1. Introduction
With the pursuit of high economic growth and a high standard of living worldwide, the environmental quality has been dramatically affected. Climate change and environmental pollution pose a serious threat to sustainable development and human health worldwide, which has aroused widespread concern [
1]. In recent years, China’s air pollution crisis has become one of the most urgent environmental problems in China. China has experienced severe haze pollution, and the load of PM
2.5 (particles with an aerodynamic diameter of less than
2.5 microns) is too high [
2]. According to research by the World Health Organization (WHO), air pollution causes
800,000 deaths every year, among which PM
2.5 produces the greatest influence on human health [
3]. PM
2.5 can absorb a large number of toxic substances because of its large surface area and high enrichment effect [
4]. In many epidemiological studies, PM
2.5 has been related to cerebrovascular, respiratory, and cardiovascular diseases [
5]. Most researchers have found that long-term exposure to PM
2.5 will negatively affect the heart and lungs [
6]. For every
ten gm3 increase in PM
2.5, respiratory mortality increases by
1.01%, and cardiovascular diseases increases by
1.04%. In addition, the rising speed of PM
2.5 also leads to increases of
0.48% and
0.60% in the hospitalization rates of the respiratory system and cardiovascular diseases, respectively [
3].
As a serious air pollutant, PM
2.5 is mainly affected by the surrounding environmental conditions, industrial production activities, meteorological factors, and the excessive use of chemical fertilizers (nitrogen-containing components) in agricultural production and other human activities [
5]. Some studies show that urbanization has an impact on the PM
2.5 levels [
7,
8]. In addition, on the macroscale, meteorological conditions have been proven to have a considerable impact on PM
2.5 pollution [
3]. According to a study conducted in northern and western China [
9], dust in spring/autumn will increase primary particles. PM
2.5 pollution is also significantly related to land use patterns [
10]. Li and Shen [
11] believe that optimizing land use patterns at the city or community level is helpful for reducing PM
2.5 pollution.
In many parts of China, PM
2.5 pollution is mainly affected by NH
3 emissions [
12], because secondary inorganic aerosols are the main component of PM
2.5 [
13]. As the only alkaline component in the atmosphere, NH
3 can neutralize with sulfuric acid (H
2SO
4) and nitric acid (HNO
3) in the atmosphere, producing a large number of secondary inorganic aerosols (the sum of sulfate, nitrate, and ammonium), causing severe haze pollution [
14]. Moreover, ammonia from agricultural fertilizers is a major contributor to PM
2.5 pollution around the world. Kawashima et al. (2022) found that ammonia from the use of agricultural fertilizers is a significant source of PM
2.5 pollution [
15]. In addition, Kang et al. (2022) found that ammonia produced by inorganic fertilizers and organic fertilizers had no significant differences in terms of soil impact [
16].
At present, China has become the world’s largest emitter of NH
3 [
17]. China is a big agricultural country, and chemical fertilizers play an important role in global food production [
18,
19]. China’s fertilizer application has exceeded the economical optimal application rate [
20]. Chemical fertilizer is one of the primary sources of atmospheric NH
3 [
21]. NH
3 emissions from agricultural sources account for more than
80% of the total NH
3 emissions, including livestock and nitrogen fertilizer applications [
22,
23]. On average, only
30% to
50% of nitrogen is absorbed by crops [
24], and a large amount of active nitrogen (Nr) is lost to the environment [
25]. Nutrients that cannot be absorbed by crops seep into water or escape into the atmosphere, resulting in various environmental problems [
26].
Controlling agricultural NH
3 emissions has been proven to effectively reduce PM
2.5 levels [
27]. To reduce NH
3 emissions from the source, on one hand, it is necessary to reduce the use of chemical fertilizers. On the other hand, it is necessary to improve the use efficiency of chemical fertilizers. As the market for the transfer of farmland rights continues to mature, the number of land transfers is increasing, and the number of large-scale farmers is also gradually increasing. Farmers with large farms are the main force in China’s future use of organic fertilizers, as they can pursue greater long-term agricultural benefits in this way [
28]. Under the condition of reducing the number of applied chemical fertilizers, large-scale land management will not lead to a decline in output [
29]. Meanwhile, for every 1% increase in farm scale, fertilizer use efficiency increases by 0.2%, reducing the environmental pollution caused by excessive use of chemical fertilizers [
30].
The geographical and temporal distribution, source analysis, health consequences, and estimation of PM
2.5 have been extensively studied by predecessors [
31], and much valuable empirical evidence about PM
2.5 pollution has been produced. However, few studies have paid attention to the relationship between land transfer, fertilizer usage, and PM
2.5 pollution. Similarly, there is no consensus on the actual nature of their interaction. However, it is urgent and vital to investigate the relationship between land transfer, fertilizer usage, and PM
2.5 pollution. Taking China as an example, this paper discusses the relationship between land transfer, fertilizer use, and PM
2.5 concentration by using various econometric methods.
Our research is particularly important for improving China’s air pollution and policy-making, and it has made scientific contributions in the following three aspects: Firstly, we used the panel vector autoregression (PVAR) model to reflect the heterogeneous influence of land transfer and fertilizer usage. As far as we know, this was the first time in China that the PVAR method has been used to study the relationship between land transfer, fertilizer usage, and PM2.5 pollution. The method helps to determine the direction of causality among PM2.5 air pollution, land transfer rate, and fertilizer use and helps to identify changes in the short-term and long-term effects between variables. Secondly, PM2.5 seriously threatens human life and health. Exploring the important sources of PM2.5 and putting forward targeted and effective policies to reduce PM2.5 pollution is of great significance. Finally, the Chinese government intends to achieve peak carbon emissions in 2030 and achieve carbon neutrality in 2060. China’s situation is attractive to the world. This paper is one of the few studies that has attracted international attention to key issues such as land transfer, fertilizer usage, and PM2.5 pollution in China.
The rest of this paper is organized as follows:
Section 2 consists of a literature review and the construction of the research hypotheses;
Section 3 includes the data sources and econometric methods;
Section 4 introduces and discusses the empirical results; and the last section includes a summary and policy suggestions.
5. Conclusions and Policy Implications
Environmental pollution has become an increasingly important obstacle to the development of all countries in the world. Alleviating air pollution has become an imminent concern, and is also related to the realization of a better life and the sustainable development of human beings in the future. Therefore, exploring the influencing factors and emission reduction measures of PM2.5 emissions is of great significance. This paper studied the causal relationship between land transfer, fertilizer usage, and PM2.5 pollution. It considered the influence of economic development and urbanization on carbon emissions through a whole set of empirical processes, having obtained the corresponding empirical results.
First, the cross-sectional correlation test verified that there was a dependency between land transfer, fertilizer use, and PM
2.5. The unit root test of the panel data was carried out using an LLC test, an IPS test, an ADF test, and a PP test to analyze the stationarity of the variables. The test results in
Table 3 showed that the variables after the first-order difference were stationary, indicating that the LnPM
2.5, Lnfertilizer, and Lnlandtransferate sequences were single-integrated sequences of the same order, and that the PVAR model can be regressed. At the same time, the results of the Kao test rejected the null hypothesis, “there is no cointegration relationship between variables”, indicating a cointegration relationship between the three variables.
In the subsequent stationarity test of the PVAR model, it can be observed that all the reciprocals of the unit root were less than one, and the blue bullets were distributed within the unit circle. The estimation results of FMOLS and DOLS mainly showed the influence coefficient of chemical fertilizer use and land transfer on PM
2.5. The results all showed that fertilizer use was positively correlated with PM
2.5 emissions, but land transfer was negatively correlated with them. The Granger causality test was used to test the causal relationship between PM
2.5, land transfer, and fertilizer use. The results showed that there was a causal relationship between the three variables, and they affected each other. The impulse response function of the PVAR model (shown in
Figure 4) more intuitively reflects the dynamic interaction and effect size of fertilizer use on PM
2.5. The conclusion is that fertilizer use increases PM
2.5 in the short term, and variance decomposition also evaluates the contribution rate of each variable to the fluctuation of endogenous variables.
Through the demonstration of the empirical results, the validity and significance of putting chemical fertilizer use, PM
2.5, and land circulation into the same system for research are ensured. At the same time, it ensures the correctness of the model construction, with no false regressions. FMOLS, DOLS estimation results, impulse response function, and variance decomposition reached the same conclusion: that fertilizer use increased PM
2.5 emissions and brought environmental pollution. This is consistent with the research views and conclusions of Li et al. [
62], who determined that reducing agricultural NH
3 emissions can effectively reduce PM
2.5 pollution [
63]. Xu et al. [
64] believed that PM
2.5 was significantly positively correlated with cultivated land area, and the fragmentation of cultivated land was beneficial to the decrease of PM
2.5. However, the correlation coefficient between the land transfer rate and PM
2.5 emissions was negative at the 1% significance level, indicating that an increase in land transfer rate would reduce PM
2.5 emissions. land transfer has greatly increased the land scale of large-scale farmers, has improved production efficiency [
11], and has encouraged large-scale farmers to apply organic fertilizers [
65], which can alleviate some environmental problems.
Based on the above research and conclusions, the following policy recommendations are put forward: (1) The government should actively promote and accelerate land transfers so that future land operations will develop on a large scale. At the same time, it should ensure the stability of land transfer quality and management rights to protect large-scale farmers’ rights and interests, encourage them to replace chemical fertilizers with organic fertilizers, and pursue the long-term interests of the land. (2) Optimize land use to actively promote ecological land improvement; improve extensive agricultural management; establish farmers’ awareness of the multidimensional balance between social, economic, and ecological benefits; and reduce PM2.5 pollution to improve air quality. (3) Implement a land rotation system, reduce agricultural production intensity, attach importance to the treatment and effective control of crop fertilizer residues, increase technology research and development, and use various advanced technologies to control agricultural ammonia emissions.
This study still has some limitations, such as using the PVAR model to treat the research variables as endogenous variables, ignoring that other activities (such as industrial activities) in the sample area may also increase PM2.5 pollution. Considering other factors that may affect PM2.5 pollution is a direction for further research.