Gas geochemistry and their associated isotope systematics are developing into powerful tools to understand geological/environmental processes and affirm source origins of geo-fluids. In addition to the traditional noble gas indicators, such as He and Ar, other major and trace gases, including CO2, N2, H2, CH4, CO, Ne, Kr and Xe – abundances and isotopes - have shown considerable application in many fields of the Earth and Environmental Sciences. For example, key constraints on geochemical processes including the degassing history of the solid Earth to form the atmosphere and oceans, the origin and migration characteristics of natural gas, the scale of climate variability, the P-T characteristics of both subaerial and deep water geothermal reservoirs, and the dynamics of the earthquake cycle, are only a few areas where gas geochemistry has been successfully exploited. Following the ‘Frontiers in Gas Geochemistry’ Special Issue in this journal (2013), this volume will reflect this diversity in scope and application of gas geochemistry, focusing on geothermal, tectonic and magmatic studies amenable to the gas geochemistry approach.

For better understanding compositions and evolutions of residual oil of shale and coal, a grain-based microscale sealed vessel (MSSV) pyrolysis method to whole rock was used to investigate the residual oil contents and its fractional compositions from shale, coal, and coaly shale samples, as well as their variations at different temperatures and maturities. Quantities of extracted oil from residuals and yields of C1 to C5 gases were used to define oil, wet gas, and dry gas windows using equivalent Ro (%) calculated through EasyRo (%) method. Oil windows are defined as 0.6–1.3%Ro for shale and 0.5–1.2%Ro for coal; wet gas windows are 0.9–3.0%Ro for shale and 0.8–2.7%Ro for coal, and dry gas window are 1.3–4.0%Ro for shale and 1.2–4.0%Ro for coal, respectively. Coal shows relatively wider oil window than shale but similar gas window to shale. The maximum residual oil can reach 133.44 mg/g TOC, 69.84 mg/g TOC for marine and lacustrine shale, 10.03 mg/g TOC for coal, and 83.79 mg/g TOC for coaly shale, respectively. Comparing with natural residual oil, the laboratory residual oil of shale is much higher, while the residual oil in coal is mainly retained due to its unique structures. The results show that, in oil window, marine and lacustrine shale residual oil show mainly saturates, aromatics, resins but less asphaltenes, while coal residual oil are mainly asphaltenes, aromatics, resins but less saturates. In the wet and dry gas window, marine and lacustrine shale residual oil is mainly made up of saturates, aromatics, and resins, while coal residual oil is mainly made up of asphaltenes and resins. These results suggest that residual oil contents of marine shale, lacustrine shale, and coaly shale are higher with high proportions of saturated and aromatic hydrocarbons in low maturities which show high shale oil prospective than coal, while in high maturities the residual oil contents decrease quickly but still have higher potential for cracking gases which might become the source of shale gas. The residual oil in coal is low mainly in forms of aromatics, resins, and asphaltenes, which can only be the source of coal-bed methane as maturity increases.

Land use changes extensively affect soil erosion, which is a great environmental concern. To evaluate the effect of land use change on soil erosion in fast economic developing areas, we studied land use changes of Guangdong, China, from 2002 to 2009 using remote sensing and estimated soil erosion using the Universal Soil Loss Equation. We calculated the areas and percentage of each land use type under different erosion intensity and analyzed soil erosion changes caused by transitions of land use types. In addition, the impact of land use change on soil erosion in different river catchments was studied. Our results show that forest and wasteland land conversions induce substantial soil erosion, while transition from wasteland to forest retards soil loss. This suggests that vegetation cover changes significantly influence soil erosion. Any conversion to wasteland causes soil erosion, whereas expansion of forests and orchards mitigates it. The most significant increase in soil erosion from 2002 to 2009 was found in the Beijiang catchment corresponding to the transition from forest/orchard to built-up and wasteland. Soil erosion in the Xijiang catchment accelerated in this period due to the enormous reduction in orchard land. In Hanjiang catchment, erosion was alleviated and vegetation coverage greatly expanded owing to considerable transitions from wasteland and cropland to orchards. Field investigations validated our estimations and proved the applicability of this method. Measures including protecting vegetation, strict control of mining as well as reasonable urban planning should be taken to prevent successive soil erosion.

The spatiotemporal evolution of sea ice of Bohai Sea in the 2009–2010 winter was studied by time-series remote sensing data, and real-time meteorological data in combination with cumulative freezing degree days (CFDD). Sea ice acreage was determined using a ratio-threshold segmentation together with visual interpretation of daily MODIS 250 m imagery. We found the sea ice acreage soared to 31,849 km2 on January 23, covering 40.8% of the Bohai Sea. But on February 12, it reached 26,700 km2 in Liaodong Bay only, covering almost 90.0% of Liaodong Bay. The rapid formation and expansion of sea ice was caused by continuous cold snaps superimposed on a background of anomalously cold weather. CFDD calculated from surrounding cities highly correlated with sea ice acreage in Liaodong Bay (R2 = 0.72) suggesting CFDD is one of the significant controlling factors. Sea ice expansion showed 7 days lag with respect to the lowest temperature from surrounding coastal cities, and it mainly occurred close to land, along the coastline, and gradually expanded from the shore outwards.

Permian coal and Triassic mudstone from the Ordos Basin were pyrolyzed in a closed system using a gold tube technique. Carbon and hydrogen isotopes of the gases generated from pyrolysis were compared to Mesozoic gases in the basin to interpret the origin, maturity and any mixing of gases. Maturation trends for thermogenic methane from both coal and lacustrine kerogens in our experiment were found to be independent of heating rate, allowing their use for determination of gas provenance. Gases from a tectonically stable area like the Shanbei slope are derived mainly from Yanchang lacustrine kerogen, and gases in tectonically active areas consist of mixtures of coal-derived gases and oil-associated methane from deeply buried formations, as well as oil-associated gases and biogenic gases from shallow depth. The thermal maturity of the C2 and C3 gases is estimated to cover an equivalent vitrinite reflectance range from 0.7% to 1.2% Ro, whereas C1 gas exhibits a wide maturity variation ranging from 0.5% to 1.5% Ro and implying significant mixing of Mesozoic methane in the basin.

Land use/land cover (LULC) has a profound impact on economy, society and environment, especially in rapid developing areas. Rapid and prompt monitoring and predicting of LULC’s change are crucial and significant. Currently, integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC’s change, which includes image processing (such as geometrical-rectifying, supervised-classification, etc.), change detection (post-classification), GIS-based spatial analysis, Markov chain and a Cellular Automata (CA) models, etc. The core corridor of Pearl River Delta was selected for studying LULC’s change in this paper by using the above methods for the reason that the area contributed 78.31% (1998)-81.4% (2003) of Gross Domestic Product (GDP) to the whole Pearl River Delta (PRD). The temporal and spatial LULC’s changes from 1998 to 2003 were detected by RS data. At the same time, urban expansion levels in the next 5 and 10 years were predicted temporally and spatially by using Markov chain and a simple Cellular Automata model respectively. Finally, urban expansion and farmland loss were discussed against the background of China’s urban expansion and cropland loss during 1990–2000. The result showed: (1) the rate of urban expansion was up to 8.91% during 1998–2003 from 169,078.32 to 184,146.48 ha; (2) the rate of farmland loss was 5.94% from 312,069.06 to 293,539.95 ha; (3) a lot of farmland converted to urban or development area, and more forest and grass field converted to farmland accordingly; (4) the spatial predicting result of urban expansion showed that urban area was enlarged ulteriorly compared with the previous results, and the directions of expansion is along the existing urban area and transportation lines.

The thermal stability of Paleozoic oil in eastern Tarim Basin, NW China was investigated through laboratory kinetic simulation experiments. Laboratory cracking of a selected marine oil sample from Ordovician strata in well LG-1 of Tarim Basin was performed by confined, dry pyrolysis system at T = 300–650 °C, P = 50 MPa. Results indicated the oil required higher temperature for cracking. At laboratory heating rates, oil cracking started at 390–400 °C and the laboratory cracking was completed at around 650 °C. At geological heating rates, the onset temperature is about 148–162 °C for cracking start and was completed at 245–276 °C. The oil-cracking history was recovered using the acquired kinetic parameters and the geothermal history of TD-2, and the threshold temperature for oil cracking under geological conditions was calculated. The oil cracking started at 165 °C (Ro = 1.45%) and stopped in early Devonian (390 Ma), and the oil-cracking rates in the strata of -O1 reached 60–70% at the end of Silurian. The calculated oil generation and oil cracking windows overlapped to some extent and were completed rapidly. The possible geological controls for the occurrence of residual oil reservoirs in Eastern Tarim basin have been discussed, including the high stability of the Paleozoic oil in Tarim Basin, the fast heating rate and longer duration time for oil cracking, the slight biodegradation in later uplift, the good preservation of the paleo-reservoirs and the moderate structural adjustment, which were critical for the exploration of residual oil and gases in this area.

An effective methodology for Bohai Sea ice detection based on gray level co-occurrence matrix (GLCM) texture analysis is proposed using MODIS 250 m imagery. The method determines texture measures for sea ice extraction by analyzing the discrepancy of textural features between sea ice and sea water. Sea ice extent and outer edge are recognized accurately by texture segmentation owing to significant differences in texture statistical features between ice and water. The texture analysis method can properly eliminate perturbations on sea ice extraction due to suspended sediment. It effectively solves the problem of spectral confusion and sea ice misassignment in the conventional gray-threshold segmentation and ratio-threshold segmentation methods. The method eliminates the need for threshold range setting for sea ice segmentation. Taking the Bohai Sea as an example, the results of the proposed method are validated using co-temporal HJ1B-CCD 30 m imagery by visual interpretation, and the accuracy of the method are evaluated using confusion matrix. The results show that the proposed method is superior and more reliable for sea ice detection compared to conventional methods, providing an ideal tool for precise sea ice extraction.

This paper presents an improved Dark Dense Vegetation (DDV) method for retrieving 500 m-resolution aerosol optical depth (AOT) based on MOD04-C005 arithmetic with the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA). The improvements include change of the movement pattern of retrieval window, selection of a more suitable aerosol type, and storage of the look-up table. The method is then applied to obtain the AOT over the Pearl River Delta region (PRD). By comparing the results with the co-temporal ground sunphotometer observations in 2010, the correlation coefficient is found to be 0.794 with RMSE 0.139 and their variations remain consistent. Contrasts between model values in 2008 and MODIS AOT products in the same date also reveal a high accuracy of the improved DDV method. We also performed sensitivity tests to analyze the impacts of several parameters on apparent reflectance at different bands, and the results show that apparent reflectance is much more sensitive to surface reflectance and AOT than to elevation.