Human Exposure to Ambient Atmospheric Microplastics in a Megacity: Spatiotemporal Variation and Associated Microorganism-Related Health Risk.

Microplastics are found in various human tissues and are considered harmful, raising concerns about human exposure to microplastics in the environment. Existing research has analyzed indoor and occupational scenarios, but long-term monitoring of ambient atmospheric microplastics (AMPs), especially in highly polluted urban regions, needs to be further investigated. This study estimated human environmental exposure to AMPs by considering inhalation, dust ingestion, and dermal exposure in three urban functional zones within a megacity. The annual exposure quantity was 7.37 × 104 items for children and 1.06 × 105 items for adults, comparable with the human microplastic consumption from food and water. Significant spatiotemporal differences were observed in the characteristics of AMPs that humans were exposed to, with wind speed and rainfall frequency mainly driving these changes. The annual human AMP exposure quantity in urban green land spaces, which were recognized as relatively low polluted zones, was comparable with that in public service zones and residential zones. Notably, significant positive correlations between the AMP characteristics and the pathogenicity of the airborne bacterial community were discovered. AMP size and immune-mediated disease risks brought by atmospheric microbes showed the most significant relationship, where Sphingomonas might act as the potential key mediator.

Influencing factors and spatiotemporal heterogeneity of livestock greenhouse gas emission: Evidence from the Yellow River Basin of China.

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO2e) in 2000 to 77.568 Mt CO2e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively.

Multiscale spatiotemporal characteristics and influencing factors of ecosystem service value of groundwater in China.

Ecosystem services are fundamental to human survival on Earth, but studies on ecosystem service value of groundwater (ESV-G) are rare. The multiscale characteristics and influencing factors of ESV-G in China from 2000 to 2020 were analyzed in this study. The results showed that ESV-G decreased first and then increased, the average ESV-G was 130.30 thousand yuan/km2, and ESV-G tended to shift towards middle level (second to fourth class). The Hu Line was the dividing line between the first class (more than half area) and the others. The AI and FRAC values indicated that the patches of ESV-G were more concentrated, with simpler shapes that were more amenable to governance at the province scale. Hot spots and cold spots were mainly located in the eastern and western parts of Hu Line, respectively. The ESV-G of the cold spots per unit area at the province scale was higher than that at the city scale, which indicated that the province scale had the potential for higher ESV-G per unit area and cost advantage. Precipitation and temperature were the main factors affecting ESV-G; the influence of human activities on ESV-G increased on a larger scale as time went by. Combination of precipitation and Digital Elevation Model (DEM) had the greatest influence on ESV-G among the combinational influencing factors. The province scale was the optimal scale to manage ESV-G. Climate change had led to the expansion of hot and cold spots of ESV-G, northern and southern areas should combine existing policies to carry out differentiated governance. This study extended the scope of ecosystem service value studies from land surface to underground, providing a scientific basis for the management of groundwater ecosystem.

Spatial-temporal distribution characteristics of surface water pollutants and their potential sources in Ngari, China.

The Ngari region has many important rivers and is critical to water resource security and water resource continuity in China and even in adjoining Asian countries. However, the spatial distribution and monthly variation in local water quality have been poorly understood until recently. In this study, the spatial-temporal variations of 12 water quality parameters, including pH, dissolved oxygen (DO), permanganate index (IMn), chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), ammonia nitrogen (NNH3), total nitrogen (Ntotal), total phosphorus (Ptotal), copper (Cu), fluoride (F), arsenic (As) and cadmium (Cd), were determined from samples collected monthly at 22 water cross-sectional sites in the Ngari region in 2020. The surface water pollution in the southern Ngari region was the most serious, and the water pollution level in winter was higher than that in the other seasons. As (0.0781 ~ 0.6154 mg/L) and F (1.05 ~ 4.64 mg/L) were the main exceedance factors derived from the recharge of high arsenic and fluoride geothermal water and weathering of As and F-bearing minerals. The hazard quotient and carcinogenic risk for As and F at the five contaminated sampling sites indicated potential health risks and even carcinogenicity to local populations. The hydrochemistry types of the lakes and rivers in the Ngari region were mainly chloride water and carbonate water. The results from this study can provide a scientific basis for the prevention and control of surface water pollution in the Ngari region and contribute to subsequent research on the ecology of water bodies.

Disaster process-based spatiotemporal characteristics of apricot frost in the warm temperate zone (WTZ), China.

Frost stress is a major environmental factor that limits apricot growth in the warm temperate zone (WTZ) of China, and is always triggered by extreme low temperature weather processes. In this study, the characteristics of the apricot frost processes f(D, Tcum), which were identified from historical disaster representation, were analyzed and apricot frost evaluation indicators were developed, thus facilitating the process-based assessment and spatiotemporal analysis of apricot frost processes. Periods of low temperature that persist for 1~2, 3, and ≥4 days (i.e., duration days, D) provide the initial identification indicator for light, moderate, and severe apricot frost. The threshold ranges for Tcum are 0~3.9, 9.2~12.0, and >16.2 for D values of 1~2, 3, and ≥4, respectively. The northwest of the WTZ is dominated by apricot frost, with approximately 80% of apricot frost being light, followed by moderate and severe. Regional apricot frost exhibited a significant decreasing trend over the last four decades. A total of 29.65% of stations, which were mainly located in the northwest and middle parts of the study region, detected an increasing trend in apricot frost. The results provide technical support for targeted apricot frost level detection, and the process-based spatiotemporal characteristics of apricot frost can provide basic information for the prevention and mitigation of apricot frost.

Satellite Video Moving Vehicle Detection and Tracking Based on Spatiotemporal Characteristics.

The complex backgrounds of satellite videos and serious interference from noise and pseudo-motion targets make it difficult to detect and track moving vehicles. Recently, researchers have proposed road-based constraints to remove background interference and achieve highly accurate detection and tracking. However, existing methods for constructing road constraints suffer from poor stability, low arithmetic performance, leakage, and error detection. In response, this study proposes a method for detecting and tracking moving vehicles in satellite videos based on the constraints from spatiotemporal characteristics (DTSTC), fusing road masks from the spatial domain with motion heat maps from the temporal domain. The detection precision is enhanced by increasing the contrast in the constrained area to accurately detect moving vehicles. Vehicle tracking is achieved by completing an inter-frame vehicle association using position and historical movement information. The method was tested at various stages, and the results show that the proposed method outperformed the traditional method in constructing constraints, correct detection rate, false detection rate, and missed detection rate. The tracking phase performed well in identity retention capability and tracking accuracy. Therefore, DTSTC is robust for detecting moving vehicles in satellite videos.

Spatiotemporal characteristics and dynamic risk assessment of a multi-solvents abandoned pesticide-contaminated site with a long history, in China.

With the development of the economy and the adjustment of urban planning and layout, abandoned pesticide sites are widely distributed in major and medium cities in China. Groundwater pollution of a large number of abandoned pesticide-contaminated sites has caused great potential risks to human health. Up to now, few relevant studies concerned the spatiotemporal variation of risks exposure to multi-pollutants in groundwater using probabilistic methods. In our study, the spatiotemporal characteristics of organics contamination and corresponding health risks in the groundwater of a closed pesticide site were systematically assessed. A total of 152 pollutants were targeted for monitoring over a time span up to five years (i.e., June 2016-June 2020). BTEX, phenols, chlorinated aliphatic hydrocarbons, and chlorinated aromatic hydrocarbons were the main contaminants. The metadata was subjected to health risk assessments using the deterministic and probabilistic methods for four age groups, and the results showed that the risks were highly unacceptable. Both methods showed that children (0-5 years old) and adults (19-70 years old) were the age groups with the highest carcinogenic and non-carcinogenic risks, respectively. Compared with inhalation and dermal contact, oral ingestion was the predominant exposure pathway that contributed 98.41%-99.69% of overall health risks. Spatiotemporal analysis further revealed that the overall risks first increased then decreased within five years. The risk contributions of different pollutants were also found to vary substantially with time, indicating that dynamic risk assessment is necessary. Compared with the probabilistic method, the deterministic approach relatively overestimated the true risks of OPs. The results provide a scientific basis and practical experience for scientific management and governance of abandoned pesticide sites.

Spatiotemporal heterogeneity of the relationships between PM2.5 concentrations and their drivers in China's coastal ports.

PM2.5 is one of the primary air pollutants that affect air quality and threat human health in the port areas. To prevent and control air pollution, it is essential to understand the spatiotemporal distributions of PM2.5 concentrations and their key drivers in ports. 19 coastal ports of China are selected to examine the spatiotemporal distributions of PM2.5 concentrations during 2013-2020. The annual average PM2.5 concentration decreases from 61.03 µg/m3 to 30.17 µg/m3, with an average decrease rate of 51.57%. Significant spatial autocorrelation exists among PM2.5 concentrations of ports. The result of the geographically and temporally weighted regression (GTWR) model shows significant spatiotemporal heterogeneity in the effects of meteorological and socioeconomic factors on PM2.5 concentrations. The effects of boundary layer height on PM2.5 concentrations are found to be negative in most ports, with a stronger effect found in the Pearl River Delta, Yangtze River Delta and some ports of the Bohai Rim Area. The total precipitation shows negative effects on PM2.5 concentrations, with the strongest effect found in ports of the Southeast Coast. The effects of surface pressure on PM2.5 concentrations are positive, with stronger effects found in Beibu Gulf Port and Zhanjiang Port. The effects of wind speed on PM2.5 concentrations generally increase from south to north. Cargo throughput shows strong and positive effects on PM2.5 concentrations in ports of Bohai Rim Area; the positive effects found in Beibu Gulf Port increased from 2013 to 2018 and decreased since 2019. The positive effects of GDP and nighttime light on PM2.5 concentrations gradually decrease and turn negative from south to north. Understandings obtained from this study can potentially support the prevention and control of air pollution in China's coastal ports.

Spatiotemporal trends and ecological determinants of cardiovascular mortality among 2844 counties in mainland China, 2006-2020: a Bayesian modeling study of national mortality registries.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in China. No previous study has reported CVD mortality at county-level, and little was known about the nonmedical ecological factors of CVD mortality at such small scale in mainland China. Understanding the spatiotemporal variations of CVD mortality and examining its nonmedical ecological factors would be of great importance to tailor local public health policies. METHODS: By using national mortality registration data in China, this study used hierarchical spatiotemporal Bayesian model to demonstrate spatiotemporal distribution of CVD mortality in 2844 counties during 2006 to 2020 and investigate how nonmedical ecological determinants have affected CVD mortality inequities from the spatial perspectives. RESULTS: During 2006-2020, the age-standardized mortality rate (ASMR) of CVD decreased from 284.77 per 100,000 in 2006 to 241.34 per 100,000 in 2020. Among 2844 counties, 1144 (40.22%) were hot spots counties with a higher CVD mortality risk compared to the national average and located mostly in northeast, north central, and westernmost regions; on the contrary, 1551 (54.53%) were cold spots counties and located mostly in south and southeast coastal counties. CVD mortality risk decreased from 2006 to 2020 was larger in counties where CVD mortality rate had been higher in 2006 in most of the counties, vice versa. Nationwide, nighttime light intensity (NTL) was the major influencing factor of CVD mortality, a higher NTL appeared to be negatively associated with a lower CVD mortality, with one unit increase in NTL, and the CVD mortality risk will decrease 11% (relative risk of NTL was estimated as 0.89 with 95% confidence interval of 0.83-0.94). CONCLUSIONS: Substantial between-county discrepancies of CVD mortality distribution were observed during past 15 years in mainland China. Nonmedical ecological determinants were estimated to significantly explain the overall and local spatiotemporal patterns of this CVD mortality risk. Targeted considerations are needed to integrate primary care with clinical care through intensifying further strategies to narrow unequally distribution of CVD mortality at local scale. The approach to county-level analysis with small area models has the potential to provide novel insights into Chinese disease-specific mortality burden.

[18F]DPA-714 PET imaging for the quantitative evaluation of early spatiotemporal changes of neuroinflammation in rat brain following status epilepticus.

BACKGROUND: Most antiepileptic drug therapies are symptomatic and adversely suppress normal brain function by nonspecific inhibition of neuronal activity. In recent times, growing evidence has suggested that neuroinflammation triggered by epileptic seizures might be involved in the pathogenesis of epilepsy. Although the potential effectiveness of anti-inflammatory treatment for curing epilepsy has been extensively discussed, the limited quantitative data regarding spatiotemporal characteristics of neuroinflammation after epileptic seizures makes it difficult to be realized. We quantitatively analyzed the spatiotemporal changes in neuroinflammation in the early phase after status epilepticus in rats, using translocator protein (TSPO) positron emission tomography (PET) imaging, which has been widely used for the quantitative evaluation of neuroinflammation in several animal models of CNS disease. METHODS: The second-generation TSPO PET probe, [18F]DPA-714, was used for brain-wide quantitative analysis of neuroinflammation in the brains of rats, when the status epilepticus was induced by subcutaneous injection of kainic acid (KA, 15 mg/kg) into those rats. A series of [18F]DPA-714 PET scans were performed at 1, 3, 7, and 15 days after status epilepticus, and the corresponding histological changes, including activation of microglia and astrocytes, were confirmed by immunohistochemistry. RESULTS: Apparent accumulation of [18F]DPA-714 was observed in several KA-induced epileptogenic regions, such as the amygdala, piriform cortex, ventral hippocampus, mediodorsal thalamus, and cortical regions 3 days after status epilepticus, and was reversibly displaced by unlabeled PK11195 (1 mg/kg). Consecutive [18F]DPA-714 PET scans revealed that accumulation of [18F]DPA-714 was focused in the KA-induced epileptogenic regions from 3 days after status epilepticus and was further maintained in the amygdala and piriform cortex until 7 days after status epilepticus. Immunohistochemical analysis revealed that activated microglia but not reactive astrocytes were correlated with [18F]DPA-714 accumulation in the KA-induced epileptogenic regions for at least 1 week after status epilepticus. CONCLUSIONS: These results indicate that the early spatiotemporal characteristics of neuroinflammation quantitatively evaluated by [18F]DPA-714 PET imaging provide valuable evidence for developing new anti-inflammatory therapies for epilepsy. The predominant activation of microglia around epileptogenic regions in the early phase after status epilepticus could be a crucial therapeutic target for curing epilepsy.

Spatiotemporal features of ß-γ phase-amplitude coupling in Parkinson's disease derived from scalp EEG.

Abnormal phase-amplitude coupling between ß and broadband-γ activities has been identified in recordings from the cortex or scalp of patients with Parkinson's disease. While enhanced phase-amplitude coupling has been proposed as a biomarker of Parkinson's disease, the neuronal mechanisms underlying the abnormal coupling and its relationship to motor impairments in Parkinson's disease remain unclear. To address these issues, we performed an in-depth analysis of high-density EEG recordings at rest in 19 patients with Parkinson's disease and 20 age- and sex-matched healthy control subjects. EEG signals were projected onto the individual cortical surfaces using source reconstruction techniques and separated into spatiotemporal components using independent component analysis. Compared to healthy controls, phase-amplitude coupling of Parkinson's disease patients was enhanced in dorsolateral prefrontal cortex, premotor cortex, primary motor cortex and somatosensory cortex, the difference being statistically significant in the hemisphere contralateral to the clinically more affected side. ß and γ signals involved in generating abnormal phase-amplitude coupling were not strictly phase-phase coupled, ruling out that phase-amplitude coupling merely reflects the abnormal activity of a single oscillator in a recurrent network. We found important differences for couplings between the ß and γ signals from identical components as opposed to those from different components (originating from distinct spatial locations). While both couplings were abnormally enhanced in patients, only the latter were correlated with clinical motor severity as indexed by part III of the Movement Disorder Society Unified Parkinson's Disease Rating Scale. Correlations with parkinsonian motor symptoms of such inter-component couplings were found in premotor, primary motor and somatosensory cortex, but not in dorsolateral prefrontal cortex, suggesting motor domain specificity. The topography of phase-amplitude coupling demonstrated profound differences in patients compared to controls. These findings suggest, first, that enhanced phase-amplitude coupling in Parkinson's disease patients originates from the coupling between distinct neural networks in several brain regions involved in motor control. Because these regions included the somatosensory cortex, abnormal phase-amplitude coupling is not exclusively tied to the hyperdirect tract connecting cortical regions monosynaptically with the subthalamic nucleus. Second, only the coupling between ß and γ signals from different components appears to have pathophysiological significance, suggesting that therapeutic approaches breaking the abnormal lateral coupling between neuronal circuits may be more promising than targeting phase-amplitude coupling per se.

Understanding the nonpoint source pollution loads' spatiotemporal dynamic response to intensive land use in rural China.

The extensive use of land resources and environmental pollution in rural areas are two major problems prevalent in China and even the world. It is unknown whether improving the degree of intensive use of rural land can reduce environmental pollution; whether environmental pollution will be promoted or inhibited still lacks in-depth discussion. This paper first provides a theoretical analysis of the generation process of nonpoint source pollution loads (NPSP) in rural land use (RLU) and the mechanism and path of intensive rural land use (IRLU) to reduce agricultural nonpoint source pollution loads (ANPSP). Then, it takes 31 provinces in China from 1978 to 2019 as the research object to examine the temporal and spatial evolution features of IRLU and ANPSP. Furthermore, the paper uses the decoupling model and the Environmental Kuznets curve (EKC) model to test the linear and nonlinear relationship between the two. The research shows that the degree of IRLU in China decreased from 0.54 in 1978 to 0.27 in 2006, and then continuously increased to 0.56 in 2019. Moreover, the ANPSP continued to increase from 1955.14 t in 1978-3622.74 t in 2019. The decoupling relationship between the degree of IRLU and environmental pollution experienced the evolution process of "negative decoupling-decoupling", and the EKC had an "inverted N-shaped" characteristic. Overall, China shows that the IRLU helps to reduce ANPSP. At the same time, it was also found that there is obvious heterogeneity among the 31 provinces used in this research in China. Among them, the degree of intensive land use (ILU) in the principal grain-producing regions tends to be better and stable, while other areas show fluctuating changes. The ANPSP in economically developed areas gradually decreases, while that in underdeveloped areas continues to increase. More than 80% of the provinces in China show a trend of IRLU to advance the reduction of ANPSP, but there has also been an increase in the over-intensification of RLU in some major grain-producing areas. The research concludes that there is an inevitable relationship between RLU and ANPSP. Appropriately increasing ILU has a positive effect on decreasing ANPSP.

Bacterioplankton community indicators for seasonal variation in a fragmented subtropical river.

In this study, spatiotemporal investigations were conducted along five cascade dams in the main channel of the North River of China during 2019 to explore bacterioplankton community indicators of water environments in a fragmented, highly regulated river. Bacterioplankton communities were good bioindicators of temporal variation in river environments, especially when considering the bacterial class level. Specifically, the most dominant bacterial classes (Gammaproteobacteria, Oxyphotobacteria, and Actinobacteria) and sub-dominant bacterial classes (Bacteroidia, Betaproteobacteria, and Acidimicrobiia) exhibited obvious temporal variation. Rainfall, water temperature (WT), water transparency (SD), and pH were all highly associated with temporal variation. In contrast, bacterioplankton indicators of spatial variation were limited to individual dominant bacterial classes for individual study periods, while rainfall, total phosphorus (TP), and pH were also associated with spatial variation. Clustering of bacterioplankton community compositions revealed that temporal differences were much stronger than spatial differences, which is consistent with most environmental parameters exhibiting obvious temporal differences, but minimal spatial differences. A possible reason for these observations could be that river fragmentation caused by cascade dams weakened spatial differences in communities, with WT, rainfall, and river runoff playing key roles in these patterns. In conclusion, bacterioplankton communities were good bioindicators of water environments in the fragmented river ecosystem of this study and their temporal variation was more apparent than their spatial variation.

Measuring green development level at a regional scale: framework, model, and application.

In this study, we propose and construct a novel model that measures regional green development level based on the "three-circle" conceptual framework for green development. Using Jiangsu Province in eastern China as a case study, the spatial-temporal characteristics and dynamics of the green development level from 2000 to 2020 were evaluated using a multi-source dataset at the grid-cell level. Our results show that (1) the analytical hierarchy process-based model proposed herein has higher reliability in terms of the development level measurement than principal component analysis and the entropy weight method. In addition, the average score of green development in the study area was approximately 0.53. Spatially, the green development level in the eastern coastal areas of the study area was found to be generally higher than in other regions, while that in southwestern regions is relatively low. In terms of sub-regions, the green development level scores of the study area have been ranked as follows: middle Jiangsu > southern Jiangsu > northern Jiangsu. (2) It was observed that the gravity center of the green development level can be divided into three stages during the study, with a whole had shifted to the north. (3) For most cities in Jiangsu, the green development level initially increased at first, then declined, and then increased again. (4) In the future, the green development level of Jiangsu Province should pay more attention to promoting regional coordinated development and relationships between society and the environment under rapid economic development.

Spatiotemporal evolution law and output prediction of construction waste in the People's Republic of China.

Based on the relevant data of construction waste (CW) in the People's Republic of China (PRC) from 2010 to 2018, this study applied K-means clustering algorithm and grey prediction methods to systematically investigate the spatiotemporal characteristic distribution and provincial clustering of CW in the PRC, and predicted the annual output of CW in the next five years from the scientific perspective. Results showed that the annual output of CW in the PRC displayed an overall trend of "rising first and then falling" and "being high in the middle east and low in the northwest," and the areas with obvious agglomeration gradually spread from the west to the middle and eastern regions. The law of development was consistent with the goals of the Chinese government to promulgate urban agglomeration development policies, prefabricated building encouragement policies, and CW management regulations. In the next five years, the annual output of CW in the PRC will increase by a small margin. Thus, all aspects of CW resource management should be conducted in a planned and step-by-step manner.

Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics.

COVID-19 blocked Wuhan in China, which was sealed off on Chinese New Year's Eve. During this period, the research on the relevant topics of COVID-19 and emotional expressions published on social media can provide decision support for the management and control of large-scale public health events. The research assisted the analysis of microblog text topics with the help of the LDA model, and obtained 8 topics ("origin", "host", "organization", "quarantine measures", "role models", "education", "economic", "rumor") and 28 interactive topics. Obtain data through crawler tools, with the help of big data technology, social media topics and emotional change characteristics are analyzed from spatiotemporal perspectives. The results show that: (1) "Double peaks" feature appears in the epidemic topic search curve. Weibo on the topic of the epidemic gradually reduced after January 24. However, the proportion of epidemic topic searches has gradually increased, and a "double peaks" phenomenon appeared within a week; (2) The topic changes with time and the fluctuation of the topic discussion rate gradually weakens. The number of texts on different topics and interactive topics changes with time. At the same time, the discussion rate of epidemic topics gradually weakens; (3) The political and economic center is an area where social media is highly concerned. The areas formed by Beijing, Shanghai, Guangdong, Sichuan and Hubei have published more microblog texts. The spatial division of the number of Weibo social media texts has a high correlation with the economic zone division; (4) The existence of the topic of "rumor" will enable people to have more communication and discussion. The interactive topics of "rumors" always have higher topic popularity and low emotion text expressions. Through the analysis of media information, it helps relevant decision makers to grasp social media topics from spatiotemporal characteristics, so that relevant departments can accurately grasp the public's subjective ideas and emotional expressions, and provide decision support for macro-control response strategies and measures and risk communication.

Laminar fMRI: What can the time domain tell us?

The rapid developments in functional MRI (fMRI) acquisition methods and hardware technologies in recent years, particularly at high field (≥7 T), have enabled unparalleled visualization of functional detail at a laminar or columnar level, bringing fMRI close to the intrinsic resolution of brain function. These advances highlight the potential of high resolution fMRI to be a valuable tool to study the fundamental processing performed in cortical micro-circuits, and their interactions such as feedforward and feedback processes. Notably, because fMRI measures neuronal activity via hemodynamics, the ultimate resolution it affords depends on the spatial specificity of hemodynamics to neuronal activity at a detailed spatial scale, and by the evolution of this specificity over time. Several laminar (≤1 mm spatial resolution) fMRI studies have examined spatial characteristics of the measured hemodynamic signals across cortical depth, in light of understanding or improving the spatial specificity of laminar fMRI. Few studies have examined temporal features of the hemodynamic response across cortical depth. Temporal features of the hemodynamic response offer an additional means to improve the specificity of fMRI, and could help target neuronal processes and neurovascular coupling relationships across laminae, for example by differences in the onset times of the response across cortical depth. In this review, we discuss factors that affect the timing of neuronal and hemodynamic responses across laminae, touching on the neuronal laminar organization, and focusing on the laminar vascular organization. We provide an overview of hemodynamics across the cortical vascular tree based on optical imaging studies, and review temporal aspects of hemodynamics that have been examined across cortical depth in high spatiotemporal resolution fMRI studies. Last, we discuss the limits and potential of high spatiotemporal resolution fMRI to study laminar neurovascular coupling and neuronal processes.

Dual-circulation: influence mechanism of ETS's carbon reduction and its spatiotemporal characteristics based on intensity modified SDID model.

Traditional DID models overlook variations in policy intensity, causing estimation deviations from the actual situation and a limited understanding of the influence mechanism. In response, the Intensity Modified SDID Model is built to examine the influence mechanism of ETS's carbon reductions. Moreover, through model extensions, the study explores the spatiotemporal characteristics and heterogeneities of ETS's effects. Results show that: (1) "Dual-circulation" influence mechanism is confirmed, where ETS directly contributes to carbon reductions (2.70% to 10.0% impact) through external pathways, and internal pathways continuously strengthen reduction effects, comprehensive mechanisms are thereby formed and enhanced based on interaction among internal and external pathways. (2) Reasonable ETS levels are estimated and proposed to achieve "Dual Carbon Target", constraining nationwide carbon quotas by 20 billion tons/year, increasing carbon trading volumes by 80 thousand tons/year, and elevating the carbon trading prices by 100 RMB (14 USD) per ton. (3) ETS's carbon reduction effects are identified with temporal and spatial characteristics, temporally, effects peak in the 4th period (Event+4) but diminish in the 5th period (Event+5), spatially, effects peak in areas distancing around 1000 km but disappear beyond 1500 km. (4) ETS also has synergistic effects with atmospheric pollution reduction, including industrial emissions of sulfur dioxide and smoke (dust), but are insignificant to industrial emissions of wastewater and solid waste.

Response of solar-induced chlorophyll fluorescence-based spatial and temporal evolution of vegetation in Xinjiang to multiscale drought.

Climate change and human activities have increased droughts, especially overgrazing and deforestation, which seriously threaten the balance of terrestrial ecosystems. The ecological carrying capacity and vegetation cover in the arid zone of Xinjiang, China, are generally low, necessitating research on vegetation response to drought in such arid regions. In this study, we analyzed the spatial and temporal characteristics of drought in Xinjiang from 2001 to 2020 and revealed the response mechanism of SIF to multi-timescale drought in different vegetation types using standardized precipitation evapotranspiration index (SPEI), solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) data. We employed trend analysis, standardized anomaly index (SAI), Pearson correlation, and trend prediction techniques. Our investigation focused on the correlations between GOSIF (a new SIF product based on the Global Orbital Carbon Observatory-2), NDVI, and EVI with SPEI12 for different vegetation types over the past two decades. Additionally, we examined the sensitivities of vegetation GOSIF to various scales of SPEI in a typical drought year and predicted future drought trends in Xinjiang. The results revealed that the spatial distribution characteristics of GOSIF, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) were consistent, with mean correlations with SPEI at 0.197, 0.156, and 0.128, respectively. GOSIF exhibited the strongest correlation with SPEI, reflecting the impact of drought stress on vegetation photosynthesis. Therefore, GOSIF proves advantageous for drought monitoring purposes. Most vegetation types showed a robust response of GOSIF to SPEI at a 9-month scale during a typical drought year, with grassland GOSIF being particularly sensitive to drought. Our trend predictions indicate a decreasing trend in GOSIF vegetation in Xinjiang, coupled with an increasing trend in drought. This study found that compared with that of the traditional greenness vegetation index, GOSIF has obvious advantages in monitoring drought in the arid zone of Xinjiang. Furthermore, it makes up for the lack of research on the mechanism of vegetation GOSIF response to drought on multiple timescales in the arid zone. These results provide strong theoretical support for investigating the monitoring, assessment, and prediction of vegetation response to drought in Xinjiang, which is vital for comprehending the mechanisms of carbon and water cycles in terrestrial ecosystems.

Spatiotemporal variability of extreme precipitation in east of northwest China and associated large-scale circulation factors.

Spatial and temporal distributions and influencing factors of extreme precipitation are important bases for coping with future climate change. The spatiotemporal variability and affecting factors of extreme precipitation indices (EPIs) in east of northwest China (ENW) during 1961-2015 were investigated using a series of approaches such as modified Mann-Kendall trend test, Hurst exponent, ensemble empirical mode decomposition (EEMD), and geodetector model. The results showed that CDD and CWD decreased significantly (P < 0.01), with rates of 1.4 days/decade and 0.07 days/decade, respectively. EPIs in ENW exhibited an obvious heterogeneity. CDD gradually increased from the southeast to the northwest. The remaining EPIs generally showed the opposite trend. Geodetector results demonstrated that large-scale circulation factors had a significant impact on EPIs in ENW. The influence of large-scale climate factors on EPIs was concentrated in nonlinear enhancement, and Nino3.4 and SO were the dominant driving factors that played a major role in the variability of EPIs. The results of this study provided a reference for ENW and other arid and semi-arid regions to cope with extreme climates and develop corresponding strategies.