Optimum investment strategy for hydrogen-based steelmaking project coupled with multiple uncertainties.

The large-scale application of hydrogen steelmaking technology is expected to substantially accelerate the decarbonization process of the iron and steel industry. However, hydrogen steelmaking projects are still in the experimental or demonstration stage, and scientific investment decision-making methods are urgently needed to support the large-scale development of the technology. When assessing the investment value, existing studies usually only consider the intrinsic project value under a specific pathway, while ignoring the option value under realistic multiple uncertainties in terms of technology, market, and policy, leading to an underestimation of the investment value. To address this issue, this study constructs a real options model to explore the optimal investment timing and revenue of the hydrogen steelmaking project, by taking into account multi-dimensional uncertainties stemming from price fluctuations in the steel market, the development of the carbon market, and technological advances. Additionally, the impacts of various subsidy policies on the investment strategy are also investigated. Least Squares Monte Carlo method is applied to overcome computational challenges posed by dynamic programming under multi-dimensional uncertainties. The results show that: (i) Investment is not recommended based on current crude steel price and hydrogen price. (ii) When the annual reduction rate of hydrogen price reaches 5%, the optimal investment timing would advance to 2036. (iii) On this basis, with the introduction of a 20% green hydrogen subsidy policy, the optimal investment timing would be further brought forward to 2033. The implementation of tax incentives would significantly increase the investment value. The investment value would surge from 170 million CNY to 262 million CNY as the tax rate decreases from 20% to zero. The findings could provide reasonable suggestions for investment decisions under realistic volatile environments, as well as scientific references for policy design, thus facilitating the large-scale and high-level development of hydrogen-based steelmaking technology.

Approaching national climate targets in China considering the challenge of regional inequality.

Achievement of national climate targets and the corresponding costs would entirely depend on regional actions within the country. However, because of substantial inequalities and heterogeneities among regions, especially in developing economies, aggressive or uniform actions may exacerbate inequity and induce huge economic losses, which in turn challenges the national climate pledges. Hence, this study extends prior research by proposing economically optimal strategies that can achieve national climate targets and ensure the greatest local and national benefits as well as regional equality. Focusing on the biggest developing country China, we find this strategy can avoid up to 1.54% of cumulative GDP losses for approaching carbon neutrality, and more than 90% of regions would obtain economic gains compared either with existing independently launched targets or with the uniform strategy that all regions achieve peak carbon emissions before 2030. We also provide optimal carbon mitigation pathways to regional peak carbon, carbon intensity and energy consumption.

Allocating China's CO2 Emissions Based on Economic Welfare Gains from Environmental Externalities.

To achieve carbon neutrality (i.e., net zero carbon emissions) by 2060, China must make significant changes in its socioeconomic systems, including appropriately allocating emissions responsibility. Traditional methods of delineating responsibilities (such as production-based and consumption-based accounting) can lead to double counting when applied simultaneously and therefore difficulty in determining responsibilities of different agents. An alternative approach based on economic welfare gains from environmental externalities has been refined, ensuring that the responsibilities of consumers and producers add up to the total emissions. The application of this approach to 48 countries and 31 Chinese provinces reveals that regions with less elastic supply and demand, such as Hebei in China and Russia, have higher responsibilities. Furthermore, larger externalities associated with unitary product value shift the burden of obligations from producers to consumers. Regions with high levels of wealth and carbon-intensive imports, such as Zhejiang and Guangdong in China, as well as the United States, typically have higher consumer-based accounting (CBA) emissions than production-based accounting (PBA) emissions and, as a result, redistributed responsibilities between PBA and CBA emissions. The new distribution results vary significantly from PBA or CBA emissions, indicating opportunities for more comprehensive and accessible policy goals.

Nexus between green financing, renewable energy generation, and energy efficiency: empirical insights through DEA technique.

The study aims to test the nexus of green financing with renewable electricity generation and energy efficiency. The study used data envelopment analysis (DEA) technique during the year of 2016 to 2020 in developed and developing countries. The findings show that there is a 24% possibility of worldwide rise in expenditures in renewable energy through energy efficiency projects and probably could fall around 17% much further in 2017 and 2018. This may jeopardize the Sustainable Development Goals (SDGs) and the Paris climate change agreement. Lack of access to private financing slows the development of green initiatives. Now that sustainable energy is not about science and technology, it is all about getting financing in developed and developing countries. As policy measure, the study suggested to value environmental initiatives, like other infrastructure initiatives, for greater electricity generation and energy efficiency in developed and developing countries. Such infrastructural projects need long-term financing and capital intensiveness. It is further suggested to sustain growth, development, and energy poverty reduction, and around $26 trillion would be required, in terms of green financing, in the developed and developing countries alone by the year 2030 to enhance energy efficiency. To achieve energy sustainability goals in developed and developing countries, recent research suggested some policy implication considering the post COVID-19 time. If such policy implications are implemented successfully, there are chances that green financing would make energy generation and energy efficiency effective.

Are electric vehicles cost competitive? A case study for China based on a lifecycle assessment.

Promoting the development of electric vehicles (EVs) is regarded as an important measure to ensure energy security, mitigate climate change, and solve the transport sector's air pollution problems. Nowadays, compared to gasoline vehicles, whether the EVs are more competitive in terms of cost is still a question. There is no consensus achieved since the total cost depends on the development stage of the automobile industry and power generation structure as well as the cost accounting boundary. Many of existing studies did not include the costs occurred in all the stages. In response to this concern, this study estimates the lifecycle cost covering the whole process of production, use, disposal, and infrastructure construction as well as externalities for passenger battery electric vehicle (BEV), fuel cell vehicle (FCV), and gasoline vehicle (GV) by applying the comprehensive lifecycle cost model to China. The results indicate that in 2018, BEV and FCV were more expensive than GV (1.2-5.3 times), but that BEV will become cheaper after 2025, and its cost advantage will be enlarged to $419 (5%) compared to GV by 2030. The lifecycle cost of FCV will be $527 (or 5%) lower than that of GV by 2030. These results clarify that the costs of vehicle production account for the largest proportion in the total lifecycle cost.

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (-1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic's effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

Opportunity and marginal abatement cost savings from China's pilot carbon emissions permit trading system: Simulating evidence from the industrial sectors.

China has launched pilot carbon emissions permit trading schemes (ETS) in seven regions since 2013/2014 and has established a nationwide ETS in the power industry by the end of 2017. Recent literature has evaluated China's seven pilot regions on design aspects of the ETS, and yet little is known about the potential recovery of economic output loss through introducing the ETS. This study considers the recovery of industrial value added loss and thus measures the abatement cost savings from trading to evaluate the necessity and feasibility of China's pilot ETSs. The analysis develops a parametric and nonparametric combined technique to calculate the opportunity abatement cost savings (i.e., potential abatement cost savings and unrealized abatement cost savings) and marginal abatement cost savings (i.e., changes on carbon shadow prices) in China's pilot ETSs during 2011-2015. It additionally provides an estimation of potential carbon emissions reduction from ETS. Both cross-industrial trading and intertemporal trading are considered, and three simulations, defined as no trading, cross-industrial trading, and cross-industrial and intertemporal trading, are conducted. We found that, i) 1-16% potential abatement cost savings and 2-12% unrealized abatement cost savings would be identified in China's pilot ETS regions. ii) 0.5-33% and 1.6-25% carbon emissions reduction potential would be realized respectively by introducing ETS and eliminating the operational inefficiency of the ETS. iii) Marginal abatement cost savings would both exist in almost all regions if the ETS were implemented and if the ETS were fully operational.

Including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the PM2.5 economic burden in China.

The concentrations of particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) and 10 µm (PM10) is a widespread concern and has been demonstrated for 103 countries. During the past few years, the exposure-response function (ERf) has been widely used to estimate the health effects of air pollution. However, past studies are either based on the cost-of-illness or the willingness-to-pay approach, and therefore, either do not cover intangible costs or costs due to the absence of work. To address this limitation, a hybrid health effect and economic loss model is developed in this study. This novel approach is applied to a sample of environmental and cost data in China. First, the ERf is used to link PM2.5 concentrations to health endpoints of chronic mortality, acute mortality, respiratory hospital admission, cardiovascular hospital admission, outpatient visits-internal medicine, outpatient visits-pediatrics, asthma attack, acute bronchitis, and chronic bronchitis. Second, the health effect of PM2.5 is monetized into the economic loss. The mean economic loss due to PM2.5 was much heavier in the North than the South of China. Furthermore, the empirical results from 76 cities in China show that the health effects and economic losses were over 4.98 million cases and 382.30 billion-yuan in 2014 and decreased dramatically compared with those in 2013.

A multi-regional input-output table mapping China's economic outputs and interdependencies in 2012.

Multi-regional input-output (MRIO) models are one of the most widely used approaches to analyse the economic interdependence between different regions. We utilised the latest socioeconomic datasets to compile a Chinese MRIO table for 2012 based on the modified gravity model. The MRIO table provides inter-regional and inter-sectoral economic flows among 30 economic sectors in China's 30 regions for 2012. This is the first MRIO table to reflect China's economic development pattern after the 2008 global financial crisis. The Chinese MRIO table can be used to analyse the production and consumption structure of provincial economies and the inter-regional trade pattern within China, as well as function as a tool for both national and regional economic planning. The Chinese MRIO table also provides a foundation for extensive research on environmental impacts by linking industrial and regional output to energy use, carbon emissions, environmental pollutants, and satellite accounts.

Chinese CO2 emission flows have reversed since the global financial crisis.

This study seeks to estimate the carbon implications of recent changes in China's economic development patterns and role in global trade in the post-financial-crisis era. We utilised the latest socioeconomic datasets to compile China's 2012 multiregional input-output (MRIO) table. Environmentally extended input-output analysis and structural decomposition analysis (SDA) were applied to investigate the driving forces behind changes in CO2 emissions embodied in China's domestic and foreign trade from 2007 to 2012. Here we show that emission flow patterns have changed greatly in both domestic and foreign trade since the financial crisis. Some economically less developed regions, such as Southwest China, have shifted from being a net emission exporter to being a net emission importer. In terms of foreign trade, emissions embodied in China's exports declined from 2007 to 2012 mainly due to changes in production structure and efficiency gains, while developing countries became the major destination of China's export emissions.

The shadow price of CO2 emissions in China's iron and steel industry.

As China becomes the world's largest energy consumer and CO2 emitter, there has been a rapidly emerging literature on estimating China's abatement cost for CO2 using a distance function approach. However, the existing studies have mostly focused on the cost estimates at macro levels (provinces or industries) with few examining firm-level abatement costs. No work has attempted to estimate the abatement cost of CO2 emissions in the iron and steel industry. Although some have argued that the directional distance function (DDF) is more appropriate in the presence of bad output under regulation, the choice of directions is largely arbitrary. This study provides the most up-to-date estimate of the shadow price of CO2 using a unique dataset of China's major iron and steel enterprises in 2014. The paper uses output quadratic DDF and investigates the impact of using different directional vectors representing different carbon mitigation strategies. The results show that the mean CO2 shadow price of China's iron and steel enterprises is very sensitive to the choice of direction vectors. The average shadow prices of CO2 are 407, 1226 and 6058Yuan/tonne respectively for the three different direction vectors. We also find substantial heterogeneity in the shadow prices of CO2 emissions among China's major iron and steel enterprises. Larger, listed enterprises are found to be associated lower CO2 shadow prices than smaller, unlisted enterprises.

Is CO2 emission a side effect of financial development? An empirical analysis for China.

Based on panel data for 29 Chinese provinces from 1995 to 2012, this paper explores the relationship between financial development and environmental quality in China. A comprehensive framework is utilized to estimate both the direct and indirect effects of financial development on CO2 emissions in China using a carefully designed two-stage regression model. The first-difference and orthogonal-deviation Generalized Method of Moments (GMM) methods are used to control for potential endogeneity and introduce dynamics. To ensure the robustness of the estimations, two indicators measuring financial development-financial depth and financial efficiency-are used. The empirical results indicate that the direct effects of financial depth and financial efficiency on environmental quality are positive and negative, respectively. The indirect effects of both indicators are U shaped and dominate the shape of the total effects. These findings suggest that the influences of the financial development on environment depend on the level of economic development. At the early stage of economic growth, financial development is environmentally friendly. When the economy is highly developed, a higher level of financial development is harmful to the environmental quality.

Multi-model comparison of the economic and energy implications for China and India in an international climate regime.

This paper presents a modeling comparison on how stabilization of global climate change at about 2 °C above the pre-industrial level could affect economic and energy systems development in China and India. Seven General Equilibrium (CGE) and energy system models on either the global or national scale are soft-linked and harmonized with respect to population and economic assumptions. We simulate a climate regime, based on long-term convergence of per capita carbon dioxide (CO2) emissions, starting from the emission pledges presented in the Copenhagen Accord to the United Nations Framework Convention on Climate Change and allowing full emissions trading between countries. Under the climate regime, Indian emission allowances are allowed to grow more than the Chinese allowances, due to the per capita convergence rule and the higher population growth in India. Economic and energy implications not only differ among the two countries, but also across model types. Decreased energy intensity is the most important abatement approach in the CGE models, while decreased carbon intensity is most important in the energy system models. The reduction in carbon intensity is mostly achieved through deployment of carbon capture and storage, renewable energy sources and nuclear energy. The economic impacts are generally higher in China than in India, due to higher 2010-2050 cumulative abatement in China and the fact that India can offset more of its abatement cost though international emission trading.