Source apportionment advances using polar plots of bivariate correlation and regression statistics

This paper outlines the development of enhanced bivariate polar plots that allow the concentrations of two pollutants to be compared using pair-wise statistics for exploring the sources of atmospheric pollutants. The new method combines bivariate polar plots, which provide source characteristic information, with pair-wise statistics that provide information on how two pollutants are related to one another. The pair-wise statistics implemented include weighted Pearson correlation and slope from two linear regression methods. The development uses a Gaussian kernel to locally weight the statistical calculations on a wind speed-direction surface together with variable-scaling. Example applications of the enhanced polar plots are presented by using routine air quality data for two monitoring sites in London, United Kingdom for a single year (2013). The London examples demonstrate that the combination of bivariate polar plots, correlation, and regression techniques can offer considerable insight into air pollution source characteristics, which would be missed if only scatter plots and mean polar plots were used for analysis. Specifically, using correlation and slopes as pair-wise statistics, long-range transport processes were isolated and black carbon (BC) contributions to PM2.5 for a kerbside monitoring location were quantified. Wider applications and future advancements are also discussed

THE IMPORTANCE OF DIRECTLY EMITTED NITROGEN DIOXIDE FROM ROAD VEHICLES TO URBAN AIR QUALITY IN THE UK

ABSTRACT Recent analyses of comprehensive ambient air pollution measurements in London have quantified the proportion of nitrogen oxides (NO X ) in vehicle exhausts that is emitted as nitrogen dioxide (NO 2 ). The analyses show that a greater proportion of NO X is emitted directly as NO 2 than previously thought. For the 43 monitoring sites considered, the mean primary NO 2 volume fraction was calculated to be 11.2 %. Emissions of primary NO 2 of this magnitude appear to explain approximately 21 % of measured NO 2 concentrations on average. However, at many congested locations with a high proportion of diesel vehicles, primary NO 2 emissions are thought to explain over 30 % of observed concentrations. For high percentile values of NO 2 , the primary NO 2 contribution can dominate ambient concentrations. These results have implications for the management of air quality in urban areas since it is likely that directly emitted NO 2 would respond differently to NO X control measures compared with that chemically produced in the atmosphere. In particular, the source apportionment of NO 2 concentrations can be very different to NO X close to roads in London. The results also have implications for dispersion modelling studies of NO 2 , where it is generally assumed that a fixed 5.0 % of the NO X emitted by vehicles is in the form of NO 2 . The implications of the increased use of particle traps on the London bus fleet that produce NO 2 to assist in the oxidation of particles is also assessed, together with the potential effects of the London Congestion Charging Scheme

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

Post-Dieselgate : Evidence of NOx Emission Reductions Using On-Road Remote Sensing

The Dieselgate scandal which broke in September 2015 demonstrated that vehicle manufacturers, such as the Volkswagen Group (VWG), engaged in software-based manipulation which led to vehicles passing laboratory-based emission testing limits but were far more polluting while being driven on roads. Using 23 000 on-road remote sensing measurements of light-duty Euro 5 diesel vehicles in the United Kingdom between 2012 and 2018, VWG vehicles with the "Dieselgate-affected" EA189 engine demonstrated anomalous NOx emission behavior between the pre- and post-Dieselgate periods which was not observed in other vehicle makes or models. These anomalous changes can be explained by voluntary VWG hardware and software fixes which have led to improved NOx emission control. The VGW 1.6 L vehicles, with a simple hardware fix and a software upgrade, resulted in a 36% reduction in NOx, whereas the 2.0 L vehicles that required a software-only fix showed a 30% reduction in NOx once controlled for ambient temperature effects. These results show that even minor changes or upgrades can considerably reduce NOx emissions, which has implications for future emission control activities and local air quality

Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories

To date, direct validation of city-wide emissions inventories for air pollutants has been difficult or impossible. However, recent technological innovations now allow direct measurement of pollutant fluxes from cities, for comparison with emissions inventories, which are themselves commonly used for prediction of current and future air quality and to help guide abatement strategies. Fluxes of NOx were measured using the eddy-covariance technique from an aircraft flying at low altitude over London. The highest fluxes were observed over central London, with lower fluxes measured in suburban areas. A footprint model was used to estimate the spatial area from which the measured emissions occurred. This allowed comparison of the flux measurements to the UK's National Atmospheric Emissions Inventory (NAEI) for NOx, with scaling factors used to account for the actual time of day, day of week and month of year of the measurement. The comparison suggests significant underestimation of NOx emissions in London by the NAEI, mainly due to its under-representation of real world road traffic emissions. A comparison was also carried out with an enhanced version of the inventory using real world driving emission factors and road measurement data taken from the London Atmospheric Emissions Inventory (LAEI). The measurement to inventory agreement was substantially improved using the enhanced version, showing the importance of fully accounting for road traffic, which is the dominant NOx emission source in London. In central London there was still an underestimation by the inventory of 30-40% compared with flux measurements, suggesting significant improvements are still required in the NOx emissions inventory

An increasing role for solvent emissions and implications for future measurements of volatile organic compounds : Solvent emissions of VOCs

Volatile organic compounds (VOCs) are a broad class of air pollutants which act as precursors to tropospheric ozone and secondary organic aerosols. Total UK emissions of anthropogenic VOCs peaked in 1990 at 2,840 kt yr -1 and then declined to approximately 810 kt yr -1 in 2017 with large reductions in road transport and fugitive fuel emissions. The atmospheric concentrations of many non-methane hydrocarbons (NMHC) in the UK have been observed to fall over this period in broadly similar proportions. The relative contribution to emissions from solvents and industrial processes is estimated to have increased from approximately 35% in 1990 to approximately 63% in 2017. In 1992, UK national monitoring quantified 19 of the 20 most abundant individual anthropogenic VOCs emitted (all were NMHCs), but by 2017 monitoring captured only 13 of the top 20 emitted VOCs. Ethanol is now estimated to be the most important VOC emitted by mass (in 2017 approx. 136 kt yr -1 and approx. 16.8% of total emissions) followed by n-butane (52.4 kt yr -1) and methanol (33.2 kt yr -1). Alcohols have grown in significance representing approximately 10% of emissions in 1990 rising to approximately 30% in 2017. The increased role of solvent emissions should now be reflected in European monitoring strategies to verify total VOC emission reduction obligations in the National Emissions Ceiling Directive. Adding ethanol, methanol, formaldehyde, acetone, 2-butanone and 2-propanol to the existing NMHC measurements would provide full coverage of the 20 most significant VOCs emitted on an annual mass basis. This article is part of a discussion meeting issue 'Air quality, past present and future'

Indoor Air Quality

This is a report from the Air Quality Expert Group to the Department for Environment, Food and Rural Affairs; Scottish Government; Welsh Government; and Department of Agriculture, Environment and Rural Affairs in Northern Ireland, on indoor air quality in the UK. The information contained within this report represents a review of the understanding and evidence available at the time of writing

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

Photothermal Heterodyne Imaging of Individual Metallic Nanoparticles: Theory versus Experiments

We present the theoretical and detailed experimental characterizations of Photothermal Heterodyne Imaging. An analytical expression of the photothermal heterodyne signal is derived using the theory of light scattering from a fluctuating medium. The amplitudes of the signals detected in the backward and forward configurations are compared and their frequency dependences are studied. The application of the Photothermal Heterodyne detection technique to the absorption spectroscopy of individual gold nanoparticles is discussed and the detection of small individual silver nanoparticles is demonstrated