mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Challenges in developing polymer flocculants to improve bitumen quality in non-aqueous extraction processes: an experimental study

Western Canada's oil sands hold the third-largest hydrocarbon deposits in the world. Bitumen, a very heavy petroleum, is currently recovered by surface mining with warm water or in situ. Recovery processes that use organic solvents are being developed to reduce water usage and tailings production. While solvent-based methods can effectively extract bitumen, removal of residual fine solids from diluted bitumen product (DBP) to meet the pipeline transport requirement of < 0.5 wt %solids and water in DBP remains a major challenge. We propose a novel area of application of polymer flocculants for fine solids removal from DBP. In principle, polymer flocculants can be applied to help remove these residual solids in conjunction with physical separation processes to increase process effectiveness and energy efficiency. Several polymers are selected and screened for flocculation behavior using kaolinite suspended in DBP and toluene, as a model system. Focused beam reflectance measurements and force tensiometer techniques are used to determine flocculation and sedimentation in DBP. The observed flocculation and sedimentation rate enhancements indicate that the polymers tested have only minor effects, providing opportunities for advanced polymer development. These findings exemplify the challenges in identifying polymers that may be effective as flocculants in heavy petroleum media.
Viscous flow simulations through multi-lobe progressive cavity pumps

Computational fluid dynamics (CFD) simulations of multi-lobe progressive cavity (PC) pumps are limited in the literature due to the geometric complexity of the pump, which places numerous restrictions on the grid generation process. The present study attempts to alleviate such restrictions by developing a detailed numerical procedure for the numerical simulations of multi-lobe progressive cavity pumps. The profile equations for the multi-lobe configuration at any section at each instant of rotation are presented. A structured grid generation method is developed to generate mesh files required for CFD simulations of multi-lobe PC pumps. Results from the present procedure are validated against single-lobe PC pump numerical results available in the literature. Finally, a numerical parametric study is carried out to investigate the effect of the number of lobes, the stator pitch, the circular fillet and clearance on the volumetric efficiency of PC pumps with viscous oils.
Modeling of fiber bridging in fluid flow for well stimulation applications

Accurate acid placement constitutes a major concern in matrix stimulation because the acid tends to penetrate the zones of least resistance while leaving the low-permeability regions of the formation untreated. Degradable materials (fibers and solid particles) have recently shown a good capability as fluid diversion to overcome the issues related to matrix stimulation. Despite the success achieved in the recent acid stimulation jobs stemming from the use of some products that rely on fiber flocculation as the main diverting mechanism, it was observed that the volume of the base fluid and the loading of the particles are not optimized. The current industry lacks a scientific design guideline because the used methodology is based on experience or empirical studies in a particular area with a particular product. It is important then to understand the fundamentals of how acid diversion works in carbonates with different diverting mechanisms and diverters. Mathematical modeling and computer simulations are effective tools to develop this understanding and are efficiently applied to new product development, new applications of existing products or usage optimization. In this work, we develop a numerical model to study fiber dynamics in fluid flow. We employ a discrete element method in which the fibers are represented by multi-rigid-body systems of interconnected spheres. The discrete fiber model is coupled with a fluid flow solver to account for the inherent simultaneous interactions. The focus of the study is on the tendency for fibers to flocculate and bridge when interacting with suspending fluids and encountering restrictions that can be representative of fractures or wormholes in carbonates. The trends of the dynamic fiber behavior under various operating conditions including fiber loading, flow rate and fluid viscosity obtained from the numerical model show consistency with experimental observations. The present numerical investigation reveals that the bridging capability of the fiber–fluid system can be enhanced by increasing the fiber loading, selecting fibers with higher stiffness, reducing the injection flow rate, reducing the suspending fluid viscosity or increasing the attractive cohesive forces among fibers by using sticky fibers.
Effect of nanoparticles on the nucleation and agglomeration rates of hydrate growth using THF–water clathrates

Four types of nanoparticles, amorphous carbon, iron III oxide, SiO_2, and amino-coated SiO_2, were tested to determine changes in tetrahydrofuran–water (THF–water) clathrate hydrate nucleation and agglomeration. Rates were experimentally found to determine their viability for preventing natural gas hydrates from developing during offshore drilling operations. THF–water clathrates were chosen as a model to represent gas hydrate growth at atmospheric pressure. Concentrations of each nanoparticle between 0.15 %and 1.0 %by weight were tested as a kinetic inhibitor to hydrate formation. Tests were repeated at various temperatures below the formation temperature of 4.4 °C for THF–water clathrate hydrates. Measurements were made to identify how the concentration of THF affects the clathrate hydrates forming under static conditions between 20 %and 30 %by mole of THF. The primary tests in this study were performed using a 20:80 THF/water ratio. Temperature increases during hydrate nucleation for THF–water were measured between - 5 and 3 °C. The range of ideal nanoparticle concentrations was found to be between 0.15 %and 0.45 %by weight for optimal static, kinetic inhibition of hydrate nucleation. At approximately 0.3 %by weight, the most significant inhibition was observed under static conditions for all four types of nanoparticles tested. We found that functionalized amino-coated SiO_2 nanoparticles, across all tests, significantly increased the time required for the formation of THF–water clathrate hydrates compared to the other three non-functionalized nanoparticles. The amorphous carbon and iron III oxide nanoparticles performed similarly across each test and were both the least effective in their inhibition of the clathrate hydrates of the four nanoparticles studied compared to a control.
Standard friction prediction model of long-distance hot oil pipelines

We developed a predictive model for the pipeline friction in the 520–730 m3/h transmission range using the multi-layerperceptron– back-propagation (MLP–BP) method and analyzing the unit friction data after the pigging of a hot oil pipeline. In view of the shortcomings of the MLP–BP model, two optimization methods, the genetic algorithm (GA) and mind evolutionary algorithm (MEA), were used to optimize the MLP–BP model. The research results were applied to the standard friction prediction of three sections of a hot oil pipeline. After the GA and MEA optimizations, the average errors of the three sections were 0.0041 MPa for the GA and 0.0012 MPa for the MEA, and the mean-square errors were 0.083 and 0.067, respectively. The MEA-BP model prediction results were characterized by high precision and small dispersion. The MEABP prediction model was applied to the analysis of the wax formation 60 and 90 days after pigging. The analysis results showed that the model can effectively guide pipe pigging and optimization. There was little sample data for the individual transmission and oil temperature steps because the model was based on actual production data modeling and analysis, which may have affected the accuracy and adaptability of the model.
Performance comparison of novel chemical agents in improving oil recovery from tight sands through spontaneous imbibition

Tight sands are abundant in nanopores leading to a high capillary pressure and normally a low fluid injectivity. As such, spontaneous imbibition might be an effective mechanism for improving oil recovery from tight sands after fracturing. The chemical agents added to the injected water can alter the interfacial properties, which could help further enhance the oil recovery by spontaneous imbibition. This study explores the possibility of using novel chemicals to enhance oil recovery from tight sands via spontaneous imbibition. We experimentally examine the effects of more than ten different chemical agents on spontaneous imbibition, including a cationic surfactant (C12TAB), two anionic surfactants (O242 and O342), an ionic liquid (BMMIM BF4), a high pH solution (NaBO_2), and a series of house-made deep eutectic solvents (DES3–7, 9, 11, and 14). The interfacial tensions (IFT) between oil phase and some chemical solutions are also determined. Experimental results indicate that both the ionic liquid and cationic surfactant used in this study are detrimental to spontaneous imbibition and decrease the oil recovery from tight sands, even though cationic surfactant significantly decreases the oil–water IFT while ionic liquid does not. The high pH NaBO_2 solution does not demonstrate significant effect on oil recovery improvement and IFT reduction. The anionic surfactants (O242 and O342) are effective in enhancing oil recovery from tight sands through oil–water IFT reduction and emulsification effects. The DESs drive the rock surface to be more water-wet, and a specific formulation (DES9) leads to much improvement on oil recovery under counter-current imbibition condition. This preliminary study would provide some knowledge about how to optimize the selection of chemicals for improving oil recovery from tight reservoirs.
Shape factor for regular and irregular matrix blocks in fractured porous media

Describing matrix–fracture interaction is one of the most important factors for modeling natural fractured reservoirs. A common approach for simulation of naturally fractured reservoirs is dual-porosity modeling where the degree of communication between the low-permeability medium (matrix) and high-permeability medium (fracture) is usually determined by a transfer function. Most of the proposed matrix–fracture functions depend on the geometry of the matrix and fractures that are lumped to a factor called shape factor. Unfortunately, there is no unique solution for calculating the shape factor even for symmetric cases. Conducting fine-scale modeling is a tool for calculating the shape factor and validating the current solutions in the literature. In this study, the shape factor is calculated based on the numerical simulation of fine-grid simulations for single-phase flow using finite element method. To the best of the author's knowledge, this is the first study to calculate the shape factors for multidimensional irregular bodies in a systematic approach. Several models were used, and shape factors were calculated for both transient and pseudo-steady-state (PSS) cases, although in some cases they were not clarified and assumptions were not clear. The boundary condition dependency of the shape factor was also investigated, and the obtained results were compared with the results of other studies. Results show that some of the most popular formulas cannot capture the exact physics of matrix–fracture interaction. The obtained results also show that both PSS and transient approaches for describing matrix–fracture transfer lead to constant shape factors that are not unique and depend on the fracture pressure (boundary condition) and how it changes with time.
Enduring effect of permeability texture for enhancing accuracy and reducing uncertainty of reservoir fluid flow through porous media

Modeling reservoir permeability is one of the crucial tasks in reservoir simulation studies. Traditionally, it is done by kriging-based methods. More rigorous modeling of the permeability results in more reliable outputs of the reservoir models. Recently, a new category of geostatistical methods has been used for this purpose, namely multiple point statistics (MPS). By this new category of permeability modeling methods, one is able to predict the heterogeneity of the reservoir permeability as a continuous variable. These methods consider the direction of property variation in addition to the distances of known locations of the property. In this study, the reservoir performance of a modified version of the SPE 10 solution project as a pioneer case is used for investigating the efficiency of these methods and paralleling them with the kriging-based one. In this way, the permeability texture concept is introduced by applying some MPS methods. This study is accomplished in the conditions of real reservoir dimensions and velocities for the whole reservoir life. A continuous training image is used as the input of calculation for the permeability modeling. The results show that the detailed permeability of the reservoir as a continuous variable makes the reservoir simulation show the same fluid front movement and flooding behavior of the reservoir similar to the reference case with the same permeability heterogeneity. Some MPS methods enable the reservoir simulation to reproduce the fluid flow complexities such as bypassing and oil trapping during water flooding similar to the reference case. Accordingly, total oil production is predicted with higher accuracy and lower uncertainty. All studied cases are identical except for the permeability texture. Even histograms and variograms of permeabilities for the studied reservoir are quite similar, but the performance of the reservoir shows that kriging-based method results have slightly less accuracy than some MPS methods. Meanwhile, it results in lower uncertainty in outputs for this water flooding case performance.
Availability Analysis of a Repairable Series-Parallel System with Redundant Dependency

This paper investigates the steady-state availability of a repairable series-parallel system with redundant dependency.The different types of components and repairmen are taken into account,the failure rate of the operating component varies as the number of other failed components and the repair rate of the failed component is constant in each parallel redundant subsystem.To quantify the redundant dependency,a modified failure dependence function is introduced to determine the failure rate of the components in each subsystem.Markov theory and matrix analysis method are used to get the steady-state probability vector of each subsystem and the steady-state availability of the entire system.A numerical example is presented to illustrate the obtained results and to analyze the effect of redundant dependency class on the system availability.
Dynamic Event-Triggered Control for Nonlinear Systems:A Small-Gain Approach

An event-triggered control(ETC)system transmits data packages and updates control inputs only when the predefined criterion is satisfied.In this way,network communication and computing resources are scheduled more reasonably in contrast to the traditional periodic sampling strategy.Small-gain approach proposed in recent literatures is a new modeling method to deal with nonlinear ETC systems.Different from traditional ETC models,stability criteria are proposed in the form of input to state stability(ISS)gain to design the triggering mechanisms.This paper introduces additional dynamic variables in this model and proposes a small-gain based dynamic event-triggered strategy.Sufficient conditions to guarantee the stability of the system are derived with the help of cyclic-smallgain theorem and Zeno behaviors are avoided to ensure the feasibility of this method in practical applications.Numerical simulations are given to demonstrate the effectiveness of our approach.
基于遗传算法的航天零件仓库货位优化研究

为提高航天零件仓储系统中零件出库效率和货架稳定性,建立多目标货位优化模型,并通过简单加权处理,将其转换成单目标优化模型。对仓储系统三个月的历史订单数据进行处理,提出基于遗传算法的存储策略。对模型仿真求解时,引入模拟退火算法解决了遗传算法出现早熟的问题。结果表明,提出的策略结果明显优于随机存储策略(RS)、ABC分类存储策略(ABC)、就近存储策略(COL),能有效提高立体仓库货物出库效率及货架稳定性。
基于支持向量机和深度信念网络的短期光伏发电预测方法

为了提高光伏发电预测的精度,提出基于支持向量机和深度信念网络的光伏发电预测方法。利用改进的相似日算法选择相似日训练样本,分别构建以线性核函数、多项式核函数、高斯径向基核函数为核函数的支持向量机预测模型作为组合预测模型中的单项模型,再将三种单项模型的预测结果作为深度信念网络的输入,利用深度信念网络对三种单项模型的预测结果进行组合优化输出,根据实际输出与期望输出的误差动态调整组合权值,从而获得更高的预测精度。最后以澳大利亚沙漠太阳能研究中心的实测数据进行仿真验证,仿真结果表明,所提方法相较于其他方法具有较高的预测精度。
睾丸生精功能障碍的促生精治疗

睾丸内精子的产生主要受生殖内分泌激素的调控,高浓度睾酮(Testosterone,T)的生精上皮及支持细胞环境是精子发生的必须条件。在生理情况下,下丘脑、垂体及睾丸的内分泌激素形成完整的反馈调控系统,促进和调控精子的发生、成熟。睾丸生精功能障碍是指因各种原因导致睾丸内生精上皮(或生精组织)生精能力下降,生精细胞部分或全部发育阻滞,形成少精子或无精子,导致男性不育。目前临床对睾丸生精功能障碍的治疗方法主要包括药物治疗、手术治疗和辅助生殖。药物治疗在临床上被广泛使用,某些药物也确实对患者有一定的积极治疗作用,能提高自然妊娠或辅助生殖获精率,也是绝大数患者首选的治疗办法,但它却多是经验性治疗,效果也不十分确切。因此,掌握睾丸生精功能障碍的促生精治疗适应症、治疗时机和注意事项,对提高临床治疗效果有重要意义。
长链非编码RNA(lncRNA)对巨噬细胞极化转录调控的研究进展

经典活化型巨噬细胞(M1型)和替代活化型巨噬细胞(M2型)是两种具有不同表型和功能的巨噬细胞亚群。巨噬细胞能响应微环境信号,迅速从一种极化状态转换到另一种极化状态。巨噬细胞极化受核因子κB(NF-κB)、信号转导子和转录激活子(STAT)、干扰素调节因子(IRF)等转录因子调控,进而参与多种炎症相关性疾病的发生发展。长链非编码RNA(lncRNA)可调控NF-κB抑制蛋白(IκB)磷酸化改变NF-κB核移位,或通过与p65/p50形成复合物抑制NF-κB与其靶基因启动子结合,进而调控巨噬细胞极性; lncRNA可直接调控Janus激酶2(JAK2)/STAT通路,或间接通过细胞因子信号传送阻抑物(SOCS)调控STAT表达参与巨噬细胞极化调控; lncRNA通过调控多梳抑制复合物2(PRC2)等间接影响IRF的转录,调控巨噬细胞极化。深入了解lncRNA对巨噬细胞极化转录调控的作用机制,有助于为这些疾病的诊断和治疗提供新的策略。
RNA特异性腺苷脱氨酶1(ADAR1)在肿瘤免疫治疗中的研究进展

RNA特异性腺苷脱氨酶1(ADAR1)是一种作用于双链RNA(dsRNA)使腺苷脱氨基产生肌苷(A-to-I)的酶,其RNA编辑依赖作用和非RNA编辑依赖的蛋白质-蛋白质相互作用在人类疾病中发挥重要作用。ADAR1在实体肿瘤中过表达使肿瘤细胞逃避免疫识别促进肿瘤发生发展,其中干扰素刺激基因(ISG)呈阳性的肿瘤细胞对ADAR1缺失具有独特的易感性。因此,在ISG呈阳性肿瘤细胞中靶向ADAR1成为增强肿瘤免疫疗法或克服肿瘤免疫检查点抑制剂抵抗的新方法。而ADAR1 p150亚型的左手螺旋DNA(Z-DNA)特异性和左手螺旋RNA(Z-RNA)特异性Zα结构域可能成为特异性的作用靶点,在实体肿瘤免疫治疗中发挥作用。
紫黑色特种两系杂交水稻新组合坤两优22

坤两优22是江西科源种业有限公司和广西恒茂农业科技有限公司利用两系不育系坤S和恢复系G022配组育成的紫黑色特种两系杂交稻新组合。该组合具有株叶形态好,茎秆粗壮,剑叶挺直,稃尖紫色,种皮紫黑色,谷壳灰褐色,后期落色好等特点,稻米花青素、β-胡萝卜素、硒含量较高。2018和2019年分别通过广西壮族自治区和江西省农作物品种审定委员会审定。
两系杂交水稻新组合深两优136高产制种技术

深两优136系湖南大农种业科技有限公司用不育系深08S与恢复系R136配组育成的籼型两系杂交水稻新组合, 2016年通过国家农作物品种审定委员会审定。根据多年的制种生产实践,总结了其亲本的特征特性和高产制种技术。
杂交水稻种子机械干燥技术

通过连续多年对4种低温谷物干燥机械干燥杂交水稻种子的试验测试和干燥实践,探明了4种谷物干燥机干燥杂交水稻种子的效果、效率、成本以及干燥脱水特性,提出了“安全、快速、低损、无混杂、低污染”的干燥目标,形成了选择适宜机型和热源、适宜收获期收获、快速转运初选入料、适温干燥、监控水分和种温等机械干燥技术。提出了“两段干燥法”干燥工艺,以实现不良天气条件下的种子安全快速干燥。
杂交水稻新组合武优6号机械辅助高产制种技术

武优6号是四川华丰种业有限责任公司以香稻不育系武香A与高产抗病恢复系华恢016配组育成的高产稳产香型杂交水稻新组合。现根据组合亲本的特征特性和制种基地的种植习惯、气候条件等,总结出武优6号的机械辅助高产制种技术。
齐穗后喷施抗逆免疫剂对杂交粳稻籽粒灌浆及产量的影响

为探明抗逆免疫剂对杂交粳稻齐穗后籽粒灌浆及产量的影响,以辽优9906(高产型品种)和粳优653(优质型品种)为试验材料,设置4个喷施处理,研究不同喷施处理对水稻灌浆期籽粒物质积累量和粒重的调节效应。结果表明,齐穗期喷施1次、齐穗期后10 d喷施1次、齐穗期和齐穗期后10 d各喷施1次均能够提高水稻产量,其中齐穗期和齐穗期后10 d各喷施1次增产效果显著,且表现为高产型品种的增产效果大于优质型品种。抗逆免疫剂通过提高分蘖成穗率、每穗实粒数、结实率、叶片SPAD值和净光合速率以及开花后14 ~ 20 d的灌浆速率来增加产量。
我国社区严重精神障碍患者高风险行为危险因素Meta分析

目的通过Meta分析探讨我国社区严重精神障碍患者高风险行为危险因素,为预防此类行为的发生提供科学依据。方法文献检索截止至2019年11月国内外公开发表的有关我国社区严重精神障碍患者高风险行为危险因素的研究文献,采用纽卡斯尔-渥太华量表评价文献质量。运用Stata 15.0分析软件进行Meta分析。利用I2衡量研究间异质性大小,并选择相应模型定量分析。用Egger's检验来评估发表偏倚。结果共纳入文献9篇(NOS评分不低于6分),病例组2 423人,对照组40 994人。Meta分析结果显示,无业(OR=3.204,95%CI:1.986~5.169)、不服药(OR=2.592,95%CI:2.250~ 2.986)、小学及以下学历(OR=2.475,95%CI:2.246~2.726)、男性(OR=2.028,95%CI:1.675 ~2.455)、精神分裂症(OR= 1.907,95%CI:1.472~2.469)、家族史阳性(OR=1.723,95%CI:1.446~2.053)和未婚(OR=1.456,95%CI:1.336~1.587)是严重精神障碍患者高风险行为的危险因素,均有统计学意义(P<0.05)。敏感性分析显示,以上因素合并结果较为稳定。Egger's检验显示纳入文献无发表偏倚。结论社区严重精神障碍患者高风险行为与多种因素有关,无业、不服药、小学及以下学历、男性、精神分裂症、家族史阳性和未婚是影响高风险行为发生较为可靠的危险因素。
Electrical conductivity of REF_3-LiF (RE=La and Nd) molten salts

The electrical conductivity of REF_3-LiF (RE = La and Nd) molten salts (xREF_3 = 5 mol%e40 mol%) was systematically measured over the temperature range from 1223 to 1423 K by using continuously varying cell constant (CVCC) method. Electrical conductivity values of LaF3-LiF and NdF3-LiF molten salts within the studied ranges are 4.11e9.39 and 3.62e9.51 S/cm, respectively. The composition and temperature dependences of electrical conductivity and the factor of RE_2O_3 on electrical conductivity were investigated. The electrical conductivity nonlinearly decreases with the increasing mole percent of REF_3 for the changing of structural ion in molten salts. A good linear relationship between the natural logarithm of electrical conductivity (lnk) and the reciprocal of the absolute temperature (T~(-1)) can be interpreted by the trend that electrical conductivity linearly increases with increasing temperature. Although it is an important factor of RE_2O_3 on electrical conductivity, the influence of RE_2O_3 on conductivity is small for the very limited solubility of RE_2O_3 in REF_3-LiF molten salts. The results of this work supplement the present electrical conductivity data of rare earth fluoride electrolyte.
Intense single-band red upconversion emission in BiOCl:Er~(3+) layered semiconductor via co-doping Ho~(3+)

Exploring a new tuning way to facilely realize single-band red emission in trivalent rare-earth ions (RE~(3+)) doped upconversion (UC) materials is still desirable. In this work, the intense single-band red emission is achieved by co-doping only Ho~(3+) in the BiOCl: Er~(3+) under 1550 nm excitation. In the BiOCl layered host, co-doping Ho~(3+) can further enhance the red emission and simultaneously suppress the green emission of Er~(3+), and thus obviously improve the red-to-green (R/G) ratio. It is found that Ho~(3+) does not serve as energy trapping through the ~5I_6 state as in traditional UC materials but acts as ET bridge (~4S_(3/2), ~2H_(11/2) (Er~(3+)) → ~5F_4, ~5S_2 (Ho~(3+)) → ~4F_(9/2) (Er~(3+))). The tuning mechanism of Ho~(3+) is discussed in detail and further confirms through a comparative experiment. Our research gives an unusual perspective to tune the UC behavior of Er~(3+) through co-doping Ho~(3+), which might be inspiring for achievement of single-band red UC emission.
Analysis of Short-term Cloud Feedback in East Asia Using Cloud Radiative Kernels

Cloud radiative kernels were built by BCC_RAD(Beijing Climate Center radiative transfer model)radiative transfer code.Then, short-term cloud feedback and its mechanisms in East Asia(0.5°S–60.5°N, 69.5°–150.5°E)were analyzed quantitatively using the kernels combined with MODIS satellite data from July 2002 to June 2018.According to the surface and monsoon types, four subregions in East Asia-the Tibetan Plateau, northwest, temperate monsoon(TM), and subtropical monsoon(SM)-were selected.The average longwave, shortwave, and net cloud feedbacks in East Asia are –0.68 ± 1.20, 1.34 ± 1.08, and 0.66 ± 0.40 W m~(–2) K~(–1)(±2σ), respectively, among which the net feedback is dominated by the positive shortwave feedback.Positive feedback in SM is the strongest of all subregions, mainly due to the contributions of nimbostratus and stratus.In East Asia, short-term feedback in spring is primarily caused by marine stratus in SM, in summer is primarily driven by deep convective cloud in TM, in autumn is mainly caused by land nimbostratus in SM, and in winter is mainly driven by land stratus in SM.Cloud feedback in East Asia is chiefly driven by decreases in mid-level and low cloud fraction owing to the changes in relative humidity, and a decrease in low cloud optical thickness due to the changes in cloud water content.
Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

While China's Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China.As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China.Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse.In addition, there is still no consensus on whether agricultural or non-agricultural emissions dominate the urban ammonia budget.Identifying the ammonia source by nitrogen isotope helps in designing a mitigation strategy for policymakers, but existing methods have not been well validated.Revisiting the concentration measurements and identifying source apportionment of atmospheric ammonia is thus an essential step towards reducing ammonia emissions.