Historical development, impact mechanism and future trends of nitrogen footprint in Wuxi City, China.

Human activities have changed the biogeochemical cycle of nitrogen, leading to a large amount of reactive nitrogen (Nr) into the environment, aggravating a series of environmental problems, affecting human and ecosystem health. Cities are the core areas driving nitrogen cycling in terrestrial ecosystems, however, there are numerous influencing factors and their contributions are unclear. The nitrogen footprint is an important index to understand the impact of human activities on the environment, however, the calculation of urban nitrogen footprint needs a simplified and accurate system method. Here we use a nitrogen footprint calculation model at the urban system level based on system nitrogen balance, and a multi-factor extended STIRPAT (stochastic impact by regression on population, affluence, and technology) model suitable for analyzing the impact mechanism of nitrogen footprint to estimate nitrogen footprint of Wuxi City during 1990-2050. We find that: (1) from 1990 to 2020, the total nitrogen footprint of Wuxi City was in an increasing trend, but the per capita nitrogen footprint was in a decreasing trend. The per capita nitrogen footprint of 22.36 kg capita-1 in 2020 was at a lower level globally. (2) Nr discharge from fossil fuel combustion and Haber-Bosch nitrogen fixation accounted for the main proportion of nitrogen footprint. (3) Dietary choice (Ad), GDP per capita (Ag), urbanization rate (Au), population (P), and fossil energy productivity (Te) were the key factors contributing to the increase of the nitrogen footprint, which resulted in an annual increase of 1.39 %. While nitrogen footprint productivity (Tn), nitrogen use efficiency in crop farming (Tc), and nitrogen use efficiency in animal breeding (Ta) were the key inhibit factors that inhibit the increase of nitrogen footprint, and these factors slow down the annual growth rate of nitrogen footprint by 0.39 %. (4) The continuous growth of nitrogen footprint in the baseline and population growth scenarios will bring more environmental problems and greater environmental governance pressure to Wuxi City, while the sustainable scenario that includes comprehensive means such as economic adaptation and technological improvement is more in line with the requirements of high-quality development in China. Several mitigation measures are then proposed by considering Wuxi's realities from both key impact factors and potential for nitrogen footprint reduction in different scenarios, which can provide valuable policy insights to other cities, especially lakeside cities to mitigate nitrogen footprint.

Wetland Destruction in a Headwater River Leads to Disturbing Decline of In-stream Nitrogen Removal.

Wetlands have long been recognized as efficient nitrogen (N) processing systems. While widespread interest is in constructing wetlands to mitigate N pollution, there is a dearth of information about the environmental consequences following wetland dismantlement. This study elucidated the changing trajectories of water quality and N removal capacity in a headwater river that initially contained a series of constructed wetlands but later underwent wetland destruction. An estimated 17% surge in total N concentration has been reported since the wetlands' destruction. This adverse trend is primarily attributed to a weakened in-stream N removal capacity, which was reduced to a mere 25% of the levels observed when the wetlands were operational. Further analysis confirms that the presence of wetlands actively shapes desirable environmental settings for N processing. In stark contrast, wetland destruction leads to unfavorable environmental conditions, which not only restrain in-stream anaerobic metabolisms but also trigger algal proliferation and biological N fixation. Collectively, this research provides compelling evidence of the detrimental consequences associated with wetland destruction, emphasizing the need for remedial strategies to mitigate these negative effects.

Small ponds have stronger potential for net nitrogen removal: Insight from direct dissolved N2 measurement.

Growing demands for watershed nitrogen (N) removal have called attention to abundant small bodies of water such as ponds, which have long been heralded as efficient storage and processing systems. Although pond conservation, restoration, and creation have been widely implemented to mitigate N pollution, information is limited regarding the impact of size-that is, whether N removal potential and efficiency are dependent upon pond size. We investigated the dynamics of N removal rates in 56 ponds from a hilly watershed by studying their bimonthly N2 concentrations and fluxes. Our results showed that smaller ponds performed better in net N removal. This can be discerned from the areal N2 fluxes, which were the highest in small ponds (< 4, 000 m2). The corresponding N2 fluxes (4.73 ± 4.53 mmol N2 m-2 d-1) were 2 to 14 times greater than those observed in larger ponds. The N removal efficiency, a metric used to describe the portions of the substrates released as N2, was also significantly higher in the small ponds (∼8.7 %) than in the larger ponds (∼5.0 %). Further regression analysis showed that both areal N2 flux and N removal efficiency were negatively correlated with pond area. The underlying mechanisms behind the size effects of N removal could be attributed to small ponds having larger sediment contact area to water volume ratios. Thus, smaller ponds allow more opportunities for N to interact with bioactive sediments than larger ponds. Overall, our findings contribute to the understanding of the distal role of pond size in affecting N removal. This research also provides a strong rationale for considering the effects of system size when implementing management practices dedicated to maximizing N removal.

Sustainable nitrogen management strategies based on nitrogen flow in urban human system.

Urban nitrogen discharge has become an important factor leading to urban water environment deterioration, water crisis, and frequent air pollution. Human consumption is the driving force of nitrogen flow and the core of urban nitrogen research. Based on the process of nitrogen flow in the urban human system, combined with the relevant United Nations Sustainable Development Goals (SDGs) and taking Dar es Salaam as an example, we established a generic analytical framework for sustainable nitrogen management and put forward the strategies of sustainable nitrogen management in the urban human system. The main conclusions are as follows. (1) Waste nitrogen discharge affected the environment quality. 5286 t of N (5095 t of N-NH3, 86 t of N-N2O, and 105 t of N-NOx) was emitted into the atmosphere that affected air quality. 9304 t of N was discharged into surface water and 203 t of N was leaked, which had a negative impact on the prevention and control of surface water pollution. And 8334 t of N pose a potential threat to environmental quality. (2) Nitrogen management in Dar es Salaam faced huge challenges. From the perspective of nitrogen flow of the urban human system, the diet structure and household energy structure need to be optimized, and food waste is serious. Sewage treatment and garbage treatment are seriously insufficient, and the corresponding technologies are backward. In order to solve the existing problems of nitrogen flow in the urban human system and include sustainable nitrogen management under future challenges of growing population and economy, we proposed strategies including healthy diet guidance, reducing food waste, detailed assessment of household nitrogen accumulation, transformation of household energy structure to low nitrogen emission energy, increasing nitrogen recycling ratio, and infrastructure improvement of sewage treatment and garbage treatment, hence contributing to the achievement of related SDGs.

Examining key impact factors of energy-related carbon emissions in 66 Belt and Road Initiative countries.

Climate change with global warming as the main feature associated with fossil energy use has been recognized as a threat to public health and welfare. Energy-related carbon emission reduction is a more serious challenge for BRI (Belt and Road Initiative) countries with rapid economic development. Examining key impact factors is necessary and helpful. This paper is the first study providing detailed country-by-country analyses aiming to identify the key drivers and inhibitors of energy-related carbon emission in 66 BRI countries with more systematic impact factors. The results show that: (1) Economic development (A), population (Ps), urbanization (Pu), and industrialization (Ss) are the key drivers for 52%, 26%, 11%, and 6% countries of BRI countries. Technological progress (T), energy consumption structure (E), and tertiary industry proportion (St) serve as key inhibitors for 65%, 17%, and 8% countries of BRI countries. (2) Different carbon emission reduction strategies should be formed on different geographical scales. At the international level, carbon emission reduction consensus should be reached and carbon emission reduction targets should be formulated. At the regional level of the Belt and Road Initiative, a carbon emission reduction cooperation fund should be established, and carbon emission reduction technologies and measures should be exchanged and data should be shared to promote the green development of the Belt and Road. At the national level, there should be carbon emission reduction policies reflecting national characteristics. At the local level, there should be specific carbon reduction measures in line with local conditions.

Reactive nitrogen budgets in human-nature coupling system in lakeside area with insufficient data - A case study of Mwanza, Tanzania.

Nitrogen (N) is an essential nutrient element for life, and also a major element involved in the composition of greenhouse gases, surface water pollutants, air pollutants, etc. Quantifying and evaluating the nitrogen budget of a region is very important for effectively controlling the nitrogen discharge and scientifically managing the nitrogen cycle. In this paper, the urban Rural Complex N Cycling (URCNC) model was used to analyze the nitrogen budget of Mwanza region, a typical lakeside area with insufficient data, and the nitrogen flow process of livestock subsystem, cropland subsystem, human subsystem and landfill subsystem was clearly described and the nitrogen input sources of atmospheric subsystem and surface water subsystem were clarified. And the results demonstrated: (1) the cropland subsystem was the subsystem with the largest nitrogen flux, and the input, output and accumulation of nitrogen were 33,116 t of N, 31,925 t of N and 1191 t of N, respectively. Livestock subsystem was the second largest subsystem of nitrogen flux, and the input, output and accumulation of nitrogen were 31,013 t, 30,183 t and 830 t, respectively. The nitrogen flux of the human subsystem was also large, and the nitrogen input, output and accumulation were 17,905, 17,125 and 780 t, respectively. The nitrogen input, output and accumulation of the landfill subsystem were 3700 t, 770 t and 2930 t, respectively. (2) 8093 t of N, 6864 t of N, 3959 t of N, and 758 t of N emitted into the atmospheric subsystem from the livestock subsystem, cropland subsystem, human subsystem, and landfill subsystem, respectively. (3) The total Nr input of surface water subsystem increased from 18,545 t of N in 2010 to 20,174 t of N in 2020, with an increase of 8.78 % in the past decade. It was estimated that by 2030, the total Nr input of the surface water subsystem would reach 24,946 t of N with an increase of 23.65 % compared with 2020. The livestock subsystem was the largest source, the cropland subsystem was the second largest source and human subsystem was an important source. (4) Population growth, economic development and urbanization are the main nitrogen driving factor. (5) Technology and policy together have important contributions to the reduction of nitrogen pollution in surface water.

Strong variability in nitrogen (N) removal rates in typical agricultural pond from hilly catchment: Evidence from diel and monthly dissolved N2 measurement.

Ponds, depressional submerged landscapes that can store and process nitrogen (N)-enriched runoff from surrounding uplands, are recognized as biogeochemical hotspots for N removal. Despite their strong potential for N removal, information is limited concerning the specifics of their changing nature. Here, we investigated the dynamics of N removal rate in a typical agricultural pond from a hilly catchment, by unraveling the monthly and diel patterns of N2 concentrations and fluxes. Our observations showed that the N pollution in the pond was severe. Its averaged total N level reached 3.6 mg L-1, of which ∼72% consisted of NO3-N. Meanwhile, the water samples were supersaturated with N2, demonstrating N removal occurring in the pond. Further estimates of net N2 fluxes indicated that N removal rates exhibited obvious day-and-night and monthly differences. On the diel scale, N removal rates exhibited a distinct diurnal cycle, with nocturnal rates around 20% higher than during the day. Such a diel pattern can be mainly explained by the fluctuation in DO levels, showing that at nighttime when photosynthesis is absent, low DO environments are conducive to N removal. On a monthly scale, the monthly rates ranged from 0.02 to 0.49 mmol N2 m-2 h-1 (mean: 0.23 mmol N2 m-2 h-1), with generally higher removal rates in the warmer and concurrently rainy months (June-September). N levels in the pond were the corresponding primary explanatory variables. Assembled data from both monthly and hourly scales provided a more complete picture of the changing nature of N removal in ponds. Future work should carefully consider the effects of altered environmental conditions triggered by hydrological events to better reveal the control mechanisms behind the time-immediate N removal from lowland ponds.

Decoding river pollution trends and their landscape determinants in an ecologically fragile karst basin using a machine learning model.

Karst watersheds accommodate high landscape complexity and are influenced by both human-induced and natural activity, which affects the formation and process of runoff, sediment connectivity and contaminant transport and alters natural hydrological and nutrient cycling. However, physical monitoring stations are costly and labor-intensive, which has confined the assessment of water quality impairments on spatial scale. The geographical characteristics of catchments are potential influencing factors of water quality, often overlooked in previous studies of highly heterogeneous karst landscape. To solve this problem, we developed a machining learning method and applied Extreme Gradient Boosting (XGBoost) to predict the spatial distribution of water quality in the world's most ecologically fragile karst watershed. We used the Shapley Addition interpretation (SHAP) to explain the potential determinants. Before this process, we first used the water quality damage index (WQI-DET) to evaluate the water quality impairment status and determined that CODMn, TN and TP were causing river water quality impairments in the WRB. Second, we selected 46 watershed features based on the three key processes (sources-mobilization-transport) which affect the temporal and spatial variation of river pollutants to predict water quality in unmonitored reaches and decipher the potential determinants of river impairments. The predicting range of CODMn spanned from 1.39 mg/L to 17.40 mg/L. The predictions of TP and TN ranged from 0.02 to 1.31 mg/L and 0.25-5.72 mg/L, respectively. In general, the XGBoost model performs well in predicting the concentration of water quality in the WRB. SHAP explained that pollutant levels may be driven by three factors: anthropogenic sources (agricultural pollution inputs), fragile soils (low organic carbon content and high soil permeability to water flow), and pollutant transport mechanisms (TWI, carbonate rocks). Our study provides key data to support decision-making for water quality restoration projects in the WRB and information to help bridge the science:policy gap.

Direct measurements of dissolved N2 and N2O highlight the strong nitrogen (N) removal potential of riverine wetlands in a headwater stream.

Increasing levels of nitrogen (N) in aquatic ecosystems due to intensified human activities is focusing attention on N removal mechanisms as a means to mitigate environmental damage. Important N removal processes such as denitrification can resolve this issue by converting N to gaseous emissions. Here, the spatiotemporal variability of N removal rates in China's Zhongtian River, a headwater stream that contains wetlands, was investigated by quantifying gaseous emissions of the main end products, N2 and N2O, using the water-air exchange model. Excess concentrations of these gases relative to their saturations in the water column generally varied within 1.4-8.7 µmol L-1 and 8.7-20.3 nmol L-1, with mean values of 4.5 µmol L-1 and 13.7 nmol L-1, respectively, demonstrating significant N removal in the river. The reach with wetlands was characterized by higher in-stream N2 production than the non-wetland reach, especially in July, when aquatic vegetation is most abundant. High N2O emissions during the same period in the non-wetland reach indicate that environmental conditions associated with vegetation are conducive to N2 production and likely constrain N2O emission. Changes in dissolved oxygen, pH, temperature, and carbon to nitrogen ratios are correlated with the observed spatiotemporal variabilities in gaseous N production. The mean N removal rate in the wetland reach was roughly twice that in the non-wetland reach, i.e., 22.4 vs. 10.3 mmol N m-2 d-1, while the corresponding efficiency was about five times as high, i.e., 15 % vs. 3 %. This study reveals the spatiotemporal patterns of in-stream N removal in a headwater stream and highlights the efficacy of wetlands in N removal. The data provide a strong rationale for constructing artificial wetlands as a means to mitigate N pollution and thereby optimize riverine environmental conditions.

Influencing mechanism of non-CO2 greenhouse gas emissions and mitigation strategies of livestock sector in developed regions of eastern China: a case study of Jiangsu province.

The livestock sector not only provides people with meat, eggs, milk, and other nutrients but also causes a large number of non-CO2 greenhouse gas emissions. It is urgent to explore the influence mechanism of non-CO2 greenhouse gas emission from the livestock sector and formulate effective mitigation strategies. Taking Jiangsu province as an example, we analyzed the influencing factors of non-CO2 greenhouse gas emissions from the livestock sector based on sources and modified the STIRPAT (stochastic impact by regression on population, affluence, and technology) model, proposed the directions, designed the generally circular path, and determined the focus of non-CO2 greenhouse gas emissions reduction from the livestock sector. The results demonstrated: (1) the top priority of emission reduction of livestock sector in Jiangsu province was the reasonable treatment of manure produced by livestock (non-CO2 greenhouse gas emissions from manure had accounted for more than 60% of the total emissions from the livestock sector since 2007.), and the core was pig manure management (the CH4 and N2O emissions from pig manure accounted for more than 90 and 50% of the total CH4 and N2O emissions from all livestock manure, respectively). (2) The decrease of the agricultural population, the increase of livestock output value per capita of the agricultural population, and the improvement of livestock carbon productivity all reduced non-CO2 greenhouse gas emissions of the livestock sector. For every 1% decrease in agricultural population, for every 1% increase in livestock carbon productivity and livestock output value per capita of the agricultural population, non-CO2 greenhouse gas emissions from the livestock sector would be reduced by 0.0859%, 0.1748%, and 0.0400%, respectively. (3) To construct and improve the low carbon industrial chain of the livestock sector, to promote low carbon technology research and development and introduction are two focuses for non-CO2 greenhouse gas emission reduction in the livestock sector. The research can provide a basis for non-CO2 greenhouse gas emissions reduction from the livestock sector in China, especially in the developed eastern regions.

Rivers draining contrasting landscapes exhibit distinct potentials to emit diffusive methane (CH4).

Methane (CH4) is the second most important greenhouse gas, contributing approximately 17% of radiative forcing, and CH4 emissions from river networks due to intensified human activities have become a worldwide issue. However, there is a dearth of information on the CH4 emission potentials of different rivers, especially those draining contrasting watershed landscapes. Here, we examined the spatial variability of diffusive CH4 emissions and discerned the roles of environmental factors in influencing CH4 production in different river reaches (agricultural, urban, forested and mixed-landscape rivers) from the Chaohu Lake Basin in eastern China. According to our results, the urban rivers most frequently exhibited extremely high CH4 concentrations, with a mean concentration of 5.46 µmol L-1, equivalent to 4.1, 9.7, and 7.2 times those measured in the agricultural, forested, and mixed-landscape rivers, respectively. The availability of carbon sources and total phosphorus were commonly identified as the most important factors for CH4 production in agricultural and urban rivers. Dissolved oxygen and oxidation-reduction potential were separately discerned as important factors for the forested and mixed-landscape rivers, respectively. Monte Carlo flux estimations demonstrated that rivers draining contrasting landscapes exhibit distinct potentials to emit CH4. The urban rivers had the highest CH4 emissions, with a flux of 9.44 mmol m-2 d-1, which was 5.1-10.4 times higher than those of the other river reaches. Overall, our study highlighted that management actions should be specifically targeted at the river reaches with the highest emission potentials and should carefully consider the influences of different riverine environmental conditions as projected by their watershed landscapes.

Restored riverine wetlands in a headwater stream can simultaneously behave as sinks of N2O and hotspots of CH4 production.

Wetlands can improve water quality, but they are also recognized as important sources of greenhouse gases (GHG) such as nitrous oxide (N2O) and methane (CH4). Emissions of these gases from wetland ecosystems, especially those in headwaters, are poorly understood. Here, we determined monthly concentrations of dissolved N2O and CH4 in a headwater stream of the Taihu Lake basin of China that contains both wetland and non-wetland reaches. Daily GHG dynamics in the wetland reach were also investigated. Riverine N2O and CH4 concentrations generally varied within 10-30 nmol L-1 and 0.1-1.5 µmol L-1, respectively. CH4 saturation levels in the wetland reach were about seven times higher than those in the non-wetland reach, but there was no difference in N2O saturation. In the wetland reach, saturation levels of CH4 peaked in July, coincident with a dip in N2O saturation to levels below its saturated solubility. This underscores that hotspots of CH4 production and sinks for N2O can occur occasionally in wetlands in mid-summer, when vegetative growth and microbial activities are high. Diurnal measurements indicated that CH4 saturation in water flows passing through the wetlands from midnight through the early morning can surge to levels 10 times higher than those detected at other times of the day. Simultaneously, saturation levels of N2O decreased by 75%, indicating a net consumption of N2O. Changes in nutrient supply determined by upstream inflows, as well as dissolved oxygen, pH, and other environmental factors mediated by the wetlands, correlate with the differentiated behavior of N2O and CH4 production in wetlands. Additional work will be necessary to confirm the roles of these factors in regulating GHG emissions in riverine wetlands.

Urban rivers are hotspots of riverine greenhouse gas (N2O, CH4, CO2) emissions in the mixed-landscape chaohu lake basin.

Growing evidence shows that riverine networks surrounding urban landscapes may be hotspots of riverine greenhouse gas (GHG) emissions. This study strengthens the evidence by investigating the spatial variability of diffusive GHG (N2O, CH4, CO2) emissions from river reaches that drain from different types of landscapes (i.e., urban, agricultural, mixed, and forest landscapes), in the Chaohu Lake basin of eastern China. Our results showed that almost all the rivers were oversaturated with dissolved GHGs. Urban rivers were identified as emission hotspots, with mean fluxes of 470 µmol m-2d-1 for N2O, 7 mmol m-2d-1 for CH4, and 900 mmol m-2d-1 for CO2, corresponding to ~14, seven, and two times of those from the non-urban rivers in the Chaohu Lake basin, respectively. Factors related to the high N2O and CH4 emissions in urban rivers included large nutrient supply and hypoxic environments. The factors affecting CO2 were similar in all the rivers, which were temperature-dependent with suitable environments that allowed rapid decomposition of organic matter. Overall, this study highlights that better recognition of the influence that river networks have on global warming is required-particularly when it comes to urban rivers, as urban land cover and populations will continue to expand in the future. Management measures should incorporate regional hotspots to more efficiently mitigate GHG emissions.

[Spatiotemporal Variations in Nutrient Loads in River-lake System of Changdang Lake Catchment in 2016-2017].

Eutrophication of shallow lakes in the middle and lower reaches of the Yangtze River has become an increasingly serious problem. In this study, we investigated the temporal and spatial variations in nutrient loads (nitrogen, N and phosphorus, P) in the Changdang Lake Catchment located to the northwest of Lake Taihu through field sampling and laboratory analysis in 2016-2017. The results show the severity of the N and P pollution in the Changdang Lake catchment. The mean river water concentrations of TN, NO3--N, NH4+-N, TP, Chla, and permanganate index are (3.70±0.76) mg ·L-1, (1.81±0.42) mg ·L-1, (1.03±0.61) mg ·L-1, (0.38±0.31) mg ·L-1, (25.74±37.00) µg ·L-1, and (6.35±0.81) mg ·L-1, respectively. N pollution in the river is more severe in winter and spring than in summer and autumn whereas P pollution in the river is worse in autumn and winter than in spring and summer. Spatially, the magnitude of river N and P pollution follows the order of northern > northwestern > southern > eastern part of the study area. The rivers are in a state of moderate to severe eutrophication. The mean lake water concentrations of TN, NO3--N, NH4+-N, TP, Chla, and permanganate index are (2.25±0.94) mg ·L-1, (0.98±0.47) mg ·L-1, (0.19±0.14) mg ·L-1, (0.11±0.03) mg ·L-1, (18.71±8.76) µg ·L-1, and (4.59±1.09) mg ·L-1, respectively. The water quality in Changdang Lake is categorized as worse than class Ⅲ for TN and TP concentrations, which show decreasing trends from the west to the east to the south of the lake. The lake is in a status of slight to moderate eutrophication. The lake water quality is affected by the combination of sewage discharge and non-point source pollutant losses. The inflow rivers including the Danjinlicao River, Tongji River, and Xuebu River are the dominant pollution sources for Changdang Lake. The Danjinlicao River transports 10-12 times the total N and P loads transported by Tongji and Xuebu rivers. Changes in land use and atmospheric deposition are the driving factors of the deterioration of water quality and eutrophication in the catchment.

Remotely monitoring ecosystem respiration from various grasslands along a large-scale east-west transect across northern China.

BACKGROUND: Grassland ecosystems play an important role in the terrestrial carbon cycles through carbon emission by ecosystem respiration (Re) and carbon uptake by plant photosynthesis (GPP). Surprisingly, given Re occupies a large component of annual carbon balance, rather less attention has been paid to developing the estimates of Re compared to GPP. RESULTS: Based on 11 flux sites over the diverse grassland ecosystems in northern China, this study examined the amounts of carbon released by Re as well as the dominant environmental controls across temperate meadow steppe, typical steppe, desert steppe and alpine meadow, respectively. Multi-year mean Re revealed relatively less CO2 emitted by the desert steppe in comparison with other grassland ecosystems. Meanwhile, C emissions of all grasslands were mainly controlled by the growing period. Correlation analysis revealed that apart from air and soil temperature, soil water content exerted a strong effect on the variability in Re, which implied the great potential to derive Re using relevant remote sensing data. Then, these field-measured Re data were up-scaled to large areas using time-series MODIS information and remote sensing-based piecewise regression models. These semi-empirical models appeared to work well with a small margin of error (R2 and RMSE ranged from 0.45 to 0.88 and from 0.21 to 0.69 g C m-2 d-1, respectively). CONCLUSIONS: Generally, the piecewise models from the growth period and dormant season performed better than model developed directly from the entire year. Moreover, the biases between annual mean Re observations and the remotely-derived products were usually within 20%. Finally, the regional Re emissions across northern China's grasslands was approximately 100.66 Tg C in 2010, about 1/3 of carbon fixed from the MODIS GPP product. Specially, the desert steppe exhibited the highest ratio, followed by the temperate meadow steppe, typical steppe and alpine meadow. Therefore, this work provides a novel framework to accurately predict the spatio-temporal patterns of Re over large areas, which can greatly reduce the uncertainties in global carbon estimates and climate projections.

Surface nitrous oxide (N2O) concentrations and fluxes from different rivers draining contrasting landscapes: Spatio-temporal variability, controls, and implications based on IPCC emission factor.

Increasing indirect nitrous oxide (N2O) emission from river networks as a result of enhanced human activities on landscapes has become a global issue, as N2O has been widely recognized as an important ozone-depleting greenhouse gas. However, indirect N2O emissions from different rivers, particularly for those that drain completely different landscapes, are poorly understood. Here, we investigated the spatial-temporal variability of N2O emissions among the different rivers in the Chaohu Lake Basin of Eastern China. Our results showed that river reaches in urban watersheds are the hotspots of N2O production, with a mean N2O concentration of ∼410 nmol L-1, which is 9-18 times greater than those mainly draining forested (23 nmol L-1), agricultural (42 nmol L-1) and mixed (45 nmol L-1) landscapes. Riverine dissolved N2O was generally supersaturated with respect to the atmosphere. Such N2O saturation can best be explained by nitrogen availability, except for those in the forested watersheds, where dissolved oxygen is thought to be the primary predictor. The estimated N2O fluxes in urban rivers reached ∼471 µmol m-2 d-1, a value of ∼22, 13, and 11 times that in forested, agricultural and mixed watersheds, respectively. Averaged riverine N2O emission factors (EF5r) of the forested, agricultural, urban and mixed watersheds were 0.066%, 0.12%, 0.95% and 0.16%, respectively, showing different deviations from the default EF5r that released by IPCC in 2019. This points to a need for more field measurements with wider spatial coverage and finer frequency to further refine the EF5r and to better reveal the mechanisms behind indirect N2O emissions as influenced by watershed landscapes.

Influence of land use and rainfall on the optical properties of dissolved organic matter in a key drinking water reservoir in China.

The concentration, source and composition of dissolved organic matter (DOM) in aquatic ecosystems are associated with land use and hydrological connectivity between terrestrial and aquatic systems. However, direct evidence of the effects of rainfall and land use on the variability of DOM in aquatic ecosystems is very limited. In this study, chromophoric DOM (CDOM) absorption and fluorescence spectroscopy were used to elucidate how rainfall and land use affect the variability of CDOM in the watershed of Lake Tianmu, a key drinking water reservoir in the Yangtze River Delta. The mean values of the fluorescence intensity (Fmax) of parallel factor analysis-derived humic-like components (C1, C3, C6) and tryptophan-like components C5 were higher in the southeastern inflowing river mouths than those downstream of the lake outlet regions. The upstream tributaries were mainly dominated by humic-like materials, while the lake was mainly dominated by protein-like materials. The Fmax values of four humic-like components and two tryptophan-like components all increased significantly as the %woodland decreased, but %anthropogenic land use (%cropland+%urban construction area) increased. The Fmax of the humic-like components at the inflowing tributaries and the lake increased with increasing rainfall during storm events, and the value was especially pronounced at the inflowing river mouths. We concluded that land use and hydrological conditions play an important role in influencing the CDOM source and optical composition, and these findings provide insights for the understanding of aquatic ecosystem metabolism and reservoir water quality management.

Differences in the responses of flow and nutrient load to isolated and coupled future climate and land use changes.

Understanding the differences in the responses of river hydrology and water quality to climate and land use changes is particularly crucial for the development and management of water resources in the future. This study was carried out to assess the isolated and coupled effects of future climate change and land use change on the flow and nutrient load of the Xitiaoxi watershed in southeast China by applying the calibrated Hydrological Simulation Program Fortran model. Four representative concentration pathways released by the Intergovernmental Panel on Climate Change and two projected land use change scenarios were used to simulate future conditions. The results indicate that climate change would result in flow increased with an average variation of 25.2% in the future, and the increased flow would be mainly concentrated on the high flow part of the total flow duration curve. Climate change would also induce seasonal shifts to nutrient load. The effects of land use change showed that nutrient load was more sensitive than flow, made Orthophosphate load increase by 2.8%-154.7%, and flow increase by 7.2%-15.1%. The results for coupled climate and land use changes indicate that flow and nutrient load would be more affected by climate change than by land use change. Climate and land use changes may amplify or weaken each other's effects on flow and nutrient load, which suggests that both should be incorporated into hydrologic models when studying the future conditions. The results of this study can help decision-makers guide management practices that aim to minimize flow and nutrient load.

Modeling phosphorus sources and transport in a headwater catchment with rapid agricultural expansion.

Increasing riverine phosphorus (P) levels in headwaters due to expanded and intensified human activities are worldwide concerns, because P is a well-known limiting nutrient for freshwater eutrophication. Here we adopt the conceptual framework of the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model to describe total phosphorus (TP) sources and transport in a headwater watershed undergoing rapid agricultural expansion in the upper Taihu Lake Basin, China. Our models, which include variables for land cover, river length, runoff depth, and pond density, explain 94% of the spatio-temporal variability in TP loads. Agricultural lands contribute the largest percentage (61%) of the TP loads delivered downstream, followed by forestland (21%) and urban land (18%). Future agricultural expansion to 15% of the total basin area is possible, which could lead to a 50% increase in TP loads. According to our analysis, an average of 24% of the total P export from the watershed landscape was intercepted in ponds. The exported amount was subsequently retained by tributaries and along the mainstem river, accounting for 14% and 43% of their inflowing loads, respectively. The remaining ∼6 tons yr-1 of TP was eventually transported into Tianmu Lake, in Southeastern China. The model identified several sub-catchments as hotspots of TP loss and thus logical sites for targeted management. Our study underscores the significance of agricultural expansion as a factor that can exacerbate headwater TP pollution, highlighting the importance of landscapes to buffer TP losses from sensitive hilly catchments. This also points to a need for an integrated management strategy that considers the spatial-varying P sources and associated transport of TP in precious headwater resources.

Carbon dynamics and environmental controls of a hilly tea plantation in Southeast China.

Tea plantations are widely distributed and continuously expanding across subtropical China in recent years. However, carbon flux exchanges from tea plantation ecosystems are poorly understood at the ecosystem level. In this study, we use the eddy covariance technique to quantify the magnitude and temporal variations of the net ecosystem exchange (NEE) in tea plantation in Southeast China over four years (2014-2017). The result showed that the tea plantation was a net carbon sink, with an annual NEE that ranged from -182.40 to -301.51 g C/m2, which was a much lower carbon sequestration potential than other ecosystems in subtropical China. Photosynthetic photon flux density (PPFD) explained the highest proportion of the variation in NEE and gross primary productivity (GPP) (for NEE: F = 389.89, p < .01; for GPP: F = 1,018.04, p < .01), and air temperature (Ta) explained the highest proportion of the variation in ecosystem respiration (RE) (F = 13,141.81, p < .01). The strong pruning activity in April not only reduced the carbon absorption capacity but also provided many plant residues for respiration, which switched the tea plantation to a carbon source from April to June. Suppression of NEE at higher air temperatures was due to the decrease in GPP more than the decrease in RE, which indicated that future global warming may transform this subtropical tea plantation from a carbon sink to carbon source.