Measurement and Comparison of Urban Haze Governance Level and Efficiency based on the DPSIR Model: A Case Study of 31 Cities in North China

Qinlin XIAO; Chao TIAN; Yanjun WANG; Xiuqing LI; Liming XIAO

doi:10.5814/j.issn.1674-764x.2020.06.002

Journals >Journal of Resources and Ecology >Volume 11 >Issue 6 >Page 549 > Article

Journal of Resources and Ecology
Vol. 11, Issue 6, 549 (2020)

Measurement and Comparison of Urban Haze Governance Level and Efficiency based on the DPSIR Model: A Case Study of 31 Cities in North China

Qinlin XIAO, Chao TIAN, Yanjun WANG, Xiuqing LI, and Liming XIAO^*

Author Affiliations

School of Economics and Management, Shanxi Normal University, Linfen 041000, Shanxi, China

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DOI: 10.5814/j.issn.1674-764x.2020.06.002 Cite this Article

Qinlin XIAO, Chao TIAN, Yanjun WANG, Xiuqing LI, Liming XIAO. Measurement and Comparison of Urban Haze Governance Level and Efficiency based on the DPSIR Model: A Case Study of 31 Cities in North China[J]. Journal of Resources and Ecology, 2020, 11(6): 549 Copy Citation Text

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Fig. 1. DPSIR model as applied to haze governance

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Fig. 2. Overall changes in the level and efficiency of urban haze governance in North China from 2007 to 2016

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Fig. 3. Distribution of urban haze governance level (a) and efficiency (b) in North China from 2007 to 2016

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Target layer	Rule layer	Index layer	Unit	Direction
Haze governance level	Driving force	Municipal public infrastructure investment	×10⁴ yuan	positive
		Urban personnel in the management of water conservancy, environment, and public facilities	×10⁴ person	positive
		Energy consumption per unit of GDP	tons of standard coal (×10⁴ yuan)^-1	negative
	Pressure	Effluent discharge	t	negative
		Sulfur dioxide emission	t	negative
		Dust discharge	t	negative
	State	Proportion of secondary industry	%	negative
	State	Mean of PM_2.5	μg m^-3	negative
	Impact	Domestic tourism revenue	×10⁴ yuan	positive
		Comprehensive utilization rate of solid waste	%	positive
		Green coverage in built-up areas	%	positive
	Response	Spending on science and technology as a share of GDP	%	positive
		Spending on education as a share of GDP	%	positive
		Number of patent applications granted in different regions	number	positive

Table 1.

Index system of haze governance level

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Index type	Primary index	Secondary indicators	Unit	Direction
Input indicators	Capital investment	Municipal public infrastructure investment	×10⁴ yuan	positive
		Spending on science and technology as a share of GDP	%	positive
		Spending on education as a share of GDP	%	positive
	Labor input	Urban personnel in the management of water conservancy, the environment, and public facilities	×10⁴ person	positive
	Technology input	Number of patent applications granted in different regions	number	positive
	Resources input	Energy consumption per unit of GDP	tons of standard coal (×10⁴ yuan)^-1	negative
Output indicators	Desirable output	Domestic tourism revenue	×10⁴ yuan	positive
		Comprehensive utilization rate of solid waste	%	positive
		Green coverage in built-up areas	%	positive
	Undesirable output	Industrial wastewater discharge	t	negative
		Industrial sulfur dioxide emissions	t	negative
		Industrial dust emission	t	negative
		PM_2.5	μg m^-3	negative

Table 2.

Index system of haze governance efficiency

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Region	Haze governance level						Haze governance efficiency						Indifference between rank of level versus efficiency
Region	2007	2010	2013	2016	Mean	Ranking for level	2007	2010	2013	2016	Mean	Ranking for efficiency	Indifference between rank of level versus efficiency
Taiyuan	0.736	0.696	0.871	0.855	0.777	1	1.042	1.066	1.212	1.279	1.165	16	↑
Shijiazhuang	0.652	0.604	0.524	0.650	0.629	2	1.003	1.036	1.040	1.029	1.011	24	↑
Hohhot	0.458	0.456	0.364	0.483	0.471	3	1.334	1.427	1.398	1.117	1.401	4	↑
Tangshan	0.485	0.510	0.339	0.342	0.448	4	1.023	1.033	1.022	1.013	0.945	26	↑
Baotou	0.434	0.407	0.342	0.392	0.419	5	1.235	1.328	1.183	1.242	1.214	13	↑
Handan	0.422	0.433	0.353	0.362	0.409	6	1.009	1.031	1.040	0.764	0.963	25	↑
Baoding	0.433	0.413	0.366	0.414	0.401	7	1.109	1.089	1.353	1.668	1.275	9	↑
Qinhuangdao	0.488	0.393	0.305	0.406	0.382	8	1.605	1.240	1.208	1.044	1.278	8	no change
Changzhi	0.354	0.378	0.336	0.361	0.365	9	1.006	0.733	0.691	1.006	0.810	29	↑
Datong	0.368	0.390	0.319	0.334	0.362	10	1.001	1.053	1.049	1.144	1.028	22	↑
Ordos	0.328	0.379	0.276	0.248	0.359	11	1.468	1.672	1.345	1.364	1.437	3	↓
Zhangjiakou	0.380	0.324	0.284	0.355	0.343	12	1.004	1.038	1.096	1.152	1.053	21	↑
Jinzhong	0.334	0.352	0.318	0.342	0.340	13	1.072	1.200	1.374	1.370	1.194	14	↑
Xinzhou	0.350	0.376	0.366	0.303	0.339	14	1.729	1.297	1.125	0.738	1.157	18	↑
Langfang	0.464	0.373	0.258	0.358	0.336	15	1.280	1.049	1.069	1.091	1.088	20	↑
Hulun Buir	0.312	0.321	0.282	0.289	0.327	16	2.251	2.394	1.955	1.211	1.912	1	↓
Chifeng	0.389	0.331	0.266	0.323	0.321	17	1.361	1.138	1.135	1.206	1.170	15	↓
Linfen	0.330	0.352	0.290	0.299	0.319	18	1.039	1.053	0.721	0.701	0.839	28	↑
Chengde	0.362	0.330	0.264	0.319	0.316	19	1.012	1.094	1.212	1.104	1.159	17	↓
Lvliang	0.285	0.320	0.314	0.313	0.313	20	1.398	1.058	0.725	1.001	1.138	19	↓
Jincheng	0.329	0.315	0.287	0.261	0.309	21	1.080	1.007	1.018	1.049	1.026	23	↑
Ulanqab	0.290	0.277	0.251	0.248	0.282	22	1.835	1.224	1.473	1.748	1.580	2		↓
Xingtai	0.309	0.305	0.211	0.296	0.275	23	1.084	1.048	1.003	0.562	0.865	27		↑
Wuhai	0.290	0.305	0.257	0.306	0.273	24	1.591	1.238	1.319	1.318	1.283	7		↓
Cangzhou	0.333	0.281	0.207	0.271	0.269	25	1.389	1.577	1.078	1.029	1.249	11		↓
Yuncheng	0.274	0.261	0.258	0.242	0.264	26	0.494	1.010	0.664	1.001	0.799	31		↑
Shuozhou	0.251	0.270	0.258	0.196	0.256	27	1.390	1.248	1.328	1.236	1.345	5		↓
Yangquan	0.285	0.302	0.227	0.210	0.255	28	1.106	1.132	1.251	1.232	1.263	10		↓
Bayan Nur	0.257	0.353	0.232	0.225	0.255	29	1.008	1.473	1.139	1.117	1.216	12		↓
Tongliao	0.281	0.303	0.229	0.219	0.252	30	0.662	1.182	1.081	0.840	0.808	30		no change
Hengshui	0.298	0.256	0.177	0.237	0.222	31	1.268	1.137	1.459	1.745	1.323	6		↓
Hebei	0.421	0.384	0.299	0.365	0.366	Ⅰ	1.162	1.125	1.144	1.109	1.110	Ⅱ		↑
Shanxi	0.354	0.365	0.349	0.338	0.354	Ⅱ	1.123	1.078	1.014	1.069	1.069	Ⅲ		↑
Inner Mongolia	0.338	0.348	0.278	0.304	0.329	Ⅲ	1.416	1.453	1.337	1.240	1.336	Ⅰ		↓
North China	0.373	0.367	0.311	0.337	0.351	‒	1.222	1.203	1.154	1.133	1.161	‒		‒

Table 3.

Comparisons of haze governance level and efficiency for 31 cities in North China

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Variable	Variable name	Unit	Observations	Mean	S.D.	Minimum value	Maximum value
hgl	Haze governance level	-	310	0.35	0.12	0.177	0.87
hge	Haze governance efficiency	-	310	1.16	0.31	0.484	2.66
pgdp	GDP per capita	yuan person^-1	310	48973.99	46015.47	8395	371725
is	Proportion of secondary industry	%	310	51.74	8.30	27.87	73.71
fdi	Actual utilization of foreign capital	×10⁴ yuan	310	228000	245000	1328.46	1300000
ds	Population density	person km^-2	310	4467.28	3429.06	248	12968
js	Proportion of construction land in urban area	%	310	13.15	14.21	0.67	97.18

Table 4.

Descriptive statistics of the main variables

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Variables	ln hgl		ln hge
Variables	Regression coefficient	T statistic	Regression coefficient	T statistic
C	0.2759^**	2.35	0.4642	0.74
ln pgdp	-0.0141^***	-3.48	-0.0786^***	-3.63
ln is	0.0530^**	2.19	0.1264	0.98
ln fdi	-0.0067^**	-2.15	0.0174	1.04
ln ds	0.0052	1.09	-0.0125	-0.49
ln js	-0.0008	-0.14	-0.0604^**	-2.02
R²	0.0935		0.0723
F-statistic	5.65		4.27
Prob(F-statistic)	0.0000		0.0000
N	310		310