Spatial and Temporal Distribution Characteristics and Cytotoxicity of Atmospheric PM2.5 in the Main Urban Area of Lanzhou City.

PM2.5, as one of the most harmful pollutant in the atmospheric environment and population health, has received much attention. We monitored PM2.5 levels at five sampling sites in the Lanzhou City and collected PM2.5 particles from two representative sites for cytotoxicity experiment. The cytotoxicity of PM2.5 samples on A549 cells and migration ability of the cells were respectively detected by Cell Counting kit-8 (CCK-8) assay and scratch assay. We detected the levels of cellular inflammatory factors and oxidative damage-related biochemical indexes. RT-qPCR was used to detect the mRNA levels of NF-κB and epithelial-mesenchymal transition (EMT)-related genes. We found that the Lanlian Hotel station had the highest PM2.5 annual average concentration. The annual average concentration change curve of PM2.5 showed a roughly "U"-shaped distribution during the whole sampling period. The cytotoxicity experiment showed the viability of A549 cells decreased and the scratch healing rate increased in the 200 and 400 µg/mL PM2.5-treated groups. We also found 400 µg/mL PM2.5 induced changes in the mRNA levels of NF-κB and EMT-related genes, the mRNA levels of IKK-α, NIK, and NF-κB in the 400 µg/mL PM2.5 group were higher than those in the control group. The mRNA levels of E-cadherin decreased and α-SMA increased in the 400 µg/mL PM2.5 groups, and the mRNA levels of Fibronectin increased in the 400 µg/mL PM2.5 groups. Moreover, we found hydroxyl radical scavenging ability and T-AOC levels were lower, and LPO levels were higher in the 200 and 400 µg/mL PM2.5 groups, and the SOD activity of cells in the 400 µg/mL PM2.5 group decreased. And compared with the control group, the levels of TNF-α were higher in the 200 and 400 µg/mL PM2.5 groups and the levels of IL-1 were higher in the 400 µg/mL PM2.5 group. The results indicated that the cytotoxicity of atmospheric PM2.5 was related to oxidative damage, inflammatory response, NF-κB activity and EMT.

[Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020].

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

Intelligent management of carbon emissions of urban domestic sewage based on the Internet of Things.

Domestic wastewater is one of the major carbon sources that cannot be ignored by human society. Against the background of carbon peaking & carbon neutrality (Double Carbon) goals, the continuous urbanization has put heavy pressure on urban drainage systems. Nevertheless, the complex subjective and objective conditions of drainage systems restrict the field monitoring, measurement, and analysis of drainage systems, which has become a great obstacle to the study of carbon emissions from drainage system. In this paper, 3389 sensor terminals of Internet of Things (IoT) are used to build a field monitoring IoT for urban domestic wastewater methane (CH4) carbon emission, with 21 main districts of Chongqing Municipality in China as the study area. Incorporating Fick's law of diffusion, this field monitoring IoT derives a measurement model for methane carbon emissions based on measured concentrations, and solves the problems of long-term and stable monitoring and measurement of methane gas in complex underground environment. With GIS spatio-temporal analysis used to analyze the spatial and temporal evolution patterns of carbon emissions from septic tanks in drainage systems, it successfully reveals the spatial and temporal distribution of methane carbon emissions from drainage systems in different seasons, as well as the relationship between methane carbon emissions from drainage systems and the latitude of direct sunlight. Applying the DTW method, it quantifies the stability of methane monitoring in drainage systems and evaluates the effects of Sampling Frequency (SF) and Number of Devices Terminal (NDT) on the stability of methane monitoring. Consequently, an intelligent management system for carbon emissions from urban domestic wastewater is constructed on the base of IoT, which integrates methane monitoring, measurement and analysis in septic tanks of drainage systems.

[Spatial and temporal distribution characteristics of extreme wind and its effect on wind erosion in Northeast China]. / ä¸œåŒ—åœ°åŒºæžç«¯å¤§é£Žæ—¶ç©ºåˆ†å¸ƒç‰¹å¾åŠå ¶å¯¹é£Žèš€é‡çš„å½±å“.

Under the background of climate change, extreme wind events occur frequently in Northeast China, and the soil erosion caused by these extreme wind events has attracted progressively more attention from scholars. We used the methods of linear analysis, Sen+Mann-Kendal trend analysis, and Kriging interpolation to analyze the spatial and temporal characteristics of extreme wind in Northeast China from 2005 to 2020, and used the RWEQ wind erosion estimation model to calculate the annual soil wind erosion of typical wind erosion sites and wind erosion under extreme wind conditions. The results showed that the extreme wind frequency in Northeast China presented a significant upward trend from 2005 to 2020, with an increase of 2.9 times·a-1. The annual average extreme wind frequency in Northeast China ranged from 1 to 49 times·a-1, and the high frequency areas were distributed in the northwest of Xilin Gol, the west of the Hulunbuir Plateau, and the northeast of Changbai Mountain. The average contribution rate of extreme wind to soil wind erosion in four typical sites (Xilinhot, New Barhu Right Banner, Nenjiang, and Tongyu) was 31%.

[Spatial-temporal Distribution and Source Analysis of Polycyclic Aromatic Hydrocarbons in the Sediments of Poyang Lake].

The concentrations, spatial-temporal distribution, and influencing factors of 16 polycyclic aromatic hydrocarbons (PAHs) in the sediments of Poyang Lake were studied, and a quantitative source analysis of PAHs in different areas of the lake was conducted. PAHs were widespread within the sediments. The concentrations of ∑16PAHs in the surface sediments of all sites ranged from 203 to 2 318 µg·kg-1. The concentrations of PAHs in the surface sediments of the lake body were higher than those in the surface sediments of the inlet rivers. The ratio of PAHs in Poyang Lake was 4 rings > 5 rings > 6 rings > 3 rings > 2 rings; the composition of 4-ring PAHs was dominant, and its content accounted for 86.11% of ∑16PAHs. The 2- and 3-ring and some 4-ring PAHs, including Flua and Pyr, were more susceptible to SOM, and the 4 through 6-ring PAHs were more susceptible to ORP and heavy metals and other environmental factors. Spatially, the higher concentration of ∑16PAHs occurred in the area of the lake adjacent to Duchang County and Poyang County, where the terrain was relatively closed, and the water exchange with the surrounding area was less than that in other sections, which was not conducive to the migration, transformation, and degradation of pollutants. In the temporal distribution, the changes in PAHs concentration level and the development of GDP in Jiangxi Province showed high consistency, and the influence of economic development and human activities might have been the main reason for the increasing PAHs concentration level. The main sources of PAHs in surface sediments of Poyang Lake included petroleum pollution and oil and coal and biomass combustion sources, and there were some spatial differences in PAHs sources in different regions. This study can provide a reference for PAHs pollution in surface sediments of Poyang Lake, which is important for the ecological environmental protection and management of Poyang Lake.

[Distribution of Typical Resistant Bacteria and Resistance Genes in Source Water of the Middle and Lower Reaches of the Yellow River].

The Yellow River water of an urban area located in the middle and lower reaches of the Yellow River was taken as the research object， in which the seasonal and along-range distribution of total culturable bacteria， typical antibiotic resistant bacteria （amoxicillin resistant bacteria and sulfamethoxazole-resistant bacteria）， and their corresponding typical resistance genes ï¼»ß-lactam resistance gene （blaCTX-M） and sulfamamide resistance genes （sulI and sulⅡ）， as well as intⅠ1 were investigated. The results showed that the total culturable bacteria， ß-lactam-resistant bacteria and sulfonamide-resistant bacteria in the Yellow River Basin were significantly affected by temperature and human activities. The composition and quantity of their genera had obvious spatiotemporal distribution characteristics， in which Bacillus and Pseudomonas were dominant in the composition and number of bacteria. The abundance of resistance genes decreased with the decrease in temperature. The proportion of ß-lactam resistance genes in the total genes was higher than that of sulfanilamide genes， and sulI was the dominant gene in sulfanilamide genes. Correlation analysis showed that class Ⅰ integron played an important role in accelerating the spread of resistance genes. This study offers insight into the status quo of water resistance pollution in the Yellow River and provides theoretical support for the risk assessment of resistance genes in the middle and lower reaches of the Yellow River Basin.

[Spatial and Temporal Distribution and Risk Assessment of Heavy Metals in Surface Water of Changshou Lake Reservoir, Chongqing].

To understand the water pollution status and environmental risks of Changshou Lake, the concentrations of heavy metals (Cr, Cu, Zn, As, Cd, and Pb) in the water were collected and analyzed during different seasons. The study investigated temporal and spatial variations, distribution characteristics, pollution levels, and health risks associated with heavy metals in Changshou Lake. The results showed that all six heavy metals were below than the Class Ⅰ standard of the Surface Water Environmental Quality Standard (GB 3838-2002), but recent years have witnessed an increasing trend, with Cu, As, and Pb showing a significant increase (P<0.05). The temporal and spatial distributions of these heavy metals were different. Temporally, Cr and Cd concentrations in surface water were higher in summer, As and Zn were higher in spring, and Pb and Cu were higher in autumn and winter. Spatially, the concentrations of Cr, As, Cu, Zn, and Pb showed higher concentrations in the southern outlet of the reservoir, the northwestern Longxi River inlet, and the central part of the reservoir, whereas Cd was higher in the northern stagnant area. The overall levels of heavy metals in the water body of Changshou Lake were low, with Cr and Cu slightly polluted, while other heavy metals were identified as having an insignificant pollution level. Drinking water was the primary exposure pathway to carcinogenic and non-carcinogenic heavy metals in surface water bodies. The health risk values of Cr and As in water bodies were high, ranging from 6.2×10-10 to 3.0×10-4 and 5.1×10-8 to 3.9×10-5, respectively. The corresponding contribution rates for children and adults to the total health risk were high, with Cr accounting for 87.18% and 87.20%, respectively, while As accounted for 12.73% and 12.71%, respectively. Therefore, it is crucial to prioritize environmental risks associated with Cr and Cu, as well as the health risks associated with Cr and As in Changshou Lake These findings provide a scientific foundation for water pollution control and environmental quality improvement in Changshou Lake, and rational development and utilization of water resources.

High-resolution estimation of near-surface ozone concentration and population exposure risk in China.

Considering the spatial and temporal effects of atmospheric pollutants, using the geographically and temporally weighted regression and geo-intelligent random forest (GTWR-GeoiRF) model and Sentinel-5P satellite remote sensing data, combined with meteorological, emission inventory, site observation, population, elevation, and other data, the high-precision ozone concentration and its spatiotemporal distribution near the ground in China from March 2020 to February 2021 were estimated. On this basis, the pollution status, near-surface ozone concentration, and population exposure risk were analyzed. The findings demonstrate that the estimation outcomes of the GTWR-GeoiRF model have high precision, and the precision of the estimation results is higher compared with that of the non-hybrid model. The downscaling method enhances estimation results to some extent while addressing the issue of limited spatial resolution in some data. China's near-surface ozone concentration distribution in space shows obvious regional and seasonal characteristics. The eastern region has the highest ozone concentrations and the lowest in the northeastern region, and the wintertime low is higher than the summertime high. There are significant differences in ozone population exposure risks, with the highest exposure risks being found in China's eastern region, with population exposure risks mostly ranging from 0.8 to 5.

Assessing Derawan Island's Coral Reefs over Two Decades: A Machine Learning Classification Perspective.

This study aims to understand the dynamic changes in the coral reef habitats of Derawan Island over two decades (2003, 2011, and 2021) using advanced machine learning classification techniques. The motivation stems from the urgent need for accurate, detailed environmental monitoring to inform conservation strategies, particularly in ecologically sensitive areas like coral reefs. We employed non-parametric machine learning algorithms, including Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Tree (CART), to assess spatial and temporal changes in coral habitats. Our analysis utilized high-resolution data from Landsat 9, Landsat 7, Sentinel-2, and Multispectral Aerial Photos. The RF algorithm proved to be the most accurate, achieving an accuracy of 71.43% with Landsat 9, 73.68% with Sentinel-2, and 78.28% with Multispectral Aerial Photos. Our findings indicate that the classification accuracy is significantly influenced by the geographic resolution and the quality of the field and satellite/aerial image data. Over the two decades, there was a notable decrease in the coral reef area from 2003 to 2011, with a reduction to 16 hectares, followed by a slight increase in area but with more heterogeneous densities between 2011 and 2021. The study underscores the dynamic nature of coral reef habitats and the efficacy of machine learning in environmental monitoring. The insights gained highlight the importance of advanced analytical methods in guiding conservation efforts and understanding ecological changes over time.

Predicting plant-pollinator interactions: concepts, methods, and challenges.

Plant-pollinator interactions are ecologically and economically important, and, as a result, their prediction is a crucial theoretical and applied goal for ecologists. Although various analytical methods are available, we still have a limited ability to predict plant-pollinator interactions. The predictive ability of different plant-pollinator interaction models depends on the specific definitions used to conceptualize and quantify species attributes (e.g., morphological traits), sampling effects (e.g., detection probabilities), and data resolution and availability. Progress in the study of plant-pollinator interactions requires conceptual and methodological advances concerning the mechanisms and species attributes governing interactions as well as improved modeling approaches to predict interactions. Current methods to predict plant-pollinator interactions present ample opportunities for improvement and spark new horizons for basic and applied research.

More than one millennium (2nd-16th century CE) of the White Plague in the Carpathian Basin - New cases, expanding knowledge.

The causative agent of tuberculosis is still a widespread pathogen, which caused the death of ca. 1.6 million people globally in 2021. The paleopathological study of human remains revealed the antiquity of the disease and its continuous presence throughout the history of humankind. The Carpathian Basin has always been a biocultural melting pot, since it has seen several migrations over the centuries, and served as a location of admixture and interaction for numerous populations of different cultures. Thus, this geographical territory is ideal for the examination of the coevolutionary processes of hosts and their pathogens. We aimed to reveal the spatial and temporal distribution of tuberculosis cases excavated inside the borders of Hungary between the 2nd and 16th centuries CE. We established a comprehensive database by collecting 114 already published cases and introducing 39 new cases. The involved cases include those that have been confirmed by different molecular methods, as well as possible infections that were identified based on the presence of macromorphological and radiological alterations. The progress of future molecular and paleopathological studies can be facilitated by our dataset, as it presents spatial and temporal information concerning the spread of the disease in the Carpathian Basin, as well as the biological profile and detailed paleopathological description of lesions illustrated by photo- and radiographs.

The Dynamic Distribution of Wolbachia and Rickettsia in AsiaII1 Bemisia tabaci.

Wolbachia and Rickettsia are bacterial endosymbionts that can induce a number of reproductive abnormalities in their arthropod hosts. We screened and established the co-infection of Wolbachia and Rickettsia in Bemisia tabaci and compared the spatial and temporal distribution of Wolbachia and Rickettsia in eggs (3-120 h after spawning), nymphs, and adults of B. tabaci by qPCR quantification and fluorescent in situ hybridization (FISH). The results show that the titer of Wolbachia and Rickettsia in the 3-120 h old eggs showed a "w" patterned fluctuation, while the titers of Wolbachia and Rickettsia had a "descending-ascending descending-ascending" change process. The titers of Rickettsia and Wolbachia nymphal and the adult life stages of Asia II1 B. tabaci generally increased with the development of whiteflies. However, the location of Wolbachia and Rickettsia in the egg changed from egg stalk to egg base, and then from egg base to egg posterior, and finally back to the middle of the egg. These results will provide basic information on the quantity and localization of Wolbachia and Rickettsia within different life stages of B. tabaci. These findings help to understand the dynamics of the vertical transmission of symbiotic bacteria.

Evaluating the spatial and temporal distribution of emerging contaminants in the Pearl River Basin for regulating purposes.

Little information is available on how the types, concentrations, and distribution of chemicals have evolved over the years. The objective of the present study is therefore to review the spatial and temporal distribution profile of emerging contaminants with limited toxicology data in the pearl river basin over the years to build up the emerging contaminants database in this region for risk assessment and regulatory purposes. The result revealed that seven groups of emerging contaminants were abundant in this region, and many emerging contaminants had been detected at much higher concentrations before 2011. Specifically, antibiotics, phenolic compounds, and acidic pharmaceuticals were the most abundant emerging contaminants detected in the aquatic compartment, while phenolic compounds were of the most profound concern in soil. Flame retardants and plastics were the most frequently studied chemicals in organisms. The abundance of the field concentrations and frequencies varied considerably over the years, and currently available data can hardly be used for regulation purposes. It is suggested that watershed management should establish a regular monitoring scheme and comprehensive database to monitor the distribution of emerging contaminants considering the highly condensed population in this region. The priority monitoring list should be formed in consideration of historical abundance, potential toxic effects of emerging contaminants as well as the distribution of heavily polluting industries in the region.

Spatiotemporal Dynamics of Phthalate Esters in Tea Plants Growing Different Geographical Environments and an Attempt on Their Risk Assessment.

The phthalate esters (PAEs) have become ubiquitous pollutants. In the present work, we investigated their pollution on teas. Dimethyl phthalate (DMP), diethyl phthalate (DEP), diisobutyl phthalate (DiBP), di-n-butyl phthalate (DBP), and di-(2-ethyl) hexyl phthalate (DEHP) were detected in all fresh tea leaves with DBP being the major congener of PAEs in teas followed by DiBP and DEHP. Seasonal variation, spatial distribution difference, correlationship of environmental factors, and potential health risks of PAEs were analyzed. The PAEs content in one bud and two leaves was lower than that in upper mature leaves in tea plants. The PAEs content in fresh tea leaves was the lowest in spring, while it was high in autumn and winter. The correlation analysis results showed that PAEs had significantly negative correlation with ambient air temperature, while it was positively correlated with the air quality index. PAEs analysis of spring tea in Anhui and Zhejiang provinces further indicated that the factor of provincial regions had little impact on the PAEs pollution level in tea. By contrast, the different environmental areas significantly affected PAE pollution, especially the agricultural areas. The human daily intake-based (13 g/day) risk assessment indicated that both the carcinogenic and non-carcinogenic risks (1.76 × 10-7-6.12 × 10-7) of PAEs via tea consumption were acceptable, with the estrogen equivalence (1.60-6.29 ng E2/kg) being at a medium level. This study provides significant information for pollution control and risk assessment of PAEs in Chinese tea production.

The spatial-temporal pattern of Japanese encephalitis and its influencing factors in Guangxi, China.

Japanese encephalitis (JE) is a major global public health threat. Using Japanese encephalitis incidence data from 2004 to 2010 in Guangxi Province, China, this study comprehensively explored the driving forces and the interactive effects between environmental and social factors of Japanese encephalitis using the Geo-detector method. The results indicated that the incidence of Japanese encephalitis showed a fluctuating downward trend from 2004 to 2010. The onset of JE was seasonal, mainly concentrated in June-July, and highly aggregated in northwestern Guangxi. Among the factors associated with Japanese encephalitis, days with temperatures >30 °C, accumulated temperatures >25 °C, slope, the normalized difference vegetation index, the gross domestic product of tertiary industries, the gross domestic product of primary industries and the number of pigs slaughtered showed higher contributions to Japanese encephalitis incidence. An enhanced interactive effect was found between environmental and social factors, and the interaction between days with humidity levels >80% and the gross domestic product of tertiary industries had the greatest combined effect on JE. These findings enhanced the understanding of the combined effect of social and environmental factors on the incidence of Japanese encephalitis and could help improve Japanese encephalitis transmission control and prevention strategies.

Spatio-Temporal Distribution Characteristics and Drivers of PM2.5 Pollution in Henan Province, Central China, before and during the COVID-19 Epidemic.

PM2.5 is the main cause of haze pollution, and studying its spatio-temporal distribution and driving factors can provide a scientific basis for prevention and control policies. Therefore, this study uses air quality monitoring information and socioeconomic data before and during the COVID-19 outbreak in 18 prefecture-level cities in Henan Province from 2017 to 2020, using spatial autocorrelation analysis, ArcGIS mapping, and the spatial autocorrelation analysis. ArcGIS mapping and the Durbin model were used to reveal the characteristics of PM2.5 pollution in Henan Province in terms of spatial and temporal distribution characteristics and analyze its causes. The results show that: (1) The annual average PM2.5 concentration in Henan Province fluctuates, but decreases from 2017 to 2020, and is higher in the north and lower in the south. (2) The PM2.5 concentrations in Henan Province in 2017-2020 are positively autocorrelated spatially, with an obvious spatial spillover effect. Areas characterized by a high concentration saw an increase between 2017 and 2019, and a decrease in 2020; values in low-concentration areas remained stable, and the spatial range showed a decreasing trend. (3) The coefficients of socio-economic factors that increased the PM2.5 concentration were construction output value > industrial electricity consumption > energy intensity; those with negative effects were: environmental regulation > green space coverage ratio > population density. Lastly, PM2.5 concentrations were negatively correlated with precipitation and temperature, and positively correlated with humidity. Traffic and production restrictions during the COVID-19 epidemic also improved air quality.

Water Environment Characteristics and Water Quality Assessment of Water Source of Diversion System of Project from Hanjiang to Weihe River.

The water source of the water diversion project from the Hanjiang River to the Weihe River is one of the most important drinking water sources in China. Its water quality is related to the water safety of the long-distance water diversion system from the Hanjiang to Weihe Rivers. In order to explore the spatiotemporal change trend of the water environment characteristics of the water source area and analyze the key factors that have a greater impact on it, this study collected 9 types of water environment physical and chemical parameters from 10 water quality monitoring sections from 2017 to 2019; the water environment characteristics of the water source area of the water diversion system from the Hanjiang River to the Weihe River were analyzed and evaluated by using the variance analysis method, the hierarchical cluster analysis method and the water quality identification index evaluation method. The results were as follows. (1) There was spatiotemporal heterogeneity in a number of physical and chemical parameters in the water body of the water source. In terms of time, the concentrations of CODMn, COD, BOD5 and F- were higher in the flood season (July-October) than in the non-flood season (November-June). The concentrations of DO, TP and TN in the non-flood season were higher than those in the flood season. Spatially, the concentration of physical and chemical parameters of the water body in the Huangjinxia Reservoir area was higher than that in the Sanhekou Reservoir area. (2) The water quality of the water source area was good. The comprehensive water quality reached the Class II water quality standard of surface water environmental quality. Time showed that the comprehensive water quality in the non-flood season was better than that in the flood season. Spatially, the overall water quality of the tributaries was better than that of the mainstream. TN is a key indicator that affects water quality. (3) The spatial and temporal differences in water quality in water source areas are mainly affected by factors such as rainfall, temperature and human activities. This study can provide a scientific and data basis for related research on maintaining and improving the quality of the ecological environment of the water source areas of the Hanjiang to Weihe River Water Diversion System.

Bayesian spatiotemporal modelling analysis of hemorrhagic fever with renal syndrome outbreaks in China using R-INLA.

Hemorrhagic fever with renal syndrome (HFRS) is a category B infectious disease caused by Hantavirus infection, which can cause acute kidney injury and has a high mortality rate. At present, China is the country most severely afflicted by HFRS in the world, and it is critical to carry out efficient HFRS prevention and management in a scientific and accurate manner. The study used data on the incidence of HFRS in mainland China from 2015 to 2018, built a Bayesian hierarchical spatiotemporal distribution model, and applied the Integrated Nested Laplace Approximation algorithm to analyse the factors influencing the development of HFRS, the spatial and temporal distribution characteristics, and the threshold exceedance locations. The results revealed that the woodland and grassland area (RR = 1.357, 95% CI: 1.005-1.791), economic level (RR = 1.299, 95% CI: 1.007-1.649), and traffic level (RR = 2.442, 95% CI: 1.825-3.199) were all significantly and positively associated with the development of HFRS, with traffic level having the strongest promoting effect. The seasonal cycle was obvious in time, with peaks in May-June and October-December each year, most notably in November. Spatially, there was a south-heavy north-light trend, with a high risk of incidence largely in places rich in mountain and forest vegetation, of which Guizhou, Guangxi, Guangdong, and Jiangxi provinces continuing to have a high incidence in recent years, and the evolution of the epidemic in Hubei and Hunan was becoming more serious. When the early warning threshold was set at 0.2, the detection impact was best, and Guizhou, Guangxi, Guangdong, Jiangxi, Hainan, and Tianjin were positioned near the critical point of the exceedance threshold with the highest risk of incidence. It is recommended that the relevant managers call for active vaccination of outdoor workers, such as those working in agriculture and construction sites, implement rat prevention and extermination before winter arrives, and warn high-risk and medium-high-risk areas to conduct early outbreak surveillance. Move the prevention and control gates forward based on the exceedance threshold for doing preventive and control detection and epidemic research and judgement work.

Evaluating traffic emission control policies based on large-scale and real-time data: A case study in central China.

The traffic control policies, including "Odd and Even" (OAE) and "One Day Per Week" (ODPW), were adopted in Zhengzhou, China. In this study, we use the bottom-up policy evaluation framework to capture the temporal-spatial characteristics of traffic conditions and vehicle emissions under various traffic restriction scenarios. Moreover, we use the street-scale simulation model to evaluate the effectiveness of improving air quality. Results showed that the improvements in traffic conditions led to the emission decrease by about 28.3 % for carbon monoxide (CO), 16.2 % for nitrogen oxide (NOx), 21.3 % for particulate matter (PM2.5), and 23.2 % for total hydrocarbon (THC) under OAE. During ODPW, total vehicle emissions decreased by 14.1 % for CO, 10.2 % for NOx, 13.7 % for PM2.5, and 12.4 % for THC. However, the spatial analysis indicates traffic restrictions could not significantly reduce those emissions caused by high traffic volume; besides, buses, middle-duty trucks, and heavy-duty trucks have partly offset the reduction benefit from restrictions. The air quality simulation results reveal no significant concentration decrease of CO and nitrogen dioxide (NO2) in most areas. With the update of vehicles, stricter management of high-emission vehicles, and limited coverage for implementation of policies, the traffic control policies were not as effective as before. The limitations of the restriction policies are gradually prominent, and upgrade policies are urgently needed to continuously improve urban air quality in the future.

Spatial and temporal dynamics of microbial community composition and factors influencing the surface water and sediments of urban rivers.

The temporal and spatial characteristics of urban river bacterial communities help us understand the feedback mechanism of bacteria to changes in the aquatic environment. The Fuhe River plays an important role in determining the water ecological environment of Baiyangdian Lake. 16S rRNA gene sequencing was used to study the microbial distribution characteristics in the Fuhe River in different seasons. The results showed that some environmental factors of the surface water (ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP)) were different on the spatial and temporal scales. Moreover, there were no seasonal differences in the contents of TN, TP, total organic carbon (TOC), or heavy metals in the sediments. The distributions of Cyanobacteria, Actinomycetes and Firmicutes in the water and Actinomycetes and Planctomycetes in the sediments differed significantly among seasons (P < 0.05). There were significant spatial differences in bacteria in the surface water, with the highest abundance of Proteobacteria recorded in the river along with the highest nutrient concentration, while the abundance of Bacteroidetes was higher in the upstream than the downstream. Microbial communities in the water were most sensitive to temperature (T) and the TP concentration (P < 0.01). Moreover, differences in the bacterial community were better explained by the content of heavy metals in the sediments than by the chemical characteristics. A PICRUSt metabolic inference analysis showed that the effect of high summer temperatures on the enzyme action led to an increase in the abundances of the metabolic-related genes of the river microorganisms.