Air pollution and its associated health risks before and after COVID-19 in Shaanxi Province, China.

Air pollution is a serious environmental problem that damages public health. In the present study, we used the segmentation function to improve the health risk-based air quality index (HAQI) and named it new HAQI (NHAQI). To investigate the spatiotemporal distribution characteristics of air pollutants and the associated health risks in Shaanxi Province before (Period I, 2015-2019) and after (Period II, 2020-2021) COVID-19. The six criteria pollutants were analyzed between January 1, 2015, and December 31, 2021, using the air quality index (AQI), aggregate AQI (AAQI), and NHAQI. The results showed that compared with AAQI and NHAQI, AQI underestimated the combined effects of multiple pollutants. The average concentrations of the six criteria pollutants were lower in Period II than in Period I due to reductions in anthropogenic emissions, with the concentrations of PM2.5 (particulate matter ≤2.5 µm diameter), PM10 (PM ≤ 10 µm diameter) SO2, NO2, O3, and CO decreased by 23.5%, 22.5%, 45.7%, 17.6%, 2.9%, and 41.6%, respectively. In Period II, the excess risk and the number of air pollution-related deaths decreased considerably by 46.5% and 49%, respectively. The cumulative population distribution estimated using the NHAQI revealed that 61% of the total number of individuals in Shaanxi Province were exposed to unhealthy air during Period I, whereas this proportion decreased to 16% during Period II. Although overall air quality exhibited substantial improvements, the associated health risks in winter remained high.

Lag Effect of Temperature and Humidity on COVID-19 Cases in 11 Chinese Cities

The global transmission of COVID-19 has caused considerable health burdens, and epidemiological studies have proven that temperature and humidity play an important role in the transmission of infectious respiratory diseases. This effect may not be immediate and can be delayed by days to weeks. In this study, the comprehensive effect of temperature and humidity on COVID-19 was evaluated using the discomfort index (DI). We analyzed the lag effect of the DI on COVID-19 from 21 January to 29 February 2020 in 11 Chinese cities by designing a generalized additive model (GAM). We classified the 11 Chinese cities into southern cities and northern cities to compare the potential effects in these two types of cities. The results reveal that the DI had the same negative correlation and different lag effects on daily COVID-19 cases. There was a significant negative correlation between the DI and daily COVID-19 cases (p < 0.05), except in Wuhan. The lag effect was stronger in the cities located further north. In northern cities, each unit decrease in the DI increased the COVID-19 risk from 7 to 13 lag days. In southern China, each unit decrease in the DI increased the COVID-19 risk from 0 to 7 lag days, especially in Shanghai, Guangzhou, and Shenzhen.

Design and Analysis of Hospital Throughput Maximization Algorithm under COVID-19 Pandemic.

Under the global pandemic of COVID-19, public health facilities, such as hospitals, are required to readjust, design, and plan a safe movement flow of people to meet the social distance rules and quarantine COVID-19 and the non-COVID-19 patients to prevent cross-infection. However, readjustments to separate patients have significantly reduced the maximum throughput of public health facilities, worsening already scarce public health resources. Therefore, this paper proposes throughput maximization algorithms based on the one-way street problem which meets the requirements of social distance rules. First, the floor plan of a hospital is transformed into a graph, each node is traversed by breadth-first search. Then, this paper considers patients' node pair sets as different set unions, the direction of edges, and the color of links based on DFS-XOR algorithm are designed to distinguish the paths of COVID-19 and non-COVID-19 patients. Finally, this paper utilizes minimum shared link algorithms to determine the minimized sharing links between paths linking different set unions and components. The throughput is maximized by reducing the number of shared links and alternating links. The results indicate that compared with the brute force algorithms, the algorithms proposed in this paper significantly improve the maximum throughput.

Association between environmental factors and COVID-19 in Shanghai, China.

The outbreak of coronavirus disease 2019 (COVID-19) continues to spread worldwide and has led to recession, rising unemployment, and the collapse of the health-care system. The aim of this study was to explore the exposure-response relationship between daily confirmed COVID-19 cases and environmental factors. We used a time-series generalized additive model (GAM) to investigate the short-term association between COVID-19 and environmental factors by using daily meteorological elements, air pollutant concentration, and daily confirmed COVID-19 cases from January 21, 2020, to February 29, 2020, in Shanghai, China. We observed significant negative associations between daily confirmed COVID-19 cases and mean temperature (Tave), temperature humidity index (THI), and index of wind effect (K), whereas air quality index (AQI), PM2.5, PM10 NO2, and SO2 were significantly associated with the increase in daily confirmed COVID-19 cases. A 1 °C increase in Tave, one-unit increase in THI, and 10-unit increase in K (lag 0-7 days) were associated with 4.7, 1.8, and 1.6% decrease in daily confirmed cases, respectively. Daily Tave, THI, K, PM10, and SO2 had significant lag and persistence (lag 0-7 days), whereas the lag and persistence of AQI, PM2.5, and NO2 were significant at both lag 0-7 and 0-14 days. A 10-µg/m3 increase in PM10 and 1-µg/m3 increase in SO2 was associated with 13.9 and 5.7% increase in daily confirmed cases at lag 0-7 days, respectively, whereas a 10-unit increase in AQI and a 10-µg/m3 increase in PM2.5 and NO2 were associated with 7.9, 7.8, and 10.1% increase in daily confirmed cases at lag 0-14 days, respectively. Our findings have important implications for public health in the city of Shanghai.

Application of polyamide 6 microfiber non-woven fabrics in the large-scale production of all-solid-state lithium metal batteries.

All-solid-state electrolytes have received extensive attention due to their excellent safety and good electrochemical performance. However, due to the harsh conditions of the preparation process, the commercial production of all-solid-state electrolytes remains a challenge. The outbreak of the novel coronavirus pneumonia (COVID-19) has caused great inconvenience to people, while also allowing soft, lightweight and mass-producible non-woven fabrics in masks come into sight. Here, a polymer/polymer solid composite electrolyte is obtained by introducing the polyamide 6 (PA6) microfiber non-woven fabric into PEO polymer through the hot-pressing method. The addition of the PA6 non-woven fabric with lithium-philic properties can not only reduce the crystallinity of the polymer, but also provide more functional transmission sites and then promote the migration of lithium ions at the molecular level. Moreover, due to the sufficient mechanical strength and flexibility of the PA6 non-woven fabric, the composite electrolyte shows excellent inhibition ability of lithium dendrite growth and high electrochemical stability. The novel design concept of introducing low-cost and large-scale production of non-woven fabrics into all-solid-state composite electrolytes to develop high-performance lithium metal batteries is attractive, and can also be broadened to the combination of different types of polymers to meet the needs of various batteries.