Current Issue [Vol. 12, No. 10] [October 2026]

This study assessed greenhouse gas emissions from white oak cladding and Louro Gamela decking manufactured in southern Vietnam using factory records and secondary life cycle inventory data. The reference unit was 1 m³ of each finished product. The scope covered production (A1–A3), end-of-life processes (C1–C4), and recovery benefits and burdens (D). Production impacts were approximately 1.05E+03 kg CO₂e/m³ for cladding and 6.60E+02 kg CO₂e/m³ for decking. Manufacturing contributed about 66% of each production result, while fossil contributions represented approximately 98% of A1–A3. End-of-life impacts were approximately 1.80E+02 and 1.16E+02 kg CO₂e/m³, respectively, with disposal as the largest contributor. Module D credits were –3.71E+01 and –2.36E+01 kg CO₂e/m³. Supplementary balances including these credits were approximately 1.19E+03 and 7.53E+02 kg CO₂e/m³. Reported electricity scenario results differed from the production baselines by approximately −2% to −3% and +8%. Comparisons with wood product EPDs and research reporting per cubic metre highlighted differences in service life, recovery scenarios, and biogenic carbon accounting that limit direct performance ranking. The study contributes factory-specific inventories for two finished wood applications in southern Vietnam and identifies manufacturing as the principal hotspot for assessing energy efficiency and material use.
Keywords: Carbon footprint, Life cycle assessment, Louro Gamela decking, White oak cladding, Wood products

Microplastics (MPs) are now reported from almost every marine habitat, but most fish surveys have examined the digestive tract, a tissue that is usually discarded before cooking. This study measured microplastics in the edible dorsal muscle of the tille trevally (Caranx tille), landed at the Junglighat fish landing centre in Sri Vijaya Puram (formerly Port Blair), South Andaman, India. Fifty-six fish (total length 17.5–20.3 cm; body weight 85.73–100.90 g) were collected on four occasions between April 2023 and October 2024. A 5 g sample of muscle tissue from each fish was digested in 10% potassium hydroxide, filtered and examined under a stereo-microscope, and the recovered particles were classified by colour, shape, size and polymer type. After correction for a single fibre found in eleven procedural blanks, 130 particles were attributed to muscle tissue, equal to 2.32 ± 1.44 items individual-1 and 0.46 ± 0.29 items g-1 wet weight. Blue particles formed 57.7% of the total, and fibres (43.2%) and filaments (40.6%) were more common than beads (16.2%). All particles were smaller than about 70 μm. Polyester was the principal polymer (52.7%), followed by cellulose (29.0%), with acrylic, polyamide, polyethylene and polypropylene each below 5%. Particle counts were not correlated with fish length, weight or condition. The dominance of small polyester fibres suggests that urban wastewater and fishing gear around Junglighat are the main sources. At the measured abundance, a 100 g serving of C. tille muscle may contain about 46 particles, which supports the inclusion of edible fish tissue in microplastic monitoring in the Andaman Islands.
Keywords: Andaman Islands; Caranx tille; fish muscle; food safety; microplastics; polyester fibres

Choosing a good route through a city is not a one-time decision, because traffic, travel time and the usefulness of side streets keep shifting while the trip is under way. This paper presents a dynamic routing system that pulls route and traffic data from Google Maps and layers a road-capacity priority model and an optional computer-vision step on top of it. The user enters a start and an end point, and the system then requests candidate driving routes together with their traffic-aware duration, distance, geometry and traffic information. Road segments are ranked with four-lane or high-capacity roads first, two-lane roads next, and one-way or narrow roads last. That ranking is blended with live congestion and estimated travel time, so a wide road that is badly jammed cannot win on its class alone. Where road-class information is missing, a map-image module estimates rough road geometry through grayscale conversion, Canny edge detection, Hough-line extraction, road-boundary separation and direction analysis. As the vehicle moves, its position is sent at intervals so that the routing data can be refreshed. Each route is scored by a weighted cost function covering traffic-aware travel time, congestion, distance, road priority and the cost of switching routes, and the active route is replaced only when an alternative beats it by a minimum margin, which keeps the route from flipping back and forth. The design brings real-time API use, computer vision, graph-based optimization, GPS tracking and ideas from intelligent transportation together in one system.
Keywords: dynamic routing, intelligent transportation, Google Maps Routes API, traffic-aware polyline, road classification, Canny edge detection, Hough transform, route optimization.