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In recent years, epidemic disasters broke through frequently around the world, posing a huge threat to economic and social development, as well as human health. A fair and accurate distribution of emergency supplies during an epidemic is vital for improving emergency rescue efficiency and reducing economic losses. However, traditional emergency material allocation models often focus on meeting the amount of materials requested, and ignore the differences in the importance of different emergency materials and the subjective urgency demand of the disaster victims. As a result, it is difficult for the system to fairly and reasonably match different scarce materials to the corresponding areas of greatest need. Consequently, this paper proposes a material shortage adjustment coefficient based on the entropy weight method, which includes indicators such as material consumption rate, material reproduction rate, durability, degree of danger to life, and degree of irreplaceability, to enlarge and narrow the actual shortage of material supply according to the demand urgency. Due to the fact that emergency materials are not dispatched in one go during epidemic periods, a multi-period integer programming model was established to minimize the adjusted total material shortage based on the above function. Taking the cases of Wuhan and Shanghai during the lockdown and static management period, the quantitative analysis based on material distribution reflected that the model established in this paper was effective in different scenarios where there were significant differences in the quantity and structure of material demand. At the same time, the model could significantly adjust the shortage of emergency materials with higher importance and improve the satisfaction rate. [ABSTRACT FROM AUTHOR]

OpenStreetMap (OSM) road networks provide public digital maps underlying many spatial applications such as routing engines and navigation services. However, turning relationships and time restrictions at OSM intersections are lacking in these maps, posing a threat to the accuracy and reliability of the services. In this paper, a new turn information detection method for OSM intersections using the dynamic connection information from crowdsourced trajectory data is proposed to address this problem. In this solution, the OSM intersection structure is extracted and simplified and crowdsourced trajectories are projected onto OSM road segments using an improved Hidden Markov Model (HMM) map matching method that explicitly traces the turning connections in road networks. Optimal path analysis increases the turning support related to short road segments. On this basis, this study transforms complex turning identification scenarios into the simple analyses of traffic connectivity. Furthermore, a voting strategy is used to identify and calculate turning time restrictions. The experimental results, using trajectory data from three cities in China, show that the turning relationships can be detected at a precision of 90.71% with a recall of 96.55% and an F1-value of 93.54% in Shanghai. For Wuhan, the precision is 95.33% and the recall is 95.00%, with an F1-value of 95.16%. The precision and recall when identifying turning time restrictions both reach 90% in Xiamen. These results demonstrate the effectiveness of the proposed turning detection method. [ABSTRACT FROM AUTHOR]

In recent years, as China's peaking carbon dioxide emissions and air pollution control projects have converged, scholars have begun to focus on the synergistic mechanisms of greenhouse gas and pollution gas reduction. In 2020, the unprecedented coronavirus pandemic, which led to severe nationwide blockade measures, unexpectedly provided a valuable opportunity to study the synergistic reduction in greenhouse gases and polluting gases. This paper uses a combination of NO2, O3, and CO2 column concentration products from different satellites and surface concentrations from ground-based stations to investigate potential correlations between these monitoring indicators in four Chinese representative cities. We found that XCO2 decreased in March to varying degrees in different cities. It was witnessed that the largest decrease in CO2, −1.12 ppm, occurred in Wuhan, i.e., the first epicenter of COVID-19. We also analyzed the effects of NO2 and O3 concentrations on changes in XCO2. First, in 2020, we used a top-down approach to obtain the conclusion that the change amplitude of NO2 concentration in Beijing, Shanghai, Guangzhou, and Wuhan were −24%, −18%, −4%, and −39%, respectively. Furthermore, the O3 concentration increments were 5%, 14%, 12%, and 14%. Second, we used a bottom-up approach to obtain the conclusion that the monthly averaged NO2 concentrations in Beijing, Shanghai, and Wuhan in March had the largest changes, changing to −39%, −40%, and −61%, respectively. The corresponding amounts of changes in monthly averaged O3 concentrations were −14%, −2%, and 9%. However, the largest amount of change in monthly averaged NO2 concentration in Guangzhou was found in December 2020, with a value of −40%. The change in O3 concentration was −12% in December. Finally, we analyzed the relationship of NO2 and O3 concentrations with XCO2. Moreover, the results show that the effect of NO2 concentration on XCO2 is positively correlated from the point of the satellite (R = 0.4912) and the point of the ground monitoring stations (R = 0.3928). Surprisingly, we found a positive (in satellite observations and R = 0.2391) and negative correlation (in ground monitoring stations and R = 0.3333) between XCO2 and the O3 concentrations. During the epidemic period, some scholars based on model analysis found that Wuhan's carbon emissions decreased by 16.2% on average. Combined with satellite data, we estimate that Wuhan's XCO2 fell by about 1.12 ppm in February. At last, the government should consider reducing XCO2 and NO2 concentration at the same time to make a synergistic reduction. [ABSTRACT FROM AUTHOR]

The concept of transit deserts stems from the concept of food deserts. There is substantial research on transit deserts in developed countries. However, there is no known research that has studied this subject in Chinese cities. Using open-source data, this paper identified transit desert areas in four major Chinese cities (Beijing, Shanghai, Wuhan, Chengdu). The results show that: (1) In these four cities, the transit desert areas are mainly concentrated in city centers and hardly occur in any suburban areas, which is very different from the cases in the US. (2) Shanghai has the largest transit-dependent population living in transit deserts, followed by Beijing, Chengdu, and Wuhan. Chengdu has the smallest transit desert areas, followed by Shanghai, Wuhan, and Beijing. (3) An oversized transit-dependent population and incomplete transit systems in these cities might contribute to the transit deserts' occurrences. (4) Different distribution of population density, traveling preference, and transportation investment policy in Chinese and American cities might contribute to the different findings. By examining transit desert problems in major Chinese cities, this study brought people's attention to the gap between transit demand and supply in China. [ABSTRACT FROM AUTHOR]

Various measures have been taken to improve ship energy efficiency while decreasing CO2 emissions. In this work, the navigation environment between Wuhan and Shanghai in China has been classified based on an improved K-means algorithm in order to realize route division. A fuel consumption prediction model considering the navigation environment factors has been established. Consequently, speed optimization models with multiple different optimization objectives have been constructed and tested based on an actual case using an artificial fish swarm algorithm. Finally, sensitivity analysis has been carried out focusing on the navigation time, fuel price, charter rate, free carbon credits, and carbon tax rate. The results show that the total shipping cost and CO2 emissions could be reduced by 0.94% and 0.38%, respectively, after the optimization. Considering a carbon tax policy with a tax rate of roughly 1300 RMB/t, the optimization result (including the carbon tax cost) is close to the compromised solution of multi-objective optimization, and the corresponding carbon tax rate can provide a useful reference for policymakers. [ABSTRACT FROM AUTHOR]

Developing the engineering design standard of wind speed is a key aspect of the climate research in the Yangtze River Inland Waterway (YRIW), which is highly sensitive to extreme weather and climate processes. An engineering design wind speed projection model was established to evaluate the distribution of extreme wind speeds in the YRIW region at spatiotemporal scales from 1979 to 2100, integrating the Weibull distribution and generalized extreme value (GEV) distribution characteristics. We also used high-precision climate model products and integrated analysis methods to predict the evolution of engineering design wind speeds in the study area in the future. The results show that: (1) The maximum wind speed in the study area shows a decline—recovery trend in the historical period in general and a weak increase in Wuhan and Shanghai. (2) The maximum wind speed does not follow the Weibull distribution, and the extracted extreme wind speed types include type I, II, and III GEV distributions. (3) The updated inland port project design wind speed can meet the climatic and topographic characteristics of the YRIW. (4) The model of CNRM-CM6-1-HR product accurately captures the spatial and temporal characteristics of the maximum wind speed. (5) In the future, the design wind speed shows a slight decrease in Shanghai, Jiujiang and Yueyang. These findings provide a scientific theoretical reference and engineering reference for the development of design wind speeds for inland port projects at various cross-sections in the YRIW. [ABSTRACT FROM AUTHOR]

Excessive phosphorus is the main problem of water pollution in the main stream of the Yangtze River, while it is not clear about the distribution characteristics and spatial differences of phosphorus in the urban river stretches of the middle and lower reaches of the Yangtze River. In this study, a field survey in June 2014 revealed that the average particulate phosphorus (PP) concentration ranged from 0.195 mg/L to 0.105 mg/L from Wuhan (WH) in the middle reaches of the Yangtze River to Shanghai (SH, 1081 km from WH) in the lower reaches of the Yangtze River, and the average PP-to-the total phosphorus (TP) ratio decreased from 85.71% in WH to 45.65% in SH, while the average soluble reactive phosphate (SRP) concentration ranged from 0.033 to 0.125 mg/L, and the average SRP-to-total dissolved phosphorus (TDP) ratio increased from 60.73% in WH to 88.28% in SH. In general, PP was still an important form of TP in the middle and lower reaches of the Yangtze River. The concentrations of PP and SRP at different sampling locations and water depths in the same monitoring section showed differences, which might be related to the transportation and sedimentation of suspended sediment (SS) and differences in the location of urban sewage outlets. Historical data showed that the concentration and particle size of the SS decreased over time, while the discharge of wastewater also increased over time in the Yangtze River Basin. The measured results showed that there was a significant positive correlation between SS and PP. As a result, the concentration of SRP might increase in the middle and lower reaches of the Yangtze River. If the SRP concentration is not properly controlled, the degree of eutrophication of water body could significantly increase in the Yangtze River estuary, the riparian zone of the urban river stretches, the tributary slow-flow section, and the corresponding lakes connected with the Yangtze River. [ABSTRACT FROM AUTHOR]