Partial Consistency with Sparse Incidental Parameters

Penalized estimation principle is fundamental to high-dimensional problems. In the literature, it has been extensively and successfully applied to various models with only structural parameters. As a contrast, in this paper, we apply this penalization principle to a linear regression model with a finite-dimensional vector of structural parameters and a high-dimensional vector of sparse incidental parameters. For the estimators of the structural parameters, we derive their consistency and asymptotic normality, which reveals an oracle property. However, the penalized estimators for the incidental parameters possess only partial selection consistency but not consistency. This is an interesting partial consistency phenomenon: the structural parameters are consistently estimated while the incidental ones cannot. For the structural parameters, also considered is an alternative two-step penalized estimator, which has fewer possible asymptotic distributions and thus is more suitable for statistical inferences. We further extend the methods and results to the case where the dimension of the structural parameter vector diverges with but slower than the sample size. A data-driven approach for selecting a penalty regularization parameter is provided. The finite-sample performance of the penalized estimators for the structural parameters is evaluated by simulations and a real data set is analyzed

Seasonal Characteristics of New Particle Formation and Growth in Urban Beijing

Understanding the atmospheric new particle formation (NPF) process within the global range is important for revealing the budget of atmospheric aerosols and their impacts. We investigated the seasonal characteristics of NPF in the urban environment of Beijing. Aerosol size distributions down to similar to 1 nm and H2SO4 concentration were measured during 2018-2019. The observed formation rate of 1.5 nm particles (J(1.5)) is significantly higher than those in the clean environment, e.g., Hyytiala, whereas the growth rate is not significantly different. Both J(1.5) and NPF frequency in urban Beijing show a clear seasonal variation with maxima in winter and minima in summer, while the observed growth rates are generally within the same range around the year. We show that ambient temperature is a governing factor driving the seasonal variation of J(1.5). In contrast, the condensation sink and the daily maximum H2SO4 concentration show no significant seasonal variation during the NPF periods. In all four seasons, condensation of H2SO4 and (H2SO4)(n)(amine)(n) clusters contributes significantly to the growth rates in the sub-3 nm size range, whereas it is less important for the observed growth rates of particles above 3 nm. Therefore, other species are always needed for the growth of larger particles.Peer reviewe

Influence of Aerosol Chemical Composition on Condensation Sink Efficiency and New Particle Formation in Beijing

Relatively high concentrations of preexisting particles, acting as a condensation sink (CS) of gaseous precursors, have been thought to suppress the occurrence of new particle formation (NPF) in urban environments, yet NPF still occurs frequently. Here, we aim to understand the factors promoting and inhibiting NPF events in urban Beijing by combining one-year-long measurements of particle number size distributions and PM2.5 chemical composition. Our results show that indeed the CS is an important factor controlling the occurrence of NPF events, with its chemical composition affecting the efficiency of the background particles in removing gaseous H2SO4 (effectiveness of the CS) driving NPF. During our observation period, the CS was found to be more effective for ammonium nitrate-rich (NH4NO3-rich) fine particles. On non-NPF event days, particles acting as CS contained a larger fraction of NH4NO3 compared to NPF event days under comparable CS levels. In particular, in the CS range from 0.02 to 0.03 s(-1), the nitrate fraction was 17% on NPF event days and 26% on non-NPF event days. Overall, our results highlight the importance of considering the chemical composition of preexisting particles when estimating the CS and their role in inhibiting NPF events, especially in urban environments.Peer reviewe

Rapid mass growth and enhanced light extinction of atmospheric aerosols during the heating season haze episodes in Beijing revealed by aerosol-chemistry-radiation-boundary layer interaction

Despite the numerous studies investigating haze formation mechanism in China, it is still puzzling that intensive haze episodes could form within hours directly following relatively clean periods. Haze has been suggested to be initiated by the variation of meteorological parameters and then to be substantially enhanced by aerosol-radiation-boundary layer feedback. However, knowledge on the detailed chemical processes and the driving factors for extensive aerosol mass accumulation during the feedback is still scarce. Here, the dependency of the aerosol number size distribution, mass concentration and chemical composition on the daytime mixing layer height (MLH) in urban Beijing is investigated. The size distribution and chemical composition-resolved dry aerosol light extinction is also explored. The results indicate that the aerosol mass concentration and fraction of nitrate increased dramatically when the MLH decreased from high to low conditions, corresponding to relatively clean and polluted conditions, respectively. Particles having their dry diameters in the size of similar to 400-700 nm, and especially particle-phase ammonium nitrate and liquid water, contributed greatly to visibility degradation during the winter haze periods. The dependency of aerosol composition on the MLH revealed that ammonium nitrate and aerosol water content increased the most during low MLH conditions, which may have further triggered enhanced formation of sulfate and organic aerosol via heterogeneous reactions. As a result, more sulfate, nitrate and water-soluble organics were formed, leading to an enhanced water uptake ability and increased light extinction by the aerosols. The results of this study contribute towards a more detailed understanding of the aerosol-chemistry-radiation-boundary layer feedback that is likely to be responsible for explosive aerosol mass growth events in urban Beijing.Peer reviewe

The effect of COVID-19 restrictions on atmospheric new particle formation in Beijing

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

SHRIMP zircon dating and LA-ICPMS Hf analysis of early Precambrian rocks from drill holes into the basement beneath the Central Hebei Basin, North China Craton

The Central Hebei Basin (CHB) is one of the largest sedimentary basins in the North China Craton, extending in a northeast–southwest direction with an area of >350 km2. We carried out SHRIMP zircon dating, Hf-in-zircon isotopic analysis and a whole-rock geochemical study on igneous and metasedimentary rocks recovered from drill holes that penetrated into the basement of the CHB. Two samples of gneissic granodiorite (XG1-1) and gneissic quartz diorite (J48-1) have magmatic ages of 2500 and 2496 Ma, respectively. Their zircons also record metamorphic ages of 2.41–2.51 and ∼2.5 Ga, respectively. Compared with the gneissic granodiorite, the gneissic quartz diorite has higher ΣREE contents and lower Eu/Eu* and (La/Yb)n values. Two metasedimentary samples (MG1, H5) mainly contain ∼2.5 Ga detrital zircons as well as late Paleoproterozoic metamorphic grains. The zircons of different origins have εHf (2.5 Ga) values and Hf crustal model ages ranging from 0 to 5 and 2.7 to 2.9 Ga, respectively. Therefore, ∼2.5 Ga magmatic and Paleoproterozoic metasedimentary rocks and late Neoarchean to early Paleoproterozoic and late Paleoproterozoic tectono-thermal events have been identified in the basement beneath the CHB. Based on regional comparisons, we conclude that the early Precambrian basement beneath the CHB is part of the North China Craton

Depletion of internal peptides by site-selective blocking, phosphate labeling, and TiO2 adsorption for in-depth analysis of C-terminome

The analysis of protein C-termini is of great importance, because it not only provides valuable information about protein function, but also facilitates the elucidation of proteolytic processing. However, even with the recent methods for the global profiling of protein C-termini, the identification of C-termini is still far behind that of N-termini due to the lack of basic residue and low reactive carboxyl group. Therefore, an unbiased and complementary method for C-termini profiling is imperative. In this work, we developed a negative enrichment strategy to achieve the in-depth analysis of C-terminome. Proteins were firstly amidated to block carboxyl groups, followed by lysyl endoproteinase (LysC) digestion to generate C-terminal peptides with alpha-amines and internal peptides bearing both alpha- and epsilon-amines. After the alpha-amines were blocked by site-selective dimethylation or succinylation, the remaining epsilon-amines on internal peptides were labeled with phosphate groups. Finally, internal peptides were depleted by TiO2, leaving exclusively the fraction of C-terminal peptides for LC-MS/MS analysis. With Escherichia coli (E. coli) digests as the sample, the efficiency of amidation, dimethylation/succinylation, phosphate labeling and TiO2 depletion was proved high. With the combination of dimethyl and succinic blocking strategy, our method enabled the identification of 477 unique C-terminal peptides in E. coli. In comparison with the C-terminal amine-based isotope labeling of substrates (C-TAILS) method, 83 C-termini were identified by both methods, whereas 369 C-termini were unique to C-TAILS and 394 to our dataset. The method proposed is therefore efficient and possibly promotes the comprehensive profiling of C-termini

Comprehensive simulations of new particle formation events in Beijing with a cluster dynamics-multicomponent sectional model

New particle formation (NPF) and growth are a major source of atmosphericfine particles. In polluted urban environments, NPF events are frequentlyobserved with characteristics distinct from those in clean environments.Here we simulate NPF events in urban Beijing with a discrete-sectional model that couples cluster dynamics and multicomponent particle growth. In the model, new particles are formed by sulfuric acid-dimethylamine nucleation, while particle growth is driven by particle coagulation and the condensationof sulfuric acid, its clusters, and oxygenated organic molecules (OOMs). Avariable simulation domain in the particle size space is applied to isolatenewly formed particles from preexisting ones, which allows us to focus onnew particle formation and growth rather than the evolution of particles ofnon-NPF origin. The simulation yields a rich set of information includingthe time-dependent NPF rates, the cluster concentrations, the particle sizedistributions, and the time- and size-specific particle chemicalcompositions. These can be compared with the field observations tocomprehensively assess the simulation-observation agreement. Sensitivityanalysis with the model further quantifies how metrics of NPF events (e.g.,particle survival probability) respond to model input variations and servesas a diagnostic tool to pinpoint the key parameter that leads tosimulation-observation discrepancies. Seven typical NPF events in urbanBeijing were analyzed. We found that with the observed gaseous precursorconcentrations and coagulation sink as model inputs, the simulations roughly captured the evolution of the observed particle size distributions; however,the simulated particle growth rate was insufficient to yield the observedparticle number concentrations, survival probability, and mode diameter.With the aid of sensitivity analysis, we identified under-detected OOMs as alikely cause for the discrepancy, and the agreement between the simulationand the observation was improved after we modulated particle growth rates in the simulation by adjusting the abundance of OOMs.Peer reviewe