Primary Air Pollutants Emissions Variation Characteristics and Future Control Strategies for Transportation Sector in Beijing, China

The effects of technological developments in transportation vehicles on air pollution mitigation of metropolitan cities: A case study of Istanbul

This study investigates the impact of transportation vehicles on air pollution emissions in Istanbul, a metropolitan city in Türkiye. The TIMES (The Integrated MARKAL-EFOM System) Model has been used to determine the current level of air pollutants coming from the transportation sector, make future estimates, and assess the impact of various scenarios on air pollution emissions. Air pollutants such as carbon monoxide, nitrogen oxides, sulfur oxides, particulate matter, and non-methane volatile organic compounds are included in the model. The amount of air pollution emissions discussed in this research were 74, 68, 13, 5, and 2 kt for NOx, CO, VOC, SO2, and PM, respectively, in the base year of 2016. In 2055, these emissions have shifted to 190, 98, 26, 8, and 5 kt, respectively. This means that emissions are predicted to increase between 1.4 and 2.6 times. According to model results, individual measures could decrease potential air pollution emissions for 2055 by up to 13 %. When all of the actions done within the pollutants of the study are combined, the total amount of emissions has decreased by 30.2 %, 24.3 %, 18.8 %, 5.3 % and 21.4 % for NOx, CO, VOC, SO2, and PM, respectively. This research emphasizes how critical it is to address metropolitan areas' transportation-related air pollution. The number of such studies dealing with air pollution parameters using the TIMES Model is very few, and it is expected that this study will create important outputs for similar studies.

A Pollution Prevention Pathway Evaluation Methodology Based on Systematic Collaborative Control

To improve the efficiency of air pollution control, in this research, a systematic air pollution collaborative governance pathway system was developed from a systemic perspective. The sequencing of air pollution control pathways in the system can significantly affect its efficiency, so the order of the sequence was optimized. To develop the system, first, two case studies on coordinated air pollution control in the U.S. and China were conducted to demonstrate the importance of systematic collaborative governance. Next, based on the analysis of these two cases and a review of the related literature, a systematic coordinated air pollution control mechanism was proposed. The priorities of collaborative governance pathways were evaluated using the Analytic Hierarchy Process (AHP) methodology. The input to the AHP was data from in-depth interviews with established scholars and practitioners in air pollution prevention and control. Several policy suggestions are put forward based on the expert ranking of the results of the priorities of the collaborative governance pathways. These policy suggestions include identifying the most critical pathways in the cooperative control of air pollution and their order of implementation as well as measures that can effectively reduce pollution. The theoretical contributions of this research include the establishment of a cooperative governance mechanism and the analysis of governance pathways to help develop an efficient air pollution pathway system. The practical contributions of this research include policy suggestions to improve the efficiency of collaborative air pollution treatment and lower its costs.

Urban Air Quality Monitoring in Decarbonization Context; Case Study—Traditional Coal Mining Area, Petroșani, Romania

Humanity is a fossil-fueled civilization with a large influence on the environment. The World Health Organization (WHO) has pointed out that air pollution is now the single biggest environmental threat to human health. The air quality in Petroșani, a traditional mining region from the Jiu Valley bituminous coal basin, Romania, is rarely debated; however, it is not often investigated. In this paper, the main air pollution sources of Petroșani are identified and the performed measurements emphasize the air quality in the area of its transit road. The monitoring program set out the objectives, parameters, and points of the monitoring system, as well as the frequency and duration of the program and other monitoring parameters. The equipment used was provided by the National Institute for Research and Development in Mine Safety and Protection to Explosion from Petroșani, within an institutional partnership with the University of Petroșani. The monitoring of the air quality parameters was conducted from March to July 2020, at six points located on the road that crosses the city. It was thus possible to capture a variety of concentrations of the monitored parameters in different weather conditions to determine the air quality in this area. Based on the variation of the measured values in one of the most important historical Romanian bituminous coal mining basins, the preliminary results suggest a worsening of local air quality parameters in relation to the decarbonization process.

Prediction of Charging Demand of Electric City Buses of Helsinki, Finland by Random Forest

Climate change, global warming, pollution, and energy crisis are the major growing concerns of this era, which have initiated the electrification of transport. The electrification of roadway transport has the potential to drastically reduce pollution and the growing demand for energy and to increase the load demand of the power grid, thereby giving a rise to technological and commercial challenges. Thus, charging load prediction is a crucial and demanding issue for maintaining the security and stability of power systems. During recent years, random forest has gained a lot of popularity as a powerful machine learning technique for classification as well as regression analysis. This work develops a random forest (RF)-based approach for predicting charging demand. The proposed method is validated for the prediction of public e-bus charging demand in the city of Helsinki, Finland. The simulation results demonstrate the effectiveness of our scheme.

Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China

On-road vehicle emissions play a crucial role in affecting air quality and human exposure, particularly in megacities. In the absence of comprehensive traffic monitoring networks with the general lack of intelligent transportation systems (ITSs) and big-data-driven, high-performance-computing (HPC) platforms, it remains challenging to constrain on-road vehicle emissions and capture their hotspots. Here, we established an intelligent modelling and visualization system driven by ITS traffic data for real-world, on-road vehicle emissions. Based on the HPC platform (named “City Brain”) and an agile Web Geographic Information System (WebGISs), this system can map real-time (hourly), hyperfine (10~1000 m) vehicle emissions (e.g., PM2.5, NOx, CO, and HC) and associated traffic states (e.g., vehicle-specific categories and traffic fluxes) over the Xiaoshan District in Hangzhou. Our results show sharp variations in on-road vehicle emissions on small scales, which even fluctuated up to 31.2 times within adjacent road links. Frequent and widespread emission hotspots were also exposed. Over custom spatiotemporal scopes, we virtually investigated and visualized the impacts of traffic control policies on the traffic states and on-road vehicle emissions. Such results have important implications for how traffic control policies should be optimized. Integrating this system with chemical transport models and air quality measurements would bridge the technical gap between air pollutant emissions, concentrations, and human exposure.

The Complexity of Space Utilization and Environmental Pollution Control in the Main Corridor of Makassar City, South Sulawesi, Indonesia

Population mobility, increasing demand for transportation, and the complexity of land use have an impact on environmental quality degradation and air quality pollution. This study aims to analyze (1) the effect of population mobility, increased traffic volume, and land use change on air quality pollution, (2) direct and indirect effects of urban activities, transportation systems, and movement patterns on environmental quality degradation and air pollution index, and (3) air pollution strategy and sustainable urban environmental management. The research method used is a sequential explanation design. Data were obtained through observation, surveys, in-depth interviews, and documentation. The results of the study illustrate that the business center and Daya terminal with a value of 0.18 µgram/m3 is polluted, the power plant and Sermani industrial area with a value of 0.16 µgram/m3 is polluted, the Makassar industrial area with a value of 0.23 is heavily polluted, and the Hasanuddin International Airport area with a value of 0.04 µgram/m3 is not polluted. Population mobility, traffic volume, and land use changes have a significant effect on environmental quality degradation, with a determination coefficient of 94.1%. The direct effect of decreasing environmental quality on the air pollution index is 66.09%. This study recommends transportation management on the main road corridor of Makassar City, which is environmentally friendly with regard to sustainable environmental management.

Evaluation of Two Improved Schemes at Non-Aligned Intersections Affected by a Work Zone with an Entropy Method

The impact of work zones on traffic is a common problem encountered in traffic management. The reconstruction of roads is inevitable, and it is necessary and urgent to reduce the impact of the work zone on the operation of traffic. There are many existing research results on the influence of highway work zones, including management strategies, traffic flow control strategies, and various corresponding model theories. There are also many research results on the impacts of urban road and subway construction on traffic operation, including construction efficiency, economic impact, and travel matrix. However, there are few studies concerning the choice of work zone location, and most previous studies have assumed that the work zone choice was scientific and reasonable. Therefore, it is reasonable to choose the location of the work zone and to assess whether there is room for improvement in the road form of the work zone, but this remains a research gap. Therefore, we studied a seven-lane main road T-intersection in Xi’an, China, and investigated a work zone located at this intersection that caused a road offset, leading to the non-aligned flow of main traffic. We designed two road improvement schemes and multiple transition schemes, used VISSIM software to evaluate the traffic operation of the two schemes, and used the entropy method to choose the suitability of the two schemes under different conditions. According to the results, in the best case, the driving time, delay, and number of stops are reduced by 44%, 66%, and 92%.