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The reaction of carbonyl-to-imine/hemiaminal conversion in the atmospheric aqueous phase is a critical pathway to produce the light-absorbing N-containing secondary organic compounds (SOC). The formation mechanism of these compounds has been wildly investigated in bulk solutions with a low ionic strength. However, the ionic strength in the aqueous phase of the polluted atmosphere may be higher. It is still unclear whether and to what extent the inorganic ions can affect the SOC formation. Here we prepared the bulk solution with certain ionic strength, in which glyoxal and ammonium were mixed to mimic the aqueous-phase reaction. Molecular characterization by High-resolution Mass Spectrometry was performed to identify the N-containing products, and the light absorption of the mixtures was measured by ultraviolet-visible spectroscopy. Thirty-nine N-containing compounds were identified and divided into four categories (N-heterocyclic chromophores, high-molecular-weight compounds with N-heterocycle, aliphatic imines/hemiaminals, and the unclassified). It was observed that the longer reaction time and higher ionic strength led to the formation of more N-heterocyclic chromophores and the increasing of the light-absorbance of the mixture. The added inorganic ions were proposed to make the aqueous phase somewhat viscous so that the molecules were prone to undergo consecutive and intramolecular reactions to form the heterocycles. In general, this study revealed that the enhanced ionic strength and prolonged reaction time had the promotion effect on the light-absorbing SOC formation. It implies that the aldehyde-derived aqueous-phase SOC would contribute more light-absorbing particulate matter in the industrial or populated area where inorganic ions are abundant., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Copyright © 2023. Published by Elsevier B.V.)

Objective: The aim of this study was to perform an exposure assessment of PM2.5 (particulate matter less than 2.5μm in aerodynamic diameter) among children and to explore the potential sources of exposure from both indoor and outdoor environments., Methods: In terms of real-time exposure measurements of PM2.5, we collected data from 57 children aged 8-12 years (9.64 ± 0.93 years) in two schools in Shanghai, China. Simultaneously, questionnaire surveys and time-activity diaries were used to estimate the environment at home and daily time-activity patterns in order to estimate the exposure dose of PM2.5 in these children. Principle component regression analysis was used to explore the influence of potential sources of PM2.5 exposure., Results: All the median personal exposure and microenvironment PM2.5 concentrations greatly exceeded the daily 24-h PM2.5 Ambient Air Quality Standards of China, the USA, and the World Health Organization (WHO). The median Etotal (the sum of the PM2.5 exposure levels in different microenvironment and fractional time) of all students was 3014.13 (μg.h)/m3. The concentration of time-weighted average (TWA) exposure of all students was 137.01 μg/m3. The median TWA exposure level during the on-campus period (135.81 μg/m3) was significantly higher than the off-campus period (115.50 μg/m3, P = 0.013 < 0.05). Besides ambient air pollution and meteorological conditions, storey height of the classroom and mode of transportation to school were significantly correlated with children's daily PM2.5 exposure., Conclusions: Children in the two selected schools were exposed to high concentrations of PM2.5 in winter of 2013 in Shanghai. Their personal PM2.5 exposure was mainly associated with ambient air conditions, storey height of the classroom, and children's transportation mode to school.

Objective: The aim of this study was to perform an exposure assessment of PM2.5 (particulate matter less than 2.5μm in aerodynamic diameter) among children and to explore the potential sources of exposure from both indoor and outdoor environments. Methods: In terms of real-time exposure measurements of PM2.5, we collected data from 57 children aged 8–12 years (9.64 ± 0.93 years) in two schools in Shanghai, China. Simultaneously, questionnaire surveys and time-activity diaries were used to estimate the environment at home and daily time-activity patterns in order to estimate the exposure dose of PM2.5 in these children. Principle component regression analysis was used to explore the influence of potential sources of PM2.5 exposure. Results: All the median personal exposure and microenvironment PM2.5 concentrations greatly exceeded the daily 24-h PM2.5 Ambient Air Quality Standards of China, the USA, and the World Health Organization (WHO). The median Etotal (the sum of the PM2.5 exposure levels in different microenvironment and fractional time) of all students was 3014.13 (μg.h)/m3. The concentration of time-weighted average (TWA) exposure of all students was 137.01 μg/m3. The median TWA exposure level during the on-campus period (135.81 μg/m3) was significantly higher than the off-campus period (115.50 μg/m3, P = 0.013 < 0.05). Besides ambient air pollution and meteorological conditions, storey height of the classroom and mode of transportation to school were significantly correlated with children’s daily PM2.5 exposure. Conclusions: Children in the two selected schools were exposed to high concentrations of PM2.5 in winter of 2013 in Shanghai. Their personal PM2.5 exposure was mainly associated with ambient air conditions, storey height of the classroom, and children’s transportation mode to school. [ABSTRACT FROM AUTHOR]

Although exposure to ambient air pollution has been associated with outpatient visits for respiratory diseases, there have been few recent studies investigating the effect of the chemical components of ambient particulate matter with an aerodynamic diameter of <2.5 μm (PM 2.5) on pediatric outpatient visits for respiratory diseases. In addition, there remains scarce evidence regarding PM 2.5 components and sources that are most relevant to pediatric outpatient visits for respiratory diseases. This study aimed to determine the association between four ambient pollutants (SO 2 , NO 2 , PM 10 , and PM 2.5), sources and chemical components of PM 2.5 , and pediatric outpatient visits for respiratory diseases. This time-series study was conducted between January 1, 2018 and December 31, 2019 in Shanghai, China. A positive matrix factorization model was used to determine the source apportionment of PM 2.5 , and a generalized additive model was employed to evaluate the effect of air pollutants and the components and sources of PM 2.5 on pediatric outpatient visits for respiratory diseases. In addition, a two-pollutant model was used to investigate the potential confounding effects of the copollutants. The study revealed that a 10 μg/m3 increase in SO 2 , NO 2 , PM 10 , and PM 2.5 concentrations corresponded to increases of 3.4% (95% CI: 2.3%–4.6%), 1.9% (95% CI: 1.7%–2.2%), 0.5% (95% CI: 0.4%–0.7%), and 0.5% (95% CI: 0.4%–0.7%), respectively, in pediatric outpatient visits for respiratory diseases on the day with the most significant lag effect. Notably, Ni exposure more strongly correlated with increased pediatric outpatient visits for respiratory diseases, with the percent of increase by 10 ng/m3 ranging from 7.6% to 16.5%. Moreover, among the PM 2.5 sources researched in this study, oil and coal combustion were the most important for increasing pediatric outpatient visits for respiratory diseases. This study demonstrates that ambient pollutants and the chemical components and sources of PM 2.5 were significantly associated with an elevated risk of pediatric outpatient visits for respiratory diseases and provides insights into the differential health risks of PM 2.5 components. The Effect of Sources and Components of PM 2.5 on Pediatric Outpatient Visits for Respiratory Diseases. [Display omitted] • A PMF model was used to study the effect of PM 2.5 sources on pediatric outpatient visits for respiratory diseases (POVRD). • PM 2.5 chemical components were associated with POVRD, especially Ni exposure. • Oil combustion is potentially responsible for increased POVRD risks. [ABSTRACT FROM AUTHOR]

The Air Quality Health Index (AQHI) based on the association between excess mortality risk and air pollutants was established by Canadian scientists in 2008 and it has been widely used for predicting multiple air pollutants related health risks. However, it remains unclear whether AQHI is a better indicator in predicting other health risks like respiratory diseases for vulnerable populations. This study aimed to propose a case on constructing an AQHI based on the association between air pollution and hospital outpatient visits for respiratory diseases among children and to determine whether the index adequately predicts early risk of respiratory diseases in children. Data of air pollutants, including particulate matter of less than 2.5 μm in aerodynamic diameter (PM 2.5), sulfur dioxide (SO 2), nitrogen dioxide (NO 2), and ozone (O 3) were collected from Shanghai Environmental Monitoring Center from January 1, 2015 to December 31, 2019. Daily number of hospital outpatient visits for pediatric (0–12 years old) respiratory diseases were also obtained. Time-series analysis with a generalized additive model (GAM) during warm (Apr. to Sep.) and cool periods (Oct. to Mar.) was conducted to estimate the associations between respiratory-related hospital outpatient visits in children and the concentrations of air pollutants including PM 2.5 , SO 2 , NO 2 , and O 3 in Shanghai from 2015 to 2018. The sum of excess risk (ER) of hospital outpatient visits in warm and cool periods was used to construct the AQHI for children (AQHI c). As AQHI c was established using the data from 2015 to 2018, we examined the validity of the index with data from 2017 to 2019. We also compared the predictive power of AQHI c and the currently used Air Quality Index (AQI) with the data of daily hospital outpatient visits from 2017 to 2019. According to one- and two-pollutant models of GAM, the concentration-response coefficients of PM 2.5 , SO 2 , NO 2, and O 3 were selected to construct the AQHI c in the warm period, while only SO 2 , NO 2, and PM 2.5 were included for the construction of AQHI c in the cool period as O 3 was negatively correlated with the hospital outpatient visits. There were almost linear exposure-response correlations between AQHI c and daily hospital outpatient visits. AQHI c and AQI showed similar results with the annual data in terms of model fit statistics. When the data was divided into warm and cool periods, the power of AQHI c was slightly stronger than that of AQI in predicting the air pollution-related health risks. AQHI c we developed might comprehensively reflect the combined effects of air pollution in Shanghai and it could be a more valid prediction index for evaluating air pollution-related health risks in children. [Display omitted] • To explore concentration-response associations during warm and cool periods between air pollution and hospital outpatient visits. • To construct an index (AQHI c) basing on the sum of excess risk (ER) of hospital outpatient visits in warm and cool periods. • To compare the power of AQHI c and AQI in predicting air pollution-related health risks. [ABSTRACT FROM AUTHOR]