Article
Environmental Sciences
Manish Soni, Sunita Verma, Manoj K. Mishra, R. K. Mall, Swagata Payra
Summary: This study uses a combination of satellite retrievals and a weather model to estimate ground-level PM10 concentration. The results show that the model captures the spatial pattern of PM10 well, but underestimates the aerosol loading. A scaling is applied to improve the estimation, resulting in better agreement with observational data. The study demonstrates the importance of integrating satellite data and models for accurate estimation of particulate pollution.
Article
Environmental Sciences
Horatiu Ioan Stefanie, Andrei Radovici, Alexandru Mereuta, Viorel Arghius, Horia Camarasan, Dan Costin, Camelia Botezan, Camelia Ginsca, Nicolae Ajtai
Summary: This study investigates the aerosol climatology in the Cluj-Napoca area in Romania using 10 years of ground-based measurements from 2010 to 2020. The results show higher aerosol loads in July and August, and the angstrom exponent has the lowest values in April and May, and the highest in August. The study also performs aerosol classification using AERONET data.
Article
Environmental Sciences
Ming Zhang, Lei Zhang, Qingqing He, Yanbin Yuan
Summary: The study evaluated the performance of the MODIS C6.1 3 km AOD product over China, finding that the C6.1_3km product outperformed the C6_3km product in urban areas and showed similar performance to the C6.1_10km product. However, there still exists an overestimation of AOD values over urban areas in the C6.1_3km aerosol product, and refinement of the DT algorithm is needed for further improvement.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Environmental Sciences
Nicolae Ajtai, Alexandru Mereuta, Horatiu Stefanie, Andrei Radovici, Camelia Botezan, Olga Zawadzka-Manko, Iwona S. Stachlewska, Kerstin Stebel, Claus Zehner
Summary: This study validates the AOD retrieved from SEVIRI data by comparing it with AERONET, Poland-AOD, and MODIS data. The results show that the SEVIRI AOD has the best correlation with AERONET, followed by Poland-AOD and MODIS. A revised uncertainty estimate is proposed based on the observed bias from the AERONET validation efforts.
Article
Environmental Sciences
Yu Wang, Md Arfan Ali, Muhammad Bilal, Zhongfeng Qiu, Song Ke, Mansour Almazroui, Md Monirul Islam, Yuanzhi Zhang
Summary: This study analyzed aerosol optical depth (AOD) data in 13 cities of Jiangsu Province, finding higher AOD in summer and lower in winter, with relatively common frequencies of 0.3 <= AOD < 0.5 associated with anthropogenic activities, increased emissions, and changes in meteorological circumstances.
Article
Environmental Sciences
Mijeong Kim, Kyunghwa Lee, Myungje Choi
Summary: The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The variability was higher in the validation results when the spatial collocation radius was longer and the AODs were higher, compared to the selection of the wavelength.
Article
Environmental Sciences
Somaya Falah, Alaa Mhawish, Meytar Sorek-Hamer, Alexei I. Lyapustin, Itai Kloog, Tirthankar Banerjee, Fadi Kizel, David M. Broday
Summary: This study highlights the importance of spatial and temporal averaging in AOD retrievals, as well as the significant impact of different environmental attributes on the accuracy of MAIAC AOD retrievals. Vegetated areas showed better performance in AOD retrievals compared to arid areas, indicating the sensitivity of retrieval accuracy to environmental factors.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Environmental Sciences
Shuai Yin
Summary: This study explores the relationship between ground-measured surface particle concentrations and remote-sensing aerosol parameters in China. It integrates PM2.5 and PM10 concentrations with MODIS-retrieved AOD and AE data, considering meteorological and topographical factors and seasonality. The study finds strong spatial disparity and seasonal patterns in PM concentrations and aerosol parameters in China. The implementation of clean air actions and policies has led to a significant decline in particle concentrations from 2015 to 2018. The study also reveals the influence of meteorological and topographic factors on the PM/AOD ratio and the variations of PM-AOD correlation in different regions of China.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Akhilesh Kumar, Manu Mehta
Summary: This study explores the applicability of a simple iterative approach for retrieving aerosol optical depth (AOD) over diverse land surface types. The results show a strong correspondence between retrieved AOD and actual measurements, indicating that the iterative approach can be adopted for most sensors.
ATMOSPHERIC ENVIRONMENT
(2023)
Article
Environmental Sciences
Manish Soni, Amit Singh Chandel, Sunita Verma, Swagata Payra, Divya Prakash, Brent Holben
Summary: This study investigates the aerosol climatology over four AERONET sites on different continents, revealing high aerosol concentration and dominance of dust aerosols in locations like Jaipur and Ilorin, while sites in America and Australia are relatively pristine. The radiative forcing and efficiency also vary significantly between Africa-Asia and America-Australia sites.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Geography, Physical
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Ghassem R. Asrar, Xia Zhao
Summary: Aerosol loadings and their spatial distribution play a crucial role in air quality monitoring, climate research, and public health. Researchers have proposed a novel algorithm to fill the gaps in MODIS AOD product, which has been tested and cross-validated in China. The algorithm outperforms other methods in accuracy and meets the requirements of typical applications.
GISCIENCE & REMOTE SENSING
(2022)
Article
Environmental Sciences
Ruonan Fan, Yingying Ma, Shikuan Jin, Wei Gong, Boming Liu, Weiyan Wang, Hui Li, Yiqun Zhang
Summary: The latest version (V23) of the Multi-angle Imaging Spectro Radiometer (MISR) aerosol optical depth (AOD) products were evaluated and compared with AERONET and MODIS products. The study found that the MISR V23 products showed good accuracy and performed best in forested areas. However, as aerosol loading increased, the accuracy of the MISR AOD products decreased. Additionally, the study revealed that MISR tended to overestimate aerosol content in areas with low vegetation cover.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Marion Ranaivombola, Nelson Begue, Hassan Bencherif, Tristan Millet, Venkataraman Sivakumar, Valentin Duflot, Alexandre Baron, Nkanyiso Mbatha, Stuart Piketh, Paola Formenti, Philippe Goloub
Summary: Fires during the rainy season in Southern Africa increase the amount of tropospheric aerosols, causing negative effects on the environment and human health. This study examines the characteristics and types of aerosols over Southern Africa and Reunion Island for a period of 13 years. The results reveal that in spring, high aerosol optical depth and Angstrom exponent are associated with biomass burning and urban industrial aerosols, as well as a mixed type of aerosol. The aerosols mainly originate from biomass burning areas near the study sites and, to a lesser extent, from remote sources like South America.
Article
Environmental Sciences
Muhammad Bilal, Alaa Mhawish, Md. Arfan Ali, Janet E. Nichol, Gerrit de Leeuw, Khaled Mohamed Khedher, Usman Mazhar, Zhongfeng Qiu, Max P. Bleiweiss, Majid Nazeer
Summary: The SEMARA approach, which combines the SREM and SARA methods, was used to retrieve AOD from satellite data over bright urban surfaces in Beijing. The approach showed high accuracy and small errors in the AOD retrievals, making it suitable for aerosol monitoring in urban areas.
Article
Water Resources
Nishi Srivastava, D. Vignesh, Nisheeth Saxena
Summary: Aerosols play a vital role in the earth's climate system, and the artificial neural network technique shows promising performance in simulating aerosol properties. Optimal selection of learning rate values and number of iterations is crucial for accurate results with low computational cost.
JOURNAL OF WATER AND CLIMATE CHANGE
(2021)
Article
Geography, Physical
Christian Kofler, Volkmar Mair, Stephan Gruber, Maria Cristina Todisco, Ian Nettleton, Stefan Steger, Marc Zebisch, Stefan Schneiderbauer, Francesco Comiti
Summary: An integrated investigation revealed that multiple factors contributed to the failures of the rock glacier fronts in 2014, not just heavy rainfall events.
EARTH SURFACE PROCESSES AND LANDFORMS
(2021)
Article
Environmental Sciences
Stefan Steger, Volkmar Mair, Christian Ko, Massimiliano Pittore, Marc Zebisch, Stefan Schneiderbauer
Summary: This study investigates how biases in landslide data can be considered within data-driven models, and found that while models failed to reflect landslide susceptibility, the impact-oriented intervention index was effective in identifying damaging landslides with high accuracy.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Infectious Diseases
Verena Harpf, Samyr Kenno, Guenter Rambach, Verena Fleischer, Nadia Parth, Christian X. Weichenberger, Peter Garred, Silke Huber, Cornelia Lass-Floerl, Cornelia Speth, Reinhard Wuerzner
Summary: Candidiasis is common in diabetic patients. This study found that the expression of FH-binding molecule Hgt1 is glucose-dependent, and Candida albicans grown at higher glucose concentrations showed lower phagocytosis and higher FH deposition. However, the absence of Hgt1 did not provide any significant benefit in a murine model.
Review
Environmental Studies
Linda Menk, Stefano Terzi, Marc Zebisch, Erich Rome, Daniel Lueckerath, Katharina Milde, Stefan Kienberger
Summary: Shifting towards cause-oriented and systemic approaches in sustainable climate change adaptation requires a solid understanding of the causes behind climate risks. Capturing, systemizing, and prioritizing factors contributing to climate risks are essential for cause-oriented climate risk assessments. Impact chains (IC) are used to capture hazard, vulnerability, and exposure factors that lead to specific risks. Challenges and opportunities for improving IC modeling include integrating dynamic feedback and stakeholder involvement. There is still limited understanding of systems, data, and uncertainties in quantifiable and executable models. Using IC to capture the underlying complex processes behind risk supports effective climate change adaptation.
WEATHER CLIMATE AND SOCIETY
(2022)
Article
Geosciences, Multidisciplinary
Christian Kofler, Volkmar Mair, Francesco Comiti, Marc Zebisch, Stefan Schneiderbauer, Stefan Steger
Summary: This study investigates the sediment transfer capacity of rock glaciers and proposes a GIS-based method to assess their sediment transfer capacity. By considering factors such as topographic conditions and sediment transport rate, this method provides a qualitative index to evaluate the sediment transfer capacity of rock glacier fronts. The feasibility of this method is evaluated through field observations, data analysis, and empirical relationships.
Article
Energy & Fuels
Marco Pierro, Fabio Romano Liolli, Damiano Gentili, Marcello Petitta, Richard Perez, David Moser, Cristina Cornaro
Summary: In this study, a methodology to evaluate the margins for imbalance reduction and flexibility in the high share of PV energy was developed. It was shown that advanced solar/wind forecasting and strengthening the national transmission grid can effectively address the increased demand/supply imbalance induced by the inherent intermittency and variability of solar energy.
Article
Meteorology & Atmospheric Sciences
Clare Mary Goodess, Alberto Troccoli, Nicholas Vasilakos, Stephen Dorling, Edward Steele, Jessica D. Amies, Hannah Brown, Katie Chowienczyk, Emma Dyer, Marco Formenton, Antonio M. Nicolosi, Elena Calcagni, Valentina Cavedon, Victor Estella Perez, Gertie Geertsema, Folmer Krikken, Kristian Lautrup Nielsen, Marcello Petitta, Jose Vidal, Martijn De Ruiter, Ian Savage, Jon Upton
Summary: There is a need for more comprehensive and robust information on the value of climate services. The SECLI-FIRM project aimed to address these gaps by co-designing 12 case studies focused on tailored sub-seasonal and seasonal forecasts in the energy and water industries. These case studies highlighted the challenges in quantifying the economic value of these forecasts and emphasized the importance of enhancing practical value for users.
Article
Meteorology & Atmospheric Sciences
Laura Trentini, Sara Dal Gesso, Marco Venturini, Federica Guerrini, Sandro Calmanti, Marcello Petitta
Summary: One critical issue when using climate simulation outputs is the systematic bias affecting the modelled data. In this study, a novel bias correction methodology is proposed that corrects the bias of extreme events by improving the description of extremes through a generalised extreme value distribution fitting. The results show that this technique significantly reduces systematic biases in the forecasting models, yielding improvements over the classic quantile mapping.
Article
Environmental Sciences
Linda Petutschnig, Erich Rome, Daniel Lueckerath, Katharina Milde, Asa Gerger Swartling, Carlo Aall, Mark Meyer, Gabriel Jorda, Julie Gobert, Mathilda Englund, Karin Andre, Muriel Bour, Emmanuel M. N. A. N. Attoh, Brigt Dale, Kathrin Renner, Adeline Cauchy, Saskia Reuschel, Florence Rudolf, Miguel Agulles, Camilo Melo-Aguilar, Marc Zebisch, Stefan Kienberger
Summary: As the climate crisis worsens, there is a growing demand for scientific evidence from Climate Risk and Vulnerability Assessments (CRVA). In this study, we propose 12 methodological advancements to the Impact Chain-based CRVA (IC-based CRVA) framework, which combines participatory and data-driven approaches to identify and measure climate risks in complex socio-ecological systems. These advancements improve the framework in terms of workflow, stakeholder engagement, uncertainty management, socio-economic scenario modeling, and transboundary climate risk examination. Through eleven case studies, we demonstrate the effectiveness and applicability of the IC-based CRVA framework in producing accurate and insightful results.
FRONTIERS IN CLIMATE
(2023)
Article
Geosciences, Multidisciplinary
Ruth Stephan, Stefano Terzi, Mathilde Erfurt, Silvia Cocuccioni, Kerstin Stahl, Marc Zebisch
Summary: This study aims to understand the vulnerability of agriculture to drought in Europe's pre-Alpine region using a mixed-method approach. Two case studies were conducted, and vulnerability factors were identified by regional experts and combined with quantitative data analyses. Two aggregation methods were implemented, resulting in vulnerability maps that showed higher vulnerability when the factors were weighted by experts' opinions. The study highlights the value of mapping vulnerability using different aggregation methods as a sensitivity analysis.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Geosciences, Multidisciplinary
Alice Crespi, Michael Matiu, Giacomo Bertoldi, Marcello Petitta, Marc Zebisch
Summary: A high-resolution gridded dataset of daily mean temperature and precipitation series covering the period 1980-2018 was built for Trentino-South Tyrol, Italy, using observation series from over 200 meteorological stations. The dataset, processed through interpolation and quality checks, provides accurate insights into the spatial and temporal distribution of temperature and precipitation over the mountainous terrain, supporting local and regional applications of climate variability and change.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Geography, Physical
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schoener, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Susnik, Alberto Trenti, Stefano Urbani, Viktor Weilguni
Summary: This study presents an Alpine-wide analysis of snow depth in the European Alps, incorporating data from over 2000 stations in six countries. The analysis reveals decreasing trends in snow depth for most stations from November to May over the past few decades. Different regions within the Alps show varying trends, challenging the generalization of results across the entire mountain range.
Article
Environmental Studies
Marc Zebisch, Stefan Schneiderbauer, Kerstin Fritzsche, Philip Bubeck, Stefan Kienberger, Walter Kahlenborn, Susanne Schwan, Till Below
Summary: The Vulnerability Sourcebook methodology provides a standardised framework for assessing climate vulnerability and risk in adaptation planning. It is based on participative development of climate impact chains to prioritize climate factors and drive climate related threats, vulnerabilities and risks.
INTERNATIONAL JOURNAL OF CLIMATE CHANGE STRATEGIES AND MANAGEMENT
(2021)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)