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HEAVY METAL CONTAMINATION OF SURFICIAL TIDAL FLAT
SEDIMENTS IN THE YANGTZE RIVER ESTUARY, CHINA
A thesis
Presented to
The Faculty of Graduate Studies
of
The University of Guelph
by
SHELLEY ANNE GORENC
In partial fulfillment of requirements
for the degree of
Master of Science
May, 200 1
O Shelley Anne Gorenc, 200 1
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HEAVY METAL CONTAMINATION OF SURFICLAI, TIDAL FLAT SEDIMENTS IN T a YANGTZE RIVIER ESTUARY, CHINA
Shelley Anne Gorenc University of Guelph
Advisor: Professor R.A. Kostaschuk
The purpose of this research was to determine controls of onshore-offshore
variations in heaw metal concentrations within surficial sediments of the Yangtze
Estuary tidal flats. In order to accomplish this, two sampling transects were
established dong the eastern shores of Chongming and Hengsha Islands. Results
showed that, while raw metals increased with distance seaward, no significant
relations exist between normdized rnetals and distance within transects and that
proximity to the turbidity maximum is not a significant control on metal distributions.
Statisticd analysis using Spearman's Rank, Mann-Whitney and PCA al1
established grain-size as the primary control on the spatial distribution of rnetals
within the Estuary. Furthemore, metal concentrations are consistent with Grade A
soils and represent a reiatively pristhe environment. This lack of evidence in support
of sediment contamination fiom dornestic and industrial discharge is likely the result
of dilution by high fluvial sediment loads.
Acknowledgernents
This thesis could not have been completed without the support and
contributions of many people. Firstly, this research opportunity would not have been
possible without the funding provided by C D A in assistance to the China Project
overseen by Dr. K.C. Tan. I would like to thank by advisor, Ray Kostaschuk for his
insight. editing and support of rny efforts. 1 also thank Dr. Chen and Yang Meng for
being such gracious hosts during my stay In their country and Dr. Les Evans for being
associated with this project. Lastly, 1 would like to thank Jen and Vicky for putting
up wiih their crazy ofice mate and my parents for al1 of their love and
encouragement. This thesis is dedicated to my husband.
TABLE OF CONTENTS
............................................................................ Acknowledgements .. i Table of Contents ............................................................................ 11
List of Figures .............................................................................. iv List of Tables ................................................................................... iv
Chapter One: Introduction ............................................................... 1
......................... ............................. 1.1 Problem Statement ... 1 ............................................. 1.2 Smdy Purpose and Hypothesis 4
..................................................................... 1 -3 Objectives 4 ............................................................. 1.4 Research Context 5
.......................................................... 1.4.1 Introduction 5 ................................... 1 .4.2 The Chemistry of Heavy Metals 6
...................................... 1.4.3 Sediment/Metal Associations 8 ................................................... 1.4.4 Sorption Processes 8
1 .4.5 Metal Associations with Organic Matter .......................... 9 1.4.6 TheGrah-SizeEffect ............................................. IO 1.4.7 Sediment Transport in the Estuarine Environment ............. 13
........................................... 1 .4.8 The Turbidity Maximum 14 ............................ 1.4.9 Tidal Flats and Tidal Wetlands ... .. 15
1 .4.10 Sediment-bound Meîais in the Estuarine Environment ....... 16 1.4.1 1 The Role of the Turbidity Maximum as a Metals Sink ....... 17 1 -4.12 Global Approaches to Estuarine Metal
............................................. Contamination Studies 18 1.4.13 Research on MetA Contamination in the Yangtze River
....................................................... Estuary, China 21 ............................................................... 1.5 Thesis Format 25
Chapter Two: Study Area ............................................................... 26
.......................................... 2.1 The Yangtze (Changjiang) River 26 ............................................... 2.2 The Yantgtze River Eshiary 29
................................................. 2.3 Yangtze Estuarine Islands 32 ............................................................ 2.4 Island Tidal Fiats 32
................................................... 2.5 The Turbidity Maximum 34 2.6 Chongming and Hengsha Island Economies ............................ 35
............................................................ Chapter Three: Metbodology 37
3.1 Objective #1: Transect Selection and Sediment Sampling ........... 37 3.2 Objective #2: Determination of Sediment Parameters and
........................... Heavy Metal Concentrations 38 3.2.1 Dx-ying ............................................................... 38
3.2.2 Grain-SizeAnaIysis ................................................ 42 ....................................................... 3.2.3 TOC Analysis 42
.................................................... 3.2.4 Percent Moisture 43 ...................................................... 3.2.5 Acid Digestion 44
3.2.6 Metal Concentrations ............................................... 45 Objective #3 : Anal yze Relations Between Metal Concentration .
Sediment Parameters and Sites AlongJBetween ..................................................... Transects 46
................................................ 3.3.1 Statistical Approach 46 Objective #4: Comparison of Heavy Metal Concentrations with
National Standards for Sediment Quality- and Global Estuaries ........................................... 50
Chapter Four: Results ...................................................................... 51
4.1 Variations in Sediment Parameters and Heavy Metal Concentrations Along Tidal Flats ............................................................ 51
4.2 Relations Between Heavy Metal Concentrations and Sediment Characteristics. Position on the Tidal Flat and Proximity to the Turbidity Maxhum ......................................................... 58 4.2.1 Scatterplots and Spearmans Rank Correlations ................ 58 4.2.2 Mann-Whitney U-Test Analyses ................................. 62 4.2.3 Principal Components Analyses (PCA) .......................... 63 Comparison of Heavy Metal Concentrations wi th National Standards For Sediment Quality and wirh Global Estuaries ....................... 66
Chapter Five: Discussion ................................................................. 69
5.1 Relations Between Heavy Metal Concsntrations and Sediment Parameters. Position on the Tidal Flat and Proximity to the Turbidity Maximum ......................................................... 69
5.2 Comparison of Heavy Metai Concentrations with National Standards for Sediment Quality and with Global Estuaries ........... 72
Chapter Six: Summary and Conclusions .......................~...........~........... 76
Appendix A: Sediment Parameters for Transects 1 and 2 ........................... 85
Appendix B: Heavy Meta1 Concentrations for Transects 1 and 2 .................. 87
Appendix C: Raw and Normalized Scatterplots for Transect 1 .................... 89
Appendix D: Raw and Normaiized Scatterplots for Transect 2 .................. 103
List of Fipures
Figure 1: Complexation and chelation by organic carboxylic acid functional groups ................................................................. 10
.................................................. Figure 2: Tidal flat classification system 15 Figure 3: Prîmary variables controlling heavy metai behaviour in the esniarine
........................................................................ environment 18 Figure 4: District of Shanghai .............................................................. 27
.......................................................... Figure 5: Yangtze Estuary? China 31 Figure 6: Plant progression along the tidal flats on Chongming and
Hengsha Islands .................................................................. 33 ........ Figure 7: Grain-size progression dong Chongming and Hengsha tidal flats 34
Figure 8: Location of the turbidity maximum n the Yangtze River E s t u q .... .. ... 35 Figure 9: View of Chongming Island tidal flats looking seaward fiom the
.......... ..................................................... retaining wall .. 39 Figure 10: View of Hengsha Island tidal flats looking towards the retaining
wall ............................................................................... 39 Figure 11: Sample collection on Chongming Island tidal flats ......................... 40 Figure 12: Kelway soi1 pH meter .......................................................... 40 Figure 13: UTM transects for Chongming and Hengsha Islands .................. .... . 41 Figure 14: Oven-dried sample fiom Chongming Island ................................. 43 Figure 15: Graphs comparing sediment characteristics between Transect 1
(Chongming Island) and Transect 2 (Hengsha Island) ..................... 52 Figure 16: Raw heavy metal concentrations on Transect 1 ........................ .... 54 Figure 17: Raw heavy metal concentrations on Transect 2 ........................... 56 Figure 18: Plot of component loadings for Transect 1 ................................... 65 Figure 19: Plot of component loadings for Transect 2 .......................... .. .... 66
List of Tables
Table 1: National standards @pm) for soi1 environmental qudity ..................... 22 Table 2: Spearrnan's Rank data for distance dong Transect 1 .......................... 60 Table 3: Spearman's Rank data for distance dong Transect 2 .......................... 60 Table 4: Spearman's Rank data for %TOC dong Transect 1 ........................... 61 Table 5: Speannan's Rank data for %TOC dong Transect 2 ........................... 61 Table 6: Mann-Whitney U-Test results for Transect 1 and 2 sediment
parameters ........................................................................... 62 Table 7: Mann-Whitney U-Test results for Transect 1 and 2 heavy metal
concentrations ...................................................................... 62 Table 8: Principal components analysis loadings ...................................... ... 64 Table 9: Principal Components Analysis summary for Transects 1 and 2 ............ 65 Table 10: Heavy metal concentrations in various global estuaries ..................... 68
Chapter One: Introduction
1.1 Paoblem Statement
Human kind is becoming aware of the complexity of nature and the delicate
baiance that exists in the global ecosystem. Every action taken towards modi*ng
the environment has countless repercussions. Geographers seek to understand these
complex interactions so that an assessrnent of the present condition of the ambient
environment rnay be known and measures may be taken in the hopes of preventing or
minlmizing future degradation. One important element of this dynamic system is the
estuarine environment and, according to Schubel(l97 1, p. XV-5):
"It is in the estuary that man has his most intimate contact with the marine environment. He makes many uses of estuaries; for shipping and transportation, for their biologicd and mineraiogical resources, and for the many varied recreational opportunities which they afford the inhabitants of the surrounding areas."
Estuaries are so vitd that many of the World's major cities have developed on
their bariks and the shores of their respective rivers. As the population and level of
industriakation of these cities increased, so did the pressure to produce a wealth of
resources, yield good land for fùrther urbanization, agricultural and industrial
development through land rectamation efforts, and accommodate waste products
(Stewart, 1972). One group of waste products associated with these pursuits is heavy
Heavy metals are produced fiom a variety of natural and anthropogenic
sources. In fluvial environments, however, metal pollution can result fiom direct
atmosphenc deposition, geologic weathering or through the discharge of agricultural,
municipal, residential and industrial waste products (Dawson and Macklin, 1998).
These metals are transporteci in solution or on suspended sediments downstream and
may reach coastal environments such as estuaries. Upon entering estuanes, complex
interactions amongst river discharge, saltwater intrusions, local currents. effluent
point sources. pH, temperature, oxygen content and sediment re-suspension processes
can effect the accumulation of rnetals in surficid sediments (Forstner and Wittman.
1979).
The distribution of metals in marine sediments adjacent to metropditan areas
c m provide researchers with endence of anthropogenic impacts on cov td
ecosystems and, therefore, aid in assessing the risks associated with discharged
hurnan waste (Buckley and Winters. 1992; Dauvalter, 1998; Karuppiah and Gupta,
1998). The build-up of metals in estuarine sediments holds significant environmental
implications for local communities as well as for mariRe water quality. For example,
many estuarine invertebrates process sediment as a food source and are susceptible to
the bioaccumulation of toxic metals. This bioaccumulation c m potentially threaten
the health of many species at the top of the food chain, especially birds, fish and
humans (Fang and Hong, 1999; Wright and Mason, 1999). Additionally, the
reclamation of metal-contaminated estuarine sediments poses a significant risk to
local consumers through the remobilization of metals from agrîcultural lands into
crops (De Jong and Stortelder, 1993; Ross and Kaye, 1994).
Most research on sediment contamination in estuaries has focussed on mid-to-
small-sized rivers in North America and Europe (Buckley and Winters, 1992; Zhang,
1999). Despite the fact that they play host to a significant portion of the global
population, there have been few studies of metals within large, high turbidity
estuaries. The watershed of the Yangtze (Changjiang) River. China, is one of the
most densely populated regions in the World (Zhang, et al, 1999b) and would be
expected to suffer fkom anthropogenic perturbations such as heavy metal pollution.
The issue of solving metal contamination has, thmefore, become a pressing task in
many Chinese cities (Zhang, et al., 1999a). Due to its abundant water and sediment
ioads, the Changjiang River provides an excellent Iaboratory for studying the
behavior of metals in hi& turbidity estuaries.
While considerable research has been performed on the Yangtze Estuary,
sampling sites tend to be very spradic in distribution and ciearly defined sampling
transects that focus on the onshore-offshore distribution of metals are lacking. There
are also few studies concerning the role of the turbidity maximum in effecting the
behavior of met& in estuaries. In their study, Chen, et al. (1996) provided a
cornparison between metal concentrations in suspended and submerged surficial
sediments in the turbidity maximum of the Yangtze Estuary. This work, however,
was performed around the JiuDuansha sand bar, the most seaward portion of land in
the Estuary and no transects, statisticd, or grain-size distribution analyses were
performed. Consequently, a stnictured study on the effects of proximity to the
turbidity maximum on heavy metal concentrations is unavailable. This observation
can be applied more generally to studies in other areas of the World as well.
Most sediment-contaminant studies in the Yangtze have focussed on
subaqueous samples, rather than studies of exposed tidal flat sediments in order to
establish the possible effects of land reciamation on metals. Of the studies that have
focussed on tidal flats within the Estuary, oniy a couple of studies have looked at
metal distributions on Chongming Island. Consequently, the question must be asked:
what is the relative statisticd significance of the various controls on heavy rnetal
concentrations within surficial tidal flat sediments of the Yangtze River Estuary.
China?
1.2 Study Purpose and Hypothesis
The purpose of this research was to determine the patterns and controls of
onshore-offshore variations in heavy metal concentrations within surficiai sediments
of the Yangtze River Estuary tidal flats. From this purpose, a research hypothesis
developed as follows:
Hvpothesis: The spatial distribution of heavy metals in surficial tidal flat sediments of the Yangtze River Estuary is affected by position on the tidal flat, sediment characteristics and proximity to the turbidity
1.3 Objectives
In order to test the research hypothesis, the following objectives have been
identified:
Obiective #1: Select two tidal flat transects (one near the turbidity maximum and one far fiom it).
Objective #2: Detennine heavy rnetal concentrations and sediment parameters for sarnples fiom each transect.
Obiective #3: Analyze relations between heaty metal concentrations and sediment characteristics, position on the tidal flat and proximity to the turbidity maximum in the Yangîze River Estuary.
Obiective #4: Compare metal concentrations on the Yangtze Estuary tidd flats with national standards for sediment quality and Ievels recorded in other estuaries around the globe.
1.4 Research Context
1.4.1 Introduction
Throughout history, it has been recognized that certain metals should be
considered toxic (Thorriton, 1995). As far back as the 19207s, research focussed on
metals within the context of agicultural production and metal deficiencies in soils-
While the postwar penod saw an increased concern in elevaîed metal concenh-ations
due to human impact, widespread interest in metal contamination of the environment
has reaily only emerged over the past 25-30 years @avies, 1992). By 1979, the field
of metal analysis in natural waters was still in a stage of developrnent, stalled by a
Iack of accurate and fiordable technoiogy. As this equipment becarne available,
however, the measurement of met& increased in popularïty within the scientific
comrnunity (Forstner and Wittman, 1979).
Mthough heavy metals are produced fkom numerous sources, both naturai and
anthropogenic in origul large-scale discharge into the environment requires human
activities (Dawson and Macklin, 1998). Natural sources of metals include the
weathering of rocks, gaseous emissions such as volcanic activity, natural methylation
and c d degassing, and airborne particulates such as windblown dust, seaspray and
volcanic emissions (Rasmussen, 1996). In fluvial environments~ anthropogenic metal
inputs resdt fiom the direct discharge of various treated and untr-ated agrïculturai.
W n g , residential or industrial effluents in addition to atmosphenc deposition and
stom water runoff (Dauvalter, 1998; Dawson and Macklin, 1998; Wright and Mason,
1999).
The significance of metals in the natural environment lies in the recognition
that heavy metals play an important role in ecotoxicology since they c m be highly
persistent and toxic in trace quantities (Fang and Hong, 1999). The ingestion or
absorption of metals by living organisms, especidly benthic invertebrates, c m lead to
bioaccurnulation within these organisms. This process can potentially Iead to the bio-
magnification of metals dong the food chain, threatening many species (Wright and
Mason, 1999). Coastal features such as estuaries are, in general, most affected by
local inputs fYom domestic and industrial wastes (Thornton. 1995; Saiz-Salinas. et al..
1996). As metals enter estuanes. complex interactions among river discharge,
saltwater intrusion, effluent point sources, pH, oxygen concentration and sediment re-
suspension processes can e ffect the concentration of heavy metals in sedirnents
(Forstner and Wittman, 1979; Williams. et al., 1994). This section discusses the
transport and deposition of sediment-bound heavy metats in the estuarine system and
reviews the current status of research regarding controis on heavy metals in estuaries,
with emphasis on metal behavior within the Yangtze Estuary, China.
1.4.2 The Chemistry of Heavy Metals
'Heavy metal' is a terni that generally includes any element with an atomic
density greater than 6 g/cm3 and may involve some 39 elernents (Jennett, et al.. 1980;
Davies, 1992). W i t b the context of this broad category, major metals such as Na,
K, Ca, and Mg are not u d l y considered to be heavy metals due to their lighter
weight and prevalence within the natural environment. Metals such as Ai, As, Cr,
Co, Cu, Fe, Mn, Mo, Ni, Sc, Sn, Va and Zn may be required by some organisrns in
small quantities and are sometirnes referred to as trace metals or trace elements
(Thomton, 1995). There is some debate over the inclusion of Al, As, Fe and Mn
under the heading of heavy metal.
AIurninum fdls outside of most definitions of heavy metals due to its light
density (3 &cm3) but is often included in contamination studies because can serve as
an indicator of clay content (Daskalakis and O'Connor, 1995). It also has a high
natural concentration that causes Al to exhibit conservative behavior in estuarine
systems (de Groot, 1995). Consequently, it tends to have relatively constant
concentrations over space and time purton and Statham, 1990). This property makes
AI usefid in normdizing totai metal results according to n a d ievels of enrichment
(Menon, et al., 1998). Arsenic is technically considered a metalloid but is often
regarded as a heavy metal due to its similar chernical properties and behavior to other
heavy metals. Lastly, Fe and Mn are not usually thought of as contaminants because
of their high, naturally occurrîng concentrations. Under certain soi1 conditions,
however? such as strong reducing, anoxic conditions, the toxicity of these elements is
a concem (Williams, et al., 1994; Chen, et al., 1999). A group of non-essential
elements hcluding Ag, Au, Cd. Hg and Pb dso qualifi as heavy metals (Furness and
Rainbow, 1990).
The most usehl definition for the purposes of this study is Thomton's (1995)
definition of heavy metal. This involves any metal or metalloid that is associated
with contamination and potentid toxicity. Heavy metds most commonly associated
wiîh human-induced contamination of the aquatic environment include As, Cd, Cr,
Cu Pb, Hg, Ni, and Zn (Jennett, et al., 1980).
1.4.3 SedimentIMetal Associations
In aquatic systems, metals are nansported either in solution or on the surface of
suspended sediments (Dawson and Maclclin, 1998). Due to their strong affinity for
particles (Luorna, 1990), metds tend to be accumulated by suspended matter or
trapped immediately by bottom sediments (Dauvalter, 1998). In estuaries, these
metals enter though direct discharge or atmospheric deposition from various sources
as well as through discharge from tributary rivers (Williams, et al., 1994; Wright and
Mason. 1999). Sediments then act as a storage cornparmient for metd contaminants
and may act as a source if changing environmental conditions cause a remobilization
of these rnetals (Salomons and Forstner, 1984). Sediment-metal associations occur
primarily through two dinerent phenomena: sorption processes and complexation by
organic matter.
1.4.4 Sorption Processes
Sorption processes are a broad group of fixation mechanisms that include
physical adsorptiodco-precipitation, chernical adsorption and ion exchange. While
some literature differentiates between adsorption and CO-precipitation (Sparks, 1999,
the distinction between the two processes is insignificant for most purposes.
Adsorption involves the precipitation of the fixating surface before the metal ion is
added and CO-precipitation involves the addition of a metai pnor to precipitation
(Salomons and Forstner, 1984). For the purposes of this discussion, the two
processes are both considered as adsorption.
Physical adsorption on the surface of a material is govemed by Van der Waals
forces (electrostatic forces of attraction produced by ions of opposing charge)
(Sparks, 1 995) and chemical adsorption requires the formation of chemical bonds
between ions or molecdes in solution with the solid surface (Salomons and Forstner,
1984). Ion exchange involves the substitution of an ion in solution with an ion on the
solid surface (Sparks, 1995). The solid phase for adsorption c m be made up of a
variety of components including clay minerals and metal oxides (iron and manganese
oxides in particular) that often form an outside layer on clay minerals. This coating
works effectively in combination with the clay as a sorbing surface for metals
(Forstner and Wittrnan? 1 979; Feltz, 1980; Salornons and Forstner, 1984; Sparks,
1995).
1.4.5 Metal Associations with Organiç Maîter
Organic matter has the ability to cornplex metais on its own but it is usually
found in association with clay minerals that are coated with Fe and Mn oxides (Feltz,
1980, Sparks, 1995). The metal sorption ability of humic organic matter lies
somewhere between those of clay mherals and metal oxides and is generally a result
of three main chemical binding groups: salicylic acid, carboxylic acid and phenolic
acid functional groups (Salomons and Forstner, f 984). As illustrated in Figure 1,
these groups c m form affiliations with met& involving one or more bonding sites on
the functional groups. If complexation involves the formation of two chemical bonds
with the metal, the process is called chelation (Sparks, 1995).
Figure 1: Complexation (A) and chelation (B) by organic
CiPTboxylic acid hctional groups (based on Sparks, 1995).
1.4.6 The Grain-Size Effect
It is possible to sub-divide estuarine sediments into two groups based upon
their respective diameters: a fine hc t ion composed of silt and clay-sized particles
(average grain diameter of less than 60 pm) and a coarser fiaction cornposed of sands
and grave1 (average grain diameter greater than 60 pm). Within the silt-clay fiaction,
the shape of particles is relatively diverse due to its various components including
clay minerals, organic matter, fine quartz and feldspars. The coarser fraction contains
sub-rounded particles of quartz and feldspars. Due to their larger size, sand and
grave1 travel relatively srnall distances in rivers and estuaries, moving close to the
bed. The silt-clay fraction may travel over large distances, suspended within the flow
and accumulate in areas of calm water such as flood plains or tidd flats (Salomons
and Forstner, 1984).
In general, the surface area and the sorption area of sediment increases
logarithmically with decreasuig grain-size (Luorna 1990). This results in a pattern of
increasing metal concentration with decreasing grain-size that has been well
establisbed within the literature (Forstner and Wittman, 1979; Buckley and Winter,
1992; Palanques, er al., 1998; Lrabien and Velasco, 1999). Within the silt-clay
fraction. two types of metal sorption can occur: pH-dependent and pH-independent
sorption. Clay rninerds are unique in that they can support both sorption processes.
W l e pH-dependent sorption occurs across the many broken bonds on the surface of
the particle, their net negative structural charge supports pH-independent sorption.
This latter phenornenon can be generated in two ways: isomorphous substitution in
one of the phylosiIicate layers or non-ideai occupancy of the octahedrai sheet. The
former involves the replacement of Si by Ai in the tetrahedral or octahedral layers of
a clay mineral while the latter occurs where the concentration of Al is slightly lower
than that required to produce a neutral charge in the mineral. The remaining silt
fiaction can attract metal ions only through pH-dependent sorption to the broken
bonds scattered across their surface (Sparks, 1995).
This strong dependency of metai concentration on the composition of
sedirnents (de Groot, 1995) is referred to as the grain-size effect. According to
Ackemann, et al. (1983, p. 3 17),
"The greatest influence on the final results in the course of the sampling processing is exerted by the grain-size effect, i.e. coarse components of the sediment (sand) with normdly very low heaw metal contents produce a random shifting of the heavy metai contents of the total sediment sample by 'diluting' it."
Most heavy metal contaminatisn studies, therefore, involve some method to correct
for this effect. This can involve the comparison of the total metals content with
reference to a conservative element such as AI, Fe or Sc (Daskalakis and O'Connor,
1995: Chen et al., in press; Shang, 1999) or separation and analysis of o d y the < 60
pm (Palanques, et al, 1998; Irabien and Velasco, 1999) or the < 20 pm (Ackermann,
1980) fraction. The analysis of total metals in sediment samples followed by a
correlation with the percentage silt-clay present has also been applied to heavy metal
research (Ackermann, et al., 1983; Palanques, et al., 1998). In some cases, however,
metals with very low sediment concentrations (typically Ag, Cd, Hg and Sb) do not
show good correlations with grain-size or Al in comparison with rnetals whose
occurrence is more prevalent in the natural environrnent (Daskalakis and O'Connor,
While metal mzdysis of the entire silt-clay fraction or correlation to its relative
abundance in a sedirnent sample rernains the dominant method of grain-size
correction, some researchers question the suitabiiity of this technique. Ackermann, et
al. (1983) studied 22 similarly polluted sediment samples fi-om the Elbe Estuary,
Germany and f o n d that the correlation of metals with the < 20 pm fraction is 2-3
times betrer than in the < 60 p fiaction. Furthemore, the 20-60 prn fraction
contains oniy 10-20% of the metals present in the < 20 jun fraction. They concluded
that the rationale behind using the eritire silt-clay hct ion seems to be based primarily
on the traditional break between silt and smd-sized sediment, Although metals have
been found within this hction. the research presented by Ackermann, et al.,
illustrates that the majority of those metals are contributed by the < 20 p m fraction.
This work is particularly relevant for estuaries, where the primax-y size of sediment
travelling in suspension lies in this segment. These findings were supported by
Forstner (1 985) who found a good correlation between conservative elements and the
< 20 pm fiaction and de Groot (1995) who confirmed a linear relationship between
metal concentrations and the c 20 pm hction.
1.4.7 Sediment Transport in the Estuarine Environment
According to Forstuer and Wittrnan (1979), an estuary c m be deficed as a
semi-enclosed body of water that has a fkee connection to the open sea and within
which seawater experiences dilution by fkesh water fiom land drainage. Simply put,
an estuary represents a mixing zone between river and sea- Estuarine sediment
transport is complex and often varies fkom case to case. In general, however.
estuaries are areas of accretion where sediment deposition and movernent is driven by
circulation patterns within the water body (Salomons and Forstner, 1984).
The primary characteristics responsible for sediment distribution are tidal
action, river inflow, waves and wind. As a result of the complex relations between
these factors, sediment distributions tend to be extremely variable on both a spatial
and temporal scale (Perillo, 1995; Williams, et al., 1994), although tides arguably
exert the most significant control over an estuary's ability to transport sediment
(Dyer, 1995). Estuaries can be classified according to their tidal range as: microtidal
(< 2 m), mesotidal (2-4 m) and rnacrotidal (> 4 rn) (Dyer, 1994). With increasing
tidal range, the whole of the esniarine water mass can move in response to tidai
periodicity @yer, 1995).
1.4.8 The Turbidity Manimum
The turbidity maximum is a feature common to mesotidal and macrotidal
estuaries and is defmed as the area within an estuary that contains higher suspended
sediment concentrations than those in the river or m e r seawards in the estuary
(Dyer, 1994). The position of the turbidity maximum responds dynamkally to
changes in river flow and tidal currents but is generally located at, or (due to diffision
processes) slightly landward of, the tip of the salt-wedge intrusion (Dyer, 1995). The
semi-enclosed residual circulation that occurs in the system sustains the high
concentration of sediment in the turbidity maximum (Dyer, 1 972).
This circulation pattern, resulting fiom a salt water intrusion and river flow of
differing densities, creates residual landward bottom flow and seaward surface flow
(Dyer, 1995). Sediment being discharged within the river flow- travels dong the
surface in a mean seaward direction until velocities are no Ionger sufficient to support
transport. The sediment then settles into the bottom layer of saline flow and is carried
dong with particles entering fiom the sea back to the upper estuary (Dyer, 1972).
This process is termed vertical gravitation circulation and is an effective sorting
mechanism for depositing coarser particles dong the bed while sweeping a narrow
range of particles through the estuary (Dyer, 1995).
1.4.9 Tidal FIlats and Tidal Wetlands
Most classification systems for tidd flat areas involve separation of the flats
into several sub-units (Figure 2). The hîghest or most landward portion of the flats is
usudly termed the supratidal or supralittord zone. Sitting above the mean hi& water
spring tide (MHWST) level, it expenences inundation only during large storm events.
The intertidal or littoral zone is comprised of three sub-units. The most landward
sub-unit falls between MHWST and mean high water neap tide (MI-IWNT) levels and
is occasiondly covered by water. The middle intertidal flats sit between MHWNT
levels and mid low water neap tide (h4LWNT) and experience inundation with every
tide. The most seaward sub-section sits below MLWNT and is occasionally exposed.
Finally, the subtidal or sublittoral zone lies seaward of the lower intertidal flats and is
very rarely fkee of water (Amos, 1995).
Supratidai Intertidal Zone Subtidal Zone
A Zone * I I I
- - I I
I 1 I rn 9
1 Upper : Middle i I Lower 1
9
Figure 2: Tidal flat classification system (based on Amos , 1995).
Tidal flats are ofien linked with the occurrence of vegetated salt marsh areas.
Salt marshes thrive in the sheltered coastal environrnents of estuaries that experience
medium to large tidal ranges (ranges > 3 m). According to Williams, et al. (2994).
colonking species establish themselves dong the flats according to their relative
tolerance to inundation and salinity. This progression of plant species can be utilized
to m e r sub-divide the tidal fiats into three distinct areas. The lowest portion of the
marsh occurs between MHWN tides and mean high water levels and displays
little v&ety in plant species due to the extremely saline conditions of the inundating
water. As a result, this area usuaiIy displays a very patchy plant distribution,
separated by areas of mud flat. The middle rnarsh lies between MHW and MHSW
tides. This area contains a greater diversity of plants because of the decrease in
sdinity. Finally, the upper marsh zone sits above MHWS tide, thus receiving tidal
inundation only 5- IO times per year. Ln general, tidal flats display an increase in grain
size with distance fiom shore. This is in due in part to the slack water produced by
tidal advancement and retraction as well as the energy attenuation ability of the native
plant species. The vegetation effectively slows currents over the flats, decreasing the
sediment load of advancing waters (Yang, 1998; Yang, 1999a).
1.4-10 Sediment-bound Metals in the Estuarine Environment
Two opposing mechanisms control the behavior of metals in the estuarine
environment. The first process involves the removal of metals from arnbient waters
by sorption, organic matter complexation and adsorption by FeMn oxides. The
second involves remobilization by desorption processes (L'Her Roux, et al. ,1998).
Re-mobilization of sediment-associated metds can occur for a variety of reasons. An
increase in salinity produces elevated concentrations of Na ions that compete with
metals for sorption sites on the sediment (Forstner and Wittman, 1979). An increase
in complexing agents, such as chioride, that form stable, soluble metal compounds
wiIl also act to release rnetals. According to de Groot (1995): significant
solubilization of metals occurs between salinities of 1-6 %.
A decrease in oxygen content results in anoxic. reducing conditions that
promotes the disassociation of Fe/= oxide coatings by altering the valencies of
manganese and iron, releasing sorbed and CO-precipitated metals to the surrounding
water (Williams, et al, 1994). Lastly, a decrease in pH effectively increases the
concentration of protons that c m compte for sorption sites (Forstner and Witmian.
1979). Forstner (1985) reported that metal adsorption increases from nearly zero to
approxirnateiy 100% over a pH elevation of one to two units. Low pH levels also act
to dissolve carbonate and hydroxide-metal compIexes (Forstner and Wittrnan, 1979).
1.4.11 Role of the Turbidity Maximum and Estuaries as a Metals Sink
While ion exchange and pH are the most significant controls on metal
mobilization, the re-suspension of bottom sediments and subsequent increase in
sorption surfaces c m act to interfere with metal solubilization (L'Her Roux, et al..
1998) and constitutes a significant loop in the cycling of metals within estuaries.
Depending on the mechanisms involved in creating a turbidity maximum, fine
sediments can either accumulate or be removed dong witt their associated metals
(Menon, et al., 1 998).
The question remains, however, whether estuaries are truly an effective sink
for heavy metids. While many studies have shown that estuaries are efficient in
trapping sediments (Palanques, et al, 1998; Fang and Hong, 1999), this may not
necessarily hold true for metals. In fact, few detailed mass balance studies have been
perfonned on estuaries. This is most likeiy due to the complex nature of the
environment and the numeruus, inter-related contro lling variables. A particular
estuary c m be considered a rnobilizing or retaining system depending on the balance
between sorption and solubilization processes within the system (Salomons and
Forstner, 1984). Figure 3 provides a summary of the prirnary variables controlling
heavy metai behaviour in an estuarine environment.
Tributary + Discharge
Atrnospheric Deposition +
Grain Size u H - -
f Remobilization from Bottorn Sediments
+ Direct Discharge
Figure 3: Primary variables controlling heavy metal ôehaviour in the estuarine environment (Based on Forstner and Wittman, 1979).
1.4.12 Global Approaches to Estuarine Metal Contamination Studies
In their 1999 study, Wright and Mason compared the distribution of metals in
the top 30 cm of sedirnent fiom two adjacent estuaries dong the East Coast of
England. Samples were collected at three sites for both the Stour and Orwell
eshiaries in order to represent the, upper rniddle and Iower estuarine sections.
Analysis of the <500 pm hct ion indicated a peak in metal concentrations at the head
and mouth of both estuaries. In the saltmarsh sediments of the Orwell Estuary.
meanwhile, metal levels were generdly higher Phan those at other sites. Spearman's
Rank Correlation coefficients identified reiationships between pairs of metals (Cd/Cu,
Cu/Hg, Zn/Hg and Pb/Zn in the Orwell and Cu/Pb in the Stour). The authors
concluded that patterns in heavy metal concentrations were most likely the result of
local point sources. The trapping of sediment by saltmarsh vegetation and the
dilution of contaminated river sediments by relatively pristine marine sediments were
also considered to effect metal distributions.
Palanques, et al. (1998) studied the distribution of heavy met& in the densely
populated and highly industrialized Besos Prodelta in the Mediterranean. Sediment
cores were taken to a depth of 30 cm to 3 m in order to determine spatial and
temporal patterns in contamination. Once normalized to percent silt-clay, results
indicated a decrease in metal concentrations and depth of contamination wiih distance
seaward. Histoncal analysis revealed present metal levels to be 5-20 times of those at
the beginning of the century and peaks in metal concentrations matched increases in
population and industrialization in the area Palanques, et al. (1998) concluded that
the vertical increase in contamination was the result of anthropogenic activities.
Physical processes such as sediment settling and fkesh and salt water scavenging
controlled the spatial distribution of rnetals within the estuary.
h b i a n and Velasco (1999) surveyed the Oka River estuarine basin in Northem
Spain to determine the distribution of heavy metals in surficial sediments and identi@
possible metal sources. Due to the relatively pnstine conditions of the ecosystem,
only the top few miHimeters of sediment were analyzed for local enrichment. The <
63p.m hction was selected for acid digestion and findings revealed a decrease in
metal concentration towards the mouth of the estuary. While point sources were
identified as the main inputs for metals, the seaward decrease in concentrations was
attributed to a variety of factors including an increase in chlorinity, decrease in point
sources and dilution by marine sediments.
Zwolsman, et al. (1996) perfomed a study of the spatial and temporal
variations in sediment-associated metals of the Schefdt Estuary, southwest
Netherlands. The authors utilized analysis of variance (ANOVA) on the < 16 p m
fraction of 13 1 1 samples that had been collected fiom the site between 1959-1 990.
Resuits isolated two groups: a group of sediments with low metals and high organic
matter content representing pristine conditions and a group of fine-grained, high
organic rnatter, high metals sediments representing polluted harbor conditions.
Principal Component Analysis identified three components that accounted for 90-
95% of the total variance. The first, and rnost significant, component explained 80-
90% of this variation and was comprised of grain-size effects, organic matter content
and al1 metals. The authors subsequently concluded that the spatial distribution of
metais in the Scheldt Estuary is primarily controlled by the dilution of polluted fluvial
sediments by relatively cIean marine particles.
BucMey and Winters (1992) utilized Principal Axis Factor Analysis with
varimax rotation to determine relationships between metal concentrations, point
sources, grain size and organic matter content for 274 samples of contarninated
surface sediments f?om Halifax Harbor. They isolated five factors that accounted for
64% of the total variance. The primary contamination factor (comprising 4 I % of the
variance) found that metal concentrations correlated with areas of fine-grained or
organic matter-rich sediment and proximity to sewage outfalls and treatment plants.
Factors 2-5 accounted for only 8%, 6%, 5% and 4% of the total variance and were
associated with the influences of land drainage, pH, reducing/anoxic conditions and
calcium carbonate on metal concentrations, respectively.
1.4.13 Research on Metal Contamination in the Yangtze River Estuary, China
The Yangtze River watershed is one of the most densely populated areas in the
World and is, therefore, expected to experience detrimental ef3ects fiom
anthropogenic activities (Zhang, et al., 1999b). As of 1996, o d y 5% of the municipal
and 17% of industrial wastewater received treatment prior to entering aquatic systems
in China (Wu, er al., 1999). While this pattern could be attributed to the high cost of
treatrnent and a lack of equipment, it resulted in an average sewage to runoff ratio of
0.014 (Chen, et al., 1999). By the 198O's, industrial and dornestic waste discharges
into the river had reached a rate of 3 5 . 7 ~ 1 0 ~ t/d. Since that tirne. the govemment of
China has made efforts to control pollution and establish national standards for
environmental quality. In July of 1995, the govemment published the first National
Standard for Soi1 Environmental Quality (Chen. et al., 1999) and in 1998, China
spent 150 million Yuan on the construction of pollution control plants for theYangtze
River (Beijing Review, 1998). Table 1 illustrates the national soi1 standards for
heavy metals established in 1995.
A variety of studies have examined heavy metals in the Yangtze River Estuary.
Meng and Liu (1996) studied 32 submerged
metds and R-mode Factor Analysis revealed
surficial sediment samples for total
that a significant relationship exists
between mean rnetal concentrations and percent clay in the sediment. Chen, et al.
(1 996) studied heavy rnetal concentrations in suspended and bed sedirnents in the area
of the turbidity maximum around the Jiuduansha sandbar in the Yangtze Estuary.
Total metal analysis for Cd, Cu, Pb and Zn indicated that higher concentrations
generally occurred in suspended sedirnents. Wu. et al. (1996) performed an
assessment of heavy metal concentrations in the tidal beach sedirnents near the
Bailonggan wastewater outlet in the Pudong New Are% China Five sampling pits
along the beach displayed unacceptable levels of Cu. Zn, Pb and Hg according to
governrnent standards. Results suggested that tidal currents tend to cany metals
against the flow of the river and deposit them on local tidal flats.
Table 1: National standards (ppm) for soil environmental quality. (8ased on Chen, et a&, 1999)
Metal
1 As: 1 1
Cd
Grade A Soi1
I Cu: I 1
(Natural Background)
1 0.20
1 farmland 1 1 3 5 1 50 1 1 00 1 100 1 400 1
Grade B Soi1
paddy soi1 ' S 15
Grade C Soi1
pH < 6.5
0.30
30 40 dryland
1 Cr: I I
I l 5
orchard
Pb
pH 6.5-7.5
0.30
25 30
paddy soi1
dryland
pH > 7.5
0.60
20 25
I
pH > 6.5
1 .O
30 40
200 300
--..- 1 3 5
_< 90
150 250
200 350
250
400 1 500
300 5 90 200 150
350 400 250 300
Xu, et al. (1997) conducted a study of the dynamic accumulation of heavy
metals along the tidai flats that connect Shanghai to Hangzhou Bay. Forty-five
surface sediment samples were collected to a depth of 5-10 cm along stable.
accumulating and eroding banks of the flats. Total metal results indicated that the
spatial distribution of Cu, Zn. Pb. Cr, and Cd was dependent on local sedimentary
dynamic conditions. with peak concentrations occurrhg in accumulating banks.
Further, while municipal sewage and hdustrial wastes were f o n d to have produced a
serious impact on the environmental quality of sediments, point source metal inputs
were not found to be a significant variable in the distribution of metals in the area
In their investigation of heavy rnetal concentrations in the intertidal zone of the
Yangtze Estuary, Zhang, et al. (in press) sarnpled 5 sites dong the southern ban. of
the Estuary and the tidal flats of Chongming Island and the Jiuduansha Shoal. Short
transects, m i n g parallel to retaining walls, were composed of 3-5 sampling sites
each. These samples were then subjected to metal and gain size analysis. Results of
the study indicated higher concentrations of metals in the marsh zones (especially the
Phragmitis zones) of the islands due to their abiiity to trap fine sediments. In general.
metal concentrations from the islands were lower compared to those on the southern
shore, with metal levels increasing hdward. These patterns were explained by
proximity to sewage discharge sources along with the strong influence of grain size
effects.
In an attempt to describe the distribution of sediment-bound metals in the
Changjiang River, Zhang, et al. (1994) anaiyzed metal concentrations in suspended
sediments dong the lower reaches of the river. Field data indicated relatively low
rnetal concentrations compared to those in the Amazon, Zaire and Orinoco Rivers as
well as those h m most Euopean rives. The authors conciuded that the enormous
discharge and tremendous sediment Ioad of the Changjiang River causes
contaminants to be rapidly diluted. Identification of heavy rnetd pollution in the
Yangtze is. therefore, extremely difficult. In an extension of this research, Zhang
(1 999) iooked at the behavior of sediment-associated metals within the Changjiang
Estuary and along the East China Sea shelf region. Suspended sediment samples
were collected in these areas during the period of 1986-1988 over three surveys.
Results of organic matter quantification showed very low, hi@y variable
concentrations lying in the range of 0.5-1 -5%. Nomalization of metd concentrations
to AI levels indicated only minimal variations in metal concentrations between
sampling sites, indicating that metal variations are rnost likely due to changes in
sediment composition across the Estuary. The author went further to compare
normalized metal levels from the Yangtze Estuary with metal concentrations fiorn
other estuaries around the WorId. The comparison indicated that metzUaluminum
ratios for Cd, C u Ni, Mn and Pb are lower than those fiom polluted European and
Asian systems such as the Sheldt, Rhine, Cauvery and Gironde by as much as a factor
of five. In fact, the ratios were comparable to those fiom the Lena Estuary, a system
that is generally considered to be one of the most pristine aquatic systems in the
WorId.
Chen, et al. (in press) used five short cores to distinguish temporal and spatial
patterns in heavy metal contamination of tidal flats in the Yangtze River Estuary.
Four sampling sites were chosen along the coast of Chongming Island in addition to
one site on the southern bank of the Estuary. AU locations were placed in the vicinity
of sewage discharge outiets. Heavy metal levels in the < 150 pm fraction were
normalized by aluminum content to account for grain-size effects and the spatial
distribution of the metals correlated with proximity to sewage outfails and local
industry. Overall, however, concentrations were lower than in other estuaries around
the globe. n i e authors suggested that this is most likely due to the dilution of
sediment-associated heavy metals by river sediment. Lead-210 dating resdts
performed on each core lacked an exponential profile that confirmed high
sedimentation rates on the tidal flats.
1.5 Thesis Format
The following thesis contains 6 Chapters. Chapter 1 has given a brief
overview of the research topic and objectives as well as a review of the Iiterature
pertaining to the fate and transport of sediment-bound merals in estuarine systems.
Chapter 2 provides a description of the study area while the Chapter 3 illustrates the
methodology utilized to achieve the objectives outlined in Chapter 1. The fourth
Chapter presents the field resdts and statistical data that are then discussed in Chapter
5. Finally, Chapter 6 provides a summary of the research findings and presents some
conclusions on relatiom of heavy metal concentrations with sediment characteristics
and the turbidity maximum in the Yangtze River Estmry.
Chapter Two: Study Area
2.1 The Yangbe (Changjiang) River
Of the estimated 7x10~ tons of fluvial sediment discharged each year by the
World's nvers, Chinese rivers contribute approximately 28% of the total (Dyer,
1994). Furthemore, the dissolved solutes associated with this discharge contribute
between 15 and 20% of the World's fluvial solute inputs. Studies of significant
Chinese river/estuary systems, therefore, should provide a positive contribution to the
global oceanographical database (Zhang, 1995; Zhang, et al., 1 999).
Stretching a distance of 6300 km and draining a total area of 1,809,000 km2 of
land, the Yangtze River is the iargest river in China and the third largest river in the
World (Yang, 1999). The mean m u a l flow of the river is 29,400 m3/s with peak
flows reaching 96,600 m3/s during the rainy season. Lasting frorn May to October,
the rainy season accounts for 71.7% of annual river flows and 87% of total annual
sediment inputs to the Yangtze Estuary (Shen, et al., 1993a). Total sediment outputs
from the river average 4 . 8 6 ~ 1 0 ~ tonnes per year. This comprises the second largest
contribution in China and the f o u l i largest in the World (Shen, et al., 1993 b).
The Yangtze River Delta covers an area of 30,000 km2 (exclusive of the
subaqueous part) and supports a population of over 60 million inhabitants (Chen, et
al., in press). The extensive tidal flat system of the D e b provides nch land resources
for the District of Shanghai (Figure 4) and some 1000 km2 of tidal flats have been
reclaimed in the Iast 50 years in order to accommodate the expanding
Figure 4: District of Shanghai (Based on Shanghai Municipal Institute of Surveying and Mapping, 2000).
population. Presently, an additional 90 km2 of flats are being targeted for
reclamation. In generaf, these efforts are seen as an opportunity to increase land
resources in the area while reducing blockages in the indispensable Yangtze shipping
channel that are produced by the immense sediment loads being carried by the river
(Li and Zhang, 1996).
While the Delta's rapid expansion into the East China Sea has provided
opportunities for agicultural production and housing, concerns have arisen regarding
the potential impact of metal contamuiated sediments on food quality and human
health. Years of unsuccessful waste management resulted in excessive pollution of
tributaries to the Changjiang River, including the Huangpu River (Zhang, 1999). In
an attempt to rninimize impacts on local land, the Chinese govemment installed a
systern of sewage pipelines in the Shanghai region in the 1980's. The purpose of this
system was to discharge urban and industrial wastes deep into the estuarine channel
where it was more likely to be flushed away and dihted by littoral hydrodynamic
circulation of the Yangtze Estuary. These municipal and industrial discharges
represent the main source of metals within the Estuary, although inputs along the
entire drainage basin contribute as well (Chen, et al., in press). Figure 5 shows the
locations of these sewage outfalls and their relative contribution of urban and
industrial waste. Three major sewage water outlets occur along the southem coast of
the Estuary near Bailonggan, Zhuyuan, and Baoshan. Chongrning Island, meanwhile,
has six sewage discharge locations. Three minor outlets are located dong the less
industrialized northem shore while the remaining three lie dong the southem shore of
the IsIand. Of the 8.4 million tons of sewage being discharged annually into the
estuary fiom Chongmhg Island, Chengqaio outfidl contributes 76% of the total
(Chen, et al., in press).
2.2 The Yangtze River Estuary
The Yangtze Es- is the outlet of the Yangtze River Valley and the
navigation channel for Shanghai Port, the Iargest shipping port in China (Shen, et al.,
1992). it supports aquaculture, fishenes and domestic waterfowl production for the
surrounding population and Zs also used as a source of water for agricultural imgation
and domestic consmption (Chen, et al., in press). The mouth of the Estuary is
approximately 90 kilometers wide and requires an annual dredging volume of 18x 1 o6
m3 to maintain river depths suficient for navigation (Shen, et al., 1 992). This is due
to the fact that, whiIe typical accretion rates in North Arnencan and European
intertidai zones are in the range of a few millimeters per year and in some cases are
retreating, deposition in the Yangtze Estuary is greater than 2 mrn/yr on average
(Yang, 1999). This rate surpasses the estimated annual global rise in sea level (Chen,
et al., 2000).
The Estuary is a coastal plain, mesotidal, partially rnixed estuary with four
mouths connecting it to the open sea (Figure 5). Each mouth is the product of river
flow diversion around islands within the Estuary. Chongming Island is the largest
island in the Yangtze Estuary and creates the barrier between the North and South
Branches. Changxing and Hengsha Islands then further divide the South Branch into
the North and South Channels. The South Channel is spIit into the North and South
Passages by the Jiuduan sandbar formation at the mouth of the Estuary.
Ninel-eight percent of the sediment that the Estuary receives from the
Yangtze River is suspended load with grain sizes ranging from fine sand to clayey
silts (Shen, et al., 1993a). Bed sediments consist of fine sands in the South Branch.
sandy silts in the South Channel and clayey silts in the North and South Passages.
Tides may effect a distance as great as 350 km into the lower reaches of the river
(Zhang, 1999). creating mean tidal ranges of 2.66 m in the Southern Branch. with
hi& tides of 3 . 3 4 2 m and low tides of 0.28-0.18 m (Li and Zhang, 1996). Marine
inputs of sediment do exist but sediment inputs fiom the River make the most
significant contribution by far to the Estuary (Li, et al, 1993). More than one half of
the sediment that enters the estuary becomes deposited on the broad deltaic area,
helping to create the well-developed tidal wetiands that prograge seaward at a rate of
100-300 m/yr (Zhang, et al., in press). The remaining sediment travels southward
and eastward and settles on the continental shelf zone of this area (Zhang, 1999).
b Sewage water outlet
Scale of arrow relative to the * amount of m a g e discharge
Lake ,, Sample transect (not to sale)
15 h O-
I rn
1 21° 122'
Figure 5: Yangtze Estuary, China (Based on Chen, et al, in press).
2.3 Yangtze Estuarine Islands
The formation of Chongming, Changxhg, Hengsha Islands and the Jiuduan
sand bar began in the 7", 17', 19', and 1950's respectively. The ùiree islands are
constantly being reclaimed using a system of continuous ring-like retaining walls or
dykes (Yang, 1999~). In total, they share approximately 301 retaining walls, each an
average of 145 m in length. These walls are used to improve shore stability and
prevent erosion or migration. As of 1999, Chongming, Chongxing and Hengsha
Islands had shorelines that were approximately 210 km, 59 km and 30 km in length,
respectively (Yang, 1999d). Alluvial grain size dong the shores of Chongming Island
lies in the range of clayey-silt whiIe sediment dong Hengsha Island ranges fiom
clayey-silt to sandy-siIt with increasing distance offshore. Benthic fauna on al1 three
Islands is dominated by the presence of two types of bottorn-feeding crabs: Sesarma
debaani and 27yoplmc deschampsi (Yang, 1 999c).
2.4 Island Tidal Flats
RecIamation efforts have significantly altered the tidal flat areas on each
island (Yang 19994. The resultant intertidai areas are 2093 km2, 44 km2 and 16 km2
for Chongming, Changxing and Hengsha Islands, respectively (Yang, 1999d). In a
seaward direction, the intertidal zone contains several distinct units that can be
identified by their colonizing pIant species: the Phragmitis ustralis zone, Scirpus
marqueter zone, and Scirpus triqueter zone followed by bare rnud flats (Figure 6).
This entire progression of plants, however, does not necessarily occur at each island
due to land reclarnation (Zhang, et al., in press). As a result, the uppermost
vegetated region of the intertidal zone is usually non-existent (Yang, 1999b). In
general, the division between continuous plant colonization and mud flat occurs at
about 50 cm above mean water Ievel (Yang, 1998).
Figure 6: Plant progression along the tidal flats on Chongming
and Hengsha Islands (Based on Zhang, et al., in press).
According to Li and Zhang (1996), the high intertidal flats in the area are
submerged a total of 3-5 h o m during a tidal period with a sediment size of clayey-
silt. The middle intertidal flats are exposed at tidal heights between mean neap hi&
tides and neap low tides and are composed mainly of silt. Lastly, the lower intertidal
flats are o d y exposed during low tide and are comprised of sandy silt, silt sand and
fine sand. This landward decrease in grain size with distance c m be affected by the
local vegetation as well as the 4-5 storm events that occur annually in the Estuary
(Yang, 1998). Grain size distributions for the upper, middle and lower tidal flats are
illustrated in Figure 7.
Figure 7: Grain-size progression dong Chongming and Hengsha tidal Bats (Based on Li and Zhang, 1996).
2.5 The Tinrbidity Maximum
The turbidity maximum is 25-46 km in length with sediment concentrations
ranging from 0.1-0.7 kg/m3 at the surface to 1-8 kg/rn3 near the bed. It is generally
located in the Southem Branch of the Estuary (Figure 8) but the ultimate position of
the turbidity maximum depends upon the season, tidal action, waves and curent
velocity. During the rainy season and at ebb tide, the turbidity maximum is forced
seaward (Shen, ef a l , 1993a). Cornposed of sediment prirnarily in the range of silts
and clays, this turbid region may experience seasonal variations due to changes in
sediment input fiom upstrearn sources (Li and Zhang, 1998). Tidal effects c m reach
as far as 300-350 km into the lower reaches of the river while brackish waters have
been recorded as much as 100 km idand fkorn the rnouth of fhe river (Zhang, 1999).
Furthemore, with approximately half of the fluvial-supplied sediment being trapped
in the mouth of the river. the turbidity maximum acts as a filter for materials such as
heaw metals, preventing their escape h t o the open sea-
. . - -_ . *. -.. .-- . .::, .. . . , Island '.,-aanfi
Figure 8: Location of the turbidity maximum in the Yangtze River Estuary.
2.6 Chongming and Hengsha Island Economies
Chongming Island is the third largest island in China and the largest alluvial
island in the World. Covering an area of 1,160 km2, the Island stretches 79 km in
length and supports a population of 733,000 people. Twenty-six villages, eight state
farrns and seven municipal state-owned enterprises exist on the land (Govemment of
China 2000a). Although it falls within the District of Shanghai, far less Uidustry has
established on the Island and it currently maintains a predominantly agricultural
economy. In 1996,448 industrial plants and factories were in existence on the Island.
the majority of which are located on the Island's south-central coast (Chen, et al., in
press). Industrial sectors include textiles, metallurgy, machinery, brick making and
electricity. More than 40 hovercraft car-passenger ships and other ferryboats provide
transportation between Shanghai and Chongming Island daily (Govemment of China
2000b).
Hengsha Island is the smailest and most seaward island in the Estuary. The
Island was founded in 1909 and also falls within the District of Shanghai. Hengsha
boasts a thriving a g r i c u l t d economy with grain, Cotton, orange, vegetable, pig and
fishery production. The 109 factories on the island focus mainly on calcination.
metal machining. fumiture, embroidery and brick making. The island is also
attempting to foster a tourism industry, encouraging visitors fkom mainland China to
stay at their national vacation site, constmcted in 1992. As with Chongming I s h d ,
ferry service allows travel to the isIand several times per day (Land Planning and
Management Authority of Baoshan, 1995).
Chapter Three: Methodology
3.1 Objective #1: Transect Selection and Sediment Sampling
The eastern shores of Chongming and Hengsha Islands were chosen as field
sites firstly because they are the shores that experience the highest degree of sediment
deposition and, thus, offer the most developed tidal flat regions for study. Secondly,
the eastern tidal flats are those ciosest to the rnouth of the Estuary and are most
intluenced by the turbidity maximum. Transect locations were selected on the basis
of accessibility and by the extent of exposed tidal flat available for sampling. Since
the islands remain relatively undeveloped and reclamation is constantly extending
their outer boundaries, very few roads extend to the edge of the tidal flats.
Furthemore, travel along the retaining walls to a particular portion of flat was
dificult and sornetimes restncted by construction activities.
Sediment samples from Chongming Island were collected on May 5, 2000
along a survey transect on the most seaward portion of the Island. The initial
sampling site was located at the retaining wall, with subsequent sites located along
the tidal flats. progressing towards the sea in an eastward direction (Figure 9).
Sampling sites were located at 100 m intervals to a total distance of 1800 m. Samples
from Hengsha Island were taken on May 6, 2000 along a survey line that progressed
offshore from the most seaward retaining wall. A more compact sampling interval of
25 m was chosen due to the limited expanse of exposed tidal flat at this location
(Figure 10). The total distance covered by the Hengsha transect was 550 m.
Horizontal distance was measured using a tape measure and a compass was
utitized to maintain a relatively straight path between points. For Chongming Island,
the compas direction was 90° and for Hengsha Island it was 150". Sampling site co-
ordinates were recorded using a hand-held Garmin GPS- 12 Personal ?%avigatorQ'.
These CO-ordinates were subsequently converted to UTM grid CO-ordinates and
plotted on a spreadsheet to c o d m the actual transect path. Figure 13 indicates that
both the Chongming and Hengsha Island transects ran very close to the estimated
lines of site at average angles of 93S0and 149S0, respectively. Samples were
collected to a maximum depth of 5cm using a stainless steel trowel and placed in
ia'oeied, sterile plastic bags for storage (Figure 11). Weather conditions, vegetation
height and relative density were recorded at each site. pH Ievels of the sedirnent were
also measured in the field using a Kelway Soi1 pH ~ e t e r @ (Figure 12). Al1 samples
were placed in cold storage to presewe them for later analysis.
Objective #2: Determination of Sedirnent Parameters and Heavy Metal Concentrations
3.2.1 Drying
Samples were allowed to dry in batches of six at 40°C in an electric oven for a
minimum of 48 hours in coated metal pans to sirnulate air-drying (Figure 14). Once
dry, the sedirnent was ground into a fine powder using a ceramic rnortar and pestle
and sieved using a 2mm plastic sieve to remove any large organic matter such as
reeds or gras. The sieved material was then placed in sterilized plastic bags and
labeled for storage at room temperature.
Figure 9: View of Chongming Island tidal flats Iooking seaward fiom the retaining wall.
Figure 10: View of Hengsha Island tidal flats looking landward towards the retaining wall.
Figure 11: Sample collection on Chongrning Island tidal flats.
Figure 12: KeIway soi1 pH meter?
UTM Co-ordinate Transect for Chongming Island
UTM Co-ordinate Transect for Hengsha island 3465300
392450 392500 392550 392600 392650 392700 392750 392800
Easting Coordinates
Figure 13: UTM co-ordinates for Transects 1 (Chongming 1s.) and 2 (Hengsha 1s.).
3.2.2 Grain Size Anaiysis
Five miIligram sub-sarnpies from each site were sent to the State Key
Laboratory of Estuarine and Coastal Sediment Dynamics and Morphodynamics at
East China Norrnal University (ECNU) for grain size analysis using a Coulter Laser
~ranulometer@ (Coulter Counter). With the exception of C h o n m g samples 1-6, al1
of the samples were sent for analysis before being dned in the electric oven due to
project time constraints. Dilute solutions of each sub-sample were treated with an
anti-flocculent (sodium metaphosphate) and fed into the Coulter Counter by a lab
technicim. Al1 results were obtained and recorded for data analysis.
3.2.3 TOC Analysis
Five gram sub-samples fiom each site were delivered to the Academy of Soi1
Science at Nanjing University for totai organic carbon (TOC) quantification. Prior to
delivery, each sub-sample was air-dried and sieved using a 0.1 mm plastic sieve to
remove any large fragments of extraneous organic matter that could contaminate
results.
Figure 14: Oven-dried sarnple fiom Chongming Island.
3.2.4 Percent Moisture
Ln preparation for heavy metals analysis, percent moisture was calculated for
each oven-dried, sieved sample. Approximately 5 g of sedirnent from each sampling
site was pfaced in clean, dry, pre-weighed cmcibles. The combined weight of the
sedirnent and the crucible was then recorded Crucibles were placed in an eleciric
oven and heated to 10S°C until they had rcached constant weight. The crucible and
sediment were then re-weighed and the difference in weight recorded. Percent
moisture for each sample was subsequently calculated as follows:
3.2.5 Acid Digestion
In order to investigate the role of grain-size in heavy metal concentntions.
sediment samples were not pre-sieved to isolate the fine fiaction prior to analysis.
Instead, two sub-samples of approximately 0.5 g in rnass were removed fkom each
original sample and placed in acid-rinsed glass. Two sub-samples were required from
each site to ensure precision and replicability. Sub-samples were then prepared for
metal extraction in batches of ten by adding 5 mL of 70% Perchloric Acid standard
solution and 15 mL of 70% Nitric Acid standard solution to each beaker. Beakers
were covered with petri dishes and placed on a large heating plate under a fume hood
and brought to a boil. Once a boil had been reached, the heat was removed and the
beakers were allowed to stand overnight. A blank sample containing the standard
solutions but no sediment was also prepared for each batch to account for any
background Ievels of heavy metals that could affect results.
After cooling overnight, heat was once again applied to the beakers in order to
produce a light boil. The samples remained in this state until al1 of the liquid had
been removed. Sub-samples turned fkom an orangehrown color (representing the
Nitric Acid) to a lime green solution. This green solution emitted a white gas that
was caused by the removal of the remaining Perchlonc Acid. Once al1 of the liquid
had been removed, the beakers were allowed to cool. A solution of 10%
Hydrochloric Acid (HCI) was then used to transfer the digested paste fkom each
beaker into a 25 mL volumetric flask that had been rinsed with dilute acid. Srnall
aliquots of the acid were used to rime each beaker and the resulting mixture was
poured into the flasks. Once the transfer was complete, the rernaining volume in each
flask was filled with 10% HCI. The material in the flasks was then mixed. allowed to
settle and delivered to the Key Lab at ECNU for metals analysis.
3.2.6 Metal Concentrations
The quantification of sediment-bond heavy metais requires reliable and
sensitive analytical tools. Criteria upon which analytical rnethods are chosen include:
sensitivity and accuracy, speed and ease of operation, degree of automation. cost of
equiprnent, and reliability of results. Analysis of heavy met& in sediment requires
sensitivity liniits in the range of parts per billion and lower (Savory and Herman,
1999).
Historically, flame Atomic Absorption Spectroscopy ( U S ) has been the
method of choice for the measurement of trace met& in sedirnent for most
researchers (Savory and Herman, 1999). For many elements, detection limits for this
device lie within the range of 0.001 to 0.020 ppm and precision is in the range of one
to two percent. Cold-vapor analysis is also available with th is technique for rnercury
quantification. Mercury represents a special case as it is the only metallic element
that has a significant vapor pressure at arnbient temperatures (Skoog et al., 1998).
With the development of Inductively Coupled Plasma Atomic Emission
Spectroscopy (ICP-AES), however, analytical results gained a sensitivity of up to
1000 times better than flarne AAS (Savory and Herman, 1999). Furthemore, while
flame AAS ody ailows for the analysis of one metal at a time, ICP-AES offers the
opportunity for muiti-element analysis (Skoog et al., 1998). Both methods are
currently wideiy used in trace rnetd research.
For this study, heavy metal concentrations were detennined using an
Inductively Coupled Plasma Atomic Emission Spectrometer. Each sample was fed
into the ICP-AES directly fiom its volumetric flask by a laboratory technician at the
Key Lab. Sarnples are carried through the instnunent to a chernically inert argon
torch that constiiutes the plasma. Upon entering the plasma, beavy metal atoms enter
an excited state and emit a charactenstic wavelength of light. A photomultiplier
detects these wavelengths and their relative intensity is coiiverted into a concentration
by entering the dry weights of each sub-sarnple into the device (Skoog, et al., 1998).
thus eliminating the need for metal concentration calculations. Percent moisture
values are ofien used to adjust heavy metal concentrations according to the oven-
dried weight of the sub-sample but moisture values fiom the study samples were so
low that they were negligible in cornparison to the error associated with ICP-AES
metal quantification. As a result, there was no need to account for the percent
moisture of the sediment sub-samples.
3 3 Objective #3: Analyze Relations Between Metal Concentrations, Sediment Parameters and Sites AlongBetween Transects
The purpose of Objective 3 was to test the hypothesis that the spatial
distribution of heaw met& in surficiai tidal flat sediments is af5ected by position on
the tidal flat, sediment characteristics and proximity to the turbidity maximum.
3.3-1 StatisticaI Approach
The initial step in the interpietaion of the data was to prepare the database for
statistical analyses. The data sets for both Chongming and Hengsha Island sites were
composed of 16 variables including individual heavy metals, distance dong the tidai
f l a ~ average grain size, percent < 20 p, %TOC and pH. Since Al, Fe, and Mn
concentrations were large relative to the other metAs, their values were converted
fiom ppm to percentage for convenience. Metal concentrations were normalized to
the < 20 pm fkacticn in order to remove the grain-size effect (Acke rmw 1983). The
percent clay fraction was also considered for normalization but clay fractions
accounted for a maximum of 18% of any sample while the < 20 p fiaction
accounted for as much as 75% of the sediment and had a larger range.
Scatterplots were constnicted for raw and normalized metal concentrations.
Raw values were plotted against average grain-size, % TOC and pH while distance
measurements were plotted against average grain-size, pH, TOC and normdized
metais. The scatterplots allow for visual analysis of relations between variables.
Simple bivariate correlations were determined using Spearman's Rank Correlation.
Spearman's correlation coefficient (Spearman's rho) was chosen over other
correlation rneihods because it is a non-parametric test that does not assume normally
distributed data with equal variances (MendenhaII and Beaver. 1994). Rasmussen
(1 996) noted that metals cannot be assumed to follow a normal distribution over even
relatively short distances. In this study, Spearman's rho was caiculated to establish
the strength of correlation between raw metal levels and the < 20 pn fraction and
%TOC, and between normalized metals and distance dong each transect and %TOC.
C o n s i d e ~ g that the turbidity maximum is an area concentrated with fine-
grained sediment, an important aspect of this study was to assess the role of this
feature with respect to metal accumulation. While Spearman's Rank Correlation
analysis dlowed for the detection of significant changes in metal concentration within
each transect, the Mann-Whitney U-Test was used to identie significant differences
in metals between the two transects. The Mann-Whitney U-Test is a non-parametric
alternative to the t-test for comp,aring differences in population means (Mendenhall
and Beaver, 1994). This technique was applied to nonnalized metal concentrations as
well as average gain size, % < 20 pm fiaction and %TOC results. A significant
difference between variables fiom the Chongming and Hengsha Island data sets
would indicate that the two population relative frequency distributions were shifted
with respect to their relative locations. This would, in turn, isolate proximity to the
turbidity maximum as a significant control on the distribution of heavy metals within
surficial sediments of the Yangtze River Es- tidal flats.
Principal Components Analysis (PCA) was applied to the original data set.
PCA is a method of data reduction that takes a large set of interrelated variabIes and
uses them to construct a srnall number of independent components or surrogate
variables. These components are ordered such that the first few components identifi
the rnajority of the variance present in al1 of the original variables (Joliffe, 1986).
While some Iiterature considers PCA as a special method of Factor Analysis (Carey,
1969), the two methods are distinct techniques (Joliffe, 1986). While PCA assumes a
closed system in which al1 variance is accounted for by the variables themselves,
Factor Analysis d!ows for sorne degree of external error. In rnost cases, however, the
two methods usually yield similar results (Shaw and Wheeler, 1985). For the
purposes of this research, PCA was chosen to detect relations between heavy metal
concentrations and sediment characteristics. This method was chosen because it
provides uncorrelated and statistically independent variables that are ranked in
descendhg order of ability to interpret variance (Carey, 1969). It was also employed
by Zwolsman. et al. (1996) to study cootrols on sediment-associated metals in the
estuarine environment.
The output values of PCA are referred to as eigenvaiues or component
loadings. These values represent the correlation between each original variable and
the new component. A perfect correlation between a variable and a component is
represented by an eigenvalue of +/- 1. The ultimate goal of PCA is to maximize the
loading value on one component while minimizing loadings on the remaining
components for each variable. In situations where this is not possible, component
rotation can be used to better isolate ctusters of variables. Two methods of data
rotation are avaiiable to the researcher. Orthogonal rotation rotates the cornponent
axes around the origin while maintaining a 90' angle between each a i s . Oblique
rotation rotates the component axes around the origin but does not preserve a 90'
angie between each axis. Both methods have the advantage of isolating groups of
variables without altering the pattern or structure of the data set. The ideal rotation
has been attained when most eigenvalues lie close to an axis and a minimal number of
eigenvaiues lie at some distance from the axes (Shaw and Wheeler, 1985).
For this study, both sets of raw data were subjected to PCA. A decision was
made to elirninate the pH data from the statistical analysis because it was uncertain
whether the instrument readings could be considered accurate. Data was analyzed
using SPSS@ software and results were plotted in component space to visualize
component loadings. Although an orthogonal rotation technique (varimax rotation)
was applied to the da- no improvement in the final results was noticeable. Rotation
was, therefore, not utilized in the statistical analysis of results.
3.2 Objective #4: Cornparison of Heavy Meta) Concentrations with National Standards for Sediment Quality and Global Estuaries
In order to establish the degree of sedirnent contamination within the two
sampbg transects, raw heavy metal concentrations were compared to national
standards for soi1 environmental quality (Table 1) and graded accordingly. When
comparing levels of As, Cu and Cr with the categories in Table 1, paddy soi1 and
familand were chosen to best represent the tidal flat environment since the study axa
is often inundated and, once reclaimed, will most likely be used for f m i n g purposes.
Results fiom this study were then compared to metal levels observed in other studies
performed in the Yangtze Estuary dong with other estuaries around the World (Table
12). A cornparison of this nature would place the research findings within a local and
global context, thus detennining the relative degree of pollution of the Yangtze River
Delta.
Chapter Four: Results
This chapter presents data on sediment charactenstics and heavy metal
concentrations recorded along each transect in the Yangtze River Estuary. Rau- data
from both the field and laboratory portions of the study have been compiied into
tabular and graphicd form. In the course of storing the Hengsha samples for
laboratory analysis, seven labels were lost (HS-1, HS-2, HS-8.5, HS-9, HS-10, HS-
I I , HS-11.5) and these unknown specimens could not be used in the study. This
chapter provides a description of the ravi data followed by a discussion of the
statistical trends present in the data.
4.1 Variations in Sediment Parameters and Heavy Metal Concentrations Along Tidal mats
Figure 15 presents grain size. TOC and pH data for surficial sediments along
the Chongming and Hengsha Island sarnpling transects, respectively (Appendix A).
Transect 1 on Chongming Island was positioned on a tidal flat that graded seaward
from a relatively dense Scirpus marsh, to a sparse marsh and finally to bare mud flat.
This area was lacking in a Phragmitis zone due to constant reclamation in the area.
Ln fact, the most recent set of retaining walls at this site was constructed only two
years ago. Transect 2, on Hengsha Island, was situated on a tidal flat that graded
seaward h m mature, dense reeds (Phragmi~is) to Scirpus marsh to relatively bare
flat. This last segment, however, was compnsed of a noticably Iarger sedirnent size
and had a definite sandy texture. Both sites had well-developed tidal creek systems
across their expanse.
Average grain size data for Transect 1 indicates a slight increase in sedirnent
diameter with distance seaward dong the flat. In general, grain size is relatively
Distance versus %TOC along Transects 1 and 2. 4.0
0.0 ! -
3
O 250 50 7M 1000 1250 1500 1750 2ûûû
Distana along trameçt (m)
Distance versais average grain diameter along Transectr 1 and 2
O 4 O 250 SM 750 Io00 lm 1500 1T50 Mo0
Distance along transeci (m)
Distance versus pH along Trans- 1 and 2.
75 1
4.0 1 0 250 MO 750 1000 1250 1MO 1750 2000
Distance almg transect (m)
Disiance versus percent QO mlcromden along Transects 1 and 2
O 4 1
O 250 500 750 Io00 1250 1500 1750 2000
Distance along b a n d (m)
I 1
Figure 15: Graphs cornparhg sediment characteristics between Transects 1 (Chongming Island) and 2 (Hengsha Island).
constant and covers a m o w range of 18 to 35 p. In contrast. the Hengsha transect
shows greater variability and range in grain diameter. Sediment size is, for the most
part, larger than in Transect 1 (ranging fiom 1 7 to 1 60 pm) and experiences a rnarked
increase at a distance of 475 meters. The < 20 pm fraction mirrors the mean grain
size results. T-tansect 1 shows an overall decrease in the fiaction with increasing
distance. Transect 2 also portrays this pattern, but with a greater degree of variability
and a significant decline at 475 meters.
Total organic carbon content for d l of the tidal flat specimens was minimal,
with a maximum value of approximately 3.5%. This peak was found at the beginning
of Transect 2, which had higher TOC values than Transect 1 up to around 150 meters.
Subsequent to this point. Transect 2 TOC levels were lower than those found on
Chongming Island. Lasdy. pH values for sampling sites along Chongming Island did
not show a significant increase or decrease with distance, although a slight dip did
occur at 100 meters. Hengsha pH vaiues showed greater variability but no visible
pattern besides a marked decrease at the end of the transect
Figure 16 presents raw heavy metal concentrations for Transect 1 and Figure
17 contains concentrations for Transect 2 (Appendix B). Concentrations for Al, Fe,
and Mg were converted fiom parts-per-million to percent for ease of use but represent
the same information. Ln general, al1 of the metals display a decrease in concentration
with distance seaward along the tidal flats. On Chongming Island, the Fe profile
exhibits a sharp peak at 1200 meters that is distinct fiom the rest of the
concentrations. Zinc, Cu, Cdr Al, As, Pb and, to a lesser extent, Mg and Ni
Chromlum rr. ~ t s a n c e Along ndjl Flat (Chongmlng I r )
Znc v s Dlstance Along Tldal Fla! (Chongmlng I r )
Copper rs. Dlstanca Along TM& nR (Chongmlng I r )
500 lm lm 2000
D l ~ . m c Along F l d (m)
4a O 500 la00 lm zoo0
Ohancc Along Fld (m)
Magneslum v s Dl8tanct Along Tldol Ra (Chongmlng 16.)
O 5(r] tooo 1500 ZOO
Distance Along Fla (m)
Nlckcl rs. Dlstance Along Tldal Flat (Chongmlng . l a ) - .
500 lm 15al MOa Distance Along FIat (m)
Figure 16: Raw heavy metal concentrations on Transect 1 (Chongming Island).
Alurninum vs. Distance Along Tldal Flmt (Chongming h)
r
O rac tra, sa, 12a: l s o iarr D i n o m Along Fht (m)
Lmid vs. Distince Along TÏdd FI.1 (Chongming h)
28 ,
Arsenic K Distance Along Yidal FIat (Chongrning k)
11 -,
--- O 5w lm 1 9 0 tOOO
Distance Alang Flat (m)
Cadmium vs. D i S i n a Along Tidil R i t (Chongming k)
Dntincc Along Flat (m)
Chmmium *r Oistance Along TiiI Fht (Herqsha k)
Pnc m. Dl- Along Tldal Rd (Hengsha 1%)
lron ~ 5 . Disîanca Along T i a l Fht ( H e w h a k)
040;
0.10 1 O 1 0 0 2 0 0 3 0 0 4 m 500m
Di- AIong Fia! (m)
Copper vz Distance Along lïdal Flat (Hengsha h)
50 ;
Y agrœsiun K Didincs Aiong Tidal Fid (Hengsha k)
006 4
O 100 200 300 400 500 600
Distance Along Flat (m)
Nlckel vs. Mdance Abng Tldal Flat (Hcngsha !S.)
10 j O 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 m
Distance Aimg Flat (ml
Figure 17: Raw heavy metal concentrations on Transect 2 (Hengsha Island).
Aîurnlnum vr Dlstancs Along ndal FI* (Hengsha 1%)
0.71 - 1
D i m n c s Along Rit (m)
Lead vs. Dtstance Along Tidal Fiat (Henpsha 1s)
50 -
O
O f O O X K ) J 0 0 4 m S 0 6 0 0 0 1 i ~ a c c long mat (m)
Cadmium vs. Distance Along Tidal Flat (Hergsha 1s.)
Manganse e. OIsgnce A l ~ n q Tidal Flat (Hengsha is.)
- I / Y
mit vs. Distana Nang Ttdal Flat (Herigsha 1s.)
4 '
O 1 0 0 2 M J 0 0 a O O m 6 0 0
Oistance Along Flat (ml
al1 show slight dips in concentration at the second sampling site and Zn, Cu, NiT As.
Mn and Al d l dispIay a visible decrease at the 700' 1500 and 1800 meter marks.
With respect to Transect 2, metals generally showed a minimum concentration at the
475 meter mark? with the steepest decline in concentration usually occurring over the
initial 100 meters for most of the contarninants. While the majority of metals display
a decrease in concentration with increasing distance, the Pb, As and Cd data sets are
extremely variable, making it difficult to distinguish pattern.
4.2 Relations Between Heavy Meta1 Concentrations and Sediment Characteristics, Position on the Tidal Flat and Proximity to the Turbidity Maximum
Results of the statistical analyses are presented in three sections. The first
section presents the results of scatterplot (Figures 15-17) and Spearman's Rank
Correlation analyses (Tables 2-5) for Transects 1 and 2. The second section contains
results from the Mann-Whitney U-Test (Tables 6 and 7) for difference of means. The
third section presents the output fiom the Principal Component Andysis conducted
on Yangtze River Estuary data.
4.2.1 Scatterplots and Spearmans Rank Correlations
Appendix C provides scatterplois for the raw and normalized data from
Transect 1 and Appendix D provides scatterplots for the raw and normaiized data
from Transect 2. On Chongming Island, al1 metals dispIay a decrease in
concentration with distance and average grain size. When pIotted against TOC
content, metal levels increase with increasing %TOC. In contrast. the scatterplots of
pH levels versus heavy metal concentrations did not dispIay any clear relationships.
On Chongming Island, normaiized metal concentrations are variable and do
not exhibit a trend in rnetal concentration with distance dong the transect. Metals,
however, do display a slight increase in concentration with average grain dimeter.
Of these increases. Cd, Pb, As and Cu show the weakest relationships. Upon pfotting
the organic carbon content of the sediment against normalized metal levels, the
previously noted increase with increasing TOC is no longer apparent. The graphs
also indicate a higher degree of variance within the data. Lastly. scatterplots of pH
versus the normaiized data did not show any visible trends.
On Hengsha Island, the normalized metal concentrations d l indicate an
increase over the 1 s t two sarnpling sites. Prior to this section of the transect, no
visible increase or decrease in concentration is evident. Similar to the results fiom
Transect 1, this data set also displays an increase in met& with average grain size
dthough the large increase in sediment diameter over the last several sampling
locations causes a gap in the plot. Scatterplots of metais versus %TOC are highly
variable with the highest rnetal levels occurring at the lowest organic matter contents.
pH data. meanwhile, do not show any obvious relationships.
Tables 2 and 3 provide Spearman's Rank correlation values for raw and
nomdized (by % < 20 prn) heavy metd concentrations fiom Chongrning and
Hengsha Islands. Before performing correlation analyses on the Fe data, the outlying
point on Chongming Island identified in the previous section was removed and
replaced with a new value by taking the mean of the two surrounding points.
Significant correlation coefficients with the < 20 p fiaction confirm the grain-size
effect for al1 of the metals except Cr and Mg in Transect 1 and Mg, As and Cd in
Transect 2- Upon normalization (by % < 20 pn), correlation analyses do not exhï'bit
statistically significant relationships between any of the metals and distance along
either transect.
Table 2: Spearrnan's correlation coefficient for raw and normalized heavy metal concentrations almg Transect 1.
Table 3: Spearman's correlation coefficient for raw and normalized heavy metal concentrations along Transect 2.
r . - . . - , . . 7 .: z - . - . - - . . - , . . . . . . . .
Spearman's Rho (metal vs. -= 20pm)
r . b w D m . ', - , - . . - . .
In order to isolate whether heavy metals were correlated to the amount of
Al
.756
*
organic matter present in the sediment, independent of grain-size, Spearman's rho was
Cr
-228
- - .: . r . . N o i m d k & ï D ~ ~ . . - . . - . - , . - . - . . - - ,. . . , - .L . . . -
Speaman's Rho (metal vs.
-=mm
Z n
;.$$O ., - 1 . , .-
<. .. 1
" la..
, - . r - . - - 3 ,. A
' . - -- .. . - . ' l
''<sig~fi&& &;OS. hl (2-taiied)
Cd
.j96
Fe
.:568'. ". . - -
. &
. . L, . .. -
Mn
,484
Cr
.661
NormilizedDlitn . . . . "
- . _
* * Signifhni a* the .OZ level(2-tuilen)
Spearman's Rho (metal vs. distance)
Fe
' -577 . . . . .. ,
f - - . . Ir
Pb
.6O.f
Z n
.354
Mn
.261
Mg
-472
Ni
.742
As
7
Z n
,641
As
.O30
Cr
-35 I
Pb
-.ZOO
Ni
.630
C u
.752
Mn
-215 Spearman's Rho (metal vs. distance)
Cd
.O42
Fe
-153
Mg
.352
C r
.O87
M g
-35 1
Fe
,087
C u
-681
C u
-.O30
AI
.675
Cd
--- Mg
,467
Zn
-386
Pb
-380
As
-493
As
-473
Ni
-339
Cd
.O57
Mn
- . -583 -
. , O --- " .
Cu
-.391
Al
-.334
Pb
- 508
- .
Ni
-410
Al
-.200
calculated for raw and noraalized metais versus %TOC. As Tables 4 and 5 indicate,
almost all of the metals correlate with %TOC at the 0.01 significance level prior to
normalizat ion. M e r norrnalization, however, only the Transect 1 Al data exhibits a
statistically signiftcant relationship with TOC.
Table 4: Speamian' s correlation coefficient for raw and normdized heavy metal concentrations versus %TOC for Transect 1.
* 4 S~W& at ,th& -05: 1&@(2-tail@) 1 ** Signijkznt at the -02 level(2-tuiled)
. . . ". . Dm.. . - _ A - ..- , , , . - * . " . I . - .. - . . r 2,
- . ' _
Table 5: Spearman's correlation coefficient for raw and n o d i z e d heavy metal concentrations versus %TOC for Transect 2,
As
.883
Spearman's Rh0 (metal vs. OhTOC)
-O*. :- . . ,. . . . . . . : . . . - - . . - - .
M g
.878
Cd
512
~~h-- D*': :. ' - . . . .,. . 5 . .
. - . - , - . . . . . . . - . - - - . : - " - . - - . .-
7 - . ' 1 .
Spearman's Rh0 (metal vs. %TOC)
C u
-920
Z n
.9S8
Cr
-706
Cr
- -832-
Fe
.763
As
-105
Spearman's Rh0 (metalvs.
Fe
: -847 , - -
. " . . , , - . . % Norm.iPiaDif.,;,. - b - ..A . . . u . - ' ,.- ; . . ? . - . - :.. . . _? . . . . . - - > . - ' , . -
Cd
.O44 %TOC)
Cr
-.227
Ni
-933
1
Fe
-001
Z n
=635 - - . . ..
Ni
: .80q -
Spearrnan's Rh0 (metalvs. Yo TOC)
Mn
-956
Al
-901
Mg
-.135
Z n
-.la3
Mn
-815 -
Ai
:. 871
Cr
-.O99
Pb
.826
Mg
-705 . . + - j
Cd
- Fe
-.O44
Cu
-.391
Pb
-200
Cu
... 835 .
Z n
-.324
As
-509
Ni
-.193
Cd
.419
M g
-,458
Mn
.158
Al
-464
Pb
.246
Cu
.463
Ni
-.410
Pb
-.315
As
-.470
Ai
.147
Mn
-.228
4.2.2 Mann-Whitney IJ-Test Analyses
Tables 6 and 7 summarize the results of the Mann-Whitney U-Test comparing
the sediment parameter and normalized metal population means fiom the Chongming
and Hengsha I s h d data sets. Tables 8 and 9 indicate that average grain size, Al, Cr
and Cd values fiom the Hengsha Island data set are signiticantly different and higher
than those on Chongming Island at the 95% level. If the confidence levei for the
analysis was expanded fiom 95% to 90%, %TOC and Fe would also be considered
significant ly different between the two transect S.
Table 6: Mann- Whitney U-Test comparing sediment parameters between Transects 1 and 2.
Table 7: Mann- Whit ney U-Test comparing heavy metal concentrations fi0 m Transects 1 and 2.
4.2.3 Principal Component Analyses (PCA)
The pH data was excluded from the PCA due to the uncertain reliability of the
field results. Furthemore, the outlying Fe data point in the Transect I data set was
also repIaced with the mean of the two closest neighboring points to ensure that this
anomaly did not affect the output fiam the test. Raw data generated fiom PCA
calculations are provided in Table 8. Table 9 provides the component loadings
calculated fkom Principal Component Anaiysis using SPSS" software. Statistical
variables for both transects consisted of raw heavy metal concentrations. distance
dong the transect, %TOC and average grain size. Figures 18 and 19 are plots of the
eigenvalues against the principal axes (components 1 and 2).
As indicated by Table 9 and Figure 18, the first component groups al1 of the
variables except Cr and Cd in Transect 1 and Cd in Transect 2. Within this grouping,
however. distance and grain size variables hold negative eigenvalues while the
remaining variables have positive eigenvaiues. Component 1 accounts for more than
70% of the variance arnong metal concentrations and sedirnent parameters for the
Chongming and Hengsha Island data sets while cornponent 2 accounts for
approximately 10% of the variance. Transect 1 shows relatively weaker relationships
between grain size with Component 1 and, Cr and Cd with Component 2, as indicated
by the similar eigenvalues for both axes. Transect 2 (Figure 19) has weaker
component loadings for Pb and As with Component 1 but these metals still show
good differentiation in eigenvalues between each a i s .
Table 8: Principal Components Analysis loadings.
Transect 1 : Chongming Island I
Variable Cornpanent
Transect 2: Hengsha Island I
TOC AS Mn Fe Pb
Distance Mg
Grain Size Cd Cr
Variable 1 Component
0.952 0.950 0-935 0.89 1 0.853 -0.792 0.784 -0.640 0.583 0.565
O. 188 -0.037 0.294
O. 1 O0 -0.158 0.0 13 0.35 1 0.618 -0.642 0.67 1
Zn TOC
Distance AI
Grain Size
0.899 0.898 -0.895 0.874 -0.785
0.058 -0.151 O. 168 -0.182 0.33 1
Component 1 1
Table 9: Principal Components Analysis summary for Transects 1 and 2.
Component 2 1 Component 1
Transect 1 Transect 2
Distance TOC
Grain Size Al Fe Mg Zn Cu Ni Mn Pb As Cr
Distance TOC
Grain Size Ai Fe Mg Zn Cu Ni Mn Pb
As % of total variance:
73.68 % of total variance: - L I
Component Plot
grain
% of total variance: 11.02
Cornponent 1
% of total variance: 7135
Figure 18: Plot of component loadings for Transect 1.
Component Plot
' - O 0
-51
grain
istance
-1 .O -.5 1
Component 1
Figure 19: Plot of component loadings for Transect 2.
4.3 Cornparison of Heavy Metal Concentrations with National Standards for Sediment Quality and with Global Estuaries
According to the National Standards for Soi1 Environmental Quality (Table
l), the ievels of heavy met& within tidal flat sediments of the Yangtze Estuary
(Table 10) contain metal concentrations consistent with natural background levels,
that is Grade A quality. Along Transect 1, Cr, Zn, Cu,Ni, Pb and As level al1 fa11
within the Grade A category and Cd falls between Grades A and B. Along Transect
2, Cr, Zn, Cu, Ni, Pb and As are consistent with concentrations in Grade A soils.
Cadmium concentrations on Hengsha Island range between those found in Grades B
and C soil.
Table 10 compares the heavy metal concentrations fkom this study with those
recorded elsewhere in the Yangtze Estuary as -ive11 as various other estuaries
throughout the World. Results from this study are consistently lower than metal
concentrations measured by Zhang (1999) and Zhang, et al. (1994) in suspended
sediments of the Yangtze Estuary. Alurninum, Cr, Fe and Mg levels in this study al1
fa11 well below those reported in other estuaries and Mn concentrations only approach
those fiom the Orinoco River. Zinc concentrations are comparable to concentrations
noted by Wright and Mason (1999). Copper and Pb ranges are similar to levels
documented in the Scheldt (intertidal flat) and Lena Estuaries and, to a lesser extent,
the Mississippi. Nickel levels approximate concentrations in Orinoco, Scheldt
(intertidal flat) and Lena Estuaries. With the exception of Cd, al1 metal
concentrations measured in this snidy are lower than those from other estuaries.
Chapter Five: Discussion
This chapter presents a discussion of the data trends and statistical results
provided in Chapter 4. The arguments are organized according to research objectives
three and four. The first section. therefore. focuses on analyzing the scatterplot and
statisticai results for both the raw and nomalized heaw metal concentrations and
interpreting the implications of these results with respect to controls on heavy metal
behavior in the Yangtze River Estuary, China. This is followed by a cornparison
between the metal Ievels recorded in this study with national standards for soi1
environmental quality as well as those documented in other studies of the Yan,atze
Estuary and estuaries around the globe.
5.1 Relations Between Heavy Metal Concentrations and Sediment Parameters, Position on the Tidal Flat and Proximity to the Turbidity Maximum
In general. the Hengsha Island tidal flats display a larger average grain size
than Chongming Island, peaking at a value of 160.2 p m compared to 37.3 p m on
Transect 1. This confirms Yang's (1 999c) observation of a progression from clayey-
silt to sandy-silt along the Hengsha flats while Chongming is primely clayey-silt.
The peak in %TOC and fine sedirnent along the initial 100 m of Transect 2 is most
likely due to die dense Phragmitis u s ~ l i s marsh situated along the Hengsha Island
seawalls. It is also possible that the rising tides wash organic matter frorn the lower
flats and deposit them in this upper marsh section. The subsequent decrease in TOC
and increase in average gain diameter beyond this point contribute to the decline in
metal concentration over the remaiMg stretch of flats. This initial peak near shore is
also seen, to a lesser extent, in the % < 20 pm fraction data. Similar fmdings were
noted by Zhang (in press) and are a testament to the current-attenuation and sedirnent-
trapping ability of the reeds during their sporadic inundation. OveralI, however. the
organic content of the sediment dong both transects is very low. This observation is
supported by the findings of Zhang (1999). In fact, the range in %TOC recorded on
the Chongming Island transect matches aimost exactly the results of Zhang (1999) of
051 .5% total organic carbon. Finally, decreases in Zn, Cu. Ni, As, Mn and Al at
700 m, 1200 m and 1700 m dong Transect 1 do not correspond to increases in grain
size but are the result of lower organic content.
The interdependent nature of grain size with TOC and raw metal
concentrations makes it difficult to interpret whether or not trends actually exist with
distance along each transect. Consequently, the nomalized scatterplots should
eliminate the possibility of these interdependencies and allow for a bivariate analysis
of results that reveal relationships between independent variables. Normdization of
the Transect 1 data resulted in no obvious trends in heavy metals with distance along
either transect while the Hengsha Island normdized metal concentrations peaked
sornewhat within the last 150 rn of the transect. While it is tempting to interpret these
results as an indication of the turbidity maximum's abiIity to trap metals, Daskalakis
and O'Connor (1995) note that high nomalized metal concentration should not be
accepted as evidence of contamination before carefid examination of the values that
comprise the ratio. This is due to the sensitivity of the normaiized value to the
denominator of the ratio. However. metal concentrations at the Iast two sarnpling
sites are much lower than concentrations over the remainder of the transect. This
would suggest that the elevated concentrations being witnessed in the scatterplots are
hkely a function of the extreme increase in average grah diameter. not an extreme
increase in heaw rnetd concentrations.
Spearman's Rank Correlation results confinned the lack of any significant
increase in sedirnent-associated heavy metal concentrations with distance seaward
along the tidai flats and, consequently, proxirnity to the turbidity maximum within
each transect for both data sets. The same was true for sediment-associated total
organic carbon levels since no significant relationships could be established once
normalization of the raw data had been performed. Furthemore, for the most part.
the Mann-Wtney U-Test result did not identifi a significant correlation between
proxirnity to the turbidity maximum and elevated metal levels between transects.
This irnplies that correlation in the raw data was merely the product of a strong
dependency between metals and organic matter content with the fine sediment
fraction.
The Principal Cornponents Analysis (PCA) results, in turn. echoed the
findings of the Spearrnan's Correlation analysis. in both transects. the primary
component, which refiects the grain-size effect. contains distance. grain diarneter,
TOC and the majority of the heavy metais. This component accounts for more than
70% of the overall variance. The second component contains the rernaining rnetals.
including Cd. This confirms the weak Spearman's correlation between Cd and grain-
size and suggests that cadmium's chemical properties are distinct fiorn other heavy
xnetals. Zwolsman, el al. (1996) reported similar fmdings in their study of the Sheldt
E s t u q . While PCA isolated Cr under Component 2 for C h o n m g Island, the
strength of the relationship is not strong enough to necessarily be considered
significant. The PCA results for both transects? therefore, are essentially identical and
lead to the conclusion that grain-size is the prirnary controIling factor in the
distribution and behavior of heavy metals in the Yangtze Estuary. China,
Magnesium was the o d y raw metal that did not indicate a significant
relationship with the < 20 pm fraction along both transects under the Spearman's
correlation technique. Furthemore. the element did not exhibit a change in
correlation afier normalization. This conse~ative behavior indicates that Mg levels
are primarily lithogenic in origin and that any anthropogenic inputs of this element
are insignificant in comparison to nanirally occurring concentrations. The Mann-
Whitney U-Test did identifi statistically significant differences in the frequencies of
average grain diameter, Al, Cr and Cd. The larger average grain-size of Transect 2
simply adds fiirther support to Yang's (1999~) observations. Aluminum
concentrations are of lithogenic origin and most likely reflect the difference in
sediment size distribution between the two islands. Finally. the elevated levels of Cr
and Cd on Hengsha Island could have resulted fkom a strong affinity for aluminurn,
which may explain cadmium's anomalous behavior with repect to other metals and
norrnalization. The possibility remains, however, that these findings are simply due
to the relatively low concentrations of Cd and Cr in the estuary.
5.2 Cornparison of Heavy Metal Concentrations with National Standards for Sediment Quality and with Global Estuaries
With the exception of Cd, the levels of heavy metals within tidal flat
sediments of the Yangtze Estuary are prharily Grade A in character. This apparent
high quality of sediment along the tidal flats does not correspond to the large arnount
of contaminating effluent that is known to be entering the study site. Two possible
explanations exist for this discrepancy between pollution inputs and level of
contamination: dilution of heaw metals by riverine suspended sedirnents or the
mobilization and subsequent transport of metals farther seaward along the continental
shelf. Whïle approximately 50% of estuarine sedirnent does escape and become
deposited on the continental shelf (Zhang, et al., in press), the lack of rnetal
contamination along the Yangtze Estuary tidal flats is likely a function of "self-
purification" by the tremendous water and sediment load of the Yangtze River. This
finding cofirms the research performed by Zhang, et ai. (1990), Zhang (1 999) and
Chen. et al. fin press) and supports their conclusion that heavy rnetal contamination in
the Yangtze E s t u q is dificuit to detect due to the dilution of metals by riverine
sediment.
When results fiorn this study were compared to metal leveis observed in two
other studies of the Yangtze Estuary, heavy metal concentrations in the tidal flat
sediments were found to be lower than those recorded in previous work. This
discrepancy can be explained by a number of factors. Firstly. the metal levels
recorded by Zhang, et al. (1994) and Zhang (1 999) were attained from suspended
sediments that are finer than those of the tidal flats and are likely to adsorb more
contaminants. They are also subject to a variety of different environmental
conditions than tidal flat sediments. Where tidd flats are intermittentiy exposed to
the atxnosphere and are effected by colonizing salt marsh species, suspended
sediments are completely inundated and experience the various adsorption and
depositional processes associated with estuarine mixing. Furthemore, the temporal
variability in riverine and tidal flow conditions as well as the spatial and temporal
variability inherent to sediment-associated metal distributions within this dynamic
system are Iikely to produce inconsistencies between studies.
Yangtze Es* tidal flat sediments have Al, Cr, Fe and Mg levels below
those reported in other estuaries. The lower Al. Fe and Mg concentrations primarily
reflect differences in the Iithogenic composition between the source materials of
sediment in the different locations, rather than lower contamination Zevels. Zinc
concentrations fa11 near those recorded in the Orwell Estuary which is considered by
Wright and Mason (1999) tc be of poor water quality due to industrial and sewage
inputs. While Cu. Ni and Pb levels match closely those of Lena Estuary, a relatively
pristine river system, they also approach rneasurements fiom Scheldt (intertidal flat)
Estuary, a highly industriaiized and populated environment. It is important to note.
however, that the Scheldt intertidal flat metal concentrations are substantially lower
than those found in submerged samples. Thus, the distinction between tidal flat
versus submerged bottom sediment is a meaningful one.
While concentrations of Cd were minimal relative to the presence of other
heavy metals detected in the Yangtze Estuary, îhey approxirnate those recorded in
heaviiy polluted estuaries h m North America, Europe and the rest of the World.
The high toxicity of Cd and its ability to accumulate aIong the food chah (Thornton,
1995), poses a significant threat to the people of Shanghai District. Concentrations
should, therefore, be closely monitored, not only in the estuarine sediment but also in
the vegetation and fish yields that are being harvested fiom the area. Finaily, Cr
levels are considerably lower in the Yangtze intertidal sediment than in other study
locations. This occurrence is most likely the result of a difference in industriai
practices between the sites. As China continues to grow and develop. however. it can
be expected that these concentrations will also increase.
Chapter Six: Summary and Conclusions
Heavy metals are produced boom a variety of natural and anthropogenic
sources. These metals enter estuaries fiom points dong the entire drainage basin and
within the estuary itself. Once ioside an estuarine system, complex interactions
amongst river discharge, saltwater intrusions. local currents, effiuent point sources.
pH. temperature, oxygen content and sediment re-suspension processes c m affect the
degree of contamination of surficial sediments. The accumulation of metals in
estuarine sediments holds significant environmental implications for local
cornmunities as well as for marine water quaiity.
The watershed of the Yangtze (Changjiang) River, China is one of the most
densely populated regions in the World. Rapid reclarnation of tidal flat zones for
agricultural and housing purposes within the District of Shanghai have raised
concems regarding the impact of contaminated sediments on the local population.
Understanding the behavior of heavy metals and establishing patterns of
contamination would allow for the prediction of areas within the Estuary that are at
high nsk to pollution. The purpose of this research was to determine the patterns and
controls of onshore-offshore variations in heavy metal concentrations within surfrcial
sediments of the Yangtze River Estuary tidal flats.
While raw heavy metal concentrations were shown to increase with distance
seaward. Spearman's Rank correlation analysis did not exhibit statistically significant
reiations between normalized metal concentrations and distance or organic matter
content within transects. With the exception of average grain diameter, Al, Cr and
Cd, the Mann-Whitney U-Test results found no significant difference between
Chongming and Hengsha tidal flats. This irnplies that proximity to the turbidity
maximum does not play an important role in controlling the occurrence of heavy
met& within surficial tidal flat sediments of the Yangtze River Estuaq.
The Spearman's Rank, Mainn-Wtney and Principal Component analyses dl
established grain-size as the dominant control on the spatial distribution of metals and
organic rnatter in the study site. Cadmium was the only heavy metd that did not
exhibit a strong relûtion with grain-size, most likely because of the its unique
chernical attributes and anomalous behaviour during normalization. Consequently.
any increase in heavy metal concentrations with distance landward on the tidal flats is
a product of the depositional pattern of nsing tidal waters, where advancing waters
experience attenuation and a decrease in sediment load with thek advance to shore.
This conclusion is supported by a variety of studies in the study area (Zhang et al.. in
press; Zhang, ei al.. 1 990; Zhang, 1 999 and Chen, ei al., in press).
While it is clear that a tremendous arnount of heavy metals, and pollutants in
general, are constantly being discharged into the Estuary. there is no evidence of
contamination on the Yangtze tidal flats. In fact, with the omission of Cd. al1 heavy
metals display concentrations that are consistent with natural background Ievels
according to China's national standards for environmental soi1 quality. Cornparison of
these results with other estuarine studies likens the sediment quality of the Yangtze
Estuary with relatively pnstine environments. The lack of evidence in support of
sediment contamination fiom ciomestic and industrial discharge is most likely the
product of dilution by high fluvial sediment loads fiom the Yangtze River. This
discrepancy, along with that between metal concentrations in intertidai sediment
versus suspended or bonom sedirnent is an ineiguing area of focus for future
research. Eventually, the "self-purification" dilution phenomena wili not be abIe to
compensate for the tremendous level of development that is, no doubt. fated for
China. While it is taking steps towards regulating pollution in the Yangtze
watershed. the govenunent of China should continue studies such as this to help
monitor. preserve and irnprove sediment and water quality in the Yangtze Estuary.
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Appendix A
Table A-1: Sediment characteristics along the Chongming Island transect.
Sample Location
CH- 1 CH-2 CH-3 CH-4 CH-5 CH-6 CH-7 CH-8 CH-9
CH- 1 O CH-I 1 CH- 12 CH- 13 CH- 14 CH- 1 5 CH-16 CH- I 7 CM- 18 CH- 19
Percent 20 pm
Distance Along Flat (ml
O 1 O0 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1 700 1800
Percent TOC
Average Grain
Diameter ( pm) 19.24 3 1 .O2 24.80 18.29 22.63 20.2 1 18.49 23.10 24.36 26.71 24.92 23.42 27.82 24.36 26.2 1 32.55 3 5 -47 21.36 37.3 1
Appendix A (cont'd)
Table A-2: Sediment characteristics along the Hengsha Island transect.
Sample Location
HS- 1.5 HS-2.5 HS-3 .O HS-3.5 HS-4.0 HS-4.5 HS-5.0 HS-5.5 HS-6.0 HS-6.5 HS-7.0 HS-7.5 HS-8.0 HS-9.5
HS- 10.5 HS- 12
Distance Along Flat (m) 25 75 t O0 125 f 50 175 200 225 250 275 300 325 350 425 475 550
Average Grain
Diameter (pm) 18-08 3 7.43 29.34 37.64 44.16 16.8 1 19.86 24.35 32.03 25.94 37.59 30.64 25 .O0 32.77 1 60.20 152.50
Percent < 20 pm
Percent TOC
O O CC) T
Sample Location
hs-1.5 hs-2.5 hs-3
hs-3.5 hs-4
hs-4.5 hs-5
hs-5.5 hs-6
hs-6.5 hs-7
hs-7.5 hs-8
hs-9.5 hs-10.5 hs-12
Distance an Tidal Flat (m)
25 75 1 O0 125 1 50 175 200 225 250 275 300 325 350 425 475 550
Appendix B Heavy Metal Concentrations Along Transect 2 (Hengsha Island)
Appendix C (cont'd)
%TOC vs. Alurninum (Chongrning Ir.)
%TOC vs. Manganese (Chongming 1%)
%TOC vs. Cadmium (Chongming 1s.) I
%TOC vs. Lcld (Chongming 1s.) 28
%TOC vs. Arsenic (Chongming 1s.)
%TOC vs. Chmmlum Concentration (Chongrning 1s.) l
a.
Chromiurn vs. Avermge Grain Size (Chongrning k) , . Zinc K Avemge Grain Size (Chongming k) . -. - - - - .- - - : !
. > . , 7 s 7 . .
O 5 10 15 M 25 30 35 40 Avmge Grain Size (mkroirmters)
lron va Average Grain She (Chongmlng 1%) 1- 7 - - . .
O 10 20 30 a 1 1
Average Grain Size (micmmctcrs)
I
Coppr vs. Average Graln Slze (Chongmlng l a )
10 1 O 5 10 15 20 25 30 35 401
! Average Grain Sire (mlcmmetera) ,
10 20 30 40
Average Grain Size (micrometers)
Magncrium vs. Avemge Grain Size (Chongming Ir.)
ocnoJ O 5 10 15 2û 25 M 35 4û
I Avernge Grain Stze (micrometers)
Nickel vs- Avetage Grain S i n (Chongming Ir.) L
- . . j 33 7
< O 1 O 20 30 i Average Grain Size (micrometers) I
Aluminum vs. Average Grain Size (Chongming k) I - - -. - - -. - - --
Average Gmin Size (micrm1en) I
Y angrnue rr Avemge Grain Sue (Chongming k) . - . _ . . l
tcad v s Average Griln Slrc (Chongrnlng 1s.)
0 10 1 1 O 10 20 Y) 40 '
! Average Grain Size ( m i c ~ e r s )
1 Arscnlc vn. Average GmIn Slze (Chongrnlng l a ) , 11 -- A -
3001 O I I
O 10 20 30 40 i O 10 20 30 40 Average Gmln Size (micromrters) 1 1 Average Grain Size (micrometerr)
I
I Cadmium vs. Average Gmin Size (Chongming h)
i 035,
, I
' 0.1 1
O 10 20 30 ag ' I I Average Grain Size (micrometers)
I
Chranium vs pH (Chongming k) i ( Zinc vs pH (Chongming ls.]
" T - - - - - - - - - - - - - - - - - -- - : ; "1 -- - - - - -- -
1 I
iron va pH (Chongmlng la) Magnalum va pH (Chongmlng 1%)
l PH ' f
I PH
i f
Copper n pH (Chongmlng 1%) Nickel K pH (Chongming k)
Cadmium vs. pH (Chongming k) . . -. - . - - . . -
Lead v r pH (Chongming k.)
- - - - -
Nonnalized lron vs. Disance Atong Flat (Chongrning 1s.)
Nonnallzed Alum~num vs. Distance Along Fkt 1
1 l Numalucd Magncuum vs. Dislance Along Flat (Chongmtng
(ChMigminp Is.) I
Nonnaluecl Chromtum vs. Distance Along Flat(Chongming is.]
0035
- O 015 - , 0 1 i
O 500 1000 1500 2oOo1
Dirtince Along FLat (m)
m
Nonnalized Z n c vs. Distance Along Flat (Chongmrng 1s.)
O 500 lm 1500 2000 i Distance Along Flat (m) I
1s.)
-
Normalized Copper vs. Distance Along Flat [Chongrntng 1s.)
O 25 I
1 0 2 . i I I O 500 :m 1500 2m j , Distance Along Flot (m)
O
- O O
+ O
O * + * O - O * O
00755 0 07 1 O M .
t O MO IO00 lm 2000 1 O 500 1OOa 1500 Mao
Distance Along Flat (m) 1
I Distance Along Flat (m)
f ""'
= o f f i . E f 0055..
! 5 - &
a - - j i 5 i o m . w X 8 o o s f - 1 ! g 0 0 2 . . - -
0 0 6 - O 2 O W -
0 0 3 5 .
O U -
O - O O
& 1 , ; O
O 0 0 : ' O = 0015 1) +
1 I
O 1 I
O 0 1 '
: ! i Nonnalkad Magnaslurn v% %TOC (Chongmlng Ir) * . ou, - - .
O 03 , 0011 O O 5 1 1 5 2 , O 0 5 1 1 5 2
% TOC x TOC
Nonalized Imn vs. % T m (Chongmlng 1%)
O4 f . -- - - -
o J G 0.5 1 1.5 2
X TOC
Normalned Chmnium vs. %TOC (Chongmlng 1s.) 0.55 - . . - . - -
O 0.5 1 15 2 i
R TOC
Nomalzed Zlnc vs. %TOC (Chongmlng lx.) Normalized Copper vs. %TOC (Chongming 1s.)
l 8 1 0 7 7 - - - - - I
1 7 A 1 065- * * . 1
1 6 , * 1 06 - *
I
O 0.5 1 15 2 X TOC
1
O O 5 1 1 5 2 .
% TOC
I
Nofmallzea Nickel vs. %TOC (Chongmlng I r ] 1
Namml id h d n %TOC (Chongming k) I
O 0 5 1 1.5 2 . X TOC
, d l O O. 5 1 1.5 2
1 X TOC
Uormallzed Caemlurn vr %TOC (Chongmlng I c ) l I - - - A - - -- -- . - - -
I I
O 0 5 1 15 2 X TOC
Nomdlted Amenlc vr %TOC (Chongmlng 1%) -- -
Oz2
O 1 O 0.5 1 1.5 2
X TOC
0003 1 O 0 5 1 ? 5 2
A TOC
I 003- '
O 5 10 15 n 25 30 35 40
Average Gmln Slze (mlcrumeter)
Hormallrtd iron vs. Average Graln Slze (Chongmlng ta) I
1
Average Grain Slze (mkmmcler)
Nonmlizcd Zinc vs. A v e q ~ e Grain Size (Chongming 1%)
1 8 7 - - - - -
Averîge Grain Size (rnicmrneter)
NormaJlxed Mqncllum vs. Average Grain Slze
: O O l J 1
O 5 1 0 1 5 2 0 2 5 j 0 3 5 4 0
Avetage Grain S i a [micromctrr]
0.1 J O 5 10 15 20 25 30 35 QO
Avemge Grain Size (micrometer)
Nonnalized Copplr vs. Aveme Grain Size (Chongming Ir.) . - -- - -- . -
- -
0.25
0.2 ! I O 10 M 30 40 j
Average Gmin S i n (micrometer) I
Normaîirrd Nickel vs. Avemgt Gnin Size (Chongming 1s.)
- -- - - ---- - &
O 10 20 30 40. Avenge Grain S i n (micrometer)
Normalizd Manganese vr. Avtrage Grain S i n (Chongming Ir.)
'6 1 . . - - . . - -- .- - - - - - - . . -
O 10 20 30 40 Average Gnin S i (micrometrr)
Nonnalizd Cadmium vs. Average Grain Sire (Chongming k)
' u - - - 5 5
1 E o m 3 O = 00035 *+
O 003 I
I O 10 20 30 40 8
Average Gmin Size (micrometer)
I Nonnalizrd hixi vr Average Grain S i n ! (Chongming k.) ! 0 6 î-- -. . . . .
I
0.25 1 O 10 20 30 40
I Average Grain Size (micromohr)
Normalizcd Arsenic vr. Average Grain Size (Chongming 1s.)
Avemge Gnin Size (micromeîcr)
Normalized Imn vs. pH (Chongming 1s.)
- - -. - -- --
Nomaiued Chmmium vr. pH (Chongming Ir.)
050- --a .- 6
045 - 6 0
Normalized Zinc vs. pH I . . 8 : . . Nomalizcd Copper vs. pH
(Chongming Ir.) 1 , I , . (Chongming Ir.)
1 8 . . , ; 070 a : -
I
Nom;alized Maganese vs. pH (Chongrnlng 1s.)
- -
Normallzed Cadmtum vs. pH (Chongm ing 1s.)
Normalized Lead vs. p H 1 (Chongming 1s.) 0 T'
Normalized Arsemic vs. pH , (Chongrn mg 1s.)
----- : 1- - --
Average Grain Sire vs. %TOC (Hengsha 1s.) / , i I %TOC vs. Zinc Concentration (Hengsha 1s.)
Average Grain Size (micrometers) %TOC
%TOC vs. lron Concentration (Hengsha 1s.) %TOC vs. Magnesium Concentration (Hengsha 1s.)
1
8 .
%TOC vs. Copper Concentration (Hengsha 1s.) / %TOC vs. Nickel Concentration (Hengsha 1s.) I
%TOC vs. Aluminum C o n c e m o n (Hengsha Is.]
7 m - . - - . - - - - - - - -- I %TOC vs. Manganese C o n c e m o n (Hengsha 1s.)
1 8 0 0 - - - -. - .
XTOC vs. Arrenlc C o n c e m o n (Hengsha 1s.)
- - - - - - -- -. -
O
%TOC vs. Lead Concerrmmon (Hengsha 1s.)
%TOC vs. Cadmium Concentmtion (Hengsha 1s.) . , 8 ,
, , %TOC vs. Chmmiurn Concentranon (Hengsha 1s.)
Appendix D (cont'd)
Chrornium Concentration vs. Average Grain Size 25 , (Hengsha 1s.) 1
t j Zinc Concentration vs. Average Grain Size
(Hengsha 1s.)
O O 50 100 150
Average Grain Size (micrometers) 200 1
I
20 1 + O 50 100 150 200
Average Gain Size (micrometers)
lron Concentration vs. Average Grain Size (Hengsha 1s.)
Magnesium Concentration vs. Average Grain Size (Hengsha 1s.)
1OOOO 0: O 50 100 150 MO
Average Grain Size (micrornctilrs) O 50 100 150 200 ,
Average Grain Size (micrometers) 1
Nickel Concentration vs. Average Grain Size (Hengsha 1s.)
Copper Concentration vs. Average Grain Size (Hengsha 1s.) I
10
O 50 100 150 200 Average Grain Size (micrometers)
1 O 50 100 150 200 1 Average Grain Size (micrometers)
Appndh D ( c d d )
Aluminum ConcenaaUon vs. Average Grain Sue Manganese Concenuanon vs. Average Grain Sue (Hengsha 1s.) (Hengsha 1s.)
70000 - - - - - - -- -
= 50000
C
E 2 m - - 5 loaoo O
ü I
O 50 1 0 0 150 O 50 100 150 200 j ; 1 ) Average Grain Site (micrometen) Average Grain Size (micrometers)
M o : I ! I
,
O ' I l
O 50 100 150 M O I ' O M 100 150 200 Average Gmin Sire (mmmhrs) Avenge Grain Size (micromebers)
Arsenic ConcemraOon VS. Average Grain Size . . ( ! Lead Concentzrbon vs. Average Grain Size
(Hengsha 1s.) 1 l
(Hengsha 1s.) - 1 l 4 5 - - - -
32 -
Cadmium Concentrabon vs. Average Grain Size (Hengsha 1s.)
Ci8 7
Ê 07 1 O
8 0 6 4 O 4
-g 11 - P = 1 0 O
O 50 100 150 2 0 0 ; I Average Gnin Size (micrometcrs)
= 9 * i 2 2 5 - ,
* - ' 1 C * C 6 7 *+ - *
' 2 . r 6 - ' ! 2 1 0 -
O j ! *+ .
5 -. O
I I
+ 4 ' 1 - ; , E 3 5 - 1 z30-
Appendix D (cont'd)
Chmmium Concentration vs. pH (biengrha 1%) ï inc Concentration us. pH (Hengsha 1%) -
- - - - - - - - - - - - .
Imn Concentration vs. pH (Hengsha 1s.) - -
Magnaium Concemon vs. pH (Hengsha Ir.)
-1 I
0 '- 1 -- - --
I
Copper Concc&aüon vs. pH (Hengsha 1s.) 45 7 -
Nickel Concentration vs. pH (Hengsha Ir.)
Aluminum Concentration vs. pH (Hengsha 1s.) . . Manganese Concentration vs. pH (Hengsha 1s.)
Arsenic Concentration us. pH (Hengsha 1s.) Lead Concentration vs. pH (Hengsha 1s.)
Cadmium Concentration vs. pH (Hengsha 1s.)
Normalized Aluminum vs. Distance Along Rat 1 , Homuluid Magnesium vs. Distance Along Flat I
(Hengsha 1s.) (Hengsha 1s.)
, ' 0.09 ,
a
Distance Along Flat (m) O l W 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0
Distance Aiong Flat (m)
Normalized lron vs. Distance Along Flrt (Hengsha 1s.)
; : ! '
O 1 0 0 2 0 0 3 0 0 4 a l 5 0 0 6 0 0
Distance Along Flat (m)
Normalized Chromiurn vs. Distance Along Flat (Hengsha Is.)
1
O-' 1
0.1 1 O 100 200 300 400 500 600:
Distance Along Flat (m) ,
/ : Normalized Zinc vs. Cistrtnce Afong F l a
j : Normalized Copper vs. Distance Along Fiat (Hengsha 1s-) (Hengsha 1s.) I
Distance Along Flat (m)
1 025 -,
1 020 1
!
O 100 200 300 4M3 500 600 l
l Distance Along mat (m)
Uonnalized Nickel vs. Distance Afong Flat (Hengsha 1s.)
2.5
+
Distance Along Flat (m) ,
Nomalized Manganese vs. Distance Aiong Flat (Hengsha 1s.)
Distance Along Flat (ni)
Nomalized Cadmium us. Distance Aiong Flat (Hengsha 1s.)
I O 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 i
I Distance Along Flat (m)
Nomralized Lead vs. Distance Along Flat (Hengsha 1s.)
t 1.8 O
1.6 ,
02 + - - ' 0.0 I
O 1 0 0 2 0 0 3 0 0 4 M 3 5 0 0 6 0 0
Distance Along Flat (m) ,
i Nomalized Arsenic vs. Distance Along Flat (Hengsha 1s.)
Distance Along Flat (m)
Normalized Aluminum vs. %TOC , . Nomaltzed Chromicm vs. %TOC (Hangrha 1s.) (Hengsha 1s.)
- -. - - - - -- - - - -. - .
Nomalized lron vs. %TOC ' i Nonnalized Zinc vs. %TOC
(Hengsha 1s.)
1 2 3 XTOC
Nonalized Magnesium vs. *ATOC Norrnalized Copper vs. %TOC (Hengsha 1s.) (Hengsha 1s.)
08 - 1 !
07 - 1
1 XTOC
2
Normaltzed Cadmium vs. %TOC
: 008, (Hengsha 1s.)
Appendix 0 (cont'd)
Ncrmaltzed Ntckel vs. XTOC i g Normaltzed Lead vs. %TOC
250 7 (Hengsha 1s.) - - - 1 8 0 - --
(Hengsha 1s.)
I t s 160..
1 '
j lm 1 1 00
x 3 la- ZlM
O
- -
iq* * * G::-* Z " = 0 6 0 i
1
Osa - - i 1 000 * * O 2 0
000 -1 O 0 0 - O * -
\ * -. - *
O 1 2 3 4 O 1 7 4
'ATOC 3
1 %TOC
Normalaed Manganese vs. %TOC Nomalaed Arsentc vs. %TOC
-33 - (Hengsha 1s.) - - .- -- * - - 0 8 -y (Hengsha 1s.)
! O 0 7 - 1
25 -. Y: 1 : 0 6 . l - E c tu
z20- i l * E O S !
5 u I
g O4 - B - - - lu Tii 15 1 : g 0 3 - .
Z - 0
O
0 2 - - v*- + O v
8 e * 0" . O , : f - 0 1 -
Appendix D ( c M d )
Normalized Aiurninum vs. Average Grain Sim Normalized Magnaiurn us. Average Gtain Size ( b g s h a 1s.) (Hengsha 1s.) o is7 - - - - -- -- --- ' ""T---- - 6
002 1 i
O 02 - , O01 1 &Ge-
O 50 100 150 200 ! O M 100 150 MO Average G n i n S i n (micrometer) ! 1 Average Grain Sirc (micrometer) f
Nomalized lron vr. Average Grain SÏze (Hengrha 1s.)
025 7 A
- -- -
Normalized Chmmium vs. Average Grain Size i : (Hengska Ir.)
50 100 150 O 50 1 û0 150
Averape Grain Size (micmmcbcr) Average Grain Size (micrometer)
Normalized Zinc vr Average Grain Sirc (Hmgsha 1s.)
4 5 7 . -
Nomalized Copper vs. Average Grain Size (iiengsha 1s.)
I Average Grain Size (micmrnekr)
1 0 2
50 100 150 MO Average Grain Sire (micmmehr)
Nonnalbed Nkkel vs. Averiige Graln She (Hengrha l n ]
- - . - - -A-- - -- . .
! Nomalhed Lead vs. Avemge Graln Slze
I ; a - - -- - (Hengsha 1s)
16 -
# ' 0.0 1 ' 0.0
O 50 1 0 0 150 m ! ; O 50 1 W 150 200
Average Grain Sim (micromcer) i ! Avenge Grain Sue (mirromter)
Normallzed Mangantre n Average Graln Slze (Hmgsha h.)
. - . - - - - - - -- . . - .- .- -. . . O
25 j
O M 100 150 m r i Average Grain Size (micrometer)
Normallzed Anenlc vr. Avecage Graln Slze
- . (Hengsha Is.) O8oT -
O 50 100 1 5 0 200 j Average Graln Slze (mlcrometer)
Nonnallzcd CIdmlum v s Average Gmln Slze (Hangsha 1s.)
, 0 x 1 I
1 O J O 50 1 0 0 150 200
I Avetage Gmln Size (micmmetar) I
O 2 4 6 8 1
PH
1 Normalizeâ Chromium vs. pH (Hengsha k.)
- . . . . - - . .
Nonnalizd Zinc vs. pH (Hengrha Ir.) (Hengsha Ir.)
Nonnalized Nickel w. pH Normalized Lead vs. pH (Hengsha 1s.) (Hengsha 1s.) - - - .-----a --- - - - -- - - - - -
O
O
Nonnalized Manganese vs. pH (Hengsha 1s.)
- -. - .
Nonnalized Cadmium vs. pH (Hengsha 1s.)
Nonnalizd Arsenic vs. pH (Hengsha 1s.)
0 7 1 - - - - - -
O