PM2.5-Related Health Risk during Chinese Spring Festival in Taizhou, Zhejiang: The Health Impacts of COVID-19 Lockdown

Exposure to high concentrations of fine particles (PM2.5) with toxic metals can have significant health effects, especially during the Chinese spring festival (CSF), due to the large amount of fireworks' emissions. Few studies have focused on the potential health impact of PM2.5 pollution in small cities in China during the 2020 CSF, which coincided with the COVID-19 outbreak that posed a huge challenge to the environment and obvious health issues to countries around the world. We examined the characteristics of PM2.5, including carbonaceous matter and elements, for three intervals during the 2020 CSF in Taizhou, identified the sources and evaluated the health risks, and compared them with those of 2018. The results showed that PM2.5 increased by 13.20% during the 2020 CSF compared to those in the 2018 CSF, while carbonaceous matter (CM) and elements decreased by 39.41% and 53.84%, respectively. The synergistic effects of emissions, chemistry, and transport may lead to increased PM2.5 pollution, while the lockdown measures contributed to the decrease in CM and elements during the 2020 CSF. Fe, Mn, and Cu were the most abundant elements in PM2.5 in both years, and As and Cr(VI) should be of concern as their concentrations in both years exceeded the NAAQS guideline values. Industry, combustion, and mineral/road dust sources were identified by PCA in both years, with a 5.87% reduction in the contribution from industry in 2020 compared to 2018. The noncarcinogenic risk posed by As, Co, Mn, and Ti in 2018 and As and Mn in 2020 was significant. The carcinogenic risk posed by As, Cr(VI), and Pb exceeded the accepted precautionary limit (1 ×10-6) in both years. Mn was the dominant contributor to the total noncarcinogenic risks, while Cr(VI) showed the largest excessive cancer risks posed by metals in PM2.5, implying its associated source, industry, was the greatest risk to people in Taizhou after exposure to PM2.5. Despite the increase in PM2.5 mass concentration, the health impacts were reduced by the lockdown policy implemented in Taizhou during the 2020 CSF compared to 2018. Our study highlights the urgent need to consider the mitigation of emissions in Taizhou and regional joint management efforts based on health protection objectives despite the rough source apportionment by PCA.

Dynamic Mapping of Paddy Rice Using Multi-Temporal Landsat Data Based on a Deep Semantic Segmentation Model

Timely, accurate, and repeatable crop mapping is vital for food security. Rice is one of the important food crops. Efficient and timely rice mapping would provide critical support for rice yield and production prediction as well as food security. The development of remote sensing (RS) satellite monitoring technology provides an opportunity for agricultural modernization applications and has become an important method to extract rice. This paper evaluated how a semantic segmentation model U-net that used time series Landsat images and Cropland Data Layer (CDL) performed when applied to extractions of paddy rice in Arkansas. Classifiers were trained based on time series images from 2017–2019, then were transferred to corresponding images in 2020 to obtain resultant maps. The extraction outputs were compared to those produced by Random Forest (RF). The results showed that U-net outperformed RF in most scenarios. The best scenario was when the time resolution of the data composite was fourteen day. The band combination including red band, near-infrared band, and Swir-1 band showed notably better performance than the six widely used bands for extracting rice. This study found a relatively high overall accuracy of 0.92 for extracting rice with training samples including five years from 2015 to 2019. Finally, we generated dynamic maps of rice in 2020. Rice could be identified in the heading stage (two months before maturing) with an overall accuracy of 0.86 on July 23. Accuracy gradually increased with the date of the mapping date. On September 17, overall accuracy was 0.92. There was a significant linear relationship (slope = 0.9, r2 = 0.75) between the mapped areas on July 23 and those from the statistical reports. Dynamic mapping is not only essential to assist farms and governments for growth monitoring and production assessment in the growing season, but also to support mitigation and disaster response strategies in the different growth stages of rice.

Surveillance on soil-transmitted nematode infections in population in Guangxi Zhuang Autonomous Region during 2016-2020

Objective: To understand and analyze the epidemic status and development trends of soil-transmitted nematodiasis in Guangxi Zhuang Autonomous Region (Guangxi), to provide scientific basis for formulating the disease control strategy, and evaluating the control effect.

Clinical characteristics and risk factors for mortality in patients with COVID-19 and chronic obstructive pulmonary disease in Wuhan, China (preprint)

Patients with COVID-19 and COPD are at high risks. However, the risk factors for mortality in COPD patients infected COVID-19 are limited. In this retrospective study, consecutive COPD cases infected COVID-19 in East District of People's Hospital of Wuhan University from Jan 11th 2020 to Mar 28th 2020 were included. Different outcomes were compared between dead and discharged patients. Cox regression analysis was performed to explore the risk factors for death. Totally, 52 cases were included (aged 64.0-79.0 years, 39 [75.0%] males). Common symptoms on admission were cough (43, 82.6%), fever (41, 78.8%) and expectoration (21, 40.3%). Thirty-eight (73.1%) patients were discharged, and 14 (26.9%) cases were dead which mainly caused by multiple organ failure (7, 50.0%) and respiratory failure (6, 42.9%). Multivariate analysis indicated that age > 70 years (HR, 7.859, 95% CI: 1.376, 44.875; P = 0.020) and count of lymphocyte ≤ 0.8×109/L (HR, 27.429, 95% CI: 3.336, 225.530; P = 0.002) were risk factors for death. The study showed that close monitoring of the risk indexes is important for early supportive care during the management of patients with COVID-19 and COPD.

The Cardiac Injury in Hospitalized Patients with Severe COVID-19 in Wuhan, China (preprint)

Background: The Coronavirus disease 2019 (COVID-19) has caused a global pandemic since December 2019, while the date on the relationship between cardiac injury and mortality in patients with COVID-19 is limited.Methods: All consecutive lab-confirmed critically ill COVID-19 patients in intensive care unit of Wuhan Red Cross Hospital from December 30, 2019 to March 18, 2020, were enrolled. Data of patients were collected. The prevalence of cardiac injury and its association with in-hospital mortality was analyzed.Results: Among the 50 ICU patients, 36 patients (72.0%) were complicated with cardiac injury and 14 patients (28.0%) without cardiac injury. Patients with cardiac injury had higher white blood cell counts, values of d-dimer, levels of lactate concentration, APACHE II score and lower PaO2/FiO2 at the time of admission than those without cardiac injury. The in-hospital case fatality ratio was higher in the cardiac injury than non-cardiac injury group (75.0% vs 21.4%;p=0.002).Multivariable-adjusted logistic proportional hazard regression analysis showed that a significantly higher risk of death in patients with cardiac injury than those without cardiac injury (OR, 5.876; 95% CI, 1.039–33.228).Conclusions: Cardiac injury is a common compilation and associated with higher risk of in-hospital death in patients with severe COVID-19.