Journal articles on the topic 'URBAN TRAFFIC EMISSION'
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Wang, Haiwei, Huiying Wen, Feng You, Jianmin Xu, and Hailin Kui. "Motor Vehicle Emission Modeling and Software Simulation Computing for Roundabout in Urban City." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/312396.
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In urban road traffic systems, roundabout is considered as one of the core traffic bottlenecks, which are also a core impact of vehicle emission and city environment. In this paper, we proposed a transport control and management method for solving traffic jam and reducing emission in roundabout. The platform of motor vehicle testing system and VSP-based emission model was established firstly. By using the topology chart of the roundabout and microsimulation software, we calculated the instantaneous emission rates of different vehicle and total vehicle emissions. We argued that Integration-Model, combing traffic simulation and vehicle emission, can be performed to calculate the instantaneous emission rates of different vehicle and total vehicle emissions at the roundabout. By contrasting the exhaust emissions result between no signal control and signal control in this area at the rush hour, it draws a conclusion that setting the optimizing signal control can effectively reduce the regional vehicle emission. The proposed approach has been submitted to a simulation and experiment that involved an environmental assessment in Satellite Square, a roundabout in medium city located in China. It has been verified that setting signal control with knowledge engineering and Integration-Model is a practical way for solving the traffic jams and environmental pollution.
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Šarić, Ammar, Suada Sulejmanović, Sanjin Albinović, Mirza Pozder, and Žanesa Ljevo. "The Role of Intersection Geometry in Urban Air Pollution Management." Sustainability 15, no. 6 (March 15, 2023): 5234. http://dx.doi.org/10.3390/su15065234.
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Air pollution represents one of the most complex problems of humanity. Traffic contributes significantly to this by emitting large amounts of harmful gases. This problem is particularly pronounced at urban intersections due to frequent changes in vehicle movement dynamics. This paper primarily presents the influence of intersection geometry on pollutant emissions levels. In addition, the influence of various traffic policies promoting greater use of public transport and zero-emission vehicles is also examined. The research combines the field part of recording existing intersections in Sarajevo, Bosnia and Herzegovina with traffic microsimulation. Detailed data on vehicles’ movements were obtained by advanced video processing using the DataFromSky tool, while the PTV Vissim 2022 and Bosch ESTM (2022) software were used to simulate traffic and estimate emissions at geometrically different intersections. The results showed that, in saturated traffic conditions, signalized intersections cause up to 50% lower emissions compared with two-lane and turbo roundabouts and that the impact of the geometric change is more significant than the impact of zero-emission vehicles. In unsaturated conditions, the differences in emissions at different intersections are negligible, with the highest reductions in pollution achieved by using zero-emission vehicles.
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Jiang, Linhui, Yan Xia, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, et al. "Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system." Atmospheric Chemistry and Physics 21, no. 22 (November 23, 2021): 16985–7002. http://dx.doi.org/10.5194/acp-21-16985-2021.
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Abstract. Urban on-road vehicle emissions affect air quality and human health locally and globally. Given uneven sources, they typically exhibit distinct spatial heterogeneity, varying sharply over short distances (10 m–1 km). However, all-around observational constraints on the emission sources are limited in much of the world. Consequently, traditional emission inventories lack the spatial resolution that can characterize the on-road vehicle emission hotspots. Here we establish a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current emission inventories. We interconnect all-around traffic monitoring (including traffic fluxes, vehicle-specific categories, and speeds) via an intelligent transportation system (ITS) over Xiaoshan District in the Yangtze River Delta (YRD) region. This enables us to calculate single-vehicle-specific emissions over each fine-scale (10 m–1 km) road segment. Thus, the most hyperfine emission dataset of its type is achieved, and on-road emission hotspots appear. The resulting map shows that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74.01, 40.35, 8.13, and 1.68 kg, respectively. More importantly, widespread and persistent emission hotspots emerged. They are of significantly sharp small-scale variability, up to 8–15 times within individual hotspots, attributable to distinct traffic fluxes, road conditions, and vehicle categories. On this basis, we investigate the effectiveness of routine traffic control strategies on on-road vehicle emission mitigation. Our results have important implications for how the strategies should be designed and optimized. Integrating our traffic-monitoring-based approach with urban air quality measurements, we could address major data gaps between urban air pollutant emissions and concentrations.
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Csikós, Alfréd, Tamás Tettamanti, and István Varga. "MACROSCOPIC MODELING AND CONTROL OF EMISSION IN URBAN ROAD TRAFFIC NETWORKS." TRANSPORT 30, no. 2 (May 30, 2015): 152–61. http://dx.doi.org/10.3846/16484142.2015.1046137.
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This work suggests a framework for modeling the traffic emissions in urban road traffic networks that are described by the Network Fundamental Diagram (NFD) concept. Traffic emission is formalized in finite spatiotemporal windows as a function of aggregated traffic variables, i.e. Total Travel Distances (TTDs) in the network and network average speed. The framework is extended for the size of an urban network during a signal cycle – the size of a window in which the network aggregated parameters are modeled in the NFD concept. Simulations have been carried out for model accuracy analysis, using the microscopic Versit+Micro model as reference. By applying the macroscopic emission model function and the traffic modeling relationships, the control objective for pollution reduction has also been formalized. Basically, multi-criteria control design has been introduced for two criteria: maximization of the TTD and minimization of traffic emissions within the network.
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Alexandrino, Katiuska, Nazly E. Sánchez, Rasa Zalakeviciute, Wilber Acuña, and Fausto Viteri. "Polycyclic Aromatic Hydrocarbons in Araucaria heterophylla Needles in Urban Areas: Evaluation of Sources and Road Characteristics." Plants 11, no. 15 (July 27, 2022): 1948. http://dx.doi.org/10.3390/plants11151948.
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Araucaria heterophylla needles were collected in urban areas of the city of Quito, Ecuador, to analyze the relationship between the concentration of polycyclic aromatic hydrocarbons (PAHs) with different emission sources and road characteristics. The PAHs were analyzed by high-performance liquid chromatography (HPLC) and included naphthalene (Naph), benzo[a]anthracene (BaA), chrysene (Chry), and benzo[a]pyrene (BaP), which are related to the sources considered in this work. The results indicated that some streets with moderate and low traffic intensity had higher total concentrations of PAHs than streets with high traffic intensity, showing the importance of non-traffic related emission sources and road characteristics on PAH emissions. All the studied PAHs were associated with traffic emissions, although Naph and BaP were more associated with acceleration and braking activities, while BaA and Chry also seemed to come from restaurant emissions. The presence of gas stations was also important in the emission of PAHs. Road capacity seems to have a higher effect on pollutant emission than road gradient and urban forms. The outcomes of this study are expected to facilitate the diagnostics of the concentration of PAHs in urban areas, which contribute to the design of strategies for the mitigation of pollution by PAHs in urban environment.
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Bebkiewicz, Katarzyna, Zdzisław Chłopek, Hubert Sar, Krystian Szczepański, and Magdalena Zimakowska-Laskowska. "Assessment of impact of vehicle traffic conditions: urban, rural and highway, on the results of pollutant emissions inventory." Archives of Transport 60, no. 4 (December 31, 2021): 57–69. http://dx.doi.org/10.5604/01.3001.0015.5477.
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The use of motor vehicles varies considerably under distinct traffic conditions: in cities, outside cities as well as on motorways and expressways. The impact of road traffic on the natural environment has been studied for many years, including in terms of the nature of the operation of motor vehicles. This problem is particularly important in highly urbanized areas, where traffic congestion is the source of increased emissions of harmful compounds contained in exhaust gases. For this reason, many cities have traffic restrictions, especially for those cars that do not meet the most stringent emission standards. Environmental protection is the driving force behind the development of modern combustion engine supply systems, which allow for proper control of the combustion of petroleum-derived fuels. The exhaust gas cleaning systems in the form of catalytic converters or particulate matter filters are also playing a very important role. Considerable differences in internal combustion engine operating states, both static and dynamic, result in important differences in pollutant emissions. Likewise, the national annual pollutant emission is affected by the share of distances travelled by vehicles under various traffic conditions. At the same time, it is very difficult to estimate exhaust emissions from road transport sources. Very interesting method of emission estimation is the application of the data included in the emission inventory which are a valuable source of information on exhaust emissions under various operating conditions. In the present study, the annual pollutant emissions were analyzed: at a national level (total pollutant emission) and in distinct traffic conditions. There were found large differences between individual pollutants’ shares in the emissions from vehicles under the tested traffic conditions. This is particularly evident for nitrogen oxides with the highest emission share outside cities, as opposed to other substances with the highest emission shares in cities, where traffic congestion is taking place.
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Wang, Peng, Ruhan Zhang, Shida Sun, Meng Gao, Bo Zheng, Dan Zhang, Yanli Zhang, Gregory R. Carmichael, and Hongliang Zhang. "Aggravated air pollution and health burden due to traffic congestion in urban China." Atmospheric Chemistry and Physics 23, no. 5 (March 7, 2023): 2983–96. http://dx.doi.org/10.5194/acp-23-2983-2023.
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Abstract. Vehicle emissions are regarded as a primary contributor to air pollution and related adverse health impacts. Heavy traffic congestion increases traffic flow and thus produces more O3 precursor emissions, leading to more adverse air quality issues. Although the development of a vehicle emission inventory has received great concern and continuous efforts, limitations still exist. For example, real-time diurnal variations and increases in emission rates due to traffic congestion are not well understood. In this study, we developed a new temporal allocation approach in transportation emissions to investigate the impact on air quality and health burden due to traffic congestion in China in 2020. Both real-time congestion-level data and emission correction factors were considered in the approach. Results show that traffic congestion aggravates air pollution and health burden across China, especially in the urban clusters such as the North China Plain and Sichuan Basin. In these regions, the average annual increases in fine particulate matter (PM2.5) and ozone (O3) could be up to 3.5 µg m−3 and 1.1 ppb, respectively. The excess PM2.5 and O3 attributed to the traffic congestion also induce an additional 20 000 and 5000 premature deaths in China, respectively. In major cities, the increased rate of premature mortality caused by traffic congestion may reach 17.5 %. Therefore, more effective and comprehensive vehicle emission control policies or better planning of the road network should be established to reduce traffic congestion and improve air quality in China.
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Bendtsen, Hans, and Lone Reiff. "An urban road traffic emission model." International Journal of Vehicle Design 20, no. 1/2/3/4 (1998): 192. http://dx.doi.org/10.1504/ijvd.1998.001813.
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Liu, Tao, Jia Sun, Baihua Liu, Miao Li, Yingbin Deng, Wenlong Jing, and Ji Yang. "Factors Influencing O3 Concentration in Traffic and Urban Environments: A Case Study of Guangzhou City." International Journal of Environmental Research and Public Health 19, no. 19 (October 10, 2022): 12961. http://dx.doi.org/10.3390/ijerph191912961.
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Ozone (O3) pollution is a serious issue in China, posing a significant threat to people’s health. Traffic emissions are the main pollutant source in urban areas. NOX and volatile organic compounds (VOCs) from traffic emissions are the main precursors of O3. Thus, it is crucial to investigate the relationship between traffic conditions and O3 pollution. This study focused on the potential relationship between O3 concentration and traffic conditions at a roadside and urban background in Guangzhou, one of the largest cities in China. The results demonstrated that no significant difference in the O3 concentration was observed between roadside and urban background environments. However, the O3 concentration was 2 to 3 times higher on sunny days (above 90 μg/m3) than on cloudy days due to meteorological conditions. The results confirmed that limiting traffic emissions may increase O3 concentrations in Guangzhou. Therefore, the focus should be on industrial, energy, and transportation emission mitigation and the influence of meteorological conditions to minimize O3 pollution. The results in this study provide some theoretical basis for mitigation emission policies in China.
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Wu, Luolin, Ming Chang, Xuemei Wang, Jian Hang, Jinpu Zhang, Liqing Wu, and Min Shao. "Development of the Real-time On-road Emission (ROE v1.0) model for street-scale air quality modeling based on dynamic traffic big data." Geoscientific Model Development 13, no. 1 (January 3, 2020): 23–40. http://dx.doi.org/10.5194/gmd-13-23-2020.
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Abstract. Rapid urbanization in China has led to heavy traffic flows in street networks within cities, especially in eastern China, the economically developed region. This has increased the risk of exposure to vehicle-related pollutants. To evaluate the impact of vehicle emissions and provide an on-road emission inventory with higher spatiotemporal resolution for street-network air quality models, in this study, we developed the Real-time On-road Emission (ROE v1.0) model to calculate street-scale on-road hot emissions by using real-time big data for traffic provided by the Gaode Map navigation application. This Python-based model obtains street-scale traffic data from the map application programming interface (API), which are open-access and updated every minute for each road segment. The results of application of the model to Guangzhou, one of the three major cities in China, showed on-road vehicle emissions of carbon monoxide (CO), nitrogen oxide (NOx), hydrocarbons (HCs), PM2.5, and PM10 to be 35.22×104, 12.05×104, 4.10×104, 0.49×104, and 0.55×104 Mg yr−1, respectively. The spatial distribution reveals that the emission hotspots are located in some highway-intensive areas and suburban town centers. Emission contribution shows that the dominant contributors are light-duty vehicles (LDVs) and heavy-duty vehicles (HDVs) in urban areas and LDVs and heavy-duty trucks (HDTs) in suburban areas, indicating that the traffic control policies regarding trucks in urban areas are effective. In this study, the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) was applied to investigate the impact of traffic volume change on street-scale photochemistry in the urban areas by using the on-road emission results from the ROE model. The modeling results indicate that the daytime NOx concentrations on national holidays are 26.5 % and 9.1 % lower than those on normal weekdays and normal weekends, respectively. Conversely, the national holiday O3 concentrations exceed normal weekday and normal weekend amounts by 13.9 % and 10.6 %, respectively, owing to changes in the ratio of emission of volatile organic compounds (VOCs) and NOx. Thus, not only the on-road emissions but also other emissions should be controlled in order to improve the air quality in Guangzhou. More significantly, the newly developed ROE model may provide promising and effective methodologies for analyzing real-time street-level traffic emissions and high-resolution air quality assessment for more typical cities or urban districts.
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Tchepel, Oxana, Daniela Dias, Joana Ferreira, Richard Tavares, Ana Isabel Miranda, and Carlos Borrego. "EMISSION MODELLING OF HAZARDOUS AIR POLLUTANTS FROM ROAD TRANSPORT AT URBAN SCALE." TRANSPORT 27, no. 3 (September 19, 2012): 299–306. http://dx.doi.org/10.3846/16484142.2012.720277.
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This study is focused on the development of a modelling approach to quantify emissions of traffic-related hazardous air pollutants in urban areas considering complex road network and detailed data on transport activity. In this work a new version of the Transport Emission Model for line sources has been developed for hazardous pollutants (TREM-HAP). Emission factors for benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein, naphthalene and also particulate matter (PM2.5) were implemented and the model was extended to integrate a probabilistic approach for the uncertainty quantification using Monte-Carlo technique. The methodology has been applied to estimate road traffic emissions in Porto Urban Area, Portugal. Hourly traffic counts provided by an automatic counting system were used to characterise the spatial and temporal variability of the number of vehicles, vehicle categories and average speed at different road segments. The data for two summer and two winter months were processed to obtain probability density functions of the input parameters required for the uncertainty analysis. For quantification of cold start excess emissions, Origin-Destination matrix for daily trips was used as additional input information. Daily emissions of hazardous air pollutants from road traffic were analysed for the study area. The uncertainty of the emission estimates related to the transport activity factors range from as small as −2 to +1.7% for acrolein and acetaldehyde on highways, to as large as −33 to +70% for 1,3-butadiene considering urban street driving. An important contribution of cold start emissions to the total daily values was estimated thus achieving 45% in case of benzene. The uncertainty in transport activity data on resulting urban emission inventory highlights the most important parameter and reveals different sensitivity of the emission quantification to the input data. The methodology presented in this work allows the development of emission inventories for hazardous air pollutants with high spatial and temporal resolution in complex urban areas required for air quality modelling and exposure studies and could be used as a decision support tool.
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Yang, Daoyuan, Shaojun Zhang, Tianlin Niu, Yunjie Wang, Honglei Xu, K. Max Zhang, and Ye Wu. "High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets." Atmospheric Chemistry and Physics 19, no. 13 (July 11, 2019): 8831–43. http://dx.doi.org/10.5194/acp-19-8831-2019.
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Abstract. On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16 400 km2). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides (NOx), fine particulate matter (PM2.5) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29 % and 38 % of estimated total on-road emissions of NOx and PM2.5, which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir®, to simulate vehicular NOx concentrations at fine resolutions (10 m × 10 m in the entire municipality and 1 m × 1 m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10 µg m−3 of NOx in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.
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Chen, Jiaguo, Xueyang Dai, Tao Zhou, and Qinmei Sun. "Analysis of Motor Vehicle Exhaust Emission Characteristics based on PEMS in Mountain Cities." Frontiers in Sustainable Development 3, no. 7 (July 22, 2023): 11–25. http://dx.doi.org/10.54691/fsd.v3i7.5326.
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Taking a gasoline vehicle in Chongqing as the research object, PEMS testing technology was used to study the exhaust emission characteristics of motor vehicles during driving on roads in the central urban area of Chongqing. The focus was on analyzing the data situation and emission rates of different mountain scenes, and analyzing the carbon emission characteristics of road traffic in Chongqing. Through the analysis and comparison of data, it is shown that in terms of the carbon emissions characteristics of road traffic in Chongqing, through long-term measurement data analysis of comprehensive road conditions in the central urban area of Chongqing, it is found that compared with the general emissions of common small vehicles (100-150 kg/km), the comprehensive carbon emissions of road traffic in Chongqing are significantly higher. This also indicates to some extent that the carbon emissions of road conditions in mountainous cities are higher than those in plain cities.
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Li, Tao, Baoli Gong, Yong Peng, Jin Nie, Zheng Wang, Yiqi Chen, Guoquan Xie, Kui Wang, and Honghao Zhang. "Analysis and Comparative Study of Signalized and Unsignalized Intersection Operations and Energy-Emission Characteristics Based on Real Vehicle Data." Energies 16, no. 17 (August 28, 2023): 6235. http://dx.doi.org/10.3390/en16176235.
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With the development of the economy, urban road transportation has been continuously improved, and the number of motor vehicles has also increased significantly, leading to serious energy consumption issues. As critical nodes in the urban road transportation network, intersections have become a focal point of research on vehicle energy consumption. To investigate whether traffic signal lights affect fuel consumption and emissions, this study analyzed the operating characteristics, fuel consumption, and emissions of intersections with and without traffic signal lights using real-world vehicle data. The data from the INTERACTION dataset for both signalized intersection VA and unsignalized intersection MA are used in the study, with a time duration of 3200 s. The VT-micro energy consumption and emissions model was applied to calculate and comprehensively analyze the vehicle flow, fuel consumption, and emissions. Additionally, the study compared the fuel consumption and emissions for different driving scenarios, including straight through, left turn, right turn, and U-turn, within a single traffic signal cycle. The results revealed that at signalized intersections, the average fuel consumption per vehicle was 26.54 L/100 km, NOx emissions were 68.76 g/100 km, and CO2 emissions were 61.07 g/100 km. In contrast, at unsignalized intersections, the average fuel consumption per vehicle was 46.88 L/100 km, NOx emissions were 149.26 g/100 km, and CO2 emissions were 107.16 g/100 km. The study indicated that for traffic volumes between 50 and 103 vehicles per 100 s, signalized intersections demonstrated better fuel consumption and emission performance than unsignalized intersections. Signalized intersections could accommodate larger traffic volumes and provide enhanced traffic safety. In conclusion, the findings of this study are important for urban traffic planning and environmental policies. They provide a scientific basis for reducing fuel consumption and emissions and improving road traffic efficiency. Due to the advantages of signalized intersections in terms of energy consumption and emissions, future urban traffic planning should consider more signal light controls to achieve energy savings, emission reduction, and improved traffic operation efficiency.
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Kuik, Friderike, Andreas Kerschbaumer, Axel Lauer, Aurelia Lupascu, Erika von Schneidemesser, and Tim M. Butler. "Top–down quantification of NO<sub><i>x</i></sub> emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model." Atmospheric Chemistry and Physics 18, no. 11 (June 13, 2018): 8203–25. http://dx.doi.org/10.5194/acp-18-8203-2018.
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Abstract. With NO2 limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NOx emissions in urban areas. High-resolution chemistry transport modelling can help to assess the impact of high urban NOx emissions on air quality inside and outside of urban areas. However, many modelling studies report an underestimation of modelled NOx and NO2 compared with observations. Part of this model bias has been attributed to an underestimation of NOx emissions, particularly in urban areas. This is consistent with recent measurement studies quantifying underestimations of urban NOx emissions by current emission inventories, identifying the largest discrepancies when the contribution of traffic NOx emissions is high. This study applies a high-resolution chemistry transport model in combination with ambient measurements in order to assess the potential underestimation of traffic NOx emissions in a frequently used emission inventory. The emission inventory is based on officially reported values and the Berlin–Brandenburg area in Germany is used as a case study. The WRF-Chem model is used at a 3 km × 3 km horizontal resolution, simulating the whole year of 2014. The emission data are downscaled from an original resolution of ca. 7 km × 7 km to a resolution of 1 km × 1 km. An in-depth model evaluation including spectral decomposition of observed and modelled time series and error apportionment suggests that an underestimation in traffic emissions is likely one of the main causes of the bias in modelled NO2 concentrations in the urban background, where NO2 concentrations are underestimated by ca. 8 µg m−3 (−30 %) on average over the whole year. Furthermore, a diurnal cycle of the bias in modelled NO2 suggests that a more realistic treatment of the diurnal cycle of traffic emissions might be needed. Model problems in simulating the correct mixing in the urban planetary boundary layer probably play an important role in contributing to the model bias, particularly in summer. Also taking into account this and other possible sources of model bias, a correction factor for traffic NOx emissions of ca. 3 is estimated for weekday daytime traffic emissions in the core urban area, which corresponds to an overall underestimation of traffic NOx emissions in the core urban area of ca. 50 %. Sensitivity simulations for the months of January and July using the calculated correction factor show that the weekday model bias can be improved from −8.8 µg m−3 (−26 %) to −5.4 µg m−3 (−16 %) in January on average in the urban background, and −10.3 µg m−3 (−46 %) to −7.6 µg m−3 (−34 %) in July. In addition, the negative bias of weekday NO2 concentrations downwind of the city in the rural and suburban background can be reduced from −3.4 µg m−3 (−12 %) to −1.2 µg m−3 (−4 %) in January and from −3.0 µg m−3 (−22 %) to −1.9 µg m−3 (−14 %) in July. The results and their consistency with findings from other studies suggest that more research is needed in order to more accurately understand the spatial and temporal variability in real-world NOx emissions from traffic, and apply this understanding to the inventories used in high-resolution chemical transport models.
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Li, Xin, and Feng Chen. "Optimal Signal Timing of Single Intersection for Traffic Emission Control." Applied Mechanics and Materials 587-589 (July 2014): 2137–40. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.2137.
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Traffic emission is one of the main pollution sources of urban atmospheric environment. Traffic control scheme of intersection has important influence on vehicle emission. Research on low emission traffic signal control scheme has become one of focuses of Intelligent Transportation. Current typical control methods of traffic emission are based on optimizing the average delay and number of stops. However, it is extremely difficult to use mathematical formula to calculate the delay and the number of stops in the presence of initial queue length of intersection. In order to solve this problem, we proposed a traffic emission control algorithm based on reinforcement learning. The simulation experiments were carried out by using the microscopic traffic simulation software. Compared with the Hideki emission control scheme, the experimental results show that the reinforcement learning algorithm is more effective. The average vehicle emissions are reduced by 12.2% for high saturation of the intersection.
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Ou, Yifu, Ji Zheng, and Kyung-Min Nam. "Impacts of Urban Rail Transit on On-Road Carbon Emissions: A Structural Equation Modeling Approach." Atmosphere 13, no. 11 (October 28, 2022): 1783. http://dx.doi.org/10.3390/atmos13111783.
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We examine the effects of urban rail transit on on-road carbon emissions in 90 Chinese cities, taking a structural equation modeling approach. Urban rail transit theoretically helps mitigate overall transport-sector emissions by absorbing part of the vehicular traffic demand or by generating traffic-diversion effects. However, its net contribution is obscure, given potential traffic-creation effects, since improved rail access can also incentivize new developments and thus induce additional on-road traffic. In contrast to many existing studies that neglect rail transit’s traffic-creation effects, we analyze these opposing effects within a single framework, where primary rail-associated emission channels are explicitly modeled. Our central results show that urban rail density is negatively associated with on-road carbon emissions with a net elasticity of −0.0175, speaking for the dominance of the traffic-diversion effects in China’s context. However, mixed evidence exists on the effects of increased urban rail density on vehicle-kilometers traveled and vehicle ownership, with the two opposing effects being relatively balanced. These findings suggest that transport-sector mitigation needs coordination between urban rail development and planning regulations.
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Wu, Na, and Yating Liu. "Potential of Ecological Benefits for the Continuous Flow Intersection." Promet 35, no. 1 (February 13, 2023): 106–18. http://dx.doi.org/10.7307/ptt.v35i1.20.
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Energy conservation and emission reduction from the transportation sector are of great significance in coping with the global energy and environmental crisis. As the bottleneck of urban road traffic, intersection burdens the urban environment greatly. When the volume of left-turn traffic is large, the continuous flow intersection (CFI) can effectively improve intersection operation efficiency. This paper first put forward the definition and application conditions of CFI. Then its mechanism for energy saving and emission reduction was analysed. CFI transformation was designed taking a typical intersection in Xi’an as an example. Operating efficiency, energy consumption and emissions of the intersection before and after CFI transformation were evaluated using the VISSIM model. The results show that energy consumption and emissions in the intersection are greatly reduced after CFI transformation. Queue length is reduced by more than 41%. Energy consumption and pollutant emission are reduced by about 8%. Through the simulation analysis, the emission reduction benefits most when the volume of left-turn traffic is 80%–85% of the design capacity, and the ratio of leftturntraffic over through traffic is maintained between 50% and 100%. This study suggests that CFI is suitable for large-scale promotion with careful examination.
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Shan, Xiaonian, Xiaohong Chen, Wenjian Jia, and Jianhong Ye. "Evaluating Urban Bus Emission Characteristics Based on Localized MOVES Using Sparse GPS Data in Shanghai, China." Sustainability 11, no. 10 (May 23, 2019): 2936. http://dx.doi.org/10.3390/su11102936.
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Bus emissions have become one of the important contributing factors in urban environmental pollution due to the frequent use of heavy-duty diesel engines in the day-time. Local bus driving cycles have a significant influence on bus emissions under the different traffic conditions. This study investigated the operation mode distributions and emission characteristics for urban buses based on localized MOtor Vehicle Emission Simulator (MOVES) using sparse Global Position System (GPS) data in Shanghai, China. Sparse GPS data from forty-three buses were prepared, and then bus trajectories were reconstructed to calculate local bus driving cycles, including model description, model calibration, and trajectory reconstruction. MOVES localization was conducted for emission estimation mainly focusing on the bus emission inventory comparison between US and China. Bus emission factors were estimated based on the localized MOVES from the aspect of different driving conditions. Results show that with the increase in average traveling speed, the proportion of idling operation mode showed a decreasing trend. Four typical vehicle operation mode distributions were identified with different average speeds to show the impact of traffic conditions. Bus emission factors first rapidly decreased and then slowly declined towards some minimum values. Bus lanes exhibited emission reduction benefits under serious traffic congestion. The findings of this study have great importance for transportation operation management and policy-making to reduce bus emissions, as well as improving air quality.
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Macdonald, Elena, Noelia Otero, and Tim Butler. "A comparison of long-term trends in observations and emission inventories of NO<sub><i>x</i></sub>." Atmospheric Chemistry and Physics 21, no. 5 (March 17, 2021): 4007–23. http://dx.doi.org/10.5194/acp-21-4007-2021.
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Abstract. Air pollution is a pressing issue that is associated with adverse effects on human health, ecosystems, and climate. Despite many years of effort to improve air quality, nitrogen dioxide (NO2) limit values are still regularly exceeded in Europe, particularly in cities and along streets. This study explores how concentrations of nitrogen oxides (NOx = NO + NO2) in European urban areas have changed over the last decades and how this relates to changes in emissions. To do so, the incremental approach was used, comparing urban increments (i.e. urban background minus rural concentrations) to total emissions, and roadside increments (i.e. urban roadside concentrations minus urban background concentrations) to traffic emissions. In total, nine European cities were assessed. The study revealed that potentially confounding factors like the impact of urban pollution at rural monitoring sites through atmospheric transport are generally negligible for NOx. The approach proves therefore particularly useful for this pollutant. The estimated urban increments all showed downward trends, and for the majority of the cities the trends aligned well with the total emissions. However, it was found that factors like a very densely populated surrounding or local emission sources in the rural area such as shipping traffic on inland waterways restrict the application of the approach for some cities. The roadside increments showed an overall very diverse picture in their absolute values and trends and also in their relation to traffic emissions. This variability and the discrepancies between roadside increments and emissions could be attributed to a combination of local influencing factors at the street level and different aspects introducing inaccuracies to the trends of the emission inventories used, including deficient emission factors. Applying the incremental approach was evaluated as useful for long-term pan-European studies, but at the same time it was found to be restricted to certain regions and cities due to data availability issues. The results also highlight that using emission inventories for the prediction of future health impacts and compliance with limit values needs to consider the distinct variability in the concentrations not only across but also within cities.
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Zhang, Hong Liang. "Urban Vehicle Emissions Management under Uncertainty - A Traffic Planning Model with Interval-Parameter Programming." Advanced Materials Research 864-867 (December 2013): 1586–91. http://dx.doi.org/10.4028/www.scientific.net/amr.864-867.1586.
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In this study, an interval-parameter programming method has been used for urban vehicle emissions management under uncertainty. The model improves upon the existing optimization methods with advantages in uncertainty reflection, system costs and limitation of emission. Moreover, the model is applied to a case study of urban vehicle emissions management in a virtual city. The results indicate that the interval linear traffic planning model can effectively reduce the vehicles emission and provide strategies for authorities to deal with problems of transportation system.
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Gu, Chaoyi, Reza Farzaneh, Geza Pesti, Gabriel Valdez, and Andrew Birt. "Estimating Vehicular Emission Impact of Nighttime Construction with VISSIM and Different MOVES Emission Estimation Approaches." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 25 (October 2, 2018): 174–86. http://dx.doi.org/10.1177/0361198118798988.
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Shifting work zones from daytime to nighttime is a potential solution to air quality issues on roadway with high traffic volume and where it is undesirable to close lanes during peak hours. The expected benefit of such shifting is to reduce total fuel consumption and on-road vehicle emissions. However, the magnitude of emission reductions and air quality impacts has not been examined comprehensively at work zones. The study presented in this paper investigated the traffic-related emission impacts of work zones using an urban freeway case study. A VISSIM test bed combined with the Environmental Protection Agency’s MOVES emission model was used to estimate total emissions assuming daytime and nighttime lane-closure scenarios. Vehicle emissions were estimated using a link-based method and operating mode-based method. The results from both methods demonstrated that nighttime construction has a significant impact on both traffic speeds and vehicle emissions, primarily as a result of reductions in vehicle miles traveled. In addition, a horizontal comparison between the results from the two methods was made to assess the impact of different emission estimation approaches. The outcomes from the comparison highlight the potential importance of the operating mode-based approach for accurately estimate total traffic emission quantities when data or simulations are available.
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Zhang, Yi, Li Juan Wan, Li Zhang, and Dong Xiang Cheng. "Forecast of Energy Consumption and Carbon Emission of Urban Traffic by Using System Dynamics." Advanced Materials Research 989-994 (July 2014): 1248–51. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1248.
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In the future development of city, traffic acts a very important role, which not only support the modernization of city, but also offer more travel and transportation service for the increasing city population. Therefore, it is necessary to study the urban traffic, energy consumption and carbon emission based on System Dynamics. System Dynamics not only offer quantificational references and advice about city planning for the government, but also make people understand the present status of urban traffic and possible development trend of urban traffic under the influence of different policies. In this review, the energy consumption and emission of urban traffic, the development of System Dynamics and the advantages on solving urban traffic problems based on System Dynamics are introduced.
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Doumbia, Madina, Adjon A. Kouassi, Siélé Silué, Véronique Yoboué, Cathy Liousse, Arona Diedhiou, N’Datchoh E. Touré, et al. "Road Traffic Emission Inventory in an Urban Zone of West Africa: Case of Yopougon City (Abidjan, Côte d’Ivoire)." Energies 14, no. 4 (February 19, 2021): 1111. http://dx.doi.org/10.3390/en14041111.
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Road traffic emission inventories based on bottom-up methodology, are calculated for each road segment from fuel consumption and traffic volume data obtained during field measurements in Yopougon. High emissions of black carbon (BC) from vehicles are observed at major road intersections, in areas surrounding industrial zones and on highways. Highest emission values from road traffic are observed for carbon monoxide (CO) (14.8 t/d) and nitrogen oxides (NOx) (7.9 t/d), usually considered as the major traffic pollution tracers. Furthermore, peak values of CO emissions due to personal cars (PCs) are mainly linked to the old age of the vehicle fleet with high emission factors. The highest emitting type of vehicle for BC on the highway is PC (70.2%), followed by inter-communal taxis (TAs) (13.1%), heavy vehicles (HVs) (9.8%), minibuses (GBs) (6.4%) and intra-communal taxis (WRs) (0.4%). While for organic carbon (OC) emissions on the main roads, PCs represent 46.7%, followed by 20.3% for WRs, 14.9% for TAs, 11.4% for GB and 6.7% for HVs. This work provides new key information on local pollutant emissions and may be useful to guide mitigation strategies such as modernizing the vehicle fleet and reorganizing public transportation, to reduce emissions and improve public health.
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Ghermandi, Grazia, Sara Fabbi, Giorgio Veratti, Alessandro Bigi, and Sergio Teggi. "Estimate of Secondary NO2 Levels at Two Urban Traffic Sites Using Observations and Modelling." Sustainability 12, no. 19 (September 24, 2020): 7897. http://dx.doi.org/10.3390/su12197897.
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Assessing secondary and primary NO2 in urban areas is important to support carefully designed environmental policies, particularly in areas with recurrent exceedance of NO2 regulatory limits. The share of secondary NO2 was preliminary estimated in intense traffic areas of Modena and Reggio Emilia (Northern Italy) by the combined analysis of regulatory air quality observations at urban traffic and urban background conditions. In addition simulations performed by the Lagrangian particle dispersion models Micro SWIFT SPRAY and the chemical transport model WRF-Chem were performed. The former was applied on the urban area representative of traffic conditions for both cities, in winter. The latter was applied twice in Modena, both with and without urban traffic emissions. Results suggest a large amount of secondary NO2 mainly at the Modena traffic site, and a better representativity of background conditions of the corresponding urban station in Reggio Emilia. NOx levels simulated by WRF-Chem show good results at Modena urban background and performance in line with reference benchmark values in reproducing observed NO2 and NOx concentrations at rural background sites, although a non-negligible bias in simulated urban NO2 remained. Overall the simulation models suggest that contribution to atmospheric NOx by domestic heating or industrial combustion emissions are not as relevant compared to traffic, consistently with the local emission inventory.
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Zhang, Na, Zijia Wang, Feng Chen, Jingni Song, Jianpo Wang, and Yu Li. "Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji." Energies 13, no. 4 (February 11, 2020): 782. http://dx.doi.org/10.3390/en13040782.
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There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation types is changing along with the adjustment of the urban traffic structure and a growing demand from passengers. The reduction of carbon emissions brought about by rail transit lacks specific quantitative research. Based on a travel survey of urban residents, this paper constructed a method of estimating carbon emissions from two different scenarios where rail transit is and is not available. This study uses the traditional four-stage model to forecast passenger volume demand at the city level and then obtains the basic target parameters for constructing the carbon emission reduction model, including the trip origin-destination (OD), mode, and corresponding distance range of different modes on the urban road network. This model was applied to Baoji, China, where urban rail transit will be available from 2023. It calculates the changes in carbon emission that rail transit can bring about and its impact on carbon emission reductions in Baoji in 2023.
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Alfoldy, Balint, Asta Gregorič, Matic Ivančič, Irena Ježek, and Martin Rigler. "Source apportionment of black carbon and combustion-related CO2 for the determination of source-specific emission factors." Atmospheric Measurement Techniques 16, no. 1 (January 12, 2023): 135–52. http://dx.doi.org/10.5194/amt-16-135-2023.
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Abstract. Black carbon (BC) aerosol typically has two major sources in the urban environment: traffic and domestic biomass burning, which has a significant contribution to urban air pollution during the heating season. Traffic emissions have been widely studied by both laboratory experiments (individual vehicle emission) and real-world measurement campaigns (fleet emission). However, emission information from biomass burning is limited, especially an insufficiency of experimental results from real-world studies. In this work, the black carbon burden in the urban atmosphere was apportioned to fossil fuel (FF) and biomass burning (BB) related components using the Aethalometer source apportionment model. Applying the BC source apportionment information, the combustion-related CO2 was apportioned by multilinear regression analysis, supposing that both CO2 components should be correlated with their corresponding BC component. The combination of the Aethalometer model with the multilinear regression analysis (AM-MLR) provided the source-specific emission ratios (ERs) as the slopes of the corresponding BC–CO2 regressions. Based on the ER values, the source-specific emission factors (EFs) were determined using the carbon content of the corresponding fuel. The analysis was carried out on a 3-month-long BC and CO2 dataset collected at three monitoring locations in Ljubljana, Slovenia, between December 2019 and March 2020. The measured mean site-specific concentration values were in the 3560–4830 ng m−3 and 458–472 ppm ranges for BC and CO2, respectively. The determined average EFs for BC were 0.39 and 0.16 g(kg fuel)−1 for traffic and biomass burning, respectively. It was also concluded that the traffic-related BC component dominates the black carbon concentration (55 %–64 % depending on the location), while heating has the major share in the combustion-related CO2 (53 %–62 % depending on the location). The method gave essential information on the source-specific emission factors of BC and CO2, enabling better characterization of urban anthropogenic emissions and the respective measures that may change the anthropogenic emission fingerprint.
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Andrych-Zalewska, Monika, Zdzislaw Chlopek, Jerzy Merkisz, and Jacek Pielecha. "Investigations of Exhaust Emissions from a Combustion Engine under Simulated Actual Operating Conditions in Real Driving Emissions Test." Energies 14, no. 4 (February 10, 2021): 935. http://dx.doi.org/10.3390/en14040935.
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The paper describes the methodology of research of exhaust emissions from a combustion engine under engine states determined by the vehicle actual operation in the RDE test. The processes of quantities determining the vehicle motion and engine states have been recorded, along with the exhaust emission intensity. Based on the developed research methodology, zero-dimensional characteristics of the processes of the emission intensity have been determined under the conditions of urban, rural and motorway traffic, as well as in the entire test. The authors also determined the average specific distance exhaust emissions under the conditions of urban, rural and motorway traffic, as well as in the entire test. Based on the above results, the unique characteristics of the relation of the average specific distance emissions and the average vehicle speed have been obtained. The obtained characteristics may be used in the modeling of exhaust emissions from motor vehicles under actual traffic conditions. The authors also explored the sensitivity of the average specific distance emissions to the vehicle driving style.
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Dai, Hongna, Enjian Yao, and Rui Zhao. "Research on Congestion Pricing in Multimode Traffic considering Delay and Emission." Discrete Dynamics in Nature and Society 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/769251.
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Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode) urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.
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Stan, Ioan, Daniel Alexandru Ghere, Paula Iarina Dan, and Rodica Potolea. "Urban Congestion Avoidance Methodology Based on Vehicular Traffic Thresholding." Applied Sciences 13, no. 4 (February 7, 2023): 2143. http://dx.doi.org/10.3390/app13042143.
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Vehicular traffic in urban areas faces congestion challenges that negatively impact our lives. The infrastructure associated with intelligent transportation systems provides means for addressing the associated challenges in urban areas. This study proposes an effective and scalable vehicular traffic congestion avoidance methodology. It introduces a traffic thresholding mechanism to predict and avoid vehicular traffic congestion during route computation. Our methodology was evaluated and validated by employing four road network topologies, three vehicular traffic density levels and various traffic light configurations, resulting in 26 urban traffic scenarios. Using our approach, the number of vehicles that can run in free flow can be increased by up to 200%, whereas for traffic congestion scenarios, the time spent in traffic may be reduced by up to 69% and CO2 emissions by up to 61%. To the best of our knowledge, in the vehicular traffic flow prediction domain, this is the first approach that covers a set of road network topologies and a large and representative set of scenarios for simulated urban traffic congestion testing. Moreover, the comparative analysis with different other solutions in the domain, showed that we obtained the best driving time and CO2 emission reduction.
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Karjalainen, P., H. Timonen, E. Saukko, H. Kuuluvainen, S. Saarikoski, P. Aakko-Saksa, T. Murtonen, et al. "Time-resolved characterization of primary and secondary particle emissions of a modern gasoline passenger car." Atmospheric Chemistry and Physics Discussions 15, no. 22 (November 25, 2015): 33253–82. http://dx.doi.org/10.5194/acpd-15-33253-2015.
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Abstract. Changes in traffic systems and vehicle emission reduction technologies significantly affect traffic-related emissions in urban areas. In many densely populated areas the amount of traffic is increasing, keeping the emission level high or even increasing. To understand the health effects of traffic related emissions, both primary and secondary particles that are formed in the atmosphere from gaseous exhaust emissions need to be characterized. In this study we used a comprehensive set of measurements to characterize both primary and secondary particulate emissions of a modern gasoline passenger car. Our aerosol particle study covers the whole process chain in emission formation, from the engine to the atmosphere, and takes into account also differences in driving patterns. We observed that in mass terms, the amount of secondary particles was 13 times higher than the amount of primary particles. The formation, composition, number, and mass of secondary particles was significantly affected by driving patterns and engine conditions. The highest gaseous and particulate emissions were observed at the beginning of the test cycle when the performance of the engine and the catalyst was below optimal. The key parameter for secondary particle formation was the amount of gaseous hydrocarbons in primary emissions; however, also the primary particle population had an influence. Thus, in order to enhance human health and wellbeing in urban areas, our study strongly indicates that in future legislation, special attention should be directed into the reduction of gaseous hydrocarbons.
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Zhou, Jingcheng, Junfeng Liu, Songlin Xiang, Yizhou Zhang, Yuqing Wang, Wendong Ge, Jianying Hu, et al. "Evaluation of the Street Canyon Level Air Pollution Distribution Pattern in a Typical City Block in Baoding, China." International Journal of Environmental Research and Public Health 19, no. 16 (August 22, 2022): 10432. http://dx.doi.org/10.3390/ijerph191610432.
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Urban traffic pollution, which is strongly influenced by the complex urban morphology, has posed a great threat to human health. In this study, we performed a high-resolution simulation of traffic pollution in a typical city block in Baoding, China, based on the Parallelized Large-eddy simulation Model (PALM), to examine the distribution patterns of traffic-related pollutants and explore their relationship with urban morphology. Based on the model results, we conducted a multi-linear regression (MLR) analysis and found that the distribution of air pollutants inside the city block was dominated by both traffic emissions and urban morphology, which explained about 70% of the total variance in spatial distribution of air pollutants. Excluding the contribution of emissions, over 50% of the total variance can still be explained by the urban morphology. Among these urban morphological factors, the key factors determining the spatial distribution of air pollution are “Distance from the road” (DR), “Building Coverage Ratio” (BCR) and “Aspect Ratio” (H/W) of the street canyon. Specifically, urban areas with lower Aspect Ratio, lower BCR and larger DR are less affected by traffic pollution. Compiling these individual factors, we developed a complex Urban Morphology Pollution Index (UMPI). Each unit increase in UMPI is associated with a one percent increase of nearby traffic pollution contribution. This index can help urban planners to semi-quantitatively evaluate building groups which tend to trap or ventilate traffic pollution and thus help to reduce human exposure to street canyon level pollution through either traffic emission control or urban morphology amelioration.
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Yang, Qing, and Mei Mei Huang. "Study on Exhaust Diffusion Control in Urban Trunk Intersection." Key Engineering Materials 579-580 (September 2013): 851–55. http://dx.doi.org/10.4028/www.scientific.net/kem.579-580.851.
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With vehicle population increase, urban trunk traffic flows augment significantly. Traffic environmental problems are become progressively severe challenge, such as congestion, emissions, and photoacoustic pollution. In view of exhaust pollution diffusion problems in urban trunk intersection, this article took North Bayi Street - South Bayi Street in Jinhua as case, carried out traffic surveys of trunk along, tested vehicle exhaust pollutants concentration of intersections, analyzed the exhaust diffusion characteristics of trunk along during the early peak, evening peak and working hours on workday, and proposed relevant emission control measures. Traffic flow in this urban trunk was about 860-3060 pcu/h, and CO was the main pollutant in the exhaust emissions. CO and NO2 diurnal variation ranges were 3.23-14.2ppm and 0.1-0.71ppm. Intersection 4 (South Bayi Street - West Shuangxi Road) with the maximum average concentration of exhaust pollutants along trunk, diurnal variation of peak period were distributed in morning, evening and noon hours, and the evening peak was the maximum. Under the same conditions, exhaust pollutant concentration raised with the traffic increasing in a linear positive correlation. Traffic management measures could control vehicle exhaust diffusion concentration and spread range in the intersection, such as using new clean energy, improving existing fuels, bettering whole road network emissions, and increasing the green rate around intersections.
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Jamshidnejad, Anahita, Ioannis Papamichail, Markos Papageorgiou, and Bart De Schutter. "A mesoscopic integrated urban traffic flow-emission model." Transportation Research Part C: Emerging Technologies 75 (February 2017): 45–83. http://dx.doi.org/10.1016/j.trc.2016.11.024.
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Wang, Junjie, Yuan Li, and Yi Zhang. "Research on Carbon Emissions of Road Traffic in Chengdu City Based on a LEAP Model." Sustainability 14, no. 9 (May 6, 2022): 5625. http://dx.doi.org/10.3390/su14095625.
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With the continuous increase in the number of vehicles, the proportion of carbon emissions from road traffic in cities has significantly increased, putting pressure on the overall carbon emission reduction of cities The implementation of low-carbon transportation has, therefore, become crucial to urban emission reductions. Based on the situation of vehicles in Chengdu, this study uses the LEAP model to construct a road traffic development scenario in Chengdu from 2020 to 2025. The research focuses on common greenhouse gases that contribute to carbon emissions such as CO2, N2O, and CH4 from motor vehicles. With current policies being considered, we simulate and evaluate energy consumption and carbon emissions under two energy-saving and emission reduction scenarios: low carbon (LC) and strengthen low carbon (SLC). The results show that carbon emissions significantly improve under the LC scenario, and that the carbon emissions of the road traffic of Chengdu will peak before 2030 under the SLC scenario.
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Reche, C., X. Querol, A. Alastuey, M. Viana, J. Pey, T. Moreno, S. Rodríguez, et al. "New considerations for PM, Black Carbon and particle number concentration for air quality monitoring across different European cities." Atmospheric Chemistry and Physics 11, no. 13 (July 1, 2011): 6207–27. http://dx.doi.org/10.5194/acp-11-6207-2011.
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Abstract. In many large cities of Europe standard air quality limit values of particulate matter (PM) are exceeded. Emissions from road traffic and biomass burning are frequently reported to be the major causes. As a consequence of these exceedances a large number of air quality plans, most of them focusing on traffic emissions reductions, have been implemented in the last decade. In spite of this implementation, a number of cities did not record a decrease of PM levels. Thus, is the efficiency of air quality plans overestimated? Do the road traffic emissions contribute less than expected to ambient air PM levels in urban areas? Or do we need a more specific metric to evaluate the impact of the above emissions on the levels of urban aerosols? This study shows the results of the interpretation of the 2009 variability of levels of PM, Black Carbon (BC), aerosol number concentration (N) and a number of gaseous pollutants in seven selected urban areas covering road traffic, urban background, urban-industrial, and urban-shipping environments from southern, central and northern Europe. The results showed that variations of PM and N levels do not always reflect the variation of the impact of road traffic emissions on urban aerosols. However, BC levels vary proportionally with those of traffic related gaseous pollutants, such as CO, NO2 and NO. Due to this high correlation, one may suppose that monitoring the levels of these gaseous pollutants would be enough to extrapolate exposure to traffic-derived BC levels. However, the BC/CO, BC/NO2 and BC/NO ratios vary widely among the cities studied, as a function of distance to traffic emissions, vehicle fleet composition and the influence of other emission sources such as biomass burning. Thus, levels of BC should be measured at air quality monitoring sites. During morning traffic rush hours, a narrow variation in the N/BC ratio was evidenced, but a wide variation of this ratio was determined for the noon period. Although in central and northern Europe N and BC levels tend to vary simultaneously, not only during the traffic rush hours but also during the whole day, in urban background stations in southern Europe maximum N levels coinciding with minimum BC levels are recorded at midday in all seasons. These N maxima recorded in southern European urban background environments are attributed to midday nucleation episodes occurring when gaseous pollutants are diluted and maximum insolation and O3 levels occur. The occurrence of SO2 peaks may also contribute to the occurrence of midday nucleation bursts in specific industrial or shipping-influenced areas, although at several central European sites similar levels of SO2 are recorded without yielding nucleation episodes. Accordingly, it is clearly evidenced that N variability in different European urban environments is not equally influenced by the same emission sources and atmospheric processes. We conclude that N variability does not always reflect the impact of road traffic on air quality, whereas BC is a more consistent tracer of such an influence. However, N should be measured since ultrafine particles (<100 nm) may have large impacts on human health. The combination of PM10 and BC monitoring in urban areas potentially constitutes a useful approach for air quality monitoring. BC is mostly governed by vehicle exhaust emissions, while PM10 concentrations at these sites are also governed by non-exhaust particulate emissions resuspended by traffic, by midday atmospheric dilution and by other non-traffic emissions.
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Aalto, T., M. Lallo, J. Hatakka, and T. Laurila. "Atmospheric hydrogen variations and traffic emissions at an urban site in Finland." Atmospheric Chemistry and Physics Discussions 9, no. 3 (June 25, 2009): 13917–42. http://dx.doi.org/10.5194/acpd-9-13917-2009.
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Abstract. Atmospheric hydrogen (H2) mixing ratios were observed over one year period from summer 2007 to 2008 in Helsinki, Finland. Relatively stable background values of hydrogen were occasionally observed at the site, with minimum in October and maximum between March and May. High hydrogen mixing ratios occurred simultaneously with high carbon monoxide (CO) values and coincided with high traffic flow periods. Carbon monoxide and radon (222Rn) were continuously monitored at the same site and they were used in estimation of the hydrogen emissions from traffic. The morning rush hour slope of ΔH2/ΔCO was in average 0.43±0.03 ppb (H2)/ppb(CO). After correction due to soil deposition of H2 the slope was 0.49±0.07 ppb (H2)/ppb(CO). Using this slope and CO emission statistics, a road traffic emission of about 260 t (H2)/year was estimated for Helsinki in 2007.
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Aalto, T., M. Lallo, J. Hatakka, and T. Laurila. "Atmospheric hydrogen variations and traffic emissions at an urban site in Finland." Atmospheric Chemistry and Physics 9, no. 19 (October 5, 2009): 7387–96. http://dx.doi.org/10.5194/acp-9-7387-2009.
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Abstract. Atmospheric hydrogen (H2) mixing ratios were observed over a one year period from summer 2007 to 2008 in Helsinki, Finland. Relatively stable background values of hydrogen were occasionally observed at the site, with minimum in October and maximum between March and May. High hydrogen mixing ratios occurred simultaneously with high carbon monoxide (CO) values and coincided with high traffic flow periods. Carbon monoxide and radon (222Rn) were continuously monitored at the same site and they were used in estimation of the hydrogen emissions from traffic. The morning rush hour slope of ΔH2/ΔCO was in average 0.43±0.03 ppb (H2)/ppb (CO). After correction due to soil deposition of H2 the slope was 0.49±0.07 ppb (H2)/ppb (CO). Using this slope and CO emission statistics, a road traffic emission of about 260 t (H2)/year was estimated for Helsinki in 2007.
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Reche, C., X. Querol, A. Alastuey, M. Viana, J. Pey, T. Moreno, S. Rodríguez, et al. "Variability of levels of PM, black carbon and particle number concentration in selected European cities." Atmospheric Chemistry and Physics Discussions 11, no. 3 (March 14, 2011): 8665–717. http://dx.doi.org/10.5194/acpd-11-8665-2011.
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Abstract. In many large cities of Europe standard air quality limit values of particulate matter (PM) are exceeded. Emissions from road traffic and biomass burning are frequently reported to be the major causes. As a consequence of these exceedances a large number of air quality plans, most of them focusing on traffic emissions reductions, have been implemented in the last decade. In spite of this implementation, a number of cities did not record a decrease of PM levels. Thus, is the efficiency of air quality plans overestimated? Or do we need a more specific metric to evaluate the impact of the above emissions on the levels of urban aerosols? This study shows the results of the interpretation of the 2009 variability of levels of PM, black carbon (BC), aerosol number concentration (N) and a number of gaseous pollutants in seven selected urban areas covering road traffic, urban background, urban-industrial, and urban-shipping environments from southern, central and northern Europe. The results showed that variations of PM and N levels do not always reflect the variation of the impact of road traffic emissions on urban aerosols. However, BC levels vary proportionally with those of traffic related gaseous pollutants, such as CO, NO2 and NO. Due to this high correlation, one may suppose that monitoring the levels of these gaseous pollutants would be enough to extrapolate exposure to traffic-derived BC levels. However, the BC/CO, BC/NO2 and BC/NO ratios vary widely among the cities studied, as a function of distance to traffic emissions, vehicle fleet composition and the influence of other emission sources such as biomass burning. Thus, levels of BC should be measured at air quality monitoring sites. During traffic rush hours, a narrow variation in the N/BC ratio was evidenced, but a wide variation of this ratio was determined for the noon period. Although in central and northern Europe N and BC levels tend to vary simultaneously, not only during the traffic rush hours but also during the whole day, in urban background stations in southern Europe maximum N levels coinciding with minimum BC levels are recorded at midday in all seasons. These N maxima recorded in southern European urban background environments are attributed to midday nucleation episodes occurring when gaseous pollutants are diluted and maximum insolation and O3 levels occur. The occurrence of SO2 peaks may also contribute to the occurrence of midday nucleation bursts in specific industrial or shipping-influenced areas, although at several central European sites similar levels of SO2 are recorded without yielding nucleation episodes. Accordingly, it is clearly evidenced that N variability in different European urban environments is not equally influenced by the same emission sources and atmospheric processes. We conclude that N variability does not always reflect the impact of road traffic on air quality, whereas BC is a more consistent tracer of such an influence. The combination of PM10 and BC monitoring in urban areas potentially constitutes a useful approach to evaluate the impact of road traffic emissions on air quality.
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Wiśniowski, Piotr, Marcin Slezak, and Andrzej Niewczas. "Simulation of road traffic conditions on a chassis dynamometer." Archives of Automotive Engineering – Archiwum Motoryzacji 84, no. 2 (June 28, 2019): 171–78. http://dx.doi.org/10.14669/am.vol84.art12.
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The article presents and compares the results of exhaust emission tests in conditions of real vehicle traffic with the results obtained during bench tests on a chassis dynamometer in conditions of road traffic simulation. A series of tests were carried out using a mobile exhaust analyzer and a vehicle speed recorder. The research route was designated in the center of a large urban agglomeration. Laboratory tests were designed according to an algorithm approximating the actual driving sections, and when choosing their order during the test construction, a random factor was introduced. The presented approach reflects the random nature of road traffic while ensuring the representativeness of toxic emissions from the vehicle's exhaust system. The results of measurements of carbon dioxide emission, carbon monoxide, nitrogen oxides and hydrocarbons registered in road and stationary, laboratory emissin tests were compared. Substantial agreement was found between the tests. Difficulties and differences in results due to research problems have also been described.
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Du, Canyi, Xinfa Qiu, Feng Li, and Ming Cai. "A simulation of traffic noise emissions at a roundabout based on a cellular automaton model." Acta Acustica 5 (2021): 42. http://dx.doi.org/10.1051/aacus/2021037.
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The calculation and evaluation of traffic noise is an important task in urban road design. Roundabouts are a common form of urban road intersection. The complexity of traffic operations makes the calculation of traffic noise near a roundabout challenging. To explore traffic noise at roundabouts, a cellular automaton traffic flow model for a two-lane roundabout is established. Based on this model, a dynamic simulation method for traffic noise at roundabouts is proposed. The traffic operation and noise emissions at a roundabout are simulated. The vehicle speed distribution and traffic noise distribution at the roundabout are analysed, and the relationship between the traffic volume and sound power level of the cells is discussed. Finally, the proposed method is compared with existing traffic noise models, and the accuracy and efficiency of the proposed method are verified. The results of this paper show that the speed distribution and noise emission distribution at the roundabout are not uniform. When the traffic volume increases to saturation, the noise emission on the ring road will not keep increasing, and the sound power level of the cells on the inner ring is approximately 2 dBA higher than that of the outer ring. The methods and results in this paper may be valuable for road traffic design and noise control.
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Du, Canyi, Xinfa Qiu, Feng Li, and Ming Cai. "A simulation of traffic noise emissions at a roundabout based on a cellular automaton model." Acta Acustica 5 (2021): 42. http://dx.doi.org/10.1051/aacus/2021037.
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The calculation and evaluation of traffic noise is an important task in urban road design. Roundabouts are a common form of urban road intersection. The complexity of traffic operations makes the calculation of traffic noise near a roundabout challenging. To explore traffic noise at roundabouts, a cellular automaton traffic flow model for a two-lane roundabout is established. Based on this model, a dynamic simulation method for traffic noise at roundabouts is proposed. The traffic operation and noise emissions at a roundabout are simulated. The vehicle speed distribution and traffic noise distribution at the roundabout are analysed, and the relationship between the traffic volume and sound power level of the cells is discussed. Finally, the proposed method is compared with existing traffic noise models, and the accuracy and efficiency of the proposed method are verified. The results of this paper show that the speed distribution and noise emission distribution at the roundabout are not uniform. When the traffic volume increases to saturation, the noise emission on the ring road will not keep increasing, and the sound power level of the cells on the inner ring is approximately 2 dBA higher than that of the outer ring. The methods and results in this paper may be valuable for road traffic design and noise control.
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Mądziel, Maksymilian. "Vehicle Emission Models and Traffic Simulators: A Review." Energies 16, no. 9 (May 7, 2023): 3941. http://dx.doi.org/10.3390/en16093941.
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Accurate estimations and assessments of vehicle emissions can support decision-making processes. Current emission estimation tools involve several calculation methods that provide estimates of the exhaust components that result from driving on urban arterial roads. This is an important consideration, as the emissions generated have a direct impact on the health of pedestrians near the roads. In recent years, there has been an increase in the use of emission models, especially in combination with traffic simulator models. This is because it is very difficult to obtain an actual measurement of road emissions for all vehicles travelling along the analysed road section. This paper concerns a review of selected traffic simulations and the estimation of exhaust gas components models. The models presented have been aggregated into a group with respect to their scale of accuracy as micro, meso, and macro. This paper also presents an overview of selected works that combine both traffic and emission models. The presented literature review also emphasises the proper calibration process of simulation models as the most important factor in obtaining accurate estimates. This work also contains information and recommendations on modelling that may be helpful in selecting appropriate emission estimation tools to support decision-making processes for, e.g., road managers.
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Salameh, T., S. Sauvage, C. Afif, A. Borbon, and N. Locoge. "Source apportionment vs. emission inventories of non-methane hydrocarbons (NMHC) in an urban area of the Middle East: local and global perspectives." Atmospheric Chemistry and Physics Discussions 15, no. 19 (October 5, 2015): 26795–837. http://dx.doi.org/10.5194/acpd-15-26795-2015.
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Abstract. We applied the Positive Matrix Factorization model to two large datasets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt % respectively in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The national road transport inventory shows lowest emissions than the ones from PMF but with a reasonable difference lower than 50 %. Global inventories show higher discrepancies with lower emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is a strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector. Highlights: – PMF model was applied to identify major NMHC sources and their seasonal variation. – Gasoline evaporation accounts for more than 40 % both in winter and in summer. – NMHC urban emissions are dominated by traffic related sources in both seasons. – Agreement with the emission inventory regarding the relative contribution of the on-road mobile source but disagreement in terms of emission quantities suggesting an underestimation of the inventories.
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Shepelev, Vladimir, Aleksandr Glushkov, Ivan Slobodin, and Yuri Cherkassov. "Measuring and Modelling the Concentration of Vehicle-Related PM2.5 and PM10 Emissions Based on Neural Networks." Mathematics 11, no. 5 (February 25, 2023): 1144. http://dx.doi.org/10.3390/math11051144.
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The urban environment near the road infrastructure is particularly affected by traffic emissions. This problem is exacerbated at road junctions. The roadside concentration of particulate (PM2.5 and PM10) emissions depends on traffic parameters, meteorological conditions, the characteristics and condition of the road surface, and urban development, which affects air flow and turbulence. Continuous changes in the structure and conditions of the traffic flow directly affect the concentration of roadside emissions, which significantly complicates monitoring and forecasting the state of ambient air. Our study presents a hybrid model to estimate the amount, concentration, and spatio-temporal forecasting of particulate emissions, accounting for dynamic changes in road traffic structure and the influence of meteorological factors. The input module of the model is based on data received from street cameras and weather stations using a trained convolutional neural network. Based on the history of emission concentration data as input data, we used a self-learning Recurrent Neural Network (RNN) for forecasting. Through micromodeling, we found that the order in which vehicles enter and exit an intersection affects the concentration of vehicle-related emissions. Preliminary experimental results showed that the proposed model provides higher accuracy in forecasting emission concentration (83–97%) than existing approaches.
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Crosignani, Paolo, Alessandro Nanni, Nicola Pepe, Cristina Pozzi, Camillo Silibello, Andrea Poggio, and Marianna Conte. "The Effect of Non-Compliance of Diesel Vehicle Emissions with Euro Limits on Mortality in the City of Milan." Atmosphere 12, no. 3 (March 6, 2021): 342. http://dx.doi.org/10.3390/atmos12030342.
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Diesel exhaust is hazardous to human health. In time, this has led the EU to impose on manufacturers lower and lower emission standards. These limits are very challenging in particular for nitrogen oxides (NOx) emitted by diesel-fueled vehicles. For the town of Milan (Italy), we used a complex modeling system that takes into account the NOx emissions from vehicular traffic and other urban sources, as well as their dispersion and chemical transformations in the atmosphere related to meteorological parameters. The traffic emissions in the Milan urban area were estimated using the geometric and structural characteristics of the road network, whereas the traffic flows were provided by the Environment and Territory Mobility Agency. Car emissions were estimated by the official European method COPERT 5. The nitrogen dioxide (NO2) concentrations were estimated under two scenarios: the actual scenario with real emissions and the Diesel Emission Standards Compliance (DESC) scenario. Using a recent meta-analysis, limited to European studies, we evaluated the relationship between NO2 concentrations and natural mortality. For the actual scenario, the NO2 annual concentration mean was 44.3 µg/m3, whereas under the DESC hypothetical scenario, this would have been of 37.7 µg/m3. This “extra” exposure of 6.6 µg/m3 of NO2 leads to a yearly excess of 574 “natural” deaths. Diesel emissions are very difficult to limit and are harmful for exposed people. This suggests that specific policies, including traffic limitations, need to be developed and enforced in urban environments.
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Saedi, Ramin, Rajat Verma, Ali Zockaie, Mehrnaz Ghamami, and Timothy J. Gates. "Comparison of Support Vector and Non-Linear Regression Models for Estimating Large-Scale Vehicular Emissions, Incorporating Network-Wide Fundamental Diagram for Heterogeneous Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 5 (April 16, 2020): 70–84. http://dx.doi.org/10.1177/0361198120914304.
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Estimation of vehicular emissions at network level is a prominent issue in transportation planning and management of urban areas. For large networks, macroscopic emission models are preferred because of their simplicity. However, these models do not consider traffic flow dynamics that significantly affect emissions production. This study proposes a network-level emission modeling framework based on the network-wide fundamental diagram (NFD), via integrating the NFD properties with an existing microscopic emission model. The NFD and microscopic emission models are estimated using microscopic and mesoscopic traffic simulation tools at different scales for various traffic compositions. The major contribution is to consider heterogeneous vehicle types with different emission generation rates in a network-level model. This framework is applied to the large-scale network of Chicago as well as its central business district. Non-linear and support vector regression models are developed using simulated trajectory data of 13 simulated scenarios. The results show a satisfactory calibration and successful validation with acceptable deviations from the underlying microscopic emissions model regardless of the simulation tool that is used to calibrate the network-level emissions model. The microscopic traffic simulation is appropriate for smaller networks, while mesoscopic traffic simulation is a proper means to calibrate models for larger networks. The proposed model is also used to demonstrate the relationship between macroscopic emissions and flow characteristics in the form of a network emissions diagram. The results of this study provide a tool for planners to analyze vehicular emissions in real time and find optimal policies to control the level of emissions in large cities.
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Zeng, Lin Hui, and Guang Ming Li. "World Expo 2010 Promotes the Reduction in Carbon Emissions of Urban Transport." Applied Mechanics and Materials 522-524 (February 2014): 1826–30. http://dx.doi.org/10.4028/www.scientific.net/amm.522-524.1826.
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Transport sector is one of the main sources of anthropogenic greenhouse gases (GHG) emissions. Comprehensive countermeasures are needed in cities to mitigate transport GHG emissions. After reviewing green traffic measures that implemented by Shanghai since bidding for Expo 2010, this paper analyzes the achievement that Shanghai has made in carbon mitigation. The results showed that travel demand management and the constrcution public transportation infrastructure promoted by the event played a vital role in promoting mode shift to form public transport oriented traffic system. Carbon emission intensity of Shanghais urban transport declined steadily from 1.66 kg/trip to 1.55 kg/trip. The CO2 reduction attributable to mode shifts amounted to 4.99 million tons. It demonstrated that Shanghai Expo has promoted the city in carbon emission reduction through public transport improvement, new energy vehicles innovation, car growth restriction measures and green commuting initiate.
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Czader, B. H., Y. Choi, X. Li, S. Alvarez, and B. Lefer. "Impact of updated traffic emissions on HONO mixing ratios simulated for urban site in Houston, Texas." Atmospheric Chemistry and Physics Discussions 14, no. 15 (August 20, 2014): 21315–40. http://dx.doi.org/10.5194/acpd-14-21315-2014.
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Abstract. Recent measurements in Houston show that HONO traffic emissions are 1.7% of NOx emissions which is about twice the previously estimated value of 0.8% based on tunnel measurements in 2001. The 0.8% value is widely used to estimate mobile emissions of HONO for air quality modeling applications. This study applies the newly estimated HONO/NOx ratio in the WRF-SMOKE-CMAQ modeling system and estimates the impact of higher HONO traffic emissions on its mixing ratios. Since applied emission inventory resulted in overestimates of NOx mixing ratios and because HONO emissions and chemical formation depends on the magnitude of NOx, thus, before proceeding with HONO emission modifications emissions of NOx were adjusted to reflect current emission trends. The modeled mixing ratios of NOx were evaluated against measured data from a number of sites in the Houston area. Overall, the NOx mean value dropped from 11.11 ppbv in the base case to 7.59 ppbv in the NOx adjusted case becoming much closer to the observed mean of 7.76 ppbv. The Index of Agreement (IOA) is improved in the reduced NOx case (0.71 vs. 0.75) and the Absolute Mean Error (AME) is lowered from 6.76 to 4.94. The modeled mixing ratios of HONO were evaluated against the actual observed values attained at the Moody Tower in Houston. The model could not reproduce the morning HONO peaks when the low HONO/NOx ratio of 0.008 was used to estimate HONO emissions. Doubling HONO emissions from mobile sources resulted in higher mixing ratios, the mean value increased from 0.30 to 0.41 ppbv becoming closer to the observed mean concentrations of 0.69 but still low; AME was slightly reduced from 0.46 to 0.43. IOA for simulation that used the 2001 emission values is 0.63 while for simulation with higher HONO emission it increased to 0.70. Increased HONO emissions impacted OH mixing ratio, up to about 6% increase was found during morning and mid-day hours. The impact on ozone is marginal. This study results sheds light on the underestimated HONO and OH in the morning from global/regional chemical transport models with the typical emission of 0.8% HONO emission out of the total NOx emissions.
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Meidiana, C., D. H. Leliana, and D. Agustina. "Potential of urban greening for carbon dioxide reduction from transportation sector." IOP Conference Series: Earth and Environmental Science 916, no. 1 (November 1, 2021): 012005. http://dx.doi.org/10.1088/1755-1315/916/1/012005.
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Abstract Various urban activities which exist in different lands uses in Mojokerto City such as settlement, commercial area, public service, and industrial area form the urban dynamic. Urban dynamic is stimulated by some factors including mobility of people and goods, information, and money. People’s mobility which dominates the urban mobility is accommodated by transportation mode causing transportation sector ranks the top first sector contributing to carbon dioxide (CO2) emissions in urban area, including Mojokerto City. Therefore, the study aims to propose reasonable solution for CO2 emissions reduction from transportation sector. The total amount of CO2 emissions is calculated first, and vegetation capacity to absorb CO2 is calculated afterwards using the formula for emission generation and bio capacity respectively. Development of urban greening is proposed to improve the bio-capacity of urban greening to absorb the remaining emissions. Based on the emission calculation, the total amount of CO2 emissions from transportation sector ranges between 6.6 to to 262.1 ton/year depending on the traffic volume and the distance covered by motorized vehicles. Meanwhile, calculation of bio capacity shows that the average absorption of vegetation in Mojokerto City is only 863.91 ton/yr. Improving urban greening area by planting more trees with higher absorption capacity is proposed to absorb the remaining emission. Calculation shows that enhanced urban greening can increase the emission absorption from 4% to 7% of the total emission from transportation sector.