Assessment of potential improvements on regional air quality modelling related with implementation of a detailed methodology for traffic emission estimation

Coelho, Margarida C.; Fontes, Tânia; Pereira, S.; Tchepel, Oxana; Dias, Daniela; Sá, E.; Amorim, Jorge Humberto; Borrego, Carlos

doi:10.1016/j.scitotenv.2013.09.042

Cited by 55 publications

(23 citation statements)

References 40 publications

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“…The aim of this study is to develop a link-based trafficrelated emission inventory of Tehran using a combination of traffic and emission rates modeling [33][34][35][36]. The Tehran traffic conditions were investigated comprehensively by the Tehran Comprehensive Transportation and Traffic Study (TCTTS) Company using modeling and measurement techniques.…”

Section: Introductionmentioning

confidence: 99%

The Relative Contributions of Mobile Sources to Air Pollutant Emissions in Tehran, Iran: an Emission Inventory Approach

Shahbazi

Reyhanian

Hosseini

et al. 2016

Emiss. Control Sci. Technol.

113

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Tehran, a city with 8.5 million inhabitants, has suffered from rapid and unplanned urbanization in recent years resulting in substantial environmental impacts perhaps foremost of which is poor air quality. A major source of air pollution is emissions from mobile vehicles; therefore, having an accurate and comprehensive mobile source emission inventory is essential for decision-makers to develop mitigating strategies. The aim of this study is to determine the relative contributions of specific mobile sources to key air pollutants through the development of an emissions inventory for mobile sources in the city of Tehran using the International Vehicle Emissions (IVE) model. Tehran traffic data were acquired to obtain link level emission rates, using IVE emission rates. The developed emission inventory was evaluated using Tehran gasoline sales data. The results indicate that the sources of carbon monoxide (CO), volatile organic compound (VOC), nitrogen oxide (NO x ), and sulfur oxide (SO x ) emissions are mainly passenger cars. The contribution of emissions of CO, VOCs, and particulate matter (PM) from motorcycles to the total traffic emissions is more than 15, 31, and 12 %, respectively. Despite the fact that medium and heavy-duty vehicles (minibuses, buses, and trucks) only comprise 2.4 % of the Tehran fleet, they contribute more than 41, 64, and 85 % of the NO x , SO x , and PM emissions, respectively. Analyzing the distribution of the aggregated emission of pollutants shows that emissions are mostly higher in central zones due to the high traffic rate of passenger cars, taxis, motorcycles, and buses.

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Section: Introductionmentioning

confidence: 99%

The Relative Contributions of Mobile Sources to Air Pollutant Emissions in Tehran, Iran: an Emission Inventory Approach

Shahbazi

Reyhanian

Hosseini

et al. 2016

Emiss. Control Sci. Technol.

113

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“…AERMOD makes distribution calculations by using the meteorological characteristics of the study area, including data such as chimney height and diameter, emission temperature, pollutant exit velocity and air temperature turbulence, and wind speed and direction, and can be used in rural and urban areas, plain and complex terrains, and in multiple sources such as point, line, area, and volume [8][9][10][11][12][13][14][15][16][17][18]. The AERMOD program needs hourly surface and upper air layer data in order to be able to make these calculations [9].…”

Section: Aermodmentioning

confidence: 99%

“…The program includes algorithms that can calculate the Planetary Boundary Layer parameters with data such as friction velocity, Monin-Obukhov length, transmission speed and temperature scale, mixing height, and surface heat flux. Furthermore, this program can be used in studies conducted at simple and plain terrains as well as complex terrains [9][10][11][12][13][14][15][16][17][18][19]. AERMOD is composed of two scripts including AERMAP (a terrain data preprocessor) and AERMET (a meteorological data preprocessor).…”

Section: Aermodmentioning

confidence: 99%

“…In recent years these data have been systematized in air quality modellings and increasingly used in complex estimations of concentrations in air. However, despite the complexities behind these developed models, accuracy and precision in the results are associated with the emission inventories generally used as input data in the model [10].…”

Section: Introductionmentioning

confidence: 99%

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Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions

Demirarslan¹,

Doğruparmak²

2016

Pol. J. Environ. Stud.

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Air quality modellings are highly useful systems used to investigate the possible impact of emissions diffusing into the atmosphere in any area they might have on that area. There are many modelling methods whose capacities are limited by their advantages and disadvantages or the equipment they use. In this study, therefore, both steady-state models (AERMOD and ISCST-3) and the Lagrangian model (CALPUFF) are used. This study has two purposes: one is to specify performance of the models. Performances were determined with various statistical methods such as fractional bias (FB), mean squared error (MSE), and geometric mean bias (MG). The other purpose of this study is to evaluate temporal and spatial variations of point (P), area (A), and line (L) -sourced CO and NO x emissions in the research area by using the modelling methods. The district of Körfez, which is one of the districts of the province of Kocaeli, was chosen as the study area.When the results obtained with modelling all P and A sources by three programs are analyzed, the highest annual concentration AERMOD, ISCST-3, and CALPUFF were found as 128.82, 86.96, and 201.30 µg/m 3 for CO, and 7.56, 26.31, and 6.10 µg/m 3 for NO x , respectively. On the other hand, when the results obtained with modelling all P and A and L sources by two programs are investigated, the highest annual concentration AERMOD and ISCST-3 were found to be 155.12, 92.46 µg/m 3 for CO, and 166.93 and 89.98 µg/m 3 for NO x , respectively. When contributions of the pollutant sources on pollution are evaluated, it was observed that area sources and line sources are more predominant than other sources for CO and NO x emissions. It was observed by analyzing the diffusion maps that residential areas in the district are more concentrated. Therefore, in the study the predicted and observed values were also compared with national and international limit values and determined to meet these limit values. According to the results obtained by evaluation of performances of the models with FB, MS, and MG statistical methods, performance sorting for NO x emissions was found to be ISCST-3 > CALPUFF > AERMOD, while for CO emissions it is given as

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“…Thus, vehicle emission inventories are a simple and needed approach that would provide a baseline estimate of on-road emissions on several scales. This information is essential to areas with incomplete or nonexistent monitoring networks (Nagpure and Gurjar, 2012) and to constrain pollutants surface fluxes for numerical air quality models (Coelho et al, 2014;Lozhkina and Lozhkin, 2015;Vara-Vela et al, 2016). As a means to minimize this gap in monitoring network, some studies suggested in general, two different approaches: top-down and bottom-up.…”

Section: Introductionmentioning

confidence: 99%

MOVEIM v1.0: Development of a bottom-up motor vehicular emission inventories for the urban area of Manaus in central Amazon rainforest

Teixeira

Freitas

Correia

et al. 2018

Preprint

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Abstract.Emissions of gases and particulates in urban areas are associated with a mixture of various sources, both natural and anthropogenic. Understanding and quantifying these emissions is necessary in studies of climate change, local air pollution issues and weather modification. Studies have highlighted that the transport sector is key to closing the world's emissions gap. 15Vehicles contribute substantially with the emission of carbon dioxide (CO 2 ), carbon monoxide (CO), nitrogen oxides (NO x ), nonmethane hydrocarbon (NMHC), particulate matter (PM), methane (CH 4 ), hydrofluorocarbon (HFC) and nitrous oxide (N 2 O).Several studies show that vehicle emission inventories are an important approach to providing a baseline estimate of on-road emissions in several scales, mainly in urban areas. This approach is essential to areas with incomplete or non-existent monitoring networks as well as for air quality models. Conversely, the direct downscale of global emission inventories in chemical transport 20and air quality models may not be able to reproduce the observed evolution of atmospheric pollution processes at finer spatial scales. To address this caveat, we developed a bottom-up vehicular emission inventory along the 258 main traffic routes from Manaus, based on local vehicle fleet data and emission factors (EFs). The results show that the light vehicles are responsible for the largest fraction of the pollutants, contributing 2.6, 0.87, 0.32, 0.03, 456 and 0.8 ton/h of CO, NO x , CH 4 , PM, CO 2 and NMHC, respectively. Including the emissions of motorcycles, buses and trucks, our total estimation of the emissions is 4.1, 1.0 , 25 0.37, 0.07, 63.5 and 2.56 ton/h, respectively. We also noted that light vehicles accounted for about 62.8%, 84.7%, 87.9%, 45.1%, 71.8%, and 33.9% and motorcycles in the order of 32.3 %, 6.5 %, 12.1 %, 6.2 %, 14.8 %, 8.7 %, respectively. Nevertheless, we can highlight the bus emissions which are around 35.7% and 45.3 % for NMHC and PM. Our results indicate a better distribution over the domain reflecting the influences of standard behavior of traffic distribution per vehicle category. Finally, this inventory provides more detailed information to improving the current understanding of how vehicle emissions contribute to the ambient 30 pollutant concentrations in Manaus and their impacts on regional climate changes. This work will also contribute to improved air quality numerical simulations, provide more accurate scenarios for policymakers and regulatory agencies to develop strategies for controlling the vehicular emissions, and, consequently, mitigate associated impacts on local and regional scales of the Amazon ecosystems. 35Key words: Vehicle emission inventories, bottom-up approach, urban air pollution, Amazon forest Geosci. Model Dev. Discuss., https://doi

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Assessment of potential improvements on regional air quality modelling related with implementation of a detailed methodology for traffic emission estimation

Cited by 55 publications

References 40 publications

The Relative Contributions of Mobile Sources to Air Pollutant Emissions in Tehran, Iran: an Emission Inventory Approach

The Relative Contributions of Mobile Sources to Air Pollutant Emissions in Tehran, Iran: an Emission Inventory Approach

Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions

MOVEIM v1.0: Development of a bottom-up motor vehicular emission inventories for the urban area of Manaus in central Amazon rainforest

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