Ammonia exhaust tailpipe mixing ratios (ppm) from 47 light-duty gasoline motor vehicles were quantified using a portable ECM miniPEMS over on-road Real Driving Emissions (RDE) tests. The ECM miniPEMS was also used to retrieve various parameters data from the vehicle’s OBDII port such as vehicle speed, the revolution per minute (RPM) readings, engine load percentages, air-fuel ratio, and the temperature of the three-way catalyst converters. The vehicle exhaust temperature was also measured by the ECM miniPEMS using Type K thermocouples. The RDE tests were conducted on a 5.3-mile predefined urban testing route designed using the local road network in the City of Logan, Utah. The urban testing route included residential and highway roads, uphill and downhill road segments, stop signs, traffic lights, and a school zone with a reduced speed limit. The test cycle was coded as UWRL-UDTC (The Utah Water Research Laboratory Urban Driving Test Cycle). The portable Applus Autologic 5-Gas Portable Vehicle Gas Analyzer (model 310-0220) was also used to measure tailpipe mixing ratios (ppm) of post-catalyst carbon monoxide. Both instruments were carried onboard the tested vehicles during the test, while their sensors were mounted in the tested vehicle’s engine exhaust. The vehicle test sample of 47 light-duty gasoline motor vehicles was chosen to represent the same tier-level distribution as the on-road gasoline vehicle fleet along the Wasatch Front and the Cache County located in the U.S. State of Utah. Vehicle specifications including type, make, model, model year, mileage reading, engine displacement, number of cylinders, gross vehicle weight rating (GVWR), and tailpipe diameter were also collected for all tested vehicles. Atmospheric temperature and pressure at the time of testing were also measured. All the data collected throughout the project are included in the "Content" section of this resource. The "Content" section also includes an R Jupyter notebook used to analyze collected data. The mixing ratios of exhaust gases were first converted into emission rates (mg per mile), then, many descriptive and inferential statistical analyses and correlation analyses were performed. Many plots were also generated using the R script included in the Jupyter notebook. The main outcomes of this study can be found in the article included in the "Related Resources" section of this resource.