scholarly journals Spatiotemporal variability of hydrocarbons in surface sediments from an intensively human-impacted Xiaoqing River-Laizhou Bay system in the eastern China: Occurrence, compositional profile and source apportionment

2018 ◽  
Vol 645 ◽  
pp. 1172-1182 ◽  
Author(s):  
Ding He ◽  
Kai Zhang ◽  
Xingqian Cui ◽  
Jianhui Tang ◽  
Yongge Sun
Keyword(s):  
Source Apportionment ◽  
Surface Sediments ◽  
Eastern China ◽  
Spatiotemporal Variability ◽  
Laizhou Bay ◽  
Compositional Profile

scholarly journals Pb Content, Risk Level and Primary-Source Apportionment in Wheat and Rice Grains in the Lihe River Watershed, Taihu Region, Eastern China

2021 ◽  
Vol 18 (12) ◽  
pp. 6256
Author(s):  
Lian Chen ◽  
Shenglu Zhou ◽  
Qiong Yang ◽  
Qingrong Li ◽  
Dongxu Xing ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Source Apportionment ◽  
Health Risk Assessment ◽  
Eastern China ◽  
Assessment Model ◽  
Primary Sources ◽  
Risk Level ◽  
River Watershed ◽  
Rice Grains

This study detailed a complete research from Lead (Pb) content level to ecological and health risk to direct- and primary-sources apportionment arising from wheat and rice grains, in the Lihe River Watershed of the Taihu region, East China. Ecological and health risk assessment were based on the pollution index and US Environmental Protection Agency (EPA) health risk assessment model. A three-stage quantitative analysis program based on Pb isotope analysis to determine the relative contributions of primary sources involving (1) direct-source apportionment in grains with a two-end-member model, (2) apportionment of soil and dustfall sources using the IsoSource model, and (3) the integration of results of (1) and (2) was notedly first proposed. The results indicated that mean contents of Pb in wheat and rice grains were 0.54 and 0.45 mg/kg and both the bio-concentration factors (BCF) were <<1; the ecological risk pollution indices were 1.35 for wheat grains and 1.11 for rice grains; hazard quotient (HQ) values for adult and child indicating health risks through ingestion of grains were all <1; Coal-fired industrial sources account for up to 60% of Pb in the grains. This study provides insights into the management of grain Pb pollution and a new method for its source apportionment.

Spatial distribution and source apportionment of PAHs in marine surface sediments of Prydz Bay, East Antarctica

2016 ◽  
Vol 219 ◽  
pp. 528-536 ◽  
Author(s):  
Rui Xue ◽  
Ling Chen ◽  
Zhibo Lu ◽  
Juan Wang ◽  
Haizhen Yang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Source Apportionment ◽  
Surface Sediments ◽  
East Antarctica ◽  
Prydz Bay ◽  
Marine Surface

scholarly journals Carbonaceous aerosols in China: top-down constraints on primary sources and estimation of secondary contribution

2011 ◽  
Vol 11 (10) ◽  
pp. 28219-28272 ◽  
Author(s):  
T.-M. Fu ◽  
J. J. Cao ◽  
X. Y. Zhang ◽  
S. C. Lee ◽  
Q. Zhang ◽  
...  
Keyword(s):  
Eastern China ◽  
Western China ◽  
Spatiotemporal Variability ◽  
Anthropogenic Source ◽  
Carbonaceous Aerosols ◽  
Top Down ◽  
Bottom Up ◽  
Secondary Sources ◽  
Secondary Formation ◽  
Emission Estimate

Abstract. We simulate elemental carbon (EC) and organic carbon (OC) aerosols in China and compare model results to surface measurements at Chinese rural and background sites, with the goal of deriving "top-down" emission estimates of EC and OC, as well as better quantifying the secondary sources of OC. We include in the model state-of-the-science Chinese "bottom-up" emission inventories for EC (1.92 Tg C yr−1) and OC (3.95 Tg C yr−1), as well as updated secondary OC formation pathways. The average simulated annual mean EC concentration at rural and background site is 1.1 μg C m−3, 56% lower than the observed 2.5 μg C m−3. The average simulated annual mean OC concentration at rural and background sites is 3.4 μg C m−3, 76% lower than the observed 14 μg C m−3. Multiple regression to fit surface monthly mean EC observations at rural and background sites yields best estimate of Chinese EC source of 3.05 ± 0.78 Tg C yr−1. Based on the top-down EC emission estimate and observed seasonal primary OC/EC ratios, we estimate Chinese OC total emissions to be 6.67 ± 1.30 Tg C yr−1. Using these top-down estimates, the simulated average annual mean EC concentration at rural and background sites significantly improved to 1.9 μg C m−3. However, the model still significantly underestimates observed OC in all seasons (simulated average annual mean OC at rural and background sites is 5.4 μg C m−3), with little skill in capturing the spatiotemporal variability. Secondary formation accounts for 21% of Chinese annual mean surface OC in the model, with isoprene being the most important precursor. In summer, as high as 62% of the observed surface OC may be due to secondary formation in eastern China. Our analysis points to three shortcomings in the current bottom-up inventories of Chinese carbonaceous aerosols: (1) the anthropogenic source is severely underestimated, particularly for OC; (2) there is a missing source in western China, likely associated with the use of biofuels or other low-quality fuels for heating; and (3) sources in fall are not well represented, either because the seasonal shifting of emissions and/or secondary formation are poorly captured or because specific fall emission events are missing. More regional measurements with better spatiotemporal coverage are needed to resolve these shortcomings.

scholarly journals Spatiotemporal variability of NO<sub>2</sub> and PM<sub>2.5</sub> over Eastern China: observational and model analyses with a novel statistical method

2018 ◽  
Vol 18 (17) ◽  
pp. 12933-12952 ◽  
Author(s):  
Mengyao Liu ◽  
Jintai Lin ◽  
Yuchen Wang ◽  
Yang Sun ◽  
Bo Zheng ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Eastern China ◽  
Ground Level ◽  
Vertical Gradient ◽  
Spatiotemporal Variability ◽  
Model Errors ◽  
Diurnal Variability ◽  
Near Surface ◽  
Synchronous Mode ◽  
The North

Abstract. Eastern China (27–41∘ N, 110–123∘ E) is heavily polluted by nitrogen dioxide (NO2), particulate matter with aerodynamic diameter below 2.5 µm (PM2.5), and other air pollutants. These pollutants vary on a variety of temporal and spatial scales, with many temporal scales that are nonperiodic and nonstationary, challenging proper quantitative characterization and visualization. This study uses a newly compiled EOF–EEMD analysis visualization package to evaluate the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes over Eastern China in fall–winter 2013. Applying the package to observed hourly pollutant data reveals a primary spatial pattern representing Eastern China synchronous variation in time, which is dominated by diurnal variability with a much weaker day-to-day signal. A secondary spatial mode, representing north–south opposing changes in time with no constant period, is characterized by wind-related dilution or a buildup of pollutants from one day to another. We further evaluate simulations of nested GEOS-Chem v9-02 and WRF/CMAQ v5.0.1 in capturing the spatiotemporal variability of pollutants. GEOS-Chem underestimates NO2 by about 17 µg m−3 and PM2.5 by 35 µg m−3 on average over fall–winter 2013. It reproduces the diurnal variability for both pollutants. For the day-to-day variation, GEOS-Chem reproduces the observed north–south contrasting mode for both pollutants but not the Eastern China synchronous mode (especially for NO2). The model errors are due to a first model layer too thick (about 130 m) to capture the near-surface vertical gradient, deficiencies in the nighttime nitrogen chemistry in the first layer, and missing secondary organic aerosols and anthropogenic dust. CMAQ overestimates the diurnal cycle of pollutants due to too-weak boundary layer mixing, especially in the nighttime, and overestimates NO2 by about 30 µg m−3 and PM2.5 by 60 µg m−3. For the day-to-day variability, CMAQ reproduces the observed Eastern China synchronous mode but not the north–south opposing mode of NO2. Both models capture the day-to-day variability of PM2.5 better than that of NO2. These results shed light on model improvement. The EOF–EEMD package is freely available for noncommercial uses.

Distribution and environmental significance of live and dead benthic foraminiferal assemblages in surface sediments of Laizhou Bay, Bohai Sea

2016 ◽  
Vol 123 ◽  
pp. 1-14 ◽  
Author(s):  
Feifei Wang ◽  
Maosheng Gao ◽  
Jian Liu ◽  
Shaofeng Pei ◽  
Chengfeng Li ◽  
...  
Keyword(s):  
Bohai Sea ◽  
Surface Sediments ◽  
Laizhou Bay ◽  
Environmental Significance

Diurnal variations and source apportionment of ozone at the summit of Mount Huang, a rural site in Eastern China

2020 ◽  
Author(s):  
Jinhui Gao
Keyword(s):  
Boundary Layer ◽  
Diurnal Variation ◽  
Source Apportionment ◽  
Southern China ◽  
Eastern China ◽  
Vertical Mixing ◽  
Diurnal Variations ◽  
Rural Site ◽  
Positive Contribution ◽  
Negative Contribution

&lt;p&gt;Comprehensive measurements were conducted at the summit of Mount (Mt.) Huang, a rural site located in eastern China during the summer of 2011. They observed that ozone showed pronounced diurnal variations with high concentrations at night and low values during daytime. The Weather Research and Forecasting with Chemistry (WRF-Chem) model was applied to simulate the ozone concentrations at Mt. Huang in June 2011. With processes analysis and online ozone tagging method we coupled into the model system, the causes of this diurnal pattern and the contributions from different source regions were investigated. Our results showed that boundary layer diurnal cycle played an important role in driving the ozone diurnal variation. Further analysis showed that the negative contribution of vertical mixing was significant, resulting in the ozone decrease during the daytime. In contrast, ozone increased at night owing to the significant positive contribution of advection. This shifting of major factor between vertical mixing and advection formed this diurnal variation. Ozone source apportionment results indicated that approximately half was provided by inflow effect of ozone from outside the model domain (O&lt;sub&gt;3-INFLOW&lt;/sub&gt;) and the other half was formed by ozone precursors (O&lt;sub&gt;3-PBL&lt;/sub&gt;) emitted in eastern, central, and southern China. In the O&lt;sub&gt;3-PBL&lt;/sub&gt;, 3.0% of the ozone was from Mt. Huang reflecting the small local contribution (O&lt;sub&gt;3-LOC&lt;/sub&gt;) and the non-local contributions (O&lt;sub&gt;3-NLOC&lt;/sub&gt;) accounted for 41.6%, in which ozone from the southerly regions contributed significantly, for example, 9.9% of the ozone originating from Jiangxi, representing the highest geographical contributor. Because the origin and variation of O&lt;sub&gt;3-NLOC&lt;/sub&gt; was highly related to the diurnal movements in boundary layer, the similar diurnal patterns between O&lt;sub&gt;3-NLOC&lt;/sub&gt; and total ozone both indicated the direct influence of O&lt;sub&gt;3-NLOC&lt;/sub&gt; and the importance of boundary layer diurnal variations in the formation of such distinct diurnal ozone variations at Mt. Huang.&lt;/p&gt;

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