Search Results (1,051)

Accurate forecasting of energy consumption in buildings is essential for achieving energy efficiency and reducing carbon emissions. However, many existing models rely on limited input variables and overlook the complex influence of indoor environmental quality (IEQ). In this study, we assess the performance of hybrid machine learning ensembles for predicting hourly energy demand in a smart office environment using high-frequency IEQ sensor data. Environmental variables including carbon dioxide concentration (CO₂), particulate matter (PM_2.5), total volatile organic compounds (TVOCs), noise levels, humidity, and temperature were recorded over a four-month period. We evaluated two ensemble configurations combining support vector regression (SVR) with either Random Forest or LightGBM as base learners and Ridge regression as a meta-learner, alongside single-model baselines such as SVR and artificial neural networks (ANN). The SVR combined with Random Forest and Ridge regression demonstrated the highest predictive performance, achieving a mean absolute error (MAE) of 1.20, a mean absolute percentage error (MAPE) of 8.92%, and a coefficient of determination (R²) of 0.82. Feature importance analysis using SHAP values, together with non-parametric statistical testing, identified TVOCs, humidity, and PM_2.5 as the most influential predictors of energy use. These findings highlight the value of integrating high-resolution IEQ data into predictive frameworks and demonstrate that such data can significantly improve forecasting accuracy. This effect is attributed to the direct link between these IEQ variables and the activation of energy-intensive systems; fluctuations in humidity drive HVAC energy use for dehumidification, while elevated pollutant levels (TVOCs, PM_2.5) trigger increased ventilation to maintain indoor air quality, thus raising the total energy load. Full article

Although particulate matter (PM) pollution from vehicles’ exhaust has decreased significantly over the years, the contribution from non-exhaust sources (brakes, tyres) has remained at the same levels. In the European Union (EU), Euro 7 regulation introduced PM limits for vehicles’ brake systems. Regenerative braking, i.e., recuperation of the deceleration kinetic and potential energy to the vehicle battery, is one of the strategies to reduce the brake emission levels and improve vehicle efficiency. According to the regulation, the shares of friction and regenerative braking can be determined with actual testing of the vehicle on a chassis dynamometer. In this study we tested the regenerative capabilities of a plug-in hybrid vehicle, both in the laboratory and on the road, under different protocols (including both smooth and aggressive braking) and covering a wide range of driving conditions (urban, rural, motorway) over 10,000 km of driving. Good agreement was obtained between laboratory and on-road tests, with the use of the friction brakes being on average 7% and 5.3%, respectively. However, at the same time it was demonstrated that the friction braking share can vary over a wide range (up to around 30%), depending on the driver’s behaviour. Full article

Food loss and waste from the European Union’s dairy supply chain, particularly in the management of fresh milk, imposes significant environmental burdens. This study demonstrates that implementing Radio Frequency Identification (RFID)-enabled digital decision-support tools can substantially reduce these impacts across the region. A cradle-to-grave life cycle assessment (LCA) was used to quantify both the additional environmental burdens from RFID (tag production, usage, and disposal) and the avoided burdens due to reduced milk losses in the farm, processing, and distribution stages. Within the EU’s fresh milk supply chain, the implementation of digital tools could result in annual net reductions of up to 80,000 tonnes of CO₂-equivalent greenhouse gas emissions, 81,083 tonnes of PM_2.5-equivalent particulate matter, 84,326 tonnes of land use–related carbon deficit, and 80,000 cubic meters of freshwater-equivalent consumption. Spatial analysis indicates that regions with historically high spoilage rates, particularly in Southern and Eastern Europe, see the greatest benefits from RFID enabled digital-decision support tools. These environmental savings are most pronounced during the peak months of milk production. Overall, the study demonstrates that despite the environmental footprint of RFID systems, their integration into the EU’S dairy supply chain enhances transparency, reduces waste, and improves resource efficiency—supporting their strategic value. Full article

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM₁₀ and PM_2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article

Ultrahigh resolution fine particulate matter (PM_2.5) mass concentration remote sensing products are crucial for atmospheric environmental monitoring, pollution source verification, health exposure risk assessment, and other fine-scale applications in urban environments. This study developed an ultrahigh resolution retrieval algorithm to estimate 30 m resolution PM_2.5 mass concentrations over urban areas from Landsat-8 and Sentinel-2A/B satellite measurements. The algorithm utilized aerosol optical depth (AOD) products retrieved from the Landsat-8 OLI and Sentinel-2 MSI measurements from 2017 to 2020, combined with multi-source auxiliary data to establish a PM_2.5-AOD relationship model across China. The results showed an overall high coefficient of determination (R²) of 0.82 and 0.76 for the model training accuracy based on samples and stations, respectively. The model prediction accuracy in Beijing and Wuhan reached R² values of 0.86 and 0.85. Applications in both cities demonstrated that ultrahigh resolution PM_2.5 has significant advantages in resolving fine-scale spatial patterns of urban air pollution and pinpointing pollution hotspots. Furthermore, an analysis of point source pollution at a typical heavy pollution emission enterprise confirmed that ultrahigh spatial resolution PM_2.5 can accurately identify the diffusion trend of point source pollution, providing fundamental data support for refined monitoring of urban air pollution and air pollution prevention and control. Full article

Solid fuels are still widely used in household heating in Europe and North America. Emissions from boilers are released in proximity to people. Therefore, there is a need to minimise the toxicity of emissions affecting human health to the greatest extent possible. This study compares the genotoxic potential of the emissions of four boilers of modern and old design (automatic, gasification, down-draft, over-fire) operating at reduced output to simulate the real-life combustion fed by various fossil and renewable solid fuels (hard coal, brown coal, brown coal briquettes, wood pellets, wet and dry spruce). Organic emissions were tested for genotoxic potential by analysing bulky DNA adducts and 8-oxo-dG adduct induction. There was no consistent genotoxic pattern among the fuels used within the boilers. Genotoxicity was strongly correlated with polycyclic aromatic hydrocarbon (PAH) content, and even stronger correlation was observed with particulate matter (PM). In all measured variables (PM, PAHs, genotoxicity), the technology of the boilers was a more important factor in determining the genotoxic potential than the fuels burned. The highest levels of both bulky and 8-oxo-dG DNA adducts were induced by organics originating from the over-fire boiler, while the automatic boiler exhibited genotoxic potential that was ~1000- and 100-fold lower, respectively. Full article

PM_2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm) pollution is one of the most common problems triggered by the acceleration of urbanization. The coordinated development of cities and the environment has been a topic of significant interest in recent years. Based on the spatiotemporal relationship between the evolution of urbanization levels and PM_2.5 concentrations, and starting from multiple factors characterizing urbanization, this study constructs a coupling coordination degree model between PM_2.5 and urbanization levels to explore the interaction and degree of coordination between urbanization and PM_2.5 in Guangdong Province from 2000 to 2021. The research reveals that the conflict between the urbanization process and PM_2.5 pollution in various cities of Guangdong Province is gradually easing. The year 2011 was a turning point as the PM_2.5 pollution levels in cities that were in an uncoordinated phase began to improve. The coupling coordination degree between urbanization and PM_2.5 pollution in Guangdong Province exhibits significant spatial heterogeneity. The coupling coordination degree in most coastal cities is higher than that in inland cities. Cities in economically underdeveloped regions also face relatively lower pressure from pollution emissions. These regions are characterized by lagging urbanization, and their coupling coordination degree is slowly increasing as urbanization progresses. In economically developed regions, the coupling coordination degree between urbanization levels and PM_2.5 pollution has reached a basic level of coordination, although the specific types vary. Full article

The occurrence of haze pollution significantly deteriorates air quality and threatens human health, yet persistent knowledge gaps in real-time source apportionment of fine particulate matter (PM_2.5) hinder sustained improvements in atmospheric pollution conditions. Thus, this study employed single-particle aerosol mass spectrometry (SPAMS) to investigate PM_2.5 sources and dynamics during winter haze episodes in Yinchuan, Northwest China. Results showed that the average PM_2.5 concentration was 57 μg·m⁻³, peaking at 218 μg·m⁻³. PM_2.5 was dominated by organic carbon (OC, 17.3%), mixed carbonaceous particles (ECOC, 17.0%), and elemental carbon (EC, 14.3%). The primary sources were coal combustion (26.4%), fugitive dust (25.8%), and vehicle emissions (19.1%). Residential coal burning dominated coal emissions (80.9%), highlighting inefficient decentralized heating. Source contributions showed distinct diurnal patterns: coal combustion peaked nocturnally (29.3% at 09:00) due to heating and inversions, fugitive dust rose at night (28.6% at 19:00) from construction and low winds, and vehicle emissions aligned with traffic (17.5% at 07:00). Haze episodes were driven by synergistic increases in local coal (+4.0%), dust (+2.7%), and vehicle (+2.1%) emissions, compounded by regional transport (10.1–36.7%) of aged particles from northwestern zones. Fugitive dust correlated with sulfur dioxide (SO₂) and ozone (O₃) (p < 0.01), suggesting roles as carriers and reactive interfaces. Findings confirm local emission dominance with spatiotemporal heterogeneity and regional transport influence. SPAMS effectively resolved short-term pollution dynamics, providing critical insights for targeted air quality management in arid regions. Full article

Regulatory air pollution monitoring is performed using a sparse monitoring network designed to provide background concentrations of pollutants but may miss small area variations due to local emission sources. Low-cost air pollution sensors operated by trained citizen scientists provide an opportunity to fill this gap. We describe the development and implementation of an air pollution monitoring and community engagement plan in response to resident concerns regarding excessive smoke production from a neighborhood restaurant. Particulate matter (PM_2.5) was measured using a low-cost, portable sensor. When cooking was taking place, the highest PM_2.5 readings were within 50 m of the source (mean PM_2.5 36.9 µg/m³) versus greater than 50 m away (mean PM_2.5 13.0 µg/m³). Sharing results with local government officials did not result in any action to address the source of the smoke emissions, due to lack of jurisdiction. A review of air pollution regulations across the United States indicated that only seven states regulate food cookers and six states specifically exempted cookers from air pollution regulations. Concerns about the smoke were communicated with the restaurant owner who eventually changed the cooking fuel. Following this change, less smoke was observed from the restaurant and PM_2.5 measurements were reduced to background levels. Although current environmental health regulations may not protect residents living near sources of food cooker-based sources of PM_2.5, community engagement shows promise in addressing these emissions. Full article

This study assessed the influence of meteorological conditions on particulate matter (PM) concentrations in Campo Grande, Brazil, from May to December 2021. Using statistical analyses, including Pearson’s correlation coefficient and multivariate regression, we analyzed secondary data on PM2.5 and PM10 concentrations and meteorological variables from the Federal University of Mato Grosso do Sul’s Physics Department. Daily PM concentrations complied with Brazil’s National Ambient Air Quality Standards (PQAr). The PM2.5/PM10 ratios averaged 0.436 (hourly) and 0.442 (daily), indicating a mix of fine and coarse particles. Significant positive correlations were found with temperature, while relative humidity showed a negative correlation, reducing PM levels through deposition. Wind speed had no significant impact. Meteorological influences suggest that air quality management should be tailored to regional conditions, particularly addressing local emission sources like vehicular traffic and biomass burning. Full article

Accurately identifying the sources of fine particulate matter (PM_2.5) pollution is crucial for pollution control and public health protection. Taking the PM_2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics and components of PM_2.5, and quantified the contributions of meteorological conditions, regional transport, and local emissions to the summertime PM_2.5 surge in a typical Yangtze River Delta (YRD) city. Chemical composition analysis highlighted a sharp increase in nitrate ions (NO₃⁻, contributing up to 49% during peak pollution), with calcium ion (Ca²⁺) and sulfate ion (SO₄²⁻) concentrations rising to 2 times and 7.5 times those of clean periods, respectively. Results from the random forest model demonstrated that emission sources (74%) dominated this pollution episode, significantly surpassing the meteorological contribution (26%). The Weather Research and Forecasting model combined with the Community Multiscale Air Quality model (WRF–CMAQ) further revealed that local emissions contributed the most to PM_2.5 concentrations in Suzhou (46.3%), while external transport primarily originated from upwind cities such as Shanghai and Jiaxing. The findings indicate synergistic effects from dust sources, industrial emissions, and mobile sources. Validation using electricity consumption and key enterprise emission data confirmed that intensive local industrial activities exacerbated PM_2.5 accumulation. Recommendations include strengthening regulations on local industrial and mobile source emissions, and enhancing regional joint prevention and control mechanisms to mitigate cross-boundary transport impacts. Full article

Particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and heavy metals (HMs) present in polluted air are strongly associated with an increased risk of respiratory diseases. In our study, we grouped cities based on their pollution levels using a method called Ward’s cluster analysis and looked at the increased cancer risk from PM₁₀-bound harmful substances for adult men and women living in Polish cities. The analysis was based on data from 8 monitoring stations where concentrations of PM₁₀, PAHs, and HMs were measured simultaneously between 2018 and 2022. The cluster analysis made it possible to distinguish three separate agglomeration clusters: cluster I (Upper Silesia, Wroclaw) with the highest concentrations of heavy metals and PAHs, with mean levels of lead 14.97 ± 7.27 ng·m⁻³, arsenic 1.73 ± 0.60 ng·m⁻³, nickel 1.77 ± 0.95 ng·m⁻³, cadmium 0.49 ± 0.28 ng·m⁻³, and ∑PAHs 15.53 ± 6.44 ng·m⁻³, cluster II (Warsaw, Łódź, Lublin, Cracow) with dominant road traffic emissions and low emissions, with average levels of lead 8.00 ± 3.14 ng·m⁻³, arsenic 0.70 ± 0.17 ng·m⁻³, nickel 1.64 ± 0.96 ng·m⁻³, and cadmium 0.49 ± 0.28 ng·m⁻³, and cluster III (Szczecin, Tricity) with the lowest concentration levels with favourable ventilation conditions. All calculated ILCR values were in the range of 1.20 × 10⁻⁶ to 1.11 × 10⁻⁵, indicating a potential cancer risk associated with long-term exposure. The highest ILCR values were reached in Upper Silesia and Wroclaw (cluster I), and the lowest in Tricity, which was classified in cluster III. Our findings suggest that there are continued preventive actions and stricter air quality control. The results confirm that PM₁₀ is a significant carrier of airborne carcinogens and should remain a priority in both environmental and public health policy. Full article

Compression–ignition engines emit particulate matter (PM) (soot), prompting the widespread use of diesel particulate filters (DPFs) in the automotive sector. An alternative method for PM reduction involves the use of ultrasonic waves to disperse and modify the structure of exhaust particles. This article presents experimental results of the effects of ultrasonic emitter parameters, including the number, arrangement, and power, along with the engine speed, on the exhaust smoke density. Tests were conducted on a laboratory prototype equipped with six ultrasonic emitters spaced 0.17 m apart. The exhaust source was a diesel engine from a construction excavator, based on the MTZ-80 tractor design, delivering 80 HP and a displacement of 4750 cm³. A regression model was developed to describe the relationship between the engine speed, emitter power and spacing, and smoke density. The optimal configuration was found to involve an emitter power of 319.35 W and a spacing of 1.361 m for a given engine speed. Under the most effective conditions—an engine speed of 1500 rpm, six active emitters, and a total power of 600 W—smoke emissions were reduced by 18%. These findings support the feasibility of using ultrasonic methods as complementary or alternative exhaust gas filtration techniques for non-road diesel engines. Full article

This study investigates the emission characteristics and environmental impacts of pollutants from bagasse-fired biomass boilers through the integrated field monitoring of two sugarcane processing plants in Guangxi, China. Comprehensive analyses of flue gas components, including PM_2.5, NOx, CO, heavy metals, VOCs, HCl, and HF, revealed distinct physicochemical and emission profiles. Bagasse exhibited lower C, H, and S content but higher moisture (47~53%) and O (24~30%) levels compared to coal, reducing the calorific values (8.93~11.89 MJ/kg). Particulate matter removal efficiency exceeded 98% (water film dust collector) and 95% (bag filter), while NOx removal varied (10~56%) due to water solubility differences. Heavy metals (Cu, Cr, Ni, Pb) in fuel migrated to fly ash and flue gas, with Hg and Mn showing notable volatility. VOC speciation identified oxygenated compounds (OVOCs, 87%) as dominant in small boilers, while aromatics (60%) and alkenes (34%) prevailed in larger systems. Ozone formation potential (OFP: 3.34~4.39 mg/m³) and secondary organic aerosol formation potential (SOAFP: 0.33~1.9 mg/m³) highlighted aromatic hydrocarbons (e.g., benzene, xylene) as critical contributors to secondary pollution. Despite compliance with current emission standards (e.g., PM < 20 mg/m³), elevated CO (>1000 mg/m³) in large boilers indicated incomplete combustion. This work underscores the necessity of tailored control strategies for OVOCs, aromatics, and heavy metals, advocating for stricter fuel quality and clear emission standards to align biomass energy utilization with environmental sustainability goals. Full article

The impact of black carbon (BC) emissions on climate change, human health, and the environment is well-documented in the scientific literature. Although BC still remains largely unregulated at the international level, efforts have been made to reduce emissions of BC and Particulate Matter (PM_2.5), particularly in sectors such as energy production, industry, and road transport. In contrast, the maritime shipping industry has made limited progress in reducing BC emissions from ships, mainly due to the absence of stringent BC emission regulations. While the International Maritime Organization (IMO) has established emission limits for pollutants such as SO_x, NO_x, and VOCs under MARPOL Annex VI, as of today, BC emissions from ships are still unregulated at the international level. Whereas it was anticipated that PM_2.5 and BC emissions would be reduced with the adoption of the SO_x regulations, especially within the sulfur emission control areas (SECA), this study reveals that BC emissions are only partially affected by the current MARPOL Annex VI regulations. Based on 886 real-world black carbon (BC) emission measurements from ships operating in the southern North Sea, the study demonstrates that SECA-compliant fuels do contribute to a notable decrease in BC emissions. However, it is important to note that the average BC emission factors (EFs) within the SECA remain comparable in magnitude to those reported for non-compliant fuels in earlier studies. Moreover, ships using exhaust gas cleaning systems (EGCSs) as a SECA-compliant measure were found to emit significantly higher levels of BC, raising concerns about the environmental sustainability of EGCSs as an emissions mitigation strategy. Full article