This study selects 20 indices of economic and environmental conditions over 15 years (1996–2010) for 14 cities in Liaoning province, China. We calculate the economic score
With the rapid pace of industrialization and urbanization in Liaoning province, the growing problems of urban environmental pollution and ecological destruction have become more serious. The joint desires of economic development and improving environmental quality have become seemingly incompatible. How to coordinate economic growth with environmental protection has become a focus of national attention and academic research.
In previous studies, both quantitative and qualitative, on the coordination degree between the economy and environment (
According to the first law of geography, the values of geographic variables in neighboring locations may be more similar or less similar than expected for randomly distributed locations [
This study uses the ESDA technology to analyze interurban differences of
Located in the northeast economic zone and the Bohai sea economic circle, Liaoning province (38°43′-43°26′ N, 118°53′-125°46′ E) has a solid heavy industry foundation and a long history. Since the introduction of Chinese economic reform, the Liaoning economy has experienced rapid growth, with resource and energy demand increasing constantly. Constraints between resources and the environment have become a significant bottleneck to the economic development of Liaoning province [
The scope and location of Liaoning province.
The heavy industry plays a leading role in the economic development of Liaoning province and also influences environment quality. Taking into account regions, data availability, and scientific evaluation, we select 20 indexes in 14 cities in Liaoning province during 1996–2010 [
The regional economic variables are
The regional environment variables are the emission of industrial
When constructing the environment indexes, an “inverse index” is one where the smaller of the index is, the better over a certain range; while the higher value of “direct index”, the better [ direct index:
inverse index:
In order to achieve the “reduced dimension,” we perform a principal component analysis of the economic and environmental indices for 14 cities using the statistical software SPSS16.0 and select the principal component factor, whose cumulative contribution rate is above 85%. As a result, we obtain an economic principal component factor
According to the definition of coordination degree, we suppose
The coordination development degree calculation formula of Yang [
Using these formulas, we calculate the coordination development degree of economic and environmental
The coordination development degree of economy and environment in Liaoning province (1996–2010).
a | b | c | d | e | f | g | h | i | j | k | l | m | n | o | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1996 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.09 | 0.00 | 0.32 | 0.00 | 0.00 | 0.00 | 0.03 | 0.00 | 0.10 | 0.04 |
1997 | 0.11 | 0.37 | 0.00 | 0.00 | 0.24 | 0.00 | 0.33 | 0.00 | 0.27 | 0.30 | 0.24 | 0.00 | 0.16 | 0.00 | 0.14 |
1998 | 0.00 | 0.50 | 0.17 | 0.19 | 0.45 | 0.14 | 0.39 | 0.00 | 0.38 | 0.26 | 0.46 | 0.00 | 0.15 | 0.32 | 0.24 |
1999 | 0.47 | 0.39 | 0.34 | 0.39 | 0.46 | 0.00 | 0.38 | 0.22 | 0.43 | 0.38 | 0.39 | 0.33 | 0.32 | 0.08 | 0.33 |
2000 | 0.47 | 0.61 | 0.49 | 0.49 | 0.67 | 0.31 | 0.19 | 0.29 | 0.44 | 0.50 | 0.00 | 0.39 | 0.42 | 0.00 | 0.38 |
2001 | 0.49 | 0.70 | 0.46 | 0.48 | 0.70 | 0.45 | 0.00 | 0.32 | 0.59 | 0.00 | 0.34 | 0.48 | 0.00 | 0.21 | 0.37 |
2002 | 0.68 | 0.81 | 0.57 | 0.52 | 0.31 | 0.50 | 0.35 | 0.35 | 0.69 | 0.51 | 0.40 | 0.47 | 0.42 | 0.41 | 0.50 |
2003 | 0.77 | 0.78 | 0.70 | 0.66 | 0.79 | 0.56 | 0.52 | 0.43 | 0.66 | 0.70 | 0.50 | 0.63 | 0.52 | 0.76 | 0.64 |
2004 | 0.87 | 0.90 | 0.77 | 0.73 | 0.93 | 0.61 | 0.54 | 0.67 | 0.79 | 0.82 | 0.61 | 0.76 | 0.60 | 0.83 | 0.74 |
2005 | 0.86 | 0.97 | 0.97 | 0.80 | 0.93 | 0.70 | 0.56 | 0.87 | 0.82 | 0.79 | 0.60 | 0.84 | 0.72 | 0.67 | 0.79 |
2006 | 0.91 | 0.92 | 0.85 | 0.77 | 0.72 | 0.75 | 0.74 | 0.82 | 0.94 | 0.83 | 0.54 | 0.85 | 0.93 | 0.75 | 0.81 |
2007 | 0.93 | 0.97 | 0.83 | 0.84 | 0.74 | 0.80 | 0.80 | 0.89 | 0.86 | 0.87 | 0.75 | 0.84 | 0.96 | 0.81 | 0.85 |
2008 | 0.92 | 0.96 | 0.95 | 0.90 | 0.86 | 0.76 | 0.87 | 0.96 | 0.90 | 0.80 | 0.77 | 0.90 | 0.97 | 0.91 | 0.89 |
2009 | 0.93 | 0.94 | 0.97 | 0.91 | 0.88 | 0.84 | 0.87 | 0.95 | 0.96 | 0.83 | 0.97 | 0.86 | 0.96 | 0.87 | 0.91 |
2010 | 0.99 | 0.97 | 1.00 | 0.96 | 0.91 | 1.00 | 1.00 | 0.97 | 0.96 | 0.95 | 0.99 | 0.88 | 0.95 | 0.93 | 0.96 |
a: “Shenyang,” b: “Dalian,” c: “Anshan,” d: “Fushun,” e: “Benxi,” f: “Dandong,” g: “Jinzhou,” h: “Yingkou,” i: “Fuxin,” j: “Liaoyang,” k: “Panjin,” l: “Tieling,” m: “Chaoyang,” n: “Huludao,” o: “Liaoning province.”
For spatial data with thematic attributes, spatial autocorrelation analysis techniques are frequently used [
Moran’s
Year | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
−0.18 | −0.26 | −0.23 | −0.09 | 0.17 | 0.062 | −0.09 | −0.11 | −0.11 | 0.13 | 0.025 | −0.13 | −0.04 | 0.079 | −0.03 |
In order to test the null hypothesis of no spatial autocorrelation and conclude the Moran’s
Moran's
We classify the economic and environmental coordinated development condition of Liaoning province during 1996–2010 [
The classification for
Value | Year | Type | |
---|---|---|---|
Coordinated development |
|
2006–2010 | Senior concordance development |
|
2003–2005 | Moderate concordance development | |
Harmonic development |
|
2002 | Low concordance development |
Disorder recession |
|
1998–2001 | Moderate disorder recession |
|
1996-1997 | Serious disorder recession |
Based on the values of Overall, between 1996 to 2010, the economic and environmental coordinated development condition of Liaoning province has been rising continuously. Generally speaking, Analyzing the difference between Analyzing
The evolutional trend of the coordination development degree between economy and environment in Liaoning Province (1996–2010).
Local spatial autocorrelation takes every local unit as the target item and can reveal the similarity and correlation among a local unit and the adjacent ones. It can also identify spatial agglomeration and spatial isolation and detect spatial heterogeneity. Local indicator of spatial association (LISA) is the most commonly used in local spatial autocorrelation. “High-High” means there is a conglomeration effect of high value among one region and the adjacent areas; “Low-Low” means; there is a conglomeration effect of low values. In each, the attributes of adjacent areas are inclined to be consistent with each other. However, “High-Low” and “Low-High” mean that the attributes of adjacent regions are in great disparity with each other [
LISA cluster map for the economic and environment coordination development degree of intercity in Liaoning province.
As Figure
As Figure
In 1996 and 2004, Huludao belonged to the “High-Low” type. The
Yingkou rises from the “High-Low” type in 1996 to the “High-High” type in 2009. The condition of economic and environmental coordinated development has been rising all the time. Even as the economic and environmental coordinated development of the adjacent cities increased, Yingkou remained a high gathered city, which indicates that the regional
In 2005, Chaoyang belonged to the “Low-Low” type. Its degree of space discreteness is high, and the
Using measures of spatial dimension, this study analyzes the economic and environmental coordinated developmental condition of Liaoning province during 1996–2010. We find that the high value city of coordinated development degree changes from a scattering in Liaoning province to a clustering in middle-south of Liaoning province, which located in the Liaodong peninsula: south to the coastal economic zone, and Dalian is the center of this area; north extending to the central urban agglomeration of Liaoning province, and its center is Shenyang, including Anshan, Fushun, Benxi, Liaoyang, and Tieling; east to the railway (highway) of Shenyang-Dandong; and west to the south of the railway (highway) of Yelin et al. [
Through analyzing the spatiotemporal