Aerosol mass yields of selected biogenic volatile organic compounds– a theoretical study with nearly explicit gas-phase chemistry

In this study we modeled secondary organic aerosol (SOA) mass loadings from the oxidation (by O-3, OH and NO3) of five representative biogenic volatile organic compounds (BVOCs): isoprene, endocyclic bond-containing monoterpenes (alpha-pinene and limonene), exocyclic double-bond compound (beta-pinene) and a sesquiterpene (beta-caryophyllene). The simulations were designed to replicate an idealized smog chamber and oxidative flow reactors (OFRs). The Master Chemical Mechanism (MCM) together with the peroxy radical autoxidation mechanism (PRAM) were used to simulate the gas-phase chemistry. The aim of this study was to compare the potency of MCM and MCM + PRAM in predicting SOA formation. SOA yields were in good agreement with experimental values for chamber simulations when MCM + PRAM was applied, while a stand-alone MCM underpredicted the SOA yields. Compared to experimental yields, the OFR simulations using MCM + PRAM yields were in good agreement for BVOCs oxidized by both O-3 and OH. On the other hand, a stand-alone MCM underpredicted the SOA mass yields. SOA yields increased with decreasing temperatures and NO concentrations and vice versa. This highlights the limitations posed when using fixed SOA yields in a majority of global and regional models. Few compounds that play a crucial role (> 95% of mass load) in contributing to SOA mass increase (using MCM + PRAM) are identified. The results further emphasized that incorporating PRAM in conjunction with MCM does improve SOA mass yield estimation.Peer reviewe

SOSAA — a new model to simulate the concentrations of organic vapours, sulphuric acid and aerosols inside the ABL — Part 2: Aerosol dynamics and one case study at a boreal forest site

Natural and anthropogenic aerosols may have a great impact on climate as they directly interact with solar radiation and indirectly affect the Earth’s radiation balance and precipitation by modifying clouds. In order to quantify the direct and indirect effects, it is essential to understand the complex processes that connect aerosol particles to cloud droplets. Modern measurement techniques are able to detect particle sizes down to 1 nm in diameter, from ground to the stratosphere. However, the data are not sufficient in order to fully understand the processes. Here we demonstrate how the newly developed one-dimensional column model SOSAA was used to investigate the complex processes of aerosols at a boreal forest site for a six-month period during the spring and summer of 2010. Two nucleation mechanisms (kinetic and organic) were tested in this study, and both mechanisms produced a good prediction of the particle number concentrations in spring. However, overestimation of the particle number concentration in summer by the organic mechanism suggests that the OH oxidation products from monoterpenes may not be the essential compounds in atmospheric nucleation. In general, SOSAA was correct in predicting new particle formation events for 35% of the time and partly correct for 45% of the time.Peer reviewe

Delineation of dew formation zones in Iran using long-term model simulations and cluster analysis

Dew is a non-conventional source of water that has been gaining interest over the last two decades, especially in arid and semi-arid regions. In this study, we performed a long-term (1979-2018) energy balance model simulation to estimate dew formation potential in Iran aiming to identify dew formation zones and to investigate the impacts of long-term variation in meteorological parameters on dew formation. The annual average of dew occurrence in Iran was similar to 102 d, with the lowest number of dewy days in summer (similar to 7 d) and the highest in winter (similar to 45 d). The average daily dew yield was in the range of 0.03-0.14 Lm(-2) and the maximum was in the range of 0.29-0.52 Lm(-2). Six dew formation zones were identified based on cluster analysis of the time series of the simulated dew yield. The distribution of dew formation zones in Iran was closely aligned with topography and sources of moisture. Therefore, the coastal zones in the north and south of Iran (i.e., Caspian Sea and Oman Sea), showed the highest dew formation potential, with 53 and 34 Lm(-2) yr(-2), whereas the dry interior regions (i.e., central Iran and the Lut Desert), with the average of 12-18 Lm(-2) yr(-2), had the lowest potential for dew formation. Dew yield estimation is very sensitive to the choice of the heat transfer coefficient. The uncertainty analysis of the heat transfer coefficient using eight different parameterizations revealed that the parameterization used in this study the Richards (2004) formulation - gives estimates that are similar to the average of all methods and are neither much lower nor much higher than the majority of other parameterizations and the largest differences occur for the very low values of daily dew yield. Trend analysis results revealed a significant (p < 0:05) negative trend in the yearly dew yield in most parts of Iran during the last 4 decades (1979-2018). Such a negative trend in dew formation is likely due to an increase in air temperature and a decrease in relative humidity and cloudiness over the 40 years.Peer reviewe

Comprehensive modelling study on observed new particle formation at the SORPES station in Nanjing, China

New particle formation (NPF) has been investigated intensively during the last 2 decades because of its influence on aerosol population and the possible contribution to cloud condensation nuclei. However, intensive measurements and modelling activities on this topic in urban metropolitan areas in China with frequent high-pollution episodes are still very limited. This study provides results from a comprehensive modelling study on the occurrence of NPF events in the western part of the Yangtze River Delta (YRD) region, China. The comprehensive modelling system, which combines the WRF-Chem (the Weather Research and Forecasting model coupled with Chemistry) regional chemical transport model and the MALTE-BOX sectional box model (the model to predict new aerosol formation in the lower troposphere), was shown to be capable of simulating atmospheric nucleation and subsequent growth. Here we present a detailed discussion of three typical NPF days, during which the measured air masses were notably influenced by either anthropogenic activities, biogenic emissions, or mixed ocean and continental sources. Overall, simulated NPF events were generally in good agreement with the corresponding measurements, enabling us to get further insights into NPF processes in the YRD region. Based on the simulations, we conclude that biogenic organic compounds, particularly monoterpenes, play an essential role in the initial condensational growth of newly formed clusters through their low-volatility oxidation products. Although some uncertain-ties remain in this modelling system, this method provides a possibility to better understand particle formation and growth processes.Peer reviewe

Is reducing new particle formation a plausible solution to mitigate particulate air pollution in Beijing and other Chinese megacities?

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.Peer reviewe

Continuous and comprehensive atmospheric observations in Beijing : a station to understand the complex urban atmospheric environment

Peer reviewe

Modelling ELVOC contribution to particle growth

I modelled the contribution of extremely low volatility organic compounds, ELVOC, to particle growth in simple conditions. This included a background aerosol particles that were allowed to develop with the gas phase for 7 hours and particles injected and grown for 8 subsequent hours. The composition and size of the injected particles was analysed. The model used to do this was MALTE- BOX with MCM 3.3 chemistry for α-pinene and inorganic molecules and an ELVOC generation mechanism developed in the group. The density, saturation vapour pressure and diffusion coefficient for these vapours were estimated using several methods from literature. The estimation shows that 21 of the 37 stable molecules in the generating mechanism, would be classified as ELVOC at 293.15 K. The resulting particle growth and composition shows similarities to already published results, where ELVOC contribution is large at early stages of particle growth and diminishes as less volatile compounds are able to condense. The contribution of ELVOC also reacts sensibly to changes in ambient conditions and remains important for early particle growth in all cases studied

A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization

Peer reviewe

Modelling studies of HOMs and their contributions to new particle formation and growth : comparison of boreal forest in Finland and a polluted environment in China

Highly oxygenated multifunctional compounds (HOMs) play a key role in new particle formation (NPF), but their quantitative roles in different environments of the globe have not been well studied yet. Frequent NPF events were observed at two "flagship" stations under different environmental conditions, i.e. a remote boreal forest site (SMEAR II) in Finland and a suburban site (SORPES) in polluted eastern China. The averaged formation rate of 6 nm particles and the growth rate of 6-30 nm particles were 0.3 cm(-3) s(-1) and 4.5 nm h(-1) at SMEAR II compared to 2.3 cm(-3) s(-1) and 8.7 nm h(-1) at SORPES, respectively. To explore the differences of NPF at the two stations, the HOM concentrations and NPF events at two sites were simulated with the MALTE-BOX model, and their roles in NPF and particle growth in the two distinctly different environments are discussed. The model provides an acceptable agreement between the simulated and measured concentrations of sulfuric acid and HOMs at SMEAR II. The sulfuric acid and HOM organonitrate concentrations are significantly higher but other HOM monomers and dimers from monoterpene oxidation are lower at SORPES compared to SMEAR II. The model simulates the NPF events at SMEAR II with a good agreement but underestimates the growth of new particles at SORPES, indicating a dominant role of anthropogenic processes in the polluted environment. HOMs from monoter-pene oxidation dominate the growth of ultrafine particles at SMEAR II while sulfuric acid and HOMs from aromatics oxidation play a more important role in particle growth. This study highlights the distinct roles of sulfuric acid and HOMs in NPF and particle growth in different environmental conditions and suggests the need for molecular-scale measurements in improving the understanding of NPF mechanisms in polluted areas like eastern China.Peer reviewe

SMEARcore - modular data infrastructure for atmospheric measurement stations

We present the SMEARcore data infrastructure framework: a collection of modular programs and processing workflows intended for measurement stations and campaigns as a real-time data analysis and management platform. SMEARcore enables new SMEAR (Station for Measuring Ecosystem-Atmosphere Relations) stations to be integrated in a way that is consistent with existing stations and transfers the existing data curation experience to the new station. It establishes robust data pipelines that allow easier diagnosis of problems. We show practical examples of how SMEARcore is utilized at operational measurement stations. This work differs from earlier similar concepts, such as those used at stations within ACTRIS (Aerosols, Clouds and Trace Gases Research Infrastructure) and ICOS (Integrated Carbon Observation System) networks, in three important aspects: firstly, by keeping all the processing under the control of the data owners; secondly, by providing tools for making data interoperable in general instead of harmonizing a particular set of instruments; and thirdly, by being extensible to new instruments. As such it is not meant as a replacement for these infrastructures but to be used in addition to them and to bring structured data curation to more measurement stations not yet using these practices.Peer reviewe