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Non-methane short-lived climate forcer (SLCF) or near-term climate forcer (NTCF) emissions, as a significant driver of climate change, can be reduced to improve air quality. These reductions may contribute to additional warming of the climate system in the short term, thereby strongly affecting the likelihood of climate extremes. However, there has been no quantitative assessment of the impact of non-methane SLCF mitigation on compound flood–heatwave extremes (CFHEs). This study quantitatively investigates the changes in future (2031–2050 versus 1995–2014) CFHEs and the resulting population exposure in the Northern Hemisphere (NH) due to non-methane SLCF reductions. We used multi-model ensemble simulations under two future scenarios from the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The two future scenarios share the same greenhouse gas (GHG) emissions but have weak (Shared Socioeconomic Pathway (SSP) 3–7.0) versus strong (SSP3-7.0-lowNTCF) levels of air quality control measures. The results show that future non-methane SLCF reductions during 2031–2050 results in about a 7.3% ± 2.3% increase in grid exposure to CFHEs in the NH relative to the period 1995–2014. The frequency, intensity, and duration of CFHEs increase by varying degrees. During the period 2031–2050, the frequency of CFHEs across the NH increases by 2.9 ± 0.9 events per decade due to non-methane SLCF reductions. The increases in CFHE frequency are more pronounced in East Asia, South Asia, Siberia, and northern and eastern North America. In East and South Asia, the intensities of both heatwaves and floods corresponding to CFHEs increase markedly, where heatwave magnitude (HWM) increases by 0.3 ± 0.2 K in East Asia and weighted average precipitation (WAP) increases by 18.3% ± 15.3% and 12.0% ± 4.5% in East Asia and South Asia, respectively. In other regions, rising temperatures dominate the increase in CFHEs. With regard to the duration of CFHEs, future reductions in non-methane SLCFs increases the duration of CFHEs in the NH by 0.3 ± 0.1 d. Regionally, the sensitivity of CFHE frequency to global warming caused by non-methane SLCF mitigation is 1.2–1.9 times higher than that caused by GHG forcing. Non-methane SLCFs results in NH-averaged increases in population exposure to CFHEs of (5.0 ± 2.0) × 105 person·event in the period 2031–2050. This study emphasizes the importance of considering the impacts of cleaner air in future responses to compound extremes and corresponding societal planning.

Opposite anthropogenic aerosol emission trends in Asia can lead to different responses of the climate. Here, we examined the responses of the East Asian summer monsoon (EASM) to changes in Asian anthropogenic aerosol emissions during 2006–2014 using a global aerosol/atmospheric chemistry–climate coupled model (BCC_AGCM2.0_CUACE/Aero) with two sets of emission inventories: the Community Emissions Data System (CEDS) inventory adopted by the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the inventory developed at Peking University (PKU). The changes in Asian anthropogenic aerosol emissions during 2006–2014 between the two inventories were remarkably different, particularly in eastern China where completely opposite trends were observed (i.e., increase in the CEDS inventory, but significant reduction in the PKU inventory). The perturbation simulations with the Asian anthropogenic aerosol forcing from the two inventories showed opposite changes in aerosol optical depth, aerosol effective radiative forcing, cloud liquid water path, and total cloud cover in eastern China. The simulated ‘dipole-type’ changes (i.e., increase in India but decrease in China) in Asian aerosols and the resulting changes in local radiation budget under the PKU inventory were consistent with the corresponding observations. The summer surface temperatures over eastern China decreased by 0–0.4 K because of the Asian anthropogenic aerosol forcing under the CEDS inventory, while they increased by 0.1–0.8 K under the PKU inventory. The weakening of the EASM index caused by the Asian aerosol forcing under the PKU inventory was twofold greater than that under the CEDS inventory (−0.4 vs. −0.2). The Asian ‘dipole-type’ aerosol forcing contributed to the observed summer ‘southern drought and northern flood’ phenomenon in eastern China during 2006–2014. The slow ocean-mediated response to the regional ‘dipole-type’ aerosol forcing dominated the weakening of the EASM circulation and the precipitation changes in eastern China in the total response. This study further confirms that the biases in anthropogenic aerosol emissions over Asia can affect the CMIP6-based regional climate attribution.

Ethereum has received increasing attention as the first blockchain platform to support smart contracts. Data mining has become an important tool for analyzing Ethereum transactions. However, existing methods have the disadvantage of covering partial transactions and being vulnerable to privacy-enhancing techniques. In this paper, we propose a scheme for transaction correlation with the node as an entity, which can cover all transactions while being resistant to privacy-enhancing techniques. Utilizing timestamps relayed from N fixed nodes to describe the network properties of transactions, we cluster transactions that enter the network from the same source node. Experimental results show that our method can determine with 97% precision whether two transactions enter the network from the same source node.

With the rapid development of wind and photovoltaic power generation, hydro-turbine generator units have to operate in a challenging way, resulting in obvious vibration problems. Because of the significant impact of vibration on safety and economical operation, it is of great significance to study the causal relationship between vibration and other variables. The complexity of the hydro-turbine generator unit makes it difficult to analyze the causality of the mechanism. This paper studied the correlation based on a data-driven method, then transformed the correlation into causality based on the mechanism. In terms of correlation, traditional research only judges whether there is a correlation between all data. When the data with correlation are interfered with by the data without correlation, the traditional methods cannot accurately identify the correlation. A piecewise correlation method based on change point detection was proposed to fill this research gap. The proposed method segmented time series pairs, then analyzed the correlation between subsequences. The causality between power load and vibration of a hydro-turbine generator unit was further analyzed. It indicated that when the power load is less than 200 MW, the causality is weak, and when the power load is greater than 375 MW, the causality is strong. The results show that the causality between vibration and power load is not fixed but piecewise. Furthermore, the piecewise correlation method compensated for the limitation of high variance of the maximum information coefficient.

The microgrid trading market can effectively solve the problem of in-situ consumption of distributed energy and reduce the impact of distributed generation (DG) on the grid. However, the traditional microgrid trading model has some shortcomings, such as high operation cost and poor security. Therefore, in this paper, a microgrid market trading model was developed using consortium blockchain technology and Nash game equilibrium theory. Firstly, blockchain container is used to authenticate the users who want to participate in the transaction. Then, the pricing system collects and integrates transaction requests submitted by users, then formulates transaction pricing strategy of microgrid using Nash equilibrium theory. Finally, the price, trading volume, and user information are submitted to the blockchain container for transaction matching to achieve the transaction. After the transaction is completed, its related information is recorded in the hyperledger and the dispatch system is called. The scene simulation was implemented on Fabric 1.1 platform and the results analyzed. Results show that the trading model proposed in this paper greatly reduces the cost of electricity purchase and improves the benefits of electricity sales. Besides, the model is far more capable of handling transactions than the models based on Bitcoin and Ethereum.

With the rapid development of the energy internet, the transaction of distributed renewable energy (DRE) is playing an increasingly important role in the energy market. However, in the transaction model of distributed renewable energy combined with public blockchain technology, nodes in the trading network can join or leave the network at any time without any permission, which hinders the regulation of electricity institutions. Corresponding to the transaction principle, a distributed renewable energy transaction authentication mechanism based on consortium blockchain is proposed in this paper. First, certificate authority nodes were set in the transaction network to provide nodes with access authority by controlling the public keys and private keys of trading participants so that they can complete their identity authentication. Next, essential chaincodes in the transaction authentication were designed and deployed on a Hyperledger Fabric blockchain site, and a simulation experiment of a simple DRE transaction was used to elaborate the details on the transaction process. Finally, the proposed model was evaluated according to its performance and proved to be practical and effective.

CUACE/Aero, the China Meteorological Administration (CMA) Unified Atmospheric Chemistry Environment for aerosols, is a comprehensive numerical aerosol module incorporating emissions, gaseous chemistry and size-segregated multi-component aerosol algorithm. On-line coupled into a meso-scale weather forecast model (MM5), its performance and improvements for aerosol chemical and optical simulations have been evaluated using the observations data of aerosols/gases from the intensive observations and from the CMA Atmosphere Watch network, plus aerosol optical depth (AOD) data from CMA Aerosol Remote Sensing network (CARSNET) and from Moderate Resolution Imaging Spectroradiometer (MODIS). Targeting Beijing and North China region from July 13 to 31, 2008, when a heavy hazy weather system occurred, the model captured the general variations of PM10 with most of the data within a factor of 2 from the observations and a combined correlation coefficient (r) of 0.38 (significance level=0.05). The correlation coefficients are better at rural than at urban sites, and better at daytime than at nighttime. Chemically, the correlation coefficients between the daily-averaged modelled and observed concentrations range from 0.34 for black carbon (BC) to 0.09 for nitrates with sulphate, ammonium and organic carbon (OC) in between. Like the PM10, the values of chemical species are higher for the daytime than those for the nighttime. On average, the sulphate, ammonium, nitrate and OC are underestimated by about 60, 70, 96.0 and 10.8%, respectively. Black carbon is overestimated by about 120%. A new size distribution for the primary particle emissions was constructed for most of the anthropogenic aerosols such as BC, OC, sulphate, nitrate and ammonium from the observed size distribution of atmospheric aerosols in Beijing. This not only improves the correlation between the modelled and observed AOD, but also reduces the overestimation of AOD simulated by the original model size distributions of primary aerosols. The normalised mean error has been reduced to 62% with the CARSNET observations and 76% with MODIS, from the original 111% and 143%, respectively. The factors resulting in the underestimation of aerosol concentrations and other discrepancies in the model are explored, and improvements in enhancing the model performance are proposed from the analysis. It is found that the accuracy in meteorological predictions plays a critical role on the simulation of the occurrence and accumulation of heavy pollution episode, especially the circulation winds and the treatment of Planetary Boundary Layer (PBL).

Objective: There were limited randomized controlled trials (RCTs) of epsilon‐aminocaproic acid (EACA) versus tranexamic acid (TXA) in total knee arthroplasty (TKA). The aim of the study was to compare the efficacy and safety of TXA and EACA in the combination of intravenous (IV) and intra‐articular (IA) administration on reducing blood loss in patients following primary TKA. Methods: From January 2020 to January 2021, a total of 181 patients undergoing a primary unilateral TKA were enrolled in this prospective randomized controlled trial. Patients in the TXA group (n = 90) received 20 mg/kg of intravenous TXA preoperatively, 1 g of intra‐articular TXA intraoperatively, and three doses of 20 mg/kg intravenous TXA at 0, 3, 6 h postoperatively. Patients in the EACA group (n = 91) received 120 mg/kg of intravenous EACA preoperatively, 2 g of intra‐articular EACA intraoperatively, and three doses of 40 mg/kg intravenous EACA at 0, 3, 6 h postoperatively. The primary outcomes were total blood loss (TBL), transfusion rates and drop of hemoglobin (HB) level. The secondary outcomes included postoperative hospital stays and postoperative complications. The chi‐square tests and Fisher's exact tests were utilized to compare categorical variables, while the independent‐samples t‐tests and Mann–Whitney tests were used to compare continuous variables. Results: The patients who received TXA averaged less TBL than the patients who received EACA (831.83 ml vs 1065.49 ml, P = 0.015), and HB drop in TXA group was generally less than that of EACA group on postoperative day 1 and 3 (20.84 ± 9.48 g/L vs 24.99 ± 9.40 g/L, P = 0.004; 31.28 ± 11.19 vs 35.46 ± 12.26 g/L, P = 0.047). The length of postoperative stays in EACA group was 3.66 ± 0.81 day, which is longer than 2.62 ± 0.68 day in TXA group (P < 0.001). No transfusions were required in either group. The risk of nausea and vomiting in TXA group was significantly higher than that in EACA group (11/90 vs 0/91, P < 0.01). Conclusion: Although the TBL and HB drop were slightly greater in EACA group, these results were not clinically important, given that no transfusions were required. EACA could be an alternative to TXA, especially for patients with severe nausea and vomiting after using TXA postoperatively. Further studies are needed to adjust dosage of EACA to make better comparison of the two drugs. [ABSTRACT FROM AUTHOR]