Seasonal Distribution Characteristics Research Articles

Pollution characteristics and health risk assessment of heavy metals in PM2.5 in Fuxin, China

Fuxin is located in the atmospheric channel around Bohai Bay, and its geographical location is very special. Few existing studies have investigated the pollution characteristics and health risk assessment of heavy metals in atmospheric PM2.5 during the four seasons in Fuxin, so a total of 180 PM2.5 samples were collected from four sampling sites in Fuxin from December 2021 to November 2022. The seasonal distribution characteristics of V, Cr, Mn, Co, Ni, Cu, Zn, Pb, As, Sb, Cd and Ba were analysed via inductively coupled plasma-mass spectrometry (ICP‒MS), and the source of the heavy metals was analysed via the enrichment factor (EF) and principal component analysis (PCA). A health risk model was used to assess the health risk of respiratory exposure in men, women and children in Fuxin. The results revealed that the annual average mass order of heavy metals in Fuxin PM2.5 was Zn (0.2947 μg·m−3) > Pb (0.0664 μg·m−3) > As (0.0225 μg·m−3) > Ba (0.0205 μg·m−3) > Mn (0.0187 μg·m−3) > Cu (0.0140 μg·m−3) > Cr (0.0095 μg·m−3) > V (0.0067 μg·m−3) > Ni (0.0061 μg·m−3) > Sb (0.0024 μg·m−3) > Cd (0.0019 μg·m−3) > Co (0.0007 μg·m−3). The annual average concentration of As was 3.75 times the GB3095-2012 (China) secondary standard limit, and the concentration of hazard quotient (HQ) in PM2.5 was lower than 1, but the concentration of incremental lifetime cancer risk (ILCR) in As was higher than the cancer risk threshold (10–4). These findings indicate a certain risk of cancer in the urban population of Fuxin. Therefore, it is necessary to control the emissions created from coal burning to minimize the health risks to the people of Fuxin.

The source of volatile organic compounds pollution and its effect on ozone in high-altitude areas

Volatile organic compounds (VOCs) are crucial precursors in the formation of ozone (O3). The sources of pollution are complex and significantly impact O3 generation. Long-term exposure to high-concentration O3 environments causes serious damage to organisms. High-altitude areas experience continuous high temperatures and strong solar radiation, which can easily produce O3 through photochemical reactions, making these areas prone to frequent air pollution. This study utilizes the National Positioning Station of the Yinchuan Urban Ecosystem in Ningxia to conduct field synchronous observations, gathering data on VOCs, meteorological variables, and O3. By employing machine learning algorithms, we examined the seasonal distribution characteristics of VOCs, their pollution sources, and their impact on O3. The results show that the seasonal distribution of VOCs areas is low in spring and autumn and high in summer and winter. The components with higher volume fraction contribution are m-tolualdehyde in spring and summer, ethane in autumn, and acetylene in winter. The main emission sources of VOCs pollution are hydrocarbon volatile emission in spring and winter, solvent volatilization emission in summer, and industrial sources in autumn. VOCs have a negative effect on O3, with a greater impact in winter and spring, evidenced by standardized effect values of −0.26 and −0.24. The key components affecting O3 in VOCs vary by season. Aromatic hydrocarbons are the key components in spring and winter, with contribution rates of 22 % and 21.3 %. Alkenes are the key components in summer and autumn (24.5 % and 26.8 %). Among meteorological variables, temperature is the key factor affecting O3, while wind speed is the key factor affecting O3 only in winter. This study aims to clarify the sources of VOCs pollution in different seasons and their impact on O3, providing a theoretical basis and technical support for the prevention and control of VOCs and O3 pollution in high-altitude areas.

Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning

Baseflow is a crucial water source in the inland river basins of high-cold mountainous region, playing a significant role in maintaining runoff stability. It is challenging to select the most suitable baseflow separation method in data-scarce high-cold mountainous region and to evaluate effects of climate factors and underlying surface changes on baseflow variability and seasonal distribution characteristics. Here we attempt to address how meteorological factors and underlying surface changes affect baseflow using the Grey Wolf Optimizer Digital Filter Method (GWO-DFM) for rapid baseflow separation and the Long Short-Term Memory (LSTM) neural network model for baseflow prediction, clarifying interpretability of the LSTM model in baseflow forecasting. The proposed method was successfully implemented using a 63-year time series (1958–2020) of flow data from the Tai Lan River (TLR) basin in the high-cold mountainous region, along with 21 years of ERA5-land meteorological data and MODIS data (2000–2020). The results indicate that: (1) GWO-DFM can rapidly identify the optimal filtering parameters. It employs the arithmetic average of three methods, namely Chapman, Chapman-Maxwell and Eckhardt filter, as the best baseflow separation approach for the TLR basin. Additionally, the baseflow significantly increases after the second mutation of the baseflow rate. (2) Baseflow sources are mainly influenced by precipitation infiltration, glacier frozen soil layers, and seasonal ponding. (3) Solar radiation, temperature, precipitation, and NDVI are the primary factors influencing baseflow changes, with Nash-Sutcliffe efficiency coefficients exceeding 0.78 in both the LSTM model training and prediction periods. (4) Changes in baseflow are most influenced by solar radiation, temperature, and NDVI. This study systematically analyzes the changes in baseflow and response mechanisms in high-cold mountainous region, contributing to the management of water resources in mountainous basins under changing environmental conditions.

Seasonal and Spatial Distribution Characteristics of Sepia esculenta in the East China Sea Region: Transfer of the Central Distribution from 29° N to 28° N.

The golden cuttlefish (Sepia esculenta) is an important cephalopod species with a lifespan of approximately one year. The species plays a crucial role in marine ecological support services and is commercially valuable in fisheries. In the seas around China, this species has emerged as the main target for cuttlefish fisheries, replacing Sepiella maindroni since the 1990s. Variations in oceanographic conditions associated with global warming could significantly impact the temporal-spatial distribution of the species. In this study, we performed bottom trawling surveys with four cruises during 2018-2019 in the East China Sea region to determine the current resource status and seasonal-spatial variations in S. esculenta. We found that the average individual weight (AIW) values were 4.87 and 519.00 g/ind at stations located at 30.50° N, 124.00° E and 30.50° N, 124.50° E, respectively, with the aggregation of larvae and parent groups in spring. The species was not distributed north of 32.00° N in summer. The catch per unit effort by weight (CPUEw) value decreased in the order of 2772.50→2575.20→503.29→124.36 g/h, corresponding to latitudes of 34.50° N→34.00° N→33.50° N→32.50° N 121.50° E in autumn. The most suitable fishing areas were the south of the East China Sea region in spring; the south of the East China Sea region extending to the center and outer parts of the East China Sea region in summer; the south of the Yellow Sea close to the Haizhou Bay fishing ground and the forbidden fishing line region of the Lusi and Dasha fishing grounds in autumn; and the south and center of the East China Sea region in winter. The most suitable sea bottom temperature (SBT) values from spring to winter were 14.76-20.53 °C, 19.54-22.98 °C, 11.79-17.64 °C, and 16.94-20.36 °C, respectively. The most suitable sea bottom salinity (SBS) values were 31.53-34.80‱ in spring, 32.95-34.68‱ in summer, 31.51-34.77‱ in autumn, and 33.82-34.51‱ in winter. We concluded the following: (1) the southern and northern areas of the East China Sea region are spawning and nursery grounds, respectively, in spring; (2) the central distribution is located at a latitude of 28.00° N in autumn and winter; and (3) the southern area of the Yangtze River to the north is a spawning ground in spring, and the areas located at 29.00-34.50° N, 124.00-124.50° E, and 28.00-30.50° N, 125.50-126.50° E are nursery grounds. The results of this study provide useful guidance for appropriate fisheries management, thereby avoiding a collapse in the S. esculenta population, which has been experienced in other species in this area.

Analysis of total nitrogen pollution load and identification of key pollution sources in Futuan River basin based on SWAT model

In order to identify the key source area of the Futuan River basin, the Futuan River basin is taken as the target area, establishes the Soil Water Assessment Tool (SWAT) model, simules the runoff and total nitrogen pollution process in the basin, and analyzes the spatiotemporal characteristics of total nitrogen pollution. The key source areas of total nitrogen pollution in the basin were identified by the cumulative load curve method. The results show that the total nitrogen pollution load in the Futuan River basin presents obvious seasonal distribution characteristics. The subbasins with high load intensity of total nitrogen into the river are mainly in the middle and upper reaches of the Futuan River.

Seasonal distribution characteristics and ecological risk assessment of phthalate esters in surface sediment of Songhua River basin

Phthalic acid esters (PAEs) are typical industrial chemicals used in China. PAEs have received considerable attention because of their ubiquity and potential hazard to humans and the ecology. The spatiotemporal distributions of six PAEs in the surface sediments of the Songhua River in the spring (March), summer (July), and autumn (September) are investigated in this study. The total concentration of phthalic acid esters (∑6PAEs) ranges from 1.62 × 102 ng g−1 dry weight (dw) to 3.63 × 104 ng g−1·dw, where the amount in the spring is substantially higher (p < 0.01) than those in the autumn and summer. Seasonal variations in PAEs may be due to rainfall and temperature. The ∑6PAEs in the Songhua River's upper reaches are significantly higher than those in the middle and lower reaches (p < 0.05). Dibutyl phthalate (DBP) and di(2-ethylhexyl) phthalate (DEHP) are the two most abundant PAEs. The ecological hazard of five PAEs is assessed using the hazard quotient method. DBP and DEHP pose moderate or high ecological risks to aquatic organisms at various trophic levels. PAEs originate primarily from industrial, agricultural, and domestic sources. Absolute principal components–multiple linear regression results indicate that agricultural sources are the most dominant contributor to the ∑6PAEs (53.7%). Guidelines for controlling PAEs pollution in the Songhua River are proposed.

Comprehensive study of algal blooms variation in Jiaozhou Bay based on google earth engine and deep learning

The Jiaozhou Bay ecosystem, a crucial marine ecosystem in China, has been plagued by frequent harmful algal blooms as due to deteriorating water quality and eutrophication. This study analyzed the temporal and spatial changes of harmful algal blooms in Jiaozhou Bay from 2000 to 2022 using the Floating Algae Index (FAI) calculated from MODIS (2000–2022) and Sentinel-2 (2015–2022) satellite image datasets. The calculation results of the image datasets were compared. The frequency of planktonic algal outbreaks was low and constant until 2017, but has increased annually since then. Algae blooms are most common in the summer and primarily concentrated along the bay’s coast, middle, and mouth, with obvious seasonal and spatial distribution characteristics. Several factors influencing algal outbreaks were identified, including sea surface temperature, wind speed, air pressure, dissolved oxygen, nitrogen and phosphorus ratios, chemical oxygen demand, and petroleum pollutants. Algal bloom outbreaks in Jiaozhou Bay are expected to remain high in 2023. The findings provide crucial information for water quality management and future algal outbreak prediction and prevention in Jiaozhou Bay.

Urban heat islands and their effects on thermal comfort in the US: New York and New Jersey

In recent decades, urbanization and the dramatic increase in urban populations have exacerbated the urban heat island effect. At present, much attention has been paid to the causes and patterns of the urban heat island effect. However, there are few quantitative studies on the impact of the urban heat island effect. By extracting post-world climate data, DEM data, and land use data for 20 years between 2001 and 2020, this paper first studies the variation pattern and spatial distribution characteristics of urban heat islands in New York State, summarizes the seasonal distribution characteristics of temperature, and then uses Giles formula to calculate Tom's discomfort index and evaluate human thermal comfort, and evaluates the effect of heat island effect on human sensory thermal comfort. The results show that on the time scale, the surface temperature in the study area generally showed a slow upward trend over the past 20 years. For example, in July, the maximum and minimum temperatures increased by 3.2 °C and 4.1 °C, respectively. At the spatial scale, most of the heat island areas in the study area were distributed in the New York City agglomeration, especially from May to October, when the heat island effect was particularly obvious. The temperature map showed obvious high temperatures. Compared with 2001, the human discomfort index (DI) increased between June and August 2020. The land use map shows that as the city expands, people's DI index also increases, and the proportion of people who feel uncomfortable with heat increases to 50%. Except for the New York City cluster, other areas were mostly athermic-free. This result shows that excessive urban development concentration seriously affects residents' quality of life. We should pay attention to the superimposed impact of climate change and urban heat islands on the human discomfort index, and adjust the local high temperature and thermal field area through reasonable planning, strengthening greening, and using building technology to make cities more livable.

Spatial and seasonal distribution of particulate phosphorous and nitrogen in the Persian Gulf: Nitrogen enrichment ties to diazotroph bloom in stratified warm waters

Understanding the particulate organic and inorganic forms of nutrients and their elemental stoichiometry in suspended particulate matter of marginal seas has important implications in several areas. Here, we present the findings from two consecutive research expeditions conducted in September 2021 and January 2022 aboard the Persian Gulf Explorer research vessel, focused on the particulate P and N in the Persian Gulf and the Strait of Hormuz. The prominent features of spatial and seasonal distribution characteristics were nearshore-offshore decreasing gradients in particulate nutrients, the summer-to-winter declining trend in particulate nutrients more notably for particulate organic nitrogen, and higher biomass N:P ratio in summer than in winter with high spatial inhomogeneity. The trends were mainly governed by shallow remineralization of organic matter, resuspension of fine sediments, summer stratification/winter mixing of the water column, and inflow of the Indian Ocean Surface Waters from the Gulf of Oman. The contribution of inorganic N in the particulate pool of N (1.8% in summer and 1.3% in winter) was much less than the contribution of inorganic P in the particulate pool of P (23.0% in summer and 32.4% in winter), and hence the biomass N:P was higher than the corresponding bulk N:P by a factor of ∼1.5. Seasonal pattern in biomass N:P was similar to those observed at many sites being higher in the summer and lower in the winter. The formation of summer thermocline, characterized by high surface temperature (∼33 °C) and limited upward flux of remineralized inorganic nutrients, coincided with the proliferation of nitrogen-fixing cyanobacteria. Samples collected from the deep offshore region in summer showed significantly higher biomass N:P ratio, reaching up to 47, which is far beyond the classical Redfield ratio of 16. The central Persian Gulf experienced less seasonal variations than the deep region in the western Persian Gulf, the northwestern Arvand estuary, and the northwestern Gulf of Oman.

The Method of Photovoltaic Power Forecast based on Seasonal Classification and Limit Learning Machine

The seasonal distribution characteristics of photovoltaic power plant output fluctuation are analyzed, and a short-term power forecasting method based on seasonal classification is proposed. Firstly, the seasonal distribution characteristics of photovoltaic output and its fluctuation are analyzed. Secondly, the forecasting model of photovoltaic output in different seasons is established by the Limit Learning Machine neural network. Finally, an empirical analysis is carried out by using photovoltaic output data. The results show that the seasonal classification method of short-term PV power forecast is better than the unclassified model.

The global spatial-temporal distribution and EOF analysis of AOD based on MODIS data during 2003–2021

The long-term global distribution study of Aerosol Optical Depth (AOD) has great significance for air pollution control, forest fire prevention and climate studies. The global spatial-temporal distribution and variation of the AOD at 550 nm are analyzed using AOD550 product of Modis/Aqua during 2003–2021. The AOD550 is also studied by Empirical Orthogonal Function (EOF) analysis method. The results show that the distribution of AOD550 has obvious regional and seasonal characteristics, and the interannual variation is distinct. The AOD550 distribution with latitude/longitude is closely related to the distribution of population and aerosol natural source. The high-AOD550 areas are mainly distributed in eastern Asia, southeast Asia, south Asia, the Middle East, northwestern Africa, central and western Africa, western waters of Africa and the Amazon region of South America; The AOD550 seasonal distribution results are JJA > MAM > DJF > SON over globe, SON > DJF > (MAM ≈ JJA) over the southern hemisphere, and MAM > JJA > DJF > SON over the northern hemisphere, respectively. Moreover, the seasonal distribution characteristics varies in different regions especially over ocean and land. The results of interannual variation show an upward trend during 2005–2011, and fluctuates during 2012–2020. The annual mean AOD550 over the northern hemisphere (0.187–0.207) is significantly higher than that of southern hemisphere (0.110–0.135), while the latter shows an increasing trend (0.0009/year). The EOF analysis results demonstrate the complexity of the AOD550 global distribution. The annual mean results show the change trends of aerosols in different regions and find some special aerosol events. While the monthly mean results show that aerosols over ocean are mostly dominated by land sources (dust and biomass burning sources), and the ocean transport pattern presents an annual cycle.

Epidemiological Characteristics of Notifiable Respiratory Infectious Diseases in Mainland China from 2010 to 2018.

Respiratory infectious diseases (RIDs) pose threats to people's health, some of which are serious public health problems. The aim of our study was to explore epidemic situations regarding notifiable RIDs and the epidemiological characteristics of the six most common RIDs in mainland China. We first collected the surveillance data of all 12 statutory notifiable RIDs for 31 provinces in mainland China that reported between 2010 and 2018, and then the six most prevalent RIDs were selected to analyze their temporal, seasonal, spatiotemporal and population distribution characteristics. From 2010 to 2018, there were 13,985,040 notifiable cases and 25,548 deaths from RIDs in mainland China. The incidence rate of RIDs increased from 109.85/100,000 in 2010 to 140.85/100,000 in 2018. The mortality from RIDs ranged from 0.18/100,000 to 0.24/100,000. The most common RIDs in class B were pulmonary tuberculosis (PTB), pertussis, and measles, while those in class C were seasonal influenza, mumps and rubella. From 2010 to 2018, the incidence rate of PTB and rubella decreased; however, pertussis and seasonal influenza increased, with irregular changes in measles and mumps. The mortality from PTB increased from 2015 to 2018, and the mortality from seasonal influenza changed irregularly. PTB was mainly prevalent among people over 15 years old, while the other five common RIDs mostly occurred among people younger than 15 years old. The incidence of the six common RIDs mostly occurred in winter and spring, and they were spatiotemporally clustered in different areas and periods. In conclusion, PTB, seasonal influenza and mumps remain as public health problems in China, suggesting that continuous government input, more precise interventions, and a high-tech digital/intelligent surveillance and warning system are required to rapidly identify emerging events and timely response.

Seasonal constraints on the burial of organic carbon in the eutrophic Lake Taihu

Eutrophication alters the function of lake ecosystems through phytoplankton blooms and is a major contributor to organic carbon (OC) burial in lakes worldwide. Although Lake Taihu is notable for its severe eutrophication yet low OC burial, why cyanobacteria-derived OC is ineffectively buried in the lake is unknown. Because seasonal hydrological and ecological dynamics in eutrophic lacustrine ecosystems would significantly modify the preservation and degradation behaviors of OC, seasonal variations in paired particulate samples from both the water column and surface sediment are critical in evaluating cyanobacteria-derived OC burial. In this study, we present the steroid results of water and sediments collected from Meiliang Bay in Lake Taihu across cyanobacteria-bloom and decay seasons (from May 2018 to June 2019) to investigate constraints on the seasonal burial of autochthonous and allochthonous OC. The results indicate that cyanobacteria contribute a considerable amount of OC to the water body in the cyanobacterial bloom season, while terrestrial OC becomes the main contributor during the cyanobacterial decay season. Although OC degradation occurs throughout the water column, substantially more OC degradation was observed at the water-sediment interface. The extensive degradation of OC in the bloom season eventually reverses the seasonal distribution characteristics of particulate OC in the water column, leading to less accumulation of OC under the background of higher cyanobacteria-derived OC input. The combined effect of OC bioavailability, temperature, oxygen exposure, and more importantly microorganism activities, accounts for much higher OC degradation rates in the bloom season. Similar phenomena were observed in subtropical shallow lakes with high primary productivity, suggesting that eutrophication might have a limited influence on OC burial when compared to other factors related to OC degradation.

Aerosol Characterization of Northern China and Yangtze River Delta Based on Multi-Satellite Data: Spatiotemporal Variations and Policy Implications

Horizontal and vertical distributions of aerosol properties in the Taklimakan Desert (TD), North central region of China (NCR),North China Plain(NCP), and Yangtze River Delta (YRD) were investigated by statistical analysis using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) L3 data from 2007 to 2020, to identify the similarities and differences in atmospheric aerosols in different regions, and evaluate the impact of pollution control policies developed in China in 2013 on aerosol properties in the study area. The aerosol optical depth (AOD) distribution had substantial seasonal and spatial distribution characteristics. AOD had high annual averages in TD (0.38), NCP (0.49), and YRD (0.52). However, these rates showed a decline post-implementation of the long-term pollution control policies; AOD values declined by 5%, 13.8%, 15.5%, and 23.7% in TD, NCR, NCP, and YRD respectively when comparing 2014–2018 to 2007–2013, and by 7.8%, 11.5%, 16%, and 10.4% when comparing 2019–2020 to 2014–2018. The aerosol extinction coefficient showed a clear regional pattern and a tendency to decrease gradually as height increased. Dust and polluted dust were responsible for the changes in AOD and extinction coefficients between TD and NCR and NCP and YRD, respectively. In TD, with change of longitude, dust aerosol first increased and then decreased gradually, peaking in the middle. Similarly in NCP, polluted dust aerosol first increased and then decreased, with a maximum value in the middle. The elevated smoke aerosols of NCP and YRD were significantly higher than those observed in TD and NCR. The high aerosol extinction coefficient values (&gt;0.1 km−1) were mainly distributed below 4 km, and the relatively weak aerosol extinction coefficients (&gt;0.001 km−1) were mainly distributed between 5–8 km, indicating that the high-altitude long-range transport of TD and NCR dust aerosols affects NCP and YRD.

Seasonal Variations of Low-Molecular-Weight Organic Acids in Three Evergreen Broadleaf Rhododendron Forests.

Low-molecular-weight organic acids (LMWOAs) are widely distributed in forests. Fresh leaves, litter, humus, and the topsoil layer of representative Rhododendron delavayi (RD), Rhododendron agastum (RA), and Rhododendron irroratum (RI) in the Baili Rhododendron National Forest Park were sampled to explore their seasonal changes. The contents of oxalic, tartaric, malic, citric, acetic, lactic, succinic, and formic acids in samples from different seasons were determined by high-performance liquid chromatography. The results showed that the composition and content of the LMWOAs in the fresh leaves, litter, humus, and topsoil layer of the rhododendrons were affected by the tree species, samples, and season. The main LMWOA was oxalic acid (the average content in the samples was 195.31 µg/g), followed by malic acid (the average content in the samples was 68.55 µg/g) and tartaric acid (the average content in the samples was 59.82 µg/g). Succinic acid had the lowest content; the average content in the samples was 18.40 µg/g. The LMWOAs of the RD were the highest (the average content in the samples was 517.42 µg/g), and the LMWOAs of the RI were the lowest (the average content in the samples was 445.18 µg/g). The LMWOAs in the three rhododendron forests were in the order of fresh leaves &gt; litter &gt; humus &gt; soil layers. This study showed the seasonal distribution characteristics of LMWOAs in three evergreen broadleaf rhododendron forests, and the results provide a reference for ecosystem management and the protection of wild rhododendron forests.

Child and adolescent psychiatry - change in the dynamics of treatment caused by the coronavirus pandemic

Introduction. The coronavirus pandemic caused a restructuring of mental health services, marked by a decrease of hospital work capacity and increased reliance on telemedicine. Children and adolescents are a particularly vulnerable group that has been affected by the newly arisen corona virus-19 pandemic. The objective was to evaluate the correlation between the coronavirus pandemic and alternations in hospitalization rates, seasonal distribution, and sociodemographic characteristics of patients admitted to the Department of Child and Adolescent Psychiatry. Material and Methods. The study was conducted at the Psychiatry Clinic of the Department of Child and Adolescent Psychiatry at the University Clinical Center of Vojvodina in the period from March 6, 2017 to March 5, 2021. The sample comprised 1114 inpatients and individuals undergoing partial hospitalizations, diagnosed with mental disorders classified according to the International Classification of Diseases. Participants were categorized into two groups: one treated before the onset of the pandemic (March 2017-March 2020) and another treated during the pandemic (March 2020-March 2021). Statistical analysis was performed on the collected data, with the results presented in tables and graphs. Results. During the pandemic, an overall reduction in admissions (-32.34%) was observed, accompanied by a noticeable decrease in admissions during the spring compared to the pre-coronavirus period (p=0.011). The most prevalent diagnoses were F9 and F4, respectively (p&lt;0.01). A higher number of hospitalizations were noted in middle adolescence (p&lt;0.001), among females (p=0.006) and those residing in urban areas (p=0.009). Conclusion. The coronavirus pandemic led to alternations in the functioning and dynamics on Department of Child and Adolescent Psychiatry. The sociodemographic characteristics of the youth changed during the pandemic.

Clinical characteristics and risk factors of 267 patients having severe fever with thrombocytopenia syndrome–new epidemiological characteristics of fever with thrombocytopenia syndrome: Epidemiological characteristics of SFTS

To analyze the epidemiological distribution, clinical characteristics, and prognostic risk factors of patients having severe fever with thrombocytopenia syndrome (SFTS). We enrolled 790 patients with SFTS divided into the ordinary group and the severe group, analyzed the clinical characteristics, and screened the risk factors of severious patients by univariate logistic regression analysis. Most of the 790 patients (SFTS) are farmers (84.56%). The proportion of patients with fieldwork history was 72.41%, of which 21.27% had a clear history of a tick bite and 98.61% were sporadic cases. The annual peak season is from April to November. 16.33% patients were not accompanied by fever. The incidence of severe thrombocytopenia was 47.59%. They were statistically significant between the 2 groups in indicators such as age, hypertension, coronary heart disease, diabetes mellitus, bunyavirus nucleic acid load and mean platelet count (P < .05). Multivariate non conditional Logistic regression analysis showed that the risk factors of the mild patients deteriorating severe disease were age (OR = 1.985, P ≤ .003), diabetes mellitus (OR = 1.702, P ≤ .001), coronary heart disease (OR = 1.381, P ≤ .003), platelet count (OR = 2.592, P ≤ .001), viral nucleic acid loading (OR = 3.908, P ≤ .001). The incidence population and seasonal distribution characteristics of patients with SFTS are obvious. The risk factors for poor prognosis of severe patients are old age, multiple basic medical histories, high viral load, a serious decrease of mean platelet count, and delay of treatment time.

Impact of Human Activities on Hydrological Drought Evolution in the Xilin River Basin

The impact of human activities on the hydrological cycle makes hydrological drought no longer a natural disaster in a strict sense, and influences the stationarity of the hydrologic process. In this context, assessment methods that consider nonstationary conditions are more reasonable in the study of hydrological drought. In this study, we used the SWAT (Soil and Water Assessment Tool) model to reconstruct the historical hydrological conditions during the period affected by human activities (1998–2019) of the Xilin River Basin. After calculating the standardized runoff index (SRI) at multiple time scales, we compared the drought characteristics of the basin under natural conditions and under the influence of human activities. The results show that human activities were the main reason for the significant decrease of runoff in the basin (an obvious change-point for runoff series is identified in 1998), which accounted for 68%. Compared with natural conditions, human activities delayed the occurrence of short-term drought in the basin and changed its seasonal distribution characteristics, resulting in an increase in the frequency of severe and extreme droughts in autumn; the corresponding drought frequency increased by 15% and 60%, respectively. Moreover, human activities have also prolonged drought duration, increased drought intensity, and increased the uncertainty of drought in the basin. The proposed method is demonstrated to be efficient in quantifying the effects of human activities on hydrological drought, and the findings of this study provide a scientific basis for water resource management, drought early warning, and forecasting under a changing environment.

Exploring the Spatiotemporal Characteristics and Causes of Rear-End Collisions on Urban Roadways

Rear-end collisions are caused by drivers misjudging urgent risks while following vehicles ahead in most cases. However, compared with other accident types, rear-end collisions have higher preventability. This study aims to reveal the prone segments and hours of rear-end collisions. First, we extracted 1236 cases from traffic accident records in Harbin from 2015 to 2019. These accidents are classified as property damage accidents, injury accidents and fatal accidents according to the collision severity. Second, density analysis in GIS was used to demonstrate the spatial distribution of rear-end collisions. The collision spots considering the density and severity were visually displayed. We counted the hourly and seasonal distribution characteristics according to the statistical data. Finally, LightGBM and random forest classifier models were used to evaluate the substantial factors affecting accident severity. The results have potential practical value in rear-end collision warning and prevention.

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2

A statistical analysis of the distribution of convective windstorms and their radar characteristics in Hubei Province, China. Part 2