China is facing tremendous multiple pressures of reducing carbon emissions, developing economy and improving peopleâ€™s lives. The implementation of economic/environmental policies is considered as a powerful tool for the nationâ€™s macroeconomic regulation and optimal allocation of resources. The objective of this paper is to develop an interactive enviro-economic equilibrium (IEEE) model to analyze the compound effects of provincial policy on other provinces within both regional and national contexts, and investigate the interactions among different taxes on relevant social-economic and environmental systems. In detail, a CGE-based multi-dimensional policy modelling is initiated for the analysis of inter-provincial interdependences under the interference of Guangdongâ€™s policy. A factorial Guangdong CGE is initiated for statistically quantifying the interactive effects of carbon, production and income taxes on Guangdongâ€™s GDP, social welfare and total carbon emissions. It is found that imposing carbon tax on one province will also reduce the carbon emissions of other provinces, while lowering production tax and income tax will promote the carbon emissions of other provinces. Production tax is always more significant than other taxes on relevant SEE issues. The significant contribution to GDP and carbon emissions is production tax, and the significant contribution to social welfare is production tax. Meanwhile, in terms of GDP and carbon emissions, there exist an interaction between production tax and carbon tax; and in terms of social welfare, there exist an interaction between income tax and production tax.
Virtual water flow and water footprint have been proposed as leading indicators to evaluate the environmental impacts of human-related water consumption. However, the risk of economic loss caused by water scarcity can be transferred via trading activities and affect local economic network. In this study, a system-based framework was proposed to assess the water scarcity risk in a national trade system based on the multiregional inputâ€“output (MRIO) analysis and the information-based network environ analysis (NEA).
In this work, an irradiance distribution measuring method based on a photodiode array was proposed to measure the irradiance distribution of truncated compound parabolic concentrators (CPCs). Firstly, truncated CPCs were designed and 3-D printed. Then twelve photodiodes were soldered on a printed circuit board to measure the irradiance distribution of CPCs. Besides, a box was manufactured to support the board and CPCs. Irradiance distribution of CPCs was measured under the illumination of Oriel AAA class solar simulator. Corresponding non-uniform factors of irradiance profiles of CPCs were evaluated based on the concept of standard deviation. Experimental results were compared with simulated irradiance profiles of CPCs. A maximum relative error of 13.1% was found between experimental and theoretical results, which verified the feasibility of the proposed photodiode array based irradiance distribution measuring method.
Sustainable agricultural development is one of the major challenges that call for effective actions. Agricultural residues and waste have been long used as an important bioresource for energy and material recovery. Biochar has great prospect which can improve soil properties, crop productivity and carbon sequestration in soil. Biochar is produced by pyrolysis of agricultural waste and residues. Slow pyrolysis process can obtain a relatively large proportion of biochar content.
The large amount of agriculture waste produced by agriculture and animal husbandry has prompted environmentally friendly treatment of biomass and nutrient recycling. Developing efficient and low energy consuming biomass carbon industry can be achieved by producing carbonized products for reuse in agriculture and for satisfying energy demands in agriculture production and rural area. The production and application of biochar in the rural area serve a suitable choice for pollution control and carbon abatement.
The agriculture sector has unique characteristics, it is main contributor to climate change. Meantime, it also affected by climate change. 20% to 35% of the greenhouse gases produced are related to the agricultural sector, while some are as high as 50%. Slow pyrolysis of agriculture waste produces relatively high proportion of biochar and bio oil, bio-gas. There are several factors will affect biochar yield and properties. Reaction temperature, reaction time, heating rate will affect biochar yield, and different type of biomass, moisture content, and particle size also will affect biochar properties. Biochar at 600â€¯Â°C had better physiochemical properties than biochar at 400 or 500â€¯Â°C. In this work, the data collect from previous literature reviews, which the properties of feedstocks and process conditions data are collected. After built up database, adaptive neuro-fuzzy inference system (ANFIS) is used for prediction of biochar yield and properties.
The traditional prediction methods have been introduced in this paper, such as the least square-support vector machine (LS-SVM), artificial neural network (ANN) and generalised linear model. They will be compared with ANFIS model in this paper.
Wastewater treatment is critical for water saving and secure water supply, but it is energy intensive. Over the past 10 years, the construction of national sewage treatment system is developing in high speed. By the end of 2018, 5370 waste water plants have been put into operation, covering 99.1 percent of cities and 95.5 percent of countries. The ratio of energy consumption for wastewater treatment to the total energy consumption in China has reached up to 2% which is still increasing. Meanwhile, the upgrading and reconstruction of the sewage treatment plants exert new pressure on energy consumption. Some studies has calculated the energy consumption for different wastewater treatment technologies mainly based on life cycle analysis (LCA) at micro level. However, few studies has focused on the whole wastewater treatment system at macro level, especially very few studies has analyzed the complex interaction between water saving and energy saving within the system. The potential tradeoffs and synergies are also rarely considered, which are critical for wastewater treatment planning. In this study, the nexus accounting framework for wastewater treatment is established to identify the key regions and technologies to boost synergies and avoid negative tradeoffs from nexus perspective. Taking China as a case study, firstly, energy consumption for wastewater treatment (EC) are systemically calculated based on LCA considering the technologies differences. The water return on investment (WROI) is defined and analyzed for wastewater treatment system. The regional differences among 30 provinces of WROI are investigated. The spatial and temporal characteristic of EC and WROI are analyzed based on ArcGIS and energy efficiency model. Finally, based on the characteristic of EC and WROI, a series of nexus indicators to show the spatial tradeoffs and synergies are defined. By analyzing nexus temporal and spatial characteristics, this study aims to provide theoretical basis for promoting sewage treatment upgrading and reconstruction as well as water and energy saving.
Combined heat and power (CHP) system has been demonstrated to be an efficient cogeneration energy system. With the development of fuel cell technology, one kind of electrochemical-combustion CHP system, such as SOFC-GT, SOFC-ICE, was studied in the past decades. However, how to optimize the system efficiency, maximize the flexibility of system are not clear yet. Aiming to improve fuel efficiency, this research studies controller design of this system using operation point optimization theory for electricity generation, and the performances are validated by simulation.
As a major vegetable planting province, Shandong is the national greenhouse vegetable center. The coupling relationship of food-water-energy based on greenhouse vegetables still remains lack for regions. Given this, the study proposes a nexus framework of greenhouse vegetable-water-energy, and the planting status and distribution of greenhouse vegetables in Shandong province were investigated. Then, based on life cycle analysis (LCA), the groundwater resource consumption and energy consumption related to water withdraw in greenhouse vegetable planting were calculated, and the pressure on local resources caused by greenhouse vegetable planting was evaluated and spatialized. Finally, based on the scenario simulation, the planting structure of greenhouse vegetables under the constraint of water resources and energy was optimized in order to achieve a high nexus degree of vegetable-water-energy coordination on the basis of ensuring the yield of greenhouse vegetables. Overall, this study proposes a framework for quantifying the water and energy consumption in vegetable production and provides a new paradigm to understand the vegetable-energy-water nexus.
Industrial parks (IPs), called the engine to Chinaâ€™s economic growth, have contributed greatly to Chinaâ€™s rapid development, while emitting a lot of air pollutants and greenhouse gas (GHG). Establishing GHG emission inventories is so essential to explore the low-carbon strategies in the industrial park level. Taking 11 IPs in Central China as objects, this study has established GHG inventories including direct and indirect emissions, and explored the characteristics from energy types and industrial sectors. On this basis, we adopted cluster analysis to classify these 11 IPs into three categories of â€œ3H (High carbon intensity, High proportion of energy-intensive industries output, and High proportion of coal in energy mix)â€, â€œ3L (Low carbon intensity, Low proportion of energy-intensive industries output, and Low proportion of coal in energy mix)â€ and â€œMixedâ€ IP, and then selected representative industrial parks for case study. The results show that: Total CO2 emissions of these eleven parks in Central China in 2017 were 14472.6 kt, and coal consumption was the dominant source of GHG emissions in these parks, accounting for 80.3% of the total. Meanwhile, energy-intensive industries were the main discharging sectors, accounting for 79.6%. Reducing the export of electricity and using renewable energy to replace coal for power generation are crucial to mitigate GHG emission in the IPs including large-scale thermal power plants. Cluster analysis reveals that â€œ3Hâ€ and â€œMixedâ€ parks should be put in the priority in the GHG mitigation, focusing on traditional energy-intensive industries transformation and energy structure adjustment. This study is helpful to uncover GHG emission characteristics of IPs in Central China, and give some recommendations on GHG mitigation strategies in IPs.
By reducing total travel time and travel distance, taxi ride-sharing is of great significance to decrease urban carbon emissions sourced from ground transport. Heavy computation in matching multiple ride demands has a negative impact in taxi ride-sharing at metropolitan-wide scale. In this paper, a fast matching strategy based on time and distance constraints is proposed to filter candidates. Experiment shows that the strategy can reduce the times of candidate matching and improve the searching efficiency. An empirical analysis of potential taxi ride-sharing in two periods of a day (9:00-10:00,21:00-22:00) based on taxi GPS trajectory data in Qingdao shows that when tolerance time of delay time is 5 min, 35% of the total trips can be shared. Total travel time of all trips can be saved by nearly 222 hours and the total travel distance can be reduced by nearly 9200 km,about 6348g CO emissions, 515g NOx emissions, 10g of PM2.5 emissions and 515200g fuel consumption were reduced respectively. Our study provides a positive evidence for potential emissions reduction by taxi ride-sharing, so as to support better understanding on low-carbon urban transport service.