scholarly journals Road Traffic Dynamic Pollutant Emissions Estimation: From Macroscopic Road Information to Microscopic Environmental Impact

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 53
Author(s):  
Giovanni De Nunzio ◽  
Mohamed Laraki ◽  
Laurent Thibault
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Estimation Error ◽  
Driving Behavior ◽  
Pollutant Emissions ◽  
Road Segment ◽  
Traffic Information ◽  
Volume Data ◽  
Modeling Framework ◽  
Boundary Parameter

Air pollution poses a major threat to health and climate, yet cities lack simple tools to quantify the costs and effects of their measures and assess those that are most effective in improving air quality. In this work, a complete modeling framework to estimate road traffic microscopic pollutant emissions from common macroscopic road and traffic information is proposed. A machine learning model to estimate driving behavior as a function of traffic conditions and road infrastructure is coupled with a physics-based microscopic emissions model. The up-scaling of the individual vehicle emissions to the traffic-level contribution is simply performed via a meta-model using both statistical vehicles fleet composition and traffic volume data. Validation results with real-world driving data show that: the driving behavior model is able to maintain an estimation error below 10% for relevant boundary parameter of the speed profiles (i.e., mean, initial, and final speed) on any road segment; the traffic microscopic emissions model is able to reduce the estimation error by more than 50% with respect to reference macroscopic models for major pollutants such as NOx and CO2. Such a high-resolution road traffic emissions model at the scale of every road segment in the network proves to be highly beneficial as a source for air quality models and as a monitoring tool for cities.

scholarly journals Estimation of emissions of air pollutants in the Krapina-Zagorje county

2019 ◽  
Vol 9 (1) ◽  
pp. 12-20
Author(s):  
Božica Šorgić ◽  
Vladimir Kušan ◽  
Igor Tošić ◽  
Bojana Borić ◽  
Hrvoje Pandža
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Pollutant Emissions ◽  
Protection Measures ◽  
Greenhouse Gas Inventories ◽  
Mitigation And Adaptation ◽  
Road Traffic Emissions ◽  
Ipcc Guidelines ◽  
Sulphur Oxides ◽  
National Greenhouse Gas Inventories

The Program for the protection of air quality, ozone layer, climate change mitigation and adaptation of the Krapina-Zagorje County is prepared in accordance with the Article 12 of the Air Protection Act (OG 130/11, 47/14, 61/17, 118/18). The Program sets targets and measures by priority sectors, deadlines and responsible authorities for measures implementation over a five-year period in the County. For the purpose of defining protection measures, based on available data, estimation of annual emissions of pollutants into air was performed: nitrogen oxides, carbon monoxide, sulphur oxides, particles, volatile organic compounds, ammonia, carbon dioxide, methane and dinitrogen monoxide from the main sectors. Emissions were estimated using the EMEP/EEA methodology and 2006 IPCC Guidelines for National Greenhouse Gas Inventories methodology. Road traffic emissions were estimated using DEFRA/DECC methodology. Based on the results on estimated pollutant emissions in the County, appropriate measures have been defined for the protection and improvement of air quality.

scholarly journals Assessing the Impact of Road Traffic Reorganization on Air Quality: A Street Canyon Case Study

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 695
Author(s):  
Marek Bogacki ◽  
Robert Oleniacz ◽  
Mateusz Rzeszutek ◽  
Paulina Bździuch ◽  
Adriana Szulecka ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Road Transport ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Maximum Speed ◽  
Commercial Vehicles ◽  
The Road ◽  
Management Changes ◽  
The Impact

One of the elements of strategy aimed at minimizing the impact of road transport on air quality is the introduction of its reorganization resulting in decreased pollutant emissions to the air. The aim of the study was to determine the optimal strategy of corrective actions in terms of the air pollutant emissions from road transport. The study presents the assessment results of the emission reduction degree of selected pollutants (PM10, PM2.5, and NOx) as well as the impact evaluation of this reduction on their concentrations in the air for adopted scenarios of the road management changes for one of the street canyons in Krakow (Southern Poland). Three scenarios under consideration of the city authorities were assessed: narrowing the cross-section of the street by eliminating one lane in both directions, limiting the maximum speed from 70 km/h to 50 km/h, and allowing only passenger and light commercial vehicles on the streets that meet the Euro 4 standard or higher. The best effects were obtained for the variant assuming banning of vehicles failing to meet the specified Euro standard. It would result in a decrease of the yearly averaged PM10 and PM2.5 concentrations by about 8–9% and for NOx by almost 30%.

scholarly journals Road Traffic Emission Inventory in an Urban Zone of West Africa: Case of Yopougon City (Abidjan, Côte d’Ivoire)

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1111
Author(s):  
Madina Doumbia ◽  
Adjon A. Kouassi ◽  
Siélé Silué ◽  
Véronique Yoboué ◽  
Cathy Liousse ◽  
...  
Keyword(s):  
Public Transportation ◽  
Road Traffic ◽  
Field Measurements ◽  
Mitigation Strategies ◽  
Pollutant Emissions ◽  
Volume Data ◽  
Traffic Emission ◽  
High Emission ◽  
Vehicle Fleet ◽  
Reduce Emissions

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.

scholarly journals Modeling framework for exploring emission impacts of alternative future scenarios

2010 ◽  
Vol 3 (4) ◽  
pp. 2021-2050 ◽  
Author(s):  
D. H. Loughlin ◽  
W. G. Benjey ◽  
C. G. Nolte
Keyword(s):  
Growth Factors ◽  
Air Quality ◽  
Energy System ◽  
Air Pollutant ◽  
Population Projections ◽  
Pollutant Emissions ◽  
Emission Scenarios ◽  
Modeling Framework ◽  
Emission Growth ◽  
Carbon Dioxide Co2

Abstract. This article presents an approach for creating anthropogenic emission scenarios that can be used to simulate future regional air quality. The approach focuses on energy production and use since these are principal sources of air pollution. We use the MARKAL model to characterize alternative realizations of the US energy system through 2050. Emission growth factors are calculated for major energy system categories using MARKAL, while growth factors from non-energy sectors are based on economic and population projections. The SMOKE model uses these factors to grow a base-year 2002 inventory to future years through 2050. The approach is demonstrated for two emission scenarios: Scenario 1 extends current air regulations through 2050, while Scenario 2 applies a hypothetical policy that limits carbon dioxide (CO2) emissions from the energy system. Although both scenarios show significant reductions in air pollutant emissions through time, these reductions are more pronounced in Scenario 2, where the CO2 policy results in the adoption of technologies with lower emissions of both CO2 and traditional air pollutants. The methodology is expected to play an important role in investigations of linkages among emission drivers, climate and air quality by the U.S. EPA and others.

scholarly journals ESP v1.0: methodology for exploring emission impacts of future scenarios in the United States

2011 ◽  
Vol 4 (2) ◽  
pp. 287-297 ◽  
Author(s):  
D. H. Loughlin ◽  
W. G. Benjey ◽  
C. G. Nolte
Keyword(s):  
United States ◽  
Growth Factors ◽  
Air Quality ◽  
Air Pollutants ◽  
Energy System ◽  
The United States ◽  
Air Pollutant ◽  
Population Projections ◽  
Pollutant Emissions ◽  
Modeling Framework

Abstract. This article presents a methodology for creating anthropogenic emission inventories that can be used to simulate future regional air quality. The Emission Scenario Projection (ESP) methodology focuses on energy production and use, the principal sources of many air pollutants. Emission growth factors for energy system categories are calculated using the MARKAL energy system model. Growth factors for non-energy sectors are based on economic and population projections. These factors are used to grow a 2005 emissions inventory through 2050. The approach is demonstrated for two emission scenarios for the United States. Scenario 1 extends current air regulations through 2050, while Scenario 2 adds a hypothetical CO2 mitigation policy. Although both scenarios show significant reductions in air pollutant emissions through time, these reductions are more pronounced in Scenario 2, where the CO2 policy results in the adoption of technologies with lower emissions of both CO2 and traditional air pollutants. The methodology is expected to play an important role within an integrated modeling framework that supports the US EPA's investigations of linkages among emission drivers, climate and air quality.

A real-time push system on road traffic information

2014 ◽  
Author(s):  
Yang Xu ◽  
Zhang Zhenjiang ◽  
Liu Yun
Keyword(s):  
Real Time ◽  
Road Traffic ◽  
Traffic Information

scholarly journals Evolution of Gaseous and Particulate Pollutants in the Air: What Changed after Five Lockdown Weeks at a Southwest Atlantic European Region (Northwest of Spain) Due to the SARS-CoV-2 Pandemic?

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 562
Author(s):  
Jorge Moreda-Piñeiro ◽  
Joel Sánchez-Piñero ◽  
María Fernández-Amado ◽  
Paula Costa-Tomé ◽  
Nuria Gallego-Fernández ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Statistical Significance ◽  
Temporal Trends ◽  
Air Pollutant ◽  
Concentration Data ◽  
Southwest Atlantic ◽  
Pollutant Concentrations ◽  
Air Quality Monitoring Stations ◽  
Almost All

Due to the exponential growth of the SARS-CoV-2 pandemic in Spain (2020), the Spanish Government adopted lockdown measures as mitigating strategies to reduce the spread of the pandemic from 14 March. In this paper, we report the results of the change in air quality at two Atlantic Coastal European cities (Northwest Spain) during five lockdown weeks. The temporal evolution of gaseous (nitrogen oxides, comprising NOx, NO, and NO2; sulfur dioxide, SO2; carbon monoxide, CO; and ozone, O3) and particulate matter (PM10; PM2.5; and equivalent black carbon, eBC) pollutants were recorded before (7 February to 13 March 2020) and during the first five lockdown weeks (14 March to 20 April 2020) at seven air quality monitoring stations (urban background, traffic, and industrial) in the cities of A Coruña and Vigo. The influences of the backward trajectories and meteorological parameters on air pollutant concentrations were considered during the studied period. The temporal trends indicate that the concentrations of almost all species steadily decreased during the lockdown period with statistical significance, with respect to the pre-lockdown period. In this context, great reductions were observed for pollutants related mainly to fossil fuel combustion, road traffic, and shipping emissions (−38 to −78% for NO, −22 to −69% for NO2, −26 to −75% for NOx, −3 to −77% for SO2, −21% for CO, −25 to −49% for PM10, −10 to −38% for PM2.5, and −29 to −51% for eBC). Conversely, O3 concentrations increased from +5 to +16%. Finally, pollutant concentration data for 14 March to 20 April of 2020 were compared with those of the previous two years. The results show that the overall air pollutants levels were higher during 2018–2019 than during the lockdown period.

scholarly journals Bottom-Up Emission Inventory and Its Spatio-Temporal Distribution from Paved Road Dust Based on Field Investigation: A Case Study of Harbin, Northeast China

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Lili Li ◽  
Kun Wang ◽  
Zhijian Sun ◽  
Weiye Wang ◽  
Qingliang Zhao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Emission Inventory ◽  
Road Dust ◽  
Field Investigation ◽  
Pollutant Emissions ◽  
County Level ◽  
Bottom Up ◽  
Spatial Allocation ◽  
Paved Road

Road dust is one of the primary sources of particulate matter which has implications for air quality, climate and health. With the aim of characterizing the emissions, in this study, a bottom-up approach of county level emission inventory from paved road dust based on field investigation was developed. An inventory of high-resolution paved road dust (PRD) emissions by monthly and spatial allocation at 1 km × 1 km resolution in Harbin in 2016 was compiled using accessible county level, seasonal data and local parameters based on field investigation to increase temporal-spatial resolution. The results demonstrated the total PRD emissions of TSP, PM10, and PM2.5 in Harbin were 270,207 t, 54,597 t, 14,059 t, respectively. The temporal variation trends of pollutant emissions from PRD was consistent with the characteristics of precipitation, with lower emissions in winter and summer, and higher emissions in spring and autumn. The spatial allocation of emissions has a strong association with Harbin’s road network, mainly concentrating in the central urban area compared to the surrounding counties. Through scenario analysis, positive control measures were essential and effective for PRD pollution. The inventory developed in this study reflected the level of fugitive dust on paved road in Harbin, and it could reduce particulate matter pollution with the development of mitigation strategies and could comply with air quality modelling requirements, especially in the frigid region of northeastern China.

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

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