Evaluation of the point sampling method and inter-comparison of remote emission sensing systems for screening real-world car emissions.

Emissions from internal combustion vehicles are currently not properly monitored throughout their life cycle. Remote emission sensing (RES) is a technology that can measure emissions under real driving conditions without contact. Current light extinction based RES systems are capable of providing emission factors for various gases, but lack accuracy for particulate matter (PM). Point Sampling (PS) is an extraction-based RES technique that can measure gases as well as various particle metrics such as black carbon or particle number. In this work, we evaluated the performance of a recently developed PS system and the state-of-the-art light extinction based remote sensing devices EDAR (HEAT) and ORSD (OPUS RSE) during co-location measurements. Validation measurements with portable emission measurement systems and emissions screening of several thousand cars in three European cities provide detailed insights into system's performance. Meteorological evaluations showed that the PS capture rate is strongly influenced by wind, but no other weather influences were found. Both light extinction based systems are unable to measure during rain. We found that all three systems tested were capable of screening NOx emissions from pre-Euro 6 diesel cars. Measurement results show the ability of the PS system to quantify high and low PM emitters equally well. The open-path RES systems (EDAR, ORSD) are capable of estimating PM emissions from pre-Euro 5 diesel cars. However, deficiencies of open-path RES systems are evident in the quantification of PM emissions from newer engine technologies (diesel Euro 5 and beyond) and from petrol cars. The PS system has a 2 to 5 times lower capture rate than open-path RES systems, but the PS measurement results are more accurate (more than 5 times for PM and more than 1.35 times for NOx). The good accuracy of individual measurements makes PS a powerful tool for reliable high emitter identification.

Can accurate distance-specific emissions of nitrogen oxide emissions from cars be determined using remote sensing without measuring exhaust flowrate?

Portable Emission Measurement Systems (PEMS) are commonly used to measure absolute (mass per unit distance) emissions of a range of pollutants from road vehicles under real driving conditions. Because measuring large numbers of vehicles with PEMS is impractical, this paper investigates how vehicle emission remote sensing device (RSD) can supplement the use of PEMS. We simulate whether remote sensing measurements can accurately predict a vehicle's real-world distance-specific nitrogen oxides (NOX) emissions using RSD without measuring its exhaust flow rate. The approach uses readily available type-approval carbon dioxide (CO2) emission data together with average real-world divergences from studies based on user-reported fuel economy data. We find that at least 30 RS measurements from a given vehicle's journey are needed to reach a mean absolute error of 30% compared to a large reference data set of individual PEMS measurements. With that condition met, it is concluded that estimates agree well with actual NOX emissions from cars and the applied method does not introduce a systematic bias. It is also found that the accuracy of estimates for distance-specific NOX emissions does not significantly improve when more than 300 remote-sensing samples are available, with a mean absolute error converging to 23%. We conclude that this method could be used to screen large car fleets and identify vehicles or group of vehicles that are likely grossly exceeding air pollution standards.

Distance-based emission factors from vehicle emission remote sensing measurements.

Vehicle emission remote sensing has the potential to provide detailed emissions information at a highly disaggregated level owing to the ability to measure thousands of vehicles in a single day. Fundamentally, vehicle emission remote sensing provides a direct measure of the molar volume ratio of a pollutant to carbon dioxide, from which fuel-based emissions factors can readily be calculated. However, vehicle emissions are more commonly expressed in emission per unit distance travelled e.g. grams per km or mile. To express vehicle emission remote sensing data in this way requires an estimate of the fuel consumption at the time of the emission measurement. In this paper, an approach is developed based on vehicle specific power that uses commonly measured or easily obtainable vehicle information such as vehicle speed, acceleration and mass. We test the approach against 55 independent comprehensive PEMS measurements for Euro 5 and 6 gasoline and diesel vehicles over a wide range of driving conditions and find good agreement between the method and PEMS data. The method is applied to individual vehicle model types to quantify distance-based emission factors. The method will be appropriate for application to larger vehicle emission remote sensing databases, thus extending real-world distance-based vehicle emissions information.

A study on the CO2 and NOx emissions performance of Euro 6 diesel vehicles under various chassis dynamometer and on-road conditions including latest regulatory provisions.

The current study presents a detailed analysis of the gaseous emissions, focusing on CO2 and NOx, of diesel vehicles under several operating conditions. An assessment is also made on the impact and effectiveness of the Real Driving Emissions (RDE) test, which is mandatory by the European Union (EU) type approval regulation for passenger cars since September 2017. The method followed comprises emissions measurement tests on three Euro 6 diesel vehicles, under laboratory and various on-road operation conditions. Chassis dynamometer tests in the laboratory showed that emissions over the current type approval test (World-wide harmonized Light-duty Test Procedure or WLTP), and over the former one (New European Driving Cycle or NEDC), poorly reflect real-world levels. However, the most demanding CADC testing comes closer to real drive emissions. Comparison of driving conditions on the chassis dynamometer over different driving cycles and on the road reveals that the emission performance substantially varies between different tests, even for apparently similar operation conditions. The NOx emissions reduction strategy of pre-RDE monitoring Euro 6 vehicles seems to be optimized for the NEDC driving conditions, which are not representative of the real-world driving conditions. The real-world emissions during normal driving conditions are effectively captured with the new RDE test, however driving the vehicle dynamically, at conditions outside the RDE regulation boundaries, results to disproportional high emissions. This is a significant shortcoming which might be critical for populations living on hilly areas or those close to specific micro-environments, such as highway entrance ramps, traffic lights, etc.