Oceanographic Basis of the Global Surface Distribution of Prochlorococcus Ecotypes

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants in outdoor air. However, the lack of monitoring of the global surface concentration of HCHO is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or, for research on a global scale, too data-demanding. To alleviate this issue, we adopted neural networks to estimate the 2019 global surface HCHO concentration with confidence intervals, utilizing HCHO vertical column density data from TROPOMI, and in-situ data from HAPs (harmful air pollutants) monitoring networks and the ATom mission. Our results show that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentrations in the Amazon Basin, Northern China, South-east Asia, the Bay of Bengal, and Central and Western Africa are among the highest. The results from our study provide the first dataset on global surface HCHO concentration. In addition, the derived confidence intervals of surface HCHO concentration add an extra layer of confidence to our results. As a pioneering work in adopting confidence interval estimation to AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper paves the way for rigorous study of global ambient HCHO health risk and economic loss, thus providing a basis for pollution control policies worldwide.

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Synoptic relationships quantified between surface Chlorophyll-<i>a</i> and diagnostic pigments specific to phytoplankton functional types

Biogeosciences Discussions ◽

10.5194/bgd-7-6675-2010 ◽

2010 ◽

Vol 7 (5) ◽

pp. 6675-6704

Author(s):

T. Hirata ◽

N. J. Hardman-Mountford ◽

R. J. W. Brewin ◽

J. Aiken ◽

R. Barlow ◽

...

Keyword(s):

Green Algae ◽

Phytoplankton Community ◽

Marine Ecosystem ◽

Global Scale ◽

Least Square ◽

Surface Distribution ◽

Functional Types ◽

Background Population ◽

Marine Ecosystem Models ◽

Global Surface

Abstract. Error-quantified, synoptic-scale relationships between chlorophyll-a (Chla) and phytoplankton pigment groups at the sea surface are presented. A total of nine pigment groups were considered to represent nine phytoplankton functional types (PFTs) including microplankton, nanoplankton, picoplankton, diatoms, dinoflagellates, green algae, picoeukaryotes, prokaryotes and Prochlorococcus sp. The observed relationships between Chla and pigment groups were well-defined at the global scale to show that Chla can be used as an index of not only phytoplankton abundance but also community structure; large (micro) phytoplankton monotonically increase as Chla increases, whereas the small (pico) phytoplankton community generally decreases. Within these relationships, we also found non-monotonic variations with Chla for certain pico-plankton (pico-eukaryotes, Prokaryotes and Prochlorococcus sp.) and for Green Algae and nano-sized phytoplankton. The relationships were quantified with a least-square fitting approach in order to estimate the PFTs from Chla alone. The estimated uncertainty of the relationships quantified depends on both phytoplankton types and Chla concentration. Maximum uncertainty over all groups (34.7% Chla) was found from diatom at approximately Chla = 1.07 mg m−3. However, the mean uncertainty of the relationships over all groups was 5.8 [% Chla] over the entire Chla range observed (0.02 < Chla < 6.84 mg m−3). The relationships were applied to SeaWiFS satellite Chla data from 1998 to 2009 to show the global climatological fields of the surface distribution of PFTs. Results show that microplankton are present in the mid and high latitudes, constituting ~9.0 [% Chla] of the phytoplankton community at the global surface, in which diatoms explain ~6.0 [% Chla]. Nanoplankton are ubiquious throught much of the global surface oceans except subtropical gyres, acting as a background population, constituting ~44.2 [% Chla]. Picoplankton are mostly limited in subtropical gyres, constituting ~46.8 [% Chla] globally, in which prokaryotes are the major species explaining 32.3 [% Chla] (prochlorococcus sp. explaining 21.5 [% Chla]), while pico-eukaryotes are notably abundant in the Southern Pacific explaining ~14.5 [% Chla]. These results may be used to constrain or validate global marine ecosystem models.

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Mapping Global Surface HCHO Distribution with Confidential Interval by Satellite Observation

10.20944/preprints202105.0595.v1 ◽

2021 ◽

Author(s):

Bohan Jin ◽

Jian Guan ◽

Yizhe Ding ◽

Wen Wang ◽

Guoxiang Li

Keyword(s):

Amazon Basin ◽

Interval Estimation ◽

Monitoring Network ◽

Surface Concentration ◽

Satellite Observation ◽

Average Concentration ◽

Vertical Column ◽

Atmospheric Pollutant ◽

Surface Distribution ◽

Global Surface

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering researches on outdoor HCHO pollution. Traditional methods are either too naïve or data-demanding for a global scale research. To alleviate this issue, we trained two fully-connected neural networks respectively for deriving point and interval estimation of surface HCHO concentration in 2019, where vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, North China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. Our study makes up for the global shortage of surface HCHO monitoring and helps people have a clearer understanding of surface concentration distribution of HCHO. In addition, with the help of quality-driven algorithm, interval estimation of surface HCHO concentration is believed to bring confidence to our results. As an early work adopting interval estimation in AI-driven atmospheric pollutant research and the first to map global HCHO surface distribution, our paper will pave way for rigorous study on global ambient HCHO health risk and economic loss, thus providing basis for pollutant controlling policies worldwide.

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Global Surface HCHO Distribution derived from Satellite Observations with Neural Networks Technique

10.20944/preprints202105.0595.v2 ◽

2021 ◽

Author(s):

Jian Guan ◽

Bohan Jin ◽

Yizhe Ding ◽

Wen Wang ◽

Guoxiang Li ◽

...

Keyword(s):

Neural Networks ◽

Confidence Interval ◽

Amazon Basin ◽

Monitoring Network ◽

Surface Concentration ◽

Average Concentration ◽

Vertical Column ◽

Atmospheric Pollutant ◽

Surface Distribution ◽

Global Surface

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or data- demanding for a global scale of research. To alleviate this issue, we adopted neural networks to estimate surface HCHO concentration with confidence intervals in 2019, where HCHO vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, Northern China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. The results from our study provides a first dataset of the global surface HCHO concentration. In addition, the derived confidence interval of surface HCHO concentration adds an extra layer for the confidence to our results. As a pioneer work in adopting confidence interval estimation into AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper will pave the way for the rigorous study on global ambient HCHO health risk and economic loss, thus providing a basis for pollutant controlling policies worldwide.

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Changes Occur in Plasma Membrane Turnover when K562 Leukemia Cells are Induced to Differentiate

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100054042 ◽

1982 ◽

Vol 40 ◽

pp. 286-287

Author(s):

L. M. Marshall

Keyword(s):

Plasma Membrane ◽

Membrane Proteins ◽

Intracellular Transport ◽

Parent Cell ◽

Membrane Turnover ◽

Coated Pits ◽

Surface Distribution ◽

Specific Proteins ◽

Erythroleukemic Cell ◽

Specific Membrane

A human erythroleukemic cell line, metabolically blocked in a late stage of erythropoiesis, becomes capable of differentiation along the normal pathway when grown in the presence of hemin. This process is characterized by hemoglobin synthesis followed by rearrangement of the plasma membrane proteins and culminates in asymmetrical cytokinesis in the absence of nuclear division. A reticulocyte-like cell buds from the nucleus-containing parent cell after erythrocyte specific membrane proteins have been sequestered into its membrane. In this process the parent cell faces two obstacles. First, to organize its erythrocyte specific proteins at one pole of the cell for inclusion in the reticulocyte; second, to reduce or abolish membrane protein turnover since hemoglobin is virtually the only protein being synthesized at this stage. A means of achieving redistribution and cessation of turnover could involve movement of membrane proteins by a directional lipid flow. Generation of a lipid flow towards one pole and accumulation of erythrocyte-specific membrane proteins could be achieved by clathrin coated pits which are implicated in membrane endocytosis, intracellular transport and turnover. In non-differentiating cells, membrane proteins are turned over and are random in surface distribution. If, however, the erythrocyte specific proteins in differentiating cells were excluded from endocytosing coated pits, not only would their turnover cease, but they would also tend to drift towards and collect at the site of endocytosis. This hypothesis requires that different protein species are endocytosed by the coated vesicles in non-differentiating than by differentiating cells.

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