Spatiotemporal Distribution and Epidemiological Characteristics of Hospital Admissions for Carbon Monoxide Poisoning in Guangdong,China,2013-2020

Objective This study aimed to determine the spatiotemporal distribution and epidemiological characteristics of hospital admissions for carbon monoxide poisoning(COP)in Guangdong,China,from 2013 to 2020.Methods Data on age-and sex-specific numbers of hospital admissions due to COP in Guangdong(2013-2020)were collected.Daily temperatures were downloaded through the China Meteorological Data Sharing Service System.We analyzed temporal trends through time series decomposition and used spatial autocorrelation analysis to detect spatial clustering.The distributed lag nonlinear model was used to quantify the effects of temperature.Results There were 48,854 COP admissions over the study period.The sex ratio(male to female)was1:1.74.The concentration ratios(M)ranged from 0.73-0.82.The highest risk occurred in January(season index=3.59).Most cases were concentrated in the northern mountainous areas of Guangdong with high-high clustering.COP in the study region showed significant spatial autocorrelation,and the global Moran’s I value of average annual hospital admission rates for COP was 0.447(P<0.05).Low temperatures were associated with high hospital admission rates for COP,with a lag lasting 7 days.With a lag of 0 days,the effects of low temperatures[5th(12℃)]on COP were 2.24-3.81,as compared with the reference temperature[median(24℃)].Conclusion COP in Guangdong province showed significant temporal and spatial heterogeneity.Low temperature was associated with a high risk of COP,and the influence had a lag lasting 7 days.

Cyber-physical Integrated Planning of Distribution Networks Considering Spatial-temporal Flexible Resources

The rapid development of cyber technology and the increase of flexible resources have transformed the distribution network into a cyber-physical distribution system,while the accompanying multidimensional uncertainties have brought new planning challenges.In this paper,an innovative approach is proposed to effectively leverage distributed resources while considering the impact of cyber-physical coupling in distribution network planning.A cyber-physical integrated planning model of the distribution network is proposed,considering the effects of spatial-temporal flexible resources and multi-network coupling.Specifically,a three-layer optimization model is established and analyzed by the simulate anneal-particle swarm optimization algorithm.The upper layer achieves the optimization of the location and configuration of energy storage systems and smart terminal units.The middle layer optimizes the data load migration strategy using spatial-temporal flexible resources to solve the voltage exceeding problem caused by high penetration of distributed power access,while the lower layer optimizes the cyber side communication topology,improving the convergence speed and control performance of the distribution network.Then,the optimization model is analyzed iteratively with objective functions including total planning cost,operation excess loss and distributed control performance.Finally,the effectiveness and economy of the proposed planning scheme is verified and compared to traditional methods.

Very Short-term Spatial and Temporal Wind Power Forecasting: A Deep Learning Approach

In power systems that experience high penetration of wind power generation,very short-term wind power forecast is an important prerequisite for look-ahead power dispatch.Conventional univariate wind power forecasting methods at presentonly utilize individual wind farm historical data.However,studies have shown that forecasting accuracy canbe improved by exploring both spatial and temporal correlations among adjacent wind farms.Current research on spatial-temporal wind power forecasting is based on relatively shallow time series models that,to date,have demonstrated unsatisfactory performance.In this paper,a convolution operation is used to capture the spatial and temporal correlations among multiple wind farms.A novel convolution-based spatial-temporal wind power predictor(CSTWPP)is developed.Due to CSTWPP’s high nonlinearity and deep architecture,wind power variation features and regularities included in the historical data can be more effectively extracted.Furthermore,the online training of CSTWPP enables incremental learning,which makes CSTWPP non-stationary and in conformity with real scenarios.Graphics processing units(GPU)is used to speed up the training process,validating the developed CSTWPP for real-time application.Case studies on 28 adjacent wind farms are conducted to show that the proposed model can achieve superior performance on 5-30 minutes ahead wind power forecasts.

Hazards of extreme events in China under different global warming targets

Changes in the frequency and intensity of extreme events affect the risk pattern of risk-bearing bodies and the effectiveness of response measures.Based on future climate scenario data,in this study,we identify global warming periods of 1.5℃ and 2℃ above pre-industrial levels,and the temporal and spatial patterns of temperature and precipitation in China during the same period,propose a methodology for risk assessment and integrated analysis of extreme events,build a database of extreme events and their hazards in China in the context of climate change,and assess the hazards caused by extreme events(i.e.,heatwaves,floods,and droughts)in China under different warming periods.Under the RCP4.5 and RCP8.5 scenarios,global temperatures increase by 1.5℃ and 2℃ above preindustrial levels by 2029 and 2026 and by 2050 and 2040,respectively.The warming would be fast in the north and slow in the south,the warming of the Qinghai-Tibet Plateau would accelerate,and the precipitation would increase in the north and decrease in the south,but the trend of the precipitation reduction in the south would be more significant under the RCP8.5 scenario.For 2℃ of warming,the hazard index of severe heatwaves in the North China Plain,parts of South China,and the western part of Inner Mongolia would double that of 1.5℃ warming.Regional differences in extreme precipitation would increase,especially under the RCP8.5 scenario,the hazard index of severe floods in parts of East China would be about twice that of 1.5℃ warming.Under the joint influence of rising temperature and changing precipitation,the drought situation would be alleviated under the RCP4.5 scenario,but it is intensified under the RCP8.5 scenario.For 2℃ of warming,the hazard index of severe droughts in some areas would reach three times that of 1.5℃ warming.For the integrated hazard of the three types of extreme events,the areas of high and medium hazards would expand,while the areas of low hazard would decrease.For 2℃ of warming,the areas of high and medium hazards would be more than half the total area.

Impacts of regional land-use patterns on ecosystem services in the typical agro-pastoral ecotone of northern China

A comprehensive understanding of the spatial-temporal evolution and driving forces on ecosystem services(ES)is essential for the agro-pastoral ecotone’s ecological security in northern China.However,the land-use pattern(LULC)agglomeration with spatial differentiation in the pastoral and agricultural areas has been rarely concerned.Taking distinct LULC(1980-2018)in Chifeng as an example,we compared four crucial categories of ESs with InVEST.Using SEM,we further contrasted the effects of several variables on regional ES variations in pastoral-dominated(North)and agriculture-dominated(South)regions,respectively.Results revealed the conversion between forest and grassland oriented the LULC transformation in the North.In contrast,human-activitiy-oriented land tended to occupy environmentally sensitive places in the South.Similar ES variations were supplied with the North outperforming the South when soil conservation was omitted.As for the impacts of regional ES variations,the natural and LULC policies both showed positive effects,whereas the anthropogenic factors showed positive in the North,which was negative in the South.Therefore,the ecologicallymaintained-dominant and ecologically-restored-dominant strategies should be separately adopted in the North and South.Our study provided appropriate regional ecological management suggestions for balancing the LULC-driven conflicts between ecological protection and regional development.