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Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques and methods for identifying extreme rainstorm warnings in cultural heritage areas. Refined warning and forecasting have become important non-engineering measures to enhance these districts' waterlogging prevention control and emergency management capabilities. This paper constructs a rainstorm-induced waterlogging risk warning model tailored for Beijing's historical and cultural districts. This model system encompasses three sets of models: a building waterlogging early-warning model, a road waterlogging early-warning model, and a public evacuation early-warning model. During the construction of the model, the core concepts and determination methods of "1 h rainfall intensity water logging index" and "the waterlogging risk index in historical and cultural districts" were proposed. The construction and application of the three models take into full account the correlation between rainfall intensity and rainwater accumulation, while incorporating the characteristics of flood resilience in buildings, roads, and the society in districts. This allows for a precise grading of warning levels, leading to the formulation of corresponding warning response measures. Empirical tests have shown that the construction method proposed in this paper is reliable. The innovative results not only provide a new perspective and method for the early-warning of rainstorm-induced waterlogging, but also offer scientific support for emergency planning and response in historical and cultural districts. [ABSTRACT FROM AUTHOR]

Under the background of global climate change, rainstorm and flood disasters have become the most serious cataclysm. Under the circumstances of an increasingly severe risk situation, it is necessary to enhance urban disaster resilience. Based on the disaster resilience process of prevention, absorption, and enhancement, and considering the safety factors such as personnel, facility, environment and management, this paper forms a dual dimension of the urban disaster resilience assessment model covering the key elements of urban disaster response and the core capacity of urban disaster recovery. Furthermore, if taking into account the characteristics of rainstorm and flood disasters, the paper screens the key indicators to build up an assessment index system of an urban rainstorm and flood disaster. The practical application was implemented in Beijing to have an assessment of the ability to recover from rainstorm and flood disasters in all districts of Beijing. And then, some pertinent suggestions for enhancing the resilience of Beijing to rainstorm and flood disasters were proposed. [ABSTRACT FROM AUTHOR]

As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei (BTH) region is the most prominent area in China where the imbalance between the supply and demand of water resources restricts the sustainable and healthy development of the regional social economy. In the context of global warming, research into water demand prediction that takes climate change into consideration would be more in line with the strategic goal of the low-carbon sustainable development of future cities. At the same time, the prediction of agricultural water demands against a background of climate change is urgently needed, while industrial water consumption is weakly correlated with climate change, an investigation of the statistical relationship between the two is needed. Thus, in this paper, future climate data from the BTH region under the scenarios RCP2.6, RCP4.5 and RCP8.5 were generated using a statistical downscaling model, and then coupled with agricultural and industrial water demand prediction models to simulate and analyze the impact of climate change on the agricultural and industrial water demands, respectively. The results show that during the forecast period (2020–2035), the reference crop evapotranspiration (ET0) growth rates in the Beijing, Tianjin and Hebei areas under the RCP2.6 scenario are 1.438 mm·a−1, 1.393 mm·a−1 and 2.059 mm·a−1, respectively. Under the RCP4.5 scenario, they are 2.252 mm·a−1, 2.310 mm·a−1 and 2.827 mm·a−1, respectively. Under the RCP8.5 scenario, they are 3.123 mm·a−1, 2.310 mm·a−1 and 2.141 mm·a−1, respectively. Furthermore, under each climate scenario, the increase in evapotranspiration in the Hebei area is the largest, followed by that in the Tianjin area, and that in the Beijing area is the smallest. For water consumption per CNY 10,000 of industrial added value during the forecast period, under the three different climate scenarios, a downward trend is seen in the Beijing area, with rates of 0.158, 0.153 and 0.110, respectively, but in the Tianjin area, there is an upward trend, with an upward tendency in rates of 0.170, 0.087 and 0.071, and an upward trend in the Hebei area, with an upward tendency in rates of 0.254, 0.071 and 0.036, respectively. This study will help the BTH region to rationally allocate agricultural and industrial water against the background of future climate change, and strengthen the coordination and cooperation between the different regions to promote the healthy and sustainable development of the cities. [ABSTRACT FROM AUTHOR]

Instrumental data from the pre–Industrial Revolution period are important to -understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing's climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

As the most concentrated area of human activities, cities consume many natural resources and discharge a large amount of waste into the natural environment, which has a huge environmental impact. Most of the ecological and environmental problems, such as environmental pollution, global climate change, and loss of biodiversity, are related to urban systems. How to coordinate urban development with the urban ecological carrying capacity is related to the destiny of the city itself, and also to whether its surrounding areas can successfully achieve the goal of high environmental quality and sustainable development. At present, the theory and methods of urban ecological carrying capacity research are relatively new, which has caused problems for policy makers in practical applications. This paper proposes a theoretical framework for urban ecological carrying capacity assessment based on the analysis of ecosystem services supply and demand. Combined with multi-source spatial data and spatial model methods, the supply and demand of ecosystem services were spatially quantified. The capital city of China, Beijing, was the case study area for this research. The spatial differentiation of the supply–demand relationship of ecosystem services is formed. The priority areas for ecological carrying capacity improvement at pixel scale and at the administrative level are obtained, respectively. The results show that the first priority area is concentrated in the center of the urban area, accounting for 31.11% of the total area of Beijing. According to the secondary zone and the specific ecosystem service type, the ecological carrying capacity improvement strategy of different zones is proposed. This study provides a new perspective for investigating urban ecological carrying capacity and for identifying the priority areas for ecological carrying capacity improvement, and helps the policy-makers to design tailored policy actions. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) is a major air pollutant worldwide. Characterizing its chemical compositions and source contributions is a critical prerequisite for effective control of PM2.5 pollution. This paper systematically reviews the sampling methods, chemical compositions, and source apportionments of PM2.5. Sampling methods have significant influences on the identification of chemical compositions and source contributions, with Quartz and Teflon filters being the most widely used. Receptor models are commonly adopted for identifying the sources of PM2.5, such as positive matrix factorization, chemical mass balance, principal component analysis, and UNMIX models, which have their respective advantages and limitations that determine their applications. The variations of PM2.5 compositions and sources in the past two decades in Beijing are also reviewed, which is the political, economic, and cultural center of China and is experiencing severe haze pollution events frequently. It was found that organic matters were the largest component (28.2%) in PM2.5, followed by sulfate (15.1%) during 2004–2013, which was overtaken by nitrate (14.9%) after 2013. Each PM2.5 source demonstrated significant seasonal and annual variations due to changes in climatic conditions and anthropogenic activities. Future research on the impacts of these external factors is urgently needed. This review is expected to provide valuable advice and evidence for those fast-growing megacities like Beijing to identify and control their PM2.5-related air pollution problems. [ABSTRACT FROM AUTHOR]

Conducting trend analysis of climatic variables is one of the key steps in many climate change impact studies where trend is often checked against aggregated variables. However, there is also a strong need to investigate the trend of the data in different regimes – examples include high flow versus low flow, and heavy precipitation versus prolonged dry period. For this matter, quantile regression (QR) based methods are preferred as they can reveal the temporal dependencies of the variable in question for not only the mean value, but also its quantiles. As such, the tendencies revealed by the QR methods are more informative and helpful in studies where different mitigation methods need to be considered at different severity levels.In this paper, we demonstrate the use of several quantile regressions methods to analyse the long-term trend of rainfall records in two climatically different regions: The Dee River catchment in the United Kingdom, for which daily rainfall data of 1970–2004 are available; and the Beijing Metropolitan Area in China for which monthly rainfall data from 1950 to 2012 are available. Two quantiles are used to represent heavy rainfall condition (0.98 quantile) and severe dry condition (0.02 quantile). The trends of these two quantiles are then estimated using linear quantile regression before being spatially interpolated to demonstrate their spatial distribution (for Dee river only). The method is also compared with traditional indices such as SPI. The results show that the quantile regression method can reveal patterns for both extremely wet and dry conditions of the areas. The clear difference between trends at the chosen quantiles manifests the utility of QR in this context. [ABSTRACT FROM AUTHOR]

Urban bio-retention system is meaningful in reducing rainfall runoff and enhancing infiltration capacity. But the moisture migration in bio-retention systems are not clear under climate change. The spatial and temporal distribution of moisture under different rainfall events in bio-retention systems are studied in this paper based on experimental data in Beijing. Richards model is introduced to simulate the spatial and temporal distribution of moisture including pressure head, hydraulic head and water content under different initial and boundary conditions. As a result, we found that from the depth of the node to the lower boundary, the values of pressure head and hydraulic head increase with depth and decrease with time, while the values of water content represent opposite trends relative to the distribution of pressure head and hydraulic head in bio-retention systems. [ABSTRACT FROM AUTHOR]

The abnormal change in the global climate has increased the chance of urban rainstorm disasters, which greatly threatens people's daily lives, especially public travel. Timely and effective disaster data sources and analysis methods are essential for disaster reduction. With the popularity of mobile devices and the development of network facilities, social media has attracted widespread attention as a new source of disaster data. The characteristics of rich disaster information, near real-time transmission channels, and low-cost data production have been favored by many researchers. These researchers have used different methods to study disaster reduction based on the different dimensions of information contained in social media, including time, location and content. However, current research is not sufficient and rarely combines specific road condition information with public emotional information to detect traffic impact areas and assess the spatiotemporal influence of these areas. Thus, in this paper, we used various methods, including natural language processing and deep learning, to extract the fine-grained road condition information and public emotional information contained in social media text to comprehensively detect and analyze traffic impact areas during a rainstorm disaster. Furthermore, we proposed a model to evaluate the spatiotemporal influence of these detected traffic impact areas. The heavy rainstorm event in Beijing, China, in 2018 was selected as a case study to verify the validity of the disaster reduction method proposed in this paper. [ABSTRACT FROM AUTHOR]

Featured Application: This paper examines rainstorm-related micro-blogging activities in response to rainstorms in an urban environment at fine spatial and temporal scales. Results could be used in supporting disaster assessment and mitigation decision making. Natural disasters cause significant casualties and losses in urban areas every year. Further, the frequency and intensity of natural disasters have increased significantly over the past couple of decades in the context of global climate change. Understanding how urban dwellers learn about and response to a natural hazard is of great significance as more and more people migrate to cities. Social media has become one of the most essential communication platforms in the virtual space for users to share their knowledge, information, and opinions about almost everything in the physical world. Geo-tagged posts published on different social media platforms contain a huge amount of information that can help us to better understand the dynamics of collective geo-tagged human activities. In this study, we investigated the spatiotemporal distribution patterns of the collective geo-tagged human activities in Beijing when it was afflicted by the "6-22" rainstorm. We used a variety of machine learning and statistical methods to examine the correlations between rainstorm-related microblogs and the rainstorm characteristics at a fine spatial and a fine temporal scale across Beijing. We also studied factors that could be used to explain the changes of the rainstorm-related blogging activities. Our results show that the human response to a disaster is very consistent, though with certain time lags, in the virtual and physical spaces at both the grid and city scales. Such a consistency varies significantly across our study area. [ABSTRACT FROM AUTHOR]

Changes of wind load caused by climate change have a considerable impact on the safety of bridge structures. This paper collects the annual maximum wind speed in Beijing from 1951 to 2009 and establishes the relationship between the reliability and the flexural load-bearing capacity of a highway continuous girder bridge. In order to consider climate change effect more broadly, the influence of climate change on the reliability of the bridge is considered under two scenarios: the first scenario assumes that wind speed increases by 10% and 20%, respectively; the second scenario is that the annual maximum wind speeds in the next 30 years are predicted based on the actual statistical wind speed data, and the changes of the flexural reliability of the bridge under the second scenario with time are obtained. According to the obtained results, it can be seen that the reliabilities calculated based on the two scenarios are quite different, and the change of flexural reliability of the bridge is affected by the probability distribution of wind speed. [ABSTRACT FROM AUTHOR]

Abstract Electrifying urban transportation through the adoption of Electric Vehicles (EVs) has great potential to mitigate two global challenges, namely climate change and energy scarcity, and also to improve local air quality and further benefit human health. This paper was focused on the six typical factors potentially influencing the purchase behaviour of EVs in Beijing, China, namely vehicle price, vehicle usage, social influence, environmental awareness, purchase-related policies and usage-related policies. Specifically, this study used the data collected in a paper-based questionnaire survey in Beijing from September 2015 to March 2016, covering all of the 16 administrative regions, and tried to quantify the relative importance of the six factors, based on their weights (scores) given by participants. Furthermore, Multinomial Logit (MNL) models and Moran's I (a measure of global spatial autocorrelation) were used to analyse the weights of each factor from statistical and spatial perspectives, respectively. The results suggest that 1) vehicle price and usage tend to be more influential among the six factors, accounting for 32.3% and 28.1% of the importance; 2) Apart from the weight of social influence, the weights of the other five factors are closely associated with socio-demographic characteristics, such as individual income and the level of education; 3) people having similar attitudes towards vehicle usage (Moran's I = 0.10) and purchase restriction (Moran's I = 0.14) tend to live close to each other. This paper concludes with a discussion on applying the empirical findings in policy making and modelling of EV purchase behaviour. [ABSTRACT FROM AUTHOR]

In this paper, the data envelopment analysis (DEA) method is introduced to analyze the input-output efficiency of energy consumption and economic indicators in Beijing city under the influence of short-term climatic factors. Total energy consumption, fixed asset investment, average temperature, precipitation, sunshine hours, average wind velocity and the average pressure being employed as the input variables, gross domestic product (GDP) and per capita disposable income being employed as the output variables, effective technology and the validity of the scale of DEA of 31 decision-making units ( DMUs) under the influence of the short-term climatic factors are analyzed, and the inefficient DMUs are improved. Empirical analysis shows that both energy consumption and economic growth are sensitive to short-term climate condition, and the reasonable employing of extreme climatic conditions is a question worthy of consideration. This study provides effective basis for the scientific and reasonable arrangement of Beijing city's short-term climatic resources and energy-economic development. [ABSTRACT FROM AUTHOR]

Sudden events of crisis ('focusing events') trigger intense media reporting, which in turn can prompt political decision-makers to respond with an adjustment of existing policies. As such, focusing events can potentially lead to long-term policy change on a certain issue. This article explores the sudden and intense period of air pollution in Beijing in January 2013 as a focusing event. The episode, which international media referred to as 'Airpocalypse', triggered widespread discussion and policy adjustments that can be assumed to have accelerated the control of air pollution in China. The 'Airpocalypse' was not the first event of intense air pollution in Beijing, but the only one which seemingly caused lasting sociopolitical changes. The aim of this article is to explore the underlying situational factors that enabled the 'Airpocalypse' to be more relevant than other events of severe air pollution. This paper argues that a combination of historically high pollution, improved access to information, increasing government willingness to address the issue, and the ability of media to more openly discuss air pollution created a public pressure situation to which the government was prompted to respond in a stronger way than during previous events of heavy air pollution. [ABSTRACT FROM AUTHOR]

On 21-22 July 2012, torrential rains hit North China, with the daily precipitation record at Beijing station reaching 160.6 mm; this event is named the Beijing 7-21 case. This paper assesses the likelihood of the occurrence of local torrential rains, such as the Beijing 7-21 case, from the perspective of climate variability. In particular, the influence of the Pacific Decadal Oscillation (PDO) is assessed. There were five extreme events, with daily precipitation records equal to or larger than 160.6 mm, at Beijing station during the period 1951-2012; all of these events happened during negative phases of the PDO. The present analysis indicates that precipitation events more extreme than the Beijing 7-21 case should happen more than once per decade during negative phases of the PDO, but only about once every four decades during positive PDO phases. The negative phase of the PDO is found to be associated with a much greater probability of daily records of southerly winds in North China during summer. Strong southerly summer monsoons are deemed favorable for increasing the occurrence of local extreme rainfall over North China. [ABSTRACT FROM AUTHOR]

There is a growing interest in addressing moral aspects in the research and education of socio-scientific issues. This paper investigates students' interpretations of climate change from a moral perspective. The students were 14 years old, studying at Green Schools in the Beijing area, China. The study was based on semi-structured group interviews and the data were analysed from an intentional perspective, which means that both cognitive and situational aspects were taken into consideration in the analysis. Previous research has revealed a close relation between morality and socio-scientific issues and also advocated the need for addressing ethical aspects in science education. However, empirical studies exploring the question of what students' moral reasoning might look like at the individual level have not yet generated enough attention. In this study this is the core focus of interest. The findings show that the students conceptualise the solutions to mitigating climate change in relation to two different stances. That is, they contextualise the problems and solutions by addressing the individual, where the individual is either 'myself' or 'someone else'. The different notions of the individual become crucial as the students' views and considerations for the environment, as well as society, change according to the different contexts. From a moral point of view, the students seem quite unaware of their varying consideration for others, the environment and society. The paper ends with a discussion of implications for practice and research. [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosols are important for absorbing aerosols, affecting global climate change and regional air quality, and potentially harming human health. From March to May 2023, we investigated black carbon aerosol levels and air pollution in Beijing. Employing methods such as linear regression, Potential Source Contribution Function (PSCF) and Concentration-Weighted Trajectory (CWT), we analyzed the characteristics and sources of black carbon aerosols in the region. Results indicate that the light absorption coefficients of BC and BrC decrease with increasing wavelength, with BrC accounting for less than 40% at 370 nm. Daily variations in BC and PM2.5 concentrations exhibit similar trends, peaking in March, and BC displays a distinct bimodal hourly concentration structure during this period. Aethalometer model results suggest that liquid fuel combustion contributes significantly to black carbon (1.08 ± 0.71 μg·m−3), surpassing the contribution from solid fuel combustion (0.31 ± 0.2 μg·m−3). Furthermore, the significant positive correlation between BC and CO suggests that BC emissions in Beijing predominantly result from liquid fuel combustion. Potential source area analysis indicates that air masses of spring in Beijing mainly originate from the northwest (40.93%), while potential source areas for BC are predominantly distributed in the Beijing–Tianjin–Hebei region, as well as parts of the Shandong, Shanxi and Henan provinces. Moreover, this study reveals that dust processes during spring in Beijing have a limited impact on black carbon concentrations. This study's findings support controlling pollution in Beijing and improving regional air quality. [ABSTRACT FROM AUTHOR]

This study investigated the adverse impact of climate change and climate-related uncertainties on urban waterlogging. Based on multiclimate models, the future extreme precipitation and urban waterlogging under uncertainties was assessed for Beijing. Future rainfall scenarios under two representative concentration pathways (RCP4.5/RCP8.5) were generated by the Delta change method combined with Chicago design storm. The InfoWorks ICM was used to simulate the extent of urban waterlogging. Results showed that urban waterlogging in Beijing would increase, which would be induced not only by more severe climate changes, but also by the limited capacity of drainage systems. In addition, the model uncertainties were found to be increased with both the precipitation intensity and the level of climate change, potentially reaching up to 109%. Therefore, this study highlights the importance for taking climate change and the consequent uncertainties into consideration when designing waterlogging prevention measures. [ABSTRACT FROM AUTHOR]

Regional vulnerability research is helpful in understanding the formation mechanism of regional disaster risk deeply. Owing to the pressure from earthquake disasters occurred frequently in the whole world, the assessment of regional vulnerability to seismic hazards is a focus in current research of seismic disaster risk. This paper presents a nonlinear dynamic model for assessing regional vulnerability to seismic hazards based on maximum flux principle (MFP). Firstly, a vulnerability index system was designed for the urban agglomeration of Beijing, Tianjin and Hebei in China, and the index data were obtained based on the Statistical Yearbook and other materials. The vulnerability indexes constituted a complex system, and the indexes were taken as the components of the complex system. Secondly, based on the information theory and MFP, a dynamic equation that controls the generation and evolution of the complex system was derived theoretically. The regional vulnerability evaluation was realized by conferring reasonable weight to the indexes to make the system become stable. Finally, the self-organizing neural network was used to simulate the mechanism model to implement vulnerability assessment. The assessment results showed that Langfang and Chengde were at high vulnerability level; Qinghuangdao, Cangzhou and Zhangjiakou were at moderate vulnerability level; Baoding, Shijiazhuang, Beijing and Tangshan were at lower vulnerability level; Tianjin was at low vulnerability level. It reveals that the investment in disaster prevention was in an unbalanced situation among all the cities in Beijing-Tianjin-Hebei metropolitan area. [ABSTRACT FROM AUTHOR]

Cloud top height (CTH) is an essential pareter for the general circulation model in understanding the impact of clouds on the Earth's radiation budget and global climate change. This paper compares the CTH products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the Aqua and Terra satellites with ground-based Ka band radar data in Beijing from 2014 to 2017. The aim was to investigate the data accuracy and the difference in CTH measurements between passive satellite data and active ground-based radar data. The results show that MODIS, on average, underestimates CTH relative to radar by −1.08 ± 2.48 km, but with a median difference of −0.65 km and about 48% of differences are within 1 km. Statistically, MODIS CTHs which are greater than 6 km show lower discrepancy to radar CTH than those of MODIS CTHs less than 4 km. The CTH difference is independent of cloud fraction and cloud layer. It shows strong dependence on cloud depth, decreasing as cloud depth increases. There is a tendency for MODIS to underestimate high thin clouds but overestimate low thin clouds relative to radar. Total ozone, SO2, CO, NO2, aerosol PM10, total water vapor and temperature inversion show unobvious influences in the CTH discrepancy. It is shown that the MODIS CO2-slicing technique performs much better than IRW (infrared window) technique when cloud layer is higher than 2 km. The average difference calculated from all comparisons by CO2-slicing technique and IRW technique is 0.09 ± 1.58 km, and −2.20 ± 2.73 km, respectively. [ABSTRACT FROM AUTHOR]

Climate change, such as temperature and precipitation changes, is becoming increasingly obvious, and in this context, planting designs need to urgently consider future climate change in advance. A field experiment was conducted in Beijing, China, where the future precipitation is predicted to increase, and extra irrigation was used to simulate the future precipitation increase. The species richness of sown meadows, including spontaneous plants and sown plants, and the adaptive strategies of the communities were recorded under different types of design models and substrates. The results showed that precipitation increased the diversity of sown plants and resource-demanding spontaneous plants but had no significant effect on the dry matter content of the entire community of species. Moreover, the interactions among precipitation and substrate, especially the design models, were significant. Of the models, the three-layer model had the highest species richness and least invasive plants. In addition, increased precipitation significantly changed the functional strategy of the plant community away from ruderals and towards competitor-stress tolerant species. This study provides guidance for the design and management of naturalistic plant communities under climate change. [ABSTRACT FROM AUTHOR]

The latest Version-7 (V7) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products were released by the National Aeronautics and Space Administration (NASA) in December of 2012. Their performance on different climatology, locations, and precipitation types is of great interest to the satellite-based precipitation community. This paper presents a study of TMPA precipitation products (3B42RT and 3B42V7) for an extreme precipitation event in Beijing and its adjacent regions (from 00:00 UTC 21 July 2012 to 00:00 UTC 22 July 2012). Measurements from a dense rain gauge network were used as the ground truth to evaluate the latest TMPA products. Results are summarized as follows. Compared to rain gauge measurements, both 3B42RT and 3B42V7 generally captured the rainfall spatial and temporal pattern, having a moderate spatial correlation coefficient (CC, 0.6) and high CC values (0.88) over the broader Hebei, Beijing and Tianjin (HBT) regions, but the rainfall peak is 6 h ahead of gauge observations. Overall, 3B42RT showed higher estimation than 3B42V7 over both HBT and Beijing. At the storm center, both 3B42RT and 3B42V7 presented a relatively large deviation from the temporal variation of rainfall and underestimated the storm by 29.02% and 36.07%, respectively. The current study suggests that the latest TMPA products still have limitations in terms of resolution and accuracy, especially for this type of extreme event within a latitude area on the edge of coverage of TRMM precipitation radar and microwave imager. Therefore, TMPA users should be cautious when 3B42RT and 3B42V7 are used to model, monitor, and forecast both flooding hazards in the Beijing urban area and landslides in the mountainous west and north of Beijing. [ABSTRACT FROM AUTHOR]

Highlights • The increases of commuting CO 2 emissions are several times larger than the urban size, population, and economics' developments. • Metro services reducing commuting CO 2 emissions near the metro stations is not statistically significant, possibly because the proportions of car users near the metro stations are similar to the two cities' average levels, which is caused by their higher household income and the longer travel time using the metro. • In Beijing, there are the smallest commuting CO 2 emissions in the outer suburbs due to job-housing balances, short distance and large percentage of non-motorized mode uses while the largest commuting CO 2 emissions in the inner sprawl suburbs due to car trips with long distance. Abstract To understand the changing relationships between commuting CO 2 emissions (CCE), travel behavior and urban forms, this paper provides a comparative study between the typical Chinese cities of Beijing (more developed) and Xi'an (rapidly developing). Further, the effects of metro services on reducing CCE were explored, and comparative analysis on CCE between the inner sprawling suburbs and outer suburbs was conducted. It was found that: (i) the increases in CCE are several times larger than the increases in urban size, population, and economic developments; (ii) metro services reducing CCE near metro stations is not statistically significant, maybe because the proportions of car users near the metro stations are similar to the two cities' average levels, which is caused by their higher household income and the longer travel time using the metro; (iii) in Beijing, there are smallest CCE in the outer suburbs due to job-housing balances, short distance and large percentage of non-motorized mode uses while largest CCE in the inner sprawl suburbs due to car trips with long distance. These findings indicate that to cope with the rapidly increasing CCE, more attention should be paid to developing strong industry and real-estate simultaneously; the improvement in the feeder bus and public bicycle systems should also be reinforced to reduce the total travel time of metro users; and satellite cities with job-housing balance are greatly needed. The implications will benefit efforts to reduce CCE and mitigate global climate change, and they also provide empirical evidence and reference values for other global cities. [ABSTRACT FROM AUTHOR]

Abstract: Remote sensing has become an important method for monitoring urban thermal environment, but, it is still difficult to analysis the spatio-temporal change of urban thermal environment quantitatively only by ground surface temperature (or brightness temperature). Three indexes on urban thermal environment monitoring are proposed in this paper: heat island intensity, heat field intensity index and heat island proportion index. Based on MODIS surface temperature products and FY3A/MERSI data of two years, urban thermal environment is monitored by remote sensing method in Beijing. The empirical results verify that three indexes proposed in this paper are meaningful in monitoring of urban heat island. It can not only monitor the intensity and changes of the urban heat island in Beijing effectively, but also, it is positive to carrying out meteorological operations in city thermal environment monitoring. [Copyright &y& Elsevier]

Abstract. In order to quantify the aerosol impact on climate, a range of aerosol parameters are required. In this paper, two-year of ground-based observations of aerosol optical properties from an urban site in Beijing of China are assessed. The aerosol absorption coefficient (σα), scattering coefficient (σs ), as well as single scattering albedo (ω) are analyzed to aid in characterizing Beijing's urban aerosol. Two-year averages (and standard deviations) for σα at 532 nm, σs at 525 nm and ω at 525 nm are 56±49Mm-1, 288±281Mm-1 and 0.80±0.09, respectively. Meanwhile, there is a distinct diurnal variation for σα, with its minimum occurring at approximately 14:00 to 15:00 and maximum at midnight. σs peaks in the late morning and the minimum occurs in the evening. σs in summer is higher than that in winter. ! is also higher in summer than that in winter, except before 07:00 a.m., and peaks in the early afternoon. Both σα and σs show strong dependence on local wind in all four seasons. When the wind blows from the north with low speed (0-2 m/s), the values of σα are high, and in contrast, very low with wind speeds higher than 4 m/s. When the wind blows from south with low speed (0-4 m/s), σα is intermediate. The patterns of the wind dependence of σα indicates that σα is mainly dominated by local emissions. σs displays a similar dependence on wind speed and direction to σα, except in summer. In summer, the σs value is highest when wind is from southeast with speed of 0-6 m/s. This indicates that the particle pollution resulting from regional transport is only significant in the summer season. ω also shows wind dependence to some extent though not as strong as σα or σs . Overall, the wind dependence results provide valuable information about the locations of aerosol pollution sources and suggest that the air pollution in summer is a regional problem but in other seasons it is mainly affected by local urban emissions. [ABSTRACT FROM AUTHOR]

As a extra-large city in China, Beijing faces a serious problem with air pollution. In 1998, a package of air pollution control measures was announced by local government. However in order to reach environment target, further policy options have to be explored. Based on previous studies on technology choices for urban transport in Beijing, this paper presents a policy assessment to examine these options. A methodology framework using criteria for policy evaluation was used in the assessment. Here diesel-car, Compressed Natural Gas (CNG) vehicle and Mass Railway based Transport (MRT) were selected, and barriers to their diffusion were identified. For each barrier, a group of policy options to remove the barrier was evaluated by five criteria. A ranking of these policy options is given in this paper. [ABSTRACT FROM AUTHOR]

For curbing the global climate crisis, China has set an ambitious target of peak carbon emissions by 2030. Beijing, the capital of China, has implemented a carbon reduction policy since 2012. Using the reduced and generalized forms of the Environmental Kuznets Curve (EKC), we deduce that both the cubic EKC and the genetic algorithm-based EKC have an N-shape. The first turning point of the three-order EKC occurs around 2011, demonstrating the effectiveness of the carbon reduction policy. However, the time series model predicts that Beijing will reach the second turning point around 2026, when the gross domestic product (GDP) is about CNY 5000 billion and carbon emissions will begin to increase again. Interpretable machine learning is proposed to explore the socio-economic drivers in carbon emissions, indicating that total energy consumption and GDP contribute the most. Therefore, we should accelerate the upgrading of energy consumption and adjust the industrial structure, thus facilitating Beijing to its peak carbon emissions and achieving carbon neutrality. [ABSTRACT FROM AUTHOR]

Extreme weather events are happening more frequently as a result of global climate change. Dust storms broke out in the spring of 2017 in China and drastically impacted the local air quality. In this study, a variety of data, including aerosol vertical profiles, surface particle concentration, meteorological parameters, and MODIS–derived aerosol optical depth, as well as backward trajectory analysis, were employed to analyze two dust events from April to May in Beijing. The dust plumes were mainly concentrated below 0.8 km, with peak PM10 values of 1000 μg·m−3 and 300 μg·m−3 in the two cases. The aerosols showed different vertical distribution characteristics. The pure dust in case 1 from 4 to 5 May 2017 had a longer duration (2 days) and presented a larger aerosol extinction coefficient (2.27 km−1 at 355 nm and 1.25 km−1 at 532 nm) than that of the mixed dust in case 2 on 17 April 2017 (2.01 km−1 at 355 nm and 1.33 km−1 at 532 nm). The particle depolarization ratio (PDR) remained constant (0.24 ± 0.03 in case 1) from the surface to 0.8 km in height. In contrast, the PDR profile in the mixed dust (case 2) layer was split into two regions—large values exceeding 0.15 above 0.6 km and small values of 0.11 ± 0.03 below 0.6 km. The influence of meteorological information on aerosol distribution was also investigated, and wind was predominant through the observing period. The pure dust in case 1 was mainly from Mongolia, with strong northwest winds, while the near-surface mixed pollution was caused by the combination of long-transported sand and local emission. Furthermore, lidar-derived profiles of dust mass concentrations in the two cases were presented. This study reveals the vertical characteristics of dust aerosols in the production and dissipation of localized dust events and confirms the efficacy of thorough observations with multiple approaches from the ground to space to monitor dust events in real time. [ABSTRACT FROM AUTHOR]

Water shortages and groundwater depletion are critical issues in the world, leading to unsustainable agricultural production and adverse ecological impacts. Here, the new Multifactor-Quantitative joint Prediction Model (MQPM) is developed to quantitatively predict the Groundwater Storage Anomalies (GWSA), which includes an annual multifactor module and a monthly quantitative module. The correlative coefficients from two modules between simulated GWSA and observed GWSA reach up to 0.98 and 0.87, respectively. Taking Beijing as an example, results show that GWSA trends before South-to-North Water Diversion (SNWD) (2005–2014) and after SNWD (2015–2018) are at a rate of −3.00 × 108 m3/yr and 1.95 × 108 m3/yr, respectively, which reflects the effectiveness of water diversion. Additionally, the predicted results show that GWSA from the multifactor module will increase to 45.97 × 108 m3 by 2028. The quantitative module designs four scenarios under different climate changes and policies, from which the predicted GWSA with values ranging from 28.49 × 108 m3 to 63.06 × 108 m3. For the latter module, the groundwater level will recover to ∼8.9 m up to 2028, combining multiple favorable conditions. Finally, factors consisting of water diversion, climate change, and water-saving policies have a vital influence on groundwater variations, and contributions of these factors to the GWSA account for 46%, 27%, and 27%, respectively. [ABSTRACT FROM AUTHOR]

The agricultural sector is extremely vulnerable to climate change and also plays a very important role in the operation of the entire economic system, leading many studies to evaluate the possible agricultural direct economic damage (ADED) of climate change. However, this damage may have an amplification impact through the intricate industrial linkages that exist among sectors, and this impact may be even greater than the original damage. Therefore, to elucidate the economic cascading effect (ECE) in China caused by ADED and industrial linkage, this paper used the ARIO model to evaluate the total ECE and analyse the differences in the 19 sectors by taking the ADED under future annual mean temperature (AMT) increases of 1–5 °C as the input condition and adjusting the exogenous parameters to enhance the adaptability of the model; the goal was to assess the economic impact of climate change in China. The results show that (i) there is a significant amplifying impact of ECE due to industrial linkage under the influence of warming, ECE will be 4.24–5.25 times that of ADED, and the total economic impact (ADED + ECE) will exceed the GDP of the Chinese capital of Beijing in 2012 when the AMT increases by 1.5 °C, while it will exceed one tenth of China's GDP when it increases by 4 °C. (ii) Manufacturing will be the sector most affected by the industrial linkage under ADED, which accounts for 26.58% of total ECE, followed by agriculture (10.39%) and construction (8.5%). (iii) The decrease in cultivated land area will have a significant impact on the economy; when it is reduced to the minimum demand (1.41% less than 2012), ADED increases by 1.65 times and ECE increases by 2.35 times. This paper aims to provide a new perspective from which to evaluate the economic impact of climate change by studying ECEs behind sectoral interactions. [ABSTRACT FROM AUTHOR]

A comprehensive GHG inventory provides an overview and the information of sources of emissions, and can serve as a sound scientific basis for mitigation actions. This study was the first initiative to develop a complete and transparent GHG inventory of Beijing, to document the current situation and to help governmental officials to clarify their priorities for reducing GHG emissions. The authors investigated and calculated the emission sources defined by the GPC, and assessed data accuracy. The contents of the detailed inventory were documented and are open for research verification and for methodological references for other cities. The results showed that three emission sources, i.e. CO 2 emissions from fossil fuel consumption, CO 2 emissions from industrial production and CH 4 emissions from landfills, contributed 97% of Beijing's GHGs. Considering the problem of missing data and low data quality, the authors suggested that instead of seeking to compile a complete inventory, Chinese cities should first report their GHG emissions from these sources, while improving the data quality for the long run. The authors anticipate that the findings reported in this paper will help to strengthen city-level GHG inventory research in China and throughout the world. [ABSTRACT FROM AUTHOR]

Beijing, as the capital of China, is under the high pressure of climate change and pollution. The consumption of non-renewable energy is one of the most important sources of the CO 2 emissions, which cause climate changes. This paper presents a study on the energy system modelling towards renewable energy and low carbon development for the city of Beijing. The analysis of energy system modelling is organized in two steps to explore the alternative renewable energy system in Beijing. Firstly, a reference energy system of Beijing is created based on the available data in 2014. The EnergyPLAN , an energy system analysis tool, is chosen to develop the reference energy model. Secondly, this reference model is used to investigate the alternative energy system for integrating renewable energies. Three scenarios are developed towards the energy system of Beijing in 2030, which are: (i) reference scenario 2030 , (ii) BAU ( business as usual ) scenario 2030 , and (iii) RES ( renewable energies ) scenario 2030 . The 100% renewable energy system with zero CO 2 emissions can be achieved by increasing solar energy, biomass and municipal solid waste (MSW) and optimizing heating system. The primary fuel consumption is reduced to 155.9 TWh in the RES scenario, which is 72% of fuel consumption in the reference scenario 2030. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) adversely affects air quality, human health and the climate, and it is more prevalent in urban areas. Few efforts have been made to quantify the impact of trade on PM concentrations in an urban economy. This paper presents an analysis of the impacts of domestic and international trade on PM emissions in Beijing using a three-scale input–output model, supported by the national and global embodied energy-related PM 2.5 , PM 10 and TSP (total suspended particulate) emission intensities. The results found that the total energy-related PM 2.5 , PM 10 and TSP emissions (production-based) in Beijing were 106 Gg, 163 Gg and 347 Gg, respectively, in 2010. Of these amounts, 48% (51 Gg, 74 Gg and 146 Gg, respectively) was associated with local demand, 42% (44 Gg, 73 Gg and 168 Gg, respectively) was associated with domestic exports, and 10% (11 Gg, 16 Gg and 33 Gg, respectively) was associated with international exports. From a consumption perspective, Beijing’s PM 2.5 , PM 10 and TSP emissions were more than double the production-based PM emissions. Approximately 75% (172 Gg, 311 Gg and 786 Gg, respectively) of the consumption-based PM emissions were domestically outsourced to other provinces, primarily via the import of metal (32 Gg, 58 Gg and 151 Gg), construction (26 Gg, 36 Gg and 91 Gg) and chemical products (16 Gg, 30 Gg and 75 Gg), and 3% (8 Gg, 10 Gg and 24 Gg, respectively) of consumption-based PM emissions were outsourced abroad. Our results indicate that domestic trade plays a dominant role in Beijing’s PM 2.5 emissions. These findings suggest that more national and sub-national government should co-ordinate design and implement effective mechanisms to alleviate urban air pollution because of the significant effects of interprovincial and international trade on local emissions. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the association between relative humidity (RH) and various cause of mortality, and then quantify the RH-related mortality fraction of low and high RH under the assumption that causal effects exist. Daily cause-specific mortality counts from 2008 to 2011, and contemporaneous meteorological data in three Chinese cities were collected. Distributed lag nonlinear models were adopted to quantify the nonlinear and delayed effects of RH on mortality risk. Low and high RH were defined as RH lower or higher than the minimum mortality risk RH (MMRH), respectively. Corresponding RH-related mortality fractions were calculated in the explanatory analysis. From the three cities, 736,301 deaths were collected. RH (mean ± standard deviation) were 50.9 ± 20.0 for Beijing, 75.5 ± 8.6 for Chengdu, and 70.8 ± 14.6 for Nanjing. We found that low RH in Beijing and high RH (about 80–90%) in Chengdu was associated with increased all-cause mortality risk. Both low and high RH may increase the CVD mortality risk in Beijing. Both low and high (about 80–85%) RH may increase the COPD mortality risk in Chengdu. Low RH (about < 45%) was associated with increased diabetes mortality risk in Nanjing. Effects of extreme low and extreme high RH were delayed in these cities, except that extreme low effects on COPD mortality appeared immediately in Chengdu. The effects of extreme low RH are higher than that of the extreme high RH in Beijing and Nanjing, while contrary in Chengdu. Finally, under the causal effect assumption, 6.80% (95% eCI: 2.90, 10.73) all-cause mortality and 12.48% (95% eCI: 7.17, 16.80) CVD deaths in Beijing, 9.59% (95% eCI: 1.38, 16.88) COPD deaths in Chengdu, and 23.79% (95% eCI: 0.92, 387.93) diabetes mortality in Nanjing were attributable to RH. Our study provided insights into RH-mortality risk, helped draw relative intervention policies, and is also significant for future predictions of climate change effects under different scenarios. [ABSTRACT FROM AUTHOR]

Understanding the effects of climate change on building indoor thermal conditions is of importance for providing a comfortable thermal environment for occupants. Some multi-family dwellings have already been listed as heritage in China (hereinafter referred to as heritage apartments), limiting modifications to the building envelope. However, the effect of climate change on thermal comfort in heritage apartments with a compact interior (i.e. without a living room) built before the 1980s in different Chinese climate zones has seldom been studied. This study focuses on the current and future thermal comfort in two-bedroom heritage apartments in China. The study was conducted for two different Chinese climate zones, that is, a cold climate zone (Beijing), and a hot summer and cold winter climate zone (Shanghai) and both current climate scenarios (typical meteorological years) and future climate scenarios (2050) were used. The results indicate, among other things, increases of 58%–60% and 41%–44% in the predicted average number of overheating hours in 2050 compared to the current climate for the studied bedrooms on the first floor in dwellings in Beijing and Shanghai, respectively. [ABSTRACT FROM AUTHOR]

The present study investigates the response of natural gas consumption to temperature on the basis of observations during heating season (middle November–middle March) for the period 2002–2021 in Beijing, China, and then estimates temperature-related changes in the gas consumption under future scenarios by using climate model simulations from the Coupled Model Intercomparison Project Phase 6. Observational evidence suggests that the daily natural gas consumption normalized by gross domestic product is linearly correlated with the daily average temperature during heating season in the past two decades in Beijing. Hence, a linear regression model is built to estimate temperature-related changes in the natural gas consumption under future scenarios. Corresponding to a rising trend in the temperature, the natural gas consumption shows a decrease trend during 2015–2100 under both the SSP245 and the SSP585 scenarios. In particular, the temperature would increase rapidly from early 2040s to the end of 21st century under the SSP585 scenario, leading to an obvious reduction in the natural gas consumption for heating in Beijing. Relative to that in the present day (1995–2014), the natural gas consumption would show a reduction of approximately 9% (±4%) at the end of 21st century (2091–2100) under the SSP245 scenario and approximately 22% (±7%) under the SSP585 scenario. [ABSTRACT FROM AUTHOR]

Beijing, a megacity in northern China, has been long facing the challenge of water scarcity, and the problem of domestic water scarcity has been becoming more serious in recent years due to climate change and global warming. To cope with the adverse effects of climate change, it is urgent to build a prediction model for water consumption in Beijing under the background of climate change. Here, a climate domestic water use model was established based on the historical meteorological data and domestic water use data, and the future domestic water demand in Beijing and the response of domestic water use to climate change were projected. The results showed that the climatic water consumption in Beijing will increase with climate warming by 177.23 million m3/°C, and the per capita annual water consumption will increase by 8.1 m3/°C. Combined with the CMIP6 multi-model climate change scenario data, the climate domestic water consumption in Beijing in 2035 under the four scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 will be 169 million m3, 189 million m3, 208 million m3, and 235 million m3 respectively; by 2050, the climate domestic water consumption in Beijing will reach 338 million m3, 382 million m3, 395 million m3, and 398 million m3, respectively. Under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, if all the increased climate domestic water consumptions are supplemented by groundwater, compared with 2019, the groundwater depth will decrease by 0.18 m, 0.22 m, 0.27 m, and 0.32 m in 2035, respectively, and the area of funnel area will increase by 6.84 km2, 8.48 km2, 10.11 km2, 12.34 km2 respectively. Compared with 2035, the groundwater depth in 2050 will decrease by 0.37 m, 0.43 m, 0.41 m and 0.36 m, respectively, the area of funnel area will increase by 14.13 km2, 16.21 km2, 15.61 km2, and 13.68 km2, respectively. If the increased climatic water consumption in Beijing is supplemented by external water transfer, the cost of external water transfer in 2035 will increase by CNY 391 million, CNY 485 million, CNY 578 million, and CNY 706 million, respectively, compared with that in 2019 under the four scenarios. Compared with 2035, the cost of external water transfer in 2050 will increase by CNY 808 million, CNY 927 million, CNY 893 million, and CNY 783 million, respectively. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports findings of a recent field study that characterized the on-road emissions of individual diesel vehicles in and around Beijing, China during November and December of 2009. We successfully sampled 230 individual trucks on 4 major expressways around the city as well as 57 individual buses in the city using refined mobile chasing techniques and fast response instruments. Emission factors (EF) for carbon monoxide (CO), black carbon (BC) and particulate matter with diameters less than 0.5 μm (PM0.5) are derived from the measurements, which are consistent with the results from laboratory dynamometer tests. The PM0.5 number emission factor distributions demonstrate consistent bimodal modes with peaks around 10 nm and 80 nm, while the mass emission factor distributions demonstrate a unimodal maximum around 110 nm for a majority of the trucks. The BC emissions are shown to be highly correlated with the mass emission of particles with 100–250 nm diameters, which are in good agreement with the results from previous studies. A number of important policy implications are discussed based on the results from this study. First, we identified “heavy emitters” in the on-road fleet we encountered, finding that 5% of diesel trucks in this sample are responsible for 50% of total BC emissions, and 20% of the trucks are responsible for 50% CO and PM0.5 number emissions, 60% PM0.5 mass emissions and over 70% of BC emissions. This suggests that emissions control programs should include identifying and removing heavy emitters from the road or improving their emissions. Second, the BC and PM0.5 number emission factors of trucks registered in regions outside Beijing are significantly higher than those of Beijing-registered trucks, suggesting that improving engine and fuel standards in Beijing alone is not sufficient in reducing the traffic-related air pollution in Beijing. Third, the significantly lower emissions from Euro IV and CNG buses compared to the Euro II and Euro III buses support that introducing clean-burning buses is an effective way to reduce the overall vehicle emissions for the pollutants studied. Fourth, our refined chasing method demonstrates a cost-effective approach to characterize the emissions from a large number of on-road diesel vehicles. Further studies with large sample sizes are critical to constructing more accurate mobile emission inventories to represent the on-road vehicle population. [Copyright &y& Elsevier]

Abstract: The aggressive traffic interventions and emission control measures implemented to improve air quality during the 2008 Beijing Olympic Games created a valuable case study to evaluate the effectiveness of these measures on mitigating air pollution and protecting public health. In this paper, we report the results from our field campaign in summer 2008 on the on-road emission factors of carbon monoxide, black carbon (BC) and ultrafine particles (UFP) as well as the ambient BC concentrations. The fleet average emission factors for light-duty gasoline vehicles (LDGV) showed considerable reduction in the Olympic year (2008) compared to the pre-Olympic year (2007). Our measurement of Black Carbon (BC), a primary pollutant, at different elevations at the ambient site suggests consistent decrease in BC concentrations as the height increased near the ground level, which indicates that the nearby ground level sources, probably dominated by traffic, contributed to a large portion of BC concentrations in the lower atmospheric layer in Beijing during summertime. These observations indicate that people living in near ground levels experience higher exposures than those living in higher floors in Beijing. The BC diurnal patterns on days when traffic control were in place during the Olympic Games were compared to those on non-traffic-control days in both 2007 and in 2008. These patterns strongly suggest that diesel trucks are a major source of summertime BC in Beijing. The median BC concentration on Olympic days was 3.7 μg m−3, which was dramatically lower than the value on non-traffic-control days, indicating the effectiveness of traffic control regulations in BC reduction in Beijing. [Copyright &y& Elsevier]

In this paper, we report the results and analysis of a recent field campaign in August 2007 investigating the impacts of emissions from transportation on air quality and community concentrations in Beijing, China. We conducted measurements in three different environments, on-road, roadside and ambient. The carbon monoxide, black carbon and ultrafine particle number emission factors for on-road light-duty vehicles are derived to be 95gkg−1-fuel, 0.3gkg−1-fuel and 1.8×1015 particleskg−1-fuel, respectively. The emission factors for on-road heavy-duty vehicles are 50gkg−1-fuel, 1.3gkg−1-fuel and 1.1×1016 particleskg−1-fuel, respectively. The carbon monoxide emission factors from this study agree with those derived from remote sensing and on-board vehicle emission testing systems in China. The on-road black carbon and particle number emission factors for Chinese vehicles are reported for the first time in the literature. Strong traffic impacts can be observed from the concentrations measured in these different environments. Most clear is a reflection of diesel truck traffic activity in black carbon concentrations. The comparison of the particle size distributions measured at the three environments suggests that the traffic is a major source of ultrafine particles. A four-day traffic control experiment conducted by the Beijing Government as a pilot to test the effectiveness of proposed controls was found to be effective in reducing extreme concentrations that occurred at both on-road and ambient environments. [Copyright &y& Elsevier]

As one of the methods of urban environmental assessment, sensitivity assessment of urban climatic environment can accurately reflect the problem areas of current urban climate and built environment through visual means, and help cities to carry out sustainable transformation and renewal in the stock era to optimize the living environment. Taking the central urban area of Beijing as the research object, the sensitivity of climatic environment was evaluated by meteorological data and built environment element data. The results showed that the distribution of sensitive units showed a centrifugal radiation pattern of "high in the center and low in the periphery". Block units with high climate sensitivity were mostly concentrated in Xicheng District and Dongcheng District, accounting for 93% of the total number of units. Further research showed that complex built environment and lack of elements to regulate climatic environment were the main reasons for the poor local climatic environment in the region with high climate sensitivity. Finally, a comprehensive evaluation of the remolding capacity, renewal potential and future development intensity of different grades of climate sensitive units was given. The results will provide scientific reference for urban renewal and reconstruction under climatic and environmental changes, so as to promote urban sustainable development and improvement of living environment. [ABSTRACT FROM AUTHOR]

The risk of urban waterlogging is increasing with global climate change and rapid urbanization, especially for urban agglomeration like Beijing-Tianjin-Hebei (BTH) region. In this study, we obtain the urban waterlogging risk index of the BTH urban agglomeration and considering the hazard, exposure, and vulnerability factors, we assess waterlogging risks in the built-up area of the BTH for two periods (1961–1990 and 1991–2019). We analyze the economic and social data as well as the climate data from 149 meteorological observation stations in Beijing, Tianjin, and Hebei provinces. The results showed that for the two considered periods, the area with the lowest (level 1) waterlogging risk has decreased by nearly 50%, and the second-lowest (level 2) ones have increased by nearly 55%. Although the area higher risk has decreased by 17%, the difference among each city is quite large. Among them, the areas at level 3 have increased by 52% and 51% in Beijing and Handan, respectively. During the years 1991–2019, the areas with risks of level 3 and above are mainly found in Beijing, Tianjin, Shijiazhuang, Qinhuangdao, Handan, and Xingtai. Among them, Beijing has the highest waterlogging risk. In particular, the areas with risk of level 3 and above have increased by 76% in the past 30 years. The areas with the highest risk level (level 4) of waterlogging in Beijing were mostly found in the downtown areas (Haidian, Chaoyang, Dongcheng, and Xicheng districts). This study provides a scientific background for urban waterlogging risk management and implementation of the national and regional strategy for the development of the BTH region. [ABSTRACT FROM AUTHOR]

Beijing has long sought to shape global narratives about China. The Xi Jinping administration not only continued that effort but also added an entirely new dimension: it now seeks to use discourse power, particularly through formulating and promoting strategic narratives, to reshape the international system itself. Drawing upon social identity theory (SIT) and strategic narratives framework, this study shows that Beijing employs a multifaceted narrative strategy to redefine existing norms or create new ones in varied global governance domains. A theoretical framework is presented to explain the strategy and subsequently applied to illustrate China's strategic narratives at the international system level and in three global governance areas, i.e., climate change, human rights, and Internet governance. [ABSTRACT FROM AUTHOR]

In the acceleration of industrialization and urbanization, brownfield is an important resource for land regeneration and restoration targeting to recover its ecosystem function. Landfills, as a type of brownfield distributed in the highly populated areas, occupy massive land resources. The ecological restoration of landfills becomes an engineering approach to achieve multiple effects of society, environment, and economy. This paper aims to monitor and assess the restoration microclimatic effects of landfills restoration in China with remote sensing data and techniques. We selected representative landfill restoration projects, including Nanhaizi Park in Beijing, Nanhu Park in Tangshan, and Tianziling Park in Hangzhou, as the study cases. Using the Landsat imagery, the scenes of the pre-restoration, mid-restoration, and post-restoration were retrieved, and the surface energy balance equation was applied to calculate normalized difference vegetation index (NDVI), land surface temperature (T s), and evapotranspiration (ET), representing vegetation conditions and hydro-heat microclimate conditions. The study areas are divided into four subzones and extracted the calculated values for statistics and comparison. We defined an indicator of restoration intensity (RI) using the different subzones to the outer contour distance radius and restoration phases to evaluate the spatial-temporal restoration degrees. The spatial pattern dynamics was displayed in the urbanization context in the cases of Beijing and Tangshan. We examined and quantified the relations between RI and the key indicators, NDVI, T s , and ET. The overall results revealed that with higher restoration intensity, NDVI and ET became higher, and T s became lower. It suggested that the ecological restoration on the landfills brought better vegetation, cooling, and humidification effects for the microclimatic environment. Our research has the implications for monitoring and assessing the climatic effects of ecological restoration in the brownfield regeneration in a macroscopic and ecosystem perspective. Unlabelled Image • With satellite dataset, we developed a way to monitor vegetation and microclimatic changes in the restored landfills. • The indicator to quantify the ecological restoration intensity was invented with spatial distance and restoration phase. • Overall, with higher restoration intensity, vegetation and evapotranspiration improved, and surface temperature declined. [ABSTRACT FROM AUTHOR]

The impacts of climate change and human activities are challenging water sustainability in many cities around the world. Advanced understanding of the future long‐term coevolution of coupled urban human‐water systems is of considerable interest in this context. This study uses a previously developed sociohydrologic model to explore the coevolutionary trajectories of Beijing City's human‐water system over the 2015–2099 period under possible climate changes. The effects of multiple human adaptive actions under alternative climate scenarios are investigated in particular. Results show that there might be a recurrent competition for water between humans and the natural environment (e.g., groundwater aquifer) in the long‐term future, indicating that effective water management needs to ensure that this competition remains within a safe operating space. Three regimes of the human‐environment competition are revealed, including a sustainable development regime in which human society and groundwater aquifer are both safe throughout their coevolutionary trajectories, a regime that may lead to severe population loss due to overaggressive population control actions, and a regime that may cause aquifer depletion due to under‐perception of the drawdown of groundwater table. Results also show that relying too much on interbasin water diversion project might slacken human water conservation measures and eventually cause more severe aquifer depletion in the long run. Maintaining a high community sensitivity to drawdown of groundwater table and moderate measures to control population growth are keys to avoid unintended, negative consequences. Key Points: Three possible regimes of human‐environment competition for water depending on human adaptive actions are revealedActively transferring water from outside might unintendedly cause more severe aquifer depletion in the long runMaintaining a high community sensitivity to changes in groundwater depth is the key to avoid unintended negative consequences [ABSTRACT FROM AUTHOR]

Abstract: This paper is to highlight the threatening of climate change on the water shortage problem in North China, a semi-arid and arid area. Observations show that the runoff of the major rivers is decreasing dramatically especially in the lower reaches where water ishighly demanded. Most noticeable are the dry-outs of the Yellow River, the so-called ‘mother river of China’.Water scarcity would be the most front challenge for the society and economy in China, especially the urban area with extremely high population density. The government already paid attention to the deepening of the underground water level at Beijing. Sustainable water resource management should the top priority for the local community to adapt to climate change. Studies show that human activities heavily impact on the local climate and environment in China and a dramatics amount of clean water is wasted or polluted. [Copyright &y& Elsevier]

Climate change action requires both adaptation and mitigation. Both need urban planning in strategic and statutory processes to mainstream the innovations now appearing. Integrating adaptation and mitigation is demonstrated using two planning tools: water sensitive urban design and biophilic urbanism and both need to be mainstreamed through urban planning in a rapidly warming world. Mitigation must be about grasping the need for decoupling fossil fuel use from GDP and data indicates this is underway. Cities like Shanghai and Beijing are showing how emerging cities can decouple wealth and car use. Disruptive innovations underway are solar and wind power, batteries, and electrifying transport but need planning tools to mainstream them. Emerging disruptive innovations include Trackless Trams that function like light rail but at significantly less cost and Hydrogen in fuel-cell vehicles for heavy transport and as an industrial fuel. The Theory of Urban Fabrics is used to show how emerging innovations can be mainstreamed in urban planning through each of the different fabrics of the city. This is illustrated using the six tools outlined in this paper to demonstrate how such nuanced and integrated urban planning responses to climate change can be mainstreamed. • Adaptation to climate change can be integrated into city and regional planning as illustrated in Perth's water sensitive urban design and Singapore's biophilic urban design. • Mitigation needs cities to demonstrate the decoupling of greenhouse emissions from wealth generation. This requires structural efficiencies that are mainstreamed through urban planning. • Disruptive innovation is also critical to mitigation being achieved rapidly and can now be seen in power and transport through solar, wind, batteries and electric vehicles, with potential disruptive innovations such as Trackless Trams and Hydrogen. • The Theory of Urban Fabrics can enable city planning to mainstream all of the above innovations by focusing different planning strategies in different parts of cities and their regions. [ABSTRACT FROM AUTHOR]