Search Results (11,889)

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

The article presents the results of research on the impact of material and construction solutions on energy demand and greenhouse gas emissions. Field research was conducted in an existing free-standing greenhouse located in southern Poland. The research period covered the entire calendar year. The measurement data were used in the next step to validate the computational model using the numerical method of elementary balances. The data distribution was also analyzed in terms of basic statistics. The validated and verified model was used in the further part of the analysis to conduct computer simulations for three variants, differing in terms of material and construction solutions. The variants included: no foundation insulation, extruded polystyrene (XPS) insulation and the use of single-chamber polycarbonate panels with thermal insulation of the foundations. The obtained results showed a high agreement between theoretical and real data (85–89% for the coefficient of determination (R²) and 84–88% for the GOF method). In the case of variant 1, which in terms of material and construction solutions corresponded to the actual construction of the greenhouse, it was found that the annual energy demand for heating purposes amounted to 153,234 kWh/year. In variant 2, in which additional thermal insulation relative to the zero state was used, the energy demand for heating purposes was lower and amounted to 147,704 kWh/year. The lowest heat load was characteristic of variant 3, in which 116,294 kWh/year was required to cover heating needs. The variant with polycarbonate and foundation insulation brought energy savings of 24% and a reduction of CO₂ emissions by 24%. In addition, replacing fuel from hard coal with natural gas brought significant benefits, reducing pollutant emissions by 51%. The paper is a new approach to the use of the mentioned numerical method for the assessment of gaseous pollutant emissions in this type of building based on numerical simulations of energy consumption. Full article

Applying nitrogen fertilizers in agriculture can cause uncontrolled gas emissions, such as N₂O and CO_2, leading to global warming and serious climate changes. In this study, we evaluated the greenhouse gas emissions (GHGs) that are concomitant with applying different rates of N fertilization, i.e., 50, 75, 100, and 125% of the recommended dose (727 kg N ha⁻¹) for two cultivars (Balady and Sids-40) of Allium sativum L. grown under three planting dates (15 September, 1 October, and 15 October). For this purpose, two field experiments were carried out during the two growing seasons of 2020/2021 and 2021/2022. Treatments were arranged in a split–split plot design with three replicates: planting dates were set up in the main plots, nitrogen levels were conducted in the submain plots, and garlic varieties were in the sub-subplots. The obtained results can be summarized as follows: Planting on 15 September significantly increased vegetative growth parameters (i.e., plant height, leaves area, number of leaves plant⁻¹, and leaves dry weight) and total bulb yield, in both seasons. The application of the highest rate of N (125%) gave significantly higher records for vegetative growth parameters, while the 75% nitrogen treatment appeared to give the highest total bulb yield in both seasons. The means of plant growth characteristics and total bulb yield were significantly increased by the cultivation of the Balady cultivar. In addition, the results show that GHGs were positively correlated with increasing the rate of N fertilization. It could be recommended that planting on 15 September and fertilizing with 75% N fertilizer from the recommended dose for Balady cultivar achieve maximum yield and its components. Full article

Formulating a scientifically sound and efficient approach to allocating carbon quota aligned with the carbon peaking goal is a fundamental theoretical and practical challenge within the context of climate-oriented trading in the power sector. Given the highly irrational allocation of carbon allowances in China’s power sector, as well as the expanding role of renewable energy, it is essential to rationalize the use of green energy in the development of carbon reduction in the power sector. This study addresses the risk of “carbon transfer” within the power industry and develops a predictive model for CO₂ emission based on multiple influential factors, thereby proposing a carbon quota distribution scheme adapted to green energy growth. The proposed model employs a hybrid of the gray forecasting model-particle swarm optimization-enhanced back-propagation neural network (GM-PSO-BPNN) for forecasting and allocating the total carbon quota. Assuming consistent total volume control through 2030, carbon quota is distributed to regional power grids in proportion to actual production allocation. Results indicate that the PSO algorithm mitigates local optimization constraints of the standard BP algorithm; the prediction error of carbon emissions by the combined model is significantly smaller than that of the single model, while its identification accuracy reaches 99.46%. With the total national carbon emissions remaining unchanged in 2030, in the end, the regional grids received the following quota values: 873.29 million tons in North China, 522.69 million tons in Northwest China, 194.15 million tons in Northeast China, 1283.16 million tons in East China, 1556.40 million tons in Central China, and 1085.37 million tons in the Southern Power Grid. The power sector can refer to this carbon allowance allocation standard to control carbon emissions in order to meet the industry’s emission reduction standards. Full article

In the context of growing concerns over food security and climate change, research on sustainable agricultural development increasingly emphasizes the interconnections within agricultural systems. This study developed a regionally integrated optimization and prediction agricultural model to systematically analyze the impacts of climate change on agricultural systems and their feedback mechanisms from a water-energy-food-carbon (WEFC) nexus perspective. Applied to the Pearl River Basin, the model evaluates future trends in grain yield, water use, energy consumption, and carbon emissions under various climate scenarios throughout this century. The results indicate that rising temperatures significantly reduce crop yields, particularly in the western basin, increasing the environmental footprint per unit of grain produced. However, the CO₂ fertilization effect substantially offsets these negative impacts. Under the SSP585 scenario, CO₂ concentrations rising from 599.77 ppm to 1135.21 ppm by the century’s end led to a shift in crop yield trends from negative (Z = −7.03) to positive (Z = 11.01). This also reduces water, energy, and carbon footprints by 12.82%, 10.62%, and 10.59%, respectively. These findings highlight the critical importance of adaptive management strategies, including precision irrigation, optimized fertilizer use, and climate-resilient practices, to ensure sustainable agricultural production. Despite these insights, the model has limitations. Future research should incorporate uncertainty analysis, diverse adaptation pathways, and advanced technologies such as machine learning and remote sensing to improve predictive accuracy and applicability. This study offers valuable guidance for mitigating the adverse impacts of climate change on the WEFC nexus, supporting sustainable agricultural practices and science-based policy development. Full article

As the greenhouse effect intensifies, China faces pressure to manage CO₂ emissions. Coal-fired power plants are a major source of CO₂ in China. Traditional CO₂ emission accounting methods of power plants are deficient in computational efficiency and accuracy. To solve these problems, this study proposes a novel RF-RFE-DF-Optuna (random forest–recursive feature elimination–deep forest–Optuna) framework, enabling accurate CO₂ emission prediction for coal-fired power plants. The framework begins with RF-RFE for feature selection, identifying and extracting the most important features for CO₂ emissions from the power plant, reducing dimensionality from 46 to just 5 crucial features. Secondly, the study used the DF model to predict CO₂ emissions, combined with the Optuna framework, to enhance prediction accuracy further. The results illustrated the enhancements in model performance and showed a significant improvement with a 0.12706 increase in R² and reductions in MSE and MAE by 81.70% and 36.88%, respectively, compared to the best performance of the traditional model. This framework improves predictive accuracy and offers a computationally efficient real-time CO₂ emission monitoring solution in coal-fired power plants. Full article

Crop production is heavily dependent on fertilizers that negatively impact the environment; therefore, research on biochar to improve the soil’s properties and reduce greenhouse gas emissions has intensified over the years. To elucidate rice yield and greenhouse gas emission (GHG) arising from the application of biochar and N fertilizer on paddy soil in Northeast China, a 3-year (2015–2017) field experiment was established. Adopting a split-plot design with three replicates, two nitrogen (N) fertilizer levels in the main plots were designated as follows: 120 kg N ha⁻¹ (N1, 2/3 of N application rate for optimal local rice yield); 180 kg N ha⁻¹ (N2, full N application rate for optimal local rice yield); and four biochar application rates of no biochar (C0, control); 1.0 t ha⁻¹ biochar (C1); 1.5 t ha⁻¹ biochar (C2); and 2.0 t ha⁻¹ biochar (C3) were designated as sub-treatments. The results showed that in 2015, biochar amendment increased GHG emissions while between 2016 and 2017, biochar amendment of 1.5 t ha⁻¹ decreased CH₄ emissions, global warming potential (GWP), and greenhouse gasses intensity (GHGI) by 11.3%, 10.9%, and 17.0%, respectively. On average, for the years 2016 and 2017, the N₂O fluxes were 17.0% lower in the N2 plots compared to the N1 plots. Biochar amendment of 1.5 t ha⁻¹ recorded an 8.6% increase in rice yield compared to the control. The soil properties of the study site showed that biochar amendment of 1, 1.5, and 2 t ha⁻¹ augmented soil organic matter by 3.3%, 5.3%, and 5.2%, respectively, and soil phosphorus availability by 6.4%, 11.2%, and 22.6%, respectively. The co-application of biochar at 1.5 t ha⁻¹ and 180 kg N ha⁻¹ effectively regulated GHG emissions while maintaining crop yield. Appropriate co-application of biochar with N fertilizer can be adopted for emission reduction and rice yield maintenance while maintaining soil fertility in Northeast China. Full article

Cement production is a major contributor to greenhouse gas (GHG) emissions, driving the need for alternative materials to reduce its environmental footprint and enhance sustainability. This study investigates the use of biochar derived from Arundo grass as a partial replacement for cement in conjunction with metakaolin to enhance the mechanical properties and environmental performance of concrete. Compressive strength analysis and sorptivity analysis were conducted to evaluate the effects of metakaolin on Arundo grass biochar concrete. The findings revealed that incorporating biochar and metakaolin negatively impacted workability. However, a mixture of 5% biochar and 10% metakaolin (by weight of cement) significantly improved early 7-day compressive strength compared to samples containing only 5% biochar and the control mix. Additionally, the sorptivity analysis indicated that this combination maintained comparable absorption rates to the control sample. In terms of sustainability, the partial replacement of cement with 5% biochar and 10% metakaolin reduced CO₂ emissions by 75 kg per cubic meter of concrete, showcasing its contribution to lowering the carbon footprint of concrete production. Overall, this study demonstrates the potential of combining biochar and metakaolin to develop more sustainable concrete solutions with enhanced early compressive strength. However, further research is needed to optimize long-term performance and workability for broader adoption in sustainable construction practices. Full article

This study evaluates the performance of biofuels created from triple blends of fossil diesel, sunflower or castor oil (SVOs), and 2-Ethylhexyl Nitrate (EHN), a low-viscosity, high-cetane (LVHC) solvent. EHN reduces the viscosity of SVOs to enable their use in conventional diesel engines without compromising fuel properties. The results show that the power output from these blends is similar to or greater than that of fossil diesel, with comparable fuel consumption. Furthermore, the blends significantly reduce emissions of carbon monoxide (CO) and soot, though NOx emissions are slightly higher due to the nitrogen content in EHN. However, NOx levels remain within permissible limits. The substitution of fossil diesel could be further enhanced if EHN were produced using green hydrogen and lignocellulosic biomass, making it a renewable and sustainable biofuel component. These findings support the potential of EHN/SVO biofuel blends to replace a significant portion of fossil diesel in conventional diesel engines while maintaining performance and reducing harmful emissions, except for a slight increase in NOx. Full article

A reduction in emissions in transportation is paramount to achieve full compliance with the European Union’s 2050 targets. In this framework, a great boost to the carbon dioxide (CO₂) emission of internal combustion engines fueled by petroleum-derived fuels can be obtained through the adoption of biomass-derived fuels that can be employed in conventional series production engine vehicles. This paper presents the results of an experimental activity on a two-cylinder turbocharged common rail diesel engine, whose main application is for urban mobility, fueled with renewable fuels: Neste MY Renewable Diesel and Eni HVOlution. Aimed at analyzing the potential employment of renewable fuels as drop-in alternative fuels, the engine performance and emissions were investigated under fixed settings of the injection parameters, in the complete range of the engine speed, at the full pedal position. The comparison with the data from tests in which the engine was fueled with fossil diesel highlighted minimal differences in the performance outcomes, while significant differences were observed in the emissions results. In more detail, there were reduced carbon monoxide (CO) emissions (HVO produced using Ecofining^TM technology retained better behavior in relation to HVO produced using the NEXBTL™ technology), advantages in hydrocarbon (HC) and nitrogen oxide (NOx) emissions (HVO from NESTE Oil performed better than HVO from ENI), a decrease in the particle mass and number emissions (HVO from Ecofining^TM technology was characterized by a lower particle number and court mean diameter in relation to HVO from the NEXBTL™ technology). The results highlight that an optimization of the engine settings based on the specific properties of each fuel could allow us to take full advantage of these fuels in reducing the environmental impact of cars. Full article

This article discusses the challenges of adapting to and mitigating climate change through sustainable resource management in the agri-food sector. These aspects are mandatory obligations for businesses under new EU directives and regulations. Greenhouse gas (GHG) emissions must be controlled at every stage of the value chain, from the acquisition of raw materials to transportation and cooperation with suppliers. The purpose of this paper is to analyze the areas generating GHG emissions in the agri-food enterprise toward the development of guidelines for the sustainable development of domestic food production. This paper presents a GHG study in three scopes at one of the mills in Poland based on the GHG protocol methodology. The analysis of consumption of energy carriers was used to determine GHG emissions (Scopes 1 and 2), and the total amounted to about 2.1 million kg CO_2eq (the share of Scope 1 was about 16% and Scope 2 as high as 83%), and the average carbon footprint of flour production in terms of unit weight was 0.040 kg CO_2eq/kg. Extending the analysis to Scope 3, the emissions associated with this scope accounted for the largest share (92%), while Scopes 1 and 2 accounted for only 8%. The determined carbon footprint (considering the three GHG emission scopes) was 0.52 kg CO_2eq/kg. In Scope 3, the largest contribution was from category 1 emissions (92%) related to grain cultivation, and category 5 (6%) were emissions related to the transportation of sold products. The smallest impact is from category 3 emissions related to the management of generated waste. Regular calculation and reporting of emissions in each area enables the company to more fully understand its environmental impact, identify risks and implement changes that bring financial and environmental benefits. Full article

The purpose of this research is to develop an advanced model to serve as a strategic tool for the Thailand government in managing the country and to propose ways for the government to exercise state power through proactive measures to address governance gaps and ensure long-term sustainability. This research employs a mixed-methods approach. The research methodology involved the following stages: (1) Quantitative research was conducted by creating the best model, which involved conducting path analysis based on an autoregressive integrated moving average with an exogenous variable model (PAARIMAX (1,1,1)). (2) The results of the quantitative research were optimized to facilitate additional qualitative research in order to identify appropriate ways of using state power for long-term sustainability in country management. The study’s findings suggest that the government will need to exercise its state power in the governance of the country through the development of a long-term national management plan (2024–2043). This plan involves the establishment of a new scenario policy wherein a minimum of 35% clean technology and green materials must be utilized within the economic sector. This is primarily due to their significant impact on environmental change. Furthermore, the government should exercise its state power to mandate an immediate reduction in energy consumption of 50%, achieved through the immediate adoption of renewable energy sources. This research utilized the results derived from the PAARIMAX model to conduct further qualitative analysis to fill the gaps, enhance the value of the quantitative research, and align it more effectively with the context of practical application. The study found that the proactive measures suggested by stakeholders must be implemented alongside the urgent establishment of new scenario policies, including for charges and taxes, subsidies and concession taxes, deposit refund systems, and property rights and market creation. Full article

Background/Objective: The relationship between food consumption and environmental sustainability is becoming increasingly evident. The aim of this study was to estimate the evolution of the environmental impact of food consumption in the Spanish population, assessed in terms of greenhouse gas (GHG) emissions. Methods: Data collected from the Household Budget Survey were included, from approximately 24,000 households for the period of 2006–2023. The environmental impact of diet, in terms of GHG emissions, was estimated from the EAT-Lancet Commission tables, and the adherence to the Mediterranean Diet (MedDiet) was calculated using the Dietary Score index. Results: The environmental impact of the Spanish diet, in terms of GHG, followed a downward trend over the years analysed, from 3978.1 g CO₂-eq in 2006 to 3281.4 g CO₂-eq in 2023, a decrease of 17.5%. The food groups with the largest decrease in consumption during this period were red meat (from 39.9 kg/year to 35.5 kg/year), fish (from 24.3 kg/year to 19.0 kg/year), and dairy products (from 113.4 kg/year to 99.7 kg/year). The level of adherence to the MedDiet increased slightly from 34 points in 2006 to 35 points in 2023 due to an increase in the amount of vegetables (42.7 kg/year vs. 44.3 kg/year) and grains consumed (53.1 kg/year vs. 72.6 kg/year) and a decrease in fish consumption (24.3 kg/year vs. 19.0 kg/year). Conclusions: In Spain, a reduction in GHG emissions associated with food consumption was observed due to a decrease in the consumption of red meat, fish, dairy products, and fats. National surveys are very useful tools to analyse the impact of food consumption on climate change and to assess the effect of the policies implemented to contain it. Full article

Urban vehicular emissions, a major contributor to environmental degradation, demand accurate methodologies that reflect real-world driving conditions. This study presents a telemetric data-driven framework for assessing emissions of Carbon Monoxide (CO), Hydrocarbons (HCs), and Nitrogen Oxides (NOx) in real-world scenarios. By utilizing Vehicle Specific Power (VSP) calculations, Gaussian Mixture Models (GMMs), and Ensemble Isolation Forests (EIFs), the framework identifies high-risk driving behaviors and maps high-emission zones. Achieving a Silhouette Score of 0.72 for clustering and a precision of 0.88 in anomaly detection, the study provides actionable insights for policymakers to mitigate urban emissions. Spatial–temporal analysis highlights critical high-emission areas, offering strategies for urban planners to reduce environmental impacts. The findings underscore the potential of interventions such as speed regulation and driving behavior modifications in lowering emissions. Future extensions of this work will include hybrid and electric vehicles, alongside the integration of granular environmental factors like weather conditions, to enhance the framework’s accuracy and applicability. By addressing the complexities of real-world emissions, this study contributes to bridging significant knowledge gaps and advancing sustainable urban mobility solutions. Full article

Carbon dioxide is emitted in several industrial processes and contributes to global warming. One of the industries that is considered a significant emitter is metallurgy. Therefore, it is necessary to search for and implement methods to reduce its emissions from metallurgical processes. An alternative option to the use of conventional coke, which is produced solely from fossil coal, is the utilization of bio-coke. The production of bio-coke involves the use of coking coal and the incorporation of biomass-derived substances such as biochar (charcoal). The article presents the results of the research on the influence of the biochar addition on the structural, textural, and technological properties of produced bio-coke. Research on the production and analysis of the properties of the obtained bio-coke aimed at assessing the potential possibilities of applying it in the process of a carbothermal reduction of manganese ore in order to smelt ferroalloys. Studies have shown that biochar addition to the coking blend in an amount of up to 20% allows a bio-coke characterized by properties enabling the mentioned use to be obtained. Bio-coke was characterized by higher CO₂ reactivity index (CRI), lower post-reaction strength (CSR), and higher reactivity to synthetic manganese ore than regular metallurgical coke. In the context of industrial applications of bio-coke, it is necessary to verify its production and use on a pilot and industrial scale. Full article