Average Energy Input Research Articles

Near-Inertial Response of a Salinity-Stratified Ocean

Abstract We study the near-inertial response of the salinity-stratified north Bay of Bengal to monsoonal wind forcing using 6 years of hourly observations from four moorings. The mean annual energy input from surface winds to near-inertial mixed layer currents is 10–20 kJ m−2, occurring mainly in distinct synoptic “events” from April–September. A total of fifteen events are analyzed: Seven when the ocean is capped by a thin layer of low-salinity river water (fresh) and eight when it is not (salty). The average near-inertial energy input from winds is 40% higher in the fresh cases than in the salty cases. During the fresh events, 1) mixed layer near-inertial motions decay about two times faster and 2) near-inertial kinetic energy below the mixed layer is reduced by at least a factor of three relative to the salty cases. The near-inertial horizontal wavelength was measured for one fresh and one salty event; the fresh was about three times shorter initially. A linear model of near-inertial wave propagation tuned to these data reproduces 2); the thin (10 m) mixed layers during the fresh events excite high modes, which propagate more slowly than the low modes excited by the thicker (40 m) mixed layers in the salty events. The model does not reproduce 1); the rapid decay of the mixed layer inertial motions in the fresh events is not explained by the linear wave propagation at the resolved scales; a different and currently unknown set of processes is likely responsible.

Insights into Nb-silicide-based in-situ composite processed by electron beam powder bed fusion

This is the first report introducing the idea of processing Nb-silicide-based in-situ composite through electron beam powder bed fusion (PBF-EB). A high energy input together with a line order strategy resulted in cracking, whilst a lower energy input without the line order led to microstructural inhomogeneity characterised by alternating dark- and bright-contrast bands. In samples printed using the line order strategy, long cracks initiated close to the melt pool boundary and propagated into the previous layer. These cracks were due to the weak interface between the primary Nb3Si columnar grains and the equiaxed (Nb,Ti) solid solution phase or Nb3Si-(Nb,Ti) solid solution eutectic structure. The porosity level increased from 0.122 % to 0.547 % with the increase of area average energy input from 2.22 J/mm2 to 6.67 J/mm2. The density decreased to 6.80 g/cm³ in the line order strategy samples due to the presence of cracks, compared to 6.84 g/cm³ in samples without employing the line order strategy. The dark-contrast band consisted of (Nb,Ti) solid solution, Nb3Si and Nb5Si3, while the bright-contrast band was composed of (Nb,Ti) solid solution and Nb3Si. Within the bright-contrast band, a recurring layered microstructural inhomogeneity appeared, with columnar grains at the bottom, whilst fine- and coarse-grained eutectic networks in the middle and upper regions. The Nb3Si phase exhibited a pronounced {001} texture, whereas the (Nb,Ti) solid solution phase displayed a weaker texture. The Nb-silicide-based in-situ composite fabricated through PBF-EB had a microhardness of ∼700 HV0.5. This value is higher than that achieved through conventional means but falls within the mid-range for laser-based additive manufacturing counterparts.

Investigating the Particle Formation Mechanism during Precipitation of Ni-Rich Hydroxide Precursors for Cathode Active Materials for Lithium-Ion Batteries

The industrial production of lithium-nickel-cobalt-manganese-oxides (LiNi x Co y Mn z O2, with x+y+z = 1) as cathode active material (CAM) for lithium-ion batteries is conducted by precipitation of a mixed metal hydroxide (Ni x Co y Mn z (OH)2) precursor (referred to as pCAM) in a stirred tank reactor, followed by a calcination of the pCAM with a lithium compound at elevated temperatures in a roller hearth kiln.1 Thereby, the physical properties of the resulting CAM powders are significantly affected by those of the associated pCAM.2 Independent of the material composition, the fluidity and filterability of pCAM and CAM powders deteriorates drastically with decreasing particle size, with non-uniformity of the particle size distribution, and with a deviation from a spherical particle shape.3,4 However, a fluent form of the pCAM and CAM powders is imperative for their further processing in tonnage quantities during pCAM and CAM manufacturing to prevent clogging of the powders in the technical equipment. As frequent cleaning and/or pulverization of the materials between process steps is cost-intensive, an economical and efficient manufacturing of pCAM and CAM powders requires a precise control of particle size and sphericity, which in turn requires an in-depth knowledge of the pCAM particle formation mechanism during the precipitation reaction.To gain a fundamental mechanistic understanding about the pCAM particle formation mechanism, the development of the secondary particle size and morphology during the semi-batch precipitation of Ni0.8Co0.1Mn0.1(OH)2 at various stirring speeds (between 550 and 1350 rpm) was monitored by light scattering and SEM imaging. The evolution of the volume-based median particle size (d 50) over the course of the run time (t run) at the different stirring speeds is depicted in Figure 1a. The d 50 of initial particles generated after 5 minutes as well as the d 50 after 8.75 h depends inversely on the applied stirring speed. After an initial nucleation time, the analysis in Figure 1b shows that the size of the approximatively spherical particles at a given stirring speed (for constant feed flow rates) increases linearly with respect to the third square root of run time/run time to the power of one third (t run1/3 ). Thus, the course of particle growth in each experiment can be divided into two distinct regimes: i) for t run1/3 < 1.0 (stage I in Figure 1b), the particle size remains essentially constant; ii) after this initial phase, for t run1/3 ≥ 1.0 (stage II in Figure 1b), the d 50 increases perfectly linearly with. It is concluded that during stage I, the seeding phase, an increasing number of particles with a constant size are being generated, since the overall volume of formed solid is increasing. In contrast, in stage II, the growth phase, the continuing precipitation occurs via deposition on already existing particles without any further increase in particle number, reflected by the linear relationship between particle size and t run1/3 .In light of these results, it is further demonstrated by SEM imaging that, during the seeding phase (stage I), irregularly shaped secondary particle agglomerates are formed, which in the subsequent growth phase (stage II) increase in size by growth of individual plate-like shaped primary particles. Moreover, it is shown that, at constant process parameters, the degree of turbulence quantified by the average energy input and the Reynolds number, both depending on the stirring speed, governs the initial agglomerate size formed during seeding. This not only dictates the growth rate, thus the final particle size, but also the ability of particles to become spherical over t run. Finally, a particle formation mechanism is proposed and compared to mechanisms described in the literature. Figure 1

Environmental life cycle assessment and energy-economic analysis in different cultivation of microalgae-based optimization method

The novelty of this study lies in its comprehensive exploration of microalgae cultivation methods, using energy-economic analysis and life cycle assessment (LCA) techniques, along with data envelopment analysis (DEA) to optimize energy and environmental impacts. The study provides insights into the energy requirements, productivity, net return, and environmental impacts of two common cultivation methods, open space and greenhouse. Results show that open space and greenhouse methods require an average input energy of 15920.40 and 17691.60 MJ kg−1, respectively, with energy ratios of 0.89 and 0.80 and productivity energy indexes of 0.06 and 0.02 kg MJ−1, respectively. The net return of open space and greenhouse methods is 204376.59 and 269276.06 ($ kg−1), productivity of 0.17 and 0.16 (kg $−1), respectively. The ReCiPe 2016 method is used to calculate environmental effects, with resource impact categories ranging from 201.11 to 205.68 USD2013. In terms of damage assessment categories, water and machinery and equipment have the highest share of damage assessment in both cultivation methods. DEA shows that total optimal energy consumption in the open space method is 14476.93 (MJ kg−1), resulting in a 7.55% decrease in energy consumption compared to the current cultivation. This is achieved by converting inefficient to efficient cultivation.

Stochastic resonance of multi-stable energy harvesting system with high-order stiffness from rotational environment

This paper aims to study the stochastic resonance of multi-stable energy harvesting system and enhance the performance of energy harvesting from random rotational environment. The influences of high-order stiffness terms and multi-stable characteristics are analyzed. The spectral amplification is derived to quantify the stochastic resonance for the energy harvesting system with penta-stable configuration driven by noise and periodic forcing. The non-monotonic dependence of spectral amplification on noise intensity indicates the existence of stochastic resonance. In particular, a critical high-order stiffness coefficient is revealed, for which the stochastic resonance is optimum. Meanwhile, the maximum of spectral amplification can be optimized by choosing appropriate unstable equilibrium positions. In addition, it is found that both the average input energy and the overall efficiency in power conversion can be further enhanced under conditions of stochastic resonance. Finally, the penta-stable energy harvester demonstrates a good performance in output power for different noise intensities and damping coefficients.

Artificial Neural Network Model to Forecast Energy Consumption in Wheat Production in India

Energy analysis in agriculture sector require modelling technique that can incorporate complex unknown interactions and non-linearity in systems. In this study Artificial neural network technique is used to model and forecast input energy consumed in wheat production in India and is compared for predictive accuracy with linear models. Household data from 256 farmers revealed that the average input energy consumed in region is 29612.43 MJ/ha with urea (47%), diesel (31.5%) and electricity (9.8%) being three main contributors. Multi-layered feed forward model with 2 hidden layers with 8 and 15 neurons respectively and sigmoidal activation function in hidden layers and output layers under gradient descent training algorithm gave the best results. The R2 was 0.99 for training dataset and 0.973 for validation data set, while for MLR model it was 0.95 and 0.73 for respective datasets. The root mean squared error (RMSE) in ANN model was 4779.2 MJ/ha and 2008.96 MJ/ha for training and validation data, respectively. This prediction system could forecast input energy with error margin of ± 7889.83 MJ/ha on training dataset and ± 3298.47 MJ/ha on validation data under various combinations. Sensitivity analysis showed that urea, diesel, and electricity are the important factors in input energy forecasting.

Disc-halo gas outflows driven by stellar clusters as seen in multiwavelength tracers

ABSTRACT We consider the dynamics of and emission from growing superbubbles in a stratified interstellar gaseous disc driven by energy release from supernovae explosions in stellar clusters with masses Mcl = 105 − 1.6 × 106 M⊙. Supernovae are spread randomly within a sphere of rc = 60 pc, and inject energy episodically with a specific rate $1/130~\mathrm{M}_\odot ^{-1}$ proportional to the star formation rate (SFR) in the cluster. Models are run for several values of SFR in the range 0.01 to 0.1 M⊙ yr−1, with the corresponding average surface energy input rate ∼0.04–0.4 erg cm−2 s−1. We find that the discrete energy injection by isolated SNe are more efficient in blowing superbubbles: Asymptotically they reach heights of up to 3 to 16 kpc for Mcl = 105 − 1.6 × 105 M⊙, correspondingly, and stay filled with a hot and dilute plasma for at least 30 Myr. During this time, they emit X-ray, Hα and dust infrared emission. X-ray luminosities LX∝SFR3/5 that we derive here are consistent with observations in star-forming galaxies. Even though dust particles of small sizes a ≤ 0.03 μm are sputtered in the interior of bubbles, larger grains still contribute considerably ensuring the bubble luminosity $L_{\rm IR}/{\rm SFR}\sim 5\times 10^7 \, \mathrm{L}_\odot \, \mathrm{M}_\odot ^{-1} ~{\rm yr}$. It is shown that the origin of the North Polar Spur in the Milky Way can be connected with activity of a cluster with the stellar mass of ∼105 M⊙ and the SFR ∼ 0.1 M⊙ yr−1 some 25–30 Myr ago. Extended luminous haloes observed in edge-on galaxies (NGC 891 as an example) can be maintained by disc spread stellar clusters of smaller masses M* ≲ 105 M⊙.

A study on bending deformation behavior induced by shot peening based on the energy equivalence

Shot peening is an essential process for forming large thin-walled components in aerospace industries. However, it is challenging to determine directly the mapping relationship between shot peening parameters and deformation response because of the complex elastic–plastic deformation of shot-peened components. In this paper, a computational model of bending deformation of peened plate samples is established by examining the shot peening behavior from the aspect of energy equivalence, in which the deformation energy of the shot-peened plate is determined by the total kinetic energy input due to the shot impacts and a correction factor that takes into account the influences of oblique impact, shot interaction and shot overlap on the peen forming process in practice. It is proven that the square of curvature radius is proportional to the cube of the thickness but inversely proportional to the indentation coverage and the average kinetic energy input of a single shot. For the effect of a single shot impact in peen forming, the average kinetic energy input of a single shot is a power function with the indentation diameter.

Assessment of carbon emission and primary energy input of a gasoline combustion-powered 2.0T SUV in China.

With the use of vehicles, large amounts of carbon dioxide are emitted by combustion of gasoline and energy consumes in their lifecycle. Therefore, the objective of this study is to evaluate the lifecycle carbon emission and primary energy input of a widely used sport utility vehicle (SUV) in China with the lifecycle assessment method. The results show that total petrol consumption of an SUV in lifetime is 21,300kg; the CO2 emissions and primary energy input in the manufacturing, assembly, operation, and decommissioning phase are respectively 8857, 443, 54,925, and 443kg and 123,413, 6171, 12,341, and 6171MJ. The average CO2 emission intensity and energy input intensity of materials are respectively 2.74kg/kg and 64.9MJ/kg. The primary energy input of materials in manufacturing phase occupies 83.3%, and CO2 emission in use phase is 64,267.3kg (occupied 92.62%), mainly attributed to the combustion of petrol.

Analysis of energy consumption in poultry management for table egg production in Nigeria

Energy audit and mass flow studies of commercial agricultural systems are increasingly becoming of utmost importance, due to high operation costs and dependence on energy. This research was designed to study energy input, output and efficiency for daily table egg production from commercially managed poultry birds. Three commercially operated poultry farms in Ibadan, Nigeria were visited for assessment of management procedures, data collection, equipment observation and personnel interview. The energy required for each management procedure was calculated from standard methods. Each farm housed average of 25,000 actively laying birds and had average daily egg production of 21,250 egg pieces. This amounted to 1169 kg egg and 3000 kg faecal materials production per day from the average energy input of 122,461.12 MJ/day. The highest energy consumption was biological energy which resulted from daily feed consumption of 3000 kg at the rate of 120 g per bird per day. This made up 83.81% of the total energy consumed. These resulted in an energy consumption ratio of 1.05, energy productivity of 0.034 kg/MJ, specific energy of 29.29 MJ/kg and net energy of 6,569.09 MJ/day, respectively. Faecal materials constituted the bulk of the output from the system. Making use of the faecal material in its treated form for the production of feed components would reduce energy costs, increase farmers’ net income and also encourage environmentally efficient processes.

A Cluster Analysis on the Energy Use Indicators and Carbon Footprint of Irrigated Wheat Cropping Systems

The objective of this study is to analyze the energy use efficiency and carbon footprint of irrigated wheat systems in different Iranian provinces. The authors resort to the k-means clustering technique to fulfil the said objective. The empirical results reveal that the average total input energy (59.5 GJ ha−1) is higher than the average energy output (45.82 GJ ha−1) from wheat production, resulting in an average energy efficiency of 0.77, thus rendering the production of irrigated wheat in Iran energy-inefficient on average. Among the thirty wheat-producing Iranian provinces considered in this analysis, only six—East Azerbaijan, Golestan, Ardabil, Kohgiluyeh and Boyer-Ahmad, Alborz, and West Azerbaijan—register an energy use efficiency greater than unity. The average total of greenhouse gas (GHG) emissions from irrigated wheat is 2243.54 kg CO2-eq ha−1 (with electricity and diesel fuel contributing 52.4% and 29.4%, respectively). The authors categorize the clusters into five groups ranging from sustainable to unsustainable. Five of the six provinces referred to earlier fall into the ‘sustainable’ category, with Bushehr being the sixth. The wheat production units in the ‘sustainable’ category can serve as a benchmark for the clusters in the other categories, which can move up the ladder of sustainability. The authors also recommend measures that policymakers can undertake to ensure the sustainable development of wheat production in Iran, fulfilling the social imperative of food self-sufficiency while truncating the environmental footprint and ensuring economic feasibility.

Pulsed electric fields using a multiple needle chamber to improve bioactive compounds extraction from unprocessed Opuntia ficus-indica fruits

Prickly pear fruit is rich in natural pigments and bioactive compounds that contribute to its antioxidant capacity and health-promoting properties. These compounds can be extracted using pulsed electric fields (PEF), a non-thermal technology that is energy efficient and is being increasingly used for food processing. For that end, a novel electroporation chamber was designed and optimum pulse parameters were selected maximizing juice yield and bioactive compounds extraction. The chamber consists of 5 rows of 10 parallel needles, and the optimum pulse parameters were: Sixty 100 μs long pulses of 1200 V/cm at a frequency of 10 Hz. The average energy input was 11.44 kJ/kg (temperature rise below 10 °C). When comparing PEF-treated samples with untreated ones, juice yield increased 3.3 times, and betalain extraction 1.48 times. Also, the juice extracted had a significantly higher total polyphenol content (1.4 times), and antioxidant capacity (1.4–1.5 times increase, measured by three techniques). This chamber and procedure could be scaled for industrial applications since large samples can be treated without the need of adding conductive medium or peeling the fruits, simplifying the procedure and reducing costs. PEF treatment of prickly pear fruits can effectively provide juice rich in natural colorants and with higher nutritional properties. • The designed chamber enables the treatment of whole fruit with no conductive medium. • PEF treated samples yielded 3.3 times more juice and 1.48 times more betalains. • Antioxidant capacity was 1.4–1.5 times higher compared to control. • The treatment chamber can be easily scaled up for industrial applications.

Comparison of energy use between fully mechanized and semi-mechanized rice production in Southwest China

This study performed energy analyses of fully mechanized rice production mode (FM) and semi-mechanized rice production mode (SM) in China. Fertilizer, fuel, and water were the three largest inputs, accounting for 92.02% of the total energy input. FM adopted side-deep fertilization with machine transplanting and implemented intermittent irrigation regime to improve water and fertilizer use efficiency. Compared with SM, FM reduced fertilizer and water energy inputs by 1252.62 MJ ha−1 and 2187.87 MJ ha−1, respectively. Because of the lower degree of mechanization, the fuel energy input of SM was 691.19 MJ ha−1 less than that of FM. The total average energy input of FM was 23,610 MJ ha−1, which was 10.80% lower than SM (26,470.01 MJ ha−1), whereas the rice and straw yields of FM were not significantly different from SM. The energy use efficiency, energy productivity, and energy profitability of FM were 11.10, 0.41 kg MJ−1, and 10.10, respectively, corresponding to increases of 8.56%, 8.61%, and 9.49% compared to SM. With appropriate agronomic measures in rice production, a higher degree of mechanization would not necessarily lead to an increase in energy input in Southwest China.

Stochastic resonance in periodic potential system with memory damping function

The stochastic dynamical system with memory effects describes a non-Markovian process that can happen in some complex systems or disordered media, such as viscoelastic media and living cell. Its velocity yields the memory effects because of the nonlocality in time, giving rise to a generalized Langevin equation for describing the dynamics of the system. In particular, the friction term in generalized Langevin equation is given by the time-dependent memory kernel. Besides, the research of stochastic resonance in periodic potential models emerges as an important subject because such systems have potential applications in diverse areas of natural sciences. However, the analysis of the influence of memory on stochastic resonance has not been reported so far in periodic potential model. In this paper, the phenomenon of stochastic resonance is investigated in the periodic potential system with friction memory kernel driven by an external periodic signal and internal noise. The generalized Langevin equation is converted into the three-dimensional Markovian Langevin equations. Analytical expression for the spectral amplification, together with the amplitude of the response, is derived in the periodic potential with an arbitrary number of simultaneously stable steady states, which can be applied to the general multi-stable dynamical model. The obtained results indicate that the curve of spectral amplification versus temperature exhibits a pronounced peak. Obviously, this typical phenomenon is a signature of stochastic resonance. The stochastic resonance effect is enhanced with the increase of the memory time or the number of stable steady states. For a certain range of the particle motion, the existence of an optimal number of stable steady states for which the output of the system can be maximized is established. Moreover, the phenomenon of stochastic resonance is studied according to the stochastic energetics. The average input energy per period is calculated over all the trajectories for quantifying stochastic resonance. It is found that the stochastic resonance effect is first weakened and then enhanced with increasing memory time. Specifically, under appropriate temperature conditions, there is an optimal memory time, which can maximize the work done by the external periodic force on the system.

Analysis and comparison of energy-economic-environmental cycle in two cultivation methods (seeding and transplanting) for onion production (case study: central parts of Iran)

Nowadays, production and consumption of inputs play an important role in agri-food sectors. But applying inappropriate management of input consumption results in negative environmental repercussions and reduced economic profits. So conducting a comprehensive study on the production process of products in terms of energy input flow, economic costs and environmental impacts could play a key role in suitable input management on the whole production cycle. Accordingly, the present study aimed to conduct an energy-economic-environmental on onion production in two cropping systems including seeding and transplanting. Required data were collected from 4 different seeding systems in Isfahan region (55 questionnaires) and 5 different transplanting systems in Semirom-Buin regions (50 questionnaires). Based on the results, for seeding onion system, the total energy input varied between 2973 and 3938 MJ. tonne−1 for system (Ι) and (ΙΙΙ), respectively, while for transplanting system, it varied between 2218 and 2339 MJ. tonne−1 for system (IV) and (Ι), respectively. The average energy input for seeding and transplanting systems was obtained as 3579 and 2322 MJ. tonne−1, respectively. Electricity and diesel fuel were identified as the most consumed inputs in all systems. In terms of production costs, labor had the highest contribution to the total costs in seeding and transplanting systems with the amount of 12.73 (32%) and 25.22 $. tonne−1 (58%), respectively. Based on the results obtained from the analysis of energy and economic indices, the integrated index of Energy Intensiveness was obtained as 90.54 and 53.50 MJ $−1 for seeding and transplanting systems, respectively, which shows the high energy-economic efficiency of transplanting systems compared to the seeding systems. LCA results related to the environmental impacts of onion production showed that in seeding and transplanting systems, Global Warming (GW) and Environmental Final Impact (EFI) were obtained as 24.7 and 4.65 kg CO2.eq. tonne−1 and 15.42 and 4.22 pPt. tonne−1, respectively. Direct emissions caused by input consumption (CO2, NH3 and NO3−), and indirect emissions caused by electricity generation and manure production were identified as the environmental hotspots in onion production. In seeding cropping systems of (Ι) and (ΙΙ) which followed by the post-harvest processes, the total energy input, input costs and EFI index were determined as 3527 MJ, 74.37 $ and 13.18 pPt per one tonne of stored crop in the cold storage and 5458 MJ, 138.74 $ and 32.89 pPt per one tonne of processed onion in processing plant, respectively. Results related to the post-harvest operations highlighted the necessity of investigation of whole cycle of agricultural crops (cradle-to-grave analysis).

3D graphene aerogel-supported copper azide nanoparticles as primary explosive with excellent initiation performance

Copper azide (CA), a high energy primary explosive, had been investigated with various supporter materials to reduce its sensitivity characteristics. However, effective supporter had not been designed to fully reduce CAs sensitivity characteristics. Hence, we presented a three-dimensional (3D) graphene aerogel-supported CA (CA-GAs) strategy to meet those needs. CA-GAs was prepared using 3D GA as the framework to uniformly grip CA. The SEM and XRD measurements revealed that CA nanoparticles were fully dispersed on GAs, the in-situ azidation reaction of Cu precursor and CAs crystalline structure were not affected by GAs. DSC further verified the thermal stability of CA-GAs. Moreover, electrostatic ignition experiment was employed to investigate CA-GAs’ ignition time, input energy, and electrical ignition performance. Those results showed that CA-GAs could be reliably detonated by a 3.5 [Formula: see text] SCB, the average electric ignition voltage, ignition time, and input energy of CA-GAs were 19.125 V, 21 [Formula: see text]s, and 0.56 mJ, respectively. All these results illustrated that GAs was an effective supporter for the stabilization of CA.

Energy optimization in wheat establishment following rice residue management with Happy Seeder technology for reduced carbon footprints in north-western India

Rice residue management (RRM) impacts ecosystems’ sustainability due to change in energy use, C footprints (CFs) and net ecosystem C budget (NECB). The energy input-output and CFs were audited to optimize energy use and C equivalent emissions (CE) in wheat following RRM with Happy Seeder using data collected from 53 farmers during face-to-face interview. Average total energy input (EI) of 23.5 GJ ha−1 produced output energy of 204.8 ± 2.9 GJ ha−1, with energy productivity (EP) of 0.24 kg MJ−1. The net energy gain (NEG) of 181.3 ± 3.0 GJ ha−1 was achieved with energy use efficiency (ER) of 8.81 ± 0.19. Chemical fertilizers were the major hotspots of energy (∼48.4% of EI) and CFs (∼59.2% of CE) in wheat cultivation. Data Envelopment Analysis (DEA) elucidated 23 decision making units (∼43% of total) as energy efficient, whilst 30 as inefficient with average technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) were 0.94, 0.97 and 0.94, respectively. DEA helped energy saving of 1462.8 MJ ha−1 (∼6.2%), mitigation of 107.8 kg CO2e ha−1 (∼7.6%) with significantly higher NECB of 716.4 kg C ha−1 (∼19.1%) due to change in soil organic C (ΔSOC) pool by 34.8 kg C ha−1 at efficient Happy Seeder sown wheat farms.

Meta-Analysis on Energy-Use Patterns of Cropping Systems in Iran

We present a meta-analysis of energy-consumption and environmental-emissions patterns in Iranian cropping systems using data collected from articles published between 2008 and 2018 for 21 different crops. The results show that the crops consuming the most energy per hectare are tomato, sugarcane, cucumber and alfalfa, while sunflower consumed the least. The average total energy input for all crops in Iran during the study period was 48,029 MJ ha−1. Our analysis revealed that potato has the highest potential to reduce energy consumption and that electricity and fertilizer inputs have the most potential for energy savings in cropping systems. Not all studies reviewed addressed the factors that create energy consumption patterns and environmental emissions. Therefore, eight indicators were modeled in this meta-analysis, which include Total Energy Input, Energy Productivity, Energy Use Efficiency, Net Energy, Greenhouse Gas Emissions, Technical Efficiency, Pure Technical Efficiency and Scale Efficiency. The effects of region (which was analyzed in terms of climate), year and crop or product type on these eight indicators were modeled using meta-regression and the nonparametric Kruskal–Wallis test. To create a comprehensive picture and roadmap for future research, the process of the agricultural-systems analysis cycle is discussed. This review and meta-analysis can be used as a guide to provide useful information to researchers working on the energy dynamics of agricultural systems, especially in Iran, and in making their choices of crop types and regions in need of study.

Analysis of Processing Hydrothermal Liquefaction of Microalgae Reaction Product with and without Dichloromethane Solvent for Biocrude Recovery

Producing biocrude from hydrothermal liquefaction (HTL) of microalgae has the potential to complement fossil fuels, while simultaneously reducing greenhouse gas emissions. However, biocrude recovery from the HTL reaction product has been a concern. In this study, analysis of yields and property of biocrude recovered with and without using dichloromethane (DCM) organic solvent was investigated. The HTL experiment were performed at reaction temperature of 350oC and 20 min reaction time using 16 w/w % solids each of Spirulina sp. and Tetraselmis sp. Data obtained showed that use of DCM favours maximum biocrude yield but of lower quality when compared with DCM-free biocrude. Biocrude yield of 58wt% was obtained from Tetraselmis sp. and 48wt% from Spirulina sp. when DCM was used. About 38 and 40wt% biocrude yields were derived with DCM-free recovery process. Higher carbon content, energy dense, and lower heteroatoms content constitutes biocrude recovered without DCM treatment, which is in contrast to the biocrude recovered with DCM. In addition, an average energy input of 13MJ/kg is required to produce unit biocrude, with an additional energy input ~0.5MJ/kg to evaporate DCM when used in biocrude recovery.Keywords— Bio-energy, Hydrothermal liquefaction, Microalgae, Organic solvent, Separation method

Energy Budgeting of Paddy-Pulse Cropping System in Bhadrak District of Odisha and Assessment of Emission from Paddy Straw Burning

Energy auditing of an existing production system helps to assess its energy-use and energy efficiency. The average input energy of paddy-black gram (PB) cropping system (19,862.01 MJ.ha-1) was higher than paddy-green gram (PG) (18,972.34 MJ.ha-1) cropping system in Bhadrak, Odisha. Harvesting and transport operation required highest operational energy for PG (35.57%) and PB (41.20%) farms; while, threshing and winnowing consumed the second highest input energy with 21.34% and 22.71% for PG and PB farms, followed by land preparation with 21.87% and 20.10% respectively. Linear regression data of PG and PB systems showed significant effect (p&lt;0.05) of predictors with R2 values of 87.70% and 82.20% for total output energy and grain energy, respectively; confirming a good fit among the data. The output energy of PB cropping system was 13.91% higher than that of PG cropping system. The PB cropping system, with energy utilisation efficiency (EUE) of 10.31 and 11.82, was more energy-efficient than PG system with EUE of 9.32 and 11.01 for “NC” and “C” farms, respectively. The net energy return of PBC farm was highest with 2,04,505.31 MJ.ha-1. Amongst various pollutants emitted from paddy straw burning in Odisha; CO2 (5,51,296.0 Mg.yr-1), CO (13,102.72 Mg.yr-1), and TPM (4,908.80 Mg.yr-1) had highest share. The quantity of major GHGs (N2O, CH4) released into the atmosphere through paddy straw burning was estimated as 26.43 Mg.yr-1 and 453.12 Mg.yr-1, respectively. Use of straw baler can prevent straw burning, and reduce emission from paddy fields by 2805.54 kg.ha-1 of CO2 and 66.69 kg.ha-1 of CO, 5.96 kg.ha-1 of NOx, 24.98 kg.ha-1 of TPM. Alternatively, use of mulcher can also reduce emission from paddy fields by 2924.44 kg.ha-1 of CO2 and 69.51 kg.ha-1 of CO, 6.21 kg.ha-1 of NOx, 26.04 kg.ha-1 of TPM. The cost of operation of a baler and mulcher were 8,617.0 ₹ ha-1 and 2,543.0 ₹ ha-1, respectively. Input energy and energy saved in paddy fields by baler were 820.0 MJ.ha-1 and 16,928.0 MJ.ha-1; and 266.0 MJ.ha-1 and 24,458.0 MJ.ha-1 by mulcher, respectively.