Why China Cannot Decarbonise

[...]it is often argued—as by Yifei Li and Judith Shapiro, for example—that China's dictatorship should be an advantage in this context: ‘Given the limited time that remains to mitigate climate change and protect millions of species from extinction, we need to consider whether a green authoritarianism can show us the way' (Li and Shapiro 2020, quoted from the publisher's book description). Since CCP bosses do not have to contend with public hearings, environmental studies, recalcitrant legislatures, labour unions, a critical press, and so on, Xi should be able to force state-owned polluters to stop polluting or else, and ram through his promised transition to renewable energy (see Smith 2017, 2020c). Climate Action Tracker estimates that in 2021 China's emissions increased by 3.4 per cent to 14.1 gigatonnes of carbon dioxide equivalent (GtCO2e)—nearly triple those of the United States (4.9 GtCO2e) with a gross domestic product just three-fourths as large (CAT n.d.;EIA 2022). Since 2019, China's emissions have exceeded those of all developed countries combined and presently account for 33 per cent of total global emissions (Larsen et al. 2021;IEA 2021). In the first half of 2021, rebounding from the first wave of Covid-19, China's carbon dioxide emissions surged past pre-pandemic levels to reach an all-time high 20 per cent increase in the second quarter before dropping back in late 2021 and the first half of 2022 as the real estate collapse, Omicron lockdowns, and drought-induced hydropower reductions slashed economic growth to near zero in the summer (Hancock 2021;Myllyvirta 2022a;Riordan and Hook 2022). China promised to stop building coal-fired power plants abroad, but it is building more than 200 new coal-fired plants at home in a drive to boost economic growth, maintain jobs in coal-dependent regions, and ensure energy self-sufficiency—locking the country into coal reliance for many decades to come, derailing the transition to renewables, and dooming Xi's UN pledge to transition to a green and low-carbon mode of development (Xie 2020).

Investment in new coal-fired power plants after the COVID-19 pandemic: experts expect 170–270 GW of new coal

To avoid dangerous climate change, the global community has committed to phasing down coal at COP26 in Glasgow. Since policies and pledges currently implemented in the power sector are not sufficient to meet mitigation targets, countries are expected to increase their ambition over time within the UNFCCC process. Furthermore, some countries are bilaterally negotiating support packages to speed up the phase-out of coal through ‘Just Energy Transition Partnerships'. Yet, to assess those ratcheting up efforts an understanding of the current baseline is pivotal. Here, we quantify the probability that currently planned coal plants will be built, based on an in-depth expert elicitation consisting of interviews with 29 experts from ten countries. We analyze the most important factors influencing the realization of the coal pipeline, isolate the effect of the COVID-19 pandemic, and compare the experts' forecasts with mitigation pathways scenarios. We find that globally 170 GW–270 GW of new coal-fired power plants are likely to be built in the upcoming years. Future negotiations for joint partnerships can use the results of this elicitation as a baseline to determine ambitious coal phase-out plans.

Coal Is a Priority for Energy Security, until It Is Not: Coal Phase-Out in the EU and Its Persistence in the Face of the Energy Crisis

In the wake of the COVID-19 pandemic and the Russian invasion of Ukraine, many countries see coal as the easiest solution to their energy sector challenges, despite the consequences for climate goals. Several countries of the European Union started to re-evaluate their coal policies vis-à-vis the current energy crisis and, although such a change is expected to be short-term in nature, it nevertheless has negative consequences for the Union's 2050 climate goal. However, most of the EU countries did not revise their phase-out goals. This paper examines Slovakia as a country that embarked on a coal phase-out trajectory only a few years before the pandemic broke out and stayed firmly on this path despite benefits stemming from the continued use of domestic coal. Domestic coal used to be considered a safeguard of energy security in Slovakia, especially after the 2009 gas crisis. However, a decision was made in 2018 to phase out coal by 2023, and this has not changed despite increased focus on domestic energy sources as energy security guarantors during the current energy crisis. This paper explains the decision in favour of a coal phase-out and its support vis-à-vis the energy crisis using the concept of ‘financial Europeanisation', which stresses the importance of EU funds for the development of the domestic policies of EU member states. While the expected funds serve as a catalyst for the coal phase-out needed to reach climate goals, short-term advantages of revising a coal phase-out were outweighed by long-term benefits provided by EU funds.

Research on the emission reduction effects of carbon trading mechanism on power industry: plant-level evidence from China

PurposeCarbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design.Design/methodology/approachThis paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO2 and PM2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016.FindingsResults suggest that the carbon trading mechanism induces 2.7% of CO2 emission reduction and 6.7% of PM2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers.Originality/valueThis paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.

Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI

The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO2, SO2, CO, HCHO, and CHOCHO) detected by the Sentinel-5P TROPOMI instrument and driven by reductions in anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in TROPOMI NO2 column amounts on all continents. For megacities, reductions in column amounts of tropospheric NO2 range between 14 % and 63 %. For China and India, supported by NO2 observations, where the primary source of anthropogenic SO2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in 2-week-averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short timescale are detectable from space is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China, which is in concert with the other trace gas reductions observed during lockdown;however, large interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19-lockdown-driven reductions in satellite-observed trace gas column amounts using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction in anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future the combined use of inverse modeling techniques with the high spatial resolution data from S5P/TROPOMI for all observed trace gases presented here will yield a significantly improved sector-specific, space-based analysis of the impact of COVID-19 lockdown measures as compared to other existing satellite observations. Such analyses will further enhance the scientific impact and societal relevance of the TROPOMI mission.

To Adopt CCU Technology or Not? An Evolutionary Game between Local Governments and Coal-Fired Power Plants

Carbon dioxide capture and utilization (CCU) technology is a significant means by which China can achieve its ambitious carbon neutrality goal. It is necessary to explore the behavioral strategies of relevant companies in adopting CCU technology. In this paper, an evolutionary game model is established in order to analyze the interaction process and evolution direction of local governments and coal-fired power plants. We develop a replicator dynamic system and analyze the stability of the system under different conditions. Based on numerical simulation, we analyze the impact of key parameters on the strategies of stakeholders. The simulation results show that the unit prices of hydrogen and carbon dioxide derivatives have the most significant impact: when the unit price of hydrogen decreases to 15.9 RMB/kg or the unit price of carbon dioxide derivatives increases to 3.4 RMB/kg, the evolutionary stabilization strategy of the system changes and power plants shift to adopt CCU technology. The results of this paper suggest that local governments should provide relevant support policies and incentives for CCU technology deployment, as well as focusing on the synergistic development of CCU technology and renewable energy hydrogen production technology.

Crop Residue Burning Emissions and the Impact on Ambient Particulate Matters over South Korea

In the study, crop residue burning (CRB) emissions were estimated based on field surveys and combustion experiments to assess the impact of the CRB on particulate matter over South Korea. The estimates of CRB emissions over South Korea are 9514, 8089, 4002, 2010, 172,407, 7675, 33, and 5053 Mg year−1 for PM10, PM2.5, OC, EC, CO, NOx, SO2, and NH3, respectively. Compared with another study, our estimates in the magnitudes of CRB emissions were not significantly different. When the CRB emissions are additionally considered in the simulation, the monthly mean differences in PM2.5 (i.e., △PM2.5) were marginal between 0.07 and 0.55 μg m−3 over South Korea. Those corresponded to 0.6–4.3% in relative differences. Additionally, the △PM10 was 0.07–0.60 μg m−3 over South Korea. In the spatial and temporal aspects, the increases in PM10 and PM2.5 were high in Gyeongbuk (GB) and Gyeongnam (GN) provinces in June, October, November, and December.

Location and Technical Requirements for Photovoltaic Power Stations in Poland

The objective of Poland’s energy policy is to guarantee energy security while enhancing economic competitiveness and energy efficiency, thus minimizing the power sector’s environmental impact and optimizing the use of energy resources in the country. Poland is not the only European country to rely on coal for power generation. Historical factors and large coal deposits act as natural barriers to increasing the share of renewable energy in the Polish power sector. Yet, today, environmental concerns and climate change are prompting many countries to move away from fossil fuels. Renewable energy sources, such as solar and wind energy, are an alternative to traditional energy generated from fossil fuels. However, investors developing solar and wind farms in Poland encounter numerous problems at each stage of the project. These difficulties are associated mainly with the location, technical requirements, infrastructure and formal and legal documents. This study aimed to identify the key factors that influence the development of photovoltaic power stations in Poland, with special emphasis on the choice of location and technical aspects of the investment process. The demand for clean energy and the renewable energy prospects for Poland are discussed based on the example of solar farms. Sixty-seven prospective farm locations were analyzed, and the results of the analysis were used to identify the main barriers and opportunities for renewable energy development in Poland. The option of connecting solar farms to the existing power grid was also examined. This study demonstrates that the development of solar farms in Poland is inhibited mainly by technical barriers, in particular the lack of options for connecting farms to the power grid, as well as the absence of support mechanisms and dedicated legislative solutions, rather than environmental obstacles.

CO2 Reduction Potential from Efficiency Improvements in China’s Coal-Fired Thermal Power Generation: A Combined Approach of Metafrontier DEA and LMDI

Among the G20 countries, China is the only country to experience an increase in electricity generation from coal-fired thermal power plants from 2019 to 2020. This study aims to develop an analytical framework combining metafrontier data envelopment analysis with the logarithmic mean Divisia index for a detailed decomposition analysis of ‘mass-based’ energy-related CO2 reduction potential through efficiency improvements in coal-fired thermal power plants in China. The results show that inefficiency in power generation can be largely attributed to differences in the location of power plants and the production scale. Moreover, the impact of regional heterogeneity on the changes in power generation efficiency is more notable for the small–medium power plants in the northeast region than the large power plants in the western region in China. However, when focusing on the mass-based CO2 reduction potential associated with the regional heterogeneity, its positive effects in the western region for the large power plants are 6.2 times larger than that in the northeast region for the small–medium power plants. These results imply that an analysis that focuses only on the efficiency score would ignore the production scale of coal-fired thermal power plants and thus would fail to properly evaluate the environmental impacts associated with efficiency changes.

Assessing the Impact of Traffic Emissions on Fine Particulate Matter and Carbon Monoxide Levels in Hanoi through COVID-19 Social Distancing Periods

Hanoi, Vietnam, is usually ranked as one of the most polluted capital cities in terms of air quality, particularly PM2.5. However, there has not been enough data to determine the main source of this pollution. In this study, we utilized the rare opportunity of the COVID-19 social distancing to assess the contribution of traffic emission to PM2.5 and CO levels when traffic volume was reduced significantly in Hanoi. Hourly PM2.5 and CO concentrations were measured from nine urban and traffic monitoring stations during pre-, soft, hard, and post-social distancing periods. As a result, we observed large reductions in both PM2.5 and CO levels during social distancing periods. PM2.5 concentrations were 14–18% lower during the social distancing than before this period, while CO concentrations had a more considerable drop by 28–41%. It is known that meteorological conditions can have significant effects on the ambient levels of air pollutants. To overcome this challenge, weather normalized concentrations of those pollutants were estimated using the random forest model, a machine learning technique. The normalized weather concentrations showed smaller reductions by 7–10% for PM2.5 and 5–11% for CO, indicating the presence of favorable weather conditions for better air quality during the social distancing period. In further analysis, the apparent improvement of air quality in Hanoi during the social distancing period was in line with reducing traffic emissions while emissions from coal-fired power plants remained relatively stable.

Resilience Analysis of Australian Electricity and Gas Transmission Networks

Given they are two critical infrastructure areas, the security of electricity and gas networks is highly important due to potential multifaceted social and economic impacts. Unexpected errors or sabotage can lead to blackouts, causing a significant loss for the public, businesses, and governments. Climate change and an increasing number of consequent natural disasters (e.g., bushfires and floods) are other emerging network resilience challenges. In this paper, we used network science to examine the topological resilience of national energy networks with two case studies of Australian gas and electricity networks. To measure the fragility and resilience of these energy networks, we assessed various topological features and theories of percolation. We found that both networks follow the degree distribution of power-law and the characteristics of a scale-free network. Then, using these models, we conducted node and edge removal experiments. The analysis identified the most critical nodes that can trigger cascading failure within the network upon a fault. The analysis results can be used by the network operators to improve network resilience through various mitigation strategies implemented on the identified critical nodes.

Protection Motivation and Food Waste Reduction Strategies

“Ugly food” refers to agricultural products that are discarded because their appearance is not attractive, even though their nutritional content is unaffected. In this study, protection motivation theory (PMT) was applied to analyze whether an individual’s awareness of food waste problems affects their “ugly food” purchase intention. Hence, the relationships between awareness of food waste problems, threat appraisal (severity and vulnerability), coping appraisal (response efficacy and self-efficacy), and ugly food purchase intention were analyzed. Additionally, a moderating effect analysis was conducted per consumer age. Descriptive statistical analysis, frequency, and SPSS reliability analysis were used, including confirmatory factor analysis, structural equation modeling, and multi-group analysis of the Amos program. For the final analysis, 361 samples were used. Results showed that awareness of food waste problems positively affected severity and vulnerability, response efficacy, and self-efficacy. Moreover, severity positively affected ugly food purchase intention and vulnerability did not. Response and self-efficacy positively affected ugly food purchase intention. In the moderating effect analysis per consumer age, the difference between severity and ugly food purchase intention and vulnerability and ugly food purchase intention was significant. This study has various academic and practical implications, and presents several strategies to reduce food waste to contribute to a sustainable future environment. It is also the first study linking the food waste problem, PMT, and ugly food purchase behavior.

Estimating the Employment and Fiscal Consequences of Thermal Coal Phase-Out in China

China hosts over half of global coal-fired power generation capacity and has the world’s largest coal reserves. Its 2060 carbon neutrality goal will require coal-fired electricity generation to shrink dramatically, with or without carbon capture and storage technology. Two macroeconomic areas in which the socioeconomic impact of this decline is felt are losses in jobs and tax revenues supported by thermal coal mining, transport and power generation. At the national level, under a ‘baseline’ (B) scenario consistent with China’s carbon neutrality goal, labour productivity growth in coal mining implies that significant job losses will occur nationally in the medium term, even if all coal plants continue operating as planned. Jobs supported by the coal power industry would decline from an estimated 2.7 million in 2021, to 1.44 million in 2035 and 94,000 in 2050, with jobs losses from mining alone expected to exceed 1.1 million by 2035. Tax revenues from thermal coal would total approximately CNY 300 billion annually from 2021–2030, peaking in 2023 at CNY 340 billion. This is significantly less than estimated subsidies of at least CNY 480 billion, suggesting coal is likely a net fiscal drain on China’s public finances, even without accounting for the costs of local pollution and the social cost of carbon. As coal plant retirements accelerate, from 2034 onwards, fiscal revenues begin to fall more rapidly, with rates of decline rising from 1% in the 2020s to over 10% a year by the 2040s. More aggressive climate policy and technology scenarios bring job and tax losses forward in time, while a No Transition policy, in which all currently planned coal plants are built, delays but does not ultimately prevent these losses. At the provincial level, China’s major coal-producing provinces will likely face challenges in managing the localised effects of expected job losses and finding productive alternative uses for this labour. Governments of coal-producing provinces like Inner Mongolia, with an industry highly dependent on exports to other provinces, are more exposed than others to declining tax revenues from coal, and more insulated from job losses, given their high current degree of labour efficiency. Although their provincial revenues are likely to remain stable until the early 2030s under the B scenario, the possibility of increasing policy stringency underlines the need for revenue and skill base diversification. At the firm level, China’s ‘Big Five’ state-owned power companies were responsible for over 40% of both jobs and tax revenues in 2021. The number of jobs supported by the activities of each of the largest ten firms, with one exception, will decline by 71–84% by the early 2040s, with the tax contribution of each declining by 43–69% in the same period.

The Development and Issues of Energy-ICT: A Review of Literature with Economic and Managerial Viewpoints

This paper reviews the economic and managerial literature on the relationship between energy-ICT and the development of the green energy economy. It is summarized that there are four lines of existing literature on energy-ICT: cost and benefit analysis, fair competition issues, cybersecurity issues, and promotion policy issues. Even though ICT is energy-consuming, most of the existing empirical studies support the idea that energy-ICT has net positive effects on energy savings, energy efficiency improvement, emission reduction, and economic growth at both enterprise and economy-wide levels. Energy-ICT equips the platform operator with higher bargaining power, such that a governance mechanism to assure the fair access right of each entitled participant is required. A smarter energy-ICT network also becomes riskier, and hence the cybersecurity protection is more important than before. Future research and development opportunities remain on these issues of the fair competition, cybersecurity, and promotion policy of energy-ICT.

Comparative Techno-Economic Analysis of Carbon Capture Processes: Pre-Combustion, Post-Combustion, and Oxy-Fuel Combustion Operations

Evaluation of economic aspects is one of the main milestones that affect taking rapid actions in dealing with GHGs mitigation;in particular, avoiding CO2 emissions from large source points, such as power plants. In the present study, three kinds of capturing solutions for coal power plants as the most common source of electricity generation have been studied from technical and economic standpoints. Aspen HYSYS (ver.11) has been used to simulate the overall processes, calculate the battery limit, and assess required equipment. The Taylor scoring method has been utilized to calculate the costliness indexes, assessing the capital and investment costs of a 230 MW power plant using anthracite coal with and without post-combustion, pre-combustion, and oxy-fuel combustion CO2 capture technologies. Comparing the costs and the levelized cost of electricity, it was found that pre-combustion is more costly, to the extent that the total investment for it is approximately 1.6 times higher than the oxy-fuel process. Finally, post-combustion, in terms of maturity and cost-effectiveness, seems to be more attractive, since the capital cost and indirect costs are less. Most importantly, this can be applied to the existing plants without major disruption to the current operation of the plants.

Changing air pollution scenario during COVID-19: Redefining the hotspot regions over India.

The present study investigates the air pollution pattern over India during the COVID-19 lockdown period (24 March-31 May 2020), pre-lockdown (1-23 March 2020) and the same periods from 2019 using Moderate Resolution Imaging Spectroradiometer (MODIS) Terra aerosol optical depth (AOD) with level 2 (10 km × 10 km) and level 3 (1° × 1° gridded) collection 6.1 Dark Target Deep Blue (DT-DB) aerosol product the Tropospheric Monitoring Instrument (TROPOMI) NO2 and SO2 data with a spatial resolution of 7 km × 3.5 km. We also use long-term average (2000-2017) of AOD for March-May to identify existing hotspot regions and to compare the variations observed in 2019 and 2020. The aim of the present work is to identify the pollution hotspot regions in India that existed during the lockdown and understanding the future projection scenarios reported by previous studies in light of the present findings. We have incorporated Menn-Kendall trend analysis to understand the AOD trends over India and percentage change in AOD, NO2 and SO2 to identify air pollution pattern changes during the lockdown. The results indicate higher air pollution levels over eastern India over the coal-fired power plants clusters. By considering the earlier projected studies, our results suggest that eastern India will have higher levels of air pollution, making it a new hotspot region for air pollution with highest magnitudes.