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Sustainable cities, as an effective response to global climate aberrations, have increasingly garnered the attention of researchers. However, due to the wide range of interpretations and applications associated with sustainable cities, diverse methodologies can yield starkly contrasting results. This paper adopts ecological and low-carbon perspectives to evaluate and discuss urban sustainability. The core of this investigation involves quantitatively measuring a city’s sustainability based on the lifecycle metrics of emergy and carbon footprint. The findings reveal that Yangzhou, recognized as a model ecological city by authorities, exhibits an emergy sustainability index below the standard benchmark (ESI = 0.02

This paper uses a perspective of life cycle ecological emergy and carbon footprint to quantitatively verify the sustainable status of building systems; it also employs a neural network model to predict and analyze their long-term ecological and carbon footprint effects. The research results show that the stages of building material production and building operation play a major role in the emergy and carbon emissions of the entire building system, and their changes show an inverse trend. As the building system operates, the greater the system loss and consumption, the environmental load rate (ELR) will gradually increase, and the sustainability parameter (ESI) will also gradually decrease. The integration of energy storage modules significantly improves the sustainability of the building system. When calculated over five time periods (5 years, 10 years, 20 years, 30 years, and 50 years), the overall carbon emission reduction rates after adding the energy storage module are 39.4%, 33.6%, 39.2%, 42.5%, and 38.8% respectively, demonstrating that the energy storage module has a significant positive effect on the sustainability of the building system. This study reveals the energy efficiency and environmental impact of the building system throughout its entire life cycle, providing a scientific basis for optimizing building design.

The global energy crisis is increasingly severe, and the construction industry, as a high-energy-consuming sector, is one of the main sources of carbon emissions. As a result, the development of green buildings has become imperative. Shear walls, as a common structural form in buildings, have their wall layout ratio significantly influencing the amount of building materials used, which is crucial for material reduction and carbon emission reduction during construction. This paper innovatively introduces the concept of the optimal shear wall layout ratio, focusing on the analysis of the variation patterns of wall ratios and their associated carbon emissions in both traditional and optimal models. Various optimal models are designed with shear wall length as the variable, and the relationship between shear wall layout ratio and carbon emissions is examined. Under a seismic fortification intensity of level 7 (0.1 g), the layout ratio of the optimal models does not exceed that of the traditional model (4.24%), and the carbon emissions are reduced by approximately 11%. A reasonable design of the shear wall layout ratio not only reduces carbon emissions in buildings and improves reverse performance but also promotes a dual enhancement in both economic and environmental benefits in the construction industry.

Logistics land is the spatial carrier for the development of logistics enterprises. Its evolution mode and driving mechanism determine the level of high-quality development of the logistics industry, and serve as an important basis for urban planning and territorial spatial planning. This study introduced a Boston consulting group (BCG) matrix and geographically weighted regression (GWR) spatial econometric models to carry out empirical research on the Yangtze River Delta (YRD), in an effort to provide scientific information for evidence-based decision-making by governments and enterprises. The scale and ratio of logistics land (LLS and LLR) in the YRD showed significant spatial heterogeneity and autocorrelation, cities with large logistics land use converging from clusters to belts from 2000 to 2020, and agglomerations with high logistics land ratio (LLR) migrating from inland to coastal areas. Diversified models of logistics land evolution also emerged, such as high scale–high speed cities, low scale–low speed cities, high scale–low speed cities, and low scale–high speed cities. In addition, the driving mechanism of LLS and LLR was very complex, with a great difference in the intensity, nature and spatial effects of the influence of different factors. The inspiration from empirical case studies is urgent to revise the planning norms and clarify the LLS and LLR control standards for logistics land use. Meanwhile, the synergistic development target of the logistics industry in the new era is changing from the manufacturing industry to the commerce and trade industry; the establishment of planning zoning and the designing of differentiated management policies significantly improve the planning applicability.

The ecological landscape design of urban rivers plays a crucial role in mitigating the urban heat island effect and preserving urban ecology. This study focuses on the construction process data of key landscape nodes along Nanjing’s urban rivers. By employing a whole life cycle emergy approach and carbon emission method, the sustainable changes in the landscape system are quantitatively assessed. Furthermore, artificial neural networks have been used to conduct long-term sustainability analysis and predictions for the landscape system. The research findings reveal that over time, the maintenance investment in landscape projects gradually becomes dominant, increasing from 2% in the first year to approximately 75% after 30 years. This phenomenon signifies a decline in the efficiency of the landscape system. Sustaining the ecological balance of the landscape system necessitates continuous inputs of material flow, energy flow, and information flow. The major contributors to carbon emissions in the landscape engineering system are diesel fuel, cement, and steel. This highlights opportunities for sustainable improvement from a low-carbon perspective. To enhance the ecological sustainability of urban waterfront landscapes, three measures are proposed: sponge city construction concepts, coupled sewage treatment systems, and information flow monitoring systems. The effectiveness of these measures was preliminarily validated.

Sustainability studies are vital for the long-term development of ecological cities. For cities, single qualitative or quantitative evaluation studies cannot effectively illustrate the ecological and sustainable status of a city. This study employs the emergy–geographic information system (GIS) method to conduct a sustainability evaluation of a city, so as to effectively verify the evaluation results. The emergy method and GIS are both commonly used approaches to address urban issues, but their synergistic effect has rarely been considered, explored, and utilized in urban planning. This study aims to investigate this effect on Hangzhou city through comparative analysis. The results show that rain (geopotential energy) and rain (chemical potential energy) have the highest emergy values from 2000 to 2035, followed by solar emergy, wind emergy, and geothermal heat emergy. These findings are also supported by the GIS map that shows a similar pattern with renewable emergy. Using the five plots (cropland, woodland, grassland, water area, and built-up land) on the GIS map as examples, the accuracy of emergy calculation results for Hangzhou city can be verified, demonstrating the effectiveness of the emergy–GIS methodology. This research provides practical recommendations for city designers and professionals worldwide on urban sustainability. By incorporating both emergy and GIS methods, cities can make informed decisions toward achieving environmentally sustainable development.

Abstract As the significant residuals in the sewage treatment system, sludge treatment and reuse play a pivotal impact on the environmental sustainability study in China. In this paper, two sewage sludge treatment systems have been investigated, calculated, and analyzed, including the conventional treatment system (Scenario A) and improved reuse system (Scenario B), respectively. The results demonstrate that (1) Compared to Scenario A, Scenario B is a comprehensive system, which integrates a sewage sludge treatment system and a brick production system for sludge recycling. (2) After considering the brick system (scenario B), on the one hand, the sludge treatment capacity has been enhanced and raised sludge utilization; on the other hand, negative influences have also generated due to the non-renewable resources input and several outputs. (3) In Scenario A and Scenario B, the input resources part reflects the main impact (about 59.6% in the entire emergy value). (4) In this new paper, the UEVs are 2.73E + 11sej/kg and 6.29E + 11sej/kg in Scenario A and Scenario B, respectively. (5) The emergy sustainability indexes (ESI) are 0.012292 and 0.00848, which express the weak comprehensive effects in Scenario A and Scenario B. (6) Scenario B has a more extensive range of change than Scenario A because of the more resource input for the sensitivity analysis. Given the all discussions, there are two effective approaches to be used for perfecting environmental sustainability in the Scenario A system and Scenario B system.

Ecologically sustainable buildings and their carbon emissions are two popular ideas for building life cycle systems. It is a challenge to comprehensively assess the sustainability of building cases using two different methods. Based on over a decade of research, this paper attempts to explore the possibility of quantitatively integrating both approaches. In this study, we adopted the emergy method and carbon emission approach to assess and analyze a building system. In particular, similarities and differences have been identified through emergy and carbon emissions at each stage of the building’s whole life cycle. The results demonstrate that the building operation phase is the critical contributor (Approximately 79.6% of the total emergy and 97.9% of the entire carbon emission), which occupies the most emergy and carbon emission amounts of the whole building system. In order to improve the ecological sustainability of the building system, renewable energy subsystems are considered and explored. While the overall sustainability of the building system is enhanced, the new systems will aggrandize the carbon emissions. Therefore, the ecological sustainability of building systems and carbon emissions should be considered comprehensively, and the relationship between the two views needs to be balanced.

Ginling College is the first women’s college founded by the American Christian Church in Nanjing, China, in the early 20th century. The architectural style of the school reflects the orientation of the “Chinese localization” of the Christian Church at that time. It is a representative work of the revival of traditional Chinese architecture. It is known as a “Renaissance of Chinese traditional architecture” and profoundly influenced later generations. Due to its important historical status and artistic value, the Ginling College complex has been designated by the Chinese government as a national key cultural relic protection unit and China’s 20th-century architectural heritage, and the protection scope of the Ginling College historical district has been specially designated for overall protection. Currently, little research has been conducted on this historic area, so the authors undertook this project. This paper adopts a combination of qualitative and quantitative methods for research, starting from the two aspects of architectural art and sustainable design, and analyzes in detail the artistic characteristics of the project, the structural materials obtained locally, and the sustainable design method that utilizes natural lighting and ventilation to explore a modern campus design method based on the concept of sustainable design with a “combination of Chinese and Western architectural art”. Through artistic creation and technological innovation, traditional Chinese revival architecture has realized a harmonious coexistence between man and nature, embodying the design concept of sustainable development, and promoting the development of architecture and the region.

The stability of social network structure (SSNS) in historical towns is influenced by changes in built environments and demographic factors. The historical towns in China have evolved into massive rural-urban migration under the rapid urbanization over the past forty years. In this context, many of these historical towns experienced “declining built environment and disintegrating social networks,” which does not contribute to the adaptive renewal of the built environment and social networks in historical towns, as well as the psychological health of residents. This article intends to explore the adaptive renewal of the built environment and social networks of historical towns based on the SSNS. Data on “households” and “social ties” (i.e., kinship, geographic, and job relationship) among households were collected via a field survey in seven historical towns in Chongqing, China. K-core models of social network analysis (SNA) were calculated to analyze SSNS. The result shows that the social networks of historical towns with centripetal-shaped structures were more stable than historical towns with divergent-shaped structures. Moreover, spatial layout forms and functions of households might affect the stability of social networks in historical towns. Based on the results of the analysis of SSNS, strategies for adaptive renewal of the built environments and social networks were put forward in two aspects. The built environment, such as the classification of public spaces and service facilities, can be designed based on the k-core indicator for increasing the spatial connection of households in the historical towns. In addition, increased social activities in historical towns with weak SSNS may promote social connection of households, and are also helpful in boosting public health in psychological aspects.

We evaluated the performance of a variety of time series models, that include the harmonic (HR) model, autoregressive (AR) model, linear Gaussian state-space (LGSS) model, cubic spline (SP) model, double logistic (DL) model, and asymmetric Gaussian (AG) model, for reconstructing (all six models) and forecasting (HR, AR, and LGSS models) dense Landsats 5–7 time series based on 4562 samples. To remove the impact of land change and human interventions on data reconstruction and forecasting, this evaluation excluded croplands and samples changed between 2000 and 2011. Results show that the widely used HR model is not a good model for data reconstruction but outperforms other models in data forecasting. The DL and AG models have the best performance in data reconstruction but cannot forecast Landsat observations. The AR and LGSS models shared similar performance in reconstructing Landsat data but are less ideal for data forecasting, particularly for the LGSS model. Integrating the HR (for forecasting) and DL or AG (for reconstruction) is recommended to improve land change detection and land cover classification results. We also evaluated the impact of data density and irregularity on reconstructing and forecasting Landsat observations. When the data density is low (

In the context of ecological building and green building popularity, building sustainability assessment is becoming more and more important. In this paper, a comprehensive evaluation platform by coupled LCA method and energy method was designed, verified, and analyzed to assess the sustainability of the building system. The main results illustrated that the construction stage is the most critical stage in terms of emergy angle. From a sustainability perspective, the Emergy Sustainability Indicator was at a moderate level (1.0141), which can be considered to increase the proportion of renewable energy and reduce the proportion of non-renewable resources to improve the sustainability degree. Of the three scenarios designed, the second scenario has the best sustainability in the building system. The unit emergy value of the whole building was also shown to demonstrate the unit emergy of an individual. In order to verify the accuracy of the data, a sensitivity analysis was conducted. Finally, two types of positive measures are proposed to ameliorate the environmental sustainability in the building system, containing the increasing proportion of renewable energy and using recycled building materials.

Abstract Background Blended learning that combines a modular object-oriented dynamic learning environment (Moodle) with face-to-face teaching was applied to a medical statistics course to improve learning outcomes and evaluate the impact factors of students’ knowledge, attitudes and practices (KAP) relating to e-learning. Methods The same real-name questionnaire was administered before and after the intervention. The summed scores of every part (knowledge, attitude and practice) were calculated using the entropy method. A mixed linear model was fitted using the SAS PROC MIXED procedure to analyse the impact factors of KAP. Results Educational reform, self-perceived character, registered permanent residence and hours spent online per day were significant impact factors of e-learning knowledge. Introversion and middle type respondents’ average scores were higher than those of extroversion type respondents. Regarding e-learning attitudes, educational reform, community number, Internet age and hours spent online per day had a significant impact. Specifically, participants whose Internet age was no greater than 6 years scored 7.00 points lower than those whose Internet age was greater than 10 years. Regarding e-learning behaviour, educational reform and parents’ literacy had a significant impact, as the average score increased 10.05 points (P

Clay brick is a commonly used building material in China. Due to the enormous land destruction and excessive consumption of resources, such as materials and energy in the manufacture of clay brick, it is important to study its overall sustainability, i.e., in terms of impact on the environment, services, and economy. In this study, emergy analysis is employed, which offers a holistic perspective, unlike typical environmental studies. A series of emergy indices such as renewability rate (R%), nonrenewability rate (N%), unit emergy values (UEVs), emergy yield ratio (EYR), environmental loading ratio (ELR), and emergy sustainability index (ESI) were used to study manufacturing of clay brick. In addition to calculating UEVs of clay brick manufacturing in China (7.18 × 1012 sej/kg), our detailed analysis shows that the nonrenewable resources and imported energy have a dominant impact on the emergy contribution (50.6%) and within the nonrenewable resources, clay is the foremost item, accounting for 33.5% of local emergy inputs. Given different electricity UEVs, the change ranges of clay brick system UEVs are 14.9% (scenario 1), 7.24% (scenario 2), 8.91% (scenario 3), and 6.94% (scenario 4). Furthermore, several policy suggestions are discussed for improving the sustainability of the evaluated system, involving the energy structure adjustment, recycling material replacement, and promotion of energy-saving systems.

The Chinese cement industry produced 2150 million metric tons of cement in 2014, accounting for 58.1% of the world’s total. This industry has a hugely destructive effect on the environment owing to its pollution. The environmental impact of cement manufacturing is a major concern for China. Although researchers have attempted to estimate impacts using life cycle assessment approaches, it lacks the ability to provide a holistic evaluation of the impacts on the environment. Emergy analysis, through ecological accounting, offers environmental decision making using elaborate book keeping. In spite of the high environmental impact of the cement industry, there has only been a handful of research work done to compute the unit emergy values (UEVs) of cement manufacturing in China. A thorough study of existing UEVs of cement manufacturing in China showed pitfalls that may lead to inaccurate estimations if used in emergy analysis. There is a strong need for a new, updated UEV for cement manufacturing in China, particularly reflecting both the dry and wet raw materials in the manufacturing process. This paper develops a methodology to calculate the nonrenewable resources used in cement manufacturing, particularly using mainstream cement production line. Our systematic approach-based UEV estimates of cement manufacturing in China using the quota method are 2.56 × 1012 sej/kg (wet material) and 2.46 × 1012 sej/kg (dry material). Emergy indicators such as environmental loading ratios which were calculated at 2390 (wet material) and 2300 (dry material); emergy yield ratios at 15.7 and 15.8; and emergy sustainability indices at 0.0066 and 0.0069 for dry and wet materials used in cement manufacturing, respectively; these show the immense impact on the environment in China.

Recently, the United States Geological Survey (USGS) has released a new dataset, called Landsat Analysis Ready Data (ARD), which is designed specifically for facilitating time series analysis. In this study, we evaluated the temporal consistency of this new dataset and recommended several processing streamlines for improving data consistency. Specifically, we examined the impacts of data resampling, cloud/cloud shadow detection, Bidirectional Reflectance Distribution Function (BRDF) correction, and topographic correction on the temporal consistency of the Landsat Time Series (LTS). We have four major observations. First, single-resampled data (ARD) are generally more consistent than double-resampled data (re-projected Collection 1 data), but the difference is very minor. Second, the improved cloud and cloud shadow detection approach (e.g., Fmask 4.0 vs. 3.3) moderately increased data consistency. Third, BRDF correction contributed the most in making LTS consistent. Finally, we corrected the topographic effects by using several widely used algorithms, including Sun-Canopy-Sensor (SCS), a semiempirical SCS (SCS+C), and Illumination Correction (IC) algorithms, however they were found to have very limited or even negative impacts on the consistency of LTS. Therefore, we recommend using Landsat ARD with the improved cloud and cloud shadow detection approach (Fmask 4.0), and with BRDF correction for routine time series analysis.