scholarly journals Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions

2018 ◽  
Author(s):  
Bo Zheng ◽  
Dan Tong ◽  
Meng Li ◽  
Fei Liu ◽  
Chaopeng Hong ◽  
...  
Keyword(s):  
Power Plants ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Control Measures ◽  
Mitigation Measures ◽  
Anthropogenic Emissions ◽  
Index Decomposition ◽  
Clean Air ◽  
New Policies ◽  
Relative Change

Abstract. To tackle the problem of severe air pollution, China has implemented active clean air policies in recent years. As a consequence, the emissions of major air pollutants have decreased and the air quality has substantially improved. Here, we quantified China's anthropogenic emission trends from 2010–2017 and identified the major driving forces of these trends by using a combination of bottom-up emission inventory and Index Decomposition Analysis (IDA) approaches. The relative change rates of China's anthropogenic emissions during 2010–2017 are estimated as follows: −62 % for SO2, −17 % for NOx, +11 % for NMVOC, +1 % for NH3, −27 % for CO, −38 % for PM10, −35 % for PM2.5, −27 % for BC, −35 % for OC, and +18 % for CO2. The IDA results suggest that emission control measures are the main drivers of this reduction, in which the pollution controls on power plants and industries are the most effective mitigation measures. The emission reduction rates markedly accelerated after the year 2013, confirming the effectiveness of China's Clean Air Action that was implemented in 2013. We estimated that during 2013–2017, China's anthropogenic emissions decreased by 59 % for SO2, 21 % for NOx, 23 % for CO, 36 % for PM10, 33 % for PM2.5, 28 % for BC, and 32 % for OC. NMVOC emissions increased by 11 % and NH3 emissions remained stable from 2010–2017, representing the absence of effective mitigation measures for NMVOC and NH3 in current policies. The relative contributions of different sectors to emissions have significantly changed after several years' implementation of clean air policies, indicating that it is paramount to introduce new policies to enable further emission reductions in the future.

scholarly journals Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions

2018 ◽  
Vol 18 (19) ◽  
pp. 14095-14111 ◽  
Author(s):  
Bo Zheng ◽  
Dan Tong ◽  
Meng Li ◽  
Fei Liu ◽  
Chaopeng Hong ◽  
...  
Keyword(s):  
Power Plants ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Control Measures ◽  
Mitigation Measures ◽  
Anthropogenic Emissions ◽  
Index Decomposition ◽  
Clean Air ◽  
New Policies ◽  
Relative Change

Abstract. To tackle the problem of severe air pollution, China has implemented active clean air policies in recent years. As a consequence, the emissions of major air pollutants have decreased and the air quality has substantially improved. Here, we quantified China's anthropogenic emission trends from 2010 to 2017 and identified the major driving forces of these trends by using a combination of bottom-up emission inventory and index decomposition analysis (IDA) approaches. The relative change rates of China's anthropogenic emissions during 2010–2017 are estimated as follows: −62 % for SO2, −17 % for NOx, +11 % for nonmethane volatile organic compounds (NMVOCs), +1 % for NH3, −27 % for CO, −38 % for PM10, −35 % for PM2.5, −27 % for BC, −35 % for OC, and +16 % for CO2. The IDA results suggest that emission control measures are the main drivers of this reduction, in which the pollution controls on power plants and industries are the most effective mitigation measures. The emission reduction rates markedly accelerated after the year 2013, confirming the effectiveness of China's Clean Air Action that was implemented since 2013. We estimated that during 2013–2017, China's anthropogenic emissions decreased by 59 % for SO2, 21 % for NOx, 23 % for CO, 36 % for PM10, 33 % for PM2.5, 28 % for BC, and 32 % for OC. NMVOC emissions increased and NH3 emissions remained stable during 2010–2017, representing the absence of effective mitigation measures for NMVOCs and NH3 in current policies. The relative contributions of different sectors to emissions have significantly changed after several years' implementation of clean air policies, indicating that it is paramount to introduce new policies to enable further emission reductions in the future.

scholarly journals A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs

2021 ◽  
Vol 13 (11) ◽  
pp. 6192
Author(s):  
Junghwan Lee ◽  
Jinsoo Kim
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Driving Forces ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Primary Energy ◽  
Intensity Effect ◽  
Activity Effect ◽  
Index Decomposition ◽  
Output Indicator

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

scholarly journals Driving Forces of Air Pollution in Ulaanbaatar City Between 2005 and 2015: An Index Decomposition Analysis

2020 ◽  
Vol 12 (8) ◽  
pp. 3185 ◽  
Author(s):  
Enkhjargal Enkhbat ◽  
Yong Geng ◽  
Xi Zhang ◽  
Huijuan Jiang ◽  
Jingyu Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Air Pollutant ◽  
Capital City ◽  
Energy Structure ◽  
Index Decomposition Analysis ◽  
Socioeconomic Drivers ◽  
Index Decomposition ◽  
Concentration Changes

Ulaanbaatar, the capital city of Mongolia, is facing serious air pollution challenges—especially during the cold and long winter months—mainly due to fossil fuel combustion. This study investigates the socioeconomic drivers of the sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter (PM2.5) concentration changes in Ulaanbaatar between 2005 and 2015 by applying the index decomposition analysis (IDA) method. Five socio-economic driving forces are considered in the decomposition analysis. All the driving forces contributed to more air pollution concentration changes in 2015 than in 2005, despite the decreasing trends of decomposition results for the period of 2010–2015. In general, economic growth, pollution intensity, and energy intensity significantly contributed to the changes of air pollutant concentrations, while energy structure and population growth had marginal effects. Finally, appropriate policy recommendations are proposed to the local government so that they can initiate feasible policies to effectively reduce air pollution, protect human health, and respond to climate change in Ulaanbaatar.

scholarly journals Multitemporal LMDI Index Decomposition Analysis to Explain the Changes of ACI by the Power Sector in Latin America and the Caribbean between 1990–2017

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2328 ◽  
Author(s):  
Paulo M. De Oliveira-De Jesus ◽  
John J. Galvis ◽  
Daniela Rojas-Lozano ◽  
Jose M. Yusta
Keyword(s):  
Latin America ◽  
Power Plants ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Power Sector ◽  
Index Decomposition Analysis ◽  
Energy Flows ◽  
Index Decomposition ◽  
The Caribbean ◽  
The One

This paper analyzes the drivers behind the changes of the Aggregate Carbon Intensity (ACI) of Latin America and the Caribbean (LAC) power sector in five periods between 1990 and 2017. Since 1990 the carbon intensity of the world has been reduced almost 8.8% whereas the carbon intensity of LAC countries only decreased 0.8%. Even though by 2017 the regional carbon intensity is very similar to the one observed by 1990, this index has showed high variability, mainly in the last three years when the ACI of LAC fell from 285 gCO2/kWh in 2015 to 257.7 gCO2/kWh. To understand what happened with the evolution of the carbon intensity in the region, in this paper a Logarithmic Mean Divisia for Index Decomposition Analysis (IDA-LMDI) is carried out to identify the accelerating and attenuating drivers of the ACI behavior along five periods. The proposal outperforms existing studies previously applied to LAC based upon a single period of analysis. Key contributions are introduced by considering the type of fuel used in power plants as well as specific time-series of energy flows and CO2 emissions by country. Results reveal structural reasons for the increase of the ACI in 1995–2003 and 2008–2015, and intensity reasons for the decrease of the ACI in 1990–1995, 2003–2008 and 2015–2017.

scholarly journals The factors of milk revenue change in Lithuania: index decomposition analysis based on the Shapley value

2015 ◽  
Vol 37 (1) ◽  
pp. 8-16 ◽  
Author(s):  
Tomas Baležentis ◽  
Irena Kriščiukaitienė
Keyword(s):  
Milk Yield ◽  
Shapley Value ◽  
Market Integration ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Milk Composition ◽  
Country Level ◽  
Index Decomposition Analysis ◽  
Level Data ◽  
Index Decomposition

The paper aims to analyse the main driving forces behind the changes in milk revenue in Lithuania during 1993–2013 by the virtue of the index decomposition analysis. Specifically, an index decomposition model based upon Shapley value is introduced to account for dynamics in endogenous and exogenous factors underlying dynamics of the revenue. Particularly, the number of cows, average milk yield, market integration, milk composition, and milk price are considered as the main factors causing variation in milk revenue. The country level data are used for the analysis. Results show that such practices as animal recording and application of improved fodder have increased milk revenue by 67 million EUR and 75 million EUR during 1993–2004 and 2004–2013, respectively, due to increase in milk yield and fat.

Driving factors of energy-relevant CO2 emissions in China’s fixed asset investment

2018 ◽  
Vol 12 (4) ◽  
pp. 601-616
Author(s):  
Hongtao Liu ◽  
Jin Shang
Keyword(s):  
Intensity Factor ◽  
Carbon Emissions ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Policy Recommendations ◽  
Fixed Asset ◽  
Content Type ◽  
Index Decomposition Analysis ◽  
Index Decomposition

Purpose The purpose of this paper is to use an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. Design/methodology/approach This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented. Findings The results suggest that the amount of CO2 emissions related to fixed asset investments increased during the entire period. The social and economic effect played a major role in promoting carbon emissions, followed by the fixed asset effect. Therefore, the activity factor was the dominant positive factor, followed by the construction factor. The negative element was the energy effect, in which the energy intensity factor played an important role in reducing emissions, followed by the structural factor. Moreover, the carbon intensity factor might be a potential inhibitory force in reducing carbon emissions. Research/limitations/implications A steady financial policy, relaxed family planning, sustainable urbanization, strategy of innovation-driven development, reform of scientific and technological structures, development of science and technology and exploration of new energy sources are proposed to mitigate carbon emissions from fixed asset investments. The conclusion also provides a reference for developing countries in similar situations. Originality/value This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented.

scholarly journals China's Clean Air Action has suppressed unfavorable influences of climate on wintertime PM<sub>2.5</sub> concentrations in Beijing since 2002

2019 ◽  
Author(s):  
Meng Gao ◽  
Zirui Liu ◽  
Bo Zheng ◽  
Dongsheng Ji ◽  
Peter Sherman ◽  
...  
Keyword(s):  
Emission Control ◽  
Field Measurements ◽  
Meteorological Conditions ◽  
Control Measures ◽  
Anthropogenic Emissions ◽  
Recent Climate ◽  
Decadal Variations ◽  
Clean Air ◽  
Haze Days ◽  
Emission Control Measures

Abstract. Severe wintertime PM2.5 pollution in Beijing has been receiving increasing worldwide attention, yet the decadal variations remain relatively unexplored. Combining field measurements and model simulations, we quantified the relative influences of anthropogenic emissions and meteorological conditions on PM2.5 concentrations in Beijing over winters of 2002–2016. Between the winters of 2011 and 2016, stringent emission control measures resulted in a 21 % decrease in mean mass concentrations of PM2.5 in Beijing, with 7 fewer haze days per winter on average. With fixed emissions, meteorological conditions over the study period would have led to an increase of haze in Beijing, but the strict emission control measures have suppressed the unfavorable influences of recent climate. The unfavorable meteorological conditions are attributed to the weakening of the East Asia Winter Monsoon associated particularly with an increase in pressure associated with the Aleutian low.

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