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Carbon footprint of road pavement rehabilitation: case study at KM 99.6 to KM 103.0 in Southbound along Sungai Petani Utara to Sungai Petani Selatan section N2, north-south expressway
No full textMaster of Science in Civil EngineeringSeveral challenges are facing the development of the industrial sector as a response to resource depletion, environment degradation, and climate change. These phenomena result from substantial carbon dioxide (CO₂) emission and increased carbon footprint. The transportation infrastructure sector consumes a large amount of energy and draws upon natural resources, and carbon footprint can be used to measure the amount of CO₂ from road, highway, or an overpass exerts on earth. CO₂ emissions comprise 95% of the total greenhouse gas (GHG) emissions. A carbon footprint is made up of two parts. The primary footprint is a measure of direct emissions, and the secondary footprint is a measure of indirect emissions from the entire life cycle of products. This research identifies and determines the amount of total carbon footprints of fuel used by machineries and quantity of materials used in the pavement rehabilitation of the PLUS Malaysia Berhad at highway site from Sungai Petani Utara to Sungai Petani Selatan km 99.60 – km 103.00 in the state of Kedah, Malaysia. The data for the research are collected from relevant site engineers through interviews and daily logbooks containing records of material and machinery used in pavement rehabilitation. This research adopts the life cycle assessment approach for evaluating the impact of carbon emission using the materials and machineries utilized in pavement rehabilitation. Results reveal that carbon footprints from materials come from quarry dust material, which emits the highest CO₂ producing 3247.91 tons of CO₂e, followed by cement, stone aggregate, and bitumen emit 251.15, 130.74, and 0.11 tons of CO₂e respectively. The dense bitumen macadam (DBM) layer emits the highest carbon footprint, accounting for 45% of carbon footprint emissions, followed by the asphaltic concrete wearing course (ACWC) layer, and asphaltic concrete binder course (ACBC) layer at CO₂ 28% and 27% respectively. Milling machinery emits the highest carbon footprint producing 478.14 tons fossil of CO₂e due to the highest engine capacity of 448.8 kW/h followed by the lorry DBM, lorry ACWC, and lorry dump truck at 459.47, 352.50, 314.64 tons fossil of CO₂e, respectively. The highest carbon footprint emissions are also observed from milling work task, accounting for 38% of total carbon emissions followed by the tasks in DBM, ACWC, and ACBC layers at 27%, 21% and 14% of CO₂ emission, respectively. The premix cutter machinery emits the lowest carbon footprint emission producing 2.64 tons fossil of CO₂e because of engine capacity is 9.5 kW/h, which is the lowest among the machineries. In the long run, these data contribute to improve methods for implementing policies that monitor and mitigate GHG emissions. As a contribution, the findings of this research are expected to assist contractors, town planners, academics, and policy makers in this field to lessen the carbon footprints in the road infrastructure system in Malaysi
Penilaian kualiti sumber air dan kesannya terhadap permintaan klorin
No full textMaster of Science in Civil EngineeringThis study aims to assess the quality of water resources in the Kedah North Canal, and its impact on chlorine demand in the Water Treatment Plant Arau Phase IV, Perlis. The study was conducted over 12 months from June 2014 to May 2015 based on the WQI, INWQS, and NSDWQ. The study found that the quality of water resources in the North Canal are in Class III. The main factors associated with this pollution is land use activities and the seasons change. Studies have shown that Pelubang, Jitra and Tunjang Station are major contributors of pollution such as ammonia, TSS, TOC, BOD, COD, turbidity, temperature, pH and DO. Iron and manganese pollution were the highest recorded at Tunjang and Jitra Station, while phosphate and nitrate pollution
concentrated in Tunjang and Padang Sera Station. Analysis of water quality in the Water Treatment Plant Arau Phase IV shows the changes of water quality resources with a significant impact on the chlorine demand when the value of r = 0.75 and r2 =
0.56. The average of chlorine demand in D1 Station (Intake), D2 (Aeration), D3 (Sedimentation) and D4 (Sand filtration) were 2.48 mg/L, 2.31 mg/L, 1.98 mg/L and 1.74 mg/L. Analysis of water quality parameters and chlorine demand also exhibits a
very strong relationship with r > 0.90, particularly by pH, ammonia, nitrate, phosphate, iron, manganese and TOC. This is followed by r > 0.70 by TSS, temperature, and turbidity, while DO exhibit the weakest correlation, r = 0.20. Multiple regression
analysis showed predictor parameters for chlorine demand in D1, D2, D3, and D4 each consisting of TSS, TOC, manganese and ammonia. The conclusion is, the combination of land use activities and seasonal changes can affect and impact on the quality of raw water resources in the North Canal, Kedah thus affecting the chlorine demand present in the water treatment process at the Water Treatment Plant Arau Phase IV, Perlis. The higher quality of water resources, chlorine demand will decline, but when low-quality water resources will increase of chlorine demand. Therefore, the effectiveness of
pollution control and water treatment process is very important to eliminate or minimize
the potential precursor to cause demand to ensure that chlorine treated water supplied to
consumers quality and safe
