The objective of this study were 1) to develop the gas detector unit for installation on Drone and 2) to test the operational sensitivity of the developed device. The development steps included designing complying the electrical circuit testing the electrical system and online connecting system. Besides the operational sensitivity of the developed device was tested comparing the Gas Alert Micro 5 IR the reference gas detector device both in the laboratory and the field site. The results showed that the developed gas detector could detect carbon dioxide carbon monoxide and methane and displayed the results via Line notification every minute. Additionally carbon dioxide detection by MG-811 sensor gave the results similar to the reference device by 95 percent of significant level with the average amount of detected carbon dioxide in the laboratory and the field site were 700-915 ppm and 138-399 ppm respectively. However the measured results of carbon monoxide and methane from the develop device were relatively different to the reference device. Further study on carbon monoxide sensor and methane sensor calibration are recommended.

This study aims to determine the management approach for organization greenhouse gas emissions reduction and decreased them from the production per unit in a case study of food and beverage company. Due to the cleaner technology was applied for greenhouse gas emissions reduction within scope 1 (Fuel Oil) and scope 2 (Electric Power). Greenhouse gas emissions shows a positive prospect with downward trend from 1.73 TonCO2e/unit in year 2016 to 1.44 TonCO2e/unit in year 2017 (16.8%). In addition it less than greenhouse gas emitted in year 2015 (1.59 TonCO2e/unit or 9.4%). These Results reveal that cleaner technology is an appropriated method for greenhouse gas emissions reduction in Food And Beverage Company.

This is an independent study on greenhouse gas emissions and ways to reduce them. A five-star resort in Koh Samui Surat Thani province has been used as a case study. The study used digital tools to gather information on activities that cause greenhouse gases and energy consumption at the resort. The calculation of carbon footprint is in line with the guidelines of the Thailand Greenhouse Gas Management Organization. Digital systems help data collection and carbon footprint analysis and this is best done at set intervals. For example digital systems can monitor power consumption every 15 minutes measured in real time. The carbon footprint maximum emission each day occurs between 2.00 and 4.00 pm the peak time of energy consumption. Use of electricity is the activity that produces the highest amount of greenhouse gases at a total volume of 4215.1 tonCO2-e per year or 88.12% of the total activity. LPG gas consumption produces the second largest volume of greenhouse gas emissions at 412.8 tonCO2-e per year or 8.63% of the total activity. From January to December 2017 the carbon footprint emission is 4783.5 tonCO2-e and the average emission per room night is 4.2 tonCO2-e. The study found that a 10% reduction in energy Consumption could reduce greenhouse gas emissions by 421.52 tonCO2-e per year or 0.4 tonCO2-e per room night.

CO2 emission of rail transportation system plays more important role including the expansion of BTS route that consume the energy and emit CO2 gas more and more. The purpose of this research was to find out amount of CO2 emission from travelling by BTS train and determine specific CO2 emission per product in the form of gCO2e/passenger/km then forecasting on CO2 emission from BTS operations. Research process was initiated from collecting monthly data on ridership distance and electricity for 55 months continuously then regression analysis CUSUM and time series analysis were used for prediction and analysis of CO2 emission. The finding indicated that BTS’s specific CO2 emission was 24.7 gCO2e/passenger/km. Forecasting CO2 Emission from BTS result that Winters Exponential Smoothing Method is most accuracy then Double Exponential Smoothing Method Trend Analysis Method and Decomposition Method respectively. The result of these analysis could be used to calculate carbon footprint from staff travelling by BTS train and promote people to use public transport by government as sustainable transportation concept.

This study is to determine guideline to reduce carbon footprint for organization of medium and small hotels in Thailand using the Carbon Footprint for Organization (CFO) according to Thailand Greenhouse Gas Management Organization (Public Organization). Conducting with 2 represented medium and small hotels the results showed that the overall carbon footprint average of 2013 was 553t.Co2-e. Considering concentration index by number of guestrooms the carbon footprint was 18.81 kg.Co2e/room-night 221.16 kg.Co2-e/m2 by total floor area and 11.65kg.Co2- e/personby guest. The dominant source of carbon footprint was use of electricity 465t.Co2-e(83.06%). Base on this assessment to use of air conditioning was 60.09 % water heater 17.64 % lighting equipment 15.05 % and other 7.22 % of total electricity used. Therefore guidelines for carbon footprint reducing of the representative hotel were to use technology to reduce electricity consumption for air conditioning water heater and lighting respectively. Based Approach to Reducing Carbon Footprint found that small and medium sized hotels can reduce emissions per year 24.87 t.CO2-e representing the ability to reduce greenhouse gas emissions by up to 4.49% or financial projections be able to save money 171.202 baht per year.