Dynamics in Diffusive Emissions of Dissolved Gases from Groundwater Induced by Fluctuated Ground Surface Temperature.

During the lateral transport with subsurface flow, amounts of manufactured volatile organic chemicals and gases dissolved in groundwater are emitted into the atmosphere via upward diffusion through soils. Quantifying gas emissions is important for assessing environmental risk associated with these constituents (e.g., air pollution and global warming). It is widely recognized that the temperature would affect gas spreading in soils, which in turn regulates the gas emission from groundwater. However, the upward diffusive gas emission induced by the fluctuated ground surface temperature (GST) remains unexplored. A coupled heat transfer and gas transport model is developed to investigate emissions of tetrachloroethylene (PCE) and N2O, a typical manufactured volatile organic chemical and a natural gas, from groundwater with seasonally fluctuating GSTs. The results indicate that both PCE and N2O emissions vary significantly from month to month. Moreover, fluctuations of emissions lag obviously behind the fluctuation of GST due to the damping effects of both capillary fringe and soil sorption. The proposed model agrees with the observed data from a monolith lysimeter experiment well. The model is also applied to the estimations of N2O emissions from 12 aquifers in Walloon Region, Belgium. The estimated N2O emission is 12.6 µg N/m2/d that falls in the estimated range (9.0-21.5 µg N/m2/d) using the IPCC emission factor approach that commonly accounts for the N2O emission of groundwater discharge to surface water only. It suggests that the upward diffusion is non-negligible for estimations of N2O emission from groundwater.

Dynamic changes in permafrost distribution over China and their potential influencing factors under climate warming.

As a major component of the cryosphere, permafrost plays important roles in the climate system and land surface processes of the Earth. Owing to the rapidly warming climate, permafrost over the globe has degraded in recent decades. However, quantifying the distribution and temporal changes in permafrost is challenging. In this study, we modified the widely used surface frost number model by considering the spatial distribution of soil hydrothermal properties and then revisited the spatiotemporal patterns of permafrost distribution and its changes during the past decades (1961-2017) in China. We found that the modified surface frost number model performs well in simulating permafrost extent in China, with the overall accuracy and kappa coefficients being 0.92 and 0.78 in the calibration (1980s) and 0.94 and 0.77 in the validation period (2000s). Based on the modified model, we also found that permafrost extent in China demonstrated a significant decreasing trend over the past decades, especially on the Qinghai-Tibet Plateau (QTP), with a trend of -1.15 × 104 km2/yr (P < 0.01). Moreover, there is a significant relationship between ground surface temperature and permafrost distribution area, with the R2 being 0.41, 0.42, and 0.77 in NE and NW China and on the QTP. The sensitivity of permafrost extent to ground surface temperature in NE China, NW China, and the QTP, respectively, was -8.56 × 104, -1.97 × 104, and -34.60 × 104 km2/°C, respectively. Permafrost degradation has accelerated since the late 1980s, possibly due to increased climate warming. This study is of great significance for improving permafrost distribution simulation at large spatial scales (trans-regional) and for offering vital information for adapting to climate change in cold regions.

Forest floor temperature and greenness link significantly to canopy attributes in South Africa's fragmented coastal forests.

Tropical landscapes are changing rapidly due to changes in land use and land management. Being able to predict and monitor land use change impacts on species for conservation or food security concerns requires the use of habitat quality metrics, that are consistent, can be mapped using above-ground sensor data and are relevant for species performance. Here, we focus on ground surface temperature (Thermal ground) and ground vegetation greenness (NDVI down) as potentially suitable metrics of habitat quality. Both have been linked to species demography and community structure in the literature. We test whether they can be measured consistently from the ground and whether they can be up-scaled indirectly using canopy structure maps (Leaf Area Index, LAI, and Fractional vegetation cover, FCover) developed from Landsat remote sensing data. We measured Thermal ground and NDVI down across habitats differing in tree cover (natural grassland to forest edges to forests and tree plantations) in the human-modified coastal forested landscapes of Kwa-Zulua Natal, South Africa. We show that both metrics decline significantly with increasing canopy closure and leaf area, implying a potential pathway for upscaling both metrics using canopy structure maps derived using earth observation. Specifically, our findings suggest that opening forest canopies by 20% or decreasing forest canopy LAI by one unit would result in increases of Thermal ground by 1.2 °C across the range of observations studied. NDVI down appears to decline by 0.1 in response to an increase in canopy LAI by 1 unit and declines nonlinearly with canopy closure. Accounting for micro-scale variation in temperature and resources is seen as essential to improve biodiversity impact predictions. Our study suggests that mapping ground surface temperature and ground vegetation greenness utilising remotely sensed canopy cover maps could provide a useful tool for mapping habitat quality metrics that matter to species. However, this approach will be constrained by the predictive capacity of models used to map field-derived forest canopy attributes. Furthermore, sampling efforts are needed to capture spatial and temporal variation in Thermal ground within and across days and seasons to validate the transferability of our findings. Finally, whilst our approach shows that surface temperature and ground vegetation greenness might be suitable habitat quality metric used in biodiversity monitoring, the next step requires that we map demographic traits of species of different threat status onto maps of these metrics in landscapes differing in disturbance and management histories. The derived understanding could then be exploited for targeted landscape restoration that benefits biodiversity conservation at the landscape scale.

Thermal regime of warm-dry permafrost in relation to ground surface temperature in the Source Areas of the Yangtze and Yellow rivers on the Qinghai-Tibet Plateau, SW China.

Ecology, hydrology, and natural resources in the source areas of the Yangtze and Yellow rivers (SAYYR) are closely linked to interactions between climate and permafrost. However, a comprehensive study of the interactions is currently hampered by sparsely- and unevenly-distributed monitoring sites and limited field investigations. In this study, the thermal regime of warm-dry permafrost in the SAYYR was systematically analyzed based on extensive data collected during 2010-2016 of air temperature (Ta), ground surface temperature (GST) and ground temperature across a range of areas with contrasting land-surface characteristics. Mean annual Ta (MAAT) and mean annual GST (MAGST) were regionally averaged at -3.19±0.71°C and -0.40±1.26°C. There is a close relationship between GST and Ta (R2=0.8477) as obtained by a linear regression analysis with all available daily averages. The mean annual temperature at the bottom of the active layer (TTOP) was regionally averaged at -0.72±1.01°C and mostly in the range of -1.0°C and 0°C except at Chalaping (~-2.0°C). Surface offset (MAGST-MAAT) was regionally averaged at 2.54±0.71°C. Thermal offset (TTOP-MAGST) was regionally averaged at -0.17±0.84°C, which was generally within -0.5°C and 0.5°C. Relatively consistent thermal conductivity between the thawed and frozen states of the soils may be responsible for the small thermal offset. Active layer thickness was generally smaller at Chalaping than that on other parts of the QTP, presumably due to smaller climatic continentality index and the thermal dampening of surface temperature variability under the presence of dense vegetation and thick peaty substrates. We conclude that the accurate mapping of permafrost on the rugged elevational QTP could be potentially obtained by correlating the parameters of GST, thermal offset, and temperature gradient in the shallow permafrost.