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The advantages of the demand control ventilation system (DCV) have been widely discussed in previous research studies. However, the literature has not addressed the benefits of DCV on controlling indoor CO2 concentration and minimizing cooling energy consumption for school buildings located in extremely hot climates. Therefore, this paper contributes to the development of DCV and mechanical ventilation systems through a comprehensive evaluation of these systems to maintain acceptable indoor air quality (IAQ) while minimizing cooling energy demands for school buildings located in the harsh hot climate of Saudi Arabia. The evaluation is based on a calibrated whole-building energy model and validated IAQ predictions using field data obtained from a school case study in Jeddah. The results of this research study confirm that hourly and sub-hourly monitoring of indoor CO2 concentration is required to ensure optimal design and operation of the ventilation systems in schools. In addition, the analyses indicate that a 13% increase in cooling energy end-use can result for any additional 0.1 students/m2 density increase in the classrooms. However, the energy penalties related to ventilation needs can be reduced by up to 25% using DCV instead of conventional mechanical ventilation systems for school buildings located in Saudi Arabia’s hot climate.

The increase of CO2 concentration in the atmosphere has brought serious greenhouse effects and environmental problems, so it is urgent to solve the problem of excessive CO2 concentration. The carbon capture, utilization, and storage technology refer to the use of CO2 as a C1 resource to generate new economic benefits in a new production process. In this work, the influence of adding different proportions of N2 and Ar to the CO2 gas on the discharge characteristics and reaction performance was investigated with a newly designed dielectric barrier discharge (DBD) micro-plasma segmented electrode reactor and optical emission spectroscopy. The results indicated that the discharge current value increased when the added N2 content was less than 50%, and decreased when the N2 content exceeded 50% under the condition of constant input power. The number and the current value of mixed gas micro-discharges showed a decreasing trend with the increase of Ar content. In the discharge system, the dielectric capacitance (Cd) and the gas gap capacitance (Cg) showed opposite trends with the increase of N2 and Ar content. The dielectric capacitance decreased and the gas gap capacitance increased as the N2 content increased, while the trend was just the opposite as the Ar content increased. In addition, adding a small amount of N2 and Ar was conducive to the conversion of CO2, but when the N2 and Ar content exceeded 50%, the amount of CO2 converted will be reduced.

Sugarcane cultivation area is exposed to irregular rainfall which leads to several water deficit events during crop development. The plants have the ability to promote physiological and morphological changes to face water deficit. It is probable that, in sugarcane, higher tolerance to recurrent water deficit events is caused by physiological adjustment after the first water deficit exposure. We tested the hypothesis that previous exposition to water deficit event increase drought tolerance of sugarcane in a second water deficit event. Our study was carried out with genotypes RB72454 (drought-susceptible) and RB867515 (drought-tolerant) submitted to two water conditions: control and two events of water deficit (WDE1 and WDE2), separated by a rehydration event (RE). Sugarcane genotypes under WDE1 decreased pre-dawn and mid-day water potential (Ψmd and Ψpd), photosynthesis (A), stomatal conductance (gs), electron transport rate (ETR), and increased intercellular CO2 concentration (Ci), when compared to control conditions. Contrastingly, sugarcane genotypes under WDE2 displayed smaller decrease in A, due to higher ETR, as compared to WDE1. The Multivariate Plasticity Index (MVPi), showed that sugarcane genotypes displayed high physiological plasticity in WDE1, being even higher in the drought-tolerant genotype than in the drought-susceptible one. In WDE2, sugarcane presented a decrease in physiological plasticity. Thus, higher physiological plasticity in WDE1 indicated that water deficit affected plant homeostasis, causing an impact in physiological traits, whereas the lower physiological plasticity showed in WDE2 is possibly related to sugarcane acclimation to water deficit, with a less prominent impact in physiological traits.

In this study, using various statistical methods such as trend analysis, Mann–Kendall (MK) test and Morlet Wavelet Analysis (MWA), the Frequency of Thunderstorm Days (FTD) and its relationship with Sunspots Frequency (SF) and Global Atmospheric Carbon Dioxide Concentration (GACDC) in the 68-year statistical period of 1951–2018 in Tabriz Synoptic Station has been studied. In terms of distribution and temporal concentration, the highest incidence of Thunderstorm Days (TD) is concentrated in the months of May and June and the lowest in the cold months of the year, i.e. January, February and December, with spring having the highest and winter having the lowest FTD. The analysis of the trend of FTD in the study area showed that except for the trends of January, February, June and December, which have no clear and significant trend, other months, especially April, have an upward and significant trend and the seasonal trend of FTD in Tabriz increase significantly in all seasons, especially in the peak of spring; Also, in the annual time scale, a significant upward trend was observed. Decadal changes in the FTD show a sharp increase in the occurrence of TD in Tabriz, especially in the second decade of the twenty-first century. The results of MWA showed that the FTD, like sunspots, has a periodic cycle in its emergence and occurrence. Based on the results of cross-wavelet analysis, there is a strong negative and anti-phased relationship between SF and the FTD in Tabriz. Also, according to the results of MWA, no significant relationship between the GACDC and the FTD in Tabriz has been found.

In China, natural ventilation is a common way of improving indoor air quality (IAQ) in college classrooms. However, until now, the effects of both manual airing strategies and architectural factors on IAQ in classrooms have not been well explored. The present work aimed to investigate the effect of manual airing strategies, such as opening doors and opening exterior or interior windows, on the concentrations of both carbon dioxide (CO2) and fine particulate matter (PM2.5) in classrooms using field measurements. Through simulation, the effects of floor level, room orientation and the height of interior windows on CO2 concentration were also analysed. The results of this study revealed that (1) simultaneously opening doors and exterior windows or opening the doors alone could effectively reduce the indoor CO2 concentration, but the same effect could not be achieved by opening interior windows only; (2) the indoor PM2.5 concentration was primarily affected by the level of outdoor PM2.5, and it may exceed the recommended limit by 33% when the outdoor pollution level is high, even with closed doors and windows; and (3) in winter, both floor level and classroom orientation exerted a significant influence on the indoor CO2 concentration, but the height of interior windows had no effect.

Facing the global warming trend, humanity has been paying more and more attention to the Carbon Capture, Utilization and Storage. Large amounts of CO2 is emitted with burning fossil fuel as well as by some special industrial processes like the decomposition of calcium carbonate in a cement plant. The cement industry contributes about 7% of the total worldwide CO2 emissions and the CO2 concentration of flue gas of the cement kiln tail even exceeds 30%. Ionic liquid is considered to be an effective and potential material to capture CO2. In order to investigate the performance of ionic liquids for capturing CO2 from flue gas of the cement kiln tail, an experiment system was established and an ionic liquid, [APMIm][NTf2] (1-aminopropyl-3-imidazolium bis(trifluoromethylsulfonyl)imine), was tested using pure CO2 and simulated gas. The results showed that both physical and chemical absorption play roles while physical absorption dominates in the absorption process. Both the absorption capacity and rate decrease with raising the operating temperature. In the experiment with pure CO2, the absorption capacity is $$0.296\,{\rm{mo}}{{\rm{l}}_{{\rm{C}}{{\rm{O}}_2}}} \cdot {\rm{mo}}{{\rm{l}}_{{\rm{IL}}}}^{ - 1}$$ at 30°C and $$0.067\,{\rm{mo}}{{\rm{l}}_{{\rm{C}}{{\rm{O}}_2}}} \cdot {\rm{mo}}{{\rm{l}}_{{\rm{IL}}}}^{ - 1}$$ at 70°C. Meanwhile, the ionic liquid can be regenerated for recycling without obvious changes of the absorption capacity. When the ionic liquid is used for flue gas of the cement kiln tail rather than pure CO2, a sharp decrease of the absorption capacity and rate was observed obviously. The absorption capacity at 30°C dropped even to $$0.038\,{\rm{mo}}{{\rm{l}}_{{\rm{C}}{{\rm{O}}_2}}} \cdot {\rm{mo}}{{\rm{l}}_{{\rm{IL}}}}^{ - 1}$$ , 12.8% of that for pure CO2. Additionally, a natural desorption of CO2 from the ionic liquid was observed and affected the experimental results of the absorption capacity and the absorption-desorption rate to some extent.

Neural network models were presented for prediction of indoor concentrations of particulate matters (PMs). Indoor PM concentrations are generally determined by the outdoor concentration, the indoor generation rate, and the air change rate of a building. In this study, indoor PM2.5 and PM10 concentrations were modelled in a single office room installed with a portable air purifier (AP) and a heat recovery ventilator (HRV), using three different neural network models with various input variables. The relative importance of individual input variables indicated that as opposed to PM10, PM2.5 is more affected by outdoor origin than indoor source. This is generally consistent with previous findings explaining that the main source of PM2.5 is outdoor environment, whereas that for PM10 is indoor human activities. The simplified models can be easily applied in practice based on the CO2 concentration measured in a room and the outdoor PM concentration data acquired from public data.

The coastal infrastructures are generally designed for 50 years or more, but often, these structures lose the functionality and need repair or retrofit within its design life. It may be due to the damage or deterioration of the concrete or embedded reinforcement. The structures are usually designed for environmental loads, but the structure is subjected to early deterioration due to the change in climate over the years. In this paper, an attempt is made to understand the effect of climate change in the rapid deterioration of structure using the non-destructive test measurements and well-established models. The study was conducted on a berthing structure located in the backwaters along the west coast of India. The deterioration of coastal structures is mainly of chloride-induced or carbonation. Both these processes depend upon parameters like temperature, relative humidity, CO2 concentration, and rainfall, etc., which in turn, changes with change in the climate. It is found from the study that the effect of climate change is present in the deterioration of the berthing structure. The concentration of chlorides and the carbonation are found to be more than that due to the natural processes of aging.

Carbonation is one of the most aggressive phenomena affecting reinforced concrete structures and causing their degradation over time. Once reinforcement is altered by carbonation, the structure will no longer fulfill service requirements. For this purpose, the present work estimates the lifetime of fly ash concrete by developing a carbonation depth prediction model that uses an artificial neural network technique. A collection of 300 data points was made from experimental results available in the published literature. Backpropagation training of a three-layer perceptron was selected for the calculation of weights and biases of the network to reach the desired performance. Six parameters affecting carbonation were used as input neurons: binder content, fly ash substitution rate, water/binder ratio, CO2 concentration, relative humidity, and concrete age. Moreover, experimental validation carried out for the developed model shows that the artificial neural network has strong potential as a feasible tool to accurately predict the carbonation depth of fly ash concrete. Finally, a mathematical formula is proposed that can be used to successfully estimate the service life of fly ash concrete.

Aims Studies dealing with plants’ mineral nutrient status under elevated atmospheric CO2 concentration (eCO2) are usually conducted in closed hydroponic systems, in which nutrient solutions are entirely renewed every several days. Here, we investigated the contribution of the fluctuation of concentrations of N ([N]), P ([P]), and K ([K]) in nutrient solutions in this short period on their concentrations in cucumber plants exposed to different [CO2] and N levels. Methods Cucumber (Cucumis sativus L.) plants were hydroponically grown under two [CO2] and three N levels. [N], [P], and [K] in nutrient solutions and cucumber plants were analyzed. Results The transpiration rate (Tr) was significantly inhibited by eCO2, whereas Tr per plant was increased due to the larger leaf area. Elevated [CO2] significantly decreased [N] in low N nutrient solutions, which imposed an additional decrease in [N] in plants. [P] in nutrient solutions fluctuated slightly, so the change of [P] in plants might be attributed to the dilution effect and the demand change under eCO2. [K] in moderate and high N nutrient solutions were significantly decreased, which exacerbated the [K] decrease in plants under eCO2. Conclusions The short-term fluctuation of [N] and [K] in nutrient solutions is caused by the asynchronous uptakes of N, K, and water under eCO2, which has an appreciable influence on [N] and [K] in plants besides the dilution effect. This defect of the closed hydroponic system may let us exaggerate the negative impact of eCO2 itself on [N] and [K] in plants.

This study investigated the relationship between the CO2 concentration and land surface temperature in Bengaluru, a recently mega industrialized city located in Southern India. Geographically weighted regression (GWR) was performed to explore the inter-relationship between orbiting carbon observatory-2 (OCO-2) XCO2 and moderate resolution imaging spectroradiometer MODIS-LST (land surface temperature). The GWR coefficient (R2 Adjusted), 0.91, confirms the strong correlation between OCO-2 XCO2 and MODIS LST over the study area. This study confirmed the industrial belt is one of the strong reasons for the remarkable increase in carbon concentration since the study area is surrounded by aerospace manufacturing industries and information technology building. The results of this study can be utilized as an important reference for evaluating the correlation between industrial belt and carbon emissions in south-east Asian countries where industrial belt is intensively constructed.

This study identified the correlation between OCO-2 XCO2 signatures and night-time light (NTL) dynamics for four different landscapes in India: Megapolis (part of Mumbai), City (part of Raipur), Town (part of Dindigul), and Village (part of Balnoi). The data used for building the correlation were collected from Orbiting Carbon Observatory-2 (OCO-2) XCO2 and Defense Meteorological Satellite Program Operational Line Scanner’s (DMSP/OLS) NTL datasets. The result of the study indicated that CO2 concentration is strongly related to NTL data. Megapolis part was found to exhibit higher values in both CO2 mean concentration (405.8 ppm) and NTL distribution level (41.5-pixel value), while the village part was low in both CO2 mean concentration (400.306 ppm) and NTL distribution level (4.4-pixel values). The city part of the data showed that the highest mean local R2 (0.964) in Geographically Weighted Regression (GWR), while the village part recorded the lowest mean local R2 (0.579) in the given data set. This study further emphasizes that the night light satellite imagery can be used as descriptors and proxies to calculate CO2 emission.

Although an increased intrinsic water-use efficiency has been observed, drought stress played a leading role in controlling Chinese pine growth in semi-arid region of northern China. Climate change, which is acknowledged as the most important factor in affecting plant performance, could be modulated by increasing atmospheric CO2 concentration. In this study, a total of 141 Chinese pine ( Pinus tabuliformis ) trees were studied to estimate tree-ring width. Based on tree-ring δ13C records, we measured the fluctuations in leaf intercellular CO2 (Ci) and intrinsic water-use efficiency (iWUE) since industrialization period on Hasi mountain, Gansu province. We found that the long-term variation of iWUE has been increasing since 1850. On average, 73% of the total variance in iWUE was explained by temperature, Standardized Precipitation-Evapotranspiration Index (SPEI) and CO2 concentration. Over 19 and 23% of the variance was attributed solely to drought stress and CO2 concentration, respectively. For BAI (basal area increment), nearly 50% of the variance was explained by temperature, SPEI and CO2, with 40% of the variance in tree growth attributed to drought stress. In addition, our results show that the positive relationship between tree growth and drought stress did not change over time. When there was a wetter condition, a larger proportion of higher tree growth occurred, otherwise more trees had lower tree growth. We therefore, conclude that despite the clear increase of iWUE, its beneficial effect of this higher iWUE on tree growth was overcome by drought stress at our study area.

Jujube–cotton intercropping system is a common efficient practice in China, especially in Xinjiang, Northwest China. While setting up two jujube–cotton intercropping systems, we planted two or four rows of cotton between two rows of jujube to study the formation of yield and factors influencing yield of 1-year jujube on intercropping cotton. The results indicated that photosynthetic/physiological characteristics of cotton in different planting patterns were significantly different only from the squaring stage to prophase of the boll opening stage, and the soil plant analyzer development value were not different all the time. Under the influence of jujube shading, the net photosynthetic rate, stomatal conductance, transpiration rate, and yield of cotton in a four-row cotton intercropping pattern (Int-4) and a two-row cotton intercropping pattern (Int-2) were significantly decreased compared with those of one-row cotton (Sole) and the intercellular CO2 concentration increased. There was no significant difference between Int-2 and Int-4 in above photosynthetic/physiological characteristics. The higher planting density makes the harvested number and boll number of Int-4 superior. Compared to the Int-2, the yield of Int-4 increased significantly by 10.50%, and the economic benefits from high to low were Int-4 > Int-2 > Sole. Therefore, we concluded that an appropriate increase of cotton planting density is beneficial to the high yield of cotton in a jujube–cotton intercropping system, because it is conducive to increasing the income of farmers.

A global rise in CO2 concentration and temperature levels can impact the living part of the earth including the plants. Stevia or candy leaf (Stevia rebaudiana Bertoni) is a medicinal aromatic plant that produces several useful chemical compounds. Studies were carried out in a fully automated greenhouse in order to determine the response of aromatic compounds of stevia leaves to different CO2 concentrations and temperature levels. This study had four treatments including (1) 26 ± 1/16 ± 1 °C day/night temperature plus 400 ± 50 ppm CO2 concentration [control], (2) 29 ± 1/19 ± 1 °C day/night temperature plus 600 ± 50 ppm CO2 concentration, (3) 32 ± 1/22 ± 1 °C day/night temperature plus 800 ± 50 ppm CO2 concentration and (4) 35 ± 1/25 ± 1 °C day/night temperature plus 1000 ± 50 ppm CO2 concentration. Results of the study showed that yield of total aromatic compounds ranged between 12.65 and 13.65 μg/g for stevia . Generally, concentrations of the compounds such as ketones, aldehydes and alcohols were decreased with increase in concentration of CO2 and temperature. Terpenes were the compounds whose concentrations were increased with increase in concentration of CO2 and temperature. The climatic conditions did not cause a significant change in the aromatic compounds of stevia.

Powdered activated coke (PAC) is a good adsorbent of SO2, but its adsorption capacity is affected by many factors in the preparation process. To prepare the PAC with a high SO2 adsorption capacity using JJ-coal under flue gas atmosphere, six parameters (oxygen-coal equivalent ratio, reaction temperature, reaction time, O2 concentration, CO2 concentration, and H2O concentration) were screened and optimized using the response surface methodology (RSM). The results of factor screening experiment show that reaction temperature, O2 concentration, and H2O (g) concentration are the significant factors. Then, a quadratic polynomial regression model between the significant factors and SO2 adsorption capacity was established using the central composite design (CCD). The model optimization results indicate that when reaction temperature is 904.74°C, O2 concentration is 4.67%,H2O concentration is 27.98%, the PAC (PAC-OP) prepared had a higher SO2 adsorption capacity of 68.15 mg/g while its SO2 adsorption capacity from a validation experiment is 68.82 mg/g, and the error with the optimal value is 0.98%. Compared to two typical commercial activated cokes (ACs), PAC-OP has relatively more developed pore structures, and its SBET and Vtot are 349 m2/g and 0.1475 cm3/g, significantly higher than the 186 m2/g and 0.1041 cm3/g of AC1, and the 132 m2/g and 0.0768 cm3/g of AC2. Besides, it also has abundant oxygen-containing functional groups, its surface O content being 12.09%, higher than the 10.42% of AC1 and 10.49% of AC2. Inevitably, the SO2 adsorption capacity of PAC-OP is also significantly higher than that of both AC1 and AC2, which is 68.82 mg/g versus 32.53 mg/g and 24.79 mg/g, respectively.

A quantitative understanding of the global gross primary productivity (GPP) and its responses to increasing CO2 levels is critical for quantifying the feedbacks of ecosystems to climate change. This study applied the daily boreal ecosystem productivity simulator (BEPSd) model to estimate the global GPP from 2000 to 2015, compare the estimated GPP with flux tower measurements and other GPP products to verify the estimation accuracy, and analyze the CO2 fertilization effect and conducted a spatial analysis of the effects of the spatiotemporal distribution of the CO2 concentration on the estimation of the GPP. The results showed that the estimates could capture the magnitude, amplitude, distribution, and variation in the GPP well compared with the flux tower measurements and other GPP products. In general, the terrestrial GPP increased as the atmospheric CO2 concentrations increased; however, the CO2 fertilization effect varied based on time and location and was constrained by climatic conditions. The increases in the lower latitudes were more significant than those in the middle and higher latitudes, and seasonal variation characteristics were observed in the middle and higher latitudes. Not considering the CO2 fertilization effect could underestimate the global GPP and its trend, while not considering the spatiotemporal distribution of the CO2 concentration could overestimate the global annual GPP. These results increase our understanding of the variations in carbon flux under future climate change, especially under the conditions of a changing atmospheric CO2 concentration.

Constant mesophyll conductance (gm), and two-resistance gm model (involved in resistances of cell wall and chloroplast), where gm reaches maximum under higher CO2 concentrations, cannot describe the phenomenon that gm decreases with increasing intercellular CO2 concentration (Ci) under relatively higher CO2 concentrations. Yin et al. (2020) proposed a gm model, according to which the ratio of chloroplastic CO2 concentration (Cc) to Ci is constant in the two-resistance gm model, which can describe the decreasing gm with increasing Ci. In the present study, we investigated the relationship between Cc and Ci in leaves of Japanese white birch by using simultaneous measurements of gas exchange and chlorophyll fluorescence under various CO2 concentrations, light intensities, and during progressive drought. Across the range of ambient CO2 from 50 to 1000 μmol mol−1, and light intensities of 50 to 2000 μmol m−2 s−1, measured under well irrigation, the ratio of Cc to Ci kept constant. During the progressive drought, overestimated Ci due to stomatal patchiness and/or cuticular transpiration was empirically corrected (threshold: stomatal conductance

This study investigated microalgal CO2 fixation at the CO2 concentration ranging from 5 to 40% and the CO2 loading rate of 14.4 to 57.6 L/L-d. Chlorella sp. (AG10133) was selected as the optimal strain for CO2 fixation among examined algal strains. The microalgal CO2 fixation was highly dependent on the CO2 loading rate as well as CO2 concentration. In batch culture, the highest CO2 fixation rate of 1.785 g/L-d was obtained at the CO2 concentration and the CO2 loading rate of 15% and 43.2 L/L-d, respectively. The high CO2 fixation performance was maintained at CO2 40% with the same CO2 loading rate. On the other hand, CO2 loading rate over 43.2 L/L-d at CO2 15% deteriorated CO2 fixation along with the decrease of microalgal growth. In continuous culture, the CO2 fixation rate of 2.25 g/L-d was achieved at the pseudo-steady state. The microalgal CO2 fixation would be suitable for high-strength CO2 gas stream such as biogas by providing proper CO2 loading rate.

This study examines the response of the clustering behavior in heavy precipitation events across Europe to increasing atmospheric CO2 concentrations. We focus on four large-scale climate modes [Arctic Oscillation (AO), North Atlantic Oscillation (NAO), East Atlantic (EA) pattern, and Scandinavia pattern (SCAND)] that have been found to play a significant role in controlling the occurrence of these events. We use a peak over threshold (POT) method to define daily heavy precipitation events and Cox regression as the modeling framework. We consider three experiments from the Coupled Model Intercomparison Project Phase 5 (CMIP5): (1) pre-industrial control run experiments (PI-control); (2) a 1%/year increase in CO2 from the CO2 concentration in PI control to quadrupling (1pctCO2); and (3) an instantaneous quadrupling of CO2, then holding it fixed (abrupt4 × CO2). We measure the effects of CO2 by examining whether the Cox regression coefficients in the CO2 experiments are significantly different from those in the PI control. We find that (1) the increases in CO2 are unlikely to lead to changes in the spatial patterns of relationships between climate modes and heavy precipitation; (2) the increases in CO2 are likely to lead to a strengthening of the relationship between the AO/SCAND and the occurrence of heavy precipitation events, while increases in CO2 have weaker effects on the role of NAO and EA; (3) the response to an abrupt increase in CO2 is generally stronger compared to a more gradual one; (4) the responses of the integrated vapor transport and 500-mb geopotential height to increasing CO2 provide a physical mechanism to explain the enhanced relationship between climate modes and clustering of heavy precipitation events.

This paper uses a case study-based approach to comparatively evaluate the relationship between measured and perceived indoor environmental conditions in two office buildings, one naturally ventilated and one mechanically ventilated, located in south England. Environmental parameters (indoor and outdoor temperature and relative humidity, and indoor CO2 concentration) were continuously monitored at 5-minute intervals over a 19-month period (March 2017 to September 2018). During this time, occupant satisfaction surveys (both transverse and longitudinal) recorded occupant perceptions of their working environment, including thermal comfort, resulting in approximately 5700 survey responses from the two case studies combined. In the NV office, CO2 levels were high (often >2000 ppm) and indoor temperature was both high (>27 °C) and variable (up to 8 °C change in a working day). In contrast, the MV office environment was found to operate within much narrower temperature, RH and CO2 bands. This was particularly evident in the little seasonal variation observed in the CO2 levels in the MV office (rarely above 1200 ppm); whereas in the NV office, CO2 concentrations exceeded 2000 ppm on 12% of working days during the heating seasons and less than 1% in the non-heating season. Despite these differences in measured indoor environmental conditions, occupants’ overall satisfaction with their environment was similar in both buildings. Occupants of the NV building were found to be more tolerant of higher indoor temperatures while neutral thermal sensation corresponded to a higher indoor temperature, indicating the role of adaptation. This has important implications for energy use in managing the indoor environment.

The CO2 injection capacity directly affects the CO2 storage efficiency. Injection temperature and formation sloping degree affect the CO2 injection capacity. Based on the actual geological conditions of the Shiqianfeng Formation in the Ordos Basin of China, a three-dimensional (3D) simulation model was established to evaluate pressure, temperature, CO2 spatial distribution, and injection amount. A total of 17 simulation schemes were carried out using the TOUGH2–ECO2N fluid property module. The results showed that the injection temperature had a significant impact on the CO2 injection capacity in the different sloping degree formations. Increasing the injection temperature resulted in increased formation pressure, CO2 gas phase, dissolved phase, and total injection amount, while decreasing the CO2 concentration, and the formation pressure changed obviously with the formation sloping degree. The larger the formation sloping degree was, the less the CO2 injection amount. Higher injection temperature and smaller sloping degree formation were more favorable for CO2 injection, and the CO2 injection capacity was stronger, signaling that it should be selected to store CO2 in the future.

The study was carried out to assess the impact of climate change on potato productivity to develop adaptation strategies in Punjab, using crop growth simulation models for future climate scenarios (2030, 2050 and 2080) under representative concentration pathways (RCPs) 4.5 and 6.0. Three potato cultivars belonging to distinct maturity groups, late (Kufri Badshah), medium (Kufri Jyoti) and early (Kufri Pukhraj), were used. Simulation results showed that under RCP 4.5, increase in CO2 concentration is expected to bring an increase in productivity of Kufri Badshah, Kufri Jyoti and Kufri Pukhraj by 6.7, 7.2 and 7.1% in 2030; 10.8, 11.6 and 11.4% in 2050; and 14.0, 15.0 and 14.8% in 2080. However, the corresponding increase in temperature is likely to decline the mean productivity by 2.6, 3.8 and 3.8% in 2030; 6.5, 8.7 and 9.3% in 2050; and 14.4, 17.6 and 18.4% in 2080, for Kufri Badshah, Kufri Jyoti and Kufri Pukhraj. But, when combined influence of temperature and CO2 was considered, the productivity of potato will not be affected in 2030 and 2050 over the baseline scenario but is expected to decline in 2080 (Kufri Badshah − 1.9%, Kufri Jyoti − 4.1% and Kufri Pukhraj − 5.2%). Similarly, for RCP 6.0, increased CO2 concentration is expected to increase the mean productivity by 6.5% in 2030, 10.5% in 2050 and 19.4% in 2080. However, yield increase due to CO2 is negated by increased temperature with respective values of 2.2, 4.4 and 14.2%. However, under combined effect for RCP 6.0, productivity of potato cultivars is not likely to be affected over the baseline scenarios for 2030, 2050 and 2080. Results further revealed that by changing the dates of planting or selection of suitable cultivars, yield can increase in 2030 by 7.4% in Kufri Badshah and 7.8 and 1.5% in Kufri Pukhraj in 2050 and 2080, under RCP 4.5. Similarly, adaptation may increase mean yield up to 9.1% for Kufri Pukhraj in 2030, 9.8% for Kufri Badshah in 2050 and 8.2% for Kufri Badshah and Kufri Jyoti in 2080 under RCP 6.0. Further, with proper irrigation and nitrogen management practices, yield can be increased.

Rice residue including root and straw are unique carbon (C) source in paddy soils. However, the potential changes in quantity and chemical composition of rice residue under co-elevated atmospheric CO2 concentration ([CO2]) and air temperature (Tair) and the legacy effect of the changed chemical composition on residue decomposition have not been investigated. This study was conducted to investigate biomass, chemical composition, and decomposability of rice root and straw produced under elevated [CO2] and Tair. Root and straw biomass increased by elevated [CO2] and elevated Tair, respectively, and the greatest biomass was achieved under co-elevated [CO2]-Tair for both root and straw. The concentration of lignin (recalcitrant) decreased while that of nonstructural carbohydrates (less recalcitrant) increased by co-elevated [CO2]-Tair. The ratio of lignin-to-nitrogen (lignin/N) decreased by co-elevated [CO2]-Tair compared to ambient [CO2]-Tair due to increased N and decreased lignin concentrations. Decomposability of root (lignin/N, 36.4) produced under co-elevated [CO2]-Tair was greater than that under ambient co-elevated [CO2]-Tair (lignin/N, 53.7); however, there was no difference in decomposability for straw, which had relatively narrow range of lignin/N (27.3–36.5) regardless of [CO2]-Tair conditions. The results of this study provide a novel insight into the changes in quantity and quality of rice residue under elevated [CO2]-Tair that are necessary to predict changes in paddy soil C sequestration under global warming.

A model predicting time required to attain undesired levels of respiratory-CO2 in closed rooms is described. The model works under the following assumptions: (1) room air is well-mixed, (2) indoor CO2 does not exchange with outdoor CO2, (3) there is no effect of individual occupants on CO2 exhalation rate of other occupants, (4) there is no indoor CO2 sink and all exhaled CO2 end up increasing CO2 concentration in the room, (5) apart from respiration, there is no other source of indoor CO2, (6) breathing rates of occupants are constant throughout the period of occupation of room. The model makes use of anthropocentric parameters like body weight, height, du bois surface area, MET levels, etc., to calculate dedicated individual CO2 exhalation rate and uses room volume and number of occupants to predict time required to reach user-earmarked levels of CO2. A model run showed that in a closed room of 12 × 12 × 10 m3, respiration by one person at rest (65 kg body weight, 1.7 m height, basal respiratory quotient of 0.83) would take 4.37 h to reach 2000 ppmV indoor CO2 when background indoor CO2 level was 380 ppmV. This model would help allocating desired number of occupants in closed rooms to help avoid building up of undesirable levels of CO2 in poorly ventilated offices, schools, hospitals or households that might frequently experience high levels of indoor CO2, undermining health and performance of occupants, patients and workers.

Many aspects can influence the CO2 biofixation efficiency by microalgae, including CO2 concentration, initial biomass concentration and photobioreactor configuration. This study evaluated two photobioreactors (raceway and tubular) and two initial biomass concentrations (0.2 and 0.4 g L−1) in the growth parameters and in the CO2 biofixation by Spirulina sp. LEB 18 cultures. The carbon source was replaced by 10% (v/v−1) of CO2 (0.05 vvm). Tubular photobioreactor cultures provided an increase of 43 and 62%, respectively, in the maximum specific growth rate and in the CO2 biofixation efficiency, compared with the raceway photobioreactor cultures. The lowest initial biomass concentration evaluated (0.2 g L−1) increased the growth parameter results, with a maximum specific growth rate of 42% higher than the cultures using the highest initial biomass concentration (0.4 g L−1). Spirulina sp. LEB 18 cultures in tubular photobioreactor with 0.2 g L−1 of initial biomass concentration showed a potential for CO2 biofixation.

Previous studies have found amplified warming over Europe-West Asia and Northeast Asia in summer since the mid-1990s relative to elsewhere on the Eurasian continent, but the cause of the amplification in these two regions remains unclear. In this study, we compared the individual contributions of influential factors for amplified warming over these two regions through a quantitative diagnostic analysis based on CFRAM (climate feedback-response analysis method). The changes in surface air temperature are decomposed into the partial changes due to radiative processes (including CO2 concentration, incident solar radiation at the top of the atmosphere, surface albedo, water vapor content, ozone concentration, and clouds) and non-radiative processes (including surface sensible heat flux, surface latent heat flux, and dynamical processes). Our results suggest that the enhanced warming over these two regions is primarily attributable to changes in the radiative processes, which contributed 0.62 and 0.98 K to the region-averaged warming over Europe-West Asia (1.00 K) and Northeast Asia (1.02 K), respectively. Among the radiative processes, the main drivers were clouds, CO2 concentration, and water vapor content. The cloud term alone contributed to the mean amplitude of warming by 0.40 and 0.85 K in Europe-West Asia and Northeast Asia, respectively. In comparison, the non-radiative processes made a much weaker contribution due to the combined impact of surface sensible heat flux, surface latent heat flux, and dynamical processes, accounting for only 0.38 K for the warming in Europe-West Asia and 0.05 K for the warming in Northeast Asia. The resemblance between the influential factors for the amplified warming in these two separate regions implies a common dynamical origin. Thus, this validates the possibility that they originate from the Silk Road pattern.

Today, environmental pollution, air pollution in particular, is among the most important problems in the world. Air pollution, which has become a global issue, is estimated to cause the death of around 1 in 8 people worldwide. Due to the significance of air pollution, all components of air pollution are of great importance for human health, and thus the studies on air pollution are highly important, especially in areas with high population density. In this study, it was aimed to determine the regional and periodic change of CO2 and particulate matter pollution in the city of Misurata, one of the important cities of Libya. The study was conducted in the city centre of Misurata, and the measurements were made once in every three days between November and February at 7 different locations selected in the city centre. As a result of the measurements made, the changes in the pollution parameters were evaluated on the basis of zones and months. As a result of the study, the cleanest areas were found to be the industrial area (B3) located in the east of the city and the zone (B4), where the Al-Swehli farm was located, while the dirtiest areas were found to be the main street (B1 and B2) in the city centre and the city centre, in general. In terms of months, the lowest CO2 values were obtained in January, and the highest value was in February, whereas the lowest particulate matter values were obtained in January and the highest values in December.

The impact of in-situ CO2 nano-bubbles generation on the freezing properties of soft serve, milk, and apple juice was investigated. Carbonated (0, 1000, and 2000 ppm) liquid foods contained in a tube were submerged and cooled for 90 min in a pre-set ethylene glycol bath (−15 °C). Before the enclosed liquid reached 0 °C, the vibration was discharged through ultrasound in the bath to create nano-bubbles within the carbonated food samples, and the changes in temperature for 90 min of each food were recorded as a freezing curve. The time for onset of nucleation of control soft serve mix was halved in samples with 2000-ppm CO2 due to the presence of nano-bubbles. Likewise, the nucleation time for milk with and without nano-bubbles at the same CO2 concentration of 2000 ppm was 7.9 ± 0.1 and 2.8 ± 0.8 min, respectively. The generation of CO2 nano-bubbles from 2000-ppm CO2 level in 10 oBx apple juice displayed −9.3 ± 0.3 °C nucleation temperature while the control one had −11.7 ± 0.9 °C.

Under the scenario of global change, continuous 13C-enriched CO2 labeling is a powerful tool for evaluating the interaction between plants and soil, especially the influence of elevated CO2 on the input of plant-derived C (new C) into soil in the short term. However, the methodological validity concerning the acquisition of isotopic signals and their implications in plants and soil remains ambiguous. We conducted an experiment simulating elevated CO2 with wheat planted in growth chambers. 13C-enriched CO2 with identical 13C abundance was supplied at two CO2 concentration levels (350 versus 600 ppm) until wheat harvest. The δ13C values of plant tissues and soil were measured periodically during the growing season. The δ13C values of wheat tissues under elevated 13CO2 were 15–17% higher than those under ambient 13CO2 after the heading stage, implying that the 13C signals themselves in plants and soil were not directly representative of the influence of elevated CO2 on the C fixation in the plant and thereby the flow of plant-derived C into soil. The proportion of plant-derived C in the soil (fnew) was calculated separately at each CO2 concentration by taking the initial soil as a reference and the corresponding δ13C values as parameters in the mixing model, and we found that elevated CO2 significantly enhanced the new soil C input by approximately 35.5% during our 62-day labeling. In our experiment, the fnew value under elevated CO2 could be overestimated by up to 1.7 times if the alteration of 13C signatures in photosynthates caused by the change in CO2 concentration is ignored. For methodological clarification, we suggest that 1) 13C labeling is essential in all CO2 treatments to achieve CO2 concentration-dependent 13C signals in plants and soil, and that 2) the influence of elevated CO2 on soil C turnover can be estimated by the difference in the fnew under the two CO2 concentrations.

This study enabled the assessment of indoor CO2 levels and evaluated the relationship between occupancy numbers with CO2 levels in a Taiwan hospital. The measurements were conducted over four seasons for five working days (Monday to Friday), with sampling conducted simultaneously from 09:00 am to 5:00 pm and across six locations (for spatial variability): hall (H), registration and cashier (RC), waiting area (WA), occupational therapy room (OT), physical therapy room (PT), and outdoors (O). Based on the analysis, three of the five indoor sampling sites showed significant differences in seasonal CO2 concentrations (p

Data directly comparing CO2 absorbents tested in identical and clinically relevant conditions are scarce or non-existent. We therefore tested and compared the efficiency of 16 different brands of Ca(OH)2 based CO2 absorbents used as loose fill or a cartridge in a refillable canister under identical low flow conditions. CO2 absorbents efficiency was tested by flowing 160 mL/min CO2 into the tip of a 2 L balloon that was ventilated with an ADU anesthesia machine (GE, Madison, WI, USA) with a tidal volume of 500 mL and a respiratory rate of 10/min while running an O2/air FGF of 300 mL/min. After the 1020 mL refillable container was filled with a known volume of CO2 absorbent (derived from weighing the initial canister content and the product's density), the time for the inspired CO2 concentration (FICO2) to rise to 0.5% was measured. This test was repeated 4 times for each product. Because the two SpiraLith Ca® products (one with and one without indicator) are delivered as a cartridge, they had to be tested using their proprietary canister. The time (min) for FICO2 to reach 0.5% was normalized to 100 mL of product, and defined as the efficiency, which was compared amongst the different brands using ANOVA. Efficiency ranged from 50 to 100 min per 100 mL of product, and increased with increasing NaOH content (a catalyst), the exception being SpiraLith Ca® cartridge with color indicator (performing as well as the most efficient granular products) and the SpiraLith Ca® cartridge without color indicator (outperforming all others). Results indicated a spherical or bullet shape is less efficient in absorbing CO2 than broken fragments or cylinders, which in turn is less efficient than a hemispherical (disc) shape, which is in turn less efficient than a solid cartridge with a molded channel geometry. The efficiency of Ca(OH)2 based CO2 absorbent differs up to 100% on a volume basis. Macroscopic arrangement (cylindrical wrap with preformed channels versus granules), chemical composition (NaOH content), and granular shape all affect efficiency per volume of product. The data can be used to compare costs of the different products.

The rising global population is forcing the need for adapting alternative sustainable technologies for enhanced crop productivity. The CO2 Concentration Mechanisms (CCMs) evolved in algae to counter the inefficient CO2 fixing enzyme, RuBisCo and slower diffusion of CO2 in water offers good scope for the above purpose. The CCMs are single-celled CO2 supply mechanisms that depend on multiple CO2/HCO 3 − transporters and acclimation states and accumulate 100-fold more CO2 than low CO2 environments. Although some insights have been obtained regarding the CCMs of blue-green algae and green algae like Chlamydomonas reinhardtii, further progress needs to take place to understand the molecular and biochemical basis for intracellular transport of CO2. In this review, complete information pertaining to the core CCM is presented and discussed in light of the available literature. In addition to this, information on CO2/HCO 3 − sensing, photo-acclimation in low CO2, liquid-like nature of pyrenoid, untapped potential of high CO2 responses and high CO2 requiring mutants, and prospects of engineering CCM components into higher plants are presented and discussed.

This correction stands to correct a spelling error found in one of the contributor names. The author group request the third contributor name to cited and acknowledged as Chunyan Zhang and not Chuanyan Zhang. The original article has been corrected.

Changes in tree’s climate sensitivity during their ontogenetic development is best assessed with stem diameter classes, which can be calculated retrospectively from the cumulative ring width. Climate affects tree growth but the effect size can be modulated by other variables, including tree’s age and size. To assess how climate sensitivity changes over the life of a tree, previous studies mostly stratified trees into age classes, while cambial ring-age stratification (age-band decomposition) was less frequently used. However, trees do not age as other organisms and arguably age is mainly a proxy for size, which in contrast to age has been shown to affect wood anatomy and physiology. Stem diameter classes, calculated from cumulative ring width, could thus facilitate a more direct assessment of size effects. Here we compare these three methods, which differ regarding how they stratify data into age/size classes. We found that using age-band decomposition and cumulative ring-width classes had major advantages over the tree-age method: (a) age and size are decoupled from other temporal changes, like atmospheric CO2 concentration or nitrogen deposition, which excludes potential biases. (b) Shifts in climate sensitivity occur earlier than estimated by the tree-age method. (c) Younger/smaller classes can be assessed. Furthermore, direct comparison supports that size, rather than age, alters climate sensitivity. Therefore, the cumulative ring-width method appears to be the best approach to assess the effect of ontogenetic changes on a tree’s climate sensitivity. Understanding how climate sensitivity changes when trees get older and larger is important for forest ecology and management, climate reconstructions, global carbon models and can help to study age and height limitations of trees.

Temperature is one of the most important factors influencing physiological responses of rubber trees, so much so that it is a limiting factor in the expansion of rubber tree plantations in Brazil. The aim of this research was to investigate the influence of thermal stress, characterized by different thermal amplitudes, on photosynthesis, stomatal conductance, transpiration and leaf temperature. Seedlings of two rubber tree clones, RRIM 600 and CDC 312, were exposed to three different environments which were characterized by the following daily temperature ranges: 25–30 °C (E1); 25–42 °C (E2) and 10–42 °C (E3). Gas exchange and leaf temperature measurements were performed during the experimental period. The results show that gas exchange was affected by higher thermal amplitudes (E2 and E3). Photosynthesis, stomatal conductance and transpiration were lower in E2 and E3 environments, being more pronounced in E3. It was also observed that, due to the higher thermal amplitude in E2 and E3, there was an increase in intercellular CO2 concentration. Reduction in transpiration rates culminated in an increase in leaf temperature in E2 and E3, being more pronounced in the CDC 312 clone than in RRIM 600.

Past studies have shown that flowering times have accelerated over the last century. These responses are often attributed to rising temperature, although short-term field experiments with warming treatments have under-estimated accelerations in flowering time that have been observed in long-term field surveys. Thus, there appears to be a missing factor(s) for explaining accelerated flowering over the last century. Rising atmospheric CO2 concentration ([CO2]) is a possible candidate, and its contributions to affecting flowering time over historic periods are not well understood. This is likely because rising [CO2] is confounded with temperature in the field and preindustrial [CO2] studies are relatively rare. To address this, we tested the individual and interactive effects of rising [CO2] and temperature between preindustrial and modern periods on flowering time in the model system, Arabidopsis thaliana. We used a variety of genotypes originating from diverse locations, allowing us to test intraspecific responses to last-century climate change. We found that accelerated flowering time between the full-preindustrial and full-modern treatments was mainly driven by an interaction between rising [CO2] and temperature, rather than through the individual effects of either factor in isolation. Furthermore, accelerated flowering time was driven by enhanced plant growth rates and not through changes in plant size at flowering. Thus, the interaction between rising [CO2] and temperature may be key for explaining large accelerations in flowering times that have been observed over the last century and that could not be explained by rising temperature alone.

The Paris Agreement1 aims to ‘pursue efforts to limit the temperature increase to 1.5 °C above pre-industrial levels.’ However, it has been suggested that temperature targets alone are insufficient to limit the risks associated with anthropogenic emissions2,3. Here, using an ensemble of model simulations, we show that atmospheric CO2 increase—an even more predictable consequence of emissions than global temperature increase—has a significant direct impact on Northern Hemisphere summer temperature, heat stress, and tropical precipitation extremes. Hence in an iterative climate mitigation regime aiming solely for a specific temperature goal, an unexpectedly low climate response may have corresponding ‘dangerous’ changes in extreme events. The direct impact of higher CO2 concentrations on climate extremes therefore substantially reduces the upper bound of the carbon budget, and highlights the need to explicitly limit atmospheric CO2 concentration when formulating allowable emissions. Thus, complementing global mean temperature goals with explicit limits on atmospheric CO2 concentrations in future climate policy would limit the adverse effects of high-impact weather extremes. A 1.5 °C temperature target can have varying atmospheric CO2 concentrations associated with it. GCM simulations reveal CO2 increases have a direct impact on climate extremes, highlighting the need for climate policy to complement temperature goals with CO2 targets.

Correctly estimating the effect of elevated CO2 (eCO2) on biomass production is paramount for accurately projecting agricultural productivity, global carbon balances and climate changes. Plant physiology suggests that eCO2 should result in a strongly positive CO2 fertilisation effect (CFE) via positive effects on photosynthesis and water use efficiency. However, the CFE in CO2 experiments is often constrained because of other factors of which rainfall pattern is particularly important. Here, we apply a generally applicable, empirically derived relationship between the CFE and an index of seasonal rainfall balance (SRB), to identify how historical and projected future rainfall patterns modify the CFE using 25 native grassland sites in south-eastern (SE) Australia as a test case. We found that historical and projected rainfall produced SRBs that varied widely from year-to-year resulting in a CFE that was only positive in about 40% of years, with no or even negative biomass responses in the remainder of years; a finding that is in marked contrast to other studies that have not taken account of relationships between rainfall seasonality and plant responses to CO2. The dependence of the CFE on SRB also means that using the CFE from a specific eCO2 experiment can be misleading as the result will be heavily influenced by the SRB during the period of experimentation but this problem can be avoided by using a robust general relationship of the kind used in this study. Generalisations of grassland biomass responses to the rising CO2 concentration are contextual in terms of the variability in precipitation seasonality; as such, this provides a new lens by which to view aboveground responses to the rising CO2 concentration and fosters a novel approach for cross-site comparisons among experiments.

In order to correctly use the column-averaged atmospheric CO2 dry-air mole fraction (XCO2) data in the CO2 flux studies, XCO2 measurements retrieved from the Orbiting Carbon Observatory-2 (OCO-2) in 2015 were compared with those obtained from the global ground-based high-resolution Fourier Transform Spectrometer (FTS) participating in the Total Carbon Column Observing Network (TCCON). The XCO2 retrieved from three observing modes adopted by OCO-2, i.e., nadir, target, and glint, were separately validated by the FTS measurements at up to eight TCCON stations located in different areas. These comparisons show that OCO-2 glint mode yields the best qualitative estimations of CO2 concentration among the three operational approaches. The overall results regarding the glint mode show no obvious systematic biases. These facts may indicate that the glint concept is appropriate for not only oceans but also land regions. Negative systematic biases in nadir and target modes have been found at most TCCON sites. The standard deviations of XCO2 retrieved from target and nadir modes within the observation period are simi-lar, and larger than those from glint mode. We also used the FTS site in Beijing, China, to assess the OCO-2 XCO2 in 2016. This site is located in a typical urban area, which has been absent in previous studies. Overall, OCO-2 XCO2 agrees well with that from FTS at this site. Such a study will benefit the validation of the newly launched TanSat products in China.

A mathematical comparison between global carbon emissions and sequestration rate has been performed, which demonstrated that global environment is currently experiencing severe vulnerability to survive all living being on earth. The annual global carbon emission rate has been calculated, considering all forms of carbon dioxide emission from burning fossil fuel, misuse of terrestrial land use along with other sources. Consequently, the global carbon sequestrations by all sources of ocean sink, terrestrial absorption, and the earth sink, and associated factors have also been calculated. This was performed in order to determine the atmospheric CO2 concentration level increasing comparing several years of data. The mathematical calculation revealed that presently atmospheric CO2 concentration is increasing at the rate of 2.11% ppm for that past several years. The 60,000 ppm CO2 concentration into the atmosphere is the toxic level at which all living beings to cause die in 30 minutes. Since atmospheric CO2 is increasing rapidly, thus, I have calculated the survival period of all living being on earth by expressing a simple equation: $$\int \nolimits_{{400^{{( {2.11\% })}} }}^{60,000} ( {2017}) = 121{,}017{,}711.2$$ which revealed that all living beings on earth will become extinct in 121,017,712 years if we do not reduce the current level of CO2 emission.

This modeling study investigates the impacts of increasing atmospheric CO2 concentration on acidification in the East Sea. A historical simulation for the past three decades (1980 to 2010) was performed using the Hadley Centre Global Environmental Model (version 2), a coupled climate model with atmospheric, terrestrial and ocean cycles. As the atmospheric CO2 concentration increased, acidification progressed in the surface waters of the marginal sea. The acidification was similar in magnitude to observations and models of acidification in the global ocean. However, in the global ocean, the acidification appears to be due to increased in-situ oceanic CO2 uptake, whereas local processes had stronger effects in the East Sea. pH was lowered by surface warming and by the influx of water with higher dissolved inorganic carbon (DIC) from the northwestern Pacific. Due to the enhanced advection of DIC, the partial pressure of CO2 increased faster than in the overlying air; consequently, the in-situ oceanic uptake of CO2 decreased.

Oak pollen is a major respiratory allergen in Korea, and the distribution of oak trees is expected to increase by ecological succession and climate change. One of the drivers of climate change is increasing CO2, which is also known to amplify the allergy risk of weed pollen by inducing elevated allergenic protein content. However, the impact of CO2 concentration on tree pollen is not clearly understood due to the experimental difficulties in carrying out extended CO2 treatment. To study the response of pollen production of sawtooth oak trees (Quercus acutissima) to elevated levels of ambient CO2, three open-top chambers at the National Institute of Forest Science in Suwon, Korea were utilized with daytime (8 am–6 pm) CO2 concentrations of ambient (× 1.0, ~ 400 ppm), × 1.4 (~ 560 ppm), and × 1.8 (~ 720 ppm) treatments. Each chamber had three sawtooth oak trees planted in September 2009. One or two trees per chamber matured to bloom in 2016. Five to six catkins were selected per tree and polyethylene bags were attached to collect pollen grains. The total number of catkins per tree was counted and the number and weight of pollen grains per catkin were measured. Oak allergen—Que a 1 (Allergon Co., Uppsala, Sweden)—was extracted and purified to make an ELISA kit by which the antigen levels in the pollen samples were quantified. Total pollen counts per tree of the × 1.4 and × 1.8 treatments showed significant increase of 353 and 1299%, respectively, from the × 1.0 treatment (p

Elevated CO2 level in the atmosphere is expected to improve the tree growth rates and intrinsic water-use efficiency (iWUE). Although current results inferring from tree rings found the tree growth decline in water-limited area, it is still unclear whether spruce trees in humid southwestern China benefit from the increasing CO2. In this study, tree-ring width data were used to investigate the tree radial growth rate of Chuanxi spruce (Picea likiangensis var. balfouriana). Moreover, combining with the tree-ring carbon isotope date, we analyzed the physiological responses of Chuanxi spruce to rising CO2 concentrations in the atmosphere (Ca) associated with climatic change in southwestern China. From 1851 to 2009, iWUE of Chuanxi spruce rose by approximately 30.4%, and the ratio of atmospheric CO2 to leaf intercellular CO2 concentration (Ci/Ca) showed no significant trend in the study area. The result suggested that Chuanxi spruce used an active response strategy when Ca was significantly increased. iWUE showed a significant increasing trend in parallel with tree radial growth, indicating that the increasing iWUE resulted in an increase in radial growth. These results suggest that spruce forests in southwestern China have not shown declining trends under increasing Ca and climate change scenarios, in contrast to trees growing in water-limited areas. Therefore, spruce forests benefit from the increasing CO2 in the atmosphere in the humid areas of southwestern China.

MgO-based absorbent has been recognized as a promising CO2 absorbent at intermediate temperature, though the carbonation performance of pure MgO is poor. Researchers have been devoted to optimize the CO2 absorption ability via introducing alkali metal carbonates or nitrates. In this paper, the absorption performance of MgO-based absorbents promoted by alkali metal carbonates or modified by alkali metal nitrates has been summarized, and the affecting mechanism has been concluded. Alkali metal nitrates are essential for high absorption ability, and alkali metal carbonates facilitate high-temperature carbonation. Effects of fuel gas conditions and absorbent pelletization are also mentioned for practical applications. H2O can accelerate the carbonation rate effectively, but the influencing mechanism of H2O and the CO2 absorption stability in presence of H2O was not clearly reported. Further investigations on pelletized MgO-based absorbents modified by alkali metal salts considering regeneration conditions of high CO2 concentration are proposed based on the recent research findings.

Ecological approaches, such as functional groups (sensu Reynolds, FG) and exclusively morphological-based groups (sensu Kruk, MBFG), have provided a reliable tool for understanding phytoplankton responses to environmental conditions. Our study evaluated the concordance and the response of these two-functional classifications of the phytoplankton community to environmental variables in reservoirs of different trophic states (ultra-oligotrophic to meso-eutrophic). We also investigated the spatial and temporal concordance of the functional classifications with the taxonomic-based classification (species). Integrated water samples were collected in the euphotic zone in two climatic periods (summer and winter) to determine physical and chemical variables and phytoplankton. Higher water temperature and thermal stratification were observed in the summer, whereas higher free CO2 concentrations and mixing regime of water column in the winter. The 35 descriptors species showed a greater relationship to the trophic conditions of the reservoirs. The functional classifications revealed that the 17 FGs and 7 MBFGs were influenced primarily by seasonal variation of limnological conditions (water temperature, CO2 concentration, Zmix depth) and secondarily by trophic state of the reservoirs. Stronger similarity (higher than 0.70) was verified between species and FGs matrices (Mantel test, mainly) than between species and MBFGs ones. Procrustes and Mantel tests also evidenced high concordance between FGs and MBFGs matrices, exhibiting similar spatial and temporal distribution to environmental conditions. Thus, these ecological classifications demonstrated to be complementary tools, besides their particular degrees of detailing, to elucidate the functional responses of numerous phytoplankton species in studied tropical reservoirs.

Indoor airborne culturable fungi exposure has been closely linked to occupants’ health. However, conventional measurement of indoor airborne fungal concentration is complicated and usually requires around one week for fungi incubation in laboratory. To provide an ultra-fast solution, here, for the first time, a knowledge-based machine learning model is developed with the inputs of indoor air quality data for estimating the concentration of indoor airborne culturable fungi. To construct a database for statistical analysis and model training, 249 data groups of air quality indicators (concentration of indoor airborne culturable fungi, indoor/outdoor PM2.5 and PM10 concentrations, indoor temperature, indoor relative humidity, and indoor CO2 concentration) were measured from 85 residential buildings of Baoding (China) during the period of 2016.11.15–2017.03.15. Our results show that artificial neural network (ANN) with one hidden layer has good prediction performances, compared to a support vector machine (SVM). With the tolerance of ± 30%, the prediction accuracy of the ANN model with ten hidden nodes can at highest reach 83.33% in the testing set. Most importantly, we here provide a quick method for estimating the concentration of indoor airborne fungi that can be applied to real-time evaluation.

This paper presents the seasonality of vertical profiles of CO2 within 0–1100 m at a suburban site and discussions on the impacts of meteorological parameters on it. CO2 concentrations as well as metrological conditions were measured on June 2–18, July 7–22 (21 days, summer), October 10–20 (10 days, autumn) in 2012, and January 15–February 1 (12 days, winter), May 7–23 (10 days, spring) in 2013. The CO2 vertical profiles were affected by meteorological conditions, source emissions, urban canopy and other factors. The CO2 concentrations’ comparison analysis between different seasons including spring, summer (previously published results), autumn and winter suggests that the highest peak of the CO2 concentration (450.00 ± 14.78 ppm) occurred during winter (2013-01-23 at 09:00–09:55) with neutral stability class whereas the lowest peak of the CO2 concentration (389.88 ± 4.67 ppm) occurred during summer (2012-07-17 at 15:48–16:40) with moderately stable conditions. The high levels of CO2 concentrations were due to the accumulation caused by the stable atmosphere dominant during the measurement period. Atmospheric CO2 concentrations in summer can be lower near the surface than at elevated altitude under certain conditions because terrestrial photosynthesis dominated the industrial pollutant emissions at that time. However, in other seasons, CO2 profiles showed monotonically declining trends with altitudes.

The principal advantage of OCO-2 satellite transect as a remote sensor is to provide, in a cost-effective manner, information required for narrow and long strip coverage, utilizing narrow view angle. Based on the postulated advantages of OCO-2 satellite transect for multiple nation-wide monitoring, a satellite transect sampling approach has been specifically proposed with focus on administrative region-wide monitoring. This research idea was formulated by incorporating the concept of typical satellite remote sensing into in situ transect techniques. The OCO-2 satellite transect was quite useful in in comparing CO2 concentrations among administrative regions in Northeast Asia and better understanding the nature and extent of carbon intensity that occurs in transect sampling points. This transect sampling survey made it possible to identify area-wide patterns of CO2 concentration changing trends subject to many different influences (e.g. the effects of specific sources of land use), which cannot be acquired by typical GHG monitoring satellite such as GOSAT. The OCO-2 satellite transects break down the usual concept of area-wide mapping established as a typical satellite survey technique. The study concludes that OCO-2 satellite transect is demonstrably suitable as a reliable information source for detecting sufficient ground detail CO2 concentrations, including administrative region monitoring.

Poor ventilation in schools is associated with accumulation of indoor-generated pollutants, which is associated with “stuffy” air, elevated risk of infectious diseases and impaired learning outcomes. This survey in Albania was conducted as part of WHO’s efforts to facilitate assessments of indoor air quality and other environmental factors in schools in the European Region. The survey was conducted in 36 classrooms in 12 middle schools (eight urban and four rural) from December 2011 through March 2012. In each school, carbon dioxide (CO2) was continuously measured in three classrooms during one school week. Ventilation rates during classes were estimated using the build-up and steady-state mass balance equations utilizing CO2 concentration data, classroom occupancy and classroom volume. All 12 schools had gravimetric ventilation systems. Heating systems were absent or not operational in most schools. Average classroom temperatures during lessons varied from 9.1 to 14.4 °C (median 11.7 °C) with lower temperature associated with poorer ventilation. Weekly average CO2 levels during classes ranged from 1286 to 5546 ppm (median 2776 ppm) while average ventilation rates ranged from 0.8 to 3.6 (median 1.8) litres per second per person. Classrooms with indoor combustion heaters had higher indoor temperature, lower CO2 levels and higher levels of carbon monoxide (CO). WHO guidelines on 1- and 8-h CO exposure levels were exceeded in one classroom. Classroom CO2 levels were substantially above and ventilation rates below existing national and international guidelines. Detrimental impacts of poor ventilation on health and learning outcomes are likely to be substantial in Albanian schools during the cold season. Indoor temperature in most classrooms was below the commonly recommended levels.