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Carbon sink afforestation (CSA) has become one of the most concerned issues of countries around the world under the background of climate change. The northern forest ecosystem, located in mid- and high latitudes, is a huge terrestrial carbon pool and is very sensitive to climate change. Studying the carbon emission accounting of CSA in northern forests helps clarify the contribution of CSA to forestry carbon sequestration and forecasts the carbon sink effect of forest ecosystems. It is of great significance for the assessment of forest carbon sink and carbon cycling by providing a scientific basis and reference for the development, utilization, and management of carbon sink afforestation, as well as the coordinated development of ecology and social economy. At present, research on the carbon emission accounting of the CSA in northern China is still lacking. According to the relevant models and parameters of estimating live biomasses with the default method from the IPCC’s (Intergovernmental Panel on Climate Change) Technical Guidelines for National Forestry Carbon Sink Accounting and Monitoring, carbon stock, carbon emission, and carbon leakage of the Weihe CSA (carbon sink afforestation) pilot demonstration area in the boreal Longjiang Forest Industry in a baseline scenario and CSA scenario were measured, and the CSA’s net carbon sink was estimated. The conclusions were as follows: (1) By the end of the crediting period of the project’s baseline, carbon fixation reached 101.85 t CO2, with an average annual CO2 fixation of 5.09 t. By the end of the CSA term, carbon sequestration was accumulated as 382.13 t CO2, with an average annual sequestration of 19.11 t CO2, nearly four times that of the baseline period. (2) By the end of the CSA term, the carbon sequestration of the coniferous standing forest was 46.2% higher than that of the broad-leaved standing forest, accounting for 65% of the total carbon sequestration of the forest. The carbon sequestration of the tree species in the coniferous forest in descending order is Picea koraiensis, Pinus koraiensis, Larix olgensis, Fraxinus mandshurica, and Populus cathayana. The carbon sink density of the coniferous standing forest was 8.7% higher than that of the broad-leaved standing forest. (3) The carbon fixation of the coniferous standing forest nearly doubled that of the broad-leaved standing forest. The highest carbon fixation belongs to Fraxinus mandshurica, closely followed by Picea koraiensis and Pinus koraiensis at a high level, and then Larix olgensis and Populus cathayana. The carbon fixation of Fraxinus mandshurica was 20 times that of Populus cathayana. (4) The accumulated greenhouse gas emissions within the boundary during the CSA period were 2.53 t CO2-e. The accumulated greenhouse gas leakage outside the boundary was 0.05 t CO2-e. Carbon emissions occurred in the first, second, and third years of the crediting period, while carbon leakage occurred only in the first year. (5) This result appeared as carbon sources during the first three years of the CSA period but changed to carbon sink from the fourth year and then accumulated to 280.28 t (70.07 t CO2-e·hm−2) as a net carbon sink by the end of the term. The Weihe CSA appeared to have a relatively strong ability of carbon sequestration in temperate forests. The CSA activity is influenced by factors such as policies, environment, management, etc., resulting in uncertainties in carbon sequestration accounting. Therefore, it is suggested that comparison studies and investigations should be strengthened, and multiple methods should be integrated into carbon sequestration estimation and accounting, leading the carbon accounting of forest ecosystems to a high-level and comprehensive development.

The rapidly evolving Coronavirus 2019 (COVID-19) pandemic has led to millions of deaths around the world, highlighting the pressing need to develop effective antiviral pharmaceuticals. Recent efforts with computer-aided rational drug discovery have allowed detailed examination of drug-macromolecule interactions primarily by molecular mechanics (MM) techniques. Less widely applied in COVID-19 drug modeling is density functional theory (DFT), a quantum mechanics (QM) method that enables electronic structure calculations and elucidations of reaction mechanisms. Here, we review recent advances in applying DFT in molecular modeling studies of COVID-19 pharmaceuticals. We start by providing an overview of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drugs and targets, followed by a brief introduction to DFT. We then provide a discussion of different approaches by which DFT has been applied. Finally, we discuss essential factors to consider when incorporating DFT in future drug modeling research.

The recent development of single-molecule sensors (SMS), which detect individual targets one at a time, allows determination of ultra-low concentrations of structurally similar compounds from a complex matrix. Protein nanopores are one of the earliest methods able to resolve the signal from a single molecule, and have already been successfully employed in commercial DNA sequencers. The protein nanopore based SMS, however, remains challenging, largely because the quantitative single-molecule analysis requires recording a sufficient number of signals for statistical significance within a reasonable time frame, thus restricting the lower limit of detection. This review aims to critically evaluate the strategies developed in this field over the last two decades. The measurement principle of nanopore SMS is first elucidated, followed by a systematic examination of the eight common protein pores, and a comprehensive assessment of the major types of sensing applications. A particular emphasis is placed on the intrinsic relationship between the size and charge of protein nanopores and their sensing capabilities for different kinds of analytes. Innovative approaches to lift the performance of nanopore SMS are also analyzed in detail, with a prediction at the end of the most promising future applications.

In this work, we first report Au nanoclusters/porous silica particles nanocomposites as fluorescence enhanced sensors for selective and sensitive detection of Cu (II). As red-emitting GSH-protected Au nanoclusters (Au NCs) were self-assemble into porous silica particles (PSPs) after ultrasonic treatment. As a result, the Au NCs can be immobilized in the nano-channels of PSPs, which leads to the observation of an immobilized induced emission enhancement phenomenon. The photoluminscence (PL) intensity of the nanocomposites can enhance dozens of times compared with Au NCs. As a result, we obtain a novel PL enhanced sensor of Au NCs/PSPs nanocomposites with excellent PL properties. The as-prepared Au NCs/PSPs nanocomposites show good water-solubility, high stability, low toxicity, and exhibit a high PL quenching for reliable, sensitive and selective detection of Cu2+. The limit of detection can reach as low as 1 ppb. What is more, the Au NCs/PSPs nanocomposites also show sensitive detection of Cu2+ in living cells. These properties provide the Au NCs/PSPs nanocomposites with promising PL sensors for Cu2+ detection in various environmental and biological systems.