Ground Surface Temperature Research Articles

Variation characteristics of soil temperature, moisture, and heat flux in the understorey of evergreen broadleaf forest in South China

Based on observation data from the observation tower station in Zhuhai in South China from October 2015 to May 2018, the variations in soil temperature, moisture, and heat flux in the understorey of evergreen broadleaf forest are analyzed. The ground surface temperature is slightly greater than the canopy surface temperature; the soil temperature is the smallest. The seasonal variation in the soil moisture fluctuates around a relative equilibrium as the rain increases or decreases. Both ground and canopy surface temperatures have valley values before sunrise and peak values in the afternoon. The diurnal variations in soil temperature are characterized by a cosine function. With the deepening of the soil layer, the time of valley and peak lag and the amplitude of the variation in the soil temperature decrease. There is almost no diurnal variation in soil temperature at 40 cm depth or the soil heat flux at 30 cm depth. The heat fluxes at depths of 7.5 cm and 15 cm show an “S” pattern variation, with a peak at 17:30. The net radiation of the canopy surface shows a bell-shaped variation, with a peak at 12:30. The averaged soil thermal conductivities are 2.18 W·m−1·K−1, 1.22 W·m−1·K−1, and 1.26 W·m−1·K−1 for 5 ~ 10 cm, 10 ~ 20 cm, and 20 ~ 40 cm depths, respectively.

Numerical experiments for improving the applications of two-phase closed thermosyphons in permafrost regions

Two-phase closed thermosyphons (TPCTs) are widely used in enhancing mechanical strength of foundation soils in permafrost regions. However, engineering problems develop in embankments containing TPCTs. Based on numerical simulations, we herein discuss the influence of four important parameters, namely model size, daily variations in air and ground surface temperatures (AGST), decreasing cooling power of a TPCT, and adiabatic section, on the simulation accuracy or the application results of a TPCT. Results show that the simulated thermal influence of the TPCT can be severely impacted by the model size. It is also found that neglecting daily AGST variations results in 0.3–0.4 °C temperature increase in soil 2 m away from the TPCT. The decreasing cooling power of a TPCT can increase the ground temperature. When the cooling power decreases by 30% and 50%, the ground temperature 2 m away from the TPCT increases by 0.2–0.3 °C and 0.4–0.6 °C in cold seasons, respectively. Although adiabatic section was applied in many TPCTs, but it has limited effect on the cooling performance of a TPCT. The results may help improving the accuracy of a simulation model and help optimize field applications of TPCTs in cold regions.

Inconsistency and correction of manually observed ground surface temperatures over snow-covered regions of the China Meteorological Administration network

Inconsistency and correction of manually observed ground surface temperatures over snow-covered regions of the China Meteorological Administration network

Vertical thermal environment of subtropical broad-leaved urban forests and the influence of canopy structure

Urban forests alter the surface energy balance and provide a comfortable thermal environment. However, little quantitative research exists on the relationship between their vertical temperature structure and influence on the urban thermal environment. In this study, we aimed to measure the differences and determine the correlations between the canopy temperature (T1), below-canopy air temperature (T2), below-canopy ground surface temperature (T3), and soil temperature (T4) of three forests: evergreen broad-leaved forest (EBF), deciduous broad-leaved forest (DBF), and mixed evergreen and deciduous broad-leaved forest (MBF) in Zhejiang Province, China. The thermal environment of DBF fluctuated greatly, whereas that of EBF and MBF was relatively stable. T1 was highly and significantly correlated with T2 (r > 0.850, p < 0.01) and T3 (r > 0.790, p < 0.01) in EBF and MBF; thus, T1 is a good predictor of T2 and T3 in EBF and MBF. T4 was susceptible to the external thermal environment and correlated relatively well with T2 (r = 0.879) in DBF. MBF and EBF had substantial cooling effects, with mean values of T2 and T3 2.4 and 2.3 °C, and 10.1 °C and 10.7 °C lower than the air and surface temperatures in the areas without canopy shade, respectively. Ambient temperature and humidity, solar radiation, canopy thickness and density, tree number, and tree species and height significantly influenced the thermal environment and cooling effect of the forests. The results of this study provide an important reference for the future design of thermally comfortable urban landscapes.

Effect of Near-Earth Surface Temperature on Soil Temperature at 5 cm Depth

The research investigates the effects of ground surface temperature (air temperature) on soil temperature at a depth of 5 cm. The study covers a period of fourteen (14) months from May 2010 to June 2011 in Akure, Southwestern Nigeria. With the aid of an automatic weather station, temperature readings were taken at a depth of 5 cm below the soil surface at five (5) minute intervals daily. It was also observed that many analyses of soil temperature are based on the theories of heat flow and energy balance. The study reveals that surface temperature has a weak effect on soil temperature. The best correlation coefficient obtained for the study period is about 0.56 with a quadratic equation of order 2 at 5% significance level. This implies that air temperature cannot be solely used to predict soil temperature at a depth of 5 cm. A study of diurnal variation reveals that air temperature is usually higher than soil temperature during the day, and vice versa. The study also revealed that surface and soil temperatures are generally lower during the wet months when compared with the dry months. The wet season average daily temperatures are 23.42oC and 27.69oC for air and soil while the corresponding dry season values are 33.92oC and 30.91oC respectively. The results are recommended for agricultural purposes such as determination of soil and environmental conditions for crop production.

Spatial variability of snow density and its estimation in different periods of snow season in the middle Tianshan Mountains, China

AbstractSnow density is an essential property of snowpack. To obtain the spatial variability of snow density and estimate it in different periods of the snow season remain challenging, particularly in the mountainous area. This study analysed the spatial variability of snow density with in‐situ measurements in three different periods (i.e., accumulation, stable and melt periods) of the snow seasons of 2017/2018 and 2018/2019 in the middle Tianshan Mountains, China. The simulation performances of the multiple linear regression (MLR) model and three machine learning (random forest [RF], extreme gradient boosting [XGB] and light gradient boosting machine [LGBM]) models were evaluated. Results showed that snow density in the melt period (0.27 g cm−3) was generally greater than that in the stable (0.20 g cm−3) and accumulation periods (0.18 g cm−3), and the spatial variability of snow density in the melt period was slightly smaller compared to that in other two periods. The snow density in the mountainous areas was generally higher than that in the plain or oasis areas. It increased significantly (p &lt; 0.05) with elevation during the accumulation and stable periods. In addition to elevation, latitude and ground surface temperature also had critically impacted the spatial variability of snow density in the study area. In the current study, the machine learning models, especially RF, performed better than MLR for simulating snow density in the three periods. Based on the key environmental variables identified by the machine learning model and correlation analysis, this study also provides practical MLR equations to estimate the spatial variance of snow density during different snow periods in the middle Tianshan Mountains. This method can be used for regional snow mass and snow water equivalent prediction, leading to a better understanding of local snow resources.

Post‐glacial dynamics of an alpine Little Ice Age glacitectonized frozen landform (Aget, western Swiss Alps)

AbstractGlaciers and frozen‐debris landforms have coexisted and episodically or continuously interacted throughout the Holocene at elevations where the climate conditions are cold enough for permafrost to occur. In the European Alps, the Little Ice Age (LIA) characterized the apogee of the last interaction phase. In areas of consecutive post‐LIA glacier shrinkage, the geomorphological dominant conditioning of the ongoing paraglacial phase may have transitioned from glacial to periglacial and later even shifted to post‐periglacial. Such transitions can be observed through the morphodynamics of glacitectonized frozen landforms (GFLs), which are permafrost‐related pre‐existing frozen masses of debris deformed (tectonized) by the pressure exerted by an interacting glacier. This contribution aims at evidencing the processes driving the ongoing morphodynamical evolution of an actively back‐creeping GFL within the LIA forefield of the Aget glacier on the basis of long‐term time series of ground surface temperature, and in‐situ geodetic and geoelectrical measurements. Our observations for the last two decades (1998–2020), which have been the warmest since the LIA, reveal a resistivity decrease in the permafrost body and a surface subsidence of up to a few centimeters per year. The former indicate a liquid water‐to‐ice content ratio increase within the permafrost body and the latter a ground ice melt at the permafrost table, both processes having taken place heterogeneously at the scale of the landform. The absence of acceleration of landform motion during that period despite a probable warming trend of the frozen ground may indicate that the ongoing degradation is reaching a tipping point at which processes related to interparticle friction and thinning of the permafrost body contribute to gradually inactivate the mechanism of permafrost creep.

TTOP‐model‐based maps of permafrost distribution in Northeast China for 1961–2020

AbstractNortheast China has experienced rapid and substantial climate warming over the past 60 years, and permafrost is degrading rapidly. In this study, permafrost distribution and extent in Northeast China were estimated from monitored ground surface temperatures using the temperature at the top of permafrost (TTOP) model and geographically weighted regression method. Using the TTOP model, the computed mean annual ground temperatures (MAGT@TOP) at the top of permafrost of Northeast China increased significantly from 1961–1990 (1.8°C) to 1991–2020 (3.0°C). The areal extents of permafrost defined by a subzero MAGT@TOP (MAGT@TOP ≤ 0°C) in Northeast China in the period 1961–1990 and 1991–2020 were estimated at 461.5 × 103 and 365.8 × 103 km2, respectively, indicating a decline of 95.7 × 103 km2. On average, the simulated MAGT@TOP values were 2.07°C lower than the observed MAGT@TOP values in boreholes. The linear correlation coefficient between the simulated and measured MAGT@TOP values was 0.63. Compared with the simulation results of other previous models, the result of this research is more reliable and accurate. The compiled maps of permafrost distribution can serve as an important reference for the study of permafrost changes in Northeast China.

Thermal environment evaluation of plastic greenhouses in southern China and optimization by phase change materials

Plastic greenhouses, broadly applied in southern China, have insufficient thermal insulation and thermal storage, resulting in a poor thermal environment at night. This paper chose a plastic greenhouse in Chengdu, Sichuan province, to measure the thermal environment variation in winter. An energy balance model of the plastic greenhouse was developed and then verified by the measurements. The influence of the ground thermal storage on the indoor thermal environment was studied. As a good thermal mass, the ground soil could regulate the indoor thermal environment at night, especially by increasing the near-ground temperature. At night, the ground surface had higher temperatures than the indoor air, with a temperature difference of 4–6 °C. Further, phase change materials (PCMs) were proposed to improve the ground thermal storage conversion efficiency. The ground surface temperature of the plastic greenhouse with PCMs was higher than that of the plastic greenhouse without PCMs by 1 °C, and the average ground thermal storage conversion rate could be increased by 7%.

The Effect of Land Use Changes on Land Surface Temperature in Malang City’s on 2016 - 2020

The land use structure in Malang City has experienced the addition of built-up areas (conversion of built-up land) to areas that are not designated, either naturally or planned. The higher the number and density of the population in Malang, which is accompanied by the need for space for living and activities, is one of the causes of land conversion. buildings and asphalt in urban areas contribute greatly to high surface temperatures. This study aims to see changes in land use that occurred in Malang City in 2016-2020, as well as their effect on soil surface temperature. The data used in this study is Landsat 8 OLI/TIRS Imagery (2016-2020) used to generate land cover, building density, vegetation density, and land surface temperature. This study uses land cover classification methods, Normalized Difference Built-Up/Barren Index (NDBI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST). The results show that the change in land use into built-up land is an increase in ground surface temperature, where in 2016 the minimum temperature was at 14.8°C to 20.2°C in 2020. Land Surface Temperature has a positive correlation with building density, and negative correlation with vegetation density.

Irrigating urban green space for cooling benefits: the mechanisms and management considerations

Evapotranspiration is an important cooling mechanism in urban green space (UGS). Irrigating vegetated surfaces with potable water, collected stormwater or recycled sewage water has the potential to increase the cooling effect of UGS by increasing evapotranspiration. Such cooling effect may not always be strong because evapotranspiration is dependent on local and regional factors such as background climate, seasonality and vegetation type. When using irrigation for cooling, city managers also need to consider management issues such as irrigation water supply and amenity use of the UGS. This study aims to develop a theoretical framework that explains the physical and energetic mechanisms of irrigation cooling effect and a framework to assist city managers to make decision about the use of irrigation for urban cooling. This is achieved by reviewing the impacts of irrigation on local climate reported in the literature and identifying the regional and local factors that influence irrigation cooling effect in warm seasons. The literature suggests that irrigation can potentially reduce daily maximum air temperature and ground surface temperature by approximately 2.5 °C and 4.9 °C, respectively, depending on weather conditions and irrigation amount. Background climate is an important factor that influences the cooling potentials of irrigation. Cities with dry and warm climates have the highest cooling potentials from irrigation. The cooling potentials are also influenced by seasonality and weather, vegetation type, irrigation time of day and irrigation amount. Cities with a dry and warm season can consider using irrigation to mitigate urban heat within UGS because such climatic conditions can increase cooling potentials. To maximise irrigation cooling effect, cities with abundant irrigation water supply can use a soil moisture-controlled irrigation regime while those with limited supply can use a temperature-controlled regime. More studies are required to understand the cooling potentials of irrigating small, individual UGS.

Prediction of Air Pollutant Concentrations via RANDOM Forest Regressor Coupled with Uncertainty Analysis—A Case Study in Ningxia

Air pollution has not received much attention until recent years when people started to understand its dreadful impacts on human health. According to air pollution and the meteorological monitoring data from 1 January 2016 to 31 December 2017 in Ningxia, we analyzed the impact of ground surface temperature, air temperature, relative humidity and the power of wind on air pollutant concentrations. Meanwhile, we analyze the relationships between air pollutant concentrations and meteorological variables by using the mathematical model of decision tree regressor (DTR), feedforward artificial neural network with back-propagation algorithm (FFANN-BP) and random forest regressor (RFR) according to air-monitoring station data. For all pollutants, the RFR increases R2 of FFANN-BP and DTR by up to 0.53 and 0.42 respectively, reduces root mean square error (RMSE) by up to 68.7 and 41.2, and MAE by up to 25.2 and 17. The empirical results show that the proposed RFR displays the best forecasting performance and could provide local authorities with reliable and precise predictions of air pollutant concentrations. The RFR effectively establishes the relationships between the influential factors and air pollutant concentrations, and well suppresses the overfitting problem and improves the accuracy of prediction. Besides, the limitation of machine learning for single site prediction is also overcame.

Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)

With the acceleration of urbanization, ozone (O3) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O3 based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O3 with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index Gi* were adopted to reveal the spatial agglomeration of O3 pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m−3 increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O3 concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O3 concentration reached 200 μg·m−3 in North China (NC) in June, while the lowest value was 60 μg·m−3 in Northeast China (NEC) in December. O3 is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O3 concentrations are significantly differentiated in space: O3 pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O3 exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC.

Near‐surface soil thermal regime and land–air temperature coupling: A case study over Spain

AbstractUnderstanding the near‐surface soil thermal regime and its connection to the atmospheric state is important for the assessment of several climate‐related processes. However, the lack of in situ soil temperatures measurements limits the analysis of such processes. In this study, we have developed a quality‐controlled soil temperature database for Spain that consists of 39 sites spanning from 1987 to 2018. We have used this database to assess the near‐surface soil thermal regime. Likewise, we evaluate at seasonal to multidecadal timescales the land–air temperature coupling over Spain by analysing the structure of the surface air temperature (SAT) and the ground surface temperature (GST) covariance and also their long‐term evolution. In addition, we have employed the ERA5‐Land reanalysis to test the consistence between observations and reanalysis. The results show that the near‐surface soil thermal structure is dominated by conduction despite some influence of hydrology‐related processes. Regarding the land–air temperature coupling, we have found a strong connection between SAT and GST. However, in the summer months there is an offset in SAT–GST at some sites due to limited evaporation and enhanced sensible heat fluxes. Furthermore, multidecadal SAT–GST decoupling may exist over some sites as a response to decreasing precipitation. The ERA5‐Land represents the observations' climatology well, but it underestimates the summer soil temperature observations and the long‐term trends at some sites.

An assessment of phase relationships between heat fluxes and ground surface temperatures in a diurnal cycle based on monitoring studies at the Verkhnee Dubrovo meteorological station

Research subject. The relationships between heat fluxes and ground surface temperatures in a diurnal cycle.Methods. Experimental studies, including actinometric observations and monitoring of surface temperatures and surface heat fluxes for a soil and an artificial layer, were performed at the Verkhnee Dubrovo meteorological station in 2020.Results. The surface heat flux varies synchronously both with the total solar radiation near the earth’s surface and insolation at the upper boundary of the atmosphere. Maximal values of these heat fluxes are observed at the solar noon. The temperature response lags behind them by the time interval determined by the soil’s thermal heterogeneity. In this study, we extend our model of the ground surface temperature response to external radiative forcing, which was developed earlier, to the case of a thermal inhomogeneous half-space. An analytical expression for the simplest case of inhomogeneity (the presence of an upper layer with thermal properties different from those of the underlying rocks) is given and investigated. If the upper layer demonstrates a reduced thermal conductivity, the phase shift between the heat flux and the temperature response decreases in comparison with the value for a homogeneous half-space (45°).Conclusion. The soil studies conducted at the “Verkhnee Dubrovo” meteorological station allowed us to construct a thermophysical section and to verify the previously developed model using experimental data. The errors of theoretical estimates, in general, do not exceed those of the phase estimate at a 10-minute sampling rate. The obtained results can be applied when conducting climatic (including palaeoclimatic) and environmental studies, as well as when investigating heat exchange processes on artificial urban surfaces and their role in the formation of urban heat islands.

Mean flow structure of katabatic winds and turbulent mixing properties

The recent field measurements of katabatic winds on steep alpine slopes provide a unique database for theoretical analysis of the mean flow development and the determination of mixing properties. The theory is based on the depth-integrated momentum and heat equations, and demonstrates an increase in mean velocity $U$ with downstream distance $x$ according to $x^{n}$ ( $n\leq 1/2$ ). An equation for the mean wind velocity is established, expressing its dependency on the buoyancy flux, related to the heat flux to the ground, entrainment and bottom friction. No ambient stratification, and ambient wind and constant ground surface temperature, lead to $U{\sim} x^{1/2}$ , while constant heat flux to the ground leads to $U{\sim} x^{1/3}$ and requires that the reduced gravity decreases as $x^{-1/3}$ . Stable ambient stratification $N$ causes, in addition to small-amplitude mean flow oscillations, a decrease in reduced gravity with $x$ , in which case the assumption of constant surface heat flux along $x$ is only an approximation. The turbulent fluxes are a function of gradient Richardson number $Ri$ with the ratio of turbulent diffusivity to viscosity $K_h/K_m$ changing from nearly $1.4$ to approximately $0.5$ at $Ri\approx 0.5$ . A new mixing efficiency is introduced that includes turbulence kinetic energy production or consumption by along-slope turbulent buoyancy flux. It increases with $Ri$ up to $0.25$ at $Ri\approx 0.5$ and then remains nearly constant. The measurements allowed us to determine the bottom drag coefficients and interfacial entrainment, with the ground surface heat flux being determined from the mean buoyancy flux.

Modeling deformation, seismicity, and thermal anomalies driven by degassing during the 2005-2006 pre-eruptive unrest of Augustine Volcano, Alaska

Understanding the subsurface processes that generate volcanic unrest, including surface deformation, earthquakes, temperature increase, and gas emissions, is essential to improve the forecasting of volcanic eruptions. Volcanic gases exsolved from magma reservoirs can transfer heat towards the surface when the system is open, or pressurize the volcano and lead up to eruptions when the system is closed. Hence, the nature of the observed precursory signals is greatly dependent on whether exsolved volatiles accumulate or escape. In this study, we develop a two-dimensional finite element model to calculate the thermal and poroelastic responses of a volcano to gases that exsolve from depth and migrate to the surface through a pre-existing fractured conduit. This model is explored through a set of sensitivity tests to quantify the controls of gas fluxes and permeability on geophysical observables; and is used to interpret surface deformation (GPS), ground temperature, and seismicity data recorded before the 2006 eruption of Augustine volcano, Alaska, by utilizing the Ensemble Kalman Filter data assimilation technique and Coulomb stress calculations. Our results show that the permeable transfer of gas through a fractured conduit can yield a measurable thermal anomaly at the surface for at least one year before the eruption, consistent with ground- and remote sensing-based data. Moreover, gas flux increased about ten times around three months before the eruption, which might have accelerated hydrothermal alteration and reduced permeability of the conduit by several orders of magnitude, thus accumulating gases inside the volcanic edifice, generating surface deformation, and triggering volcano-tectonic earthquakes. Eventually, failure of the sealed pathways due to high overpressure led to the eruption. Multi-physical numerical models coupling gas flow with host rock deformation and heat transfer are useful tools to understand the triggering mechanisms of volcanic eruptions driven by volcanic gases.

A Combined Cosmogenic Nuclides Approach for Determining the Temperature‐Dependence of Erosion

AbstractPhysical weathering in cold, steep bedrock hillslopes occurs at rates that are thought to depend on temperature, but our ability to quantify the temperature‐dependence of erosion remains limited when integrating over geomorphic timescales. Here, we present results from a 1D numerical model of in‐situ cosmogenic 10Be, 14C, and 3He concentrations that evolve as a function of erosion rate, erosion style, and ground surface temperature. We used the model to explore the suitability of these nuclides for quantifying erosion rates in areas undergoing non‐steady state erosion, as well as the relationship between bedrock temperature, erosion rate, and erosional stochasticity. Our results suggest that even in stochastically eroding settings, 10Be‐derived erosion rates of amalgamated samples can be used to estimate long‐term erosion rates, but infrequent large events can lead to bias. The ratio of 14C to 10Be can be used to evaluate erosional stochasticity, and to determine the offset between an apparent 10Be‐derived erosion rate and the long‐term rate. Finally, the concentration of 3He relative to that of 10Be, and the paleothermometric interpretations derived from it, are unaffected by erosional stochasticity. These findings, discussed in the context of bedrock hillslopes in mountainous regions, indicate that the 10Be‐14C‐3He system in quartz offers a method to evaluate the temperature‐sensitivity of bedrock erosion rates in cold, high‐alpine environments.

The rainfall thresholds and soil characteristics of large geological disasters in Zhejiang, China

Based on observed minute precipitation data during Lekima influencing Zhejiang (from 2019–08-07 00:00:00 to 2019–08-12 23:55:00), the rainfall thresholds for debris flow and landslide are investigated. The rainfall intensity and duration (I-D) thresholds are I = 1247.73D−403.44 + 19.09 and I = 142.63D−0.58–3.37 for debris flow and landslide, respectively. Hourly meteorological data and soil data reveal that (1) the soil volume water content (SVWC) at deep soil layers (50–100 cm) fluctuated continuously during the occurrence of debris flow and landslide. At the end of the landslide period, SVWC at deep soil layers returned stable. (2) At the same soil layer, there was little difference between the upper adjacent values of SVWC in the periods of debris flow and landslide, but the lower adjacent values in the period of landslide were smaller. However, different from the distribution of soil moisture, the lower adjacent values of the soil temperature at all layers were basically the same when debris flow and landslide occurred, while the upper adjacent values were higher when landslide occurred than when debris flow occurred. (3) Compared with the whole typhoon influencing period and debris flow occurrence period, ground surface temperature and surface air temperature, soil temperature, and surface air temperature showed better correlations in landslide occurrence period. (4) Both during debris flow and landslide occurrence time, the soil temperature at all layers did not change with the change of soil depth. Soil temperature and moisture at shallow soil layers owned better correlations than at deep soil layers.

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.