The spatial dynamics of heavy metal contamination in the upland soils of northern China are relatively unknown, despite the region's high contribution to the national grain output. In this study, the concentrations of As, Cd, Co, Cr, Cu, Mn, Pb, Sb, Sc, Ti, and Zn and subsequent ecological and human health risks were investigated in three major grain producing areas (Hexi Corridor, L1; Hetao irrigation area, L2; and eastern Inner Mongolia, L3) of northern China. Among the heavy metals, Ti had the highest average concentration of 3.02 g/kg, followed by Mn (470 mg/kg), Cr (56.6 mg/kg), Zn (34.3 mg/kg), Pb (19.4 mg/kg), Cu (17.8 mg/kg), Co (9.66 mg/kg), Sc (7.26 mg/kg), As (5.35 mg/kg), Sb (0.73 mg/kg), and Cd (0.17 mg/kg). Generally, the heavy metal concentrations decreased from west to east (L1 > L2 > L3) across northern China. Moreover, three potential sources of the heavy metal were distinguished, including natural process, anthropogenic activities (industrial development and agricultural cultivation), and atmospheric deposition. Although the contamination of the single metal (including Cd, Cr, Cu, and Pb) was moderate in L1 and L2, the combined contamination was low in the upland soils. It was noted that Cd posed a moderate to considerable ecological risk on the upland soils in northern China. This metal was the most sensitive factor in assessing the combined ecological risk, with a contribution rate of 91.56-94.84%. Considering the ingestion exposure, the current concentrations of the metals posed minimal risks to human health. Furthermore, children experienced higher health risks than adults. Present study analyzed the probabilistic distribution of contamination, ecological, and health risk of heavy metals in upland soils of northern China, providing fundamental information for better agricultural heavy metal pollution assessment in China.

Background: After the outbreak of novel coronavirus (2019-nCoV) starting in late 2019, a number of researchers have reported the predicted the virus transmission dynamics. However, under the strict control policy the novel coronavirus does not spread naturally outside Hubei Province, and none of the prediction closes to the real situation. Methods and findings: We used the traditional SEIR model, fully estimated the effect of control measures, to predict the virus transmission in Wuhan, the capital city of Hubei Province, and Beijing. We forecast that the outbreak of 2019-nCoV would reach its peak around March 6±10 in Wuhan and March 20±16 in Beijing, respectively. The infectious population in Beijing would be much less (only 0.3%) than those in Wuhan at the peak of this transmission wave. The number of confirmed cases in cities inside Hubei Province grow exponentially, whereas those in cities outside the province increase linearly. Conclusions: The unprecedented province lockdown substantially suspends the national and global outbreak of 2019-nCoV.

The novel coronavirus (2019-nCoV) appeared in Wuhan in late 2019 have infected 34,598 people, and killed 723 among them until 8 ^th February 2020. The new virus has spread to at least 316 cities (until 1 ^st February 2020) in China. We used the traffic flow data from Baidu Map, and number of air passengers who left Wuhan from 1 ^st January to 26 ^th January, to quantify the potential infectious people. We developed multiple linear models with local population and air passengers as predicted variables to explain the variance of confirmed cases in every city across China. We found the contribution of air passengers from Wuhan was decreasing gradually, but the effect of local population was increasing, indicating the trend of local transmission. However, the increase of local transmission is slow during the early stage of novel coronavirus, due to the super strict control measures carried out by government agents and communities.