Soil CO2 Concentration Research Articles

Design of a Novel Remote Monitoring System for Smart Greenhouses Using the Internet of Things and Deep Convolutional Neural Networks

To support farmers and improve the quality of crops production, designing of smart greenhouses is becoming indispensable. In this paper, a novel prototype for remote monitoring of a greenhouse is designed. The prototype allows creating an adequate artificial environment inside the greenhouse (e.g., water irrigation, ventilation, light intensity, and CO2 concentration). Thanks to the Internet of things technique, the parameters controlled (air temperature, relative humidity, capacitive soil moisture, light intensity, and CO2 concentration) were measured and uploaded to a designed webpage using appropriate sensors with a low-cost Wi-Fi module (NodeMCU V3). An Android mobile application was also developed using an A6 GSM module for notifying farmers (e.g., sending a warning message in case of any anomaly) regarding the state of the plants. A low-cost camera was used to collect and send images of the plants via the webpage for possible diseases identification and classification. In this context, a deep learning convolutional neural network was developed and implemented into a Raspberry Pi 4. To supply the prototype, a small-scale photovoltaic system was built. The experimental results showed the feasibility and demonstrated the ability of the prototype to monitor and control the greenhouse remotely, as well as to identify the state of the plants. The designed smart prototype can offer real-time remote measuring and sensing services to farmers.

Xylem transport of root-derived CO2 caused a substantial underestimation of belowground respiration during a growing season.

Previous research has indicated that a potentially large portion of root-respired CO2 can move internally through tree xylem, but these reports are relatively scarce and have generally been limited to short observations. Our main objective was to provide a continuous estimate of the quantity and variability of root-respired CO2 that moves either internally through the xylem (FT ) or externally through the soil to the atmosphere (FS ) over most of a growing season. Nine trees were measured in a Populus deltoides stand for 129days from early June to mid-October. We calculated FT as the product of sap flow and dissolved [CO2 ] in the xylem (i.e., [CO2 *]) and calculated FS using the [CO2 ] gradient method. During the study, stem and soil CO2 concentrations, temperature, and sap flow were measured continuously. We determined that FT accounted for 33% of daily total belowground CO2 flux (i.e., FS +FT ; FB ) during our observation period that spanned most of a growing season. Cumulative daily FT was lower than FS 74% of the time, equivalent to FS 26% of the time, and never exceeded FS . One-third of the total CO2 released by belowground respiration over most of the growing season in this forest stand followed the FT pathway rather than diffusing into the soil. The magnitude of FT indicates that measurements of FS alone substantially underestimate total belowground respiration in some forest ecosystems by systematically underestimating belowground autotrophic respiration. The variability in FT observed during the growing season demonstrated the importance of making long-term, high-frequency measurements of different flux pathways to better understand physiological and ecological processes and their implications to global change.

Identification and Inversion of CO2 Leakage from Geological Storage by Using Maize Spectral Characteristic Indexes

CO2 capture and storage (CCS) is an important technical strategy to reduce global CO2 emission from heavy industries. However, the risk of CO2 leakage in CCS-related projects cannot be ignored and it is crucial to identify and monitor CO2 leakage in CCS project areas in a timely and effective manner. So here we investigate the biological characteristics (plant height, leaf length, leaf width and SPAD value) and leaf spectral characteristics of maize under soil CO2 concentration of 10, 30, and 50%, with normal soil condition as control (CK). By analysing the original spectrum and first derivative spectrum of maize leaves, spectral parameters relatively sensitive to soil CO2 stress were extracted. Further, eight composite spectral characteristic indexes that are expected to identify CO2 leakages were constructed and analyzed. Besides, the normalized pigment chlorophyll index (NPCI) and modified chlorophyll absorption in reflectance index (MCARI) were also investigated for the indication role in CO2 leakage. The results showed that maize morphological traits had a significant hysteresis effect for the indication of CO2 leakage; the SPAD value was difficult to indicate the lower concentration of soil CO2 early. But it was found that three spectral characteristic indexes REP-BEP, RGP/RRV and RGP-RRV/RGP+RRV can effectively identify CO2 leakage, and three spectral characteristic indexes (RVP-GPP, REP-BEP and MCARI) can be used for quantitative inversion of soil CO2 concentration. Especially, REP-BEP index could both indicate CO2 leakage and quantitatively inverse soil CO2 concentration. In sum, the spectral characteristic indexes of maize leaves can be used as effective indicators to quickly and effectively identify CO2 leakage and quantitatively invert the CO2 concentration in soil.

Evaluation of effective quantum yields of photosystem II for CO2 leakage monitoring in carbon capture and storage sites.

Vegetation monitoring can be used to detect CO2 leakage in carbon capture and storage (CCS) sites because it can monitor a large area at a relatively low cost. However, a rapidly responsive, sensitive, and cost-effective plant parameters must be suggested for vegetation monitoring to be practically utilized as a CCS management strategy. To screen the proper plant parameters for leakage monitoring, a greenhouse experiment was conducted by exposing kale (Brassica oleracea var. viridis), a sensitive plant, to 10%, 20%, and 40% soil CO2 concentrations. Water and water with CO2 stress treatments were also introduced to examine the parameters differentiating CO2 stress from water stresses. We tested the hypothesis that chlorophyl fluorescence parameters would be early and sensitive indicator to detect CO2 leakage. The results showed that the fluorescence parameters of effective quantum yield of photosystem II (Y(II)), detected the difference between CO2 treatments and control earlier than any other parameters, such as chlorophyl content, hyperspectral vegetation indices, and biomass. For systematic comparison among many parameters, we proposed an indicator evaluation score (IES) method based on four categories: CO2 specificity, early detection, field applicability, and cost. The IES results showed that fluorescence parameters (Y(II)) had the highest IES scores, and the parameters from spectral sensors (380–800 nm wavelength) had the second highest values. We suggest the IES system as a useful tool for evaluating new parameters in vegetation monitoring.

Short-Term Monitoring of Geogenic Soil CO2 Flux in a Non-Volcanic and Seismically Inactive Emission Site, South Korea

Temporal changes of soil CO2 flux (FCO2) and soil CO2 concentration ([CO2]v) were surveyed in a natural CO2 emission site to characterize the factors controlling the short-term temporal variation of geogenic FCO2 in a non-volcanic and seismically inactive area. Due to a lack of long-term monitoring system, FCO2 was discontinuously measured for three periods: Ⅰ, Ⅱ at a high FCO2 point (M17) and Ⅲ about 30 cm away. Whereas [CO2]v was investigated at a point (60 cm depth) for all periods. A 2.1 magnitude earthquake occurred 7.8 km away and 20 km deep approximately 12 h before the period Ⅱ. The negative correlation of FCO2 with air pressure suggested the non-negligible advective transport of soil CO2. However, FCO2 was significantly and positively related with air temperature as well, and [CO2]v showed different temporal changes from FCO2. These results indicate the diffusive transport of soil CO2 dominant in the vadose zone, while the advection near the surface. Meanwhile [CO2]v rapidly decreased while an anomalous FCO2 peak was observed during the period Ⅱ, and the CO2 emission enhanced by the earthquake was discussed as a possible reason for the synchronous decrease in [CO2]v and increase in FCO2. In contrast, [CO2]v increased to 56.8% during the period Ⅲ probably due to low gas diffusion at cold weather. In addition, FCO2 was low during the period Ⅲ and showed different correlations with measurements compared to FCO2 at M17, implying heterogeneous CO2 transport conditions at the centimeter scale. The abnormal FCO2 observed after the earthquake in a seismically inactive area implies that the global natural CO2 emission may be higher than the previous estimation. The study result suggests a permanent FCO2 monitoring station in tectonically stable regions to confirm the impact of geogenic CO2 to climate change and its relation with earthquakes.

Soil CO2 concentration, efflux, and partitioning in a recently afforested grassland

Soil CO2 concentration, efflux, and partitioning in a recently afforested grassland

Comparison of statistical methods for determining risk of leakage from soil gas monitoring

The objective of this paper is to test different methods for detecting anomalies in environmental monitoring of CO2 geological storage sites. This type of monitoring relies on a baseline that is performed before injection. Data collected during injection are then compared to this baseline in order to detect deviations from a normal behavior. A robust method for detecting anomalous measurements would have few false positives (i.e. when an anomaly is wrongly detected) and false negatives (when a real anomaly is not detected). We use a dataset of soil gas measurements that were collected in 36 different locations in the surrounding of a CO2 storage pilot in the South-West of France. We consider CO2 and O2 concentrations in soil. The dataset is modified in order to simulate a leak. We compare the performance of four different methods. The first method uses a threshold in CO2 concentrations. The second method compares measurements with a threshold in the CO2 and O2 relationship (respiration line). The third method fits a Bayesian hierarchical model to the data, accounting for variability between measurements locations. The fourth method fits a Bayesian model to the CO2 / O2 relationship. The Bayesian models both use the same method: a “normal” model is fitted to the baseline data. An additional “anomalous” model (same model but with higher deviation) is tested with the measurements collected during injection. Bayesian inference is used in order to check which of these two models fits best to each measurement. With the data used in this paper, the Bayesian version of the CO2 / O2 relationship has the best results in terms of false positives and false negatives. One advantage of using a Bayesian approach is that the result is a probability that a data point is an anomaly, allowing for a natural interpretation. However, Bayesian approaches may be harder to communicate to lay people.

Determining soil CO2 threshold levels by means of common forecasting methods as part of near-surface monitoring for carbon sequestration projects

Throughout several pilot-projects for CO2 storage soil gas monitoring tied in with monitoring of other parameters have long been considered key elements to ensure safe operating and raise public acceptance. However, no real-life application of soil gas monitoring has been developed until now. We present a new monitoring approach that is based on a continuous comparison of actual soil CO2 concentration data against predicted target values including estimated confidence intervals which are considered as threshold values.Our new approach is based on time series forecasting methods. Since they are not commonplace in soil gas monitoring we give an introduction to simple approaches and more sophisticated modelling categories. These have been tested on different data sets from our soil gas monitoring data base. Finally, we apply the most robust overall model to real time monitoring data of the Hontomín carbon sequestration pilot site.The evaluation revealed that Auto-Regressive Integrated Moving Average (ARIMA) models give reliable estimates of future soil gas concentrations. On a practice-relevant time frame, the accuracy of predicted values and confidence intervals is better than compared to simple approaches like seasonal means. As a result, we present a practical, methodological approach that increases the technology readiness level of soil gas monitoring. Moreover, it has a high potential to be transferred to other environmental monitoring compartments (e.g. soil gas emissions). Since the applied workflow can be automated, integration in real time monitoring systems is straightforward. However, a minimum of two years of data is required to achieve an adequate forecasting precision.

Soil–vegetation–atmosphere interaction over a hilly forest in the southern Huaihe River Basin: Long-term field experiment and preliminary analysis of basic observations 淮河流域南部丘陵森林地区土壤-植被-大气相互作用:长期野外试验观测的初步分析

To improve the understanding of the CO2 exchange and the cycling of energy and water between the land surface and atmosphere over a typical hilly forest in southeastern China, a long-term field experimental observatory was established in Huainan, Anhui Province. Here, the authors briefly describe the three parts of ongoing research activities: the environmental monitoring at the site, the meteorological observations on a high tower, and particularly the intensive measurement of soil–vegetation–atmosphere interaction on a lower tower. Specifically, the diurnal variation of basic meteorological variables on a typical clear day (13 July 2018), and their temporal variation in the first three months of the low tower's operation (4 June to 31 August 2018), and in combination with simultaneous data from the high tower, are analyzed. Results show that the data demonstrate reasonable variabilities, and the variables exhibit significant diurnal variation, characteristics of summer values, and considerable differences in summer months. The daily and monthly average albedos above the forest canopy were both 0.13. The daily average soil CO2 concentration was 1726 and 4481 ppm at 2 and 10 cm, respectively. The soil CO2 concentration changed with soil volumetric moisture contents, but showed a weak correlation with soil temperature in summer 2018. As the observatory continues to run and data continue to be collated, further investigation of the long-term variation of monsoon characteristics should be performed in the future. The experiment is useful in ecosystem and atmosphere interaction research, as well as for the development and evaluation of climate models, in the transitional climate zone of the Huaihe River basin.摘要本文简要介绍了包括三部分观测的安徽淮南长期野外试验观测站, 特别是土壤-植被-大气的集中观测, 对小塔运行前三个月 (2018年6月至8月) 的数据, 并结合同一时段大塔获得的数据, 进行了初步分析.结果表明这些资料有合理的变化特征, 日变化和夏季值特征显著, 各月份间气象变化有明显差异.土壤水分和温度受降雨影响, 在不同的下垫面条件下表现出不同的变化.土壤CO2日平均浓度在2 cm和10 cm处分别为1726和4481 ppm.2018年夏季土壤CO2浓度随土壤体积含水量的变化而变化, 但与土壤温度呈弱相关.

Century-scale climatic oscillations during the Last Glacial Maximum revealed by stalagmite isotopic records from Longfugong Cave, China

The isotopic records of two 230Th-dated stalagmites from Longfugong Cave, Mt. Shennongjia, central China, reveal a highly resolved Asian summer monsoon (ASM) history from 29.5 to 14.5 ka BP. The two δ18O records are consistent with other Chinese cave δ18O records, suggesting that our new records are of regional significance. Due to the reservoir mixing of seepage water in the epikarst system, the stalagmite δ18O signals in this cave are more severely muted than those in other caves. Here, we observed that the amplitude of the δ13C variability is approximately twice that of the δ18O signal and can be used as a sensitive proxy of East Asian monsoon climates. First, the two stalagmite δ13C records are consistent with each other on decadal to centennial timescales. Second, there are high correlation coefficients between the δ13C and δ18O signals over shorter timescales. Third, from 25.2 to 19.6 ka BP, six peaks in the δ13C records were identified and are coincident with corresponding warming events in the Greenland ice-core δ18O records, suggesting that strong coupling occurred between the high- and low-latitude northern climates on centennial timescales. Therefore, we propose that atmospheric transmission mechanisms probably played an important role in linking the ASM and Greenland climates on short timescales. A shift in westerly winds associated with variability in the extent of temperature in the North Atlantic likely influenced changes in hydrological and thermal conditions at the cave site, leading to changes in vegetation cover and soil CO2 concentrations above the cave. Therefore, the calcite δ13C records probably had faster and more sensitive responses to rapid climate shifts compared with their related δ18O records.

Subsoil carbonate dissolution rates and their determining factors in a karst drainage basin, SW China

Subsoil carbonate dissolution is the drives of atmosphere CO2 consumption, underground water alkalinity and karst landform. Specifically, the determining factors and corresponding dissolution models for subsoil carbonate dissolution rate ( $${\text{R}}_{\text{Carb}}$$ ) remain under-researched in various seasons and soil profiles in situ with standard limestone tablets. They are the results of both ecosystem dynamics and hydrological processes. Thus, this study aimed to explore $${\text{R}}_{\text{Carb}}$$ under different seasons, soil depths and water drainage conditions in a karst drainage basin and reveal the factors determining them. Six hundred eighty-four standard limestone tablets were exposed to fields in the subsoil of 10 cm, 20 cm, 30 cm and 40 cm deep, sixteen plots, five sites over every 3 to 4 months in a total of 423 days in the basin of the Miaoguang underground river in Southwest China. The determining factors, including soil CO2 concentration, moisture content, temperature, and pH, were monitored at the same time. The results are summarized in the following statements. $${\text{R}}_{\text{Carb}}$$ , ranged from -0.39 to 18.15 mg cm−2 a−1, were in a clear seasonal pattern. Principal component analysis (PCA) of the observed soil factors revealed the mechanisms that in hot and rainy summer, high $${\text{R}}_{\text{Carb}}$$ occurred in an open system with continuously supplemented CO2 (period I) and decreased with rainfall amount (period IV). Low $${\text{R}}_{\text{Carb}}$$ occurred in a closed system with inactive biological CO2 production under cold weather (period II and III). Hence as soil temperature decreased, $${\text{R}}_{\text{Carb}}$$ increased. $${\text{R}}_{\text{Carb}}$$ increased with soil depths as the elevated soil CO2, temperature and available acid water. Dissolution occurred in an open system on an annual average scale, and a well-fitting equation of $${\text{R}}_{\text{Carb}}$$ and soil factors were given. Local water drainage was critical in carbonate chemical dissolving with implications of formations of local karst landform. Due to no or less groundwater drain and spring seepage, $${\text{R}}_{\text{Carb}}$$ measured in site B (a flat saddle with underlying dolomite bedrock) was nearly zero. Conversely, with water retention, $${\text{R}}_{\text{Carb}}$$ was higher in gentle limestone hillslope or depression than in steep hillside because of longer water–rock interaction duration. In general, in karst drainage basin areas, $${\text{R}}_{\text{Carb}}$$ was determined by multiple factors about seasons, soil depths, and water drainage.

Geochemical Characteristics of Soil Gas and Strong Seismic Hazard Potential in the Liupanshan Fault Zone (LPSFZ)

Eight soil gas measurements were performed in the Liupanshan fault zone (LPSFZ) to observe the concentration and flux of soil gas radon (Rn) and CO2 in October 2017 and October 2018. By combining the historical strong earthquake background and modern seismic activity of the fault zone, the relation between the geochemical distribution characteristics of soil gas and the seismicity of the fault zone was studied herein. Furthermore, the strong seismic hazard potential of the fault zone was discussed. Results show that the concentration of soil gas Rn and CO2 considerably varies in the northern segment of the LPSFZ and is relatively stable in the southern segment. The spatial distribution of the concentration intensity and flux is strong in the north and weak in the south. However, the southern segment of the LPSFZ has a seismic gap that has not been ruptured by strong earthquakes with Ms ≥ 6.5 for the last 1400 years, whereas the seismic activity in the northern segment is relatively frequent, indicating that the fault zone locking degree of the southern segment is higher than that of the northern segment. This observation is completely consistent with the geochemical characteristic distribution of soil gas. Therefore, the southern segment of the LPSFZ should be considered a hazardous segment, where major or strong earthquakes can occur in the future.

Soil Respiration Response to Rainfall Modulated by Plant Phenology in a Montane Meadow, East River, Colorado, USA

AbstractSoil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1‐D diffusion‐reaction model to calculate depth‐resolved CO2 production rates from soil CO2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016–2018. While soil respiration correlated with temperature on diel timescales (p < 0.05), seasonal variability was dominated by soil moisture and plant phenology (p < 0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest that the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore‐summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Finally, we observed significant late season CO2 fluxes from the deep subsoil (>165 cm) that support growing evidence for the importance of subsoil processes in driving integrated respiration fluxes.

Quantitative assessment of deep-seated CO2 leakage around CO2-rich springs with low soil CO2 efflux using end-member mixing analysis and carbon isotopes

This study examined a mountainous area with two hydrochemically distinct CO2-rich springs to understand the origin, flow, and leakage of CO2, which may provide implications for precise monitoring of CO2 leakage in geological carbon storage (GCS) sites. The carbon isotopic compositions of dissolved inorganic carbon (DIC) in CO2-rich water (δ13CDIC) and those of soil CO2 (δ13CCO2) indicated a deep-seated CO2 supply to the near-surface environment in the study area. The hydrochemical difference (e.g. pH, total dissolved solids) for the two CO2-rich springs separated by 7 m, despite similar δ13CDIC and partial pressure of CO2, was considered as the result of different evolution of shallow groundwater affected by deep-seated CO2 preferentially rising along fracture zones. Electrical resistivity tomography also suggested flow through fracture zones beneath the CO2-rich springs, showing low resistivity compared to other surveyed zones. However, soil CO2 efflux was low compared to that in other natural CO2 emission sites, and in particular it was noticeably low near the CO2-rich springs, whereas δ13CCO2 was high close the CO2-rich springs. The dissolution of CO2 in the near-surface water body seemed to decrease the deep-seated CO2 leakage through the soil layer, while δ13CCO2 imprinted the source. End-member mixing analysis was performed to assess the contribution of deep-seated CO2 to the low soil CO2 efflux by assuming that atmospheric CO2 and soil CO2 (by respiration) as well as deep-seated CO2 contribute to the soil CO2 efflux. For each end-member, characteristic δ13CCO2 and CO2 concentrations were defined, and then their apportionment to soil CO2 efflux was estimated. The resultant proportion of deep-seated CO2 was up to 8.8%. Unlike the spatial distribution of high soil CO2 efflux, high proportions exceeding 3% were found around the CO2-rich springs along the east-west valley. The study results indicate that soil CO2 efflux measurement should be combined with carbon isotopic analysis in GCS sites for CO2 leakage detection because CO2 dissolution in the underground water body may blur leakage detection on the surface. The implication of this study is the need to quantitatively assess the contribution of deep-seated CO2 using the soil CO2 concentration, soil CO2 efflux, and δ13CCO2 at each measurement site.

Characteristics of soil CO2 under different conditions and its influence on water chemical composition: an experimental and modeling study in the laboratory

The water quality of the rainwater is obviously different from that of the groundwater after it reaches the surface and passes through the vadose zone. This study aims to further evaluate and analyze how soil CO2 changes under natural conditions, to provide a theoretical background for the establishment of CO2 geological storage, and to provide a basis for the detection of CO2 leakage in order to provide insights for expanding CO2 research. The changes in soil CO2 concentration under different conditions were simulated and analyzed by laboratory experiments, and the effects of CO2 on water chemical composition were also analyzed. In this study, two experimental groups (vegetation group (V) and high-temperature sterilization group (R)) and one blank group (B) were established. The results showed that the CO2 concentration in column R was the lowest, while that in column V was the highest. With rainfall infiltration, soil CO2 concentration gradually increased. When the rainwater infiltrated to 215 cm, the CO2 concentrations in the columns V, B, and R were 5100 mg·m−3, 4450 mg·m−3, and 32,000 mg·m−3, respectively. At infiltration depths from 5 to 215 cm, the Na+, Ca2+, Mg2+, SO42−, and HCO3− concentrations in columns V and B decreased, whereas they increased in soil column R. The simulation revealed that the CO2 concentration ranged from 560 mg·m−3 to 50,000 mg·m−3; pH value decreased; NO3− and Cl− remained stable; SO42− decreased; and fCO2, HCO3−, Ca2+ and Mg2+ increased.

An ignored key link in greenhouse effect: Soil and soil CO2 slow heat loss

The ever-increasing atmospheric CO2 concentration is a key driver of modern global warming. However, the low heat capacity of atmosphere and strong convection processes in the troposphere both limit heat retention. Given the higher heat capacity and CO2 concentration in soil compared to the atmosphere, the direct contributions of soil to the greenhouse effect may be significant. By experimentally manipulating CO2 concentrations both in the soil and the atmosphere, we demonstrated that the soil-retained heat and the slower soil heat transmission decrease the amount of heat energy leaking from the earth. Furthermore, the soil air temperature was affected by soil CO2 concentration, with the highest value recorded at 7500 ppm CO2. This study indicates that soil and soil CO2, together with atmospheric CO2, play a crucial role in the greenhouse effect. The spatial and temporal heterogeneity of soils and soil CO2 should be further investigated, given their potentially significant influence on global climate change.

Precipitation-drainage cycles lead to hot moments in soil carbon dioxide dynamics in a Neotropical wet forest.

Soil CO2 concentrations and emissions from tropical forests are modulated seasonally by precipitation. However, subseasonal responses to meteorological events (e.g., storms, drought) are less well known. Here, we present the effects of meteorological variability on short-term (hours to months) dynamics of soil CO2 concentrations and emissions in a Neotropical wet forest. We continuously monitored soil temperature, moisture, and CO2 for a three-year period (2015-2017), encompassing normal conditions, floods, a dry El Niño period, and a hurricane. We used a coupled model (Hydrus-1D) for soil water propagation, heat transfer, and diffusive gas transport to explain observed soil moisture, soil temperature, and soil CO2 concentration responses to meteorology, and we estimated soil CO2 efflux with a gradient-flux model. Then, we predicted changes in soil CO2 concentrations and emissions under different warming climate change scenarios. Observed short-term (hourly to daily) soil CO2 concentration responded more to precipitation than to other meteorological variables (including lower pressure during the hurricane). Observed soil CO2 failed to exhibit diel patterns (associated with diel temperature fluctuations in drier climates), except during the drier El Niño period. Climate change scenarios showed enhanced soil CO2 due to warmer conditions, while precipitation played a critical role in moderating the balance between concentrations and emissions. The scenario with increased precipitation (based on a regional model projection) led to increases of +11% in soil CO2 concentrations and +4% in soil CO2 emissions. The scenario with decreased precipitation (based on global circulation model projections) resulted in increases of +4% in soil CO2 concentrations and +18% in soil CO2 emissions, and presented more prominent hot moments in soil CO2 outgassing. These findings suggest that soil CO2 will increase under warmer climate in tropical wet forests, and precipitation patterns will define the intensity of CO2 outgassing hot moments.

Analyses and numerical evaluation of integrated time-series monitoring datasets including CO2 concentration and fluxes at controlled CO2 release site in South Korea

In Eumseong, Republic of Korea, a controlled CO2 release site was designed by Korea CO2 Storage Environmental Management (K-COSEM) Research Center to evaluate properly integrated CO2 monitoring tools at the soil surface. CO2 was released from the 55 m-length PVC-pipe buried at 2.5 m-depth, and then, CO2 concentration and flux were monitored from August 1, 2015 to March 21, 2018 (965 days). Influencing environmental factors such as meteorological data, soil moisture and temperature at 5 different depths were monitored concurrently. The measured soil moisture content decreased rapidly when the soil temperature dropped below 0 °C. When CO2 release began, both surface CO2 flux and soil CO2 concentration increased with a time lag. However, with occurrence of precipitation events, CO2 flux decreased to almost 0 cm3 cm−2 day−1 but soil CO2 concentration increased rapidly. The HYDRUS-SOILCO2 predicted soil moisture, temperature and natural background CO2 flux compared to measured data (R2 = 0.74, 0.89, and 0.85). The 10 scenarios were constructed with different soil characteristic curves. Unlike soil moisture content, the simulated natural CO2 flux did not depend heavily on soil characteristics. The mass of released CO2 was estimated by the difference between the measured CO2 flux data during the release test and natural CO2 prediction model. At the 2nd CO2 release test, there was 1.5 times difference between the actual released CO2 mass and calculated CO2 mass.

Application of a low‐cost NDIR sensor module for continuous measurements of in situ soil CO2 concentration

AbstractWe tested the performance of a newly developed CO2 probe, K33SOIL [based on the sensor module K33 (Senseair, Sweden)], under harsh temperature and humidity conditions in a laboratory experiment. The K33SOIL, competed well (RMSE = 0.032% CO2) with the often used GMP343 (Vaisala, Finland) in precision and accuracy. A field experiment showed that the K33SOIL is also suitable for in situ applications. Thus, the K33SOIL is a valuable and cost‐efficient tool for measurement of soil CO2 concentration.

Highly efficient colorimetric CO2 sensors for monitoring CO2 leakage from carbon capture and storage sites

Carbon capture and storage (CCS) technology used for reducing anthropogenic CO2 emissions involves the capture of CO2 from industrial sources and its injection into geological sinks, such as oil reservoirs and abandoned gas fields. To ensure environmental and public safety in implementing CCS technology, efficient CO2-monitoring technology must be developed to detect potential CO2 leakage from CCS sites. Conventional CO2 sensors used for monitoring CCS sites are typically high in cost and require professional staff for maintenance. In this study, we developed a portable and low-cost colorimetric CO2 sensor with high soil CO2 detection efficiency for CCS sites. The sensor consists of a detection solution that contains the pH indicator cresol red encapsulated with a gas-permeable membrane. When CO2 enters the sensor through the membrane, the color of the pH indicator changes and this was quantified using an RGB (red, green, blue) application (app), an app that measures the RGB values of a given color. The change in G and B values of the detection solution showed a significant linear relationship with soil CO2 concentration determined via non-dispersive infra-red (NDIR) CO2 sensor (r2 = 0.98, p = 0.001), and thus these values were used for quantification of CO2 concentration. Tests using CO2-injection chamber showed that the optical CO2 sensors can detect soil CO2 concentration of 0.1 to 30% within a few minutes. Field studies conducted at a natural CO2 vent and an artificial CO2 leakage site showed that the optical CO2 sensors can be applied in analyzing surficial CO2 leakage patterns. The advantage of this optical CO2 sensor when applied to field monitoring is that it is inexpensive and has few installation restrictions. Therefore, this optical CO2 sensor has a strong potential for use in monitoring CO2 leakages from CCS sites.