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We specify a general model of the dynamic abatement technology adoption process and show how the accumulated experience among them can alter the adoption timing. Learning-by-doing (LBD) effect is considered to describe the reduction of the costly price to the adoption. Moreover, spillovers effect which reflects how accumulated experience can be shared among different technologies, is integrated into the learning process. To ensure the specification convincing, some reasonable assumptions are considered such as one abatement technology must conduct its own experience in order to realize the spillover. Besides, to investigate how the abatement process is influenced by the technology allocation under the spillovers effect, an endogenous emission path is considered to necessitate a meaningful optimization problem. Finally, apart from obtaining some basic properties of the model, we implement an empirical study to verify the effectiveness of the model. Data from the iron industry in China is used to specify the process, which can highlight the spillovers effect among different technologies from a sector angle. In the results, we find that intrinsic mechanism in the model results in the interplay among abatement coefficient, spillover factor and the growing rate of the emission etc. Collaborative relationships between variables are discussed as well. [ABSTRACT FROM AUTHOR]

The Sichuan-Tibet Railway traverses the Qinghai-Tibet Plateau in China, where giant landslides occur frequently and densely. Accurately assessing the velocity, runout distance, and influenced area of the potential landslides is one of the nonnegligible scientific and technical issues. This study establishes a dynamic model for the landslide runout assessment along the Sichuan-Tibet Railway. The proposed model is based on the shallow water theory and takes into account the mechanism that the friction is weakening with the increase of velocity, the finite difference method is used to solve the governing equations, and the ideal one-dimensional dam break experiment was used to verify the shock-capturing capacity of the numerical methods. The Lagang ancient landslide, only 500 m away from the Jiacha Station of the Sichuan-Tibet Railway, represents the typical environment and development pattern of landslides in this region. Therefore, the proposed model is applied to discuss its effects on the landslide dynamic process and deposit patterns. Besides, 75 sets of numerical experiments were further carried out to explore the sensibility of the three parameters including peak friction coefficient μ p , steady friction coefficient μ s , and critical velocity V c in this model. The results indicate that μ s determine the lower limit of the friction coefficient, which significantly impacts the landslide runout distance; μ p is mainly acting at the initial and final stage and has less influence on the landslide dynamic. By contrast, V c is the most significant. When the V c is small, the landslide can quickly reach the threshold velocity after the initial, and the dynamic process has a small correlation with the μ p ; when the V c is large, the landslide is difficult to reach the threshold, and the mobility will be limited. It should be noted that the materials, lithology, strength, and micro-cracks of landslides mass formed under the special geological, geomorphic, and climatic conditions in this region may affect the input values when using the friction weakening model on landslides risk assessment. • Established a numerical method for landslide risk assessment in the Sichuan-Tibet railway area • The parameters sensitivity of the resistance weakening model was discussed based numerical tests • Provides a calibration basis and range for the parameters required to apply the model [ABSTRACT FROM AUTHOR]

Abstract: This paper analyzes TOMS AOD at 500 nm (1980–2001), along with MODIS data (2000–2008) at 550 nm to investigate variations at one-degree grid over eight typical regions in China and the trends in AODs, temporally and spatially. In contrast to recently reported global decrease in AOD over global ocean beginning around 1990, we find there virtually exists no apparent AOD transition in China for that: firstly no notable upward tendencies in AOD during 1980–1992 for the relative low value (+0.001/decade), then during 1996–2001 a discernible ascending tendency with larger magnitude at 0.01/decade, and finally, since 2000, a weak upward trend with +0.004/decade. The large increases during 1996–2001 are presumably consequences of large increases in industrial activities and bear a strong resemblance to the long-term decreasing observations of incident solar radiation and cloud cover in China. Specifically, in late 1990’s, only in Taklimakan Desert a negative trend with a maximum magnitude of −0.04/decade is detected. However, over regions such as Jingjinji and Pearl River Delta influenced by industrial activities, positive tendencies at +0.01/decade are observed. Seasonal patterns in the AOD regional long-term trend are evident. AODs exhibit generally similar seasonality and the summer dominates higher AOD value than the autumn. In particular, during the period 1980–2001, all the eight regions except Taklimakan Desert witness the maximum aerosols in winter while there is not such seasonality during the period 2000–2008. Geographically, we also document spatial patterns of AOD variations over China. Results reveal that no apparent upward trends in AOD (about 15% per decade) are observed in 1980’s, while beginning 1990 till 2008, both data (TOMS and MODIS) are indicative of a significant AOD increase across China, especially in 1990’s it is indeed the case, roughly in accordance with the overall trends at regional scale. [Copyright &y& Elsevier]

Abstract: Using one year of Aerosol Optical Depth (AOD) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite and particular matter (PM) contents measured at eleven sites located mostly in the eastern China in 2007, the relationship between columnar AOD and hourly and daily average (DA) PM were established. The peak AOD observed from MODIS was generally consistent with the surface PM measurements in eastern China, where Zhengzhou had the maximum annual mean PM10 of 182.1 μg m−3, while Longfengshan had the minimum annual mean of 38.1 μg m−3. Ground level observations indicated that PM concentration varies widely across different regions, which was mainly due to the difference in weather conditions and anthropogenic emissions. The coarse particles accounted for the main air pollution in Zhengzhou and Benxi whiles the fine particles, however, were the main constituents in other sites. Results showed that MODIS AOD (averaged over the box of 5 × 5 and 3 × 3 pixels) had a better positive correlation with the coincident hourly average (HA) PM concentration than with DA due to diurnal variation in PM mass measurements. After correcting AOD for relative humidity (RH), the correlation did not improve significantly, suggesting that the RH was not the main factor affecting the correlation of PM with AOD. The statistical regression analysis between MODIS AOD and PM mass suggested that the satellite-derived AOD is a useful tool for mapping PM distribution over large spatial domains. [Copyright &y& Elsevier]

Abstract: Four sets of remote sensing images from 1987, 1994, 2000, and 2006, 50 years of meteorological and soil moisture data corresponding to different desertified lands were combined with populations and livestock data to analyze the process and cause of desertification in a portion of the Qinghai–Tibetan Plateau (QTP). It showed that surface soil temperature in the region has increased at an average rate of 0.6 °C per decade between 1980 and 2005, the thawing days on the surface have increased by 60 days from 1983 to 2001, and the depth of the seasonal thawing layer has increased by 54 cm, 102 cm and 77 cm in April, May and June, respectively, from 1983 to 2003. As a result, the upper soil layer has become drier due to the thickening active layer and soil water infiltration. These changes, in turn, have inhibited the growth of alpine meadow vegetation that has shallow root systems. It is concluded that climate warming and permafrost thawing have caused desertification in grazing regions of the Qinghai–Tibetan Plateau (QTP). [Copyright &y& Elsevier]

• We propose a new CCS project investment model, which helps to design the CCS development roadmap for achieving the next 2050. • Reductions in the cost of technologies as a result of learning-by-doing is considered to enrich the model. • We transform the original continuous problem into a nonlinear integer programming problem. • We are trying to answer questions about when to adopt CCS technology and what are their cost. • Flexible installation levels can be considered to improve efficiency and reduce costs. In the medium to long term, China must conduct deep emission reduction actions to transform the country's economy and meet the conditions of the Paris Agreement. As an advanced emission reduction technology, carbon capture and storage (CCS) is undoubtedly an important means of achieving this goal. China must consider how to retrofit existing thermal power plants to install CCS technology. Thus, the expected future roadmap for power plants with CO 2 capture is of significant interest. To achieve this aim, we propose a new CCS project investment model, which helps design the CCS development roadmap for achieving the emission targets for 2050. Reductions in the cost of technologies as a result of learning-by-doing is considered to enrich the model to describe the reality more sensibly. Through some mathematical skills, we transform the original continuous problem into a nonlinear integer programming problem. By solving the model, we are trying to answer questions about when to adopt CCS technology and the cost. The results reveal that early large-scale CCS demonstrations are not necessary. The peak investment period of CCS is around 2035. Operating costs account for 80% of the overall cost of CCS, and thus, policymakers must fully motivate the development and investment of operating technologies, especially capture technologies. The results also show that when the scale of CCS technology is promoted, flexible installation levels can be considered to improve efficiency and reduce costs. [ABSTRACT FROM AUTHOR]

To compare the effects of short-term exposure to particulate matter (PM) with different particle sizes on first-ever stroke risk in the middle-aged and elderly Chinese population. Health information was collected from the China National Stroke Screening Survey (CNSSS) from March 1, 2013, to April 10, 2015. Ambient exposures to PM 1 , PM 2.5 , and PM 10 were obtained from ChinaHighAirPollutants (CHAP) Grid data. Case-crossover design was used to estimate the increase of first-ever stroke risk per 10 μg/m3 increase in ambient exposures to different size particles. We used distributed lag linear model (DLM) to estimate the hysteresis effects of particle exposures. In addition, in order to assess the effect modification of long-term exposure, we did a stratified analysis using median exposure as the dividing line. We included 1326 first-ever stroke events from 242 communities in the present study. We found that effects on first-ever stroke risk increased with the decrease in particle size. The percent increases of first-ever stroke risk increased by 6.6% (95% CI: 1.4, 12.0), 3.3% (95% CI: 0.5, 6.1), and 0.6% (95% CI: -1.2, 2.6) per 10 g/m3 increases in PM 1 , PM 2.5 , and PM 10 exposures in lag 0–2 days, respectively. Furthermore, the cumulative effect of PM on first-ever stroke reached its peak at distinct time points under different layers of long-term PM exposure. In areas with low PM exposure, the cumulative effects of the three kinds of particles on stroke reached their peak in lag1 day, while the cumulative effect peaked in lag3 day in areas with high PM exposure. This study found that smaller particles had a stronger short-term effect on first-ever stroke. We also found that people in areas with long-term exposures to lower levels were more sensitive to short-term exposures. These results have public health significance for stroke prevention and air pollution reduction. [Display omitted] • The effects of PM on first-ever stroke in a large area were evaluated. • The impacts of PM increase with decreasing particle size. • The short-term effects of PM were larger in areas with lower long-term exposure levels. [ABSTRACT FROM AUTHOR]

Although environmental exposure to multiple metals is common, epidemiological studies on the associations of exposure to 23 metals with kidney function have not been analyzed. We aimed to investigate the associations of 23 metals levels with renal function. We conducted a cross-sectional study in four rural regions of Hunan province. Plasma and urine metals levels were determined by inductively coupled plasma mass spectrometer (ICP-MS). Two-level logistic regression was used to investigate the associations of metals levels with estimated glomerular filtration rate (eGFR) with adjustment for confounding factors. We conducted a sensitivity analysis of the results using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. A total of 3553 participants completed the investigation. Five metals (plasma arsenic and molybdenum; urine copper, rubidium, and strontium) were identified to be significantly associated with renal function. Participants in the highest quartile of plasma arsenic and molybdenum were at 17.95 (95% CI: 6.35–50.76) and 24.23 (95% CI: 7.42–79.19) fold risk of abnormal eGFR, respectively, compared with the lowest quartile. The highest quartiles of urine copper, rubidium, and strontium were associated with 3.70 (95% CI:1.92–7.14), 0.16 (95% CI:0.07–0.37) and 0.08 (95% CI: 0.03–0.21) fold risk of abnormal eGFR. The sensitivity analysis revealed that plasma arsenic, molybdenum and urine copper, rubidium and strontium levels retained similar associations with abnormal eGFR. Plasma arsenic and molybdenum, and urine copper are risk factors for abnormal renal function, while urine rubidium and strontium are protective factors for renal function. • A cross-sectional study was conducted in four rural regions of Hunan province. • The associations of multiple metal levels with renal function was investigated. • Multiple metals in plasma and urine are associated with abnormal eGFR. [ABSTRACT FROM AUTHOR]

• The RSDI is suitable for monitoring aeolian desertification. • The areas with significant restoration (34.1%) exceeded those with significant deterioration (6%) in the NSPB. • In the areas with significant restoration, 57.4% of the land was mainly affected by human activities. The northern sand-prevention belt (NSPB) is the key area for sand control in China, and the various ecological projects conducted there are important to the Chinese strategy for ecological security. In this paper, a new remote sensing-based desertification index (RSDI) based on principal component analysis was constructed from four aspects of vegetation greenness, surface moisture, soil grain size, and surface radiation. The overall evaluation accuracy of the index was 89.2%, and the kappa coefficient was 0.80, indicating high sensitivity to different degrees of aeolian desertification and suitability for multiscale research. The coefficient of variation, Mann–Kendall test, Theil–Sen median trend analysis, and residual analysis were used to analyze the spatiotemporal changes and driving forces of the RSDI in the NSPB from 2000 to 2020. The RSDI was used to compare aeolian desertification in different subregions, land use types, and ecological project areas. The important results are as follows: (1) the trend of the average RSDI was downward, but it increased significantly in 2008–2009 and 2013–2014; (2) the RSDI was characterized by relatively high volatility in 28.9% and moderate volatility in 27.1% of the area; (3) the areas with significant restoration (34.1%) greatly exceeded those with significant deterioration (6%), whereas 59.9% of the total area was stable; and (4) within the area with significant restoration, 57.4% was primarily affected by human activities, and 42.4% was primarily affected by climate change; however, most of the area with significant deterioration (71.1%) was affected by human activities. In general, the degree of aeolian desertification in the NSPB has decreased in the past 20 years and its ecological quality has continued to recover. However, unreasonable human activities still need to be reduced, and the ecological management of areas under serious threat of desertification needs to be strengthened. [ABSTRACT FROM AUTHOR]

[Display omitted] • A selection strategy for base-period images of spatio-temporal fusion was proposed. • The spatio-temporal inconsistency between field samples and images was reduced. • The estimation accuracy of grassland aboveground biomass was improved. The accurate estimation of the aboveground biomass (AGB) is crucial for the sustainable utilization and management of grassland resources. Spatio-temporal inconsistencies between field samples and satellite images are major source of error in the estimation of grassland AGB. To solve this problem, this study selected the Three Rivers Headwater Region as the study area and proposed a selection strategy for base-period images of spatio-temporal fusion that was suitable for use at a large spatial scale in which cloud-free images are difficult to obtain. The spatial and temporal adaptive reflectance fusion model (STARFM) based on the selection strategy was used to generate a synthetic Normalized Difference Vegetation Index (NDVI) dataset with high spatial-temporal resolution by using the maximum value composite of GF-1 NDVI and MODIS NDVI to enhance the spatial-temporal quality of the images for field-scale application. Three estimation models for grassland AGB were then constructed by the random forest algorithm using synthetic NDVI, MODIS NDVI, GF-1 NDVI respectively, together with ancillary data. Following this, the estimation model with the highest accuracy was used to generate a 16-m eight-day time-series AGB in the growing season. The results showed: (1) The synthetic NDVI was correlated closely with the observed GF-1 NDVI, with an average R of 0.825 and a RMSE of 0.087. The temporal trend of the synthetic NDVI for each grassland type was highly consistent with that of the MODIS NDVI in the growing season with a correlation higher than 0.9. (2) The synthetic NDVI reduced the spatial difference between field samples and images to 16-fold, and the temporal difference was controlled to within four days under ideal conditions. (3) The synthetic NDVI improved the estimation accuracy of grassland AGB by about 15.9% and 19.7% (R2), and 13.7% and 17.5% (RMSE) relative to MODIS NDVI and GF-1 NDVI, respectively. (4) The time-series AGB revealed accurately the spatial distribution of and seasonal temporal variations in the grassland biomass. The results of this study may serve as scientific guidance for timely monitoring of grassland conditions and precise management of grassland resources in China. [ABSTRACT FROM AUTHOR]

• Annual PM 2.5 constituent exposure was associated with abnormal ECG outcomes. • Per IQR increase of sulfate related to a 26% increased risk of ECG abnormalities. • Differential toxicity of PM 2.5 constituents on ECG may inform policy making. Electrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM 2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM 2.5 constituents and changes in ECG diagnoses. We designed a longitudinal study among participants with repeated records of ECG examination based on the China National Stroke Screening Survey 2013–2018. Logistic regressions with multiple adjustment, estimated by the generalized estimating equation to incorporate repeated measurements, were used to assess the associations between the occurrence of any physician-diagnosed ECG abnormalities and long-term exposure to PM 2.5 constituents. We included 61,094 participants with 132,249 visits. All five constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) were significantly associated with an increased risk of ECG abnormalities. The excess risk of ECG abnormalities per interquartile-range increase in exposure was the highest for sulfate (26%, 95% confidence interval [CI] 23–29%), followed by ammonium (22%, 19–26%), nitrate (21%, 17–24%), black carbon (16%, 13–10%) and organic matter (9%,6%-11%). We also found that atrial fibrillation patients might be susceptible to the adverse effects of PM 2.5 constituents on ECG. Differential associations between various constituents of PM 2.5 and ECG abnormalities were found. The unequal toxicities for different chemical constituents of ambient particles on cardiovascular electrophysiological endpoints should be taken into consideration when considering the biological pathways linking PM 2.5 and cardiovascular conditions. [ABSTRACT FROM AUTHOR]

Landslide modeling based on seismic signal characteristics is an effective method to study landslide evolution. The scientific challenge lies in how to systematically characterize and reconstruct the entire landslide evolution process using the recorded seismic data. We selected the 2017 "6.24" Xinmo landslide as a case study. Empirical mode decomposition (EMD) is used to analyze the seismic signals from 14 seismic stations near the landslide area. Numerical simulations using two-dimensional discrete element methods (DEM) are performed to simulate landslide dynamics using the calculated kinetic energy profile. After analyzing the short-time Fourier transform (STFT) and fast Fourier transform (FFT) characteristics of the signal, the landslide process is reconstructed and compared with the DEM simulation. The landslide process is observed to consist of a stationary stage, slipping stage, transition stage, entrainment-transportation stage, and a deposition stage. This is the first study that uses seismic signals to identify a transition stage, which is a feature that is difficult to constrain from field survey and analysis alone. Landslide development and movement in the transition stage are discussed considering the sedimentology of the study area. This study provides improved theoretical guidance for the reconstruction and characterization of landslide processes by seismic signals. • Seismic signals generated by the Xinmo landslide (Sichuan - China) were analyzed. • 5 stages of landslide were recognized from spectral variations of seismic recording. • One transition stage was identified between first slipping and entrainment stage. • Discrete element simulations supported the landslide process reconstruction. [ABSTRACT FROM AUTHOR]

Traversing the Qinghai–Tibetan Plateau, the Sichuan–Tibet Railway is by far the most difficult railway project in the world. The Qinghai–Tibetan Plateau features the most active crustal dynamics on earth, the strongest coupling effects of endogenic and exogenic dynamics, and the environment most sensitive to global climate change. The project area is characterized by extremely cold climate, high elevation and relief, high seismic intensity, high geothermal activity, and high tectonic stress. Consequently, the threat of various disaster risks is ever-present at different stages of the entire life cycle of the Sichuan–Tibet Railway. There is urgent need to systematically study these problems at various levels from the fundamental science to the development of key technologies. This article investigates the different disaster risks recognized during the various stages of construction of the Sichuan–Tibet Railway project, and summarizes the scientific challenges and technical problems faced in relation to disaster risk prevention and control. This work also introduces the scientific deployment and relevant research progress of the Sichuan–Tibet Fund special project initiated by the National Natural Science Foundation of China. Here, we also aim to solve the major fundamental scientific challenges in terms of long-term risk prevention and control during the construction of the Sichuan–Tibet Railway, and lay a theoretical foundation to promote breakthroughs in the bottleneck of key technologies. The scientific challenges addressed in the study of disaster risk associated with the Sichuan–Tibet Railway include the following: The quantitative assessment of the activity of deep-large faults and strong earthquake prediction, the evolution of physical fields in areas of strong tectonic activity, the development mechanisms of tunnel hazards, the slope evolution processes under coupled endogenic and exogenic dynamics in alpine gorges, the impact of climate change on the formation and evolution of surface hazards, and the evolution of extreme wind fields in deep-cut canyons. The technical problems faced in disaster risk prevention and mitigation in relation to the Sichuan–Tibet Railway are as follows: Advanced identification, monitoring, and early warning of geological disasters in mountainous areas with steep and complex terrain; risk analysis, prevention, and control of railway engineering disasters based on their dynamic processes; tunnel engineering hazard monitoring, early warning, risk analysis, prevention, and control technologies; key technologies for emergency response; and the green and resilient railway system and lifecycle risk management. The Sichuan–Tibet Fund special project will include five key research topics: (1) the interior geological structure and dynamic evolution of the eastern plateau; (2) the hazard-inducing mechanisms of coupled internal and external forces in canyons and gullies within plateaus; (3) the cataclysm mechanics of deeply buried long-distance tunnel engineering; (4) risk identification and projection of major disasters affecting the railway; and (5) the integrated management of scientific innovations and super large-scale railway construction. Systematic research is expected to reveal the evolution of earth surface movements and coupled engineering-disturbance related disasters. It will also enable the formation of a comprehensive risk analysis method for major engineering disasters, and promote the development of green, safe, efficient, and resilient engineering disaster risk reduction technologies that will support the disaster risk management during the entire lifecycle of the Sichuan–Tibet Railway. • Investigated the natural and anthropic disaster risks in different construction stages of the Sichuan–Tibet Railway. • Identified the scientific challenges and technical gaps faced in disaster risk reduction of the Sichuan–Tibet Railway. • Proposed fundamental research and technologies development directions for a safe and resilient Sichuan–Tibet Railway. [ABSTRACT FROM AUTHOR]

Urban spatial structure has important impact on environmental pollutant emissions, but few studies have investigated the possibility of a bidirectional influence mechanism between the two. This study used panel data of 108 prefecture-level cities in the Yangtze River Economic Belt (China) from 2009 to 2018. The objective was to test empirically the dynamic emission reduction effect of polycentric spatial structure on environmental pollution using the STIRPAT model as a framework to decipher the bidirectional causality effect. System generalized method of moments and the Sobel Test were applied to construct a panel intermediary effect model to verify the mechanism of urban polycentric development mode on urban haze pollution in China. Results showed that the urban polycentric structure in the Yangtze River Economic Belt has produced substantial pollution reduction effects, and that there are heterogenous regional, size, and functional differences in the impact of urban spatial structure of the Yangtze River Economic Belt on the environment. Moreover, the results of the intermediary effect test showed that market integration and industrial structure optimization are important ways via which to improve environmental pollutant emissions using the polycentric spatial development model. On this basis, suggestions were proposed for optimizing urban spatial structure to promote high-quality development of the Yangtze River Economic Belt. [Display omitted] • Urban polycentric spatial structure has a dynamic abatement effect on environmental pollution. • There are heterogeneous regional, size, and functional differences in the influence mechanism. • Market integration and industrial structure optimization play an intermediary role. • Two intermediary variables can more effectively release the positive externality of polycentric spatial structure. • Cities should strengthen polycentric spatial structure to reduce PM 2.5 pollution. [ABSTRACT FROM AUTHOR]

Abstract: Tap water, aerobically pre-treated leachate, and anaerobically pre-treated leachate, were each fed into the top of a series of three simulated landfills columns, filled with municipal solid waste collected in Shanghai, China. Changes in leachate, including pH, total organic carbon (TOC), and volatile fatty acids (VFAs), and the produced biogas were monitored over time. The tap-water-fed columns had a low hydrolysis rate that yielded an acidic environment (pH 4.8–5.4) in the leachate that inhibited methanogenesis reaction in the refuse. When aerobically pre-treated leachate was fed into the columns, the hydrolysis rate of total organic carbon fluctuated between 200 and 400mgd−1 and methanogenesis in the refuse column was only partly activated. The hydrolysis rate of refuse fed with anaerobically pre-treated leachate was the highest among the three solutions. The high alkaline levels of the anaerobically pre-treated leachate and its methanogenic bacteria led to an early activation of methanogenesis in the refuse columns. The VFAs contributed approximately 40–60% of TOC in tap-water-fed columns, 60–80% of TOC in the columns fed aerobically pre-treated leachate, and up to 70–90% of TOC in columns fed with anaerobically pre-treated leachate. The feed solution had considerably affected leachate characteristics, and then the build-up of the methanogenesis in the refuse column and the composition of fermentation products in the leachate. The success of a bioreactor landfill depends on whether the recycled leachate could yield a favorable methanogenic environment in the top refuse layer, or whether an appropriate pre-treatment is adopted to modify the leachate characteristics. [Copyright &y& Elsevier]

Many flow-like landslides entrain material from their paths during motion. At the flow front and along the lateral margins the sliding mass can plow into the path material pushing or entraining the existing soil. Although plowing can be a dominant mechanism for landslide mobility, little attention has been paid to this phenomenon in comparison with other entraining mechanism such as basal scouring. Therefore, establishing a suitable mathematical description is still a challenge. In this paper, a two-layer finite difference model is proposed to simulate frontal plowing. The frontal erodible mass and the sliding mass are simplified as two separate layers based on the assumption that they are immiscible in their propagation processes. The interaction (i.e., thrusting and shear) between the two layers is simulated by the normal force and shear force acting on the two-layer interface. The governing equations for the two-layer model are deduced from the mass and momentum conservations of a soil column and transformed into a finite difference form for numerical solving. Then the proposed model is tested in the back analysis of the Ximiaodian landslide which is a typical loess flow-like landslide located at the south bank of the Jing River, China. The modeling results show that frontal plowing has significant influence on the propagation of this landslide, especially on the final topography of the deposit. Without considering this effect, the thickness of the final deposit tends to be underestimated, while the propagation duration, area and distance are likely to be overestimated. The proposed model can provide more accurate and reliable simulations for rapid flow-like landslides with frontal plowing phenomenon. • A mathematical model was proposed for depicting frontal plowing in flow-like landslides. • The run-out and frontal plowing processes of the Ximiaodian landslide were analyzed by the model. • Frontal plowing impeded the motion of this landslide, but it also caused the rapid lateral spreading of the terrace. • The modeling results indicate that the proposed model performs well in simulating frontal plowing. [ABSTRACT FROM AUTHOR]