35 research outputs found

    Fair Beam Allocations through Reconfigurable Intelligent Surfaces

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    A fair beam allocation framework through reconfigurable intelligent surfaces (RISs) is proposed, incorporating the Max-min criterion. This framework focuses on designing explicit beamforming functionalities through optimization. Firstly, realistic models, grounded in geometrical optics, are introduced to characterize the input/output behaviors of RISs, effectively bridging the gap between the requirements on explicit beamforming operations and their practical implementations. Then, a highly efficient algorithm is developed for Max-min optimizations involving quadratic forms. Leveraging the Moreau-Yosida approximation, we successfully reformulate the original problem and propose iterations to attain the optimal solution. A comprehensive analysis of the algorithm's convergence is provided. Importantly, this approach exhibits excellent extensibility, making it readily applicable to address a broader class of Max-min optimization problems. Finally, numerical and prototype experiments are conducted to validate the effectiveness of the framework. With the proposed beam allocation framework and algorithm, we clarify that several crucial redistribution functionalities of RISs, such as explicit beam-splitting, fair beam allocation, and wide-beam generation, can be effectively implemented. These explicit beamforming functionalities have not been thoroughly examined previously

    Impacts of coagulation on the appearance time method for new particle growth rate evaluation and their corrections

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    The growth rate of atmospheric new particles is a key parameter that determines their survival probability of becoming cloud condensation nuclei and hence their impact on the climate. There have been several methods to estimate the new particle growth rate. However, due to the impact of coagulation and measurement uncertainties, it is still challenging to estimate the initial growth rate of new particles, especially in polluted environments with high background aerosol concentrations. In this study, we explore the influences of coagulation on the appearance time method to estimate the growth rate of sub-3 nm particles. The principle of the appearance time method and the impacts of coagulation on the retrieved growth rate are clarified via derivations. New formulae in both discrete and continuous spaces are proposed to correct for the impacts of coagulation. Aerosol dynamic models are used to test the new formulae. New particle formation in urban Beijing is used to illustrate the importance of considering the impacts of coagulation on the sub-3 nm particle growth rate and its calculation. We show that the conventional appearance time method needs to be corrected when the impacts of coagulation sink, coagulation source, and particle coagulation growth are non-negligible compared to the condensation growth. Under the simulation conditions with a constant concentration of non-volatile vapors, the corrected growth rate agrees with the theoretical growth rates. However, the uncorrected parameters, e.g., vapor evaporation and the variation in vapor concentration, may impact the growth rate obtained with the appearance time method. Under the simulation conditions with a varying vapor concentration, the average bias in the corrected 1.5-3 nm particle growth rate ranges from 6 %-44 %, and the maximum bias in the size-dependent growth rate is 150 %. During the test new particle formation event in urban Beijing, the corrected condensation growth rate of sub-3 nm particles was in accordance with the growth rate contributed by sulfuric acid condensation, whereas the conventional appearance time method overestimated the condensation growth rate of 1.5 nm particles by 80 %.Peer reviewe

    Precursor apportionment of atmospheric oxygenated organic molecules using a machine learning method

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    Publisher Copyright: © 2023 The Author(s). Published by the Royal Society of Chemistry.Gas-phase oxygenated organic molecules (OOMs) can contribute significantly to both atmospheric new particle growth and secondary organic aerosol formation. Precursor apportionment of atmospheric OOMs connects them with volatile organic compounds (VOCs). Since atmospheric OOMs are often highly functionalized products of multistep reactions, it is challenging to reveal the complete mapping relationships between OOMs and their precursors. In this study, we demonstrate that the machine learning method is useful in attributing atmospheric OOMs to their precursors using several chemical indicators, such as O/C ratio and H/C ratio. The model is trained and tested using data acquired in controlled laboratory experiments, covering the oxidation products of four main types of VOCs (isoprene, monoterpenes, aliphatics, and aromatics). Then, the model is used for analyzing atmospheric OOMs measured in both urban Beijing and a boreal forest environment in southern Finland. The results suggest that atmospheric OOMs in these two environments can be reasonably assigned to their precursors. Beijing is an anthropogenic VOC dominated environment with ~64% aromatic and aliphatic OOMs, and the other boreal forested area has ~76% monoterpene OOMs. This pilot study shows that machine learning can be a promising tool in atmospheric chemistry for connecting the dots.Peer reviewe

    Acid-Base Clusters during Atmospheric New Particle Formation in Urban Beijing

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    Molecular clustering is the initial step of atmospheric new particle formation (NPF) that generates numerous secondary particles. Using two online mass spectrometers with and without a chemical ionization inlet, we characterized the neutral clusters and the naturally charged ion clusters during NPF periods in urban Beijing. In ion clusters, we observed pure sulfuric acid (SA) clusters, SA-amine clusters, SA-ammonia (NH3) clusters, and SA-amine-NH3 clusters. However, only SA clusters and SA-amine clusters were observed in the neutral form. Meanwhile, oxygenated organic molecule (OOM) clusters charged by a nitrate ion and a bisulfate ion were observed in ion clusters. Acid-base clusters correlate well with the occurrence of sub-3 nm particles, whereas OOM clusters do not. Moreover, with the increasing cluster size, amine fractions in ion acid-base clusters decrease, while NH3 fractions increase. This variation results from the reduced stability differences between SA-amine clusters and SA-NH3 clusters, which is supported by both quantum chemistry calculations and chamber experiments. The lower average number of dimethylamine (DMA) molecules in atmospheric ion clusters than the saturated value from controlled SA-DMA nucleation experiments suggests that there is insufficient DMA in urban Beijing to fully stabilize large SA clusters, and therefore, other basic molecules such as NH3 play an important role.Peer reviewe

    Contribution of Atmospheric Oxygenated Organic Compounds to Particle Growth in an Urban Environment

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    Gas-phase oxygenated organic molecules (OOMs) can contribute substantially to the growth of newly formed particles. However, the characteristics of OOMs and their contributions to particle growth rate are not well understood in urban areas, which have complex anthropogenic emissions and atmospheric conditions. We performed long-term measurement of gas-phase OOMs in urban Beijing during 2018-2019 using nitrate-based chemical ionization mass spectrometry. OOM concentrations showed clear seasonal variations, with the highest in the summer and the lowest in the winter. Correspondingly, calculated particle growth rates due to OOM condensation were highest in summer, followed by spring, autumn, and winter. One prominent feature of OOMs in this urban environment was a high fraction (similar to 75%) of nitrogen-containing OOMs. These nitrogen-containing OOMs contributed only 50-60% of the total growth rate led by OOM condensation, owing to their slightly higher volatility than non-nitrate OOMs. By comparing the calculated condensation growth rates and the observed particle growth rates, we showed that sulfuric acid and its clusters are the main contributors to the growth of sub-3 nm particles, with OOMs significantly promoting the growth of 3-25 nm particles. In wintertime Beijing, however, there are missing contributors to the growth of particles above 3 nm, which remain to be further investigated.Peer reviewe

    Responses of gaseous sulfuric acid and particulate sulfate to reduced SO2 concentration : A perspective from long-term measurements in Beijing

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    SO2 concentration decreased rapidly in recent years in China due to the implementation of strict control policies by the government. Particulate sulfate (pSO(4)(2-)) and gaseous H2SO4 (SA) are two major products of SO2 and they play important roles in the haze formation and new particle formation (NPF), respectively. We examined the change in pSO(4)(2-) and SA concentrations in response to reduced SO2 concentration using long-term measurement data in Beijing. Simulations from the Community Multiscale Air Quality model with a 2-D Volatility Basis Set (CMAQ/2D-VBS) were used for comparison. From 2013 to 2018, SO2 concentration in Beijing decreased by similar to 81% (from 9.1 ppb to 1.7 ppb). pSO(4)(2-) concentration in submicrometer particles decreased by similar to 60% from 2012-2013 (monthly average of similar to 10 mu g.m(-3)) to 2018-2019 (monthly average of similar to 4 mu g.m(-3)). Accordingly, the fraction of pSO(4)(2-) in these particles decreased from20-30% to b10%. Increased sulfur oxidation ratio was observed both in the measurements and the CMAQ/2D-VBS simulations. Despite the reduction in SO2 concentration, there was no obvious decrease in SA concentration based on data from several measuring periods from 2008 to 2019. This was supported by the increased SA:SO2 ratio with reduced SO2 concentration and condensation sink. NPF frequency in Beijing between 2004 and 2019 remains relatively constant. This constant NPF frequency is consistent with the relatively stable SA concentration in Beijing, while different from some other cities where NPF frequency was reported to decrease with decreased SO2 concentrations. (C) 2020 Elsevier B.V. All rights reserved.Peer reviewe

    Sulfuric acid-amine nucleation in urban Beijing

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    New particle formation (NPF) is one of the major sources of atmospheric ultrafine particles. Due to the high aerosol and trace gas concentrations, the mechanism and governing factors for NPF in the polluted atmospheric boundary layer may be quite different from those in clean environments, which is however less understood. Herein, based on long-term atmospheric measurements from January 2018 to March 2019 in Beijing, the nucleation mechanism and the influences of H2SO4 concentration, amine concentrations, and aerosol concentration on NPF are quantified. The collision of H2SO4-amine clusters is found to be the dominating mechanism to initialize NPF in urban Beijing. The coagulation scavenging due to the high aerosol concentration is a governing factor as it limits the concentration of H2SO4-amine clusters and new particle formation rates. The formation of H2SO4-amine clusters in Beijing is sometimes limited by low amine concentrations. Summarizing the synergistic effects of H2SO4 concentration, amine concentrations, and aerosol concentration, we elucidate the governing factors for H2SO4-amine nucleation for various conditions.Peer reviewe

    Particle growth with photochemical age from new particle formation to haze in the winter of Beijing, China

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    Secondary aerosol formation in the aging process of primary emission is the main reason for haze pollution in eastern China. Pollution evolution with photochemical age was studied for the first time at a comprehensive field observation station during winter in Beijing. The photochemical age was used as an estimate of the time scale attributed to the aging process and was estimated from the ratio of toluene to benzene in this study. A low photochemical age indicates a fresh emission. The photochemical age of air masses during new particle formation (NPF) days was lower than that on haze days. In general, the strongest NPF events, along with a peak of the formation rate of 1.5 nm(J(1.5)) and 3 nmparticles (J(3)), were observed when the photochemical age was between 12 and 24 h while rarely took place with photochemical ages less than 12 h. When photochemical age was larger than 48 h, haze occurred and NPF was suppressed. The sources and sinks of nanoparticles had distinct relation with the photochemical age. Our results show that the condensation sink (CS) showed a valley with photochemical ages ranging from 12 to 24 h, while H2SO4 concentration showed no obvious trend with the photochemical age. The high concentrations of precursor vapours within an air mass lead to persistent nucleation with photochemical age ranging from 12 to 48 h in winter. Coincidently, the fast increase of PM2.5 mass was also observed during this range of photochemical age. Noteworthy, CS increased with the photochemical age on NPF days only, which is the likely reason for the observation that the PM2.5 mass increased faster with photochemical age on NPF days compared with other days. The evolution of particles with the photochemical age provides new insights into understanding how particles originating from NPF transform to haze pollution. (C) 2020 Elsevier B.V. All rights reserved.Peer reviewe

    The missing base molecules in atmospheric acid-base nucleation

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    Forming an (H2SO4)(1)(amine)(1) cluster is the rate-limiting step in atmospheric H2SO4-amine nucleation, which governs the fast formation of new particles from gaseous precursors.Transformation of low-volatility gaseous precursors to new particles affects aerosol number concentration, cloud formation and hence the climate. The clustering of acid and base molecules is a major mechanism driving fast nucleation and initial growth of new particles in the atmosphere. However, the acid-base cluster composition, measured using state-of-the-art mass spectrometers, cannot explain the measured high formation rate of new particles. Here we present strong evidence for the existence of base molecules such as amines in the smallest atmospheric sulfuric acid clusters prior to their detection by mass spectrometers. We demonstrate that forming (H2SO4)(1)(amine)(1) is the rate-limiting step in atmospheric H2SO4-amine nucleation and the uptake of (H2SO4)(1)(amine)(1) is a major pathway for the initial growth of H2SO4 clusters. The proposed mechanism is very consistent with measured new particle formation in urban Beijing, in which dimethylamine is the key base for H2SO4 nucleation while other bases such as ammonia may contribute to the growth of larger clusters. Our findings further underline the fact that strong amines, even at low concentrations and when undetected in the smallest clusters, can be crucial to particle formation in the planetary boundary layer.Peer reviewe
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