David C. Carslaw

openair - An R package for air quality data analysis

openair is an R package primarily developed for the analysis of air pollution measurement data but which is also of more general use in the atmospheric sciences. The package consists of many tools for importing and manipulating data, and undertaking a wide range of analyses to enhance understanding of air pollution data. In this paper we consider the development of the package with the purpose of showing how air pollution data can be analysed in more insightful ways. Examples are provided of importing data from UK air pollution networks, source identification and characterisation using bivariate polar plots, quantitative trend estimates and the use of functions for model evaluation purposes. We demonstrate how air pollution data can be analysed quickly and efficiently and in an interactive way, freeing time to consider the problem at hand. One of the central themes of openair is the use of conditioning plots and analyses, which greatly enhance inference possibilities. Finally, some consideration is given to future developments.

Conditional bivariate probability function for source identification

In this paper a new receptor modelling method is developed to identify and characterise emission sources. The method is an extension of the commonly used conditional probability function (CPF). The CPF approach is extended to the bivariate case to produce a conditional bivariate probability function (CBPF) plot using wind speed as a third variable plotted on the radial axis. The bivariate case provides more information on the type of sources being identified by providing important dispersion characteristic information. By considering intervals of concentration, considerably more source information can be revealed that is absent in the basic CPF or CBPF. We demonstrate the application of the approach by considering an area of high source complexity, where many new sources can be identified and characterised compared with currently used techniques. Dispersion model simulations are undertaken to verify the approach. The technique has been made available through the openair R package.

An empirical approach for the prediction of daily mean PM10 concentrations

Abstract An empirical model has been devised to predict concentrations of PM 10 at background and roadside locations in London. Factors to calculate primary PM 10 and PM 2.5 concentrations are derived from annual mean NO X , PM 2.5 and PM 10 measurements across London and south east England. These factors are used to calculate daily means for the primary and non-primary PM 10 fractions for the London area. The model accurately predicts daily mean PM 10 and EU Directive Limit values across a range of sites from kerbside to rural. Predictions of future PM 10 can be made using the expected reductions in secondary PM 10 and site specific annual mean NO X predicted from emission inventories and dispersion modelling. The model suggests that the EU Directive Limit values will be exceeded close to many of Londons busiest roads, and perhaps at central background sites should there be a repeat of 1996 meteorological conditions during 2005. A repeat of 1997 meteorology conditions during 2005 would lead to the EU Limit Value being exceeded alongside the busiest central London roads only. The model is applicable for London and south east England but the methodology could be applied elsewhere at a city or regional level. The model relies on the currently observed ratio between NO X and PM 10 . This ratio has remained constant over the last 4 years but might change in the future. The NO X :PM 10 ratio derived from measurements and used in this model, implies that emission inventories might over estimate primary PM 10 by more than 50%.

Characterising and understanding emission sources using bivariate polar plots and k-means clustering

This paper develops the idea of bivariate polar plots as a method for source detection and characterisation. Bivariate polar plots provide a graphical method for showing the joint wind speed, wind direction dependence of air pollutant concentrations. Bivariate polar plots provide an effective graphical means of discriminating different source types and characteristics. In the current work we apply k-means clustering techniques directly to bivariate polar plots to identify and group similar features. The technique is analogous to clustering applied to back trajectories at the regional scale. When applied to data from a monitoring site with high source complexity it is shown that the technique is able to identify important clusters in ambient monitoring data that additional analysis shows to exhibit different source characteristics. Importantly, this paper links identified clusters to known emission characteristics to confirm the inferences made in the analysis. The approaches developed should have wide application to the analysis of air pollution monitoring data and have been made freely available as part of the openair R package.

The efficacy of low emission zones in central London as a means of reducing nitrogen dioxide concentrations

Abstract This paper considers the effects of different strategies that might be considered to reduce the impact made by road traffic on air pollution in London. The management of road traffic in large urban areas is one of many options being considered to reduce pollutant emissions to meet statutory air pollution objectives. Increasingly, the concept of a low emission zone (LEZ) is being proposed as a means of achieving this reduction. An assessment has been made of different LEZ scenarios in central London, which involve reducing traffic flow or modifying the vehicle technology mix. Methods of predicting annual mean nitrogen dioxide concentrations utilising comprehensive traffic data and air pollution measurements have been used to develop empirical prediction models. Comparisons with statutory air pollution objectives show that significant action will be required to appreciably decrease concentrations of nitrogen dioxide close to roads. The non-linear atmospheric chemistry leading to the formation of nitrogen dioxide, results in a complex relationship between vehicle emissions and ambient concentrations of the pollutant. We show that even ambitious LEZ scenarios in central London produce concentrations of nitrogen oxides that are achieved through a “do nothing” scenario only five years later.

The gas-phase chemistry of urban atmospheres

This paper reviews the chemistry of urban atmospheres,using recent measurement data to highlight the key concepts. We briefly summarise historical reports of air pollution and the impact that human activities have had on urban atmospheres since the IndustrialRevolution. Although pollution events in the first half of the 20th century were caused by high concentrations of smoke and sulphur dioxide, photochemical pollution has become the major problem in most of the major citiesaround the world. The chemistry of photochemical pollution episodes is discussed in some detail, particularly the crucial role played by volatile organic carbon and nitrogen oxides. Issues to be considered when modelling the chemistry of urban areas are briefly summarised, such as the uncertainties in chemical mechanisms and emission inventories, as well as the complexities of dynamical processes. Finally, we present some recent issues in urban chemistry, including the discovery that the amount of volatile organic carbon in urban atmospheres may be grossly under-estimated. We also use modelling resultsto show the importance of the reaction of ozone with reactive hydrocarbons as a radical source in urban atmospheres. Finally, the use of NOX-NO2 relationships to predict annual mean NO2 concentrations is discussed.

Measurement of NOx fluxes from a tall tower in central London, UK and comparison with emissions inventories

Direct measurements of NOx concentration and flux were made from a tall tower in central London, UK as part of the Clean Air for London (ClearfLo) project. Fast time resolution (10 Hz) NO and NO2 concentrations were measured and combined with fast vertical wind measurements to provide top-down flux estimates using the eddy covariance technique. Measured NOx fluxes were usually positive and ranged from close to zero at night to 2000-8000 ng m(-2) s(-1) during the day. Peak fluxes were usually observed in the morning, coincident with the maximum traffic flow. Measurements of the NOx flux have been scaled and compared to the UK National Atmospheric Emissions Inventory (NAEI) estimate of NOx emission for the measurement footprint. The measurements are on average 80% higher than the NAEI emission inventory for all of London. Observations made in westerly airflow (from parts of London where traffic is a smaller fraction of the NOx source) showed a better agreement on average with the inventory. The observations suggest that the emissions inventory is poorest at estimating NOx when traffic is the dominant source, in this case from an easterly direction from the BT Tower. Agreement between the measurements and the London Atmospheric Emissions Inventory (LAEI) are better, due to the more explicit treatment of traffic flow by this more detailed inventory. The flux observations support previous tailpipe observations of higher NOx emitted from the London vehicle diesel fleet than is represented in the NAEI or predicted for several EURO emission control technologies. Higher-than-anticipated vehicle NOx is likely responsible for the significant discrepancies that exist in London between observed NOx and long-term NOx projections.

Lower vehicular primary emissions of NO 2 in Europe than assumed in policy projections

Many European countries do not meet legal air quality standards for ambient nitrogen dioxide (NO2) near roads; a problem that has been forecasted to persist to 2030. Although European air quality standards regulate NO2 concentrations, emissions standards for new vehicles instead set limits for NOx—the combination of nitric oxide (NO) and NO2. From around 1990 onwards, the total emissions of NOx declined significantly in Europe, but roadside concentrations of NO2—a regulated species—declined much less than expected. This discrepancy has been attributed largely to the increasing usage of diesel vehicles in Europe and more directly emitted tailpipe NO2. Here we apply a data-filtering technique to 130 million hourly measurements of NOx, NO2 and ozone (O3) from roadside monitoring stations across 61 urban areas in Europe over the period 1990–2015 to estimate the continent-wide trends of directly emitted NO2. We find that the ratio of NO2 to NOx emissions increased from 1995 to around 2010 but has since stabilized at a level that is substantially lower than is assumed in some key emissions inventories. The proportion of NOx now being emitted directly from road transport as NO2 is up to a factor of two smaller than the estimates used in policy projections. We therefore conclude that there may be a faster attainment of roadside NO2 air quality standards across Europe than is currently expected.The fraction of NO2 in NOx emitted from European road transport is up to a factor of two smaller than used in policy projections, suggests an analysis of 130 million roadside observations. Roadside air quality standards may thus be obtained faster.

Crucial Role for Outdoor Chemistry in Ultrafine Particle Formation in Modern Office Buildings

In the developed world, we spend most of our time indoors, where we receive the majority of our exposure to air pollution. This paper reports model simulations of PM2.5 and ozone concentrations in identical landscape offices in three European cities: Athens, Helsinki, and Milan. We compare concentrations during an intense heatwave in August 2003 with a meteorologically more typical August in 2009. During the heatwave, average indoor ozone concentrations during office hours were 44, 19, and 41 ppb in Athens, Helsinki, and Milan respectively, enhanced by 7, 4, and 17 ppb respectively relative to 2009. Total predicted PM2.5 concentrations were 13.5, 3.6, and 17.2 μg m(-3) in Athens, Helsinki, and Milan respectively, enhanced by 0.5, 0.4, and 6.7 μg m(-3) respectively relative to 2009: the three cities were affected to differing extents by the heatwave. A significant portion of the indoor PM2.5 derived from gas-phase chemistry outdoors, producing 2.5, 0.8, and 4.8 μg m(-3) of the total concentrations in Athens, Helsinki, and Milan, respectively. Despite filtering office inlet supplies to remove outdoor particles, gas-phase precursors for particles can still enter offices, where conditions are ripe for new particles to form, particularly where biogenic emissions are important outdoors. This result has important implications for indoor air quality, particularly given the current trend for green walls on buildings, which will provide a potential source of biogenic emissions near to air inlet systems.

Dispersion modelling considerations for transient emissions from elevated point sources

Abstract Air pollution dispersion modelling of tall stacks that emit infrequently during periods of a year poses various problems for dispersion modellers. One of the most significant issues is that the predictions of peak concentrations become increasingly susceptible to the prevailing meteorology as the amount of time a source emits during a year decreases. A probabilistic approach has been adopted by randomly sampling the predicted concentrations at different receptor locations over 5 different years. This approach is used to explore how source-operating time affects high-percentile concentration predictions of SO2 from a single stack and a network of four stacks. For locations that are rarely downwind of sources and for low operational times, the inter-annual variability of predicted concentrations is shown to be high. Furthermore, the range of possible concentrations for a particular year is wide and suggests that model results under such conditions could easily be atypical, even when several years of meteorological data are used. The modelling also highlights how the probability distributions are affected by plant operating patterns for two cases: first, where sources are assumed to emit simultaneously and second, where they emit independent of one another. By considering ensembles in this manner, it is possible to derive median predicted concentrations and information concerning the probability of exceeding a certain concentration, thus providing decision makers with a richer source of information.