Search Results (235)

Given the deteriorating situation of ambient ozone (O₃) pollution in some areas of China, understanding the mechanisms driving O₃ formation is essential for formulating effective control measures. This study examines O₃ formation mechanisms and RO_x (OH, HO_2, and RO₂) radical cycling driven by photochemical processes in Bozhou, located at the junction of Jiangsu–Anhui–Shandong–Henan (JASH), a region heavily affected by O₃ pollution, by applying a zero-dimensional box model (Framework for 0-Dimensional Atmospheric Modeling, F0AM) coupled with the Master Chemical Mechanism (MCM v3.3.1) and Positive Matrix Factorization (PMF 5.0) to characterize O₃ pollution, identify volatile organic compound (VOC) sources, and quantify radical budgets during pollution episodes. The results show that O₃ episodes in Bozhou mainly occurred in June under conditions of high temperature and low wind speed. Oxygenated volatile organic compounds (OVOCs), alkanes, and halocarbons were the dominant VOCs groups. The CH₃O₂ + NO reaction accounted for 24.3% of O₃ production, while photolysis contributed 68.7% of its removal. Elevated VOCs concentrations in Bozhou were largely maintained by anthropogenic sources such as vehicle exhaust, solvent utilization, and gasoline evaporation, which collectively enhanced O₃ production. The findings indicate that O₃ formation in the region is primarily regulated by NO_x availability. Therefore, emission reductions targeting NO_x, along with selective control of OVOCs and alkenes, would be the most effective strategies for lowering O₃ levels. Model simulations further highlight Bozhou’s strong atmospheric oxidation capacity, with OVOC photolysis identified as the dominant contributor to RO_x generation, accounting for 33% of the total. Diurnal patterns were evident: NO_x-related reactions dominated radical sinks in the morning, while HO₂ + RO₂ reactions accounted for 28.5% in the afternoon. By clarifying the mechanisms of O₃ formation in Bozhou, this study provides a scientific basis for designing ozone control strategies across the JASH junction region. In addition, ethanol was not directly measured in this study; given its potential to generate acetaldehyde and affect local O₃ formation, its possible contribution introduces additional uncertainty that warrants further investigation. Full article

This work addresses the issue of estimating air pollution maps for urban areas. Spatially dense maps of air pollution can be calculated using physical models, such as ADMS-Urban; however, due to the high computational cost of such models, maps are verified with low temporal resolution (such as monthly or yearly averages). We investigate the feasibility of using machine learning models to predict air pollution maps based on historical data and current measurements from a limited number of monitoring stations. The models are trained on spatially dense pollution maps generated by physical models, along with corresponding measurements from monitoring stations and selected meteorological data. We evaluate the performance of the models using real-world data from a central district in Wrocław, Poland, considering various pollutants such as $P{M}_{2.5}$, $P{M}_{10}$, CO, VOC, and NOx, presented on spatially dense pollution maps with ca. $2\times {10}^5$ points with a 10 × 10 m grid. The results demonstrate that the proposed method can effectively predict air pollution maps with high spatial resolution and a fast inference time, making it suitable for generating pollution maps with significantly higher temporal resolution (e.g., hourly) compared to physical models. We also experimentally demonstrated that PM10, CO, and VOC pollution models can be built based on measurements from $P{M}_{2.5}$ monitoring stations only with similar, and in the case of CO, higher, accuracy than using measurements from $P{M}_{10}$, CO, and VOC monitoring stations, respectively. Full article

Background: Submarines represent extremely confined environments where breathing air is continuously recirculated for extended periods with minimal renewal, generating complex multipollutant atmospheres. Objectives: This critical narrative review aims to (i) summarize sources and composition of submarine indoor air, (ii) evaluate respiratory and cardiovascular risks for crews, and (iii) assess current purification technologies. Methods: A narrative review was conducted following PRISMA recommendations applicable to non-systematic reviews. The PubMed search covered all years from inception to September 2025, complemented by backward citation tracking and technical reports. Results: Eligible studies consistently report elevated levels of CO₂, VOCs, NO_X, CO, PM_2.5, and bioaerosols aboard submarines. Evidence from submariner cohorts and toxicological studies indicates risks of airway irritation, impaired mucociliary defenses, endothelial dysfunction, cardiovascular stress, and neurobehavioral alterations. Conclusions: Submarine indoor air quality is a credible determinant of crew health. Existing filtration systems mitigate some risks but do not address multipollutant mixtures adequately. Improved real-time monitoring, advanced filtration, CFD-guided airflow optimization, and longitudinal medical surveillance are necessary. Full article

This study presents a well-to-wheel life-cycle assessment (WTW-LCA) comparing battery-electric heavy-duty trucks (BEVs) with conventional diesel trucks, utilizing real-world fleet data from Southern California’s Volvo LIGHTS project. Class 7 and Class 8 vehicles were analyzed under ISO 14040/14044 standards, combining measured diesel emissions from portable emissions measurement systems (PEMSs) with BEV energy use derived from telematics and charging records. Upstream (“well-to-tank”) emissions were estimated using USLCI datasets and the 2020 Southern California Edison (SCE) power mix, with an additional scenario for BEVs powered by on-site solar energy. The analysis combines measured real-world energy consumption data from deployed battery electric trucks with on-road emission measurements from conventional diesel trucks collected by the UCR team. Environmental impacts were characterized using TRACI 2.1 across climate, air quality, toxicity, and fossil fuel depletion impact categories. The results show that BEVs reduce total WTW CO₂-equivalent emissions by approximately 75% compared to diesel. At the same time, criteria pollutants (NO_x, VOCs, SO_x, PM_2.5) decline sharply, reflecting the shift in impacts from vehicle exhaust to upstream electricity generation. Comparative analyses indicate BEV impacts range between 8% and 26% of diesel levels across most environmental indicators, with near-zero ozone-depletion effects. The main residual hotspot appears in the human-health cancer category (~35–38%), linked to upstream energy and materials, highlighting the continued need for grid decarbonization. The analysis focuses on operational WTW impacts, excluding vehicle manufacturing, battery production, and end-of-life phases. This use-phase emphasis provides a conservative yet practical basis for short-term fleet transition strategies. By integrating empirical performance data with life-cycle modeling, the study offers actionable insights to guide electrification policies and optimize upstream interventions for sustainable freight transport. These findings provide a quantitative decision-support basis for fleet operators and regulators planning near-term heavy-duty truck electrification in regions with similar grid mixes, and can serve as an empirical building block for future cradle-to-grave and dynamic LCA studies that extend beyond the operational well-to-wheels scope adopted here. Full article

Simultaneous catalytic elimination of nitrogen oxides (NO_x) and volatile organic compounds (VOCs) represents a promising technology for addressing the synergistic pollution of fine particulate matters of <2.5 μm diameter (PM_2.5) and O₃. Nevertheless, it has been maintaining significant challenges in practical implementation, particularly the inherent mismatch in temperature windows between NO_x reduction and VOCs oxidation pathways, coupled with catalyst poisoning and deactivation phenomena. These limitations have hindered the industrial application of bifunctional catalysts for the removal of concurrent pollutant. This review systematically explored the fundamental mechanisms and functional roles of active sites in controlling synchronous catalytic processes. The mechanism of catalyst deactivation caused by multiple toxic substances has been comprehensively analyzed, including sulfur dioxide (SO₂), water vapor (H₂O), chlorine-containing species (Cl*), reaction by-products, and heavy metal contaminants. Furthermore, we critically evaluated the strategies of doping regulation, nanostructure engineering and morphology optimization to enhance the performance and toxicity resistance of catalysts. Meanwhile, emerging regeneration techniques and reactor design optimizations are discussed as potential solutions to improve the durability of catalysts. Based on the above critical aspects, this review aims to provide insights and guidelines for developing robust catalytic systems capable of controlling multi-pollutants in practical applications, and to offer theoretical guidance and technical solutions to bridge the gap between laboratory research and industrial environmental governance applications. Full article

Understanding aerosol chemical components’ roles in light extinction is critical for air quality management and climate mitigation. This study compared PM₁ optical properties and chemical compositions in Shanghai (southern China) and Dezhou (northern China) during winter using high-resolution aerosol mass spectrometers and optical instruments. Results showed PM₁ scattering coefficients (10.9–549.8 Mm⁻¹) in Shanghai were dominated by traffic-related organic aerosols (OA) (45.2%), with ammonium sulfate and nitrate contributing 60.5% of extinction. In Dezhou, higher scattering coefficients (3.5–2635.1 Mm⁻¹) were driven by heating/biomass burning, with OA accounting for 57.8% and ammonium nitrate 27.2%. Mass scattering efficiencies (MSEs) in Dezhou were significantly higher (sulfate: 10.75 m²/g; nitrate: 10.15 m²/g; OA: 4.9 m²/g) than those in Shanghai (4.2/3.85/3.00 m²/g). Pollution episodes revealed distinct mechanisms: high-humidity OA accumulation for Shanghai vs. nitrate-organic synergy for Dezhou. The IMPROVE model systematically underestimated scattering coefficients, emphasizing the need for region-specific parameterization. OA was identified as the primary scattering contributor in both cities, though inorganic species became critical under high-pollution conditions. These findings suggest targeted strategies: reducing VOC emissions in southern China and controlling NOx in northern industrial areas to improve winter visibility and air quality. Full article

Ground-level ozone is a critical secondary air pollutant and greenhouse gas, especially in urban oil and gas regions, where it poses severe public health and environmental risks. Urban areas in North Texas have experienced persistently elevated ozone levels over the past two decades despite emission control efforts, highlighting the need for advanced forecasting tools. This study presents a hybrid recurrent neural network (RNN) model that combines Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) architectures to predict 8 h average ground-level ozone concentrations over a full annual cycle. The model leverages one-hour lagged ozone precursor pollutants (VOC and NO_x) and seven meteorological variables, using a novel framework designed to capture complex temporal dependencies and spatiotemporal variability in environmental data. Trained and validated on multi-year datasets from two distinctly different urban air quality monitoring sites, the model achieved high predictive accuracy (R² ≈ 0.97, IoA > 0.96), outperforming standalone LSTM and Random Forest models by 6–12%. Beyond statistical performance, the model incorporates Shapley Additive exPlanation (SHAP) analysis to provide mechanistic interpretability, revealing the dominant roles of relative humidity, temperature, solar radiation, and precursor concentrations in modulating ozone levels. These findings demonstrate the model’s effectiveness in learning the nonlinear dynamics of ozone formation, outperforming traditional statistical models, and offering a reliable tool for long-term ozone forecasting and regional air quality management. Full article

Tropospheric ozone (O₃) is a harmful air pollutant and a short-lived greenhouse gas. To find effective O₃ reduction strategies, it is essential to understand the sensitivity of O₃ concentrations to its precursors, nitrogen oxides (NO_x), and volatile organic compounds (VOC). This study applied the Community Multi-Scale Air Quality model (CMAQ) to assess the effects of domestic anthropogenic emissions in 2015 and 2050. The emission scenarios were based on Japan’s CO₂ reduction targets, assuming an 80% decrease by 2050. Sensitivity analysis was performed by adjusting NO_x and VOC emissions by ±10% and ±20%, respectively, and examining seasonal and regional variations in the O₃ response. The results show that O₃ levels will decrease notably in spring and summer by 2050, although concentrations will still exceed the standards in some areas. NO_x reductions lead to significant O₃ decreases, while VOC reductions show limited benefits, except in urban regions such as Kanto and Kansai. In winter, NO_x reductions may even increase O₃ levels due to weakened titration. Overall, the findings highlight the importance of prioritizing NO_x control measures for effective O₃ mitigation in Japan’s future energy transition. Full article

Heavy-duty diesel trucks (HDDTs) are recognized as significant sources of air pollutants and greenhouse gases (GHGs) along freight corridors in port cities. Despite their impact, few studies have provided detailed spatiotemporal insights into their emissions within port-adjacent highway systems. This study presents a high-resolution, hourly emission inventory at the road-segment level for six major expressways in Shanghai, one of China’s leading port cities. The emission estimates are derived using a locally adapted COPERT V model, calibrated with HDDT GPS trajectory data and detailed road network information from OpenStreetMap. The inventory quantifies emissions of CO₂, NO_x, CO, PM, and VOCs, highlighting distinct temporal and spatial variation patterns. Weekday emissions consistently exceed those of weekends, with three prominent traffic-related peaks occurring between 5:00–7:00, 10:00–12:00, and 14:00–16:00. Spatial analysis identifies the G1503 and S20 expressways as major emission corridors, with S20 exhibiting particularly high emission intensity relative to its length. Combined spatiotemporal patterns reveal that weekday emission hotspots are more concentrated, reflecting typical freight activity cycles such as morning dispatch and afternoon return. The findings provide a scientific basis for formulating more precise emission control measures targeting HDDT operations in urban port environments. Full article

As an energy-intensive sector, China’s iron and steel industry is crucial for achieving “Dual Carbon” goals. This study fills the research gap in systematically comparing the synergistic effects of multiple policies by evaluating five key measures (2020–2023) in ultra-low-emission retrofits and clean energy alternatives. Using public macro-data at the national level, this study quantified cumulative reductions in air pollutants (SO₂, NOx, PM, VOCs) and CO₂. A synergistic control effect coordinate system and a normalized synergistic emission reduction equivalent (AP_eq) model were employed. The results reveal significant differences: Sintering machine desulfurization and denitrification (SDD) showed the highest AP_eq but increased CO₂ emissions in 2023. Dust removal equipment upgrades (DRE) and unorganized emission control (UEC) demonstrated stable co-reduction effects. While electric furnace short-process steelmaking (ES) and hydrogen metallurgy (HM) showed limited current benefits, they represent crucial deep decarbonization pathways. The framework provides multi-dimensional policy insights beyond simple ranking, suggesting balancing short-term pollution control with long-term transition by prioritizing clean alternatives. Full article

Currently, ozone (O₃) has become one of the primary air pollutants in China, underscoring the importance of analyzing ozone formation sensitivity (OFS) for effective pollution control. Ozone sensitivity indices serve as effective tools for OFS identification. Among them, the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NO_x)—such as the formaldehyde-to-nitrogen dioxide ratio (FNR, defined as HCHO/NO₂, where HCHO represents VOCs and NO₂ represents NO_x)—is one of the most widely used satellite-based indicators. Recent studies have highlighted glyoxal (CHOCHO) as another critical ozone precursor, prompting the proposal of the glyoxal-to-nitrogen dioxide ratio (GNR, CHOCHO/NO₂) as an alternative metric. This study systematically compares the performance of FNR and GNR across four major urban agglomerations in China: Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Chengdu–Chongqing (CY) region, by integrating satellite remote sensing with ground-based observations. Results reveal that both indices exhibit consistent spatial trends in OFS distribution, transitioning from VOC-limited regimes in urban centers to NO_x-limited regimes in surrounding suburban areas. However, differences emerge in threshold values and classification outcomes. During summer, FNR identifies urban areas as transitional regimes (or VOC-limited in regions such as YRD and PRD), while suburban areas are classified as NO_x-limited. In contrast, GNR, which shows heightened sensitive to anthropogenic VOCs (AVOCs), exhibits a more restricted spatial extent in the transition regimes. By autumn, most urban areas shift toward VOC-limited regimes, while suburban regions remain NO_x-limited. Thresholds for both VOCs and NO_x increase during this period, with GNR demonstrating stronger sensitivity to NO_x. These findings underscore that the choice between FNR and GNR directly influences OFS determination, as their differing responses to biogenic and anthropogenic emissions lead to different conclusions. Future research should focus on integrating the complementary strengths of both indices to develop a more robust OFS identification method, thereby providing a theoretical basis for formulating effective ozone control strategies. Full article

Atmospheric formaldehyde (HCHO) is a major component of oxygenated volatile organic compounds (OVOCs) and plays an important role in O₃ formation and atmospheric oxidation capacity. In this study, seasonal observations of gaseous pollutants (HCHO, O₃, peroxyacetyl nitrate (PAN), CO, NOx, and VOCs) and ambient conditions (J_HCHO, J_NO2, solar radiation, temperature, relative humidity, wind speed, and wind direction) were conducted in a coastal city in southeast China. The average HCHO concentrations were 2.54 ppbv, 3.38 ppbv, 2.53 ppbv, and 1.98 ppbv in spring, summer, autumn, and winter, respectively. Diurnal variations were high in the daytime and low in the nighttime, and the peak times varied in different seasons. The correlation between HCHO and O₃ was not significant in spring and winter, which is likely related to the effects of photochemical reactions and diffusion conditions. The contributions of background (23.0%), primary (47.6%), and secondary (29.4%) sources to HCHO were quantified using multiple linear regression (MLR) models, revealing that secondary formation was the most significant contributor in summer, whereas primary emissions were predominant in spring. These findings help to improve the understanding of the influence of atmospheric formaldehyde on photochemical pollution control in coastal cities. Full article

The acceleration of industrialization and urbanization have led to the increasingly serious problem of waste gas pollution. Pollutants such as sulfur dioxide (SO₂), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH₃), formaldehyde (HCHO), and hydrogen sulfide (H₂S) emitted from industrial production, transportation, and agricultural activities have posed a major threat to the ecological environment and public health. Although traditional physical and chemical treatment methods can partially reduce the concentration of pollutants, they face three core bottlenecks of high cost, high energy consumption, and secondary pollution, and it is urgent to develop sustainable alternative technologies. In this context, probiotic waste gas treatment technology has become an emerging research hotspot due to its environmental friendliness, low energy consumption characteristics, and resource conversion potential. Based on the databases of PubMed, Web of Science Core Collection, Scopus, Embase, and Cochrane Library, this paper systematically searched the literature published from 2014 to 2024 according to the predetermined inclusion and exclusion criteria (such as research topic relevance, experimental data integrity, language in English, etc.). A total of 71 high-quality studies were selected from more than 600 studies for review. By integrating three perspectives (basic theory perspective, environmental application perspective, and waste gas treatment facility perspective), the metabolic mechanism, functional strain characteristics, engineering application status, and cost-effectiveness of probiotics in waste gas bioconversion were systematically analyzed. The main conclusions include the following: probiotics achieve efficient degradation and recycling of waste gas pollutants through specific enzyme catalysis, and compound flora and intelligent regulation can significantly improve the stability and adaptability of the system. This technology has shown good environmental and economic benefits in multi-industry waste gas treatment, but it still faces challenges such as complex waste gas adaptability and long-term operational stability. This review aims to provide useful theoretical support for the optimization and large-scale application of probiotic waste gas treatment technology, promote the transformation of waste gas treatment from ‘end treatment’ to ‘green transformation’, and ultimately serve the realization of sustainable development goals. Full article

Reliable, high-resolution emission inventories are essential for accurately simulating air quality and for designing evidence-based mitigation policies. Yet their performance over Japan—where transboundary inflow, strict fuel regulations, and complex source mixes coexist—remains poorly quantified. This study therefore benchmarks four widely used anthropogenic inventories—REAS v3.2.1, CAMS-GLOB-ANT v6.2, ECLIPSE v6b, and HTAP v3—by coupling each to WRF-Chem (10 km grid) and comparing simulated surface PM₂.₅, SO₂, CO, and NO_x with observations from >900 stations across eight Japanese regions for the years 2010 and 2015. All simulations shared identical meteorology, chemistry, and natural-source inputs (MEGAN 2.1 biogenic VOCs; FINN v1.5 biomass burning) so that differences in model output isolate the influence of anthropogenic emissions. HTAP delivered the most balanced SO₂ and CO fields (regional mean biases mostly within ±25%), whereas ECLIPSE reproduced NO_x spatial gradients best, albeit with a negative overall bias. REAS captured industrial SO₂ reliably but over-estimated PM₂.₅ and NO_x in western conurbations while under-estimating them in rural prefectures. CAMS-GLOB-ANT showed systematic biases—under-estimating PM₂.₅ and CO yet markedly over-estimating SO₂—highlighting the need for Japan-specific sulfur-fuel adjustments. For several pollutant–region combinations, absolute errors exceeded 100%, confirming that emissions uncertainty, not model physics, dominates regional air quality error even under identical dynamical and chemical settings. These findings underscore the importance of inventory-specific and pollutant-specific selection—or better, multi-inventory ensemble approaches—when assessing Japanese air quality and formulating policy. Routine assimilation of ground and satellite data, together with inverse modeling, is recommended to narrow residual biases and improve future inventories. Full article

In recent years, ozone (O₃) pollution has become a prominent air quality concern in the Sichuan Basin (SCB). Based on surface O₃ measurements from 22 cities between 2015 and 2024, this study investigates the evolution of extreme O₃ pollution events and their underlying causes. While the average O₃ concentration, the number of affected cities, and the total O₃ pollution hours have all increased during the past decade, extreme O₃ concentrations have shown a significant decline since 2020. These trends suggest that O₃ pollution in the SCB has become more spatially extensive and less intense. Decomposition analysis attributed ~75% of the post-2020 decline in extreme O₃ concentrations to precursor emission reductions, with meteorological variability explaining the remaining ~25%. Satellite observations of formaldehyde (HCHO) and nitrogen dioxide (NO₂) column densities indicate a regional shift in O₃ formation regimes across the SCB, with many areas transitioning from VOC (volatile organic compound)-limited to transitional or NO_x (nitrogen oxide)-limited conditions. This shift likely contributed to the broader spatial extent and longer duration of O₃ pollution in recent years. Model sensitivity simulations and Integrated Reaction Rate (IRR) analysis demonstrate that reductions in precursor emissions, particularly NO_x, directly weakened daytime photochemical O₃ production and disrupted NO_x-driven radical propagation under transition and NO_x-limited conditions, collectively driving the observed decline in extreme O₃ concentrations. Full article