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This paper presents a new algorithm using physics-informed neural networks (PINNs) to track and characterize spatio-temporally varying chemical sources based on time-resolved measurements of chemical concentration, fluid velocity, and pressure. Chemical source emission functions, chemical concentration, fluid velocity and fluid pressure fields are modeled as multi-layer perceptrons (MLPs). During the training process, sensors readings of chemical concentration, fluid velocity, and fluid pressure are matched to the output of the respective MLPs at the given spatio-temporal locations. Simultaneously, the physics of fluid flow and chemical dispersion at an arbitrary number of spatio-temporal locations in the domain of interest are enforced through regularization. Once trained, the constituent MLPs can be evaluated to generate the time resolved maps of source emissions, chemical concentration, fluid velocity and pressure. Extensive numerical simulation validate the method, including scenarios with both static and dynamic sources in complex flow fields. This innovative approach marks a significant advancement in environmental monitoring technologies. • Novel physics-informed neural net (PINN) formulation for chemical source localization. • No simplifying assumptions on physics, terrain, nor parameterization of source required. • Method tested in complex 2D scenarios incorporating mobile sources with transient emissivity. [ABSTRACT FROM AUTHOR]

Nitrous oxide is one of the atmospheric greenhouse gases whose amount is significantly influenced by human activity. Its major anthropogenic sources are the agricultural soils but the emission is known only with large uncertainty yet. The paper presents a tall tower based measuring system installed in Hungary, which is designed for the long-term monitoring of nitrous oxide emission of a regionally typical composition of agricultural fields by means of eddy covariance technique. Due to the careful calibration of the gas analyzer applied the measuring system is also suitable for the recording of the atmospheric concentration of nitrous oxide on the globally compatible scale (WMO X2006A). The paper reports the results of the first two years of the monitoring program, which is the first of its kind in Central Europe. For the period of July 2015–June 2017 the concentration measurements indicate an increasing trend of 0.91 nmol mol −1 year −1 with an average concentration of 330.64 nmol mol −1 . During the two years of the project, the monitoring system recorded a total of 441 ± 195 mg N 2 O-N m −2 nitrous oxide emission with late spring/early summer maximum. The measurements also revealed the episodic nature of the emission typically triggered by major precipitation events. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the calculation of personal air pollution exposure during trips made by active transportation using activity patterns without personal monitors. We calculate exposure as the inhaled dose of particulate matter 2.5 μg or smaller. Two modes of active transportation are compared, and they include cycling and walking. Ambient conditions are calculated by combining mobile and stationary monitoring data in an artificial neural network space-time model. The model uses a land use regression framework and has a prediction accuracy of R 2 = 0.78. Exposure is calculated at 10 m or shorter intervals during the trips using inhalation rates associated with both modes. The trips are children’s routes between home and school. The average dose during morning cycling trips was 2.17 μg, during morning walking trips was 3.19 μg, during afternoon cycling trips was 2.19 μg and during afternoon walking trips was 3.23 μg. The cycling trip dose was significantly lower than the walking trip dose. The air pollution exposure during walking or cycling trips could not be strongly predicted by either the school or household ambient conditions, either individually or in combination. Multiple linear regression models regressing both the household and school ambient conditions against the dose were only able to account for, at most, six percent of the variance in the exposure. This paper demonstrates that incorporating activity patterns when calculating exposure can improve the estimate of exposure compared to its calculation from ambient conditions. [ABSTRACT FROM AUTHOR]

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]

Abstract: This paper aims to advance regional worldwide source–receptor relationships, providing fate factors for acidifying and eutrophying air emissions (NO x , HNO3, SO2, SO4 and NH3) to be used within life cycle impact assessment. A simulation for the reference year 2005 of the three-dimensional global scale tropospheric GEOS-Chem model was used as the basis of a novel methodological approach to derive source–receptor matrices (SRMs) whose elements are fate factors at a global 2° × 2.5° grid. This new approach makes it possible to assess the impact of transboundary emissions while maintaining regional scale emission differentiation. These 2° × 2.5° grid resolution fate factors were later aggregated at continental and country resolutions using emission weighting. Continental fate factor results showed that 50–70% of nitrogen oxides (NO x , HNO3) and sulfur oxides (SO2, SO4) and approximately 80% of ammonia (NH3) emissions will deposit on the same continent. Results showed that the developed fate factor derivation approach was within a ±10% agreement with GEOS-Chem simulations in which fate factors were determined by withdrawing the regional emission inventory over Canada and in ±50% agreement with current state-of-the-art LCIA fate factors (calculated with the European Monitoring and Evaluation Programme (EMEP) model). The SRMs outlined in this paper facilitate further modeling developments without having to run the underlying tropospheric model, thus opening the door to the assessment of the regional life cycle inventories of a global economy. [Copyright &y& Elsevier]

Abstract: Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model. [Copyright &y& Elsevier]

Abstract: A numerically efficient methodology for the optimal design of monitoring networks aiming at the surveillance of accidental atmospheric release is proposed in this paper. In a realistic context, the design of such a network requires the knowledge of a database of potential dispersion accidents occurring in the domain of the study. An objective function measures the ability of a potential network to provide measurements in order to reconstruct any accidental plume taken from the database. In the optimisation of such cost functions with respect to networks, most of the computational time is spent in the evaluation of the function, especially if the accidents database is large. In this paper we show how to optimally reduce this database and how this affects the design via a mathematical expansion in the cost function. We introduce methods based on principal component analysis, which are rigorous when the cost function is of least-squares type. These methods are then tested and validated with success on the design of a radionuclides monitoring network to be deployed over France. This is the so-called Descartes network which will be operated by the French Institute for Radiation and Nuclear Safety. These techniques are then applied on Descartes to solve several issues that are computationally demanding, but are also of more general interest, such as: how should one sequentially deploy the stations of the network? How is affected the optimal network when other European potential radiological sources are taken into account? [Copyright &y& Elsevier]

This paper proposes and validates a methodology for the quantification of the daily African PM load during dust outbreaks in southern Europe. The daily net dust load in PM10 attributable to an African episode in a given region can be obtained by subtracting the daily regional background (RB) level from the PM10 concentration value at an RB station. As demonstrated in this paper, the daily RB level can be obtained by applying a monthly moving 30th percentile to the PM10 time series at an RB station after a prior extraction of the data of the days with African dust transport. The daily PM10 RB levels obtained can be subtracted from the daily PM10 levels recorded at the same RB site only on days when the occurrence of African dust outbreaks was demonstrated, the difference being the daily net African dust load. It is thus possible to quantify the African dust contribution during an African PM event in southern Europe without the need for PM speciation. The validation of this methodology was performed by comparing the estimated net dust load during African dust outbreaks at three RB stations and the crustal load determined by chemical speciation of PM10 filters. The correlation (r 2>0.6) and the equivalence (correlation lines’ slopes ∼1) were significant in the three cases. [Copyright &y& Elsevier]

During a transition period from 2007 to 2009, the Chemical Speciation Network (CSN) altered its carbon sampling instrumentation and analysis methods to be more consistent with the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. CSN and IMPROVE operated collocated samplers spanning the transition at eight sites. This paper compares elemental, organic, and total carbon (EC, OC, and TC, respectively) measurements at these collocated sites from 2005 through March 2016. Prior to the changes, the concentration measurements between the two networks had imprecisions of 17, 17, and 16% and biases of 0.22, −1.93, and −1.69 μg m −3 for EC, OC, and TC, respectively, with CSN measuring higher OC and TC than IMPROVE. After the sampling equipment and analytical methods were changed, the imprecision improved to 14, 12, and 10% and biases decreased to −0.02, −0.12, and −0.15 μg m −3 for EC, OC, and TC, respectively. The increased comparability, particularly the smaller biases, between the two networks facilitates comparisons between urban and rural aerosols in geospatial analyses. [ABSTRACT FROM AUTHOR]

This paper describes and discusses fifteen years (1999–2013) of continuous hourly atmospheric radon ( 222 Rn) monitoring at the coastal low-altitude Southern Hemisphere Cape Point Station in South Africa. A strong seasonal cycle is evident in the observed radon concentrations, with maxima during the winter months, when air masses arriving at the Cape Point station from over the African continental surface are more frequently observed, and minima during the summer months, when an oceanic fetch is predominant. An atmospheric mean radon activity concentration of 676 ± 2 mBq/m 3 is found over the 15-year record, having a strongly skewed distribution that exhibits a large number of events falling into a compact range of low values (corresponding to oceanic air masses), and a smaller number of events with high radon values spread over a wide range (corresponding to continental air masses). The mean radon concentration from continental air masses (1 004 ± 6 mBq/m 3 ) is about two times higher compared to oceanic air masses (479 ± 3 mBq/m 3 ). The number of atmospheric radon events observed is strongly dependent on the wind direction. A power spectral Fast Fourier Transform analysis of the 15-year radon time series reveals prominent peaks at semi-diurnal, diurnal and annual timescales. Two inter-annual radon periodicities have been established, the diurnal 0.98 ± 0.04 day −1 and half-diurnal 2.07 ± 0.15 day −1 . The annual peak reflects major seasonal changes in the patterns of offshore versus onshore flow associated with regional/hemispheric circulation patterns, whereas the diurnal and semi-diurnal peaks together reflect the influence of local nocturnal radon build-up over land, and the interplay between mesoscale sea/land breezes. The winter-time diurnal radon concentration had a significant decrease of about 200 mBq/m 3 (17%) while the summer-time diurnal radon concentration revealed nearly no changes. A slow decline in the higher radon percentiles (75th and 95th) for the winter and spring seasons is found over the 15-year data set, with most of the change occurring in the first 9 years (1999–2007). This observed inter-annual decline appears to be associated with changes in the frequency of air masses having originated from over the African continental surfaces, and no significant trend is found in the lower radon percentiles associated with oceanic air masses. The general decrease of atmospheric radon-associated with continental air-masses at Cape Point could be attributed to changing meteorological conditions, possibly driven by climate change. [ABSTRACT FROM AUTHOR]

A large emission of air pollutants from the Asian continent has caused transboundary air pollution, especially in northeastern Asia. This paper evaluates sulfate deposition at a leeward area of Asian continent, i.e., the Nagaoka observation station located along the Sea of Japan. We have monitored atmospheric sulfate deposition and its sulfur isotopic ratio for 28 years at the station. The sulfur isotopic ratios of non-sea-salt sulfate (δ 34 Snss) ranged from 0.0 to +6.2‰. The isotopic ratios of local emission and Chinese coal sulfur showed negative and positive values, respectively. Several statistically significant trends were detected on the deposition of non-sea-salt sulfate (nss-SO 4 2− ) during the study period. The decrease of nss-SO 4 2− deposition since the middle of 1980s was considered to have been caused by local anthropogenic SO 2 emission that showed relatively low δ 34 Snss values during the period. The increase of nss-SO 4 2− deposition from the end of 1990s to the second half of 2000s was interpreted to have been caused by the change in SO 2 emission in China because the δ 34 Snss values increased during the period with the winter values getting closer to the averaged value of Chinese coal sulfur. The decreasing trend of nss-SO 4 2− deposition from the middle of 2000s was likely affected by reduction of Chinese SO 2 emission judging from the decrease in δ 34 Snss values in the period. Mass balance calculations suggested that sulfur released by coal combustion in China during 1990s contributed by about 40% of annual total sulfur deposition in Nagaoka, and its contribution increased up to 60% in the middle of 2000s. The contribution turned to decrease after that peak, which was in harmony with the temporal change of emission from China. [ABSTRACT FROM AUTHOR]

BioSampler is now being widely used for bioaerosol sampling. However, the sampling efficiency in wide size range especially for nanoparticles as well as the size-dependent retention efficiency have not been well evaluated until now. Through literature review, theoretic analysis and experiments, this paper reviews the sampling process, collection mechanism and sampling performance of commercial BioSampler including pressure drop as a function of sampling flow rate, the mass loss rate and temperature of the collection fluid as a function of sampling time, the variation of retention efficiency with time, and the sampling efficiency in wide size range from nanometers to microns. The effects of low pressure and high relative humidity on determination of sampling efficiency in literature were carefully analyzed. To compensate the collection fluid loss and extract the insoluble/dissolved sample for further analysis, Continuous-Extraction BioSampler (CEBS) is proposed. The retention efficiency for particles of different sizes as well as the collection efficiency were determined and found to be identical with commercial BioSampler when no steam was introduced into CEBS. Finally, the combination uses of CEBS and Inductively-Coupled-Plasma Mass Spectrometer (ICP-MS) was developed. Exponentially Modified Gaussian (EMG) Model was derived and verified to describe the temporal concentration of the dissolved component originating from individual soluble droplet. Using internal standard calibration method and EMG fitting of signal curve, the target element amount in individual droplet could be determined accurately. For continuously-collected soluble droplet with duration of minutes, the observed signal curve can be described by EMG model and the fitted value of area varies linearly with the sample amount introduced. This paper not only provides comprehensive performance evaluation of commercial BioSampler, but also demonstrates that the proposed CEBS-ICPMS is capable of monitoring environmental coarse aerosol with time resolution of ~17 min. • The comprehensive performances of commercial BioSampler are carefully evaluated, including the pressure drop, mass loss rate and temperature of the collection liquid (for the first time), retention efficiency and physical sampling efficiency, through literature review, theoretic analysis and experiments. • The retention efficiency of BioSampler decreases linearly with sampling time and drops to ~85% in submicron size range. The literature values of physical sampling efficiency are in good aggrement for particles between ~0.4 and 10 μm. High relative humidity is beneficial for improving the collection of nanoparticles. • Continuous-Extraction BioSampler (CEBS) is proposed for long time sampling with high efficiency and combination use with sensitive detectors. The proposed CEBS-ICPMS is capable of monitoring environmental coarse aerosol with time resolution of ~17 min. [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]

Understanding the characteristics of the size distribution of ambient black carbon (BC) in distinct environments is critical because the influence of BC aerosols on climate, visibility, and human health depends strongly on the distribution of BC aerosols over the particle size spectrum. In this study, a novel method for determining the mass size distribution of BC in atmospheric aerosols was developed. This size-segregation method relies on measuring BC in parallel using two aethalometers, one of which is used to measure the total BC (BC T ) mass concentration as a reference level and the other is used to measure the BC (BC i ) mass concentration for BC sizes below specific particle sizes that are selected using a size cut-off inlet. In this study, this method was applied to measure BC in atmospheric samples at an urban traffic site. The aethalometers were operated continually from December 15, 2012 to January 31, 2013, and from February 15, 2013 to March 31, 2013. The measurement results presented in this paper are for the diurnal variation patterns, average concentrations, mass fractions, and size distributions of BC aerosols. The results indicate that BC T mass concentration is approximately 2.8 μg m−3 in the Taipei urban area. The levels of BC at this sampling site were affected markedly by traffic emission levels and local wind speed. At the sampling site, the average BC2.5/BC T , BC1.0/BC T , BC0.5/BC T , BC0.25/BC T , and BC0.1/BC T were 0.96 ± 0.04, 0.92 ± 0.07, 0.89 ± 0.04, 0.73 ± 0.10, and 0.18 ± 0.08, respectively. The results indicate that approximately 90% of the BC aerosols were smaller than 0.5 μm, that most of the BC aerosols (55%) were in the size range of 0.1–0.25 μm, and that approximately 18% of the BC aerosols were ultrafine. Moreover, the daily average mass size distribution of BC exhibited a single accumulation mode at 0.16 μm at this sampling site. The mode of the BC mass size distribution at rush hour (9 AM) was only 0.14 μm, which is smaller than the daily average. Moreover, the mode of the BC mass size distribution at an early morning hour (3 AM) was 0.18 μm, and a minor coarse mode was also observed during this period. The results further revealed that the geometric diameter (D pg) of the BC aerosols varied between 0.14 and 0.22 μm and the geometric standard deviation (σ g ) of these BC aerosols ranged between 1.4 and 2.3 during the sampling period. Because BC exhibits extremely low chemical reactivity; the size distribution of BC in the atmosphere does not change substantially except through coagulation. [ABSTRACT FROM AUTHOR]

Abstract: In the present paper, 1-year PM10 and PM2.5 data from roadside and urban background monitoring stations in Athens (Greece), Madrid (Spain) and London (UK) are analysed in relation to other air pollutants (NO, NO2, NO x , CO, O3 and SO2) and several meteorological parameters (wind velocity, temperature, relative humidity, precipitation, solar radiation and atmospheric pressure), in order to investigate the sources and factors affecting particulate pollution in large European cities. Principal component and regression analyses are therefore used to quantify the contribution of both combustion and non-combustion sources to the PM10 and PM2.5 levels observed. The analysis reveals that the EU legislated PM10 and PM2.5 limit values are frequently breached, forming a potential public health hazard in the areas studied. The seasonal variability patterns of particulates varies among cities and sites, with Athens and Madrid presenting higher PM10 concentrations during the warm period and suggesting the larger relative contribution of secondary and natural particles during hot and dry days. It is estimated that the contribution of non-combustion sources varies substantially among cities, sites and seasons and ranges between 38–67% and 40–62% in London, 26–50% and 20–62% in Athens, and 31–58% and 33–68% in Madrid, for both PM10 and PM2.5. Higher contributions from non-combustion sources are found at urban background sites in all three cities, whereas in the traffic sites the seasonal differences are smaller. In addition, the non-combustion fraction of both particle metrics is higher during the warm season at all sites. On the whole, the analysis provides evidence of the substantial impact of non-combustion sources on local air quality in all three cities. While vehicular exhaust emissions carry a large part of the risk posed on human health by particle exposure, it is most likely that mitigation measures designed for their reduction will have a major effect only at traffic sites and additional measures will be necessary for the control of background levels. However, efforts in mitigation strategies should always focus on optimal health effects. [Copyright &y& Elsevier]

Abstract: Photochemical ozone (O3) formation is related to its precursors and meteorological conditions. A conceptual model of O3 air pollution is developed based on the analysis of data obtained at Tung Chung (TC) in Hong Kong. By comparing meteorological parameters between O3 and non-O3 episode days, it was found that high temperatures, strong solar radiation, low wind speeds and relative humidity, northeasterly and/or northwesterly prevailing winds were favorable for the O3 formation, while tropical cyclones were most conducive to the occurrence of O3 episodes. Backward trajectories simulation and graphical illustration of O3 pollution suggested that super-regional (i.e. central and eastern China) and regional (i.e. Pearl River Delta, southern China) transport was another factor that contributed to high O3 levels in Hong Kong. The photochemical O3 formation, generally VOC-limited in Hong Kong, was controlled by a small number of volatile organic compounds (VOCs). Furthermore, the positive matrix factorization (PMF) simulation suggested that solvent usage and vehicular emissions are the major contributors to ambient VOCs in Hong Kong. Finally, this paper presents recommendations for further O3 research and implementation of O3 control strategies. [Copyright &y& Elsevier]

Abstract: Road traffic is both a major source of ozone precursors (e.g. nitrogen oxides and hydrocarbons) and a potential local sink for ozone in the form of fresh nitric oxide (NO) that depletes ozone. This study investigates the effect of road traffic characteristics on ground level ozone concentration (ppb) applying a quantile regression model (QRM). QRM has certain advantages over other regression methods, including its applicability to non-normal ozone distribution and its ability to handle non-linearities in the relationship of ozone with its covariates. The paper is developed in two parts. In the first part ozone concentrations at urban and rural sites have been compared using data from 80 ozone monitoring sites throughout the UK. The model results in an average urban decrement of about 7 ppb (26%) but indicates variations at various quantiles of the ozone distribution, for instance the difference is 5.25 ppb (25%) and 10.78 ppb (30%) at quantile 0.1 and 0.99, respectively. In the second part the effect of road-traffic characteristics (traffic flow, speed and fleet composition) on urban decrement has been modelled, as a case study in Leeds, UK. The relationship between urban decrement and road traffic characteristics changes at different regimes of ozone distribution indicating a highly non-linear association. Flow of cars, buses and articulated heavy vehicles seem to have the strongest effect on urban decrement; however buses are the only category showing significant effect at all quantiles. The effect of average speed and motorcycles flow was not significant. The results of QRM show that up to 86% ozone variations between rural and urban sites can be explained with the help of traffic characteristics. The effect of various traffic scenarios on urban decrements has been investigated. [Copyright &y& Elsevier]

Abstract: Health can be impacted in many ways by exposure to chemical stressors in urban areas. Epidemiological research community has established consistent associations between traffic related air pollution and various health outcomes. Nevertheless, many urban environments, due to practical reasons (bulk of equipment) and mainly due to economical constraints, are characterised by the absence of the necessary monitoring infrastructure, for pollutants such as toluene. This chemical stressor is associated with numerous risks to human health, mainly with acute and chronic effects on the central nervous system. Due to the lack of monitoring data, it may be convenient to identify and establish a set of possible empirical relationships between health stressors in order to assess air quality trends of traffic related pollution in an urban area and support decision making. The use of environmental statistics can be meaningful towards this direction. This paper aims at developing and presenting a tractable approach, in order to reliably forecast toluene levels in EU urban environments. Multiple stepwise regression analysis is used for this purpose and a strong statistical relationship is detected mainly between toluene, benzene and CO. The adopted regression models are validated in order to depict their applicability and representativeness. In addition the models are applied to Thessaloniki, Greece, which is considered one of the most polluted cities within Europe. A comparison between available measurements, predictions based on the developed statistical models and air quality modelling output, provides discussion for transferability issues of such statistical relations between cities, but also interesting insights for the specific city. In general the presented results demonstrate that the adopted approach is capable of capturing toluene concentration trends and should be considered as complementary to air quality monitoring. [Copyright &y& Elsevier]

Abstract: This paper focuses on 7Be concentration in the atmospheric surface aerosols of the Spanish city of Granada, in the southern Iberian Peninsula. We analyze the effects of meteorological conditions in the geographical zone over the period 2005–2009. A prediction model is suggested to describe the behaviour of atmospheric aerosols containing 7Be. The model was applied from January to May 2010 and shows that temperature, relative humidity and precipitation are the meteorological factors responsible for the behaviour of atmospheric aerosols. The statistical significance of the results was 99%. This study helps understanding of the atmosphere of Granada as well as the climate variables responsible for transportation and deposition of atmospheric aerosols. Moreover, in case of a massive release of radionuclides into the atmosphere, the results of this study will help predict behaviour in this city and other continental areas with a similar climate. [Copyright &y& Elsevier]

Abstract: The Centre for Environmental Monitoring of the Vietnam Environment Administration in Hanoi launched a 2-year emissions monitoring program which aimed at determining the emission factors and emission inventories for two typical types of vehicle in Hanoi. To achieve these objectives, developing driving cycles representative of the local driving conditions are of essential tasks before any emission testing can be conducted. Therefore, this paper presents the results of the development of two driving cycles for a motorcycle and a light-duty vehicle (LDV) in Hanoi. On-road speed–time data were collected by two test vehicles along 10 routes in the urban areas of Hanoi. The collected data were analysed to characterise the typical driving patterns and characteristics. A unique driving cycle was therefore developed for each of the two types of vehicle for Hanoi (i.e. CEMDC and CECDC). The cycles were developed by a random selection process to match the overall summary statistics. The CEMDC and CECDC cycles are the first set of driving cycles developed for Hanoi which can be applied to the next stage of the program for emission testing to determine the emission factors for Hanoi as well as for government’s emission control testing. [Copyright &y& Elsevier]

Abstract: The final 2008 lead (Pb) national ambient air quality standards (NAAQS) revision maintains Pb in total suspended particulate matter as the indicator. However, the final rule permits the use of low-volume PM10 (particulate matter sampled with a 50% cut-point of 10 μm) Federal Reference Method (FRM) monitors in lieu of total suspended particulate (TSP) monitors for some non-source-oriented monitoring. PM10 FRM monitors are known to provide more reliable concentration measurements than TSP samplers because they are omni-directional samplers and so are not biased by wind conditions. However, by design they exclude the upper tail of the particle size distribution. Hence, each monitor produces uncertainties about measured concentrations of Pb-bearing PM. Uncertainties in reported Pb data are also related to spatiotemporal variation of the concentration and size distribution of Pb-bearing PM. Therefore, a comprehensive literature review was performed to summarize the current knowledge regarding the concentration and size distribution of Pb particles in the atmosphere. The objectives of this review were to compile data that could shed light on these uncertainties, to provide insights useful during future Pb NAAQS reviews, and to identify areas where more research is needed. Results of this review indicated that Pb size distribution data are relatively limited and often outdated. Thirty-nine articles were found to have sufficiently detailed information regarding airborne Pb concentrations, study location, sample collection methods, and analytical techniques; only 16 of those papers reported Pb concentration data for multiple size fractions. For the most part, U.S. and European studies from the last forty years illustrate that the largest mode of the size distribution of airborne particle-bound Pb has shifted to larger sizes while airborne Pb concentrations have decreased in urban areas. This shift occurred as tetraethyl Pb additives in gasoline were phased out and industrial emissions and resuspended road dust became more important sources of Pb. Several studies also suggested the occurrence of long-range transport of Pb-bearing PM from industrial emissions. Uncertainties associated with these studies include influence of wind speed and direction on captured concentrations and variability in analytical techniques used to quantify Pb concentrations on the reported size distributions. [Copyright &y& Elsevier]

Abstract: Ambient air quality monitoring, modeling and compliance to the standards set by European Union (EU) directives and World Health Organization (WHO) guidelines are required to ensure the protection of human and environmental health. Congested urban areas are most susceptible to traffic-related air pollution which is the most problematic source of air pollution in Ireland. Long-term continuous real-time monitoring of ambient air quality at such urban centers is essential but often not realistic due to financial and operational constraints. Hence, the development of a resource-conservative ambient air quality monitoring technique is essential to ensure compliance with the threshold values set by the standards. As an intelligent and advanced statistical methodology, a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality model. In STS methodology, the different components of a time-series dataset such as the trend, seasonal, cyclical and calendar variations can be modeled separately. To test the effectiveness of the proposed modeling strategy, average hourly concentrations of nitrogen dioxide and nitrogen oxides from a congested urban arterial in Dublin city center were modeled using STS methodology. The prediction error estimates from the developed air quality model indicate that the STS model can be a useful tool in predicting nitrogen dioxide and nitrogen oxides concentrations in urban areas and will be particularly useful in situations where the information on external variables such as meteorology or traffic volume is not available. [Copyright &y& Elsevier]

Abstract: In the frame of the MIUR-AEROCLOUDS project (Study of Direct and Indirect Aerosol Effects on Climate), night-time and daytime size-segregated aerosol samples were collected concurrently at five different sites (near-city, urban, rural, marine and mountain background sites). The paper reports on the daily evolution of the main aerosol chemical characteristics as a function of particle size in different environments over the Italian Peninsula, spanning from the Po Valley to the south Tyrrhenian coast. Two 4-day intensive observation periods (IOPs) were undertaken in July 2007 and February 2008, under meteorological conditions typical of the summer and winter climate for Italy. In the summer IOP, under stable atmospheric conditions, at the low-altitude continental sites the diurnal evolution of the planetary boundary layer (PBL), induces an atmospheric dilution effect driving the particulate matter (PM) concentrations, while, at the mountain site, it determines the upward motion of polluted air masses from the Po Valley PBL in daytime. The fine fraction was dominated by ammonium salts and carbonaceous matter (water-soluble organic matter, WSOM, and water-insoluble carbonaceous matter, WINCM). High concentrations of ammonium sulphate and WSOM due to enhanced photochemical activity constituted the background aerosol composition over the whole country, whereas, ammonium nitrate and WINCM were more associated to local emissions (e.g. urban site with concentrations peaking in the finest size range due to strong local traffic-related sources of ultrafine particles). During the winter IOP in the Po Valley, the shallow PBL depths and low wind velocity, especially at night, favoured the condensation of semi-volatile species (i.e. organic matter and ammonium nitrate), causing the high fine PM concentration observed at ground level. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the 2005 global inventory of anthropogenic emissions to the atmosphere component of the work that was prepared by UNEP and AMAP as a contribution to the UNEP report Global Atmospheric Mercury Assessment: Sources, Emissions and Transport (). It describes the methodology applied to compile emissions data on the two main components of the inventory – the ‘by-product’ emissions and the ‘intentional use’ emissions – and to geospatially distribute these emissions estimates to produce a gridded dataset for use by modelers, and the results of this work. It also presents some initial results of work to develop (simplified) scenario emissions inventories for 2020 that can be used to investigate the possible implications of actions to reduce mercury emissions at the global scale. [Copyright &y& Elsevier]

Abstract: The existing and emerging international and European policy framework for the reduction of ship exhaust emissions dictates the need to produce reliable national, regional and global inventories in order to monitor emission trends and consequently provide the necessary support for future policy making. Furthermore, the inventories of ship exhaust emissions constitute the basis upon which their external costs are estimated in an attempt to highlight the economic burden they impose upon the society and facilitate the cost–benefit analysis of the proposed emission abatement technologies, operational measures and market-based instruments prior to their implementation. The case of Greece is of particular interest mainly because the dense ship traffic within the Greek seas directly imposes the impact of its exhaust emission pollutants (NOx, SO2 and PM) upon the highly populated, physically sensitive and culturally precious Greek coastline, as well as upon the land and seas of Greece in general, whereas the contribution of Greece in the global CO2 inventory at a time of climatic change awareness cannot be ignored. In this context, this paper presents the contribution of Greece in ship exhaust emissions of CO2, NOx, SO2 and PM from domestic and international shipping over the last 25 years (1984–2008), utilizing the fuel-based (fuel sales) emission methodology. Furthermore, the ship exhaust emissions generated within the Greek seas and their externalities are estimated for the year 2008, through utilizing the fuel-based (fuel sales) approach for domestic shipping and the activity-based (ship traffic) approach for international shipping. On this basis, it was found that during the 1984 to 2008 period the fuel-based (fuel sales) ship emission inventory for Greece increased at an average annual rate of 2.85%. In 2008, the CO2, NOx, SO2 and PM emissions reached 12.9 million tons (of which 12.4 million tons of CO2) and their externalities were found to be around 3.1 billion euro. With regard to shipping within the Greek seas, the utilization of the fuel-based (fuel sales) analysis for domestic shipping and the activity-based (ship traffic) analysis for international shipping shows that the ship-generated emissions reached 7.4 million tons (of which 7 million tons of CO2) and their externalities were estimated at 2.95 billion euro. Finally, the internalization of external costs for domestic shipping was found to produce an increase of 12.96 and 2.71 euro per passenger and transported ton, respectively. [Copyright &y& Elsevier]

Abstract: This paper synthesizes data on aerosol (particulate matter, PM) physical and chemical characteristics, which were obtained over the past decade in aerosol research and monitoring activities at more than 60 natural background, rural, near-city, urban, and kerbside sites across Europe. The data include simultaneously measured PM10 and/or PM2.5 mass on the one hand, and aerosol particle number concentrations or PM chemistry on the other hand. The aerosol data presented in our previous works () were updated and merged to those collected in the framework of the EU supported European Cooperation in the field of Scientific and Technical action COST633 (Particulate matter: Properties related to health effects). A number of conclusions from our previous studies were confirmed. There is no single ratio between PM2.5 and PM10 mass concentrations valid for all sites, although fairly constant ratios ranging from 0.5 to 0.9 are observed at most individual sites. There is no general correlation between PM mass and particle number concentrations, although particle number concentrations increase with PM2.5 levels at most sites. The main constituents of both PM10 and PM2.5 are generally organic matter, sulfate and nitrate. Mineral dust can also be a major constituent of PM10 at kerbside sites and in Southern Europe. There is a clear decreasing gradient in SO4 2− and NO3 − contribution to PM10 when moving from rural to urban to kerbside sites. In contrast, the total carbon/PM10 ratio increases from rural to kerbside sites. Some new conclusions were also drawn from this work: the ratio between ultrafine particle and total particle number concentration decreases with PM2.5 concentration at all sites but one, and significant gradients in PM chemistry are observed when moving from Northwestern, to Southern to Central Europe. Compiling an even larger number of data sets would have further increased the significance of our conclusions, but collecting all the aerosol data sets obtained also through research projects remains a tedious task. [Copyright &y& Elsevier]

Abstract: This paper presents an objective methodology for determining the optimum number of ambient air quality stations in a monitoring network. The methodology integrates the multiple-criteria method with the spatial correlation technique. The pollutant concentration and population exposure data are used in this methodology in different ways. In the first stage, the Fuzzy Analytic Hierarchy Process (FAHP) with triangular fuzzy numbers (TFNs) is used to identify the most desirable monitoring locations. The network configuration is then determined on the basis of the concept of sphere of influences (SOIs). The SOIs are dictated by a predetermined cutoff value (r c) in the spatial correlation coefficients (r) between the pollutant concentrations at the monitoring stations identified from first step and the corresponding concentrations at neighboring locations in the region. Finally, the optimal station locations are ranked by using combined utility scores gained from the first and second steps. The expansion of air quality monitoring network of Riyadh city in Saudi Arabia is used as a case study to demonstrate the proposed methodology. [Copyright &y& Elsevier]

Abstract: To evaluate the spatial variability of ozone concentrations, two studies were undertaken in the montane environment of Trentino region, northern Italy, in 2007. In the first study, a 225 km2 area was considered. Here, a randomized design was used to evaluate the variability of ozone concentration at 1 and 225 km2 scale. Measurements were carried out by passive samplers between May and June 2007. In a second study, the whole 6207 km2 area of Trentino was considered. The area is covered by five grid cells of the European Monitoring and Evaluation Programme (EMEP). A systematic 15 × 15 km grid was used to allocate 15 passive samplers over the entire province, resulting into 1–4 samplers for each of the 5 EMEP grid cells (2500 km2 each) overlapping the study area. Measurements were carried out between June and September 2007. Accuracy of passive samplers was checked by direct comparison with conventional ozone analysers. Significant differences (P = 0.034) were found in ozone concentration among 1 × 1 km quadrates within the 225 km2 study area, while variability within the 1 × 1 km grid cells (coefficient of variation, CV′ = 0.12) slightly exceed the measurement error (CV′ = 0.08). At larger scales (225, 2500 and 6207 km2), ozone concentration shows much higher variability (CV′ from 0.18 to 0.28, with peak values at 0.40). Reported differences lead to very different AOT40 estimates even within the same EMEP grid cell. These findings suggest that 1 × 1 km resolution seems appropriate for ozone concentration modelling. On the other hand, significant sub-grid variation may exist at the resolution adopted by the EMEP model. Coupled with the likely variability of other important meteorological, soil and vegetation variables, our findings suggest that ozone risk assessment for vegetation based on large-scale modelled AOT40 and flux needs to be considered with great caution. The evidence reported in this paper asks for more detailed national-scale modelling, and the development of methods to incorporate local scale variations into large-scale models. [Copyright &y& Elsevier]

Abstract: In the event of an accidental atmospheric release of radionuclides from a nuclear power plant, accurate real-time forecasting of the activity concentrations of radionuclides is acutely required by the decision makers for the preparation of adequate countermeasures. Yet, the accuracy of the forecasted plume is highly dependent on the source term estimation. Inverse modelling and data assimilation techniques should help in that respect. However the plume can locally be thin and could avoid a significant part of the radiological monitoring network surrounding the plant. Deploying mobile measuring stations following the accident could help to improve the source term estimation. In this paper, a method is proposed for the sequential reconstruction of the plume, by coupling a sequential data assimilation algorithm based on inverse modelling with an observation targeting strategy. The targeting design strategy consists in seeking the optimal locations of the mobile monitors at time t + 1 based on all available observations up to time t. The performance of the sequential assimilation with and without targeting of observations has been assessed in a realistic framework. It focuses on the Bugey nuclear power plant (France) and its surroundings within 50 km from the plant. The existing surveillance network is used and realistic observational errors are assumed. The targeting scheme leads to a better estimation of the source term as well as the activity concentrations in the domain. The mobile stations tend to be deployed along plume contours, where activity concentration gradients are important. It is shown that the information carried by the targeted observations is very significant, as compared to the information content of fixed observations. A simple test on the impact of model error from meteorology shows that the targeting strategy is still very useful in a more uncertain context. [Copyright &y& Elsevier]

Abstract: H2O2 is produced in the atmospheric gas phase only through a single pathway, the HO2 radical recombination. Its main role has been identified in oxidizing SO2 dissolved in hydrometeors to sulphate. Thus aqueous-phase chemistry has been considered to be a main sink (apart from dry deposition and scavenging) but rarely a source of H2O2 despite early findings of its heterogeneous and aqueous-phase production. The aim of this paper is to discuss the atmospheric budget of H2O2 from the multiphase chemistry approach with special emphasis on new sources other than gas-phase HO2 recombination. After providing a brief historic view on H2O2 chemistry, often unknown to young atmospheric chemists but important for a complete understanding, the results of a one-year study of simultaneous measurements of H2O2 in rain and air are presented that show strong evidence for aqueous-phase H2O2 formation. Implications for future changes in atmospheric chemistry are discussed from the viewpoint of an “interfacial chemistry”. [Copyright &y& Elsevier]

Abstract: The use of regulatory and compliance-based modeling for air quality impact assessment is invariably relied upon to predict future air quality under various management scenarios particularly where air quality monitoring data are limited. This paper examines the dispersion from a multi-stack cement manufacturing complex with associated quarries and transport activities for regulatory compliance under uncertain emission and meteorological conditions. The concentrations of CO, NOx, SO2 and PM at sensitive receptor locations were used as indicators in comparison to World Health Organization (WHO) interim guidelines. Exceedance exposure areas were delineated under bounded uncertainties in input emission factors and meteorological parameters. Planning and management initiatives were tested to control/minimize potential exposure. Compared to the case of low emissions and actual meteorological conditions, the consideration of worst emissions coupled to worst meteorological conditions enlarged the boundaries of the exceedance exposure areas considerably. The implementation of best available technologies and enforcement of emission standards improved air quality in the region significantly and lowered the exposure at many population centers to below health standards. Uncertainty in the output of atmospheric dispersion models continues to play a significant role to be considered at the point where science is translated into political decision making. [Copyright &y& Elsevier]

Abstract: In this paper we describe and quality assure the sampling system of a mobile research laboratory SNIFFER which was shown to be a useful tool for studying emission levels of respirable dust from street surfaces. The dust plume had bimodal structure; another mode rising to higher altitudes whereas the other mode remained at lower altitudes. The system was tested on a route in Helsinki, Finland, during spring 2005 and 2006. The PM2.5 and PM10 were positively correlated and the PM levels increased with the vehicle speed. SNIFFER was able to identify the characteristic emission levels on different streets. A clear downward trend in the concentrations was observed in all street locations between April and June. The composition of the street dust collected by SNIFFER was compared with springtime PM10 aerosol samples from the air quality monitoring stations in Helsinki. The results showed similarities in the abundance and composition of the mineral fraction but contained significantly more salt particles. [Copyright &y& Elsevier]

Abstract: An interdisciplinary field study designed to investigate the spatial and temporal variability of atmospheric aerosols during high particulate matter (PM) events along the US–Mexico border near Yuma, AZ was run during the week of March 18, 2007. The experiments were designed to quantify chemical composition and physical phenomena governing the transport of aerosols generated from episodic high PM events. The field study included two micrometeorological monitoring sites; one rural and one urban, equipped with sonic anemometers, continuous particulate concentration monitors and ambient aerosol collection equipment. In addition to the two main monitoring sites, five additional locations were equipped with optical particle counters to allow for the investigation of the spatial and temporal distribution of PM 2.5 in the urban environment. In this paper, the meteorological and turbulence parameters governing the distribution and concentration of PM 2.5 in the urban environment for two high-wind erosion events and one burning event are compared. The interaction between local atmospheric conditions and the particulate distribution is investigated. Results indicate that a single point measurement in the urban area of Yuma may not be sufficient for determining the ambient PM concentrations that the local population experiences; all three high PM events indicated PM 2.5 varied considerably with maximum urban concentrations 5–10 times greater than the measured minima. A comparison of inorganic and carbonaceous content of the aerosols for the three high PM events is presented. The comparison shows an increase in silicon during crustal dust events and an increase in elemental and organic carbon during the burn event. Additional surface chemistry analysis, using time-of-flight secondary ion mass spectrometry (ToF-SIMS), for aerosols collected at the urban and rural sites during the burn event are discussed. The surface chemistry analysis provides positive ion mass spectra of organic and inorganic species in the ambient aerosol, and can be used to determine the type of combustion process that contributed to an increase in PM concentration during the burn event. [Copyright &y& Elsevier]

Abstract: In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network''s capability to correctly follow and represent SO2 fields in Bilbao, in the frame of a continuous network optimization process. The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area. To assess the spatial variability of SO2 measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R. [Copyright &y& Elsevier]

In order to carry out efficient traffic and air quality management, validated models and PM emission estimates are needed. This paper compares current available emission factor estimates for PM10 and PM2.5 from emission databases and different emission models, and validates these against eight high quality street pollution measurements in Denmark, Sweden, Germany, Finland and Austria. The data sets show large variation of the PM concentration and emission factors with season and with location. Consistently at all roads the PM10 and PM2.5 emission factors are lower in the summer month than the rest of the year. For example, PM10 emission factors are in average 5–45% lower during the month 6–10 compared to the annual average. The range of observed total emission factors (including non-exhaust emissions) for the different sites during summer conditions are 80–130mgkm−1 for PM10, 30–60mgkm−1 for PM2.5 and 20–50mgkm−1 for the exhaust emissions. We present two different strategies regarding modelling of PM emissions: (1) For Nordic conditions with strong seasonal variations due to studded tyres and the use of sand/salt as anti-skid treatment a time varying emission model is needed. An empirical model accounting for these Nordic conditions was previously developed in Sweden. (2) For other roads with a less pronounced seasonal variation (e.g. in Denmark, Germany, Austria) methods using a constant emission factor maybe appropriate. Two models are presented here. Further, we apply the different emission models to data sets outside the original countries. For example, we apply the “Swedish” model for two streets without studded tyre usage and the “German” model for Nordic data sets. The “Swedish” empirical model performs best for streets with studded tyre use, but was not able to improve the correlation versus measurements in comparison to using constant emission factors for the Danish side. The “German” method performed well for the streets without clear seasonal variation and reproduces the summer conditions for streets with pronounced seasonal variation. However, the seasonal variation of PM emission factors can be important even for countries not using studded tyres, e.g. in areas with cold weather and snow events using sand and de-icing materials. Here a constant emission factor probably will under-estimate the 90-percentiles and therefore a time varying emission model need to be used or developed for such areas. All emission factor models consistently indicate that a large part (about 50–85% depending on the location) of the total PM10 emissions originates from non-exhaust emissions. This implies that reduction measures for the exhaust part of the vehicle emissions will only have a limited effect on ambient PM10 levels. [Copyright &y& Elsevier]

Abstract: This paper describes the procedures employed to spatially distribute global inventories of anthropogenic emissions of mercury to the atmosphere, prepared by Pacyna, E.G., Pacyna, J.M., Steenhuisen, F., Wilson, S. [2006. Global anthropogenic mercury emission inventory for 2000. Atmospheric Environment, this issue, doi:10.1016/j.atmosenv.2006.03.041], and briefly discusses the results of this work. A new spatially distributed global emission inventory for the (nominal) year 2000, and a revised version of the 1995 inventory are presented. Emissions estimates for total mercury and major species groups are distributed within latitude/longitude-based grids with a resolution of 1×1 and 0.5×0.5°. A key component in the spatial distribution procedure is the use of population distribution as a surrogate parameter to distribute emissions from sources that cannot be accurately geographically located. In this connection, new gridded population datasets were prepared, based on the CEISIN GPW3 datasets (CIESIN, 2004. Gridded Population of the World (GPW), Version 3. Center for International Earth Science Information Network (CIESIN), Columbia University and Centro Internacional de Agricultura Tropical (CIAT). GPW3 data are available at http://beta.sedac.ciesin.columbia.edu/gpw/index.jsp). The spatially distributed emissions inventories and population datasets prepared in the course of this work are available on the Internet at www.amap.no/Resources/HgEmissions/ [Copyright &y& Elsevier]

Abstract: This paper presents the development, laboratory evaluation, and field tests of a personal respirable particulate sampler (PRPS). The PRPS is designed as a personal sampling system to collect particulate matter (PM0.5, PM1.0, PM2.5, PM4.5, and PM10) and gaseous pollutants, including O3, SO2, and NO2. It operates at a flow rate of 5.0LPM and consists of five selectable impaction stages (with cutpoints of 10, 4.5, 2.5, 1.0, and 0.5μm), a backup filter, and two diffusion passive samplers. In each impaction stage, particles are collected onto a polyurethane foam (PUF) substrate. This substrate, using no adhesive, was shown to have minimum particle bounce and re-entrainment. A backup 37mm Teflon membrane filter is used downstream to collect particles smaller than the cutoff diameter of the final impaction stage. The impaction stage cutpoints were characterized in the laboratory using artificially generated polydisperse aerosols. Particle losses for each stage were found to be acceptably low. The performance of the PRPS was also compared with that of a collocated micro-orifice cascade impactor (MOI) and real-time particle sizing instruments (SMPS/APS) in laboratory experiments using artificially generated particles. The size distributions measured by the PRPS were found to be much closer to those measured by the real-time particle sizing instruments than to those measured by the MOI. A field PM intercomparison study was also conducted using the PRPS and three reference samplers, the Harvard Impactor (HI), the USEPA PM2.5 Well Impactor Ninety Six (WINS), and the Harvard Personal Environmental Monitor (Harvard PEM) sampler. The PM10, PM2.5, and sulfate concentrations measured by PRPS were in a very good agreement with those obtained from the reference samplers. [Copyright &y& Elsevier]

Abstract: The percentage weighting polygon (PWP) method is proposed as an alternative to the classical arithmetic average (AA) method for calculating the average areal concentration (AAC) over an urban centre. The basis of the method is to divide the study area into a set of sub-areas by considering three adjacent air pollutants concentration percentages at a time. This method is more reliable and flexible than the AA method where the subareas remain the same independent of the measured air pollutants concentrations. In this paper, the PWP method is applied to the urban centre of Erzurum in Turkey for the first time, at six air quality monitoring stations. In the PWP method, higher air pollutant concentration values are represented with the smaller sub-areas than in the case of the AA method. It is observed that the PWP method yields a 16.5% smaller AAC value than the classical AA method. [Copyright &y& Elsevier]

In order to protect public health by providing an early warning of harmful air pollutants, various forecasting models are proposed to forecast the average values of daily pollutant concentrations. In fact, even on the same day, the concentration of pollutants will fluctuate greatly during different time periods, point-based models can not reflect the variability well. Thus, an enhanced interval PM 2.5 concentration forecasting model is developed in this paper, which is based on interval decomposition ensemble and considering influencing factors. For the purpose of obtaining main influencing factors, interval grey incidence analysis (IGIA) is used to select input variables for model. The interval-valued time series (ITS) of PM 2.5 concentration and its influencing factors are decomposed into a finite number of complex-valued intrinsic mode functions (IMFs) and one complex-valued residual by bivariate empirical mode decomposition (BEMD) algorithm. Considering the different amounts of various IMFs, the complex-valued IMFs and residual are clustered into fewer classes by reconstruction technique. Then, interval multilayer perceptron (MLPI) is employed to fit the lower and upper bound simultaneously of all classes to obtain the corresponding forecasting results, which are combined to generate the aggregated interval-valued output by a simple addition approach. The model is tested by the dataset collected from three environmental monitoring stations in Beijing, China. Experimental results show that the enhanced model outperforms other considered models by means of forecasting accuracy and stability. • Model is applied to interval-valued PM 2.5 concentration forecasting. • BEMD and MLPI model the lower and upper bound of ITS simultaneously. • A new interval-valued reconstruction technique is proposed. • The proposed model takes into account influencing factors. • The enhanced model improves accuracy and stability. [ABSTRACT FROM AUTHOR]