Evaluating the feasibility of a personal particle exposure monitor in outdoor and indoor microenvironments in Shanghai, China.

Existing particulate matter (PM) monitors have too low spatiotemporal resolution to properly characterize individual exposure doses. In order to support health impact assessment, it is essential to develop a better method to assess individual exposure by taking account of varied environments in which people spend their time. Compact light-scattering PM monitors can potentially fill this need. This study was conducted to evaluate feasibility of a low-cost PM monitor (Plantower PMS 7003) in indoor and roadside outdoor microenvironments compared to research-grade instruments in Shanghai, China. The monitors exhibited excellent performance with a high linear response and low bias values both in outdoor and indoor tests. The monitors also showed little confounding bias in low relative humidity environments. Taking into account the accessibility and portability of this monitor, the monitors were able to detect the dynamic nature of individual exposures and provide data and knowledge about human exposure assessments.

Acute respiratory response to individual particle exposure (PM1.0, PM2.5 and PM10) in the elderly with and without chronic respiratory diseases.

Limited data were on the acute respiratory responses in the elderly in response to personal exposure of particulate matter (PM). In order to evaluate the changes of airway inflammation and pulmonary functions in the elderly in response to individual exposure of particles (PM1.0, PM2.5 and PM10), we analyzed 43 elderly subjects with either asthma, chronic obstructive pulmonary disease (COPD) or Asthma COPD Overlap (ACO) and 40 age-matched subjects without asthma nor COPD in an urban community in Shanghai, China. Data were collected at the baseline and in 6 follow-ups from August 2016 to December 2018, once every 3 months except for the last twice with a 6-month interval. In each follow-up, pulmonary functions, fractional exhaled nitric oxide (FeNO), 7-day continuous personal exposure to airborne particles were measured. Multivariate linear mixed effect regression models were applied to investigate the quantitative changes of pulmonary functions and FeNO in two respective groups. The results showed that on average 4.7 follow-up visits were completed in each participant. In subjects with CRDs, an inter-quartile range (IQR) increase of personal exposure to PM1.0, PM2.5 and PM10 was significantly associated with an average increase of FeNO(Lag1) of 6.7 ppb (95%CI 1.2, 9.9 ppb), 6.2 ppb (95%CI 1.5, 12.0 ppb) and 5.6 ppb (95%CI 1.5, 11.0 ppb), respectively, and an average decrease of FEV1(Lag2) of -3.6 L (95%CI -6.0, -1.1 L), -3.6 L (95%CI -6.4, -0.8 L) and -3.2 L (95%CI -5.8, -0.6 L), respectively, in the single-pollutant model. These associations remained consistent in the two-pollutant models adjusting for gaseous air pollutants. Stratified analysis showed that subjects with lower BMI, females and non-allergies were more sensitive to particle exposure. No robust significant effects were observed in the subjects without CRDs. Our study provided data on the susceptibility of the elderly with CRDs to particle exposure of PM1.0 and PM2.5, and the modification effects by BMI, gender and history of allergies.

The effects of PM2.5 on asthmatic and allergic diseases or symptoms in preschool children of six Chinese cities, based on China, Children, Homes and Health (CCHH) project.

The urbanization and industrialization in China is accompanied by bad air quality, and the prevalence of asthma in Chinese children has been increasing in recent years. To investigate the associations between ambient PM2.5 levels and asthmatic and allergic diseases or symptoms in preschool children in China, we assigned PM2.5 exposure data from the Global Burden of Disease (GBD) project to 205 kindergartens at a spatial resolution of 0.1° × 0.1° in six cities in China (Shanghai, Nanjing, Chongqing, Changsha, Urumqi, and Taiyuan). A hierarchical multiple logistical regression model was applied to analyze the associations between kindergarten-level PM2.5 exposure and individual-level outcomes of asthmatic and allergic symptoms. The individual-level variables, including gender, age, family history of asthma and allergic diseases, breastfeeding, parental smoking, indoor dampness, interior decoration pollution, household annual income, and city-level variable-annual temperature were adjusted. A total of 30,759 children (average age 4.6 years, 51.7% boys) were enrolled in this study. Apart from family history, indoor dampness, and decoration as predominant risk factors, we found that an increase of 10 µg/m3 of the annual PM2.5 was positively associated with the prevalence of allergic rhinitis by an odds ratio (OR) of 1.20 (95% confidence interval [CI] 1.11, 1.29) and diagnosed asthma by OR of 1.10 (95% CI 1.03, 1.18). Those who lived in non-urban (vs. urban) areas were exposed to more severe indoor air pollution arising from biomass combustion and had significantly higher ORs between PM2.5 and allergic rhinitis and current rhinitis. Our study suggested that long-term exposure to PM2.5 might increase the risks of asthmatic and allergic diseases or symptoms in preschool children in China. Compared to those living in urban areas, children living in suburban or rural areas had a higher risk of PM2.5 exposure.

Validation of a light-scattering PM2.5 sensor monitor based on the long-term gravimetric measurements in field tests.

BACKGROUND: Portable direct-reading instruments by light-scattering method are increasingly used in airborne fine particulate matter (PM2.5) monitoring. However, there are limited calibration studies on such instruments by applying the gravimetric method as reference method in field tests. METHODS: An 8-month sampling was performed and 96 pairs of PM2.5 data by both the gravimetric method and the simultaneous light-scattering real-time monitoring (QT-50) were obtained from July, 2015 to February, 2016 in Shanghai. Temperature and relative humidity (RH) were recorded. Mann-Whitney U nonparametric test and Spearman correlation were used to investigate the differences between the two measurements. Multiple linear regression (MLR) model was applied to set up the calibration model for the light-scattering device. RESULTS: The average PM2.5 concentration (median) was 48.1µg/m3 (min-max 10.4-95.8µg/m3) by the gravimetric method and 58.1µg/m3 (19.2-315.9µg/m3) by the light-scattering method, respectively. By time trend analyses, they were significantly correlated with each other (Spearman correlation coefficient 0.889, P<0.01). By MLR, the calibration model for the light-scattering instrument was Y(calibrated) = 57.45 + 0.47 × X(the QT - 50 measurements) - 0.53 × RH - 0.41 × Temp with both RH and temperature adjusted. The 10-fold cross-validation R2 and the root mean squared error of the calibration model were 0.79 and 11.43 µg/m3, respectively. CONCLUSION: Light-scattering measurements of PM2.5 by QT-50 instrument overestimated the concentration levels and were affected by temperature and RH. The calibration model for QT-50 instrument was firstly set up against the gravimetric method with temperature and RH adjusted.