{"title":"种植转基因树木对大气二氧化碳控制作用的模拟研究","authors":"Maitri Verma, A. Verma","doi":"10.1111/nrm.12300","DOIUrl":null,"url":null,"abstract":"The increase in carbon dioxide (CO2) gas concentration in the atmosphere is primarily responsible for the threat of global warming. Forest is one of the prime sinks of CO2. The reduction in the global forest cover due to human activities has contributed significantly to the increase in CO2 levels. Reforestation and afforestation are avenues to control the atmospheric CO2 level; however, several demographic, ecological, and economic constraints exist in the large‐scale plantations. In this scenario, the plantation of genetically modified trees, which absorb more CO2 from the atmosphere, may aid in attaining the CO2 mitigation target. In this study, a mathematical model is proposed to investigate the effect of the plantation of genetically modified trees on the control of the atmospheric CO2 level. A comprehensive qualitative analysis of the model is carried out. The model is calibrated to fit the actual data of global CO2 concentration, population, and forest area. Numerical simulations are carried out to show the effect of key parameters on the dynamics of forest cover and atmospheric CO2 gas. The optimal strategies for the reduction in CO2 concentration while minimizing the implementation cost of plantation programs are also investigated by proposing the optimal control problem.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12300","citationCount":"10","resultStr":"{\"title\":\"Effect of plantation of genetically modified trees on the control of atmospheric carbon dioxide: A modeling study\",\"authors\":\"Maitri Verma, A. Verma\",\"doi\":\"10.1111/nrm.12300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increase in carbon dioxide (CO2) gas concentration in the atmosphere is primarily responsible for the threat of global warming. Forest is one of the prime sinks of CO2. The reduction in the global forest cover due to human activities has contributed significantly to the increase in CO2 levels. Reforestation and afforestation are avenues to control the atmospheric CO2 level; however, several demographic, ecological, and economic constraints exist in the large‐scale plantations. In this scenario, the plantation of genetically modified trees, which absorb more CO2 from the atmosphere, may aid in attaining the CO2 mitigation target. In this study, a mathematical model is proposed to investigate the effect of the plantation of genetically modified trees on the control of the atmospheric CO2 level. A comprehensive qualitative analysis of the model is carried out. The model is calibrated to fit the actual data of global CO2 concentration, population, and forest area. Numerical simulations are carried out to show the effect of key parameters on the dynamics of forest cover and atmospheric CO2 gas. The optimal strategies for the reduction in CO2 concentration while minimizing the implementation cost of plantation programs are also investigated by proposing the optimal control problem.\",\"PeriodicalId\":49778,\"journal\":{\"name\":\"Natural Resource Modeling\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2021-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1111/nrm.12300\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Natural Resource Modeling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1111/nrm.12300\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Natural Resource Modeling","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1111/nrm.12300","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Effect of plantation of genetically modified trees on the control of atmospheric carbon dioxide: A modeling study
The increase in carbon dioxide (CO2) gas concentration in the atmosphere is primarily responsible for the threat of global warming. Forest is one of the prime sinks of CO2. The reduction in the global forest cover due to human activities has contributed significantly to the increase in CO2 levels. Reforestation and afforestation are avenues to control the atmospheric CO2 level; however, several demographic, ecological, and economic constraints exist in the large‐scale plantations. In this scenario, the plantation of genetically modified trees, which absorb more CO2 from the atmosphere, may aid in attaining the CO2 mitigation target. In this study, a mathematical model is proposed to investigate the effect of the plantation of genetically modified trees on the control of the atmospheric CO2 level. A comprehensive qualitative analysis of the model is carried out. The model is calibrated to fit the actual data of global CO2 concentration, population, and forest area. Numerical simulations are carried out to show the effect of key parameters on the dynamics of forest cover and atmospheric CO2 gas. The optimal strategies for the reduction in CO2 concentration while minimizing the implementation cost of plantation programs are also investigated by proposing the optimal control problem.
期刊介绍:
Natural Resource Modeling is an international journal devoted to mathematical modeling of natural resource systems. It reflects the conceptual and methodological core that is common to model building throughout disciplines including such fields as forestry, fisheries, economics and ecology. This core draws upon the analytical and methodological apparatus of mathematics, statistics, and scientific computing.