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Urban air pollutant concentrations are highly variable both in space and time. In order to understand these variabilities high-resolution measurements of air pollutants are needed. Here we present results of a mobile laboratory and a drone measurements made within a street-canyon network in Helsinki, Finland, in summer and winter 2017. The mobile laboratory measured the total number concentration (N) and lung-deposited surface area (LDSA) of aerosol particles, and the concentrations of black carbon, nitric oxide (NOx) and ozone (O3). The drone measured the vertical profile of LDSA. The main aims were to examine the spatial variability of air pollutants in a wide street canyon and its immediate surroundings, and find the controlling environmental variables for the observed variability's. The highest concentrations with the most temporal variability were measured at the main street canyon when the mobile laboratory was moving with the traffic fleet for all air pollutants except O3. The street canyon concentration levels were more affected by traffic rates whereas on surrounding areas, meteorological conditions dominated. Both the mean flow and turbulence were important, the latter particularly for smaller aerosol particles through LDSA and N. The formation of concentration hotspots in the street network were mostly controlled by mechanical processes but in winter thermal processes became also important for aerosol particles. LDSA showed large variability in the profile shape, and surface and background concentrations. The expected exponential decay functions worked better in well-mixed conditions in summer compared to winter. We derived equation for the vertical decay which was mostly controlled by the air temperature. Mean wind dominated the profile shape over both thermal and mechanical turbulence. This study is among the first experimental studies to demonstrate the importance of high-resolution measurements in understanding urban pollutant variability in detail. publishedVersion

Atmospheric gas-to-particle conversion is a crucial or even dominant contributor to haze formation in Chinese megacities in terms of aerosol number, surface area and mass. Based on our comprehensive observations in Beijing during 15 January 2018-31 March 2019, we are able to show that 80-90% of the aerosol mass (PM2.5) was formed via atmospheric reactions during the haze days and over 65% of the number concentration of haze particles resulted from new particle formation (NPF). Furthermore, the haze formation was faster when the subsequent growth of newly formed particles was enhanced. Our findings suggest that in practice almost all present-day haze episodes originate from NPF, mainly since the direct emission of primary particles in Beijing has considerably decreased during recent years. We also show that reducing the subsequent growth rate of freshly formed particles by a factor of 3-5 would delay the buildup of haze episodes by 1-3 days. Actually, this delay would decrease the length of each haze episode, so that the number of annual haze days could be approximately halved. Such improvement in air quality can be achieved with targeted reduction of gas-phase precursors for NPF, mainly dimethyl amine and ammonia, and further reductions of SO2 emissions. Furthermore, reduction of anthropogenic organic and inorganic precursor emissions would slow down the growth rate of newly-formed particles and consequently reduce the haze formation.

We investigate the boundary-layer (BL) height at Hyytiälä in southern Finland diagnosed from radiosonde observations, a microwave radiometer (MWR) and ERA5 reanalysis. Four different, pre-existing algorithms are used to diagnose the BL height from the radiosondes. The diagnosed BL height is sensitive to the method used. The level of agreement, and the sign of systematic bias between the four different methods, depends on the surface-layer stability. For very unstable situations, the median BL height diagnosed from the radiosondes varies from 600 to 1500 m depending on which method is applied. Good agreement between the BL height in ERA5 and diagnosed from the radiosondes using Richardson-number-based methods is found for almost all stability classes, suggesting that ERA5 has adequate vertical resolution near the surface to resolve the BL structure. However, ERA5 overestimates the BL height in very stable conditions, highlighting the ongoing challenge for numerical models to correctly resolve the stable BL. Furthermore, ERA5 BL height differs most from the radiosondes at 18:00 UTC, suggesting ERA5 does not resolve the evening transition correctly. BL height estimates from the MWR are also found to be reliable in unstable situations but often are inaccurate under stable conditions when, in comparison to ERA5 BL heights, they are much deeper. The errors in the MWR BL height estimates originate from the limitations of the manufacturer's algorithm for stable conditions and also the misidentification of the type of BL. A climatology of the annual and diurnal cycle of BL height, based on ERA5 data, and surface-layer stability, based on eddy covariance observations, was created. The shallowest (353 m) monthly median BL height occurs in February and the deepest (576 m) in June. In winter there is no diurnal cycle in BL height; unstable BLs are rare, yet so are very stable BLs. The shallowest BLs occur at night in spring and summer, and very stable conditions are most common at night in the warm season. Finally, using ERA5 gridded data, we determined that the BL height observed at Hyytiälä is representative of most land areas in southern and central Finland. However, the spatial variability of the BL height is largest during daytime in summer, reducing the area over which BL height observations from Hyytiälä would be representative.

Cities have become increasingly interested in reducing their greenhouse gas emissions and increasing carbon sequestration and storage in urban vegetation and soil as part of their climate mitigation actions. However, most of our knowledge of the biogenic carbon cycle is based on data and models from forested ecosystems, despite urban nature and microclimates differing greatly from those in natural or forested ecosystems. There is a need for modelling tools that can correctly consider temporal variations in the urban carbon cycle and take specific urban conditions into account. The main aims of our study were to (1) examine the carbon sequestration potential of two commonly used street tree species (Tilia × vulgaris and Alnus glutinosa) growing in three different growing media by taking into account the complexity of urban conditions and (2) evaluate the urban land surface model SUEWS (Surface Urban Energy and Water Balance Scheme) and the soil carbon model Yasso15 in simulating the carbon sequestration of these street tree plantings at temporal scales (diurnal, monthly, and annual). SUEWS provides data on the urban microclimate and on street tree photosynthesis and respiration, whereas soil carbon storage is estimated with Yasso. These models were used to study the urban carbon cycle throughout the expected lifespan of street trees (2002–2031). Within this period, model performances were evaluated against transpiration estimated from sap flow, soil carbon content, and soil moisture measurements from two street tree sites located in Helsinki, Finland. The models were able to capture the variability in the urban carbon cycle and transpiration due to changes in environmental conditions, soil type, and tree species. Carbon sequestration potential was estimated for an average street tree and for the average of the diverse soils present in the study area. Over the study period, soil respiration dominated carbon exchange over carbon sequestration due to the high initial carbon loss from the soil after street construction. However, the street tree plantings turned into a modest sink of carbon from the atmosphere on an annual scale, as tree and soil respiration approximately balanced the photosynthesis. The compensation point when street tree plantings turned from an annual source into a sink was reached more rapidly – after 12 years – by Alnus trees, while this point was reached by Tilia trees after 14 years. However, these moments naturally vary from site to site depending on the growing media, planting density, tree species, and climate. Overall, the results indicate the importance of soil in urban carbon sequestration estimations.

The structure of the urban boundary layer, and particularly the surface layer, displays significant complexity, which can be exacerbated by coastal effects for cities located in coastal regions. Resolving the complexity of the coastal urban boundary layer remains an important question for many applications such as air quality and numerical weather prediction. One of the most promising new techniques for measuring the structure of the surface layer is fibre-optic distributed temperature sensing (DTS), which has the potential to provide new significant insights for boundary layer meteorology by making it possible to study thermal turbulence with high spatial and temporal resolution. We present 14 weeks of profile measurements with a DTS system at an urban site in Helsinki, Finland, during the winter and spring of 2020. We assess the benefits and drawbacks of using DTS measurements to supplement sonic anemometry for longer measurement periods in varying meteorological conditions, including those found difficult for the DTS method in prior studies. Furthermore, we demonstrate the capabilities of the DTS system using two case scenarios: a study of the erosion of a near-ground cold layer during the passage of a warm front, and a comparison of the near-ground thermal structure with and without the presence of a sea-breeze cell during springtime convective boundary layer development. This study demonstrates the utility of DTS measurements in revealing the internal surface layer structure, beyond the predictions of traditional surface layer theories. This knowledge is important for improving surface layer theories and parametrisations, including those used in numerical weather prediction. The study also highlights the drawbacks of DTS measurements, caused by low signal-to-noise ratios in near-neutral atmospheric conditions, especially when such a system would be used to supplement turbulence measurements over longer periods. Overall, this study presents important considerations for planning new studies or ongoing measurements utilising this exciting and relatively new instrumentation.

Water storage plays an important role in mitigating heat and flooding in urban areas. Assessment of the water storage capacity of cities remains challenging due to the inherent heterogeneity of the urban surface. Traditionally, effective storage has been estimated from runoff. Here, we present a novel approach to estimate effective water storage capacity from recession rates of observed evaporation during precipitation-free periods. We test this approach for cities at neighborhood scale with eddy-covariance based latent heat flux observations from 14 contrasting sites with different local climate zones, vegetation cover and characteristics, and climates. Based on analysis of 583 drydowns, we find storage capacities to vary between 1.3 and 28.4 mm, corresponding to e-folding timescales of 1.8-20.1 days. This makes the urban storage capacity at least five times smaller than all the observed values for natural ecosystems, reflecting an evaporation regime characterized by extreme water limitation.

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3–7 and 7–15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.

International audience; The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO2 emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO2 fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

This work was supported by the Spanish Ministry of Economy and Competitiveness through projects PID2020-120015RB-100, CGL201681092-R, and CGL2017-90884-REDT, by the Andalusia Regional Government through project P18-RT-3820 and P20-00136, by the European Union's Horizon 2020 research and innovation program through project ACTRIS-2 (grant agreement No 654109). This research was partially supported by Project RTI2018.101154.A.I00 funded by MCIN/AEI/10.13039/501100011033/FEDER "Una manera de hacer Europa". The authors thank the Parque de la Ciencias for making this research possible. Juan Andr ' es Casquero-Vera is supported by BES-2017-080015 funded by MCIN/AEI/10.13039/501100011033 and FSE "El FSE invierte en tu futuro". Funding for open access charge: Universidad de Granada/CBUA., Although cities are an important source of aerosol particles, aerosol number flux measurements over urban areas are scarce. These measurements are however important as they can allow us to identify the different sources/sinks of aerosol particles and quantify their emission contributions. Therefore, they can help us to understand the aerosol impacts on human health and climate, and to design effective mitigation strategies through the reduction of urban aerosol emissions. In this work we analyze the aerosol number concentrations and fluxes for particles with diameters larger than 2.5 nm measured by eddy covariance technique at an urban area (Granada city, Spain) from November 2016 to April 2018. This is the first study of particle number flux in an urban area in the Iberian Peninsula and is one of the few current studies that report long-term aerosol number flux measurements. The results suggest that, on average, Granada urban area acted as a net source for atmospheric aerosol particles with median particle number flux of 150 x 10(6) m(-2) s(-1). Downward negative fluxes were observed in only 12% of the analyzed data, and most of them were observed during high aerosol load conditions. Both aerosol number fluxes and concentrations were maximum in winter and 50% larger than those measured in summer due to the increased emissions from domestic heating, burning of residual agricultural waste in the agricultural area surrounding the site, as well as to the lower aerosol dilution effects during winter. The analysis of the seasonal diurnal variability of the aerosol number concentration revealed the significant impact of traffic emissions on aerosol population over Granada urban area in all seasons. It also shows the impact of domestic heating and agricultural waste burning emissions in winter as well as the influence of new particle formation processes in summer and spring seasons. Closer analysis by wind sector demonstrated that both aerosol concentrations and fluxes from urban sector (where high density of anthropogenic sources is located) were lower than those from rural sector (which includes agricultural area but also the main highway of the city). This evidences the strong impact of aerosol emissions from traffic circulating on the highway on aerosol population over our measurement site., Spanish Government PID2020-120015RB-100 CGL201681092-R CGL2017-90884-REDT, Andalusia Regional Government P18-RT-3820 P20-00136, European Commission 654109, MCIN/AEI/FEDER "Una manera de hacer Europa" RTI2018.101154.A.I00, FSE "El FSE invierte en tu futuro", Universidad de Granada/CBUA MCIN/AEI BES-2017-080015

Urban pedestrian-level air quality is a result of an interplay between turbulent dispersion conditions, background concentrations, and heterogeneous local emissions of air pollutants and their transformation processes. Still, the complexity of these interactions cannot be resolved by the commonly used air quality models. By embedding the sectional aerosol module SALSA2.0 into the large-eddy simulation model PALM, a novel, high-resolution, urban aerosol modelling framework has been developed. The first model evaluation study on the vertical variation of aerosol number concentration and size distribution in a simple street canyon without vegetation in Cambridge, UK, shows good agreement with measurements, with simulated values mainly within a factor of 2 of observations. Dispersion conditions and local emissions govern the pedestrian-level aerosol number concentrations. Out of different aerosol processes, dry deposition is shown to decrease the total number concentration by over 20 %, while condensation and dissolutional increase the total mass by over 10 %. Following the model development, the application of PALM can be extended to local- and neighbourhood-scale air pollution and aerosol studies that require a detailed solution of the ambient flow field. © 2019. This work is distributed under the Creative Commons Attribution 4.0 License.

In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O-3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism.

The role of new particle formation (NPF) events and their contribution to haze formation through subsequent growth in polluted megacities is still controversial. To improve the understanding of the sources, meteorological conditions, and chemistry behind air pollution, we performed simultaneous measurements of aerosol composition and particle number size distributions at ground level and at 260 m in central Beijing, China, during a total of 4 months in 2015–2017. Our measurements show a pronounced decoupling of gas-to-particle conversion between the two heights, leading to different haze processes in terms of particle size distributions and chemical compositions. The development of haze was initiated by the growth of freshly formed particles at both heights, whereas the more severe haze at ground level was connected directly to local primary particles and gaseous precursors leading to higher particle growth rates. The particle growth creates a feedback loop, in which a further development of haze increases the atmospheric stability, which in turn strengthens the persisting apparent decoupling between the two heights and increases the severity of haze at ground level. Moreover, we complemented our field observations with model analyses, which suggest that the growth of NPF-originated particles accounted up to ∼60% of the accumulation mode particles in the Beijing–Tianjin–Hebei area during haze conditions. The results suggest that a reduction in anthropogenic gaseous precursors, suppressing particle growth, is a critical step for alleviating haze although the number concentration of freshly formed particles (3–40 nm) via NPF does not reduce after emission controls.

Intense and frequent new particle formation (NPF) events have been observed in polluted urban environments, yet the dominant mechanisms are still under debate. To understand the key species and governing processes of NPF in polluted urban environments, we conducted comprehensive measurements in downtown Beijing during January–March, 2018. We performed detailed analyses on sulfuric acid cluster composition and budget, as well as the chemical and physical properties of oxidized organic molecules (OOMs). Our results demonstrate that the fast clustering of sulfuric acid (H2SO4) and base molecules triggered the NPF events, and OOMs further helped grow the newly formed particles toward climate- and health-relevant sizes. This synergistic role of H2SO4, base species, and OOMs in NPF is likely representative of polluted urban environments where abundant H2SO4 and base species usually co-exist, and OOMs are with moderately low volatility when produced under high NOx concentrations. publishedVersion

Trees and other vegetation have been advocated as a mitigation measure for urban air pollution mainly due to the fact that they passively filter particles from the air. However, mounting evidence suggests that vegetation may also worsen air quality by slowing the dispersion of pollutants and by producing volatile organic compounds that contribute to formation of ozone and other secondary pollutants. We monitored nanoparticle (>10 nm) counts along distance gradients away from major roads along paired transects across open and forested landscapes in Baltimore (USA), Helsinki (Finland) and Shenyang (China) − i.e. sites in three biomes with different pollution levels − using condensation particle counters. Mean particle number concentrations averaged across all sampling sites were clearly reduced (15 %) by the presence of forest cover only in Helsinki. For Baltimore and Shenyang, levels showed no significant difference between the open and forested transects at any of the sampling distances. This suggests that nanoparticle deposition on trees is often counterbalanced by other factors, including differing flow fields and aerosol processes under varying meteorological conditions. Similarly, consistent differences in high frequency data patterns between the transects were detected only in Helsinki. No correlations between nanoparticle concentrations and solar radiation or local wind speed as affecting nanoparticle abundances were found, but they were to some extent associated with canopy closure. These data add to the accumulating evidence according to which trees do not necessarily improve air quality in near-road environments. Trees and other vegetation have been advocated as a mitigation measure for urban air pollution mainly due to the fact that they passively filter particles from the air. However, mounting evidence suggests that vegetation may also worsen air quality by slowing the dispersion of pollutants and by producing volatile organic compounds that contribute to formation of ozone and other secondary pollutants. We monitored nanoparticle (>10 nm) counts along distance gradients away from major roads along paired transects across open and forested landscapes in Baltimore (USA), Helsinki (Finland) and Shenyang (China) − i.e. sites in three biomes with different pollution levels − using condensation particle counters. Mean particle number concentrations averaged across all sampling sites were clearly reduced (15 %) by the presence of forest cover only in Helsinki. For Baltimore and Shenyang, levels showed no significant difference between the open and forested transects at any of the sampling distances. This suggests that nanoparticle deposition on trees is often counterbalanced by other factors, including differing flow fields and aerosol processes under varying meteorological conditions. Similarly, consistent differences in high frequency data patterns between the transects were detected only in Helsinki. No correlations between nanoparticle concentrations and solar radiation or local wind speed as affecting nanoparticle abundances were found, but they were to some extent associated with canopy closure. These data add to the accumulating evidence according to which trees do not necessarily improve air quality in near-road environments.

A new aerosol component approach that infers aerosol species fractions from satellite observations was developed and incorporated by Li et al. (2019) into Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm. In the current work we employ this aerosol component approach for derivation and analysis of temporal and spatial characteristics of black and brown carbon (BC and BrC) concentrations in East and South Asia using POLDER/PARASOL satellite observations during 2005–2013. The inter-comparison of the satellite retrieved and in situ measured BC in China shows a reasonably good agreement for both monthly averaged and daily values. The distribution of light-absorbing carbon (BC and BrC) shows a significant temporal variation cycle with increases matching the months known for strong biomass burning or fossil fuels combustion emissions. The main concentrations of BC are found near the fire or anthropogenic emission regions, while concentrations of BrC are predominantly distanced from the emission sources. Seasonal means of BC/(BC + BrC) ratio in East and South Asia are also presented. High ratios (above 0.5) in Northeast India and North China during December, January, and February can be attributed to fossil fuels combustion and anthropogenic emissions. Medium ratios (around 0.2–0.3) over the Indo-China Peninsula and Northeast China during March, April, and May are associated with the biomass burning (e.g., forest fires, agriculture waste burning). The provided observationally-based retrievals of BC, BrC, and BC/(BC + BrC) are believed to be of high importance for constraining the aerosol modeling and reducing the uncertainties of the model estimations.

Running large-eddy simulations (LESs) can be burdensome and computationally too expensive from the application point of view, for example, to support urban planning. In this study, regression models are used to replicate modelled air pollutant concentrations from LES in urban boulevards. We study the performance of regression models and discuss how to detect situations where the models are applied outside their training domain and their outputs cannot be trusted. Regression models from 10 different model families are trained and a cross-validation methodology is used to evaluate their performance and to find the best set of features needed to reproduce the LES outputs. We also test the regression models on an independent testing dataset. Our results suggest that in general, log-linear regression gives the best and most robust performance on new independent data. It clearly outperforms the dummy model which would predict constant concentrations for all locations (multiplicative minimum RMSE (mRMSE) of 0.76 vs. 1.78 of the dummy model). Furthermore, we demonstrate that it is possible to detect concept drift, i.e. situations where the model is applied outside its training domain and a new LES run may be necessary to obtain reliable results. Regression models can be used to replace LES simulations in estimating air pollutant concentrations, unless higher accuracy is needed. In order to have reliable results, it is however important to do the model and feature selection carefully to avoid overfitting and to use methods to detect the concept drift.

International audience; The climatological characteristics of total aerosol optical thickness (AOT) together with fine and coarse mode AOT (fAOT and cAOT) and fine mode fraction (FMF ¼ fAOT/AOT) over East and South Asia are presented here for the period March 2005 to October 2013. The characteristics are retrieved from POLDER/PARASOL measurements using recently developed aerosol component module of GRASP algorithm. The satellite retrievals were validated and presented a good agreement with the AERONET products (e.g., R of~0.8-0.9 for AOT, fAOT, Ångström exponent, and FMF). The results show a seasonal cycle and strong relation to the emission sources. For example, FMF has a peak of nearly 1.0 in March in the Indo-China Peninsula region, reaching a minimum of about 0.4 in April in Northwestern China region. These patterns can be explained by dominance of anthropogenic pollution or desert dust emissions. Maps of fine, coarse, and total AOT, as well as of FMF for the East and South Asia region, are presented and analyzed in scope of seasonal and interannual variabilities.

The choice of coordinate system to calculate eddy covariance fluxes becomes particularly relevant at complex measurement sites. The traditional way is to perform double rotation (DR) of the coordinate system i.e., to calculate turbulent fluxes in a coordinate system that is aligned with the flow streamlines within the flux averaging period (e.g., Kaimal and Finnigan, 1994). The second approach, the so-called planar-fitted (PF) coordinate system, averages the flow over a longer period of time, in practice a month or more. The PF method allows to derive an intercept coefficient of the vertical wind speed which can be attributed to the offset of the sonic anemometer or the average vertical flow related to meteorological conditions. We evaluated the variants of the PF methods using data from a variety of sites ranging from complex urban and forest sites to nearly ideal forest and peatland sites. At complex sites, we found that the intercept of the vertical wind speed derived from the PF method is a function of wind direction, time of day and/or stability. The sector-wise PF (SPF) method frequently led to insignificant statistical relationships. We tested a continuous PF (CPF) method where the relationship establishing the coordinate frame was represented as the continuous function in the form of Fourier series. The method enabled to obtain the PF with lower uncertainty as compared to the SPF method, by selecting necessary number of harmonics for each site based on confidence intervals of estimated parameters. Therefore, we recommend to use the CPF method in cases when the number of observations in some wind direction interval is low or the obtained SPF is insignificant due to large variance in measurements. We also showed that significant systematic difference can exist in cumulative turbulent fluxes between the DR and PF methods over a longer period of time. Derived vertical advection of carbon dioxide exhibited large variability with wind direction due to topography at complex sites and therefore, without considering horizontal advection, cannot be used to improve the net ecosystem exchange estimation during nocturnal, low turbulence conditions.

High-resolution modelling is needed to understand urban air quality and pollutant dispersion in detail. Recently, the PALM model system 6.0, which is based on large-eddy simulation (LES), was extended with the detailed Sectional Aerosol module for Large Scale Applications (SALSA) v2.0 to enable studying the complex interactions between the turbulent flow field and aerosol dynamic processes. This study represents an extensive evaluation of the modelling system against the horizontal and vertical distributions of aerosol particles measured using a mobile laboratory and a drone in an urban neighbourhood in Helsinki, Finland. Specific emphasis is on the model sensitivity of aerosol particle concentrations, size distributions and chemical compositions to boundary conditions of meteorological variables and aerosol background concentrations. The meteorological boundary conditions are taken from both a numerical weather prediction model and observations, which occasionally differ strongly. Yet, the model shows good agreement with measurements (fractional bias , normalised mean squared error , fraction of the data within a factor of 2 >0.3, normalised mean bias factor and normalised mean absolute error factor ) with respect to both horizontal and vertical distribution of aerosol particles, their size distribution and chemical composition. The horizontal distribution is most sensitive to the wind speed and atmospheric stratification, and vertical distribution to the wind direction. The aerosol number size distribution is mainly governed by the flow field along the main street with high traffic rates and in its surroundings by the background concentrations. The results emphasise the importance of correct meteorological and aerosol background boundary conditions, in addition to accurate emission estimates and detailed model physics, in quantitative high-resolution air pollution modelling and future urban LES studies.

Ultrafine particles (UFP) are suspected of having significant impacts on health. However, there have only been a limited number of studies on sources of UFP compared to larger particles. In this work, we identified and quantified the sources and processes contributing to particle number size distributions (PNSD) using Positive Matrix Factorization (PMF) at six monitoring stations (four urban background and two street canyon) from four European cities: Barcelona, Helsinki, London, and Zurich. These cities are characterised by different meteorological conditions and emissions. The common sources across all stations were Photonucleation, traffic emissions (3 sources, from fresh to aged emissions: Traffic nucleation, Fresh traffic - mode diameter between 13 and 37 nm, and Urban - mode diameter between 44 and 81 nm, mainly traffic but influenced by other sources in some cities), and Secondary particles. The Photonucleation factor was only directly identified by PMF for Barcelona, while an additional split of the Nucleation factor (into Photonucleation and Traffic nucleation) by using NOx concentrations as a proxy for traffic emissions was performed for all other stations. The sum of all traffic sources resulted in a maximum relative contributions ranging from 71 to 94% (annual average) thereby being the main contributor at all stations. In London and Zurich, the relative contribution of the sources did not vary significantly between seasons. In contrast, the high levels of solar radiation in Barcelona led to an important contribution of Photonucleation particles (ranging from 14% during the winter period to 35% during summer). Biogenic emissions were a source identified only in Helsinki (both in the urban background and street canyon stations), that contributed importantly during summer (23% in urban background). Airport emissions contributed to Nucleation particles at urban background sites, as the highest concentrations of this source took place when the wind was blowing from the airport direction in all cities. Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved., This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 747882. We also thank Academy of Finland Center of Excellence programme (grant no. 307331) and ACTRIS-2 project that receives funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 654109, the “Agencia Estatal de Investigación” from the Spanish Ministry of Science, Innovation and Universities and FEDER funds under the project HOUSE (CGL2016-78594-R). The authors acknowledge the Departament de Territori i Sostenibilitat and AGAUR (2017 SGR41) from Generalitat de Catalunya, the Faculty of Physics of Barcelona University (Prof. J. Lorente), the Met Office (UK), the Department for Environment, Food and Rural Affairs (DEFRA, UK), and the Swiss Federal Office for the Environment (FOEN) for providing the air pollution and meteorological data.

This study examines the statistical predictability of local wind conditions in a real urban environment under realistic atmospheric boundary layer conditions by means of Large-Eddy Simulation (LES). The computational domain features a highly detailed description of a densely built coastal downtown area, which includes vegetation. A multi-scale nested LES modelling approach is utilized to achieve a setup where a fully developed boundary layer flow, which is also allowed to form and evolve very large-scale turbulent motions, becomes incident with the urban surface. Under these nonideal conditions, the local scale predictability and result sensitivity to central modelling choices are scrutinized via comparative techniques. Joint time&ndash, frequency analysis with wavelets is exploited to aid targeted filtering of the problematic large-scale motions, while concepts of information entropy and divergence are exploited to perform a deep probing comparison of local urban canopy turbulence signals. The study demonstrates the utility of wavelet analysis and information theory in urban turbulence research while emphasizing the importance of grid resolution when local scale predictability, particularly close to the pedestrian level, is sought. In densely built urban environments, the level of detail of vegetation drag modelling description is deemed most significant in the immediate vicinity of the trees.

In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

The spatial and temporal variability of the number size distribution of aerosol particles is an indicator of the dynamic behavior of Beijing's atmospheric pollution cocktail. This variation reflects the strength of different primary and secondary sources, such as traffic and new particle formation, as well as the main processes affecting the particle population. In this paper, we report size-segregated particle number concentrations observed at a newly developed Beijing station during the winter of 2018. Our measurements covered particle number size distributions over the diameter range of 1.5 nm–1 µm (cluster mode, nucleation mode, Aitken mode and accumulation mode), thus being descriptive of a major fraction of the processes taking place in the atmosphere of Beijing. Here we focus on explaining the concentration variations in the observed particle modes, by relating them to the potential aerosol sources and sinks, and on understanding the connections between these modes. We considered haze days and new particle formation event days separately. Our results show that during the new particle formation (NPF) event days increases in cluster mode particle number concentration were observed, whereas during the haze days high concentrations of accumulation mode particles were present. There was a tight connection between the cluster mode and nucleation mode on both NPF event and haze days. In addition, we correlated the particle number concentrations in different modes with concentrations of trace gases and other parameters measured at our station. Our results show that the particle number concentration in all the modes correlated with NOx, which reflects the contribution of traffic to the whole submicron size range. We also estimated the contribution of ion-induced nucleation in Beijing, and we found this contribution to be negligible.

The meteorological input parameters for urban and local scale dispersion models can be evaluated by pre-processing meteorological observations, using a boundary-layer parametrization model. This study presents a sensitivity analysis of a meteorological pre-processor model (MPP-FMI) that utilises readily available meteorological data as input. The sensitivity of the pre-processor to meteorological input was analysed using algorithmic differentiation (AD). The AD tool used was TAPENADE. The AD method numerically evaluates the partial derivatives of functions that are implemented in a computer program. In this study, we focus on the evaluation of vertical fluxes in the atmosphere, and in particular on the sensitivity of the predicted inverse Obukhov length and friction velocity on the model input parameters. The study shows that the estimated inverse Obukhov length and friction velocity are most sensitive to wind speed, and second most sensitive to solar irradiation. The dependency on wind speed is most pronounced at low wind speeds. The presented results have implications for improving the meteorological pre-processing models. AD is shown to be an efficient tool for studying the ranges of sensitivities of the predicted parameters on the model input values quantitatively. A wider use of such advanced sensitivity analysis methods could potentially be very useful in analysing and improving the models used in atmospheric sciences.

There is a growing need to simulate the effect of urban planning on both local climate and greenhouse gas emissions. Here, a new urban surface carbon dioxide (CO2) flux module for the Surface Urban Energy and Water Balance Scheme is described and evaluated using eddy covariance observations at two sites in Helsinki in 2012. The spatial variability and magnitude of local-scale anthropogenic and biogenic CO2 flux components at high spatial (250 m x 250 m) and temporal (hourly) resolution are examined by combining high-resolution (down to 2 m) airborne lidar-derived land use data and mobility data to account for people's movement. Urban effects are included in the biogenic components parameterized using urban eddy covariance and chamber observations. Surface Urban Energy and Water Balance Scheme reproduces the seasonal and diurnal variability of the CO2 flux well. Annual totals deviate 3% from observations in the city center and 2% in a suburban location. In the latter, traffic is the dominant CO2 source but summertime vegetation partly offsets traffic-related emissions. In the city center, emissions from traffic and human metabolism dominate and the vegetation effect is minor due to the low proportion of vegetation surface cover (22%). Within central Helsinki, human metabolism accounts for 39% of the net local-scale emissions and together with road traffic is to a large extent responsible for the spatial variability of the emissions. Annually, the biogenic emissions and sinks are in near balance and thus the effect of vegetation on the carbon balance is small in this high-latitude city.

Although increased aerosol concentration modifies local air temperatures and boundary layer structure in urban areas, little is known about its effects on the urban hydrological cycle. Changes in the hydrological cycle modify surface runoff and flooding. Furthermore, as runoff commonly transports pollutants to soil and water, any changes impact urban soil and aquatic environments. To explore the radiative effect of haze on changes in the urban surface water balance in Beijing, different haze levels are modelled using the Surface Urban Energy and Water Balance Scheme (SUEWS), forced by reanalysis data. The pollution levels are classified using aerosol optical depth observations. The secondary aims are to examine the usability of a global reanalysis dataset in a highly polluted environment and the SUEWS model performance. We show that the reanalysis data do not include the attenuating effect of haze on incoming solar radiation and develop a correction method. Using these corrected data, SUEWS simulates measured eddy covariance heat fluxes well. Both surface runoff and drainage increase with severe haze levels, particularly with low precipitation rates: runoff from 0.06 to 0.18 mm d−1 and drainage from 0.43 to 0.62 mm d−1 during fairly clean to extremely polluted conditions, respectively. Considering all precipitation events, runoff rates are higher during extremely polluted conditions than cleaner conditions, but as the cleanest conditions have high precipitation rates, they induce the largest runoff. Thus, the haze radiative effect is unlikely to modify flash flooding likelihood. However, flushing pollutants from surfaces may increase pollutant loads in urban water bodies.

The main chemical composition of PM1 (total organics, black carbon, sulphate, nitrate and ammonium), mass concentrations of PM2.5 and PM2.5–10 and concentration of specific trace gases were measured in a high temporal resolution from May 2013 to April 2015 in the city centre of Helsinki, Finland. On average, the concentrations of PM2.5 and PM2.5–10 were 9.1 µg m–3 and 16 µg m–3, respectively, during a two-year campaign. PM1 consisted mostly of organics (60%), followed by sulphate (12%), black carbon (11%), nitrate (9.8%) and ammonium (6.5%). The particle and gas data were combined with the meteorological data in order to obtain information on how local meteorology affects concentrations of air pollutants. Two meteorological parameters that mostly affected the pollutant concentrations were the wind speed and temperature, while sulphate and PM2.5–10 were also impacted by the relative humidity. The highest concentrations of the measured PM1 components were observed when the wind was calm or the temperature was either very cold or very warm. PM2.5–10 concentrations were at the highest during calm or very windy conditions, due to local street and construction dust. The seasonal-and diurnal-varying mixing height did not seem to affect markedly the concentrations of pollutants. Overall, air quality in terms of the aerosol mass was governed by three different main pollution sources in the Helsinki city centre: 1) local sources, of which traffic-related emissions were the most important; 2) long-range or regional transport of pollutants; and 3) local sources of organic aerosol. © 2019, Finnish Environment Institute. All rights reserved.

We have carried out an inter-comparison between EddyUH and EddyPro®, two public software packages for post-field processing of eddy covariance data. Datasets including carbon dioxide, methane and water vapour fluxes measured over 2 months at a wetland in southern Finland and carbon dioxide and water vapour fluxes measured over 3 months at an urban site in Helsinki were processed and analysed. The purpose was to estimate the flux uncertainty due to the use of different software packages and to evaluate the most critical processing steps, determining the largest deviations in the calculated fluxes. Turbulent fluxes calculated with a reference combination of processing steps were in good agreement, the systematic difference between the two software packages being up to 2.0 and 6.7 % for half-hour and cumulative sum values, respectively. The raw data preparation and processing steps were consistent between the software packages, and most of the deviations in the estimated fluxes were due to the flux corrections. Among the different calculation procedures analysed, the spectral correction had the biggest impact for closed-path latent heat fluxes, reaching a nocturnal median value of 15 % at the wetland site. We found up to a 43 % median value of deviation (with respect to the run with all corrections included) if the closed-path carbon dioxide flux is calculated without the dilution correction, while the methane fluxes were up to 10 % lower without both dilution and spectroscopic corrections. The Webb–Pearman–Leuning (WPL) and spectroscopic corrections were the most critical steps for open-path systems. However, we found also large spectral correction factors for the open-path methane fluxes, due to the sensor separation effect.

Street vegetation has been found to have both positive and negative impacts on pedestrian-level air quality, but the net effect has remained unclear. In this study, the effect of street trees on aerosol mass (PM10 and PM2.5) and number in a boulevard-type street canyon with high traffic volumes in Helsinki is examined using the large-eddy simulation model PALM. Including a detailed aerosol module and a canopy module to comprise permeable trees, PALM allows to examine the effect of street trees in depth. The main aim is to understand the relative importance of dry deposition and the aerodynamic impact of street trees on the different aerosol measures at pedestrian-level and to find a suitable street-tree layout that would minimise the pedestrian-level aerosol particle concentrations over the boulevard pavements. The layout scenarios were decided together with urban planners who needed science-based knowledge to support the building of new neighbourhoods with boulevard-type streets in Helsinki. Two wind conditions with wind being parallel and perpendicular to the boulevard under neutral atmospheric stratification are examined. Adding street trees to the boulevard increases aerosol particle concentrations on the pavements up to 123%, 72% and 53% for PM10, PM2.5 and total number, respectively. This shows decreased ventilation to be more important for local aerosol particle concentrations than dry deposition on vegetation. This particularly for PM10 and PM2.5 whereas for aerosol number, dominated by small particles, the importance of dry deposition increases. Therefore the studied aerosol measure is important when the effect of vegetation on pedestrian-level air quality is quantified. Crown volume fraction in the street space is one of the main determining factors for elevated mass concentrations on the pavements. The lowest pedestrian-level mass concentrations are seen with three rows of trees of variable height, whereas the lowest number concentrations with four rows of uniform trees. The tree-height variation allows stronger vertical turbulent transport with parallel wind and largest volumetric flow rates with perpendicular wind. Introducing low (height

The eddy covariance (EC) technique is the most direct method for measuring the exchange between the surface and the atmosphere in different ecosystems. Thus, it is commonly used to get information on air pollutant and greenhouse gas emissions, and on turbulent heat transfer. Typically an ecosystem is monitored by only one single EC measurement station at a time, making the ecosystem-level flux values subject to random and systematic uncertainties. Furthermore, in urban ecosystems we often have no choice but to conduct the single-point measurements in non-ideal locations such as close to buildings and/or in the roughness sublayer, bringing further complications to data analysis and flux estimations. In order to tackle the question of how representative a single EC measurement point in an urban area can be, two identical EC systems – measuring momentum, sensible and latent heat, and carbon dioxide fluxes – were installed on each side of the same building structure in central Helsinki, Finland, during July 2013–September 2015. The main interests were to understand the sensitivity of the vertical fluxes on the single measurement point and to estimate the systematic uncertainty in annual cumulative values due to missing data if certain, relatively wide, flow-distorted wind sectors are disregarded. The momentum and measured scalar fluxes respond very differently to the distortion caused by the building structure. The momentum flux is the most sensitive to the measurement location, whereas scalar fluxes are less impacted. The flow distortion areas of the two EC systems (40–150 and 230–340∘) are best detected from the mean-wind-normalised turbulent kinetic energy, and outside these areas the median relative random uncertainties of the studied fluxes measured by one system are between 12 % and 28 %. Different gap-filling methods with which to yield annual cumulative fluxes show how using data from a single EC measurement point can cause up to a 12 % (480 g C m−2) underestimation in the cumulative carbon fluxes as compared to combined data from the two systems. Combining the data from two EC systems also increases the fraction of usable half-hourly carbon fluxes from 45 % to 69 % at the annual level. For sensible and latent heat, the respective underestimations are up to 5 % and 8 % (0.094 and 0.069 TJ m−2). The obtained random and systematic uncertainties are in the same range as observed in vegetated ecosystems. We also show how the commonly used data flagging criteria in natural ecosystems, kurtosis and skewness, are not necessarily suitable for filtering out data in a densely built urban environment. The results show how the single measurement system can be used to derive representative flux values for central Helsinki, but the addition of second system to other side of the building structure decreases the systematic uncertainties. Comparable results can be expected in similarly dense city locations where no large directional deviations in the source area are seen. In general, the obtained results will aid the scientific community by providing information about the sensitivity of EC measurements and their quality flagging in urban areas.

Hydrological cycles of two suburban neighborhoods in Vancouver, BC, during initial urban development and subsequent urban densification (1920–2010) are examined using the Surface Urban Energy and Water Balance Scheme (SUEWS). The two neighborhoods have different surface characteristics (as determined from aerial photographs) which impact the hydrological processes. Unlike previous studies of the effect of urbanization on the local hydrology, densification of already built lots are explored with a focus on the neighborhood scale. Human behavioral changes to irrigation are accounted for in the simulations. Irrigation is the dominant factor, accounting for up to 56% of the water input on an annual basis in the study areas. This may surpass garden needs and go to runoff. Irrigating once a week would provide sufficient water for the garden. Without irrigation, evaporation would have decreased over the 91 years at a rate of up to 1.4 mm year−1 and runoff increased at 4.0 mm year−1 with the increase in impervious cover. Similarly, without irrigation, the ratio of sensible heat flux over the available energy would have increased over the 91 years at a rate of up to 0.003 year−1. Urbanization and densification cause an increase in runoff and increase risk of surface flooding. Small daily runoff events with short return periods have increased over the century whereas the occurrence of heavy daily runoff events (return period > 52 days) are not affected. The results can help us to understand the dominant factors in the suburban hydrological cycle and can inform urban planning.

Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved. Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved. Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.

Buildings and vegetation alter the wind and pollutant transport in urban environments. This comparative study investigates the role of orientation and shape of perimeter blocks on the dispersion and ventilation of traffic-related air pollutants, and the street-level concentrations along a planned city boulevard. A large-eddy simulation (LES) model PALM is employed over a highly detailed representation of the urban domain including street trees and forested areas. Air pollutants are represented by massless and passive particles (non-reactive gases), which are released with traffic-related emission rates. High-resolution simulations for four different city-block-structures are conducted over a 8.2 km domain under two contrasting inflow conditions with neutral and stable atmospheric stratification corresponding the general and wintry meteorological conditions. Variation in building height together with multiple cross streets along the boulevard improves ventilation, resulting in 7-9% lower mean concentrations at pedestrian level. The impact of smaller scale variability in building shape was negligible. Street trees further complicate the flow and dispersion. Notwithstanding the surface roughness, atmospheric stability controls the concentration levels with higher values under stably stratified inflow. Little traffic emissions are transported to courtyards. The results provide urban planners direct information to reduce air pollution by proper structural layout of perimeter blocks.

UMEP (Urban Multi-scale Environmental Predictor), a city-based climate service tool, combines models and tools essential for climate simulations. Applications are presented to illustrate UMEP's potential in the identification of heat waves and cold waves; the impact of green infrastructure on runoff; the effects of buildings on human thermal stress; solar energy production; and the impact of human activities on heat emissions. UMEP has broad utility for applications related to outdoor thermal comfort, wind, urban energy consumption and climate change mitigation. It includes tools to enable users to input atmospheric and surface data from multiple sources, to characterise the urban environment, to prepare meteorological data for use in cities, to undertake simulations and consider scenarios, and to compare and visualise different combinations of climate indicators. An open-source tool, UMEP is designed to be easily updated as new data and tools are developed, and to be accessible to researchers, decision-makers and practitioners. (C) 2017 The Authors. Published by Elsevier Ltd.

In this study, the crosswind (wind component perpendicular to a path, U⊥) is measured by a scintillometer and estimated with Doppler lidar above the urban environment of Helsinki, Finland, for 15 days. The scintillometer allows acquisition of a path-averaged value of U⊥ (U⊥), while the lidar allows acquisition of path-resolved U⊥ (U⊥ (x), where x is the position along the path). The goal of this study is to evaluate the performance of scintillometer U⊥ estimates for conditions under which U⊥ (x) is variable. Two methods are applied to estimate U⊥ from the scintillometer signal: the cumulative-spectrum method (relies on scintillation spectra) and the look-up-table method (relies on time-lagged correlation functions). The values of U⊥ of both methods compare well with the lidar estimates, with root-mean-square deviations of 0.71 and 0.73 m s−1. This indicates that, given the data treatment applied in this study, both measurement technologies are able to obtain estimates of U⊥ in the complex urban environment. The detailed investigation of four cases indicates that the cumulative-spectrum method is less susceptible to a variable U⊥ (x) than the look-up-table method. However, the look-up-table method can be adjusted to improve its capabilities for estimating U⊥ under conditions under for which U⊥ (x) is variable.

While approximately 338 million people in the Northern hemisphere live in regions that are regularly snow covered in winter, there is little hydro-climatologic knowledge in the cities impacted by snow. Using observations and modelling we have evaluated the energy and water exchanges of four cities that are exposed to wintertime snow. We show that the presence of snow critically changes the impact that city design has on the local-scale hydrology and climate. After snow melt, the cities return to being strongly controlled by the proportion of built and vegetated surfaces. However in winter, the presence of snow masks the influence of the built and vegetated fractions. We show how inter-year variability of wintertime temperature can modify this effect of snow. With increasing temperatures, these cities could be pushed towards very different partitioning between runoff and evapotranspiration. We derive the dependency of wintertime runoff on this warming effect in combination with the effect of urban densification.

Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddy-covariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES–LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.

We investigated the drivers of street tree transpiration in boreal conditions, in order to better understand tree water use in the context of urban tree planning and stormwater management. Two streets built in Helsinki in 2002, hemiboreal zone that had been planted either with Tilia x vulgaris or Alnus glutinosa f. pyramidalis were used as the study sites. Tree water use was measured from sap flow over the 2008-2011 period by the heat dissipation method. Penman-Monteith based evapotranspiration models of increasing complexity were tested against the tree water use measurements to assess the role of environmental and tree related factors in tree transpiration. Alnus and Tilia respectively used 1.1 and 0.8 l of water per m(2) of leaf area per day under ample water conditions, but the annual variation was high. The Penman-Monteith evapotranspiration estimate and soil water status changes explained over 80 % of the variation in tree transpiration when the model was parameterized annually. The addition of tree crown surface area in the model improved its accuracy and diminished variation between years and sites. Using single parameterization over all four years instead of annually varying one did not produce reliable estimates of tree transpiration. Tree transpiration, scaled to different canopy cover percentages, implied that the columnar Alnus trees could transpire as much as all annual rainfall at or less than 50 % canopy cover.

Contributors: Hanna K. Lappalainen1,2, Veli-Matti Kerminen1, Tuukka Petäjä1, Theo Kurten3, Aleksander Baklanov4,5, Anatoly Shvidenko6, Jaana Bäck7, Timo Vihma2, Pavel Alekseychik1, Stephen Arnold8, Mikhail Arshinov9, Eija Asmi2, Boris Belan9, Leonid Bobylev10, Sergey Chalov11, Yafang Cheng12, Natalia Chubarova11, Gerrit de Leeuw1,2, Aijun Ding13, Sergey Dobrolyubov11, Sergei Dubtsov14, Egor Dyukarev15, Nikolai Elansky16, Kostas Eleftheriadis17, Igor Esau18, Nikolay Filatov19, Mikhail Flint20, Congbin Fu13, Olga Glezer21, Aleksander Gliko22, Martin Heimann23, Albert A. M. Holtslag24, Urmas Hõrrak25, Juha Janhunen26, Sirkku Juhola27, Leena Järvi1, Heikki Järvinen1, Anna Kanukhina28, Pavel Konstantinov11, Vladimir Kotlyakov29, Antti-Jussi Kieloaho1, Alexander S. Komarov30, Joni Kujansuu1, Ilmo Kukkonen31, Ella Kyrö1, Ari Laaksonen2, Tuomas Laurila2, Heikki Lihavainen2, Alexander Lisitzin32, Aleksander Mahura5, Alexander Makshtas33, Evgeny Mareev34, Stephany Mazon1, Dmitry Matishov35,†, Vladimir Melnikov36, Eugene Mikhailov37, Dmitri Moisseev1, Robert Nigmatulin33, Steffen M. Noe38, Anne Ojala7, Mari Pihlatie1, Olga Popovicheva39, Jukka Pumpanen40, Tatjana Regerand19, Irina Repina16, Aleksei Shcherbinin27, Vladimir Shevchenko33, Mikko Sipilä1, Andrey Skorokhod16, Dominick V. Spracklen8, Hang Su12, Dmitry A. Subetto19, Junying Sun41, Arkady Yu Terzhevik19, Yuri Timofeyev42, Yuliya Troitskaya34, Veli-Pekka Tynkkynen42, Viacheslav I. Kharuk43, Nina Zaytseva22, Jiahua Zhang44, Yrjö Viisanen2, Timo Vesala1, Pertti Hari7, Hans Christen Hansson45, Gennady G. Matvienko9, Nikolai S. Kasimov11, Huadong Guo44, Valery Bondur46, Sergej Zilitinkevich1,2,11,34, and Markku Kulmala1 1Department of Physics, University of Helsinki, 00014 Helsinki, Finland 2Finnish Meteorological Institute, Research and Development, 00101 Helsinki, Finland 3Department of Chemistry, University of Helsinki, 00014 Helsinki, Finland 4World Meteorological Organization, 1211 Genève, Switzerland 5Danish Meteorological Institute, Research and Development Department, 2100, Copenhagen 6International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria 7Department of Forest Sciences, University of Helsinki, 00014 Helsinki, Finland 8Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK 9Institute of Atmospheric Optics, Russian Academy of Sciences, Tomsk 634021, Russia 10Nansen International Environmental and Remote Sensing Center, St. Petersburg, Russia 11Lomonosov Moscow State University, Faculty of Geography, Moscow 119899, Russia 12Max Planck Institute for Chemistry, 55128 Mainz, Germany 13Institute for Climate and Global Change Research & School of Atmospheric Sciences, Nanjing University, 210023 Nanjing, China 14Institute of Chemical Kinetics & Combustion, Russian Academy of Sciences, 630090 Novosibirsk, Russia 15Institute of Monitoring of Climatic & Ecological Systems SB RAS, 634055 Tomsk, Russia 16A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Russia 17National Centre of Scientific Research "DEMOKRITOS", Greece 18Nansen Environmental and Remote Sensing Center/Bjerknes Centre for Climate Research, 5006 Bergen, Norway 19Northern Water Problems Institute, Karelian Research Center, Russian Academy of Sciences,185003 Petrozavodsk, Russia 20P. P. Shirshov, Institute of Oceanology, Russian Academy of Sciences, Russian Academy of Sciences, 117997 Moscow, Russia 21Institute of Geography, Russian Academy of Sciences, Moscow, Russia 22Depart ment of Earth Sciences of the Russian Academy of Sciences, Russian Academy of Sciences, 119991, Moscow, Russia 23Max-Planck-Institute for Biogeochemistry, 07745 Jena, Germany 24Wageningen University, 6708 Wageningen, Nederland 25Institute of Physics, University of Tartu, 18 Ülikooli St., 50090 Tartu, Estonia 26University of Helsinki, Department of World Cultures, 00014 Helsinki, Finland 27Department of Environmental Sciences, University of Helsinki, 00014 Helsinki, Finland 28Russian State Hydrometeorological University, 195196 Saint Petersburg, Russia 29Institute of Geography, Russian Academy of Sciences, Moscow, Russia 30Institute of Physico-chemical & Biological Problems in Soil Science, Russian Academy of Sciences, 142290 Institutskaya, Russia 31University of Helsinki, Geophysics and Astronomy, 00014 Helsinki, Finland 32Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia 33Actic & Antarctic Research Institute, Russian Academy of Sciences, St. Petersburg 199397, Russia 34Department of Radiophysics, Nizhny Novgorod State University, Nizhny Novgorod, Russia 35Southern Center of Russian Academy of Sciences, Rostov on Don, Russia 36Tyumen Scientific Center, Siberian Branch, Russian Academy of Science, Russia 37Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034 Russia 38Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 51014 Tartu, Estonia 39Skobeltsyn Institute of Nuclear Physics, Moscow State University, Department Microelectronics, Russia 40University of Eastern Finland, Department of Environmental Science, P.O. Box 1627, FI-70211 Kuopio, Finland 41Craduate University of Chinese Academy of Sciences, 100049 Beijing, China 42Aleksanteri Institute and Department of Social Research, 00014 University of Helsinki, Finland 43Sukachev Forest Institute, Russian Academy of Sciences, Krasnoyarsk 660036, Russia 44Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China 45Environmental Science and Analytical Chemistry, Stockholm University, Sweden 46AEROCOSMOS Research Institute for Aerospace Monitoring, 105064, Moscow, Russia †deceased, 20 August 2015 The Northern Eurasian regions and Arctic Ocean will very likely undergo substantial changes during the next decades. The arctic-boreal natural environments play a crucial role in the global climate via the albedo change, carbon sources and sinks, as well as atmospheric aerosol production via biogenic volatile organic compounds. Furthermore, it is expected that the global trade activities, demographic movement and use of natural resources will be increasing in the Arctic regions. There is a need for a novel research approach, which not only identifies and tackles the relevant multi-disciplinary research questions, but is also able to make a holistic system analysis of the expected feedbacks. In this paper, we introduce the research agenda of the Pan-Eurasian Experiment (PEEX), a multi-scale, multi-disciplinary and international program started in 2012 (https://www.atm.helsinki.fi/peex/). PEEX is setting a research approach where large-scale research topics are investigated from a system perspective and which aims to fill the key gaps in our understanding of the feedbacks and interactions between the land–atmosphere–aquatic–society continuum in the Northern Eurasian region. We introduce here the state of the art of the key topics in the PEEX research agenda and give the future prospects of the research which we see relevant in this context.

Large-eddy simulation (LES) and Lagrangian stochastic modeling of passive particle dispersion were applied to the scalar flux footprint determination in the stable atmospheric boundary layer. The sensitivity of the LES results to the spatial resolution and to the parameterizations of small-scale turbulence was investigated. It was shown that the resolved and partially resolved (“subfilter-scale”) eddies are mainly responsible for particle dispersion in LES, implying that substantial improvement may be achieved by using recovering of small-scale velocity fluctuations. In LES with the explicit filtering, this recovering consists of the application of the known inverse filter operator. The footprint functions obtained in LES were compared with the functions calculated with the use of first-order single-particle Lagrangian stochastic models (LSMs) and zeroth-order Lagrangian stochastic models – the random displacement models (RDMs). According to the presented LES, the source area and footprints in the stable boundary layer can be substantially more extended than those predicted by the modern LSMs.

Severe air pollution episodes have been frequent in China during the recent years. While high emissions are the primary reason for increasing pollutant concentrations, the ultimate cause for the most severe pollution episodes has remained unclear. Here we show that a high concentration of particulate matter (PM) will enhance the stability of an urban boundary layer, which in turn decreases the boundary layer height and consequently cause further increases in PM concentrations. We estimate the strength of this positive feedback mechanism by combining a new theoretical framework with ambient observations. We show that the feedback remains moderate at fine PM concentrations lower than about 200 μg m−3, but that it becomes increasingly effective at higher PM loadings resulting from the combined effect of high surface PM emissions and massive secondary PM production within the boundary layer. Our analysis explains why air pollution episodes are particularly serious and severe in megacities and during the days when synoptic weather conditions stay constant.

We measured volatile organic compounds (VOCs), carbon dioxide (CO2) and carbon monoxide (CO) at an urban background site near the city centre of Helsinki, Finland, northern Europe. The VOC and CO2 measurements were obtained between January 2013 and September 2014 whereas for CO a shorter measurement campaign in April–May 2014 was conducted. Both anthropogenic and biogenic sources were identified for VOCs in the study. Strong correlations between VOC fluxes and CO fluxes and traffic rates indicated anthropogenic source of many VOCs. The VOC with the highest emission rate to the atmosphere was methanol, which originated mostly from traffic and other anthropogenic sources. The traffic was also a major source for aromatic compounds in all seasons whereas isoprene was mostly emitted from biogenic sources during summer. Some amount of traffic-related isoprene emissions were detected during other seasons but this might have also been an instrumental contamination from cycloalkane products. Generally, the observed VOC fluxes were found to be small in comparison with previous urban VOC flux studies. However, the differences were probably caused by lower anthropogenic activities as the CO2 fluxes were also relatively small at the site.

Five one-dimensional (1D) lake models were run for the open water season in 2006 for Lake Valkea-Kotinen (Finland) using on-lake measured meteorological forcing. The model results were validated using measurements of water temperature and of eddy covariance (EC) fluxes. The surface temperature is satisfactorily simulated by all models showing slight overestimation (by 0.1–1.1°C). Both sensible and latent heat fluxes are positively biased in respect to EC data, consistent with earlier studies. However, correlation coefficients between EC-fluxes and those simulated are relatively high ranging from 0.55 to 0.74. The skill to simulate vertical temperature profiles by different models is assessed as well. It is found that the lake models underestimate the EC-derived surface drag coefficient, however providing realistic temperature profiles. It is argued that the real momentum flux from the atmosphere is larger than simulated, however it is split up between the wave development and the acceleration of lake currents. Adopting the simple parameterisation for momentum flux partitioning in one of the models showed that this mechanism can be significant. Finally, the effect of including the lake bathymetry data in k-ɛ models was the drastic overheating of water below the thermocline. This is likely to be caused by omitting the heat flux at the lake margins. Thus, the parameterisation of heat flux at the lake’s margins should be included in the models; otherwise it is recommended to neglect bathymetry effects for such small water bodies as the Lake Valkea-Kotinen. Keywords: lakes, numerical modelling, stratification, surface fluxes (Published: 16 January 2014) Citation: Tellus A 2014, 66 , 21389, http://dx.doi.org/10.3402/tellusa.v66.21389 This publication is part of a Thematic Cluster entitled "Parameterization of lakes in numerical weather prediction and climate models". Read the other papers from this thematic cluster here

The Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated at two locations in the UK: a dense urban site in the centre of London and a residential suburban site in Swindon. Eddy covariance observations of the turbulent fluxes are used to assess model performance over a two-year period (2011−2013). The distinct characteristics of the sites mean their surface energy exchanges differ considerably. The model suggests the largest differences can be attributed to surface cover (notably the proportion of vegetated versus impervious area) and the additional energy supplied by human activities. SUEWS performs better in summer than winter, and better at the suburban site than the dense urban site. One reason for this is the bias towards suburban summer field campaigns in observational data used to parameterise this (and other) model(s). The suitability of model parameters (such as albedo, energy use and water use) for the UK sites is considered and, where appropriate, alternative values are suggested. An alternative parameterisation for the surface conductance is implemented, which permits greater soil moisture deficits before evaporation is restricted at non-irrigated sites. Accounting for seasonal variation in the estimation of storage heat flux is necessary to obtain realistic wintertime fluxes.

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