Revealing Greenhouse Gas Emission and Nitrogen Fertilizer Destination: A Case Study in Chengdu Plain Cultivation Industry

Abstract

The cultivation industry occupies a large proportion of greenhouse gas emissions in agriculture. Assessing greenhouse gas emissions from the cultivation industry is pivotal for mitigating emissions and promoting sustainable cultivation. Utilizing greenhouse gas emission calculation methods recommended by the Intergovernmental Panel on Climate Change (IPCC) and other methods, this work evaluated annual emissions and the emission structure of major crops from 2005 to 2021 in the Chengdu Plain, a significant agricultural region in Southwest China. We identified nitrogen fertilizer as the primary contributing factor to high emissions from cultivation production. Subsequently, we analyzed the trend and utilization of nitrogen fertilizer, which proposes essential strategies for reducing greenhouse gas emissions. The results showed that greenhouse gas (GHG) emissions from the cultivation industry in the Chengdu Plain exhibited a growth, fluctuation, and eventual decline trend from 2005 to 2021. The emissions increased from 5,148,900 t in 2005 to 6,289,700 t in 2009, representing a 22.16% increase, and subsequently decreased to 5,109,900 t in 2021, marking a 23.31% decrease. Nitrogen fertilizer application emerges as the primary source of GHG emissions, constituting approximately half of the total, with nitrogen fertilizer manufacturing contributing significantly as well, collectively amounting to about 70%. We also found that the proportion of greenhouse gas emissions attributed to cash crop cultivation has gradually increased over the last decade. Among these crops, vegetables exhibit the highest emissions, comprising nearly half of the total emissions from 2019 onwards. However, the nitrogen fertilizer use efficiency of cash crops is less than 30%, with higher nitrogen surplus, ammonia volatilization, and nitrogen leaching per unit area, and the total amount is higher than that of grain crops. Among cash crops, vegetables exhibit the highest amount of nitrogen surplus, ammonia volatilization, and nitrogen leaching, constituting nearly half of the total amount in the study area since 2019. Our findings significantly affect sustainable and low-carbon cultivation industry development in the study area.

1. Introduction

Mitigating greenhouse gas (GHG) emissions from human activities is the primary strategy to address global climate change [1]. The Paris Agreement sets a “hard target” for the international community, aiming to restrict the rise in global average temperature to below 2 °C compared to pre-industrial levels. The Chinese government also attaches great importance to this issue and has introduced measures to promote greenhouse gas emissions reduction and carbon neutrality. In 2021, China submitted to the United Nations documents titled “China’s Implementation of the Effectiveness of Independent National Contribution and New Goals and Initiatives” and “China’s Long-term Low Greenhouse Gas Emissions Development Strategy for the Middle of the 21st Century” [2]. In the “14th Five-Year Plan”, strategic deployment is actively pursued, clearly outlining the development strategy to optimize industrial and energy structures, promote energy conservation and emission reduction, and enhance carbon sinks. Among them, reducing emissions from agriculture is both an important and a potential initiative. According to the Fourth Assessment Report of the United Nations Intergovernmental Panel on Climate Change, carbon dioxide emissions from agricultural sources constitute 21–25% of total anthropogenic greenhouse gas emissions [3,4,5]. The Initial National Communication on Climate Change of the People’s Republic of China (2000) revealed that agricultural greenhouse gas emissions comprised 17% of the total national emissions, with methane and nitrous oxide contributing 50% and 92% of the total national emissions, respectively [6,7]. Hence, it is evident that the agricultural sector holds significant potential for reducing emissions. Consequently, ensuring food security while expediting efforts to reduce greenhouse gas emissions and facilitate a low-carbon transition in agriculture is essential for achieving comprehensive emission reductions and the “Carbon peaked, carbon neutral” goal [8]. Cultivation, the cornerstone of agriculture, constitutes a significant portion of greenhouse gas emissions in the agricultural sector. As cultivation industry practices undergo further mechanization and chemicalization, cultivation industry output has experienced substantial growth. However, this advancement is accompanied by elevated energy consumption, pollution, and emissions. Hence, reducing greenhouse gas emissions in the cultivation industry is paramount to achieving nationwide reductions in greenhouse gas emissions and attaining the strategic goals of carbon peak and carbon neutrality.

In recent years, academic research on agricultural greenhouse gas emissions has garnered continued attention, and existing studies have been categorized into the following areas. The primary focus of the research was the investigation of measurement methods for Agro-Chain greenhouse gas Emissions (ACE), which involved the development of measurement techniques such as the emission factor method [9], mass balance method [10], measured value method [11], and modeling method [12]. Among the methods utilized, the emission factor method stands out for its widespread adoption, primarily due to its facilitation of data acquisition and its ability to more accurately reflect the situation of each emission source in agriculture. For example, Burney et al. [13] calculated the global ACE for 1961–2005, which included emissions from agricultural soils, methane emissions from rice paddies, agricultural land expansion, and fertilizer production and use. West et al. [14] conducted a detailed study on ACE and concluded that ACE comes mainly from agricultural inputs, including fertilizers, agricultural lime, pesticides, agricultural irrigation, and seed breeding. The second type of research focuses on analyzing the factors that influence agricultural GHG emissions. Lal [15] concluded that different farming practices on farms are the main reason for the significant differences in direct and indirect emissions. Wei et al. [16] concluded that factors such as the optimization of the agricultural industry structure and the overall reduction of the agricultural population would inhibit the growth of agricultural GHG emissions. The third research category focuses on the mechanism of agricultural GHG emission reduction. Gomierol [17] argued that developing organic agriculture suppresses agricultural carbon emissions. Jiang et al. [18] believe that the zero-growth project of chemical fertilizers, pesticides, and livestock and poultry manure’s essential resource utilization action is conducive to GHG emission reduction. Academics have extensively researched the quantification methods, influencing factors, and emission reduction strategies of agricultural greenhouse gas emissions, providing a solid theoretical foundation for agricultural environmental policy formulation and emission reduction practice. However, the significant knowledge gap is that the previous studies only generalized nitrogen fertilizer application as a whole, neglecting the fact that different crop species have different emission factors for nitrogen fertilizer application. To fill this gap, differentiated emission factors are considered in this study to improve the precision degree. In addition, significant inputs of nitrogen fertilizers, while increasing yields, also hurt the environment, mainly through losses to water bodies through leaching and to the atmosphere through ammonia volatilization, nitrification, and denitrification, which are closely related to environmental problems such as increased greenhouse gas emissions [16]. Therefore, based on identifying nitrogen fertilizer application and manufacturing as the primary source of emissions from the cultivation industry, understanding the issue of the destination of nitrogen fertilizers in the crop-soil system can help to explore the potential part of emission reduction and propose more targeted key pathways for GHG emission reduction in the cultivation industry.

Located in the cultivation industry heartland of China, the Chengdu Plain has experienced a steady rise in its economic output, with the total output value of agriculture, forestry, livestock husbandry, and fisheries reaching 94.261 billion RMB in 2021, reflecting an increase of 42.426 billion RMB from 2010. With the rapid development of the cultivation industry in the Chengdu Plain, the issue of GHG emissions has become more pressing. Achieving GHG emission reductions from cultivation without hindering its development constitutes one of the critical challenges facing the Chengdu Plain region. Currently, research on GHG emissions focuses mainly on the national level, while research on the emission characteristics of key agricultural regions is still limited. Given the complexity of the production environment, factors, resources, and structure in the cultivation industry, there is a lack of precise calculation methods for GHG emissions from the cultivation industry in the Chengdu Plain. Furthermore, research on emission reduction technologies and policies also suffers from a lack of necessary data support. In this study, we proposed a complete accounting system for GHG emissions by considering the specific conditions of the Chengdu Plain and the primary and secondary emissions related to crop cultivation, building upon methodologies outlined by the IPCC and other GHG calculation approaches. We calculated the annual emissions and structure of major crops (wheat, maize, rice, soybean, tea, fruits, and vegetables) between 2005 and 2021. We identified nitrogen fertilizer as the primary element for emission reduction and examined the changes in its destination and utilization rates. Additionally, the study proposed key pathways for greenhouse gas emission reduction within the cultivation industry. We tried to answer the following three questions: (1) Key elements of greenhouse gas emissions in the cultivation industry; (2) nitrogen fertilizer destinations and utilization changes; (3) key strategies and mechanisms for reducing greenhouse gas emissions in cultivation.

2. Research Methodology and Data Sources

2.1. Study Area and Data Sources

The Chengdu Plain, located in the western part of the Sichuan Basin (Figure 1), has a total area of 2,024,600 ha and a cultivated area of 648,830 ha. The Chengdu Plain is the most extensive in southwestern China, with a topography that slopes from northwestern to southeastern and an elevation of about 600 m above sea level. The plains have a mild climate, abundant rainfall, and fertile soil. Based on the time-honored Dujiangyan Irrigation Project, the region boasts a developed water system, a prosperous cultivation industry, abundant produce, and a dense population. It is China’s main rice, sugarcane, silk, and rapeseed production area.

We collected data on the sown area of crops, livestock and poultry stocks, and production of rice, wheat, maize, soybeans, tea, fruits, and vegetables in Chengdu and Deyang city from the Chengdu City Statistical Yearbook, Deyang City Statistical Yearbook, and Sichuan Statistical Yearbook published for the years 2006–2022, in addition to diesel fuel used for agricultural machinery and the effective irrigated area. Livestock data are employed to estimate the amount of organic nitrogen fertilizer input to crops. Agricultural diesel data reflect the use of agricultural machinery during the year, while irrigation data indicate the effective irrigated area during the year. The spatial data on atmospheric nitrogen deposition in China are based on the spatio-temporal dataset of wet deposition of inorganic nitrogen from 1996 to 2015 [19]. Data on nitrogen fertilizer inputs for rice, wheat, maize, soya beans, tea, fruits, and vegetables were provided in the National Compendium of Cost-Benefit Information on Agricultural Products [20] and the findings of Zuo et al. [21]. Data on seed N content of rice, wheat, and maize were quoted from Bao et al. [22], soybean from the China Fertilizer Information Network [23], tea from Liang et al. [24], and N content of fruits and vegetables from Smill [25]. In addition, data on N fixation rates of crops were derived from studies by Li and Smil et al. [25,26].

2.2. Greenhouse Gas Emission Calculation Boundaries and Methods

Agricultural GHG emissions can be categorized into three types of sources: primary, secondary, and tertiary emissions [15]. Primary emissions refer to the GHG emissions directly resulting from agricultural activities such as plowing, sowing, harvesting, and transport [15]. Secondary emissions are GHG emissions from producing, packaging, and storing fertilizers and pesticides [15]. Tertiary emissions are the greenhouse gas emissions from the procurement of raw materials, the manufacture of agricultural machinery and other agricultural equipment, and the construction of agricultural buildings [15]. The IPCC defines primary emissions as direct emissions, while secondary and tertiary emissions are implied and indirect emissions [15]. Primary emissions have received extensive attention in GHG inventory preparation and carbon management. In primary emissions, agricultural activities emit carbon dioxide, methane, and nitrous oxide mainly through livestock enteric fermentation, manure management, methane emissions from rice paddies, arable land, crop residue burning, energy use, and land tillage [27]. Life cycle analysis (LCA) of agricultural products usually considers secondary emissions. Due to the wide range of tertiary emissions, most studies have concentrated on primary and secondary emissions to guide the practice of agricultural GHG control [27,28].

This study focuses primarily on the cultivation sector, mainly primary and secondary emissions. In terms of primary emissions, the study included (1) nitrogen fertilizer application, (2) methane emissions from rice paddies, (3) pesticide application, (4) plowing and breaking up the soil, (5) agricultural diesel, and (6) irrigation. For secondary emissions, we considered (1) nitrogen fertilizer manufacturing, (2) pesticide manufacturing, and (3) agricultural films, according to FAO 2014 [29]. The explanation for each emission source is as follows: (1) Nitrogen fertilizer application: the application of synthetic nitrogen fertilizers, manure, and straw on land emits N₂O directly through nitrification and denitrification and indirectly through volatilization and decomposition [30]. (2) Methane emissions from rice paddies: In rice paddies that have been flooded for an extended period, methane-producing bacteria in the soil use organic materials (e.g., root secretions, plant and animal residues, and organic fertilizers) to produce CH₄, which is then emitted into the atmosphere [27,31]. (3) Carbon emissions directly or indirectly caused by pesticide application [32]. (4) Organic carbon loss due to plowing and soil breaking [32]. (5) Carbon emissions caused by the use of agricultural diesel, which consumes energy, and carbon emissions caused by the use of electricity for irrigation [32]. (6) Nitrogen fertilizers, pesticides, and agricultural films produce CO₂, CH₄, and N₂O emissions during production and transport [32]. GHG emissions are expressed in carbon dioxide equivalent, converted according to the 100-year global warming potential (GWP100) of the IPCC’s Sixth Assessment Report 2022 (AR6), where the GWP100 is 27.9 for CH₄ and 273 for N₂O [27]. The system for calculating GHG for the cultivation industry is shown in Figure 2. The values and units of the parameters used in the following calculations are included in

Table 1. Calculated parameter values for cultivation activities.

Cultivation Activities	Parameters	Value	Reference Sources
Nitrogen fertilizer application	fFvolat	0.1 kg NH3-N and NOX-N/kg N applied	[33]
	fOvolat	0.2 kg NH3-N and NOX-N/kg N applied
	EFCRLA,atm	0.01 kg N2O-N/kg NH3-N and NOx-N volatilized
	EFCRLA,leach	0.0075 kg N2O-N/kg N leaching or runoff
Methane emissions from rice paddies	ti,j,k	134 day	[33]
	EFC	1.3
	SFW	0.676
	SFP	0.68
	SFO	1.01
Pesticide application	Average consumption per hectare	6.75 kg/ha	Oak Ridge Laboratory, USA
	Emission factor	18.09 kg CO2 eq/kg
ploughing and breaking up of soil	Emission factor	312.6 kg CO2 eq/km2	College of Biology and Technology, China Agricultural University
Agricultural diesel	Emission factor	0.5927 kg CO2 eq/kg	United Nations Intergovernmental Panel on Climate Change (IPCC)
irrigated	Average consumption per hectare	72.75 kg CO2 eq/ha	[34]
agro-film	Emission factor	5.18 kg CO2 eq/kg	Institute of Agricultural Resources and Ecological Environment, Nanjing Agricultural University
Nitrogen fertilizer manufacturing	EFFERT for CO2	6.08 kg CO2/kg N	[35]
	EFFERT for CH4	0.02 kg CH4/kg N
	EFFERT for N2O	0.0009 kg N2O/kg N
Pesticide manufacturing	EFPEST	16.35 kg CO2 eq/kg application	[36]

.

2.2.1. Greenhouse Gas Emissions from Nitrogen Fertilizer Application

(1)

Nitrogen Surplus

Nitrogen surplus is the difference between nitrogen inputs (including chemical fertilizers, organic fertilizers, biological nitrogen fixation, and atmospheric nitrogen deposition) and nitrogen outputs (nitrogen removed mainly through crop harvesting). The exact formula can be expressed as follows:

$${\mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}={\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}}+{\mathrm{N}}_{\mathrm{i},\mathrm{m}\mathrm{a}\mathrm{n}}+{\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{i}\mathrm{x}}+{\mathrm{N}}_{\mathrm{i},\mathrm{d}\mathrm{e}\mathrm{p}}-{\mathrm{N}}_{\mathrm{i},\mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}$$

(1)

$${\mathrm{N}}_{\mathrm{i},\mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}={\mathrm{Y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}_{\mathrm{i}}\times {\mathrm{N}\mathrm{C}}_{\mathrm{i}}$$

(2)

where ${\mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}$ denotes the nitrogen surplus of crop $\mathrm{i}$ (kg); ${\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}}$ denotes fertilizer nitrogen input for crop $\mathrm{i}$ (kg); ${\mathrm{N}}_{\mathrm{i},\mathrm{m}\mathrm{a}\mathrm{n}}$ denotes organic fertilizer nitrogen input for crop $\mathrm{i}$ (kg); ${\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{i}\mathrm{x}}$ denotes the amount of nitrogen fixed by biological nitrogen fixation in crop $\mathrm{i}$ (kg); ${\mathrm{N}}_{\mathrm{i},\mathrm{d}\mathrm{e}\mathrm{p}}$ denotes atmospheric nitrogen deposition from crop $\mathrm{i}$ (kg). ${\mathrm{N}}_{\mathrm{i},\mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}$ denotes the amount of nitrogen utilized by crop $\mathrm{i}$ harvested (kg); ${\mathrm{Y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}_{\mathrm{i}}$ denotes the yield of crop $\mathrm{i}$ (kg); and ${\mathrm{N}\mathrm{C}}_{\mathrm{i}}$ is an empirical parameter indicating the proportion of crop $\mathrm{i}$ harvested with nitrogen (%).

(2)

Greenhouse gas emissions

Crop greenhouse gas emissions N₂O emissions originate from nitrogen fertilizers and consist of direct and indirect emissions. The formula is as follows:

$${\mathrm{C}\mathrm{F}}_{\mathrm{r},\mathrm{C}\mathrm{H}\mathrm{G}}={\mathrm{C}\mathrm{F}}_{\mathrm{i},\mathrm{N}2\mathrm{O}}\times {\displaystyle \frac{44}{28}}\times 273$$

(3)

where ${\mathrm{C}\mathrm{F}}_{\mathrm{i},\mathrm{G}\mathrm{H}\mathrm{G}}$ denotes greenhouse gas emissions (kg CO₂ eq); ${\mathrm{C}\mathrm{F}}_{\mathrm{i},\mathrm{N}2\mathrm{O}}$ denotes emissions from crop i (kg CO₂ eq); 44/28 is the conversion factor from N₂O-N to N₂O; ${\mathrm{C}\mathrm{F}}_{\mathrm{r},\mathrm{C}\mathrm{H}₄}$ denotes rice emissions (kg CO₂ eq); and 273 is the global warming potential [27].

(2-1)

Direct emission of N₂O

According to Chen et al. [37], nitrogen losses are correlated with the amount of N fertilizer applied. Excessive nitrogen fertilizer inputs exceeding crop requirements may induce N₂O emissions. For direct N₂O emissions from rice, wheat, and maize, we relied on the experimental results of Chen et al. For direct N₂O emissions from soybeans, we referred to the research method of Gerber et al. [38]; for direct N₂O emissions from vegetables, the present study was calculated based on the results of Mei et al. [39], and the calculation method of emissions from fruits and teas adopted the results of the study of Wang et al. [40]. The specific calculation formula is as follows:

$${\mathrm{E}}_{\mathrm{i},\mathrm{N}2\mathrm{O}\_\mathrm{d}\mathrm{i}\mathrm{r}}=\left\{\begin{array}{cc}0.74\times {\mathrm{e}}^{0.011{\times \mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}},\hfill & \hfill \mathrm{Rice}\\ 0.54\times {\mathrm{e}}^{0.0063\times {\mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}},\hfill & \hfill \mathrm{Wheat}\\ 1.13\times {\mathrm{e}}^{0.0071\times {\mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}},\hfill & \hfill \mathrm{Maize}\\ 0.0017\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Soybeans}\\ 0.0228\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Vegetables}\\ 0.0272\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Fruits} \mathrm{and} \mathrm{teas}\end{array}\right.$$

(4)

where ${\mathrm{E}}_{\mathrm{i},\mathrm{N}2\mathrm{O}\_\mathrm{d}\mathrm{i}\mathrm{r}}$ denotes the direct N₂O emissions from crop $\mathrm{i}$ (kg), ${\mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}$ denotes the nitrogen fertilizer surplus from crop $\mathrm{i}$ (kg/ha), and ${\mathrm{N}}_{\mathrm{s},\mathrm{f}\mathrm{e}\mathrm{r}}$ denotes the amount of nitrogen fertilizer applied to crop $\mathrm{i}$ (kg).

(2-2)

Indirect N₂O emissions

The equations for calculating indirect N₂O emissions from crops were obtained from Liang et al. [33], and the emission factors were obtained from the IPCC Guidelines for National Greenhouse Gas Inventories [27], as follows:

$${\mathrm{E}}_{\mathrm{i},\mathrm{j}}^{\mathrm{C}\mathrm{R}\mathrm{L}\mathrm{A},\mathrm{i}\mathrm{n}\mathrm{d}}={\mathrm{A}\mathrm{t}\mathrm{m}\mathrm{o}\mathrm{s}}_{\mathrm{i},\mathrm{j}}+{\mathrm{L}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{h}}_{\mathrm{i},\mathrm{j}}$$

(5)

$${\mathrm{A}\mathrm{t}\mathrm{m}\mathrm{o}\mathrm{s}}_{\mathrm{i},\mathrm{j}}=[{\mathrm{N}\mathrm{F}\mathrm{e}\mathrm{r}\mathrm{t}}_{\mathrm{i},\mathrm{j}}\times {\mathrm{f}}^{\mathrm{F}\mathrm{v}\mathrm{o}\mathrm{l}\mathrm{a}\mathrm{t}}{+\mathrm{M}\mathrm{a}\mathrm{n}\mathrm{u}}_{\mathrm{i},\mathrm{j}}\times {\mathrm{f}}^{\mathrm{O}\mathrm{v}\mathrm{o}\mathrm{l}\mathrm{a}\mathrm{t}}]\times {\mathrm{E}\mathrm{F}}^{\mathrm{C}\mathrm{R}\mathrm{L}\mathrm{A},\mathrm{a}\mathrm{t}\mathrm{m}}$$

(6)

$${\mathrm{L}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{h}}_{\mathrm{i},\mathrm{j}}={\mathrm{N}}_{\mathrm{i},\mathrm{l}\mathrm{e}\mathrm{a}}+{\mathrm{E}\mathrm{F}}^{\mathrm{C}\mathrm{R}\mathrm{L}\mathrm{A},\mathrm{l}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{h}}$$

(7)

where ${\mathrm{E}}_{\mathrm{i},\mathrm{j}}^{\mathrm{C}\mathrm{R}\mathrm{L}\mathrm{A},\mathrm{i}\mathrm{n}\mathrm{d}}$ is the indirect on-farm emissions from area $\mathrm{i}$ in year j; ${\mathrm{A}\mathrm{t}\mathrm{m}\mathrm{o}\mathrm{s}}_{\mathrm{i},\mathrm{j}}$ is the amount of N₂O-N from atmospheric deposition of nitrogen volatilized from managed soils in the corresponding area and year; and ${\mathrm{L}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{h}}_{\mathrm{i},\mathrm{j}}$ is the amount of N₂O-N from leaching and runoff of nitrogen additions from managed soils in the corresponding area and year where leaching or runoff occurs. ${\mathrm{N}\mathrm{F}\mathrm{e}\mathrm{r}\mathrm{t}}_{\mathrm{i},\mathrm{j}}$ is the number of fertilizer nitrogen inputs in the corresponding region and year. ${\mathrm{M}\mathrm{a}\mathrm{n}\mathrm{u}}_{\mathrm{i},\mathrm{j}}$ is the amount of organic N inputs for the corresponding area and year; $f^{Fvolat}$ is the fraction of synthetic fertilizer N applied to the soil; $f^{Ovolat}$ is the fraction of synthetic fertilizer N volatilized to NH₃ and NO_x; and ${\mathrm{E}\mathrm{F}}^{\mathrm{C}\mathrm{R}\mathrm{L}\mathrm{A},\mathrm{a}\mathrm{t}\mathrm{m}}$ is the emission factor for atmospheric deposition. Equation (7) ${\mathrm{N}}_{\mathrm{i},\mathrm{l}\mathrm{e}\mathrm{a}}$ is the amount of N leaching from crops and ${\mathrm{E}\mathrm{F}}^{\mathrm{C}\mathrm{R}\mathrm{L}\mathrm{A},\mathrm{l}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{h}}$ is the emission factor for leaching or runoff, and the study used parameters from the IPCC guidelines [27].

2.2.2. Greenhouse Gas Emissions of Methane from Paddy Fields

The CH₄ calculation equation was obtained from IPCC, where the parameter reference values were taken from Zuo et al. [21]. The CH₄ emission equations for paddy fields were calculated as follows:

$${\mathrm{C}\mathrm{F}}_{\mathrm{r},{\mathrm{C}\mathrm{H}}_4}={\sum }_{\mathrm{i},\mathrm{j},\mathrm{k}}({\mathrm{E}\mathrm{F}}_{\mathrm{i},\mathrm{j},\mathrm{k}}\times {\mathrm{t}}_{\mathrm{i},\mathrm{j},\mathrm{k}}\times {\mathrm{A}}_{\mathrm{i},\mathrm{j},\mathrm{k}}\times {10}^{-6})\times 27.9$$

(8)

where ${\mathrm{C}\mathrm{F}}_{\mathrm{r},{\mathrm{C}\mathrm{H}}_4}$ denotes paddy field emissions (kg CO₂ eq); ${\mathrm{E}\mathrm{F}}_{\mathrm{i},\mathrm{j},\mathrm{k}}$ denotes paddy field CH₄ emission coefficient (kg CH₄ ha⁻¹ day⁻¹); ${\mathrm{t}}_{\mathrm{i},\mathrm{j},\mathrm{k}}$ denotes paddy field emission days (days);${\mathrm{A}}_{\mathrm{i},\mathrm{j},\mathrm{k}}$ denotes paddy field emission area (ha); i, j, k indicate the types and amounts of ecosystems, aquatic environments, and organic fertilizers that differ in other cases due to CH₄ emissions from rice paddies; and 27.9 is the global warming potential [27].

The CH₄ emission factor is calculated as follows:

$${\mathrm{E}\mathrm{F}}_{\mathrm{i}}={\mathrm{E}\mathrm{F}}_{\mathrm{c}}\times {\mathrm{S}\mathrm{F}}_{\mathrm{w}}\times {\mathrm{S}\mathrm{F}}_{\mathrm{p}}\times {\mathrm{S}\mathrm{F}}_{\mathrm{o}}$$

(9)

where ${\mathrm{E}\mathrm{F}}_{\mathrm{i}}$ represents the adjusted daily emission factor for a given harvest area; ${\mathrm{E}\mathrm{F}}_{\mathrm{c}}$ represents the baseline emission factor for a continuously flooded field without organic amendments; ${\mathrm{S}\mathrm{F}}_{\mathrm{w}}$ denotes the scale factor, which takes into account differences in water conditions throughout the reproductive period; ${\mathrm{S}\mathrm{F}}_{\mathrm{p}}$ denotes the scale factor, which takes into account differences in drainage throughout the pre-season prior to the reproductive period; and ${\mathrm{S}\mathrm{F}}_{\mathrm{o}}$ denotes the scale factor, which varies with the type and amount of organic fertilizer applied.

${\mathrm{S}\mathrm{F}}_{\mathrm{o}}$ is calculated as follows:

$${\mathrm{S}\mathrm{F}}_0=(1+{\sum }_{\mathrm{i}}{\mathrm{R}\mathrm{O}\mathrm{A}}_{\mathrm{I}}\times {\mathrm{C}\mathrm{F}\mathrm{O}\mathrm{A}}_{\mathrm{I}}{)}^{0.59}$$

(10)

where ${\mathrm{S}\mathrm{F}}_0$ denotes a scale factor that varies with the type and amount of organic modifier applied; $\mathrm{i}$ is the organic modification factor for the different types; ${\mathrm{R}\mathrm{O}\mathrm{A}}_{\mathrm{I}}$ is the rate of application of organic fertilizer (kg ha⁻¹), using dry weight for straw and fresh weight for the others; ${\mathrm{C}\mathrm{F}\mathrm{O}\mathrm{A}}_{\mathrm{I}}$ denotes the conversion factor for the organic modification factor $\mathrm{i}$.

2.2.3. Greenhouse Gas Emissions from Pesticide Application, Ploughing and Breaking, Agro-Diesel, Irrigation, and Agricultural Films

Equation (11) was used in this study to calculate the emissions from the above sources [32].

$${\mathrm{E}}_{\mathrm{i},\mathrm{j}}={\mathrm{T}}_{\mathrm{i}}\times {\mathsf{\epsilon }}_{\mathrm{i}}$$

(11)

where E_i,j is the GHG emissions from source $\mathrm{i}$ in year j (kg CO₂ eq), T_i indicates input from source $\mathrm{i}$ (kg), ${\mathsf{\epsilon }}_{\mathrm{i}}$ indicates emission factor for source $\mathrm{i}$(kg CO₂ eq/kg), and the emission coefficients for pesticide application, tilling and breaking of the soil, agro-diesel, irrigation, and agricultural film are shown in Table 1.

2.2.4. Greenhouse Gas Emissions from Nitrogen Fertilizer Manufacturing

The study used Equation (12) to calculate synthetic nitrogen fertilizer manufacturing emissions, including GHG emissions from energy extraction and transport, ammonia synthesis, fertilizer manufacturing, and fertilizer transport.

$${\mathrm{E}}_{\mathrm{i},\mathrm{j}}^{\mathrm{F}\mathrm{E}\mathrm{R}\mathrm{T}}={\mathrm{N}\mathrm{F}\mathrm{e}\mathrm{r}\mathrm{t}}_{\mathrm{i},\mathrm{j}}\times {\mathrm{E}\mathrm{F}}^{\mathrm{F}\mathrm{E}\mathrm{R}\mathrm{T}}$$

(12)

where ${\mathrm{E}}_{\mathrm{i},\mathrm{j}}^{\mathrm{F}\mathrm{E}\mathrm{R}\mathrm{T}}$ is the GHG emissions from nitrogen fertilizer manufacturing in region $\mathrm{i}$ in year j (kg CO₂ eq); NFert_i,j is the amount of synthetic nitrogen fertilizer applied (kg); EF^FERT is the emission factor for nitrogen production (kg CO₂ eq/kg N). Emission factors were calculated according to Zhang et al. [36].

2.2.5. Greenhouse Gas Emissions from Pesticide Manufacturing

Equations (13) and (14) calculate pesticide manufacturing emissions, which include GHG emissions from pesticide manufacturing and transport.

$${\mathrm{E}}_{\mathrm{i},\mathrm{j}}^{\mathrm{P}\mathrm{E}\mathrm{S}\mathrm{T}}={\mathrm{P}\mathrm{e}\mathrm{s}\mathrm{t}}_{\mathrm{i},\mathrm{j}}\times {\mathrm{f}}_{\mathrm{j}}^{\mathrm{p}\mathrm{l}\mathrm{P}\mathrm{e}\mathrm{s}\mathrm{t}}\times {\mathrm{E}\mathrm{F}}^{\mathrm{P}\mathrm{E}\mathrm{S}\mathrm{T}}$$

(13)

$${\mathrm{f}}_{\mathrm{j}}^{\mathrm{P}\mathrm{l}\mathrm{P}\mathrm{e}\mathrm{s}\mathrm{t}}={\displaystyle \frac{{\mathrm{P}\mathrm{e}\mathrm{s}\mathrm{t}}_{\mathrm{j}}^{\mathrm{p}\mathrm{u}\mathrm{r}\mathrm{e}}}{{\mathrm{P}\mathrm{e}\mathrm{s}\mathrm{t}}_{\mathrm{j}}}},\mathrm{j}=2005,\cdots ,2021$$

(14)

where ${\mathrm{E}}_{\mathrm{i},\mathrm{j}}^{\mathrm{P}\mathrm{E}\mathrm{S}\mathrm{T}}$ is the GHG emissions from pesticide manufacturing in year j in region $\mathrm{i}$ (kg CO₂ eq); Pest_i,j is the amount of pesticide applied (kg); ${\mathrm{f}}_{\mathrm{j}}^{\mathrm{P}\mathrm{l}\mathrm{P}\mathrm{e}\mathrm{s}\mathrm{t}}$ is the proportion of active ingredient in pesticides in that year; EF^PEST is the emission factor for pesticide manufacturing (kg CO₂ eq/kg); the proportion of active ingredient is from Liang et al. [33]; and the emission factor is from Zhang et al. [36].

2.3. Nitrogen Fertilizer Destinations and Nitrogen Fertilizer Utilization Rates for Primary Emission Sources

2.3.1. Nitrogen Fertilizer Utilization Rate

Nitrogen fertilizer utilization efficiency (NUE) is the ratio of the amount of nitrogen fertilizer output at the time of crop harvesting to the total amount of agricultural nitrogen fertilizer input (including chemical fertilizer nitrogen input, organic fertilizer nitrogen input, nitrogen fixation, and atmospheric nitrogen deposition). The calculation formula is as follows:

$${\mathrm{N}\mathrm{U}\mathrm{E}}_{\mathrm{i}}={\displaystyle \frac{{\mathrm{N}}_{\mathrm{i},\mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}}{{\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}}+{\mathrm{N}}_{\mathrm{i},\mathrm{m}\mathrm{a}\mathrm{n}}+{\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{i}\mathrm{x}}+{\mathrm{N}}_{\mathrm{i},\mathrm{d}\mathrm{e}\mathrm{p}}}}\times 100\mathrm{\%}$$

(15)

$${\mathrm{N}}_{\mathrm{i},\mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}={\mathrm{Y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}_{\mathrm{i}}\times {\mathrm{N}\mathrm{C}}_{\mathrm{i}}$$

(16)

where ${\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}}$ denotes fertilizer nitrogen input to crop $\mathrm{i}$ (kg); ${\mathrm{N}}_{\mathrm{i},\mathrm{m}\mathrm{a}\mathrm{n}}$ denotes organic fertilizer nitrogen input to crop $\mathrm{i}$ (kg); ${\mathrm{N}}_{\mathrm{i},\mathrm{d}\mathrm{e}\mathrm{p}}$ denotes atmospheric nitrogen deposition to crop $\mathrm{i}$ (kg); and ${\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{i}\mathrm{x}}$ denotes nitrogen fixation to crop $\mathrm{i}$ (kg). ${\mathrm{N}}_{\mathrm{i},\mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}$ denotes the amount of nitrogen utilized by harvesting of crop $\mathrm{i}$ (kg); ${\mathrm{Y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}}_{\mathrm{i}}$ denotes the yield of crop $\mathrm{i}$ (kg); and ${\mathrm{N}\mathrm{C}}_{\mathrm{i}}$ denotes an empirical parameter for the proportion of nitrogen contained in crop $\mathrm{i}$ at the time of harvest (%).

2.3.2. NH₃ Volatilization

NH₃ volatilization and nitrogen leaching are two critical pathways of nitrogen fertilizer loss after the agricultural production process, and analyzing the unit intensity of both provides a more intuitive measure of their pollution of the environment. The calculation of NH₃ volatilization for rice, wheat, and maize was quoted from Chen et al. [37]; for NH₃ volatilization of soybean, fruit, and tea, we used Zhang et al. [35]. For NH₃ volatilization of vegetables, we used Ti et al. [41]. with the following formulae:

$${\mathrm{E}}_{\mathrm{i},\mathrm{N}\mathrm{H}₃\_\mathrm{v}\mathrm{o}\mathrm{l}}=\left\{\begin{array}{cc}2.97+0.16\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Rice}\\ -4.95+0.17\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Wheat}\\ 1.45+0.24\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Maize}\\ {0.129\times \mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{ }\mathrm{Soybean}, \mathrm{Fruit} \mathrm{and} \mathrm{tea}\\ {0.194\times \mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Vegetables}\end{array}\right.$$

(17)

where ${\mathrm{E}}_{\mathrm{i},\mathrm{N}\mathrm{H}₃\_\mathrm{v}\mathrm{o}\mathrm{l}}$ denotes the amount of NH₃ volatilized from crop $\mathrm{i}$ (kg) and ${\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}}$ denotes the amount of nitrogen fertilizer applied to crop $\mathrm{i}$ (kg).

2.3.3. Nitrogen Leaching

For nitrogen leaching from wheat, maize, and rice, the study used the results of Chen et al. [37]; for nitrogen leaching from soya beans, fruits, and tea, we used the results of Zhang et al. [35]. For nitrogen leaching from vegetables, we used the results of Ti et al. [41]. The calculation equations are as follows:

$${\mathrm{N}}_{\mathrm{i},\mathrm{L}\mathrm{e}\mathrm{a}}=\left\{\begin{array}{cc}6.03\times {\mathrm{e}}^{0.0048{\times \mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}},\hfill & \hfill \mathrm{Rice}\\ 13.59\times {\mathrm{e}}^{0.009{\times \mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}},\hfill & \hfill \mathrm{Wheat}\\ 25.31\times {\mathrm{e}}^{0.0095{\times \mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}},\hfill & \hfill \mathrm{Maize}\\ {0.098\times \mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Soyabeans}, \mathrm{fruits} \mathrm{and} \mathrm{tea}\\ 0.249\times {\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}},\hfill & \hfill \mathrm{Vegetables}\end{array}\right.$$

(18)

where ${\mathrm{N}}_{\mathrm{i},\mathrm{L}\mathrm{e}\mathrm{a}}$ denotes the amount of N leaching from crop $\mathrm{i}$ (kg) and ${\mathrm{N}\mathrm{U}}_{\mathrm{i},\mathrm{s}\mathrm{u}\mathrm{r}}$ denotes the amount of N surplus from crop $\mathrm{i}$ (kg/ha). ${\mathrm{N}}_{\mathrm{i},\mathrm{f}\mathrm{e}\mathrm{r}}$ denotes the amount of N fertilizer applied to crop $\mathrm{i}$ (kg).

3. Results

3.1. Time-Varying Characteristics of Greenhouse Gas Emissions

Figure 3 illustrates the trend of GHG emissions from cultivation in the Chengdu Plain, indicating a pattern of growth followed by a fluctuating decline between 2005 and 2021. During this period, specifically between 2005 and 2009, emissions escalated from 5,148,900 t to 6,289,700 t, marking an increase of 1,140,800 t, or 22.16%. Before 2009, China’s agricultural economic growth relied excessively on chemical fertilizers and pesticides, among other factors, with the substantial increase in these inputs being a pivotal factor in the escalating greenhouse gas emissions from cultivation. From 2009 to 2021, emissions decreased from 6,289,700 t to 5,109,900 t, representing a reduction of 1,188,800 t, or 23.31%. After 2009, China implemented a series of low-carbon emission reduction and agricultural green development policies, catalyzing a transition in the cultivation industry from a lavish to a low-carbon and thrifty approach. Notably, initiatives such as the Action Program for Zero Growth in Fertilizer Use by 2020, the National Plan for Sustainable Agricultural Development (2015–2030), and the Comprehensive Work Program for Energy Conservation and Emission Reduction for the Thirteenth Five-Year Plan have facilitated the restructuring of agricultural production and the adoption of green technologies, effectively diminishing the utilization of high-emission materials such as nitrogen fertilizers and pesticides, thereby resulting in a year-on-year decline in greenhouse gas emissions.

In Fan Ziyue’s [42] investigation into the greenhouse gas emissions from China’s agricultural systems, the total emissions rose from 66,536.21 million t to 85,613.82 million t between 1980 and 2000, with an average annual growth rate of 1.43%. From 2000 to 2010, the average yearly growth rate of greenhouse gas emissions from the agricultural system was 1.34%. Since 2010, with the implementation of national strategies such as green development and the “Two-Oriented Society”, by 2020, the total greenhouse gas emissions from the agricultural system reached 97,041 million t, which is a decrease compared to 2010. In our study, the overall trend of greenhouse gas emissions rises and then fluctuates downward, similar to the findings of scholars including Fan Ziyue.

3.2. Characteristics of the Structure of Greenhouse Gas Emissions

Figure 4 shows that over the last 16 years, the proportions of emissions from GHG-emitting sources have been, in descending order, as follows: Nitrogen fertilizer Application (with an average annual emission of 2,560,410 t) > Nitrogen fertilizer Manufacturing (1,361,224 t) > Methane Emission from Rice Paddies (713,335 t) > Pesticide Manufacturing (580,324 t) > Pesticide Application (113,584 t) > Agricultural Films (72,880 t) > Agricultural diesel (27,073 t) > Irrigation (26,257 t) > Ploughing (2908 t); the specific numerical values are detailed in

Table 2. Greenhouse gas emissions by source (t CO₂-eq).

Vintages	Agricultural Diesel	Irrigated	Plough	Agro-Film	Pesticide Manufacturing	Pesticide Application	Nitrogen Fertilizer Manufacturing	Nitrogen Fertilizer Application	Rice Paddy Methane
2005	23,775	25,587	2902	78,280	536,721	113,341	1,200,420	2,366,672	801,218
2007	24,776	26,282	2970	86,936	561,733	116,022	1,307,578	2,590,127	791,942
2009	24,392	25,221	2939	93,509	567,920	114,784	1,332,429	3,353,149	775,397
2011	24,995	25,199	2917	101,114	570,455	113,942	1,417,644	2,675,395	739,568
2013	23,979	24,444	2818	100,052	570,455	110,067	1,428,104	2,532,874	708,669
2015	24,931	26,023	2745	110,609	570,455	107,207	1,306,522	2,385,460	685,329
2017	33,777	28,920	3107	45,083	645,473	121,347	1,453,964	2,503,646	700,242
2019	32,936	29,439	2898	21,007	602,121	113,197	1,404,911	2,332,342	607,687
2021	30,095	25,200	2876	19,329	597,584	112,344	1,399,446	2,304,023	609,966
Annual average	27,073	26,257	2908	72,880	580,324	113,584	1,361,224	2,560,410	713,335

. Nitrogen fertilizer application was the most dominant source of emissions, accounting for 46.77% of the total average annual emissions, followed by nitrogen fertilizer production with 25.02%, a finding consistent with that of other studies. An assessment by Cheng et al. [43] showed that 57–53% of the carbon footprint of crop production in China comes from nitrogen fertilizer use. Similarly, Hillier et al. [44], in their study in the UK, found that nitrogen fertilizers accounted for 75% of total emissions from crop production. Greenhouse gas emissions due to nitrogen fertilizer application and fertilizer production have generally experienced a change from an increase to a fluctuating decrease. It is evident that the efficient use of resources such as nitrogen fertilizer and the mitigation of its environmental impact are critical issues for the reduction of greenhouse gas emissions from the cultivation industry and the development of sustainable agriculture, and the reduction of nitrogen fertilizer application and the improvement of nitrogen fertilizer utilization are the key ways to reduce greenhouse gas emissions from the cultivation industry. The share of methane emissions from rice paddies in total greenhouse gas (GHG) emissions has declined from 15.36% in 2005 to 11.96% in 2021, primarily owing to an 83,900 ha reduction in the area of rice paddies, from 352,900 hectares to 269,900 ha. Greenhouse gas emissions from pesticide manufacturing, which accounted for 10.68% of total annual emissions, are closely related to the area under cultivation and have shown a downward trend since peaking in 2017. Average annual GHG emissions from agricultural films, agricultural diesel, irrigation, tillage, and pesticide application constitute about 1% of total average annual emissions. Fluctuations in these emission sources are primarily influenced by low-carbon agricultural policies, agricultural infrastructure development, and cultivation areas.

3.3. Analysis of Nitrogen Fertilizer Utilization and Destination of Nitrogen Fertilizer for Main Emission Sources

3.3.1. Nitrogen Fertilizer Utilization Rate

As shown in Figure 5, N fertilizer utilization rates for grain crops are generally higher than those for cash crops, with the latter having N fertilizer utilization efficiencies of less than 30%, leading to a severe waste of resources. This is a far cry from the study by Xin Zhang et al. [45], where the average NUE for global crop production needs to be increased from about 40% to about 70% to achieve the twin goals of food security and environmental management by 2050. Nitrogen fertilizer utilization rates for the two types of crops exhibit distinct patterns: a slight decrease in grain crops between 2005 and 2009, followed by a continuous increase from 2009 to 2021. Over the same period, nitrogen fertilizer utilization for cash crops (excluding vegetables) increased overall, whereas the opposite trend was observed for vegetables. The utilization of nitrogen fertilizer in crops is associated with fluctuations in nitrogen inputs and outputs. Higher nitrogen input results in lower utilization rates at a constant output level. These findings can be attributed to the lower nitrogen inputs for grain crops compared to those for cash crops. Although nitrogen application to grain crops initially increased and subsequently decreased, fertilizer application to cash crops, particularly vegetables, has continued to rise.

3.3.2. Nitrogen Surplus and GHG Emissions from Nitrogen Fertilizer Application

As illustrated in Figure 6 and Figure 7, distinct variations in nitrogen surplus and greenhouse gas (GHG) emissions per unit area are observed between two categories of crops. Between 2005 and 2009, the grain crops (rice, wheat, maize, and soybean) exhibited an increasing trend in nitrogen surplus and GHG emissions per unit area, peaking in 2009, followed by a declining trend up to 2021. Concurrently, the cash crops (tea and fruits) showed an overall decreasing trend in these parameters, while vegetables demonstrated a continuous increase. Cash crops generally have a higher nitrogen surplus and GHG emissions per unit area than grain crops. Specifically, among the cash crops, vegetables have the lowest mean annual nitrogen surplus per unit area, at 296.72 kg/ha, which is still higher than grain crops, with maize having the highest at 207.65 kg/ha. The tea crop has the highest mean annual nitrogen surplus per unit area, reaching 528.28 kg/ha. In terms of GHG emissions, the mean annual emissions per unit area for crops, ranked from highest to lowest, are as follows: tea (7039.14 kg CO₂ eq/ha), fruits (5094.67 kg CO₂ eq/ha), rice (4215.49 kg CO₂ eq/ha), vegetables (4205.56 kg CO₂ eq/ha), maize (2811.89 kg CO₂ eq/ha), wheat (708.24 kg CO₂ eq/ha), and soybean (228.38 kg CO₂ eq/ha). The annual mean GHG emissions of tea are 2823.65 kg CO₂ eq/ha higher than those of rice, which has the highest emissions among grain crops.

In terms of the total amount, the proportion of the total nitrogen surplus from grain crops was 56.91% in 2005, experiencing a slight increase to 58.34% in 2009, before gradually declining to 35.56% by 2021. In contrast, the total nitrogen surplus of cash crops decreased from 43.09% in 2005 to 41.66% in 2009 before rising to 64.44% in 2021. Over the past 16 years, the average annual total nitrogen surplus for each crop has been as follows: vegetables (69.6 million t), rice (47.7 million t), fruits (28.3 million t), maize (21.8 million t), wheat (18.1 million t), tea (6.60 million t), and soybeans (1.7 million t). As depicted in Figure 8, the total nitrogen surplus of vegetables ranked first and continued to rise with fluctuations, constituting 46.28% of the total nitrogen surplus in the Chengdu Plain by 2021. In comparison, the proportions of the nitrogen surplus for the other crops were, in descending order: rice (15.76%), fruits (14.60%), maize (13.79%), wheat (5.38%), tea (3.56%), and soybeans (0.64%).

As depicted in Figure 9, the greenhouse gas (GHG) emissions, standardized by the economic value of the crops (expressed in kilograms of carbon dioxide equivalent per US dollar), exhibited a secular increase for grain crops from 2005 to 2009, reaching a peak in 2009, followed by a declining trend through 2021. Within the category of cash crops, vegetables demonstrated a fluctuating upward trend in standardized emissions, whereas fruits and tea showed a decreasing trend. This phenomenon indicates a year-on-year fluctuating increase in the GHG emissions associated with producing each dollar’s worth of vegetables. The standardized emissions for grain crops are generally higher than those for cash crops. Rice has the highest mean annual emissions at 1.29 kg CO₂ eq/$, followed by maize (1.24 kg CO₂ eq/$), tea (0.55 kg CO₂ eq/$), fruits (0.46 kg CO₂ eq/$), wheat (0.41 kg CO₂ eq/$), vegetables (0.36 kg CO₂ eq/$), and soybeans (0.10 kg CO₂ eq/$). These data suggest that the GHG emissions per unit of economic value for grain crop production are comparatively higher than those for cash crops. This phenomenon is correlated with the pricing of crops. Cash crops are often considered luxury or specialty consumer goods, whereas grain crops (wheat, rice, maize, etc.) are essential commodities for basic living needs. Their prices are subject to governmental control or subsidies, resulting in relatively lower costs.

3.3.3. NH₃ Volatilization and Nitrogen Leaching

As shown in Figure 10, NH₃ volatilization and nitrogen leaching per unit area of grain crops increased annually between 2005 and 2009, reaching a peak in 2009 and declining until 2021. This trend can be attributed mainly to recent initiatives aimed at enhancing efficiency and reducing waste in grain crop production in the Chengdu Plain. Additionally, a series of measures have been implemented to improve nitrogen fertilizer efficiency in grain crops, resulting in an initial increase in nitrogen application intensity followed by a subsequent decrease. Between 2005 and 2021, NH₃ volatilization and nitrogen leaching per unit area increased for vegetables among cash crops, while they decreased for fruits and tea. NH₃ volatilization and nitrogen leaching per unit area are typically higher in cash crops compared to grain crops. Specifically, among cash crops, vegetables exhibit the highest annual average NH₃ volatilization per unit area, exceeding that of maize, the grain crop with the highest NH₃ volatilization per unit area, by 24.10 kg N/ha. This phenomenon stems from significant differences in the theoretical foundation and technical approaches to fertilizer reduction between cash crops and grain crops. Moreover, the promotion of fertilizer reduction in cash crops is inadequate and lacks widespread acceptance among farmers. On the one hand, the pursuit of high yields and quality vegetables driven by the market economy results in a yearly increase in nitrogen application. On the other hand, for economic reasons, farmers frequently rotate crops, causing a notable decline in soil fertility. As a result, excessive application of nitrogen fertilizer in farmland to maintain soil fertility has resulted in large amounts of nitrogen surplus, NH₃ volatilization, and nitrogen leaching due to incomplete crop uptake.

In terms of total volume, the proportion of total ammonia volatilization from cash crops decreased slightly from 37.01% in 2005 to 36.63% in 2009 before steadily increasing to reach 53.48% in 2021. Likewise, the proportion of total nitrogen leaching from cash crops decreased from 41.39% in 2005 to 32.73% in 2009 before gradually increasing to 54.62% in 2021, whereas the trend was converse for grain crops. Vegetables exhibit the highest total NH₃ volatilization and nitrogen leaching, comprising nearly half of the total emissions from 2019 onwards. The release of reactive nitrogen from agricultural soils presents numerous threats to the environment and human health, including groundwater contamination, eutrophication of freshwater and estuarine ecosystems, tropospheric pollution, and the accumulation of nitrous oxide (N₂O) resulting from NO_x and ammonia emissions. These environmental issues, notably climate change and the depletion of the tropospheric ozone layer, subsequently impact crop yields and human health.

In general, cash crops exhibit a low nitrogen fertilizer utilization rate (NUE) alongside high levels of nitrogen application intensity, nitrogen surplus, greenhouse gas (GHG) emissions, NH₃ volatilization, and nitrogen leaching; consequently, the environmental impacts associated with cash crops are more severe, offering more significant potential for emission reduction and efficiency improvement. Thus, reducing nitrogen fertilizer application and enhancing nitrogen fertilizer utilization, precisely the proportion of N inputs converted into harvested products in cash crops (particularly vegetables), represents a pivotal strategy for mitigating GHG emissions, improving crop productivity, and alleviating environmental degradation in the Chengdu Plain.

4. Discussion

Since 2015, the average nitrogen fertilizer use efficiency of grain crops in the Chengdu Plain (47.08%) has surpassed that of Japan (45.45%), and the efficiency of soybeans (56.43%) has reached more than the European Union standard (50.41%), showcasing the effectiveness of nitrogen fertilizer management in the region. In comparison with other countries in 2011, the efficiency of vegetable nitrogen fertilizer use in the Chengdu Plain (25.63%) was comparable to that of Sweden (28.72%). In contrast, the efficiency in the United States (73.37%) was 2.86 times higher than that of the Chengdu Plain, indicating that China’s nitrogen fertilizer inputs were nearly three times higher when yielding the same quantity of vegetables.

The nitrogen fertilizer utilization rate for cash crops remains below 30%, and the application of nitrogen fertilizer to vegetables has not yet achieved the national target of zero growth in fertilizer use. There remains a significant disparity compared to the international standard of excellence, primarily due to the irrational application of nitrogen fertilizer. Consequently, reducing nitrogen fertilizer application to cash crops, especially vegetables, and enhancing nitrogen fertilizer utilization represent pivotal strategies for mitigating greenhouse gas emissions from cash crop production in the Chengdu Plain.

Previous studies did not comprehensively incorporate all relevant emission sources when measuring GHG emissions from cultivation. Initially, studies predominantly focused on GHG emissions from agricultural materials. Subsequent research incorporated rice cultivation as an emission source; however, it overlooked the potential influence of varying moisture conditions on GHG emission coefficients during and before the rice cultivation period. Furthermore, while N fertilizer application has been recognized as a significant emission source, prior studies have primarily treated N fertilizer application as a collective entity and have not sufficiently considered emission factors specific to different crop species. Consequently, the current study has improved on the previous studies. Firstly, we have incorporated secondary emission sources, such as nitrogen fertilizer production, agricultural films, and pesticide manufacturing, into the emission calculation framework. Secondly, we meticulously differentiated between various emission factors attributable to differing moisture conditions during rice planting and pre-planting periods. Additionally, we have applied distinct emission factors for nitrogen fertilizer application. Variations in emission factors for nitrogen fertilizer application across different crop types necessitate a more nuanced approach to evaluating the impact of nitrogen fertilizer application on GHG emissions. By leveraging experimental data from other researchers, we identified precise emission factors for nitrogen fertilizer application across various crop species, enabling us to more accurately quantify the contribution of nitrogen fertilizer application to GHG emissions. This study not only comprehensively considers traditional emission sources but also meticulously examines emission sources that may have been neglected in previous studies. By considering various factors, our objective is to offer a more precise methodology for assessing GHG emissions from cultivation. Moving forward, we will explore additional potentially overlooked emission sources and refine our assessment methodology.

5. Conclusions

Utilizing IPCC and other greenhouse gas emission calculation methods, we assessed the Chengdu Plain’s annual emissions and emission structure from various sources during the cultivation of major crops in the region from 2005 to 2021. Then, it identifies nitrogen fertilizer as the primary factor contributing to high emissions from cultivation production. The paper conducts research and analysis on changes in the distribution and utilization of nitrogen fertilizer and proposes key strategies for reducing emissions from the cultivation sector. The specific conclusions are as follows:

Quantitatively, greenhouse gas emissions from the cultivation industry in the Chengdu Plain exhibited a trend of growth followed by fluctuation and subsequent decline from 2005 to 2021. Between 2005 and 2009, emissions increased from 5,148,900 t to 6,289,700 t, marking a rise of 1,140,800 t, or 22.16%. Subsequently, between 2009 and 2021, emissions decreased from 6,289,700 t to 5,109,900 t, representing a decline of 1,188,800 t, or 23.31%. This suggests a transition in cultivation production in the Chengdu Plain towards becoming a low-carbon green industry.

Regarding the structure of GHG emission sources, N₂O emissions from agricultural land resulting from nitrogen fertilizer application represent the primary source of greenhouse gas emissions, comprising approximately half of the total. This is followed by nitrogen fertilizer manufacturing, which collectively accounts for about 70% of the total. It can be seen that there is enormous potential to reduce the sources of GHG emissions surrounding the application and manufacture of nitrogen fertilizers and that the efficient use of resources such as nitrogen fertilizers and the mitigation of their environmental impacts are critical issues for the reduction of GHG emissions from the cultivation industry and the development of sustainable agriculture.

The proportion of greenhouse gas (GHG) emissions attributed to the cultivation of cash crops has seen a slight decline, followed by a steady rise, in stark contrast to the emissions from the cultivation of grain crops. Among the seven crops assessed, vegetables stand out as the most significant contributors to emissions, representing nearly half of the total emissions since 2019.

Nitrogen surplus, NH₃ volatilization, and nitrogen leaching per unit area were not only higher for cash crops compared to grain crops but also constituted the majority of the total, with vegetables representing the highest total N surplus, ammonia volatilization, and nitrogen leaching, comprising approximately half of the total in the study area since 2019. Generally, cash crops exhibit lower nitrogen use efficiency (NUE), higher nitrogen intensity, nitrogen surplus, GHG emissions, NH₃ volatilization, and nitrogen leaching. The environmental impacts associated with cash crops are more severe, presenting more significant potential for emission reduction and efficiency improvements overall.