Area Of Beijing Research Articles

Study on the Patterns of Porcelain of Yuan Dynasty in Beijing Area

In recent years, with the continuous discovery of porcelain in the Yuan dynasty in Beijing, the history of the Yuan dynasty, have been gradually rediscovered by the academic circle. The subject study of porcelain not only includes the craft analysis, origin discussion and artistic characteristics of the ware, but also the discussion of porcelain trade and cultural exchange. The ornamentation of the porcelain was a reflection of people’s social life in Mongolian Yuan period, through which people’s social life and spiritual world could be vaguely seen at that time. This paper classifies the subjects of porcelain decorative patterns, analyzes and sorts out the patterns in all kinds of subjects, and discusses their decorative techniques and social and cultural backgrounds, thus discuss further it discusses the life situation and national cultural characteristics of the people of different classes in the Yuan dynasty. Юань гүрний үед холбогдох Бээжин орчмын шаазан эдлэлийн хээ чимэглэлийн судалгаа Хураангуй: Сүүлийн жилүүдэд Бээжингээс Юань гүрний үеийн шаазан олноор олдсон нь Юань гүрний түүх, урлаг, эрдэм шинжилгээ, судалгаанд дахин анхаарал хандуулах болсныг илтгэнэ. Эдгээр шаазан эдлэлийн судалгааны сэдвүүд нь зөвхөн техникийн шинжилгээ, гарал үүслийн баталгаа, олдворын уран сайхны шинж чанараар хязгаарлагдахгүй, шаазан эдлэлийн худалдаа, соёлын солилцоо зэрэг өргөн хүрээний асуудлуудыг хамардаг. Юань гүрний үеийн шаазан эдлэлүүд нь тухайн үеийн нийгмийн амьдралын чухал тусгал байсан бөгөөд тэдгээрийн хээ чимэглэлээр дамжуулан тухайн үеийн ард түмний нийгмийн амьдрал, оюун санааны ертөнцийг харж болно. Энэхүү өгүүлэл нь Юань гүрний шаазан хээ чимэглэлийг судалгааны сэдэв болгон авч, түүний гоёл чимэглэлийн хээг ангилж, төрөл бүрийн сэдэвт хээ угалзыг шинжлэхийг зорьсон болно. Гоёл чимэглэлийн урлал, нийгэм, соёлын талаарх судалгаагаар дамжин бид Юань гүрний үеийн ноёд язгууртнууд, жирийн иргэд зэрэг нийгмийн давхарга давхаргын хүмүүсийн ахуй амьдрал, үндэсний соёлын онцлогийг судлах болно. Түлхүүр үгс: Юань гүрэн, Бээжин, хээ чимэглэл, шаазан, урлагийн онцлог

Characteristics and Correlates of Health Information Literacy Among Patients With Type 2 Diabetes and Metabolic Syndrome: A Cross-Sectional Study.

The purpose of the study was to examine the characteristics and the influential effect of individual and social contextual factors on health information literacy among Chinese patients with type 2 diabetes coexisting with metabolic syndrome. Following convenience sampling, a total of 225 patients with type 2 diabetes coexisting with metabolic syndrome were recruited from a tertiary hospital in a suburban area of Beijing, China. Participants' information was gathered through a set of self-reported questionnaires. Descriptive statistics, normality test, correlational analysis, univariate analysis, multiple linear regression, and logistic regression analysis were adopted to examine the potential factors of personal and social contextual resource related to health information literacy based on the health empowerment theory. The health information literacy in this current sample was limited, with a mean score of 16.83 ± 2.96. Correlational analysis showed that self-management knowledge, attitude, and practice for metabolic syndrome; self-efficacy; health problem-solving; resilience; and chronic illness resources were significantly and positively related to health information literacy. Logistic regression analysis showed that self-management knowledge, health problem-solving, and the chronic illness resources were significantly correlated with health information literacy after controlling covariates. Overall, the health information literacy among Chinese patients with type 2 diabetes coexisting with metabolic syndrome is suboptimal. Study findings demonstrated that personal and social contextual resources factors are significantly related to health information literacy. Health care professionals should consider strategies to enhance people's health information literacy level and promote individuals' health problem-solving, enhance chronic illness resources, and improve self-management knowledge when developing tailored interventions.

Spatial-temporal variations and Attribution analysis of SO2 concentration in Beijing-Tianjin-Hebei regions from 2013 to 2022

Based on the monitoring data of air pollutants in Beijing-Tianjin-Hebei regions from 2012 to 2022, the spatial-temporal distribution of SO2 concentration and main influencing factors were analyzed through multi-methods of Daniel trend test, KZ filtering and WRF/CMAQ model simulations. From 2013 to 2022, the annual averaged concentrations of SO2 in Beijing, Tianjin and Hebei regions were all in obvious downward trends, and all passed the Daniel trend test (α=0.01). The annual averaged concentration of SO2 in Beijing, Tianjin and Hebei regions decreased from 26.6~114.3μg·m-3 in 2013 to 3.0~11.0μg·m-3, with the decline rates fluctuating from 2.62~11.81μg/(m3·yr) while the decrease rate of SO2 in Beijing was the lowest. The average annual concentration of SO2 in Tangshan city decreased the most, reaching 92.3% and it changed to be the smallest, about 78.2% in Chengde City. The reduction of coal consumption in the Beijing-Tianjin-Hebei regions significantly reduced atmospheric SO2 emissions and directly reduced the regional average concentration of SO2. Meteorological factors were generally conducive to the diffusion of SO2 concentration during 2013~2022, and the meteorological factors contributed about 0.4~5.5% in 13 cities in Jingjinji area while the contribution of anthropogenic emission reduction was 94.5~99.6%. The inter-annual variation of meteorological factors in summer from 2013 to 2022 was not conducive to the diffusion of SO2 concentration on the whole, and the contribution changed to -52.6 ~ -1.0% in 13 cities. From June to August in summer under the easterly and southerly winds, the SO2 concentration in Beijing was basically twice that of the northerly and westerly winds. The contribution of southwest transport channel to SO2 concentration in Beijing was 33.5%, while it changed to 38.9% in the southeast transport channel. Therefore, strengthening the management and control of air pollutants in surrounding area of Beijing is helpful for Beijing to further reduce the levels of air pollutants and achieve targets of air quality improvement in the 14th Five-Year Plan period.

Development of Air Pollution Forecasting Models Applying Artificial Neural Networks in the Greater Area of Beijing City, China

The ever-increasing industrialization of certain areas of the planet combined with the simultaneous degradation of the natural environment are alarming phenomena, especially in the field of human health. The concentration of particulate matter with an aerodynamic diameter of 2.5 μm (PM2.5) and 10 μm (PM10), nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3) needs constant monitoring, as they consist of the main cause for many diseases. Based on the existence of statutory limits from the World Health Organization (WHO) for the concentration of each of the aforementioned air pollutants, it is considered necessary to develop forecasting systems that have the ability to correlate the current meteorological data with the concentrations of the above pollutants. In this work, the attempt to predict air pollutant concentrations in the wider area of Beijing, China, is successfully carried out using artificial neural network (ANN) models. In the frame of a specific work, a significant number of ANNs are developed. For this purpose, an open-access meteorological and air pollution database was used. Finally, a statistical evaluation of the developed prognostic models was carried out. The results showed that ANNs present a remarkable prognostic ability in order to forecast air pollution levels in an urban environment.

Inventory of shallow landslides triggered by extreme precipitation in July 2023 in Beijing, China

The extreme meteorological events caused by climate change have increasingly caused serious clustered landslides. A systematic and timely inventory of triggered landslides is a prerequisite for quantifying and evaluating the impact of extreme meteorological events. In addition, a landslide inventory can provide basic data for any subsequent analysis of the event or be used innovatively in landslide risk analysis. The Rainfall-induced Landslides in Beijing (RLBJ) inventory presented here contains data on 15,383 rainfall-induced shallow landslides triggered by a single extreme precipitation event in July 2023 in an area of ~3,250 km2 in western mountainous areas of Beijing, China. High-resolution satellite images before and after this rainstorm event were used to visually analyze the landslides. All landslides were reported as vectorized points and polygon features and classified according to their motion forms. This inventory is now freely available for the benefit of international geohazard researchers.

Probabilistic assessment of earthquake casualties in residential areas

Accurately and reasonably assessing earthquake casualties is crucial for seismic disaster planning and governmental decision-making. However, current research on earthquake casualty assessments often lacks sufficient consideration of the uncertainties related to seismic scenarios and influencing factors. To enhance the authenticity and reliability of casualty assessments, this study proposes a seismic casualty assessment model capable of simultaneously considering multiple influencing factors. It quantitatively evaluates each influencing factor and comprehensively integrates the uncertainty characteristics associated with seismic occurrence time, building damage states, and the number of occupants. Using a residential area as an example, the research compares casualty assessment results with and without considering apartment layouts and the age structure of residents. It also explains the probabilistic method for quantifying casualties and constructing vulnerability models for seismic events in the residential area. Additionally, a simplified analytical method applicable to probabilistic assessment of earthquake casualties in masonry residential areas in Beijing is proposed. The research findings indicate that the apartment layouts within buildings have a relatively minor impact on the assessment results of casualties in the residential area, while the age structure of residents significantly affects earthquake casualty estimates. Casualty rates in the residential area, considering uncertainties in the three factors, approximately follow a log-normal distribution. For seismic intensities ranging from VI(0.05g) to IX(0.40g), the standard deviation of casualty rates across different seismic intensities exceeds 0.4. The probabilistic analysis method proposed in this study enhances existing models for earthquake casualty assessments and addresses the shortcomings in probabilistic evaluation research.

Model sensitivity in predicting extreme precipitation events in urban areas: A case study over Beijing

Understanding and forecasting the spatial and temporal distributions of extreme precipitation over urban areas is crucial for effective planning and mitigation efforts. However, this task remains challenging as accurate forecasting depends on properly representing urban surfacees and their interactions with the planetary boundary layer (PBL). We examined the hindcast of an extreme precipitation event over Beijing on 21–22 July 2012. The primary focus was assessing its sensitivity to two widely used PBL parameterizations (MYJ and YSU), two urban parameterizations (SLUCM and BEP_BEM), and two different land-use and land-cover (LULC) datasets.Sensitivity experiments were initialized at different times to explore the model dependence on initial conditions. The analyses were conducted over three selected regions: the entire model domain covering the Beijing metropolitan area, an upwind region of Beijing, and the entire urban area of Beijing. The results show that the MYJ PBL scheme performs better than the YSU PBL scheme in capturing near-surface air temperature as well as the location and timing of the heaviest precipitation. The variability in simulated precipitation among the chosen PBL schemes is lower compared to that among different time of initializations. The LULC impacted the spatial distribution of precipitation but its effect on the amount of precipitation was minimal. Overall, using a combination of the MYJ PBL scheme, SLUCM urban parameterization, and locally-enhanced Beijing LULC, and initializing the model simulations at 0000 UTC July 20, 2012, demonstrated superior performance in capturing precipitation levels, despite some spatial discrepancies in the precipitation distribution. The performance of BEP_BEM urban parameterization is similar to SLUCM across various factors such as average rain rate, maximum rain rate, and rain volume. These findings offer valuable insights towards better simulations of extreme precipitation and flooding in rapidly urbanizing areas such as Beijing.

Assessing bicycle safety risks using emerging mobile sensing data

The surge in global electric bicycle ownership has exerted immense pressure on bicycle infrastructure. Theoretically, there’s a need to reassess the risk factors associated with multiple bike lane users. Based on this, there’s a practical need to re-evaluate the safety and quality of outdated infrastructure. This paper aims to reconsider risk factors related to bicycle infrastructure safety in the context of electric bicycles sharing lanes with traditional bicycles. Moreover, many countries lack precise spatial data concerning bicycle infrastructure. This study introduces a mobile sensing method based on bicycles, aiming to acquire daytime and nighttime bike lane datasets in a cost-effective, efficient, and large-scale manner. A computer vision-based bicycle risk factor assessment model was established, and the distribution of bicycle safety risk factors was visually analyzed. Research data was collected from a representative 59.5-kilometer bicycle lane area in Beijing. The results confirm the significant impact of the surge in electric bicycles, with electric bike users accounting for 72.1% of cyclists, 32.3% wearing helmets, and 8.4% riding against traffic. During the day, the highest-ranking risk factors include the type of bicycle lanes (half lacking dedicated lanes or being shared), roadside parking, and subpar road conditions. At night, insufficient street lighting are notable concerns. The research methodology is easily replicable and can be extended to new multi-user coexistence cycling environments or countries without bicycle spatial data, offering insights for bicycle safety policies and road design.

Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China

Abstract Debris flow is one of the most common types of geological disasters in China. Owing to the influence of topography, geomorphology, geological conditions, human activity, and rainfall debris flow disasters frequently occur in the mountainous areas of Beijing. The research on debris flow in the Beijing area focuses on rainfall and risk evaluation, material sources, and early warning and prevention of debris flow. However, there are few studies on the development characteristics of single-gully debris flow and the prediction of hazardous areas in the Beijing area. Therefore, we chose the debris flow of Bangou Village in Yanqing District of Beijing as the research object. We analyzed the recharge conditions in the ditch domain and predicted the extent of the hazardous area around the gully, providing suggestions for control measures. The dynamic reserves of the loose deposits in the debris flow gully, currently in the development stage, were estimated as 15.48 × 104 m3, representing four supply sources: artificial deposits, alluvium and diluvium, residual slope deposits, and collapse. The peak flow is 24.49 m3/s for a 10-year rainfall event, 27.64 m3/s for a 20-year rainfall event, 31.79 m3/s for a 50-year rainfall event, and 34.93 m3/s for a 100-year rainfall event. The total amounts of solids washed out by a debris flow from the preceding events are 0.70 × 104 m3, 0.79 × 104 m3, 0.91 × 104 m3, and 1.00 × 104 m3, respectively. The size of the debris flow is small, with a maximum hazardous area of 0.2810 km2. We conclude that a small debris flow outbreak in the Bangou Village gully is possible. We expect that the results of this study will provide basic information and help improve debris flow research in Beijing.

Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level.

Application of CSAMT Geophysical Method in Geothermal Exploration of Beijing

Abstract Geothermal resources are abundant in the southeast urban area of Beijing, but the complex geological structure and high geomagnetic interference in the urban area make it difficult to detect the distribution characteristics of geothermal resources by the electromagnetic exploration method from natural sources. This paper presents an integrated physical exploration method combining the controlled source acoustic magneto-telluric (CSAMT) and gravity exploration for middle-deep geothermal exploration in the southeast Beijing urban area. The method is verified by examining the recommended boreholes, which have produced water at temperatures of 62.5°C and 63°C. This is a highly beneficial and socially impactful outcome, and it serves as a valuable reference for future exploration and utilization of geothermal resources in this area. It also has significant implications for future exploration and utilization of geothermal resources not only in the southeastern urban area of Beijing but also in similar urban environments around the world. The methodologies and findings from this research offer a valuable blueprint for future geothermal energy prospecting and development, contributing to the global transition towards cleaner and more sustainable energy alternatives.

Mediation of Knowledge Management on the Effect of Human Resource Management Practices to Innovation Capability

This study aimed to investigate the innovation capability in IT small and medium-sized enterprises (SMEs) in depth, with a key focus on human resource management practices, and knowledge management. Nowadays, managers recognize the value of knowledge as an intangible asset which stimulates innovation in organizations. However, few studies examine the role of human resource management in fostering knowledge capability which eventually leads to innovation. For this reason, this paper investigates the impacts of knowledge management in the relationship between the policies and practices of human resource management and innovation. The study is empirically based on the primary data collected from 130 IT small and medium-sized companies that are registered to Haidian District, one of the most important information technology industry base areas of Beijing, China. Data obtained from questionnaires will be analyzed through the SPSS statistical packet. The General Linear Mediation Regression test is used to measure the significance of the mediation effect of knowledge management capability. This study suggests that the innovation capability of IT SMEs may come from many aspects, and there is a certain degree of uncertainty that requires further exploration and research.

Research on the Socio-Spatial Resilience Evaluation and Evolution of the Central Area of Beijing in Transitional China

In recent decades, the increasing threats of global climate change, natural disasters, and epidemics have brought extensive attention to resilience theory. However, most studies focus on the physical aspects of cities, overlooking the significance of the social perspective. This study addresses this gap by using social areas as the core spatial unit for analysis. By constructing a scientific indicator system and employing the set pair analysis method, this study comprehensively evaluates the multidimensional resilience levels of Beijing’s central area during its transitional period (1990–2020). The findings reveal that socio-spatial divisions, which emphasize the network structure of social relations and the dynamic changes in social spaces, are more suitable than traditional administrative divisions as fundamental units for resilience assessment. During Beijing’s transitional period, the comprehensive resilience of the central area and all social areas steadily increased, although social capital resilience faced the challenges of loss and slow recovery. Social areas with a unique internal connection, such as those based on ethnicity, exhibited more positive social capital resilience development. Additionally, social areas with lower population diversity and greater homogeneity tended to have higher comprehensive resilience and a more positive trend in social capital resilience development, whereas highly heterogeneous social areas faced significant constraints in resilience development. These findings may provide valuable insights for cities and communities to enhance their capacity to address future uncertainties and assist policymakers in making informed governance decisions.

Strong upwards transport of HONO in daytime over urban area of Beijing, China

Strong upwards transport of Nitrous acid (HONO) in daytime over urban area of Beijing was observed based on combined observations of HONO, NOx (NO and NO2), nitrate, and PM2.5 at two heights (90 m and 528 m) on the highest building of Beijing (528 m above ground). The mean HONO at the 528 m (0.26 ppb) was lower than that at the 90 m (0.54 ppb), and a clear difference in diurnal variation of HONO between the two heights was observed. HONO at the 90 m showed two peaks in the morning rush hour and mid-night, but decreased sharply in daytime (e.g., from 0.62 ppb at 08:00 to 0.34 at 14:00); while the decreasing trend of HONO in daytime significantly weakened at the 528 m (e.g., from 0.26 ppb at 08:00 to 0.27 at 14:00).With PBL development in the morning, HONO in low layer was upwards transported to the 528 m, which compensated partly HONO loss via photolysis and resulted in a relatively stable concentration at the 528 m in daytime. A positive relationship of the bulk Richardson number (Ri) in 0–500 m with the difference of HONO between the two heights during daytime (08:00–18:00) confirmed the above analyses. HONO budget analysis indicated that a strong unknown HONO source existed at the 528 m in daytime, which was negative correlated to the Ri. These results further confirmed that vertical transport of HONO from low layer was a potential HONO source at the 528 m. Moreover, the contribution of photolysis of particulate nitrate significantly increased at the 528 m. Its contribution in total HONO sources increased from 11.9 % at the 90 m to 16.0 % at the 528 m.

Artificial light at night decreases leaf herbivory in typical urban areas.

Artificial light at night (ALAN) is exerting growing pressure on natural ecosystems, but its impact on biological interactions remains unclear. This study aimed to assess how ALAN influences leaf functional traits and herbivory in two prevalent street tree species (Styphnolobium japonicum (L.) Schott and Fraxinus pennsylvanica) through field surveys and paired experiments in the urban areas of Beijing, China. We found that ALAN led to increased leaf toughness and decreased levels of leaf herbivory. Additionally, ALAN showed species-specific effects on leaf nutrients, size as well as defense substances. The findings illustrate that ALAN can significantly alter some key functional traits and ecological processes (nutrient cycling, energy flow). In general, we suggest that high ALAN intensity will be detrimental to the energy flow from urban plants to higher trophic levels, posing a potential threat to the maintenance of biodiversity (e.g., arthropod diversity, bird diversity) in urban ecosystems.

Spatiotemporal Variation of Urban Park System and Its Policy-driven Factors: A Case Study of the Central Urban Area of Beijing

Spatiotemporal Variation of Urban Park System and Its Policy-driven Factors: A Case Study of the Central Urban Area of Beijing

Effect of water treatment processes on microbial contamination in drinking water in rural areas of the urban periphery

ABSTRACT The water treatment infrastructure facilities play an important role in ensuring the safety of drinking water. A survey of the drinking water treatment process was conducted in the urban peripheral areas of Beijing, China, and the main water treatment infrastructure facilities in terms of their impact on microbial contamination were investigated. The sedimentation equipment, filtration facilities, and disinfection equipment are all significantly correlated with the concentration of heterotrophic plate counts in drinking water. The filtration facilities and disinfection equipment were also positively correlated with the concentration of total coliform and Escherichia coli. The effect of removing microorganisms by different water disinfection methods gradually decreases in the order of ozone, chlorine, chlorine dioxide, and ultraviolet light. The effect of microbial contamination removal of different water pumping methods is as follows: direct water supply > pressure tank > secondary pressing pump station > water tower > high-level water tank, and the removal effects are 7.6, 7.4, 4.1, 3.6, and 1.7 times that of self-flowing water supply. The study provides scientific support for the renovation, and upgrading of microbial pollution reduction in drinking water in rural areas of the urban periphery.

Coordination of interests between upstream and downstream governments in water source areas

Exploration of establishing a robust intergovernmental benefit compensation mechanism for water source areas holds significant importance in promoting regional coordinated development. Taking the Guanting Reservoir basin, a water source area in Beijing, China, as an example, we established an ecological location model with urban water sources as the core by drawing on the concept of spatial circle structure in traditional location theory. Based on this, we proposed the theory of ecological cost of water source land level difference and analyzed the basic composition of ecological cost of water source land. Finally, the differential ecological costs method was used to estimate the ideal horizontal eco-compensation funds between the downstream city of the water source (Beijing) and the upstream city (Zhangjiakou). The results are as follows: (1) the closer to the water source reservoir area and the higher the protection zone level, the greater the contribution of the ecological product value realization and the ecological protection costs to the protection of water resources in the reservoir area. (2) The compensation funds for water source areas are jointly composed of the increment of ecological product value and protection costs. (3) In 2021, the value addition of ecological products in the upstream region was 3.075 billion yuan, and the protection cost was 6.702 billion yuan. After multiplying by the differential adjustment coefficient, the horizontal eco-compensation amount that the upstream cities should receive in 2021 is 4.194 billion yuan. This study theoretically addresses the shortcomings of traditional ecological compensation, which overlooked differences in resource and environmental costs due to variations in ecological functional location. It provides a new perspective for further exploring the role of location theory in addressing inter-governmental interest coordination issues in cross-border water source areas.

Prediction of soil heavy metal contents in urban residential areas and the strength of deep learning: A case study of Beijing

Predicting soil heavy metal (SHM) content is crucial for understanding SHM pollution levels in urban residential areas and guide efforts to reduce pollution. However, current research indicates low SHM prediction accuracy in urban areas. Therefore, we employed a deep learning method (fully connected deep neural network) alongside four other methods (muti-layer perceptron, radial basis function neural network, multiple stepwise linear regression, and Kriging interpolation) to predict SHM content in the urban residential areas of Beijing and demonstrated the strength of deep learning in improving prediction accuracy. We found the contents of the evaluated heavy metals (Cd, Cu, Pb, and Zn) exhibited significant correlations with numerous other soil physicochemical properties and environmental factors. The prediction accuracy for Cu, Pb, and Zn contents was relatively high across different methods. Notably, deep learning showed considerable strength in predicting the contents of the four heavy metals, with the R2 for the test set of the model ranging from 0.75 to 0.91. Compared to other methods, deep learning achieved markedly higher prediction accuracy according to different accuracy evaluation indicators (e.g., deep learning showed increases in the cumulative R2 of the four heavy metals ranging from 53.16 % to 187.36 % compared to other methods). Our study indicates that deep learning can significantly improve SHM content prediction accuracy in urban areas and is highly applicable in urban residential areas with complex environmental influences.

Tree-Ring δ13C and Intrinsic Water-Use Efficiency Reveal Physiological Responses to Climate Change in Semi-Arid Areas of North China

Climate change has had a widespread and profound impact on global temperature and precipitation patterns, especially in semi-arid areas. Plant δ13C and iWUE indicate the trade-off between carbon uptake and water loss, which is pivotal for understanding plant responses to climate change. Information about the long-term responses of the physiological and ecological processes of different tree species to climate change is also required. To investigate the impact of different forest stand structures and site conditions on long-term growth and physiological processes of coniferous and broad-leaved trees in the mountainous area of Beijing, we analyzed the tree-ring δ13C variation of four tree species (Platycladus orientalis, Pinus tabuliformis, Quercus variabilis, Robinia pseudoacacia) sampled from 64 plots with varying site and stand conditions. We found that the tree-ring δ13C of the four tree species varied from each other and was mainly affected by density and slope aspect, followed by slope and age. Both tree-ring δ13C and iWUE of the four tree species showed increasing trends over time, mechanistically linked to long-term changes in global CO2 concentration. This indicates the four native tree species have adapted well to climate change, and the risk of decline is relatively low. The increased iWUE translated into different growth patterns which varied with tree species, site, and stand condition. Different tree species have varying sensitivities to environmental factors. The iWUE of coniferous tree species is more sensitive to climate change than that of broad-leaved tree species, especially to temperature (T), the Standardized Precipitation Evapotranspiration Index (SPEI), and vapor pressure deficit (VPD).