Fetal growth restriction (FGR) is not only a major determinant of perinatal morbidity and mortality but also leads to adverse health effects in later life. Over the past decade, numerous studies have indicated that maternal exposure to ambient air pollution has been a risk factor for abnormal fetal growth in developed countries where PM2.5 levels are relatively low. However, studies in highly polluted regions, such as China, and studies that rely on assessments in utero are scarce. A total of 7965 women were selected from 11,441 women from the Shanghai Maternity and Infant Living Environment (SMILE) cohort who were pregnant between January 1, 2014, and April 30, 2015. From January 1, 2014, to April 30, 2015, weekly average PM2.5 values from 53 monitors were calculated and the inverse distance weighted (IDW) method was used to create a Shanghai pollution surface map according to the participants residential addresses. Individual exposure was the average PM2.5 value of every gestational week between the first gestational week and one week before the ultrasound measurement date (the range of measurements per participant was 1 to 10). Repeated fetal ultrasound measurements during gestational weeks 14~40 were selected. The estimated fetal weight (EFW) was calculated by biparietal diameter (BPD), abdominal circumference (AC), and femur length (FL) formulas. In total, 29,926 ultrasound measurements were analysed. Demographic variables, other pollutants (SO2, NO2, PM10 and O3) and relative humidity and temperature were controlled for potential confounding through generalized estimating equations (GEE). The full model showed that with each 10 μg/m3 increase in PM2.5 exposure, the means (mm) of AC, BPD, FL decreased by 5.48 (− 9.06, − 1.91), 5.57 (− 6.66, − 4.47), and 5.47 (− 6.39, − 4.55), respectively; the mean EFW decreased by 14.49 (− 16.05, − 13.49) grams by Hadlock’s third formula and 13.56 (− 14.71, − 12.50) grams by Shepard’s formula with each 10 μg/m3 increase in PM2.5 exposure. A negative correlation existed between maternal PM2.5 exposure during pregnancy and fetal growth indicators, which may increase the risk of fetal growth restriction.

The outbreak of the COVID-19 Omicron variant in Shanghai in 2022 elicited complex emotions among Shanghainese during the two-month quarantine period. This paper aims to identify prevailing public themes and sentiments by analyzing social media posts from Weibo. Initially, we conducted research based on a dataset of 90,000 Weibo posts during the 2022 COVID-19 outbreak in Shanghai. By examining social media data that mirrors residents' emotional shifts and areas of focus during unforeseen circumstances, we have developed an analytical framework combining hotspot analysis and public sentiment assessment. Subsequently, we employed the Latent Dirichlet Allocation (LDA) method to conduct topic modeling on the Weibo text data. The SnowNLP sentiment classification method was then utilized to quantify sentiment values. Ultimately, we performed spatial visualization of sentiment and concern data, categorizing them into distinct time periods based on Shanghai's infection curve. This approach allowed us to investigate concern focal points, sentiment trends, and their spatiotemporal evolution characteristics. Our findings indicate that variations in public sentiment primarily hinge on the severity of the epidemic's spread, emerging events, the availability of essential resources, and the government's ability to respond promptly and accurately. It is evident that, while residents' concerns shift over time, their primary objective on social media remains expressing demands and releasing emotions. This research offers an avenue for leveraging public opinion analysis to enhance governance capacity during crises, fortify urban resilience, and promote public involvement in governmental decision-making processes.

Increasingly, Chinese cities are proposing city-scale ventilation corridors (VCs) to strengthen wind velocities and decrease pollution concentrations, although their influences are ambiguous. To assess VC impacts, an effort has been made to predict the impact of VC solutions in the high density and diverse land use of the coastal city of Shanghai, China, in this paper. One base scenario and three VC scenarios, with various VC widths, locations, and densities, were first created. Then, the combination of the Weather Research and Forecasting/Single-Layer Urban Canopy Model (WRFv.3.4/UCM) and Community Multiscale Air Quality (CMAQv.5.0.1) numerical simulation models were employed to comprehensively evaluate the impacts of urban spatial form and VC plans on PM2.5 concentrations. The modeling results indicated that concentrations increased within the VCs in both summer and winter, and the upwind concentration decreased in winter. These counter-intuitive results could be explained by decreased planetary boundary layer (PBL), roughness height, deposition rate, and wind speeds induced by land use and urban height modifications. PM2.5 deposition flux decreased by 15–20% in the VCs, which was attributed to the roughness height decrease for it weakens aerodynamic resistance (Ra). PBL heights within the VCs decreased 15–100 m, and the entire Shanghai’s PBL heights also decreased in general. The modeling results suggest that VCs may not be as functional as certain urban planners have presumed.