Spatial and Temporal Distributions of Ionospheric Irregularities Derived from Regional and Global ROTI Maps

Major advancements in the monitoring of both the occurrence and impacts of space weather can be made by evaluating the occurrence and distribution of ionospheric disturbances. Previous studies have shown that the fluctuations in total electron content (TEC) values estimated from Global Navigation Satellite System (GNSS) observations clearly exhibit the intensity levels of ionospheric irregularities, which vary continuously in both time and space. The duration and intensity of perturbations depend on the geographic location. They are also dependent on the physical activities of the Sun, the Earth’s magnetic activities, as well as the process of transferring energy from the Sun to the Earth. The aim of this study is to establish ionospheric irregularity maps using ROTI (rate of TEC index) values derived from conventional dual-frequency GNSS measurements (30-s interval). The research areas are located in Southeast Asia (15°S–25°N latitude and 95°E–115°E longitude), which is heavily affected by ionospheric scintillations, as well as in other regions around the globe. The regional ROTI map of Southeast Asia clearly indicates that ionospheric disturbances in this region are dominantly concentrated around the two equatorial ionization anomaly (EIA) crests, occurring mainly during the evening hours. Meanwhile, the global ROTI maps reveal the spatial and temporal distributions of ionospheric scintillations. Within the equatorial region, South America is the most vulnerable area (22.6% of total irregularities), followed by West Africa (8.2%), Southeast Asia (4.7%), East Africa (4.1%), the Pacific (3.8%), and South Asia (2.3%). The generated maps show that the scintillation occurrence is low in the mid-latitude areas during the last solar cycle. In the polar regions, ionospheric irregularities occur at any time of the day. To compare ionospheric disturbances between regions, the Earth is divided into ten sectors and their irregularity coefficients are calculated accordingly. The quantification of the degrees of disturbance reveals that about 58 times more ionospheric irregularities are observed in South America than in the southern mid-latitudes (least affected region). The irregularity coefficients in order from largest to smallest are as follows: South America, 3.49; the Arctic, 1.94; West Africa, 1.77; Southeast Asia, 1.27; South Asia, 1.24; the Antarctic, 1.10; East Africa, 0.89; the Pacific, 0.32; northern mid-latitudes, 0.15; southern mid-latitudes, 0.06.

Transmission of COVID-19 from community to healthcare agencies and back to community: a retrospective study of data from Wuhan, China

BackgroundThe early spatiotemporal transmission of COVID-19 remains unclear. The community to healthcare agencies and back to community (CHC) model was tested in our study to simulate the early phase of COVID-19 transmission in Wuhan, China.MethodsWe conducted a retrospective study. COVID-19 case series reported to the Municipal Notifiable Disease Report System of Wuhan from December 2019 to March 2020 from 17 communities were collected. Cases from healthcare workers (HW) and from community members (CM) were distinguished by documented occupations. Overall spatial and temporal relationships between HW and CM COVID-19 cases were visualised. The CHC model was then simulated. The turning point separating phase 1 and phase 2 was determined using a quadratic model. For phases 1 and 2, linear regression was used to quantify the relationship between HW and CM COVID-19 cases.ResultsThe spatial and temporal distributions of COVID-19 cases between HWs and CMs were closely correlated. The turning point was 36.85±18.37 (range 15–70). The linear model fitted well for phase 1 (mean R2=0.98) and phase 2 (mean R2=0.93). In phase 1, the estimated α^s were positive (from 18.03 to 94.99), with smaller β^s (from 2.98 to 15.14); in phase 2, the estimated α^s were negative (from −4.22 to −81.87), with larger β^s (from 5.37 to 78.12).ConclusionTransmission of COVID-19 from the community to healthcare agencies and back to the community was confirmed in Wuhan. Prevention and control measures for COVID-19 in hospitals and among HWs are crucial and warrant further attention.

Spatial and temporal distribution characteristics of ground-level nitrogen dioxide and ozone across China during 2015-2020

In recent years, the emissions control in nitrogen oxides (NOx) was conducted across China, and how the concentrations of NOx and its product ozone (O3) in the atmosphere varied in space and time remains uncertain. Here, the spatial and temporal distributions of nitrogen dioxide (NO2) and O3 in 348 cities of China based on the hourly concentrations data during 2015-2020 were investigated, and the relationships among NO2, O3 and meteorological and socioeconomic parameters were explored. It is shown that higher NO2 and O3 concentrations were mainly distributed in North, East and Central China, where are economically developed and densely populated regions. The annual mean concentrations of NO2 increased by 4% from 2015 to 2017 but decreased by 17% from 2017 to 2020. The annual variations in O3 generally exhibited an upward trend in 2015-2019 but decreased by 5% from 2019 to 2020. 74% and 78% of cities had a decline in NO2 and O3 in 2020, respectively, compared to 2019, due to the limits of the motorized transports and industrial production activities during COVID-2019 lockdown. The monthly mean concentrations of NO2 showed an unusual decrease in February in all regions due to the reduced emissions during the Chinese Spring Festival holidays. Compared to 2019, the mean concentrations of NO2 in January, February and March, 2020 during COVID-2019 lockdown decreased by 16%, 28% and 20%, respectively, but O3 increased by 13%, 14% and -2%, respectively. Correlation analysis showed that NO2 and O3 concentrations are likely associated with anthropogenic emissions, including energy consumption, burning fossil fuel, and vehicle exhaust emissions. In addition, meteorological parameters can affect NO2 and O3 concentrations by influencing the production process, the diffusion and local accumulation and the regional circulations.

Satellite-Based Analysis of Spatial–Temporal Distributions of NH3 and Factors of Influence in North China

NH3 is an important part of the global nitrogen cycle as the most important atmospheric alkaline gas. NH3 reacts rapidly with acidic substances and accelerates the generation of particulate matter (PM2.5), which has important effects on the atmosphere and climate change. In this study, satellite NH3 column data were used to analyze spatial and temporal distributions of NH3 in China, and because of high concentrations and rates of change, North China was selected for more detailed analysis. Qualitative analysis was conducted to understand the relations between concentrations of NH3 and those of SO2 and NO2. Last, the random forest method was used to quantify relations between concentrations of atmospheric NH3 and factors influencing those concentrations, such as meteorological factors, NH3 self-emission, and concentrations of SO2 and NO2. Satellite-retrieved NH3 column concentrations showed an increasing trend during the 11 years from 2008 to 2018, and the rate of increase in summer was faster than that in winter. In those 11 years, NH3 self-emission had the greatest influence on NH3 concentrations. Concentrations of SO2 and NO2 had some effect and were negatively correlated with NH3 concentrations. The effect of SO2 on NH3 concentration was greater than that of NO2. Atmospheric NH3 concentration was also affected by meteorological conditions (temperature, relative humidity, pressure, and wind). In summer, temperature is the most important factors of meteorological conditions and relative humidity is the most important factors in winter. Therefore, to better control atmospheric NH3 concentrations, it is particularly important to formulate practical NH3 emission reduction policies and to consider the effects of SO2 and NO2 emission reduction policies.

Spatial and Temporal Distributions of Air Pollutants in Nanchang, Southeast China during 2017–2020

In response to COVID-19 in December 2019, China imposed a strict lockdown for the following two months, which led to an unprecedented reduction in industrial activities and transportation. However, haze pollution was still recorded in many Chinese cities during the lockdown period. To explore temporal and spatial variations in urban haze pollution, concentrations of air pollutants (PM2.5, PM10, SO2, CO, NO, NO2, and O3) from April 2017 to March 2020 were observed at 23 monitoring stations throughout Nanchang City (including one industrial site, sixteen urban central sites, two mountain sites, and four suburban sites). Overall, the highest concentrations of PM2.5, PM10, and SO2 were observed at industrial sites and the highest CO and NOx (NO and NO2) concentrations were recorded at urban sites. The air pollutants at mountain sites all showed the lowest concentrations, which indicated that anthropogenic activities are largely responsible for air pollutants. Concentrations of PM2.5, PM10, CO, NO, and NO2 showed similar season trends, that is, the highest levels in winter and lowest concentrations in summer, but an opposite season pattern for O3. Except for a sharply dropping pattern from January to May 2018, there were no seasonal patterns for SO2 concentration in all the observed sites. Daily PM2.5, PM10, CO, NOx, and SO2 concentrations showed a peak during the morning commute, which indicated the influences of anthropogenic activities on PM2.5, PM10, CO, NOx, and SO2. PM2.5, PM10, NOx, and CO concentrations at industrial, urban, and suburban sites were higher during nighttime than during daytime, but they showed the opposite pattern at mountain sites. In addition, PM2.5, PM10, CO, and NOx concentrations were lower during the lockdown period (D2) than those before the lockdown (B1). After the lockdown was lifted (A3), PM2.5, PM10, CO, and NOx concentrations showed a slowly increasing trend. However, O3 concentrations continuously increased from B1 to A3.

Transport and Variability of Tropospheric Ozone over Oceania and Southern Pacific during the 2019–20 Australian Bushfires

The present study contributes to the scientific effort for a better understanding of the potential of the Australian biomass burning events to influence tropospheric trace gas abundances at the regional scale. In order to exclude the influence of the long-range transport of ozone precursors from biomass burning plumes originating from Southern America and Africa, the analysis of the Australian smoke plume has been driven over the period December 2019 to January 2020. This study uses satellite (IASI, MLS, MODIS, CALIOP) and ground-based (sun-photometer, FTIR, ozone radiosondes) observations. The highest values of aerosol optical depth (AOD) and carbon monoxide total columns are observed over Southern and Central Australia. Transport is responsible for the spatial and temporal distributions of aerosols and carbon monoxide over Australia, and also the transport of the smoke plume outside the continent. The dispersion of the tropospheric smoke plume over Oceania and Southern Pacific extends from tropical to extratropical latitudes. Ozone radiosonde measurements performed at Samoa (14.4°S, 170.6°W) and Lauder (45.0°S, 169.4°E) indicate an increase in mid-tropospheric ozone (6–9 km) (from 10% to 43%) linked to the Australian biomass burning plume. This increase in mid-tropospheric ozone induced by the transport of the smoke plume was found to be consistent with MLS observations over the tropical and extratropical latitudes. The smoke plume over the Southern Pacific was organized as a stretchable anticyclonic rolling which impacted the ozone variability in the tropical and subtropical upper-troposphere over Oceania. This is corroborated by the ozone profile measurements at Samoa which exhibit an enhanced ozone layer (29%) in the upper-troposphere. Our results suggest that the transport of Australian biomass burning plumes have significantly impacted the vertical distribution of ozone in the mid-troposphere southern tropical to extratropical latitudes during the 2019–20 extreme Australian bushfires.