Search Results (396)

As a consequence of measures imposed during the COVID-19 pandemic, anthropogenic emissions worldwide decreased markedly in impacted sectors, including the aviation industry. The aim of this study is to investigate the effects of the pandemic on aircraft emissions below the mixing height (3000 feet above ground) at Václav Havel Airport Prague during 2020. For this purpose, real aircraft emissions during 2020 were computed using provided surveillance data, while business-as-usual aircraft emissions that could have been expected at the airport that year under normal circumstances were estimated using traffic data from previous years and derived emission factors. We found that the median real emissions at the airport in 2020 were 220.859 t of NO_X, 101.364 t of CO, 15.025 t of HC, 44,039.468 t of CO₂, 17,201.825 t of H₂O and 11.748 t of SO₂. The median estimated reduction in emissions due to the pandemic in 2020 was −476.317 t of NO_X, −203.998 t of CO, −28.388 t of HC, −95,957.278 t of CO₂, −37,476.400 t of H₂O and −25.595 t of SO₂. Absolute differences between the real and business-as-usual emissions peaked in June 2020, while the relative differences peaked in April/May at −89.4% to −92.0%. Full article

An important issue in the sustainable development of agricultural engineering today is the use of biogas plants for the production of electricity and heat from the organic waste of agricultural products and other low-quality products, which also contributes to the improvement of environmental safety. Traditional methods for assessing the apparent severity of the Roslynnytsia campaign based on statistics from the dominions proved to be ineffective. A hypothesis was proposed regarding the possibility of estimating the apparent biomass by averaging the indicators of depletion and assessing the CH₄ and CO emissions based on satellite monitoring data. The aim of this work is to create a methodology for preparing a raw material base in united territorial communities to provide them with electrical and thermal energy using biogas plants. The achievement of this goal was based on solving the following tasks: monitoring biomethane emissions in the atmosphere as a result of rotting organic waste, and monitoring carbon monoxide emissions as a result of burning agricultural waste. Experimental studies were conducted using earth satellites on sites with geometric centers in the village of Gaishin in the Pereyaslav united territorial community, the city of Ovruch in the Zhytomyr region, the Oleshkovsky Sands National Park in the Kherson region (Ukraine), and the city of Jüterbog, which is located in the state of Brandenburg and is part of the Teltow-Fläming district (Germany). The most significant results of this research involve the methodology for the preparation of the raw material base in the united territorial communities for the production of biogas, based on indirect measurements of methane and carbon dioxide emissions using the process of remote sensing. Based on the use of the proposed scientific and methodological apparatus, it was found that the location of the territory with the center in the village of Gaishin has better prospects for collecting plant raw materials for biogas production than the location of the territorial district with the center in the city of Ovruch, the emissions in which are significantly lower. From March 2020–August 2023, a higher CO concentration was recorded on average by 0.0009 mol/m², which is explained precisely by crop growing practices. In addition, as a result of the conducted studies, for the considered emissions of methane and carbon monoxide for monitoring promising raw materials, carbon monoxide has the best prospects, since methane emissions can also be caused by anthropogenic factors. Thus, in the desert (Oleshkivskie Pisky), large methane emissions were recorded throughout the year which could not be explained by crop growing practices or the livestock industry. Full article

Accurately assessing the impact of anthropogenic carbon dioxide (CO₂) emissions on CO₂ concentrations is essential for understanding regional climate change, particularly in high-emission countries like China. This study employed the GEOS-Chem chemical transport model to simulate and compare the spatiotemporal distributions of XCO₂ of three anthropogenic CO₂ emission inventories in mainland China for the 2018–2020 period and analyzed the effects of emission variations on atmospheric CO₂ concentrations. In eastern China, particularly in the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) regions, column-averaged dry air mole fractions of CO₂ (XCO₂) can exceed 420 ppm during peak periods, with emissions from these areas contributing significantly to the national total. The simulation results were validated by comparing them with OCO-2 satellite observations and ground-based monitoring data, showing that more than 70% of the monitoring stations exhibited a correlation coefficient greater than 0.7 between simulated and observed data. The average bias relative to satellite observations was less than 1 ppm, with the Emissions Database for Global Atmospheric Research (EDGAR) showing the highest degree of agreement with both satellite and ground-based observations. During the study period, anthropogenic CO₂ emissions resulted in an increase in XCO₂ exceeding 10 ppm, particularly in the North China Plain and the YRD. In scenarios where emissions from either the BTH or YRD regions were reduced by 50%, a corresponding decrease of 1 ppm in XCO₂ was observed in the study area and its surrounding regions. These findings underscore the critical role of emission control policies in mitigating the rise in atmospheric CO₂ concentrations in densely populated and industrialized areas. This research elucidates the impacts of variations in anthropogenic emissions on the spatiotemporal distribution of atmospheric CO₂ and emphasizes the need for improved accuracy of CO₂ emission inventories. Full article

Industrial boilers are one of the important anthropogenic emission sources of primary air pollutants including particulate matter (PM), sulfur dioxide (SO₂), and nitric oxide (NOx). China possesses the largest number of industrial boilers in the world, characterized by a wide spatial and industrial distribution, and a small scale of individual capacity. The study of air pollutant emissions of industrial boilers in China is an essential field for realizing the green and sustainable development of Chinese industrial sectors in terms of air pollution and CO₂ reduction. Therefore, this study comprehensively summarized the research progress of industrial boilers in terms of primary air pollutant emissions. Currently, significant progress has been made in the study of air pollutant emissions from industrial boilers in China, including the following aspects: (1) the characterization of air pollutant emissions based on field data, (2) the development of multi-scale air pollutant emission inventories, and (3) the scenario analysis of emission reduction potentials and control strategies. In addition, this study further clarified the evolution of air pollution control technologies, based on the analysis of the development of air pollutant emission standards for industrial boilers. Further, the shortcomings of the research on air pollutant emissions of industrial boilers were elucidated, and the perspectives were proposed in view of the development requirements of air pollution control in China. This is expected to provide important contributions to the development of pollution-carbon reduction policies and formulation of green sustainable development strategies related to industrial boilers. Full article

The impact of PM_2.5 on the environment and human health has garnered significant attention. While research on PM_2.5 composition is increasing, fewer studies have focused on how dusty conditions in a special region affect the PM_2.5 composition. This region’s unique environmental conditions, characterized by frequent dust events, complicate air quality management. The study investigates the seasonal distribution of inorganic elements in the PM_2.5 under both dusty and non-dusty conditions through systematic sampling. Selective screening methods identified key pollutant elements, and a respiratory system model was developed to examine their diffusion and deposition patterns in the upper respiratory tract. Key findings reveal that inorganic element concentrations in the PM_2.5 follow consistent seasonal trends, with significantly higher levels during dust events compared to non-dusty periods. Crustal elements are dominated in the PM_2.5, but non-metallic elements (Cl, S) and metallic/quasi-metallic elements (Mn, Cd, Cr, As, Hg) are also prevalent, likely influenced by anthropogenic activities and industrial emissions. By PCA with human health assessments, six characteristic pollutants were identified: As, Co, Cd, Cr, V, and Mn. Simulations using COMSOL Multiphysics 6.2 software demonstrated distinct behaviors: As tends to concentrate in the posterior regions of the respiratory tract, while Co and Cd exhibit relatively uniform distributions, primarily affecting areas where airflow slows upstream. Cr, V, and Mn show dispersed and uniform patterns. Notably, even during dusty conditions, the concentration of the six pollutants remains relatively low in the different parts of the upper respiratory tract, suggesting minimal immediate health impacts. Our study provides valuable insights into the behavior of inorganic elements in the PM_2.5 and their potential health implications, highlighting the need for further research on the effects of dusty conditions on air quality and public health. Full article

Anthropogenic CO₂ emissions are one of the primary drivers of the increase in atmospheric CO₂ concentrations. It has been indicated that reducing emitted pollution gases can simultaneously bring out anthropogenic CO₂ reduction, known as the synergistic effects of pollution and carbon reduction for controlling increases in CO₂ and pollution gas concentrations. This study aims to assess these synergistic effects, which are still not clearly understood, by analyzing the mechanisms of atmospheric CO₂ and NO₂ concentration variability in response to human emission reduction activities. We utilize satellite-observed NO₂, which is a short-lived anthropogenic pollution gas with the same emission sources as CO₂, along with CO₂ concentration data to detect their simultaneous response to anthropogenic CO₂ emissions, thereby assessing and comparing the synergistic effects of pollution and carbon reduction in the two study areas of China and the United States, as well as in a special scenario of abrupt reductions in anthropogenic CO₂ emissions. The results show that the synergistic effects of pollution and carbon reduction in the United States are likely better than those in China, as the United States demonstrates a stronger response (R² = 0.53) between atmospheric NO₂ and anthropogenic CO₂ emission compared with China (R² = 0.36). This difference is attributable to the CO₂ emissions from coal-fired power generation in China are much more than those in the United States, where oil and natural gas dominate. Furthermore, the analysis of special scenarios during the COVID-19 pandemic (2020–2022) in China demonstrates that the types of anthropogenic emission sources are the main factors influencing the synergistic effects of pollution and carbon reduction. Specifically, the megacity regions, where fossil fuel power plants and transportation are the main emission sources, presented stronger synergistic effects of pollution and carbon reduction than those regions dominated by coal-based metallurgical and chemical plants. Full article

Carbon Capture and Storage (CCS) is a critical technology for reducing anthropogenic CO₂ emissions, but its large-scale deployment is complicated by uncertainties in geological storage performance. These uncertainties pose significant financial and operational risks, as underperforming storage sites can lead to costly infrastructure modifications, inefficient pipeline routing, and economic shortfalls. To address this challenge, we propose a novel optimization workflow that is based on mixed-integer linear programming and explicitly integrates probabilistic modeling of storage uncertainty into CCS infrastructure design. This workflow generates multiple infrastructure scenarios by sampling storage capacity distributions, optimally solving each scenario using a mixed-integer linear programming model, and aggregating results into a heatmap to identify core infrastructure components that have a low likelihood of underperforming. A risk index parameter is introduced to balance trade-offs between cost, CO₂ processing capacity, and risk of underperformance, allowing stakeholders to quantify and mitigate uncertainty in CCS planning. Applying this workflow to a CCS dataset from the US Department of Energy’s Carbon Utilization and Storage Partnership project reveals key insights into infrastructure resilience. Reducing the risk index from $15\%$ to $0\%$ is observed to lead to an $83.7\%$ reduction in CO₂ processing capacity and a $77.1\%$ decrease in project profit, quantifying the trade-off between risk tolerance and project performance. Furthermore, our results highlight critical breakpoints, where small adjustments in the risk index produce disproportionate shifts in infrastructure performance, providing actionable guidance for decision-makers. Unlike prior approaches that aimed to cheaply repair underperforming infrastructure, our workflow constructs robust CCS networks from the ground up, ensuring cost-effective infrastructure under storage uncertainty. These findings demonstrate the practical relevance of incorporating uncertainty-aware optimization into CCS planning, equipping decision-makers with a tool to make informed project planning decisions. Full article

Land use change is associated with both higher fossil fuel usage and global cement production, significantly impacting environmental sustainability. Cement dust emission is the third-largest source of anthropogenic CO₂ emissions, right behind fossil fuel usage due to intense agricultural practices like aggressive tillage management. This study’s aim is to determine cement dust emissions impacts on various tillage management methods and the formation of cement dust-affected CO₂ emissions, soil pH, soil organic matter content, total nitrogen content, available phosphorus, CaCO₃ content, bacteria and fungi populations, and enzyme activities. The target of this study is to evaluate how cement dust emissions impact the soil properties and sustainability of different tillage practices. Composite soils from wheat–sugar beet (potato)–fallow cropping sequences under conventional tillage (CT) and no-till (NT) management were collected (0–30 cm depth) with three replications at varying distances from a cement factory (1, 2, 4, 6, 8, and 10 km). To find differences among individual treatments and distances, a two-way ANOVA was employed along with Duncan’s LSD test comparing the various effects of tillage techniques. The associations between soil chemical and biological properties and CO₂ fluxes under the impact of cement dust were examined using Pearson’s correlation analysis. There were notable relationships between soil microbial population, enzyme activities, pH, CaCO₃, and CO₂ fluxes. The sampling distance from the cement plant had a substantial correlation with soil organic carbon, urease activity, pH, CaCO₃, and bacterial populations. According to the study, different tillage methods (CT and NT) affected the diversity and abundance of microorganisms within the soil ecosystem. CT was more beneficial for the microbial population and for sustainable management. Full article

A new meteorological station (DMS) was established at the Morning Glory summit in Zhejiang Province to provide regional background information on atmospheric composition in the Yangtze River Delta (YRD) region, China. This study investigated the first carbon monoxide (CO) records at DMS from September 2020 to January 2022. The annual average concentration of CO was 233.4 ± 3.8 ppb, which exceeded the measurements recorded at the other Asian background sites. The winter CO concentration remained elevated but peaked in March in the early spring due to the combined effect of regional emissions within the YRD and transportation impacts of North China and Southeast Asia sources. The diurnal cycle had a nocturnal peak and a morning valley but with a distinct afternoon climb, as the metropolis in the YRD contributed to a local concentration enhancement. The back trajectory analysis and the Weighted Potential Sources Contribution Function (WPSCF) maps highlighted emissions from Anhui, Jiangxi, Zhejiang, and Jiangsu provinces as significant sources. Due to well-mixed air conditions and fewer anthropogenic influences, DMS records closely aligned with the CO averages derived from the Copernicus Atmospheric Monitoring Service (CAMS) covering the YRD, confirming its representativeness for regional CO levels. This study underscored DMS as a valuable station for monitoring and understanding CO spatiotemporal characteristics in the YRD region. Full article

Soil, geochemical, microbiological, and archeological studies were conducted at eight settlements dating from the Paleolithic to Late Medieval and Modern Ages near the southern Trans-Urals Mountains, Russia. The forest-steppe landscapes, rivers, and abundant mineral resources have attracted people to the region since ancient times. Cultural layers (CLs) are marked by finds of ceramics fragments, animal bones, stone, and metal tools. The properties of CLs include close-to-neutral pH, being well structured, the absence of salinity, enrichment with exchangeable calcium, and anthropogenic phosphorus (0.2–0.4%). The majority of CLs start at a depth of 3–25 cm, extend to 40–60 cm, and contain 6–10% organic carbon (Corg) in the 0–20 cm layer, reflecting carbon input from modern-day processes. At the Ishkulovo site (0.6–0.8 ka BP), Corg decreases to 1.3% because the CL is below 80 cm, and in the absence of fresh organic material input, carbon has been mineralized. The proximity of sites to deposits of copper, chromium, zinc, and manganese in the Ural Mountains creates natural high-content anomalies in the region, as indicated by their abundance in soils and parent rocks. In the past, these elements were also released into CLs from metal products, ceramic fragments, and raw materials used in their manufacture. The sites are quite far (18–60 km) from the Magnitogorsk Metallurgical plant, but industrial stockpiles of S (technogenic coefficient—Ct 30–87%), and, less often, Cr, Mn, and Sr (Ct 30–40%) accumulated in surface layers. These three factors have led to the concentration of pollutants of the first (arsenic, chromium, lead, and zinc) and second (cobalt, copper, and nickel) hazard classes at CLs, often in quantities 2–5 times higher than values for parent materials and geosphere average content (“Clarke” value), and, and less often, more than the allowable content for human health. This may have influenced their health and behavioral functions. Due to the above properties, chernozems have a high buffering capacity and a strong bond with heavy metals. Therefore, no inhibition of microbes was observed. The microbial biomass of the 0–10 cm layer is high, 520–680 µg C/g, and microbes cause the emission of 1.0 C-CO₂ µg/g of soil per hour. During the ancient settlements’ development, a favorable paleoclimate was noted based on the data cited. This contributed to the spread of productive paleolandscapes, ensuring the development of domestic cattle breeding and agriculture. Full article

This review paper examines the critical intersection of energy consumption and environmental impacts within the global food system, emphasizing the substantial footprint (including land usage, costs, food loss and waste, and carbon and water footprints) associated with current practices. The study delineates the high energy demands and ecological burdens of food production, trade, and consumption through a comprehensive bibliographic analysis of high-impact research papers, authoritative reports, and databases. The paper systematically analyzes and synthesizes data to characterize the food industry’s current energy use patterns and environmental impacts. The results underscore a pressing need for strategic interventions to enhance food system efficiency and reduce the footprint. In light of the projected population growth and increasing food demand, the study advocates for a paradigm shift towards more sustainable and resilient food production practices, adopting energy-efficient technologies, promoting sustainable dietary habits, and strengthening global cooperation among stakeholders to achieve the Sustainable Development Goals. Investigations have revealed that the food system is highly energy-intensive, accounting for approximately 30% of total energy consumption (200 EJ per year). The sector remains heavily reliant on fossil fuels. Associated greenhouse gas (GHG) emissions, which constitute 26% of all anthropogenic emissions, have shown a linear growth trend, reaching 16.6 Gt_CO2eq in 2015 and projected to approach 18.6 Gt_CO2eq in the coming years. Notably, 6% of these emissions result from food never consumed. While the water footprint has slightly decreased recently, its demand is expected to increase by 20% to 30%, potentially reaching between 5500 and 6000 km³ annually by 2050. Energy efficiency interventions are estimated to save up to 20%, with a favorable payback period, as evidenced by several practical implementations. Full article

Multivariate and statistical tool advancements help to assess potential pollution threats, their geochemical distribution, and the competition between natural and anthropogenic influences, particularly on sediment contamination with potentially toxic metals (PTMs). For this, riverine sediments from 25 locations along urban banksides of the River Ravi, Pakistan, were collected and analyzed to explore the distribution, pollution, ecological, and toxicity risk indices of PTMs like Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sb, Sn, Sr, V, and Zn using Inductively Coupled Plasma–Optical Emission Spectrometry (ICP-OES) technique. Additionally, techniques such as X-ray Diffraction (XRD) and Scanning Electron Microscopy–Energy Dispersive X-ray Spectroscopy (SEM-EDS) were employed to investigate the mineralogical and morphological aspects. The results indicated that mean concentrations (mg kg⁻¹) of Cd (2.37), Cr (128), Hg (16.6), Pb (26.6), and Sb (2.44) were significantly higher than reference values given for upper continental crust (UCC) and world soil average (WSA), posing potential threats. Furthermore, the geochemical pollution indices showed that sediments were moderately polluted with Cd (I_geo = 2.37, EF = 12.1, and CF = 7.89) and extremely polluted with Hg (I_geo = 4.54, EF = 63.2, and CF = 41.41). Ecological and toxicity risks were calculated to be extremely high, using respective models, predominantly due to Hg (Er_i = 1656 and ITRI = 91.6). SEM-EDS illustrated the small extent of anthropogenic particles having predominant concentrations of Zn, Fe, Pb, and Sr. Multivariate statistical analyses revealed significant associations between the concentrations of PTMs and the sampling locations, highlighting the anthropogenic contributions linked to local land-use characteristics. The present study concludes that River Ravi sediments exhibit moderate levels of Cd and extreme pollution by Hg, both of which contribute highly to extreme ecological and toxicity risks, influenced by both natural and anthropogenic contributions. Full article

The condition of the aquatic environment, particularly in protected areas of high ecological value such as the Narew River, requires detailed monitoring to identify and minimise the impact of anthropogenic factors on the ecosystem. This study focused on the content of heavy metals in bottom sediments and macrophytes of the Narew River, emphasising the influence of human activities and natural factors on this ecologically valuable ecosystem. Pb, Cr, Zn, Cd, Fe, and Mn concentrations were analysed in sediment samples, and ten macrophyte species were collected at 11 sampling points along the river. A geochemical index (Igeo) and multivariate statistical analyses were employed to identify sources of contamination. The digested samples (sediments and plants) were analysed for Pb, Cr, Cu, Zn, Ni, Cd, Fe, and Mn using flame atomic absorption spectrometry (AAS) on an ICE 3500 Thermo Scientific spectrometer, with a measurement error below 5%, validated against certified reference materials. The study results indicated that most metals, including Ni, Cr, Co, Fe, and Mn, predominantly originate from natural geological processes. In contrast, Zn, Cd, Cu, and Pb were identified as being enriched due to anthropogenic activities. An analysis of macrophytes revealed varied patterns of metal accumulation, which correspond to the bioavailability of metals and their environmental concentrations. Comprehensive statistical analyses provided insights into the predominant sources of metal contamination, closely associated with industrial emissions, agricultural runoff, and transportation activities. The integration of sediment and macrophyte monitoring allowed for a thorough evaluation of the Narew River ecosystem, facilitating the identification of key pollution sources. These findings highlight the critical need for measures to mitigate anthropogenic contributions of heavy metals—particularly from industrial, agricultural, and transportation sectors—to safeguard the Narew River’s unique ecological and natural heritage. Full article

In this study, gaseous element mercury (GEM) and gaseous oxidized mercury (GOM) in the atmosphere were continuously observed at a minute resolution from 1 April 2019 to 31 December 2020 in urban Xi’an, the largest central city in Northwestern China. The concentrations of GEM and GOM drastically fluctuated within the ranges of 0.022–297 ng/m³ and 0.092–381 pg/m³, showing average values of 5.78 ± 7.36 ng/m³ and 14.2 ± 20.8 pg/m³, respectively. GEM and GOM showed a decreasing trend of 0.121 ng/m³ and 0.472 pg/m³ per month, respectively, which we believe was mainly caused by anthropogenic sources, especially by a reduction in coal-fired emissions, rather than meteorological factors. The significant positive correlation between GEM and PM_2.5, SO₂, NO₂, and CO, as well as Cr, As, and Pb in PM_2.5 also proves that. GEM showed a higher concentration at nighttime than daytime, while an M-shaped diurnal trend was observed for GOM. The hazard quotient of GEM for both males and females decreased at a rate of 0.003 per month, and children aged 2–5 were more sensitive to non-carcinogenic health risks. The changing trends, controlling factors, and human health risks of Hg in the atmosphere are necessary and crucial to study for improving our understanding of the impacts of Hg in Northwestern China. Full article

The chemistry of atmospheric precipitation serves as an important proxy for discriminating the source(s) of air contaminants in urban environments as well as to discuss the dynamic of atmospheric chemistry exchanges. This approach can be undertaken at time scales varying from single events to seasonal and yearly time frames. Here, we characterized the chemical composition of two single rain episodes (18 July 2018 and 21 February 2019) collected in Wrocław (SW Poland). Our results demonstrated inner variations and seasonality (within the rain event as well as between summer and winter), both in ion concentrations as well as in their potential relations with local air contaminants and scavenging processes. Coupling statistical analysis of chemical parameters with meteorological/synoptic conditions and HYSPLIT back trajectories allowed us to identify three main factors (i.e., principal components; PC) controlling the chemical composition of precipitation, and that these fluctuated during each event: (i) PC1 (40%) was interpreted as reflecting the long-range transport and/or anthropogenic influences of emission sources that included biomass burning, fossil fuel combustion, industrial processes, and inputs of crustal origin; (ii) PC2 (20%) represents the dissolution of atmospheric CO₂ and HF into ionic forms; and (iii) PC3 (20%) originates from agricultural activities and/or biomass burning. Time variations during the rain events showed that each factor was more important at the start of the event. The study of both SO₄²⁻ and Ca²⁺ concentrations showed that while sea spray inputs fluctuated during both rain events, their overall impact was relatively low. Finally, below-cloud particle scavenging processes were only observed for PM₁₀ at the start of the winter rain episode, which was probably explained by the corresponding low rain intensity and an overlap from local aerosol emissions. Our study demonstrates the importance of multi-time scale approaches to explain the chemical variability in rainwater and both its relation to emission sources and the atmosphere operating processes. Full article