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Microplastic sources and distribution in tropical mangroves: Natural and planted systems in China
(2026-08-01)
Pradit, Siriporn
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Loh, Pei Sun
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Jitkaew, Preyanuch
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Noppradit, Prakrit
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Nitiratsuwan, Thongchai
Mangrove forests sequester microplastics (MPs); however, the long-term accumulation efficiency of planted and natural mangrove forests remains poorly understood. MP pollution poses a pervasive threat to coastal ecosystems worldwide. We reconstructed the burial record of MPs in 1-m sediment cores from two contrasting mangrove ecosystems in China: a planted forest on Ximen Island (four cores) and a natural forest in Fangchenggang (two cores). MPs were present in all sediment layers and identified by stereomicroscope and micro-Fourier transform infrared spectroscopy. Fibers overwhelmingly dominated the MP assemblage (88.6–98.2% in planted mangroves; 90.8–92.6% in natural mangroves), with the polymer profile (rayon, polypropylene, polyethylene terephthalate) strongly implicating local fishing and aquaculture activities as primary sources. MP contamination dates to at least 1963 in the natural forest and 1989 in the planted forest, thereby providing a >50-year and >30-year pollution record, respectively. Although total MP abundance exhibited no simple increasing trend with depth, the natural mangrove sequestered a significantly ( p < 0.001) higher MP burden than the plantation. The co-occurrence of an early onset and great contamination magnitude in the natural forest underlines superior particle-trapping efficiency of its mature, complex vegetation structure. Therefore, natural mangroves are critical long-term archives for coastal MP pollution; their conservation is vital for carbon sequestration and mitigating coastal plastic pollution.
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A simple mathematical model for assessing water quality in a closed-system shrimp farm
(2025-08-01)
Thongtha, Kaboon
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Pochai, Nopparat
The problem of wastewater from shrimp farming affects the environment, both in terms of wastewater discharge and soil deterioration. Wastewater management is also quite expensive for the production costs of shrimp farmers. Therefore, the approach to using shrimp farming technology in closed-system farms is proposed, which reduces wastewater discharge into the environment and reduces the cost of wastewater treatment for farmers. This research presents a simple mathematical model for assessing water quality in such closed-system shrimp farms. The method for determining various parameters for determining the mathematical model is presented. The model solution is estimated by the Runge-Kutta method of the fourth order. This research simulates the situation to compare the different parameter values in each situation, which affect the level of water quality in closed-system shrimp farms at different times. The research found that the initial water quality, the rate of chemical reaction of pollutants, the rate of pollution formation, the rate of pollution decomposition, the rate of decrease in pollution concentration due to water circulation between the farm and the water treatment pond, and time all affect water quality. The results from the calculation can help closed-system shrimp farmers know the trend of pollution concentration changes in closed-system shrimp farms in order to find ways to develop techniques for improving water quality.
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Microplastics in construction and built environment
(2023-10-01)
Prasittisopin, Lapyote
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Ferdous, Wahid
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Kamchoom, Viroon
Plastics have been extensively used in the building and construction industries for decades. However, the more plastics are utilised, the more microplastics are released. This review and analysis article summarises and organises the knowledge from 211 current related publications published in 2014–2022. The review and analysis explain the kinds of plastics employed in construction and built environment. Fabrics or textiles, fibres and plastics in cementitious systems, paints, tyres and roads are discussed. The entry points of microplastics into the human body are reviewed next, followed by the management of recycled wastes. The important research gaps and possible solutions include using high-strength concretes and surface-hardening agents is suggested to encapsulate the microplastics inside the matrix; DPSIR model analysis can be holistically adopted for each composite; innovative bio-chemical technology like self-healing concrete and bio-degradable plastics can be a viable choice; and social science, law and urban planning can support awareness and comprehension.
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The Creation of Single-Use Packaging from Leaves to Reduce Plastic Waste in Thailand
(2021-07-01)
Asawadechsakdi, Wilai
;
Chavalkul, Yada
This research aims to analyze design criteria for creating single-use packaging from leaves to reduce plastic bag waste generated by street food and T-shirt purchases along with evaluating tools for producing these biodegradeable packages. Design Thinking was utilized as a conceptual research framework. The research covered consumers, street food vendors and packaging producers. Observations and interview forms were used to collect data on the characteristics of different leaf varieties and street food, plus related user behaviors and needs. After data analysis, prototype packages were created: hard structure packaging made from fresh Noni leaves and bamboo strips and soft structure packaging made from dried leaves from the Purple Orchid tree and Banana tree derived cords. These multipurpose containers address the design criteria: supporting the food's weight, carrying both dry finger food and moist food and being held with one hand. Evaluation of the tools producing the packaging suggested development gaps related to simplicity were recognized.
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Air Quality Assessment Based on Landsat 8 Images Using Supervised Machine Learning Techniques
(2020-06-01)
Vijaranakul, Nattadet
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Jaiyen, Saichon
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Srestasathiern, Panu
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Lawawirojwong, Siam
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Jitkajornwanich, Kulsawasd
Since 2018 during the winter of every year (December - January), Thailand has been suffering from air pollution problems known as PM 2.5 toxic dust, affecting people's daily lives especially in Bangkok and its metroplex. To cope with this problem, one of the traditional methods used is to implement physical air quality measurement devices at specific locations. Currently there are 21 stations across Bangkok and surrounding areas. Each station can assess air quality at the station point along with the given radius, meaning that areas far away from the station will not be assessed properly. In this paper, we propose a methodology that incorporates satellite images for air quality assessment with supervised machine learning techniques. Several classification models tested in this paper are Decision Tree, Naïve Bayes, k-Nearest Neighbors (kNN), Random Forest, and Gradient Boosting. From our experiments, the highest performance model is Random Forest that has averaged accuracy of 0.914, averaged precision of 0.89, averaged recall of 0.814 and averaged F-1 score of 0.84825.
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A mathematical model for pollution in a river and its remediation by aeration
(2009-03-01)
Pimpunchat, Busayamas
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Sweatman, Winston L.
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Wake, Graeme C.
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Triampo, Wannapong
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Parshotam, Aroon
We present a simple mathematical model for river pollution and investigate the effect of aeration on the degradation of pollutant. The model consists of a pair of coupled reaction-diffusion-advection equations for the pollutant and dissolved oxygen concentrations, respectively. The coupling of these equations occurs because of reactions between oxygen and pollutant to produce harmless compounds. Here we consider the steady-state case in one spatial dimension. For simplified cases the model is solved analytically. We also present a numerical approach to the solution in the general case. The extension to the transient spatial model is relatively straightforward. The study is motivated by the crucial problem of water pollution in many countries and specifically within the Tha Chin River in Thailand. For such real situations, simple models can provide decision support for planning restrictions to be imposed on farming and urban practices. © 2008 Elsevier Ltd. All rights reserved.
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Modelling river pollution and removal by aeration
(2007-12-01)
Pimpunchat, B.
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Sweatman, W. L.
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Triampo, W.
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Wake, G. C.
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Parshotam, A.

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