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Currently, an inactivated vaccine has been widely used with encouraging results as a prophylactic agent against COVID-19 infection, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants. However, in vitro SARS-CoV-2 vaccine-specific immune features remain elusive, hindering the promotion of a third dose of the vaccine. Here, we present a detailed in vitro immune cellular response and large-scale multi-omics analysis for peripheral blood mononuclear cells (PBMCs) from participants vaccinated with CoronaVac (Sinovac Life Sciences, Beijing, China) and recovered participants from COVID-19. The mean titers of SARS-CoV-2 serum-neutralizing antibodies were significantly increased after the boosting immunization (Day 45) compared to the unimmunized state. We observed that type-1 helper T cells (Th1) tended to dominate after the first dose of vaccine, while humoral immune responses became dominant after the second dose due to the activation of type-2 helper T cell (Th2), memory B cells, and plasmablasts. T follicular helper cells (Tfh) involved in antibody production were activated after the first dose and were maintained for the observed time points. Single-cell RNA sequencing of PBMCs revealed specific changes in cell compositions and gene expression in immunized participants. Multi-omics analysis also demonstrated that CoronaVac-specific serum proteins, plasma metabolites, and plasma lipid changes were skewed to those changes in convalescent patients. Collectively, we provide a comprehensive understanding of CoronaVac-specific in vitro immune features. [ABSTRACT FROM AUTHOR]

PM 2.5 , generated via both direct emission and secondary formation, can have varying environmental impacts due to different physical and chemical properties of its components. However, traditional methods to quantify different PM 2.5 components are often based on online or offline observations and numerical models, which are generally high economic cost- or labor-intensive. In this study, we develop a new method, named Multi-Tracer Estimation Algorithm (MTEA), to identify the primary and secondary components from routine observation of PM 2.5. By comparing with long-term and short-term measurements of aerosol chemical components in China and the United States, it is proven that MTEA can successfully capture the magnitude and variation of the primary PM 2.5 (PPM) and secondary PM 2.5 (SPM). Applying MTEA to the China National Air Quality Network, we find that (1) SPM accounted for 63.5 % of the PM 2.5 in cities in southern China on average during 2014–2018, while the proportion dropped to 57.1 % in the north of China, and at the same time the secondary proportion in regional background regions was ∼ 19 % higher than that in populous regions; (2) the summertime secondary PM 2.5 proportion presented a slight but consistent increasing trend (from 58.5 % to 59.2 %) in most populous cities, mainly because of the recent increase in O 3 pollution in China; (3) the secondary PM 2.5 proportion in Beijing significantly increased by 34 % during the COVID-19 lockdown, which might be the main reason for the observed unexpected PM pollution in this special period; and finally, (4) SPM and O 3 showed similar positive correlations in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions, but the correlations between total PM 2.5 and O 3 in these two regions, as determined from PPM levels, were quite different. In general, MTEA is a promising tool for efficiently estimating PPM and SPM, and has huge potential for future PM mitigation. [ABSTRACT FROM AUTHOR]

Assessing the urban-scale building photovoltaic (PV) potential is important for designing urban environments, retrofitting existing structures, or integrating PVs with grids. However, few studies have considered high-temporal-resolution simulations, the facade PV potential, and a comprehensive PV model simultaneously; thus, the overall accuracy of the estimation of PV potential may be limited. Therefore, this study developed an integrated framework to assess the urban-scale PV potential of rooftops and facades at high spatiotemporal resolution. The proposed approach integrates an anisotropic sky diffuse model, a vector-based shading calculation method, and a temperature-related PV performance model. The annual PV potential and spatial/temporal characteristics were analyzed in a case study of over 170,000 buildings in Beijing. The results showed that the estimated rooftop PV power generation was 7.55 TWh/y, whereas the facade PV power generation was 18.07 TWh/y, which was 239% of the rooftop PV yield. The integrated model estimated PV yield with higher accuracy than the simplified models by depicting more details. The proposed approach can be applied to the large-scale assessment of future energy systems with increasing penetration of PVs, and the results can support effective policies for the integration of PVs into the built environment in dense cities. [Display omitted] • High-accuracy models of sky diffusion, shading, and PV performance were integrated. • Facade PV potential was equivalent to 239% of the rooftop PV potential in Beijing. • Shading affects less on rooftops, but reduces up to 15% of facade PV yield in blocks. • PV potential on facades is greater downtown than in suburbs, while similar on roofs. [ABSTRACT FROM AUTHOR]

Energy suppliers pay more and more attention to bioenergy which has great potential for responding to extreme climate challenges. Nevertheless, few studies concentrate on the optimal planning of the downstream bioenergy supply chain. This study proposes a multiperiod bilevel game-theoretic framework for the optimal planning of biofuel refueling stations, including an upper-level model for petroleum companies and a lower-level model for biofuel companies. Based on the characteristic of the game theory and the implementation of carbon taxes, four scenarios are established. Finally, the proposed method is validated by a real-world case in Beijing, China. Under the upper limit of the blending ratio, the results show that cooperation can achieve the biggest overall profit. Petroleum companies are more profitable for cooperating with biofuel companies no matter whether carbon tax exists or not. Biofuel companies can get more profit if they non-cooperate with petroleum companies when there is no carbon tax, but the existence of the carbon tax makes it more profitable for biofuel companies to cooperate with petroleum companies. Besides, the best choice for biofuel companies to enter the fuel retailing market is the early stage of energy transition when no carbon tax exists or carbon tax is low. [ABSTRACT FROM AUTHOR]