Skip to main content
PMC home page
Data in Brief logoLink to Data in Brief
. 2020 Jun 7;31:105839. doi: 10.1016/j.dib.2020.105839

Dataset for atmospheric transport of nutrients during a harmful algal bloom

Rongxiang Tian a,⁎, Qun Lin a, Dewang Li b, Wei Zhang c, Xiuyi Zhao a
PMCID: PMC7326717  PMID: 32637471

Abstract

The data presented in this article are related to the research article entitled “Atmospheric transport of nutrient matter during a harmful algal bloom”[1]. These data provide the concentration of nutrients (nitrate, ammonium and FeⅡ) in the atmosphere and their deposited flux in the East China Sea prior to the harmful algal bloom on May 3–8, 2006. They can be helpful for analyzing the source of nutrients causing the harmful algal blooms.

Keywords: Harmful algal blooms, Atmospheric transport, Nutrients, The East China Sea

Specifications table

Subject Environmental Science (General)
Specific subject area harmful algal bloom, Atmospheric transport, nutrient matter, numerical simulation, deposition flux, the East China Sea.
Type of data Figure
How data was acquired Survey and computer simulation using the Global Nested Air Quality Prediction Modeling System
Data format Raw and Analyzed
Description of data collection • The large-scale harmful algal bloom events were collected from the Marine Environmental Quality Bulletin of China (http://www.coi.gov.cn/hygb)
• Global Nested Air Quality Prediction Modeling System [2], [3], [4] were used to simulate the atmospheric transport and deposition flux of nutrient.
Parameters for data collection • The harmful algal bloom event with an area larger than 1000km2 in the East China Sea during 2006.
• The harmful algal bloom event (a spatial coverage of 1000km2), which developed in coast water off Zhejiang, China between the 3rd- the 8th of May 2006, was use as research case. Then the Global Nested Air Quality Prediction Modeling System was used to simulate the atmospheric transport and deposition flux of nutrient in algal bloom area.
Data source location Zhejiang Province, China
Data accessibility The data is available within this article.
https://data.mendeley.com/datasets/mh54hnp52f/draft?a=d6217d12-3d9d-45d6–8050–43f55a5d2e8e
Related research article Rongxiang Tian, Qun Lin, Dewang Li, Wei Zhang, Xiuyu Zhao. Atmospheric transport of nutrients during a harmful algal bloom event[J]. Regional Studies in Marine Science, 2019: 101,007, DOI: https://doi.org/10.1016/j.rsma.2019.101007
Open in a new tab

Value of the Data

  • •

    The data could be used to assess the contribution of the atmospheric nutrients to algal blooms

  • •

    The data can be used to identify areas of elevated nutrient concentrations and deposition flux in the East China Sea.

  • •

    The data can be used as a reference for predicting harmful algal bloom.

Data description

The harmful algal bloom event developed between May 3 and 8, 2006 was the first bloom with a spatial coverage of 1000 km2 that year. The considerable nutrient matter (nitrate, ammonium, ferrous iron) were transported to the algal bloom area via the atmosphere before occurring the harmful algal bloom. Fig. 1, Fig. 2, Fig. 3 show the Atmospheric transport of nitrate, ammonium and FeⅡ, respectively. Fig. 4 shows the deposition flux of nutrients.

Fig. 1.

Fig 1

Open in a new tab

Atmospheric transport of nitrate (μg/m3). The small square represents the location of the 28–32°N, 120–124°E.

Fig. 2.

Fig 2

Open in a new tab

Atmospheric transport of ammonium (μg/m3). The small square represents the location of the 28–32°N, 120–124°E.

Fig. 3.

Fig 3

Open in a new tab

Atmospheric transport of FeⅡ(μg/m3) [1]. The small square represents the location of the 28–32°N, 120–124°E.

Fig. 4.

Fig 4

Open in a new tab

Deposition flux of nutrients. The small square represents the location of the 28–32°N, 120–124°E.

Experimental design, materials and methods

There were 6 harmful algal bloom events which were larger than 1000 km2 in East China Sea during 2006. The first harmful algal bloom with a spatial coverage of 1000 km2 developed on May 3–8, 2006. April and May are the transition time between winter and summer in the Northern Hemisphere. The atmospheric circulation patterns and oceanic currents in East China Sea were shifting from winter patterns to summer patterns during this period. In consideration of the seasonal change and time when the first harmful algla bloom with a spatial coverage of 1000km2, we used the Global Nested Air Quality Prediction Modeling System (GNAQPMS) to calculate the atmospherically transported nutrients (nitrate, ammonium and FeⅡ) and their deposition flux by setting the simulation time from April 15 to May 6, 2006.

The GNAQPMS was independently developed by Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS)[5] . The GNAQPMS model and its running schedule were provided by IAP/CAS [2]. A summary is presented here:

The GNAQPMS utilized in this study is a fully modularized three-dimensional regional Eulerian chemical transport model, driven by the meteorological model the Weather Research and Forecasting (WRF) model. GNAQPMS reproduces the physical and chemical evolution of reactive pollutants by solving the mass balance equation in terrain-following coordinates [5, [7], [8], [9]]. It includes advection, diffusion and convection processes, gas/aqueous/aerosol chemistry, and parameterization of dry/wet deposition. GNAQPMS is composed of input, physic-chemical process and output:

Input. The input items are the meteorological fields and emission inputs. The output of the WRF model was used for the meteorological fields. The meteorological data on April 15, 2006, as the initial meteorological fields inputted to the WRF model, comes from http://rda.ucar.edu. The emission inputs consist of anthropogenic inputs (aerosol and trace gas) and natural emissions (vegetation, soil, volcano and lighting). In this study, we used the Fifth Assessment Report of the United Nations Intergovernmental Panel on Climate Change as anthropogenic input (1850–2000 decade, 0.5° × 0.5°), Global Emissions Inventory Activity and Model of Emissions of Gases and Aerosols from Nature as biological input (2000 decade, 0.5° × 0.5°). Regional Emission inventory in Asia as soil NOx input (year of 2001, 1° × 1°) and Global Emissions Inventory Activity as lighting NOx input (average value from 1983–1990, 1° × 1°)[6].

Physic-chemical process. The physical-chemical process included gas/aqueous/ heterogeneous/aerosol chemistry, advection, diffusion and convection processes, and modules for dry and wet deposition, and dust and sea salt dynamic emissions reactions and processes [4, 6, 9].

Output. The output items included the wet and dry deposition and spatial distribution of chemical species [6].

The GNAQPMS had been modified on the basis of the topography and pollution pattern of East Asia. It has been widely applied to simulate the transport of air pollutants and to provide operational air quality forecasts in East Asia [3, 4, [7], [8], [9], [10], [11], [12], [13], [14], [15]]

Declaration of Competing Interest

The authors declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (41775142). We thank Zifa Wang for providing Global Nested Air Quality Prediction Modeling System model and meteorological data. We thank the Huansheng Chen, wenyi Yang, Jie Li, and Zhe Wang for technical assistance.

References

  • 1.Tian Rongxiang, Lin Qun, Li Dewang, Zhang Wei, Zhao Xiuyi. Atmospheric transport of nutrients during a harmful algal bloom even. Reg. Stud. Mar. Sci. 2019 doi: 10.1016/j.rsma.2019.101007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Wang Z., Li J., Wang Z., Yang W., Tang X., Ge B., Wand W. Modeling study of regional severe hazes over mid-eastern China in January 2013 and its implications on pollution prevention and control. Sci. China Earth Sci. 2014;57(1):3–13. [Google Scholar]
  • 3.Wang Z., Ueda H., Huang M. A deflation module for use in modeling long-range transport of yellow sand over East Asia. J. Geophys. Res. 2000;105:26947–26960. [Google Scholar]
  • 4.Wang Z., Li J., Wang X., Pochanart P., Akimoto H. Modeling of regional high ozone episode observed at two mountain sites (Mt. Tai and Huang) in East China. J. Atmosp. Chem. 2006;55:253–272. [Google Scholar]
  • 5.Wang Z.F., Xie F.Y., Wang X.Q., An J.L., Zhou J. Development and application of nest air quality prediction modeling system (in Chinese) Chin. J. Atmosp. Sci. 2006;30(5):778–790. [Google Scholar]
  • 6.Chen H. University of Chinese Academy Sciences; 2013. Development of Global Multi-Scale Nested Atmospheric Chemical Transport Model (GNAQPMS) and its Application to Atmospheric Mercury Transport (in Chinses) pp. 1–17. [Google Scholar]
  • 7.Li J., Wang Z., Akimoto H., Gao C., Pochanart P., Wang X. Modeling study of ozone seasonal cycle in lower troposphere over East Asia. J. Geophys. Res. Atmosp. 2007;112:22–25. [Google Scholar]
  • 8.Li J., Wang Z., Akimoto H., Yamaji K., Takigawa M., Pochanart P., Kanaya Y. Near-ground ozone source attributions and outflow in Central Eastern China during MTX2006. Atmosp. Chem. Phys. 2008;8:7335–7351. [Google Scholar]
  • 9.Li J., Wang Z., Zhuang G., Luo G., Sun Y., Wang Q. Mixing of Asian mineral dust with anthropogenic pollutants over East Asia: a model case study of a super-dust storm in March 2010. Atmosp. Chem. Phys. 2012;12:7591–7607. [Google Scholar]
  • 10.Tang X., Zhu J., Wang Z.F., Gbaguidi A. Improvement of ozone forecast over Beijing based on ensemble Kalman filter with simultaneous adjustment of initial conditions and emissions. Atmosp. Chem. Phys. 2011;11:7811–7849. [Google Scholar]
  • 11.Wang Z., Akimoto H., Uno I. Neutralization of soil aerosol and its impact on the distribution of acid rain over East Asia: observations and model results. J. Geophys. Res. Atmosp. 2002;107:1–6. [Google Scholar]
  • 12.Wang Q., Fu Q.Y., Wang Z.F., Wang T.J., Liu P., Lu T., Huang Y.M. Application of ensemble numberical model system on the air quality forecast in Shanghai (in Chinese) Environ. Monit. Forewarn. 2010;2:1–6. [Google Scholar]
  • 13.Wang Z., Ueda H., Huang M. A deflation module for use in modeling long-range transport of yellow sand over East Asia. J. Geophys. Res. 2000;105:26947–26960. 2000. [Google Scholar]
  • 14.Wu Q.Z., Wang Z.F., Gbaguidi A., Gao C., Li L.N., Wang W. A numerical study of contributions to air pollution in Beijing during CAREBeijing-2006. Atmosp. Chem. Phys. 2011;11:5997–6011. [Google Scholar]
  • 15.Wu Q., Wang Z., Chen H., Zhou W., Wenig M. An evaluation of air quality modeling over the Pearl River Delta during November 2006. Meteorol. Atmosp. Phys. 2012;116:113–132. [Google Scholar]

Articles from Data in Brief are provided here courtesy of Elsevier

RESOURCES