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Nitrogen Dioxide is both a primary pollutant with direct health effects and a key precursor of the secondary pollutant ozone. This paper reports on the development, characterisation and test flight of the Atmospheric Nitrogen Dioxide Imager (ANDI) remote sensing system. The ANDI system includes an imaging (UV)-vis grating spectrometer able to capture scattered sunlight spectra for the determination of tropospheric nitrogen dioxide (NO2) concentrations by way of DOAS slant column density and vertical column density measurements. Results are shown for an ANDI test flight over Leicester City in the UK. Retrieved NO2 columns at a surface resolution of 80 m x 20 m revealed hot spots in a series of locations around Leicester City, including road junctions, the train station, major car parks, areas of heavy industry, a nearby airport (East Midlands) and a power station (Ratcliffe-on-Soar). In the city centre the dominant source of NO2 emissions was identified as road traffic, contributing to a background concentration as well as producing localised hot spots. Quantitative analysis revealed a significant urban increment over the city centre which increased throughout the flight. [ABSTRACT FROM AUTHOR]

We present an algorithm for retrieving tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) from ground-based zenith-sky (ZS) measurements of scattered sunlight. The method is based on a four-step approach consisting of (1) the Differential Optical Absorption Spectroscopy (DOAS) analysis of ZS radiance spectra using a fixed reference spectrum corresponding to low NO2 absorption, (2) the determination of the residual amount in the reference spectrum using a Langley-plot-type method, (3) the removal of the stratospheric content from the daytime total measured slant column based on stratospheric VCDs measured at sunrise and sunset, and simulation of the rapid 10 NO2 diurnal variation, (4) the retrieval of tropospheric VCDs by dividing the resulting tropospheric slant columns by appropriate air mass factors (AMFs). These steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a ZS dataset acquired with a Multi-AXis (MAX-) DOAS instrument during the Cabauw (51.97° N, 4.93° E, sea level) Intercomparison campaign for Nitro15 gen Dioxide measuring Instruments (CINDI) held from the 10 June to the 21 July 2009 in the Netherlands. A median value of 7.9°1015 moleccm-2 is found for the retrieved tropospheric NO2 VCDs, with maxima up to 6.0°1016 moleccm-2. The error budget assessment indicates that the overall error °TVCD on the column values is less than 28 %. In case of low tropospheric contribution, °TVCD is estimated to be around 39% and is dominated by uncertainties in the determination of the residual amount in the reference spectrum. For strong tropospheric pollution events, °TVCD drops to approximately 22% with the largest uncertainties on the determination of the stratospheric NO2 abundance and tropospheric AMFs. The tropospheric VCD amounts derived from ZS observations are compared to VCDs retrieved from o°-axis and direct-sun mea25 surements of the same MAX-DOAS instrument as well as to data from a co-located Système d'Analyse par Observations Zénithales (SAOZ) spectrometer. The retrieved tropospheric VCDs are in good agreement with the different datasets with correlation coeffcients and slopes close to or larger than 0.9. The potential of the presented ZS retrieval algorithm is further demonstrated by its successful application on a 2 year dataset, acquired at the NDACC (Network for the Detection of Atmospheric Composition Change) station Observatoire de Haute Provence (OHP; Southern France). [ABSTRACT FROM AUTHOR]

The article presents a study which examines the quantitative estimate biases for tropospheric nitrogen dioxide from the satellite sensors SCIAMACHY, OMI and GOME-2. A common standard has been used for the investigation to quantitatively evaluate the biases. A comparison of the SCIAMACHY, OMI and GOME-2 data from the MAX-DOAS observations is provided.

The article focuses on a study which seeks to quantify and mitigate the impact of inhomogeneous slit illumination on tropospheric O3, NO2, SO2, and HCHO columns obtained from measurements of the Sentinel-4 UVN imaging spectrometer. It simulates spectra for inhomogeneous ground scenes based on a combination of a radiative transfer model and spatially high resolved MODIS. The calculation of Instrument Spectral Response Functions (ISRF) is provided.

The article presents a research which investigates the assimilation of Ozone Monitoring Instrument Nitrogen Dioxide (OMI-NO2) column concentrations into the limited-area chemical transport model, Danish Eulerian Hemispheric Model (DEHM, version 2007.0). It describes the utilization of observational data in estimating background error covariance matrix, B. A comparison of the concentration fields with the ground-based observation of NO2 concentration is discussed.

Injection of aerosol particles (or their precursors) into the stratosphere to scatter solar radiation back into space, has been suggested as a solar-radiation management scheme for the mitigation of global warming. TiO2 has recently been highlighted as a possible candidate particle because of its high refractive index, but its impact on stratospheric chemistry via heterogeneous reactions is as yet unknown. In this work the heterogeneous reaction of airborne sub-micrometre TiO2 particles with N2O5 has been investigated for the first time, at room temperature and different relative humidities (RH), using an atmospheric pressure aerosol flow tube. The uptake coefficient of N2O5 onto TiO2, γ(N2O5), was determined to be ~ 1.0 × 10-3 at low RH, increasing to ~ 3 × 10-3 at 60% RH. The uptake of N2O5 onto TiO2 is then included in the UKCA chemistry climate model to assess the impact of this reaction on stratospheric chemistry. While the impact of TiO2 on the scattering of solar radiation is chosen to be similar to the aerosol from the Mt. Pinatubo eruption, the impact of TiO2 injection on stratospheric N2O5 is much smaller. [ABSTRACT FROM AUTHOR]

In this study we develop a Secondary Inorganic Aerosol (SIA) module for the chemistry transport model MOCAGE developed at CNRM. Based on the thermodynamic equilibrium module ISORROPIA II, the new version of the model is evaluated both at the global scale and at the regional scale. The results show high concentrations of secondary inorganic aerosols in the most polluted regions being Europe, Asia and the eastern part of North America. Asia shows higher sulfate concentrations than other regions thanks to emissions reduction in Europe and North America. Using two simulations, one with and the other without secondary inorganic aerosol formation, the model global outputs are compared to previous studies, to MODIS AOD retrievals, and also to in situ measurements from the HTAP database. The model shows a better agreement in all geographical regions with MODIS AOD retrievals when introducing SIA. It also provides a good statistical agreement with in situ measurements of secondary inorganic aerosol composition: sulfate, nitrate and ammonium. In addition, the simulation with SIA gives generally a better agreement for secondary inorganic aerosols precursors (nitric acid, sulfur dioxide, ammonia) in particular with a reduction of the Modified Normalised Mean Bias (MNMB). At the regional scale, over Europe, the model simulation with SIA are compared to the in situ measurements from the EMEP database and shows a good agreement with secondary inorganic aerosol composition. The results at the regional scale are consistent with those obtained with the global simulations. The AIRBASE database was used to compare the model to regulated air quality pollutants being particulate matter, ozone and nitrogen dioxide concentrations. The introduction of the SIA in MOCAGE provides a reduction of the PM2.5 MNMB of 0.44 on a yearly basis and even 0.52 on a three spring months period (March, April, May) when SIA are maximum. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the atmospheric greenhouse gas (GHG) observations using an in-situ fourier transform infrared (FTIR) analyser. GHGs measured by the FTIR analyser are highlighted which include carbon dioxide, methane and nitrogen dioxide. The cross-sensitivies and the thermodynamic properties of the sample constituents are outlined.

Nitrous oxide (N2O) emissions are highly variable in time, with high peak emissions lasting as couple of days to weeks and low background emissions. This temporal variability is poorly understood which hampers the simulation of daily N2O emissions. In structured soils, like clay and peat, aggregates hamper the diffusion of oxygen, which leads to anaerobic microsites in the soil, favourable for denitrification. In this paper we studied the effect of aggregates in soils on the N2O emissions from denitrification. We presented a parameterization to simulate the effects of aggregates on N2O, following the mobile-immobile model concept. This parameterization was implemented in a field-scale hydrological-biogeochemical model combination. We compared the simulated fluxes with observed fluxes from a fertilized and drained peat soil with grass. The results of this study showed that aggregates strongly affect N2O emissions: peak emissions are lower, whereas the background emissions are slightly higher. Implementation of the effect of aggregates caused a decrease in the simulated annual emissions of more than 40%. The new parameterization also significantly improved the model performance to simulate observed N2O fluxes. Aggregates have more impact on the reduction of N2O than on the production of N2O. Reduction of N2O is more sensitive to changes in the drivers than production of N2O and is in that sense the key process to understand N2O emissions from denitrification. The effects of changing conditions on reduction of N2O relative to N2O production is dependent on the NO3 content of the soil. It is expected that in soils with a low NO3 content the influence of aggregates on the NO3 concentration is not negligible. This study showed that the current knowledge of the hydrological, biogeochemical and physical processes is sufficient to understand the observed N2O fluxes from a fertilized peatland. Further research is needed to test how aggregates affect the N2O fluxes in areas or periods with little NO3 in the soil. [ABSTRACT FROM AUTHOR]

The article presents a study which proposes a monitoring scheme for atmospheric chemical monitoring using instrumental line shape (ILS) of high-resolution, ground-based Fourier transform infrared (FTIR) spectrometers. The method is applying measurements using different gas cells instead of a single calibration cell with pressure gauge to provide pressure-broadened nitrogen dioxide lines. The study demonstrates that the ILS retrieval using the cell improves sensitivity of the ILS.

The article presents a two-step retrieval scheme to derive aerosol corrected tropospheric nitrogen dioxide columns from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations. It states that MAX-DOAS is a technique to measure trace gas amounts in the lower troposphere from ground-based scattered sunlight observations. It notes that tropospheric nitrogen dioxide is found in many chemical cycles such as in the formation of tropospheric zone which is toxic to humans.

The article presents a study to measure the atmospheric nitrogen dioxide with the use of long path differential optical absorption spectroscopy (LP-DOAS) based on light emitting diode (LED) in Hong Kong, China. The instrument uses a high power blue LED coupled into a telescope using a Y-fibre bundle. It uses the long-term data set in validating the ozone monitoring instrument (OMI) data product. The study finds that LP-DOAS detects a weekly cycle that the OMI cannot observe.

The article focuses on the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI) which was participated by in-situ and remote sensing instruments from all over the world. The campaign was held at Koninklijk Nederlands Meteorologisch's Instituut (KNMI) Cabauw Experimental Site for Atmospheric Research in the Netherlands. It notes that the campaign aimed to determine the accuracy of measurement techniques for the detection of atmospheric nitrogen dioxide.

The article presents a study which compares the performances of different commercial nitrogen dioxide (NO2) instruments and a NO2-LOPAP in the urban atmosphere and in a smog chamber in Santiago de Chile. A field experiment was conducted wherein chemiluminescence instruments with molybdenum or photolytic converters were compared to NO2-LOPAP with spectroscopic techniques to detect interferences. Results show strong interferences and agreements in all instruments.

The article focuses on surface reflectance anisotropy in satellite trace gas retrievals of nitrogen dioxide vertical tropospheric columns (VTC). It discusses the nitrogen dioxide VTC retrieval using MODIS bi-directional reflectance distribution function (BRDF) data. Moreover, an overview of satellite observations of tropospheric nitrogen dioxide using solar backscatter UV/VIS spectrometers is offered.

The article focuses on the impact of horizontal gradients and spatial measurement resolution on the retrieval of global vertical nitrogen dioxide distributions from SCIAMACHY limb measurements. It mentions that SCIAMACHY measurements in limb only mode on the ENVISAT satellite allow retrieving stratospheric profiles of trace gases on a global scale. Further, it adds the application of tomographic approach and acquisition of 2-D distribution fields of stratospheric trace gases in one inversion.

In this paper, we present long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground-based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate ozone monitoring instrument (OMI) satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by ∼30 % with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. An age-weighted backward-propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward-propagated HCHO data do not show a strong spatial correlation with the OMI HCHO observations. The result shows that the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %–50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants over the Yangtze River Delta as well as the effect of emission control measures during large international events, which are important for the future design of air pollution control policies. [ABSTRACT FROM AUTHOR]

In order to improve the forecasting accuracy of atmospheric pollutant concentration, a prediction model of atmospheric PM2.5 and nitrogen dioxide (NO2) concentration based on support vector regression (SVR) is established. Quantum-behaved particle swarm optimization (QPSO) algorithm is used to select the optimal parameters influencing the performance of SVR. And in order to improve the problem that the fixed SVR model is difficult to adapt to the highly nonlinear process, a simple online SVR based on re-modeling method is proposed instead of the fixed one. According to hourly PM2.5 and NO2 concentrations and meteorological conditions from May 2014 to April 2015 in Wanliu Monitoring Station of Beijing in China, the experiment is carried out based on the data of 3 months. Meanwhile, PM2.5 concentration is predicted by three different prediction methods, including the recursive prediction method, direct prediction method, and online direct prediction method. The results show that the online direct prediction method is the most accurate in the three prediction methods. In addition, compared with original particle swarm optimization (PSO) algorithm, QPSO algorithm is tested more efficiently for the improvement of global search ability and robustness during the procedure of parameter selection. Moreover, the hybrid QPSO-SVR model proposed in this paper has higher prediction accuracy and less computational time compared with the PSO-SVR model, genetic algorithm (GA)-SVR model, and grid search (GS)-SVR model, which indicates reliability and effectiveness of the QPSO-SVR model in prediction of these two pollutant concentrations. [ABSTRACT FROM AUTHOR]

GANDALF (Gas Analyzer for Nitrogen Dioxide Applying Laser-induced Fluorescence), a new instrument for the detection of nitrogen dioxide based on the laser-induced fluorescence (LIF) technique, is presented in this paper. GANDALF is designed for ground-based and airborne deployment with a robust calibration system. In the current set-up, it uses a multi-mode diode laser (447–450 nm) and performs in situ, continuous, and autonomous measurements with a laser pulse repetition rate of 5 MHz. The performance of GANDALF was tested during the summer of year 2011 (15 August–10 September) in a field experiment at Kleiner Feldberg, Germany. The location is within a forested region with an urban influence, where NOx levels were between 0.12 and 22 parts per billion by volume (ppb). Based on the field results, the limit of detection is estimated at 5–10 parts per trillion by volume (ppt) in 60 s at a signal-to-noise ratio (SNR) of 2. The overall accuracy and precision of the instrument are better than 5 % (1 σ) and 0.5%+3 ppt (1 σ min-1), respectively. A comparison of nitrogen dioxide measurements based on several techniques during the field campaign PARADE 2011 is presented to explore methodic differences. [ABSTRACT FROM AUTHOR]

In this paper we present an investigation of the spatial and temporal variability of street-level concentrations of NO2 in Hong Kong as an example of a densely populated megacity with heavy traffic. For the study we use a combination of open-path remote sensing and in situ measurement techniques that allows us to separate temporal changes and spatial patterns and analyse them separately. Two measurement campaigns have been conducted, one in December 2010 and one in March 2017. Each campaign lasted for a week which allowed us to examine diurnal cycles, weekly patterns as well as spatially resolved long-term changes. We combined a long-path differential optical absorption spectroscopy (DOAS) instrument with a cavity-enhanced DOAS and applied several normalizations to the data sets in order to make the different measurement routes comparable. For the analysis of long-term changes we used the entire unfiltered data set and for the comparison of spatial patterns we filtered out the accumulation of NO2 when stopping at traffic lights for focusing on the changes of NO2 spatial distribution instead of comparing traffic flow patterns. For the generation of composite maps the diurnal cycle has been normalized by scaling the mobile data with coinciding citywide path-averaged measurement results. An overall descending trend from 2010 to 2017 could be observed, consistent with the observations of the Ozone Monitoring Instrument (OMI) and the Environment Protection Department (EPD) air quality monitoring network data. However, long-term difference maps show pronounced spatial structures with some areas, e.g. around subway stations, revealing an increasing trend. We could also show that the weekend effect, which for the most part of Hong Kong shows reduced NO2 concentrations on Sundays and to a lesser degree on Saturdays, is reversed around shopping malls. Our study shows that spatial differences have to be considered when discussing citywide trends and can be used to put local point measurements into perspective. The resulting data set provides a better insight into on-road NO2 characteristics in Hong Kong, which helps to identify heavily polluted areas and represents a useful database for urban planning and the design of pollution control measures. [ABSTRACT FROM AUTHOR]

We describe and characterize a modular folded tubular photometer for making direct measurements of the concentrations of nitrogen dioxide (NO2) and specify how this method could be extended to measure other pollutants such as sulfur dioxide (SO2), ozone (O3), and black carbon particulate matter. Direct absorbance measurements using this photometer can be made across the spectral range from the ultraviolet (UV) to the near infrared. The absorbance cell makes use of modular components (tubular detection cells and mirror cubes) that allow construction of path lengths of up to 2m or more while maintaining low cell volumes. The long path lengths and low cell volumes enable sensitive detection of ambient air pollutants down to low part-perbillion levels for gas species and aerosol extinctions down to 1Mm-1, corresponding to ~0.1 μgm-3 for black carbon particulates. Pressure equalization throughout the stages of the absorbance measurement is shown to be critical to accurate measurements of analyte concentrations. The present paper describes the application of this photometer to direct measurements of nitrogen dioxide (NO2) and the incorporation of design features that also enable measurement of nitric oxide (NO) in the same instrument. Excellent agreement for ambient measurements along an urban roadside was found for both NO2 and NO measured by the folded tubular photometer compared to existing standard techniques. Compared to commonly used methods for measurements of NOx species, the advantages of this approach include (1) an absolute quantification for NO2 based on the Beer-Lambert law, thereby greatly reducing the frequency at which calibrations are required; (2) the direct measurement of NO2 concentration without prior conversion to NO as is required for the commonly used chemiluminescence method; (3) the use of modular components that allow construction of absorbance detection cells of varying lengths for extending the dynamic range of concentrations that can be measured; (4) a more economical instrument than other currently available direct measurement techniques for NO2; and (5) the potential for simultaneous detection of additional species such as SO2, O3, and black carbon in the same instrument. In contrast to other commercially available direct NO2 measurements, such as cavity-attenuated phase-shift spectroscopy (CAPS), the folded tubular photometer also measures NO simultaneously in the same apparatus by quantitatively converting NO to NO2 with ozone, which is then detected by direct absorbance. [ABSTRACT FROM AUTHOR]

This paper reports on the first experimental evidence of the impact of a solar proton event on the stratospheric NO2 content derived from ground-based spectrometric measurements at middle and high latitudes of the Northern Hemisphere. In October 2003, a solar proton event caused an increase in the NO2 content in the upper stratosphere by 0.6 × 1015 cm-2, which accounted for about one-third of the increase in the column NO2 content. Solar proton events may be an essential factor for variability of the column NO2 content in the atmosphere of the high and middle latitudes. [ABSTRACT FROM AUTHOR]

The PM 2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM 2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM 2.5 . In this paper, we attempted to realize the relevance analysis and short-term prediction of PM 2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM 2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO 2 , SO 2 , PM 10 ) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO 2 , PM 10 , and the daily number of microblog entries with key words ‘Beijing; Air pollution’ show high mathematical correlation with PM 2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM 2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM 2.5 and it also helps to broaden the application of big data and the multi-source data mining methods. [ABSTRACT FROM AUTHOR]

A 13-year analysis (2000-2012) of the NO2 vertical column densities derived from ground-based (GB) instruments and satellites has been carried out over the Izaña NDACC (Network for the Detection of the Atmospheric Composition Change) subtropical site. Ground-based DOAS (differential optical absorption spectroscopy) and FTIR (Fourier transform infrared spectroscopy) instruments are intercompared to test mutual consistency and then used for validation of stratospheric NO2 from OMI (Ozone Monitoring Instrument) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY). The intercomparison has been carried out taking into account the various differences existing in instruments, namely temporal coincidence, collocation, sensitivity, field of view, etc. The paper highlights the importance of considering an "effective solar zenith angle" instead of the actual one when comparing direct-sun instruments with zenith sky ones for a proper photochemical correction. Results show that NO2 vertical column densities mean relative difference between FTIR and DOAS instruments is 2.8±10.7% for a.m. data. Both instruments properly reproduce the NO2 seasonal and the interannual variation. Mean relative difference of the stratospheric NO2 derived from OMI and DOAS is -0.2±8.7% and from OMI and FTIR is -1.6±6.7%. SCIAMACHY mean relative difference is of 3.7±11.7 and -5.7±11.0% for DOAS and FTIR, respectively. Note that the days used for the intercomparison are not the same for all the pairs of instruments since it depends on the availability of data. The discrepancies are found to be seasonally dependent with largest differences in winter and excellent agreement in the spring months (AMJ). A preliminary analysis of NO2 trends has been carried out with the available data series. Results show increases in stratospheric NO2 columns in all instruments but larger values in those that are GB than that expected by nitrous oxide oxidation. The possible reasons for the discrepancy between instruments and the positive trends are discussed in the text. [ABSTRACT FROM AUTHOR]

The oxygen (Δ17 O) and nitrogen (δ15 N) isotopic compositions of atmospheric nitrate (NO 3-) are widely used as tracers of its formation pathways, precursor (nitrogen oxides (NO x) ≡ nitric oxide (NO) + nitrogen dioxide (NO 2)) emission sources, and physico-chemical processing. However, the lack of observations on the multi-isotopic composition of NO 2 perpetuates significant uncertainties regarding the quantitative links between the isotopic composition of NO x and NO 3- , which ultimately may bias inferences about NO 3- formation processes and the distribution of sources, particularly in winter urban atmospheres. We report here on the first simultaneous atmospheric observations of Δ17 O and δ15 N in NO 2 (n=16) and NO 3- (n=14). The measurements were carried out at sub-daily (∼3 h) resolution over 2 non-consecutive days in an Alpine city in February 2021. A strong diurnal signal is observed in both NO 2 and NO 3- multi-isotopic composition. Δ17 O of NO 2 and NO 3- ranges from 19.6 ‰ to 40.8 ‰ and from 18.3 ‰ to 28.1 ‰, respectively. During the day and night, the variability in Δ17 O(NO 2) is mainly driven by the oxidation of NO by ozone, with a substantial contribution from peroxy radicals in the morning. NO 3- mass balance equations, constrained by observed Δ17 O(NO 2), suggest that during the first day of sampling, most of the NO 3- was formed locally from the oxidation of NO 2 by hydroxyl radicals by day and via heterogeneous hydrolysis of dinitrogen pentoxide at night. For the second day, calculated and observed Δ17 O(NO 3-) do not match, particularly daytime values; the possible effects on Δ17 O(NO 3-) of a Saharan dust event that occurred during this sampling period and of winter boundary layer dynamics are discussed. δ15 N of NO 2 and NO 3- ranges from - 10.0 ‰ to 19.7 ‰ and from - 4.2 ‰ to 14.9 ‰, respectively. Consistent with theoretical predictions of N isotope fractionation, the observed variability in δ15 N(NO 2) is explained by significant post-emission equilibrium N fractionation. After accounting for this effect, vehicle exhaust is found to be the primary source of NO x emissions at the sampling site. δ15 N(NO 3-) is closely linked to δ15 N(NO 2) variability, bringing further support to relatively fast and local NO x processing. Uncertainties in current N fractionation factors during NO 2 to NO 3- conversion are underlined. Overall, this detailed investigation highlights the potential and necessity of simultaneously using Δ17 O and δ15 N in NO 2 and NO 3- in order to better constrain quantitative inferences about the sources and formation chemistry of NO 3- in urban environments in winter. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the application of an ensemble forecasting approach to the Prev’Air operational platform. This platform aims at forecasting maps, on a daily basis, for ozone, nitrogen dioxide and particulate matter. It relies on several air quality models which differ by their physical parameterizations, their input data and numerical strategies, so that one model may perform better with respect to observations for a given pollutant, at a given time and location. We apply sequential aggregation methods to this ensemble of models, which has already proved good potential in previous research papers. Compared to these studies, the novelties of this paper are the variety of models, the real operational context, which requires robustness assessment, and the application to several pollutants. In this paper, we first introduce the ensemble forecasting methods and the operational platform Prev’Air along with its models. Then, the sequential aggregation performance and robustness are assessed using two different data sets. The results with the discounted ridge regression method show that the errors of the forecasts are respectively reduced by at least 29%, 35% and 19% for hourly, daily and peak O3 concentrations, by 19%, 26% and 20% for hourly, daily and peak NO2 concentrations, and finally by 17%, 19% and 11% for hourly, daily and peak PM10 concentrations. At last, we give a first insight of the ensemble ability to forecast threshold exceedances. [Copyright &y& Elsevier]

Abstract: Estimating measurement uncertainty for NO2 and PM10 is a complex issue that is normally addressed by experimentalists specifically for every type of instrument and measurement. On the other hand, an estimate of the maximum expected measurement uncertainty is needed when a numerical model is to be evaluated against observations, as proposed in Thunis et al. (2012, referred to as T2012). In a companion paper (Thunis et al., 2013, referred to as T2013) a simplified formulation of the measurement uncertainty in function of the measured concentration is proposed and applied to the simpler case of Ozone. In this paper the same approach is applied for NO2 and PM10, but using different techniques for the uncertainty estimation. For NO2 the Guide to the expression of Uncertainty in Measurement JCGM (2008, referred to as GUM) approach is used and applied on each urban AirBase (1997) measurement over the year 2009. For PM10, the method of the Guide for the Demonstration of Equivalence (ECWG, 2010) is used on data obtained with two different PM samplers used in parallel either during specific monitoring campaign or as available within the AirBase database. The resulting concentration dependent measurement uncertainties are then used to update the MQO (Model Quality Objective) and MPC (Model Performance Criteria) proposed in T2012. An estimate of the measurement uncertainty for annual means is proposed as well. [Copyright &y& Elsevier]

This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon-nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels. Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia. New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°-2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as ++0.083 W m−2 for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change. [ABSTRACT FROM AUTHOR]

This paper presents a detailed laboratory characterization of a thermal dissociation chemical ionization mass spectrometer (TD-CIMS) for the atmospheric measurement of Peroxyacetyl nitrate (PAN) and its homologues (PANs). PANs are efficiently dissociated in a heated inlet and the resulting peroxy acyl radicals are reacted with I- ions in a flow tube. The mass spectrometer detects the corresponding carboxylate ions. PAN, peroxypropionyl nitrate (PPN), peroxyisobutyryl nitrate (PiBN), peroxy-n-butyryl nitrate (PnBN), peroxyacryloyl nitrate (APAN), peroxycrotonyl nitrates (CPAN) and peroxymethacryloyl nitrate (MPAN) were cross-calibrated with both a dual channel GC/ECD and a total odd-nitrogen (NOy) instrument for the NCAR TD-CIMS' typical aircraft operation conditions. In addition, the instrument sensitivity to a number of more exotic PANs (peroxyhydroxyacetyl nitrate, methoxyformyl peroxynitrate, and peroxybenzoyl nitrate) was evaluated qualitatively by comparisons with a long-path FTIR instrument. The sensitivity for PPN is slightly higher than that of PAN. Larger aliphatic and olefinic PAN compounds generally showed lower sensitivities. We postulate that these differences are owing to secondary reactions in the thermal decomposition region, which either reduce the yield of peroxy acyl radicals or cause losses of these radicals through intramolecular decomposition. The relative importance of these secondary reactions varies considerably between different PAN species. Results also indicate that the reaction of the larger peroxy acyl radicals with the ion-water cluster, I- (H2O)n proceeds about an order of magnitude faster than with I- alone, as has been observed for peroxy acetyl radicals. Sensitivity variations among the individual PAN species at very low water vapor were observed. The results call for careful evaluation of each PAN species to be measured and for each desired operating condition of a TD-CIMS instrument. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present the results obtained using three prognostic models to forecast ozone (O3) and nitrogen dioxide (NO2) levels in real-time up to 8h ahead at four stations in Bilbao (Spain). Two multilayer perceptron (MLP) based models and one multiple linear regression based model were developed. The models utilised traffic variables, meteorological variables and O3 and NO2 hourly levels as input data, which were measured from 1993 to 1994. The performances of these three models were compared with persistence of levels and the observed values. The statistics of the Model Validation Kit determined the goodness of the fit of the developed models. The results indicated improved performance for the multilayer perceptron-based models over the multiple linear regression model. Furthermore, comparisons of the results of the multilayer perceptron-based models proved that the insertion of four additional seasonal input variables in the MLP provided the ability of obtaining more accurate predictions. The comparison of the results indicated that this model performance was more efficient in the forecasts of O3 and NO2 hourly levels k hours ahead (k =1, 4, 5, 6, 7, 8), but not in the forecasted values 2 and 3h ahead. Future research in this area could allow us to improve results for the above forecasts. The multilayer perceptron modelling was developed using the MATLAB software package. [Copyright 2006 Elsevier]

GANDALF (Gas Analyzer for Nitrogen Dioxide Applying Laser-induced Fluorescence), a new instrument for the detection of nitrogen dioxide based on the laser-induced fluorescence (LIF) technique, is presented in this paper. GANDALF is designed for ground based and air-borne deployment with a robust calibration system. In the current setup, it uses a multi-mode diode laser (447-450nm) and performs in situ, continuous, and autonomous measurements with a laser pulse repetition rate of 5MHz. The performance of GANDALF was tested during the field experiment at a forested location with urban influence where NOx levels were between 0.12 and 22 parts per billion by volume (ppbv). Based on the field results, the limit of detection is estimated at 5-10 parts per trillion by volume (pptv) in 60s at a signal to noise ratio (SNR) of 2. The overall accuracy and precision of the instrument are better than 5% (1σ) and 0.5%+3pptv (1σmin-1), respectively. A comparison of nitrogen dioxide measurements based on several techniques during the field campaign is presented to explore methodic differences. [ABSTRACT FROM AUTHOR]

This paper presents the retrieval method that was developed to derive tropospheric NO2 columns from UV/VIS spectral measurements obtained with the Spectrolite Breadboard Instrument during the AROMAPEX campaign in Berlin (April 2016). A typical DOAS retrieval approach is followed. For the calculation of air mass factors this study specifically focuses on the impact of the surface reflectance, which varies considerably from pixel to pixel over this urban region. Ground-based aerosol optical thickness measurements are used as prior information. It is shown that retrieved surface reflectance shows good agreement with those derived from Landsat 8 measurements performed on the same day. Furthermore we demonstrate that tropospheric NO2 columns retrieved for pairs of adjacent pixels are self-consistent in the sense that they do not show a substantial systematic dependence on surface reflectance, in contrast to differential slant column densities. Also some cases are identified to illustrate this on a pixel-by-pixel level. An error budget is provided to quantify the impact of various assumptions on the accuracy of the retrieval of surface reflectance and tropospheric NO2 columns. Both in the morning and afternoon flight a NO2 plume is observed stretching out over Berlin from West to East. Peak values between 15 × 1015 and 20 × 1015 molec/cm² are detected, whereas - at much lower spatial resolution - OMI detects peak values between 9 × 1015 (first overpass) and 4 × 1015 molec/cm² (second overpass). [ABSTRACT FROM AUTHOR]

Tropospheric NO 2 and SO 2 concentrations are of great importance with regard to air quality, atmospheric chemistry, and climate change. Due to lack of surface monitoring stations, this study analyzes long term trend of NO 2 and SO 2 levels (2005–2014), retrieved from Ozone Monitoring Instrument (OMI) board on the NASA's Aura satellite, in an important region of China – Henan Province. Henan Province, located in North China Plain, has encountered serious air pollution problems including extremely high PM 2.5 concentrations and as one of the most polluted region in China. The satellite spatial images clearly show that high levels of both NO 2 and SO 2 are concentrated in north and northeastern regions with much lower levels observed in other parts of Henan. Both pollutants exhibit the highest levels in winter with the least in summer/spring. The temporal trend analysis based on moving average of deseasonalized and decyclic data indicates that for NO 2 , there is a continuous increasing pattern from 2005 to 2011 at 6.4% per year, thereafter, it shows a decreasing trend (10.6% per year). As for SO 2 , the increasing trend is about 16% per year from 2005 to 2007 with decreasing rate 7% per year from 2007 to 2014. The economic development with incredible annual 11% GDP growth in Henan is responsible for increasing levels of NO 2 and SO 2 . The observed decreasing SO 2 level starting in 2007 is due to reduced SO 2 emission, utilization of flue gas desulfurization (FGD) devices and to some extent, in preparation of Beijing 2008 Olympic Games. On the other hand, increasing vehicle numbers (155% from 2006 to 2012) and coal consumption (37% during the same span), along with the lack of denitration process for removing flue/exhaust gas NO x are responsible for increasing NO 2 trend until 2011. The ratio of SO 2 /NO 2 started decreasing in 2007 and dropped significantly from 2011 to 2013 indicating good performance of FGD and ever increasing NO x contribution from mobile sources. Unlike those observed in developed countries (US, EU and Japan) where a decreasing trend for both SO 2 and NO 2 has been observed since 1990s, the observed upward and downward trend found in Henan is similar to those found in North China Plain and other parts of China. The spatial and temporal trend analyses of SO 2 and NO 2 in four other regions in Henan further indicate a similar trend to those observed in Henan Province, albeit with different increasing and decreasing rate. The results provide regulatory agency to develop action plans to combat air pollution problem in general and SO 2 and NO 2 problems in particular in Henan. The implications of our findings and recommendations for decision makers are discussed in the paper. [ABSTRACT FROM AUTHOR]

Background: Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future.Methods: We conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO2); ozone (O3); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM2.5), and less than 10 micrometers (PM10); and sulphur dioxide (SO2). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP).Results: NO2 exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO2 in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO2 emissions and concentrations.Conclusions: NO2 concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time. [ABSTRACT FROM AUTHOR]

Real world emissions of oxides of nitrogen (NO x ) often greatly exceed those achieved in the laboratory based type approval process. In this paper the real world emissions from a substantial sample of the latest Euro 6 diesel passenger cars are presented with a focus on NO x and primary NO 2 . Portable Emissions Measurement System (PEMS) data is analysed from 39 Euro 6 diesel passenger cars over a test route comprised of urban and motorway sections. The sample includes vehicles installed with exhaust gas recirculation (EGR), lean NO x traps (LNT), or selective catalytic reduction (SCR). The results show wide variability in NO x emissions from 1 to 22 times the type approval limit. The average NO x emission, 0.36 (sd. 0.36) g km −1 , is 4.5 times the Euro 6 limit. The average fraction primary NO 2 (fNO 2 ) is 44 (sd. 20) %. Higher emissions during the urban section of the route are attributed to an increased number of acceleration events. Comparisons between PEMS measurements and COPERT speed dependent emissions factors show PEMS measurements to be on average 1.6 times higher than COPERT estimates for NO x and 2.5 times for NO 2 . However, by removing the 5 most polluting vehicles average emissions were reduced considerably. [ABSTRACT FROM AUTHOR]

In this paper, we present the measurements of atmospheric gas concentrations of NO 2 , SO 2 , NH 3 , HNO 3 , and O 3 performed at two traffic sites in the context of the POLCA (Pollution of African Capitals) program. These gases were measured using a passive sampling technique from Jan. 2008 to Dec. 2009 at Dakar and from Jun. 2008 to Dec. 2009 at Bamako. In addition, during these periods there were two intensive measurement campaigns (from 19 Jan. to 2 Feb. 2009 at Bamako and from 30 Nov. to 13 Dec. 2009 at Dakar) where real-time active analysers were used to measure NO 2 and SO 2 . Results show that Dakar has a pollution level for NO 2 and SO 2 higher than that of Bamako, whereas it is lower for NH 3 concentrations. Monthly values of NO 2 range between 21.1 and 43.5 ppb in Dakar with an annual mean concentration of 31.7 ppb (59.6 μg/m3). NO 2 values in Bamako are 9.4–22.6 ppb with a mean of 16.2 ppb. At Dakar, the mean annual NO 2 limit value (21.3 ppb or 40 μg/m3) recommended by the World Health Organization (WHO) is widely exceeded. The mean annual concentration of SO 2 is 15.9 ppb in Dakar and 3.6 ppb in Bamako. These differences may be explained by different sources of traffic between Bamako (with mainly gasoline vehicles) and Dakar (with mainly diesel vehicles). The annual mean NH 3 concentration is about two times higher in Bamako (46.7 ppb) than in Dakar (21.1 ppb). In addition to other possible sources, we assume that the ammonia from domestic fires and uncontrolled garbage incineration may have more influence at Bamako than at Dakar. The mean annual concentrations of HNO 3 and O 3 are 1.3 ppb and 7.7 ppb in Dakar and 0.6 ppb and 5.1 ppb in Bamako, respectively. Seasonal variation in measured gas concentrations are low in Bamako and more pronounced in Dakar, except for HNO 3 and NH 3 . At Dakar, NO 2 and SO 2 daily mean concentrations are higher during the weekdays than on weekends, when urban activities are reduced, whereas at Bamako, no significant difference was observed between weekdays and weekends. At Dakar, the daily average concentrations of SO 2 in the dry season (11.6–39.6 ppb) widely exceed the WHO air quality guideline (7.6 ppb or 20 μg/m3 as 24-h average). Finally, the spatial distribution of gases at different sites in these two capitals have been investigated and showed higher pollution levels at the traffic sites, especially for NO 2 , NH 3 and SO 2 , and lower levels in the suburban area, with the exception of ozone. [ABSTRACT FROM AUTHOR]

An additive modeling approach is employed to provide a statistical description of hourly variation in concentrations of NO x measured in proximity of the Venice “Marco Polo” International Airport, Italy. Differently from several previous studies on airport emissions based on daily time series, the paper analyzes hourly data because variations of NO x concentrations during the day are informative about the prevailing emission source. The statistical analysis is carried out using a one-year time series. Confounder effects due to seasonality, meteorology and airport traffic volume are accounted for by suitable covariates. Four different model specifications of increasing complexity are considered. The model with the aircraft source expressed as the NOx emitted near the airport is found to have the best predictive quality. Although the aircraft source is statistically significant, the comparison of model-based predictions suggests that the relative impact of aircraft emissions to ambient NOx concentrations is limited and the road traffic is the likely dominant source near the sampling point. [ABSTRACT FROM AUTHOR]

It has been well documented that air pollution adversely affects health, and epidemiological pollution-health studies utilise pollution data from automatic monitors. However, these automatic monitors are small in number and hence spatially sparse, which does not allow an accurate representation of the spatial variation in pollution concentrations required for these epidemiological health studies. Nitrogen dioxide (NO 2 ) diffusion tubes are also used to measure concentrations, and due to their lower cost compared to automatic monitors are much more prevalent. However, even combining both data sets still does not provide sufficient spatial coverage of NO 2 for epidemiological studies, and modelled concentrations on a regular grid from atmospheric dispersion models are also available. This paper proposes the first modelling approach to using all three sources of NO 2 data to make fine scale spatial predictions for use in epidemiological health studies. We propose a geostatistical fusion model that regresses combined NO 2 concentrations from both automatic monitors and diffusion tubes against modelled NO 2 concentrations from an atmospheric dispersion model in order to predict fine scale NO 2 concentrations across our West Central Scotland study region. Our model exhibits a 47% improvement in fine scale spatial prediction of NO 2 compared to using the automatic monitors alone, and we use it to predict NO 2 concentrations across West Central Scotland in 2006. [ABSTRACT FROM AUTHOR]

Land use regression (LUR) models are widely used in epidemiological studies to assess exposure to air pollution. However, most of the existing LUR studies focus on estimating annual or monthly average concentration of air pollutants, with high spatial but low temporal resolution. In this paper, we combined LUR models with meteorological conditions to estimate daily nitrogen dioxide (NO 2 ) and particulate matter (PM 10 ) concentrations in the urban area of Changsha, China. Seventy-four sites for NO 2 and thirty-six sites for PM 10 were selected to build LUR models. The LUR models explained 51% and 62% of spatial variability for NO 2 and PM 10 . The most important spatial explanatory variables included major roads, residential land and public facilities land, indicating that the spatial distributions of NO 2 and PM 10 are closely related to traffic conditions and human activities. Meteorological factors were introduced to model the temporal variability of NO 2 and PM 10 by using meteorological factors regression (MFR) and back propagation neural network (BPNN) modeling techniques. Important temporal explanatory variables included temperature, wind speed, cloud cover and percentage of haze. Pearson's r values between predicted and measured concentrations were much higher in BPNN models than in MFR models. The results demonstrate that the BPNN models showed a better performance than the MFR models in modeling temporal variation of NO 2 and PM 10. The approach of modeling spatial and temporal variation of air pollutants using LUR models coupled with meteorological conditions has potential usefulness for exposure assessment, especially for medium or short term exposure, in health studies. [ABSTRACT FROM AUTHOR]

Indoor air quality (IAQ) is very important for children health and well-being, since children are particularly vulnerable and sensitive to the presence of air pollutants. This study was performed in two naturally ventilated schools located in the same municipality. The first school is located in an urban area, at a residential-industrial site, while the other school is situated in a rural area. School buildings were chosen based on their urban environment features. The measurements were carried out in heating and non-heating periods in duration of five consecutive working days. The objective of the study was to analyze IAQ in the classrooms with special emphasis on levels and diurnal variations of particulate matter (PM10 and PM2.5), carbon dioxide (CO2) and nitrogen dioxide (NO2) in occupied and unoccupied school classrooms. In this paper, the CO2 concentrations were measured at both indoor and outdoor environments. Concentrations of CO2 higher than 1000 ppm were regularly detected in the classrooms during teaching hours. Indoor concentrations of PM10 were not exceeded the guideline, daily average, value of 50 μg/m³. Concentrations of PM2.5exceeded the guideline daily average value of 25 μg/m³ in both school during heating period. Concentrations of NO2 did not exceed the guideline value of 200 μg/m³. Ventilation rates were calculated and compared with the prescribed limits. In both occupied and unoccupied periods high correlation between CO2 and PM concentrations was determined. [ABSTRACT FROM AUTHOR]

Abstract: This paper introduces the Semi-Empirical Urban Street (SEUS) model. SEUS is a simple mathematical model based on the scaling of air pollution concentration inside street canyons employing the emission rate, the width of the canyon, the dispersive velocity scale and the background concentration. Dispersive velocity scale depends on turbulent motions related to wind and traffic. The parameterisations of these turbulent motions include two dimensionless empirical parameters. Functional forms of these parameters have been obtained from full scale data measured in street canyons at four European cities. The sensitivity of SEUS model is studied analytically. Results show that relative errors in the evaluation of the two dimensionless empirical parameters have less influence on model uncertainties than uncertainties in other input variables. The model estimates NO2 concentrations using a simple photochemistry scheme. SEUS is applied to estimate NO x and NO2 hourly concentrations in an irregular and busy street canyon in the city of Buenos Aires. The statistical evaluation of results shows that there is a good agreement between estimated and observed hourly concentrations (e.g. fractional bias are −10.3% for NO x and +7.8% for NO2). The agreement between the estimated and observed values has also been analysed in terms of its dependence on wind speed and direction. The model shows a better performance for wind speeds >2 m s−1 than for lower wind speeds and for leeward situations than for others. No significant discrepancies have been found between the results of the proposed model and that of a widely used operational dispersion model (OSPM), both using the same input information. [Copyright &y& Elsevier]

Abstract: This paper presents a comprehensive evaluation of AMS-MINNI modelling system for the year 2005, over Italian peninsula and major islands Sicily and Sardinia, for gas-phase species ozone (O3) and nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM10), against surface measurements from the Italian air quality database. Statistical indicators currently used in air quality models performance assessment and recommended by European Union (EU) guidelines were calculated at rural, urban and suburban background air quality monitoring stations, on purpose of understanding the model behaviour in areas not directly affected by anthropogenic pollution sources. Results show that measured O3 concentrations are generally well reproduced by the model, with the best agreement between model and observations at rural stations. Simulated PM10 annual average concentrations are generally lower than those observed but simulated and observed variabilities are comparable at urban and suburban stations. As for NO2, the model underestimates concentrations at all stations but gives similar variability to the observed one. Overall, the values of the statistical indicators comply with the acceptance criteria requested by EU legislation and are similar with those published by previous studies for the three pollutants investigated in this study. Further work will be carried out to evaluate the impact of uncertainties in input data (meteorology, emissions and boundary conditions) and in description of gaseous and aerosol chemical and physical processes on the simulated concentrations. [Copyright &y& Elsevier]

Abstract: This paper investigates the variations in levels of nitrogen dioxide, NO2, monitored over the decade 2001–2010, in Newcastle-upon-Tyne (UK) city centre, to develop fundamental understanding of the periods of persistence of levels of NO2 greater than 40 μg m−3 (∼21 ppb) defined as air pollution event duration. The appropriateness of the hazard theory as a mechanism to understand failure rate of the duration of poor air pollution events was explored. The results revealed two types of air quality events. The longer duration air quality events (between 24 and 68 h) were associated with the “extreme-weather” conditions and were responsible for a small number of extremely long air pollution duration events. These created bias in the results and therefore the analysis was restricted specifically to the ‘normal-weather’ related air pollution event durations, conforming to a geometric distribution. This novel approach shows promise as a mechanism to monitor and investigate year on year trends observed in air quality data. [Copyright &y& Elsevier]

Abstract: Land use regression (LUR) models are widely employed in health studies to characterize chronic exposure to air pollution. The LUR is essentially an interpolation technique that employs the pollutant of interest as the dependent variable with proximate land use, traffic, and physical environmental variables used as independent predictors. Two major limitations with this method have not been addressed: (1) variable selection in the model building process, and (2) dealing with unbalanced repeated measures. In this paper, we address these issues with a modeling framework that implements the deletion/substitution/addition (DSA) machine learning algorithm that uses a generalized linear model to average over unbalanced temporal observations. Models were derived for fine particulate matter with aerodynamic diameter of 2.5 microns or less (PM2.5) and nitrogen dioxide (NO2) using monthly observations. We used 4119 observations at 108 sites and 15,301 observations at 138 sites for PM2.5 and NO2, respectively. We derived models with good predictive capacity (cross-validated-R 2 values were 0.65 and 0.71 for PM2.5 and NO2, respectively). By addressing these two shortcomings in current approaches to LUR modeling, we have developed a framework that minimizes arbitrary decisions during the model selection process. We have also demonstrated how to integrate temporally unbalanced data in a theoretically sound manner. These developments could have widespread applicability for future LUR modeling efforts. [Copyright &y& Elsevier]

Abstract: There is a high interest in quantifying temporal trends of air pollutant concentrations as they serve to assess the effects of emission control strategies. In this paper temporal trends (1997–2012) in air pollutant concentrations in the City of Makkah, near the Holy Mosque, have been assessed with the help of Theil–Sen approach and changepoint analysis, which are applicable to both normal and non-normal distributed data and are therefore preferred over classic parametric statistics. Trend analysis of nitrogen oxides (NO x ), nitric oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2), particulate matter with aerodynamic diameter of 10 micron or less (PM10) and ozone (O3) was performed, not only at mean concentrations but also at several selected quantiles (minimum, first quartile, median, third quartile and maximum). Trends were positive in SO2, NO2, PM10 and ozone and negative in CO and NO concentrations. NO x (negative) and NO2 (positive) trends were predominantly non-significant, however other pollutants showed mostly significant trends. Trends vary at various metrics suggesting different behaviour of air pollutants at various quantiles of the distributions. Changepoint analysis was performed, which provides further insight into the temporal trends and highlights the points when the trends have changed significantly. Potential factors responsible for the observed temporal trends are discussed. Further work on source apportionment of various emission sources and spatial variability of air pollutants is required to provide further insight into the causes behind the trends of air pollutants and help better manage air pollutant levels in Makkah and elsewhere in the country. [Copyright &y& Elsevier]

Abstract: The possible influence on the Castel Porziano Presidential Estate pine forest (Italy) of pollutant-rich air masses from the neighboring metropolitan area of Rome is analyzed. This study aims to highlight the consequences which this natural reserve located along the coast may suffer due to the vicinity of the metropolitan area. Two case studies, one representative of synoptic and the other of breeze patterns, are presented and analyzed to evaluate how the local wind circulation can influence these processes of mutual interaction between the wooded and the urban area nearby. This is a common situation in many other places around the world. To this end an up-to-date version of a method for gas profile retrieval in the lower troposphere, developed by the authors, is exploited to study the time evolution of the vertical structure of O3 and NO2 concentrations on the Estate. The method consists of applying an inversion technique, based on the weighted Chahine algorithm, to DOAS (Differential Optical Absorption Spectroscopy) remote-sensing measurements. The analysis of the retrieved vertical profiles shows that the degradation process associated with the arrival of air masses rich in photo-chemical pollutants, due to breeze circulation modified by the Coriolis Effect, is more apparent at upper levels than near the surface, affecting to a greater degree the higher branches of the trees. The paper also examines the impact of O3 on the wooded part of the Castel Porziano Estate. The incidence of this effect is evaluated with the analysis of the so-called AOT40 parameter. [Copyright &y& Elsevier]

Abstract: High resolution model estimates (10×10km2) of tropospheric NO2 column amounts from the Comprehensive Air Quality Model (CAMx) for the Balkan Peninsula are compared with OMI/Aura measurements (13×24km2 at nadir) for the year April 2009 to March 2010. The Balkan area contributes significantly to the NO2 burden in European air and so numerous urban, industrial and rural regions are studied aiming to investigate the consistency of both satellite retrievals and model predictions at high spatial resolution. It has already been shown that OMI can detect the tropospheric column of NO2 over polluted Balkan cities due to its fine horizontal resolution and instrument sensitivity (Zyrichidou et al., 2009). In this study the improved OMI DOMINO v2.0 satellite retrievals showed that over South-Eastern Europe the monthly mean NO2 tropospheric column density fluctuated between 2.0 and 5.7±1.1×1015 molecules/cm2 over urban areas, 1.6–5.0±0.7×1015 molecules/cm2 over large industrial complexes and 1.1–2.2±0.4×1015 molecules/cm2 over rural areas for the year studied. The Comprehensive Air Quality Model with extensions (CAMx) version 4.40 is a publicly available open-source computer modeling system for the integrated assessment of gaseous and particulate air pollution. The anthropogenic emissions used in CAMx for the Greek domain being studied were compiled employing bottom-up approaches (road transport sector, off-road machinery, etc.) as well as other national registries and international databases. The rest of the Balkan domain has natural and anthropogenic emissions based on the TNO emission inventory of 2003. The high-resolution CAMx simulations reveal consistent spatial and temporal patterns with the OMI/Aura data. The annual spatial correlation coefficient between OMI and CAMx computed in this high spatial resolution analysis is of the order of 0.6, somewhat improved over those estimated in Zyrichidou et al. (2009) (R ≈0.5). However, in such a validation study it is important to take into account the averaging kernel (AK) information in order to achieve the creation of comparable data sets. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of limiting the effect of the a priori profile on the comparison is on average small. The main aim of the paper, which was to evaluate OMI retrieved and high resolution simulated tropospheric NO2 column densities over South-Eastern Europe and to assess the use of the averaging kernels, is achieved and the two data sources are being employed further in an inverse emission inventory creation study (Zyrichidou et al., in preparation). [Copyright &y& Elsevier]

Abstract: In this paper we have compared detailed road traffic NOx emissions with the equivalent trends in ambient roadside NOx measurements. This was undertaken separately in Great Britain and London, for all of the major roads, and by road type and location. The emissions trends were created using different emissions factors, those used in UK emissions inventories (Base case), the Swiss-German handbook (HBEFA), and those created from recent remote sensing measurements in the UK (RSD). An alternative assumption for use of Selective Catalytic Reduction (SCR) in the articulated Heavy Goods Vehicle (HGV) fleet was also tested. For all scenarios traffic flows, speeds and vehicle age were kept constant. Comparison between the emissions scenarios in Great Britain showed that by 2009, NOx emissions estimates from road traffic could be as much as 25% greater than current UK estimates and 31% greater in London. The RSD emissions inventory gave the smallest downward trend in NOx emissions, from 2004 to 2009, of between 3 and 4%/year and this compared with a reduction of ∼6%/year from the Base Case and HBEFA scenarios. All scenarios compared poorly with roadside NOx measurement trends from UK sites, which typically reduce by between 1% and 2%/year. We have shown that the differences in NOx emissions trends were driven, partially at least, by the relative contribution from light duty diesel vehicles. An analysis from 2700 NOx measurement sites throughout Europe has shown that this problem is unlikely to be limited to the UK, and identifies a difficulty in meeting EU limit values for NO2, obligations under the National Emission Ceilings Directive () and the Gothenburg Protocol () and for forecasting future changes in PM2.5. [Copyright &y& Elsevier]

This paper represents, for the first time, scientific data as a part of monitoring air quality in the city of Split. The city has a problem with the air pollution mostly caused by anthropogenic activities and partly by natural origin activities. This study presents results of monthly and seasonal variations of NO2, SO2 and black-smoke as well as the influence of meteorological parameters on observed concentration levels. Average seasonal values for SO2 ranged from 22.54 to 54.81 gg m-3, for NO2 from 48.24 to 56.38 gg m-3 and for black-smoke from 4.15 to 5.64/µg m-3. The results obtained for SO2 and black-smoke were below, while for NO2 were above the limit value of pollutants in the air recommended by Croatian Government (Air Protection Act (OG 178/04); Regulation on limit values of pollutants in air (OG 133/05)). As the result of stable meteorological conditions (high temperatures and drought), the increase in SO2 concentration was significant in summer period, while the concentrations of NO2 and black-smoke were not significantly changed during year and did not depend on other parameters. [ABSTRACT FROM AUTHOR]

The article presents a study which investigates the weekly cycle in the atmospheric layer in Moscow, Russia. Spectral analysis of the nitrogen dioxide content and meteorological and atmospheric parameters over the working days and weekends was performed at points near Moscow. Calculations on long term monthly mean data of each parameter and their root-mean-square deviations was conducted as well as comparison of the results of the spectral analysis based on the maximum entropy method and based on the autoregressive method. The study founds the existence of cyclicity of the weekly scale in the atmosphere both in stratospheric heights and surface layer and the influence of human activity in the dynamics and thermodynamics of the atmosphere.