Emission Abatement Target Research Articles

Impact of artificial intelligence technology applications on corporate energy consumption intensity

Artificial intelligence (AI), as a new technology, not only revolutionizes economic development, but also provides an opportunity for environment governance. Extant studies primarily explore the environmental performance of AI from a macro perspective, while evidence on how AI technology applications affect firms’ energy-saving behavior is scarce. Employing Python technology to recognize AI-related keywords in the annual reports of listed enterprises and adopting data on corporate energy consumption from 2011 to 2020, we explore the impact of AI on corporate energy consumption intensity (CECI) and its mechanisms. We observe that AI technology applications reduce CECI. After a range of robustness tests, the conclusions are still solid. The mechanism analysis reveals that AI cuts CECI through spurring firm green innovation, stimulating firms to introduce new equipment, and reducing firms’ internal management costs. Heterogeneity analysis reveals that this negative impact is more prominent for SOEs and private enterprises’ energy intensity; we also find that this effect is more pronounced for high-tech industry enterprises and high-polluting enterprises. Our findings provide micro evidence for policymakers to reduce corporate energy intensity and realize energy conservation and emission abatement targets.

Allocation of the Carbon Emission Abatement Target in Low Carbon Supply Chain Considering Power Structure

The proposal of China’s dual carbon strategy is not only a kind of pressure but also an opportunity for enterprises. Both upstream and downstream enterprises in the supply chain pay more attention to carbon emission reduction, and consumers are gradually turning to a low-carbon preference. How carbon reduction targets are allocated among supply chain members with different technical efficiency and market opportunities will directly affect supply chain performance and social welfare. Power structure is an important factor that dominates the decision-making of the supply chain, so we establish the low-carbon supply chain model under three different power structures: manufacturer-led, retailer-led, and power pairs between two parties. We study the government distribution decisions of carbon emissions reduction targets under different supply chain power structures and discuss the influence of supply chain power structures on carbon emissions reduction distribution decisions and social welfare. The study found that if the carbon emissions reduction target increases, the government will adjust the allocation strategy to increase the proportion of enterprises whose emissions cuts have less impact on market demand. The study also found that the government will allocate more emissions reduction to enterprises with higher emissions reduction efficiency, and enterprises whose emissions reductions have a greater impact on market demand. When supply chain enterprises have equal power, the supply chain will have greater social welfare and market demand, but not necessarily greater supply chain profits.

Net GHG emissions and air quality outcomes from different residential building electrification pathways within a California disadvantaged community

• Electrification can reduce net GHG emissions and public health impacts from PM-2.5 μ exposures. • Electrification of different gas appliances produces different load profile shapes. • Load profile shapes determine grid fossil generator unit responses and overall net impacts. • Local air quality benefits are principally determined by the volume of avoided gas use. • Ambient air quality impacts are principally determined by the timing of load profile changes. Electrification of gas appliances in residential buildings will be necessary to rapidly decarbonize the energy system. In California however, recent rates of adoption of electric appliances, especially within disadvantaged and vulnerable communities (DVCs), have been insufficient to meet the state's ambitious GHG emissions abatement targets. In this study we use an integrated assessment modeling framework to quantify the holistic benefits of different electrification pathways within a representative study area DVC. Results indicate that aggressive electrification retrofits can deliver significant net reductions in GHG emissions, even when future grid emissions from increased electric loads are factored in. We also find that these measures can also create significant net public health benefits, in terms of overall avoided impacts from particulate matter (PM-2.5 μ ) exposures. However, the realization of these net benefits requires tradeoffs between local improvements in air quality in the areas where electrification occurs, for smaller, but still significant, reductions in air quality, in areas where fossil fueled electricity generators remain active. We conclude with a discussion of some of the persistent barriers to electrification within DVCs and the import role of electrification within broader efforts to combat climate change and improve equity within the energy system.

Optimizing crop rotation increases soil carbon and reduces GHG emissions without sacrificing yields

Enhancing soil organic carbon (SOC) while concurrently reducing greenhouse gas (GHG) emissions and without compromising yield is a contemporary challenge for many agricultural sectors across the globe. In China, resolving the "carbon- food" nexus is a key pillar of government policies aimed at constraining “Carbon Peak” and delivering “Carbon Neutrality”. The present study explores the potential to increase SOC stocks while reducing GHGs emissions, without sacrificing crop yields considering crop rotation optimization under different irrigation managements in the North China Plain (NCP) based on a 6-year experiment. We found higher crop yields for the irrigated treatments compared with the rainfed treatments, demonstrating that rainfed crops were constrained by water deficit stress in the region. Yield was highest in the winter wheat-summer maize rotation (WM), followed by yields of the winter wheat-summer soybean (WS), while the average yields of winter wheat-summer maize-spring maize (WMMs) were lowest. SOC stocks in the surface soil (0–20 cm) increased for the irrigated treatments, but soil carbon sequestration (i.e. the rate of SOC stocks change over time) for the rainfed treatments decreased for all treatments. SOC stocks for WMMs was greatest of all treatments, leading to the highest carbon sustainability index (CSI) for this treatment. Nitrous oxide (N2O) emissions were 23–57% higher in the irrigated treatments than the rainfed treatments for the three rotations, which was highest in WMMs and lowest in WS. Carbon footprints (CFs) were highest in WS and lowest in WMMs. Overall, we found that increasing SOC stocks reduced CFs and increased yield. WMMs with irrigation was the most effective treatment for promoting SOC sequestration and mitigating GHG emissions with relatively high yield in this study, suggesting that crop rotations that are (1) more intensive and (2) grow more aboveground biomass are more likely to promulgate lower CFs and contribute towards national emissions abatement targets, such as those aimed at Net Zero.

Combined Source-Storage-Transmission Planning Considering the Comprehensive Incomes of Energy Storage System

An energy storage system transfers power and energy in both time and space dimensions and is considered as critical technique support to realize high permeability of renewable energy in future power systems. It contributes to the achievement of China’s long-term carbon emission abatement targets. However, the promotion and application of energy storage are severely restricted due to the high construction cost of energy storage systems and lack of effective compensation mechanisms for peak-regulating ancillary service. In this study, a source-storage-transmission joint planning method is proposed considering the comprehensive incomes of energy storage. The comprehensive income of the energy storage system is divided in detail from the planning level, and the accounting method of energy storage income is proposed. Based on the load fluctuating trend under the condition of the connecting wind power grid, the dynamic electricity pricing methods of power trisection and time trisection are introduced to achieve the dual goals of direct income from energy storage and improving system flexibility. To comprehensively consider the direct income of peak-valley arbitrage and indirect income of energy storage configuration, a coordinated planning model of source-storage-transmission is constructed and tested in the Garver-6 system using the measured data from one province grid in China. The results verify the effectiveness of the proposed methods and show improvements in cost recovery and system flexibility.

Should I stay or should I go? Carbon leakage and ETS in an evolutionary model

Emissions trading is gaining increasing importance around the world as a suitable instrument to address climate change. In the absence of a global carbon market, however, unilateral carbon policies may end up causing carbon leakage effects, the more so if carbon prices are to increase in the future to achieve more ambitious emissions abatement targets. This paper intends to explore the possible delocalization effects of an Emissions Trading System (ETS) by proposing an evolutionary theoretical model in which regulated firms decide whether to stay (keep their production activities in the domestic country) or leave (move production abroad where no ETS is in place) imitating what other firms do. We investigate how this decision is affected by some key ETS design features, such as the emissions cap, the number of allowances granted for free to ETS firms, the level of a floor price for allowances. Numerical simulations show that the firms’ decision on whether to abate emissions or relocate abroad are more sensitive to policies that reduce the cost of green technologies than to changes in specific features of the ETS design such as the emissions cap, the floor price and the number of permits granted for free.

Spatial heterogeneity analysis of CO2 emissions in China’s thermal power industry: GWR model

The thermal power industry is a major contributor to China's CO2 emissions, and its absolute emissions are still increasing year by year. Hence, this paper introduced a geographically weighted regression model to explore the spatial heterogeneity of different driving factors for this industry's CO2 emissions. The empirical results show that standard coal consumption is a decisive factor affecting thermal power industry's CO2 emissions, and its response to the western region is at the forefront. The average utilization hours of thermal power equipment in the central region exert a profound impact, while the western region devotes a lot to the installed capacity, and these two variables have great potential for CO2 emission mitigation. However, the urbanization level and per capita electricity consumption have a slight effect on CO2 emissions. These findings furnish constructive reference and policy implications to achieve emission abatement targets of different regions.

Achieving China’s Long-Term Carbon Emission Abatement Targets: A Perspective from Regional Disparity

As China is the largest greenhouse gas emitter and has the characteristics of significant regional disparity, the issue of regional low-carbon development strategy is of vital importance for the achievement of the country’s long-term emission targets. This work focused on China’s long-term carbon emission abatement from the perspective of regional disparity. We firstly analyzed the national emission trajectories consistent with the current Intended Nationally Determined Contributions (INDCs), 2 °C, and 1.5 °C goals in two economic growth pathways by 2050 using a linear programming model, then classified the provinces into three categories, and compared results of different scenarios of regional disparity patterns, economic growth rates, and emission targets. Results showed that different regional patterns led to different required carbon reduction targets for all categories, and the regional emission reduction measures had to be stronger in a higher growth rate or a more stringent emission target, especially for the developed areas. A scheme of regionally coordinated low-carbon development was then recommended for the formulation of long-term regional emission targets, and carbon reduction strategies for categories were proposed in terms of energy mix optimization, industrial transformation, and technology innovation, which is of great policy implication for China in regional development and national emission targets enhancement.

Pathways to a low-carbon economy: Estimations on macroeconomic costs and potential of carbon emission abatement in Beijing

Developing reliable frameworks to estimate the potential of CO2 emission abatement and its associated costs merits urgent attention. This study aims to estimate the potential as well as macroeconomic costs of CO2 emission abatement in Beijing. Using the industrial economy as the basis, multiobjective programming and genetic algorithm are integrated into the input–output analysis. Several important findings have been gathered in the study: (1) The abatement cost varies between $259.97 and $535.46 per ton at different rates of economic growth. (2) A reinforced emission abatement target can induce higher macroeconomic costs. (3) An inverse U-shaped relationship between CO2 reduction cost and GDP growth rate was found. When GDP growth rate is above the threshold value of 7%, marginal abatement costs decrease rapidly in parallel with GDP growth. When the GDP growth rate is below 7%, the marginal abatement cost increases significantly with economic growth. (4) Industries that have the highest and least potential of abatement have been identified. For effectively reducing CO2 emissions, Beijing needs to promote economic restructuring to maximize the potential of emission abatement and also fulfil the emission abatement target in a cost-effective way. This paper provides a quantitative approach to rationalize the policy design process of enacting emission targets and recommends cost-effective abatement strategies.

Efficient distribution of carbon emissions reduction targets at the city level: A case of Yangtze River Delta region

The Chinese central government has released detailed carbon emissions abatement targets at the provincial level, but provides no specific emissions reduction targets at the city level. Most provincial governments simply allocate carbon emissions reduction tasks to their cities based on the GDP of their cities. Allocation approaches, however, should emphasize the most effective distribution to reach overall targets that reflect actual reduction capacities of cities. This paper proposes an allocation method at the city level by combining a data envelop analysis method, an entropy weight method and a clustering analysis method using the Yangtze River Delta region as a case study. Results of our analysis indicate that cities with higher carbon emissions abatement potentials, financial abilities, a larger number of above-scaled industrial enterprises and higher GDP are better positioned to reduce carbon emissions and should be assigned proportionately higher reduction targets. The merits and policy implications of the proposed approach are discussed in comparison to simply using GDP to allocate emission reduction targets.

The Impact of Accidental Deviation by Natural Disaster-Prone Countries on Renegotiation-Proof Climate Change Agreements

This study provides a new framework for international environmental agreements (IEAs), which include punishment exceptions for accidental deviation, using repeated games. We consider that deviation from an agreement can occur accidentally because of phenomena such as natural disasters, even if the agreement is sustained as a weakly renegotiation-proof equilibrium. If an IEA signatory deviates accidentally, it fails to achieve its emission abatement target. In the repeated game, a cooperative relationship among signatories is sustained by a strategy that prescribes rules of cooperation and punishment for deviation. We present a new strategy, called Regional Cooperative, which integrates accidental deviations into an IEA. Our model reveals that punishing countries tend to revoke the punishment of deviators and return to cooperation if an accidental deviator increases its abatement volume. That is, the abatement efforts of the accidental deviator can lead to renegotiation. The Regional Cooperative strategy motivates the accidental deviator to try to engage in abatement and the punishing countries to restart cooperation by renegotiation. We conclude that social welfare loss by punishment is prevented through renegotiation in cases of accidental deviation.

Multistage Investment Actions with the Emission Cap

To achieve the emission reduction target in 2020, China plans to establish a nationwide carbon trading market during 2016–2019. It is therefore an important but difficult task for policymakers to set emission allowances and allocate them among entities. There are three alternative allocation rules, which vary from free of charge to full auctioning. For business managers, the question is whether one of these rules meets the emission cap at the minimum cost. Based on China’s emission-abatement target, this paper examines the optimal investment and analyzes its implementation in different allocation rules. A new model is developed to formulate enterprises’ emission reduction pathways and the cost-minimization problem with the emission cap. The results show that the magnitude of enterprises’ emission reduction is positively related to their innovation potential; neither auctioning nor being free of charge can make enterprise’s individual emission-abatement investment in accordance with the optimal level; enterprise’s individual emission-abatement investment is sensitive to efficiency, budget cap, and environmental benefit. This paper discusses simultaneously their policy implications for China.

Allocation of product-related carbon emission abatement target in a make-to-order supply chain

This paper investigates the product-related carbon emission abatement target (PCEAT) allocation problem in a decentralized make-to-order supply chain, which is composed of a manufacturer and a retailer. The product-related carbon emissions here refer to the total emissions generated from the product manufacturing and retailing processes. To effectively reduce carbon emissions on the product level in the whole supply chain, a compulsory PCEAT is imposed on each unit of product. The problem is how to allocate the PCEAT between the manufacturer and the retailer, where the allocator can be either firm. We use Stackelberg game models to solve this problem by considering the following four scenarios: (1) the manufacturer is the leader and the allocator; (2) the manufacturer is the follower and the allocator; (3) the retailer is the follower and the allocator; and (4) the retailer is the leader and the allocator. Ignoring the carbon emission abatement limits of firms, it is found that if the leader is the allocator, the proportions of the PCEAT allocated to the two participators are determined by their marginal abatement costs. If the follower is the allocator, the PCEAT will be completely allocated to the leader. When the abatement limits of firms are taken into consideration, the firm constrained by the limit will undertake the portion of PCEAT up to its limit; while the other firm should undertake the remaining part. In any case, we find that it is always not bad to let the leader allocate the PCEAT.

Exploring the impacts of a carbon tax on the Chinese economy using a CGE model with a detailed disaggregation of energy sectors

This paper applies a computable general equilibrium model to investigate the impacts of a carbon tax on China's economy and carbon emissions based on China's 2010 Input–Output Table. To obtain robust simulation results, we further disaggregate the energy sectors into eight departments according to energy use characteristics. The empirical results indicate that a moderate carbon tax would significantly reduce carbon emissions and fossil fuel energy consumption and slightly reduce the pace of economic growth. However, a large carbon tax has a significantly negative impact on China's economy and social welfare. Moreover, a large carbon tax would entail marked price changes in China. Of the fossil fuels in use, reducing coal consumption would have the greatest impact on reducing carbon emissions, and the ad valorem duty rate for coal would be the highest after levying a carbon tax because it has the highest carbon emission coefficient. Therefore, China should strive to promote clean coal technology, which may be crucial to reducing carbon emissions. Moreover, levying a carbon tax would improve the use of clean energy, which would be an effective means of reducing carbon emissions. Therefore, the Chinese government should formulate the regulations for and pass a carbon tax as early as possible to achieve its carbon emission abatement target and further contribute to mitigating climate change.

Implications of CO2 reduction policies for a high carbon emitting economy

This paper uses a dynamic computable general equilibrium model to compare the macroeconomic and sectoral impacts of three environmental policies in Australia — an emissions trading scheme (ETS), an ETS combined with technological innovation in the renewable energy sector and a fuel tax as an alternative to the ETS. Overall, the impacts of the ETS were not significantly adverse. Although the fuel tax had similar impacts to the ETS on key macro-variables such as real GDP, employment, household consumption, exports and imports, it was however not effective compared to the latter in reducing emissions. Neither policy led to inflation growth of more than 0.8% for any coal mining and non-mining Australian state. At the sectoral level, the GDP growth of energy-intensive industries such as coal, iron ore, steel and coal-powered electricity generators is adversely affected while electricity generators who use gas and renewable energy sources and the forestry sector gain. It was also found that a 10% technological change in the renewable energy sector over a decade did not significantly improve the outcome when coupled with the ETS. Thus the Australian government's industry assistance to invest in low pollution technologies needs to be more aggressive to meet current and future international emission abatement targets.

Is There Space for Agreement on Climate Change? A Non-Parametric Approach to Policy Evaluation

Economic evaluation of climate policy is notoriously dependent on assumptions about time and risk preferences, since reducing greenhouse gas emissions today has a highly uncertain payoff, far into the future. These assumptions have always been much debated. Rather than occupy a position in this debate, we take a non-parametric approach here, based on the concept of Time-Stochastic Dominance. Using an integrated assessment model, we apply Time-Stochastic Dominance analysis to climate change, asking are there global emissions abatement targets that everyone who shares a broad class of time and risk preferences would agree to prefer? Overall we find that even tough emissions targets would be chosen by almost everyone, barring those with arguably `extreme' preferences.

Optimal investment and uncertainty on China's carbon emission abatement

To realize environmentally sustainable development of the economy, China has decided to cut carbon dioxide emissions per unit of GDP by 40 to 45 percent by 2020, compared with the level in 2005. Based on China's emission abatement target, this paper first analyzes enterprises' emission reduction pathways in practical production processes, and then develops a framework to derive the magnitude of investment required in each pathway in order to achieve the designated target at the minimal cost. Under the framework, it is found that in the absence of policy guidance, individual enterprises' emission reduction investments deviate from the optimal level. To correct the distortion, an alternative option is provided. Meanwhile, to ensure achievement of the emission reduction target, a stochastic model is introduced to measure the uncertainty arising from emission abatement investment. The results show that an appropriate emission abatement ratio can reduce ‘the systemic risk’ of emission abatement. Finally, a simulation is given to demonstrate the results derived from the stochastic model.

Modelling and mapping long-term risks due to reactive nitrogen effects: An overview of LRTAP convention activities

Long-range transboundary air pollution has caused severe environmental effects in Europe. European air pollution abatement policy, in the framework of the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP Convention) and the European Union Clean Air for Europe (CAFE) programme, has used critical loads and their exceedances by atmospheric deposition to design emission abatement targets and strategies. The LRTAP Convention International Cooperative Programme on Modelling and Mapping Critical Loads and Levels and Air Pollution Effects, Risks and Trends (ICP M&M) generates European critical loads datasets to enable this work. Developing dynamic nitrogen flux models and using them for a prognosis and assessment of nitrogen effects remains a challenge. Further research is needed on links between nitrogen deposition effects, climate change, and biodiversity.

Analysis: Sell yourself cleaner

Emissions abatement targets threaten to cripple the power sector, but a cost-effective, market-based strategy could ease the pain. Miles Austin lays out the options.