[Multi-scale Driving Mechanism of Urbanization on PM2.5 Concentration in Urban Agglomeration in the Middle Reaches of the Yangtze River]

Exploring the nonlinear effect of urbanization on PM2.5 concentration and its driving mechanism is crucial for controlling urban air pollution. Based on remote sensing data and statistical data from 2002 to 2020, spatial autocorrelation, systematic dynamic panel regression, and spatio-temporal geographical weighted regression models were used to analyze the spatio-temporal evolution of PM2.5 concentration in the urban agglomeration of the middle reaches of the Yangtze River and explore the driving mechanism of urbanization on PM2.5 concentration at different spatial scales. The results showed that:① PM2.5 concentration in the middle reaches of the Yangtze River showed an overall decreasing trend from 2002 to 2020, with a spatial distribution pattern of "high in the north and low in the south." ② Hot spot cities expanded towards the western part of the urban agglomeration, whereas cold spot cities showed enhanced spatial correlation. ③ The relationship between PM2.5 concentration and economic, land, and population urbanization followed N-shaped, U-shaped, and U-shaped curves, respectively. Secondary industry and energy consumption significantly promoted the change in PM2.5 concentration, and precipitation and vegetation helped mitigate PM2.5 pollution. ④ The overall driving effects of all urbanization factors in local areas were transformed, and the main areas of influence were concentrated in the southeast, northwest, and southwest of the study area. Considering the current urban development status and regional characteristics of the urban agglomeration in the middle reaches of the Yangtze River, promoting green industrial transformation, rational planning of urban spatial distribution and population distribution, and enhancing infrastructure construction will facilitate the coordinated development between urbanization and environmental protection.

[Spatial-temporal variations of vegetation coverage and its driving force in Inner Mongolia grassland, China]

Inner Mongolia grassland is rich in natural vegetation and mineral resources. Based on Landsat5/7/8 NDVI data, we used pixel binary model to invert vegetation coverage of Inner Mongolia grassland area, investigated the stability, spatial distribution, and future evolution trend of vegetation coverage by using Sen+MK and Hurst index, and analyzed the driving factors of the spatial differentiation of vegetation coverage by the optimal parameters-based geographical detector. The results showed that vegetation coverage of Inner Mongolia grassland showed an increasing trend from 2006 to 2020, and the overall spatial pattern was high in the east and low in the west, mainly with great fluctuation. The regions with slight or obvious improvement characteristics (64.8%) were much more than those with slight or severe degradation characteristics (23.2%). Compared with that in the past 15 years, the proportion of degraded vegetation in the future is expected to increase to 36.6%. The central part of Xilin Gol League and Wulanqab in the central grassland area, the western part of Hulunbuir and Erdos in the eastern grassland area, and Wuhai in the western grassland area were at the risk of degradation, which should be paid more attention. Precipitation was the dominant factor of spatial differentiation in Inner Mongolia grassland, while soil type, land use, and air temperature had the most significant synergistic effect.

Spatio-temporal evolution of human neural activity during visually cued hand movements

Making hand movements in response to visual cues is common in daily life. It has been well known that this process activates multiple areas in the brain, but how these neural activations progress across space and time remains largely unknown. Taking advantage of intracranial electroencephalographic (iEEG) recordings using depth and subdural electrodes from 36 human subjects using the same task, we applied single-trial and cross-trial analyses to high-frequency iEEG activity. The results show that the neural activation was widely distributed across the human brain both within and on the surface of the brain, and focused specifically on certain areas in the parietal, frontal, and occipital lobes, where parietal lobes present significant left lateralization on the activation. We also demonstrate temporal differences across these brain regions. Finally, we evaluated the degree to which the timing of activity within these regions was related to sensory or motor function. The findings of this study promote the understanding of task-related neural processing of the human brain, and may provide important insights for translational applications.

Characterizing the Spatio-Temporal Variations of Urban Growth with Multifractal Spectra

Urban morphology exhibits fractal characteristics, which can be described by multifractal scaling. Multifractal parameters under positive moment orders primarily capture information about central areas characterized by relatively stable growth, while those under negative moment orders mainly reflect information about marginal areas that experience more active growth. However, effectively utilizing multifractal spectra to uncover the spatio-temporal variations of urban growth remains a challenge. To addresses this issue, this paper proposes a multifractal measurement by combining theoretical principles and empirical analysis. To capture the difference between growth stability in central areas and growth activity in marginal areas, an index based on generalized correlation dimension Dq is defined. This index takes the growth rate of Dq at extreme negative moment order as the numerator and that at extreme positive moment order as the denominator. During the stable stage of urban growth, the index demonstrates a consistent pattern over time, while during the active stage, the index may exhibit abnormal fluctuations or even jumps. This indicates that the index can reveal spatio-temporal information about urban evolution that cannot be directly observed through multifractal spectra alone. By integrating this index with multifractal spectra, we can more comprehensively characterize the evolutionary characteristics of urban spatial structure.

Spatio-Temporal Coupling Evolution of Urbanisation and Carbon Emission in the Yangtze River Economic Belt

The distribution characteristics of urbanisation level and per capita carbon emissions from 2006 to 2019 were investigated by the ranking scale rule, using 108 cities in the Yangtze River Economic Belt of China. A coupling coordination model was established to analyse the relative development relationship between the two, and exploratory spatial-temporal data analysis (ESTDA) was applied to reveal the spatial interaction characteristics and temporal evolution pattern of the coupling coordination degree. The results demonstrate that: (1) The urbanisation level and per capita carbon emissions of the Yangtze River Economic Belt show a stable spatial structure of 'high in the east and low in the west'. (2) The coupling and coordination degree of urbanisation level and carbon emissions show a trend of 'decreasing and then increasing', with a spatial distribution of 'high in the east and low in the west'. (3) The spatial structure exhibits strong stability, dependence, and integration. The stability is enhanced from west to east, the coupling coordination degree has strong transfer inertia, and the spatial pattern's path dependence and locking characteristics show a trend of weak fluctuation. Therefore, the coupling and coordination analysis is required for the coordinated development of urbanisation and carbon emission reduction.

The Spatio-Temporal Evolution of Food Production and Self-Sufficiency in China from 1978 to 2020: From the Perspective of Calories

Ensuring national food security is an eternal topic. We unified six categories of food with calorie content including grain, oil, sugar, fruits and vegetables, animal husbandry, and aquatic products on the basis of provincial-level data, and we dynamically evaluated caloric production capacity and the supply-demand equilibrium under the increase in feed-grain consumption as well as the food losses and waste in China from 1978 to 2020 at four different levels. The results show that: (1) From the perspective of food production, the total national calorie production showed a linear growth trend, with a growth rate of 31.7 × 10¹² kcal/year, of which the proportion of grain crops has always exceeded 60%. Most provinces showed significant increasing trends in food calorific production, except for Beijing, Shanghai, and Zhejiang, which showed slightly decreasing trends. The distribution pattern of food calories and their growth rate were high in the east and low in the west. (2) From the perspective of the food supply-demand equilibrium, the national food calorie supply has been in surplus since 1992, but significant spatial heterogeneity is detected, with the Main Marketing Region changing from a tight balance to a short surplus, North China always remaining in calorie shortage, and 15 provinces still presenting supply and demand gaps up to 2020, necessitating the establishment of a more efficient and faster flow and trade system. (3) The national food caloric center has shifted 204.67 km to the northeast, and the population center has shifted to the southwest. The reverse migration of the centers of food supply and demand will further aggravate the pressure on water and soil resources and cause higher requirements for ensuring the circulation and trade system of food supply. The results are of great significance for the timely adjustment of agricultural development policies, making rational use of natural advantages and ensuring China's food security and sustainable agricultural development.

Spatio-Temporal Evolution and Influencing Factors of Ecological Well-Being Performance from the Perspective of Strong Sustainability: A Case Study of the Three Gorges Reservoir Area, China

The concept of strong sustainability suggests that natural capital is irreplaceable and emphasizes that human natural consumption cannot exceed the carrying capacity of the ecological environment. In the realistic context of tightening resource constraints and ecological degradation, how to explore the optimal economic and well-being output under certain ecological constraints has become an important topic in sustainability research. Ecological well-being performance (EWP) can comprehensively reflect the efficiency of natural resources and ecological inputs into the well-being level and has become an important tool for sustainable development research. Based on strong sustainability, this paper constructs an EWP evaluation index system. It decomposes EWP into two stages: ecological economy and economic well-being, which opens the "black box" of the ecological well-being conversion process. PCA-DEA, the network super-efficiency Epsilon-based measure (Network SEBM) model, and Geodetector are used to dynamically measure the EWP in the Three Gorges Reservoir Area (TGRA) from 2010 to 2020 and analyze its spatial and temporal characteristics and influencing factors. The results show that (1) temporally, the EWP in the TGRA shows an increasing trend from 2010 to 2020, but the overall level is low. Spatially, it shows a high pattern in the east and low in the west, and spatial differences are gradually decreasing; (2) ecological economic efficiency is significantly lower than economic well-being efficiency, and ecological economic efficiency is the main reason limiting the improvement in EWP in the TGRA. The ecological well-being situation of the TGRA is not optimistic; (3) there is an overall problem of excessive ecological input and insufficient per-capita GDP and well-being output in the TGRA, and decisions should be made according to local conditions; (4) the level of economic development has an EWP level that plays a dominant role and also has a greater relationship with the policy system, socioeconomic conditions, and natural environment.

Evaluation and Impact Mechanism of High-Quality Development in China's Coastal Provinces

With economic expansion having moderated to a "new normal" pace, the eastern coastal provinces have been given a new historical task of high-quality development and become a window and frontier of China's high-quality development. By designing and optimizing an index system of high-quality development levels and using the entropy-TOPSIS method, the study selected 21 indicators, include economic vitality, residents' living standards, innovation efficiency and green development, and took China's eastern coastal provinces as an example to study the characteristics of spatial-temporal variations in the high-quality development level from 2010 to 2020. Then, the study used the obstacle degree model to explore the factors that are obstacles to high-quality development. The results show that the high-quality development of the eastern coastal provinces presents an "up-down-up" fluctuation, with an increase of 40.1%. In particular, the development level of the residents' living standards dimension is higher, and the high-quality development level of each province shows different degrees of growth and gradually tends to balanced development, with the high-quality development of Shanghai, Jiangsu Province and Zhejiang Province in a dominant position. The spatial pattern of high-quality development in the study areas shows a spatial distribution pattern of "high in the east and low in the west, high in the north and low in the south", in which the bipolar spatial effect of the innovation efficiency dimension is becoming more and more prominent, while the regional synergistic development effect of the residents' living standard dimension is more obvious, and the high-quality development spatial pattern shows a "core-periphery" structure, and there is a path-dependent effect in time change, and agglomeration is produced by trickle-down effect in space. The obstacles to residents' living standards are high, and the main obstacle factor has gradually changed from insufficient output in innovation to a reduction in the scale of foreign trade. In addition, the problems of unreasonable industrial structure and shortage of per capita public cultural resources still exist. In provinces with a high-quality development level and a relatively developed economy, the biggest obstacle factors are economic vitality and residents' living standards. In provinces with a low level of high-quality development and a relatively backward economy, the biggest obstacle factors are green development and innovation efficiency, and there are both similarities and differences in the main obstacle factors among provinces.

Examining Poverty Reduction of Poverty-Stricken Farmer Households under Different Development Goals: A Multiobjective Spatio-Temporal Evolution Analysis Method

Accurately identifying the degree of poverty and poverty-causing factors of poverty-stricken farmer households is the first key step to alleviating absolute and relative poverty. This paper introduces a multiobjective spatio-temporal evolution analysis method to examine poverty reduction of poverty-stricken farmer households under different development goals. A G-TOPSIS model was constructed to evaluate poverty-stricken households under short-, medium-, and long-term development goals. Then, GIS analysis methods were employed to reveal the spatio-temporal distribution of poverty-stricken households, and poverty causing factors were detected using the obstacle degree model. Taking Fugong County in Yunnan Province, China, as an example, the empirical results show that: (1) Great progress has been made in poverty reduction during the study period; however, some farmer households which have escaped absolute poverty are still in relative poverty and are still highly vulnerable. (2) Farmers with higher achievement rates under three different development goals are mainly distributed in the central and northern regions of study area, with a pattern of high-high agglomeration under the medium and low development goals, while low-low agglomeration mostly appears in central-southern regions. (3) Under the short-term development goals, the main poverty-causing factors are per capita net income, safe housing, sanitary toilets, years of education of labor force and family health. Under the medium- and long-term goals, per capita net income, labor force education and safe housing are the development limitations. (4) Infrastructure and public service are crucial to ending absolute poverty, and the endogenous force of regional development should be applied to alleviate the relative poverty through sustainable development industries and high-quality national education.

High-resolution mapping of the global silicate weathering carbon sink and its long-term changes

Climatic and non-climatic factors affect the chemical weathering of silicate rocks, which in turn affects the CO₂ concentration in the atmosphere on a long-term scale. However, the coupling effects of these factors prevent us from clearly understanding of the global weathering carbon sink of silicate rocks. Here, using the improved first-order model with correlated factors and non-parametric methods, we produced spatiotemporal data sets (0.25° × 0.25°) of the global silicate weathering carbon-sink flux (SCSF_α ) under different scenarios (SSPs) in present (1950-2014) and future (2015-2100) periods based on the Global River Chemistry Database and CMIP6 data sets. Then, we analyzed and identified the key regions in space where climatic and non-climatic factors affect the SCSF_α . We found that the total SCSF_α was 155.80 ± 90 Tg C yr^-1 in present period, which was expected to increase by 18.90 ± 11 Tg C yr^-1 (12.13%) by the end of this century. Although the SCSF_α in more than half of the world was showing an upward trend, about 43% of the regions were still showing a clear downward trend, especially under the SSP2-4.5 scenario. Among the main factors related to this, the relative contribution rate of runoff to the global SCSF_α was close to 1/3 (32.11%), and the main control regions of runoff and precipitation factors in space accounted for about 49% of the area. There was a significant negative partial correlation between leaf area index and silicate weathering carbon sink flux due to the difference between the vegetation types. We have emphasized quantitative analysis the sensitivity of SCSF_α to critical factors on a spatial grid scale, which is valuable for understanding the role of silicate chemical weathering in the global carbon cycle.

Spatio-temporal Evolution and Driving Factors of the High-quality Development of Provincial Tourism in China

Accelerating the promotion of high-quality development of tourism (HQDT) is of great significance to the sustainable development of tourism. This paper defined the concept of HQDT, and then built an evaluation system for HQDT measurement to analyze the spatio-temporal evolution characteristics of China's HQDT based on provincial panel data from 2010 to 2019, using Geodetector to explore the similarities and differences between driving factors of HQDT and tourism development scale (TDS). The results show that: 1) Taking the development concepts of innovation, coordination, green, openness and sharing as the guidance, and considering the organic unity of quantity and quality, the evaluation index system of the HQDT consists of six dimensions of economic stability, innovation driving, coordination and linkage, green and sustainability, openness and cooperation, and sharing and harmony, which respectively represent the basis, momentum, means, orientation, direction and purpose of the HQDT; 2) The level of China's HQDT shows an upward trend, presenting the characteristics of eastern region > central region > western region > northeastern region in 2019. The regional differences in China's HQDT show a downward trend, and the intra-regional differences have replaced the inter-regional differences as the main source of regional differences; 3) China's HQDT shows the characteristics of higher in the east and lower in the west along the Hu line, while the improvement speed of HQDT shows the characteristics of faster in the west and slower in the east, making the decline of east-west differentiation of China's HQDT and the movement of the gravity center towards southwest; 4) Both HQDT and TDS are obviously driven by tourism capital investment and regional consumption. In terms of differences, the HQDT is more driven by government guidance, innovation driving force, and opening up, while the main driving factors of TDS are more biased toward capital elements and hardware facilities, including informatization, tourism resource, traffic, and eco-environment.

Spatio-Temporal Characteristics of SO2 across Weifang from 2008 to 2020

China has achieved good results in SO₂ pollution control, but SO₂ pollution still exists in some areas. Analyzing the spatio-temporal distribution of SO₂ is critical for regional SO₂ pollution prevention and control. Compared with existing air pollution studies that paid more attention to PM₂.₅, NO₂ and O₃, and focused on the macro scale, this study took the small-scale Weifang city as the research area, analyzed the temporal and spatial changes in SO₂, discussed the migration trajectory of SO₂ pollution and explored the impact of wind on SO₂ pollution. The results show that the average annual concentration of SO₂ in Weifang has exhibited a downward trend in the past 13 years, showing the basic characteristics of “highest in winter, lowest in summer and slightly higher in spring and autumn”, “highest on Sunday, lowest on Thursday and gradually decreasing from Monday to Thursday” and “highest at 9 a.m., lowest at 4 p.m. and gradually increasing from midnight to 9 a.m.”. SO₂ concentration showed obvious spatial heterogeneity: higher in the north and lower in the south. In addition, Shouguang, Changyi and Gaomi were seriously polluted. The SO₂ pollution shifted from south to northeast. The clean wind direction (southeast wind and northeast wind) of Weifang city accounted for about 41%, and the pollution wind direction (northwest wind and west wind) accounted for about 7%. Drawing from the multi-scale analysis, vegetation, precipitation, temperature, transport situation and human activity were the most relevant factors. Limited to data collection, more quantitative research is needed to gain insight into the influence mechanism in the future.

[Spatio-Temporal Characteristics and Potential Source Areas of Seasonal Atmospheric Pollution in Shijiazhuang]

In order to systematically study the transmission characteristics of seasonal and typical pollutants in Shijiazhuang, hourly data of ground-level pollutants(PM_2.5, PM₁₀, O₃, NO₂, SO₂, and CO) from 46 state-and provincial-controlled stations, and meteorological(temperature, humidity, and wind speed) data from 17 counties in Shijiazhuang City from December 2018 to November 2019 was analyzed. The interpolation(IDW) and correlation analysis were applied to seasonal and temporal spatial patterns of pollutant concentration. The backward trajectories analysis was performed to explore the seasonal transmission pattern and potential source areas of pollution in Shijiazhuang by combining with the global data assimilation system(GDAS). The results indicate that the different seasons have characteristic pollutants, as follows:spring(PM₁₀, 48.91%), summer(O₃, 81.97%), autumn(PM₁₀ and PM_2.5, 47.54% and 32.79%), and winter(PM_2.5, 74.44%), which are related to the variation of meteorological conditions. Furthermore, the PM₁₀(spring) concentration correlated negatively with the wind speed, presenting a high distribution in the northwest and low in the southeast, with a southerly transmission direction(53.32%). Central and southern Hebei, central and northern Henan, and central Shanxi are the potential sources of pollution(WPCWT_ij ≥ 160 μg·m^-3), impacting western Shandong and northwest Shanxi(WPSCF_ij ≥ 0.3) with PM₁₀. Moreover, the O₃(summer) concentration correlated positively with temperature, and negatively with humidity. The southeast-south(54.24%) is the source direction of the transmission, and the potential source of O₃ pollution is an arc area with Shijiazhuang in the center and Cangzhou and Heze as the double wings. Lastly, the PM_2.5(autumn and winter) concentration correlated positively with humidity, and the winter concentration shows an increasing gradient from west to east. The trajectories of PM_2.5 clustered the source directions:autumn(northeast-southeast, 74.75%), winter(northwest, 55.47%); central and southern Hebei, central and western Shanxi and northern Henan are the concentrated sources of potential pollution(WPCWT_ij ≥ 180 μg·m^-3).

Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region-A Case Study of 17 Cities in Hubei Province, China

With the rapid development of the social economy, factors of social and economic development in China's rural areas have been continuously reorganized, and the pattern and distribution of rural residential areas have undergone significant changes. In rural areas, there have been many peculiar phenomena of "reducing people but not reducing land in rural areas, which has caused tremendous pressure on land resource protection. We used geographic detectors and a geographically temporally weighted regression model (GTWR) to explore the rural settlements' evolution and driving mechanism in Hubei Province from 1990 to 2015. The results show that the kernel density of rural settlements decreased from 1.62 villages/km² in 1990 to 1.60 villages/km² in 2015. The scale of rural residential patches has obvious regional differentiation characteristics. From southeast to northwest, there is a wave-like distribution structure of "high-low-high-low-high", and the clustering characteristics of "cold and hot spots" are strengthened with time. Based on GTWR analysis, the total rural population, total power of agricultural machinery, and rural electricity consumption have promoted the expansion of rural settlements, with the regression coefficients 0.096, 0.484, and 0.878, respectively. Cultivated land, agricultural output value, and rural labor force have negative impacts on the expansion, the regression coefficients of the village were -0.584, -0.510, and -0.109, respectively.

Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification of Oncomelania hupensis Breeding Grounds-A Case Study of Dongting Lake Area

Spatio-temporal epidemic simulation, assessment, and risk monitoring serve as the core to establishing and improving the national public health emergency management system. In this study, we investigated Oncomelania hupensis breeding grounds and analyzed the locational and environmental preferences of snail breeding in Dongting Lake (DTL), Hunan, China. Using geographic information systems and remote sensing technology, we identified schistosomiasis risk areas and explored the factors affecting the occurrence and transmission of the disease. Several key conclusions were drawn. (1) From 2006 to 2016, the spatial change of potential O. hupensis breeding risk showed a diminishing trend from the eastern and northern regions to southwest DTL. Environmental changes in the eastern DTL region resulted in the lakeside and hydrophilic agglomerations of the O. hupensis populations. The shift in snail breeding grounds from a fragmented to centralized distribution indicates the weakening mobility of the O. hupensis population, the increasing independence of solitary groups, and the growing dependence of the snail population to the local environment. (2) The spatial risk distribution showed a descending gradient from west Dongting area to the east and an overall pattern of high in the periphery of large lakes and low in other areas. The cold-spot areas had their cores in Huarong County and Anxiang County and were scattered throughout the peripheral areas. The hot-spot areas had their center at Jinshi City, Nanxian County, and the southern part of Huarong County. The areas with increased comprehensive risks changed from centralized and large-scale development to fragmented shrinkage with increased partialization in the core area. The risk distribution's center shifted to the northwest. The spatial risk distribution exhibited enhanced concentricity along the major axis and increased dispersion along the minor axis.

[Spatio-temporal Evolution of PM2.5 Concentration During 2000-2019 in China]

An ensemble estimation model of PM_2.5 concentration was proposed on the basis of extreme gradient boosting, gradient boosting, random forest model, and stacking model fusion technology. Measured PM_2.5 data, MERRA-2 AOD and PM_2.5 reanalysis data, meteorological parameters, and night light data sets were used. On this basis, the spatiotemporal evolution features of PM_2.5 concentration in China during 2000-2019 were analyzed at monthly, seasonal, and annual temporal scales. The results showed that:① Monthly PM_2.5 concentration in China from 2000-2019 can be estimated reliably by the ensemble model. ② PM_2.5 annual concentration changed from rapid increase to remaining stable and then changed to significant decline from 2000-2019, with turning points in 2007 and 2014. The monthly variation of PM_2.5 concentration showed a U shape that first decreased then increased, with the minimum value in July and the maximum value in December. ③ Natural geographic conditions and human activities laid the foundation for the annual spatial pattern change of PM_2.5 concentration in China, and the main trend of monthly spatial pattern change of PM_2.5 concentration was determined by meteorological conditions. ④ At an annual scale, the national PM_2.5 concentration average center of standard deviation ellipse moved eastward from 2000-2014 and westward from 2014-2018. At a monthly scale, the average center shifted to the west from January to March, moved northward then southward from April to September, and shifted to the east from September to December.

A quantitative analysis of the spatial and temporal evolution patterns of the bluetongue virus outbreak in the island of Lesvos, Greece, in 2014

Bluetongue virus (BTV) causes an infectious disease called bluetongue, a vector-borne viral disease of ruminants, which has major implications and causes severe economic damage due to its effect on livestock. These economic costs are mostly ascribed to the trade restrictions imposed during the epidemic period. In August 2014, an epidemic of bluetongue occurred in the island of Lesvos, Greece. The epidemic was severe and evolved over time, lasting until December 2014. The total cases of infected farms were 490, including a total number of 136,368 small ruminants. In this paper, we describe a bluetongue virus serotype 4 (BTV-4) epidemic and utilize Bayesian epidemic models to capture the spatio-temporal spread of the disease. Our study provides important insights into the drivers of BTV transmission and has implications for designing control strategies. The results showed strong spatial autocorrelations, with BTV being more likely to spread between farms located nearby. The spatial modelling results proposed a certain spatial radius (~12 km) around the onset of a similar epidemic for imposing restrictions on animal movement, which can be sufficient for the control of the disease and limit economic damage.

[Spatio-temporal Evolution of Groundwater Vulnerability Based on Spatial Autocorrelation]

The distribution patterns of human activities affecting groundwater vulnerability vary with time. Studying the temporal and spatial changes in groundwater vulnerability, exploring the distribution characteristics of each period, and predicting the trends of development are important to formulate an effective development plan and reduce the risk of groundwater pollution at the same time. Based on the hydrogeological data as well as humanities and social data for 2004, 2010, and 2016 for the Chaoyang District of Beijing, a comprehensive evaluation model considering the human factors such as the land use types was established using the DRASTIC model. The spatiotemporal pattern of groundwater vulnerability was quantitatively characterized by calculating the Global Moran's Ⅰ and Getis-Ord Gi^* index, and the distribution characteristics and variations in groundwater vulnerability were analyzed by the centroid of the G index and the standard deviation ellipse of the study area. The results indicate that in 2004, 2010, and 2016, the areas of high vulnerability have gradually reduced. The groundwater vulnerability in the study area shows a strong spatial aggregation; high concentration areas are mainly distributed in the northeast and southwest regions. The vulnerability of the northeast region has been decreasing each year, while the vulnerability of the northwest region has not changed much. The main reasons are the land use changes and the reductions in fertilizer use.

Spatial Characteristics and Driving Factors of Provincial Wastewater Discharge in China

Based on the increasing pressure on the water environment, this study aims to clarify the overall status of wastewater discharge in China, including the spatio-temporal distribution characteristics of wastewater discharge and its driving factors, so as to provide reference for developing “emission reduction” strategies in China and discuss regional sustainable development and resources environment policies. We utilized the Exploratory Spatial Data Analysis (ESDA) method to analyze the characteristics of the spatio-temporal distribution of the total wastewater discharge among 31 provinces in China from 2002 to 2013. Then, we discussed about the driving factors, affected the wastewater discharge through the Logarithmic Mean Divisia Index (LMDI) method and classified those driving factors. Results indicate that: (1) the total wastewater discharge steadily increased, based on the social economic development, with an average growth rate of 5.3% per year; the domestic wastewater discharge is the main source of total wastewater discharge, and the amount of domestic wastewater discharge is larger than the industrial wastewater discharge. There are many spatial differences of wastewater discharge among provinces via the ESDA method. For example, provinces with high wastewater discharge are mainly the developed coastal provinces such as Jiangsu Province and Guangdong Province. Provinces and their surrounding areas with low wastewater discharge are mainly the undeveloped ones in Northwest China; (2) The dominant factors affecting wastewater discharge are the economy and technological advance; The secondary one is the efficiency of resource utilization, which brings about the unstable effect; population plays a less important role in wastewater discharge. The dominant driving factors affecting wastewater discharge among 31 provinces are divided into three types, including two-factor dominant type, three-factor leading type and four-factor antagonistic type. In addition, the proposals aimed at reducing the wastewater discharge are provided on the basis of these three types.

Spatio-temporal evolution of Beijing 2003 SARS epidemic

Studying spatio-temporal evolution of epidemics can uncover important aspects of interaction among people, infectious diseases, and the environment, providing useful insights and modeling support to facilitate public health response and possibly prevention measures. This paper presents an empirical spatio-temporal analysis of epidemiological data concerning 2321 SARS-infected patients in Beijing in 2003. We mapped the SARS morbidity data with the spatial data resolution at the level of street and township. Two smoothing methods, Bayesian adjustment and spatial smoothing, were applied to identify the spatial risks and spatial transmission trends. Furthermore, we explored various spatial patterns and spatio-temporal evolution of Beijing 2003 SARS epidemic using spatial statistics such as Moran's I and LISA. Part of this study is targeted at evaluating the effectiveness of public health control measures implemented during the SARS epidemic. The main findings are as follows. (1) The diffusion speed of SARS in the northwest-southeast direction is weaker than that in northeast-southwest direction. (2) SARS's spread risk is positively spatially associated and the strength of this spatial association has experienced changes from weak to strong and then back to weak during the lifetime of the Beijing SARS epidemic. (3) Two spatial clusters of disease cases are identified: one in the city center and the other in the eastern suburban area. These two clusters followed different evolutionary paths but interacted with each other as well. (4) Although the government missed the opportunity to contain the early outbreak of SARS in March 2003, the response strategies implemented after the mid of April were effective. These response measures not only controlled the growth of the disease cases, but also mitigated the spatial diffusion.