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Ecological Compensation Method for Soil Polluted by Heavy Metals Based on Internet of Things
Método de compensación ecológica para suelos contaminados por metales pesados basado en Internet de las cosas
DOI:
https://doi.org/10.15446/esrj.v24n2.87441Palabras clave:
Heavy Metal Pollution, Soil, Ecological Compensation, Internet of Things, (en)Contaminación por metales pesados, Suelo, Compensación ecológica, Internet de las Cosas, (es)
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The traditional ecological compensation method for soil polluted by heavy metals is complicated and consumes a lot of manpower and material resources, and cannot meet the real life needs, so take the area where the soil is polluted by heavy metals as an example. Increasing soil retention in this area is the specific target for ecological compensation, and compensation for polluted areas is based on the internet of things. The willingness of users to participate in the land heavy metal pollution control project was studied, and the pollution degree was calculated. Through radio frequency identification information sensing equipment, the soil heavy metal pollution area was connected with the Internet according to the agreed agreement, and the information exchange was carried out, so as to provide the basis for the ecological compensation standard of soil heavy metal pollution area. According to the content, changing trend and characteristics of pollutants in the study area, the best forest species were selected for this area, and the soil retention was increased to the maximum extent in order to realize the ecological compensation to the area polluted by heavy metals. The final results show that the ecological compensation method for soil polluted with heavy metals based on the internet of things is cost-effective and has great feasibility, which can be the important means for sustainable development of ecological construction.
El método tradicional de compensación ecológica para el suelo contaminado por metales pesados es complicado, consume mucha mano de obra y recursos materiales, y no puede satisfacer las necesidades de la vida real, por lo tanto, se toma como ejemplo el área donde el suelo está contaminado por metales pesados. El aumento de la retención del suelo en esta área es el objetivo específico de la compensación ecológica, y la compensación de las áreas contaminadas se basa en Internet de las cosas. Se estudió la disposición de los usuarios a participar en el proyecto de control de la contaminación por metales pesados y se calculó el grado de contaminación. A través del equipo de detección de información de identificación por radiofrecuencia, el área de contaminación de metales pesados del suelo se conectó a Internet segùn el acuerdo, y el intercambio de información se llevó a cabo, a fin de proporcionar la base para el estándar de compensación ecológica del área de contaminación de metales pesados del suelo. Según el contenido, la tendencia cambiante y las características de los contaminantes en el área de estudio, se seleccionaron las mejores especies forestales para esta área, y la retención del suelo se incrementó al máximo para obtener la compensación ecológica al área contaminada por metales pesados. Los resultados finales muestran que el método de compensación ecológica para el suelo contaminado con metales pesados basado en Internet de las cosas es rentable y tiene una gran viabilidad, que puede ser el medio importante para el desarrollo sostenible de la construcción ecológica.
Referencias
Chen, I. A., Markowitz, V. M., Chu, K., Palaniappan, K., Szeto, E., Pillay, M., Ratner, A., Huang, J., Andersen, E., Huntemann, M., Varghese, N., Hadjithomas, M., Tennessen, K., Nielsen, T., Ivanova, N. N., & Kyrpides, N. C. (2017). IMG/M: Integrated Genome and Metagenome Comparative Data Analysis System. Nucleic Acids Research, 45, D507.
Cunha, E. R. D., Bacani, V. M., & Panachuki, E. (2017). Modeling Soil Erosion Using RUSLE and GIS in A Watershed Occupied by Rural Settlement in the Brazilian Cerrado. Natural Hazards, 85, 1-18.
Diepens, N. J., & Koelmans, A. A. (2018). Accumulation of Plastic Debris and Associated Contaminants in Aquatic Food Webs. Environmental Science & Technology, 52, 8510-8520.
Gäsiorek, M., Kowalska, J., Mazurek, R., & Pajak, M. (2017). Comprehensive Assessment of Heavy Metal Pollution in Topsoil of Historical Urban Park on an Example of the Planty Park in Krakow. Chemosphere, 179, 148-158.
Gao, W., Ghanbari, B., & Baskonus, H. M. (2019). New numerical simulations for some real world problems with Atangana-Baleanu fractional derivative. Chaos, Solitons & Fractals, 128, 34-43.
He, J., Li, Y. W., Xu, D., Liang, X., Liang, B., & Wang, C. (2017). Deadbeat Weighted Average Current Control With Corrective Feed-Forward Compensation for Microgrid Converters With Nonstandard LCL Filter. IEEE Transactions on Power Electronics, 32, 2661-2674.
He, Q., Zeng, C., Xie, P., Liu, Y., & Zhang, M. (2018). An Assessment of Forest Biomass Carbon Storage and Ecological Compensation Based on Surface Area: A Case Study of Hubei Province, China. Ecological Indicators, 90, 392-400.
Kaiserbunbury, C. N., Mougal, J., Whittington, A. E., Valentin, T., Gabriel, R., Olesen, J. M., & Blüthgen, N. (2017). Ecosystem Restoration Strengthens Pollination Network Resilience and Function. Nature, 542, 223.
Kan, T., Nguyen, T. D., White, J. C., Malhan, R. K., & Mi, C. C. (2017). A New Integration Method for an Electric Vehicle Wireless Charging System Using LCC Compensation Topology: Analysis and Design. IEEE Transactions on Power Electronics, 32, 1638-1650.
Kim, J., Johnson, L. E., Cifelli, R., Choi, J., & Chandrasekar, C. (2018). Derivation of Soil Moisture Recovery Relation Using Soil Conservation Service (SCS) Curve Number Method. Water, 10, 833.
Kokkonis, G., Psannis, K. E., Roumeliotis, M., & Schonfeld, D. (2017). Real-time Wireless Multisensory Smart Surveillance with 3D-HEVC Streams for Internet-Of-Things. Journal of Supercomputing, 73, 1-19.
Li, Y., Qiu, J., Zhao, B., Pavao-Zuckerman, M., Bruns, A., Qureshi, S., Zhang, C., & Li, Y. (2017). Quantifying Urban Ecological Governance: A Suite of Indices Characterizes the Ecological Planning Implications of Rapid Coastal Urbanization. Ecological Indicators, 72, 225-233.
Lin, Y., Chen, J., Jin, Z., Quan, Y., Han, P., Guan, S., & Jiang, X. (2018). Impacts of Human Activities on Coastal Ecological Environment during the Rapid Urbanization Process in Shenzhen, China. Ocean & Coastal Management, 154, 121-132.
Liu, C., Wei, C., Zhang, C., Ma, M., Rao, W., Li, W., He, K., & Gao, M. (2018). Developing the Ecological Compensation Criterion of Industrial Solid Waste Based on Emergy for Sustainable Development. Energy, 157, 940-948.
Liu, H., Xu. R. Z., & Yu. H. L. (2017). Simulation of Agricultural Greenhouse Humidity Data Extraction Based on Internet of Things. Computer Simulation, 34.
Lomas, J., Claxton, K., Martin, S., & Soares, M. (2018). Resolving the “Cost-Effective but Unaffordable” Paradox: Estimating the Health Opportunity Costs of Nonmarginal Budget Impacts. Value in Health, S1098301517336136.
Millard, L., Davies, N. M., Gaunt, T. R., Davey-Smith, G., & Tilling, K. (2018). Software Application Profile: PHESANT: A Tool for Performing Automated Phenome Scans in UK Biobank. International Journal of Epidemiology, 47, 29-35.
Monaco, D., Chianese, E., Riccio, A., Delgado-Sanchez, A., & Lacorte, S. (2017). Spatial Distribution of Heavy Hydrocarbons, Pahs and Metals in Polluted Areas (The case of “Galicia”, Spain). Marine Pollution Bulletin, 121, 230.
Myhre, G., Forster, P. M., Samset, B. H., Hodnebrog, O., Sillmann, J., Aalbergsjo, S. G., Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Iversen, T., Kasoar, M., Kharin, V., Kirkevag, A., Lamarque, J. F., Olivié, D., Richardson, T. B., Shindell, D., Shine, K. P., … Zwiers, F. (2017). PDRMIP: A Precipitation Driver and Response Model Intercomparison Project—Protocol and Preliminary Results. Bulletin of the American Meteorological Society, 98, 1185-1198.
Oliveira, L. M., Maillard, P., & Andrade Pinto, E. J. (2017). Application of a Land Cover Pollution Index to Model Non-Point Pollution Sources in a Brazilian Watershed. Catena, 150, 124-132.
Shu, L. (2018). Games between Stakeholders and the Payment for Ecological Services: Evidence from the Wuxijiang River Reservoir Area in China. 6:e4475.
Sun, P. G., & Ma, X. (2017). Understanding the Controllability of Complex Networks from the Microcosmic to the Macrocosmic. New Journal of Physics, 19, 013022.
Yang, G., Shang, P., He, L., Zhang, Y., Wang, Y., Zhang, F., Zhu, L., & Wang, Y. (2019). Interregional Carbon Compensation Cost Forecast and Priority Index Calculation Based on the Theoretical Carbon Deficit: China as a Case. Science of the Total Environment, 654, 786-800.
Zabihollah, R. (2017). Supply Chain Management and Business Sustainability Synergy: A Theoretical and Integrated Perspective. Sustainability, 10, 275.
Zhang, T., Li, B., Yuan, Y., Gao, X., Sun, Q., Xu, L., & Jiang, Y. (2018). Spatial Downscaling of TRMM Precipitation Data Considering the Impacts of Macro-Geographical Factors and Local Elevation in the Three-River Headwaters Region. Remote Sensing of Environment, 215, 109-127.
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