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In this paper, we consider a nonlinear switched dynamical system (NSDS) with unknown system parameters in the context of uncertain experimental data. This system is employed to model the continuous fermentation for the production of 1,3-propanediol through glycerol bioconversion. The uncertain experimental data points are regarded as stochastic variables and only their first-order moment information of the probability distributions is available. The target of this paper is to optimize these system parameters under the environment of uncertain experimental data. Taking these factors into account, we propose a distributionally robust system identification (DRSI) problem (i.e., a bi-level system identification problem) governed by the NSDS. The objective functional comprises two level objectives: (i) the inner-level objective aims to maximize the expectation of the relative error between the solution of the NSDS and the uncertain experimental data with respect to their probability distributions at approximately stable time; and (ii) the outer-level objective is to minimize the expectation with respect to these system parameters. The DRSI problem is equivalently transformed into a single-level system identification (SLSI) problem with non-smooth term through the application of the duality theory in the probability space. A smoothing technique is employed to approximate the non-smooth term in the SLSI problem. Subsequently, an error analysis of the employed smoothing technique is derived. The gradients of the objective functional in the SLSI with respect to these system parameters are obtained. An optimization algorithm is designed to solve the SLSI problem. Finally, the paper concludes with simulation results. • The DRSI problem lies between RSI problem and SSI problem. • An optimization algorithm with the duality theory is proposed to solve the DRSI problem. • A smoothing technique is employed to approximate the non-smooth term in the objective functional. [ABSTRACT FROM AUTHOR]

The refractive index structure constant ( C n 2 ) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating C n 2 were analyzed in detail. A new method that uses a combination of these methods for continuous C n 2 profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov "2/3 law", the C n 2 profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10−16 m−2/3 and 1.27 × 10−15 m−2/3, respectively. In the vertical direction, the continuous profiling results of C n 2 and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of C n 2 estimation normally does not exceed 30% under the convective boundary layer (CBL). [ABSTRACT FROM AUTHOR]

In recent years, the Beijing–Tianjin–Hebei region has become one of the worst areas for haze pollution in China. Sun photometers are widely used for aerosol optical property monitoring due to the advantages of fully automatic acquisition, simple maintenance, standardization of data processing, and low uncertainty. Research sites are mostly concentrated in cities, while the long-term analysis of aerosol optical depth (AOD) for the pollution transmission channel in rural Beijing is still lacking. Here, we obtained an AOD monitoring dataset from August 2017 to March 2019 using the ground-based CE-318 sun photometer at the Gucheng meteorological observation site in southwest Beijing. These sun photometer AOD data were used for the ground-based validation of MODIS (Moderate Resolution Imaging Spectroradiometer) and AHI (Advanced Himawari Imager) AOD data. It was found that MODIS and AHI can reflect AOD variation trends by sun photometer on daily, monthly, and seasonal scales. The original AOD measurements of the sun photometer show good correlations with satellite observations by MODIS (R = 0.97), and AHI (R = 0.89), respectively, corresponding to their different optimal spatial and temporal windows for matching with collocated satellite ground pixels. However, MODIS is less stable for aerosols of different concentrations and particle sizes. Most of the linear regression intercepts between the satellite and the photometer are less than 0.1, indicating that the errors due to surface reflectance in the inversion are small, and the slope is least biased (AHI: slope = 0.91, MODIS: slope = 0.18) in the noon period (11 a.m.–2 p.m.) and most biased in summer (AHI: slope = 0.77, MODIS: slope = 1.31), probably due to errors in the aerosol model. The daily and seasonal variation trends between CE-318 AOD measurements in the Gucheng site and fine particulate observations from the national air quality site nearby were also compared and investigated. In addition, a typical haze–dust complex pollution event in North China was analyzed and the changes in AOD during the pollution event were quantified. In processing, we use sun photometer and satellite AOD data in combination with meteorological and PM data. Overall, this paper has implications for the study of AOD evolution patterns at different time scales, the association between PM2.5 concentrations and AOD changes, and pollution monitoring. [ABSTRACT FROM AUTHOR]

The monitoring and tracking of urban air pollution is a challenging environmental issue. The approach of synchronous 3-D detection of wind and pollution using a solo coherent Doppler wind lidar (CDWL) is developed and demonstrated. The 3-D distribution of pollutant is depicted by the backscatter coefficient based on signal intensity of CDWL. Then, a high-resolution wind field is derived to track the local air pollution source with its diffusion and to analyze transboundary air pollution episodes. The approach is experimentally implemented in a chemical industry park. Smoke plumes caused by point source pollutions are captured well using plan position indicator (PPI) scanning with low elevation. A typical source of pollution is located, combining the trajectory of the smoke plume and the horizontal wind vector. In addition, transboundary air pollution caused by the transport of dust storms is detected in a vertical profile scanning pattern, which is consistent with the results of national monitoring stations and backward trajectory models. Our present work provides a significant 3-D detection approach to air pollution monitoring with its sources, paths, and heights by using a solo-CDWL system. [ABSTRACT FROM AUTHOR]

Nanozymes are a type of nanomaterials that mimics natural enzymes with biocatalytic functions. Oxidase is a kind of oxidoreductase which oxidizes hydrogen donor substrates in the presence of molecular oxygen. Recently, there have been many reports on various nanomaterials exhibiting oxidase-mimicking activity, which currently became one of the most extensively studied enzymatic property with broad applications. Considering the significant advances and superior prospects of oxidase mimics, this review categorizes oxidase mimicking nanozymes based on their substrates and brief introduction of their syntheses. Further their sensing applications along with the possible catalytic mechanisms are systematically and comprehensively overviewed and discussed. Eventually, the possible opportunities and challenges in the future to explore oxidase mimics for applications in sensing or analytical chemistry are prospected. [Display omitted] • An overview of oxidase mimics based on different nanostructures. • An overview of oxidase mimics category of oxidase mimics. • Oxidase mimics based sensing and catalytic mechanisms are summarized and reviewed. • Challenges and perspectives in oxidase mimics based sensing envisioned. [ABSTRACT FROM AUTHOR]

Accurate wind shear detection is crucial for aviation safety, especially in landing and departure. A new approach for windshear alerting is proposed and demonstrated. This approach monitors orthogonal wind components in multiple runways using single coherent Doppler wind lidar (CDWL). First, the two orthogonal components of the wind field are retrieved from radial speed by an updated variational method. Then, the heading wind and cross wind on different runways are calculated simultaneously, without the location restriction of the single lidar. Finally, a windshear alerting message is generated through quantitatively evaluating the distribution of shear ramps over the monitoring area. The new CDWL-based approach for windshear alerting is implemented at the Beijing Daxing International Airport. The retrieved horizontal wind from the lidar is consistent with that from anemometers. Thanks to its high spatial/temporal resolution, some meteorological phenomena of aviation hazards, including microburst, windshear, gust front, and vortex are well captured. Particularly, all 10 windshear cases reported by crews are successfully identified during the windshear verification experiment, demonstrating the effectiveness and robustness of the new approach. [ABSTRACT FROM AUTHOR]

The long-term atmospheric mixing layer height (MLH) information plays an important role in air quality and weather forecasting. However, it is not sufficient to study the characteristics of MLH using long-term high spatial and temporal resolution data in the desert. In this paper, over the southern edge of the Taklimakan Desert, the diurnal, monthly, and seasonal variations in the daytime MLH (retrieved by coherent Doppler wind lidar) and surface meteorological elements (provided by the local meteorological station) in a two-year period (from July 2021 to July 2023) were statistically analyzed, and the relationship between the two kinds of data was summarized. It was found that the diurnal average MLH exhibits a unimodal distribution, and the decrease rate in the MLH in the afternoon is much higher than the increase rate before noon. From the seasonal and monthly perspective, the most frequent deep mixing layer (>4 km) was formed in June, and the MLH is the highest in spring and summer. Finally, in terms of their mutual relationship, it was observed that the east-pathway wind has a greater impact on the formation of the deep mixing layer than the west-pathway wind; the dust weather with visibility of 1–10 km contributes significantly to the formation of the mixing layer; the temperature and relative humidity also exhibit a clear trend of a concentrated distribution at about the height of 3 km. The statistical analysis of the MLH deepens the understanding of the characteristics of dust pollution in this area, which is of great significance for the treatment of local dust pollution. [ABSTRACT FROM AUTHOR]

In this paper, we consider maximum hands-off control problem governed by a nonlinear dynamical system, where the maximum hands-off control constraint is characterized by an L 0 norm. For this problem, we first approximate the L 0 norm constraint by a L 1 norm constraint. Then, the control parameterization together with sequential adaptive switching time optimization technique is proposed to approximate the optimal control problem by a sequence of finite-dimensional optimization problems. Furthermore, a smoothing technique is exploited to approximate the non-smooth maximum operator and an error analysis is investigated for this approximation. The gradients of the cost functional with respect to the decision variables in the approximate problem are derived. On the basis of these results, we develop a gradient-based optimization algorithm to solve the resulting optimization problem. Finally, an example is solved to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Convective weather is often accompanied by precipitation and windshear, seriously endangering the safety of aircraft during takeoff and landing. However, under rainfall conditions, conventional wind lidars have a limited detection range due to significant signal attenuation. To solve this problem, a 200 mm temperature-controlled telescope coated with a hydrophobic film is applied in the coherent Doppler wind lidar system to improve the detection capability in rain. The maximum detection range of the lidar is extended to 30 km and demonstrated at Kunming Changshui International Airport at an altitude of 2102 m. Firstly, the detection accuracy and maximum detection range of the lidar are verified. Through the analysis of the horizontal wind field under two typical convective weather conditions, it is found that convective weather often accompanies low-level convergence and divergence structures, leading to headwind shear and crosswind shear on the airport runway. From the vertical profile, it is shown that the triggering of convective weather is accompanied by low-level southwest winds and high-altitude northeastern winds. According to the statistics of wind speed and direction on clear and rainy days over 9 months, rainy days are usually caused by the invasion of cold air from Northeast China, resulting in airport windshear. In summary, the enhanced lidar can effectively identify and analyze windshear during rainy days, which is very useful for aviation safety, especially for takeoff and landing in all weather conditions. [ABSTRACT FROM AUTHOR]

Perimeter control is the manipulation of traffic flow by adjusting traffic signals on the borders between regions. It can be used to address the problem of traffic congestion in urban areas. Although there are many papers devoted to perimeter control, the dependence of time delay on traffic state is rarely considered. Moreover, most of them depend on accumulation reference points of the network and the stability of given equilibrium points to derive a perimeter controller. In reality, such equilibrium points and the optimal reference points are unavailable in advance. With these in minds, this paper formulates an optimal feedback perimeter control problem (OFPCP) subject to state-dependent delays without given information about the optimal reference point and equilibrium point. Different from the control method based on linearization or partial linearization, a hybrid algorithm combining filled function method and gradient-based method is introduced to solve this challenging optimal feedback control problem. Some experiments are performed to demonstrate the effectiveness of our method. • Feedback perimeter control calculated as a delay optimal control problem; • Computational algorithm developed for state-dependent delay optimal control problem; • Control efficacy validated via various comparisons. [ABSTRACT FROM AUTHOR]

The studies of intracloud discharges may shed light on the microphysical structure of thunderclouds, as both the magnitude and the sign of charge separation due to graupel collides with ice crystals within the strong updrafts are influenced by the surrounding environment. Here, a compact all-fiber coherent Doppler wind lidar (CDWL) working at the 1.5 µm wavelength is applied for probing the dynamics and microphysics structure of thunderstorms. Thanks to the precise spectrum measurement, multi-component spectra signals of thunderstorms can be analyzed by the CDWL. The spectrum width, skewness, and Doppler velocity of CDWL is used to separate and identify the particle composition and polarity. In the experiment, the thundercloud properties are detected by the CDWL, 10.6 cm Doppler weather radar (DWR), and Advanced Geosynchronous Radiation Imager (AGRI) onboard Fengyun-4 satellites. In particular, the spectrum width and skewness of the thundercloud below the 0 ∘C isotherm are increased, and when a cloud-ground lightning occurs, there is additional graupel with a velocity greater than 5 ms-1. It indicates that this region is a melting layer, and lightning activity changes the motion characteristics of graupel, affecting the charge structure of the whole thundercloud. In general, our findings provide details on the velocity, phase, and composition of particles in the outside updraft region of the thunderstorm. The identification and analysis of graupel is particularly important. It is proved that the precise spectrum of CDWL is a promising indicator for studying the charge structure of thunderstorms. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear enzyme-catalytic time-delayed switched dynamical system is considered to describe batch culture of glycerol bioconversion to 1,3-propanediol induced by Klebsiella pneumoniae . This system can not only predict the exponential growth phase but also the lag and the stationary growth phases of batch culture since it contains two switching times for representing the starting moment of lag growth phase and the time when the cell specified growth rate reaches the maximum. The biological robustness is expressed in terms of the expectation and variance of the relative deviation. Our aim is to identify the switching times. To this end, a robust parameter identification problem is formulated, where the switching times are decision variables to be chosen such that the biological robustness measure is optimized. This problem, which is governed by the nonlinear system, is subject to a quality constraint and continuous state inequality constraints. Using a hybrid time-scaling transformation to parameterize the switching times into new parameters, an equivalently robust parameter identification problem is investigated. The continuous state inequality constraints are approximated by a conventional inequality constraint, yielding a sequence of approximate robust parameter identification subproblems. The convergence analysis of this approximation is also investigated. Owing to the highly complex nature of these subproblems, a parallel algorithm, based on simulated annealing, is proposed to solve these subproblems. From an extensive simulation study, it is observed that the obtained optimal switching times are satisfactory. [ABSTRACT FROM AUTHOR]

Most economic and industrial processes are governed by inherently nonlinear dynamic system in which mathematical analysis (with few exceptions) is unable to provide general solutions; even the conditions to the existence of equilibrium point for the nonlinear dynamic system are simply not established in some special cases. In this paper, based on numerical solution of a nonlinear multi-stage automatic control dynamic (NMACD) in fed-batch culture of glycerol bioconversion to 1,3-propanediol (1,3-PD) induced by Klebsiella pneumoniae ( K. pneumoniae), we consider an optimal design of the NMACD system. For convenience, the NMACD system is reconstructed together with the existence, uniqueness and continuity of solutions are discussed. Our goal is to prove the strong stability with respect to the perturbation of initial state for the solution to the NMACD system. To this end, we construct corresponding linear variational system for the solution to the NMACD system, and also prove the boundedness of fundamental matrix solutions to the linear variational system. On this basis, we prove the strong stability appearing above through the application of this boundedness. [ABSTRACT FROM AUTHOR]

In this paper, we propose a nonlinear enzyme-catalytic time-delayed switched system with unknown state-delays, switching times and system parameters for describing the process of batch culture of glycerol bioconversion to 1,3-propanediol (1,3-PD) induced by Klebsiella pneumoniae ( K. pneumonia e). Some important properties of the time-delayed switched system are discussed. In consideration of the difficulty in accurately measuring the concentration of intracellular substances and the absence of equilibrium points for the time-delayed switched system, we quantitatively define biological robustness of the intracellular substance concentrations for the entire process of batch culture. Our goal is to identify the unknown quantities. To this end, we formulate an optimization problem in which the cost function minimizes the defined biological robustness and the unknown state-delays, switching times and system parameters are regarded as decision variables. This optimization problem is subject to the time-delayed switched system, continuous state inequality constraints and parameter constraints. The hybrid time-scaling transformation, constraint transcription and local smoothing approximation techniques are used to convert this optimization problem to a sequence of approximate subproblems. In consideration of both the difficulty of finding analytical solutions and the highly complex nature of this optimization problem, we develop a parallel particle swarm optimization (PPSO) algorithm to solve these approximate subproblems. Finally, we explore the appropriateness of the optimal estimates for the state-delays, switching times and system parameters as well as the effectiveness of the parallel algorithm via numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a nonlinear time-delay dynamic system with uncertain system parameters to characterize the process of batch fermentation. Our goal is to design an optimal control scheme to maximize the productivity of 1,3-propanediol (1,3-PD). Accordingly, we introduce an optimal control problem governed by the nonlinear time-delay dynamic system, in which the control variables are the free terminal time of the batch fermentation process and the initial concentrations of biomass and glycerol. The optimal control problem is subject to a cost sensitivity constraint for ensuring that an acceptable level of the system performance is achieved and continuous state inequality constraints for ensuring that the concentrations of biomass, glycerol, 1,3-PD, acetate, ethanol lie within specified limits. Then, the optimal control problem with free terminal time is transformed, via a hybrid time-scaling strategy, into an equivalent problem with fixed terminal time, which is much preferred for numerical computation. Using the constraint transcription and local smoothing approximation techniques, we approximate these continuous state inequality constraints by conventional inequality constraints to yield an approximate optimal control problem. Because of the highly complex nature of this approximate problem, a parallel algorithm based on the filled function method is constructed to solve this approximate problem. Finally, it is observed that the optimal control obtained is satisfactory through numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a nonlinear multi-stage dynamic system to characterize batch culture. We construct corresponding linear variational system for the solution to the multi-stage system, also prove the boundedness of fundamental matrix solutions for the linear variational system. On this basis, we prove strong stability with respect to perturbance of initial state vector for the multi-stage system through the application of such boundedness. From extensive simulation study, it is observed that the strong stability is highly satisfactory. [ABSTRACT FROM PUBLISHER]

The bioconversion of glycerol to 1,3-propanediol (1,3-PD) is a complex bioprocess. In this paper, based on biological phenomena of different characteristics at different stages and the genetic regulation of dha regulon , we consider a fourteen-dimensional nonlinear multi-stage dynamic system with unknown time and system parameters for formulating the multi-stage cell growth in batch culture. Some important properties of the multi-stage system are discussed. Our goal is to identify the time and system parameters. To this end, we present a parameter identification problem in which the time and system parameters are decision variables and the cost function measures the discrepancy between experimental data and computational results, subject to the multi-stage system, parameter constraints and continuous state inequality constraints. The system sensitivity (the cost function’s gradient, namely, the derivative of the cost function with respect to the time and system parameters), which can be computed by solving an auxiliary initial value problem, can be regarded as the search direction of optimization algorithm. The identification problem is converted into a sequence of nonlinear programming subproblems through the application of the time-scaling transformation, the constraint transcription and local smoothing approximate techniques. Due to the highly complex nature of the identification problem, the computational cost is high. Thus, a parallel algorithm is proposed to solve these subproblems based on the novel combinations of system sensitivity and genetic algorithm. Finally, numerical results show that the multi-stage system can reasonably describe the process of batch culture. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, in view of glycerol bioconversion to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae (K. pneumoniae), we study an enzyme-catalytic nonlinear dynamic system with uncertain parameters for formulating the process of batch culture. Some important properties are also discussed. Taking account of the difficulty in accurately measuring the concentrations of intracellular substances and the absence of equilibrium point of the nonlinear system in batch culture, a novel approach is used here to define quantitatively biological robustness of the intracellular substance concentrations for the overall process of batch culture. The purpose of this paper is to identify these uncertain parameters. To this end, taking the defined biological robustness as a performance index, we establish an identification model, which is subject to the nonlinear system. Simultaneously, the existence of optimal solution to the identification model is deduced. We develop an optimization algorithm, based on novel combinations of Nelder–Mead algorithm and the change rate of state variable, for solving the identification model under various experiment conditions. The convergence analysis of this algorithm is also investigated. Numerical results not only show that the established model can be used to describe the process of batch culture reasonably, but also imply that the optimization algorithm is valid. [Copyright &y& Elsevier]

In this paper, robust control problem using μ-synthesis in microbial continuous culture is studied. The dissimilation process of glycerol to 1,3-propanediol cannot avoid the disturbances caused by uncertain factors. Based on the biodynamical model, a control system with the initial glycerol concentration as input control is proposed to simplify the controller design. μ-synthesis method is applied to find a feedback controller to assure both of robust stability and robust performance of the closed-loop system simultaneously. To solve the corresponding structured singular value optimization problem, a converged result is obtained through D-K iteration method. The μ-synthesis system is also compared with the corresponding $$H_\infty$$ system. The simulation results indicate that the μ-controller might be more feasible for the continuous bioprocess controlling. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, based on the microorganism batch fermentation of glycerol to 1,3-propanediol, we study a kind of nonlinear multi-stage dynamic system for the batch fermentation and its properties. Since it is difficult to measure the concentration of intracellular substance so far, we quantitatively describe robustness according to the basic features of biological systems. Taking experimental data of the concentration of extracellular substance and robustness as the performance index, we establish identification model of dynamic system for the batch fermentation. Then, its identifiability, the existence and continuity with respect to the parameters of the solution have been discussed. We decompose the identification problem into bilevel multi-stage optimal control subproblem, and both of them are equivalent. This work is a theoretical foundation of further numerical calculation. [Copyright &y& Elsevier]

Marine mixed layer height (MLH) detection using a ship-borne coherent Doppler wind lidar (CDWL) based on a constant turbulent kinetic energy dissipation rate (TKEDR) threshold is realized and experimentally demonstrated. The MLH can be retrieved from the TKEDR estimated by the CDWL via setting an appropriate threshold. Here, the value of threshold is determined by a reference MLH retrieved from aerosol backscattered signal. The threshold of 10−4 m2 s−3 is found to be applicable in retrieving both inland and marine MLHs. In the experiments, to validate the reliability of the constant threshold, the MLH diurnal cycles at inland and marine sites are retrieved by using a ground-based CDWL. The MLH retrieval result at the marine site shows good agreement with radiosonde-derived MLH. After that, by using a ship-borne CDWL, the marine MLH along the ship's route in South China Sea is successfully detected in real time. [ABSTRACT FROM AUTHOR]

Evaluation of the cloud seeding effect is a challenge due to lack of directly physical observational evidence. In this study, an approach for directly observing the cloud seeding effect is proposed using a 1548 nm coherent Doppler wind lidar (CDWL). Normalized skewness was employed to identify the components of the reflectivity spectrum. The spectrum detection capability of a CDWL was verified by a 24.23-GHz Micro Rain Radar (MRR) in Hefei, China (117°15′ E, 31°50′ N), and different types of lidar spectra were detected and separated, including aerosol, turbulence, cloud droplet, and precipitation. Spectrum analysis was applied as a field experiment performed in Inner Mongolia, China (112°39′ E, 42°21′ N) to support the cloud seeding operation for the 70th anniversary of China's national day. The CDWL can monitor the cloud motion and provide windshear and turbulence information ensuring operation safety. The cloud-precipitation process is detected by the CDWL, microwave radiometer (MWR) and Advanced Geosynchronous Radiation Imager (AGRI) in FY4A satellites. In particular, the spectrum width and skewness of seeded cloud show a two-layer structure, which reflects cloud component changes, and it is possibly related to cloud seeding effects. Multi-component spectra are separated into four clusters, which are well distinguished by spectrum width and vertical velocity. In general, our findings provide new evidence that the reflectivity spectrum of CDWL has potential for assessing cloud seeding effects. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of the planetary boundary layer (PBL) is crucial for comprehending land-atmosphere interactions. This study utilizes three years of Doppler wind lidar measurements from June 2019 to June 2022 to investigate PBL dynamics over Hefei, a city in the Western Yangtze River Delta, China. We focus on the seasonal and diurnal variations in key characteristics, such as wind profiles, shear intensity, turbulent mixing, low-level jets (LLJs), and mixing layer heights (MLH). Results show that horizontal wind speeds accelerated more rapidly above 3 km, with the predominant westerly winds (270°±15°) in all seasons. The vertical depth of high wind zone (> 8 m s-1) during the day is found generally deeper than at night, particularly in winter. In Hefei, LLJs primarily form at sunset and dissipate by noon, typically at altitudes between 0.5 and 0.6 km throughout the year, except in July. LLJ occurrences are most frequent in spring (31.7 %), followed by summer (24.7 %), autumn (22.3 %), and winter (21.3 %). Summer LLJs are most intensified, extending up to 1.5 km. The larger wind gradient below the jets significantly enhances turbulence and shear intensity near the ground at night. The seasonal average MLH peaks between 2:00 p.m. and 3:00 p.m., reaching approximately 1.2 km in spring and summer. Cloud cover raises MLH by about 100 m at night but decreases it by 200 m at the afternoon peak. This study provides insights into lidar-based PBL dynamics and highlights implications for local standards concerning low-altitude economic activities. [ABSTRACT FROM AUTHOR]

Bioaerosols are usually defined as aerosols arising from biological systems such as bacteria, fungi, and viruses. They play an important role in atmospheric physical and chemical processes including ice nucleation and cloud condensation. As such, their dispersion affects not only public health but also regional climate. Lidar is an effective technique for aerosol detection and pollution monitoring. It is also used to profile the vertical distribution of wind vectors. In this paper, a coherent Doppler wind lidar (CDWL) is deployed for aerosol and wind detection in Hefei, China, from 11 to 20 March in 2020. A wideband integrated bioaerosol sensor (WIBS) is used to monitor variations in local fluorescent bioaerosols. Three aerosol transport events are captured. The WIBS data show that, during these transport events, several types of fluorescent aerosol particles exhibit abnormal increases in their concentration, number fractions to total particles, and number fractions to whole fluorescent aerosols. These increases are attributed to external fluorescent bioaerosols instead of local bioaerosols. Based on the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model and the characteristics of external aerosols in WIBS, their possible sources, transport paths, and components are discussed. The results prove the influence of external aerosol transport on local high particulate matter (PM) pollution and fluorescent aerosol particle composition. The combination of WIBS and CDWL expands the aerosol monitoring parameters and provides a potential method for real-time monitoring of fluorescent biological aerosol transport events. In addition, it also helps to understand the relationships between atmospheric phenomena at high altitudes like virga and the variation of surface bioaerosol. It contributes to the further understanding of long-range bioaerosol transport, the roles of bioaerosols in atmospheric processes, and in aerosol–cloud–precipitation interactions. [ABSTRACT FROM AUTHOR]

Characterization of aerosol transportation is important in order to understand regional and global climatic changes. To obtain accurate aerosol profiles and wind profiles, aerosol lidar and Doppler wind lidar are generally combined in atmospheric measurements. In this work, a method for calibration and quantitative aerosol properties using coherent Doppler wind lidar (CDWL) is adopted, and data retrieval is verified by contrasting the process with synchronous Rayleigh–Mie–Raman lidar (RMRL). The comparison was applied to field measurements in the Taklimakan desert, from 16 to 21 February 2023. Good agreements between the two lidars was found, with the determination coefficients of 0.90 and 0.89 and the root-mean-square error (RMSE) values of 0.012 and 0.013. The comparative results of continuous experiments demonstrate the ability of the CDWL to retrieve aerosol properties accurately. [ABSTRACT FROM AUTHOR]

Previous studies are primarily based on surface air pollution for a single event, leaving research on the temporal characteristics of aerosols and wind fields in the atmospheric boundary layer (ABL) and their associations unclear due to a lack of long-term vertical profile data. This study was the first to conduct long-term Doppler wind LiDAR measurements from Sep. 2019 to Aug. 2022 in Hefei in western Yangtze River Delta (YRD) region, China. The spatiotemporal characteristics of retrieved aerosol backscatter coefficient (β) and wind profiles were analyzed from the perspective of long-term statistics and typical heavy pollution episodes (HPEs). The seasonal profile of β showed a peak in the near-surface layer meanwhile the overall β profile (<0.5 km) was the highest in winter but lowest in summer. Combined with ground-based meteorological and air quality observations, 12 HPEs were identified and classified into dust-related events and fog-haze episodes. The results showed a consistency between hourly variations in PM 10 (particulate matter smaller than 10 μm) concentration and β retrieved at 300 m during a high PM 10 concentration (>150 μg/m3) period. Different roles of horizontal wind at different altitudes and its associated time delay effect on surface PM 10 pollution were evaluated based on correlation coefficients (Ф) and air pollution diffusion conditions. Significant positive Ф values were noticed below 0.5 km during the entire dust-related EP4 and EP6, indicating that the higher wind speeds could exacerbate PM 10 pollution. In contrast, large negative Ф values meant the removal of PM 10 pollutants by strong winds below 0.8 km during 24 h after peak in EP3. Combining with backward trajectory analysis and meteorological condition, notable transboundary pollution with positive contributions from upper winds (>1.5 km) was discovered in dust-related EP1, EP4, EP7, EP9, and EP10. Time delay effect (1-h/2-h lag) of upper winds (>0.8 km) on surface PM 10 pollution was explored in EP5, EP6, EP7, EP8, and EP9. In spring dust-related HPEs, surface PM 10 pollution was mostly contributed by long-range transport of aerosol particles at higher altitudes (>1.5 km) from the northwest direction, driven by the Mongolian cyclone and the cold front system. Transboundary aerosols originated from the northern part of Anhui province and the YRD region in the middle altitudes (∼0.5 km) was the main contributor to fog-haze HPEs. The findings demonstrated the ability of the real-time Doppler wind LiDAR system to monitor transboundary air pollution and provided a scientific reference for policy makers. • Vertical profile of aerosol backscatter coefficient (<0.5 km) was highest in winter. • Hourly averaged aerosol backscatter coefficient at 300 m peaked at 10:00 a.m. (LST). • Impact of vertical wind profile and surface PM 10 concentration were assessed. • Long-range transport (>1.5 km) contributed the most to PM 10 in spring dust events. • Northern Anhui and YRD was the main source region to fog-haze pollution in Hefei. [ABSTRACT FROM AUTHOR]

A micro-pulse lidar system incorporating differential absorption lidar (DIAL) and coherent Doppler wind lidar (CDWL) is proposed and demonstrated. Due to the high signal-to-noise ratio (SNR) of the superconducting nanowire single-photon detector (SNSPD), the DIAL channel achieves high sensitivity in CO2 measurement. Meanwhile, the CDWL channel is used to obtain the horizontal wind field. In the process of the optimization and calibration of the DIAL receiver, specifically, mode scrambling and temperature control of the connecting fiber between the telescope and the SNSPD enhance the stability and robustness of the system. Horizontal scanning of the CO2 concentration and the wind field is carried out in a 6 km range over a scanning span of 60° with a radial resolution of 150 m and 15 s. The results show that the hybrid lidar system captures the spatial distribution of CO2 concentration and the wind field simultaneously. The horizontal net CO2 flux in a radius of 6 km is estimated by integrating the CO2 concentration and the wind transport vector, indicating different characteristics of horizontal net CO2 fluxes in an industrial area, a university campus, and a park. During most of the experiment, CO2 flux remained positive in the industrial area, but balances fell to nearly zero on the campus and in the park. The horizontal net fluxes averaged over 24 h in the three areas are 3.5 × 105 ppm·m2·s−1, 0.7 × 105 ppm·m2·s−1, and 0.1 × 105 ppm·m2·s−1. [ABSTRACT FROM AUTHOR]

Although coherent Doppler wind lidar (CDWL) is promising in detecting boundary layer height (BLH), differences between BLH results are observed when different CDWL measurements are used as tracers. Here, a robust solution for BLH detections with CDWL is proposed and demonstrated: mixed layer height (MLH) is retrieved best from turbulent kinetic energy dissipation rate (TKEDR), while stable boundary layer height (SBLH) and residual layer height (RLH) can be retrieved from carrier-to-noise ratio (CNR). To study the cause of the BLH differences, an intercomparison experiment is designed with two identical CDWLs, where only one is equipped with a stability control subsystem. During the experiment, it is found that the CNR could be distorted by instrument instability because the coupling efficiency from free-space to the polarization-maintaining fiber of the telescope is sensitive to the surrounding environment. In the ML, a bias up to 2.13 km of the MLH from CNR is found, which is caused by the CNR deviation. In contrast, the MLH from TKEDR is robust as long as the accuracy of wind is guaranteed. In the SBL (RL), the CNR is found capable to retrieve SBLH and RLH simultaneously and robustly. This solution is tested during an observation period over one month. Statistical analysis shows that the root-mean-square errors (RMSE) in the MLH, SBLH, and RLH are 0.28 km, 0.23 km, and 0.24 km, respectively. [ABSTRACT FROM AUTHOR]

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method's advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance. [Display omitted] • Meta-analysis for primers and impact factors to their recognition performance. • Viruses-based primers showed a better specificity and recognition ability. • Regional differences of HF183 was not observed in China, Canada, and Singapore. • The influence factors from sample to environment of 21 primers had been listed. • Meta-analysis of economy, climate, and geographic zone on the primers. [ABSTRACT FROM AUTHOR]

Global behavior for stochastic system of regulation of bacterial tryptophan ( trp ) operon is analyzed in this paper. This bioprocess cannot avoid the internal and external disturbances reflected on the cell growth rate within the biosynthesis of trp . These factors can affect the integrated results of repression and attenuation, leading to genetic circuit or switch. The equilibria and bifurcations of the deterministic system are analyzed. Then, a stochastic model is presented by considering the effect of a bounded Markov diffusion process on critical parameters. In order to analyze the global behavior, we compute the control sets through solving the associated control system by using parallel control set algorithm. In particular, we compute the bifurcation as discontinuous topology changes in the support of a stationary measure. The probability distributions of relative supports are also provided. The results provide indication on how the disturbances affect the bioprocess with sustained oscillations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a nonlinear hybrid dynamic (NHD) system to describe fed-batch culture where there is no analytical solutions and no equilibrium points. Our goal is to prove the strong stability with respect to initial state for the NHD system. To this end, we construct corresponding linear variational system (LVS) for the solution of the NHD system, also prove the boundedness of fundamental matrix solutions for the LVS. On this basis, the strong stability is proved by such boundedness. [ABSTRACT FROM AUTHOR]