Bilevel Programming Model of Private Capital Investment in Urban Public Transportation: Case Study of Jinan City

Increasing public transportation subsidies have created fiscal pressures for governments. To ease this financial pressure, Chinese government strongly encourages private capital investment in public transportation. However, previous private capital investments in public transportation operations have largely failed, mainly due to low ticket fares that cannot support sustainable operations. To address this issue, several previous research projects have developed methods to facilitate private capital investment. The majority of the research focuses on qualitative analysis and value for money analysis. Our research proposed a new method of private capital investment in public transportation operations based on the concept of “passenger value.” The feasibility of the proposed method of private investment was analyzed quantitatively by constructing a bilevel programming model. The model was verified based on a sample analysis of Jinan city traffic. Results showed that effective private capital investment increases the total societal benefit from the public transportation system and additionally that the investment method considering “passenger value” is superior to the traditional one. A quantitative tool was provided by the model to evaluate private capital investment effects, design investment policies, and develop further research

Ecoenzymatic stoichiometry reveals widespread soil phosphorus limitation to microbial metabolism across Chinese forests

8 páginas.- 4 figuras.- 57 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s43247-022-00523-5Forest soils contain a large amount of organic carbon and contribute to terrestrial carbon sequestration. However, we still have a poor understanding of what nutrients limit soil microbial metabolism that drives soil carbon release across the range of boreal to tropical forests. Here we used ecoenzymatic stoichiometry methods to investigate the patterns of microbial nutrient limitations within soil profiles (organic, eluvial and parent material horizons) across 181 forest sites throughout China. Results show that, in 80% of these forests, soil microbes were limited by phosphorus availability. Microbial phosphorus limitation increased with soil depth and from boreal to tropical forests as ecosystems become wetter, warmer, more productive, and is affected by anthropogenic nitrogen deposition. We also observed an unexpected shift in the latitudinal pattern of microbial phosphorus limitation with the lowest phosphorus limitation in the warm temperate zone (41-42 degrees N). Our study highlights the importance of soil phosphorus limitation to restoring forests and predicting their carbon sinks. Phosphorus limitation of soil microbial communities in forests is widespread, increases with soil depth, and is enhanced under wetter and warmer climates and elevated anthropogenic nitrogen deposition, according to ecoenzymatic stoichiometric analyses across 181 forests in China.This study was financially supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB40000000), Funds for International Cooperation and Exchange of National Natural Science Foundation of China (32061123007), National Natural Science Foundation of China (41977031), Program of State Key Laboratory of Loess and Quaternary Geology CAS (SKLLQGZR1803). Contributions from Dr. Chen are funded by H2020 Marie Skłodowska-Curie Actions (No. 839806). M.D.-B. acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 funded by CIN/AEI/10.13039/501100011033. M.D.-B. is also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014-2020 Objetivo temático “01–Refuerzo de la investigación, el desarrollo tecnológico y la innovación”) associated with the research project P20_00879 (ANDABIOMA).Peer reviewe

Quantifying a Financially Sustainable Strategy of Public Transport: Private Capital Investment Considering Passenger Value

Releaving traffic congestion by developing public transport as an alternative mode of travel is a common practice all over the world. However, the increasing public transport subsidies have created a financial burden for governments. Encouragingly, private capital supplies an opportunity for public transport in sustainable finance. Previous research mainly focuses on qualitative analysis and money-for-value (MFV) analysis. In this paper, a new investment model is proposed based on the concept ‘passenger value’, and a bi-level programming model (BLPM) is constructed as a quantitative analysis tool. The upper target of BLPM is the total surplus (including the value of time (VOT) of passengers) of the public transport system and the upper constraint is the ticket price. The lower target of BLPM is passenger’s surplus, the lower constraints are service capability and the lowest return rate of the private sector. The public transport of Jinan City, China is taken as a case to quantify the impacts of private capital investment in public transport. Results show that the proposed investment model considering passenger value is superior to the traditional one, and effective private capital investment could increase the total societal benefit of the transportation system. The proposed investment strategy satisfies economic viability and is a financially sustainability strategy. Additionally, travelers should be encouraged to use public transport through improving the service quality and passenger returns. Only in this way can the success rate of the private sector investment in public transport be improved efficiently

Commuter Departure Time Choice Considering Parking Space Shortage and Commuter’s Bounded Rationality

In order to better understand how commuters decide departure time considering parking space shortage and commuters’ bounded rationality, the reference point hypothesis of prospect theory is applied in the departure time decision-making. Commuter personal perception differences, the road congestion situation, destination parking status, and other factors were also analysed in the influence of commuter departure time choice. Based on prospect theory, an experiment was designed to investigate the intention of the commuter departure time choice. The experiment results show that the commuter’s travel satisfaction and the departure time choice of the next trip are related to the parking space residual status after the commuter arrives at the destination. The satisfaction degree of the commuter is reduced, with the decrease of the remaining parking spaces. If the commuter is satisfied with the travel result, the commuter’s departure time of next trip tends to be later. In the case of illegal parking, different penalty measures may lead to different decisions of next departure time choice. A commuter tends to depart earlier when more severe punishment for illegal parking is enforced. The research results can reveal to some degree the travellers’ departure time choice behaviour when they face the risk of no parking spaces and provide a theoretical and practical support for parking management and car travelling decision

Research on the combinatorial optimization of EBs departure interval and vehicle configuration based on uncertain bi-level programming

Based on uncertainty theory, this paper proposed a vehicle scheduling method considering the dynamic departure interval and vehicle configuration of electric buses (EBs). An uncertain bi-level programming model (UBPM) is established, which takes the total cost of passenger travel (CP) as the upper and total cost of EBs (CB) as the lower. A chance constrained programming model (CCPM) based on the randomness of passenger waiting time and the uncertainty of interstation running time is proposed as the upper model. With a certain confidence level of service level as constraints, the goal is to minimize the total cost of passenger travel. Then, an expected value model (EVM) based on the fluctuation of energy consumption is proposed as the lower model. Taking the number of EBs as the constraint condition, the goal was to minimize the energy consumption of EBs. Finally, a practical bus route is taken as an example to verify the effectiveness of the proposed method. The results demonstrated that the optimal scheduling plan considering the uncertain variables can reduce the passenger travel cost. Collaborative optimization of EBs vehicle configuration can reduce energy consumption, delay, and the number of EBs

A Traffic Mode Choice Model for the Bus User Groups based on SP and RP Data

Enhancing the bus share rate is a major measure to relieve the traffic congestion. To analyze the effect of public transit policy, this paper establishes MNL models based on both SP data and combining SP and RP data, which was collected in Jinan city. Then the paper analyzes how the influencing factors affect the choice proportion of bus travel mode for the bus user groups. In the end, the paper obtains some significant conclusions and proposes measures which would enhance the bus attraction

Research on Optimization of Customized Bus Routes Based on Uncertainty Theory

In the optimization process of the routes of customized buses, there are numerous uncertainties in the route planning and setting. In this study, the uncertainty theory is introduced into the optimization problem of a customized bus route, and an uncertain customized bus route optimization model is established, which aims at the minimizing the total mileage of vehicle operation. An improved genetic algorithm is used to solve the model, whose feasibility is verified by a case study. The results show that the optimization model based on the uncertainty theory can yield a reasonable customized bus route optimization scheme, and the total mileage reduced from 35.6 kilometers to 32.2 kilometers. This research provides the theoretical support for the optimization of customized bus routes

Hydrodynamic analysis of clastic injection and hydraulic fracturing structures in the Jinding Zn-Pb deposit, Yunnan, China

The Jinding Zn-Pb deposit has been generally considered to have formed from circulating basinal fluids in a relatively passive way, with fluid flow being controlled by structures and sedimentary facies, similar to many other sediments-hosted base metal deposits. However, several recent studies have revealed the presence of sand injection structures, intrusive breccias, and hydraulic fractures in the open pit of the Jinding deposit and suggested that the deposit was formed from explosive release of overpressured fluids. This study reports new observations of fluid overpressure-related structures from underground workings (Paomaping and Fengzishan), which show clearer crosscutting relationships than in the open pit. The observed structures include: 1) sand (±rock fragment) dikes injecting into fractures in solidified rocks; 2) sand (±rock fragment) bodies intruding into unconsolidated or semi-consolidated sediments; 3) disintegrated semi-consolidated sand bodies; and 4) veins and breccias formed from hydraulic fracturing of solidified rocks followed by cementation of hydrothermal minerals. The development of ore minerals (sphalerite) in the cement of the various clastic injection and hydraulic fractures indicate that these structures were formed at the same time as mineralization. The development of hydraulic fractures and breccias with random orientation indicates small differential stress during mineralization, which is different from the stress field with strong horizontal shortening prior to mineralization. Fluid flow velocity may have been up to more than 11 m/s based on calculations from the size of the fragments in the clastic dikes. The clastic injection and hydraulic fracturing structures are interpreted to have formed from explosive release of overpressured fluids, which may have been related to either magmatic intrusions at depth or seismic activities that episodically tapped an overpressured fluid reservoir. Because the clastic injection and hydraulic structures are genetically linked with the mineralizing fluid source, they can be used as a guide for mineral exploration

Cross-Regional Customized Bus Route Planning Considering Staggered Commuting During the COVID-19

In order to solve the problem of cross-regional customized bus (CB) route planning during the COVID-19, we develop a CB route planning method based on an improved Q-learning algorithm. First, we design a sub-regional route planning approach considering commuters' time windows of pick-up stops and drop-off stops. Second, for the CB route with the optimal social total travel cost, we improve the traditional Q-learning algorithm, including state-action pair, reward function and update rule of Q value table. Then, a setup method of CB stops is designed and the path impedance function is constructed to obtain the optimal operating path between each of the two stops. Finally, we take three CB lines in Beijing as examples for numerical experiment, the theoretical and numerical results show that (i) compared with the current situation, although the actual operating cost of optimized route increases slightly, it is covered by the reduction of travel cost of passengers and the transmission risk of COVID-19 has also dropped significantly; (ii) the improved Q-learning algorithm can solve the problem of data transmission lag effectively and reduce the social total travel cost obviously