The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the parameterizations. Finally, SCMs are run for a 24–48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24–48 hr runs suggest that most models have problems in simulating boundary layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.

In this paper we analyse aerosol loading and its direct radiative effects over the Bay of Bengal (BoB) and Arabian Sea (AS) regions for the Integrated Campaign on Aerosols, gases and Radiation Budget (ICARB) undertaken during 2006, using satellite data from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, the Aerosol Index from the Ozone Monitoring Instrument (OMI) on board the Aura satellite, and the European-Community Hamburg (ECHAM5.5) general circulation model extended by Hamburg Aerosol Module (HAM). By statistically comparing with large-scale satellite data sets, we firstly show that the aerosol properties measured during the ship-based ICARB campaign and simulated by the model are representative for the BoB and AS regions and the pre-monsoon season. In a second step, the modelled aerosol distributions were evaluated by a comparison with the measurements from the ship-based sunphotometer, and the satellite retrievals during ICARB. It is found that the model broadly reproduces the observed spatial and temporal variability in aerosol optical depth (AOD) over BoB and AS regions. However, AOD was systematically underestimated during high-pollution episodes, especially in the BoB leg. We show that this underprediction of AOD is mostly because of the deficiencies in the coarse mode, where the model shows that dust is the dominant component. The analysis of dust AOD along with the OMI Aerosol Index indicate that missing dust transport that results from too low dust emission fluxes over the Thar Desert region in the model caused this deficiency. Thirdly, we analysed the spatio-temporal variability of AOD comparing the ship-based observations to the large-scale satellite observations and simulations. It was found that most of the variability along the track was from geographical patterns, with a minor influence by single events. Aerosol fields were homogeneous enough to yield a good statistical agreement between satellite data at a 1° spatial, but only twice-daily temporal resolution, and the shipbased sunphotometer data at a much finer spatial, but dailyaverage temporal resolution. Examination of the satellite data further showed that the year 2006 is representative for the five-year period for which satellite data were available. Finally, we estimated the clear-sky solar direct aerosol radiative forcing (DARF). We found that the cruise represents well the regional-seasonal mean forcings. Constraining simulated forcings using the observed AOD distributions yields a robust estimate of regional-seasonal mean DARF of −8.6, −21.4 and +12.9Wm−2 at the top of the atmosphere (TOA), at the surface (SUR) and in the atmosphere (ATM), respectively, for the BoB region, and over the AS, of, −6.8, −12.8, and +6Wm−2 at TOA, SUR, and ATM, respectively.

To date, no observation-based proxy for climate change has been successful in quantifying the feedbacks between clouds and climate. The most promising, yet demanding, avenue to gain confi dence in cloud–climate feedback estimates is to utilize observations and large-eddy simulations (LES) or cloud-resolving modeling (CRM) to improve cloud process parameterizations in large-scale models. Sustained and improved satellite observations are essential to evaluate large-scale models. A reanalysis of numerical prediction models with assimilation of cloud, aerosol, and precipitation observations would provide a valuable dataset for examining cloud interactions. The link between climate modeling and numerical weather prediction (NWP) may be exploited by evaluating how accurate cloud characteristics are represented by the parameterization schemes in NWP models. A systematic simplifi cation of large-scale models is an important avenue to isolate key processes linked to cloud–climate feedbacks and would guide the formulation of testable hypotheses for fi eld studies. Analyses of observation-derived correlations between cloud and aerosol properties in combination with modeling studies may allow aerosol–cloud interactions to be detected and quantifi ed. Reliable representations of cloud dynamic and physical processes in large-scale models are a prerequisite to assess aerosol indirect effects on a large scale with confi dence. To include aerosol indirect effects in a consistent manner, we recommend that a “radiative fl ux perturbation” approach be considered as a complement to radiative forcing.

Aerosols show type-specific characteristics, which depend on intensive aerosol optical and microphysical properties that influence the radiation processes in the atmosphere in several ways. There are still large uncertainties in the calculation of the aerosol direct radiative effect. The classification of aerosols and the characterization of the vertical aerosol distribution is needed in order to provide more accurate information for radiative-transfer simulations. In the framework of the present thesis, the vertical and spatial distribution as well as optical properties of atmospheric aerosols over the European continent were investigated based on lidar measurements. Possibilities for an aerosol classification or so-called aerosol typing were presented and major aerosol types were specified. Former studies about the classification of aerosols were summarized and representative values for aerosol-type-dependent parameters were given. Case studies were used to demonstrate how observations of the European lidar network EARLINET from 2008 until 2010 were analyzed for aerosol layers and how model simulations and auxiliary data including the assessment of meteorological conditions were applied to determine the origin of each single aerosol layer. Thus, aerosol-type dependent parameters were evaluated and a novel method for the typing of aerosols was developed, which can be used, e.g., within algorithms of satellite data retrievals. Additionally, conversion factors were determined, which are needed for the harmonization of satellite data of present and upcoming missions. Furthermore, findings of the aerosol typing based on EARLINET data were compared to results of the aerosol classification scheme for satellite-borne lidar measurements onboard CALIPSO. It could be shown that deficient classifications of the aerosol type emerged systematically within the automated CALIPSO algorithm. Those wrong classification leads to an underestimation of the single-scattering albedo and hence to an overestimation of the warming effect of the respective aerosol layer. This overestimated warming effect has to be kept in mind for simulations of the global aerosol radiative effect based on CALIPSO data. / Die Bestimmung des direkten Strahlungsantriebs von Aerosolen ist mit großen Unsicherheiten behaftet. Inwiefern Aerosole die Strahlungsprozesse in der Atmosphäre beeinflussen ist abhängig von ihren optischen und mikrophysikalischen Eigenschaften. Zur Optimierung von Strahlungstransfersimulationen werden daher ergänzende Informationen über typspezifische Aerosoleigenschaften sowie die vertikale Aerosolverteilung benötigt. Im Rahmen der vorliegenden Arbeit wurden anhand von Lidarmessungen die vertikale und räumliche Verteilung atmosphärischer Aerosole über Europa analysiert sowie deren optische Eigenschaften ermittelt. Einleitend werden Möglichkeiten der Aerosolklassifizierung erläutert und Aerosoltypen spezifiziert, die über Europa beobachtet werden können. Vorherige Studien zur Aerosolklassifizierung sind in einer Literaturübersicht zusammengefasst. Anhand von Fallstudien wurde zunächst die Analyse von Beobachtungen des europäischen Lidarnetzwerkes EARLINET von 2008 bis 2010 auf das Vorhandensein von Aerosolschichten verdeutlicht. Die Herkunft jeder einzelnen Aerosolschicht wurde anschließend unter Verwendung von Modellrechnungen sowie weiteren Informationen bestimmt und aerosoltypspezifische Kenngrößen berechnet. Mit Hilfe dieser Kenngrößen ist es möglich, den Typ des Aerosols abzuleiten. Daraus wurde eine neuartige Methode zur Typisierung von Aerosolen entwickelt, die z.B. in Algorithmen zur Verarbeitung von Satellitendaten verwendet werden kann. Zusätzlich wurden Umrechnungsfaktoren bestimmt, die zur Zusammenführung und zum Vergleich von Daten aktueller und zukünftiger Satellitenmissionen benötigt werden. Die Ergebnisse der Aerosoltypisierung auf Basis von EARLINET-Daten wurden anschließend mit Ergebnissen der automatischen Typisierung weltraumbasierter Lidarmessungen des CALIPSO-Satelliten verglichen. Es konnte gezeigt werden, dass innerhalb des CALIPSO-Algorithmus systematisch fehlerhafte Klassifizierungen des Aerosoltyps auftreten. Diese falsche Klassifizierung führt zu einer Unterschätzung der Einfachstreualbedo und zu einer Überschätzung der erwärmenden Wirkung der betreffenden Aerosolschicht. Die überschätzte Wärmewirkung hat wiederum fehlerhafte Ergebnisse bei Strahlungstransferrechnungen, die auf CALIPSO-Daten basieren, zur Folge.

Aerosol Partikel interagieren mit solarer und terrestrischer Strahlung durch Absorption und Streuung. Zusätzlich bilden und modifizieren sie die Eigenschaften von Wolken da sie das Potential besitzen als Wolkenkondensationskeim (CCN) fungieren zu können und stellen somit eine wichtige Komponente im Klimasystem dar. Die Eigenschaften von Partikeln und CCN müssen genaustens bekannt sein um deren Einfluss in Klima- und Strahlungsmodellen akurat berücksichtigen zu können. Ziel dieser Arbeit ist die Charakterisierung der Partikeleigenschaften in Regionen, welche das Klima maßgeblich beeinflussen, wie die Arktis und die Antarktis. Im Rahmen dieser Arbeit wurden 2 Datensätze aufgenommen, welche helfen das Verständnis über Partikel und CCN im Frühjar und Sommer in der Arktis und Antarktis zu verbessern. Es wurden jeweils die Gesamt- und die CCN-Anzahlkonzentration (NCN, NCCN), die Anzahlgrößenverteilung (PNSD) und der Hygroskopizitätsparameter (k) der Partikel bestimmt. Die Herkunft der vermessenen Partikel wurde mit Rückwärtstrajektorien ermittelt sowie weitere Analysen bezüglich der Verweilzeiten durchgeführt. Beide Datensätze zeigen, dass eine starke Abhängigkeit der Partikel- und CCN-Eigenschaften vom Luftmassenursprung vorliegt. Zeigen arktische PNSDs nur eine Akkumulationsmode, konnte diese auf gealtertes Aerosol mit einem eurasischen Ursprung zurückgeführt werden. Kommt eine zweite Mode mit kleineren Partikeln hinzu, wurde der Nord-Pazifische Raum als Ursprung bestimmt. In der Antarktis wurde besonders für NCN und NCCN eine starke Abhängigkeit vom Luftmassenursprung gefunden. Dabei konnten mit der Anwendung des Dispersionsmodells NAME Antarktische Hintergrundkonzentrationen ermittelt werden. Weiterhin wurde gefunden, dass Antarktische Aerosolpartikel mit einem k von 1 hygroscopischer als das Arktische ist, für welches ein k von 0,19 bestimmt wurde. Zusätzlich durchgeführte Flugzeugmessungen über Tuktoyaktuk (Arktis) zeigen, dass die Messungen am Boden auch repräsentativ für die Grenzschicht sind. Die Schichten über der Grenzschicht scheinen jedoch von dieser entkoppelt zu sein und es wird vermutet, dass der Ursprung der Partikel in größeren Höhen in niedrigeren geographischen Breiten liegt.:Contents List of Abbreviations iii List of Symbols v 1. Introduction 1 2. Experimental 9 2.1. Measured Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1. Total Particle Number Concentration . . . . . . . . . . . . . . . 9 2.1.2. Particle Number Size Distribution . . . . . . . . . . . . . . . . . 10 2.1.3. Total Concentration of Cloud Condensation Nuclei . . . . . . . . 15 2.2. Determination of the CCN hygroscopicity . . . . . . . . . . . . . . . . . 16 2.2.1. Köhler theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.2. The hygroscopicity parameter k and the critical diameter dcrit . . 18 2.3. Determination of the Air Mass Origin . . . . . . . . . . . . . . . . . . . 20 2.3.1. The NAME Dispersion Model . . . . . . . . . . . . . . . . . . . 20 2.3.2. Potential Source Contribution Function . . . . . . . . . . . . . . 22 3. Results and Discussion 25 3.1. Measurements of aerosol and CCN properties in the Mackenzie River delta (Canadian Arctic) during Spring-Summer transition in May 2014 . . 25 3.1.1. Campaign overview . . . . . . . . . . . . . . . . . . . . . . . . 25 3.1.2. Overview of NCN, NCCN and PNSD data for the entire measurement period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1.3. Identification of air mass origins and potential source regions . . . 32 3.1.4. PNSD of the three periods . . . . . . . . . . . . . . . . . . . . . 35 3.1.5. Critical diameter dcrit and hygroscopicity parameter k . . . . . . 38 3.1.6. Comparison of height resolved airborne and ground based PNSDs 41 3.2. Measurements of aerosol and CCN properties at the Princess Elisabeth Antarctica Research Station during three austral summers . . . . . . . . . 45 3.2.1. Campaign overview . . . . . . . . . . . . . . . . . . . . . . . . 45 3.2.2. Total Particle and CCN number concentrations and regional analysis of the NAME model footprints . . . . . . . . . . . . . . . . 50 3.2.3. PSCF results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3.2.4. Hygroscopicity . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 4. Summary, Conclusions and Outlook 65 A. Appendix 71 A.1. SS calibration of the CCNC . . . . . . . . . . . . . . . . . . . . . . . . . 71 A.2. Error Analysis with Monte Carlo Simulation . . . . . . . . . . . . . . . . 73 B List of Figures vii C List of Tables viii Bibliography xi / Atmospheric aerosol particles interact with solar and terrestrial radiation by absorption and scattering. Further, they have the potential to act as cloud condensation nuclei (CCN) and to form and modify the radiative properties of clouds and thus are an important component in the Earth’s climate system. An accurate knowledge about the aerosol particle and CCN properties is very important for accurate climate and radiation models. The objective of this thesis is the characterization of aerosol particles in regions that are key regulators of the Earth’s climate. The Arctic and the Antarctic are such regions. Hence, in the framework of this doctoral thesis two data sets were recorded, that help gaining further knowledge about the spring and summer time aerosol particles and CCN in the Arctic and Antarctic region. For both, the Arctic and the Antarctic aerosol population, the CCN and the total particle number concentration (NCCN, NCN), the particle number size distribution (PNSD) and the hygroscopicity parameter k were determined. The history of the measured air masses was explored using back trajectories and residence time analysis. For both examined regions, a strong influence of the air mass origin on the aerosol particle and CCN properties was found. The PNSDs measured in the Arctic were found to be mono-modal showing an accumulation mode which most likely contains well aged particles that have an Eurasian origin. Bi-modal PNSDs with an additional mode of smaller particles were found to originate from the Northern Pacific. In the Antarctic the air mass origin was found to significantly influence NCCN and NCN. With the application of the NAME dispersion model Antarctic continental background concentrations could be determined. With k values of 1 the Antarctic aerosol was found to be much more hygroscopic than the Arctic aerosol, for which a k of 0.19 was determined. Additional Arctic aircraft measurements show that ground based measurements are representative for the Arctic boundary layer. However particles above the boundary layer seem to be decoupled from lower layers and were believed to be advected from lower latitudes in different height layers and mixed down in the lower Arctic troposphere.:Contents List of Abbreviations iii List of Symbols v 1. Introduction 1 2. Experimental 9 2.1. Measured Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1. Total Particle Number Concentration . . . . . . . . . . . . . . . 9 2.1.2. Particle Number Size Distribution . . . . . . . . . . . . . . . . . 10 2.1.3. Total Concentration of Cloud Condensation Nuclei . . . . . . . . 15 2.2. Determination of the CCN hygroscopicity . . . . . . . . . . . . . . . . . 16 2.2.1. Köhler theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.2. The hygroscopicity parameter k and the critical diameter dcrit . . 18 2.3. Determination of the Air Mass Origin . . . . . . . . . . . . . . . . . . . 20 2.3.1. The NAME Dispersion Model . . . . . . . . . . . . . . . . . . . 20 2.3.2. Potential Source Contribution Function . . . . . . . . . . . . . . 22 3. Results and Discussion 25 3.1. Measurements of aerosol and CCN properties in the Mackenzie River delta (Canadian Arctic) during Spring-Summer transition in May 2014 . . 25 3.1.1. Campaign overview . . . . . . . . . . . . . . . . . . . . . . . . 25 3.1.2. Overview of NCN, NCCN and PNSD data for the entire measurement period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1.3. Identification of air mass origins and potential source regions . . . 32 3.1.4. PNSD of the three periods . . . . . . . . . . . . . . . . . . . . . 35 3.1.5. Critical diameter dcrit and hygroscopicity parameter k . . . . . . 38 3.1.6. Comparison of height resolved airborne and ground based PNSDs 41 3.2. Measurements of aerosol and CCN properties at the Princess Elisabeth Antarctica Research Station during three austral summers . . . . . . . . . 45 3.2.1. Campaign overview . . . . . . . . . . . . . . . . . . . . . . . . 45 3.2.2. Total Particle and CCN number concentrations and regional analysis of the NAME model footprints . . . . . . . . . . . . . . . . 50 3.2.3. PSCF results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3.2.4. Hygroscopicity . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 4. Summary, Conclusions and Outlook 65 A. Appendix 71 A.1. SS calibration of the CCNC . . . . . . . . . . . . . . . . . . . . . . . . . 71 A.2. Error Analysis with Monte Carlo Simulation . . . . . . . . . . . . . . . . 73 B List of Figures vii C List of Tables viii Bibliography xi

Au cours des dernières décennies, les communautés de recherches océanographiques et atmosphérique ont démontrées que pour améliorer notre compréhension du couplage entre l'atmosphère et l'océan, et le paramétrage du flux de masse entre l'océan et l'atmosphère (gaz, aérosols, par exemple) , de moment (pour la génération de vagues et de courants marins) et d'énergie (flux de chaleur et énergie cinétique pour les courants et le processus de mélange près de la surface ) dans les modèles couplés océan-atmosphère, les vagues doivent être prises en compte. La physique du couplage dépend de la cinématique et de la dynamique du champ de vagues, y compris les processus de génération de vagues liées au vent, les interactions non-linéaires, ondes-ondes et la dissipation des vagues, cette dernière étant normalement considérée comme dominée par le déferlement. Nous présentons ici une série d'études expérimentales et numériques, démontrant l'importance du champ de vagues sur les interactions océan - atmosphère. / Over the last several decades there has been growing recognition from both the traditional oceanographic and atmospheric science communities that to better understand the coupling between the atmosphere and the ocean, and reflect that understanding in improved air-sea fluxes of mass (e.g. gases, aerosols), momentum (e.g. generation of waves and currents) and energy (e.g. heat and kinetic energy for currents and mixing) in coupled ocean-atmosphere models, surface-wave processes must be taken into account. The underlying physics of the coupling depends on the kinematics and dynamics of the wave field, including processes of wind-wave growth, nonlinear wave-wave interactions, wave-current interactions and wave dissipation, with the last normally considered dominated by wave breaking. Here we present a series of experiments, both numerical and field observations, focusing on surface wave effects on air-sea interaction processes.

This article gives an overview of the DACAPO-PESO field experiment, which has taken place in Punta Arenas, Chile, from November 2018 to November 2021, and showcases first exciting research results that have already emerged from it. / In diesem Artikel wird ein Überblick über das DACAPO-PESO Experiment gegeben, welches von November 2018 bis November 2021 in Punta Arenas, Chile, stattgefunden hat. Außerdem werden erste spannende Forschungsergebnisse vorgestellt, die bereits daraus gewonnen wurden.

Thesis: M.S., Massachusetts Institute of Technology, Department of Chemical Engineering, 1975 / Includes bibliographical references. / M.S. / M.S. Massachusetts Institute of Technology, Department of Chemical Engineering

To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (τD) and coarse-(τPC) and fine-pollution particles (τPF) depending on emission sources and size. Ångström exponent values are also identified separately as total and fine-mode particles (αT and αPF). We checked these trends in various ways; (1) first-order linear regression analysis of the annual average values, (2) percent variation using the slope of linear regression method, and (3) a reliability analysis using the Mann–Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. Although there were regional differences, τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of τPC and τPF, show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular, τPF considerably decreased in Europe and Northeast Asia (95% confidential levels in MK-test), and τPC decreased in Northeast Asia (Z-values for Seoul and Osaka are −2.955 and −2.306, respectively, statistically significant if |z| ≥ 1.96). The decrease in τPC seems to be because of the reduction of primary and anthropogenic emissions from regulation by air quality policies. The meaningful result in this paper is that the particle size became smaller, as seen by values of αT that decreased by −3.30 to −30.47% in Europe, North Africa, and the Middle East because αT provides information on the particle size. Particle size on average became smaller over India and Asian regions considered in our study due to the decrease in coarse particles. In particular, an increase of αPF in most areas shows the probability that the average particle size of fine-mode aerosols became smaller in recent years. We presumed the cause of the increase in αT is because relatively large-sized fine-mode particles were eliminated due to air quality policies.

<p>The uncertainty of the climate and health effects of aerosols is still large, one important reason being lack of knowledge of the primary emissions. This thesis combines laboratory and field experiments, and process modelling in an effort to better quantify the submicrometre aerosol emissions and to understand some of the processes in the atmosphere.</p><p>A parameterisation was derived for the source flux of sea salt particles (particles m^-2s^-1) in the size range 0.02-2.8 µm dry diameter (D_p), it is the first parameterisation to almost cover two full decades of the submicrometre sea salt aerosol production, and to include the effect of water temperature. This sea salt parameterisation was validated for temperate water in the 0.1-1.1 μm D_p range using in situ size resolved emissions of marine aerosol particles, which were measured with the eddy covariance (EC) method. For periods sampled air was heated to 300ºC in order to evaporate semi-volatile organics and isolate the sea salt fraction. Comparisons with the total aerosol emissions suggest that in these emissions organic carbon and sea salt are internally mixed in the same particles. Finally an aerosol dynamics model was modified for marine conditions. In the model parameterised emissions of sea salt was included together with aerosol dynamics, chemistry and clouds representative for the marine boundary layer. The sea salt emissions are together with secondary sulphate, and cloud processing able to reproduce a typical marine aerosol size distribution and cloud condensation nuclei population.</p><p>Measurements with the EC method of the road traffic related aerosol source number flux for D_p>0.011 µm show that the major part of the aerosol fluxes is due to road traffic emissions. Both an emission factor for the whole fleet mix in Stockholm (1.4x10¹⁴ vehicle^-1 km^-1) and separate emission factors for light- and heavy-duty vehicles (HDV) were deduced. The result shows that during weekdays 70-80% of the emissions come from HDV.</p>