International experience of carbon neutrality and prospects of key technologies:Lessons for China

Carbon neutrality(or climate neutrality)has been a global consensus,and international experience exchange is essential.Given the differences in the degree of social development,resource endowment and technological level,each country should build a carbon-neutral plan based on its national conditions.Compared with other major developed countries(e.g.,Germany,the United States and Japan),China's carbon neutrality has much bigger challenges,including a heavy and time-pressured carbon reduction task and the current energy structure that is over-dependent on fossil fuels.Here we provide a comprehensive review of the status and prospects of the key technologies for low-carbon,near-zero carbon,and negative carbon emissions.Technological innovations associated with coal,oil-gas and hydrogen industries and their future potential in reducing carbon emissions are particularly explained and assessed.Based on integrated analysis of international experience from the world's major developed countries,in-depth knowledge of the current and future technologies,and China's energy and ecological resources potential,five lessons for the implementation of China's carbon neutrality are proposed:(1)transformation of energy production pattern from a coal-dominated pattern to a diversified renewable energy pattern;(2)renewable power-to-X and large-scale underground energy storage;(3)integration of green hydrogen production,storage,transport and utilization;(4)construction of clean energy systems based on smart sector coupling(ENSYSCO);(5)improvement of ecosystem carbon sinks both in nationwide forest land and potential desert in Northwest China.This paper provides an international perspective for a better understanding of the challenges and opportunities of carbon neutrality in China,and can serve as a theoretical foundation for medium-long term carbon neutral policy formulation.

Detection of Omicron Caused Pneumonia from Radiology Images Using Convolution Neural Network(CNN)

COVID-19 disease caused by the SARS-CoV-2 virus has created social and economic disruption across theworld.The ability of the COVID-19 virus to quickly mutate and transfer has created serious concerns across the world.It is essential to detectCOVID-19 infection caused by different variants to take preventive measures accordingly.The existing method of detection of infections caused by COVID-19 and its variants is costly and time-consuming.The impacts of theCOVID-19 pandemic in developing countries are very drastic due to the unavailability of medical facilities and infrastructure to handle the pandemic.Pneumonia is the major symptom of COVID-19 infection.The radiology of the lungs in varies in the case of bacterial pneumonia as compared to COVID-19-caused pneumonia.The pattern of pneumonia in lungs in radiology images can also be used to identify the cause associated with pneumonia.In this paper,we propose the methodology of identifying the cause(either due to COVID-19 or other types of infections)of pneumonia from radiology images.Furthermore,because different variants of COVID-19 lead to different patterns of pneumonia,the proposed methodology identifies pneumonia,the COVID-19 caused pneumonia,and Omicron caused pneumonia from the radiology images.To fulfill the above-mentioned tasks,we have used three Convolution Neural Networks(CNNs)at each stage of the proposed methodology.The results unveil that the proposed step-by-step solution enhances the accuracy of pneumonia detection along with finding its cause,despite having a limited dataset.

Effect of ultrasonic assisted KOH pretreatment on physiochemical characteristic and anaerobic digestion performance of wheat straw

In this study,ultrasonic field was applied during potassium hydroxide(KOH) pretreatment of wheat straw(WS).Three concentrations of KOH(2%,4%,and 6%) were tested during pretreatment.The results showed that there was a significant influence of the ultrasonic assisted KOH pretreatment(KOH(Upt)) on physiochemical characteristics of WS during pretreatment as well as on digester performance.The pretreatment time was optimized to 36 h for all KOH concentrations.The highest total volatile fatty acid(TVFA) productions(3189 mg·L^-1) from 6%KOHupt samples were observed.Similarly,the SEM analysis and FTIR observation revealed that KOH(Upt) effectively disrupted the physical morphology of WS and successful breaking of lignin and hemicellulose linkage between carboxyl groups.Moreover,the highest biogasification(555 ml·(g VS(loaded))^-1) and biomethane productions(282 ml·(g VS(loaded))^-1) from 4%KOH(Upt) digesters,with 69% of biodegradability,indicated significant availability of organic matter from KOH(Upt).The R^2 values(0.993-0.998) in Modified Gompertz Model indicated that the model was feasible to predict methane yield for this study.Similarly,the Bo values for 4%KOH(Upt)(283.30±2.74 ml·(gVS(loaded))^-1) were also in agreement to the experimental methane yield.These results suggested that ultrasonic addition during KOH pretreatment of WS can effectively increase the organic yield during pretreatment.Moreover,the increase in methane production from 4% KOH(Upt) suggested that digester performance can be improved with lower KOH concentrations using this pretreatment.

A numerical study to assess the effect of heterogeneity on CO_(2) storage potential of saline aquifers

Many parameters have been indicated crucial for the selection of a saline aquifer as a carbon dioxide(CO_(2))storage site.However,less attention has been given to the impact of heterogeneity on the performance of these storage media.Thus,the heterogeneity effect was evaluated in this paper by adopting a numerical modeling approach and the existing screening criterion developed for the aquifers was updated.The updated criterion for CO_(2)storage purpose would enhance the confidence level during the selection of deep saline aquifer and thus,help to address the climate change issue.The numerical modeling was carried out via CO_(2)STORE module of Eclipse300 Simulator to evaluate the effect of different levels of heterogeneity on CO_(2)storage potential.Different degrees of heterogeneity from homogenous systems to highly heterogeneous systems in the model were incorporated through the Lorenz coefficient.In this way,simulation of nine cases was carried out for three different aquifers with different porosity values.A comparison of these results showed that heterogeneity causes the aquifer to have lower storage capacity.On the trapping potential,dissolution trapping was significant and the amount of free gas in all cases was minimum.In addition,the aquifer with the highest level of heterogeneity(HLH)had a minimum fraction of residual trapping regardless of porosity.It was also found that final pressure at the end of 30 years is the same and high for low-level heterogeneity(LLH)and medium level heterogeneity(MLH)cases and low for HLH,while the injection rate stability duration is least for HLH and maximum for LLH.Based on the results obtained,it can be concluded that low to medium level heterogeneous aquifers with a good porosity can be a suitable choice for CO_(2)storage.

Analyzing the effect of steam quality and injection temperature on the performance of steam flooding

The heavy oil reservoirs are currently mainly targeted by thermal enhanced oil recovery technologies,particularly,steam flooding.Steam flooding is carried out by introducing heat into the reservoir to unlock the recovery of heavy oil by reducing oil viscosity.Several investigations were carried out to improve oil recovery by steam flooding.Most recently,high steam flooding is reported as an effective approach to improve recovery in high pressure heavy oil reservoirs.The oil recovery from steam flooding is sub-stantially affected by the steam quality and injection temperature.In this study,an attempt was made to look into the integration of parameters,i.e.steam quality and injection temperature upon steam flooding on oil recovery by using a simulation approach via ECLIPSE.The results obtained indicated that high temperature along with the moderate value of steam quality gives the best result regarding oil recovery for steam flooding in an economical way.