Air pollution emission effects of changes in transport supply: the case of Bogotá, Colombia

Mangones, Sonia C.; Jaramillo, Paulina; Rojas, Néstor Y.; Fischbeck, Paul S.

doi:10.1007/s11356-020-08481-1

Cited by 22 publications

(10 citation statements)

References 24 publications

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“…The empirical studies based on diverse samples provide evidence on transport and emission nexus. Timilsina and Shrestha (2009) for Asian economies, Chandran and Tang (2013) for ASEAN countries, Zhang and Nian (2013) for China, Saboori et al (2014) for OECD economies, Shahbaz et al (2015) for Tunisia, Saidi and Hammami (2017) for a panel of 75 economies, Danish et al (2018) and Shouket et al (2019) for Pakistan, Du et al (2019) for China, Ahmed et al (2020) for India, Isik et al (2020) for Turkey, Mangones et al (2020) for Columbia, Hossain et al (2020) for Bangladesh, and Go et al (2020) for Malaysia explored transport and environment nexus. These studies assume a symmetric relationship between transportation and emissions.…”

Section: Introductionmentioning

confidence: 99%

Pakistan management of green transportation and environmental pollution: a nonlinear ARDL analysis

Sohail

Ullah

Majeed

et al. 2021

Environ Sci Pollut Res

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Modern advances in nonlinear modeling have exposed that nonlinear models yield more robust results compared with linear models. Research on the effect of air-railway transportation on environmental pollution has now arrived into a new way of asymmetry analysis and captured the real issue among the nexus. This study aims to inspect the asymmetric impact of air-railway transportation on environmental pollution in Pakistan by using annual time series data from 1991 to 2019. The findings show that positive shock in air passenger carried and railway passenger carried increases carbon emissions, which implies that 1% increase in air passenger carried (railway passenger carried) enhances environmental pollution by 0.21% (0.32%) in long run in Pakistan. While positive shock in railway passengers carried increases environmental pollution and negative shock in railway passengers carried decreases the environmental pollution in the short run. The outcomes have also confirmed the short- and long-run asymmetries in Wald statistics. The findings are country-specific and it would be regionally specific.

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Section: Introductionmentioning

confidence: 99%

Pakistan management of green transportation and environmental pollution: a nonlinear ARDL analysis

Sohail

Ullah

Majeed

et al. 2021

Environ Sci Pollut Res

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“…Indeed, this term had a similar or very close magnitude between nearby monitoring stations. For the case of PM10, the following spatial distribution was identified in the megacity: northwestern (1,1,5), center-southwest (1,1,6-9), and southeast (1,1,4). In relation to the PM2.5 concentrations, the following spatial distribution was detected: north (1,1,10), center (1,1,4), and south-west (1,1,9).…”

Section: Spatial Distributionmentioning

confidence: 99%

“…For the case of PM10, the following spatial distribution was identified in the megacity: northwestern (1,1,5), center-southwest (1,1,6-9), and southeast (1,1,4). In relation to the PM2.5 concentrations, the following spatial distribution was detected: north (1,1,10), center (1,1,4), and south-west (1,1,9). This spatial distribution was possibly related to wind direction and speed, and land use [12].…”

Section: Spatial Distributionmentioning

confidence: 99%

“…Air pollution has become a public health problem of great magnitude, especially in the large cities of the world. The city of Bogotá, Colombia, is one of the Latin American cities with the highest air pollution due to its economic and social dynamics [1]; several air quality studies conducted in the megacity have reported significant associations between air pollutants such as particulate matter < 10 µm (PM10), particulate matter < 2.5 µm (PM2.5), and ozone (O3), and negative effects on human health [2]. Due to the air pollution risk in the megacity, environmental authorities use air quality modelling tools in order to establish actions and protocols for action in the face of alert and emergency episodes [3].…”

Section: Introductionmentioning

confidence: 99%

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Box-Jenkins stochastic models for studying air pollutants in a Latin American megacity

Pinzón-Hassan

Tique-Ortiz

Zafra-Mejía

2021

J. Phys.: Conf. Ser.

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The objective of this paper is to show the development of Box-Jenkins stochastic models to study the behavior of air pollutants concentrations in the megacity of Bogotá, Colombia. Information was collected from 10 stations in the city’s air quality monitoring network over a ten-year period. The temporal relationship between air pollutants, their spatial variation, and the occurrence of extreme pollution episodes was studied using Box-Jenkins models. The results showed that the moving average term of the models developed was the main indicator of spatial distribution for the daily pollutant concentrations. In the case of atmospheric particulate matter < 10 μm, the following spatial distribution was identified in the megacity: northwestern, center-southwest, and southeast. For atmospheric particulate matter < 2.5 μm: north, center, and southwest. For ozone: northwest, center, and south. Maximum hourly particulate matter concentrations were observed between 6-10 a.m., and between 11 a.m. - 4 p.m. for ozone. Monthly, the highest particulate matter concentrations were observed in February (14.1%), January (13.5%), and March (12.2%). In the context of atmospheric physics, this study was relevant for the following findings: The usefulness of Box-Jenkins models in simulating the temporal behavior of air pollutants, and for their adequate performance in detecting urban spatial trends.

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“…Consequently, the IVE model has no EF available for new vehicle technologies greater than Euro 5 entering Colombia, i.e., EF are available for private vehicles only up to Euro IV and for buses only up to Euro V with gasoline and diesel as fuels [30]. In contrast, the application of the COPERT model has increased [5,31] because it has been constantly updated (last update in 2021) and directly related to the inclusion of EF for new vehicle technologies [32].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Top-Down and Bottom-Up Road Transport Emissions through High-Resolution Air Quality Modeling in a City of Complex Orography

et al. 2021

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Vehicular emissions are a predominant source of pollution in urban environments. However, inherent complexities of vehicular behavior are sources of uncertainties in emission inventories (EIs). We compare bottom-up and top-down approaches for estimating road transport EIs in Manizales, Colombia. The EIs were estimated using a COPERT model, and results from both approaches were also compared with the official top-down EI (estimated from IVE methodology). The transportation model PTV-VISUM was used for obtaining specific activity information (traffic volumes, vehicular speed) in bottom-up estimation. Results from COPERT showed lower emissions from the top-down approach than from the bottom-up approach, mainly for NMVOC (−28%), PM10 (−26%), and CO (−23%). Comparisons showed that COPERT estimated lower emissions than IVE, with higher differences than 40% for species such as PM10, NOX, and CH4. Furthermore, the WRF–Chem model was used to test the sensitivity of CO, O3, PM10, and PM2.5 predictions to the different EIs evaluated. All studied pollutants exhibited a strong sensitivity to the emission factors implemented in EIs. The COPERT/top-down was the EI that produced more significant errors. This work shows the importance of performing bottom-up EI to reduce the uncertainty regarding top-down activity data.

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Air pollution emission effects of changes in transport supply: the case of Bogotá, Colombia

Cited by 22 publications

References 24 publications

Pakistan management of green transportation and environmental pollution: a nonlinear ARDL analysis

Pakistan management of green transportation and environmental pollution: a nonlinear ARDL analysis

Box-Jenkins stochastic models for studying air pollutants in a Latin American megacity

Comparison of Top-Down and Bottom-Up Road Transport Emissions through High-Resolution Air Quality Modeling in a City of Complex Orography

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