This page has only limited features, please log in for full access.
Ground-level ozone is a secondary air pollutant that is formed by chemical reactions between precursors, including nitrogen oxides (NOx) and hydrocarbon (HC). Highway traffic, which can be controlled by traffic operational strategies, is one of the main sources of atmospheric NOx and HC. Managed-lane pricing is one of the popularly used freeway traffic management approaches, while its impacts on ground-level ozone-related vehicle emissions is, however, still unclear. This motivated the purpose of this research. A case study in Houston, USA indicates that, vehicles on managed lanes had fewer hard accelerations/decelerations and higher average speed, which resulted in higher per-vehicle emissions in grams/hour, while the total emissions of a vehicle were roughly comparable to what they would be on a general-purpose lane. Total daily NOx and HC emissions per managed lane were 31.9%–42.6% of those per general-purpose lane. The weight ratios between HC and NOx show that, the ground-level ozone formation of this area is hydrocarbon-limited.
Jianbang Du; Fengxiang Qiao; Lei Yu; Ying Lv. Impact of Managed-Lane Pricing Strategies on Vehicle-Sourced NOx and HC Emissions. Gases 2021, 1, 117 -132.
AMA StyleJianbang Du, Fengxiang Qiao, Lei Yu, Ying Lv. Impact of Managed-Lane Pricing Strategies on Vehicle-Sourced NOx and HC Emissions. Gases. 2021; 1 (2):117-132.
Chicago/Turabian StyleJianbang Du; Fengxiang Qiao; Lei Yu; Ying Lv. 2021. "Impact of Managed-Lane Pricing Strategies on Vehicle-Sourced NOx and HC Emissions." Gases 1, no. 2: 117-132.
Freight transportation contributes to increasing carbon emissions in the transportation sector. The CO2 emissions inherently caused by the intercity freight transportation between cities should be emphasized. This study first introduces the concepts of CO2 emission intensity (EI) based on the extraction of freight transportation information in the form of GPS trajectory data. A gravity theory-based intercity CO2 EI model is proposed, so that the driving forces of emission generation can be revealed. Then, we analyze the CO2 EI in terms of mobility characteristics, spatial autocorrelation, and influencing factors. Finally, the proposed method is applied to a typical case study of the Beijing-Tianjin-Hebei urban agglomeration for evaluation of an emission control policy. The findings provide a theoretical reference for analyzing the intercity connections within a regional urban agglomeration in terms of emissions, and support the implementation of feasible emission reduction strategies.
Guangtong Xu; Ying Lv; Huijun Sun; Jianjun Wu; Zhenzhen Yang. Mobility and evaluation of intercity freight CO2 emissions in an urban agglomeration. Transportation Research Part D: Transport and Environment 2021, 91, 102674 .
AMA StyleGuangtong Xu, Ying Lv, Huijun Sun, Jianjun Wu, Zhenzhen Yang. Mobility and evaluation of intercity freight CO2 emissions in an urban agglomeration. Transportation Research Part D: Transport and Environment. 2021; 91 ():102674.
Chicago/Turabian StyleGuangtong Xu; Ying Lv; Huijun Sun; Jianjun Wu; Zhenzhen Yang. 2021. "Mobility and evaluation of intercity freight CO2 emissions in an urban agglomeration." Transportation Research Part D: Transport and Environment 91, no. : 102674.
The accidents caused by hazardous material during road transportation may result in catastrophic losses of lives and economics, as well as damages to the environment. Regarding the deficiencies in the information systems of hazmat transportation accidents, this study conducts a survey of 371 accidents with consequence Levels II to V involving road transportation in China from 2004–2018. The study proposes a comprehensive analysis framework for understanding the overall status associated with key factors of hazmat transportation in terms of characteristics, cause, and severity. By incorporating the adaptive data analysis techniques and tackling uncertainty, the preventative measures can be carried out for supporting safety management in hazmat transportation. Thus, this study firstly analyzed spatial–temporal trends to understand the major characteristics of hazmat transportation accidents. Secondly, it presented a quantitative description of the relation among the hazmat properties, accident characteristics, and the consequences of the accidents using the decision tree approach. Thirdly, an enhanced F-N curve-based analysis method that can describe the relationship between cumulative probability F and number of deaths N, was proposed under the power-law distribution and applied to several practical data sets for severity analysis. It can evaluate accident severity of hazmat material by road transportation while taking into account uncertainty in terms of data sources. Through the introduction of the as low as reasonably practicable (ALARP) principle for determining acceptable and tolerable levels, it is indicated that the F-N curves are above the tolerable line for most hazmat accident scenarios. The findings can provide an empirically supported theoretical basis for the decision-makers to take action to reduce accident frequencies and risks for effective hazmat transportation management.
Li Zhou; Chun Guo; Yunxiao Cui; Jianjun Wu; Ying Lv; Zhiping Du. Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management. International Journal of Environmental Research and Public Health 2020, 17, 2793 .
AMA StyleLi Zhou, Chun Guo, Yunxiao Cui, Jianjun Wu, Ying Lv, Zhiping Du. Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management. International Journal of Environmental Research and Public Health. 2020; 17 (8):2793.
Chicago/Turabian StyleLi Zhou; Chun Guo; Yunxiao Cui; Jianjun Wu; Ying Lv; Zhiping Du. 2020. "Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management." International Journal of Environmental Research and Public Health 17, no. 8: 2793.
Forecasting of river ice breakup timing is directly related to the local ice-caused flooding management. However, river ice forecasting using k-nearest neighbor (kNN) algorithms is limited. Thus, a kNN stacking ensemble learning (KSEL) method was developed and applied to forecasting breakup dates (BDs) for the Athabasca River at Fort McMurray in Canada. The kNN base models with diverse inputs and distance functions were developed and their outputs were further combined. The performance of these models was examined using the leave-one-out cross validation method based on the historical BDs and corresponding climate and river conditions in 1980–2015. The results indicated that the kNN with the Chebychev distance functions generally outperformed other kNN base models. Through the simple average methods, the ensemble kNN models using multiple-type (Mahalanobis and Chebychev) distance functions had the overall optimal performance among all models. The improved performance indicates that the kNN ensemble is a promising tool for river ice forecasting. The structure of optimal models also implies that the breakup timing is mainly linked with temperature and water flow conditions before breakup as well as during and just after freeze up.
Wei Sun; Ying Lv; Gongchen Li; Yumin Chen. Modeling River Ice Breakup Dates by k-Nearest Neighbor Ensemble. Water 2020, 12, 220 .
AMA StyleWei Sun, Ying Lv, Gongchen Li, Yumin Chen. Modeling River Ice Breakup Dates by k-Nearest Neighbor Ensemble. Water. 2020; 12 (1):220.
Chicago/Turabian StyleWei Sun; Ying Lv; Gongchen Li; Yumin Chen. 2020. "Modeling River Ice Breakup Dates by k-Nearest Neighbor Ensemble." Water 12, no. 1: 220.
The shipments of hazardous materials (hazmat) which are indispensable for economic and social development have increased; accordingly, a rising number of incidents involving hazmat transportation may inflict more dread damages to both people and environment. This severe situation has prompted the need for deep mining trip purposes using trajectory information in order to enhance the hazmat-transportation regulatory. This paper presents an unsupervised two-phase framework for inferring multiple trip purposes (i.e. loading, unloading, in-yard, and other stops) based on the passive global positioning system (GPS) data during the hazmat-transportation process. In detail, a scalable ordering points to identify the clustering-structure mixture algorithm (SOMA) is first developed to group hazmat vehicles trip ends into hotspot places in phase I; In phase II, a two-stage trip-purpose identification approach is proposed with a combination of the fuzzy c-means (FCM) method and the point-of-interest (POI) information. The effectiveness and efficiency of the designed two-phase framework are evaluated through the real-world datasets, which are generated by more than 12,000 vehicles in Liaoning Province, China. The results demonstrate that the method can infer four types of freight trip purposes with an accuracy of 82.1%. The proposed approach framework can help analyze the vehicle trips associated with the loading states, which will provide effective decision-making support for the hazmat-transportation regulatory.
Huiying Zhao; Dalin Qian; Ying Lv; Bo Zhang; Rongyu Liang. Development of a global positioning system data-based trip-purpose inference method for hazardous materials transportation management. Journal of Intelligent Transportation Systems 2019, 24, 24 -39.
AMA StyleHuiying Zhao, Dalin Qian, Ying Lv, Bo Zhang, Rongyu Liang. Development of a global positioning system data-based trip-purpose inference method for hazardous materials transportation management. Journal of Intelligent Transportation Systems. 2019; 24 (1):24-39.
Chicago/Turabian StyleHuiying Zhao; Dalin Qian; Ying Lv; Bo Zhang; Rongyu Liang. 2019. "Development of a global positioning system data-based trip-purpose inference method for hazardous materials transportation management." Journal of Intelligent Transportation Systems 24, no. 1: 24-39.
Road transportation is one of the main sources of atmospheric emissions in many countries and areas. Road pricing, is not only effective for urban transportation management, but also helpful in reducing the negative externalities caused by transportation. In this study, an inexact two-phase minimal emission programming (TMEP) model is proposed for design of the environment-friendly toll scheme with an acceptable road network performance. Through introduction of fuzzy stochastic programming, multiple uncertainties involved in vehicle emission evaluation are dealt with; the Traffic Performance Index (TPI) based constraints are incorporated to reflect the decision-maker's requirements for network congestion management. The solution method is proposed for generating the range of fuzzy stochastic objectives. An optimal toll scheme associated with the minimal emission based flow pattern is obtained through searching for a set of the best and the worst optimal solutions. A numerical experiment and a real-world road network in Beijing of China are used to illustrate the application of the developed method. In the case study, the toll scheme is obtained at the desired congestion level. The effects of emission and congestion abatement are analyzed under different policy scenarios. The proposed TMEP method can generate the toll scheme with obvious improvements in total emission reduction and congestion mitigation.
Ying Lv; Shanshan Wang; Ziyou Gao; Xijie Li; Wei Sun. Design of a heuristic environment-friendly road pricing scheme for traffic emission control under uncertainty. Journal of Environmental Management 2019, 236, 455 -465.
AMA StyleYing Lv, Shanshan Wang, Ziyou Gao, Xijie Li, Wei Sun. Design of a heuristic environment-friendly road pricing scheme for traffic emission control under uncertainty. Journal of Environmental Management. 2019; 236 ():455-465.
Chicago/Turabian StyleYing Lv; Shanshan Wang; Ziyou Gao; Xijie Li; Wei Sun. 2019. "Design of a heuristic environment-friendly road pricing scheme for traffic emission control under uncertainty." Journal of Environmental Management 236, no. : 455-465.
This study focuses on an environment-friendly toll design problem, where an acceptable road network performance is promised. First, a Traffic Performance Index (TPI)-based evaluation method is developed to help identify the optimal congestion level and the management target of a transportation system. Second, environment-oriented cordon- and link-based road toll design models are respectively proposed through the use of bi-level programming. Both upper-level submodel objectives are to minimize gross revenue (the total collected toll minus the emissions treatment cost) under different pricing strategies. Both lower-level submodels quantify the user equilibrium (UE) condition under elastic demand. Moreover, the TPI-related constraints for the management requirements of the network performance are incorporated into the bi-level programming modeling framework, which can lead to 0–1 mixed integer bi-level nonlinear programming for toll design problems. Accordingly, a genetic algorithm-based heuristic searching method is proposed for the two pricing models. The proposed cordon- and link-based pricing models were then applied to a real-world road network in Beijing, China. The effects of the toll schemes generated from the two models were compared in terms of emissions reduction and congestion mitigation. In this study, it was indicated that a higher total collected toll may lead to more emissions and related treatment costs. Tradeoffs existed between the toll scheme, emissions reduction, and congestion mitigation.
Xijie Li; Ying Lv; Wei Sun; Li Zhou. Cordon- or Link-Based Pricing: Environment-Oriented Toll Design Models Development and Application. Sustainability 2019, 11, 258 .
AMA StyleXijie Li, Ying Lv, Wei Sun, Li Zhou. Cordon- or Link-Based Pricing: Environment-Oriented Toll Design Models Development and Application. Sustainability. 2019; 11 (1):258.
Chicago/Turabian StyleXijie Li; Ying Lv; Wei Sun; Li Zhou. 2019. "Cordon- or Link-Based Pricing: Environment-Oriented Toll Design Models Development and Application." Sustainability 11, no. 1: 258.
Gongchen Li; Wei Sun; Guohe (Gordon) Huang; Ying Lv; Zhenfang Liu; ChunJiang An. Planning of integrated energy-environment systems under dual interval uncertainties. International Journal of Electrical Power & Energy Systems 2018, 100, 287 -298.
AMA StyleGongchen Li, Wei Sun, Guohe (Gordon) Huang, Ying Lv, Zhenfang Liu, ChunJiang An. Planning of integrated energy-environment systems under dual interval uncertainties. International Journal of Electrical Power & Energy Systems. 2018; 100 ():287-298.
Chicago/Turabian StyleGongchen Li; Wei Sun; Guohe (Gordon) Huang; Ying Lv; Zhenfang Liu; ChunJiang An. 2018. "Planning of integrated energy-environment systems under dual interval uncertainties." International Journal of Electrical Power & Energy Systems 100, no. : 287-298.
Road charging scheme may be required to address both congestion and emission externalities by traffic. In this study, a modeling framework with two phases is proposed, in which the traffic flow distribution of the minimum emissions can be obtained firstly and the charging scheme can be determined accordingly. Considering the complexity for traffic emission evaluation, the emission rates can be presented as fuzzy-random variables, which thus would lead to a set of inexact mixed integer programming models. Moreover, the management target for congestion level control is also incorporated as constraints into the modeling framework. A case study obtained from the real-world road network is used to illustrate the application of the developed method. It is indicated that the optimal road charging scheme can be generated with the minimum total emission under the management requirements. Meanwhile, the effects for congestion control and emission abatement of the proposed road pricing strategy are also discussed.
Xijie Li; Shanshan Wang; Ying Lv; Kailong Zhang. Design of Road Pricing Strategies under Emission Uncertainty. CICTP 2017 2018, 1 .
AMA StyleXijie Li, Shanshan Wang, Ying Lv, Kailong Zhang. Design of Road Pricing Strategies under Emission Uncertainty. CICTP 2017. 2018; ():1.
Chicago/Turabian StyleXijie Li; Shanshan Wang; Ying Lv; Kailong Zhang. 2018. "Design of Road Pricing Strategies under Emission Uncertainty." CICTP 2017 , no. : 1.
Regional energy-environment systems management become more and more focused on greenhouse gas emission control through improving energy efficiency and efficiently managing energy activities. Inexact linear programming models are developed for supporting the management. Due to the weather/climatic variations in the future, electricity demands and renewable power generations (in the right/left hand sides of constraints) have random characteristics. Moreover, an overall satisfactory level needs to be quantified based on multiple chance constraints. Therefore, this study improved upon traditional chance-constrained programming and interval linear programming, and developed an interval joint-probabilistic two-side chance-constrained programming (IJTCP) approach. A sufficient but non-equivalent linearization form of the model was proposed so that the inexact model could be solved through the two-step solution algorithm. The IJTCP was then applied to an integrated energy-environment systems management under dual uncertainties. The application demonstrated that the IJTCP can effectively address the uncertainties presented as not only interval numbers and two-side multi-randomness but also the reliability of satisfying the entire system constraints. The application implicated that the IJTCP approach can be applied to other energy-environment management problems under dual uncertainties.
Gongchen Li; Wei Sun; Ying Lv; Guanhui Cheng; Yumin Chen; Guo H. Huang. Interval joint-probabilistic chance-constrained programming with two-side multi-randomness: an application to energy-environment systems management. Stochastic Environmental Research and Risk Assessment 2017, 32, 2093 -2110.
AMA StyleGongchen Li, Wei Sun, Ying Lv, Guanhui Cheng, Yumin Chen, Guo H. Huang. Interval joint-probabilistic chance-constrained programming with two-side multi-randomness: an application to energy-environment systems management. Stochastic Environmental Research and Risk Assessment. 2017; 32 (7):2093-2110.
Chicago/Turabian StyleGongchen Li; Wei Sun; Ying Lv; Guanhui Cheng; Yumin Chen; Guo H. Huang. 2017. "Interval joint-probabilistic chance-constrained programming with two-side multi-randomness: an application to energy-environment systems management." Stochastic Environmental Research and Risk Assessment 32, no. 7: 2093-2110.
Transportation sector has a critical impact on the energy system and sustainable development. In this study, a stochastic fractional transportation-energy system planning model (SFP-LR) is developed for identification of sustainable system management strategies under uncertainties. Based on a hybrid of stochastic programming and fractional programming techniques, the proposed method can systematically reflect multiple complexities in such a management system. It can not only optimize the transportation energy consumption represented as output/input ratios, but also handle imprecise uncertainties in terms of left-hand-side random variables for examining the reliability of satisfying the constraints. The SFP-LR model is applied to support regional transportation-energy planning for demonstrating effectiveness of the developed approach. The solutions obtained from the SFP-LR approach can provide optimal transportation system planning schemes for regional CO2 emission control towards sustainable management under multiple complexities. It is also indicated that transport structure and management measures have important impacts on transportation energy consumption.
Ying Lv; Shanshan Wang; Ziyou Gao; Wei Sun. Identification of Sustainable Transportation Energy Management Strategies Using a Stochastic Fractional Programming Approach under Uncertainties. CICTP 2015 2015, 3347 -3361.
AMA StyleYing Lv, Shanshan Wang, Ziyou Gao, Wei Sun. Identification of Sustainable Transportation Energy Management Strategies Using a Stochastic Fractional Programming Approach under Uncertainties. CICTP 2015. 2015; ():3347-3361.
Chicago/Turabian StyleYing Lv; Shanshan Wang; Ziyou Gao; Wei Sun. 2015. "Identification of Sustainable Transportation Energy Management Strategies Using a Stochastic Fractional Programming Approach under Uncertainties." CICTP 2015 , no. : 3347-3361.
Emergencies involved in a bus–subway corridor system are associated with many processes and factors with social and economic implications. These processes and factors and their interactions are related to a variety of uncertainties. In this study, an interval chance-constrained integer programming (EICI) method is developed in response to such challenges for bus–subway corridor based evacuation planning. The method couples a chance-constrained programming with an interval integer programming model framework. It can thus deal with interval uncertainties that cannot be quantified with specified probability distribution functions. Meanwhile, it can also reflect stochastic features of traffic flow capacity, and thereby help examine the related violation risk of constraint. The EICI method is applied to a subway incident based evacuation case study. It is solved through an interactive algorithm that does not lead to more complicated intermediate submodels and has a relatively low computational requirement. A number of decision alternatives could be directly generated based on results from the EICI method. It is indicated that the solutions cannot only help decision makers identify desired population evacuation and vehicle dispatch schemes under hybrid uncertainties, but also provide bases for in-depth analyses of tradeoffs among evacuation plans, total evacuation time, and constraint-violation risks.
Y. Lv; X.D. Yan; W. Sun; Z.Y. Gao. A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties. Reliability Engineering & System Safety 2015, 139, 188 -199.
AMA StyleY. Lv, X.D. Yan, W. Sun, Z.Y. Gao. A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties. Reliability Engineering & System Safety. 2015; 139 ():188-199.
Chicago/Turabian StyleY. Lv; X.D. Yan; W. Sun; Z.Y. Gao. 2015. "A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties." Reliability Engineering & System Safety 139, no. : 188-199.
Six new cyanine dye functionalised β-cyclodextrins were designed and synthesized to improve the drawback of the inadequate chromophore in β-cyclodextrin and to be suitable for the study of supramolecular interactions directly by visible spectroscopy. The dye structures were confirmed by 1H NMR, IR, UV–Vis and HRMS. The UV–Vis spectra of the new cyanine dyes in different solvents were investigated. The inclusion behaviour of a quinocyanine derived β-cyclodextrin dye which was used as the supramolecular host with 1-adamantanol or vitamin B6 was investigated. The results indicated that the stoichiometry for the inclusion complex of the quinocyanine derived β-cyclodextrin dye and both 1-adamantanol and vitamin B6 was 1:1, and their inclusion constants were 9.39 × 104 L/mol and 6.14 × 102 L/mol, respectively. The quinocyanine derived β-cyclodextrin dye was also used as the supramolecular host for the analysis of vitamin B6 in tablets with satisfactory results.
Jun-Long Zhao; Ying Lv; Hai-Jing Ren; Wei Sun; Qi Liu; Yi-Le Fu; Lan-Ying Wang. Synthesis, spectral properties of cyanine dyes-β-cyclodextrin and their application as the supramolecular host with spectroscopic probe. Dyes and Pigments 2012, 96, 180 -188.
AMA StyleJun-Long Zhao, Ying Lv, Hai-Jing Ren, Wei Sun, Qi Liu, Yi-Le Fu, Lan-Ying Wang. Synthesis, spectral properties of cyanine dyes-β-cyclodextrin and their application as the supramolecular host with spectroscopic probe. Dyes and Pigments. 2012; 96 (1):180-188.
Chicago/Turabian StyleJun-Long Zhao; Ying Lv; Hai-Jing Ren; Wei Sun; Qi Liu; Yi-Le Fu; Lan-Ying Wang. 2012. "Synthesis, spectral properties of cyanine dyes-β-cyclodextrin and their application as the supramolecular host with spectroscopic probe." Dyes and Pigments 96, no. 1: 180-188.