Article
Energy & Fuels
Peiran Sun, Xuejun Hao, Jun Wang, Di Shen, Lu Tian
Summary: This study focuses on the low-carbon economic operation of the integrated energy system under the carbon trading mechanism in China, using commercial optimization software to study the operation modes under different carbon trading prices. The results show that operation modes in summer change significantly with the increase of carbon trading prices, while operation modes in winter remain basically unchanged; the integrated energy system can not only reduce carbon emissions under the carbon trading mechanism, but also reduce annual total cost.
ENERGY SCIENCE & ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Xiyun Yang, Lingzhuochao Meng, Xintao Gao, Wenbing Ma, Liwei Fan, Yan Yang
Summary: This study proposes a low-carbon economic scheduling model for the ADN system, taking into account the step-type carbon emissions trading mechanism and source-load side uncertainty. By using the discretized step transformation and convolutional sequence operation, the multi-dimensional discrete probability sequences of the source-load side are converted into the global equivalent load (EL), with the predicted value of EL expressed as the expected value of the EL probability sequence. The proposed strategy considers the influence of power prediction error on the ADN system by setting the probability constraint of the spinning reserve capacity, and converts the chance constraint problem to a deterministic mixed-integer linear programming problem by linearizing power flow constraints. Experimental results show that the strategy achieves synergy between economic and environmental benefits, with significantly reduced solution time compared to other intelligent algorithms and improved optimization effect.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Energy & Fuels
Xiujie Tan, Qian Sun, Meiji Wang, Tsun Se Cheong, Wai Yan Shum, Jinpeng Huang
Summary: This study provides firm level evidence on the effects of the carbon emissions trading system (ETS) by examining the Hubei ETS pilot in China. The results demonstrate that ETS can potentially reduce energy consumption, shift from coal to electricity, and decouple economic growth from fossil energy and carbon emissions.
Article
Green & Sustainable Science & Technology
Dewen Liu, Zhao Luo, Jinghui Qin, Hua Wang, Gang Wang, Zhao Li, Weijie Zhao, Xin Shen
Summary: In this paper, a multi-district integrated energy systems scheduling model considering the carbon emission trading and green certificate trading mechanisms is proposed. The feasibility of introducing these mechanisms into the integrated energy system is analyzed, and a joint trading market framework is established using a combinatorial double auction mechanism. The impacts of carbon emission trading, green certificate trading, and changes in natural gas prices on system operating costs are analyzed, and case studies demonstrate the effectiveness of the proposed model.
Article
Energy & Fuels
Yue Xiang, Mengqiu Fang, Junyong Liu, Pingliang Zeng, Ping Xue, Gang Wu
Summary: This paper proposes a hierarchical distributed dispatch model of Multiple Energy Systems (MESs) considering carbon trading. The effectiveness of the proposed method is proved by comparing it with a centralized algorithm in a case study based on a 3-MES system. The impacts of different carbon prices on MESs with different resource endowments are also analyzed.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2023)
Article
Energy & Fuels
Qiang Fan, Jiaming Weng, Dong Liu
Summary: In this paper, a bi-level scheduling model is proposed to investigate the low-carbon operation of electricity and natural gas integrated energy systems. The upper level formulates an optimal energy flow model considering carbon trading, while the lower level introduces a developed demand-side management strategy to enable user participation in joint energy and carbon trading. The model is solved iteratively to reach an equilibrium, and case studies demonstrate the effectiveness of the proposed method in reducing carbon emissions and improving consumer surplus.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Economics
Sheng Zhou, Qing Tong, Xunzhang Pan, Min Cao, Hailin Wang, Ji Gao, Xunmin Ou
Summary: This study examines China's low-carbon energy transformation from a global perspective, finding that to achieve the goals of the Paris Agreement, China should advance its peak CO2 emissions and increase deep emissions reduction efforts, with a particular focus on the power and industrial sectors.
Article
Energy & Fuels
Jing-Yue Liu, Yue-Jun Zhang
Summary: This study evaluates the impact of China's Emissions Trading Scheme (ETS) on non-fossil energy development using a difference-in-differences model. The results show that the ETS has significantly promoted the development of non-fossil energy in China, with a greater impact observed with higher carbon prices.
Article
Multidisciplinary Sciences
Yash Dixit, Hassan El-Houjeiri, Jean-Christophe Monfort, Liang Jing, Yiqi Zhang, James Littlefield, Wennan Long, Christoph Falter, Alhassan Badahdah, Joule Bergerson, Raymond L. Speth, Steven R. H. Barrett
Summary: The transition in the energy mix has increased the need for accurate emissions reporting in the petroleum supply chain. Current carbon footprint assessments lack resolution and traceability, leading to poor visibility into carbon intensities in crude oil trading. Through the use of high-fidelity datasets and optimization algorithms, this study reveals significant variability in carbon intensities at the level of crude trade pathways. By prioritizing low-carbon supply chain pathways, additional CO2-equivalent savings can be realized.
NATURE COMMUNICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Hongbin Sun, Xinmei Sun, Lei Kou, Wende Ke
Summary: Against the background of the 30 x 60 target, this study proposes an optimal dispatching model for a park-level integrated energy system considering flexible load and Power-to-Gas (P2G) participation in the carbon trading market. The results demonstrate the importance of considering the operational cost of P2G and the feasibility of integrating operating economy and wind power accommodation ability in integrated energy systems.
Article
Economics
Qianqian Hong, Linhao Cui, Penghui Hong
Summary: This study examines the impact of carbon emissions trading on energy efficiency and finds that it can significantly improve energy efficiency in cities, particularly in areas with high marketization and industrial agglomeration.
Article
Multidisciplinary Sciences
Xiaoyong Zhou, Ye Hang, Dequn Zhou, B. W. Ang, Qunwei Wang, Bin Su, Peng Zhou
Summary: The carbon costs and economic benefits of ICT trade are unevenly distributed among global regions, with emerging economies bearing the carbon emissions and developed economies gaining the value-added. However, this inequality has decreased from 2000 to 2018, partly due to global production fragmentation.
Article
Economics
Yanfang Zhang, Jinpeng Wei, Qi Gao, Xunpeng Shi, Dequn Zhou
Summary: The Chinese government implemented an energy-consumption permit trading scheme (ECPTS) and a carbon emissions trading scheme (ETS) in Fujian Province. The study found that coastal cities dominate the allocation of energy-consumption permits and carbon allowances, leading to economic inequality among cities in Fujian. However, by introducing the principle of equity, the allocation structure of energy-consumption permits can be adjusted to mitigate the distributional inequality in economic development rights among cities.
Article
Green & Sustainable Science & Technology
Xiaoyu Ju, Jie Wan, Ziwei Zhang, Chunai Ma, Liangwei Zhang, Xiaodong Zhao
Summary: Balancing sustainable economic growth and environmental protection is crucial for mitigating climate change in developing countries. This study analyzed the impact of carbon emissions trading policy on Chongqing's carbon emissions and economic development using various methods. The results indicate that carbon trading helps reduce carbon emissions while maintaining economic growth, and the economic activity effect and energy intensity effect mediate the reduction in carbon emissions.
Article
Green & Sustainable Science & Technology
Huarong Peng, Shaozhou Qi, Jingbo Cui
Summary: The study shows that China's carbon emission trading scheme contributes to a reduction in carbon emissions and an improvement in energy efficiency, especially in regions using benchmarking allowance allocation. However, the scheme has minimal impacts on employment and returns on assets.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2021)
Article
Green & Sustainable Science & Technology
Hao Fu, Peng Li, Xiaopeng Fu, Zhiying Wang, Jinyue Yan, Jianzhong Wu, Chengshan Wang
Summary: This paper presents an asynchronous multi-rate method and design for the real-time simulation of large-scale active distribution networks (ADNs). The proposed method decouples the ADN into different subsystems and assigns optimized time-steps to each subsystem, enabling fully distributed simulation. Real-time results demonstrate the superiority of this method in simulation flexibility and accuracy.
IET RENEWABLE POWER GENERATION
(2023)
Article
Energy & Fuels
Mingxuan Mao, Siyu Chen, Jinyue Yan
Summary: This paper proposes a dynamic modelling of two-lane pavement photovoltaic arrays based on cellular automata theory, and explores the influence of random vehicle shadows on the output characteristics. A mathematical model of two-lane pavement PV arrays considering bypass diodes and blocking diodes is established. An asymmetric two-lane Nagel-Scheckenberg (ATNS) model is introduced to characterize the change of irradiation intensity caused by vehicle shadows. Simulations and experiments show that the slowing probability and shading degree significantly affect the output characteristics, and the dynamic random vehicle shadows result in a changing multi-peak state of the power-voltage curve.
Article
Thermodynamics
Houpei Li, Jun Li, Sihui Li, Jinqing Peng, Jie Ji, Jinyue Yan
Summary: This study investigated the matching characteristics of PVAC using a case in an office room. A coupled simulation model was built to integrate the building, PV, AC, and control strategy. The results showed that optimizing the PV and battery capacities, as well as setting the PV factor and battery factor appropriately, could maximize the AC efficiency and ensure grid flexibility.
Article
Thermodynamics
Huiru Sun, Bingbing Chen, Kehan Li, Yongchen Song, Mingjun Yang, Lanlan Jiang, Jinyue Yan
Summary: This study analyzes the factors influencing hydrate re-formation characteristics by simulating two-phase flow in hydrate sediment. The results show that temperature and pressure exhibit three stages of change in the water-dominated two-phase flow process. A lower effective sectional velocity of water enhances the hydrate re-formation process. Meanwhile, the gas phase impedes mass transfer on the water-hydrate interface and acts as a nucleation site to promote hydrate re-formation. The onset time of flow blockage is linearly positively correlated with the effective sectional velocity of water, but the amount of hydrate re-formation decreases with increasing velocity.
Article
Thermodynamics
Zhengyi Luo, Jinqing Peng, Yutong Tan, Rongxin Yin, Bin Zou, Maomao Hu, Jinyue Yan
Summary: Leveraging the flexibility of static batteries and residential flexible loads is an effective way to reduce the impacts of intermittent renewable energy power generation on the utility grid. A novel forecasting and flexibility-based operation strategy was proposed for the PV-battery-FL system to manage distributed energy resources. The strategy fully harnesses the flexibility of batteries and residential flexible loads, and outperforms traditional strategies in terms of grid-friendliness and performance.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Automation & Control Systems
Jian Du, Jianqin Zheng, Yongtu Liang, Qi Liao, Bohong Wang, Xu Sun, Haoran Zhang, Maher Azaza, Jinyue Yan
Summary: Recently, clean solar energy has gained attention for its potential in electricity production. However, current studies lack consideration of the regional correlation characteristics of photovoltaic power generation (PVPG) and fail to propose effective frameworks incorporating prior knowledge for more physically reasonable results. In this study, a hybrid deep learning framework is introduced to capture spatial correlations and temporal dependency patterns, incorporating scientific theory and domain knowledge for physically reasonable predictions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Jinli Zhao, Ziqi Zhang, Hao Yu, Haoran Ji, Peng Li, Wei Xi, Jinyue Yan, Chengshan Wang
Summary: In this article, a cloud-edge collaboration-based local voltage control strategy for distributed generators (DGs) is proposed with privacy preservation. The strategy utilizes a surrogate model and federated learning to optimize voltage control performance and protect sensitive information, effectively mitigating voltage violations in active distribution networks.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Green & Sustainable Science & Technology
Lili Wang, Xinyu Huang, Masoud Babaei, Zhengguang Liu, Xiaohu Yang, Jinyue Yan
Summary: Geothermal energy utilization is crucial in the transition to sustainable energy sources. A hybrid geothermal system that uses CO2 as the working fluid can generate electricity and utilize waste heat and GSHPs for heating. This system has the potential to effectively utilize geothermal energy for a sustainable future.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Environmental Studies
Weila Gong, Joanna I. Lewis
Summary: As China's Belt and Road Initiative (BRI) takes the lead as the largest public financier for global energy infrastructure projects, concerns about environmental and climate impacts have prompted international pressure for greener investment practices. This study examines the role of international engagement in greening China's BRI, proposing direct and indirect models of engagement and identifying factors that have hindered international influence. Opportunities for international engagement with China regarding its overseas investment practices are also suggested.
ENVIRONMENTAL POLITICS
(2023)
Article
Green & Sustainable Science & Technology
Zhengguang Liu, Wene Wang, Yuntian Chen, Lili Wang, Zhiling Guo, Xiaohu Yang, Jinyue Yan
Summary: It is widely recognized that climate change has drawn extensive attention to carbon sequestration in solar greenhouse plants. Solar greenhouse technologies have played and will continue to play a leading role in this crucial transition. The main objective of this research is to investigate the energy efficiency and carbon sequestration potential of a solar-assisted ground-source heat pump (SAGSHP) heating system. This hybrid system, combining a horizontal ground-source heat pump (GSHP) system with PVT and heat storage, effectively meets the heating demands of a greenhouse and functions as a positive energy building. Four plant species, including cucumber, tomato, cowpea, and lettuce, were selected for comparison of carbon absorption effects. The results demonstrate that the hybrid system outperforms conventional systems, with a coefficient of performance (COP) of 6.71 during peak hours and PVT efficiency over 57.88%, satisfying the heat load of the greenhouse while maintaining comfortable indoor temperatures. Additionally, tomato exhibited the highest photosynthetic carbon sequestration of 3522 kgCO(2).m(-2), while cowpea showed the strongest daily carbon sequestration capacity at 26.86 gCO(2)m(-2)d(-1) and better economic income. Through the implementation of this enhanced solar greenhouse, solar energy utilization can be enhanced, flexible interaction between energy and information flow can be established, and a promising option for sustainable building design can be created.
Article
Engineering, Environmental
Zhen Huang, Lingri Ying, Fengchun Gong, Jianfeng Lu, Weilong Wang, Jing Ding, Jinyue Yan
Summary: Carbon dioxide capture and storage (CCS) is a promising strategy for reducing CO2 emissions, and the development of CO2 adsorption materials with high selectivity and adsorption capacity is crucial for this technology. This study synthesized a new MOF adsorbent (SAP-MIL-125) by modifying the MIL-125 MOF with aminosilane, which showed improved CO2 adsorption capacity at room temperature. SAP-MIL-125 exhibited excellent selectivity for CO2 and good stability over multiple adsorption-desorption cycles. The adsorption mechanism of CO2 on SAP-MIL-125 was identified as non-homogeneous layer chemisorption.
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING
(2023)
Article
Energy & Fuels
Hao Fu, Peng Li, Xiaopeng Fu, Jinyue Yan, Zhiying Wang, Kun Wang, Jianzhong Wu, Chengshan Wang
Summary: This paper presents a compact real-time simulator for large-scale wind farms based on field programmable gate array (FPGA). A spatial-temporal parallel design method is proposed to address the demand for huge computing resources associated with detailed modeling. The wind farm is decoupled into subsystems and the electrical system and control system of each subsystem are solved in parallel. The simulation incorporates module-level and superscalar pipeline techniques to improve hardware resource utilization. Case studies demonstrate the accuracy and effectiveness of the proposed design.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2023)
Article
Energy & Fuels
Zhengguang Liu, Xiaohu Yang, Hafiz Muhammad Ali, Ran Liu, Jinyue Yan
Summary: This paper provides an integrated assessment on developing a nanofluid geothermal-photovoltaic hybrid system that addresses the multi-objective optimization and multicriteria evaluation difficulties. The results show that the combination of 2% Al2O3 nanofluid and spiral pipe has the optimum performance. The proposed coupling system proves the robustness and superiority of the hybrid system.
Article
Remote Sensing
Rui Zhu, Dongxue Guo, Man Sing Wong, Zhen Qian, Min Chen, Bisheng Yang, Biyu Chen, Haoran Zhang, Linlin You, Joon Heo, Jinyue Yan
Summary: To estimate electricity generation and evaluate the socio-economic effects of solar photovoltaic (PV) systems, accurate calculation of installed PV areas and capacity is critical. This study proposes a detail-oriented deep learning network called Deep Solar PV Refiner to enhance PV segmentation from satellite imagery. The optimized network outperforms the benchmark network in various evaluation metrics, and also has competitive performance with state-of-the-art semantic segmentation networks.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Letter
Energy & Fuels
Jinyue Yan
ADVANCES IN APPLIED ENERGY
(2023)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
