Dominance of nitrous oxide production by nitrification and denitrification in the shallow Chaohu Lake, Eastern China: Insight from isotopic characteristics of dissolved nitrous oxide

Environmental Pollution 255 (2019) 113212

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Dominance of nitrous oxide production by nitrification and denitrification in the shallow Chaohu Lake, Eastern China: Insight from isotopic characteristics of dissolved nitrous oxide* Qingqian Li a, b, 1, Fang Wang a, 1, Qibiao Yu a, Weijin Yan a, *, Xinyan Li c, Shucong Lv a a b c

Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China University of Chinese Academy of Sciences, Beijing, 100049, China Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 28 May 2019 Received in revised form 5 August 2019 Accepted 6 September 2019 Available online 11 September 2019

In recent decades, most lakes in Eastern China have suffered unprecedented nitrogen pollution, making them potential “hotspots” for N2O production and emission. Understanding the mechanisms of N2O production and quantifying emissions in these lakes is essential for assessing regional and global N2O budgets and for mitigating N2O emissions. Here, we measure isotopic compositions (d15N-N2O and d18ON2O) and site preference (SP) of dissolved N2O in an attempt to differentiate the relative contribution of N2O production processes in the shallow, eutrophic Chaohu Lake, Eastern China. Our results show that the bulk isotope ratios for d15N-N2O, d18O-N2O, and SP were 5.8 ± 3.9‰, 29.3 ± 13.4‰, and 18.6 ± 3.2‰, respectively. More than 76.8% of the dissolved N2O was produced via microbial processes. Findings suggest that dissolved N2O is primarily produced via nitrification (between 27.3% and 48.0%) and denitrification (between 31.9% and 49.5%). In addition, isotopic data exhibit significant N2O consumption during denitrification. We estimate the average N2O emission rate (27.5 ± 26.0 mg N m
2 h
1), which is higher than that from rivers in the Changjiang River network (CRN). We scaled-up the regional N2O emission (from 1.98 Gg N yr
1 to 4.58 Gg N yr
1) using a N2O emission factor (0.51 ± 0.63%) for shallow lakes in the middle and lower region of the CRN. We suggest that beneficial circumstances for promoting complete denitrification may be helpful for reducing N2O production and emissions in fresh surface waters. © 2019 Elsevier Ltd. All rights reserved.

Keywords: N2O Isotopic composition Site preference Nitrification Denitrification

1. Introduction Nitrous oxide (N2O) has drawn extensive attention both in terms of greenhouse effects and with respect to the depletion of the stratospheric ozone. The most recent report from the Intergovernmental Panel on Climate Change (IPCC) estimated that the atmospheric concentration of N2O has been increasing since the 1750s (IPCC, 2013). Deleterious effects on the environment caused by the rising atmospheric N2O concentration have prompted urgent demands for the regulation of N2O emissions (Turner et al., 2015).

* This paper has been recommended for acceptance by Dr. Sarah Harmon. * Corresponding author. E-mail addresses: [email protected] (Q. Li), [email protected] (F. Wang), [email protected] (Q. Yu), [email protected] (W. Yan), [email protected] (X. Li), [email protected] (S. Lv). 1 Qingqian Li and Fang Wang contribute equally to this work.

https://doi.org/10.1016/j.envpol.2019.113212 0269-7491/© 2019 Elsevier Ltd. All rights reserved.

Current studies suggest that an accurate quantification of N2O emissions from individual sources is essential for the assessment, prediction, and mitigation of N2O emissions (Ravishankara et al., 2009; Ostrom and Ostrom, 2017). Although inland waters (such as lakes and rivers) have been recognized as an important source of atmospheric N2O (Cole and Caraco, 2001; Snider et al., 2015), a reliable estimation of N2O emissions from inland waters is still challenged by a lack of data (Turner et al., 2015; Soued et al., 2016; DelSontro et al., 2018). Furthermore, lakesdas “hotspots” for the occurrence of nitrogen (N) cycling and N retention in inland watersdare potential contributors of N2O emissions to the atmosphere, but relative knowledge is fragmented (Soued et al., 2016; DelSontro et al., 2018). Estimating N2O emissions from lakes would be helpful for increasing the accuracy of estimates of N2O budgets, for both inland waters and global ecosystems. Toyoda et al. (2017) deemed that the accurate quantification of N2O emission depends on an insight into N2O production

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Q. Li et al. / Environmental Pollution 255 (2019) 113212

mechanisms. N2O can be produced in situ through microbial processes in sediments and in water columns (Jia et al., 2016; Xia et al., 2017). These processes include nitrification, denitrification, nitrifier denitrification, and dissimilatory nitrate reduction to ammonium (DNRA) (Denk et al., 2017; Toyoda et al., 2017) (Fig. 1). Nitrification, the oxidation of ammonia (NH3) to nitrate (NO
3 ), releases N2O as a by-product, whereas denitrification (NO
3 reduction) can either produce N2O or transform it to dinitrogen (N2) in a final reaction (Toyoda et al., 2017). Nitrifier denitrification is the process of nitrite (NO
2 ) reduction and N2O production by nitrifying bacteria under hypoxic conditions (Toyoda et al., 2017). DNRA is another process of
þ N2O production by the reduction of NO
3 to NO2 , and then to NH4 and N2O (Denk et al., 2017). Despite a mass of studies involving N2O production mechanisms, the identification of N2O production processes and the quantification of the contributions of each process under natural circumstances, remain challenging. Advanced stable isotopic approaches have been recommended for addressing this difficult issue (Peters et al., 2014; Toyoda et al., 2017). Stable isotope techniques have been applied to provide insight into N2O production mechanisms through the determination of stable N and oxygen (O) isotope ratios (d15N-N2O and d18O-N2O) and site preference (SP, defined as SP ¼ d15Na- d15Nb) within the linear molecule (Nb-Na-O) (Kim and Craig, 1993; Yoshida and Toyoda, 2000). In particular, SP is controlled by N2O production processes and is constant with variations of isotopic compositions þ of substrates (such as NO
3 and NH4 ) (Yoshida and Toyoda, 2000; 15 Sutka et al., 2006), while d N-N2O and d18O-N2O are variable (Perez et al., 2000; Sutka et al., 2006). To date, SP values of N2O derived from nitrification, denitrification, and nitrifier denitrification were determined and have relatively stable ranges, except for DNRA. SP ranges of N2O from nitrification, denitrification, and nitrifier denitrification are from 30‰ to 36‰, from
5‰ to 9‰, and from
11‰ to 0‰, respectively (Denk et al., 2017; Toyoda et al., 2017). Additionally, the simultaneous growth of d15N-N2O, d18ON2O, and SP will occur during the N2O consumption process via

complete denitrification, with an increase of 2‰e9‰, 5‰e25‰, and 2‰e8‰, respectively (Ostrom et al., 2007; Lewicka-Szczebak et al., 2014). This powerful approach has been widely and effectively used in soils, oceans, and inland saline waters (Snider et al., 2015; Toyoda et al., 2017), but has been less used in freshwaters, especially in shallow lakes. N2O emissions are an integrated result of N2O production and N2O consumption (Wang et al., 2016). The N2O yieldddefined as the mole ratio of net N2O production to the sum of net N2O production and net N2 production (i.e., N2O yield ¼ △[N2O]/ (△[N2O] þ △[N2]))dwas developed to represent N2O reduction during the denitrification process (Ostrom et al., 2007). The reported values vary by ~0.02% to 5.6% in natural water bodies (Seitzinger and Kroeze, 1998; Beaulieu et al., 2011; Wang et al., 2016). A low N2O yield responds to the strong N2O consumption in a denitrification-dominated situation. Previous studies have suggested that N2O emissions can be directly linked to anthropogenic N inputs (Seitzinger and Kroeze, 1998; Soued et al., 2016). Thus, the N2O emission factor (EF) was introduced to present the proportion of N load converted to N2O and emitted to the atmosphere, i.e., the amount of N2O emission/N load (Seitzinger and Kroeze, 1998; IPCC, 2006). The IPCC recommend an EF of 0.25% for the estimation of the global N2O emission from inland waters (IPCC, 2006). Current research argues that the default IPCC EF contains a lot of uncertainties, and is either higher (Maavara et al., 2019) or lower (Beaulieu et al., 2011) than their estimations. This implies that there is a demand for a comprehensive EF database of different types of inland waters, on both regional and global scales. However, most present studies have focused on streams, rivers, reservoirs, and estuaries rather than lakes (Beaulieu et al., 2011; Turner et al., 2015; Maavara et al., 2019). A reasonable value of a N2O EF for lakes would be helpful for reducing uncertainties in the estimation of N2O emission. Thus, there is an urgent need for addressing the lack of studies in relation to the N2O EF for lakes, and especially for shallow eutrophic lakes

Fig. 1. Schematic illustration of microbial processes of N2O production and consumption. N2O production processes (in red rectangles) include nitrification, incomplete denitrification, nitrifer denitrification and dissimilatory nitrate reduction to ammonium (DNRA) (Denk et al., 2017; Toyoda et al., 2017). The process of N2O reduction (in blue rectangle) represents the pathway of N2O altering to N2 during complete denitrification. Complete denitrification (in black rectangle) includes processes of incomplete denitrification and N2O reduction. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Q. Li et al. / Environmental Pollution 255 (2019) 113212

that receive an excessive N load from upstream areas because of intensive agricultural production and/or rapid urbanization. In recent decades, most lakes on the middle and lower region of the Changjiang River network (ML-CRN) have suffered serious N pollution. There is therefore the potential to stimulate N2O production in these lakes (Yan et al., 2012; Wang et al., 2016). Here, we hypothesize that lakes are potential “hotspots” for N2O production and emission. We aim to identify the microbial processes in N2O production, quantify the relative contribution of these processes, and estimate a reasonable EF for lakes. A typical shallow eutrophic lake, Chaohu Lake, is used to: (1) measure the isotopic compositions of dissolved N2O (including SP, d15N-N2O, and d18O-N2O), (2) identify N2O production processes and quantify individual contribution, (3) calculate the in situ N2O emission rate and estimate a practical N2O EF for shallow eutrophic lakes, and (4) provide an approximation of the magnitude of N2O emissions from lakes on the ML-CRN. Specifically, we assess the role of lakes in N2O emissions from the entire Changjiang River network (CRN). 2. Materials and methods 2.1. Study area The Chaohu Lake (783 km2, 31250 2800 -31430 2800 N, 117160 5400 117 5104600 E) is located on ML-CRN (Fig. S1), and is the fifth largest freshwater lake in China. The lake area is 783 km2 and the mean depth is approximately 2.75 m. It experiences a humid subtropical climate with most precipitation occurring from May to September. The average annual precipitation during the latest decade was 1067 mm and the average annual air temperature was 18.9  C (Statistics Committee of Anhui Province, 2017). Algal blooms normally occur during the period from June to October (Zhang and Kong, 2015). There is no water stratification all year round due to frequent, strong wind-wave disturbance in the Chaohu basin (Deng et al., 2006). Due to the construction of the Chaohu dam in the 1960s, the lake became a dam controlled, shallow, eutrophic lake.

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processes, and ε presents the isotope effect during each microbial process (hereafter termed 15ε for 15N and 18ε for 18O). Reference point data are available in Table S1. Reference points of denitrification (d15N-N2O and d18O-N2O) were the sum of the measured stable N and O isotope ratios (d15N 15 18 and d18O) of NO
3 (d N-NO3 and d O-NO3) and the theoretical isotope effect, ε (15ε and 18ε), respectively (Casciotti et al., 2002; Denk et al., 2017). To account for the impacts of the incorporation of O from H2O into N2O during denitrification, d18O-N2O reference points were computed again from the measured d18O of H2O (d18OH2O) and a previously reported 18ε value (Lewicka-Szczebak et al., 2014). We also considered the increase of d15N-N2O, d18O-N2O, and SP via the subsequent N2O consumption during denitrification using the ε values of 36‰, 74‰, and 8‰ for d15N, d18O, and SP, respectively (Vieten et al., 2007; Lewicka-Szczebak et al., 2014). We þ þ 15 failed to measure d15N of NHþ 4 (d N-NH4 ) due to the low NH4 concentration in the water column of the lake. We estimated two þ 15 values of d15N-NHþ 4 to represent the possible range of d N-NH4 15 15 based on available data of d N in surface sediments (d N-sedi15 mentary-N, ε ¼
1.74‰) and algae (d15N-algal-N, 15 15 ε ¼
9.4 ± 6.6‰) (Denk et al., 2017). The d N of the reference points for nitrification and nitrifier denitrification were subsequently estimated using the above estimated values of d15N-NHþ 4 in combination with their corresponding 15ε values (as reviewed in Denk et al., 2017). The d18O values of the reference points for nitrification and nitrifier denitrification were estimated from published data on d18O-O2 (23.5‰, Toyoda et al., 2017) and d18O-NO-2 (
4.9 ± 0.1‰, Peters et al., 2014), respectively. 2.3.2. Partition N2O production According to results from Keeling plots and laboratory measurements of SP produced from microbial processes, the relative contribution ratios of different sources can be calculated following Equations (2)e(5):

SPmicro ¼ f N  SPN þ f D  SPD þ f ND  SPND ;

(2)

2.2. Sampling sites

100% ¼ f N þ f D þ f ND ;

(3)

Samples were collected during four periods: January 2016, June 2016, October 2016, and August 2017. Sampling sites are shown in Fig. S1a. In addition, two sites on inflowing rivers (the Nanfei River, NFR, and the Hangbu River, HBR) were also sampled in the same sampling periods. Sampling and analytical methods are detailed in the supplementary material (S1).

SPdis ¼ Fmicro  SPmicro þ Fatm  SPatm ;

(4)

100% ¼ Fmicro þ Fatm ;

(5)

2.3. Calculations 2.3.1. Isotopic composition of reference points Dissolved N2O sources in the lake were divided into two components: (1) atmospheric via air-water exchange and (2) authigenic, primarily via microbial processes in the lake. Based on previous studies (Sutka et al., 2006; Denk et al., 2017; Toyoda et al., 2017) and the geochemical characteristics of collected samples, we assume that authigenic N2O in the lake is primarily produced by nitrification, denitrification, and nitrifier denitrification. Reference points were estimated to present the possible isotopic compositions of N2O derived from microbial processes according to the isotopic fractionation theory and detected isotopic data, according to Equation (1) (Mariotti et al., 1981; Denk et al., 2017):

dcal ¼ dsub þ ε

(1)

where, dcal denotes the calculated isotope ratio value of production, dsub is the isotope ratio value of substrates during microbial

where, SPdis denotes the SP values of dissolved N2O in water column, SPmicro is the SP value of microbial-derived N2O in the lake, SPatm is the SP value of atmospheric N2O (19.4 ± 1.9‰, Snider et al., 2015), SPN is the SP value of nitrification-derived N2O (33 ± 5‰, Sutka et al., 2006), SPD is the SP value of denitrification-derived N2O (0 ± 5‰, Sutka et al., 2006), and SPND is the SP value of nitrifier denitrification-derived N2O (
10.7 ± 2.9‰, Frame and Casciotti, 2010) (Table S1). Fmicro denotes the fraction of microbial-derived N2O to dissolved N2O in water column, Fatm is the fraction of atmospheric N2O to dissolved N2O in water column, fN is the fraction of nitrification-derived N2O to microbial-derived N2O, fD is the fraction of denitrification-derived N2O to microbial-derived N2O, and fND is the fraction of nitrifier denitrification-derived N2O to microbial-derived N2O. 2.4. Statistical analyses Statistical analyses were performed using SPSS 24.0 statistics software. The linear correlation between variables were evaluated using Pearson correlation analysis, and the spatio-temporal variation of the variables was evaluated using ANOVA analysis (both at a

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Q. Li et al. / Environmental Pollution 255 (2019) 113212

statistical significance of 0.05, i.e., p < 0.05). 3. Results 3.1. Isotopic compositions of water and sediment The d15N-NO-3 and d18O-NO-3 of water samples were determined in the lake ecosystem (Fig. 2a). The d15N-NO-3 values ranged from 2.54‰ to 22.0‰ and d18O-NO-3 values ranged from
4.39‰ to 17.0‰ in the lake and inflowing rivers during the sampling periods from January to October 2016. d15N-NO-3 data demonstrated significant spatial variation (ANOVA, p < 0.05), with the highest values corresponding to the NFR (18.8 ± 5.26‰) and the lowest values to the HBR (3.50 ± 1.02‰). The elevated d15N-NO-3 in the NFR are the consequence of N contamination from urban wastewater discharge from Hefei City, while the lower d15N-NO-3 in the HBR likely originate from organic ammonium diffused from the soil. The lake appears to have d15N-NO-3 (8.50 ± 3.46‰) from various sources. However, we observed no significant spatial change in d18O-NO-3 values (ANOVA, p > 0.05). The d15N-sedimentary-N values ranged from 3.89 to 9.25‰, with an average of 6.50 ± 1.78‰ for the lake. The d15N-algal-N values ranged from 8.37 to 12.5‰ with an average of 10.5 ± 1.40‰ for the lake. Our data show that the d15N-algal-N values were higher than those of d15N-NO-3 (Fig. S2), which implies a preferen
18 tial uptake of NHþ 4 over NO3 by algae. The d O-H2O values ranged from
7.84 to
4.06‰ with an average of
5.48 ± 1.29‰ for the lake (Table S2). 3.2. Isotopic compositions of dissolved N2O and N2 We measured the d15N and d18O of dissolved gases (d15N-N2O, d18O-N2O, and d15N-N2), and SP values in the lake and in two major inflowing rivers (NFR and HBR, Fig. 2bed). The d15N-N2O and d18O-

N2O values ranged over the three sampling periods (January to October 2016) from
3.60‰ to 20.1‰ and 16.3‰e59.0‰, respectively, in the lake and inflowing rivers. These were similar to the spatial pattern of d15N-NO-3, whereby the d15N-N2O value in the NFR was the highest (9.71 ± 1.88‰), and the HBR had the lowest value (
0.53 ± 4.35‰). The lake had mixture of d15N-N2O values (5.76 ± 3.90‰). There was no significant correlation between d15NN2O and d18O-N2O (r ¼ 0.127, p > 0.05). SP values ranged from 15.4‰ to 32.3‰ in the lake and inflowing rivers. SP values had a significant spatial variation (ANOVA, p < 0.05), with the highest values in the NFR (27.4 ± 6.92‰) and the lowest values in the lake (18.6 ± 3.16‰). The measured SP values in the lake ranged between the theoretical denitrification-derived SP values (0 ± 5‰) and nitrification-derived SP values (33 ± 5‰) (Sutka et al., 2006; Toyoda et al., 2017), which implies that both denitrification and nitrification were two potential N2O sources. There was neither any correlations between d15N-N2O and SP (r ¼ 0.229, p > 0.05), nor between d18O-N2O and SP (r ¼
0.308, p > 0.05). However, SP values showed a significant positive relationship to the concen
þ þ tration of NO
3 ([NO3 ]w, r ¼ 0.849, p < 0.01), NH4 ([NH4 ]w, r ¼ 0.590, p < 0.05), and dissolved inorganic N ([DIN]w, r ¼ 0.916, p < 0.01) in the water column (Figs. S3aec), suggesting that DIN (both NO
3 and NHþ 4 ) was an important factor in N2O production in the lake. d15N-N2 values ranged between
1.51‰ and 0.37‰ in the lake and inflowing rivers (Fig. 2d). There was no significant spatial variation in d15N-N2 (ANOVA, p > 0.05). Overall, most d15N-N2O values were significantly lower than those of d15N-NO-3 (Fig. 3a). Whereas d18O-N2O values were significantly higher than those of d18O-NO-3 in the lake (Fig. 3b). In addition, we found significant seasonal difference in d15N-N2O in the lake (ANOVA, p < 0.05). The higher d15N-N2O values were observed in January 2016 (9.07 ± 6.17‰), and the lower were observed in June and October 2016 (4.03 ± 2.63‰), which indicates the different mechanisms and productions of N2O in the lake. There

Fig. 2. Isotopic compositions and spatial distribution in water in inflowing rivers (Nanfei River and Hangbu River) and the lake. (a). d15N-NO-3 and d18O-NO-3; (b). d15N-N2O and d18ON2O; (c). SP values; (d). d15N-N2 and d18O-H2O.

Q. Li et al. / Environmental Pollution 255 (2019) 113212

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Fig. 3. Distribution plots of isotopic compositions of NO
3 , N2O and N2 in the lake.

was no significant seasonal difference in d15N-NO-3 in the lake (ANOVA, p > 0.05). Our study showed that d15N-N2 values were lower than d15N-NO-3 and d15N-N2O values (Fig. 3c and d), which implies a significant depletion of d15N-N2 due to denitrification during N2 production processes. However, we found that not all the d15N-N2O data were lower than those of d15N-NO-3, thus suggesting that depletion was not solely due to denitrification (Fig. 3a).

3.3. N2O emission from the lake The concentration of dissolved N2O ([N2O]) ranged from 0.39 mg N L
1 to 42.3 mg N L
1 in the lake water column, and the net N2O production (D[N2O]) ranged from 0.05 mg N L
1 to 41.8 mg N L
1 (Table S2). The D[N2O] data were larger than zero, thus indicating that the lake was a source of local atmospheric N2O. Seasonal variations were observed in [N2O] and D[N2O], with the highest values in January 2016, followed by October 2016, August 2017, and the lowest in June 2016. We speculate that algal growth in the lake is primarily responsible for the seasonal variation of D[N2O] (refer to Section 4). The D[N2O] showed a significant positive correlation to þ [NO
3 ]w, (r ¼ 0.418, p < 0.05), [NH4 ]w, (r ¼ 0.705, p < 0.01), and [DIN]w, (r ¼ 0.657, p < 0.01). We also found a significant positive relationship between D[N2O] and SP values (r ¼ 0.820, p < 0.01), which suggests a robust influence of nitrification on N2O production (Fig. S3d). The ratios of the mole of N-N2O to the sum of N-N2 and N-N2O were calculated to determine the magnitude of N2O yields as a means of assessing N2O production and consumption during

denitrification (Ostrom et al., 2007; Beaulieu et al., 2011; Wang et al., 2016). The N2O yield in the lake ranged from 0.16% to 27.0%, which is higher than that generally observed in natural waters (Table S2). The calculated air-water N2O emission rate ranged from 1.07 mg N m
2 h
1 to 657 mg N m
2 h
1 (Table S2). Despite this wide range in the N2O emission rate, the range narrowed considerably after two extremely high values were excluded, resulting in an average N2O emission rate of 27.5 ± 26.0 mg N m
2 h
1. The average emission rate was subsequently scaled-up for the whole lake, resulting in an estimated annual lake N2O emission of 0.19 ± 0.18 Gg N yr
1 (Table S2).

4. Discussion 4.1. Mechanisms of N2O production N2O production processes in freshwater ecosystems include nitrification, denitrification, nitrifier denitrification, and DNRA (Park et al., 2012; Toyoda et al., 2017). These processes interact with other N transformation processes, such as algal N uptake, mineralization, and sedimentation (Fig. 4). Our laboratory sediment incubation experiments (refer to the supplementary material, S1) combined with in situ field observations demonstrated several N transformation processes, including nitrification, denitrification, anammox, and DNRA. Simultaneous identification and interpretation of N2O production processes were achieved by analyzing observed isotopic data for NO
3 , H2O, N2, N2O, algae, and sediment within the framework of N cycling. The conceptual diagram is

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Q. Li et al. / Environmental Pollution 255 (2019) 113212

Fig. 4. Conceptual diagram of simultaneous identification and interpretation of N2O sources. Microbial processes of N2O production (in red rectangles) include nitrification, incomplete denitrification, nitrifer denitrification and dissimilatory nitrate reduction to ammonium (DNRA). Complete denitrification (in black rectangle) includes processes of incomplete denitrification and N2O reduction (in blue rectangle). Blue words present theoretical values of isotope effects (15ε for 15N and 18ε for 18O) and site preference (SP) during each microbial process of N2O production (Toyoda et al., 2005; Perez et al., 2006; Sutka et al., 2006; Frame and Casciotti, 2010; Park et al., 2011; Denk et al., 2017; Toyoda et al., 2017). Theoretical 15ε during NHþ 4 uptake and mineralization (in black rectangles) are also present in blue words (Denk et al., 2017). Black words present measured values in this study. Potential rates of nitrification, denitrification and DNRA are abbreviated to NR, DR and DNR, respectively. Green words present calculated values based on theoretical values and measured values. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

presented in Fig. 4, which illustrates the related processes for identifying and quantifying N2O sources in the lake. The corresponding potential reaction rate (Fig. S4), characteristics of chemical parameters, and isotopic compositions are also summarized in Fig. 4. In combination with the documented SP data, reference points were used to denote possible isotopic compositions of N2O from different production processes, and were subsequently compared with measured isotopic data of N2O and available SP data (June and October 2016) (Fig. 5 and Equation (1)). Firstly, denitrificationdduring which NO
3 is reduced to N2O before being reduced to N2dmay play an important role in NO
3 reduction processes in the lake (Fig. 4). We further measured the potential denitrification rate and the potential anammox rate in the laboratory via sediment incubation experiments (Fig. S4). A high denitrification rate (222 ± 72.4 mmol N kg
1 h
1) and low anammox rate (14.1 ± 8.07 mmol N kg
1 h
1) indicate the strong denitrification and extremely weak anammox processes in the lake, thus suggesting that N2 production may be dominated by denitrification

rather than anammox. A high organic carbon content (as an electron acceptor) and sufficient NO
3 in the water and sediment, could support complete denitrification (Wrage et al., 2001). The significant depletion in measured d15N-N2O to d15N-N2 (Fig. 3d) indicates a flourishing N2O consumption in the lake. Typically, the reference point of denitrification is expected to be
34.4 ± 3.46‰, 45.9 ± 5.16‰, and 0 ± 5‰ for d15N-N2O, d18ON2O, and SP, respectively (Fig. 5 and Table S1). Considering the impacts of isotope fractionation during N2O reduction, d15N-N2O, d18O-N2O, and SP would increase to 1.6 ± 3.46‰, 120 ± 5.16‰ and 8 ± 5‰ (Vieten et al., 2007; Lewicka-Szczebak et al., 2014). The reference point of nitrification is expected to be 14.8 ± 1.40‰, 20.6‰, and 33 ± 5‰ for d15N-N2O, d18O-N2O, and SP, respectively (Fig. 5 and Table S1). Our d15N-N2O, d18O-N2O, and SP data were near or within these reference values (Fig. 5). For d15N-N2O and SP values, the measured data are consistent with a situation of two potential sources (nitrification and incomplete denitrification) and are affected by N2O reduction (Fig. 5a). In terms of the isotopic

Q. Li et al. / Environmental Pollution 255 (2019) 113212

7

Fig. 5. Distribution patterns of measured d15N-N2O, d18O-N2O and SP (red or blue) and reference points of N2O from various microbial processes (black). Black arrows represent impacts on d15N-N2O, d18O-N2O and SP caused by N2O reduction. Legends with the label of “sediment”, “algae” or “oxygen exchange” present reference points estimated from d15N of sediment, d15N of algae or d18O of H2O (presents the scenario of isotopic exchange of oxygen from H2O to N2O during denitrification), respectively. Legends with the label of “W” or “E” present the location of the sample site, at the west or east part of the lake. Data of reference points are listed in Table S1. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

signature of d18O-N2O (Fig. 5b and c), based on the d18O-N2O value calculated from the d18O-NO-3 alone, there was an inconsistency in the identification result from Fig. 5a. But the scenario, involving isotopic exchange of oxygen from H2O to N2O during denitrification (Lewicka-Szczebak et al., 2014), shows the same identification result with that from Fig. 5a. This implies that the occurrence of isotopic exchange of oxygen and subsequent N2O consumption effectively controlled the value of d18O-N2O in the lake. In particular, the measured isotopic data are close to the reference point of atmospheric N2O for all three isotopic constraints (d15N-N2O, d18ON2O, and SP). This illustrates that apart from the governance of nitrification and denitrification, isotope compositions of N2O were also influenced by air-water exchange of N2O in the lake. Secondly, nitrification can be a major process of N transformation, during which N2O leaks into the lake. During this process, the NHþ 4 input (from rivers or produced from organic matter mineralization in sediment) is converted to NO
3 on the surface of the sediment (Fig. 4). We observed a high NHþ 4 content (69.6 ± 47.2 mg N kg
1) in the sediment samples and a high dissolved oxygen concentration (6.57 ± 1.79 mg L
1) in the water column. Taken together (Fig. 4), these provide the basic actors and substrates for the occurrence of nitrification. We also observed a high potential nitrification rate (73.6 ± 39.9 mmol N kg
1 h
1) in the

laboratory sediment incubation experiments (Fig. S4), thus demonstrating the strong process of nitrification in the lake. The observed data for all three isotopic constraints illustrates that nitrification is one of the primary potential sources of N2O to the lake (Fig. 5). In particular, the observed values in January 2016 (non-growth season for algae) were much closer to the reference point of nitrification than those in June and October 2016 (algal growth season) (Fig. 5c), which implies an enhanced nitrification during the non-growth season for algae. The difference between two reference points of nitrification is caused by the difference between d15N-sedimentary-N and d15N-algal-N values. Organic N in surface sediments is not only sourced from dead algae but also from inflowing rivers. Contributions of these two sources to sediment organic N may control the d15N-sedimentary-N, thus differing from d15N-algal-N values and the effects of subsequent mineralization þ processes. A competition for NHþ 4 utilization exists between NH4 uptake by algae and nitrification (Wan et al., 2018). Based on the þ comparability of molecular ratios of NO
3 /NH4 in inflowing rivers, lake water, and lake surface sediment (Fig. S5, same sampling times), the higher ratios in the lake water reflect active NHþ 4 conþ sumption and/or NO
3 production processes (such as NH4 uptake and nitrification) in the lake, especially in the algal growth season. The lower D[N2O] that were observed in the algal growth season,

8

Q. Li et al. / Environmental Pollution 255 (2019) 113212

þ along with the higher ratio of NO
3 /NH4 (Fig. S5), reflect a repressed nitrification due to an enhanced competition for NHþ 4 uptake in the algal growth season. Thirdly, nitrifier denitrification is considered as one pathway for N2O production, and occurs under hypoxic circumstances and high NO
2 concentrations (Wrage et al., 2001; Wenk et al., 2016). This process is unlikely to occur in the Chaohu Lake, given the high dissolved oxygen content and the undetectable NO
2 concentration in the water column (Fig. 4). The NO
2 concentration was also undetectable in laboratory nitrification experiments that use the lake sediment. Finally, DNRA could be one pathway of NO
3 reduction in the lake (Fig. 4). However, our study demonstrated much lower rates for both DNRA (10.2 ± 5.15 mmol N kg
1 h
1) in comparison to the very high rates for nitrification and denitrification (Fig. S4). Generally, DNRA outcompetes denitrification under conditions of
NO
3 limitation and high organic carbon lability (normally, C/NO3 ratio > 12), and presents the function of N cycling (NO
3 reduced to
NHþ 4 ) rather than N removal (NO3 reduced to N2O) (Salk et al., 2017; Friedl et al., 2018; Sun et al., 2018). Our study showed that higher

1 NO
3 concentrations (5.26 ± 6.17 mg N kg ) and lower C/NO3 ratio (2.75 ± 1.12) in surface sediments, and such circumstances may restrain the occurrence of DNRA. However, Sun et al. (2018) used
anaerobic growth experiments with various C/NO
3 ratios and NO3 concentrations to demonstrate that DNRA-derived N2O production is considered negligible with concurrent denitrification. Thus, we did not consider the contribution of DNRA to N2O production in the lake. Overall, our results suggest that N2O production in the lake is dominated by nitrification and denitrification, and that it is also associated with N2O consumption and air-water exchange of N2O.

4.2. Partition N2O production In this study, SP values were used for the quantifying the relative contribution of nitrification and denitrification to N2O production due to the independence from isotopic compositions of substrates and the dependence on N2O production processes. The Keeling plot method was firstly introduced to identify sources of atmospheric carbon dioxide (Keeling, 1958, 1961), and was subsequently used for N2O sources (Yamagishi et al., 2007; Toyoda et al., 2011; Salk et al., 2016; Toyoda et al., 2017). We used this method to estimate SP values for microbial-derived N2O (excluding the disturbance of air-water exchange of N2O) for partition of N2O production (Fig. S6). The SP values of microbial-derived N2O are shown on the y-intercept of the regression line with an inverse concentration of N2O, which includes measured data from June and October 2016 and published atmospheric N2O data (Snider et al., 2015). Subsequently, relative contributions of nitrification and denitrification in June and October 2016 were calculated using Equations (2)e(5). Notably, many researchers have verified that the SP of N2O will be elevated during N2O consumption and that the increments vary from 2‰ to 8‰ (Vieten et al., 2007; Lewicka-Szczebak et al., 2014). Here, we selected 0‰ to present the SP of denitrification-derived N2O (Toyoda et al., 2017) and 8‰ to present the SP of denitrificationderived N2O, which was elevated by N2O consumption (Vieten et al., 2007; Lewicka-Szczebak et al., 2014). The quantitative results are listed in Table 1 and suggest that approximately 76.8%e79.9% of the dissolved N2O was sourced from nitrification and denitrification, and that 20.1%e23.2% was sourced from local atmospheric N2O via air-water exchange. In June, the relative contributions of nitrification and denitrification to total dissolved N2O (after the exclusion of the atmospheric contribution via air-water exchange) range from 35.5% to 51.2% and from 48.8% to 64.5%, respectively. In contrast, there were higher nitrification contributions and lower denitrification contributions in October,

from 47.3% to 60.1% and from 39.9% to 52.7%, respectively. When isotopic fractionation during N2O consumption is considered, the relative contributions of denitrification increased by 15.7% in June and 12.8% in October. Hence, oversight of N2O consumption will lead to a biased assessment when quantifying N2O production since the contribution of denitrification is underestimated. The reduction of N2O to N2 during complete denitrification is the only known biological pathway of N2O consumption, and is catalyzed by N2O reductase encoded by the functional gene of nosZ (Zumft, 1997; Pauleta et al., 2019). Given the fact that N2O consumption is controlled by the densities and expression of nosZ (Pauleta et al., 2019), more work is needed to construct a more complete pattern of the impacts of N2O consumption on N2O emissions through the combination of molecular microbiological methods, isotopic analysis, and in situ measurements of N2O yields, with the overall purpose of regulating of N2O emissions. High contribution ratios of nitrification can explain the high N2O yield in the lake. Given the observed SP data, we conclude that the relative contributions of nitrification and denitrification to total dissolved N2O ranged from 27.3% to 48.0% and from 31.9% to 49.5% in the algal growth season. The increase in the relative contribution of nitrification was expected in the lake during the non-algal growth season because of the weak competition between nitrification and NHþ 4 uptake, however, there was a lack of SP data in corresponding seasons. Further observations involving seasonal variation of N2O isotopic compositions are therefore recommended. 4.3. N2O emission and EF of the lake Lake N2O emission is a key component of inland waters at both the global and regional scales of N2O budgeting owing to the following hydrological and biogeochemical conditions: (1) lakes are receiving water bodies with high N loads from both agricultural runoff and urban wastewater effluents, (2) lakes have favored and highly reduced anoxic conditions, including high dissolved organic matter contents in sediments during algal decomposition, and (3) lakes also have higher residence times. Taken together, these circumstances favor the conversion of bioavailable N into reduced N through the processes of nitrification, denitrification, nitrifier denitrification, and DNRA, during which N2O is produced (Seitzinger et al., 2006; Burgin and Hamilton, 2007). Parameters for assessing regional N2O emissions from lakes includes in-lake △[N2O], kN2O, and the surface area of lakes within the basin (Equations S1eS3). kN2O is an important factor in N2O emission calculations and is calculated from k600. Models for k600 estimation based on wind speed are widely applied, especially in open waters such as lakes, rivers, and estuaries (Cole and Caraco, 2001; Borges et al., 2004). Here, we compile a series of studies with eight models (Table S3). We found that values of k600 varied from 0.46 cm h
1 to 11.4 ± 2.98 cm h
1 (average 5.10 ± 3.63 cm h
1). The model developed by Crusius and Wanninkhof (2003) was selected for k600 estimates in this study, because the k600 calculated from this model (4.00 ± 2.46 cm h
1) had no significant difference with most k600 values reported by others (Wanninkhof, 1992; Cole and Caraco, 1998; MacIntyre et al., 2010; Aufdenkampe et al., 2011). Therefore, we estimated the lake air-water N2O emission rate using the k600 determined by Crusius and Wanninkhof (2003) and in situ D[N2O]. Many studies have introduced the EF to estimate N2O emissions from aquatic ecosystems on large regional scales or on a global scale. However, most research has focused on the EF of streams, rivers, reservoirs, and estuaries (Beaulieu et al., 2011; Turner et al., 2015; Maavara et al., 2019), and less research has been given to the EF of lakes. Here we attempt to address this gap by estimating the EF for a shallow eutrophic lake. The EF was 0.51 ± 0.63% for the

Q. Li et al. / Environmental Pollution 255 (2019) 113212

9

Table 1 Relative contribution ratios (%) of different N2O sources. Sampling time

Atmosphere exchange

Microbial sources

Jun. 2016

23.2

76.8

Oct. 2016

20.1

79.9

No N2O reductiona

N2O reductiona

Nitrification

Denitrification

Nitrification

Denitrification

39.3 51.2 48.0 60.1

37.5 48.8 31.9 39.9

27.3 35.5 37.8 47.3

49.5 64.5 42.1 52.7

Note: Values with underline are relative contribution ratios of nitrification or denitrification to microbial sources. a , It presents two scenarios, ignoring the occurrence of N2O reduction (No N2O reduction) and considering the occurrence of N2O reduction (N2O reduction), respectively.

Chaohu Lake for a N2O emission of 0.17 ± 0.20 Gg N yr
1 and N loading into the Chaohu Lake (in 2016) of 32.3 Gg N yr
1. Our EF estimation is at the range reported by Seitzinger and Kroeze (1998) (between 0.3% and 3%), and higher than the EF suggested by the IPCC (2006) (0.25%) for global aquatic ecosystems (groundwater, rivers, and estuaries). This suggests that shallow eutrophic lakes have a higher potential capacity for N2O production and emission compared with other types of inland waters. Furthermore, in terms of significant impacts on N2O production from the complex N cycling in lakes, the total nitrogen (TN) load is more considerable than the NO
3 concentration or DIN load for the EF estimation of lakes. 4.4. N2O emission from ML-CRN We further applied this EF and available data of N loads to lakes to quantify N2O emission rates from the five largest freshwater lakes within the ML-CRN: Poyang Lake, Dongting Lake, Taihu Lake, Hongze Lake, and Chaohu Lake (Table 2) (Song et al., 2005; Ji et al., 2014; Jia, 2016; Lu et al., 2017; Huang et al., 2018). Calculated N2O emission rates were consistent with previously published data for N2O emission rates from Poyang Lake and Taihu Lake (Table 2) (Wang et al., 2007; Wang et al., 2009; Wang et al., 2016; Xu et al., 2016). This confirms the rationality and feasibility in using N2O

emission rates with an EF value of 0.51 ± 0.63% for other eutrophic and shallow lakes on the ML-CRN. For the five largest freshwater lakes, the calculated N2O emission rates varied from 13.7 mg N m
2 h
1 to 31.7 mg N m
2 h
1, and N2O emissions were expected ranged from 1.40 Gg N yr
1 to 3.24 Gg N yr
1 over a total area of 11,672 km2 (Table 2). We assume that this range of N2O emission rate of the five largest lakes represents the magnitude of the N2O emission rate for lakes on the ML-CRN. The total surface area of lakes with a surface area >1 km2 on the ML-CRN is estimated to be 16,476 km2 (Dong et al., 2012). Thus, the amount of N2O emission from all lakes on the ML-CRN approximately range from 1.98 Gg N yr
1 to 4.58 Gg N yr
1 (Table 2). Yan et al. (2012) reported that the N2O emission from the Changjiang River range of 0.33 Gg N yr
1 to 3.65 Gg N yr
1, and that the N2O emission rates range from 0.44 mg N m
2 h
1 to 4.87 mg N m
2 h
1 (total water surface area of 85,600 km2). Thus, the N2O emission rates of lakes on the ML-CRN (13.7 mg N m
2 h
1 to 31.7 mg N m
2 h
1) are higher than those of the rivers in the CRN. The amount of N2O emission from lakes on the ML-CRN is comparable with that from the rivers in the CRN. Combined global N2O emission data (Soued et al., 2016), approximately 0.73% of the N2O emissions from global lakes originated from lakes on the ML-CRN, which accounts for 0.39% of the total estimated global lake surface area. This evidence supports the hypothesis that lakes on the

Table 2 Average N2O emission rates and annual N2O emission from lakes on ML-CRN. Lakes

N input load (Gg N yr
1)

EF (%)

Annual N2O emission (Gg N yr
1)

Pub.b

0.783

24.1 ± 29.8

0.75 1.88 1.00 1.10 0.28

3.960 3.960 3.960 3.960 2.338

21.7 25.5 28.7 31.7 13.7

2016 e2017 23.0 ± 9.70 2013

0.51 ± 0.63 0.28

2.338

13.7

0.51 ± 0.63 0.54 0.51 ± 0.63 0.53 0.51 ± 0.63 0.43

2.740 2.740 1.851

22.3 22.1 26.8

1.40e3.24

11.672c

13.7e31.7 nd

1.98e4.58 0.33e3.65 627 ± 396

16.476d 85.600 4202

13.7e31.7 nd 0.44e4.87 3.85e75.5

820 ± 389

4560

References

Chaohu Lake

32.3 2016

Current study

0.51 ± 0.63 0.17 ± 0.20

Poyang Lake Poyang Lake Poyang Lake Poyang Lake Taihu Lake

147 172 194 215 54.8

Jia (2016) (Huang, 2018) Jia (2016) (Huang, 2018) Song et al. (2005) Song et al. (2005) Lu et al. (2017) Lu et al. (2017) Ji et al. (2014)

0.51 ± 0.63 0.51 ± 0.63 0.51 ± 0.63 0.51 ± 0.63 0.51 ± 0.63

Taihu Lake Dongting Lake Dongting Lake Hongze Lake The five largest lakes Changjiang Lakes Changjiang River Global Lakes Global inland water

N2O emission rates (mg N m
2 h
1) Cal.a

Input Year

2013 2013 2014 2014 2002 e2003 54.8 2002 e2003 105 2010 104 2014 84.7 2003 e2010

Lake area (103 km2)

Note: a Cal. is the abbreviation of “the calculated data based on the EF (0.51%) in this study”. b Pub. is the abbreviation of “published data”. c The total water area of five largest lakes in CRN. d This is the water area of lakes with the size larger than 1 km2 on ML-CRN (Dong et al., 2012).

Year

23.2 ± 19.3 2014 e2015 13.8 2003 13.2 ± 37.7 2003 e2004 nd nd nd

1.98e151

References Current study Wang et al. (2016) Xu et al. (2016) Wang et al. (2009) Wang et al. (2007)

Yan et al. (2012) Soued et al. (2016) Soued et al. (2016)

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Q. Li et al. / Environmental Pollution 255 (2019) 113212

ML-CRN are “hotspots” of N2O emissions both within the watershed and on a global scale, and highlight that the area deserves more attention in terms of the mitigation of N2O emissions. In addition, we found that less than 1% of N2O emissions from global inland water bodies were from lakes and rivers in the CRN, which accounts for approximately 2.24% of the estimated total surface area of global inland water bodies. 5. Conclusions The current study measured the isotopic compositions of dissolved N2O in a shallow eutrophic lake. Results show average values of 5.76 ± 3.90‰, 29.3 ± 13.4‰, and 18.6 ± 3.16‰ for d15N-N2O, d18ON2O, and SP, respectively. Evidence from water chemical parameters, sediment incubation experiments, and distribution patterns of N2O isotopic compositions (Fig. 4) demonstrate that nitrification and denitrification were the primary production processes. In addition, isotopic compositions of N2O were primarily affected by N2O consumption processes. d18O-N2O values were controlled by the effective isotopic exchange of oxygen from H2O to N2O during denitrification in the lake. SP data were also used for the quantified analysis of N2O production processes. Microbial processes dominated N2O production, accounting for approximately 76.8% to 79.9% of the total dissolved N2O. Dissolved N2O was primarily produced via nitrification and denitrification. N2O produced via nitrification accounted for 27.3% to 48.0% of the total dissolved N2O, and that produced via denitrification accounted for 31.9% to 49.5% of the total. A higher relative contribution of nitrification was expected in the non-algal growth season because of the weak competition between nitrification and NHþ 4 uptake. The average N2O emission rate was 27.5 ± 26.0 mg N m
2 h
1 and the estimated N2O emission factor was 0.51 ± 0.63% for the lake. We propose an EF of 0.51% as being reasonable for estimating N2O emissions from shallow eutrophic lakes. Lakes on the ML-CRN were “hotspots” for N2O emissions, on the scale of the watershed and globally, with estimated N2O emissions ranging from 1.98 Gg N yr
1 and 4.58 Gg N yr
1. We suggest that lakes deserve more attention for the regulation of N2O emissions from the CRN. Funding This study was supported by the National Key Research and Development Program of China (2016YFA0601004 and 2016YFA0602704); and the National Natural Science Foundation of China (41877483, 41371454, 41771050 and 41671479). Conflicts of interest The authors declare that they have no conflict of interest. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.envpol.2019.113212. References Seitzinger, S., Harrison, J.A., Bohlke, J.K., Bouwman, A.F., Lowrance, R., Peterson, B., Tobias, C., Van Drecht, G., 2006. Denitrification across landscapes and waterscapes: a synthesis. Ecol. Appl. 16, 2064e2090. https://doi.org/10.1890/10510761(2006),_016[2064:dalawa]2.0.co;2. Aufdenkampe, A.K., Mayorga, E., Raymond, P.A., Melack, J.M., Doney, S.C., Alin, S.R., Aalto, R.E., Yoo, K., 2011. Riverine coupling of biogeochemical cycles between land, oceans, and atmosphere. Front. Ecol. Environ. 9, 53e60. https://doi.org/10. 1890/100014. Beaulieu, J.J., Tank, J.L., Hamilton, S.K., Wollheim, W.M., Hall Jr., R.O., Mulholland, P.J.,

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