Search Results (7,555)

In this study, the PM_2.5 pollution transport budget in the atmospheric boundary layer (ABL) of Beijing–Tianjin–Hebei (BTH) and Chengdu–Chongqing (CY) was quantitatively evaluated from the perspective of horizontal and vertical exchange. Based on the aircraft meteorological data relay (AMDAR) observation data, the study found that the vertical exchange process of pollutants is mainly influenced by the combined effects of meteorological conditions and topographical factors. Meteorological factors determine the direction and intensity of the vertical exchange, while the complexity of the terrain affects the exchange pattern through local circulation and air flow convergence. The characteristics of the pollution transport budget between the BTH and CY regions show that the BTH region has a net output of pollutants throughout the year, while the CY region has a net input of pollutants. The total transport budget of the four typical representative seasons in BTH is negative. It indicated that BTH, as the region with the highest intensity of air pollution emission in China, is dominated by outward transport of air pollutants to surrounding regions. Due to the influence of topographic and meteorological conditions in the CY region, the air pollutants tend to accumulate in the basin rather than diffuse. The transport budget relationship of the four seasons is positive and the input of air pollutants can be obviously simulated. Combined with the results of the vertical wind profile, Beijing is more vulnerable to the prevailing cold air sinking in the northwest in winter, which is characterized by the inflow of the free troposphere (FT) into the ABL. As for Chongqing, it is blocked by mountains so that the gas convection at the top of the ABL is obvious. This horizontal convergence phenomenon induces upward vertical movement, which makes Chongqing show a strong characteristic of the ABL transport to the FT. Full article

Plastic pollution has emerged as a critical environmental challenge due to the widespread accumulation of petrochemical plastics in natural ecosystems. Conventional waste management strategies, including mechanical recycling and incineration, have demonstrated limited efficiency in addressing the persistence of plastics such as polyethylene, polypropylene, polyethylene terephthalate, and polyvinyl chloride. While incineration eliminates plastic material, it does not promote circularity and may generate toxic emissions. As a sustainable alternative, microbial biodegradation involves bacteria, fungi, and actinomycetes capable of degrading synthetic polymers through enzymatic processes. This review provides a comprehensive overview of microbial degradation of major plastics such as polyethylene, polypropylene, polyethylene terephthalate, and polyvinyl chloride, highlighting key strains, degradation rates, and enzymatic mechanisms. Importantly, biodegradation research also informs the development of in situ remediation technologies and supports new recycling strategies. Advances in protein engineering and synthetic biology are discussed for enhancing degradation efficiency. However, scaling biodegradation to environmental conditions remains challenging due to variable temperature, pH, microbial competition, and potentially toxic intermediates. Despite these limitations, microbial biodegradation represents a promising ecofriendly approach to address plastic waste and promote a biobased circular economy. Future work should integrate microbial processes into existing recycling infrastructure and design robust consortia guided by omics tools. Full article

Natural gas (NG) engine catalysts face unique challenges in emission control due to their distinct raw emission characteristics. This study investigates the exhaust conversion and by-product generation of a Palladium-based catalyst of an NG engine through small-sample catalyst experiments, mainly focusing on the effect of feed gas composition on the conversion efficiency and N₂O/NH₃ emissions. Results show that N₂O is generated via NO reduction by H₂ (80~275 °C) and CO (275~400 °C) in the temperature range of 80~400 °C. NH₃ generation occurs at 175~550 °C, mainly via NO reduction by H₂ (supplied from the water–gas shift (WGS) reaction) and CO below 425 °C and exclusively by H₂ (supplied from the steam reforming (SR) reaction) above 425 °C. An increase (0.9705~1.0176) in lambda enhances CO and CH₄ conversion while reducing N₂O and NH₃ emissions, but it inhibits NO conversion and promotes NO₂ formation. A lambda of 0.9941 achieves high conversion efficiency (≥90%) for CO, CH₄, and NO, with reduced N₂O and zero NH₃ emissions. An increase in H₂O (8~16%) accelerates the WGS and SR reactions, improving pollutant conversion. However, it aggravates N₂O and NH₃ emissions, with peak levels rising by 54% and 31%, respectively. Increased H₂ (500~1500 ppm) preferentially consumes NO and reversely shifts the equilibrium of the WGS and SR reactions, reducing CO and CH₄ conversion while improving NO conversion. And it promotes N₂O selectivity at high temperature and NH₃ selectivity at low temperature and peak emissions, with peak concentrations increasing by 58% and 15%, respectively. These findings reveal the by-product formation mechanism in the catalyst, providing valuable insights for the emission control of NG-fueled engines. Full article

This study employs a systems theory approach to investigate the coupling coordination and driving mechanisms within the economic–social–environmental (ESE) system in China’s ethnic regions. It analyzes 67 ethnic counties in Sichuan Province, using an integrated framework that combines dynamic Shannon entropy, coupling coordination modeling, and GeoDetector. Based on data from 2005 to 2024, the study reveals the spatiotemporal patterns of ESE coupling coordination. The key findings are as follows: (1) The coupling coordination degree has gone through four stages: moderate imbalance → mild imbalance → primary coordination → moderate coordination. By 2024, 81.8% of counties had achieved coordinated development, and “highly coordinated” counties emerged for the first time. (2) The Western Sichuan Plateau has formed a high–high agglomeration zone by monetizing ecological assets and utilizing ethnic cultural resources. In contrast, the hilly and parallel ridge–valley regions in central and eastern Sichuan remain in low–low agglomerations due to their dependency on traditional industrialization paths. The decrease in high–low and low–high outliers indicates the recent policy polarization effects. (3) The interaction between habitat quality and per capita GDP has the strongest explanatory power. The rising marginal contributions of energy and carbon emission intensity suggest that green industrialization is crucial to breaking the “poverty–pollution” trap. Full article

Environmental emissions from the maritime sector, including CO₂, NO_x, and SO_x, contribute significantly to global air pollution and climate change. The International Maritime Organization (IMO) has set a target to reduce greenhouse gas emissions from international shipping to reach zero GHG by 2050 compared to 2008 levels. To meet these goals, the IMO strongly encourages the transition to alternative fuels, such as hydrogen, ammonia, and biofuels, as part of a broader decarbonization strategy. This study presents a comparative analysis of converting conventional diesel engines to dual-fuel systems utilizing alternative fuels such as methanol or natural gas. The methodology of this research is based on theoretical calculations to estimate various types of emissions produced by conventional marine fuels. These results are then compared with the emissions generated when using methanol and natural gas in dual-fuel engines. The analysis is conducted using the EVER ALOT container ship as a case study. The evaluation focuses on both environmental and economic aspects of engines operating in natural gas–diesel and methanol–diesel dual-fuel modes. The results show that using 89% natural gas in a dual fuel engine reduces nitrogen oxides (NO_x), sulfur oxides (SO_x), carbon dioxide (CO₂), particulate matter (PM), and carbon monoxide (CO) pollutions by 77.69%, 89.00%, 18.17%, 89.00%, and 30.51%, respectively, while the emissions percentage will be 77.78%, 91.00%, 54.67%, 91.00%, and 55.90%, in order, when using methanol as a dual fuel with percentage 91.00% Methanol. This study is significant as it highlights the potential of natural gas and methanol as viable alternative fuels for reducing harmful emissions in the maritime sector. The shift toward these cleaner fuels could play a crucial role in supporting the maritime industry’s transition to low-emission operations, aligning with global environmental regulations and sustainability goals. Full article

This paper contains a comparison of air pollutant emissions of different vehicle types and a presentation of the issue of assessing the environmental impact of hybrid, conventional, and electric vehicles in terms of the changing electricity production sources in Poland over time. The research method used in this paper for hybrid and conventional vehicles was on-road testing of air pollutant emissions using the SEMTECH DS analyzer. Air pollutant emissions from electric vehicles were determined based on the authors’ analytical method involving air pollutant emission factors published annually in Poland by the National Centre for Emissions Management (KOBiZE). Measurements of on-road air pollutant emissions for hybrid and conventional vehicles were compared with electric vehicle emissions; however, the electric vehicle emissions covered the area of electricity production. The hybrid vehicle emissions recorded in on-road tests have been corrected for the emissions that arise from the production of the electricity consumed by the hybrid vehicle. The recovery phenomenon was not analyzed. The aim of this paper is to compare air pollutant emissions of electric vehicles with those of hybrid and conventional vehicles, considering the energy transition that has taken place in Poland in the last decade. Full article

Recycled water is commonly considered an environmentally friendly alternative water source for urban water systems, which can not only serve as a solution for water scarcity, but also reduce wastewater discharge from sewage systems. However, owing to the high degree of energy consumption during recycled water production, the utilization of recycled water may be detrimental to greenhouse gas emission reduction. In this work, we conduct a detailed investigation into greenhouse gas emissions from different sources in a typical multisource urban water system in China. Furthermore, we develop an optimization model for water resource allocation based on the rime optimization algorithm and regret theory. The results show that although greenhouse gas emissions from recycled water exceed those from other sources, their impact can be eliminated through rational water resource allocation. Specifically, compared with the original water resource allocation, the optimal results effectively reduce pollutant emissions by 7.6~11.1% without excessively increasing water resource shortages and greenhouse gas emissions. Additionally, both subjective preferences and recycled water utilization conditions have significant impacts on the optimization results, which should be carefully selected according to practical situations and technologies. Overall, the methods developed in this study provide a new general framework for the water resource allocation of multisource urban water systems in the context of greenhouse gas emission reduction and recycled water utilization, which can be employed in other areas. Full article

Air pollution is one of the major environmental challenges worldwide. Settleable particulate matter (SPM), related to this environmental problem, contains metals capable of producing negative effects on human health (e.g., cardiovascular and respiratory illness). For this study, continuous monitoring was carried in the urban city of Loja (Ecuador), where 10 points were distributed based on different land uses. Samples were collected on a monthly basis using a passive method, by means of samplers built based on the 502 Method. The gravimetric method was then used in the laboratory to determine the concentration of SPM. The inductively coupled plasma–optical emission spectroscopy (ICP-OES) technique was used to identify the presence of metals as such as Copper (Cu), Lead (Pb), Cobalt (Co), Cadmium (Cd), Chromium (Cr), Silver (Ag), Arsenic (As), and Mercury (Hg) in SPM. The results obtained showed that SPM and As differed significantly between land uses, but most metals showed significant differences in relation to temporal changes. Although 90% of the sampling points show SPM concentrations within the limits established by environmental regulations, some of the points exceed the World Health Organization (WHO) limit of 0.5 mg/cm². Finally, the temporal changes in more metals were clearly observed, probably because of increased combustion processes (vehicular traffic), with a higher percentage of metals clearly observed during the April and August months. Furthermore, the highest levels of vegetation burning in Loja province, including the surroundings of the city of Loja, occurred in August. This analysis provides essential data to guide environmental monitoring and air quality management strategies, aiming to reduce health risks from long-term exposure to metal-enriched particulate matter. Full article

Mass gatherings such as the annual Hajj pilgrimage in Makkah, Saudi Arabia, generate extreme, short-term anthropogenic emission loads with significant air quality and public health implications. This study assesses the spatiotemporal dynamics of key atmospheric pollutants—including nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂), formaldehyde (HCHO), and aerosols—across Makkah and its holy sites before and during the Hajj seasons of 2023 and 2024. Using high-resolution Sentinel-5P TROPOMI satellite data, pollutant fields were reconstructed at 100 m spatial resolution via cloud-based geospatial analysis on the Google Earth Engine. During Hajj 2023, spatially resolved NO₂ concentrations ranged from 15.4 μg/m³ to 38.3 μg/m³ with an average of 24.7 μg/m³, while SO₂ during the 2024 event peaked at 51.2 μg/m³ in key hotspots, occasionally exceeding World Health Organization (WHO) guideline values. Aerosol index values showed episodic surges (up to 1.43), particularly over transportation corridors, parking areas, and logistics facilities. CO concentrations reached values as high as 1069.8 μg/m³ in crowded zones, and HCHO concentrations surged up to 9.99 μg/m³ during peak periods. Quantitative correlation analysis revealed that during Hajj, atmospheric chemistry diverged from urban baseline: the NO₂–SO₂ relationship shifted from strongly negative pre-Hajj (r = −0.74) to moderately positive during the event (r = 0.35), while aerosol–HCHO correlations intensified negatively from r = −0.23 pre-Hajj to r = −0.50 during Hajj. Meteorological analysis indicated significant positive correlations between wind speed and NO₂ (r = 0.35) and wind speed and CO (r = 0.35) during 2024, demonstrating that extreme emission rates overwhelmed typical dispersive processes. Relative humidity was positively correlated with aerosol loading (r = 0.37), pointing to hygroscopic growth patterns. These results quantitatively demonstrate that Hajj drives a distinct, event-specific pollution regime, characterized by sharp increases in key pollutant concentrations, altered inter-pollutant and pollutant–meteorology relationships, and spatially explicit hotspots driven by human activity and infrastructure. The integrated satellite–meteorology workflow enabled near-real-time monitoring in a data-sparse environment and establishes a scalable framework for evidence-based air quality management and health risk reduction in mass gatherings. Full article

Particulate matter (PM) is a significant air pollutant in modern egg production. However, high-quality PM data from commercial egg farms are still very limited. A 6-month study, covering both cold and hot seasons, measured PM₁₀ concentrations and emissions in a 140,000-hen commercial laying hen house in the Midwest USA. An advanced measurement system was implemented for continuous and real-time monitoring, collecting data from 67 online instruments and sensors. The study generated 4318 h of valid PM₁₀ data, with 97.8% data completeness. The average daily mean (ADM) PM₁₀ concentration in the house exhaust air, standardized to 20 °C and 1 atm, was 236 ± 162 (ADM ± standard deviation) µg m⁻³. The ADM net PM₁₀ emission was 18.9 ± 2.2 mg d⁻¹ hen⁻¹. Increasing outdoor temperatures were correlated with decreased indoor PM₁₀ concentrations but increased overall emissions. Comparison with the ADM emission of 12.4 ± 13.3 mg d⁻¹ hen⁻¹ from the same house during a previous six-month study in 2004–2005 revealed that artificial hen molting in this study increased PM₁₀ concentrations and emissions. Extrapolating the ADM PM₁₀ emission from the house, the ADM PM₁₀ emission from the entire egg farm was estimated at 35.6 ± 31.1 kg d⁻¹ (or 35.6 ± 4.5 kg d⁻¹ with a 95% confidence interval). This study provides valuable insights into air quality in animal agriculture and contributes high-quality and real-world data for use in data-driven approaches such as artificial intelligence, machine learning, data mining, and big data analytics. Full article

This paper investigates the dispersion of atmospheric pollutants in urban environments using a fractional-order convection–diffusion-reaction model with dynamic line sources associated with vehicle traffic. The model includes Caputo fractional time derivatives and Riesz fractional space derivatives to account for memory effects and non-local transport phenomena characteristic of complex urban air flows. Vehicle trajectories are generated stochastically on the road network graph using Dijkstra’s algorithm, and each moving vehicle acts as a mobile line source of pollutant emissions. To reflect the daily variability of emissions, a time-dependent modulation function determined by unknown parameters is included in the source composition. These parameters are inferred by solving an inverse problem using synthetic concentration measurements from several fixed observation points throughout the area. The study presents two main contributions. Firstly, a detailed numerical analysis of how fractional derivatives affect pollutant dispersion under realistic time-varying mobile source conditions, and secondly, an evaluation of the performance of the proposed parameter estimation method for reconstructing time-varying emission rates. The results show that fractional-order models provide increased flexibility for representing anomalous transport and retention effects, and the proposed method allows for reliable recovery of emission dynamics from sparse measurements. Full article

The health risks of PM_2.5-bound metals highlight the need for burden assessment, metal prioritization, and key factor analysis to support effective air quality management, yet relevant studies remain limited. Shandong Province is one of the most polluted regions in northern China, providing an ideal setting for this investigation. We monitored 17 PM_2.5-bound metals for three years across Shandong, China and performed disease burden assessment based on disability-adjusted life years (DALYs). Furthermore, key influencing factors contributing to high-hazard metals were identified through explainable machine learning. The results showed that PM_2.5-bound metal concentrations were generally higher in inland areas than in coastal regions, with Ni concentrations elevated in coastal areas. K, Ca, Zn, and Mn exhibited the highest three-year average concentrations among the metals, while Cr averaged 6.12 ng/m³, significantly exceeding the recommended annual limit of 0.025 ng/m³ set by Chinese Ambient Air Quality Standards. Jinan carried the greatest burden at 4.67 DALYs per 1000 people, followed by Zibo (3.78), Weifang (2.98), and Rizhao (2.80). CKD, interstitial pneumonia, and chronic respiratory diseases account for the highest DALYs from PM_2.5-bound metals in Shandong Province. Industrial emissions are the largest contributors to the disease burden (>34%), with Cr, Cd, and Pb as the primary contributing metals requiring priority control. Fractional vegetation cover was identified as the key factor contributing to the reduction in their concentrations. These results underscore that prioritizing the regulation of industrial combustion, particularly concerning Cr, Cd, and Pb, and enhancing fractional vegetation cover could reduce disease burden and provide public health benefits. Full article

In Central Asian countries (CACs) Yes. we agree to remove Highlights part atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

Background: Exposure to indoor air pollution (IAP), including particulate matter of size 2.5 µm/m³ (PM_2.5) and carbon monoxide (CO) resulting from the combustion of biomass fuels in homes, is an important risk factor associated with growth and developmental delays in neonates. We investigated the association between exposure to HAP and adverse birth outcomes in a birth cohort study of 594 pregnant females in Sri Lanka. Methods: Pregnant females between the ages of 18 and 40 years were enrolled in their first trimester and followed until delivery. Baseline assessments of fuel used for cooking were used to categorize the females into high-exposure (wood and kerosene) or low-exposure (liquid petroleum gas and electricity) groups. Indoor air quality measurements of PM_2.5 (n = 303) and CO (n = 258) were conducted in a subgroup of households. The outcomes at birth included the neonates’ appearance, pulse, grimace, activity, respiration (APGAR) score, Brazelton Neonatal Behavioural Assessment Scale (BNBAS) score, and birth weight. Linear and logistic regressions were used to evaluate the association between household air pollution (HAP) and birth outcomes. Results: Of the 526 neonates assessed at delivery, 55.7% were born to mothers with high HAP exposure and 44.3% with low HAP exposure, respectively. The results of the linear regression found an inverse association between higher exposure to HAP and birthweight in the adjusted and unadjusted models; the birth weight of children in the high-exposure group was lower by 107 g compared to that of the low-exposure group after adjusting for other variables (β = −106.8; 95% confidence intervals: −197.6, −16.0). Exposure status was not associated with birth length, gestational age, or the APGAR score; however, the BNBAS motor score was significantly lower in the neonates of the high-exposure group (6.41 vs. 6.55, p = 0.04), though it was not significant when adjusted for other variables. No correlation was found between the measured indoor PM_2.5 levels and birth weight, birth length, gestational age, APGAR score, or BNBAS score. Conclusions: Exposure to IAP due to emissions from combustion products from biomass fuels adversely affects birth weight. These effects may be more pronounced in vulnerable populations in settings where primary healthcare for pregnant women is limited. Full article

Urban traffic congestion remains a major contributor to vehicle emissions and travel inefficiency, prompting the need for adaptive and intelligent traffic management systems. In response, we introduce DeepSIGNAL-ITS (Deep Learning Signal Intelligence for Adaptive Lights in Intelligent Transportation Systems), a unified framework that leverages real-time traffic perception and learning-based control to optimize signal timing and reduce congestion. The system integrates vehicle detection via the YOLOv8 architecture at roadside units (RSUs) and manages signal control using Proximal Policy Optimization (PPO), guided by global traffic indicators such as accumulated vehicle waiting time. Secure communication between RSUs and cloud infrastructure is ensured through Transport Layer Security (TLS)-encrypted data exchange. We validate the framework through extensive simulations in SUMO across diverse urban settings. Simulation results show an average 30.20% reduction in vehicle waiting time at signalized intersections compared to baseline fixed-time configurations derived from OpenStreetMap (OSM). Furthermore, emissions assessed via the HBEFA-based model in SUMO reveal measurable reductions across pollutant categories, underscoring the framework’s dual potential to improve both traffic efficiency and environmental sustainability in simulated urban environments. Full article