Does Industrial Transfer Change the Spatial Structure of CO2 Emissions?—Evidence from Beijing-Tianjin-Hebei Region in China

As an important cause of global warming, CO2 emissions have become a research hotspot in recent years. Industrial transfer impacts regional CO2 emissions and is related to the low-carbon development of regional industries. Taking the Beijing-Tianjin-Hebei region (BTH region) as an example, this study analysed industrial transfer’s direct and indirect impacts on CO2 emissions based on a mediating model and two-way fixed effect panel regression. The results obtained indicate that industrial transfer-in has promoted CO2 emissions to a small extent, and the positive impact of industrial transfer-in on CO2 emissions wanes over time. Industrial transfer affects CO2 emissions by acting on the economic level, on population size, and on urbanisation level, but the indirect effect is weaker than the direct effect. Industrial transfer does not lead to technological upgrading, but the latter is an effective means of carbon emission reduction. Industrial transfer-in has shown a positive effect on CO2 emissions for most cities, but there are exceptions, such as Cangzhou. In the future, the BTH region should maintain coordinated development among cities and improve the cooperative innovation mechanism for energy conservation and emission reduction.

Does the “Blue Sky Defense War Policy” Paint the Sky Blue?—A Case Study of Beijing–Tianjin–Hebei Region, China

Improving air quality is an urgent task for the Beijing–Tianjin–Hebei (BTH) region in China. In 2018, utilizing 365 days’ daily concentration data of six air pollutants (including PM2.5, PM10, SO2, NO2, CO and O3) at 947 air quality grid monitoring points of 13 cities in the BTH region and controlling the meteorological factors, this paper takes the implementation of the Blue Sky Defense War (BSDW) policy as a quasi-natural experiment to examine the emission reduction effect of the policy in the BTH region by applying the difference-in-difference method. Results show that the policy leads to the significant reduction of the daily average concentration of PM2.5, PM10, SO2, O3 by −1.951 μg/m3, −3.872 μg/m3, −1.902 μg/m3, −7.882 μg/m3 and CO by −0.014 mg/m3, respectively. The results of the robustness test support the aforementioned conclusions. However, this paper finds that the concentration of NO2 increases significantly (1.865 μg/m3). In winter heating seasons, the concentration of SO2, CO and O3 decrease but PM2.5, PM10 and NO2 increase significantly. Besides, resource intensive cities, non-key environmental protection cities and cities in the north of the region have great potential for air pollutant emission reduction. Finally, policy suggestions are recommended; these include setting specific goals at the city level, incorporating more cities into the list of key environmental protection cities, refining the concrete indicators of domestic solid fuel, and encouraging and enforcing clean heating diffusion.

Impact of Water Rights Transaction in the Beijing-Tianjin-Hebei Region in China Based on an Improved Computable General Equilibrium Model

Water shortages in the Beijing-Tianjin-Hebei (BTH) region in China have constrained the region’s coordinated development. A feasible solution is introducing water rights transactions through the middle route of the South-to-North Water Diversion Project (SNWDP). However, there are few methods available for systematically simulating and evaluating the impact of inter-regional water rights transactions. In this study, an improved computable general equilibrium (CGE) model was developed to simulate the water rights transactions. Different water resources were integrated as intermediate inputs, and the model includes a substitution mechanism between different water resources. The water stress index (WSI) was used to evaluate the impact on the economy and water resources simulated by the model. The study proposes and evaluates different scenarios with different water-saving levels and transaction volumes. Water rights transactions have a positive effect on the overall economic growth of the BTH region, reducing the local water resource stress in Beijing and Tianjin; the transactions have a limited impact on the economy and water usage of Hebei Province. Compared with the general water-saving intensity scenario without water rights transactions, the recommended scenario adopts ultra water-saving intensity, along with the transfer of 100 hm3 of water rights from Hebei to Beijing and Tianjin. This leads to an increase in the overall gross domestic product (GDP) of the BTH region by CNY 0.587 trillion (USD 99.6 billion); a decrease in local water usage in Beijing and Tianjin of 197 hm3; and a relief in the regional imbalance of water resources stress. This study provides a quantitative analysis tool for evaluating the impact of water rights transactions and optimizing water resources allocations in the BTH region, providing a reference for simulating and evaluating water rights transactions in other regions.

Diurnal Variation and Distribution of Short-Duration Heavy Rainfall in Beijing–Tianjin–Hebei Region in Summer Based on High-Density Automatic Weather Station Data

The distribution and diurnal variation of short-duration heavy rainfall (SDHR) and the influence of a complex underlying surface were studied by using fine-scale hourly precipitation data in the Beijing–Tianjin–Hebei (BTH) region during the summers of 2014–2020. Areas prone to SDHR are located mainly in the southern foothills of the Yanshan Mountains, the foothills area, and the trumpet-shaped topographic entrance area north of Beijing, areas inland of the west coast of Bohai Bay, and the northern Beijing urban area. Owing to the influence of topography and the geographical location, the distribution and diurnal variation SDHR is significantly different in the western and northern mountainous areas, the foothills, and the plains. Compared to the underlying urban surface, the topography and the land–sea interface have considerable effects on the distribution of SDHR. A key finding is that the foothills of northern of Beijing, eastern slope and piedmont area of the Taihang Mountains, and the land–sea interface of Bohai Bay play important roles in the formation and propagation of SDHR.

A new inverse modeling approach for emission sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei region

We develop a new inversion method which is suitable for linear and nonlinear emission source (ES) modeling, based on the three-dimensional decoupled direct (DDM-3D) sensitivity analysis module in the Community Multiscale Air Quality (CMAQ) model and the three-dimensional variational (3DVAR) data assimilation technique. We established the explicit observation operator matrix between the ES and receptor concentrations and the background error covariance (BEC) matrix of the ES, which can reflect the impacts of uncertainties of the ES on assimilation. Then we constructed the inversion model of the ES by combining the sensitivity analysis with 3DVAR techniques. We performed the simulation experiment using the inversion model for a heavy haze case study in the Beijing–Tianjin–Hebei (BTH) region during 27–30 December 2016. Results show that the spatial distribution of sensitivities of SO2 and NOx ESs to their concentrations, as well as the BEC matrix of ES, is reasonable. Using an a posteriori inversed ES, underestimations of SO2 and NO2 during the heavy haze period are remarkably improved, especially for NO2. Spatial distributions of SO2 and NO2 concentrations simulated by the constrained ES were more accurate compared with an a priori ES in the BTH region. The temporal variations in regionally averaged SO2, NO2, and O3 modeled concentrations using an a posteriori inversed ES are consistent with in situ observations at 45 stations over the BTH region, and simulation errors decrease significantly. These results are of great significance for studies on the formation mechanism of heavy haze, the reduction of uncertainties of the ES and its dynamic updating, and the provision of accurate “virtual” emission inventories for air-quality forecasts and decision-making services for optimization control of air pollution.

Urban Sprawl and Changes in Land-Use Efficiency in the Beijing–Tianjin–Hebei Region, China from 2000 to 2020: A Spatiotemporal Analysis Using Earth Observation Data

Sustainable development in urban areas is at the core of the implementation of the UN 2030 Agenda and the Sustainable Development Goals (SDG). Analysis of SDG indicator 11.3.1—Land-use efficiency based on functional urban boundaries—provides a globally harmonized avenue for tracking changes in urban settlements in different areas. In this study, a methodology was developed to map built-up areas using time-series of Landsat imagery on the Google Earth Engine cloud platform. By fusing the mapping results with four available land-cover products—GlobeLand30, GHS-Built, GAIA and GLC_FCS-2020—a new built-up area product (BTH_BU) was generated for the Beijing–Tianjin–Hebei (BTH) region, China for the time period 2000–2020. Using the BTH_BU product, functional urban boundaries were created, and changes in the size of the urban areas and their form were analyzed for the 13 cities in the BTH region from 2000 to 2020. Finally, the spatiotemporal dynamics of SDG 11.3.1 indicators were analyzed for these cities. The results showed that the urban built-up area could be extracted effectively using the BTH_BU method, giving an overall accuracy and kappa coefficient of 0.93 and 0.85, respectively. The overall ratio of the land consumption rate to population growth rate (LCRPGR) in the BTH region fluctuated from 1.142 in 2000–2005 to 0.946 in 2005–2010, 2.232 in 2010–2015 and 1.538 in 2015–2020. Diverged changing trends of LCRPGR values in cities with different population sizes in the study area. Apart from the megacities of Beijing and Tianjin, after 2010, the LCRPGR values were greater than 2 in all the cities in the region. The cities classed as either small or very small had the highest LCRPGR values; however, some of these cities, such as Chengde and Hengshui, experienced population loss in 2005–2010. To mitigate the negative impacts of low-density sprawl on environment and resources, local decision makers should optimize the utilization of land resources and improve land-use efficiency in cities, especially in the small cities in the BTH region.

Spatiotemporal Changes of Land Ecological Security and Its Obstacle Indicators Diagnosis in the Beijing–Tianjin–Hebei Region

Land ecological security (LES) is a cornerstone of sustainable development, and the study of the LES evaluation has become a hot field in the LES problems. The coordinated development of the Beijing–Tianjin–Hebei (BTH) region is one of China’s national development strategies. With the development of urbanization and industrialization, the conflicts between people and land in this area are increasingly prominent, and there are large regional differences in land ecological quality. To evaluate the land ecological security (LES) of this region, an evaluation index system is constructed based on the pressure–state–response (PSR) framework model, and the entropy-weighted TOPSIS method is applied to calculate the LES index. Then, the spatio-temporal changes of LES in the BTH region from 2007 to 2018 are analyzed. In addition, we adopt an obstacle degree model to analyze the obstacle indicators. The results show that the LES of the BTH region increased from 0.1934 to 0.3284 during 2007–2018, and the LES level increased from the dangerous level (I) to the critical level (III). Despite the improved LES in all areas in the BTH region, there were different trends (high in the central area, relatively low in the northern and southern areas). We identified seven obstacle indicators and discussed different development strategies. Our findings will provide guidelines for land use management and offer references for the coordinated development of the BTH region.

A New Inverse Modeling Approach for Emission Sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei Region

We develop a new inversion method which is suitable for linear and nonlinear emission sources (ES) modeling, based on the three-dimensional decoupled direct (DDM-3D) sensitivity analysis module in the Community Multiscale Air Quality (CMAQ) model and the three-dimensional variational (3DVAR) data assimilation technique. We established the explicit observation operator matrix between the ES and receptor concentrations, and the background error covariance (BEC) matrix of the ES which can reflect the impacts of uncertainties of the ES on assimilation. Then we constructed the inversion model of the ES by combining the sensitivity analysis with 3DVAR techniques. We performed the simulation experiment using the inversion model for a heavy haze case study in the Beijing-Tianjin-Hebei (BTH) region during December 27–30, 2016. Results show that the spatial distribution of sensitivities of SO2 and NOX ES to their concentrations, as well as the BEC matrix of ES, are reasonable. Using the posteriori inversed ES, underestimations of SO2 and NO2 during the heavy haze period are remarkably improved, especially for NO2. Spatial distributions of SO2 and NO2 concentrations simulated by the constrained ES were more accurate compared with the priori ES in the BTH region. The temporal variations in regionally averaged SO2, NO2, and O3 modelled concentrations using the posteriori inversed ES are consistent with in-situ observations at 45 stations over the BTH region, and simulation errors decrease significantly. These results are of great significance for: studies on the formation mechanism of heavy haze; reducing uncertainties of ES and its dynamic updating; providing accurate “virtual” emission inventories for air-quality forecasts and decision-making services for optimization control of air pollution.