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Grassland ecosystems are vital terrestrial ecosystems. As areas sensitive to climate change, they are critical for assessing the effects of global climate change. In China, grasslands account for over 40% of the land area. There is currently limited information on microbial diversity evolution in different grassland areas, particularly microorganisms with ice nucleation activity (INA) and their potential resources with potential influence to regulate regional precipitation and climate. We used Illumina MiSeq to sequence the 16S rRNA V3-V4 hypervariable region and performed a simple droplet freezing experiment to determine the variation in the grassland microbial community species composition and community structure. Rainwater and topsoil samples from the Hulunbuir Grassland in Inner Mongolia collected over three years were characterized. The dominant bacterial genus in the rainwater was Massilia, and the dominant fungus was Cladosporium. Additionally, the dominant bacteria in the soil were Sphingomonas, and the dominant fungus was Gibberella. There were differences in the microbial communities before and after the coronavirus disease epidemic. Pathogenic microorganisms exhibited inconsistent responses to environmental changes. The low relative abundance of known high-INA microorganisms and the higher freezing temperature indicated that unknown high-efficiency biological ice nucleating particles may be present. We found significant differences in species diversity and richness between the rainwater and soil populations in grassland areas by analyzing the sample community structures. Our research results revealed the species composition and structure of the microbiota in grassland ecosystems in China, indicating that environmental media and human activities may affect the microbiota in the grassland area and indicating underlying microorganisms with high INA., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Controlling anthropogenic mercury emissions is an ongoing effort and the effect of atmospheric mercury mitigation is expected to be impacted by accelerating climate change. The lockdown measures to restrict the spread of Coronavirus Disease 2019 (COVID-19) and the following unfavorable meteorology in Beijing provided a natural experiment to examine how air mercury responds to strict control measures when the climate becomes humid and warm. Based on a high-time resolution emission inventory and generalized additive model, we found that air mercury concentration responded almost linearly to the changes in mercury emissions when excluding the impact of other factors. Existing pollution control and additional lockdown measures reduced mercury emissions by 16.7 and 12.5 kg/d during lockdown, respectively, which correspondingly reduced the concentrations of atmospheric mercury by 0.10 and 0.07 ng/m 3 . Emission reductions from cement clinker production contributed to the largest decrease in atmospheric mercury, implying potential mitigation effects in this sector since it is currently the number one emitter in China. However, changes in meteorology raised atmospheric mercury by 0.41 ng/m 3 . The increases in relative humidity (9.5%) and temperature (1.2 °C) significantly offset the effect of emission reduction by 0.17 and 0.09 ng/m 3 , respectively, which highlights the challenge of air mercury control in humid and warm weather and the significance of understanding mercury behavior in the atmosphere and at atmospheric interfaces, especially the impact from relative humidity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

To control the spread of the novel coronavirus disease 2019 (COVID-19) in China, many anthropogenic activities were reduced and even closed on the national scale. To study the impact of this reduction and closing down, hourly concentrations of PM 2.5 -related elements were measured at a rural site before (12-25 January 2020), during (26 January-9 February 2020) and after (22 March-2 April 2020) the control period when all people remained socially isolated in their homes and could not return to economic zones for work. Nine major sources were identified by the positive matrix factorization model, including fireworks burning, coal combustion, vehicle emissions, dust, Cr industry, oil combustion, Se industry, Zn smelter, and iron and steel industry. Before the control period, K, Fe, Ca, Zn, Ba and Cu were the main elements, and fireworks burning, Zn smelter and vehicle emissions provided the highest contributions to the total element mass with 55%, 12.1% and 10.3%, respectively. During the control period, K, Fe, Ba, Cu and Zn were the dominating elements, and fireworks burning and vehicle emissions contributed 55% and 27% of the total element mass. After the control period, Fe, K, Ca, Zn and Ba were the main elements, and dust and iron and steel industry were responsible for 56% and 21% of the total element mass. The increased contribution from vehicle emissions during the control period could be attributed to our sampling site being near a town hospital and the fact that the vehicle activities were not restricted. The source apportionment results were also related to air mass backward trajectories. The largest reductions of dust, coal combustion, and the industrial sources (Cr industry, Zn smelter, Se industry, iron and steel industry) were distinctly seen for northwest transport (Ulanqab) and were least significant for northeast transport (Tangshan and Tianjin)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The novel coronavirus disease (COVID-19) is a highly pathogenic, transmittable and invasive pneumococcal disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which emerged in December 2019 and January 2020 in Wuhan city, Hubei province, China and fast spread later on the middle of February 2020 in the Northern part of Italy and Europe. This study investigates the correlation between the degree of accelerated diffusion and lethality of COVID-19 and the surface air pollution in Milan metropolitan area, Lombardy region, Italy. Daily average concentrations of inhalable particulate matter (PM) in two size fractions PM2.5, PM10 and maxima PM10 ground level atmospheric pollutants together air quality and climate variables (daily average temperature, relative humidity, wind speed, atmospheric pressure field and Planetary Boundary Layer-PBL height) collected during 1 January-30 April 2020 were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces, or direct human-to-human personal contacts, it seems that high levels of urban air pollution, weather and specific climate conditions have a significant impact on the increased rates of confirmed COVID-19 Total number, Daily New and Total Deaths cases, possible attributed not only to indoor but also to outdoor airborne bioaerosols distribution. Our analysis demonstrates the strong influence of daily averaged ground levels of particulate matter concentrations, positively associated with average surface air temperature and inversely related to air relative humidity on COVID-19 cases outbreak in Milan. Being a novel pandemic coronavirus (SARS-CoV-2) version, COVID-19 might be ongoing during summer conditions associated with higher temperatures and low humidity levels. Presently is not clear if this protein "spike" of the new coronavirus COVID-19 is involved through attachment mechanisms on indoor or outdoor airborne aerosols in the infectious agent transmission from a reservoir to a susceptible host in some agglomerated urban areas like Milan is., Competing Interests: Declaration of competing interest The authors declare no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 National Institute of R&D for Optoelectronics INOE 2000. Published by Elsevier B.V. All rights reserved.)

The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, -0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between -9.41 °C and -13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (<0 °C) was exponentially associated with an increased transmission rate of COVID-19. These findings suggest that the mitigation of COVID-19 spread in densely populated and/or cold regions will be a great challenge., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)