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Top-down atmospheric inversion infers surface–atmosphere fluxes from spatially distributed observations of atmospheric composition in order to quantify anthropogenic and natural emissions. In this study, we developed a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) based on the Weather Research and Forecasting–Community Multiscale Air Quality (WRF–CMAQ) modeling system model, the three-dimensional variational (3D-Var) algorithm, and the ensemble square root filter (EnSRF) algorithm. This system can simultaneously assimilate hourly in situ CO, SO 2 , NO 2 , PM 2.5 , and PM 10 observations to infer gridded emissions of CO, SO 2 , NO x , primary PM 2.5 (PPM 2.5), and coarse PM 10 (PMC) on a regional scale. In each data assimilation window, we use a "two-step" scheme, in which the emissions are inferred first and then input into the CMAQ model to simulate initial conditions (ICs) of the next window. The posterior emissions are then transferred to the next window as prior emissions, and the original emission inventory is only used in the first window. Additionally, a "super-observation" approach is implemented to decrease the computational costs, observation error correlations, and influence of representative errors. Using this system, we estimated the emissions of CO, SO 2 , NO x , PPM 2.5 , and PMC in December and July 2016 over China using nationwide surface observations. The results show that compared to the prior emissions (2016 Multi-resolution Emission Inventory for China – MEIC 2016)), the posterior emissions of CO, SO 2 , NO x , PPM 2.5 , and PMC in December 2016 increased by 129 %, 20 %, 5 %, 95 %, and 1045 %, respectively, and the emission uncertainties decreased by 44 %, 45 %, 34 %, 52 %, and 56 %, respectively. With the inverted emissions, the RMSE of simulated concentrations decreased by 40 %–56 %. Sensitivity tests were conducted with different prior emissions, prior uncertainties, and observation errors. The results showed that the two-step scheme employed in RAPAS is robust in estimating emissions using nationwide surface observations over China. This study offers a useful tool for accurately quantifying multi-species anthropogenic emissions at large scales and in near-real time. [ABSTRACT FROM AUTHOR]

Many important engineering systems can be classified as Euler–Lagrange (EL) systems. In this work we develop a new Proportional‐Integral‐Derivative (PID) ‐based tracking control solution for uncertain EL systems subject to actuation failures and saturation. Two set of control algorithms are developed using robust adaptive and neuroadaptive methods, which are shown to exhibit several salient features: (1) the control schemes are of PID form, hence is characterized with simplicity in structure and intuition in concept; (2) the PID gains in the scheme are automatically updated by analytic algorithms with no need for manual tuning, rendering the control scheme more user‐friendly; and (3) the developed control algorithms are robust against nonvanishing disturbances, adaptive to unknown virtual parameter and immune to partial actuation effectiveness faults. [ABSTRACT FROM AUTHOR]

In this paper, Ho3+/Yb3+ co-doped Sodium Gadolinium Fluoride (NaGdF4) phosphors were synthesized by a facile and efficient hydrothermal method. The samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), energy spectrum (EDS), and photoluminescence (PL). The results of XRD and SEM indicated that the prepared NaGdF4 samples have the hexagonal structure and good orientation in the case of changing the concentration of Yb3+. The results of pump power dependence of up-conversion intensity indicated that the energy transfer mechanism from Yb3+ to Ho3+ is a two-photon process. The energy transfer between Ho3+ and Yb3+ under 448 nm excitation was determined by PL spectra and fluorescence lifetimes. All the results proved that the doping of Yb3+ ions can effectively improve the up-conversion luminescence of NaGdF4 phosphors and achieve quantum cutting efficiency of up to 179.8%. Overall, NaGdF4:Ho3+/Yb3+ have potential application in the field of optoelectronic materials. [ABSTRACT FROM AUTHOR]

El Niño has two different flavors, eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on the interannual carbon cycle variability remain unclear. Here we compared the behaviors of interannual atmospheric CO2 variability and analyzed their terrestrial mechanisms duringthese two types of El Niños, based on the Mauna Loa (MLO) CO2 growth rate (CGR) and the Dynamic Global Vegetation Model's (DGVM) historical simulations. The composite analysis showed that evolution of the MLO CGR anomaly during EP and CP El Niños had three clear differences: (1) negative or neutral precursors in the boreal spring during anEl Niño developing year (denoted as "yr0"), (2) strong or weak amplitudes, and (3) durations of the peak from December (yr0) to April during an El Niño decaying year (denoted as "yr1") compared to October (yr0) to January (yr1) for a CP El Niño, respectively. The global land-atmosphere carbon flux (FTA) simulated by multi-models was able to capture the essentials of these characteristics. We further found that the gross primary productivity (GPP) over the tropics and the extratropical Southern Hemisphere (TropCSH) generally dominated the global FTA variations during both El Niño types. Regional analysis showed that during EP El Niño events significant anomalous carbon uptake caused by increased precipitation and colder temperatures, corresponding to the negative precursor, occurred between 30°S and 20°N from January (yr0) to June (yr0). The strongest anomalous carbon releases, largely due to the reduced GPP induced by low precipitation and warm temperatures, occurred between the equator and 20°N from February (yr1) to August (yr1). In contrast, during CP El Niño events, clear carbon releases existed between 10°N and 20°S from September (yr0) to September (yr1), resulting from the widespread dry and warm climate conditions. Different spatial patterns of land temperatures and precipitation in different seasons associated with EP and CP El Niños accounted for the evolutionary characteristics of GPP, terrestrial ecosystem respiration (TER), and the resultant FTA. Understanding these different behaviors of interannual atmospheric CO2 variability, along with their terrestrial mechanisms during EP and CP El Niños, is important because the CP El Niño occurrence rate might increase under global warming. [ABSTRACT FROM AUTHOR]