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Frontiers of Earth Science

, Volume 11 Issue 1

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Global consistency check of AIRS and IASI total CO2 column concentrations using WDCGG ground-based measurements
Anyuan DIAO,Jiong SHU,Ci SONG,Wei GAO
Front. Earth Sci.. 2017, 11 (1): 1-10.
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This article describes a global consistency check of CO2 satellite retrieval products from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) using statistical analysis and data from the World Data Centre for Greenhouse Gases (WDCGG). We use the correlation coefficient (r), relative difference (RD), root mean square errors (RMSE), and mean bias error (MBE) as evaluation indicators for this study. Statistical results show that a linear positive correlation between AIRS/IASI and WDCGG data occurs for most regions around the world. Temporal and spatial variations of these statistical quantities reflect obvious differences between satellite-derived and ground-based data based on geographic position, especially for stations near areas of intense human activities in the Northern Hemisphere. It is noteworthy that there appears to be a very weak correlation between AIRS/IASI data and ten ground-based observation stations in Europe, Asia, and North America. These results indicate that retrieval products from the two satellite-based instruments studied should be used with great caution.

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Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data
Menglong YAN,Thomas BLASCHKE,Hongzhao TANG,Chenchao XIAO,Xian SUN,Daobing ZHANG,Kun FU
Front. Earth Sci.. 2017, 11 (1): 11-19.
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Airborne laser scanning (ALS) is a technique used to obtain Digital Surface Models (DSM) and Digital Terrain Models (DTM) efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object-based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing (ESRGG) algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.

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Land surface temperature retrieval from Landsat 8 data and validation with geosensor network
Kun TAN,Zhihong LIAO,Peijun DU,Lixin WU
Front. Earth Sci.. 2017, 11 (1): 20-34.
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A method for the retrieval of land surface temperature (LST) from the two thermal bands of Landsat 8 data is proposed in this paper. The emissivities of vegetation, bare land, buildings, and water are estimated using different features of the wavelength ranges and spectral response functions. Based on the Planck function of the Thermal Infrared Sensor (TIRS) band 10 and band 11, the radiative transfer equation is rebuilt and the LST is obtained using the modified emissivity parameters. A sensitivity analysis for the LST retrieval is also conducted. The LST was retrieved from Landsat 8 data for the city of Zoucheng, Shandong Province, China, using the proposed algorithm, and the LST reference data were obtained at the same time from a geosensor network (GSN). A comparative analysis was conducted between the retrieved LST and the reference data from the GSN. The results showed that water had a higher LST error than the other land-cover types, of less than 1.2°C, and the LST errors for buildings and vegetation were less than 0.75°C. The difference between the retrieved LST and reference data was about 1°C on a clear day. These results confirm that the proposed algorithm is effective for the retrieval of LST from the Landsat 8 thermal bands, and a GSN is an effective way to validate and improve the performance of LST retrieval.

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Numerical research on evolvement of submarine sand waves in the Northern South China Sea
Qikun ZHOU,Guanghai HU,Yongfu SUN,Xiaohui LIU,Yupeng SONG,Lifeng DONG,Changming DONG
Front. Earth Sci.. 2017, 11 (1): 35-45.
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Submarine sand waves, vital to seabed stability, are an important consideration for oceanic engineering projects such as oil pipe lines and submarine cables. The properties of surface sediment and the evolvement of submarine sand waves in a specified area in the South China Sea are studied using both a hydrological model and field observational data. The bottom flow field data between 2010 and 2011 in the study area are simulated by the Regional Ocean Model System (ROMS). The migration of submarine sand waves is calculated using Rubin’s formula along with typhoon data and bottom flow field data, which allows for the analysis of sand wave response under the influence of typhoons. The migration direction calculated by Rubin’s formula and bottom flow are very similar to collected data. The migration distance of different positions is between 0.0 m and 21.8 m, which reciprocates cumulatively. This shows that Rubin’s formula can predict the progress of submarine sand waves with the bottom flow simulated by ROMS. The migration distances of 2 sites in the study area are 2.0 m and 2.9 m during the typhoon “Fanapi”. The proportion of the calculated migration distance by the typhoon is 9.17% and 26.36% of the annual migration distance, respectively, which proves that the typhoon can make a significant impact on submarine sand waves.

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Emissions inventory and scenario analyses of air pollutants in Guangdong Province, China
Front. Earth Sci.. 2017, 11 (1): 46-62.
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Air pollution, causing significantly adverse health impacts and severe environmental problems, has raised great concerns in China in the past few decades. Guangdong Province faces major challenges to address the regional air pollution problem due to the lack of an emissions inventory. To fill this gap, an emissions inventory of primary fine particles (PM2.5) is compiled for the year 2012, and the key precursors (sulfur dioxide, nitrogen oxides) are identified. Furthermore, policy packages are simulated during the period of 2012–2030 to investigate the potential mitigation effect. The results show that in 2012, SO2, NOx, and PM2.5 emissions in Guangdong Province were as high as (951.7, 1363.6, and 294.9) kt, respectively. Industrial production processes are the largest source of SO2 and PM2.5 emissions, and transport is the top contributor of NOx emissions. Both the baseline scenario and policy scenario are constructed based on projected energy growth and policy designs. Under the baseline scenario, SO2, NOx, and PM2.5 emissions will almost double in 2030 without proper emissions control policies. The suggested policies are categorized into end-of-pipe control in power plants (ECP), end-of-pipe control in industrial processes (ECI), fuel improvement (FI), energy efficiency improvement (EEI), substitution-pattern development (SPD), and energy saving options (ESO). With the implementation of all these policies, SO2, NOx, and PM2.5 emissions are projected to drop to (303.1, 585.4, and 102.4) kt, respectively, in 2030. This inventory and simulated results will provide deeper insights for policy makers to understand the present situation and the evolution of key emissions in Guangdong Province.

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Investigation of the spatiotemporal variation and influencing factors on fine particulate matter and carbon monoxide concentrations near a road intersection
Zhanyong WANG,Qing-Chang LU,Hong-Di HE,Dongsheng WANG,Ya GAO,Zhong-Ren PENG
Front. Earth Sci.. 2017, 11 (1): 63-75.
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The minute-scale variations of fine particulate matter (PM2.5) and carbon monoxide (CO) concentrations near a road intersection in Shanghai, China were investigated to identify the influencing factors at three traffic periods. Measurement results demonstrate a synchronous variation of pollutant concentrations at the roadside and setbacks, and the average concentration of PM2.5 at the roadside is 7% (44% for CO) higher than that of setbacks within 500 m of the intersection. The pollution level at traffic peak periods is found to be higher than that of off-peak periods, and the morning peak period is found to be the most polluted due to a large amount of diesel vehicles and unfavorable dispersion conditions. Partial least square regressions were constructed for influencing factors and setback pollutant concentrations, and results indicate that meteorological factors are the most significant, followed by setback distance from the intersection and traffic factors. CO is found to be sensitive to distance from the traffic source and vehicle type, and highly dependent on local traffic conditions, whereas PM2.5 originates more from other sources and background levels. These findings demonstrate the importance of localized factors in understanding spatiotemporal patterns of air pollution at intersections, and support decision makers in roadside pollution management and control.

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Investigating the spectral characteristic and humification degree of dissolved organic matter in saline-alkali soil using spectroscopic techniques
Qiang LI,Xujing GUO,Lu CHEN,Yunzhen LI,Donghai YUAN,Benlin DAI,Sisi WANG
Front. Earth Sci.. 2017, 11 (1): 76-84.
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Soil samples were collected from the areas surrounding Wuliangsuhai Lake in China. Dissolved organic matter (DOM) was extracted from the samples and characterized by fluorescence and UV-Vis spectra. Spectral properties and humification degree of DOM were studied. The results indicated that both humic- and protein-like fluorophores were present in the DOM spectra, and the former was the dominant component. The analysis of humification (HIX) and r (A, C) indices revealed that the maximum humification degree in three agricultural soils (AAF, ASC, and ASW) was presented in the second soil layer (20–40 cm). However, the humification degree of the two Halophytes soils (SSE and GKF) decreased with increasing depth. One index, I344/270, showed that humification degree increased gradually with an increasing proportion of humic-like acid. There was a significant positive correlation between humification degree (HIX) and aromaticity (SUVA254), indicating that a higher aromaticity corresponded to a higher humification degree. Land use was an important factor responsible for the major difference of cation exchange capacity (CEC) in different soils, which led to a higher CEC value in the second soil layer for the three agricultural soils. CEC values and humification degree had the same trend for all five soils. The correlation analysis showed that there was a significant positive correlation between HIX and CEC, and a negative correlation between the r (A, C) index and CEC, indicating that humification degree increases gradually with increasing CEC values.

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Assessment of heavy metal levels in surface sediments of estuaries and adjacent coastal areas in China
Xianbin LIU,Deliang LI,Guisheng SONG
Front. Earth Sci.. 2017, 11 (1): 85-94.
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This article investigates the variations of contamination levels of heavy metals such as copper, lead, chromium, cadmium, zinc, arsenic, and mercury over time in surface sediments of the Changjiang River Estuary (CRE), Yellow River Estuary (YRE), Pearl River Estuary (PRE), and their adjacent coastal areas in China. The contamination factor (CF), pollution load index (PLI), and geoaccumulation index (Igeo) are used to evaluate the quality of the surface sediments in the study areas. The results showed that the CRE, YRE, and their adjacent coastal areas were at a low risk of contamination in terms of heavy metals, while the PRE and its adjacent coastal area were at a moderate level. By comparison, the concentrations of heavy metals in the surface sediments of the YRE and its adjacent coastal area were relatively lower than those in the CRE, PRE, and their adjacent coastal areas.

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Projected hydrologic regime changes in the Poyang Lake Basin due to climate change
Le Wang,Shenglian Guo,Xingjun Hong,Dedi Liu,Lihua Xiong
Front. Earth Sci.. 2017, 11 (1): 95-113.
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Poyang Lake, the largest freshwater lake in China, and its surrounding sub-basins have suffered frequent floods and droughts in recent decades. To better understand and quantitatively assess hydrological impacts of climate change in the region, this study adopted the Statistical Downscaling Model (SDSM) to downscale the outputs of a Global Climate Model (GCM) under three scenarios (RCP2.6, RCP4.5 and RCP8.5) as recommended by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) during future periods (2010–2099) in the Poyang Lake Basin. A semi-distributed two-parameter monthly water balance model was also used to simulate and predict projected changes of runoff in the Ganjiang sub-basin. Results indicate that: 1) SDSM can simulate monthly mean precipitation reasonably well, while a bias correction procedure should be applied to downscaled extreme precipitation indices (EPI) before being employed to simulate future precipitation; 2) for annual mean precipitation, a mixed pattern of positive or negative changes are detected in the entire basin, with a slightly higher or lower trend in the 2020s and 2050s, with a consistent increase in the 2080s; 3) all six EPI show a general increase under RCP4.5 and RCP8.5 scenarios, while a mixed pattern of positive and negative changes is detected for most indices under the RCP2.6 scenario; and 4) the future runoff in the Ganjiang sub-basin shows an overall decreasing trend for all periods but the 2080s under the RCP8.5 scenario when runoff is more sensitive to changes in precipitation than evaporation.

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Spatial assessment of water quality using chemometrics in the Pearl River Estuary, China
Meilin WU,Youshao WANG,Junde DONG,Fulin SUN,Yutu WANG,Yiguo HONG
Front. Earth Sci.. 2017, 11 (1): 114-126.
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A cruise was commissioned in the summer of 2009 to evaluate water quality in the Pearl River Estuary (PRE). Chemometrics such as Principal Component Analysis (PCA), Cluster analysis (CA) and Self-Organizing Map (SOM) were employed to identify anthropogenic and natural influences on estuary water quality. The scores of stations in the surface layer in the first principal component (PC1) were related to NH4-N, PO4-P, NO2-N, NO3-N, TP, and Chlorophyll a while salinity, turbidity, and SiO3-Si in the second principal component (PC2). Similarly, the scores of stations in the bottom layers in PC1 were related to PO4-P, NO2-N, NO3-N, and TP, while salinity, Chlorophyll a, NH4-N, and SiO3-Si in PC2. Results of the PCA identified the spatial distribution of the surface and bottom water quality, namely the Guangzhou urban reach, Middle reach, and Lower reach of the estuary. Both cluster analysis and PCA produced the similar results. Self-organizing map delineated the Guangzhou urban reach of the Pearl River that was mainly influenced by human activities. The middle and lower reaches of the PRE were mainly influenced by the waters in the South China Sea. The information extracted by PCA, CA, and SOM would be very useful to regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions.

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The spatial distribution of threats to plant species with extremely small populations
Chunjing WANG, Jing ZHANG, Jizhong WAN, Hong QU, Xianyun MU, Zhixiang ZHANG
Front. Earth Sci.. 2017, 11 (1): 127-136.
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Many biological conservationists take actions to conserve plant species with extremely small populations (PSESP) in China; however, there have been few studies on the spatial distribution of threats to PSESP. Hence, we selected distribution data of PSESP and made a map of the spatial distribution of threats to PSESP in China. First, we used the weight assignment method to evaluate the threat risk to PSESP at both country and county scales. Second, we used a geographic information system to map the spatial distribution of threats to PSESP, and explored the threat factors based on linear regression analysis. Finally, we suggested some effective conservation options. We found that the PSESP with high values of protection, such as the plants with high scientific research values and ornamental plants, were threatened by over-exploitation and utilization, habitat fragmentation, and a small sized wild population in broad-leaved forests and bush fallows. We also identified some risk hotspots for PSESP in China. Regions with low elevation should be given priority for ex- and in-situ conservation. Moreover, climate change should be considered for conservation of PSESP. To avoid intensive over-exploitation or utilization and habitat fragmentation, in-situ conservation should be practiced in regions with high temperatures and low temperature seasonality, particularly in the high risk hotspots for PSESP that we proposed. Ex-situ conservation should be applied in these same regions, and over-exploitation and utilization of natural resources should be prevented. It is our goal to apply the concept of PSESP to the global scale in the future.

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Spatial and temporal variations in prehistoric human settlement and their influencing factors on the south bank of the Xar Moron River, Northeastern China
Xin JIA,Shuangwen YI,Yonggang SUN,Shuangye WU,Harry F. LEE,Lin WANG,Huayu LU
Front. Earth Sci.. 2017, 11 (1): 137-147.
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The West Liao River Basin is the hub of ancient civilizations as well as the birthplace of rain-fed agriculture in Northern China. In the present study, based on 276 archaeological sites on the south bank of the Xar Moron River, Northeastern China, we trace the changes in prehistoric cultures as well as the shifts in the spatial and temporal patterns of human settlement in the West Liao River Basin. Location information for those sites was obtained from fieldwork. Factors such as climate change, landform evolution of the Horqin Dunefield, and subsistence strategies practiced at the sites were extracted via the meta-analysis of published literature. Our results show that the Holocene Optimum promoted the emergence of Neolithic Culture on the south bank of the Xar Moron River. Monsoon failure might have caused the periodic collapse or transformation of prehistoric cultures at (6.5, 4.7, 3.9, and 3.0) kyr B.P., leaving spaces for new cultural types to develop after these gaps. The rise and fall of different cultures was also determined by subsistence strategies. The Xiaoheyan Culture, with mixed modes of subsistence, weakened after 4.7 kyr B.P., whereas the Upper Xiajiadian Culture, supported by sheep breeding, expanded after 3.0 kyr B.P. Global positioning system data obtained from the archaeological sites reveal that cultures with different subsistence strategies occupied distinct geographic regions. Humans who subsisted on hunting and gathering resided at higher altitudes during the Paleolithic Age (1074 m a.s.l.). Mixed subsistence strategies led humans to settle down at 600–1000 m a.s.l. in the Neolithic Age. Agricultural activities caused humans to migrate to 400–800 m a.s.l. in the early Bronze Age, whereas livestock production shifted human activities to 800–1200 m a.s.l. in the late Bronze Age.

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Impact of thermal time shift on wheat phenology and yield under warming climate in the Huang-Huai-Hai Plain, China
Dengpan XIAO,Yongqing QI,Zhiqiang LI,Rende WANG,Juana P. MOIWO,Fengshan LIU
Front. Earth Sci.. 2017, 11 (1): 148-155.
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Given climate change can potentially influence crop phenology and subsequent yield, an investigation of relevant adaptation measures could increase the understanding and mitigation of these responses in the future. In this study, field observations at 10 stations in the Huang-Huai-Hai Plain of China (HHHP) are used in combination with the Agricultural Production Systems Simulator (APSIM)–Wheat model to determine the effect of thermal time shift on the phenology and potential yield of wheat from 1981–2009. Warming climate speeds up winter wheat development and thereby decreases the duration of the wheat growth period. However, APSIM–Wheat model simulation suggests prolongation of the period from flowering to maturity (Gr) of winter wheat by 0.2–0.8 d·10yr−1 as the number of days by which maturity advances, which is less than that by which flowering advances. Based on computed thermal time of the two critical growth phases of wheat, total thermal time from floral initiation to flowering (TT_floral_initiation) increasesd in seven out of the 10 investigated stations. Alternatively, total thermal time from the start of grain-filling to maturity (TT_start_ grain_fill) increased in all investigated stations, except Laiyang. It is thus concluded that thermal time shift during the past three decades (1981–2009) prolongs Gr by 0.2–3.0 d·10yr−1 in the study area. This suggests that an increase in thermal time (TT) of the wheat growth period is critical for mitigating the effect of growth period reduction due to warming climatic condition. Furthermore, climate change reduces potential yield of winter wheat in 80% of the stations by 2.3–58.8 kg·yr−1. However, thermal time shift (TTS) increases potential yield of winter wheat in most of the stations by 3.0–51.0 kg·yr−1. It is concluded that wheat cultivars with longer growth periods and higher thermal requirements could mitigate the negative effects of warming climate on crop production in the study area.

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Driving factors of carbon dioxide emissions in China: an empirical study using 2006--2010 provincial data
Yu LIU,Zhan-Ming CHEN,Hongwei XIAO,Wei YANG,Danhe LIU,Bin CHEN
Front. Earth Sci.. 2017, 11 (1): 156-161.
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The rapid urbanization of China has increased pressure on its environmental and ecological well being. In this study, the temporal and spatial profiles of China’s carbon dioxide emissions are analyzed by taking heterogeneities into account based on an integration of the extended stochastic impacts using a geographically and temporally weighted regression model on population, affluence, and technology. Population size, urbanization rate, GDP per capita, energy intensity, industrial structure, energy consumption pattern, energy prices, and economy openness are identified as the key driving factors of regional carbon dioxide emissions and examined through the empirical data for 30 provinces during 2006–2010. The results show the driving factors and their spillover effects have distinct spatial and temporal heterogeneities. Most of the estimated time and space coefficients are consistent with expectation. According to the results of this study, the heterogeneous spatial and temporal effects should be taken into account when designing policies to achieve the goals of carbon dioxide emissions reduction in different regions.

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Regional study on investment for transmission infrastructure in China based on the State Grid data
Wendong WEI, Xudong WU, Xiaofang WU, Qiangmin XI, Xi JI, Guoping LI
Front. Earth Sci.. 2017, 11 (1): 162-183.
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Transmission infrastructure is an integral component of safeguarding the stability of electricity delivery. However, existing studies of transmission infrastructure mostly rely on a simple review of the network, while the analysis of investments remains rudimentary. This study conducted the first regionally focused analysis of investments in transmission infrastructure in China to help optimize its structure and reduce investment costs. Using State Grid data, the investment costs, under various voltages, for transmission lines and transformer substations are calculated. By analyzing the regional profile of cumulative investment in transmission infrastructure, we assess correlations between investment, population, and economic development across the regions. The recent development of ultra-high-voltage transmission networks will provide policy-makers new options for policy development.

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Shale gas reservoir characteristics of Ordovician-Silurian formations in the central Yangtze area, China
Chang’an SHAN,Tingshan ZHANG,Yong WEI,Zhao ZHANG
Front. Earth Sci.. 2017, 11 (1): 184-201.
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The characteristics of a shale gas reservoir and the potential of a shale gas resource of Ordovician–Silurian age in the north of the central Yangtze area were determined. Core samples from three wells in the study area were subjected to thin-section examination, scanning electron microscopy, nuclear magnetic resonance testing, X-ray diffraction mineral analysis, total organic carbon (TOC) testing, maturity testing, gas-bearing analysis, and gas component and isothermal adsorption experiments. A favorable segment of the gas shale reservoir was found in both the Wufeng Formation and the lower part of the Longmaxi Formation; these formations were formed from the late Katian to early Rhuddanian. The high–quality shale layers in wells J1, J2, and J3 featured thicknesses of 54.88 m, 48.49 m, and 52.00 m, respectively, and mainly comprised carbonaceous and siliceous shales. Clay and brittle minerals showed average contents of 37.5% and 62.5% (48.9% quartz), respectively. The shale exhibited type II1 kerogens with a vitrinite reflectance ranging from 1.94% to 3.51%. TOC contents of 0.22%–6.05% (average, 2.39%) were also observed. The reservoir spaces mainly included micropores and microfractures and were characterized by low porosity and permeability. Well J3 showed generally high gas contents, i.e., 1.12–3.16 m3/t (average 2.15 m3/t), and its gas was primarily methane. The relatively thick black shale reservoir featured high TOC content, high organic material maturity, high brittle mineral content, high gas content, low porosity, and low permeability. Shale gas adsorption was positively correlated with TOC content and organic maturity, weakly positive correlated with quartz content, and weakly negatively correlated with clay content. Therefore, the Wufeng and Longmaxi formations in the north of the central Yangtze area have a good potential for shale gas exploration.

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Erratum to: Newmark displacement model for landslides induced by the 2013 Ms 7.0 Lushan earthquake, China
Renmao YUAN,Qinghai DENG,Dickson CUNNINGHAM,Zhujun HAN,Dongli ZHANG,Bingliang ZHANG
Front. Earth Sci.. 2017, 11 (1): 202-202.
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17 articles