However, if we take GOR or production water temperature as the target, the optimal structure of the hybrid system is the fifth or the seventh option. The obtained results are helpful in structural optimization of the hybrid system with aspects of operational cost reduction, maximum GOR, or minimizing the wastewater discharge.Based on the mathematical modeling and operational optimization studies of reverse osmosis (RO) and multistage flash (MSF) desalination, the structural optimization of the hybrid process was specially studied in this work with the consideration of reducing comprehensive expenses under given operational conditions. Firstly, according to the process mechanism and flowchart of the RO and MSF seawater desalination technologies, seven hybrid structures with different feed conditions were designed, and their connection equations were established for numerical calculation. Then, in order to evaluate the economic performance of the hybrid systems with different structures, the hourly average operational cost equations of RO and MSF processes were established and formulated as the comprehensive evaluation indicators. Next, with a given water production requirement, simulation calculations of the hybrid system with seven different structures were performed. The results show that the hybrid system with the fourth structure has the lowest operational cost of 4.6834 CNY/m The lack of fresh water resources is an indisputable fact, and desalination technology is an effective strategy to solve this problem ,2. At prIn many regions where there are no renewable energies or nuclear energy available, the hybrid desalination technologies for full utilization of energy and cost saving were also studied by researchers. Kuenstle et al.  proposedFor the detailed quantitative analysis and performance prediction requirement to guide the hybrid system’s application, a series of modeling, simulation, and optimization works have been carried out at home and abroad. The relevant characteristics of the hot-film hybrid system is deeply understood by using the calculation tool. Cardona et al.  studied Wu et al.  adopted The above studies have confirmed the advantages and prospects of the MSF-RO system, and carried out relevant work in the aspect of optimal control. However, there are still some works that should be done for better guiding the structural and operational optimization of the MSF-RO system, especially in the plants who need to upgrade their RO or MSF system and achievement better operational profits. In this work, based on our earlier studies of full-scale detailed mechanism models of SWRO and MSF systems, detailed structural optimizations of the MSF-RO system under certain operational conditions and with techno-economics indexes are studied. After establishing the complete mechanism models of MSF and SWRO systems, according to the different feeding, mixture, and separation forms of the MSF-RO system, seven structural combination forms are designed and modeled for numerical calculation, and furthermore, the economic and performance equations are established for comparative analysis end scheme evaluation. Our work is helpful to guide structural optimization and detailed quantitative analysis of the MSF-RO system.The OT-MSF system and SWRO system feed water independently;The BR-MSF system and SWRO system feed water independently;The last stage flash water of the OT-MSF system is the feed water of the SWRO system;The last stage flash water of the BR-MSF system is the feed water of the SWRO system;The brine in the thermal discharge section of the BR-MSF system is used as the feed water of the SWRO system;The rejected water of the SWRO system is used as part of the feed water of the OT-MSF system;The rejected water of the SWRO system is used as part of the feed water of the BR-MSF system.In order to deeply analyze the impact of its feeding mode on the economy of the hybrid MSF-RO seawater desalination system, this paper proposes seven hybrid schemes of the MSF-RO system according to different feeding conditions:In order to facilitate the analysis and make the study more targeted, in this work, the MSF desalination adopted 16-stage OT-MSF and BR-MSF systems, respectively. The SWRO system adopted the SW30HR-400i spiral-wound RO modules, and put seven RO modules in each pressure vessel. The whole system depends on the actual situation to determine the number of pressure vessels. Since the mechanism models of MSF process and SWRO process have been established by our earlier work and can be referred in literatures, the model equations of the MSF and SWRO system that were used in our work were not listed in this paper. The steady-state models of OT-MSF and BR-MSF systems can be seen from Mujtaba ,27,28, WAs is shown in the 1:Mixer M2:Mixer MThe hybrid option 1 only affects the water production temperature and concentration of the coupling system, and has no effects on the overall water production of the system. It can be used as the basic scheme for hybrid scheme comparison.As is shown in the 1:Splitter S2:Splitter S1:Mixer M2:Mixer M3:Mixer M1, S2, and the mixer M1 are self-owned by the BR-MSF system. As in hybrid option 1, option 2 only couples the system water production and brine water, which has an impact on the water production temperature and concentration of the hybrid system, but has no impact on the overall water production of the system.In the hybrid option 2, the splitters SBDW1 in the OT-MSF system is used as the feed water FW2 of the SWRO system, removing the seawater pretreatment link in the SWRO system. Its flow chart is shown in In the hybrid option 3, part of the blowdown water 1:Splitter S1:Mixer M2:Mixer MWBD1 in the BR-MSF system is used as the feed water FW2 of the SWRO system, and the seawater pretreatment in the SWRO system is removed. Its flow chart can be seen in the Similarly to the hybrid situation of option 3, in option 4, part of the blowdown water 1:Splitter S2:Splitter S3:Splitter S1:Mixer M2:Mixer M3:Mixer MWr1 of the BR-MSF system is used as the feed water FW2 of the SWRO system. At this time, the temperature of the feed water in the SWRO system is increased, and the whole process of seawater pretreatment is removed. At this time, the entire hybrid system aggregates the production water and wastewater of the two subsystems. At this time, the overall water production and quality of the system are affected.The process flow diagram can be seen in the 1:Splitter S2:Splitter S3:Splitter S1:Mixer M2:Mixer M3:Mixer MAmong the five options mentioned above, the output of the MSF system is used as the feed water of the SWRO system. Options 6 and 7 are compared, on the other hand, with the wastewater from the SWRO system and part of the seawater as the feed water for the MSF system.rjW of the SWRO system is used as the feed water FW1 of the OT-MSF system. In option 6, the blowdown water Coupling system blowdown:1:Mixer M2:Mixer MrjW of the SWRO system is used as the feed water FW1 of the BR-MSF system. In option 7, the blowdown water Coupling system blowdown:1:Splitter S2:Splitter S1:Mixer M2:Mixer M3:Mixer MIPOC;Preliminary energy consumption cost CHOC;Chemical cost ENOC;Operating energy consumption cost MEROC;Reverse osmosis membrane replacement cost MNOC;Maintenance cost LBOC1;Labor costs WSOC1.Wastewater management cost The economic model discussed in this article is an hourly operating cost model, and the investment cost is ignored due to the unequal years of plant service life. The operation cost of the SWRO system mainly includes the following seven parts:The relevant expression of the corresponding operation cost of each part is as follows:IPOC:inP refers to the outlet pressure of the water intake pump, which is 5 bar; FW2 is the feed water flowrate; elcP is the price of electricity; PLF is the load factor, which is 0.9; The preliminary energy consumption cost of SWRO system refers to the energy consumption cost of water intake and pretreatment. CHOC:The cost of chemical agents mainly includes various acid reagents, scale inhibitors, flocculants, and other additives that change the water hardness.ENOC:fP denotes the feed water pressure, which is 65 bar; rP is the outlet pressure of concentrated brine; rjW refers to the concentrated brine outlet flowrate; MEROC:MEPri is the unit price of the RO membrane, 6200 CNY/group; MOD refers to the total number of RO membranes used in the system; MNOC:MNCONOC and the cleaning and maintenance cost of reverse osmosis membrane module MNCLOC. clN is the number of membrane module cleanings in a membrane replacement cycle; mrX is the membrane replacement cycle; OTOC is the cost of chemicals in membrane cleaning; PCOC is the system startup and shutdown costs incurred by the cleaning operation.The maintenance cost of the SWRO system is composed of the maintenance cost of conventional equipment LBOC1:LBN refers to the number of labors. DNW2 represents the water production of the SWRO system, and NP refers to the number of pressure vessels in the system.WSOC2:rjW is the blowdown water from the SWRO system.This article studies the operation plan of the system within the day, and the cost of RO membrane cleaning can be ignored. Therefore, Equation (36) can be rewritten as Equation (41) as shown:The total cost of SWRO system can be formulated as follows:STOC;Heating steam, ELOC;System power consumption cost, MTOC;Maintenance cost, PROC;Pretreatment cost, MNOC;Maintenance cost, LBOC2;Labor costs, WSOC2;Wastewater management cost, Likewise, the economic model of the MSF seawater desalination system is only for the hourly operating cost model. It mainly includes the following six parts, namely:The relevant expression of the corresponding operation cost of each part is as follows:STOC:The MSF system economic model can be seen from Gao et al. , and theELOC:MTOC:PROC:LBOC2:WSOC2:The specific cost of the above six parts, which make up the total hourly operational costs of the MSF system can be expressed as:7 kg/h = 1.203 × 104 m3/h.The feed seawater flowrate of the OT-MSF system and the SWRO system are both 1.203 × 10The heating steam temperature is 97 °C.3, and the feed seawater concentration of the SWRO system is 30 kg/m3. Because the pretreatment requirements of the system are inconsistent, the feed seawater concentrations of MSF system and RO system are different.The feed seawater concentration of the OT-MSF system is 5.7% = 57 kg/mThe unit price of single RO membrane of SWRO system is 6200 CNY.The economic model of MSF-RO system is composed of the economic model of MSF system and SWRO system. In order to evaluate the economy of the hybrid model, the economic models of the OT-MSF system and the SWRO system need to be verified respectively. For the MSF system, the OT-MSF system is selected for economic model verification. This study only discusses the case that the seawater temperature is 25 °C and the electricity price is 0.67 CNY/KW h. The verification premises of the economic model of MSF-RO hybrid system are as follows:Substitute the above parameters into the SWRO system economic model, and the IPOPT and CONOPT solver of the GAMS platform is called for simulation . The SWRThe above parameters were substituted into the OT-MSF system economic model, and simulated on the GAMS platform. The OT-MSF system water production and system cost ratio are shown in 3, and for the OT-MSF system, the unit price of water production is 7.63 CNY/m3. The ratio of the MSF system to the SWRO system’s water price is 0.4594, and Fan [ENOC accounts for the highest proportion of the overall cost, exceeding 50% of the overall cost, and the remaining costs account for a small proportion. It can be seen from STOC accounts for the highest proportion of the overall cost, followed by the system power consumption cost, and the remaining costs account for a relatively low proportion. On the whole, the operation cost of SWRO and MSF system is 1:2, and both account for the highest proportion in the power consumption of the two processes.Under the same water intake flowrate conditions, the total price and cost ratio of the water production cost of SWRO and MSF systems can be obtained, respectively. For the SWRO system, the unit price of water production is 3.51 CNY/m and Fan  et al.’s3/h, the SWRO system stipulates that the water production is 2000 m3/h. The relationship between the water production flowrate of the two systems is 1:2, and the overall water production flowrate is 3000 m3/h. The detailed model of the coupled system with different structures are coded and implemented under the platform of GAMS 24.0, and the IPOPT was used as the solver to solve the complex nonlinear programming problems.In order to quantitatively evaluate the economy and water production performance of the MSF-RO system with different feeding modes, it is necessary to fix the water production and water production ratio of each option. According to the research of Helal et al. , assumin3. For the OT-MSF system, the total operating cost is 7422.27 CNY, of which the running energy consumption accounts for 27.21%. Additionally, the unit price of OT-MSF water production is 7.4223 CNY/m3. Both systems account for a large proportion of energy consumption costs.The simulation results are shown in It can be seen from 3. For the BR-MSF system, the total operating cost is 7397.14 CNY, of which the running energy consumption accounts for 26.81%. The unit price of BR-MSF water production is 7.3971 CNY/m3. Combining The simulation results of the SWRO and BR-MSF system costs in option 2 are shown in It can be seen from 3/h and 92.66 m3/h. In options 1 and 3, the feed water flowrate of OT-MSF system is the same. In option 3, the feed water of the SWRO system is part of the wastewater from the OT-MSF system. Due to the high production temperature of the OT-MSF system, the permeation flux of the SWRO system is improved, so the feed water flowrate of the SWRO system of option 3 is lower than that of the SWRO system of option 1. In addition, option 3 reduces the wastewater management cost of the OT-MSF system. It can be seen from The cost simulation results of SWRO and OT-MSF systems in option 3 are shown in The cost-simulation results of SWRO and BR-MSF systems in option 4 are shown in 3. For the BR-MSF system, the total operating cost is 7287.39 CNY, of which the running energy consumption accounts for 27.21%. The unit price of BR-MSF system water production is 7.2874 CNY/m3.In the option 5, rejected water in the BR-MSF system is used as the feed water of the SWRO system. The cost simulation results of SWRO and BR-MSF systems in option 5 are shown in According to 3. For the OT-MSF system, the total operating cost is 7266.67 CNY, of which the running energy consumption accounts for 27.28%. The unit price of SWRO system water production is 7.2667 CNY/m3.Differently from options 3, 4, and 5, in option 6, seawater and part of blowdown in the SWRO system are used as feed water of the OT-MSF system. The cost simulation results of SWRO and OT-MSF systems are shown in According to 3. Due to the economic advantages of the BR-MSF system in water production, option 7 has lower water production price than option 6, but compared with option 4, the economic advantages are insufficient. Because option 4 utilizes the waste heat of the BR-MSF system, the utilization rate of water resources is improved.In option 7, the seawater and part of blowdown in the SWRO system are used as the feed water of BR-MSF system, which saves the feed water of BR-MSF system, comprehensively improves the water production quality of SWRO system and reduces the blowdown. The simulation results are shown in 3, and option 1 has the highest water production price at 4.8115 CNY/m3. Option 4 is that the last-stage flash water from the BR-MSF system is used as the feed water of the SWRO system, which saves a lot of wastewater management costs of the BR-MSF system. Although the unit price advantage of system water production is not obvious, the total price of system water production is quite different.As shown in 3/h. Consistent with the comparison of system water prices, option 4 has an advantage in terms of system water price because of its blowdown flowrate.As shown in As shown in As shown in As shown in It can be seen from the results that option 4 ranks first among the seven options in terms of price and blowdown flowrate, and remains in the forefront in terms of water-making ratio. However, there is little difference between options 5 and 4 in terms of water-making ratio. Overall, option 4 has certain advantages and performs well in the four evaluation indexes. For the option 1 and option 2, they all rank last in the four evaluation indexes, with obvious disadvantages. The above results provide guidance for the feeding conditions of the MSF-RO system, and provide a certain basis for the subsequent optimization of system operation and the complexity of the hybrid option.3, which is obviously better than the other options. In addition, the fourth structural option can achieve the lowest wastewater blowdown. For minimizing the index of gained output ratio and production temperature, the seventh and the fifth option rank the first. More than that, from the numerical simulation and analysis, the evaluation index of the production price, blowdown flowrate, water production ratio, and water production temperature can all be obtained as well as those important state variables. Our work is helpful for the optimal operation and design of the MSF-RO system with detailed model-based numerical calculation. In the future work, more case studies for real plant application and the optimal control will be focused.In addition to combining a new energy-driven system with RO or MSF seawater desalination to achieve better economic and social benefits, studies of better combinations of MSF-RO systems to obtain more techno-economic profits are also very attractive. In this work, based on the mechanism models of RO and MSF processes, modeling and structural optimization of hybrid MSF-RO system is carried out with the consideration of seven coupled structures. The feeding, discharging, and mixing separation modules of the system are modeled and the operational economics, the evaluation indexed are built. Simulation and calculation of the hybrid system with the seven coupled structures leading to the profiles of techno-economic performance as well as specific state values. The results show that: the fourth structural option has the lowest operational cost with the value of 4.6834 CNY/m


For millimeter-wave (MMW) imaging security systems, the image resolution promisingly determines the performance of suspicious target detection and recognition. Conventional synthetic aperture radar (SAR) imaging algorithms only provide limited resolution in active MMW imaging, which is limited by the system. In terms of enhancing the resolution of a region of interest (ROI) image containing suspicious targets, super-resolution (SR) imaging is adopted via Bayesian compressive sensing (BCS) implemented by fast Fourier transform (FFT). The spatial sparsity of MMW ROI images is well exploited with BCS to achieve resolution enhancement without computational cost. Both simulated and measured experiments confirm that the proposed scheme effectively improves the resolution of ROI images. Millimeter wave (MMW) signals are widely used in remote sensing, communication, medicine, transportation and other fields. In particular, MMW radar possesses advantages such as high resolution, good penetrability, and an absence of harmful radiation. Thus, it constitutes an alternative for body inspection imaging ,2,3,4, wAs imaging resolution plays a key role in complex security recognition, its enhancement attracts considerable research interest. In order to raise the resolution, most studies have concentrated on improving the architecture of an active MMW system. In , a methoAlthough these methods ,9,10,11 Active MMW body inspection systems based on synthetic aperture radar (SAR) imaging theory usually provide sparse images due to the limited penetration of MMW. CS ,13,14 stThe remainder of this paper is organized as follows. In In an active MMW 3D holographic imaging system, a set of linear array is used to collect the echo signal in an all-round way by moving along the circular path while alternately scanning, and then, the 3D high-resolution images are obtained by the holographic imaging algorithm. According to SAR imaging theory, high resolution in the range dimension is achieved by transmitting and receiving wideband signals, while high resolution in the array dimension is achieved by synthetic aperture formed by array scanning, and high resolution in the azimuth dimension is achieved by synthetic aperture formed by array motion. The operating mode of the active MMW 3D holographic imaging system is shown in RV is the motion direction of the array, P is a scattering point of the scanning area. In the radar imaging coordinate system, X, Y, and Z correspond to the azimuth dimension, range dimension, and array dimension (height dimension) of the radar, respectively. In an active MMW 3D holographic imaging system, a set of linear array is used to collect the echo signal in a 360 degree pathway while alternately scanning, and then, the 3D high-resolution images are obtained by the holographic imaging algorithm. According to [c is the propagation speed of electromagnetic waves. The Fourier transform of  , we subsZh* in  for Zh in (Zh in  and remon (Zh in  can be wn (Zh in .(7)SKr,The first phase term in  is the cKr2−KZh2→Equation  is writtEquation .(9)SKr,z in St,t is the Fourier-transform variable corresponding to In , t is thhe SM in , the sighe SM in  are not The back-projection (BP) imaging algorithm ,22 can bSince  operate  for all Generally, in the process of body inspection, we can project the 3D image of a target on the X–Z plane through maximum projection to obtain its 2D projection image. Assume that the size of the original 3D holographic image along the X, Y and Z directions is In MMW 3D imaging, the resolution of the image is determined by the coverage of the wave number spectrum . According to the dispersion relationship of plane waves in free space or uniform medium, we haveB is the signal bandwidth of the system. As shown in For a wideband signal, the relationship between the bandwidth and the pulse width satisfies In theory, holographic imaging systems can be used to obtain the image with high resolution. However, in real active millimeter-wave imaging systems, the image resolution is degraded due to limitations of signal processing algorithms, such as bandwidth loss. From  to 20),,20), we Since the MMW imaging of the human body is three-dimensional and the MMW’s penetration is limited, all the 2D slice images of an active MMW 3D holographic image are sparse. Then, we take a 2D projection image for an example to demonstrate this sparsity, as shown in In the threat detection through MMW imaging, once the suspicious item is confirmed in the 2D projection image, we extract the part corresponding to the suspicious item 22), on tIn general, the noise term in  can be mAccording to sparse Bayesian learning  and Bayerding to  and Bayealent to .27)S^RS^R25)pSpS(25)pSγding to UsmFrom the above derivation, we can know that  includesIts conjugate gradient can be expressed asIn the iterative process, since the matrix Since the compressive sensing algorithm can enhance the resolution of a 2D slice image, a 3D super-resolution image can be obtained by executing the algorithm for each 2D slice image. Finally, according to , the 2D In addition to the effectiveness of BCS, its computational efficiency proves necessary for the MMW image SR. Commonly, CS based on FFT operation can be used to reduce the algorithm complexity of resolution enhancement. However, if we try to enhance the resolution of a whole three-dimensional image in a threat recognition task, the computational load still probably becomes unacceptable.In fact, in a MMW body inspection image, we just need to focus on the part where the suspected target appears instead of the others. As a result, once the suspected target is confirmed in the projected MMW-2D image, the corresponding ROI images can be yielded. According to the projection relation of these ROI images, the 3D image of the suspected target as well as its 2D slice images can be obtained. By the pixel depth, we can choose the slice images that can reflect the suspected target and then enhance the resolution of them through compressive sensing. Based on this idea, a regional 3D imaging SR technique is developed so as to significantly reduce the computational load and raise the accuracy of the object detection and recognition. The flowchart of the regional 3D image SR technique is shown in To demonstrate the effectiveness and accuracy of the compressive sensing SR algorithm, an echo simulation and 3D imaging experiment of 2D lattice point targets is designed in this section. The operation mode of the MMW 3D imaging system is shown in The image of lattice point targets and its 2D wave number spectrum are shown in In this experiment, the SR image size is set to twice the original image size, and the experimental result is shown in In order to illustrate the performance of the lattice point targets image SR, the 2D wave number spectrum after the outside of the effective region in In order to quantitatively give the results, the point target response functions before and after SR are shown in The imaging results of these lattice point targets imaging results show that the MMW 3D image SR method described in this paper is effective. The BCS algorithm can be used to significantly expand the wave number spectrum of the 2D image. In addition to improving the main lobe resolution of the targets, the image super-resolution algorithm also significantly reduces the side-lobe amplitude, which indicates that the image resolution and quality are greatly improved.In order to further verify the effectiveness and accuracy of this proposed regional image SR method, the MMW 3D imaging system of the human body is applied to collect the echo data of the human body and image it. The parameters of the system are shown in As shown in According to the regional 3D image super-resolution scheme, a pre-detection of suspicious targets is first performed on the 2D projection image of the MMW 3D image to obtain the ROI (as shown in the red box and blue box in The resolution of the system in this experiment is As shown in Due to the image sparsity of active MMW 3D imaging, this paper studies the method of MMW image SR based on wave number spectrum distribution and compressive sensing algorithm, and it develops a regional 3D image SR scheme to improve threat detection and recognition. First, the working principle and holographic imaging algorithm of the active MMW imaging system are discussed, and the wave number spectrum distribution and image sparsity of MMW 3D images are analyzed. Then, the echo data and 3D imaging of the lattice point targets are simulated according to the active MMW working mode, and the SR image reconstruction results verify the effectiveness and feasibility in image resolution enhancement and image quality improvement. Finally, the correctness of the proposed method in measured image resolution improvement is demonstrated by the human body imaging experiment.


Among them, the patch shape index (LSI), patch density (PD) and patch proportion in landscape area (PLAND) of forest land can affect the concentration of PM2.5, NO2, and SO2, respectively. The PLAND, PD, and LSI of grassland and farmland can also have an additional impact on the concentration of SO2 pollutants. The study also found that there was a significant threshold effect within the impact mechanism of urban green space landscape pattern indicators  on the concentrations of PM2.5, NO2, and SO2 air pollutants. The results of this study not only clarified the impact mechanism of the spatial pattern of urban green space on air pollutant concentrations but also provided quantitative reference and scientific basis for the optimization and updating of urban green space to promote public health.Relevant studies have demonstrated that urban green spaces composed of various types of plants are able to alleviate the morbidity and mortality of respiratory diseases, by reducing air pollution levels. In order to explore the relationship between the spatial pattern of urban green spaces and air pollutant concentrations, this study takes 37 garden cities with subtropical monsoon climate in China as the research object and selects the urban air quality monitoring data and land use type data in 2019 to analyze the relationship between the spatial pattern and the air pollutant concentration through the landscape metrics model and spatial regression model. Moreover, the threshold effect of the impact of green space on air pollutant concentrations is estimated, as well. The results showed that the spatial pattern of urban green space was significantly correlated with the concentrations of PM The emergence and development of modern urban green spaces are closely related to the improvement of human living environments and public health . As an ihttps://www.who.int/zh/ (accessed on 15 July 2021)). Numerous studies have verified that short-term or long-term exposure to air pollutants, including PM2.5, PM10, NO2, and SO2, increased the risks of mortality and morbidity, thereby posing a severe threat to the public health of the residents . Therefore, when the landscape shape index of the forest is 18.02, the minimum concentration of PM2.5 reaches 37.94 μg/m3. Therefore, this study found that the LSI value of 18.02 is the threshold of forest land (est land .2 concentration (p < 0.1); therefore, the study determined the range of both thresholds by analyzing the trend of the effect of NO2 concentration changes. From the equation curve in 2 concentration exhibited a decreasing trend, and then started increasing with the increase in the PD of the forestland. From the function calculation, the value of the polynomial vertex coordinates of the PD of forestland was ; hence, when the forestland patch density was 0.072, the NO2 concentration reached the minimum of 29.161 μg/m3. Therefore, 0.072 was deduced to be the threshold value for the PD of forestland in this study  in grass patches resulted in the subsequent decrease in the efficiency of SO2 absorption by green spaces [As the density of forestland patches increased, SOy of SO2 . As the n spaces . Therefo2.5 [2.5 concentrations then continue to rise to show a trend of first decreasing and then increasing [The LSI of forest land is related to the edge complexity and patch density of green space patches. The increase in LSI value can enhance the energy flow and exchange between green patches and surrounding patches and create more interaction opportunities for source and sink landscapes, so as to absorb and settle more pollution particles and reduce the concentration of PM2.5 . Howevercreasing .2 concentration shows a trend of first decreasing and then increasing. When the density of forested land patches increases continuously from 0, the intra-urban green space gradually transitions from single-core large green space to multi-core green space. With the connection of streets, rivers, and other green channels, the multi-core urban green space plays a greater ecosystem service function, more contact area of air pollutants, and higher efficiency of material exchange and energy circulation, which is conducive to the reduction of NO2 pollutant concentration [2 pollutants then increases [As the PD of forest land keeps increasing, NOntration . Howeverncreases .2 concentrations of different green space types was first increasing and then decreasing.Except for the LSI of grassland, with the increasing values of PLAND and PD of forest land, PLAND and PD of grassland, and PLAND of agricultural land, the trend between the landscape pattern index and SO2 pollution, which can adsorb and absorb and deter SO2 through plant leaves and branches, while urban construction land is a source landscape for SO2 pollutants [2 air pollution by vegetation in such cities being much lower than the SO2 emissions, and therefore the pollution concentration is higher. With the increasing area of forest land emissions and reductions gradually reaching a balance or even vegetation reduction exceeding the local pollution emissions air pollution levels are reduced again [Green space is a sink landscape for mitigating urban SOllutants . The deced again ,43.In the context of optimizing and renewing the landscape patterns of urban green spaces, several studies have demonstrated that regulating land use patterns by carefully planning the morphology and layout of green space networks effectively improves air quality and enhances the public health of residents. Based on the aforementioned findings, we made the following recommendations for the improvement of air pollution in cities with subtropical monsoon climates.2.5, NO2, and SO2. The grassland area in the urban built-up area should be properly controlled, the forest coverage should be gradually increased, the restoration and reconstruction of damaged forest land should be accelerated, the integrity and stability of the ecosystem should be improved, the urban green space landscape pattern should be reasonably controlled through scientific basis, and the production and living ecological space layout should be coordinated.Forestland, grassland, and farmland can inhibit the concentration of PM2 and SO2 as the main pollutants, the pollutants can be reduced systematically by reasonably arranging the land use pattern of forest land, grassland, farmland, and other green areas, and cooperating with each other. When the PD value of forest land is about 0.072, the overall value of urban NO2 pollutant concentration reaches the optimum. When the land and PD values of forest land are away from 50% and 0.038, the land and PD values of grassland are away from 3.33% and 0.121, and the LSI of grassland reaches 14.13, the urban SO2 pollutant concentration reduction effect is the best. Therefore, reasonable urban green space planning should be carried out to optimize the density of green space patches and evenly distribute the types of green space patches, to achieve a close relationship between various land uses and better alleviate air pollution. Through the way of inserting green in the gap, the coverage of urban green space can be improved economically and efficiently, and the contact area between green space and air pollutants can be increased to better improve the air quality level.For cities with NO2.5 mainly comes from industrial waste gas emission, traffic emission, and biomass combustion, and mainly exists in roads and factories in built-up areas. China’s subtropical monsoon climate zone is in the stage of rapid urban development, and it is difficult to reduce traffic emissions and industrial emissions. However, PM2.5 pollution can be improved by optimizing the landscape pattern of urban green space. When the LSI of forest land reaches 18.02, the overall value of PM2.5 pollution concentration is the best. It is suggested to reasonably arrange the urban green space area. For the streets and factories with large traffic and industrial emissions, we will focus on improving the greening level of the streets, appropriately increasing the contact area between the street green space and PM2.5, improving the vertical structure of the urban green belt, block, and absorb PM2.5 pollutants to the greatest extent, and reduce the transmission route. In addition, the treatment efficiency of polluted gas in the factory shall be strictly controlled to reduce air pollution.PM2.5, NO2, and SO2 pollution should be actively disseminated to the residents so that the relevant departments can implement the relevant pollution control measures more smoothly, and the residents can support the air pollution control.The comprehensive management of unused land and inefficient land should be promoted to form a reasonable and efficient urban green landscape pattern. At the same time, it is suggested to promote the development of residents’ lifestyle and consumption concepts towards green, healthy, and low-carbon. The scientific achievements in the prevention and control of PMIn addition, the results of the spatial regression model in this study also show that air pollution has obvious spatial effects, so it is not feasible to carry out internal air pollution control for a single city. From the perspective of urban agglomerations, we should coordinate and plan the air pollution control policies among cities, jointly improve the regional air quality level and reduce the threat of air pollution to residents’ public health. At the same time, our results show that the careful planning of urban green space landscape patterns has brought some positive benefits to air pollution, but compared with traffic emissions, industrial emissions, and biomass combustion, the role of pollutant gas emissions is still limited. Therefore, improving the rationality of urban green space landscape patterns is on the one hand. On the other hand, we should also attach great importance to energy efficiency and traffic management, further promote the reform of industrial structure, and eliminate backward industries with high pollution and high consumption. Finally, it aims to increase the proportion of high-tech industries, promote China’s transformation from incremental expansion to stock revitalization, improve development quality and resource utilization efficiency, and reduce air pollutant emissions from the source.2.5 pollution and determined that vegetation and water bodies were significant landscape components that reduced PM2.5 concentrations. In 2016, Xu et al. [2, NO2, and PM10) through binary correlation analysis, and the results indicated that land use had a significant effect on air quality. For each standard deviation increase in construction land, NO2 concentrations increased by 2%. For one standard deviation increase in water bodies, SO2 or PM10 concentrations decreased by 3–6%. Although this study quantified the role of land use type on air pollution levels, it did not explore the quantitative relationship between land use effects on PM2.5. In 2020, Li et al. [2.5, using the boosted regression tree method to capture the effects of land use scale on PM2.5 in different seasons. It was inferred that when the grassland and forestland areas were below 8% and 20%, respectively, the air quality improved significantly with the increase in grassland and forestland areas. When the distribution of construction land was greater than approximately 10%, PM2.5 pollution increased significantly with the increase in the construction land area. This study was the first to identify the threshold for the effect of land use type on PM2.5 concentrations. However, the role of the effect on the three air pollutants such as PM10, NO2, and SO2 is yet to be addressed. Most of the aforementioned studies adopted linear regression models to explore the role of land use types on air pollutants, which could not comprehensively incorporate the spatial effects between cities into the study, and also failed to demonstrate how the effects of landscape patterns on multiple air pollutants varied with changes in landscape pattern indices. On this premise, this study employed a spatial regression model approach to regress air pollutant concentrations and landscape pattern indices in 37 subtropical monsoon climate garden cities of China in 2019, to explore the core landscape pattern indices that exhibited significant effects on air pollution concentrations and the optimal core indicator thresholds for mitigating urban air pollution, to quantify the spatial effects of the landscape pattern indices on air pollutants, using urban spatial effects as a starting point, and then a general framework that differed from existing studies was proposed. In addition to focusing on quantifying the negative or positive effects of landscape pattern indices on air pollutant concentrations, to a certain extent, this study also reflected the appropriate threshold values of landscape pattern indices for reducing air pollution concentrations, which provides quantitative reference and technical support for urban planning in a more targeted manner.As early as the end of the last century Wickham et al.  proposedu et al.  exploredi et al.  studied However, in general, this study had some limitations. Firstly, the spatial resolution of satellite remote sensing images in this study is low, and there may be a certain misclassification of patch types, which may cause deviation to the impact indicators of air pollution. At the same time, because the research object is a large city with a subtropical monsoon climate, it is not universal for other climate belt cities. In addition, the image data used in our study provide a reference for the overall land use pattern of the whole city. The conclusion is that it provides a reference for the overall planning of urban green space landscape patterns from a macro perspective. The role of small-scale urban green space in reducing pollutants needs to be further discussed. At the same time, in order to ensure the accuracy of the urban green space landscape pattern indicators, the image data selected in this study are all summer image data, but the air pollution data is the annual average value of pollutants. Due to the seasonal changes, the green space coverage of a few cities in winter is reduced, so the impact analysis of this study on air pollutants is still insufficient. Therefore, based on the above shortcomings, in future research, we will expand the sample number of research objects, improve the accuracy of remote sensing data, and analyze the urban landscape pattern and air pollutant concentration in different seasons and climate zones respectively, so as to reduce variables, improve universality and research accuracy, and put forward more targeted urban green space landscape pattern planning strategies.2.5, PM10, NO2, and SO2 and the landscape pattern index of these 37 cities in 2019 as the dependent variable and independent variable, respectively, to carry out the spatial regression model. Based on the output of the model, the impact mechanism between landscape pattern index and PM2.5, PM10, NO2, and SO2 pollution was explored. Finally, a new threshold effect estimation method based on a polynomial model is designed to explore the threshold effect of green space landscape patterns on air quality ). In addition, the specific distributions of the air pollution index data  for the 37 cities are presented in http://www.stats.gov.cn/ (accessed on 1 September 2020)), and the number of permanent residents in 2019 was selected as the population index (https://www.usgs.gov/ (accessed on 20 September 2020)). The urban land use map was converted to a tiff format by ArcGIS10.3 and then imported into FRAGSTATS for calculations, to obtain the data for patch-level landscape pattern indices  were selected as the independent variables of air pollutant concentration that influence factors for spatial regression analysis.First, in the selection of the model, after the regression analysis. The calculation of Moran’s I index for air pollutants using the GeoDa software revealed that the Moran’s I index was 0.57, and the model exhibited a significant spatial correlation. This indicated that air pollutants exhibit spatial interactions, and their effects could spread through adjacent regions, which confirmed that local and regional landscape pattern changes directly or indirectly affected their surrounding air pollutant concentrations. Therefore, the spatial regression model can better reveal the relationship between air pollutant concentration and landscape green space pattern.1–X9 represents the impact factors of landscape pattern indexes  for three types of urban green space: forest land, grassland, and farmland, respectively (The independent variables); β1–β9 denote the regression coefficients of independent factors such as landscape pattern indices; ε denotes the random error. This was ultimately utilized to establish the SEM spatial regression model between pollutant concentrations and landscape patterns in 2019.Secondly, the regression results of the spatial autoregression model (SAR) and spatial error model (SEM) were compared in (1)2.5, NO2, and SO2 pollutants in the air, while the concentrations of PM10 pollutants were not significantly affected by the green space pattern.The landscape pattern of urban green space was significantly correlated with the concentrations of PM(2)2.5, NO2 and SO2, respectively. The PLAND, PD, and LSI of grassland and farmland can also have an additional impact on the concentration of SO2 pollutants.Among them, the patch shape index (LSI), patch density (PD), and patch proportion in landscape area (PLAND) of forest land can affect the concentration of PM(3)2.5, NO2, and SO2 air pollutants. When the PD value of forest land is about 0.072, the overall value of urban NO2 pollutant concentration reaches the optimum. When the land and PD values of forest land are away from 50% and 0.038, the land and PD values of grassland are away from 3.33% and 0.121, and the LSI of grassland reaches 14.13, the urban SO2 pollutant concentration reduction effect is the best.The study also found that there was a significant threshold effect on the impact mechanism of urban green space landscape pattern indicators  on the concentrations of PMUrban green space is an effective tool to improve air quality. Quantifying the relationship between urban green space landscape patterns and air pollution concentration is of great significance to promote the public health level and sustainable development of residents in high-density population areas. This study takes 37 garden cities with subtropical monsoon climate in China as the research object, selects the urban air quality monitoring data and land use remote sensing data in 2019, carries out regression analysis on urban air pollutant concentration and landscape pattern index through spatial regression model method, and explores the relationship between landscape pattern index and air pollutant concentration, According to the above regression analysis results, the landscape pattern index threshold with significant correlation with air pollutant concentration was explored. The specific conclusions are as follows:The results of this study not only clarify the impact mechanism of the landscape pattern of urban green space on air quality but also propose a polynomial-based threshold effect estimation method, which provides quantitative reference and scientific basis for the optimization and updating of urban green space landscape patterns to promote public health.


Additionally, we demonstrated that the distance between the gas inlet and the sensor and gas inlet orientation influences the sensor performance. As the distance to the 2D gas sensor surface decreased from 4 to 2 mm, the sensitivity of the sensor improved to 9.20%. Furthermore, when the gas inlet orientation was perpendicular to the gas sensor surface, the sensitivity of the sensor was the maximum (4.29%). To attain the optimum operating conditions of the MoS2-based gas sensor, the effects of measurement conditions, such as gas concentration and temperature, on the sensitivity of the gas sensor were investigated.Gas sensors applied in real-time detection of toxic gas leakage, air pollution, and respiration patterns require a reliable test platform to evaluate their characteristics, such as sensitivity and detection limits. However, securing reliable characteristics of a gas sensor is difficult, owing to the structural difference between the gas sensor measurement platform and the difference in measurement methods. This study investigates the effect of measurement conditions and system configurations on the sensitivity of two-dimensional (2D) material-based gas sensors. Herein, we developed a testbed to evaluate the response characteristics of MoS Gas sensors are becoming increasingly important for gas leak detection, respiration measurement and analysis, and air quality monitoring in residential, industrial, medical, and environmental fields. There are various types of gas sensors, such as optical gas imaging, acoustic, and electrochemical. Optical gas imaging can detect hydrocarbon leak of the chemical plant in real-time from several meters away . AcoustiTo evaluate the performance of the gas sensor, a testbed, an instrument that measures characteristics such as the sensitivity and detection limits under different operating conditions, is utilized in the early stages of development. The testbed for gas sensors is classified into two types of measurement systems: static and dynamic ,21. The Accurate gas-sensing measurements require several considerations. The factors contributing to the measurement uncertainty include the purity of each gas, resolution of the MFC, temperature, and pressure deviation, which determine the concentration uncertainty of the mixed gas. In addition, to achieve accurate and reliable gas detection, it is necessary to reduce the measurement noise and time delay caused by various factors during performance evaluation. Among these factors, testbed configurations, such as the volume and shape of the test chamber, design of gas inlets, and gas-mixing units, should be carefully considered as these factors influence the time to a change in the test gas concentration ,31,32,332-based gas sensors under a test gas flow, which allows simple adjustment of system configurations and low-noise measurements, and used this apparatus to better understand the system configuration dependence of the gas sensor performance. Through the evaluation platform developed in this study, the effect of the change in the position and angle of the gas inlet, which is a component of the chamber, on the gas sensitivity was investigated. To attain optimum working conditions of the MoS2 nanoflower-based gas sensor, we investigated the effect of measurement conditions such as temperature and gas concentration on the sensitivity of the 2D gas sensor. The sensor shows a linearly increasing response as the temperature and gas concentration increases. We demonstrate that the testbed is a traceability measurement platform where the system configuration and operating sequence do not affect the linear response of the gas sensor. The testbed we developed is not limited to only 2D material-based sensors, but will be applicable to measurement systems for various types of gas sensors.Herein, we developed a dynamic apparatus to evaluate the gas-sensing properties of MoS2 nanoflower, the MoS2, an active sensing layer, was grown on a p-type Si wafer with 300-nm-thick SiO2  using metalorganic chemical vapor deposition (MOCVD) at a partial pressure ratio of 1.9 in the H2S to the Mo(CO)6 precursor [2 nanoflower sample, which is a sensing material of the gas sensor. The 2D MoS2 based sensing material has a unique flower shape, and is suitable for gas sensors due to its high surface-to-volume ratio. Furthermore, 2 nanoflower. The Raman spectra exhibits two peaks related to in-plane  and out-of-plane  vibration modes. The PL peak of the sample was detected at 1.90 eV, which corresponds to the A excitons. The bonding characteristic of the MoS2 nanoflower was captured by X-ray photoelectron spectroscopy (XPS), and the representative result is shown in 2 as the active material of the gas sensor, MoS2 grown wafer was cut into 6 mm × 9 mm size and the unnecessary part of MoS2 film was removed by the scotch-tape method. As previously reported [2-based gas sensor was fabricated by depositing Au/Pt/Ti (150/50/50 nm) electrodes on the MOCVD-grown MoS2 sensing layer using a stencil mask and e-beam evaporator under high-vacuum conditions (<10−4 Pa). The gap between the electrodes was 100 µm and the open area of the gas sensor was 30 mm2. The gas sensor was attached to a printed circuit board with adhesive tape, and the electrical connection between the electrodes of the gas sensor and the tip of the printed circuit board was made using gold wire bonding. For the fabrication of the gas sensor based on MoSrecursor . Figure reported , a MoS2-Morphological analysis was performed using SEM . The Raman and PL measurement were performed using a confocal Raman spectroscope  with a 488-nm laser. The bonding characteristic was measured using XPS .3. The test chamber was composed of a two-gas inlet, a gas outlet, two cartridge heaters, and an electrical feedthrough to control resistance meter, as shown in The sensing test chamber was made of aluminum and had a volume of 0.01 m2 gas was then introduced into the test chamber by a MFC through the gas inlets to obtain N2 saturated condition of the gas sensor. Once the saturation condition was set, a DC voltage of +1 V was applied to the sensor. Subsequently, the sensor was exposed to the analyte gas such as NO2, NH3, and CO2 gas  at the desired concentration for 300 s. The analyte gases are the certified reference material manufactured by the Korea Research Institute of Standards and Sciences. The total gas flow rate was maintained at 100 sccm, and the variation in the sensor resistance was measured. After each successive test, the chamber was evacuated and purged with N2 gas to remove residual gases and recover the sensor. Finally, the sensitivity of the gas sensor was calculated from the resulting changes in sensor resistance.g represents the sensor resistance to the analyte gas and R0 represents the initial sensor resistance in a N2 atmosphere.In this study, the change in sensitivity of the gas sensor was investigated using nitrogen dioxide gas as the test gas. The sensitivity ,38,39 of2 exposure obtained from the gas-sensing test carried out using a single gas inlet system. The sensor showed a resistance change 10 s after exposure to NO2 gas. This is a result of the residence time required for NO2 gas to travel from the MFC outlet to the sensor. Conversely, In many gas-sensor studies, most gas-sensing measurement systems usually contain a single gas inlet, which influences the gas sensor performance ,42,43,442 gas sensor to a NO2 concentration of 5 ppm, which was the result obtained from the gas-sensing test conducted in the two-gas inlets system. When the on/off control of the MFC and gas valve was simultaneously operated at each measurement step, hunting signals occurred at the point of NO2 exposure and N2 purge. These hunting signals appear because if each valve is opened and closed simultaneously, the gas supply is momentarily stopped while the gas moves from the valve close to the gas inlet into the chamber. To remove unexpected hunting behaviors, the on/off switching time control of the gas inlet valve, that is, one-second time delay, was controlled. 2 purge, as shown in 2 exposure, as shown in 2 exposure and N2 purge, as shown in Further experimental study on how the system configuration and operating sequence influence the sensor signal was conducted. 2 gas sensors were exposed to 5 ppm of the analyte NO2 gas injected at various angles and distances between the gas inlet and the sensor surface. During all comparison experiments, the angle between two-gas inlets was maintained at 45°, as shown in To investigate the influence of different gas inlet orientations toward the sensor and distance to the sensor on sensitivity, the MoS2 molecule on the sensor surface, as with the effect of the gas inlet angle on the sensor sensitivity. As the gas inlet moves farther away from the sensor surface, interference with the analyte gas transfer to the surface by atmospheric gas occurs more frequently during its travel. This is due to its extremely limited mean free path under atmospheric pressure, which causes a decrease in the impingement rate of analyte gas molecules. 2 gas sensor to 5 ppm of the analyte NO2 with different angles and distances between the gas inlet and the sensor surface.2-based gas sensor. The gas-sensing responses of the sensor for various NO2 concentrations from 1 to 10 ppm are depicted in 2 concentration. The sensor responses were obtained from the two-gas inlet system with optimal configuration (angle of 90° and distance of 2 mm) using the time delay on/off valve control. The gas concentration was determined by the analyte to balance the gas volume ratio under standard atmospheric pressure. As the NO2 concentration increased from 1 to 10 ppm, the sensor sensitivity increased linearly to 1.5%, 2.8%, 3.8%, and 4.8% at concentrations 1, 4, 7, and 10 ppm, respectively.We further investigated the analyte gas concentration and temperature dependence of the sensor sensitivity to determine the optimum operating conditions of the MoS2 at different operating temperatures obtained from the two-gas inlet system with a gas inlet angle of 90° and a gas inlet to sensor distance of 2 mm at room temperature. As the temperature increased from 21 to 80 °C, the sensitivity increased linearly to 3.1%, 4.6%, 6.0%, and 7.8% for temperatures of 21, 40, 60, and 80 °C, respectively. The MoS2 nanoflower layer of the 2D gas sensor used in this study acts as a p-type semiconductor, which is attributed to a decrease in its resistance upon exposure to NO2 gas. When NO2 acts as the oxidizing gas adsorbed on the surface of the MoS2 active layer, the influence of the low-resistance hole accumulation region on the overall change in the sensor resistance is relatively more dominant than that of the high-resistance electron shell depletion region, and the total resistance of MoS2 decreases significantly [ficantly ,45,46. T2 gas sensor. By using a two-gas inlet system and time delay on/off control of the gas inlet valve, abnormal signal hunting was removed, leading to the enhancement of the response time without delayed reaction. It was found that the variations in the system configuration (the gas inlet orientation and the gas inlet to sensor distance) significantly affected the sensor sensitivity. The sensor sensitivity was enhanced by increasing the gas inlet angle (gas flow direction perpendicular to the sensor surface) and decreasing the distance from the sensor. Furthermore, the analyte gas concentration and temperature dependence of the sensor sensitivity were investigated, and it was confirmed that the higher the concentration and temperature, the linearly higher the sensitivity of the gas sensor. For more precise and reliable gas-sensing measurements, further discussion on the critical factors  in addition to the measurement system configuration influencing the sensor responses, signal noise, and cross-interference, should be conducted.In summary, we developed a dynamic gas sensor test platform that allows simple adjustments of the measurement system configurations and low-noise measurement. This apparatus allows us to better understand how the measurement system configuration and operating conditions affect the sensing response of the MOCVD-grown MoS


P, and the feedthrough was only 4.2 mV. The quality factor was higher than 5000 and was maintained with no drop in the 50-day test. The vacuum in the chamber of the sensor was about 10 Pa. A sensitivity of 0.16 mV/(kV/m) was achieved within the electrostatic field range of 0–50 kV/m. The linearity of the microsensor was 1.62%, and the uncertainty was 4.42%.This paper proposes a novel wafer-level vacuum packaged electric field microsensor (EFM) featuring a high quality factor, low driving voltage, low noise, and low power consumption. The silicon-on-insulator (SOI) conductive handle layer was innovatively used as the sensing channel to transmit the external electric field to the surface of the sensitive structure, and the vacuum packaging was realized through anodic bonding between the SOI and glass-on-silicon (GOS). The fabrication process was designed and successfully realized, featured with a simplified process and highly efficient batch manufacturing, and the final chip size was only 5 × 5 mm. A theoretical model for the packaged device was set up. The influence of key parameters in the packaging structure on the output characteristics of the microsensor was analyzed on the basis of the proposed model. Experiments were conducted on the wafer-level vacuum-packaged EFM to characterize its performance. Experimental results show that, under the condition of applying 5 V DC driving voltage, the required AC driving voltage of the sensor was only 0.05 V P (peak voltage) AC, and noise feedthrough of 13.9 mV [P AC [Electric field sensors are widely used in many fields such as meteorology, electric power, aerospace, and petrochemicals ,3,4,5,6, 13.9 mV . Chu promV [P AC . The micIn recent years, there have been some research reports on EFM’s packaging technology ,16,17,18WLVP is required to improve manufacturing efficiency and yield, and to reduce driving voltage, the size of the packaged chip for high-density integration, and the cost . WLVP caThis paper proposes a novel wafer-level vacuum-packaged EFM featuring a higher quality factor, lower driving voltage, lower noise, and lower consumption compared with previously reported EFMs ,16,17,18The schematic view of the proposed WLVP structure is shown in In the newly developed micromachined wafer-level vacuum-packaged EFM, the SOI conductive handle layer was innovatively used as the sensing channel to transmit the external electric field to the surface of the sensitive structure, and the vacuum packaging was realized through the anodic bonding between SOI and GOS. Moreover, signal transmission was realized in the vertical interconnection hole of the GOS substrate, to be far away from the sealing cap, so as to reduce the interference of the signal to the measured electric field. The shielding ring composed of shielding beams and grounded sealing ring separated the driving and sensing parts, and the silicon layer of the GOS substrate was grounded to reduce the noise coupled by the AC driving power. Through the SOI buried oxygen layer with uniform thickness, the mismatch of the spatial capacitance between the differential driving power and the output is reduced to reduce the crosstalk noise and improve the output stability of the sensor. The wafer-level vacuum packaging structure of the sensor can significantly improve the quality factor of the device, and reduce the driving voltage and noise interference.The working principle of the EFM is based on charge induction. The schematic diagram of the sensor’s working principle is shown in A theoretical model was set up from the perspective of structural capacitance to analyze the output characteristics of wafer-level vacuum packaged EFM. The packaging structure model and the capacitance model are shown in =ε0Aeid1 . Cgi rep=ε0A2jd2  considerε0εrA3d3 .+A2+2A3) , where EWhen the shielding electrodes move along the central axis by a distance of The charge in area Q(t) = Q0 + QA sin (wt), where When the shielding electrodes of the microsensor are harmonically actuated, the induced charge on the sensing electrodes can be expressed as ectrodes . In thisessed as i=d(Q(t)Equation (10) shows that the output current of the microsensor was proportional to the peak of the charge variation of the working electrodes, which is In the theoretical model mentioned above, we set the gap  simulation model, constructed according to the packaging structure in Although a larger output current was achieved when In order to study For the other parameters of In order to obtain large vibration, the microsensor was designed to work at the resonant frequency. In COMSOL 5.4 software, the 3D simulation model was constructed according to the structure in We completed the microfabrication process of the wafer-level vacuum-packaged EFM in our laboratory by breaking through some key processes. The fabrication of the sensitive structure and the vacuum packaging of the microsensor were realized by batch manufacturing. The microfabrication process was mainly based on GOS, SOI, and anodic bonding technologies. The GOS was anodically bonded by a 300 µm thick silicon wafer and a 300 µm thick BF33 glass wafer, and the glass layer of the GOS was then thinned to 100 µm by chemical mechanical polishing (CMP). The main steps of fabrication shown in (a) Deep reactive ion etching (DRIE) was utilized to etch the SOI device layer to form the sealing ring, driving electrodes, shielding beams, and working electrodes.(b) The oxide layer below the driving electrodes and the working electrodes was removed by vapor HF.6 gas was used to form alignment marks on the silicon surface of the GOS wafer, which was used for the alignment of anodic bonding.(c) Cr/Au with thickness of 30/200 nm was deposited on the glass surface of the prepared GOS wafer to form the protective layer. Then, reactive-ion etching (RIE) with SF(d) The Cr/Au deposited on the glass surface of the GOS was patterned using the metal corrosive fluid with the protection of the patterned AZ4620 photoresist to form the mask. Then, the glass layer of the GOS was patterned utilizing vapor HF with the protection of the patterned Cr/Au mask.(e) Ti/Au with thickness of 1 µm/30 nm getter was deposited with the protection of a hard mark, which was patterned by a laser process.(f) The anodic bonding of the SOI and GOS wafers in a vacuum environment was conducted, and the Ti/Au getter was activated during the bonding process. The bonding voltage was 400 V, the bonding temperature was 350 °C, and the bonding pressure was 500 mbar.(g) DRIE was utilized to etch completely through the GOS’s silicon layer from the backside, and the etch stopped at the surface of the GOS’s glass layer. Then, vapor HF was utilized to etch the exposed GOS’s glass layer from the backside with the protection of the patterned GOS’s silicon layer.(h) Al metal pads with thickness of 1 µm were deposited in the via holes with the protection of another hard mark, and wire bonding was conducted.In Step (b), due to the weak stiffness of the structure, the adhesion of the beams appeared while utilizing the two-step process of HF etching and water removal with isopropyl alcohol (IPA) . TherefoAs shown in The detection schematic is shown in The tested amplitude–frequency response of the microsensor is shown in The quality factor of the vacuum-packaged EFM proposed in this paper was calculated to be 5738, while the quality factor of the unpackaged EFM was approximately 60 at atmospheric pressure . We testP AC voltage are required for the microsensor proposed in this paper, while driving signals with 20 V DC voltage and 1 VP AC voltage are required for the unpackaged EFM [P AC driving signal is required, and noise reduction designs are carried out in the structure. Therefore, the noise coupled by the AC driving signal is greatly reduced. The noise is not further reduced due to the noise in the circuit itself, which can be improved with the optimization of the circuit. Sensor consumption was in the order of mW or lower due to the decrease in driving voltages.Experimental results show that driving signals with 5 V DC voltage and 0.05 Vaged EFM . The feeaged EFM . The vacFurthermore, the microsensor was tested in three roundtrip measurements, and results are shown in Three dies were selected, and quality factors were measured every five days during the 50-day test. Quality factors of the microsensors versus time are shown in The comparison between previously reported EFMs and this work is shown in In this paper, a novel wafer-level vacuum-packaged electric field microsensor was proposed and successfully fabricated. The sensor requires low driving voltages to reduce power consumption, and achieved higher quality factor and lower noise feedthrough compared with previously reported EFM. The SOI conductive handle layer was innovatively used as the sensing channel to reduce interference. The newly designed fabrication process based on SOI and GOS was successfully realized, featuring a simplified process and high efficiency in batch manufacturing, which could be used for reference for other kinds of WLVP microsensors. The proposed improved HF release method can be used for the high-quality release of other weak-stiffness structures. A theoretical structural capacitance model was set up to analyze the sensitive mechanism and characteristics of the microsensor, which are of great significance to study the influence of the package structure on EFMs.P, and the feedthrough was only 4.2 mV. The quality factor was higher than 5000 and was maintained with no drop in the 50-day test.Experimental results show that the final chip size was only 5 × 5 mm; under the condition of applying 5 V DC driving voltage, the required AC driving voltage of the sensor was only 0.05 VThe proposed microsensor could be used in high-density integrated devices due to its small size, such as by being integrated into a mobile phone. The proposed microsensor can also be used in some practical application scenarios that require long-term use and long-term stability, such as power transmission and meteorological sounding, due to its low driving voltages, low power consumption, and low noise. In the future, we will further improve the sensor’s sensitivity by optimizing the packaging structure, and further carry out application verification for practical application scenarios.


The ship exhaust sniffing unmanned aerial vehicle (UAV) system can be applied to monitor vessel emissions in emission control areas (ECAs) to improve the efficiency of maritime law enforcement and reduce ship pollution. To solve the problems of large size, heavy weight and high cost of ship exhaust sniffing sensors, in this paper, a unique diffused mini-sniffing sensor was designed, which provides a low-cost, lightweight, and highly adaptable solution for ship exhaust sniffing UAV. To verify the measurement accuracy of the system, a large number of on-site tests were performed based in the mouth of the Yangtze River, and some cases of violation of the fuel sulfur content (FSC) were verified and punished. Maritime law enforcement officers boarded the ship to take oil samples from eight suspected ships and sent them to the laboratory for testing. The results showed that the FSCs of the eight ships in chemical inspection were all greater than the regulatory limit 0.5% (m/m) of the International Maritime Organization (IMO). The system enables authorities to monitor emissions using rotary UAVs equipped with diffused mini-sniffing sensors to measure the FSC of navigating ships, which couple hardware and operational software with a dedicated lab service to produce highly reliable measurement results. The system offers an effective tool for screening vessel compliance. In 1997, the International Maritime Organization (IMO) formulated the MARPOL73/78 Annex VI, “Rules for the Prevention of Air Pollution from Ships”, which requires that the sulfur content of global marine fuel oil shall not exceed 3.5% (m/m) from 2012 and 0.5% (m/m) after 2020 [The shipping industry is the artery of global trade and plays an important role in promoting the world economy and trade development and in stabilizing the global supply chain. According to the report of the United Nations Conference on Trade and Development, more than 70% of the current international trade volume and more than 80% of the international trade volume are realized through shipping ,2. In remissions , respectery year . The useter 2020 ,14.2, NOx and PM from ships, on 10 December 2018, the MOT issued the “Implementation Scheme of the Domestic Emission Control Areas (DECAs)” for Atmospheric Pollution from Vessels [For reducing the impact of ship exhaust on air quality in coastal cities, developed countries in Europe and the United States have set up air pollutant ship emission control areas (ECAs) with stricter standards. Since 2015, ships entering ECAs are required to use fuel with sulfur content of no more than 0.1% (m/m). Compared with developed countries in Europe and the United States, China’s coastal areas have more developed water transportation and a higher population density. The damage of ship exhaust to the health of coastal residents is significantly more serious, which has attracted the attention of the Chinese government. To reduce air pollution caused by ship exhaust emissions, in December 2015, The Ministry of Transport (MOT) of China issued an Action Plan, which was used to control marine emissions in the Bohai-rim Waters, Yangtze River Delta and Pearl River Delta region [ Vessels ,17,18. T2 and CO2 in the exhaust plume of the ship, so as to estimate the FSC. According to the location of installation, the monitoring equipment includes: a shore-based or bridge-based fixed ship exhaust remote monitoring instrument and a boat-borne ship exhaust telemeter and airborne ship exhaust telemeter [In view of the emission supervision of ships underway, the traditional direct boarding inspection method has the problems of difficult boarding, low supervision efficiency, and low sampling inspection ratio. At present, most of the high-efficiency monitoring methods of ship exhaust without boarding use the sniffing method , which melemeter ,24,25,262- and CO2-monitoring instruments and equipment. In the experiment, the tail gas of 10 ships was monitored [2) and particle (10–500 nm) emissions of a ship at sea, the UAV system successfully assessed ship emissions to derive EFPN under real world conditions. Ning et al. [Additionally, many researchers have successfully used small aircraft equipped with sensors to monitor navigating ships. The European Union Joint Research Center JRC launched a sister project of the SIRENAS-R project, the SIRENAS-G project, in conjunction with the Italian Coast Guard, which carried out experiments in the Gulf of Genoa using unmanned aerial vehicles (UAV) equipped with small SOonitored . From thonitored  used smaonitored  used aironitored . Villa eonitored  used an g et al. ,31 develg et al. ,18 desig2 and CO2, it can quickly analyze whether the FSC exceeds the standard without boarding. A large number of on-site tests were carried out in the mouth of the Yangtze River, and some cases of violation of the FSC were verified and punished, which verified the reliability and accuracy of the diffused mini-sniffing sensor.Based on the above problems, a unique diffused mini-sniffing sensor was designed, which provides a low-cost, lightweight, and highly adaptable solution for a ship exhaust sniffing UAV. The UAV is equipped with a diffused mini-sniffing sensor to fly into the ship’s tail gas plume for monitoring. By analyzing the ratio of SO2 and CO2 in real time, records the time information, calculates the FSC, and completes the data integration and packaging process.The research undertaken in this paper is from the “Monitoring ship exhaust emissions of navigating ships in Key waters of Shanghai” project. In this project, a set of ship exhaust mini-sniffing UAV systems (MSUS) is designed, which is used for monitoring the FSC of navigating ships in ECAs. MSUS consists of four modules: (1) four rotor UAV; (2) diffused mini-sniffing sensor; (3) mobile control terminal; (4) data server. The system structure is shown in 2 and CO2, and the processor, battery and communication modules. MSUS has been tested in the key waters of Shanghai (ECA), which has verified the stability, reliability and safety of the system.The DJI Phantom 4 Pro V2.0 UAV  is used as the flight carrier of the sniffing sensor, and a diffused mini-sniffing sensor is designed and manufactured, which is installed under the bottom bracket of the UAV, as shown in 2 sensor, CO2 sensor, power supply module, processor and communication module. The size of the diffused mini-sniffing sensor is 140 × 80 × 40 mm, weighing about 300 g. The structure diagram of the diffused mini-sniffing sensor is shown in As an important part of gas detection, the diffused mini-sniffing sensor mainly includes an SO2 sensor with a large volume and weight must be used. The ship exhaust sniffing UAV can carry the diffused mini-sniffing sensor to fly directly into the smoke plume for monitoring and analysis, and it can monitor the high concentration of tail gas within tens of meters. Therefore, the UAV airborne sniffer can sacrifice the accuracy of the sensor, so as to reduce the volume and weight of the sensor.The boat-mounted ship exhaust telemeter monitors the exhaust gas of navigating ships. It is necessary to maintain a safe distance of more than 100 m between the sea patrol boat and the measured ship. The concentration of exhaust gas that can be monitored is low; thus, a high-precision CO2 after tens of meters of diffusion dilution of ship tail gas is about 100–1500 ppm (removing the concentration of CO2 in the air background). Therefore, this paper adopts a non-dispersive infrared CO2 sensor with small size, light weight and suitable precision. This kind of sensor has the advantages of excellent long-term stability and low maintenance cost. The CO2 sensor was purchased from Shenzhen Singoan Electronic Technology Co., Ltd., Shenzhen, China; sensor model: SGA-700B-CO2; technical principles: non-dispersive infrared. The selected CO2 sensor has a detection range of 0–2000 ppm, a detection accuracy of 5 ppm, a response time T90 less than 30 s, a sensor diameter of 34.5 mm, a height of 30 mm, and a weight of about 30 g.According to the test experience, the concentration range of CO2 and CO2 in the ship tail gas after diffusion dilution. The FSC can be calculated by Equation (1):FSC is the sulfur content of the fuel, Comprehensively consider the principle of the sniffing method: that is, the molar ratio of C and H of marine fuel is about 1:2, and the C content is calculated at about 87%. From the principle of material conservation, the S content in the fuel oil can be deduced by monitoring the ratio of SO2 and CO2 in the ship’s tail gas reaches more than 3 times, which means the FSC exceeds 0.5% (m/m). In this paper, a SO2 sensor based on the electrochemical method is adopted. Because of its low power consumption, small size, light weight and high precision, an SO2 electrochemical sensor is widely used. The SO2 sensor was purchased from Shenzhen Singoan Electronic Technology Co., Ltd.; sensor model: SGA-700B-SO2; technical principles: electrochemical. The selected electrochemical SO2 sensor has a detection range of 0–1 ppm, a detection accuracy of 10 ppb, a response time T90 less than 30 s, a sensor diameter of 34.5 mm, a height of 30 mm, and a weight of about 30 g.According to the sniffing method, when the ratio of SOThe power of the diffused mini-sniffing sensor is about 12W; thus, the power module can be powered by two No.5 batteries separately, which can not only reduce the secondary development cost of the UAV but can also be independent of the UAV and can be easy to disassemble. The capacity of a single battery is 2775 mAh, and the capacity of two batteries is 5550 mAh. According to 70% of the effective capacity, the effective capacity is 3885 mAh. The voltage of the two batteries is 3V, which can support the sensor to work continuously for about 1 h after calculations. Generally, the effective flight time of the rotor UAV does not exceed 30 min, and the power supply module can support the ship exhaust detection of the UAV’s normal endurance flight time.Combined with the wind speed of the inland river emission control area, the weight of the sensor, and the endurance of the UAV, the DJI Phantom 4 Pro V2.0 UAV was selected as the flight carrier of the diffused mini-sniffing sensor. The system adopts phantom 4 Pro V2.0 UAV, which is the most popular consumer UAV at present. It has the advantages of small size, low cost and simple operation. The diffused mini-sniffing sensor can be fixed on the two brackets of the UAV, and the pan-tilt camera can transmit a real-time picture of the ship’s exhaust to the remote control for the technician to view.2 and CO2 concentration curves in real time through the data server to screen suspected ships that use high-sulfur oil in violation of regulations.The data server of the ship exhaust mini-sniffing UAV system is realized by a laptop and a data-receiving module. The software functions mainly include acquisition control, data display, FSC estimation and historical data query. Technicians can control the UAV to fly into the exhaust plume of navigating ships as well as remotely monitor the SO2 and SO2 are diffused and diluted with the wind, but the ratio remains unchanged. As long as the exhaust gas can be monitored, the FSC can be estimated. A safe distance between the UAV and the ship’s chimney should be 10–15 m, the height should be equal to or slightly higher than 1–2 m of the chimney height, and it should be followed for about 1–2 min. 2 and CO2.When the wind speed is less than 10 m/s and the wind direction is different, the position of the UAV relative to the chimney is various. It should always be kept at a close distance to the downwind direction. Although the distance between the UAV and the ship’s chimney is different, and the concentrations of the exhaust components are different, the COThe Yangtze River is the longest river in China, and the Yangtze River is a golden waterway with the largest freight volume in the world. The density of ships is high, especially at the mouth of the Yangtze River, where ships are constantly flowing. Therefore, the experimental test site was selected in the key waters of the Shanghai Emission Control Area, Yangtze River. The test site was preferred to take off on shore, which has the advantages of simple operation and low cost. The monitoring process of ship exhaust mini-sniffing UAV includes a series of steps.1.Observe the relative distance between the ship and the monitoring point, select an appropriate take-off time, and control the ship exhaust mini-sniffing UAV to fly to the monitored ship;2.Adjust the position of the UAV according to the wind speed, wind direction and the height of the ship’s chimney to ensure that the UAV is always in the downwind direction of the plume;3.Control the position of the UAV in the downwind direction of the plume, keep a safe distance of 10–15 m from the ship’s chimney, and track and monitor for 1–2 min;4.2 and CO2 in the curve of the data-monitoring software in real time, and determine whether the FSC exceeds the standard according to the FSC estimated by the software;Check the concentrations of SO5.After the exhaust gas monitoring is completed, observe whether the power of the drone is sufficient. If the power is sufficient, continue to track and monitor the next ship; if the power is low, control the UAV to return.2 and SO2, respectively. Since the CO2 and SO2 sensors in this paper have the same response time (T90 less than 30 s) and the same sampling frequency (the data sampling frequency is set to 1 s), the peak concentration of SO2 and CO2 is used to calculate FSC [2 and SO2 concentration data detected by the sniffing sensor through the micro-controller can estimate the FSC in real time and send the FSC data to the server through the communication module.The carbon content in marine fuel oil or diesel oil is about 87%. Under ideal conditions of the engine, all carbon and sulfur are burned and converted into COlate FSC ,24,32,33As can be seen from 2 and CO2 concentrations are shown in the monitoring curve. 2 and CO2 were actually measured) was different for each plume: (a) air background, 14:00:00–14:06:40, 14 August 2021; (b) diesel ship exhaust, 15:12:00–15:28:40, 14 August 2021; (c) compliant heavy oil ship exhaust, 9:00:00–9:02:20, 15 August 2021; (d) illegal heavy oil ship exhaust, 10:12:00–10:20:20, 27 August 2021.The X-axis and Y-axis of the curve represent time (s) and gas concentration, respectively, the red curve represents SO2 concentration (ppb), and the blue curve represents CO2 concentration (ppm). From 2 and CO2 concentrations basically do not change. When the diffused mini-sniffing sensor monitors the ship tail gas without sulfur, there will be obvious peaks of CO2, and the concentration of SO2 will remain basically unchanged. When the diffused mini-sniffing sensor monitors the ship tail gas of compliant low sulfur oil, there will be obvious peaks of CO2 and SO2. When the sniffing sensor monitors the ship tail gas of illegal high sulfur oil, it can be observed that the concentration of SO2 and CO2 will increase, and the increase in SO2 concentration is much greater than that in CO2.To verify the effectiveness of the diffused mini-sniffing sensor, the experimental group conducted a comparative test on the ship exhaust of different sulfur content fuels. 2 concentration in tail gas exceeds three times that of CO2 concentration, it can be considered that the FSC of the ship exceeds the standard. 2 concentration (ppb), and the blue curve represents CO2 concentration (ppm). From 2 concentration in tail gas of high sulfur oil ships is more than three times that in CO2 concentration. Therefore, the sulfur content in ship fuel can be estimated according to the concentration changes of SO2 and CO2 in the monitoring curve. The peaks of (a), (c) and (f) in The test results show that when the increase in SOTo fully verify the accuracy of the sensor, we provided the comparison results between the measured value and the true value of FSC of eight ships. The true value of FSC is obtained through laboratory testing. The data are shown in 2), monitoring distance, and other factors. Although there is a certain deviation between the estimated FSC of the ship exhaust mini-sniffing UAV and the true FSC of the oil sample, it is basically within the allowable deviation ±0.2% (m/m), and the suspected ship locked by the UAV is a ship with excessive FSC, which verifies the reliability of the ship exhaust sniffing UAV technology based on the sniffing method. Through the analysis of the measured values of eight ships and the true values of laboratory tests, it can be concluded that the ship exhaust telemetry UAV proposed is effective for monitoring the illegal use of high-sulfur oil ships. In most cases, the estimated FSC is less than the true value; thus, the appropriate threshold and confidence interval can be set, and the estimated value can be used as the basis for the preliminary judgment of whether the ship exceeds the standard, which can establish a new supervision mode of “telemetry first and then boarding verification” for the maritime system.From To solve the problems of large size, heavy weight and high cost of the ship exhaust sniffing sensors on the market, in this paper, a diffused mini-sniffing sensor was designed, which provides a low-cost, lightweight, and highly adaptable solution for a ship exhaust sniffing UAV. From the test results, the reliability of ship exhaust sniffing UAV technology based on the sniffing method is fully verified. A new supervision mode of “telemetry first and then boarding inspection” can be established, which can improve the sampling inspection rate and reduce the supervision cost.The ship exhaust mini-sniffing UAV system still has some parts that need to be improved. For example, the system is not suitable for complex weather such as rain and fog, and due to the limitation of wind resistance level, the system is not mature enough for the tail gas monitoring of navigating ships in the sea area, which still needs further research. In addition, the wireless communication module of the system adopts a single-chip wireless transceiver chip, which is not suitable for long-distance transmission and is blocked by obstacles, and the data receiver cannot obtain real-time monitoring results.


The aim of study is the effect of educational intervention on anxiety of pregnant women.  This quasi-experimental study is done on the pregnant women referring to family physician’s offices in Gerash City, Iran. 62 women were selected and divided into 2 groups (control and intervention). In intervention group the anxiety reduction training classes were held as a group discussion in 4 weekly 90-minute sessions. Control group received routine care. The anxiety assessment completed by two groups before and after the educational intervention. The measurement instruments included a demographic information questionnaire and the short form of the Pregnancy Related Anxiety Questionnaire (PRAQ-17). p < 0.05) in comparison with control group.  Comparison of the mean scores of different dimensions of pregnancy anxiety in the pre-intervention and post-intervention stages in the intervention group using paired t-test indicated a statistically significant difference in the dimensions Fear of childbirth, Fear of giving birth to a physically or mentally disabled child, Fear of mood swings and Fear of changes in marital relations ( Holding pregnancy-training classes using group discussion method is a good strategy to reduce anxiety in pregnant women. Therefore, it is recommended that this educational strategy classes be used with mothers from the second trimester of pregnancy in urban family physician centers or those referred to a nearby clinic.  In the final analysis, 4 subjects from the intervention group due to irregular attendance in the training classes and 4 subjects from the control group due to lack of access to the questionnaire were excluded from the study and 62 subjects (31 in each group) were examined. The study inclusion criteria were: being pregnant women, willingness to participate in the study, age <35 years old, being in the first and second trimesters of pregnancy, no history of hypertension, lack of gestational diabetes, lack of smoking, no signs of risk of miscarriage, lack of placenta Previa, ectopic pregnancy, bleeding, and mental illness, and being Iranian, and fluency in Persian. The exclusion criteria included any problems or illnesses during pregnancy, such as bleeding, multifetal pregnancy, premature rupture of membranes (PROM), diabetes mellitus (DM), and preeclampsia, and failure to attend the training sessions. .This was quasi-experimental study. The statistical population consisted of all eligible pregnant women who referred to the selected family physicians’ offices in Gerash City, Iran from November 1 to December 1, 2021.The study was carried out with the objective to investigate the effect of group training on reducing pregnancy anxiety. After obtaining the necessary permissions from the research and ethics committee of Gerash University of Medical Sciences, Gerash, Iran, a list of family physicians’ offices was prepared, which were randomly divided into 2 groups (intervention and control groups). For this work, the list of all family physicians was written on paper and placed in a box and the paper was randomly removed. Paired numbers were in the control group and odd numbers were in the intervention group. Then, by referring to the family physician’s offices and by examining the electronic records, the pregnant women who had the study inclusion criteria were extracted. Adopting the quota sampling method, 70 pregnant women were selected as the participants. Using the Jokar Data Collection Tools. The data collection tools used included a demographic information questionnaire and the Pregnancy Related Anxiety Questionnaire (PRAQ-17). The demographic information questionnaire included 9 items related to age, gestational age, height, weight, gravidity, pregnancy type, education level, occupation of the pregnant woman, and average monthly family income. The PRAQ-17 was designed by Wendenburg and includes 17 items. The exploratory factor analysis (EFA) of data from this questionnaire showed 5 factors, with the factors indicating fear of childbirth (3 items), fear of giving birth to a physically or mentally disabled child (4 items), fear of changes in marital relations (4 items), fear of mood swings and its consequences on the child (3 items), and self-centered fears or fear of changes in the mother’s personal life (3 items). The total score of this questionnaire is the sum of the scores of all items. The score of each item ranges between 1 and 7, so the total PRAQ-17 score can range from 17 to 119. This questionnaire does not have a cut-off point, but to examine correlations, it has been stated that if an individual has 65-70 percent of the assessed criteria, he/she can be identified as evidently anxious. .et al. The reliability of the questionnaire was confirmed based on a Cronbach’s alpha coefficient of 0.78; the Cronbach’s alpha of the 5 factors ranged between 0.69 and 0.76. The CI of the questionnaire 1 month later in 40 pregnant women ranged from 0.65 to 0.72 (p < 0.02), indicating the reliability of the PRAQ-17 over time. .Validity and reliability of the questionnaire. The validity and reliability of the questionnaire were measured by Askarizadeh ) , and the Pearson correlation coefficient were utilized in SPSS software . The significance level was 2, respectively. Among the participants, 13 (41.9%) and 16 (51.6%) women, respectively, in the intervention group and control group were primiparous. The rate of wanted pregnancy in the control and intervention groups was equal (74.2%). Moreover, 22.6% and 29.0% of the pregnant women in the intervention and control groups had a university degree, respectively. In the intervention and control groups 80.6% and 87.1% of the subjects were housewives, respectively. The comparison of mean age and gestational age between the control and intervention groups at the beginning of the study did not show a significant difference (p > 0.05), but the mean BMI of the pregnant women in the intervention group was significantly higher than that of women in the control group (p < 0.05) A total of 62 subjects (31 women in each group) participated in the study, and the rate of the clearly anxious women in the whole sample before the intervention was 8.1%. There was no significant relationship between any of the demographic characteristics and questionnaire subgroups in the whole sample before the intervention. The mean age of the women participating in the intervention and control groups was 27.23 ± 5.20 and 26.06 ± 5.51 years, respectively. The mean gestational age of the women participating in the experimental and control groups was 19.00 ± 4.35 and 20.25 ± 3.15 weeks, respectively. The mean body mass index (BMI) of the women participating in the intervention and control groups was 25.71 ± 3.71 and 23.61 ± 4.21 kg/mp > 0.05) The independent t-test was employed to compare the mean scores of different aspects of pre-intervention pregnancy anxiety between the control and intervention groups. The results suggested that there was no statistically significant difference between the groups in any of the dimensions  (p < 0.05), but there were no significant differences in the other dimensions  (p > 0.05) The comparison of the mean scores of different dimensions of post-intervention pregnancy anxiety between the control and intervention groups indicated a decrease in the level of anxiety of pregnant mothers in both groups; however, the level of anxiety in the intervention group showed a greater decrease. The independent t-test showed a statistically significant difference in the mean score of fear of giving birth to a physically or mentally disabled child between the two groups in the post-intervention stage (p > 0.05) p < 0.05) p > 0.05). .Comparison of the mean scores of different dimensions of pregnancy anxiety in the control group before and after the intervention using paired t-test did not show a statistically significant difference . Kazemi et al. et al. stated that, despite the cultural and religious limitations of women in expressing their marital problems, group education provided an opportunity for women in Gerash to reduce their fear of change in marital relations by reducing their pregnancy anxiety. The mean scores of different dimensions of pregnancy anxiety in the intervention group before and after the intervention revealed that the group discussion training method caused a statistically significant difference in all dimensions except self-centered fears. Girija et al. stated that there is a gap between the current care provided and high-quality care, and that continuous follow-up and clarification can be effective in reducing this gap. In this regard, it can be claimed that the presence of health care providers (including NPs and midwives) alongside family physicians, as one of the main pillars of the referral system, plays a significant role in reducing pregnancy anxiety through their encouragement of pregnant mothers to participate regularly in pregnancy training classes and follow-up on their presence in these classes. Nurses Practitioner and midwife in the hospital can also use this training program to reduce the anxiety of women referring to labor and gynecology wards and even postpartum care. .In urban family physician programs, pregnancy care is provided by a physician and health care provider such as nurses, while training classes are held at comprehensive health centers. This was a quasi-experimental study performed on pregnant women under 35 years of age who were in the first and second trimesters of pregnancy, so it is recommended that subsequent clinical trials be performed on high-risk women (over 35 years of age or lower 18 years of old) with period follow up. .Holding pregnancy training classes using group discussion method is a suitable strategy to reduce anxiety in pregnant women covered by an urban family doctor. Therefore, it is recommended that educational classes be continuously held as group discussion in the second trimester of pregnancy in urban family physician centers or mothers be referred to a nearby clinic. The following up and monitoring of these classes by health center education liaisons is also recommended. Therefore, group education under the supervision of a family physician can be used as an acceptable way to reduce anxiety and fear among pregnant women.