Spatial distribution and temporal variation of atmospheric pollution in the South Gobi Desert, China, during 2016-2019

Characterization of air pollution and associated health risks in Gansu Province, China from 2015 to 2022

Air pollution poses a major threat to both the environment and public health. The air quality index (AQI), aggregate AQI, new health risk-based air quality index (NHAQI), and NHAQI-WHO were employed to quantitatively evaluate the characterization of air pollution and the associated health risk in Gansu Province before (P-I) and after (P-II) COVID-19 pandemic. The results indicated that AQI system undervalued the comprehensive health risk impact of the six criteria pollutants compared with the other three indices. The stringent lockdown measures contributed to a considerable reduction in SO2, CO, PM2.5, NO2 and PM10; these concentrations were 43.4%, 34.6%, 21.4%, 17.4%, and 14.2% lower in P-II than P-I, respectively. But the concentration of O3 had no obvious improvement. The higher sandstorm frequency in P-II led to no significant decrease in the ERtotal and even resulted in an increase in the average ERtotal in cities located in northwestern Gansu from 0.78% in P-I to 1.0% in P-II. The cumulative distribution of NHAQI-based population-weighted exposure revealed that 24% of the total population was still exposed to light pollution in spring during P-II, while the air quality in other three seasons had significant improvements and all people were under healthy air quality level.

Environmental implications of reduced electricity consumption in Wuhan during COVID-19 outbreak: A brief study

Due to the COVID-19 outbreak, Wuhan was locked down from 23 January 2020 to 8 April 2020, a total of 76 days. It is well known that the electricity consumption is a direct reflection of human activity. During the lockdown of Wuhan, most of human activities were forbidden. The reduction in human activity would inevitably lead to a reduction in electricity consumption. At the same time, anthropogenic emissions of air pollutants would also be reduced with the reduction of human activity. In this study, the correlation between electricity consumption and air pollutants during lockdown was discussed in detail. The result showed that the drop in pollutants concentrations in January should be attributed to the washout effect of rainfall rather than the lockdown. The decrease of electricity consumption in the secondary industry might play a significant role on the decrease of PM2.5 and NO2 concentrations in Wuhan in February 2020. The decrease in NO2 concentration in March should be attributed to the reduction of pollutants emissions from the tertiary industry, which means that more attention should be paid to the control of NO2 emission in the tertiary industry. Due to reduced emissions from local sources, the role of long-range transport sources might be more significant during the lockdown of Wuhan. By PSCF analysis, southeast of Wuhan could be the major potential emission sources of PM2.5 , especially in the northern part of Jiangxi province. It was suggested that stricter regulation of pollutants emissions should be implemented in this area.

COVID-19 and energy: Influence mechanisms and research methodologies

Considering the important role of energy in modern society, it is imperative to study the current situation and future development of energy under the influence of COVID-19. This paper identifies the current research hotspots, proposes future research directions accordingly, and summarizes the methodologies via a bibliometric analysis. Five research hotspots include COVID-19 and the changes of energy consumption, COVID-19 and the fluctuation of the energy market, COVID-19 and the development of renewable energy, COVID-19 and climate impacts caused by energy consumption, and COVID-19 and the energy policy. According to the influence mechanism of COVID-19 on each hotspot, the pandemic has exerted short-term influencs on energy consumption, energy price, and air pollution. Meanwhile, the pandemic could have a far-reaching impact on the renewable energy sector, climate, and energy policy. In addition, the main methodologies are reviewed, revealing that regression analysis and scenario analysis are commonly used as the quantitative and qualitative methods, respectively. Moreover, given the nonlinear relations between the pandemic and energy, an artificial neural networks model is used to enhance the prediction efficiency of energy demand and price. Finally, policy implications for obtaining clean, low-carbon, safe, and efficient energy in the context of COVID-19 are proposed.

Element transfer by a vapor-gas stream from sulfide mine tailings: from field and laboratory evidence to thermodynamic modeling

Condensates of vapor-gas streams were collected during field and laboratory experiments for the determination of the volatility of chemical elements in sulfide tailings under ambient conditions. The object of research was the Ursk waste heaps (Kemerovo region, Russia). Field experiments were performed on the top of the heap and in neighboring territories; the elements' concentrations in condensates from the top exceed the background values in 2-3 orders of magnitude. To obtain condensates in the laboratory, the waste material was heated to 60 °С. Laboratory condensate-contended high concentrations Ca, Mg, but Fe, Cd, Mo, Sn, Zr, and W were lower by more than 2 orders of magnitude. Also, chemical elements such as Au, Zr, Cs, U, and Tl were determined in the laboratory condensates at elevated temperatures. Also, solid samples were leached with water at the laboratory. A high positive correlation of condensate compositions with compositions of water extracts obtained from parallel samples was established. The most mobile elements transferred in the steam-gas phase are alkaline (Li, Cs, Na, K), alkaline earth (Ca, Sr), chalcophile metals (Hg, Zn, Cu), and metalloids (As, Sb, Se). The numerical experiment of metal transfer forms using thermodynamic modeling methods has been performed, including those with organic ligands.