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China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fluid overpressure plays a key important role in the formation of skarn iron deposit. Skarn iron deposits are important resources for iron-rich ores and their genesis has been a topic of debate. The Nanminghe iron deposit is a typical skarn iron deposit in Wu'an, Hebei Province, China which provides a good example to investigate the metallogenic mechanism. In this paper, we present a detailed study of the geology, petrography, and geochemical characteristics of magnetite in the Nanminghe iron deposit. Two types of magnetite can be identified in the massive ores: Mag1 is euhedral with radial cracks developed in the margin. It is a low-Si magnetite, with SiO 2 content ranging from 0.07% to 0.92%, with an average value of 0.49%. The SiO 2 content of Mag2 is from 0.90% to 3.29%, and an average value of 2.03%. The Mag2 is associated with quartz, goethite, and apatite. Geochemical characteristics of Mag1, together with the ore textures suggest its crystallization from an iron magma. There are significant differences in the geochemical characteristics between Mag1 and Mag2. Mag2 is rich in Nb, Ta, high field strength elements, large ion lithophile elements and has higher silica content. The Nb/Ta of Mag2 is higher than that of the original mantle. These characteristics as well as La/Ta vs Th/La, Th/U vs Sm/Nd and Nb/Ta vs Nb features show that Mag2 is formed in the environment of supercritical fluids. The δ56Fe of Mag1 is 0.157‰-0.172‰, with an average value of 0.166‰, and the δ56Fe of Mag2 is 0.119‰-0.160‰, with an average value of 0.139‰. The Fe isotope of Mag2 is lighter than Mag1. There is a negative correlation between δ56Fe and SiO 2 of Mag1 and Mag2, suggesting that the lighter δ56Fe of Mag2 was caused by injection of Si-rich fluids. We propose a genetic model where we envisage that the iron-rich melt formed in the deep magma chamber by reaction of dioritic rocks and carbonates. Mag1 formed by cooling of the iron-rich magma, following which Si-rich supercritical fluid were injected into the deep chamber resulting in fluid overpressure. The iron-bearing melt-fluid migrated upward along the magmatic conduit, when Mag2 formed. Our study provides insights into the formation mechanism of skarn iron deposits. [ABSTRACT FROM AUTHOR]

[Display omitted] • In the case of a small number of known deposits and mineral occurrences, the prospecting prediction model based on the Siamese network can extract effective features without relying on prior knowledge to realize supervised prospecting prediction. • On the basis of sliding window data enhancement, this paper generates paired sample data sets by randomly combining deposit samples and non-deposit samples, which can further enhance the data and improve the generalization ability and prediction accuracy of the model to a certain extent. • Compared with the prediction results of the weight of evidence method and the convolutional neural network, the prediction results of the Siamese network are better, and 7 new gold prospecting areas have been discovered in Zhangjiakou, Hebei Province, China. Supervised neural networks constitute an important research area for the intelligent prediction of locations for prospecting mineral deposits. Accurate training of a supervised neural network requires many training samples, something that is often difficult to obtain. This paper reports the use of geological, geochemical, and geophysical data by a Siamese network to overcome the problem of insufficient training samples, and implements a supervised deep learning prospecting prediction method based on the Siamese network. Intelligent prediction for gold deposits prospecting is carried out for the Chongli mineral concentrate area in Zhangjiakou, Hebei Province, China, and compared with the weight of evidence method and convolutional neural network model. The results show that:(a) the performance of the Siamese network model is no less than that of the convolutional neural network (CNN) model and better than that of the weight of evidence (WOE) method; (b) the gold prospective areas differentiated by the established models are strongly consistent with geological and metallogenic characteristics in the study area. This study suggests Siamese network model as an effective mineral prospectivity modeling tool. This method is also suitable for prospecting prediction using geoscience data in other areas. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [ABSTRACT FROM AUTHOR]

[Display omitted] • The genesis of the Fenghuangshan gold deposit is considered to be magmatic-hydrothermal. • The Fenghuangshan gold deposit is related to the Paleo-Pacific plate subduction. • The study area is highly prospective for deep-seated gold mineralization. The Jidong area is a vital gold province in North China, including plenty of metamorphic rock-hosted gold deposits. Whether ore-forming fluids are magmatic or metamorphic remains controversial. The genesis for gold mineralization in this gold province is ambiguous. The Fenghuangshan gold deposit lies on the eastern fragment of the Jidong gold province. In this paper, we present a detailed study on ore geology, fluid inclusions, and stable isotopes for the deposit to illustrate the characteristics of ore-forming fluids and ore genesis. The deposit occurs as gold-bearing quartz vein and disseminated- and veinlet-type mineralization. The main orebody named 7# is hosted in migmatitic granite, controlled by NE trending secondary fracture system. Four hydrothermal mineralization stages were identified, including: (Ⅰ) white quartz, (II) pyrite-quartz, (III) quartz-polymetallic sulfide, and (IV) calcite-chlorite-quartz. The Stage II and III belong to main gold mineralization stage. Fluid inclusions from different stages show that a lowering trend of fluid inclusion homogenization temperature was observed. They ranged from 222 °C to 407 °C (early-stage), 144 °C to 375 °C (main-stage), and 86 °C to 174 °C (late-stage), respectively. The salinities of the ore-forming fluids were typically low, ranging from 0.83 to 15.47 wt% NaCl equivalent. On the basis of Laser Raman analysis and fluid inclusion microthermometry, the ore-forming fluids belonged to a low- to moderate-temperature, low-salinity H 2 O-NaCl-CO 2 system. Fluid immiscibility gave rise to rapid gold deposition. The early-stage δD and δ18O H2O values from quartzs ranged from –96.4‰ to –92.5‰ and from 1.74‰ to 2.44‰, whereas main-stage fluids had δ18O H2O values of –4.10‰ to –3.50‰ and δD values of –91.5‰ to –89.5‰. The early- and main-stage sulfide δ34S values varied from –2.0‰ to + 2.2‰, with average values of + 0.4‰. H-O-S-isotope data indicated that the primary ore-forming fluids were magmatic water mixing meteoric water during mineralization, and ore-forming materials were derived from a homogeneous magmatic source. Ore geology, fluid inclusions, and stable isotopes illustrate that the Fenghuangshan gold deposit is a low- to moderate-temperature magmatic-hydrothermal gold deposit. Future deep-seated and surrounding gold exploration should center on this area. [ABSTRACT FROM AUTHOR]

• Analyzed residents' thermal demand characteristics under the global climate change. • A new thermal comfort evaluation model of traditional dwellings was established. • The new thermal neutral temperature and comfort range of residents were proposed. • Different measures to improve the old and new types of dwellings were put forward. Global climate change has led to increased differences in the indoor thermal environment of traditional dwellings and residents' thermal adaptability, but quantitative research in this area needs to be updated and improved. In this paper, taking the old and new types of traditional dwellings of Guangfu Ancient City in Hebei province, China as the example, we first investigated the current situation of indoor thermal environment and thermal comfort characteristics of residents by means of subjective questionnaire survey and objective data measurement. The measured data showed that the average indoor temperature of old-type traditional dwellings in winter was far lower than the thermal comfort range of human body, and it was also higher than the relevant standard in summer. Secondly, we established a new thermal comfort evaluation model of traditional dwellings and proposed a new thermal neutral temperature of residents: old-type traditional dwellings (18.1 °C in winter and 27.1 °C in summer), new-type traditional dwellings (19.8 °C in winter and 25.7 °C in summer). Although the measured data showed that the thermal environment quality of the old-type traditional dwellings was poor, the residents had strong thermal adaptability. Finally, we put forward the different living performance improvement strategies of old and new types of traditional dwellings: The old-type traditional dwellings should focus on strengthening the thermal performance of the envelope structure, while the new-type traditional dwellings should solve the problem of low indoor humidity in winter. This research improves the evaluation system of human thermal comfort of dwellings in cold region of China, and provides a good case reference. [ABSTRACT FROM AUTHOR]

In this paper, heavy metals (i.e., V, Cr, Co, Cu, Zn, Cd, Pb, and Sb) in soils from a tannery waste lagoon, Hebei, north China were investigated. Element concentrates were determined by a portable X-ray fluorescence in situ and an inductively coupled plasma mass spectrometry in the lab. Two sets of indexes, including geological accumulation index, contamination factor, and pollution load index, and hazard quotient and total carcinogenic risk were adopted to evaluate the pollution and health-risk of heavy metals. A scanning electron microscopy in conjunction with an energy dispersive X-ray spectroscopy and an X-ray photoelectron spectroscopy was used to observe chromium occurrence and speciation. With an average of 6493.11 mg/kg, chromium contents in the lagoon soils reached up to 12971.19 mg/kg, 211-times higher than the threshold of Chinese soils (61.00 mg/kg). Elevated Cr contents resulted in significantly high pollution and noncarcinogenic and carcinogenic risks in the studied area. Chromium in most soils occurred predominately as Cr3+ (60–74%), and to a lesser extent, Cr6+. The mechanism responsible for decreasing Cr6+ percentages in soils with increasing depth was summarized: Cr6+ favors aqueous environment; soil moisture decreased with increasing depth; in soils especially in the lower portion, Cr6+ was reduced by Fe0 and Fe2, transforming into Cr3+ and Fe3+. In addition, the alkaline condition promoted Cr3+ to precipitate, resulting more Cr3+ absorbing in soils. The intimate association of Cr and Fe in soils (i.e., Cr mainly occurred in Fe oxides and dolomite) further confirmed our assumptions. A combined application of microorganism (e.g., Aeromonas hydrophila) and biochar (prepared from maize stalk or peanut shells) were recommended to alleviate Cr pollution in the soils. [Display omitted] • Chromium contents in lagoon soils are much higher than those of soils from the leather tanning districts worldwide. • The average I geo of Cr from studied soils is 7.59, higher than the threshold (>5) for significant pollution. • The Cr3+ percentages ranged from 60 to 74% in most soils, except for 42% in soils kb2 1–10 and kb3 1–10. • Chromium contents and Cr3+ percentages increased with the increasing depth. • Chromium occurs mainly in dolomite and Fe oxides; while no Cr was found in calcite. [ABSTRACT FROM AUTHOR]

Balancing socioeconomic development with water resources among cities is critical for the sustainable development of urban agglomerations. Despite this urgent need to analyse balanced development, a recognized method to measure and improve the balanced degree in urban agglomerations impacted by water resource constraints is still lacking. This study proposes a framework to evaluate the balanced development degree and simulate the impacts of interactions and management policies of economy-society-water on balanced development in urban agglomerations. This paper establishes a balanced development degree index using the coupling coordinated degree (CCD) model; constructs a system dynamic (SD) model to simulate economy-society-water interactions; and designs future scenarios to evaluate the impacts of industry, population, water, and comprehensive regulation policies on balanced development. The integrated framework that couples the above three methods was validated in the Beijing-Tianjin-Hebei (BTH) region in China. The results showed that (a) industrial and population regulations slightly increase the level of balanced development by 0.0025 and 0.0024 in the BTH region but will increase water scarcity in Hebei; (b) improving water use efficiency is an effective way to relieve water stress; and (c) the balanced degree increases by 15% under comprehensive regulatory policies. Integrated water-economy-society management makes it possible to achieve co-development without increasing the water crisis in the BTH region. This study provides support for policy-makers and promotes sustainable development of the water-economy-society in urban agglomerations. [Display omitted] • A framework for balancing urban agglomerations under water constraints is developed. • An index of urban agglomerations balanced development is established. • Efficiency of the proposed approach is examined in the Beijing-Tianjin-Hebei region. • The water system is key to balanced development in the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Proponents of distributive justice with regard to energy hold that every household has the right to affordable access to energy. However, when passively participating in clean energy reform policies, households, and especially low-income households, are often forced to use energy beyond the scope of affordability, resulting in distributive injustice. However, research on the quantitative estimation of injustice in energy distribution is still rare. In this paper, an evaluation model of energy vulnerability and distributive justice is established through the "reverse deduction method," and the change value of energy vulnerability before and after energy reform is used to calculate the loss value of distributive justice, which is used as the basis for energy policy evaluation. Taking the policy of replacing coal with natural gas for rural heating in Gaocheng District, Hebei Province, China as a case study, the value of lost distributive justice is calculated. The results show that 34.51% of households experienced distributive injustice after the energy reform, while 19.34% of households improved their energy vulnerability and achieved energy justice through energy subsidy policies. However, 46.15% of households were able to adapt to the energy reform independently without subsidies, which indicates a waste of resources in the energy subsidy policy. The policy implication of these results is that differentiated energy subsidy policies should be implemented according to household energy vulnerability, so as to maximize the policy benefits on the premise of ensuring justice in household energy distribution and minimizing injustice. The empirical study proves that the method of assessing injustice in energy distribution based on the "reverse deduction method" of energy vulnerability is feasible and a new attempt. • The passive participation of low-income households in clean energy reform policies results in distributive injustice. • Apply the vulnerability framework to calculate energy distribution injustice. • The implementation of differentiated subsidies can effectively improve the vulnerability of rural households energy poverty. • It is feasible and a new attempt to measure energy distributive injustice by using the "reverse deduction method". [ABSTRACT FROM AUTHOR]

With the advantages of avoiding land-use competition, biomass from agricultural residues is a promising solution to alleviate the energy crisis and environmental problems. In the traditional biomass utilization management problem, few studies have considered that land and water are key resources for the sustainable development of biomass from a life cycle view. Concerning the complex food-water-energy nexus, this paper focuses on the synergetic management of crop planting structure and biomass utilization as a whole system. An integrated framework is proposed for the co-optimization of cropland distribution and biomass utilization pathway under multiple uncertainties. Base on interval programming and fuzzy set theory, a type-2 fuzzy interval linear programming model is developed to handle multiple uncertainties with various characteristics and provide the optimum strategies for decision makers with different risk preferences. The proposed framework is verified by a case study of Hebei Province, China. Moreover, the impacts of water shortage and the implementation of the carbon price on the optimized strategies, economic and environmental benefits are investigated to provide deeper management insights when facing complex external factors. The obtained results suggest that corn and wheat will still be the primary crops, and bioethanol production will gain priority in the biomass utilization pathways for economic purposes. Water resources availability will greatly affect the crop planting allocation as well as total benefits but barely influence the biomass utilization pathways. Furthermore, with the implementation of the carbon trade market, a higher carbon price will stimulate biomass pellets production to replace fossil fuel consumption and improve the economic benefits directly. • Synergetic management of crop planting and biomass utilization is proposed. • A novel hybrid inexact programming approach is developed to address uncertainties. • The impacts of water resources availability are analyzed from a nexus perspective. • The influences of carbon price on the biomass utilization pathway are explored. [ABSTRACT FROM AUTHOR]

The role of precursors' concentrations and meteorological conditions on the emerging ozone pollution problem in China has received wide attention, especially after the releasing of the Air Pollution Prevention Control and Action Plan (APPC) since 2013. With the decreasing trend of PM 2.5 nationwide, the effect of the strict control measures on increasing ozone variation has less been studied due to the challenge of complexity of nonlinear relationship among a number of factors on ozone formation. This paper evaluated the influence of both ozone precursors and meteorology on maximum daily average 8 h (MDA8) ozone at two urban sites and one rural site in Hebei province, China, from 2013 to 2017, by using a combined application of Kolmogorov-Zurbenko (KZ) filter and artificial neural network (ANN) model. Results showed that R2 was 0.80 between the measured and the simulated MDA8 ozone concentration when using meteorological factors and precursors' concentrations as input variables for ANN model. However, ANN model has limitation in estimating O 3 concentration peaks. The values of threat score (TS), probability of detection (POD) and false alarm rate (FAR) for MDA8 ozone concentration were 39%, 44% and 21%, respectively, throughout three studied sites in Hebei province. The annual average percentage change of precursor-related ozone was 0.67% from 2014 to 2017. Temperature, atmospheric pressure and boundary layer height were shown to account for 64% of the variability in long-term ozone levels. Ozone variation in Hebei province was reproduced mainly by meteorological parameters, and the contribution from precursors' concentration was smaller during the years when the APPC was implemented. [Display omitted] • Ozone level was estimated based on precursors' level and meteorological factors. • The ambient ozone concentration estimated by ANN model was acceptable. • Meteorology dominates the ozone variation in 2013–2017 in Hebei province. [ABSTRACT FROM AUTHOR]