Direct mitigation of secondary organic aerosol particulate pollutants by multiphase photocatalysis

Particulate matter represents one of the most severe air pollutants globally. Organic aerosol (OA) comprises 30-70 % of submicron particle mass in urban areas. An effective way to mitigate OA particulate pollutants is to reduce the formation of secondary organic aerosol (SOA). Here, we studied the effect of titanium dioxide (TiO2) photocatalytic seeds on the formation and mitigation of SOA particles from α-pinene or toluene oxidation in chamber. For the first time, we discovered that under ultraviolet (UV) irradiation, the presence of TiO2 directly removed internally mixed α-pinene SOA mass by 53.7 % within 200 mins, and also directly removed SOA matter in an externally mixed state that is not in direct contact with TiO2 surface: the mass of externally mixed α-pinene SOA was reduced by 21.9 % within 81 mins, and the toluene SOA mass was reduced by 46.6 % in 145mins. In addition, the presence of TiO2 effectively inhibited the formation of SOA particles with a SOA mass yield of zero. This study brings up an innovative concept for air pollution control - the direct photocatalytic degradation of OA with aid of TiO2-based photocatalysts. Our novel findings will potentially bring practical applications in air pollution abatement and regional, even global aerosol-climate interactions.

Implications of PM2.5 chemical composition in modulating microbial community dynamics during spring in Seoul

Particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) harbors a diverse microbial community. To assess the ecological dynamics and potential health risks associated with airborne microorganisms, it is crucial to understand the factors influencing microbial communities within PM2.5. This study investigated the influence of abiotic parameters, including air pollutants, PM2.5 chemical composition (water-soluble ions and organics), and meteorological variables, on microbial communities in PM2.5 samples collected in Seoul during the spring season. Results revealed a significant correlation between air pollutants and water-soluble ions of PM2.5 with microbial α-diversity indices. Additionally, air pollutants exerted a dominant effect on the microbial community structure, with stronger correlations observed for fungi than bacteria, whereas meteorological variables including temperature, pressure, wind speed, and humidity exerted a limited influence on fungal α-diversity. Furthermore, the results revealed specific water-soluble ions, such as SO42-, NO3-, and NH4+, as important factors influencing fungal α-diversity, whereas K+ negatively correlated with both microbial α-diversity. Moreover, PM2.5 microbial diversity was affected by organic compounds within PM2.5, with fatty acids exhibited a positive correlation with fungal diversity, while dicarboxylic acids exhibited a negative correlation with it. Furthermore, network analysis revealed direct links between air pollutants and dominant bacterial and fungal genera. The air pollutants exhibited a strong correlation with bacterial genera, such as Arthrospira and Clostridium, and fungal genera, including Aureobasidium and Cladosporium. These results will contribute to our understanding of the ecological dynamics of airborne microorganisms and provide insights into the potential risks associated with PM2.5 exposure.

A review of the influence of environmental pollutants (microplastics, pesticides, antibiotics, air pollutants, viruses, bacteria) on animal viruses

Microorganisms, especially viruses, cause disease in both humans and animals. Environmental chemical pollutants including microplastics, pesticides, antibiotics sand air pollutants arisen from human activities affect both animal and human health. This review assesses the impact of chemical and biological contaminants (virus and bacteria) on viruses including its life cycle, survival, mutations, loads and titers, shedding, transmission, infection, re-assortment, interference, abundance, viral transfer between cells, and the susceptibility of the host to viruses. It summarizes the sources of environmental contaminants, interactions between contaminants and viruses, and methods used to mitigate such interactions. Overall, this review provides a perspective of environmentally co-occurring contaminants on animal viruses that would be useful for future research on virus-animal-human-ecosystem harmony studies to safeguard human and animal health.

Development and application of a multi-task oriented deep learning model for quantifying drivers of air pollutant variations: A case study in Taiyuan, China

Quantitative assessment of the drivers behind the variation of six criteria pollutants, namely fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM10), and carbon monoxide (CO), in the warming climate will be critical for subsequent decision-making. Here, a novel hybrid model of multi-task oriented CNN-BiLSTM-Attention was proposed and performed in Taiyuan during 2015-2020 to synchronously and quickly quantify the impact of anthropogenic and meteorological factors on the six criteria pollutants variations. Empirical results revealed the residential and transportation sectors distinctly decreased SO2 by 25 % and 22 % and CO by 12 % and 10 %. Gradual downward trends for PM2.5, PM10, and NO2 were mainly ascribed to the stringent measures implemented in transportation and power sectors as part of the Blue Sky Defense War, which were further reinforced by the COVID-19 pandemic. Nevertheless, temperature-dependent adverse meteorological effects (27 %) and anthropogenic intervention (12 %) jointly increased O3 by 39 %. The O3-driven pollution events may be inevitable or even become more prominent under climate warming. The industrial (5 %) and transportation sectors (6 %) were mainly responsible for the anthropogenic-driven increase of O3 and precursor NO2, respectively. Synergistic reduction of precursors (VOCs and NOx) from industrial and transportation sectors requires coordination with climate actions to mitigate the temperature-dependent O3-driven pollution, thereby improving regional air quality. Meanwhile, the proposed model is expected to be applied flexibly in various regions to quantify the drivers of the pollutant variations in a warming climate, with the potential to offer valuable insights for improving regional air quality in near future.

Trajectories of depressive symptom and its association with air pollution: evidence from the Mr. OS and Ms. OS Hong Kong cohort study

BACKGROUND

Depression is a global health priority. Maintaining and delaying depressive symptoms in older adults is a key to healthy aging. This study aimed to identify depressive symptom trajectories, predictors and mortality, while also exploring the relationship between air quality and depressive symptoms in older adults in the Hong Kong community over 14 years.

METHODS

This study is a longitudinal study in Hong Kong. The target population was community-dwelling older adults over age 65. Depressive symptoms were measured by the Geriatric Depression Scale (GDS-15). Group-based trajectory model was used to identify heterogeneity in longitudinal changes over 14 years and examine the associations between baseline variables and trajectories for different cohort members using multinomial logistic regression. The Kaplan-Meier method was employed to conduct survival analysis and explore the variations in survival probabilities over time among different trajectory group. Linear mixed model was used to explore the relationship between air quality and depressive symptoms.

RESULTS

A total of 2828 older adults were included. Three different trajectories of depressive symptoms in older people were identified: relatively stable (15.4%), late increase (67.1%) and increase (17.5%). Female, more number of chronic diseases, poor cognitive function, and poor health-related quality of life (HRQOL) were significantly associated with other less favorable trajectories compared with participants with stable levels of depressive symptoms. The late increase group had a lower mortality rate than the relatively stable and increased groups. Lower baseline ambient air pollutant exposure to NO2 over 14 years was significantly associated with fewer depressive symptoms.

CONCLUSIONS

In this study, we found that a late increase in depressive symptoms was the predominant trend in older Chinese people in Hong Kong. Poorer HRQOL was predictive of less favorable trajectories of depressive symptoms. Ambient air pollution was associated with depressive symptoms. This novel observation strengthens the epidemiological evidence of longitudinal changes in depressive symptoms and associations with late-life exposure to air pollution.

Detection of morphological and eco-physiological traits of ornamental woody species to assess their potential Net O3 uptake

Urban greening can improve cities' air quality by filtering the main gaseous pollutants such as tropospheric ozone (O3). However, the pollutant removal capacity offered by woody species strongly depends on eco-physiological and morphological traits. Woody species with higher stomatal conductance (gs) can remove more gases from the atmosphere, but other species can worsen air quality due to high O3 forming potential (OFP), based on their emitting rates of biogenic volatile organic compounds (bVOCs) and Leaf Mass per Area (LMA). Presently, there is a lack of data on eco-physiological (gs, bVOCs emissions) and foliar traits (LMA) for several ornamental species used in urban greening programs, which does not allow assessment of their O3 removal capacity and OFP. This study aimed to (i) parameterize gs, assess bVOCs emissions and LMA of 14 ornamental woody species commonly used in Mediterranean urban greening, and (ii) model their Net O3 uptake. The gs Jarvis model was parameterized considering various environmental conditions alongside isoprene and monoterpene foliar bVOCs emission rates trapped in the field and quantified by gas chromatography-mass spectrometry. The results are helpful for urban planning and landscaping; suggesting that Catalpa bignonioides and Gleditsia triacanthos have excellent O3 removal capacity due to their high maximum gs (gmax) equal to 0.657 and 0.597 mol H2O m-2 s-1. Regarding bVOCs, high isoprene (16.75 μg gdw-1 h-1) and monoterpene (13.12 μg gdw-1 h-1) emission rates were found for Rhamnus alaternus and Cornus mas. In contrast, no bVOCs emissions were detected for Camellia sasanqua and Paulownia tomentosa. In conclusion, 11 species showed a positive Net O3 uptake, while the use of large numbers of R. alaternus, C. mas, and Chamaerops humilis for urban afforestation planning are not recommended due to their potential to induce a deterioration of outdoor air quality.

Zeolite application mitigates NH3 and N2O emissions from pig slurry-applied field and improves nitrogen use efficiency in Italian ryegrass-maize crop rotation system for forage production

The present study aimed to assess the efficiency of zeolite in mitigating the nitrogen (N) losses through ammonia (NH3) and nitrous oxide (N2O) emissions from pig slurry (PS) applied to Italian ryegrass (IRG)-maize fields under a crop rotation system and the consequent effect on nitrogen use efficiency (NUE) for forage production. PS was applied at rates of 150 and 200 kg N ha-1 for the IRG and maize growing seasons, respectively, with or without zeolite. Soil mineral N content and NH3 and N2O emissions were measured periodically throughout the year-round cultivation of IRG and maize. Forage yield and nutritional composition were also analyzed at the harvest time of each crop. The PS with/without zeolite application effects were interpreted by comparison with those obtained for the negative control (no-N fertilization). Soil ammonium (NH4+) content in the PS-applied plots sharply increased within the first week, then progressively decreased in both the IRG and maize growing seasons. Soil NH4+ contents in the zeolite-amended plots were higher compared to the treatment without zeolite except for the first 1 or 2 weeks after PS application when soil nitrate (NO3-) contents significantly decreased. The increase in soil NH4+ content as affected by zeolite application was more distinct in the maize growing season than in the IRG growing season. NH3 emission was predominant at the early 2 weeks after PS application. Zeolite application reduced the cumulative emission of NH3 from PS by 16.7% and 24.4% and that of N2O by 15.6% and 31.5% in the IRG growing and maize growing seasons, respectively. NUE for dry matter (DM) and total digestible nutrients (TDN) production significantly improved in annual yield basis of the IRG-maize cropping. Zeolite application in PS-applied field may represent effective management in mitigating N losses through odorous NH3 and greenhouse gas (N2O) emissions, thereby improving NUE forage production.

Nitrogen dioxide exposure, attentional function, and working memory in children from 4 to 8 years: Periods of susceptibility from pregnancy to childhood

BACKGROUND

Air pollution exposure during pregnancy and childhood has been linked to executive function impairment in children, however, very few studies have assessed these two exposure periods jointly to identify susceptible periods of exposure. We sought to identify potential periods of susceptibility of nitrogen dioxide (NO2) exposure from conception to childhood on attentional function and working memory in school-aged children.

METHODS

Within the Spanish INMA Project, we estimated residential daily NO2 exposures during pregnancy and up to 6 years of childhood using land use regression models (n = 1,703). We assessed attentional function at 4-6 years and 6-8 years, using the Conners Kiddie Continuous Performance Test and the Attention Network Test, respectively, and working memory at 6-8 years, using the N-back task. We used distributed lag non-linear models to assess the periods of susceptibility of each outcome, adjusting for potential confounders and correcting for multiple testing. We also stratified all models by sex.

RESULTS

Higher exposure to NO2 between 1.3 and 1.6 years of age was associated with higher hit reaction time standard error (HRT-SE) (0.14 ms (95 % CI 0.05; 0.22) per 10 μg/m3 increase in NO2) and between 1.5 and 2.2 years of age with more omission errors (1.02 (95 % CI 1.01; 1.03) of the attentional function test at 4-6 years. Higher exposure to NO2 between 0.3 and 2.2 years was associated with higher HRT-SE (10.61 ms (95 % CI 3.46; 17.75) at 6-8 years only in boys. We found no associations between exposure to NO2 and working memory at 6-8 years.

CONCLUSION

Our findings suggest that NO2 exposure during the first two years of life is associated with poorer attentional function in children from 4 to 8 years of age, especially in boys. These findings highlight the importance of exploring long-term effects of traffic-related air pollution exposure in older age groups.

Decoding seasonal variability of air pollutants with climate factors: A geostatistical approach using multimodal regression models for informed climate change mitigation

In response to changes in climatic patterns, a profound comprehension of air pollutants (AP) variability is vital for enhancing climate models and facilitating informed decision-making in nations susceptible to climate change. Earlier research primarily depended on limited models, potentially neglecting intricate relationships and not fully encapsulating associations. This study, in contrast, probed the spatiotemporal variability of airborne particles (CO, CH4, SO2, and NO2) under varying climatic conditions within a climate-sensitive nation, utilizing multiple regression models. Spatial and seasonal AP data were acquired via the Google Earth Engine platform, which indicated elevated AP concentrations in primarily urban areas. Remarkably, the average airborne particle levels were lower in 2020 than in 2019, though they escalated during winter. The study employed linear regression, Pearson's correlation (PC), Spearman rank correlation models, and Geographically Weighted Regression (GWR) models to probe the relationship between pollutant variability and climatic elements such as rainfall, temperature, and humidity. Across all seasons, APs showed a negative correlation with rainfall while displaying positive correlations with temperature and humidity. The GWR and PC models produced the most reliable results from all the models employed, with the GWR model superseding the rest. Moreover, heightened aerosol levels were detected within a rainfall range of 600 mm/season, a temperature range of 25-30 °C, and humidity levels of 75 %-85 %. Overall, this study emphasizes the growing levels of APs in correlation with meteorological changes. By adopting a comprehensive approach and considering multiple factors, this research provides a more sophisticated understanding of the relationship between AP variability and climatic shifts.

Higher temperature and humidity exacerbate pollutant-associated lung dysfunction in the elderly

RATIONALE

Air pollution and extreme temperature and humidity are risk factors for lung dysfunction, but their interactions are not clearly understood.

OBJECTIVES

To assess the impact of exposure to air pollutants and meteorological factors on lung function, and the contribution of their interaction to the overall effect.

METHODS

The peak expiratory flow rates of 135 participants were repeatedly measured during up to four visits. Two weeks before each visit, the concentrations of gaseous pollutants and 19 fine particle components, and the temperature and relative humidity, were continuously monitored in the community where they lived. A Bayesian Kernel machine regression model was used to explore the non-linear exposure-response relationships of the peak expiratory flow rate with pollutant exposure and meteorological factors, and their interactions.

MEASUREMENTS AND MAIN RESULTS

Increased temperature and relative humidity could exacerbate pollutant-associated decline in the peak expiratory flow rate, although their associations with lung dysfunction disappeared after adjustment for pollutant exposure. For example, declines of peak expiratory flow rate associated with interquartile range increase of 3-day cadmium exposure were -0.03 and -0.07 units, when temperature was at 0.1 and 19.5 °C, respectively. Decreased temperature were associated with declines of peak expiratory flow rate after adjustment for pollutant exposure, and had interaction with pollutant exposure on lung dysfunction.

CONCLUSIONS

High temperature, low temperature, and high humidity were all high-risk factors for lung dysfunction, and their interactions with pollutant levels contributed greatly to the overall effects.

Long-term exposure to air pollutants and new-onset migraine: A large prospective cohort study

BACKGROUNDS

Short-term exposure to air pollutants increases the risk of migraine, but the long-term impacts of exposure to multiple pollutants on migraine have not been established. The aim of this large prospective cohort study was to explore these links.

METHODS

A total of 458,664 participants who were free of migraine at baseline from the UK Biobank were studied. Cox proportional hazards models were used to estimate the risk of new-onset migraine from combined long-term exposure to four pollutants, quantified as an air pollution score using principal component analysis.

RESULTS

During a median (IQR) follow-up of 12.5 (11.8, 13.2) years, a total of 5417 new-onset migraine cases were documented. Long-term exposure to multiple air pollutants was associated with an increased risk of new-onset migraine, as indicated by an increased in the SDs of PM2.5 (hazard ratio (HR): 1.04, 95% CI: 1.01-1.06, P = 0.009), PM10 (HR: 1.07, 95% CI: 1.04-1.10, P < 0.001), NO2 (HR: 1.10, 95% CI: 1.07-1.13, P < 0.001) and NOx (HR: 1.04, 95% CI: 1.01-1.07, P = 0.005) in the main model. The air pollution score showed a doseresponse association with an increased risk of new-onset migraine. Similarly, compared with those of the lowest tertile, the HRs (95% CI) of new-onset migraine were 1.11 (95% CI: 1.04-1.19, P = 0.002) and 1.17 (95% CI: 1.09-1.26, P < 0.001) in tertiles 2 and 3, respectively, according to the main model (P trend < 0.001).

CONCLUSION

Long-term individual and joint exposure to multiple air pollutants is associated with an increased risk of new-onset migraine.

Impact of the coronavirus disease 2019 pandemic on the diversity of notifiable infectious diseases: a case study in Shanghai, China

The outbreak of coronavirus disease 2019 (COVID-19) has not only posed significant challenges to public health but has also impacted every aspect of society and the environment. In this study, we propose an index of notifiable disease outbreaks (NDOI) to assess the impact of COVID-19 on other notifiable diseases in Shanghai, China. Additionally, we identify the critical factors influencing these diseases using multivariate statistical analysis. We collected monthly data on 34 notifiable infectious diseases (NIDs) and corresponding environmental and socioeconomic factors (17 indicators) from January 2017 to December 2020. The results revealed that the total number of cases and NDOI of all notifiable diseases decreased by 47.1% and 52.6%, respectively, compared to the period before the COVID-19 pandemic. Moreover, the COVID-19 pandemic has led to improved air quality as well as impacted the social economy and human life. Redundancy analysis (RDA) showed that population mobility, particulate matter (PM2.5), atmospheric pressure, and temperature were the primary factors influencing the spread of notifiable diseases. The NDOI is beneficial in establishing an early warning system for infectious disease epidemics at different scales. Furthermore, our findings also provide insight into the response mechanisms of notifiable diseases influenced by social and environmental factors.

Greenness mitigate cause-specific mortality associated with air pollutants in ischemic and hemorrhagic stroke patients: An ecological health cohort study

BACKGROUND

Air pollution is one of the most serious environmental risks to mortality of stroke. However, there exists a noteworthy knowledge gap concerning the different stroke subtypes, causes of death, the susceptibility of stroke patient, and the role of greenness in this context.

METHODS

We analyzed data from an ecological health cohort, which included 334,261 patients aged ≥40 years with stroke (comprising 288,490 ischemic stroke and 45,771 hemorrhagic stroke) during the period 2013-2019. We used Cox proportional hazards models with time-varying exposure to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) to assess the associations of annual average fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with both all-cause and cause-specific mortality. Additionally, we conducted analyses to examine the effect modification by greenness and identify potential susceptibility factors through subgroup analyses.

RESULT

In multivariable-adjusted models, long-term exposure to PM2.5 and NO2 was associated with increased risk of all-cause mortality (HR: 1.038, 95% CI: 1.029-1.047 for PM2.5; HR: 1.055, 95% CI: 1.026-1.085 for NO2, per 10 μg/m3, for ischemic stroke patients; similar for hemorrhagic stroke patients). Gradually increasing effect sizes were shown for CVD mortality and stroke mortality. The HRs of mortality were slightly weaker with high versus low vegetation exposure. Cumulative exposures increased the HRs of pollutant-related mortality, and greater greenness decreased this risk. Two subtypes of stroke patients exhibited diverse patterns of benefit.

CONCLUSION

Increasing residential greenness attenuates the increased risk of mortality with different patterns due to chronic air pollutants for ischemic and hemorrhagic stroke, offering valuable insights for precise tertiary stroke prevention strategies.

Fine particulate matter and sleep-disordered breathing severity in a large Italian cohort

BACKGROUND

Air pollution and obstructive sleep apnea (OSA) are both linked with cardiovascular co-morbidities and share similar pathophysiological mechanisms. A causal association between the two has been postulated. However, the results of the studies on this topic are conflicting mainly because of the lack of adjustment for important confounders such as seasonality and temperature. We aimed to evaluate if such an association exists in a highly polluted area like Lombardy region (Italy) when accounting for all confounders.

METHODS

Data of adult patients seen at the Sleep Disorder Centre in Milan from 2010 to 2020 were analysed and the main polygraphic data were retrieved. Air pollutant concentrations of the following pollutants NO2, O3, PM2.5, and PM10 were collected through monitoring stations.

RESULTS

A total of 3493 patients were included: males (2358, 67.5%) mean age 60.1 (SD = 14.3) years, BMI 29.2 (6.2) kg/m2, mean AHI 16.5 (18.1) events/h. After adjusting for all confounders, in the multivariable analysis, the only associations that remained significant were long-term exposure to O3 with indexes of OSA severity (AHI and ODI) but only in spring. Furthermore, a positive association was seen between long-term exposure to PM10 and ODI but in springtime only.

CONCLUSION

The findings of the current study does not support an association between fine particulate matter and OSA severity.

Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand

OBJECTIVES

Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous.

METHODS

This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand's Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels.

RESULTS

Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) concentration exceeded those later observed during the pandemic (p<0.001). In single-pollutant models, a 10 μg/m3 increase in PM2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p<0.01). After adjustment for co-pollutants, PM2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p<0.01). However, the PM2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak.

CONCLUSIONS

Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.

Long-term prediction of the effects of climate change on indoor climate and air quality

Limiting the negative impact of climate change on nature and humans is one of the most pressing issues of the 21st century. Meanwhile, people in modern society spend most of the day indoors. It is therefore surprising that comparatively little attention has been paid to indoor human exposure in relation to climate change. Heat action plans have now been designed in many regions to protect people from thermal stress in their private homes and in public buildings. However, in order to be able to plan effectively for the future, reliable information is required about the long-term effects of climate change on indoor air quality and climate. The Indoor Air Quality Climate Change (IAQCC) model is an expediant tool for estimating the influence of climate change on indoor air quality. The model follows a holistic approach in which building physics, emissions, chemical reactions, mold growth and exposure are combined with the fundamental parameters of temperature and humidity. The features of the model have already been presented in an earlier publication, and it is now used for the expected climatic conditions in Central Europe, taking into account various shared socioeconomic pathway (SSP) scenarios up to the year 2100. For the test house examined in this study, the concentrations of pollutants in the indoor air will continue to rise. At the same time, the risk of mold growth also increases (the mold index rose from 0 to 4 in the worst case for very sensitive material). The biggest problem, however, is protection against heat and humidity. Massive structural improvements are needed here, including insulation, ventilation, and direct sun protection. Otherwise, the occupants will be exposed to increasing thermal discomfort, which can also lead to severe heat stress indoors.

Air quality and characterization of synoptic circulation weather patterns in a South American city from Argentina

The potential cause-effect relationship between synoptic meteorological conditions and levels of criteria air pollutants, including CO, NO2, O3, PM10, PM2.5 and SO2, in Bahia Blanca, Argentina, was assessed for the period of 2018-2019. Daily back-trajectories and global meteorological data fields were employed to characterize the primary transport paths of air masses reaching the study site, and to identify the synoptic meteorological patterns responsible for these atmospheric circulations. Time series of surface-level meteorological parameters and midday mixing layer height were collected to examine the impact of the synoptic meteorological patterns on local meteorology. Furthermore, the NAAPS global aerosol model was utilized to identify days when contributions from long-range transport processes, such as dust and/or biomass burning smoke, impacted air quality. By applying this methodology, it was determined that the air masses coming from the N, NW and W regions significantly contributed to increased mean concentrations of coarse particles in this area through long-range transport events involving dust and smoke. Indeed, the high average levels of PM10 recorded in 2018-2019 (annual mean values of 47 and 52 μg/m3, respectively) represent the main air quality concern in Bahía Blanca. Moreover, PM10, PM2.5 and NO2 emissions should be reduced in order to meet recommended air quality guidelines. On the other hand, the results from this study suggest that the sources and meteorological processes leading to the increase in the concentrations of CO and SO2 have a local-regional origin, although these air pollutants did not reach high values probably as a consequence of the strong wind speed registered in this region during any synoptic meteorological pattern.

Proposal of policies based on temporal-spatial dynamic characteristics and co-benefits of CO2 and air pollutants from vehicles in Shanghai, China

In megacities, vehicle emissions face urgent challenges related to air pollution and CO2 control. To achieve the refinement of vehicle control policies for the co-control of air pollutants and CO2, this study established a vehicle emission inventory with high spatial and temporal resolution based on the hourly traffic flow in Shanghai and analyzed the spatial and temporal distribution characteristics of the real-time vehicle emissions. Meanwhile, a policy evaluation framework was constructed by combining pollutant emission predictions with quantitative co-control effect assessments. The results indicated that spatio-temporal variations in different air pollutants and CO2 could mainly be attributed to primary contributing vehicle types. The pollutants (CO2, CO and VOCs) primarily contributed by private cars exhibited a bimodal pattern in 24-h time series and their spatial distribution was concentrated in the urban city center. The spatial distribution of NOx and PM primarily contributed by heavy trucks was still obvious on non-urban center areas. Furthermore, the results of synergistic effect analysis revealed that the alternative energy replacement scenario demonstrated the most significant potential for the co-control. Based on temporal-spatial and co-benefit analysis, the precise control policy of vehicle emissions can be established through time-, region-, and model-control. This study provides references and research methods for the formulation of the vehicle refinement control policies in worldwide megacities.

Associations between air pollutants and acute exacerbation of drug-resistant tuberculosis: evidence from a prospective cohort study

BACKGROUND

Short-term exposure to air pollution may trigger symptoms of drug-resistant tuberculosis (DR-TB) through stimulating lung tissue, damaging tracheobronchial mucosa, the key anti-mycobacterium T cell immune function, and production and release of inflammatory cytokines.

OBJECTIVE

To investigate the association between acute exacerbations of DR-TB and short-term residential exposure to air pollutants (PM10, PM2.5, SO2, NO2, CO and O3) based on a large prospective cohort in Anhui Province, China.

METHOD

Patients were derived from a prospective cohort study of DR-TB in Anhui Province. All DR-TB patients underwent drug-susceptibility testing and prefecture-level reference laboratories confirmed their microbiologies. The case-crossover design was performed to evaluate the association between the risk of acute exacerbations of DR-TB and short-term residential exposure to air pollution.

RESULTS

Short-term NO2 exposure was significantly related to an elevated risk of first-time outpatient visit due to acute exacerbations of DR-TB(relative risk:1.159, 95% confidence interval:1.011 ~ 1.329). Stratification analyses revealed that the relationship between the risk of acute exacerbations and NO2 exposure was stronger in the elderly (age ≥ 65) DR-TB patients, and in individuals with a history of TB treatment.

CONCLUSIONS

NO2 Exposure was significantly associated with an elevated risk of acute exacerbation of DR-TB in Anhui Province, China.

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study

BACKGROUND AND AIMS

Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown.

METHODS

This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset.

RESULTS

Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx.

CONCLUSIONS

In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Wood heater smoke and mortality in the Australian Capital Territory: a rapid health impact assessment

OBJECTIVES

To estimate the number of deaths and the cost of deaths attributable to wood heater smoke in the Australian Capital Territory.

STUDY DESIGN

Rapid health impact assessment, based on fine particulate matter (PM2.5 ) data from three outdoor air pollution monitors and published exposure-response functions for natural cause mortality attributed to PM2.5 exposure.

SETTING

Australian Capital Territory (population, 2021: 454 000), 2016-2018, 2021, and 2022 (2019 and 2020 excluded because of the impact of extreme bushfires on air quality).

MAIN OUTCOME MEASURES

Proportion of PM2.5 exposure attributable to wood heaters; numbers of deaths and associated cost of deaths (based on the value of statistical life: $5.3 million) attributable to wood heater smoke.

RESULTS

Wood heater emissions contributed an estimated 1.16-1.73 μg/m3 to the annual mean PM2.5 concentration during the three colder years (2017, 2018, 2021), or 17-25% of annual mean exposure, and 0.72 μg/m3 (15%) or 0.89 μg/m3 (13%) during the two milder years (2016, 2022). Using the most conservative exposure-response function, the estimated annual number of deaths attributable to wood heater smoke was 17-26 during the colder three years and 11-15 deaths during the milder two years. Using the least conservative exposure-response function, an estimated 43-63 deaths per year (colder years) and 26-36 deaths per year (milder years) were attributable to wood heater smoke. The estimated annual equivalent cost of deaths was $57-136 million (most conservative exposure-response function) and $140-333 million (least conservative exposure-response function).

CONCLUSIONS

The estimated annual number of deaths in the ACT attributable to wood heater PM2.5 pollution is similar to that attributed to the extreme smoke of the 2019-20 Black Summer bushfires. The number of wood heaters should be reduced by banning new installations and phasing out existing units in urban and suburban areas.

High-precision spatio-temporal variations and future perspectives of multiple air pollutant emissions from Chinese biomass-fired industrial boilers

Biomass-fired industrial boilers (BFIBs) are one of the neglected and important anthropogenic sources of air pollutants. A comprehensive boiler-based emission inventory of multiple air pollutants from BFIBs in China in 2020 was first developed based on the activity level database and updated emission factors. Results showed that national emissions of air pollutants from BFIBs in 2020 were estimated to be 11.5 kt of PM, 10.8 kt of PM10, 7.4 kt of PM2.5, 40.5 kt of SO2, 79.8 kt of NOx, 4.2 kt of organic carbon (OC), 1.0 kt of elemental carbon (EC), 31.7 kt of nonmethane volatile organic compounds (NMVOCs), 15.9 kt of NH3, and 116.5 t of five trace metals (Hg, Cr, Cd, Pb, and As), respectively. Air pollutant emissions exhibited significant spatio-temporal heterogeneity. Monthly air pollutant emissions varied by geographical division due to the combined effects of industrial production and winter heating demand. These emissions were mainly concentrated in the eastern coastal region, with Guangdong, Guangxi, Fujian, Jiangsu, and Zhejiang being the five provinces having the highest emissions. In addition, scenario predictions indicate that as the pollution and carbon reduction strategy is implemented, air pollutant emissions from BFIBs in China could become well controlled, with PM, NOx, SO2, and Hg emissions in 2050 projected to be 3.0-8.3 kt, 36.5-75.7 kt, 16.2-32.8 kt, and 0.52-0.87 t, respectively. Our results can provide a highly spatio-temporal resolution inventory of multiple air pollutant emissions from BFIBs for air quality modelling and support the formulation of air pollution control policies for biomass fuel utilization in the context of the pollution and carbon reduction strategy.

Association between short-term exposure to ambient air pollutants and biomarkers indicative of inflammation and oxidative stress: a cross-sectional study using KoGES-HEXA data

BACKGROUND

Air pollution-induced systemic inflammation and oxidative stress are hypothesized to be the major biological mechanisms underlying pathological outcomes. We examined the association between short-term exposure to ambient air pollutants and biomarkers of inflammation and oxidative stress in 2199 general middle-aged Korean population residing in metropolitan areas.

METHODS

Serum levels of inflammatory cytokines (interleukin [IL]-1β, IL-6, IL-8, IL-10, and tumor necrosis factor [TNF]-α) and urinary levels of 8-hydroxy-2'-deoxyguanosine (8-OHdG) were measured. Daily concentrations of a series of air pollutants (particulate matter [PM]10, PM2.5, SO2, NO2, CO, and O3) were predicted using the Community Multiscale Air Quality modeling system, and participant-level pollutant exposure was determined using geocoded residential addresses. Short-term exposure was defined as the 1- to 7-day moving averages.

RESULTS

The multivariable-adjusted linear models controlling for the sociodemographic, lifestyle, temporal, and meteorological factors identified positive associations of PM with IL-1β, IL-8, IL-10, TNF-α, and 8-OHdG levels; SO2 with IL-10 levels, CO with IL-1β, IL-10, and TNF-α levels; and O3 with IL-1β, IL-8, and 8-OHdG levels. O3 levels were inversely associated with IL-10 levels. For each pollutant, the strongest associations were observed for the 7-day average PM and CO with IL-1β (per 10-µg/m3 increase in PM10: 2.7%, 95% confidence interval [CI] = 0.6-4.8; per 10-µg/m3 increase in PM2.5: 6.4%, 95% CI = 2.4-10.5; per 0.1-ppm increase in CO: 3.3%, 95% CI = 0.3-6.5); the 2-day average SO2 with IL-10 levels (per 1-ppb increase in SO2: 1.1%, 95% CI = 0.1-2.1); and the 7-day average O3 with IL-8 levels (per 1-ppb increase in O3: 1.3%, 95% CI = 0.7-1.9).

CONCLUSIONS

Short-term exposure to ambient air pollutants may induce oxidative damage and pro-inflammatory roles, together with counter-regulatory anti-inflammatory response.

Non-linear association between long-term air pollution exposure and risk of metabolic dysfunction-associated steatotic liver disease

BACKGROUND

Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) has become a global epidemic, and air pollution has been identified as a potential risk factor. This study aims to investigate the non-linear relationship between ambient air pollution and MASLD prevalence.

METHOD

In this cross-sectional study, participants undergoing health checkups were assessed for three-year average air pollution exposure. MASLD diagnosis required hepatic steatosis with at least 1 out of 5 cardiometabolic criteria. A stepwise approach combining data visualization and regression modeling was used to determine the most appropriate link function between each of the six air pollutants and MASLD. A covariate-adjusted six-pollutant model was constructed accordingly.

RESULTS

A total of 131,592 participants were included, with 40.6% met the criteria of MASLD. "Threshold link function," "interaction link function," and "restricted cubic spline (RCS) link functions" best-fitted associations between MASLD and PM2.5, PM10/CO, and O3 /SO2/NO2, respectively. In the six-pollutant model, significant positive associations were observed when pollutant concentrations were over: 34.64 µg/m3 for PM2.5, 57.93 µg/m3 for PM10, 56 µg/m3 for O3, below 643.6 µg/m3 for CO, and within 33 and 48 µg/m3 for NO2. The six-pollutant model using these best-fitted link functions demonstrated superior model fitting compared to exposure-categorized model or linear link function model assuming proportionality of odds.

CONCLUSION

Non-linear associations were found between air pollutants and MASLD prevalence. PM2.5, PM10, O3, CO, and NO2 exhibited positive associations with MASLD in specific concentration ranges, highlighting the need to consider non-linear relationships in assessing the impact of air pollution on MASLD.

Temporal variation of allergenic potential in urban parks during the vegetation period: a case study from Bratislava, Slovakia

Park greenery represents an oasis for urban residents; however, during the flowering period of trees that produce allergenic pollen grains, these areas threaten individuals suffering from seasonal allergic respiratory diseases. In this study, we evaluated the temporal distribution of the allergenic potential of three most important urban parks in Bratislava over the vegetation period, using a modification of the Urban Green Zone Allergenicity Index (IUGZA) and Individual-Specific Allergenic Potential Index (IISA) designed as a running index - rIUGZA and rIISA. We found that rIUGZA gives better information for park management and revitalization, since it considers the potential size of woody plants, while rIISA, considering the actual size of the vegetation, provides more relevant information for pollen-allergy sufferers. Based on rIISA, the allergenic potential was highest in May for the Grassalkovich Garden (formal baroque garden) and Janko Kráľ Park (English landscape park) and in April for the Medic Garden (repurposed baroque garden). We also found differences in the duration of the period of increased allergenic potential in these parks, ranging from 1 to 3 months. Based on the total annual sums of rIISA, we found the highest allergenic potential in the Medic Garden and lowest in the Janko Kráľ Park. This variance is caused mainly by the different density of trees and percentage of allergenic species. The biggest contributors to the allergenic potential were Platanus, Acer and Tilia. Based on the information on temporal variation of the allergenic potential during the vegetation period provided by the running indices, it is possible to improve the planning of park revitalization based on the flowering period of allergenic species and provide better information to the pollen-allergy sufferers for minimizing the allergenic effect of urban green areas on their health during a particular month.

Grid computing method for atmospheric environmental capacity coupled with ventilation coefficient using CALPUFF simulation and GIS spatial analysis technology

Atmospheric environmental issues have evolved from point source pollution to regional pollution, leading to controlling specific air pollutant emissions. A-value method has been found suitable for estimating large-scale atmospheric environmental capacity rather than small-scale, resulting in the inaccuracy of developing air pollution control strategy. This study proposed a grid computing method based on the CALPUFF modelling system and GIS spatial analysis tool. The meteorological data from the MM5 model were used to simulate the spatial distribution of air pollutants. The meteorological flow field data was used to simulate the ventilation coefficient. The A value was revised with the simulated to achieve accurate results of atmospheric environment capacity. The credibility was verified by applying this method to Fengtai District, Beijing, China. The research area was divided into small partitions via the ArcGIS spatial analysis tool. The simulation results agreed well with the observation data from actual monitoring stations, even for the PM10 concentration with the most significant error (MRE: 7.05%-13.28%, RMSE: 11.62-17.89, R2: 0.84-0.90). The GIS spatial analysis tools were applied to match the underlying surface types and overcome the restrictions of administrative boundary management. The study proposed four schemes to achieve differentiated air pollutant emission reduction and develop suitable control strategies. Furthermore, this method can be applied on different scales of natural geographic boundaries and realize the precise spatial management of atmospheric environmental capacity.

Multiomics was used to clarify the mechanism by which air pollutants affect chronic obstructive pulmonary disease: A human cohort study

Exposure to air pollutants has been associated with various adverse health outcomes, including chronic obstructive pulmonary disease (COPD). However, the precise underlying mechanism by which air pollution impacts COPD through remains insufficiently understood. To elucidated the molecular mechanism by which air pollutant exposure contributes to alterations in the gut microbiome and metabolism in AECOPD patients, we employed metagenomics and untargeted metabolomics to analyse the gut microbial, faecal, and serum metabolites. The correlations among air pollutants, gut microbes, serum metabolites, and blood biochemical markers were assessed using generalised additive mixed models and Spearman correlation analysis. The findings revealed that for every 10 μg/m3 increase in PM2.5 concentration, the α-diversity of the gut flora decreased by 2.16% (95% CI: 1.80%-2.53%). We found seven microorganisms that were significantly associated with air pollutants, of which Enterococcus faecium, Bacteroides fragilis, Ruthenibacterium lactatiformans, and Subdoligranulum sp.4_3_54A2FAA were primarily associated with glycolysis. We identified 13 serum metabolites and 17 faecal metabolites significantly linked to air pollutants. Seven of these metabolites, which were strongly associated with air pollutants and blood biochemical indices, were found in both serum and faecal samples. Some of these metabolites, such as 2,5-furandicarboxylic acid, C-8C1P and melatonin, were closely associated with disturbances in lipid and fatty acid metabolism in AECOPD patients. These findings underscore the impact of air pollutants on overall metabolism based on influencing gut microbes and metabolites in AECOPD patients. Moreover, these altered biomarkers establish the biologic connection between air pollutant exposure and AECOPD outcomes.The identification of pertinent biomarkers provides valuable insights for the development of precision COPD prevention strategies.

Impact of Lockdown on Air Quality in the Most Polluted Cities of India

Background

COVID-19 has become a global pandemic, prompting lockdowns in practically every country. To prevent the spread of the disease, India has enforced a rigorous nationwide lockdown that commenced in March 2020. The lockdown imposed amid the pandemic ensured that most commercial activities and vehicle transportation ceased, resulting in a significant reduction in air pollution levels.

Material and Methods

The value of air pollutants PM10, PM2.5, NO2, and SO2 from January to May 2020 was obtained from the Indian Central Pollution Control Board. Before lockdown and during lockdown, relative fluctuations in ambient concentrations of four air contaminants were investigated. The Box-Jenkins approach was used to estimate future air pollution data points using time series data analysis.

Results

The PM10 level reduced by 61%, 30%, 68%, 37%, and 43% in the selected cities, respectively. Comparison of other pollutant concentrations before and after the lockdown also found a reduction in ambient pollutant concentrations, resulting in improved air quality. Inference of predicted model values to observed values revealed a significant increase in the concentrations of all pollutants. The percentage increases in AQImean from predicted to observed values were 206% in Ghaziabad, 148% in Delhi, 59% in Hyderabad, and 160% in Cochin.

Conclusion

The strict lockdown has resulted in a significant drop in air pollutant levels. Upgrading present technologies could help keep pollution to a minimum of 37% under control. The findings would prompt the government to consider how to strictly reduce vehicle and industrial pollution to improve air quality and maintain improved public health.

Effects of air pollutants and temperature on the number of asthma outpatient visits in Hohhot, China

Although numerous studies have linked asthma to air temperature and pollution, few studies have examined their interactive effects on asthma outpatient visits. This study investigated how air pollutants and their interactions with temperature affect asthma outpatient visits in a city in northern Chinaduring the time period 2018 - 2020 . . As the results, 24,163 asthma outpatients were recorded, a 10-μg/m3 increase in PM10, PM2.5, SO2, and NO2 concentrations was associated with significant increases in visits of 3.47% (95% CI: 2.35%-4.60%), 0.83% (95% CI: 0.36%-1.30%), 3.17% (95% CI: 1.47%-4.90%), and 8.90% (95% CI: 6.09%-11.79%), respectively. The effect was stronger in females than males, and stronger in the elderly (≥65 years) than among the young. The interaction between low temperatures and high air pollution levels significantly increased the number of asthma outpatient visits. This study emphasizesthe importance of reducing air pollution in order to lessen the effects of cold.

Positive association between ambient air pollutants and incident kidney stones

We aimed to assess the association between exposure to various air pollutants, individually or jointly, and incident kidney stones, and examine whether genetic susceptibility for kidney stones may modify this association. 453,977 participants without prior kidney stones from the UK Biobank were included. Annual mean concentrations of PM2.5, PM2.5-10, PM10, NO2, and NOx were estimated with a land use regression model. A weighted air pollution score was constructed that incorporates the five pollutants mentioned above. A genetic risk score (GRS) was calculated based on 20 single-nucleotide polymorphisms associated with kidney stones. The primary outcome was incident kidney stones. During a median follow-up of 11.9 years, 5,375 kidney stones were recorded. The adjusted HRs (95%CI) of incident kidney stones were 1.04 (1.01-1.07), 1.02 (1.00-1.05), 1.03 (1.01-1.06), 1.05 (1.02-1.08), and 1.04 (1.01-1.07), for per standard deviation (SD) increment in PM2.5 (SD:1.06 μg/m3), PM2.5-10 (SD:0.90 μg/m3), PM10 (SD:1.90 μg/m3), NO2 (SD:7.63 μg/m3), and NOx (SD: 15.63 μg/m3), respectively. Moreover, there was a significantly linear association between the air pollution score and incident kidney stones (per SD increment: HR, 1.05, 95%CI: 1.02-1.08), especially in those without diabetes (vs. participants with diabetes; P-interaction = 0.037). In addition, the association between air pollution and kidney stones was statistically significant only in participants within intermediate-high kidney stone GRS, but not in those with low GRS kidney stone, though the interaction was not significant (P-interaction = 0.385). In conclusion, exposure to air pollution was associated with a higher risk of incident kidney stones, calling for the need to improve air quality.

A review of personal exposure studies in selected Asian countries' public transport microenvironments: lessons learned and future directions

This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.

Cooking fuel frequency use in urban Uganda: addressing household air pollution

This study examines the frequency use of cooking fuels by residents of four urban areas in Uganda (Kampala, Lira, Soroti, and M'bale). The specific objective is to identify urban dweller characteristics influencing the frequency of use of fuelwood, charcoal, kerosene, gas, or electricity in daily cooking. An ordered probit regression uses the survey data to estimate five relationships of cooking fuel use frequency generating measures of probability use in response to socio-demographic, income, and location characteristics. Charcoal and firewood remain the key cooking fuels and their use exposes families to excessive levels of toxic emissions. The probability of frequent firewood use increases among elderly, those with children or lower incomes, and residing outside Kampala. Frequency of cooking with charcoal decreases with higher age, having children, or residing in Kampala, but increases if married, with high income, or if college educated. The frequent use of liquid gas or electricity increases with income and among the college educated, but there is no detectable effect of residing in Kampala, likely due to hindered progress of expanding supply infrastructure. Targeting meal preparers with public education campaigns offers a path of changing cooking fuels use to those less polluting.

In vitro toxicity of fine and coarse particulate matter on the skin, ocular and lung microphysiological cell-culture systems

Particulate matter (PM) has been associated with adverse effects on human health, causing allergies, skin and eye irritation and corrosion, respiratory tract irritation, headaches, bronchoconstriction, cardiopulmonary diseases such as asthma, chronic obstructive pulmonary disease (COPD), lung cancer, reproductive problems, premature deaths, and epigenetic changes that lead to a wide variety of cancers, among other health conditions. The air quality in the Medellín - Colombia presents fluctuations that oscillate between the maximum permissible levels established at the national level and by the WHO, which represents a latent risk to people's health. Although important efforts have been made to quantify the different levels of pollution and administrative measures have been established to mitigate air pollution, little research work has been done to establish the relationship between these levels of pollutants and the effects on biological systems. The objective of the present research was to make a morphological and chemical characterization of particulate matter (PM) captured with a commercial air filter and a electrospun nanofiber membrane and evaluate the cytotoxicity of the each PM extracts in monolayer and co-culture models which recreate microphysiological systems of lung, skin and cornea and propose the possible cellular interactions that lead the cytotoxic response of the chemical compounds found in particulate matter in cities. The morphology and elemental chemical characterization were done with scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM - EDS). For the polycyclic aromatic hydrocarbons detection was made with a chromatographic method accoupled to mass spectrometer. Finally, the cytotoxicity was made in monolayers of A549, HEK001, and SIRC cell lines and microphysiological systems consisting of two-cell layer construct to resemble the interaction between fibroblast and epithelial cells that comprises naturally the corneal, skin and lung tissue. We performed three different cocultures models with BALB/3T3 clone A31 as a feeder layer, using porous Transwell® inserts in the in-contact and non-contact way. Monolayer and co-culture models were exposed to coarse and fine PM (1, 2, and 5 mg/mL) and the cell viability was evaluated at 24 h using an MTT assay. The electrospun nanofibers membranes demonstrates higher efficiency to capture PM with different sizes and high concentration of polycyclic aromatic hydrocarbons, heavy metals, and other chemical compounds responsible of many human diseases. Cytotoxic effects of MP were observed in all models at higher concentration; however, models exposed to fine PM exhibited a significant reduction in cell viability compared to those exposed to coarse PM. In addition, multilayer models are more resistant to PM exposure than monolayer models. Furthermore, the study indicated that, depending on the seeding strategy, different results might be observed: the non-contact model showed higher resistance to PM exposure than in-contact for SIRC and HEK001, but A549 monolayers showed the highest viability response. This study demonstrates the usefulness of applying co-culture models to assess environmental pollutant toxicity, in addition to being a potential alternative method to animal testing for risk assessment.

Association Between Air Pollution and Coronary Heart Disease Hospitalizations in Lanzhou City, 2013-2020: a Time Series Analysis

Coronary heart disease (CHD) is one of the most serious public health problems. However, few studies have focused on the effects of exposure to particulate matter and gaseous air pollutants on CHD. This study aimed to explore the relationship between air pollutants and the number of hospitalized patients with CHD in Lanzhou, and we collected daily data on the number of hospitalized patients with CHD, daily air pollutants, and meteorological factors from 2013 to 2020. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson regression model was applied to evaluate the relationship between air pollutants and the number of hospitalized patients with CHD. The results indicated that the hysteresis effect of all pollutants except O38h reached its maximum at lag3, and the relative risk of coronary heart disease admission was 1.0014 (95%CI: 1.0004, 1.0023), 1.0003 (95%CI: 1.0000, 1.0006), 1.0020 (95%CI: 1.0004, 1.0035), and 1.0053 (95%CI: 1.0026, 1.0080) when PM2.5, PM10, NO2, and SO2 concentrations were increased by 10 μg/m3, respectively. Each 1 mg/m3 increase in CO concentration was associated with a relative risk of coronary heart disease; hospitalization risk was 1.1076 (95%CI: 1.0530, 1.1650). We observed a relative risk of 0.9991 (95%CI: 0.9986, 0.9999) for each 10 μg/m3 increase in O38h for coronary heart disease admission at lag1. Women and elderly were more susceptible to the impact of air pollution, and the impact was greater during cold seasons. Our results indicate that air pollution increased the risk of hospitalization for CHD in a short term. The research findings can provide strategic insights into the impact of current and future air pollution on CHD.

Association between cognitive function and dusty weather: a propensity score matching study

BACKGROUND

With a rapidly aging global population, the health of older adults is a national priority for countries across the world. Dusty weather has been demonstrated to be a potential risk factor of cognitive function among the elderly population. However, there is a paucity of studies exploring the associations between dusty weather and cognitive function among the older in China.

METHODS

Data on individual characteristics were obtained from the China Health and Retirement Longitudinal Survey (CHARLS) 2018, whereas data on air pollution were sourced from environmental monitoring stations in China. Cognitive function, including general cognitive function, episodic memory, and linguistic competence, was assessed by self- or informant-questionnaires. We used propensity score matching and linear regression to investigate the relationship between dusty weather and cognitive function. Sensitivity analyses were conducted to test the robustness of the results.

RESULTS

This study included 8,604 participants older than 60 years old. After controlling air pollutant weather, dusty weather was demonstrated to be positively associated with a decline in cognitive function (Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), 4.0, 95% confidence interval (CI): 3.11, 4.89; Mini-Mental State Exam (MMSE), 0.63, 95% CI: 0.34, 0.92). Results of sensitivity analysis showed that our research findings are robust.

CONCLUSION

Older adults living in dusty weather regions suffered a higher level of cognitive impairment, and such adverse effects were more substantial among females compared with their male counterparts. Targeted health interventions to help older adults living in regions where dusty weather occurs frequently are suggested to be proposed.

Impacts of short-term low-level exposure to air pollutants on hospital admissions for pulmonary sepsis in elderly patients

BACKGROUND

Acute exposures to high levels of air pollutants are thought to be associated with hospitalization of patients with lung infection, while relatively little is known about the association between air pollutants and HOSPITAL ADMISSIONS FOR pulmonary sepsis.

OBJECTIVES

To assess the correlation between low-level exposure to air pollutants and the hospitalizations for pulmonary sepsis in elderly patients.

METHODS

A total of 249 elderly patients with pulmonary sepsis from January 2018 to December 2020 in Shenzhen people's hospital were included. The data regarding hospitalizations for pulmonary sepsis, meteorological factors, and daily average levels of air pollutants on single-day lags (Lag0 to Lag7) in Shenzhen were collected. Low-level exposure was defined as the annual means of air pollutants below the levels of the Ambient Air Quality Standard (AAQS) in China (NO. GB3095-2012) and/or Global Air Quality Guidelines (AQG). A time-stratified case-crossover study design approach was used to evaluate the associations between exposure to air pollutants and incidence of the disease, univariate and multivariate logistic regression analysis to analyze the association between levels of air pollutants and hospitalizations for pulmonary sepsis in elderly patients.

RESULTS

Exposure to PM1(P = 0.007, Lag 2 day; P = 0.038, Lag6 day), PM2.5(P = 0.046, Lag2 day), PM10(P = 0.048, Lag4 day), and O3(P = 0.044, Lag6 day) was positively correlated with elevated risk of hospitalizations for pulmonary sepsis. In addition, logistic regression analysis revealed that exposure to PM1 (OR = 1.833, 95%CI:1.032 ~ 3.256, Lag6 day) and O3 (OR = 2.091, 95%CI:1.019 ~ 4.289, Lag6 day) were the independent risk factors of pulmonary sepsis in elderly patients.

CONCLUSION

Our results demonstrate that short-term low-level exposure to PM1 and O3 could elevate the risk of hospitalizations for pulmonary sepsis in elderly patients in Shenzhen, providing evidence for developing early warning and screening systems for pulmonary sepsis.

Trends in air pollutants emissions in the Qinghai-Tibet Plateau and its surrounding areas under different socioeconomic scenarios

The Qinghai-Tibetan Plateau (QTP) and its surrounding areas are undergoing rapid changes in socioeconomic conditions, activity sectors, and emission levels. These changes underscore the significance of conducting local environmental assessments in the future and generating air pollutant emission forecasts necessary for effective evaluation. Current pollutants emissions pathways exhibit regional limitation since their based historical inventory could not accurately reflect the emission characteristics in QTP. This study constructed a high spatial resolution (0.1° × 0.1°) atmospheric pollutant emissions dataset in the Qinghai-Tibet Plateau and its surrounding Areas (QTPA) based on updated emission inventory and various socioeconomic scenarios. We found that the pollutant emissions levels are distinct among different social development scenarios, with SSP3-7.0 demonstrating the highest magnitude of emissions. Regional and sectoral contributions exhibit substantial variations. Notably, solid fuel combustion originating from residential sectors in Northeast India and open fires in Myanmar are identified as high-density sources of PM2.5 emissions. Current pollutant emission patterns in the QTPA are more akin to SSP2-4.5, however, specific regions such as Qinghai and Tibet have exhibited more pronounced trends of emission reduction. The comparison with previous datasets reveals that the predicted pollutant emissions in this study are lower than Scenario Model Intercomparison Project (SMIP) dataset but higher than Asian-Pacific Integrated Model (AIM) dataset due to the revised inventory data and model variations, in which the latter might be the main obstacle to accurate emissions prediction.

Emissions from international airport and its impact on air quality: A case study of beijing daxing international airport (PKX), China

The Beijing Daxing International Airport is a newly opened airport, and a comprehensive emission inventory of air pollution sources has not yet been established. The lack of basic inventory data will cause difficulties in controlling the air quality (AQ) in and around the airport. Based on actual flight data, we established a comprehensive emission inventory (carbon monoxide (CO), nitrogen oxides (NOX), hydrocarbons (HC), sulfur dioxide (SO2), particulate matter (PM), and carbon dioxide (CO2)) at Beijing Daxing International Airport. Furthermore, we evaluated the impact of airport emissions on the AQ of the surrounding areas using the ADMS-Airport model. The results showed that Beijing Daxing International Airport emitted 1.15 E+03, 1.76 E+03, 1.38 E+02, 1.16 E+02, 3.53 E+01, and 3.75 E+05 t of CO, NOX, HC, SO2, PM, and CO2, respectively, from July 1, 2020, to June 30, 2021. Engine exhaust emissions (landing and takeoff [LTO] cycles) dominated all airport pollutant emissions except for PM from the power plant. Among all aircraft types, B738 emitted the most CO2, as it accounted for almost half of all the flights. The AQ simulations showed that the air pollutant diffusion range was concentrated within 15 km of the airport and the surrounding areas. The contribution of airport emissions to NOX concentrations was most apparent under the most unfavorable meteorological conditions. Based on the average pollutant concentration during the study period, the Gu'an Li Hu Primary School station was the most affected. In particular, NOX concentrations at this station were approximately 50% higher in winter than in summer. Currently, the airport's contribution to pollution in the surrounding areas is insignificant. However, with the continuous increase in the number of flights at the airport, its impact on the AQ in the surrounding areas must be addressed in the future.

Effects of air environmental audit on reducing air pollutant emissions: evidence from China

In order to mitigate air pollution, governments have implemented various active measures for air pollution prevention and control, among which the air environmental audit is an essential supervision initiative of air environmental regulation policy. This study aims to focus on and investigate the role of air environmental audit in national governance systems by collecting panel data on air environmental audits and air pollutant emissions from 261 prefecture-level cities across China between 2004 and 2018. Using difference-in-differences (DID) models, we empirically analyzed the policy effects of air environmental audits on reducing air pollutant emissions. The results indicate that air environmental audits have a significant impact on reducing air pollutant emissions, which is robust under multiple scenarios, including propensity score matching and placebo tests. The effect of air environmental audits varies significantly among different air pollutants, with the most significant and rapid effect observed on PM2.5 concentration, while industrial sulfur dioxide and industrial smoke (dust) emissions exhibit a time lag. Moreover, the promotion effect of air environmental audits on air pollution control displays strong heterogeneity based on local economic levels, initial environmental quality, and government competition. Therefore, it is of great significance to intensify the implementation of air environmental audits for air pollution control and to promote and improve the audit work according to pollutant classification and local conditions, thereby fully leveraging the audit's role and further improving air quality continuously.

Association of air pollution and green space with all-cause general practitioner and emergency room visits: A cross-sectional study of young people and adults living in Belgium

BACKGROUND

Residing in areas with lower levels of air pollution and higher green space is beneficial to physical and mental health. We investigated associations of PM2.5, tree cover and grass cover with in-hours and out-of-hours GP visits and ER visits, for young people and adults. We estimated potential cost savings of GP visits attributable to high PM2.5.

METHODS

We linked individual-level health insurance claims data of 315,123 young people (10-24 years) and 885,988 adults (25-64 years) with census tract-level PM2.5, tree cover and grass cover. Deploying negative binomial generalized linear mixed models, we estimated associations between quartile exposures and the three outcome measures.

RESULTS

For in-hours and out-of-hours GP visits, among young people as well as adults, statistically significant pairwise differences between quartiles suggested increasing beneficial effects with lower PM2.5. The same outcomes were statistically significantly less frequent in quartiles with highest tree cover (>30.00%) compared to quartiles with lower tree cover, but otherwise pairwise differences were not statistically significant. These associations largely persisted in rural and urban areas. Among adults living in urban areas lower grass cover was associated with increased in-hours GP visits and ER visits. Assuming causality, reducing PM2.5 levels to the lowest quartile (4.91-7.49 μg/m³), among adults, 195,964 in-hours and 74,042 out-of-hours GP visits could be avoided annually. Among young people, 27,457 in-hours and 22,423 out-of-hours GP visits could be avoided annually. Nationally, this amounts to an annual potential cost saving of €43 million (€5.7 million in out-of-pocket payments and €37.2 million in compulsory health insurance).

CONCLUSION

Higher ambient PM2.5 and lower tree cover show associations with higher non-urgent and urgent medical care utilization. These findings confirm the importance of reducing air pollution and fostering green zones, and that such policies may contribute positively to economic growth.

Association between exposure to air pollution during preconception and risk of gestational diabetes mellitus: The role of anti-inflammatory diet

BACKGROUND

Regarding the association between the sensitive time-windows of air pollution (AP) exposure and gestational diabetes mellitus (GDM), epidemiological findings are inconsistent. The dietary inflammatory potential has been implicated in the development of GDM, but it is unclear whether an anti-inflammatory diet during pregnancy reduces the association between AP and GDM.

OBJECTIVE

We aimed to characterize the sensitive time-windows of AP to GDM risk. Further, to verify whether a maternal anti-inflammatory diet can reduce the risk of AP-induced GDM, by inhibiting inflammation.

METHODS

A total of 8495 pregnant women were included between 2015 and 2021 in the Maternal & Infants Health in Hefei study. Weekly mean AP exposure to fine particles (PM2.5 and PM10), SO2, and NO2 was estimated from the data of Hefei City Ecology and Environment Bureau. High-sensitivity C-reactive protein (hs-CRP) concentrations were measured to evaluate systemic inflammation. The empirical dietary inflammatory pattern (EDIP) score based on a validated food frequency questionnaire was used to assess the dietary inflammatory potential of pregnant women. Logistic regression models with distributed lags were used to identify the sensitive time-window for the effect of AP on GDM. Mediation analysis estimated the mediated effect of hs-CRP, linking AP with GDM. Stratified analysis was used to investigate the potential effect of anti-inflammatory diet on GDM risk.

RESULTS

The increased risks of GDM were found to be positively associated with exposure to PM2.5 (OR = 1.11, 95% CI:1.07-1.15), PM10 (OR = 1.12, 95% CI:1.09-1.16), and SO2 (OR = 1.42, 95% CI:1.25-1.60) by distributed lag models, and the critical exposure windows were 21st to 28th weeks of preconception. The proportion of association between PM2.5, PM10, and SO2 with GDM mediated by hs-CRP was 25.9%, 21.1%, and 19.4%, respectively, according to mediation analysis. In the stratified analyses by EDIP, the association between AP and GDM was not statistically significant among women those with anti-inflammatory diets.

CONCLUSIONS

Exposure to AP, especially in 21st to 28th week of preconception, is associated with risk of GDM, which is partly mediated by hs-CRP. Adherence to the anti-inflammatory dietary pattern may reduce the risk of AP-induced GDM.

Short-term environmental triggers of hemorrhagic stroke

Hemorrhagic stroke (HS) is associated with severe morbidity and high mortality. Identifying the trigger factors for HS is critical for disease prevention. This study aimed to assess the associations between short-term environmental triggers (STETs) and HS risk. We systematically searched six databases for articles published up to September 9, 2022. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random-effect models to evaluate the associations between STETs and the risk of HS. Heterogeneity was assessed using Cochran Q and I2 tests. A total of 63 studies were included for analysis. Of these, 40 focused on air pollutants and 23 on meteorological factors. Pooling results showed that exposure to particulate matter 2.5 (PM2.5; OR, 1.003 per 10 μg/m3; 95% CI, 1.001-1.007), sulfur dioxide (SO2; OR, 1.022 per 10 ppb; 95% CI, 1.005-1.040), and nitrogen dioxide (NO2; OR, 1.026 per 10 ppb; 95% CI, 1.004-1.047) was associated with an increase in HS risk. Moreover, exposure to PM2.5 (OR, 1.018 per 10 μg/m3; 95% CI, 1.009-1.027) and SO2 (OR, 1.102 per 10 ppb; 95% CI, 1.010-1.204) was positively associated with the risk of intracerebral hemorrhage. In addition, extreme temperature, high pressures, high and low relative humidity were potentially associated with HS risk. Targeted preventive measures to limit the effect of these air pollutants and extreme meteorological factors should be taken to reduce the HS disease burden. Further studies are warranted to verify these findings.

Revealing the impact of China's clean air policies on synergetic control of CO2 and air pollutant emissions: Evidence from Chinese cities

China is presently confronted with the intricate challenge of simultaneously mitigating air pollution and decelerating the pace of climate change. An integrated perspective to investigate the synergetic control of CO2 and air pollutant emissions is in an urgent need. Using data for 284 Chinese cities from 2009 to 2017, we introduced an indicator called coupling and coordination degree of CO2 and air pollutant emissions control (CCD) and found an upward and spatial agglomeration trend of CCD distribution during the research period. Then, this study posed a specific focus on the impact of China's Air Pollution Prevention and Control Action Plan (APPCAP). The DID model revealed that implementation of the APPCAP resulted in a 4.0% increase in CCD for cities with special emission limits, attributed to industrial structural adjustments and the promotion of technology innovation. Furthermore, we also identified positive spillover effects of the APPCAP on neighboring control group cities situated within 350 km of the treatment group cities, providing an explanation for the spatial agglomeration trend observed in CCD distribution. These findings hold significant implications for the synergetic control in China and underscored the potential benefits of industrial structural adjustments and technology innovation in mitigating environmental pollution.

Outdoor environmental exposome and the burden of tuberculosis: Findings from nearly two million adults in northwestern China

We simultaneously assessed the associations for a range of outdoor environmental exposures with prevalent tuberculosis (TB) cases in a population-based health program with 1940,622 participants ≥ 15 years of age. TB status was confirmed through bacteriological and clinical assessment. We measured 14 outdoor environmental exposures at residential addresses. An exposome-wide association study (ExWAS) approach was used to estimate cross-sectional associations between environmental exposures and prevalent TB, an adaptive elastic net model (AENET) was implemented to select important exposure(s), and the Extreme Gradient Boosting algorithm was subsequently applied to assess their relative importance. In ExWAS analysis, 12 exposures were significantly associated with prevalent TB. Eight of the exposures were selected as predictors by the AENET model: particulate matter ≤ 2.5 µm (odds ratio [OR]=1.01, p = 0.3295), nitrogen dioxide (OR=1.09, p < 0.0001), carbon monoxide (OR=1.19, p < 0.0001), and wind speed (OR=1.08, p < 0.0001) were positively associated with the odds of prevalent TB while sulfur dioxide (OR=0.95, p = 0.0017), altitude (OR=0.97, p < 0.0001), artificial light at night (OR=0.98, p = 0.0001), and proportion of forests, shrublands, and grasslands (OR=0.95, p < 0.0001) were negatively associated with the odds of prevalent TB. Air pollutants had higher relative importance than meteorological and geographical factors, and the outdoor environment collectively explained 11% of TB prevalence.

Residential green and blue spaces with nonalcoholic fatty liver disease incidence: Mediating effect of air pollutants

BACKGROUND

This study aimed to investigate the relationship of residential green and blue spaces with incident nonalcoholic fatty liver disease (NAFLD), and explore the potential mediation effects of air pollutants and modification effect of genetic susceptibility.

METHODS

411,200 UK Biobank participants without prior liver diseases were included. Land use data were used to estimate residential green and blue spaces (land coverage percentage) at 300 m and 1000 m buffer. The study outcome was incident NAFLD, ascertained through linkage to hospital admissions and death registry records.

RESULTS

5198 NAFLD cases were documented after a median follow-up of 12.5 years. Green and blue spaces were inversely associated with the hazard of NAFLD: per standard deviation (SD) increment of green space coverage at 300 m (SD: 14.5 %; HR, 0.88, 95 %CI, 0.86-0.91) and 1000 m (SD: 14.1 %; HR, 0.88, 95 %CI, 0.86-0.91) buffer, and blue space coverage at 300 m (SD: 1.0 %; HR,0.95, 95 %CI, 0.93-0.98) and 1000 m (SD: 1.2 %; HR,0.96, 95 %CI, 0.93-0.99) buffer were related with a 4-12 % reduction of NAFLD incidence. The beneficial effects of approximately 25-52 % of green space exposure and about 5-35 % of blue space exposure on NAFLD incidence were mediated by the reduction of PM2.5, NO2 and NOx (All Pindirect effect <0.05). Moreover, genetic susceptibility of NAFLD did not modify the relationship of green and blue spaces with NAFLD incidence.

CONCLUSION

Residential green and blue spaces were inversely related to NAFLD incidence. These results suggest that green and blue spaces are modifiable factors that may help prevent NAFLD, and therefore, can be considered as a novel environmental strategy to promote liver health at the community level, rather than only at the individual level.

Association of air pollutants and meteorological factors with tuberculosis: a national multicenter ecological study in China

The impact of weather variability and air pollutants on tuberculosis (TB) has been a research hotspot. Previous studies have mostly been limited to a certain area or with a small sample size of cases, and multi-scale systematic studies are lacking. In this study, 14,816,329 TB cases were collected from 31 provinces in China between 2004 and 2018 to estimate the association between TB risk and meteorological factors and air pollutants using a two-stage time-series analysis. The impact and lagged time of meteorological factors and air pollutants on TB risk varied greatly in different provinces and regions. Overall cumulative exposure-response summary associations across 31 provinces suggested that high monthly mean relative humidity (RH) (66.8-82.4%, percentile56-100 (P56-100)), rainfall (316.5-331.1 mm, P96-100), PM2.5 exposure concentration (93.3-145.0 μg/m3, P58-100), and low monthly mean wind speed (1.6-2.1 m/s, P0-38) increased the risk of TB incidence, with a relative risk (RR) of 1.10 (95% CI: 1.04-1.16), 1.10 (95% CI: 1.03-1.16), 2.08 (95% CI: 1.18-3.65), and 2.06 (95% CI: 1.27-3.33), and attributable risk percent (AR%) of 9%, 9%, 52%, and 51%, respectively. Conversely, high monthly average wind speed (2.3-2.9 m/s, P54-100) and mean temperature (20.2-25.3 °C, P79-96), and low monthly average rainfall (2.4-25.2 mm, P0-7) and concentration of SO2 (8.1-21.2 μg/m3, P0-16) exposure decreased the risk of TB incidence, with an overall cumulative RR of 0.92 (95% CI: 0.87-0.98), 0.74 (95% CI: 0.59-0.94), 0.87 (95% CI: 0.79-0.95), and 0.72 (95% CI: 0.56-0.93), respectively. Our study provided insights into future planning of public health interventions for TB.

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

Air pollution is a major public health problem that can lead to conjunctivitis. This study aimed to explore the associations between air pollutants and outpatient visits for conjunctivitis in Hangzhou, China. This study collected data on 50,772 patients with conjunctivitis and the concentrations of six air pollutants from February 1, 2014, to August 31, 2018. A time series analysis using a generalized additive model (GAM) was conducted. We found that the risk of conjunctivitis was related to the air pollutants PM2.5, PM10, SO2, NO2, and O3, which had concentration hysteresis effects. The risk of conjunctivitis increased by 1.009 (95% confidence interval (CI): 1.003, 1.014), 1.011 (95% CI: 1.008, 1.015), 1.238 (95% CI: 1.186, 1.292), 1.028 (95% CI: 1.019, 1.038), and 1.013 (95% CI: 1.008, 1.017) for every 10 µg/m3 increase in PM2.5, PM10, SO2, NO2, and O3 concentrations, respectively. The lag effects of SO2 and NO2 were stronger than those of particulate matter. Females exposed to PM10, PM2.5, SO2, and O3 had a higher risk of conjunctivitis than males, while males exposed to NO2 had a nearly identical risk of conjunctivitis as females. People aged 19-59 were more likely to suffer from conjunctivitis. The risk of conjunctivitis caused by PM10, SO2, and O3 was highest in the transitional season, while the risk caused by NO2 was highest in the winter season. In conclusion, females and middle-aged adults were at higher risk of conjunctivitis. People were more susceptible to conjunctivitis during the transitional season. These findings highlight the importance of atmospheric pollution governance and reference for public health measures.

Regional heterogeneity in short-term associations of meteorological factors, air pollution, and asthma hospitalizations in Guangxi, China

OBJECTIVES

This study aimed to identify and evaluate the short-term and lag effects of environmental factors on asthma hospitalizations in different regions.

STUDY DESIGN

The ecological study on asthma is performed in three regions of Guangxi, China, that are distinctly different in geography and climate.

METHODS

We used distributed lag non-linear models to investigate the exposure-response-lag relationship between meteorological factors, air pollutants, and asthma hospital admissions across the three regions during 2015 (January 1 to December 31).

RESULTS

Cold was an important meteorological factor affecting asthma. At lag 0, the relative risk (RR; 23°C as reference) of cold in the Northwest, Northeast, and South was 1.10 (10°C), 1.14 (8°C), and 1.30 (11°C), respectively. NO2 was identified as the most important air pollutant affecting asthma. The RR of asthma hospitalization increased by 10.9% (at lag 4), 8.1% (at lag 0), and 4.2% (at lag 2) for every 10 μg/m3 increase in NO2 concentration in the Northwest, Northeast, and South, respectively.

CONCLUSIONS

In the three regions of Guangxi, there were differences in the dominant factors affecting asthma hospitalizations. Differences in geography can inform governments as to how to prepare the healthcare system to meet the expected peaks.

The impact of ambient air pollutants on childhood respiratory system disease and the resulting disease burden: a time-series study

PURPOSE

The effects of air pollution on human health have long been a hot topic of research. For respiratory diseases, a large number of studies have proved that air pollution is one of the main causes. The purpose of this study was to investigate the risk of hospitalization of children with respiratory system diseases (CRSD) caused by six pollutants (PM2.5, PM10, NO2, SO2, CO, and O3) in Hefei City, and further calculate the disease burden.

METHOD

In the first stage, the generalized additive models were combined with the distributed lag non-linear models to evaluate the impact of air pollution on the inpatients for CRSD in Hefei. In the second stage, this study used the cost-of-illness approach to calculate the attributable number of hospitalizations and the extra disease burden.

RESULT

Overall, all the six kinds of pollutants had the strongest effects on CRSD inpatients within lag10 days. SO2 and CO caused the highest and lowest harm, respectively, and the RR values were SO2 (lag0-5): 1.1 20 (1.053, 1.191), and CO (lag0-6): 1.002 (1.001, 1.003). During the study period (January 1, 2014 to December 30, 2020), the 7-year cumulative burden of disease was 36.19 million CNY under the WHO air pollution standards.

CONCLUSION

In general, we found that six air pollutants were risk factors for CRSD in Hefei City, and create a huge burden of disease.