| Literature DB >> 33218109 |
Penghao Ye1,2, Senmao Xia3, Yu Xiong4, Chaoyang Liu5, Fei Li5, Jiamin Liang2, Huarong Zhang1.
Abstract
Thermal power generation based on coal-fired power plants has the advantages of stability and controllability and has been the largest source of electricity supply in China. Coal-fired power plants, however, are also accompanied by high carbon emissions and the release of harmful substances (mainly including sulfur dioxide, nitrogen oxides, and smoke dust), and are even regarded as the "chief criminal" in terms of air pollution. However, thermal power is also a pioneering industry involved in several environmental regulations and cleaner production techniques before other industries. Evidence of this is China's ultra-low emissions (ULE) policy on coal-fired power plants, implemented in 2015. To verify this policy's effect, this study treats ULE as an exogenous impact variable, examining its emissions reduction effect on SO2, NOx, and smoke dust in Eastern and Central China using the difference-in-difference method (DID). The results show that the total emissions of the three pollutants were abated by 0.133%, 0.057% and 0.036% in Eastern, and by 0.120%, 0.035% and 0.043% in Central China at every 1% rise of thermal power generated after ULE. In addition, several other factors can also argue for the promotion of thermal power. Other industries, such as steel or chemical, have proven that they can contribute significant SO2 and NOx emissions. Based on these results, we provide suggestions on synergistic emissions reduction among multiple industries, as well as a discussion on the necessity of implementing ULE in Western China.Entities:
Keywords: NOx; SO2; difference-in-difference; emission reduction; smoke dust; thermal power industry; ultra-low emission
Mesh:
Substances:
Year: 2020 PMID: 33218109 PMCID: PMC7698952 DOI: 10.3390/ijerph17228555
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1World gross generation and world coal-fired power generation from 1971 to 2018 (data source: World Bank/International Energy Agency).
Figure 2Proportion of coal-fired power generation to total power generation from 1999 to 2018 (data source: World Bank/International Energy Agency).
Figure 3Statistics on China’s electricity production at different stages from 1952 to 2017 (data source: National Bureau of Statistics of China).
Current limitation standards and the limiting value of thermal power in China.
| Emission Standard’s Name | Date of Issue | Concentration Limits (mg/m3) | ||
|---|---|---|---|---|
| SO2 | NOx | Smoke Dust | ||
| Emission standards for air pollutants from coal-fired power plants | Sep 2011 | 100 | 100 | 30 |
| Standards for the discharge of atmospheric pollutants from boilers 1 | May 2014 | 300 (400) | 300 (400) | 50 (80) |
| Energy Development Strategic Action Plan (2014–2020) 2 | June 2014 | No new restricted limits proposed | ||
| Coal-fired energy-saving emission reduction upgrade and transformation action plan (2014–2020) | Sep 2014 | 35 | 50 | 10 |
| Full implementation of the ultra-low emission and energy-saving transformation work plan for coal-fired power plants 2 | Mar 2015 | 35 | 50 | 10 |
Note: 1 Values without brackets are the emissions limits for newly-built boilers while bracketed values are the emissions limits for existing boilers. This standard is relevant for all industries, including coal-fired power plants using coal-fired boilers. The development level varies in different industries, such that the standard limits are relatively loose. 2 The Energy Development Strategic Action Plan (2014–2020) states that the emissions reduction limits for Eastern, Central, and Western China are different from the concentration limits, whereas the full implementation of the ultra-low emission and energy-saving transformation work plan for coal-fired power plant requires identical emissions reduction limits for Eastern, Central, and Western China, but with different completion times.
Figure 4The availabilities of three fossil fuels and their total amount in China from 1998 to 2017 (Data source: China Energy Statistical Yearbook).
Figure 5Flowchart of ULE implementation.
Figure 6Distribution of thermal and hydropower generation in Eastern (green), Central (yellow), and Western (purple) China in 2017 (data source: [31]).
Figure 7Proportion of electricity generated by hydropower/thermal power from 2009 to 2017 in Eastern China, Central China, and in two western provinces.
Control variable set corresponding to the three emissions.
| Name of Control Variable (Unit) | Symbol | Generated Pollutant | Taking the Logarithm or Not |
|---|---|---|---|
| Crude steel |
| SO2 | Yes |
| Sulfuric acid (in 100%) |
| SO2 | Yes |
| Chemical fertilizer (in NPK 1) |
| NOx | Yes |
| Vehicle holdings |
| NOx and smoke dust | Yes |
| Annual fixed-asset investment (trillion CNY) |
| Smoke dust | Yes |
Note: 1 “in NPK” means the weight of the chemical fertilizer has been converted into the content of nitrogen, phosphorus pentoxide, and potassium chloride [39].
Descriptive statistics of the main variables.
| Variable | Region | Obs | Mean | St.d | Min | Median | Max | Unit |
|---|---|---|---|---|---|---|---|---|
|
| East | 63 | 1 | 0 | 1 | 1 | 1 | - |
| Central | 70 | 1 | 0 | 1 | 1 | 1 | ||
| West | 14 | 0 | 0 | 0 | 0 | 0 | ||
|
| East | 63 | 220.279 | 129.192 | 58.732 | 225.860 | 514.288 | billion kWh |
| Central | 70 | 147.094 | 95.242 | 51.625 | 89.721 | 375.033 | ||
| West | 14 | 44.850 | 13.520 | 23.804 | 46.072 | 62.810 | ||
|
| East | 63 | 0.668 | 0.471 | 0.019 | 0.593 | 1.827 | million tons |
| Central | 70 | 0.630 | 0.370 | 0.166 | 0.525 | 1.409 | ||
| West | 14 | 0.652 | 0.164 | 0.384 | 0.668 | 0.902 | ||
|
| East | 63 | 0.862 | 0.499 | 0.142 | 0.843 | 1.801 | million tons |
| Central | 70 | 0.728 | 0.355 | 0.255 | 0.606 | 1.665 | ||
| West | 14 | 0.330 | 0.071 | 0.224 | 0.340 | 0.429 | ||
|
| East | 63 | 0.505 | 0.417 | 0.047 | 0.354 | 1.798 | million tons |
| Central | 70 | 0.523 | 0.282 | 0.188 | 0.447 | 1.507 | ||
| West | 14 | 0.330 | 0.071 | 0.224 | 0.340 | 0.429 | ||
|
| East | 63 | 2.238 | 2.645 | 0 | 0 | 6.243 | - |
| Central | 70 | 2.062 | 2.436 | 0 | 0 | 5.927 | ||
| West | 14 | 0 | 0 | 0 | 0 | 0 |
Note: As certain control variables are missing in the data source, the eastern municipality of Beijing and the eastern Hainan province were not be incorporated in this empirical analysis.
Regression outcome for the ULE’s reduction effect on SO2.
| Explained Variable | Region |
| Control Variable |
|
| Constant | R2 within | Obs. |
|---|---|---|---|---|---|---|---|---|
|
| Eastern | −0.124 *** | No | - | - | −0.455 * | 0.447 | 77 |
| −0.133 *** | Yes | 0.517 *** | 0.321 *** | −2.408 * | 0.422 | 77 | ||
| Central | −0.121 *** | No | - | - | −0.388 *** | 0.529 | 84 | |
| −0.120 *** | Yes | 0.054 | −0.039 | −518 | 0.527 | 84 | ||
|
| Eastern | −0.140 *** | No | - | - | −5.365 *** | 0.483 | 77 |
| −0.149 *** | Yes | 0.057 | 0.299 *** | −5.724 *** | 0.477 | 77 | ||
| Central | −0.148 *** | No | - | - | −4.960 *** | 0.531 | 84 | |
| −0.144 *** | Yes | −0.420 *** | 0.109 ** | −3.824 | 0.506 | 84 |
Note: ***, **, and * represent the statistical significance at the 1%, 5%, and 10% level. The values in the brackets are the t statistics.
Regression outcome for the ULE reduction effect on NOx.
| Explained Variable | Region |
| Control Variable |
|
| Constant | R2 within | Obs. |
|---|---|---|---|---|---|---|---|---|
|
| Eastern | −0.078 *** | No | - | - | −0.273 | 0.587 | 77 |
| −0.057 *** | Yes | 0.213 *** | −0.167 | 0.053 | 0.646 | 77 | ||
| Central | −0.093 *** | No | - | - | −0.304 *** | 0.640 | 84 | |
| −0.053 *** | Yes | 0.076 * | −0.393 *** | 0.128 | 0.758 | 84 | ||
|
| Eastern | −0.091 *** | No | - | - | −5.188 *** | 0.628 | 77 |
| −0.065 *** | Yes | 0.168 *** | −0.256 ** | −4.717 *** | 0.648 | 77 | ||
| Central | −0.110 *** | No | - | - | −4.893 *** | 0.605 | 84 | |
| −0.098 *** | Yes | −0.021 | −0.144 | −4.700 *** | 0.630 | 84 |
Note: ***, **, and * represent the statistical significance at the 1%, 5%, and 10% level and the values in the brackets are the t statistics.
Regression outcomes for the ULE reduction effect on smoke dust.
| Explained Variable | Region |
| Control Variable |
|
| Constant | R2 within | Obs. |
|---|---|---|---|---|---|---|---|---|
|
| Eastern | −0.032 *** | No | - | - | −1.014 *** | 0.097 | 77 |
| −0.036 * | Yes | 0.196 | −0.194 | −1.017 *** | 0.092 | 77 | ||
| Central | −0.047 *** | No | - | - | −0.838 *** | 0.174 | 84 | |
| −0.043 *** | Yes | −0.015 | −0.028 | −0.076 *** | 0.178 | 84 | ||
|
| Eastern | −0.043 *** | No | - | - | −5.932 *** | 0.143 | 77 |
| −0.052 *** | Yes | 0.064 | −0.063 | −6.148 *** | 0.154 | 77 | ||
| Central | −0.058 *** | No | - | - | −5.685 *** | 0.210 | 84 | |
| −0.041 *** | Yes | −0.287 | 0.124 | −5.458 *** | 0.220 | 84 |
Note: *** and * represent the statistical significance at the 1% and 10% levels and the values in the brackets are the t statistics.
Figure 8Parallel trend test for the treated and control groups.
Placebo test results.
| Explained Variable | Region |
| Execution Year | Timespan | Control Variable | R2 Within | Obs. |
|---|---|---|---|---|---|---|---|
|
| East | −0.019 * | 2011 | 2009–2014 | Yes | 0.000 | 66 |
| Central | −0.015 * | 2011 | 2009–2014 | Yes | 0.113 | 72 | |
|
| East | −0.007 | 2012 | 2011–2014 | Yes | 0.027 | 44 |
| Central | 0.001 | 2012 | 2011–2014 | Yes | 0.837 | 48 | |
|
| East | 0.009 | 2013 | 2011–2014 | Yes | 0.422 | 44 |
| Central | 0.014 | 2013 | 2011–2014 | Yes | 0.198 | 48 |
Note: * represents the statistical significance at 10% level and the values in the brackets are the t statistics.