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This paper compares the ideas contained in the main papers published on climate change since World War II to arrive at a suggested consensus of our present knowledge regarding climatic changes and their causes. Atmospheric carbon dioxide is only suggested as a cause in one theory, which, despite its wide acceptance by Politicians, the media, and the Public, ignores the findings in other studies, including the ideas found in the Milankovitch Cycles. It also does not explain the well-known NASA map of the changes between the global 1951–1978 and the 2010–2019 mean annual temperatures. The other theories by Oceanographers, Earth scientists, and Geographers fit together to indicate that the variations in climate are the result of differential solar heating of the Earth, resulting in a series of processes redistributing the heat to produce a more uniform range of climates around the surface of the Earth. Key factors are the shape of the Earth and the Milankovitch Cycles, the distribution of land and water bodies, the differences between heating land and water, ocean currents and gateways, air masses, and hurricanes. Low atmospheric carbon dioxide levels during cold events could result in too little of this gas to support photosynthesis in plants, resulting in the extermination of most life on Earth as we know it. The 23 ka Milankovitch cycle has begun to reduce the winter insolation received at the surface of the atmosphere in the mid-latitudes of the Northern Hemisphere starting in 2020. This results in extreme weather as the winter insolation reaching the surface of the atmosphere in the higher latitudes of the Northern Hemisphere decreases while the summer air temperatures increase. It heralds the start of the next glaciation. A brief outline is given of some of the climatic changes and consequences that may be expected in western Canada during the next 11.5 ka. [ABSTRACT FROM AUTHOR]

A nonlinear dynamical model for the plankton population in a fixed sea area under the influence of asymmetric multiple factors, including atmospheric CO 2 concentration, atmospheric temperature, nutrient concentration, seawater temperature, light intensity, and predator density is proposed to address the survival of the plankton population due to global warming. The model's accuracy is confirmed by comparison with actual data, and numerical simulations are carried out to justify the relevant findings. The results suggest that increasing plankton's ability to absorb atmospheric CO 2 or regulate atmospheric temperature can help to mitigate global warming. Furthermore, if the population density of fish, the primary predator of plankton, falls within a certain range, the increase in atmospheric temperature will be mitigated. Additionally, the stability conditions for the suggested model are obtained, along with the equilibrium point of the system. Overall, this paper considers the effects of asymmetric multifactor interaction on plankton population density and establishes a mathematical connection between environmental ecosystems and plankton that might aid in addressing the challenges posed by global warming and preserving the plankton population. [ABSTRACT FROM AUTHOR]

Indoor air quality and thermal conditions are important considerations when designing indoor spaces to ensure occupant health, satisfaction, and productivity. Carbon dioxide (CO2) concentration and indoor air temperature are two measurable parameters to assess air quality and thermal conditions within a space. Occupants are progressively affected by the indoor environment as the time spent indoors prolongs. Specifically, there is an interest in carrying out investigations on the indoor environment through surveying existing Heating, Ventilation, Air Conditioning (HVAC) system operations in classrooms. Indoor air temperature and CO2 concentration in multiple lecture halls in Toronto, Canada were monitored; observations consistently show high indoor air temperature (overheating) and high CO2 concentration. One classroom is chosen as a representative case study for this paper. The results verify a strong correlation between the number of occupants and the increase in air temperature and CO2 concentration. Building Energy Simulation (BES) is used to investigate the causes of discomfort in the classroom, and to identify methods for regulating the temperature and CO2 concentration. This paper proposes retro-commissioning strategies that could be implemented in institutional buildings; specifically, the increase of outdoor airflow rate and the addition of occupancy-based pre-active HVAC system control. The proposed retrofit cases reduce the measured overheating in the classrooms by 2-3 °C (indoor temperature should be below 23 °C) and maintain CO2 concentration under 900 ppm (the CO2 threshold is 1000 ppm), showing promising improvements to a classroom's thermal condition and indoor air quality. [ABSTRACT FROM AUTHOR]

2–(1H–1,2,4–Triazol–3–yl)phenol (CAT–1) was used as an organocatalyst for the coupling reaction of CO2 and epoxides at an ambient temperature and atmospheric CO2 pressure (1 bar). This compound has a structure in which a hydrogen bond donor, a hydrogen bond acceptor, and another hydrogen bond donor are adjacent in sequence in a molecule. The binary catalytic system of CAT–1/nBu4NI showed TON = 19.2 and TOF = 1.60 h−1 under 1 bar CO2 at room temperature within 12 h using 2–butyloxirane. Surprisingly, the activity of CAT–1, in which phenol and 1H–1,2,4–triazole are chemically linked, showed a much greater synergistic effect than when simply mixing the same amount of phenol and 1H–1,2,4–triazole under the same reaction conditions. In addition, our system showed a broad terminal and internal epoxide substrate scope. [ABSTRACT FROM AUTHOR]

Research on carbon management is fueled by the growing concern over rising carbon dioxide (CO2) levels in the atmospheric air and its possible impacts on the climate. In this study, we proposed a method of CO2 separation from atmospheric air. This study aimed to investigate the effects of CO2 enrichment on the air temperature inside a greenhouse using a hollow fiber (HF) membrane system. The experiment was conducted over a period of 30 days in two experimental conditions: 15 days without CO2 enrichment (WCS) and 15 days with CO2 enrichment (CS). Results showed that the mean CO2 concentration and air temperature were highest inside the greenhouse during the CS period, with values of 1120 ppm and 37.42 °C, respectively. Regression analysis revealed a positive correlation between CO2 concentration and temperature during the CS period (R2 = 0.628). The HF membrane system was found to be effective in increasing both the CO2 concentration and air temperature inside the greenhouse. However, the system also has limitations, including the cost, maintenance, and suitability for all types of crops. Further experiments are needed to address these limitations and determine the optimal CO2 concentration for different kinds of crops growing in greenhouses. [ABSTRACT FROM AUTHOR]

Air quality monitoring in cities is significant for both human health and environment. Here, an innovative miniaturized active air sampler wearable by free-flying birds is presented. The device integrates a GPS logger and atmospheric calibrated sensors allowing for high spatiotemporal resolution measurements of carbon dioxide (CO2) concentration, barometric pressure, air temperature, and relative humidity. A field campaign, carried out from January to June 2021, involved the repeated release of homing pigeons (Columba livia) from downtown Rome (Italy), to sample the air on their way back to the loft, located in a rural area out of the city. The measurements suggest the importance of green urban areas in decreasing CO2 levels. Moreover, a positive relation between CO2 levels, relative humidity, and air temperature was revealed. In contrast, a negative relation with distance from the point of release, month, and time of day was found. Flight speed and the altitude of flight were related to rising CO2 levels. The easy use of such devices paves the way for the application of miniaturized air samplers to other synanthropic species (i.e., gulls), making birds convenient biomonitors for the urban environment. [ABSTRACT FROM AUTHOR]

Accurate modeling for nonlinear and nonstationary rainfall-runoff processes is essential for performing hydrologic practices effectively. This paper proposes two hybrid machine learning models (MLMs) coupled with variational mode decomposition (VMD) to enhance the accuracy for daily rainfall-runoff modeling. These hybrid MLMs consist of VMD-based extreme learning machine (VMD-ELM) and VMD-based least squares support vector regression (VMD-LSSVR). The VMD is employed to decompose original input and target time series into sub-time series called intrinsic mode functions (IMFs). The ELM and LSSVR models are selected for developing daily rainfall-runoff models utilizing the IMFs as inputs. The performances of VMD-ELM and VMD-LSSVR models are evaluated utilizing efficiency and effectiveness indices. Their performances are also compared with those of VMD-based artificial neural network (VMD-ANN), discrete wavelet transform (DWT)-based MLMs (DWT-ELM, DWT-LSSVR, and DWT-ANN) and single MLMs (ELM, LSSVR, and ANN). As a result, the VMD-based MLMs provide better accuracy compared with the single MLMs and yield slightly better performance than the DWT-based MLMs. Among all models, the VMD-ELM and VMD-LSSVR models achieve the best performance in daily rainfall-runoff modeling with respect to efficiency and effectiveness. Therefore, the VMD-ELM and VMD-LSSVR models can be an alternative tool for reliable and accurate daily rainfall-runoff modeling. [ABSTRACT FROM AUTHOR]

The relevance and role of aesthetic, thermal and physical facets to climatic tourism potential over Algeria at 12.00 UTC (13.00 local time) are analyzed. This role is revealed using the Climate-Tourism-Information-Scheme (CTIS) elaborated for six Algerian cities having indisputable tourism potentiality and representing different regions and climate regimes: Coastline, Highland and Sahara zone. In this paper, the relevance of the use of the 10-day time-scale resolution of the physiologically equivalent temperature (PET) derived from the body-atmosphere energy balance as well as the importance of the CTIS at this time-scale resolution is illustrated. The CTIS diagrams produced concern the period 1986–2015 and comprise detailed information on the frequencies of the occurrence of different climatological and human biometeorological parameters throughout the year, which could help tourists to plan ahead their vacations. A significant upward trend in discomfort conditions, as well as a substantial decline in human thermal comfort acceptability, are observed during the period of the study. The obtained results could help enormously in the promotion of tourism and leisure services in the country as a highly promising economic sector in the future and those who are involved, such as tour operators, by diversifying their products through the provision of alternative types of tourism offerings in line with the climate conditions. [ABSTRACT FROM AUTHOR]

Assessing human impacts on climate and biodiversity requires an understanding of the relationship between the concentration of carbon dioxide (CO2) in the Earth's atmosphere and global temperature (T). Here I explore this relationship empirically using comprehensive, recently-compiled databases of stable-isotope proxies from the Phanerozoic Eon (~540 to 0 years before the present) and through complementary modeling using the atmospheric absorption/transmittance code MODTRAN. Atmospheric CO2 concentration is correlated weakly but negatively with linearly-detrended T proxies over the last 425 million years. Of 68 correlation coefficients (half non-parametric) between CO2 and T proxies encompassing all known major Phanerozoic climate transitions, 77.9% are non-discernible (p > 0.05) and 60.0% of discernible correlations are negative. Marginal radiative forcing (ΔRFCO2), the change in forcing at the top of the troposphere associated with a unit increase in atmospheric CO2 concentration, was computed using MODTRAN. The correlation between ΔRFCO2 and linearly-detrended T across the Phanerozoic Eon is positive and discernible, but only 2.6% of variance in T is attributable to variance in ΔRFCO2. Of 68 correlation coefficients (half non-parametric) between ΔRFCO2 and T proxies encompassing all known major Phanerozoic climate transitions, 75.0% are non-discernible and 41.2% of discernible correlations are negative. Spectral analysis, autoand cross-correlation show that proxies for T, atmospheric CO2 concentration and ΔRFCO2 oscillate across the Phanerozoic, and cycles of CO2 and ΔRFCO2 are antiphasic. A prominent 15 million-year CO2 cycle coincides closely with identified mass extinctions of the past, suggesting a pressing need for research on the relationship between CO2, biodiversity extinction, and related carbon policies. This study demonstrates that changes in atmospheric CO2 concentration did not cause temperature change in the ancient climate. [ABSTRACT FROM AUTHOR]