Global Warming Research Articles

Cooling and optimizing urban heat island based on a thermal knowledge-informed multi-type ant colony model

In the context of rapid urbanization and global warming, the urban heat island (UHI) intensifies the risk of heat-related mortality, endangering the health of urban residents. Urban greening effectively mitigates severe urban heating climates, but increasing green space without restrictions is undesirable due to the scarcity of urban land. Accurately characterizing the scope and intensity of UHI and determining the spatial location of the area that needs to be optimized are necessary. In this study, an inverse S-shaped function was used to fit the urban-rural temperature attenuation, whose parameters explicitly describe the properties of UHI. Additionally, a thermal knowledge-informed multi-type ant colony model was proposed to cool UHI automatically. A case study of Wuhan showed that: (1) the fitting effect of the inverse S-shaped function is desirable with the adjusted R2 exceeding 0.97, and the derived parameters with clear physical meanings avoid subjectivity in describing thermal characteristics; (2) high-level heat island of the main urban areas can be reduced by 7.7%–8.5% after land use optimization; and (3) a comparison with the traditional multi-type ant colony model verifies that the model proposed in this study can avoid excessive dispersion of the optimized pixels whose land use types are modified and achieve more reasonable and stable optimization results. This study provides useful exploratory tools for sustainable urban planning, heat mitigation solutions, and other urban retrofitting.

Effect of generator temperature on steam ejector performance in renewable refrigeration cycle considering wet steam model and dry steam model

The rise in global warming has led to an increased utilization of cooling systems. High energy consumption associated with common refrigeration cycles not only contributes to air pollution but also intensifies the consumption of fossil fuels. Consequently, the imperative to conserve energy has become paramount in today's world. One of the methods to decrease energy consumption involves employing systems capable of harnessing waste heat from industries, solar energy, and other sources. The ejector refrigeration cycle (ERC) stands as an example of such systems. In present study, the impact of elevating the generator temperature on various aspects such as flow behavior in the ejector, aerodynamic shocks, entrainment ratio (ER), and entropy production was examined. The investigation encompassed both wet steam model (WSM) and dry steam model (DSM). Based on the findings, it was observed that with an increase in generator temperature, the ER decreases while the production entropy increases. In the WSM, the liquid mass fraction (LMF) also experiences an increase. Additionally, the Mach number distribution in the DSM surpasses that of the WSM and the temperature drop in the DSM is greater compared to the WSM. With the rise in generator temperature from 388 K to 418 K, both the DSM and WSM exhibit a decrease in ER by 52.9% and 58.7%, respectively. Furthermore, the production entropy experiences a substantial increase of 180% and 206% for the DSM and WSM, respectively.

Two-pathway spatiotemporal representation learning for extreme water temperature prediction

Accurate predictions of extreme water temperatures are criticalto understanding the variability of the marine environment and reducing marine disasters maximized by global warming. In this study, we propose a two-pathway framework with separated spatial and temporal encoders for accurate prediction of water temperature, especially extremely high water temperature, through effective spatiotemporal representation learning. The spatial and temporal encoder networks based on the Transformer’s self-attention mechanism performs the task of predicting the water temperature time series at the 16 coastal locations around the Korean Peninsula for the seven consecutive days ahead at daily intervals with various combinations of patch embedding methods, positional embedding for for spatial features. Comparative experiments with conventional deep convolutional and recurrent networks are also conducted for comparison. By comparing and assessing these results, the proposed two-pathway framework can improve the predictability of extremely high coastal water temperature by better capturing spatiotemporal interrelationships and long-range dependencies from open ocean and regional sea, and further determines the optimal architectural details of self-attention-based spatial and temporal encoders. Furthermore, to examine the explainability of the proposed model and its consistency with domain knowledge, spatial and temporal attention maps are visualized and analyzed that represents weights for spatiotemporal input sequences that are more relevant to predict for future predictions.

Predicting Current and Future Habitat Suitability of an Endemic Species Using Data-Fusion Approach: Responses to Climate Change

Fritillaria imperialis L., an indicator plant species in Iran, is facing threats and its population has declined in recent years. To provide insights into the drivers affecting its loss, this research aims to identify the effects of three groups of factors, including climate, soil, and physiographic variables, on the current and future spatial distributions of F. imperialis. For this purpose, we used five machine learning algorithms as well as an ensemble forecasting of species distribution approach to explain the geographical distributions of the species as a function of these factors. In addition, we used two shared socio-economic pathways scenarios – SSP 1-2.6 and SSP 5-8.5 – to project the future distributions of F. imperialis in 2030, 2050, 2070, and 2090. Based on evaluation indices, area under the ROC curve (AUC) and true skill statistic (TSS), the Random Forest (RF) model generated the strongest prediction of the distribution of F. imperialis (TSS>0.9 and AUC>0.9). No significant difference observed among the three datasets (climate-only variables, climate + physiography variables, and climate + physiography + soil variables) in terms of AUC values. In models using climate + physiography + soil datasets, soil electrical conductivity, clay, and pH emerged as the most important variables affecting the growth and development of F. imperialis while climate factors played a lesser role in its distribution. Future projections revealed different patterns when using the optimistic (SSP 1-2.6) and pessimistic (SSP 5-8.5) socio-economic pathway scenarios and either the climate only or climate + physiography models. The climate + physiography + soil model produced similar prediction patterns for the scenarios. The climate-only models predicted larger areas suitable for crown imperial in the future than did the climate + physiography + soil model. These results emphasize the consideration of factors beyond climate scenarios when modeling biological responses to global warming and regional climate change.

Experimental and kinetic evaluation on cobalt Salen conjugated organic polymers for CO2 cycloaddition reactions and iodine vapor adsorption

The fixing reactions of carbon dioxide with epoxides will not only help to ameliorate the problem of global warming, but also facilitate the synthesis of cyclic carbonates that have a multitude of applications. Herein, a new sequence of Salen cobalt complexes adjusted with different counterions and interconnected with pyrene group were synthesized through Friedel–Crafts alkylation, which were served as conjugated organic polymers (SP-COPs) for taking advantage of catalytic CO2 fixation reactions and iodine adsorption. Further characterizations were carried out through FT-IR, UV, TGA, and SEM to comprehend the intact structure, thermal stability, morphology and other physical and chemical properties. All materials exhibited effective catalytic performance, and in particular, SP-COP-1 with co-catalyst of TBAI achieved 96.2 % conversion under ultra-mild conditions. The Ea was obtained to be 46.4 kJ·mol−1 by performing kinetic experiments at different temperatures by fitting the experimental data. The performance of iodine vapor adsorbed by these materials at ambient pressure of 75 °C reached 2.8 g·g−1, 2.2 g·g−1 and 2.6 g·g−1 respectively, and the adsorption process is describable in terms of pseudo-first-order and pseudo-second-order adsorption kinetics.

Nonequilibrium Fluctuations of Global Warming

Abstract While the warming trends of Earth’s mean temperature are evident at climatological scales, the local temperature at shorter time scales are highly fluctuating. Here we show that the probabilities of such fluctuations are characterized by a special symmetry typical of small systems out of equilibrium. Their nearly universal properties are linked to the fluctuation theorem and reveal that the progressive warming is accompanied by growing asymmetry of temperature distributions. These statistics allow us to project the global temperature variability in the near future, in line with predictions from climate models, providing original insight about future extremes.

L-arginine alleviates heat stress-induced mammary gland injury through modulating CASTOR1-mTORC1 axis mediated mitochondrial homeostasis

As global warming intensifies, extreme heat is becoming increasingly frequent. These extreme heatwaves have decreased the milk production of dairy animals such as cows and goats and have caused significant damage to the entire dairy industry. It is known that heat stress (HS) can induce the apoptosis and autophagy of mammary epithelial cells (MECs), leading to a decrease in lactating MECs. L-arginine can effectively attenuate HS-induced decreases in milk yield, but the exact mechanisms are not fully understood. In this study, we found that HS upregulated the arginine sensor CASTOR1 in mouse MECs. Arginine activated mTORC1 activity through CASTOR1 and promoted mitochondrial biogenesis through the mTORC1/PGC-1α/NRF1 pathway. Moreover, arginine inhibited mitophagy through the CASTOR1/PINK1/Parkin pathway. Mitochondrial homeostasis ensures ATP synthesis and a stable cellular redox state for MECs under HS, further alleviating HS-induced damage and improving the lactation performance of MECs. In conclusion, these findings reveal the molecular mechanisms by which L-arginine relieves HS-induced mammary gland injury, and suggest that the intake of arginine-based feeds or feed additives is a promising method to increase the milk yield of dairy animals in extreme heat conditions.

Power Generation Using Gravity

Abstract: In recent times due to effect of pollution and global warming there is a need for generating power from renewable sources. The reason for generating power using gravity is that it is available all over the Earth, abundant and consistent too. This method utilizes the force of gravity to drive mechanical systems, such as falling weights or water, which in turn generate electricity. Due to the development and modernization the electricity demand is increasing at high extent. To fulfil this demand globally which is without any harmful effect on environment is possible by using gravity power generation. In recent times due to effects of pollution there is a need for generating power from renewable sources. In this project, the gravitational energy of a heavy particle is converted to the electrical energy. When the heavy particle falls down from a higher altitude to a lower one, its potential energy is converted into the kinetic energy. Then this energy is converted to electricity by using a synchronous motor. When increasing the altitude of the load, the lighting time increases. If load increases, power production also increases

Estimation of Electric Vehicle Range Using Artificial Neural Networks

Abstract: This paper presents a project that addresses the transportation sector's rapid growth contributes to pollution through conventional fossil fuel vehicles emitting harmful gases, leading to global warming. Electric vehicles (EVs) offer a cleaner alternative, but range anxiety hinders widespread adoption. Range prediction, crucial for EV practicality, estimates travel distance on a single charge, considering factors like battery capacity, driving conditions, and weather. Accurate models, rooted in deep knowledge of EV technology and real-world driving, are essential. Our proposed solution employs a machine learning approach, integrating physical and environmental variables to minimize range anxiety, empower informed decision-making, and enhance the overall electric vehicle experience, promoting sustainable transportation

Bioprospecting for plant resilience to climate change: mycorrhizal symbionts of European and American beachgrass (Ammophila arenaria and Ammophila breviligulata) from maritime sand dunes.

Climate change and global warming have contributed to increase terrestrial drought, causing negative impacts on agricultural production. Drought stress may be addressed using novel agronomic practices and beneficial soil microorganisms, such as arbuscular mycorrhizal fungi (AMF), able to enhance plant use efficiency of soil resources and water and increase plant antioxidant defence systems. Specific traits functional to plant resilience improvement in dry conditions could have developed in AMF growing in association with xerophytic plants in maritime sand dunes, a drought-stressed and low-fertility environment. The most studied of such plants are European beachgrass (Ammophila arenaria Link), native to Europe and the Mediterranean basin, and American beachgrass (Ammophila breviligulata Fern.), found in North America. Given the critical role of AMF for the survival of these beachgrasses, knowledge of the composition of AMF communities colonizing their roots and rhizospheres and their distribution worldwide is fundamental for the location and isolation of native AMF as potential candidates to be tested for promoting crop growth and resilience under climate change. This review provides quantitative and qualitative data on the occurrence of AMF communities of A. arenaria and A. breviligulata growing in European, Mediterranean basin and North American maritime sand dunes, as detected by morphological studies, trap culture isolation and molecular methods, and reports on their symbiotic performance. Moreover, the review indicates the dominant AMF species associated with the two Ammophila species and the common species to be further studied to assess possible specific traits increasing their host plants resilience toward drought stress under climate change.

Pivotal Impact Factors in Photocatalytic Reduction of CO2 to Value-Added C1 and C2 Products.

Over the past decades, CO2 greenhouse emission has been considerably increased, causing global warming and climate change. Indeed, converting CO2 into valuable chemicals and fuels is a desired option to resolve issues caused by its continuous emission into the atmosphere. Nevertheless, CO2 conversion has been hampered by the ultrahigh dissociation energy of C=O bonds, which makes it thermodynamically and kinetically challenging. From this prospect, photocatalytic approaches appear promising for CO2 reduction in terms of their efficiency compared to other traditional technologies. Thus, many efforts have been made in the designing of photocatalysts with asymmetric sites and oxygen vacancies, which can break the charge distribution balance of CO2 molecule, reduce hydrogenation energy barrier and accelerate CO2 conversion into chemicals and fuels. Here, we review the recent advances in CO2 hydrogenation to C1 and C2 products utilizing photocatalysis processes. We also pin down the key factors or parameters influencing the generation of C2 products during CO2 hydrogenation. In addition, the current status of CO2 reduction is summarized, projecting the future direction for CO2 conversion by photocatalysis processes.

Observed Energetic Adjustment of the Arctic and Antarctic in a Warming World

Abstract Satellite observations reveal that decreasing surface albedo in both polar regions is increasing the absorption of solar radiation, but the disposition of this absorbed energy is fundamentally different. Fluxes of absorbed solar radiation, emitted thermal radiation, and net energy imbalances are assessed for both polar regions for the last 21 years in the Clouds and Earth’s Radiant Energy System record. Arctic absorbed solar radiation is increasing at 0.98 ± 0.69 W m−2 decade−1, consistent with the anticipated response to sea ice loss. However, Arctic thermal emission is responding at a similar rate of 0.94 ± 0.55 W m−2 decade−1. This is surprising since the radiative impact of ice loss would be expected to favor increasing solar absorption. We find however, that clouds substantially mask trends in Arctic solar absorption relative to clear sky while having only a modest impact on thermal emission trends. As a result, the Arctic net radiation imbalance has not changed over the period. Furthermore, variability of absorbed solar radiation explains two-thirds of the variability in annual thermal emission suggesting that Arctic thermal fluxes rapidly adjust to offset changes in solar absorption and re-establish equilibrium. Conversely, Antarctic thermal emission is not responding to the increasing (although not yet statistically significant) solar absorption of 0.59 ± 0.64 W m−2 decade−1 with less than a third of the annual thermal variability explained by accumulated solar absorption. The Arctic is undergoing rapid adjustment to increasing solar absorption resulting in no change to the net energy deficit, while increasing Antarctic solar absorption represents additional energy input into the Earth system. Significance Statement The polar regions of Earth are undergoing ice loss through ongoing global warming, reducing the ice cover and decreasing solar reflectivity, which would be expected to warm these regions. We use satellite observations to measure the trends in solar absorption and emitted thermal radiation over the Arctic and Antarctic for the last two decades. Arctic thermal emission is increasing at a compensating rate to solar absorption with a close relationship between these processes. Conversely, Antarctic thermal emission is not responding to solar absorption demonstrating that Antarctic surface temperatures are not significantly influenced by the region’s reflectivity. The Arctic is undergoing rapid adjustment to increasing solar absorption through warming, while increasing Antarctic solar absorption represents additional energy input into the Earth system.

A Role of Biosynthesized Zinc Oxide Nanoparticles (ZnO NPs) for Enhancing Seed Quality: A Review

Abiotic and biotic stresses impact seed growth, resulting in economic losses. Seeds are being subjected to an increasing number of biotic and abiotic stress combinations as a result of global warming and climate change, which has adverse effects on their growth and production. Drought, flood, salinity, heavy mineral contamination, cold, and heat were all found to have a negative impact on seed germination. Because of their massive surface area-to-volume ratio, nanoparticles—microscopic pieces with a nanoscale dimension ranging from 1-100 nm—have exceptional thermal conductivity, catalytic reactivity, nonlinear optical performance, and chemical durability. There are various methods for creating nanoparticles, such as chemical, physical, and biological ones. However, because dangerous chemical compounds are used as reducing agents, the chemical and physical procedures are expensive, complicated, and might be hazardous to the environment. The synthesis of nanoparticles using green approaches may be easily scaled up, and they are also cost-effective. Because of their superior qualities, greenly coordinated nanoparticles are currently preferred over traditionally delivered NPs. Green synthesis approaches are particularly appealing due to their ability to reduce nanoparticle toxicity. The use of vitamins, amino acids, and plant extracts has increased as a result. While dangerous and extremely hazardous substances are used in the chemical and physical processes that may cause environmental issues, capping and reducing agents are essential to the synthesis of nanoparticles. The capping or reducing agent used in physical and chemical processes is expensive. When used as a seed treatment, nanoparticles can enhance germination as well as the length, vigor, viability, and quality of the seedlings. This paper aims to provide an overview and evaluation of zinc oxide nanoparticles (ZnO NPs) as a potential substitute for biosynthesised nanoparticles in seed quality improvement.

Anthropogenic changes of interannual-to-decadal climate variability in CMIP6 multi-ensemble simulations

Abstract As well as having an impact on the background state of the climate, global warming due to human activities could affect its natural oscillations and internal variability. In this study, we use four initial-condition ensembles from the CMIP6 framework to investigate the potential evolution of internal climate variability under different warming pathways for the 21st century. Our results suggest significant changes in natural climate variability, and point to two distinct regimes driving these changes. First, a decrease of internal variability of surface air temperature at high latitudes and all frequencies, associated with a poleward shift and the gradual disappearance of sea-ice edges, which we show to be an important component of internal variability. Second, an intensification of the interannual variability of surface air temperature and precipitation at low latitudes, which appears to be associated with the El Niño–Southern Oscillation (ENSO). This second regime is particularly alarming because it may contribute to making the climate more unstable and less predictable, with a significant impact on human societies and ecosystems.

Modulated Trends in Arctic Surface Air Temperature Extremes as a Fingerprint of Climate Change

Abstract Strengthened by polar amplification, Arctic warming provides direct evidence for global climate change. This analysis shows how Arctic surface air temperature (SAT) extremes have changed throughout time. Using ERA5, we demonstrate a pan-Arctic (>60°N) significant upward SAT trend of +0.62°C decade−1 since 1979. Due to this warming, the warmest days of each month in the 1980s to 1990s would be considered average today, while the present coldest days would be regarded as normal in the 1980s to 1990s. Over 1979–2021, there was a 2°C (or 7%) reduction of pan-Arctic SAT seasonal cycle, which resulted in warming of the cold SAT extremes by a factor of 2 relative to the SAT trend and dampened trends of the warm SAT extremes by roughly 25%. Since 1979, autumn has seen the strongest increasing trends in daily maximum and minimum temperatures, as well as counts of days with SAT above the 90th percentile and decreasing trends in counts of days with SAT below the 10th percentile, consistent with rapid Arctic sea ice decline and enhanced air–ocean heat fluxes. The modulated SAT seasonal signal has a significant impact on the timing of extremely strong monthly cold and warm spells. The dampening of the SAT seasonal fluctuations is likely to continue to increase as more sea ice melts and upper-ocean warming persists. As a result, the Arctic winter cold SAT extremes may continue to exhibit a faster rate of change than that of the summer warm SAT extremes as the Arctic continues to warm. Significance Statement As a result of global warming, the Arctic Ocean’s sea ice is receding, exposing more and more areas to air–sea interactions. This reduces the range of seasonal changes in Arctic surface air temperatures (SAT). Since 1979, the reduced seasonal SAT signal has decreased the trend of warm SAT extremes by 25% over the background warming trend and doubled the trend of cold SAT extremes relative to SAT trends. A substantial number of warm and cold spells would not have been identified as exceptional if the reduction of the Arctic SAT seasonal amplitudes had not been taken into account. As the Arctic continues to warm and sea ice continues to diminish, seasonal SAT fluctuations will become more dampened, with the rate of decreasing winter SAT extremes exceeding the rate of increasing summer SAT extremes.

Impact of Parameterized Convection on the Storm Track and Near-Surface Jet Response to Global Warming: Implications for Mechanisms of the Future Poleward Shift

Abstract While a poleward shift of the near-surface jet and storm track in response to increased greenhouse gases appears to be robust, the magnitude of this change is uncertain and differs across models, and the mechanisms for this change are poorly constrained. An intermediate complexity GCM is used in this study to explore the factors governing the magnitude of the poleward shift and the mechanisms involved. The degree to which parameterized subgrid-scale convection is inhibited has a leading-order effect on the poleward shift, with a simulation with more convection (and less large-scale precipitation) simulating a significantly weaker shift, and eventually no shift at all if convection is strongly preferred over large-scale precipitation. Many of the physical processes proposed to drive the poleward shift are equally active in all simulations (even those with no poleward shift). Hence, we can conclude that these mechanisms are not of leading-order significance for the poleward shift in any of the simulations. The thermodynamic budget, however, provides useful insight into differences in the jet and storm track response among the simulations. It helps identify midlatitude moisture and latent heat release as a crucial differentiator. These results have implications for intermodel spread in the jet, hydrological cycle, and storm track response to increased greenhouse gases in intermodel comparison projects.

Impact of Climate Change on Extreme Rainfall Events and Pluvial Flooding Risk in the Vojvodina Region (North Serbia)

Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring in the Vojvodina region, covering both past (1971–2019) and future (2020–2100) periods. We utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, selecting the RCP8.5 scenario to examine future Rx3day amounts. The probabilities of occurrences of Rx3day were modeled using the GEV distribution, while the number of events where Rx3day in spring exceeds specific thresholds was modeled using the Poisson distribution. The results indicate that Rx3day with a ten-year return period during the spring months is expected to increase by 19% to 33%. Additionally, the probabilities of having more than one event where Rx3day exceeds thresholds are projected to rise by 105.6% to 200.0% in the future compared to the historical period. The analysis comparing the design values of Rx3day with future projections for the period 2020–2100 revealed that 51 drainage systems are likely to function without difficulties under future climate conditions. However, for the remaining 235 drainage systems, an increased risk of pluvial flooding was identified, as their design precipitation amounts are lower than the future projections. This study reveals that analyzing extreme rainfall events in the context of climate change yields crucial information that facilitates effective planning and policy making in water management, particularly flood protection.

Reliable Physics Demand Revision of the IPCC Global Warming Potentials

The Global Warming Potentials (GWP) of the Intergovernmental Panel on Climate Change (IPCC) in Table 2.14 of the Fourth Assessment Report (AR4) show the increase in warming by methane (CH4) and nitrous oxide (N2O) is 21 and 310 times respectively that of CO2. There has been wide acceptance of these values since publishing in 2007. Nevertheless, they are inaccurate. This study uses accurate methods to calculate the impacts of CO2, CH4, and N2O on the warming of the atmosphere. For example, this quantitative analysis from reliable physics shows the contribution of CO2 to warming at Amsterdam is 0.0083oC out of a difference of 26oC. The warming effect of CH4 on the Earth’s atmosphere is 0.408% of that of CO2, and the warming by N2O is 0.085% of that of CO2. Thus, the warming effects of CO2, CH4, and N2O are too small to measure. The invalidity of the methane and nitrous oxide values indicates the GWPs of the remaining approximately sixty chemicals in the Table 2.14 list are also invalid. A recommendation is that the IPCC consider revising or retracting the GWP values in Table 2.14.

Comparison and Evaluation of Five Global Land Cover Products on the Tibetan Plateau

The Tibetan Plateau (TP) region contains maximal alpine grassland ecology at the mid-latitudes. This region is also recognized as an ecologically fragile and sensitive area under the effects of global warming. Regional climate modeling and ecosystem research depend on accurate land cover (LC) information. In order to obtain accurate LC information over the TP, the reliability and precision of five moderate/high-resolution LC products (MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 in 2020) were analyzed and evaluated in this study. The different LC products were compared with each other in terms of areal/spatial consistency and assessed with four reference sample datasets (Geo-Wiki, GLCVSS, GOFC-GOLD, and USGS) using the confusion matrix method for accuracy evaluation over the TP. Based on the paired comparison of these five LC datasets, all five LC products show that grass is the major land cover type on the TP, but the range of grass coverage identified by the different products varies noticeably, from 43.35% to 65.49%. The fully consistent spatial regions account for 43.72% of the entire region of the TP, while, in the transition area between grass and bare soil, there is still a large area of medium-to-low consistency. In addition, a comparison of LC datasets using integrated reference datasets shows that the overall accuracies of MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 are 54.29%, 49.32%, 53.03%, 53.73%, and 60.11%, respectively. The producer accuracy of the five products is highest for grass, while glaciers have the most reliable and accurate characteristics among all LC products for users. These findings provide valuable insights for the selection of rational and appropriate LC datasets for studying land-atmosphere interactions and promoting ecological preservation in the TP.

A Comparative Study of SOx, NOx, PM2.5 and PM10 in the UK and Poland from 1970 to 2020

Presently, there is growing discourse surrounding climate change, global warming, and the possibility of urban smog. Daily, we encounter air pollutants unwittingly, often oblivious to the substantial adverse impacts they may impart on our health. This manuscript furnishes a thorough examination of the shifts in the concentrations of distinct air pollutants, namely, sulphur oxides (SOx), nitrogen oxides (NOx), and particulate matter PM2.5 and PM10, within the contexts of the United Kingdom (a country progressively transitioning to alternative energy sources) and Poland (a country in the EU with the second lowest climate policy evaluation in the climate change performance index or CCPI) from 1970 to 2020. This comparative study between the two countries clearly showed the importance of the transition to clean energy sources. The UK’s efforts towards cleaner energy sources have led to reduced emissions of sulphur oxides (SOx) and particulate matter. In contrast, Poland’s heavy dependence on energy primarily from coal over the years has resulted in elevated pollution levels, notably in the concentration of pollutants such as particulate matter. This study also revealed that changes in emissions predominantly stem from technological advancements and economic activities. Additionally, political regulations and the gradual phase-out of specific fuels or energy-rich substances and their substitution with alternative energy sources have also imparted considerable influence.