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Atmospheric ammonia (NH3) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH3concentration based on the absorption lines of NH3in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH3column from the Hyperspectral Infrared Atmospheric Sounder (HIRAS) onboard the Chinese FengYun (FY)-3D satellite and present the first atmospheric NH3column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH3hotspots around the world, e.g., India, West Africa, and East China, where large NH3emissions exist. The HIRAS NH3columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer (IASI) measurements, and we find that the two instruments observe a consistent NH3global distribution, with correlation coefficient (R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH3retrieval are discussed.

IMPORTANCE: China has experienced both rapid urbanization and major increases in myopia prevalence. Previous studies suggest that green space exposure reduces the risk of myopia, but the association between myopia risk and specific geometry and distribution characteristics of green space has yet to be explored. These must be understood to craft effective interventions to reduce myopia. OBJECTIVE: To evaluate the associations between myopia and specific green space morphology using novel quantitative data from high-resolution satellite imaging. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study included students grades 1 to 4 (aged 6 to 9 years) in Shenzhen, China. Baseline data were collected in 2016-2017, and students were followed up in 2018-2019. Data were analyzed from September 2020 to January 2022. EXPOSURES: Eight landscape metrics were calculated using land cover data from high-resolution Gaofen-2 satellite images to measure area, aggregation, and shape of green space. MAIN OUTCOME AND MEASURES: The 2-year cumulative change in myopia prevalence at each school and incidence of myopia at the student level after 2 years were calculated as main outcomes. The associations between landscape metrics and school myopia were assessed, controlling for geographical, demographic, and socioeconomic factors. Principal component analyses were performed to further assess the joint effect of landscape metrics at the school and individual level. RESULTS: A total of 138 735 students were assessed at baseline. Higher proportion, aggregation, and better connectivity of green space were correlated with slower increases in myopia prevalence. In the principal component regression, a 1-unit increase in the myopia-related green space morphology index (the first principal component) was negatively associated with a 1.7% (95% CI, −2.7 to −0.6) decrease in myopia prevalence change at the school level (P = .002). At the individual level, a 1-unit increase in myopia-related green space morphology index was associated with a 9.8% (95% CI, 4.1 to 15.1) reduction in the risk of incident myopia (P < .001), and the association remained after further adjustment for outdoor time, screen time, reading time, and parental myopia (adjusted odds ratio, 0.88; 95% CI, 0.80 to 0.97; P = .009). CONCLUSIONS AND RELEVANCE: Structure of green space was associated with a decreased relative risk of myopia, which may provide guidance for construction and renovation of schools. Since risk estimates only indicate correlations rather than causation, further interventional studies are needed to assess the effect on school myopia of urban planning and environmental designs, especially size and aggregation metrics of green space, on school myopia.

This study explores a new scheme to retrieve the global aerosol optical depth (AOD) over land for the advanced Medium Resolution Spectral Imager (MERSI-II) aboard the Fengyun-3D (FY-3D) satellite based on the dark target (DT) algorithm. The main improvement is that the global surface reflectance (SR) model nonlinearly varies with the solar zenith angle and normalized difference vegetation index (NDVIswir) is made, which is more complex relative to that of Moderate-Resolution Imaging Spectro-Radiometer (MODIS) operational algorithm. Our AOD retrievals are compared with an aerosol robotic network (AERONET) AOD and cross evaluated with Aqua/MODIS, respectively. Overall, the MERSI-II retrieved results over the global scale have good consistency with the AERONET observations; on the same condition, the percentage of matchups within the expected error (EE: ±0.05 ± 0.15AOD) is 67.06%, which is slightly lower than the percentage of MODIS (79.84%). On a spatial scale, the coverage of MERSI-II retrievals at one granule is significantly higher than that of MODIS, which is related to successful inversion of haze pixels and has retrieval ability in urban, grassland, and other surface types. The monthly mean AOD values retrieved by MERSI-II are close to those of MODIS, indicating that MERS-II has similar quantitative capability and application potential as its international counterparts.

Atmospheric carbon dioxide (CO2) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing (ERF). Active remote-sensing technique using differential absorption light detection and ranging (LiDAR) (DIAL) is recognized as the most promising remote sensing means for atmospheric CO2 measurements. The aerosol and carbon detection LiDAR (ACDL) instrument onboard the DaQi-1 (DQ-1) is dedicated to quantifying the global spatial distribution of atmospheric CO2. To meet the requirement of accuracy and precision, a reasonable averaging scheme for ACDL measurements is needed to minimize the effect of random noise of observations on CO2 retrievals. In this study, three averaging schemes were conducted in the retrieval process: averaging of CO2 columns (AVX), averaging of differential absorption optical depth (AVD), and averaging of signals (AVS). The performances were compared at three representative sites. The experiments were first carried out on simulations. The results show that the optimal size of the averaging window is 50 km, corresponding to an averaging of measurements over 150 pulse pairs. In addition, the AVX and AVD schemes are less affected by altitude variations and can be applied to surfaces with moderate and severe topographic variation, such as hills and mountains, whereas the AVS method is more suitable for surfaces with slight topographic variation, such as oceans, plains, and terraces. Furthermore, the ACDL observations were also retrieved by applying three averaging schemes and validated against ground-based Total Carbon Column Observing Network (TCCON) measurements at the Xianghe station. The AVS scheme exhibits better performance than the AVX and AVD methods with the lowest biases of less than 0.5 ppm, which is consistent with the simulation results.

The payload MEdium Resolution Spectral Imager–low light (MERSI-LL) of Fengyun-3E (FY-3E) equipped with a low-light band (LLB) first enabled the FY series satellite to detect low lights at night. Due to the early morning orbit of FY-3E, MERSI-LL/LLB only obtains nighttime observations in one hemisphere during the winter half-year, and nighttime observations are only found at high latitudes for the ascending orbit (at dusk) and globally covered for the descending orbit (at dawn). Using MERSI-LL/LLB data, we developed FY nighttime lights (FY-NTLs) product for socioeconomic use. Publicly released FY-NTL data include monthly and annual products for both ascending and descending orbits, which are composited from multitemporal MERSI-LL/LLB data after quality control. At present, the quality control procedure consists of moonlit data identification, stray light removal, cloud screening, and natural illumination exclusion. The absolute radiometric accuracy of FY-NTL degraded in the stray light removal process, and the comparison results with VIIRS NTL suggested that FY-NTL may bear a negative bias. Nonetheless, FY-NTL first images global NTLs at dawn and provides us with an opportunity to study city lights in different periods of the night.

China is likely the world's largest anthropogenic source of methane emissions, with coal mine methane (CMM) being the predominant contributor. Here, we deploy 2 years of satellite observations to survey facility‐level CMM emitters in Shanxi, the most prolific coal mining province in China. A total of 138 detected episodic events at 82 facilities are estimated to emit 1.20 (+0.24/−0.20, 95% CI) million tons of methane per year (Mt CH4/yr) during 2021–2023, roughly equivalent to 4.2 times the integrated flux from the Permian plumes and four times of the integrated flux from the Four Corners plumes, two of the world's largest hotspots for oil and gas methane emissions. This work reveals the heavy‐tailed distribution characteristic of CMM emission sources for the first time, with 20% of emitters contributing approximately 50% of total emissions. Comparison with the Global Energy Monitor (GEM) inventory reveals that the GEM estimate is about 4.1 times our estimate. This study examines methane emissions from coal mines in Shanxi, China, identified as a significant source of global methane, a potent greenhouse gas. Using satellite data over 2 years, we found 138 detected episodic events at 82 facilities in Shanxi emitting an estimated 1.2 million tons of methane annually, far exceeding emissions from known global hotspots in the oil and gas sectors. Our analysis shows that a small percentage of these facilities contribute to the majority of emissions. The results, which challenge previous estimates from environmental monitoring organizations, underscore the need for direct, observational methods to accurately assess and address methane emissions. This work aims to guide efforts in mitigating climate change by identifying key areas for reducing methane release. Satellite data identify 82 major methane emitters in Shanxi, China, with high annual emissions of up to 1.2 MtTop 20% of coal mines contribute to half of the region's total methane emissionsFindings highlight the importance of direct measurements for accurate emission estimates Satellite data identify 82 major methane emitters in Shanxi, China, with high annual emissions of up to 1.2 Mt Top 20% of coal mines contribute to half of the region's total methane emissions Findings highlight the importance of direct measurements for accurate emission estimates

ABSTRACTThe authors evaluated and compared the behavior of PM2.5with respect to NOxand NH3emission changes in high (the year 2013) and low (the year 2018) SO2emission cases. Two groups of simulations were conducted based on anthropogenic emissions from China in 2013 and 2018, respectively. In each group of simulations, a respective 25% reduction in NOxand NH3emissions were assumed. A sensitivity factor (β) was defined as the relative change in PM2.5concentration due to 1% change in NOxor NH3emissions. In the high SO2emissions case, PM2.5was more sensitive to NH3(0.31) emissions change than NOx(0.21). Due to the significant decrease in SO2emissions from the high to low SO2emissions case, the sensitivity of PM2.5to NOxincreased to 0.33, while its sensitivity to NH3decreased to 0.22. The result implies that now and in the future, PM2.5is/will be less sensitive to NH3emissions change, while NOxemissions control is more effective in reducing the surface PM2.5concentration. Seasonally, in the low SO2emissions case, the sensitivities of PM2.5to NOxand NH3in winter were higher than those in summer, indicating that to deal with severe winter haze more attention should be paid to the emissions control of inorganic PM2.5precursors, especially NOx.

Designing scaffolds with persistent elasticity and conductivity to mimic microenvironments becomes a feasible way to repair cardiac tissue. Injectable biomaterials for cardiac tissue engineering have demonstrated the ability to restore cardiac function by preventing ventricular dilation, enhancing angiogenesis, and improving conduction velocity. However, limitations are still among them, such as poor mechanical stability, low conductivity, and complicated procedure. Here, we developed thermal plastic poly(glycolic acid) surgical suture and mussel-inspired conductive particle’s adhesion into a highly elastic, conductive spring-like coils. The polypyrrole (PPy)-coated biospring acted as an electrode and then was assembled into a solid-state supercapacitor. After being injected through a syringe needle (0.33 mm inner diameter), the tangled coils formed an elastically conductive three-dimensional (3-D) network to modulate cardiac function. We found that cardiomyocytes (CMs) grew along the spring coils’ track with elongated morphologies and formed highly oriented sarcomeres. The biospring enhanced the CMs’ maturation in synchronous contraction accompanied by high expressions of cardiac-specific proteins, α-actinin, and connexin 43 (cx43). After the elastic, conductive biosprings were injected into the myocardial infarction (MI) area, the left ventricular fractional shortening was improved by about 12.6% and the infarct size was decreased by about 34%. Interestingly, the spring can be utilized as a sensor to measure the CMs’ contractile force, which was 1.57 × 10–3± 0.26 × 10–3mN (∼4.1 × 106cells). Accordingly, this study highlights an injectable biospring to form a tangled conductive 3-D network in vivofor MI repair.

3D printing, an additive manufacturing based technology for precise 3D construction, is currently widely employed to enhance applicability and function of cell laden scaffolds. Research on novel compatible biomaterials for bioprinting exhibiting fast crosslinking properties is an essential prerequisite toward advancing 3D printing applications in tissue engineering. Printability to improve fabrication process and cell encapsulation are two of the main factors to be considered in development of 3D bioprinting. Other important factors include but are not limited to printing fidelity, stability, crosslinking time, biocompatibility, cell encapsulation and proliferation, shear-thinning properties, and mechanical properties such as mechanical strength and elasticity. In this review, we recite recent promising advances in bioink development as well as bioprinting methods. Also, an effort has been made to include studies with diverse types of crosslinking methods such as photo, chemical and ultraviolet (UV). We also propose the challenges and future outlook of 3D bioprinting application in medical sciences and discuss the high performance bioinks.

Atmospheric SO2has a significant impact on the urban environment and global climate. Band Residual Difference Algorithm (BRD) and Differential Optical Absorption Spectroscopy (DOAS) were used respectively by NASA and ESA science team to derive SO2columns from satellite observations, but there are few studies on the comparison and validation of BRD and DOAS SO2retrievals under the same observation conditions. In this study, the radiative transfer model SCIATRAN was firstly used to validate the accuracies of BRD and DOAS SO2retrievals, and analyse the uncertainty of SO2retrieval caused by band selection, O3 absorption, aerosol, surface reflectance, solar and viewing zenith angle. Finally, BRD and DOAS algorithms were applied to the same radiances from satellite observations, and comparisons of BRD and DOAS SO2retrievals were conducted over volcanic eruption and North China. Results show that, for the case with low SO2columns, BRD SO2retrievals have higher retrieval accuracy than DOAS, but typical seasonal variation with high SO2column in winter and low in summer can be more clearly discernible in DOAS SO2retrievals than BRD from satellite observations. For the case with high SO2columns, the differences between BRD (310.8–314.4 nm) and DOAS (315–327 nm) retrievals are large, and the value and accuracy of BRD (310.8–314.4 nm) SO2retrievals are lower than those of DOAS (315–327 nm) retrievals. Compared with the SO2inputs in forward model, both BRD (310.8–314.4 nm) and DOAS (315–327 nm) SO2retrievals are underestimated for the case with high SO2columns. The selection of wavelength range can significantly affect the accuracy of SO2retrieval. The error of BRD SO2retrieval from 310.8–314.4 nm is lower than other bands in the ultraviolet spectral region (306–327 nm). The increase of wavelength in the ultraviolet spectral region 306–330 nm can reduce the underestimation of DOAS SO2retrievals in the case of high SO2column, but slight overestimation of SO2retrieval is found from the 315–327 nm range in the case of low SO2column. The values of BRD and DOAS SO2retrieval decrease with atmospheric O3column and aerosol optical depth increasing, but increase with surface reflectance increasing. Large solar zenith angle and viewing zenith angle can introduce more errors to the BRD and DOAS SO2retrievals. This study is important for the improvement of retrieval algorithm and the application of SO2products from satellite observations.

Zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR-Cas9) are the most commonly used genome editing tools. Previous studies demonstrated that hypothermia treatment increased the mutation rates induced by ZFNs and TALENs in mammalian cells. Here, we characterize the effect of different culture temperatures on CRISPR-Cas9 mediated genome editing and find that the genome editing efficiency of CRISPR-Cas9 is significantly hampered by hypothermia treatment, unlike ZFN and TALEN. In addition, hyperthermia culture condition enhances genome editing by CRISPR-Cas9 in some cell lines, due to the higher enzyme activity and sgRNA expression level at higher temperature. Our study has implications on CRISPR-Cas9 applications in a broad spectrum of species, many of which do not live at 37°C.

Utilization of the underlying mechanisms of biological systems is the principal endeavor of biomimetics, the primary goal of which is to treat on-going biological processes. From the perspective of tissue engineering, one purpose of biomimetics is to create highly cellular- or tissue-favored environments for bio-defect repair. Marine creatures such as mussels have inspired bioengineers to design ideal cellular substrates, strong adhesives, and other bioengineering materials. Herein, we report a novel mussel shell-derived membrane for wound dressing. Mussel shell in situmanufactured a highly flexible membrane with a regular porous pattern after the direct action of acid (A-shell) followed by base treatment (B-shell). The SEM images display elegantly patterned polygons with nanowalls (about 710 nm). Compared with the A-shell, the B-shell has a more defined and flexible structure. FTIR characterization of the structures indicates that deacetylation occurred on the B-shell. A cellular toxicity study was conducted to determine the optimized processing parameters before applying the wound healing model. The B-shell significantly closed the wound at an early stage (day 10) followed by complete contraction at a later stage (day 21). This is completely consistent with the higher level of α-SMA protein, which accelerates wound contraction in the wound sites. As a key index of the integration between host and guest, a high blood vessel density was detected in both the A-shell and B-shell groups. The treated shells can improve epidermal migration, the formation of granulation tissue, neovascularization and hair follicles, and reduce scar tissue. Our mussel shell-derived membrane could have potential as a wound dressing and other biomedical uses.

A high-accuracy surface modeling (HASM) method based on the fundamental theorem of surfaces, is developed to simulate XCO2surfaces using the GOSAT retrieval XCO2data. Two tests are designed to investigate the simulation accuracy. The first test divides the existing satellite retrieval XCO2data into training points and testing points, and simulates the XCO2surface using the training points while computing the simulation error using the testing points. The absolute mean error (MAE) of the testing points is 1.189 ppmv, and the corresponding values of the comparison methods, Ordinary Kriging, IDW, and Spline are 1.203, 1.301, and 1.355 ppmv, respectively. The second test simulates the XCO2surface using all the satellite retrieval points and uses the TCCON (Total Carbon Column Observing Network) site observation values as the ture values. For the six typical TCCON sites, the HASM simulation MAE is 1.688 ppmv, and the satellite retrieval MAE at the same sites is 2.147 ppmv. These results indicate that HASM can successfully simulate XCO2surfaces based on satellite retrieval data.

The spectra of O2A-band (0.76 μm) and CO2near-infrared emissions (1.6 μm) are simulated by the SCIATRAN radiative transfer model (V3.1.23), and compared with those observed by GOSAT-FTS (Greenhouse gases Observing SATellite-Fourier Transform Spectrometer). Systematic deviations between the observed and simulated spectra are found to exist, especially for the O2A-band. The discrepancies are characterized by their mean differences averaged over the observed spectral ranges. A correction is applied to the observed GOSAT-FTS L1B (V141.141) spectra by scaling the spectral intensity measured by TANSO-FTS (Thermal and Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) onboard GOSAT. The average columnar CO2concentrations (XCO2) are retrieved from the observed and the corrected GOSAT-FTS spectra by using the SCIATRAN inversion algorithm. Compared with the GOSAT-FTS L2 XCO2data products retrieved from the observed spectra of GOSAT-FTS, the SCIATRAN retrievals from the corrected spectra show a much better agreement, with the relative error less than 1%. But the results of GOSAT TANSO-FTS (V161.160) show smaller residuals than GOSAT TANSO-FTS (V141.141) without mean residual correction. The results indicate that the mean residual correction would increase the precision of XCO2retrieval for spectra with systematic deviations.

Based on the optimal estimation method, a satellite XCO2retrieval algorithm was constructed by combining LBLRTM with VLIDORT. One-year GOSAT/TANSO observations over four TCCON stations were tested by our algorithm, and retrieval results were compared with GOSAT L2B products and ground-based FTS measurements. Meanwhile, the influence of CO2line mixing effect on retrieval was estimated, and the research showed that neglecting CO2line mixing effect could result in approximately 0.25% XCO2underestimation. The accuracy of XCO2retrievals was similar to GOSAT L2B products at cloud-free footprints with aerosol optical depth less than 0.3, and 1% accuracy of XCO2retrievals can be reached based on the validation result with TCCON measurements.

It is very important in accurately estimating the forests’ carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data, and the whole process consumes too much labor, money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems, this paper, based on High Accuracy Surface Modeling (HASM), proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points, and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg, while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure, and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China, and they account for 39.82% and 20.46% of the country’s total forest vegetation carbon stock respectively. Compared with the former value (1975-1995), it manifests that the carbon storage of the two regions do increase clearly. The results of this research show that the large-scale reforestation in the last decades in China attains a significant carbon sink.

The rapid urbanization in China and the long‐range transport dust (LRTD) from arid and semi‐arid areas has resulted in an increase of PM10concentration. In this study, an interpretable deep learning model [deep forest (DF)] with FY‐4A top‐of‐the‐atmosphere reflectance (TOAR) data were used to obtain the hourly PM10in China. The optimal hourly average R2of 10‐fold cross validation can achieve 0.85 (13:00 Beijing time); The R2(RMSE, μg/m³) of the daily, monthly, and annual averages were 0.82 (24.16), 0.97 (6.53), and 0.99 (2.30), respectively. Using TOAR data, the DF model performed better than other machine learning models. The feature importance of the TOAR‐PM10model showed that TOAR and meteorological elements both contributed significantly to the model. In spring, the PM10in northern China was greater than that in southern China, which may be related to the LRTD. Excluding the dust weather periods, the areas with high PM10values in China were mainly in cities and their suburbs, where were correlated with human activities. During a dust weather process, LRTD increased PM10in northern China by 80.4%. During a mixture haze and dust weather process, the PM10increased by 130.2% in northern China, of which LRTD led to an increase of 73.7%. The sources (from the Taklimakan Desert in China) and transmission paths of these two LRTD processes were similar. The contribution of LRTD to PM10was related to dust intensity and meteorological conditions. The results showed that LRTD and local pollution to PM10was both important in haze periods. Hourly PM10in China was estimated using interpretable deep forest and FY‐4A top‐of‐the‐atmosphere reflectance, and the daily and monthly mean R2were 0.82 and 0.97Excluding dust weather periods, the areas with high PM10values in China were mainly in cities and suburbs related to human activitiesThe contribution of long‐range transport dust and local pollution in China to PM10was both important during haze periods Hourly PM10in China was estimated using interpretable deep forest and FY‐4A top‐of‐the‐atmosphere reflectance, and the daily and monthly mean R2were 0.82 and 0.97 Excluding dust weather periods, the areas with high PM10values in China were mainly in cities and suburbs related to human activities The contribution of long‐range transport dust and local pollution in China to PM10was both important during haze periods

Bioadhesives act as a bridge in wound closure by forming an effective interface to protect against liquid and gas leakage and aid the stoppage of bleeding. To their credit, tissue adhesives have made an indelible impact on almost all wound-related surgeries. Their unique properties include minimal damage to tissues, low chance of infection, ease of use and short wound-closure time. In contrast, classic closures, like suturing and stapling, exhibit potential additional complications with long operation times and undesirable inflammatory responses. Although tremendous progress has been made in the development of tissue adhesives, they are not yet ideal. Therefore, highlighting and summarizing existing adhesive designs and synthesis, and comparing the different products will contribute to future development. This review first provides a summary of current commercial traditional tissue adhesives. Then, based on adhesion interaction mechanisms, the tissue adhesives are categorized into three main types: adhesive patches that bind molecularly with tissue, tissue-stitching adhesives based on pre-polymer or precursor solutions, and bioinspired or biomimetic tissue adhesives. Their specific adhesion mechanisms, properties and related applications are discussed. The adhesion mechanisms of commercial traditional adhesives as well as their limitations and shortcomings are also reviewed. Finally, we also discuss the future perspectives of tissue adhesives.

Star styrene–isoprene–butadiene rubber (SIBR) was synthesized with a new kind of star anionic initiator made from naphthalene lithium and an SnCl4 coupled agent. The relationship between the structure and properties of star SIBR was studied. Star block styrene–isoprene–butadiene rubber (SB-SIBR), having low hysteresis, high road-hugging, and excellent mechanical properties, was closer to meeting the overall performance requirements of ideal tire-tread rubber according to a comparison of the morphology and various properties of SB-SIBR with those of star random SIBR and natural rubber/star styrene–butadiene rubber blends. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 336–341, 2004

Oceans are widely regarded as major offsets for anthropogenic carbon emissions, leading to an evident lower measured atmospheric CO2concentration than expected. It is thus of great significance to develop effective means to monitor CO2fluxes over oceans globally. In this work, we utilized observations obtained by an airborne CO2‐IPDA LIDAR to evaluate the potential of such means in estimating sea‐air CO2flux. During a flight experiment in 2019, we have estimated the CO2exchange rate, −1.5 ± 0.18 mmol/m2/h, between the Bohai Bay and the atmosphere using equilibrium atmospheric boundary layer theory. These findings indicated that the forthcoming space‐borne CO2‐IPDA LIDAR is capable of identifying CO2uptakes over oceans qualitatively, which would be a novel means and a basis for monitoring CO2fluxes over global oceans. Oceans are regarded as important offsets to anthropogenic CO2emissions, delaying an increase in atmospheric CO2concentration. However, there is a lack of understanding of the intensity, distribution, and variability of marine carbon sinks. China is due to launch a space‐borne LIDAR for measuring atmospheric CO2concentration globally in 2021. In this work, we utilized data collected during a flight test for the forthcoming satellite mission to explore the ability of such a novel means in revealing and estimating CO2fluxes of oceans quantitatively. Results confirmed an evident CO2uptake in the Bohai Bay and exhibited a promising prospect for the novel CO2measuring means. We detected XCO2gradient during a flight campaign in ChinaRetrieve XCO2in the atmosphere boundary layer by cloud slicing methodProvide a model to retrieve CO2flux over ocean by CO2‐IPDA system We detected XCO2gradient during a flight campaign in China Retrieve XCO2in the atmosphere boundary layer by cloud slicing method Provide a model to retrieve CO2flux over ocean by CO2‐IPDA system

Mapping the mass concentration of near-surface atmospheric particulate matter (PM) using satellite observations has become a popular research niche, leading to the development of a variety of instruments, algorithms, and datasets over the past two decades. In this study, we conducted a holistic review of the major advances and challenges in quantifying PM, with a specific focus on instruments, algorithms, datasets, and modeling methods that have been developed over the past 20 years. The aim of this study is to provide a general guide for future satellite-based PM concentration mapping practices and to better support air quality monitoring and management of environmental health. Specifically, we review the evolution of satellite platforms, sensors, inversion algorithms, and datasets that can be used for monitoring aerosol properties. We then compare various practical methods and techniques that have been used to estimate PM mass concentrations and group them into four primary categories: (1) univariate regression, (2) chemical transport models (CTM), (3) multivariate regression, and (4) empirical physical approaches. Considering the main challenges encountered in PM mapping practices, for example, data gaps and discontinuity, a hybrid method is proposed with the aim of generating PM concentration maps that are both spatially continuous and have high precision.