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Abdelhaleem Khader
Department of Civil Engineering, An-Najah National University, Nablus 44830, Palestine

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Journal article
Published: 11 September 2019 in Atmosphere
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Few air pollutant studies within the Palestinian territories have been reported in the literature. In March–April and May–June of 2018, three low-cost, locally calibrated particulate monitors (AirU’s) were deployed at different elevations and source areas throughout the city of Nablus in Northern West Bank, Palestine. During each of the three-week periods, high but site-to-site similar particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) and less than 10 µm (PM10) concentrations were observed. The PM2.5 concentrations at the three sampling locations and during both sampling periods averaged 38.2 ± 3.6 µg/m3, well above the World Health Organization’s (WHO) 24 h guidelines. Likewise, the PM10 concentrations exceeded or were just below the WHO’s 24 h guidelines, averaging 48.5 ± 4.3 µg/m3. During both periods, short episodes were identified in which the particulate levels at all three sites increased substantially (≈2×) above the regional baseline. Air mass back trajectory analyses using U.S. National Oceanic and Atmospheric Administration’s (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model suggested that, during these peak episodes, the arriving air masses spent recent days over desert areas (e.g., the Saharan Desert in North Africa). On days with regionally low PM2.5 concentrations (≈20 µg/m3), back trajectory analysis showed that air masses were directed in from the Mediterranean Sea area. Further, the lower elevation (downtown) site often recorded markedly higher particulate levels than the valley wall sites. This would suggest locally derived particulate sources are significant and may be beneficial in the identification of potential remediation options.

ACS Style

Abdelhaleem Khader; Randal S. Martin. Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust Storms. Atmosphere 2019, 10, 539 .

AMA Style

Abdelhaleem Khader, Randal S. Martin. Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust Storms. Atmosphere. 2019; 10 (9):539.

Chicago/Turabian Style

Abdelhaleem Khader; Randal S. Martin. 2019. "Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust Storms." Atmosphere 10, no. 9: 539.

Journal article
Published: 28 August 2019 in Journal of the Air & Waste Management Association
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On-road vehicles have become a dominant source of air pollution and energy consumption in many parts of the world. As a result, estimating the amount of pollution from these vehicles and analyzing the factors affecting their emission is necessary to understand and manage ambient air quality. Traditionally, automobile emissions have been measured with dynamometer tests using representative driving cycles. A review of the related literature shows that there is a lack of real life, on-the-road testing of automobile emissions. Moreover, a few previous studies have directly discussed the impact of driver variability on emissions from the vehicles. This research analyzes the impacts of driver experience, gender, speed, and road grade on vehicle emissions through on-the-road testing experiment in Logan, Utah, USA during summer of 2016. The methodology of the research starts by selecting a representative car to perform the tests on. The next step was to choose test drivers representing four groups: young males, young females, experienced males, and experienced females. After that, the drivers were assigned a specified route that has different speed limits and grades. Emissions from the car exhaust (specifically carbon monoxide-CO, hydrocarbons-HC, and nitrogen oxides-NOx) in addition to the engines rotational speed (rpm), car speed, and exhaust temperature, were measured every second while driving on the specified route. Statistical analysis of the results shows that contrary to the common stereotypes, experienced drivers emitted 52% more HC and 49% more NOx than young drivers and female drivers, and male drivers emitted 14% more HC and 44% more NOx than female drivers. It also shows that CO emission is not significantly dependent on age, gender, nor driving conditions. Finally, driving through low-speed segments emits significantly higher HC (79%), while driving through uphill segments emits significantly higher (98%) NOx than driving through downhill segment. Implications: This study showed that there are significant differences in vehicular emissions among drivers from different genders and age. These differences should be taking into consideration in future emission modeling studies and regulatory scenarios.

ACS Style

Abdelhaleem I. Khader; Randal S. Martin. On-the-road testing of the effects of driver’s experience, gender, speed, and road grade on car emissions. Journal of the Air & Waste Management Association 2019, 69, 1182 -1194.

AMA Style

Abdelhaleem I. Khader, Randal S. Martin. On-the-road testing of the effects of driver’s experience, gender, speed, and road grade on car emissions. Journal of the Air & Waste Management Association. 2019; 69 (10):1182-1194.

Chicago/Turabian Style

Abdelhaleem I. Khader; Randal S. Martin. 2019. "On-the-road testing of the effects of driver’s experience, gender, speed, and road grade on car emissions." Journal of the Air & Waste Management Association 69, no. 10: 1182-1194.

Journal article
Published: 01 July 2014 in Environmental Modelling & Software
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ACS Style

Abdelhaleem I. Khader; Mac McKee. Use of a relevance vector machine for groundwater quality monitoring network design under uncertainty. Environmental Modelling & Software 2014, 57, 115 -126.

AMA Style

Abdelhaleem I. Khader, Mac McKee. Use of a relevance vector machine for groundwater quality monitoring network design under uncertainty. Environmental Modelling & Software. 2014; 57 ():115-126.

Chicago/Turabian Style

Abdelhaleem I. Khader; Mac McKee. 2014. "Use of a relevance vector machine for groundwater quality monitoring network design under uncertainty." Environmental Modelling & Software 57, no. : 115-126.