Zhao, H., Zhou, Y., Wu, H., Kutser, T., Han, Y., Ma, R., Yao, Z., Zhao, H., Xu, P., Jiang, C., Gu, Q., Ma, S., Wu, L., Chen, Y., Sheng, H., Wan, X., Chen, W., Chen, X., Bai, J., ... Liu, D. (2023). Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters. Environmental Science and Technology, 57(38), 14226-14236. https://doi.org/10.1021/acs.est.3c04212
Zhao, Hongkai ; Zhou, Yudi ; Wu, Hongda et al. / Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters. In: Environmental Science and Technology. 2023 ; Vol. 57, No. 38. pp. 14226-14236.
@article{e1a68cc01bc14bf28cbe2b8c2030f85f,
title = "Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters",
abstract = "Vertical distribution of phytoplankton is crucial for assessing the trophic status and primary production in inland waters. However, there is sparse information about phytoplankton vertical distribution due to the lack of sufficient measurements. Here, we report, to the best of our knowledge, the first Mie-fluorescence-Raman lidar (MFRL) measurements of continuous chlorophyll a (Chl-a) profiles as well as their parametrization in inland water. The lidar-measured Chl-a during several experiments showed good agreement with the in situ data. A case study verified that MFRL had the potential to profile the Chl-a concentration. The results revealed that the maintenance of subsurface chlorophyll maxima (SCM) was influenced by light and nutrient inputs. Furthermore, inspired by the observations from MFRL, an SCM model built upon surface Chl-a concentration and euphotic layer depth was proposed with root mean square relative difference of 16.5% compared to MFRL observations, providing the possibility to map 3D Chl-a distribution in aquatic ecosystems by integrated active-passive remote sensing technology. Profiling and modeling Chl-a concentration with MFRL are expected to be of paramount importance for monitoring inland water ecosystems and environments.",
keywords = "Mie−fluorescence−Raman lidar, chlorophyll a, inland water, integrated active−passive remote sensing, subsurface chlorophyll maxima",
author = "Hongkai Zhao and Yudi Zhou and Hongda Wu and Tiit Kutser and Yicai Han and Ronghua Ma and Ziwei Yao and Huade Zhao and Peituo Xu and Chengchong Jiang and Qiuling Gu and Shizhe Ma and Lingyun Wu and Yang Chen and Haiyan Sheng and Xueping Wan and Wentai Chen and Xiaolong Chen and Jian Bai and Lan Wu and Qun Liu and Wenbo Sun and Suhui Yang and Miao Hu and Chong Liu and Dong Liu",
note = "Publisher Copyright: {\textcopyright} 2023 American Chemical Society",
year = "2023",
month = sep,
day = "26",
doi = "10.1021/acs.est.3c04212",
language = "English",
volume = "57",
pages = "14226--14236",
journal = "Environmental Science and Technology",
issn = "0013-936X",
publisher = "American Chemical Society",
number = "38",
}
Zhao, H, Zhou, Y, Wu, H, Kutser, T, Han, Y, Ma, R, Yao, Z, Zhao, H, Xu, P, Jiang, C, Gu, Q, Ma, S, Wu, L, Chen, Y, Sheng, H, Wan, X, Chen, W, Chen, X, Bai, J, Wu, L, Liu, Q, Sun, W, Yang, S, Hu, M, Liu, C & Liu, D 2023, 'Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters', Environmental Science and Technology, vol. 57, no. 38, pp. 14226-14236. https://doi.org/10.1021/acs.est.3c04212
Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters. / Zhao, Hongkai; Zhou, Yudi; Wu, Hongda et al.
In:
Environmental Science and Technology, Vol. 57, No. 38, 26.09.2023, p. 14226-14236.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters
AU - Zhao, Hongkai
AU - Zhou, Yudi
AU - Wu, Hongda
AU - Kutser, Tiit
AU - Han, Yicai
AU - Ma, Ronghua
AU - Yao, Ziwei
AU - Zhao, Huade
AU - Xu, Peituo
AU - Jiang, Chengchong
AU - Gu, Qiuling
AU - Ma, Shizhe
AU - Wu, Lingyun
AU - Chen, Yang
AU - Sheng, Haiyan
AU - Wan, Xueping
AU - Chen, Wentai
AU - Chen, Xiaolong
AU - Bai, Jian
AU - Wu, Lan
AU - Liu, Qun
AU - Sun, Wenbo
AU - Yang, Suhui
AU - Hu, Miao
AU - Liu, Chong
AU - Liu, Dong
N1 - Publisher Copyright:
© 2023 American Chemical Society
PY - 2023/9/26
Y1 - 2023/9/26
N2 - Vertical distribution of phytoplankton is crucial for assessing the trophic status and primary production in inland waters. However, there is sparse information about phytoplankton vertical distribution due to the lack of sufficient measurements. Here, we report, to the best of our knowledge, the first Mie-fluorescence-Raman lidar (MFRL) measurements of continuous chlorophyll a (Chl-a) profiles as well as their parametrization in inland water. The lidar-measured Chl-a during several experiments showed good agreement with the in situ data. A case study verified that MFRL had the potential to profile the Chl-a concentration. The results revealed that the maintenance of subsurface chlorophyll maxima (SCM) was influenced by light and nutrient inputs. Furthermore, inspired by the observations from MFRL, an SCM model built upon surface Chl-a concentration and euphotic layer depth was proposed with root mean square relative difference of 16.5% compared to MFRL observations, providing the possibility to map 3D Chl-a distribution in aquatic ecosystems by integrated active-passive remote sensing technology. Profiling and modeling Chl-a concentration with MFRL are expected to be of paramount importance for monitoring inland water ecosystems and environments.
AB - Vertical distribution of phytoplankton is crucial for assessing the trophic status and primary production in inland waters. However, there is sparse information about phytoplankton vertical distribution due to the lack of sufficient measurements. Here, we report, to the best of our knowledge, the first Mie-fluorescence-Raman lidar (MFRL) measurements of continuous chlorophyll a (Chl-a) profiles as well as their parametrization in inland water. The lidar-measured Chl-a during several experiments showed good agreement with the in situ data. A case study verified that MFRL had the potential to profile the Chl-a concentration. The results revealed that the maintenance of subsurface chlorophyll maxima (SCM) was influenced by light and nutrient inputs. Furthermore, inspired by the observations from MFRL, an SCM model built upon surface Chl-a concentration and euphotic layer depth was proposed with root mean square relative difference of 16.5% compared to MFRL observations, providing the possibility to map 3D Chl-a distribution in aquatic ecosystems by integrated active-passive remote sensing technology. Profiling and modeling Chl-a concentration with MFRL are expected to be of paramount importance for monitoring inland water ecosystems and environments.
KW - Mie−fluorescence−Raman lidar
KW - chlorophyll a
KW - inland water
KW - integrated active−passive remote sensing
KW - subsurface chlorophyll maxima
UR - http://www.scopus.com/inward/record.url?scp=85172425294&partnerID=8YFLogxK
U2 - 10.1021/acs.est.3c04212
DO - 10.1021/acs.est.3c04212
M3 - Article
C2 - 37713595
AN - SCOPUS:85172425294
SN - 0013-936X
VL - 57
SP - 14226
EP - 14236
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 38
ER -
Zhao H, Zhou Y, Wu H, Kutser T, Han Y, Ma R et al. Potential of Mie-Fluorescence-Raman Lidar to Profile Chlorophyll a Concentration in Inland Waters. Environmental Science and Technology. 2023 Sept 26;57(38):14226-14236. doi: 10.1021/acs.est.3c04212
