Mining operations are important causes of environmental pollution in developing countries where mining waste management is not adequate. Consequently, heavy metal(loid)s are easily released into the environment, being a potential risk to human health. This study carries out a Bayesian probabilistic human health risk assessment, related to multi-pathway exposure to heavy metal(loid)s in a gold mining area in Southern Ecuador. Concentrations of As, Cd, Cr, Cu, Ni, Pb, and Zn in tap water, surface water, and soil samples, were analyzed to assess the potential adverse human health effects based on the Hazard Index (HI) and Total cancer risk (TCR). Adults and children residents were surveyed to adjust their exposure parameters to the site-specific conditions. Exposure to heavy metal(loid)s resulted in unacceptable risk levels for human health in the two age groups, both carcinogenic (TCR > 1 × 10^-5) and non-carcinogenic (HI > 1) through ingestion of tap water and incidental ingestion of surface water. Sensitivity analysis showed that As concentration in waters and exposure frequency were the main contributors to risk outcome. Exposure to soil via accidental ingestion and dermal contact was below the safety limit, not posing a risk to human health. These findings can provide a baseline for the environmental management of the mining area and indicate the need for further research on As pollution in water and its implications on the health of the inhabitants of mining communities.

The total energy demand in the transport sector represented 48.80% of the total consumption in Ecuador throughout 2016, where 89.87% corresponded to the road transport sector. Therefore, it is crucial to analyze the future behavior of this sector and assess the economic and environmental measures towards sustainable development. Consequently, this study analyzed: (1) the total energy demand for each vehicle class and fuel type; (2) the GHG (greenhouse gas) emissions and air pollutants NO_x and PM₁₀; and (3) the cost attributed to the fuel demand, between 2016 and 2035. For this, four alternative demand scenarios were designed: BAU: Business As Usual; EOM: Energy Optimization and Mitigation; AF: Alternative Fuels; and SM: Sustainable Mobility using Long-range Energy Alternatives Planning system. After analysis, the EOM, AF, and SM scenarios have advantages relative to BAU, where SM particularly stands out. The results show that SM compared to BAU, contributes with a 12.14% (141,226 kBOE) decrease of the total energy demand, and the economic savings for this fuel demand is of 14.22% (26,720 MUSD). Moreover, global NO_x and PM₁₀ emissions decreased by 14.91% and 13.78%, respectively. Additionally, accumulated GHG emissions decreased by 13.49% due to the improvement of the fuel quality for the vehicles that mainly consume liquefied petroleum gas, natural gas, and electricity.