Maize, a major food source for the world, is a high-yield commodity crop, and one of five major crops in Thailand. Occupying about 33% of the Thai upland farmlands, maize farming has been growing tremendously especially in northern Thailand. However, after harvesting, open burning is widely used in order to get rid of maize cobs and husks in land preparation for the next period. The current maize farming practices have caused several problems to local communities as well as urban dwellers. The objectives of this research were: (i) to analyze the life cycle inventory of maize cultivation, maize cob pellet production and heavy fuel oil production in northern Thailand using IDEA v2.0 and ecoinvent v3.0 databases; (ii) to evaluate environmental impacts of maize cultivation, maize cob pellet production and heavy fuel oil production using A Global Scale Environmental Life Cycle Impact Assessment (LIME-3) with the results of weighting (Country-specific) based on monetary valuation of end-points. This study evaluated the life cycle environmental impacts of maize cultivation and continuing through biomass energy production from maize cob by comparing with heat production from heavy fuel oil in Mae Chaem and Chiang Dao districts in the north of Thailand by using two different databases, IDEA v2.0 and ecoinvent v3.0 with an endpoint-based life cycle impact assessment (LCIA) method (LIME-3). The system boundary of this study includes land preparation, planting, weeding, farming, harvesting, maize cob pellet production and heat production from maize cob pellet and heavy fuel oil. The units of analysis in this study are 1 kg of maize grain, 3.76E-03 MJ of biomass energy production from maize cob and 3.76E-03 MJ of heat production from heavy fuel oil, respectively. The data were obtained from field survey supplemented with the Thai National Life Cycle Inventory Database and other scientific publications. The results included the environmental impacts of maize cultivation and continuing through biomass energy production from maize cob by comparing with heat production from heavy fuel oil in Mae Chaem and Chiang Dao districts by using two different databases with LCIA method on the endpoint approaches (LIME-3). The total damage cost based on IDEA v2.0 life cycle inventory (LCI) database in Mae Chaem and Chiang Dao districts was about 4.64E-01 USD and 4.89E-01 USD, respectively. As regards ecoinvent v3.0 database, the total damage cost in Mae Chaem and Chiang Dao districts was about 5.37E-01USD and 5.99E-01 USD, respectively. It can be seen that the total damage cost using different inventory databases in Chiang Dao are slightly higher than Mae Chaem due to different input materials. The result of total cost using inventory data from ecoinvent v3.0 is slightly higher than IDEA v2.0 due to different inventory processes in each database. However, the results in this study demonstrated that the databases show similar trends in the assessment results. On the other hand, certain numerical differences between the databases at some points were found to be more substantial. The results of present study are particularly relevant to policy choices for improving or using the good practices for maize cultivation, which would reduce the environmental performance of maize production systems in the area. To address the air pollution issue from biomass open burning of agricultural residues in the study area, the government agencies in Thailand should be responsible for promoting better biomass management for the future.

Chiang Mai has been one of the most polluted cities globally, exceeding the PM_2.5 quality standards for decades and facing hazardous air pollution on an annual basis. As ambient PM_2.5 strongly affects human health, this study aims to investigate the hotspots of PM_2.5 and health impact areas due to exposure to PM_2.5 by illustrating a spatial distribution via a Chiang Mai health risk map. The association between PM_2.5 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 PM_2.5 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 PM_2.5 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. PM_2.5 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 PM_2.5 concentration resulted in heightened hospital admissions. The results provide insightful information for policymakers and local public health organizations regarding priority areas in resource management.