Traffic Restrictions Research Articles

Impact of the emergency response to COVID-19 on air quality and its policy implications: Evidence from 290 cities in China

The emergency response to the COVID-19 pandemic had an extreme exogenous impact on society and the economy. This paper aims to explore the impacts of the national emergency response and the subsequent emergency response termination on air quality and its policy implications through regression discontinuity design (RDD) estimation by employing panel data on daily air quality from January 1, 2019, to July 31, 2020, for 290 cities in China. The empirical results showed that the emergency response resulted in a significant decrease in most of the major pollutant concentrations within a short time frame, and the average air quality index (AQI) decreased by approximately 11.0%. The concentrations of PM2.5, PM10, SO2, NO2, and CO decreased by approximately 18.8%, 13.1%, 13.5%, 11.1% and 6.7%, respectively, while the O3 concentration did not change significantly. Further causal analysis found that mandatory traffic restrictions and the shutdown of industries were two important factors that contributed greatly to air quality improvement. Moreover, since the process of returning to normal daily activities and promoting the economy were gradual, the results showed that air pollution did not rebound immediately after the government called for the “resumption of production and work” and announced the “termination of the emergency response”. Our findings suggest that to achieve a substantial and sustainable improvement in air quality, it is necessary to continuously implement strict emission control routines and take co-control measures for various VOCs precursors of ozone.

Is vehicle scrapping affected by low-emission zones? The case of Madrid

This paper provides an initial empirical evaluation of the possible impact a low-emission zone (LEZ) has on vehicle scrappage rates. The analysis is based on a quasi-experimental design, which is applied to the Spanish case known as Madrid Central. Our results, which are quite robust to reasonable changes in the geographic areas used as controls, reveal an excess of scrapping decisions by vehicle owners in the city of Madrid following the implementation of this urban policy. This excess scrapping is transitory and particularly notable for old vehicles subject to major traffic restrictions. The results suggest that establishing a LEZ in a relatively small area can generate some social gains, in terms of transport safety and removal of the vehicles that pollute the most, which may outweigh the simple benefit of improving air quality in the area.

Characteristics of Surface Ozone and Nitrogen Oxides over a Typical City in the Yangtze River Delta, China

The Yangtze River Delta (YRD) is the most developed region in China. Influenced by intensive and complex anthropogenic activities, atmospheric pollution in this region is highly variable, and reports are sparse. In this study, a seven-year history of the atmospheric O3 and NOx mixing ratios over a typical city, Hangzhou, was presented to enrich the studies on air pollution in the YRD region. Our results revealed that the diurnal variation in NOx corresponded to traffic rush hours, while O3 was mainly impacted by photochemical reactions in the daytime. The weekend effect was significant for NOx, but inapparent for O3. Two O3 peaks in May and September were caused by seasonal atmospheric stability and climatic conditions. The lower NOx and higher O3 levels observed suggested direct effects from traffic restrictions and large-scale industrial shutdowns during the COVID-19 lockdown in 2020 compared with those in the periods before and after lockdown. The model simulation results showed that O3 mixing ratios were not only related to regional anthropogenic emissions but were impacted by air mass transportation from surrounding provinces and the China shelf seas. The NOx mixing ratios showed a decreasing trend, while the O3 mixing ratios showed the opposite trend from 2015 to 2021, which is indicative of the implementation of the Air Pollution Prevention and Control Acton Plan issued by the Chinese government in 2013.

Dynamic Cooperation of Transportation and Power Distribution Networks via EV Fast Charging Stations

With the development of electric vehicles, research on the cooperation of transportation networks (TNs) and power distribution networks (PDNs) has become important. Because of practicability, most cooperation research focuses on user equilibrium assignment based on the Wardrop I principle. There is less research focusing on network cooperation involving the system optimal assignment based on Wardrop II. This research paper constructs a cooperation between dynamic system optimal (DSO) and dynamic optimal power flow (DOPF) assignments with multi-objective optimization. Based on Wardrop II, this DSO model realizes multiple origin–destination pairs, multiple tasks, and multiple vehicle types. Electric vehicle and fast charging station models are designed as the connection between both networks. The optimal result gives three scenarios: TN prior, PDN prior, and a compromise of both. DSO minimized the total travel cost and DOPF minimized the total cost of power generation. Several path choices resulted from the scenarios. Whichever scenario is chosen, an electric vehicle is assigned dispersedly for a certain time period to reduce power loss. The optimal solution is also affected by the charging power in fast charging stations. This research can be applied to logistics transportation under traffic restrictions. It offers a dynamic optimization model for transportation and power operators.

A prototype of a micro-scale model for the distribution of NO2 in urban areas

We present a new 2.5D model for predicting the concentration of nitrogen dioxide (NO2) at street level in an urban area. This work develops the first prototype of a tool that should provide fast quantitative answers to help decision-making on the suitability of implementing traffic restrictions during air pollution episodes. The model first solves the wind flow over the city streets ignoring vorticity and turbulence. The obtained velocity field is used to transport the pollutant via a semi-Lagrangian model, combining the particle finite element method of second generation (PFEM2) with the finite element method. A variable absorption term is used to account for the part of the contaminant entering and leaving the calculation plane. The NO2 emissions are estimated from the historical traffic data. The model has been tested during four air pollution episodes in the city of Barcelona (Spain), two in summer and two in winter. A comparison against experimental measurements has been performed at seven different locations throughout the city with promising results.

The carbon neutrality feasibility of worldwide and in China's transportation sector by E-car and renewable energy sources before 2060

Fuel cars are the major contributor with 41 % released emissions, which is about 7.3 billion metric tons (BMt) of CO2 produced in 2020 by the international transportation sector. The most significant polluted regions are U.S.A with 0.731BMt, China with 0.545BMt, and Europe with 0.437BMt of CO2 emissions annually. The four provinces of China named Guangdong, Shandong, Jiangsu, and Henan releases considerable CO2 emissions due to the enormous number of F-cars. This paper discusses the reason of banning F-car, fossil fuel and introduce of E-car and renewable energy as fuel for mitigation of carbon emission in transport sector. Chinese government set the goal and promotion policies for manufacturing companies and consumers for E-car promotion such as tax exemption, innovation technologies for high-range cars, financial support, charging pile construction, free parking, and fewer traffic restriction, etc., are assisting to encourage buyer and help to achieve the target of CO2 reduction by 2060. Consequently, the Li-ion and SSBs batteries are more efficient to use in E-cars and eco-friendly than other battery types. The bottom-up accounting framework analysis reflects the results of all national quick response policies and indicated the mitigation of CO2 emissions from global were decreased from 2.6BMt to 0.006BMt 2010 to 2060, and use of non-renewable energy sources decline from 55 % to 4 % while use of renewable energy sources rises from 42 % to 93 % from 2030 to 2060 due to launching E-cars and devised policies. This research helps to understand the prospects of policies and changes in energy sources to meet the target of CO2 mitigation from transportation sector globally and in China.

GIS-Based Urban Traffic Assessment in a Historical European City under the Influence of Infrastructure Works and COVID-19

Urban areas have developed organically over time, driven by the economic success of cities. However, this development has usually been accompanied by the side effects of urbanization, such as increased traffic and its associated problems: traffic congestion, increased accident rates and pollution. As urban populations grow and expand, the importance of GIS lies in its ability to collect a large amount of geospatial data, including human-generated data. This data is necessary to understand the complexity of the city, set priorities, solve complicated planning problems and perform a variety of spatial analysis, which shows not only the feasibility but also the consistency of the proposed infrastructure with the requirements of a sustainable city. In this paper, we demonstrate the benefits of integrating real-time traffic data with GIS technology and remote sensing data for analyzing the impact of infrastructure works and COVID-19 on traffic in Oradea, Romania. The case study was focused on the historical center of Oradea and was based on remote sensing data collected before, during, and after traffic restrictions. The study also shows the need for using GIS and crowdsourcing-based applications in traffic analysis and planning.

Cooperative Truck–Drone Delivery Path Optimization under Urban Traffic Restriction

In the traditional express delivery sector, trucks are the most available and efficient transportation mode in urban areas. However, due to the pressures of traffic congestion and air pollution problems, many cities have implemented strict measures to restrict trucks’ access to many zones during specified time periods, which has caused significant effects on the business of the industry. Due to their advantages, which include high speed, flexibility, and environmental friendliness, drones have great potential for being combined with trucks for efficient delivery in restricted traffic zones. In this paper, we propose a cooperative truck and drone delivery path optimization problem, in which a truck carrying cargo travels along the outer boundary of the restricted traffic zone to send and receive a drone, and the drone is responsible for delivering the cargo to customers. The objective of the problem is to minimize the completion time of all delivery tasks. To efficiently solve this problem, we propose a hybrid metaheuristic optimization algorithm to cooperatively optimize the outer path of the truck and the inner path of the drone. We conduct experiments on a set of test instances; the results demonstrate that the proposed algorithm exhibits a competitive performance compared to other selected popular optimization algorithms.

The Unignorable Near-ground PM2.5, UFP, PAHs, and BC Levels around a Traffic Prohibited Night Market

In some special densely populated areas, the background atmospheric fine particulate matter (PM2.5) concentration is very high, which makes near-ground (NG) exposure a major problem endangering human health. In our study, the night market in Chiayi City was selected as the research object and collected the 24-hour PM2.5 samples through the federal reference method (FRM), characterizing the mass concentration, water-soluble ionic components, carbon specious, metal compositions and source contributions of PM2.5. To better analyze the contribution of traffic sources under different sampling conditions, the mobile real-time monitoring system was used to analyze the quality of NG-PM2.5, the number of ultra-fine particles (UFP), the concentration of black carbon (BC) and total polycyclic aromatic hydrocarbons (PAH) before and after the traffic restriction. Results indicated the concentration of PM2.5 was 7.26–58.6 mg m-3. In chemical analysis, secondary contents e.g., carbonaceous and ionic components accounted for ~60% of the PM2.5, supporting the importance of long-range transport. However, the traffic contribution accounted for ~30% and hardly changed between different samples, which was not conducive to source apportionment. Through traffic restriction, it was found that all kinds of pollutants increased significantly before restriction, and even after restriction, the concentrations of PM2.5 and BC increased 131% and 151% in low concentration season. In the high concentration season, the traffic restriction significantly reduced the NG-UFP and NG-PAH concentration by 27% and 55%, respectively, but NG-BC and NG-PM2.5 was almost unaffected. Therefore, besides the contribution of traffic source, emissions from cooking activities are very important for the increase of NG-PM2.5 levels in the night market area.

Impacts of Sandstorms on Chemistries of Ambient PAHs in a Small City in North China

Sandstorm events frequently perplex northern China, addressing the people's concern due to subsequent increases in the toxicity and carcinogenicity of PM2.5-bound PAHs (PB-PAHs) in receptor area of sand dust. Here, we enacted a field campaign in a small city between Beijing and Baoding in spring of 2021 covering the sandstorm period (SSP) and non-sandstorm period (NSSP) to examine the sandstorm impacts on chemistries of PB-PAHs. SSP exhibited a slightly high average PAH concentrations of 10.3 ng m–3 than 9.16 ng m–3 in the NSSP. At the same time, the average PM2.5 concentrations obviously increased from 60.7 μg m–3 to 75.2 μg m–3. Positive matrix factorization (PMF) analysis manifested that sandstorm largely enhanced the oil leakage and combustion (OLC) fractions from 18.0% in the NSSP to 34.4% in the SSP. Potential source contribution function (PSCF) indicated that OLC partly came from sandstorm origin area–Inner Mongolia. Low diagnostic ratios of FA / (FA + PY) in the SSP also indicated OLC was more important. Accordingly, the largest contributor of incremental lifetime cancer risks (ILCRs) changed from vehicle exhaust (VE) (36.2%) in the NSSP to OLC (34.4%) in the SSP. VE and industrial emission (IE) contributions decreased obviously due to emission control and traffic limitation in the SSP. Coal burning (CB) still held a high contribution to PAHs regardless of the implementation of “coal to gas” law in the sampling area. In addition, sandstorms increased the levels of high molecular weight PAHs (HMW-PAHs) with high toxicity by 4.07%. ILCRs for adults and children increased from 3.90 × 10–7 to 4.74 × 10–7 and from 2.41 × 10–7 to 2.93 × 10–7, respectively, in the SSP, which should be more concerned.

A socioeconomic analysis for a green traffic restrictions scheme in Athens

The objective of this paper is the appraise of the socioeconomic impacts until 2035 of a proposed annual charging policy called Green Car Access Card (GCAC) for the daily access of a passenger car in the city center of Athens, Greece with the charging being adjusted according to the Euro class. A questionnaire survey was conducted using stated preference while a binary logistic model was developed to determine the acceptability of GCAC. A socioeconomic analysis was developed to quantify the impact on traffic, road safety, and air pollution until 2035 due to GCAC implementation. For the “Do Nothing” and the “GCAC” Scenarios the road casualties, the travel time, the fuel consumption and the emissions from motorized transport are estimated and expressed in monetary units. Results indicate a positive NPV which proves that the proposed investment provides a significant benefit to society.

A critical assessment of Athens Traffic Restrictions using multiple data sources

This paper presents a critical assessment of Athens Traffic Restrictions (ATR) by analyzing data on traffic volumes and speeds from the Traffic Management Centre of Athens, as well as ticket validations from Athens public transport operator (OASA S.A.). ATR were reinstated on 24/10/2021 as a response to increasing congestion. The analysis showed an increase in average speeds and reduction in congestion inside ATR. Outside ATR, no conclusive evidence was found supporting a persistent impact of the measure on traffic. The reinstatement of ATR contributed to the increase in metro ridership. Transport and local authorities should set clear goals and KPIs to monitor the success of the measure in the long term. Enhancing the implementation of ATR with micromobility options and MaaS solutions inside the restricted area can further boost compliance and strengthen the uptake of public transport.

Estimating long-term and short-term impact of COVID-19 activity restriction on regional highway traffic demand: A case study in Zhejiang Province, China

Since the outbreak of COVID-19 in China in late 2019, government administrators have implemented traffic restriction policies to prevent the spread of COVID-19. However, highway traffic volumes obtained from ETC data in some provinces did not return to the levels of previous years after the end of the traffic restriction policy, suggesting that traffic restriction policy may have long-term effects. This paper proposed a method that analyzes traffic restriction policies' long-term and short-term impact on highway traffic volume under COVID-19. This method first analyzes the long-term and short-term impacts of traffic restriction policies on the highway traffic volume using the Prophet model combined with the concept of traffic volume loss. It further investigates the relationship between COVID-19 cases and the long-term and short-term impacts of the traffic restriction policy using Granger causality and the impulse response function of the Bayesian vector autoregressive (BVAR) model. The results showed that during the COVID-19 pandemic, highway traffic in Zhejiang Province decreased by about 95.5%, and the short-term impact of COVID-19 cases was most pronounced on the second day. However, the long-term effects were relatively small when the traffic restriction policy ended and was verified by data from other provinces. These results will provide decision support for traffic management and provide recommendations for future traffic impact assessments in the event of similar epidemics.

Adaptive Data Transmission Algorithm for the System of Inertial Sensors for Hand Movement Acquisition.

Modern systems of intelligent sensors commonly use radio data transmission. Hand movement acquisition with the use of inertial sensors requires the processing and transmission of a relatively large amount of data, which may be associated with a significant load on the network structure. Network traffic limitation, without losing the quality of monitoring parameters from the sensor system, is therefore important for the functioning of the radio network which integrates both the teletransmission sensor system and the data acquisition server. The paper presents a wearable solution for hand movement acquisition, which uses data transmission in the Wi-Fi standard and contains 16 MEMS (Micro Electro Mechanical System) sensors. An adaptive algorithm to control radio data transmission for the sensor system has been proposed. The algorithm implemented in the embedded system controls the change of the frame length, the length of the transmission frame and the frequency of its sending, which reduces the load on the network router. The use of the algorithm makes it possible to reduce the power consumption by the sensor system by up to 19.9% and to limit the number of data transferred by up to about 91.6%, without losing the quality of the monitored signal. The data analysis showed no statistically significant differences (p > 0.05) between the signal reconstructed from the complete data and processed by the algorithm.

To what extent the traffic restriction policies can improve its air quality? An inspiration from COVID-19.

The online version contains supplementary material available at 10.1007/s00477-022-02351-7.

A Scheme to Improve Network Performance Based on Traffic Restriction and Pricing in the Presence of Carpooling

For the purpose of optimizing the traffic network in the presence of carpooling, a traffic demand management scheme was proposed with the consideration of traffic restriction, carpooling, and road pricing. We establish a variational inequality describing the travelers’ mode and route choice following the logit mode split and multimodal user equilibrium principle in the condition of elastic demand. A bilevel programming was designed with the variational inequality as the lower level and optimization objective function taking into account traffic congestion and social welfare as the upper level. The results show that this scheme is possible to be effective in improving network performance. The higher average occupancy of carpooling vehicles and the carpooling demand may not bring better network performance due to the topology, parameters of the network, and travel demand. The fare of carpooling travelers is possible to impact the network very slightly with this scheme. Besides, the group of travelers who is able to afford more than one vehicle is hardly affected by this scheme.

Impacts of COVID-19 Lockdown on Traffic Flow, Active Travel and Gaseous Pollutant Concentrations; Implications for Future Emissions Control Measures in Oxford, UK

The COVID-19 lockdown provided a unique opportunity to test the impacts of changes in travel patterns on air quality and the environment. Therefore, this study provides insights into the impacts of COVID-19 emergency public health “lockdown” measures upon traffic flow, active travel and gaseous pollutant concentrations (NO, NO2 and O3) in Oxford city centre during 2020 using time-series analysis and linear regression methods. Comparisons of traffic counts indicated pronounced changes in traffic volume associated with national lockdown periods. Car volume reduced by 77.5% (statistically significant) during the first national lockdown, with lesser changes in goods vehicles and public transport (bus) activity during the second lockdown. Cycle flow reduced substantively during the first lockdown only. These changes resulted in a reduction in nitric oxide (NO) and nitrogen dioxide (NO2) concentrations of 75.1% and 47.4%, respectively, at roadside, and 71.8% and 34.1% at urban background during the first lockdown period. In contrast ozone (O3) concentrations increased at the urban background site by 22.3% during the first lockdown period, with no significant changes in gaseous concentrations during the second lockdown at either roadside or urban background location. The diurnal pattern of peak mean NO and NO2 concentrations reduced in magnitude and was shifted approximately 2 h earlier in the morning and 2 h later in the evening (roadside) and 3 h earlier in the morning and 3 h later in the evening (urban background). Our findings provide an example of how gaseous air quality in urban environments could respond to future urban traffic restrictions, suggesting benefits from reductions in peak and daily NO2 exposures may be offset by health harms arising from increases in ground level O3 concentrations in the summer months.

Evaluation of low traffic neighbourhood (LTN) impacts on NO2 and traffic

• Generalised difference in differences is used to examine effects of LTN. • LTNs reduced NO 2 both within intervention areas (5.7%) and in boundary areas (8.9%) • Traffic volumes were reduced by 58.2% within LTNs and by 13.4% at LTN boundary sites. Traffic restriction measures may create safer and healthier places for community members but may also displace traffic and air pollution to surrounding streets. Effective urban planning depends on understanding the magnitude of changes resulting from policy measures, both within and surrounding intervention areas; these are largely unstudied in the case of Low traffic Neighbourhoods (LTN). We evaluated impacts of three LTNs in the London Borough of Islington, UK, on air pollution and traffic flows in and around intervention areas, based on monthly Nitrogen Dioxide (NO 2 ) and traffic volume data provided by the local authority. We identified pre- and post-intervention monitoring periods and intervention, boundary and control sites. We then adapted the generalised difference in differences approach to evaluate the effects within LTNs and at their boundary. We found that LTNs have the potential to substantially reduce air pollution and traffic in target areas, without increasing air pollution or traffic volumes in surrounding streets. These results provide sound arguments in favour of LTNs to promote health and wellbeing in urban communities.

Особенности проведения медицинской эвакуации пациентов в условиях временного ограничения на федеральном уровне полетов гражданской авиации, в том числе из-за рубежа

Summary. The aim of the study is to analyze and to substantiate alternative ways of solving problematic issues of medical evacuation of patients and casualties in conditions of temporary restriction of civil aviation flights. Materials and research methods. Materials of the study: practical experience of the specialists of the Center of sanitary aviation and emergency medical care of “Zashchita” Disaster Medicine Center of Federal Medical Biophysical Center named after A.I.Burnazyan of the Federal Medical and Biological Agency of Russia, as well as LLC “Medaero-Service”; statistical data on the field work of teams of the Center of sanitary aviation and emergency medical care on medical evacuation of patients from closed airspace areas; data from the official websites of the Federal Air Transport Agency, of Government and Ministry of Foreign Affairs of the Russian Federation, of Border Service, of Federal Tourism Agency, and assistance companies; electronic database of regulatory legal documents. Research methods: analytical, method of direct observation, comparison, description. Results of the study and their analysis. Results of the study, characterizing the problematic issues of medical evacuation of patients and victims in conditions of temporary restriction of civil aviation flights regime, are presented. The main ways of optimization of medical evacuation of patients and victims at the federal level during the period of air traffic limitation have been suggested and substantiated.

Optimization Modeling of Urban Freight Transportation Network by Using a Metaheuristic Approach, Genetic Local Search Procedure

Creating a transportation network that reduces the cost of urban freight is highly challenging. Freight route is determined by the amount of congestion generated by the vehicle type. Furthermore, it must compete with other users to locate the optimal path for their traffic on the city's restricted road network infrastructure system. Freight network routing begins with identifying and determining the optimum route. The freight network is optimized by introducing a heavy traffic restriction mechanism in metropolitan areas, and an attempt is made to propose a set of routes as a set of freight traffic modes. The primary goal of freight routing in this research is making a freight network model optimization to find a set of freight routing by optimizing (efficiency) trip prices due to limited road infrastructure and the difficulties of constructing road infrastructure in metropolitan areas. Therefore, selecting a group of routes as the journey of the commodities is a realistic alternative to minimizing costs. The problem of route selection is one of combinatorial optimization. The challenge is to narrow the pool of action options to a set of recommended actions. Due to vehicle characteristics and traffic flow, route selection carefully considers vehicle behavior. A two-level mathematical model that was created by formulating route options served as the framework for the research. The combination of chosen routes is maximized using a genetic algorithm such as a Genetic Local Search. The model is examined via its application to a fictitious network. The result converges to the target value of 246,311.9 IDR. It shows that the model satisfies the convergence condition of producing in 0.76 seconds. As a result, a model with a genetic local search technique that can search more effectively in the city's freight network's ideal path is created. The GLS combinatorial optimization model shows us it could find the best set of urban freight networks with the best performance. This is consistent with Yamada et al. GLS methods perform well in solving combinatorial problems.