Abstract
This research investigated the implementation of a citizen science system for monitoring
and managing risks from transboundary acid gas and mercury deposition in Nan Province,
Thailand. The study aimed to transform from a "demonstration" to an "operational problemsolving system." A network of 28 citizen science trainers across seven villages collected 1,210
data entries, which were analyzed through the C-Site monitoring system integrated with artificial
intelligence (AI) technology.
Soil analyses revealed topsoil (0-5 cm) pH values below 5.5 in nearly all study areas,
exhibiting significant negative correlations with plant disease occurrence (p < 0.01). Statistical
analyses demonstrated that decreasing pH values strongly correlated with increased incidence
of grain discoloration (r = -0.67) and leaf blight in rice and corn (r = -0.62). Methylmercury
bioaccumulation in fish ranged from 0.01-0.49 mg/kg, with fin-feather fish from the Nan River in
Thung Chang District exceeding safety standards (0.49 mg/kg). Rice samples showed
methylmercury accumulation ranging from non-detectable to 0.03 mg/kg, below safety
standards (0.1 mg/kg).
The research identified distinct bioaccumulation patterns along the Nan River, with
increasing methylmercury concentration from upstream to downstream. Carnivorous fish
exhibited significantly higher accumulation than herbivorous fish (0.09 vs. 0.04 mg/kg, p < 0.001),
and fish in flowing water environments showed greater concentrations than those in still water
(0.09 vs. 0.05 mg/kg, p < 0.01). For rice, dark-colored native varieties (Kho Lai Dam and Khem)
demonstrated higher mercury accumulation than common varieties, and lowland rice contained
significantly more mercury than upland rice (p < 0.05).
Statistical analyses revealed significant positive correlations between mercury deposition
patterns from the AERMOD dispersion model and methylmercury accumulation in both fish (r =
0.64, p < 0.01) and rice (r = 0.58, p < 0.05). Areas with high predicted mercury deposition
consistently showed elevated methylmercury levels in the food chain, demonstrating a clear
link between transboundary pollution and food web contamination. Soil acidity analysis
identified combined factors of acid rain and ammonium fertilizer usage, with border areas more
significantly impacted by acid rain.
The project established effective data transfer mechanisms to government agencies,
creating functional collaborations between citizen science networks and seven government
institutions. This integration enabled the incorporation of citizen science data into routine
operations and targeted interventions. The research demonstrates that citizen science represents
a cost-effective, high-coverage tool for monitoring and managing transboundary pollution,
particularly in remote areas with limited government access. This model offers a replicable
framework for addressing environmental challenges in similar contexts globally.
