Search

Simple Summary: Chiggers are common ectoparasites on rodents and other small mammals, and they transmit scrub typhus, a zoonotic disease. Dehong in Yunnan Province of southwest China is located on the China–Myanmar border, and it is a focus of scrub typhus. The present paper reports the infestation and distribution of chiggers on small mammals in Dehong for the first time. From 1760 rodents and other sympatric small mammals, a total of 9309 chiggers were identified, representing 117 species. Most chigger species had low host specificity. Leptotrombidium deliense, a major vector of scrub typhus in China, was the dominant chigger species in Dehong, and it was mainly distributed in flatland areas and indoors. The infestation and community indexes of chiggers in mountainous areas and outdoors were higher than those in flatland areas and indoors. The species abundance distribution of the chigger community conformed to log-normal distribution, and the total number of chigger species was roughly estimated to be 147. The species diversity of the chigger community is high in Dehong, with an obvious environmental heterogeneity. The low host specificity of chiggers and the occurrence of a large number of L. deliense in Dehong would increase the transmission risk of scrub typhus on the China–Myanmar border. Chiggers (chigger mites) are a group of tiny arthropods, and they are the exclusive vector of Orientia tsutsugamushi (Ot), the causative agent of scrub typhus (tsutsugamushi disease). Dehong Prefecture in Yunnan Province of southwest China is located on the China–Myanmar border and is an important focus of scrub typhus. Based on the field surveys in Dehong between 2008 and 2022, the present paper reports the infestation and ecological distribution of chiggers on the body surface of rodents and other sympatric small mammals (shrews, tree shrews, etc.) in the region for the first time. The constituent ratio (Cr), prevalence (PM), mean abundance (MA), and mean intensity (MI) were routinely calculated to reflect the infestation of small-mammal hosts with chiggers. Additionally, the species richness (S), Shannon–Wiener diversity index (H), Simpson dominance index (D), and Pielou's evenness index (E) were calculated to illustrate the chigger community structure. Preston's log-normal model was used to fit the theoretical curve of species abundance distribution, and the Chao 1 formula was used to roughly estimate the expected total species. The "corrplot" package in R software (Version 4.3.1) was used to analyze interspecific relationships, and the online drawing software was used to create a chord diagram to visualize the host–chigger associations. From 1760 small-mammal hosts, a total of 9309 chiggers were identified as belonging to 1 family, 16 genera, and 117 species, with high species diversity. The dominant chigger species were Leptotrombidium deliense, Walchia ewingi, and Gahrliepia longipedalis, with a total Cr = 47.65% (4436/9309), among which L. deliense is the most important vector of Ot in China. The overall infestation indexes (PM, MA, and MI) and community parameters (S, H, and E) of chiggers in the mountainous areas and outdoors were higher than those in the flatland areas and indoors, with an obvious environmental heterogeneity. Leptotrombidium deliense was the dominant species in the flatland and indoors, while G. longipedalis was the prevalent species in the mountainous and outdoor areas. The species abundance distribution of the chigger community conformed to log-normal distribution with the theoretical curve equation: S (R) ′ = 28 e − [ 0.23 (R − 0) ] 2 , indicating the existence of many rare species and only a few dominant species in the community. The expected total number of chigger species was roughly estimated to be 147 species, 30 more than the 117 species actually collected, suggesting that some uncommon species may have been missed in the sampling survey. The host–parasite association analysis revealed that one host species can harbor different chigger species, and one chigger species can parasitize different host species with low host specificity. A positive or negative correlation existed among different chigger species, indicating a cooperative or competitive interspecific relationship. The species diversity of chiggers is high in Dehong on the China–Myanmar border, and a large host sample is recommended to find more uncommon species. There is an obvious environmental heterogeneity of the chigger community, with different species diversity and dominant species in different environments. The low host specificity of chiggers and the occurrence of a large number of L. deliense in Dehong, especially in flatland areas and indoors, would increase the risk of persistent transmission of scrub typhus in the region. [ABSTRACT FROM AUTHOR]

A regional aerosol model can complement globally averaged models and improve the accuracy of atmospheric numerical models in local applications. This study established a seasonal aerosol model based on data from the Aerosol Robotic Network (AERONET) of the sea area around eastern China, and its performance in calculating the aerosol optical depth (AOD) was evaluated. The seasonal columnar volume particle size distributions (VPSDs) illustrated a bimodal structure consisting of fine and coarse modes. The VPSDs of spring, autumn, and winter roughly agreed with each other, with their amplitudes of fine and coarse modes being almost equal; however, the fine mode of the summer VPSD was approximately twice as high as that of the coarse mode. Lognormal mode decomposition analysis revealed that fine and coarse modes comprised two sub-modes. Fitting the seasonal VPSDs to the four-mode lognormal distribution yielded a parameterized aerosol size distribution model. Furthermore, seasonal variations in complex refractive indices (CRIs) indicated unignorable changes in aerosol compositions. Overall, error analysis validated that the proposed model could meet accuracy requirements for optical engineering applications, with median AOD calculation errors of less than 0.01. [ABSTRACT FROM AUTHOR]

To comprehend the empirical seismic vulnerability capability of various typical structures in towns and suburbs, this study considers, as the research background, the structural damage data observation from the Mw 7.1 Yushu earthquake that occurred on 2010 April 14th in China. The proposed research activity sorts out the actual investigation data (7156 buildings) of five types of typical structures in towns and villages and establishes the vulnerability and seismic fragility evaluation model of a group of buildings considering multidimensional parameters by using the Chinese macroseismic intensity standard. Using spatial modal, numerical calculation, and regression analysis methods, an updated lognormal distribution vulnerability and resilience assessment model based on multidimensional quantitative parameters is performed. Based on the principle of the conditional probability and damage quantification model, an innovative model (domain, point cloud, curve, surface, matrix, and function) is established for regional vulnerability and seismic resilience assessment of typical group buildings. A logarithmic relationship model considering both the updated Chinese macroseismic intensity and three-dimensional composite peak ground acceleration as intensity measures is proposed, and an empirical vulnerability assessment model for typical rural buildings is established. The traditional average earthquake loss index calculation model is updated, and an innovative regional domain vulnerability assessment model is conducted. Taking the samples of various typical structures surveyed in the Yushu earthquake, regional group structure vulnerability domain comparison models of various structures are performed. Ultimately, depending on the typical damage characteristics of structures, the actual damage features and mechanisms of various structures are analysed. [ABSTRACT FROM AUTHOR]

Chiggers are a group of ectoparasites and they are the vector of scrub typhus. Although the Ryukyu mouse (Mus caroli) is a common species of rodent in some outdoor habitats, few studies are about the mouse itself and its ectoparasites. To date, there has been no specific report on chiggers of M. caroli. Based on the field investigation in southwest China from 2001 to 2019, this paper reported the infestation and distribution of chiggers on M. caroli for the first time. Among the 91 sites investigated, 263 Ryukyu mice were captured at 18 sites, and 678 chiggers were collected from the mice. The collected chiggers were identified to be one family, two subfamilies, six genera, and 16 species with relatively low species diversity. The overall infestation prevalence (PM), mean abundance (MA), and mean intensity (MI) were PM = 27.38%, MA = 2.58 chiggers/per mouse, and MI = 9.42 chiggers/per mouse respectively. The dominant chigger species are Walchia ewingi and W. micropelta with a total constituent ratio of Cr = 94.10% (638/678), and they were of aggregated distribution among different individuals of the host M. caroli. The distribution of two dominant chigger species seemed to be mutually independent with the association coefficient V ≈ 0 (p < 0.001). The infestation (PM, MA, and MI) of M. caroli with chiggers greatly fluctuated in different geographical landscapes, altitudes, and latitudes with an obvious environmental heterogeneity. The male and adult M. caroli harbored much more chigger mites with significantly higher infestations (PM, MA and MI) than the female and juvenile mice. The theoretical curve of species abundance distribution of the chigger mite community on M. caroli was fitted by Preston lognormal distribution model with fitting goodness R2 = 0.77. Based on the iChao1 formula, the expected total number of chigger species on the mice was estimated to be 24 species. [ABSTRACT FROM AUTHOR]

Insoluble particles influence weather and climate by means of heterogeneous freezing process. Current weather and climate models face considerable uncertainties in freezing-process simulation due to limited information regarding species and number concentrations of heterogeneous ice-nucleating particles, particularly insoluble particles. Here, for the first time, the size distribution and species of insoluble particles are analyzed in 30 shells of 12 hailstones collected from China using scanning electron microscopy and energy-dispersive X-ray spectrometry. A total of 289 461 insoluble particles were detected and divided into three species – organics, dust, and bioprotein – utilizing machine learning methods. The size distribution of the insoluble particles of each species varies greatly among the different hailstones but little in their shells. Further, a classic size distribution of organics and dust followed logarithmic normal distributions, which could potentially be adapted in future weather and climate models despite the existence of uncertainties. Our findings highlight the need for atmospheric chemistry to be considered in the simulation of ice-freezing processes. [ABSTRACT FROM AUTHOR]

The temporal distribution of earthquakes provides important basis for earthquake prediction and seismic hazard analysis. The relatively limited records of strong earthquakes have often made it difficult to study the temporal distribution models of regional strong earthquakes. However, there are hundreds of years of complete strong earthquake records in the North China Seismic Zone, providing abundant basic data for studying temporal distribution models. Using the data of M ≥ 6.5 earthquakes in North China as inputs, this paper estimates the model parameters using the maximum likelihood method with Poisson, Gamma, Weibull, Lognormal and Brownian passage time (BPT) distributions as target models. The optimal model for describing the temporal distribution of earthquakes is determined according to Akaike information criterion (AIC),and Kolmogorov–Smirnov test (K–S test). The results show that Lognormal and BPT models perform better in describing the temporal distribution of strong earthquakes in North China. The mean recurrence periods of strong earthquakes (M ≥ 6.5) calculated based on these two models are 8.1 years and 13.2 years, respectively. In addition, we used the likelihood profile method to estimate the uncertainty of model parameters. For the BPT model, the mean and 95% confidence interval of recurrence interval μ is 13.2 (8.9–19.1) years, and the mean and 95% confidence interval of α is 1.29 (1.0–1.78). For the Lognormal model, the mean value and 95% confidence interval of v is 2.09 (1.68–2.49), the mean value exp (v) corresponding to earthquake recurrence interval is 8.1 (5.4–12.1) years. In this study, we also calculated the occurrence probability of M ≥ 6.5 earthquakes in the North China Seismic Zone in the future, and found that the probability and 95% confidence interval in the next 10 years based on the BPT model is 35.3% (26.8%-44.9%); the mean value and 95% confidence interval of earthquake occurrence probability based on the Lognormal distribution is 35.4% (22.9%-49.7%); the mean probability and 95% confidence interval based on the Poisson model is 53.1% (41.1%-64%). The results of this study may provide important reference for temporal distribution model selection and earthquake recurrence period calculation in future seismic hazard analysis in North China. [ABSTRACT FROM AUTHOR]

A 6.9 magnitude earthquake at a depth of 10 km struck Menyuan County, Haibei Prefecture, Qinghai Province, China, on January 8, 2022. This earthquake damaged some railway bridges on the Lanzhou-Xinjiang Passenger Dedicated Line. This study combines relevant historical earthquake damage experience, considers the effects of earthquake intensity, site soil classification, superstructure type, foundation failure factor, number of spans, and total bridge length, and develops empirical formulas for seismic damage prediction of railway bridges using ordinal logistic regression model in SPSS software. Since the accuracy of both predictions for seismic damage is practically the same, using this regression to predict seismic damage to railway bridges is considered valid. The predicated seismic damage matrix, as were the anticipated multi-intensity mean damage index and the empirical vulnerability curve based on the two-parameter lognormal distribution function, were generated on this basis. We get a risk assessment of future seismic damage for regional bridges when they experience different intensities or peak ground acceleration. According to the conclusions, although the suggested particular equations and vulnerability curves do not apply to the remainder of the region owing to geographical uniqueness, the technical approach is valid. It may be used as a reference for seismic damage prediction and vulnerability evaluation in other regions. The earthquake damage prediction matrix derived from the regression analysis can provide reasonable and fast forecasts before the next earthquake. [ABSTRACT FROM AUTHOR]

By integrating the vulnerability index of buildings, earthquake disaster matrix, and historical earthquake disaster data, the vulnerability of typical buildings and compounds in rural areas of China are analyzed. The disaster matrix of buildings in historical earthquakes was obtained by analyzing historical earthquake disaster data. By integrating the historical disaster matrix and vulnerability analysis of typical structures in rural areas, a seismic disaster matrix was established to assess the seismic performance of regional compounds. Combined with the historical earthquake disaster matrix and vulnerability index, the lognormal distribution function was used to analyze the vulnerability index of regional structures and compounds to obtain the disaster matrix of structures under different seismic intensities. Considering the structures and compounds in the rural areas in the Tianjin district as an example, the seismic vulnerability of typical structures was investigated. The regional structure disaster matrix of the study region was established and the vulnerability indices of different types of structures and compounds were obtained to clarify the regional disaster prevention ability. [ABSTRACT FROM AUTHOR]

Based on the field investigation in five provincial regions of Southwest China between 2001 and 2019, the present paper reports the infestation and distribution of chigger mites on the Confucian white-bellied rat Niviventer confucianus in China for the first time. A total of 11,017 chigger mites were collected from the body surface of 911 N. confucianus rat hosts, and 10,161 of them were identified as 166 species and 16 genera in three subfamilies under two families with high species diversity (S = 166, H' = 3.19, E = 0.62). Of 911 N. confucianus rats, 341 individuals were infested with chiggers with high overall prevalence (PM = 37.43%), mean abundance (MA = 12.09 mites/rat) and mean intensity (MI = 32.31 mites/rat). On the body surface of N. confucianus, Ascoschoengastia sifanga was the most dominant chigger species followed by Walchia ewingi and Leptotrombidium rupestre. All the three dominant chigger species showed an aggregated distribution pattern among different individuals of N. confucianus. Chigger infestations on the same rat host (N. confucianus) showed some heterogeneity under different environmental conditions such as latitudes, longitudes, altitudes and landscapes. Based on Preston's lognormal model, the species abundance distribution of chiggers on N. confucianus conformed to a lognormal distribution pattern, and the predicted total species of chiggers on N. confucianus in Southwest China was estimated to be 228 species. [ABSTRACT FROM AUTHOR]

Late frost is one of the most destructive meteorological disasters in the Loess Plateau of China. A great threat can be posed to the sustainable production of apples, leading to great economic losses in the apple industry. Thus, it is a high demand to explore the occurrence of late frost events for the prevention of apple late frost disasters in the decision-making of the local apple industry. In this study, the late frost return periods were investigated on the duration and severity of late frost events using the Coupla functions. The reliability of the model was then verified to analyze the characteristics of apple late frost. The study area was taken as the apple-producing areas of Shaanxi Province in western China. The meteorological datasets were collected from the seven weather stations from 1971-2018. The daily minimum temperature (Tmin) of 0℃ was taken as the critical temperature for the occurrence of apple late frost events, in order to extract the two characteristic variables of duration and severity of late frost events. These characteristic variables of late frost events were first fitted by seven common distribution functions, respectively. Kolmogorov Smirnov (K-S) test was then carried out to verify the model. The joint distributions of late frost characteristic variables were constructed to evaluate the goodness-of-fit using six Copula functions. The occurrence probability and return period of late frost events were analyzed with the optimized Copula functions. The results showed that the severity of late frost risks generally increased from the southeast to northwest in the study area from 1971 to 2018. The optimal marginal distribution of late frost duration was in the log-normal distribution, while there was a great difference in the optimal marginal distributions of late frost severity. A significant positive correlation was found between the duration variables and the severity of late frost at each station. The goodness-of-fit test demonstrated that most of the stations presented the optimal distribution of Normal Copula function for late frost events. The joint cumulative probability increased significantly, as the severity and duration of late frost increased, but the increasing trend was much slower than before. A much more significant increase was observed in the co-occurrence return period under the same increase of univariate value, compared with the joint. The univariate return period was always between the joint and co-occurrence return period. Once the univariate return period was small enough, the optimal range of the actual univariate return period can be estimated, according to the joint and the co-occurrence return period. In general, a low probability was found in the late frost events with long duration and high severity at the weather stations in apple-producing areas in Shaanxi Province of China. However, the stations in the Yan’an area were more susceptible to the late frost events with high severity or long duration, as well as the late frost events with both high severity and long duration. Thus, more attention can be paid to late frost risks in the Yan’an area. This finding can provide a theoretical base to deal with the late frost disaster in apple production. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) may cause severe impacts on the activities of coastal fishing vessels. Due to the unavailability or unacceptability of detailed Automatic Identification System (AIS) data that are capable of differentiating fishing activity from navigation, as well as the lack of detailed models and observation data of TC winds, few studies have provided quantitative and reliable assessment of the impacts of TCs on fishing activities. In this study, we modeled snapshots for the TC winds of 52 TCs over the Northwest Pacific (NWP) basin from 2013 to 2018, as well as daily fishing hours and daily hours of presence (hereafter "vessel hours") of fishing vessels. Based on these data, the spatiotemporal pattern of fishing vessel activity over offshore China was first analyzed and mapped. Then, a TC wind hazard index and absolute and relative impact indices were proposed to assess the impact of the 52 TCs on fishing and vessel hours. Their relationship was then fitted with the cumulative distribution function (CDF) of the log-normal distribution. The results show that in the 2013−2018 period, the most active fishing areas were located in the South China Sea. In each instance, an increase was first observed in the initial several years; then a decrease followed in the yearly total fishing hours per vessel in the remaining years. The relative impact index was significantly correlated to the TC wind hazard index proposed in this study. Based on the quantitative relationship between the specified TC hazard index and the impact indices, it is possible to implement a pre-cyclone rapid loss assessment due to TC avoidance in the future. [ABSTRACT FROM AUTHOR]

With the improvement of living standards, more and more residents in China choose short leisure travel at weekends. This study aims to model the leisure travel duration to investigate the relationship between travel time and residents' factors, which can provide guidance for the development of urban parks and improve the structure of transportation modes to promote low-carbon travel modes. The accelerated hazard model is applied to establish the model equation between travel time and various factors, to obtain the differences between weekend travel time in scenic spots and personal characteristics such as residents' playing time and travel mode choice. First, an analysis of variance was performed on the valid data which have been collected. Then, the Kaplan–Meier test proved that weekend activity types tend to follow different survival functions. Finally, this study established the lifespan regression equation of the travel time, and we found that the best fit is the Log-normal distribution. This study shows clearly that accelerated hazard models based on fixed parameters are better at evaluating the attractiveness of urban parks, and they can also get feedback travel characteristics of primary residents. So, we can build a lifespan analysis-based model for the travel time of urban residents, to help plan the urban parks. The result of this study can be used for predicting the flow of different travel modes at urban parks in cities, which can be helpful for regional traffic organization such as regional traffic flow guidance and signal timing. [ABSTRACT FROM AUTHOR]

At present, many levees contain a large number of loose bodies as a result of poor-quality construction, biological damage and other factors. In this context, loose bodies refer to soil with a relative density less than a specified value. Taking the Huaishu River levee in China as an example, this paper studies the distribution characteristics of loose bodies in the levee using statistical methods. First, ground-penetrating radar and other geophysical exploration methods are used to investigate loose bodies in the levee. The frequency distribution and Shapiro–Wilk method are then employed to study the distribution characteristics of the area and depth of loose bodies. The influence of loose bodies on the seepage field of the levee is then examined considering the spatial distribution of the loose bodies. It was found that the areas of loose bodies in the western and eastern upstream slope obey a logarithmic normal distribution. In the shallow layer (depth 0–1 m), loose bodies appear relatively frequently, and the frequency initially increases with depth before decreasing. The maximum hydraulic gradient of the levee initially increases and then decreases as the depth of the loose body increases. [ABSTRACT FROM AUTHOR]

The source identification and apportionment of heavy metals (HMs) is a vital issue for restoring contaminated soil. In this study, qualitative approaches [a finite mixture distribution model (FMDM) and raster-based principal components analysis (RB-PCA)] and a quantitative approach [positive matrix factorization (PMF)] were composed to identify and apportion the sources of five HMs (Cd, Hg, As, Pb, Cr) in Wenzhou City, China, using several crucial auxiliary variables. An initial ecological risk assessment suggested that the ecological risk level in the study area was generally considered low, with the greatest contamination contributions coming from Cd and Hg. The result of the FMDM showed that Cd and Pb fit a single log-normal distribution, Hg fit a double log-normal mixed distribution, and As and Cr presented a triple log-normal distribution. Each element was identified and separated from its natural or anthropogenic sources. A map of RB-PCA combined with an analysis of corresponding auxiliary variables suggested that the three main contribution sources in the entire study area were parental materials, industrial and agricultural mixed pollution, and mining exploration activities. Each element was discussed, using the PMF model, with regard to its quantitative contributions. Parental materials contributed to all elements (Cd, Hg, As, Pb, Cr) at 89.22%, 7.31%, 35.84%, 84.81% and 27.42%, respectively. Industrial emissions and agricultural inputs mixed pollution contributed 2.94%, 80.77%, 15.93%, 4.79%, and 25.63%, respectively. Mining activities contributed 7.84%,11.92%, 48.23%, 10.40% and 46.95%, respectively, to the five HMs. Such result could be used efficiently to generate scientific decisions and strategies in terms of decision-making on regulating HM pollution in soils. [ABSTRACT FROM AUTHOR]

The aim of this work is to present a method for calculating seismic fragility function of urban road network. In this paper, urban road system is simplified to a planar network. The spatial correlation of seismic ground motions is considered. The damage probability of network edge is determined by the fragility function of single road section. By repeating simulation, a large number of samples of post-earthquake road network are obtained. Their damage states are classified as minor, moderate, extensive and complete by piece number and diameter of the maximal piece. The seismic fragility function of road network is assumed in the form of lognormal cumulative distribution function and its parameters are identified by fitting the fragility function to the exceeding probability of the damage states. To demonstrate the practicality of the proposed method, an application to the urban road network of Tangshan City is performed. The case study indicates that the rare earthquake may cause the disconnection and fragmentation of the road network with high probability. The proposed framework is a valuable contribution to the seismic performance evaluation of urban road system and provides engineers and practitioners with a tool to design road network in high seismic hazard zone. [ABSTRACT FROM AUTHOR]

To control the deformation disaster and explore the effective in-situ evaluation method of filling in the Loess Plateau of China, the laboratory tests and cone penetration test (CPT), dynamic penetration test (DPT), standard penetration test (SPT) were carried out for a case of filling with large area. The research was performed based on data distribution, non-uniformity evaluation, correlation and sensitivity analysis. The results are as follows: (1) the filling filled by layered compaction still has non-uniformity. The distribution of CPT tip resistance is consistent with collapsibility coefficient and obeys logarithmic normal distribution. The distribution of CPT side friction and SPT hammer number are consistent with moisture content, void ratio and dry density and obey normal distribution. The distribution of DPT hammer number does not correspond to any soil properties index. The CPT also has the advantages to reflect layered compaction characteristics along filling depth and distinguish the boundary between filling and undisturbed soil. (2) Three test methods can all reflect the non-uniformity of soil properties in depth direction. However, for the horizontal direction, the CPT results can best reflect non-uniformity of actual collapse deformation, followed by SPT and DPT is the worst. (3) For the testing of filling compaction state, CPT tip resistance and SPT have good mathematical correlation, and the sensitivity of CPT tip resistance is significantly higher than other methods. For the testing of filling collapse deformation capacity, the CPT tip resistance, DPT and SPT all have good correlation and sensitivity. So CPT tip resistance has the best cooperation between correlation and sensitivity. (4) The CPT (especially tip resistance part) can be effectively applied to the properties evaluation of silty loess filling. The tip resistance to void ratio and collapsibility coefficient follow the exponential function and logarithmic function respectively. [ABSTRACT FROM AUTHOR]

The Ms 8.0 Wenchuan earthquake in 2008 and Ms 7.0 Lushan earthquake in 2013 produced thousands of landslides in the southern region of the Longmen Mountains in China. We conducted field investigations and analyzed remote sensing data to determine the distribution law of earthquake-triggered landslides. The results show a strong negative power law relationship between the size and frequency of landslides in VII, VIII, and IX seismic intensity zones, a weak power law in the X seismic intensity zone, and a lognormal distribution in the XI seismic intensity zone. Landslide density increases with increasing seismic intensity. A sandpile cellular automata model was built under the conceptual framework of self-organized criticality theory to simulate earthquake-induced landslides. Data from the simulations demonstrate that, with increasing disturbance intensity, the dynamical mechanism of the sandpile model changes from a strong power law to a weak power law and then to a lognormal distribution. Results from shaking table experiments of a one-sided slope sandpile show that, for peak ground acceleration (PGA) in the range of 0.075 – 0.125 g, the relation between the amount and frequency of sand follows a negative power law. For PGA between 0.15 and 0.25 g, the relation obeys a lognormal distribution. This verifies that the abovementioned distribution of earthquake-induced landslides should be a universal law from a physical viewpoint and may apply to other areas. This new perspective may be used to guide the development of an inventory of earthquake-triggered landslides and provide a scientific basis for their prediction. [ABSTRACT FROM AUTHOR]

Geological materials have randomness in nature. Statistical analysis can help revealing the variation pattern of the material parameters and the reliability of the slope. In this paper, the probability distribution and variability of shear strength parameters of typical Q2 and Q3 loess in Northwest China were statistically analysed using the collected geological survey data in Yan'an, Shaanxi Province. Resulting probability properties were applied to the reliability analysis for the natural and fill slope in loess area using the Monte Carlo Method. Finally, an optimization analysis was carried out for the fill slope in the background engineering project. Research results show that normal distribution and lognormal distribution can be used to describe the statistical properties of c and φ of Q2 and Q3 loess. Variance of c is large while the variability of φ is relatively small. The influence of the variability of φ on the reliability index of loess natural slope is generally larger than that of c. On the contrary, influence of the variability of c on the reliability index of the fill slope is generally greater than that of φ, which is related to the structural and uniformity of the soil. Finally, relation between slope height and minimum gradient coefficient is linear when the failure probability of fill slope is less than 10%. Results in this study can be used as a reference for the slope design and construction for the cut and fill engineering in loess area. [ABSTRACT FROM AUTHOR]

Objective: To determine whether or not chronic disease positively impacts medical costs among the rural elderly in China and to calculate medical expenditure induced by chronic disease between different groups of the rural elderly, as well as provide insight into the factors that affect medical losses induced by chronic disease among different household registration groups and different New Rural Pension Scheme statuses.Design: To estimate the share of medical expenses induced by chronic disease, this article uses a two-part model and a four-part model to analyze the causal effect of chronic disease on medical services and then uses a counter-factual method to estimate the share of medical expenses.Setting: The rapid development of China has changed nearly every aspect of life for the rural elderly. Many are concerned about the increasing prevalence of physical health issues, particularly chronic diseases, among the rural elderly. Nevertheless, there are no articles using nationally representative panel datasets that report differences in the cost of chronic disease between sub-populations.Participants: The panel dataset used for this study comes from the China Family Panel Studies (CFPS) data. In this study, we use the CFPS data for the years 2012, 2014 and 2016 to create a panel dataset that includes 2730 rural elderly for 3 years.Interventions: This article reports the representative estimate of medical expenditures attributable to chronic disease among rural elderly in China. On this basis, we estimate per capita medical spending among rural elderly under the condition of logarithmic normal distribution of different parameters between urban and rural or between groups that participate in the New Rural Pension Program and groups that do not.Main Outcome Measures: This study indicates that physical health status has a significant impact on both the probability of undergoing medical care and the size of medical expenditures among the rural elderly, and the influence was significant for all patients, including outpatients and inpatients.Results: Chronic illness has significant effects on individual medical expenses, and they aggregately contribute to 63.96% of total personal expected medical expenditure. Specifically, the medical spending caused by chronic disease was part of a non-uniform distribution, with the rural, male, older, married and higher educated groups spending more money on medical costs induced by chronic disease.Conclusions: Examining trends in the prevalence of chronic diseases and evaluating medical spending on chronic diseases can prevent and control potential medical costs among rural elderly, especially for vulnerable groups, which helps to predict future health-care needs. [ABSTRACT FROM AUTHOR]

The Ms 8.0 Wenchuan earthquake in 2008 and Ms 7.0 Lushan earthquake in 2013 produced thousands of landslides in the southern region of the Longmen Mountains in China. We conducted field investigations and analyzed remote sensing data to determine the distribution law of earthquake-triggered landslides. The results show a strong negative power-law relationship between the size and frequency of landslides in VII, VIII, and IX seismic intensity zones, a weak power law in the X seismic intensity zone, and a lognormal distribution in the XI seismic intensity zone. Landslide density increases with increasing seismic intensity. A sand pile cellular automata model was built under the conceptual framework of self-organized criticality theory to simulate earthquake-induced landslides. Data from the simulations demonstrate that with increasing disturbance intensity, the dynamical mechanism of the sand pile model changes from a strong power law to a weak power law and then to a lognormal distribution. Results from shaking table experiments of a one-sided slope sand pile show that for peak ground acceleration (PGA) in the range of 0.075 g-0.125 g, the relation between the amount and frequency of sand follows a negative power law. For PGA between 0.15 g and 0.25 g, the relation obeys a lognormal distribution. This verifies that the above-mentioned distribution of earthquake-induced landslides should be a universal law from a physical viewpoint and may apply to other areas. This new perspective may be used to guide development of an inventory of earthquake-triggered landslides and provide a scientific basis for their prediction. [ABSTRACT FROM AUTHOR]

Transport of dust sand caused by wind erosion is a serious problem in many arid regions in the world, and it plays animportantrolein global biogeo chemical cycle. The dust induced by transport of aeolian sand can affect atmospheric radiation balance, climate, environment, air quality and human health. It has hence attracted increased attention in various areas ranging from geomorphology and climatology to meteorology and ecological-environmental science. In addition to its natural origin, dust could also be instigated by anthropogenesis activities due to desertification.However, the relative contribution of the two origins is still an issue remaining elusive. In addition, being able to accurately estimate the potential of a dust source is crucial to evaluating the influence of desertification and climate change on dust flux. The Taklimakan desert(TD) is the second largest shifting sand desert in the world, with about 85% made up by shifting sand dunes.It is an important source of the dusts seen in China. Understanding particle size distribution of the sand and dust emission is helpful to evaluate quality of the atmospheric environment and the consequence for climate at regional scale. We collected 138 samples from soil surface based on spatial distribution and types of the surfaces including farmland, dune and desert. Particle sizes of each sample was analyzed using the Mastersizer 2000 laser particle size analyzer, and the associated dust release flux was calculated using the DPM model.The particle size distribution of the micro aggregates in each sample was obtained to elucidate its potential influence on dust release flux. The results showed that: 1) The content of silt and clay in the 138 samples was least, accounting for 10% to 18% of the total particles in the mobile sand dunes, and 20% to 30% of the total particles in the sand ridges (e.g., sandy soil and sandy-sandy loams). Most samples taken from farmland (e. g., oasis and forest belt) are meadow soil, with silt and clay content being 50%-80%, differing from the silt and clay content in samples taken from the Gobi (desert area). 2) Fine sand and silty-fine sand are the smaller particles in the surface soil and can be divided into three groups, each described by a log normal distribution: silt-fine sand group, fine sand group and coarse sand group, with median particle size being 90, 225 and 500 μm, and the standard deviation being 1.02, 1.53 and 1.08, respectively, accounting for 30%, 49% and 21% respectively. 3) Emission of silt-fine sand and fine sand is most potential, followed by medium-coarse sand. The coarse sand is least to emit; the difference between the maximum and the minimum emission was in the order of 10-2μg/(m²·s) in magnitude. The results reflect the difference in dust emission from different soil surfaces and they are greatly important for quantitative assessment of dust emission in the studied region and beyond [ABSTRACT FROM AUTHOR]

In response to regional ozone (O 3) pollution, Chinese government has implemented air pollution control measures in recent years. Here, a case study was performed at an O 3 -polluted city, Wuhu, in Yangtze River Delta region of China to investigate O 3 variation trend and the relationship to its precursors after implementation of Clean Air Action Plan Phase II, which aims to reduce O 3 pollution. The results showed that peak O 3 concentration was effectively reduced since Clean Air Action Plan Phase II. Due to significant NOx reduction, O 3 formation tended to shift from volatile organic compound (VOC)-limited regimes to NOx-limited regimes during 2018–2022. VOC/NOx ratios measured in 2022 revealed that peak O 3 concentration tended to respond positively to NOx. Apart from high-O 3 period, Wuhu was still in a VOC-limited regime. The relationship of maximum daily 8-h ozone average and NO 2 followed a lognormal distribution with an inflection point at 20 μg m−3 of NO 2 , suggesting that Wuhu should conduct joint control of VOC and NOx with a focus on VOC reduction before the inflection point. Alkenes and aromatics were suggested to be preferentially controlled due to their higher ozone formation potentials. Using random forest meteorological normalization method, meteorology had a positive effect on O 3 concentration in 2018, 2019 and 2022, but a negative effect in 2020 and 2021. The meteorology could explain 44.0 ± 19.1% of the O 3 variation during 2018–2022. High temperature favors O 3 production and O 3 pollution occurred more easily when temperature was over 25 °C, while high relative humidity inhibits O 3 generation and no O 3 pollution was found at relative humidity above 70%. This study unveils some new insights into the trend of urban O 3 pollution in Yangtze River Delta region since Clean Air Action Plan Phase II and the findings provide important references for formulating control strategies against O 3 pollution. [Display omitted] • Peak O 3 pollution was mitigated by sustained NOx reduction since CAAPP II. • O 3 formation sensitivity tended to switch from VOC-limited regimes to transition regimes. • Alkenes and aromatics were suggested to be controlled preferentially. • Meteorological influence was responsible for 44.0 ± 19.1% of the O 3 variation. [ABSTRACT FROM AUTHOR]

PM 2.5 separator directly affects the accuracy of PM 2.5 sampling. The specification testing and evaluation for PM 2.5 separator is particularly important, especially under China's wide variation of terrain and climate. In this study, first a static test apparatus based on polydisperse aerosol was established and calibrated to evaluate the performance of the PM 2.5 separators. A uniform mixing chamber was developed to make particles mix completely. The aerosol concentration relative standard deviations of three test points at the same horizontal chamber position were less than 0.57%, and the particle size distribution obeyed logarithmic normal distribution with an R 2 of 0.996. The flow rate deviation between the measurement and the set point flow rate agreed to within ± 1.0% in the range of − 40 to 50°C. Secondly, the separation, flow and loading characteristics of three cyclone separators (VSCC-A, SCC-A and SCC112) were evaluated using this system. The results showed that the 50% cutoff sizes (D 50) of the three cyclones were 2.48, 2.47 and 2.44 μm when worked at the manufacturer's recommended flow rates, respectively. The geometric standard deviation (GSD) of the capture efficiency of VSCC-A was 1.23, showed a slightly sharper than SCC-A (GSD = 1.27), while the SCC112 did not meet the relevant indicator (GSD = 1.2 ± 0.1) with a GSD = 1.44. The flow rate and loading test had a great effect on D 50 , while the GSD remained almost the same as before. In addition, the maintenance frequency under different air pollution conditions of the cyclones was summarized according to the loading test. Unlabelled Image [ABSTRACT FROM AUTHOR]

To adaptively forecast forthcoming large aftershocks of the 2008 Mw7.9 Wenchuan, China, earthquake, we construct a new hazard model to describe the occurrence rate of aftershocks in a study region along the Longmenshan fault. The model is denoted by SRJ since it is a combination of the Reasenberg–Jones (RJ) model and a spatial hazard model that is obtained by taking a reference of previous earthquakes in the study region. We employ the maximum likelihood (ML) method to estimate the SRJ model based on aftershocks that occurred within 1 or 2 days after the Wenchuan earthquake. The probabilities of M ≥ 5.0 aftershocks at each of the grids in the study region during next few days are then computed according to the estimated SRJ model, and hence the corresponding relative aftershock hazard (RAH) map is constructed. Finally, according to a variety of criteria for evaluating the hazard maps on depicting possible rupture area of forthcoming large aftershocks, the SRJ-based RAH map is demonstrated to be more efficient than the RAH maps constructed based on the RJ model incorporated with the gridding method using a fixed radius or varying radii. [ABSTRACT FROM AUTHOR]

Controlled laboratory combustion experiments were conducted in the fire test room to mimic freshly emitted smoldering smoke of biomass burning in China. The biomass components were determined by ultimate analysis and proximate analysis before experiments. The particle number size distribution (PNSD) between 5 and 1000 nm of smoke was measured by a high sampling frequency size spectrometer. A cavity-enhanced aerosol albedometer with wavelength of 532 nm was used to measure scattering coefficients, extinction coefficients, and single scattering albedo (SSA) of smoldering smoke. The PNSDs of smoldering smoke from the burning of agricultural straw could be fitted with a bimodal lognormal distribution as modes around 10 nm (nucleation mode) and 60 nm (Aitken mode). The PNSDs of wood sawdust could be fitted with a trimodal lognormal distribution, while the two modes were in nucleation mode, and one was in Aitken mode. The bulk optical properties (scattering and extinction coefficients) of smoldering smoke had strong correlations with particle number concentrations of sizes bigger than 100 nm. The correlation between SSA and fixed carbon (FC) was strong (the correlation coefficient is 0.89), while the correlation between SSA and volatile matter (VM) or ash was weak. The relationship between SSA and N (or S) showed a positive correlation, while that of SSA and C showed a negative correlation. The relationship between SSA and VM/FC (or N) showed a strong linear relationship (r2 > 0.8). This paper could improve understanding of the relationship between the optical and particle size distribution properties of smoke from biomass burning and the components of biomass materials under similar combustion conditions. [ABSTRACT FROM AUTHOR]

It is critical to assess drought risk probability based on a really spatio-temporal continuum identification and characterization method, which is of great importance for drought resistance, planning, and management of water resource as well as agricultural production. Therefore, the major motivation of this study is to identify and characterize hydrological drought events in a three-dimensional framework and further assess the potential drought risk probability in a multivariate framework in the Luanhe River basin during 1961–2011. The study adopts a really spatio-temporal continuum identification method to characterize drought, and copula functions for multivariate risk probability assessment of hydrological drought. First, the Soil and Water Assessment Tool (SWAT) model is used to simulate the watershed runoff and the cubic spline interpolation method is used to obtain the gridded data sets. Second, the Standardized Runoff Index (SRI) and the three-dimensional identification method are employed to identify hydrological drought. Third, according to three drought parameters of drought severity (S), duration (D), and affect area (A), the marginal distribution, bivariate, and trivariate joint distribution are constructed, and the optimal ones are selected based on different evaluation methods of goodness-of-fit. Fourth, based on the derived marginal and joint distributions, drought risk probability is fully assessed. Results indicate that: (1) SWAT model is a reliable tool to simulate the watershed hydrologic processes; (2) the three-dimensional identification method used in this study is robust and efficient; (3) the optimal marginal distributions for S, D, and A are GEV, GEV, and lognormal distribution; the optimal bivariate copula function for S-D, S-A, and D-A are Joe, Gumbel, and Joe copula; and the optimal trivariate copula function for S-D-A is Nested Gumbel copula; (4) return periods of the first five most serious drought events are 80, 75, 46, 45, and 40 years, respectively; (5) to completely characterize the spatio-temporal variability of hydrological drought, it is necessary to completely consider the three characteristic variables of S, D, and A. [ABSTRACT FROM AUTHOR]

Recent studies show that the API p - y method may underestimate the pile-soil initial stiffness of offshore wind turbine (OWT) monopiles in clay while overestimate that in sand. To facilitate the reliability-based design of OWT monopiles with the API p - y design method, a two-stage evaluation method of the model bias factor for the p - y method (ε py) of monopiles under the serviceability limit state (SLS) was presented. The model bias factor ε py is derived by comparing field test data with high-fidelity 3D finite element model (FEM) results, and the p - y method predictions, addressing the issues of limited field test data for OWT monopiles. Results show that the mean of the model bias factor ε py depends on the characteristics of piles, the soil properties, and the composition of the layered ground. The systematic dependency is expressed by a trend function and the residual model bias factor follows a lognormal distribution with a mean of 1.01 and a COV of 0.14. The significance of the model uncertainty is illustrated using a case study. The results of the field example show that the design in clay sites may be considerably conservative and may be less conservative in sand sites if ignoring the model uncertainty. The result of this work can provide a basis for promoting reliability-based design for OWT monopiles. • A two-stage approach is presented to characterize the model bias factor for the API p-y method of OWT monopiles underSLS. • The proposed approach addresses the issues of limited field test data for OWT monopiles. • The model bias factor is applied to evaluate the reliability index of OWT monopiles under SLS in a real project in China. • Ignoring the model bias factor causes a conservative design in clay sites and a less conservative design in sand sites. • The result of this work can provide a basis for promoting reliability-based design for OWT monopiles. [ABSTRACT FROM AUTHOR]

The permeability of the host rock of the nuclear waste underground repository is one of the most keys for estimating the potential risk for nuclide waste to escape. Therefore, a three-dimensional discrete fracture network (DFN) model using the Monte Carlo method is generated based on the statistical geometrical characteristics of fracture network in Beishan I area which is selected as the site for constructing the nuclear waste repository in China. And the permeability of Beishan I fractured rock masses is calculated through the equivalent pipe network (EPN) method and representative elementary volume (REV) of it is determined. A rotating algorithm is developed to calculate different direction permeability. Furthermore, the influence of fracture statistical geometrical characteristics on REV size is explored by creating a series of DFN models with varying log-normal distribution of side lengths. The results show that the REV size of the Beishan Ⅰ area is 1.66 × 105 m3 and the corresponding principal permeability direction is 111.29°/75.36°. The REV size and permeability both increase with the increment of the mean and variance of the log-normal distribution increases. And with the increase of mean and variance, the growth rate gradually accelerated. [ABSTRACT FROM AUTHOR]

Based on the reliability theory, this paper gave the expression of the "failure-non failure"state of the urban road traffic unit and the traffic network and analyzed the change law of their states; analyzed the time distribution of the link unit and the traffic network from the observed starting point t0 to the "first failure state". Based on these, it deduced the failure probability, average failure time, failure rate and conditional length of failure time of the urban road unit and traffic network, it also gave the method of model calibration. It took a road traffic network that composed of five road units in a core city of China by an example, fitted and checked the first failure time of the road units and the traffic network, also compared the model calculation results with the actual observation results. The results show that it is better to use logarithmic normal distribution to fit the first failure time, and the calculation results of the model are very close to the actual observation results, which shows that the model has good practicability. [ABSTRACT FROM AUTHOR]

Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network. [ABSTRACT FROM AUTHOR]

In this paper, the correlation between fire fighting time and fire loss (burned area of urban building) based on fire statistical data in Jiangxi Province (China) from 2000 to 2010 was studied. The results showed the probability distribution of fire fighting time met lognormal distribution. In the probability density function, the expectation of the distribution represents the average level of fire fighting time. We found the average fighting time of warehouse and workshop fires were higher than the average level of whole building fires. In addition, the probability distribution of the burned area in each fire fighting time interval also followed power function, which was valid in the case of the fire fighting time within 4 hours. Furthermore, the absolute value of the exponent of the function is positively correlated with the small-scale fires and negatively with the large-scale fires. The value decreased with the increase of the fire fighting time, indicating that the fire control ability became poor with longer fire fighting time. Also, the fire control ability in residential waned fastest as the fighting time increased, and the ability in warehouse waned slowest. [ABSTRACT FROM AUTHOR]

An optimized macroseismic intensity index, which integrates the traditional macroseismic intensity scale and the instrument intensity evaluation model, is proposed to evaluate regional buildings' empirical resilience and vulnerability. The traditional failure probability of the group structure is modified and improved. The parameters and probability indexes used to assess the resilience and vulnerability of group structure in urban and rural areas are innovatively proposed. The empirical group structure seismic loss data from the actual field investigation of the Jiuzhaigou earthquake in Sichuan Province, China, on August 8, 2017, were statistically analysed, the vulnerability of the sample data was assessed by using the optimized Chinese seismic intensity scale (OCSIS-20), European Macroseismic Scale (EMS-98) and the Modified Mercalli Intensity (MMI), and the assessment and comparison model of multidimensional modal resilience and probability index was established. To improve the rationality and accuracy of typical building resilience in the macrointensity quantification region, a new quantitative model of resilience and vulnerability based on optimizing the macrointensity index and updating the lognormal distribution is proposed, and the group structure resilience comparison models for typical macrointensity standard evaluation are established. The structural vulnerability database of the Jiuzhaigou earthquake is utilized to verify the rationality of the innovative model. Ultimately, field loss inspection and damage mechanism analysis are conducted based on the characteristics of regional structural seismic resilience and the actual vulnerability of the Jiuzhaigou earthquake. • The rapid resilience and vulnerability prediction and evaluation domain, plane, surface, and matrix based on quantity and failure index parameters are established. • An innovative regional domain vulnerability and resilience assessment model is conducted. • A new quantitative model of resilience and vulnerability based on optimizing the macrointensity index and updating the lognormal distribution is proposed. [ABSTRACT FROM AUTHOR]

The geometric attributes of discontinuities are critical to an accurate discrete fracture network (DFN) model of rock mass. It is difficult to estimate three-dimensional (3D) geometric parameters of multiple groups of discontinuities by observation data. The study proposes a mixture distribution model for the 3D geometric attributes of multiple discontinuity sets. The method of estimating the mixture distributions of 3D geometric attributes of all discontinuity sets from the two-dimensional (2D) trace data in a sampling window is established and modified, including discontinuity diameter distribution estimation, volume density estimation, orientation distribution estimation, and distribution mixing. Discontinuities are assumed to be thin disks uniformly distributed in space, and their roughness and aperture are ignored. Discontinuity diameter and orientation follow lognormal distribution and bivariate normal distribution, respectively. Orientation distributions defined on the definitional domain of the geological coordinate system are derived to represent the real frequency distributions of orientation measurements in 3D rock mass space. The mixture distribution model is verified by using Monte Carlo method to generate DFNs with different volume densities, and distribution parameters of orientation and diameter. The maximum error of volume density is <0.5 m−3. The estimated distributions of diameter and orientation are in good agreement with the true distributions, while there are limited symmetry estimation errors of the discontinuity sets with orientation samples covering both sides of the 0° or 180° polar axis. The model is applied to Sejilashan tunnel, and the result indicates that the surrounding rock of two excavation faces have a high probability to be rated as the V classification according to the engineering classification of rock mass in China, which is in good agreement with the reality according to the geological survey and field observation. • A mixture distribution model for 3D geometric parameters is proposed. • Bayesian law is employed to mix the distributions by density-based weights. • The coupling relation of the orientation distributions is derived. • Mixture distributions represent the real frequency distributions of discontinuities. [ABSTRACT FROM AUTHOR]

The rainfall data of 20 rain gauge stations are used for analysis on the spatiotemporal characteristics of rainstorm-induced hazards in Beijing. A local model used to calculate rainstorm hazards index values (RHIVs) has been developed to reflect the degree of rainstorm-induced hazards. The Mann-Kendall test on the RHIVs series recognizes 1984 as the changepoint in the series, which is shortly after the beginning of a rapid urban expansion period in 1981. The RHIV trend analysis reveals that the trends indices of all stations are negative before 1984 but mostly positive after 1984. Although the climate in north China shows drought conditions, and the annual rainfalls have decreased in recent years, no relationship is implied to a reduction in rainstorm-induced hazards. By using the lognormal distribution model, the probability analysis on the RHIVs of 20 stations indicates that very extreme precipitation occurred in increasing frequency after 1984. Moreover, the estimated spatial distributions of 100-, 150-, and 200-mm daily rainfall exceedance probabilities (EPs) indicate that these EPs have increased mainly in the urban areas and northward, which are the downwind of the summer monsoon, whereas the EPs to the south of the urban areas have decreased since 1984. Such spatiotemporal characteristics of the RHIVs can be attributed to modification of precipitation by the changed land use and land cover in urban areas. Moreover, the urban-induced rainfall downwind of the urban areas enhanced the rain intensity and rain rate, which led to an increase in RHIVs and contributed to the frequent occurrences of flash floods in Beijing metropolis. [ABSTRACT FROM AUTHOR]

Recent empirical studies have suggested that the patch-size distribution of vegetation can be fitted by a power law, truncated power law, or lognormal model to provide explanatory mechanisms for vegetation pattern formation in arid and semiarid regions. However, contradictory results have been reported. Therefore, additional empirical studies are necessary to test the patch-size distribution of vegetation over several regions before it can be considered as an indicator for assessing the discontinuous transition of ecosystems and understanding the mechanisms of vegetation pattern formation. Analogous to arid and semiarid regions of the world, vegetation patterns are characterized by a two-phase mosaic composed of dense vegetation patches interspersed with areas of bare soil, referred to as quasi-circular vegetation patches (QVPs), in the Yellow River Delta (YRD), China. However, research on the patch-size distribution of the QVPs reflecting vegetation patterns and ecosystem functioning is lacking. To fill this gap, for the first time, we examined the patch-size distribution of the QVPs using the fused IKONOS high-spatial-resolution image and evaluated the statistical distributions that better fit the patch size data of the QVPs in the YRD. We found that a power law, truncated power law, or lognormal distribution was not supported in the study area, whereas gamma distribution reasonably fits the size data of QVPs, implying that micro-depressions, combined with the water-limited and salinization environments had considerable effects on vegetation pattern formation. Our results provide helpful insights and suggest that further studies are needed to classify different types of QVPs. Additionally, more efficient approaches need to be used to fit the statistical distributions for elucidating the spatial vegetation patterns in the YRD. • A power-law distribution does not fit the entire size data for QVPs in the YRD, China. • A lognormal distribution does not fit the entire size data for QVPs. • A gamma distribution reasonably fit the entire size data for QVPs. • Micro-depressions and water-salt stress creates the pattern formation of QVPs. • The plant–plant interactions may be the dominant driver for the formation of QVPs. [ABSTRACT FROM AUTHOR]

This paper studies the statistical law of fire attendance time and analyzes the correlation between fire attendance time and burned area based on the urban fire statistical data of Japan from 1995 to 2003 and in Jiangxi Province (China) from 2000 to 2010. The frequency of fire attendance time was better modeled by a lognormal distribution, and the probability density function for both Japan and China were formulated. The expectation of the lognormal distribution reflects the average level of fire attendance time. This study is the first to report that the distribution law of the burned area in each fire attendance time observes power function. And they are valid within 12 min of fire attendance time. The larger absolute value of the exponent of the power law function subjects to the larger probability of small-scale fire and the smaller probability of large-scale fire. It decreases as the fire attendance time increases. This indicates that the fire control ability becomes poor with longer fire attendance time. [ABSTRACT FROM AUTHOR]

• Statistical analysis of hourly wind speed series. • Finding out the optimal distribution to characterize the hourly wind speed series. • Guiding wind farm operation with the hourly expected wind power. Accurate wind speed characterization is important for wind farms to efficiently utilize wind energy which plays a significant role in reducing the dependence on fossil fuels and promoting global carbon peak and carbon neutrality. Since hourly wind speed density exhibit a variety of shapes, their characteristic features change substantially within a day, influenced by meteorological factors, therefore, the hourly wind speed analysis is considered to improve the accuracy of wind speed characterization. In this paper, 4 commonly used wind speed probability distributions (Weibull, Rayleigh, Gamma, Lognormal distribution) are applied for hourly wind speed analysis, and the best fitting distribution of each hourly wind speed series is identified by the goodness-of-fit test. Then the hourly wind power distribution of wind farms is determined by the corresponding optimal hourly wind speed distribution and the relation between wind power and wind speed. Finally, the hourly expected wind power calculated by the hourly wind power distribution is used to guide the hourly operation of the wind farm. The measured wind speed and wind power data of Dashuikeng wind farm in the Ningxia Autonomous Region of China is taken as an example to illustrate the results, 1) the hourly wind speed analysis performs a more accurate characterization of wind speed than annual wind speed series analysis. 2) The range of the average value of hourly wind speed series is 5.7 m/s–6.9 m/s, and the average wind speed, overall, during the daytime is smaller than that during the nighttime. 3) Gamma distribution shows a better performance than the other three distributions in characterizing the hourly wind speed series. 4) Wind energy resources are not fully consumed during the daytime, especially the period of 11:00–18:00. The proposed method improves the characterization of wind speed and guidance of the hourly operation for the wind farm, which has an important significance in raising the efficiency of wind energy utilization. [ABSTRACT FROM AUTHOR]

The present paper gives a method to directly estimate the dynamic failure peak ground acceleration of single-layer reticulated domes according to the Chinese earthquake response spectrum. A method given by the Japanese code for seismic design of buildings is presented first, which can be used to estimate the dynamic failure peak ground acceleration of a single-layer dome. However, the existing method cannot be used to calculate the dynamic failure load for a structure in China because of the different codes and methods used for the seismic design of single-layer reticulated domes. Meanwhile, the existing method needs to repeat the finite element method (FEM) elasto-plastic static analysis and FEM nonlinear time–history response analysis to calculate the FEM plasticity adjustment factor and the dynamic ductility index of different domes. Secondly, on this basis, 28 Kiewitt-8 (K8) single-layer reticulated domes with different key structural design parameters are designed using the relevant Chinese specifications, they will be used for the parameter revision of the peak ground acceleration and the dome's design spectral acceleration, the fitting of the formula to calculate the FEM plasticity adjustment factor, and the statistical analysis of the dynamic ductility index respectively. Thirdly, the peak ground acceleration and the dome's design spectral acceleration in the existing method are revised according to the Chinese code for the seismic design of buildings. Fourthly, the FEM elasto-plastic static analysis is carried out to get a fitting formula to directly calculate the FEM plasticity adjustment factor with the static safety factor K of the dome. The calculation results of this formula are smaller than that of FEM analysis, which can ensure the safety of the dome. Fifthly, the failure criteria with clear physical meaning are selected from the existing dynamic failure criteria to predict the dynamic failure load of the domes. Then, a FEM nonlinear time–history response analysis is carried out using the FE package ANSYS for the 28 typical domes subjected to 30 different ground motions, and the dynamic failure loads are calculated by the selected failure criteria. It is found that the dynamic failure loads correspond to two different failure modes, one is the local failure caused by the sudden increase of the displacement of the dome's local node, the other is the global failure caused by the sudden increase of the overall energy of the single-layer reticulated dome. After this, the lower bound failure accelerations with a certain guaranteed rate of those dynamic failure loads are determined using a lognormal distribution. The dynamic ductility index is then revised by the lower bound failure accelerations and the statistical analysis of the dynamic ductility index of the 28 typical domes is conducted to get a lower bound value for it. Finally, a method directly estimating the dynamic failure load of a dome is constructed and verified. The research will provide a new method under a certain degree of reliability to directly estimate the dynamic failure loads of single-layer reticulated shells in the earthquake area of China and contribute to the structural design with more overall confidence. • We proposed a method to directly calculate the dynamic failure peak ground acceleration of single layer reticulated domes. • The dynamic failure peak ground acceleration calculated by the method is a statistical value with a certain guarantee rate. • The dynamic failure peak ground acceleration calculated by this direct method corresponds to two different failure modes. [ABSTRACT FROM AUTHOR]

Highlights: [•] High concentrations of Cd in soils of a rural area in the Three Gorges region, China, are reported. [•] Lognormal distribution plots and enrichment factors were applied to identify Cd sources. [•] Sedimentary rocks are main source of Cd in the Cd-enriched soils. [•] Results of sequential extractions show that a considerable fraction of the Cd in soils is in a labile form. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard (AQS) and the reduction of particulate matter emission to meet the AQS from the statistical properties (probability density functions) of air pollutant concentration. Methods: The daily PM10 average concentration in Beijing, Shanghai, Guangzhou, Wuhan, and Xi'an was measured from 1 January 2004 to 31 December 2008. The PM10 concentration distribution was simulated by using the lognormal, Weibull and Gamma distributions and the best statistical distribution of PM10 concentration in the 5 cities was detected using to the maximum likelihood method. Results: The daily PM10 average concentration in the 5 cities was fitted using the lognormal distribution. The exceeding duration was predicted, and the estimated PM10 emission source reductions in the 5 cities need to be 56.58%, 93.40%, 80.17%, 82.40%, and 79.80%, respectively to meet the AQS. Conclusion: Air pollutant concentration can be predicted by using the PM10 concentration distribution, which can be further applied in air quality management and related policy making. [Copyright &y& Elsevier]

Abstract: Collections of building energy consumption data are often uncertain due to unavoidable measurement errors, random errors, non-representativeness of sample data, etc. On the basis of the quantitative uncertainty and Monte Carlo uncertainty propagation methods, the uncertainty of building energy consumption data is quantified. A real case study is conducted on the electricity and gas consumptions of buildings in Ma’anshan city in China in 2009. The results show that the electricity consumption distributions of four kinds of buildings fit Weibull distribution, gamma distribution, normal distribution and lognormal distribution respectively. The total energy consumption of buildings in the city at the cumulative probability of 97.5% is 16.6% higher than that obtained using the conventional method. The uncertainty of random sampling error in total energy consumption is about 14%. The sensitivity analysis results can provide information about the main sources that can help in reducing the uncertainty of the overall energy consumption inventory. This kind of quantification of uncertainty in energy consumption inventories could assist the decision-makers in determining the likelihood of complying with energy reduction objectives, and framing more scientific energy-saving strategies that may reduce building energy consumption. [Copyright &y& Elsevier]

A detailed study on particulate matter from vehicle emission was carried out at roadsides in Hong Kong downtown area. The study aims to explore the variations of particulate matter at roadsides in morning and afternoon. Data of concentrations of different size groups of particulate matter were collected and analyzed. It was found that the particulate levels generally vary periodically with traffic signal changes. During the green traffic light period, concentrations of the particulate matter increase to peak point and then diffuse to a relatively stable level in the red traffic light period. Such stable level is regarded as background level, to which pedestrians are exposed when they walk-by and cross the zebra zones. To analyze and further explore the collected data, a statistical distribution model, i.e., goodness-of-fit test, was employed. It was noticed that the lognormal distribution best fits the particulate matter data in both morning and afternoon. In addition, the non-parametric test was also used to assess the differences between morning and afternoon data. The results show that both data sets statistically differ from each other at 5% significance level. It can be deduced that the change of traffic volume, humidity and wind speed between morning and afternoon may cause this difference. [ABSTRACT FROM AUTHOR]

Abstract: In agroecosystems, spiders are important predators that play a role in the control of agricultural pests. Modifying the vegetation around crops is an effective measure that can increase plant diversity and enhance the abundance and diversity of spider species. In this study, spiders were sampled monthly from May 2006 through April 2008 from tea canopies and ground covers in four tea plantation treatments in Xingchun (27°38′51.4″ N and 117°54′29.9″ E), which is in the Wuyi Mountains, Fujian Province, Southeastern China. The first tea plantation was intercropped with Paspalum notatum, the second with Cassia rotundifolia, and the third with natural ground cover. All ground cover was removed by hand in the fourth tea plantation. The spiders collected in the tea canopies numbered 21,170 individuals, representing 21 families and 158 species, whereas a total of 978 individual spiders, representing 16 families and 74 species, were collected in the ground cover treatments. Subsequent analysis revealed that Coleosoma octomacutatum (Boesenberg et Strand, 1906), Telamonia bifurcilinea Bosenberg et Strand, 1999, and Erigone sp. 1 were the dominant spider species in these tea plantations. There were no significant differences among cover crop treatments with respect to the species richness, species abundance, or absolute abundance of spiders in either study year. In this work, all fourteen communities sampled had similar types of species abundance distributions, which followed bell-shaped and left-truncated lognormal distributions, with an almost identical modal octave on a log2 scale and a missing zero class. The results of the present study do not support the natural enemy hypothesis, but rather indicate that ground covers do not have adverse effects on the tea plantations. [Copyright &y& Elsevier]

It was not unusual in soil and environmental studies that the distribution of data is severely skewed with several high peak values, which causes the difficulty for Kriging with data transformation to make a satisfied prediction. This paper tested an approach that integrates kriging and triangular irregular network interpolation to make predictions. A data set consisting of total Copper (Cu) concentrations of 147 soil samples, with a skewness of 4.64 and several high peak values, from a copper smelting contaminated site in Zhejiang Province, China. The original data were partitioned into two parts. One represented the holistic spatial variability, followed by lognormal distribution, and then was interpolated by lognormal ordinary kriging. The other assumed to show the local variability of the area that near to high peak values, and triangular irregular network interpolation was applied. These two predictions were integrated into one map. This map was assessed by comparing with rank-order ordinary kriging and normal score ordinary kriging using another data set consisting of 54 soil samples of Cu in the same region. According to the mean error and root mean square error, the approach integrating lognormal ordinary kriging and triangular irregular network interpolation could make improved predictions over rank-order ordinary kriging and normal score ordinary kriging for the severely skewed data with several high peak values. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a 91-year data set at the Wusong Station near Shanghai City in Yangtze Estuary has been used to estimate the 100-year Annual Maximum Water Level (AMWL). The performances of four common distribution models have been evaluated. The GEV model provides the best estimates of an AMWL. It results in the minimum difference (0.04m) compared to the observed 92-year AMWL, with the high correlation coefficient (0.99) and minimum root-mean-square-error (0.045m) value. Predictions from other distribution models cause non-negligible deviations, underestimating the 92-year AMWL by 0.57, 0.38, and 0.15m for Weibell, Lognormal, and Gumbel distribution models, respectively. In order to examine the effects of a shorter data set, a 59-year data set was investigated. Model predictions using 59-year data set underestimates the observed 60-year AMWLs. By comparing to the 100-year AMWL estimated by the GEV distribution, using the 91-year data set, results using the shorter 59-year data set lead to underestimates of the 100-year AMWL by 0.78m for Weibull, 0.58m for Lognormal, 0.38m for Gumbel, and 0.39m for GEV distributions. Therefore, one should be cautious when estimating the 100-year AMWL if the data set covers a period much shorter than 100 years. Selecting an appropriate distribution model can improve prediction accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Dechlorane Plus (DP) has been used as a highly chlorinated flame retardant substituting those that are now internationally regulated under the Stockholm Convention. Nevertheless DP’s environmental behavior has seldom been studied in China. There is only one DP manufacturer producing DP since 2005, which is located in Huai’an, Jiangsu Province. The DP levels in 21 soil samples that were taken from Huai’an in October 2009 and determined by gas chromatography/electron-capture negative ion–mass spectrometry (GC/ECNI–MS) method ranged from 0.83 to 1.2×103 ngg−1, following a lognormal distribution. The geometric mean was 5.1ngg−1 dry weight (dw) and the geometric standard deviation was 4.6. Sampled soils had f anti[C anti -DP/(C syn -DP +C anti -DP)] values of 0.67–0.85, with the average value of 0.79, which are close to the values in DP commercial products. This suggests that the main DP pollution source is the commercial DP product. The contour map of DP levels in soil indicated that the factory was the point pollution source with the highest DP level in its surrounding area, especially the southern area. A Monte Carlo based inventory estimation was conducted. The DP inventory in Huai’an is estimated to be 4–31tons. To our knowledge, this study is the first that reports soil pollution by DP. [Copyright &y& Elsevier]

A one-year (from June 2003 to May 2004) study of airborne microbial concentration and size distribution was conducted systematically at three selected sampling sites in Beijing. Microbial samples were collected in triplicate for 3 min, 3 times per day, for 3 consecutive days of each month using FA-I sampler (imitated Andersen sampler, made by Applied Technical Institute of Liaoyang, China). Results showed that the concentration of total culturable microorganisms ranged from 4.8 × 102 colony forming units (CFU)/m3 to 2.4 × 104 CFU/m3, with an arithmetic mean of 3.7 × 103± 2.1 × 102 (standard deviation) CFU/m3. As a whole, the percentage of airborne bacteria, accounting for 59.0% of the total culturable microorganisms, was significantly higher than those of airborne fungi (35.2%) and actinomycetes (5.8%). At RCEES (Research Center for Eco-Environmental Sciences—a culture and education area) and XZM (Xizhimen—a main traffic line), significantly higher percentages of airborne bacteria were found as compared to airborne fungi. No significant difference was observed between airborne bacteria and fungi at BBG (Beijing Botanical Garden—a green garden area). The total microbial concentration was significantly higher at RCEES than at XZM and BBG (*P < 0.05), and no significant difference between XZM and BBG was observed (P > 0.05). Total microbial concentrations were higher in summer and autumn, and lower in spring and winter at RCEES and XZM (*P < 0.05). At BBG, higher concentration was observed in summer during the sampling periods (***P < 0.001). The size distribution of airborne bacteria showed a skewed distribution at three sampling sites. The proportion of bacterial particles decreased gradually from Stage 1 (>7.0 μm) to Stage 6 (0.65 ∼ 1.1 μm), and there was an obvious downtrend on Stage 2 (4.7 ∼ 7.0 μm). Bacterial particles were mainly distributed at the first four Stages (>2.1 μm), accounting for 78.6% at RCEES, 84.0% at XZM, and 81.5% at BBG. The size distribution pattern of airborne fungi was found with normal logarithmic distribution at three sampling sites. Fungal particles were mainly distributed at Stage 3 (3.0 ∼ 6.0 μ m), Stage 4 (2.0 ∼ 3.5 μ m) and Stage 5 (1.0 ∼ 2.0 μ m), composing 71.6% of the population at RCEES, 74.2% at XZM, and 68.3% at BBG. However, different distribution patterns were found in different dominant fungal genera. Cladosporium, Penicillium, and Aspergillus were present with normal logarithmic distribution, while Alternaria and sterile mycelia were found with skewed distribution. In opposition to the distribution pattern of fungal particles, the actinomycete particles at all sampling sites were primarily collected on Stage 1, Stage 5, and Stage 6, accounting for 61.1% at RCEES, 60.7% at XZM, and 64.8% at BBG. [ABSTRACT FROM AUTHOR]

The theoretical prediction on targeted exchange rates expects mean reversion of the exchange rates. There is some empirical evidence to support this prediction. This paper presents a model for valuing European foreign exchange options in which the forward foreign exchange rate follows a mean-reverting lognormal process. The corresponding closed-form solutions for the option valuation are derived. The mean-reverting process has material impact on the foreign exchange rate option values and their hedge parameters. This tends to decrease the value of a simple put or call. On the other hand, the process also keeps the exchange rate in a small range around the mean level. As this is the region in which an option's intrinsic value is high because of the level of its strike price, there is also a tendency for option values to be enhanced compared with the values of the Black–Scholes model. The numerical results using the forward exchange rates of the Hong Kong dollar and market data of their options show that both of these effects are important for the realistic choices of parameter values. As the dynamics of targeted exchange rates may not follow the standard lognormal process as described by the Black–Scholes model, the mean-reverting option-pricing model may be considered for the valuation of options and estimation of associated hedge parameters on targeted exchange rates. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An assessment is presented of distribution characteristics of heavy metals in the urban topsoil from the city of Xuzhou. The concentrations of Ag, Al, As, Au, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Ga, Hg, Li, Mn, Mo, Ni, Pb, Pd, Pt, Sb, Sc, Se, Sn, V and Zn have been determined from 21 soil samples. Examination of lognormal distribution plots indicates that the diagrams of Al, Be, Fe, Ga, Li, and V are almost linear suggesting that these metals are almost unaffected by anthropogenic activities while the plots for As, Cd, Cu, Pb, Pd, Pt, Se, Zn and others are not linear probably due to anthropogenic activities from which these metals are delivered to the soils. Al is used for mineralogical normalization of these data. An evaluation of background values for topsoil is also carried out by means of lognormal distribution plots. The results show our background values obtained from the lognormal distribution plots are comparable to those values of uncontaminated soils of Xuzhou obtained by previous work except for Cd and Hg. At present, no explanation for the exceptions Cd and Hg can be given. [ABSTRACT FROM AUTHOR]

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy. [ABSTRACT FROM AUTHOR]