GREENHOUSE GASES EMISSIONS (GHG) REDUCTION STRATEGIES HAVE GAINED INTEREST IN THE RECENT DECADE, AS THEY CAN POSITIVELY IMPACT ENVIRONMENTAL AND LIFE QUALITY IN BIG CITIES. TRANSPORTATION IS RESPONSIBLE FOR A GREAT PERCENTAGE OF THESE EMISSIONS, WHICH ARE STRONGLY RELATED TO FUEL CONSUMPTION PROFILES ALONG WITH TRAJECTORY CHARACTERISTICS. AVAILABLE TECHNOLOGIES, SUCH AS GPS TRACKING, GENERATE DATA WHICH CAN BE USED TO BETTER CHARACTERIZE FUEL CONSUMPTION AND GHG EMISSIONS ALONG A TRAJECTORY AND THUS HELP MAKE BETTER PLANNING TOWARDS ENERGY EFFICIENT AND REDUCE EMISSIONS PATHS. THIS WORK SEEKS TO CHARACTERIZE ENERGY CONSUMPTION AND GHG EMISSIONS GENERATED BY HEAVY-DUTY VEHICLES. IMPLEMENTED METHODOLOGY ALLOWS FOR ESTIMATING INSTANTANEOUS POWER DEMAND OF A HAUL TRUCK ALONG WITH FUEL CONSUMPTION AND ASSOCIATED GHG EMISSIONS. GPS DATA PROCESSING IS IMPLEMENTED BY A SERIES OF PROCESSES SUPPORTED BY PYTHON. TRUCK TRAJECTORY INFORMATION IS STORED BY MEANS OF AN AD-HOC DATA STRUCTURE, WHICH CONSISTS OF SPACE-TIME LINEAR SEGMENTS OF EQUAL SIZE THAT CONTAIN THE SPEED AND INSTANTANEOUS ACCELERATION OF THE VEHICLE. IN THIS WAY IT IS POSSIBLE TO ESTIMATE INSTANTANEOUS POWER AT EACH POINT OF THE TRAJECTORY. THE OBTAINED RESULTS INDICATE THAT AREAS WITH HIGHER POWER CONSUMPTION COINCIDE WITH HIGHER SLOPE VARIATION IN THE TRAJECTORY, WHILE AREAS WITH LOWER CONSUMPTION COINCIDE WITH THE AREAS WHERE THE ELEVATION REMAINS CONSTANT, THIS IS REFLECTED IN FUEL CONSUMPTION RATE.