Repositioning fertilizer manufacturing subsidies for improving food security and reducing greenhouse gas emissions in China

China removed fertilizer manufacturing subsidies from 2015 to 2018 to bolster market-oriented reforms and foster environmentally sustainable practices.However,the impact of this policy reform on food security and the environment remains inadequately evaluated.Moreover,although green and low-carbon technologies offer environmental advantages,their widespread adoption is hindered by prohibitively high costs.This study analyzes the impact of removing fertilizer manufacturing subsidies and explores the potential feasibility of redirecting fertilizer manufacturing subsidies to invest in the diffusion of these technologies.Utilizing the China Agricultural University Agri-food Systems model,we analyzed the potential for achieving mutually beneficial outcomes regarding food security and environmental sustainability.The findings indicate that removing fertilizer manufacturing subsidies has reduced greenhouse gas(GHG)emissions from agricultural activities by 3.88 million metric tons,with minimal impact on food production.Redirecting fertilizer manufacturing subsidies to invest in green and low-carbon technologies,including slow and controlled-release fertilizer,organic-inorganic compound fertilizers,and machine deep placement of fertilizer,emerges as a strategy to concurrently curtail GHG emissions,ensure food security,and secure robust economic returns.Finally,we propose a comprehensive set of government interventions,including subsidies,field guidance,and improved extension systems,to promote the widespread adoption of these technologies.

Effect of rice cultivar on greenhouse-gas emissions from rice-fish co-culture

In aquaculture,co-culturing rice with fish may mitigate greenhouse-gas emissions.In this study,co-culture of four rice cultivars in a laboratory-scale rice–fish system reduced CH_(4)and N_(2)O emissions relative to fish monoculture.Differences in CH_(4)and N_(2)O emissions among rice cultivars primarily stem from the differential effects of rice plants on plant-mediated CH_(4)transport,CH_(4)oxidation and nitrogen absorption.

Greenhouse gas emission analysis and measurement for urban rail transit: A review of research progress and prospects

Rail transit plays a key role in mitigating transportation system carbon emissions.Accurate measurement of urban rail transit carbon emission can help quantify the contribution of urban rail transit towards urban transportation carbon emission reduction.Since the whole life cycle of urban rail transit carbon emission measurement involves a wide range of aspects,a systematic framework model is required for analysis.This research reviews the existing studies on carbon emission of urban rail transit.First,the characteristics of urban rail transit carbon emission were determined and the complexity of carbon emission measurement was analyzed.Then,the urban rail transit carbon emission measurement models were compared and analyzed in terms of the selection of research boundaries,the types of greenhouse gas(GHG)emissions calculation,and the accuracy of the measurement.Following that,an intelligent station was introduced to analyze the practical application of digital collaboration technology and energy-saving and carbon-reducing system platforms for rail transit.Finally,the urgent problems and future research directions at this stage were discussed.This research presents the necessity of establishing a dynamic carbon emission factor library and the important development trend of system integration of carbon emission measurement and digital system technology.

Gas drainage from different mine of drainage systems for deep coal areas： optimal placement seams with high gas emissions

The techniques of stress relief mining in low-permeability coal seams and pillarless gob side retained roadway entry using Y-type ventilation and gas drainage systems were developed to control gas outbursts and applied successfully. However, as the mining depth increasing, parts of the gas drainage system are not suitable for mines with high gas emissions. Because larger mining depths cause higher ground stresses, it becomes extremely difficult to maintain long gob side roadways. The greater deformation suffered by the roadway is not favorable lor borehole drilling for continuous gas drainage. To solve these problems, Y-type ventilation and gas drainage systems installed from a roof roadway were designed for drainage optimization. This system was designed based on a gas-enrichment zone analysis developed from mining the 11-2 coal seam in the Zhuji Mine at Huainan, Anhui Province, China. The method of Y-type gas extraction from different mine areas was applied to the panel 1112（1） in the Zhuji Mine. The absolute gas emission rate was up to 116.3 m^3/min with an average flow of 69.1 m^3/min at an average drainage concentration of nearly 85 %. After the Y-type method was adopted, the concentration of gas in the return air was 0.15 %-0.64 %, averaging 0.39 % with a ventilation rate of 2100-2750 m^3/min. The gas management system proved to be efficient, and the effective gas control allowed safe production to continue .

Prediction of Gas Emission Based on Infor-mation Fusion and Chaotic Time Series

In order to make more exact predictions of gas emissions, information fusion and chaos time series are com- bined to predict the amount of gas emission in pits. First, a multi-sensor information fusion frame is established. The frame includes a data level, a character level and a decision level. Functions at every level are interpreted in detail in this paper. Then, the process of information fusion for gas emission is introduced. On the basis of those data processed at the data and character levels, the chaos time series and neural network are combined to predict the amount of gas emission at the decision level. The weights of the neural network are gained by training not by manual setting, in order to avoid subjectivity introduced by human intervention. Finally, the experimental results were analyzed in Matlab 6.0 and prove that the method is more accurate in the prediction of the amount of gas emission than the traditional method.

Gas emission quantity prediction and drainage technology of steeply inclined and extremely thick coal seams

Gas emissions of workfaces in steeply inclined and extremely thick coal seams differ from those under normal geological conditions, which usually feature a high gas concentration and a large emission quantity. This study took the Wudong coal mine in Xinjiang province of China as a typical case. The gas occurrence of the coal seam and the pressure-relief range of the surrounding rock(coal) were studied by experiments and numerical simulations. Then, a new method to calculate the gas emission quantity for this special geological condition was provided. Based on the calculated quantity, a further gas drainage plan, as well as the evaluation of it with field drainage data, was finally given. The results are important for engineers to reasonably plan the gas drainage boreholes of steeply inclined and extremely thick coal seams.

Greenhouse gas emissions from a constructed wetland for municipal sewage treatment

The fluxes of greenhouse gases (methane and nitrous oxide) emission from a constructed wetland in the Eastern China as municipal sewage treatment were measured from June 1999 to August 2000 by the closed chamber method. The constructed wetland for municipal sewage treatment is a significant source of methane, up to 976 6×10 6 g CH 4/a, which was emitted from the constructed wetland with the area of 495000 m 2 and wastewater loading rate of 12000 m 3/d. Its daily mean methane flux reached 5 22 g CH 4/(m 2·d), 250 times as much as that in natural wetland in the same latitude region. 227 8 mg CH 4 was produced from the treatment of 1 liter wastewater, up to 700—1000 times as much as that in the secondary treatment. The emission of nitrous oxide from the constructed wetland is not higher than that from secondary treatment of wastewater, only 0 07 mgN 2O/L.

Characteristics of Gas Emission at Super-Length Fully-Mechanized Top Coal Caving Face

Characteristics of gas emission at the K8206 working face in the Third mine of the Yangquan Coal Group were investigated. The effects of strata movement,advancing velocity of working face,production capacity of working face and gas extraction capability of strike high-level entry on gas emission at K8206 working face were analyzed. A regression equation,reflecting the relationship between relative gas emission rate and the production capacity of work-ing faces,was established. Another regression equation showing the relationship between the gas emission rate from adjacent layers when the working face was advancing for one metre and advancing velocity was derived. It can be con-cluded that,1) the amount of gas emitted at the K8206 working face is far greater than that of ordinary top coal caving faces with a dip length of 180-190 m; 2) the dynamic process of gas emission from adjacent layers during the initial mining stage is controlled by the movement of key strata; 3) the amount of gas emitted that needs to be forced out by air is greatly affected by the capability of gas extraction; 4) when the advancing velocity is between 3.5-5.5 m/d or when the output is up to 8-12 kt/d,the gas emission from adjacent layers is almost constant.

Greenhouse gas emissions from shallow uncovered coal seams

This study discusses a method of quantifying emissions from surface coal mining that has been trialled in Australia. The method is based on direct measurement of surface emissions from uncovered coal seams in mine pits, concurrent measurement of residual gas content of blasted coal in mine pits, and measurement of pre-mining gas content of the same seam from cores retrieved from exploration boreholes drilled away from active mining. The results from one of the mines studied are presented in this paper. In this mine,the pre-mining gas content of the target seam was measured using cores from an exploration borehole away from active mining. Gas content varied from 0.7 to 0.8 m3/t and gas composition varied from16% to 21% CH4(84–79% CO2). In-pit measurements included seam surface emissions and residual gas content of blasted and ripped coal. Residual gas content varied from 0.09 to 0.15 m3/t, less than twofold across the mine pit. Composition of the residual gas was in general 90% CO2and 10% CH4, with slight variation between samples. Coal seam surface emissions varied from 1.03 to 7.50 mL of CO2-e per minute and per square meter of the coal seam surface, a sevenfold variation across the mine pit.

Dynamic prediction of gas emission based on wavelet neural network toolbox

This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time intervals through training the WNN with even time-interval samples. The method builds successive new model with the width of sliding window remaining invariable so as to obtain a dynamic prediction method for gas emission quantity. Furthermore, the method performs prediction by a self-developed WNN toolbox. Experiments indicate that such a model can overcome the deficiencies of the traditional static prediction model and can fully make use of the feature extraction capability of wavelet base function to reflect the geological feature of gas emission quantity dynamically. The method is characterized by simplicity, flexibility, small data scale, fast convergence rate and high prediction precision. In addition, the method is also characterized by certainty and repeatability of the predicted results. The effectiveness of this method is confirmed by simulation results. Therefore, this method will exert practical significance on promoting the application of WNN.

Cooperative prediction method of gas emission from mining face based on feature selection and machine learning

Collaborative prediction model of gas emission quantity was built by feature selection and supervised machine learning algorithm to improve the scientifc and accurate prediction of gas emission quantity in the mining face.The collaborative prediction model was screened by precision evaluation index.Samples were pretreated by data standardization,and 20 characteristic parameter combinations for gas emission quantity prediction were determined through 4 kinds of feature selection methods.A total of 160 collaborative prediction models of gas emission quantity were constructed by using 8 kinds of classical supervised machine learning algorithm and 20 characteristic parameter combinations.Determination coefcient,normalized mean square error,mean absolute percentage error range,Hill coefcient,mean absolute error,and the mean relative error indicators were used to verify and evaluate the performance of the collaborative forecasting model.As such,the high prediction accuracy of three kinds of machine learning algorithms and seven kinds of characteristic parameter combinations were screened out,and seven optimized collaborative forecasting models were fnally determined.Results show that the judgement coefcients,normalized mean square error,mean absolute percentage error,and Hill inequality coefcient of the 7 optimized collaborative prediction models are 0.969–0.999,0.001–0.050,0.004–0.057,and 0.002–0.037,respectively.The determination coefcient of the fnal prediction sequence,the normalized mean square error,the mean absolute percentage error,the Hill inequality coefcient,the absolute error,and the mean relative error are 0.998%,0.003%,0.022%,0.010%,0.080%,and 2.200%,respectively.The multi-parameter,multi-algorithm,multi-combination,and multijudgement index prediction model has high accuracy and certain universality that can provide a new idea for the accurate prediction of gas emission quantity.

A comprehensive investigation of loading variance influence on fuel consumption and gas emissions in mine haulage operation

The data collected from haul truck payload management systems at various surface mines show that the payload variance is significant and must be considered in analysing the mine productivity, diesel energy consumption, greenhouse gas emissions and associated costs. The aim of this study is to determine the energy and cost saving opportunities for truck haulage operations associated with the payload variance in surface mines. The results indicate that there is a non-linear relationship between the payload variance and the fuel consumption, greenhouse gas emissions and associated costs. A correlation model, which is independent of haul road conditions, has been developed between the payload variance and the cost saving using the data from an Australian surface coal mine. The results of analysis for this particular mine show that a significant saving of fuel and greenhouse gas emissions costs is possible if the standard deviation of payload is reduced from the maximum to minimum value.

CONTROL OF GAS EMISSION AT COAL FACE IN CHINA

All the underground coal mines in China are gassy mines. The gas emission at coal face increasingly grows with the increase of working depth and coal output, for example, the gas emission at a full mechanized coal face of mine No. 2 at Yongquan with a daily output of 2. 000t/d is up to 66-72m2/min. Special gas emission phenomena such as gas blowout, gas and coal outburst etc. have occurred at some faces, which threatens the safe production of face. obstructs the growth of productivity and limits the full play of mechanized equipment.In this paper, gas at face is divided, according to its origin, into three constituents, namely , coming from the coal wall, mined coal and goaf;and a formula for calculation is given. Also , the characteristics of the variation of gas emission at coal face, and the influence of mining sequence of a group of seams and supplied air quantity on the gas emission are discussed. Furthermore . based on the regularity of gas emission at coal face from the above three sources, and on the experiences of years, three principles on controlling gas emission at coal face are presented, that are managing the gas on classification basis, harnessing each source separately and comprehensive prevention and control. Finally, technical measures for prevention and treatment of the accumulation of gas in the upper corner of face, at the working place of coal-winning machine and in the bottom trough of conveyor are introduced.

Scenario analysis on abating industrial process greenhouse gas emissions from adipic acid production in China

Adipic acid is an important petrochemical product,and its production process emits a high concentration of greenhouse gas N_2 O.This paper aims to provide quantitative references for relevant authorities to formulate greenhouse gas control roadmaps.The forecasting method of this paper is consistent with the published national inventory in terms of caliber.Based on the N_2 O abatement technical parameters of adipic acid and the production trend,this paper combines the scenario analysis and provides a measurement of comprehensive N_2 O abatement effect of the entire industry in China.Four future scenarios are assumed.The baseline scenario(BAUS) is a frozen scenario.Three emission abatement scenarios(ANAS,SNAS,and ENAS) are assumed under different strength of abatement driving parameters.The results show that China's adipic acid production process can achieve increasingly significant N_2 O emission abatement effects.Compared to the baseline scenario,by 2030,the N_2 O emission abatements of the three emission abatement scenarios can reach 207-399 kt and the emission abatement ratios can reach 32.5%-62.6%.By 2050,the N_2 O emission abatements for the three emission abatement scenarios can reach 387-540 kt and the emission abatement ratios can reach 71.4%-99.6%.

Grey Smoothing Model for Predicting Mine Gas Emission

A grey smoothing model for predicting mine gas emission was presented by combining the grey system theory with the smoothing prediction technique. First of all, according to the variable sequence, GM(1,1) model was set up to predict the general development trend of variable as first fitted values, then the smoothing prediction technique was used to revise the fitted values so as to improve the accuracy of prediction. The results of application in the No.6 Coal Mine in Pingdingshan mining area show that the grey smoothing model has higher accuracy than that of GM(1,1) in predicting the variable sequence with strong fluctuation. The research provides a new scientific method for predicting mine gas emission.

Energy Consumption and Greenhouse Gas Emission of Korean Offshore Fisheries

This paper presents the energy and greenhouse gas(GHG) emission assessments of Korean offshore fisheries. The consumption of energy by fisheries is a significant concern because of its attendant environmental effect, as well as the cost of the fuel consumed in fishing industry. With the global attention of reducing GHG emission and increasing energy efficiency of fuel, the seafood industry needs to further understand its energy use and reduce its GHG emission. In the present study, the amount of energy consumed and the GHG emission of Korean offshore fisheries in a period from 2009 to 2013 were examined. Offshore fisheries accounted for 24% of Korean production in 2013 and 60% of fuel consumption related GHG emission. Whereas the total GHG emission intensity of this sector improved slightly between 2009 and 2012; as such emission decreased by approximately 1.9%, which increased again in 2013. The average amount of total GHG emission in this five years period was 1.78 × 10~6 tons of carbon dioxide equivalent/year(tCO_2eq. y^(-1)). Active fishing gear was found to consume 20% more fuel than passive gear. However, the production from passive gear was 28%, lower than 72% from active gear. The reason for this is that less abundant stationary resources are harvested using passive gear. Furthermore, the consumption of fuel was significantly influenced by the fishing method. Implementation and development of new fishing technologies and methods are important for improving energy efficiency and reducing the climate impact on fisheries. To realize these purposes, the fishery management system needs to be established by centralizing on energy efficiency and climate effect.

Effects of Biochar Application on Soil Properties, Plant Biomass Production, and Soil Greenhouse Gas Emissions: A Mini-Review

Biochar has been applied extensively as a soil amendment over the past decades. This review summarizes the general findings of the impacts of biochar application on different aspects from soil physical, chemical, and microbial properties, to soil nutrient availabilities, plant growth, biomass production and yield, greenhouse gases (GHG) emissions, and soil carbon sequestration. Due to different biochar pyrolysis conditions, feedstock types, biochar application rates and methods, and potential interactions with other factors such as plant species and soil nutrient conditions, results from those studies are not inclusive. However, most studies reported positive effects of biochar application on soil physical and chemical properties, soil microbial activities, plant biomass and yield, and potential reductions of soil GHG emissions. A framework of biochar impacts is summarized, and possible mechanisms are discussed. Further research of biochar application in agriculture is called to verify the proposed mechanisms involved in biochar-soil-microbial-plant interactions for soil carbon sequestration and crop biomass and yield improvements.

Hybrid optimization model and its application in prediction of gas emission

According to the complex nonlinear relationship between gas emission and its effect factors, and the shortcomings that basic colony algorithm is slow, prone to early maturity and stagnation during the search, we introduced a hybrid optimization strategy into a max-rain ant colony algorithm, then use this improved ant colony algorithm to estimate the scope of RBF network parameters. According to the amount of pheromone of discrete points, the authors obtained from the interval of net- work parameters, ants optimize network parameters. Finally, local spatial expansion is introduced to get further optimization of the network. Therefore, we obtain a better time efficiency and solution efficiency optimization model called hybrid improved max-min ant system （H1-MMAS）. Simulation experiments, using these theory to predict the gas emission from the working face, show that the proposed method have high prediction feasibility and it is an effective method to predict gas emission.

Energy return on investment, energy payback time, and greenhouse gas emissions of coal seam gas(CSG) production in China: a case of the Fanzhuang CSG project

The studies and development of coal seam gas（CSG） have been conducted for more than 30 years in China, but few of China＇s CSG projects have achieved large-scale commercial success; faced with the boom of shale gas, some investors are beginning to lose patience and confidence in CSG. China currently faces the following question： Should the government continue to vigorously support the development of the CSG industry？ To provide a reference for policy makers and investors, this paper calculates the EROI_（stnd）[a standardized energy return on investment（EROI） method], EROI_（ide）（the maximum theoretical EROI）, EROI_（3,i）（EROI considering the energy investment in transport）, and EROI_（3,1＋e）（EROI with environmental inputs） of a single vertical CSG well in the Fanzhuang CSG project in the Qinshui Basin. The energy payback time（EPT） and the greenhouse gas（GHG） emissions of the CSG systems are also calculated. The results show that over a 15-year lifetime, EROI_（stnd）, EROI_（ide）, EROI_（3,1）, and EROI_（3,1＋e）are expected to deliver EROIs of approximately11：1, 20：1, 7：1, and 6：1, respectively. The EPT within different boundaries is no more than 2 years, and the life-cycle GHG emissions are approximately 18.8 million kg CO_2 equivalent. The relatively high EROI and short EPT indicate that the government should take more positive measures to promote the development of the CSG industry.

Is pork trade good for China's greenhouse gas emissions?

China produces the largest amount of pork in the world, which emits the largest amount of greenhouse gases （GHGs）. This paper calculates GHG emissions from China＇s hog production at the provincial level using newly published emission factors~ Empirical results show that GHG emissions from China＇s hog production mainly respond to the scale intensity~ Capital abundance and income contribute positively to GI-IG emissions from hog production. Pork trade increases GHG emissions from China＇s hog produc- tion with a significantly direct effect, reduces GHG emissions through indirect technique effects.