EKC Test of the Relationship between Nitrogen Dioxide Pollution and Economic Growth—A Spatial Econometric Analysis Based on Chinese City Data

Abstract

During the just concluded 13th Five-Year Plan, China continued to maintain the momentum of rapid economic development, but still faced environmental pollution problems caused by this. Finding the relationship between Nitrogen Dioxide pollution and economic development is helpful and significant in better achieving and optimizing sustainable environmental development. Taking China’s 333 prefecture-level cities as samples from 2016 to 2018, the spatial lag model (SAR) was used to study the impact of economic growth on urban Nitrogen Dioxide pollution. The results show that Nitrogen Dioxide has strong positive characteristics of spatial spillover, but there is a linear relationship between economic growth and Nitrogen Dioxide concentration that slowly rises, and there is no inverted U-shaped relationship, which does not support the Environmental Kuznets Curve (EKC) hypothesis; The results also show the impact of per capita GDP, natural gas consumption, residential natural gas consumption, industrialization, and transportation development on the increase of Nitrogen Dioxide concentration, and the impact of green coverage on the decrease of Nitrogen Dioxide concentration. However, there is no significant relationship between technological investment and Nitrogen Dioxide concentration. The above conclusions are still valid after the robustness test, and recommendations are put forward to reduce Nitrogen Dioxide pollution.

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

“…The EKC assumes that environmental quality is initially degraded during the improvement of per capita income level, but gradually improves when the income reaches the inflection point, that is, the relationship between environmental quality and income is an inverted U-shaped [ 47 ]. Previous studies have shown that the EKC shows other trends, including type U, N, inverted N, monotonous decreasing, and monotonous increasing trends [ 14 , 18 ]. We found that the EKC of SO 2 emissions and per capita GDP in the YREB is N-shaped ( Figure 3 a) and that the 11 provinces in the YREB show N-shaped and inverted U-shaped curves ( Figure 3 b,c).…”

“…For example, previous studies have used this method to study the agglomeration characteristics of pollutants such as wastewater [ 14 ], carbon dioxide (CO 2 ) [ 15 ], fine particulate matter (PM 2.5 ) [ 16 ], and SO 2 [ 12 ], and have shown that there is a positive spatial autocorrelation of SO 2 concentration in China; that is, the SO 2 concentration in an area will increase because air pollutant spread is affected by nearby areas [ 9 , 12 ]. The EKC has been used to explain the relationship between pollutants and economic development, such as CO 2 [ 17 ], SO 2 [ 13 ], nitrous oxide (NO 2 ) [ 18 ], and wastewater [ 14 ]. According to the EKC, the relationship between national incomes and their contribution to environmental degradation resembles an inverted U-shaped curve [ 19 ].…”

Impact of Coastal Urbanization on Marine Pollution: Evidence from China

“…According to Anselin, the Moran’s I can measure whether there is interdependence between variables in space [ 41 ]. Furthermore, Moran’s I has been widely utilized to examine spatial correlations of spatially adjacent regional units [ 42 , 43 ]. The specific formula is shown in Equation (1): where is the sample variance, is the ( , ) element of the spatial weight matrix, and the value of the Moran’s I is generally between −1 and 1.…”

Reexamining the Environmental Kuznets Curve in Chinese Cities: Does Intergovernmental Competition Matter?

“…Several types of factors, which generally have been investigated separately in the previous literature, have been verified to influence the validity of the EKC hypothesis, and they include: (1) pollutant indicators––such as flow pollutants (e.g., SO 2 and NO x ), which cause immediate damage and elicit constant pressure on the administrative authorities, and stock pollutants (e.g., CO 2 and heavy metal wastes), which harm the environment later and long into the future, and which some myopic governments allow to grow with income [ 18 ]; (2) regional discrepancies––which are especially salient because economic scale and income accumulation remain significantly unbalanced across the eastern, middle, and western regional divisions in China [ 2 , 19 ]; (3) trade openness and technology aggregation––which imply that increasing scale effects arise from production expansion, that composition effects arise due to the shifting of “dirty” industries, and that technique effects occur because of the advancement of technology and distribution [ 1 , 13 , 19 ]; (4) the industrial and energy structure––which, because China’s energy consumption structure remains coal-dominated, its rapid industrialization would stimulate rigid demands for energy and present sustained growth of pollutant emissions [ 3 , 16 ]; (5) governments’ environmental regulation and policy preferences––which, in the face of fundamentally conflicting objectives between economic growth and environmental preservation, can cause local governments to tend to strategically implement top-down environmental regulations, consequently leading to varying income–pollution nexuses in different localities [ 3 , 20 ]; and (6) pollution diffusion––which is salient because geographically adjacent regions share many characteristics in terms of factor endowments, development patterns, and institutional environments that may cause them to present an interactive strategy for emissions reduction, as well as an interrelated income–pollution nexus [ 21 , 22 ] (as shown in Table 1 ).…”