15 results about "Microbial respiration" patented technology

The present application belongs to the field of sewage treatment, and particularly relates to a sewage treatment performance intelligent prediction method and device. The specific technical scheme is as follows: a sewage treatment performance prediction method, which takes the microbial respiration rate as a characteristic index for prediction. The present application uses the microbial activity index to construct an intelligent prediction model of the pollutant removal performance such as the pollutant removal rate in sewage, strengthens the description of the influence of the microbial action in the artificial intelligent model on the sewage treatment performance, and solves the problem that the model prediction result is inaccurate due to the lack of online data of water quality in the current numerous sewage treatment systems.

Aerobic microbial processes comprise culturing microbes comprising a (per)chlorate respiration pathway in a bioreactor in a bioprocess employing microbial respiration of chloroxyanions as a source of oxygen for the bioprocess, in the absence of external addition of molecular oxygen.

The invention provides a cultivated land quality monitoring system based on cultivated land protection, and relates to the technical field of agricultural management monitoring, and the system comprises the following modules: a data collection module which collects biological activity data including enzyme activity, earthworm biomass, microbial respiration rate and earth surface hardening index; the biological activity analysis module is used for constructing a biological activity digital model and outputting a soil biological activity index of the cultivated land to be detected; the degradation correction module is used for establishing degradation grades; and the quality evaluation module is used for correcting and adjusting the soil biological activity index based on the obtained degradation grading index, and outputting an evaluation result through the soil biological activity correction index. According to the method, multi-dimensional biological activity data such as enzyme activity, earthworm biomass, microbial respiration rate and earth surface hardening index are collected, and data consistency is ensured by using a standardization method, so that the limitation that a conventional technology depends on a single index is avoided; the defect that a traditional method neglects the influence of climate change accumulation is overcome.

The invention relates to the technical field of forestry monitoring, in particular to a forestry carbon sink dynamic monitoring method and system based on multi-source image data, and the method comprises the steps: collecting multi-source data to form a multi-source data set; inverting vegetation biomass and carbon density, initial reserve of organic carbon in surface soil and annual input of litter; calculating the decomposition rate and residual quantity of the litter according to the meteorological data; based on the soil initial carbon reserve, the litter input quantity and the microbial respiratory capacity, calculating the soil carbon library variation; integrating the dynamic process of the carbon library, and calculating the vegetation carbon variation and the total carbon sequestration amount per month; repeating the steps S1 to S4 periodically, updating data and parameters, and outputting a periodic carbon sequestration amount; and accumulating data to generate an annual carbon sink dynamic curve and a spatial distribution map. The dynamic carbon sequestration process is completely reflected, and the deviation with the actual carbon sequestration capacity is eliminated.

The invention relates to the technical field of agricultural ecology and resource environment, and discloses a planting and breeding cycle management method with synergism of reduced fertilization and soil remediation. The method comprises the following steps: deploying an in-situ soil sensing network integrated with a microbial respiratory activity electrochemical sensor, and obtaining soil physicochemical and biological activity data in real time; livestock and poultry waste resource product component online monitoring and crop multispectral nutrition inversion information are combined; a soil-crop-cultivation coupled dynamic state characterization model is constructed; and generating a cooperative regulation and control instruction of partition variable fertilization and directional field returning of the organic materials, and performing optimization execution through closed-loop feedback. Through multi-source data fusion and intelligent decision making, accurate reduction of the chemical fertilizer and synchronous improvement of the soil ecological function are achieved, nitrogen fertilizer application can be reduced on the premise of stable yield, and the diversity of soil organic matter and microorganisms is improved.

The application discloses a kind of determination methods of soil microbial carbon utilization efficiency, it is related to the determination field of carbon utilization efficiency, the application includes pre-culturing soil sample, multi-source 18 O Isotope gradient labeling, dynamic gas monitoring, dynamic correction of microbial respiration rate, microbial growth rate and carbon utilization efficiency acquisition, by multi-source isotope labeling, the contribution of different oxygen sources to microbial DNA synthesis is quantified, the low estimation of carbon utilization efficiency caused by traditional single labeling method is avoided, the limitation problem existing in the current soil microbial carbon utilization efficiency determination process is solved, gradient labeling reduces the inhibitory effect of local concentration on microbial metabolism, improves the uniformity of labeling, sets multiple soil samples, simultaneously uses dynamic monitoring to capture the real-time change of microbial respiration, eliminates the influence of isotope fractionation on carbon dioxide concentration calculation, avoids the instantaneous error of traditional static measurement, to a certain extent, the accuracy of analysis result is improved.

The invention discloses a forest carbon sink meteorological influence assessment method, system, device, medium and product, and relates to the field of ecological environment, the method comprises the following steps: based on meteorological data, adopting an individual-based forest carbon income and expenditure model to estimate an actual forest carbon sink amount; estimating a potential forest carbon sink amount based on a difference value between the potential net primary productivity and a soil microorganism respiration carbon consumption amount; based on the actual forest carbon sink amount and the potential forest carbon sink amount, establishing a forest carbon sink climate utilization rate estimation model by using a ratio method, and calculating a forest carbon sink climate resource utilization rate; based on the forest carbon sink climate utilization rate, constructing a forest carbon sink meteorological influence evaluation model by adopting a distance-average percentage method, and calculating a forest carbon sink meteorological influence index; and determining a forest carbon sink meteorological influence grade based on the forest carbon sink meteorological influence index, and completing forest carbon sink meteorological influence evaluation. According to the method, the carbon sink function of the forest ecosystem and the response of the carbon sink function to meteorological condition changes can be quantitatively and dynamically evaluated.

The invention provides a strip mine waste dump ecological system carbon sink evaluation method and device and electronic equipment, and relates to the technical field of environmental science and ecological restoration, and the method comprises the steps: determining remote sensing characteristic parameters based on multispectral remote sensing image data of a strip mine waste dump; constructing a vegetation net primary productivity model based on the remote sensing characteristic parameters and ground actual measurement data, and performing inversion to generate an estimated value of vegetation net primary productivity NPP; constructing a soil carbon storage model based on the soil sample index data and the microbial respiration intensity, wherein the soil carbon storage model is used for predicting soil carbon storage capability index data; and according to the NPP estimated value of each target soil sample area generated by the NPP model in each time period and the corresponding soil carbon storage capacity index data, determining a soil dump carbon sink space-time distribution result, thereby solving the technical problem that the carbon sink capacity is difficult to accurately and dynamically assess in the prior art, and improving the carbon sink capacity evaluation efficiency. The spatial-temporal dynamic accurate evaluation of the carbon sequestration capability of the ecological system of the strip mine dumping site is realized.

The invention discloses a graphene 13C isotope-based haloxylon ammodendron seedling marking method. The method comprises the following steps: carrying out double-peak pit soil preparation by taking a root of a haloxylon ammodendron seedling as a center; the double-peak pits sequentially comprise a first pit, a first peak, a second pit, a second peak and the earth surface from inside to outside by taking the root of the haloxylon ammodendron seedling as the center; a graphene 13C isotope water-soluble fertilizer is applied to a first pit of the double-peak pits; placing a carbon dioxide absorption device; laying a thin film to cover the double-peak pits, so that the first pit becomes a closed space; according to the method, photosynthesis of the haloxylon ammodendron seedlings is effectively isolated from carbon dioxide generated by respiration of the graphene water-soluble fertilizer and soil microorganisms, so that carbon dioxide with < 13 > C isotope released by respiration of the microorganisms is prevented from being absorbed by photosynthetic organs of plants, and a reliable solution is provided for marking and tracing the haloxylon ammodendron seedlings by adopting the graphene < 13 > C isotope.

The invention discloses a soil carbon sequestration and recarburization optimization method based on artificial intelligence, and relates to the technical field of soil carbon sequestration and recarburization. The method comprises the following steps: acquiring a soil internal data set and a remote sensing image data set of soil in a target area; constructing a time prediction model based on an LSTM network, inputting a soil internal data set, and outputting a future soil carbon content change rate; constructing a spatial distribution prediction model, inputting a remote sensing data set, and outputting soil carbon density spatial distribution; combining the change rate with the spatial distribution by using a weighted fusion algorithm to calculate a soil carbon reserve prediction value, and further obtaining the soil carbon sequestration capability; determining a microbial respiration rate, calculating carbon content natural loss in combination with soil oxygen content, and then obtaining soil carbon sink potential in combination with carbon sequestration capacity; and grading the target area according to the carbon sink potential, and implementing carbon sequestration and recarburization measures for areas with different potential grades. By integrating multi-source data, soil carbon content coupling analysis is realized, and the pertinence of carbon sequestration and recarburization measures is optimized.

The application discloses a kind of soil carbon sequestration and carbon increase optimization method based on artificial intelligence, and the application relates to soil carbon sequestration and carbon increase technical field.The steps of the method include: obtaining the soil internal data set and remote sensing image data set of the target area soil;Based on LSTM network, a time prediction model is constructed, the soil internal data set is input, and the future soil carbon content change rate is output;A spatial distribution prediction model is constructed, the remote sensing data set is input, and the soil carbon density spatial distribution is output;The change rate and spatial distribution are combined using a weighted fusion algorithm to calculate the predicted value of soil carbon storage, and then the soil carbon sequestration capacity is obtained;Determine the microbial respiration rate, calculate the carbon content natural loss combined with the soil oxygen content, and then obtain the soil carbon sink potential combined with the carbon sequestration capacity;According to the carbon sink potential, the target area is classified, and carbon sequestration and carbon increase measures are implemented for different potential level areas.The application integrates multiple data sources to realize soil carbon content coupling analysis, and then optimizes the pertinence of carbon sequestration and carbon increase measures.

The application discloses a device and method for accelerating redox oscillation region microbial advanced oxidation degradation of pollutants based on electric stimulation, and belongs to the field of bioelectrochemistry and advanced oxidation technology. The application provides a device for accelerating redox oscillation region microbial advanced oxidation degradation of pollutants based on electric stimulation, which comprises a computer, a data line, an electrochemical workstation, a wire, a glassy carbon electrode, a gas guide pipe, an aeration head, a screw neck bottle, a sealing plug with three Φ6 through holes, a nitrogen gas cylinder and an air gas cylinder. The application can accelerate the degradation of pollutants by strengthening microbial respiration and accelerating dissimilatory iron reduction and hydroxyl radical generation through electric stimulation. Unlike traditional microbial electrochemical methods that promote pollutant decomposition through electrode reaction, the application can significantly reduce the high requirements of bioelectrochemical methods on electrode materials and power consumption, and can provide a new method for the application of microbial electrochemistry in pollution remediation.

The application discloses a rhizosphere sedimentation carbon flux real-time monitoring method using a sensor array, relates to the technical field of soil carbon cycle monitoring, and is based on the three-dimensional distribution characteristics of target plant roots to determine a layered sampling depth and a horizontal concentric circle partition range and map to a preset three-dimensional grid coordinate system; gas sensors and environmental parameter sensors are arranged according to root partition to construct a multidimensional sensor array. The application realizes accurate spatial mapping of rhizosphere carbon flux through a three-dimensional grid coordinate system and a root density gradient model, utilizes vertical layering and horizontal concentric circle partitioning to ensure that the sensor arrangement is highly matched with the root biomass distribution, and the collaborative arrangement of the gas sensors and the environmental parameter sensors can capture root secretion pulse, microbial respiration and other transient changes, generate continuous and consistent carbon flux data sets, and provide a high-resolution dynamic observation basis for the study of plant-soil-microorganism interaction.

The utility model discloses a soil microorganism detection device and relates to the technical field of soil detection equipment. The device comprises a sampling assembly and a detection assembly, the sampling assembly comprises a collecting cylinder and a sampling needle tube, a connecting sleeve fixedly arranged at one end of the sampling needle tube is fixedly sleeved at one end of the collecting cylinder, and the detection assembly comprises a gas guide rod and a detection box. A piston edge is fixedly arranged on the outer side of one end of the air guide rod and slidably sleeved with the collecting cylinder. According to the utility model, the piston edge at the lower part of the gas guide rod is sleeved in the collecting cylinder, the sampling needle tube sucks the soil water immersion liquid into the collecting cylinder, carbon dioxide generated by respiration of microorganisms in the soil water immersion liquid is conveyed into the kit for reaction through the gas guide rod, and the content of the microorganisms in the soil is judged according to the reaction degree, so that the detection efficiency is improved; the sampling needle tube is inserted into soil needing to be measured, and the sampling needle head is inserted into the corresponding depth according to the needed depth, so that different soil depths can be quickly measured.

The invention discloses a mine restoration area vegetation base material performance identification monitoring system. The system comprises a base material sample collection module, a multi-parameter sensing detection module, a data transmission processing module, a performance parameter calculation module, a bacterial colony activity analysis module and a vegetation resistance monitoring module. The base material sample acquisition module acquires different soil layer samples, and the multi-parameter sensing detection module synchronously detects the water content, the nutrient concentration and the pH value; the data transmission processing module guarantees data integrity and accuracy through dual-mode transmission and noise filtering; the performance parameter calculation module generates water and fertilizer retention comprehensive parameters; the bacterial colony activity analysis module outputs bacterial colony activity data in combination with the microbial respiration rate and the ATP concentration; and the vegetation resistance monitoring module is associated with environment and vegetation data to complete cold-resistant and drought-resistant monitoring. The system realizes multi-parameter real-time monitoring and correlation analysis of the base material, replaces traditional manual sampling analysis, improves data timeliness and integrity, and provides support for dynamic adjustment of a mine repair scheme.