Air CO2 Concentration Research Articles

CO2 Emission from Caves by Temperature-Driven Air Circulation—Insights from Samograd Cave, Croatia

Opposite to atmospheric CO2 concentrations, which reach a minimum during the vegetation season (e.g., June–August in the Northern Hemisphere), soil CO2 reaches a maximum in the same period due to the root respiration. In karst areas, characterized by high rock porosity, this excess CO2 seeps inside caves, locally increasing pCO2 values above 1%. To better understand the role of karst areas in the carbon cycle, it is essential to understand the mechanisms of CO2 dynamics in such regions. In this study, we present and discuss the spatial and temporal variability of air temperature and CO2 concentrations in Samograd Cave, Croatia, based on three years of monthly spot measurements. The cave consists of a single descending passage, resulting in a characteristic bimodal climate, with stable conditions during summer (i.e., stagnant air inside the cave) and a strong convective cell bringing in cold air during winter. This bimodality is reflected in both CO2 concentrations and air temperatures. In summer, the exchange of air through the cave’s main entrance is negligible, allowing the temperature and CO2 concentration to equilibrate with the surrounding rocks, resulting in high in-cave CO2 concentrations, sourced from enhanced root respiration. During cold periods, CO2 concentrations are low due to frequent intrusions of fresh external air, which effectively flush out CO2 from the cave. Both parameters show distinct spatial variability, highlighting the role of cave morphology in their dynamics. The CO2 concentrations and temperatures have increased over the observation period, in line with external changes. Our results highlight the role of caves in transferring large amounts of CO2 from soil to the atmosphere via caves, a process that could have a large impact on the global atmospheric CO2 budget, and thus, call for a more in-depth study of these mechanisms.

Seasonality in cave dripwater and air properties – implications for speleothem palaeoclimatology, Nova Grgosova Cave (Croatia)

Due to the wealth of climate-sensitive properties, speleothems have been propelled into prominence as one of the most powerful continental archives of past climate changes. However, the multitude of processes that operate in the unsaturated karst zone and in the cave atmosphere can make palaeoclimate interpretations of the speleothem proxies challenging and site specific. Hence, to better understand the climate-proxy relationship, cave monitoring studies are usually undertaken. Here, we present the first results of an ongoing cave monitoring study in the Nova Grgosova Cave in Croatia covering an eighteen-month long monitoring period. The driving mechanisms for Mg/Ca and Sr/Ca variability in dripwater samples that feed ten stalagmites are discussed. The results reveal high variability in infiltration among the monitored sites as well as strong seasonal variability in cave air carbon dioxide (CO2) concentrations. A strong positive correlation between dripwater Mg/Ca and Sr/Ca suggests that prior calcite precipitation (PCP) is taking place at this site affecting the chemical composition of dripwater. Principal component analysis furthermore reveals that dripwater Mg/Ca and Sr/Ca are in strong negative correlation with cave air CO2 concentrations, while there is a weak correlation with dripwater quantity. Cave ventilation is a primary process leading to the PCP at the Nova Grgosova Cave. The seasonality revealed in this study suggests the possibility that the Mg/Ca and Sr/Ca ratio in the speleothems from this cave site can be used to aid seasonal reconstructions of past climate conditions in central Croatia and beyond.

Unveiling spatial variations in atmospheric CO2 sources: a case study of metropolitan area of Naples, Italy

In the lower atmosphere, CO2 emissions impact human health and ecosystems, making data at this level essential for addressing carbon-cycle and public-health questions. The atmospheric concentration of CO2 is crucial in urban areas due to its connection with air quality, pollution, and climate change, becoming a pivotal parameter for environmental management and public safety. In volcanic zones, geogenic CO2 profoundly affects the environment, although hydrocarbon combustion is the primary driver of increased atmospheric CO2 and global warming. Distinguishing geogenic from anthropogenic emissions is challenging, especially through air CO2 concentration measurements alone. This study presents survey results on the stable isotope composition of carbon and oxygen in CO2 and airborne CO2 concentration in Naples’ urban area, including the Campi Flegrei caldera, a widespread hydrothermal/volcanic zone in the metropolitan area. Over the past 50 years, two major volcanic unrests (1969–72 and 1982–84) were monitored using seismic, deformation, and geochemical data. Since 2005, this area has experienced ongoing unrest, involving the pressurization of the underlying hydrothermal system as a causal factor of the current uplift in the Pozzuoli area and the increased CO2 emissions in the atmosphere. To better understand CO2 emission dynamics and to quantify its volcanic origin a mobile laboratory was used. Results show that CO2 levels in Naples’ urban area exceed background atmospheric levels, indicating an anthropogenic origin from fossil fuel combustion. Conversely, in Pozzuoli's urban area, the stable isotope composition reveals a volcanic origin of the airborne CO2. This study emphasizes the importance of monitoring stable isotopes of atmospheric CO2, especially in volcanic areas, contributing valuable insights for environmental and public health management.

Complex imprint of air pollution in the basal area increments of three European tree species

The impact of atmospheric pollution on the growth of European forest tree species, particularly European beech, Silver fir and Norway spruce, is examined in five mesic forests in the Czech Republic. Analyzing of basal area increment (BAI) patterns using linear mixed effect models reveals a complex interplay between atmospheric nitrogen (N) and sulphur (S) deposition, climatic variables and changing CO2 concentrations. Beech BAI responds positively to N deposition (in tandem with air CO2 concentration), with soil phosphorus (P) availability emerging as a significant factor influencing overall growth rates. Fir BAI, on the other hand, was particularly negatively influenced by S deposition, although recent growth acceleration suggests growth resilience in post-pollution period. This fir growth surge likely coincides with stimulation of P acquisition following the decline of acidic pollution. The consequence is the current highest productivity among the studied tree species. The growth dynamics of both conifers were closely linked to the stoichiometric imbalance of phosphorus in needles, indicating the possible sensitivity of exogenous controls on nutrient uptake. Furthermore, spruce BAI was positively linked to calcium availability across sites. Despite enhanced water-use efficiency under elevated CO2, spruce growth is constrained by precipitation deficit and demonstrates weakening resilience to increasing growing season air temperatures. Overall, these findings underscore the intricate relationships between atmospheric pollution, nutrient availability, and climatic factors in shaping the growth dynamics of European forest ecosystems. Thus, incorporating biogeochemical context of nutrient availability is essential for realistic modelling of tree growth in a changing climate.

A two-year dataset of energy, environment, and system operations for an ultra-low energy office building

This paper describes a two-year high-fidelity dataset for an ultra-low energy office building and living laboratory called HouseZero®. The building integrates multiple low-energy technologies, such as natural ventilation with automatic windows, ground source heat pump, and thermally activated building systems. The building’s performance is continuously monitored with an extensive sensor network. The dataset consists of breakdown energy end uses, photovoltaic (PV) production, zone-level indoor environment including indoor air temperature, CO2 concentration, and relative humidity, micro-climatical conditions, building façade temperature, and detailed system operations including zone-level BTU meter, valve status, slab temperature, window/skylight opening status, heat pump, and geothermal well operations. The data can be used to support data analytics of ultra-low-energy building operations, and data-driven modeling of low-energy building systems.

Effects of indoor plants on CO2 concentration, indoor air temperature and relative humidity in office buildings.

This experimental study investigates the influence of indoor plants on three aspects of air quality in office spaces: relative humidity, indoor air temperature, and carbon dioxide concentration. Employing a Latin square design, we rotated three different treatments across three offices over six time periods. These treatments included a control (no plants), a low-volume treatment (five plants), and a high-volume treatment (eighteen plants) of Nephrolepis exaltata (Boston fern). Air quality parameters were continuously monitored at five-minute intervals using Trace Gas Analyzers. Generalised linear mixed modelling (GLMM) was employed to examine the effect of each treatment on relative humidity, indoor air temperature and CO2 concentration. We observed a significant positive correlation between the number of indoor plants and relative humidity levels. In offices without any plants, the median relative humidity was 29.1%. This increased to 38.9% in offices with 5 plants and further to 49.2% in offices with 18 plants. However, we did not find significant associations between the number of indoor plants and indoor air temperature or corrected CO2 concentration. Our research provides support for the use of indoor plants to increase relative humidity, which can have health benefits in dry climates, but does not provide support for using indoor plants to regulate indoor air temperatures or CO2 concentration in office environments.

Surface plasmon resonance sensor of hollow microstructure fiber based on ZIF-8 thin film

An annular hollow microstructured fiber surface plasmon resonance (SPR) sensor based on ZIF-8 film is proposed for the measurement of CO2 concentration in air. Internal detection is adopted to enhance the spectral response to CO2 gas, and nano-gold pillars are embedded on both sides of the channel. The geometric parameters of the sensor are optimized to achieve an average sensitivity of 1.01 nm/% over the range of CO2 concentration from 0% to 100%. The results indicate that the sensor is a promising SPR gas sensor with great potential in CO2 detection applications.

Post-modified porous aromatic frameworks for carbon dioxide capture

A new method was developed for post-modification of porous aromatic framework-1 (PAF-1) with chloride and then amine groups confirmed by different characterizations such as nuclear magnetic resonance (NMR), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FTIR). Compared to PAF-1, the amine-functionalized PAF-1 (PAF-1-NH2) exhibits a 50% improvement in carbon dioxide (CO2) adsorption capacity reaching 42 cm3·g-1 at room temperature and 1 bar, and the uptakes under CO2 concentration in air (4 kPa) and flue gas (150 kPa) also greatly increase. The column breakthrough experiments showed that PAF-1-NH2 can separate CO2 from a simulated flue gas of CO2/N2 (15:85, v/v) indicating its potential applications in post-combustion systems.

Limitations of Plant Stress Tolerance upon Heat and CO2 Exposure in Black Poplar: Assessment of Photosynthetic Traits and Stress Volatile Emissions.

Volatile organic compounds (VOCs) emitted by plants may help in understanding the status of a plant's physiology and its coping with mild to severe stress. Future climatic projections reveal that shifts in temperature and CO2 availability will occur, and plants may incur the uncoupling of carbon assimilation and synthesis of key molecules. This study explores the patterns of emissions of key VOCs (isoprene, methanol, acetaldehyde, and acetic acid) emitted by poplar leaves (more than 350) under a combined gradient of temperature (12-42 °C) and air CO2 concentration (400-1500 ppm), along with measurements of photosynthetic rates and stomatal conductance. Isoprene emission exhibited a rise with temperature and CO2 availability, peaking at 39 °C, the temperature at which methanol emission started to peak, illustrating the limit of stress tolerance to severe damage. Isoprene emission was uncoupled from the photosynthesis rate, indicating a shift from the carbon source for isoprene synthesis, while assimilation was decreased. Methanol and acetaldehyde emissions were correlated with stomatal conductance and peaked at 25 °C and 1200 ppm CO2. Acetic acid emissions lacked a clear correlation with stomatal conductance and the emission pattern of its precursor acetaldehyde. This study offers crucial insights into the limitations of photosynthetic carbon and stress tolerance.

Arbuscular Mycorrhizal Fungi Improve the Performance of Tempranillo and Cabernet Sauvignon Facing Water Deficit under Current and Future Climatic Conditions.

Climate change (CC) threatens Mediterranean viticulture. Rhizospheric microorganisms may be crucial for the adaptation of plants to CC. Our objective was to assess whether the association of two grapevine varieties with arbuscular mycorrhizal fungi (AMF) increases grapevine's resilience to environmental conditions that combine elevated atmospheric CO2, increased air temperatures, and water deficit. Tempranillo (T) and Cabernet Sauvignon (CS) plants, grafted onto R110 rootstocks, either inoculated (+M) or not (-M) with AMF, were grown in temperature-gradient greenhouses under two environmental conditions: (i) current conditions (ca. 400 ppm air CO2 concentration plus ambient air temperature, CATA) and (ii) climate change conditions predicted by the year 2100 (700 ppm of CO2 plus ambient air temperature +4 °C, CETE). From veraison to maturity, for plants of each variety, inoculation treatment and environmental conditions were also subjected to two levels of water availability: full irrigation (WW) or drought cycles (D). Therefore, the number of treatments applied to each grapevine variety was eight, resulting from the combination of two inoculation treatments (+M and -M), two environmental conditions (CATA and CETE), and two water availabilities (WW and D). In both grapevine varieties, early drought decreased leaf conductance and transpiration under both CATA and CETE conditions and more markedly in +M plants. Photosynthesis did not decrease very much, so the instantaneous water use efficiency (WUE) increased, especially in drought +M plants under CETE conditions. The increase in WUE coincided with a lower intercellular-to-atmospheric CO2 concentration ratio and reduced plant hydraulic conductance. In the long term, mycorrhization induced changes in the stomatal anatomy under water deficit and CETE conditions: density increased in T and decreased in CS, with smaller stomata in the latter. Although some responses were genotype-dependent, the interaction of the rootstock with AMF appeared to be a key factor in the acclimation of the grapevine to water deficit under both current and future CO2 and temperature conditions.

Simultaneous thermal zoning and demand control ventilation

Heating, Ventilation, and Air Conditioning systems play a crucial role in controlling indoor air conditions, including temperature, humidity, and CO₂ concentration, to ensure human comfort and safety. Thermal zoning and demand-controlled ventilation have demonstrated enhancements in comfort and energy efficiency. This study aims to develop a mathematical model for a Heating, Ventilation, and Air Conditioning system employing an estimated state-feedback control algorithm to optimize indoor comfort and energy savings while minimizing sensor requirements. The model encompasses dynamic equations governing CO₂ concentration and temperature in a five-room building. Temperature regulation is achieved by adjusting the airflow from a cooling unit with dampers, while CO₂ levels are managed by controlling the proportion of fresh air intake. To showcase the advantages of the proposed control approach, comparisons were made with alternative methods based on response performance, energy consumption, and sensor requirements. The estimated state-feedback control outperformed other approaches, requiring only one temperature and one CO₂ sensor at the mixed return. Additional occupancy sensors in each room are not necessary if an Extended Kalman filter is utilized. This technique exhibits scalability, adaptable to varying output variables and room configurations, and holds promise for broader implementation in the HVAC industry. By optimizing energy consumption and maintaining indoor air quality, this approach aligns with established sustainability metrics, promoting environmental responsibility. Compliance with health and safety audit standards ensures the fulfillment of social targets, while adherence to regulations and laws ensures governance targets are met.

Environmental Quality bOX (EQ-OX): A Portable Device Embedding Low-Cost Sensors Tailored for Comprehensive Indoor Environmental Quality Monitoring.

The continuous monitoring of indoor environmental quality (IEQ) plays a crucial role in improving our understanding of the prominent parameters affecting building users' health and perception of their environment. In field studies, indoor environment monitoring often does not go beyond the assessment of air temperature, relative humidity, and CO2 concentration, lacking consideration of other important parameters due to budget constraints and the complexity of multi-dimensional signal analyses. In this paper, we introduce the Environmental Quality bOX (EQ-OX) system, which was designed for the simultaneous monitoring of quantities of some of the main IEQs with a low level of uncertainty and an affordable cost. Up to 15 parameters can be acquired at a time. The system embeds only low-cost sensors (LCSs) within a compact case, enabling vast-scale monitoring campaigns in residential and office buildings. The results of our laboratory and field tests show that most of the selected LCSs can match the accuracy required for indoor campaigns. A lightweight data processing algorithm has been used for the benchmark. Our intent is to estimate the correlation achievable between the detected quantities and reference measurements when a linear correction is applied. Such an approach allows for a preliminary assessment of which LCSs are the most suitable for a cost-effective IEQ monitoring system.

Impact of water exhaled out by visitors in show caves: a case study from the Moravian Karst (Czech Republic)

The anthropogenic impact of the water and CO2 exhaled by visitors was studied in the show caves of the Moravian Karst (Czech Republic), especially in the Balcarka and Výpustek Caves. Two alternative models based on (1) the known/presumed composition of the breathed air and physical activity of visitors and (2) the detailed monitoring microclimatic data were proposed. The CO2 fluxes of 2.4 × 10−4 and (2.0–3.9) × 10−4 mol person−1 s−1 and the water vapor fluxes of (3.2–8.9) × 10−3 and (0.6–1.2) × 10−2 g person−1 s−1 were found for a slightly increased physical load. The total attendance and cave tour duration were the main driving factors. For the available data on attendance and accessibility periods, the total mass of water vapor exhaled by visitors in all show caves in the Moravian Karst was estimated between 9.6 × 106 and 4.3 × 108 g with significant seasonality. According to the geochemical model, this mass of water is capable of dissolving 1280 to 59,038 g of calcite, assuming a mean winter and summer CO2 concentration in the cave air of 1000 and 3000 ppmv. The larger extent of water condensation can lead to the so-called condensation corrosion, whereas the lower extent of condensation probably causes a recrystallization of calcite on the surface of speleothems and rocks.

Responses of underground air and drip water geochemistry to meteorological factors: A multi-parameter approach in the Rull Cave (Spain)

Our research aims to assess the complex interactions between the elements that constitute and influence a cave system through the analysis of an extensive dataset of climatic and environmental parameters (222Rn, CO2, drip rates, chemical composition, and environmental isotopes) measured in air, water, and solid in the Rull Cave (southeastern Spain). Of particular importance is understanding the effect of rainfall and temperature on water and gas transport through the epikarst and the involved processes. Our results show that the cave gaseous concentration patterns do not only depend on the temperature-caused movement of air masses, but they can also be affected by abundant rainfall. The δ18O and δD composition of cave water also relies on such precipitations for the effective transfer of the rainfall signal into the cave, which can take between 3 and 7 days. The elemental ratios (Sr/Ca and Mg/Ca) show high responsiveness to the water drip rate, hinting that enhanced prior calcite precipitation (PCP) occurs at slower drip rates. Despite this, and regardless of drip rates, calcite saturation indices follow a seasonal variation pattern inversely proportional to the cave air CO2 concentration, while δ13C-DIC is proportional. Our results show how the interlinkage between these multiple components defines the dynamics of the atmosphere-soil-cave system. Cave monitoring is then essential to understand the karstic vadose zone, which is highly sensitive to climatic influence and its changes.

PREDICTING FIRE ALARMS USING MULTI SENSOR DATA: A BINARY CLASSIFICATION APPROACH

Fires pose significant threats to human life, property, and the environment. Early detection of fire incidents is crucial to prevent extensive damage and to ensure the safety of occupants. Traditional fire alarm systems typically rely on a single type of sensor, such as smoke detectors or heat sensors, to detect specific fire indicators. These systems operate based on predefined thresholds and triggers. However, they can be prone to false alarms triggered by non-fire-related events (e.g., cooking fumes or dust) and may not provide early warning signs in certain scenarios. To address these limitations, researchers and engineers have turned to advanced technologies, such as multi-sensor data analysis and machine learning algorithms, to develop more reliable and efficient fire alarm prediction systems. On the other hand, the need for a more robust and accurate fire alarm prediction system stems from the shortcomings of traditional methods. False alarms not only lead to wasted resources but also desensitize occupants, potentially leading them to ignore genuine alarms. Additionally, a delayed response to a fire incident can result in severe consequences, making it essential to develop an intelligent system that can effectively and timely predict fire events. Therefore, this work presents the utilization of multi-sensor data and binary classification to develop a more reliable fire alarm prediction system. The experiments are conducted using a dataset collected from various sensor inputs, including air temperature, humidity, CO2 concentration, molecular hydrogen, ethanol gas, and air pressure etc. Then applied binary classification algorithm to learn patterns from the data and classify fire-related events accurately. The results showed promising improvements in prediction accuracy, reduced false alarm rates, and early detection of fire incidents.

Sources and transport of CO2 in the karst system of Jiguan Cave, Funiu Mountains, China

Conveyance and modification of carbon-isotope signals within the karst system remain difficult to constrain, due to the complexity of interactions between multiple components, including precipitation, bedrock, soil, atmosphere, and biota. Cave monitoring is thus critical to understanding both their transport in the karst system and dependence on local hydroclimatic conditions. Jiguan Cave, located in Funiu Mountain in central China, is representative of karst tourist caves with relatively thin epikarst zone. We conducted a comprehensive monitoring program of cave climate from 2018 to 2021 and measured δ13C during 2021 in monthly and heavy-rainfall samples of soil CO2, cave CO2, cave water (drip water and underground river), and underground river outlet. Our results demonstrate synchronous variations between CO2 concentration and δ13CCO2 in both soil and cave air on seasonal time scales. Cave pCO2 and carbon-isotope composition further exhibited a high sensitivity to human respiration with fluctuations of ~2000–3000 ppm within 4 days during the cave closure period in July 2021 without tourists. 13C-depleted isotopic signal of cave air in summer is the mixture of human respiration and soil CO2 which varies as a function of regional hydrological conditions of the summer monsoon during the rainy season with high temperatures and humidity. However, respired CO2 from the overlying soil was expected to be the only principal source of the cave CO2 when the anthropogenic CO2 source was removed. The high seasonal amplitude of cave air δ13CCO2 reflects ventilation dynamics, which leads to a prominent contribution from the external atmosphere during winter. Intriguingly, although the δ13C signal reflects complex vertical processes in the vertical karst profile, a heavy summer rainfall event was related to anomalously high δ13C values of cave water that can be utilized to interpret rainfall intensity and regional hydroclimate.

Membrane Separation Technology in Direct Air Capture.

Direct air capture (DAC) is an emerging negative CO2 emission technology that aims to introduce a feasible method for CO2 capture from the atmosphere. Unlike carbon capture from point sources, which deals with flue gas at high CO2 concentrations, carbon capture directly from the atmosphere has proved difficult due to the low CO2 concentration in ambient air. Current DAC technologies mainly consider sorbent-based systems; however, membrane technology can be considered a promising DAC approach since it provides several advantages, e.g., lower energy and operational costs, less environmental footprint, and more potential for small-scale ubiquitous installations. Several recent advancements in validating the feasibility of highly permeable gas separation membrane fabrication and system design show that membrane-based direct air capture (m-DAC) could be a complementary approach to sorbent-based DAC, e.g., as part of a hybrid system design that incorporates other DAC technologies (e.g., solvent or sorbent-based DAC). In this article, the ongoing research and DAC application attempts via membrane separation have been reviewed. The reported membrane materials that could potentially be used for m-DAC are summarized. In addition, the future direction of m-DAC development is discussed, which could provide perspective and encourage new researchers' further work in the field of m-DAC.

One-year operation performance of a decentralised all-air HVAC system for a school room

Since the first COVID outbreak in 2020, schools have been considered a substantial issue with regard to the spread of the disease, as they represent indoor environments that are continuously occupied most of the time. Several studies have underscored the crucial role of mechanical ventilation systems in the fight against any pandemic caused by airborne pathogens. AiCARR, through its associated companies, donated a mechanical ventilation system to a public school in Rho, Milan province (IT). The primary objective of the installation was to enhance safety by diluting indoor contaminants, improving indoor air quality, and ensuring thermal comfort. During the course of the project, the focus included advancing energy efficiency and reducing operational and maintenance costs. This article presents the first year operational data recorded by the monitoring system that include outdoor and indoor air temperature, relative humidity, CO2 concentration and unit electric consumption.

A deep learning model for predicting risks of crop pests and diseases from sequential environmental data

Crop pests reduce productivity, so managing them through early detection and prevention is essential. Data from various modalities are being used to predict crop diseases by applying machine learning methodology. In particular, because growth environment data is relatively easy to obtain, many attempts are made to predict pests and diseases using it. In this paper, we propose a model that predicts diseases through previous growth environment information of crops, including air temperature, relative humidity, dew point, and CO2 concentration, using deep learning techniques. Using large-scale public data on crops of strawberry, pepper, grape, tomato, and paprika, we showed the model can predict the risk score of crop pests and diseases. It showed high predictive performance with an average AUROC of 0.917, and based on the predicted results, it can help prevent pests or post-processing. This environmental data-based crop disease prediction model and learning framework are expected to be universally applicable to various facilities and crops for disease/pest prevention.

Combined effects of elevated air temperature and CO2 on growth, yield, and yield components of japonica rice (Oryza sativa L.)

In the region where heat stress has become evident, the elevation of air temperature could reduce yield of heat stress-susceptible crops, such as rice (Oryza sativa L.), which is a major food staple in Asia. In addition to air temperature, atmospheric CO2 is projected to be elevated in the future. To project rice yield in the future, it is necessary to clarify the responses of rice to concurrent elevations of air temperature and atmospheric CO2. In the present study, two japonica rice cultivars with different heat tolerance, Hinohikari (sensitive) and Nikomaru (tolerant), were grown in pots inside open-top chambers and exposed to elevated air temperature and/or CO2. The degrees of increase in the air temperature and CO2 concentration by the treatments were approximately 1 °C and 120 µmol mol−1 (ppm). The study was conducted in Nagasaki, Japan, where heat stress on rice has become evident. Elevated air temperature significantly decreased both whole-plant growth and grain yield. Elevated CO2 significantly increased the growth but significantly decreased the yield. The effects of elevated air temperature and elevated CO2 on growth and yield did not significantly differ between two cultivars. In both cultivars, the main cause of yield reduction by both treatments was reduction in spikelet fertility, which is typical heat stress on rice. The elevated CO2-induced reduction in spikelet fertility could be explained partially by high-temperature regime during flowering due to acceleration of heading and by increase in canopy temperature via stomatal closure in flag leaves. Because elevated air temperature and elevated CO2 treatments additively reduced spikelet fertility in both cultivars, concurrent elevations of air temperature and CO2 caused considerable reduction in grain yield.