Effect of Carbon Emission from Road Transportation When EEC Project Started In 2020

Bamrungwong, Natthakrit; Vongmanee, Varin; Rattanawong, Wanchai

doi:10.2139/ssrn.3513219

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“…A study by Zhang [22] was then published in 2019 focusing on pollution from NO x , SO 2 and particulate matter (PM) released by heavy-duty diesel trucks (HDDTs) in China, within which the economical and societal factors are factored in to estimate the actual pollution level caused by such transports. Then, in 2019, Bamrungwong [23][24][25] conducted a study on calculation of CO 2 emission by road transportation and its estimated environmental impact when the eastern economic corridor (EEC) comes into effect in 2020. The study, however, factors in only the number of vehicles already active in the target area and predicts the actual number of vehicles when EEC begins using the growth rate of the government-supported new s-curve as a reference, with pollution statistics collected to be used in planning for measures to combat health effects residents of the EEC area are predicted to suffer from.…”

Section: Carbon Dioxide Emission (Co 2 ) and Road Slope Conditionmentioning

confidence: 99%

The Development of a CO2 Emission Coefficient for Medium- and Heavy-Duty Vehicles with Different Road Slope Conditions Using Multiple Linear Regression, and Considering the Health Effects

2020

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The current studies on carbon dioxide (CO2) emissions and the impacts on public health focus mainly on evaluating CO2 emissions from two types of emission sources. The first is a fixed source type from industrial plants, which can be controlled or easily evaluated. The second is a mobile source type from the transport sector, especially from medium- and heavy-duty vehicles (MHDVs), which produce high emissions. However, the common methods of evaluation of the average value of CO2 emissions per kilometer of a vehicle use a general Intergovernmental Panel on Climate Change (IPCC) model that does not consider the topography or road conditions. This affects the accuracy of CO2 emission assessments and, in turn, affects the accuracy of any analysis needed to establish health policies and the management of public health within the affected area. In this paper, therefore, we present the development of emission coefficient calculations with varying topography conditions for MHDVs with consideration of the health effects on the populace. The study area was the Asian highway network in Thailand that passes through all regions and is geographically diverse. Data were collected from the Department of Highway’s records, global positioning system (GPS) and electronic control unit (ECU) with data consisting of road data, slope, distance, traffic level and vehicle weight, as well as fuel consumption along the transportation route. To analyze and map out the correlation of the CO2 emission coefficients for each road slope, we determined the coefficient of the CO2 emissions using multiple linear regression analysis and validated this using Huber–White robust standard errors for heteroscedasticity. This method was more cost-efficient and time-efficient compared to the conventional approaches. We also created CO2 emission maps with risk points for health effects, and we propose policy designs and plans to manage the traffic level in each of these areas prone to higher levels of such emissions.

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Section: Carbon Dioxide Emission (Co 2 ) and Road Slope Conditionmentioning

confidence: 99%