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تعداد مقالات یافته شده: 3
ردیف عنوان نوع
1 Optimal carbon storage reservoir management through deep reinforcement learning
مدیریت بهینه ذخیره مخزن کربن از طریق یادگیری تقویتی عمیق-2020
Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decisionmaking problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.
Keywords: Reinforcement learning | Multistage decision-making | Deep autoregressive model | Deep Q network | Surrogate modeling | Markov decision process | Geological carbon sequestration
مقاله انگلیسی
2 Identifying the terrestrial carbon benefits from ecosystem restoration in ecologically fragile regions
شناسایی فواید کربن زمینی از ترمیم اکوسیستم در مناطق شکننده محیط زیست-2020
Ecosystem restoration is an urgent and vital measure to restore degraded land in ecologically fragile regions. The terrestrial carbon sequestration capacity is important to indicate the effectiveness of ecosystem restoration, which has attracted the interest of many researchers. Ecologically fragile regions cover a large area in China, but few studies have focused on the carbon benefit of ecological restoration in these regions. In this study, we investigated the spatial and temporal changes in the carbon benefit, indicated by net primary productivity (NPP), in ecologically fragile regions in China. We evaluated the contributions of ecological restoration and climate change to terrestrial ecosystem carbon sink changes. The results showed that the ecological restoration projects significantly improved the carbon sequestration capacity in most of the ecologically fragile regions. From 2001–2017, the annual NPP of the entire study region was 460.1±5.4 Tg C yr−1, and more than 70 % of the ecologically fragile region experiencing a significant (p<0.05) increase. The effect of ecological restoration projects significantly intensified and was the main driver of the NPP growth in 87 % of the study region. The land use and land cover (LULC) change pattern indicates that the restoration project-induced conversion of agricultural land contributed to nearly 10 % of the total carbon sequestration after 2010. However, some extreme climatic conditions weakened the effectiveness of ecological restoration projects, highlighting the need for stricter management. Finally, this study identified the key area for effective ecological restoration in ecologically fragile regions in China.
Keywords: Carbon sequestration | Ecological restoration project | Ecologically fragile region
مقاله انگلیسی
3 Mountain farmland protection and fire-smart management jointly reduce fire hazard and enhance biodiversity and carbon sequestration
حفاظت از زمین های کشاورزی کوهستانی و مدیریت هوشمند آتش سوزی به طور مشترک خطر آتش سوزی را کاهش می دهد و تنوع زیستی و ترسیب کربن را افزایش می دهد-2020
The environmental and socio-economic impacts of wildfires are foreseen to increase across southern Europe over the next decades regardless of increasing resources allocated for fire suppression. This study aims to identify fire- smart management strategies that promote wildfire hazard reduction, climate regulation ecosystem service and biodiversity conservation. Here we simulate fire-landscape dynamics, carbon sequestration and species dis- tribution (116 vertebrates) in the Transboundary Biosphere Reserve Gerês-Xurés (NW Iberia). We envisage 11 scenarios resulting from different management strategies following four storylines: Business-as-usual (BAU), expansion of High Nature Value farmlands (HNVf), Fire-Smart forest management, and HNVf plus Fire-Smart. Fire-landscape simulations reveal an increase of up to 25% of annual burned area. HNVf areas may counter- balance this increasing fire impact, especially when combined with fire-smart strategies (reductions of up to 50% between 2031 and 2050). The Fire-Smart and BAU scenarios attain the highest estimates for total carbon se- questered. A decrease in habitat suitability (around 18%) since 1990 is predicted for species of conservation concern under the BAU scenario, while HNVf would support the best outcomes in terms of conservation. Our study highlights the benefits of integrating fire hazard control, ecosystem service supply and biodiversity con- servation to inform better decision-making in mountain landscapes of Southern Europe.
Keywords: Biomod2 | Fire-smart landscape management | Fire suppression | InVEST model | Land abandonment | REMAINS model | Wildfires
مقاله انگلیسی
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