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In depth and detailed study about various classes of aerosols over an urban city of Beijing has been carried out, with the help of cluster technique during the period from (2005–2017). Aerosol Robotic Network (AERONET), retrieved data for Aerosol Optical Depth (AOD), Angstrom Exponent (AE), Extinction Angstrom Exponent (EAE), Absorption Angstrom Exponent (AAE), Single Scattering Albedo (SSA), Real and Imaginary index of Refraction (RRI & IRI respectively), Asymmetry Parameter (ASY) has been utilized for discrimination of aerosols over the study site. Higher mean values of AOD and AE were found in winter and spring season as (0.86 ± 0.38, 0.85 ± 0.32) and (1.06 ± 0.36, 1.19 ± 0.21), while lower values (0.75 ± 0.33, 0.75 ± 0.33) and (0.97 ± 0.22, 0.85 ± 0.17) for summer and autumn season respectively, representing mixed anthropogenic aerosols over the site. Three main types of aerosol were reported in this study: Mixed Carbonaceous (MC), Biomass Residuals (BR), and coarse mode local and transported Dust Particles (DP). Various aerosol parameters and their inter-relationship were investigated in detail to analyze the dominant aerosol type and its seasonal variations. The EAE and AAE values ranged from (0.10–1.77 and 0.00–1.70 respectively), could mainly be attributed towards MC aerosols. Real and Imaginary parts of Index (RRI & IRI) were recorded in the range from (1.33–1.60 and 0–0.010) respectively. Similarly, the range for SSA and ASY was found as (0.79–0.99 and 0.43–0.78) respectively. Back-trajectories using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model revealed transportation of air masses from Mongolian deserts, Gobi desert, and other neighboring regions (i.e. Russia and Kazakhstan). • Aerosols study of Beijing • AERONET • AOD • Carbonaceous aerosols [ABSTRACT FROM AUTHOR]

Abstract The oxidative potential (OP) of fine and coarse fractions of ambient aerosols was studied in the urban environment of Athens, Greece. OP was quantified using a dithiothreitol (DTT) assay, applied to the water soluble fraction of aerosol that was extracted from 361 fine and 84 coarse mode of 24-h and 12-h filter samples over a one-year period. During the cold period, samples were collected on a 12-h basis, to assess the impact of night-time biomass burning emissions from domestic heating on OP. The chemical characteristics of aerosols were measured in parallel using an Aerosol Chemical Speciation Monitoring (ACSM) and a 7-wavelength Aethalometer. A source apportionment analysis on the ACSM data resulted in the identification of organic aerosol (OA) factors on a seasonal basis. A good correlation of OP with NO 3 −, NH 4 +, BC (Black Carbon), Organics and LV-OOA (low volatility oxygenated OA) was found during winter, revealing the importance of combustion and aging processes for OP. During the summertime, a good correlation between OP and SO 4 −2 and NH 4 +indicates its association with regional aerosol – thus the importance of oxidative aging that reduces its association with any characteristic source. Multiple regression analysis during winter revealed that highly oxygenated secondary aerosol (LV-OOA) and, to a lesser extent, fresh biomass burning (BBOA) and fossil fuel (HOA) organic aerosol, are the prime contributors to the OP of fine aerosol, with extrinsic toxicities of 54 ± 22 pmol min−1 μg−1, 28 ± 7 and 17 ± 4 pmol min−1μg−1, respectively. In summer, OP cannot be attributed to any of the identified components and corresponds to a background aerosol value. In winter however, the regression model can reproduce satisfactorily the water soluble DTT activity of fine aerosol, providing a unique equation for the estimation of aerosol OP in an urban Mediterranean environment. Graphical abstract Image 1 Highlights • Yearlong oxidative potential measurements on 367 fine aerosol samples. • Fine urban aerosol oxidative potential is 3 times higher compared to coarse mode. • Winter elevated oxidative potential attributed to fresh aerosol emissions. • Summer background aerosol oxidative potential due to long-range transport. • Satisfactory reconstruction of fine aerosol water-soluble dithiothreitol activity. [ABSTRACT FROM AUTHOR]

Abstract Vertical variation in aerosol optical properties [e.g. Single Scattering Albedo (SSA) and aerosol extinction coefficient] over a polluted environment is extremely important for better understanding of columnar radiative characteristics. The present case study over a typical polluted environment (New Delhi) discusses the vertical profile (ground to 700 m) of modelled optical properties of atmospheric particles at different altitudes. Here, we used the aerosol physico-chemical data generated in the tethered balloon-based observation conducted at CSIR-NPL, New Delhi (28° 38′ 10″ N, 77° 10′ 17″ E) from 21st −27th February 2014. Based on the microscopic observations of individual particles, we developed the aerosol model shapes (coated spheres) for simulating their optical properties. Total three cases were considered for simulating the aerosol optics at varying altitude; Case A: External mixture of coated dust and coated sulfate particles; Case B: External mixture of coated dust, coated sulfate, coated OC (Organic Carbon) and coated EC (Elemental Carbon) (with assumption that 6% EC at ground level); Case C: External mixture of coated dust, coated sulfate, coated OC and coated EC (with assumption that 10% EC at ground level). At 550 nm wavelength, the value of SSA has been found to be highest (i.e. 0.985) at 200 m altitude for Case A while Case B (i.e. 0.9523) and Case C (i.e. 0.9291) show highest values at 500 m altitude. SSA was found to be maximum at 500 m altitude for both Case B and Case C due to the presence of lowest graphitic counts at that particular altitude. Case B and Case C exhibit similar pattern but differ in magnitude, this is due to two EC extremities at ground level i.e. minima (6%) and maxima (10%). The percentage deviation in SSA from ground level to 700 m was found to be highest for Case C (i.e. 5.95%) followed by Case B (i.e. 4.19%) and Case A (i.e. 1.4%). Modelled aerosol optical properties within boundary layer may improve our understanding about the thermodynamics of lower atmosphere. Highlights • A case study over a typical polluted environment (New Delhi) discusses the vertical profile of modelled optical properties of atmospheric particles at different altitudes. • The aerosol physico-chemical data (bulk and individual particle level) used to simulate the vertical profile of aerosol optical properties. • Better assessment of vertical profile of aerosol optical properties plays an important role in reducing the uncertainties associated with radiative forcing. • Frequent airborne observations will certainly provide statistically significant region-specific aerosol properties. [ABSTRACT FROM AUTHOR]

Abstract Cities are now becoming the focus for CO 2 emission reduction efforts worldwide and there is a growing need for establishing emission inventories, developing methodologies for improved CO 2 monitoring and understanding of the multiple source, sink and storage processes inside the complex urban environment. This study combines Eddy Covariance (EC) measurements of CO 2 flux (F C) during one year period over the city centre of Heraklion with analytical morphological and land cover data to achieve a thorough investigation of the spatiotemporal variability and the controlling factors of F C in the urban setting. The detailed characterization of the urban land cover and 3D structure was performed using high resolution Earth Observation data. The urban morphological data was used to parameterize a turbulent flux source area model and the land cover data used to analyse the contribution of the source area components to the measured F C. Heraklion F C does not present any specific seasonal trend according to the meteorological or vegetation changes throughout the year. Heraklion centre behaves as a net emitter diurnally and throughout the year. The diurnal variability presents a standard pattern in weekdays with a major peak in midday and a secondary in afternoon, clearly following the traffic rush-hour peaks. Space heating emissions during winter remain low, hardly affecting the seasonal and diurnal F C patterns. The main CO 2 sources are the major roads and the intersections, where the heavy traffic is located. The source area analysis revealed that traffic contributes 69% to the estimated annual CO 2 emissions. Space heating contributes only 11.6%, while human metabolism is estimated to contribute 19.4%. Vegetation cover of the source area is very low and was assumed to have minor effect to the annual F C budget. The estimated total annual emissions of Heraklion case study reach 19.4 kg CO 2 m−2 y−1. Highlights • Urban heterogeneity induces increased spatial variability of CO 2 flux. • Earth Observation data can support a detailed spatial CO 2 flux interpretation. • Detailed source area analysis can reveal the controlling factors of urban CO 2 flux. • Vehicle traffic in major roads and intersections are main CO 2 sources of Heraklion. [ABSTRACT FROM AUTHOR]

Abstract Recently, Haze-fog as an atmospheric phenomenon associated with high level of air pollutant has negative impacts on human health and environment, which arises the society attention. This paper is aimed at investigating the haze-fog dispersion in the urban environment from the physical view. The wind flow and particle dispersion in the urban environment are simulated by using the Delayed Detached-eddy Simulation (DDES) turbulence model and the Discrete Phase Model (DPM) under the atmospheric boundary layer flow. The results show that the particle dispersion is dominated by the wind flow including the velocity and vortex distribution and the gravity can slightly influence the particle deposition. The particle-empty areas around the buildings are identified during the dispersion and then they disappear gradually mainly through the recirculation function. When the wind direction changes, the blockage cross-section area derived from the building group becomes larger resulting in the larger low wind velocity area. Furthermore, the different reference inlet velocities directly affect the vorticity magnitude and the particle dispersion periods. It is concluded that the DDES model is a promising approach to simulate the haze-fog physical development in the urban environment. Highlights • The DDES turbulence model is combined with the DPM to simulate the wind flow and particle dispersion. • The particle dispersion is dominated by the wind flow including the velocity and vortex distribution. • The different wind directions significantly change the low wind velocity area distribution. • The different reference inlet velocities directly affect the vorticity magnitude and the particle dispersion periods. • The DDES model is a promising approach to simulate the haze-fog physical development. [ABSTRACT FROM AUTHOR]

Abstract In this study we investigated the respective contributions of changing meteorology and anthropogenic emissions to Hg wet deposition in New York State (NYS), which illustrated quantitatively how the variations in meteorological conditions modified the response of Hg wet deposition to anthropogenic emission reductions in NYS. A regional chemical transport model, CMAQ-newHg-Br (Ye et al., 2018), was employed driven by four sets of meteorological fields (2004, 2005, 2007, and 2010) and two anthropogenic emission inventories (NEI, 2005 and 2011). Four major findings emerged from this study. First, simulated Hg wet deposition flux in NYS was greatly affected by variation in meteorological conditions, ranging from a 91% decrease to a factor of 5 increase in monthly Hg wet deposition, whereas it hardly responded (2%) to a near doubling of emissions in the northeastern U.S. Second, the precipitation amount dominated interannual and seasonal variations of Hg wet deposition over all other meteorological variables, with total (= convective + non-convective) precipitation explained 60% of Hg wet deposition variance in an urban environment compared to convective precipitation alone explaining 65% in a rural area. Third, large-scale atmospheric circulation influenced regional transport greatly leading to out-of-state anthropogenic emissions explaining at least 80% of Hg wet deposition changes in a NYS urban environment. Fourth, higher Hg concentrations in precipitation and higher atmospheric reactive mercury concentrations in urban areas were related to calm conditions due likely to regional build-up of emissions, whereas in rural areas photochemical oxidation of gaseous elemental mercury was a more important source of reactive mercury. Solar radiation variance was found to explain 41–55% of the variance in simulated reactive mercury concentrations. Given that more than 95% of the US is rural lands and the majority of water bodies occur in rural areas, a realistic chemical mechanism for photochemical gaseous elemental mercury oxidation is paramount to accurate simulation of reactive mercury formation and Hg wet deposition in the US. Highlights • Simulated Hg wet deposition in NYS was dominated by precipitation amounts. • NYS averaged Hg wet deposition was insensitive to changes in NE U.S. emissions. • Regional emissions build-up caused higher urban precipitation Hg concentrations & RM. • In-situ photochemistry was a significant source for RM in rural environments. [ABSTRACT FROM AUTHOR]

Abstract Locating and quantifying the hazardous material source plays a significant role in the emergency action plans related to the intentional or accidental release. This issue is the most important in the cities where the threat to peoples health is the highest. In this paper, we present a complete framework to identify in real-time the airborne toxics source in an urban environment. Proposed framework utilizes the adjusted sequential version of the Approximate Bayesian Computation (ABC) methodology. Dedicated modifications enhanced the estimation of the posterior distributions of contamination source parameters significantly. The source parameters assessments are dynamically updated with the use of on-line arriving concentrations of released substance reported by sensors network. In reconstruction we utilize the advanced Quick Urban & Industrial Complex Dispersion Modeling system (QUIC), developed by Los Alamos National Laboratory, to predict the concentrations at the sensors locations. We validate the proposed methodology on real data coming from a full-scale field experiment DAPPLE conducted in central London in 2007. We confirm the effectivity of the proposed framework by successful estimation of six parameters characterizing the contamination source, i.e., source position (x,y,z) in a city environment, the mass of release (q), the release start time (s) and its duration (l). The presented results prove the utility of the proposed approach for event reconstruction problem in the highly urbanized environment. The presented framework can be adopted quickly during the emergency response planning in any complex urban environment with the use of suitable dispersion model. Graphical abstract Image 1 Highlights • Sensors data-driven localization of atmospheric contamination source in urban area. • SMC ABC algorithm modifications dedicated to source identification task in urban area. • Estimation of a posteriori distribution of airborne toxics source parameters. • Verification of the proposed framework with use of the data from DAPPLE experiment. • Successful stochastic reconstruction of six source parameters in urban area. [ABSTRACT FROM AUTHOR]

Abstract Unexpected releases of hazardous airborne materials may happen in various circumstances, more frequently in accidental situations, less usually due to malicious activities. In all cases, the risk for the population and the rescue team is real and must be evaluated in order to take appropriate protection measures. Numerical models are more and more used in emergency response tools for predicting the atmospheric dispersion of pollutants and estimating impacted areas. Still, flow and dispersion modelling in a built-up environment may be very challenging given the complex geometry and meteorological conditions. Here, we present and evaluate a modelling approach that is a compromise between accuracy and timeliness of the computations. It is based on a 3D Lagrangian Particle Dispersion model driven by 3D flow and turbulence input provided by either a diagnostic mass-consistent model or a model solving the Reynolds-Averaged Navier-Stokes equations. This modelling system has been validated on a panel of experimental test cases from the Cooperation in Science and Technology (COST) Action ES1006 in both idealized and realistic urban mock-ups, wind tunnel and field trials, continuous and puffs releases. The sensitivity of the model to the meteorological input data is assessed. The results are discussed comparing predicted concentrations to measurements. The performances of the modelling system are evaluated through a statistical analysis. They were found to depend on the type of test case, type of release and location of the source in the built-up domain. Results show that the model is compliant with the validation criteria, established in literature for the reference metrics, in the large majority of the test cases. The modelling system proved to be robust enough to be used in the context of emergency response, when fast but still reliable results are needed. Graphical abstract We present and evaluate a modelling approach that is a compromise between accuracy and timeliness of the computations for simulating unexpected releases in built environments. (P)MSS, a 3D Lagrangian Particle Dispersion model driven by 3D flow and turbulence input, is applied. The modelling system is validated on a panel of experimental test-cases from the Cooperation in Science and Technology (COST) Action ES1006 in both idealized and realistic urban mock-ups, wind tunnel and field trials, continuous and puffs releases. Results show that the model is compliant with the validation criteria in the large majority of the test-cases. The modelling system provides reliable results and it is prone to quickly inform about the distribution of possibly noxious materials in built-up populated areas. Image 1 Highlights • Unexpected releases of hazardous materials in the atmosphere need to be simulated. • Releases of hazardous materials may have complex patterns in built-up areas. • A timely response is fundamental to handle the protection measures. • Lagrangian Particle Models provide good accuracy and timeliness of computation. • Model validation on observed data is essential to assess the simulation performance. [ABSTRACT FROM AUTHOR]

Nitrate has become the most important hydrophilic chemical component in PM 2.5 during serious air pollution periods in urban areas of the Pearl River Delta (PRD) region of south China, but there is a lack of fully understanding of its formation mechanisms and controlling factors, especially during daytime nitrate episodes. To fill the knowledge gap, water-soluble inorganic ions in PM 2.5 and trace gases including SO 2 , HNO 3 , NH 3 , NOx and O 3 , particle size distribution, vertical profile of aerosol backscatter density, and ground-level and vertical profiles of key meteorological variables were simultaneously measured at high time resolution in urban Guangzhou of the PRD. The remarkably enhanced nitrate mass concentrations observed at the surface-level during daytime were identified to be caused by strong boundary-layer turbulent mixing of residual aerosols produced from evaporation of low-level shallow stratocumulus clouds. This finding may have important implications on the sources of secondary inorganic aerosols in this and other similar cloudy regions. [ABSTRACT FROM AUTHOR]

Particle number size distributions are among the most important parameters in trying to understand the characteristics of particle population. Atmospheric particles were measured in an interaction of mixed environments in the Southeastern coastal city of Wollongong, Australia, during a comprehensive field campaign known as Measurements of Urban, Marine and Biogenic Air (MUMBA). MUMBA ran in summer season between 21 st December 2012 and 15 th February 2013. Particle number concentrations measured during this campaign were indicative of the interplay between marine environments and urban air which met the objective of this campaign. Particle number size distributions ranging from 14 nm to 660 nm in diameter, as measured by Scanning Mobility Particle Sizer (SMPS) in this study, were grouped using Principal Component Analysis. Based on strong component loadings (value ≥ 0.75), three different factors were identified (i) Small Factor (N S ): 15 nm < D p < 50 nm, (ii) Medium Factor (N M ): 60 nm < D p < 150 nm and (iii) Large Factor (N L ): 210 nm < D p < 450 nm. The three factors describe 89% of the dataset cumulative variance. Particles in this region are dependent upon the interaction between the sources, and cannot be viewed as a simple mixture of biogenic and anthropogenic sources associated with various mechanical processes. The particles observed in the morning were found to be influenced by combustion emissions, presumably primarily from traffic, which is most obvious in N L . The particle population during the day was found to be influenced by a mixture of marine sources and secondary aerosols production initiated by photochemical oxidation. The local steel works and the urban environment were the major contributors of particles at night. Secondary organic aerosols were identified in this study by the mass ratio of organic carbon to elemental carbon (OC/EC). Biogenic sources influenced secondary organic aerosols formation as a moderate correlation (R 2  = 0.6) was observed between secondary organic aerosols mass and biogenic isoprene. The processes described in this paper are likely repeated at other coastal urban environments worldwide. [ABSTRACT FROM AUTHOR]

The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R 2  = 0.36–0.51), a gradient boosting regression tree model can significantly improve device calibration (R 2  = 0.68–0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors. [ABSTRACT FROM AUTHOR]

Poor air quality episodes are common in central China. Here, based on 10 years of ground-based sun-photometric observations, aerosol optical and radiative forcing characteristics were analyzed in Wuhan, the biggest metropolis in central China. Aerosol optical depth (AOD) in the last decade declined significantly, while the Ångström exponent (AE) showed slight growth. Single scattering albedo (SSA) at 440 nm reached the lowest value (0.87) in winter and highest value (0.93) in summer. Aerosol parameters derived from sun-photometric observations were used as input in a radiative transfer model to calculate aerosol radiative forcing (ARF) on the surface in ultraviolet (UV), visible (VIS), near-infrared (NIR), and shortwave (SW) spectra. ARF SW sustained decreases (the absolute values) over the last 10 years. In terms of seasonal variability, due to the increases in multiple scattering effects and attenuation of the transmitted radiation as AOD increased, ARF in summer displayed the largest value (−73.94 W/m 2 ). After eliminating the influence of aerosol loading, the maximum aerosol radiative forcing efficiency in SW range (ARFE SW ) achieved a value of −64.5 W/m 2 /AOD in April. The ARFE change in each sub-interval spectrum was related to the change in SSA and effective radius of fine mode particles (Refff), that is, ARFE increased with the decreases in SSA and Refff. The smallest contribution of ARFE NIR to ARFE SW was 34.11% under strong absorbing and fine particle conditions, and opposite results were found for the VIS range, whose values were always over 51.82%. Finally, due to the serious air pollution and frequency of haze day, aerosol characteristics in haze and clear days were analyzed. The percentage of ARFE NIR increased from 35.71% on clear-air days to 37.63% during haze periods, while both the percentage of ARFE UV and ARFE NIR in ARFE SW kept decreasing. The results of this paper should help us to better understand the effect of aerosols on solar spectral radiation and to develop improved the aerosol models over central China. [ABSTRACT FROM AUTHOR]

Nitrous acid (HONO) is a key reservoir of the hydroxyl radical (OH) and plays a central role in the atmospheric chemistry. To understand the sources and impact of HONO in the polluted atmosphere of northern China, continuous measurements of HONO and related parameters were conducted from September 2015 to August 2016 at an urban site in Ji'nan, the capital city of Shandong province. HONO showed well-defined seasonal and diurnal variation patterns with clear wintertime and nighttime concentration peaks. Elevated HONO concentrations (e.g., over 5 ppbv) were frequently observed with a maximum value of 8.36 ppbv. The HONO/NO X ratios of direct vehicle emissions varied in the range of 0.29%–0.87%, with a mean value of 0.53%. An average NO 2 -to-HONO nighttime conversion frequency (k het ) was derived to be 0.0068 ± 0.0045 h −1 from 107 HONO formation cases. A detailed HONO budget analysis suggests an unexplained daytime missing source of 2.95 ppb h −1 in summer, which is about seven times larger than the homogeneous reaction of NO with OH. The effect of HONO on OH production was also quantified. HONO photolysis was the uppermost source of local OH radical throughout the daytime. This study provides the year-round continuous record of ambient HONO in the North China Plain, and offers some insights into the characteristics, sources and impacts of HONO in the polluted atmospheres of China. [ABSTRACT FROM AUTHOR]

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM 2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM 2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM 2.5 events that contributed to elevated seasonal PM 2.5 levels. Similarly, in spring, high PM 2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM 2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM 2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM 2.5 . [ABSTRACT FROM AUTHOR]

In this work, we present an inverse computational method for the identification of the location, start time, duration and quantity of emitted substance of an unknown air pollution source of finite time duration in an urban environment. We considered a problem of transient pollutant dispersion under stationary meteorological fields, which is a reasonable assumption for the assimilation of available concentration measurements within 1 h from the start of an incident. We optimized the calculation of the source-receptor function by developing a method which requires integrating as many backward adjoint equations as the available measurement stations. This resulted in high numerical efficiency of the method. The source parameters are computed by maximizing the correlation function of the simulated and observed concentrations. The method has been integrated into the CFD code ADREA-HF and it has been tested successfully by performing a series of source inversion runs using the data of 200 individual realizations of puff releases, previously generated in a wind tunnel experiment. [ABSTRACT FROM AUTHOR]

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NO x predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies. [ABSTRACT FROM AUTHOR]

The application of salts and salty brines to roads is common practice during the winter in many urban environments. Road salts can become aerosolized, thereby injecting sodium and chloride particulate matter (PM) into the atmosphere. Here, data from the United States Environmental Protection Agency Chemical Speciation Monitoring Network were used to assess temporal trends of sodium and chloride PM 2.5 (PM < 2.5 μm) at 25 locations across the United States to investigate the ubiquity of road salt aerosols. Sodium and chloride PM 2.5 concentrations were an average of three times higher in the winter, as compared to the summer, for locations with greater than 25 cm of average annual snowfall. Winter urban chloride PM 2.5 concentrations attributed to road salt can even sometimes rival those of coastal sea spray aerosol-influenced sites. In most snow-influenced cities, chloride and sodium PM 2.5 concentrations were positively correlated with snowfall; however, this relationship is complicated by differences in state and local winter maintenance practices. This study highlights the ubiquity of road salt aerosols in the United States and their potential impact on wintertime urban air quality, particularly due to the potential for multiphase reactions to liberate chlorine from the particle-phase. Since road salt application is a common practice in wintertime urban environments across the world, it is imperative that road salt application emissions, currently not included in inventories, and its impacts be investigated through measurements and modeling. [ABSTRACT FROM AUTHOR]

Two analytical methods for determining levels of 1,3-butadiene in urban and industrial atmospheres were evaluated in this study. Both methods are extensively used for determining the concentration of volatile organic compounds in the atmosphere and involve collecting samples by active adsorptive enrichment on solid sorbents. The first method uses activated charcoal as the sorbent and involves liquid desorption with carbon disulfide. The second involves the use of a multi-sorbent bed with two graphitised carbons and a carbon molecular sieve as the sorbent, with thermal desorption. Special attention was paid to the optimization of the sampling procedure through the study of sample volume, the stability of 1,3-butadiene once inside the sampling tube and the humidity effect. In the end, the thermal desorption method showed better repeatability and limits of detection and quantification for 1,3-butadiene than the liquid desorption method, which makes the thermal desorption method more suitable for analysing air samples from both industrial and urban atmospheres. However, sampling must be performed with a pre-tube filled with a drying agent to prevent the loss of the adsorption capacity of the solid adsorbent caused by water vapour. The thermal desorption method has successfully been applied to determine of 1,3-butadiene inside a 1,3-butadiene production plant and at three locations in the vicinity of the same plant. [ABSTRACT FROM AUTHOR]

Exposure to particulate matter air pollution with a nominal mean aerodynamic diameter less than or equal to 2.5 μm (PM 2.5 ) has been associated with health effects including cardiovascular disease and death. Here, we add to the understanding of urban and rural PM 2.5 concentrations over large spatial and temporal scales in recent years. We used high-quality, publicly-available air quality monitoring data to evaluate PM 2.5 concentration patterns and changes during the years 2000–2015. Compiling and averaging measurements collected across the U.S. revealed that PM 2.5 concentrations from urban sites experienced seasonal maxima in both winter and summer. Within each year from 2000 to 2008, the maxima of urban summer peaks were greater than winter peaks. However, from 2012 to 2015, the maxima of urban summertime PM 2.5 peaks were smaller than the urban wintertime PM 2.5 maxima, due to a decrease in the magnitude of summertime maxima with no corresponding decrease in the magnitude of winter maxima. PM 2.5 measurements at rural sites displayed summer peaks with magnitudes relatively similar to those of urban sites, and negligible to no winter peaks through the time period analyzed. Seasonal variations of urban and rural PM 2.5 sulfate, PM 2.5 nitrate, and PM 2.5 organic carbon (OC) were also assessed. Summer peaks in PM 2.5 sulfate decreased dramatically between 2000 and 2015, whereas seasonal PM 2.5 OC and winter PM 2.5 nitrate concentration maxima remained fairly consistent. These findings demonstrate that PM 2.5 concentrations, especially those occurring in the summertime, have declined in the U.S. from 2000 to 2015. In addition, reduction strategies targeting sulfate have been successful and the decrease in PM 2.5 sulfate contributed to the decline in total PM 2.5 . [ABSTRACT FROM AUTHOR]

Plants can mitigate ambient particulate matter by cleaning the air, which is crucial to urban environments. A novel approach was presented to quantitatively characterize particulate matter deposited on urban tree foliage. This approach could accurately quantify the number, size, shape, and spatial distribution of particles with different diameters on leaves. Spatial distribution is represented by proximity, which measures the closeness of particles. We sampled three common broadleaf species and obtained images through field emission scanning electron microscopy. We conducted the object-based method to extract particles from images. We then used Fragstats to analyze the landscape characteristics of these particles in term of selected metrics. Results reveal that Salix matsudana is more efficient than Ailanthus altissima and Fraxinus chinensis in terms of the number and area of particles per unit area and the proportion of fine particulate matter. The shape complexity of the particles increases with their size. Among the three species, S. matsudana and A. altissima particles respectively yield the highest and lowest proximity. PM 1 in A. altissima and PM 10 in F. chinensis and S. matsudana show the highest proximity, which may influence subsequent particle retention. S. matsudana should be generally considered to collect additional small particles. Different species and particle sizes exhibit various proximities, which should be further examined to elucidate the underlying mechanism. [ABSTRACT FROM AUTHOR]

Bulk Atmospheric Deposition (BAD), Wet Atmospheric Deposition (WAD) and Dry Atmospheric Deposition (DAD) were all measured within an urban residential area in Nantes (France) over a 9-month period (27 February - 10 December 2014). The objectives of this study were to compare 2 methods for measuring dry and wet atmospheric depositions in the urban environment (DAD and WAD: direct method; BAD and WAD: indirect one), and to characterize as well the variations and relative contributions of these depositions. Trace metals (As, Cd, Cr, Cu, Ni, Pt and V) were used to carry out these comparison and quantification. BAD was collected with two open polyethylene containers (72 × 54 × 21 cm), while WAD was collected by means of an automated rainwater collector and DAD was determined from both air measurements (recorded by an air sampler) and 7 Be deposition velocities. The comparison based on a detailed evaluation of uncertainties showed a significant difference between the direct and indirect methods. Dry and wet depositions varied widely from one month to the next. Zn and Cu were the most abundant elements in both dry and wet depositions. The mean contribution of DAD to the bulk atmospheric deposition during this 9-month study was significant for Zn, Cu and V (about 25%) as well as for Pb (approx. 60%). For this relatively unpolluted urban residential catchment, the contribution of atmospheric deposition to global load at the catchment outlet was low, between 10% and 20% for Zn, Cu, V and Pb, 25% for Cr and about 30% for Ni. For other urban sites exhibiting high atmospheric pollution however, the atmospheric contribution to the global pollution load could be much greater. An accurate and representative estimation of DAD thus proves critical. [ABSTRACT FROM AUTHOR]

The aim of this study was to improve our understanding of what controls the isotope composition of Cu, Zn and Pb in particulate matter (PM) in the urban environment and to develop these isotope systems as possible source tracers. To this end, isotope ratios (Cu, Zn and Pb) and trace element concentrations (Fe, Al, Cu, Zn, Sb, Ba, Pb, Cr, Ni and V) were determined in PM 10 collected at two road sites with contrasting traffic densities in central London, UK, during two weeks in summer 2010, and in potential sources, including non-combustion traffic emissions (tires and brakes), road furniture (road paint, manhole cover and road tarmac surface) and road dust. Iron, Ba and Sb were used as proxies for emissions derived from brake pads, and Ni, and V for emissions derived from fossil fuel oil. The isotopic composition of Pb (expressed using 206 Pb/ 207 Pb) ranged between 1.1137 and 1.1364. The isotope ratios of Cu and Zn expressed as δ 65 Cu NIST976 and δ 66 Zn Lyon ranged between −0.01‰ and +0.51‰ and between −0.21‰ and +0.33‰, respectively. We did not find significant differences in the isotope signatures in PM 10 over the two weeks sampling period and between the two sites, suggesting similar sources for each metal at both sites despite their different traffic densities. The stable isotope composition of Pb suggests significant contribution from road dust resuspension and from recycled leaded gasoline. The Cu and Zn isotope signatures of tires, brakes and road dust overlap with those of PM 10 . The correlation between the enrichments of Sb, Cu, Ba and Fe in PM 10 support the previously established hypothesis that Cu isotope ratios are controlled by non-exhaust traffic emission sources in urban environments (Ochoa Gonzalez et al., 2016). Analysis of the Zn isotope signatures in PM 10 and possible sources at the two sites suggests significant contribution from tire wear. However, temporary additional sources, likely high temperature industrial emissions, need to be invoked to explain the isotopically light Zn found in 3 out of 18 samples of PM 10 . [ABSTRACT FROM AUTHOR]

This paper introduces a new parameter to characterize the random component in temporal variability of atmospheric pollutants and proposes a simple statistical technique for its evaluation. That parameter is the net decay time (or the time scale) of the local anomalies in concentrations of atmospheric pollutants, rather than the traditionally used chemical lifetimes of total amounts of the species. Using widely available data of hourly multi-year surface trace gas pollutant concentrations we demonstrate a simplified way to estimate the net decay time with an exponential approximation of lag-correlation functions. We assessed the decay times of fluctuations in observations of eight atmospheric pollutants (SO 2 , NO, NO 2 , NO y , O 3 , CO, NH 3 , and HNO 3 ) at two urban sites and one cleaner rural site in the Eastern US. The time scales of temporal fluctuations (net decay times) vary from about one hour to slightly more than one day. These scales are generally much shorter in urban environments than in remote regions. We also compared day- and night-time observations in warm and cold seasons. At night in the cold season, time scales of fluctuations in atmospheric pollutants are usually the longest. Such estimates should be useful to air quality prediction, public health, and satellite remote sensing research communities. [ABSTRACT FROM AUTHOR]

A two-week measurement campaign by a mobile laboratory van was performed in urban environments in the Helsinki metropolitan area, Finland, in winter 2012, to obtain a comprehensive view on aerosol properties and sources. The abundances and physico-chemical properties of particles varied strongly in time and space, depending on the main sources of aerosols. Four major types of winter aerosol were recognized: 1) clean background aerosol with low particle number (Ntot) and lung deposited surface area (LDSA) concentrations due to marine air flows from the Atlantic Ocean; 2) long-range transported (LRT) pollution aerosol due to air flows from eastern Europe where the particles were characterized by the high contribution of oxygenated organic aerosol (OOA) and inorganic species, particularly sulphate, but low BC contribution, and their size distribution possessed an additional accumulation mode; 3) fresh smoke plumes from residential wood combustion in suburban small houses, these particles were characterized by high biomass burning organic aerosol (BBOA) and black carbon (BC) concentrations; and 4) fresh emissions from traffic while driving on busy streets in the city centre and on the highways during morning rush hours. This aerosol was characterized by high concentration of Ntot, LDSA, small particles in the nucleation mode, as well as high hydrocarbon-like organic aerosol (HOA) and BC concentrations. In general, secondary components (OOA, NO 3 , NH 4 , and SO 4 ) dominated the PM 1 chemical composition during the LRT episode accounting for 70–80% of the PM 1 mass, whereas fresh primary emissions (BC, HOA and BBOA) dominated the local traffic and wood burning emissions. The major individual particle types observed with electron microscopy analysis (TEM/EDX) were mainly related to residential wood combustion (K/S/C-rich, soot, other C-rich particles), traffic (soot, Si/Al-rich, Fe-rich), heavy fuel oil combustion in heat plants or ships (S with V-Ni-Fe), LRT pollutants (S/C-rich secondary particles) and sea salt (Na/Cl-rich). Tar balls from wood combustion were also observed, especially (∼5%) during the LRT pollution episode. [ABSTRACT FROM AUTHOR]

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μ m (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment. [ABSTRACT FROM AUTHOR]

The concentrations of As, Cd, Co, Cu, Fe, Mn, Ni, Pb, V and Zn were measured by ICP-OES in samples of bark of the holm oak ( Quercus ilex L.) collected from trees in different urban environments (residential and mixed residential/industrial). The use of tree bark as a bioindicator makes it easy to create maps that can provide detailed data on the levels and on the spatial distribution of each trace element. For most of the elements considered (As, Co, Fe, Mn, Ni, V and Zn), the concentrations in the industrial sites are about twice (from 1.9 to 2.8 times higher) of those in the residential area. Arsenic, Fe and Zn show the highest concentrations near a steel plant (operational until 2005), but for the other elements it is not possible to identify any localized source, as evident from the maps. In areas where urban pollution is summed up by the impact of industrial activities, the population is exposed to significantly higher amounts of some metals than people living in residential areas. [ABSTRACT FROM AUTHOR]

There is a lack of knowledge regarding in-vehicle concentrations of nitrogen dioxide (NO 2 ) during transit through road tunnels in urban environments. Furthermore, previous studies have tended to involve a single vehicle and the range of in-vehicle NO 2 concentrations that vehicle occupants may be exposed to is not well defined. This study describes simultaneous measurements of in-vehicle and outside-vehicle NO 2 concentrations on a route through Sydney, Australia that included several major tunnels, minor tunnels and busy surface roads. Tests were conducted on nine passenger vehicles to assess how vehicle characteristics and ventilation settings affected in-vehicle NO 2 concentrations and the in-vehicle-to-outside vehicle (I/O) concentration ratio. NO 2 was measured directly using a cavity attenuated phase shift (CAPS) technique that gave a high temporal and spatial resolution. In the major tunnels, transit-average in-vehicle NO 2 concentrations were lower than outside-vehicle concentrations for all vehicles with cabin air recirculation either on or off. However, markedly lower I/O ratios were obtained with recirculation on (0.08–0.36), suggesting that vehicle occupants can significantly lower their exposure to NO 2 in tunnels by switching recirculation on. The highest mean I/O ratios for NO 2 were measured in older vehicles (0.35–0.36), which is attributed to older vehicles having higher air exchange rates. The results from this study can be used to inform the design and operation of future road tunnels and modelling of personal exposure to NO 2 . [ABSTRACT FROM AUTHOR]

GEOS-Chem, a chemical transport model, provides time-space continuous estimates of atmospheric pollutants including PM 2.5 and its major components, but model predictions are not highly correlated with ground monitoring data. In addition, its spatial resolution is usually too coarse to characterize the spatial pattern in pollutant concentrations in urban environments. Our objective was to calibrate daily GEOS-Chem simulations using ground monitoring data and incorporating meteorological variables, land-use terms and spatial-temporal lagged terms. Major PM 2.5 components of our interest include sulfate, nitrate, organic carbon, elemental carbon, ammonium, sea salt and dust. We used a backward propagation neural network to calibrate GEOS-Chem predictions with a spatial resolution of 0.500° × 0.667° using monitoring data collected during the period from 2001 to 2010 for the Northeastern United States. Subsequently, we made predictions at 1 km × 1 km grid cells. We determined the accuracy of the spatial-temporal predictions using ten-fold cross-validation and “leave-one-day-out” cross-validation techniques. We found a high total R 2 for PM 2.5 mass (all data R 2 0.85, yearly values: 0.80–0.88) and PM 2.5 components (R 2 for individual components were around 0.70–0.80). Our model makes it possible to assess spatially- and temporally-resolved short- and long-term exposures to PM 2.5 mass and components for epidemiological studies. [ABSTRACT FROM AUTHOR]

A mobile laboratory unit (MOBILAB) with on-board instrumentation (Scanning Mobility Particle Sizer, SMPS; Ambient NOx analyzer) was used to measure size-resolved particle number concentrations (PNCs) of quasi-ultrafine particles (UFPs, 9–372 nm), along with NOx, in road microenvironments. On-road measurements were carried out in and around a large Greek urban agglomeration, the Thessaloniki Metropolitan Area (TMA). Two 2-week measurement campaigns were conducted during the warm period of 2011 and the cold period of 2012. During each sampling campaign, MOBILAB was driven through a 5-day inner-city route and a second 5-day external route covering in total a wide range of districts (urban, urban background, industrial and residential), and road types (major and minor urban roads, freeways, arterial and interurban roads). All routes were conducted during working days, in morning and in afternoon hours under real-world traffic conditions. Spatial classification of MOBILAB measurements involved the assignment of measurement points to location bins defined by the aspect ratio of adjacent urban street canyons (USCs). Source apportionment was further carried out, by applying Positive Matrix Factorization (PMF) to particle size distribution data. Apportioned PMF factors were interpreted, by employing a two-step methodology, which involved (a) statistical association of PMF factor contributions with 12 h air-mass back-trajectories ending at the TMA during MOBILAB measurements, and (b) Multiple Linear Regression (MLR) using PMF factor contributions as the dependent variables, while relative humidity, solar radiation flux, and vehicle speed were used as the independent variables. The applied data analysis showed that low-speed cruise and high-load engine operation modes are the two dominant sources of UFPs in most of the road microenvironments in the TMA, with significant contributions from background photochemical processes during the warm period, explaining the reversed seasonal variation of UFP concentrations, compared to those observed in cities across Northern Europe. It was also demonstrated that town planning exerts a profound effect on the mitigation of traffic emissions. [ABSTRACT FROM AUTHOR]

Urbanized valleys are particularly vulnerable to particulate air pollution during the winter, when ground-based stable layers or cold-air pools persist over the valley floor. We examine whether the temporal variability of PM 10 concentration in the section of the Arve River Valley between Cluses and Servoz in the French Alps can be explained by the temporal variability of the valley heat deficit, a bulk measure of atmospheric stability within the valley. We do this on the basis of temperature profile and ground-based PM 10 concentration data collected during wintertime with a temporal resolution of 1 h or finer, as part of the Passy-2015 field campaign conducted around Passy in this section of valley. The valley heat deficit was highly correlated with PM 10 concentration on a daily time scale. The hourly variability of PM 10 concentrations was more complex and cannot be explained solely by the hourly variability of the valley heat deficit. The interplay of the diurnal cycles of emissions and local dynamics is demonstrated and a drainage mechanism for observed nocturnal dilution of near-surface PM 10 concentrations is proposed. [ABSTRACT FROM AUTHOR]

Long-range transportation of air pollutants from industrial and urban environments can significantly affect the quality of the air in remote regions. In this study, we investigate episodes of particulate transport (PT) from Eurasia to the remote environment of Northeastern Mediterranean, i.e., the region of the North Aegean Sea (NAS), during the summer when the synoptic Etesian wind conditions prevail. A temporary monitoring station was set up at a remote region on the island of Lemnos, which is located at the center of the NAS at a distance of ca. 250 km from the continent. Measurements of the aerosol particle size distributions, the total number and mass concentrations, as well as the chemical composition of the particles were conducted from 27 August to 10 September 2011. During this period, the wind speeds were high (typically higher than 5.5 ms −1 ) with a direction that mostly ranged from north to northeast (68% frequency). Winds having direction ranging from northwest to south were less frequent (7% frequency), while the rest of the cases were characterized as calm (i.e., wind speeds less than 1 m s −1 ; 25% frequency). Seven PT episodes were observed during the sampling period. When the wind direction was northeastern we observed up to a six-fold increase in particle number concentration of nucleation mode, while the peak size of the particles decreased from 100 to 20 nm. Interestingly, the nucleation-mode particles grew from ca. 15 to 25 nm with rates of ca. 9.0 nm h −1 , which are representative of polluted areas. Analysis of the chemical composition of particle samples collected on filters during the PT episodes shows that the concentration of sulfates and nitrates increased by ca. 60%, while the OC/EC ratio increased by ca. 22% compared to the rest of the sampling period. Back-trajectory analysis for the period during the episodes shows that the air masses arriving at the station passed over the greater Istanbul area and the Black Sea 9 to 12 h before reaching our station. These observations provide strong evidence that the air quality in the remote region of the NAS can be significantly affected by the transportation of particulate pollution during the summer period, having potentially important effects upon human health and climate in the region. [ABSTRACT FROM AUTHOR]

Highly resolved pollution maps are a valuable resource for many issues related to air quality including exposure modelling and urban planning. We present an approach for their generation based on data from a mobile sensor network and statistical modelling. An extensive record of particle number concentrations (PNCs) spanning more than 1.5 years was compiled by the tram-based OpenSense mobile sensor network in the City of Zurich. The sensor network consists of 10 sensor nodes installed on the roof of trams operating on different services according to their regular operation schedules. We developed a statistical modelling approach based on Generalized Additive models (GAMs) utilizing the PNC data obtained along the tram tracks as well as georeferenced information as predictor variables. Our approach includes a variable selection algorithm to ensure that individual models rely on the optimal set of predictor variables. Our models have high temporal and spatial resolutions of 30 min and 10 m by 10 m, respectively, and allow the spatial prediction of PNC in the municipal area of Zurich. We applied our approach to PNC data from two dedicated time periods: July–Sept. 2013 and Dec. 2013–Feb. 2014. The models strongly rely on traffic related predictor variables (vehicle counts) and, due to the hilly topography of Zurich, on elevation. We assessed the model performance by leave-one-out cross-validation and by comparing PNC predictions to measurements at fixed reference sites and to PNC measurements obtained by pedestrians. Model predictions reproduce well the main features of the PNC field in environment types similar to those passed by individual trams. Model performance is worse at elevated background locations probably due to the weak coverage of similar spots by the tram network. We end the paper by outlining a route finding algorithm which utilizes the highly resolved PNC maps providing the exposure minimal route for cyclists. [ABSTRACT FROM AUTHOR]

Indian cities are the hotspots of human population with population densities as high as 66,135 persons/sq km and are hence emerging as one of the significant CO 2 emitters on par with cities of the developed nations. In this regard, quantification of Indian urban CO 2 emissions at a finer resolution of space and time is becoming a crucial prerequisite for the implementation of India's National Action Plan on Climate Change. This paper presents the quantification of CO 2 emissions of Chennai city at a fine spatial (1 km × 1 km) and temporal (diurnal, weekday-weekend, seasonal) resolution. In the present study, data sets of residential, industrial, commercial, traffic and waste management sectors were considered and bottom up approach was used for quantifying the CO 2 emissions. Results indicated that the total annual CO 2 emission of Chennai city was 2.12 Mt. Domestic (45.7%) and transportation (29.7%) sectors were identified as the larger CO 2 emitters followed by power generation sector (17.4%). The average grid wise anthropogenic CO 2 emission was found to be 0.01 ± 0.02 Mt/yr with peak CO 2 emissions observed from the grids with point sources and minimal CO 2 emissions from the grids overlaying on the urban forest of the city. The average per capita CO 2 emission of Chennai was found to be 0.45 tons/yr which is less than the national per capita CO 2 emission of 1.6 tons/year. The estimated CO 2 fluxes due to anthropogenic emissions were in the range of 0–8.5 × 10 −6 kg/m 2 /s with an average flux of 0.36 × 10 −6 kg/m 2 /s. CO 2 emissions during weekdays and weekends in summer season (5862.6 and 6235.58 tons/day) were slightly higher than in winter season (5540.8 and 5929.6 tons/day). Grids overlaying on commercial and residential zones showed higher CO 2 emissions during morning (07:00–10:00 AM) and evening rush hours (07:00–09:00 PM) of a day. [ABSTRACT FROM AUTHOR]

A numerical approach is proposed to predict the short time dispersion of odors in the urban environment. The model is based on (i) a three dimensional computational domain describing the urban topography at fine spatial scale (1 m) and on (ii) highly time resolved (1 min frequency) meteorological data used as inflow conditions. The time dependent, three dimensional wind velocity field is reconstructed in the Eulerian framework using a fast response finite volume solver of Navier–Stokes equations. Odor dispersion is calculated using a Lagrangian approach. An application of the model to the historic city of Verona (Italy) is presented. Results confirm that this type of odor dispersion simulations can be used (i) to assess the impact of odor emissions in urban areas and (ii) to evaluate the potential mitigation produced by odor abatement systems. [ABSTRACT FROM AUTHOR]

During late autumn and winter, the western Mediterranean basin is often affected by severe pollution episodes (SPE) caused by stagnant weather conditions that produce a notable increase in particulate matter (PM) levels. The main objective of the present study is to evaluate the impact of these episodes on the variability of PM 1 concentrations at an urban and a high mountain station in the western Mediterranean. At the urban site, SPEs caused increases in PM 1 levels of up to 20 μg m −3 at 20:00–21:00 UTC due to a decrease in the mixing layer depth during the evening rush hour. In contrast, the highest increments at the high mountain station (∼12 μg m −3 ) were observed around midday. Since there are little anthropogenic emissions in the surroundings of the mountain station, this was most likely the result of aerosol transport from coastal urban areas and photochemical formation of secondary particles during transport. The transport of air pollutants through a complex orography occurs under specific weather conditions. [ABSTRACT FROM AUTHOR]

Indian cities feature high human population density, heterogeneous traffic, mixed land-use patterns and mostly tropical meteorological conditions. Characteristics of ambient CO 2 concentrations under these distinctive features are very specific and the related studies are limited. This paper presents the characteristics of ground level CO 2 concentrations at three contrasting land uses (residential, commercial and industrial) in a tropical urban area of India. The CO 2 concentrations were monitored in Chennai city for 31 days at each land use during June–September, 2013. Emissions of CO 2 from all the major anthropogenic sources present at the three study sites were also quantified. Results indicated that the daily average CO 2 concentrations were high at commercial (467 ± 35.15 ppm) and industrial (464 ± 31.68 ppm) sites than at residential site (448 ± 33.45 ppm). The quantified CO 2 emissions were also showed high levels at commercial (1190 tons/day) and industrial sites (8886 tons/day) than at residential site (90 tons/day). On a diurnal scale, CO 2 concentrations were low during afternoons and high during the late evenings and early morning hours at all the three types of land use sites. At the urban residential site, the domestic sector had a strong impact on the day time CO 2 concentrations, while soil and plant respiration phenomena had a greater control over the night time CO 2 concentrations. Further, the CO 2 concentrations were high during the stagnation and stable meteorological conditions than the ventilation and unstable conditions. [ABSTRACT FROM AUTHOR]

To investigate chemical profiles and formation mechanisms of aerosol particles in winter haze events, daily PM 2.5 and TSP, 5-min BC, and 15-min trace gases (SO 2 , NO 2 , and O 3 ) were measured continuously during Dec. 1–31, 2012 in Xi'an. Chemical analysis was also conducted for nine water-soluble inorganic ions (Na + , NH 4 + , K + , Mg 2+ , Ca 2+ , F − , Cl − , NO 3 − , and SO 4 2 − ), organic carbon (OC), elemental carbon (EC), and eight carbon fractions (OC1, OC2, OC3, OC4, EC1, EC2, EC3, and OP) in both PM 2.5 and TSP samples. Higher levels of TSP, PM 2.5 , BC, SO 2 , and NO 2 , and lower levels of O 3 were observed during haze periods in comparison with non-haze days. The sum of the major secondary ionic species ( NH 4 + , NO 3 − , and SO 4 2 − ) in PM 2.5 or TSP during haze periods was about 3 times of that during non-haze days. Ion balance calculations showed that PM 2.5 samples were acidic during haze periods and were close to neutral during non-haze days. The mean carbon levels were 52.9 μg m −3 and 82.1 μg m −3 in PM 2.5 and TSP, respectively, during haze events, which were ∼1.5 times of those during non-haze days. The diurnal variations of BC during non-haze days showed a bimodal distribution with two peaks coincided with traffic rush hours. This was not the case during haze periods, which exhibited a relatively smooth pattern but with high concentration levels, providing evidence of particle accumulation. The ratios of SO 4 2 − /EC, NO 3 − /EC, and NH 4 + /EC sharply increased during haze periods, indicating the important pathway of secondary inorganic species formation through aqueous-phase transformation under high relative humidity condition. This study also highlights that wintertime secondary organic carbon (SOC) formation can be an important contributor to carbonaceous aerosol, especially during haze periods. [ABSTRACT FROM AUTHOR]

Inorganic ionic constituents (Na + , NH 4 + , K + , Mg 2+ , Ca 2+ , Cl − , NO 3 − and SO 4 2− ) of PM 2.5 and associated trace gases (NH 3 , HNO 3 and HCl) were measured simultaneously by Ambient Ion Monitor – Ion Chromatograph (AIM-IC) system with a time resolution of one hour at an urban location in semi-arid region of western India during summer and winter. The average NH 3 , HNO 3 and HCl concentrations were 11.6 ± 5.0, 2.9 ± 0.8 and 0.15 μg m −3 , respectively, during winter. During summer, NH 3 and HNO 3 concentrations were of similar magnitude, whereas HCl concentration was less than ∼0.03 μg m −3 . NH 3 concentration exhibited a distinct diurnal variation during both seasons. However, HNO 3 did not show a specific diurnal trend during the observation period in both seasons. The data obtained were used to study gas-aerosol equilibrium characteristics using a thermodynamic equilibrium model, ISORROPIA II. The results suggest that NH 3 exists in equilibrium between measured fine-mode particle and gas phase with a systematic bias of ∼14%, whereas HCl and HNO 3 deviate significantly from the modelled data. These observations have implications on thermodynamic equilibrium assumptions used for estimating various aerosol parameters such as liquid water content, pH, etc., thus causing significant bias in chemical transport model results over the study region. [ABSTRACT FROM AUTHOR]

Distributed power generation, located close to consumers, plays an important role in the current and future power systems. However, its near-source impacts in complex urban environments are not well understood. In this paper, we focused on diesel backup generators that participate in demand response (DR) programs. We first improved the micro-environmental air quality simulations by employing a meteorology processor, AERMET, to generate site-specific boundary layer parameters for the Large Eddy Simulation (LES) modeling. The modeling structure was then incorporated into the CTAG model to evaluate the environmental impacts of diesel backup generators in near-source microenvironments. We found that the presence of either tall upwind or downwind building can deteriorate the air quality in the near-stack street canyons, largely due to the recirculation zones generated by the tall buildings, reducing the near-stack dispersion. Decreasing exhaust momentum ratio (stack exit velocity/ambient wind velocity) draws more exhaust into the recirculation zone, and reduces the effective stack height, which results in elevated near-ground concentrations inside downwind street canyons. The near-ground PM 2.5 concentration for the worst scenarios could well exceed 100 μg m −3 , posing potential health risk to people living and working nearby. In general, older diesel backup generators (i.e., Tier 1, 2 or older) without the up-to-date emission control may significantly increase the pollutant concentration in the near-source street canyons if participating in DR programs. Even generators that comply with Tier-4 standards could lead to PM hotspots if their stacks are next to tall buildings. Our study implies that the siting of diesel backup generators stacks should consider not only the interactions of fresh air intake and exhaust outlet for the building housing the backup generators, but also the dispersion of exhaust plumes in the surrounding environment. [ABSTRACT FROM AUTHOR]

Quantification of disproportionate contribution made by signalised traffic intersections (TIs) to overall daily commuting exposure is important but barely known. We carried out mobile measurements in a car for size–resolved particle number concentrations (PNCs) in the 5–560 nm range under five different ventilation settings on a 6 km long busy round route with 10 TIs. These ventilation settings were windows fully open and both outdoor air intake from fan and heating off (Set 1 ), windows closed, fan 25% on and heating 50% on (Set 2 ), windows closed, fan 100% on and heating off (Set 3 ), windows closed, fan off and heating 100% on (Set 4 ), and windows closed, fan and heating off (Set 5 ). Measurements were taken sequentially inside and outside the car cabin at 10 Hz sampling rate using a solenoid switching system in conjunction with a fast response differential mobility spectrometer (DMS50). The objectives were to: (i) identify traffic conditions under which TIs becomes hot–spots of PNCs, (ii) assess the effect of ventilation settings in free–flow and delay conditions (waiting time at a TI when traffic signal is red) on in–cabin PNCs with respect to on–road PNCs at TIs, (iii) deriving the relationship between the PNCs and change in driving speed during delay time at the TIs, and (iv) quantify the contribution of exposure at TIs with respect to overall commuting exposure. Congested TIs were found to become hot–spots when vehicle accelerate from idling conditions. In–cabin peak PNCs followed similar temporal trend as for on–road peak PNCs. Reduction in in–cabin PNC with respect to outside PNC was highest (70%) during free–flow traffic conditions when both fan drawing outdoor air into the cabin and heating was switched off. Such a reduction in in–cabin PNCs at TIs was highest (88%) with respect to outside PNC during delay conditions when fan was drawing outside air at 25% on and heating was 50% on settings. PNCs and change in driving speed showed an exponential–fit relationship during the delay events at TIs. Short–term exposure for ∼2% of total commuting time in car corresponded to ∼25% of total respiratory doses. This study highlights a need for more studies covering diverse traffic and geographical conditions in urban environments so that the disparate contribution of exposure at TIs can be quantified. [ABSTRACT FROM AUTHOR]

Air quality models which are nowadays used for a wide range of scopes (i.e. assessment, forecast, planning) see their intrinsic complexity progressively increasing as better knowledge of the atmospheric chemistry processes is gained. As a result of this increased complexity potential non-linearities are implicitly and/or explicitly incorporated in the system. These non-linearities represent a key and challenging aspect of air quality modeling, especially to assess the robustness of the model responses. In this work the importance of non-linear effects in air quality modeling is quantified, especially as a function of time averaging. A methodology is proposed to decompose the concentration change resulting from an emission reduction over a given domain into its linear and non-linear contributions for each precursor as well as in the contribution resulting from the interactions among precursors. Simulations with the LOTOS-EUROS model have been performed by TNO over three regional geographical areas in Europe for this analysis. In all three regions the non-linear effects for PM 10 and PM 2.5 are shown to be relatively minor for yearly and monthly averages whereas they become significant for daily average values. For Ozone non-linearities become important already for monthly averages in some regions. An approach which explicitly deals with monthly variations seems therefore more appropriate for O 3 . In general non-linearities are more important at locations where concentrations are the lowest, i.e. at urban locations for O 3 and at rural locations for PM 10 and PM 2.5 . Finally the impact of spatial resolution (tested by comparing coarse and fine resolution simulations) on the degree of non-linearity has been shown to be minor as well. The conclusions developed here are model dependent and runs should be repeated with the particular model of interest but the proposed methodology allows with a limited number of runs to identify where efforts should be focused in order to include the relevant terms into a simplified surrogate model for integrated assessment purposes. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) varies in chemical composition and mass concentration based on location, source, and particle size. This study sought to evaluate the in vitro and in vivo toxicity of coarse (PM 10-2.5 ) and fine (PM 2.5 ) PM samples collected at 5 diverse sites within California. Coarse and fine PM samples were collected simultaneously at 2 rural and 3 urban sites within California during the summer. A human pulmonary microvascular endothelial cell line (HPMEC-ST1.6R) was exposed to PM suspensions (50 μg/mL) and analyzed for reactive oxygen species (ROS) after 5 h of treatment. In addition, FVB/N mice were exposed by oropharyngeal aspiration to 50 μg PM, and lavage fluid was collected 24 h post-exposure and analyzed for total protein and %PMNs. Correlations between trace metal concentrations, endotoxin, and biological endpoints were calculated, and the effect of particle size range, locale (urban vs. rural), and location was determined. Absolute principal factor analysis was used to identify pollution sources of PM from elemental tracers of those sources. Ambient PM elicited an ROS and pro-inflammatory-related response in the cell and mouse models, respectively. These responses were dependent on particle size, locale, and location. Trace elements associated with soil and traffic markers were most strongly linked to the adverse effects in vitro and in vivo . Particle size, location, source, and composition of PM collected at 5 locations in California affected the ROS response in human pulmonary endothelial cells and the inflammatory response in mice. [ABSTRACT FROM AUTHOR]

In order to investigate relationships between outdoor air pollution and concentrations indoors, a novel design of experiment has been conducted at two sites, one heavily trafficked and the other residential. The novel design aspect involves the introduction of air directly to the centre of an unoccupied room by use of a fan and duct giving a controlled air exchange rate and allowing an evaluation of particle losses purely due to uptake on indoor surfaces without the losses during penetration of the building envelope which affect most measurement programmes. The rooms were unoccupied and free of indoor sources, and consequently reductions in particle concentration were due to deposition processes within the room alone. Measurements were made of indoor and outdoor concentrations of PM 2.5 , major chemical components and particle number size distributions. Despite the absence of penetration losses, indoor to outdoor ratios were very similar to those in other studies showing that deposition to indoor surfaces is likely to be the major loss process for indoor air. The results demonstrated a dramatic loss of nitrate in the indoor atmosphere as well as a selective loss of particles in the size range below 50 nm, in comparison to coarser particles. Depletion of indoor particles was greater during a period of cold weather with higher outdoor concentrations probably due to an enhancement of semi-volatile materials in the outdoor particulate matter. Indoor/outdoor ratios for PM 2.5 were generally higher at the trafficked site than the residential site, but for particle number were generally lower, reflecting the different chemical composition and size distributions of particles at the two sites. [ABSTRACT FROM AUTHOR]

This study is focused in the evolution of NO, NO 2 , SO 2 , O 3 and PM 10 concentrations, from 2000 to 2012, at urban, suburban and regional observatories in the Balearic Islands (Spain), an insular region in the Western Mediterranean. At urban and suburban areas, daily patterns of most pollutants are strongly linked to land-traffic emissions, being the regional background less influenced. SO 2 variations, however, are mostly driven by the impact of other sources different from road traffic, including shipping emissions and power generation. Urban NO x , SO 2 and PM 10 concentrations exhibit a common weekly pattern, with a very slight accumulation during the weekdays and sharp decreases (15–39%) on weekends. Our long-term database displays clear decreasing NO and NO 2 concentrations from 2000 onwards, prominent in the urban environment (−1.1 μg/m 3 year), and moderate in suburban and regional areas (up to −0.3 μg/m 3 year). At urban sites, O 3 behaviour (+1.0 μg/m 3 year) is opposite to that of NO, one of its main depletion agents. A moderate O 3 increasing trend (+0.5 μg/m 3 year) is detected at regional background areas, whereas a modest decreasing trend occurred at the suburban background (−0.4 μg/m 3 year), probably caused by enhanced vehicular emissions over these areas induced by urban planning and mobility policies. Finally, substantial PM 10 drops are obvious, −0.7 μg/m 3 year at urban and suburban areas, and −0.5 μg/m 3 year in the regional background. Our results link the sharpest declines to air masses from western to northern sectors, pointing to effective pollution abatement strategies at a European scale. Some additional benefits are connected to the implementation of diverse local policies. The effect of the North Atlantic Oscillation (NAO) was investigated. Negative NAO phases were related to additional air quality benefits, while positive phases mostly contributed to air degradation. [ABSTRACT FROM AUTHOR]

All around the world, many studies and experimental results have assessed elevated concentrations of Particulate Matter (PM) in underground metro systems, with non-negligible implications for human health due to protracted exposure to fine particles. Starting from this consideration, an intensive particulate sampling campaign was carried out in January 2014 measuring the PM concentrations in the Naples (Italy) Metro Line 1, both at station platforms and inside trains. Naples Metro Line 1 is about 18 km long, with 17 stations (3 ground-level and 14 below-ground ones). Experimental results show that the average PM 10 concentrations measured in the underground station platforms range between 172 and 262 μg/m 3 whilst the average PM 2.5 concentrations range between 45 and 60 μg/m 3 . By contrast, in ground-level stations no significant difference between stations platforms and urban environment measurements was observed. Furthermore, a direct correlation between trains passage and PM concentrations was observed, with an increase up to 42% above the average value. This correlation is possibly caused by the re-suspension of the particles due to the turbulence induced by trains. The main original finding was the real-time estimations of PM levels inside the trains travelling both in ground-level and underground sections of Line 1. The results show that high concentrations of both PM 10 (average values between 58 μg/m 3 and 138 μg/m 3 ) and PM 2.5 (average values between 18 μg/m 3 and 36 μg/m 3 ) were also measured inside trains. Furthermore, measurements show that windows left open on trains caused the increase in PM concentrations inside trains in the underground section, while in the ground-level section the clean air entering the trains produced an environmental “washing effect”. Finally, it was estimated that every passenger spends on average about 70 min per day exposed to high levels of PM. [ABSTRACT FROM AUTHOR]

Long-term measurement of speciated Hg concentrations is the first step toward identifying the seasonal and spatial characteristics of Hg concentrations; however, atmospheric Hg research is scarce in Korea. In this study, total gaseous mercury (TGM), gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) were measured in urban (Seoul) and rural (Chuncheon) areas over a more than 3 year period in order to improve the understanding of speciated Hg transport. The mean concentrations of TGM, GOM and PBM were 3.72 ± 2.96 (0.19-149.84) ng m-3, 11.3 ± 9.5 (0.9-57.3) pg m-3, and 13.4 ± 12.0 (2.1-64.3) pg m-3 at the Seoul site and 2.12 ± 1.47 (0.26-10.75) ng m-3, 2.7 ± 2.7 (0.1-16.9) pg m-3, and 3.7 ± 5.7 (0.1-30.0) pg m-3 in Chuncheon. Both long-range transport and local sources caused high TGM concentration events, while local coal combustion was a main cause of enhancing the GOM and PBM concentrations in Seoul. However, there was no correlation between the pollutants emitted from coal combustion and the speciated Hg concentration in Chuncheon, indicating that other mechanisms were involved in the Hg increase. We found a positive correlation between the GOM and the O3 concentrations and a negative correlation between the GEM and the GOM concentrations, especially on foggy days, suggesting that the oxidation of GEM was an important source for GOM in Chuncheon. In addition, the ratio of PBM/GOM was inversely proportional to the atmospheric temperature and directly proportional to the relative humidity, which suggests that the in-situ formation of PBM through gas-particle partitioning of GOM was important in rural areas. [ABSTRACT FROM AUTHOR]

The concentrations of many harmful metals in air have been continuously decreasing around the world especially in North America and Western Europe, although deviations from such trend have been observed elsewhere such as East Asia. To help understand spatiotemporal factors governing the environmental behavior of hazardous metals, the concentrations of copper (Cu) in total suspended particulate (TSP) fractions were analyzed in the seven major cities in South Korea over a two decadal period (1991 through 2012). Unlike other metal species, there was no distinctive seasonal trend (e.g., spring/winter maximum and summer minimum) in the Cu levels in most South Korean cities. The long-term trend of Cu, if assessed by its annual mean values, recorded two contrasting trends for each decade: the earlier period (from 1991 to early 2000) is characterized by high variabilities with a maximum concentration of 243 ng m-3 (in 2003), while the later period showed an appreciable (several-fold) reduction to the latest (2012) available concentration level of 35.7 ng m-3. As such, the present Cu levels in Korea should approach those commonly seen in moderately clean urban environments elsewhere. The overall results suggest that South Korean regulatory efforts to control particulate matter (PM) emissions have greatly influenced the present Cu levels consistent with the observed temporal trends of airborne PM. [ABSTRACT FROM AUTHOR]

Bulk aerosol samples collected during 2010 and 2011 at one receptor site in Córdoba City, Argentina, have been quantitatively analyzed to determine aerosol elemental composition by using SR-XRF. A receptor model analysis has been applied to ambient PM2.5 measurements. Four sources have been identified being their contributions: traffic: (13 ± 2) μg m−3, /combustion processes, including biomass burning: (15 ± 1) μg m−3, mineral dust: (7 ± 2) μg m−3 and industry: (8 ± 1) μg m−3. Source identification was carried out by inspection of key species in source profiles, seasonality of source contributions, comparison with literature data and the knowledge of the city; for the biomass burning contribution the MODIS burned area daily product was used to confirm wildfire events along the year. In addition, from May to August 2011, aerosols were collected in two additional size fractions (PM0.25–0.5, PM0.5–1) to investigate the toxic metal contributions to the finer fractions. An important result of this work is that toxic metals make an important contribution to the finest (PM0.25–0.5) size fraction. The results of the present analysis can help to demonstrate to local and national authorities the urgent need to carry out emission inventories, to implement air quality monitoring systems and to set regulations for PM2.5. [ABSTRACT FROM AUTHOR]

Abstract: Ultrafine particles (UFP) and black carbon (BC) concentrations show a highly dynamic micro-variability in urban area. Mobile monitoring using a bicycle platform (354 runs in 1 month) was adopted in this study to characterize the micro-variability in relation to traffic intensity, street topology and meteorological conditions. For UFP and BC a positive relationship was demonstrated between pollutant concentration and traffic intensity. In addition, the distance to the traffic and the street topology were the dominant factors influencing the UFP and BC concentrations. A high variability between streets and even within streets was observed, and also between days and hour of the day. The exposure of cyclists in urban environments is strongly linked to the spatio-temporal variability of the pollutant concentrations. Fixed-track comparisons through time revealed significant differences in exposure between days and hour of the day, but even more importantly due to the occurrence of peak concentrations along the cycling track. Peaks were mainly found near busy cross-roads and in tunnels. [Copyright &y& Elsevier]