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User authentication nowadays has become an important support for not only security guarantees but also emerging novel applications. Although WiFi signal-based user authentication has achieved initial success, it works in single-user scenarios while multi-user authentication remains a challenging task. In this paper, we present MultiAuth, a multi-user authentication system that can authenticate multiple users with a single pair of commodity WiFi devices. The basic idea is to profile multipath components of WiFi signals, and leverage the multipath components to characterize each user individually for multi-user authentication. MultiAuth first profiles multipath components of WiFi signals through a proposed MUltipath Time-of-Arrival estimation algorithm (MUTA). Then, after matching corresponding multipath components to each user in complex multi-user scenarios, MultiAuth constructs individual CSI based on the multipath components to characterize each user individually. An AoA-based approach is exploited to further separate individual CSI constructed by the users with same ToA. To identify users through their activities, MultiAuth extracts user behavior profiles based on the individual CSI, and leverages a dual-task neural network for robust user authentication. Extensive experiments involving 3 simultaneously present users demonstrate that MultiAuth is effective in multi-user authentication with 86.2% average accuracy and 9.5% average false accept rate.

Nitrogen oxides affect health and climate. Their emissions, in the form of nitric oxide, from inland waters such as lakes are generally considered negligible and are absent in air quality and climate models. Here we find unexpected high emissions of nitric oxide from remote lakes on the Tibetan Plateau, based on satellite observations of tropospheric nitrogen dioxide vertical column densities and subsequent emission inversion at a fine resolution of 5 km. The total emissions from 135 lakes larger than 50 km2reach 1.9 metric tons N h−1, comparable to anthropogenic emissions in individual megacities worldwide or the Tibet Autonomous Region. On average, the emissions per unit area reach 63.4 μg N m−2h−1, exceeding those from crop fields. Such strong natural emissions from inland waters have not been reported, to the best of our knowledge. The emissions are derived from microbial processes in association with substantial warming and melting of glacier and permafrost on the plateau, constituting a previously unknown feedback between climate, lake ecology and nitrogen emissions.

Neural architecture search (NAS) is an emerging paradigm to automate the design of competitive deep neural networks (DNNs). In practice, DNNs are subject to strict latency constraints and any violation may lead to catastrophic consequences (e.g., autonomous vehicles). However, to obtain the architecture that strictly satisfies the required latency constraint, previous hardware-aware differentiable NAS methods have to repeat a plethora of search runs to tune relevant hyperparameters by trial and error, and as a result, the total design cost increases proportionally (empirically by ten times). To tackle this, we, in this article, introduce a lightweight and scalable hardware-aware NAS framework named LightNAS, which consists of two separate stages. In the first stage, we strive to search for the architecture that strictly satisfies the required latency constraint at the macro level in a differentiable manner, and more importantly, through a one-time search (i.e., you only search once). The architectures searched in the first stage are denoted as LightNets. After that, in the second stage, we introduce an efficient evolutionary scheme to further explore the micro-level channel configuration of each LightNet at low cost. To achieve this, we propose an effective yet computationally cheap proxy, namely, batchwise training estimation (BTE), as a plug-in complement to enable the channel-level exploration of LightNets on the fly such that the accuracy of LightNets can be improved without degrading the runtime latency on target hardware. Finally, extensive experiments are conducted on one popular embedded platform (i.e., Nvidia Jetson AGX Xavier) to demonstrate the efficacy of the proposed approach over previous state-of-the-art counterparts.

As an important semiconductor photocatalytic material, titanium oxide (TiO2) has attracted increasing attention in photocatalytic degradation of organic pollutants due to its high oxidation ability, long-term photostability, and non-toxicity. In this work, we propose a green, facile, efficient, and sustainable strategy to mineralize TiO2nanocrystals on biomolecules using biomimetic synthesis. Different from previous reports, we used short peptides with different functional sequences to carry out the biomimetic growth of TiO2in the process of peptide self-assembly to obtain peptide nanofiber (PNF)–TiO2nanohybrids with controllable structure. In subsequent applications, the biomimetic synthesized PNF-TiO2nanohybrids were non-covalently cross-linked with graphene oxide (GO) and graphitic carbon nitride (g-C3N4) and freeze-dried to obtain nanohybrids with heterostructured aerogels (hetero-aerogels). The GO/PNF/g-C3N4–TiO2hetero-aerogel exhibits good photocatalytic activity after thermal annealing and exhibits rapid photocatalytic degradation of methylene blue (MB) and rhodamine B (RhB). Finally, the sustainability of the hetero-aerogels is evaluated using the ranking efficiency product (REP) method. The strategy for preparing TiO2-functionalized hetero-aerogels viabiomimetic synthesis in this study is green, economical, and efficient, and the obtained hetero-aerogels are expected to reveal wide applications in the fields of energy storage, wearable devices, environmental science, and analytical science. More importantly, in future research, we can prepare TiO2nanohybrids with different requirements by controlling the structure and morphology of the biological template self-assembly for application in more fields.

Differentiable neural architecture search (NAS) is an emerging paradigm to automate the design of top-performing convolutional neural networks (CNNs). Nonetheless, existing differentiable NAS methods suffer from several crucial weaknesses, such as inaccurate gradient estimation, high memory consumption, search fairness, etc. In this work, we introduce a novel hardware-aware differentiable NAS framework, namely SurgeNAS, in which we leverage the one-level optimization to avoid inaccuracy in gradient estimation. To this end, we propose an effective identity mapping regularization to alleviate the over-selecting issue. Besides, to mitigate the memory bottleneck, we propose an ordered differentiable sampling approach, which significantly reduces the search memory consumption to the single-path level, thereby allowing to directly search on target tasks instead of small proxy tasks. Meanwhile, it guarantees the strict search fairness. Moreover, we introduce a graph neural networks (GNNs) based predictor to approximate the on-device latency, which is further integrated into SurgeNAS to enable the latency-aware architecture search. Finally, we analyze the resource underutilization issue, in which we propose to scale up the searched SurgeNets within Comfort Zone to balance the computation and memory access, which brings considerable accuracy improvement without deteriorating the execution efficiency. Extensive experiments are conducted on ImageNet with diverse hardware platforms, which clearly show the effectiveness of SurgeNAS in terms of accuracy, latency, and search efficiency.

High-resolution (e.g., 5 km) emission data of nitrogen oxides (NOx= NO + NO2) provide localized knowledge of pollution sources for targeted regulations, yet such data are lacking or inaccurate over most regions at present. Here we improve our PHLET-based inversion method to derive NOxemissions in China at a 5-km resolution in summer 2019, based on the TROPOMI-POMINO satellite product of nitrogen dioxide (NO2) columns. With low computational costs, our inversion explicitly accounts for the effects of horizontal transport and nonlinear chemistry. We find numerous small-to-medium sources related to minor roads and small human settlements at relatively low affluence levels, in addition to clear emission signals along major transportation lines, consistent with road line density and Tencent location data. Many small-to-medium sources and transportation emissions are unclear or missing in the spatial distributions of four widely used emission inventories. Our emissions offer a unique reference for targeted emission control.

A new style of low temperature combustion cigarettes was prepared by implanting a thermally conductive cellulose/coper composite rod (TCCR) in the cut tobacco section, so as to explore the application feasibility at the low temperature environment. The burning temperature of the cigarettes was investigated by thermocouple to study the influence of the implanted TCCRs. The emission of conventional components and seven harmful components in mainstream smoke were also carried out to study the effect of TCCRs. The results show that implantation of TCCRs could reduce the burning temperature of cigarettes effectively, which decreased over 100 °C. In compared with conventional cigarettes, the amount of nicotine and nicotine-freed dry particulate matter (NFDPM) in mainstream smoke of TCCRs implanted cigarettes changed little, while the release of harmful components such as CO, HCN, NNK and phenol decreased over 20%. Moreover, the TCCRs, which made of copper paper with 2 g / 18 g weight ratio of pulp and copper, and 5 mm interval perforating, could reduce the burning temperature of cigarettes by 145 °C and the hazard index by 2.01.

As a green sustainable inorganic material, hydroxyapatite (HA) has potential application in water purification. Aerogel materials with 3D structure have great advantages in the field of adsorption due to their low density and large specific surface area. In this work, peptide nanofibers (PNFs) with a motif-designed peptide sequence are synthesized viamolecular self-assembly, and are then bound to the surface of graphene oxide (GO) nanosheets through π–π conjugation and provided active sites for nucleation and growth of HA crystals during the subsequent biomineralization process. The hybrid aerogel cross-linked between polyvinyl alcohol (PVA) and GO has a regular pore structure, and the mineralization process promotes functional regulation of aerogels. The mineralized PVA/PNF/GO–HA hybrid aerogels show good adsorption performance for Pb2+, and the saturated adsorption capacity can reach 113.88 mg g−1when Pb2+is 400 mg L−1(pH = 5, 25 °C). At the same time, the adsorption effect of the PVA/PNF/GO–HA hybrid aerogel on MB is also obvious, and the adsorption capacity reaches 234.85 mg g−1when the methylene blue (MB) concentration is 500 mg L−1(pH = 7, 25 °C). In addition, the hybrid aerogel has better stability in water, which is convenient for recovery after adsorption. Finally, the fabricated hybrid aerogels are evaluated for their sustainability using the Ranking Efficiency Product (REP) method. This study facilitates the design and synthesis of nanohybrid aerogels through biomimetic synthesis with highly sustainable applications in water purification.

Environmental pollution is a global problem that endangers human health and ecological balance. As a new type of functional material, two-dimensional material (2DM)-based aerogel is one of the most promising candidates for pollutant detection and environmental remediation. The porous, network-like, interconnected three-dimensional (3D) structure of 2DM-based aerogels can not only preserve the characteristics of the original 2DMs, but also bring many distinct physical and chemical properties to offer abundant active sites for adsorbing and combining pollutants, thereby facilitating highly efficient monitoring and treatment of hazardous pollutants. In this review, the synthesis methods of 2DM aerogels and their broad environmental applications, including various sensors, adsorbents, and photocatalysts for the detection and treatment of pollutants, are summarized and discussed. In addition, the sustainability of 2DM aerogels compared to other water purification materials, such as activated carbon, 2DMs, and other aerogels are analyzed by the Sustainability Footprint method. According to the characteristics of different 2DMs, special focuses and perspectives are given on the adsorption properties of graphene, MXene, and boron nitride aerogels, as well as the sensing and photocatalytic properties of transition metal dichalcogenide/oxide and carbon nitride aerogels. This comprehensive work introduces the synthesis, modification, and functional tailoring strategies of different 2DM aerogels, as well as their unique characteristics of adsorption, photocatalysis, and recovery, which will be useful for the readers in various fields of materials science, nanotechnology, environmental science, bioanalysis, and others.

To assess the role of protein-energy malnutrition on perioperative outcomes in patients with pancreatic cancer undergoing open pancreaticoduodenectomy. We conducted a retrospective observational cohort study and investigated patients ≥ 18 years old with pancreatic cancer undergoing open pancreaticoduodenectomy within the National inpatient sample database during 2012–2014. The study population was divided into two groups based on the presence of protein-energy malnutrition. In-hospital mortality, length of stay, cost of hospitalization, and in-hospital complications were compared between the two groups. Logistic and linear regression analyses were used to adjust for potential confounders. A trend analysis was further conducted on the in-hospital outcomes. Of the 12,785 patients aged ≥ 18 years undergoing open pancreaticoduodenectomy during years 2012–2014, 9865 (77.0%) had no protein-energy malnutrition and 2920 (23.0%) had protein-energy malnutrition. Patients with protein-energy malnutrition were found to have significantly higher mortality rate, longer length of hospital stay, and higher total hospital cost compared to those without protein-energy malnutrition. The risks of gastroparesis, small bowel obstruction, intraoperative and postoperative hemorrhage, infectious complications, and several systemic complications were found to be significantly higher in the protein-energy malnutrition group in a multivariate regression model. A study of trends from 2009 to 2012 revealed an increasing prevalence of protein-energy malnutrition, a declining trend in mortality and length of stay and a stable total hospital cost in the protein-energy malnutrition group. Protein-energy malnutrition was found to be associated with higher mortality, longer length of hospital stay and greater hospital cost in pancreatic cancer patients undergoing open pancreaticoduodenectomy, as well as increased occurrence of various systemic complications. Attention should be paid to patients’ nutritional status, which can be corrected before surgery as an effective means to optimize postoperative results.

Oncolytic adenoviruses (OAs) have shown great potential for cancer viral gene therapy in clinical studies. To date, clinical trials have shown that the curative efficacy of OAs is still limited by hepatic sequestration and preexisting neutralizing antibodies (nAbs), which decrease the accumulation of the OAs in tumors. Herein, with the biosilicification method, we encapsulated an OA encoding the anticancer gene Trail (OA-Trail) with silica, which significantly improved virus distribution and tumor inhibition. In vitroand in vivoresults indicated that compared with the native OA, biosilicified OA-Trail (OA-Trail@SiO2) showed significantly reduced viral clearance in the liver and evaded nAb degradation, inducing an efficacious anticancer effect under the premise of biocompatibility. These achievements present an alternative strategy involving biosilicification for enhanced OA-based cancer gene therapy.

An aptamer-linked assay of a target biomarker (e.g., thrombin) is facing the challenges of long-term run, complex performance, and expensive instrument, unfitting clinical diagnosis in resource-limited areas. Herein, a facile chip electrophoresis titration (ET) model was proposed for rapid, portable, and low-cost assay of thrombin via aptamer-linked magnetic nanoparticles (MNPs), redox boundary (RB), and horseradish peroxidase (HRP). In the electrophoresis titration-redox boundary (ET-RB) model, thrombin was chosen as a model biomarker, which could be captured within 15 min by MNP-aptamer 1 and HRP-aptamer 2, forming a sandwich complex of (MNP-aptamer 1)–thrombin–(HRP-aptamer 2). After MNP separation and chromogenic reaction of 3,3′,5,5′-tetramethylbenzidine (TMB) within 10 min, an ET-RB run could be completed within 5 min based on the reaction between a 3,3′,5,5′-tetramethylbenzidine radical cation (TMB•+) and l-ascorbic acid in the ET channel. The systemic experiments based on the ET-RB method revealed that the sandwich complex could be formed and the thrombin content could be assayed via an ET-RB chip, demonstrating the developed model and method. In particular, the ET-RB method had the evident merits of simplicity, rapidity (less than 30 min), and low cost as well as portability and visuality, in contrast to the currently used thrombin assay. In addition, the developed method had high selectivity, sensitivity (limit of detection of 0.04 nM), and stability (intraday: 3.26%, interday: 6.07%) as well as good recovery (urine: 97–102%, serum: 94–103%). The developed model and method have potential to the development of a point-of-care testing assay in resource-constrained conditions.

This study examined the antecedents of an individual’s creative self-efficacy (CSE) using a sample of 41 semiconductor design teams. Drawing from social cognitive theory, we expected that a dynamic interaction of an individual’s learning goal orientation, creativity as a job requirement, and team learning behavior would build CSE. In addition, employing the combinational perspective, we conjectured that consistency among the three antecedents would enhance CSE, and subsequently, creative performance. As predicted, results showed that effects of learning goal orientation and job requirement on CSE were subject to other members’ learning behavior. A significant three-way interaction supported the position that individual–contextual congruence facilitates the development of CSE, while incongruence of these factors impedes such development. Implications for theory and human resource practices are discussed in light of these findings.JEL Classification: M54, O32

Here we report a visible light-triggered, catalyst free bioorthogonal reaction that proceeds via a distinct pathway from reported bioorthogonal reactions. The prototype of this bioorthogonal reaction was the photocycloaddition of 9,10-phenanthrenequinone with electron-rich alkenes to form fluorogenic [4+2] cycloadducts. The bioorthogonal photoclick cycloaddition was readily initiated using a conventional visible light source such as a hand-held LED lamp. The reaction proceeded rapidly under biocompatible conditions, without observable competition from side reactions such as nucleophilic additions by water or common nucleophilic species. The bioorthogonal functionality in this reaction did not cross react with various alkynes and electron-deficient alkenes such as monomethyl fumarate. We demonstrated orthogonal labeling of two proteins using this reaction together with a strain promoting azide–alkyne click reaction or the UV-triggered reaction of tetrazole with monomethyl fumarate. The application of this reaction in the temporal and spatial labeling of live cells was also demonstrated.

Although the output of industrial solid waste carbide slag is high, its utilization rate is low. Furthermore, carbide slag has a tendency to cause serious environmental problems. In this study, thermochemical heat storage through dehydration and rehydration is presented for resource utilization of carbide slag. The thermodynamic and kinetic properties of carbide slag in fluidized thermochemical heat storage were studied both experimentally and theoretically. The thermochemical heat storage capacities of three carbide slags were evaluated. In a temperature range of 50–300 °C, the specific heat capacity of carbide slags and their decomposition products was 1.0–1.5 J/(g·°C) and 0.72–0.96 J/(g·°C), respectively. The ratio of the sensible heat storage capacity of carbide slag to the total heat storage capacity increased with storage temperature. Furthermore, the rapid decomposition reaction of carbide slag conformed to the contracting cylinder model with an apparent activation energy of 96.94 kJ/mol and pre-exponential factor of 8.09 × 104 s−1. The reaction time of the carbide slag predicted by the kinetic control equation was close to the experimental result of the fluidized bed reactor, providing reliable kinetic information for the design of the fluidized bed reactor. This study demonstrates that carbide slag is a low-cost heat-storage material with promising large-scale industrial applications.

Identification of infectious bacteria responsible for biofilm-associated infections is challenging due to the complex and heterogeneous biofilm matrix. To address this issue and minimize the impact of heterogeneity on biofilm identification, we developed a gold nanoparticle (AuNP)-based multichannel sensor to detect and identify biofilms based on their physicochemical properties. Our results showed that the sensor can discriminate six bacterial biofilms including two composed of uropathogenic bacteria. The capability of the sensor was further demonstrated through discrimination of biofilms in a mixed bacteria/mammalian cell in vitrowound model.

A protein corona is formed at the surface of nanoparticles in the presence of biological fluids, masking the surface properties of the particle and complicating the relationship between chemical functionality and biological effects. We present here a series of zwitterionic NPs of variable hydrophobicity that do not adsorb proteins at moderate levels of serum protein and do not form hard coronas at physiological serum concentrations. These particles provide platforms to evaluate nanobiological behavior such as cell uptake and hemolysis dictated directly by chemical motifs at the nanoparticle surface.

Having understood the disadvantages of traditional marine development mode, the sustainable development mode, which makes overall planning of land and sea and endorses equal importance to both development and protection, is attracting more and more attentions from coastal regions. To formulate the right orientation of marine development, this thesis attempts to apply SWOT-AHP method, a combination of qualitative and quantitative analysis, into strategy formulation. And, by introducing revision coefficient, this thesis modifies the current quantitative calculation methods. Finally, a SWOT-AHP analysis system of sustainable marine development plan has been constructed. In the study of Shantou marine development, strength, weakness, opportunity and threat factors have been listed through symposium and data analysis; attribution and impacts of these factors are calculated from experts’ evaluation. Based on these scores, a strategic quadrilateral is built, which could directly reflect the orientation of Shantou marine development. According to the analysis results, we can see that the advantage of Shantou marine development is obvious. Shantou should take growth strategy to make better use of its strength and opportunity factors; and transform its development mode from the traditional overexploitation to a sustainable one, which highly emphasizes on protecting marine ecological services and achieving the equilibrium of both ecological civilization and economic growth.

Coastal management practices, regulatory decision-making, and land use planning activities along coastal areas have historically been made with insufficient scientific information concerning the dynamic environment. The idea of integration of science and coastal management has risen rapidly in both environmental science and public environmental policy since the mid-1990s, and encouraged innovative relationships between scientists and practitioners in a range of contexts. In this paper, based on materials analysis, we explore the existing practices, evaluating past successes and failures in the management mode of coastal areas in Hong Kong. Though this case study we examine the challenges Hong Kong faces presently, illustrate the strong need for integrating science and coastal management.

Today, the coastal areas of the world amounting to nearly 10% of the total world’s land area, supports nearly half of the world’s human population. This causes serious population pressure and environmental problems. To reduce the pressure of land scarcity, cities along the coastal land are now paying their attention to land reclamation. Although land reclamation results in significant benefits to the coastal cities, it simultaneously causes serious environmental problems. Therefore, satisfactory management of reclaimed land is a big challenge which governments are now facing. Based on economics, this article presents some economic means to efficiently manage coastal areas. Integrating the costs-benefits analysis and input-output table, this paper builds the “costs-benefits analysis system”, and provides the models of estimating the value of some main aspects of the costs. Through outcome consult method, shadow price, TCM (Travel Cost Method), CVM (Contingent Valuation Method) and other methods, one can appraise the ecological damage in monetary terms, which allows to transform questions of “yes” or “no” into questions of “more” or “less”, one can easily judge the feasibility of this project in terms of social benefits. Using this costs-benefits analysis system to assess the land reclamation in Gulei port, Zhangzhou, China, the outcome showed that the total costs were almost 3.4 times more than the benefits, meaning that it is really not beneficial to construct the project from economics point of view.

The aim of this present study was to investigate the d-dimer in acute pancreatitis and its associations with triglyceride (TG).

A fascinating nanoobject, amphiphilic polymer brushes with a hard core of multi-walled carbon nanotubes MWNTs and a relatively soft shell of polystyrene-block-polyacrylic acid PS-b-PAA, was easily constructed by in situatom transfer radical polymerization ATRP of styrene followed by tert-butyl acrylate on the modified convex surfaces of MWNTs MWNT-PS followed by hydrolysis of the grafted polytert-butyl acrylate PtBA blocks. The structure and morphology of the as-prepared hybrid nanomaterials were characterized and confirmed by electron microscopy TEM and SEM, nuclear magnetic resonance NMR spectrometry, and thermogravimetric analysis TGA. The results showed that both styrene and acrylate types of ATRP-active vinyl monomers can be easily initiated and then propagated on the MWNT sidewalls viathe in situATRP approach, and the length of the PtBA blocks increases with increasing tBA : MWNT-PS weight feed ratio. We believe that the breakthrough associated with formation of such a complex nanoobject would open a door for the fabrication of novel functional carbon nanotube-based nanomaterials or nanodevices with designable structure and tailor-made properties.

A fascinating nanoobject, amphiphilic polymer brushes with a hard core of multi-walled carbon nanotubes (MWNTs) and a relatively soft shell of polystyrene-block-poly(acrylic acid) (PS-b-PAA), was easily constructed by in situ atom transfer radical polymerization (ATRP) of styrene followed by tert-butyl acrylate on the modified convex surfaces of MWNTs (MWNT-PS) followed by hydrolysis of the grafted poly(tert-butyl acrylate) (PtBA) blocks. The structure and morphology of the as-prepared hybrid nanomaterials were characterized and confirmed by electron microscopy (TEM and SEM), nuclear magnetic resonance (NMR) spectrometry, and thermogravimetric analysis (TGA). The results showed that both styrene and acrylate types of ATRP-active vinyl monomers can be easily initiated and then propagated on the MWNT sidewalls via the in situ ATRP approach, and the length of the PtBA blocks increases with increasing tBA : MWNT-PS weight feed ratio. We believe that the breakthrough associated with formation of such a complex nanoobject would open a door for the fabrication of novel functional carbon nanotube-based nanomaterials or nanodevices with designable structure and tailor-made properties.

We present a new divergence method to estimated methane (CH4) emissions from satellite observed mean mixing ratio of methane (XCH4) by deriving the regional enhancement of XCH4in the Planetary Boundary Layer (PBL). The applicability is proven by comparing the estimated emissions with its known emission inventory from a 3‐month GEOS‐Chem simulation. When applied to TROPOspheric Monitoring Instrument observations, sources from well‐known oil/gas production areas, livestock farms and wetlands in Texas become clearly visible in the emission maps. The calculated yearly averaged total CH4emission over the Permian Basin is 3.06 (2.82, 3.78) Tg a−1for 2019, which is consistent with previous studies and double that of EDGAR v4.3.2 for 2012. Sensitivity tests on PBL heights, on the derived regional background and on wind speeds suggest our divergence method is quite robust. It is also a fast and simple method to estimate the CH4emissions globally. Methane (CH4) is an important greenhouse gas in the atmosphere and plays a crucial role in the global climate change. It kept increasing over the last decades. About 70% of CH4comes from human activities like oil/gas productions or livestock farms. The recently launched TROPOspheric Monitoring Instrument provides an opportunity to estimate the emissions of CH4on a regional scale. This work presents a new method to fastly derive CH4emissions at a fairly high spatial resolution without a priori knowledge of sources. A new divergence method is developed to estimate methane emissions based on satellite observations, requiring no a priori emissionsThe applicability of this method in identifying and quantifying sources is proven by a GEOS‐Chem simulation with known emission inventoryThe estimated emissions over Texas (United States) based on TROPOspheric Monitoring Instrument observations are evaluated and are found to be robust A new divergence method is developed to estimate methane emissions based on satellite observations, requiring no a priori emissions The applicability of this method in identifying and quantifying sources is proven by a GEOS‐Chem simulation with known emission inventory The estimated emissions over Texas (United States) based on TROPOspheric Monitoring Instrument observations are evaluated and are found to be robust