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Cities are the important spaces, responsible entities and action units for achieving low-carbon and high-quality economy. Blockchain technology provides a new solution for low-carbon development in cities. Based on low-carbon information sharing, low-carbon incentives, low-carbon regulations with blockchain technology, this paper endeavors to propose a low-carbon development model for Chinese cities. The results indicate that: (1) blockchain-based governments, enterprises, city dwellers, and third-party service agencies are important stakeholders in promoting urban low-carbon development; (2) the effectiveness of the blockchain platform needs the coordination between the production and consumption systems, the equal emphasis on systemicity and long-term effectiveness, and the deep integration of government regulations and market mechanism; (3) blockchain-based information sharing instruments, incentive instruments, and regulation instruments should be applied to low-carbon development in cities; (4) blockchain technology promotes low-carbon development for cities in both direct ways and indirect ways. This study can provide a reference for the urban sustainable development in China and other countries.

Abstract There is a rapid increase in the air pollution level of the earth atmosphere due to the extreme demand and usage of the petroleum products. The demand has accelerated the recent research to explore an environment-friendly fuels suitable for the performance on the diesel engine. The optimization of the engine parameters using RSM with combination of taguchi method is an important aspect which generates an important optimized model for the responses. In the present study, an investigation of optimum performance and emission parameters of an engine fuelled with jojoba biodiesel is presented. The study also includes the optimization of input parameters to attain corresponding optimal thermal performance of the engine. The input parameters are injection pressure, injection timing of fuel, percentage blends of jojoba based biodiesel and engine load whereas the corresponding output responses such as brake thermal efficiency, peak cylinder pressure, exhaust gas temperature, and hydrocarbon emission are considered for the optimization during the investigation. The experimental design used in the study is based on a central composite rotating design matrix. The best combination of input parameters is recorded at 25°bTDC injection timing of fuel, 21.52 MPa injection pressure of fuel, 24% mixing of jojoba biodiesel with diesel, and 80% engine load which maximum BTE and Pmax minimum EGT and UHC emission of the engine. Experimental and optimized results of the output responses at optimum input parameters are compared and they were found to be in the suggested error range.

Soil erosion is a major threat in the Three Gorges Reservoir Area (TGRA) of China. Since 1990, the Chinese government has launched a series of ecological restoration projects to promote soil conservation in the TGRA. To understand the effects of ecological restoration on soil conservation in the TGRA, we used the abrupt change analysis of soil mass from 1982 to 2015 and its drivers; soil mass was obtained with the universal soil loss equation at continental scale. We found that soil conservation and annual rainfall decreased in the TGRA over the study period. Abrupt change points of soil conservation occurred in 1984 and 2007. Soil conservation in the TGRA showed a dramatic decrease before 1984, a slow increase after 1984 as a result of climate, and a rapid increase after 2007 due to an increase in vegetation cover. From 1982 to 2015, climate change played a primary role in soil conservation changes and was more influential than topography and vegetation. However, ecological restoration was an important factor affecting soil conservation in the TGRA, and it needs to be promoted.

Optimal scheduling of a distributed energy resources system (DERs) can be beneficial for utilizing renewable energy and relieving the pressures upon the main electric grid. One of the most popular DER systems is the Building mount photovoltaic (BMPV) system. In this paper, a large office building is taken as a case study to develop an optimal day-ahead strategy for the BMPV system considering 24 hours ahead of energy consumption and PV generation uncertainty. This paper mainly includes BMPV system capacity determination, 24 hours ahead of energy usage and PV generation forecasting, and day-ahead optimal strategy development. Firstly, based on collected history energy demands, weather data, and building information, the install capacity of PV is defined by roof area. Furthermore, the battery capacity is constructed by China's latest photovoltaic energy storage capacity standard. Secondly, the ensemble learning model is established using a time-series algorithm and Long Short-term memory (LSTM) to predict day-ahead energy consumption. Moreover, an interval prediction method is used to forecast the PV generation for the next 24 hours. Finally, the accurate energy consumption prediction and PV generation interval are introduced to establish the BMPV system scheduling strategy. The day-ahead optimization scheduling strategy was developed based on Mixed integer linear programming (MILP), targeting minimal economic cost. As a result of the optimization process, the proposed strategy could save 4.8% in economic costs and reduce the peak load of the main grid effectively. Moreover, it can effectively optimize the energy consumption structure of buildings or even distributed energy systems and can provide feasibility to achieve net-zero energy consumption without sacrificing any comfort of occupancy.

Air pollution is prevalent throughout the entire world due to the release of various gases such as NOx, PM, SO2, tropospheric ozone (O3), etc. Ground-stage ozone is the predominant issue in smog and is the product of the interplay between sunlight and emissions. The destructive impact on the health of the populace might also still occur in cities with noticeably clean air and where ozone levels hardly ever exceed safe limits. Therefore, the findings of small variations in air quality and the technique of regulating air contamination are thought-provoking. The study employs various techniques to effectively observe and assess strategies for detecting and eliminating outliers in ozone emissions from pollution episodes. This technique helps to describe the sources and exceedance values and enhance the value of monitoring the data. In this study, the data have some missing observations. The method of imputation, the classical statistical technique, the statistical process control (SPC) technique, functional data analysis (FDA), and functional process control help to fill in the data and detect outliers, trend deviations, and changes in ozone concentration at ground level. A comparison study is carried out using these three techniques: classical analysis, SPC, and FDA, and the results show how the statistical process control and functional data methods performed better than the classical technique for the detection of outliers and also in what way this methodology can enable an additional, comprehensive method of defining air pollution control measures and water pollution control measures.

Abstract Soot volume fraction distribution of ethanol blended fuels (ethanol volume fraction 0%, 20%, 40% and 60%, named as E0, E20, E40 and E60) were measured in an optical direct injection spark ignition (DISI) engine by combined laser induced incandescence (LII) and two-color (2C) method. Exhaust particulate matter (PM) emissions were measured by a Combustion DMS500 Fast Particulate Analyzer. For DISI engines, pool fire and the resulting diffusion flame are the main sources of soot in the cylinder. Choosing a suitable measurement plane and detection time, laser induced incandescent can be used to quantitatively measure the soot concentration produced by the pool fire. This research explores the effect of ethanol blending on engine particulate matter by comprehensively analyzing the soot process in the cylinder and exhaust particulate emissions. According to the two-dimensional quantitative soot volume fraction results, the maximum average soot volume fraction of the same fuel on the 10 mm plane is greater than the 5 mm plane; on the same plane, E20 shows the highest soot concentration compared to the other fuel blends which could be the physical properties of the ethanol become apparent. For exhaust particle emissions, ethanol can significantly reduce the total particle number and accumulation mode particle number. E0, E40 and E60 show fairly similar behavior between the exhaust particle emissions and the soot-LII imaging measurements. For E20, however, this is in poor agreement when comparing the soot-LII imaging results to the results of exhaust particle emission measurements.

Abstract The impact of wood use by isolated Forest Dependent Communities (FDC) on forest conservation is not well understood. We present a study of wood use in the YUS area (combined watersheds of Yopno, Uruwa and Som rivers) in northern Papua New Guinea, where 57 communities depend on forests for their subsistence. Using a survey methodology based on the Poverty and Environment Network (PEN) survey protocol, we assess the annual volume of wood used, primary sources for this wood and evaluate the capacity of natural forest to sustainably support current rates of wood-use as well as their per capita CO 2 emissions. The primary reason for wood extraction was for fuelwood (6.4 kg person −1 day −1 or ∼11.1 tonne household −1 year −1 ) and housing construction (0.6 m −3 household −1 year −1 ). Fuelwood was collected primarily from areas close to the village, in fallow (grassland) and agroforestry land types, while construction wood was being sourced primarily from secondary and primary forests. The volume of construction wood currently harvested across YUS was approximately 11% the annual increase in timber volumes in available and accessible natural forest. Under this wood use rate and projected population growth (2.5–4%) these communities can harvest construction wood at a sustainable rate for between 55 and 90 years. Nonetheless, we demonstrate that the CO 2 emissions from wood extraction, and in particular fuelwood, are high; approaching 1.15 tonnes CO 2 person −1 year −1 . Household surveys revealed that all smallholders had a strong interest in planting trees for production of wood for house construction, which could reduce pressures on forests and compensate for CO 2 emissions.

Building resilient cities is the foundation and guarantee for the Chengdu-Chongqing economic circle to achieve high-quality and sustainable development. This research uses the entropy TOPSIS method to evaluate the urban resilience level of the Chengdu-Chongqing Economic Circle and uses the Fuzzy Set Qualitative Comparative Analysis (fsQCA) approach to analyze the configuration of contributing factors. Research indicates that the overall urban resilience level is relatively low, with more than 70% of the areas being less than 0.3. Overall, Chengdu (Level 1) and Chongqing central districts (Level 2) are 1–3 levels higher than their surrounding areas, which indicates insufficient spatial balance. The consistency scores of the single-antecedent condition necessity analyses were all less than 0.9, and the consistencies of all configuration analysis results were all greater than 0.8. This research proves that the creation of urban resilience is the result of a combination of factors, rather than the independent influence from any individual factor. Financial and innovation forces are the key driving factors that affect the level of urban resilience. The multiple driving model also helps to improve the level of resilience. The lack of cultural and innovation forces in Chongqing area has been proven to inhibit the level of urban resilience, and the lack of openness and political focus has resulted in a low level of resilience in the Sichuan area. We propose to promote the construction of a “dual core”, to create synergies between Chongqing and Chengdu, and to achieve balanced and integrated development in the entire region. We focus on the key factors affecting the resilience level of the Chengdu-Chongqing economic circle. In the future, we suggest further opening the market and implementing a developing strategy that is driven by economy and innovation. Regarding the construction of the Sichuan and the Chongqing areas, we encourage the two regions to adjust policies based on local conditions. First, the administration should solve the driving force deficiencies for development, then adopt differentiation strategies for regional development.