Site In Beijing Research Articles

A novel hybrid multi-criteria decision-making approach for solar photovoltaic power plant site selection based on the quantity and quality matching of resource-demand

Solar photovoltaic has received wide attention and is regarded as the most promising power generation technology. The success of SPV often depends on the site selection, so this study proposes a novel hybrid multi-criteria decision-making(MCDM) technique based on the matching of resource and demand to evaluate and select the optimal site. This technique emphasizes the important role of resource and demand matching in SPV site selection, and its core is to develop a matching model, which takes into account both the matching quantity and matching quality. The technique includes three modules: the selection of criteria system, the determination of criteria weight and the establishment of matching model. The criteria system is constructed from the perspective of resource and demand by highlighting the resource criteria such as grid conditions, absorption capacity, and the demand criteria such as energy conservation, energy security and transition. Based on the variable precision rough number modified by inverse prospect value function, developing a subjective weighting method. From the matching perspective, proposing a novel siting integration decision-making model based on WLC and angle cosine match(ACM), which enriches the siting perspective. The model outperforms conventional methods, as verified by performance application and comparison on Beijing SPV site selection. The proposed method can better denote the criteria importance and improve the problem of inaccurate prioritization caused by the imperfect processing perspective of criteria and methods. Additionally, the model’s adaptability under different weight conditions is demonstrated by evaluating its spatial range and sensitivity. In the application of SPV plant site in Beijing, the method effectively serves the renewable energy siting, and concludes that Shunyi is the priority alternative for SPV development.

Unraveling Potential Causative Components for the Deleterious Effect of Atmospheric Fine Particulate Matter on Red Blood Cells.

Atmospheric fine particulate matter (PM2.5) poses threats to the cardiovascular system. Red blood cells (RBCs) are the most abundant cells in blood, which are actively involved in multiple hematological diseases, such as blood clot formation and thrombosis. Exploring how PM2.5 with spatiotemporal heterogeneity influences the hematological system by targeting RBCs would help gain insights into the deleterious effects of PM2.5 and provide clues for finding the causative components therein. Herein, the PM2.5 samples collected from 3 urban sites in Beijing (i.e., Chaoyang, Shunyi, and Yanqing districts) during 4 seasons of 2022 were studied for their toxicities to mouse RBCs, and the main contributing components were further explored through chemical analysis and correlation measure. The results showed that exposure to PM2.5 samples decreased adenosine triphosphate (ATP) levels and increased phosphatidylserine (PS) externalization of RBCs, causing cell morphological deformity. The Pearson correlation analysis showed that the aromaticity of the dissolved organic matter (DOM) in PM2.5 samples was positively correlated with PS exposure of RBCs, showing that the lignin-like compounds were the potential contributors. The negative correlation of zeta potentials of PM2.5 samples with PS exposure of RBCs showed the particle-derived bioactivities of this airborne pollutant. The simulative test based on artificial nanomaterials of carbon black (CB) and oxidized CB (OCB) confirmed the crucial role of particulate carbon in PM2.5-induced effects on RBCs, and soot with a certain oxidation degree was, thus, recognized as another contributor, given its ubiquitous existence in PM2.5 samples. This study, for the first time, revealed PM2.5-induced PS exposure of RBCs, and the causative components of DOM and soot were unraveled. Considering the inevitable contact of airborne PM2.5 with RBCs in the blood circulatory system, the findings obtained herein would help bridge the gap between PM2.5 exposure and the risk of cardiovascular diseases, like thrombogenesis.

Multi-Objective Optimization of Outdoor Thermal Comfort and Sunlight Hours in Elderly Residential Areas: A Case Study of Beijing, China

To optimize the outdoor thermal comfort and sunlight hours of elderly residential areas in cold regions of China, we collected data on streets and building forms from 121 elderly residential sites in Beijing. Utilizing parametric modeling tools to generate ideal residential models, a multi-objective optimization algorithm was applied to identify 144 Pareto solutions. The optimal solutions were analyzed using K-means clustering and Pearson correlation analysis to examine how block form affects outdoor environmental performance. The universal thermal climate index (UTCI) in summer showed significant positive correlations (r > 0.72) with the distance between buildings (DB), building density (BD), shape coefficient (SC), and coefficient of variation for building height (CVH), and significant negative correlations (r < −0.82) with average building height (AH), floor area ratio (FAR), volume area ratio (VAR), mean building area (MA), average building volume (AV), and open space ratio (OSR). Winter UTCI was significantly positively correlated with AH, FAR, VAR, MA, and AV (r > 0.83) and significantly negatively correlated with DB, porosity (PO), SC, and CVH (r < −0.88). Sunlight hours were significantly positively correlated with DB, PO, OSR, and CVH (r > 0.84) and significantly negatively correlated with AH, BD, FAR, SC, VAR, MA, and AV (r > 0.88). Courtyard and point-building configurations performed the best across all optimization objectives. (The value of r, Pearson’s correlation coefficient, ranges from −1 to +1. r = +1: Perfect positive correlation, r = −1: Perfect negative correlation, r = 0: No linear correlation).

CO2 flux emissions at two urban sites in Beijing and responses to human activity

During the COVID-19 pandemic in 2020–2021, continuous measurements of CO2 flux were conducted using the eddy covariance method at two representative urban sites in Beijing, China, to assess the temporal and spatial variability of CO2 emissions in urban areas. We further examined the impacts of vegetation and human activities on CO2 emissions. Both sites exhibited characteristics of urban carbon sources in the two years, with higher carbon emissions observed at the Beijing Academy of Landscape and Greening Science (BALGS) site compared to that in the campus of the Research Center of Eco-Environment (RCEES), Chinese Academy of Science. Although the seasonal and diurnal patterns of CO2 flux were similar at both sites, differences in the magnitude of CO2 flux emissions were primarily attributed to variations in underlying surface characteristics within the source area. Seasonal variations and daytime carbon uptake reflected the role of urban vegetation in carbon sequestration. Additionally, our observations revealed that the implementation of COVID-19 control measures effectively reduced urban carbon emissions, with stricter controls associated with lower carbon emissions. Furthermore, we compared the differences in carbon emission reductions between anthropogenic controls and seasonal variations at the two sites. We found that at the densely trafficked BALGS site, the impact of control measures on carbon emission reductions was more pronounced, while at the RCEES site, seasonal variations contributed more to carbon uptake compared to control measures.

Assessing and mitigating health risks of workers exposed to volatile organic compounds in contaminated soils during active pit excavation: Accounting for exposure variability and uncertainty

Health risks to workers involved in the active pit excavation of volatile organic compound (VOC)-contaminated soils have been overlooked, despite the prevalence of ex-situ remediation practices in China. This study developed a new VOC exposure in pit excavation (VEPE) model that comprehensively accounts for the release of gas-phase VOCs in soil pores, surface volatilization of newly exposed agglomerates, and volatilization of newly exposed excavation pit bottom surfaces. Additionally, the model incorporates the concentration variation of soil contaminants, spatial heterogeneity of soil properties, and the variability and uncertainty of worker exposure using two-dimensional Monte Carlo simulation (2D MCS), highlighting the importance of controlling area of new exposure surfaces, soil saturation, and air exchange during the pit excavation to mitigate risks. The study evaluated worker-health-based risks during the excavation of a VOC-contaminated site in Beijing and revealed that the inhalation cancer risk for trichloroethylene (2.35 × 10−6) and its hazard quotient (143.92) exceed the acceptable levels (10−6 and 1.0, respectively). The comparison of models demonstrated the theoretical advancements of the VEPE model over existing pit excavation models, while the field test comparison showed a significant improvement in the predication accuracy. This study addresses the under-researched area of worker safety in contaminated excavation sites. The findings have the potential to promote cleaner and more sustainable practices in ex-situ contaminated site remediation by providing valuable insights for implementing effective control measures to mitigate the emission of toxic VOCs, thereby reducing adverse social and environmental impacts.

Metropolitan pressures: Significant biodiversity declines and strong filtering of functional traits in fish assemblages

Accelerating global urbanization is leading to drastic losses and restructuring of biodiversity. Although it is crucial to understand urban impacts on biodiversity to develop mitigation strategies, there is a dearth of knowledge on the functional structure of fish assemblages spanning the entire city-scale spectrum of urbanization intensity. Here, using environmental DNA sampled from 109 water sites in Beijing, we investigated the taxonomic and functional diversity patterns of fish assemblages across the city and uncovered community-, trait-, and species-level responses to various environmental stressors. By ranking sampling sites into three disturbance levels according to water physiochemical and landcover conditions, we found that both native and non-native fish taxonomic and functional α-diversity decreased significantly with elevating disturbance, as strong disturbance led to the disappearance of many species. However, the quantitative taxonomic and functional β-diversity components of native and non-native fish showed distinct patterns; assemblage turnover dominated native fish β-diversity and decreased with increasing disturbance, whereas species/trait richness differences dominated non-native fish β-diversity and increased with disturbance intensity particularly in lotic waters. RLQ and fourth-corner analyses revealed that fish size, fecundity, diet, and reproductive behaviors were significantly correlated with water quality, with pollution-tolerant, larger-sized native and omnivorous non-native fishes being urban winners, which indicates strong trait-dependent environmental filtering. Potential ecological indicator species were identified based on the sensitivity of fish responses to pollution loads; these were mostly small native species, and many have bivalve-dependent reproduction. Our results demonstrate that, along with native fish assemblage simplification and homogenization, urban stressors exert profound impacts on community trait composition, highlighting the need to consider both biodiversity loss and functional reorganization in combating disturbance of aquatic ecosystems under global urbanization. Furthermore, correlations between cropland cover and water nutrient level suggested that the management of agricultural runoff might be critically important for safeguarding urban water quality.

Simulated phase state and viscosity of secondary organic aerosols over China

Abstract. Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states. Chemical transport models (CTMs), however, usually assume that SOA particles are homogeneous and well-mixed liquids, with rapid establishment of gas–particle equilibrium for simulations of SOA formation and partitioning. Missing the information of SOA phase state and viscosity in CTMs impedes accurate representation of SOA formation and evolution, affecting the predictions of aerosol effects on air quality and climate. We have previously developed a parameterization to estimate the glass transition temperature (Tg) of an organic compound based on volatility and to predict viscosity of SOA. In this study, we apply this method to predict the phase state of SOA particles over China in summer of 2018 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The simulated Tg of dry SOA (Tg,org) agrees well with the value estimated from ambient volatility measurements at an urban site in Beijing. For the spatial distributions of Tg,org, simulations show that at the surface the values of Tg,org range from ∼287 to 305 K, with higher values in northwestern China, where SOA particles have larger mass fractions of low-volatility compounds. Considering water uptake by SOA particles, the SOA viscosity shows a prominent geospatial gradient in which highly viscous or solid SOA particles are mainly predicted in northwestern China. The lowest and highest SOA viscosity values both occur over the Qinghai–Tibet Plateau, where the solid phase state is predicted over dry and high-altitude areas and the liquid phase state is predicted mainly in the south of the plateau with high relative humidity during the summer monsoon season. Sensitivity simulations show that, including the formation of extremely low-volatility organic compounds, the percent time that a SOA particle is in the liquid phase state decreases by up to 12 % in southeastern China during the simulated period. With an assumption that the organic and inorganic compounds are internally mixed in one phase, we show that the water absorbed by inorganic species can significantly lower the simulated viscosity over southeastern China. This indicates that constraining the uncertainties in simulated SOA volatility distributions and the mixing state of the organic and inorganic compounds would improve prediction of viscosity in multicomponent particles in southeastern China. We also calculate the characteristic mixing timescale of organic molecules in 200 m SOA particles to evaluate kinetic limitations in SOA partitioning. Calculations show that during the simulated period the percent time of the mixing timescale longer than 1 h is >70 % at the surface and at 500 hPa in most areas of northern China, indicating that kinetic partitioning considering the bulk diffusion in viscous particles may be required for more accurate prediction of SOA mass concentrations and size distributions over these areas.

Exploring pottery origin by composition and technique comparison: a case study at the Daqu burial site, Beijing, China

Scientific analysis of excavated pottery reveals critical archaeological insights, yet data on Han Dynasty pottery remains limited. This study focuses on pottery artifacts excavated from the Daqu burial site in Beijing, renowned for their polychrome decorations and size. Utilizing optical microscopy (OM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and X-ray Fluorescence (XRF), this study examined five substrate samples sourced from fragments of pottery towers and ellipse-shaped dishes. All samples exhibited similar inclusions and the same firing atmosphere. The mineralogical analysis indicated that quartz and feldspar are predominant components, with minor constituents like chlorite and kaolinite observed in the coarse pottery of the ellipse-shaped dish. Minor mineral variations suggest differences in firing temperatures. The resemblance between low-value pottery cups and delicate polychrome towers suggests they were crafted locally. These findings advance our understanding of ceramic materials and techniques in late Eastern Han Dynasty Beijing, providing crucial insights for future studies on ancient Chinese economy and society.

Enhanced nitrous acid (HONO) formation via NO2 uptake and its potential contribution to heavy haze formation during wintertime

A full understanding of the sources of atmospheric nitrous acid (HONO) in the polluted urban atmosphere remains a challenge. In this study, ambient HONO and relevant species were measured during January 2019 at an urban site in Beijing, China, and a budget analysis of HONO was conducted using a box model combined with field observations. Large nighttime “missing sources” of HONO were identified on heavily polluted days based on traditional sources, which had a significant correlation with the relative humidity, ammonia (NH3), and aerosol surface area, and the promotional effect of NH3 for nitrogen dioxide (NO2) uptake on the wet aerosol surface was discussed. Then, an updated parameterization scheme for quantifying the enhanced heterogeneous reactions of NO2 on aerosol surfaces is proposed, and the missing nighttime sources of HONO could be substantially compensated after the new scheme was incorporated. Further evaluation on the contributions of HONO to hydroxyl radicals was conducted, and the authors found that the photolysis of HONO played a dominant role in the primary OH production on the polluted days (78%–90%). The study reveals great potential of an NH3-enhanced uptake coefficient of NO2 on the aerosol surface in the nocturnal HONO budget, and highlights the significance of HONO in the strong atmospheric oxidation capability during episodes with a heavily polluted atmosphere.摘要本文研究了重污染过程中气态亚硝酸 (HONO) 的关键来源并基于化学箱模型对其源汇过程进行了闭合分析. 结果显示, 现有的HONO 源汇机制并不能解释观测期间出现的高HONO事件, 尤其是重污染过程夜间存在大量的HONO "未知源". 本文提出了一套新的HONO 源汇参数化方案, 可以较好的模拟观测期间HONO日间和夜间来源, 并进一步评估了HONO 对羟基自由基 (OH) 的贡献, 发现 HONO 光解主导了重污染天OH生成 (78%–90%). 研究结果揭示了华北城市富氨大气环境促进 NO2在气溶胶表面的摄取和非均相反应进而主导了夜间HONO生成, 凸显了HONO化学对于重污染过程维持大气氧化能力的重要作用.

Preliminary study on the enhanced bioremediation of PAH-contaminated soil in Beijing and assessment of remediation effects based on toxicity tests.

In this study, we focused on soil contaminated by polycyclic aromatic hydrocarbons (PAHs) at typical coking-polluted sites in Beijing, conducted research on enhanced PAH bioremediation and methods to evaluate remediation effects based on toxicity testing, and examined changes in pollutant concentrations during ozone preoxidation coupled with biodegradation in test soil samples. The toxicity of mixed PAHs in soil was directly evaluated using the Ames test, and the correlation between mixed PAH mutagenicity and benzo(a)pyrene (BaP) toxicity was investigated in an effort to establish a carcinogenic risk assessment model based on biological toxicity tests to evaluate remediation effects on PAH-contaminated soil. This study provides a theoretical and methodological foundation for evaluating the effect of bioremediation on PAH-contaminated soil at industrially contaminated sites. The results revealed that the removal rate of PAHs after 5min of O3 preoxidation and 4weeks of soil reaction with saponin surfactants and medium was 83.22%. The soil PAH extract obtained after remediation had a positive effect on the TA98 strain at a dose of 2000μg·dish-1, and the carcinogenic risk based on the Ames toxicity test was 8.98 times greater than that calculated by conventional carcinogenic PAH toxicity parameters. The total carcinogenic risk of the remediated soil samples was approximately one order of magnitude less than that of the original soil samples.

Perceptions on Cultural Ecosystem Services of World Cultural Heritages in Beijing: A cross-cultural Comparison of Social Media-based Online Reviews and Images

This study introduces an innovative approach combining social media text and image comments to quantify the perceptual differences of cultural ecosystem services among various sociocultural groups. For five World Heritage Sites in Beijing, natural-language processing classifies visitor perceptions using social media comments and image data, and importance-performance analysis quantifies the differences between Chinese and international visitor perceptions of these cultural ecosystem services. For the six perceived cultural ecosystem service categories, cross-cultural and local visitors exhibit the same satisfaction trends. In particular, international tourists assign higher importance scores for a given cultural ecosystem service than Chinese tourists. The proposed methods incur a lower cost than traditional methods and acquire large volumes of broad-ranging data. Additionally, the importance of‒the performance analysis data-acquisition method is improved. Moreover, World Heritage Site sustainability can be promoted by understanding the different heritage tourism perceptions of different cultural groups. Furthermore, this study provides valuable insights for decision-makers to improve tourism management and conservation strategies.

Source apportionment of atmospheric ammonia in suburban Beijing revealed through 15N-stable isotopes

Addressing the urgent issue of atmospheric ammonia (NH3) emissions is crucial in combating poor air quality in megacities. Previous research has highlighted the significant contribution of nonagricultural sources, particularly fossil fuel emissions, to urban NH3 levels. However, there is limited assessment of NH3 dynamics in suburban areas. This study focuses on four suburban sites in Beijing, covering a 16 to 22-month observation period, to investigate spatial and temporal patterns of NH3 concentrations. The δ15N-stable isotope method is employed to identify NH3 sources and their contributions. Our results demonstrate that agricultural sources (53 %) dominate atmospheric NH3 emissions in suburban areas of Beijing, surpassing nonagricultural sources, and primarily emanate from local sources. Notably, fertilizer application (37 ± 11 %) and livestock breeding (32 ± 6 %) emerge as the primary contributors in summer and spring, respectively, leading to significantly elevated NH3 concentrations during these seasons. Even in autumn and winter, both agricultural (49 %) and nonagricultural (51 %) sources contribute almost equally to NH3 emissions. This study emphasizes the need for coordinated efforts to control atmospheric NH3 pollution in Beijing City, with particular attention to addressing both vehicular and agricultural emissions.

Interpreting the impact of augmented reality on heritage tourism: two empirical studies from World Heritage sites

ABSTRACT The promotion of tourism experiences through Augmented Reality (AR) technology has become a hot topic in current tourism research. Nevertheless, in heritage tourism research, when AR technology is adopted in heritage destinations, empirical studies on tourist responses still need to be further investigated. To bridge this research gap, this study constructed a theoretical model based on the stimulus organism response (SOR) and presence theories to explore the influence of authenticity (object-based and existential authenticity) on tourist presence perception and behavioral intention. The survey data revealed that, based on these two different World Heritage sites in Beijing (The Forbidden City) and Macao (Ruins of St. Paul's), China, presented through AR, similar findings were revealed, i.e. two different kinds of authenticity affect the formation of tourists’ presence and further influence tourists’ travel intentions. This current study extends the SOR theory by integrating object-based authenticity, existential authenticity, and presence into a theoretical model. In addition to this, the findings presented in the study can contribute to heritage site managers’ knowledge of how AR affects the heritage tourism experience of visitors as well as the marketing of heritage sites.

Wintertime fine aerosol particles composition and its evolution in two megacities of southern and northern China

Study on fine aerosols composition can help understand the particles formation and is crucial for improving the accuracy of model simulations. Based on field data measured by a Q-ACSM (Quadrupole-Aerosol Chemical Speciation Monitor), we have comprehensively compared the characteristics, evolution, and potential formation mechanisms of the components in NR-PM2.5 during wintertime at two megacities (Beijing and Guangzhou) of southern and northern China. We show that as PM pollution intensifies, the mass fraction of the primary aerosols (e.g., COA, HOA) in PM2.5 in Guangzhou increased, along with a slight decline in proportion of both the secondary organic (SOA) and inorganic (SIA) aerosols; In contrast, in Beijing, the proportion of the SIA ramped up from 28 % to 53 % with the pollution evolution; and the fraction of SOA in total OA also increased due to a substantial increment in the proportion of MO-OOA (from 29 % to 48 %), suggesting a significance of the secondary processes in worsening aerosols pollution in Beijing. Our further analysis demonstrates a leading role of aqueous pathway in the secondary formation of aerosols at the Beijing site, presenting an exponential rising of SIA and SOA with the relative humidity (RH) increase. Compared to Beijing, however, we find that the photochemical oxidation other than aqueous process in Guangzhou plays a more critical role in those secondary aerosols formation. Combined with the Hysplit trajectory model, we identify the high humid conditions in Guangzhou are typically affected by clean marine air masses, explaining the slower response of secondary components to the RH changes. Moreover, the particles in Guangzhou were observed less hygroscopic that is adverse to the aerosol aqueous chemistry. The results provide basis for the precise control of PM pollution in different regions across China and would be helpful in improving model simulations.

Significant influence of nitrate on light absorption enhancement of refractory black carbon in the winter of 2022 in Beijing

The mixing state of refractory black carbon (rBC) aerosols is regarded as a major uncertainty in climate-forcing assessments. This study measured the size distribution and mixing state of rBC using a single-particle soot photometer in the winter of 2022 at an urban site in Beijing. During the campaign, the mean mass concentration of rBC was 0.79 ± 0.63 μg m−3, much lower than that observed in Beijing in the winter of 2013. The number and mass median diameter of the rBC cores were 97 and 200 nm, respectively. The average relative coating thicknesses (RCT) of rBC-containing particles was 1.45 ± 0.27 and average light absorption enhancement (Eabs) was 1.43 ± 0.22. Similar to Eabs, RCT and secondary inorganic aerosols (SIA), especially nitrate, increased with increasing relative humidity. This suggests that higher SIA mass fraction in aerosol with a higher relative humidity in the environment results in a thicker coating and black carbon ageing, thus enhancing light absorption. RCT and Eabs increased rapidly with the increase of PM1 loading but increased slowly when the PM1 mass concentration exceeded 60 μg m−3. This indicates that a further increase in the NR-PM1 species at high PM loading does not increase the thickness of the coatings; therefore, there is no further increase in Eabs. The effects of the chemical composition of the Eabs obtained using the Lindeman, Merenda, and Gold method showed that nitrate plays a prominent role in the enhancement of light absorption, followed by SOA. The rBC mass concentration exhibited clear day-low and night-high patterns which were influenced by the synergetic effects of the boundary layer and emissions. RCT and Eabs presented similar diurnal variations, peaking in the afternoon, which was consistent with the pattern of SIA. This suggests that the SIA produced via photochemical reactions supports the ageing of black carbon-containing particles, leading to light-absorption enhancement. The back-trajectory analysis showed the highest values of rBC mass concentration, RCT, and Eabs appeared in the S cluster suggested that the rBC-containing particles transported from south Beijing were more aged with a thicker coating. While the rBC-containing particles from northern and northwestern Beijing had lower RCT and Eabs values.

Evaluating the accessibility and capacity of SARS-CoV-2 vaccination and analyzing convenience-related factors during the Omicron variant epidemic in Beijing, China

ABSTRACT The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination service system lacks standardized indicators to assess resource allocation. Moreover, data on specific vaccination-promoting measures is limited. This study aimed to evaluate vaccination accessibility and capacity and investigate convenience-related factors in China during the Omicron variant epidemic. We collected information on SARS-CoV-2 vaccination services among vaccination sites in Beijing. Analysis was performed using nearest neighbor, Ripley’s K, hot spot analysis, and generalized estimating equations. Overall, 299 vaccination sites were included. The demand for the SARS-CoV-2 vaccine increased with the increase in daily new cases, and the number of staff administering vaccines should be increased in urban areas at the beginning of the epidemic. Providing vaccination for both children and adults, extending vaccination service hours, and offering a wider range of vaccine categories significantly increased the doses of vaccines administered (all P < .05). The provision of mobile vaccination vehicles effectively increased the doses of vaccines administered to individuals aged ≥ 60 years (P < .05). The allocation of SARS-CoV-2 vaccination services should be adjusted according to geographic location, population size, and vaccination demands. Simultaneous provision of vaccination services for children and their guardians, flexible service hours, prompt innovative vaccine production, and tailored vaccination strategies can foster vaccination uptake.

Autumn and spring observations of PM2.5-bound polycyclic aromatic hydrocarbons and nitro-polycyclic aromatic hydrocarbons in China and Japan

The transboundary transport of polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs (NPAHs) aggravated by the East Asian winter monsoon is a major atmospheric environmental issue in East Asia. To thoroughly elucidate the role of the East Asian monsoon on regional PAH and NPAH pollution in East Asia, PM2.5-bound PAHs and NPAHs were investigated concurrently at five sites in Beijing and Shenyang in China and Tsukuba, Kanazawa, and Wajima in Japan in autumn (November 2018) and spring (March 2019). During both autumn and spring sampling periods, the concentrations of PM2.5, PAHs, and NPAHs at sites in China were 1–2 orders of magnitude higher than those at sites in Japan, and showed an opposite temporal variation, with higher concentrations during the autumn sampling period due to intensive emissions and unfavourable weather conditions. During the sampling periods, PAHs at the Beijing and Shenyang sites had mixed sources of traffic emissions and coal and biomass combustion, while those at the Tsukuba, Kanazawa, and Wajima sites were mainly characterized by domestic traffic emissions. In addition, NPAHs at the five sites were jointly affected by primary combustion sources and atmospheric generation, with a greater contribution of atmospheric generation to the Beijing and Shenyang sites. Based on backwards trajectory clustering and concentration-weighted trajectory analysis, external contributions to PM2.5, PAHs, and NPAHs at each site were relatively stable during the two sampling periods, and potential source areas were mainly distributed in domestic cities and nearby sea areas. Therefore, the apparent temporal differences in the characteristics and sources of pollutants between sites in the two countries indicate that transboundary pollution dominated by the East Asian winter monsoon was unobvious in autumn and spring. The results of the study provide a time-specific solution for the effective management of regional air pollution during the East Asian winter monsoon.

Machine learning revealing key factors influencing HONO chemistry in Beijing during heating and non-heating periods

Nitrous acid (HONO) is of great interest due to its contribution to hydroxyl (OH) radicals by self-photolysis. Nowadays, machine learning (ML) algorithms are good at capturing complicated non-linear relationships between predictors and dependent variables. Here, using the whole year of 2018 of observed HONO and related pollutant data at an urban site in Beijing, an ML-RF (random forest) model is carried out to predict HONO concentrations and explore the main factors influencing HONO formation mechanisms. ML-RF models show satisfactory performance during the heating, non-heating and whole year periods with R values of 0.95, 0.96 and 0.95, respectively. Primary emissions and diffusion have an obvious influence on ambient HONO during the heating period, while chemical formation processes such as NO2 heterogeneous reaction and photolysis of nitrate are important for HONO during the non-heating period with higher RH and stronger solar intensity. O3 and NH3 are the most important variables for HONO in both periods, indicating the close relationship of HONO with atmospheric oxidation and the important role of NH3 in HONO formation processes. Although there are deviations due to some variability in HONO formation mechanisms between years, ML-RF models based on 2018 data are able to roughly predict HONO for three periods in 2017 and 2021. Overall, machine learning with limited meteorological and pollutant parameters offers great advantages in HONO prediction, and it can also provide some clues to improve the chemical mechanisms of HONO by finding related variables of ambient HONO.

Multi-source variational mode transfer learning for enhanced PM2.5 concentration forecasting at data-limited monitoring stations

Hybrid methods combining data decomposition with deep learning have recently exhibited remarkable performance in PM2.5 concentration forecasting. However, these methods still encounter limitations when confronted with monitoring sites lacking adequate historical data. To overcome this challenge, this study proposes a novel methodological framework named as Multi-source Variational Mode Transfer Learning (MSVMTL) that integrates data decomposition, deep learning, and multi-source transfer learning strategies. The framework consists of four stages: source domain selection, data decomposition by Variational Mode Decomposition (VMD), mode sequence clustering, and multi-source mode transfer learning. The source domain selection stage utilizes EMS (Euclidean Distance and Maximum Mean Discrepancy Distance) to identify the most suitable source domain for knowledge transfer. The mode sequence clustering employs the LDDK algorithm (Largest Triangle Three Buckets, Dynamic Time Warping, Dynamic Time Warping Barycenter Averaging, and K-means) to cluster modes from VMD-derived domains. The multi-source mode transfer stage combines VMD with pre-training and fine-tuning, leveraging source domain knowledge for target domain prediction. To validate the proposed framework, a case study, including multiple sets of comparative experiments and ablation study, was conducted using data from 12 air quality monitoring sites in Beijing, China. The experimental results demonstrate that EMS, LDDK, and multi-source mode transfer learning strategy all achieved excellent performance, and the presented MSVMTL significantly enhances the prediction accuracy of PM2.5 concentrations at monitoring sites with limited historical data.

Effects of pH on Disintegration Characteristics of Gypsum Karst Breccia under Scouring Action

Water–rock interactions and scouring actions are recognized key factors that significantly influence the disintegration of rock on the surface of slopes. However, the research on rock disintegration, specifically under the action of scouring, is limited, which makes it difficult to understand the characteristics of rock disintegration. Therefore, in this study disintegration tests were performed on the gypsum karst breccia collected from the Zhoukoudian site in Beijing, using a self-made disintegration test device. Further, this study investigated the impact of solution pH, flow velocity, and the number of cycles on the characteristics of rock disintegration. The changes in pore structure, microstructure, and mineral composition of the rock were analyzed using nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and inductively coupled plasma optical emission spectrometer (ICP-OES) methods. The findings reveal that the cumulative relative disintegration amount of the gypsum karst breccia experiences an increase as the pH value of the soaking solution decreases and the number of cycles increases. Once a specific flow rate is attained, the cumulative relative disintegration amount stabilizes (about 73%) and no longer exhibits significant changes. This phenomenon signifies the presence of a stabilizing flow rate for disintegration. The stable flow rate concerning rock disintegration is influenced by both the solution’s pH and the number of cycles. Following acid contamination, the rock sample’s particle morphology undergoes disruption, leading to the dissolution of cement. This, in turn, leads to an augmented release of Ca2+, Al3+, and Ma2+ ions in the solution, intensifying the disintegration of the rock samples. Conversely, alkali contamination prompts secondary cementation, mitigating localized damage. This results in a marginal increase in the calcite content within the rock samples (from 15.3% to 19.2%), while the release of Ca2+ in the solution experiences a decrease. Additionally, there is a slight increase in the release of Al3+ (a maximum increase of 1.71 mg/L), which minimally inhibits the disintegration of the rock samples. Notably, the rock disintegration predominantly occurs around macropores, and the effect of solution pH on the disintegration characteristics and stable flow rate is primarily due to the changes in the relative proportion of macropore volume in the rock samples. The findings of this study have significant implications for the prediction and control of slope-related issues.