Pollution Characteristics Research Articles

Exploring the microbe-mediated biological processes of BTEX and toxic metal(loid)s in aging petrochemical landfills

Aging petrochemical landfills serve as reservoirs of inorganic and organic contaminants, posing potential risks of contamination to the surrounding environment. Identifying the pollution characteristics and elucidating the translocation/ transformation processes of typical contaminants in aging petrochemical landfills are crucial yet challenging endeavors. In this study, we employed a combination of chemical analysis and microbial metagenomic technologies to investigate the pollution characteristics of benzene, toluene, ethylbenzene, and xylene (BTEX) as well as metal(loid)s in a representative aging landfill, surrounding soils, and underlying groundwater. Furthermore, we aimed to explore their transformations driven by microbial activity. Our findings revealed widespread distribution of metal(loid)s, including Cd, Ni, Cu, As, Mn, Pb, and Zn, in these environmental media, surpassing soil background values and posing potential ecological risks. Additionally, microbial processes were observed to contribute significantly to the degradation of BTEX compounds and the transformation of metal(loid)s in landfills and surrounding soils, with identified microbial communities and functions playing key roles. Notably, co-occurrence network analysis unveiled the coexistence of functional genes associated with BTEX degradation and metal(loid) transformation, driven primarily by As, Ni, and Cd. These results shed light on the co-selection of resistance traits against BTEX and metal(loid) contaminants in soil microbial consortia under co-contamination scenarios, supporting microbial adaptive evolution in aging petrochemical landfills. The insights gained from this study enhance our understanding of characteristic pollutants and microbial transformation processes in aging landfills, thereby facilitating improved landfill management and contamination remediation strategies.

Characteristics, drivers and ecological risk assessment of microplastics in the surface water of urban rivers in Guangdong-Hong Kong-Macao Greater Bay Area cities - A case study of Dongguan city

In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), microplastic pollution in urban rivers is a prominent problem due to the developed economy and high industrial intensity. Using the Xiaohai River, Hanxi River and Dongguan Canal in Dongguan City, an important node city in the GBA, as an example, microplastic characteristics, drivers and ecological risks in the surface water of three rivers were investigated. Results showed that the average abundance of rivers in the wet period (1646.22 ± 154.73 items/m3) was 4.7 times higher than that in the dry period (351.09 ± 34.2 items/m3). Microplastics were mainly in the form of fragments and fibers, with a size range of 30–500 μm, and appeared transparent with white color. The microplastic polymer types PE, PP, PET and PA accounted for more than 70%. There are large differences in the characteristics of microplastic pollution during different hydrological periods. Redundancy analysis showed that the distribution of plastics, chemical materials, packaging and printing industries along the rivers dominated the differences in microplastic abundance. The electronic information industry contributed most to the composition of microplastic polymer types. The polymer hazard index, pollution load index, and potential ecological risk index for rivers indicate a medium-high risk classification or higher. Therefore, the industrial layout along the urban rivers should be rationalized, the disposal of microplastics in wastewater should be increased, and the use of green plastic products should be promoted. This study provides support for the management of microplastic pollution in urban surface water in the GBA.

Pollution Characteristics and Risk Assessment of Heavy Metals in the Soil of a Municipal Solid Waste Landfill Site

ABSTRACT With the excavation of landfill sites, the disposal and reduction of organic-rich soils with high proportions of heavy metals have become urgent issues. This study focuses on the pollution characteristics and ecological risks associated with heavy metals in the humus soil of a municipal solid waste (MSW) landfill. The results indicate that the concentrations of heavy metals in the humus soil followed the sequence of Cu > Zn > Cr > Pb > Ni > As > Cd > Hg, and Cu and Cd exhibited the highest exceedance multiples. Except for Cr, the concentrations of the heavy metals in the humus soil were higher than those in combustible components, with a strong Hg correlation. Heavy metal forms indicate varying degrees of mobility and stability; Cr, As, Hg, and Pb were stable, while Ni, Cd, Cu, and Zn showed higher mobility. The results of the principal component analysis reveal that heavy metals primarily originate from industrial and agricultural waste. Finally, the geoaccumulation index of the metals indicated that Cu, Zn, Cd, and Pb exhibited severe contamination. Most importantly, Cd posed the greatest environmental risk as it has the highest effective content, bioavailability, and mobility. This study provides a scientific foundation for mitigating heavy metal pollution in the humus soil of landfill sites.

Study on the characteristics of urban background ozone pollution based on long-term observations from mountain sites in China during 2015–2022

In recent years, Chinese cities have faced persistent O3 pollution challenges. O3 concentrations at urban mountain sites, serving as proxies for urban background O3 levels, can help address data gaps in O3 research in China. This study, for the first time, analyzed O3 data from ten urban mountain sites during 2015–2022 using statistical methods like the Mann-Kendall test, Theil-Sen slope estimation, and Pearson correlation analysis to reveal characteristics and trends in urban background O3 and proposed a metric for assessing mountain sites as urban background stations. Results indicate that O3 at mountain sites were generally higher than at plain sites, regardless of mean, 10th percentile, or 90th percentile the average maximum daily 8-h average (MDA8) O3. Although mountain sites exhibited similar annual and diurnal variations as plain sites, their amplitudes were significantly lower. Significant upward trends (P < 0.05) in MDA8 O3 were observed mainly at plain sites, whereas trends at mountain sites were insignificant (P > 0.05) during 2015–2022. The increase in urban ground-level O3 was largely due to changes in VOCs and NOx emission structures, which reduce nighttime titration effects while enhancing daytime O3 production. The insignificant trends observed at mountain sites suggest that these mountain sites may be in NOx-limited or transitional regimes rather than VOCs-limited regimes, which is also associated with their lower NOx concentrations compared to plain sites. These findings suggest that if China continues to prioritize the reduction of NOx emissions, urban ground-level O3 could further increase and approach the O3 at mountain sites. Finally, this study proposes that the correlation in nighttime O3 concentrations between mountain and plain stations can serve as a valuable indicator for evaluating the suitability of mountain stations as regional background stations in urban areas. It recommends mountain sites in cities such as Changji, Nanping for urban background O3 monitoring stations.

Detecting atmospheric oxidation in the PM2.5 and ozone multilayer complex network

Abstract Reducing the levels of Fine particulate matter (PM2.5) and ozone (O3) is essential for further improving air quality in China. The intricate and non-linear interactions between PM2.5 and O3 on a national scale over long-term records are not well understood. Here, we proposed a novel multi-layer network approach to bridge the gap. Our findings reveal that the variability of O3 precedes that of PM2.5 by one day. The degree, weighted degree, and edge distance follow a power-law decay distribution, suggesting that their relationship is not a random process. O3 concentration in the Yangtze River Delta (YRD) region and eastern Shandong Province significantly impacts the PM2.5 levels in surrounding areas. Conversely, PM2.5 concentrations in Shandong Province, Henan Province, YRD and Pearl River Delta (PRD) have a strong influence on O3 levels. Moreover, we quantified the seasonality of the interactions and elucidated the underlying reasons. The results revealed the interactions between PM2.5 and O3 are intricately tied to atmospheric oxidation processes. More specifically, in summer, the atmospheric oxidation has a strong impact on the interactions in key regions, such as the Beijing–Tianjin–Hebei,YRD region and Fenwei Plain. However, the PRD region experiences a more pronounced effect from atmospheric oxidation on this relationship in winter. These findings demonstrate that it is crucial to effectively regulate atmospheric oxidation to mitigate PM2.5 and O3. Our results also serve as a valuable methodological framework for understanding the characteristics of pollutants.

Pollution characteristics and ecological risk assessment of glucocorticoids in the Jiangsu section of the Yangtze River Basin

Pollution characteristics and ecological risk assessment of glucocorticoids in the Jiangsu section of the Yangtze River Basin

Flame propagation, explosion hazard, and pollutant emission characterization of typical clean fuels leaks in plateau low-pressure region

To accelerate energy transformation and sustainable development, various countries are rushing to lay hydrogen doped natural gas pipelines. However, the installation of pipelines will pass through plateau low-pressure region, and the impact of low-pressure environments on the flame propagation, explosion hazards, and pollutant emission characteristics of hydrogen doped natural gas is not yet clear. To solve this problem, a combination of constant volume combustion experiment and numerical simulations is used. The characterization parameters of flame, explosion and pollutant concentration of natural gas/H2/air under low-pressure environment are obtained, and their chemical reaction kinetics are analyzed. When the pressure drops, the laminar burning velocity (LBV) of them increases, and the Lewis number (Le) gradually increases by more than 1. Thermal diffusion is stronger than mass diffusion, and the growth rate of flame thickness exceeds 26 %. The effect of hydrodynamic instability enhances, causing an increment in the average size of flame cells, the critical instability radius, and the Markstein length (Lu). At the equivalent ratio (φ) of 1, there is a change from negative to positive in the Lu, and flame stability continuously strengthens. The explosion overpressure is reduced by 78 % to 90 %, the explosion temperature by 16 % to 20 %. As the φ increases, the LBV exhibits an inverted U-shaped relationship, reaching its maximum value near “φ = 1″. The flame stability first weakens and then strengthens. The explosion hazard is strongest in the range of ”φ = 1–1.2″. With a decrease in pressure, the total reaction rate of fuel consumption is reduced by more than 50 %. The continuous reaction distance is extended by 12 %. Changes in pressure have a relatively weak impact on the content of CO and CO2. The increase in the φ results in an increase in CO content of over 7 %. The content of CO2 reaches its maximum value around “φ = 1″. It is an essential reference for the safe delivery of hydrogen energy and the reduction of environmental pollution.

Changes in urban residential and agricultural sources induce a decrease in PM10 levels in cold clean area: A thirteen-year monitoring at the Longfengshan WMO/GAW regional background station in Northeast China

Atmospheric background monitoring provides insights into the long-term changes in atmospheric composition resulting from human activities on both global and regional scales. It is important to understand the local characteristics of key air pollutants to evaluate and manage air quality control policies effectively. This study analyzed 13 years of continuous data of PM10 (particulate matter with aerodynamic diameter ≤10 μm) concentration from the only atmospheric background station in Northeastern China, the Longfengshan (LFS) World Meteorological Organization (WMO)/Global Atmosphere Watch (GAW) regional station. The results revealed a significant decrease of 58.02% in PM10 concentrations in the LFS from 2007 to 2019, which was primarily influenced by transport from Changchun and Harbin. Over periods exceeding eight months, the correlation between PM10 levels at the LFS atmospheric background station and those in Changchun and Harbin became more pronounced. The observed decline in PM10 concentrations at the LFS atmospheric background station was largely attributed to reduced emissions from urban residential and agricultural sources. Emissions of carbon monoxide and ammonia from these sources, along with temperature and relative humidity (RH), significantly affected the PM10 concentrations. Using machine learning (ML) methods and PM10 data from the LFS atmospheric background station, this study effectively predicted PM10 concentrations in neighboring cities, demonstrating that the LFS atmospheric background station can effectively assess the trend of PM10 changes in Northeast China. This study quantified the influence of urban areas on atmospheric background stations, highlighting the effectiveness of existing environmental policies, and offering a reference for similar studies and forecasts in other regions.

Characteristics of Water-soluble Ion Pollution in PM2.5 and the Causes of High Acidity of PM2.5 in Dalian

To gain a deeper understanding of the pollution status and influencing factors of fine particles （PM2.5） and their water-soluble ions （WSI） in Dalian and to implement precise control of pollution events such as haze and acid rain, PM2.5 samples were collected in Dalian from June 2021 to May 2022. Then, the mass concentrations of PM2.5 and WSI were determined using the weight method and ion chromatography, respectively, and the pollution characteristics and sources were analyzed. Furthermore, the causes of the high acidity of PM2.5 in spring were discussed. The results showed that the annual average mass concentrations of PM2.5 and WSI in Dalian during the sampling period were （33.24 ±28.87） μg·m-3 and （18.66 ±20.52） μg·m-3, respectively, and the secondary ions （SNA, including SO42-, NO3-, and NH4+） accounted for the highest proportion of WSI [（86.2 ±9.3）%]. The order of ion concentration levels from highest to lowest was： NO3-&gt;SO42-&gt;NH4+&gt;Cl-&gt;K+&gt;Ca2+&gt;Na+&gt;Mg2+&gt;F-. Due to the influence of meteorological conditions and coal combustion emissions during the concentrated heating period from late autumn to early spring, the seasonal variation in PM2.5 and WSI was winter&gt;spring&gt;autumn&gt;summer, whereas SNA was the highest in spring and the lowest in summer. The results of correlation and principal component analysis showed that WSI in PM2.5 was mainly from the secondary transformation of atmospheric SO2 and NO2 （contributing to the majority of SNA）, mixed sources of combustion and dust （characterized by K+, Mg2+, Cl-, and F-）, and sources of sand and sea salt （characterized by Na+, Ca2+, and Mg2+）. In summer, the main combustion source was biomass burning, whereas in autumn, winter, and spring, coal combustion emissions were predominant. The change in wind direction from autumn to winter brought by a shift from the source of sea salt to soil dust； additionally, the external pollution transported by northwest winds contributed to the complexity of the sources of WSI in PM2.5 during spring in Dalian. ISORROPIA-II model simulations suggested NH4NO3 as the most present solid aerosol form in PM2.5 in Dalian, followed by CaSO4 and （NH4）2SO4； compared to that in solid aerosols, more SNA existed in liquid aerosols. The annual average pH of PM2.5 in Dalian was 5.65 ±3.00, with pH values close to neutral in summer, autumn, and winter but significantly acidic in spring （2.03 ±3.18）. The high acidity observed in spring was attributed to the combination of low temperature, high humidity, and high SNA concentrations. These conditions resulted in higher aerosol water content and increased gas-to-particle conversion rates, ultimately leading to an ammonia-deficient environment. The backward trajectory and PSCF results indicated that the external transport of high acidity PM2.5 in spring mainly came from the northwest （45.0%） and southwest （40.8%） directions. Mobile source emissions made the most significant contribution to the transportation of pollutants in the former, forming high-pollution source areas in the Beijing-Tianjin-Hebei Region, which may have been mainly related to urban motor vehicle and port vessel emissions； the latter was influenced by relatively strong stationary sources and showed higher SO2 emissions in the southern part of Henan Province and the central part of Jiangsu Province.

Pollution Characteristics and Source Apportionment of Heavy Metals in Topsoil of Counties Along the Shandong Section of the Yellow River

The 25 counties along the Shandong section of the Yellow River are the core areas for promoting the ecological protection and high-quality development of the Yellow River in Shandong Province. Moreover, it is of great significance to study the current situation, sources, and potential risks of heavy metal pollution in the topsoil in this region. In this study, 103 soil samples were collected from the 25 counties along the Shandong section of the Yellow River, and the contents of eight heavy metals （As, Cu, Pb, Cr, Zn, Ni, Cd, and Hg） were determined. The pollution characteristics of heavy metals were analyzed and evaluated using the geological accumulation index and potential ecological risk index. Correlation analysis and the positive matrix factorization （PMF） model were used to analyze the sources of heavy metals. The results showed that the average contents of Cu and Cr were lower than that of the background values of soils, whereas the average contents of As, Pb, Zn, Ni, Cd, and Hg were 1.16, 1.42, 1.05, 1.14, 2.29, and 1.85 times higher than that of the background values, respectively, and the average contents of all eight elements were lower than the screening value of soil pollution risk in agricultural land. In terms of different heavy metal variations, the coefficient of variation （CV） of Cu and Cd was higher than 0.500, indicating high variations, whereas As, Pb, Cr, Zn, Ni, and Hg showed moderate variation. Cd and Hg were slightly polluted, whereas the other six elements were not polluted. Cd and Hg had a moderate potential ecological risk level, whereas the other six elements were at a low level. Correlation analysis and PMF model showed that the sources of heavy metals in the study area were influenced by four factors, i.e., agricultural activities, natural sources, industrial emissions, and atmospheric dust from coal combustion and vehicle exhaust emissions, and the relative contribution rates were 32.4%, 34.9%, 16.5%, and 16.2%, respectively.

Characteristics, Sources Analysis, and Environmental Impacts of VOCs Based on Photochemical Loss in Summer in Zhengzhou

To clarify the pollution characteristics and sources of atmospheric VOCs in Zhengzhou City in the summer, multi-site offline sampling and laboratory analyses of atmospheric VOCs in Zhengzhou were carried out in August 2022. The observed and initial VOC volume fraction levels, OFP, SOAFP, and sources were compared. During the study period, the average values of three-site observation and initial φ（VOCs） during the study period were （31.83 ±13.51）×10-9 and （35.92 ±15.30）×10-9,respectively. Olefins （52.5 %） and aromatic hydrocarbons （29.7 %） were the components with a higher photochemical loss rate, and the spatial variations of the observed TVOCs concentration at each site were： Zhengzhou University （ZZU） &gt; Gangli Reservoir （GLR） &gt; Jingkaiqu （JKQ）, and the concentrations of alkanes and OVOCs at each site were higher. Olefins and aromatic hydrocarbons were the components that contributed greatly to the formation of O3 and SOA. Motor vehicle sources, solvent-use sources, and industrial sources were the main contributing sources of atmospheric VOCs in Zhengzhou. Compared with the source analysis results based on the initial concentration, the contribution rates of motor vehicle sources, industrial sources, and solvent use sources were relatively high, and the contribution rates of combustion sources, plant sources, and oil and gas volatilization sources were relatively low.

Pollution Characterization and Source Apportionment of Volatile Organic Compounds and Their Odor-causing Species in Industrial Parks

To improve the phenomenon of the volatile organic compounds （VOCs） odor pollution nuisance in industrial parks and to promote the synergistic control of atmospheric VOCs and their odor-causing substances, based on the field observation of atmospheric VOCs in residential living areas and five different types of industrial clusters in industrial parks, we analyzed the pollution characteristics of atmospheric VOCs and their odor-causing volatile organic compounds （O-VOCs） in the residential living areas and each industrial cluster, evaluated the characteristics of the odor activity of the O-VOCs in the industrial parks, and identified the key odor-causing species and their main sources. The results showed that the mean values of atmospheric φ （TVOCs） and φ（O-VOCs） in the residential living area of the industrial park were 102.57×10-9 and 72.33×10-9, respectively. φ（TVOCs） and φ（O-VOCs） were significantly higher in the industrial clusters of basic chemical industry and pharmaceutics than in the other industrial clusters, and the sum （OAVsum） and maximum （OAVmax） of the odor activity values of these two clusters were relatively high, with a potential risk of odor nuisance. Overall, the O-VOCs species with higher odor intensity were similar in residential living areas and the five industrial clusters, and effective control of O-VOCs species such as acrolein, p-diethylbenzene, p-xylene, and 1,3-diethylbenzene is essential to mitigate or eliminate organic odor pollution. The results of the source apportionment of O-VOCs in the residential area showed that the sources of O-VOCs in the residential area were mainly influenced by natural gas chemical and pharmaceutics, and the coefficients of divergence （CDO-VOCs） between the O-VOC chemical profiles from residential areas and those from natural gas chemical and pharmaceutics were 0.31 and 0.38, respectively. Principal component analysis （PCA） also confirmed this result, with residential O-VOCs mainly originating from natural gas chemicals and pharmaceutics, followed by iron and steel manufacturing and automobile manufacturing, with the lowest contribution from the basic chemicals.

Pollution Evaluation and Risk Control Suggestion of Heavy Metals in Soil-crop System in Different Soil Parent Material Areas of Guangxi

To study the heavy metal pollution and influencing factors of soils and crops in different parent material areas and provide the basis for the classification and control of cultivated land, a total of 1 326 soil surface samples and 46 crop seed-root soil samples were collected from Xingye County in the southeast of Guangxi. The enrichment characteristics of heavy metals in the soil-crop system of four soil-forming parent materials were compared and analyzed, and the influencing factors of Cd absorption by rice were studied. The comprehensive quality impact index method was used to evaluate the soil and crops in the study area, and the safe use of cultivated land was proposed according to the evaluation results. The results showed that in the four soil-forming parent material areas, only the carbonate rock parent material area showed obvious enrichment of heavy metals in the soil, especially Cd. According to the "National Food Safety Standard for the Limit of Pollutants in Food" （GB 2762-2022）, the excess rate of heavy metal Cd in rice seeds was 35.7%, and the other heavy metal rates were not exceeded. The bioconcentration coefficient of heavy metal Cd in rice from different parent material areas was as follows： quaternary sediment area &gt; carbonate parent material area &gt; clastic parent material area &gt; granite parent material area. The enrichment of Cd in rice was affected by soil pH and CaO. When the soil pH value was in the range of 5.5-6.5, the Cd content and exceeding rate of rice seed increased significantly. The evaluation results of soil-crop heavy metal pollution showed that the overall heavy metal risk in the study area was high, and the proportions of clean, mild, light, moderate, and heavy pollution were 23.91%, 10.87%, 17.39%, 17.39%, and 30.43%, respectively. Combined with the distribution of the comprehensive quality influence index and the pollution characteristics of different parent materials, the classification and control suggestions were put forward, which provided ideas for the safe utilization of polluted cultivated land.

Seasonal biogenic volatile organic compound emission factors in temperate tree species: Implications for emission estimation and ozone formation

Variability in biogenic volatile organic compound (BVOC) emissions across species and seasons poses challenges for accurate regional emission estimates and effective ozone (O3) control policies. To address this issue, we conducted in-situ measurements of emission factors for six dominant tree species in Beijing across four seasons. Subsequently, we developed monthly dynamic standard emission factors (SER-MDs) to model monthly BVOC emissions and their impacts on O3 formation at citywide and district levels. Our observations revealed pronounced seasonal differences in the BVOC composition and emission rates, as well as their responsiveness to monthly average temperature. By introducing the SER-MDs, we estimated BVOC emissions from the dominant tree species in Beijing to be 38.2 Gg yr−1, with monoterpenes and isoprene contributing 49% and 11%, respectively. This calculation reduced the overestimation associated with constant standard emission factors by 31%–38% at district level. The estimates also revealed regional differences in plant compositions rather than simple feedback from regional temperature and photosynthetically active radiation periods. Under these conditions, the maximum monthly BVOC-induced O3 concentration occurred in August and ranged from 4 to 17 μg m−3 across districts, with isoprene being the dominant contributor. Quercus mongolica and Populus tomentosa played significant roles in the formation of BVOC-induced O3 due to their strong isoprene emitting potential in July–August. These results indicate the necessity of introducing species-specific rhythms of BVOC emissions from dominant species in the development of urban BVOC emission inventories. This approach could inform the development of air pollution management policies that are consistent with the local vegetation composition and O3 pollution characteristics. For Beijing and other similar northern cities, reducing the use of tree species emitting substantial amounts of isoprene during periods of regional peak ambient O3 concentrations could constitute an effective nature-based solution for improving urban air quality in the future.

Study on the Mechanism of Algae Bacteria Symbiotic System in Treating Fracturing Flowback Fluid

Fracturing operations in oil and gas wells are one of the main measures to increase production. Fracturing flowback fluid has the characteristics of high viscosity, high COD value, and containing multiple chemical reagents, making it difficult to treat. It has become one of the main pollutants in oil fields. Directly discharging untreated fracturing fluid can cause serious pollution to the environment and soil. Therefore, in-depth research on the treatment methods of fracturing flowback fluid is of great significance for environmental protection and cost reduction in oil and gas fields. This article systematically analyzes the sources, components, pollution characteristics, and treatment status of fracturing flowback fluid. The efficient treatment of fracturing flowback fluid using a microalgae aerobic bacteria mixed culture system was conducted, and the mechanism of algae bacteria symbiotic treatment of oily wastewater and the mechanism of microalgae aerobic bacteria mixed culture purification of fracturing flowback fluid were analyzed in depth.

Distribution, sources, and risk assessment of polycyclic aromatic hydrocarbons in surface soils and plants from industrial and agricultural areas, Junggar Basin, Xinjiang

The contamination characteristics of Polycyclic Aromatic Hydrocarbons (PAHs) in different environmental functional areas are different. In this study, the contamination of PAHs in soils and common plants in typical mining and farmland areas in Xinjiang, China, was analyzed. The results showed that the contamination levels of PAHs in mining soils were significantly higher than those in farmland soils, and the mining soils were dominated by 4-5-ring PAHs and farmland soils by 3-4-ring PAHs. Analysis of their sources using a positive definite factor matrix model showed that PAHs in mining soils mainly originated from coal and natural gas combustion, and transportation processes; while farmland soils mainly came from biomass and coal combustion, and fossil fuel volatile spills. The cancer risk of PAHs in soils was evaluated using a combination of the Monte Carlo and the lifetime carcinogenic risk models, and the results showed that the overall level of cancer risk for mining soils was higher than that for farmland soils, and can put some people in high risk of cancer. For plant samples, except for individual crop samples, the contamination levels of mining plants and crops were similar, with 4-5-ring PAHs dominating in desert plants in mining areas and the highest proportion of 3-ring PAHs in crops in agricultural fields, and PAHs in both plants were mainly from biomass and coal combustion. The results of correlation analysis showed that 2-ring PAHs in crop roots were significantly positively correlated with it in corresponding soils, and some high-ring PAHs in crop leaves were significantly negatively correlated with it in corresponding soils. Therefore, there were significant differences in the pollution characteristics of PAHs in soils and common plants in mining and agricultural areas. Human health risks and ecological risks are mainly concentrated in mining areas, and appropriate intervention measures should be taken for pollution remediation.

Characterizations of air pollutants at roadside monitoring stations and traffic emission effects: A case study in Tianjin, China

To investigate the response of Roadside Monitoring Stations (RSs) to traffic-related air pollution, traffic and pollutant characteristics, influencing factors, and potential source characterization in Tianjin, China were determined based on roadside monitoring of real-world data conducted at RSs in 2022. The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station (NM), with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs, where the average diurnal concentration was 41.46 % higher than that at the NM. The generalized additive model (GAM) for nitrogen oxides (NOx) and carbon monoxide (CO), responding to the multiple influencing factors, performed well at RSs, with deviance explained by 86.6 and 61.4 %, respectively. The synergistic effects of wind direction and speed contributed to most of the variations in NOx and CO, which were 14.74 and 12.87 %, respectively. Pollutant concentrations were highest under windless conditions, with pollutants originating primarily from local vehicle emissions. The model results indicated that medium-duty truck (MDT) traffic flow predominantly contributed to the variability in NOx emissions, whereas passenger car (PC) traffic flow was the primary source of CO emissions from traffic variables. MDTs should be the focus of urban NOx traffic emissions control. Potential-source analysis validated the results obtained from the GAM, and both analyses showed that RSs can better characterize traffic-related air pollutants. Furthermore, more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition, effectively decreasing CO concentrations.

Pollution characteristics, sources and ecological risks of typical pesticides in Dongting Lake Basin

Pollution characteristics, sources and ecological risks of typical pesticides in Dongting Lake Basin

Nano chloropsis microalgae biofuel with butyl alcohol and ZnO inhibited diesel engine combustion efficiency and pollution characteristics

Using alternative energy sources is crucial in light of the swift exhaustion of worldwide fossil fuel reserves, a situation worsened by industrialization and population expansion. Incorporating a certain amount of algal bio-oil into the biodiesel production process can improve its long-term sustainability. The use of butyl alcohol (butanol) as a blending enhancer, which mixes biodiesel (BD) and conventional fossil fuel (FD), shows potential for raising the total energy content and improving viscosity qualities. This research primarily focuses on oil extraction from algae and the subsequent production of biodiesel (BD). Five different BM variants were created utilizing B20But30 (BD-50 %, BD20 %, But-30 %), each with different amounts of zinc oxide. The several types of BM considered are B20But30 and B20But30 with ZnO at concentrations ranging from 25 to 100 ppm. The results demonstrate that the utilization of B20But30ZnO at different concentrations (100 ppm, 75 ppm, 50 ppm, and 25 ppm) and B20But30 alone lead to improvements in Brake Thermal Efficiency (BTE) by 13 %, 12.23 %, 10.68 %, 5.93 %, and 1.53 % respectively, compared to the baseline condition of FD (Full Load). The observed exhaust gas temperatures were as follows: 210°C for diesel fuel, 213°C for B20But30 fuel mix, 216°C for B20But30ZnO fuel blend with 25 ppm, 218°C for B20But30ZnO fuel blend with 50 ppm, 219°C for B20But30ZnO fuel blend with 75 ppm, and 223°C for B20But30ZnO fuel blend. Empirical studies have demonstrated that including ZnO in BM decreases NOx, CO2, and SO2 while concurrently increasing the concentration of HC (hydrocarbons). Therefore, it was found that the potential of using micro-algae-based biodiesel, along with butanol and Zinc oxide, as an alternative to traditional fuel in diesel engines showed great promise and practicality.

A new hybrid deep neural network for multiple sites PM2.5 forecasting

Many studies have confirmed that fine particulate matter (PM2.5) poses significant hazards to both human health and the ecological environment. Predicting future trends in PM2.5 concentrations is crucial for preventing air pollution hazards to human health. However, current machine learning-based forecasting models often focus on specific regions or sites, resulting in poor spatial generalization performance. To address this issue, this study utilizes ERA5 meteorological reanalysis data, MERRA2 assimilated aerosol optical depth (AOD) data, and ground pollutant monitoring site data to construct a three-dimensional dataset. A novel hybrid deep neural network model (D_GAT) is proposed to simultaneously forecast the future 72h PM2.5 concentration trends for all sites in China. The D_GAT model combines the advantages of a graph attention network and a long short-term memory neural network, which can effectively aggregate spatial information between sites and simulate the spatial transport process and time series change characteristics of pollutant particles. Moreover, the proposed calculation method for attention scores quantified based on the actual pollutant propagation characteristics, combined with the upper atmosphere pollution transport process represented by AOD, can better express the pollution contributions of different neighboring sites to the predicted central site. Experimental results show that, compared to four other baseline models, the novel model achieves an average R2 of 0.732 for all sites in 72-h prediction, which is the highest among the five models, and the prediction accuracy of 72h is also in the forefront compared with the current similar research. The RMSE and MAE are 14.63 μg/m3 and 9.49 μg/m3, respectively, which are 2–4 μg/m3 lower than the other four baseline models, indicating that it has higher reliability and can achieve the goal of timely prediction and early warning. Overall, the new model is an effective tool for multiple sites generalization forecasting.