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The Printed Optical Particle Spectrometer (POPS) is an advanced and small low-cost, light-weight, and high-sensitivity optical particle counter (OPC), particularly designed for deployed on unpiloted aerial vehicles (UAVs) and balloon sondes. We report the performance of the POPS against a reference scanning mobility particle sizer (SMPS) and an airborne passive cavity aerosol spectrometer probe (PCASP) while the POPS is operated on the ground and also while operated on a quadcopter drone, a DJI Matrice 200 V2. This is the first such documented test of the performance of a POPS instrument on a UAV. We investigate the root mean square difference (RMSD) and mean absolute difference (MAD) in particle number concentrations (PNCs) when operating on the ground and on the Matrice 200. When windspeeds are less than 2.6 m/s, we find only modest differences in the RMSDs and MADs of 2.4 % and 2.3 % respectively when operating on the ground, and to 5 % and 3 % when operating at 10m altitude. When windspeeds are greater than 2.6 m/s but less than 7.7 m/s the RMSDs and MADs increase to 10.2 % and 7.8 % respectively when operating on the ground, and 26.2 % and 19.1 %, respectively when operating at 10m altitude. No statistical difference in PNCs was detected when operating on the UAV in either ascent or descent. We also find size distributions of aerosols in the accumulation mode (here defined by diameter, d, where 0.1 ≤ d ≤ 1 µm) are relatively consistent between measurements at the surface and measurements at 10m altitude with RMSD and MAD of less than 21.6 % and 15.7 %, respectively. However, the differences between coarse mode (here defined by d > 1 µm) are universally larger than those measured at the surface with a RMSD and MAD approaching 49.5 % and 40.4 %. Our results suggest that the impact of the UAV rotors on the POPS does not unduly affect the performance of the POPS for wind speed less than 2.6 m/s, but when operating under higher wind speed of up to 7.6 m/s, larger discrepancies are noted. In addition to this, it appears that the POPS measures sub-micron aerosol particles more accurately than super-micron aerosol particles when airborne on the UAV. These measurements lay the foundations for determining the magnitude of potential errors that might be introduced into measured aerosol particle size distributions and concentrations owing to the turbulence created by the rotors on the UAV.

Environmental issues and health-benefitting design strategies have raised interest in natural and renewable building materials, resulting in an increased focus on the use of wood in built environment. The influence of wooden materials on measured and perceived indoor environment quality (IEQ) has gained attention during the past few decades, with a growing number of studies having explored the issue. This review was conducted to examine and summarise the body of research on the influence of wooden interior materials on IEQ, with an emphasis on the following themes: emissions of chemical compounds, moisture buffering of indoor air, antibacterial effects, acoustics, and psychological and physiological effects. This review found that wooden interior materials exert mainly positive or neutral effects on IEQ, such as moderating humidity fluctuations of indoor air, inducing positive feelings in occupants, and inhibiting certain bacteria. Negative effects on IEQ are limited to volatile organic compounds emitted from wood. The odour thresholds of some aldehydes and terpenes are low enough to affect the perceived IEQ. Additionally, concentrations of formaldehyde and acrolein may under certain conditions cause adverse health effects. Further studies are needed to better understand these phenomena and take advantage of the beneficial effects while hindering the unpleasant ones.

We applied data-based recurrence CFD (rCFD) to model pollutant dispersion in near-field flow configurations. In case of complex topologies, the global-domain version of rCFD fails to account for local recurrent flow features. We therefore developed a novel island-based version of rCFD, which partitions the computational domain to isolate islands of high recurrence prominence, and subsequently defines a distinct recurrence path for each of these islands. We applied island-based rCFD to pollutant dispersion for two side-by-side cubical buildings with three different gap widths in between them and a real urban environment. We showed that numerical predictions of pollutant dispersion by island-based rCFD were in excellent agreement with full CFD simulations, thus outperforming the global-domain version of rCFD. In both applications, island-based rCFD simulations ran three orders of magnitude faster than corresponding full CFD simulations. In the second application, this speed-up enabled real-time simulations on a computational grid of 10 million cells.

Many of the world’s major cities have implemented tree planting programs based on assumed environmental and social benefits of urban forests. Recent studies have increasingly tested these assumptions and provide empirical evidence for the contributions of tree planting programs, as well as their feasibility and limits, for solving or mitigating urban environmental and social issues. We propose that current evidence supports local cooling, stormwater absorption, and health benefits of urban trees for local residents. However, the potential for urban trees to appreciably mitigate greenhouse gas emissions and air pollution over a wide array of sites and environmental conditions is limited. Consequently, urban trees appear to be more promising for climate and pollutionadaptationstrategies than mitigation strategies. In large part, this is due to space constraints limiting the extent of urban tree canopies relative to the current magnitude of emissions. The most promising environmental and health impacts of urban trees are those that can be realized with well-stewarded tree planting and localized design interventions at site to municipal scales. Tree planting at these scales has documented benefits on local climate and health, which can be maximized through targeted site design followed by monitoring, adaptive management, and studies of long-term eco-evolutionary dynamics.

The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections. The authors acknowledge financial support from the Spanish Government, Grant RTI2018-354 094336-B-I00 (MCIU/AEI/FEDER, UE), the Spanish Carlos III Health Institute, COV 20/01213, and the Basque Government, Grant IT1207-19.

Highlights: • New COVID-19 data to parameterize anthropogenic aerosol properties are released for use in climate studies. • First MACv2-SP estimate of anthropogenic aerosol radiative forcing for 2020 suggests a change by +0.04 Wm−2 due to the pandemic. • Recovery scenarios for 2050 have a spread in anthropogenic aerosol forcing of −0.38 to −0.68 Wm−2 relative to pre-industrial. Abstract: The pandemic in 2020 caused an abrupt change in the emission of anthropogenic aerosols and their precursors. We estimate the associated change in the aerosol radiative forcing at the top of the atmosphere and the surface. To that end, we perform new simulations with the CMIP6 global climate model EC-Earth3. The simulations use the here newly created data for the anthropogenic aerosol optical properties and an associated effect on clouds from the simple plumes parameterization (MACv2-SP), based on revised SO2 and NH3 emission scenarios. Our results highlight the small impact of the pandemic on the global aerosol radiative forcing in 2020 compared to the CMIP6 scenario SSP2-4.5 of the order of +0.04 Wm−2, which is small compared to the natural year-to-year variability in the radiation budget. Natural variability also limits the ability to detect a meaningful regional difference in the anthropogenic aerosol radiative effects. We identify the best chances to find a significant change in radiation at the surface during cloud-free conditions for regions that were strongly polluted in the past years. The post-pandemic recovery scenarios indicate a spread in the aerosol forcing of −0.68 to −0.38 Wm−2 for 2050 relative to the pre-industrial, which translates to a difference of +0.05 to −0.25 Wm−2 compared to the 2050 baseline from SSP2-4.5. This spread falls within the present-day uncertainty in aerosol radiative forcing and the CMIP6 spread in aerosol forcing at the end of the 21st century. We release the new MACv2-SP data for studies on the climate response to the pandemic and the recovery scenarios. Our 2050 forcing estimates suggest that sustained aerosol emission reductions during the post-pandemic recovery cause a stronger climate response than in 2020, i.e., there is a delayed influence of the pandemic on climate.

Summarization: Fire constitutes a key process in the Earth system (ES), being driven by climate as well as affecting the climate by changing atmospheric composition and impacting the terrestrial carbon cycle. However, studies on the effects of fires on atmospheric composition, radiative forcing and climate have been limited to date, as the current generation of ES models (ESMs) does not include fully atmosphere–composition–vegetation coupled fires feedbacks. The aim of this work is to develop and evaluate a fully coupled fire–composition–climate ES model. For this, the INteractive Fires and Emissions algoRithm for Natural envirOnments (INFERNO) fire model is coupled to the atmosphere-only configuration of the UK's Earth System Model (UKESM1). This fire–atmosphere interaction through atmospheric chemistry and aerosols allows for fire emissions to influence radiation, clouds and generally weather, which can consequently influence the meteorological drivers of fire. Additionally, INFERNO is updated based on recent developments in the literature to improve the representation of human and/or economic factors in the anthropogenic ignition and suppression of fire. This work presents an assessment of the effects of interactive fire coupling on atmospheric composition and climate compared to the standard UKESM1 configuration that uses prescribed fire emissions. Results show a similar performance when using the fire–atmosphere coupling (the “online” version of the model) when compared to the offline UKESM1 that uses prescribed fire. The model can reproduce observed present-day global fire emissions of carbon monoxide (CO) and aerosols, despite underestimating the global average burnt area. However, at a regional scale, there is an overestimation of fire emissions over Africa due to the misrepresentation of the underlying vegetation types and an underestimation over equatorial Asia due to a lack of representation of peat fires. Despite this, comparing model results with observations of CO column mixing ratio and aerosol optical depth (AOD) show that the fire–atmosphere coupled configuration has a similar performance when compared to UKESM1. In fact, including the interactive biomass burning emissions improves the interannual CO atmospheric column variability and consequently its seasonality over the main biomass burning regions – Africa and South America. Similarly, for aerosols, the AOD results broadly agree with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Presented on: Geoscientific Model Development

Particulate matter (PM) is a crucial health risk factor for respiratory and cardiovascular diseases. The smaller size fractions, ≤2.5 μm (PM2.5; fine particles) and ≤0.1 μm (PM0.1; ultrafine particles), show the highest bioactivity but acquiring sufficient mass for in vitro and in vivo toxicological studies is challenging. We review the suitability of available instrumentation to collect the PM mass required for these assessments. Five different microenvironments representing the diverse exposure conditions in urban environments are considered in order to establish the typical PM concentrations present. The highest concentrations of PM2.5 and PM0.1 were found near traffic (i.e. roadsides and traffic intersections), followed by indoor environments, parks and behind roadside vegetation. We identify key factors to consider when selecting sampling instrumentation. These include PM concentration on-site (low concentrations increase sampling time), nature of sampling sites (e.g. indoors; noise and space will be an issue), equipment handling and power supply. Physicochemical characterisation requires micro- to milli-gram quantities of PM and it may increase according to the processing methods (e.g. digestion or sonication). Toxicological assessments of PM involve numerous mechanisms (e.g. inflammatory processes and oxidative stress) requiring significant amounts of PM to obtain accurate results. Optimising air sampling techniques are therefore important for the appropriate collection medium/filter which have innate physical properties and the potential to interact with samples. An evaluation of methods and instrumentation used for airborne virus collection concludes that samplers operating cyclone sampling techniques (using centrifugal forces) are effective in collecting airborne viruses. We highlight that predictive modelling can help to identify pollution hotspots in an urban environment for the efficient collection of PM mass. This review provides guidance to prepare and plan efficient sampling campaigns to collect sufficient PM mass for various purposes in a reasonable timeframe.

Sub-micron aerosols are a vital air pollutant to be measured because they pose health effects. These particles are quantified as particle number concentration (PN). However, PN measurements are not always available in air quality measurement stations, leading to data scarcity. In order to compensate this, PN modeling needs to be developed. This paper presents a PN modeling framework using sensitivity analysis tested on a one year aerosol measurement campaign conducted in Amman, Jordan. The method prepares a set of different combinations of all measured meteorological parameters to be descriptors of PN concentration. In this case, we resort to artificial neural networks in the forms of a feed-forward neural network (FFNN) and a time-delay neural network (TDNN) as modeling tools, and then, we attempt to find the best descriptors using all these combinations as model inputs. The best modeling tools are FFNN for daily averaged data (with R 2 = 0.77 ) and TDNN for hourly averaged data (with R 2 = 0.66 ) where the best combinations of meteorological parameters are found to be temperature, relative humidity, pressure, and wind speed. As the models follow the patterns of diurnal cycles well, the results are considered to be satisfactory. When PN measurements are not directly available or there are massive missing PN concentration data, PN models can be used to estimate PN concentration using available measured meteorological parameters.

Identifying the contributions of chemistry and transport to observed ozone pollution using regional-to-global models relies on accurate representation of ozone dry deposition. We use a recently developed configuration of the NOAA GFDL chemistry-climate model - in which the atmosphere and land are coupled through dry deposition-to investigate the influence of ozone dry deposition on ozone pollution over northern midlatitudes. In our model, deposition pathways are tied to dynamic terrestrial processes, such as photosynthesis and water cycling through the canopy and soil. Small increases in winter deposition due to more process-based representation of snow and deposition to surfaces reduce hemispheric-scale ozone throughout the lower troposphere by 5-12 ppb, improving agreement with observations relative to a simulation with the standard configuration for ozone dry deposition. Declining snow cover by the end of the 21st-century tempers the previously identified influence of rising methane on winter ozone. Dynamic dry deposition changes summer surface ozone by -4 to +7 ppb. While previous studies emphasize the importance of uptake by plant stomata, new diagnostic tracking of depositional pathways reveals a widespread impact of nonstomatal deposition on ozone pollution. Daily variability in both stomatal and nonstomatal deposition contribute to daily variability in ozone pollution. Twenty-first century changes in summer deposition result from a balance among changes in individual pathways, reflecting differing responses to both high carbon dioxide (through plant physiology versus biomass accumulation) and water availability. Our findings highlight a need for constraints on the processes driving ozone dry deposition to test representation in regional-to-global models.

Projections of future atmospheric compositionchange and its impacts on air quality and climate dependheavily on chemistry–climate models that allow us to investigatethe effects of changing emissions and meteorology.These models are imperfect as they rely on our understandingof the chemical, physical and dynamical processes governingatmospheric composition, on the approximations neededto represent these numerically, and on the limitations of theobservations required to constrain them. Model intercomparisonstudies show substantial diversity in results that reflectunderlying uncertainties, but little progress has been madein explaining the causes of this or in identifying the weaknessesin process understanding or representation that couldlead to improved models and to better scientific understanding.Global sensitivity analysis provides a valuable methodof identifying and quantifying the main causes of diversity incurrent models. For the first time, we apply Gaussian processemulation with three independent global chemistry-transportmodels to quantify the sensitivity of ozone and hydroxyl radicals(OH) to important climate-relevant variables, poorlycharacterised processes and uncertain emissions. We show aclear sensitivity of tropospheric ozone to atmospheric humidityand precursor emissions which is similar for the models,but find large differences between models for methane lifetime,highlighting substantial differences in the sensitivity ofOH to primary and secondary production. This approach allowsus to identify key areas where model improvements arerequired while providing valuable new insight into the processesdriving tropospheric composition change.

Assessments of long-term changes of air quality and global radiative forcing at a large scale heavily rely on satellite aerosol optical depth (AOD) datasets, particularly their temporal binning products. Although some attempts focusing on the validation of long-term satellite AOD have been conducted, there is still a lack of comprehensive quantification and understanding of the representativeness of satellite AOD at different temporal binning scales. Here, we evaluated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products at various temporal scales by comparing the MODIS AOD datasets from both the Terra and Aqua satellites with the entire global AErosol RObotic NETwork (AERONET) observation archive between 2000 and 2017. The uncertainty levels of the MODIS hourly and daily AOD products were similarly high, indicating that MODIS AOD retrievals could be used to represent daily aerosol conditions. The MODIS data showed the reduced quality when integrated from the daily to monthly scale, where the relative mean bias (RMB) changed from 1.09 to 1.21 for MODIS Terra and from 1.04 to 1.17 for MODIS Aqua, respectively. The limitation of valid data availability within a month appeared to be the primary reason for the increased uncertainties in the monthly binning products, and the monthly data associated uncertainties could be reduced when the number of valid AOD retrievals reached 15 times in one month. At all three temporal scales, the uncertainty levels of satellite AOD products decreased with increasing AOD values. The results of this study could provide crucial information for satellite AOD users to better understand the reliability of different temporal AOD binning products and associated uncertainties in their derived long-term trends.

Biogenic volatile organic compounds (BVOC) play an important role in global environmental chemistry and climate. In the present work, biogenic emissions from China in 2017 were estimated based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN). The effects of BVOC emissions on ozone and secondary organic aerosol (SOA) formation were investigated using the WRF-CMAQ modeling system. Three parallel scenarios were developed to assess the impact of BVOC emissions on China's ozone and SOA formation in July 2017. Biogenic emissions were estimated at 23.54 Tg/yr, with a peak in the summer and decreasing from southern to northern China. The high BVOC emissions across eastern and southwestern China increased the surface ozone levels, particularly in the BTH (Beijing-Tianjin-Hebei), SCB (Sichuan Basin), YRD (Yangtze River Delta) and central PRD (Pearl River Delta) regions, with increases of up to 47 μg m−3 due to the sensitivity of VOC-limited urban areas. In summer, most SOA concentrations formed over China are from biogenic sources (national average of 70%). And SOA concentrations in YRD and SCB regions are generally higher than other regions. Excluding anthropogenic emissions while keeping biogenic emissions unchanged results that SOA concentrations reduce by 60% over China, which indicates that anthropogenic emissions can interact with biogenic emissions then facilitate biogenic SOA formation. It is suggested that controlling anthropogenic emissions would result in reduction of both anthropogenic and biogenic SOA.

PMCAMx-UF, a three-dimensional chemical transport model focusing on the simulation of the ultrafine particle size distribution and composition has been extended with the addition of the volatility basis set (VBS) approach for the simulation of organic aerosol (OA). The model was applied in Europe to quantify the effect of secondary semi-volatile organic vapors on particle number concentrations. The model predictions were evaluated against field observations collected during the PEGASOS 2012 campaign. The measurements included both ground and airborne measurements, from stations across Europe and a zeppelin measuring above Po Valley. The ground level concentrations of particles with a diameter larger than 100 nm (N100) were reproduced with a daily normalized mean error of 40 % and a daily normalized mean bias of −20 %. PMCAMx-UF tended to overestimate the concentration of particles with a diameter larger than 10 nm (N10) with a daily normalized mean bias of 75 %. The model was able to reproduce, within a factor of 2, 85 % of the N10 and 75 % of the N100 zeppelin measurements above ground. The condensation of organics led to an increase (50 %–120 %) in the N100 concentration mainly in central and northern Europe, while the N10 concentration decreased by 10 %–30 %. Including the VBS in PMCAMx-UF improved its ability to simulate aerosol number concentration compared to simulations neglecting organic condensation on ultrafine particles.

Isoprene is a highly reactive volatile organic compound emitted by vegetation, known to be a precursor of secondary organic aerosols and to enhance tropospheric ozone formation under polluted conditions. Isoprene emissions respond strongly to changes in meteorological parameters such as temperature and solar radiation. In addition, the increasing CO2 concentration has a dual effect, as it causes both a direct emission inhibition as well as an increase in biomass through fertilization. In this study we used the MEGAN (Model of Emissions of Gases and Aerosols from Nature) emission model coupled with the MOHYCAN (Model of HYdrocarbon emissions by the CANopy) canopy model to calculate the isoprene fluxes emitted by vegetation in the recent past (1979–2014) and in the future (2070–2099) over Europe at a resolution of 0.1∘×0.1∘. As a result of the changing climate, modeled isoprene fluxes increased by 1.1 % yr−1 on average in Europe over 1979–2014, with the strongest trends found over eastern Europe and European Russia, whereas accounting for the CO2 inhibition effect led to reduced emission trends (0.76 % yr−1). Comparisons with field campaign measurements at seven European sites suggest that the MEGAN–MOHYCAN model provides a reliable representation of the temporal variability of the isoprene fluxes over timescales between 1 h and several months. For the 1979–2014 period the model was driven by the ECMWF ERA-Interim reanalysis fields, whereas for the comparison of current with projected future emissions, we used meteorology simulated with the ALARO regional climate model. Depending on the representative concentration pathway (RCP) scenarios for greenhouse gas concentration trajectories driving the climate projections, isoprene emissions were found to increase by +7 % (RCP2.6), +33 % (RCP4.5), and +83 % (RCP8.5), compared to the control simulation, and even stronger increases were found when considering the potential impact of CO2 fertilization: +15 % (RCP2.6), +52 % (RCP4.5), and +141 % (RCP8.5). However, the inhibitory CO2 effect goes a long way towards canceling these increases. Based on two distinct parameterizations, representing strong or moderate inhibition, the projected emissions accounting for all effects were estimated to be 0–17 % (strong inhibition) and 11–65 % (moderate inhibition) higher than in the control simulation. The difference obtained using the two CO2 parameterizations underscores the large uncertainty associated to this effect.

The characteristics of ozone variations and the impacts of synoptic and local meteorological factors in northern China were quantitatively analyzed during the warm season from 2013 to 2017 based on multi-city in situ ozone and meteorological data as well as meteorological reanalysis. The domain-averaged maximum daily 8 h running average O3 (MDA8 O3) concentration was 122±11 µg m−3, with an increase rate of 7.88 µg m−3 yr−1, and the three most polluted months were closely related to the variations in the synoptic circulation patterns, which occurred in June (149 µg m−3), May (138 µg m−3) and July (132 µg m−3). A total of 26 weather types (merged into five weather categories) were objectively identified using the Lamb–Jenkinson method. The highly polluted weather categories included the S–W–N directions (geostrophic wind direction diverts from south to north), low-pressure-related weather types (LP) and cyclone type, which the study area controlled by a low-pressure center (C), and the corresponding domain-averaged MDA8 O3 concentrations were 122, 126 and 128 µg m−3, respectively. Based on the frequency and intensity changes of the synoptic circulation patterns, 39.2 % of the interannual increase in the domain-averaged O3 from 2013 to 2017 was attributed to synoptic changes, and the intensity of the synoptic circulation patterns was the dominant factor. Using synoptic classification and local meteorological factors, the segmented synoptic-regression approach was established to evaluate and forecast daily ozone variability on an urban scale. The results showed that this method is practical in most cities, and the dominant factors are the maximum temperature, southerly winds, relative humidity on the previous day and on the same day, and total cloud cover. Overall, 41 %–63 % of the day-to-day variability in the MDA8 O3 concentrations was due to local meteorological variations in most cities over northern China, except for two cities: QHD (Qinhuangdao) at 34 % and ZZ (Zhengzhou) at 20 %. Our quantitative exploration of the influence of both synoptic and local meteorological factors on interannual and day-to-day ozone variability will provide a scientific basis for evaluating emission reduction measures that have been implemented by the national and local governments to mitigate air pollution in northern China.

Black carbon (BC) is an important component of particulate matter (PM) in urban environments. BC is typically emitted from gas and diesel engines, coal-fired power plants, and other sources that burn fossil fuel. In contrast to PM, BC measurements are not always available on a large scale due to the operational cost and complexity of the instrumentation. Therefore, it is advantageous to develop a mathematical model for estimating the quantity of BC in the air, termed a BC proxy, to enable widening of spatial air pollution mapping. This article presents the development of BC proxies based on a Bayesian framework using measurements of PM concentrations and size distributions from 10 to 10,000 nm from a recent mobile air pollution study across several areas of Jordan. Bayesian methods using informative priors can naturally prevent over-fitting in the modelling process and the methods generate a confidence interval around the prediction, thus the estimated BC concentration can be directly quantified and assessed. In particular, two types of models are developed based on their transparency and interpretability, referred to as white-box and black-box models. The proposed methods are tested on extensive data sets obtained from the measurement campaign in Jordan. In this study, black-box models perform slightly better due to their model complexity. Nevertheless, the results demonstrate that the performance of both models does not differ significantly. In practice, white-box models are relatively more convenient to be deployed, the methods are well understood by scientists, and the models can be used to better understand key relationships.

We analysed δ13C of total carbon (TC) and δ15N of total nitrogen (TN) in submicron (PM1) and size segregated aerosol particles (PM0.056–2.5) collected during a cruise in the Baltic Sea from 9 to 17 November 2012. PM1 were characterized by the highest δ13C (–26.4‰) and lowest δ15N (–0.2 and 0.8‰) values when air masses arrived from the southwest direction (Poland). The obtained δ13C values indicated that combined emissions of coal and diesel/gasoline combustion were the most likely sources of TC. The depleted δ15N values indicated that TN originated mainly from liquid fuel combustion (road traffic, shipping) during this period. The lowest δ13C and highest δ15N values were determined in PM1 samples during the western airflow when the air masses had no recent contact with land. The highest δ15N values were probably associated with chemical aging of nitrogenous species during long-range transport, the lowest δ13C values could be related to emissions from diesel/gasoline combustion, potentially from ship traffic. The δ13C analysis of size-segregated aerosol particles PM0.056–2.5 revealed that the lowest δ13C values were observed in the size range from 0.056 to 0.18 µm and gradual 13C enrichment occurred in the size range from 0.18 to 2.5 µm due to different sources or formation mechanisms of the aerosols.

A reliable assessment of the optical properties of atmospheric black carbon is of crucial importance for an accurate estimation of radiative forcing. In this study we investigated the spatio-temporal variability of the mass absorption cross-section (MAC) of atmospheric black carbon, defined as light absorption coefficient (σap) divided by elemental carbon mass concentration (mEC). σap and mEC have been monitored at supersites of the ACTRIS network for a minimum period of one year. The 9 rural background sites considered in this study cover southern Scandinavia, central Europe and the Mediterranean. σap was determined using filter based absorption photometers and mEC using a thermal-optical technique. Homogeneity of the data-set was ensured by harmonization of all involved methods and instruments during extensive intercomparison exercises at the European Center for Aerosol Calibration (ECAC). Annual mean values of σap at a wavelength of 637 nm vary between 0.66 and 1.3 Mm−1 in southern Scandinavia, 3.7–11 Mm−1 in Central Europe and the British Isles, and 2.3–2.8 Mm−1 in the Mediterranean. Annual mean values of mEC vary between 0.084 and 0.23 μg m−3 in southern Scandinavia, 0.28–1.1 in Central Europe and the British Isles, and 0.22–0.26 in the Mediterranean. Both σap and mEC in southern Scandinavia and Central Europe have a distinct seasonality with maxima during the cold season and minima during summer, whereas at the Mediterranean sites an opposite trend was observed. Annual mean MAC values were quite similar across all sites and the seasonal variability was small at most sites. Consequently, a MAC value of 10.0 m2 g−1 (geometric standard deviation = 1.33) at a wavelength of 637 nm can be considered to be representative of the mixed boundary layer at European background sites, where BC is expected to be internally mixed to a large extent. The observed spatial variability is rather small compared to the variability of values in previous literature, indicating that the harmonization efforts resulted in substantially increased precision of the reported MAC. However, absolute uncertainties of the reported MAC values remain as high as ± 30–70% due to the lack of appropriate reference methods and calibration materials. The mass ratio between elemental carbon and non-light-absorbing matter was used as a proxy for the thickness of coatings around the BC cores, in order to assess the influence of the mixing state on the MAC of BC. Indeed, the MAC was found to increase with increasing values of the coating thickness proxy. This provides evidence that coatings do increase the MAC of atmospheric BC to some extent, which is commonly referred to as lensing effect. © 2016 The Authors, The research leading to these results has received funding from the European Union Seventh Framework Programme (ACTRIS, FP7/2007-2013, grant agreement no. 262254 ). ACTRIS-2 is a European Project supported by the European Commission Horizon 2020 Research and Innovation Framework Programme (ACTRIS-2, H2020-INFRAIA-2014-2015, grant agreement no. 654109 ). This work was also supported by grants from Labex OSUG@2020 (PhD investissements d'avenir – ANR10 LABX56) and from the European Research Council (ERC-CoG 615922-BLACARAT). Appendix A.

Dall'Osto, Manuel ... et al.-- 11 pages, 4 figures, supplementary material https://dx.doi.org/10.1038/s41598-017-17343-9, The formation of new atmospheric particles involves an initial step forming stable clusters less than a nanometre in size (~10 nm). Although at times, the same species can be responsible for both processes, it is thought that more generally each step comprises differing chemical contributors. Here, we present a novel analysis of measurements from a unique multi-station ground-based observing system which reveals new insights into continental-scale patterns associated with new particle formation. Statistical cluster analysis of this unique 2-year multi-station dataset comprising size distribution and chemical composition reveals that across Europe, there are different major seasonal trends depending on geographical location, concomitant with diversity in nucleating species while it seems that the growth phase is dominated by organic aerosol formation. The diversity and seasonality of these events requires an advanced observing system to elucidate the key processes and species driving particle formation, along with detecting continental scale changes in aerosol formation into the future, We gratefully acknowledge support by the German Federal Environment Agency (Umweltbundesamt), grants no. 351 03 031 and 351 01 038, and UFOPLAN grant 3703 43 200 (title “Erfassung der Zahl feiner und ultrafeiner Partikel in der Außenluft”). [...] The study was funded by the Spanish Ministry of Economy through projects BIO-NUC (CGL2013-49020-R), and by the EU though the FP7-PEOPLE-2013-IOF programme (Project number 624680, MANU – Marine Aerosol NUcleations) and the Ramon y Cajal fellowship (RYC-2012-11922).The National Centre for Atmospheric Science NCAS Birmingham group is funded by the UK Natural Environment Research Council

Optimisation of aircraft ground operations to reduce airport emissions can reduce resultant local air quality impacts. Single engine taxiing (SET), where only half of the installed number of engines are used for the majority of the taxi duration, offers the opportunity to reduce fuel consumption, and emissions of NOX, CO and HC. Using 3510 flight data records, this paper develops a model for SET operations and presents a case study of London Heathrow, where we show that SET is regularly implemented during taxi-in. The model predicts fuel consumption and pollutant emissions with greater accuracy than previous studies that used simplistic assumptions. Without SET during taxi-in, fuel consumption and pollutant emissions would increase by up to 50%. Reducing the time before SET is initiated to the 25th percentile of recorded values would reduce fuel consumption and pollutant emissions by 7–14%, respectively, relative to current operations. Future research should investigate the practicalities of reducing the time before SET initialisation so that additional benefits of reduced fuel loadings, which would decrease fuel consumption across the whole flight, can be achieved.

The MACC reanalysis dust product is evaluated over Europe, northern Africa and the Middle East using the EARLINET-optimized CALIOP/CALIPSO pure dust satellite-based product LIVAS (2007–2012). MACC dust optical depth at 550 nm (DOD550) data are compared against LIVAS DOD532 observations. As only natural aerosol (dust and sea salt) profiles are available in MACC, here we focus on layers above 1 km a.s.l. to diminish the influence of sea salt particles that typically reside at low heights. So, MACC natural aerosol extinction coefficient profiles at 550 nm are compared against dust extinction coefficient profiles at 532 nm from LIVAS, assuming that the MACC natural aerosol profile data can be similar to the dust profile data, especially over pure continental regions. It is shown that the reanalysis data are capable of capturing the major dust hot spots in the area as the MACC DOD550 patterns are close to the LIVAS DOD532 patterns throughout the year. MACC overestimates DOD for regions with low dust loadings and underestimates DOD for regions with high dust loadings where DOD exceeds ∼ 0.3. The mean bias between the MACC and LIVAS DOD is 0.025 (∼ 25 %) over the whole domain. Both MACC and LIVAS capture the summer and spring high dust loadings, especially over northern Africa and the Middle East, and exhibit similar monthly structures despite the biases. In this study, dust extinction coefficient patterns are reported at four layers (layer 1: 1200– 3000 m a.s.l., layer 2: 3000–4800 m a.s.l., layer 3: 4800– 6600 m a.s.l. and layer 4: 6600–8400 m a.s.l.). The MACC and LIVAS extinction coefficient patterns are similar over areas characterized by high dust loadings for the first three layers. Within layer 4, MACC overestimates extinction coefficients consistently throughout the year over the whole domain. MACC overestimates extinction coefficients compared to LIVAS over regions away from the major dust sources while over regions close to the dust sources (the Sahara and Middle East) it underestimates strongly only for heights below ∼ 3–5 km a.s.l. depending on the period of the year. In general, it is shown that dust loadings appear over remote regions and at heights up to 9 km a.s.l. in MACC contrary to LIVAS. This could be due to the model performance and parameterizations of emissions and other processes, due to the assimilation of satellite aerosol measurements over dark surfaces only or due to a possible enhancement of aerosols by the MACC assimilation system.

The impact of ship emissions on the surface concentration of nitrogen oxides (NOx) and ozone (O-3) in the Mediterranean area of the harbour of Brindisi (IT) has been investigated. Numerical simulations have been performed for a summer period of the year 2012, at different spatial scale, using the meso-scale BOLCHEM and the local-scale ADMS-Urban models. Results show that while average ground concentration of primary pollutant NOx increases in the area surrounding the port, a decrease in O-3 concentration is observed.

After carbon dioxide (CO2), aerosol black carbon (BC) is considered to be the second most important contributor to global warming. This paper presents equivalent black carbon (eBC) (derived from an optical absorption method) data collected from three sites in the interior of South Africa where continuous measurements were conducted, i.e. Elandsfontein, Welgegund and Marikana, as well elemental carbon (EC) (determined by evolved carbon method) data at five sites where samples were collected once a month on a filter and analysed offline, i.e. Louis Trichardt, Skukuza, Vaal Triangle, Amersfoort and Botsalano. Analyses of eBC and EC spatial mass concentration patterns across the eight sites indicate that the mass concentrations in the South African interior are in general higher than what has been reported for the developed world and that different sources are likely to influence different sites. The mean eBC or EC mass concentrations for the background sites (Welgegund, Louis Trichardt, Skukuza, Botsalano) and sites influenced by industrial activities and/or nearby settlements (Elandsfontein, Marikana, Vaal Triangle and Amersfoort) ranged between 0.7 and 1.1, and 1.3 and 1.4 µg m−3, respectively. Similar seasonal patterns were observed at all three sites where continuous measurement data were collected (Elandsfontein, Marikana and Welgegund), with the highest eBC mass concentrations measured from June to October, indicating contributions from household combustion in the cold winter months (June–August), as well as savannah and grassland fires during the dry season (May to mid-October). Diurnal patterns of eBC at Elandsfontein, Marikana and Welgegund indicated maximum concentrations in the early mornings and late evenings, and minima during daytime. From the patterns it could be deduced that for Marikana and Welgegund, household combustion, as well as savannah and grassland fires, were the most significant sources, respectively. Possible contributing sources were explored in greater detail for Elandsfontein, with five main sources being identified as coal-fired power stations, pyrometallurgical smelters, traffic, household combustion, as well as savannah and grassland fires. Industries on the Mpumalanga Highveld are often blamed for all forms of pollution, due to the NO2 hotspot over this area that is attributed to NOx emissions from industries and vehicle emissions from the Johannesburg–Pretoria megacity. However, a comparison of source strengths indicated that household combustion as well as savannah and grassland fires were the most significant sources of eBC, particularly during winter and spring months, while coal-fired power stations, pyrometallurgical smelters and traffic contribute to eBC mass concentration levels year round., published version, peerReviewed

© 2017 American Chemical Society. Laboratory studies of atmospheric chemistry characterize the nature of atmospherically relevant processes down to the molecular level, providing fundamental information used to assess how human activities drive environmental phenomena such as climate change, urban air pollution, ecosystem health, indoor air quality, and stratospheric ozone depletion. Laboratory studies have a central role in addressing the incomplete fundamental knowledge of atmospheric chemistry. This article highlights the evolving science needs for this community and emphasizes how our knowledge is far from complete, hindering our ability to predict the future state of our atmosphere and to respond to emerging global environmental change issues. Laboratory studies provide rich opportunities to expand our understanding of the atmosphere via collaborative research with the modeling and field measurement communities, and with neighboring disciplines.

Highly time-resolved measurements of water soluble ions, organic and elemental carbon concentrations in the particle diameter size range D-p

Global measurements of the elemental composition of fine particulate matter across several urban locations by the Surface Particulate Matter Network reveal an enhanced fraction of anthropogenic dust compared to natural dust sources, especially over Asia. We develop a global simulation of anthropogenic fugitive, combustion, and industrial dust which, to our knowledge, is partially missing or strongly underrepresented in global models. We estimate 2-16 mu g m(-3) increase in fine particulate mass concentration across East and South Asia by including anthropogenic fugitive, combustion, and industrial dust emissions. A simulation including anthropogenic fugitive, combustion, and industrial dust emissions increases the correlation from 0.06 to 0.66 of simulated fine dust in comparison with Surface Particulate Matter Network measurements at 13 globally dispersed locations, and reduces the low bias by 10% in total fine particulate mass in comparison with global in situ observations. Global population-weighted PM2.5 increases by 2.9 mu g m(-3) (10%). Our assessment ascertains the urgent need of including this underrepresented fine anthropogenic dust source into global bottom-up emission inventories and global models.

This work presents a novel approach to comparing and graphically representing simultaneous concentration measurements of PM10, PM2.5 and PM1 (i.e., aerosol particles with aerodynamic diameters less than 10, 2.5 and 1 μm, respectively) with similar data reported in the literature using PM2.5/PM10 and PM1/PM10 concentration ratios. With this aim, a dedicated triangular diagram was used. The proposed approach was applied to size-segregated particulate matter (PM) concentrations recorded in the Agri Valley (Basilicata region – southern Italy). Results show that the PM10, PM2.5 and PM1 concentrations recorded in the Agri Valley are comparable both in terms of PM concentration ratios and PM levels to an urban site.

Although particulate organic and elemental carbon (OC and EC) are important constituents of the suspended atmospheric particulate matter (PM), measurements of OC and EC are much less common and more uncertain than measurements of e.g. the ionic components of PM. In the framework of atmospheric research infrastructures supported by the European Union, actions have been undertaken to determine and mitigate sampling artefacts, and assess the comparability of OC and EC data obtained in a network of 10 atmospheric observatories across Europe. Positive sampling artefacts (from 0.4 to 2.8 μg C/m3) and analytical discrepancies (between −50% and +40% for the EC/TC ratio) have been taken into account to generate a robust data set, from which we established the phenomenology of carbonaceous aerosols at regional background sites in Europe. Across the network, TC and EC annual average concentrations range from 0.4 to 9 μg C/m3, and from 0.1 to 2 μg C/m3, respectively. TC/PM10 annual mean ratios range from 0.11 at a Mediterranean site to 0.34 at the most polluted continental site, and TC/PM2.5 ratios are slightly greater at all sites (0.15–0.42). EC/TC annual mean ratios range from 0.10 to 0.22, and do not depend much on PM concentration levels, especially in winter. Seasonal variations in PM and TC concentrations, and in TC/PM and EC/TC ratios, differ across the network, which can be explained by seasonal changes in PM source contributions at some sites. © 2016 The Authors, EUSAAR (FP6/2001-2006, grant agreement no. RII3-GT-2006-026140), ACTRIS (FP7/2007-2013, grant agreement no. 262254), ACTRIS2 (H2020-INFRAIA-2014-2015, grant agreement no. 654109), EPA Ireland is acknowledged for the research support at Mace Head, the Norwegian Environment Agency for the measurements at Birkenes. Appendix A

The global environment is changing rapidly due to anthropogenic emissions and actions. Such activities modify aerosol and greenhouse gas concentrations in the atmosphere, leading to regional and global climate change and affecting, e.g., food and fresh-water security, sustainable use of natural resources and even demography. Here we present a conceptual design of a global, hierarchical observation network that can provide tools and increased understanding to tackle the inter-connected environmental and societal challenges that we will face in the coming decades. The philosophy behind the conceptual design relies on physical conservation laws of mass, energy and momentum, as well as on concentration gradients that act as driving forces for the atmosphere-biosphere exchange. The network is composed of standard, flux and/or advanced and flagship stations, each of which having specific and identified tasks. Each ecosystem type on the globe has its own characteristic features that have to be taken into consideration. The hierarchical network as a whole is able to tackle problems related to large spatial scales, heterogeneity of ecosystems and their complexity. The most comprehensive observations are envisioned to occur in flagship stations, with which the process-level understanding can be expanded to continental and global scales together with advanced data analysis, Earth system modelling and satellite remote sensing. The denser network of the flux and standard stations allows application and up-scaling of the results obtained from flagship stations to the global level.

An assessment of current and future emissions, air concentrations, and atmospheric deposition of mercury worldwide is presented on the basis of results obtained during the performance of the EU GMOS (Global Mercury Observation System) project. Emission estimates for mercury were prepared with the main goal of applying them in models to assess current (2013) and future (2035) air concentrations and atmospheric deposition of this contaminant. The combustion of fossil fuels (mainly coal) for energy and heat production in power plants and in industrial and residential boilers, as well as artisanal and small-scale gold mining, is one of the major anthropogenic sources of Hg emissions to the atmosphere at present. These sources account for about 37 and 25 % of the total anthropogenic Hg emissions globally, estimated to be about 2000 t. Emissions in Asian countries, particularly in China and India, dominate the total emissions of Hg. The current estimates of mercury emissions from natural processes (primary mercury emissions and re-emissions), including mercury depletion events, were estimated to be 5207 t year−1, which represents nearly 70 % of the global mercury emission budget. Oceans are the most important sources (36 %), followed by biomass burning (9 %). A comparison of the 2035 anthropogenic emissions estimated for three different scenarios with current anthropogenic emissions indicates a reduction of these emissions in 2035 up to 85 % for the best-case scenario. Two global chemical transport models (GLEMOS and ECHMERIT) have been used for the evaluation of future mercury pollution levels considering future emission scenarios. Projections of future changes in mercury deposition on a global scale simulated by these models for three anthropogenic emissions scenarios of 2035 indicate a decrease in up to 50 % deposition in the Northern Hemisphere and up to 35 % in Southern Hemisphere for the best-case scenario. The EU GMOS project has proved to be a very important research instrument for supporting the scientific justification for the Minamata Convention and monitoring of the implementation of targets of this convention, as well as the EU Mercury Strategy. This project provided the state of the art with regard to the development of the latest emission inventories for mercury, future emission scenarios, dispersion modelling of atmospheric mercury on a global and regional scale, and source–receptor techniques for mercury emission apportionment on a global scale.

There is evidence that long-range transport of natural and/or anthropogenic particles can have a negative impact on urban air quality. Certain European cities may fail to comply with the currently implemented 24-h PM (10) limit value due to the additional impact of remote sources of particles, which are not controllable at local level. For that reason, reliable methodologies identifying long-range transport patterns and quantifying their contribution to urban PM10 levels are required. In this study, a two-stage clustering methodology was developed and applied to back trajectories arriving in three European cities: Athens, Madrid and Birmingham, which experience large, moderate and small numbers of daily PM10 episodes, respectively. The atmospheric trajectories used in this analysis were computed with HYSPLIT model (NOAA) for a 3-year period. The two-stage cluster analysis has the advantage of providing highly disaggregated trajectory clusters, which proved to correspond to significantly different PM10 levels. In the case of Madrid and Birmingham, clusters of trajectories originating from North Africa and continental Europe, respectively, were strongly associated with the highest PM10 levels recorded in selected monitoring stations. In Athens, long-range transport patterns and trans-boundary influences were less evident, which highlighted the more substantial impact of local emission sources. Finally, two simple statistical indexes were proposed for assessing PM10 episodes associated with different clusters of trajectories. This study has established a practical methodology for examining the impact of long-range atmospheric transport on local air quality, without resorting to high resource-demanding source apportionment techniques. (c) 2007 Published by Elsevier Ltd. Atmospheric Environment

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Bells et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management. (C) 2015 The Authors. Published by Elsevier Ltd.

For the assessment of personal exposure, information about the concentration of pollutants when people are in given indoor environments (occupancy time) are of prime importance. However this kind of data frequently is not reported. The aim of this study was to assess differences in particle characteristics between occupancy time and the total monitoring period, with the latter being the most frequently used averaging time in the published data. Seven indoor environments were selected in Sweden and Finland: an apartment, two houses, two schools, a supermarket, and a restaurant. They were assessed for particle number and mass concentrations and number size distributions. The measurements using a Scanning Mobility Particle Sizer and two photometers were conducted for seven consecutive days during winter in each location. Particle concentrations in residences and schools were, as expected, the highest during occupancy time. In the apartment average and median PM2.5 mass concentrations during the occupancy time were 29% and 17% higher, respectively compared to total monitoring period. In both schools, the average and medium values of the PM2.5 mass concentrations were on average higher during teaching hours compared to the total monitoring period by 16% and 32%, respectively. When it comes to particle number concentrations (PNC), in the apartment during occupancy, the average and median values were 33% and 58% higher, respectively than during the total monitoring period. In both houses and schools the average and median PNC were similar for the occupancy and total monitoring periods. General conclusions on the basis of measurements in the limited number of indoor environments cannot be drawn. However the results confirm a strong dependence on type and frequency of indoor activities that generate particles and site specificity. The results also indicate that the exclusion of data series during non-occupancy periods can improve the estimates of particle concentrations and characteristics suitable for exposure assessment, which is crucial for estimating health effects in epidemiological and toxicological studies. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).

We evaluate planetary boundary-layer (PBL) parametrizations in the Weather Research and Forecasting (WRF) numerical model, with three connected objectives: first, for a 16-year period, we use a cluster analysis algorithm of three-day back-trajectories to determine general synoptic flow patterns over Barcelona, Spain arriving at heights of 0.5, 1.5, and 3 km; to represent the lower PBL, upper PBL, and lower free troposphere, respectively. Seven clusters are determined at each arriving altitude. Regional recirculations account for 54 % of the annual total at 0.5 km, especially in summertime. In the second objective, we assess a time-adaptive approach using an extended Kalman filter to estimate PBL height from backscatter lidar returns at 1200 UTC $$\pm $$ 30 min for 45 individual days during a seven-year period. PBL heights retrieved with this technique are compared with three classic methods used in the literature to estimate PBL height from lidar. The methods are validated against PBL heights calculated from daytime radiosoundings. Lidar and radiosonde estimated PBL heights are classified under objectively-determined synoptic clusters. With the final objective, WRF model-simulated PBL heights are validated against lidar estimates using eight unique PBL schemes as inputs. Evaluation of WRF model-simulated PBL heights are performed under different synoptic situations. Determination coefficients with lidar estimates indicate the non-local assymetric convective model scheme is the most reliable, with the widely-tested local Mellor–Yamada–Janjic scheme showing the weakest correlations with lidar retrievals. Overall, there is a systematic underestimation of PBL height simulated in the WRF model.

Between late 1980s and 2014, the Greater Delhi region has witnessed an increase in vehicular fleet, four sets of emission standards, and changes in engine technology and fuel usage. This paper presents and evaluate these measures on on-road vehicle exhaust emissions under four counterfactual scenarios - (a) no penetration of 4-stroke (45) 2-wheelers (2Ws) (b) no introduction of compressed natural gas (CNG) (c) no implementation of emission standards post 2000 and (d) no dual emission standards (supply of better fuel in the metropolitan areas and a grade lower for the rest). Introduction of 45 engines reduced VOC emissions by 90%, thus being the most effective compared to the three emission standards (BS-II, Ill, and IV) combined. Introducing CNG reduced 50% of PIV12.5 and increased 20% of NO emissions in 2014, mostly from buses and light duty vehicles. Implementation of emission standards affected all pollutants, with 60% reduction in VOCs and 20-30% reduction for the rest. Dual emission standards increased the PIV12.5, emissions from heavy duty vehicles, as much as the reductions from passenger vehicles, thus negating the benefits of the latter. Under the proposed road map of emission standards and vehicular technology by the Auto Fuel Policy 2025 committee, PM2.5 emissions in 2030 will be halved, CO emissions will reach three times, and VOC and NO emissions will at least stabilize compared to 2014 estimates. If leapfrogged to BS-VI in 2017, there will be additional reduction in NO, and VOC emissions. (C) 2015 Elsevier B.V. All rights reserved.

In-use, fuel-based motor vehicle emission factors were determined using measurements made in a highway tunnel in Pittsburgh, Pennsylvania. Concentrations Of PM2.5 mass, CO, CO2, and NO, were measured continuously. Filter-based measurements included PM2.5 mass, organic and elemental carbon (OC and EQ, inorganic ions and metals. Fuel-based emission factors for each pollutant were calculated using a fuel-carbon balance. The weekday traffic volume and fleet composition varied in a consistent diurnal pattern with the estimated fraction of fuel consumed by heavy-duty diesel ve ' hicle (HDDV) traffic ranging from 11% to 36%. The emission rate of most species showed a significant dependence on sample period. NOx, PM2.5, EC and OC emission factors were significantly larger during the early morning, truckdominated period. Emissions of particulate metals associated with brake wear (Cu, Sb, Ba and potentially Ga) were emitted at higher rates during the rush-hour period, which is characterized by slower, stop-and-go traffic. Emission rates of crustal elements (Fe, Ca, Mg, Li), Zn and Mn were highest during the early-morning period when there was more heavytruck traffic. A seasonal shift in average OC/EC ratio for the rush-hour period was observed; fall and summer OC/EC ratios are 1.0+0.6 and 0.26+0.06, respectively. Potential causes for this shift are increased partitioning of semi-volatile organic compounds into the gas phase during the summer months and/or effects of seasonal changes in fuel formulation. Emission factors for HDDV and light-duty vehicles (LDV) classes were estimated using a linear regression of emission factor as a function of fleet composition. The extrapolated emission factors generally agree with previously published measurements, though a substantial range in published values is noted. (c) 2006 Elsevier Ltd. All rights reserved.

Urban dwellers often breathe air that does not meet the European and WHO standards. Next to legislative initiatives to lower atmospheric pollutants, much research has been conducted on the potential of urban trees as mitigation tool for atmospheric particles. While leaf-deposited dust has shown to vary significantly throughout single tree crowns, this study evaluated the influence of micro-scale tree crown morphology (leaf density) on the amount of leaf-deposited dust. Using a ground-based LiDAR approach, the three-dimensional tree crown morphology was obtained and compared to gravimetric measurements of leaf-deposited dust within three different size fractions (>10, 3-10 and 0.2-3 mu m). To our knowledge, this is the first application of ground-based LiDAR for comparison with gravimetric results of leaf-deposited particulate matter. Overall, an increasing leaf density appears to reduce leaf-deposition of atmospheric particles. This might be explained by a reduced wind velocity, suppressing turbulent deposition of atmospheric particles through impaction. Nevertheless, the effect of tree crown morphology on particulate deposition appears almost negligible (7% AIC decrease) compared to the influence of physical factors like height, azimuth and tree position. (C) 2014 Elsevier Ltd. All rights reserved.

National parks in the United States are protected areas wherein the natural habitat is to be conserved for future generations. Deposition of anthropogenic nitrogen (N) transported from areas of human activity (fuel combustion, agriculture) may affect these natural habitats if it exceeds an ecosystem-dependent critical load (CL). We quantify and interpret the deposition to Class I US national parks for present-day and future (2050) conditions using the GEOS-Chem global chemical transport model with 1/2° × 2/3° horizontal resolution over North America. We estimate CL values in the range 2.5–5 kg N ha−1 yr−1 for the different parks to protect the most sensitive ecosystem receptors. For present-day conditions, we find 24 out of 45 parks to be in CL exceedance and 14 more to be marginally so. Many of these are in remote areas of the West. Most (40–85%) of the deposition originates from NOx emissions (fuel combustion). We project future changes in N deposition using representative concentration pathway (RCP) anthropogenic emission scenarios for 2050. These feature 52–73% declines in US NOx emissions relative to present but 19–50% increases in US ammonia (NH3) emissions. Nitrogen deposition at US national parks then becomes dominated by domestic NH3 emissions. While deposition decreases in the East relative to present, there is little progress in the West and increases in some regions. We find that 17–25 US national parks will have CL exceedances in 2050 based on the RCP8.5 and RCP2.6 scenarios. Even in total absence of anthropogenic NOx emissions, 14–18 parks would still have a CL exceedance. Returning all parks to N deposition below CL by 2050 would require at least a 50% decrease in US anthropogenic NH3 emissions relative to RCP-projected 2050 levels.

We have analysed the trends of total aerosol particle number concentrations (N) measured at long-term measurement stations involved either in the Global Atmosphere Watch (GAW) and/or EU infrastructure project ACTRIS. The sites are located in Europe, North America, Antarctica, and on Pacific Ocean islands. The majority of the sites showed clear decreasing trends both in the full-length time series, and in the intra-site comparison period of 2001–2010, especially during the winter months. Several potential driving processes for the observed trends were studied, and even though there are some similarities between N trends and air temperature changes, the most likely cause of many northern hemisphere trends was found to be decreases in the anthropogenic emissions of primary particles, SO2 or some co-emitted species. We could not find a consistent agreement between the trends of N and particle optical properties in the few stations with long time series of all of these properties. The trends of N and the proxies for cloud condensation nuclei (CCN) were generally consistent in the few European stations where the measurements were available. This work provides a useful comparison analysis for modelling studies of trends in aerosol number concentrations.

A nationwide study was carried out to develop air pollution source profiles specific to India. Chemical speciation profiles are reported for 27 major non-vehicular sources of particulate matter (combustion and non-combustion) in six cities in India viz. Bengaluru, Chennai, Delhi, Kanpur, Mumbai and Pune. PM10 and PM2.5 samples were collected from these sources using three different modes of sampling viz, dilution, resuspension and source dominated sampling, depending on the nature of the source. Filter samples were analyzed for mass by gravimetric analysis, elements by Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), water soluble ions by ion chromatography and elemental (EC) and organic carbon (OC) by thermal/optical reflectance. Reported profiles include 39 elements, 12 ions, EC and OC. Developed profiles are compared with similar profiles that have been reported previously. (C) 2013 Elsevier B.V. All rights reserved.

A three-dimensional regional chemical transport model (CTM) with detailed aerosol microphysics, PMCAMx-UF, was applied to the European domain to simulate the contribution of direct emissions and secondary formation to total particle number concentrations during May 2008. PMCAMx-UF uses the Dynamic Model for Aerosol Nucleation and the Two-Moment Aerosol Sectional (TOMAS) algorithm to track both aerosol number and mass concentration using a sectional approach. The model predicts nucleation events that occur over scales of hundreds up to thousands of kilometers especially over the Balkans and Southeast Europe. The model predictions were compared against measurements from 7 sites across Europe. The model reproduces more than 70% of the hourly concentrations of particles larger than 10 nm (N10) within a factor of 2. About half of these particles are predicted to originate from nucleation in the lower troposphere. Regional nucleation is predicted to increase the total particle number concentration by approximately a factor of 3. For particles larger than 100 nm the effect varies from an increase of 20% in the eastern Mediterranean to a decrease of 20% in southern Spain and Portugal resulting in a small average increase of around 1% over the whole domain. Nucleation has a significant effect in the predicted N50 levels (up to a factor of 2 increase) mainly in areas where there are condensable vapors to grow the particles to larger sizes. A semi-empirical ternary sulfuric acid-ammonia-water parameterization performs better than the activation or the kinetic parameterizations in reproducing the observations. Reducing emissions of ammonia and sulfur dioxide affects certain parts of the number size distribution.

Measurements of the aerosol size distribution from 11 nm to 2.5 microns were made in Mexico City in March 2006, during the MILAGRO (Megacity Initiative: Local and Global Research Observations) field campaign. Observations at the urban supersite, referred to as T0, could often be characterized by morning conditions with high particle mass concentrations, low mixing heights, and highly correlated particle number and CO2 concentrations, indicative that particle number is controlled by primary emissions. Average size-resolved and total number- and volume-based emission factors for combustion sources impacting T0 have been determined using a comparison of peak sizes in particle number and CO2 concentration. Peaks are determined by subtracting the measured concentration from a calculated baseline concentration time series. The number emission and volume emission factors for particles from 11 nm to 494 nm are 1.56 × 1015 particles, and 9.48 × 1011 cubic microns per kg of carbon, respectively. The uncertainty of the number emission factor is approximately plus or minus 50 %. The mode of the number emission factor was between 25 and 32 nm, while the mode of the volume factor was between 0.25 and 0.32 microns. These emission factors are reported as log normal model parameters and are compared with multiple emission factors from the literature. In Mexico City in the afternoon, the CO2 concentration drops during ventilation of the polluted layer, and the coupling between CO2 and particle number breaks down, especially during new particle formation events when particle number is no longer controlled by primary emissions. Using measurements of particle number and CO2 taken aboard the NASA DC-8, the determined primary emission factor was applied to the Mexico City Metropolitan Area (MCMA) plume to quantify the degree of secondary particle formation in the plume; the primary emission factor accounts for less than 50 % of the total particle number and the surplus particle count is not correlated with photochemical age. Primary particle volume and number in the size range 0.1–2 μm are similarly too low to explain the observed volume distribution. Contrary to the case for number, the apparent secondary volume increases with photochemical age. The size distribution of the apparent increase, with a mode at ~250 nm, is reported.

A series of wildfires broke out in Western Russia starting in late July of 2010. Harmful particulates and gases released into the local Russian atmosphere have been reported, as have possible negative consequences for the global atmosphere. In this study, an extremely hazy area and its transport trajectory on Russian wildfires were analysed using aerosol optical depth (AOD) images retrieved via the synergy method from Moderate Resolution Imaging Spectroradiometer (MODIS) data. In addition, we used trace gases (NO2 and SO2) and CO2 products measured using Ozone Monitoring Instrument (OMI) data, vertical distribution of AOD data retrieved from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the mass trajectory analyses, synoptic maps from a HYSPLIT model simulation and ground-based data, including AERONET (both AOD and Ångström exponent) data and PM2.5. First, an Optimal Smoothing (OS) scheme was used to develop more precise and reliable AOD data based on multiple competing predictions made using several AOD retrieval models; then, integrated AOD and PM2.5 data were related using a chemical transport model (GEOS-Chem), and the integrated AOD and visibility data were related using the 6S radiative transfer code. The results show that the PM2.5 concentration is enhanced by a factor of 3–5 as determined from both satellite and in situ observations with peak daily mean concentrations of approximately 500 μg m3. Also, the visibility in many parts of Russia, for instance in Moscow, was less than 100 m; in some areas, the visibility was less than 50 m. Additionally, the possible impact on neighbouring countries due to long-transport was analysed for 31 July and 15 August 2010. A comparison of the satellite aerosol products and ground observations from the neighbouring countries suggests that wildfires in Western Russian had little impact on most european and asian countries, the exceptions being Finland, Estonia, Ukraine and Kyrgyzstan. However, a possible impact on the Arctic region was identified; such an effect would have a serious influence on the polar atmospheric enviroment, and on animals such as polar bears.

Road traffic emission factors (EFs) are one of the main sources of uncertainties in emission inventories; it is necessary to develop methods to reduce these uncertainties to manage air quality more efficiently. Recently an alternative method has been proposed to estimate the EFs. In that work the emission factors were estimated from a long term tracer study developed in Ho Chi Minh City (HCMC) Vietnam. A passive tracer was continuously emitted from a finite line source placed in one side of an urban street canyon. Simultaneously, the resulting tracer concentrations were monitored at the other side of the street. The results of this experiment were used to calculate the dispersion factors and afterwards, these dispersion factors were used to estimate the EFs. In this paper we use the Computational Fluids Dynamics (CFD) model WinMISKAM to critically evaluate the proposed methodology. In a first step, we use the results of the tracer study to validate the CFD model. Results show that the model is able to simulate quite well the tracer dispersion in most of the cases. The model is then used to evaluate the effect of varying the source configuration and to correct the EFs. A comparison with available studies shows that the corrected EFs are within the range of the EFs reported in other studies. Finally, the CFD model is used to find a source configuration that better represents the vehicle emissions and that may be used in future studies to estimate the EFs more accurately. Results show that a 200 m line placed in the center of the street would represent very well the vehicle emissions. This work shows that it is possible to accurately estimate the EFs from tracer studies.

Road traffic emissions, one of the largest source categories in megacity inventories, are highly uncertain. It is essential to develop methodologies to reduce these uncertainties to manage air quality more effectively. In this paper, we propose a methodology to estimate road traffic emission factors (EFs) from a tracer experiment and from roadside pollutants measurements. We emitted continuously during about 300 non-consecutive hours a passive tracer from a finite line source placed on one site of an urban street. At the same time, we measured continuously the resulting tracer concentrations at the other side of the street with a portable on-line gas chromatograph. We used n-propane contained in commercial liquid petroleum gas (LPG) as a passive tracer. Propane offers several advantages to traditional tracers (SF6, N2O, CFCs): low price, easily available, non-reactive, negligible global warming potential, and easy to detect with commercial on-line gas chromatographs. The tracer experiment was carried out from January to March 2007 in a busy street of Ho Chi Minh City (Vietnam). Traffic volume, weather information and pollutant concentrations were also measured at the measurement site. We used the results of the tracer experiment to calculate the dilution factors and afterwards we used these dilution factors, the traffic counts and the pollutant concentrations to estimate the EFs. The proposed method assumes that the finite emission line represents the emission produced by traffic in the full area of the street and therefore there is an error associated to this assumption. We use the Computational Fluids Dynamics (CFD) model MISKAM to calculate this error and to correct the HCMC EFs. EFs for 15 volatile organic compounds (VOCs) and NO are reported here. A comparison with available studies reveals that most of the EFs estimated here are within the range of EFs reported in other studies.

In the last decade, North China (NC) has been one of the most populated and polluted regions in the world. The regional air pollution has had a serious impact on people’s health; thus, all levels of government have implemented various pollution prevention measures since 2013. Based on multi-city in situ environmental and meteorological data, as well as the meteorological reanalysis dataset from 2013 to 2017, regional pollution characteristics and meteorological formation mechanisms were analyzed to provide a more comprehensive understanding of the evolution of PM2.5 in NC. The domain-averaged PM2.5 was 79 ± 17 µg m−3 from 2013 to 2017, with a decreasing rate of 10 μg m−3 yr−1. Two automatic computer algorithms were established to identify 6 daily regional pollution types (DRPTs) and 48 persistent regional pollution events (PRPEs) over NC during 2014–2017. The average PM2.5 concentration for the Large-Region-Pollution type (including the Large-Moderate-Region-Pollution and Large-Severe-Region-Pollution types) was 113 ± 40 µg m−3, and more than half of Large-Region-Pollution days and PRPEs occurred in winter. The PRPEs in NC mainly developed from the area south of Hebei. The number of Large-Region-Pollution days decreased notably from 2014 to 2017, the annual number of days varying between 194 and 97 days, whereas a slight decline was observed in winter. In addition, the averaged PM2.5 concentrations and the numbers and durations of the PRPEs decreased. Lamb-Jenkinson weather typing was used to reveal the impact of synoptic circulations on PM2.5 across NC. Generally, the contributions of the variations in circulation to the reduction in PM2.5 levels over NC between 2013 and 2017 were 64% and 45% in summer and winter, respectively. The three most highly polluted weather types were types C, S and E, with an average PM2.5 concentration of 137 ± 40 µg m−3 in winter. Furthermore, three typical circulation dynamics were categorized in the peak stage of the PRPEs, namely, the southerly airflow pattern, the northerly airflow pattern and anticyclone pattern; the averaged relative humidity, recirculation index, wind speed and boundary layer height were 63%, 0.33, 2.0 m s−1 and 493 m, respectively. Our results imply that additional emission reduction measures should be implemented under unfavorable meteorological situations to attain ambient air quality standards in the future. Keywords: North China, PM2.5, Regional pollution events, Identification of regional pollution type, Meteorological formation mechanism