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Concentration–QTc (C–QTc) modeling is being increasingly used in phase 1 studies. For studies without a placebo arm (single arm studies), the scientific whitepaper by Garnett et al. ( https://doi.org/10.1007/s10928-017-9558-5 ) states that time-matched baseline adjustments may minimize the effect of diurnal variation in QTc intervals, and categorical time effects are not needed in the model. However, how diurnal variations can be accounted for when only pre-dose baselines are available is unclear. This research investigates whether including categorical time effects in the model can adjust diurnal variation in single arm studies with pre-dose baselines, where QTc prolongation is evaluated at a concentration of interest based on ΔQTc at 24 h and ΔΔQTc (a model-derived difference in ΔQTc from concentration zero). To understand the operating characteristics for the models with and without categorical time effects, simulations were conducted under various scenarios considering oncology early phase studies. When the C–QTc relationship is linear, models without categorical time effects provided biased estimates for model parameters and inflated or decreased false negative rates (FNRs) depending on the pattern of diurnal variations in QTc intervals, whereas models with categorical time effects caused no biases and controlled the FNRs. For non-linear C–QTc relationships, ΔΔQTc estimations made using the model with categorical time effects were not robust. Thus, for single arm studies where only pre-dose baselines are available, we recommend collecting QTc measurements at 24 h and estimating ΔQTc at a concentration of interest at 24 h using the C–QTc model with categorical time effects.

Diurnal temperature range (DTR) is one of the climate indicators likely to be related to human health. The purpose of this study was to investigate the relation between mortality and DTR in Kerman, Iran. The DLNM (Distributed Lag Non-linear Model)with a quas/i-Poisson regression model was used to evaluate the effect of DTR on mortality in age and sex groups by controlling the confounding variables (long-term trend of daily mortality, effect of day of the week, holidays, mean temperature, humidity, and air pollution). Since DTR effects on mortality may vary in cold and warm seasons, separate analyses were conducted for cold and warm seasons. DTR showed a non-linear relation with mortality. Mortality increased at the 90th percentile of DTR (CRR = 1.16, 95% CI 1.00–1.34), in lag 0–21 and at the 10th percentile of DTR in lag 0–13 (1.27, 95% CI 1.06–1.52), and lag 0–21 1.35 (95% CI 1.06–1.71). Increased mortality was more observed in the > 60 age group and in men. High levels of DTR after long lags (13 days) in the cold season were associated with increasing mortality. High and low diurnal temperature range may be a risk factor for mortality, especially in the men and elderly.

International audience; Summertime HONO concentrations were synchronously measured at two (agricultural and nonagricultural) sites in the North China Plain (NCP). Daytime HONO (1.4 ± 0.6 ppbv) and HONO/NO2 ((12 ± 8)%) over the agricultural field after fertilization were found to be remarkably higher than those before fertilization, implying strong HONO emission from the fertilized fields. Synchronous enhancements of HONO and O3 after fertilization at both sites suggested that the emitted HONO accelerated the local and the regional O3 pollution. HONO budget analysis further revealed that its emission was significantly enhanced after fertilization. Soil HONO emission flux and its uncertainty were estimated and discussed. The estimated emission flux exhibited a distinct diurnal variation with a noontime maximum. The net OH production rate from HONO photolysis greatly exceeded that from O3 photolysis over the agricultural field, and their maximum ratio of 4.7 was obtained after fertilization. We provide field evidence that fertilized fields in the NCP act as a strong HONO source, which accelerates daytime photochemistry, leading to an increase of regional photo-oxidants such as O3. Considering the severe O3 pollution in the summer NCP and that the large area of the agricultural field is regularly treated with high fertilization amount in this region, HONO emission should be taken into account in the regional air quality deterioration.

Eveningness, as opposed to other chronotypes, in childhood and adolescence is associated with more parental conflicts, such as regarding bed and rising times, which might adversely influence future relationships with parents, and adult attachments. The current survey of 524 Chinese university students (mean = 20.05 and range 18-36 years of age) investigated whether eveningness shows these adverse associations. Morning affect and amplitude distinctness facets of circadian functioning were also assessed. It was found that eveningness is not related to adults' perception of current parental relationships, or to adult attachment security, but low morning affect and stronger amplitude distinctness were associated with perception of more fatherly control, less regard for parents, and more attachment insecurity, and these were related to poorer wellbeing. These findings indicate that components of circadian functioning are related to the quality of adult relationships. Further research is needed to confirm these findings and establish explanatory mechanisms for these associations.

Monitoring of air quality is demanding, especially in poor air quality regions. China has been suffering from PM2.5 pollution associated with the fast urbanization and economic productivity. The purpose of this work is to analyze PM2.5 with regard to air quality for five populated cities (Beijing, Chengdu, Guangzhou, Shanghai and Shenyang) of China. In this study, hourly concentration of PM2.5 is decomposed into annual and seasonal concentrations and is evaluated. The results show the downward trend of PM2.5 for Beijing and Chengdu from 2013 to 2016 and for Guangzhou from 2012 to 2016, but no clear trend is observed for Shanghai and Shenyang. Although trend is decreasing for three cities (Beijing, Chengdu, Guangzhou), but overall annual average is found higher than the annual U.S. national ambient air quality standards for PM2.5. Among all five cities, highest annual PM2.5 concentration is found to be 104.1 µgm−3for Beijing in 2010 and lowest (32.6 µgm−3) is found for Guangzhou in 2016. The diurnal variation is high during night for Beijing, Guangzhou and Shanghai and it is high after morning rush hours for Chengdu and Shenyang (during April 2008–June 2017), respectively. In all studied sites, the seasonal variability is found highest in winter and lowest in the summer. Due to more contribution from biomass burning and dust, high PM2.5 variation is also found in the autumn and spring, respectively. To the best of our knowledge, this is the first study for Guangzhou, Chengdu and Shenyang that explores PM2.5 concentration for 5 years.

HighlightsAnnual average PM10 (daily) and PM2.5 (hourly) concentrations of 509 ±203 and 43.3 ±36.1 µg m-3, respectively.Significant seasonal and diurnal variations in PM concentrations; higher in colder seasons and during daytime.Annual average PM10 (daily) and PM2.5 (hourly) emission rates of 17.9 ±9.6 and 1.41 ±1.53 mg d-1 hen-1, respectively.Significant diurnal variations in PM emission rates but inconsistent seasonal variations; higher during daytime.Abstract. Particulate matter (PM) concentration and emission rate information is needed to assess air quality concerns and environmental impacts related to egg production. Many egg layer buildings were retrofitted from high-rise to manure-belt houses over the past few decades. However, no studies have reported these PM data for the retrofitted layer houses. In this study, concentrations and emission rates of PM10 and PM2.5 were continuously monitored for 12 months at two commercial retrofitted manure-belt layer houses in the Midwestern U.S. The average daily mean PM10 and average hourly mean PM2.5 concentrations in the houses were 509 ±203 µg m-3 and 43.3 ±36.1 µg m-3, respectively. Significant seasonal and diurnal variations in PM concentrations were observed, with higher concentrations in colder seasons and during daytime. The average daily mean PM10 and average hourly mean PM2.5 emission rates from the two houses were 17.9 ±9.6 mg d-1 hen-1 and 1.41 ±1.53 mg d-1 hen-1, respectively. There were no consistent patterns in seasonal variations. Significant diurnal variations were also observed for PM emission rates, with higher PM emission rates observed during daytime. The PM concentrations were significantly correlated with ambient temperature, ventilation rate, bird age, egg production, daily mortality, and feed conversion ratio, while PM emission rates were significantly correlated with ambient temperature, bird age, bird mass, egg mass, and ventilation rate. Keywords: Diurnal variation, Dust, Egg production, PM, Poultry, Seasonal variation.

The urinary 8-hydroxy-2'-deoxyguanosine levels have been widely used as a biomarker of oxidative stress. The purpose of this study is to investigate the diurnal and day-to-day variations of urinary 8-hydroxy-2'-deoxyguanosine levels. For the diurnal variation, the urine samples were collected at the time of awakening and every 2 h, from 10:00 to 22:00, from 6 healthy participants. For the day-to-day variation, the urine samples were collected at the time of awakening for 35 consecutive days, from 27 healthy participants. As a result, no differences were observed in the diurnal urinary 8-hydroxy-2'-deoxyguanosine levels, and each subject had a characteristic 8-hydroxy-2'-deoxyguanosine level. On the other hand, the daily 8-hydroxy-2'-deoxyguanosine values showed a certain range of variation reflecting lifestyle factors, such as stress status, exercise, sleep time, drinking and diet. In conclusion, urinary 8-hydroxy-2'-deoxyguanosine may be a useful biomarker to control and prevent oxidative stress-related diseases, if the certain range of day-to-day variations of urinary 8-hydroxy-2'-deoxyguanosine is known. Even with only one measurement per year, the baseline urinary 8-hydroxy-2'-deoxyguanosine level could be achieved in a few years by incorporating the 8-hydroxy-2'-deoxyguanosine measurement as part of an annual health check. As the number of subjects was limited, further studies are needed for practical applications.

Heart failure increases among the elderly; however, the influence of ambient temperature on cardiorenal function has not been well investigated. Patients (n = 110, mean age 82.9 years, 43 males) with stable heart failure and creatinine < 3.0 mg/dl were studied. Medical records, such as ejection fraction, B-type natriuretic peptide (BNP), and estimated glomerular filtration rate (eGFR) at each visit every 1-3 months were collected by the end-point for death, additional prescription to treat heart failure, or heart failure hospitalization. The ambient temperatures at each visit were obtained from the Japan Meteorological Agency. During the follow-up period (median 399 days and 7 visits), follow-up BNP showed a trend toward a positive correlation with the diurnal temperature range. After dividing into two groups by median baseline eGFR, follow-up BNP was positively correlated with minimum temperature (p = 0.039) and the diurnal temperature range (p = 0.007) in the Low-eGFR group but not in the High-eGFR group. Follow-up eGFR was negatively correlated with the ambient day temperature in both groups (p ≤ 0.002). Follow-up BNP was positively correlated with follow-up eGFR (p < 0.0001) only in the Low-eGFR group and not in the High-eGFR group, suggesting that BNP and eGFR increase in winter and BNP and eGFR decrease in summer in the Low-eGFR group. In conclusions, heart failure may be worsened by larger diurnal temperature range or in winter in patients with renal impairment. This population should be carefully managed in the clinic according to the ambient temperature.

High spatiotemporal resolution land surface temperature (LST) plays an important role in various environment applications. However, the limitation of thermal infrared sensors and the effect of clouds and other atmospheric conditions result in discontinuous daily thermal observations of the Moderate Resolution Imaging Spectroradiometer (MODIS). Annual temperature cycle (ATC) models can help to supply daily continuous LSTs via limited observations, but these ATC models seldom consider the disturbance of weather conditions or the land cover change. On the other hand, spatial interpolation techniques also limit in implementation when available data in one day or several days are not able to obtain enough spatiotemporal information for LST reconstruction. The objective of this study is to propose a phenology-based ATC model (termed PATC), which takes the phenology change and local weather change into account, to reconstruct daily unscanned LSTs at an annual scale. Daily MODIS LSTs collected in 2015 were utilized to analyze the performance of PATC compared with other ATC models. Results show that PATC improved the accuracy by 1.6 and 0.5 K compared to the classic ATC model in the daytime and nighttime, respectively. Compared to the enhanced ATC model, PATC also shows better performance with higher accuracies, especially during the growing season of vegetation in the daytime. Future research may focus on an incorporation with Landsat observations and diurnal temperature cycle models to implement LST reconstruction at a diurnal scale.

As a crucial absorptive component of aerosols, black carbon (BC) plays a key role in modifying the planetary boundary layer (PBL) meteorology and hence aggravating the haze pollution. In this study, using the seven-channel Aethalometer model AE-33, the equivalent BC aerosols were continuously observed for one year in a typical city of Nanjing in the Yangtze River Delta (YRD). Together with the pollutant data of PM2.5 and trace gases (NO2, SO2, CO and O3), and the methods of potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models, the spatiotemporal distribution and source apportionment of BC mass concentrations in Nanjing are discussed. It had large discrepancies in monthly and seasonal variations of BC concentrations, which were found to be the highest in December (3109.4 ± 1875.0 ng m−3) and the lowest in September (1300.8 ± 1031.6 ng m−3). Meanwhile, the BC concentrations ranked in the order of winter (2619.5 ± 1576.8 ng m−3) > spring (2142.4 ± 1219.3 ng m−3) > summer (1645.6 ± 1229.7 ng m−3) > autumn (1583.1 ± 1333.1 ng m−3). The diurnal variation of BC exhibited bimodal distributions in four seasons, peaking at 07:00–09:00 and 20:00–23:00, respectively. Fossil fuel BC (BCff) was calculated to contribute 71–77% to BC concentration. Long-range transport of BC was noticed mainly across inland China of North China Plain (NCP) and Twain-Hu regions in winter, and from the eastern YRD and southern PRD regions in summer. Overall, BC in Nanjing mainly originated from the surrounding cities in YRD, which had a maximum contribution more than 2000 ng m−3. The potential sources of BC varied significantly in the four seasons.

An experimental study on the effect of weather conditions such as solar radiation, humidity, temperature, and rain on the Long Range (LoRa) communication in a tropical region (Malaysia) via a campus environment has been carried out and analyzed. The weather parameters were obtained from an online meteorological weather station (Meteoblue) and the use of a local automatic weather station. A temperature sensor was attached to the LoRa node to measure the onboard temperature. We analyze the diurnal variation and the effects of the weather condition based on the LoRa link in a LoRaWAN setup. A regular pattern of RSSI was observed with stronger RSSI values having a positive correlation with the atmospheric temperature, onboard temperature, and solar radiation during the day but degrades in late evenings. The positive correlation and pattern observed can be attributed to the prevailing metrological conditions and opens room for further research needed for propagation modeling. The RSSI signals and relative humidity, on the other hand, showed no correlation. Furthermore, strong RSSI signals were obtained when the atmospheric temperature was between 30 - 40 °C, and the onboard temperature between 40 - 50 °C. No significant impact was observed on the RSSI signals when the rainfall rates vary from 12 mm/h to 180 mm/h. The study presents useful information to be considered on the effects of weather conditions in the propagation model and deployment of LoRa for IoT communication.

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dates back to December 29, 2019, in Wuhan, China. It quickly spreads like wildfire to all continents in the following months. In Guinea, the first case of COVID-19 and death were all reported respectively on March 12 and April 16, 2020. Since then, several studies have found a relationship between certain environmental conditions such as the meteorological factors to have the potential of contributing to the spread of the virus. Thus, this study aims at examining the extent to which observed meteorological factors might have contributed to the spread of the coronavirus disease 2019 (COVID-19) cases in Conakry, from March 1 to May 31, 2020. Meteorological factors such as temperature (Tmin, Tmean and Tmax) and relative humidity (RHmin, RHmean and RHmax) were analyzed together with the data on the COVID-19. The dynamic of the COVID-19 in Guinea was analyzed along with that of some west African countries. The analysis on the dynamic of the COVID-19 pandemic in West Africa indicated Guinea as one of the most affected countries by the pandemic after Nigeria and Ghana. The study found that in general an increase in the temperature is linked to a decline in the COVID-19 number of cases and deaths, while an increase in the humidity is positively correlated to the number of cases and deaths. Nevertheless, from this study it was also observed that low temperature, mild diurnal temperature and high humidity are likely to favor its transmission. The study therefore, recommends that habitations and hospital rooms should be kept in relatively low humidity and relatively higher temperature to minimize the spread of the (SARS-CoV-2).

This study aimed to forecast temperature variations in the western and southwestern part of Iran using a general circulation model and artificial neural networks (ANN). The data included mean diurnal temperatures from synoptic stations, National Centers for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) reanalysis data, and outputs of a third-generation global climate model, the Hadley Centre Coupled Model version 3 (HadCM3), under A2 and B2 scenarios for the baseline period (1961–1990). The data of the first (1961–1975) and second 15 years (1976–1990) of the baseline period were used for model calibration and validation, respectively. Both models, however, produced reliable estimates at the plain stations with neither outperforming the other due to their negligible errors. However, the neural network results of mountain synoptic stations showed a lower error rate than the statistical downscaling model (SDSM) outputs. All in all, we can say that there was a larger amount of error in the outputs of the atmospheric general circulation models (AGCMs) in the mountainous regions. According to the outputs of the neural network and the AGCMs, temperatures at the studied stations were on the rise. In fact, this increase was more noticeable at the plain stations. This can be attributed to their proximity to the sea, to their latitude, and to the more intensive industrial activities (especially, extraction of petroleum and production of petroleum products) taking place near the plain stations.

Most dairy cows experience a period of energy deficit in early lactation, resulting in increased plasma concentrations of nonesterified fatty acids (NEFA) and β-hydroxybutyrate (BHB). Our objectives were to determine (1) the diurnal variation in plasma BHB and NEFA, (2) the correlation between plasma NEFA and BHB when accounting for diurnal changes, and (3) the effect of hyperketonemia (HYK) on the diurnal pattern of blood metabolites. Jugular catheters were placed in 28 multiparous Holstein cows between 3 and 9 days in milk, and blood samples were collected every 2 h for 96 h. Cows were retrospectively classified as HYK positive (HYK; n = 13) if they had plasma BHB concentrations ≥1.2 mmol/L for ≥3 study days, or HYK negative (non-HYK; n = 15) if they had plasma BHB concentrations ≥1.2 mmol/L for ≤2 study days. Generalized linear mixed models were used to analyze concentrations of analytes over time and differences in metabolites between HYK groups. The correlation between total plasma NEFA and BHB was analyzed by calculating the area under the curve for plasma NEFA and BHB for all cows. Plasma NEFA reached a peak approximately 2 h before morning feed delivery, falling to a nadir in the late evening. Plasma BHB was at a nadir at the time of morning feed delivery, peaking 4 h later. We observed a strong positive correlation between daily plasma NEFA and BHB. Additionally, HYK cows had greater concentrations of plasma NEFA and BHB than non-HYK cows. The HYK cows also experienced a greater magnitude of change in BHB throughout the day than the non-HYK cows. Our results suggest that the time relative to feeding should be considered when analyzing plasma metabolites, as classification of energy status may change throughout a day.

International audience; Photochemical aging of volatile organic compounds (VOCs) in the atmosphere is an important source of secondary organic aerosol (SOA). To evaluate the formation potential of SOA at an urban site in Lyon (France), an outdoor experiment using a Potential Aerosol Mass (PAM) oxidation flow reactor (OFR) was conducted throughout entire days during January-February 2017. Diurnal variation of SOA formations and their correlation with OH radical exposure (OHexp), ambient pollutants (VOCs and particulate matters, PM), Relative Humidity (RH), and temperature were explored in this study. Ambient urban air was exposed to high concentration of OH radicals with OHexp in range of (0.2–1.2)×1012 molecule/(cm3•sec), corresponding to several days to weeks of equivalent atmospheric photochemical aging. The results informed that urban air at Lyon has high potency to contribute to SOA, and these SOA productions were favored from OH radical photochemical oxidation rather than via ozonolysis. Maximum SOA formation (36 µg/m3) was obtained at OHexp of about 7.4 × 1011molecule/(cm3•sec), equivalent to approximately 5 days of atmospheric oxidation. The correlation between SOA formation and ambient environment conditions (RH & temperature, VOCs and PM) was observed. It was the first time to estimate SOA formation potential from ambient air over a long period in urban environment of Lyon.

The immense reduction in aerosol levels during the COVID-19 pandemic provides an opportunity to reveal how atmospheric chemistry is regulating our climate, among which the effect of aerosols on climate is a phenomenon of great interest but still in hot debate. The Intergovernmental Panel on Climate Change (IPCC) has continually identified the effect of aerosols on climate to have the largest uncertainty among the factors contributing to global climate change. Several studies indicate an inverse relationship between aerosol presence in the atmosphere and the diurnal surface air temperature range (DTR). Herein, we test this relationship by analyzing the DTR values from in situ weather station records for periods before and during the COVID-19 epidemic in China where aerosol levels have substantially reduced, compared with the climatological mean levels for a 19 year period. Our analyses find that DTRs from February to June during the COVID-19 pandemic are greater than 3 standard deviations above the climatological mean DTR. This anomaly has never occurred before in the 21st century and is at least in part associated with the observed reduction in aerosols.

Free thyroxin hormones FT4 and FT3 are unbounded thyroid hormone are biologically active and involves in regulation of metabolism. Measuring the concentrations of free thyroid hormones is of great diagnostic value. A cross sectional study was carried out during the March 2019 to September 2019 in patients between 18 years to 60 years. A total of 60 samples were collected from 30 patients attending Karpaga Vinayaga Institute of Medical Sciences at morning (6am-8am) and 2nd sampling at night (8pm-9pm). FT4, FT3 and TSH were measured by Enzyme linked immunosorbent assay, using Avantor kit.In our study 36.67% participants were males, 63.3% participants were females. The mean FT3, FT4 and TSH in day are 2.43±0.56, 1.14±0.44 and 2.74±3.16 respectively. The mean night FT3, FT4 and TSH are 2.66±0.55, 1.3±0.61 and 3.21±3.18 respectively. The one sample t test shows difference of FT3, t 4.489 and p value 0.000, FT4, t value 3.092 and p value 0.004 and TSH t value 3.394 and p value 0.002. The time of blood sampling has an important role in the interpretation of TSH levels. However fluctuations in diurnal variations in thyroid hormone levels are less. In our study although statistically significant, all the values are within the normal biological reference interval Further studies in larger cohorts is essential to desire important conclusions.

Diurnal variation of precipitation is a fundamental periodic signal of local climate. Comprehensive study of diurnal variation of precipitation is helpful in studying the formation of local climate and validating satellite precipitation products. In this study, a comparison is drawn between precipitation gauge observations and Tropical Rainfall Measuring Mission (TRMM) 3B42 data on diurnal variation of precipitation. First, using the K-means clustering algorithm, stations with gauge observations and pixels with TRMM data are divided into different groups according to the diurnal variation of precipitation, respectively. In each group, the stations have similar diurnal variation of precipitation. Then maps of diurnal variation of precipitation for gauge observations and TRMM data are obtained. According to these maps, the diurnal variation of precipitation over the contiguous United States (CONUS) presents seasonal variability in both gauge observations and TRMM data. In addition, the diurnal variation of precipitation shows clustered features in space. However, the spatial patterns of the obtained maps do not match, and the TRMM satellite data perform poorly in capturing the hourly precipitation event. Finally, the possible mechanism behind the prevailing nocturnal precipitation over the middle of the CONUS is discussed, with the prevailing nocturnal precipitation judged likely to be strongly related to the mountain-plains solenoid (MPS) circulation.

PurposeThe paper aims to determine the thermal comfort perception of schoolchildren from a warm and humid environment. There is a concern about the effect of high temperature on the health and academic performance of schoolchildren.Design/methodology/approachObjective and subjective methodological approaches were adopted to collect data during the fieldwork in the selected primary schools. ASHRAE adaptive comfort model was adopted to analyze the data.FindingsThe paper provided empirical results about the comfort requirements of schoolchildren from the warm and humid environment. During the occupied school time, the studied schoolchildren were found to tolerate temperatures higher than the upper limit temperature recommended by ASHRAE Standard 55. The paper recommends that the studied children may not need any active ventilator to be thermally comfortable during the occupied school hoursOriginality/valueThe paper found the range of temperatures that schoolchildren from the warm and humid environment can adapt to. The information may be useful to architects, engineers and facility managers

SUMMARY Accurate models of the spatial structure of ionospheric magnetic fields in the diurnal variation (DV) band (periods of a few hours to a day) would enable use of magneto-variational methods for 3-D imaging of upper mantle and transition zone electrical conductivity. Constraints on conductivity at these depths, below what is typically possible with magnetotellurics, would in turn provide valuable constraints on mantle hydration and Earths deep water cycle. As a step towards this objective, we present here a novel approach to empirical modelling of global DV magnetic fields. First, we apply frequency domain (FD) principal components analysis (PCA) to ground-based geomagnetic data, to define the dominant spatial and temporal modes of source variability. Spatial modes are restricted to the available data sites, but corresponding temporal modes are effectively continuous in time. Secondly, we apply FD PCA to gridded surface magnetic fields derived from outputs of the physics-based Thermosphere–Ionosphere–Electrodynamics General Circulation Model (TIEGCM), to determine the dominant modes of spatial variability. The TIEGCM spatial modes are then used as basis functions, to fit (or interpolate) the sparsely sampled data spatial modes. Combining the two steps, we have a FD model of DV band global magnetic fields that is continuous in both space and time. We show that the FD model can easily be transformed back to the time domain (TD) to directly fit time-series data, allowing the use of satellite, as well as ground-based, data in the empirical modelling scheme. As an illustration of the methodology we construct global FD and TD models of DV band source fields for 1997–2018. So far, the model uses only ground-based data, from 127 geomagnetic observatories. We show that the model accurately reproduces surface magnetic fields in both active and quiet times, including those at sites not used for model construction. This empirical model, especially with future enhancements, will have many applications: improved imaging of electrical conductivity, ionospheric studies and improved external field corrections for core and crustal studies.

A targeted exploration of the dependence of seismic activity on the time of day continues for about a century and a half. During this time, numerous scientific studies have been done on the diurnal periodicity in the occurrence of earthquakes. In this work, we present the first results of a study of diurnal periodicity in the occurrence of weak earthquakes by the example of individual seismically active zones of the Zhongar North Tian Shan region. The research was performed on the data on number of earthquakes with energy classes (K = logE, J) equal to 5, 6, 7 and 8, which arose within the North Tian Shan (1), Zhongar (2), Halyktau (3) and Ketmen (4) zones. To do this, by counting the number of earthquakes of corresponding energy that occurred during each hour, a time series of hourly values of number of shocks for the entire time period was compiled. Then, using the method of superposition of periods, the number of seismic events for each hour over the entire time interval is summed up, and a graph of the average daily course of the number of earthquakes was compiled. Studies have established the existence of diurnal periodicity in the realization of weak earthquakes and microquakes. It was most clearly observed for seismic events with K ≤ 6 for the North Tien Shan, Zhongar, Ketmen, and K ≤ 7 for Halyktau zones. With an increase in energy class (magnitude) of earthquakes, the observed pattern weakens and practically disappears for shocks with K ≥ 7 for the earthquakes, Zhongar, Ketmen and with K ≥ 8 for the Halyktau zones. The obtained graphs of the diurnal sequence of seismicity are identical to the analogous curves of diurnal variation in the numbers of weak earthquakes allocated for other regions (areas) of the globe.

Summary Background Heart rate variability, or the variation in the time interval between consecutive heart beats, is a non-invasive dynamic metric of the autonomic nervous system and an independent risk factor for cardiovascular death. Consumer wrist-worn tracking devices using photoplethysmography, such as Fitbit, now provide the unique potential of continuously measuring surrogates of sympathetic and parasympathetic nervous system activity through the analysis of interbeat intervals. We aimed to leverage wrist-worn trackers to derive and describe diverse measures of cardiac autonomic function among Fitbit device users. Methods In this cross-sectional study, we collected interbeat interval data that are sent to a central database from Fitbit devices during a randomly selected 24 h period. Age, sex, body-mass index, and steps per day in the 90 days preceding the measurement were extracted. Interbeat interval data were cleaned and heart rate variability features were computed. We analysed heart rate variability metrics across the time (measured via the root mean square of successive RR interval differences [RMSSD] and SD of the RR interval [SDRR]), frequency (measured by high-frequency and low-frequency power), and graphical (measured by Poincare plots) domains. We considered 5 min windows for the time and frequency domain metrics and 60 min measurements for graphical domain metrics. Data from participants were analysed to establish the correlation between heart rate variability metrics and age, sex, time of day, and physical activity. We also determined benchmarks for heart rate variability (HRV) metrics among the users. Findings We included data from 8 203 261 Fitbit users, collected on Sept 1, 2018. HRV metrics decrease with age, and parasympathetic function declines faster than sympathetic function. We observe a strong diurnal variation in the heart rate variability. SDRR, low-frequency power, and Poincare S2 show a significant variation with sex, whereas such a difference is not seen with RMSSD, high-frequency power, and Poincare S1. For males, when measured from 0600 h to 0700 h, the mean low-frequency power decreased by a factor of 66·5% and high-frequency power decreased by a factor of 82·0% from the age of 20 years to 60 years. For females, the equivalent factors were 69·3% and 80·9%, respectively. Comparing low-frequency power between males and females at the ages of 40–41 years, measured from 0600 h to 0700 h, we found excess power in males, with a Cohen's d effect size of 0·33. For high-frequency power, the equivalent effect size was −0·04. Increased daily physical activity, across age and sex, was highly correlated with improvement in diverse measures of heart rate variability in a dose-dependent manner. We provide benchmark tables for RMSSD, SDRR, high and low frequency powers, and Poincare S1 and S2, separately for different ages and sex and computed at two times of the day. Interpretation Diverse metrics of cardiac autonomic health can be derived from wrist-worn trackers. Empirical distributions of heart rate variability can potentially be used as a framework for individual-level interpretation. Increased physical activity might yield improvement in heart rate variability and requires prospective trials for confirmation. Funding Fitbit.

The Cloud-Aerosol Transport System (CATS) lidar, on board the International Space Station (ISS), provides a new opportunity for studying aerosol vertical distributions, especially the diurnal variations, from space observations. In this study, we investigate the seasonal variations and diurnal cycles in the vertical aerosol extinction coefficients (AECs) over East Asia by taking advantage of 32 months of continuous and uniform aerosol measurements from the CATS lidar. Over the Tibetan Plateau, a belt of AECs at approximately 6 km between 30 and 38∘ N persistently exists in all seasons with an obvious seasonal variation. In summer, the aerosols at 6 km are identified as a mixture of both anthropogenic aerosols transported from India and coarse dust particles from Asian dust sources. In addition, the high AECs up to 8 km in summer over the Tibetan Plateau are caused by smoke aerosols from thermal dynamic processes. In fall and winter, the northern slope of the plateau is continuously influenced by both dust aerosols and polluted aerosols transported upslope from cities located at lower elevations in northwestern Asia. The diurnal variation in AECs in North China is mainly related to the diurnal variations in the transported dust and local polluted aerosols. Below 2 km, the AEC profiles in North China at 06:00 and 12:00 CST (China standard time) are significantly higher than those at 00:00 and 18:00 CST, reaching a maximum at midday. The aerosol vertical profiles over the Tarim Desert region in summer have obvious diurnal variations, and the AECs at 12:00 and 18:00 CST are significantly higher than those at 00:00 and 06:00 CST, which are induced by the strong diurnal variations in near-surface wind speeds. In addition, the peak in the AEC profiles has a significant seasonal variation, which is mainly determined by the boundary layer height.

Formaldehyde (HCHO) is a naturally occurring compound found in ambient air which can induce cancer and sick-building syndrome. It plays an important role in the formation of OH radicals, which are connected to the formation of various airborne chemicals. Herein, we present a simple modeling for the simulation of diurnal variations in the HCHO concentration of ambient air. This was achieved using data collected during different seasons from November 2015 to March 2017 at a suburban location in Toyama City (Japan), where non-methane hydrocarbon (NMHC) levels were low at sub carbon ppm (ppmC) order. The modeling was based on the assumption that photochemical reactions of methane were the major factor of secondary HCHO formation. The model took into account the production and decomposition of HCHO by photochemical reactions as well as its loss due to other reactions such as dry deposition. Accordingly, the model's equation contained terms for solar radiation, temperature, and methane concentration. The results predicted using the model showed good agreement with the experimental data observed on fine days, i.e., except rainy, foggy, and heavily cloudy days. The relationships between HCHO concentration and solar radiation/temperature on different days as well as the seasonal variation of HCHO concentration were also interpreted by the proposed model. This study contributes to the evaluation of the pollution levels of formaldehyde. Moreover, the model may be used to demonstrate the impact of increasing methane levels, with regard to global warming and the background levels of HCHO in the atmosphere.

It is an essential component of the operational weather forecast agencies to capture the diurnal behavior of the rainfall on the spatiotemporal scale by numerical models for its accurate prediction. In this study, the mean diurnal cycle of precipitation is investigated with (i) atmospheric model-based predictions, (ii) space-based estimates, and (iii) ground-based rainfall observations during the active phase of Indian monsoon. Further, high-resolution precipitation data are used to identify the characteristics features of the model forecasts. The variability of mean diurnal variations in rain rate and frequency of rain is analyzed to determine the characteristics feature of precipitation. It is found that precipitation activity over Western Ghats, Bay of Bengal regions, is maximum during late afternoon. The time of peak rain rate is advanced during day time. The active phase of monsoon has the highest amplitude of diurnal variation in precipitation. The variability in the specific humidity is increased during this active period. The numbers of rainy hours are highly varying in nature for the space-based rainfall estimation than the model.

The biophysical effects of reforestation and afforestation (herein jointly called re/afforestation) on the diurnal temperature cycle in European summer are investigated by analyzing a regional climate model (RCM) ensemble, established within the Land Use and Climate Across Scales Flagship Pilot Study (LUCAS FPS). With this RCM ensemble, two idealized experiments are performed for Europe, one with a continent with maximized forest cover, and one in which all forests are turned into grassland. First, an in-depth analysis of one ensemble member (“CCLM-VEG3D”) is carried out, to reveal the complex process chain caused by such land use changes (LUCs). From these findings, the whole ensemble is analyzed and principal biophysical effects of re/afforestation are derived. Results show that the diurnal temperature range is reduced at the surface (top of the vegetation) with re/afforestation. Most RCMs simulate colder surface temperatures Tsurf during the day and warmer Tsurf during the night. Thus, for the first time, the principal temperature interrelations found in observation-based studies in the midlatitudes could be reproduced within a model intercomparison study. On the contrary, the diurnal temperature range in the lowest atmospheric model level (Tair) is increased with re/afforestation. This opposing temperature response is mainly caused by the higher surface roughness of forest, enhancing the turbulent heat exchange. Furthermore, these opposing temperature responses demonstrate that the use of the diagnostic 2-m temperature (weighted interpolation between Tsurf and Tair) has a limited potential to assess the effects of re/afforestation. Thus, studies about the biophysical impacts of LUCs should investigate the whole near-surface temperature profile.

Meteorological conditions regulate particulate matter concentrations near the earth surface. This study investigates the impacts of meteorological conditions (yellow-dust events, wind-speed, relative humidity, days after rainfall, solar duration, downward short-wave radiation, and diurnal temperature range) on particulate matter concentration less than 10 ㎛ (PM10) and less than 2.5 ㎛ (PM2.5) and their ratio (PM2.5/PM10) by analyzing five years (2015-2019) of in-situ surface observations in Seoul. Our results show apparent impacts of meteorological conditions on PM2.5 and PM10 concentrations and their ratio: 1) decrease in PM2.5/PM10 during yellow-dust events, 2) negative (positive) relationships of PM2.5 and PM2.5/PM10 with wind-speed (relative humidity), and 3) increase in PM10 and PM2.5 concentrations with elapsed days after rainfall.

OBJECTIVE To investigate the effects of various biological factors on total protein concentration (TPC) and serum albumin levels in canine tears. ANIMALS STUDIED 10 healthy beagles (5 female, 5 male) were used. PROCEDURES Experiments were conducted on separate days, collecting tears with either capillary tubes or Schirmer strips, as follows: (i) Tear collection at 3 hours intervals (from 6 am to 12 am); and (ii) Tear collection before and 20 minutes following topical histamine application (1, 10, 375 mg/mL) to induce mild, moderate, and severe conjunctivitis, respectively. TPC and serum albumin were measured with infrared spectroscopy and ELISA, respectively. RESULTS Tear film TPC and serum albumin ranged from 9.7-26.1 mg/mL and 6.4-1662.6 µg/mL, respectively. Protein levels did not differ significantly among time points (P ≥ .080). Median coefficient of variation (CV%) was lower with Schirmer strips compared to capillary tubes for both TPC (12% vs 15%, P = .020) and serum albumin (57% vs 78%, P = .232). TPC (P

This paper aims to study the foF2 seasonal asymmetry diurnal variation at Dakar station from 1976 to 1995. We show that equinoctial asymmetry is less pronounced and somewhere is absent throughout 21 and 22 solar cycles. The absence of equinoctial asymmetry may be due to Russell-McPherron mechanism and the vertical drift E × B . The solstice anomaly or annual anomaly is always observed throughout both 21 and 22 solar cycles as measured at Dakar ionosonde. The maximum negative value of σfoF2, fairly equal to -65%, is observed during the decreasing phase at solstice time; this value appeared usually at 0200 LT except during the maximum phase during which it is observed at 2300 LT. The maximum positive value, fairly equal to +94%, is observed at 0600 LT during solar minimum at solstice time. This annual asymmetry may be due to neutral composition asymmetric variation and solar radiation annual asymmetry with the solstice time. The semiannual asymmetry is also observed during all solar cycle phases. The maximum positive value (+73%) is observed at 2300 LT during solar maximum, and its maximum negative (-12%) is observed during the increasing phase. We established, as the case of annual asymmetry, that this asymmetry could not be explained by the asymmetry in vertical velocity E × B phenomenon but by the axial mechanism, the “thermospheric spoon” mechanism, and the seasonally varying eddy mixing phenomenon.

Disinfection by-products (DBPs) discharged from sewage treatment plants (STPs) could harm downstream receiving waters and drinking water resources. In-stream attenuation of photo- and non-photodegradable DBPs during river transportation is currently not well understood. Here we sought to fill this knowledge gap by meta-data-analysis for modeling in-stream attenuation of DBPs. Data were collected along a treated-wastewater-dominated 1.6-km stretch of a river channel for 3 years and incorporated seasonal and diurnal patterns. Photo-irradiation and water temperature were the main factors responsible for in-stream attenuation of photodegradable N-nitrosodimethylamine (NDMA), and water temperature for that of non-photodegradable formaldehyde (FAH). The factors were incorporated into photo-dependent and -independent models to account for temporal variations in NDMA and FAH, respectively. Estimated mass recoveries of NDMA and FAH agreed well with observed values along the stretch. The models developed here offer a novel and useful tool for estimating levels of NDMA and FAH during river transportation.

Greenhouse experiments were conducted in three seasons (2017-18, 2018-19, 2019-20) to study the feasibility to grow cabbage, a temperature sensitive crop, during freezing winter months at high altitude (elevation 3340 m) trans-Himalayan Ladakh region. Three varieties viz. Golden Acre, Videshi and Megaton were studied under an improvised passive solar greenhouse. Head was formed in all the varieties despite the temperature extremes (0.0±1.6 to 39.5±0.9 ºC) inside the greenhouse. The mean marketable head weight ranged from 428.6±72.1 g to 831.2±193.0 g, depending on the variety. The mean head weight of Golden Acre was 831 g, which is 15-fold higher as compared to that of the crop grown under traditional greenhouse in Ladakh. However, the marketable head weight was lower as compared to the yield potential of the varieties. It took 133-163 days for Golden Acre to reach maturity for harvest as compared to the expected 60-65 days. Dramatic declines in intercellular CO2 concentration, photosynthesis rate and water-use efficiency were observed at 2:00 PM, which indicated that the plants were severely affected by high temperatures inside the greenhouse. High temperature inside the greenhouse resulted in bolting, head-splitting and loose head forming, and it ranged from 8-36% of the crop depending on the year and variety. The study suggested that cabbage can be successfully grown under improvised passive solar greenhouse during severe winter months in the trans-Himalayan Ladakh.

Replicating the physiological cortisol secretion is key in the treatment of glucocorticoid insufficient individuals and optimization may enhance quality of life. The study investigates fatigue measured by ecological momentary assessments in patients treated with conventional hydrocortisone compared with once-daily dual-release hydrocortisone (Plenadren). A 21-week open-label switch pilot trial included 30 patients with adrenal insufficiency due to hypopituitarism. Fatigue was assessed four times daily for 20 days using a momentary item version of the Multidimensional Fatigue Inventory on patients’ usual hydrocortisone regimen. Participants switched treatment to an identical daily dose of Plenadren for 16 weeks where fatigue assessments were repeated. Change in fatigue and diurnal variation of fatigue was analyzed using mixed models for repeated measurements. In four out of five fatigue subscales fatigue was significantly reduced 0.7–1.1 points (scales ranging from 4 to 20), when treated with Plenadren compared with conventional hydrocortisone, corresponding to small effect sizes below the scale-specific minimal important changes. However, 33% of the participants completing the study (9/27) experienced reductions in fatigue above the minimal important change. On Plenadren, we found larger between-person variances and smaller within-person variances. Finally, we identified diurnal fatigue curves for both treatments. The Plenadren-related reduction in fatigue was significant but not necessarily of clinical importance when looking at a group level. However, there was a large interindividual variation in treatment effect, why patients with a large benefit in quality of life should be identified. Future RCTs should be powered to detect the effect magnitudes identified here.

ObjectivesThe impact of extreme diurnal temperature range (DTR) on cardiovascular morbidity in Mediterranean regions remains uncertain. We aimed to analyse the impact of extreme low DTR (stable temperature) or high DTR (changeable temperature) on cardiovascular hospitalisations in Catalonia (Southern Europe).MethodsWe conducted a self-controlled case series study using whole-year data from the System for the Development of Research in Primary Care database and 153 weather stations from the Catalan Meteorological Service. The outcome was first emergency hospitalisation. Monthly DTR percentiles were used to define extreme DTR as low (DTR 95th percentile). We assessed two effects: same-day (1-day exposure, coinciding with the extreme DTR episode) and cumulative (3-day exposure, adding two subsequent days). Incidence rate ratios (IRR) were calculated adjusted by age, season and air pollution. Stratified analyses by gender, age or cardiovascular type and regions are provided.ResultsWe computed 121 206 cardiovascular hospitalisations from 2006 to 2013. The IRR was 1.032 (95% CI 1.005 to 1.061) for same day and 1.024 (95% CI 1.006 to 1.042) for cumulative effects of extreme high DTR. The impact was significant for stroke and heart failure, but not for coronary heart disease. Conversely, extreme low DTR did not increase cardiovascular hospitalisations.ConclusionsExtreme high DTR increased the incidence of cardiovascular hospitalisations, but not extreme low DTR. Same-day effects of extreme high DTR were stronger than cumulative effects. These findings contribute to better understand the impact of outdoor temperature on health, and to help defining public health strategies to mitigate such impact.

Variation of visual selective attention through the day has been demonstrated in several arenas of human performance, including radiology. It is uncertain whether this variation translates to an identifiable diurnal pattern of error rates for radiology interpretation. The purpose of this study was to attempt to identify particular days of the week and times of the day when radiologists might be most prone to error. Abdomen/pelvis CT studies containing at least one major error were collected from a 10-year period from the quality assurance (QA) database at our institution. A major error was defined as a missed finding that had altered management in a way potentially detrimental to the patient. The identified studies were categorized by the day of the week and hour of the day that the study was interpreted. Study volume data over this same period was also obtained by day of the week and time of day, so to normalize the data based on case volume. Standard errors of the volume-adjusted error rates were obtained based on the binomial distribution. The null hypothesis of constant error rates over time was tested using a weighted logistic regression model with linear time as predictor. A total of 252 major errors were identified. More errors were made on Monday than on any other day of the week (n = 58). Major error rates increased through the mid to late morning (9 am to 12 pm), and then decreased progressively through the afternoon until 4 pm, when a rise in the error rate was seen. This pattern persisted when error rates were normalized by study volume within each hour. Overall tests of time-constancy of error rates by day and hour were statistically significant (both p-values

OBJECTIVE The purpose of this study was to evaluate the change in Bruch membrane opening minimum rim width (BMO-MRW) during scleral lens (SL) wear. METHODS Twenty young white subjects were enrolled (10 women and 10 men); preliminary evaluation consisted of serial measurements of intraocular pressure (IOP) using a dynamic noncontact tonometer (Corvis, Oculus), which also yielded a corneal biomechanical index and central corneal thickness, and BMO-MRW using optical coherence tomography imaging (OCT) imaging (Spectralis, Heidelberg) through 6 hrs to establish normative diurnal curves. The next day, participants were fitted with a 16-mm SL on one eye, and OCT measurements were repeated over the same time span. Statistical analysis was carried out with a two-way analysis of variance. Multiple linear regressions were used to identify significant associations. RESULTS The average diurnal variation for BMO-MRW without lenses was -4.65 μm (95% confidence interval [CI], 0.52-8.77) after 6 hours, whereas it decreased by 8 μm (95% CI, 3.87-12.12; P

In this work, hourly averaged sun photometer data from Barentsburg and Ny-Ålesund, both located on Spitsbergen in the European Arctic, are compared. Our data set comprises the years from 2002 to 2018 with overlapping measurements from both sites during the period from 2011 to 2018. For more turbid periods (aerosol optical depth, AOD, τ0.5>0.1), we found that Barentsburg is typically more polluted than Ny-Ålesund, especially in the shortwave spectrum. However, the diurnal variation in the AOD is highly correlated. Next, τ was divided into a fine and coarse mode. It was found that the fine-mode aerosol optical depth generally dominates and also shows a larger interannual than seasonal variation. The fine-mode optical depth is in fact largest in spring during the Arctic haze period. Overall the aerosol optical depth seems to decrease (at 500 nm the fine-mode optical depth decreased by 0.016 over 10 years), although this is hardly statistically significant.

Chemical effects on the size-resolved hygroscopicity of urban aerosols were examined based on the Korea–US Air Quality Study (KORUS-AQ, 2020) field campaign data. The information on size-resolved hygroscopicity and the chemical composition of aerosols were obtained by a hygroscopic tandem differential mobility analyzer (HTDMA) and a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), respectively. Good correspondence was shown between measured and estimated κ values calculated from the combination of bulk chemical composition data and oxidation parameters of organic aerosols (f44 and O∕C). These results imply that chemical composition is closely associated with aerosol hygroscopicity. However, the correlation between measured and estimated κ values degraded as particle size decreased, implying that size-resolved chemical composition data are required for more detailed hygroscopicity analysis. In addition to size-resolved chemical data, the m∕z tracer method was applied for size-resolved organic factors. Specifically, m∕z 57 and 44 were used as AMS spectral markers for hydrocarbon-like organic aerosol (HOA) and oxygenated organic aerosol (OOA), respectively. These size-resolved chemical composition data were found to be critical in explaining size-dependent hygroscopicity, as well as the diurnal variation in κ for small particles, i.e., low κ in the morning and high κ in the afternoon. Additionally, aerosol mixing state information was associated with the size-resolved chemical composition data. That is to say that the relationship between the number fraction of each hygroscopicity mode and the volume fraction of different chemical composition was investigated. For example, the HOA volume fraction comprised about 60 % of the variation in less hygroscopic (LH) mode number fractions for externally mixed aerosols.

Stable isotopologues of water are widely used to derive relative root water uptake (RWU) profiles and average RWU depth in lignified plants. Uniform isotope composition of plant xylem water (δxyl) along the stem length of woody plants is a central assumption of the isotope tracing approach which has never been properly evaluated. Here we evaluate whether strong variation in δxyl within woody plants exists using empirical field observations from French Guiana, northwestern China, and Germany. In addition, supported by a mechanistic plant hydraulic model, we test hypotheses on how variation in δxyl can develop through the effects of diurnal variation in RWU, sap flux density, diffusion, and various other soil and plant parameters on the δxyl of woody plants. The hydrogen and oxygen isotope composition of plant xylem water shows strong temporal (i.e., sub-daily) and spatial (i.e., along the stem) variation ranging up to 25.2 ‰ and 6.8 ‰ for δ2H and δ18O, respectively, greatly exceeding the measurement error range in all evaluated datasets. Model explorations predict that significant δxyl variation could arise from diurnal RWU fluctuations and vertical soil water heterogeneity. Moreover, significant differences in δxyl emerge between individuals that differ only in sap flux densities or are monitored at different times or heights. This work shows a complex pattern of δxyl transport in the soil–root–xylem system which can be related to the dynamics of RWU by plants. These dynamics complicate the assessment of RWU when using stable water isotopologues but also open new opportunities to study drought responses to environmental drivers. We propose including the monitoring of sap flow and soil matric potential for more robust estimates of average RWU depth and expansion of attainable insights in plant drought strategies and responses.

Novel coronavirus (SARS-CoV-2) causing COVID-19 disease has arisen to be a pandemic. Since there is a close association between other viral infection cases by epidemics and environmental factors, this study intends to unveil meteorological effects on the outbreak of COVID-19 across eight divisions of Bangladesh from March to April 2020. A compound Poisson generalized linear modeling (CPGLM), along with a Monte-Carlo method and random forest (RF) model, was employed to explore how meteorological factors affecting the COVID-19 transmission in Bangladesh. Results showed that subtropical climate (mean temperature about 26.6 °C, mean relative humidity (MRH) 64%, and rainfall approximately 3 mm) enhanced COVD-19 onset. The CPGLM model revealed that every 1 mm increase in rainfall elevated by 30.99% (95% CI 77.18%, − 15.20%) COVID-19 cases, while an increase of 1 °C of diurnal temperature (TDN) declined the confirmed cases by − 14.2% (95% CI 9.73%, − 38.13%) on the lag 1 and lag 2, respectively. In addition, NRH and MRH had the highest increase (17.98% (95% CI 22.5%, 13.42%) and 19.92% (95% CI: 25.71%, 14.13%)) of COVID-19 cased in lag 4. The results of the RF model indicated that TDN and AH (absolute humidity) influence the COVID-19 cases most. In the Dhaka division, MRH is the most vital meteorological factor that affects COVID-19 deaths. This study indicates the humidity and rainfall are crucial factors affecting the COVID-19 case, which is contrary to many previous studies in other countries. These outcomes can have policy formulation for the suppression of the COVID-19 outbreak in Bangladesh.

This study examines the diurnal variation of the convective area and eye size of 30 rapidly intensifying tropical cyclones (RI TCs) that occurred in the western North Pacific from 2015 to 2017 utilizing Himawari-8 satellite imagery. The convective area can be divided into the active convective area (ACA), mixed phase, and inactive convective area (IACA) based on specific thresholds of brightness temperature. In general, ACA tends to develop vigorously from late afternoon to early the next morning, while mixed phase and IACA develop during the day. This diurnal pattern indicates the potential for ACA to evolve into mixed phase or IACA over time. From the 30 samples, RI TCs tend to have at least a single-completed diurnal signal of ACA inside the radius of maximum wind (RMW) during the rapidly intensifying period. In the same period, the RMW also contracts significantly. Meanwhile, more intense storms such as those of category 4 or 5 hurricane intensity are apt to have continuous ACA inside the RMW and maintain eyewall convective clouds. These diurnal patterns of the ACA could vary depending on the impact of large-scale environments such as vertical wind shear, ocean heat content, environmental mesoscale convection, and terrain. The linear regression analysis shows that from the tropical storm stage, RI commences after a slow intensification period, which enhances both the primary circulation and eyewall convective cloud. Finally, after the eye structure appears in satellite imagery, its size changes inversely to the diurnal variation of the convective activity (e.g., the eye size becomes larger during the daytime).

Satellite-derived land surface temperature (LST) has been widely used to understand surface energy exchange and surface radiation budget and is a critical input of earth system models for carbon and water cycles studies at regional to global scales. Spatially and temporally consistent thermal measurements with long historical records are in a high demand to understand the biophysical changes of Earth surfaces. The current monthly LST products’ spatial resolutions are relatively coarse and the temporal and spatial consistency could be interrupted by the presence of clouds and satellite orbit limitations. This study develops a diurnal temperature cycle (DTC) model-based approach from MODIS observations that are suitable for constructing the long-term and near-global coverage of monthly LSTs at 1 km to fill these data gaps. The new approach allows us to estimate temporally representative 24-hr mean and maximum temperatures in a diurnal cycle of each month. We performed an inter-comparison among satellite-based data, including DTC-based MODIS estimates, the simple composite of four MODIS overpasses, and the hourly geostationary observations (GEO), and also assessed the satellite-based LST against in-situ LSTs from FLUXNET globally. Our proposed DTC-based mean LSTs outperformed the other two satellite estimates from the simple composite and GEO, showing a mean difference of 0.3 °C and an RMSE of 2.2 °C relative to the in-situ measurements. Moreover, we illustrate an application that explores the relationship between the DTC-based monthly LSTs and the soil moisture anomalies across the United States. The monthly maximum LSTs estimated from DTC scheme show higher sensitivity to droughts than the monthly mean. In sum, the improved monthly LST dataset using DTC scheme can enhance our understanding of the thermal dynamics resulting from land–atmosphere interaction across the local, regional, and global scales.

The diurnal temperature range (DTR) is an identifiable and sensitive indicator of the synchronicity of changes in diurnal temperature extrema, but capturing DTR dynamics is challenging for climate models. This study investigates the climatology, variability, and changes of DTR in recent models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The results show that the CMIP6 models underestimate DTR climatology relative to observations. Most individual models overestimate December–February variability, particularly at high latitudes of the Northern Hemisphere. The models show substantially different changes over land surfaces and do not fully capture the observed spatiotemporal evolution of DTR. Large intermodel differences seem to be controlled by daily minimum air temperature. In the Northern Hemisphere, precipitation and cloud longwave and shortwave radiative effects appear to make important contributions to the intermodel discrepancies. Evaporative fraction is an important factor contributing to the intermodel differences in DTR during the summer in the Northern Hemisphere. In general, CMIP6 models have not improved their ability to simulate temporal DTR changes in a consistent way over the entire analysis period (1901–2005) relative to their CMIP5 counterparts. For periods of rapid DTR decline (e.g., 1951–80) CMIP6 models are typically better than the CMIP5 versions at simulating DTR, whereas for other periods CMIP6 models underperform their CMIP5 counterparts.

We performed a global analysis with data from 149 countries to test whether temperature can explain the spatial variability of the spread rate and mortality of COVID-19 at the global scale. We performed partial correlation analysis and linear mixed effect modelling to evaluate the association of the spread rate and motility of COVID-19 with maximum, minimum, average temperatures and diurnal temperature variation (difference between daytime maximum and night-time minimum temperature) and other environmental and socio-economic parameters. After controlling the effect of the duration since the first positive case, partial correlation analysis revealed that temperature was not related with the spatial variability of the spread rate of COVID-19 at the global scale. Mortality was negatively related with temperature in the countries with high-income economies. In contrast, diurnal temperature variation was significantly and positively correlated with mortality in the low- and middle-income countries. Taking the country heterogeneity into account, mixed effect modelling revealed that inclusion of temperature as a fixed factor in the model significantly improved model skill predicting mortality in the low- and middle-income countries. Our analysis suggests that warm climate may reduce the mortality rate in high-income economies, but in low- and middle-income countries, high diurnal temperature variation may increase the mortality risk.

Background: Compared with reported data of radon concentration, data of radon progeny concentration is limited in general, especially in outdoor environment. Materials and Methods: To know both the level and the variation of radon progeny concentration in outdoor environment in Beijing area, one-year continuous measurement with a cycle of 60 minutes was carried out by a step-advanced filter (SAF) monitor for radon progeny measurement. The observation site was located in a park in Eastern Beijing area, and the observation period was from October 17, 2018 to September 29, 2019. Results and Discussion: The equivalent equilibrium concentration (EEC) of radon progeny varies from 0.7 to 19.1 Bq·m-3, with an annual average of 4.9 ± 2.7 Bq·m-3. A clear diurnal variation of EEC, higher in the early morning and lower in the late afternoon, is observed due to the high sensitivity of the SAF monitor. Conclusion: Vertical convection of atmospheric boundary layer is thought to be the main reason of this phenomenon. For annual variation, the lowest monthly average EEC appeared in April, while the highest appeared in November, which might attribute to the atmospheric stability in different seasons.

To investigate characteristics and seasonal variations of carbonaceous species for PM-2.5 in Forest, Organic carbon(OC) and Element carbon(EC) were measured using Semi-Continuous OC/EC Analyzer (Sunset Laboratory INC., USA) at Taehwa Research Forest (TRF) located in Sanglim-ri, Gwangju City, Gyeonggi-Province for 1 year from January to November 2018. Mean concentrations of OC and EC were estimated 3.6 ± 1.86 μg/m3 and 0.79 ± 0.67 μg/m3 respectively. OC showed seasonality reaching their maximum in summer (4.0 ± 2.0 μg/m3) and minimum in fall (3.1 ± 1.8 μg/m3). EC showed the same concentration except summer. The annual averaged OC/EC ratio was 6.49 ± 4.70. OC (except summer)and EC showed similar trend in seasonal variations. The diurnal variation in OC and EC concentration increased in the morning due to the influence of nearby highways and industrial complexes, and in the afternoon it was estimated that they were affected by forest rather than artificial. Using the EC tracer method, primary OC/EC ratio and SOC was assessed. SOC concentration was the greatest in summer and the lowest in winter. Through this study, Continuous monitoring of atmospheric carbonaceous species in Korea, where over 64% of the total land is forest, is essential to provide the science-based data to policy-marker establishing the air quality improvement policy.