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Air pollutants seriously impact climate change and human health. In this study, the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation system was extended from ground data to vertical profile data, which reduced the simulation error of the model in the vertical layer. The coupled GSI-Lidar-WRF-Chem system was used to improve the accuracy of fine particulate matter (PM2.5) simulation during a wintertime heavy pollution event in the North China Plain in late November 2017. In this experiment, two vehicle-mounted Lidar instruments were utilized to make synchronous observations around the 6th Ring Road of Beijing, and five ground-based Lidars were used for long-term network observations on the North China Plain. Data assimilation was then performed using the PM2.5 vertical profile retrieved from the seven Lidars. Compared with the model results, the correlation of assimilation increased from 0.74–0.86, and the root-mean-square error decreased by 36.6%. Meanwhile, the transport flux and transport flux intensity of the PM2.5 were analyzed, which revealed that the PM2.5 around the 6th Ring Road of Beijing was mainly concentrated below 1.8 km, and there were obvious double layers of particles. Particulates in the southwest were mainly input, while those in the northeast were mainly output. Both the input and output heights were around 1 km, although the input intensity was higher than the output intensity. The GSI-Lidar-WRF-Chem system has great potential for air quality simulation and forecasting.

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It has been previously shown that the simultaneous exposure of colon cancer cells MIP to irinotecan and secreted protein acidic and rich in cysteine (SPARC) enhances anticancer activity. However, whether there is same effect of SPARC in pancreatic cancer remains largely unknown. Therefore in this study, we aimed to investigate the role of SPARC played in the sensitivity of pancreatic cancer to gemcitabine. We first treated MIAPaCa2 and MIAPaCa2/SPARC69 cells with different concentrations of gemcitabine (2, 5, 10, and 20 μM) for 24, 48, and 72 h and selected the appropriated concentration for further study. Then we analyzed cell viability, cell cycle, and apoptosis and the levels of apoptosis-related proteins by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, fluorescence-activated cell sorting and Western blot were used, respectively. In this study, we found that gemcitabine inhibited the proliferation of pancreatic cancer cells in a time- and dose-dependent manner. Overexpression of SPARC increased the inhibiting effect of gemcitabine on pancreatic cancer cells. The colony size of MIAPaCa2/SPARC69 was much smaller than that of MIAPaCa2/V. There was a G0/G1 arrest with significant increase of apoptosis after gemcitabine treatment in MIAPaCa2/SPARC69 cells. Furthermore, our results demonstrated that overexpression of SPARC markedly increased the levels of pro-apoptotic proteins in gemcitabine-treated pancreatic cancer cells. The SPARC can enhance the chemosensitivity of pancreatic cancer cells to gemcitabine via regulating the expression of apoptosis-related proteins. These results have shown that the SPARC/ gemcitabine combination treatment may be a potentially useful therapeutic option for individuals diagnosed with pancreatic cancer.

Abstract. China has made great efforts to monitor and control air pollution in the past decade. Comprehensive characterization and understanding of pollutants in three-dimensions are, however, still lacking. Here, we used data from an observation network consisting of 13 aerosol lidars and more than 1000 ground observation stations combined with a data assimilation technique to conduct a comprehensive analysis of extreme heavy aerosol pollution (HAP) over the North China Plain (NCP) from November–December 2017. During the studied period, the maximum hourly mass concentration of surface PM2.5 reached ∼390 µg m−3. After assimilation, the correlation between model results and the independent observation sub-dataset was ∼50 % higher than that without the assimilation, and the root mean square error was reduced by ∼40 %. From pollution development to dissipation, we divided the HAP in the NCP (especially in Beijing) into four phases: an early phase (EP), a transport phase (TP), an accumulation phase (AP), and a removal phase (RP). We then analyzed the evolutionary characteristics of PM2.5 concentration during different phases on the surface and in 3-D space. We found that the particles were mainly transported from south to north at a height of 1–2 km (during EP and RP) and near the surface (during TP and AP). The amounts of PM2.5 advected into Beijing with the maximum transport flux intensity (TFI) were through the pathways in the relative order of the southwest > southeast > east pathways. The dissipation of PM2.5 in the RP stage (with negative TFI) was mainly from north to south with an average transport height of ∼1 km above the surface. Our results quantified the multi-dimensional distribution and evolution of PM2.5 concentration over the NCP, which may help policymakers develop efficient air pollution control strategies.