritation.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study provides empirical evidence from a typical arid industrial city in Northwest China, revealing a significant short-term association between exposure to ambient air pollutants and the risk of outpatient visits for conjunctivitis. Contrary to the intuitive impression that the region is prone to sandstorms, our analysis shows that gaseous pollutants (NO\u003csub\u003e2\u003c/sub\u003e and CO), rather than particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e), are the key environmental factors driving the increased risk of conjunctivitis. This finding suggests that in industrialized cities in arid and semi-arid regions, chemical irritants from industrial emissions and traffic exhaust may pose a greater acute hazard to ocular health than physical dust from natural sources. Furthermore, this study elucidates the time lag characteristics of risk and its significant population heterogeneity. The adverse effects are more pronounced during the cold season, and the impact of different pollutants varies on susceptible subgroups: NO\u003csub\u003e2\u003c/sub\u003e primarily threatens the eye health of women and children aged 0\u0026ndash;14 years, while CO exposure is significantly associated with increased outpatient visits for conjunctivitis in men and older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years. Based on the above findings, we recommend: When formulating strategies for the prevention and control of eye diseases in arid regions, local environmental protection and health departments should not only focus on sand control and desertification prevention, but also attach great importance to the coordinated control of gaseous pollutants from industrial and transportation sources. Besides, during cold seasons and when gaseous pollutant concentrations are high, eye protection recommendations are issued for specific vulnerable groups. Despite limitations such as the lack of individual-level exposure data and the absence of consideration for indoor allergens, our findings fill a gap in research on ocular environmental health under special climatic conditions and provide important scientific evidence for subsequent public health interventions aimed at reducing the burden of environmentally induced eye diseases.\u003c/p\u003e"},{"header":"Appendix List of abbreviations","content":"\u003cp\u003eParticulate matter 2.5 PM2.5\u003c/p\u003e\n\u003cp\u003eParticulate matter 10 PM10\u003c/p\u003e\n\u003cp\u003eNO2 Nitrogen dioxide\u003c/p\u003e\n\u003cp\u003eSO2 Sulfur dioxide\u003c/p\u003e\n\u003cp\u003eO3 Ozone\u003c/p\u003e\n\u003cp\u003eCO Carbon monoxide\u003c/p\u003e\n\u003cp\u003eDLNM Distributed Lag Nonlinear Model\u003c/p\u003e\n\u003cp\u003eICD-10 International Classification of Diseases, Tenth Revision\u003c/p\u003e\n\u003cp\u003eTem Daily mean temperature\u003c/p\u003e\n\u003cp\u003eRH Daily mean relative humidity\u003c/p\u003e\n\u003cp\u003eCI Confidence Intervals\u003c/p\u003e\n\u003cp\u003eRR Relative Risks\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This work was supported by the Natural Science Foundation of Gansu Province, China (Grant No. 24JRRA407).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u003c/strong\u003e Data cannot be shared for privacy or ethical reasons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e Yanan Zhang contributed to the conception and design of the work. Yanan Zhang, guorui Song, Bo Zheng, Fei Chen, Lijun Ma and Xiaofeng Luo contributed to the acquisition, analysis, or interpretation of data for the work. Yanan Zhang drafted the manuscript and provided funding support. Fei Chen, Lijun Ma and Xiaofeng Luo critically revised the manuscript and supervised the development of research. All gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbusharha, A.A., Pearce, E.I. (2013). The effect of low humidity on the human tear film. Cornea 32, 429\u0026ndash;434. https://doi.org/10.1097/ICO.0b013e31826671ab\u003c/li\u003e\n \u003cli\u003eAlryalat, S.A., Toubasi, A.A., Patnaik, J.L., Kahook, M.Y. (2024). The impact of air pollution and climate change on eye health: a global review. 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Association between air pollution and emergency room admission for eye diseases in Rome, Italy: A time-series analysis. Environmental Pollution 343, 123279. https://doi.org/10.1016/j.envpol.2023.123279\u003c/li\u003e\n \u003cli\u003eUpaphong, P., Thonusin, C., Wanichthanaolan, O., Chattipakorn, N., Chattipakorn, S.C. (2024). Consequences of exposure to particulate matter on the ocular surface: Mechanistic insights from cellular mechanisms to epidemiological findings. Environmental Pollution 345, 123488. https://doi.org/10.1016/j.envpol.2024.123488\u003c/li\u003e\n \u003cli\u003eYan, K., Wang, M., Cheng, Y., Zou, J., Zhang, Y., Hu, S., Chen, Y., Lv, Q., Ying, S. (2023). An update on the association between ambient short-term air pollution exposure and daily outpatient visits for conjunctivitis: a time-series study in Hangzhou, China. Environ Sci Pollut Res 30, 102790\u0026ndash;102802. https://doi.org/10.1007/s11356-023-29647-7\u003c/li\u003e\n \u003cli\u003eZhou, J., Fan, L., Lin, H., Zheng, D., Yang, L., Zhuo, D., Zhuoma, J., Li, H., Zhang, S., Ruan, Z. (2023). Size-specific particulate matter and outpatient visits for allergic conjunctivitis in children: a time-stratified case-crossover study in Guangzhou, China. Environ Sci Pollut Res Int 30, 33949\u0026ndash;33959. https://doi.org/10.1007/s11356-022-24564-7\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"aerosol-and-air-quality-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Aerosol and Air Quality Research","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Air pollution, Conjunctivitis, Distributed lag non-linear model, Nitrogen dioxide, Carbon monoxide, Arid region","lastPublishedDoi":"10.21203/rs.3.rs-8454171/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8454171/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e: This study aims to quantify the short-term association between ambient air pollutants and outpatient visits for conjunctivitis using empirical data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This study collected daily outpatient visits for conjunctivitis in Jiayuguan City from January 1, 2023 to December 31, 2024, as well as meteorological and air pollutant data during the same period. We used a quasi-Poisson generalized linear regression model that incorporates a distributed lag nonlinear model to analyze the nonlinear relationship and lag effect between pollutant exposure and the risk of outpatient visits for conjunctivitis, and conducted stratified analysis by gender, age and season to identify susceptible populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: A total of 14,598 cases of conjunctivitis were included during the study. The results showed that particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e) was not statistically significantly associated with outpatients for conjunctivitis, and the exposure-response curve showed a downward trend. Conversely, gaseous pollutants (NO\u003csub\u003e2\u003c/sub\u003e and CO) showed a significant positive linear correlation with outpatients for conjunctivitis, with the effect being stronger in the cold season. NO\u003csub\u003e2\u003c/sub\u003e was significant at lag1-3, lag5 days and lag02–07 days, with each 10 μg/m\u003csup\u003e3\u003c/sup\u003e increase corresponding to an RR of 1.126 (95%CI: 1.050, 1.208), corresponding to a 12.60% increase in patient visits. CO had the strongest effect at lag07 days (RR =1.836, 95% CI: 1.126, 2.991). Furthermore, NO\u003csub\u003e2\u003c/sub\u003e primarily increases conjunctivitis visits in women and children (0-14 years), while CO exposure is significantly associated with conjunctivitis visits in men and older adults (≥65 years).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: In this arid, industrial city in Northwest China, gaseous pollutants (rather than particulate matter) are the key environmental factor driving the increase in conjunctivitis outpatient visits. This study reveals the differentiated effects of specific pollutants on populations with different demographic characteristics, highlighting the public health significance of strengthening ocular surface health protection for specific vulnerable subgroups during the cold season.\u003c/p\u003e","manuscriptTitle":"Short-term association between air pollutants and outpatient visits for conjunctivitis in an arid industrial city of Northwest China: A time-series study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 09:16:45","doi":"10.21203/rs.3.rs-8454171/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-05T15:49:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T08:14:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74971399433711307107418335509301518384","date":"2026-04-22T06:51:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-07T04:11:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279210570535638026135025546522357653762","date":"2026-03-02T03:50:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-25T02:44:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-29T12:38:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-29T12:36:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aerosol and Air Quality Research","date":"2025-12-26T09:29:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"aerosol-and-air-quality-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Aerosol and Air Quality Research","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"91f4fd62-910e-4fa9-b9a4-e9896c69051c","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-05T15:49:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T08:14:59+00:00","index":35,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T15:55:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 09:16:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8454171","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8454171","identity":"rs-8454171","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}