Pilot Region Research Articles

Improvement of Maritime Management as a Key Aspect of Sustainable Development and Blue Growth in the Russian Federation

The conservation and sustainable use of oceans, seas and marine resources has been declared by the United Nations as one of 17 priority Sustainable Development Goals. At present, most of the maritime states are striving to improve the efficiency of their use of marine resources, including sea space. In particular, the European Union is implementing a number of projects related to the implementation of marine spatial planning (MSP) tools. The Baltic Sea is considered as a pilot region, where a pan-Baltic coordinated MSP plan has been developed to provide for sustainable development and blue growth in the marine and coastal economy. The Russian Federation is one of the Baltic countries, but the MSP procedure at the state level does not have institutional and regulatory support, which requires the elimination of gaps and additional development of the maritime management system. The laws of the organization and development of the general theory of management are used in this study. An Integrated Management Model for sustainable marine and coastal use is proposed as a tool for ensuring blue growth, including four interrelated elements (specific management functions), namely “Integrated Coastal Zone Management”, “Marine Spatial Planning”, “Management of Marine Macroregion” and “Ocean Governance”. Their functional content and interaction mechanisms are discussed in order to implement an integral approach to marine use. The vertical structure of the proposed integral model includes three levels corresponding to the federal and regional levels of government and the level of municipal self-governance. The use of the integral model should help accelerate the process of introducing and using MSP instruments in the process of strategic planning in the socio-economic development of the Russian coastal territories.

Efficiency of regional agriculture state support

The study analyzed data on state support for agricultural production in the Samara region. The regional level is the main source of budgetary funding for the agro-industrial complex. The Samara region is a pilot region in the research field into the results impact effectiveness of support measures on the agricultural organizations activities. The study purpose is to substantiate the need to improve state support in agriculture in the Samara region. It is necessary to solve the following tasks: to analyze the experience of state regulation in the Samara region agro-industrial complex; to classify the existing directions of state support for agriculture; to substantiate the need to correct the existing approach when improving state support for agricultural production. As a result of the consistent policy implementation in the field of agro-industrial complex supporting, agricultural production in the Samara region was able to become quite effective. The twofold excess of taxes in 2019 over the amount of support indicates that agricultural producers were able to switch to expanded reproduction using their resources. If the current situation persists in the long term, then the state role will be reduced to stimulating extremely promising directions for the region’s agro-industrial complex development.

Integrating socioecological indexes in multiobjective intelligent optimization of green-grey coupled infrastructures

Ecological conservation is an important objective in urban runoff management today. Maintaining a sustainable ecological system is as equally important a task as to ensure the safety of drainage systems and runoff management cost control. Thus, the socioecological influences of runoff control infrastructure are innovatively included in a uniform evaluation framework with the control functions and capital investments in this study. These indexes are quantified through hydrological model simulation, life cycle cost analysis, and life cycle assessment. Traditional grey infrastructure and rapidly developing green infrastructure for runoff control are optimized simultaneously. For the trade-off between multiobjectives and configurations of multi-infrastructures, nondominated sorting genetic algorithm-II is utilized to achieve automatic optimization of runoff control infrastructure scale, thereby avoiding the dilemma where manually arranged schemes cannot perform optimally. This multiobjective intelligent optimization is applied to a sponge city pilot region in Wuhan, China, and trade-offs are made in the Pareto optimal solution set. A breakthrough is claimed in quantifying the respective contribution of green and grey infrastructures to the optimal scenario in terms of runoff control function, cost input, and socioecological influence. For socioecological influence, the paybacks can meet the investment in the aspect of toxicity health hazard, pathogenic matter, global warming, terrestrial acidification, and water eutrophication (average socioecological paybacks are 2.0, 2.1, 2.9, 1.9, and 2.1 times to the investments respectively). Results prove the necessity of considering multiobjective optimization and green-grey couple infrastructures in a uniform framework.

Contribution of phytoecological data to spatialize soil erosion: Application of the RUSLE model in the Algerian atlas

Among the models used to assess water erosion, the RUSLE model is commonly used. Policy makers can act on cover (C-factor) and conservation practice (P-factor) to reduce erosion, with less costly action on soil surface characteristics. However, the widespread use of vegetation indices such as NDVI does not allow for a proper assessment of the C-factor in drylands where stones, crusted surfaces and litter strongly influence soil protection. Two sub-factors of C, canopy cover (CC) and soil cover (SC), can be assessed from phytoecological measurements that include gravel-pebbles cover, physical mulch, annual and perennial vegetation. This paper introduces a method to calculate the C-factor from phytoecological data and, in combination with remote sensing and a geographic information system (GIS), to map it over large areas. A supervised classification, based on field phytoecological data, is applied to radiometric data from Landsat-8/OLI satellite images. Then, a C-factor value, whose SC and CC subfactors are directly derived from the phytoecological measurements, is assigned to each land cover unit. This method and RUSLE are implemented on a pilot region of 3828 km2 of the Saharan Atlas, composed of rangelands and steppe formations, and intended to become an observatory. The protective effect against erosion by gravel-pebbles (50%) is more than twice that of vegetation (23%). The C-factor derived from NDVI (0.67) is higher and more evenly distributed than that combining these two contributions (0.37 on average). Finally, priorities are proposed to decision-makers by crossing the synthetic map of erosion sensitivity and a decision matrix of management priorities.

Potential Analysis of Mediterranean Forestry for Offsetting GHG Emissions at Regional Level: Evidence from Valencia, Spain

Forest management is an untapped tool, yet to realize its full potential to fight against climate change. The capability of forests to act as carbon sinks makes them a key resource to reduce CO2 concentration in the atmosphere. However, carbon which has been fixed can be suddenly emitted again as a consequence of disturbances such as pests or wildfires. Mediterranean plant phenology, climatic conditions, and the accumulation of fuel biomass due to abandonment of traditional forest uses generate a scenario prone to large wildfires and consequently large greenhouse gases (GHG) emissions. The abandonment could be offset by considering the economic value of forest ecosystem services, principally carbon fixation. Nevertheless, currently existing forest carbon markets consider only anthropogenic fixation based on a business as usual scenario without disturbances that cannot be applied to Mediterranean forest reality. Thus, a methodology to monetize carbon fixed has been developed and applied. A range between 55.5 and 250 million € produced by the monetization of 16.5 million potential carbon credits has been obtained based on anthropogenic avoided emissions produced over a 10 year-period. Thereby, the potential for offsetting emissions of the pilot region was between 1.2% and 5.6% of total diffuse GHG emissions. Consequently, sustainable forest management represents an important opportunity to combat climate change, taking advantage of the margin of improvement that the Mediterranean forests currently have to avoid GHG emissions through forest fire prevention silviculture.

The Milky Way Project: Probing Star Formation with First Results on Yellowballs from DR2

Abstract Yellowballs (YBs) were first discovered during the Milky Way Project (MWP) citizen science initiative. The MWP users noticed compact, yellow regions in Spitzer Space Telescope mid-infrared (MIR) images of the Milky Way plane and asked professional astronomers to explain these “yellow balls.” Follow-up work by Kerton et al. determined that YBs likely trace compact photodissociation regions associated with massive and intermediate-mass star formation. The YBs were included as target objects in a version of the MWP launched in 2016, which produced a listing of over 6000 YB locations. We have measured distances, cross-match associations, physical properties, and MIR colors of ∼500 YBs within a pilot region covering the l = 30°–40°, b = ±1° region of the Galactic plane. We find that ∼20%–30% of YBs in our pilot region contain high-mass star formation capable of becoming expanding H ii regions that produce MIR bubbles. A majority of YBs represent intermediate-mass star-forming regions whose placement in evolutionary diagrams suggest they are still actively accreting and may be precursors to optically revealed Herbig Ae/Be nebulae. Many of these intermediate-mass YBs were missed by surveys of massive star formation tracers; thus, this catalog provides information for many new sites of star formation. Future work will expand this pilot region analysis to the entire YB catalog.

Make saving crucial again: building energy efficiency awareness of people living in urban areas

ABSTRACT Construction is one of the most energy-intensive sectors in the world. To scale down the energy demand of the building sector, some changes must be made. Formal exemplifications of this need can be seen in recent changes in the law in different countries. The energy identity/performance certificate contains requirements about buildings’ energy consumption in Turkey, and the Energy Performance Regulation in Buildings is mandatory from 01.01.2020. Moreover, it aimed to measure the level of awareness of individuals in saving energy. Face-to-face surveys were conducted with the use of a questionnaire with individuals residing in Adana's pilot region on the awareness of similar issues such as green buildings and energy efficiency, especially energy identity/performance certificate. The survey results were prepared in Microsoft Excel, and the reliability of the survey questions was measured with the help of the SPSS (Statistical Package for the Social Sciences) program. The analysis of the data was obtained from WEKA (Waikato Environment for Knowledge Analysis). Association rule extraction, which is one of the data mining methods, was used in the analysis. Based on the findings, it was seen that most of the individuals did not have enough information about the topics in the survey.

Techno-Economic Assessment of Flexibility Options Versus Grid Expansion in Distribution Grids

In this paper five different flexibility options are analysed from a techno-economic perspective as alternatives to traditional grid expansion for a specific distribution grid in Germany. The options are: two reactive power control strategies with photovoltaic inverters (as a function of the power feed-in, or of the voltage at the connection point), one residential and two large scale battery storage applications (primary control reserve with autonomous reactive power control or self consumption maximisation strategy with autonomous reactive power control). For the pilot grid located in Southern Germany a photovoltaic expansion pathway is determined. The main goal of this work is to quantify the grid expansion actions that can be avoided by applying these five flexibility options for the assumed expansion pathway, focusing on large scale battery storages. It is shown that the five flexibility options increase the hosting capacity for PV systems, compared to a scenario without, by up to 45%. Furthermore, the results of the economic assessment indicate that the analysed flexibility options might be a viable alternative to traditional grid expansion as all of them show a cost reduction potential for the pilot region. These results could encourage DSOs to consider the integration of additional PV and battery storage systems not as a problem which triggers grid expansion, but as part of the solution reducing future grid expansion costs.

Waste food reduction as a way to reduce resources and energy consumption in the Italian industrial sector: an IO-LCA analysis

Food production involves both agricultural and industrial activities which consume several resources among which: water, energy, land, minerals and chemicals. The efficiency in the use of the resources depends on the type of food which is produced and the adopted processes. In any case if food is discarded or lost at any step of the supply chain this represents a waste of energy and resources. For this reason, the LIFE project irexfo, coordinated by the University of Perugia has proposed a way to promote a business model aiming at both: the reduction of food losses and also the reuse of the not comestible food waste in biogas plants. The model has been tested in Umbria as a pilot region and in this study the results obtained are scaled up to a national level and applied to the Italian IO database reported in the EXIOBASE, to evaluate which could be the benefits of the application of the irexfo business model to the whole Italian agroindustry sector and also the interrelations between this sector and the Italian energy sector. The analysis is performed using SimaPro software 9.0, results are compared with those of similar studies which have been performed at European level. This is the first study of this kind focused on Italy.

Research on Multi-level Distribution Strategy Based on Energy Internet

Smart city energy Internet is to comply with the trend of sustainable energy development, urban power energy as the center, comprehensive utilization of all kinds of energy, especially renewable energy, to achieve interconnection and common optimization. Based on the background of distribution network in Disney Park, this paper studies the regulation, operation and management strategy of distribution network of smart city energy Internet. This paper describes the characteristics of the energy Internet, and then analyzes the key technologies that affect power grid regulation, operation and management. The paper investigated the distribution network construction in Shanghai Disney Park under the background of urban energy Internet pilot region to understand the allocation of distributed energy in the park grid. Through simulation calculation and analysis, this paper puts forward a distribution network regulation and management scheme suitable for the characteristics of energy Internet. In this paper, the study found that with the rapid development of power grid, especially all kinds of distributed energy access, the new lines are becoming more. In a wide range of power grid structure is becoming more and more complex, in order to ensure the reliability of power supply and power supply quality, scientific regulation under the background of urban energy Internet development mode, enhancing the management level of power grid is the inevitable developing trend of power grid.

Analiza potencijala za uvođenje sistema pametnih mreža u Bosni i Hercegovini

The paper presents an analysis of the current situation regarding the development of an electricity distribution network and potential for a smart grid development in the selected pilot region of Bosnia and Herzegovina. Apart from the policy framework assessment, several indicator based criteria were included in the scope of analysis: share of renewable energy and renewable energy as distributed energy resource, total share of distributed energy resources, a number of installed smart meters for measuring electricity consumption, a number of charging stations for electric vehicles, energy storage capacities and technological development. The overall analysis of the assessment has been done by normalization of the calculated values of the indicators on a scale of 1-5. The indicators have showed that the smart grid sector in the Region is currently underdeveloped.

An integrated Shannon Entropy and reference ideal method for the selection of enhanced oil recovery pilot areas based on an unsupervised machine learning algorithm

Pilot-scale enhanced oil recovery in hydrocarbon field development is often implemented to reduce investment risk due to geological uncertainties. Selection of the pilot area is important, since the result will be extended to the full field. The main challenge in choosing a pilot region is the absence of a systematic and quantitative method. In this paper, we present a novel quantitative and systematic method composed of reservoir-geology and operational-economic criteria where a cluster analysis is utilized as an unsupervised machine learning method. A field of study will be subdivided into pilot candidate areas, and the optimized pilot size is calculated using the economic objective function. Subsequently, the corresponding Covariance (COV) matrix is computed for the simulated 3-D reservoir quality maps in the areas. The areas are optimally clustered to select the dominant cluster. The operational-economic criteria could be applied for decision making as well as the proximity of each area to the center of dominant cluster as a geological-reservoir criterion. Ultimately, the Shannon entropy weighting and the reference ideal method are applied to compute the pilot opportunity index in each area. The proposed method was employed for a pilot study on an oil field in south west Iran.

Determining the optimum medium voltage level by analysis of different voltage levels

Electric energy, which is the main input of the growing world economy, depending on the consumption of the rapidly increasing world population and the devices fed with this energy, have become more indispensable in our lives with each passing day. In the consumption of electrical energy, determining the voltage level plays an important role in planning distribution systems that will directly affect consumers. Distribution systems in our country have been established at different levels for technical and financial reasons. Incorrect choices that can be made during the determination of the voltage level in distribution systems may increase energy unit costs and network losses, and may cause insulation and reliability problems. The aim of this study is to determine the optimum voltage level in distribution systems. A pilot region was determined for a local electricity distribution network in our country, and modeling and analysis were carried out at different voltage levels in the region with the help of a numerical analysis program. According to the results achieved, Insulation and reliability problems at low voltages are few and economic in terms of investment costs, but it has been observed that the operating load and cost are high due to high network losses. In high voltages, although the operating burden and cost are relatively low, it has been observed that the investment costs are high and the isolation and reliability problems are high. Keywords: cost; distribution; investment; operating ;Voltage

Implementation of Law on Socialization of Health Services No. 224 in Muş province in the 1960’s

Çalışmada 5 Ocak 1961 tarihinde Milli Birlik Komitesi’nce kabul edilen “224 Sayılı Sağlık Hizmetlerinin Sosyalleşmesi Hakkında Kanun”un uygulaması için pilot bölge seçilen Muş ili konu alınacaktır. 1961 Anayasası ile köklü sosyo-ekonomik reformların hayata geçirilmesi öngörülmüş, bireylerin temel hak ve özgürlükleri anayasada ayrıntılı bir biçimde ele alınmıştır. Bunlardan biri de sağlık hakkıdır ve anayasanın 49. Maddesi’nde yer bulmuştur. Bu bağlamda 15 Temmuz 1960 yılında Sağlık Bakanlığı Müsteşarı olarak göreve başlayan ve bu görevi 6 yıl boyunca sürdüren Doktor Nusret Fişek ayrıca zikredilmelidir. Keza kendisi 224 Sayılı Sağlık Hizmetlerinin Sosyalleştirilmesine Dair Kanun’un mimarıdır. Fişek, Muş’ta başlatılan çalışmaların sadece fikir babası olmamış, buradaki gelişmeleri de mümkün olduğunca yakından takip etmeye çalışmıştır. Çalışmada, 1960’lı yıllarda sağlık hizmetlerindeki sosyalleştirme uygulamalarının Muş ili özelinde incelenmesi amaçlanmıştır.

TREE INVENTORY REGISTRATION SYSTEM

Abstract. As human life develops in all aspects, nature is damaged and faced with the threat of extinction. With the increasing population, cities are expanding. The importance given to greenery and the ecological system is very low in these cities and they look like a concrete forest. However, urban trees are the most important and dominant vegetation materials that make important contributions to the city and the city people in terms of ecology, social, cultural, economic and aesthetics. A tree inventory system that will be created using GIS technologies will be very helpful in terms of both protecting the trees and tracking the forestation. In Nicosia, the capital of Northern Cyprus, the importance of the trees in the city has started to reflect on public awareness. In this study, with the GIS study carried out on the pilot region selected in Nicosia, trees were registered by using a tree registration form and ArcMap and shown on the system according to their types. The tree information stored in the database together with the data collected in 9 categories will make it easier to track trees and prevent them from being cut down. In addition, in the study, it was explained how the system should be converted into a smart city application with use of mobile technology.

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network.

This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. Tobacco is a major revenue generating crop of Khyber Pakhtunkhwa (KP) province of Pakistan, with over 90% of the country’s Tobacco production. In order to analyze the performance of the developed classification framework, a pilot sub-region named Yar Hussain is selected for experimentation work. Yar Hussain is a tehsil of district Swabi, within KP province of Pakistan, having highest contribution to the gross production of the KP Tobacco crop. KP generally consists of a diverse crop land with different varieties of vegetation, having similar phenology which makes crop classification a challenging task. In this study, a temporal convolutional neural network (TempCNNs) model is implemented for crop classification, while considering remotely sensed imagery of the selected pilot region with specific focus on the Tobacco crop. In order to improve the performance of the proposed classification framework, instead of using the prevailing concept of utilizing a single satellite imagery, both Sentinel-2 and Planet-Scope imageries are stacked together to assist in providing more diverse features to the proposed classification framework. Furthermore, instead of using a single date satellite imagery, multiple satellite imageries with respect to the phenological cycle of Tobacco crop are temporally stacked together which resulted in a higher temporal resolution of the employed satellite imagery. The developed framework is trained using the ground truth data. The final output is obtained as an outcome of the SoftMax function of the developed model in the form of probabilistic values, for the classification of the selected classes. The proposed deep learning-based crop classification framework, while utilizing multi-satellite temporally stacked imagery resulted in an overall classification accuracy of 98.15%. Furthermore, as the developed classification framework evolved with specific focus on Tobacco crop, it resulted in best Tobacco crop classification accuracy of 99%.

An integrated well-pattern optimization strategy to unlock continental tight gas reservoir in China

The successful technology in development the tight gas reservoir in North America—a combination of long horizontal drilling and multi-stages hydraulic fracturing—has poor adaptability for the tight gas reservoir in China, where the tight gas reservoirs are mostly deposited on the background of continental geological setting with thin formation thickness, low lateral continuity and poor permeability. In this work, an integrated well-pattern optimization frame in adaption to the geological setting of Ordos basin is systematically proposed. In this frame, the strong heterogeneity, horizontal sand continuity, multi-layers sand matching, as well as ground surface environment are all adequately considered. The field application of the frame to a pilot region in Yan’an gas field, a typical continental tight gas reservoir in Ordos basin, shows a very good response, which demonstrates the superiority of the proposed frame. The results show that the strong heterogeneity, low horizontal sand continuity, and multi-layers sand matching compel the well spacing to be non-uniform, well pattern to be irregular and well type to be diverse, respectively, meanwhile, the complex ground surface environment gives constraints on the drilling operations. Through this frame, the world-class challenging tight gas reservoir in Ordos basin is successfully unlocked and maximized, which can be taken as a good reference for the development of similar types of tight gas reservoirs in the world.

Does emission trading lead to carbon leakage in China? Direction and channel identifications

Unilateral emission trading may lead to carbon leakage. The leakage direction and channel are critical to multilateral emission mitigation. Despite the increasing number of investigations into the carbon leakage induced by emission trading, there is a lack of empirical research on the specific leakage channels related to the emission trading market. This paper develops a difference-in-difference-in-differences model to identify carbon leakage directions in emission trading pilots in China. The issue of whether market participation and industrial transfer are the specific leakage channels related to emission trading is also examined. Emission trading pilots lead to reverse carbon leakage, which moves from the non-pilot region to the pilot region. Market participation and industrial transfer are confirmed to be the specific leakage channels in emission trading. Of the two channels, market participation is the one that determines the reverse direction.

Distances and Statistics of Local Molecular Clouds in the First Galactic Quadrant

Abstract We present an analysis of local molecular clouds ( km s−1, i.e., <1.5 kpc) in the first Galactic quadrant ( and ), a pilot region of the Milky Way Imaging Scroll Painting (MWISP) CO survey. Using the Spectral Clustering for Interstellar Molecular Emission Segmentation algorithm to divide large molecular clouds into moderate-size ones, we determined distances to 28 molecular clouds with the background-eliminated extinction-parallax method using the Gaia DR2 parallax measurements aided by A G and A V ; the distance ranges from 250 to about 1.5 kpc. These incomplete distance samples indicate a linear relationship between the distance and the radial velocity (V LSR) with a scatter of 0.16 kpc, and kinematic distances may be systematically larger for local molecular clouds. In order to investigate fundamental properties of molecular clouds, such as the total sample number, the line width, the brightness temperature, the physical area, and the mass, we decompose the spectral cube using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. Post-selection criteria are imposed on DBSCAN clusters to remove the noise contamination, and we found that the separation of molecular cloud individuals is reliable based on a definition of independent consecutive structures in l–b–V space. The completeness of the local molecular cloud flux collected by the MWISP CO survey is about 80%. The physical area, A, shows a power-law distribution, dN/d , while the molecular cloud mass also follows a power-law distribution but is slightly flatter, dN/dM ∝ M −1.96 ± 0.11.

A Watershed-Based Water Environment Eco-compensation Mechanism: a Case Study of Taihu Lake Basin, China

In 2008, a simple punitive eco-compensation method was implemented in the Taihu pilot region, China. However, due to the use of a flawed formula and weak compensation criterion the payments were considered unsuitable. To improve the scheme, the following issues were considered: determination of compensation criterion; compensation when water quality is acceptable; consideration of reciprocating flow; control of the errors in pollutant fluxes due to the non-synchronization of river flow and water quality data. Two alternative ways to calculate eco-compensation payments were assessed for a case study in 2013: a payment based on the “Water quality exceedance rate (WQER) method” was found to be 172 million CNY (24.9 million USD). This method avoided errors caused by the pollutant flux and considered the situations of reciprocating flow and acceptable water quality; and the “Pollutant treatment cost (PTC) method” was considered suitable for immediate implementation, although the payment was higher at 245 million CNY (35.4 million USD). The determination of compensation criterion using this method had a scientific basis, but it required perfect and reliable monitoring data. If these conditions are met, the method was considered suitable for future implementation.