Objective At the end of 2019, the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan was a serious threat to public health. This study aimed to evaluate the risk perception of COVID-19 among college students in China during the quarantine, explore its related factors, and provide reference for future study. Methods This study invited college students from various provinces of China to participate in the survey through the Internet, and a total of 1,461 college students were included. T-test and analysis of variance were used to explore the relationship between demographic characteristics, social pressure, knowledge and risk perception. Multiple linear regression was used to identify factors associated with risk perception. Results This study shows that college students in China have high risk perception of COVID-19. Female college students (p<0.01), non-medical students (p<0.01), college students whose schools are located in Hubei (p = 0.01) and college students with higher knowledge level (p<0.01) have higher risk perception. Conclusion Due to the strong infectivity and occult nature of COVID-19, it is necessary to improve the risk perception of college students through health education in various ways, and attention should be paid to some college students with low risk perception.

Photosynthetically active radiation (PAR) and other solar components were observed for a period of 3 years at Wuhan, China to determine for the first time the temporal variability of PAR fraction [PAR/G (G here stands for global solar radiation)] and its dependence on different sky conditions in Central China. PAR, G and PAR/G showed similar seasonal features that peaked in summer and reached their lowest values in winter. The seasonal PAR/G ranged from 1.70 E MJ(-1) (winter) to 2.01 E MJ(-1) (summer) with an annual mean value of 1.89 E MJ(-1). Hourly values of PAR/G increased from 1.78 to 2.11 E MJ(-1) on average as sky conditions changed from clear to cloudy. Monthly mean hourly PAR/G revealed a diurnal variation, with highest values observed around sunrise and sunset, slightly higher PAR fractions were also found around noon for most months. The effect of daylength on PAR/G was also studied and no significant impact was found. Three models were developed to estimate PAR from G. These models consisted of atmospheric parameters that were found to cause substantial changes of PAR/G, such as sky clearness, brightness, path length and the sky clearness index. The estimations obtained from different models were very close to the measured values with maximum relative errors below 8 % (hourly values) in Wuhan. The models were not only tested at seven radiation stations in Central China, but also verified in six stations with different climates in China. The models were found to estimate PAR accurately from commonly available G data in Central China; however, the results also implied that the models need to be modified to account for local climatic conditions when applied to the whole country.

, an outbreak of coronavirus disease 2019 (COVID-19) has occurred in Wuhan, China, and it has become a global pandemic currently. At the early stage, the Chinese government had adopted strict quarantine and hygiene measures, including disease detection and social distancing. Preventive behaviors, such as mask-wearing and hand-washing, had shown its importance in the control of the SARS (severe acute respiratory syndrome) and COVID-19 epidemic. 1-3 Previous studies suggest that individual's health behavior against disease was influenced by knowledge, 4 attitude, 5 and demographic factors. 6 This study investigated Chinese college students' health behavior toward COVID-19 during the quarantine period and identified its influencing factors. A cross-sectional questionnaire survey was conducted among Chinese college students between February 4, 2020, and February 21, 2020. The questionnaire consisted of 4 sections: (1) Demographic characteristics: gender, age, education level, major, residence, infection situation, contact situation, and parents' health condition. (2) Knowledge: included the general nature of virus, infection symptoms, and preventive measures (see Supplemental Table S1, available online). (3) Attitude: included perceived potential risk of infection and confidence on the final control of COVID-19 (see Supplemental Table S2, available online). (4) Health behavior: included hand-washing, mask-wearing, and social distancing. A 5-point Likert-type scale was used ranging from never to always. This study was approved by the Institution Review Board of Wuhan University (Approval Number: 2020YF0026). Informed consent was obtained from all participants. Among 1599 participants, 290 (18.14%) were living in Hubei Province, 902 (56.41%) were female, and 766 (47.90%) majored in medicine (Table 1). The mean knowledge score among participants was 8.63 (SD = 1.32, range = 0-10), and the mean attitude score was 22.51 (SD = 2.59, range = 6-30). Most college students reported a good health behavior in mask-wearing (94.06%), handwashing (91.13%), and social distancing (89.49%) during the epidemic. Results of binary logistic regression analysis on the influencing factors of health behavior are presented in Table 2. Gender, knowledge, and attitude toward COVID-19 were significantly associated with hand-washing. The odds ratio of female students was 1.93 times higher compared with

With the outbreak of COVID-19 in Wuhan, aggressive countermeasures have been taken, including the implementation of the unprecedented lockdown of the city, which will necessarily cause huge economic losses for the city of Wuhan. In this paper, we attempt to uncover the interactions between epidemic prevention and control measures and economic-social development by estimating the health loss and meso-economic loss from a human-oriented perspective. We implemented a compartmental model for the transmission dynamics and health burden assessment to evaluate the health losses, then estimated the direct and indirect economic losses of industries using the Input-Output model. Based on these estimates, the first monthly health losses and meso-economic losses caused by the lockdown was assessed. The overall policy effect of the lockdown policy in Wuhan was also investigated. The health loss and meso-economic losses are used to evaluate the health burden and loss of residents’ mental health, the direct economic loss of several worst-hit industries, and the indirect economic loss of all industries, respectively. Our findings reveal that the health burden caused by this pandemic is estimated to be 4.4899 billion yuan (CNY), and the loss of residents’ mental health is evaluated to be 114.545 billion yuan, the direct economic losses in transport, logistics, and warehousing, postal service, food, and beverage service industries reach 21.6094 billion yuan, and the monthly indirect economic losses of all industries are 36.39661994 billion yuan caused by the lockdown. The total monthly economic losses during the lockdown reach 177.0413 billion yuan. However, the lockdown policy has been considered to reduce COVID-19 infections by >180 thousand, which saves about 20 thousand lives, as well as nearly 30 billion yuan on medical costs. Therefore, the lockdown policy in Wuhan has obvious long-term benefits on the society and the total economic losses will be at a controllable level if effective measures are taken to combat COVID-19.

A severe haze episode that occurred in Wuhan, central China, from 6-14 June 2012 was investigated using ground-based and satellite-derived observations, from which the optical properties and vertical distribution of the aerosols were obtained. The mass concentrations of PM 2.5 and black carbon (BC) were 9.9 (332.79 versus 33.66 μg·m ). Particle size became larger, consistent with the reduced scattering Ångström exponent. The high asymmetry parameter (0.65) and single scattering albedo (SSA) (0.97) observed in the haze, which coincided with the relatively low backscatter ratio (0.11) and up-scatter fraction (0.23), were related to the increased particle size, and could have had a heating effect on the atmosphere. Aerosols accumulated primarily below 3 km and according to CALIPSO, were regular in their shapes. At the surface, the aerosol extinction coefficient detected by satellite remained at ~1 km , very close to the ground-based observations. Aerosol optical properties measured at this downtown site could help further the understanding of the effects of aerosols on the air quality, city environment, and radiation balance. OPEN ACCESSAtmosphere 2014, 5 700

No abstract

IntroductionThe water-level fluctuation in the Three Gorges Reservoir Region has changed dramatically as a result of the hydroelectric project for flood control and power generation. The riparian seasonal hydrological environment also has changed from summer flooding with winter drought to summer drought with winter flooding. The changes of riparian seed bank and vegetation were investigated to determine the effects of the seasonal flooding on the composition and spatial distribution of riparian soil seed bank and the similarity of seed bank to standing vegetation.Case descriptionWe conducted intensive riparian soil sampling (525 samples) along altitude gradient in the Shanmu River, a tributary of the Yangzi River in the reservoir region of China. Seed bank density, species richness and composition of soil seed bank were examined using the seedling-emergence method. The seasonal hydrological conditions resulted in a decrease in species diversity and an increase in the distribution heterogeneity of the soil seed bank. The soil seed bank was composed of 48 species from 22 families and 40 genera. Most species were annual and perennial herbaceous Polygonaceae, Asteraceae, and Poaceae. Rumex dentatus was the predominant species accounting for 27.0 % of the total seeds. Diversity and composition of the seed bank changed along an altitude gradient and soil depth. Maximum species richness was found in the top soil layer at 165 m and 175 m above sea level. The mean overall seed density of the soil seed bank was 13,475.3 ind m−2. Density and the number of seeds increased initially and then decreased with increased altitude. Maximum seed density (22,500.2 ind m−2) was found at 165 m above sea level in the intermediately flooded riverbank, with the seed number accounting for 27.8 % of the total soil seed bank. Average seed density declined significantly with soil depth. The similarity of seed bank to standing vegetation was relatively high.Discussion and EvaluationThe environmental heterogeneity created by the wide range and seasonal flooding led to the changes in biodiversity and seed density along altitude gradient. The seasonal flooding also led to the increase in the similarity of seed bank to standing vegetation as their composition both degraded.ConclusionsThe seasonal flooding due to the dam reshape the composition and spatial distribution of riparian soil seed bank and limit the vegetation to a grassland dominated by a few annuals and perennials in the Three Gorges Reservoir Region.

Net primary productivity (NPP) is an important component of the carbon cycle and a key indicator of ecosystem performance. The aim of this study is to construct a more accurate regional vegetation NPP estimation model and explore the relationship between NPP and climatic factors (air temperature, rainfall, sunshine hours, relative humidity, air pressure, global radiation, and surface net radiation). As a key variable in NPP modeling, photosynthetically active radiation (PAR) was obtained by finding a linear relationship between PAR and horizontal direct radiation, scattered radiation, and net radiation with high accuracy. The fraction of absorbed photosynthetically active radiation (FPAR) was estimated by enhanced vegetation index (EVI) instead of the widely used normalized difference vegetation index (NDVI). Stress factors of temperature/humidity for different types of vegetation were also considered in the simulation of light use efficiencies (LUE). The authors used EVI datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2011 and geographic information techniques to reveal NPP variations in Wuhan. Time lagged serial correlation analysis was employed to study the delayed and continuous effects of climatic factors on NPP. The results showed that the authors’ improved model can simulate vegetation NPP in Wuhan effectively, and it may be adopted or used in other regions of the world that need to be further tested. The results indicated that air temperature and air pressure contributed significantly to the interannual changes of plant NPP while rainfall and global radiation were major climatic factors influencing seasonal NPP variations. A significant positive 32-day lagged correlation was observed between seasonal variation of NPP and rainfall (P &lt; 0.01); the influence of changing climate on NPP lasted for 64 days. The impact of air pressure, global radiation, and net radiation on NPP persisted for 48 days, while the effects of sunshine hours and air temperature on NPP only lasted for 16 and 32 days, respectively.