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Weather forecasting plays a vital role in estimating energy generation from variable renewable energy sources (VRES). Current weather forecast methods for estimating energy from VRES are typically at a scale of a few kilometers, which is not the fine spatial resolution needed for distributed energy planning. In this paper, we propose IrMaSet (an intelligent weather forecaster system) that integrates weather data obtained from existing massive sensing infrastructure and processes data using state-of-the-art communication and computational technologies. IrMaSet generates hyper-local real-time weather and forecast information (HyReF) and enables accurate estimation of the amount of electricity to be generated by VRES, resulting in the optimal management of microgrid energy systems. We present challenges and possible solutions for deploying IrMaSet and demonstrate the feasibility of IrMaSet in saving energy, and reducing costs and carbon emissions, using meteorological data including wind and solar radiation from eleven official monitoring stations (OMS) in greater Helsinki, Finland.

Weather forecasting plays a vital role in estimating energy generation from variable renewable energy sources (VRES). Current weather forecast methods for estimating energy from VRES are typically at a scale of a few kilometers, which is not the fine spatial resolution needed for distributed energy planning. In this paper, we propose IrMaSet (an intelligent weather forecaster system) that integrates weather data obtained from existing massive sensing infrastructure and processes data using state-of-the-art communication and computational technologies. IrMaSet generates hyper-local real-time weather and forecast information (HyReF) and enables accurate estimation of the amount of electricity to be generated by VRES, resulting in the optimal management of microgrid energy systems. We present challenges and possible solutions for deploying IrMaSet and demonstrate the feasibility of IrMaSet in saving energy, and reducing costs and carbon emissions, using meteorological data including wind and solar radiation from eleven official monitoring stations (OMS) in greater Helsinki, Finland.

Precipitation chemistry is influenced by a number of complex processes, which include the temporal and spatial evolution of air masses. Previous wet deposition studies in South Africa could not distinctly relate the influence of air mass history on rain chemistry in order to substantiate the influence of different sources. The Welgegund atmospheric monitoring station in South Africa measures several atmospheric parameters, which include vertical profiling of the atmosphere that could assist in relating rain chemistry to air mass history. Therefore, the aim of this study was to conduct an advanced assessment on factors influencing chemical composition of rain in the South African interior by relating individual rain events at Welgegund to air mass history at cloud base height (CBH) and arrival heights below clouds, as well as supplementary in situ measurements conducted at the site. Hierarchical cluster analysis was performed through two approaches, i.e. clustering based on the chemical composition of rain, as well as grouping based on air masses arriving at CBH and 100 m above ground level (a.g. l.). Although statistical analyses highlighted the complexity associated with correlating rain chemistry to sources of chemical species, it proved useful to determine some correlations between rain chemistry and air mass history. Clustering according to the chemical composition of rain events grouped rain events from high to low volume weighted mean (VWM) concentrations. Correlation of air mass histories to these clusters indicated that higher VWM concentrations were associated with air masses at 100 m a.g.l. passing over anthropogenic source regions. Air mass history clustering grouped air masses passing predominantly over predefined source regions. The rain chemistry of clusters determined for air masses at 100 m a.g.l. arrival heights could be related to the influence of different source regions, with the impact of large point sources, the clean western background region

Purpose: To report clinical features and potential disease markers of inherited retinal dystrophy (IRD) caused by the biallelic c.148delG variant in the tubby-like protein 1 (TULP1) gene. Methods: A retrospective observational study of 16 IRD patients carrying a homozygous pathogenic TULP1 c.148delG variant. Clinical data including fundus spectral-domain optical coherence tomography (SD-OCT) were assessed. A meta-analysis of visual acuity of previously reported other pathogenic TULP1 variants was performed for reference. Results: The biallelic TULP1 variant c.148delG was associated with infantile and early childhood onset IRD. Retinal ophthalmoscopy was primarily normal converting to peripheral pigmentary retinopathy and maculopathy characterized by progressive extra-foveal loss of the ellipsoid zone (EZ), the outer plexiform layer (OPL), and the outer nuclear layer (ONL) bands in the SD-OCT images. The horizontal width of the foveal EZ showed significant regression with the best-corrected visual acuity (BCVA) of the eye (p < 0.0001, R2 = 0.541, F = 26.0), the age of the patient (p < 0.0001, R2 = 0.433, F = 16.8), and mild correlation with the foveal OPL-ONL thickness (p = 0.014, R2 = 0.245, F = 7.2). Modelling of the BCVA data suggested a mean annual loss of logMAR 0.027. The level of visual loss was similar to that previously reported in patients carrying other truncating TULP1 variants. Conclusions: This study describes the progression of TULP1 IRD suggesting a potential time window for therapeutic interventions. The width of the foveal EZ and the thickness of the foveal OPL-ONL layers could serve as biomarkers of the disease stage.

South Africa is one of the largest atmospheric sulphur emitting countries, but the contribution of H2S to this regional burden is not known. Also, no H2S source apportionment for South Africa have been undertaken, although H2S has adverse effects on the environment and human health both directly and after being oxidised. Measurements were conducted for 2 years at a site on the Mpumalanga Highveld (South Africa), which is influenced by multiple sources. A mean of 3.1 ppb H2S was obtained, which is similar than concentrations re ported for some large Northern Hemisphere cities and areas close to gas processing plants. Well defined seasonal and diurnal patterns indicated that low-level emission sources likely made a significant contribution to the ambient H2S concentrations. In this study, a receptor method was developed to enable identification of sources and quantification of their contribution to atmospheric H2S levels above the baseline concentrations. The results indicate that emissions from urban areas on the Mpumalanga Highveld, associated with sources in towns, as well as semi- and informal settlements (e.g. ineffective household combustion of low grade coal, sewage waste water treatment facilities, landfills, small industries and traffic) contributed most to atmospheric H2S levels in excess of baseline concentrations (34.6%), followed by pyrometallurgical smelters (19.8%) and a petrochemical operation near Secunda (17.9%). The Johannesburg-Pretoria megacity, coal-fired power stations, burning coal dumps and cattle feedlots contributed 10.9, 4.7, 3.8 and 0.4%, respectively, to H2S concentrations in excess of the baseline levels, respectively. The results from this study will be informative for legislation that is currently being considered, wherein regional ambient H2S standards for South Africa are suggested.

This paper presents an introduction to the Southern Hemisphere High Altitude Experiment on Particle Nucleation and Growth (SALTENA). This field campaign took place between December 2017 and June 2018 (wet to dry season) at Chacaltaya (CHC), a GAW (Global Atmosphere Watch) station located at 5,240 m MSL in the Bolivian Andes. Concurrent measurements were conducted at two additional sites in El Alto (4,000 m MSL) and La Paz (3,600 m MSL). The overall goal of the campaign was to identify the sources, understand the formation mechanisms and transport, and characterize the properties of aerosol at these stations. State-of-the-art instruments were brought to the station complementing the ongoing permanent GAW measurements, to allow a comprehensive description of the chemical species of anthropogenic and biogenic origin impacting the station and contributing to new particle formation. In this overview we first provide an assessment of the complex meteorology, airmass origin, and boundary layer-free troposphere interactions during the campaign using a 6-month high-resolution Weather Research and Forecasting (WRF) simulation coupled with Flexible Particle dispersion model (FLEXPART). We then show some of the research highlights from the campaign, including (i) chemical transformation processes of anthropogenic pollution while the air masses are transported to the CHC station from the metropolitan area of La Paz-El Alto, (ii) volcanic emissions as an important source of atmospheric sulfur compounds in the region, (iii) the characterization of the compounds involved in new particle formation, and (iv) the identification of long-range-transported compounds from the Pacific or the Amazon basin. We conclude the article with a presentation of future research foci. The SALTENA dataset highlights the importance of comprehensive observations in strategic high-altitude locations, especially the undersampled Southern Hemisphere.

Air pollution introduces a major challenge for societies, where it leads to the premature deaths of millions of people each year globally. Massive deployment of air quality sensing devices and data analysis for the resultant data will pave the way for the development of real-time intelligent applications and services, e.g., minimization of exposure to poor air quality either on an individual or city scale. 5G and edge computing supports dense deployments of sensors at high resolution with ubiquitous connectivity, high bandwidth, high-speed gigabit connections, and ultralow latency analysis. This article conceptualizes AI-powered scalable air quality monitoring and presents two systems of calibrating low-cost air quality sensors and the image processing of pictures captured by hyperspectral cameras to better detect air quality. We develop and deploy different AI algorithms in these two systems on a 5G edge testbed and perform a detailed analytics regarding to 1) the performance of AI algorithms and 2) the required communication and computation resources.

Atmospheric new-particle formation (NPF) affects climate by contributing to a large fraction of the cloud condensation nuclei (CCN). Highly oxygenated organic molecules (HOMs) drive the early particle growth and therefore substantially influence the survival of newly formed particles to CCN. Nitrogen oxide (NOx) is known to suppress the NPF driven by HOMs, but the underlying mechanism remains largely unclear. Here, we examine the response of particle growth to the changes of HOM formation caused by NOx We show that NOx suppresses particle growth in general, but the suppression is rather nonuniform and size dependent, which can be quantitatively explained by the shifted HOM volatility after adding NOx By illustrating how NOx affects the early growth of new particles, a critical step of CCN formation, our results help provide a refined assessment of the potential climatic effects caused by the diverse changes of NOx level in forest regions around the globe.

Atmospheric new-particle formation (NPF) affects climate by contributing to a large fraction of the cloud condensation nuclei (CCN). Highly oxygenated organic molecules (HOMs) drive the early particle growth and therefore substantially influence the survival of newly formed particles to CCN. Nitrogen oxide (NOx) is known to suppress the NPF driven by HOMs, but the underlying mechanism remains largely unclear. Here, we examine the response of particle growth to the changes of HOM formation caused by NOx. We show that NOx suppresses particle growth in general, but the suppression is rather nonuniform and size dependent, which can be quantitatively explained by the shifted HOM volatility after adding NOx. By illustrating how NOx affects the early growth of new particles, a critical step of CCN formation, our results help provide a refined assessment of the potential climatic effects caused by the diverse changes of NOx level in forest regions around the globe.

Atmospheric new-particle formation (NPF) affects climate by contributing to a large fraction of the cloud condensation nuclei (CCN). Highly oxygenated organic molecules (HOMs) drive the early particle growth and therefore substantially influence the survival of newly formed particles to CCN. Nitrogen oxide (NOx) is known to suppress the NPF driven by HOMs, but the underlying mechanism remains largely unclear. Here, we examine the response of particle growth to the changes of HOM formation caused by NOx. We show that NOx suppresses particle growth in general, but the suppression is rather nonuniform and size dependent, which can be quantitatively explained by the shifted HOM volatility after adding NOx. By illustrating how NOx affects the early growth of new particles, a critical step of CCN formation, our results help provide a refined assessment of the potential climatic effects caused by the diverse changes of NOx level in forest regions around the globe.

Atmospheric new-particle formation (NPF) affects climate by contributing to a large fraction of the cloud condensation nuclei (CCN). Highly oxygenated organic molecules (HOMs) drive the early particle growth and therefore substantially influence the survival of newly formed particles to CCN. Nitrogen oxide (NOx) is known to suppress the NPF driven by HOMs, but the underlying mechanism remains largely unclear. Here, we examine the response of particle growth to the changes of HOM formation caused by NOx. We show that NOx suppresses particle growth in general, but the suppression is rather nonuniform and size dependent, which can be quantitatively explained by the shifted HOM volatility after adding NOx. By illustrating how NOx affects the early growth of new particles, a critical step of CCN formation, our results help provide a refined assessment of the potential climatic effects caused by the diverse changes of NOx level in forest regions around the globe.

Over Boreal regions, monoterpenes emitted from the forest are the main precursors for secondary organic aerosol (SOA) formation and the primary driver of the growth of new aerosol particles to climatically important cloud condensation nuclei (CCN). Autoxidation of monoterpenes leads to rapid formation of Highly Oxygenated organic Molecules (HOM). We have developed the first model with near-explicit representation of atmospheric new particle formation (NPF) and HOM formation. The model can reproduce the observed NPF, HOM gas-phase composition and SOA formation over the Boreal forest. During the spring, HOM SOA formation increases the CCN concentration by ~10 % and causes a direct aerosol radiative forcing of −0.10 W/m². In contrast, NPF reduces the number of CCN at updraft velocities < 0.2 m/s, and causes a direct aerosol radiative forcing of +0.15 W/m². Hence, while HOM SOA contributes to climate cooling, NPF can result in climate warming over the Boreal forest.

The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date, aiming to strengthen research and innovation regarding climate change issues in the Nordic region. CRAICC gathered more than 100 scientists from all Nordic countries in a virtual centre with the objectives of identifying and quantifying the major processes controlling Arctic warming and related feedback mechanisms, outlining strategies to mitigate Arctic warming, and developing Nordic Earth system modelling with a focus on short-lived climate forcers (SLCFs), including natural and anthropogenic aerosols. The outcome of CRAICC is reflected in more than 150 peer-reviewed scientific publications, most of which are in the CRAICC special issue of the journal Atmospheric Chemistry and Physics. This paper presents an overview of the main scientific topics investigated in the centre and provides the reader with a state-of-the-art comprehensive summary of what has been achieved in CRAICC with links to the particular publications for further detail. Faced with a vast amount of scientific discovery, we do not claim to completely summarize the results from CRAICC within this paper, but rather concentrate here on the main results which are related to feedback loops in climate change–cryosphere interactions that affect Arctic amplification.

The volatility distribution of secondary organic aerosols that formed and had undergone aging — i.e., the particle mass fractions of semi-volatile, low-volatility and extremely low volatility organic compounds in the particle phase — was characterized in a boreal forest environment of Hyytiälä, southern Finland. This was done by interpreting field measurements using a volatility tandem differential mobility analyzer (VTDMA) with a kinetic evaporation model. The field measurements were performed during April and May 2014. On average, 40% of the organics in particles were semi-volatile, 34% were low-volatility organics and 26% were extremely low volatility organics. The model was, however, very sensitive to the vaporization enthalpies assumed for the organics (ΔHVAP). The best agreement between the observed and modeled temperature dependence of the evaporation was obtained when effective vaporization enthalpy values of 80 kJmol⁻¹ were assumed. There are several potential reasons for the low effective enthalpy value, including molecular decomposition or dissociation that might occur in the particle phase upon heating, mixture effects and compound-dependent uncertainties in the mass accommodation coefficient. In addition to the VTDMA-based analysis, semi-volatile and low-volatility organic mass fractions were independently determined by applying positive matrix factorization (PMF) to high-resolution aerosol mass spectrometer (HR-AMS) data. The factor separation was based on the oxygenation levels of organics, specifically the relative abundance of mass ions at m∕z 43 (f43) and m∕z 44 (f44). The mass fractions of these two organic groups were compared against the VTDMA-based results. In general, the best agreement between the VTDMA results and the PMF-derived mass fractions of organics was obtained when ΔHVAP = 80 kJmol⁻¹ was set for all organic groups in the model, with a linear correlation coefficient of around 0.4. However, this still indicates that only abou

The formation of new atmospheric particles involves an initial step forming stable clusters less than a nanometre in size (similar to 10 nm). Although at times, the same species can be responsible for both processes, it is thought that more generally each step comprises differing chemical contributors. Here, we present a novel analysis of measurements from a unique multi-station ground-based observing system which reveals new insights into continental-scale patterns associated with new particle formation. Statistical cluster analysis of this unique 2-year multi-station dataset comprising size distribution and chemical composition reveals that across Europe, there are different major seasonal trends depending on geographical location, concomitant with diversity in nucleating species while it seems that the growth phase is dominated by organic aerosol formation. The diversity and seasonality of these events requires an advanced observing system to elucidate the key processes and species driving particle formation, along with detecting continental scale changes in aerosol formation into the future.

© 2018 The Authors. Governance Published by Wiley Periodicals, Inc. This article explores the issue of the major reform of the child welfare sector that has been carried out in Russia in recent years. Focusing on deinstitutionalization and a child's right to a family, this reform moves Russia in the direction of international trends in this area and represents a break with previous state- and institution-dominated approach to “problem families.” The article explores how and why this process has come about in a traditionally top-down hybrid regime and applies the Multiple Streams Framework first developed by Kingdon to argue that Russian child welfare nongovernmental organizations have acted in concert with government officials to act as policy entrepreneurs in framing the policy problem and presenting solutions to it in a way that has influenced national priorities in this area. At the same time, the article acknowledges that major challenges remain in terms of implementing the reform at the regional level of government in Russia.

© 2018 The Authors. Governance Published by Wiley Periodicals, Inc. This article explores the issue of the major reform of the child welfare sector that has been carried out in Russia in recent years. Focusing on deinstitutionalization and a child's right to a family, this reform moves Russia in the direction of international trends in this area and represents a break with previous state- and institution-dominated approach to “problem families.” The article explores how and why this process has come about in a traditionally top-down hybrid regime and applies the Multiple Streams Framework first developed by Kingdon to argue that Russian child welfare nongovernmental organizations have acted in concert with government officials to act as policy entrepreneurs in framing the policy problem and presenting solutions to it in a way that has influenced national priorities in this area. At the same time, the article acknowledges that major challenges remain in terms of implementing the reform at the regional level of government in Russia.

Climate models are important tools that are used for generating climate change projections, in which aerosol–climate interactions are one of the main sources of uncertainties. In order to quantify aerosol–radiation and aerosol–cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in pre-compiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few, very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. In the GAINS model the emission number size distributions vary, for example, with respect to the fuel and technology. Special attention was paid to accumulation mode particles (particle diameter dp > 100nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100nm particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol–climate interactions, are expected to be affected. Analysis of global particle number concentrations and size distributions reveals that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particles agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp

Climate models are important tools that are used for generating climate change projections, in which aerosol–climate interactions are one of the main sources of uncertainties. In order to quantify aerosol–radiation and aerosol–cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in pre-compiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few, very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. In the GAINS model the emission number size distributions vary, for example, with respect to the fuel and technology. Special attention was paid to accumulation mode particles (particle diameter dp > 100nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100nm particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol–climate interactions, are expected to be affected. Analysis of global particle number concentrations and size distributions reveals that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particles agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp

Climate models are important tools that are used for generating climate change projections, in which aerosol–climate interactions are one of the main sources of uncertainties. In order to quantify aerosol–radiation and aerosol–cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in pre-compiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few, very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. In the GAINS model the emission number size distributions vary, for example, with respect to the fuel and technology. Special attention was paid to accumulation mode particles (particle diameter dp > 100nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100nm particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol–climate interactions, are expected to be affected. Analysis of global particle number concentrations and size distributions reveals that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particles agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp

Atmospheric new-particle formation (NPF) is an important source of climatically relevant atmospheric aerosol particles. NPF can be directly observed by monitoring the time-evolution of ambient aerosol particle size distributions. From the measured distribution data, it is relatively straightforward to determine whether NPF took place or not on a given day. Due to the noisiness of the real-world ambient data, currently the most reliable way to classify measurement days into NPF event/non-event days is a manual visualization method. However, manual labor, with long multi-year time series, is extremely time-consuming and human subjectivity poses challenges for comparing the results of different data sets. These complications call for an automated classification process. This article presents a Bayesian neural network (BNN) classifier to classify event/non-event days of NPF using a manually generated database at the SMEAR II station in Hyytiälä, Finland. For the classification, a set of informative features are extracted exploiting the properties of multi-modal log normal distribution fitted to the aerosol particle concentration database and the properties of the time series representation of the data at different scales. The proposed method has a classification accuracy of 84.2 % for determining event/non-event days. In particular, the BNN method successfully predicts all event days when the growth and formation rate can be determined with a good confidence level (often labeled as class Ia days). Most misclassified days (with an accuracy of 75 %) are the event days of class II, where the determination of growth and formation rate are much more uncertain. Nevertheless, the results reported in this article using the new machine learning-based approach points towards the potential of these methods and suggest further exploration in this direction.

The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and-10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion-pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and-10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, supercooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.

Sulfuric acid is widely recognized as a very important substance driving atmospheric aerosol nucleation. Based on quantum chemical calculations it has been suggested that the quantitative detection of gas phase sulfuric acid (H2SO4) by use of Chemical Ionization Mass Spectrometry (CIMS) could be biased in the presence of gas phase amines such as dimethylamine (DMA). An experiment (CLOUD7 campaign) was set up at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber to investigate the quantitative detection of H2SO4 in the presence of dimethylamine by CIMS at atmospherically relevant concentrations. For the first time in the CLOUD experiment, the monomer sulfuric acid concentration was measured by a CIMS and by two CI-APi-TOF (Chemical Ionization-Atmospheric Pressure interface-Time Of Flight) mass spectrometers. In addition, neutral sulfuric acid clusters were measured with the CI-APi-TOFs. The CLOUD7 measurements show that in the presence of dimethylamine (<5 to 70 pptv) the sulfuric acid monomer measured by the CIMS represents only a fraction of the total H2SO4, contained in the monomer and the clusters that is available for particle growth. Although it was found that the addition of dimethylamine dramatically changes the H2SO4 cluster distribution compared to binary (H2SO4-H2O) conditions, the CIMS detection efficiency does not seem to depend substantially on whether an individual H2SO4 monomer is clustered with a DMA molecule. The experimental observations are supported by numerical simulations based on A Self-contained Atmospheric chemistry coDe coupled with a molecular process model (Sulfuric Acid Water NUCleation) operated in the kinetic limit.

Sulfuric acid, amines and oxidized organics have been found to be important compounds in the nucleation and initial growth of atmospheric particles. Because of the challenges involved in determining the chemical composition of objects with very small mass, however, the properties of the freshly nucleated particles and the detailed pathways of their formation processes are still not clear. In this study,we focus on a challenging size range, i.e., particles that have grown to diameters of 10 and 15 nm following nucleation, and measure their water uptake. Water uptake is useful information for indirectly obtaining chemical composition of aerosol particles. We use a nanometer-hygroscopicity tandem differential mobility analyzer (nano-HTDMA) at sub-saturated conditions (ca. 90% relative humidity at 293 K) to measure the hygroscopicity of particles during the seventh Cosmics Leaving OUtdoor Droplets (CLOUD7) campaign performed at CERN in 2012. In CLOUD7, the hygroscopicity of nucleated nanoparticles was measured in the presence of sulfuric acid, sulfuric acid-dimethylamine, and sulfuric acid-organics derived from alpha-pinene oxidation. The hygroscopicity parameter kappa decreased with increasing particle size, indicating decreasing acidity of particles. No clear effect of the sulfuric acid concentration on the hygroscopicity of 10 nm particles produced from sulfuric acid and dimethylamine was observed, whereas the hygroscopicity of 15 nm particles sharply decreased with decreasing sulfuric acid concentrations. In particular, when the concentration of sulfuric acid was 5.1 x 10(6) molecules cm(-3) in the gas phase, and the dimethylamine mixing ratio was 11.8 ppt, the measured kappa of 15 nm particles was 0.31 +/- 0.01: close to the value reported for dimethylaminium sulfate (DMAS) (kappa(DMAS) similar to 0.28). Furthermore, the difference in kappa between sulfuric acid and sulfuric acid-dimethylamine experiments increased with increasing particle size. The kappa values of

The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and -10 degrees C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion-pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and -10 degrees C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, supercooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 degrees C is correct.

Aerosol formation from biogenic and anthropogenic precursor trace gases in continental background areas affects climate via altering the amount of available cloud condensation nuclei. Significant uncertainty still exists regarding the agents controlling the formation of aerosol nanoparticles. We have performed experiments in the Julich plant-atmosphere simulation chamber with instrumentation for the detection of sulfuric acid and nanoparticles, and present the first simultaneous chamber observations of nanoparticles, sulfuric acid, and realistic levels and mixtures of biogenic volatile compounds (BVOCs). We present direct laboratory observations of nanoparticle formation from sulfuric acid and realistic BVOC precursor vapour mixtures performed at atmospherically relevant concentration levels. We directly measured particle formation rates separately from particle growth rates. From this, we established that in our experiments, the formation rate was proportional to the product of sulfuric acid and biogenic VOC emission strength. The formation rates were consistent with a mechanism in which nucleating BVOC oxidation products are rapidly formed and activate with sulfuric acid. The growth rate of nanoparticles immediately after birth was best correlated with estimated products resulting from BVOC ozonolysis.

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 mu g 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.

The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and-10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion-pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and-10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, supercooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.

Sulfuric acid is widely recognized as a very important substance driving atmospheric aerosol nucleation. Based on quantum chemical calculations it has been suggested that the quantitative detection of gas phase sulfuric acid (H2SO4) by use of Chemical Ionization Mass Spectrometry (CIMS) could be biased in the presence of gas phase amines such as dimethylamine (DMA). An experiment (CLOUD7 campaign) was set up at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber to investigate the quantitative detection of H2SO4 in the presence of dimethylamine by CIMS at atmospherically relevant concentrations. For the first time in the CLOUD experiment, the monomer sulfuric acid concentration was measured by a CIMS and by two CI-APi-TOF (Chemical Ionization-Atmospheric Pressure interface-Time Of Flight) mass spectrometers. In addition, neutral sulfuric acid clusters were measured with the CI-APi-TOFs. The CLOUD7 measurements show that in the presence of dimethylamine (<5 to 70 pptv) the sulfuric acid monomer measured by the CIMS represents only a fraction of the total H2SO4, contained in the monomer and the clusters that is available for particle growth. Although it was found that the addition of dimethylamine dramatically changes the H2SO4 cluster distribution compared to binary (H2SO4-H2O) conditions, the CIMS detection efficiency does not seem to depend substantially on whether an individual H2SO4 monomer is clustered with a DMA molecule. The experimental observations are supported by numerical simulations based on A Self-contained Atmospheric chemistry coDe coupled with a molecular process model (Sulfuric Acid Water NUCleation) operated in the kinetic limit.

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.

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.

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.

Condensation of water vapor on active cloud condensation nuclei produces micron-size water droplets. To form rain, they must grow rapidly into at least 50-to 100-mu m droplets. Observations show that this process takes only 15-20 min. The unexplained physical mechanism of such fast growth is crucial for understanding and modeling of rain and known as "condensation-coalescence bottleneck in rain formation." We show that the recently discovered phenomenon of the tangling clustering instability of small droplets in temperature-stratified turbulence [Phys. Fluids 25, 085104 (2013)] results in the formation of droplet clusters with drastically increased droplet number densities. The mechanism of the tangling clustering instability is much more effective than the previously considered by us the inertial clustering instability caused by the centrifugal effect of turbulent vortices. This is the reason of strong enhancement of the collision-coalescence rate inside the clusters. The mean-field theory of the droplet growth developed in this study can be useful for explanation of the observed fast growth of cloud droplets in warm clouds from the initial 1-mu m-size droplets to 40- to 50-mu m-size dropletswithin 15-20 min., QC 20150814

The growth of aerosol due to the aqueous phase oxidation of SO2 by O3 was measured in laboratory generated clouds created in the CLOUD chamber at CERN. Experiments were performed at 10 and −10 °C, on acidic (sulphuric acid) and on partially to fully neutralised (ammonium sulphate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted by oxidation rates previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system are well represented by accepted rates, based on bulk measurements. To the best of our knowledge, these are the first laboratory based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rates to temperatures below 0 °C is correct.

Condensation of water vapor on active cloud condensation nuclei produces micron-size water droplets. To form rain, they must grow rapidly into at least 50-to 100-mu m droplets. Observations show that this process takes only 15-20 min. The unexplained physical mechanism of such fast growth is crucial for understanding and modeling of rain and known as condensation-coalescence bottleneck in rain formation. We show that the recently discovered phenomenon of the tangling clustering instability of small droplets in temperature-stratified turbulence [Phys. Fluids 25, 085104 (2013)] results in the formation of droplet clusters with drastically increased droplet number densities. The mechanism of the tangling clustering instability is much more effective than the previously considered by us the inertial clustering instability caused by the centrifugal effect of turbulent vortices. This is the reason of strong enhancement of the collision-coalescence rate inside the clusters. The mean-field theory of the droplet growth developed in this study can be useful for explanation of the observed fast growth of cloud droplets in warm clouds from the initial 1-mu m-size droplets to 40- to 50-mu m-size dropletswithin 15-20 min.

The integrated land ecosystem-atmosphere processes study (iLEAPS) is an international research project focussing on the fundamental processes that link land-atmosphere exchange, climate, the water cycle, and tropospheric chemistry. The project, iLEAPS, was established 2004 within the International Geosphere-Biosphere Programme (IGBP). During its first decade, iLEAPS has proven to be a vital project, well equipped to build a community to address the challenges involved in understanding the complex Earth system: multidisciplinary, integrative approaches for both observations and modeling. The iLEAPS community has made major advances in process understanding, land-surface modeling, and observation techniques and networks. The modes of iLEAPS operation include elucidating specific iLEAPS scientific questions through networks of process studies, field campaigns, modeling, long-term integrated field studies, international interdisciplinary mega-campaigns, synthesis studies, databases, as well as conferences on specific scientific questions and synthesis meetings. Another essential component of iLEAPS is knowledge transfer and it also encourages community-and policy-related outreach activities associated with the regional integrative projects. As a result of its first decade of work, iLEAPS is now setting the agenda for its next phase (2014-2024) under the new international initiative, future Earth. Human influence has always been an important part of land-atmosphere science but in order to respond to the new challenges of global sustainability, closer ties with social science and economics groups will be necessary to produce realistic estimates of land use and anthropogenic emissions by analysing future population increase, migration patterns, food production allocation, land management practices, energy production, industrial development, and urbanization.

The Pan-Eurasian Experiment (PEEX) is a multidisciplinary, multiscale and multicomponent research, research infrastructure and capacity-building program. PEEX has originated from a bottom-up approach by the science communities and is aiming at resolving the major uncertainties in Earth system science and global sustainability issues concerning the Arctic and boreal pan-Eurasian regions, as well as China. The vision of PEEX is to solve interlinked, global grand challenges influencing human well-being and societies in northern Eurasia and China. Such challenges include climate change; air quality; biodiversity loss; urbanization; chemicalization; food and freshwater availability; energy production; and use of natural resources by mining, industry, energy production and transport sectors. Our approach is integrative and supra-disciplinary, recognizing the important role of the Arctic and boreal ecosystems in the Earth system. The PEEX vision includes establishing and maintaining long-term, coherent and coordinated research activities as well as continuous, comprehensive research and educational infrastructure and related capacity-building across the PEEX domain. In this paper we present the PEEX structure and summarize its motivation, objectives and future outlook.

The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and the particle phase) or a kinetic approach (accounting for the size dependence of condensation). We show that model treatment of the partitioning of biogenic organic vapours into the particle phase, and consequent distribution of material across the size distribution, controls the magnitude of the first aerosol indirect effect (AIE) due to biogenic secondary organic aerosol (SOA). With a kinetic partitioning approach, SOA is distributed according to the existing condensation sink, enhancing the growth of the smallest particles, i.e. those in the nucleation mode. This process tends to increase cloud droplet number concentrations in the presence of biogenic SOA. By contrast, an approach that distributes SOA according to pre-existing organic mass restricts the growth of the smallest particles, limiting the number that are able to form cloud droplets. With an organically mediated new particle formation mechanism, applying a mass-based rather than a kinetic approach to partitioning reduces our calculated global mean AIE due to biogenic SOA by 24 %. Our results suggest that the mechanisms driving organic partitioning need to be fully understood in order to accurately describe the climatic effects of SOA.

The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and the particle phase) or a kinetic approach (accounting for the size dependence of condensation). We show that model treatment of the partitioning of biogenic organic vapours into the particle phase, and consequent distribution of material across the size distribution, controls the magnitude of the first aerosol indirect effect (AIE) due to biogenic secondary organic aerosol (SOA). With a kinetic partitioning approach, SOA is distributed according to the existing condensation sink, enhancing the growth of the smallest particles, i.e. those in the nucleation mode. This process tends to increase cloud droplet number concentrations in the presence of biogenic SOA. By contrast, an approach that distributes SOA according to pre-existing organic mass restricts the growth of the smallest particles, limiting the number that are able to form cloud droplets. With an organically mediated new particle formation mechanism, applying a mass-based rather than a kinetic approach to partitioning reduces our calculated global mean AIE due to biogenic SOA by 24 %. Our results suggest that the mechanisms driving organic partitioning need to be fully understood in order to accurately describe the climatic effects of SOA.

Air ion concentrations influence new particle formation and consequently the global aerosol as potential cloud condensation nuclei. We aimed to evaluate air ion concentrations and characteristics of new particle formation events (NPF) in the megacity of Paris, France, within the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric Pollution and climate effects, and Integrated tools for assessment and mitigation) project. We measured air ion number size distributions (0.8-42 nm) with an air ion spectrometer and fine particle number concentrations (>6 nm) with a twin differential mobility particle sizer in an urban site of Paris between 26 June 2009 and 4 October 2010. Air ions were size classified as small (0.82 nm), intermediate (2-7 nm), and large (7-20 nm). The median concentrations of small and large ions were 670 and 680 cm 3, respectively, (sum of positive and negative polarities), whereas the median concentration of intermediate ions was only 20 cm 3, as these ions were mostly present during new particle formation bursts, i.e. when gas-to-particle conversion produced fresh aerosol particles from gas phase precursors. During peaks in traffic-related particle number, the concentrations of small and intermediate ions decreased, whereas the concentrations of large ions increased. Seasonal variations affected the ion population differently, with respect to their size and polarity. NPF was observed in 13% of the days, being most frequent in spring and late summer (April, May, July, and August). The results also suggest that NPF was favoured on the weekends in comparison to workdays, likely due to the lower levels of condensation sinks in the mornings of weekends (CS weekdays 09: 00: 18 x 10(-3) s(-1); CS weekend 09:00: 8 x 10(-3) s(-1)). The median growth rates (GR) of ions during the NPF events varied between 3 and 7 nm h(-1), increasing with the ion size and being higher on workdays than on weekends for intermediate and large ions. The median GR

The integrated land ecosystem-atmosphere processes study (iLEAPS) is an international research project focussing on the fundamental processes that link land-atmosphere exchange, climate, the water cycle, and tropospheric chemistry. The project, iLEAPS, was established 2004 within the International Geosphere-Biosphere Programme (IGBP). During its first decade, iLEAPS has proven to be a vital project, well equipped to build a community to address the challenges involved in understanding the complex Earth system: multidisciplinary, integrative approaches for both observations and modeling. The iLEAPS community has made major advances in process understanding, land-surface modeling, and observation techniques and networks. The modes of iLEAPS operation include elucidating specific iLEAPS scientific questions through networks of process studies, field campaigns, modeling, long-term integrated field studies, international interdisciplinary mega-campaigns, synthesis studies, databases, as well as conferences on specific scientific questions and synthesis meetings. Another essential component of iLEAPS is knowledge transfer and it also encourages community- and policy-related outreach activities associated with the regional integrative projects. As a result of its first decade of work, iLEAPS is now setting the agenda for its next phase (2014–2024) under the new international initiative, future Earth. Human influence has always been an important part of land-atmosphere science but in order to respond to the new challenges of global sustainability, closer ties with social science and economics groups will be necessary to produce realistic estimates of land use and anthropogenic emissions by analysing future population increase, migration patterns, food production allocation, land management practices, energy production, industrial development, and urbanization.

The growth of aerosol due to the aqueous phase oxidation of SO2 by O3 was measured in laboratory generated clouds created in the CLOUD chamber at CERN. Experiments were performed at 10 and −10 °C, on acidic (sulphuric acid) and on partially to fully neutralised (ammonium sulphate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted by oxidation rates previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system are well represented by accepted rates, based on bulk measurements. To the best of our knowledge, these are the first laboratory based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rates to temperatures below 0 °C is correct.

The integrated land ecosystem-atmosphere processes study (iLEAPS) is an international research project focussing on the fundamental processes that link land-atmosphere exchange, climate, the water cycle, and tropospheric chemistry. The project, iLEAPS, was established 2004 within the International Geosphere-Biosphere Programme (IGBP). During its first decade, iLEAPS has proven to be a vital project, well equipped to build a community to address the challenges involved in understanding the complex Earth system: multidisciplinary, integrative approaches for both observations and modeling. The iLEAPS community has made major advances in process understanding, land-surface modeling, and observation techniques and networks. The modes of iLEAPS operation include elucidating specific iLEAPS scientific questions through networks of process studies, field campaigns, modeling, long-term integrated field studies, international interdisciplinary mega-campaigns, synthesis studies, databases, as well as conferences on specific scientific questions and synthesis meetings. Another essential component of iLEAPS is knowledge transfer and it also encourages community- and policy-related outreach activities associated with the regional integrative projects. As a result of its first decade of work, iLEAPS is now setting the agenda for its next phase (2014–2024) under the new international initiative, future Earth. Human influence has always been an important part of land-atmosphere science but in order to respond to the new challenges of global sustainability, closer ties with social science and economics groups will be necessary to produce realistic estimates of land use and anthropogenic emissions by analysing future population increase, migration patterns, food production allocation, land management practices, energy production, industrial development, and urbanization.

The integrated land ecosystem-atmosphere processes study (iLEAPS) is an international research project focussing on the fundamental processes that link land-atmosphere exchange, climate, the water cycle, and tropospheric chemistry. The project, iLEAPS, was established 2004 within the International Geosphere-Biosphere Programme (IGBP). During its first decade, iLEAPS has proven to be a vital project, well equipped to build a community to address the challenges involved in understanding the complex Earth system: multidisciplinary, integrative approaches for both observations and modeling. The iLEAPS community has made major advances in process understanding, land-surface modeling, and observation techniques and networks. The modes of iLEAPS operation include elucidating specific iLEAPS scientific questions through networks of process studies, field campaigns, modeling, long-term integrated field studies, international interdisciplinary mega-campaigns, synthesis studies, databases, as well as conferences on specific scientific questions and synthesis meetings. Another essential component of iLEAPS is knowledge transfer and it also encourages community- and policy-related outreach activities associated with the regional integrative projects. As a result of its first decade of work, iLEAPS is now setting the agenda for its next phase (2014-2024) under the new international initiative, future Earth. Human influence has always been an important part of land-atmosphere science but in order to respond to the new challenges of global sustainability, closer ties with social science and economics groups will be necessary to produce realistic estimates of land use and anthropogenic emissions by analysing future population increase, migration patterns, food production allocation, land management practices, energy production, industrial development, and urbanization.

The integrated Land Ecosystem - Atmosphere Processes Study (iLEAPS) is an international research project focussing on the fundamental processes that link land-atmosphere exchange, climate, the water cycle, and troposheric chemistry. The project, iLEAPS, was established 2004 within the International Geosphere-Biosphere Programme (IGBP). During its first decade iLEAPS has proven to be a vital project, well equipped to build a community to address the challenge involved in understanding the complex Earth system: multidisciplinary, integrative approaches for both observations and modelling. The iLEAPS community has made major advances in process understanding, land-surface modelling, and observation techniques and networks. The modes of iLEAPS operation include elucidating specific iLEAPS scientific questions through networks of process studies, field campaigns, modelling, long-term integrated field studies, international interdisciplinary mega-campaigns, synthesis studies databases, as well as conferences on specific scientific questions and synthesis meetings. Another essential component of iEAPS is knowledge transfer and it also encourages community- and policy-related outreach activities associated with the regional integrative projects. As a result of its first decade of work, iLEAPS is now setting the agenda for its next phase (2014-2024) under the new international initiative, Future Earth. Human influence has always been an important part of land-atmosphere science but in order to respond to the new challenges of global sustainability, closer ties with social science and economics groups will be necessary to produce realistic estimates of land use and anthropogenic emissions by analysing future population increase, migration patterns, food production allocation, land management practices, energy production, industrial development, and urbanization.