Article
Green & Sustainable Science & Technology
Zia ul Rehman Tahir, Saiqa Hafeez, Muhammad Asim, Muhammad Amjad, Muhammad Farooq, Muhammad Azhar, Ghulam Murtza Amjad
Summary: This study evaluated 30 models for estimating diffuse horizontal irradiance, with newly developed models outperforming those selected from literature. The performance of models varies across different zones and stations.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Environmental Sciences
T. Chakraborty, X. Lee, D. M. Lawrence
Summary: The diffuse radiation fertilization effect, an understudied aspect of atmosphere-biosphere interactions, can have important implications for our understanding of the Earth system and future climate projections. However, limited observational data make it difficult to globally constrain this mechanism. Simulations show that uncertainties in the diffuse fraction of sunlight significantly affect simulated gross primary productivity and terrestrial evapotranspiration.
Article
Environmental Sciences
Hao Zhou, Xu Yue, Yadong Lei, Chenguang Tian, Yimian Ma, Yang Cao
Summary: Diffuse radiation can increase plant photosynthesis light use efficiency. By using an artificial neural network model to bias-correct global hourly diffuse fraction, the updated data shows better correlations and reduced errors compared to original reanalysis, leading to improved simulations of global gross primary productivity.
GLOBAL BIOGEOCHEMICAL CYCLES
(2021)
Article
Environmental Sciences
Irfan Uckan, Kameran Mohammed Khudhur
Summary: This study compares sunshine duration-based models with other meteorological parameter-based models and develops new forecasting models. The results show that models based on other meteorological parameters have better predictions, and the newly proposed models provide more accurate estimates of global solar radiation at different locations.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Marcia Akemi Yamasoe, Nilton Manuel Evora Rosario, Samantha Novaes Santos Martins Almeida, Martin Wild
Summary: The study found a dimming effect on surface solar irradiation in Sao Paulo between 1961 and the early 1980s, with no brightening effect observed. There was an increasing trend in cloud cover fraction and surface downward irradiation, while sunshine duration and diurnal temperature range showed decreasing trends.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2021)
Article
Agronomy
Hang Xu, Zhiqiang Zhang, Xiaoyun Wu, Jiaming Wan
Summary: Estimating dynamic changes in gross primary productivity (GPP) of terrestrial ecosystems has always been challenging. Improved big-leaf and two-leaf light use efficiency (LUE) models have been developed to address the effects of diffuse radiation on GPP. However, their global performance has not been comprehensively evaluated.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Siyuan Chen, Lichun Sui, Liangyun Liu, Xinjie Liu
Summary: This paper proposes a method based on the partitioning of diffuse and direct absorbed photosynthetically active radiation for more accurate estimation of half-hourly gross primary productivity (GPP). The method takes into consideration the influence of diffuse radiation and demonstrates a higher level of accuracy compared to total absorbed photosynthetically active radiation-based GPP estimations.
Article
Geosciences, Multidisciplinary
Zhaoyang Zhang, Meng Fan, Minghui Tao, Yunhui Tan, Quan Wang
Summary: Four remote sensing data-driven (RS) models were evaluated in simulating the effect of diffuse radiation on water-use efficiency (WUE). There was a large divergence among RS models in estimating the response of WUE to fraction of diffuse PAR (FDP). PML model performed better than other RS models in simulating the diffuse radiation effect on WUE.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Hao Zhou, Xu Yue, Yadong Lei, Tianyi Zhang, Chenguang Tian, Yimian Ma, Yang Cao
Summary: This study utilized artificial neural networks and FLUXNET site data to estimate the global effect of diffuse radiation. Evaluations showed that the impact of diffuse radiation on GPP has regional characteristics, and the radiation effect does not depend solely on the increase in intensity.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Environmental Sciences
Hao Zhou, Xu Yue, Bin Wang, Chenguang Tian, Xiaofei Lu, Jun Zhu, Yang Cao
Summary: This study combines advanced machine learning algorithms with an established explanatory method to explore the impacts of climatic factors on long-term GPP variability at global FLUXNET sites. The results show that diffuse shortwave radiation plays a dominant role in GPP variability at sub-daily timescales, especially for tree species, and acts as a secondary factor after air temperature at daily or longer timescales.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Energy & Fuels
Shujing Qin, Zhihe Liu, Rangjian Qiu, Yufeng Luo, Jingwei Wu, Baozhong Zhang, Lifeng Wu, Evgenios Agathokleous
Summary: Accurate forecasting of daily global solar radiation (Rs) is important for photovoltaic power and other sectors. A novel sunshine duration converting method (n_new) based on forecasted temperature and weather types data was proposed and validated. The Rs_n new model showed better accuracy than the Rs_n com model and Rs_T model, with increased correlation coefficients (R) and index of agreement (dIA) and decreased root mean squared error (RMSE) for the 1-7 days lead time over 86 sites. The Rs_n new model is recommended for short-term daily Rs forecasting.
Article
Plant Sciences
Peirong Liu, Xiaojuan Tong, Jinsong Zhang, Ping Meng, Jun Li, Jingru Zhang, Yu Zhou
Summary: This study explores the impacts of diffuse fraction (DF) on gross primary productivity (GPP) and light use efficiency (LUE) based on a 6-year dataset of carbon flux in a warm-temperate mixed plantation site in North China. The results show that canopy photosynthesis and the apparent quantum yield (alpha) are significantly higher on cloudy days compared to clear days. Increasing DF enhances GPP and LUE, and both variables are mainly controlled by DF and photosynthetically active radiation (PAR). Incorporating DF into the Michaelis-Menten model improves GPP estimation. The findings emphasize the importance of considering DF in carbon sequestration estimation.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Geosciences, Multidisciplinary
Fei Feng, Kaicun Wang
Summary: By combining SunDu, satellite cloud fraction, and AOD data, this study generated high-spatial-resolution Rs over China from 2000 to 2017, with geographically weighted regression (GWR) showing better performance. The study found that incorporating satellite cloud fraction and AOD data into GWR can produce reliable long-term Rs variations based on SunDu-derived data.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Environmental Sciences
Yamei Shu, Shuguang Liu, Zhao Wang, Jingfeng Xiao, Yi Shi, Xi Peng, Haiqiang Gao, Yingping Wang, Wenping Yuan, Wende Yan, Ying Ning, Qinyuan Li
Summary: Aerosols have an impact on the gross primary productivity (GPP) of plants. This study quantifies the aerosol diffuse fertilization effect (DFE) and incorporates it into a light use efficiency model. The results show that the new model improves the performance in simulating GPP and emphasizes the importance of understanding aerosol-radiation interactions and incorporating aerosol effects into GPP models.
Article
Environmental Sciences
Yimian Ma, Xu Yue, Hao Zhou, Cheng Gong, Yadong Lei, Chenguang Tian, Yang Cao
Summary: This study conducted sensitivity tests on GPP modeling at FLUXNET sites, revealing that biases in meteorology, especially related to photosynthetically active radiation, play a critical role in modulating GPP uncertainties. Simulations using specific forcings help reduce climate-driven biases in GPP significantly.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Geography, Physical
Guiying Li, Longwei Li, Dengsheng Lu, Wei Guo, Wenhui Kuang
GISCIENCE & REMOTE SENSING
(2020)
Article
Geography, Physical
Yaoliang Chen, Shuai Zhao, Zhuli Xie, Dengsheng Lu, Erxue Chen
GISCIENCE & REMOTE SENSING
(2020)
Article
Environmental Sciences
Xiandie Jiang, Guiying Li, Dengsheng Lu, Erxue Chen, Xinliang Wei
Article
Environmental Sciences
Dengqiu Li, Dengsheng Lu, Emilio Moran, Ramon Felipe Bicudo da Silva
Article
Environmental Sciences
Xiaozhi Yu, Dengsheng Lu, Xiandie Jiang, Guiying Li, Yaoliang Chen, Dengqiu Li, Erxue Chen
Article
Remote Sensing
Longwei Li, Nan Li, Zhuo Zang, Dengsheng Lu, Guangxing Wang, Ni Wang
Summary: Moso bamboo has unique characteristics such as fast growth rate, short harvesting cycle, and on/off-year phenomenon. This research used data from the VEN mu S micro-satellite to analyze the phenological features of Moso bamboo forests, determining sensitive spectral ranges for seasonal variation and identifying different phenological periods using the Red-edge Position Index (REPI).
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Geography, Physical
Yaoliang Chen, Xiaotao Huang, Jingfeng Huang, Shanshan Liu, Dengsheng Lu, Shuai Zhao
Summary: The study successfully monitored the dynamics of desert vegetation in a dryland basin of Northwest China using MESMA method. Results showed areas of degradation, recovery, and greening, and analyzed different influencing factors, demonstrating the potential application of this method in semi-arid and arid regions.
GISCIENCE & REMOTE SENSING
(2021)
Article
Biodiversity Conservation
Dengqiu Li, Dengsheng Lu, Yan Zhao, Mingxing Zhou, Guangsheng Chen
Summary: This study developed a new framework to assess habitat fragmentation by integrating spatial patterns of vegetation coverage and its change in the giant panda habitat ecosystem of China. The results revealed that most disturbed areas experienced negative abrupt vegetation change, while undisturbed areas mainly showed an increase in vegetation. By identifying spatial clusters and outliers, the study pinpointed areas in need of careful management to reduce habitat fragmentation.
ECOLOGICAL INDICATORS
(2021)
Article
Geography, Physical
Wenke Lin, Yagang Lu, Guiying Li, Xiandie Jiang, Dengsheng Lu
Summary: This study compares the performance of LS-CHM and L-CHM for FGSV modeling and explores the advantages of using the hierarchical Bayesian approach when sample size is small. The results show that L-CHM provides better predictions overall using the same modeling approaches, but LS-CHM-based variables produce better modeling accuracy than L-CHM-based variables in a specific range of FGSV. The HBA based on stratification of both forest type and slope aspect provides the best FGSV estimation.
GISCIENCE & REMOTE SENSING
(2022)
Article
Environmental Sciences
Mengzhuo Fan, Kuo Liao, Dengsheng Lu, Dengqiu Li
Summary: Examining the characteristics and spatial patterns of vegetation change under different protection levels can provide a scientific basis for national park protection and management. The study analyzed the vegetation change in Wuyishan National Park using Landsat EVI data from 1986 to 2020 and the WBS approach. The results showed that the highest percentage of area without abrupt change was in the strictly protected area, while the non-protected area had the lowest percentage. The study also found that the vegetation coverage generally improved in the park, with higher positive percentage in the protected areas. However, the non-protected area had a higher mean greenness change. The study highlighted the importance of protection level in determining vegetation change and spatial patterns in the national park.
Article
Environmental Sciences
Kuo Liao, Yunhe Li, Bingzhang Zou, Dengqiu Li, Dengsheng Lu
Summary: This study compared the accuracy of tree height measurements using different methods and the influence of allometric models on tree volume estimation accuracy. The results showed significant impacts of different measurement methods on tree volume calculations, and incorporating UAV Lidar data with DBH field measurements can effectively improve tree volume estimation accuracy.
Article
Environmental Sciences
Yi Zhang, Dengsheng Lu, Xiandie Jiang, Yunhe Li, Dengqiu Li
Summary: In this study, the 3-PG model was optimized and calibrated using survey and UAV lidar data at the sample plot scale and applied at the forest sub-compartment scale. The results show that both survey forests age data and remote-sensing-derived forest age data can accurately estimate eucalyptus plantation parameters. The simulation results based on remote-sensed forest age data are significantly better than the ones based on survey data, providing an important reference for future studies using remote sensing-derived forest age data in large spatial scales.
Article
Remote Sensing
Ruoqi Wang, Guiying Li, Yagang Lu, Dengsheng Lu
Summary: This research compared the advantages of using object-based GSV modeling approach with traditional grid-based approaches for poplar GSV estimation. The results showed that the object-based approach was more accurate in estimating GSV and solving the mixed plot problem in the striped forest distribution areas.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Environmental Sciences
Yongpeng Ye, Dengsheng Lu, Zuohang Wu, Kuo Liao, Mingxing Zhou, Kai Jian, Dengqiu Li
Summary: This study developed a framework based on multi-source high-resolution satellite images to analyze vertical characteristics of mountainous vegetation distribution. The results showed distinct differentiation of vegetation types along elevation gradients in Wuyishan National Park, with significant differences in distribution patterns under different human protection levels.
Article
Forestry
Shiyun Pang, Guiying Li, Xiandie Jiang, Yaoliang Chen, Yagang Lu, Dengsheng Lu
Summary: This research aims to explore the method of accurately retrieving forest canopy height from ATLAS data and improve retrieval accuracy by incorporating a high-precision digital terrain model (DTM) and a data-filtering strategy. The results show that using the proposed method, the retrieval accuracy of forest canopy height in mountainous regions with dense forest cover and complex terrain conditions can be considerably improved.
Article
Energy & Fuels
Siddharth Sradhasagar, Omkar Subhasish Khuntia, Srikanta Biswal, Sougat Purohit, Amritendu Roy
Summary: In this study, machine learning models were developed to predict the bandgap and its character of double perovskite materials, with LGBMRegressor and XGBClassifier models identified as the best predictors. These models were further employed to predict the bandgap of novel bismuth-based transition metal oxide double perovskites, showing high accuracy, especially in the range of 1.2-1.8 eV.
Article
Energy & Fuels
Wei Shuai, Haoran Xu, Baoyang Luo, Yihui Huang, Dong Chen, Peiwang Zhu, Gang Xiao
Summary: In this study, a hybrid model based on numerical simulation and deep learning is proposed for the optimization and operation of solar receivers. By applying the model to different application scenarios and considering multiple performance objectives, small errors are achieved and optimal structure parameters and heliostat scales are identified. This approach is not only applicable to gas turbines but also heating systems.
Article
Energy & Fuels
Mubashar Ali, Zunaira Bibi, M. W. Younis, Muhammad Mubashir, Muqaddas Iqbal, Muhammad Usman Ali, Muhammad Asif Iqbal
Summary: This study investigates the structural, mechanical, and optoelectronic properties of the BaCuF3 fluoroperovskite using the first-principles modelling approach. The stability and characteristics of different cubic structures of BaCuF3 are evaluated, and the alpha-BaCuF3 and beta-BaCuF3 compounds are found to be mechanically stable with favorable optical properties for solar cells and high-frequency UV applications.
Article
Energy & Fuels
Dong Le Khac, Shahariar Chowdhury, Asmaa Soheil Najm, Montri Luengchavanon, Araa mebdir Holi, Mohammad Shah Jamal, Chin Hua Chia, Kuaanan Techato, Vidhya Selvanathan
Summary: A novel recycling system is proposed in this study to decompose and reclaim the constituent materials of organic-inorganic perovskite solar cells (PSCs). By utilizing a one-step solution process extraction approach, the chemical composition of each layer is successfully preserved, enabling their potential reuse. The proposed recycling technique helps mitigate pollution risks, minimize waste generation, and reduce recycling costs.
Article
Energy & Fuels
Peijie Lin, Feng Guo, Xiaoyang Lu, Qianying Zheng, Shuying Cheng, Yaohai Lin, Zhicong Chen, Lijun Wu, Zhuang Qian
Summary: This paper proposes an open-set fault diagnosis model for PV arrays based on 1D VoVNet-SVDD. The model accurately diagnoses various types of faults and is capable of identifying unknown fault types.