科研成果

In this paper, a novel mathematical model for the heat extraction process from hot dry rocks (HDRs) by enclosed water recycling in a horizontal well is established, on a basis of which a series of exergy analyses are conducted. The pressure and temperature distributions in the wellbore and the exergy extracted under different working conditions are calculated. Eight factors are specifically studied to evaluate their effects on the accumulated exergy of the produced hot water. It is found that the accumulated exergy first gradually increases but decreases subsequently with the water rising flow rate. The accumulated exergy is noticed to increase obviously with the increase of the length for the horizontal section, temperature of the HDR, thermal conductivity of the HDR, and diameter of the casing. The temperature distributions in the HDR around the wellbore are analyzed at different time. More specifically, the temperature drop of the HDR gradually spreads to far area of the wellbore with the continuous extraction of geothermal energy. The temperature of the rock around the wellbore decreases by increasing the injection rate. A higher HDR thermal conductivity leads to a quick heat transfer from the remote to near wellbore area. The exergy analyses in this study provide strong theoretical supports to utilize the HDR heat extraction.

In China, a significant reduction in primary pollution has been observed due to the Clean Air Action since 2013, and ozone pollution has become increasingly prominent over the past years. Pearl River Delta (PRD) is one of the most successful regions concerning primary pollution control, while is suffering from severe ozone pollution during autumn. In this study, we present a field campaign in Shenzhen, a megacity in PRD, in October 2018 with measurements of ozone and photochemical precursors. These observational data are helpful to analyze the local ozone budget and its sensitivity to precursors with the help of an observation-based model (RACM2-LIM1). The observed ozone concentration was up to 121 ppbv during a photochemical episode from 1 to 8 October, when intensive ozone formation up to tens of ppbv/h was found. Ozone vertical measurement indicates the fast ozone production is happening throughout the planetary boundary layer (PBL), which is an important source of morning ozone increase resulting in ozone pollution. An explicit case study is performed to reveal the diurnal feature of instantaneous ozone production rate (P(O-x)) and accumulative P(O-x) based on the O-3-NOx-VOC sensitivity, ROx radical primary production rate (P (ROx)), and L-N/Q for three cases including ozone pollution and attainment periods. Results show that nitrogen oxides (NOx = NO + NO2) reduction have positive and negative impact on local ozone production from one pollution episode to the other, which indicates the complexity of O-3-precursors sensitivity and difficulty to control ozone pollution in Shenzhen. Finally, comparison among measurements in other campaigns provides additional evidence on local ozone production sensitivity on NOx and anthropogenic volatile organic compounds (AVOCs) with respect to a temporal and spatial change. The

Excessive fertilization in rice paddy fields leads to surface water eutrophication, groundwater contamination and air pollution. Determining optimum nitrogen (N) management is essential for maintaining rice yield while reducing the environmental risk caused by N loss. A two-year field experiment (2017–2018) was carried out in a typical paddy field in the middle reaches of the Yangtze River. The WHCNS (soil Water Heat Carbon Nitrogen Simulator) model was calibrated and evaluated for simulations of measured ponding water depth, evapotranspiration, aboveground dry matter, yield, runoff and crop N. The model was then used to evaluate the effects of different N fertilizer rates and split-N application ratios (SNR) practices on crop growth and N losses. Results showed that the model performed well in simulating rice growth and N losses in the region. Ammonia volatilization and denitrification were the mainly pathways of N loss in paddy field, and their two-year average losses were 34% and 38% of the total N loss, respectively. N leaching accounted for 23%, and runoff N loss accounted for 5% of total N loss. N losses were evaluated for two different scenarios and simulated ratios of ammonia volatilization, denitrification, N leaching, and runoff to total N loss under different N management scenarios were 15%–53%, 33%–55%, 6%–30%, and 4%–8%, respectively. Ammonia volatilization and N runoff exponentially increased with an increase of N fertilizer rate, whereas denitrification and N leaching showed an increasing and then a decreasing trend. Yield increased by 36 kg ha−1, and the total N loss decreased by 32.6 kg N ha−1 when the N fertilizer rate was reduced from 231 kg N  ha−1 to 155 kg N ha−1 and the SNR was changed from 5:3:1 to 1:1:4. Therefore, reducing the N fertilizer rate and increasing the SNR in the late rice growing season can significantly reduce N loss and effectively improve N use efficiency.

Energy Return on Investment (EROI) has become a policy analysis tool related to sustainability. However, most EROI studies adopt the standard EROI method, which has two inherent defects. First, standard EROI leaves out energy quality. Second, input factors such as labor, auxiliary services and environmental factors are not considered. Therefore, this paper introduces exergy into the EROI calculation and establishes a new extended exergy-based EROI (ExEROI). ExEROI treats “available energy” as energy quality; with the idea of embodied flows, ExEROI quantifies all the five input factors of the EROI analysis framework. Shale gas exploitation in the Sichuan Basin is used as an example in the case study. The ExEROI result is 9.68, which is much lower than the standard EROI result of 82.95. This is due to the inclusion of more input factors and the fact that the input factors are measured by exergy. Specifically, the auxiliary service input factor accounts for 77.10% of the total inputs, and such inputs are ignored by the standard EROI method. ExEROI makes up for the shortcomings of standard EROI and avoids the possible misinformation caused by standard EROI. ExEROI has the potential for use as an integral aspect of energy resource exploitation evaluations.

© 2019 Elsevier Ltd In the medium to long term, China must conduct deep emission reduction actions to transform the country's economy and meet the conditions of the Paris Agreement. As an advanced emission reduction technology, carbon capture and storage (CCS) is undoubtedly an important means of achieving this goal. China must consider how to retrofit existing thermal power plants to install CCS technology. Thus, the expected future roadmap for power plants with CO2 capture is of significant interest. To achieve this aim, we propose a new CCS project investment model, which helps design the CCS development roadmap for achieving the emission targets for 2050. Reductions in the cost of technologies as a result of learning-by-doing is considered to enrich the model to describe the reality more sensibly. Through some mathematical skills, we transform the original continuous problem into a nonlinear integer programming problem. By solving the model, we are trying to answer questions about when to adopt CCS technology and the cost. The results reveal that early large-scale CCS demonstrations are not necessary. The peak investment period of CCS is around 2035. Operating costs account for 80% of the overall cost of CCS, and thus, policymakers must fully motivate the development and investment of operating technologies, especially capture technologies. The results also show that when the scale of CCS technology is promoted, flexible installation levels can be considered to improve efficiency and reduce costs.