Publications by authors named "Tianci Qi"

Article Synopsis
  • * A study focused on 161 large lakes globally developed a Random Forest model, showing a predicted increase in algal blooms by the century's end, particularly under high socio-economic scenarios.
  • * Lakes in Africa, Asia, and North America are likely to see more algal blooms, while Europe may experience a decline, highlighting regional disparities in sensitivity to socio-economic changes.
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Limited field samplings result in significant uncertainties in regional and global estimates of lake carbon dioxide (CO) emissions. However, quantitative analysis of uncertainty in regional lake CO emission estimates remains unclear. In this study, we utilized satellite data to estimate carbon dioxide flux from 113 eastern China lakes, revealing substantial spatial and temporal variations in flux, averaging 18.

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Aquaculture ponds (APs) are rapidly expanding globally and are considered crucial for guaranteeing the supply of food, population growth, and economic development. However, the rapid expansion of aquaculture not only brought benefits but also a series of eco-environmental issues, such as water eutrophication. To achieve sustainable development, it is essential to gain a profound understanding of the spatiotemporal evolution of APs, the drivers behind their dynamics, and their relationship with the aquatic environment.

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Remote sensing monitoring of particulate organic carbon (POC) concentration is essential for understanding phytoplankton productivity, carbon storage, and water quality in global lakes. Some algorithms have been proposed, but only for regional eutrophic lakes. Based on in-situ data (N = 1269) in 49 lakes across China, we developed a blended POC algorithm by distinguishing Type-I and Type-II waters.

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Cyanobacterial blooms release a large number of algal toxins (e.g., Microcystins, MCs) and seriously threaten the safety of drinking water sources what the SDG 6.

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Lakes are major emitters of methane (CH); however, a longstanding challenge with quantifying the magnitude of emissions remains as a result of large spatial and temporal variability. This study was designed to address the issue using satellite remote sensing with the advantages of spatial coverage and temporal resolution. Using Aqua/MODIS imagery (2003-2020) and measured data (2011-2017) in eutrophic Lake Taihu, we compared the performance of eight machine learning models to predict diffusive CH emissions and found that the random forest (RF) model achieved the best fitting accuracy ( = 0.

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Lakes are recognized as important sources of carbon dioxide (CO) emissions, which vary greatly across land use type. However, CO emissions from lakes in urban landscapes are generally overlooked despite their daily connections to human activity. Furthermore, the role of management actions in CO emissions remained unclear mostly because of the lack of long-term observations.

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Under the influence of climate warming and human activities, many large lakes have experienced an increase in eutrophication and algal blooms. Although these trends have been identified using low temporal resolution (~16 days) satellites such as those of the Landsat missions, the opportunity to compare high-frequency spatiotemporal variations of algal bloom characteristics between lakes has not been explored. In the present study, we explore daily satellite observations by developing a universal, practical, and robust algorithm to identify the spatiotemporal distribution of algal bloom dynamics in large lakes (>500 km) across the globe.

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Lakes play an important role in the global carbon cycle; however, there are still large uncertainties in the estimation of global lake carbon emission due to the limitations in conducting field surveys at large geographic scales. Using long-term Moderate-Resolution Imaging Spectroradiometer (MODIS) imagery and field observation data in eutrophic Lake Taihu, we developed a novel approach to estimate the concentration of dissolved carbon dioxide (CO) in lakes. Based on the MODIS-derived chlorophyll- concentration, lake surface temperature, diffuse attenuation coefficient of photosynthetically active radiation, and photosynthetically active radiation, a spatially explicit CO model was developed using multivariate quadratic polynomial regression (coefficient of determination () = 0.

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Inland waters emit large amounts of carbon dioxide (CO) to the atmosphere, but emissions from urban lakes are poorly understood. This study investigated seasonal and interannual variations in the partial pressure of CO (pCO) and CO flux from Lake Wuli, a small eutrophic urban lake in the heart of the Yangtze River Delta, China, based on a long-term (2000-2015) dataset. The results showed that the annual mean pCO was 1030 ± 281 μatm (mean ± standard deviation) with a mean CO flux of 1.

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Aquatic ecosystems are recognized as a source of NO in accordance with the flux estimations of rivers and estuaries; however, limited research has been conducted on large lakes. In this study, we report the annual NO dynamics of a large eutrophic freshwater lake located in the subtropical zone of East China. The dissolved NO concentrations in Lake Chaohu were observed to be between 8.

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Inland lakes receive growing attentions on eutrophication and their roles in global carbon cycle. However, understanding how inland lakes contribute to global carbon cycle is seriously hampered due to a shortage of long-term records. This study investigated the carbon dioxide (CO) flux from the Lake Taihu, a large (2400 km) and shallow (mean depth 1.

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