Carbon Emission Intensity Research Articles

The influence of digital intelligence transformation on carbon emission reduction in manufacturing firms

Severe global climate change has resulted in the focus of social attention shifting to the manufacturing industry's low-carbon transformation. Digital intelligent transformation (DIT) in enterprises is identified as a crucial driver in mitigating carbon emissions. An estimation of DIT's impact on manufacturing industries' carbon emission intensity (CEI) and its underlying mechanisms was conducted using data from Chinese A-share listed companies. Research findings indicate that DIT significantly reduces corporate CEI. Robustness tests, such as the instrumental variable method and variable substitution method, confirm this conclusion. By enhancing labor productivity and accelerating capital renewal, DIT indirectly lowers CEI. Furthermore, non-state-owned enterprises with superior market competitiveness have been observed to be markedly adept at harnessing DIT for CEI. The heterogeneity test found that DIT has a considerably significant effect on reducing CEI in enterprises that are not low-carbon pilots, non-broadband pilots, smart pilots, non-provincial capitals, and eastern cities. This study provides new evidence supporting the promotion of enterprise DIT for achieving green development, offering insights for corporate policy making.

Digital Inclusive Finance, Digital Technology Innovation, and Carbon Emission Intensity

Digital Inclusive Finance, Digital Technology Innovation, and Carbon Emission Intensity

Green fiscal policy and carbon emission: Enterprises’ level evidence from China

The Chinese government has systematically developed and implemented a wide-ranging set of policies for sustainable development. The Fiscal Policy for Energy Conservation and Emission Reduction (FPECER) is a pivotal component within this integrated policy framework. Nevertheless, there is currently an absence of literature assessing its' impact on the carbon emission performances of manufacturing enterprises and discussing the potential impact channels. To this end, by applying the difference-in-difference method to a unique micro-level panel dataset, this study empirically investigates the impact of FPECER on manufacturing enterprises' carbon emissions and proposes some explanations for the impact channels between the two. This research substantiates that the FPESER has played a pivotal role in diminishing both the levels and intensity of carbon emissions for manufacturing enterprises located in pilot cities. Moreover, this has been achieved through an augmentation of financial subsidies granted to enterprises, a vigorous promotion of research and development activities, and a significant reduction in both the level and intensity of energy consumption. Furthermore, this research also discerns that the negative impact of FPECER on carbon emission performance is more pronounced for manufacturing enterprises in regions experiencing heightened local fiscal pressure and higher economic policy uncertainty, those classified within high-emission and capital-intensive industries, as well as non-export-oriented and state-owned manufacturing entities. Finally, FPECER does not significantly impact the output and value-added of enterprises, yet it does reduce the emission levels of a range of pollutants.

Impact and transmission mechanism of digital economy on agricultural energy carbon emission reduction

The digital economy is a powerful driver for accelerating economic growth and an innovative approach to promoting high-quality agricultural development. Utilizing panel data encompassing 30 provincial-level administrative regions in China from 2011 to 2021, this paper quantifies the development level of digital economy and agricultural energy carbon emission intensity, and examines the impact and mechanism of digital economy on agricultural energy carbon emission intensity. The results reveal that: (1) Distinct regional disparities exist in both the development level of the digital economy and the carbon emission intensity of agricultural energy across China from 2011 to 2021, although an overall decreasing trend is observed; (2) The development of digital economy has a significant inhibitory effect on agricultural energy carbon emission intensity, and this conclusion remains robust after a series of tests; (3) Digital economy development can mitigate agricultural energy carbon emission intensity by alleviating misallocation of agricultural capital and promoting green technology innovation. In addition, there are significant regional differences in the impact of the digital economy on the carbon intensity of agricultural energy. These findings contribute to a deeper understanding of the environmental governance implications of the digital economy in agriculture and offer valuable guidance for the effective application of digital technologies towards achieving agricultural emission reduction goals.

How Does Digital Inclusive Finance Policy Affect the Carbon Emission Intensity of Industrial Land in the Yangtze River Economic Belt of China? Evidence from Intermediary and Threshold Effects

Digital inclusive finance (DIF) is a strategic tool that fosters the green transformation of the industrial economy. Based on the data from the 11 provinces and municipalities in the Yangtze River Economic Belt of China between 2012 and 2021, This paper utilizes the Tobit, intermediary effect, and threshold effect models to empirically study the impact of DIF on the industrial land carbon emission intensity (ILCEI). This paper reaches the following conclusions: (1) The ILCEI in the region revealed a downward trend during the study period. There are substantial differences in carbon ILCEI; higher upstream and lower downstream. The average ILCEI in the lower reach provinces is 0.5829 ton/m2 during the research period, while that in the upper reach region is 1.0104 ton/m2. (2) DIF has a significantly inhibitory effect on the ILCEI; this effect has nonlinear characteristics. The impact of DIF on ILCEI exhibits a marginally diminishing trend as the industrial land economic agglomeration degree improves. (3) Regarding the transmission mechanism, the level of industrial R&D investment plays a primary intermediary role in the impact of DIF on ILCEI. (4) Concerning control variables, foreign investment dependence and trade contribute significantly to inhibiting ILCEI. Lastly, this paper proposes a series of measures to promote DIF to fully utilize the emission reduction effect. The research outcomes have substantial implications for the sustainable development of industrial land.

Coupling and Coordinated Development of Carbon Emission Efficiency in Industrial Enterprises and the Digital Economy: Empirical Evidence from Anhui, China

To delve into the interrelationship between the green transformation of industry and the economy’s high-quality development, to promote the coordinated development of industrial carbon emission efficiency and digital economy, to expand the scope and research ideas related to economic and social sustainable development, and to provide scientific reference for the low-carbon sustainable development of regional economy, this article introduced a data-centric methodology for evaluating the collaborative advancement of both industrial enterprises’ carbon emission efficiency and the digital economy. To accurately gauge the carbon footprint of industrial enterprises, models focusing on carbon emissions as well as carbon emission intensity were employed. To enhance the precision of evaluation outcomes and mitigate biases stemming from subjective weighting factors, we employed the entropy weight method to objectively assign weights to each indicator. Furthermore, the super-efficient slack-based model (SBM) can solve the problem that the conclusions are biased, due to the different radial. Subsequently, a carbon-emission efficiency slack-based measure model, and models for coupling degree and coupling-coordination degree were formulated. Anhui, as a central province in China, is also an important province in the Yangtze River Delta integration development. Coordinated development of its carbon emission efficiency and digital economy has important implications for the sustainable economy advancements of other regions in China, and even other countries or regions in the world. Therefore, Anhui was selected to be the empirical research sample. The results showed that the comprehensive levels of these two systems followed an increasing trend, while the digital economy lagged. Their coupling degree fluctuated and reached its highest point in 2021, whereas their coupling-coordination degree increased, showing high coupling and low coordination overall. This study proposes specific countermeasures and suggestions for the relevant decision-makers.

An LCA-BIM integrated model for carbon-emission calculation of prefabricated buildings

Carbon emissions from the building sector account for around half of China's national CEs and have been the obstacle to reaching China's two-carbon goal. However, whether the prefabricated technique can mitigate CEs for the building sector is still argued by studies. In consideration of this, this study proposes an LCA and BIM-simulation integrated model to comprehensively calculate CEs of prefabricated (PBs) and traditional cast-in-situ buildings (TBs). The BIM simulation is verified by an analytical method. The results show that the total carbon emission intensity (CEI) of PB is 9.61 % lower than that of the TB, showing a significant advantage in CE reduction potential and can be chosen as the developing direction in the future. The main CEs come from the operation and maintenance stage, where the TB emits 11.02 % higher CEs than those of the PB. For the materialization stage, where CEs are centralized in a short period, the difference between CEIs of the PB and TB is 3.32 %, which is not significantly different. The collected data and calculated results in this study can be quite beneficial to future sustainability studies in the same research domain, especially the integrated application of BIM and LCA. This study also contributes to knowledge by proposing a comprehensive CE calculation model and providing reasonable measures for CE reduction, which is beneficial to the sustainable development of the building sector to achieve China's two-carbon goal.

Study on carbon emission characteristics and its influencing factors of energy consumption in Sichuan Province, China

Clarifying the key sectors and influencing factors of carbon emissions from energy consumption is an important prerequisite for achieving the “carbon peaking and carbon neutrality” goals. This study calculated the carbon emissions of fuel combustion in 7 major departments and regional electricity trading of Sichuan Province from 2000 to 2021, and empirically analyzed the impact of energy structure effect, energy intensity effect, industrial structure effect, economic development level effect, and population size effect on the carbon emissions of energy consumption based on the LMDI model. The main research conclusions are as follows: (1) LMDI model has the advantages of no residual and high interpretation. By refining the multi-departments of energy consumption and different types of fuel, it is helpful to improve the accuracy of empirical analysis results. (2) The carbon emissions of energy consumption mainly come from the fuel combustion process. Specifically, the industry sector composed of steel, building materials, chemicals and machinery is the key emission sector, and transportation and residential life are also vital. Regional electricity trading can indirectly reduce the intensity of carbon emissions while ensuring the safety of energy supply. (3) From 2000 to 2021, the energy intensity effect and the economic development level effect were key factors in slowing down and promoting the carbon emission growth of energy consumption in Sichuan Province, respectively. The population scale effect mainly played a positive role in driving carbon emissions, but the impact is small and almost negligible. Before 2012, the energy structure effect and the industrial structure effect were mainly positive driving effects, and after 2012, they all turned into negative inhibitory effects. This was mainly due to the low-carbon transformation of energy structure and the optimization of industrial structure.

Can digital financial inclusion converge the regional agricultural carbon emissions intensity gap?

To explore whether digital finance can reduce agricultural carbon emissions, promote regional convergence, and foster inclusivity in rural revitalization and shared prosperity, this paper uses the provincial-level index of digital financial inclusion to analyze the impact of digital financial inclusion on the intensity of agricultural carbon emissions and the Degum Gini coefficient (D-Gini coefficient) of regional carbon emission intensity in 30 sample provinces from 2010 to 2020. It examines the mechanism of the impact of digital financial inclusion on both variables to understand the underlying factors better. The main conclusions are as follows: (1) Digital financial inclusion significantly reduces the intensity of agricultural carbon emissions and narrows the gap in carbon emission intensity between regions. (2) The unconditional quantile regression coefficients show that the negative coefficients of the digital financial inclusion index and the three-dimensional indices decrease with increasing quantiles. However, the significant effects vary significantly at different quantiles. (3) Technological progress and the government's ability to allocate financial resources play a significant mediating role, and the income gap between urban and rural areas can be further narrowed, as well as the carbon emission intensity gap between provinces. The empirical results are robust and proven by replacing the econometric analysis method, changing the core variables, and other methods.

Development Strategy Based on Combination Typologies of Building Carbon Emissions and Urban Vibrancy—A Multi-Sourced Data-Driven Approach in Beijing, China

When confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the factors influencing urban carbon emissions and the practical strategies regarding urban vibrancy, the unclear mutual nexus between them and the development strategy for collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and buildings’ carbon emission data, we have developed a reproducible method to estimate total carbon emissions and emission intensity. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each of these four typologies based on the geographical location and requirements of urban development policies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

Research on Carbon Emission Pre-Assessment of Residential Buildings in Xi’an City during the Scheme Design Stage

The effect of energy saving and carbon reduction in the building industry is closely related to the realization of China’s double carbon goal. In this study, a two-dimensional framework for building life cycle carbon emissions was established, which takes into account the early stages of building design such as the feasibility study stage and scheme design stage. Taking 57 residential buildings in Xi’an City as examples, the life cycle carbon emission characteristics of residential buildings in cold areas were introduced. This study found that the life cycle carbon emission intensity is about 45~55 kgCO2/(m2·a). The operation and maintenance stage and building materials production stage accounted for the largest proportion of carbon emissions, and the sum of carbon emissions of the two stages accounted for 92.3% of the total carbon emissions. In addition, based on the probability density function, the carbon emission intensity distributions of the building life cycle, building material production stage, building material transportation stage, and operation and maintenance stage were analyzed, and it was found that each distribution fitting graph was generally in line with a lognormal distribution, and their expected value provided a reference index for carbon emission pre-assessment in the feasibility study stage. Based on the analysis and determination of 11 independent variables that affect the total carbon emissions, such as area, floor number, story height, and number of households, a multiple linear regression model for carbon emission pre-assessment in the design stage of building schemes is proposed. The R2adj of the model is 0.985 and the error is about 10%. The prediction model can provide beneficial guidance for the life cycle carbon emission prediction in the design stage of building projects, so as to reduce carbon emissions by changing building design.

Can smart transportation reduce carbon emission intensity? — An empirical study from macro and micro perspectives in China

Traditional transportation development has yielded significant economic and social benefits, but it has also led to increased pollution emissions and substantial environmental impacts. Transport has become a major source of carbon emissions in China. Against the backdrop of national goals for “carbon peak” and “carbon neutrality”, the development of smart transportation offers a fresh perspective on reducing carbon emission intensity. In this study, both provincial and enterprise-level data from China are used to examine the critical role of smart transportation in reducing carbon emission intensity from both macro and micro perspectives, and the dynamic threshold model is employed to validate the inverted U-shaped relationship between the energy structure and digital infrastructure in the carbon reduction process facilitated by smart transportation. In addition, in this mechanism, green innovation and the digital economy play pivotal roles. Multiple robustness tests confirmed the reliability of the empirical analysis. This study highlights the important role of smart transport in carbon intensity and provides valuable insights for developing countries aimed at transitioning toward environmentally friendly, low-carbon, intelligent and advanced transport.

Unlocking the nexus: exploring the effect of urban green innovation on haze pollution and carbon emissions intensity in Chinese cities

Unlocking the nexus: exploring the effect of urban green innovation on haze pollution and carbon emissions intensity in Chinese cities

The Impact of Global Value Chain Embedment on Energy Conservation and Emissions Reduction:Theory and Empirical Evidence

Abstract An in-depth investigation into the effect of embedment in global value chain (GVC) on energy conservation and emissions reduction is of great significance for scientifically assessing the environmental impact of GVC participation, and promoting high-quality development in China. This paper incorporates GVC embedment, energy consumption and carbon emissions into the same analysis framework for the first time. Based on the WIOD database, this paper theoretically and empirically examines the impact and mechanism of global value chain embeddedness on carbon emission reduction from two dimensions: energy consumption intensity and energy consumption structure. The study found that GVC embedment significantly reduced the industry’s carbon emission intensity; developing economies’ embedment in GVC helped reduce their carbon emission intensity, while the effect was not obvious in developed economies. GVC embedment had a significant inhibitory effect on the carbon emissions in both upstream and downstream industries, but not conducive to carbon reduction of low-tech manufacturing. The mechanism test shows that the GVC embedment not only exhibits the dual effects of energy conservation and emissions reduction, but also has a significant impact on carbon emissions by reducing the energy consumption intensity and improving the energy consumption structure.

Response of Low Carbon Level to Transportation Efficiency in Megacities: A Case Study of Beijing, China

Global warming caused by massive carbon dioxide emissions can lead to a chain of ecological disasters. As one of the main sources of carbon emissions, transportation is of great significance, and the evaluation of its connections with carbon emissions is necessary to achieve “carbon neutrality”. Taking Beijing as an example, this study evaluated traffic efficiency (TE) by utilizing principal component analysis and fuzzy comprehensive evaluation. Using the Tapio decoupling model and coupling coordination degree model, the corresponding relationship between urban low carbon level (LCL) and TE was explored. The results showed the following: (1) The total carbon emission (CE) level exhibited fluctuating variation from increasing to decreasing. The carbon emission intensity (CEI) continued to slow down, and the rapid growth of population density played a key role in low-carbon development. (2) The traffic operations continually showed a positive trend in development. TE increased from a step-like to a slow shape, until it declined in 2020 due to the pandemic. (3) TE and LCL both developed from low coordination to an extreme level of coordination. Per capita carbon emission (CEP) and TE presented an inverted U-shaped curve; meanwhile, with increases in TE, the decline in CEI slowed. In addition, the weak decoupling of TE changed to become strong, due to CE and CEP, and maintained a strong decoupling state from CEI. (4) There is a necessity for the rational planning of land use for transportation infrastructure, the encouragement of a combination of public and private transportation, and the strengthening of the maintenance of the relative infrastructure and the management of traffic behaviors to attain a win–win situation. The results provide a reference for optimizing the traffic structure to achieve “carbon neutrality”.

How Does Density Impact Carbon Emission Intensity: Insights from the Block Scale and an Optimal Parameters-Based Geographical Detector

Density is a crucial indicator for urban sustainable development and is considered a critical factor influencing the carbon emission intensity of construction land (CICL). The impact of density on carbon emissions has been extensively explored, mainly focusing on grid-scale and single-factor effects. However, how density and its interactions affect carbon emissions at the block scale is unclear. Therefore, based on multiple data sources such as energy consumption, remote sensing, and the point of interest (POI) in the urban block of Changxing County, this study constructed a density system that reflects the block’s physical environment and socioeconomic characteristics. An optimal-parameters-based geographical detector was employed to investigate the effects and interactions of density factors on the carbon emission intensity of residential blocks (CIRB), carbon emission intensity of commercial blocks (CICB), and carbon emission intensity of public blocks (CIPB). The results indicate the following: (1) The impact of density factors on different types of CICL varied significantly. Physical environmental factors (PEFs) had greater explanatory power than socioeconomic factors (SEFs) across the CIRB, CICB, and CIPB, with the floor area ratio (FAR) being the most influential. The spatial morphology of blocks also influenced the relationship between density factors and the CICL. (2) The interactions between the FAR and building density (BD), the FAR and commercial outlet density (COD), and the FAR and population density (PD) had the strongest explanatory power for the CIRB, CICB, and CIPB, respectively, and all exhibited nonlinear enhancements. Some factors exhibited more significant effects only when interacting with others. (3) An association chain encompassing the interactions of multiple density factors was extracted for the CIRB, CICB, and CIPB, respectively, as the basis for conducting collaborative management and control in spatial planning. The research findings can provide decision support for urban planners to consider the comprehensive effects of density factors and promote the development of low-carbon urban spaces.

Spatial characteristic of carbon emission intensity under "dual carbon" targets: Evidence from China

<p><span style="font-size:10.5pt"><span style="line-height:150%"><span style="font-family:Calibri,sans-serif"><span class="fontstyle01" style="font-family:仿宋"><span style="color:black"><span lang="EN-US" style="font-size:10.0pt"><span style="line-height:150%"><span style="font-family:"Times New Roman",serif"><span style="color:#0d0d0d">Reducing carbon emissions is one of the important ways to achieve the goal of "dual carbon". Taking carbon emission intensity as the research object, this paper analyzes the spatial effects of carbon emission intensity at provincial level in China during 2005-2022 by kaya extended model, standard deviation ellipse, Theil index and kernel density analysis model. The results show that: (1) Overall, the distribution of carbon emission intensity in China exhibits distinct regional characteristics, with significant heterogeneity in emissions among regions. (2) With advancements in technology and economy, China's carbon emission intensity has shown a downward trend, </span></span></span></span></span></span><span lang="EN-US" style="font-size:10.0pt"><span style="line-height:150%"><span style="font-family:"Times New Roman",serif"><span style="color:#0d0d0d">albeit with <span class="fontstyle01" style="font-family:仿宋"><span style="color:black"><span style="font-family:"Times New Roman",serif">a U-shaped fluctuation. (3) During the sample period, the contribution of Theil index to carbon emission intensity decreased first and then increased. (4) </span></span></span>From a geographical perspective<span class="fontstyle01" style="font-family:仿宋"><span style="color:black"><span style="font-family:"Times New Roman",serif">, carbon emissions </span></span></span>exhibit a pattern characterized by<span class="fontstyle01" style="font-family:仿宋"><span style="color:black"><span style="font-family:"Times New Roman",serif"> "high in the east, low in the west, dense in the north and sparse in the south". Therefore, establishing a sound regional carbon reduction cooperation mechanism and promoting green development </span></span></span>tailored to<span class="fontstyle01" style="font-family:仿宋"><span style="color:black"><span style="font-family:"Times New Roman",serif"> local conditions have become the main direction for advancement.</span></span></span></span></span></span></span></span></span></span></p>

A Bottom-Up Carbon Emission Assessment Model for Carbon Emission Control at the Level of Rural Detailed Planning

Incorporating green and low-carbon building targets into the rural planning management system requires scientific and quantitative methods for assessing carbon emissions from rural land use. At present, the research in this field mainly focuses on urban areas, but there are fewer theoretical and practical studies on the assessment of carbon emissions from rural land use. This paper proposes a new carbon emission assessment method based on land use modes, and the model can not only assess carbon emissions but also directly reflect the carbon emission intensity of different land use spaces in rural areas and guide the carbon emission control of construction land in village planning. In this paper, we take suburban rural areas in Hunan Province as an example and establish a land use carbon emission assessment model with 13 indicators in five dimensions: total carbon emission, carbon emission efficiency, carbon emission intensity per unit of land use, carbon emission structure of land use, and carbon emission intensity of buildings, based on the bottom-up field research data. We practised our method in Jinlong Town, Hunan Province, and gave examples of model applications. It was found that the carbon emission calculation method based on the carbon emission intensity of land use can be used to calculate the current status of carbon emissions in different villages in Jinlong Town. At the same time, the carbon emission assessment results can be used as a scientific basis for carbon emission control in detailed village planning in Jinlong Town. In general, the carbon emission assessment model can complete the assessment of land carbon emissions in rural areas and provide a low-carbon land use management tool for the government.

Economic Feasibility of LNG Business: An Integrated Model and Case Study Analysis

Liquefied natural gas (LNG), recognized as the fossil fuel with the lowest carbon emission intensity, is a crucial transitional energy source in the global shift towards low-carbon energy. As the natural gas industry undergoes rapid expansion, the complexity of investment business models has increased significantly. Optimizing the combination of various segments within the value chain has become standard practice, making it essential to control risks and enhance economic benefits in these multifaceted scenarios. This paper introduces an integrated economic model encompassing upstream, liquefaction, shipping, regasification, and consumption, suitable for both upstream and downstream integration. The model offers a comprehensive analysis of the primary business models and key factors across each segment of the value chain. By constructing a robust economic evaluation framework, the study aims to provide a holistic approach to understanding the economic feasibility of LNG projects. Two detailed case studies are conducted to demonstrate the application and effectiveness of the proposed model, highlighting its capability to guide investment decisions, support risk management, and optimize asset portfolios. The integrated economic model developed in this study serves as a valuable tool for stakeholders in the LNG industry. It not only facilitates informed investment decision-making but also enhances the strategic management of risks and resources. By leveraging this model, investors and managers can better navigate the complexities of the LNG business, ensuring sustainable and economically viable operations.

Low-carbon development path based on carbon emission accounting and carbon emission performance evaluation: a case study of Chinese coal production enterprises.

Carbon emission accounting is the basic premise of effective carbon emission reduction and management. This study aimed to establish the carbon emission model and performance evaluation framework of coal mine production enterprises and clarify the low-carbon development path of enterprises. In this study, we took a typical coal production enterprise (K enterprise) in the Shanxi province of China as the research object. We also estimated the carbon emissions of the enterprise mainly according to the Chinese Carbon Emission Accounting Standard (GB/T 32151.11-2018). The triangular model was used to construct the carbon performance evaluation framework. On this basis, we suggested the enterprise's low-carbon development path. The results showed that (1) the carbon emission of K enterprise in 2021 was 36,875.38 tCO2eq; the carbon emission intensity of each ton of coal produced was 0.089 tCO2eq. The critical carbon emissions were electricity consumption and methane fugitive emissions during production. (2) The evaluation indicators for carbon emission performance revealed an imbalance in K enterprise's economic, energy, and environmental development in 2021. The work on energy saving and consumption reduction was relatively weak. (3) Countermeasures for low-carbon development, including a carbon emission ledger, were proposed based on carbon emission accounting and performance evaluation results. This study can help typical underground coal production enterprises in Shanxi province obtain more accurate carbon emission data, providing practical guidance and reference for the same underground coal production enterprises to improve the carbon emission control effect.