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A dual-wavelength high-spectral-resolution lidar (HSRL) based on an iodine absorption filter and a field-widened Michelson interferometer (FWMI) has been developed to profile backscatter and extinction coefficients of aerosols and clouds accurately. This instrument was tested and calibrated on multiple observations in Hangzhou and Zhoushan, respectively, from August 2018 to April 2019. This paper discusses the design and the internal calibration method of the lidar system in detail, with several typical cases of observations and the analysis of these data products. The optical properties of urban aerosols in Hangzhou and the evolvement of clouds in Zhoushan are presented, respectively.

This paper presents two approaches to calibrate the overlap factor under inhomogeneous atmospheric condition without critical assumption and delivers detailed analysis about the retrieval errors of overlap profile in High-Spectral-Resolution-Lidar (HSRL). The first method employs an additional optical subsystem with different field-of-view, that is dual field-of-view HSRL, for the retrieval of overlap profile. The second method takes advantage of the difference of the result between the HSRL and Klett method, that is about the retrieval of backscatter coefficient for uncorrected lidar signal, to correct overlap profile. Surprisingly, two methods show very high-level consistency and stability of the result. It is potential that this technique would be an excellent solution for experimental determination of lidar overlap in ground-based HSRL.

The detection of clouds and aerosols is important for climate research. Lidar has been widely used in atmospheric remote sensing research because of its high spatial and temporal resolution and ability to detect profiles. High spectral resolution lidar (HSRL) accurately calculates the optical properties of aerosols and clouds without relying on any assumptions. Based on the 532nm iodine HSRL system, the lidar ratio of the urban aerosol in Hangzhou is 40-50sr, and the average lidar ratio of the cirrus is 24.79sr, demonstrating that the HSRL system and retrieval algorithms accurately obtain the optical properties of clouds and aerosols.

SignificanceAerosol-cloud interaction affects the cooling of Earth's climate, mostly by activation of aerosols as cloud condensation nuclei that can increase the amount of sunlight reflected back to space. But the controlling physical processes remain uncertain in current climate models. We present a lidar-based technique as a unique remote-sensing tool without thermodynamic assumptions for simultaneously profiling diurnal aerosol and water cloud properties with high resolution. Direct lateral observations of cloud properties show that the vertical structure of low-level water clouds can be far from being perfectly adiabatic. Furthermore, our analysis reveals that, instead of an increase of liquid water path (LWP) as proposed by most general circulation models, elevated aerosol loading can cause a net decrease in LWP.

Litter decomposition is important for soil nutrient cycling, but how the quality of litter links to nutrient dynamics is still unclear. In this work, high-quality Populus alba × P. Berolinensis, widely planted in Northeast China, and low-quality maize straw were selected as samples for a comparative study. In a short-term controlled litter decomposition incubation experiment, we applied different concentrations (25 u/g and 50 u/g) of biocatalyst (cellulase) to accelerate litter decomposition. Destructive sampling was conducted at 3, 7, 14, and 28 days to examine the influence of exogenous cellulase and litter with varying C:N ratios on the stoichiometric balance of soil carbon and nitrogen contents, as well as associated enzymatic activity. Litter addition significantly increased soil nutrients. Low nitrogen limited nutrient release during the decomposition of maize straw. After treatment, the soil organic carbon (SOC), total nitrogen (TN), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) in maize straw were 11.7%, 11.35%, 24.49%, and 39.7% lower than those in high-quality Populus alba × P. Berolinensis, respectively. Exogenous cellulase addition increased microbial biomass and β-D-glucosidase activity. The promotion of soil urease (S-UE), sucrase (S-SC), and β-D-glucosidase (S-β-GC) activities was more significant in combination with litter and exogenous cellulase. In addition, soil nutrients were directly affected by the litter C:N ratio and indirectly affected by cellulase. Overall, these results suggest that high-quality litter better facilitates soil nutrient cycling and accumulation due to its higher carbon and nitrogen release. [ABSTRACT FROM AUTHOR]

Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain's oxygen saturation of hemoglobin (sO , US imaging can probe the blood flow based on the Doppler effect. Further, by tracking gas-filled microbubbles, ultrasound localization microscopy (ULM) can map the blood flow velocity with sub-diffraction spatial resolution. In this work, we present a 3D deep-brain imaging system that seamlessly integrates PACT and ULM into a single device, 3D-PAULM. Using a low ultrasound frequency of 4 MHz, 3D-PAULM is capable of imaging the brain hemodynamic functions with intact scalp and skull in a totally non-invasive manner. Using 3D-PAULM, we studied the mouse brain functions with ischemic stroke. Multi-spectral PACT, US B-mode imaging, microbubble-enhanced power Doppler (PD), and ULM were performed on the same mouse brain with intrinsic image co-registration. From the multi-modality measurements, we further quantified blood perfusion, sO2, vessel density, and flow velocity of the mouse brain, showing stroke-induced ischemia, hypoxia, and reduced blood flow. We expect that 3D-PAULM can find broad applications in studying deep brain functions on small animal models.

Kidney stone disease is a major public health issue. By breaking stones with repeated laser irradiation, laser lithotripsy (LL) has become the main treatment for kidney stone disease. Laser-induced cavitation is closely associated with stone damage in LL. Monitoring the cavitation activities during LL is thus crucial to optimizing the stone damage and maximizing LL efficiency. In this study, we have developed 3-D super-resolution passive cavitation mapping (3D-SRPCM), in which the cavitation bubble positions can be localized with an accuracy of m, which is 1/10th of the acoustic diffraction limit. Moreover, the 3D-SRPCM reconstruction speed has been improved by 300 times by adopting a GPU-based sparse-matrix beamforming approach. Using 3D-SRPCM, we studied LL-induced cavitation activities on BegoStones, both in free space of water and confined space of a kidney phantom. The dose-dependent analysis provided by 3D-SRPCM revealed that accumulated impact pressure on the stone surface has the highest correlation with the stone damage. By providing high-resolution cavitation mapping during LL treatment, we expect that 3D-SRPCM may become a powerful tool to improve the clinical LL efficiency and patient outcome.

Photoacoustic imaging (PAI), also known as optoacoustic imaging, is a hybrid imaging modality that combines the rich contrast of optical imaging with the deep penetration of ultrasound (US) imaging. Over the past decade, PAI has been increasingly utilized in biomedical studies, providing high-resolution high-contrast images of endogenous and exogenous chromophores in various fundamental and clinical research. However, PAI faces challenges in achieving high imaging resolution and deep tissue penetration simultaneously, limited by the optical and acoustic interactions with tissues. Overcoming these limitations is crucial for maximizing the potential of PAI for biomedical applications. Recent advances in super-resolution (SR) PAI have opened new possibilities for achieving high imaging resolution at greater depths. This review provides a comprehensive summary of these promising strategies, highlights their representative applications, envisions the potential future directions, and discusses the broader impact on biomedical imaging.

Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain's oxygen saturation of hemoglobin (sO 2 ), US imaging can probe the blood flow based on the Doppler effect. Further, by tracking gas-filled microbubbles, ultrasound localization microscopy (ULM) can map the blood flow velocity with sub-diffraction spatial resolution. In this work, we present a 3D deep-brain imaging system that seamlessly integrates PACT and ULM into a single device, 3D-PAULM. Using a low ultrasound frequency of 4 MHz, 3D-PAULM is capable of imaging the whole-brain hemodynamic functions with intact scalp and skull in a totally non-invasive manner. Using 3D-PAULM, we studied the mouse brain functions with ischemic stroke. Multi-spectral PACT, US B-mode imaging, microbubble-enhanced power Doppler (PD), and ULM were performed on the same mouse brain with intrinsic image co-registration. From the multi-modality measurements, we future quantified blood perfusion, sO 2 , vessel density, and flow velocity of the mouse brain, showing stroke-induced ischemia, hypoxia, and reduced blood flow. We expect that 3D-PAULM can find broad applications in studying deep brain functions on small animal models.