Sources and processes of iron aerosols in a megacity in Eastern China

Iron (Fe) in aerosol particles is a major external source of micronutrients for marine ecosystems and poses a potential threat to human health. To understand the impacts of aerosol Fe, it is essential to quantify the sources of dissolved Fe and total Fe. In this study, we applied receptor modeling for the first time to apportion the sources of dissolved Fe and total Fe in fine particles collected under five different weather conditions in the Hangzhou megacity of Eastern China, which is upwind of the East Asian outflow. Results showed that Fe solubility (dissolved Fe to total Fe) was the largest on fog days (6.7 ± 3.0 %), followed by haze (4.8 ± 1.9 %), dust (2.1 ± 0.7 %), clear (1.9 ± 1.0 %), and rain (0.9 ± 0.5 %) days. Positive matrix factorization (PMF) analysis suggested that industrial emissions were the largest contributor to dissolved Fe (44.5 %–72.4 %) and total Fe (39.1 %–55.0 %, except for dust days) during haze, fog, dust, and clear days. Transmission electron microscopy analysis of individual particles showed that > 75 % of Fe-containing particles were internally mixed with acidic secondary aerosol species on haze, fog, dust, and clear days. Furthermore, Fe solubility showed significant positive correlations with aerosol acidity/total Fe and liquid water content. These results indicated that the wet surface of aerosol particles promotes heterogeneous reactions between acidic species and Fe aerosols, contributing to a high Fe solubility

Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China

Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µgm−3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species

An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography : Implications for aerosol pH estimate

Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl-, SO2-4, NO-3, NHC4 and KC. However, F-, Mg2C and Ca2C were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO2-4, NO-3 and NHC4 generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl-from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl-, SO2-4, NO-3, NHC4 and KC across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl-, SO2-4, NO-3, NHC4 and KC decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE/CE) and ion balance (anions-cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent

Atmospheric pollution and human health in a Chinese megacity (APHH-Beijing) programme. Final report

In 2016, over 150 UK and Chinese scientists joined forces to understand the causes and impacts - emission sources, atmospheric processes and health effects - of air pollution in Beijing, with the ultimate aim of informing air pollution solutions and thus improving public health. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) research programme succeeded in delivering its objectives and significant additional science, through a large-scale, coordinated multidisciplinary collaboration. In this report are highlighted some of the research outcomes that have potential implications for policymaking

A Three-Phase Top- Query Based Distributed Data Collection Scheme in Wireless Sensor Networks

We propose a three-phase top- k query based distributed data collection scheme which is designed for clustered or multisink wireless sensor networks. The proposed scheme consists of a distributed iterative hard thresholding algorithm and a three-phase top- k query algorithm. In the distributed iterative hard thresholding algorithm, the cluster heads or sink nodes reconstruct the compressed data in a distributed and cooperative manner. Meanwhile, the top- k query operation in the above algorithm is realized by pruning unnecessary elements among cluster heads or sink nodes in the three-phase top- k query algorithm. Simulation results show that there is no obvious difference in the performance of data reconstruction between our proposed scheme and existing compressive sensing theory based data collection schemes. However, both the number of interactions and the amount of transmitted data among cluster heads or sink nodes can be effectively reduced in the proposed scheme. The performance of the proposed scheme is analyzed in detail in this paper to support the claims

Improved Results on Delay-Dependent Robust H∞ Control of Uncertain Neutral Systems with Mixed Time-Varying Delays

In this paper, the problem of the delay-dependent robust H∞ control for a class of uncertain neutral systems with mixed time-varying delays is studied. Firstly, a robust delay-dependent asymptotic stability criterion is shown by linear matrix inequalities (LMIs) after introducing a new Lyapunov–Krasovskii functional (LKF). The LKF including vital terms is expected to obtain results of less conservatism by employing the technique of various efficient convex optimization algorithms and free matrices. Then, based on the obtained criterion, analyses for uncertain systems and H∞ controller design are presented. Moreover, on the analysis of the state-feedback controller, different from the traditional method which multiplies the matrix inequality left and right by some matrix and its transpose, respectively, we can obtain the state-feedback gain directly by calculating the LMIs through the toolbox of MATLAB in this paper. Finally, the feasibility and validity of the method are illustrated by examples

A core–shell copper oxides-cobalt oxides heterostructure nanowire arrays for nitrate reduction to ammonia with high yield rate

Electrochemical nitrate reduction to ammonia (NRA) can realize the green synthesis of ammonia (NH3) at ambient conditions, and also remove nitrate contamination in water. However, the current catalysts for NRA still face relatively low NH3 yield rate and poor stability. We present here a core–shell heterostructure comprising cobalt oxide anchored on copper oxide nanowire arrays (CuO NWAs@Co3O4) for efficient NRA. The CuO NWAs@Co3O4 demonstrates significantly enhanced NRA performance in alkaline media in comparison with plain CuO NWAs and Co3O4 flocs. Especially, at −0.23 V vs. RHE, NH3 yield rate of the CuO NWAs@Co3O4 reaches 1.915 mmol h−1 cm−2, much higher than those of CuO NWAs (1.472 mmol h−1 cm−2), Co3O4 flocs (1.222 mmol h−1 cm−2) and recent reported Cu-based catalysts. It is proposed that the synergetic effects of the heterostructure combing atom hydrogen adsorption and nitrate reduction lead to the enhanced NRA performance

Micropores regulating enables advanced carbon sphere catalyst for Zn-air batteries

Energy conversion technologies like fuel cells and metal-air batteries require oxygen reduction reaction (ORR) electrocatalysts with low cost and high catalytic activity. Herein, N-doped carbon spheres (N-CS) with rich micropore structure have been synthesized by a facile two-step method, which includes the polymerization of pyrrole and formaldehyde and followed by a facile pyrolysis process. During the preparation, zinc chloride (ZnCl2) was utilized as a catalyst to promote polymerization and provide a hypersaline environment. In addition, the morphology, defect content and activity area of the resultant N-CS catalysts could be regulated by controlling the content of ZnCl2. The optimum N-CS-1 catalyst demonstrated much better catalytic activity and durability towards ORR in alkaline conditions than commercial 20 wt% Pt/C catalysts, of which the half-wave potential reached 0.844 V vs. RHE. When applied in the Zn-air batteries as cathode catalysts, N-CS-1 showed a maximum power density of 175 mW cm−2 and long-term discharging stability of over 150 h at 10 mA cm−2, which outperformed 20 wt% Pt/C. The excellent performance could be due to its ultrahigh specific surface area of 1757 m2 g−1 and rich micropore channels structure. Meanwhile, this work provides an efficient method to synthesize an ultrahigh surface porous carbon material, especially for catalyst application