Source apportionment of wide range particle size spectra and black carbon collected at the airport of Venice (Italy)

Atmospheric particles are of high concern due to their toxic properties and effects on climate, and large airports are known as significant sources of particles. This study investigates the contribution of the Airport of Venice (Italy) to black carbon (BC), total particle number concentrations (PNC) and particle number size distributions (PNSD) over a large range (14 nm-20 mu m). Continuous measurements were conducted between April and June 2014 at a site located 110 m from the main taxiway and 300 m from the runway. Results revealed no significantly elevated levels of BC and PNC, but exhibited characteristic diurnal profiles. PNSD were then analysed using both k-means cluster analysis and positive matrix factorization. Five clusters were extracted and identified as midday nucleation events, road traffic, aircraft, airport and nighttime pollution. Six factors were apportioned and identified as probable sources according to the size profiles, directional association, diurnal variation, road and airport traffic volumes and their relationships to micrometeorology and common air pollutants. Photochemical nucleation accounted for similar to 44% of total number, followed by road + shipping traffic (26%). Airport-related emissions accounted for similar to 20% of total PNC and showed a main mode at 80 nm and a second mode beyond the lower limit of the SMPS (<14 nm). The remaining factors accounted for less than 10% of number counts, but were relevant for total volume concentrations: nighttime nitrate, regional pollution and local resuspension. An analysis of BC levels over different wind sectors revealed no especially significant contributions from specific directions associated with the main local sources, but a potentially significant role of diurnal dynamics of the mixing layer on BC levels. The approaches adopted in this study have identified and apportioned the main sources of particles and BC at an international airport located in area affected by a complex emission scenario. The results may underpin measures for improving local and regional air quality, and health impact assessment studies. (C) 2016 Elsevier Ltd. All rights reserved

Real-world assessment of vehicle air pollutant emissions subset by vehicle type, fuel and EURO class: New findings from the recent UK EDAR field campaigns, and implications for emissions restricted zones

This paper reports upon and analyses vehicle emissions measured by the Emissions Detecting and Reporting (EDAR) system, a Vehicle Emissions Remote Sensing System (VERSS) type device, used in five UK based field campaigns in 2016 and 2017. In total 94,940 measurements were made of 75,622 individual vehicles during the five campaigns. The measurements are subset into vehicle type (bus, car, HGV, minibus, motorcycle, other, plant, taxi, van, and unknown), fuel type for car (petrol and diesel), and EURO class, and particulate matter (PM), nitric oxide (NO) and nitrogen dioxide (NO2) are reported. In terms of recent EURO class emission trends, NO and NOx emissions decrease from EURO 5 to EURO 6 for nearly all vehicle categories. Interestingly, taxis show a marked increase in NO2 emissions from EURO 5 to EURO 6. Perhaps most concerningly is a marked increase in PM emissions from EURO 5 to EURO 6 for HGVs. Another noteworthy observation was that vans, buses and HGVs of unknown EURO class were often the dirtiest vehicles in their classes, suggesting that where counts of such vehicles are high, they will likely make a significant contribution to local emissions. Using Vehicle Specific Power (VSP) weighting we provide an indication of the magnitude of the on-site VERSS bias and also a closer estimate of the regulatory test/on-road emissions differences. Finally, a new ‘EURO Updating Potential’ (EUP) factor is introduced, to assess the effect of a range of air pollutant emissions restricted zones either currently in use or marked for future introduction. In particular, the effects of the London based Low Emission Zone (LEZ) and Ultra-Low Emissions Zone (ULEZ), and the proposed Birmingham based Clean Air Zone (CAZ) are estimated. With the current vehicle fleet, the impacts of the ULEZ and CAZ will be far more significant than the LEZ, which was introduced in 2008

Detecting high emitting vehicle subsets using emission remote sensing systems

It is often assumed that a small proportion of a given vehicle fleet produces a disproportionate amount of air pollution emissions. If true, policy actions to target the highly polluting section of the fleet could lead to significant improvements in air quality. In this paper, high-emitter vehicle subsets are defined and their contributions to the total fleet emission are assessed. A new approach, using enrichment factor in cumulative Pareto analysis is proposed for detecting high emitter vehicle subsets within the vehicle fleet. A large dataset (over 94,000 remote-sensing measurements) from five UK-based EDAR (emission detecting and reporting system) field campaigns for the years 2016–17 is used as the test data. In addition to discussions about the high emitter screening criteria, the data analysis procedure and future issues of implementation are discussed. The results show different high emitter trends dependent on the pollutant investigated, and the vehicle type investigated. For example, the analysis indicates that 23 % and 51 % of petrol and diesel cars were responsible for 80 % of NO emissions within that subset of the fleet, respectively. Overall, the contributions of vehicles that account for 80 % of total fleet emissions usually reduce with EURO class improvement, with the subset fleet emissions becoming more homogenous. The high emitter constituent was more noticeable for pollutant PM compared with the other gaseous pollutants, and it was also more prominent for petrol cars when compared to diesel ones

Laser-induced breakdown spectroscopy: a tool for real-time, in vitro and in vivo identification of carious teeth

BACKGROUND: Laser Induced Breakdown Spectroscopy (LIBS) can be used to measure trace element concentrations in solids, liquids and gases, with spatial resolution and absolute quantifaction being feasible, down to parts-per-million concentration levels. Some applications of LIBS do not necessarily require exact, quantitative measurements. These include applications in dentistry, which are of a more "identify-and-sort" nature – e.g. identification of teeth affected by caries. METHODS: A one-fibre light delivery / collection assembly for LIBS analysis was used, which in principle lends itself for routine in vitro / in vivo applications in a dental practice. A number of evaluation algorithms for LIBS data can be used to assess the similarity of a spectrum, measured at specific sample locations, with a training set of reference spectra. Here, the description has been restricted to one pattern recognition algorithm, namely the so-called Mahalanobis Distance method. RESULTS: The plasma created when the laser pulse ablates the sample (in vitro / in vivo), was spectrally analysed. We demonstrated that, using the Mahalanobis Distance pattern recognition algorithm, we could unambiguously determine the identity of an "unknown" tooth sample in real time. Based on single spectra obtained from the sample, the transition from caries-affected to healthy tooth material could be distinguished, with high spatial resolution. CONCLUSIONS: The combination of LIBS and pattern recognition algorithms provides a potentially useful tool for dentists for fast material identification problems, such as for example the precise control of the laser drilling / cleaning process

Extreme Concentrations of Nitric Oxide Control Daytime Oxidation and Quench Nocturnal Oxidation Chemistry in Delhi during Highly Polluted Episodes

Delhi, India, suffers from periods of very poor air quality, but little is known about the chemical production of secondary pollutants in this highly polluted environment. During the postmonsoon period in 2018, extremely high nighttime concentrations of NOx (NO and NO2) and volatile organic compounds (VOCs) were observed, with median NOx mixing ratios of ∼200 ppbV (maximum of ∼700 ppbV). A detailed chemical box model constrained to a comprehensive suite of speciated VOC and NOx measurements revealed very low nighttime concentrations of oxidants, NO3, O3, and OH, driven by high nighttime NO concentrations. This results in an atypical NO3 diel profile, not previously reported in other highly polluted urban environments, significantly perturbing nighttime radical oxidation chemistry. Low concentrations of oxidants and high nocturnal primary emissions coupled with a shallow boundary layer led to enhanced early morning photo-oxidation chemistry. This results in a temporal shift in peak O3 concentrations when compared to the premonsoon period (12:00 and 15:00 local time, respectively). This shift will likely have important implications on local air quality, and effective urban air quality management should consider the impacts of nighttime emission sources during the postmonsoon period

Short-term exposure to traffic-related air pollution and daily mortality in London, UK.

Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 μg/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC

Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study

Measurement and source apportionment of atmospheric pollutants are crucial for the assessment of air quality and the implementation of policies for their improvement. In most cases, such measurements use expensive regulatory-grade instruments, which makes it difficult to achieve wide spatial coverage. Low-cost sensors may provide a more affordable alternative, but their capability and reliability in separating distinct sources of particles have not been tested extensively yet. The present study examines the ability of a low-cost optical particle counter (OPC) to identify the sources of particles and conditions that affect particle concentrations at an urban background site in Birmingham, UK. To help evaluate the results, the same analysis is performed on data from a regulatory-grade instrument (SMPS, scanning mobility particle sizer) and compared to the outcomes from the OPC analysis. The analysis of the low-cost sensor data manages to separate periods and atmospheric conditions according to the level of pollution at the site. It also successfully identifies a number of sources for the observed particles, which were also identified using the regulatory-grade instruments. The low-cost sensor, due to the particle size range measured (0.35 to 40 µm), performed rather well in differentiating sources of particles with sizes greater than 1 µm, though its ability to distinguish their diurnal variation, as well as to separate sources of smaller particles, at the site was limited. The current level of source identification demonstrated makes the technique useful for background site studies, where larger particles with smaller temporal variations are of significant importance. This study highlights the current capability of low-cost sensors in source identification and differentiation using clustering approaches. Future directions towards particulate matter source apportionment using low-cost OPCs are highlighted