Treated wastewater changes the export of dissolved inorganic carbon

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Characterization of Natural and Affected Environments

Treated wastewater changes the export of dissolved inorganic carbon and its isotopic composition and leads to acidification in coastal oceans Xufeng Yang, Liang Xue, Yunxiao Li, Ping Han, Xiangyu Liu, Longjun Zhang, and Wei-Jun Cai Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00273 • Publication Date (Web): 16 Apr 2018 Downloaded from http://pubs.acs.org on April 16, 2018

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Treated wastewater changes the export of dissolved inorganic

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carbon and its isotopic composition and leads to acidification in

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coastal oceans

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Xufeng Yang,1, 2 Liang Xue,3 Yunxiao Li,1 Ping Han,1 Xiangyu Liu,1 Longjun Zhang,1, 2* Wei-Jun

5

Cai4,*

6 7

1

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University of China, Qingdao 266100, China.

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2

Qingdao National Laboratory for Marine Science and Technology, Qingdao 266003, China.

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3

Centre for Ocean and Climate Research, First Institute of Oceanography, State Oceanic

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Administration, Qingdao 266061, China.

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4

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*Corresponding author. Email: [email protected], [email protected]

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Notes: The authors declare no competing financial interest.

Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean

School of Marine Science and Policy, University of Delaware, Newark, Delaware 19716, USA.

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ABSTRACT

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Human-induced changes to carbon fluxes across the land-ocean interface can influence the

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global carbon cycle, yet the impacts of rapid urbanization and establishment of wastewater

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treatment plants (WWTPs) on coastal ocean carbon cycles are poorly known. This is

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unacceptable as at present ~64% of global municipal wastewater is treated before discharge.

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Here, we report surface water dissolved inorganic carbon (DIC) and sedimentary organic carbon

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concentrations and their isotopic compositions in the rapidly urbanized Jiaozhou Bay in northeast

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China as well as carbonate parameters in effluents of three large WWTPs around the bay. Using

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DIC, δ13CDIC and total alkalinity (TA) data and a tracer model, we determine the contributions to

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DIC from wastewater DIC input, net community production, calcium carbonate precipitation and

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CO2 outgassing. Our study shows that high-DIC and low-pH wastewater effluent represents an

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important source of DIC and acidification in coastal waters. In contrast to the traditional view of

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anthropogenic organic carbon export and degradation, we suggest that with the increase of

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wastewater discharge and treatment rates, wastewater DIC input may play an increasingly more

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important role in the coastal ocean carbon cycle.

31 32

ABSTRACT ART

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INTRODUCTION

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Determining the strength of sources and sinks with respect to atmospheric CO2 in coastal oceans

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has attracted considerable attention in recent years.1-3 There are large uncertainties associated

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with the current estimates of air-sea CO2 fluxes;1-3 these uncertainties result partly from

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insufficient understanding of the mechanisms controlling CO2 sources and sinks.1,2 In coastal

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areas, a variety of anthropogenic activities are changing the strength and form of terrestrial

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inputs and thus it has been increasingly challenging to understand the controls of coastal ocean

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CO2 dynamics.4,5 Among these, wastewater discharge derived from rapid urbanization and

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continuing growth of human population at present result in approximately 0.1 Pg yr-1(1 Pg = 1015

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g) organic carbon export to coastal oceans on the assumption that anthropogenic wastewater is

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untreated,6,7 which accounts for 22% of riverine organic carbon fluxes.5 However, this

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understanding is out of date6,7 as wastewater treatment plants (WWTPs) are increasingly

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common and transform most of the organic carbon into inorganic carbon before wastewater

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enters the receiving waters. The municipal wastewater treatment rate of the world was already

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more than 64% while that in North America and Western Europe region was even over 77% in 3 ACS Paragon Plus Environment

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2014 according to the data from the Food and Agriculture Organization of the United Nations

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(FAO).8 Increasing discharge of treated wastewater is expected to induce substantial changes in

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the form (organic vs inorganic) of carbon fluxes and in inorganic carbon speciation and isotopic

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composition, and thus these changes will lead to new environmental impacts as this source water

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has very different properties from untreated or inadequately treated wastewater.9,10 Major

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challenges in the study of impacts of treated wastewater on the structure and function of the

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natural carbon cycle mainly rest in separating the signal of wastewater input from various kinds

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of natural processes. Resolving the above issues is necessary to accurately estimate the carbon

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fluxes and to improve our understanding of the carbon cycle in the land-ocean interface.

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Dissolved inorganic carbon (DIC) and total alkalinity (TA) are two important parameters in the

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aquatic system that have been widely used to study the processes controlling seawater CO2

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distribution and air-sea CO2 fluxes as well as coastal ocean acidification.11-15Most previous

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studies focused on isolating the biological effect on DIC using nutrient16 or oxygen variation17,

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and water mixing effect using a simple linear relationship between DIC and salinity12 or a simple

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two end-member mixing model,13 each of which may yield large uncertainties. However, the

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stable carbon isotopic composition of dissolved inorganic carbon (δ13CDIC) is a powerful tool to

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track the sources and controls of DIC in estuaries and coastal oceans18-22 since carbon isotopic

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fractionation effects differ among biogeochemical processes including organic carbon (OC)

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degradation, primary production and outgassing of CO2. For instance, Burt et al. identified the

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DIC contributions from biological activity and denitrification by means of the carbon isotopic

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fractionation factors in the North Sea.22 Thus, the combination of a δ13CDIC value and a DIC and

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TA pair makes it possible to better quantify DIC sources and sinks in coastal oceans.

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The Jiaozhou bay is greatly influenced by urbanization because the eastern region of the bay

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abuts downtown Qingdao, which has a population of approximately 4.8 million and discharges

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approximately 75% of its urban wastewater (~5.1×108 ton year-1) into the bay at present.23 Over

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the last two decades, not only have population and urban wastewater total amount increased

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rapidly (by 140% and 220%, respectively)24 but also more importantly the wastewater treatment

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rate has increased from a mere 40% in 1999 to 98.6% in 2016.21 Thus, this bay provides an

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excellent case study for how rapid urbanization and the development of modern WWTPs could

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affect coastal ocean carbon cycle and the environments. This study quantifies the contributions

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of main controls to DIC in the bay using stable carbon isotopic data and a ternary model based

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on DIC, δ13CDIC and TA data. The results indicate that DIC directly transported from wastewater

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discharge (wastewater DIC input) to the bay is larger than that from total OC degradation in the

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northeastern region of the bay. Noteworthily, the main detrimental environmental effect caused

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by treated wastewater is to lower the pH level of the receiving waters. We suggest that

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wastewater DIC input is an important source of coastal ocean DIC and acidification, and it will

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play a more important role in the carbon cycle of coastal oceans in the future.

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MATERIALS AND METHODS

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Study Area. The Jiaozhou Bay (35º18´-36º18´N, 120º04´-120º23´E) is a typical semi-enclosed

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bay with an average water depth of 7 m, which is surrounded by land on three sides and

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exchanges with the Yellow Sea just through the southern opening (Figure S1). The water

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residence time of the bay ranges from less than 20 days in the bay mouth to over 100 days in the

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northwest.25 The tidal system is regular semi-diurnal with an average tidal range of 2.8 m. The

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strong tidal effect leads to a vertically mixed water column all year round.25 There are seven

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relatively large residual current eddies, which have significant influences on the material

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transport in the Jiaozhou Bay.26

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Sample collection and processing. Two cruises were conducted on 13 June and 1 July 2014 in

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the Jiaozhou Bay.. Thirty-five discrete surface water samples were collected using a 5-L Niskin

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bottle during each cruise. Twelve surface sediment samples (0-4 cm) were also collected in the

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northern region of Jiaozhou Bay on 1 July 2014. Note that no heavy rain occurred within one

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month before sampling and thus the influence of natural freshwater input was considered

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negligible. In addition, wastewater samples were collected monthly from November 2014 to

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December 2015 in three municipal wastewater treatment plants located in the northeastern region

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of the bay.

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The samples collected for δ13CDIC measurement were filtered into 12 ml septum-sealed glass

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vials (Labco Limited) through a 0.45 µm cellulose acetate membrane (Whatman, Maidstone, UK)

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and immediately poisoned by adding 8 µL saturated HgCl2. Samples for dissolved organic

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carbon (DOC) were filtered through a 0.7 µm glass fiber membrane (Whatman, Maidstone, UK)

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and poisoned with saturated HgCl2.

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The surface sediment samples were kept in a freezer at -20°C. Prior to undergoing

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measurements of TOC% and δ13CPOC, all samples were crushed with a mortar after being

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freeze-dried for 48 h. Approximately 0.5 g of each treated sample was reacted with 5 mL 10%

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hydrochloric acid for 10 hours to remove inorganic carbon. All samples were washed with

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distilled water until pH was neutral; after the supernatants were removed, the samples were

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freeze-dried and stored.

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Sample analyses and measurement precisions. The δ13CDIC and δ13CPOC values were

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determined using a Gasbench II extraction line coupled with a Finnigan MAT 253 mass

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spectrometer (Thermo Electron Corporation, USA) , and calibrated by IAEA-CO-1, a marble

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from Viareggio, Italy. The results are given as per mil deviations from the standard (PDB) and

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are denoted as δ13C.

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(n=4), and based on the calculation method of Humphreys et al.,27 1-sigma measurement

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precisions of sample duplicate measurements in δ13CDIC and δ13CPOC were 0.06‰ and 0.15‰.

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The partial pressure of carbon dioxide (pCO2) and the carbon isotopic composition of CO2

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(δ13CCO2) dissolved in seawater were measured using a G2131-i Analyzer for Isotopic CO2

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(Picarro Inc., California, USA). The SD of the 5-min moving average of δ13CCO2 in one hour is

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0.09‰ when the standard gas is at a level of 380 ppm. DOC was measured by a total organic

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analyzer (TOC-Vcpn, Shimadzu Corporation, Kyoto, Japan) with a measurement precision of

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±1%. TOC% value was determined using a CHN elemental analyzer (Thermo Flash 2000, USA).

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Based on the repeated measurements of standards, the SD of these results was 0.04% (n=5).

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Temperature and salinity were measured continuously using an SBE 45 Micro TSG (Sea-Bird

The standard deviation (SD) of reference material measurements was 0.05‰

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Inc., Bellevue, WA, USA). DO saturation was measured using a YSI-5000 oxygen analyzer (YSI

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Corporation Yellow Spring, Ohio, USA) with a membrane electrode. pH was measured using an

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Orion 3-Star Plus pH Benchtop meter with a ROSS pH combination electrode (Thermo Fisher

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Scientific Inc., Beverly, MA, USA) calibrated on the NIST scale. DIC was determined by acid

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extraction using a total organic analyzer (TOC-Vcpn, Shimadzu Corporation, Kyoto, Japan). TA

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was determined by Gran titration (AS-ALK2, Apollo SciTech, USA). Measurements of DIC and

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TA were calibrated against certified reference material (CRM, provided by A.G. Dickson from

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Scripps Institution of Oceanography). The 1-sigma measurement precisions of DIC and TA

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analysis are 2.0 µmol kg-1 and 1.6 µmol kg-1. These hydrologic data and carbonate parameters

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were reported by Li et al.28

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The relationship between DIC addition or loss and deviation of δ13C. Previous studies have

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defined deviations from the conservative mixing of freshwater and seawater when studying DIC

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stable carbon isotopic patterns in estuaries and coastal oceans.18,20,21 These are applied to discuss

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the effects of biogeochemical processes on DIC during physical mixing. In this approach, the

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excess or deficient DIC is defined as DIC deviation in addition to the river-ocean mixing. In

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some coastal bays with little river input, a single ocean end-member can be used as a reference

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point and then the difference between the observed property and the oceanic contribution is

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defined as the DIC addition or loss (∆DICexcess) in excess of the ocean contributions, which is

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applied to assess terrestrial inputs (e.g. rivers, salt marshes and groundwater) and internal

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biogeochemical processes.11,29-30 It is equally rigorous to use a two end-member (ocean and river)

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approach or a single end-member (ocean only) approach. In the Jiaozhou Bay, nearby rivers have

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little natural runoff, while effluents from discrete WWTPs represent the main contributors to

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freshwater. Therefore, it is suitable to use the ∆DICexcess based on a single ocean end-member to

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evaluate the DIC contributions from wastewater DIC input and other biogeochemical processes.

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The calculation method is also applied to TA for ∆TAexcess.

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ΔDIC = DIC  − DIC 

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ΔTA = TA  − TA 

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The subscripts “sample” and “ocean” denote the measured values and the ocean end-member

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values, respectively; Ssample and Socean are the salinities of the sample and the ocean end-member,

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respectively. The second term in Eq. (1) or Eq. (2) represents the oceanic contribution to sample

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DIC or TA as ocean end-member is diluted from Socean to Ssample.



(1)





(2)



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Similar to DIC, we use the difference between the measured δ13C value (δ13Csample) and the

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δ13C value of the ocean end-member (δ13Cocean) to represent the isotopic deviation induced by

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local processes from the ocean end-member, as shown in Eq. (3).

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Δδ C

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When DIC produced by OC degradation is added to the initial water or some DIC is removed by

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primary production or CO2 outgassing, the isotopic composition of DIC is also altered following

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the 13C mass balance equation.20

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DIC  δ C  =

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The δ13Cexcess in the equation is the carbon isotopic composition of the added or lost DIC.

!"

= δ C  − δ C 

 

DIC  δ C

(3)

!"

+ ΔDIC δ C

(4)

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From Eq. (4), the carbon isotopic composition of the sample can be expressed as follows:

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δ C  =

173

From Eq. (1), we can obtain the next equation:

174

 

!" 

!" 

!"

!"

=1−

δ C  +

% !"& !"

% !"&  δ C !"



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(5)

(6)

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Inserting Eq. (6) into Eq. (5) yields the following equation:

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δ C  − δ C  =

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(7)

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Now, by the definition of Eq. (3), we can convert Eq. (7) into the following equation:

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Δδ C

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In coastal bays with limited freshwater input, the ∆DICexcess produced by a single process is small

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(less than 10% of ocean end-member DIC) and then DICsample and DICocean are approximately the

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same. Thus

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Δδ C

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Therefore, as expressed in Eq. (9), the

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process are linearly related, and the slope of each relationship is equal to the difference in the

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isotopic compositions of the added or lost DIC and the ocean end-member value, which

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approximately equals the fractionation factor of each biogeochemical process at the current

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situation20-22. Thus, in this paper, we will use the deviations in DIC and δ13CDIC values from

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those of the ocean end-member to determine the main processes influencing DIC based on the

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unique slope representing each process.

!"

!"

=



% !"& !"

% !"& !"

% !"& !"

% !"& (δ C −δ C  ) !"

(δ C −δ C  )

can be replaced by

(8)

% !"& !"

and Eq. (8) can be further simplified to:

(δ C −δ C  ) % !"& !"

(9) and ∆δ13CDIC values resulting from a single

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The CO2 produced by OC degradation has no substantial isotopic fractionation relative to

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OC31 while the magnitude of isotopic signal change of OC degradation between OC and seawater

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DIC is similar to the isotopic fractionation of primary production and they have opposing

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directions.20-22 Therefore, the δ13C value of additional DIC or lost DIC due to net community

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production is taken as δ13CPOC or δ13CDOC value. We use the average δ13CPOC value of 12 surface

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sediments in the bay. The δ13C value of CO2 removed by outgassing was measured directly using

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a CO2 carbon isotope analyzer coupled to a gas equilibrator. In addition, according to the study

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performed by Emrich,32 the δ13C values of newly produced calcium carbonate can be calculated

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using the following equation:

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δ C" "+, = δ C-"+,. + (1.85 ± 0.23) + (T − 20) × (0.035 ± 0.013).

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Since the HCO3- ion accounts for more than 90% of DIC species in the seawater here, the δ13C of

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DIC is approximately equal to that of HCO3-. In terms of wastewater DIC input, the average

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δ13CDIC value of all wastewater samples is interpreted to represent the δ13C of DIC produced by

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wastewater DIC input.

(10)

205 206

RESULTS AND DISCUSSION

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δ13CDIC and DIC concentrations of bay water. δ13CDIC values in the bay varied from -2.09‰ to

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0.22‰, and they were more negative in June than July (Figure 1). More than two thirds of the

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whole area showed negative values and the most negative values were in the northeastern region

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of the bay. The depleted δ13CDIC values corresponded well with regions with low salinity (Figure

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S2A, B), probably by effluents from municipal WWTPs. The δ13CDIC distribution also supports 11 ACS Paragon Plus Environment

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previous results that high DIC in the eastern area mainly came from terrestrial input.28 The

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δ13CDIC values from the western region and the mouth of the bay were slightly positive and

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similar, while DIC concentrations were significantly lower in the west than those in the mouth of

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the bay. The difference between the δ13CDIC and DIC distributions suggests that multiple

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processes may have contributed to DIC in the bay.

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TOC% and δ13CPOC of surface sediment. The total organic carbon content (TOC%) in the

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sediments varied from 0.42% to 2.89%, decreasing from the eastern region of the bay to the west

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(Figure 1C). The highest value emerged near the east coast of the bay, consistent with a recent

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report in the same area.33 However, compared with data reported ten years ago (3.10%~8.96%),34

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the TOC% in the eastern region decreased substantially while in the bay centre the TOC%

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showed no obvious change. An improving wastewater treatment rate in the City of Qingdao24

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may be the main reason for the sharp weakening of the terrestrial organic input signal. The

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carbon isotopic composition of the particulate organic carbon (δ13CPOC) varied between -23.2‰

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and -21.1‰ and increased from east to west (Figure 1C); the values were slightly more negative

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than the characteristic value of marine OC (-20‰).35 The samples located near the east coast had

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the most negative values, which corresponded well with the distribution of TOC%. We note that

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TOC% and δ13CPOC had peak values along the east coast while DIC and δ13CDIC peaked in the

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northeast. The reason for their lack of strict geographic consistency is that terrestrial coarse

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particles sink to the bottom quickly near the WWTPs, while dissolved material can be

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transported to the north because of the counterclockwise coastal current.26

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Carbonate parameters of effluents from WWTPs. Considering that there is no natural river

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inflow in the eastern region of the bay, three large-scale municipal WWTPs (Haibo River, Licun

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River and Loushan River) nearby become the dominant contributor to terrestrial input. These 12 ACS Paragon Plus Environment

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plants have the designed disposal capability of 160, 250 and 100 thousand tons per day

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respectively. We obtained comprehensive carbonate data and isotopic compositions of DIC for

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these three municipal WWTPs over one year. As shown in Figure 2, the monthly DIC

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concentrations of the wastewater varied from 2554 to 5173 µmol kg-1; even the lowest value was

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greater than that of coastal seawater (approximately 1800-2100 µmol kg-1). However, the DOC

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concentrations only varied from 409 to 898 µmol kg-1. This is consistent with a recent report that

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the average DIC concentration of nine small-scale (2-15 thousand tons per day) municipal

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WWTPs in Germany was 3408 µmol kg-1 (40.9 mg L-1) and DOC concentration was 770 µmol

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kg-1 (9.2 mg L-1).9 The TA values in our treated wastewater were also high and spanned a wide

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monthly range (2402-4386 µmol kg-1), but they remained lower than DIC concentrations.

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Moreover, we noted that pH values (7.30±0.21), TA/DIC ratios (0.93±0.05) and δ13CDIC values

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(-11.8±1.01‰; SD, n=12) of the wastewater were relatively stable but were much lower than

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those of coastal seawater. Thus, the discharge of the effluents from municipal WWTPs has the

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great potential to disturb the coastal ocean carbonate system.

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Processes affecting DIC. As stated in the Methods section, in this work, a single ocean

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end-member is used to determine the overall DIC input from all terrestrial sources (dominated by

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WWTPs) and the internal processes and isotope signals are used together with DIC to identify

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the various sources and sinks of DIC. We notice that DIC addition or loss (∆DICexcess), defined in

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Materials and Methods (Eq. 1), relative to the ocean end-member value (

254

linear relationships with the difference in the carbon isotopic composition from the ocean

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end-member value (∆δ13CDIC) (Figure 3). Thus, we used these relationships to identify the

% !"& ) !"

exhibits

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control mechanisms of DIC in the bay (see Materials and Methods). As shown in Figure 3, DIC

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additions occurred in the northeastern region and DIC losses occurred in the west whereas the

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bay centre samples had minimum addition or loss. Almost all samples from the northeastern

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region of the bay fall within the lower right or fourth (IV) quadrant. Among them, a few samples

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from nearshore areas with high ∆DICexcess and very negative ∆δ13C values are distributed

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between the two vectors and represent wastewater DIC input and OC degradation. Those

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offshore samples locate close to the vector and represent OC degradation, but show less

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∆DICexcess and elevated ∆δ13CDIC compared with the vector, which suggests that some of their

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DIC is removed by either outgassing of CO2 (ref. 36) or calcium carbonate precipitation.37 Based

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on the pCO2 level of approximately 1100 µatm and the pH of 7.8 (Figure S3) as well as a

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relatively low aragonite saturation state level of less than 1.6 (Figure S4) observed in the

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northeastern region, we conclude CaCO3 precipitation can be neglected here.38 The high pCO2

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levels and long water residence times in the northeastern region of the bay25 support the effect of

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outgassing of CO2. As all samples from the northeastern region are affected by outgassing of

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CO2 to some extent, we suggest that the samples whose isotope-DIC relationship (Figure 3)

271

locates near the vector representing OC degradation can still be seriously influenced by

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wastewater DIC input (showed by the purple outgassing arrows) even though OC degradation

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appears to be the main contributor to DIC there.

274

In contrast, most of the samples in the west fall within the lower left quadrant III and are

275

located close to the vector representing carbonate precipitation. We note that the DO saturation

276

(DO%) in this region was approximately 100% (Figure S2C), indicating that net ecosystem

277

production cannot explain the observed DIC loss in this region and CaCO3 precipitation is the 14 ACS Paragon Plus Environment

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likely cause. Additional evidence supporting a CaCO3 precipitation mechanism is the

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substantially loss of TA in the high-salinity region (Figure S5). The area near the Dagu River

280

estuary has a relatively high aragonite saturation state (Figure S4) and is an important shellfish

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aquaculture area in the bay, where the production of shellfish in 2014 exceeded 2.9×105 tons.39

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Thus, carbonate precipitation is most likely induced by aquaculture activity. Moreover, because

283

of the longest water residence time of over 100 days in the western region of the bay,25

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continuous outgassing of CO2 must also influence the DIC level in this region. Thus, CaCO3

285

precipitation and CO2 outgassing dominate the loss of DIC in the western region.

286

Separating DIC contribution from each process. To further evaluate the perturbation of

287

treated wastewater in the coastal carbon cycle compared with natural biogeochemical processes,

288

it is necessary to build a source model for DIC to quantify the contribution from each process.

289

DIC addition or loss in coastal oceans, as defined by Jiang et al,30 mainly results from several

290

processes, including terrestrial input (terr), net ecosystem production (nep), sea-air CO2 exchange

291

(as) and calcium carbonate precipitation/dissolution (carb).30 The DIC addition or loss through

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these processes can be explicitly expressed as follows:

293

ΔDIC = ΔDIC788 + ΔDIC + ΔDIC  + ΔDIC 89

294

Note again in our system terrestrial input is dominated by wastewater discharge. In addition, for

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the vertically-mixed bay, the DIC contribution of OC degradation in water column is not

296

separated from that in sediments at present.

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The corresponding isotopic composition of the added or lost DIC due to all processes is defined

(11)

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in the following 13C mass balance equation:

299

ΔDIC δ C =

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ΔDIC788 δ C788 + ΔDIC δ C + ΔDIC  δ C  + ΔDIC 89 δ C 89

301

Here, δ13Cterr, δ13Cnep, δ13Cas and δ13Ccarb are the δ13C values of DIC that are produced by the

302

above processes, respectively. For later calculation, we use the site values for δ13Cas and δ13Ccarb

303

and the mean values for δ13Cterr and δ13Cnep (see Methods and Materials).

(12)

304

It is known both TA and DIC will change following mass balance laws and specific

305

stoichiometric relationships when biogeochemical processes occur. In particular, carbonate

306

precipitation removes DIC and TA at a ratio of 1:2, while net primary production results in a

307

sharp decrease in DIC but only a small increase in TA (in a ratio of TA/DIC = -17/106).40

308

Moreover, TA does not change when sea-air CO2 exchange occurs. Because of these variations,

309

TA is used to build the third equation of the model. Similar to DIC, TA addition or loss can be

310

explicitly expressed by the following equation:

311

ΔTA = xΔDIC788 − 17/106 ΔDIC + 2ΔDIC 89

312

The letter x denotes the ratio of TA to DIC (TA/DIC) for terrestrial input. In a case of known

313

freshwater end-member, the contribution of terrestrial input can be obtained by freshwater

314

(wastewater here) DIC concentration and the proportion of freshwater in the seawater sample.11

315

Now with the three equations (11-13), if one of four terms is known or negligible, we can

316

calculate the contributions of three other processes.

317

(13)

In the northeastern region of the bay, CaCO3 precipitation was weak and can be neglected

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318

due to low pH conditions. Therefore, three factors (wastewater DIC input, net ecosystem

319

production and air-water exchange) can be solved by the three equations. To this end, we

320

estimate that the area influenced by wastewater input has a salinity of lower than 30.6 because

321

the DIC contribution from wastewater DIC input at this salinity value is less than 0.8% of the

322

sample DIC concentration based on the average DIC concentration of the wastewater and the

323

salinity of ocean ender-member. In other areas of the bay, with the salinity greater than 30.6, we

324

infer there is no terrestrial input occurring. By now, we are able to obtain the DIC sources and

325

sinks in the bay using the quantitative model built following the above procedure.

326

The model-calculated DIC contributed by wastewater DIC input (∆DICterr) varied from 33 to 287

327

µmol kg-1 in the northeastern region of the bay, while the DIC contributed by OC degradation

328

(∆DICnep, net effect of primary production and OC degradation) only varied from 47 to 125 µmol

329

kg-1 (Figure 4). Most notably, ∆DICterr was twice as large as ∆DICnep at the three nearshore

330

stations during June. CaCO3 precipitation caused the removal of DIC with the highest value of

331

54 µmol kg-1 in the western region. The DIC removed by CaCO3 precipitation (∆DICcarb)

332

decreased with distance offshore and fallen to only 5 µmol kg-1 in the centre of the bay.

333

Furthermore, the amount of DIC removed by the outgassing of CO2 (∆DICas) decreased from the

334

western and northeastern regions to the centre of the bay. The maximum value of 140 µmol kg-1

335

occurred in the west during June and was nearly three times as large as the ∆DICcarb value. The

336

large ∆DICas values in the western region of the bay are related to the shallow water depths (less

337

than 2m) and long water residence time in this region. The ∆DICas values were relatively smaller

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338

in July than June, consistent with a lower wind speed in the two weeks before the sampling days

339

in July than June (Figure S6). Overall, the amount of DIC from wastewater DIC input

340

approached and even exceeded that from OC degradation.

341

There are some uncertainties associated with model calculation. First, we ignored the

342

possible contribution from denitrification in sediments on DIC, but this contribution may be

343

minor, especially relative to wastewater DIC input and aerobic degradation of OC. This is

344

because treated wastewater has a lower total nitrogen concentration of less than 15 mg L-1 (ref.

345

41) due to advanced nitrogen removal technology, and thus the bay receives a much lower nitrate

346

loading. In contrast, the regions where denitrification in sediments provides substantial effluxes

347

of DIC receives a far larger nitrate loading usually from river input e.g. in the southern North

348

Sea.30,42 Moreover, if OC degradation occurs via anaerobic processes in shallow sediments, the

349

produced methane oxidation is another source for DIC. However, its role on increasing water

350

DIC is also relative small, given that the oxidation rate of methane in bottom water is low to 150

351

nmol L-1 d-1 in the bay43.

352

Coastal acidification induced by treated wastewater. One important effect of treated

353

wastewater input on environment is its contribution to coastal acidification. The influence of

354

wastewater input on pH represents re-equilibration of the carbonate system after mixing of

355

seawater and wastewater effluent. We quantified the pH drop (∆pH) only induced by physical

356

mixing in June 2014, assuming that the pH in the mouth of the bay represented the initial level of

357

the bay water. From the change in TA and DIC, the pH drop (∆pH) can be calculated via the

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358

CO2SYS program.44 The detailed procedures are as follows.

359

The concentrations of DIC and TA resulting from mixing of seawater and wastewater are:

360

DIC> = DIC  

361

TA> = TA 

362

The subscript “ocean” denotes the ocean end-member and the letter i denotes the station; ∆DICterr

363

and ∆TAterr are the contributions of the wastewater input to DIC and TA, respectively, which are

364

obtained using the source model for DIC; and x is the ratio of TA to DIC (TA/DIC), which is

365

0.93 in this calculation.

366

Then, the pH drop (∆pH) induced by mixing is calculated as follows:

367

ΔpH = f (DIC> , TA> , S> , T> ) − f (DIC  , TA  , S  , T  )

368

In this equation, f (DICi, TAi, Si, Ti) represents the pH resulting from mixing of seawater and

369

wastewater at a given temperature and salinity, and f (DICocean, TAocean, Socean, Tocean) is the pH

370

for the ocean end-member. As shown in Figure 5A, pH drop was maximum (∆pH = -0.09) in the

371

northeastern region and it diminished away from the wastewater source and approached near

372

zero in the central region of the bay.

? 

?



+ [ΔDIC788 ]>

+ x[ΔDIC788 ]>

(14) (15)

(16)

373

Moreover, the wastewater discharge in the metropolitan area of Qingdao almost tripled from

374

1987 to 2013.23 We thus simulated variations in pH under different treated wastewater discharge

375

conditions using a simple dilution law as both population and wastewater discharge are expected

376

to increase in the next few decades. According to the results of the model, the relationship

377

between the contribution of wastewater DIC input (∆DICterr) and salinity (S) follows this

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378

equation (Figure S7):

379

ΔDIC788 = −211.48 × S + 6466.2 (r I = 0.98, n = 7)

380

Assuming that DIC and TA concentrations of the wastewater input remain unchanged and the

381

biologically contributed DIC and TA are not considered, the DIC and TA contributions resulting

382

from the increase in wastewater discharge can be expressed as follows:

383

[ΔDIC788 ] 8 = −211.48 × S 8 + 6466.2

(18)

384

[ΔTA788 ]pre = 0.93 × [ΔDIC788 ] 8

(19)

385

Spre denotes the predicted salinity for a certain wastewater discharge amount, which can be

386

calculated based on the proportion of freshwater and the dilution law. Note that if there is any

387

microbial decomposition of organic matter in the wastewater effluent, it will further increase

388

DIC and decrease pH.

389

According to mass balance, the sample salinity of a station can be defined as:

390

S> =

391

When wastewater discharge changes, the predicted salinity (Spre) becomes:

392

S 8 =

393

Here, Qocean and QF are the volumes of seawater and wastewater at a certain station, and y

394

denotes the ratio of the future wastewater discharge to the present one.

395

Combining Eq. (20) with Eq. (21) yields:

396

S 8 = P

397

Next, [∆DICterr]pre and [∆TAterr]pre are calculated. Then, the pH drop that occurs when the

M 

(17)

(20)

M NMO

M 

(21)

M NPMO

? 

(22)

 QP? N?

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398

wastewater discharge increases is also calculated using Eq. (14), Eq. (15) and Eq. (16). The

399

results showed the intensity and extent of influence on pH enlarged as expected when treated

400

wastewater discharge there triples (Figure 5B). At station #3, which records the lowest salinity

401

values, pH will decrease by 0.19 pH units, which is greater than the pH drop that has occurred in

402

ocean surface ocean water (0.1) since the Industrial Revolution.45 Moreover, pH drop and the

403

increment of sewage discharge are related by a quadratic function (r2=1, n=5) (Figure 5C). Note

404

that the acidification induced by wastewater DIC input is different from that induced by

405

degradation of OC from terrestrial input or eutrophication. The influence of wastewater DIC

406

input may just occur in the mixing layer, whereas the influence of OC degradation may occur in

407

the subsurface layer.46 Moreover, OC degradation is controlled by various natural factors such as

408

temperature and dissolved oxygen, and thus OC may not be degraded immediately in local under

409

adverse conditions (e.g. low temperature), which indicates that OC has enough time to be

410

transported to farther regions to induce acidification. However, wastewater DIC input causes an

411

immediate and continuous influence on water pH regardless of nature condition variability. More

412

importantly, with the wide construction of WWTPs and the improvement of wastewater

413

treatment technology, more POC and DOC in wastewater will be converted to DIC before

414

entering coastal oceans. This probably means additional acidification induced by wastewater

415

DIC input in excess of the effect of increasing atmospheric CO2 will be a growing problem

416

worldwide.

417

Global implications. In summary, treated wastewater characterized by low pH and high pCO2

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418

can lead to seawater acidification in many coastal areas, exemplified by the urbanized Jiaozhou

419

Bay. Many coastal regions, mainly including some bays and estuaries, are adjacent to big cities

420

and thus receive high wastewater loadings. These bays are vulnerable for acidification caused by

421

treated wastewater due to poor water exchange with open ocean, such as the Jiaozhou Bay.

422

Among them, the areas with water hypoxia47 may also suffer a greater acidification due to the

423

combined effect of anthropogenic CO2, CO2 from biological acidification (OC respiration), and

424

DIC from WWTPs. In addition, the acidification effect in low salinity estuary can be also

425

severe48 because low TA to DIC ratio of rivers lead to a weak buffering capacity. According to

426

incomplete data (from 116 countries) from FAO,8 the global municipal wastewater discharge in

427

2014 was 309.2 billion cubic meters while the current treatment rate is approximately 64%, the

428

rate for developed countries is even greater than 77% (Figure S8). This means that inorganic

429

carbon is the primary export form for over half of municipal wastewater, because more than 90%

430

of OC is removed during wastewater treatment prior to discharging into natural waters,49

431

especially in the coastal areas of developed countries. Although 90% of wastewater in many

432

developing countries is untreated,50 the treatment infrastructures in some countries with the rapid

433

economic growth are currently going through a period of rapid development. For instance, the

434

urban wastewater treatment rate in Chile increased from only 8% to almost 87% in 2010.51

435

However, other large developing countries still have low treatment rates, e.g., Brazil and India at

436

only about 30%,8 and have a great potential to improve their rates of treatment.

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437

There is no doubt that the DIC fluxes from treated wastewater to coastal oceans are

438

increasing with improved treatment rate and a rapid growth of the population in coastal regions.

439

According to data collected by the FAO,8 the average annual growth rate of municipal

440

wastewater discharge from 2007 to 2014 was 0.86% in 20 developed countries (from a total for

441

28), while it was approximately 5.8% in 59 developing countries. Assuming that these growth

442

rates remain unchanged, the predicted global municipal wastewater discharge in 2030 will be

443

approximately 563 billion cubic meters. This value is probably an underestimate because these

444

data cover only major countries and some industrial wastewater is not drained into municipal

445

wastewater systems. For example, the industrial wastewater discharge of China in 2014 was up

446

to 20.5 billion tons52, but it is not counted in municipal wastewater discharge.

447

increasing amounts of treated wastewater will further increase acidity and influence the strength

448

of CO2 source/sink with respect to the atmosphere in coastal oceans. In addition, it is unrealistic

449

to apply organic fluxes as total carbon fluxes for anthropogenic wastewater in future land-ocean

450

carbon cycle model and the organic carbon removal and transformation during wastewater

451

treatment process thoroughly should be better considered.

Therefore,

452 453

ASSOCIATED CONTENT

454

Supporting Information

455

Sampling stations and tracks, spatial distributions of basic hydrological parameters including

456

salinity, temperature, dissolved oxygen saturation, pCO2 and pH, ∆DICexcess and ∆TAexcess, the

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457

wind speeds during sampling, the ratio of treated to untreated wastewater for the world are

458

included in the Supporting Information file.

459 460

ACKNOWLEDGMENT: The authors acknowledge financial support from the National

461

Science Foundation of China (NSFC) (Grant No. 41376123), the National Science Foundation of

462

China - Shandong Joint Fund for Marine Science Research Centres (NSFC) (Grant No.

463

U1406404), the National Science Foundation for Creative Research Groups (Grant No.

464

41521064) and the FIO basic science and research programs (Grant No. 2016Q01). W-J.C.

465

acknowledges support from NSF, NASA and NOAA for his coastal ocean carbon cycling and

466

acidification research

467

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51. Informe de Gestión del Sector Sanitario 2010; Superintendencia de Servicios Sanitarios,

600

Santiago, 2011; http://www.siss.gob.cl/577/articles-8333_recurso_1.pdf.

601

52. Environmental Statistics Annual Report 2006-2015; Ministry of environmental protection in

602

China, Beijing, 2006-2015. http://www.zhb.gov.cn/gzfw_13107/hjtj/hjtjnb.

603 604 605

FIGURES

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606 607

Figure 1. Spatial distributions of surface water DIC and its isotopic composition in (A) June

608

2014 and (B) July 2014 and (C) TOC% and δ13CPOC of the surface sediment samples in July

609

2014. The δ13CDIC and δ13CPOC are plotted in contours, while the DIC and TOC% in colors. The 32 ACS Paragon Plus Environment

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610

black stars show the locations of three municipal wastewater treatment plants. Treated

611

wastewater is discharged into the bay directly. The sediment samples are thinner than 4cm and

612

can record the impact of changing environmental conditions within one to two years. Note that

613

the DIC data was from Li et al.28

614 615

616 617

Figure 2. Temporal variations in carbonate parameters of treated wastewater from the three

618

WWTPs. The samples from Haibo River and Licun River WWTPs were not collected in January

619

2015. These WWTPs apply primary (bar screen and primary settler) and secondary 33 ACS Paragon Plus Environment

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(anoxia/anaerobic/oxic digester and secondary clarifier) treatments based on an activated sludge

621

system. The daily treatment loads of the Haibo River, Licun River and Loushan River WWTPs

622

are approximately 86, 170 and 100 thousand tons, respectively.

623

624 625

Figure 3. The deviation in δ13CDIC (Δδ C

626

end-member R

627

represents the difference between observed property and the oceanic contribution as calculated

628

by Jiang et al.30 The plot is divided into four quadrants (I, II, III and IV). The origin represents

629

sample values equal to the ocean end-member value. The vectors passing through the origin

630

indicate the theoretical effect of each process affecting DIC. Those slopes representing

631

degradation of OC and primary production, outgassing of CO2, CaCO3 precipitation and

632

wastewater DIC input are -22.2‰, -9.4‰, 1.5‰ and -12.0‰, respectively (Table S1), which are

% !"& !"

!" )

versus DIC addition or loss relative to the ocean

S in June and July 2014. The DIC addition or loss (∆DICexcess)

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633

equal to the difference between the δ13C values produced by each process and the ocean

634

end-member value (see Materials and Methods for details). The purple arrows indicate sample

635

moving directions when degassing occurs. Sample pCO2 values are given in color with the

636

associated color bar presented.

637 638

Figure 4. Distribution of DIC produced by OC degradation and wastewater DIC input and DIC 35 ACS Paragon Plus Environment

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639

removed by carbonate precipitation and CO2 outgassing in (A) June and (B) July. A reference

640

size of the pie in the legend represents 220 µmol kg-1 of DIC. ∆DICterr represents DIC changes

641

contributed by wastewater DIC input. ∆DICnep represents the net effect of DIC loss by primary

642

production and addition by OC degradation. The values in the bay are all positive, indicating

643

biological process is dominated by OC degradation. In addition, DIC changes due to air-sea CO2

644

exchange, ∆DICas, and DIC changes due CaCO3 precipitation, ∆DICcarb, are negative and the

645

results well support the above conclusion that carbonate precipitation and CO2 outgassing have

646

important impacts on DIC concentrations during these two cruises.

647

648 649

Figure 5. Distribution of the pH drop (∆pH) induced by wastewater DIC input. (A) pH drop due

650

to present wastewater discharge and (B) due to a twofold increase in it. (C) The relationship

651

between the increments of treated wastewater discharge compared to the present one and pH

652

drop in station #3. The pH was calculated on the NIST scale by the CO2SYS program.44 The

653

letter Q represents the present wastewater discharge of the three WWTPs that is located in the

654

northeast of the Jiaozhou Bay.

655 656 657

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