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Abstract China has proposed the Renewable Portfolio Standard (RPS) policy to advance the stable development of renewable energy. The RPS requires each province to achieve a stated minimum share of renewable energy power in the total provincial power generation. However, there is an obvious mismatch between the actual capability of generating renewable power and the assigned responsibility for the share of renewable energy power based on the RPS in some provinces. Therefore, this study aims to optimize the renewable power dispatching strategy across provinces for satisfying the RPS requirements in China and to assess the corresponding pressure for each province. A renewable energy power dispatching model is developed, and an economically feasible strategy for dispatching renewable energy power in Chinese provinces in 2020–2022 was obtained. The results indicate that it is necessary to dispatch 395.2 and 140.4 TWh of hydropower and non-hydropower nationwide, respectively, in 2022 to fulfill the RPS target when the COVID-19 is effectively controlled worldwide. If COVID-19 cannot be effectively controlled, 376.6 and 127.8 TWh of hydropower and non-hydropower must be dispatched nationwide to fill the gap. Beijing, Tianjin, Shanghai, and Zhejiang are faced with a relatively high pressure under the RPS target. Finally, a path for each province to achieve its RPS target is proposed.

The COVID-19 pandemic caused severe economic contraction and paralyzed industrial activity. Despite a growing body of literature on the impacts of COVID-19 mitigation measures, scant evidence currently exists on the impacts of lockdowns on the economic and industrial activities of developing countries. Our study provides an empirical assessment of lockdown measures using 298,354 data points on daily electricity consumption in 396 sub-industries. To infer causal relationships, we employ difference-in-differences models that compare cities with and without lockdown policies and provide quantitative evidence on whether the long-term gain of lockdowns outweighs the short-term loss. The results show that lockdown policies led to a significant short-term drop in electricity consumption of 15.2% relative to the control group. However, the electricity loss under the no-lockdown scenario is 2.6 times larger than that under the strict lockdown scenario within 4 months of the outbreak. Discrepancies in the impacts among industries are identified, and even within the same industry, lockdowns have heterogeneous effects. The impact of lockdowns on small and medium-sized enterprises in developing countries is seriously underestimated, raising concerns about the distributional impact of subsidy measures. This study serves as a crucial reference for the government when facing public health emergencies and shocks to support better policies.

Microalgae-based bioremediation is likely to be challenged by the microplastics (MPs) in wastewater induced by the widely use of surgical masks (SMs) during COVID-19. However, such toxic impact was generally evaluated under high exposure concentrations of MPs, which was not in agreement with the actual wastewater environments. Therefore, this study investigated the microalgal cellular responses to the surgical mask exudates (SMEs) in wastewater and explored the underlying inhibitory mechanism from the molecular perspective. Specifically, 390 items/L SMEs (including 200 items/L MPs which was the actual MP level in wastewater) significantly inhibited nutrient uptake and photosynthetic activities interrupted peroxisome biogenesis and induced oxidative stress which destroyed the structure of cell membrane. Moreover, the SMEs exposure also affected carbon fixation pathways, suppressed ABC transporters while promoted oxidative phosphorylation processes for the ATP accumulation These comprehensive processes led to an 8.5% reduced microalgae growth and variations of cellular biocomponents including lipid, carbohydrate, and protein. The increased carotenoids and consumed unsaturated fatty acid were considered to alleviate the SMEs-induced stress, and the enhanced EPS secretion facilitated the homogeneous aggregation. These findings will enhance current understandings of the SMEs effects in wastewater on microalgae and further improve the practical relevance of microalgae wastewater bioremediation technology.

Rational detection of syndrome coronavirus 2 (SARS-CoV-2) is crucial to prevention, control, and treatment of disease. Herein, a dual-wavelength ratiometric electrochemiluminescence (ECL) biosensor based on resonance energy transfer (RET) between g-C3N4 nanosheets and Ru-SiO2@folic acid (FA) nanomaterials was designed to realize ultrasensitive detection of SARS-CoV-2 virus (RdRp gene). Firstly, the unique g-C3N4 nanosheets displayed very intense and stable ECL at 460 nm, then the triple helix DNA was stably and vertically bound to g-C3N4 on electrode by high binding affinity between ssDNA and g-C3N4. Meanwhile, trace amounts of target genes were converted to a large number of output by three-dimensional (3D) DNA walker multiple amplification, and the output bridged a multifunctional probe Ru-SiO2@FA to electrode. Ru-SiO2@FA not only showed high ECL at 620 nm, but also effectively quenched g-C3N4 ECL. As a result, ECL decreased at 460 nm and increased at 620 nm, which was used to design a rational ECL biosensor for detection of SARS gene. The results show that the biosensor has excellent detection sensitivity for RdRp gene with a dynamic detection range of 1 fM to 10 nM and a limit of detection (LOD) of 0.18 fM. The dual-wavelength ratio ECL biosensor has inestimable value and application prospects in the fields of biosensing and clinical diagnosis.

Abstract A better understanding of the carbon market can guide further reforms to improve its functionality. Market efficiency is a key indicator to uncover its current performance. Previous studies have revealed passed carbon market efficiency; however, given the dynamics of the market, it is worthy to track the up-to-date status. This paper, specifically, studies the Hubei pilot carbon market, which is quite interesting, considering its market scale, as well as the COVID-19 pandemic context. Wild bootstrapping Variance Ratio test is implemented to detect the market efficiency with the most recent and abundant data. Results show that the market efficiency in the period of 2014–2020 is around 0.3951, less than 1, suggesting a weak form of efficiency. Observing the sub-sample periods, the efficiency shows to be quite volatile: it climbes from 0.3621 to 0.4027 and finally drops to 0.3985. Furthermore, the market efficiency soares after the COVID-19, which echoes the smooth local reopening thanks to supporting policies. To some extent, this study enlarged the analysis of COVID-19 impact on the industrial sector and for this reason it provides important reference for further research. The unique contribution of this paper is to provide the more updated evidence on the efficiency of China’s pilot carbon market, as well as proofs of soaring market efficiency, after the pandemic.

Balances in the energy sector have changed since the implementation of the Covid-19 pandemic lockdown in Europe. This paper analyses how the lockdown affected electricity generation in European countries and how it will reshape future energy generation. Monthly electricity generation from total renewables and non-renewables in France, Germany, Spain, Turkey, and the UK from January 2017 to September 2020 were evaluated and compared. Four seasonal grey prediction models and three machine learning methods were used for forecasting; the quarterly results are presented to the end of 2021. Additionally, the share of electricity generation from renewables in total electricity generation from 2017 to 2021 for the selected countries was compared. Electricity generation from total non-renewables in the second quarter of 2020 for France, Germany, Spain, and the UK decreased by 21%-25% compared to the same period of 2019; the decline in Turkey was approximately 11%. Additionally, electricity generation from non-renewables in the third quarter of 2020 for all countries, except Turkey, decreased compared to the same period of the previous year. All grey prediction models and support vector machine method forecast that the share of renewables in total electricity generation will increase continuously in France, Germany, Spain, and the UK to the end of 2021. The forecasting methods provided by this study open new avenues for research on the impact of the Covid-19 pandemic on the future of the energy sector.

China's carbon reduction is of substantial significance in combating global climate change. In the context of the COVID-19 epidemic hit and economic and social development uncertainty, this study intends to discover whether China can attain the strategic destination of carbon peaking by 2030 and carbon neutrality by 2060 on schedule. Toward this aim, the grey relation analysis (GRA) is applied to filter the elements influencing carbon emissions to downgrade the dimensionality of indicators. A hybrid prediction is proposed integrated with Elman neural network (ENN) and sparrow search algorithm (SSA) to explore the potential for China to carbon neutrality from 2020 to 2060. The results reveal eight elements including GDP per capita, population, urbanization, total energy consumption and others are highly correlated with carbon emissions. China has a good chance of carbon peaking from 2028 to 2030, with a value of 11568.6-12330.5 Mt, while only one scenario can achieve carbon neutrality in 2060. In the neutral scenario, China should reach a proportion of renewable energy exceeding 80%, the urbanization rate reaching 85% and energy consumption controlling within 6.5 billion tons. A set of countermeasures for carbon abatement are presented to facilitate the implementation of carbon neutrality strategy.