Beijing-Tianjin-Hebei Area Research Articles

A Risk Assessment of the Vegetation Ecological Degradation in Hunshandake Sandy Land, China: A Case Study of Dabusennur Watershed

In the context of climate change, it is essential for sustainable development to assess the risks associated with climate change and human-induced vegetation degradation. The Hunshandake Sandy Land provides a variety of ecosystem services and is a substantial ecological security barrier in the Beijing–Tianjin–Hebei area of China. This study used the Normalized Difference Vegetation Index (NDVI) to analyze the spatiotemporal variation trend in vegetation in the Dabusennur Watershed using linear trend analysis and the GeoDetector model to identify the main drivers of vegetation change in the watershed. Finally, the study assessed the risk of ecological degradation in the vegetation of the watershed. The results show that the NDVI in the study area has had a fluctuating trend in the last 22 years, and the change has been small. Precipitation and groundwater depth are the key factors affecting vegetation change. The NDVI reaches its maximum value when the groundwater depth is at 2.75 m. The vegetation ecology of the basin is relatively fragile, mainly with medium risk and large risk. To cope with the ecological risk of vegetation degradation caused by climate change, appropriate water use strategies should be formulated to ensure ecological water use. The present study’s outcomes provide the basis for developing ecological engineering solutions in the arid and semi-arid parts of northern China.

Elucidating transport dynamics and regional division of PM2.5 and O3 in China using an advanced network model

Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.

Coking exhaust contributes to airborne particulate matter in the Beijing–Tianjin–Hebei region

Coking was regarded as a predominant source of air pollution. Despite the adoption of more environmentally friendly equipment, whether the coking enterprises in the Beijing–Tianjin–Hebei (BTH) region are still causing regional air pollution is worthy of study, which is essential for the control of coking enterprises in this area. To improve the prediction accuracy of large-scale air pollutant distribution, the air particle distribution in the BTH region was simulated via land use regression (LUR) combined with Bayesian maximum entropy (BME); then, the distribution was correlated with the exhaust gas emitted from coking enterprises. Results indicated that the R2 of the “LUR + BME” method reached 0.95, higher than 0.82 using LUR alone. The air quality distribution presented a pattern of “low in the northern mountains and high in the southern plains”, similar to the distribution of coking enterprises in BTH region. A significant correlation was found between exhaust emissions from coking enterprises and air quality in the BTH region, confirming the contribution of coking emissions to air pollution in this region, and the necessity to continue the strict control on coking enterprises in BTH area.

Air quality and heath co-benefits of low carbon transition policies in electricity system: the case of Beijing–Tianjin–Hebei region

Low carbon transition strategies of power plants are crucial to meet China’s ‘Dual Carbon’ targets. While the Beijing–Tianjin–Hebei (BTH) region, the ‘capital economic circles’ of China, is suffering from serious air pollution, air quality co-benefits of low carbon transition policies in electricity system in BTH area remain unclear. Here, we estimate the impacts of low carbon transition policies, including one BAU, six single and five combined scenarios, in electricity system in BTH area on installed power capacity, CO2 emissions, air quality and human health through 2060 based on open source energy modeling system and extend response surface model ERSM models. Results show that the total installed capacity under single and combined scenarios (except RE and Tech single scenarios) fluctuates around the BAU level of 310.5 GW in 2060. While all single and combined scenarios would generally achieve ‘carbon peak’ in BTH electricity system before 2030, only S4 (combining technological progress, renewable energy development and CCUS) and S5 (in additional to S4, including gas-fired power generation instead of coal-fired power generation) scenarios have the potential to realize carbon neutrality by 2060. The magnitude of reductions in air pollutant emissions and improvement in air quality in BTH area from the BAU level in 2060 under combined scenarios, especially S4 and S5, generally exceed that of six single scenarios. Importantly, S5 in 2060 contributes to about 8528 avoided premature mortalities in BTH area, which are more effective than any other scenarios. The results suggest that S5 is a promising low carbon transition policy to achieve environmental improvement and produce health benefits.

Locally opposite responses of the 2023 Beijing–Tianjin–Hebei extreme rainfall event to global anthropogenic warming

The effect of anthropogenic warming on extreme rainfall events is a hot topic in this era of global warming, and increasing attention is being paid to its impact at regional and local scales. We explore the localized response of precipitation during the high-impact “23·7” extreme rainfall event in the Beijing–Tianjin–Hebei region under anthropogenic warming using ensemble convective-permitting simulations. We identify two sub-regions with opposite responses: anthropogenic warming decreased (increased) precipitation in the northern (southern) sub-region of the Beijing–Tianjin–Hebei area. Further analysis shows that anthropogenic warming intensified the remnant of Typhoon Dusuari and increased rainfall in its inner core but decreased rainfall in the peripheral spiral rain band. These are the main reasons for the locally inconsistent responses of extreme rainfall to anthropogenic warming. We emphasize that anthropogenic warming, as a global background signal, directly affects the intensity and structure of specific weather systems rather than local precipitation. A high-impact extreme rainfall event, therefore, cannot always be simply attributed to climate warming enhancing precipitation at every location in a particular region.

Evaluation of the Spatiotemporal Change of Ecological Quality under the Context of Urban Expansion—A Case Study of Typical Urban Agglomerations in China

As a significant manifestation of human activities influencing natural environment, rapid urbanization has enhanced economic prosperity while simultaneously posing threats to ecological quality. Beijing–Tianjin–Hebei (BTH), the core region of the Yangtze River Delta (CYRD), and the Pearl River Delta (PRD) stand as three major economic centers characterized by the highest level of urbanization in China, encompassing areas of heightened ecological sensitivity. Nevertheless, the ecological quality at the scale of urban agglomerations remains ambiguous, with many studies failing to develop a comprehensive and effective method for comparing diverse urban agglomerations. Consequently, this study integrates multi-source remote sensing data, including information on land cover and other socio-economic parameters, to construct the Ecological Quality Index (EQI) based on the “Function–Interaction–Pressure–Stability” (FIPS) framework. Through a stratified determination of indicator weights grounded in both objective importance and empirical knowledge, we mapped the spatiotemporal changes of EQI and analyzed the impact of urbanization on ecological quality in three urban agglomerations from 2001 to 2020. We determined the following: (1) The calculated EQI can further capture the nuanced details with better performance at both underlining the discrepancy of highs and lows of EQI and describing the spatial detail of urban agglomerations’ characteristics. (2) Substantial disparities in EQI and its changes are evident across different urban agglomerations. Notably, only the average EQI improves in PRD, while ecological degradation is prominent in specific regions, such as the southeastern plains of BTH area, along the Yangtze River, and around Shanghai in CYRD and central PRD. The CYRD exhibits the largest affected area. (3) Urbanization predominantly influences ecological quality through land cover transitions. In expansion areas, ecological deterioration is significantly more pronounced, constituting approximately 90% of the total area. (4) Despite significant urbanization, city-level analysis in CYRD reveals a better coordination between urban expansion and ecological protection, with a lower intensity of ecological degradation compared to urban expansion rates. Conversely, some cities in the BTH, despite modest urban expansion, exhibit substantial declines in ecological quality, highlighting the need for targeted policy interventions. In conclusion, this study elucidates the intricate relationship between urbanization and ecological quality, offering valuable insights for the development of targeted protection strategies and sustainable urban planning.

Land Subsidence Prediction and Analysis along Typical High-Speed Railways in the Beijing–Tianjin–Hebei Plain Area

High-speed railways in the Beijing–Tianjin–Hebei (BTH) Plain are gradually becoming more widespread, covering a greater area. The operational safety of high-speed railways is influenced by the continuous development of land subsidence. It is necessary to predict the subsidence along the high-speed railways; thus, this work is of critical importance to the safety of high-speed railway operation. In this study, we processed Sentinel-1A data using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the land subsidence in the typical BTH area. Then, we combined the Empirical Mode Decomposition (EMD) and Gradient Boosting Decision Tree (GBDT) methods (EMD-GBDT) to forecast land subsidence along high-speed railways. The results revealed that some parts of the high-speed railways in the BTH plain had passed through or approached the land subsidence area; the maximum cumulative subsidence of the Beijing–Shanghai, Tianjin–Baoding and Shijiazhuang–Jinan high-speed railways reached 326 mm, 384 mm and 350 mm, respectively. The forecasting accuracy for land subsidence along high-speed railways was enhanced by the EMD-GBDT model. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.38 mm to 0.56 mm and 0.23 mm to 0.38 mm, respectively.

Assessing the Impact of a Regional Integration Policy on Corporate Environmental Performance: Micro-Evidence from Chinese Industrial Firms

Environmental performance is extremely vital for sustainable growth in China, and the impact of a regional integration policy plays an important role in improving environmental performance. However, current studies are weak in causal inference, and firm-level evidence is lacking. As a result, taking the Outline of the Pearl River Delta Reform and Development Plan as a quasi-natural experiment, with propensity score matching and difference-in-differences methods, this paper investigates the effect of regional integration on firms’ environmental performance. Our empirical results show that regional integration can significantly improve corporate environmental performance; specifically, the regional integration will result in an increase in the output value, of 46.7%, 22.3%, and 68.1% per unit emission of sulfur dioxide (SO2), industrial wastewater (WATER), and industrial smoke and dust (SD). Moreover, the impact of regional integration differs across different industries. For SO2, the impact of regional integration is greater for the petroleum processing, coking and nuclear fuel processing industries, and special equipment manufacturing; in terms of WATER, the impact is much higher in the tobacco products industry and printing and the reproduction of recording media industry; for SD, the petroleum processing, coking, and nuclear fuel processing industries are highly impacted. Finally, this impact also differs for core and peripheral cities. For policy implications, first, regional integration policies are highly recommended, and China is implementing regional integration in the Beijing–Tianjin–Hebei area and Yangtze River Delta, and these policies should be enhanced for other areas. Second, to maximize the effect of regional integration, the government needs to combine regional industrial structural characteristics to formulate industrial and environmental policies.

Impacts of the clean residential combustion policies on environment and health in the Beijing–Tianjin–Hebei area

The Chinese government has implemented a series of air pollution control measures in the residential combustion sector, especially in the Beijing–Tianjin–Hebei (BTH) area. The government launched the Three-year Action Plan for Winning the Blue Sky War in 2018. Cutting down the coal combustions in the residential sector has been highly addressed. To compare the environmental and health impacts, we set two scenarios: implementing the residential coal-switch policy and excluding the policy, through an integrated evaluation framework consisting of the GAINS IV Asia model and the IMED/HEL model. Results show that compared with the 2030 Baseline, emission of NOx, SO2, and PM2.5 in BTH would decline by 49.7 kt (3.8%), 216.2 kt (20.6%), and 199 kt (25.7%), respectively. Meanwhile, it leads to reductions of PM2.5 concentrations by 9.8 μg/m³ (19.9%), 3.1 μg/m³ (6.4%), 5.0 μg/m³ (10.7%) in Beijing, Tianjin, and Hebei, respectively. However, PM2.5 concentration in BTH would still exceed the World Health Organization Interim Target-1 of 35 μg/m3 by 2030. Carrying out the residential coal-switch policy can avoid 0.78 million morbidities (15.2%) and 0.01 million mortalities (5.6%) in BTH by 2030 compared to Baseline. Further, work time loss would decrease by 15.1% in 2030. The value of statistical life (VSL) of 9.58 billion USD (12.4%), 2.23 billion USD (3.8%), and 12.48 billion USD (6.6%) would be saved for Beijing, Tianjin, and Hebei by 2030. Regions with heavy pollution have benefited more from the clean residential combustion strategies and Hebei would account for 50.8%–62.3% of the total avoided health benefits in 2030. The benefit-cost ratio in Beijing is much higher than that in other regions. Implementing the residential coal-switch policies poses remarkable co-benefits on human health and the economy. This research lays a foundation for future environmental and health risks in other Chinese cities.

Multi-Scale Spatiotemporal Variations and Drivers of PM2.5 in Beijing-Tianjin-Hebei from 2015 to 2020

Understanding the spatiotemporal heterogeneity and complex drivers of PM2.5 concentration variations has important scientific value for sustainable urban development. Taking Beijing-Tianjin-Hebei (BTH) as the research area, and using spatial analysis techniques and wavelet methods to explore the spatiotemporal heterogeneity of variations in PM2.5 concentrations, the research shows that in the past six years (2015–2020), the PM2.5 concentrations in the BTH area have a downward trend, and the mean is 59.41 μg/m3; however, the distribution pattern of PM2.5 pollution has changed very little, and the concentration in the south and southwest is still generally high. The continuous wavelet transform revealed that the PM2.5 concentrations in the study area have a short period of about a week to a half a month and a long period dominated by annual cycle. The effect of a single meteorological factor on PM2.5 concentrations is weak, but this effect has obvious spatial differentiation characteristics from coastal to inland and has a double-sided effect due to different geographical locations. The wavelet transform coherence revealed that dewpoint temperature at 2 m (TED), meridional wind at 10 m (WV) and air temperature at 2 m (TEM) are important single meteorological factors that affect the variation of PM2.5 concentrations. The multiple wavelet coherence reveals that in scenarios where two meteorological factors are combined, the combination of TED-mean wind speed (WS) is the best combination to explain the variation in PM2.5 concentrations (AWC = 0.77, PASC = 41%). In the combination of three meteorological factors, TEM-WV-WS explained the variations of PM2.5 concentrations in the BTH region to the greatest degree (AWC = 0.89, PASC = 45%). Finally, the research shows that the variations of PM2.5 concentrations in the BTH region can be better explained by a combination of 2–3 meteorological factors, among which temperature and wind are the key meteorological factors. This research will provide a new window for the multi-scale variation characteristics and multi-factor control relationship of PM2.5 concentrations in the BTH region and provide a new insight for the prevention and control of air pollution.

Characteristics of wintertime carbonaceous aerosols in two typical cities in Beijing-Tianjin-Hebei region, China: Insights from multiyear measurements

In order to investigate the impact of “Blue Sky War” implemented during 2018–2020 on carbonaceous aerosols in Beijing-Tianjin-Hebei (BTH) region, China, fine particulate matter (PM2.5) samples were collected simultaneously in Tianjin and Handan in three consecutive winters from 2018 to 2020. Organic carbon (OC) and elemental carbon (EC) in PM2.5 were measured with the same thermal-optical methods and analysis protocols. Significant reductions in primary organic carbon (POC) and EC concentrations were observed both in Tianjin and Handan, with decreasing rates of 0.65 and 2.95 μg m−3 yr−1 for POC and 0.13 and 0.64 μg m−3 yr−1 for EC, respectively. The measured absorption coefficients of EC (babs, EC) also decreased year by year, with a decreasing rate of 1.82 and 6.16 Mm−1 yr−1 in Tianjin and Handan, respectively. The estimated secondary organic carbon (SOC) concentrations decreased first and then increased in both Tianjin and Handan, accounting for more than half of the total OC in winter of 2020–2021 and with increasing contributions especially in highly polluted days. SOC was recognized as one of key factors influencing EC light absorption. EC in the two cities was relatively more related to coal combustion and industrial sources. The reductions of primary carbonaceous components may be attributed to the air quality regulations targeting coal combustion and industrial sources emissions in BTH area. Potential source contribution function (PSCF) analysis results indicated that the major source areas of OC and EC in Tianjin were the southwest region of the sampling site, while the southeast areas for Handan. These findings demonstrated the effectiveness of air quality regulation in primary emissions in typical polluted cities in BTH region and highlighted the needs for further control and in-depth investigation of SOC formation along with implementation of air pollution control act in the future.

Addressing External Shock in Urban Agglomeration: Implications From the Transmission Pattern of COVID-19 in the Beijing-Tianjin-Hebei Area.

Properly addressing external shocks in urban agglomeration is critical to sustaining the complex regional system. The COVID-19 pandemic has been widely acknowledged as an unintended external shock, but the temporal and spatial transmission patterns are largely ignored. This study analyzed the temporal and spatial transmission patterns of COVID-19 at the macro, meso, and micro levels, and proposes a conceptual model for regional comprehensive risk calculation, taking the Beijing-Tianjin-Hebei (BTH) area as the focus region. Our results showed that 1) at the temporal scale, the epidemic in the BTH area experienced stages of rapid increase, gradual decrease, and stabilization, and the first wave of the epidemic was under control from 23 February 2020; 2) at the spatial scale, confirmed cases were largely distributed at the terminal of the migration network, with closely interconnected cities in the BTH area, including Beijing, Tianjin, Tangshan, and Langfang, holding the highest comprehensive epidemic risk, thus requiring special attention for epidemic prevention and control. Finally, a “two-wheels” conceptual framework was built to discuss implications for future policies for addressing external shocks. Our proposed framework consists of an isolation wheel, which involves information sharing from the holistic perspective, and a circulation wheel, which emphasizes stakeholder involvement from the individual perspective. The findings of this study provide a knowledge basis for epidemic prevention and control as well as useful implications for addressing external shocks in the future.

Research on the impact of Beijing–Tianjin–Hebei electric power and thermal power industry on haze pollution

As one of the main reasons of haze pollution in Beijing–Tianjin–Hebei area, electric-power and thermal-power industry continues to increase its production scale and total energy consumption, which makes haze pollution in Beijing–Tianjin–Hebei area increasingly serious. Based on the exploration of the spatio-temporal variance map of electric-power and thermal-power industry in Beijing–Tianjin–Hebei area, the article selects pand data of 13 cities in Beijing–Tianjin–Hebei area from 2006–2019 and empirically tests the spatial effect of electric-power and thermal-power industry on haze pollution by using the measures of spatial autoregressive model (SAR) and spatial Durbin model (SDM). It was found that in the Beijing–Tianjin–Hebei area, the electric-power and thermal-power industry converges to Beijing, Tangshan and Tianjin, where high demand exists. The electric-power and thermal-power industry shows an overall trend of shifting to the east coast and south inland. Through SDM, it is found that the electric-power and thermal-power industry is an crucial source of haze pollution and has a significant spatial spillover effect. In response to the above phenomenon, it is suggested to improve the haze pollution in Beijing–Tianjin–Hebei area scientifically by improving the supply and distribution system, scientifically deploying power supply, scientifically planning the development of electric-power and thermal-power industry according to the environmental self-purification capacity, and scientifically improving technological innovation.

Study of the Effect of Vegetation on Reducing Atmospheric Pollution Particles

Atmospheric particulate matter (PM) is a major air pollutant. PM2.5 and PM10 pose particularly serious threats to the ecological environment and human health. Vegetation plays an important role in reducing the concentration of particles. Based on a long time series of air quality, meteorological, and vegetation coverage data in the Beijing–Tianjin–Hebei (BTH) region, the present paper evaluated the influence at the overall and built-up area scales and quantified the process involved in the dry settlement of particles on vegetation based on a mathematical model. The experimental results showed that (1) the total amounts of PM10 reduced by vegetation in the BTH area were 505,200 t, 465,500 t, 477,200 t and 396,500 t in 2015, 2016, 2017 and 2018, respectively, and the total amount of PM2.5 was reduced by 19,400 t, 19,200 t, 16,400 t and 12,700 t, respectively. The annual reduction in PM10 and PM2.5 from 2015 to 2018 by vegetation in the BTH region showed a downwards trend, and the annual reduction was mainly caused by the significant decrease in PM concentration. (2) More than 80% of the reduction in annual yield was concentrated in May–September, and a large leaf area was the main reason for the largest yield reduction in the growing season. The efficiency of PM reduction in forestland was approximately five–seven times that in grassland, and the deciduous broad-leaved forest was the main driver of this reduction in each forest. (3) The reduction in PM10 by vegetation was approximately 30 times that of PM2.5. However, the reduction in PM2.5 by vegetation should not be ignored because PM2.5 has a stronger correlation with human production and living activities. Increasing the area and density of green space via afforestation, returning farmland to forest and giving full play to the self-purification function of green spaces are very important to reducing and controlling the concentration of PM.

Understanding Urban Growth in Beijing-Tianjin-Hebei Region over the Past 100 Years Using Old Maps and Landsat Data

Studying urban expansion from a longer-term perspective is of great significance to obtain an in-depth understanding of the process of urbanization. Remote sensing data are mostly selected to investigate the long-term expansion of cities. In this study, we selected the world-class urban agglomeration of Beijing-Tianjin-Hebei (BTH) as the study area, and then discussed how to make full use of multi-source, multi-category, and multi-temporal spatial data (old maps and remote sensing images) to study long-term urbanization. Through this study, we addressed three questions: (1) How much has the urban area in BTH expanded in the past 100 years? (2) How did the urban area expand in the past century? (3) What factors or important historical events have changed the development of cities with different functions? By comprehensively using urban spatial data, such as old maps and remote sensing images, geo-referencing them, and extracting built-up area information, a long-term series of urban built-up areas in the BTH region can be obtained. Results show the following: (1) There was clear evidence of dramatic urban expansion in this area, and the total built-up area had increased by 55.585 times, from 126.181 km2 to 7013.832 km2. (2) Continuous outward expansion has always been the main trend, while the compactness of the built-up land within the city is constantly decreasing and the complexity of the city boundary is increasing. (3) Cities in BTH were mostly formed through the construction of city walls during the Ming and Qing dynasties, and the expansion process was mostly highly related to important political events, traffic development, and other factors. In summary, the BTH area, similarly to China and most regions of the world, has experienced rapid urbanization and the history of such ancient cities should be further preserved with the combined use of old maps.

A 3D study on the amplification of regional haze and particle growth by local emissions

The role of new particle formation (NPF) events and their contribution to haze formation through subsequent growth in polluted megacities is still controversial. To improve the understanding of the sources, meteorological conditions, and chemistry behind air pollution, we performed simultaneous measurements of aerosol composition and particle number size distributions at ground level and at 260 m in central Beijing, China, during a total of 4 months in 2015–2017. Our measurements show a pronounced decoupling of gas-to-particle conversion between the two heights, leading to different haze processes in terms of particle size distributions and chemical compositions. The development of haze was initiated by the growth of freshly formed particles at both heights, whereas the more severe haze at ground level was connected directly to local primary particles and gaseous precursors leading to higher particle growth rates. The particle growth creates a feedback loop, in which a further development of haze increases the atmospheric stability, which in turn strengthens the persisting apparent decoupling between the two heights and increases the severity of haze at ground level. Moreover, we complemented our field observations with model analyses, which suggest that the growth of NPF-originated particles accounted up to ∼60% of the accumulation mode particles in the Beijing–Tianjin–Hebei area during haze conditions. The results suggest that a reduction in anthropogenic gaseous precursors, suppressing particle growth, is a critical step for alleviating haze although the number concentration of freshly formed particles (3–40 nm) via NPF does not reduce after emission controls.

Establishment of Conceptual Schemas of Surface Synoptic Meteorological Situations Affecting Fine Particulate Pollution Across Eastern China in the Winter

AbstractIn the present study, the characteristics of weather conditions and local meteorological variables over the Beijing‐Tianjin‐Hebei (BTH) and the Yangtze River Delta (YRD) regions in the winter are analyzed using the principal component analysis (PCA) method and daily PM2.5 accumulation rate. Typical synoptic weather patterns over China in the winter can be classified into four types. During the Type 1 synoptic weather pattern, China is under the influence of the Siberian High, and northerly winds prevail; this situation is beneficial to the transport of pollutants from north to south. However, when the Siberian High is weak, southerly winds prevail which may result in the transport of pollutants from south to north. The Type 2 weather pattern refers to a weak high pressure located in the BTH resulting in the accumulation of pollutants. During the Type 3 weather pattern, an intense cold Siberian High moves to the south and affects the northern areas of China. The associated front brings heavy precipitation in the YRD resulting in the wet deposition of pollution. During the Type 4 weather condition, the weak Siberian High is blocked by the northeast cold vortex and moves towards the south, causing the accumulation of pollution in the YRD. The PCA model shows that there are two transport pathways for pollutants to the BTH (YRD) area: one from the YRD (BTH) and Shandong during Types 1 and 2 (Types 1 and 3) situations and the other one from the central provinces during Type 4 (Types 1 and 4).

Assessment of mortality burden and economic loss attributed to long-term PM(2.5) exposure in the Beijing-Tianjin-Hebei area

Objective: To accurately estimate the health burden and corresponding economic loss attributed to PM(2.5) pollution in the Beijing-Tianjin-Hebei (BTH) area in China in 2015. Method: By using satellite-retrieved PM(2.5) concentration data and population data provided by NASA (the spatial resolution was 1 km×1 km), this study estimated excess mortality attributed to long-term PM(2).5 exposure in BTH area in 2015 based on Global Exposure Mortality Model (GEMM). Besides, Value of Statistic Life (VSL) method was used to evaluate the corresponding health economic loss. Result: In BTH area, the population-weighted average PM(2.5) concentration during 2012-2014 was 46.25 μg/m(3), and 56.6% of total population lived in the area where annual average PM(2.5) concentration exceeded Grade Ⅱ of National Ambient Air Quality Standard in China (35 μg/m(3)); The PM(2.5)-related premature deaths amounted to 193.8 thousand (95%CI: 140.9 thousand-233.3 thousand), Beijing, Tianjin, Baoding, Shijiazhuang, and Handan were the top five cities with high incidences of PM(2.5)-related premature deaths; The corresponding health economic loss was about 35.934 billion (95%CI: 26.099 billion - 43.255 billion) RMB, accounting for 0.70% (95%CI: 0.51%-0.85%) of the area's GDP in 2015, Beijing, Tianjin, Baoding, Shijiazhuang, and Cangzhou were the top five cities with high health economic loss. Conclusions: PM(2.5) pollution has caused severe disease and economic burden in BTH area. Its spatial distribution suggested that it is particularly necessary to develop the air pollution prevention and control policies for key cities.

A Geomorphological Regionalization using the Upscaled DEM: the Beijing-Tianjin-Hebei Area, China Case Study

Characterizing geomorphological patterns based on digital elevation models (DEMs) has become a basic focus of current geomorphology. A new DEM upscaling method based on the high-accuracy surface modelling method (HASM-US method) has been developed to improve the accuracy of current models and the subjectivity of macroscopic geomorphological patterns. The topographic variables of elevation (EL), slope (SL), aspect (AS), relief amplitude (RA), surface incision (SI), surface roughness (SR), and profile curvature (PC) with a spatial resolution of 1 km × 1 km in the Beijing-Tianjin-Hebei (BTH) area of China have been obtained by using the HASM-US method combined with the principal component analysis (PCA) method in terms of the elevation data of the SRTM-4 DEM, meteorological station location information, and field measurements with a GPS receiver. A geomorphological regionalization pattern has been developed to quantitatively classify the geomorphological types in the BTH area by combining the seven topographic factors of EL, SL, AS, RA, SI, SR, and PC that have significant spatial variation. The results show that the upscaling accuracy of elevation (mean difference only −2.32 m) with the HASM-US method is higher than that with the bilinear interpolation method and nearest neighbour interpolation method. The geomorphologic distribution in the BTH area includes 11 types: low plain, low tableland, low hill, low basin, middle plain, middle hill, low mountain with low RA values, low mountain with medium RA values, middle mountain with low RA values, middle mountain with medium RA values, and middle mountain with high RA values. The low plain is the dominant geomorphological type that covers 40.58% of the whole BTH area. The geomorphological distribution shows the different significant characteristics: the elevation rapidly decreases from the Taihang Mountains to the eastern area, gradually decreases from the Yanshan Mountains to the southern area, and first increases and then decreases from the Bashang Plateau to the southeastern area in the whole BTH area.

Spatial Differentiation of Land Use and Landscape Pattern Changes in the Beijing–Tianjin–Hebei Area

Landscape pattern analysis based on geometric features effectively reflects the spatial patterns of land use. Based on the administrative boundaries of prefecture-level cities, the Beijing–Tianjin–Hebei collaborative development area is divided into three sub-regions, according to ecological–production–living functions. We used remote sensing data of long time series land-use change from late 1980 to 2015, and analyzed landscape pattern changes and spatial differentiation in the past 30 years. The results show that: (1) The main type of land-use change was the flow of cultivated land to urban construction land, and the urbanization process was significant. (2) The urban construction land was the landscape type with the highest degree of fragmentation and maximum land-use change in the region. (3) The patch density in the Beijing–Tianjin–Hebei area increased while the average patch area decreased, and the entire landscape tended towards significant fragmentation. The Shannon diversity and evenness indexes continued to increase, indicating that the overall landscape in this region is heterogeneous and diversified. The ecological and environmental protection measures implemented in this region so far have achieved results, but require more stringent measures to ensure the total diversification of land use in the region.