All publications

A Dynamical Systems Approach to Modelling Food Loss of Fresh Fruit Bunches in Oil Palm Cultivation for Enhanced Sustainability

Nattawut Khansai, Nongnuch Poolsawad, Jantima Samneangngam, Prakaytham Suksatit, Tassaneewan Chom‐in, Khaowpradabdin Songma

2026

This article develops a dynamical systems model to simulate the flows and loss mechanisms of fresh fruit bunches (FFB). Formulated as a system of differential equations, the model represents FFB stocks and associated flows while incorporating explicit loss terms. The existence of a unique and globally stable steady state, which represents the equilibrium proportion of total FFB loss, was proven. Subsequently, the parameterisation approach combines small-scale survey data from 27 smallholders in southern Thailand, which has the highest concentration of oil palm plantations, with assumption-driven values based on official statistical records, academic literature, and expert insights. Scenario and sensitivity analyses were conducted to identify the key drivers of FFB loss. This model-based analysis indicates that the most effective strategies for reducing FFB loss are those that focus on improving harvest efficiency while simultaneously optimising in-field operational practices, thereby supporting more sustainable palm oil supply chain management.

Prediction of Maize Yield and Assessment of the Material Circularity of Maize Residues Used in the Dairy Cattle Feed Production

Nongnuch Poolsawad

Natural and Life Sciences Communications · 2024

The dairy cattle industry is expanding rapidly to accommodate the growing demand for human consumption. This results in high cattle feed production. This study aims to forecast the amount of maize residue and calculate the circularity level of using maize residue as a feedstock for total mixed ration feed production in dairy cattle feed production. The multiple linear regression analysis is performed to predict maize yields in Thailand so that maize residues can be calculated and used in feed production. The material circularity indicator is also used with biological cycles to assess the circularity level of dairy cattle feed production under the circular economy concept. The results show that the maize yield is expected to increase, resulting in more maize residues. The use of maize residues in daily cattle feed production gives the MCI value of 0.6038, representing a high degree of circularity and explaining the sustainable management of wastes in the cattle feed industry. Moreover, using maize residues as a part of feed ingredients instead of the Napier grass saves the cost by 14.2%. The study results provide a guideline for farmers and related authorities to plan for managing maize residue in daily cattle feed production to lower operation costs and minimize environmental problems. Keywords: Biological cycle, Circular economy, Dairy cattle feed production, Maize residues, Material circularity indicator, Multiple linear regression

MATERIAL CIRCULARITY INDICATOR FOR THAI OIL PALM INDUSTRY

NONGNUCH POOLSAWAD

Journal of Oil Palm Research · 2024

Material circularity indicator for accelerating low‐carbon circular economy in Thailand's building and construction sector

Nongnuch Poolsawad, Tassaneewan Chom‐in, Jantima Samneangngam, Prakaytham Suksatit, Khaowpradabdin Songma, Saowalak Thamnawat, Somrath Kanoksirirath, Thumrongrut Mungcharoen

Environmental Progress & Sustainable Energy · 2023

Abstract Thailand's steady growth of urban areas and industrial estates, the construction sector needs to adopt a low‐carbon circular economy (CE) model that emphasizes material circularity and resource efficiency. This research aims to measure the low‐carbon CE of the construction industry through significant representative products, life cycle assessment and material circularity indicator (MCI) were measured on significant representative products materials were evaluated. In the results of the study, it was found that the MCI and GHGs revealed the following results: 1 ton of construction steel products = 0.73 and 2.32 kgCO2/ton, 1 bag (50 kg) of mortar and cement products = 0.17 and 16.92 kgCO2/bag, 1 m3 of ready‐mixed concrete at compressive strength 240 kilograms per square centimeter = 0.11 and 253.63 kgCO2/m3, 1 m3 of wood and composite wood products = 0.17 and 745.84 kgCO2/bag, also 1 m2K/W (meters squared Kelvin per Watt) of glass wool insulation = 0.50 and 1.63 kgCO2/m2K/W, respectively. These values are indicated as national baselines for monitoring CE performance that contribute to the industry's long‐term viability and turn to sustainability in Thailand through the key strategic issues in Thailand's CE and low‐carbon society. The GHGs reduction of 11 million tons is expected, which can also increase the 10% of material circularity, also the estimation of the economic value, by considering the value added from material reduction and the price of carbon credit from construction and demolition waste reduction affect the Thai construction industry by approximately 67 million dollars.

Life Cycle Costing of a Detached House in Bangkok, Thailand

Sornsawan Budsang, Nongnuch Poolsawad, Tassaneewan Chom‐in, Thanwadee Chinda

2022

Life Cycle Costing of a Detached House in Bangkok, Thailand Sornsawan Budsang School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12120, Thailand [email protected] Tassaneewan Chom-in Technology and Informatics Institute for Sustainability, National Metal and Materials Technology Center, National Science and Technology Development Agency, Pathum Thani, 12120, Thailand [email protected] Nongnuch Poolsawad* Technology and Informatics Institute for Sustainability, National Metal and Materials Technology Center, National Science and Technology Development Agency, Pathum Thani, 12120, Thailand [email protected] Thanwadee Chinda School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12120, Thailand [email protected] * Corresponding author E-mail address: [email protected] Abstract In Thailand, the number of residential buildings in the detached house category tends to increase due to increasing consumer demand. This causes economic competition among contractors and customers who would like to construct detached houses. As a result, stakeholders in detached house construction must manage costs to the lowest possible expenses throughout the building life cycle from construction to residential use, replacing maintenance equipment, and eventual demolition. Life cycle costing is growing in popularity, especially in the field of sustainable construction. However, the use of life cycle costing in the construction industry remains restricted and plagued by practical issues. One of the major issues in the widespread use of life cycle costing in the construction stage, use stage, and endof-life stage is a lack of knowledge of the research methods and usage of life cycle costing. This study describes a research that shows how a detached house's life cycle cost evaluation was undertaken, along with how the life cycle cost variables were defined and applied to advance a life cycle budget for the entire life cycle of a detached house. This research analyzed the life cycle cost of a detached house through a case study in Bangkok by considering diverse expenses, including construction materials, maintenance, labor, electricity, water, and demolition during service life of 50 years for the building. Costs throughout the life cycle of a detached house analyzed over 50 years amount to 4,901,775.21 70 SDC2022 9th Sustainable Development Conference [SDC2022], 10th – 12th of November 2022 – Bangkok, Thailand SDConference Proceedings 2022 ISBN: 978-86-87043-85-5 baht. This sum may be categorized into costs for each stage of a detached house life cycle, to be used in considering detached house project development and consumer decision-making. Keywords: Life cycle costing, Detached house, Construction, Demolition

Updating and Road-testing Life Cycle Inventory Data Review Criteria: Toward Global Consensus and Guidance On Data Quality Assessment

Guido Sonnemann, Dieuwertje Schrijvers, Anne Asselin, Nongnuch Poolsawad, Jitti Mungkalasiri, Tim Grant, Cristóbal Loyola, Bruce Vigon

Integrated Environmental Assessment and Management · 2020

Data quality of life cycle inventory background databases should be ensured in order to be useful for life cycle assessment (LCA) studies. However, databases do not always have procedures to evaluate the quality of the data sets in place. The Global Guidance Principles for LCA Databases of the United Nations Environment Programme (UNEP) in collaboration with the Society of Environmental Toxicology and Chemistry (SETAC) provide, among others, recommendations to enhance data quality through improved documentation and review. Flagship 2a in Phase 3 of the UNEP/SETAC Life Cycle Initiative aimed to enable the practical implementation of these recommendations with the development of review criteria and the testing of these criteria on 3 national databases. After a pilot-testing phase, this project entered a more mature road-testing exercise, of which the results are presented in this paper. The review criteria have been updated and provide more emphasis on goal and scope documentation completeness and include a new cluster of criteria that evaluate the materiality of the data set. The updated criteria have been applied to national databases of Thailand, Australia, and Chile. All databases would benefit from additional documentation, for example, on system boundaries, the reference model, sampling procedures, and cut-off criteria. Furthermore, conducting the review was enabled by extensive documentation and data accessibility in LCA software. Communication of the criteria to the database managers enabled them to anticipate data quality requirements of the global LCA community and improve the data sets in advance. Reviewers sometimes had a different interpretation of the criteria, which suggests that there is room for additional fine-tuning of the process guidance and exemplification of review criteria. This project has demonstrated that the criteria are applicable to and provide useful feedback for databases with different levels of maturity and contribute to improving quality of life cycle inventory (LCI) data. Integr Environ Assess Manag 2020;16:517-524. © 2020 SETAC.

Life Cycle Greenhouse Gas Emissions for Circular Economy

Thumrongrut Mungcharoen, Viganda Varabuntoonvit, Nongnuch Poolsawad

2020

Environmental Impacts Related to Food Consumption of Indonesian Adults (Proceedings of the 13th Asian Congress of Nutrition (ACN) : Nutrition and Food Innovation for Sustained Well-being)

Rofiqa Noor Rahmi, Nongnuch Poolsawad, Kitti Sranacharoenpong

Journal of Nutritional Science and Vitaminology · 2020

Environmental Impacts Related to Food Consumption of Indonesian Adults

Rofiqa Noor Rahmi, Nongnuch Poolsawad, Kitti Sranacharoenpong

Journal of Nutritional Science and Vitaminology · 2020

The challenge for nutrition science is to understand strategies to enable a balance between healthy diets and sustainable food systems. This study was to quantify greenhouse gas (GHG) emission of food consumption related to different dietary preferences among Indonesian adults by body mass index (BMI). Methods: We utilized the existing food consumption survey databases. Dietary and anthropometric information were obtained from Total Diet Study (Studi Diet Total/SDT) in 2014 and Basic Health Research (Riskesdas/RKD) in 2013. The most consumed food items from 14 food groups were selected as representatives of rice, cassava, tofu, long beans, banana, chicken meat, chicken liver, mackerel tuna, chicken egg, condensed milk, palm oil, white sugar, shallot, and ground coffee. The GHGs emission factors were acquired from Thai National Life Cycle Inventory Database. Food weight (gram), energy intake (kcal), and GHGs emission (kgCO2eq) from consumption of these food items were analyzed among BMI groups. Results: Annual GHGs emission by underweight, normal, overweight and obesity group were 794, 827, 801, and 791 kgCO2eq/person, respectively. The highest contributor of GHG was chicken meat, followed by rice and chicken eggs (190, 175, and 123 kgCO2eq/person/y, respectively). Indonesian people in the obesity group consumed higher amount of food (p=0.001) than other groups, however, they emitted lowest GHG emission (p=0.001). Conclusion: This finding suggested that selection of food type plays a critical role on the environment and amount of consumption. Food choices of the population may ultimately result in impacts on environment and have public health consequences.

Thai national life cycle inventory readiness for product environmental footprint

Nongnuch Poolsawad, Wanwisa Thanungkano, Jitti Mungkalasiri, Ruthairat Wisansuwannakorn, Prakaytham Suksatit, Athiwatr Jirajariyavech, Kittipoj Datchaneekul

The International Journal of Life Cycle Assessment · 2016

In the near future, the products of Thai industries and companies mainly producing parts and products for export to the European Union (EU) will require the Product Environmental Footprint (PEF) to assess the environmental performance and resource efficiency of products by using a life cycle perspective. The potential generic (often used interchangeably with background data) data have to be modified and improved for mandatory use in the product-specific and country-specific PEF database. PEF is used as a tool for assessing the environmental burden of products and services for export to the EU. It requires both specific data from primary sources and generic data to fulfill assessment requirement. Accordingly, the Thai national life cycle inventory (LCI) database plays a key role in generic data that was used to evaluate the environmental performance of products. This paper presents the perspective of Thai data readiness for PEF in which the quality of LCI is the main issue of concern. The current situation of the Thai national LCI database was reviewed. Then, the gaps of data were addressed, and the gaps were also filled. Non-representative data and untreated waste are the selected issues that were presented in this paper. Many gaps were revealed for the Thai national LCI database because this database was developed based on ISO 14040/44, which may not be compliant with the PEF guide. The issues that have been selected for improvement are non-representative data and untreated waste because these gaps can offer inaccuracy concerning the environmental burden of products potentially leading to the reliability of products for export to the EU. However, the Thai national LCI database has not achieved the data quality aspects of the PEF, continuously improving the quality of data to meet the requirements of the PEF. The lessons learned from the real-world situation of data quality development based on PEF requirements were extracted. The practical procedure and recommendations were transparent for drivers and researchers who would like to start with data quality issues and prepare for the EU single market.

Product Environmental Footprint for Feed Production in Thailand

Prakaytham Suksatit, Nongnuch Poolsawad, Wanwisa Thanungkano, Jitti Mungkalasiri

Proceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2016

Extended Abstract Food industry in Thailand is one of the high-volume exports. According to the statistics, in 2014, exports accounted for 27% of chicken production, which is ranked fourth in the world and ranked first in the EU (42%) [1], it presents the majority market share. This study aims to prepare and support Thailand industries to export to the EU single market by using product environmental footprint (PEF) to be a tool for evaluating the quality of products on environmental perspective. The study complied with methodology and environmental footprint impact category to conform to the PEF guide [2]. Also this study is a part of the shadow pilot project of the PEF, which led by the National Science Technology and Innovation Policy Office (STI) and National Metal and Materials Technology Center (MTEC) that collaborated with one of the large chicken industries named Betagro Public Company Limited. In a nutshell, the environmental impacts of chicken feed shall be assessed whole life cycle from cradle to grave, which covered from raw materials acquisition stage to disposal stage, by considering the functional unit was 1 kg of chicken feed products. The main ingredients of chicken feed should be provided the protein and energy to improve chicken health as with increasing in size and to produce more eggs. Maize, wheat, rice bran and soy bean meal are majorly used for chicken feed which contain high nutritive values, and therefore most widely used in animal feed industries because they contain less in fat and high in proteins. The composition of feed by each recipe based on age of chicken (breeder and broiler) and the growth stage of the chicken. The mainly environmental impact categories of chicken product has feed production (approximately value more than 50% by weight) and the significant environmental impact categories were climate change, freshwater eutrophication, freshwater ecotoxicity, water resource depletion and land use. The results found that the main contribution to environmental impacts of feed production is raw materials acquisition, especially maize from Thailand and soybean meal from Argentina. In worldwide typically use maize starch for main ingredient of poultry feed because its energy source is highly digestible for poultry. In addition, the plant protein source traditionally used for feed manufacture is soybean meal, which is the preferred source for poultry feed [4]. However, the environmental impact of broiler feed shows higher than breeder feed that because the ratio of maize in boiler feed to tonne feed is 1:0.46 whereas breeder feed 1: 0.54. Thus, this study focuses on the feedstuffs of broiler feed with percentage of protein is retained. The percentage of crude protein in feedstuffs as shown in table 1 [5,6].

Review of LCA datasets in three emerging economies: a summary of learnings

Bruce Vigon, Guido Sonnemann, Anne Asselin, Dieuwertje Schrijvers, Andreas Ciroth, Sau Soon Chen, Tiago Emmanuel Nunes Braga, Nongnuch Poolsawad, Jitti Mungkalasiri, F. Boureima, Llorenç Milà i Canals

The International Journal of Life Cycle Assessment · 2016

Practical approaches to mining of clinical datasets : from frameworks to novel feature selection

Nongnuch Poolsawad

Repository@Hull (Worktribe) (University of Hull) · 2014

Research has investigated clinical data that have embedded within them numerous complexities and uncertainties in the form of missing values, class imbalances and high dimensionality. The research in this thesis was motivated by these challenges to minimise these problems whilst, at the same time, maximising classification performance of data and also selecting the significant subset of variables. As such, this led to the proposal of a data mining framework and feature selection method. The proposed framework has a simple algorithmic framework and makes use of a modified form of existing frameworks to address a variety of different data issues, called the Handling Clinical Data Framework (HCDF). The assessment of data mining techniques reveals that missing values imputation and resampling data for class balancing can improve the performance of classification. Next, the proposed feature selection method was introduced; it involves projecting onto principal component method (FS-PPC) and draws on ideas from both feature extraction and feature selection to select a significant subset of features from the data. This method selects features that have high correlation with the principal component by applying symmetrical uncertainty (SU). However, irrelevant and redundant features are removed by using mutual information (MI). However, this method provides confidence in the selected subset of features that will yield realistic results with less time and effort. FS-PPC is able to retain classification performance and meaningful features while consisting of non-redundant features. The proposed methods have been practically applied to analysis of real clinical data and their effectiveness has been assessed. The results show that the proposed methods are enable to minimise the clinical data problems whilst, at the same time, maximising classification performance of data.

Issues in the Mining of Heart Failure Datasets

Nongnuch Poolsawad, L. Moore, C. Kambhampati, John G.F. Cleland

Machine Intelligence Research · 2014

Handling missing values in data mining - A case study of heart failure dataset

Nongnuch Poolsawad, L. Moore, C. Kambhampati, John G.F. Cleland

2012

In this paper, we investigate the characteristics of a clinical dataset using feature selection and classification techniques to deal with missing values and develop a method to quantify numerous complexities. The research aims to find features that have high effect on mortality time frame, and to design methodologies which will cope with the following challenges: missing values, high dimensionality, and the prediction problem. The experimental results will be extended to develop prediction model for HF This paper also provides a comprehensive evaluation of a set of diverse machine learning schemes for clinical datasets.

Feature Selection Approaches With Missing Values Handling For Data Mining - A Case Study Of Heart Failure Dataset

Nongnuch Poolsawad, C. Kambhampati, John G.F. Cleland

Zenodo (CERN European Organization for Nuclear Research) · 2011

In this paper, we investigated the characteristic of a clinical dataseton the feature selection and classification measurements which deal with missing values problem.And also posed the appropriated techniques to achieve the aim of the activity; in this research aims to find features that have high effect to mortality and mortality time frame. We quantify the complexity of a clinical dataset. According to the complexity of the dataset, we proposed the data mining processto cope their complexity; missing values, high dimensionality, and the prediction problem by using the methods of missing value replacement, feature selection, and classification.The experimental results will extend to develop the prediction model for cardiology.

Dysphonia Measures in Parkinson's Disease and Their use in Prediction of Its Progression .

C. Kambhampati, Mayur Sarangdhar, Nongnuch Poolsawad

Repository@Hull (Worktribe) (University of Hull) · 2010

Parkinson's Disease (PD) is a neurodegenerative disorder that impairs the motor skills, speech and general muscle coordination. The progression of PD is assessed using a clinically defined rating scale known as Unified Parkinson's Disease Rating Scale (UPDRS). Recent studies have shown the use of telemonitoring of PD using simple speech tests which replicate the UPDRS to clinician's accuracy. Regression analysis is performed on a database of speech recordings of 42 PD patients to analyse the relation between dysphonia measures and the UPDRS with the progression of PD. It is observed that there is a strong correlation between the dysphonia measures and the UPDRS and it is possible to predict the UPDRS scores weekly using linear regression techniques. The results also suggest that certain dysphonia measures evolve more significantly with the progression in PD. This is supported by Principle Component Analysis (PCA) which identifies the dysphonia measures that are strongly correlated during the course of PD progression. The data is classed by trials undertaken by the patients and each patient had at least 20 valid trials.