Developing an Optimization Model to Manage Unpaved Roads

Saha, Promothes; Ksaibati, Khaled

doi:10.1155/2017/9474838

Cited by 14 publications

(2 citation statements)

References 10 publications

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“…Low-income residential unpaved roads have no flood control infrastructure, poor drainage systems and lack traffic management infrastructures (Nkomo, 2016). They also have a high deterioration rate with a lifespan of less than one year (Saha and Ksaibati, 2017). This decreases overall air quality in surrounding areas as unpaved roads and sidewalks are an infinite source of loose soil particles, especially during non-rainy seasons.…”

Section: Discussionmentioning

confidence: 99%

The impact of vehicle parameters on road PM10 vehicle resuspended emissions: A case in South African low-income settlement

Nkosi,

Burger,

Pauw

et al. 2023

Clean Air J.

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About 70% of the roads in low-income settlements are unpaved and close (≤15m) to residents, thus a major source of ambientand indoor PM10 concentrations. International studies have suggested that decreasing vehicle speed and managing vehicle type onpaved or unpaved roads can reduce vehicle dust emissions. These mitigation strategies should be examined before being adoptedand gazetted into South African air quality management plans. This study aimed to characterise roads and traffic, emphasisingdetermining the impact of vehicle type on PM10 emissions. GIS was used to determine the proportion of paved and unpaved roads. Atraffic counter was used to monitor vehicles and to determine traffic composition, diurnal cycles, and average speed per road type.Field campaigns (summer; 6 days; 15 hrs per day) were carried out in Bokamoso to monitor PM10 concentration usinga TSI DustTrak DRX® real-time optical aerosol counter. The Box Model method quantifies vehicle PM10 emission factors for heavy-duty, medium-duty, and motor vehicles. About 0.88 km of road within Bokamoso is paved with a daily traffic volume of >2000, and 3.6 km is unpaved with >250 daily traffic volume. Paved road heavy-duty vehicle non-exhaust PM10 emissions reported a positive medium to strong coefficient of determination to vehicle speed increase with a coefficient of determination of 0.59. Even though there is a positive coefficient of determination between heavy-duty vehicle non-exhaust PM10 emission factors and speed on unpaved roads, it is weak (0.2) due to low and less variable vehicle speed. Motor vehicle paved and unpaved road non-exhaust emission factors showed no significant coefficient of determination with increased vehicle speed. Paved road non-exhaust emission factors were not significantly variable with vehicle type. They ranged between an average of 0.15-0.18 g/km/h, with motor vehicles reporting an average of 0.18 g/km/h while heavy-duty vehicles reported an average of 0.15 g/km/h. On the contrary, unpaved road non-exhaust traffic PM10 emissions ranged between 0.16-0.3 g/km/h. The emission factors presented may be used to model vehicle traffic emissions, improve on-road vehicle dust emissions impact assessment and as a guide when deciding on local applicable road dust mitigation strategies

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Section: Discussionmentioning

confidence: 99%

The impact of vehicle parameters on road PM10 vehicle resuspended emissions: A case in South African low-income settlement

Nkosi,

Burger,

Pauw

et al. 2023

Clean Air J.

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“…Most studies on PMS have considered pavement deterioration as nondeterministic variable [23][24][25][26]. Durango-Cohen took pavement deterioration models as nondeterministic models and evaluated the M&R policies efficiently when imprecise pavement deterioration models are available [27].…”

Section: Introductionmentioning

confidence: 99%

A Two‐Stage Stochastic Model for Maintenance and Rehabilitation Planning of Pavements

Ameri

Jarrahi

Haddadi

et al. 2019

Mathematical Problems in Engineering

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Pavement maintenance and rehabilitation (M&R) plan for maintaining the pavement quality in an acceptable level has direct influence on the required budget. Deterministic budgeting is an unrealistic assumption, so, in this study, a two-stage stochastic model using integer programming is developed to address uncertainty in budgeting. Another aim of this study is to develop an executive model that considers a broad range of parameters at network level maintenance and rehabilitation planning. While having too many details in planning problems makes them more complicated, some restrictions called “technical constraints” were considered to reduce solution time of solving procedure as well as improve M&R activities assignment efficiency. Comparing results of the stochastic model with a deterministic model for a case study revealed that the two-stage stochastic model led to increased total cost compared to the deterministic one due to considering probability in budgeting. However, the developed model provides several M&R plans that are compatible with budget variation.

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Enviro-Health Consequences of Unpaved Road Deterioration in Liberia: Implications for Development

Apeh¹,

Onyekuru

Chiemela

et al. 2022

Climate Change Management

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Developing an Optimization Model to Manage Unpaved Roads

Cited by 14 publications

References 10 publications

The impact of vehicle parameters on road PM10 vehicle resuspended emissions: A case in South African low-income settlement

The impact of vehicle parameters on road PM10 vehicle resuspended emissions: A case in South African low-income settlement

A Two‐Stage Stochastic Model for Maintenance and Rehabilitation Planning of Pavements

Enviro-Health Consequences of Unpaved Road Deterioration in Liberia: Implications for Development

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