ALBERT

Description: Since its first confirmed case at the end of 2019, COVID-19 has become a global pandemic in three months with more than 1.4 million confirmed cases worldwide, as of early April 2020. Quantifying the changes of pollutant emissions due to COVID-19 and associated governmental control measures is crucial to understand its impacts on economy, air pollution, and society. We used the WRF-GC model and the tropospheric NO2 column observations retrieved by the TROPOMI instrument to derive the top-down NOx emission change estimation between the three periods: P1 (January 1st to January 22nd, 2020), P2 (January 23rd, Wuhan lockdown, to February 9th, 2020), and P3 (February 10th, back-to-work day, to March 12th, 2020). We found that NOx emissions in East China averaged during P2 decreased by 50% compared to those averaged during P1. The NOx emissions averaged during P3 increased by 26% compared to those during P2. Most provinces in East China gradually regained some of their NOx emissions after February 10, the official back-to-work day, but NOx emissions in most provinces have not yet to return to their previous levels in early January. NOx emissions in Wuhan, the first epicenter of COVID-19, had no sign of emission recovering by March 12. A few provinces, such as Zhejiang and Shanxi, have recovered fast, with their averaged NOx emissions during P3 almost back to pre-lockdown levels.

Description: Wildfire occurrence and spread are affected by atmospheric and land-cover conditions, and therefore meteorological and land-cover parameters can be used in area burned prediction. We apply three forecast methods, a generalized linear model, regression trees, and neural networks (Levenberg–Marquardt backpropagation) to produce monthly wildfire predictions 1 year in advance. The models are trained using the Global Fire Emissions Database version 4 with small fires (GFEDv4s). Continuous 1-year monthly fire predictions from 2011 to 2015 are evaluated with GFEDs data for 10 major fire regions around the globe. The predictions by the neural network method are superior. The 1-year moving predictions have good prediction skills over these regions, especially over the tropics and the southern hemisphere. The temporal refined index of agreement (IOA) between predictions and GFEDv4s regional burned areas are 0.82, 0.82, 0.8, 0.75, and 0.56 for northern and southern Africa, South America, equatorial Asia and Australia, respectively. The spatial refined IOA for 5-year averaged monthly burned area range from 0.69 in low-fire months to 0.86 in high-fire months over South America, 0.3–0.93 over northern Africa, 0.69–0.93 over southern Africa, 0.47–0.85 over equatorial Asia, and 0.53–0.8 over Australia. For fire regions in the northern temperate and boreal regions, the temporal and spatial IOA between predictions and GFEDv4s data in fire seasons are 0.7–0.79 and 0.24–0.83, respectively. The predictions in high-fire months are better than low-fire months. This study illustrates the feasibility of global fire activity outlook forecasts using a neural network model and the method can be applied to quickly assess the potential effects of climate change on wildfires.

Description: In this paper, the effects of Ti and Cu addition on inclusion modification and corrosion behavior in the simulated coarse-grained heat-affected zone (CGHAZ) of low-alloy steels were investigated by using in-situ scanning vibration electrode technique (SVET), scanning electron microscope/energy-dispersive X-ray spectroscopy (SEM/EDS), and electrochemical workstation. The results demonstrated that the complex inclusions formed in Cu-bearing steel were (Ti, Al, Mn)-Ox-MnS, which was similar to that in base steel. Hence, localized corrosion was initiated by the dissolution of MnS. However, the main inclusions in Ti-bearing steels were modified into TiN-Al2O3/TiN, and the localized corrosion was initiated by the dissolution of high deformation region at inclusion/matrix interface. With increased interface density of inclusions in steels, the corrosion rate increased in the following order: Base steel ≈ Cu-bearing steel 〈 Ti-bearing steel. Owing to the existence of Cu-enriched rust layer, the Cu-bearing steel shows a similar corrosion resistance with base steel.

Description: Digital rock physics is an often-mentioned approach to better understand and model transport processes occurring in tight nanoporous media including the organic and inorganic matrix of shale. Workflows integrating nanometer-scale image data and pore-scale simulations are relatively undeveloped, however. In this paper, a workflow is demonstrated progressing from sample acquisition and preparation, to image acquisition by Scanning Transmission Electron Microscopy (STEM) tomography, to volumetric reconstruction to pore-space discretization to numerical simulation of pore-scale transport. Key aspects of the workflow include (i) STEM tomography in high angle annular dark field (HAADF) mode to image three-dimensional pore networks in µm-sized samples with nanometer resolution and (ii) lattice Boltzmann method (LBM) simulations to describe gas flow in slip, transitional, and Knudsen diffusion regimes. It is shown that STEM tomography with nanoscale resolution yields excellent representation of the size and connectivity of organic nanopore networks. In turn, pore-scale simulation on such networks contributes to understanding of transport and storage properties of nanoporous shale. Interestingly, flow occurs primarily along pore networks with pore dimensions on the order of tens of nanometers. Smaller pores do not form percolating pathways in the sample volume imaged. Apparent gas permeability in the range of 10−19 to 10−16 m2 is computed.

Description: Ambient carbonyls are critical precursors of ozone (O3) and secondary organic aerosols (SOA). To better understand the pollution characteristics of carbonyls in Taiyuan, field samplings were conducted, and 13 carbonyls were detected in an urban site of Taiyuan for the four seasons. The total concentration of carbonyls in the atmosphere was 19.67 ± 8.56 μg/m3. Formaldehyde (7.70 ± 4.78 μg/m3), acetaldehyde (2.95 ± 1.20 μg/m3) and acetone (5.57 ± 2.41 μg/m3) were the dominant carbonyl compounds, accounting for more than 85% of the total carbonyls. The highest values for formaldehyde and acetone occurred in summer and autumn, respectively, and the lowest occurred in winter. The variations for acetaldehyde were not distinct in the four seasons. Formaldehyde and acetone levels increased obviously in the daytime and decreased at night, while acetaldehyde did not show significant diurnal variations. Higher temperature and stronger sunlight intensity could facilitate the photochemical reaction of volatile organic compounds (VOCs) and enhance the O3 levels in summer. Formaldehyde and acetaldehyde contributed 70–95% of carbonyls’ ozone formation potential (OFP) caused by carbonyls with the highest totals of 268.62 μg/m3 and 38.14 μg/m3, respectively. The highest concentrations of carbonyls from south and southwest winds in summer suggest that the coke industries in the southern Taiyuan Basin should be, firstly, controlled for the alleviation of ozone pollution.

Description: The properties of alfalfa-derived biochars etched with phosphoric (PBC) or hydrochloric acid (ClBC) compared with raw materials (BC) were examine in this paper. SEM, FT-IR, XRD, BET and elemental analysis were performed to characterize the micromorphology and chemical structure comprehensibly. The results showed that the porous structure was enhanced, and surface area was increased via etching with inorganic acids. Batch adsorption experiments were performed for sulfamethoxazole (SMX) to biochars. The experimental data showed that modified biochars exhibited higher adsorption capacity for SMX, i.e., the adsorption quantity of ClBC and PBC had risen by 38% and 46%. The impact on pH values suggested that the physisorption, including pore-filling and electrostatic interaction, might be applied to original biochar. In addition, chemisorption also played a role, including hydrogen bonding, π-π electron donor acceptor interaction (π-π EDA), and so on. Furthermore, both pH and coexisting ions also had a certain effect on sorption. Enhancement of the electrostatic attraction between biochar and SMX might also account for the enhanced capacity of SMX at pH 〈 7, and coexisting ions could decrease the amount of SMX adsorbed onto biochars, mainly because of competition for adsorption sites.

Description: The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the Least Absolute Shrinkage and Selection Operator (LASSO) method to construct the stock network, compare the heterogeneity of bull and bear markets, and further use the Map Equation method to analyse the evolution of modules in the SSE A-shares market. Empirical results show that (1) the connected effect is more significant in bear markets than bull markets and gives rise to abnormal volatilities in the stock market; (2) a system module can be found in the network during the first four stages, and the industry aggregation effect leads to module differentiation in the last four stages; (3) some stocks have leading effects on others throughout eight periods, and medium- and small-cap stocks with poor financial conditions are more likely to become risk sources, especially in bear markets. Our conclusions are beneficial to improving investment strategies and making regulatory policies.

Description: The spread of the COVID-19 pandemic and consequent lockdowns all over the world have had various impacts on atmospheric quality. This study aimed to investigate the impact of the lockdown on the air quality of Nanjing, China. The off-axis measurements from state-of-the-art remote-sensing Multi-Axis Differential Optical Absorption Spectroscope (MAX-DOAS) were used to observe the trace gases, i.e., Formaldehyde (HCHO), Nitrogen Dioxide (NO2), and Sulfur Dioxide (SO2), along with the in-situ time series of NO2, SO2 and Ozone (O3). The total dataset covers the span of five months, from 1 December 2019, to 10 May 2020, which comprises of four phases, i.e., the pre lockdown phase (1 December 2019, to 23 January 2020), Phase-1 lockdown (24 January 2020, to 26 February 2020), Phase-2 lockdown (27 February 2020, to 31 March 2020), and post lockdown (1 April 2020, to 10 May 2020). The observed results clearly showed that the concentrations of selected pollutants were lower along with improved air quality during the lockdown periods (Phase-1 and Phase-2) with only the exception of O3, which showed an increasing trend during lockdown. The study concluded that limited anthropogenic activities during the spring festival and lockdown phases improved air quality with a significant reduction of selected trace gases, i.e., NO2 59%, HCHO 38%, and SO2 33%. We also compared our results with 2019 data for available gases. Our results imply that the air pollutants concentration reduction in 2019 during Phase-2 was insignificant, which was due to the business as usual conditions after the Spring Festival (Phase-1) in 2019. In contrast, a significant contamination reduction was observed during Phase-2 in 2020 with the enforcement of a Level-II response in lockdown conditions i.e., the easing of the lockdown situation in some sectors during a specific interval of time. The observed ratio of HCHO to NO2 showed that tropospheric ozone production involved Volatile Organic Compounds (VOC) limited scenarios.