ผลงานตีพิมพ์ทั้งหมด

Beyond Forests: A Strategic Framework for Climate-Positive Development from Thailand’s Net-Negative Provinces

Sate Sampattagul, Shabbir H. Gheewala, Ratchayuda Kongboon

Sustainability · 2026

As the global climate discourse shifts from mitigation to achieving net-negative emissions, there is a critical need for replicable, real-world models of climate-positive development at a regional scale, particularly in the Global South. This study addresses this gap by conducting a detailed greenhouse gas (GHG) inventory of four diverse provinces in Thailand and analyzing the results through the newly proposed Climate-Positive Pathways Framework (CPPF). Our findings reveal that all four provinces function as significant net-negative GHG sinks. They achieve this status through three distinct archetypes: a Conservation-Dependent pathway, an Agricultural Frontier pathway, and a novel Agro-Sink pathway. Most significantly, in the Agro-Sink model, we find that in specific economic contexts, managed agricultural landscapes can surpass natural forests as the primary driver of regional carbon removal. This typology provides a new, landscape-scale paradigm for cleaner production, proposing these three archetypes as transferable, evidence-based models for regional policymakers. This underscores that effective climate action requires context-specific regional planning that strategically leverages both natural and agricultural capital.

Carbon Footprint Data Flow Process Improvement for Strawberry Jam Tube Product by Lean Techniques

Kritiya Kanjina, Sakgasem Ramingwong, Nivit Charoenchai, Jutamat Jintana, Sate Sampattagul

Sustainability · 2026

Environmental transparency in food manufacturing requires efficient carbon footprint data collection, yet multi-departmental coordination often creates time-consuming, fragmented processes that impede adoption. This study applies lean office methodologies to optimize carbon footprint assessment processes in food manufacturing. Using a case study approach at a Thai food processing facility, we implemented flow process charts, value stream mapping, eight waste analysis, and ECRS methodology to evaluate the data collection process for strawberry jam production. The baseline assessment documented 142 activities across 12 departments, requiring 17,540 min. The lean interventions included establishing a centralized cross-functional team, developing standardized data collection templates, implementing a unified digital repository system, and consolidating redundant verification procedures. The improved process reduced activities from 142 to 63, decreased the required time from 17,540 to 11,190 min (36.2% reduction), and eliminated 95.8% of non-value-added activities while maintaining regulatory compliance. These efficiency gains enable more frequent environmental assessments and facilitate the broader adoption of carbon footprint measurement within resource-constrained manufacturing contexts. The study demonstrates that lean principles effectively optimize environmental assessment processes themselves, providing a replicable framework adaptable across diverse food manufacturing facilities and product lines while addressing critical adoption barriers including resource constraints and administrative complexity.

From Local Challenges to Global Solutions Integrating Energy–Environment–Economy for Climate Resilience_MIFS2026

Sate Sampattagul, Ratchayuda Kongboon, Ekkaporn Nawapanan, Phuchiwan Suriyawong, Hisam Samae, Netchanakan Sununta, Nattapong Sangkapong, Thunchanok Thongsamer

Open MIND · 2026

Optimizing Residential Energy Usage with Smart Devices: A Case Study on Energy Efficiency and Environmental Sustainability

Nat Weerawan, Phuchiwan Suriyawong, Hisam Samae, Sate Sampattagul, Worradorn Phairuang

Sustainability · 2025

In this study, we examined the impact of an intelligent system and air conditioning control on power consumption. The experiment was carried out during five distinct time periods: (1) background room usage, (2) smart system setup, (3) air conditioning control to maintain room temperature at no more than 27 °C, (4) air conditioning temperature control during working hours, and (5) air conditioning operated continuously to maintain the room temperature at 27 °C. For each time period, the daily power consumption was evaluated, and outliers were identified and eliminated using a threshold derived from the hourly average. The findings demonstrated that the smart system setup period and air conditioning control resulted in lower usage compared to continuously operated air conditioning with substantial spikes in demand. The impacts of the novel system and air conditioning control on energy consumption were revealed through statistical analysis, which included regression models and hypothesis tests. According to this study’s findings, it is essential to regulate spikes and guarantee proper operation to reduce the carbon footprint while maintaining a comfortable atmosphere. Notably, the integration of the smart system and optimized scheduling resulted in a substantial decrease in greenhouse gas emissions, with annual carbon emissions reduced by up to 65% compared to continuously operated air conditioning without smart control. Moreover, these systems can optimize energy use.

Precision and Accuracy Analysis of PM2.5 Light-Scattering Sensor: Field and Laboratory Experiments

Hisam Samae, Phuchiwan Suriyawong, Artit Yawootti, Worradorn Phairuang, Sate Sampattagul

Atmosphere · 2025

The widely used low-cost particulate matter (PM) sensors in Thailand, such as the DustBoy, require performance improvements to ensure their data align with the established standards set by the US Environmental Protection Agency (US EPA). This study evaluates the accuracy and reliability of the DustBoy, a commonly used PM2.5 monitoring device in Thailand. A comparative analysis was conducted between the DustBoy and the US EPA’s Federal Reference Method (FRM) and Federal Equivalent Method (FEM). The research involved both laboratory and field testing, where the DustBoy’s performance was analyzed at various particulate matter concentration levels and environmental conditions. The study demonstrated that the DustBoy readings diverged from those of standard monitors at higher PM2.5 concentrations; however, a positive correlation between the devices remained evident. Below 100 µg/m3, the DustBoy overestimated PM concentrations compared to the FRM devices but underestimated them compared to the FEM devices. At higher concentrations, the DustBoy showed a significant overestimation, although the data trends aligned with those of standard devices. The sensor performance was also affected by factors such as the sensor age and device model. Corrections were developed to adjust the DustBoy readings to match the reference devices more closely, enhancing the accuracy post-adjustment. These corrections will refine the DustBoy’s public data reporting and serve as guidelines for other low-cost sensors in Thailand.

A Blueprint for Data-Driven Climate Action: A Quantified Mitigation Pathway for Chiang Mai Using GHG Accounting and Spatial Analysis

Sate Sampattagul, Phakphum Paluang, Shabbir H. Gheewala, Ratchayuda Kongboon

Urban Science · 2025

This study develops a replicable, data-driven framework for subnational climate action, demonstrated through a case study of Chiang Mai Province, Thailand. The framework integrates a comprehensive greenhouse gas (GHG) inventory with spatial analysis to identify and quantify location-specific mitigation strategies. Using 2019 as the base year, total emissions were 5,387,482 tCO2e (BASIC+), dominated by stationary energy (40%) and transportation (32%). Under a Business-as-Usual scenario, emissions are projected to reach 6.35 million tCO2e by 2030, highlighting an urgent need for intervention. As a key mitigation strategy, this research conducts a detailed spatial analysis of solar rooftop potential. The findings reveal a significant opportunity: a conservative 30% adoption rate on suitable rooftops could generate approximately 2070 GWh of clean energy annually, leading to an emissions reduction of over 1 million tCO2e. Crucially, this single intervention could offset 16% of the province’s projected 2030 emissions. This study presents a viable pathway for subnational entities to contribute to national climate targets, offering a practical blueprint for other cities and regions globally to develop effective, evidence-based climate action plans.

Economic Viability of Electric Bus Adoption for Public Transportation in Thailand: A Monte Carlo Simulation Approach

Sakgasem Ramingwong, Sate Sampattagul, Jutamat Jintana

Logistics · 2025

Background: Thailand is actively transitioning toward electric vehicle adoption as part of its commitment to reducing greenhouse gas emissions. This study investigates the economic feasibility of replacing diesel buses with electric buses in Thailand’s public transportation sector. Methods: The research employs a comprehensive methodological framework combining Total Cost of Ownership (TCO) analysis with Monte Carlo simulation to address uncertainties in long-term financial projections. The study examines four pilot routes operated by a major Thai bus company, incorporating potential carbon credit revenues through Thailand’s Voluntary Emission Reduction program. Results: The analysis reveals substantial cost advantages for electric buses across all examined routes, with TCO savings ranging from 23.07% to 38.25%. Even under conservative scenarios, all routes demonstrate positive economic benefits. The fleet-wide net savings amount to approximately 236 million THB over a 10-year period, with an additional 16.7 million THB potential carbon credit revenue. Sensitivity analysis identifies fuel costs as the most significant factor (45.2%) affecting economic outcomes. Conclusions: The transition to electric buses presents a compelling economic and environmental case for Thai public transportation operators, with significant cost savings and emission reductions. A phased implementation approach beginning with routes offering the highest percentage savings is recommended.

Health Impact Related to Ambient Particulate Matter Exposure as a Spatial Health Risk Map Case Study in Chiang Mai, Thailand

Kannika Jarernwong, Shabbir H. Gheewala, Sate Sampattagul

Atmosphere · 2023

Chiang Mai has been one of the most polluted cities globally, exceeding the PM2.5 quality standards for decades and facing hazardous air pollution on an annual basis. As ambient PM2.5 strongly affects human health, this study aims to investigate the hotspots of PM2.5 and health impact areas due to exposure to PM2.5 by illustrating a spatial distribution via a Chiang Mai health risk map. The association between PM2.5 concentration and human health impact were assessed using Pearson’s correlation, focused on the peak period from January to April 2021 in Chiang Mai. The primary data on PM2.5 concentration were collected using low-cost sensors. The health impact is based on the number of hospital admissions in all incidences of diseases due to PM2.5 exposure following the ICD-10. The results showed that the highest polluted and health-risk areas were located in the center of Chiang Mai, especially in the Mueang district. PM2.5 concentration was highly correlated with the incidence of dermatitis (R = 0.84), conjunctivitis (R = 0.81), stroke (R = 0.74), and lung cancer (R = 0.73). Thus, the increased PM2.5 concentration resulted in heightened hospital admissions. The results provide insightful information for policymakers and local public health organizations regarding priority areas in resource management.

Greenhouse gas emissions inventory data acquisition and analytics for low carbon cities

Ratchayuda Kongboon, Shabbir H. Gheewala, Sate Sampattagul

Journal of Cleaner Production · 2022

Green GDP Indicator with Application to Life Cycle of Sugar Industry in Thailand

Ekkaporn Nawapanan, Ratchayuda Kongboon, Sate Sampattagul

Sustainability · 2022

The objective of this study was to develop new indicators that reflect economic growth by taking into account the impact on the environment and natural resources as well. The indicator calculated by subtracting environmental cost from the “Gross Domestic Product (GDP)” and is used in the assessment of the GDP by taking into consideration the cost of natural resources and the environment, called “green GDP”. This study uses Life Cycle Assessment, which is a technique used to assess the environmental impact of sugar industry from raw materials, distribution, production, and waste management. The system boundary for the life cycle inventory are cultivation, planting, transportation and sugar production. The results of the green GDP and GDP is difference about 6–12% due to the depletion cost resulting from the use of natural resources between 9.0–9.52 $/ton of sugar production and the degradation cost caused by the airborne emission and waterborne emission between 37–57 $/ton of sugar production. The quantity of Total Suspended Particulate (TSP) generated from the sugar production process is the main causing the environmental cost about 55%. In order to solve environmental causes, the policy making as Circular Economy Strategies can be used to meet the sustainable development in the future.