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This paper presents a methodology to forecast the changes of NO2 immissions due to changes in fleet composition of passenger vehicles and emission classes. Within this scope, possible changes in vehicle technologies (e.g. lower emission of diesel engines) are considered in different scenarios using the example of Munich. In line with this purpose,...
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Context 1
... the approach as described in chapter 2.4 the NO 2 concentration rates of the road sections with roadside structures are calculated and assigned to the road section in the road network map with colours. Figure 3 shows the NO 2 pollution in the year 2015 assessed with PROKAS. The pollution level of each section in the main road network is determined. ...
Context 2
... highest NO 2 immission loads with more than 60 µg/m³ occur on 24 km (5 % of the main road network). The map in Figure 3 shows that most of the high polluted street segments are located within the middle ring road (Mittlerer Ring). A similar map of the immission situation in 2015 in Munich is published on the website of Regional government of Upper Bavaria (Regierung von Oberbayern, 2017). ...
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During the months of March and April 2020 we witnessed the largest-scale experiment in history in terms of air quality in cities. Any prediction of this experiment's results may be obvious to science, as it was totally expected, the air quality has improved substantially. Simply stated, it comes as no surprise. The lockdown has made it possible to...
Citations
... In the VEU scenarios, emission factors consider diverse vehicle fleets based on size, engine distribution, and technologies. By 2040, HBEFA assumes EURO 6 conformity for gas and diesel vehicles (Volker et al., 2020), aligned with Gerstenberger & Listl (2019). HBEFA also provides emission factors for Hybrid, PHEV, and BEV technologies, including energy consumption (Seum et al., 2019a). ...
This study explores the impact of emerging vehicle technologies on direct urban traffic emissions. It investigates emission reduction potential from shifts in fleet compositions and modal choices, especially considering climate change. To achieve this, three key research areas are explored for historical, current, and future scenarios (up to 2050): mode choice, emission factors for different vehicle categories, and diverse vehicle propulsion technologies. The estimation of the modal split is pivotal, developing a methodology utilizing Stated Preference survey data, discrete choice modeling, Monte Carlo simulations, and macroscopic traffic simulations. Future scenarios derive from the reference year’s modal split, and emission factors and fleet compositions are predetermined via an extensive literature review, aiding the assessment of their respective emissions. A subsequent sensitivity analysis identifies the impact of specific parameters on emissions, guiding future research focus. Study results underscore differences in greenhouse gas emissions and primary air pollutants between base and future scenarios.
... In the case of conventional vehicle technologies of gasoline and diesel, the HBEFA emission factors were expanded for the year 2040, assuming that all vehicles will be EURO 6 emission class(Volker et al., 2020). This assumption is also demonstrated byGerstenberger & Listl, (2019), ...
The objective of this master thesis is to understand the impact of new vehicle technologies on the direct emissions due to traffic volumes in urban areas. This research aims to investigate the potential reduction in future emissions due to the change in fleet compositions and the modal shift, of the climate change effects. For this reason, three research fields are evaluated for historical and the current situation, as well as for future scenarios till 2050: the mode choice model (or modal split), the emission model (emission factors for each vehicle category), and the various vehicle technologies regarding the propulsion system of the vehicle (gasoline, diesel, electric, etc.). The estimation of the modal split is important here, and thus a methodology is developed by using data from a Stated Preference survey and discrete choice modeling in combination with Monte Carlo simulations and macroscopic traffic simulations. The resulted modal split of the reference year is used to generate scenarios for the future. Moreover, based on the literature review, emission factors and fleet compositions were defined for future scenarios to be evaluated concerning their emissions. Finally, a sensitivity analysis followed to investigate how specific parameter affects the results of emissions, and where the focus should be given in the future.
Overall, the results include the greenhouse gas emissions and the main air pollutants for each historical and future scenario, as well as for the sensitivity analysis scenarios. A conclusion part follows to interpret the results, analyze the main findings, and propose further research work for investigation in the future.
... After the lockdown, Ningbo began to resume economic production, NO 2 emissions increased, and NO 2 concentration increased significantly and reached the same level as the previous year (Figure 5c). NO2 in ambient air mainly comes from the combustion of fossil fuels, such as ship and vehicular exhausts and industrial activities [32,33]. NO2 concentration is considered to be an indicator of anthropogenic pollution as it mainly arises from anthropogenic sources and not biogenic emission [34,35]. ...
... The significant decrease of NO2 concentration can be attributed to the reduction of emissions from ship-related air pollutants (e.g., freighters and heavy trucks), local vehicle exhaust and industrial emissions during the lockdown. The decline of NO2 concentration NO 2 in ambient air mainly comes from the combustion of fossil fuels, such as ship and vehicular exhausts and industrial activities [32,33]. NO 2 concentration is considered to be an indicator of anthropogenic pollution as it mainly arises from anthropogenic sources and not biogenic emission [34,35]. ...
Ningbo is a major coastal city in the Yangtze River Delta region, China, with the largest cargo capacity in the world. We conducted a field campaign in Ningbo to measure the impact of the COVID-19 lockdown on air pollutants including NO2, O3 and CO from 21 January to 23 March 2020, using a home-made low-cost sensor package. The average concentrations of NO2, O3 and CO were observed to be 7.2, 37.5 and 648.5 ppb, respectively, during the lockdown. Compared with the previous year, the concentrations of NO2 and CO decreased by 63.1% and 6.9%, while the concentration of O3 increased by 37.9%. The significant reduction of NO2 concentration may be attributed to the reduced emissions of freighters and heavy trucks with lower port cargo throughput, which led to a decrease of NO concentration. The increase of O3 concentration was probably due to the lower titration of O3 by NO. After the lockdown, the concentrations of O3 and NO2 increased by 15.5% and 143.1%, respectively, compared with those during the lockdown. The temporal variations of the concentrations of NO2, O3 and CO measured by the sensor package were coincident with those obtained by the reference apparatus, which proves the sensor package to be suitable for air quality monitoring in field campaigns. This is the first time that a dramatic decrease in NO2 concentration in a coastal city due to a lockdown has been reported.
... However, this study estimates vehicular emissions of NO x and PM. Gerstenberger et al. considered how changing passenger vehicle composition affects NO 2 emissions [26]. Traffic volumes were used to calculate NO 2 emissions within a road network. ...
This study reports the likely real-world effects of fleet replacement with electric vehicles (EVs) and higher efficiency EURO 6 vehicles on the exhaustive emissions of NOx, PM, and CO2 in the seven boroughs of the West Midlands (WM) region, UK. National fleet composition data, local EURO distributions, and traffic compositions were used to project vehicle fleet compositions for different roads in each borough. A large dataset of real-world emission factors including over 90,000 remote-sensing measurements, obtained from remote sensing campaigns in five UK cities, was used to parameterize the emission profiles of the studied scenarios. Results show that adoption of the fleet electrification approach would have the highest emission reduction potential on urban roads in WM boroughs. It would result in maximum reductions ranging from 35.0 to 37.9%, 44.3 to 48.3%, and 46.9 to 50.3% for NOx, PM, and CO2, respectively. In comparison, the EURO 6 replacement fleet scenario would lead to reductions ranging from 10.0 to 10.4%, 4.0 to 4.2%, and 6.0 to 6.4% for NOx, PM, and CO2, respectively. The studied mitigation scenarios have higher efficacies on motorways compared to rural and urban roads because of the differences in traffic fleet composition. The findings presented will help policymakers choose climate and air quality mitigation strategies.
... However, this study estimates vehicular emissions of NOx and PM. [26] considered how changing passenger vehicle composition affects NO2 emissions. Traffic volumes were used to calculate NO2 emissions within a road network. ...
This study reports the likely real-world effects of fleet replacement with electric vehicles (EVs) and higher efficiency EURO6 vehicles on the exhaust emissions of NOx, PM, and CO2 in the seven boroughs of the West Midlands (WM) region, UK. National fleet composition data, local EURO distributions and traffic compositions were used to project vehicle fleet compositions for different roads in each borough. A large dataset of real-world emission factors including over 90,000 remote-sensing measurements, obtained from remote sensing campaigns in five UK cities, was used to parameterise the emission profiles of the studied scenarios. Results show that adoption of the fleet electrification approach would have the highest emission reduction potential on urban roads in WM boroughs. It would result in maximum reductions ranging from 35.0-37.9%, 44.3-48.3%, 46.9-50.3% for NOx, PM, and CO2, respectively. In comparison, the EURO6 replacement fleet scenario would lead to reductions ranging from 10.0-10.4%, 4.0-4.2%, and 6.0-6.4% for NOx, PM, and CO2, respectively. The studied mitigation scenarios have higher efficacies on motorways than on rural and urban roads because of the differences in traffic fleet composition. The findings presented will help policymakers choose climate and air quality mitigation strategies.
This study based on daily data of six major pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , CO and O 3 ) from 2016 to 2020, the spatiotemporal variation characteristics of air quality in Panzhihua and its surrounding cities were analyzed. On this basis, trajectory model is used to analyze the origin and direction of migration of the pollutants in the days with high pollution degree, so as to find a method to prevent and control the air pollution in the cities with special geographical location. The results show that the concentration of pollutants in the study area showed an overall downward trend, but Ozone showed an opposite trend. The air quality in the study area has been significantly improved. Air quality was the best in 2018, followed by 2020. The annual variation trend of PM 2.5 , PM 10 , SO 2 , NO 2 and CO is U-shaped (flat W), while the O 3 is M-shaped. In addition, the monthly average concentration of pollutants in Panzhihua is higher than these in its surrounding cities. O 3 has a significant correlation with its various precursor pollutants, and the air pollution situation is complex and diverse. According to the analysis of pollutant diffusion trajectory, the direction of pollution source in Panzhihua city is southwest and the diffusion direction is east and southeast.
