From Production to Consumption: A Coupled HumanâEnvironmental

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From production to consumption: A coupled humanenvironmental nitrogen flow analysis in China Zhibo Luo, Shanying Hu, Dingjiang Chen, and Bing Zhu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03471 • Publication Date (Web): 30 Jan 2018 Downloaded from http://pubs.acs.org on January 30, 2018

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Environmental Science & Technology

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From production to consumption: A coupled human-

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environmental nitrogen flow analysis in China

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Zhibo Luo§, Shanying Hu∗,§, Dingjiang Chen§, Bing Zhu§

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§ Center for Industrial Ecology, Department of Chemical Engineering, Tsinghua University, Beijing 100084,

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China

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*Corresponding email: [email protected]

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ABSTRACT

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Anthropogenic inputs of reactive nitrogen (Nr) provide sufficient food, energy and industrial products to meet human

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demands; however, only a fraction of Nr is consumed as food and nonfood goods, and the rest is lost to the

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environment and negatively affects ecosystems. High-resolution studies of nitrogen flows are invaluable to increase

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nitrogen use efficiencies and reduce environmental emissions. In this study, a comprehensive substance flow analysis

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of nitrogen for China in 2014 is presented. Based on the conceptual framework, which highlights the key roles of

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human drivers, the analysis of the synthetic ammonia supply and demand balance shows that 75% of ammonia is used

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for agricultural purposes. Moreover, the life cycle analysis of food nitrogen shows that human food consumption

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accounts for approximately 7% of the total Nr inputs. A quantitative analysis of pollutant emissions shows that

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industrial and crop production are the main sources of atmospheric emissions, while livestock farming and crop

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production are the main sources of water emissions. Finally, we investigate four scenarios (efficiency improvement,

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high recycling rate, nitrogen oxide emission reduction and a combined scenario) and provide relevant policy

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recommendations (large farm size, standardized agricultural production model, flue gas denitration, etc.) for improving

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nitrogen management practices.

ACS Paragon Plus Environment


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22 TOC Art

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INTRODUCTION

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Nitrogen (N) is one of the most important elements in natural ecosystems and is the main factor that influences the

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species composition, diversity, functions and dynamic change of ecoystems1, 2. Because N is related to different kinds

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of biochemical reactions and compound forms, it is difficult to accurately measure and quantify, thereby affecting the

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large-scale estimations and simulations3, 4. Before the 20th century, N was naturally cycled and regulated during the

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operation of natural ecosystems by biological N fixation (BNF), lightning N fixation (LNF), N deposition and

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denitrification4, 5. Since the invention of Haber-Bosch nitrogen fixation (HBNF), a large amount of reactive N (all N

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species other than N2, Nr) has been added to terrestrial ecosystems (an increase of 14 times from 1890 to 20106) to

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ensure global food security and meet the food demands of approximately 48% of the world population7, 8. Such

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processes have greatly altered the N cycles in terrestrial ecosystems and marine ecosystems5, 9, 10.

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The Nr cascade effect also creates various environmental problems11-13, such as nitrate enrichment in groundwater14,

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freshwater eutrophication15, air pollution16 (photochemical smog and particulate matter), stratospheric ozone

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depletion17, loss of biodiversity18, climate change19 and the deterioration of coastal ecosystems20, which have seriously

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threatened human health and safety21. Some scholars believe that N pollution is the third largest environmental problem

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in the world following biodiversity reduction and global warming21-24.

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With population growth and urbanization, China has become the largest Nr producer and consumer in the world25-27.

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The problems of accelerated Nr creation and emission (e.g., lake water eutrophication14, 15, haze and nitrogen oxide

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emissions16, etc) in China have posed important and growing impacts to human and ecosystem health28. Thus, efficient


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resource management, including the reduction of Nr losses and improvement of the Nr use efficiencies across different

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sectors of the Nr nexus, is key to securing food production and reducing environmental pressure in China29, 30.

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To map the potential of the recovery and reuse of Nr, high-resolution information regarding Nr streams is critical.

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Substance flow analysis31 (SFA) allows for the quantification of Nr flows throughout processes driven by human

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consumption, and the approach can identify Nr hot spots and losses to the environment; thus, SFA provides an

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important tool for the transition toward sustainable Nr management. Moreover, the input of anthropogenic Nr is mainly

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required to meet human demands for food, energy and nonfood goods26; therefore, highlighting the key roles of human

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consumption is particularly important32, 33. These human drivers are critical regulators of Nr flows and the associated

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spatial interactions, as the environmental system is most directly affected by anthropogenic perturbations4, 21, 34. The

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conceptual framework of an “N footprint” was developed to provide a tool to determine the contribution of an entity to

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Nr losses to the environment from personal resource uses26, 35. The N footprint has become a well-established method

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for describing how human activities impose various types of burdens and impacts on the life support systems of Earth

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and showing how changing behavior patterns have altered Nr losses in recent years26, 36-39. The underlying calculation

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methods and corresponding indicators for the N footprint method have gained increasing public attention and been

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applied at several scales37, 40-44.

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The previous large-scale studies of N flows have mainly focused on specific aspects of the nutrient chain41, 42, 45, 46,

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industrial systems47, 48 or environmental impacts49, 50, and in-depth studies of the historical trends of several major N

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flows (e.g., HBNF, BNF, LNF and fossil fuel combustion) have been performed at global5, national27 and regional51

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scales; however, a holistic and detailed approach is still lacking. Notably, the current N footprint model is a bottom-up

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calculation approach that is mainly based on personal estimates of food and energy consumption, and industrial

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products and non-food agricultural products are not considered in the model35. The research on N metabolism from a

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limited perspective will ignore some of the sudden hot spots and new pollution sources, such as the rapid growth of

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industrial N emissions in China in recent years19, which will result in a missed opportunity to guard against these

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becoming sources of pollution in the future. Therefore, it is particularly important to provide high-quality data

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acquisition and detailed analysis that can form an interesting tool for the transition towards sustainable N management.

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The primary purposes of this study are to develop a new coupled human-environmental N cycle model at the national



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scale and then use this model to assess and quantify the contributions of different N sources to the overall N pollution

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in China. The model core is based on the human drivers of N metabolism and the associated effects on various

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subsystems. This study is beneficial for understanding N trends and proposing effective policy measures (Fig. 1).

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We conducted an N balance analysis from the perspective of consumption, including a supply and demand balance

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analysis of synthetic ammonia and a life cycle analysis of food-based N. Then, the impact of the N flow process on the

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environment was quantitatively estimated. In addition, we investigated future agricultural, industrial and waste

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management scenarios that could minimize total N emissions while meeting N production demands. Finally, we

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provide suggestions to improve the N management practices and reduce the N losses from the environment in China.

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These methods and results can function as decision support tools in other nutrient intensive regions.

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METHODS

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Model Description

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In this study, the national N cycle based on human-environmental coupling (Fig. 1) is divided into six subsystems:

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industry, agriculture, human consumption, waste management, the atmosphere and the hydrosphere (excluding the

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ocean). The agricultural subsystem is subdivided into five modules: cropland, grassland, livestock, forest and

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aquaculture. The industrial subsystem includes energy production, food industry, feed industry, chemical industry,

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process transportation and other industries. The human consumption subsystem is defined as the consumption of food,

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energy, and nonfood goods, which is a node that helps to understand the relationship between biological communities

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and the physical environment. The main features of the waste management subsystem are industrial digester,

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incineration, landfill, wastewater treatment, manure processing and secondary composting. The atmospheric and

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hydrological subsystems are mainly used to quantify the N stock and its cascade effect. Each subsystem can be viewed

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as a dynamic system and an N reservoir. The N balance framework involves processes, flows, assumptions and

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calculations for each subsystem, as described in the supporting information. Based on the law of the conservation of

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mass, the N balance is given in Eq. 1. The N input and output elements include both new (e.g., HBNF and BNF

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induced by cultivation) and recycled Nr (e.g., manure N and straw N). The results are aggregated to the national level

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to analyze the Nr fate and flux across subsystems throughout the country.


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95 96 97


∑ ∑ ∑

[Eq. 1]

where and represent the different N flow inputs and outputs, respectively.

represents the different N accumulations. The detailed calculations for each subsystem are shown in the supporting information.

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Figure 1. Coupled human-environmental N cycle model in China at the national scale, with 2014 as an example. The units

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are Tg N yr-1 (1 Tg = 106 t).



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Data Resources

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The main data sources used in the model of the national N cycle are as follows: (1) a number of national statistical

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databases for 2014; (2) national resource survey statistics for 2014, such as rural and urban populations and forest,

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grassland and lake resource information; and (3) the statistics, parameters and methodologies available in the existing

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literature. A detailed description of the data resources and an uncertainty analysis are given in the supporting

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information.

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Scenarios for the Potential Reduction of Waste N

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We treated the total N emissions estimated in this study, including gas emissions and water emissions, as a baseline

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scenario. In addition to the baseline scenario, we established four scenarios to study the potential for the reduction of

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total waste N emissions (a detailed description is provided in the supporting information).

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Scenario S1: Efficiency improvement. In this scenario, we suggest improved N use efficiency in the agricultural

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subsystem. These improvements focus on large farms (N fertilization can be reduced by approximately 40% for an

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average farm size of 36.6 ha52), fertilization methods (issuing conventional fertilization recommendations for specific

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farming systems; the average fertilization intensity of N fertilizer was reduced to 130 kg/ha53) and a new form of N

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fertilizer (which increases N fertilizer utilization by 8%54).

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Scenario S2: High recycling rate. This scenario reflects a change in the N recycling rate. We assumed that the

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manure (including human and livestock excretions) and straw waste recycling rates reached the current optimal levels

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worldwide52, 55, 56, and the specific values were as follows: livestock excretion recycling ratio of 80%, human excretion

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recycling ratio of 50% and straw recycling ratio of 100%.

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Scenario S3: Nitrogen oxide emission reduction. Industrial flue gas denitration technology (assuming that 90% of

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industrial flue gas is removed by selective catalytic reduction (SCR)57-59 and selective non-catalytic reduction (SNCR)

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denitration technologies60), motor vehicle denitration plants (assuming that 90% of the motor vehicle exhaust is treated

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with denitration techniques61) and clean energy alternatives to fossil fuels (assuming that 30% of fossil fuels are

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replaced by new energy sources62, 63) are proposed in this scenario.

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Scenario S4: Combined scenario. This scenario combines all the measures implemented in scenarios S1, S2, and S3.

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By subtracting the overlapping portions of the measures in each scenario, the total emissions of waste N in the

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combined scenario can be obtained.


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RESULTS

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Analysis of the N Balance in an Integrated Human Consumption-Driven System

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We combined the industry, agriculture, human consumption, and waste management subsystems into an integrated

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system driven by human consumption, which is conducive to understanding the creation, consumption and emissions of

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Nr. In addition, the atmospheric and hydrological subsystems are environmental systems that are used to assess the

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environmental impact of N cycling in the context of human disturbances. Figure 2a shows the Nr inputs and outputs of

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the integrated system, and the larger lines represent the larger Nr fluxes and vice versa. In the integrated system, the

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total Nr input is 103.1 Tg N yr-1, where the anthropogenic Nr (excluding BNF and atmospheric deposition) totaled 70.7

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Tg N yr-1, which is more than 2 times the natural Nr level (Fig. 2b). The top three Nr inputs were HBNF, atmospheric

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deposition and N fixation due to fossil fuel combustion. HBNF, which accounted for 46% of the Nr, is utilized to meet

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the N fertilizer and industrial N application requirements, and it greatly affects the N cycle in China. Notably, in the

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near future, HBNF will likely exceed half of the total anthropogenic Nr input6. The total Nr output of the integrated

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system is 76.5 Tg N yr-1, of which air emissions account for approximately 79% and water emissions account for

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approximately 20% (Fig. 2c). As a result of the Nr inputs and outputs in the integrated system, approximately 75% of

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the Nr was ultimately discharged into the environment. This large flux of Nr emissions could lead to serious

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environmental problems.



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Figure 2. N balance analysis in a human consumption-driven system. (a) The Nr input and output diagram of the integrated

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system (units of Tg N yr-1). (b) The proportions of Nr inputs. (c) The proportions of Nr outputs.

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Analysis of N Accumulation in the Agricultural Subsystem

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The agricultural subsystem has complex interactions with other subsystems through N input-biotransformation-waste

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N emission processes. The new Nr (through HBNF and BNF process induced by cultivation)35 in the agricultural

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subsystem accounted for 69% of the integrated system (Fig. 2a and Fig. S1). Moreover, the agricultural subsystem is

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the largest subsystem in terms of the emissions of waste N (Fig. 2a). To understand the origin and fate of Nr in

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agroecosystems and determine the reasons for the high consumption of Nr for agriculture in China, which results in

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considerable pollution33, 34, 55, we split the agricultural subsystem into five modules: cropland, grassland, livestock,

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forest and aquaculture. The N balance analysis is shown in Figure S1. The numbers in the red boxes in Figure S1

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indicate the amount of Nr that accumulates in each module. Approximately 11% of the Nr accumulates in the cropland

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module, which suggests that the retention capacity of Nr is small in cropland areas. The accumulation of Nr in

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grassland areas is very small, while the rate of Nr accumulation associated with livestock is 12%. For the forest

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module, the input of Nr is dominated by natural processes, and few anthropogenic processes are involved, but the


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accumulation rate is the highest among the five modules, reaching 79%; therefore, forest areas are important N storage

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pools. Moreover, aquaculture is the only module that exhibited negative Nr accumulation, which may be due to

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overfishing in the current year. Thus, China must introduce appropriate policy measures to guide the healthy

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development of aquaculture.

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Analysis of the Ammonia Supply and Demand Balance

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The success of the synthetic ammonia industry has changed the history of world food production and solved the food

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requirements for the growing population8. HBNF is one of the most important inventions and innovations of the 20th

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century64. Because the Nr created by HBNF profoundly affects the Nr trends in China, we established a model of

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ammonia supply and demand balance using e!Sankey 4 software (Digital River Ireland Ltd., 2016). The model is

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shown in Figure 3. Exploring the balance of supply and demand of synthetic ammonia will help reveal the pattern of

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the N industry in China. This method also helps to understand the entire process (from creation to consumption) of

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anthropogenic Nr.

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The total ammonia production in China in 2014 was 46.9 Tg N yr-1 65, accounting for approximately 30% of the

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global production66. Figure 3 shows that synthetic ammonia in China is mainly used in agriculture, including N

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fertilizer and ammoniated feed production. These uses account for 75% of the total ammonia production. To meet the

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human consumption demands, synthetic ammonia has been increasingly used to synthesize artificial N products,

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including synthetic fibers, artificial pharmaceuticals, synthetic rubber, synthetic detergents, plastics, nitric acid,

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explosives and other products (details are provided in the industrial subsystem section of the supporting information).

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In addition, approximately 9% of synthetic ammonia is used for flue gas denitration, where the main flue gas refers to

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NOx emissions from thermal power, cement, and ceramic production processes. Currently, the main NOx control

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technologies are SCR and SNCR57, 59, 60, and these two technologies use synthetic ammonia as a reducing agent. As

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industrial flue gas denitration in China gradually progresses, more denitration agents will be consumed, which will lead

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to flue gas denitration and agricultural competition. In addition, the supply and demand balance model of synthetic

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ammonia shows that the proportion of waste N emissions is extremely small, which suggests that the use of synthetic

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ammonia as a raw material in industrial production processes is extremely efficient. It is conceivable that in the future,

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the production of Nr by HBNF must be controlled to reduce anthropogenic Nr. Furthermore, HBNF is the basis for

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ensuring food safety and meeting the industrial N and flue gas denitration demands; therefore, the rational use of



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ammonia is the key to achieving these goals.

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Figure 3. Synthetic ammonia supply and demand balance model. The net imports of synthetic ammonia are equal to the

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total imports minus the export volume. The original raw materials for synthetic industrial N products are derived from

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synthetic ammonia. In addition, China still imported a small amount of raw industrial N materials in 2014. It would be more

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accurate to deduct the synthetic industrial N products from the imports of raw industrial N materials in the calculations of

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the ammonia supply and demand model.

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Life Cycle Analysis of the Food N Flow

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Increased anthropogenic inputs of Nr provide sufficient food for most of the human demands; however, only a

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fraction of Nr is actually consumed as food, and the rest is lost to the environment and negatively affects ecosystems33.

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Increasing the productivity of agricultural ecosystems and reducing the N losses during food production processes are

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currently imminent. Taking this concern, life cycle analyses of food N are beneficial to understanding the context of

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food N and Nr utilization efficiency. Figure 4, which was created using e!Sankey 4 software, intuitively shows the

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analysis process from food (including crops, livestock and aquatic products) production to consumption. Nr is created

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to sustain food production, but only a small fraction of this N (32%) is consumed as raw food material (17.4 Tg N yr-1)

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and raw industrial materials (10.8 Tg N yr-1). In addition, 7.6 Tg N yr-1 is lost during food processing, and human food

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consumption is 6.1 Tg N yr-1, which is only 7% of the total Nr inputs (including net food imports). From a life cycle


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perspective, the loss or accumulation of Nr before it is consumed by humans as food (47.2 + 7.6 = 54.8 Tg N yr-1, the

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detailed data on N loss and N accumulation are shown in Fig. 1 and Fig. S1) in the food flow processes account for 59%

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of the total Nr inputs (including net food imports); thus, this negatively affects soils, ecosystems and the local climate.

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With the development of chemical technology, N fertilizers and pesticides have made significant contributions to

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improving crop yields and livestock populations. In the food production process, only N fertilizer inputs have exceeded

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natural Nr inputs (BNF and atmospheric deposition), accounting for 35% of the total Nr inputs. China has historically

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used environmentally friendly organic fertilizers, but the application of processed manure has recently increased. In

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addition, only 52% of livestock manure, 30% of crop straw and 33% of human excreta are returned to the field as

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organic fertilizer (details are shown in Tables S2, S5, S11, S16 and S25). The remaining livestock manure (48%), straw

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(12%) and human excreta (33%) that are not consumed for industrial use or harmless treatments, are lost to the

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environment and can cause serious environmental pollution.

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Figure 4. Life cycle analysis of the flow of food N.

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Analysis of the Input-output Ratio of N in the Agricultural and Industrial Subsystems Efficient use of N is one of the major assets of eco-efficient and sustainable production67. Intensive N use has



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triggered problems that threaten public health and the environment. A low input of N compared to the output of

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products and services is a sustainable practice68. Here, we used the N input-output ratio, which is calculated as the total

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N product outputs (in the forms of products and raw materials) divided by the N inputs, to evaluate the N utilization

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efficiency of these six production sectors (Figure S2).

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There are three main levels of input-output ratios in these sectors. The first level includes the industrial subsystem

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and the aquaculture module, with an input-output ratio ranging from 60-70%. The high input-output ratio of N in the

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industrial subsystem is due to advanced industrial processing technology, and there is room for improvement. In

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addition, the high N input-output ratio of the aquaculture module is mainly due to overfishing, rather than precision

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farming techniques. This finding is reflected by the negative accumulation of the aquaculture module (Figure S1).

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Overfishing leads to high aquatic product yields, which further improve the input-output ratio, but this is a false

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impression.

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The second level includes croplands and grasslands, which have input-out ratios ranging from 30-40%. The main

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reason for the low input-output ratio of N associated with croplands is that the application amounts and methods are

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often not optimal. To ensure food security, high-yield areas in China will pursue high yields and excessively use N

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fertilizer. In addition, overexposure to N fertilizer in the early stages of crop growth is often emphasized as an

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application method69. However, the crop root absorption capacity is weak during the early growth stages, especially for

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surface fertilization; therefore, the utilization rate is low, and the N losses are large70.

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The third level includes livestock and forestry and is characterized by an input-output ratio of less than 20%. In

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contrast to vegetable crop production, the N input-output ratio of animal food production is approximately half that of

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crop production. Table S5 shows that the total amount of excreta produced during livestock farming is 13.4 Tg N yr-1,

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accounting for 72% of the total N input of this module; therefore, the input-output ratio may be limited by the growth

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and development of animals. Among these six sectors, the largest proportion of waste management is associated with

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livestock. In addition, livestock manure can be used to achieve optimal resource use. Increasing the proportion of waste

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management is an effective way to reduce N emissions and improve N use efficiencies. The extremely low N input-

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output ratio of the forest module is due to the large amount of Nr stored (79%) in forest ecosystems. In addition, the

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forest ecosystem plays an important regulatory role in the N biogeochemical cycle71. Hence, the forest ecosystem is a

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repository of environmental N and plays a significant role in climate regulation and pollution control.


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Environmental Fate and Flow Analysis of N

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The atmosphere and hydrosphere are considered an environmental subsystem. The air emissions and water emissions

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of each module to the environmental subsystem during the N cycle are shown in Figure 5. The N air emission types can

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be divided into N2, NH3, NOx (not including N2O), and N2O, and the types of water emissions include nitrate N

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( − ), nitrite N ( − ), ammonia N ( − ) and organic N (ORG-N). As presented in Figure 2c, the total

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amount of air emissions is close to four times the total amount of water emissions, which suggests that most N loss

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occurs in the form of gas.

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A significant portion of air emissions is N2, especially in the agricultural subsystem (Fig. 5a). During the natural

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biogeochemical cycling of N, Nr mainly returns to the atmosphere as harmless N2 (N2 is generally considered to be

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inert and, therefore, does not react with the other elements, which in turn affects the environment and human health1)

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through denitrification72. Due to human disturbances, harmful nitrogenous gases (such as NH3, NOx, and N2O) are

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released into the atmosphere, followed by atmospheric flows and secondary reactions, which can cause gaseous

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pollution, such as haze, over large areas73. The main sources of NOx are the industrial, human consumption and waste

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management subsystems, which account for 76%, 17% and 7% of the NOx emissions, respectively (Fig. 5c). Most of

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the NOx emissions, which are driven by human activities, are from fossil fuel combustion, such as by automobiles,

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aircrafts, internal combustion engines and industrial furnaces. In addition, NOx is emitted during the production and use

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of nitric acid, such as N from fertilizer plants, organic intermediates, and nonferrous and ferrous metal smelters. NH3

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emissions are mainly associated with agricultural production processes, especially planting and the irrational use of N

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fertilizer. In this study, we consider N2O alone because its warming potential is 298 times that of CO2 (IPCC, 2007),

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and the warming effect on the global climate has increased over time74. In natural biogeochemical cycles, N2O is a

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byproduct of nitrification and denitrification processes75. Currently, the intensity of N cycling in farmland ecosystems

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is high, resulting in an increase in N2O emissions. In addition, nitrification and denitrification associated with industrial

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and waste treatment processes can produce N2O emissions. In 2014, the total N2O emissions in China were estimated to

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be 2.1 Tg N yr-1, and if the N2O warming potential is converted to CO2, the equivalent CO2 emissions would total

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approximately 996.7 million tons, which is equivalent to 10% of the total estimated CO2 emissions from China

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(10291.9 million tons) in 201476. Thus, N exhaust gas emissions in China must receive increased attention, and

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measures must be implemented to reduce these emissions.



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Excessive Nr in water can cause eutrophication and water quality deterioration, as well as affect the growth and

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reproduction of aquatic organisms14, 15. Figure 5b shows that Nr in the water mainly comes from processes associated

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with livestock production, the loss of N fertilizer, and the discharge of industrial wastewater and domestic sewage, with

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the main forms being − and ORG-N. Due to the characteristics of the small-scale peasant economy in China,

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the distribution of agriculture is relatively scattered and not conducive to the unified treatment of agricultural

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wastewater. In addition, due to the production level, Nr that is used in agriculture often results in surface and

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groundwater pollution through surface runoff and leakage from farmlands25. In particular, the livestock breeding

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industry, which has rapidly grown in China, is the largest source of N water emissions due to the emission of livestock

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manure that has not been treated and poor resource utilization. Because industrial wastewater can be discharged after

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treatment, the total associated emissions are slightly less than those from agriculture. Moreover, the discharge of

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domestic wastewater cannot be ignored. In addition, with the advancement of urbanization and the improvement of

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living standards, the discharge of domestic sewage will continue to increase.


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Figure 5. N loss in each module during N cycle analysis. (a) N air emission forms and fluxes. (b) N water emission forms and fluxes. (c) The proportion of waste N emissions in each module.

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Future Scenario Analysis of N Environmental Emissions and Policy Implications

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Clearly, the increasing rate of Nr creation and the declining N retention capacity of the environmental ecosystem

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conflict. There is great interest in reducing the environmental emissions of N (including gas emissions and water

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emissions) while ensuring that the growing human consumption demands are met. In this section, we analyze future

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scenarios. Specifically, the scenarios are compared with the baseline scenario to assess the effects of policy measures

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on reducing N emissions to the environment (Table 1). Compared to the baseline scenario, the trends in waste N

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emissions suggest that emissions could be significantly mitigated in all scenarios, especially by controlling larger farms

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(by 25%), issuing conventional fertilization recommendations for specific farming systems (by 25%) and implementing



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flue gas denitration measures (by 25%). Furthermore, the results of the scenario analysis reveal that the use of

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agricultural N fertilizer in China is excessive. The inefficient use of N fertilizer is the cause of the substantial waste N

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emissions from farming. The large amount of untreated NOx is another significant problem that could be addressed for

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waste N abatement. The combination of all measures represents the most effective strategy for mitigating waste N

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emissions.

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Table 1. Analyses of future scenarios for reducing N emissions to the environment

Scenario

Baseline scenario

Total waste N emissions

Relative reduction

excluding N2 (Tg N yr-1)

percentage (%)

-

47.3

-

Large farm size

35.6

25%

35.7

25%

45.1

5%

42.6

10%

Higher straw recycling ratio

46.2

2%

Flue gas denitration

35.4

25%

Vehicle exhaust denitration

44.9

5%

New energy applications

42.2

11%

All

7.5

84%

Measure(s)

Issuing conventional fertilization Efficiency improvement recommendations for specific farming systems New forms of N fertilizer Higher manure recycling High recycling rate

ratio

Nitrogen oxide emission reduction

Combined scenario

306 307

The emission reduction potential of each policy measure can be seen from the results of the scenario analysis.

308

Relevant agricultural regulations and measures must be adopted and enforced to eliminate the overuse of N fertilizer in

309

agricultural activities. Such measures include encouraging large-scale agriculture, promoting a standardized

310

agricultural production model77, prescribing recommended N application rates78, and issuing conventional fertilization


Page 17 of 27


311

recommendations for specific farming systems53. In addition, other approaches include improving the livestock manure,

312

human feces and straw recycling rates; systematic crop rotation; optimum fertilizer timing, placement, and formulation;

313

the effective use of nitrification inhibitors; and watershed management to mitigate or redirect N losses from fields27, 79.

314

In addition to the effects of agriculture activities, the treatment measures that correspond to fossil fuel combustion and

315

N production in industrial processes can also result in changes in Nr losses. Gradually promoting industrial flue gas

316

denitration80 and vehicle exhaust denitration61 and expanding the use of new energies to transition away from the

317

current coal-based consumption structure are ideal strategies in China. These proactive measures require the

318

cooperation of relevant sectors and industries (e.g., the agriculture and fertilizer industries, environmental sector,

319

industrial sector, energy sector, and political sector) and the implementation of coordinated measures (e.g., denitration

320

processes, environmental regulations, energy policies, and new material development).

321 322

DISCUSSION

323

A high-resolution SFA approach was applied in this study to quantify the N balance in China. This analysis resulted

324

in comprehensive descriptions of the different economic and ecologic processes based on 6 subsystems and 45

325

individual N flows in the model. Therefore, the model offers a higher resolution and more comprehensive perspective

326

than previous national and regional N flow models, such as the national model of Nr cycling in China constructed by

327

Cui et al.27 (3 subsystems, 18 flows), the European N balance by Leip et al.41 (4 subsystems, 20 flows), the N flows

328

analysis for food production in China by Ma et al.81 (4 subsystems, 17 flows), the N budget model of mainland China

329

by Ti et al.82 (3 subsystems, 18 flows) and the net anthropogenic N accumulation analysis in Beijing reported by Han et

330

al51. (3 subsystems, 12 flows). In addition, portions of our findings are in line and consistent with the existing literature.

331

For example, the N deposition and recycling rate of animal manure in our study were 17.6 Tg N yr-1 and 53% in 2014,

332

respectively, while they were estimated by Cui et al.27 to be 16.0 Tg N yr-1 and approximately 55% in 2010,

333

respectively. Nevertheless, some of the results estimated in this study are different from previous reports. For example,

334

we found that the rate of water emissions from waste management in 2014 was 0.4 Tg N yr-1, and the calculation by

335

Cui et al.27 was 1.3 Tg N yr-1 in 2010. Although there is a time lag between the reported values of the two studies, the

336

difference in wastewater treatment rates have more significant effects. China has made significant improvements in the

337

environmental protection requirements in recent years, so we have adopted a higher wastewater treatment rate. As a



Page 18 of 27

338

result, we estimated lower water emissions from waste management than were estimated by Cui et al.27. Another

339

example is the average N use efficiencies of food throughout the food chain, which was estimated to be 9% in 2005 by

340

Ma et al.81, while it was 7% in 2014 in our study. The main reason for the difference is the dramatic increase in the total

341

amount of N fertilizer and atmospheric deposition between 2005 and 2014. In 2005, the total amount of N fertilizer

342

used in China and atmospheric deposition were 27.0 and 2.0 Tg N yr-1, respectively, while in 2014 these values were

343

31.3 and 17.6 Tg N yr-1, respectively.

344

Similar to the N footprint model reported by Gu et al.26, we first constructed a coupled human-environmental N cycle

345

model on the national scale at high resolution. After that, we evaluated the specific aspects of the models with a

346

different perspective than in the existing literature. The balance analysis of synthetic ammonia supply and demand in

347

this study provides the framework for connecting the industrial and agricultural subsystems, whereas the associations

348

between industry and agriculture were weak in previous studies. For example, Gu et al. attempted to assess the

349

production perspective and not the consumption structure of goods and services26. This study also focuses on a life

350

cycle analysis of food N, which reflects the driver of human consumption in the N cycle. Moreover, it is intuitive and

351

novel to apply input-output ratios for industrial and agricultural subsystems, such as a production system in the

352

economic field, to measure N use efficiency. The application of an input-output ratio as an indicator is helpful for

353

analyzing the differences in the development status within the human-consumption integrated system under the same

354

dimension, which can also function as a decision support tool for other elements of metabolism.

355

Population growth, economic development and urbanization strongly affect the N cycle process of Chinese

356

ecosystems. For example, the Nr input of crop production in 2000 was approximately 21.0 kg N yr-1 per capita, as

357

estimated by Liu et al.33, which is slightly lower than the global per-capita average (22.3 kg N yr-1 per capita). In our

358

study, China reached approximately 64.0 kg N yr-1 per capita in 2014. The growth of human consumption (food,

359

products, energy and services) further drives Nr emissions and environmental accumulation. The estimates of Chinese

360

NH3, NOx, N2O emission in 2005 by Gu et al.16 are 10.9 Tg N yr-1, 5.3 Tg N yr-1 and 1.0 Tg N yr-1, respectively. We

361

estimate that the emissions in 2014 are 12.1 Tg N yr-1, 17.4 Tg N yr-1 and 2.1 Tg N yr-1, respectively. For water

362

emissions, there is a certain degree of growth. The total Nr leakage to the hydrosphere in 2008 was reported to be

363

approximately 5.0 Tg N yr-1 14, while in 2014, this value was approximately 15.6 Tg N yr-1. In addition, our study notes

364

and highlights the key role of policy in reducing waste N impacts through the simulation and assessment of scenarios,


Page 19 of 27


365

rather than simply discussing the development of N industry technologies and N pollution control measures. Because

366

the development of the N industry process differs in different countries and regions, a general policy cannot easily

367

solve such problems; thus, a case-by-case analysis is necessary, and a quantitative scenario analysis should be

368

performed.

369

Several potential improvements could be made to our methodology. First, the primary data source in our model is the

370

Statistical Yearbook, which is less evidence-based than other methods. Moreover, the statistical yearbook data mainly

371

record the statistics of domestic enterprises above the state-designated scale. As China is a developing country, there

372

are still some small microenterprises and self-employed individuals, especially in the agricultural sector. The possible

373

missing relevant data results in data deviation (the data will be relatively smaller than the actual situation). Thus,

374

additional data validation will be required in the future, especially for N cycle processes that are driven by human

375

activities. Second, the parameters in the model are mainly reported in the literature and are considered to be the overall

376

mean values for a country. Due to the differences in natural conditions, social development and cultures in the different

377

regions of China, the parameters will vary regionally. The averaging of the parameters used in the analysis process also

378

makes the result somewhat uncertain. The next steps in the development of the human-environmental coupled N cycle

379

model will be to link the Nr losses to effects35. For example, the establishment of high-precision atmospheric remote

380

sensing, ground-based remote sensing, geographic information systems and other technologies can improve the

381

accuracy of the systematic spatial analysis. Finally, as living standards improve, the demand for urban greening will

382

increase. In addition, pets are popular in many areas. The urban-greening and pet-breeding modules will also involve N

383

recycling, which has not been previously considered due to the small proportions of these N amounts and the lack of

384

statistical data. In the future, studies of these two modules could be integrated into the coupled human consumption-

385

environmental system.

386 387 388

ASSOCIATED CONTENT Supporting Information

389

This section includes the details of the system definition, data sources, Nr flow description and uncertainty analysis;

390

a figure associated with the N accumulation analysis in the agricultural subsystem; and a figure associated with the

391

analysis of the input-output ratio of N in the industrial and agricultural subsystems. Overall, the supporting information



Page 20 of 27

392

contains 67 pages, 2 figures and 26 tables. This information is available free of charge via the Internet at

393

http://pubs.acs.org.

394 395 396

AUTHOR INFORMATION Corresponding author *Phone & Fax: +86 10 62794513; e-mails: [email protected] (S.H.).

397 398

ORCID Shanying Hu: 0000-0002-3447-6395

399 400

Notes The authors declare no competing financial interests.

401 402 403

ACKNOWLEDGMENTS This study was supported through National Natural Science Foundation of China (Project Code: L1522024) and

404 405

Chinese Academy of Engineering (Project Code: 2015-ZCQ-05).

406 407

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